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Harvested TG were digested with collagenase III
(5mg/ml) in RPMI 1640 containing 10% fetal bovine serum (FBS), 1% antibiotic/antimycotic, and
gentamicin at 37° C. TG and cornea were dissociated with a 3-mL syringe-plunger head in the
presence of media. Cell suspensions were passed through a 40-micron filter before staining. Single
cell suspensions were labeled with the following fluorochrome-conjugated monoclonal antibodies:
anti-mouse B220, CD73, PD-L2, CD80, CD45(A20), CD3(145-2C11), CD4(GK1.5), CXCR5, CD44,
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
CD62L, ICOS, PD-1 (BD Biosciences, San Jose, CA). For surface staining, mAbs were added
against various cell markers to a total of 1 x106 cells in phosphate-buffered saline (PBS) containing
1% FBS and 0.1% sodium azide (fluorescence-activated cell sorter [FACS] buffer) and left for 45
minutes at 4°C. For intracellular/intranuclear staining, cells were first treated with cytofix/cytoperm (BD
Biosciences) for 30 minutes. Upon washing with Perm/Wash buffer, mAbs were added to the cells
and incubated for 45 minutes on ice in the dark, washed with Perm/TFFACS buffer and fixed in PBS
containing 2% paraformaldehyde. Labeled cells were suspended in 1% BSA in PBS and analyzed
using the BD Fortessa flow cytometer. Intracellular staining was performed to detect HSV-1 specific
plasma cells. HSV-1 gD -specific ASC ELISPOT assay: PBMCs from human or immune cells were
stimulated (2-4 million cells/ ml) in B-cell media containing Human or mouse polyclonal B cell activator
(Immunospot) for 5 days. Both CTL Human B-Poly-S and CTL Mouse B-Poly-S are stock solutions
containing Resiquimod and either recombinant Human IL-2 or recombinant Mouse IL-2 respectively,
used for the polyclonal expansion of memory B cells. This will activate the memory B cells to ASC. Cells were then washed in RPMI medium and plated in specified cell numbers in ELISPOT membrane
plates coated with either HSV-1 gD antigen (Virusys) (1ng/well) or IgG/ IgA capture antibody
(Immunospot Basic ELIPOT kits). The ASC secreting cells were detected after 48 hours of addition of
cells to ELISPOT plates. HSV-1-specific IgA/IgG ELISA assay: Sera or plasma was isolated from blood by
centrifugation for 10 min at 800g. Heat-inactivated HSV-1 McKrae strain was used for coating ELISA
plates (Nunc Immunosorbent). The affinity of binding of antigen-specific antibodies to the HSV-1
McKrae strain was measured by ELISA plates coated overnight at 4°C with (104 pfu/ well) heat-
inactivated HSV-1. Heat-inactivated human or mouse serum (56°C for 1 hour) was then incubated at
a specified dilution overnight at 4ºC. |
HSV-1 specific IgG / IGA were then detected using human or
mouse IgG/ IgA detection antibodies conjugated to HRP. Subsequently, TMB substrate was added to
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
stop the reaction before performing the reading at 450 nm in the ELISA plate reader (iMark Microplate
Reader, Bio-Rad). Viral plaque neutralization assay: Neutralizing antibody titers were determined by
incubating 100 PFU of HSV-1 strain McKrae with serial dilutions of serum starting at 1:40 for 1 hour at
37°C. The endpoint neutralization titer was determined by the plaque assay on RS cells and was
calculated as the serum dilution that reduced the number of plaques by 50% compared with PBS
controls. Virus propagation and titration: For virus propagation, rabbit skin (RS) cells (ATCC,
Manassas, VA) were grown in Minimum Essential Medium Eagle with Earl’s salts and L-Glutamine
(Corning, Manassas, VA) supplemented with 10% fetal bovine serum and 1% penicillin-streptomycin. The HSV-1 laboratory strain McKrae was propagated in RS cells and purified by ultracentrifugation in
sucrose gradient and titrated by the plaque assay. Mice and infection: All animals were handled with care according to the guidelines of
American Association for Laboratory Animal Science (AALAS). For primary herpes infection, six- to
eight-week-old male and female B6 mice were purchased from the Jackson Laboratory. The mice
were anaesthetized with xylazine (6.6mg/kg) and ketamine (100mg/kg) prior to infection. Both corneas
in each mouse was briefly scarified with a 25-gauge needle, tear film blotted, and 1X106 pfu/eye of
HSV-1 (strain McKrae) in 2 μL of sterile PBS were inoculated into the cornea. Corneal infection in all
the infected mice was confirmed by viral plaque assay in tear swabs. Virus shedding in tear swabs
was collected at day 2, 7 and 7 post-infections (p.i.). At day 35 p.i., eyes were reactivated by exposure
to UV-B radiation for one minute and at day 6 post-reactivation, mice were categorized into ASYMP or
SYMP depending on disease occurrence. ASYMP and SYMP mice were euthanized and immune
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available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
cells from peripheral blood, spleen, bone marrow and TG were collected for flow cytometry staining
for memory B cells and Tfh cells. |
Quantification of infectious virus: Tears were collected from both eyes using a Dacron
swab (type 1; Spectrum Laboratories, Los Angeles, CA) on days 3, 5 and 7 p.i. Individual swabs were
transferred to a 2mL sterile cryogenic vial containing 1ml culture medium and stored at -80oC until
further use. The HSV-1 titers in tear samples were determined by standard plaque assays on RS cells
as previously described (28). Eye swabs (tears) were analyzed for viral titers using the plaque assay. RS cells were grown to 70% confluency in 24-well plates. Infected monolayers were incubated at
37°C for 1 hour and rocked every 15 minutes for viral adsorption and then overlaid with medium
containing carboxymethyl cellulose. After 48 hours of incubation at 37°C, cells were fixed and stained
with crystal violet, and viral plaques and counted under a light microscope. Positive control assays
used previously titrated laboratory stocks of McKrae. B cell development by Luminex: Asymptomatic and symptomatic patients’ serum (heat-
inactivated at 56ºC for 30 minutes) were assayed for cytokines involved in B cell development namely
APRIL, BAFF, IL-10, IL-21, IL-7 and TNF-using the Luminex kit according to the manufacturer’s
instructions (R & D systems). Samples were assayed using the Luminex assay system (Magpix). Statistical analyses: Data for each assay were compared by analysis of variance (ANOVA)
and Student's t test using GraphPad Prism version 5 (La Jolla, CA). Differences between the groups
were identified by ANOVA and multiple comparison procedures, as we previously described (29). Data are expressed as the mean + SD. Results were considered statistically significant at p < 0.05. 9
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
RESULTS
1. Increased frequency of HSV-1 specific circulating memory B cell in ASYMP HSV-1
infected individuals: Asymptomatic and symptomatic HSV-1 infected individuals were recruited to
the study to understand the role of B cells in herpes. We collected their peripheral blood samples. PBMCs from ASYMP and SYMP individuals were stained for total B cells (CD19+), memory B cells
(CD19+CD27+), IgG memory B cells (IgG+CD19+CD27+), IgA memory B cells (IgA+CD19+CD27+), IgM
memory B cells (IgM+CD19+CD27+). ASYMP and SYMP individuals showed no differences in these
general B cell profiles (Fig. S1). We stained the ASYMP and SYMP individuals for HSV-1 gD antigen
specific memory B cells. HSV-1 specific memory B cells were studied by both antigen specific flow
cytometry and ELISA. PBMC ex vivo was stained for CD19+ CD27+ B cells and analyzed for HSV-1
gD antigen binding cells. |
As expected, the percentage of herpes specific memory B cells were very
low in the peripheral blood. Memory B cells express the antibody on their surface. HSV-1 gD antigen
was conjugated to Alexa-fluor 488 and A647 fluorophores. Cells binding to both the antigen bound
fluorophore were gated as HSV-1 specific cells. To confirm the gate, we performed florescence minus
one (FMO) (Fig. 1A). We found an increased percentage of HSV-1 gD binding memory B cells in
circulation of ASYMP individuals compared to SYMP herpes positive subjects [0.639 ± 0.102 % Vs
0.358± 0.070 %] (Fig. 1B). HSV-1 and HSV-2 negative individuals showed no detectable memory B
cells compared to ASYMP individuals and SYMP herpes positive subjects (data not shown). PBMCs from ASYMP, SYMP HSV-1 infected individuals and HSV-1 uninfected individuals
were also treated with (IL-2 & Resiquimod) for 5 days for polyclonal stimulation of memory B cells into
plasma cells (Antibody Secreting Cells-ASC). Stimulated cells were then analyzed for HSV-1 gD
specific IgG/ IgA ASC and total IgG/ IgA ASC by ELISPOT. We detected an increased HSV-1 gD
specific ASC (both IgG [41.36 ± 7.7 Vs 22.57 ± 3.92] and IgA [21.14 ± 3.15 Vs 12 ± 1.5] in ASYMP
compared to SYMP (Fig. 1C and 1D). The ELISPOT findings confirm flow cytometry that ASYMP
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this version posted October 7, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
individuals have increased circulating memory cells binding to HSV-1 gD compared to SYMP
individuals. As expected, HSV-1 and HSV-2 negative individuals showed no detectable HSV-1 gD
specific IgG/ IgA ASC compared to ASYMP and SYMP herpes positive subjects (Fig. 1C). 2. Circulating HSV-1 specific switched memory B cells positively correlates with
memory Tfh: CD19+CD27+IgD− cells are known as “switched” memory B cells which indicates B-cell
activation & development in germinal centers in lymph nodes or other secondary lymphoid tissues. PBMCs from asymptomatic and symptomatic HSV-1 infected individuals were stained for memory
switched B cells (CD19+CD27+IgD-) and HSV-1 gD specific memory switched B cells (Fig. 2A). We
found a trend towards increased switched memory B cells in ASYMP (0.771 ± 0.12%) compared to
SYMP (0.345 ± 0.09%) (P = 0.04) (Fig. 2B), indicating that T cell dependent memory B cell is
diminished during SYMP herpes infection. Switched memory B cells are derived from naïve B cells with T-cell help in extra-follicular or
germinal centers. Hence, we explored the levels of circulating T follicular helper T memory cells
(cTFH memory) that is found in circulation of asymptomatic and symptomatic HSV-1 infected
individuals by flow cytometry. |
ASYMP (n = 7) and SYMP (n = 7) individuals PBMCs was also stained
for Tfh cells (CD3+ CD4+ CXCR5+ T cells) and Tfh memory cells (CD3+CD4+CD45R0+CXCR5+ T cells)
(Fig. 2C). We detected a positive correlation between the percentage of HSV-1 specific switched
memory B cells (CD19+CD27+IgD- B cells) and T follicular helper memory cells (Tfh memory)
(CD3+CD4+CD45R0+CXCR5+ T cells) in PBMCs of HSV-1 infected individuals (P = 0.04). 3. HSV-1 binding antibody and neutralizing antibody levels in plasma of ASYMP and
SYMP herpes infected individuals are similar: Circulating binding/neutralizing antibodies (secreted
by ASC/plasma cells) are the first-line of B cell defense that target the virus. Serum from
asymptomatic and symptomatic HSV-1-infected individuals were used in the estimation of anti-HSV-1
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available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
gD antibodies by ELISA. No significant difference in the anti-HSV-1 IgG and IgA antibody levels in
plasma of ASYMP and SYMP herpes infected individuals was observed (Fig. 3C). Similarly, anti-
HSV-1 neutralizing antibody titer of ASYMP (PRNT50 is 832) and SYMP (PRNT50 is 1024) herpes
individuals did not vary significantly. PRNT50 represents reciprocal serum dilution at which 50% virus
neutralization was observed. 4. Increased memory B cells in spleen of ASYMP HSV-1 reactivated mice: To further
understand the role of circulating memory B cell in asymptomatic herpes, we used UV-B reactivation
in the HSV-1 infected mouse model. Cornea of B6 mice were infected with HSV-1 McKrae (1X106
pfu/eye) and virus reactivation was provoked at day 35 PI in latently infected mice, using a 60-second
corneal UV-B irradiation. At day 6 post-reactivation, mice were categorized into ASYMP or SYMP
depending on disease occurrence and euthanized and immune cells from peripheral blood, spleen
and bone marrow were collected for flow cytometry staining of B memory cells. Memory B cells are
B220+CD73+ B cells and its subsets B220+CD73+CD80+PD-L2+ B cells (Fig. 4A). The percentage of
memory B cells B220+CD73+ in the spleen was observed to be higher in ASYMP (12.65 ± 0.55%) as
compared to SYMP (7.64± 0.42%) while no difference was observed in the memory B cells bone
marrow in ASYMP and SYMP infected mice (3.01± 0.03%Vs 2.35± 0.25%) (Fig. 4B). Immune cells from peripheral blood, spleen and bone marrow were stimulated with mouse
polyclonal B cell activator (IL-2 + Resiquimod) for maturation of memory B cells to ASC (using human
B-Poly-S from Immunospot, OH, USA). The stimulated cells were incubated in ELISPOT plates to
enumerate anti-HSV-1 IgG ASC and total IgG ASC (from PBMC, spleen and bone marrow). |
Anti-
HSV-1 IgG ASC from PBMCs, spleen and BM depicted an increased trend in ASYMP compared to
SYMP. The results from the mouse reactivation model confirm the results from humans showing an
increased memory B cell profile in ASYMP herpes. However, we did not find any difference in the
memory B cell frequency in the cornea of infected ASYMP mice compared to SYMP mice (data not
shown). 12
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
5. Increased plasma cells in TG of ASYMP mice compared to SYMP mice: ASYMP and
SYMP mice were euthanized and immune cells from peripheral blood, spleen, BM and TG cells were
stained for plasma cells (CD138+ B cells) for flow cytometry. There was an increase in the percentage
of plasma B cells (CD138+ B cells) in TG of ASYMP (5.23 ± 0.47%) as compared to SYMP (2.15 ±
0.50%) mice (Fig. 5A). ASYMP mice had increased HSV-1 specific plasma B cells (HSV-1 gD+
CD138+ B cells) (6.53 ± 0.15% Vs 4.54± 0.44%) compared to SYMP mice (Fig. 5B). 6. Tfh and Tfh memory cell profile in spleen of ASYMP and SYMP HSV-1 infected mice:
Spleen cells were collected
for
flow cytometry staining of T
follicular helper
(Tfh)
(CD3+CD4+CXCR5+PD1+
cells) and T
follicular helper memory
(Tfh memory
cells)
(CD3+CD4+CD44+CXCR5+ PD-1+ cells). There was no difference detected in the percentage of Tfh
cells (top) Tfh memory (bottom) in spleen of ASYMP (Tfh: 11.7± 1.2%, Tfh memory: 7.45 ± 0.45%)
and SYMP (Tfh: 12.57± 0.88%, Tfh memory: 8.99 ± 0.32%) infected mice (Figs. 6A and 6B). 7. Increased APRIL (B cell proliferation
inducing
ligand)
in asymptomatic vs
symptomatic herpes individuals: Asymptomatic and symptomatic patients’ serum (heat-inactivated
at 56ºC for 30 minutes) were assayed for cytokines involved in B cell development APRIL (a B cell
proliferation inducing ligand), BAFF (B cell activating factor), IL-10, IL-21, IL-7 and TNF-(B cell
development cytokine) by Luminex. We found increased APRIL levels in serum of ASMP herpes
individuals (109.4 ± 16.03 pg/ml) compared to SYMP herpes individuals (73.5 ± 6.7 pg/ml). The levels
of other B cell associated cytokines such as BAFF, IL-10, IL-21, IL-7 and TNF- did not vary
significantly between asymptomatic and symptomatic herpes individuals. 13
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It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
DISCUSSION
The development of an effective therapy to alleviate symptoms of recurrent Herpes Stromal
Keratitis is dependent on our understanding of immune response to herpes infection. In the current
study, we are examining the role of B cell mediated immunity in the human response to HSV-1
reactivation. Anti-herpes antibodies are reported to not be protective during primary herpes infection
(32). Reports are indicating that high titers of herpes neutralizing antibodies in the blood of
symptomatic herpes is neither associated with the frequency of symptomatic herpes (30, 31) nor
protection after vaccination (32, 33). Thus, the general understanding is that anti-herpes antibodies
although are neutralizing or binding, are not protective (34). Another theory states that certain HSV-
specific antibodies may function protectively in tissue near the site of viral release. However,
circulating antibody levels do not reflect this tissue-based event (35). Cell-to-cell spread of the virus is
sufficient for propagation and development of symptomatic reactivation even in the presence of
effective neutralizing antibodies. Therefore, the concentration of such antibodies is below the
threshold of efficacy (36). Recent evidence suggests a more migratory role of B cells to the site of
herpes reactivation in skin (15). Memory B cells can survive for long periods & can induce faster and stronger humoral
responses when they reencounter the same antigen (37), in contrast to plasma cells which provide
the first line of protection against infection but do not respond to the second infection because of low
expression of membrane-bound Ig (38). There is evidence which indicates that human memory B
cells reside mostly in the spleen, & some memory B cells recirculate in the blood. In the present study,
we evaluated whether and if memory B cell response is associated with protection in HSV-1 infection,
a question that is not yet fully understood. The frequency of memory B cells and a counterpart of
follicular helper T cells (Tfh) found in circulation of asymptomatic and symptomatic HSV-1 infected
individuals were studied by flow cytometry. The memory B cells can respond to re-infection with rapid
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
formation of extra-follicular foci, thereby broadening the oligo-clonal repertoire of germ-line encoded B
cells causing a broadening of the antiviral B- cell repertoires (37). Our results show that asymptomatic
HSV-1 infected individuals do not only have an increased frequency of circulating memory B cell
specific to HSV-1 gD antigen but also an increased HSV-1 specific memory B cell functional response
as estimated by ELISPOT and the levels of circulating HSV-1 specific memory B cells were directly
proportional to the level of circulating follicular helper CD4 T cells. |
We also examined if there were
any differences in B cell development associated cytokines and ligands (APRIL, BAFF, IL-10, IL-21,
TNF-
in the serum of ASYMP and SYMP herpes individuals. We found that APRIL, released by
myeloid and stromal cells, which can enhance the longevity of humoral immune response, was
increased in the serum of asymptomatic herpes individuals. Currently, there is no effective cure or vaccine against HSV infection. HSV vaccines from the
past focused on subunit formulations designed to elicit neutralizing antibodies targeting the envelope
glycoprotein D (gD). Passive antibody transfer and sequential infection experiments demonstrated
'original antigenic suppression', a phenomenon in which antibodies suppress memory responses to
the priming antigenic site. While these vaccines elicited high levels of neutralizing antibodies in
animals and humans, they failed to protect against HSV-2 infections in clinical trials. Our observation
showed that in spite of an increased memory B cells in circulation, the herpes antibody levels
remained the same between ASYMP and SYMP. Thus, we wanted to explore if HSV-1 specific
memory B cells found in circulation would possibly have any role or effect that is confined locally at
the site of reactivation in asymptomatic herpes using UV-B-induced HSV-1 reactivation mouse
model. Although the spleen and tonsil are the major reservoirs for antigen-specific human memory B
cells, they appear to be dispensable for preserving immunological memory following a re-encounter
with the antigen (38). There was a trend towards an increased memory B cell response, but not the
antibody-secreting plasma cells in PBMCs, spleen and bone-marrow of asymptomatic compared to
symptomatic HSV-1 reactivated mice. In another recent study, investigators have shown that maternal
antibodies were found at fetal trigeminal ganglia conferring complete protection for newborn mice
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
against HSV infection. In our study, we detected an increase in HSV-1 specific plasma B cells in the
TG of asymptomatic mice as compared to symptomatic mice. Thus, the discordance between HSV-
specific memory B cells and antibody levels in circulation in human natural infection can be explained
by a virus driven memory B cell recruitment mechanism that leads to antibody production at the site of
reactivation (TG) using mouse model. Our findings suggest that circulating HSV-specific antibody-
producing memory B cells recruited locally at the TG site could contribute to protection from
symptomatic recurrent ocular herpes. |
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
ACKNOWLEDGEMENTS
This work is supported by a grant from Trefoil Therapeutics, Inc. and by Public Health Service
research grants EY019896, EY14900 and EY024618 from the National Eye Institutes (NEI) and
AI150091, AI143348, AI147499, AI143326, AI138764, AI124911 and AI110902 from the National
Institutes of Allergy and Infectious Diseases (NIAID) to LBM and from The Discovery Center for Eye
Research, and in part by Research to Prevent Blindness. 17
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
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Invariant Natural Killer 1 Cells
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this version posted October 7, 2021. |
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available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
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The copyright holder for this preprint
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available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
37. Baumgarth N. 2013. How specific is too specific? B-cell responses to viral infections reveal the
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https://doi.org/10.1101/2021.10.05.463293
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this version posted October 7, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
FIGURE LEGENDS
Figure 1: Circulating HSV-1 gD specific memory B cell profile in asymptomatic and
symptomatic herpes infected individuals: PBMC from asymptomatic and symptomatic HSV-1
infected individuals were stained for HSV-1 gD antigen specific memory B cells. PBMC were also
treated with (IL-2 & Resiquimod) for 5 days for polyclonal stimulation of memory B cells in to plasma
cells (Antibody Secreting Cells-ASC). The stimulated cells were then analyzed for HSV-1 gD specific
IgG/ IgA ASC and total IgG/ IgA ASC by ELISPOT. (A) FACS plot showing the gating strategy for
HSV-1 specific memory B cells (CD19+CD27+ B cells) in PBMC of asymptomatic (ASYMP) (Left
panels) and symptomatic (SYMP) (Right panels) HSV-1 infected individuals. (B) Graph showing
percentage of HSV-1 specific memory B cells (CD19+CD27+ B cells) in PBMC of ASYMP and SYMP
HSV-1 infected individuals. (C) Representative ELISPOT images for anti-HSV-1 IgG ASC (Left, top
panel) anti-HSV-1 IgA ASC (Left, bottom panel) from PBMC of ASYMP, SYMP HSV-1 infected
individuals and HSV-1 uninfected individuals (polyclonally stimulated for maturation of memory B cells
to ASC). (D) Graph showing anti-HSV-1 IgG (Left, top panel) and IgA (Left, bottom panel) ASC; total
IgG (Right, top panel) and total IgA (Right, bottom panel) ASC from PBMC of ASYMP, SYMP HSV-1
infected individuals and HSV-1 uninfected individuals. Statistical analysis was done using student’s t
test. NS: not significant. Figure 2: Correlation of HSV-1 specific memory B cell and memory T follicular helper T
cells in herpes infected individuals: PBMC from asymptomatic and symptomatic HSV-1 infected
individuals were stained for switched memory B cells (CD19+CD27+IgD-) and HSV-1 gD specific
switched memory B cells. (A) FACS plot showing gating strategy for HSV-1 specific switched memory
B cells (CD19+CD27+ B cells) in PBMC of asymptomatic (ASYMP) (Left panels) and symptomatic
(SYMP) (Right panels) HSV-1 infected individuals. |
(B) Graph showing percentage of HSV-1 specific
switched memory B cells (CD19+CD27+IgD- B cells) in PBMC of ASYMP and SYMP HSV-1 infected
individuals. (C) FACS plot showing gating strategy
for T
follicular helper cells
(Tfh)
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https://doi.org/10.1101/2021.10.05.463293
;
this version posted October 7, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
(CD3+CD4+CXCR5+ T
cells) and T
follicular helper memory
cells
(Tfh memory)
(CD3+CD4+CD45R0+CXCR5+ T cells) in PBMC of asymptomatic (ASYMP) (Left panels) and
symptomatic (SYMP) (Right panels) HSV-1 infected individuals. (B) Graph showing correlation of the
percentage of HSV-1 specific switched memory B cells (CD19+CD27+IgD- B cells) and T follicular
helper memory cells (Tfh memory) (CD3+CD4+CD45R0+CXCR5+ T cells) in PBMC of HSV-1 infected
individuals. Statistical analysis was done using student’s t test. NS: not significant. Figure 3: Anti-HSV-1 IgG and IgA antibody levels and neutralizing antibody titre in
ASYMP and SYMP herpes infected individuals: Serum from asymptomatic and symptomatic HSV-
1 infected individuals were used for estimation of anti-HSV-1 gD antibodies by ELISA. (A) Graphs
showing levels of anti-HSV-1 IgG antibody level (left panel) and anti-HSV-1 IgA antibody level (left
panel) in serum of ASYMP and SYMP herpes infected individuals. (A) Graph showing anti-HSV-1
neutralizing antibody titer in serum of ASYMP and SYMP herpes infected individuals. Statistical
analysis was done using student’s t test. NS: not significant. Figure 4: Memory B cell profile in PBMC, Spleen and bone marrow of ASYMP and SYMP
HSV-1 reactivated mice: For this experiment, the cornea of B6 mice were infected with HSV-1
McKrae (1X106 pfu/eye) by scarification and virus reactivation was provoked at day 35 PI in latently
infected mice, using a 60 second corneal UV-B irradiation. At day 6 post-reactivation, mice were
categorized into ASYMP or SYMP depending on disease occurrence. ASYMP and SYMP mice were
euthanized and immune cells from peripheral blood, Spleen and bone marrow were collected for
flowcytometry staining for memory B cells. (A) FACS plot showing representative plots for memory B
cells (B220+ CD73+ B cells) and the subsets (B220+CD80+PD-L2+ B cells) in spleen (Left panels) and
bone marrow (Right panels) of ASYMP and SYMP infected mice. (B) Graph showing percentage of
for memory B cells (B220+CD73+ B cells) and the subsets (B220+CD73+CD80+PD-L2+ B cells) in
Spleen (left panel) and bone marrow (Right panel) of ASYMP and SYMP infected mice. (C)
Representative ELISPOT images for anti-HSV-1 IgG ASC (Left panel) and total IgG ASC (Right
25
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bioRxiv preprint
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https://doi.org/10.1101/2021.10.05.463293
;
this version posted October 7, 2021. |
The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
panel) from PBMC, spleen and bone marrow from ASYMP, SYMP infected mice (polyclonally
stimulated with mouse polyclonal B cell activator (IL-2+Resiquimod) for maturation of memory B cells
to ASC). Graph showing anti-HSV-1 IgG (Left panel) and total IgG (Right panel) ASC from PBMC of
