Proteomic Analysis of the Senescence-Associated Secretory Phenotype: GDF-15, IGFBP-2, and Cystatin-C Are Associated With Multiple Aging Traits.

Cellular senescence, a hallmark of aging, results in a senescence-associated secretory phenotype (SASP) with an increased production of proinflammatory cytokines, growth factors, and proteases. Evidence from nonhuman models demonstrates that SASP contributes to tissue dysfunction and pathological effects of aging. However, there are relatively few human studies on the relationship between SASP and aging-related health outcomes. Proteins from the SASP Atlas were measured in plasma using aptamer-based proteomics (SomaLogic). Regression models were used to identify SASP protein associations with aging-related traits representing multiple aspects of physiology in 1 201 participants from 2 human cohort studies (BLSA/GESTALT and InCHIANTI). Traits examined were fasting glucose, C-reactive protein, interleukin-6, alkaline phosphatase, blood urea nitrogen, albumin, red blood cell distribution width, waist circumference, systolic and diastolic blood pressure, gait speed, and grip strength. Study results were combined with a fixed-effect inverse-variance weighted meta-analysis. In the meta-analysis, 28 of 77 SASP proteins were significantly associated with age. Of the 28 age-associated SASP proteins, 18 were significantly associated with 1 or more clinical traits, and 7 SASP proteins were significantly associated with 3 or more traits. Growth/differentiation factor 15, Insulin-like growth factor-binding protein 2, and Cystatin-C showed significant associations with inflammatory markers and measures of physical function (grip strength or gait speed). These results support the relevance of SASP proteins to human aging, identify specific traits that are potentially affected by SASP, and prioritize specific SASP proteins for their utility as biomarkers of human aging.

Translating Senotherapeutic Interventions into the Clinic with Emerging Proteomic Technologies.

Cellular senescence is a state of irreversible growth arrest with profound phenotypic changes, including the senescence-associated secretory phenotype (SASP). Senescent cell accumulation contributes to aging and many pathologies including chronic inflammation, type 2 diabetes, cancer, and neurodegeneration. Targeted removal of senescent cells in preclinical models promotes health and longevity, suggesting that the selective elimination of senescent cells is a promising therapeutic approach for mitigating a myriad of age-related pathologies in humans. However, moving senescence-targeting drugs (senotherapeutics) into the clinic will require therapeutic targets and biomarkers, fueled by an improved understanding of the complex and dynamic biology of senescent cell populations and their molecular profiles, as well as the mechanisms underlying the emergence and maintenance of senescence cells and the SASP. Advances in mass spectrometry-based proteomic technologies and workflows have the potential to address these needs. Here, we review the state of translational senescence research and how proteomic approaches have added to our knowledge of senescence biology to date. Further, we lay out a roadmap from fundamental biological discovery to the clinical translation of senotherapeutic approaches through the development and application of emerging proteomic technologies, including targeted and untargeted proteomic approaches, bottom-up and top-down methods, stability proteomics, and surfaceomics. These technologies are integral for probing the cellular composition and dynamics of senescent cells and, ultimately, the development of senotype-specific biomarkers and senotherapeutics (senolytics and senomorphics). This review aims to highlight emerging areas and applications of proteomics that will aid in exploring new senescent cell biology and the future translation of senotherapeutics.

Surfaceome analysis of extracellular vesicles from senescent cells uncovers uptake repressor DPP4.

Senescent cells are beneficial for repairing acute tissue damage, but they are harmful when they accumulate in tissues, as occurs with advancing age. Senescence-associated extracellular vesicles (S-EVs) can mediate cell-to-cell communication and export intracellular content to the microenvironment of aging tissues. Here, we studied the uptake of EVs from senescent cells (S-EVs) and proliferating cells (P-EVs) and found that P-EVs were readily taken up by proliferating cells (fibroblasts and cervical cancer cells) while S-EVs were not. We thus investigated the surface proteome (surfaceome) of P-EVs relative to S-EVs derived from cells that had reached senescence via replicative exhaustion, exposure to ionizing radiation, or treatment with etoposide. We found that relative to P-EVs, S-EVs from all senescence models were enriched in proteins DPP4, ANXA1, ANXA6, S10AB, AT1A1, and EPHB2. Among them, DPP4 was found to selectively prevent uptake by proliferating cells, as ectopic overexpression of DPP4 in HeLa cells rendered DPP4-expressing EVs that were no longer taken up by other proliferating cells. We propose that DPP4 on the surface of S-EVs makes these EVs refractory to internalization by proliferating cells, advancing our knowledge of the impact of senescent cells in aging-associated processes.

