Dynamics of protein turnover, a missing dimension in proteomics

Global, site-resolved analysis of ubiquitylation occupancy and turnover rate reveals systems properties

Ubiquitylation regulates most proteins and biological processes in a eukaryotic cell. However, the site-specific occupancy (stoichiometry) and turnover rate of ubiquitylation have not been quantified. Here we present an integrated picture of the global ubiquitylation site occupancy and half-life. Ubiquitylation site occupancy spans over four orders of magnitude, but the median ubiquitylation site occupancy is three orders of magnitude lower than that of phosphorylation. The occupancy, turnover rate, and regulation of sites by proteasome inhibitors are strongly interrelated, and these attributes distinguish sites involved in proteasomal degradation and cellular signaling. Sites in structured protein regions exhibit longer half-lives and stronger upregulation by proteasome inhibitors than sites in unstructured regions. Importantly, we discovered a surveillance mechanism that rapidly and site-indiscriminately deubiquitylates all ubiquitin-specific E1 and E2 enzymes, protecting them against accumulation of bystander ubiquitylation. The work provides a systems-scale, quantitative view of ubiquitylation properties and reveals general principles of ubiquitylation-dependent governance.

Metabolomic and proteomic applications to exercise biomedicine

Objectives

'OMICs encapsulates study of scaled data acquisition, at the levels of DNA, RNA, protein, and metabolite species. The broad objectives of OMICs in biomedical exercise research are multifarious, but commonly relate to biomarker development and understanding features of exercise adaptation in health, ageing and metabolic diseases.

Methods

This field is one of exponential technical (i.e., depth of feature coverage) and scientific (i.e., in health, metabolic conditions and ageing, multi-OMICs) progress adopting targeted and untargeted approaches.

Results

Key findings in exercise biomedicine have led to the identification of OMIC features linking to heritability or adaptive responses to exercise e.g., the forging of GWAS/proteome/metabolome links to cardiovascular fitness and metabolic health adaptations. The recent addition of stable isotope tracing to proteomics ('dynamic proteomics') and metabolomics ('fluxomics') represents the next phase of state-of-the-art in 'OMICS.

Conclusions

These methods overcome limitations associated with point-in-time 'OMICs and can be achieved using substrate-specific tracers or deuterium oxide (D2O), depending on the question; these methods could help identify how individual protein turnover and metabolite flux may explain exercise responses. We contend application of these methods will shed new light in translational exercise biomedicine.

Lanosterol elevates cytoprotective response through induced-proteasomal degradation of aberrant proteins

Efficient protein synthesis is a basic requirement of our cells to replace the old or defective proteins from the intrinsic crowded biomolecular environment. The interconnection among synthesis, folding, and degradation of proteins represents central paradigm to proteostasis. Failure of protein quality control (PQC) mechanisms results in the disturbance and inadequate functions of proteome. The consequent misfolded protein accumulation can form the basis of neurodegeneration onset and largely represents imperfect aging. Understanding how cells improve the function of deregulated PQC mechanisms to establish and maintain proteostasis against the unwanted sequestration of normal proteins with misfolded proteinaceous inclusions is a major challenge. Here we show that treatment of Lanosterol, a cholesterol synthesis pathway intermediate, induces Proteasome proteolytic activities and, therefore, supports the PQC mechanism for the elimination of intracellular aberrant proteins. The exposure of Lanosterol not only promotes Proteasome catalytic functions but also elevates the removal of both bona fide and neurodegenerative diseases associated toxic proteins. Our current study suggests that increasing Proteasome functions with the help of small molecules such as Lanosterol could serve as a cytoprotective therapeutic approach against abnormal protein accumulation. Cumulatively, based on findings in this study, we can understand the critical importance of small molecules and their potential therapeutic influence in re-establishing disturbed proteostasis linked with neurodegeneration.

Dynamics of seminal fluid production after mating

Seminal fluid proteins (SFPs) play vital roles for optimizing reproductive success in diverse animals. Underlining their significance, SFP production and transfer are highly plastic, e.g., depending on the presence of rivals or mating status of partners. However, surprisingly little is known about replenishing SFPs after mating. This is especially relevant in species that mate multiple times, as they continuously produce and use SFPs throughout their reproductive life. Here we examined the expression pattern of SFP genes after mating in the great pond snail, Lymnaea stagnalis. Our results show that two out of the six SFP genes investigated here were upregulated 1 week after mating. Surprisingly, most SFP genes did not change their expression immediately after mating. Even after 1 week, when supposedly seminal fluid is fully replenished, the expression of SFP genes is rather high. In addition, the difference with previous studies hints at the possibility that SFP production after mating is plastic and depends on the mating history of female-acting snails. Our results shed light on unexplored aspects of SFP production, thereby expanding the understanding of reproductive strategies in animals.

Multi-modal proteomic characterization of lysosomal function and proteostasis in progranulin-deficient neurons

BACKGROUND

Progranulin (PGRN) is a lysosomal glycoprotein implicated in various neurodegenerative diseases, including frontotemporal dementia and neuronal ceroid lipofuscinosis. Over 70 mutations discovered in the GRN gene all result in reduced expression of the PGRN protein. Genetic and functional studies point toward a regulatory role for PGRN in lysosome functions. However, the detailed molecular function of PGRN within lysosomes and the impact of PGRN deficiency on lysosomes remain unclear.