ASYMP, SYMP HSV-1 infected mice. Statistical analysis was done using student’s t test. NS: not
significant. Figure 5: Plasma cell profile in PBMC, spleen, bone marrow and TG of ASYMP and
SYMP HSV-1 infected mice: For this experiment, the cornea of B6 mice were infected with HSV-1
McKrae (1X106 pfu/eye) by scarification and virus reactivation was provoked at day 35 PI in latently
infected mice, using a 60 second corneal UV-B irradiation. At day 6 post-reactivation, mice were
categorized into ASYMP or SYMP depending on disease occurrence. ASYMP and SYMP mice were
euthanized and immune cells from peripheral blood, Spleen and bone marrow were collected for
flowcytometry staining for plasma cells. (A) Representative plots for plasma B cells (CD138+ B cells)
in PBMC, Spleen, PBMC and TG (Left panels) of ASYMP and SYMP mice is shown. Graph showing
percentage of plasma B cells (CD138+ B cells) in PBMC, Spleen, PBMC and TG (Right panels) of
ASYMP and SYMP mice. (B) Representative FACS plot showing HSV-1 specific plasma B cells
(HSV-1gD+CD138+ B cells) in PBMC, Spleen, PBMC, and TG (Left panels) of ASYMP and SYMP
mice. Graph showing percentage of HSV-1 specific plasma B cells (HSV-1gD+CD138+ B cells) in
PBMC, Spleen, PBMC and TG (Right panels) of ASYMP and SYMP mice. Figure 6. T follicular helper (Tfh) and T follicular helper memory (Tfh memory) cell
profile in spleen of ASYMP and SYMP HSV-1 infected mice: B6 mice were infected with HSV-1
McKrae (1X106 pfu/eye) by scarification and at day 35 PI, reactivation was done by a 60 second
corneal UV-B irradiation. Mice were categorized as ASYMP /SYMP and euthanized at day6 post-
reactivation. Spleen cells were collected for flowcytometry staining of T follicular helper (Tfh)
(CD3+CD4+CXCR5+PD-1+
cells)
and
T
follicular
helper memory
(Tfh memory)
(CD3+CD4+CD44+CXCR5+PD-1+
cells). (A) Representative FACS plots
for Tfh
cells
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bioRxiv preprint
doi:
https://doi.org/10.1101/2021.10.05.463293
;
this version posted October 7, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . Memory B cells in Ocular Herpes
(CD3+CD4+CXCR5+PD-1+
cells)
is
shown
in
top
panel
and Tfh memory
cells
(CD3+CD4+CD44+CXCR5+PD-1+ cells) is shown in bottom panels for ASYMP (left panel) and SYMP
(right panel) infected mice. |
(A) Graph showing percentage of Tfh cells (top) Tfh memory (bottom) in
spleen of ASYMP and SYMP infected mice is shown. Figure 7. B cell ligand and cytokine level in serum of asymptomatic ans symptomatic
herpes: Asymptomatic (n=20) and symptomatic (n=20) patients’ serum were assayed for cytokines
involved in B cell development. Graph showing serum level of A). APRIL (B cell proliferation inducing
ligand), BAFF (B cell activating factor), IL-10 (B regulatory cell cytokine) B). IL-21 (involved in
expansion and differentiation of plasma cells), IL-7 (B cell development cytokine) and TNF-(B cell
development cytokine) by Luminex. Statistical analysis was done using student’s t test. NS: not
significant. 27
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. bioRxiv preprint
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this version posted October 7, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . bioRxiv preprint
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this version posted October 7, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license
. bioRxiv preprint
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this version posted October 7, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY 4.0 International license . bioRxiv preprint
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;
this version posted October 7, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
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bioRxiv preprint
doi:
https://doi.org/10.1101/2021.08.18.456454
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this version posted August 19, 2021. The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . THE TRANSCRIPTIONAL RESPONSE TO OXIDATIVE STRESS IS INDEPENDENT
OF STRESS-GRANULE FORMATION
Amanjot Singh1,#, Arvind Reddy Kandi2,*, Deepa Jayaprakashappa1,*, Guillaume Thuery3,
Devam J Purohit1, Joern Huelsmeier3, Rashi Singh1, Sai Shruti Pothapragada1, Mani
Ramaswami1,3†, and Baskar Bakthavachalu2,4 †. 1National Centre for Biological Sciences, TIFR, Bangalore 560065, India. 2Tata
Institute for Genetics and Society Centre at inStem, Bellary Road, Bangalore 560065, India. 3Trinity College Institute of Neuroscience, School of Genetics and Microbiology, Smurfit
Institute of Genetics and School of Natural Sciences, Trinity College Dublin, Dublin-2
Ireland. 4School of Basic Sciences, Indian Institute of Technology, Mandi 175005, India. Equal contribution. † Lead Corresponding Authors:
[email protected]; Phone +353 (1) 896 8400
[email protected]; Phone +91 1905-267114
# Co-corresponding author:
[email protected]
Running Title: Drosophila stress transcriptome without Rin/ G3BP. Keywords: Oxidative stress response, stress granule, RNA-binding protein, transcriptome, chaperone, HSP, G3BP, Rasputin, Ataxin-2, Drosophila, S2 cells. bioRxiv preprint
doi:
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . ABSTRACT Cells respond to stress with translational arrest, robust transcriptional changes, and transcription- independent formation of mRNP assemblies termed stress granules (SGs). Despite considerable interest in the role of SGs in oxidative, unfolded-protein, and viral stress responses, whether and how SGs contribute to stress-induced transcription has not been rigorously examined. To address this issue, we characterized transcriptional changes in Drosophila S2 cells induced by acute oxidative-stress and assessed how these were altered under conditions that disrupted SG assembly. Sodium-arsenite stress for 3 hours predominantly resulted in the induction or upregulation of stress-responsive mRNAs whose levels peaked during cell recovery after stress cessation. The stress-transcriptome is enriched in mRNAs coding for protein chaperones, including HSP70 and low molecular-weight heat shock proteins, glutathione transferases, and several non-coding RNAs. Oxidative stress also induced prominent cytoplasmic stress granules that disassembled 3-hours after stress cessation. As expected, RNAi-mediated knockdown of the conserved G3BP1/ Rasputin protein inhibited stress-granule assembly. |
However, this disruption had no significant effect on the stress-induced transcriptional response or stress-induced translational arrest. Thus, SG assembly and stress-induced effects on gene expression appear to be driven by distinctive signaling processes. We suggest that while SG assembly represents a fast, transient mechanism, the transcriptional response enables a slower, longer-lasting mechanism for adaptation to and recovery from cell stress. INTRODUCTION
Oxidative stress can have several cellular consequences, including DNA damage and increased
levels of oxidized and misfolded proteins (Schieber and Chandel, 2014). It also activates
components of the cellular integrated stress response (ISR) pathway, including stress kinases that
modify the mRNA translational machinery (Balchin et al., 2016; Costa-Mattioli and Walter, 2020;
Gidalevitz et al., 2011). Phosphorylation of the eukaryotic initiation factor, eIF2α, results in
translational inhibition together with the formation of stress granules (SG), assemblies of
translationally arrested mRNAs, RNA-binding proteins and accessory components (Kedersha et
al., 1999; Kedersha and Anderson, 2002; Ron, 2002). Pathways and proteins involved in the ISR have been implicated in normal aging and in
neurodegenerative disease (Halliday et al., 2017; Krukowski et al., 2020; Radford et al., 2015). Increased levels of oxidative stress are also thought to be associated with normal brain aging
(Milton and Sweeney, 2012). Consistent with this, unusual SG-related neuronal inclusions have
been observed in post-mortem brain samples of aged but not young brains (Bäuerlein et al., 2017;
Geser et al., 2010; Ginsberg et al., 1998). SGs have gained even more significance since the
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available under a
CC-BY-NC-ND 4.0 International license . discovery that protein inclusions associated with neurodegenerative diseases can contain SG
components. In some cases, both inclusion formation and disease progression depend on factors
that drive normal SG assembly (Advani and Ivanov, 2020). In addition to SG formation, oxidative stresses regulate transcription factors such as FOXO, HSF1,
and Nrf2 to induce changes in the cellular transcriptome (Donovan and Marr, 2015; Doonan et al.,
2019; Fedoroff, 2006; Vihervaara et al., 2018). In particular, stress increases the expression of
mRNAs coding for cytoprotective proteins, including protein chaperones and modulators of lipid
oxidation (Jacobson et al., 2012). The third effect of acute oxidative stress is to induce translational
arrest for the majority of cellular mRNAs. Here we ask whether these different stress responses
occur independently of each other. In particular, we test whether signaling mediated through
assembled stress granules contributes to the transcriptional responses to stress as has been
suggested by the role of SGs in signaling required for transcription of genes involved in viral
defense (Fung et al., 2013; McCormick and Khaperskyy, 2017; Tsai and Lloyd, 2014). |
In cultured
Drosophila S2 cells, we: (a) document the requirements and kinetics of SG formation and
disassembly; (b) obtain robust data sets for stress-induced transcriptional changes during and after
acute stress; and (c) examine how the stress-induced transcriptome and global mRNA translation
is altered when SG assembly is perturbed. We address these issues in Drosophila cells, partly for
the ease with which stress-granule assembly can be visualized and perturbed in these cells but
mainly because Drosophila allows facile, future follow-up experiments to assess the function of
stress-regulated genes in vivo. As anticipated, Drosophila S2 cells acutely exposed to the well-known stressor sodium arsenite
show robust formation of Ataxin-2 and Rasputin (Rin)/Ras GTPase-activating protein-binding
protein 1 (G3BP1) positive SGs along with simultaneous inhibition of global translation (Escalante
and Gasch, 2021; Ivanov et al., 2019; Jain et al., 2016; Kedersha et al., 2016; Kedersha and
Anderson, 2007; Wheeler et al., 2016). Parallel RNA-seq analyses show that arsenite stress also
induces upregulation of around 300 different transcripts. Following three hours of post-stress
recovery in the absence of arsenite, SGs disassemble and become invisible. In contrast, the vast
majority of stress-induced mRNAs remain upregulated, consistent with a model in which SGs
represent an acute protective mechanism that provides cells time to launch a longer-lasting
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available under a
CC-BY-NC-ND 4.0 International license . transcription-dependent program for recovery from stress. In cells lacking Rin, although stress
granules are not visible, stress-induced translational arrest and stress-induced transcription remain
unchanged. These data indicate stress-granule formation is largely dispensable for oxidative-
stress-induced changes to gene regulation. RESULTS
Kinetics of assembly of arsenite-induced stress granules in Drosophila S2 cells
To understand cellular changes occurring during oxidative stress and subsequent recovery, we
employed sodium arsenite as a stressor in Drosophila S2 cells, an established cellular model for
studying the stress response (Aguilera-Gomez et al., 2017; Farny et al., 2009). Consistent with
prior observations (Bakthavachalu et al., 2018; Farny et al., 2009), we found that exposure of cells
to 0.5mM arsenite for 1h leads to the formation of numerous Ataxin-2 (Atx2) and Rin/G3BP
positive stress granules; these appeared larger and more distinct after 3h of stress (Fig. 1A-i,-ii). To determine the temporal dynamics of clearance of SGs, we stressed the cells for 3h, allowed
them to recover by replacing the stressor with a fresh culture medium, and monitored SGs at
specified time points afterward. |
Although some cells still had several granules, recovery from
stress, in general, was accompanied by the progressive disappearance of SGs with majority of cells
having no or a few granules (Fig. 1B; Supplementary Fig. 1A). While some Atx2-positive granules
remained after 1h of recovery (Fig. 1A- iv), none were visible after 3 hours in most cells (Fig. 1A-
v). To address whether the disappearance of stress granules after recovery correlated with reduced
stress signaling, we assessed phosphorylation levels of eIF2α at S51 (Fig. 1D). It is well
established that stress-kinases such as PEK and GCN2 phosphorylate eIF2α trigger arsenite-
induced SGs formation (Farny et al., 2009). Consistent with this, we observed that eIF2α
phosphorylation in S2 cells is significantly elevated following either 1h or 3h of exposure to
arsenite (Fig. 1D). After 3 hours of arsenite removal, levels of eIF2α phosphorylation were
comparable to those under control conditions: moreover, there was no change in total eIF2α
expression under any of these conditions (Fig. 1D). Taken together, these observations confirm
and extend previous findings in S2 cells, showing that oxidative-stress induced SGs are transient,
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available under a
CC-BY-NC-ND 4.0 International license . dynamic structures whose assembly/disassembly is concomitant to eIF2α phosphorylation and
whose formation is associated with the shutdown of protein translation. A. B. Control 3hrs
Stress 1hrs 3hrs
Recovery 1hrs 3hrs
l l e c
20
****
****
****
(i)
(ii)
(iii)
(iv)
(v)
r e p s G S
15
10
2 x t A
f o r e b m u N
5
0
C o ntrol
Stress R ec o very
C.
Atx2
Rin
Merge
l
D.
o r t n o C
No stress
Stress
S1 S2
Recovery
R1 R2
eIF2-alpha S51
eIF2-alpha
s s e r t S
Fig. 1. Kinetics of assembly of arsenite-induced SGs in Drosophila S2 cells. A. Progression of arsenite-
induced SGs assembly. Untreated S2 cells do not show any granular structures stained by anti-Atx2
antibodies. Atx2-positive stress granules appear within 1-hour of arsenite exposure. More distinct granules
are seen after 3 hours. Upon removing stress, the granules gradually start to clear, and after 3h of recovery,
Atx2 returns to its normal diffused state. Staining was performed using antibodies against Atx2. B. Number
of granules present per cell under control, stress and recovery are plotted. The number of cells and the
granules present in the cells were quantified using CellProfiler. Mann-Whitney U- test shows that there was
a significant difference in the number of granules between stressed and recovered cells (p < 0.05). Images
and raw values corresponding to the analyses are shown in Supplementary Fig. 1A and Supplementary File
1. C. Atx2 and Rin co-localize in SGs, shown by staining with antibodies against Atx2 and Rin. |
D. Western
blotting of total cell lysates shows that eIF2-α is hyper-phosphorylated during 1h (S1) and 3h (S2) stress. Cells were allowed to recover for 3h after both 1h (R1) and 3h (R2) of stress. Total eIF2 α levels do not
show any change. Uncropped Western blots are shown in Supplementary Fig. 1B. Scale bar represents 2µm
(A) and 10µm (C). bioRxiv preprint
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available under a
CC-BY-NC-ND 4.0 International license . Distinctive acute stress and post-stress (“recovery”) transcriptomes
Genes transcriptionally regulated by stress could potentially encode factors involved in regulating
the assembly and clearance of SGs or managing molecular or physiological consequences of stress. To identify molecules potentially involved in these processes, we examined transcriptional
changes in S2 cells under acute stress conditions and following recovery. We isolated total RNA
from cells that were (a) untreated, (b) stressed for 3h, and (c) recovered for 3h following 3hr stress
and used RNA-Seq to identify and analyse polyA-selected RNA populations in each condition
(Fig. 2A). Three independent biological replicates were used for each of the three conditions. A
total of more than 114 million high-quality reads (average ~10 million reads per sample) were
generated and mapped to the Drosophila genome using STAR v2.5.3 (Supplementary File 2). The
uniquely mapped reads for each sample were processed using HTSeq to determine the transcripts'
normalized expression levels. The correlation coefficient values demonstrate high similarity
(0.992 to 1.0) across the biological replicates and clear differences in global transcriptomes during
normal, stress, and recovery conditions (Fig. 2B; Supplementary Fig. 2). Thus, the analyses show
that control transcriptomes differ significantly from those of cells during stress and following 3
hours of recovery. bioRxiv preprint
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CC-BY-NC-ND 4.0 International license . bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Fig. 2. Distinctive normal, stress, and recovery transcriptomes. A. Schematic representation of the
experimental design. Cells were stressed for 3h with 0.5mM sodium arsenite and pelleted for RNA
isolation. |
For Recovery, arsenite was removed after 3h of stress, and cells were washed three times with S2
cell culture media and then maintained in fresh media for an additional 3h. Cells were subsequently
harvested for RNA isolation. B. Pearson’s correlation plot visualizing the correlation between samples. The
colour scale represents the range of correlation coefficients displayed. C. Volcano plots showing the
differentially regulated transcripts in stress and recovery. D. Venn diagram depicting the overlap between
“stress” and “recovery” transcriptomes. E. Gene ontology analysis of differentially expressed genes during
stress and recovery. The enriched GO terms (biological process) in differentially expressed (up/down)
genes under stress and recovery conditions compared to control conditions are shown via heatmap. The
scale at the bottom represents enriched GO terms in –log10p-value. Strong transcriptional changes are observed after stress cessation. To identify the main differences in transcriptomes across cells at rest, under stress, and after
recovery, we identified genes whose expression was altered at least log2 fold change of 2 with an
adjusted P-value (padj) <0.05 between conditions (using the average expression values across
replicates in each). Of 374 transcripts that were differentially regulated after 3 hours of stress, we
found that levels of 325 transcripts were elevated and only 49 reduced compared to untreated cells
(Fig. 2C, Supplementary File 3), indicating that stress predominantly resulted in induction of
transcription. Transcriptomes of cells 3-hours after recovery were even more different from untreated cells, than
were transcriptomes of cells 3-hours after stress. Thus, 1105 transcripts showed at least log2 fold
change of 2 difference in expression in cells 3-hours post-recovery compared to untreated cells. Of these 1105 transcripts, 1065 were upregulated, and 40 transcripts were downregulated (Fig. 2C). More detailed comparisons indicate that mRNAs upregulated more than log2 fold change of
2 after 3-hours recovery were generally induced, albeit to a lesser extent, after stress alone. Consistent with this, when transcriptomes of cells 3-hours post-recovery compared with
transcriptomes of stressed cells, we found only 355 transcripts that showed a log2 fold change of
2 increase in expression after 3-hours of recovery (Fig. 2C). Intriguingly, mRNAs induced by acute
stress stayed upregulated for hours after the stressor was removed. Thus, the expression of almost
all the transcripts differentially regulated in stress was also similarly altered following 3 hours of
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available under a
CC-BY-NC-ND 4.0 International license . post-stress recovery (Fig. 2D). |
Only 48 transcripts were unique to stress transcriptome; 22 of these
were upregulated while 26 were downregulated. These observations clearly show that unlike SGs,
which disassemble when the stressor is removed, stress-induced transcriptional changes persist
long after the stressor is gone. A Gene Ontology (GO) enrichment analysis provided a high-level view of functional classes of
genes over-represented during stress and subsequent recovery (Fig. 2E). In particular, mRNAs
known to respond to increased temperature and heat stress were particularly highly enriched during
stress and after a 3-hour recovery (Fig. 2E, Supplementary File 3). Multiple classes of potentially cytoprotective mRNAs induced by stress:
A detailed analysis of the identity of stress-regulated mRNAs was consistent with a model in which
oxidative stress predominantly leads to the upregulation of a cohort of genes required for a delayed
response to acute stress in S2 cells (Fig. 2C, D, Supplementary Fig. 3). Of 100 genes most strongly
upregulated after 3 hours of recovery, several encoded heat-shock proteins (HSP) of the HSP70
(Hsp70Bc, Hsp70Bbb, Hsp70Ba, Hsp68), HSP40 (DnaJ-1), low molecular weight (LMW), HSP
(Hsp23, Hsp26, Hsp27) families, and co-chaperones (stv) families (Fig. 3A). Interestingly, several
of these upregulated genes have been previously shown to be regulated by heat stress in Drosophila
(Vos et al., 2016). This indicates significantly overlapping cellular mechanisms for the
management of oxidative stress and heat stress, which is consistent with previous observations for
the phenomenon of “cross-tolerance” in other organisms (Mittal et al., 2012; Perez and Brown,
2014; Vert and Chory, 2011). The upregulation of Hsp mRNAs seems to be an evolutionarily
conserved response required for folding the misfolded/aggregated proteins during stress (Verghese
et al., 2012). In this regard, the upregulation of LMW HSPs (Hsp20/α-crystallin family) and
HSP70 mRNAs upon oxidative stress suggests extensive misfolding of proteins under the
conditions, which needs to be managed such that they can be refolded into the native state for the
cell to recover. Small HSPs (sHSPs) function as “holdases” and prevent the formation of denatured
protein aggregates in the cell and while HSP70s are the main folding agents of nascent polypeptide
chains as well as for misfolded proteins during periods of stress (Finka et al., 2016; Vos et al.,
2016). HSP27 has also been shown to bind poly-ubiquitin chains and interact with 19S proteasome
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available under a
CC-BY-NC-ND 4.0 International license . (Bozaykut et al., 2014; Mogk et al., 2019), suggesting elevated levels of this protein during
recovery may also play a role in protein triage. |
In addition, we noticed a more specific upregulation of transcripts encoding factors expected to
help counter the effects of oxidative stress (Fig. 3A), in particular, genes for glutathione-S-
transferases (GstD5, GstE7, GstE8, and GstS1). GSTs are detoxification enzymes that detoxify
reactive oxygen species by catalyzing the addition of glutathione (GSH) and protect the cell from
oxidative damage (Mailloux et al., 2013). Apart from Hsp and GST transcripts, several non-coding (nc) RNAs, CR43481, CR45380, Uhg5,
CR31044, CR43626, CR32865, Hsr-omega, and RNaseMRP:RNA were also upregulated (Fig. 3A). We speculate that these, as well as upregulated mRNAs encoding DNA-binding proteins like
bab2, edl, e(y)2b, peb, Rev1, E(spl)m3-HLH, and E(spl)mbeta-HLH could potentially regulate the
expression of “late” genes, such as those strongly induced 3-hours of recovery, of which several
interestingly encode metabolic factors (Fig. 3A, Supplementary Fig. 3). An unexpected finding is that reads corresponding to several small nucleolar RNA (snoRNA)
genes that are frequent in resting cells are highly reduced in number both during stress and after 3
hours of recovery (Fig. 3B, Supplementary Fig. 3B). snoRNAs are RNA PolII-transcribed, short
essential non-protein-coding RNAs (60-300 nucleotides long) that are mostly localized to nucleoli
(Bratkovič et al., 2020; Kufel and Grzechnik, 2019). The primary function of snoRNA-
ribonucleoprotein complex is post-transcriptional maturation of ribosomal RNA (rRNA) and small
nuclear RNAs (snRNA) through 2-O’-methylation and pseudouridylation. Because most snoRNAs
do not have polyA tails, it was quite surprising to find reads corresponding to snoRNAs in our
polyA libraries under normal conditions. Since several snoRNAs are encoded in the introns of pre-
mRNAs, particularly those encoding ribosomal proteins (Bratkovič et al., 2020; Kufel and
Grzechnik, 2019), one possibility is that RNA-Seq reads for snoRNAs correspond to the introns
from unspliced, polyadenylated nuclear pre-mRNAs (Supplementary Fig. 3C). We therefore,
examined whether the reduced number of snoRNA reads after stress could correspond to increased
splicing of the parent pre-RNAs. bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . The bed graph files for two intron-encoded snoRNAs; snoRNA:Psi18S-920 and snoRNA:Psi28S-
s648 (Fig. 3C), show that RNA-Seq reads corresponding to these snoRNAs are almost absent
during stress and recovery. If this decrease corresponds to reduced transcription, then the parent
mRNAs must also be downregulated. Instead, the normalized counts of 11 such parent ribosomal
protein genes show that in contrast to respective snoRNA reads, their levels are slightly elevated,
certainly not decreased, during stress as well as after 3 hours of recovery (Supplementary Fig. |
3C). Similarly, transcript levels of snoRNA:Me28S-A2113 and snoRNA:Psi28S-2996, which arise
from RpL30 and RpL5 respectively, also show significant reduction both during stress and
recovery (Supplementary Fig. 3D). The most likely interpretation of these observations is that the
generation of mature snoRNA present within the parent polyA mRNA through splicing becomes
more efficient in response to stress, thereby enhancing their function in modifications of rRNA
and snRNA, which ultimately could contribute to selective translation of oxidative stress specific
mRNAs. An alternative possibility is that snoRNAs are rapidly degraded under stress conditions,
thereby altering their steady-state levels without affecting levels of the spliced parent transcripts. bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . A. Control
Stress
Recovery
B. Control
Stress
Recovery
Receptor
Metabolism
ncRNA
Structural
Transporters
Glutathione
Uncharacterized
Protein homeostasis
Translation
Ion channel
DNA binding
Galphaf Toll−7 Fer2LCH CG1673 Tep2 ImpL2 bmm GlcAT−S CG6770 spin CG6330 CG31674 Mocs1 CG13893 Sirup Ugt302C1 CG2065 fok pirk CG12224 CG15097 CG5707 Gli lncRNA:CR43626 lncRNA:alphagamma−element:CR32865 Uhg5 lncRNA:Hsromega snRNA:U2:34ABa lncRNA:CR31044 RNaseMRP:RNA lncRNA:CR45380 asRNA:CR43481 Eip71CD Culd a glec scyl mfas CG17646 Mrp4 rdog Tret1−1 CG3036 Fatp3 w CG8177 GstS1 GstD5 GstE8 GstE7 CG34330 Rcd2 CG13252 CG44251 T48 r−cup Reg−5 CG17834 CG14961 CG6785 CG12723 l(1)G0469 CG42240 Hsp70Ba stv rpr Hsp70Bbb Atg18b Hsp26 Hsp70Bc Hsp23 rho DnaJ−1 Hsp27 CG11700 Hsp68 dnr1 Gadd45 Thor Trpm Piezo e(y)2b peb Rev1 CG18446 E(spl)m3−HLH E(spl)mbeta−HLH edl bab2 CG15385 IP3K1 Rgk1 stg aay Dgp−1 CG46339 CG11951 SP1029 Ccz1 Dgk
Uncharacterized
snoRNA
Metabolism
Receptor
ncRNA
C.
