Proteome dynamics: revisiting turnover with a global perspective

Changes in protein fluxes in skeletal muscle during sequential stages of muscle regeneration after acute injury in male mice

Changes in protein turnover play an important role in dynamic physiological processes, including skeletal muscle regeneration, which occurs as an essential part of tissue repair after injury. The inability of muscle tissue to recapitulate this regenerative process can lead to the manifestation of clinical symptoms in various musculoskeletal diseases, including muscular dystrophies and pathological atrophy. Here, we employed a workflow that couples deuterated water (2H2O) administration with mass spectrometry (MS) to systematically measure in-vivo protein turnover rates across the muscle proteome in 8-week-old male C57BL6/J mice. We compared the turnover kinetics of over 100 proteins in response to cardiotoxin (CTX) induced muscle damage and regeneration at unique sequential stages along the regeneration timeline. This analysis is compared to gene expression data from mRNA-sequencing (mRNA-seq) from the same tissue. The data reveals quantitative protein flux signatures in response to necrotic damage, in addition to sequential differences in cell proliferation, energy metabolism, and contractile gene expression. Interestingly, the mRNA changes correlated poorly with changes in protein synthesis rates, consistent with post-transcriptional control mechanisms. In summary, the experiments described here reveal the signatures and timing of protein flux changes during skeletal muscle regeneration, as well as the inability of mRNA expression measurements to reveal changes in directly measured protein turnover rates. The results of this work described here provide a better understanding of the muscle regeneration process and could help to identify potential biomarkers or therapeutic targets.

Proteome Birthdating Reveals Age-Selectivity of Protein Ubiquitination

Within a cell, proteins have distinct and highly variable half-lives. As a result, the molecular ages of proteins can range from seconds to years. How the age of a protein influences its environmental interactions is a largely unexplored area of biology. To investigate the age-selectivity of cellular pathways, we developed a methodology termed "proteome birthdating" that barcodes proteins based on their time of synthesis. We demonstrate that this approach provides accurate measurements of protein turnover kinetics from a single biological sample encoding multiple labeling time-points. As a first application of the birthdated proteome, we investigated the age distribution of the human ubiquitinome. Our results indicate that the vast majority of ubiquitinated proteins in a cell consist of newly synthesized proteins and that these young proteins constitute the bulk of the degradative flux through the proteasome. Rapidly ubiquitinated nascent proteins are enriched in cytosolic subunits of large protein complexes. Conversely, proteins destined for the secretory pathway and vesicular transport have older ubiquitinated populations. Our data also identify a smaller subset of older ubiquitinated cellular proteins that do not appear to be targeted to the proteasome for rapid degradation. Together, our data provide an age census of the human ubiquitinome and establish proteome birthdating as a robust methodology for investigating the protein age-selectivity of diverse cellular pathways.

The purpose and ubiquity of turnover

Turnover-constant component production and destruction-is ubiquitous in biology. Turnover occurs across organisms and scales, including for RNAs, proteins, membranes, macromolecular structures, organelles, cells, hair, feathers, nails, antlers, and teeth. For many systems, turnover might seem wasteful when degraded components are often fully functional. Some components turn over with shockingly high rates and others do not turn over at all, further making this process enigmatic. However, turnover can address fundamental problems by yielding powerful properties, including regeneration, rapid repair onset, clearance of unpredictable damage and errors, maintenance of low constitutive levels of disrepair, prevention of stable hazards, and transitions. I argue that trade-offs between turnover benefits and metabolic costs, combined with constraints on turnover, determine its presence and rates across distinct contexts. I suggest that the limits of turnover help explain aging and that turnover properties and the basis for its levels underlie this fundamental component of life.

Systematic analysis of proteome turnover in an organoid model of pancreatic cancer by dSILO

The role of protein turnover in pancreatic ductal adenocarcinoma (PDA) metastasis has not been previously investigated. We introduce dynamic stable-isotope labeling of organoids (dSILO): a dynamic SILAC derivative that combines a pulse of isotopically labeled amino acids with isobaric tandem mass-tag (TMT) labeling to measure proteome-wide protein turnover rates in organoids. We applied it to a PDA model and discovered that metastatic organoids exhibit an accelerated global proteome turnover compared to primary tumor organoids. Globally, most turnover changes are not reflected at the level of protein abundance. Interestingly, the group of proteins that show the highest turnover increase in metastatic PDA compared to tumor is involved in mitochondrial respiration. This indicates that metastatic PDA may adopt alternative respiratory chain functionality that is controlled by the rate at which proteins are turned over. Collectively, our analysis of proteome turnover in PDA organoids offers insights into the mechanisms underlying PDA metastasis.

Simultaneous proteome localization and turnover analysis reveals spatiotemporal features of protein homeostasis disruptions

The spatial and temporal distributions of proteins are critical to protein function, but cannot be directly assessed by measuring protein bundance. Here we describe a mass spectrometry-based proteomics strategy, Simultaneous Proteome Localization and Turnover (SPLAT), to measure concurrently protein turnover rates and subcellular localization in the same experiment. Applying the method, we find that unfolded protein response (UPR) has different effects on protein turnover dependent on their subcellular location in human AC16 cells, with proteome-wide slowdown but acceleration among stress response proteins in the ER and Golgi. In parallel, UPR triggers broad differential localization of proteins including RNA-binding proteins and amino acid transporters. Moreover, we observe newly synthesized proteins including EGFR that show a differential localization under stress than the existing protein pools, reminiscent of protein trafficking disruptions. We next applied SPLAT to an induced pluripotent stem cell derived cardiomyocyte (iPSC-CM) model of cancer drug cardiotoxicity upon treatment with the proteasome inhibitor carfilzomib. Paradoxically, carfilzomib has little effect on global average protein half-life, but may instead selectively disrupt sarcomere protein homeostasis. This study provides a view into the interactions of protein spatial and temporal dynamics and demonstrates a method to examine protein homeostasis regulations in stress and drug response.

In utero pulse injection of isotopic amino acids quantifies protein turnover rates during murine fetal development

Protein translational control is critical for ensuring that the fetus develops correctly and that necessary organs and tissues are formed and functional. We developed an in utero method to quantify tissue-specific protein dynamics by monitoring amino acid incorporation into the proteome after pulse injection. Fetuses of pregnant mice were injected with isotopically labeled lysine and arginine via the vitelline vein at various embyonic days, and organs and tissues were harvested. By analyzing the nascent proteome, unique signatures of each tissue were identified by hierarchical clustering. In addition, the quantified proteome-wide turnover rates were calculated between 3.81E-5 and 0.424 h-1. We observed similar protein turnover profiles for analyzed organs (e.g., liver vs. brain); however, their distributions of turnover rates vary significantly. The translational kinetic profiles of developing organs displayed differentially expressed protein pathways and synthesis rates, which correlated with known physiological changes during mouse development.

