Global analysis of protein structural changes in complex proteomes

Thermal proteome profiling for interrogating protein interactions

Thermal proteome profiling (TPP) is based on the principle that, when subjected to heat, proteins denature and become insoluble. Proteins can change their thermal stability upon interactions with small molecules (such as drugs or metabolites), nucleic acids or other proteins, or upon post-translational modifications. TPP uses multiplexed quantitative mass spectrometry-based proteomics to monitor the melting profile of thousands of expressed proteins. Importantly, this approach can be performed in vitro, in situ, or in vivo. It has been successfully applied to identify targets and off-targets of drugs, or to study protein-metabolite and protein-protein interactions. Therefore, TPP provides a unique insight into protein state and interactions in their native context and at a proteome-wide level, allowing to study basic biological processes and their underlying mechanisms.

An isothermal shift assay for proteome scale drug-target identification

Most small molecule drugs act on living systems by physically interacting with specific proteins and modulating target function. Identification of drug binding targets, within the complex milieu of the human proteome, remains a challenging task of paramount importance in drug discovery. Existing approaches for target identification employ complex workflows with limited throughput. Here, we present the isothermal shift assay (iTSA), a mass spectrometry method for proteome-wide identification of drug targets within lysates or living cells. Compared with prevailing methods, iTSA uses a simplified experimental design with increased statistical power to detect thermal stability shifts that are induced by small molecule binding. Using a pan-kinase inhibitor, staurosporine, we demonstrate improved performance over commonly used thermal proteome profiling methods, identifying known targets in cell lysates and living cells. We also demonstrate the identification of both known targets and additional candidate targets for the kinase inhibitor harmine in cell and tissue lysates.

Drug target discovery by magnetic nanoparticles coupled mass spectrometry

Drug target discovery is the basis of drug screening. It elucidates the cause of disease and the mechanism of drug action, which is the essential of drug innovation. Target discovery performed in biological systems is complicated as proteins are in low abundance and endogenous compounds may interfere with drug binding. Therefore, methods to track drug-target interactions in biological matrices are urgently required. In this work, a Fe₃O₄ nanoparticle-based approach was developed for drug-target screening in biofluids. A known ligand-protein complex was selected as a principle-to-proof example to validate the feasibility. After incubation in cell lysates, ligand-modified Fe₃O₄ nanoparticles bound to the target protein and formed complexes that were separated from the lysates by a magnet for further analysis. The large surface-to-volume ratio of the nanoparticles provides more active sites for the modification of chemical drugs. It enhances the opportunity for ligand-protein interactions, which is beneficial for capturing target proteins, especially for those with low abundance. Additionally, a one-step magnetic separation simplifies the pre-processing of ligand-protein complexes, so it effectively reduces the endogenous interference. Therefore, the present nanoparticle-based approach has the potential to be used for drug target screening in biological systems.

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Fe₃O₄ NPs were made hydrophilic to adequately disperse in the cell lysate and fully contact with target proteins.

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The magnetic property of the NPs allowed one-step isolation while maintaining ligand-protein non-covalent bindings.

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It enabled the capture of low abundant targets in biological matrices while eliminated the endogenous interference.

A simple and rapid pipeline for identification of receptor-binding sites on the surface proteins of pathogens

Ligand-receptor interactions play a crucial role in the plethora of biological processes. Several methods have been established to reveal ligand-receptor interface, however, the majority of methods are time-consuming, laborious and expensive. Here we present a straightforward and simple pipeline to identify putative receptor-binding sites on the pathogen ligands. Two model ligands (bait proteins), domain III of protein E of West Nile virus and NadA of Neisseria meningitidis, were incubated with the proteins of human brain microvascular endothelial cells immobilized on nitrocellulose or PVDF membrane, the complex was trypsinized on-membrane, bound peptides of the bait proteins were recovered and detected on MALDI-TOF. Two peptides of DIII (~916 Da and ~2003 Da) and four peptides of NadA (~1453 Da, ~1810 Da, ~2051 Da and ~2433 Da) were identified as plausible receptor-binders. Further, binding of the identified peptides to the proteins of endothelial cells was corroborated using biotinylated synthetic analogues in ELISA and immunocytochemistry. Experimental pipeline presented here can be upscaled easily to map receptor-binding sites on several ligands simultaneously. The approach is rapid, cost-effective and less laborious. The proposed experimental pipeline could be a simpler alternative or complementary method to the existing techniques used to reveal amino-acids involved in the ligand-receptor interface.

Crellastatin A, a PARP-1 Inhibitor Discovered by Complementary Proteomic Approaches

Crellastatin A, a cytotoxic sulfated bis-steroid isolated from the Vanuatu Island marine sponge Crella sp., was selected as an interesting probe for a comprehensive proteomic analysis directed at the characterization of its protein interactors. Given its peculiar structural features, A was submitted to a mass spectrometry-based drug affinity responsive target stability (DARTS) assay combined with (targeted-limited proteolysis-multiple reaction monitoring (t-LiP MRM), rather than a classical affinity purification strategy. Poly-ADP-ribose-polymerase-1 (PARP-1) emerged as the main crellastatin A cellular partner. This result was confirmed by both biochemical and in silico analyses. Further in vitro biological assays highlighted an interesting crellastatin A inhibitory activity on PARP-1.

