Protein turnover on the scale of the proteome

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.

Quantitative serum proteome analysis using tandem mass tags in dogs with epilepsy

This study included four groups of dogs (group A: healthy controls, group B: idiopathic epilepsy receiving antiepileptic medication (AEM), group C: idiopathic epilepsy without AEM, group D: structural epilepsy). Comparative quantitative proteomic analysis of serum samples among the groups was the main target of the study. Samples were analyzed by a quantitative Tandem-Mass-Tags approach on the Q-Exactive-Plus Hybrid Quadrupole-Orbitrap mass-spectrometer. Identification and relative quantification were performed in Proteome Discoverer. Data were analyzed using R. Gene ontology terms were analyzed based on Canis lupus familiaris database. Data are available via ProteomeXchange with identifier PXD041129. Eighty-one proteins with different relative adundance were identified in the four groups and 25 were master proteins (p < 0.05). Clusterin (CLU), and apolipoprotein A1 (APOA1) had higher abundance in the three groups of dogs (groups B, C, D) compared to controls. Amine oxidase (AOC3) was higher in abundance in group B compared to groups C and D, and lower in group A. Adiponectin (ADIPOQ) had higher abundance in groups C compared to group A. ADIPOQ and fibronectin (FN1) had higher abundance in group B compared to group C and D. Peroxidase activity assay was used to quantify HP abundance change, validating and correlating with proteomic analysis (r = 0.8796). SIGNIFICANCE: The proteomic analysis of serum samples from epileptic dogs indicated potential markers of epilepsy (CLU), proteins that may contribute to nerve tissue regeneration (APOA1), and contributing factors to epileptogenesis (AOC3). AEM could alter extracellular matrix proteins (FN1). Illness (epilepsy) severity could influence ADIPOQ abundance.

Impact of biological sex and sex hormones on molecular signatures of skeletal muscle at rest and in response to distinct exercise training modes

Substantial divergence in cardio-metabolic risk, muscle size, and performance exists between men and women. Considering the pivotal role of skeletal muscle in human physiology, we investigated and found, based on RNA sequencing (RNA-seq), that differences in the muscle transcriptome between men and women are largely related to testosterone and estradiol and much less related to genes located on the Y chromosome. We demonstrate inherent unique, sex-dependent differences in muscle transcriptional responses to aerobic, resistance, and combined exercise training in young and older cohorts. The hormonal changes with age likely explain age-related differential expression of transcripts. Furthermore, in primary human myotubes we demonstrate the profound but distinct effects of testosterone and estradiol on amino acid incorporation to multiple individual proteins with specific functions. These results clearly highlight the potential of designing exercise programs tailored specifically to men and women and have implications for people who change gender by altering their hormone profile.

Global Proteomics for Identifying the Alteration Pathway of Niemann-Pick Disease Type C Using Hepatic Cell Models

Niemann-Pick disease type C (NPC) is an autosomal recessive disorder with progressive neurodegeneration. Although the causative genes were previously identified, NPC has unclear pathophysiological aspects, and patients with NPC present various symptoms and onset ages. However, various novel biomarkers and metabolic alterations have been investigated; at present, few comprehensive proteomic alterations have been reported in relation to NPC. In this study, we aimed to elucidate proteomic alterations in NPC and perform a global proteomics analysis for NPC model cells. First, we developed two NPC cell models by knocking out NPC1 using CRISPR/Cas9 (KO1 and KO2). Second, we performed a label-free (LF) global proteomics analysis. Using the LF approach, more than 300 proteins, defined as differentially expressed proteins (DEPs), changed in the KO1 and/or KO2 cells, while the two models shared 35 DEPs. As a bioinformatics analysis, the construction of a protein-protein interaction (PPI) network and an enrichment analysis showed that common characteristic pathways such as ferroptosis and mitophagy were identified in the two model cells. There are few reports of the involvement of NPC in ferroptosis, and this study presents ferroptosis as an altered pathway in NPC. On the other hand, many other pathways and DEPs were previously suggested to be associated with NPC, supporting the link between the proteome analyzed here and NPC. Therapeutic research based on these results is expected in the future.

A novel dynamic proteomics approach for the measurement of broiler chicken protein fractional synthesis rate

RATIONALE

The study of protein synthesis in farm animals is uncommon despite its potential to increase knowledge about metabolism and discover new biomarkers of health and growth status. The present study describes a novel dynamic proteomics approach for the measurement of protein fractional synthesis rate (FSR) in broiler chickens.

METHODS

Chickens received a 10 g/kg oral dose of ² H₂ O at day 21 of their life. Body water ² H abundance was measured in plasma samples using a portable Fourier transform infrared spectrometer. Free and protein-bound amino acids (AAs) were isolated and had their ² H enrichment measured by gas chromatography with mass spectrometry (GC/MS). Peptide ² H enrichment was measured by proteomics analysis of plasma and muscle samples. Albumin, fibrinogen and muscle protein FSR were calculated from GC/MS and proteomics data.

RESULTS

Ala appeared to be more enriched at the site of protein synthesis than in the AA free pools. Glu was found to be the AA closest to isotopic equilibrium between the different AA pools. Glu was used as an anchor to calculate n(AA) values necessary for chicken protein FSR calculation in dynamic proteomics studies. FSR values calculated using proteomics data and GC/MS data showed good agreement as evidenced by a Bland-Altman residual plot.

CONCLUSIONS

A new dynamic proteomics approach for the measurement of broiler chicken individual protein FSR based on the administration of a single ² H₂ O oral bolus has been developed and validated. The proposed approach could facilitate new immunological and nutritional studies on free-living animals.

Profiling of Secreted Proteins in Serum-Containing Media Using BONCAT and Pulsed SILAC

Secreted proteins play pivotal roles in signal transduction and cell-to-cell communication. Despite increasing interest in secretome analysis over the past decade, most studies on this topic have utilized serum-free medium (SFM). However, fetal bovine serum (FBS) is the most widely used serum supplement for cell culture, and secretome analysis using serum-containing medium (SCM) is important to identify proteins secreted under realistic conditions and to understand their physiological roles. In this chapter, we describe a simple and robust protocol based on bioorthogonal non-canonical amino acid tagging (BONCAT) and pulsed stable isotope labeling by amino acids in cell culture (pSILAC), for identification and quantitation of the cell secretome in SCM. In this protocol, the secretome of SFM is compared with that of SCM to confirm the effect of FBS. Additionally, for mass spectrometric data processing, we provide parameters that increase true positives and decrease both false positives and false negatives.

