Abstract
Despite extensive studies at the genomic, transcriptomic and
metabolomic levels, the underlying mechanisms regulating longevity are
incompletely understood. Post-translational protein acetylation is
suggested to regulate aspects of longevity. To further explore the role
of acetylation, we develop the PHARAOH computational tool based on the
100-fold differences in longevity within the mammalian class. Analyzing
acetylome and proteome data across 107 mammalian species identifies 482
and 695 significant longevity-associated acetylated lysine residues in
mice and humans, respectively. These sites include acetylated lysines
in short-lived mammals that are replaced by permanent acetylation or
deacetylation mimickers, glutamine or arginine, respectively, in
long-lived mammals. Conversely, glutamine or arginine residues in
short-lived mammals are replaced by reversibly acetylated lysine in
long-lived mammals. Pathway analyses highlight the involvement of
mitochondrial translation, cell cycle, fatty acid oxidation,
transsulfuration, DNA repair and others in longevity. A validation
assay shows that substituting lysine 386 with arginine in mouse
cystathionine beta synthase, to attain the human sequence, increases
the pro-longevity activity of this enzyme. Likewise, replacing the
human ubiquitin-specific peptidase 10 acetylated lysine 714 with
arginine as in short-lived mammals, reduces its anti-neoplastic
function. Overall, in this work we propose a link between the
conservation of protein acetylation and mammalian longevity.
Subject terms: Acetylation, Ageing, Proteome informatics
__________________________________________________________________
Acetylome and proteome data analysis across 107 mammalian species
identifies significant longevity-associated acetylated lysines. This
study proposes a link between protein acetylation conservation and
changes in mammalian longevity during evolution.
Introduction
The significant increase in human longevity and the growing proportion
of elderly in society over the past century are accompanied by an
exponential rise in age-related diseases^[42]1. This led to an urgent
need for new approaches for extending human healthspan. However, to
this end, a deeper understanding of the underlying mechanisms of
healthy ageing is required. Armed with such knowledge, it will be
possible to develop interventions that will help alleviate the negative
impact of ageing and convert the elderly population from dependent to
contributing individuals. One intriguing option to explore how healthy
ageing may be achieved is by analyzing nature’s largest ongoing
biological experiment, namely, evolution, and in particular, the
development of long-lived animals.
To date, few studies have sought to understand the mechanisms
underlying the increased lifespans of long-lived organisms. These
studies suggested that such species develop and enhance specific
longevity-favoring characteristics such as body size, brain
development, sociality, increased DNA repair, and protection against
tumor formation^[43]2. Specifically, a number of proteins/pathways
shown to control lifespan in short-lived model organisms may have
life-extending functions in long-lived ones. For example, the
expression of the well-known tumor suppressor protein p53, which was
shown to control the lifespan of short-lived organisms^[44]3, is
significantly increased in elephants. This finding was suggested to
explain the low incidence of cancer and increased survival in these
long-lived mammals^[45]4,[46]5.
Various attempts were also performed at the -omics level to identify
the regulation of lifespan in long-lived animals. Meta-analysis of
age-related gene expression profiles in mice, rats, and humans
identified common signatures of ageing, including inflammation, immune
response, and energy metabolism-related pathways^[47]6. Wider meta
RNA-seq analyses across databases of 26 or 41 mammalian species also
identified transcriptional signatures of known longevity-related
pathways^[48]7,[49]8. In addition to the above-mentioned pathways,
these analyses identified DNA repair, IGF1 expression, and
mitochondrial translation. Interestingly, the expression of these genes
was modulated by pro-longevity interventions, including mTOR inhibition
and caloric restriction (CR)^[50]9,[51]10. In contrast to transcriptome
analyses, most attempts to identify longevity-associated proteomic
signatures were performed in humans. For example, a recent study
identified 754 human plasma proteins that are associated with
chronological age and are mostly related to inflammatory response,
organismal injury, cell and organismal survival, and cell death
pathways^[52]11. In addition, Coenen et al. identified 273 plasma
proteins significantly associated with ageing^[53]12. Pathway and
network analyses of these proteins highlighted several pathways,
including those that were shown to regulate longevity, such as IGF
signaling, sulfur binding, TNFα (inflammation), and metabolic diseases.
Likewise, among the pathways of ageing-related proteins identified by
Wyss-Coray and his colleagues were sulfur binding and IGF1-related
hormonal signaling^[54]13. Besides transcriptome and proteome analyses,
several studies attempted to characterize the human age-related
metabolome and found several known pathways that were shown to regulate
longevity, such as kynurenine NAD^+ biosynthesis, one
carbon/transsulfuration, inflammation, oxidative stress, and lipid
metabolism pathways^[55]8,[56]14.
Reversible post-translational modifications (PTMs) refer to the
post-translational addition of any of a plethora of modifying
molecules, such as acetyl, phosphoryl, and methyl groups, to one or
more specific amino acid residues of a target protein (PTM
sites)^[57]15.
Surprisingly, despite the extensive studies on various -omics datasets,
to the best of our knowledge, no in-depth study has been performed to
explore the role of reversible protein PTMs in longevity regulation.
Yet, some PTMs were found to be associated with age-related diseases
and to accumulate with age^[58]16. The attachment of specific moieties
to a protein can affect a wide range of its characteristics, including
stability, enzymatic activity, localization, and interactions^[59]17.
Thus, PTMs regulate various biological processes, such as signal
transduction, gene expression, DNA repair, and metabolism. As a result,
in addition to the fundamental cellular roles, PTMs are a key factor in
regulating systemic processes, including adaptation to environmental
changes encountered by the organism over a lifetime. The plasticity of
such reversible PTMs can maintain homeostasis to preserve a healthy
lifespan and thus provides a specific rationale for their regulation of
longevity. Moreover, it can be hypothesized that over the course of
evolution, specific PTM sites evolved or mutated to support the
lifespan extension occurring in long-lived organisms. Accordingly,
exploring the regulation of lifespan by PTMs could offer major new
insight into the ageing process.
Protein acetylation on lysine ε-amino group is one of the most
extensively studied PTMs in eukaryotes. Lysine
acetyltransferases/deacetylases (KATs/KDACs) control the acetylation
status of thousands of proteins^[60]18. Still, although acetylation has
been connected to the regulation of lifespan^[61]19, it remains largely
unknown which of these proteins/pathways directly regulate ageing.
Significant results^[62]19–[63]23 have demonstrated that KAT/KDAC
activities directly control yeast, nematode, fly, and mammalian^[64]24
lifespan. For example, a transgenic (TG) mouse model overexpressing the
SIRT6 deacetylase lives longer and with improved health compared to
wild-type (WT) littermates^[65]25. Yet, acetylation sites that control
a healthy lifespan remain to be specifically explored. Traditionally, a
point mutation of acetylated lysine (K) to glutamine (Q) is used in
molecular biology to mimic constant acetylation, while the exchange
from K to arginine (R) is used to mimic the fixation of the
non-acetylated state of the protein^[66]26. Our hypothesis is that
during the evolution of long-lived organisms, a limited set of
acetylation sites in short-lived organisms were specifically replaced
by amino acids that mimic the fixed state of such PTMs, potentially
resulting in lifespan extension. Likewise, the acquisition of new
acetylation sites in long-lived organisms could also support the longer
lifespans of such animals.
Here, to explore the relationship between acetylation and lifespan
regulation in mammals, we created a computational tool, which we named
Post-translational modificAtions Regulator Of Healthspan (PHARAOH).