CETSA in integrated proteomics studies of cellular processes

The Cellular Thermal Shift Assay (CETSA) has recently emerged as a promising method to directly monitor functional modulations of protein interaction states in intact cells and tissue samples. Recent data support that the mass spectrometry-coupled proteome-wide implementation of CETSA (MS-CETSA) generates stringent information on a wide range of different interaction classes and is uniquely well suited to study the modulation of protein interaction states in cellular processes and during drug action. To expand the mechanistic insight of CETSA shifts, and to complement information from CETSA experiments, we outline how the integration of MS-CETSA with other proteomics techniques can provide a new platform for detailed, comprehensive, and interactive studies of the functional modulations of proteomes in situ.

Glucose-dependent control of leucine metabolism by leucyl-tRNA synthetase 1

Despite the importance of glucose and amino acids for energy metabolism, interactions between the two nutrients are not well understood. We provide evidence for a role of leucyl-tRNA synthetase 1 (LARS1) in glucose-dependent control of leucine usage. Upon glucose starvation, LARS1 was phosphorylated by Unc-51 like autophagy activating kinase 1 (ULK1) at the residues crucial for leucine binding. The phosphorylated LARS1 showed decreased leucine binding, which may inhibit protein synthesis and help save energy. Leucine that is not used for anabolic processes may be available for catabolic pathway energy generation. The LARS1-mediated changes in leucine utilization might help support cell survival under glucose deprivation. Thus, depending on glucose availability, LARS1 may help regulate whether leucine is used for protein synthesis or energy production.

Mass spectrometric approaches for profiling protein folding and stability

Protein stability reports on protein homeostasis, function, and binding interactions, such as to other proteins, metabolites and drugs. As such, there is a pressing need for technologies that can report on protein stability. The ideal technique could be applied in vitro or in vivo systems, proteome-wide, independently of matrix, under native conditions, with residue-level resolution, and on protein at endogenous levels. Mass spectrometry has rapidly become a preferred technology for identifying and quantifying proteins. As such, it has been increasingly incorporated into methodologies for interrogating protein stability and folding. Although no single technology can satisfy all desired applications, several emerging approaches have shown outstanding success at providing biological insight into the stability of the proteome. This chapter outlines some of these recent emerging technologies.

Native peptide mapping - A simple method to routinely monitor higher order structure changes and relation to functional activity

In the biopharmaceutical environment, controlling the Critical Quality Attributes (CQA) of a product is essential to prevent changes that affect its safety or efficacy. Physico-chemical techniques and bioassays are used to screen and monitor these CQAs. The higher order structure (HOS) is a CQA that is typically studied using techniques that are not commonly considered amenable to quality control laboratories. Here, we propose a peptide mapping-based method, named native peptide mapping, which could be considered as straightforward for HOS analysis and applicable for IgG4 and IgG1 antibodies. The method was demonstrated to be fit-for-purpose as a stability-indicating assay by showing differences at the peptide level between stressed and unstressed material. The unfolding pathway induced by a heat stress was also studied via native peptide mapping assay. Furthermore, we demonstrated the structure–activity relationship between HOS and biological activity by analyzing different types of stressed samples with a cell-based assay and the native peptide mapping. The correlation between both sets of results was highlighted by monitoring peptides located in the complementary-determining regions and the relative potency of the biotherapeutic product. This relationship represents a useful approach to interrogate the criticality of HOS as a CQA of a drug.

Proteases Immobilization for In Situ Time-Limited Proteolysis on MALDI Chips

A large number of different enzyme immobilization techniques are used in the field of life sciences, clinical diagnostics, or biotechnology. Most of them are based on a chemically mediated formation of covalent bond between an enzyme and support material. The covalent bond formation is usually associated with changes of the enzymes’ three-dimensional structure that can lead to reduction of enzyme activity. The present work demonstrates a potential of an ambient ion-landing technique to effectively immobilize enzymes on conductive supports for direct matrix-assisted laser desorption/ionization (MALDI) mass spectrometry analyses of reaction products. Ambient ion landing is an electrospray-based technique allowing strong and stable noncovalent and nondestructive enzyme deposition onto conductive supports. Three serine proteolytic enzymes including trypsin, α-chymotrypsin, and subtilisin A were immobilized onto conductive indium tin oxide glass slides compatible with MALDI mass spectrometry. The functionalized MALDI chips were used for in situ time-limited proteolysis of proteins and protein–ligand complexes to monitor their structural changes under different conditions. The data from limited proteolysis using MALDI chips fits to known or predicted protein structures. The results show that functionalized MALDI chips are sensitive, robust, and fast and might be automated for general use in the field of structural biology.