PROTACs: Current Trends in Protein Degradation by Proteolysis-Targeting Chimeras

In the recent past, proteolysis-targeting chimera (PROTAC) technology has received enormous attention for its ability to overcome the limitations of protein inhibitors and its capability to target undruggable proteins. The PROTAC molecule consists of three components, a ubiquitin E3 ligase ligand, a linker, and a target protein ligand. The application of this technology is rapidly gaining momentum, especially in cancer therapy. In this review, we first look at the history of degraders, followed by a section on the ubiquitin proteasome system (UPS) and E3 ligases used in PROTAC development. PROTACs are dependent on the UPS for degradation of target proteins. We further discuss the scope and design of degraders and mitigation strategies for overcoming the hook effect seen with degraders. As PROTACs do not follow Lipinski's 'Rule of 5', these molecules face drug metabolism and pharmacokinetic challenges. A detailed section on absorption, distribution, metabolism, and excretion of degraders is provided wherein we discuss methodologies and strategies to surmount the challenges faced by these molecules. For understanding PROTAC-mediated degradation, the characterization and measurement of protein levels in cells is important. Currently used techniques and recent advancements in assessment tools for degraders are discussed. Furthermore, we examine the challenges and emerging technologies that need to be focused on in order to competently develop potent degraders. Many companies are working in this area of emerging new modality and a few PROTACs have already entered clinical trials; the details of the trials are included in this review.

Advances in stable isotope labeling: dynamic labeling for spatial and temporal proteomic analysis

The field of proteomics is continually improving, requiring the development of new quantitative methods. Stable isotope labeling in cell culture (SILAC) is a metabolic labeling technique originating in the early 2000s. By incorporating isotopically labeled amino acids into the media used for cell culture, unlabeled versus labeled cells can be differentiated by the mass spectrometer. Traditional SILAC labeling has been expanded to pulsed applications allowing for a new quantitative dimension of proteomics - temporal analysis. The complete introduction of Heavy SILAC labeling chased with surplus unlabeled medium mimics traditional pulse-chase experiments and allows for the loss of heavy signal to track proteomic changes over time. In a similar fashion, pulsed SILAC (pSILAC) monitors the initial incorporation of a heavy label across a period of time, which allows for the rate of protein label integration to be assessed. These innovative techniques have aided in inspiring numerous SILAC-based temporal and spatial labeling applications, including super SILAC, spike-in SILAC, spatial SILAC, and a revival in label multiplexing. This review reflects upon the evolution of SILAC and the pulsed SILAC application, introduces advances in SILAC labeling, and proposes future perspectives for this novel and exciting field.

Proteome Turnover Analysis in Haloferax volcanii by a Heavy Isotope Multilabeling Approach

The cellular protein repertoire is highly dynamic and responsive to internal or external stimuli. Its changes are largely the consequence of the combination of protein synthesis and degradation, referred collectively as protein turnover. Different proteomics techniques have been developed to determine the whole proteome turnover of a cell, but very few have been applied to archaea. In this chapter we describe a heavy isotope multilabeling method that allowed the successful analysis of relative protein synthesis and degradation rates on the proteome scale of the halophilic archaeon Haloferax volcanii. This method combines ¹⁵N and ¹³C isotope metabolic labeling with high-resolution mass spectrometry and data analysis tools (QuPE web-based platform) and could be applied to different archaea.

JUMPt: Comprehensive Protein Turnover Modeling of In Vivo Pulse SILAC Data by Ordinary Differential Equations

Recent advances in mass spectrometry (MS)-based proteomics allow the measurement of turnover rates of thousands of proteins using dynamic labeling methods, such as pulse stable isotope labeling by amino acids in cell culture (pSILAC). However, when applying the pSILAC strategy to multicellular animals (e.g., mice), the labeling process is significantly delayed by native amino acids recycled from protein degradation in vivo, raising a challenge of defining accurate protein turnover rates. Here, we report JUMPt, a software package using a novel ordinary differential equation (ODE)-based mathematical model to determine reliable rates of protein degradation. The uniqueness of JUMPt is to consider amino acid recycling and fit the kinetics of the labeling amino acid (e.g., Lys) and whole proteome simultaneously to derive half-lives of individual proteins. Multiple settings in the software are designed to enable simple to comprehensive data inputs for precise analysis of half-lives with flexibility. We examined the software by studying the turnover of thousands of proteins in the pSILAC brain and liver tissues. The results were largely consistent with the proteome turnover measurements from previous studies. The long-lived proteins are enriched in the integral membrane, myelin sheath, and mitochondrion in the brain. In summary, the ODE-based JUMPt software is an effective proteomics tool for analyzing large-scale protein turnover, and the software is publicly available on GitHub (https://github.com/JUMPSuite/JUMPt) to the research community.

Using protein turnover to expand the applications of transcriptomics

RNA expression and protein abundance are often at odds when measured in parallel, raising questions about the functional implications of transcriptomics data. Here, we present the concept of persistence, which attempts to address this challenge by combining protein half-life data with RNA expression into a single metric that approximates protein abundance. The longer a protein's half-life, the more influence it can have on its surroundings. This data offers a valuable opportunity to gain deeper insight into the functional meaning of transcriptome changes. We demonstrate the application of persistence using schizophrenia (SCZ) datasets, where it greatly improved our ability to predict protein abundance from RNA expression. Furthermore, this approach successfully identified persistent genes and pathways known to have impactful changes in SCZ. These results suggest that persistence is a valuable metric for improving the functional insight offered by transcriptomics data, and extended application of this concept could advance numerous research fields.

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.