Identification and functional analysis of senescent cells in the cardiovascular system using omics approaches.

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality worldwide, and senescent cells have emerged as key contributors to its pathogenesis. Senescent cells exhibit cell cycle arrest and secrete a range of proinflammatory factors, termed the senescence-associated secretory phenotype (SASP), which promotes tissue dysfunction and exacerbates CVD progression. Omics technologies, specifically transcriptomics and proteomics, offer powerful tools to uncover and define the molecular signatures of senescent cells in cardiovascular tissue. By analyzing the comprehensive molecular profiles of senescent cells, omics approaches can identify specific genetic alterations, gene expression patterns, protein abundances, and metabolite levels associated with senescence in CVD. These omics-based discoveries provide insights into the mechanisms underlying senescence-induced cardiovascular damage, facilitating the development of novel diagnostic biomarkers and therapeutic targets. Furthermore, integration of multiple omics data sets enables a systems-level understanding of senescence in CVD, paving the way for precision medicine approaches to prevent or treat cardiovascular aging and its associated complications.

Transcriptomes of human primary skin fibroblasts of healthy individuals reveal age-associated mRNAs and long noncoding RNAs.

Changes in the transcriptomes of human tissues with advancing age are poorly cataloged. Here, we sought to identify the coding and long noncoding RNAs present in cultured primary skin fibroblasts collected from 82 healthy individuals across a wide age spectrum (22-89 years old) who participated in the GESTALT (Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing) study of the National Institute on Aging, NIH. Using high-throughput RNA sequencing and a linear regression model, we identified 1437 coding RNAs (mRNAs) and 1177 linear and circular long noncoding (lncRNAs) that were differentially abundant as a function of age. Gene set enrichment analysis (GSEA) revealed select transcription factors implicated in coordinating the transcription of subsets of differentially abundant mRNAs, while long noncoding RNA enrichment analysis (LncSEA) identified RNA-binding proteins predicted to participate in the age-associated lncRNA profiles. In summary, we report age-associated changes in the global transcriptome, coding and noncoding, from healthy human skin fibroblasts and propose that these transcripts may serve as biomarkers and therapeutic targets in aging skin.

Concerted epithelial and stromal changes during progression of Barrett's Esophagus to invasive adenocarcinoma exposed by multi-scale, multi-omics analysis.

Esophageal adenocarcinoma arises from Barrett's esophagus, a precancerous metaplastic replacement of squamous by columnar epithelium in response to chronic inflammation. Multi-omics profiling, integrating single-cell transcriptomics, extracellular matrix proteomics, tissue-mechanics and spatial proteomics of 64 samples from 12 patients' paths of progression from squamous epithelium through metaplasia, dysplasia to adenocarcinoma, revealed shared and patient-specific progression characteristics. The classic metaplastic replacement of epithelial cells was paralleled by metaplastic changes in stromal cells, ECM and tissue stiffness. Strikingly, this change in tissue state at metaplasia was already accompanied by appearance of fibroblasts with characteristics of carcinoma-associated fibroblasts and of an NK cell-associated immunosuppressive microenvironment. Thus, Barrett's esophagus progresses as a coordinated multi-component system, supporting treatment paradigms that go beyond targeting cancerous cells to incorporating stromal reprogramming.

Blood Biomarkers for Healthy Aging.

Measuring the abundance of biological molecules and their chemical modifications in blood and tissues has been the cornerstone of research and medical diagnoses for decades. Although the number and variety of molecules that can be measured have expanded exponentially, the blood biomarkers routinely assessed in medical practice remain limited to a few dozen, which have not substantially changed over the last 30-40 years. The discovery of novel biomarkers would allow, for example, risk stratification or monitoring of disease progression or the effectiveness of treatments and interventions, improving clinical practice in myriad ways. In this review, we combine the biomarker discovery concept with geroscience. Geroscience bridges aging research and translation to clinical applications by combining the framework of medical gerontology with high-technology medical research. With the development of geroscience and the rise of blood biomarkers, there has been a paradigm shift from disease prevention and cure to promoting health and healthy aging. New -omic technologies have played a role in the development of blood biomarkers, including epigenetic, proteomic, metabolomic, and lipidomic markers, which have emerged as correlates or predictors of health status, from disease to exceptional health.

The transcription regulator ATF4 is a mediator of skeletal muscle aging.

