Abstract
Insulin/IGF-1 Signaling (IIS) is known to constrain longevity by
inhibiting the transcription factor FOXO. How phosphorylation mediated
by IIS kinases regulates lifespan beyond FOXO remains unclear. Here, we
profile IIS-dependent phosphorylation changes in a large-scale
quantitative phosphoproteomic analysis of wild-type and three IIS
mutant Caenorhabditis elegans strains. We quantify more than 15,000
phosphosites and find that 476 of these are differentially
phosphorylated in the long-lived daf-2/insulin receptor mutant. We
develop a machine learning-based method to prioritize 25 potential
lifespan-related phosphosites. We perform validations to show that
AKT-1 pT492 inhibits DAF-16/FOXO and compensates the loss of daf-2
function, that EIF-2α pS49 potently inhibits protein synthesis and
daf-2 longevity, and that reduced phosphorylation of multiple germline
proteins apparently transmits reduced DAF-2 signaling to the soma. In
addition, an analysis of kinases with enriched substrates detects that
casein kinase 2 (CK2) subunits negatively regulate lifespan. Our study
reveals detailed functional insights into longevity.
Subject terms: Proteomic analysis, Machine learning, Ageing,
Phosphorylation
__________________________________________________________________
How phosphorylation mediated by Insulin/IGF-1 Signaling kinases
regulates lifespan remains unclear. Here the authors perform a
large-scale quantitative phosphoproteomic analysis of wildtype and IIS
mutant C. elegans strains to reveal detailed functional insights into
longevity.
Introduction
Despite the great diversity of lifespan in the animal kingdom, there
exist ancient genetic pathways that regulate lifespan across
species^[46]1,[47]2. The best known example is insulin/insulin-like
growth factor 1 (IGF-1) signaling (IIS; see abbreviation in
Supplementary Table [48]1). Polymorphisms of the component genes of
this pathway are tightly associated with human longevity^[49]2.
Disrupted IIS can extend lifespan up to tenfold in Caenorhabditis
elegans^[50]3. The canonical IIS pathway of C. elegans comprises
insulin-like ligands, the insulin/IGF-1 receptor tyrosine kinase DAF-2,
the phosphatidylinositol-3-OH kinase (PI3K) AGE-1, the serine/threonine
(S/T) kinases PDK-1, AKT-1, and AKT-2, and a downstream transcription
factor (TF) DAF-16, which is the C. elegans homolog of human
FOXO^[51]4. Inhibiting the IIS kinases leads to nuclear translocation
of DAF-16, transcriptional activation of the target genes of DAF-16,
and ultimately lifespan extension. While DAF-16 is required for
IIS-mediated lifespan extension, recapitulating the daf-2 longevity to
its fullness requires more than DAF-16 overexpression or nuclear
translocation^[52]4.
Deep profiling of the C. elegans transcriptomes and proteomes made
clear that age-dependent protein abundance changes poorly correlated
with mRNA abundance changes^[53]5,[54]6. Comparing the wild-type (WT)
and the long-lived daf-2 mutant, a subset of proteins that were
markedly upregulated or downregulated in the latter were not found to
exhibit corresponding changes in the abundance of their mRNA templates.
Changes in these proteins affect known lifespan modulators, such as
components of the translational machinery^[55]7–[56]9. The above
evidence indicates that lifespan regulation involves not only
transcriptional mechanisms but also translational or posttranslational
mechanisms.
Protein phosphorylation, among various posttranslational modifications
(PTMs), is a fundamental mechanism that mediates IIS. The IIS kinases
AKT-1 and AKT-2 prevent lifespan extension by sequestering DAF-16 in
the cytoplasm^[57]4. Other kinases such as JNK-1/JNK, CST-1/MST1, and
AAK-2/AMPK contribute to daf-2 longevity partly by promoting nuclear
translocation of DAF-16^[58]4, although it has not been proven that
these kinases directly phosphorylate DAF-16 in vivo. Protein
phosphatases also modulate daf-2 longevity. For example, PPTR-1, a
regulatory subunit of PP2A, reduces the phosphorylation of AKT-1 T350
and renders AKT-1 less active^[59]10. PP4^SMK-1 dephosphorylates the
transcriptional regulator SPT-5/SUPT5H, which facilitates DAF-16
activity in daf-2 worms^[60]11. However, only a handful of phosphosites
are known to be involved in lifespan regulation^[61]12–[62]16, and no
large-scale studies of IIS-related phosphorylation events are reported
for C. elegans. To date, the number of identified phosphosites has
reached 119,809 for human proteins but only 10,767 for C.
elegans^[63]17,[64]18. Clearly, the C. elegans system has not benefited
from advanced phosphoproteomic analysis based on liquid
chromatography-tandem mass spectrometry (LC-MS/MS).
Here, in the processing of comparing the long-lived daf-2 mutant to WT,
the daf-16 mutant, and the daf-16; daf-2 double mutant using
quantitative phosphoproteomics based on metabolic labeling, we surveyed
the landscape of protein phosphorylation in C. elegans. In total, we
identified 15,443 phosphosites, which included 9949 newly identified
ones and doubled the database of C. elegans phosphosites. To identify
functionally important phosphosites in C. elegans, we developed a
machine learning method named inference of functional phosphosites
(iFPS). From 476 phosphosites differentially regulated by IIS, iFPS
prioritized 25 of these to be potentially related to lifespan
regulation. Furthermore, we examined the functions of three
high-priority phosphosites and validated that they all had notable
roles in lifespan regulation. Briefly, we added an
element—phosphorylation of AKT-1 T492—to the negative feedback
regulation mechanism of IIS. We also uncovered two signaling branches
downstream of DAF-2: phosphorylation of eukaryotic initiation factor
(EIF)-2α S49 by GCN-2 and phosphorylation of CDK-1 T179. The former,
which inhibits translation and promotes longevity, is upregulated in
the daf-2 mutant; the latter, which promotes germ cell proliferation
and limits longevity, is downregulated in the daf-2 mutant. Globally,
enrichment analysis and subsequent validation experiments highlighted
the germline as a target tissue of IIS. We also statistically detected
kinases with enriched substrates and found that casein kinase 2 (CK2),
whose subunits are encoded by kin-3 and kin-10, acts to limit lifespan.
Results
Profiling the C. elegans phosphoproteome using an advanced LC-MS/MS workflow
The phosphoproteome of C. elegans has not been surveyed rigorously.
Seeking to increase the coverage of the C. elegans phosphoproteome
while aiming for high accuracy in both identification and
quantification of phosphopeptides, we combined multiple technical
elements and optimized the analytical workflow (Fig. [65]1a). These
technical elements included extensive high-pH reverse phase
fractionation coupled with interval pooling^[66]19, polyMAC-Ti
enrichment of phosphopeptides^[67]20, high-speed and accurate-mass
MS/MS, and stable isotope (^15N) metabolic labeling, which is a highly
accurate quantitative proteomics strategy (Fig. [68]1a).
Fig. 1. Characterization of the C. elegans phosphoproteome.
[69]Fig. 1
[70]Open in a new tab
a Phosphoproteomics profiling of WT and IIS mutants by advanced
techniques, including extensive high-pH reverse phase fractionation
followed by interval pooling, polyMAC-Ti enrichment of phosphopeptides,
as well as high-speed, accurate-mass mass spectrometry. Phosphopeptides
from synchronized adult day 1 worms were quantified against a
stable-isotope-labeled internal reference (introduced via feeding WT
worms entirely on ^15N-labeled E. coli cells). b The identification
scope of this study: 9949 of the 15,443 high-confidence phosphosites
identified here were not present in the latest release of the C.
elegans phosphosite database (dbPAF). c Phosphorylation of C. elegans
IIS proteins. Phosphosites identified in this study are displayed with
S or T (serine or threonine), followed by their residue number. Dark
blue highlights 17 phosphosites that were not collected in dbPAF. d The
DAF-16, isoform h protein, as an example to illustrate phosphoisoforms
derived from the identified tryptic phosphopeptides. pT^343 pS^348 and
pS^345 pS^348 are phosphoisoforms that carry two phosphosites. A
phosphorylation hotspot was observed outside of the DAF-16 Forkhead
domain. Only pS345 is positioned within a consensus sequence
(RPRTQS^345) that matches the known AKT-1 phosphorylation consensus
motif (RxRxxS/T).
From WT C. elegans and the IIS mutants (daf-2, daf-16, and the daf-16;
daf-2 double mutant)—each analyzed in three or four biological
replicates with two technical replicates—we identified a total of
15,443 phosphosites with >0.75 PhosphoRS site probability^[71]21, a
commonly used threshold to ensure the quality of phosphosite assignment
(Supplementary Fig. [72]1a, b). These phosphosites were located at
22,536 phosphopeptides or 15,723 phosphoisoforms that belonged to 4418
unique proteins (Supplementary Fig. [73]1b, c). By comparison, 9949
phosphosites identified in this study were not covered by dbPAF, a
comprehensive database dedicated to collecting known phosphosites in
human, animals, and fungi^[74]17. Notably, the addition of these newly
identified phosphosites was close to doubling the current collection
for C. elegans (Fig. [75]1b). The phosphosites identified in our study
were of high quality as indicated by the following statistics: 5.01
MS/MS spectra per phosphopeptide on average, and ≥2 MS/MS spectra for
16,263 phosphopeptides (72.16% of the total) (Supplementary
Fig. [76]1d); 68.49% of the phosphosites were identified in at least 2
samples, and on average a phosphosite was identified in 4.72 samples
(Supplementary Fig. [77]1e).
Although it is well established that phosphorylation is the primary
means by which the IIS pathway transmits signals, very little is known
about which sites are phosphorylated, even for the core components of
C. elegans IIS. For example, dbPAF contained no phosphosites for the
PI3K AGE-1. Here, our phosphoproteomic analysis uncovered 32
phosphosites in 10 C. elegans IIS proteins, 17 of which have not been
reported previously (Fig. [78]1c). These unreported and highly
confident phosphosites (Fig. [79]1c, dark blue) were distributed
throughout the IIS pathway, from the upstream insulin-like ligands to
the downstream TF DAF-16—a homolog of mammalian FOXO, and for every
kinase in between. Besides DAF-16, IIS-mediated lifespan extension
requires TFs including SKN-1/Nrf^[80]22, HSF-1^[81]23,
ELT-2/GATA^[82]24, PQM-1^[83]25, HLH-30^[84]26, and FKH-9^[85]27. The
mammalian homologs of those TFs are often regulated by phosphorylation.