The effects of IFITM1 and IFITM3 gene deletion on IFNγ stimulated protein synthesis

Interferon-induced transmembrane proteins IFITM1 and IFITM3 (IFITM1/3) play a role in both RNA viral restriction and in human cancer progression. Using immunohistochemical staining of FFPE tissue, we identified subgroups of cervical cancer patients where IFITM1/3 protein expression is inversely related to metastasis. Guide RNA-CAS9 methods were used to develop an isogenic IFITM1/IFITM3 double null cervical cancer model in order to define dominant pathways triggered by presence or absence of IFITM1/3 signalling. A pulse SILAC methodology identified IRF1, HLA-B, and ISG15 as the most dominating IFNγ inducible proteins whose synthesis was attenuated in the IFITM1/IFITM3 double-null cells. Conversely, SWATH-IP mass spectrometry of ectopically expressed SBP-tagged IFITM1 identified ISG15 and HLA-B as dominant co-associated proteins. ISG15ylation was attenuated in IFNγ treated IFITM1/IFITM3 double-null cells. Proximity ligation assays indicated that HLA-B can interact with IFITM1/3 proteins in parental SiHa cells. Cell surface expression of HLA-B was attenuated in IFNγ treated IFITM1/IFITM3 double-null cells. SWATH-MS proteomic screens in cells treated with IFITM1-targeted siRNA cells resulted in the attenuation of an interferon regulated protein subpopulation including MHC Class I molecules as well as IFITM3, STAT1, B2M, and ISG15. These data have implications for the function of IFITM1/3 in mediating IFNγ stimulated protein synthesis including ISG15ylation and MHC Class I production in cancer cells. The data together suggest that pro-metastatic growth associated with IFITM1/3 negative cervical cancers relates to attenuated expression of MHC Class I molecules that would support tumor immune escape.

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IFITM1/3 expression in cervical cancers inversely correlates with metastases.

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Isogenic IFITM1 and IFITM3 null cervical cancer cells were developed.

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Pulse SILAC approaches were used to define IFITM1/3 dependent signalling pathways.

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The major IFITM1/3-interferon-γ dependent effectors are HLA-B and ISG15.

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IFITM1/3 loss would be predicted to reduce HLA expression and ISG15ylation in vivo.

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.

Secretome Dynamics in a Gram-Positive Bacterial Model

Protein secretion is a central biological process in all organisms. Most studies dissecting bacterial secretion mechanisms have focused on Gram-negative cell envelopes such as that of Escherichia coli However, proteomics analyses in Gram negatives is hampered by their outer membrane. Here we studied protein secretion in the Gram-positive bacterium Streptomyces lividans TK24, in which most of the secretome is released in the growth medium. We monitored changes of the secretome as a function of growth phase and medium. We determined distinct protein classes of "house-keeping" secreted proteins that do not change their appearance or abundance in the various media and growth phases. These comprise mainly enzymes involved in cell wall maintenance and basic transport. In addition, we detected significant abundance and content changes to a sub-set of the proteome, as a function of growth in the different media. These did not depend on the media being minimal or rich. Transcriptional regulation but not changes in export machinery components can explain some of these changes. However, additional downstream mechanisms must be important for selective secretome funneling. These observations lay the foundations of using S. lividans as a model organism to study how metabolism is linked to optimal secretion and help develop rational optimization of heterologous protein production.

Comparative analysis of differentially secreted proteins in serum-free and serum-containing media by using BONCAT and pulsed SILAC

Despite the increased interest in secretomes associated with paracrine/autocrine mechanisms, the majority of mass spectrometric cell secretome studies have been performed using serum-free medium (SFM). On the other hand, serum-containing medium (SCM) is not recommended very much because the secretome obtained with SCM is easily contaminated with fetal bovine serum (FBS) proteins. In this study, through the combination of bioorthogonal non-canonical amino acid tagging (BONCAT) and pulsed-SILAC (pSILAC), we analyzed differentially secreted proteins between SFM and SCM in a cancer-derived human cell, U87MG, and a mesenchymal stem cell derived from human Wharton’s jelly (hWJ-MSCs). In most cases, the bioinformatic tools predicted a protein to be truly secretory when the secretion level of the protein was more in SCM than in SFM. In the case of hWJ-MSCs, the amount of proteins secreted in SCM for 24 hours was larger than that of SFM (log₂ fold change = 0.96), even considering different cell proliferation rates. hWJ-MSCs proteins secreted more in SCM included several positive markers of MSC paracrine factors implicated in angiogenesis, neurogenesis and osteogenesis, and upstream regulators of cell proliferation. Our study suggests the analysis of the secretome should be processed in SCM that promotes cell proliferation and secretion.

Gene Regulatory Network Inference from Perturbed Time-Series Expression Data via Ordered Dynamical Expansion of Non-Steady State Actors

The reconstruction of gene regulatory networks from gene expression data has been the subject of intense research activity. A variety of models and methods have been developed to address different aspects of this important problem. However, these techniques are narrowly focused on particular biological and experimental platforms, and require experimental data that are typically unavailable and difficult to ascertain. The more recent availability of higher-throughput sequencing platforms, combined with more precise modes of genetic perturbation, presents an opportunity to formulate more robust and comprehensive approaches to gene network inference. Here, we propose a step-wise framework for identifying gene-gene regulatory interactions that expand from a known point of genetic or chemical perturbation using time series gene expression data. This novel approach sequentially identifies non-steady state genes post-perturbation and incorporates them into a growing series of low-complexity optimization problems. The governing ordinary differential equations of this model are rooted in the biophysics of stochastic molecular events that underlie gene regulation, delineating roles for both protein and RNA-mediated gene regulation. We show the successful application of our core algorithms for network inference using simulated and real datasets.

Incompatibility of chemical protein synthesis inhibitors with accurate measurement of extended protein degradation rates

Protein synthesis inhibitors are commonly used for measuring protein degradation rates, but may cause cytotoxicity via direct or indirect mechanisms. This study aimed to identify concentrations providing optimal inhibition in the absence of overt cytotoxicity. Actinomycin D, cycloheximide, emetine, and puromycin were assessed individually, and in two-, three-, and four-drug combinations for protein synthesis inhibition (IC₅₀ ) and cytotoxicity (CC₅₀ ) over 72 h. Experiments were conducted in HepG2 cells and primary rat hepatocytes (PRH). IC₅₀ for actinomycin D, cycloheximide, emetine, and puromycin were 39 ± 7.4, 6600 ± 2500, 2200 ± 1400, and 1600 ± 1200 nmol/L; with corresponding CC₅₀ values of 6.2 ± 7.3, 570 ± 510, 81 ± 9, and 1300 ± 64 nmol/L, respectively, in HepG2 cells. The IC₅₀ were 1.7 ± 1.8, 290 ± 90, 620 ± 920, and 2000 ± 2000 nmol/L, with corresponding CC₅₀ values of 0.98 ± 1.8, 680 ± 1300, 180 ± 700, and 1600 ± 1000 (SD) nmol/L, respectively, in PRH. CC₅₀ were also lower than the IC₅₀ for all drug combinations in HepG2 cells. These data indicate that using pharmacological interference is inappropriate for measuring protein degradation over a protracted period, because inhibitory effects cannot be extricated from cytotoxicity.

