Distinct and diverse chromatin-proteomes of ageing mouse organs reveal protein signatures that correlate with physiological functions

Temporal molecular changes in ageing mammalian organs are of relevance to disease etiology because many age-related diseases are linked to changes in the transcriptional and epigenetic machinery that regulate gene expression. We performed quantitative proteome analysis of chromatin-enriched protein extracts to investigate the dynamics of the chromatin-proteomes of the mouse brain, heart, lung, kidney, liver, and spleen at 3, 5, 10, and 15 months of age. Each organ exhibited a distinct chromatin-proteome and sets of unique proteins. The brain and spleen chromatin-proteomes were the most extensive, diverse, and heterogenous among the six organs. The spleen chromatin proteome appeared static during the lifespan, presenting a young phenotype that reflects the permanent alertness state and important role of this organ in physiological defense and immunity. We identified a total of 5928 proteins, including 2472 nuclear or chromatin associated proteins across the six mouse organs. Up to 3125 proteins were quantified in each organ demonstrating distinct and organ-specific temporal protein expression timelines and regulation at the post-translational level. Bioinformatics meta- analysis of these chromatin proteomes revealed distinct physiological and ageing- related features for each organ. Our results demonstrate the efficiency of organelle specific proteomics for in vivo studies of a model organism and consolidate the hypothesis that chromatin-associated proteins are involved in distinct and specific physiological functions in ageing organs. HIGHLIGHTS Quantitative chromatin-proteome analysis during mouse lifespan; Chromatin analysis in vitro and in vivo mouse models; Distinct chromatin proteomes of six organs during mouse lifespan; Correlations between ageing and chromatin regulation in mammalian lifespan.


SUMMARY 19
Temporal molecular changes in ageing mammalian organs are of relevance to disease 20 etiology because many age-related diseases are linked to changes in the transcriptional 21 and epigenetic machinery that regulate gene expression. We performed quantitative 22 proteome analysis of chromatin-enriched protein extracts to investigate the dynamics of 23 the chromatin-proteomes of the mouse brain, heart, lung, kidney, liver, and spleen at 3, 24 5, 10, and 15 months of age. Each organ exhibited a distinct chromatin-proteome and 25 sets of unique proteins. The brain and spleen chromatin-proteomes were the most 26 extensive, diverse, and heterogenous among the six organs. The spleen chromatin 27 proteome appeared static during the lifespan, presenting a young phenotype that 28 reflects the permanent alertness state and important role of this organ in physiological 29 defense and immunity. We identified a total of 5928 proteins, including 2472 nuclear or 30 chromatin associated proteins across the six mouse organs. Up to 3125 proteins were 31 quantified in each organ demonstrating distinct and organ-specific temporal protein 32 expression timelines and regulation at the post-translational level. Bioinformatics meta-33 analysis of these chromatin proteomes revealed distinct physiological and ageing-34 related features for each organ. Our results demonstrate the efficiency of organelle 35 specific proteomics for in vivo studies of a model organism and consolidate the 36 hypothesis that chromatin-associated proteins are involved in distinct and specific 37 physiological functions in ageing organs. 38 39 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in • Ageing 50 • Proteomics 51 • Chromatin 52 • Epigenetic 53 • Tissue 54 •  Table S1 69 70 2) Brain proteome whole cell lysate during adult mouse lifespan 71 File name: Supplementary material, Table S2 72 73 3) Chromatin proteomics of six mouse organs over time 74 File name: Supplementary material, Table S3 75 76 4) Uniquely regulated proteins organ-specific during ageing.

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File name: Supplementary material, Table S4 78 79 80 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021

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Ageing is a natural process resulting in progressive changes of most, if not all, cellular 83 components. Ageing is generally associated with declining biological performance and 84 increased incidence of disease (1). The gene expression apparatus, comprised of the 85 DNA itself, the chromatin environment it is housed in, and the machinery of 86 transcription and translation is profoundly affected by ageing (2) (3). Models of ageing 87 often display similar phenotypes to those undergoing senescence or genome instability, 88 highlighting how integrated the ageing process is with these phenomena (1). Diseases 89 that mimic or accelerate the ageing process, including Hutchinson-Gilford progeria and 90 Werner syndromes, result in molecular changes in nucleosomes and chromatin (4) (5) 91 (6). 92 In eukaryotes, chromatin includes histone molecules that package the DNA, locally 93 controlling access to the underlying genes by facilitating 'open' or 'closed' states 94 associated with transcriptional activation or repression, respectively (7). In this way, 95 transcription of individual gene products may be regulated in temporal or location-96 specific manners. 97 One of the main routes of proteome expansion is dedicated to enzymes that carry out 98 post-translational modifications of proteins. Enzyme catalysed PTMs at distinct amino 99 acid residues regulate or modulate protein structure, interactions, and functions (8). 100 The mouse, Mus musculus, is the most commonly used experimental animal in 101 biomedical research, and serves as a model system for studying human health and 102 disease (9)(10). Mice have a relatively short lifespan, with one adult mouse month 103 equivalent to approximately three human years (11)(12). This allows for maximum 104 lifespan studies to proceed within the timelines of typical research projects, while 105 environmental factors that affect ageing can be controlled (13)(14)(15). Lifespan and 106 health-span are mutually influenced by many genes that can either predispose to age-107 related diseases or slow the ageing process itself (16). 108 We recently applied a middle-down proteomics strategy to demonstrate that mouse 109 chromatin undergoes major changes during ageing, specifically that histone H3.3 110 replaces H3.1 and that the extent of H3 methylation marks at multiple sites is 111 profoundly altered during ageing (17). We here extend these proteomics studies of 112 mouse chromatin to investigate the protein composition of chromatin in multiple mouse 113 organs during ageing. 