Here, for HLH-30, we uncover a cluster of phospho-serine residues
preceding the HLH motif (Supplementary Fig. [86]1f). Additionally,
eight phosphosites were found on HSF-1 and two on FKH-9 (Supplementary
Fig. [87]1f). Thus, our phosphoproteomic profiling could serve as a
useful resource for further analysis regarding phosphorylation in C.
elegans.
Phosphorylation changes resulted from genetic disruption of IIS
More than 15,000 phosphopeptides were quantified against their
^15N-labeled cognate peptides, which were introduced as an internal
reference standard by feeding C. elegans on ^15N-labeled bacteria
(Supplementary Figs. [88]1b and [89]2a and Supplementary Data [90]1).
These peptides represented 10,705 quantifiable phosphoisoforms, about a
quarter of which carried combinatorial information for two or more
phosphosites. A total of 2656 phosphoisoforms were quantified across
all four genotypes (Supplementary Fig. [91]2b). We performed principal
component analysis (PCA) on the quantitation values of 400
phosphoisoforms quantified across all 15 samples. The results showed
that the daf-2 replicates were obviously distinct from all other
samples, while the WT, daf-16, and daf-16; daf-2 replicates were not
clearly separated (Supplementary Fig. [92]2c). We further calculated
the Spearman correlation coefficients pairwise, which involved
thousands of phosphoisoforms in each comparison. The subsequent
clustering analysis showed again that the long-lived daf-2 worms were
distinctly different from those without a longevity phenotype
(Supplementary Fig. [93]2d).
Disrupting the activity of IIS induced abundance changes on 501
phosphoisoforms (>1.5-fold in at least one of the IIS mutants relative
to WT), including 333, 178, and 270 phosphoisoforms from the daf-2,
daf-16, and daf-16; daf-2 mutant samples, respectively. Based on the
one-sided hypergeometric test, we conducted pathway enrichment analysis
for these changed phosphoisoforms, using the pathway annotations of
Kyoto Encyclopedia of Genes and Genomes (KEGG)^[94]28 (Supplementary
Fig. 2e, f, E-ratio > 1, p < 0.05). As expected, the FOXO signaling and
longevity-related pathways were overrepresented in the daf-2 mutant
only (Supplementary Fig. [95]2e). Glycerolipid metabolism, ribosome,
and glycerophospholipid metabolism were also overrepresented in the
daf-2 mutant but not in the daf-16 or daf-16; daf-2 mutant, suggesting
that phosphorylation of proteins in these pathways is regulated by
daf-2 in a DAF-16-dependent manner (Supplementary Fig. [96]2e).
By analyzing the hypo- or hyper-phosphoproteins separately, we found
that proteins involved in RNA transport had low phosphorylation levels
in both the daf-2 and daf-16; daf-2 mutants, indicative of
phosphorylation that depends on daf-2 but not daf-16 (Supplementary
Fig. [97]2f). Notably, hypo-phosphorylated sites may be either directly
or indirectly targeted by IIS, whereas hyper-phosphorylated sites are
surely indirectly related to IIS. Proteins with upregulated
phosphorylation in the daf-2 mutant were enriched in glycerolipid
metabolism and glycerophospholipid metabolism (Supplementary
Fig. [98]2f). Upregulation of lipid metabolisms is a major phenotype of
daf-2 mutants^[99]4. Phosphorylation changes, along with changes of
gene expression^[100]24,[101]29 and protein abundance^[102]8, might
contribute to the lipid metabolism phenotype of the daf-2 worms.
Taken together, these above analyses show that this is a high-quality
quantitative phosphoproteomic data set and it will be informative for
understanding IIS and, more broadly, regulation of protein
phosphorylation.
Development of iFPS to prioritize highly potential lifespan-related
phosphosites (LiRPs)
A bottleneck in the present-day biomedical research is the lack of
efficient methods for extracting useful information from omics
data^[103]30,[104]31. To facilitate the translation of
phosphoproteomics data into biological insights, we developed a machine
learning-based method named iFPS (Fig. [105]2a, see “Methods”). In
iFPS, five frequently used sequence and structure features were
integrated to evaluate the functionality of a candidate phosphosite,
including the number of predicted upstream kinase families
(UKFs)^[106]18,[107]32, the phosphorylation conservation
(PhC)^[108]18,[109]30,[110]32,[111]33, acetylation site co-occurrence
(ASC) nearby the phosphosite^[112]18, and predicted relative surface
accessibility (RSA)^[113]18 as well as secondary structures (SSs) of
the phosphosite^[114]18,[115]32 (Supplementary Fig. [116]3a–h). Also,
we added another structural feature, the number of interacting domains
and/or motifs (IDMs) that harbor phosphosites (Supplementary
Fig. [117]3c). From the literature, 121 known worm phosphosites were
collected and taken as the positive data set, whereas the negative data
set was prepared by randomly selecting samples from other worm
phosphosites in dbPAF^[118]17 (Supplementary Data [119]2). The
algorithm of multinomial logistic regression was used for feature
integration and model training, with an area under the curve (AUC)
value of 0.8784 [95% confidence interval (CI) = 0.8408–0.9129] though
the tenfold cross-validation (Fig. [120]2b).
Fig. 2. Discerning functionally relevant clues from the phosphoproteome.
[121]Fig. 2
[122]Open in a new tab
a Schematic diagram illustrating the design of iFPS, which employs
multinomial logistic regression from machine learning to integrate six
features and predict the functionally impactful phosphosites in C.
elegans. iFPS inference of functional phosphosites, UKF upstream kinase
family, PhC phosphorylation conservation, RSA relative surface
accessibility, ASC acetylation site co-occurrence, SS secondary
structure, IDM interacting domain and/or motif, RCR residue
conservation ratio, CMGC/AGC/CDK/CAMK kinase groups, HMMER software
that predicts functional domain, 3did database of three-dimensional
interacting domains, Phos phosphorylation, Ac acetylation. b Prediction
power (AUC, area under the curve) of different models. One hundred and
one known functional phosphosites and 605 randomly phosphosites from
dbPAF served as the training data set. Tenfold cross-validations were
performed. The iFPS model, which integrated six features, was superior
to models constructed from individual feature. c Phosphorylation
changes in the long-lived daf-2 mutant compared to the WT control (see
“Methods”). Phosphoisoforms quantified at least three times in both
daf-2 and WT control were subjected to statistical comparison. The
log[2][median of (^14N/^15N)[daf-2])/median of (^14N/^15N)[control]]
values and the log[10](p value, Wilcoxon rank-sum test) of
phosphoisoforms were plotted on the x axis and y axis, respectively.
Dots (n = 2365 phosphoisoforms) met the criteria of [log2(fold change)
beyond 1.5× SD and one-tailed p value < 0.05] or [log2(fold change)
beyond 1.0× SD and two-tailed p value < 0.05] are colored in red
(hyper-phosphorylated) or green (hypo-phosphorylated). AKT-1 pT492,
EIF-2α pS49, and CDK-1 pT179 are functionally validated in this study.
See statistics in Source data. d Prioritizing the daf-2-regulated
phosphosites by iFPS ranking. The daf-2-regulated phosphosites that
ranked among the top 5% highest scoring iFPS phosphosites are shown.
Proteins were grouped by KEGG ontology or function annotations recorded
in WormBase release WS275. Royal blue marks the lifespan-regulating
proteins. Red colors the upregulated phosphoisoforms. Green colors the
downregulated phosphoisoforms. The daf-2/WT values are the relative
phosphorylation levels of phosphoisoforms in daf-2 compared to WT.
Next, iFPS was applied to score all the identified phosphosites, which
covered 31 known functional phosphosites from the positive data set
(Supplementary Data [123]2). The distribution of iFPS scores showed
that known functional phosphosites ranked higher than other
phosphosites (Supplementary Fig. [124]3i). Then we focused on
identifying potential LiRPs regulated by daf-2. The phosphoisoforms
quantified at least three times in both the daf-2 mutant and the WT
control (see “Methods”) were subjected to statistical analysis. This
led to a finding of 212 downregulated and 196 upregulated
phosphoisoforms, which corresponded to 476 phosphosites, upon reduction
of daf-2 activity (Fig. [125]2c). By overlapping the 476 phosphosites
and the top 5% highest scoring iFPS phosphosites (Supplementary
Data [126]3), we identified 25 LiRPs (Fig. [127]2d). These sites are
obviously not a random set because the majority of the proteins
harboring these sites function in FOXO signaling, translation
initiation/ribosome biogenesis, or cell cycle regulation. Furthermore,
14 out of the 25 predicted LiRPs belong to 8 proteins that are known to
regulate lifespan according to the phenotypic data taken from WormBase
release WS275. These proteins are AAK-2, AKT-1, CDK-1, DAF-16, EGL-45,
MLT-3, PDHA-1, and PPFR-1. Of note, LiRPs on AAK-2, the catalytic
subunit of C. elegans AMPK, were differentially regulated in the daf-2
mutant: phosphorylation of S570, T597, and S601 increased, whereas S553
decreased.
The functions for most of the predicted LiRPs remain uncharacterized.
In lifespan regulation, only S345 of DAF-16, a conserved AKT site, has
been implicated: simultaneous mutation of S345 and other three
predicted AKT sites induced nuclear accumulation of DAF-16, much like
in the daf-2 mutant but without the extraordinary longevity
phenotype^[128]13. To experimentally validate iFPS predictions and to
flesh out the mechanism of lifespan extension by protein
phosphorylation in response to reduced insulin signaling, we focused on
phosphosites within the three prominent protein function groups for
in-depth functional analysis. Among the FoxO signaling group, we were
interested in AKT-1 pT492 because of its unexpected
hyper-phosphorylation upon reduction of daf-2 activity. In the other
two groups, we chose to validate phosphorylation changes on EIF-2α—a
key component of translation initiation machinery, and CDK-1—a master
regulator of cell cycle. The corresponding phosphosites on human eIF2α
or CDK1 are known to regulate protein synthesis^[129]34 or cell
division^[130]35, respectively. It is not clear whether these
phosphosites or phosphorylation events are related to IIS and lifespan.
Constitutive phosphorylation of AKT-1 T492 promotes AKT-1 activity
pT492 of worm AKT-1 corresponds to pT450 of human AKT-1 (Fig. [131]3a).
This LiRP is positioned in a highly conserved turn motif near the AKT-1
C-terminus, and work in mammalian cells has shown that this site is
co-translationally phosphorylated by mammalian target of rapamycin
complex 2 (mTORC2), supporting the notion that this site may stabilize
newly synthesized AKT^[132]36,[133]37. However, the functional impact
of this site has not been confirmed.
Fig. 3. Constitutive phosphorylation of AKT-1 T492 compensates for loss of
daf-2.