Exploring ribosome composition and newly synthesized proteins through proteomics and potential biomedical applications

INTRODUCTION

Protein synthesis is the outcome of tightly regulated gene expression which is responsive to a variety of conditions. Efforts are ongoing to monitor individual stages of protein synthesis to ensure maximum efficiency and accuracy. Due to post-transcriptional regulation mechanisms, the correlation between translatome and proteome is higher than between transcriptome and proteome. However, the most accurate approach to assess the key modulators and final protein expression is directly by using proteomics. Areas covered: This review covers various proteomic strategies that were used to better understand post-transcriptional regulation, specifically during and early after translation. The methods that identify both regulatory proteins associated with translational components and newly synthesized proteins are discussed. Expert commentary: Emerging proteomic approaches make it possible to monitor protein dynamics in cells, tissues and whole animals. The ability to detect alteration in protein abundance soon after their synthesis enables earlier recognition of disease causing factors and candidates to prevent/rectify disease phenotype.

Degradation of protein translation machinery by amino acid starvation-induced macroautophagy

Macroautophagy is regarded as a nonspecific bulk degradation process of cytoplasmic material within the lysosome. However, the process has mainly been studied by nonspecific bulk degradation assays using radiolabeling. In the present study we monitor protein turnover and degradation by global, unbiased approaches relying on quantitative mass spectrometry-based proteomics. Macroautophagy is induced by rapamycin treatment, and by amino acid and glucose starvation in differentially, metabolically labeled cells. Protein dynamics are linked to image-based models of autophagosome turnover. Depending on the inducing stimulus, protein as well as organelle turnover differ. Amino acid starvation-induced macroautophagy leads to selective degradation of proteins important for protein translation. Thus, protein dynamics reflect cellular conditions in the respective treatment indicating stimulus-specific pathways in stress-induced macroautophagy.

Identification of syntrophic acetate-oxidizing bacteria in anaerobic digesters by combined protein-based stable isotope probing and metagenomics

Inhibition of anaerobic digestion through accumulation of volatile fatty acids occasionally occurs as the result of unbalanced growth between acidogenic bacteria and methanogens. A fast recovery is a prerequisite for establishing an economical production of biogas. However, very little is known about the microorganisms facilitating this recovery. In this study, we investigated the organisms involved by a novel approach of mapping protein-stable isotope probing (protein-SIP) onto a binned metagenome. Under simulation of acetate accumulation conditions, formations of (13)C-labeled CO2 and CH4 were detected immediately following incubation with [U-(13)C]acetate, indicating high turnover rate of acetate. The identified (13)C-labeled peptides were mapped onto a binned metagenome for improved identification of the organisms involved. The results revealed that Methanosarcina and Methanoculleus were actively involved in acetate turnover, as were five subspecies of Clostridia. The acetate-consuming organisms affiliating with Clostridia all contained the FTFHS gene for formyltetrahydrofolate synthetase, a key enzyme for reductive acetogenesis, indicating that these organisms are possible syntrophic acetate-oxidizing (SAO) bacteria that can facilitate acetate consumption via SAO, coupled with hydrogenotrophic methanogenesis (SAO-HM). This study represents the first study applying protein-SIP for analysis of complex biogas samples, a promising method for identifying key microorganisms utilizing specific pathways.

Proteome Dynamics: Tissue Variation in the Kinetics of Proteostasis in Intact Animals

Understanding the role of protein turnover in the maintenance of proteostasis requires accurate measurements of the rates of replacement of proteins in complex systems, such as intact animals. Moreover, any investigation of allometric scaling of protein turnover is likely to include species for which fully annotated proteomes are not available. We have used dietary administration of stable isotope labeled lysine to assess protein turnover rates for proteins from four tissues in the bank vole, Myodes glareolus. The annotated genome for this species is not available, so protein identification was attained through cross-species matching to the mouse. For proteins for which confident identifications were derived, the pattern of lysine incorporation over 40 days was used to define the rate of synthesis of individual proteins in the four tissues. The data were heavily filtered to retain a very high quality dataset of turnover rates for 1088 proteins. Comparative analysis of the four tissues revealed different median rates of degradation (kidney: 0.099 days⁻¹; liver 0.136 days⁻¹; heart, 0.054 days⁻¹, and skeletal muscle, 0.035 days⁻¹). These data were compared with protein degradation rates from other studies on intact animals or from cells in culture and indicate that both cell type and analytical methodology may contribute to variance in turnover data between different studies. These differences were not only due to tissue-specific proteins but were reflected in gene products common to all tissues. All data are available via ProteomeXchange with identifier PXD002054.

Proteome Scale-Protein Turnover Analysis Using High Resolution Mass Spectrometric Data from Stable-Isotope Labeled Plants

Protein turnover is an important aspect of the regulation of cellular processes for organisms when responding to developmental or environmental cues. The measurement of protein turnover in plants, in contrast to that of rapidly growing unicellular organismal cultures, is made more complicated by the high degree of amino acid recycling, resulting in significant transient isotope incorporation distributions that must be dealt with computationally for high throughput analysis to be practical. An algorithm in R, ProteinTurnover, was developed to calculate protein turnover with transient stable isotope incorporation distributions in a high throughput automated manner using high resolution MS and MS/MS proteomic analysis of stable isotopically labeled plant material. ProteinTurnover extracts isotopic distribution information from raw MS data for peptides identified by MS/MS from data sets of either isotopic label dilution or incorporation experiments. Variable isotopic incorporation distributions were modeled using binomial and beta-binomial distributions to deconvolute the natural abundance, newly synthesized/partial-labeled, and fully labeled peptide distributions. Maximum likelihood estimation was performed to calculate the distribution abundance proportion of old and newly synthesized peptides. The half-life or turnover rate of each peptide was calculated from changes in the distribution abundance proportions using nonlinear regression. We applied ProteinTurnover to obtain half-lives of proteins from enriched soluble and membrane fractions from Arabidopsis roots.