METHODS

We developed multifaceted proteomic techniques to characterize the dynamic lysosomal biology in living human neurons and fixed mouse brain tissues. Using lysosome proximity labeling and immuno-purification of intact lysosomes, we characterized lysosome compositions and interactome in both human induced pluripotent stem cell (iPSC)-derived glutamatergic neurons (i3Neurons) and mouse brains. Using dynamic stable isotope labeling by amino acids in cell culture (dSILAC) proteomics, we measured global protein half-lives in human i3Neurons for the first time.

RESULTS

Leveraging the multi-modal proteomics and live-cell imaging techniques, we comprehensively characterized how PGRN deficiency changes the molecular and functional landscape of neuronal lysosomes. We found that PGRN loss impairs the lysosome's degradative capacity with increased levels of v-ATPase subunits on the lysosome membrane, increased hydrolases within the lysosome, altered protein regulations related to lysosomal transport, and elevated lysosomal pH. Consistent with impairments in lysosomal function, GRN-null i3Neurons and frontotemporal dementia patient-derived i3Neurons carrying GRN mutation showed pronounced alterations in protein turnover, such as cathepsins and proteins related to supramolecular polymerization and inherited neurodegenerative diseases.

CONCLUSION

This study suggested PGRN as a critical regulator of lysosomal pH and degradative capacity, which influences global proteostasis in neurons. Beyond the study of progranulin deficiency, these newly developed proteomic methods in neurons and brain tissues provided useful tools and data resources for the field to study the highly dynamic neuronal lysosome biology.

Spatially resolved mapping of proteome turnover dynamics with subcellular precision

Cellular activities are commonly associated with dynamic proteomic changes at the subcellular level. Although several techniques are available to quantify whole-cell protein turnover dynamics, such measurements often lack sufficient spatial resolution at the subcellular level. Herein, we report the development of prox-SILAC method that combines proximity-dependent protein labeling (APEX2/HRP) with metabolic incorporation of stable isotopes (pulse-SILAC) to map newly synthesized proteins with subcellular spatial resolution. We apply prox-SILAC to investigate proteome dynamics in the mitochondrial matrix and the endoplasmic reticulum (ER) lumen. Our analysis reveals a highly heterogeneous distribution in protein turnover dynamics within macromolecular machineries such as the mitochondrial ribosome and respiratory complexes I-V, thus shedding light on their mechanism of hierarchical assembly. Furthermore, we investigate the dynamic changes of ER proteome when cells are challenged with stress or undergoing stimulated differentiation, identifying subsets of proteins with unique patterns of turnover dynamics, which may play key regulatory roles in alleviating stress or promoting differentiation. We envision that prox-SILAC could be broadly applied to profile protein turnover at various subcellular compartments, under both physiological and pathological conditions.

Comprehensive quantitative modeling of translation efficiency in a genome-reduced bacterium

Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.

The transcriptional response to acute cocaine is inverted in male mice with a history of cocaine self-administration and withdrawal throughout the mesocorticolimbic system

A large body of work has demonstrated that cocaine-induced changes in transcriptional regulation play a central role in the onset and maintenance of cocaine use disorder. An underappreciated aspect of this area of research, however, is that the pharmacodynamic properties of cocaine can change depending on an organism's previous drug-exposure history. In this study, we utilized RNA sequencing to characterize how the transcriptome-wide effects of acute cocaine exposure were altered by a history of cocaine self-administration and long-term withdrawal (30 days) in the ventral tegmental area (VTA), nucleus accumbens (NAc), and prefrontal cortex (PFC) in male mice. First, we found that the gene expression patterns induced by a single cocaine injection (10 mg/kg) were discordant between cocaine-naïve mice and mice in withdrawal from cocaine self-administration. Specifically, the same genes that were upregulated by acute cocaine in cocaine-naïve mice were downregulated by the same dose of cocaine in mice undergoing long-term withdrawal; the same pattern of opposite regulation was observed for the genes downregulated by initial acute cocaine exposure. When we analyzed this dataset further, we found that the gene expression patterns that were induced by long-term withdrawal from cocaine self-administration showed a high degree of overlap with the gene expression patterns of acute cocaine exposure - even though animals had not consumed cocaine in 30 days. Interestingly, cocaine re-exposure at this withdrawal time point reversed this expression pattern. Finally, we found that this pattern was similar across the VTA, PFC, NAc, and within each brain region the same genes were induced by acute cocaine, re-induced during long-term withdrawal, and reversed by cocaine re-exposure. Together, we identified a longitudinal pattern of gene regulation that is conserved across the VTA, PFC, and NAc, and characterized the genes constituting this pattern in each brain region.