[134]Fig. 3
[135]Open in a new tab
a Schematic of the protein structure of worm AKT-1, isoform a. AKT-1
pT492 is conserved with human AKT1 pT450, an mTORC2 target site.
Sequences were aligned via the UniProt website tool
([136]https://www.uniprot.org/align/). PH Pleckstrin Homology domain,
Pkinase protein kinase domain. b Phosphorylation on AKT-1 T492 is
constitutive. MS-based quantification of target peptides indicated that
daf-2(lf) significantly enhanced the levels of both the AKT-1 pT492 and
AKT-1 proteins, doing so in a DAF-16-dependent manner. In contrast,
endogenous unphosphorylated AKT-1 T492 peptides were not detected.
Peptides were quantified against isotopically labeled synthetic
peptides spiked into whole-worm lysates. n.d. not detected. *p < 0.05,
**p < 0.01, ***p < 0.001, mutant versus WT, two-tailed Student’s t
test, error bars denote the SEM. See statistics and biologically
independent results in Source data. c AKT-1 T492 phosphorylation
partially requires CeTORC2. Human AKT1 is phosphorylated on T450 and
stabilized by mTORC2. MS-based target quantification showed that
phosphorylation on AKT-1 T492 decreased by 40% in rict-1(ft7) worms,
while AKT-1 protein levels were not affected. NS p = 0.57,
***p = 4.6e-5, mutant versus WT, two-tailed Student’s t test, error
bars denote the SEM. Representative data from n = 3 independent
experiments. See statistics in Source data. d AKT-1 T492A induced
nuclear accumulation of DAF-16. Representative images show endogenous
DAF-16::GFP cellular localization in intestinal cells of worms growing
for 6–10 h after the L4 stage. ***p < 0.001, mutant versus WT,
two-sided Fisher exact test. WT (n = 64), hqKi245 (n = 58), hqKi246
(n = 64). Scale bar: 30 µm. e AKT-1 T492A significantly extended the
lifespan of C. elegans. ***p < 0.001, two-sided log-rank test, n > 70
worms per strain. Lifespan assays were performed at 20 °C, with
50 ng/μl FUdR supplied in plates. See survival statistics in
Supplementary Dataset 4. f A model illustrates the IIS feedback
regulation at the AKT-1 level. akt-1 mRNA data, from Son et
al.^[137]41.
Verifying the earlier suggestion, we found that phosphorylation of C.
elegans AKT-1 on T492 is constitutive. The AKT-1 protein and T492
phosphorylation levels both doubled in the long-lived daf-2 mutant
(FC = 2.2–2.4, daf-2/WT), as measured by shotgun proteomics
(Fig. [138]2d and Supplementary Data [139]3) and by targeted
quantitation assays using synthesized peptides bearing isotope labels
(Fig. [140]3b). Whereas the T492-containing peptide of AKT-1 was
undetectable in any of the four strains analyzed (Fig. [141]3b), the
pT492-containing peptide of AKT-1 was readily detectable, and its
abundance change followed that of the AKT-1 protein very closely. Thus,
the T492 site is apparently constitutively phosphorylated following
ATK-1 translation.
Utilizing the same targeted quantitation assay, we found that the C.
elegans TOR complex 2 (CeTORC2) is involved in phosphorylating AKT-1
T492. RICT-1, the only homolog of human RICTOR defines CeTORC2^[142]38
(Fig. [143]3c). We found that a loss-of-function mutation of rict-1
reduced AKT-1 T492 phosphorylation by 40% without affecting the AKT-1
protein level (Fig. [144]3c). In line with this result, the
unphosphorylated AKT-1 T492 peptide, which was undetectable in WT
worms, became detectable in the rict-1(lf) mutant (Supplementary
Fig. [145]4). We thus conclude that AKT-1 T492 is a substrate
phosphosite of CeTORC2 and that AKT-1 may exist stably in the absence
of this constitutive phosphorylation on T492.
We used CRISPR/Cas9 to produce a T492A AKT-1 variant. Compared to the
WT worms, those expressing the non-phosphorylatable T492A AKT-1 variant
exhibited diverse phenotypes: akt-1-T492A mutant worms resembled weak
IIS loss-of-function mutants such as akt-1(lf) or weak alleles of
daf-2(lf). AKT-1-T492A caused nuclear accumulation of DAF-16::GFP in
the intestinal cells of nearly 60% of the worms, representing a sixfold
increase from the 9% detected in the WT animals (Fig. [146]3d) and
indicating that phosphorylation of T492 promotes AKT-1’s ability to
phosphorylate and thereby inhibits DAF-16. Consistently, the T492A
mutation moderately but significantly extended the lifespan of WT worms
by 8–17% (Fig. [147]3e and Supplementary Fig. [148]5a). Notably,
whereas akt-1(null) strongly induced dauer arrest at 27 °C^[149]39,
AKT-1-T492A did not (Supplementary Fig. [150]5b). However, the T492A
mutation did enhance the dauer formation phenotype in the sensitized
background of daf-2(e1370) at 21 °C (Supplementary Fig. [151]5b).
To determine whether the loss-of-function phenotypes resulting from the
T492A mutation were caused by destabilization of AKT-1, we generated
knock-in strains to express either AKT-1::GFP or AKT-1-T492A::GFP. Both
fusion proteins were seen in nearly all examined tissues, with no
discernable difference in green fluorescent protein (GFP) intensity
(Supplementary Fig. [152]5c, d), suggesting that T492A imparts no or
little destabilizing effect on AKT-1 in WT animals. However, we did
observe an effect related to the subcellular localization of AKT-1. In
the oocytes, AKT-1-T492A::GFP was detected only in the nucleus, whereas
AKT-1::GFP was detected throughout the cytoplasm (Supplementary
Fig. [153]5e). This T492A-induced localization change for AKT-1 was
limited to the germline with 84% penetrance. Since AKT-1 is normally
recruited to the plasma membrane where it transmits signals from
receptor tyrosine kinases such as DAF-2, loss of cytosolic AKT-1 may
partially account for the observed loss-of-function effect of the T492A
mutation. These results showed that mutation of T492 to alanine impairs
the correct localization of AKT-1, which may lessen the inhibition of
DAF-16 by AKT-1 and lead to a longer lifespan as well as a higher
propensity for dauer formation. Thus, in WT animals, constitutive
phosphorylation of T492 promotes the function of AKT-1.
AKT-1 is controlled by a negative feedback loop at the gene
transcription level; that is, the expression of the akt-1 gene is
positively regulated by DAF-16^[154]40, while DAF-16 itself is
negatively regulated by AKT-1. In the long-lived daf-2 mutant,
activated DAF-16 induces transcription of akt-1, although the akt-1
mRNA level is elevated by only 10%^[155]41. However, this elevation is
strikingly higher when examined at the protein level: the AKT protein
level is elevated by around 140% as measured by quantitative
proteomics^[156]6, a finding validated by epifluorescence of AKT-1::GFP
in the present study (Supplementary Fig. [157]5f, g). daf-2(lf) also
enhanced the expression of AKT-1::GFP and that of AKT-1-T492A::GFP in a
daf-16-dependent manner (Supplementary Fig. [158]5f, g). To sum up, our
phosphoproteomics analysis thus revealed T492 phosphorylation as a
previously unknown layer of regulation in a complex regulatory network.
Recalling that AKT-1 is phosphorylated at T492 immediately following
its translation and that this PTM promotes AKT-1 activity, our work at
the phosphoproteomics level underscored how a negative IIS feedback
loop is intricately controlled at multiple regulatory layers, including
gene transcription, protein synthesis, and posttranslational regulation
(Fig. [159]3e).
EIF-2α pS49 potently regulates protein synthesis and lifespan in the daf-2
mutant
Downregulation of the processes that support protein synthesis (e.g.,
translation initiation and ribosome biogenesis) has been associated
with longevity in previous studies^[160]42,[161]43. The same
downregulation trend was evident in our phosphoproteomics data:
phosphorylation of multiple EIFs was generally reduced in the
long-lived daf-2 mutant (Supplementary Fig. [162]6a). The only
exception to this trend was EIF-2α. Phosphorylation of EIF-2α at S49,
which was an iFPS-prioritized site (Fig. [163]2d), nearly doubled in
the daf-2 mutant relative to WT worms (Fig. [164]4a), and this was
verified by the immunoblotting assay (Fig. [165]4b).
Fig. 4. EIF-2α pS49 is a potent regulator of translation and lifespan in
daf-2.
[166]Fig. 4
[167]Open in a new tab
a Phosphoproteomics data showed that EIF-2α S49, corresponding to human
eIF2α S51, is hyper-phosphorylated in the daf-2 mutant. Model
illustrates that phosphorylation on the α-subunit of human eIF2 by
kinases including GCN-2, PERK, HRI, and PKR prevents the formation of
translation preinitiation complex and results in repression of global
protein synthesis. b Immunoblotting analysis confirmed the
hyper-phosphorylation on EIF-2α S49 in the adult day 1 daf-2(e1370)
worms. WT or daf-2 worm lysates were immunoblotted with a
phospho-specific antibody that recognizes EIF-2α pS49 or with an
antibody specific to the EIF-2α total protein. NS p = 0.085,
**p = 0.0019, n = 3 technical replicates, two-tailed Student’s t test,
error bars denote the SEM. See biological replicates in Source data. c
Polyribosome profiles of the WT, daf-2(e1370), or eif-2α-S49A(hqKi188);
daf-2(e1370) worms harvested at adult day 1. hqKi188 was generated
using CRISPR/Cas9 technology. Worm lysates with the same amount of
total proteins were separated by sucrose gradient centrifugation and
analyzed with the absorbance recording at OD 254 nm. See biological
replicates in Source data. d Phosphorylation of EIF-2α S49 contributes
to daf-2 longevity. eif-2α-S49A(hqKi188) mutation and EIF-2α kinase
mutation gcn-2(ok886) significantly shortened the lifespan of the
daf-2(e1370) worms but did not disturb the WT lifespan. ***p < 0.001,
NS not significant, two-sided log-rank test, n > 80 worms per strain.
Lifespan assays were performed at 20 °C, with 50 ng/μl FUdR supplied in
plates. See statistics and the FUdR-free results in Supplementary
Data [168]4. e Immunoblotting showing the level of EIF-2α pS49 and
EIF-2α total protein in the daf-2(e1370), gcn-2(ok886); daf-2(e1370),
or daf-2(e1370); pek-1(ok275) mutants harvested at adult day 1. The
ratios of EIF-2α pS49 intensity, normalized to the EIF-2α total protein
level, are presented below. n = 2 independent experiments. In both
trials, through comparing to daf-2, EIF-2α pS49 was markedly decreased
in gcn-2; daf-2 but mildly reduced in daf-2; pek-1. f A model
illustrates that IIS regulates EIF-2α S49 phosphorylation through
GCN-2. EIF-2α pS49 potently inhibits protein synthesis and contributes
substantially to daf-2 longevity.