5
l
5
o r t n o c
5
5
5
s s e r t s
5
5
y r e v o c e r
5
5
RpL10Ab
Regularized logarithm
−2 −1
0
1
4
4
4
4
4
4
4
4
4
CG43149 CG44437 CG42654 CG13912 CG13021 CG14668 CG3323
snoRNA:Me28S−A2113 snoRNA:Psi18S−920 snoRNA:Psi28S−1175c snoRNA:Me28S−A2634b snoRNA:Me28S−A2634c snoRNA:Psi28S−1175b snoRNA:Me18S−C1831 snoRNA:Psi28S−2996 snoRNA:Me28S−G3113a snoRNA:Psi28S−2179 snoRNA:Me28S−A771 snoRNA:Psi28S−3327c snoRNA:Psi28S−2648 snoRNA:Psi28S−3305c snoRNA:Me28S−C3420a snoRNA:Or−aca1 snoRNA:Me18S−A28a snoRNA:Me28S−G3113b snoRNA:Psi28S−1192d
CG12896 Prx2540−1 CG11825 Prx2540−2 CG12200 CG11029 Vm34Ca CG6294
Ir62a
lncRNA:CR46011 lncRNA:CR44023 lncRNA:CR45981 lncRNA:CR46111 lncRNA:CR45039
2
RpL36A
Protein modification
snoRNA:Psi18S-920
snoRNA:Psi28S-2648
Regularized logarithm
−2 −1
0
1
2
Fig. 3. Oxidative stress results predominantly in the induction of target mRNAs. A. Heat map for 100 genes
most robustly upregulated following 3-hours of recovery from 3-hours of acute stress. |
Genes are grouped
based on predicted cellular functions. The fold induction is indicated in the colour scale below. B. Heat
map shows a smaller group of mRNAs for which reads are substantially decreased after acute stress. The
colour scale bar indicated fold changes represented. C. Bed graphs showing the reads under control, stress,
and recovery corresponding to the parent genes RpL10Ab and RpL36A, which harbour snoRNA:Psi18S-
920 and snoRNA:Psi28S-2648. bioRxiv preprint
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available under a
CC-BY-NC-ND 4.0 International license . Persistent transcription of chaperones after acute stress
Metabolic labeling of RNA allows one to discriminate between alterations in dynamics of RNA
production or degradation (Rabani et al., 2011). Conventional RNA-seq does not always reflect
transcriptional changes because changed levels of steady-state mRNA can also arise from altered
RNA turnover (Bansal et al., 2020; Blatt et al., 2020). To determine the origin of altered transcript
levels during stress and recovery as indicated by RNA seq analysis, we in vivo labeled nascent
mRNAs using 5-ethyl uridine (5-EU) and determined whether there was clear evidence for new
transcription of “upregulated” mRNAs using Click-iT, a technique that has been used to
distinguish mRNA turnover and de novo transcription in several organisms (Battich et al., 2020;
Chen et al., 2018; Jao and Salic, 2008; Szabo et al., 2020). For control and acutely stressed cells,
we added 5-EU in normal or arsenite-containing medium and collected cells after 3h. To analyze
transcription after the stressor had been removed (during recovery), we added 5-EU after 3h of
stress and then harvested the cells for RNA isolation (Fig. 4A). We isolated total RNA from all
the samples and used the Click-iT Nascent RNA Capture kit to selectively pull down labeled
nascent RNA on beads for cDNA synthesis and RNA-Seq. This method captured new transcripts
without the need for them to be polyadenylated. RNA-seq analysis of the Click-iT captured mRNAs confirmed increased stress-induced
transcription of mRNAs whose levels were elevated after stress. Transcripts coding for Hsps, for
example, stv, Hsp23, Hsp26, Hsp27, DnaJ-1, Hsp70Bc, Hsp68, Hsp70Ba, etc., were seen as
transcriptionally upregulated during recovery (Fig. 4B, C). This observation confirms that new
transcription of chaperones occurs during acute stress and continues for a substantial period during
recovery from stress. Interestingly, almost all the transcripts which were upregulated in stress and
recovery are predicted to be excluded from the SGs (Fig. 4D). Out of the 1856 transcripts reported
as present in SGs in Drosophila stress granules (Van Leeuwen et al., 2021), we found that only 5
transcripts were included among the stress-regulated mRNAs that we identified (Supplementary
File 3). |
Similarly, only 22, corresponding to 1.2% differentially regulated transcripts in recovery,
were found to be present in the reported collection of SG-associated mRNAs (Fig. 4D). This
comparison reveals that the mRNAs that are upregulated during stress are excluded from SGs,
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available under a
CC-BY-NC-ND 4.0 International license . suggesting that they either have roles in translational repression or encode factors that are
translated during stress and recovery. Figure 4. Recovery is characterized by de novo transcription. A. Schematic for labeling mRNAs using 5-EU. B. Enhanced levels of de novo synthesized transcripts corresponding to chaperones, GSTs, and genes involved in
metabolism during recovery from stress. C. Normalized counts of mRNAs during recovery. Transcripts coding for
GSTs, chaperones, and metabolism-related genes are shown. D. Venn diagrams comparing SG transcriptome (Van
Leeuwen et al., 2021) with mRNAs differentially regulated in both stress and recovery. Oxidative stress transcriptional response is uncoupled from SG assembly
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Given that stress induces both stress-granules and new transcription, we were interested to know
whether the assembly of SGs contributed to signaling transcription of at least a significant subset
of target mRNAs, as has been proposed following viral infection (Alam and Kennedy, 2019;
McCormick and Khaperskyy, 2017; Tsai and Lloyd, 2014). To address this outstanding question,
we asked how disrupting SG assembly would affect stress-induced transcription. The SG protein Rin/G3BP is a primary nucleator of SGs, whose knockdown prevents SG assembly
in response to starvation in Drosophila S2 cells (Aguilera-Gomez et al., 2017) as well as during
several other conditions in different mammalian cell lines (Lee et al., 2020; Sanders et al., 2020;
Yang et al., 2020). Apart from its role in SG assembly, the housekeeping functions of Rin/G3BP
involve binding to RNA and regulating selective protein synthesis during oxidative stress via
mRNA partitioning (Laver et al., 2020; Somasekharan et al., 2020). We used dsRNA-mediated
RNAi to knock down the levels of Rin in S2 cells and independently assessed the effect of this
perturbation on SG granule assembly as well as on stress-induced transcription. Experimental cells treated with dsRNA targeting endogenous Rin mRNA showed reduced levels
of Rin protein compared to mock control cells (treated with dsRNA targeting GFP) (Fig. |
5A). In
mock control cells, arsenite exposure robustly induced Atx2- and Rin- containing SGs (Fig. 5B). In contrast, and as predicted, Rin-RNAi treated cells with reduced Rin mRNA and protein (Fig 5A)
were unable to form SGs (Fig. 5B). To test whether the inability to form SGs affected the
transcriptional response to stress, we used RNA-seq to determine and analyse transcriptomes in
control and Rin RNAi cells exposed to arsenite as described previously (Fig 2A). Transcriptomes
for three control and three Rin RNAi replicates showed high internal correlation coefficients within
each group (between 0.992 and 1.0), demonstrating high similarity among biological replicates
within each condition. However, and remarkably, similar levels of correlation were also seen
across groups: indeed, mock and Rin RNAi transcriptomes were largely indistinguishable
(Supplementary Fig. 4A). This observation suggests that Rin knockdown, which prevents normal
SG formation, has no significant effect on stress-induced transcription. Consistent with this: (a)
transcriptomes of Rin-deficient cells following 3 hours of arsenite exposure matched most closely
with those of control cells after 3 hours of acute stress (Figure 5 C-ii), and (b) transcriptomes of
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available under a
CC-BY-NC-ND 4.0 International license . Rin-deficient cells 3 hours post-stress recovery matched most closely with those of similarly
treated controls (Figure 5 C-iii). Further, volcano plots comparing mock and Rin RNAi transcriptomes showed that the transcript
levels for all genes remained mostly unchanged following Rin knockdown, with the notable
exception of Rin itself, which was reduced almost four-fold compared to the levels in mock RNAi
(Fig. 5C; Supplementary Fig. 4B). The selective effect on Rin also confirmed that the effect of Rin
RNAi was target-specific, with no significant off-target effects. A comparison of the top 100
differentially regulated genes showed no difference among the mock and Rin RNAi cells
(Supplementary Fig. 4C, Supplementary File 5). These observations suggest that oxidative stress-
induced SGs do not have a role in oxidative stress-induced transcription, and they appear to be
independent but parallel pathways. It was notable that neither stress nor Rin knockdown had any significant effect on the expression
of mRNAs encoding known stress-granule or stress-granule-associated RNA-binding proteins
within the time scale of our experiments. Thus, there were no significant changes in the transcript
levels for Atx2, Caprin, Cabeza (Fus), Fmr1 (FMRP), Me31B, Pontin (RuvBL1), Reptin
(RuvBL2), Ref(2)p (p62/SQSTM1), Rox8 (TIA1), TBPH (TDP43) and Lingerer (UBAP2L)
(Supplementary Fig. 4B). We also used O-propargyl-puromycin incorporation assays to examine whether global
translational repression induced by stress was affected under conditions where Rin levels are low,
and SGs are not observed. |
Strikingly, under conditions of reduced levels of Rin where SGs do not
form, global translation is still inhibited by stress (Fig. 5D, 5E). This is consistent with previous
work in mammalian cells, suggesting that although the translation is widely repressed during
stress, only about 5% of mRNA is sequestered within SGs (Khong et al., 2017). Interestingly,
levels of Rin showed an increase during stress in mock cells treated with puromycin which further
points to another layer of complexity (Fig. 5D). bioRxiv preprint
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available under a
CC-BY-NC-ND 4.0 International license . A. C
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Fig. 5. Rin knockdown prevents stress granule assembly without altering stress-induced transcription. A. Western blot analyses using total cell lysates from mock RNAi and Rin RNAi cells under control, stress,
and recovery show drastically reduced Rin protein levels in Rin RNAi cells. Western blot analyses for
tubulin using the same lysates were used as the loading control. Anti-Rin and anti-tubulin antibodies were
used. B. Arsenite does not cause stress-granule induction in Rin/G3BP deficient cells (after Aguilera-
Gomez et al., 2017). Upon stress, both Atx2 and Rin co-localize in granules in mock RNAi cells (i-iii). However, in Rin RNAi cells, no granules are assembled upon stress, and Atx2 is diffusely distributed (i’-
iii’). Scale bars represent 5 μm. Anti-Atx2 (1:500) and anti-Rin (1:500) antibodies were used for
immunofluorescence. C. Volcano plots showing the similarity in transcriptomes across mock RNAi and
Rin RNAi samples with log2FoldChange =1.5 and padj< 0.05. The red dot indicates the levels of Rin in
Rin RNAi samples. D. O-propargyl-puromycin incorporation assays in mock and Rin RNAi cells. Western
analyses using total cell lysates from mock RNAi and Rin RNAi cells under control and stress conditions
were used for puromycin incorporation. |
Anti-puromycin and Anti-Rin antibodies were used at 1:1000 and
1:500 dilutions respectively. A representative blot of four independent experiments is shown. E. Bar graphs
showing the relative intensity of puromycylation in mock RNAi and Rin RNAi cells under control and
stress conditions. DISCUSSION
The transcriptional response to oxidative stress. Given the importance of oxidative-stress for physiology and disease, there have been relatively
few studies of oxidative stress-induced transcription in metazoa (Brown et al., 2014; Zou et al.,
2000). However, extensive work in bacteria, plants, and yeast, as well as some in metazoan animal
species, have provided important insights (Blevins et al., 2019; He et al., 2018; Reichmann et al.,
2018; Wohlbach et al., 2009). Global transcriptional changes that occur during recovery following
stress remain even relatively sparsely studied (Sørensen et al., 2005). First, that different types of
stress can induce overlapping groups of genes, pointing to the principle of cross-tolerance, wherein
proteins induced by and that confer protection to heat stress, for instance, may also be similarly
regulated and perhaps protective during oxidative stress (Chowdhary et al., 2019; Dahl et al., 2015;
Jacobson et al., 2012; Morimoto, 1998). This could, in part, be explained by overlapping cellular
effects of stressors: both heat and oxidative stress alter protein folding, and chaperone systems that
prevent protein aggregation or promote refolding may be required in both conditions. Moreover,
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available under a
CC-BY-NC-ND 4.0 International license . stress-responsive genes could also encode conserved proteins involved in constitutive cellular
maintenance (Kültz, 2003; Rebeaud et al., 2020). Specific suites of genes (and functions) induced by and required under oxidative stress
The induction of oxidative stress by arsenite generates reactive oxygen species (ROS) in the cell,
which regulates many stress-regulators, including heat shock proteins (Ruiz-Ramos et al., 2009). Hsp mRNAs are, in general known to be upregulated during different stress conditions, aging as
well as during development (Brown et al., 2014; Colinet et al., 2010; Colinet and Hoffmann, 2010;
Michaud et al., 1997; Ruiz-Ramos et al., 2009; Vos et al., 2016; Zou et al., 2000). In Drosophila,
Hsps are also induced during recovery from cold stress (Colinet et al., 2010; Štětina et al., 2015),
however, the type of HSPs and the amount of HSPs induced depends on the type of stress (Morano
et al., 2012; Zhao et al., 2015). We find a similar upregulation of Hsp mRNAs during stress
(Supplementary Fig. 3A) as well as during recovery (Fig. 3). Intriguingly, the upregulation of
mRNAs during recovery was via active transcription as seen by metabolic labeling (Fig. |
4B) and
not because of the enhanced stability of mRNAs during recovery. This is a significant finding as
it implies the Hsp coding mRNAs, which are upregulated during stress may have separate
functions than those upregulated during recovery, just like it has been shown for HSP70 in
thermotolerant cells (Tian et al., 2021). Akin to chaperones, GSTs also have a cytoprotective function; for example, they can protect
against oxidative damage to DNA and prevent mutations (Allocati et al., 2018; Veal et al., 2002). As seen for Hsp mRNAs, we find that several GST mRNAs are upregulated both during stress
(Supplementary Fig. 3A) and are actively transcribed during recovery (Figs. 3A, 4B). In yeast, it
is known that GSTs are required for cellular resistance to oxidative stress (Veal et al., 2002). There
is also the interesting possibility of GSTs being regulators of stress kinases and thus, modulating
signal transduction (Adler et al., 1999; Laborde, 2010). Upregulation of transcripts encoding for
proteins involved in such cytoprotective functions points to the fact that to attain homeostasis
during recovery, a cell needs to prevent protein aggregation (by the action of sHSPs), fold/refold,
misfolded proteins (by a harmonious action of HSP70s and HSP40s) and get rid of free radicals
generated due to oxidative stress (by synthesizing more GSTs). bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Similar to the coding genes, aberrant upregulation of several ncRNAs is observed during stress
and disease conditions (Brown et al., 2014; Connerty et al., 2020; Torrent et al., 2018). We find
that several ncRNAs are upregulated during stress and recovery, prominent ones being Hsr omega
and RNaseMRP:RNA (Fig. 4). During stress, rRNA processing might be affected, and
upregulation of RNaseMRP RNA might be a counteractive response during stress. ncRNAs can
likely regulate the stability of mRNAs as they bind to several different proteins and modulate their
activity by sequestering them away from their sites of action (Lakhotia, 2012). LncRNAs can also
act as a sponge for microRNAs, preventing the cleavage of mRNAs whose translation is required
during stress and recovery, as well as regulate translation because of complementarity (Lee and
Rio, 2015). Although mature Rpl13a mRNA levels are not affected, oxidative stress reportedly
leads to upregulation of intronic C/D box snoRNAs present in the Rpl13a gene that is required for
propagation of oxidative stress whilst their loss affected mitochondrial metabolism and lowered
ROS (Lee et al., 2016; Ly et al., 2017; Michel et al., 2011). Akin to the above observation, we also
found several snoRNA transcripts significantly reduced during stress and recovery. |
These studies
imply that the differentially regulated snoRNAs might be crucial for oxidative stress response in
Drosophila cells as well. Several other snoRNAs are also involved in alternative splicing of
mRNAs (Bratkovič et al., 2020; Falaleeva et al., 2016; Kishore et al., 2010; Kishore and Stamm,
2006). It is obvious to speculate that the levels of a set of snoRNAs might be regulated via their
splicing while another set of snoRNAs might be involved in promoting alternative splicing of
mRNAs. General and specific features of the oxidative stress transcriptome in flies
In the current study, we provide an overview of the global transcriptional changes in Drosophila
S2 cells upon exposure to sodium arsenite stress and subsequent recovery. The results reveal a
general increase in the transcription of Hsp genes during both stress and recovery, accompanied
by increased transcription of genes coding for detoxifying enzymes and several ncRNAs. We also
show that knockdown of Rin prevents the assembly of SGs during stress and that oxidative stress-
induced transcriptional alterations are a completely independent but a parallel event with respect
to SG assembly. The number of transcripts that are differentially regulated during recovery is
almost three times more than that in stress and belong to several different classes of proteins as
compared to the stress, where the transcripts mainly belong to genes coding for proteins involved
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available under a
CC-BY-NC-ND 4.0 International license . in stress response or proteolysis. The upregulation of several transcripts involved in the
development and metabolic processes during recovery similarly underlines the efforts being made
by the cell to restore homeostasis. Significance of analysis of acute stress and recovery transcriptomes and potential functions for
specific classes of genes identified
The transcriptional upregulation of various types of chaperones (Fig. 3A, Supplementary Fig. 3A)
suggests that apart from their protein folding role, these proteins are also crucial for preventing
promiscuous interactions among aggregation-prone proteins by promoting the formation of SGs
(Gitter et al., 2013; Gong and Golic, 2006; Štětina et al., 2015). The chaperones could modulate
SG formation and disassembly (Alberti et al., 2017; Ganassi et al., 2016; Mateju et al., 2017). HSP70 has also been found to be present in the cores of ring-shaped TDP43 annuli in neurons (Yu
et al., 2021). HSP27 also prevents the entrance of FUS into SGs, suggesting that HSP27 may be
necessary for the stabilization of the dynamic phase of SGs (Liu et al., 2020). HSP67BC, another
small HSP, has been implicated in preventing toxic protein aggregates in Drosophila in a HSP70
independent manner (Vos et al., 2016). |
Similarly, the yeast HSP40s, Ydj1, and Sis1 are important
for the disassembly of SGs (Walters et al., 2015). Upregulation of specific chaperone mRNAs
during recovery (Fig. 3A) and the concomitant dissolution of arsenite-induced SGs can be likened
to the clearance of protein aggregates achieved by overexpression of specific HSPs (Chan et al.,
2000; Huen and Chan, 2005; Vendredy et al., 2020; Vos et al., 2016; Warrick et al., 1999; Webster
et al., 2019). In fact, pharmacological activation of HSP70 has been shown to ameliorate
neurotoxicity caused by aiding the clearance of polyglutamine aggregates (Wang et al., 2013). Upregulation of transcripts of both ATP-dependent and -independent HSP mRNAs (Fig. 4B, C)
might implicate a cellular strategy wherein a cell can employ these proteins in clearing aggregates
distinctly and more efficiently (Fare and Shorter, 2021); some of these genes may also be involved
in long-term stress adaptation (Bijlsma and Loeschcke, 2005; De Bruijn, 2016). SG assembly contributes minimally to the transcription of oxidative stress-induced genes. If SG formation is essential for the cellular stress response, blocking its formation should affect
the cellular stress response (Lee et al., 2020). Apart from their role in blocking cellular translation,
SGs are also known to stimulate transcription of interferons in response to viral infections
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available under a
CC-BY-NC-ND 4.0 International license . suggesting that SGs may modulate transcription indirectly (McCormick and Khaperskyy, 2017;
Tsai and Lloyd, 2014). We also find that lowering the levels of Rin, thereby preventing SG
formation, had no effect on the inhibition of global translation in S2 cells during stress (Fig. 5D). In yeast cells that were deficient in forming SG in response to heat stress, enormously high levels
of mRNAs coding for the HSPs (HSP12 and HSP104) and significantly lower levels of genes
involved in rRNA processing, part of the RiBi regulon (PWP1, UTP13, and DIP2) were found
(Yang et al., 2014). The authors opined that this increase or decrease in specific mRNAs levels
could be due to alteration in transcription kinetics or altered mRNA stability. In contrast, we find
that lowering Rin levels hence inhibiting the formation of SGs, does not affect transcription under
stress (Fig. 5). This is surprising because Rin has several housekeeping functions apart from being
essential for SG condensation, but it may also not be required in specific cells (Baumgartner et al.,
2013; Buddika et al., 2020; Guillén-Boixet et al., 2020; Kedersha et al., 2016; Laver et al., 2020;
Pazman et al., 2000; Sanders et al., 2020; Yang et al., 2020). Strikingly, comparative transcriptome
analysis between mock and Rin RNAi cells revealed no change in the type of differentially
regulated transcripts nor any significant alterations of fold changes in expression of individual
mRNAs during stress and recovery (Fig. |
5). The differentially regulated transcripts in stress and
recovery are also excluded from SGs (Fig. 4D), which also implies that the arsenite-induced SG
assembly and transcriptional alterations are parallel but independent events. There might be several
underlying layers of cellular intricacies that might link these two events. Transcription of stress-responsive genes serves a crucial role in implementing a rapid and robust
stress response (Vihervaara et al., 2018, 2017). Upon stress removal, the SGs dissolve, and cap-
dependent translation begins as suggested by the loss of eIF2a phosphorylation; however, if these
recovery responses are attributed to the reversal of transcriptional changes that had occurred during
stress is not known (Fig. 6). Further, if transcriptional dysregulation during recovery plays any role
in SG dissolution remains unknown. Ultimately, comparing stress and recovery responses as a
continuum but not in isolation is crucial in dissecting these two phenomena with exact opposite
consequences to cellular homeostasis. We propose that alterations in oxidative transcriptional response are a cellular response against
long-term chronic stress. At the same time, the assembly of SGs is an immediate effect to counter
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . stress (Fig. 6). However, it remains to be elucidated what the involvement is of the genes that are
differentially regulated during recovery upon the dissolution of SGs? Since Rin RNAi cells do not
form visible SGs, it raises several important questions, (i) although mRNA is devoid of ribosomes,
what is their fate? (ii) what is the status of the global proteome when SG assembly has been
prevented? Further studies need to be undertaken to address these questions. Control
Stress
Recovery
Modulation of translation
eIF2A
PERK PKR GCN2 HRI
P
eIF2A
GADD34
eIF2A
SG Dynamics
Inhibition of SG formation
Transcriptional alterations
P
Proteostatic TF’s
Cryoprotective genes
Hsp23, Hsp26, Hsp27, Hsp70Ba, GSTD5, GSTE7, GSTE8, GSTS1
Fig. 6: A model depicting the various cellular changes taking place during stress and subsequent recovery. eIF2α gets phosphorylated at serine 51 during stress by the action of any of the four kinases, leading to a
block in cap-dependent translation. Upon the removal of stress, phosphorylation is lost, and cap-dependent
translation is restored. This is concomitant with assembly and clearance of SGs respectively during stress
and recovery, as well as with increased transcription of cytoprotective genes such as HSPs and GSTs
mediated by proteostatic transcription factors (HSF1, FOXO, NRF2, etc). However, when the formation of
SG is prevented by lowering down levels of Rin, there is no change in the transcription of the cytoprotective
genes. |
ACKNOWLEDGMENTS
We thank Prof. K. VijayRaghavan for his valuable feedback and suggestions during the course of
this work. We also thank the members of the Ramaswami, and Bakthavachalu labs, as well as Prof.