Simultaneous proteome localization and turnover analysis reveals spatiotemporal features of protein homeostasis disruptions

The functions of proteins depend on their spatial and temporal distributions, which are not directly measured by static protein abundance. Under endoplasmic reticulum (ER) stress, the unfolded protein response (UPR) pathway remediates proteostasis in part by altering the turnover kinetics and spatial distribution of proteins. A global view of these spatiotemporal changes has yet to emerge and it is unknown how they affect different cellular compartments and pathways. Here we describe a mass spectrometry-based proteomics strategy and data analysis pipeline, termed Simultaneous Proteome Localization and Turnover (SPLAT), to measure concurrently the changes in protein turnover and subcellular distribution in the same experiment. Investigating two common UPR models of thapsigargin and tunicamycin challenge in human AC16 cells, we find that the changes in protein turnover kinetics during UPR varies across subcellular localizations, with overall slowdown but an acceleration in endoplasmic reticulum and Golgi proteins involved in stress response. In parallel, the spatial proteomics component of the experiment revealed an externalization of amino acid transporters and ion channels under UPR, as well as the migration of RNA-binding proteins toward an endosome co-sedimenting compartment. The SPLAT experimental design classifies heavy and light SILAC labeled proteins separately, allowing the observation of differential localization of new and old protein pools and capturing a partition of newly synthesized EGFR and ITGAV to the ER under stress that suggests protein trafficking disruptions. Finally, application of SPLAT toward human induced pluripotent stem cell derived cardiomyocytes (iPSC-CM) exposed to the cancer drug carfilzomib, identified a selective disruption of proteostasis in sarcomeric proteins as a potential mechanism of carfilzomib-mediated cardiotoxicity. Taken together, this study provides a global view into the spatiotemporal dynamics of human cardiac cells and demonstrates a method for inferring the coordinations between spatial and temporal proteome regulations in stress and drug response.

Emerging Prognostic and Predictive Significance of Stress Keratin 17 in HPV-Associated and Non HPV-Associated Human Cancers: A Scoping Review

A growing body of literature suggests that the expression of cytokeratin 17 (K17) correlates with inferior clinical outcomes across various cancer types. In this scoping review, we aimed to review and map the available clinical evidence of the prognostic and predictive value of K17 in human cancers. PubMed, Web of Science, Embase (via Scopus), Cochrane Central Register of Controlled Trials, and Google Scholar were searched for studies of K17 expression in human cancers. Eligible studies were peer-reviewed, published in English, presented original data, and directly evaluated the association between K17 and clinical outcomes in human cancers. Of the 1705 studies identified in our search, 58 studies met criteria for inclusion. Studies assessed the prognostic significance (n = 54), predictive significance (n = 2), or both the prognostic and predictive significance (n = 2). Altogether, 11 studies (19.0%) investigated the clinical relevance of K17 in cancers with a known etiologic association to HPV; of those, 8 (13.8%) were focused on head and neck squamous cell carcinoma (HNSCC), and 3 (5.1%) were focused on cervical squamous cell carcinoma (SCC). To date, HNSCC, as well as triple-negative breast cancer (TNBC) and pancreatic cancer, were the most frequently studied cancer types. K17 had prognostic significance in 16/17 investigated cancer types and 43/56 studies. Our analysis suggests that K17 is a negative prognostic factor in the majority of studied cancer types, including HPV-associated types such as HNSCC and cervical cancer (13/17), and a positive prognostic factor in 2/17 studied cancer types (urothelial carcinoma of the upper urinary tract and breast cancer). In three out of four predictive studies, K17 was a negative predictive factor for chemotherapy and immune checkpoint blockade therapy response.

Proteomic Approach to Investigating Expression, Localization, and Functions of the SOWAHD Gene Protein Product during Granulocytic Differentiation

Cataloging human proteins and evaluation of their expression, cellular localization, functions, and potential medical significance are important tasks for the global proteomic community. At present, localization and functions of protein products for almost half of protein-coding genes remain unknown or poorly understood. Investigation of organelle proteomes is a promising approach to uncovering localization and functions of human proteins. Nuclear proteome is of particular interest because many nuclear proteins, e.g., transcription factors, regulate functions that determine cell fate. Meta-analysis of the nuclear proteome, or nucleome, of HL-60 cells treated with all-trans-retinoic acid (ATRA) has shown that the functions and localization of a protein product of the SOWAHD gene are poorly understood. Also, there is no comprehensive information on the SOWAHD gene expression at the protein level. In HL-60 cells, the number of mRNA transcripts of the SOWAHD gene was determined as 6.4 ± 0.7 transcripts per million molecules. Using targeted mass spectrometry, the content of the SOWAHD protein was measured as 0.27 to 1.25 fmol/μg total protein. The half-life for the protein product of the SOWAHD gene determined using stable isotope pulse-chase labeling was ~19 h. Proteomic profiling of the nuclear fraction of HL-60 cells showed that the content of the SOWAHD protein increased during the ATRA-induced granulocytic differentiation, reached the peak value at 9 h after ATRA addition, and then decreased. Nuclear location and involvement of the SOWAHD protein in the ATRA-induced granulocytic differentiation have been demonstrated for the first time.

In utero pulse injection of isotopic amino acids quantifies protein turnover rates during murine fetal development

Protein translational control is highly regulated step in the gene expression program during mammalian development that is critical for ensuring that the fetus develops correctly and that all of the necessary organs and tissues are formed and functional. Defects in protein expression during fetal development can lead to severe developmental abnormalities or premature death. Currently, quantitative techniques to monitor protein synthesis rates in a developing fetus (in utero) are limited. Here, we developed a novel in utero stable isotope labeling approach to quantify tissue-specific protein dynamics of the nascent proteome during mouse fetal development. Fetuses of pregnant C57BL/6J mice were injected with isotopically labeled lysine (Lys8) and arginine (Arg10) via the vitelline vein at various gestational days. After treatment, fetal organs/tissues including brain, liver, lung, and heart were harvested for sample preparation and proteomic analysis. We show that the mean incorporation rate for injected amino acids into all organs was 17.50 ± 0.6%. By analyzing the nascent proteome, unique signatures of each tissue were identified by hierarchical clustering. In addition, the quantified proteome-wide turnover rates (kobs) were calculated between 3.81E-5 and 0.424 hour-1. We observed similar protein turnover profiles for analyzed organs (e.g., liver versus brain), however, their distributions of turnover rates vary significantly. The translational kinetic profiles of developing organs displayed differentially expressed protein pathways and synthesis rates which correlated with known physiological changes during mouse development.