C. elegans EIF-2α S49 is a highly conserved site and is equivalent to
human eIF2α S51, whose phosphorylation is known to block global mRNA
translation^[169]34,[170]44 (Fig. [171]4a). We thus asked whether mRNA
translation is suppressed in the daf-2 mutant through
hyper-phosphorylation of EIF-2α S49. We engineered an EIF-2α S49A
mutation in the C. elegans genome using a CRISPR/Cas9-mediated
gene-editing method. Indeed, the S49A mutation, which locked EIF-2α in
the dephosphorylation state, markedly increased the polyribosome
fraction in the daf-2 mutant, albeit short of restoring it to the WT
level (Fig. [172]4c). Further, the EIF-2α S49A mutation, which had no
effect on WT lifespan, suppressed daf-2 longevity by 30%
(Fig. [173]4d). Similar effects were observed for worms with
overexpressed eif-2α-S49A::gfp (Supplementary Data [174]4). These
results suggested that enhanced phosphorylation of EIF-2α S49 in the
daf-2 mutant may promote longevity by suppressing protein synthesis.
Next, we asked which kinase was responsible for hyper-phosphorylation
of EIF-2α S49 in the daf-2 mutant. Mammalian eIF2α S51 may be
phosphorylated by PERK, GCN2, HRI, or PKR^[175]34, among which only
PERK and GCN2 have orthologs in C. elegans. We found that the gcn-2(lf)
mutation significantly reduced EIF-2α S49 phosphorylation in the daf-2
mutant, while deletion of pek-1 had a weaker effect (Fig. [176]4e).
Consistently, gcn-2(lf) or RNA interference (RNAi) of gcn-2 suppressed
daf-2 longevity (Fig. [177]4d and Supplementary Data [178]4), whereas
pek-1(null) did not (Supplementary Fig. [179]6b). Therefore, we
concluded that the GCN-2 kinase is responsible for the increased
phosphorylation of EIF-2α S49 we observed in the daf-2 mutant and that
GCN-2-mediated hyper-phosphorylation of EIF-2α S49 slows down protein
synthesis in the daf-2 mutant to delay ageing.
Of note, two lines of evidence suggested that phospho-EIF-2α had a
potent effect. First, a tiny amount of EIF-2α pS49, so low that it was
undetectable by LC-MS/MS unless the phosphopeptides were enriched
beforehand, is sufficient to generate the protein synthesis and
lifespan phenotype. The S49 containing peptide generated by trypsin
digestion from endogenous EIF-2α was only detectable and quantifiable
by LC-MS/MS in the non-phosphorylated form in whole-worm lysate samples
(Supplementary Fig. [180]6c–e). Second, overexpression or knock-in
mutation of the phospho-mimic EIF-2α S49D/E was lethal, suggesting a
strong dominant effect of EIF-2α S49 phosphorylation. These target
quantitation and genetics results both supported that EIF-2α S49
phosphorylation has a potent inhibitory effect on protein synthesis and
contributes substantially to daf-2 longevity (Fig. [181]4f).
Notably, our quantitative phosphoproteomics data also suggested that
the observed EIF-2α pS49 increase of the daf-2 mutant (daf-2/WT = 1.82)
may occur independently of daf-16: the EIF-2α pS49 increase was still
observed upon deletion of daf-16 (daf-16; daf-2/WT = 1.91)
(Supplementary Fig. [182]6f). Along the same line, we found that, among
the 408 phosphoisoforms differentially regulated in the daf-2 mutant,
100 apparently required daf-16 but 158 did not (Supplementary
Data [183]3). That the DAF-16-independent phosphorylation changes
outnumber the DAF-16-dependent ones is rather unique, because most of
the documented changes in daf-2(lf) worms are dependent on daf-16. For
example, two-thirds or more of the protein abundance changes seen in
the daf-2 mutant were suppressed by daf-16(lf)^[184]9.
Beyond EIF-2α, we characterized another EIF protein C37C3.2 (C. elegans
eIF5). iFPS did not rank EIF-5 pT376 and pS380 among the top 5%
(Supplementary Fig. [185]6g). The phosphorylation level of pS380 or
pT376 pS380 either decreased or had no change, respectively, in the
daf-2 mutant (Supplementary Fig. [186]6g). Simultaneous mutation of
EIF-5 T376 and S380 to T375A S380A (2A) or T375E S380E (2E) by
CRISPR/Cas9 had no or little effect on the lifespan of WT or daf-2
(e1370 or RNAi) worms (Supplementary Fig. [187]6h, i). These findings
indicated that, at least in the context of insulin-signaling-mediated
lifespan extension, the two phosphosites of EIF-5 are not functionally
impactful. At minimum, this result validated the utility of iFPS
ranking as a hypothesis-generating tool to efficiently inform
prioritization of candidates for functional studies.
CDK-1 and other germline phosphoproteins contribute to lifespan determination
CDK-1 is a master regulator of the cell cycle. For C. elegans germ cell
division, CDK-1 is specifically required for entry into the M
phase^[188]45. iFPS prioritized worm CDK-1 pT32, pY33, and pT179 as
potential LiRPs (Fig. [189]2d), which respectively correspond to human
CDK1 pT14, pY15, and pT161, (Fig. [190]5a). CDK1 activity is inhibited
by phosphorylation of T14 and Y15 by WEE1/MYT1 but is activated by
phosphorylation of T161 by CAK^[191]35. In the daf-2 mutant, both
inhibitory phosphorylation (pT32 and pY33) and activating
phosphorylation (pT179) of C. elegans CDK-1 decreased by 34–49%, while
the CDK-1 protein level was about the same as that in WT worms
(Fig. [192]5b).
Fig. 5. CDK-1 pT179 and other germline phosphoproteins contribute to lifespan
determination.
[193]Fig. 5
[194]Open in a new tab
a Model shows the human CDK1 activity regulated through phosphorylation
by WEE1 kinase, CAK kinase, and CDC25 phosphatase. Sequences around
worm CDK-1 pT32, pY33, and pT179 are identical to that around human
CDK1 pT14, pY15, and pT161. Blue, inhibitory phosphorylation. Red,
activating phosphorylation. b Phosphoproteomics data show that
phosphorylation on CDK-1 decreased in daf-2 worms. CDK-1 protein levels
remained similar in WT and daf-2 worms. c Reduction of CDK-1 activity
significantly extended the lifespan of WT worms but did not affect the
lifespan of the daf-16(mu86) worms. The ne2257ts[cdk-1-I173F] mutation
inactivates CDK-1 at the restricted temperature 22.5 °C. d
Germline-restricted degradation of WEE-1.3, a negative regulator of
CDK-1, significantly shortened the C. elegans lifespan. Endogenous
wee-1.3 and daf-2 were tagged with degron by CRISPR/Cas9. All strains
carried the ieSi38[Psun-1::TIR1] allele to induce germline-specific
protein degradation upon auxin treatment. Lifespan assays were
performed at 20 °C, with 1 mM auxin supplied from adult day 1. e
Top-ranking tissues that were significantly (p < 1.0e−15, two-sided Z
test) enriched or depleted for the hypo-phosphorylated proteins in the
daf-2 mutant. The predicted gene expression scores across tissues or
cell types were derived from Kaletsky et al.^[195]79. Boxplot shows the
first quartile, median, and third quartile of tissue-specific
expression scores of the hypo-phosphoproteins (n = 166). See statistics
in Source data. f Germline proteins that were hypo-phosphorylated in
the daf-2 mutant participate in lifespan regulation. Individual RNAi
clone of genes was fed to the rrf-1(pk1417) worms from adult day 1 at
20 °C and assayed in two independent trials. L4440 is the empty vector
control. Red highlights the pro-reproduction and anti-longevity genes.
Blue highlights the anti-reproduction and pro-longevity genes. The
diagram of a gonad was adapted from WormBook^[196]82. The
germline-related phenotypes refer to WormBase release WS275. g A model
illustrates dual roles of germline phosphoproteins in mediating the
effects of IIS on reproduction and lifespan regulation. *p < 0.05,
***p < 0.001, NS not significant, two-sided log-rank test, n > 80 worms
per strain. See survival statistics in Supplementary Dataset 4.
Since the inactive form of CDK-1 (pT32 and pY33) is not dominant
negative, a reduced level of pT179 could be interpreted as a reduction
of CDK-1 activity in the daf-2 mutant. Note that interpretation is
supported by elaborated study of the daf-2 germline, which reported a
cell cycle delay in G2 in the proliferative zone; that is,
proliferating daf-2 germ cells are slow to enter the M phase^[197]46.
Importantly, all of our phosphoproteomics samples were synchronized to
adult day 1—a stage at which germ cells are the only dividing cells—so
we can confidently assume that any detected CDK-1 activity must come
from the germline.
We then asked whether the reduction of CDK-1 pT179 or CDK-1 activity in
the daf-2 germline contributes to longevity. Mutating CDK-1 T179 to
either A or E by gene editing was predictably unsuccessful:
experimentally locking CDK-1 into either a completely inactive or a
constitutively active state prevents cell cycle progression, causing
lethality. We then took advantage of a temperature-sensitive allele of
cdk-1(ne2257ts) harboring an I173F mutation five amino acids away from
T179 in the activation loop. We found that shifting cdk-1(ne2257ts)
worms from the permissive temperature of 15 °C to the restrictive
temperature 22.5 °C on adult day 1 significantly extended WT lifespan
(by 11–30%) and noted that this extension was DAF-16 dependent
(Fig. [198]5c). We also found that temperature-shift-induced
inactivation of CDK-1(I173F) at earlier time points extended WT
lifespan (Supplementary Fig. [199]7a). Likewise, we observed an
extended lifespan of 20–30% upon knockdown of cdk-1 starting from adult
day 1 in the rrf-1(pk1417) mutant (in which RNAi is restricted in the
germline, intestine, and some hypodermal cells^[200]47), whereas no
extended lifespan phenotype resulted from intestine- or
hypodermis-restricted cdk-1 RNAi in worms (Supplementary Data [201]4).
These results supported that reduced CDK-1 activity in the adult
germline is sufficient to promote a moderate lifespan extension.
Next, we investigated whether reduced CDK-1 pT179 in the adult germline
is necessary for lifespan extension upon DAF-2 depletion. Using both
gene editing and auxin-induced protein degradation (AID)
technologies^[202]48, we were able to selectively degrade DAF-2 or
WEE-1.3, or both, in the adult germline with high spatiotemporal
precision. Degradation of WEE-1.3, the C. elegans ortholog of human
WEE1/MYT1^[203]35, should eliminate inhibitory phosphorylation of CDK1
on T32 and Y33 to drive an elevation of CDK-1 activity. Indeed,
degrading WEE-1.3 specifically in the adult germline significantly
shortened the lifespan of worms lacking germline DAF-2 (Fig. [204]5d).