PHARAOH identifies sites significantly associated with lifespan
extension by comparing the conservation of acetylation sites in a set
of 107 mammalian proteomes and their correlation to longevity. Pathway
analyses of these sites identified various ageing-related pathways,
such as fatty acid metabolism, PPAR signaling, TCA cycle, translation,
one-carbon cycle /transsulfuration pathway (TSP), and DNA repair.
Validation of specific acetylation sites on cystathionine beta synthase
(CBS) from the TSP and Ubiquitin carboxyl-terminal hydrolase 10 (USP10)
of the DNA repair pathway addresses the mechanism underlying their
positive effect on longevity.
Results
Identifying longevity-associated acetylation sites
To identify PTMs that potentially regulate the extension of lifespan in
long-lived organisms, we employed the PHARAOH computational tool.
PHARAOH compares the conservation of PTM sites and whether each site
was replaced by another amino acid in a set of all identified mammalian
orthologous proteins. Next, PHARAOH uses sequence and lifespan data to
examine whether any PTM or specific amino acid (AA) replacement is
associated with a longer lifespan. Thus, we utilized PHARAOH to search
for specific lysine acetylation sites that regulate longevity. Global
mouse and human acetylomes (Supplementary Data [67]1 and [68]2) were
created based on identified acetylation data found in the
PhosphoSite^[69]27 database together with a mouse acetylome generated
by our lab, and consisted of 25,959 and 22,849 mouse and human
acetylation sites, respectively (Fig. [70]1a left panel). For this
study, we used both high and low throughput PhosphoSite analyses. To
identify the acetylation sites that are significantly associated with
longevity, three additional datasets were created. An orthologous
protein dataset and phylogenetic tree were created using the
OrthoFinder tool^[71]28 based on 107 mammalian proteomes from
Uniprot^[72]29 (Fig. [73]1a, middle panel). In addition, a maximum
lifespan dataset for these animals was generated, based on The Animal
Ageing and Longevity Database (AnAge)^[74]30 (Fig. [75]1a, right
panel). Specifically, during evolution, an acetylated/deacetylated
lysine (K) can be converted into arginine (K-to-R) or glutamine
(K-to-Q), mimicking a permanently deacetylated or acetylated lysine,
respectively^[76]26 (Supplementary Fig. [77]1a). Interestingly,
acetylated lysines tend to be more conserved than unacetylated lysines
(χ^2, P = 0.08, Supplementary Fig. [78]1b) in comparison between mouse
and human. Thus, the PHARAOH tool calculates the significance of the
correlation between conservation of a given acetylated site versus
conversion to R or Q and maximal lifespan (Fig. [79]1b).
Fig. 1. General overview of the PHARAOH computational tool.
[80]Fig. 1
[81]Open in a new tab
PHARAOH was designed to assess and identify correlations between amino
acid (AA) changes and a longer lifespan. a The tool uses three types of
data sets, mouse/human acetylomes (left box), a collection of mammalian
orthologue proteins, and the phylogenetic tree of each species based on
its orthologs set (middle box), and mammalian maximal lifespans (right
box). b The tool analyses changes in amino acids at each acetylation
site using pairwise sequence alignment between the acetylated peptide
and the orthologous protein of each mammal (upper panel), generating a
replacement matrix (middle panel). Subsequently, statistical analysis
and validation against the phylogenetic tree are employed to examine
the correlation between amino acid replacements and a longer lifespan
(lower panel). c An example of a significant acetylation site on Bphl
K188 from K-to-R analysis - the central portion of the figure showcases
the OrthoFinder phylogenetic tree. Surrounding the tree, the inner
circle represents the lifespan of each mammal, while the outer circle
displays the amino acid found at that site in each mammal. Lysine (K)
in pink arginine (R) in purple, other AA in turquoise, and in green
sites with no ortholog found. Color coding is shown on the right.
Created in BioRender. Cohen (2025) [82]https://BioRender.com/y84l114.
A replacement matrix was built based on pairwise sequence alignment
between each acetylated peptide and the orthologous mammalian protein.
Using the replacement matrix, maximal lifespan data, and the
phylogenetic tree, PHARAOH calculates the statistical significance of
the correlation between an acetylation/replacement site and longevity
(Fig. [83]1b and Supplementary Fig. [84]2, see “Methods” section for
detailed description). The OrthoFinder phylogenetic tree of 107 mammals
was validated with the recently published Zoonomia project^[85]31
phylogenetic tree of 62 overlapping mammals (Supplementary
Fig. [86]3a). Importantly, using a correction based on the phylogenetic
tree enabled us to eliminate the influence of evolutionary distances
between different mammals. This ensures that any bias introduced by
other evolutionary factors is neutralized. A representative output of
the analysis is shown in Fig. [87]1c.
R/Q conversion of acetylation sites in longevity
Comparison of the acetylation sites contained in the mouse and human
acetylomes with the orthologues’ dataset revealed 321 lysine to
arginine (K-to-R) and 161 lysine to glutamine (K-to-Q) substitutions
that were significantly associated with longer lifespan (Mann–Whitney
FDR < 0.1; phylogenetic tree statistical correction FDR < 0.05)
(Supplementary Fig. [88]3b, c). Importantly, the same analysis with
lysine to leucine (K-to-L), as a random control, identified only 8
longevity-associated substitutions (Supplementary Data [89]3). These
sites are only 3% of the total K-to-L replacements between mouse and
human, demonstrating the insignificance of this process in comparison
to K-to-R/Q, which consists of ~40% of such substitutes. In addition,
in comparison to the global acetylome, K-to-R/Q replacements did not
show significant enrichment in any specific protein domains or
non-domain regions across the 9251 known domains in the mouse proteome
(based on UniProt, Supplementary Data [90]4). Similar to the global
acetylome, the largest group was mapped to disordered regions,
suggesting that acetylation may play a role in stabilizing undefined
structures, as previously reported^[91]26,[92]32. Interestingly, as
seen in Supplementary Fig. [93]4, with the increase in lifespan during
evolution, the conversion from K to either R or Q happened gradually
rather than after a specific lifespan threshold. Pathway analyses and
protein-protein interaction (PPI) of the K-to-R sites assigned these
changes to proteins associated with protein translation and folding, as
well as many metabolic pathways, including those of fatty acid
metabolism, PPAR signaling, the TCA cycle, amino acid biosynthesis, and
the one-carbon/TSP cycle. (Fig. [94]2a, b). Pathway analyses of the
K-to-Q sites identified cytochrome p450, peroxisome, mitochondrial
translation, taurine metabolism, fatty acid β-oxidation, and others
(Fig. [95]2c, d). Importantly, pathway analyses of the human orthologs
of these mouse proteins revealed a similar set of pathways,
demonstrating that their role in longevity is potentially conserved
(Supplementary Fig. [96]5a, b).
Fig. 2. Enrichment analysis of mouse longevity-associated sites.
[97]Fig. 2
[98]Open in a new tab
a Pathway enrichment analysis of K-to-R replacement sites
(hypergeometric test and Benjamini–Hochberg p-value correction by
Metascape), and b their corresponding MCODE clusters identified from
PPI networks. c, d Similar analysis for K-to-Q replacements. e CC
analysis of K-to-R (green) and K-to-Q (blue) replacements. pLOGO of 7
amino acids flanking the mouse total acetylome (f), the
longevity-associated acetylation sites replaced to R (g), or Q (h)
sites in the mammalian ortholog set. K-to-R = lysine to arginine
replacement, K-to-Q = lysine to glutamine replacement. For (f–h),
significantly enriched AA are seen between the red lines.