Exploiting Interdata Relationships in Next-generation Proteomics Analysis

Mass spectrometry based proteomics and other technologies have matured to enable routine quantitative, system-wide analysis of concentrations, modifications, and interactions of proteins, mRNAs, and other molecules. These studies have allowed us to move toward a new field concerned with mining information from the combination of these orthogonal data sets, perhaps called "integromics." We highlight examples of recent studies and tools that aim at relating proteomic information to mRNAs, genetic associations, and changes in small molecules and lipids. We argue that productive data integration differs from parallel acquisition and interpretation and should move toward quantitative modeling of the relationships between the data. These relationships might be expressed by temporal information retrieved from time series experiments, rate equations to model synthesis and degradation, or networks of causal, evolutionary, physical, and other interactions. We outline steps and considerations toward such integromic studies to exploit the synergy between data sets.

Identification of bioactive metabolites using activity metabolomics

The metabolome, the collection of small-molecule chemical entities involved in metabolism, has traditionally been studied with the aim of identifying biomarkers in the diagnosis and prediction of disease. However, the value of metabolome analysis (metabolomics) has been redefined from a simple biomarker identification tool to a technology for the discovery of active drivers of biological processes. It is now clear that the metabolome affects cellular physiology through modulation of other 'omics' levels, including the genome, epigenome, transcriptome and proteome. In this Review, we focus on recent progress in using metabolomics to understand how the metabolome influences other omics and, by extension, to reveal the active role of metabolites in physiology and disease. This concept of utilizing metabolomics to perform activity screens to identify biologically active metabolites - which we term activity metabolomics - is already having a broad impact on biology.

Metabolism-Centric Trans-Omics

Two recent studies in Cell and Science demonstrate the reconstruction of global mechanistic networks and identification of regulatory principles from multi-omics data.

Glycolytic flux in Saccharomyces cerevisiae is dependent on RNA polymerase III and its negative regulator Maf1

Protein biosynthesis is energetically costly, is tightly regulated and is coupled to stress conditions including glucose deprivation. RNA polymerase III (RNAP III)-driven transcription of tDNA genes for production of tRNAs is a key element in efficient protein biosynthesis. Here we present an analysis of the effects of altered RNAP III activity on the Saccharomyces cerevisiae proteome and metabolism under glucose-rich conditions. We show for the first time that RNAP III is tightly coupled to the glycolytic system at the molecular systems level. Decreased RNAP III activity or the absence of the RNAP III negative regulator, Maf1 elicit broad changes in the abundance profiles of enzymes engaged in fundamental metabolism in S. cerevisiae In a mutant compromised in RNAP III activity, there is a repartitioning towards amino acids synthesis de novo at the expense of glycolytic throughput. Conversely, cells lacking Maf1 protein have greater potential for glycolytic flux.

Global analysis of methionine oxidation provides a census of folding stabilities for the human proteome

The stability of proteins influences their tendency to aggregate, undergo degradation, or become modified in cells. Despite their significance to understanding protein folding and function, quantitative analyses of thermodynamic stabilities have been mostly limited to soluble proteins in purified systems. We have used a highly multiplexed proteomics approach, based on analyses of methionine oxidation rates, to quantify stabilities of ∼10,000 unique regions within ∼3,000 proteins in human cell extracts. The data identify lysosomal and extracellular proteins as the most stable ontological subsets of the proteome. We show that the stability of proteins impacts their tendency to become oxidized and is globally altered by the osmolyte trimethylamine N-oxide (TMAO). We also show that most proteins designated as intrinsically disordered retain their unfolded structure in the complex environment of the cell. Together, the data provide a census of the stability of the human proteome and validate a methodology for global quantitation of folding thermodynamics.

Mapping Molecular Structure of Protein Locating on Nanoparticles with Limited Proteolysis

The molecular structure of a protein could be altered when it is attached to nanoparticles (NPs), affecting the performance of NPs present in biological systems. Limited proteolysis coupled with LC-MS/MS could reveal the changes in protein structure when it binds to a variety of entities, including macro-molecules and small drugs, but it has not yet been applied to study protein-NP interaction. Herein, adsorption of proteins, transferrin, and catalase on the polystyrene (PS) or iron oxide (IO) NPs was analyzed with this method. Both increased and decreased proteolytic efficiency in certain regions on the proteins were observed. Identification of the peptides affected by protein-NP interaction led to proper prediction of alterations to protein function as well as to colloidal stability of NPs. Overall, the present work has demonstrated the utility of limited proteolysis in helping to elucidate the potential biological outcomes of the protein-NP conjugate, obtaining knowledge to guide improvement of the rational design of the protein-conjugated NPs for biomedical applications and to understand the biological behaviors of the engineered NPs.