The biogenesis of the immunopeptidome

The immunopeptidome is the repertoire of peptides bound and presented by the MHC class I, class II, and non-classical molecules. The peptides are produced by the degradation of most cellular proteins, and in some cases, peptides are produced from extracellular proteins taken up by the cells. This review attempts to first describe some of its known and well-accepted concepts, and next, raise some questions about a few of the established dogmas in this field: The production of novel peptides by splicing is questioned, suggesting here that spliced peptides are extremely rare, if existent at all. The degree of the contribution to the immunopeptidome by degradation of cellular protein by the proteasome is doubted, therefore this review attempts to explain why it is likely that this contribution to the immunopeptidome is possibly overstated. The contribution of defective ribosome products (DRiPs) and non-canonical peptides to the immunopeptidome is noted and methods are suggested to quantify them. In addition, the common misconception that the MHC class II peptidome is mostly derived from extracellular proteins is noted, and corrected. It is stressed that the confirmation of sequence assignments of non-canonical and spliced peptides should rely on targeted mass spectrometry using spiking-in of heavy isotope-labeled peptides. Finally, the new methodologies and modern instrumentation currently available for high throughput kinetics and quantitative immunopeptidomics are described. These advanced methods open up new possibilities for utilizing the big data generated and taking a fresh look at the established dogmas and reevaluating them critically.

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

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

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.

Measurement of protein in vivo turnover rate with metabolic labeling using LC-MS

Understanding the protein dynamics of a drug target is important for pharmaceutical research because it provides insight into drug design, target engagement, pharmacodynamics and drug efficacy. Nonradioactive isotope labeling has been the method of choice for protein turnover measurement thanks to the advancement of high-resolution mass spectrometry. While the changes in proteome in cell cultures can be monitored precisely, as the culture media can be completely replaced with ² H-, ¹⁵ N- or ¹³ C-labeled essential amino acids, quantifying rates of protein synthesis in vivo is more challenging. The amount of isotope tracer that can be administered into the body is relatively small compared with the existing protein, thus requiring more sensitive detection, and the precursor-product labeling relationship is more complicated to interpret. The purpose of this review is to provide an overview of the principles of in vivo protein turnover studies using deuterium water (² H₂ O) with an emphasis on targeted protein analysis by hybrid LC-MS assay platforms. The pursuit of these opportunities will facilitate drug discovery and research in preclinical and clinical stages.

The metabolite-controlled ubiquitin conjugase Ubc8 promotes mitochondrial protein import

Mitochondria play a key role in cellular energy metabolism. Transitions between glycolytic and respiratory conditions induce considerable adaptations of the cellular proteome. These metabolism-dependent changes are particularly pronounced for the protein composition of mitochondria. Here, we show that the yeast cytosolic ubiquitin conjugase Ubc8 plays a crucial role in the remodeling process when cells transition from respiratory to fermentative conditions. Ubc8 is a conserved and well-studied component of the catabolite control system that is known to regulate the stability of gluconeogenic enzymes. Unexpectedly, we found that Ubc8 also promotes the assembly of the translocase of the outer membrane of mitochondria (TOM) and increases the levels of its cytosol-exposed receptor subunit Tom22. Ubc8 deficiency results in compromised protein import into mitochondria and reduced steady-state levels of mitochondrial proteins. Our observations show that Ubc8, which is controlled by the prevailing metabolic conditions, promotes the switch from glucose synthesis to glucose usage in the cytosol and induces the biogenesis of the mitochondrial TOM machinery to improve mitochondrial protein import during phases of metabolic transition.

Degradation-driven protein level oscillation in the yeast Saccharomyces cerevisiae

Generating robust, predictable perturbations in cellular protein levels will advance our understanding of protein function and enable the control of physiological outcomes in biotechnology applications. Timed periodic changes in protein levels play a critical role in the cell division cycle, cellular stress response, and development. Here we report the generation of robust protein level oscillations by controlling the protein degradation rate in the yeast Saccharomyces cerevisiae. Using a photo-sensitive degron and red fluorescent proteins as reporters, we show that under constitutive transcriptional induction, repeated triangular protein level oscillations as fast as 5-10 min-scale can be generated by modulating the protein degradation rate. Consistent with oscillations generated though transcriptional control, we observed a continuous decrease in the magnitude of oscillations as the input modulation frequency increased, indicating low-pass filtering of input perturbation. By using two red fluorescent proteins with distinct maturation times, we show that the oscillations in protein level is largely unaffected by delays originating from functional protein formation. Our study demonstrates the potential for repeated control of protein levels by controlling the protein degradation rate without altering the transcription rate.

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.

Harmonizing Labeling and Analytical Strategies to Obtain Protein Turnover Rates in Intact Adult Animals

Changes in the abundance of individual proteins in the proteome can be elicited by modulation of protein synthesis (the rate of input of newly synthesized proteins into the protein pool) or degradation (the rate of removal of protein molecules from the pool). A full understanding of proteome changes therefore requires a definition of the roles of these two processes in proteostasis, collectively known as protein turnover. Because protein turnover occurs even in the absence of overt changes in pool abundance, turnover measurements necessitate monitoring the flux of stable isotope–labeled precursors through the protein pool such as labeled amino acids or metabolic precursors such as ammonium chloride or heavy water. In cells in culture, the ability to manipulate precursor pools by rapid medium changes is simple, but for more complex systems such as intact animals, the approach becomes more convoluted. Individual methods bring specific complications, and the suitability of different methods has not been comprehensively explored. In this study, we compare the turnover rates of proteins across four mouse tissues, obtained from the same inbred mouse strain maintained under identical husbandry conditions, measured using either [¹³C₆]lysine or [²H₂]O as the labeling precursor. We show that for long-lived proteins, the two approaches yield essentially identical measures of the first-order rate constant for degradation. For short-lived proteins, there is a need to compensate for the slower equilibration of lysine through the precursor pools. We evaluate different approaches to provide that compensation. We conclude that both labels are suitable, but careful determination of precursor enrichment kinetics in amino acid labeling is critical and has a considerable influence on the numerical values of the derived protein turnover rates.