Roy Parker (HHMI and University of Colorado Boulder) for useful discussions and/or comments
on the manuscript. We thank Prof. Elizabeth Gavis (Princeton University, USA) and Dr. Nicholas
Sokol (Indiana University, USA) for sharing Rasputin and Rox8 antibodies with us. We
acknowledge Drosophila Genomics Resource Centre (supported by NIH grant 2P40OC010949)
for Drosophila S2 cells. The work was supported by a Science Foundation Ireland (SFI)
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Investigator grant to MR, and an Irish Council Postgraduate Fellowship to GT. The work is partly
supported by the DBT/Wellcome Trust India Alliance Fellowship (IA/I/19/1/504286) awarded to
BB, who is also a recipient of the SERB-STAR award (STR/2020/000056). We acknowledge the
support from INSA Young Scientist Project (INSA/SP/YSP/143/2017) (AS), from SERB to MR
from a collaborative VAJRA award to Dr. Raghu Padinjat, and a CSIR fellowship (DJ). We thank
Dr. Awadhesh Pandit from the NCBS NGS facility for help with RNA-seq. bioRxiv preprint
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available under a
CC-BY-NC-ND 4.0 International license . Methods
Cell culture and treatments
Drosophila S2R+ cells were obtained from DGRC and cultured in the semi-adhering state in
Schneider’s medium (S2 medium) with 10% FBS, penicillin, and streptomycin at 250C. Cells were
maintained at 50% confluency in fresh S2 media for atleast 24h before being used for stress
experiments. To induce stress, cells were subjected to 0.5mM sodium arsenite in S2 media for 3 hours at room
temperature on a rocking shaker. After 3 hours, arsenite containing S2 media was removed by
centrifugation at 2000 rpm for 5’, and the cells were washed three times with fresh media and kept
for recovery in fresh complete S2 media. Recovering cells were kept on the rocking shaker for an
additional 3h at room temperature. For labeling with 5-EU, 200um EU was added as indicated in Fig 4. Briefly, for labeling transcripts
under control and stress conditions, 5-EU either in a normal medium or in a medium containing
0.5mM sodium arsenite at the start of the 3h stress regime. Cells were then washed and harvested
for RNA isolation. For labeling transcripts during recovery, cells were initially stressed with
0.5mM sodium arsenite for 3h and then were washed three times with fresh S2 media. |
5-EU was
added at the start of the 3h recovery period, after which cells were harvested for RNA isolation. RNA isolation and RNA Seq
After stress and recovery, RNA was isolated using TRIzol reagent (Invitrogen, USA) as per the
manufacturer’s protocol. RNA concentration was measured using a Qubit RNA assay kit in Qubit
2.0 Fluorometer (Life Technologies, USA). RNA integrity was confirmed using the RNA Nano
6000 assay kit of the Bioanalyzer 2100 system (Agilent Technologies, USA). Poly(A) enriched
mRNA library was made using TruSeq RNA Library Preparation Kit V2 (RS-122-2001) and
sequenced using HiSeq SR Rapid Cluster Kit v2 (GD-402-4002) to generate 1X50 single-end reads
on Illumina HiSeq2500 sequencing platform. In silico analysis
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available under a
CC-BY-NC-ND 4.0 International license . For transcriptome analysis, all sequencing reads obtained post adaptor removal had a mean quality
score (Q-Score) >= 37, so no trimming was required. All the further downstream analyses were
performed on this high-quality data. For read mapping, the reference genome and gene model
annotation files of D. melanogaster, version dm6 were downloaded from the UCSC genome
browser. Single-end processed reads were aligned to the reference genome using STAR v2.5.3
with default parameters. HTSeq-count v0.11.2 and the “-s reverse” option were used to count the
read numbers mapped to each gene before differential gene expression analysis. Differential gene
expression among samples was performed using the DESeq2 package. The data is available with
the assigned GEO accession # GSE178464. For Gene Ontology analysis of differentially expressed
genes under stress and recovery, enriched GO terms with <0.05 p-value were identified using
BINGO plug-in at Cytoscape (v.3.8.0) and the enriched GO terms were shown in heatmap via
MeV (v.4.9.0). For granule counting, Cellprofiler was used. On an average, 140 cells per field
were acquired. The number of granules observed in each cell were tabulated for control, stress and
recovered cells. Outliers were determined by calculating the number of granules that were 1.5
standard deviations above and below the mean and were thus excluded from further analysis. The
values were plotted as average number of granules observed as well as the numbers of granules
per cell. On applying Mann-Whitney statistics, it was observed that there was a significant
difference in the number of granules between stressed and recovered cells (p < 0.05). Immunostaining and fluorescence
Immunostaining was performed as described earlier (Bakthavachalu, Huelsmeier et al., 2018). Briefly, S2R+ cells were grown in T25 flasks to almost 70-80% confluency. Stress and recovery
experiments were performed as described above. |
Cells were fixed with 4% paraformaldehyde for
10 min, followed by permeabilization with 0.05% Triton-X-100 for 10 min. This was followed by
blocking with 1% BSA for 30 min. The cells were then incubated with antibodies against Atx2
(1:500), Rox8 (1:1000) and Rin (1:500), followed by probing with 1:1000 dilution of Alexa Fluor
488, 568 and 647 (Abcam) secondary antibodies respectively. Confocal imaging was done using
the PALPON 60x/1.42 oil objective of the Olympus FV3000 microscope. Images were processed
using ImageJ software. bioRxiv preprint
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available under a
CC-BY-NC-ND 4.0 International license . Double-stranded (ds) RNA generation
Mock and Rin RNAi were performed using dsRNA produced by in vitro transcription (IVT). For
mock, we utilized GFP open reading frame as the target site. RNAi target sites were chosen using
the SnapDragon tool (https://fgr.hms.harvard.edu/snapdragon) (Hu et al., 2017). PCR generated
DNA templates containing the T7 promoter sequence at both ends were used as IVT template for
dsRNA synthesis using Megascript T7 High Yield Transcription kit (Invitrogen). The primer
details are provided in Supplementary File 6.
dsRNA transfection into cells for RNAi experiments
Wild type Drosophila S2 cells were depleted for Rin mRNA by double-stranded (ds) RNAi. Briefly, 0.5 million cells were transfected with 5μg of dsRNA. After 48h of the first round of
transfections, cells were again transfected with 5μg of dsRNA. After 96 hours of the first
transfection, cells were analyzed for the knockdown of Rin, and RNA was isolated using TRIzol
reagent (Invitrogen) as per the manufacturer’s protocol. Illumina library was prepared from
Poly(A) enriched mRNA using TruSeq RNA Library Preparation Kit V2 (RS-122-2001) and
sequenced using HiSeq SR Rapid Cluster Kit v2 (GD-402-4002) to generate 1X50 single-end
reads. For puromycylation assays, after 93 hours of mock and Rin dsRNA transfections, stress was
induced as previously described above. Puromycin was added during the final 15 minutes at a final
concentration of 4μg /mL. Cells were then immediately harvested and analysed for the knockdown
of Rin, and for puromycin incorporation. Protein isolation and Western analysis
Mock RNAi and Rin RNAi cells were maintained, stressed, and recovered as mentioned above. Total protein isolation was performed as described earlier (Sudhakaran et al., 2014). Briefly, 0.2
million cells were pelleted and resuspended in 50ul lysis buffer [25mM Tris HCl (pH7.5), 150mM
NaCl, 10% (v/v) glycerol, 1mM EDTA, 1mM DTT, 0.5% Nonidet P-40 and complete protease
inhibitor tablets from Roche) and incubated at 40C for 30 min with intermittent vortexing. The
lysate was then spun at 40C at 13000 rpm for 30 min. The supernatant was collected, and protein
was quantified using Nanodrop. |
For puromycylation, cells were lysed and normalised for protein
bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . concentration using the Bio-Rad Protein Assay Kit (Bio-Rad Laboratories, Inc. # 5000001) and a
spectrophotometer. Westerns blots were performed using rabbit anti-Rin (1:1000), rabbit anti-
phospho-eIF2α (1:1000, 9721L CST), rabbit anti-eIF2α (1:1000, SAB4500729-100UG), mouse
anti-puromycin (1:2000, MABE343 Sigma-Aldrich) and mouse anti-tubulin (1:2000, E7c DSHB). Goat anti-Rabbit HRP (sc-2004) and goat anti-mouse HRP (sc-2005) HRP-conjugated secondary
antibodies were used at 1:10000 dilution. bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . A. B. Control
Stress
Recovery
1
3
6
12
1
3
6
12
1
3
6
12
eIF2 alpha PSer51
Total eIF2 alpha
Supplementary Fig. 1: A. Control stressed and recovered cells were stained with Hoechst33342 (dilution 1:1000) for staining the nucleus and probed for Atx2 and Rox8 which have been shown to colocalize in granules upon stress (Bakthavachalu et al., 2018; Farny et al., 2009). Images were acquired on Olympus FV3000 6 lasers using a PLAPON60XO 1.42 NA objective at 1024 x 1024 resolution. Two fields of cells were acquired for each condition. Z projections of slices of cells acquired with a 1 μm step size were used for granule quantification. The number of cells and the granules present in the cells were quantified using CellProfiler. The punctae formed by Rox8 were annotated as granules and Hoechst33342 staining was used
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . for identifying cells. The cytoplasmic boundary was defined such that punctae observed beyond the plasma membrane were considered as background. Clumped objects were distinguished based on intensity and thresholding for granule quantification was maintained in the range of 0.2 to 1.0. |
The scale bars represent 10μ. B. Levels of total and phosphorylated eIF2α under control, stress and recovery. Total cell lysate was taken at 1h, 3h, 6h and 12h from control, stress and recovery cells and analyzed for serin 51 phosphorylation of eIF2α (upper panel). Lower panel shows the levels of total eIF2α. bioRxiv preprint
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available under a
CC-BY-NC-ND 4.0 International license . A.
e c n a i r a v % 2 1
5
Control
Recovery
:
2 C P
0
Stress
−20
−10
0
10
PC1: 87% variance
Supplementary Fig. 2: Principal component analysis (PCA) of the data from control, stress and recovery transcriptomes. PCA shows that within the replicate transcriptomes of control, stress and recovery, there is no variation. However, the control, stress and recovery transcriptomes themselves vary a lot among each other. bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . A. Control
Stress
B. Control
Stress
Ion channel
Protein modification
Transporters
Glutathione metabolism
cytochrome/iron binding
Translation
ncRNA
Protein homeostasis
uncharacterized
Receptor
Structural
DNA binding
Metabolism
Regularized logarithm
Porin2 CG32454 Rgk1 SP1029 Zip89B Vha100−4 GstD6 GstD10 GstD7 GstD4 Cyp6a19 Cyp4e1 Thor lncRNA:CR42767 lncRNA:CR46006 lncRNA:CR43857 lncRNA:CR43626 lncRNA:alphagamma−element:CR32865 lncRNA:Hsromega RNaseMRP:RNA lncRNA:CR31044 snRNA:U2:34ABa lncRNA:CR44206 lncRNA:CR45380 snRNA:7SK asRNA:CR43465 scaRNA:MeU5−C46 lncRNA:CR43432 lncRNA:CR44135 scaRNA:PsiU2−35.45 lncRNA:CR43651 Hsp70Ba stv Hsp27 rho Hsp26 Hsp70Bc Hsp68 Hsp70Bbb amon CG4757 CG12723 Ppi1 CG6785 CG43647 CG9279 Rcd2 CG32040 CG34330 CG7509 CG31029 r−cup CG14961 CG14309 CG43646 CG13252 CG10005 CG31676 Gr63a spdo Toll−7 bbg Galphaf comm2 a sog IFT54 corn Culd Cp18 dmrt93B dve CG9747 CG33337 CG15097 Fatp3 CG15385 CG18808 CG4267 CG11034 CG10182 bmm bb8 Acox57D−d AOX2 FASN2 Nrt fng Faa CG10621 CG6770 CG12224 Gli CG9008 CG6142 CG5321 CG9447 CG18585 CG10051 CG7025
C.
80000
s t n u o c d e a z i l a m r o n
60000
40000
20000
0
R p L 10 A b
D.
Control-1
Control-2
Control-3
Stress-1
Stress-2
Stress-3
Recovery-1
Recovery-2
Recovery-3
A N R c n
lncRNA:CR43837 lncRNA:CR45039 lncRNA:CR45566 lncRNA:CR42491 lncRNA:CR45981
r e h o
t
ninaC mir−9382 Tmc CG42564 sisRNA:CR46357 CG44385 Ir62a drm CG3323 Prx2540−1 CG11825 Prx2540−2 Oseg2 CG6000 CG4631 asRNA:CR45257 CG5078 CG42654 CG12896 CG31697
A N R o n s
snoRNA:Psi28S−1192d snoRNA:Me28S−G3113b snoRNA:Me28S−A2634c snoRNA:Me28S−G3113a snoRNA:Psi28S−2996 snoRNA:Or−CD2 snoRNA:Psi18S−920 snoRNA:Psi28S−2562 snoRNA:Psi28S−1175b snoRNA:Me18S−C1831 snoRNA:Psi18S−531 snoRNA:Me28S−A2113 snoRNA:Psi18S−640e snoRNA:Psi28S−1175c snoRNA:Me28S−A1322 snoRNA:Psi28S−2648 snoRNA:Me18S−C419 snoRNA:Me28S−C3351 snoRNA:Me28S−A771 snoRNA:Psi28S−2179 snoRNA:SC35−a snoRNA:Or−aca1 snoRNA:Me28S−G2017 snoRNA:Psi28S−3186
Regularized logarithm
−2
−1
0
1
2
control
stress
recovery
R p L 22
R p L 23 A
R p L 27
R p L 30
R p L 36 A
R p L 5
R p S 11
R p S 16
R p S 4
R p S 5a
RpL30
RpL5
5
5
snoRNA:Psi28S-2996
snoRNA:Me28S-A2113
Control-1
0
0
Control-2
Control-3
Stress-1
Stress-2
Stress-3
Recovery-1
Recovery-2
Recovery-3
−2
−1
0
1
2
bioRxiv preprint
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The copyright holder for this preprint
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . Supplemental Fig. 3: Oxidative stress results in widespread changes in transcription. A. Heat map for 100
genes most robustly upregulated following 3-hours of acute stress. Genes are grouped based on predicted
cellular functions. The fold induction is indicated in the colour scale below. B. Heat map shows a smaller
group of mRNAs for which reads are substantially decreased after acute stress. The colour scale bar
indicated fold changes represented. C. Normalized counts of the parent ribosomal protein genes in control,
stress and recovery showing no significant change in the levels. D. Bed graphs showing the reads
corresponding to snoRNA:Me28S-A2113 (i) and snoRNA:Psi28S-2996 (ii) under control, stress, and
recovery. Reads corresponding to the parent genes are also depicted. bioRxiv preprint
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made
available under a
CC-BY-NC-ND 4.0 International license . A.
C.
Mock RNAi
Rin RNAi
Mock RNAi Control-1
control
stress
recovery
control
stress
recovery
B.
s t n u o c d e z i l a m r o n
M o c k R N A
M o c k R N A
C o n t r o l - 1
C o n t r o l - 3
0 . 9 9 2
10000
8000
6000
4000
2000
0
Atx2
R n R N A
i
C o n t r o l - 2
R n R N A
i
C o n t r o l - 3
C a pr
M o c k R N A
C o n t r o l - 2
R n R N A
i
C o n t r o l - 1
M o c k R N A
S t r e s s - 1
M o c k R N A
S t r e s s - 3
R n R N A
i
S t r e s s - 2
R n R N A
i
S t r e s s - 1
R n R N A
i
S t r e s s - 3
R n R N A
i
R e c o v e r y - 1
0 . 9 9 4
0 . 9 9 6
Mock_RNAi
Rin_RNAi
F m r1
R o x8
T B P H
U b q n
M o c k R N A
S t r e s s - 2
R n R N A
i
R n R N A
i
R e c o v e r y - 2
R e c o v e r y - 3
0 . 9 9 8
caz
M o c k R N A
R e c o v e r y - 1
lig
M o c k R N A
M o c k R N A
R e c o v e r y - 2
R e c o v e r y - 3
m e31 B
Mock RNAi Control-3
Rin RNAi Control-2
Rin RNAi Control-3
Mock RNAi Control-2
Rin RNAi Control-1
Mock RNAi Stress-1
Mock RNAi Stress-3
Rin RNAi Stress-2
Rin RNAi Stress-1
Rin RNAi Stress-3
Rin RNAi Recovery-1
Mock RNAi Stress-2
Rin RNAi Recovery-2
Rin RNAi Recovery-3
Mock RNAi Recovery-1
Mock RNAi Recovery-2
Mock RNAi Recovery-3
1
ref(2)P p o nt
re pt
rin
CG6785 CG6770 CG42240 CG8177 CG44251 CG5707 CG6330 CG46339 Hsp23 GstS1 Gli GstE7 GstE8 GstD5 CG3036 CG2065 CG17834 CG1673 CG34330 CG31674 CG17646 CG18446 Eip71CD Fer2LCH Gadd45 E(spl)m3−HLH E(spl)mbeta−HLH DnaJ−1 Dgk Galphaf Dgp−1 Culd GlcAT−S Fatp3 Ccz1 Piezo Hsp27 Hsp70Bc Hsp26 Mrp4 Mocs1 Rcd2 ImpL2 Reg−5 IP3K1 RNaseMRP:RNA Hsp70Bbb Hsp70Ba Hsp68 rpr snRNA:U2:34ABa stg w stv mfas scyl rho lncRNA:CR31044 glec spin l(1)G0469 pirk lncRNA:Hsromega r−cup lncRNA:alphagamma−element:CR32865 lncRNA:CR43626 fok rdog lncRNA:CR45380 peb bmm edl dnr1 bab2 e(y)2b SP1029 Rev1 Sirup Rgk1 Thor Tep2 Ugt302C1 Tret1−1 Trpm T48 Toll−7 Uhg5 a CG11951 Atg18b CG11700 CG14961 CG15385 CG13893 CG12224 CG13252 CG15097 CG12723 asRNA:CR43481 aay
Regularized logarithm
−2
−1
0
1
2
Supplemental Fig. |
4: A. Correlation plot depicting the similarities and differences among different
transcriptomes. B. Normalized counts of transcripts coding for different SG constituent proteins in mock
RNAi and Rin RNAi cells. C. Heat maps depicting transcriptional alterations in the top100 genes mock and
Rin RNAi cells under control, stress, and recovery with a cutoff of log2 fold. |
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available under a
CC-BY-NC 4.0 International license . Allosteric modulation of the adenosine A2A receptor by cholesterol
Shuya Kate Huang1,2, Omar Almurad1,2, Reizel J. Pejana1,2, Zachary A. Morrison1, Aditya
Pandey1,2, Louis-Philippe Picard1,2, Mark Nitz1, Adnan Sljoka4, and R. Scott Prosser1,2,3 *
1 Department of Chemistry, University of Toronto, 80 St. George Street, Toronto, Ontario M5S
3H6, Canada. 2 Department of Chemical and Physical Sciences, University of Toronto Mississauga, 3359
Mississauga Road North, Mississauga, Ontario L5L 1C6, Canada. 3 Department of Biochemistry, University of Toronto, 1 King’s College Circle, Toronto, Ontario
M5S 1A8, Canada. 4 RIKEN Center for Advanced Intelligence Project, RIKEN, 1-4-1 Nihombashi, Chuo-ku,
Tokyo, 103-0027 Japan. Correspondence to: [email protected]
Abstract
Cholesterol is a major component of the cell membrane and commonly regulates membrane
protein function. Here, we investigate how cholesterol modulates the conformational equilibria
and signaling of the adenosine A2A receptor (A2AR) in reconstituted phospholipid bilayers. GTP
hydrolysis assays show that cholesterol is a weak positive allosteric modulator of A2AR, as seen
through enhanced basal signaling and a small decrease in agonist EC50. Fluorine nuclear magnetic
resonance (19F NMR) spectroscopy suggests that this enhancement arises from an increase in the
receptor’s active state populations and stronger G protein coupling. 19F NMR of fluorinated
cholesterol analogs reveals transient and non-specific interactions with A2AR, indicating a lack of
high-affinity binding sites or direct allosteric modulation. This is confirmed by computational
analysis which suggests that cholesterol contacts confer a weak and possibly negative allosteric
effect. The combined results suggest that the observed cholesterol allostery in A2AR is likely a
result of indirect membrane effects through cholesterol-mediated changes in membrane properties,
as shown by membrane fluidity measurements and high-pressure NMR. 1
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available under a
CC-BY-NC 4.0 International license . Introduction
In mammalian cell membranes, cholesterol accounts for ~5-45% of the total lipid content
across different cell types and subcellular components (Casares et al., 2019; Ingólfsson et al.,
2017). It is a critical metabolic precursor to steroid hormones, bile salts, and vitamin D, while
numerous cardiovascular and nervous system disorders are attributed to abnormalities in
cholesterol metabolism (Arsenault et al., 2009; Martín et al., 2014). |
The rigid planar structure of
cholesterol promotes ordering of bilayer lipids, thus modulating membrane fluidity and thickness. Cholesterol also drives the formation of raft-like microdomains and commonly interacts with
membrane proteins as a ligand or allosteric modulator (Hulce et al., 2013). Here, we investigate how cholesterol influences the conformational equilibria and
signaling of a well-studied integral membrane protein, the adenosine A2A receptor (A2AR), in
reconstituted phospholipid/cholesterol nanodiscs. Specifically, we seek to understand if the effects
on A2AR function are a consequence of direct allosteric interplay between cholesterol and the
receptor, or if the observed effects result primarily from cholesterol-driven changes in viscoelastic
properties and thickness of the lipid bilayer. A2AR is a member of the rhodopsin family of G protein-coupled receptors (GPCRs). The
GPCR superfamily of 7-transmembrane receptors includes well over 800 species and are targeted
by over one-third of currently approved pharmaceuticals (Hauser et al., 2017). A2AR activates the
stimulatory heterotrimeric G protein (Gsαβγ) and is a target for the treatment of inflammation,
cancer, diabetes, and Parkinson’s disease (Effendi et al., 2020; Guerrero, 2018; Ruiz et al., 2014;
Yu et al., 2020; Zheng et al., 2019). Several GPCRs have been shown to interact with cholesterol,
including the serotonin 5-HT1A receptor, the β2-adrenergic receptor, the oxytocin receptor, the
CCR5 and CXCR4 chemokine receptors, the CB1 cannabinoid receptor, and A2AR (Gimpl, 2016;
Jafurulla et al., 2019; Kiriakidi et al., 2019). Presently, 38 out of 57 published structures of A2AR
contain co-crystallized cholesterol (Fig. 1). In detergent preparations of A2AR, the soluble
cholesterol analog, cholesteryl hemisuccinate (CHS), is important for receptor stability and ligand
binding (O’Malley et al., 2011a, 2007). Apart from those found in crystal structures, cholesterol
interaction sites within A2AR have also been proposed in computational studies. These include the
widely conserved cholesterol consensus motif (CCM) in GPCRs, various hydrophobic patches
around A2AR, and regions of the receptor interior (Genheden et al., 2017; Guixà-González et al.,
2017; Lee et al., 2013; Lee and Lyman, 2012; Lovera et al., 2019; McGraw et al., 2019; Rouviere
2
5
10
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;
this version posted September 14, 2021.
available under a
CC-BY-NC 4.0 International license . et al., 2017; Sejdiu and Tieleman, 2020; Song et al., 2019). The CRAC (cholesterol
recognition/interaction amino acid consensus) motif, another sequence commonly found in
membrane proteins that bind cholesterol, is also present in A2AR (Fig. 1B) (Li and Papadopoulos,
1998). Additionally, cell-based assays have shown that A2AR-dependent cyclic adenosine
monophosphate (cAMP) production is positively correlated with membrane cholesterol
(Charalambous et al., 2008; McGraw et al., 2019). |
Fig. 1. A2AR crystal structures reveal many cholesterol interaction sites. (A) Overlay of 38
currently published A2AR crystal structures containing co-crystallized cholesterol (extracellular
view, with cholesterols shown as orange sticks). For simplicity, extracellular loops and fusion
proteins are removed and only one receptor structure is shown (PDB: 4EIY). (B) Side views of
(A) highlighting the CCM (blue), the CRAC motifs (green), and V229C 19F labeling site (violet). 3
5
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;
this version posted September 14, 2021.