While maximal and average lifespan are correlated, their regulatory
pathways may differ. We analyzed K-to-R/Q replacements using an average
lifespan dataset of 93 mammals, based on Animal Diversity^[99]33, Max
Planck Longevity Records^[100]34, and other datasets (Supplementary
Data [101]5). Pathways unique to the average lifespan included
beta-oxidation of long fatty acids, NAD/NADH metabolism, and
glycolysis/gluconeogenesis (Supplementary Data [102]5 and [103]6). For
maximal lifespan, the Alzheimer’s disease pathway was prominent.
Despite these differences, over 80% of the pathways were common,
suggesting that analyses based on maximal lifespan provide insights
into both median and maximal lifespan. Interestingly, major members of
these pathways were previously found to be associated with longevity.
For example, the rate-limiting enzyme of the TSP, CBS, is a main
producer of hydrogen sulfide (H[2]S), which was found to mediate the
effects of a CR diet on longevity^[104]35. Cellular component (CC)
analyses, based on Gene Ontology (GO) annotations, of the identified
sites revealed that these proteins are localized mainly to the cytosol
and the mitochondria (Fig. [105]2e). No K-to-R sites were found in the
nuclear proteins, nor K-to-Q sites in proteins of the plasma membrane
and the ER.
In order to identify the specific acetylation consensus sequence, pLogo
analysis was performed on the whole mouse acetylome, and no consensus
sequence was found, as previously published^[106]36. Yet, an enrichment
for lysine residues flanking the acetylated K was found, probably due
to other acetylation sites nearby (Fig. [107]2f). Importantly, these
positive K’s and R were eliminated on positions −1,−2 and were replaced
with D/E on these positions. F/Y were enriched on position +1. These
findings might have implications for the enzymatic activity of
KATs/KDACs. pLogo analyses of main CC as cytosol, mitochondria, and
nucleus showed that D/E at positions −1,−2 are mostly from
mitochondrial and cytosolic acetylated proteins. Whereas the G/A at
position −1 originated from nuclear proteins (Supplementary
Fig. [108]6a–c). However, pLogo analysis on K-to-R sites identified
overrepresented D/EAV at positions −3, −2, −1 and an enrichment for K
downstream to the acetylation site. Additionally, R/YK/S were
underrepresented at positions −2, −1, and T on position +1
(Fig. [109]2g). Interestingly, tyrosine, serine, and threonine (Y, S,
and T, respectively) can potentially be phosphorylated, suggesting that
additional PTMs flanking the acetylation sites may also be associated
with lifespan. For K-to-Q sites, pLogo analysis identified hydrophobic
amino acids VVL at positions −3, −2, −1 and DGK at positions +1+2+3
(Fig. [110]2h). This finding suggests that specific KATs/KDACs may
regulate the acetylation status of longevity-associated acetylation
sites.
Since the effect of these conversions is expressed in long-lived
animals, we searched for transcription factors that are known to
regulate the enriched pathways in humans. Such factors can provide an
additional regulatory layer on ageing. SP1, PPARG, PPARA, SREBF1, ATF2,
RelA, VDR and NFKB1 regulators were found within K-to-R
longevity-associated sites (Supplementary Fig. [111]7a). Importantly,
these regulators are significantly associated with ageing mechanisms
such as inflammation (RelA of NFKB1), DNA repair (ATF2 and SP1), and
metabolism (PPARG, PPARA and VDR). The same analysis identified SP1 and
NFE2L2 /NRF2 transcription factors in the K-to-Q set (Supplementary
Fig. [112]7b). Similarly, NFE2L2 /NRF2 is involved in ageing-related
pathways, such as protection against oxidative stress, and likely
mediates CR protection against carcinogenesis^[113]37. In addition,
gene-disease association (GO_DisGeNET) analysis was performed in order
to examine which diseases are associated with longevity-related K-to-R
or K-to-Q sites in humans. Interestingly, the majority of the most
highly significant results were of metabolic diseases, particularly
liver-related, and other diseases such as diabetes and other
metabolic-related pathologies such as myopathy and lethargy, all known
to be ageing-related (Supplementary Fig. [114]7c, d).
CBS K386R enhances its pro-longevity activity
Next, we further explored the role of a longevity-associated
acetylation site on CBS, a mediator of the CR response. CBS K386 was
acetylated in the mouse reference dataset (both in our lab and
PhosphoSite data) and exchanged with R in long-lived mammals. The
average lifespan of mammals with K-to-R conversion, such as humans, was
significantly higher than that of animals with conserved K at this site
(Mann–Whitney FDR < 0.1, q-value = 0.00014; tree statistical correction
FDR < 0.001) (Fig. [115]3a, b and Supplementary Fig. [116]8). Thus, we
next followed the effect of K386R replacement on CBS H[2]S production
activity. Human embryonic kidney (HEK) 293T cells overexpressing either
WT, K386Q, or K386R mouse CBS were examined for their H[2]S production
capacity using the lead acetate method as previously described^[117]38.
As seen in Fig. [118]3c, in comparison to cells overexpressing the WT
protein, overexpression of K386R CBS resulted in significantly higher
H[2]S production capacity (p < 0.05). Cells expressing K386Q CBS had a
similar H[2]S production capacity as cells expressing the WT protein.
In the reverse experiment, the H[2]S production activity of
immunoprecipitated WT, R389K, or R389Q human CBS was tested. While
activity of the R389K mutant was similar to the activity of the WT
protein, the acetylation-mimicking mutant R389Q exhibited a
significantly reduced H[2]S production capacity (p < 0.001,
Fig. [119]3d). The non-significant trend of lower H[2]S production of
R389K compared to the WT CBS is most likely due to low percentages of
acetylation on the mutated lysine. All together, these findings show
that constitutive deacetylation of the CBS K386 residue, as found in
long-lived animals, promotes H[2]S production and potentially
contributes to their longer lifespan.
Fig. 3. CBS K386R enhances its H[2]S production activity.
[120]Fig. 3
[121]Open in a new tab
a Maximal lifespan of animals with conserved K vs. animals with K-to-R
conversion at cystathionine beta synthase (CBS) lysine 386 (K386)
(FDR < 0.1). Dot color represents the maximal lifespan of a given
species. Schematic representation of the various maximal lifespans of
species with K vs. R is shown on the left. Species are ordered by
lifespan along the Y-axis. Elephant’s silhouette was contributed by
Leonardo255. Created in BioRender. Cohen (2025)
[122]https://BioRender.com/l52n801. b Sequence alignment of CBS K386 in
mouse and R389 in human using Clustal Omega. c Hydrogen sulfide (H[2]S)
production capacity in HEK293T cells lysates overexpressing flag-tagged
mouse wild-type (WT), K386R, K386Q CBS or GFP control, using lead
acetate strips. Tubulin was used as a loading control. d H[2]S
production capacity of flag-tagged human WT, R389K or R389Q CBS
immunoprecipitated from HEK293T cells. ImageJ quantification of (c and
d) is shown on the right. Number of biological replicates: n = 3 (c)
and 4 (d) independent experiments. H[2]S production was corrected to
CBS expression levels. For (c) and (d), one-way ANOVA with Bonferroni
post hoc was used. For all graphs, bars represent mean ± SEM.
*p < 0.05, ***p < 0.001. Source data are provided as a Source Data
file.