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Controlled comparison of heavy water or amino acid labeling for protein turnover.

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Delays in amino acid precursor labeling mostly affect high turnover proteins

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Both methods produced similar turnover rates after adjustment of precursor kinetics.

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Recommendations for analytical workflows for protein turnover studies in animals.

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.

Spatial Stable Isotopic Labeling by Amino Acids in Cell Culture: Pulse-Chase Labeling of Three-Dimensional Multicellular Spheroids for Global Proteome Analysis

Three-dimensional cell cultures, or spheroids, are important model systems for cancer research because they recapitulate chemical and phenotypic aspects of in vivo tumors. Spheroids develop radially symmetric chemical gradients, resulting in distinct cellular populations. Stable isotopic labeling by amino acids in cell culture (SILAC) is a well-established approach to quantify protein expression and has previously been used in a pulse-chase format to evaluate temporal changes. In this article, we demonstrate that distinct isotopic signatures can be introduced into discrete spatial cellular populations, effectively tracking proteins to original locations in the spheroid, using a platform that we refer to as spatial SILAC. Spheroid populations were grown with light, medium, and heavy isotopic media, and the concentric shells of cells were harvested by serial trypsinization. Proteins were quantitatively analyzed by ultraperformance liquid chromatography-tandem mass spectrometry. The isotopic signatures correlated with the spatial location and the isotope position do not significantly impact the proteome of each individual layer. Spatial SILAC can be used to examine the proteomic changes in the different layers of the spheroid and to identify protein biomarkers throughout the structure. We show that SILAC labels can be discretely pulsed to discrete positions, without altering the spheroid's proteome, promising future combined pharmacodynamic and pharmacokinetic studies.

Why Environmental Biomarkers Work: Transcriptome-Proteome Correlations and Modeling of Multistressor Experiments in the Marine Bacterium Trichodesmium

Ocean microbial communities are important contributors to the global biogeochemical reactions that sustain life on Earth. The factors controlling these communities are being increasingly explored using metatranscriptomic and metaproteomic environmental biomarkers. Using published proteomes and transcriptomes from the abundant colony-forming cyanobacterium Trichodesmium (strain IMS101) grown under varying Fe and/or P limitation in low and high CO₂, we observed robust correlations of stress-induced proteins and RNAs (i.e., involved in transport and homeostasis) that yield useful information on the nutrient status under low and/or high CO₂. Conversely, transcriptional and translational correlations of many other central metabolism pathways exhibit broad discordance. A cellular RNA and protein production/degradation model demonstrates how biomolecules with small initial inventories, such as environmentally responsive proteins, achieve large increases in fold-change units as opposed to those with a higher basal expression and inventory such as metabolic systems. Microbial cells, due to their immersion in the environment, tend to show large adaptive responses in both RNA and protein that result in transcript-protein correlations. These observations and model results demonstrate multi-omic coherence for environmental biomarkers and provide the underlying mechanism for those observations, supporting the promise for global application in detecting responses to environmental stimuli in a changing ocean.

An atlas of protein turnover rates in mouse tissues

Protein turnover is critical to cellular physiology as well as to the growth and maintenance of tissues. The unique synthesis and degradation rates of each protein help to define tissue phenotype, and knowledge of tissue- and protein-specific half-lives is directly relevant to protein-related drug development as well as the administration of medical therapies. Using stable isotope labeling and mass spectrometry, we determine the in vivo turnover rates of thousands of proteins-including those of the extracellular matrix-in a set of biologically important mouse tissues. We additionally develop a data visualization platform, named ApplE Turnover, that enables facile searching for any protein of interest in a tissue of interest and then displays its half-life, confidence interval, and supporting measurements. This extensive dataset and the corresponding visualization software provide a reference to guide future studies of mammalian protein turnover in response to physiologic perturbation, disease, or therapeutic intervention.

Neutrophil-Derived Protein S100A8/A9 Alters the Platelet Proteome in Acute Myocardial Infarction and Is Associated With Changes in Platelet Reactivity

Supplemental Digital Content is available in the text.

Objective:

Platelets are central to acute myocardial infarction (MI). How the platelet proteome is altered during MI is unknown. We sought to describe changes in the platelet proteome during MI and identify corresponding functional consequences.