Aging slowly erodes skeletal muscle strength and mass, eventually leading to profound functional deficits and muscle atrophy. The molecular mechanisms of skeletal muscle aging are not well understood. To better understand mechanisms of muscle aging, we investigated the potential role of ATF4, a transcription regulatory protein that can rapidly promote skeletal muscle atrophy in young animals deprived of adequate nutrition or activity. To test the hypothesis that ATF4 may be involved in skeletal muscle aging, we studied fed and active muscle-specific ATF4 knockout mice (ATF4 mKO mice) at 6 months of age, when wild-type mice have achieved peak muscle mass and function, and at 22 months of age, when wild-type mice have begun to manifest age-related muscle atrophy and weakness. We found that 6-month-old ATF4 mKO mice develop normally and are phenotypically indistinguishable from 6-month-old littermate control mice. However, as ATF4 mKO mice become older, they exhibit significant protection from age-related declines in strength, muscle quality, exercise capacity, and muscle mass. Furthermore, ATF4 mKO muscles are protected from some of the transcriptional changes characteristic of normal muscle aging (repression of certain anabolic mRNAs and induction of certain senescence-associated mRNAs), and ATF4 mKO muscles exhibit altered turnover of several proteins with important roles in skeletal muscle structure and metabolism. Collectively, these data suggest ATF4 as an essential mediator of skeletal muscle aging and provide new insight into a degenerative process that impairs the health and quality of life of many older adults.

Proteomic Analysis of Huntington's Disease Medium Spiny Neurons Identifies Alterations in Lipid Droplets.

Huntington's disease (HD) is a neurodegenerative disease caused by a CAG repeat expansion in the Huntingtin (HTT) gene. The resulting polyglutamine (polyQ) tract alters the function of the HTT protein. Although HTT is expressed in different tissues, the medium-spiny projection neurons (MSNs) in the striatum are particularly vulnerable in HD. Thus, we sought to define the proteome of human HD patient-derived MSNs. We differentiated HD72-induced pluripotent stem cells and isogenic controls into MSNs and carried out quantitative proteomic analysis. Using data-dependent acquisitions with FAIMS for label-free quantification on the Orbitrap Lumos mass spectrometer, we identified 6323 proteins with at least two unique peptides. Of these, 901 proteins were altered significantly more in the HD72-MSNs than in isogenic controls. Functional enrichment analysis of upregulated proteins demonstrated extracellular matrix and DNA signaling (DNA replication pathway, double-strand break repair, G1/S transition) with the highest significance. Conversely, processes associated with the downregulated proteins included neurogenesis-axogenesis, the brain-derived neurotrophic factor-signaling pathway, Ephrin-A:EphA pathway, regulation of synaptic plasticity, triglyceride homeostasis cholesterol, plasmid lipoprotein particle immune response, interferon-γ signaling, immune system major histocompatibility complex, lipid metabolism, and cellular response to stimulus. Moreover, proteins involved in the formation and maintenance of axons, dendrites, and synapses (e.g., septin protein members) were dysregulated in HD72-MSNs. Importantly, lipid metabolism pathways were altered, and using quantitative image analysis, we found that lipid droplets accumulated in the HD72-MSN, suggesting a deficit in the turnover of lipids possibly through lipophagy. Our proteomics analysis of HD72-MSNs identified relevant pathways that are altered in MSNs and confirm current and new therapeutic targets for HD.

Data-independent acquisition and quantification of extracellular matrix from human lung in chronic inflammation-associated carcinomas.

Early events associated with chronic inflammation and cancer involve significant remodeling of the extracellular matrix (ECM), which greatly affects its composition and functional properties. Using lung squamous cell carcinoma (LSCC), a chronic inflammation-associated cancer (CIAC), we optimized a robust proteomic pipeline to discover potential biomarker signatures and protein changes specifically in the stroma. We combined ECM enrichment from fresh human tissues, data-independent acquisition (DIA) strategies, and stringent statistical processing to analyze "Tumor" and matched adjacent histologically normal ("Matched Normal") tissues from patients with LSCC. Overall, 1802 protein groups were quantified with at least two unique peptides, and 56% of those proteins were annotated as "extracellular." Confirming dramatic ECM remodeling during CIAC progression, 529 proteins were significantly altered in the "Tumor" compared to "Matched Normal" tissues. The signature was typified by a coordinated loss of basement membrane proteins and small leucine-rich proteins. The dramatic increase in the stromal levels of SERPINH1/heat shock protein 47, that was discovered using our ECM proteomic pipeline, was validated by immunohistochemistry (IHC) of "Tumor" and "Matched Normal" tissues, obtained from an independent cohort of LSCC patients. This integrated workflow provided novel insights into ECM remodeling during CIAC progression, and identified potential biomarker signatures and future therapeutic targets.