Toward a hypothesis-free understanding of how phosphorylation dynamically impacts protein turnover

The turnover measurement of proteins and proteoforms has been largely facilitated by workflows coupling metabolic labeling with mass spectrometry (MS), including dynamic stable isotope labeling by amino acids in cell culture (dynamic SILAC) or pulsed SILAC (pSILAC). Very recent studies including ours have integrated themeasurement of post-translational modifications (PTMs) at the proteome level (i.e., phosphoproteomics) with pSILAC experiments in steady state systems, exploring the link between PTMs and turnover at the proteome-scale. An open question in the field is how to exactly interpret these complex datasets in a biological perspective. Here, we present a novel pSILAC phosphoproteomic dataset which was obtained during a dynamic process of cell starvation using data-independent acquisition MS (DIA-MS). To provide an unbiased "hypothesis-free" analysis framework, we developed a strategy to interrogate how phosphorylation dynamically impacts protein turnover across the time series data. With this strategy, we discovered a complex relationship between phosphorylation and protein turnover that was previously underexplored. Our results further revealed a link between phosphorylation stoichiometry with the turnover of phosphorylated peptidoforms. Moreover, our results suggested that phosphoproteomic turnover diversity cannot directly explain the abundance regulation of phosphorylation during cell starvation, underscoring the importance of future studies addressing PTM site-resolved protein turnover.

Protein-Peptide Turnover Profiling reveals the order of PTM addition and removal during protein maturation

Post-translational modifications (PTMs) regulate various aspects of protein function, including degradation. Mass spectrometric methods relying on pulsed metabolic labeling are popular to quantify turnover rates on a proteome-wide scale. Such data have traditionally been interpreted in the context of protein proteolytic stability. Here, we combine theoretical kinetic modeling with experimental pulsed stable isotope labeling of amino acids in cell culture (pSILAC) for the study of protein phosphorylation. We demonstrate that metabolic labeling combined with PTM-specific enrichment does not measure effects of PTMs on protein stability. Rather, it reveals the relative order of PTM addition and removal along a protein's lifetime-a fundamentally different metric. This is due to interconversion of the measured proteoform species. Using this framework, we identify temporal phosphorylation sites on cell cycle-specific factors and protein complex assembly intermediates. Our results thus allow tying PTMs to the age of the modified proteins.

Quantifying Turnover Dynamics of Selenoproteome by Isotopic Perturbation

Selenium, as an essential trace element of life, is closely related to human health and is required to produce selenoproteins, a family of important functional proteins in many living organisms. All selenoproteins contain a special amino acid, selenocysteine, which often serves as their active-site residue, and the expression and activity of selenoproteins are fine-tuned. However, the turnover dynamics of selenoproteome has never been systematically investigated, especially in a site-specific manner for selenocysteines. In the current work, we developed a chemical proteomic strategy named "SElenoprotein Turnover Rate by Isotope Perturbation (SETRIP)" to quantitatively monitor the turnover dynamics of selenoproteins at the proteomic level. The kinetic rates and half-lives of nine selenoproteins were accurately measured by combining Na₂⁷⁴SeO₃ metabolic labeling with pulse-chase chemoproteomics. The half-lives of selenoproteins were measured to range from 6 to 32 h with the housekeeping selenoprotein glutathione peroxidases (GPX4) showing a faster turnover rate, implying that the hierarchy regulation also exists in the turnover of selenoproteins in addition to expression and activity. Our study generated a global portrait of dynamic changes in the selenoproteome and provided important clues to study the roles of selenium in biology.

Versatile Functional Energy Metabolism Platform Working From Research to Patient: An Integrated View of Cell Bioenergetics

Mitochondrial dysfunctions that were not discovered during preclinical and clinical testing have been responsible for at least restriction of use as far as withdrawal of many drugs. To solve mitochondrial machinery complexity, integrative methodologies combining different data, coupled or not to mathematic modelling into systems biology, could represent a strategic way but are still very hard to implement. These technologies should be accurate and precise to avoid accumulation of errors that can lead to misinterpretations, and then alter prediction efficiency. To address such issue, we have developed a versatile functional energy metabolism platform that can measure quantitatively, in parallel, with a very high precision and accuracy, a high number of biological parameters like substrates or enzyme cascade activities in essential metabolism units (glycolysis, respiratory chain ATP production, oxidative stress...) Its versatility (our platform works on either cell lines or small animals and human samples) allows cell metabolism pathways fine tuning comparison from preclinical to clinical studies. Applied here to OXPHOS and/or oxidative stress as an example, it allows discriminating compounds with acute toxic effects but, most importantly, those inducing low noise chronic ones.

Protein turnover models for LC-MS data of heavy water metabolic labeling

Protein turnover is vital for cellular functioning and is often associated with the pathophysiology of a variety of diseases. Metabolic labeling with heavy water followed by liquid chromatography coupled to mass spectrometry is a powerful tool to study in vivo protein turnover in high throughput and large scale. Heavy water is a cost-effective and easy to use labeling agent. It labels all nonessential amino acids. Due to its toxicity in high concentrations (20% or higher), small enrichments (8% or smaller) of heavy water are used with most organisms. The low concentration results in incomplete labeling of peptides/proteins. Therefore, the data processing is more challenging and requires accurate quantification of labeled and unlabeled forms of a peptide from overlapping mass isotopomer distributions. The work describes the bioinformatics aspects of the analysis of heavy water labeled mass spectral data, available software tools and current challenges and opportunities.

Studying Autophagy Using a TMT-Based Quantitative Proteomics Approach

Maintenance of cellular homeostasis through regulated degradation of proteins and organelles is a defining feature of autophagy. This process itself is tightly regulated in a series of well-defined biochemical reactions governed largely by the highly conserved ATG protein family. Given its crucial role in regulating protein levels under both basal and stress conditions such as starvation and infection, genetic or pharmacological perturbation of autophagy results in massive changes in the cellular proteome and impacts nearly every biological process. Therefore, studying autophagy perturbations at a global scale assumes prime importance. In recent years, quantitative mass spectrometry (MS)-based proteomics has emerged as a powerful approach to explore biological processes through global proteome quantification analysis. Tandem mass tag (TMT)-based MS proteomics is one such robust quantitative technique that can examine relative protein abundances in multiple samples (parallel multiplexing). Investigating autophagy through TMT-based MS approach can give great insights into autophagy-regulated biological processes, protein-protein interaction networks, spatiotemporal protein dynamics, and identification of new autophagy substrates. This chapter provides a detailed protocol for studying the impact of a dysfunctional autophagy pathway on the cellular proteome and pathways in a healthy vs. disease (virus infection) condition using a 16-plex TMT-based quantitative proteomics approach. We also provide a pipeline on data processing and analysis using available web-based tools.