Approach and Results:

Platelets from patients experiencing ST-segment–elevation MI (STEMI) before and 3 days after treatment (n=30) and matched patients with severe stable coronary artery disease before and 3 days after coronary artery bypass grafting (n=25) underwent quantitative proteomic analysis. Elevations in the proteins S100A8 and S100A9 were detected at the time of STEMI compared with stable coronary artery disease (S100A8: FC, 2.00; false discovery rate, 0.05; S100A9: FC, 2.28; false discovery rate, 0.005). During STEMI, only S100A8 mRNA and protein levels were correlated in platelets (R=0.46, P=0.012). To determine whether de novo protein synthesis occurs, activated platelets were incubated with 13C-labeled amino acids for 24 hours and analyzed by mass spectrometry. No incorporation was confidently detected. Platelet S100A8 and S100A9 was strongly correlated with neutrophil abundance at the time of STEMI. When isolated platelets and neutrophils were coincubated under quiescent and activated conditions, release of S100A8 from neutrophils resulted in uptake of S100A8 by platelets. Neutrophils released S100A8/A9 as free heterodimer, rather than in vesicles or extracellular traps. In the community-based Bruneck study (n=338), plasma S100A8/A9 was inversely associated with platelet reactivity—an effect abrogated by aspirin.

Conclusions:

Leukocyte-to-platelet protein transfer may occur in a thromboinflammatory environment such as STEMI. Plasma S100A8/A9 was negatively associated with platelet reactivity. These findings highlight neutrophils as potential modifiers for thrombotic therapies in coronary artery disease.

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 stable isotope labeling to advance our understanding of Alzheimer's disease etiology and pathology

Stable isotope labeling with mass spectrometry (MS)-based proteomic analysis has become a powerful strategy to assess protein steady-state levels, protein turnover, and protein localization. Applying these analyses platforms to neurodegenerative disorders may uncover new aspects of the etiology of these devastating diseases. Recently, stable isotopes-MS has been used to investigate early pathological mechanisms of Alzheimer's disease (AD) with mouse models of AD-like pathology. In this review, we summarize these stable isotope-MS experimental designs and the recent application in the context of AD pathology. We also describe our current efforts aimed at using nuclear magnetic resonance (NMR) analysis of stable isotope-labeled amyloid fibrils from AD mouse model brains. Collectively, these methodologies offer new opportunities to study proteome changes in AD and other neurodegenerative diseases by elucidating mechanisms to target for treatment and prevention.

Impact of Target Turnover on the Translation of Drug-Target Residence Time to Time-Dependent Antibacterial Activity

The translation of time-dependent drug-target occupancy to extended pharmacological activity at low drug concentration depends on factors such as target vulnerability and the rate of target turnover. Previously, we demonstrated that the postantibiotic effect (PAE) caused by inhibitors of bacterial drug targets could be used to assess target vulnerability, and that high levels of target vulnerability coupled with relatively low rates of target resynthesis resulted in a strong correlation between drug-target residence time and the PAE following compound washout. Although the residence time of inhibitors on UDP-3-O-acyl-N-acetylglucosamine deacetylase (LpxC) in Pseudomonas aeruginosa (paLpxC) results in significant PAE, inhibitors of the equivalent enzyme in Escherichia coli (ecLpxC) do not cause a PAE. Hyperactivity of the fatty acid biosynthesis enzyme FabZ or the inclusion of sub-MIC levels of azithromycin lead to the observation of a PAE for three inhibitors of ecLpxC. FabZ hyperactivity has been shown to stabilize ecLpxC, and using mass spectrometry, we demonstrate that the appearance of a PAE can be directly linked to a 3-fold increase in the stability of ecLpxC. These studies substantiate the importance of target turnover in time-dependent drug activity.

The Effect of Interferons on Presentation of Defective Ribosomal Products as HLA Peptides

A subset of class I major histocompatibility complex (MHC)-bound peptides is produced from immature proteins that are rapidly degraded after synthesis. These defective ribosomal products (DRiPs) have been implicated in early alert of the immune system about impending infections. Interferons are important cytokines, produced in response to viral infection, that modulate cellular metabolism and gene expression patterns, increase the presentation of MHC molecules, and induce rapid degradation of proteins and cell-surface presentation of their derived MHC peptides, thereby contributing to the battle against pathogen infections. This study evaluated the role of interferons in the induction of rapid degradation of DRiPs to modulate the repertoire of DRiP-derived MHC peptides. Cultured human breast cancer cells were treated with interferons, and the rates of synthesis and degradation of cellular protein and their degradation products were determined by LC-MS/MS analysis, following the rates of incorporation of heavy stable isotope–labeled amino acids (dynamic stable isotope labeling by amino acids in cell culture, dynamic SILAC) at several time points after the interferon application. Large numbers of MHC peptides that incorporated the heavy amino acids faster than their source proteins indicated that DRiP peptides were abundant in the MHC peptidome; interferon treatment increased by about twofold their relative proportions in the peptidome. Such typical DRiP-derived MHC peptides were from the surplus subunits of the proteasome and ribosome, which are degraded because of the transition to immunoproteasomes and a new composition of ribosomes incorporating protein subunits that are induced by the interferon. We conclude that degradation of surplus subunits induced by the interferon is a major source for DRiP–MHC peptides, a phenomenon relevant to coping with viral infections, where a rapid presentation of MHC peptides derived from excess viral proteins may help alert the immune system about the impending infection.

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Degradation products of surplus subunits are often presented as HLA peptides.

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Interferons increase degradation and presentation of such defective products.

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Dynamic SILAC facilitates identification of such HLA peptides.

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This cellular pathway provides alert to the immune system about viral infections.