The long-lived acquired acetylome
During evolution, the specific generation of new acetylation sites
would be a complementary set of events to the above-mentioned
replacements. Specifically, this would involve the replacement of R and
Q residues present in short-lived animals with acetylated K residues in
long-lived mammals (R-to-K and Q-to-K, respectively). Therefore, using
PHARAOH, we examined the conservation of human acetylated K sites among
all mammalian orthologs. Particularly, the data was searched for R-to-K
and Q-to-K sites within the 22,849 human acetylation sites. We
identified 495 R-to-K and 150 Q-to-K sites that were significantly
associated with longer lifespan (Mann–Whitney FDR < 0.1, tree
statistical correction FDR < 0.05). In comparison to the global human
acetylome, R-to-K replacements did not show significant enrichment in
any specific protein domains or non-domain regions across the 9767
known domains in the human proteome (based on UniProt, Supplementary
Data [123]4). However, a comparison of the total number of acetylation
sites mapped to domains between the global human acetylome and R-to-K
replacements revealed a significant association, which was not observed
for Q-to-K replacements. Similar to mouse data, the largest group was
mapped to disordered regions. Enrichment analyses of the R-to-K sites
assigned these changes to various pathways, including chromosome
organization, amino acid metabolism, and cell cycle (Fig. [124]4a).
Strikingly, PPI analysis identified many ageing-related pathways in
this dataset, including cellular respiration, ribosomal biogenesis,
regulation of protein translation, response to stress, and mismatch DNA
repair and diseases of DNA repair pathways (Fig. [125]4b and
Supplementary Fig. [126]9a). Analyses of Q-to-K events also identified
many ageing-related pathways, such as response to stress, the TCA
cycle, sulfur compound metabolic process (including proteins from the
TSP related pathway, one-carbon pool by folate cycle), and response to
starvation (Fig. [127]4c). PPI analysis also identified ribosomal
biogenesis and DNA repair pathways (Supplementary Fig. [128]9b).
Interestingly, CC analyses of all identified R/Q-to-K sites revealed
that these proteins localized to most cell components. However, no
R-to-K sites were found in proteins expressed in the endoplasmic
reticulum (ER), and no Q-to-K sites were found in the extracellular
space or cytoplasmic proteins (Fig. [129]4d).
Fig. 4. Enrichment analysis of human longevity-associated sites.
[130]Fig. 4
[131]Open in a new tab
a Pathway enrichment analysis of R-to-K replacement sites
(hypergeometric test and Benjamini–Hochberg p-value correction by
Metascape) and b their DNA repair corresponding MCODE clusters
identified from PPI networks. c Pathway enrichment analysis of Q-to-K
replacement sites using Metascape. d CC analysis of R-to-K (green) and
Q-to-K (blue), based on Gene Ontology (GO) annotations. e Pathway
enrichment analysis of R-to-K DNA metabolic processes and f their
corresponding DNA repair MCODE clusters identified from PPI networks.
pLogo analysis of the global human acetylome revealed an enrichment for
lysine and an under-representation of C in the flanking sequence. As
suggested above for the mouse acetylome, these lysines are the adjacent
acetylated lysines (Supplementary Fig. [132]9c). Interestingly, there
was an overrepresentation for G/A/D in position −1, suggesting that in
humans, there is a G/A/D [(-1)]K enrichment. Further pLogo analyses of
CC showed that G/A/D in position −1 stemmed from the mitochondrial and
cytosolic acetylated proteins, whereas nuclear protein showed only G at
−1 (Supplementary Fig. [133]9d–f). Likewise, a pLogo analysis was
performed using the R-to-K sites (Supplementary Fig. [134]9g) and
showed an enrichment for K downstream of the acetylated site, E on
position −7 and SS/AK on positions −1 and −2. For Q-to-K sites, the
pLogo analysis did not identify a specific logo besides a tendency for
F on position −2 and a higher probability for A between −7 and +1
(Supplementary Fig. [135]9h). Further search for regulators of the
enriched pathways in identified R-to-K proteins showed that the vast
majority of regulators have a negative/positive role in tumorigenesis,
such as STAT1/3, P53, BRCA1, PARP1, MYCN, and E2F1/4 (Supplementary
Fig. [136]9i). Likewise, out of the seven identified regulators of
Q-to-K proteins, TP53, STAT1, BRCA1, and SPI1 have a direct
enhancing/preventing role in tumorigenesis, whereas manipulation of the
others was also suggested to affect cancer (Supplementary
Fig. [137]9j). In addition, GO_DisGeNET analyses of R-to-K and Q-to-K
revealed several human ageing-associated diseases, including myocardial
ischemia, inflammatory disorders, multiple types of cancer, ataxia
telangiectasia, and Werner syndrome (Supplementary Data [138]7 and
[139]8).
Remarkably, as seen in Supplementary Fig. [140]10, the initial
conversions from R/Q-to-K occurred early in evolution and more sites
accumulated as it progressed. Interestingly, as seen in Fig. [141]4e,
f, pathway enrichment analyses of the long-lived associated acetylome
also highlighted various DNA repair pathways. These include
non-homologous end joining (NHEJ), homology-directed repair of DNA
double-strand breaks, and DNA mismatch repair. Importantly, substantial
evidence suggests DNA repair as a key mechanism of longevity, mostly
via protection against the two major threats to long survival: cancer
and cognitive decline. Thus, acquiring acetylation on DNA repair
proteins during evolution can support healthy longevity. This suggests
that accumulating new acetylation sites helps address the gradual
increase in body size associated with longevity.
USP10 K714 Acetylation controls PCNA stability
Next, we aimed to further elucidate the effect of acquired acetylation
sites in longevity. To this end, the effect of K714 acetylation of a
DNA repair pathway protein (Fig. [142]4b) ubiquitin-specific peptidase
10 (USP10) (Mann–Whitney FDR < 0.05; tree statistical correction
FDR < 0.05) was examined (Fig. [143]5a). In short-lived mammals, there
is a R instead of the K714 residue of human USP10. USP10 catalyzes a
hydrolase activity, which removes conjugated ubiquitin from its target
proteins, such as Proliferating Cell Nuclear Antigen (PCNA), thereby
stabilizing them^[144]39. Increased PCNA levels are associated with
poor prognosis of various tumors^[145]40. Indeed, a correlation test
showed a significant positive correlation between PCNA and USP10 levels
in lung, glioblastoma, and breast cancers (P = 0.001, 0.000001, and
0.002, respectively) (Fig. [146]5b), supporting the function of USP10
in stabilizing PCNA. Since long-lived animals tend to be physically
larger, one of the major challenges facing such animals is the higher
probability of cancer development with age^[147]41,[148]42. Thus, the
acquisition of USP10 acetylation in long-lived animals might contribute
to addressing this challenge. PCNA protein levels were examined in
human colorectal carcinoma (HCT116) cells overexpressing either WT,
K714Q or K714R human USP10. The translation inhibitor cycloheximide
(CHX) was used to specifically examine the effect on protein
stabilization. As seen in Fig. [149]5c, in comparison to cells
overexpressing the WT protein or the mutant K714R, overexpression of
K714Q resulted in significantly higher PCNA protein levels with or
without CHX treatment. Besides PCNA, USP10 has a spectrum of targets
that might affect tumorigenesis as well^[150]43. Thus, we followed the
role of acetylated USP10 on its global deubiquitylation activity. As
seen in Supplementary Fig. [151]11, in comparison to WT or K714Q, the
expression of constitutively deacetylated USP10 mutant K714R results in
significantly lower global ubiquitylation levels. Therefore,
acetylation/deacetylation controls USP10 activity, and it would be of
interest to identify additional USP10 targets that affect longevity.
This result shows a potential role of the acquired acetylation on USP10
in reducing cancer incidence, and hence its role in promoting
longevity. Altogether, the fixation of the acetylation status or the
acquisition of new acetylation sites during evolution enables
long-lived animals to enhance pro-longevity mechanisms. Specifically,
our study demonstrated that acetylations play a crucial role in
promoting H[2]S production and DNA repair, two key factors that play a
significant role in enhancing a healthy and extended lifespan.