Nasal ciliated cells are primary targets for SARS-CoV-2 replication in the early stage of COVID-19

The upper respiratory tract is compromised in the early period of COVID-19, but SARS-CoV-2 tropism at the cellular level is not fully defined. Unlike recent single-cell RNA-Seq analyses indicating uniformly low mRNA expression of SARS-CoV-2 entry-related host molecules in all nasal epithelial cells, we show that the protein levels are relatively high and that their localizations are restricted to the apical side of multiciliated epithelial cells. In addition, we provide evidence in patients with COVID-19 that SARS-CoV-2 is massively detected and replicated within the multiciliated cells. We observed these findings during the early stage of COVID-19, when infected ciliated cells were rapidly replaced by differentiating precursor cells. Moreover, our analyses revealed that SARS-CoV-2 cellular tropism was restricted to the nasal ciliated versus oral squamous epithelium. These results imply that targeting ciliated cells of the nasal epithelium during the early stage of COVID-19 could be an ideal strategy to prevent SARS-CoV-2 propagation.

Protocol for intervention-free quantification of protein turnover rate by steady-state modeling

Protein turnover rate is difficult to obtain experimentally. This protocol shows how to mathematically model turnover rates in an intervention-free manner given the ability to quantify mRNA and protein expression from initiation to homeostasis. This approach can be used to calculate production and degradation rates and to infer protein half-life. This model was successfully employed to quantify turnover during Drosophila embryogenesis, and we hypothesize that it will be applicable to diverse in vivo or in vitro systems. For complete details on the use and execution of this protocol, please refer to Matsubayashi et al. (2020).

Impact of Preanalytical Factors on the Measurement of Tumor Tissue Biomarkers Using Immunohistochemistry

Analysis of formalin-fixed paraffin-embedded (FFPE) tissue by immunohistochemistry (IHC) is commonplace in clinical and research laboratories. However, reports suggest that IHC results can be compromised by biospecimen preanalytical factors. The National Cancer Institute's Biospecimen Preanalytical Variables Program conducted a systematic study to examine the potential effects of delay to fixation (DTF) and time in fixative (TIF) on IHC using 24 cancer biomarkers. Differences in IHC staining, relative to controls with a DTF of 1 hr, were observed in FFPE kidney tumor specimens after a DTF of ≥2 hr. Reductions in H-score and/or staining intensity were observed for c-MET, p53, PAX2, PAX8, pAKT, and survivin, whereas increases were observed for RCC1, EGFR, and CD10. Prolonged TIF of 72 hr resulted in significantly reduced H-scores of CD44 and c-Met in kidney tumor specimens, compared with controls with 12-hr TIF. An elevated probability of altered staining intensity due to DTF was observed for nine antigens, whereas for prolonged TIF an elevated probability was observed for one antigen. Results reported here and elsewhere across tumor types and antigens support limiting DTF to ≤1 hr when possible and fixing tissues in formalin for 12-24 hr to avoid confounding effects of these preanalytical factors on IHC.

BoxCarmax: A High-Selectivity Data-Independent Acquisition Mass Spectrometry Method for the Analysis of Protein Turnover and Complex Samples

The data-independent acquisition (DIA) performed in the latest high-resolution, high-speed mass spectrometers offers a powerful analytical tool for biological investigations. The DIA mass spectrometry (DIA-MS) combined with the isotopic labeling approach holds a particular promise for increasing the multiplexity of DIA-MS analysis, which could assist the relative protein quantification and the proteome-wide turnover profiling. However, the wide MS1 isolation windows employed in conventional DIA methods lead to a limited efficiency in identifying and quantifying isotope-labeled peptide pairs through peptide fragment ions. Here, we optimized a high-selectivity DIA-MS named BoxCarmax that supports the analysis of complex samples, such as those generated from Stable isotope labeling by amino acids in cell culture (SILAC) and pulse SILAC (pSILAC) experiments. BoxCarmax enables multiplexed acquisition at both MS1 and MS2 levels, through the integration of BoxCar and MSX features, as well as a gas-phase separation strategy. We found BoxCarmax significantly improved the quantitative accuracy in SILAC and pSILAC samples by mitigating the ratio suppression of isotope-peptide pairs. We further applied BoxCarmax to measure protein degradation regulation during serum starvation stress in cultured cells, revealing valuable biological insights. Our study offered an alternative and accurate approach for the MS analysis of protein turnover and complex samples.

Isoform-resolved correlation analysis between mRNA abundance regulation and protein level degradation

Profiling of biological relationships between different molecular layers dissects regulatory mechanisms that ultimately determine cellular function. To thoroughly assess the role of protein post‐translational turnover, we devised a strategy combining pulse stable isotope‐labeled amino acids in cells (pSILAC), data‐independent acquisition mass spectrometry (DIA‐MS), and a novel data analysis framework that resolves protein degradation rate on the level of mRNA alternative splicing isoforms and isoform groups. We demonstrated our approach by the genome‐wide correlation analysis between mRNA amounts and protein degradation across different strains of HeLa cells that harbor a high grade of gene dosage variation. The dataset revealed that specific biological processes, cellular organelles, spatial compartments of organelles, and individual protein isoforms of the same genes could have distinctive degradation rate. The protein degradation diversity thus dissects the corresponding buffering or concerting protein turnover control across cancer cell lines. The data further indicate that specific mRNA splicing events such as intron retention significantly impact the protein abundance levels. Our findings support the tight association between transcriptome variability and proteostasis and provide a methodological foundation for studying functional protein degradation.

The application of proteomics in muscle exercise physiology

INTRODUCTION

Exercise offers protection from non-communicable diseases and extends healthspan by offsetting natural physiological declines that occur in older age. Striated muscle is the largest bodily organ; it underpins the capacity for physical work, and the responses of muscle to exercise convey the health benefits of a physically active lifestyle. Proteomic surveys of muscle provide a means to study the protective effects of exercise and this review summaries some key findings from literature listed in PubMed during the last 10 years that have led to new insight in muscle exercise physiology.