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.

Application of Advanced Mass Spectrometry-Based Proteomics to Study Hypoxia Driven Cancer Progression

Cancer is one of the largest contributors to the burden of chronic disease in the world and is the second leading cause of death globally. It is associated with episodes of low-oxygen stress (hypoxia or ischemia/reperfusion) that promotes cancer progression and therapeutic resistance. Efforts have been made in the past using traditional proteomic approaches to decipher oxygen deprivation stress-related mechanisms of the disease initiation and progression and to identify key proteins as a therapeutic target for the treatment and prevention. Despite the potential benefits of proteomic in translational research for the discovery of new drugs, the therapeutic outcome with this approach has not met expectations in clinical trials. This is mainly due to the disease complexity which possess a multifaceted molecular pathology. Therefore, novel strategies to identify and characterize clinically important sets of modulators and molecular events for multi-target drug discovery are needed. Here, we review important past and current studies on proteomics in cancer with an emphasis on recent pioneered labeling approaches in mass spectrometry (MS)-based systematic quantitative analysis to improve clinical success. We also discuss the results of the selected innovative publications that integrate advanced proteomic technologies (e.g. MALDI-MSI, pSILAC/SILAC/iTRAQ/TMT-LC-MS/MS, MRM-MS) for comprehensive analysis of proteome dynamics in different biosystems, including cell type, cell species, and subcellular proteome (i.e. secretome and chromatome). Finally, we discuss the future direction and challenges in the application of these technological advancements in mass spectrometry within the context of cancer and hypoxia.

The Vital Role of Proteomics in Characterizing Novel Protein Degraders

Mass spectrometry-based proteomics profiling is a discovery tool that enables researchers to understand the mechanisms of action of drug candidates. When applied to proteolysis targeting chimeras (PROTACs) such approaches provide unbiased perspectives of the binding, degradation selectivity, and mechanism related to efficacy and safety. Specifically, global profiling experiments can identify direct degradation events and assess downstream pathway modulation that may result from degradation or off-target inhibition. Targeted proteomics approaches can be used to quantify the levels of relevant E3 ligases and the protein of interest in cell lines and tissues of interest, which can inform the line of sight and provide insights on possible safety liabilities early in the project. Furthermore, proteomics approaches can be applied to understand protein turnover and resynthesis rates and inform on target tractability, as well as pharmacokinetics/pharmacodynamics understanding. In this perspective, we survey the literature around the impact of mass spectrometry-based proteomics in the development of PROTACs and present our envisioned proteomics cascade for supporting targeted protein degradation projects.

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.

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.

Protein quality control and regulated proteolysis in the genome-reduced organism Mycoplasma pneumoniae

Protein degradation is a crucial cellular process in all-living systems. Here, using Mycoplasma pneumoniae as a model organism, we defined the minimal protein degradation machinery required to maintain proteome homeostasis. Then, we conditionally depleted the two essential ATP-dependent proteases. Whereas depletion of Lon results in increased protein aggregation and decreased heat tolerance, FtsH depletion induces cell membrane damage, suggesting a role in quality control of membrane proteins. An integrative comparative study combining shotgun proteomics and RNA-seq revealed 62 and 34 candidate substrates, respectively. Cellular localization of substrates and epistasis studies supports separate functions for Lon and FtsH. Protein half-life measurements also suggest a role for Lon-modulated protein decay. Lon plays a key role in protein quality control, degrading misfolded proteins and those not assembled into functional complexes. We propose that regulating complex assembly and degradation of isolated proteins is a mechanism that coordinates important cellular processes like cell division. Finally, by considering the entire set of proteases and chaperones, we provide a fully integrated view of how a minimal cell regulates protein folding and degradation.

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.

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.

Escherichia coli metabolism under short-term repetitive substrate dynamics: adaptation and trade-offs

Background

Microbial metabolism is highly dependent on the environmental conditions. Especially, the substrate concentration, as well as oxygen availability, determine the metabolic rates. In large-scale bioreactors, microorganisms encounter dynamic conditions in substrate and oxygen availability (mixing limitations), which influence their metabolism and subsequently their physiology. Earlier, single substrate pulse experiments were not able to explain the observed physiological changes generated under large-scale industrial fermentation conditions.

Results

In this study we applied a repetitive feast–famine regime in an aerobic Escherichia coli culture in a time-scale of seconds. The regime was applied for several generations, allowing cells to adapt to the (repetitive) dynamic environment. The observed response was highly reproducible over the cycles, indicating that cells were indeed fully adapted to the regime. We observed an increase of the specific substrate and oxygen consumption (average) rates during the feast–famine regime, compared to a steady-state (chemostat) reference environment. The increased rates at same (average) growth rate led to a reduced biomass yield (30% lower). Interestingly, this drop was not followed by increased by-product formation, pointing to the existence of energy-spilling reactions. During the feast–famine cycle, the cells rapidly increased their uptake rate. Within 10 s after the beginning of the feeding, the substrate uptake rate was higher (4.68 μmol/g_CDW/s) than reported during batch growth (3.3 μmol/g_CDW/s). The high uptake led to an accumulation of several intracellular metabolites, during the feast phase, accounting for up to 34% of the carbon supplied. Although the metabolite concentrations changed rapidly, the cellular energy charge remained unaffected, suggesting well-controlled balance between ATP producing and ATP consuming reactions.