Fig. 5. Acquisition of acetylated K714 on hUSP10 regulates PCNA levels.
[152]Fig. 5
[153]Open in a new tab
a Significant acetylation site on Ubiquitin-Specific Peptidase 10
(USP10) lysine 714 (K714) from R-to-K analysis. The central portion of
the left panel shows the OrthoFinder phylogenetic tree. Surrounding the
tree, the inner circle represents the lifespan of each mammal, while
the outer circle displays the amino acid found at the site in each
mammal (K in pink, R in blue, and other AA in green). Color code is
shown on the right (left panel). Maximal lifespan of animals with
conserved K vs. animals with R/Q/other AA at USP10 K714 (FDR < 0.1).
Dot color represents the maximal lifespan of a given species. b
Pairwise Pearson correlation between USP10 and PCNA protein expression
levels in lung (left), glioblastoma (central), and breast (right)
cancers. Each dot represents a single patient, color code indicating
tumor stage is shown on the right. c Biological replicates of PCNA
levels in HCT116 cells overexpressing GFP, WT, K714R, and K714Q USP10
with or without cycloheximide (CHX) treatment for 8 h. Each condition
was tested using biological triplicates. n = 3 independent experiments.
Tubulin was used as a loading control. ImageJ quantification is shown
below. One-way ANOVA with Bonferroni post hoc was used. For all graphs,
bars represent mean ± SEM. **p < 0.01, ***p < 0.001, ****p < 0.0001.
Source data are provided as a Source Data file.
Discussion
Tens of thousands of reversible acetylation sites allow the organism to
respond to changes in internal and external conditions and thereby
prolong survival of long-lived animals. To identify those acetylation
sites that promote longevity, we developed the PHARAOH computational
tool. The conversion of 482 acetylation sites found in short-lived
mammals to either R or Q residues in long-lived mammals was
significantly associated with extended lifespan. These proteins,
although localized to almost all CC, are significantly enriched in
specific cellular pathways, particularly ageing-related pathways. These
include translation, fatty acid metabolism, PPAR signaling, TCA cycle,
amino acid biosynthesis, and the one-carbon/TSP, mitochondrial
translation, taurine metabolism, and others. Further activity
validation of a specific longevity-associated acetylation site, K386 of
CBS, showed that the conversion to a permanently deacetylated state in
long-lived mammals increases the production of the pro-longevity
gasotransmitter, H[2]S. In addition, 695 acetylated lysines were
significantly acquired in long-lived mammals. These sites are also
distributed to all CC; however, a larger fraction was found in the
nucleus and extracellular compartments. The acquired acetylated lysine
sites were also enriched in various pathways, including ageing-related
pathways such as translation, TCA cycle, and amino acid biosynthesis.
Likewise, regulation analyses of the significantly changed acetylated
proteins identified transcription factors associated with many
ageing-related pathways such as oxidative stress, inflammation, and DNA
repair. Uniquely, many identified acetylated proteins are enriched in
cell cycle and DNA repair pathways. Further activity analysis of USP10,
a member of these pathways, showed that the acquisition of acetylated
sites in long-lived mammals restrains the oncogenic activity of this
protein. Altogether, these findings identified the longevity-associated
acetylome and provide two mechanisms, via H[2]S production and
anti-cancer, for its positive impact on lifespan.
Pathway analyses of longevity-associated fixed or new acetylation sites
(K-to-Q/R or Q/R-to-K, respectively) identified numerous
ageing-associated pathways. These include pathways that were also
identified by previous transcriptomic and metabolomic analyses, such as
one carbon/TSP, translation, mitochondria-related pathways, energy, and
fatty acid metabolism. In addition to demonstrating the strength of the
PHARAOH tool, these results also emphasize the importance of various
pathways identified by PHARAOH in regulating longevity. Moreover, the
identified acetylation sites revealed a new layer of regulation of
these fundamental longevity pathways.
The enzymatic activities of two members of the one carbon/TSP pathway,
cystathionine gamma-lyase (CGL) and cystathionine beta synthase (CBS),
produce the gasotransmitter H[2]S. Enhanced H[2]S production was found
to mediate the positive effect of CR^[154]39. PHARAOH analysis found a
significant correlation between CBS K386R conversion and longevity.
Accordingly, CBS K386R adaptation significantly increased H[2]S
production (Fig. [155]3). This suggests that the fixation of
deacetylated CBS might mediate the increased lifespan of long-lived
mammals. Indeed, it would be of great interest to follow the effect of
such substitution, as others found by PHARAOH, on mice lifespan in
future research. However, continuous exposure to excessive levels of
H[2]S is highly toxic^[156]44. Therefore, it is noteworthy that the
observed increase in H[2]S production did not reach the toxic
concentration range, and it is likely that as yet uncharacterized
mechanisms maintain H[2]S levels within the beneficial range.
Interestingly, whereas fixed or new acetylation sites share enriched
pathways, we also identified unique pathways associated with
acetylation sites that were gained in long-lived animals. Specifically,
these unique pathways include DNA repair and the cell cycle. Longevity
is positively associated with increased body size. As a result,
long-lived animals have 3–6 orders of magnitude more cells than
short-lived mammals. Given their lifespan, which is up to 30 times
longer, one would expect that long-lived animals would show much higher
cancer incidence. Yet, as established by Peto’s Paradox, no
statistically significant relationship is found between body size and
cancer incidence^[157]45, indicating that long-lived animals have
developed mechanisms to avoid cancer. Indeed, previous studies showed
that elephants have lower cancer incidence due to 20 copies of the p53
tumor suppressor gene^[158]4,[159]5. Hence, we suggest that one
mechanism underlying the longer lifespan of large animals is via the
conversion of R or Q in DNA repair and cell cycle proteins to
acetylated K, to protect against cancer. In addition, in the
acquisition of a new acetylation site on DNA repair and cell cycle
proteins, the reversible acetylation could allow the cell to control
the decision between repair and continued division, senescence, or
apoptosis. In support of this, our findings of a significant positive
correlation between USP10 and PNCA levels (Fig. [160]5b), along with an
acquired acetylation site on the human USP10 (K714), which decreases
PCNA stabilization by USP10, demonstrate the need for acetylated K with
reduced activity in humans.
The accumulation of longevity-associated acetylation sites (R/Q-to-K,
Supplementary Fig. [161]10) occurred more rapidly in evolution in
comparison to K-to-Q/R along with the increase in lifespan
(Supplementary Fig. [162]4). Cancer-related pathways such as DNA repair
and cell cycle were enriched in R/Q-to-K proteins. This suggests that
relatively early during evolution, mammals had to acquire these new
acetylation sites in order to cope with the increase in body mass and
the potential increase in cancer risk.
In comparison to R/Q-to-K, CC analysis of K-to-R/Q showed a significant
enrichment of mitochondrial proteins (Figs. [163]2e and [164]4d).
Mitochondrial protein acetylation occurs mostly through a non-enzymatic
pathway, mediated by acetyl-CoA^[165]45 and to date, only mitochondrial
KDACs but not KATs have been identified. Thus, acetylation of proteins
within the mitochondria is only partially reversible. Therefore, it is
possible that during the evolution of longevity, these mitochondrial
longevity-associated acetylation sites were fixed to avoid dependence
on fluctuating acetyl-CoA levels. Importantly, the partial dependency
in enzymatic activities can lead to a large number of acetylated
mitochondrial proteins, and the finding of many mitochondrial pathways
here might be inevitable. However, in comparison to the number of all
mitochondrial acetylation sites within the global acetylome, the amount
of longevity-associated mitochondrial sites within all PHARAOH K-to-Q/R
results is statistically significant (Chi-square test, P < 0.00001).