AREAS COVERED

'Bottom-up' analyses involving liquid-chromatography tandem mass spectrometry (LC-MS/MS) of peptide digests have become the mainstay of proteomic studies and have been applied to muscle mitochondrial fractions. Enrichment techniques for post-translational modifications, including phosphorylation, acetylation and ubiquitination, have evolved and the analysis of site-specific modifications has become a major area of interest in exercise proteomics. Finally, we consider emergent techniques for dynamic analysis of muscle proteomes that offer new insight to protein turnover and the contributions of synthesis and degradation to changes in protein abundance in response to exercise training.

EXPERT OPINION

Burgeoning methods for dynamic proteome profiling offer new opportunities to study the mechanisms of muscle adaptation.

Transmembrane Prolyl 4-Hydroxylase is a Novel Regulator of Calcium Signaling in Astrocytes

Prolyl 4-hydroxylases (P4Hs) have vital roles in regulating collagen synthesis and hypoxia response. A transmembrane P4H (P4H-TM) is a recently identified member of the family. Biallelic loss of function P4H-TM mutations cause a severe autosomal recessive intellectual disability syndrome in humans, but functions of P4H-TM are essentially unknown at cellular level. Our microarray data on P4h-tm ^-/- mouse cortexes where P4H-TM is abundantly expressed indicated expression changes in genes involved in calcium signaling and expression of several calcium sequestering ATPases was upregulated in P4h-tm ^-/- primary mouse astrocytes. Cytosolic and intraorganellar calcium imaging of P4h-tm ^-/- cells revealed that receptor-operated calcium entry (ROCE) and store-operated calcium entry (SOCE) and calcium re-uptake by mitochondria were compromised. HIF1, but not HIF2, was found to be a key mediator of the P4H-TM effect on calcium signaling. Furthermore, total internal reflection fluorescence (TIRF) imaging showed that calcium agonist-induced gliotransmission was attenuated in P4h-tm ^-/- astrocytes. This phenotype was accompanied by redistribution of mitochondria from distal processes to central parts of the cell body and decreased intracellular ATP content. Our data show that P4H-TM is a novel regulator of calcium dynamics and gliotransmission.

Interspecies Differences in Proteome Turnover Kinetics Are Correlated With Life Spans and Energetic Demands

Cells continually degrade and replace damaged proteins. However, the high energetic demand of protein turnover generates reactive oxygen species that compromise the long-term health of the proteome. Thus, the relationship between aging, protein turnover, and energetic demand remains unclear. Here, we used a proteomic approach to measure rates of protein turnover within primary fibroblasts isolated from a number of species with diverse life spans including the longest-lived mammal, the bowhead whale. We show that organismal life span is negatively correlated with turnover rates of highly abundant proteins. In comparison with mice, cells from long-lived naked mole rats have slower rates of protein turnover, lower levels of ATP production, and reduced reactive oxygen species levels. Despite having slower rates of protein turnover, naked mole rat cells tolerate protein misfolding stress more effectively than mouse cells. We suggest that in lieu of a rapid constitutive turnover, long-lived species may have evolved more energetically efficient mechanisms for selective detection and clearance of damaged proteins.

Proteome Turnover in the Spotlight: Approaches, Applications, and Perspectives

In all cells, proteins are continuously synthesized and degraded to maintain protein homeostasis and modify gene expression levels in response to stimuli. Collectively, the processes of protein synthesis and degradation are referred to as protein turnover. At a steady state, protein turnover is constant to maintain protein homeostasis, but in dynamic responses, proteins change their rates of synthesis and degradation to adjust their proteomes to internal or external stimuli. Thus, probing the kinetics and dynamics of protein turnover lends insight into how cells regulate essential processes such as growth, differentiation, and stress response. Here, we outline historical and current approaches to measuring the kinetics of protein turnover on a proteome-wide scale in both steady-state and dynamic systems, with an emphasis on metabolic tracing using stable isotope-labeled amino acids. We highlight important considerations for designing proteome turnover experiments, key biological findings regarding the conserved principles of proteome turnover regulation, and future perspectives for both technological and biological investigation.

Global and Site-Specific Effect of Phosphorylation on Protein Turnover

To date, the effects of specific modification types and sites on protein lifetime have not been systematically illustrated. Here, we describe a proteomic method, DeltaSILAC, to quantitatively assess the impact of site-specific phosphorylation on the turnover of thousands of proteins in live cells. Based on the accurate and reproducible mass spectrometry-based method, a pulse labeling approach using stable isotope-labeled amino acids in cells (pSILAC), phosphoproteomics, and a unique peptide-level matching strategy, our DeltaSILAC profiling revealed a global, unexpected delaying effect of many phosphosites on protein turnover. We further found that phosphorylated sites accelerating protein turnover are functionally selected for cell fitness, enriched in Cyclin-dependent kinase substrates, and evolutionarily conserved, whereas the glutamic acids surrounding phosphosites significantly delay protein turnover. Our method represents a generalizable approach and provides a rich resource for prioritizing the effects of phosphorylation sites on protein lifetime in the context of cell signaling and disease biology.

High-Resolution Mass Spectrometry for In Vivo Proteome Dynamics using Heavy Water Metabolic Labeling

Cellular proteins are continuously degraded and synthesized. The turnover of proteins is essential to many cellular functions. Combined with metabolic labeling using stable isotopes, LC-MS estimates proteome dynamics in high-throughput and on a large scale. Modern mass spectrometers allow a range of instrumental settings to optimize experimental output for specific research goals. One such setting which affects the results for dynamic proteome studies is the mass resolution. The resolution is vital for distinguishing target species from co-eluting contaminants with close mass-to-charge ratios. However, for estimations of proteome dynamics from metabolic labeling with stable isotopes, the spectral accuracy is highly important. Studies examining the effects of increased mass resolutions (in modern mass spectrometers) on the proteome turnover output and accuracy have been lacking. Here, we use a publicly available heavy water labeling and mass spectral data sets of murine serum proteome (acquired on Orbitrap Fusion and Agilent 6530 QToF) to analyze the effect of mass resolution of the Orbitrap mass analyzer on the proteome dynamics estimation. Increased mass resolution affected the spectral accuracy and the number acquired tandem mass spectra.

Examining Targeted Protein Degradation from Physiological and Analytical Perspectives: Enabling Translation between Cells and Subjects

The ability to target specific proteins for degradation may open a new door toward developing therapeutics. Although effort in chemistry is essential for advancing this modality, i.e., one needs to generate proteolysis targeting chimeras (bifunctional molecules, also referred to as PROTACS) or "molecular glues" to accelerate protein degradation, we suspect that investigations could also benefit by directing attention toward physiological regulation surrounding protein homeostasis, including the methods that can be used to examine changes in protein kinetics. This perspective will first consider some metabolic scenarios that might be of importance when one aims to change protein abundance by increasing protein degradation. Specifically, could protein turnover impact the apparent outcome? We will then outline how to study protein dynamics by coupling stable isotope tracer methods with mass spectrometry-based detection; since the experimental conditions could have a dramatic effect on protein turnover, special attention is directed toward the application of methods for quantifying protein kinetics using in vitro and in vivo models. Our goal is to present key concepts that should enable mechanistically informed studies which test targeted protein degradation strategies.