114 We hypothesised that a time-course investigation of the dynamic chromatin proteome 115 could reveal distinct molecular differences of mammalian organs and provide new 116 insights into regulatory mechanisms in different organs during ageing. 117 We studied the progressive chromatin protein expression changes in six mouse organs 118 during ageing by quantitative proteomics by mass spectrometry (graphical abstract). 119 Among almost 6,000 proteins identified, organ-specific patterns predominated, with 120 age-responsive subsets identified for each organ. We mapped pathway level molecular 121 changes specific to individual organ over time. 122 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021 5 Our results demonstrate that the ageing process affects each mouse organ in a distinct 123 manner illustrated by the diversity and heterogeneity of the temporal chromatin 124 proteomes of each organ. 125 126 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021 RESULTS 127

Isolation of chromatin associated proteins from mouse cells and organs. 128
We aimed to provide a comprehensive overview of the chromatin-enriched proteome in 129 mouse organs and obtain insights into molecular processes involved in growth and 130 ageing. 131 We initially applied a nuclear protein extraction protocol to the mouse embryonic stem 132 cell (mESC) model, which is a "gold standard" for epigenetics research (Supplementary 133 material, Table S1) (18) (19). Briefly, mESCs were lysed and cellular compartments 134 were isolated by mechanical disruption followed by a high salt gradient separation to 135 obtain cytosolic, nuclear, chromatin and histone fractions (20) (21). These lysates were 136 initially analysed by western blotting using specific protein markers for each cellular 137 compartment to assess the degree of enrichment of chromatin associated proteins 138 (Figure 1, Panel A). 139 We performed quantitative proteomics by triplicate high-mass-accuracy mass 140 spectrometry analysis of the mESC proteome and the mESC chromatin proteome to 141 assess the enrichment of chromatin associated proteins ( Figure 1, panels B and C). 142 Subsequently, we presented the difference in chromatin enzymes detection in Table 1. 143 We annotated all nuclear or chromatin associated proteins using available database 144 resources (Supplementary material, Figure S1) (22)  . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in In general, we observed an overall increase in the proportion of proteins classified as 156 either "nuclear" (20%) or "chromatin associated" (35%) within the mESC chromatin 157 sample ( Figure 1, panel C). 158 Gene ontology (GO) analysis showed a distinct enrichment of proteins associated with 159 "DNA-protein binding", "histone binding", and "chromatin and nucleosome organisation" 160 within the chromatin sample ( Figure 1, panel D). The mESC total lysate sample mainly 161 contained proteins involved in "translational protein", "cell-cell structure organisation" 162 and "ribosomal and ATP processes" (Figure 1, panel D). 163 We next demonstrated that the chromatin enrichment protocol used for mESCs is 164 applicable to mouse organs. We first extracted chromatin proteins from mouse brain 165 and assessed chromatin enrichment by western blotting using specific protein markers 166 (Supplementary material, Figure S2). We observed enrichment of the chromatin marker 167 histone H3 and reduced level of the cytosolic marker GAPDH expression within the 168 "chromatin fraction" lysate. 169 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021 8 Next, we performed quantitative mass spectrometry profiling of the mouse brain 170 proteome and the mouse brain chromatin-enriched proteome. The dynamic range plots 171 demonstrated that the major chromatin binding protein complexes were enriched in the 172 brain chromatin sample, including MLL, NuRD, Polycomb and BHC complexes (Figure 2,  173  panel A, Supplementary material, Table S2). 174 The mouse brain chromatin enriched fraction contained more than 30% chromatin 175 associated proteins, up from ~8% in the total brain lysate (Figure 2 panel A, bottom). 176 This was accompanied by a large increase in the content of "nuclear proteins" (~20%) 177 ( Figure 2, panel A). 178 We conclude that our chromatin-proteome fraction of mouse brain tissue was highly 179 enriched in chromatin associated and nuclear proteins as compared to the whole brain 180 lysate ( Figure 2, panel A). 181 182

Quantitative chromatin proteomics of ageing mouse organs. 183
We performed quantitative chromatin proteomics of six mouse organs to investigate the 184 in vivo dynamics of chromatin during ageing. We isolated chromatin associated proteins 185 from mouse brain, heart, liver, kidney, lung and spleen at time points 3, 5, 10 and 15 186 months representing the "mature adult mouse lifespan", from the early adult stage 187 (3month), middle aged adult (5 to 10 months) and mature adult (15month) (graphical 188 abstract) (12) (13) (14) (15). 189 We excluded mice older than 18 months to minimize any age-related changes that might 190 be due to social behavior, physical characteristics of motor function and locomotor 191 activity. 192 Proteins were identified and quantified by high mass accuracy LC-MS/MS by hybrid 193 quadrupole-orbitrap technology using a peptide-intensity based (label-free) protein 194 quantification strategy (see Materials and Methods, Supplementary material, Table S3). 195 The proportion of nuclear proteins or chromatin associated proteins ranged from 30% 196 to 60% of all detected proteins and it was similar across all time points for each organ 197 (Figure 2,panel B). 198 Subsequent data analysis included all identified proteins of each organ and all time 199 points to avoid loss of essential information and to achieve a more detailed 200 characterisation of the chromatin proteomes of mouse organs. 201 We identified a total of 5928 proteins in the chromatin enriched protein samples across 202 all six mouse organs over time ( Figure 2, panel C). Most proteins were identified in the 203 chromatin fractions of mouse brain (3110) and spleen (3125), whereas the lowest 204 number of proteins were identified in the chromatin fraction of mouse heart organ 205 (2051) (Figure 2 panel C). The lung and spleen samples were highly enriched in nuclear 206 proteins and chromatin associated proteins (55-65%), whereas the chromatin enriched 207 heart sample contained 30-35% nuclear/chromatin associated proteins. 