Protein turnover during in vitro tissue engineering

Repopulating acellular biological scaffolds with phenotypically appropriate cells is a promising approach for regenerating functional tissues and organs. Under this tissue engineering paradigm, reseeded cells are expected to remodel the scaffold by active protein synthesis and degradation; however, the rate and extent of this remodeling remain largely unknown. Here, we present a technique to measure dynamic proteome changes during in vitro remodeling of decellularized tissue by reseeded cells, using vocal fold mucosa as the model system. Decellularization and recellularization were optimized, and a stable isotope labeling strategy was developed to differentiate remnant proteins constituting the original scaffold from proteins newly synthesized by reseeded cells. Turnover of matrix and cellular proteins and the effects of cell-scaffold interaction were elucidated. This technique sheds new light on in vitro tissue remodeling and the process of tissue regeneration, and is readily applicable to other tissue and organ systems.

The role of proteomics in studies of protein moonlighting

The increasing acceptance that proteins may exert multiple functions in the cell brings with it new analytical challenges that will have an impact on the field of proteomics. Many proteomics workflows begin by destroying information about the interactions between different proteins, and the reduction of a complex protein mixture to constituent peptides also scrambles information about the combinatorial potential of post-translational modifications. To bring the focus of proteomics on to the domain of protein moonlighting will require novel analytical and quantitative approaches.

Elements of the cellular metabolic structure

A large number of studies have demonstrated the existence of metabolic covalent modifications in different molecular structures, which are able to store biochemical information that is not encoded by DNA. Some of these covalent mark patterns can be transmitted across generations (epigenetic changes). Recently, the emergence of Hopfield-like attractor dynamics has been observed in self-organized enzymatic networks, which have the capacity to store functional catalytic patterns that can be correctly recovered by specific input stimuli. Hopfield-like metabolic dynamics are stable and can be maintained as a long-term biochemical memory. In addition, specific molecular information can be transferred from the functional dynamics of the metabolic networks to the enzymatic activity involved in covalent post-translational modulation, so that determined functional memory can be embedded in multiple stable molecular marks. The metabolic dynamics governed by Hopfield-type attractors (functional processes), as well as the enzymatic covalent modifications of specific molecules (structural dynamic processes) seem to represent the two stages of the dynamical memory of cellular metabolism (metabolic memory). Epigenetic processes appear to be the structural manifestation of this cellular metabolic memory. Here, a new framework for molecular information storage in the cell is presented, which is characterized by two functionally and molecularly interrelated systems: a dynamic, flexible and adaptive system (metabolic memory) and an essentially conservative system (genetic memory). The molecular information of both systems seems to coordinate the physiological development of the whole cell.

Protein kinetic signatures of the remodeling heart following isoproterenol stimulation

Protein temporal dynamics play a critical role in time-dimensional pathophysiological processes, including the gradual cardiac remodeling that occurs in early-stage heart failure. Methods for quantitative assessments of protein kinetics are lacking, and despite knowledge gained from single-protein studies, integrative views of the coordinated behavior of multiple proteins in cardiac remodeling are scarce. Here, we developed a workflow that integrates deuterium oxide (2H2O) labeling, high-resolution mass spectrometry (MS), and custom computational methods to systematically interrogate in vivo protein turnover. Using this workflow, we characterized the in vivo turnover kinetics of 2,964 proteins in a mouse model of β-adrenergic-induced cardiac remodeling. The data provided a quantitative and longitudinal view of cardiac remodeling at the molecular level, revealing widespread kinetic regulations in calcium signaling, metabolism, proteostasis, and mitochondrial dynamics. We translated the workflow to human studies, creating a reference dataset of 496 plasma protein turnover rates from 4 healthy adults. The approach is applicable to short, minimal label enrichment and can be performed on as little as a single biopsy, thereby overcoming critical obstacles to clinical investigations. The protein turnover quantitation experiments and computational workflow described here should be widely applicable to large-scale biomolecular investigations of human disease mechanisms with a temporal perspective.

Metabolic labeling with stable isotope nitrogen (15N) to follow amino acid and protein turnover of three plastid proteins in Chlamydomonas reinhardtii

BACKGROUND

The length of time that a protein remains available to perform its function is significantly influenced by its turnover rate. Knowing the turnover rate of proteins involved in different processes is important to determining how long a function might progress even when the stimulus has been removed and no further synthesis of the particular proteins occurs. In this article, we describe the use of 15N-metabolic labeling coupled to GC-MS to follow the turnover of free amino acids and LC-MS/MS to identify and LC-MS to follow the turnover of specific proteins in Chlamydomonas reinhardtii.

RESULTS

To achieve the metabolic labeling, the growth medium was formulated with standard Tris acetate phosphate medium (TAP) in which14NH4Cl was replaced with 15NH415NO3 and (14NH4)6Mo7O24.4H2O was replaced with Na2MoO4.2H2O. This medium designated 15N-TAP allowed CC-125 algal cells to grow normally. Mass isotopic distribution revealed successful 15N incorporation into 13 amino acids with approximately 98% labeling efficiency. Tryptic digestion of the 55 kDa SDS-PAGE bands from 14N- and 15N-labeled crude algal protein extracts followed by LC-MS/MS resulted in the identification of 27 proteins. Of these, five displayed peptide sequence confidence levels greater than 95% and protein sequence coverage greater than 25%. These proteins were the RuBisCo large subunit, ATP synthase CF1 alpha and beta subunits, the mitochondrial protein (F1F0 ATP synthase) and the cytosolic protein (S-adenosyl homocysteine hydroxylase). These proteins were present in both labeled and unlabeled samples. Once the newly synthesized 15N-labeled free amino acids and proteins obtained maximum incorporation of the 15N-label, turnover rates were determined after transfer of cells into 14N-TAP medium. The t½ values were determined for the three plastid proteins (RuBisCo, ATP synthase CF1 alpha and beta) by following the reduction of the 15N-fractional abundance over time.

CONCLUSION

We describe a more rapid and non-radioactive method to measure free amino acid and protein turnover. Our approach is applicable for determination of protein turnover for various proteins, which will lead to a better understanding of the relationship between protein lifetime and functionality.

Proteomic approach to aging research

The scope of the current paper is to review existing and potential applications of proteomic analysis to aging research. The focus will lie on the unique opportunities of high-throughput studies for uncovering specific alterations in protein expression, protein complexes or protein modifications caused by biological aging. The result of such studies will outline aging phenotypes and potentially indicate pathways involved in the pathogenesis of age-associated disfunctions. Specific attention is paid to the illustrations of successful applications of proteomic technologies and potential applications of new proteomic concepts to biogerontological studies.