Thus, the high representation of mitochondrial pathways identified by
PHARAOH’s significant fixed sites is not arbitrary. In addition,
fixation of these sites enables the acetyl-CoA to be used in other
cellular compartments or for other purposes, such as a source of energy
by the TCA cycle. Indeed, recent findings showed that increased
longevity is associated with maintaining energy production in old
age^[166]25,[167]46,[168]47. Moreover, fixation of acetylation might
reduce the dependency of KDACs on external stimuli for releasing
Acetyl-CoA for energy.
The conversion of 482 acetylation sites of short-lived mammals to R or
Q in long-lived mammals was significantly associated with longevity.
Yet, the impact of individual replacements on lifespan extension and
whether some have redundant effects is not known. In line with this, as
seen in Supplementary Fig. [169]4, K-to-R/Q transitions occurred
gradually during the evolution of longevity. It would be interesting to
use machine learning tools to explore which combination of converted
sites has the highest positive effect on longevity. Nevertheless,
acetylation is only one modification out of ~400 known PTMs. Further
research is required to explore the impact of different combinations of
lysine acetylation and other modifications on longevity.
Do all pathways contribute to longevity? To address this, we performed
pathway analysis using non-significant sites that fit the selection
criteria applied by PHARAOH. A comparison of the top 20 identified
pathways with all longevity-associated pathways revealed three that
were not overlapping: mitochondrial protein degradation, cytoskeleton
in muscle cells, and carboxylic acid metabolic processes. Since these
pathways involve up to hundreds of proteins, some of which are shared
with significant pathways, it’s challenging to draw evolutionary
conclusions about lifespan extension. This complexity is compounded by
the absence of methods to analyze how specific protein modifications
affect the broader activity of these proteins within pathways.
Most animals die before reaching old age due to various causes, leaving
natural selection with a limited window to influence lifespan. Thus,
several theories, such as mutation accumulation, antagonistic
pleiotropy, and the disposable soma theory, have been proposed to
explain the evolution of aging and lifespan^[170]48. The antagonistic
pleiotropy theory suggests that alleles or pathways that have a
beneficial effect early in life, and therefore tend to accumulate, also
have a detrimental effect later in life, thereby promoting aging. In
the context of longevity-associated acetylations, one could propose
that the acquisition of new acetylation sites (R/Q-to-K replacements)
allows the organism to maintain early-life benefits, while
deacetylation or acetylation can mitigate the negative effects in later
life. An example of this might be USP10, which promotes growth via
PCNA/cell cycle regulation during youth, while potentially its
acetylation in later life slows these processes, reducing the risk of
age-related cancer. The alternative disposable soma theory suggests
that aging arises from an imbalance in resource allocation,
prioritizing reproduction over somatic maintenance, given the
likelihood of early death from external threats. However, improvements
in metabolism could enable organisms to invest more in somatic
maintenance and repair. Indeed, replacements leading to constant
acetylation or deacetylation (K-to-R/Q replacements) are often linked
to metabolic pathways, such as beta-oxidation and glucose metabolism,
which fits the disposable soma theory by enhancing energy production.
These improvements in repair, particularly those related to genome
stability, would also benefit from R/Q-to-K replacements that affect
DNA repair, promoting the cellular flexibility required for fitness.
They will also allow complexity, particularly of the brain, that is
associated with increased lifespan^[171]49.
One striking finding of this study is that in contrast to global
acetylation sites, the flanking polypeptide sequences of the
longevity-associated acetylation sites are enriched or depleted in
specific amino acids (Figs. [172]2g, h and Supplementary Fig. [173]9g,
h). This finding suggests that the activity of one or more specific
KDAC/s or KAT/s regulates longevity. In yeast, genetic manipulation of
KDACs, such as hda1, hda2, or rpd3 deletion, or Sir2 overexpression
significantly extends lifespan^[174]22,[175]50,[176]51. In addition,
deletion of the KAT SAS2 significantly extends yeast lifespan^[177]20.
Likewise, in worms and flies, mutation or overexpression of various
KDACs/KATs was found to extend their lifespan^[178]50,[179]52,[180]53.
In mammals, only the manipulation of sirtuins was found to extend mouse
lifespan. Overexpression of hypothalamic-specific SIRT1 extends mouse
lifespan by 10%^[181]54 and whole body SIRT6 overexpression extends
mouse lifespan by up to almost 30%^[182]46. Thus, it would be of great
interest to explore which of the identified longevity-associated
acetylation loci is regulated by SIRT6. Moreover, to date, no
manipulation in KAT activity or levels has been found to extend
mammalian lifespan. Accordingly, it would be important to elucidate if
a mammalian homolog of KAT that was found to extend yeast/worm/fly
lifespan, or another as yet unidentified KAT homolog, regulates
mammalian lifespan. Identification of such a KAT, together with SIRT6,
would provide potential targets for developing drugs supporting
healthspan extension.
In this study, we characterized the longevity-related acetylome and its
associated pathways. These findings shed light on the previously
unknown role of PTMs in general, particularly acetylation, in
regulating longevity. In addition, this set of acetylation sites and,
as yet unidentified, key regulators of these changes during evolution
can suggest future therapeutic targets to promote longevity.
Methods
The research conducted in this study complies with all relevant ethical
regulations. All procedures involving mice and experimental protocol
(32-06-20) were approved by the Institutional Animal Care and Use
Committee of Bar Ilan University and by the Ministry of Health of
Israel.
Animal experimentation and acetylome generation
Mice were housed on a 12 h light / dark cycle at room temperature
(22–24 °C) with a relative humidity within 45–65% in the Bar Ilan
animal facilities. Mice were maintained on a standard rodent chow diet
with ad libitum access to food and water. All mice used in these
experiments were in good health. Mice were kept under specific
pathogen-free conditions in IVC cages that were routinely screened and
found negative for viral serology and both endo and ectoparasites. Male
littermates were used for all experiments.
LC-MS/MS-based acetylome
Lysine acetylome of mouse liver was performed as described^[183]55 with
minor modifications. Briefly, liver tissues from 18 male mice
(C57BL/J6) were homogenized in denaturation buffer containing 9 M urea,
20 mM HEPES, 1 µM TSA, and 5 mM NAM. Samples were sonicated for 20 s
with an amplitude of 40%, and then centrifuged. Next, 7 mg lysate was
taken from each sample and added to 1 mM DTT. Samples were then
incubated for 30 min at room temperature with shaking at 1000 rpm,
added to 5 mM IAA, and incubated for an additional 30 min. Trypsin /
LysC (1 µg / 1 mg protein) cleavage was performed at room temperature
for 2-3 h. The samples were then diluted with 20 mM HEPES to a final
urea concentration of 2 M. Trypsin was added at a ratio of 1 µg /
100 µg protein, and the samples were incubated overnight at room
temperature. The samples were then added to 1% acetonitrile (ACN) and
adjusted to pH <3 with TFA. The samples were purified on C18 columns
(Waters WAT036800), and the eluate was taken for IP acetyl lysine. A
mixture of two pan-acetyl lysine antibody beads (Immunochem and Cell
Signaling) was used at a 1:1 ratio^[184]55. The process was then
continued following the Cell Signaling Acetylome kit protocol.