208 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in  9   The very different morphology and cell type compositions of the mouse organs likely  209  influence the efficiency of the chromatin protein extraction protocol and thereby the  210  detected proteome compositions. Cell-type and cell cycle specific transcriptional  211 activities likely explain some of the observed variation in proteome composition. 212 Nevertheless, the fraction of proteins classified as either "nuclear" or "chromatin 213 associated" was similar among all mouse organs and time points, demonstrating the 214 high reproducibly and reliability of the experimental approach with a coefficient 215 variation estimated less than 10% among all the samples ( Figure 2B). 216 Overall, we identified a total of 4581 different chromatin associated proteins across all 217 organs, including 2717 different nuclear proteins (Table 2). 218 We assessed the entire mouse organ chromatin enriched proteome dataset using 227 principle component analysis (PCA) (Figure 3, Panel A). The time points (age of mouse 228 at organ harvest) were well separated from one another for each organ, such that the 229 replicates for each time point were more closely clustered to one another than to 230 replicates of other time points. More strikingly, however, was the observation that the 231 origin of organ was the fundamental discriminating factor for the overall clustering of 232 samples: each organ formed its distinct cluster made up of sub-clusters comprising the 233 different ages of the organ samples ( Figure 3, Panel A). 234 Pearson correlation analysis (Supplementary material, Figure S3) demonstrated 235 reproducibility of biological replicates and confirms the robustness of our biochemical 236 and proteomics methodology. To further characterise similarities between ageing organ 237 and proteome expression profiles, we performed clustering of Pearson correlation 238 coefficients ( Figure 3, Panel B). This showed the consistency and reproducibility of 239 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021 analysis of three biological replicates at all time points, and revealed distinct organ 240 proteome profiles. The brain derived proteome exhibited poor correlation to all other 241 organs. Kidney, liver, heart and lung samples exhibited protein expression profiles, 242 which were slightly positively correlated. Spleen displayed slightly positive correlation 243 with kidney and lung and poor correlation to brain, liver and heart. 244 Overall, our PCA and Pearson correlation analyses demonstrate that each mouse tissue 245 exhibits a distinct and ageing-related chromatin-proteome profile ( Figure 3). Brienfly, overlapping organ proteome was performed to estimate the number of co-254 occurrence proteins shared and determined degree of similarity between datasets and 255 subsequently, identify unique organ-specific feature. Then, the dataset undergo to Gene 256 Ontology analysis to explore the relationship between chromatin and ageing. 257 A "core" proteome of 863 proteins was identified in all six organs during mouse lifespan 258 across all four time points, including 289 shared chromatin binding proteins and 157 259 shared nuclear proteins ( Figure 4, Panel A, Table 3). 260 For each of the six organs we detected from 214 to 793 proteins that were unique to that 272 organ, i.e. proteins not detected in other organs (Figure 4, Panel A and Table 3) 273 The mouse brain chromatin proteome contained 793 unique proteins, constituting the 274 largest set of unique proteins among the six organs ( Figure 4, Panel A). Approximately 275 24% of these proteins (188) were classified as chromatin associated proteins or nuclear 276 proteins ( Figure 4, Panel A, below) ( The spleen chromatin preparation contained 582 unique proteins, ~50% of which are 281 chromatin associated proteins or nuclear proteins, strongly suggesting a distinctive 282 chromatin proteome profile for this organ ( Figure 4, Panel A, below) (Table 3). 283 The spleen is an organ with the innate capacity to regenerate (31). It acts as a filter for 284 blood and it controls the blood-borne immune response (32 The relatively large numbers of unique proteins of each organ likely reflects the inherent 296 features of the individual organs, the diversity of cell types and physiology (Figure 4,297 Panel A). 298 GO analysis of the "core" 863 proteins revealed a large number of "chromatin 299 associated" or "nuclear" proteins. The GO output was enriched for categories related to 300 mouse ageing, such as: "oxidation-reduction process", "ageing", "regulator of cell cycle", 301 and "stress response" (Figure 4, Panel B) (33) (34) (35) (36) (37). 302 Subsequently, each category of the core proteome was further broken down into its 303 constituent parts to create a map of the shared ageing-related molecular network of the 304 six mouse organs ( Figure 4, Panel B). Our aim was to identify novel biological features 305 and associate them with ageing-related pathways and annotations. 306 GO classification of the unique proteins present in each organ proteome, suggested 307 distinctive molecular signs of ageing in each organ ( Figure 4, Panel C). We observed 308 distinctive organ-specific categories, "age-classes and age-development" and categories 309 that reflected their organ source ( Figure 4, Panel C). For instance, unique GO term 310 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.09.459706 doi: bioRxiv preprint categories were associated with each organ, such as: "Nervous system development" and 311 "chemical synaptic transmission" related to the brain; "Cardiac myofibril assembly" and 312 "adult heart development" were attributed to the heart; "Steroid metabolic process" and 313 "liver development" were distinctive to the liver; "Transport" and "sodium ion 314 transport" categories related to the kidney, and "Angiogenesis" and "respiratory gaseous 315 exchange" were present in the lung. 316 These results confirm that many chromatin-proteins found in individual organs likely 317 confer organ-specific functions ( Figure 4, Panel C). 318 Taken together, our proteomics analysis showed a robust enrichment of chromatin 319 associated proteins in mouse organs as confirmed by GO term analysis. We reported a 320 significant enrichment of age-related proteome features, including a large class of 321 protein annotations associated with the core chromatin environment present in all 322 organs. 323