Ozone risk assessment of castor (Ricinus communis L.) cultivars using open top chamber and ethylenediurea (EDU)

Castor bean (Ricinus communis L.) an important non-edible oilseed crop, is a prominent feed stock towards the generation of renewable materials for industrial production which has multiple applications ranging from cosmetics to biofuels industry. India accounts for 76% of the total world production of castor oil seed. However, major concern for developing countries like India where expanding economy led to rapid increases in gases like NOx, CO and VOCs photochemically form ozone. Ozone is strong oxidant that damages agriculture, ecosystems, and materials with considerable reduction in crop yields and crop quality. One way to reduce ozone induced loss is to focus on the adapting crops to ozone exposure by selecting cultivars with demonstrated ozone resistance. An experiment was conducted for ozone risk assessment of castor cultivars to select cultivar with demonstrated resistance against ozone pollution. This study comprise an open top chamber experiment with three treatments viz. (i) control (ambient ozone concentration), (ii) enhanced ozone (average 75 ppb for 4 h daily throughout the growing season), and (iii) EDU application. Results suggested that the ozone pollution substantially affected growth and physiology of castor cultivars. Crop biomass and yield was also negatively influenced by ozone pollution. Developed defence provided strength to withstand against ozone pollution to the experimental crop cultivars. However, developed defence is cultivar specific and positively correlated with the resistance against ozone pollution. Study concluded that the damage to ozone is directly dependent on the antioxidative potential of plant species. However, ozone adaptability is based on the genetic makeup of the cultivar and yield related loss to ozone can be minimizing by selecting ozone tolerant variety as seen in cultivar Nidhi-999.

A supramolecular sensor array for selective immunoglobulin deficiency analysis

A host–guest based fluorescence sensor array can fully discriminate five structurally similar Ig protein isotypes, and recognize Ig deficiencies in serum.

Hepatitis C virus NS5A inhibitor daclatasvir allosterically impairs NS4B-involved protein-protein interactions within the viral replicase and disrupts the replicase quaternary structure in a replicase assembly surrogate system

Daclatasvir (DCV) is a highly potent direct-acting antiviral that targets the non-structural protein 5A (NS5A) of hepatitis C virus (HCV) and has been used with great clinical success. Previous studies have demonstrated its impact on viral replication complex assembly. However, the precise mechanisms by which DCV impairs the replication complex assembly remains elusive. In this study, by using HCV subgenomic replicons and a viral replicase assembly surrogate system in which the HCV NS3-5B polyprotein is expressed to mimic the viral replicase assembly, we assessed the impact of DCV on the aggregation and tertiary structure of NS5A, the protein-protein interactions within the viral replicase and the quaternary structure of the viral replicase. We found that DCV did not affect aggregation and tertiary structure of NS5A. DCV induced a quaternary structural change of the viral replicase, as evidenced by selective increase of NS4B's sensitivity to proteinase K digestion. Mechanically, DCV impaired the NS4B-involved protein-protein interactions within the viral replicase. These phenotypes were consistent with the phenotypes of several reported NS4B mutants that abolish the viral replicase assembly. The DCV-resistant mutant Y93H was refractory to the DCV-induced reduction of the NS4B-involved protein interactions and the quaternary structural change of the viral replicase. In addition, Y93H reduced NS4B-involved protein-protein interactions within the viral replicase and attenuated viral replication. We propose that DCV may induce a positional change of NS5A, which allosterically affects protein interactions within the replicase components and disrupts replicase assembly.

Chemo-Selection Strategy for Limited Proteolysis Experiments on the Proteomic Scale

Described here is a chemo-selective enrichment strategy, termed the semitryptic peptide enrichment strategy for proteolysis procedures (STEPP), to isolate the semitryptic peptides generated in mass spectrometry-based proteome-wide applications of limited proteolysis methods. The strategy involves reacting the ε-amino groups of lysine side chains and any N-termini created in the limited proteolysis reaction with isobaric mass tags. A subsequent digestion of the sample with trypsin and the chemo-selective reaction of the newly exposed N-termini of the tryptic peptides with N-hydroxysuccinimide (NHS)-activated agarose resin removes the tryptic peptides from solution, leaving only the semitryptic peptides with one nontryptic cleavage site generated in the limited proteolysis reaction for subsequent LC-MS/MS analysis. As part of this work, the STEPP technique is interfaced with two different proteolysis methods, including the pulse proteolysis (PP) and limited proteolysis (LiP) methods. The STEPP-PP workflow is evaluated in two proof-of-principle experiments involving the proteins in a yeast cell lysate and two well-studied drugs, cyclosporin A and geldanamycin. The STEPP-LiP workflow is evaluated in a proof-of-principle experiment involving the proteins in two cell culture models of human breast cancer, MCF-7 and MCF-10A cell lines. The STEPP protocol increased the number of semitryptic peptides detected in the LiP and PP experiments by 5- to 10-fold. The STEPP protocol not only increases the proteomic coverage, but also increases the amount of structural information that can be gleaned from limited proteolysis experiments. Moreover, the protocol also enables the quantitative determination of ligand binding affinities.