available under a
CC-BY-NC 4.0 International license . Despite the prevalence of cholesterol or its analogues in many crystal structures, there is
little consensus on the role that membrane cholesterol plays in A2AR function. While some studies
found that ligand binding was unaffected by cholesterol depletion (Charalambous et al., 2008;
McGraw et al., 2019), others have observed the opposite (Guixà-González et al., 2017; O’Malley
et al., 2011a, 2011b). One study in particular suggested that cholesterol may laterally diffuse in the
membrane and enter the receptor interior at the orthosteric site (Guixà-González et al., 2017). Additionally, whereas A2AR is found in both non-raft and raft-like membranes, its colocalization
and modulatory effects on other cellular binding partners, including tyrosine receptor kinase B,
Ca2+-activated K+ (IK1) channel, and the stimulatory G protein, have been reported to depend on
cholesterol-rich microdomains (Charalambous et al., 2008; Lam et al., 2009; Mojsilovic-Petrovic
et al., 2006). One possible source of discrepancy between studies is the use of different cell lines. For instance, Guixà-González et al. observed an increased binding by A2AR inverse agonist
[3H]ZM241385 upon cholesterol depletion in C6 glioma cells. This effect was absent in a study by
McGraw et al., who employed HEK293 cells. Cholesterol extraction or enrichment from cells
exhibiting different membrane compositions and signaling patterns may trigger variable cellular
response and complicates the comparison of results from different cell lines. The in vitro studies,
on the other hand, relied on measuring ligand affinity in detergent micelles while titrating water-
soluble cholesterol analogs. Although the composition of detergent preparations can be carefully
controlled, the micellar environment is quite different from a lipid bilayer from the perspective of
both receptor and cholesterol. To mitigate the many complexities encountered in live cells or the inherent biases
associated with detergent micelles, we employed reconstituted discoidal high density lipoprotein
particles (rHDLs, also known as nanodiscs) to investigate the role of cholesterol in A2AR
conformation and signaling. |
In this case, both the size and composition of these phospholipid
bilayer model systems can be controlled. Through fluorine nuclear magnetic resonance
spectroscopy (19F NMR) and in vitro assays, we find that cholesterol is a weak positive allosteric
modulator of A2AR. This can be attributed to a subtle rise in population of the receptor’s active
state conformers and a stronger coupling to the G protein. Interactions between A2AR and
fluorinated cholesterol analogs appear to be short-lived and non-specific, indicating a lack of high-
affinity binding sites or direct allosteric modulation. Rather, the observed allostery is likely a result
of indirect membrane effects through cholesterol-mediated changes in bilayer fluidity and
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;
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available under a
CC-BY-NC 4.0 International license . thickness, which can be recapitulated (without the use of cholesterol) by the application of
hydrostatic pressure. Results
Cholesterol is a weak positive allosteric modulator of A2AR
We sought to explore receptor-cholesterol allostery in a native lipid bilayer environment,
free from the complexities associated with other cellular response to membrane alteration in live
cells. To this end, we reconstituted A2AR (residues 2-317 with valine 229 mutated to cysteine for
19F-labelling) in nanodiscs containing a 3:2 ratio of 1-palmitoyl-2-oleoyl-sn-glycero-3-
phosphocholine
(POPC)
and 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1'-rac-glycerol)
(POPG), supplemented with different amounts of cholesterol. In our hands, cosolubilization of
cholesterol with phospholipids prior to reconstitution (Midtgaard et al., 2015) resulted in
polydisperse particles and low cholesterol incorporation. We therefore adapted a procedure
commonly used in cells and liposomes, to deliver cholesterol via methyl-β-cyclodextrin (MβCD)
to preformed nanodiscs (Zidovetzki and Levitan, 2007). This allowed us to incorporate up to ~15
mol% cholesterol into A2AR-embedded nanodiscs without affecting their size distribution (Fig. S1). To examine the effects of cholesterol on receptor-mediated G protein activation, we
measured the GTPase activity of purified G proteins (Gsαshortβ1γ2, henceforth referred to as Gαβγ)
in the presence of A2AR-nanodiscs containing 0%, 3%, 8%, 11% and 13% cholesterol. As shown
in Fig. 2A, similar agonist dose-response profiles were obtained across different cholesterol
concentrations. GTP hydrolysis (cumulative over 90 min) was higher in the presence of A2AR
relative to G protein alone and was amplified by the agonist 5'-N-ethylcarboxamidoadenosine
(NECA) in a dose-dependent manner. Upon careful inspection, a small yet notable decrease in
agonist EC50 values can be observed as a function of cholesterol. |
There is also a slight enhancement
in receptor basal activity at high cholesterol concentrations (Fig. 2B-C). Thus, functionally
cholesterol behaves as a positive allosteric modulator (PAM) of A2AR, although there is very weak
cooperativity between cholesterol and agonist. The weak cholesterol dependence above implies that either cholesterol does not form tight
interactions with A2AR, or that the interactions it establishes with the receptor do not grossly
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;
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available under a
CC-BY-NC 4.0 International license . overlap with the predominant allosteric pathways established by the agonist. The observed
enhancement may also be a consequence of an indirect effect resulting from changes to membrane
physical properties. Although the amounts of cholesterol used in this study were lower than that
of a typical plasma membrane, they greatly exceed the concentrations needed to saturate potential
high-affinity binding sites. Therefore, a simple allosteric mechanism involving specific binding by
cholesterol is unlikely. Fig. 2. A2AR agonist potency and basal activity are weakly enhanced by cholesterol. (A)
Agonist (NECA) Dose-response curves for A2AR-nanodiscs containing varying concentrations of
cholesterol. The vertical axis represents GTP hydrolysis by purified Gαβγ (cumulative over 90
min) in the presence of A2AR and agonist, relative to GTP hydrolysis by Gαβγ alone in the absence
of A2AR. Each data point represents the mean ± SEM (n = 6, technical triplicates). (B) Relative
GTP hydrolysis in the presence of apo A2AR (no agonist) in nanodiscs containing varying
concentrations of cholesterol. Data represents mean ± SD (n = 6, averages from each technical
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available under a
CC-BY-NC 4.0 International license . triplicate presented as individual points) and the asterisk represent statistical significance relative
to the 0% cholesterol condition. Statistical significance was determined by one-way ANOVA
followed by the Tukey’s multiple comparison test. * P ≤ 0.05. (C) pEC50 values of the NECA
dose-response curves in (A). Error bars represent 95% (asymmetrical profile likelihood)
confidence intervals. Using 19F NMR, it is possible to directly assess the effects of cholesterol on the distribution
of receptor functional states. Based on the agonist dose-response curves, we expected a
stabilization of activation intermediates or active states, at least in the presence of G protein. |
19F
NMR spectra of A2AR were recorded as a function of ligand, G protein, and cholesterol (Figs. 3A
and S2). In this case, the receptor was labelled at the intracellular side of transmembrane helix 6
(TM6), in a region known to undergo large conformational changes upon activation (Fig. 3B). The
resulting resonances have been assigned in our previous works and are shown as cartoons in Fig. 3C (Huang et al., 2021; Ye et al., 2016). Briefly, S1 and S2 represent two inactive state conformers
differentiated by a conserved salt bridge (“ionic lock”) between TM3 and TM6. The A3 state is an
activation intermediate stabilized by Gαβγ binding in the absence of ligands and is hence
associated with the “precoupled” state. A1 and A2 represent distinct active state conformers that
facilitate nucleotide exchange in the receptor G protein complex. It was found that while A1 is
preferentially stabilized by full agonist, A2 is more pronounced in the presence of partial agonist. Inspection of the overlaid spectra in Fig. 3A reveals nearly identical distributions of
conformational states between A2AR in the presence of 0% and 4% membrane cholesterol. At 13%
cholesterol, subtle changes can be observed in the inverse agonist-saturated, apo, full agonist-
saturated, and full agonist + Gαβγ spectra. In particular, we observed a small population shift
toward the active states, A1 and A2. The results imply that cholesterol is a positive allosteric
modulator of A2AR and acts in part through stabilization of the active state ensemble. Interestingly,
13% cholesterol resulted in line-broadening and a 0.09 ppm downfield shift of the A1 state in the
full agonist-saturated spectrum, changes which are not observed in the full agonist + Gαβγ
condition. The changes seen with the A1 resonance in the presence of 13% cholesterol and NECA
alone could be a consequence of motional averaging and/or a perturbation of the average
orientation of TM6. Clearly, cholesterol exerts differential effects on distinct conformers in the
ensemble. The outcome of the NMR experiments is consistent with the GTPase activity assay. 7
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available under a
CC-BY-NC 4.0 International license . Nearly complete overlap between the 0% and the 4% spectral series suggest that the principal
allosteric mechanism is unlikely related to high-affinity binding. While the subtle changes
observed at 13% cholesterol are evidence for positive allosteric modulation, the effects are much
smaller than those of any orthosteric ligands or other known allosteric modulators of A2AR (Gao
et al., 2020; Ye et al., 2018). Fig. 3. Cholesterol induces a small population increase in the active state conformers of A2AR. (A) 19F NMR spectra of A2AR in nanodiscs containing 0, 4, and 13% cholesterol, as a function of
ligand and G protein. |
Two inactive states (S1-2) and three active states (A1-3), previously identified,
are indicated by grey dashed lines. For each ligand condition, spectra from the three cholesterol
concentrations are normalized via their inactive state intensity. (B) Intracellular view of an inactive
(grey, PDB: 4EIY) and an active (yellow, PDB: 5G53) crystal structure of A2AR highlighting the
movement of TM6 upon activation. The 19F-labeling site is shown in violet. (C) Cartoon
representations of the key functional states of A2AR indicated in (A). At the bottom are two inactive
states (S1 and S2) where a conserved salt bridge is either intact or broken. A3 is an intermediate
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doi:
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;
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available under a
CC-BY-NC 4.0 International license . state that facilitates G protein recognition and precoupling. A1 and A2 are active states that drive
nucleotide exchange. While A1 is more efficacious and preferentially stabilized by the full agonist,
A2 is less efficacious and reinforced by a partial agonist. To understand if the weakly activating role of cholesterol arises because of enhanced
efficiency in nucleotide exchange or pre-association with G protein (precoupling), we carried out
19F NMR experiments on apo-A2AR in the presence of Gαβγ without agonist. As mentioned above,
this condition produces the precoupled receptor-G protein complex and greatly stabilizes the A3
state (Huang et al., 2021). This is recapitulated in Fig. 4 for all three cholesterol concentrations,
where a shift in the equilibrium populations toward the active conformers, particularly A3 and A2,
is observed upon the addition of Gαβγ. Importantly, an increase in cholesterol further enhanced
the A3 state in addition to a decrease in the peak width. The magnitudes of these changes are small,
consistent with results shown in Figs. 2-3. The results suggest that membrane cholesterol may help
to stabilize the precoupled complex of A2AR and G protein, and possibly modulates the amplitudes
of motion about the precoupled state. This in turn may favor further conformational exchange to
A1 or A2. Taken together, 19F NMR showed that mechanistically, the PAM effect of cholesterol in
A2AR can be attributed to an increase in the population of active state conformers as well as a more
robust coupling to the G protein. 9
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available under a
CC-BY-NC 4.0 International license . Fig. 4. The precoupled complex of A2AR-Gsαβγ is stabilized by cholesterol. |
19F NMR spectra
of apo A2AR in the presence of 0, 4, and 13% cholesterol, and as a function of Gαβγ. The key
functional states are indicated by grey dashed lines and the three spectra in the presence of G
protein are normalized via the A2 state. Allosteric network analysis reveals small negative allosteric modulation by cholesterol
Given the above observations, we employed rigidity-transmission allostery (RTA) analysis
(Sljoka, 2021) to survey allosteric activation pathway perturbation by cholesterol within the
ternary complex. The RTA algorithm is a computational tool based on mathematical rigidity theory
and has been used to identify allosteric networks within proteins (Jacobs et al., 2001; Sljoka, 2021;
Whiteley, 2005). It predicts how changes in the conformational rigidity or flexibility of one region
in the protein are transmitted to distal sites by quantifying the resulting differences in the degrees
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;
this version posted September 14, 2021.
available under a
CC-BY-NC 4.0 International license . of freedom within the system. Similarly, ligand-induced perturbations can be examined by
rigidifying the ligand itself or its binding pocket. Using a model of an agonist- and GDP-bound
A2AR-Gsαβγ complex, equilibrated in a 1 µs simulation in POPC bilayer with 20% cholesterol, our
previous work revealed that rigidification of the agonist NECA results in changes in the degrees
of freedom which can be transmitted from the orthosteric pocket to the Gα nucleotide binding site
(Huang et al., 2021). This allosteric network encompasses large portions of the receptor, the N-
and C-terminal helices of Gα, parts of the Gα Ras domain, three out of seven beta propellers within
Gβ, and a section of the Gβ N-terminal helix that forms coiled-coil interactions with Gγ. Using the above model, we repeated the RTA analysis to examine whether this previously
identified allosteric network is sensitive to the presence of cholesterol. Seven cholesterol
molecules were found in the vicinity (within 6 Å) of A2AR and were removed prior to rigidification
of the agonist. The resulting change in degrees of freedom is mapped in Fig. 5 for each residue
within the ternary complex. Removal of cholesterol gave rise to an allosteric pathway which is
very similar to that in the presence of cholesterol, although with altered intensities for some
regions. Higher allosteric transmission is observed for the CWxP motif of TM6, in particular the
tryptophan toggle switch W2466.48, in the absence of cholesterol. On the other hand, stronger
allosteric transmission is observed for the NPxxY motif of TM7 in the presence of cholesterol. Interestingly, the removal of cholesterol resulted in a slight overall enhancement in allosteric
transmission to the G protein. |
This includes the Gα N- and C-terminal helices which interact with
the receptor, as well as Gβ which has been found to play a role in conferring ligand efficacy (Huang
et al., 2021). The above observations suggest that the overall presence of cholesterol, while not
drastically perturbing, reduces signal transmission across the ternary complex. This is inconsistent
with our experimental observations, however, which indicate that cholesterol is a weak PAM. 11
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available under a
CC-BY-NC 4.0 International license . Fig. 5. Removal of cholesterol leads to a small overall enhancement in allosteric transmission
from the agonist binding site. (A) Allosteric networks within the A2AR-Gαβγ complex in the
presence and absence of cholesterol, revealed through RTA analysis via rigidification of the
agonist NECA (yellow spheres). The intensity of allosteric transmission is measured by the
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;
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available under a
CC-BY-NC 4.0 International license . resulting regiospecific changes in degrees of freedom and is mapped in color (red/blue gradient
bar). Cholesterol molecules are shown as orange sticks while green spheres represent GDP. (B)
The intensity of allosteric transmission is plotted for each residue in A2AR, Gα, and Gβ. Secondary
structural elements are indicated on the right. Grey blocks denote α-helices and β-strands, while
white gaps represent loops. For the Gα subunit, the common Gα numbering system is used (Flock
et al., 2015). A2AR-cholesterol interactions are short-lived and non-specific
To further evaluate the nature of cholesterol-A2AR interactions, we carried out 19F NMR
experiments of fluorinated cholesterol analogs, delivered into either empty or A2AR-embedded
nanodiscs via MβCD. Two different molecules were tested (Fig. 6). 3β-fluoro-cholest-5-ene (3β-
F-chol) was synthesized in house and features a fluorine atom in place of the cholesterol hydroxyl
headgroup. The fluoro group is a relatively benign substitute for the hydroxyl due to its similar
size and electronegativity. It also retains some ability to accept hydrogen bonds (Hoffmann and
Rychlewski, 2002). Another cholesterol analog, referred to as F7-chol, was purchased
commercially and had the tail isopropyl group replaced by CF(CF3)2. Incorporation of these
analogs did not affect the response of A2AR toward ligands nor its ability to activate the G protein
(Fig. S3). The NMR resonances were significantly broadened for both cholesterol analogs upon
incorporation into the membrane (Fig. |
6). This is expected for lipid molecules situated in a slow-
tumbling nanodisc. In the case of F7-chol, the peak shapes are further complicated by resonance
overlap of the two CF3 groups, which are inequivalent and exhibit complicated multiplicity
patterns. Comparison between the spectra of 3β-F-chol in empty nanodiscs and A2AR-embedded
nanodiscs shows a clear environmental difference in the presence of receptor (Fig. 6A). The
resonance is ~0.5 ppm upfield shifted and broader relative to empty nanodiscs. However, the lack
of chemical shift difference between 4% and 11% 3β-F-chol suggests that the above changes are
predominantly a result of altered environment (i.e. availability of hydrophobic proteinaceous
surfaces) rather than a shift toward receptor-bound states at specific binding pockets. The spectra of F7-chol are harder to interpret. Due to the two overlapped CF3 resonances,
a small change in chemical shift for either one could bring about dramatic variation in the overall
peak shape (Fig. 6B). As such, we cannot be confident about whether the observed changes in the
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available under a
CC-BY-NC 4.0 International license . CF3 peaks in response to A2AR are a consequence of specific binding. However, it is clear from
the two empty nanodisc spectra (containing either 6% or 9% F7-chol) that the membrane
environment is altered with increasing F7-chol. Overall, the NMR data from the two 19F-
cholesterol analogs show environmental differences between empty and A2AR-embedded
nanodiscs as well as between different cholesterol concentrations. However, there is no direct
evidence of a long-lived receptor-bound state. Fig. 6. 19F-cholesterol analogs interact with A2AR but show no evidence of a long-lived bound
state. Non-decoupled 19F NMR spectra of 3β-F-chol (A) and F7-chol (B) in chloroform, empty
nanodisc, and A2AR (apo)-embedded nanodisc. The fluorine groups contributing to each of the
resonances are circled and shown above the corresponding peak. As a classical PAM, cholesterol would be expected to exhibit stronger binding to A2AR in
the presence of an agonist or G protein, versus an inverse agonist. The opposite would hold for a
classical negative allosteric modulator (NAM). Yet, there was no apparent difference in chemical
shift sensitivity toward agonist or inverse agonist for either 19F cholesterol analogs (Fig. S4). The
NMR spectra of 3β-F-chol in A2AR-embedded nanodiscs are nearly identical upon the addition of
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available under a
CC-BY-NC 4.0 International license . |
inverse agonist, full agonist, and mini-G, a G protein mimetic that has been shown to stabilize the
A1 active state (Carpenter et al., 2016; Huang et al., 2021). Small chemical shift changes were
observed for F7-chol between the apo receptor and the ligand/mini-G-bound conditions. However,
the direction of shift is the same between full agonist and inverse agonist. Thus, cholesterol
interactions are independent from the identity of the orthosteric ligand bound to A2AR, despite
being observed as a functional PAM in vitro (Figs. 2-3) and predicted as a NAM in silico (Fig. 5). This leads us to consider that the observed positive allosteric effects of cholesterol are
predominantly indirect and relayed through the physical changes to the membrane bilayer. Cholesterol allostery in A2AR may be a result of indirect membrane effects
The effects of cholesterol on the physical properties of lipid bilayers have been well
documented. The planar structure of cholesterol promotes orientational order in the liquid
disordered phase of the bilayer, leading to reduced lateral diffusion and increased hydrophobic
thickness (Fig. 7A) (Crane and Tamm, 2004; De Meyer and Smit, 2009; Filippov et al., 2003;
Hung et al., 2007). For instance, as much as 20% increase in thickness can be expected for a POPC
bilayer when the cholesterol concentration is varied from 0 to 30% (Mouritsen and Bagatolli, 2016;
Tharad et al., 2018). We employed the lipophilic fluorescent probe Laurdan to monitor the membrane
orientational order of A2AR-embedded nanodiscs as a function of cholesterol. The generalized
polarization (GP =
I440−I490 I440+ I490
) of Laurdan fluorescence is a consequence of solvent contact. Fluid
(disordered) membranes exhibit smaller GP values, a consequence of dipole relaxation between
Laurdan and nearby water molecules which causes a red shift of the emission wavelength. In a
phospholipid bilayer, greater water accessibility at the hydrophobic-hydrophilic interface is
typically a signature of enhanced reorientational dynamics within the lipid milieu (Yu et al., 1996). As shown in Fig. 7B-C, we observed a consistent shift of the Laurdan fluorescence spectra which
gave rise to higher GP values at elevated cholesterol concentrations. This indicates that cholesterol
incorporation enhances lipid orientational order in A2AR-embedded nanodisc bilayers. An enhanced orientational order arises from a higher fraction of trans conformers in the
lipid chains and consequently, an increased hydrophobic thickness. In the case where A2AR adopts
an ensemble of states, the equilibrium is expected to shift toward those states which are more
compatible with an increased hydrophobic thickness (Andersen and Koeppe, 2007). Bilayer
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available under a
CC-BY-NC 4.0 International license . |
thickness can be readily modulated by changing the composition of lipids or acyl chain lengths. Alternatively, the application of hydrostatic pressure can be used in an NMR experiment to affect
changes in bilayer properties while avoiding potential complications associated with specific lipid-
receptor interactions. For a typical liquid disordered phosphatidylcholine bilayer, pressure-induced
compression is far more significant in the lateral than in the transverse direction (Stamatoff et al.,
1978). An elevation in pressure at constant temperature promotes ordering of the fatty acyl chains. This leads to an increase in lipid packing density and hydrophobic thickness, and a reduction of
lateral diffusion (Ding et al., 2017). Thus, hydrostatic pressure provides an effective way to mimic
the effects of cholesterol on a lipid bilayer (Fig. 7A). We recorded the 19F NMR spectra of the apo receptor in nanodiscs without cholesterol, at
a pressure of 1, 200, 1000, and 2000 bar. Like cholesterol, the rise in pressure resulted in a bias
toward the active ensemble, particularly the A1 (full agonist) state (Fig. 7D). Interestingly, the
magnitude of change is non-linear and considerably larger at 2000 bar in comparison to 1000 and
200 bar. This is consistent with the expected change in membrane thickness as a function of
pressure. For a pure POPC bilayer at 20 °C, the increase in hydrophobic thickness is small (up to
~2 Å) and roughly linear below 1200 bar. Above this pressure, the bilayer transitions to a solid
ordered phase which results in a rapid increase of membrane thickness on the order of 10 Å
(Rappolt et al., 2003). In comparison, the thickness increase as a result of 10-15% cholesterol is
on the order of 1-3 Å (Hung et al., 2007). The NMR results are similar to that of previous pressure studies of the β1AR and β2AR in
detergent micelles (Abiko et al., 2019; Lerch et al., 2020). In both cases a shift toward the active
state was observed in response to pressure, which was correlated with a reduction in void volume
of the active receptor relative to the inactive form. Here, 19F NMR allowed a more detailed
delineation of the conformational landscape of A2AR. Unlike agonist- or G protein-induced
activation, where the inactive ensemble is significantly diminished and all three active state
conformers are promoted, the redistribution of states brought about by pressure saw a smaller
decrease of the inactive ensemble and a specific shift in equilibrium toward the A1 state (Fig. 7D). The effects from pressure directly exerted on the receptor cannot be easily separated from indirect
effects that are manifested through changes in the lipid bilayer. However, more influence from the
membrane is expected since the molecular assembly of lipid bilayers is much more sensitive to
pressure relative to the conformation of proteins (Michiko and Rikimaru, 1999). The lipid bilayer,
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It is made
doi:
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;
this version posted September 14, 2021.