Distinct organ ageing profiles are defined by unique protein expression patterns. 325
We hypothesised that different mammalian organs have ageing-dependent and distinct 326 expression profiles of characteristic chromatin associated proteins. 327 We employed a temporal analysis of the overall dataset which included chromatin 328 associated proteins, nuclear proteins and unassigned proteins, to uncover common 329 features that may contribute to the chromatin environment during ageing. 330 We used the rank products test to identify proteins that exhibited significant abundance 331 changes during ageing (supplementary material, Figure S5, Panel D) (38) (39). We call 332 these "differentially regulated proteins" ( Figure 5). 333 We then retrieved those unique regulated proteins that were specifically detected in 334 only one organ, in two organs or three organs (UpSet plot) ( Figure 5, Panel A). The 335 majority of uniquely regulated proteins were indeed specific to one organ. 336 We subjected the organ-specific uniquely regulated proteins to hierarchical clustering 337 based on their expression changes and depicted them as heatmaps for each organ (three 338 replicates  Table S4). 342 The hierarchical clustering shows that the number of up and down-regulated proteins is 343 similar in each organ. Further, assigned cell compartments of the "unique differentially 344 regulated proteins" are shown as sidebars ( Figure 5, Panel B) (Supplementary material, 345 Table S4). A large number of non-annotated "unique differentially regulated proteins" 346 show a similar quantitative behaviour across all organs. We hypothesised that these 347 proteins may represent a useful list of candidates that may regulate gene expression by 348 been transiently recruited to chromatin at distinct time points during ageing. 349 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.09.459706 doi: bioRxiv preprint 13 Brain, heart and kidney showed mainly gradual changes of protein levels over time. 350 Lung and liver show a more dramatic change of protein expression between 5 and 10 351 months of age ( Figure 5, Panel B, supplementary material Figure S5, Panel E). We 352 detected few significant protein abundance changes in the spleen. The spleen fraction 353 was highly enriched in chromatin associated and nuclear proteins (approx. 60%) and 354 contained many unique proteins (Figure 3 and 4). Thus, the spleen seems to 355 continuously exhibit a young phenotype that may be due to the constitutively active role 356 of the spleen in maintaining immune functions, red blood cell turnover and microbial 357 defense (40). The spleen contains multiple cell populations capable of supporting 358 immune responses, which may indicate the presence of self-renewal cell types that are 359 "age-less" (31). 360 In summary, we identified a large number of unique differentially regulated proteins in 361 the chromatin enriched proteomes of mouse organs. The abundance of these proteins 362 changes dramatically during ageing from month 3 to month 15, across all organs, except 363 for spleen. 364 Next, we explored potential functional links between chromatin proteome dynamics and 365 ageing. We investigated all known chromatin associated proteins that were identified 366 among the "unique differentially regulated proteins". 367 The majority of chromatin modifying enzymes belonging to a given multiprotein 368 complex, exhibited similar expression profiles over time within a specific organ ( Figure  369 5, Panel C). For instance, the MLL subunits WDR82, CTR9 and WDR61 were down-370 regulated in liver during ageing. Components of same chromatin modifying complexes 371 were detected in several organs, albeit not by the same subunits and with opposite 372 temporal expression profiles. NuRD subunit HDAC2, was down-regulated in liver 373 whereas NuRD subunits GATA2AD and TRIM28 were up-regulated in kidney. 374 This is consistent with the highly dynamic nature and spatio-temporal regulation of 375 chromatin remodelling complexes. Some protein subunits are only present in a complex 376 at distinct time-points to provide a unique function or feature (41). 377 A series of "Reader" enzymes were up-regulated in brain (GLYR1, BAZ1B) and spleen 378 (BRD3, BRD7), whereas other "Reader" enzymes were down-regulated in liver (DPF2, 379 BRD2, CHD2) ( Figure 4C). 380 Next, we queried the "Human Ageing Genomic Resources" and "GenAge machine 381 learning databank" using our complete list of "unique regulated proteins" that are not 382 yet assigned to chromatin or nuclear environment, to demonstrate the ability of our 383 mouse organ proteomics approach to detect known human ageing biomarkers 384 (supplementary material Figure S5, Panel F) (42)(43). 385 We identified a series of human protein biomarker candidates for ageing. The brain 386 protein IREB2 is associated with Alzheimer's disease, whereas the brain protein MAOB 387 is associated with both Alzheimer's and Parkinson's diseases. The heart proteins ADD3, 388 PTGIS, and COL1A2 are candidates for hypertension and myocardial infarction. The liver 389 proteins INSR, PTPN1, and ENPP1 are associated with diabetes mellitus type 2 and 390 obesity. Lung protein CYP2E1 is related to lung adenocarcinoma and MMP9 is associated 391 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in

Functional analysis of chromatin-enriched proteomes of ageing mouse organs 395
Next, we applied Gene Ontology (GO) analysis to characterise all "unique differentially 396 regulated proteins" detected in each organ ( Figure 6). 397 We listed the overall common pathways and processes that were found by quantitative 398 chromatin proteomics to be differentially regulated during ageing across all the organs. 399 We sorted the annotated features by their relative GO term category and separated them 400 by their main family source ( Figure 6, left panel). 401 During adult mouse lifespan, we observed several ageing stress response pathways and 402 categories associated to regulate chromatin architecture leads to effect the cell structure 403 conformation. 404 By listing every single category, we could describe the biological profile and pathways 405 affected by the age-related protein expression responses present in all organs ( Figure  406 6). 407 Subsequently, the differentially regulated proteins were sorted by their organ source 408 and subject to further GO Term analysis to distinguish unique organ related processes 409 from those pathways associated with ageing ( Figure 6, center panel). 