Rapid temporal dynamics of transcription, protein synthesis, and secretion during macrophage activation

Macrophages provide the first line of host defense with their capacity to react to an array of cytokines and bacterial components requiring tight regulation of protein expression and secretion to invoke a properly tuned innate immune response. To capture the dynamics of this system, we introduce a novel method combining pulsed stable isotope labeling with amino acids in cell culture (SILAC) with pulse labeling using the methionine analog azidohomoalanine that allows the enrichment of newly synthesized proteins via click-chemistry followed by their identification and quantification by mass spectrometry. We show that this permits the analysis of proteome changes on a rapid time scale, as evidenced by the detection of 4852 newly synthesized proteins after only a 20-min SILAC pulse. We have applied this methodology to study proteome response during macrophage activation in a time-course manner. We have combined this with full proteome, transcriptome, and secretome analyses, producing an integrative analysis of the first 3 h of lipopolysaccharide-induced macrophage activation. We observed the rapid induction of multiple processes well known to TLR4 signaling, as well as anti-inflammatory proteins and proteins not previously associated with immune response. By correlating transcriptional, translational, and secretory events, we derived novel mechanistic principles of processes specifically induced by lipopolysaccharides, including ectodomain shedding and proteolytic processing of transmembrane and extracellular proteins and protein secretion independent of transcription. In conclusion, we demonstrate that the combination of pulsed azidohomoalanine and pulsed SILAC permits the detailed characterization of proteomic events on a rapid time scale. We anticipate that this approach will be very useful in probing the immediate effects of cellular stimuli and will provide mechanistic insight into cellular perturbation in multiple biological systems. The data have been deposited in ProteomeXchange with the identifier PXD000600.

Analysis of individual protein turnover in live animals on a proteome-wide scale

Classical quantitative proteomics studies focus on the relative or absolute concentration of proteins at a given time. In contrast, the investigation of protein turnover reveals the dynamics leading to these states. Analyzing the balance between synthesis and degradation of individual proteins provides insights into the regulation of protein concentration and helps understanding underlying biological processes. Comparing the half-lives of proteins allows detecting functional relationships and common regulation mechanisms. Moreover, comparing turnover of individual brain and plasma proteins between control- and treatment-groups indicates turnover changes induced by the treatment.Here, we describe a procedure for determining turnover information of individual proteins in mice on a proteome-wide scale based on partial (15)N metabolic labeling. We will outline the complete experimental workflow starting from (15)N labeling the animals over sample preparation and mass spectrometric measurement up to the analysis of the data.

Proteome turnover in bacteria: current status for Corynebacterium glutamicum and related bacteria

With the advent of high-resolution mass spectrometry together with sophisticated data analysis and interpretation algorithms, determination of protein synthesis and degradation rates (i.e. protein turnover) on a proteome-wide scale by employing stable isotope-labelled amino acids has become feasible. These dynamic data provide a deeper understanding of protein homeostasis and stress response mechanisms in microorganisms than well-established ‘steady state’ proteomics approaches. In this article, we summarize the technological challenges and solutions both on the biochemistry/mass spectrometry and bioinformatics level for turnover proteomics with a focus on chromatographic techniques. Although the number of available case studies for Corynebacterium glutamicum and related actinobacteria is still very limited, our review illustrates the potential of protein turnover studies for an improved understanding of questions in the area of biotechnology and biomedicine. Here, new insights from investigations of growth phase transition and different stress dynamics including iron, acid and heat stress for pathogenic but also for industrial actinobacteria are presented. Finally, we will comment on the advantages of integrated software solutions for biologists and briefly discuss the remaining technical challenges and upcoming possibilities for protein turnover analysis.

Proteome dynamics: revisiting turnover with a global perspective

Although bulk protein turnover has been measured with the use of stable isotope labeled tracers for over half a century, it is only recently that the same approach has become applicable to the level of the proteome, permitting analysis of the turnover of many proteins instead of single proteins or an aggregated protein pool. The optimal experimental design for turnover studies is dependent on the nature of the biological system under study, which dictates the choice of precursor label, protein pool sampling strategy, and treatment of data. In this review we discuss different approaches and, in particular, explore how complexity in experimental design and data processing increases as we shift from unicellular to multicellular systems, in particular animals.

Transcriptome and proteome dynamics of a light-dark synchronized bacterial cell cycle

BACKGROUND

Growth of the ocean's most abundant primary producer, the cyanobacterium Prochlorococcus, is tightly synchronized to the natural 24-hour light-dark cycle. We sought to quantify the relationship between transcriptome and proteome dynamics that underlie this obligate photoautotroph's highly choreographed response to the daily oscillation in energy supply.

METHODOLOGY/PRINCIPAL FINDINGS

Using RNA-sequencing transcriptomics and mass spectrometry-based quantitative proteomics, we measured timecourses of paired mRNA-protein abundances for 312 genes every 2 hours over a light-dark cycle. These temporal expression patterns reveal strong oscillations in transcript abundance that are broadly damped at the protein level, with mRNA levels varying on average 2.3 times more than the corresponding protein. The single strongest observed protein-level oscillation is in a ribonucleotide reductase, which may reflect a defense strategy against phage infection. The peak in abundance of most proteins also lags that of their transcript by 2-8 hours, and the two are completely antiphase for some genes. While abundant antisense RNA was detected, it apparently does not account for the observed divergences between expression levels. The redirection of flux through central carbon metabolism from daytime carbon fixation to nighttime respiration is associated with quite small changes in relative enzyme abundances.

CONCLUSIONS/SIGNIFICANCE

Our results indicate that expression responses to periodic stimuli that are common in natural ecosystems (such as the diel cycle) can diverge significantly between the mRNA and protein levels. Protein expression patterns that are distinct from those of cognate mRNA have implications for the interpretation of transcriptome and metatranscriptome data in terms of cellular metabolism and its biogeochemical impact.

Protein turnover: measurement of proteome dynamics by whole animal metabolic labelling with stable isotope labelled amino acids

The measurement of protein turnover in tissues of intact animals is obtained by whole animal dynamic labelling studies, requiring dietary administration of precursor label. It is difficult to obtain full labelling of precursor amino acids in the diet and if partial labelling is used, calculation of the rate of turnover of each protein requires knowledge of the precursor relative isotope abundance (RIA). We describe an approach to dynamic labelling of proteins in the mouse with a commercial diet supplemented with a pure, deuterated essential amino acid. The pattern of isotopomer labelling can be used to recover the precursor RIA, and sampling of urinary secreted proteins can monitor the development of liver precursor RIA non-invasively. Time-series analysis of the labelling trajectories for individual proteins allows accurate determination of the first order rate constant for degradation. The acquisition of this parameter over multiple proteins permits turnover profiling of cellular proteins and comparisons of different tissues. The median rate of degradation of muscle protein is considerably lower than liver or kidney, with heart occupying an intermediate position.