Biomarkers for diseases with TDP-43 pathology

The discovery that aggregated transactive response DNA-binding protein 43 kDa (TDP-43) is the major component of pathological ubiquitinated inclusions in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) caused seminal progress in the unveiling of the genetic bases and molecular characteristics of these now so-called TDP-43 proteinopathies. Substantial increase in the knowledge of clinic-pathological coherencies, especially for FTLD variants, could be made in the last decade, but also revealed a considerable complexity of TDP-43 pathology and often a poor correlation of clinical and molecular disease characteristics. To date, an underlying TDP-43 pathology can be predicted only for patients with mutations in the genes C9orf72 and GRN, but is dependent on neuropathological verification in patients without family history, which represent the majority of cases. As etiology-specific therapies for neurodegenerative proteinopathies are emerging, methods to forecast TDP-43 pathology at patients' lifetime are highly required. Here, we review the current status of research pursued to identify specific indicators to predict or exclude TDP-43 pathology in the ALS-FTLD spectrum disorders and findings on candidates for prognosis and monitoring of disease progression in TDP-43 proteinopathies with a focus on TDP-43 with its pathological forms, neurochemical and imaging biomarkers.

Protein Dynamics in Solution by Quantitative Crosslinking/Mass Spectrometry

The dynamics of protein structures and their interactions are responsible for many cellular processes. The rearrangements and interactions of proteins, which are often transient, occur in solution and may require a biological environment that is difficult to maintain in traditional structural biological approaches. Quantitative crosslinking/mass spectrometry (QCLMS) has emerged as an excellent method to fill this gap. Numerous recent applications of the technique have demonstrated that protein dynamics can now be studied in solution at sufficient resolution to gain valuable biological insights, suggesting that extending these investigations to native environments is possible. These breakthroughs have been based on the maturation of CLMS at large, and its recent fusion with quantitative proteomics. We provide here an overview of the current state of the technique, the available workflows and their applications, and remaining challenges.

In-solution dynamics of protein structures and their interactions can be studied by QCLMS.

Successful applications of QCLMS provide insights into multiple different biological processes.

Recent advances in QCLMS allow analyses in the context of native cellular environments, including living cells.

Alternative workflows allow researchers to tailor the analysis to their biological question.

Progress in data processing now offers this technique to researchers with limited initial expertise in crosslinking and quantitative proteomics.

Proteome-Wide Structural Biology: An Emerging Field for the Structural Analysis of Proteins on the Proteomic Scale

Over the past decade, a suite of new mass-spectrometry-based proteomics methods has been developed that now enables the conformational properties of proteins and protein-ligand complexes to be studied in complex biological mixtures, from cell lysates to intact cells. Highlighted here are seven of the techniques in this new toolbox. These techniques include chemical cross-linking (XL-MS), hydroxyl radical footprinting (HRF), Drug Affinity Responsive Target Stability (DARTS), Limited Proteolysis (LiP), Pulse Proteolysis (PP), Stability of Proteins from Rates of Oxidation (SPROX), and Thermal Proteome Profiling (TPP). The above techniques all rely on conventional bottom-up proteomics strategies for peptide sequencing and protein identification. However, they have required the development of unconventional proteomic data analysis strategies. Discussed here are the current technical challenges associated with these different data analysis strategies as well as the relative analytical capabilities of the different techniques. The new biophysical capabilities that the above techniques bring to bear on proteomic research are also highlighted in the context of several different application areas in which these techniques have been used, including the study of protein ligand binding interactions (e.g., protein target discovery studies and protein interaction network analyses) and the characterization of biological states.

Revisiting the role of metabolism during development

An emerging view emphasizes that metabolism is highly regulated in both time and space. In addition, it is increasingly being recognized that metabolic pathways are tightly connected to specific biological processes such as cell signaling, proliferation and differentiation. As we obtain a better view of this spatiotemporal regulation of metabolism, and of the molecular mechanisms that connect metabolism and signaling, we can now move from largely correlative to more functional studies. It is, therefore, a particularly promising time to revisit how metabolism can affect multiple aspects of animal development. In this Review, we discuss how metabolism is mechanistically linked to cellular and developmental programs through both its bioenergetic and metabolic signaling functions. We highlight how metabolism is regulated across various spatial and temporal scales, and discuss how this regulation can influence cellular processes such as cell signaling, gene expression, and epigenetic and post-translational modifications during embryonic development.

Biology/Disease-Driven Initiative on Protein-Aggregation Diseases of the Human Proteome Project: Goals and Progress to Date

The Biology/Disease-driven (B/D) working groups of the Human Proteome Project are alliances of research groups aimed at developing or improving proteomic tools to support specific biological or disease-related research areas. Here, we describe the activities and progress to date of the B/D working group focused on protein aggregation diseases (PADs). PADs are characterized by the intra- or extracellular accumulation of aggregated proteins and include devastating diseases such as Parkinson's and Alzheimer's disease and systemic amyloidosis. The PAD B/D working group aims for the development of proteomic assays for the quantification of aggregation-prone proteins involved in PADs to support basic and clinical research on PADs. Because the proteins in PADs undergo aberrant conformational changes, a goal is to quantitatively resolve altered protein structures and aggregation states in complex biological specimens. We have developed protein-extraction protocols and a set of mass spectrometric (MS) methods that enable the detection and quantification of proteins involved in the systemic and localized amyloidosis and the probing of aberrant protein conformational transitions in cell and tissue extracts. In several studies, we have demonstrated the potential of MS-based proteomics approaches for specific and sensitive clinical diagnoses and for the subtyping of PADs. The developed methods have been detailed in both protocol papers and manuscripts describing applications to facilitate implementation by nonspecialized laboratories, and assay coordinates are shared through public repositories and databases. Clinicians actively involved in the PAD working group support the transfer to clinical practice of the developed methods, such as assays to quantify specific disease-related proteins and their fragments in biofluids and multiplexed MS-based methods for the diagnosis and typing of systemic amyloidosis. We believe that the increasing availability of tools to precisely measure proteins involved in PADs will positively impact research on the molecular bases of these diseases and support early disease diagnosis and a more-confident subtyping.