Optimal leaf life strategies determine Vc,max dynamic during ontogeny

Leaf photosynthetic properties, for example the maximum carboxylation velocity or V_c,max , change with leaf age due to ontogenetic processes. This study introduces an optimal dynamic allocation scheme to model changes in leaf-level photosynthetic capacity as a function of leaf biochemical constraints (costs of synthesis and defence), nitrogen availability and other environmental factors (e.g. light). The model consists of a system of equations describing RuBisCO synthesis and degradation within chloroplasts, defence and ageing at leaf levels, nitrogen transfer and carbon budget at plant levels. Model results show that optimal allocation principles explained RuBisCO dynamics with leaf age. An approximated analytical solution can reproduce the basic pattern of RuBisCO and V_c,max in rice and in two tropical tree species. The model also reveals leaf life complementarities that remained unexplained in previous approaches, as the interplay between V_c,max at maturation, life span and the decline in photosynthetic capacity with age. Furthermore, it explores the role of defence, which is not implemented in current models. This framework covers some of the existing gaps in integrating multiple processes across plant organs (chloroplast, leaf and whole plant) and is a first-step towards representing mechanistically leaf ontogenetic processes into physiological and ecosystem models.

Kinetically distinct processing pathways diversify the CD8+ T cell response to a single viral epitope

The source proteins from which CD8⁺ T cell-activating peptides are derived remain enigmatic. Glycoproteins are particularly challenging in this regard owing to several potential trafficking routes within the cell. By engineering a glycoprotein-derived epitope to contain an N-linked glycosylation site, we determined that optimal CD8⁺ T cell expansion and function were induced by the peptides that are rapidly produced from the exceedingly minor fraction of protein mislocalized to the cytosol. In contrast, peptides derived from the much larger fraction that undergoes translocation and quality control are produced with delayed kinetics and induce suboptimal CD8⁺ T cell responses. This dual system of peptide generation enhances CD8⁺ T cell participation in diversifying both antigenicity and the kinetics of peptide display.

Global analysis of protein degradation in prion infected cells

Prion diseases are rare, neurological disorders caused by the misfolding of the cellular prion protein (PrP^C) into cytotoxic fibrils (PrP^Sc). Intracellular PrP^Sc aggregates primarily accumulate within late endosomes and lysosomes, organelles that participate in the degradation and turnover of a large subset of the proteome. Thus, intracellular accumulation of PrP^Sc aggregates has the potential to globally influence protein degradation kinetics within an infected cell. We analyzed the proteome-wide effect of prion infection on protein degradation rates in N2a neuroblastoma cells by dynamic stable isotopic labeling with amino acids in cell culture (dSILAC) and bottom-up proteomics. The analysis quantified the degradation rates of more than 4,700 proteins in prion infected and uninfected cells. As expected, the degradation rate of the prion protein is significantly decreased upon aggregation in infected cells. In contrast, the degradation kinetics of the remainder of the N2a proteome generally increases upon prion infection. This effect occurs concurrently with increases in the cellular activities of autophagy and some lysosomal hydrolases. The resulting enhancement in proteome flux may play a role in the survival of N2a cells upon prion infection.

Adipose Tissue-Liver Cross Talk in the Control of Whole-Body Metabolism: Implications in Nonalcoholic Fatty Liver Disease

Adipose tissue and the liver play significant roles in the regulation of whole-body energy homeostasis, but they have not evolved to cope with the continuous, chronic, nutrient surplus seen in obesity. In this review, we detail how prolonged metabolic stress leads to adipose tissue dysfunction, inflammation, and adipokine release that results in increased lipid flux to the liver. Overall, the upshot of hepatic fat accumulation alongside an insulin-resistant state is that hepatic lipid enzymatic pathways are modulated and overwhelmed, resulting in the selective buildup of toxic lipid species, which worsens the pro-inflammatory and pro-fibrotic shift observed in nonalcoholic steatohepatitis.

Protein Turnover in Epithelial Cells and Mucus along the Gastrointestinal Tract Is Coordinated by the Spatial Location and Microbiota

The gastrointestinal tract is covered by a single layer of epithelial cells that, together with the mucus layers, protect the underlying tissue from microbial invasion. The epithelium has one of the highest turnover rates in the body. Using stable isotope labeling, high-resolution mass spectrometry, and computational analysis, we report a comprehensive dataset of the turnover of more than 3,000 and the expression of more than 5,000 intestinal epithelial cell proteins, analyzed under conventional and germ-free conditions across five different segments in mouse intestine. The median protein half-life is shorter in the small intestine than in the colon. Differences in protein turnover rates along the intestinal tract can be explained by distinct physiological and immune-related functions between the small and large intestine. An absence of microbiota results in an approximately 1 day longer protein half-life in germ-free animals.

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Dataset of protein turnover rate and expression along the mice intestinal tract

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Protein turnover rate is slower in colon than in small intestine

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Median protein half-life is 1 day longer in germ-free mice

In Vivo Large-Scale Mapping of Protein Turnover in Human Cerebrospinal Fluid

The extraction of accurate physiological parameters from clinical samples provides a unique perspective to understand disease etiology and evolution, including under therapy. We introduce a new methodologic framework to map patient proteome dynamics in vivo, either proteome-wide or in large targeted panels. We applied it to ventricular cerebrospinal fluid (CSF) and could determine the turnover parameters of almost 200 proteins, whereas a handful were known previously. We covered a large number of neuron biology- and immune system-related proteins, including many biomarkers and drug targets. This first large data set unraveled a significant relationship between turnover and protein origin that relates to our ability to investigate organ physiology with protein-labeling strategy specifics. Our data constitute the first draft of CSF proteome dynamics as well as a repertoire of peptides for the community to design new analyses. The disclosed methods apply to other fluids or tissues provided sequential sample collection can be performed. We show that the proposed mathematical modeling applies to other analytical methods in the field.