Measurement of apolipoprotein E and amyloid β clearance rates in the mouse brain using bolus stable isotope labeling

Background

Abnormal proteostasis due to alterations in protein turnover has been postulated to play a central role in several neurodegenerative diseases. Therefore, the development of techniques to quantify protein turnover in the brain is critical for understanding the pathogenic mechanisms of these diseases. We have developed a bolus stable isotope-labeling kinetics (SILK) technique coupled with multiple reaction monitoring mass spectrometry to measure the clearance of proteins in the mouse brain.

Results

Cohorts of mice were pulse labeled with ¹³ C₆-leucine and the brains were isolated after pre-determined time points. The extent of label incorporation was measured over time using mass spectrometry to measure the ratio of labeled to unlabeled apolipoprotein E (apoE) and amyloid β (Aβ). The fractional clearance rate (FCR) was then calculated by analyzing the time course of disappearance for the labeled protein species. To validate the technique, apoE clearance was measured in mice that overexpress the low-density lipoprotein receptor (LDLR). The FCR in these mice was 2.7-fold faster than wild-type mice. To demonstrate the potential of this technique for understanding the pathogenesis of neurodegenerative disease, we applied our SILK technique to determine the effect of ATP binding cassette A1 (ABCA1) on both apoE and Aβ clearance. ABCA1 had previously been shown to regulate both the amount of apoE in the brain, along with the extent of Aβ deposition, and represents a potential molecular target for lowering brain amyloid levels in Alzheimer's disease patients. The FCR of apoE was increased by 1.9- and 1.5-fold in mice that either lacked or overexpressed ABCA1, respectively. However, ABCA1 had no effect on the FCR of Aβ, suggesting that ABCA1 does not regulate Aβ metabolism in the brain.

Conclusions

Our SILK strategy represents a straightforward, cost-effective, and efficient method to measure the clearance of proteins in the mouse brain. We expect that this technique will be applicable to the study of protein dynamics in the pathogenesis of several neurodegenerative diseases, and could aid in the evaluation of novel therapeutic agents.

A proteomics strategy for determining the synthesis and degradation rates of individual proteins in fish

In order to study the protein dynamics in the tissues of fish we have developed a proteomics-based strategy to determine the rates of synthesis and degradation of individual proteins. We have demonstrated the feasibility of this approach by measuring the turnover of multiple isoforms of parvalbumin (β1-7) in the skeletal muscle of common carp (Cyprinus carpio). A stable isotope-labelled amino acid ([(2)H(7)] l-leucine) was administered to the carp via the diet and its incorporation into the isoforms of parvalbumin in muscle over time was monitored by LC-MS analysis of signature peptides. The relative isotope abundance was calculated and used to deconvolute the data. The β7 parvalbumin isoform had a rate of synthesis that was greater than the rate of degradation. In contrast the rate of degradation of the β5 isoform exceeded its rate of synthesis, whilst the analysis revealed that the other parvalbumin β-isoforms (β1, β2, β3, β4 and β6) had a rate of synthesis that was equal to the rate of degradation. This work has addressed a number of technical challenges and represents the first study to use proteomic approaches to measure the turnover of individual proteins in fish.

Dynamic proteome analysis of Cyanothece sp. ATCC 51142 under constant light

Understanding the dynamic nature of protein abundances provides insights into protein turnover not readily apparent from conventional, static mass spectrometry measurements. This level of data is particularly informative when surveying protein abundances in biological systems subjected to large perturbations or alterations in environment such as cyanobacteria. Our current analysis expands upon conventional proteomic approaches in cyanobacteria by measuring dynamic changes of the proteome using a (13)C(15)N-l-leucine metabolic labeling in Cyanothece ATCC51142. Metabolically labeled Cyanothece ATCC51142 cells grown under nitrogen-sufficient conditions in continuous light were monitored longitudinally for isotope incorporation over a 48 h period, revealing 414 proteins with dynamic changes in abundances. In particular, proteins involved in carbon fixation, pentose phosphate pathway, cellular protection, redox regulation, protein folding, assembly, and degradation showed higher levels of isotope incorporation, suggesting that these biochemical pathways are important for growth under continuous light. Calculation of relative isotope abundances (RIA) values allowed the measurement of actual active protein synthesis over time for different biochemical pathways under high light exposure. Overall results demonstrated the utility of "non-steady state" pulsed metabolic labeling for systems-wide dynamic quantification of the proteome in Cyanothece ATCC51142 that can also be applied to other cyanobacteria.

Dynamic proteomic profiling of a unicellular cyanobacterium Cyanothece ATCC51142 across light-dark diurnal cycles

Background

Unicellular cyanobacteria of the genus Cyanothece are recognized for their ability to execute nitrogen (N₂)-fixation in the dark and photosynthesis in the light. An understanding of these mechanistic processes in an integrated systems context should provide insights into how Cyanothece might be optimized for specialized environments and/or industrial purposes. Systems-wide dynamic proteomic profiling with mass spectrometry (MS) analysis should reveal fundamental insights into the control and regulation of these functions.

Results

To expand upon the current knowledge of protein expression patterns in Cyanothece ATCC51142, we performed quantitative proteomic analysis using partial ("unsaturated") metabolic labeling and high mass accuracy LC-MS analysis. This dynamic proteomic profiling identified 721 actively synthesized proteins with significant temporal changes in expression throughout the light-dark cycles, of which 425 proteins matched with previously characterized cycling transcripts. The remaining 296 proteins contained a cluster of proteins uniquely involved in DNA replication and repair, protein degradation, tRNA synthesis and modification, transport and binding, and regulatory functions. Functional classification of labeled proteins suggested that proteins involved in respiration and glycogen metabolism showed increased expression in the dark cycle together with nitrogenase, suggesting that N₂-fixation is mediated by higher respiration and glycogen metabolism. Results indicated that Cyanothece ATCC51142 might utilize alternative pathways for carbon (C) and nitrogen (N) acquisition, particularly, aspartic acid and glutamate as substrates of C and N, respectively. Utilization of phosphoketolase (PHK) pathway for the conversion of xylulose-5P to pyruvate and acetyl-P likely constitutes an alternative strategy to compensate higher ATP and NADPH demand.