Conclusions

The adaptation of the physiology and metabolism of E. coli under substrate dynamics, representative for large-scale fermenters, revealed the existence of several cellular mechanisms coping with stress. Changes in the substrate uptake system, storage potential and energy-spilling processes resulted to be of great importance. These metabolic strategies consist a meaningful step to further tackle reduced microbial performance, observed under large-scale cultivations.

Hypothesis: protein and RNA attributes are continuously optimized over time

Background

Little is known why proteins and RNAs exhibit half-lives varying over several magnitudes. Despite many efforts, a conclusive link between half-lives and gene function could not be established suggesting that other determinants may influence these molecular attributes.

Results

Here, I find that with increasing gene age there is a gradual and significant increase of protein and RNA half-lives, protein structure, and other molecular attributes that tend to affect protein abundance. These observations are accommodated in a hypothesis which posits that new genes at ‘birth’ are not optimized and thus their products exhibit low half-lives and less structure but continuous mutagenesis eventually improves these attributes. Thus, the protein and RNA products of the oldest genes obtained their high degrees of stability and structure only after billions of years while the products of younger genes had less time to be optimized and are therefore less stable and structured. Because more stable proteins with lower turnover require less transcription to maintain the same level of abundance, reduced transcription-associated mutagenesis (TAM) would fixate the changes by increasing gene conservation.

Conclusions

Consequently, the currently observed diversity of molecular attributes is a snapshot of gene products being at different stages along their temporal path of optimization.

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 molecular toolbox for studying protein degradation in mammalian cells

Protein degradation is a crucial regulatory process in maintaining cellular proteostasis. The selective degradation of intracellular proteins controls diverse cellular and biochemical processes in all kingdoms of life. Targeted protein degradation is implicated in controlling the levels of regulatory proteins as well as eliminating misfolded and any otherwise abnormal proteins. Deregulation of protein degradation is concomitant with the progression of various neurodegenerative disorders such as Parkinson's and Alzheimer's diseases. Thus, methods of measuring metabolic half-lives of proteins greatly influence our understanding of the diverse functions of proteins in mammalian cells including neuronal cells. Historically, protein degradation rates have been studied via exploiting methods that estimate overall protein degradation or focus on few individual proteins. Notably, with the recent technical advances and developments in proteomic and imaging techniques, it is now possible to measure degradation rates of a large repertoire of defined proteins and analyze the degradation profile in a detailed spatio-temporal manner, with the aim of determining proteome-wide protein stabilities upon different physiological conditions. Herein, we discuss some of the classical and novel methods for determining protein degradation rates highlighting the crucial role of some state of art approaches in deciphering the global impact of dynamic nature of targeted degradation of cellular proteins. This article is part of the Special Issue "Proteomics".

Histone deacetylase activity mediates thermal plasticity in zebrafish (Danio rerio)

Regulatory mechanisms underlying thermal plasticity determine its evolution and potential to confer resilience to climate change. Here we show that class I and II histone deacetylases (HDAC) mediated thermal plasticity globally by shifting metabolomic profiles of cold acclimated zebrafish (Danio rerio) away from warm acclimated animals. HDAC activity promoted swimming performance, but reduced slow and fast myosin heavy chain content in cardiac and skeletal muscle. HDAC increased sarco-endoplasmic reticulum ATPase activity in cold-acclimated fish but not in warm-acclimated animals, and it promoted cardiac function (heart rate and relative stroke volume) in cold but not in warm-acclimated animals. HDAC are an evolutionarily ancient group of proteins, and our data show that they mediate the capacity for thermal plasticity, although the actual manifestation of plasticity is likely to be determined by interactions with other regulators such as AMP-activated protein kinase and thyroid hormone.

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.

Neuronal and synaptic protein lifetimes

Neuronal proteostasis is uniquely challenged by the extraordinary architecture of neurons, the vast number of synapses they form, and the need to precisely preserve function at individual synapses. Quantitative information on protein lifetimes can provide clues as to how these challenges are met. Advances in proteomics and mass spectrometry, which now enable comprehensive lifetime estimations for thousands of proteins, suggest that neuronal and synaptic protein lifetimes are unusually long, with half-lives typically ranging from days to weeks, even months and beyond for certain protein families. Half-lives in vivo are several-fold longer than those in cell culture, tend to cluster for proteins belonging to multimolecular complexes, are affected by developmental stage, and possibly by environmental conditions and activity levels.

Mass Spectrometry-Based Biomarkers in Drug Development

Advances in mass spectrometry, proteomics, protein bioanalytical approaches, and biochemistry have led to a rapid evolution and expansion in the area of mass spectrometry-based biomarker discovery and development. The last decade has also seen significant progress in establishing accepted definitions, guidelines, and criteria for the analytical validation, acceptance and qualification of biomarkers. These advances have coincided with a decreased return on investment for pharmaceutical research and development and an increasing need for better early decision making tools. Empowering development teams with tools to measure a therapeutic interventions impact on disease state and progression, measure target engagement and to confirm predicted pharmacodynamic effects is critical to efficient data-driven decision making. Appropriate implementation of a biomarker or a combination of biomarkers can enhance understanding of a drugs mechanism, facilitate effective translation from the preclinical to clinical space, enable early proof of concept and dose selection, and increases the efficiency of drug development. Here we will provide descriptions of the different classes of biomarkers that have utility in the drug development process as well as review specific, protein-centric, mass spectrometry-based approaches for the discovery of biomarkers and development of targeted assays to measure these markers in a selective and analytically precise manner.