Mass spectrometry analysis
The tryptic peptides were desalted using C18 tips (Top tip, Glygen),
dried, and re-suspended in 0.1% Formic acid. The peptides were resolved
by reverse-phase chromatography on 0.075 × 180-mm fused silica
capillaries (J&W) packed with Reprosil reversed phase material (Dr
Maisch GmbH, Germany). The peptides were eluted with different
concentration of Acetonitrile with 0.1% of formic acid: a linear
180 min gradient of 5 to 28% acetonitrile followed by a 15 min gradient
of 28–95% and 25 min at 95% acetonitrile with 0.1% formic acid in water
at flow rates of 0.15 μl/min. Mass spectrometry was performed by Q
Executive HFX mass spectrometer (Thermo) in a positive mode (m/z
300–1800, resolution 120,000 for MS1 and 15,000 for MS2) using
repetitively full MS scan followed by collision induces dissociation
(HCD, at 27 normalized collision energy) of the 30 most dominant ions
(>1 charges) selected from the first MS scan. The AGC settings were
3 × 106 for the full MS and 1 × 105 for the MS/MS scans. The intensity
threshold for triggering MS/MS analysis was 1 × 104. A dynamic
exclusion list was enabled with an exclusion duration of 20 s.
Data Analysis
The mass spectrometry data was analyzed using the MaxQuant software
1.5.2.8^[185]56,[186]57 for peak picking and identification using the
Andromeda search engine, searching against the mouse proteome from the
Uniprot database with mass tolerance of 6 ppm for the precursor masses
and the fragment ions. Oxidation on Met, Dimethyl (KR), Methyl (KR),
Trimethyl (K), Acetyl (K), and protein N-terminus acetylation were
accepted as variable modifications, and carbamidomethyl on cysteine was
accepted as static modifications. Minimal peptide length was set to six
amino acids, and a maximum of two miscleavages was allowed. The data
was quantified by label-free analysis using the same software. Peptide-
and protein-level false discovery rates (FDRs) were filtered to 1%
using the target-decoy strategy. Protein tables were filtered to
eliminate the identifications from the reverse database and common
contaminants and single peptide identifications.
Orthologous proteins and phylogenetic tree prediction
OrthoFinder 2.5.4^[187]28 was applied to compute the orthologs of mouse
or human proteins in 107 mammals. To reduce computation time, the
proteomes of human/mouse were grouped with those of other mammals
within separate directories, allowing the algorithm to be executed in
parallel across these directories. Next, a phylogenetic tree comprising
all 107 mammals was constructed based on the calculation of all versus
all orthologs.
PHARAOH analyzed two phylogenetic trees, the Zoonomia project
tree^[188]31, containing 62 animals overlapping with our dataset, and
the OrthoFinder^[189]28-based tree using our 107-mammals’ dataset
(Supplementary Fig. [190]3a). Final outcomes were derived from the
intersection of significant findings obtained from both analyses. The
distribution of these results is presented in Supplementary
Fig. [191]3b–e.
Phylogenies and comparative methods
Statistical validation
Since during evolution different organisms evolved from common
ancestors, it introduces a level of dependence between animals. Thus,
the standard assumption of variable independence cannot be used for the
statistical analysis of the PHARAOH^[192]58. To acknowledge the fact
that species are not fully independent, a novel statistical test was
devised that incorporates the evolutionary context. This allows the
examination of the relationship between amino acid changes and
longevity, regardless of phylogenetic distances. The statistical test
consisted of two parts. First, the correlation between maximal lifespan
and AA replacement was examined; then, a correction was introduced for
the distances between the animals on the evolutionary tree. A
pseudocode illustrating the algorithm of PHARAOH is shown in
Supplementary Data [193]9.
Part I (Supplementary Fig. [194]2a) - correlation between amino acid exchange
and longevity-
Data preparation
The acetylome datasets used for the replacement matrix are based on the
14 AA flanking the amino acid of interest. An entry in the matrix is
denoted as: Mi,j = the amino acid found in mammal j, at the orthologous
site to the i acetylation site in human/mouse.
For each row in the replacement matrix, the mammals were divided into
two groups based on the amino acid found at the specific acetylated
site: lysine site of reference (K) (includes either mouse or human), or
arginine (R)/glutamine (Q)/other. Each group contains the maximal
lifespan in captivity for each member.
Correlation test
To identify AA substitutions (K-to-R/Q) that significantly correlate
with longevity, the Mann–Whitney test was employed to compare the
lifespans between the two above-mentioned groups that were divided
based on their amino acid found at the acetylation site. A minimum of
three mammals was required in each group to ensure significant
findings. False Discovery Rate (FDR) correction was applied to account
for multiple testing, and a significance level of q-value ≤ 0.1 was
adopted.
Part II (Supplementary Fig. [195]2b and c) - phylogenetic correction
The assumption that the lifespan difference between the two mammals in
each comparison is derived from an exchange of the examined acetylated
lysine, without contributions from phylogeny, was taken as the H[0]
hypothesis.
To normalize the impact of the phylogenetic tree on the statistical
validation process, each acetylation site (represented by a row in the
replacement matrix) was further divided into a set of pairs derived
from the database. The relationship between a pair of mammals is
represented by three factors (Supplementary Fig. [196]2, table):
* Lifespan difference.
* Phylogenetic (tree) distance.
* The amino acid (AA) found in the examined site.
Importantly, this part is independent of Part I and aims to examine if
the difference in lifespan is due to changes in amino acids or their
relative position on the evolutionary tree.
Strengthening, weakening, and non-informative categories
The entries in the table shown in Supplementary Fig. [197]2 are
categorized into three distinct groups based on their impact on the
hypothesis: strengthening, weakening, or not informative.
* Claims that are not informative with regard to the hypothesis
(colored in gray in the table):
+ Pairs that have a small difference in lifespan, a small
distance in the phylogenetic tree, and have the same amino
acid at the acetylation site (e.g., human and chimp sharing
the same AA at the specific site).
+ Pairs that have a large difference in lifespan, a large
distance in the phylogenetic tree, and have different amino
acids at the acetylation site (e.g., mouse and human that have
different AAs at a specific site).
* Claims that strengthen the hypothesis (colored in green in the
table):
+ Pairs that have a small difference in lifespan, a large
distance in the phylogenetic tree, and have the same amino
acid at the acetylation site (e.g., human and whale sharing
the same AA at a specific site).
+ Pairs that have a large difference in lifespan, a small
distance in the phylogenetic tree, and have different amino
acids at the acetylation site (e.g., mouse and naked mole rat,
having different AAs at a specific site).
* Claims that weaken the hypothesis (colored in red in the table):
+ Pairs that have a small difference in lifespan, a small
distance in the phylogenetic tree, and have different amino
acids at the acetylation site (e.g., human and chimp having a
different AA at a specific site).
+ Pairs that have a small difference in lifespan, a large
distance in the phylogenetic tree, and have different amino
acids at the acetylation site (e.g., human and whale having
different AAs at a specific site).
+ Pairs that have a large difference in lifespan, a small
distance in the phylogenetic tree, and have the same amino
acid in the acetylation site (e.g., mouse and naked mole rat
having the same AA at a specific site).
+ Pairs that have a large difference in lifespan, a large
distance in the phylogenetic tree, and have the same amino
acid at the acetylation site (e.g., mouse and human having the
same AA at a specific site).
Weight calculation
Weights were assigned to each comparison according to the following
equation:
[MATH: (1)Weight=±P(∣lifespan1−lifespan2∣∧
tree_di<
mi>stance)
:MATH]
Where P is the probability of the mammalian pair occupying a specific
position in the table (Supplementary Fig. [198]2b, right column),
regardless of the amino acid found at the acetylation site. For
instance, the probability of a pair from the data falling into the
first strengthening row is determined by their lifespan difference
being smaller than average, AND their distance in the phylogenetic tree
being larger than average. The strengthening or weakening category is
assigned positive or negative weights, respectively (table in
Supplementary Fig. [199]2).