available under a
CC-BY-NC 4.0 International license . relative to detergent micelles, was shown to protect integral membrane proteins from pressure-
induced denaturation (Kangur et al., 2008). Overall, our pressure-resolved NMR data suggest that
A2AR can be regulated indirectly through changes in the lipid bilayer. While the mechanism may
be complex and the effects are subtle, receptor activation appears to be favored in an environment
with higher packing density, acyl chain order, and hydrophobic thickness. Fig. 7. Cholesterol allostery in A2AR is likely a result of indirect membrane effects. (A) The
lipid bilayer can be rigidified and thickened upon addition of cholesterol or an increase in lateral
pressure. (B) Averaged fluorescence spectra (n = 4) of Laurdan in A2AR-embedded nanodiscs
containing varying concentrations of cholesterol. (C) The emission intensity of Laurdan at 440 nm
and 490 nm were used to calculate the generalized polarization values. Data represent mean ±
SEM (n = 4, technical triplicates). Astrisks represent statistical significance over both the 0% and
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;
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available under a
CC-BY-NC 4.0 International license . the 3% conditions. Statistical significance was determined via one-way ANOVA followed by
Tukey’s multiple comparisons test. ** P ≤ 0.01. (D) 19F NMR spectra of A2AR, in the absence of
ligand or cholesterol, acquired at 1, 200, 1000, and 2000 bar pressures. The key functional states
are inducated by grey dashed lines. Discussion
A2AR has been intensely studied by both X-ray crystallography and more recently by
electron cryomicroscopy (cryo-EM). In many cases, cholesterol or CHS have proven useful in
stabilizing the receptor and obtaining high resolution structures. Earlier in vitro and cell-based
studies, along with the clear delineation of cholesterol in many crystal structures of A2AR suggest
that the molecule may play a direct allosteric role in modulating receptor function. A body of
computational work has since showcased cholesterol hot spots across the receptor and some of
these studies proposed state-dependent interactions (Lovera et al., 2019; McGraw et al., 2019). Nevertheless, there is no literature consensus on the allosteric role of cholesterol on this
prototypical GPCR. In this study, we set out to investigate both the magnitude and origin of the allosteric
interplay between cholesterol and A2AR in phospholipid bilayers. Functional and spectroscopic
studies in nanodiscs identify cholesterol as a weak PAM. Specifically, GTP hydrolysis assays
found a marginal increase in basal activity with increasing cholesterol, in addition to a very weak
enhancement in the agonist potency. |
19F NMR experiments revealed little or no difference in the
receptor spectra upon addition of 4% cholesterol. A very modest shift in equilibrium toward the
active states (A1 and A2) was observed at 13% cholesterol, indicating weak positive allostery. A
distinct enhancement of A3 is also found at 13% cholesterol for apo receptor bound to G protein,
implying that cholesterol either directly or indirectly stabilizes the precoupled A2AR-Gαβγ
complex. However, further computational analysis predicted that the presence of cholesterol
reduces allosteric transmission within the ternary complex, suggesting negative allostery by
cholesterol. In seeking an explanation for the observed positive allosteric effects of cholesterol on
A2AR, we first considered the possibility of a bound state through 19F NMR experiments using
fluorinated cholesterol analogs. However, no apparent binding isotherm could be observed,
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doi:
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;
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available under a
CC-BY-NC 4.0 International license . implying a weak or transient interaction between cholesterol and A2AR in phospholipid nanodiscs. There is also no correlation between the chemical shifts of the cholesterol analogs and orthosteric
ligand efficacy, suggesting that the origin of the observed positive allostery is through the indirect
effects of cholesterol on the membrane itself. Laurdan fluorescence experiments confirmed that
lipid orientational order is indeed increased by cholesterol. Furthermore, an increased hydrostatic
pressure predicted to yield comparable changes in membrane fluidity and thickness as those seen
with cholesterol gave rise to a shift in receptor equilibrium toward the fully active state. There may
indeed be subtle NAM effects from direct interaction with cholesterol, as suggested by our
computational analysis, which at the same time are overcome by stronger indirect effects through
the membrane. While we cannot rule out the possibility of a cumulative influence from multiple fast-
exchanging, weakly binding interactions, results from the current study strongly suggest that
changes in membrane physical properties are the primary, albeit indirect means by which
cholesterol regulates A2AR. It is possible that this is also the mechanism through which CHS
enhances the ligand binding activity of A2AR in detergent micelles (i.e. by modulating the micellar
structure to a more bilayer-like morphology). In support of this idea, an evaluation of A2AR
reconstituted in various mixed micelle systems revealed a correlation between receptor activity to
those detergent/CHS compositions that gave rise to a micellar hydrophobic thickness that closely
matches that of native mammalian bilayers (O’Malley et al., 2011b). One limitation of the current study is the range of cholesterol concentrations being probed,
which is below the physiological norm. |
In cell-based experiments, total cholesterol depletion is
not possible without adversely affecting cellular integrity. In many cases, the amount of cholesterol
left in the membrane was not quantified and the focus was instead on the disruption of raft-like
domains. Our nanodisc samples contained 0-13% cholesterol, which is below the concentration
regime for raft formation (Barrett et al., 2013; Crane and Tamm, 2004). These two strategies
(extraction from cholesterol-rich membranes and delivery into cholesterol-free membranes)
explore largely different processes; the former involves the disruption of rafts while the latter
allows studies of the interaction of cholesterol monomers with the receptor. Our data suggests that such interactions, if present for A2AR, are non-specific and short-
lived. This may explain why structural and computational work has yet to converge upon a single
cholesterol binding site. Like lipids, the observation of cholesterol in crystal structures may simply
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available under a
CC-BY-NC 4.0 International license . be a consequence of having cholesterol as a part of the crystallization matrix. In fact, many A2AR
structures which do not contain co-crystallized cholesterol (all the active state structures and some
inactive state structures) had the molecule present in large quantities during crystallization. In one
example, complexes of A2AR bound to an engineered mini-G protein were crystallized in
octylthioglucoside micelles either in the presence or absence of CHS. No discernible difference
was found between crystals that grew with or without CHS and the structure was solved using data
collected from two crystals, one from each condition (Carpenter et al., 2016). Similarly, the
numerous cholesterol “hot spots” predicted through computational approaches may not necessarily
indicate functional specificity, but rather geometric compatibility between certain hydrophobic
patches or grooves surrounding the receptor and the cholesterol backbone. This is reflected in the
fact that nearly all seven transmembrane helices and grooves between helices in A2AR have been
predicted in various studies to bind cholesterol (Genheden et al., 2017; Guixà-González et al.,
2017; Lee and Lyman, 2012; Lovera et al., 2019; McGraw et al., 2019; Rouviere et al., 2017;
Sejdiu and Tieleman, 2020; Song et al., 2019). Furthermore, the presence of CCM or CRAC motifs
has recently been shown to not be predictive of cholesterol binding in GPCRs (Taghon et al., 2021). The current work shows that A2AR does not require cholesterol to function in an in vitro
bilayer setting. However, many experiments have highlighted the role of cholesterol-rich domains
for A2AR to function in a cellular context. |
As alluded to above, a major shortcoming of our nanodisc
system is the upper limit of cholesterol that can be delivered. This prevented us from evaluating
the system at higher, more physiological cholesterol concentrations and probing the effects from
protein partitioning between liquid ordered and liquid disordered phases (Gutierrez et al., 2019). It is unclear whether A2AR alone prefers certain regions on the plasma membrane. Nevertheless,
both the stimulatory G protein and many isoforms of adenylyl cyclase were shown to partition into
raft-like domains (Kamata et al., 2008; Oh and Schnitzer, 2001; Ostrom et al., 2001; Ostrom and
Insel, 2004). Spatial co-localization of the receptor with other cellular binding partners in these
membrane regions may therefore be required to form and maintain signaling complexes. 20
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available under a
CC-BY-NC 4.0 International license . Supplementary Figures
Fig. S1. The size distribution of nanodiscs are minimally affected by cholesterol
incorporation. Hydrodynamic diameters of A2AR-nanodiscs containing varying levels of
cholesterol, measured through dynamic light scattering. 21
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available under a
CC-BY-NC 4.0 International license . Fig. S2. A2AR exhibits similar activation signatures in the absence and presence of
cholesterol. Non-overlapped (relative to Fig. 3) 19F NMR spectra of A2AR-V229C in nanodiscs
containing 0, 4, and 13% cholesterol. 22
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available under a
CC-BY-NC 4.0 International license . 02468
Gαβγ + A2AR (apo)
Relative GTP hydrolysisGαβγ (no A2AR)
Gαβγ + A2AR (NECA)
Gαβγ + A2AR (ZM241385)
0% Chol4% 3-F-chol11% 3-F-chol2% F7-chol8% F7-chol
Gαβγ + A2AR (LUF5834)
Fig. S3. Incorporation of 19F-cholesterol analogs into nanodiscs did not affect A2AR ligand
sensitivity and G protein activation. Cumulative hydrolysis of GTP by Gαβγ in the presence of
A2AR-nanodiscs with and without 19F-cholesterol analog, relative to GTP hydrolysis by Gαβγ
alone in the absence of A2AR. To assess ligand sensitivity, samples were saturated with either
inverse agonist (ZM241385), no ligand, partial agonist (LUF5834), or full agonist (NECA). Data
represent mean ± SEM (n = 3, technical triplicates). |
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available under a
CC-BY-NC 4.0 International license . Fig. S4. 19F-cholesterol analogs behave similarly in the presence of agonist- and inverse
agonist-bound A2AR. 19F NMR spectra of 3β-F-chol (A) and F7-chol (B) in A2AR-embedded
nanodiscs in the presence of inverse agonist (ZM241385), no ligand, full agonist (NECA), or
NECA + mini-Gs. The fluorine groups giving rise to each resonance is shown above their
corresponding peaks and the blue arrows indicate the direction of chemical shift change in response
to the addition of ligand and miniGs. 24
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available under a
CC-BY-NC 4.0 International license . Materials and Methods
A2AR expression, purification, and nanodisc reconstitution
Receptor cloning, expression, and purification have been described previously (Huang et al., 2021; Ye et al., 2016). Briefly, Pichia pastoris (P. pastoris) SMD 1163 (Δhis4 Δpep4 Δprb1) cells carrying the gene for A2AR (residues 2-317 with the V229C mutation for 19F-labeling) were grown to high density in either shaker flasks or a bioreactor. Methanol (5% v/v) was added every 12-16 h to induce expression and the cells were harvested after 60-72 h post induction. The receptors were extracted from the yeast membrane, reacted with the fluorine tag 2-Bromo-N-[4- (trifluoromethyl)phenyl] acetamide (BTFMA) when applicable, and further purified in the absence of cholesterol or cholesterol analogs. Prior to cholesterol incorporation, the receptors were reconstituted in rHDL nanodiscs using a 3:2 ratio of 1-palmitoyl-2-oleoyl-sn-glycero-3- phosphocholine (POPC) to 1-palmitoyl-2-oleoyl-sn-glycero-3-phospho-(1'-rac-glycerol) (POPG) and the MSPΔH5 membrane scaffold protein (Franz Hagn, Manuel Etzkorn, 2013). The sample was purified using a HiLoad 16/600 Superdex 200 preparatory grade size exclusion column equilibrated with nanodisc storage buffer (50 mM HEPES, pH 7.4, 100 mM NaCl), and the peak containing monodisperse nanodiscs were collected for cholesterol incorporation and further purification. Incorporation of cholesterol and cholesterol analogs
Incorporation of cholesterol and its fluorinated analogs in nanodiscs was achieved via incubation of the nanodiscs with cholesterol solubilized in methyl-β-cyclodextrin (MβCD, MilliporeSigma Canada, Oakville, Canada). One to two days prior to incorporation, a concentrated MβCD- cholesterol stock was prepared by mixing cholesterol (MilliporeSigma) with MβCD buffer (50 mM HEPES, pH 7.4, 100 mM NaCl, 40 mM MβCD) to a final concentration of 8 mM (4 mM in the case of fluorinated analogs, due to their increased hydrophobicity). |
The mixture was sonicated briefly to disperse any large chunks, then incubated at 30 °C for 24-36 hours with shaking until the solution is clear to the eye. The solution is filtered through a 0.2 µM filter to eliminate any undissolved particles, then diluted with MβCD buffer to make MβCD-cholesterol stocks containing 0.8 mM, 2 mM, 3 mM, and 4 mM cholesterol (0.8 mM and 3 mM in the case of fluorinated analogs). These stocks were mixed with nanodiscs collected from the size exclusion column described above (containing both empty and A2AR-embedded nanodiscs, which co-eluted) in a 1:3 v/v ratio, such that the final concentrations in the mixtures are 10 mM MβCD, 20-30 µM nanodisc, and 0.2 mM, 0.5 mM, 0.75 mM, or 1 mM cholesterol, for different levels of cholesterol incorporation. The mixtures were incubated at room temperature for 15 min with gentle shaking, then diluted 10-fold with nanodisc storage buffer containing 1-2 mL bed volume of Ni-NTA resin prior to incubation at 4 °C for 2 h. After incubation, Ni-NTA resins were collected using a gravity column and washed extensively with nanodisc storage buffer to remove residual empty nanodiscs, MβCD, and MβCD-cholesterol. Nanodiscs containing the His-tagged A2AR were eluted from the column using elution buffer (50 mM HEPES, pH 7.4, 100 mM NaCl, 250 mM imidazole), concentrated, and exchanged to nanodisc storage buffer for subsequent experiments. For empty nanodiscs, a His6-tagged MSPΔH5 protein was used. The reconstituted discs were treated with MβCD-cholesterol as above, incubated with Ni-NTA resins, and the MβCD was washed away prior to elution and concentration. 25
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available under a
CC-BY-NC 4.0 International license . Lipid quantification
Phospholipid concentrations were measured using a modified sulfo-phospho-vanillin assay (Frings and Dunn, 1970). Each sample containing unsaturated phospholipids (nanodiscs or phospholipid standards) was dissolved in 50-fold volume of concentrated sulfuric acid and incubated in a boiling water bath for 10 min. The samples were cooled in a cold-water bath for 5 min, then diluted 16- fold with a phospho-vanillin reagent (0.12% w/v vanillin dissolved in 68% v/v phosphoric acid). The samples were incubated in the dark for 30 min prior to absorbance measurements at 525 nm using a spectrophotometer. Lipid concentrations were determined using standard curves of A525 from pure POPC and POPG. In the case of nanodiscs, the lipid concentrations were determined using standard curves of both POPC and POPG:
[Lipidnanodisc,adjusted] =
3 5
[Lipidnanodisc,POPC] +
2 5
[Lipidnanodisc,POPG]
Quantification of cholesterol and fluorinated cholesterol analogs
Cholesterol concentrations were measured calorimetrically using a commercial kit (R-Biopharm and Roche Diagnostics, Cat. |
No. 10139050035) following the manufacturer’s protocol. The concentrations of 3β-F-cholesterol and F7-cholesterol (Avanti Polar Lipids) were estimated via integration of 19F NMR resonances of the cholesterol analog in relation to a reference compound (fluoroacetate in the case of 3β-F-cholesterol and trifluoroacetate in the case of F7-cholesterol), where the relative signal loss in the reference peak due to shortened relaxation delay was corrected for. Percent cholesterol in a given sample was calculated as follows:
% cholesterol =
[Cholesterol] [Lipid]
× 100
G protein cloning, expression, and purification
The expression and purification of Gsα, Gβγ, and mini-Gsα have been described previously (Huang et al., 2021) with the only difference being that a wild-type Gsα was used in the current work. To generate this construct, a double-stranded DNA fragment for the wild-type Gsα short isoform was codon optimized and synthesized using the GeneArt service from Thermofisher. This fragment carried overlapping sequences with the previously described pET15b MBP-Gsα mutant sequence (Huang et al., 2021). The plasmid was digested with XhoI and SacI (New England BioLabs, Ipswich, MA, USA) to remove the mutant Gsα sequence and purified via electrophoresis and gel extraction kit (Bio Basic, Markham, Canada). The resulted plasmid backbone and DNA fragment were fused using the pEasy assembly kit from TransGen Biotech following manufacturer’s instructions. The plasmid was transformed into Escherichia coli (E. coli) BL21 (DE3) cells and a resulting colony containing the gene for the wild-type Gsα was selected for protein expression. NMR experiments
NMR samples were prepared in nanodisc storage buffer with 20-100 µM A2AR-V229C (BTFMA- labelled for receptor NMR, unlabelled for 19F-cholesterol NMR), 10% D2O, and 20 µM sodium trifluoroacetate (TFA) or 100 µM fluoroacetate as the 19F chemical shift reference. For samples
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available under a
CC-BY-NC 4.0 International license . containing G protein (1.1-fold excess), the buffer also included 100 µM GDP, 2 mM MgCl2, and 5% glycerol. When applicable, A2AR ligands were added at saturating concentrations (1 mM NECA, 500 µM LUF5834, or 500 µM ZM241385). All samples were sterile-filtered and prepared in sterile Shigemi tubes to prevent microbial contamination. NMR experiments were acquired at 20 °C on a 500 MHz Varian Inova spectrometer equipped with a 5 mm room temperature inverse HFX probe. A typical fluorine NMR experiment included a 100 ms recycle delay, a 5.5 μs (45°) excitation pulse, and a 500 ms acquisition time. Each experiment acquired between 100,000- 400,000 scans, yielding a S/N of approximately 50-100. Spectra were processed using MestReNova (Mestrelab Research S.L.) |
employing chemical shift referencing (-75.6 ppm for TFA and -217 ppm for fluoroacetate), baseline correction, zero filling, and exponential apodization equivalent to a 5-20 Hz line broadening. For high pressure NMR, the sample was transferred to a 3 mm zirconia tube (Daedalus Innovations, Aston, PA, USA) and covered with paraffin oil. The tube was placed inside a 600 MHz Varian Inova spectrometer equipped with a triple-resonance cryoprobe tunable to 19F, via a stainless-steel fluid line connected to an Xtreme-60 syringe pump (Daedalus Innovations) prefilled with paraffin oil as the pressurizing fluid. Pressure was increased at a rate of 100 bar/min to the desired value, and the sample was equilibrated for 5 min at the final set pressure prior to acquisition at 20 °C. Membrane fluidity measurements
A2AR-embedded nanodiscs were incubated with the fluorescent probe Laurdan (MilliporeSigma) at room temperature for 30 min in the dark at a final concentration of 1 μM A2AR and 10 μM Laurdan (diluted from a 10 mM dimethylformamide stock). Free Laurdan was removed by extensive buffer-exchange with the nanodisc storage buffer and subsequently filtering the sample through a 0.2 μm filter. Flow-through from the final round of buffer-exchange was kept for background correction. The samples were transferred to a black 384-well plate and the fluorescent emission spectra (410 nm – 520 nm) were acquired using a TECAN Spark multi-mode plate reader (Tecan, Männedorf, Switzerland) at 26 °C with an excitation wavelength of 350 nm. Each emission spectrum was background-corrected, then area-normalized to the 13% cholesterol condition. The , generalized polarization (GP) of each sample was determined using the formula GP =
I440−I490 I440+ I490
where I440 and I490 represent the emission intensities at 440 nm and 490 nm, respectively. GTP hydrolysis experiments
GTP hydrolysis experiments were carried out using the GTPase-GloTM assay kit (Promega, Madison, WI, USA) following the manufacturer’s protocol (Mondal et al., 2015). Briefly, purified receptor and G protein were incubated at room temperature in a buffer containing 50 mM HEPES, pH 7.4, 100 mM NaCl, 2 mM MgCl2, 1 μM GDP, and 4 μM GTP, at a final concentration of 250 nM G protein, 250 nM A2AR, and various concentrations of the agonist NECA. Control reactions included buffer with GTP but in the absence of either A2AR or both A2AR and G protein. After 90 min, unreacted GTP was converted to ATP prior to the addition of a detection reagent containing luciferase. The resulting luminescence, which is proportional to the amount of unreacted GTP, was measured using a TECAN Spark multi-mode plate reader with an integration time of 1 min. GTP hydrolysis was determined as follows:
G protein only (in the absence of A2AR):
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It is made
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available under a
CC-BY-NC 4.0 International license . ∆Lum𝐺 = Lum(buffer only) − Lum(G protein only)
In the presence of A2AR:
∆Lum𝐺+𝑅 = Lum(buffer only) − Lum(G protein + A2AR)
where Lum is the luminescence signal intensity. The relative GTP hydrolysis for each A2AR (NECA) sample was calculated as follows:
Relative GTP hydrolysis =
∆Lum𝐺+𝑅 ∆Lum𝐺
× 100
The NECA dose-response data were fit using a variable slope model in GraphPad Prism 8.4.2 employing the equation:
Response = Emin +
(xn)(Emax − Emin) xn + (EC50)n
where x is the agonist concentration, Emin is the minimum response, Emax is the maximum response, EC50 is the agonist concentration that promotes half-maximum response, and n is the Hill coefficient. Dynamic Light Scattering
DLS samples were prepared in nanodisc storage buffer containing 5 μM A2AR-embedded nanodiscs supplemented with different mol% of cholesterol. Each sample was filtered through a 0.2 μm syringe filter to remove large dust particles before transferring to a small-volume 10 mm quartz cuvette (Starna Cells, Atascadera, CA, USA). DLS measurements were carried out inside a Zetasizer Nano-ZS particle size analyzer (Malvern Panalytical, Malvern, United Kindom) equipped with a He-Ne laser (λ = 633nm). Samples were equilibrated at 25 °C for 2 minutes and the scattered light was measured at a 173° backscatter angle. The resulting correlation function was analyzed using the general purpose (non-negative least squares) analysis model in the Zetasizer software (v7.13, Malvern Panalytical) for distribution analysis, assuming a buffer viscosity of 0.9066 cP, a buffer refractive index of 1.332, and a protein refractive index of 1.450. Data was averaged over three independent trials, each having 3 replicate measurements of 10-20 scans. Synthesis of 3β-fluoro-cholest-5-ene
3β-fluoro-cholest-5-ene was synthesized from cholesterol in one step, using the deoxyfluorination reagent DAST (diethylaminosulfur trifluoride, Toronto Research Chemicals, North York, Canada). Though fluorinations with DAST often proceed through an SN2 mechanism, fluorination of cholesterol is known to retain its stereochemistry (Rozen et al., 1979). This results from homoallylic participation forming a carbonium ion intermediate (Li et al., 2016; Rozen et al., 1979). 28
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available under a
CC-BY-NC 4.0 International license . Cholesterol (650 mg, 1.68 mmol) was dissolved in dry CH2Cl2 (15 mL) in a plastic reaction vessel under argon. The mixture was cooled to -20 °C and DAST (4 eq., 0.89 mL) was added dropwise over 5 min. The solution was stirred at -20 °C for 1 h. The cooling bath was removed, and the reaction was continued at rt for 3 h. It was quenched by slowly pouring the mixture into a vigorously stirred solution of sodium bicarbonate at 0 °C. |
After the bubbling stopped, the aqueous phase was extracted twice with CH2Cl2 (50 mL). The organic layer was washed with brine and concentrated to give an orange syrup. Silica column chromatography (eluent: 100% pentanes, Rf = 0.27) yielded the product as a white solid (283 mg, 43%). The product’s spectroscopic characterization was consistent with published data (Li et al., 2016; Reibel et al., 2015). 1H NMR (400 MHz, CDCl3) δ 5.39 (d, J = 4.9, 1H), 4.67 – 4.13 (dm, 2JH-F = 50.4 Hz, 1H), 2.44 (t, J = 7.0, 2H), 2.10 – 1.92 (m, 3H), 1.93 – 1.78 (m, 2H), 1.77 – 1.63 (m, 1H), 1.63 – 0.80 (m, 32H), 0.69 (s, 3H). 19F NMR (377 MHz, CDCl3) δ -167.82 (dm, 2JF-H = 50.4 Hz). 13C NMR (101 MHz, CDCl3) δ 139.50 (d, J = 12.6 Hz), 123.16 (d, J = 1.3 Hz), 92.98 (d, J = 174.1 Hz), 56.88, 56.33, 50.17 (d, J = 1.8 Hz), 42.49, 39.91, 39.69, 39.57 (d, J = 19.3 Hz), 36.69 (d, J = 1.2 Hz), 36.53 (d, J = 10.8 Hz), 36.36, 35.95, 32.09 (d, J = 1.1 Hz), 32.03, 28.95 (d, J = 17.5 Hz), 28.39, 28.18, 24.45, 24.01, 22.98, 22.73, 21.29, 19.47, 18.89, 12.02. HRMS (EI): Calcd. For C27H45F: 388.3505; Found: 388.3506. Computational rigidity-transmission allostery analysis
The fully active state of A2AR in complex with Gsαβγ, NECA and GDP was constructed, equilibrated and relaxed in a 1 µs MD simulation in 4:1 POPC:cholesterol extended membrane as previously described (Huang et al., 2021). This model was used to probe agonist-induced allosteric communication in the A2AR-Gαβγ complex with rigidity-transmission allostery (RTA) algorithm, whose details have been previously described (Huang et al., 2021; Ye et al., 2018). The RTA algorithm is a computational method based on mathematical rigidity theory, which predicts how perturbations of conformational rigidity and flexibility (conformational degrees of freedom) at one site transmit across a protein or a protein complex to modify degrees of freedom at other distant sites (Sljoka, 2021). Here, RTA was applied the allosteric pathways between the orthosteric pocket and distal regions in the A2AR-Gαβγ complex with and without cholesterol. We quantified the available conformational degrees of freedom at every residue before
to examine
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available under a
CC-BY-NC 4.0 International license . and after rigidification of the agonist NECA. The change in degrees of freedom was then extracted for each residue, which represents the extent of allosteric transmission from the orthosteric pocket. In the presence of cholesterols, the analysis was carried out as previously described (Huang et al., 2021). To measure the impact of cholesterol on allosteric communication, the same analysis was repeated upon removal of all seven cholesterols found within 6 Å of the receptor. |
Author contributions
S.K.H. and R.S.P. designed the research. S.K.H and O.A. performed protein expression and purification for A2AR. S.K.H. performed protein expression and purification for Gsα and mini-G. A.P. and S.K.H conducted expression and purification of Gβγ. L.P cloned the wild-type Gsα construct. S.K.H. and O.A. performed the NMR experiments. S.K.H. performed the GTP hydrolysis assays and DLS experiments. R.J.P. performed the Laurdan fluorescence experiments. Z.A.M. and M.N. provided the 3β-fluoro-cholest-5-ene. A.S. performed the RTA analysis. S.K.H and R.S.P prepared the manuscript. R.S.P. supervised the project. Acknowledgements
This work was supported by the CIHR Operating Grant MOP-43998 to R.S.P. ; S.K.H. was supported by Alexander Graham Bell Canada Graduate Scholarship-Doctoral from NSERC; A.S. was supported by CREST, Japan Science and Technology Agency (JST), Japan JPMJCR1402; R.J.P. was supported by QEII F.E. Beamish Graduate Scholarship in Science and Technology. Special thanks to Dmitry Pichugin for NMR spectrometer maintenance. Competing interests