410 We report a high proportion of uniquely annotated categories for each mouse organ. For 411 instance, the highest unique changes observed in the brain were relative to "gene 412 expression" and "ageing/development"; in the heart and kidney significant changes 413 were observed relative to "structure organization and biogenesis"; the liver showed 414 changes across the "gene expression" and "structure organization and biogenesis" 415 categories; the lung showed the highest unique changes in the "ageing/development" 416 category, and; relative changes in the spleen were detected at the "gene expression" 417 level. 418 419 These results are in line with our above observations suggesting a unique ageing 420 response from each organ as evidenced by distinct dynamic changes of chromatin 421 associated proteins. 422 We further interrogated the list of unique annotated organ categories to highlight 423 distinct and significant temporal pathway profiles among the up-and down-regulated 424 proteins in each organ to reveal the most distinctive regulated features ( Figure 6, right 425 panel). 426 In the mouse brain tissue, proteins involved in pathways such as "chromosome 427 organisation" and "histone modification" were strongly up-regulated, while those 428 involved in the regulation of "neuron projection regeneration" were down-regulated. In 429 mouse heart tissue, up-regulated protein pathways included "oxidoreductase activity" 430 and "regulation of response to stress", while down-regulated pathways included 431 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.09.459706 doi: bioRxiv preprint "cardiovascular system development" and "chromosome organisation". In the kidneys, 432 proteins involved in pathways related to changes in chromatin conformation were both 433 going up and going down during the mouse lifespan. In the liver, we observed that 434 down-regulated proteins were associated with "chromosome organisation" and "histone 435 modification", while "oxidation-reduction process" pathways were up-regulated. In the 436 lungs we noticed proteins associated with "apoptotic process" and "programmed cell 437 death" were up-regulated, while pathways related to "muscle organisation and 438 reassemble" were down-regulated. 439 Similarly, several different processes were altered in the other organs, except for the 440 spleen that did not show many significant changes during ageing. In line with previous 441 data, little pathway-level changes were observed in the spleen, especially in the down-442 regulated proteins, possibly indicating the important role of this organ in removing old 443 red blood cells and microbes which seem, from our data, to not be affected by ageing. 444 For this reason the spleen was not considered for further analysis. 445 Overall, using GO term analysis we dissected the biological features of the chromatin 446 proteomes of organs in the context of mouse lifespan. By breaking down common and 447 unique regulated functional categories we surveyed ageing-related pathways and 448 improved gene-annotation enrichment analyses. 449 In conclusion, we identified and measured distinct and extensive protein abundance 450 changes during ageing, specifically in early to mature adult mouse lifespan. A large 451 number of differentially expressed proteins are unique for each organ as defined by 452 specific GO Term categories. This demonstrated that the ageing process affects each 453 mouse organ differently. 454 455

Characterization of regulated molecular networks in ageing mouse organs. 456
We looked in more detail at the most significant regulated organ-specific up-regulated 457 and down-regulated protein categories during mouse ageing ( Figure 6, right panel). 458 We used protein-protein interaction (PPI) data, from the STRING database to map the 459 network of chromatin associated protein belonging to the most significant GO categories 460 of each organ (44) (45) (Figure 7, Panel A). 461 Subsequently, we combined the protein interaction networks with the quantitative 462 dataset (Figure 7, Panel A). By integrating protein-protein interactions and protein 463 expression we derived co-interaction and co-expression networks to improve our 464 understanding of biological mechanisms involved in ageing. 465 Finally, we attempted to confirm independently, by western blot, the observations noted 466 in our wider dataset, specifically to the co-expression network generated (Figure 7,  467 Panel B). 468 Brain: The majority of up-regulated proteins of the ageing brain belonged to the 469 category "chromosome organisation", including histones and histone binding enzymes 470 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in ageing. These proteins were not detected in any other mouse organ in this proteomics 477 study (data not shown). Macro-H2A2.1 is an epigenetic marker whose major function is 478 to maintain nuclear organisation and heterochromatin architecture (46). HP1BP3 is a 479 heterochromatin marker protein that recognises the histone mark H3K9me3 and 480 promotes transcriptional repression (48). HP1BP3 loss-of-function is associated with 481 cognitive impairment suggesting a role for this protein in establishing or maintaining 482 cognitive functions (49). We also confirmed the expression of other heterochromatin 483 markers including RING1b (50) and RNF20 (51)   with SIRT5 being up-regulated from 3 to 15months. 499 The abundance change of SIRT3 levels was less pronounced. This data was confirmed by 500 western blotting (Figure 7, Panel B). SIRT5 is a histone deacylase that removes malonyl, 501 succinyl, and glutaryl groups from histones. The ageing-dependent increase in histone 502 H3 acetylation observed in our proteomics study and by western blotting (Figure 7,  503 Panel B) is consistent with the fact that SIRT5 has no deacylases activity towards histone 504 H3. 505 CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.09.459706 doi: bioRxiv preprint acylation levels. We indeed observed decreased levels of global histone H3 acetylation at 514 this time point (Figure 7, Panel B), which contrasts with what we observe in the heart 515 tissue. These results confirm our previously published data on decreased H3 acetylation 516 (H3K14, K23, K27) in liver tissue during ageing (17), and that there is a decreased 517 activity of histone acylation in the liver at late stages of ageing. 