Score calculation
Each acetylation site was addressed as a collection of mammalian pairs,
with each pair assigned a position/category in the options table.
The overall score for an acetylation site was computed as shown in the
following equation:
[MATH: (2)Sitescore=∑eachpairofmammalswei
ght*lifesp<
/mi>an1−lifespan2<
/mfenced>*tree_distance :MATH]
In which the score for each site is calculated as the sum of the values
received from all two-mammal comparisons: weight multiplied by the
difference in lifespans and the distance in the phylogenetic tree (both
normalized to numbers between 0 and 1, see table in Supplementary
Fig. [200]2).
Permutation Test
To determine a p-value for each site’s score, 1000 permutations of the
non-zero weights were performed, effectively randomizing the positions
where pairs are placed in the tree. FDR correction was applied to
adjust for multiple testing.
Changed acetylation sites are considered longevity-associated only in
case they are significant in both the Mann–Whitney test and the
phylogenetic tree validation described here (Supplementary Fig. [201]2,
bottom).
PHARAOH implementation
The PHARAOH tool was fully implemented in Python 3. The replacement
matrix algorithm uses SQLite3 tables as the database. Pandas,
more_itertools, and NumPy Python libraries were used throughout the
creation of the matrix. In the statistical validation, Bio (biopython)
was used for working with phylogenetic data (Phylo), as well as
statsmodels and scipy.stats for the Mann-Whitney and FDR tests.
Matplotlib was used for basic visualization of the outputs.
Lysine residue conservation
PHARAOH was employed to investigate the conservation of lysine
residues. Matplotlib was used for basic visualization, with or without
acetylation, between mouse and human, by comparing proteomics/acetylome
data. The conservation patterns within the proteomes were independently
assessed. Orthologous proteins were obtained through OrthoFinder, and
the alignment of these orthologous protein sequences was conducted
using the Linux version of bl2seq. To identify unacetylated lysines,
the acetylome sites were subtracted from the proteome outcomes.
Subsequently, the percentage of each amino acid replacement was
calculated in relation to the total count of lysines in the proteome,
or the acetylated lysines present within the acetylome.
Analysis of the acetylome results
Pathway enrichment analyses were performed via the Metascape
site^[202]59, which uses MCODE^[203]60 and various interaction tools to
create the protein-protein interaction network. Cytoscape^[204]61 was
used to edit and visualize the PPI networks.
Gene ontology was used for CC analysis, and the results were manually
divided into categories of extracellular, nucleus, cytoplasm, plasma
membrane, mitochondrion, endoplasmic reticulum, and others.
pLogo^[205]62 (probability Logo generator) was used with the
appropriate background (mouse background for the mouse acetylome and
human for the human acetylome).
TRRUST^[206]63 database was used for human transcription factor
analysis. Gene-disease association analysis was performed using
DisGeNET^[207]64.
R was used via RStudio to enable visualization of the results.
ggtree^[208]65 was used for visualization of the phylogenetic tree, and
gheatmap was used to append the heatmaps to the phylogenetic tree. A
heatmap of the replacement matrix data was created by
ComplexHeatmap^[209]66, filtered only to the significant results and
the relevant changes of AAs. Proteomics data from the NIH Cancer
Institute^[210]67 was used for Pearson correlation between USP10 and
PCNA in cancer data, visualized and calculated using R. Venn diagrams
for the method's visualizations were also created in R using
eulerr^[211]68.
Cloning and mutagenesis
The human and mouse CBS and the human USP10 cDNA sequences were cloned
into a pcDNA3.1+ vector using EcoRI and XhoI (CBS) or XhoI and XbaI
(USP10) restriction enzymes. All genes were tagged with a flag tag at
the C-terminal region. Site-directed mutagenesis was done with PfuUltra
II Fusion HS DNA Polymerase kit (Agilent), following the manufacturer’s
protocol. Primers used here are listed in Supplementary Table [212]1 in
the Supplementary Information file.
Cell culture and treatments
HEK293T and HCT116 cell lines were purchased from ATCC (cat. CRL-3216
and CCL-247, respectively) and grown in Dulbecco’s Modified Eagle
Medium (DMEM) supplemented with 10% fetal bovine serum (FBS), 1%
glutamine, and 1% penicillin/streptomycin in 5% CO[2]. For PCNA
ubiquitin-related degradation, HCT116 cells were treated with 100 µg/ml
cycloheximide for 8 h, and then harvested with PBSx1 and lysed in urea
buffer for western blot analysis.
Transfection
HEK293T cells were seeded in 10 cm plates as previously published^25.
The cells were grown for 48 h before harvesting in cold PBS x1.
HCT116 cells were transfected using Lipofectamine 3000 (Thermo
L3000008) following the manufacturer’s protocol.
Flag immunoprecipitation (IP-flag)
HEK293T transfected with CBS-flag were harvested in cold PBS x1 and
lysed on ice with lysis buffer (50 mM Tris pH 7.4, 150 mM NaCl, 1%
Triton, 0.5% NP40, 10% glycerol) for 30 min. The CBS-flag was
immunoprecipitated from 1 mg lysate as previously described^[213]25 and
used for the H[2]S production assay.
H[2]S production capacity assay
H[2]S capacity was measured as previously described^[214]38 using
200–500 µg cell lysate or 5 µl eluate after IP-flag of CBS,
supplemented with 10 mM L-cysteine, 10 µM PLP, and 10 mM
L-homocysteine. Lead acetate papers were purchased from Sigma
(37104-1EA). Measurements were quantified using ImageJ.
Western blot and antibodies
Western blot analyses were done as previously published^[215]25, using
antibodies for PCNA (Cell Signaling 13110S) or USP10 (Cell Signaling
CST-8501S) as primary antibody and the appropriated HRP-conjugated
secondary antibodies (ENCO). HRP-conjugated primary antibodies were
used against Ubiquitin (Santa Cruz 8017), Flag (Proteintech HRP-66008),
and Tubulin (Proteintech HRP-66240). Uncropped images are shown in the
Data Source and Supplementary Information files.
Statistical analysis for H[2]S production and western blot analyses
For the analysis of H[2]S production capacity assay and western blot
measurements, statistical significance was tested using one-way ANOVA.
Reporting summary
Further information on research design is available in the [216]Nature
Portfolio Reporting Summary linked to this article.
Supplementary information
[217]Supplementary Information^ (41.5MB, pdf)
[218]Peer Review file^ (1MB, pdf)
[219]41467_2025_58762_MOESM3_ESM.pdf^ (64.7KB, pdf)
Description of Additional Supplementary Files
[220]Supplementary Data 1^ (2.2MB, csv)
[221]Supplementary Data 2^ (1MB, csv)
[222]Supplementary Data 3^ (13.3KB, xlsx)
[223]Supplementary Data 4^ (372.8KB, xlsx)
[224]Supplementary Data 5^ (18KB, xlsx)
[225]Supplementary Data 6^ (11.8KB, xlsx)
[226]Supplementary Data 7^ (215KB, csv)
[227]Supplementary Data 8^ (100.3KB, csv)
[228]Supplementary Data 9^ (199.3KB, pdf)
[229]Supplementary Data 10^ (430KB, xlsx)
[230]Reporting Summary^ (104KB, pdf)
Source data
[231]Source Data^ (625.2KB, xlsx)
Acknowledgements