The authors declare no competing interests. 30
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available under a
CC-BY-NC 4.0 International license . References
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made available under a
CC-BY-NC-ND 4.0 International license . Multi-omics analysis identifies essential regulators of mitochondrial stress
response in two wild-type C. elegans strains
Arwen W. Gao1*, Gaby El Alam1*, Amélia Lalou1, Terytty Yang Li1, Marte Molenaars2,
Yunyun Zhu5, Katherine A. Overmyer3,4,5, Evgenia Shishkova3,4, Kevin Hof1, Maroun Bou
Sleiman1, Riekelt H. Houtkooper2, Joshua J. Coon3,4,5,6, and Johan Auwerx1#
1Laboratory of Integrative Systems Physiology, Interfaculty Institute of Bioengineering, École
Polytechnique Fédérale de Lausanne, CH-1015 Lausanne, Switzerland;
2Laboratory Genetic Metabolic Diseases, Amsterdam Gastroenterology, Endocrinology, and
Metabolism, Amsterdam Cardiovascular Sciences, Amsterdam UMC, University of
Amsterdam, 1105 AZ Amsterdam, the Netherlands;
3National Center for Quantitative Biology of Complex Systems, Madison, WI 53706, USA;
4Morgridge Institute for Research, Madison, WI 53515, USA;
5Department of Biomolecular Chemistry, University of Wisconsin, Madison, WI 53506, USA;
6Department of Chemistry, University of Wisconsin, Madison, WI 53506, USA. Equal contribution
#Correspondence: [email protected]
1
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made available under a
CC-BY-NC-ND 4.0 International license . Abstract
The mitochondrial unfolded protein response (UPRmt) is a promising pharmacological target
for aging and age-related diseases. However, the integrative analysis of the impact of UPRmt
activation on different layers of signaling in animals with a different genetic background is
lacking. In this study, we applied systems approaches to investigate the effect of UPRmt
induced by administering doxycycline (Dox) on transcriptome, proteome, lipidome, and
metabolome in two genetically divergent C. elegans strains. We found that Dox prolongs
lifespan of both worm strains through pathways in both shared and strain-specific manners. From the integrated omics datasets, we observed a strong impact of Dox on mitochondrial
functions, detected upregulated defense response and lipid metabolism, identified decreased
triglycerides and lowered metabolome profiles in both strains. This conserved phenomic
footprint has great translational value as it indicates that the beneficial effects of Dox-induced
UPRmt on health and lifespan are consistent across different genetic backgrounds. Key words: C. elegans, multi-omics, UPRmt, Doxycycline, and aging
2
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made available under a
CC-BY-NC-ND 4.0 International license . Introduction
Mitochondria are essential organelles for numerous processes, such as energy harvesting,
intermediate metabolism, autophagy, and immune response (Nunnari and Suomalainen 2012;
Quiros et al. 2016; West and Shadel 2017). Changes in mitochondrial number, morphology,
and functions not only impact cellular metabolism but also influence whole body metabolism,
health, and lifespan (Nunnari and Suomalainen 2012; Vafai and Mootha 2012; Andreux et al. 2013). There has been increasing evidence that mitochondrial dysfunction accumulates upon
aging and correlates with the development of many age-associated diseases (Sun et al. 2016). Age-associated mitochondrial
impairments
include decreased efficiency of oxidative
phosphorylation, increases in oxidative damage, aggregation of mitochondrial proteins,
alteration of mitochondrial quality control (e.g. mitophagy), accumulation of mtDNA mutations,
as well as dysregulation of many aspects of mitochondrial metabolism (Sun et al. 2016; Jang
et al. 2018; D'Amico et al. 2019). Given the central role of mitochondria in health- and lifespan, mitochondria evolved an
elaborate quality control system directing pleiotropic mitochondrial stress response (MSR)
pathways to ensure optimal mitochondrial function and promote cell survival upon stress and
aging. One of the MSR pathways is the mitochondrial unfolded protein response (UPRmt),
which is well-characterized in C. elegans (Quiros et al. 2016; Shpilka and Haynes 2018). The
UPRmt is a proteotoxic stress response that senses protein-folding perturbations, which
overload the capacities of the mitochondrial quality control network (Jovaisaite et al. 2014). The prototypical UPRmt is best characterized in C. elegans; when unfolded or misfolded
proteins accumulate in the mitochondrial matrix in the worm, CLPP-1, a mitochondrial
protease, cleaves these proteins into small peptides, which are then exported into the cytosol
by the mitochondrial inner membrane peptide transporter HAF-1. On the other hand, those
released peptides can impede the import of proteins into the mitochondria (Yoneda et al. 2004;
Haynes et al. 2010; Naresh and Haynes 2019). The transcription factor ATFS-1 therefore
cannot be imported into the mitochondrial matrix where it is degraded by the LON protease
(Nargund et al. 2012). As a result, ATFS-1 translocases and accumulates in the nucleus,
forming a complex with the small ubiquitin-like protein UBL-5 and the transcription factor DVE-
1. Together, this transcription complex activates the expression of nuclear-encoded protein
quality components including the heat-shock proteins hsp-6 and hsp-60 to re-establish
mitochondrial homeostasis (Benedetti et al. 2006; Nargund et al. 2012; Jovaisaite et al. 2014). Paradoxically, induction of mild mitochondrial perturbations that activate the UPRmt in a
moderate fashion have been shown to lead to the extension of lifespan in worms (Dillin et al. |
2002; Durieux et al. 2011; Houtkooper et al. 2013), flies (Copeland et al. 2009), and mice
3
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made available under a
CC-BY-NC-ND 4.0 International license . (Houtkooper et al. 2013), suggesting that approaches to enhance UPRmt activation may
potentially be useful to manage certain age-related diseases. Tetracyclines, such as
doxycycline (Dox), are antibiotics that inhibit both bacterial and mitochondrial translation
(Houtkooper et al. 2013). Dox has therefore been applied as a pharmacological inducer of the
UPRmt (Moullan et al. 2015). Despite evidence that the UPRmt has a beneficial effect on
health and aging, the molecular mechanisms that couple the Dox-mediated UPRmt with
health- and lifespan extension remain to be elucidated. In addition, these effects of Dox have
only been demonstrated in the reference Bristol N2 strain, and the impact of the genetic
background on the protective effect of Dox has never been characterized. In this study, we
have pharmacologically induced the UPRmt by Dox administration in two genetically divergent
worm strains, the N2 and the Hawaii CB4856 strains (Fig. 1A). We show that the Dox-related
protective effects are likely mediated at multiple levels of biological regulations, including
transcription, translation, lipid, and metabolite levels. Activation of mitochondrial stress
response by Dox prolongs lifespan of both worm strains, coupling with some shared and
strain-specific features at different layers of regulation. Our findings highlight a strong impact
of Dox on mitochondrial functions in both worm strains. Beyond that, Dox administration also
upregulated stress response and lipid metabolism, while lowering triglycerides and a
comprehensive panel of metabolites in both strains. Results
Doxycycline prolongs lifespan of both N2 and CB4856 strains
To determine whether doxycycline (Dox) has a strain-dependent effect on lifespan, we
cultured both N2 and CB4856 worms on plates with or w/o Dox (15 µg/mL) and measured
their lifespan in nine independent experiments (Fig. 1B). In basal conditions, CB4856 worms
had a shorter lifespan compared to N2 worms. Upon Dox exposure, both worm strains showed
an increased lifespan compared to the controls. Because Dox was known to block
mitochondrial translation and attenuate respiration (Houtkooper et al. 2013), we measured the
oxygen consumption rate (OCR) in N2 and CB4856 worms fed with Dox (Fig. 1C). Respiration
was decreased upon Dox addition in both strains. These data suggest that Dox has a universal
effect on lifespan and mitochondrial function in both worm strains. 4
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made available under a
CC-BY-NC-ND 4.0 International license . Figure 1. Doxycycline (Dox) activates the mitochondrial stress response (MSR) and prolongs lifespan in two wild-type C. elegans strains, N2 (Bristol) and CB4856 (Hawaii). (A) Flowchart of the strategy to identify shared and strain-specific MSR regulators. (B) Survival analysis of worms fed with control bacteria (E. coli HT115) culture on plates with or without Dox (15 μg/mL) by merging nine independent lifespan experiments (n=2400). The shadow area represents the 95% confidence intervals. P-values represent comparison with the controls calculated using log-rank test (**: p<0.01; ***: p<0.001; ****: p<0.0001). (C) Dox reduced basal and maximal oxygen consumption rate (OCR) in both worm strains. Error bars denote SEM. Statistical analysis was performed by ANOVA followed by Tukey post-hoc test (*p<0.05; **p<0.01; ***p<0.001; ****p<0.0001; N.S., not significant). (D) Principal component analysis (PCA) of transcripts/mRNAs, proteins, lipids and metabolites measured in N2 and CB4856 worms treated with or without Dox. Related to Figure S1, Table S1, S2, S5 and S6. To further investigate the difference in the regulation of Dox-induced longevity in N2 and
CB4856 strains, we collected worm samples either exposed to Dox or not, and extracted total
RNAs, proteins, lipids and metabolites for multi-omic analysis. We first assessed the strain
and Dox effects on each of the omic profiles (Fig. 1D). Interestingly, a primary separation by
Dox exposure and a second separation by strain was observed at the transcript and lipid layers
(Fig. 1D). Whereas at the protein layer, the first component separated the strains and the
second component separated the treatments. For metabolites, we observed a primary
separation by Dox followed by a very minor separation by strains. These data suggest that
5
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made available under a
CC-BY-NC-ND 4.0 International license . Dox showed a stronger effect on the transcriptomic, lipidomic, and metabolomic layers and
the genetic background seems to play a larger role in determining the proteomic layer. Next, we questioned whether these alterations are commonly shared between the two wild-
type strains upon Dox (Supplemental Fig. S1A). In line with the PCA analysis (Fig. 1D), up to
80% of transcripts showed similar Dox-induced changes in both worm strains, in which 2,414
and 2,021 genes were significantly up- and down-regulated, respectively. Consistent with the
PCA of the protein profiles, we detected fewer overlapping changes between the two strains
upon Dox exposure, in which 127 and 205 proteins were significantly up- and down- regulated,
respectively. |
In particular, the majority of the altered proteins in CB4856 worms were not found
to be altered in N2 worms upon Dox (Supplemental Fig. S1A and Supplemental Table S2). Additionally, we also detected a group of genes that showed reciprocal regulation between
the two strains, including the 24 at transcript and 65 at the protein level. Lipid and metabolite
levels altered similarly in both N2 and CB4856 strains during mitochondrial stress. We then
asked how many genes were significantly altered at both transcript and the corresponding
protein levels (Supplemental Fig. S1B, Supplemental Table S1 and S2). In N2 worms, 271
transcript-protein pairs were similarly altered in the transcriptomics and proteomics profiles, in
which 188 and 83 pairs were up- and down-regulated, respectively, and 66 transcript-protein
pairs were reciprocally regulated by Dox. In CB4856 worms, 196 and 181 transcript-protein
pairs were up- and down-regulated whereas 172 pairs of mRNAs/proteins were reciprocally
regulated by Dox. However, in both worm strains, the genes/proteins that did not change at
both transcript and protein levels account for a substantial part of the total altered genes. This
reveals that mitochondrial stress induced by Dox may have a global impact on gene
expression as well as on post-transcriptional regulation. Collectively, these results suggest
that mitochondrial stress induced by Dox prolongs lifespan of both worm strains and the
underlying changes at the molecular levels exhibit shared and strain-specific features. Defense response and oxidative reduction are affected by genetic variants in CB4856
compared with N2 worms
Since N2 and CB4856 at the basal levels have distinct lifespans as well as different OCR (Fig. 1B-C), we catalogued the genetic differences and their consequences and explored gene and
protein expression differences in basal conditions (Fig. 2). We compiled high impact variants
present in the CB4856 strain (retrieved from the Caenorhabditis elegans Natural Diversity
Resource: https://elegansvariation.org/data/release/latest), relative to the N2 reference strain. Among these, we filtered from all the detected variants and selected the major types of
consequences from homozygous variants that are of high impact, including frame-shift, start
codon lost, stop codon lost, and stop codon gained for further investigations. Across the six
chromosomes, most of the detected variants were distributed at the ends of each
6
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made available under a
CC-BY-NC-ND 4.0 International license . chromosomes (Fig. 2A and Supplemental Table S3). Of these protein-coding genes, 2,755
had a frameshift (Supplemental Table S3), 32 lost a start codon, 52 lost a stop codon, and
305 had a stop-gained in CB4856 relative to N2 (Fig. |
2C). Figure 2. Variant analysis and gene set enrichment analyses (GSEA) determined the differences in the genetic background and gene expression between the N2 and CB4856 strains. (A) distribution of high impact variants in CB4856 per chromosome compared to the N2 reference from https://elegansvariation.org/data/release/latest. (B) Main classes of genes with high impact homozygous variants detected in the CB4856 genome are listed in the table. (C) As an example, a circos plot of high impact variants (hard-filtered) present in the CB4856 strain compared the N2 reference strain. Analyzed variants are homozygous and with one of the following consequences: Brown: genes with start codon lost; Dark pink: genes with stop codon lost; Blue: genes with stop codon gained. The full list of variants with a soft filter are shown in Table S1. (D) GSEA reveals the differences between the N2 and CB4856 strains at both mRNA and protein expression levels under basal condition. Q-value: false discovery rate adjusted p-values, grey dots: non-significant (n.s. ); gene ratio: ratio of found genes within a given gene set. NES: normalized enrichment score. Related to Figure S2 and Table S3. strain. CB4856 VCF
(Variant Call Format)
file was
retrieved
These genes with codon variants could be pseudogenes in CB4856 as a rapid means of
adaption (Olson 1999); however, the persistence of these regions may suggest the presence
of functional and essential genes. The genes altered by the variants are composed of
members of large gene classes, including 107 fbx (F-box), 19 math (MATH), 47 clec (C-lectin),
16 cyp (cytochrome P450 family), 12 bath (BTB-MATH) genes, 28 nhr (nuclear hormone
receptor), and 190 sr/str (serpentine receptor superfamily) genes (Fig. 2B). F-box family,
7
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made available under a
CC-BY-NC-ND 4.0 International license . MATH and BTB-MATH gene families encode ubiquitin-dependent proteosome adapters that
were largely involved in targeting foreign proteins for proteolysis during pathogen defense
(Thomas 2006). The serpentine receptor superfamily belongs to the G-protein-coupled
receptors (GPCRs) that are involved in signal transmission and are playing a vital role in
controlling innate immunity against bacterial infections (Nagarathnam et al. 2012; Kaur and
Aballay 2020). The variants detected in these genes may lead to defects in pathogen defense
in CB4856 worms, which partly could contribute to their shorter lifespan at basal condition
compared with the N2 strain. Mammalian C-lectins are carbohydrate-binding proteins that
have very narrow ligand specificity, and many C-lectins are involved in innate immune
response. Although there are 264 genes encoding C-lectins in C. elegans, functions and roles
of most C-lectins remain unclear (including the four detected clec genes), except for the few
of them that were annotated as innate immune genes (Pees et al. |
2016). The cytochrome
P450 family is composed of enzymes that catalyze oxidative reactions and their substrates
include lipids, exogenous and xenobiotic chemicals (Harlow et al. 2018; Herholz et al. 2019). Nuclear hormone receptors are a family of transcription factors that often influence lipid
metabolism in C. elegans (Chinetti et al. 2000; Ashrafi et al. 2003; Taubert et al. 2006). Variants found in the stop codons of these genes could impair protein function and thus affect
lipid oxidation or other oxidation-reduction process. Overall, differences in these gene families
could partially explain the lifespan difference between the two wild-type strains under control
conditions. To further explore the impact of the genetic background on the transcript and protein levels,
we examined the top gene sets enriched in N2 or CB4856 at the control condition (Fig. 2D
and Supplemental Fig. S2). Interestingly, we detected overall more pronounced differences
level between the two strains at the protein level, as compared to those detected at the
transcript level. At the transcript level, the top enriched gene sets were mainly in CB4856
worms, including those involved in cell fate and transcription factor activity. In contrast, the
majority of the top detected gene sets at the protein level were more pronouncedly enriched
in N2 worms, including lipid metabolism, carboxylic acid metabolism, ribonucleoprotein
granule, metabolic process, and biosynthesis of small molecules, fatty acids, organic acids,
and monocarboxylic acids. In CB4856 worms, proteins involved in chromatin organization,
histone modification, extracellular region, anchoring junction, and taxis were more enriched,
compared to those detected in N2 worms. Next, we generated enrichment maps for each worm strain to broaden the view and explore
other interesting gene sets (Supplemental Fig. S2). Of note, we observed a presence of
various gene sets involved in the nucleotide metabolism, and lipid metabolism in the N2 worms
at the transcript level, compared to those in CB4856 (Supplemental Fig. S2A). Additionally, a
8
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made available under a
CC-BY-NC-ND 4.0 International license . large gene set cluster enriched for lipid metabolism and a cluster of genes enriched for
defense response was detected at the protein level in the N2 worms (Supplemental Fig. S2C). Hence, in line with our variant analysis results (Fig. 2), genes involved in defense response,
and lipid metabolism were more enriched in N2 worms in control conditions compared with
those in CB4856 worms (Supplemental Fig. S2A,C). In the CB4856 worms, we detected a
trend of very large gene set for nucleic acid metabolism especially those are associated with
RNA metabolism at the mRNA level (Supplemental Fig. |
S2B). At protein level, we detected a
cluster of gene sets enriched for neuron development (Supplemental Fig. S2D), in addition to
the gene sets already mentioned above (Fig. 2D). Altogether, these data provide details on
strain specificity of the gene set enrichment at both transcriptomic and proteomic level and
suggest that some of these differences could be attributed to genetic variants present in the
CB4856 genome. Dox upregulates lipid metabolism, proteolysis, and stress response in both strains
After observing a considerable impact of genetic variants in the CB4856 strain, we wondered
whether the molecular changes upon mitochondrial stress will be affected by the different
genetic backgrounds as well. We first analyzed differentially expressed genes using gene
ontology (GO) analysis on the 2,414 upregulated transcripts and 127 upregulated proteins in
both worm strains upon Dox exposure (Supplemental Fig. S1A, and Fig. 3A,B). At the
transcript level, factors involved in proteolysis, lipid metabolism and transport, stress response,
innate immune response, and muscle contraction were enriched in both worm strains upon
Dox (Fig. 3A). At the protein level, we found fewer GO-terms compared to those at the
transcript level, and most of them were related to defense response, including response to
stimulus, immune response, response to oxidative stress and to osmotic stress (Fig. 3B). Additionally, we also detected a group of GO-terms related to metabolic processes of
flavonoids, organic acids, and monocarboxylic acids. Similar to the number of transcripts exclusively altered in either N2 or CB4856 worms upon
Dox (Supplemental Fig. S1A), we also detected fewer N2-specific and more CB4856-specific
enriched GO terms (Supplemental Fig. S3A,B). In the N2 strain, transcripts related to
proteolysis, defense response, carbohydrate metabolism, cuticle development, and oxidation-
reduction process were upregulated exclusively upon Dox (Supplemental Fig. S3A). In
CB4856, the majority of the GO-term clusters have already been identified in the shared GO-
term profile (Fig. 3A), suggesting that CB4856 worms required expression of more genes in
order to cope with the mitochondrial stress induced by Dox. 9
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made available under a
CC-BY-NC-ND 4.0 International license . Figure 3. GO-term enrichment and GSEA revealed shared key players and strain-specific regulators of Dox-mediated longevity in N2 and CB4856. (A) GO term enrichment analysis (biological process) on the upregulated transcripts shared between N2 and CB4856 upon Dox exposure identified via David and ReviGO. The size of the dots indicates the frequency of the GO term in the underlying Gene Ontology Annotation database; the plots are color-coded according to significance (Log10-transformed); level of significance increases from red to blue. |
GO terms belonging to the same cluster were grouped and circled in dark grey dashed lines. (B) Go term enrichment analysis on upregulated proteins shared by N2 and CB4856 worms upon Dox. (C-D) GSEA showed top 18 enriched gene sets in N2 (C) and CB4856 (D) worms upon Dox at both transcript and protein level. The shared gene sets between the two strains are highlighted in red. Q-value: false discovery rate adjusted p-values; gene ratio: ratio of found genes within a given gene set. NES: normalized
10
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made available under a
CC-BY-NC-ND 4.0 International license . enrichment score. Shared gene sets are indicated in red. (E-F) Scatter plots of differentially expressed genes (p<0.05, Log2(fold-change)>1 or <-1)) at mRNA (x-axis) and protein level (y-axis) of N2 (E) and CB4856 (F) upon Dox. Go-term enrichment analysis was then performed on each of the 8 different categories (defined based on directionality change at mRNA & protein levels). Significantly enriched GO terms are presented as a circle (radius determined by gene ratio) and edges to the related genes are shown in grey. Related to Figure S3. Dox induces various responses in N2 and CB4856 worms at transcript and protein
levels
Next, we determined the top enriched gene sets at mRNA and protein levels separately to
assess the effects of Dox on N2 and CB4856 strains. Most top enriched gene sets at the
mRNA level in N2 worms were upregulated, while the majority of the top detected gene sets
at protein level were downregulated (Fig. 3C). In CB4856 worms, top enriched genes were
primarily downregulated at both transcript and protein levels (Fig. 3D). Moreover, immune
responses were upregulated in both worm strains upon Dox at the protein level, and gene sets
annotated as extracellular region and defense response were upregulated in N2 and CB4856,
respectively. Downregulated proteins upon Dox showed strain-specific gene set enrichments,
in which proteins related to ribonucleoprotein complex and reproduction were only decreased
in N2, whereas those involved in cell cycle and chromosome organization were exclusively
decreased in CB4856. Although Dox is known to inhibit mitochondrial translation (Houtkooper
et al. 2013), our data confirm that Dox may also attenuate cytosolic translation and this in turn
leads to a downregulation of protein sets in different worm strains (D'Amico et al. 2017;
Molenaars et al. 2020). To better understand whether the changes detected at transcriptomic and proteomic levels
were representative of one another, we compared the transcriptomic and proteomic profiles
of N2 and CB4856 upon Dox (Fig. 3E,F). We divided significantly altered transcripts and
proteins (adjusted p-value<0.05 & an abs. fold-change>1) into eight categories based on their
differences in a co-regulation analysis. |
An overrepresentation analysis on the detected genes
was performed on each of the eight categories to determine the major altered gene sets. In
N2 worms, gene sets related to molting cycle, structure organization and cuticle development
were co-upregulated at both mRNA and protein level upon Dox (Fig. 3E, pink box). Genes
enriched for immune response and defense response were primarily up-regulated at the
mRNA level (yellow box). In contrast, genes related to eggshell formation and amino sugar
metabolism were co-downregulated at both mRNA and protein levels (blue box). In CB4856
worms, those that encode factors for immune response, defense response, and stress
response were co-upregulated upon Dox (Fig. 3F, pink box). Gene sets involved in
transmembrane transport and muscle system process were only upregulated at transcriptional
level (yellow box). As expected, a number of gene sets were exclusively downregulated at the
11
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made available under a
CC-BY-NC-ND 4.0 International license . protein level, including those enriched for chromosome organization, cell cycle, nuclear
division, organelle fission, chromatin organization, transcription, biosynthesis of RNA and
macromolecules (purple box). Lastly, genes involved in DNA replication, cell cycle and
chromosome organization were co-downregulated at both levels (blue box). These data
suggest that shared and strain-specific regulation is present at both transcriptomic and
proteomic levels upon mitochondrial stress. Figure 4. Dox induced significant alterations in mitochondrial genes in both N2 and CB4856 worms. (A) Mitochondrial genes associated with different functions are significantly altered in both worm strains upon Dox at the transcript level. Outer ring: N2; inner ring: CB4856. Orange bars: upregulated genes by Dox; blue bars: downregulated genes by Dox. (B) Changes in the expression of mitochondrial transcripts encoding for proteins localizing at different mitochondrial compartments after Dox. (C-D) KEGG pathway enrichment analysis of up- and down-regulated mitochondrial genes upon Dox in N2 (C) and CB4856 (D). Orange bars: upregulated genes; blue bars: downregulated genes. Pathway in red: shared between the two strains. (E) GO enrichment analysis of the Dox- affected mitochondrial genes in both worm strains. Related to Figure S4 and Table S4. Dox affects mitochondrial gene expressions of both worm strains in a similar fashion
As mitochondria are the target of Dox, we then sought to investigate whether expression of
specific groups of mitochondrial genes were altered by Dox in the two strains. About 138
mitochondria-related genes were significantly changed in at least one worm strain upon Dox. We first annotated the altered mRNAs based on their associated functions to assess the
12
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It is
doi:
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;
this version posted July 20, 2021.