Moreover, both adult-specific and germline-specific degradation of
DAF-2 slightly increased the mean lifespan and the maximal lifespan in
two independent experiments but not in a statistically significant
manner (Supplementary Data [205]4). We thus concluded that reduced
CDK-1 pT179 in the adult germline may confer a small contribution to
daf-2 longevity.
It was highly striking that germline expression was predicted for the
parent proteins of >85% of the iFPS-prioritized phosphosites
(Supplementary Fig. [206]7b). Further, it was conspicuous that proteins
of the reproductive system were highly enriched among the
hypo-phosphorylated proteins detected in the long-lived daf-2 mutant
(Fig. [207]5e). These findings motivated us to conduct a small-scale
RNAi screen in the rrf-1(pk1417) mutant background to explore how
germline phosphoproteins may affect ageing of the soma (Supplementary
Fig. [208]7c). Interestingly, we found that adult onset RNAi of genes
that promote mitosis or meiosis generally extended lifespan, whereas
RNAi of genes that limit the genesis of germ cells or gametes shortened
lifespan (Fig. [209]5f and Supplementary Fig. [210]7c). These results
are in line with reports of lifespan extension through germline
ablation^[211]49 and echo with the antagonistic pleiotropy theory of
ageing^[212]50. They also suggested that, although reduced CDK-1 pT179
alone contributes marginally to daf-2 longevity, the phosphorylation
changes among all germline proteins may collectively confer a sizable
contribution to lifespan extension (Fig. [213]5g).
Reduction of CK2 activity prolongs lifespan
In the daf-2 mutant, there were 229 hyper-phosphorylated and 248
hypo-phosphorylated sites in 159 and 176 phosphoproteins (Supplementary
Data [214]3). The kinases responsible for regulating these phosphosites
might be also important for longevity. Based on the site-specific
kinase–substrate relations (ssKSRs) predicted by a software package
named in vivo Group-based Prediction System (iGPS)^[215]51, we
statistically detected kinases with predicted ssKSRs enriched in hyper-
or hypo-phosphorylated sites of the daf-2 mutant against all identified
phosphosites (one-sided hypergeometric test, p < 0.05). In total, we
identified 27 potentially important kinases with enriched ssKSRs on the
hypo-phosphorylated sites, whereas no kinases were predicted on the
hyper-phosphorylated sites (Fig. [216]6a). Ten of the 27 identified
kinases have been reported to regulate lifespan. There were eight
kinases reported to extend lifespan with the treatment of RNAi or
loss-of-function mutation, including the worm mTOR kinase LET-363, the
MAPK activated kinase MAK-2, and the cell cycle kinases CDK-1, CDK-2,
CHK-1, PAR-1, PAK-1, and PDHK-2 (Fig. [217]6a).
Fig. 6. Inhibition of CK2 extends the worm lifespan.
[218]Fig. 6
[219]Open in a new tab
a Honeycomb diagram displays iGPS-predicted kinases whose target motifs
were significantly (one-sided hypergeometric test, p < 0.05) enriched
among the hypo-phosphorylated sites in the daf-2 mutant. Kinase groups
are depicted in different colors. Bold black highlights the kinases
reported to regulate lifespan. See statistics in Source data. b CK2
consensus motifs overrepresented in the hypo-phosphorylated peptides in
the daf-2 mutant. An online service pLogo^[220]52
([221]https://plogo.uconn.edu/) was used to visualize the statistical
significance of the frequently occurred motifs among the
hypo-phosphorylated sequences in daf-2. The phosphosites were fixed at
position 0. All quantified phosphopeptides were taken as the background
sequences. The red horizontal lines correspond to p = 0.05. c CK2
knockdown in adulthood significantly extended the lifespan of WT worms.
kin-3 or kin-10 encodes the catalytic or regulatory subunit of CK2,
respectively. Lifespan assays were performed at 25 °C, with 50 ng/μl
FUdR supplied in plates. d RNAi of kin-3 or kin-10 from adult day 1 for
24 h significantly extended the lifespan of WT worms. Lifespan assays
were performed at 20 °C without FUdR. e Feeding WT with TBB, the highly
selective inhibitor of CK2, from adult day 1 for 24 h significantly
extended the worm lifespan. Lifespan assays were performed at 20 °C,
with 50 ng/μl FUdR supplied in plates. f TBB treatment from adult day 1
for 24 h significantly extended the lifespan of C. elegans. Lifespan
assays were performed at 20 °C without FUdR. *p < 0.05, ***p < 0.001,
two-sided log-rank test, n > 70 worms per strain. See survival
statistics in Supplementary Dataset 4.
Among the 27 identified kinases, the CK2 kinase was composed of the
catalytic subunit KIN-3 and the regulatory subunit KIN-10. Using a
motif discovery tool pLogo^[222]52, we found that two CK2-specific
phosphorylation motifs were significantly overrepresented in the
hypo-phosphorylated sites found in the daf-2 mutant (Fig. [223]6b),
hinting a role of CK2 in daf-2 longevity. CK2 was reported to
accelerate both chronological and replicative ageing in Saccharomyces
cerevisiae^[224]53,[225]54. However, one study in C. elegans proposed
that KIN-10 might be required to slow down ageing^[226]55. To clarify
this controversial point, we examined the lifespans of worms treated
variously with kin-3 RNAi, kin-10 RNAi, or the CK2 inhibitor
4,5,6,7-tetrabromo-1H-benzotriazole (TBB). Knockdown of kin-3 or kin-10
during adulthood moderately but significantly extended worm lifespan in
independent trials (Fig. [227]6c and Supplementary Data [228]4). More
strikingly, treating WT worms from adult day 1 with TBB, kin-3 RNAi, or
kin-10 RNAi for only 24 h extended worm lifespan by 9–27%
(Fig. [229]6d–f and Supplementary Data [230]4). These results
demonstrated that inhibition of CK2 in young adults promotes longevity
in C. elegans.
Discussion
Reducing the activity of IIS significantly extends lifespan and
mobilizes deeply conserved lifespan modulators, primarily through
phosphorylation. However, the in-depth mechanisms of lifespan
regulation by IIS-related phosphorylation have been largely neglected.
Also, technical challenges for large-scale characterization of
functional phosphosites have hindered the gathering of experimentally
confirmed phosphosites. In the present study, we conducted a
large-scale quantitative phosphoproteomics survey to address these
issues. Our results increased the total number of in vivo phosphosites
in C. elegans. Moreover, we developed a machine learning-based method
named iFPS to prioritize phosphosites for in-depth functional analysis,
which includes phosphosite-specific mutagenesis analysis. We offered
multiple demonstrations for how functional phosphorylation events
modulate signaling pathways to control lifespan regulation (Fig. [231]7
and Supplementary Discussion).
Fig. 7. Phosphoproteomics analysis supports concerted regulation of longevity
from multiple pathways upon reduced IIS.
[232]Fig. 7
[233]Open in a new tab
daf-2(lf) induced extensive phosphorylation changes on components of
the IIS pathway, translational machinery, reproductive system, and
kinome. Phosphorylation changes at AKT-1 pT492, EIF-2α pS49, and CDK-1
pT179 all affect lifespan, while their parent proteins and the encoding
mRNAs show no or little change in the daf-2 mutant, except for AKT-1.
The proteins involved in reproduction and lifespan determination are
likely regulated through phosphorylation by IIS, since no clear pattern
of changes is evident based on analysis of their mRNA or protein
levels. Similarly, reduction in IIS may lower the activity of
pro-ageing kinases, and the regulation pattern cannot be inferred from
mRNA^[234]41 or protein^[235]6 abundance changes. ↑ increase or extend,
↓ decrease or shorten, — no significant change.
In a genetic mutant, the organism makes many adjustments to cope with
the mutation until it reaches a steady state. As such, there are often
many differences between the mutant and WT, some of which are direct
and some, likely most, are not. A comprehensive phosphoproteomic study
of the budding yeast nonessential kinases and phosphatases found that
32 and 53% of the 8814 regulated phosphorylation events resulted from
direct actions of the kinases or phosphatases examined,
respectively^[236]56. In this study, the three functionally validated
phosphosites AKT-1 pT492, EIF-2α pS49, and CDK-1 pT179 are all
indirectly regulated by the tyrosine kinase DAF-2. To differentiate
direct targets from indirect ones, we envision that a kinase could be
degraded rapidly in vivo using the AID^[237]48 or proteolysis-targeting
chimera (PROTAC)^[238]57 method, followed by a time course
phosphoproteomic analysis. For cultured cells or unicellular organisms,
a kinase inhibitor could be used in place of AID or PROTAC. Since
direct targets should change earlier than indirect targets, the early
responding phosphosites are more likely to be direct targets of a
kinase.
We designed and implemented a machine learning-based tool—iFPS—for
systematically ranking the likely functional importance of worm
phosphosites (see Supplementary Discussion). Such a tool was not
previously available for the C. elegans research community, but it is a
precondition for phosphoproteome-scale functional elucidation of
phosphosites. The current iFPS method was an encouraging start. The
predictive power of iFPS has not been fully explored owing to a paucity
of experimentally confirmed functional phosphosites, ssKSRs,
protein–protein interactions (PPIs), and other PTMs in C. elegans.
Thus, additional experimental data, further computational resources,
and innovative research strategies are needed to better comprehend
which type of data is informative, and to what extent, regarding
prediction of functional phosphosites. Nevertheless, this work
illustrated how our present strategy can be generally applied for a
wide range of studies examining complicated biological phenomena to
inform both basic mechanistic research and rational drug design.
Methods
C. elegans and Escherichia coli strains
The genotypes, sources, and generating methods of C. elegans strains
are listed in Supplementary Table [239]2. Worms were maintained on
nematode growth media (NGM) agar plates seeded with E. coli strain OP50
(Caenorhabditis Genetics Center, Cat#OP50) at 20 °C using standard
protocols^[240]58, unless otherwise indicated.
The ^15N-labeled food source was prepared by growing E. coli MG1655
(laboratory collection) in M9 minimal media (^15NH[4]Cl as the unique
nitrogen source) until OD600 value reached to 1.0 at 37 °C^[241]59.
MG1655 cells were concentrated and seeded on nitrogen-free worm plates.