Mass spectrometric analysis of PTM dynamics using stable isotope labeled metabolic precursors in cell culture

Biological organisms represent highly dynamic systems, which are continually exposed to environmental factors and always strive to restore steady-state homeostasis. Posttranslational modifications are key regulators with which biological systems respond to external stimuli. To understand how homeostasis is restored, it is important to study the kinetics of posttranslational modifications. In this review we discuss proteomic approaches using stable isotope labeled metabolic precursors to study dynamics of posttranslational modifications in cell culture.

A mass spectrometry workflow for measuring protein turnover rates in vivo

Proteins are continually produced and degraded, to avoid the accumulation of old or damaged molecules and to maintain the efficiency of physiological processes. Despite its importance, protein turnover has been difficult to measure in vivo. Previous approaches to evaluating turnover in vivo have required custom labeling approaches, involved complex mass spectrometry (MS) analyses, or used comparative strategies that do not allow direct quantitative measurements. Here, we describe a robust protocol for quantitative proteome turnover analysis in mice that is based on a commercially available diet for stable isotope labeling of amino acids in mammals (SILAM). We start by discussing fundamental concepts of protein turnover, including different methodological approaches. We then cover in detail the practical aspects of metabolic labeling and explain both the experimental and computational steps that must be taken to obtain accurate in vivo results. Finally, we present a simple experimental workflow that enables measurement of precise turnover rates in a time frame of ~4-5 weeks, including the labeling time. We also provide all the scripts needed for the interpretation of the MS results and for comparing turnover across different conditions. Overall, the workflow presented here comprises several improvements in the determination of protein lifetimes with respect to other available methods, including a minimally invasive labeling strategy and a robust interpretation of MS results, thus enhancing reproducibility across laboratories.

Proteome Dynamics from Heavy Water Metabolic Labeling and Peptide Tandem Mass Spectrometry

Protein homeostasis (proteostasis) is a result of a dynamic equilibrium between protein synthesis and degradation. It is important for healthy cell/organ functioning and is often associated with diseases such as neurodegenerative diseases and non-Alcoholic Fatty Liver disease. Heavy water metabolic labeling, combined with liquid-chromatography and mass spectrometry (LC-MS), is a powerful approach to study proteostasis in vivo in high throughput. Traditionally, intact peptide signals are used to estimate stable isotope incorporation in time-course experiments. The time-course of label incorporation is used to extract protein decay rate constant (DRC). Intact peptide signals, computed from integration in chromatographic time and mass-to-charge ratio (m/z) domains, usually, provide an accurate estimate of label incorporation. However, sample complexity (co-elution), limited dynamic range, and low signal-to-noise ratio (S/N) may adversely interfere with the peptide signals. These artifacts complicate the DRC estimations by distorting peak shape in chromatographic time and m/z domains. Fragment ions, on the other hand, are less prone to these artifacts and are potentially well suited in aiding DRC estimations. Here, we show that the label incorporation encoded into the isotope distributions of fragment ions reflect the isotope enrichment during the metabolic labeling with heavy water. We explore the label incorporation statistics for devising practical approaches for DRC estimations.

Improved Sensitivity for Protein Turnover Quantification by Monitoring Immonium Ion Isotopologue Abundance

We describe an analytical strategy allowing for the direct quantification of stable isotope label incorporation in newly synthesized proteins following administration of the stable isotope tracer deuterium oxide. We present a demonstration of coupling high-resolution mass spectrometry, metabolic stable isotope labeling, and MS/MS-based isotopologue quantification for the measurement of protein turnover. Stable isotope labeling with deuterium oxide, followed by immonium ion isotopologue quantification, is a more sensitive strategy for determining protein fractional synthesis rates compared to peptide centric mass isotopomer distribution analysis approaches when labeling time and/or stable isotope tracer exposure is limited and, as such, offers a great advantage for human studies.

Tandem Fluorescent Protein Timers for Noninvasive Relative Protein Lifetime Measurement in Plants

Targeted protein degradation is an important and pervasive regulatory mechanism in plants, required for perception and response to the environment as well as developmental signaling. Despite the significance of this process, relatively few studies have assessed plant protein turnover in a quantitative fashion. Tandem fluorescent protein timers (tFTs) offer a powerful approach for the assessment of in vivo protein turnover in distinct subcellular compartments of single or multiple cells. A tFT is a fusion of two different fluorescent proteins with distinct fluorophore maturation kinetics, which enable protein age to be estimated from the ratio of fluorescence intensities of the two fluorescent proteins. Here, we used short-lived auxin signaling proteins and model N-end rule (N-recognin) pathway reporters to demonstrate the utility of tFTs for studying protein turnover in living plant cells of Arabidopsis (Arabidopsis thaliana) and Nicotiana benthamiana We present transient expression of tFTs as an efficient screen for relative protein lifetime, useful for testing the effects of mutations and different genetic backgrounds on protein stability. This work demonstrates the potential for using stably expressed tFTs to study native protein dynamics with high temporal resolution in response to exogenous or endogenous stimuli.

Advanced proteomics approaches to unravel protein homeostasis

Quantitative proteomics methods are instrumental in measuring the interplay between protein synthesis and protein degradation in cells and tissues in different conditions and substantially contribute to the understanding of control mechanisms for protein homeostasis. Proteomics and chemoproteomics approaches enable the characterization of small molecule modifiers of protein degradation for therapeutic applications. Here, we review recent developments and applications of mass spectrometry-based (chemo-)proteomics methods for the study of cellular homeostasis.

Multi-omic measurements of heterogeneity in HeLa cells across laboratories

Reproducibility in research can be compromised by both biological and technical variation, but most of the focus is on removing the latter. Here we investigate the effects of biological variation in HeLa cell lines using a systems-wide approach. We determine the degree of molecular and phenotypic variability across 14 stock HeLa samples from 13 international laboratories. We cultured cells in uniform conditions and profiled genome-wide copy numbers, mRNAs, proteins and protein turnover rates in each cell line. We discovered substantial heterogeneity between HeLa variants, especially between lines of the CCL2 and Kyoto varieties, and observed progressive divergence within a specific cell line over 50 successive passages. Genomic variability has a complex, nonlinear effect on transcriptome, proteome and protein turnover profiles, and proteotype patterns explain the varying phenotypic response of different cell lines to Salmonella infection. These findings have implications for the interpretation and reproducibility of research results obtained from human cultured cells.

Protein Turnover in Aging and Longevity

Progressive loss of proteostasis is a hallmark of aging that is marked by declines in various components of proteostasis machinery, including: autophagy, ubiquitin-mediated degradation, protein synthesis, and others. While declines in proteostasis have historically been observed as changes in these processes, or as bulk changes in the proteome, recent advances in proteomic methodologies have enabled the comprehensive measurement of turnover directly at the level of individual proteins in vivo. These methods, which utilize a combination of stable-isotope labeling, mass spectrometry, and specialized software analysis, have now been applied to various studies of aging and longevity. Here we review the role of proteostasis in aging and longevity, with a focus on the proteomic methods available to conduct protein turnover in aging models and the insights these studies have provided thus far.