Biodynamics: A novel quasi-first principles theory on the fundamental mechanisms of cellular function/dysfunction and the pharmacological modulation thereof

Cellular function depends on heterogeneous dynamic intra-, inter-, and supramolecular structure-function relationships. However, the specific mechanisms by which cellular function is transduced from molecular systems, and by which cellular dysfunction arises from molecular dysfunction are poorly understood. We proposed previously that cellular function manifests as a molecular form of analog computing, in which specific time-dependent state transition fluxes within sets of molecular species ("molecular differential equations" (MDEs)) are sped and slowed in response to specific perturbations (inputs). In this work, we offer a theoretical treatment of the molecular mechanisms underlying cellular analog computing (which we refer to as "biodynamics"), focusing primarily on non-equilibrium (dynamic) intermolecular state transitions that serve as the principal means by which MDE systems are solved (the molecular equivalent of mathematical "integration"). Under these conditions, bound state occupancy is governed by kon and koff, together with the rates of binding partner buildup and decay. Achieving constant fractional occupancy over time depends on: 1) equivalence between kon and the rate of binding site buildup); 2) equivalence between koff and the rate of binding site decay; and 3) free ligand concentration relative to koff/kon (n · Kd, where n is the fold increase in binding partner concentration needed to achieve a given fractional occupancy). Failure to satisfy these conditions results in fractional occupancy well below that corresponding to n · Kd. The implications of biodynamics for cellular function/dysfunction and drug discovery are discussed.

A Metabolic Labeling Strategy for Relative Protein Quantification in Clostridioides difficile

Clostridioides difficile (formerly Clostridium difficile) is a Gram-positive, anaerobe, spore-forming pathogen, which causes drug-induced diseases in hospitals worldwide. A detailed analysis of the proteome may provide new targets for drug development or therapeutic strategies to combat this pathogen. The application of metabolic labeling (ML) would allow for accurate quantification of significant differences in protein abundance, even in the case of very small changes. Additionally, it would be possible to perform more accurate studies of the membrane or surface proteomes, which usually require elaborated sample preparation. Such studies are therefore prone to higher standard deviations during the quantification. The implementation of ML strategies for C. difficile is complicated due to the lack in arginine and lysine auxotrophy as well as the Stickland dominated metabolism of this anaerobic pathogen. Hence, quantitative proteome analyses could only be carried out by label free or chemical labeling methods so far. In this paper, a ML approach for C. difficile is described. A cultivation procedure with 15N-labeled media for strain 630Δerm was established achieving an incorporation rate higher than 97%. In a proof-of-principle experiment, the performance of the ML approach in C. difficile was tested. The proteome data of the cytosolic subproteome of C. difficile cells grown in complex medium as well as two minimal media in the late exponential and early stationary growth phase obtained via ML were compared with two label free relative quantification approaches (NSAF and LFQ). The numbers of identified proteins were comparable within the three approaches, whereas the number of quantified proteins were between 1,110 (ML) and 1,861 (LFQ) proteins. A hierarchical clustering showed clearly separated clusters for the different conditions and a small tree height with ML approach. Furthermore, it was shown that the quantification based on ML revealed significant altered proteins with small fold changes compared to the label free approaches. The quantification based on ML was accurate, reproducible, and even more sensitive compared to label free quantification strategies.

Endothelial siRNA delivery in nonhuman primates using ionizable low-molecular weight polymeric nanoparticles

Dysfunctional endothelial cells contribute to the pathophysiology of many diseases, including vascular disease, stroke, hypertension, atherosclerosis, organ failure, diabetes, retinopathy, and cancer. Toward the goal of creating a new RNA-based therapy to correct aberrant endothelial cell gene expression in humans, efficient gene silencing in the endothelium of nonhuman primates was achieved by delivering small interfering RNA (siRNA) with 7C1, a low-molecular weight, ionizable polymer that forms nanoparticles. After a single intravenous administration of 1 mg of siRNA per kilogram of animal, 7C1 nanoparticles delivering Tie2 siRNA caused Tie2 mRNA levels to decrease by approximately 80% in the endothelium of the lung. Significant decreases in Tie2 mRNA were also found in the heart, retina, kidney, pancreas, and bone. Blood chemistry and liver function analysis before and after treatment all showed protein and enzyme concentrations within the normal reference ranges. Furthermore, after controlling for siRNA-specific effects, no significant increases in inflammatory cytokine concentrations were found in the serum. Similarly, no gross lesions or significant underlying pathologies were observed after histological examination of nonhuman primate tissues. This study is the first demonstration of endothelial gene silencing in multiple nonhuman primate organs using systemically administered siRNA nanoparticles and highlights the potential of this approach for the treatment of disease in humans.

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.