518 Kidney: The up-regulated "chromosomal part" category in ageing kidney tissue included 519 components of the SCF-type E3 ubiquitin-protein ligase family (FBXO41, RNF13, NEDD4, 520 TRIM28) and the proteasome subunits PSMD14 and PSME2. (Figure 7, Panel A). The 521 mechanistic links between proteasome activity and ageing are well established (59)  522 (60). 523 The proteasome is a large self-compartmentalised protease complex that recognizes, 524 unfolds, and destroys ubiquitylated substrates (60). 525 The protein expression levels of FBX041 and NEDD4 increased gradually during kidney 526 ageing, while the signal intensity for PSMD14 and PSME2 was more pronounced at the 527 latest time point (15 months) (Figure 7, Panel B). Thus, ageing kidney increases E3 528 ubiquitin-protein ligases, enhance the ubiquitylated substrates and stimulate 529 proteasome abundance and activity. 530 Lungs: Many down-regulated proteins of ageing lungs were involved in processes such 531 as "muscle organisation and reassembly", and the top GO Term encompasses an array of 532 myosin motor proteins (Figure 7, Panel A). The down-regulated "myosin complex" GO 533 category included several proteins belonging to the myosin family, following the 534 observations that human muscle ageing is accompanied by changes in expression of 535 myosins (61). We did not perform any immunoblotting validation of these myosin 536 proteins due to the high sequence similarity among myosin subunits and the lack of 537 highly specific antibodies against them. 538 These observations suggested that ageing might influence the lung cell structure 539 through alteration of the higher-order chromatin architecture. 540 541 Spleen: Only few differentially expressed proteins were observed in the spleen and they 542 did not allow for useful GO analysis and protein network analysis. 543 544 545 546 547 548 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in We implemented a comprehensive high mass accuracy mass spectrometry based 551 proteomics strategy to monitor changes in the chromatin-enriched proteomes of six 552 mouse organs over a time course that mimics adult development and ageing, from the 553 early adult to the mature adult stage. 554 Many age-related diseases are linked to changes in the transcriptional and epigenetic 555 machinery that regulate gene expression. 556 We focused on the changes in the expression of proteins that mediate transcription, 557 including DNA-binding proteins and chromatin modifiers such as "writers", "erasers" 558 and "readers" (29) (30). Chromatin modifiers add, remove or recognise particular post-559 translational modifications (PTMs) of proteins associated with the alteration of 560 chromatin architecture, and ultimately involved in the regulation of gene expression (8). 561 Over 2000 proteins were quantified in each organ, generating a useful resource for 562 researchers investigating mammalian development and ageing. 563 We identified distinct and organ-specific unique ageing features associated with each 564 organ. We observed unique chromatin modifiers that were expressed and accumulated 565 differently during ageing, leading to changes in the chromatin architecture, including 566 changes in expression of heterochromatin markers, histone deacetylases, ubiquitin-567 protein ligase, histone acetylation enzymes, and myosin complex in brain, heart, kidney, 568 liver, and lung respectively. 569 Brain and spleen displayed the largest and most diverse and heterogenous chromatin-570 proteomes. The brain is arguably the most complex organ of a mammal. Brain 571 chromatin structure and function is sustained by a large set of chromatin-associated and 572 nuclear proteins, that also exhibit temporal dynamics of expression during mouse 573 lifespan as demonstrated here. The spleen chromatin proteome was rather constant 574 during lifespan whilst large and diverse, which may reflect the physiological role of the 575 spleen for continuous maintenance of important immune and defense activities of the 576 organism. 577 We demonstrated progressive changes of chromatin associated protein expression in 578 response to ageing. Also, the specific nature of the organ was more of a significant 579 discrimination factor, and subsequently distinct proteome profiles in response to ageing 580 were observed. For instance, we noticed over the mouse lifespan, strongly up-regulated 581 chromatin associated proteins relate to distinctive pathways involved in "oxidation-582 reduction response", "response to oxidation stress" and "nucleosome assembly", as well 583 as signals that promote apoptosis processes. Conversely, chromatin associated proteins 584 strongly down-regulated, are related to "muscle organization and reassembly" and 585 "histone-modifying enzymes" associated with chromatin assembly and organisation. 586 Our study of chromatin-enriched proteomes demonstrated that  accumulates in the mouse brain during ageing. The epigenetic regulator HP1BP3 588 accumulates at a similar rate and very likely interacts with macro-H2A2. Both macro-589 H2A2 and HP1BP3 are highly expressed in the adult mouse brain and we suggest that a 590 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.09.459706 doi: bioRxiv preprint complex involving these two proteins is implicated in maintaining heterochromatin 591 integrity and promote gene silencing during mouse lifespan. 592 Reversible acetylation of histones plays a critical role in transcriptional regulation in 593 eukaryotic cells. We detected reduced levels of histone H3 acetylation during ageing in 594 mouse liver. The opposite trend was observed in ageing heart, i.e. an increase in histone 595 H3 acetylation. Two families of deacylase enzymes were identified: the histone 596 deacetylases, HDACs, and the Sir family protein (Silent Information Regulator)-like 597 family of NAD-dependent deacylases, or sirtuins (62). Both enzyme families play a 598 major role in gene regulation by modifying the histone acetylation/acylation landscape 599 in response to external stimuli and specific environmental stress conditions, such as 600 oxidative stress (63). In mammals, the brain and heart have the greatest oxygen demand 601 for their ATP dependent processes. Nearly all cellular processes of cardiomyocytes are 602 driven by ATP-dependent pathways (64). SIRT3 plays an important role in maintaining 603 basal ATP levels and regulated energy production in mouse embryonic fibroblasts (64)  604 (65). 