TurnoveR: A Skyline External Tool for Analysis of Protein Turnover in Metabolic Labeling Studies.

In spite of its central role in biology and disease, protein turnover is a largely understudied aspect of most proteomic studies due to the complexity of computational workflows that analyze in vivo turnover rates. To address this need, we developed a new computational tool, TurnoveR, to accurately calculate protein turnover rates from mass spectrometric analysis of metabolic labeling experiments in Skyline, a free and open-source proteomics software platform. TurnoveR is a straightforward graphical interface that enables seamless integration of protein turnover analysis into a traditional proteomics workflow in Skyline, allowing users to take advantage of the advanced and flexible data visualization and curation features built into the software. The computational pipeline of TurnoveR performs critical steps to determine protein turnover rates, including isotopologue demultiplexing, precursor-pool correction, statistical analysis, and generation of data reports and visualizations. This workflow is compatible with many mass spectrometric platforms and recapitulates turnover rates and differential changes in turnover rates between treatment groups calculated in previous studies. We expect that the addition of TurnoveR to the widely used Skyline proteomics software will facilitate wider utilization of protein turnover analysis in highly relevant biological models, including aging, neurodegeneration, and skeletal muscle atrophy.

A bright future for proteomics of health and disease. Introduction to the US HUPO 2021 themed issue - proteomics from single cell to systems biology in health and disease.

In this themed issue of Molecular Omics, in partnership with the U.S. Human Proteome Organization, we are proud to present the latest research featured at the 17th Annual US HUPO conference: Proteomics from Single Cell to Systems Biology in Health and Disease. This issue is a testament to the continuing contributions of proteomic research, particularly the application of modern mass spectrometry-based proteomic workflows, to the advancement of our understanding of the underlying human biology and mechanisms of disease.

Connecting aging biology and inflammation in the omics era.

Aging is characterized by the accumulation of damage to macromolecules and cell architecture that triggers a proinflammatory state in blood and solid tissues, termed inflammaging. Inflammaging has been implicated in the pathogenesis of many age-associated chronic diseases as well as loss of physical and cognitive function. The search for mechanisms that underlie inflammaging focused initially on the hallmarks of aging, but it is rapidly expanding in multiple directions. Here, we discuss the threads connecting cellular senescence and mitochondrial dysfunction to impaired mitophagy and DNA damage, which may act as a hub for inflammaging. We explore the emerging multi-omics efforts that aspire to define the complexity of inflammaging - and identify molecular signatures and novel targets for interventions aimed at counteracting excessive inflammation and its deleterious consequences while preserving the physiological immune response. Finally, we review the emerging evidence that inflammation is involved in brain aging and neurodegenerative diseases. Our goal is to broaden the research agenda for inflammaging with an eye on new therapeutic opportunities.

Comprehensive proteomic quantification of bladder stone progression in a cystinuric mouse model using data-independent acquisitions.

Cystinuria is one of various disorders that cause biomineralization in the urinary system, including bladder stone formation in humans. It is most prevalent in children and adolescents and more aggressive in males. There is no cure, and only limited disease management techniques help to solubilize the stones. Recurrence, even after treatment, occurs frequently. Other than a buildup of cystine, little is known about factors involved in the formation, expansion, and recurrence of these stones. This study sought to define the growth of bladder stones, guided by micro-computed tomography imaging, and to profile dynamic stone proteome changes in a cystinuria mouse model. After bladder stones developed in vivo, they were harvested and separated into four developmental stages (sand, small, medium and large stone), based on their size. Data-dependent and data-independent acquisitions allowed deep profiling of stone proteomics. The proteomic signatures and pathways illustrated major changes as the stones grew. Stones initiate from a small nidus, grow outward, and show major enrichment in ribosomal proteins and factors related to coagulation and platelet degranulation, suggesting a major dysregulation in specific pathways that can be targeted for new therapeutic options.

Measurement of Protein Turnover Rates in Senescent and Non-Dividing Cultured Cells with Metabolic Labeling and Mass Spectrometry.