Impact of Mass Spectrometry-Based Technologies and Strategies on Chemoproteomics as a Tool for Drug Discovery

Chemoproteomics is an invaluable tool to discover protein targets from phenotypic assays and to understand on- and off-target engagement of potential therapeutic compounds. Highlighted in this technology perspective is our view on how improvements in mass spectrometry (MS)-based proteomics technology have dramatically impacted chemoproteomics. Improvements in sample preparation, MS instrumentation, data acquisition, and quantification strategies have enabled medicinal chemists, chemical biologists, and mass spectrometrists to develop new chemoproteomic experiments and improve existing methods. As a result of improvements in MS, we will detail how bead-based affinity capture and activity-based proteome profiling methods have been reduced from multiple LC-MS runs for samples and controls down to a single LC-MS run each for sample and control. With improvements in scan duty cycle and sensitivity, sufficient depth of proteome coverage can be obtained for capture-free methods, which do not utilize an enrichment step.

Reversible, functional amyloids: towards an understanding of their regulation in yeast and humans

Protein aggregates, and in particular amyloids, are generally considered to be inherently irreversible aberrant clumps, and are often associated with pathologies, such as Alzheimer's disease, Parkinson's disease, or systemic amyloidosis. However, recent evidence demonstrates that some aggregates are not only fully reversible, but also perform essential physiological functions. Despite these new findings, very little is known about how these functional protein aggregates are regulated in a physiological context. Here, we take the yeast pyruvate kinase Cdc19 as an example of a protein forming functional, reversible, solid, amyloid-like aggregates in response to stress conditions. Cdc19 aggregation is regulated via an aggregation-prone low complexity region (LCR). In favorable growth conditions, this LCR is prevented from aggregating by phosphorylation or oligomerization, while upon glucose starvation it becomes exposed and allows aggregation. We suggest that LCR phosphorylation, oligomerization or partner-binding may be general and widespread mechanisms regulating LCR-mediated reversible protein aggregation. Moreover, we show that, as predicted by computational tools, Cdc19 forms amyloid-like aggregates in vitro. Interestingly, we also observe striking similarities between Cdc19 and its mammalian counterpart, PKM2. Indeed, also PKM2 harbors a LCR and contains several peptides with high amyloidogenic propensity, which coincide with known phosphorylation sites. Thus, we speculate that the formation of reversible, amyloid-like aggregates may be a general physiological mechanism for cells to adapt to stress conditions, and that the underlying regulatory mechanisms may be conserved from yeast to humans.

Chemical-Mediated Digestion: An Alternative Realm for Middle-down Proteomics?

Protein digestion in mass spectrometry (MS)-based bottom-up proteomics targets mainly lysine and arginine residues, yielding primarily 0.6-3 kDa peptides for the proteomes of organisms of all major kingdoms. Recent advances in MS technology enable analysis of complex mixtures of increasingly longer (>3 kDa) peptides in a high-throughput manner supporting the development of a middle-down proteomics (MDP) approach. Generating longer peptides is a paramount step in launching an MDP pipeline, but the quest for the selection of a cleaving agent that would provide the desired 3-15 kDa peptides remains open. Recent bioinformatics studies have shown that cleavage at the rarely occurring amino acid residues such as methionine (Met), tryptophan (Trp), or cysteine (Cys) would be suitable for MDP approach. Interestingly, chemical-mediated proteolytic cleavages uniquely allow targeting these rare amino acids, for which no specific proteolytic enzymes are known. Herein, as potential candidates for MDP-grade proteolysis, we have investigated the performance of chemical agents previously reported to target primarily Met, Trp, and Cys residues: CNBr, BNPS-Skatole (3-bromo-3-methyl-2-(2-nitrophenyl)sulfanylindole), and NTCB (2-nitro-5-thiobenzoic acid), respectively. Figures of merit such as digestion reproducibility, peptide size distribution, and occurrence of side reactions are discussed. The NTCB-based MDP workflow has demonstrated particularly attractive performance, and NTCB is put forward here as a potential cleaving agent for further MDP development.

Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity

Metabolic flux is in part regulated by endogenous small molecules that modulate the catalytic activity of an enzyme, e.g., allosteric inhibition. In contrast to transcriptional regulation of enzymes, technical limitations have hindered the production of a genome-scale atlas of small molecule-enzyme regulatory interactions. Here, we develop a framework leveraging the vast, but fragmented, biochemical literature to reconstruct and analyze the small molecule regulatory network (SMRN) of the model organism Escherichia coli, including the primary metabolite regulators and enzyme targets. Using metabolic control analysis, we prove a fundamental trade-off between regulation and enzymatic activity, and we combine it with metabolomic measurements and the SMRN to make inferences on the sensitivity of enzymes to their regulators. Generalizing the analysis to other organisms, we identify highly conserved regulatory interactions across evolutionarily divergent species, further emphasizing a critical role for small molecule interactions in the maintenance of metabolic homeostasis.

Analytical Cascades of Enzymes for Sensitive Detection of Structural Variations in Protein Samples

Protein function critically depends on structure. However, current analytical tools to monitor consistent higher-order structure with high sensitivity, as for instance required in the development of biopharmaceuticals, are limited. To complement existing assays, we present the analytical cascade of enzymes (ACE), a method based on enzymatic modifications of target proteins, which serve to exponentially amplify structural differences between them. The method enables conformational and chemical fingerprinting of closely related proteins, allowing for the sensitive detection of heterogeneities in protein preparations with high precision. Using this method, we detect protein variants differing in conformation only, as well as structural changes induced by diverse covalent modifications. Additionally, we employ this method to identify the nature of structural variants. Moreover, the ACE method should help to address the limited reproducibility in fundamental research, which partly relates to sample heterogeneities.

Advancing translational research and precision medicine with targeted proteomics

Remarkable advances in quantitative mass spectrometry have shifted the focus of proteomics from the characterization of protein expression profiles to detailed investigations on the spatial and temporal organization of the proteome. Demands for precision therapy and personalized medicine are challenged by heterogeneity in the larger population, which have led to drawbacks in biomarker performance and therapeutic efficacy. The consistent adaptation of the cellular proteome in response to distinctive signals defines a phenotype. Acquisition of quantitative multi-layered omics data on multiple individuals over defined time scales has made it possible to establish means to probe the extent to which the genome, transcriptome and environment influence the variability of the proteome in given conditions, over time. Comprehensive, reproducible datasets generated with contemporary quantitative, massively parallel, targeted proteomic approaches offer as yet untapped benefits for biomarker discovery, development, and validation. The objective of this review is to recapitulate on advances in targeted proteomics approaches for quantifying the cellular proteome and to address ways to incorporate these data towards improving present day methodologies for biomarker evaluation and precision medicine. SIGNIFICANCE: Advances in quantitative mass spectrometry have shifted the focus of proteomics from the characterization of protein expression profiles to detailed investigations on the spatial and temporal organization of the proteome. This review expounds on avenues through which targeted proteomic methodologies can be constructively implemented in translational research and precision medicine to overcome existing challenges that hinder the success of protein biomarkers in clinics, and to develop precise therapeutics for future applications.

High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds

Rapidly spreading antibiotic resistance and the low discovery rate of new antimicrobial compounds demand more effective strategies for early drug discovery. One bottleneck in the drug discovery pipeline is the identification of the modes of action (MoAs) of new compounds. We have developed a rapid systematic metabolome profiling strategy to classify the MoAs of bioactive compounds. The method predicted MoA-specific metabolic responses in the nonpathogenic bacterium Mycobacterium smegmatis after treatment with 62 reference compounds with known MoAs and different metabolic and nonmetabolic targets. We then analyzed a library of 212 new antimycobacterial compounds with unknown MoAs from a drug discovery effort by the pharmaceutical company GlaxoSmithKline (GSK). More than 70% of these new compounds induced metabolic responses in M. smegmatis indicative of known MoAs, seven of which were experimentally validated. Only 8% (16) of the compounds appeared to target unconventional cellular processes, illustrating the difficulty in discovering new antibiotics with different MoAs among compounds used as monotherapies. For six of the GSK compounds with potentially new MoAs, the metabolome profiles suggested their ability to interfere with trehalose and lipid metabolism. This was supported by whole-genome sequencing of spontaneous drug-resistant mutants of the pathogen Mycobacterium tuberculosis and in vitro compound-proteome interaction analysis for one of these compounds. Our compendium of drug-metabolome profiles can be used to rapidly query the MoAs of uncharacterized antimicrobial compounds and should be a useful resource for the drug discovery community.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Proteome-Wide Characterization of Phosphorylation-Induced Conformational Changes in Breast Cancer

Because of the close link between protein function and protein folding stability, knowledge about phosphorylation-induced protein folding stability changes can lead to a better understanding of the functional effects of protein phosphorylation. Here, the stability of proteins from rates of oxidation (SPROX) and limited proteolysis (LiP) techniques are used to compare the conformational properties of proteins in two MCF-7 cell lysates including one that was and one that was not dephosphorylated with alkaline phosphatase. A total of 168 and 251 protein hits were identified with dephosphorylation-induced stability changes using the SPROX and LiP techniques, respectively. Many protein hits are previously known to be differentially phosphorylated or differentially stabilized in different human breast cancer subtypes, suggesting that the phosphorylation-induced stability changes detected in this work are disease related. The SPROX hits were enriched in proteins with aminoacyl-tRNA ligase activity. These enriched protein hits included many aminoacyl-tRNA synthetases (aaRSs), which are known from previous studies to have their catalytic activity modulated by phosphorylation. The SPROX results revealed that the magnitudes of the destabilizing effects of dephoshporylation on the different aaRSs were directly correlated with their previously reported aminoacylation activity change upon dephosphorylation. This substantiates the close link between protein folding and function.