605 Sirtuin proteins are mostly annotated as mitochondrial proteins, but they can 606 translocate further into the nucleus or other cell compartment (55) (56) (57). The 607 translocation of sirtuins through different cell departments remains unclear. Here, we 608 speculate that the roles of SIRT3 and SIRT5 in heart are essential as they compensate for 609 age-related cellular dysfunction by controlling the levels of histone acylation marks. 610 They may thereby promote the expression of proteins required for DNA repair to 611 prevent cardiac hypertrophy in response to oxidative stress (64). 612 The SAGA complex is a multi-subunit histone modifying complex. KAT2A (67), suggesting the down-617 regulation of histone acetylation is connected with reducing activation of gene 618 expression of target genes which promote self-renewal and pluripotency state during 619 ageing. Overall, our experiments suggest a connection between the roles of two 620 epigenetic enzymes CHD2 and KAT2A, whereby their mutual protein expression is 621 associated with liver differentiation during mouse lifespan. 622 The proteasome is a complex proteolytic machine formed by the assembly of several 623 subunits (69). The ubiquitin-proteasome system (UPS) is the primary selective 624 degradation system in eukaryotic cells, localised both in the nuclei and cytoplasm 625 compartment, which is required for the turnover of soluble proteins (70). The UPS is 626 mainly implicated in protein degradation in response to the regulation of several 627 processes including the maintenance of cellular quality control, transcription, cell cycle 628 progression, DNA repair, receptor-mediated endocytosis, cell stress response, and 629 apoptosis (71). Before a protein is degraded, it is first flagged for destruction by the 630 ubiquitin conjugation system, which ultimately results in the attachment of a 631 polyubiquitin chain on the target protein (72) (73). 632 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in

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Ubiquitin and the proteasome have been implicated in processes as diverse as the 633 control of transcription, the response to DNA damage, the regulation of chromatin 634 structure and function, and the export of RNAs from the nucleus (60). 635 We found an increase in the levels of two proteasome subunits in ageing kidney organ 636 consistent with increased E3-ubiquitin ligase activity. Increased expression of FBXO41, a 637 subunit of the SCF E3 ubiquitin ligase complex, correlates with NEDD4 expression. 638 Recent reports suggested a decline of proteasome function related to senescence 639 observed in several mammalian tissues and human cells (74) (75) (76) (77). During the 640 ageing process, dysfunction of the ubiquitination machinery or the proteolytic activity 641 may occurred, lead to proteasome failure, which is linked to several age-related human 642 diseases (70) (78). We therefore, speculate that an increase expression E3-643 ubiquitination ligase activity may compensate for the proteasome activity, during ageing 644 in kidneys. 645 Not all functions of the actin and actin-related proteins in the complexes are yet clear: it 646 is known that they play important roles in maintaining the stability of the proteins, 647 possibly by bridging subunits and recruiting the complexes to chromatin. In line with 648 previous analysis, the majority of down-regulated "chromatin associated proteins" in 649 lung tissue were assigned to the categories: "myosin complex", "chromatin organisation" 650 and "histone modification". The most significant sub-network corresponds to "muscle 651 organisation and reassembly" category and is related to the myosin family. This is in 652 accordance with recent reports where the change of protein expression of particular 653 myosin subsets implied a human ageing response (79) (80) The presence of actomyosin-654 like protein in the chromatin environment raises questions about the role of actin-like 655 protein such as myosin in nuclear and chromatin processes (81). 656 In the spleen we detected a large number of chromatin associated proteins but only a 657 fraction of these proteins were differentially regulated during ageing. Thus, the spleen 658 chromatin proteome exhibits a "young" or "age-less" phenotype Consequently, only a 659 few pathway-level changes were observed, possibly indicating the important role of this 660 organ in maintaining immune functions, removing old red blood cells and microbes 661 which seem, from our data, not be affected by ageing and consistent with our hypothesis 662 that the time-course changes in protein expression distinctly affect each organ. We 663 observed the largest numbers of chromatin remodelling proteins in the spleen, which 664 suggest that this organ is may provide a good model for epigenetic studies. 665 Overall, our findings using high mass resolution LC-MS/MS suggest a new approach to 666 investigate the dynamic chromatin protein environment during the lifespan of an 667 organism. We provide a high quality and robust dataset of protein expression changes in 668 mouse organs during the ageing process. The dataset shows that in vivo models can 669 describe how the dynamic changes of chromatin associated protein may alternatively 670 promote or repress gene expression during ageing, also reflecting some physiological 671 features of the organ. 672 Our study adds novel details to mouse biology and chromatin dynamics of organs, and it 673 complements previous attempts to identify biomarkers for mouse lifespan (82) (83). 674 Walther et al. reported the bulk proteins abundance are less prone to change in organs 675 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ; https://doi.org/10.1101/2021.09.09.459706 doi: bioRxiv preprint such as the brain, heart, and kidney obtained from mice aged 5 or 26 months. They 676 reported only few proteins that exhibited statistically significant expression changes 677 during ageing (82). Thus, bulk proteome analysis of mammalian organs has limitations, 678 whereas organelle specific proteomics, as presented here for chromatin, is a more viable 679 strategy to reveal molecular details of important biological processes, such as ageing 680 and chromatin regulation. 681 Using a rat model (83) We see a consistent overlap between our results and a list of human ageing-related 688 biomarker candidates of the "Human Ageing Genomic Resources" and "GenAge machine 689 learning databank" (supplementary material Figure 5, Panel F) (42) (43). Our 690 differentially expressed candidate mouse proteins behaved just as human ageing 691 biomarkers or ageing-related human proteins that promote disease. 