made available under a
CC-BY-NC-ND 4.0 International license . effects on the mitochondria (Fig. 4A and Supplemental Table S4). Most genes that encode
the mitochondrial complex I, II, and IV, were downregulated upon Dox exposure in both worm
strains, whereas those that encode complex III protein remained unchanged. Moreover, we
also detected Dox-induced downregulation in transcripts involved in energy-consuming
processes, such as DNA replication, DNA repair, apoptosis, mitochondrial translation, and
oxidation-reduction process. Many genes involved in transport, such as mitochondrial ATP
translocase, ant-1.3 and ant-1.4 (Hoshino et al. 2019), and mitochondrial ion transport, sfxn-
1.1, sfxn-1.2, sfxn-1.3, sfxn-1.4, and sfxn-5, were upregulated in both worm strains. For
pathways that are involved in energy production, although transcripts involved in the TCA
cycles were not changed in the same trend, we detected an overall upregulation in genes
involved in mitochondrial fatty acid oxidation (FAO). These data suggest an enhanced energy
support from FAO upon Dox. When we plotted the altered mitochondrial transcripts based on their localization within the
mitochondria, we noticed that genes that encode proteins/enzymes located in the inter
membrane space (IMS) and for membrane proteins were down-regulated, whereas those at
outer mitochondrial membrane (OMM) were mainly upregulated in both worm strains (Fig. 4B). Genes that encode for proteins functioning in the mitochondrial matrix and inner mitochondrial
membrane (IMM) were partly upregulated and downregulated upon Dox exposure. Because
Dox mainly inhibits mitochondrial translation (Houtkooper et al. 2013), we then sought to
assess the alterations of mitochondrial proteins upon Dox (Supplemental Fig. S4). However,
due to technical challenges in proteomics measurements, we were not able to collect the
comprehensive changes at the protein level for these mitochondrial genes upon Dox (only
detected 59 mitochondrial proteins were significantly altered). To determine pathways that are significantly affected by Dox, we performed KEGG pathway
and GO-term enrichment analysis on these transcripts (Fig. 4C-4E). In N2 worms, degradation
of BCAAs and fatty acids were significantly upregulated whereas FOXO signaling pathway
and those associated with peroxisome functions were downregulated by Dox (Fig. 4C). In
CB4856 worms, metabolic processes involved in BCAAs, propionate, and carbons were
upregulated and those involved in base excision repair and sulfur metabolism were
downregulated by Dox (Fig. 4D). We then wondered if there were more similarities in the
mitochondrial gene sets shared between the two strains besides BCAA degradation. Under
Dox, we detected a number of upregulated GO-terms in both worm strains, including those
involved in catalytic activity, oxidation-reduction process, carbon transmembrane transporter
activity, cation transport and mitochondrial inner membrane (Fig. |
4E). The downregulated
mitochondrial genes shared between the two worm strains upon Dox, were mainly enriched
for DNA repair, DNA recombination, and transferase activity transferring acyl-groups (Fig. 4E). 13
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made available under a
CC-BY-NC-ND 4.0 International license . These GO terms were similar to the ones that we detected in co-downregulated gene sets
(Fig. 3E,F), suggesting that the majority of downregulated proteins were related to
mitochondria, which could be a consequence of inhibited mitochondrial translation by Dox. Dox induces triglyceride degradation by lysosomal lipase to sustain energy production
by fatty acid oxidation
In the above-mentioned analysis performed on transcript and protein levels, we detected a
large number of genes directly or indirectly linked to lipid metabolism, such as lipid transport,
lipid catabolism, and mitochondrial fatty acid metabolism. To expand on the characterization
of lipid-related features, we profiled lipids for N2 and CB4856 worms exposed to Dox (Fig. 5,
Supplemental Fig. S5, Supplemental Table S5). As the primary component of lipidomic PCA
was separated by treatment and the second component was separated by strains (Fig. 1D),
we expected to detect more shared and less strain-specific lipidomic changes in the two worm
strains. In total we detected 1,572 lipids that belong to 38 lipid classes, which could be
categorized further into seven main lipid categories consisting of monoacylglycerol lipids,
diacylglycerol lipids, fatty acids/esters, glycerophospholipids, sphingolipids, sterol lipids, and
triacylglycerol lipids (Supplemental Fig. S5A). We then determined the percentage of lipids showing significant changes in each worm strain
upon Dox (Supplemental Fig. S5B,C). Although the overall lipid changes were similar between
the two strains, we detected more decreased lipid species exclusively in the N2 worms (126
reduced lipids), compared to those only lowered in CB4856 worms (31 reduced lipids) upon
Dox (Supplemental Fig. S1A). In addition, about half of the lowered lipids by Dox are TGs, of
which 143 and 105 TGs were decreased in N2 and CB4856 worms, respectively
(Supplemental Table S5). To better understand the overall impact on the lipidomic profiles
upon Dox, we performed overrepresentation analysis on the lipid classes to identify the top
changed lipid species upon Dox in each worm strain (Fig. 5A). Among the top altered lipid
classes, most of them increased in N2 worms upon Dox, including LPE, PC, PA, LPA, DG,
PLC, PE, CE, PS, DG, SM, CL, and PI. Different than those detected in N2 worms, fewer
classes of lipids were increased in CB4856 worms upon Dox, including PE, PA, LPE, CE, PC,
LPA, PS, and PI (Fig. 5A). Intriguingly, three classes of lipids, Cer, TG and PG were lowered
in both worms upon Dox (Fig. |
5A). Notably, the sphingolipids, such as ceramides, hydroxyceramides, sphingomyelins, and
hydroxy-sphingomyelins were significantly altered upon Dox; many of them decreased in both
strains except few hydroxy species which were increased exclusively in CB4856 worms (Fig. 5B,C). Low levels of sphingolipids, especially low ceramides, have been shown to couple with
increased lifespan in C. elegans (Cutler et al. 2014; Huang et al. 2014; Kim et al. 2016) and
14
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doi:
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;
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made available under a
CC-BY-NC-ND 4.0 International license . with caloric restriction in mouse liver (Green et al. 2017). It is therefore not surprising that
these sphingolipids were decreased in both worm strains upon Dox exposure, which
universally increased lifespan. 15
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made available under a
CC-BY-NC-ND 4.0 International license . Figure 5. Lipids were significantly altered in Dox-treated worms. (A) Lipid class over- representation analysis was performed to identify top changes in the lipidomic layer in N2 and CB4856 worms upon Dox exposure. The asterisk (*): indicates the glycerol position sn-2. (B-C) Percentages of increased and decreased lipids in different sphingolipids, including ceramides, hydroxyceramides, sphingomyelins and hydroxy-sphingomyelins in N2 (B) and CB4856 (C) worms upon Dox exposure (p<0.05). A Benjamini-Hochberg corrected p<0.05 was applied to determine statistical significance. (D-E) Changes in different lipid classes, including triglyceride (TG), diglyceride (DG), phosphatidic acid (PA), phosphatidylcholine (PC), phosphatidylethanolamine (PE) and phosphatidylglycerol (PG) in Dox-treated N2 worms compared to N2 controls (D) and in Dox-treated CB4856 compared to CB4856 worms (E). (F) Lysosomal lipase genes are upregulated at transcript level upon Dox in both N2 and CB4856 worms. (G)The majority of acylcarnitines was significantly increased in Dox-treated worms in variant of their genetic background. The dotted-line indicates the significance threshold (p<0.01). Y-axis: number of double bonds; x-axis: number of carbon-chain length. Related to Figure S5 and Table S5. In addition, we also observed some shared features in other lipid species, including increased
level of DG, PA, PC, and PE, and decreased level of TG and PG (Fig. 5A). Although some
TGs with three double bonds slightly increased in both worm strains and alkyl-diacylglycerol
(TG[O]) increased in N2, the majority of the significantly altered TGs were decreased upon
Dox (Fig. |
5D,E). In line with this, we also detected a marked increase of DGs with >2 double
bonds and decrease of those with ≤1 double bond, irrespective of the carbon chain lengths in
Dox-treated worms. This could be due to either enhanced lipolysis of TGs or reduced TG
synthesis. To assess this hypothesis, we checked the changes in the expression of genes
encode the enzymes that are involved in both TG synthesis and breakdown pathways. The
transcripts of genes involved in TG synthesis, i.e. diglycerol acyltransferase dgat-2 and mboa-
2 remained unchanged in both worms upon Dox (Supplemental Table S1), whereas transcripts
of genes involved in TG breakdown, belonging to both adipocyte triglyceride lipase ATGL
family (Srinivasan 2015) and lysosomal lipase family, lipl-1, was upregulated in both worms
upon Dox (Fig. 5F). The transcript of another gene that belongs to the ATGL family, lipl-3, was
upregulated exclusively in CB4856 worms upon Dox. In addition, transcripts of many other
lysosomal lipase genes, including lipl-2, lipl-4, lipl-5, and lipl-6, were higher in CB4856 worms,
and lipl-4, and lipl-6 in N2 worms upon Dox (Fig. 5F). However, in the proteomics analysis,
lipl-2, lipl-5 and lipl-7 abundances were not significantly changed upon Dox (Supplemental
Table S2), suggesting that the regulation of the ATGL family enzymes occurred mainly at the
transcriptional level. We then analyzed the fatty acid and acylcarnitine profiles (Supplemental Fig. S5D,E, and Fig. 5G). In both N2 and CB4856 worms, fatty acids remained largely unchanged upon Dox, except
for increases of two polyunsaturated fatty acids (PUFAs), C18:3 and C20:4, and a decrease
of saturated fatty acid (SFA) C22:0 in N2, and increases of C18:0, C18:1 and C15:1 in CB4856
worms (Supplemental Fig. S5D). Strikingly, we detected a major change in the acylcarnitines
upon Dox in both strains (Fig. 5F), with levels of medium-chain and long-chain acylcarnitines
16
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made available under a
CC-BY-NC-ND 4.0 International license . being largely increased in response to mitochondrial stress. In line with the detection of
upregulated FAO transcripts in both worms upon Dox (Fig. 4A-D), we therefore speculated
that FAO was activated during mitochondrial stress induced by Dox, to produce energy using
fatty acids that were released from TGs by lipolysis. Consistent with this, CPT-1 protein was
significantly upregulated in both strains with Dox treatment (Supplemental Table S2). Dox reduces many metabolites in both N2 and CB4856 strains
As we observed that a large number of metabolic pathways and processes were significantly
altered at both transcript and protein levels upon Dox, we also questioned whether metabolites
involved in these pathways exhibit shared and strain specific variations. |
Intriguingly, the
majority of metabolites (70 out of 79 significantly altered metabolites in N2, 72 out of 80
significantly altered metabolites in CB4856) altered by Dox were significantly reduced in both
N2 and CB4856 (Fig. 6A). Among these metabolites, we detected decreased levels of TCA
cycle intermediates, such as citrate and fumarate. Amino acids that could fuel the TCA cycle
were also decreased, suggesting an overall reduction in TCA cycle activity. Figure 6. Dox reduces metabolite levels in both N2 and CB4856 worms. (A) Volcano plots of the log2 fold change for metabolites (x-axis) against the -Log10 adjusted p-value (y-axis) in N2 (top panel) and CB4856 (lower panel) worms upon Dox. (B) Cellular localization enrichment analysis of the downregulated metabolites (annotated using the Human Metabolome Database IDs (HMDBs)) in N2 and CB4856 worms. (C) Chemical classes enrichment analysis of the downregulated metabolites (annotated using the HMDBs) in N2 and CB4856 worms. For panel B and C, the size of the dots indicates the number of metabolites for that group; the plots are color-coded according to significance (adjusted p-value); level of significance increases from red to blue. Related to Table S6. 17
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made available under a
CC-BY-NC-ND 4.0 International license . To better understand the overall pronounced decrease in the metabolite profiles, we assigned
these metabolites to the cellular components and organelles (Fig. 6B). Not surprisingly, the
most affected organelle in both worm strains was the mitochondria. Other organelles that were
likely affected or associated with the reduced metabolites in both strains were the nucleus,
ER, peroxisomes, Golgi apparatus, and lysosomes. Based on the annotated chemical classes
of the reduced metabolites, pathways involved in nucleotide metabolism, such as pyrimidine
metabolism, which is partly carried out in the mitochondria (Evans and Guy 2004; Loffler et al. 2005; Lane and Fan 2015), explain the pronounced impact on nuclear metabolites. In line with
the reduced metabolic activity upon Dox, these data suggest that nucleotide metabolism and
amino acid metabolism were likely slowed down in both strains, and energy production through
TCA cycle, seem also attenuated in order to cope with mitochondrial stress. Discussion
In this study, we employed a comprehensive systems approach to explore effects of Dox-
induced mitochondrial stress on multiple layers of biology and elucidate the molecular changes
in two wild-type C. elegans strains, i.e. N2 (Bristol) and CB4856 (Hawaii). This included the
integrated analyses of transcripts, proteins, lipids and metabolites collected in these two worm
strains either not exposed or exposed to Dox. |
Through this approach, we uncovered shared
and strain-specific effects of Dox, and important pathways/regulators that are involved in Dox-
induced mitochondrial stress response and lifespan extension. Previously, we have showed
the robust activation of UPRmt by administering Dox to N2 worms (Houtkooper et al. 2013; Li
et al. 2021). It remains, however, unknown whether Dox could also activate the UPRmt and
prolong lifespan in other C. elegans strains. Although CB4856 worms are genetically divergent
and have a shorter lifespan compared with the N2 strain under normal conditions (Doroszuk
et al. 2009; Dingley et al. 2014; Thompson et al. 2015; Banse et al. 2019), we observed a
comparable effect of Dox on the lifespan and respiratory rate in both worm strains. These data
suggest a general and beneficial effect of Dox in terms of lifespan extension. Given the
inherent complexity of certain phenotypes, such as lifespan, we assessed whether Dox
exhibited shared or strain specific effect at different molecular levels. Based on the PCA of
each molecular layer, we noticed that both strain and treatment effects could explain the
majority of the difference at each layer of biological regulation. To better understand the influence of the genetic background in response to mitochondrial
stress, we first explored the genetic variants between the two strains in the control condition. In total, we catalogued 3,658 variants with potential disruptive impact on the protein translation,
that are distributed on six chromosomes of CB4856 compared to the N2 reference. This
number is comparable to the scope of variations detected between these two strains in prior
studies (Thompson et al. 2015; Kim et al. 2019). Genes with these homozygous variants
18
bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.07.20.453059
;
this version posted July 20, 2021.
made available under a
CC-BY-NC-ND 4.0 International license . mostly belonged to the F-box, MATH, BTB-MATH, C-lectins, Cytochrome P450, serpentine
receptor, and nuclear hormone receptor families. Variants that were detected in these families
of genes may lead to impaired defense response, oxidative reduction, and lipid metabolism in
CB4856 worms. This may partly contribute to their shorter lifespan compared to N2 worms
since all these pathways are closely involved in mediation of lifespan (Goudeau et al. 2011;
Kaur and Aballay 2020). At the protein levels, we detected more enriched gene sets in N2
worms for lipid metabolism and defense response, supporting our findings in the variant
analysis. In addition, we detected more significantly changed mRNAs/proteins in our study
compared with a previous study (Kamkina et al. 2016). Difference in the genetic backgrounds of the two worm strains not only influenced molecular
changes at the unstressed condition but also played a vital role upon mitochondrial stress. |
When analyzing either transcriptomic or proteomic data, we observed a number of shared and
strain-specific regulations of different pathways and gene sets. Genes involved in lipid
metabolism, proteolysis and stress response were upregulated in both worms upon Dox at the
transcript level, which is consistent with the results of previous studies activating UPRmt via
other inducers in N2 worms (Liu et al. 2014; Pellegrino et al. 2014; Sorrentino et al. 2017; Liu
et al. 2020; Li et al. 2021). Of note, after we integrated transcriptome and proteome profiles,
we observed more strain-specific alterations upon Dox. In N2 worms, immune and defense
response-associated genes were exclusively upregulated at transcriptomic level, while these
genes were upregulated at both transcriptomic and proteomic levels in CB4856 worms. Upregulation of these genes at both transcriptional and translational levels might be a part of
a compensatory mechanism balancing the defects in gene expression caused by the large
number of disruptive variants present in the CB4856 compared to the N2 worms. In addition,
downregulated proteins also showed to be strain-specific, in which ribonucleoprotein complex
and reproduction-related proteins were exclusively decreased in N2, and cell cycle and
chromosome organization associated proteins were exclusively decreased in CB4856. Our
results validated that blocking mitochondrial translation reduces cytosolic translation and leads
to a detection of reduced level of proteins in both N2 and CB4856 worms as a consequence
(D'Amico et al. 2017; Molenaars et al. 2020). As the primary molecular target of Dox is the mitochondrial ribosome and mitochondrial
translation (Houtkooper et al. 2013), we took a deeper look at the differentially expression
mitochondrial genes at both mRNA level and protein level according to their function and
localization within the mitochondria. At transcript level, we observed a common effect of Dox
on genes involved in various mitochondrial functions. Overall energy-consuming pathways
were attenuated, including mitochondrial translation (Houtkooper et al. 2013), consistent with
reported observations in worms with mitochondrial stress induced by other stressors (Nargund
19
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doi:
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;
this version posted July 20, 2021.
made available under a
CC-BY-NC-ND 4.0 International license . et al. 2015; Melber and Haynes 2018; Li et al. 2021). Moreover, we observed a metabolic
remodeling upon Dox in both worm strains, in which FAO genes were significantly upregulated
in both worm strains, suggesting a switch to lipid breakdown to fuel energy production. This
speculation was further supported by the upregulated transcripts that belong to the ATGL and
lysosomal lipase families, and by the lowered TGs as well as the increased acylcarnitines
levels in both worm strains upon Dox. |
Evidence for enhanced FAO in mitochondrially stressed
worms has been documented by others (Baruah et al. 2014; Liu et al. 2020; Tharyan et al. 2020). Moreover, increased expression of fatty acid b-oxidation gene acs-2 (fatty acyl-CoA
synthetase, (Van Gilst et al. 2005)) in mitochondrial stressed worms was previously shown to
be atfs-1-dependent (Wu et al. 2018), suggesting a specific requirement of FAO upon
mitochondrial stress. Although upregulated lipid metabolism at the transcript level was not
mirrored at the proteomic level, the lipidomic layers still underwent significant alterations in
worms exposed to Dox. Besides TGs, sphingolipids, and PGs were significantly decreased in
both strains. This was accompanied with an increase of DG, PA, PC, PE. In our study, we revealed an overall decrease of metabolites in both worm strains upon
mitochondrial stress, suggesting a global attenuated metabolism by Dox. The majority of these
lowered metabolites were found to be annotated as mitochondrial metabolites, including
amino acids, nucleotides and their derivatives, substrates required for TCA cycles. This result
correlates well with the lowered expression of mitochondrial genes detected in these
pathways. Notably, the lowered nucleotides upon Dox occur concomitantly with the
downregulation of transcripts that are involved in DNA replication and repair in both strains. The progression of the replication machinery requires the polymerization of nucleosides
triphosphate. As such, low abundance of nucleotides can limit DNA synthesis and arrest the
replication process. Likewise, decrease in purine and pyrimidine intermediates may attenuate
DNA replication and nucleoside triphosphate synthesis, which could hence prevent the energy
consumption in DNA replication. Collectively, our comprehensive multi-omics systems approach revealed shared and strain-
specific pathways that are important for mitochondrial stress-induced longevity in two wild-
type worm strains. Effects of Dox-induced mitochondrial stress at different omics layers in the
two different worm strains showed more shared features, suggesting universal benefits of Dox. Our data provide new mechanistic insights in Dox-induced mitochondrial stress, which is
accompanied by a metabolic rewiring that shuts down anabolic processes and favors catabolic
processes including lipid metabolism and TG degradation. This highlights the importance of
lipid metabolism in mitochondrial stress-mediated longevity in genetically divergent worm
strains. 20
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doi:
https://doi.org/10.1101/2021.07.20.453059
;
this version posted July 20, 2021.
made available under a
CC-BY-NC-ND 4.0 International license . Materials and methods
C. elegans strains
The Bristol strain (N2) and Hawaii strain (CB4856) were used as the wild-type strains
obtained from the Caenorhabditis Genetics Center (CGC; Minneapolis, MN). |
Worms were
cultured and maintained at 20 ̊C and fed with E. coli OP50 on Nematode Growth Media (NGM)
plates unless otherwise indicated. Lifespan measurements
Worm lifespan was performed as described previously (Mouchiroud et al. 2011). In brief, 5-10
L4 worms of each strain were transferred onto RNAi plates (containing 2 mM IPTG and 25
mg/mL carbenicillin) or RNAi plates containing 15 µg/mL Doxycycline (Dox, Cat. D9891,
Sigma) seeded with E. coli HT115 bacteria. After the progenies reached the last larval stage
L4, worms were then transferred onto RNAi (or RNAi + 15 µg/mL Dox) plates containing 10
µM 5FU. Approximately 80 worms were used for each condition and scored every other day. 9 independent lifespan experiments were performed. Sample collection for RNA-seq, proteomics, lipidomics and metabolomics analyses
Worms of each strain were cultured on plates seeded with E. coli OP50, then eggs were
obtained by alkaline hypochlorite treatment of gravid adults. A synchronized L1 population
was obtained by incubating the egg suspension in M9 butter overnight at room temperature. Approximately 2000 L1 worms were transferred onto plates with or without 15 µg/mL Dox
seeded with E. coli HT115. L4 worms were harvested after 50 h by three times of washing
with M9 buffer. Tubes containing worm pellets were immediately submerged in liquid nitrogen
for snap freezing and stored at -80ºC until use. Three biological replicates were collected for
each condition. RNA extraction and RNA-seq data analysis
On the day of the extraction, 1 mL of TriPure Isolation Reagent was added to each tube. The
samples were then frozen and thawed quickly eight times with liquid nitrogen and 37 ºC water
bath to rupture cell membranes. RNA was then extracted by using a column-based kit from
Macherey-Nagel. RNA-seq was performed by BGI with the BGISEQ-500 platform. RNA-seq
data analysis was performed using the R package as described previously (Merkwirth et al. 2016). FastQC was used to verify the quality of the mapping (de Sena Brandine and Smith
2019). No low-quality reads were present and no trimming was needed. Alignment was
performed against worm genome (WBcel235 ce11 primary assembly and Ensembl release 89
annotation) following the STAR (version 2.73a) manual guidelines (Dobin et al. 2013). The
obtained STAR gene-counts for each alignment were analyzed for differentially expressed
21
bioRxiv preprint The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
doi:
https://doi.org/10.1101/2021.07.20.453059
;
this version posted July 20, 2021.
made available under a
CC-BY-NC-ND 4.0 International license . genes using the R package edgeR (version 3.24.3) using a generalized-linear model
(Robinson et al. 2010). The trimmed mean of M values (TMM) method was chosen to
normalize the counts and the Cox-Reid common dispersion method for computing the
dispersion parameter (tag wise dispersion was also computed). |
A principal component
analysis was also generated to explore the primary variation in the data (Lê et al. 2008; Risso
et al. 2014). Protein extraction and proteomics analysis
Pellets containing ~2,000 worms were resuspended in 900 µL lysis buffer A (6M Guanidine
hydrochloride, 100 mM Tris pH 8.0), and one large stainless-steel bead was added to each 2
mL tube. Tubes were shaken in a bead miller (Retsch) at 30 Hz continuously for 10 min. Then
the lysates were placed in a sand bath and heated at 95ºC for 10 min. Protein concentrations
of lysates were determined using protein BCA assay (Pierce). To extract proteins, 100 µL of
lysate were added to 900 µL 100% methanol. Tubes were then spun for 7 min at 15,000 rpm,
supernatants were discarded, and protein pellets were allowed to briefly air dry. 50 µL lysis
buffer B (8 M urea, 100 mM Tris, 40 mM TCEP, and 10 mM 2-chloroacetamide) were added
to the pellets, and the tubes were vigorously vortexed for 10 min. LysC (Wako) was added in
1:50 enzyme: protein ratio, and samples were digested overnight at ambient temperature on
a rocker (Fisher Scientific). On the next day, digestion mixtures were diluted down to 1.5 M
urea with addition of 50 mM Tris, pH 8.0. Sequencing grade trypsin (Promega) was added in
1:50 enzyme: protein ratio for further 3 h digestion. Samples were then acidified to pH of ~2
by addition of 10% TFA and desalted using Strata SPE columns (Phenomenex). Desalted
peptides were lyophilized to dryness in a SpeeVac (Thermo), then resuspended in 50 µL 0.2%
formic acid. Final peptide concentrations were determined using Peptide Colorimetric Assay
(Pierce). 1 µg peptides were injected onto an in-house high pressure packed capillary column
(Shishkova et al. 2018), housed at 55 ºC, and separated using Dionex Ultimate 3000 nano
HPLC system (Thermo Fisher) over 120 min gradient at 325 nL/min. Mobile phase A consisted
of 0.2% formic acid in water, and mobile phase B consisted of 0.2% formic acid in 70%
acetonitrile. Eluting peptides were electro-sprayed into and analyzed on Orbitrap Fusion
Lumos mass spectrometer (Thermo Fisher). Orbitrap MS1 scans were collected at resolution
of 240,000 at 200 m/z with an AGC target of 1x106 ions and maximum injection time set to 50
ms. Precursors were isolated in a quadrupole with the isolation window of 0.7 Th. Tandem MS
scans were collected in the ion trap using rapid scan rate, AGC target of 1x104 ions, HCD
fragmentation with NCE of 25, and dynamic exclusion of 20 s. RAW files were searched using
MaxQuant (Cox et al. 2014) against Uniprot database of C. elegans, containing canonical
sequences and isoforms. Unless specified, default settings were used. Protein abundances
were quantified using label-free quantification with count of 1 and match-between-runs
22
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doi:
https://doi.org/10.1101/2021.07.20.453059
;
this version posted July 20, 2021.
made available under a
CC-BY-NC-ND 4.0 International license . |
enabled. MS2 tolerance was set to 0.27 Da. Similar differential analysis was performed as for
the transcriptome layer using the R package edgeR (version 3.24.3) with a generalized-linear
model, similar normalization and principal component analysis methods (Robinson et al. 2010). Lipid extraction and data analyses
Around ~2500 worms were collected in a 2 mL tube and the following amounts of internal
standards dissolved in 1:1 (v/v) methanol:chloroform were added to each sample:
BMP(14:0)2 (0.2 nmol), CL(14:0)4 (0.1 nmol), LPA(14:0) (0.1 nmol), LPC(14:0) (0.5 nmol),
LPE(14:0) (0.1 nmol), LPG(14:0) (0.02 nmol), PA(14:0)2 (0.5 nmol), PC(14:0)2 (0.2 nmol),
PE(14:0)2 (0.5 nmol), PG(14:0)2 (0.1 nmol), PS(14:0)2 (5 nmol), ceramide phosphocholine
SM(d18:1/12:0) (2 nmol) (Avanti Polar Lipid). A steel bead and 1:1 (v/v) methanol:chloroform
was added to each sample to a volume of 1.5 mL. Samples were homogenized using a
TissueLyser II (Qiagen) for 5 min at 30 Hz and centrifuged for 10 min at 20,000 g. The
supernatant was transferred to a 4 mL glass vial and evaporated under a stream of nitrogen
at 45°C. The lipids were dissolved in 150 μL of 1:1 (v/v) chloroform:methanol and lipidomics
analysis was performed as described (Molenaars et al. 2021). In brief, the HPLC system consisted of a Thermo Fisher Scientific Ultimate 3000 binary UPLC
coupled to a Q Exactive Plus Orbitrap mass spectrometer using Nitrogen as the nebulizing
gas. The column temperature was maintained at 25 ◦C. For normal-phase separation, 2 μL lipid extract was injected onto a Phenomenex® LUNA silica, 250×2 mm, 5 µm 100 Åand for
reverse phase 5 μL of each sample was injected onto a Waters HSS T3 column (150×2.1 mm,
1.8 μm particle size). A Q Exactive Plus Orbitrap (Thermo Scientific) mass spectrometer was
used in the negative and positive electrospray ionization mode. In both ionization modes, mass
spectra of the lipid species were acquired by continuous scanning over the range m/z 150-
2000 with a resolution of 280,000 full width at half maximum (FWHM). For quantification of the
data, lipids were normalized to corresponding internal standards according to lipid class, as
well as total protein content in samples, determined using a PierceTM BCA Protein Assay
Kit.The dataset was processed using an in-house developed semi-automated metabolomics
pipeline written in the R programming language (http://www.r-project.org) (Herzog et al. 2016). Similar differential analysis was performed as for the transcriptome and proteome, using the
Bioconductor package limma version 3.42.2 (Ritchie et al. 2015), with a generalized-linear
model, similar normalization and principal component analysis methods. Results of the
statistical tests were corrected for multiple testing using the Benjamini-Hochberg method. Metabolomics analysis
23
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It is
doi:
https://doi.org/10.1101/2021.07.20.453059
;
this version posted July 20, 2021.
made available under a
CC-BY-NC-ND 4.0 International license . Metabolite extraction. Around ~2500 worms were collected in a 2 mL tube. All reagents were
placed on ice and samples were maintained at ≤4°C during extraction procedure. A metal
bead was added to each sample. Next, 500 µL M1 solvent (methyl tert-butyl ether
(MTBE):MEOH=3:1, v/v) was added to each tube and vortexed for 2 min. 325 µL M2 solvent
(H2O:MEOH=3:1, v/v) were added to each tube. Samples were vortexed briefly. Then
samples were flash-freezed in liquid nitrogen and thawed on ice. This step was repeated three
times to facilitate cell breakage. Samples were transferred to a bead-beater and shaken at
1/25 s frequency for 5 min, and this process was repeated 3 times with 5 min interval between
each cycle. The samples were centrifuged for 10 min at 12,500 g at 4˚C. For downstream
metabolomic analysis, 200 µL of the aqueous layer (lower phase) was transferred to glass
autosampler vials and dried down by vacuum centrifugation. Aqueous extracts were stored in
80 ˚C freezer until analysis. Extracts were resuspended in 50 µL 1:1 Acetonitrile:Water and
vortexed for 20 s prior to analysis by LC-MS.
LC-MS metabolomics. Extracted small molecules were separated on a Sequant ZIC®-
pHILIC HPLC column (150 mm x 2.1 mm x 5 µm particle size) at 53 °C using the following
gradient: 95% mobile phase B from 0-2 min, decreased to 30% B over next 16 min, held at
30% B for 8 min, then increased to 95% B over next 1 min, then held at 95% B for next 8 min. Flow rate was 130 µL/min. For each analysis, 2 µL/sample was injected by autosampler. Mobile phase A consisted of 10 mM ammonium acetate in 10:90 (v/v) LC-MS grade
acetonitrile: H2O with 0.1% ammonium hydroxide. Mobile phase B consisted of 10 mM
ammonium acetate in 95:5 (v/v) LC-MS grade acetonitrile: H2O with 0.1% ammonium
hydroxide. 2 µL sample was loaded onto column. The LC system (Vanquish Binary Pump, Thermo Scientific) was coupled to a Q Exactive HF
Orbitrap mass spectrometer through a heated electrospray ionization (HESI II) source
(Thermo Scientific). Source and capillary temperatures were 350 °C, sheath gas flow rate was
45 units, aux gas flow rate was 15 units, sweep gas flow rate was 1 unit, spray voltage was
3.0 kV for both positive and negative modes, and S-lens RF was 50.0 units. The MS was
operated in a polarity switching mode; with alternating positive and negative full scan MS and
MS2 (Top 10). Full scan MS were acquired at 60K resolution with 1 x 106 automatic gain
control (AGC) target, max ion accumulation time of 100 ms, and a scan range of 70-900 m/z. MS2 scans were acquired at 45K resolution with 1 x 105 AGC target, max ion accumulation
time of 100 ms, 1.0 m/z isolation window, stepped normalized collision energy (NCE) at 20,
30, 40, and a 30.0 s dynamic exclusion. Metabolomics data analysis. Data processing was done using Compound Discoverer 3.1
(Thermo Scientific) with untargeted metabolomic study workflow. |
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