Increased Degradation Rates in the Components of the Mitochondrial Oxidative Phosphorylation Chain in the Cerebellum of Old Mice

Brain structures differ in the magnitude of age-related neuron loss with the cerebellum being more affected. An underlying cause could be an age-related decline in mitochondrial bioenergetics. Successful aging of mitochondria reflects a balanced turnover of proteins involved in mitochondrial biogenesis and mitophagy. Thus, an imbalance in mitochondrial turnover can contribute to the diminution of cellular function seen during aging. Mitochondrial biogenesis and mitophagy are mediated by a set of proteins including MFN1, MFN2, OPA1, DRP1, FIS1 as well as DMN1l and DNM1, all of which are required for mitochondrial fission. Using N15 labeling, we report that the turnover rates for DMN1l and FIS1 go in opposite directions in the cerebellum of 22-month-old C57BL6j mice as compared to 3-month-old mice. Previous studies have reported decreased turnover rates for the mitochondrial respiratory complexes of aged rodents. In contrast, we found increased turnover rates for mitochondrial proteins of the oxidative phosphorylation chain in the aged mice as compared to young mice. Furthermore, the turnover rate of the components that are most affected by aging –complex III components (ubiquinol cytochrome C oxidoreductase) and complex IV components (cytochrome C oxidase)– was significantly increased in the senescent cerebellum. However, the turnover rates of proteins involved in mitophagy (i.e., the proteasomal and lysosomal degradation of damaged mitochondria) were not significantly altered with age. Overall, our results suggest that an age-related imbalance in the turnover rates of proteins involved in mitochondrial biogenesis and mitophagy (DMN1l, FIS1) in conjunction with an age-related imbalance in the turnover rates of proteins of the complexes III and IV of the electron transfer chain, might impair cerebellar mitochondrial bioenergetics in old mice.

Systematic analysis of protein turnover in primary cells

A better understanding of proteostasis in health and disease requires robust methods to determine protein half-lives. Here we improve the precision and accuracy of peptide ion intensity-based quantification, enabling more accurate protein turnover determination in non-dividing cells by dynamic SILAC-based proteomics. This approach allows exact determination of protein half-lives ranging from 10 to >1000 h. We identified 4000-6000 proteins in several non-dividing cell types, corresponding to 9699 unique protein identifications over the entire data set. We observed similar protein half-lives in B-cells, natural killer cells and monocytes, whereas hepatocytes and mouse embryonic neurons show substantial differences. Our data set extends and statistically validates the previous observation that subunits of protein complexes tend to have coherent turnover. Moreover, analysis of different proteasome and nuclear pore complex assemblies suggests that their turnover rate is architecture dependent. These results illustrate that our approach allows investigating protein turnover and its implications in various cell types.

Cross-species Comparison of Proteome Turnover Kinetics

The constitutive process of protein turnover plays a key role in maintaining cellular homeostasis. Recent technological advances in mass spectrometry have enabled the measurement of protein turnover kinetics across the proteome. However, it is not known if turnover kinetics of individual proteins are highly conserved or if they have evolved to meet the physiological demands of individual species. Here, we conducted systematic analyses of proteome turnover kinetics in primary dermal fibroblasts isolated from eight different rodent species. Our results highlighted two trends in the variability of proteome turnover kinetics across species. First, we observed a decrease in cross-species correlation of protein degradation rates as a function of evolutionary distance. Second, we observed a negative correlation between global protein turnover rates and maximum lifespan of the species. We propose that by reducing the energetic demands of continuous protein turnover, long-lived species may have evolved to lessen the generation of reactive oxygen species and the corresponding oxidative damage over their extended lifespans.

Integrated omics dissection of proteome dynamics during cardiac remodeling

Transcript abundance and protein abundance show modest correlation in many biological models, but how this impacts disease signature discovery in omics experiments is rarely explored. Here we report an integrated omics approach, incorporating measurements of transcript abundance, protein abundance, and protein turnover to map the landscape of proteome remodeling in a mouse model of pathological cardiac hypertrophy. Analyzing the hypertrophy signatures that are reproducibly discovered from each omics data type across six genetic strains of mice, we find that the integration of transcript abundance, protein abundance, and protein turnover data leads to 75% gain in discovered disease gene candidates. Moreover, the inclusion of protein turnover measurements allows discovery of post-transcriptional regulations across diverse pathways, and implicates distinct disease proteins not found in steady-state transcript and protein abundance data. Our results suggest that multi-omics investigations of proteome dynamics provide important insights into disease pathogenesis in vivo.

Plasma Protein Turnover Rates in Rats Using Stable Isotope Labeling, Global Proteomics, and Activity-Based Protein Profiling

Protein turnover is important for general health on cellular and organism scales providing a strategy to replace old, damaged, or dysfunctional proteins. Protein turnover also informs of biomarker kinetics, as a better understanding of synthesis and degradation of proteins increases the clinical utility of biomarkers. Here, turnover rates of plasma proteins in rats were measured in vivo using a pulse-chase stable isotope labeling experiment. During the pulse, rats (n = 5) were fed ¹³C₆-labeled lysine ("heavy") feed for 23 days to label proteins. During the chase, feed was changed to an unlabeled equivalent feed ("light"), and blood was repeatedly sampled from rats over 10 time points for 28 days. Plasma samples were digested with trypsin and analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS). MaxQuant was used to identify peptides and proteins and quantify heavy/light lysine ratios. A system of ordinary differential equations was used to calculate protein turnover rates. Using this approach, 273 proteins were identified, and turnover rates were quantified for 157 plasma proteins with half-lives ranging 0.3-103 days. For the ∼70 most abundant proteins, variability in turnover rates among rats was low (median coefficient of variation: 0.09). Activity-based protein profiling was applied to pooled plasma samples to enrich serine hydrolases using a fluorophosphonate (FP2) activity-based probe. This enrichment resulted in turnover rates for an additional 17 proteins. This study is the first to measure global plasma protein turnover rates in rats in vivo, measure variability of protein turnover rates in any animal model, and utilize activity-based protein profiling for enhancing turnover measurements of targeted, low-abundant proteins, such as those commonly used as biomarkers. Measured protein turnover rates will be important for understanding of the role of protein turnover in cellular and organism health as well as increasing the utility of protein biomarkers through better understanding of processes governing biomarker kinetics.