Mounting evidence has shown that the accumulation of senescent cells in the central nervous system contributes to neurodegenerative disorders such as Alzheimer's and Parkinson's diseases. Cellular senescence is a state of permanent cell cycle arrest that typically occurs in response to exposure to sub-lethal stresses. However, like other non-dividing cells, senescent cells remain metabolically active and carry out many functions that require unique transcriptional and translational demands and widespread changes in the intracellular and secreted proteomes. Understanding how protein synthesis and decay rates change during senescence can illuminate the underlying mechanisms of cellular senescence and find potential therapeutic avenues for diseases exacerbated by senescent cells. This paper describes a method for proteome-scale evaluation of protein half-lives in non-dividing cells using pulsed stable isotope labeling by amino acids in cell culture (pSILAC) in combination with mass spectrometry. pSILAC involves metabolic labeling of cells with stable heavy isotope-containing versions of amino acids. Coupled with modern mass spectrometry approaches, pSILAC enables the measurement of protein turnover of hundreds or thousands of proteins in complex mixtures. After metabolic labeling, the turnover dynamics of proteins can be determined based on the relative enrichment of heavy isotopes in peptides detected by mass spectrometry. In this protocol, a workflow is described for the generation of senescent fibroblast cultures and similarly arrested quiescent fibroblasts, as well as a simplified, single-time point pSILAC labeling time-course that maximizes coverage of anticipated protein turnover rates. Further, a pipeline is presented for the analysis of pSILAC mass spectrometry data and user-friendly calculation of protein degradation rates using spreadsheets. The application of this protocol can be extended beyond senescent cells to any non-dividing cultured cells such as neurons.

Short-term senolytic treatment: a paradigm to promote fracture repair during aging.

Increased age is blamed for a wide range of bone physiological changes, and although the underlying mechanisms affecting the decreased capacity for fracture healing are not fully understood, they are clearly linked to changes at the cellular level. Recent evidence suggests potential roles of senescent cells in response to most tissue injuries, including bone fractures. In this issue of the JCI, Liu, Zhang, and co-authors showed that a senolytic drug cocktail cleared senescent cells from the callus and improved bone fracture repair in aged mice. Understanding how senescent cells emerge at fracture sites and how their timely removal improves fracture healing should provide insights for effective therapeutic approaches in old age.

Quantification and Identification of Post-Translational Modifications Using Modern Proteomics Approaches.

Post-translational modifications (PTMs) occur dynamically, allowing cells to quickly respond to changes in the environment. Lysine residues can be targeted by several modifications including acylations (acetylation, succinylation, malonylation, glutarylation, and others), methylation, ubiquitination, and other modifications. One of the most efficient methods for the identification of post-translational modifications is utilizing immunoaffinity enrichment followed by high-resolution mass spectrometry. This workflow can be coupled with comprehensive data-independent acquisition (DIA) mass spectrometry to be a high-throughput, label-free PTM quantification approach. Below we describe a detailed protocol to process tissue by homogenization and proteolytically digest proteins, followed by immunoaffinity enrichment of lysine-acetylated peptides to identify and quantify relative changes of acetylation comparing different conditions.

Proteomics in aging research: A roadmap to clinical, translational research.

The identification of plasma proteins that systematically change with age and, independent of chronological age, predict accelerated decline of health is an expanding area of research. Circulating proteins are ideal translational "omics" since they are final effectors of physiological pathways and because physicians are accustomed to use information of plasma proteins as biomarkers for diagnosis, prognosis, and tracking the effectiveness of treatments. Recent technological advancements, including mass spectrometry (MS)-based proteomics, multiplexed proteomic assay using modified aptamers (SOMAscan), and Proximity Extension Assay (PEA, O-Link), have allowed for the assessment of thousands of proteins in plasma or other biological matrices, which are potentially translatable into new clinical biomarkers and provide new clues about the mechanisms by which aging is associated with health deterioration and functional decline. We carried out a detailed literature search for proteomic studies performed in different matrices (plasma, serum, urine, saliva, tissues) and species using multiple platforms. Herein, we identified 232 proteins that were age-associated across studies. Enrichment analysis of the 232 age-associated proteins revealed metabolic pathways previously connected with biological aging both in animal models and in humans, most remarkably insulin-like growth factor (IGF) signaling, mitogen-activated protein kinases (MAPK), hypoxia-inducible factor 1 (HIF1), cytokine signaling, Forkhead Box O (FOXO) metabolic pathways, folate metabolism, advance glycation end products (AGE), and receptor AGE (RAGE) metabolic pathway. Information on these age-relevant proteins, likely expanded and validated in longitudinal studies and examined in mechanistic studies, will be essential for patient stratification and the development of new treatments aimed at improving health expectancy.