Conclusion

This study provides a deeper systems level insight into how Cyanothece ATCC51142 modulates cellular functions to accommodate photosynthesis and N₂-fixation within the single cell.

Proteome turnover in the green alga Ostreococcus tauri by time course 15N metabolic labeling mass spectrometry

Protein synthesis and degradation determine the cellular levels of proteins, and their control hence enables organisms to respond to environmental change. Experimentally, these are little known proteome parameters; however, recently, SILAC-based mass spectrometry studies have begun to quantify turnover in the proteomes of cell lines, yeast, and animals. Here, we present a proteome-scale method to quantify turnover and calculate synthesis and degradation rate constants of individual proteins in autotrophic organisms such as algae and plants. The workflow is based on the automated analysis of partial stable isotope incorporation with (15)N. We applied it in a study of the unicellular pico-alga Ostreococcus tauri and observed high relative turnover in chloroplast-encoded ATPases (0.42-0.58% h(-1)), core photosystem II proteins (0.34-0.51% h(-1)), and RbcL (0.47% h(-1)), while nuclear-encoded RbcS2 is more stable (0.23% h(-1)). Mitochondrial targeted ATPases (0.14-0.16% h(-1)), photosystem antennae (0.09-0.14% h(-1)), and histones (0.07-0.1% h(-1)) were comparatively stable. The calculation of degradation and synthesis rate constants k(deg) and k(syn) confirms RbcL as the bulk contributor to overall protein turnover. This study performed over 144 h of incorporation reveals dynamics of protein complex subunits as well as isoforms targeted to different organelles.

Proteomics moves from expression to turnover: update and future perspective

Proteomics is a rapidly developing discipline that seeks to understand the role of proteins in the wider biological context. In order to take a holistic view of a biological system, it is vital that we can elucidate the dynamics of the proteome. In this article, we have outlined the recent advances in experimental strategies for measuring protein synthesis and degradation on a proteome-wide scale. The application of mass spectrometry and non-mass spectrometric-based approaches in this field of research has been discussed. The article also explores the challenges associated with these types of analyses and the development of appropriate bioinformatic resources for interrogating the complex datasets that are generated.

Protein turnover methods in single-celled organisms: dynamic SILAC

Early achievements in proteomics were qualitative, typified by the identification of very small quantities of proteins. However, as the subject has developed, there has been a pressure to develop approaches to define the amounts of each protein--whether in a relative or an absolute sense. A further dimension to quantitative proteomics embeds the behavior of each protein in terms of its turnover. Virtually every protein in the cell is in a dynamic state, subject to continuous synthesis and degradation, the relative rates of which control the expansion or the contraction of the protein pool, and the absolute values of which dictate the temporal responsiveness of the protein pool. Strategies must therefore be developed to assess the turnover of individual proteins in the proteome. Because a protein can be turning over rapidly even when the protein pool is in steady state, the only acceptable approach to measure turnover is to use metabolic labels that are incorporated or lost from the protein pool as it is replaced. Using metabolic labeling on a proteome-wide scale in turn requires metabolic labels that contain stable isotopes, the incorporation or loss of which can be assessed by mass spectrometry. A typical turnover experiment is complex. The choice of metabolic label is dictated by several factors, including abundance in the proteome, metabolic redistribution of the label in the precursor pool, and the downstream mass spectrometric analytical protocols. Key issues include the need to control and understand the relative isotope abundance of the precursor, the optimization of label flux into and out of the protein pool, and a sampling strategy that ensures the coverage of the greatest range of turnover rates. Finally, the informatics approaches to data analysis will not be as straightforward as in other areas of proteomics. In this chapter, we will discuss the principles and practice of workflow development for turnover analysis, exemplified by the development of methodologies for turnover analysis in the model eukaryote Saccharomyces cerevisiae.

Proteomics in nutrition: status quo and outlook for biomarkers and bioactives

Food and beverages are the only physical matter we take into our body, if we disregard the air we inhale and the drugs we may have to apply. While traditional nutrition research has aimed at providing nutrients to nourish populations and preventing specific nutrient deficiencies, it more recently explores health-related aspects of individual bioactive components as well as entire diets and this at group rather than population level. The new era of nutrition research translates empirical knowledge to evidence-based molecular science. Modern nutrition research focuses on promoting health, preventing or delaying the onset of disease, optimizing performance, and assessing risk. Personalized nutrition is a conceptual analogue to personalized medicine and means adapting food to individual needs. Nutrigenomics and nutrigenetics build the science foundation for understanding human variability in preferences, requirements, and responses to diet and may become the future tools for consumer assessment motivated by personalized nutritional counseling for health maintenance and disease prevention. The scope of this paper is to review the current and future aspects of nutritional proteomics, focusing on the two main outputs: identification of health biomarkers and analysis of food bioactives.

Advances in protein turnover analysis at the global level and biological insights

The concept of a dynamic state of body constituents, a precursor of the modern term of proteome dynamics, was conceived over a century ago. But, not until recently can we examine the dynamics of individual "constituents" for example, proteins at a truly global level. The path of advancement in our understanding of protein turnover at the global level is marked by the introduction of some key technological innovations. These methods include the isotopic tracer technique in the 1930s, the two-dimensional gel electrophoresis technique in the 1970s, the sector mass spectrometer that could analyze isotopomers of peptides in the early 1990s, the 2D gel/MALDI-TOF proteomics technology in the late 1990s, the booming liquid chromatography/mass spectrometry proteomics technology in this decade, and the recently emerging protein-tagging approaches that offer single-cell resolution for protein turnover measurements. The long-standing inquiry raised in the 1950s about the existence of a dynamic state in different organisms at different physiological conditions can now be answered with an individual "constituent" resolution on a truly global scale. Now it appears that protein degradation is not necessarily an end to the protein function. Rather, it can be the start of a new function because protein degradation clears the way for the action of other proteins. Protein turnover participates in a multi-layer complex regulatory network and shares equal importance with gene transcription and protein translation. The advances in technologies for protein turnover analysis and the improved understanding of the biological role of protein turnover will likely help to solve some long-standing biomedical problems such as the tuberculosis disease that at the present day still affects one-third of the world population.