E. coli HT115 cells (Caenorhabditis Genetics Center, Cat#HT115)
transferred with RNAi plasmids or the empty vector control were
cultured overnight in LB plus ampicillin (100 µg/ml) and tetracycline
(10 µg/ml) and then seeded on NGM plates containing ampicillin
(100 µg/ml), tetracycline (10 µg/ml), and IPTG (1 mM). RNAi clones made
in this paper were constructed by inserting the cDNA of genes into the
L4440 vector. Other RNAi bacteria were derived from Ahringer RNAi
library (Source BioScience) or C. elegans RNAi feeding library (Open
Biosystems, CAT#RCE1181).
Phosphoprotein sampling
Worms were synchronized by egg bleaching and overnight incubation in M9
buffer. The synchronized L1 larvae were fed with OP50 at 20 °C,
harvested at adult day 1, and subjected as unlabeled (^14N) C. elegans
samples. The ^15N-labeled C. elegans reference sample was prepared by
culturing WT for generations on ^15N-labeled MG1655 at 20 °C and
harvesting in mixed stages.
The ^14N and ^15N worms mixed at ratio 1:1 by volume were suspended in
lysis buffer [2× RIPA buffer, 2× EDTA-free proteinase inhibitors
cocktail (Roche), and 2× PhosSTOP EASYpack (Roche)], homogenized in a
FastPrep®-24 instrument (MP Biomedicals), and spun at >20,817 × g for
30 min. The supernatants were precipitated and resolved in urea
solution (8 M urea, 100 mM Tris-HCl, pH 8.5). Ten milligrams of total
proteins determined by Bradford assay were subjected to reduction (5 mM
TCEP), alkylation (10 mM Iodoacetamide), and trypsin digestion
(overnight at 37 °C). The resulting products were fractionated on an
Xtimate^TM C18 reversed-phase HPLC column (10 × 250 mm, 5 µm, Welch
Materials) using an Agilent 1200 Series HPLC instrument^[242]19.
Solvent A (2% acetonitrile (ACN), 10 mM ammonium formate, pH 10) and
solvent B (90% ACN, 10 mM ammonium formate, pH 10) were used to
separate peptides at a flow rate of 3 ml/min. A nonlinear gradient was
programmed with 5 different slopes (0% for 2 min; 0% to 10% in 5 min;
10% to 27% in 34 min; 27% to 31% in 4 min; 31% to 39% in 4 min; 39% to
60% in 7 min; 60% for 8 min). Eluted peptides were collected throughout
the gradient with 0.66 min (=2 ml) per fraction. The non-contiguous
fractions were combined into 11 or 13 samples. After acidification and
desalination, each fractionation was subjected to enrichment via the
PolyMAC-Ti Enrichment Kit (Tymora Analytical). The resulting
phosphopeptides were resolved in 20 µl buffer (0.25% formic acid (FA)).
MS data acquisition
Each phosphopeptide sample was technically analyzed twice though a
Q-Exactive mass spectrometer (Thermo Fisher Scientific) interfaced with
an Easy-nLC1000 reversed-phase chromatography system (Thermo Fisher
Scientific). Five microliters of sample was loaded on a 75 µm × 4 cm
trap column packed with 10 µm, 120 Å ODS-AQ C18 resin (YMC Co.) and
separated by a 75 µm × 10 cm analytical column packed with 1.8 µm,
120 Å UHPLC XB-C18 resin (Welch Materials) at a flow rate of 200 nl/min
using a linear gradient of 0–28% ACN (0.1% FA) over 80 min, followed by
raising the ACN concentration to 80% within 15 min and maintaining for
another 15 min.
The FTMS full scan between 350 and 2000 m/z were acquired from the
Orbitrap at 70,000 resolution in profile data type with 1e6 automatic
gain control (AGC) target, 60 ms maximum injection time. Ion 445.12003
was used for internal calibration. Top ten most abundant precursor ions
were selected using a 2.0 m/z isolation window for higher-energy
collisional dissociation (HCD) fragmentation (27% collision energy).
MS2 scans were acquired from the Orbitrap at 17,500 resolution in
profile data type with 5e4 AGC target, 250 ms maximum injection time.
The intensity threshold for MS2 scan was 4e3. Precursors with +1, >+6,
and unassigned charge state were excluded. Peptide match was set as
preferred. Dynamic exclusion was 60 s.
Phosphopeptide identification and phosphosite localization
MS/MS spectra were extracted from raw MS files by RawXtract
1.9.9.2^[243]60 and searched against a composite target/decoy database
using ProLuCID^[244]61. The C. elegans protein database WS233 was used
as target while the corresponding reversed sequences was generated as
decoy. Spectra were searched with ±50 ppm for both precursor ion and
fragment ion accuracy, peptide length >7 residues, and fully tryptic
restriction. Carbamidomethylation of cysteines was included as a fixed
modification. Phosphorylation of serine, threonine, and tyrosine
residues were included as variable modifications. The peptide spectrum
matches were filtered using DTASelect2^[245]62. The estimated false
discovery rate was no more than 1.07% for phosphopeptides. The ^14N-
and ^15N-labeled peptides were identified in paralleled pipelines.
For each ^14N peptide, phosphosites with phosphoRS site
probability^[246]21 >0.75 were assigned as confident modification. The
phosphosite localization on the ^15N-labeled peptide was corrected
corresponding to its ^14N-isotopic version. The residual number of
phosphosites was determined by mapping the phosphopeptides to the
longest transcripts of C. elegans genes (UniProt release 2015_01).
Phosphosites from single-phosphorylated peptides and
multi-phosphorylated peptides were extracted as different
phosphoisoforms (see examples in Supplementary Fig. [247]1c).
Phosphoisoform quantification
For each MS sample, LC-MS/MS measured the ^14N- and ^15N-labeled
phosphoproteomes simultaneously. The ^15N-labeled phosphopeptides serve
as internal reference that avoid systematic errors during
quantification as well as monitor batch effects among replicates.
Ratios of ^14N- to ^15N-labeled phosphopeptide were determined by a
modified version of pQuant software^[248]63. In brief, confident
quantification was accepted when both the least interfered isotopic
ratio and the monoisotopic ratio of a ^14N and ^15N ion pair had the σ
values < 0.5. ^15N/^14N ratios were normalized to the median value of
all quantified peptides per technical replicates and then assigned to
their corresponding phosphoisoforms (see examples in Supplementary
Fig. [249]2a). The median values of ^15N/^14N ratios of each
phosphoisoform were used in PCA (Supplementary Fig. [250]2b) and
hierarchical clustering analysis (Supplementary Fig. [251]2c).
Phosphorylation changes in IIS mutants
To determine the daf-2-regulated phosphorylation, phosphoisoforms
quantified at least three times in daf-2 samples were extracted to
compare with WT control. ^14N/^15N ratios of WT was adopted as
control-1 if the number of quantitation ratios in WT samples were more
than two. Alternatively, ^14N/^15N ratios of WT, daf-16, and daf-16;
daf-2 samples were adopted as control-2 if the phosphoisoform was
quantified only once or twice in WT samples. The control-1 and
control-2 were merged into a single WT control data, and log[2](median
of daf-2/median of control) distribution was plotted to estimate the
median and normalized interquartile (NIQ) ranges. Here Q[1] was the
lower 25% quantile, and Q[3] was the upper 25% quantile. Then
interquartile (IQ) and NIQ ranges were calculated as below:
[MATH: IQ=Q3−Q
1 :MATH]
1
[MATH: NIQ=0.7413×IQ :MATH]
2
The ^14N/^15N ratios of each phosphoisoforms were subjected to Wilcoxon
rank-sum test. Then a flexible filter was applied to define the daf-2
regulated phosphoisoforms, which met the criteria of either
[log[2](daf-2/control) out the range of median ±1.5 × NIQ with
one-tailed p < 0.05, Wilcoxon rank-sum test] or [log[2](daf-2/control)
out the range of median ± NIQ with two-tailed p < 0.05, Wilcoxon
rank-sum test].
Similarly, phosphoisoforms quantified at least three times in both
daf-2 and daf-16; daf-2 were subjected to statistical comparison. The
DAF-16-dependent phosphorylation was defined using the same filter as
the daf-2-regulated phosphoisoforms.
Preparation of benchmark data sets for iFPS
Previously, we developed a comprehensive database named dbPAF
([252]http://dbpaf.biocuckoo.org/), containing 483,001 experimentally
identified phosphosites of 54,148 phosphoproteins from 7 model
eukaryotes, through literature biocuration and public database
integration^[253]17. In dbPAF, there were 10,767 known phosphosites of
2933 phosphoproteins in C. elegans. To find phosphosites with important
functions, we searched PubMed using multiple keyword combinations, such
as “elegans phosphorylation,” “elegans phosphosite,” and “elegans
phosphoprotein.” The full texts of returned manuscripts were carefully
read and curated, and 121 known functional phosphosites in C. elegans,
of which 69 were covered by dbPAF, were collected as the positive data
set (Supplementary Data [254]2). The remaining 10,698 worm phosphosites
in dbPAF were taken as negative samples. For each phosphosite of both
positive and negative samples, the UniProt accession number of its
corresponding protein, the full protein sequence, phosphorylation
position, and phosphorylatable residue were shown in a tab-delimited
format (Supplementary Data [255]2).
Performance measurements
To evaluate the accuracy of iFPS, we calculated two measurements,
including sensitivity (Sn) and specificity (Sp) as below:
[MATH: Sn=TPTP+FN :MATH]
3
[MATH: Sp=TNTN+FP :MATH]
4
The 10-fold cross-validation was automatically performed by Weka 3.8, a
widely used machine learning software package in Java^[256]64, after
model training. The receiver operating characteristic curves were
illustrated based on Sn and 1 − Sp values, and the AUC scores were
directly calculated by Weka 3.8.
The iFPS algorithm
We developed iFPS as a three-step method to computationally prioritize
functionally important phosphosites in C. elegans, including individual
feature encoding, feature integration and model training, and
normalization of predicted scores.
(1) Individual feature encoding. In this step, 6 sequence or structure
features were encoded as below:
(i) UKFs^[257]18,[258]32. Functional phosphosites are often regulated
by multiple important kinases, and act as pivotal hubs to link various
biological processes and signaling pathways. To assign potential UKFs
for individual phosphosites, we used a previously developed tool named
iGPS^[259]51, which combined both sequence profiles specifically
recognized by difference kinases and PPIs between kinases and
substrates to predict ssKSRs. iGPS supported species-specific
predictions for five model organisms, including Homo sapiens, Mus
musculus, Drosophila melanogaster, C. elegans, and S.
cerevisiae^[260]51. In iGPS, there were 44 and 15 specific predictors
for S/T kinases and tyrosine kinases in C. elegans, respectively. To
enable a higher coverage for phosphosite annotation, the low thresholds
were adopted with false positive rates of 10% for S/T kinases and 15%
for tyrosine kinases. From predicted ssKSRs, the number of UKFs was
counted for each phosphosite.