Designing and interpreting 'multi-omic' experiments that may change our understanding of biology

Most biological mechanisms involve more than one type of biomolecule, and hence operate not solely at the level of either genome, transcriptome, proteome, metabolome or ionome. Datasets resulting from single-omic analysis are rapidly increasing in throughput and quality, rendering multi-omic studies feasible. These should offer a comprehensive, structured and interactive overview of a biological mechanism. However, combining single-omic datasets in a meaningful manner has so far proved challenging, and the discovery of new biological information lags behind expectation. One reason is that experiments conducted in different laboratories can typically not to be combined without restriction. Second, the interpretation of multi-omic datasets represents a significant challenge by nature, as the biological datasets are heterogeneous not only for technical, but also for biological, chemical, and physical reasons. Here, multi-layer network theory and methods of artificial intelligence might contribute to solve these problems. For the efficient application of machine learning however, biological datasets need to become more systematic, more precise - and much larger. We conclude our review with basic guidelines for the successful set-up of a multi-omic experiment.

A Perspective on Extracellular Vesicles Proteomics

Increasing attention has been given to secreted extracellular vesicles (EVs) in the past decades, especially in the portrayal of their molecular cargo and role as messengers in both homeostasis and pathophysiological conditions. This review presents the state-of-the-art proteomic technologies to identify and quantify EVs proteins along with their PTMs, interacting partners and structural details. The rapid growth of mass spectrometry-based analytical strategies for protein sequencing, PTMs and structural characterization has improved the level of molecular details that can be achieved from limited amount of EVs isolated from different biological sources. Here we will provide a perspective view on the achievements and challenges on EVs proteome characterization using mass spectrometry. A detailed bioinformatics approach will help us to picture the molecular fingerprint of EVs and understand better their pathophysiological function.

Optimization of Experimental Parameters in Data-Independent Mass Spectrometry Significantly Increases Depth and Reproducibility of Results

Comprehensive, reproducible and precise analysis of large sample cohorts is one of the key objectives of quantitative proteomics. Here, we present an implementation of data-independent acquisition using its parallel acquisition nature that surpasses the limitation of serial MS2 acquisition of data-dependent acquisition on a quadrupole ultra-high field Orbitrap mass spectrometer. In deep single shot data-independent acquisition, we identified and quantified 6,383 proteins in human cell lines using 2-or-more peptides/protein and over 7100 proteins when including the 717 proteins that were identified on the basis of a single peptide sequence. 7739 proteins were identified in mouse tissues using 2-or-more peptides/protein and 8121 when including the 382 proteins that were identified based on a single peptide sequence. Missing values for proteins were within 0.3 to 2.1% and median coefficients of variation of 4.7 to 6.2% among technical triplicates. In very complex mixtures, we could quantify 10,780 proteins and 12,192 proteins when including the 1412 proteins that were identified based on a single peptide sequence. Using this optimized DIA, we investigated large-protein networks before and after the critical period for whisker experience-induced synaptic strength in the murine somatosensory cortex 1-barrel field. This work shows that parallel mass spectrometry enables proteome profiling for discovery with high coverage, reproducibility, precision and scalability.

Discovery of Tamoxifen and N-Desmethyl Tamoxifen Protein Targets in MCF-7 Cells Using Large-Scale Protein Folding and Stability Measurements

The proteins in an MCF-7 cell line were probed for tamoxifen (TAM) and n-desmethyl tamoxifen (NDT) induced stability changes using the Stability of Proteins from Rates of Oxidation (SPROX) technique in combination with two different quantitative proteomics strategies, including one based on SILAC and one based on isobaric mass tags. Over 1000 proteins were assayed for TAM- and NDT-induced protein stability changes, and a total of 163 and 200 protein hits were identified in the TAM and NDT studies, respectively. A subset of 27 high-confidence protein hits were reproducibly identified with both proteomics strategies and/or with multiple peptide probes. One-third of the high-confidence hits have previously established experimental links to the estrogen receptor, and nearly all of the high-confidence hits have established links to breast cancer. One high-confidence protein hit that has known estrogen receptor binding properties, Y-box binding protein 1 (YBX1), was further validated as a direct binding target of TAM using both the SPROX and pulse proteolysis techniques. Proteins with TAM- and/or NDT-induced expression level changes were also identified in the SILAC-SPROX experiments. These proteins with expression level changes included only a small fraction of those with TAM- and/or NDT-induced stability changes.