692 Whereas our study provides novel features and details of molecular ageing processes in 693 mammals, it does not provide mechanistic details of the protein-mediated ageing 694 process in chromatin. Quantitative proteomics is an important tool for further studies of 695 chromatin dynamics and the emerging field of high-sensitivity single-cell proteomics 696 will assist in revealing features of organ function in health, ageing, and disease using 697 limited sample amounts. The experimental protocols used in the present study provides 698 a foundation for a more detailed interrogation of chromatin biology by functional 699 proteomics. The data resource associated with this study provides a framework for 700 generating novel hypotheses aimed at revealing the molecular features of ageing and at 701 developing novel approaches to mitigate age-related ailments. 702 703 704 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in lysates were separated on SDS-PAGE gels and transferred to nitrocellulose membranes. 755 Membranes were blocked with 5% non fat milk or 5% BSA at room temperature for 1 756 hour and incubated overnight with diluted primary antibody at 4 °C. Membranes were 757 then washed and incubated with HRP-conjugated goat-anti-rabbit or mouse IgG 758 secondary antibody for 1 hour at room temperature. Membrane was incubated with 759 enhanced chemiluminescence reagents (Thermo Scientific) followed by exposure to X-760 ray films. Immunoblotting was performed using the antibodies and conditions listed in 761 Supplementary material

ABSTRACT FIGURE 936
Quantitative proteomics strategy for the enrichment of chromatin associated proteins 937 from six mouse organs harvested from an ageing model. Following chromatin extraction, 938 proteins were analysed using high resolution quantitative mass spectrometry couple 939 with biochemistry and bioinformatics analysis to identify unique differentially regulated 940 proteins and pathways. 941 protein among different organs (heart, liver, lung, kidney and spleen). The relative 976 abundances were quantified based on the total ion current. Obtained quantitative 977 results were used to calculate the relative abundances of distinct chromatin associated 978 and nuclear proteins in each organ, where the sum of all total ion current intensities was 979 considered as 100%. Legend colour indicates blue chromatin associated protein, green 980 nuclear proteins, and yellow protein associated with other cellular components. The 981 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. proportion of chromatin associated proteins and nuclear proteins present for the "core" 1002 proteome and for the unique organ-specific profile are shown. The relative abundances 1003 were quantified based on the total ion current. Obtained quantitative results were used 1004 to calculate the relative abundances of distinct chromatin associated and nuclear 1005 proteins in each organ, where the sum of all total ion current intensities was considered 1006 as 100%. Legend colour indicates blue chromatin associated protein, green nuclear 1007 proteins, and yellow protein associated with other cellular components. 1008 1009 B) Gene Ontology analysis (Biological Processes) of the core proteome (863)  Gene Ontology pathways found to be significantly up-or down-regulated in five organs. 1055 Each chord corresponds to a protein-protein interaction while the STRING interaction 1056 score is indicated by colour (red for high confidence). The quantitative differentially 1057 protein expression during mouse lifespan between 3 and 15 months is shown on the 1058 outer circle on a grey-black intensity scale. 1059 (B) Biochemical validation of four protein module responses to ageing identified using 1060 chromatin associated proteomics. Organ lysates (from brain, heart, liver and kidney) 1061 were immunoblotted with the indicated antibodies. The bar above the blots, organs (brain, heart, kidney, lung, liver, and spleen) over time. Colour subgroups 1096 represent each mouse adult lifespan point, being 3, 5, 10, and 15 months, respectively. 1097 The square black line underneath each box plot represents a technical replicate of each 1098 biological set. 1099 C) Volcano plots of differentially regulated proteins in mouse brain using PolySTest 1100 statistical analysis tool. Specific enrichments for each protein were calculated by Rack 1101 test. Adjusted q-values were calculated to correct for multiple testing (-log10 qValue < 1102 0.1 cutoff). 1103 1104 SUPPLEMENTARY FIGURE 5 (S5). Distinct organ ageing profiles are defined by 1105 unique differentially protein expression. 1106 D) Volcano plots of differentially regulated proteins across six organs (brain, heart, 1107 kidney, lung, liver and spleen) between the early (3 months) and the late (15 months) 1108 adult mouse lifespan. Expressed protein significantly changed highlighted in red and 1109 green show respectively down-regulation and up-regulation during mouse lifespan. 1110 Specific enrichments for each protein were calculated by Rack test. Adjusted q-values 1111 were calculated to correct for multiple testing (-log10 qValue < 0.1 cutoff) 1112 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021 E) Co-expression cluster profile, extrapolated from the hierarchical clustering heatmap, 1113 shows the "unique differentially expressed protein" trend changed over time in each 1114 organ. 1115 F) Meta-data analysis reported the quantitative changed expression profile of human 1116 ageing biomarker candidates obtained from the "Human Ageing Genomic Resources" 1117 and "GenAge machine learning databank". 1118 1119 1120 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021 17.
Tvardovskiy, A., Schwämmle, V., Kempf, S. J., Rogowska-Wrzesinska, A., and1157 Jensen, O. N. (2017) Accumulation of histone variant H3.3 with age is associated 1158 with profound changes in the histone methylation landscape. Nucleic Acids Res. 1159 33, 5005-5020 1160 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021  CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in The copyright holder for this this version posted September 12, 2021. ;https://doi.org/10.1101https://doi.org/10. /2021 . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in  . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in  . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in        . CC-BY 4.0 International license perpetuity. It is made available under a preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in