(ii) PhC^[261]18,[262]30,[263]32,[264]33. The residue conservation
score (RCS) was calculated to measure the conservation of each
phosphosite^[265]65. First, the potential orthologs of worm
phosphoproteins were pairwisely detected in other six eukaryotes,
including H. sapiens, M. musculus, Rattus norvegicus, Drosophila
melanogaster, S. cerevisiae, and S. pombe. The classical method of
reciprocal best hits^[266]66 was adopted, using the mainstream sequence
alignment tool BLAST (version 2.2.31)^[267]66. Then protein sequences
were multi-aligned by MUSCLE^[268]67 for each worm phosphoprotein and
its orthologs if available. The RCS value was calculated for each worm
phosphosite as below:
[MATH: RCS=MBL×RCR=MBL×NpN
:MATH]
5
The maximum branch length (MBL) was the longest evolutionary distance
between any two organisms that contained a conserved phosphorylatable
residue. A phylogenetic tree built by Interactive Tree Of Life
([269]https://itol.embl.de/)^[270]68 was used to estimate the
evolutionary distance. The residue conservation ratio was defined as
the proportion of conserved phosphorylatable residues at the desired
position (N[p]) against all organisms within the MBL (N).
(iii) IDMs. Phosphorylation status of residues located in the
domain–domain or domain–motif interacting pairs may influence the
structure of protein complex or the PPI network. Based on Pfam 31.0
database^[271]69, functional domains of all worm phosphoproteins were
predicted using the hmmsearch program in the HMMER v3.1b2 software
package^[272]70. The pre-compiled domain–domain and domain–motif
interactions were derived from the database of three-dimensional
interacting domains^[273]71. The number of interacting domains and
motifs was directly counted for each phosphosite located in at least
one domain. For phosphosites not located in any domains, the number of
its interacting domains/motifs was set as 0.
(iv) ASC^[274]18. To predict potential acetylation sites close to
phosphosites, we used a previously developed software package named
GPS-PAIL 2.0^[275]72, which contained seven histone acetyltransferase
(HAT)-specific predictors. In this work, five predictors for EP300,
HAT1, KAT2B, KAT5, and KAT8 were selected to predict HAT-specific
acetylation sites for their proximal homologs, CBP-1, HAT-1, PCAF-1,
MYS-1, and MYS-1 in C. elegans, respectively. For a better coverage,
the low threshold with the Sp value of 85% was adopted. The ASC value
was set as 1 or 0 for the worm phosphosites with or without at least
one nearby acetylation site within 15 amino acids [−15 to +15],
respectively.
(v) RSA^[276]18. We predicted the surface accessibility of worm
phosphosites using NetSurfP v1.1
([277]http://www.cbs.dtu.dk/services/NetSurfP/)^[278]73. The FASTA
sequences of each phosphoprotein was submitted to NetSurfP. The RSA
scores of residues that were identified as phosphosites were extracted.
(vi) SSs^[279]18,[280]32. The structural environment around
phosphosites is also important for its function. Again, NetSurfP
v1.1^[281]73 was adopted to predict the SSs of phosphosites. The
probability scores of α-Helix, β-strand, and Coil were used in
modeling.
(2) Feature integration and model training. For each worm phosphosite,
the numerical values of the 6 types of sequence and structure features
were obtained as described above, and the initial weight value of each
feature was equally assigned as 1. The multinomial logistic regression
algorithm was implemented in Weka 3.8^[282]64 for model training, in
which the weight values were automatically determined based on the
highest AUC value from the tenfold cross-validation. Because the number
of negative samples was much larger than the positive data set, we
randomly selected 121, 242, 605, or 1210 phosphosites from the negative
samples and generated benchmark data sets with a positive versus
negative ratio of 1:1, 1:2, 1:5, or 1:10. By testing, the benchmark
data set with the ratio of 1:5 exhibited a higher AUC value
(Supplementary Fig. [283]8f). To avoid overfitting, we generated ten
different sets of benchmark data sets for model training (Supplementary
Data [284]2), and the final model was determined based the highest AUC
value of the tenfold cross-validation. For the final model, the 95% CI
was computed with 10,000 stratified bootstrap replicates.
(3) Normalization of predicted scores. The raw scores directly
predicted by iFPS ranged from −5.5649 to 24.9553 (Supplementary
Data [285]2). Here, we normalized the scores into a range of 0 to 1.
The IQ range was calculated, while upper and lower fences were defined
as below:
[MATH: Lowerfence=Q<
mrow>1−3*IQ :MATH]
6
[MATH: Upperfence=Q<
mrow>3+3*IQ :MATH]
7
where Q[1] was the lower 25% quantile and Q[3] was the upper 25%
quantile. To eliminate the influence of iFPS scores that were too high
or too low, the 3×IQ was adopted in this study. Phosphosites with iFPS
scores higher or lower than upper or lower fence were scored to 1 and
0, respectively. The highest and lowest iFPS scores within the upper
and lower fences were denoted as S[max] and S[min], whereas other iFPS
scores were normalized as below:
[MATH: Snorm=
S−SminSmax−S<
/mi>min :MATH]
8
A higher S[norm] value denoted a higher probability of a phosphosite to
be functionally important.
Target quantification of phosphorylation and proteins
Endogenous levels of target phosphorylation and protein were quantified
by LC-MS/MS analysis of the worm proteome using isotopically labeled
peptides as a spike-in standard. Total proteins were extracted from the
synchronized adult day 1 worms by cryogenic grinding (mixer mill MM
400, Retsch) and resolved in lysis buffer (0.1 M Tris/HCl, pH 7.6, 4%
sodium dodecyl sulfate (SDS), 0.1 M dithiothreitol (DTT), protease
inhibitor cocktail, and phosphatase inhibitor cocktail). The crude
extract was incubated at 95 °C for 5 min followed by centrifugation at
20,817 × g (10 min, room temperature). Supernatant was collected and
sent for protein concentration measurement by 2-D quant. In all, 100 µg
of total proteins were subjected to buffer exchange, alkylation
reaction, and trypsin digestion by the filter-aided sample preparation
method^[286]74. The synthesized isotopically labeled peptides were
simultaneously spiked in right before adding trypsin (see Supplementary
Data [287]6).
After 18 h digestion, the peptide mixture was centrifuged at 20,817 × g
(30 min, 4 °C). Each sample with 5–10 µg peptides were analyzed twice
on a Q-Exactive or Q-Exactive HF mass spectrometer (Thermo Fisher
Scientific) interfaced with an Easy-nLCII or Easy-nLC1000 LC system
(Thermo Fisher Scientific). Homemade 75 µm × 4 cm or 150 µm × 4 cm trap
columns (ReproSil-Pur 120 C18-AQ, 3 µm, Dr. Maisch GmbH), and
75 µm × 12 cm or 150 µm × 20 cm analytical columns (ReproSil-Pur 120
C18-AQ, 1.9 µm, Dr. Maisch GmbH) were heated to 60 °C for online
desalting followed by separation at a flow rate of 200 or 600 nl/min
with a linear gradient (0% B at 0 min, 12% B at 1 min, 25% B at 61 min,
80% B at 71 min, and 80% B at 81 min, or 0% B at 0 min, 12% B at 1 min,
25% B at 41 min, 80% B at 51 min, and 80% B at 61 min). Solvents A and
B were 0.1% (v/v) FA in water and 0.1% (v/v) FA in ACN, respectively.
Peptides were mobilized in the positive-ion mode by electrospray
ionization with 2 or 2.2 kV spray voltage and 320 °C capillary
temperature. Ion 445.120025 m/z was used for internal calibration.
Full-scan mass spectra were acquired in the Orbitrap over the m/z range
of 300–1500 at a resolution of 70,000 or 60,000, and AGC target was set
to 3e6. Maximum injection time was 60 or 100 ms. Precursor ions of
target peptides were selected for HCD fragmentation and Orbitrap
detection during the desired acquisition time. The operating parameters
were: resolution 35,000 or 60,000; AGC targets 1e5; maximum IT auto;
isolation window 2 m/z; normalized collision energy 27.
MS/MS spectra were processed in Xcalibur (version 2.2 SP1.48, Thermo
Fisher Scientific) and pLabel (version 2.4)^[288]75. Isotopically
labeled peptide ions were used to locate the endogenous targets across
the elution. For each target precursor ion, at least three fragment
ions with high abundance and low interference were selected for
identification and quantitation. Peak areas of precursor ions
generating each desired fragment ion were determined in Xcalibur with
default parameter and used for quantification.
Endogenous peptides (light ions) and their isotopically labeled
counterparts (heavy ions) were quantified by extracting peak areas of
each quantifiable transition (precursor → fragment). For each
transition, peak areas of light were divided by that of heavy. Relative
abundance of individual phosphorylation or protein was determined by
the mean value of light/heavy ratios. Two-tailed p value was calculated
by Student’s t test in Excel 2013.
CRISPR/Cas9-based mutagenesis
The CRISPR/Cas9-mediated mutagenesis of C. elegans endogenous genes was
performed as described with little modification^[289]76–[290]78. For
the single guide RNA (sgRNA)-Cas9 expression plasmid-based mutagenesis,
individual sgRNA was incorporated into the pDD162 plasmid (Addgene,
#47549) at the desired locus. Usually two different sgRNAs were used
simultaneously. For the Cas9 ribonucleoprotein-based mutagenesis, a
crRNA that contains the target sequence at the 5′ end was synthesized.
Two or more alleles were assayed in follow-up studies.
To mutate eif-2α and eif-5, two sgRNA-Cas9 expression vectors (each
50 ng/μl) and one template plasmid containing the desired mutation
(50 ng/μl) were co-injected with pRF4 (rol-6(su1006)) marker (50 ng/μl)
into N2 young adults. For editing akt-1, two sgRNA-Cas9 expression
vectors (each 50 ng/μl) and one single-stranded oligonucleotide
containing the desired mutation (50 ng/μl) were injected together with
25 ng/μl of both dpy-10 gRNA-Cas9 vector and its donor oligonucleotide
into N2 young adults. Worms were grown at 20 °C after injection. The F1
generation were genotyped by restriction enzymatic digestion of the PCR
product. The non-roller homozygote F2 worms were isolated and sequenced
to verify the substitution fidelity.
The AKT-1::GFP strain was generated by the Cas9 RNP system. The dsDNA
asymmetric-hybrid donors were two PCR products: a gfp cassette and a
long PCR product, which was composed of 470 bp akt-1 homologous arm,
gfp, and 342 bp akt-1 homologous arm from 5′ to 3′. A mixture
containing the crRNA, dsDNA donors, tracrRNA, Cas9 protein, and pRF4
were injected to the WT or AKT-1-T492A mutant worms. The concentration
of each element in injection mixture followed the
recommendation^[291]78. Worms were verified as described above.
To specifically deplete WEE-1.3 in the germline of C. elegans, reagents
for the AID system were obtained as previously reported^[292]48. In
brief, the mNeonGreen::degron cassette was inserted adjacent to the ATG
codon of endogenous wee-1.3 by the CRIPSR/Cas9 technology. Three
different sgRNA-Cas9 vectors and one template plasmid together with
injection markers were co-injected into young adults of CA1199
(unc-119(ed3) III; ieSi38[sun-1p::TIR1::mRuby::sun-1 3’UTR+
Cbr-unc-119(+)] IV) strain.
Knocking out of atf-5 was achieved by injecting two sgRNA-Cas9 vectors
and the pRF4 marker (each 50 ng/μl) into N2 young adults to induce
indel mutations around the ATG of atf-5. The resulting allele hq35 was
a five base-pair deletion around the 25th residue of ATF-5, while hq36,
by replacing three bases with two others, caused a frame shift. Both
alleles led to early stop on atf-5 translation.
Immunoblotting analysis
Synchronized worms of each strain were grown on OP50 plates at 20 °C
and harvested at adult day 1 using M9 buffer, followed by liquid
nitration freezing. Worm pellets were boiled in SDS loading buffer and
loaded to replicate SDS-polyacrylamide gel electrophoresis gels. The
transferred fluorescence PVDF membranes (Millipore) were probed
overnight at 4 °C with anti-phospho-eIF2α (Ser51) (1:1000 dilution,
Cat#3398S, Cell Signaling Technology) and anti-eIF2α (1:500 dilution,
kindly provided by Dr. Shin Takagi) primary antibody, respectively. The
blots were visualized by 1 h incubation at room temperature with IRDye
800CW fluorescent secondary antibodies (1:10,000 dilution,
Cat#926-32211, LI-COR Biosciences), followed by scanning in the LI-COR
Odyssey Infrared Imaging System according to the manufacturer’s
instruction. Images were quantified with Image Studio Lite Ver 4.0
(LI-COR). The significance of intensity difference was evaluated by
paired t test in Excel 2013. To examine the AKT-1::GFP level,
nitrocellulose membranes were probed with anti-GFP (1:3000 dilution,
Cat#11814460001, Roche) or anti-tubulin (1:5000 dilution, Cat#T3526,
Sigma-Aldrich) antibodies. Horseradish peroxidase-conjugated secondary
antibodies (1:10,000 dilution, Cat#AP124, Sigma-Aldrich) were used for
detection.
Lifespan assays
The strains used for lifespan assays were well fed and maintained at
desired temperature for at least three generations. To set up the
lifespan assay, adult day 2 hermaphrodites were placed on OP50-seeded
NGM plates to lay eggs for 4 h. The synchronized offspring were
transferred to desired plates (25–35 worms per plate) when they reached
adulthood and continually transferred to fresh plates every other day.
After they ceased laying egg, living worms were scored every 2 days and
transferred to fresh plates every 4–7 days. Statistical analysis of
lifespan data was performed in the SPSS software package version 20.
Replicates as well as measuring conditions including temperature and
supplements in plates are recorded in Supplementary Data [293]4.
For lifespan assays performed with 5-fluoro-2’-deoxyuridine (FUdR),
50 ng/μl FUdR was supplied in the sterilized NGM agar, which were then
poured in dishes. Concentrated OP50 were seeded on the FUdR-containing
plates and dried at room temperature for 12–24 h. Synchronized worms
were cultured on normal NGM plates until lifespan assays were initiated
and adult day 1 worms were transferred to FUdR-containing plates.
Auxin treatment was performed as previous description^[294]48. Briefly,
auxin, which was dissolved in ethanol, was added to NGM agar before
pouring into plates. The final concentration of auxin and ethanol per
plate was 1 mM and 0.25%, respectively. 0.25% ethanol was used as
control. Freshly prepared auxin plates were maintained at 4 °C in the
dark for up to 2 weeks. Auxin plates were seeded with OP50 12 h before
use. Living worms were transferred to fresh plates every 4 days. Auxin
treatment was imitated from adult day 1.
For TBB treatment, TBB was resolved in 80% dimethyl sulfoxide
(DMSO):phosphate-buffered saline solvent. NGM plates with or without
50 ng/µl FUdR were seeded with OP50 and dried at room temperature for
12 h. Then TBB solution was added to the surface of plates with the
final concentration of 15 or 45 μM TBB. The final concentration of DMSO
for each plate was adjusted to 0.36%, including the control. Supplied
volume is based on the volume of media. The freshly prepared plates
were left for drug diffusion overnight and used within 2 days.
Synchronized adult day 1 WT were transferred to plates with TBB or
control treatment at 20 °C. After 24 or 48 h, worms were moved to fresh
NGM plates (with or without 50 ng/µl FUdR).
Dauer formation
For dauer assays at 21 °C, parent worms were maintained on NGM plates
seeded with OP50 at 15 °C for over three generations and allowed to lay
eggs for 4–6 h at 21 °C. Progeny were incubated at 21 °C. For dauer
assays at 27 °C, parent worms were cultured at 20 °C for over three
generations. Eggs were laid within 4–6 h at 20 °C and transferred to
27 °C. Dauer and non-dauer animals were scored and confirmed at the
third, fourth, or fifth day post egg-laying.
Polyribosome profiling assays
Polyribosome profiling was performed as previous description with
little modification^[295]9. Ten milliliters of 7–50% (w/v) linear
sucrose gradients in gradient buffer (110 mM KAc, 20 mM MgAc2 and 10 mM
HEPES pH 7.6) were prepared in 13.2 ml polyallomer centrifuge tubes
(Beckman-Coulter) just before use. Adult day 1 synchronized worms were
lysed in lysis buffer (30 mM HEPES pH 7.6, 100 mM KCl, 10 mM MgCl[2],
0.1% NP-40, 100 mg/ml cycloheximide, 2 mM DTT, 40 U/ml RNase inhibitor,
and protease inhibitor cocktail) with a dounce homogenizer. Worm lysate
was centrifuged at 14,000 × g (10 min, 4 °C). The supernatant was
immediately subject to protein content estimation by A[280 nm] on
NanoDrop 1000 (Thermo Fisher Scientific). The same amount of A[280 nm]
units (3000–6100 units) of each sample was layered atop the 7–50% (w/v)
linear sucrose gradient and centrifuged for 2 h at 27,3620 × g in a
SW41Ti rotor (Beckman-Coulter) at 4 °C. Gradients were analyzed with a
density gradient fractionator coupled with the absorbance recording at
an optical density of 254 nm (Teledyne Isco). Images were transferred
into digital data using Adobe Photoshop and merged by aligning base
line of absorbance using Adobe Illustrator.
Microscopy
Worms were cultured at 20 °C. To measure the cellular localization of
DAF-16::GFP, worms growing for 6–10 h after the L4 stage were picked on
pad and visualized under fluorescent microscopy within 2 min.
DAF-16::GFP localization in intestinal cells was manually classified
(Fig. [296]3d). The number of worms in each category was counted.
Images were taken using a Zeiss Axio Imager M1 microscope at 400-fold
magnification with the Axiovision Rel. 4.7 software (Carl Zeiss Ltd.).
Images of worms expressing AKT-1::GFP or AKT-T492A::GFP were taken by
the Zeiss Axio Imager M1 microscope at 100- or 200-fold magnification.
The penetrance of AKT-1-T492A::GFP nuclear localization in proximal
gonad was calculated by scoring the number of worms under the same
microscope at 1000-fold magnification. Fluorescence images of
AKT-1::GFP or AKT-T492A::GFP in the germline were acquired using a
Spinning Disk microscope and processed with Volocity Demo 6.3
(PerkinElmer).
Tissue expression prediction
Proteins with decreased or increased phosphorylation on the
daf-2-regulated phosphoisoform were defined as hypo- or
hyper-phosphorylated proteins, respectively. Expression of the
daf-2-regulated phosphoproteins across 76 tissues and cell types were
implemented on an interactive webserver
([297]http://worm.princeton.edu)^[298]79. The prediction scores were
downloaded for statistical enrichment calculation using the R software
(v.3.5.0). The two-tailed p value per subtissue was calculated by
Z-test.
Statistical detection of kinases with enriched substrates
First, the ssKSRs predicted by iGPS51 were adopted for each candidate
kinase. Then the one-sided hypergeometric test was used to determine
whether targets of any kinases were statistically enriched in the daf-2
hyper- or hypo-phosphorylated data set. For each kinase k[i], we
defined the following:
N = number of phosphosites identified in this work,
n = number of phosphosites predicted to be phosphorylated by ki,
M = number of hyper- or hypo-phosphorylated sites in the daf-2 mutant,
m = number of hyper- or hypo-phosphorylated sites predicted to be
phosphorylated by k[i].
The enrichment ratio (E-ratio) of k[i] was computed, and the p value
was calculated based on the hypergeometric distribution as below:
[MATH: E-ratio=m
M/n
N :MATH]
9
[MATH: p=∑m
′=m<
mi>nMm′N−Mn−m<
mrow>′Nn(E-ratio>1) :MATH]
10
Potentially important kinases were identified with significantly
enriched hyper- or hypo-phosphorylated sites (p < 0.05 and
E-ratio > 1).
The KEGG enrichment analysis
KEGG annotation files that contained 3525 worm genes annotated with at
least one pathway were downloaded from the ftp server of KEGG
([299]ftp://ftp.bioinformatics.jp/). The hypergeometric test was
performed to detect enriched KEGG pathways (p < 0.05 and E-ratio > 1).
Reporting summary
Further information on research design is available in the [300]Nature
Research Reporting Summary linked to this article.
Supplementary information
[301]Supplementary Information^ (6.9MB, pdf)
[302]Peer Review File^ (378.8KB, pdf)
[303]Dataset 1^ (4.3MB, xlsx)
[304]Dataset 2^ (2.6MB, rar)
[305]Dataset 3^ (150.2KB, xlsx)
[306]Dataset 4^ (31.3KB, xlsx)
[307]Dataset 5^ (54.9KB, xlsx)
[308]Dataset 6^ (20.2KB, xlsx)
[309]41467_2021_24816_MOESM9_ESM.pdf^ (103.3KB, pdf)
Description of Additional Supplementary Files
[310]Reporting Summary^ (2.1MB, pdf)
Acknowledgements