A Biologist's Field Guide to Multiplexed Quantitative Proteomics

OMICs approaches and technologies for understanding low-high feed efficiency traits in chicken: implication to breeding

In poultry production, there has been a trend of continuous increase in cost of feed ingredients which represents the major proportion of the production costs. Feed costs can be reduced by improving feed efficiency traits which increase the possibility of using various indigestible feed sources and decrease the environmental impact of the enhanced poultry production. Therefore, feed efficiency has been used as one of the most important economic traits of selection in the breeding program of chickens. Recently, many OMICs experimental studies have been designed to characterize biological differences between the high and low feed efficiency chicken phenotypes. Biological complexity cannot be fully captured by main individual OMICs such as genomics, transcriptomics, proteomics and metabolomics. Therefore, researchers have combined multiple assays from the same set of samples to create multi-OMICs datasets. OMICs findings are crucial in improving existing approaches to poultry breeding. The current review aimed to highlight the components of feed efficiency and general OMICs approaches and technologies. Besides, individual and multi-OMICs based understanding of chicken feed efficiency traits and the application of the acquired knowledge in the chicken breeding program were addressed.

Perspectives of Proteomics in Respiratory Allergic Diseases

Proteomics in respiratory allergic diseases has such a battery of techniques and programs that one would almost think there is nothing impossible to find, invent or mold. All the resources that we document here are involved in solving problems in allergic diseases, both diagnostic and prognostic treatment, and immunotherapy development. The main perspectives, according to this version, are in three strands and/or a lockout immunological system: (1) Blocking the diapedesis of the cells involved, (2) Modifications and blocking of paratopes and epitopes being understood by modifications to antibodies, antagonisms, or blocking them, and (3) Blocking FcεRI high-affinity receptors to prevent specific IgEs from sticking to mast cells and basophils. These tools and targets in the allergic landscape are, in our view, the prospects in the field. However, there are still many allergens to identify, including some homologies between allergens and cross-reactions, through the identification of structures and epitopes. The current vision of using proteomics for this purpose remains a constant; this is also true for the basis of diagnostic and controlled systems for immunotherapy. Ours is an open proposal to use this vision for treatment.

Quantification of snake venom proteomes by mass spectrometry-considerations and perspectives

The advent of soft ionization mass spectrometry-based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global-integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label-free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non-model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review-essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof-of-concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism.

Quantitative proteomics analysis in small cell carcinoma of cervix reveals novel therapeutic targets

BACKGROUND

As a rare pathologic subtype, small cell carcinoma of the cervix (SCCC) is characterized by extensive aggressiveness and resistance to current therapies. To date, our knowledge of SCCC origin and progression is limited and sometimes even controversial. Herein, we explored the whole-protein expression profiles in a panel of SCCC cases, aiming to provide more evidence for the precise diagnosis and targeting therapy.

METHODS

Eighteen SCCC samples and six matched normal cervix tissues were collected from January 2013 to December 2017. Data independent acquisition mass spectrometry (DIA) was performed to discriminate the different proteins (DEPs) associated with SCCC. The expression of CDN2A and SYP in corresponding SCCC tissues was verified using immunohistochemistry. GO and KEGG enrichment analyses were used to identify the key DEPs related to SCCC development and tumor recurrence.

RESULTS

As a result, 1311 DEPs were identified in SCCC tissues (780 up-regulated and 531 down-regulated). In up-regulated DEPs, both GO analysis and KEGG analysis showed the most enriched were related to DNA replication (including nuclear DNA replication, DNA-dependent DNA replication, and cell cycle DNA replication), indicating the prosperous proliferation in SCCC. As for the down-regulated DEPs, GO analysis showed that the most enriched functions were associated with extracellular matrix collagen-containing extracellular matrix. KEGG analysis revealed that the DEPs were enriched in Complement and coagulation cascades, proteoglycans in cancer, and focal adhesion-related pathways. Down-regulation of these proteins could enhance the mobility of cancer cells and establish a favorable microenvironment for tumor metastasis, which might be accounted for the frequent local and distant metastasis in SCCC. Surprisingly, the blood vessels and circulatory system exhibit a down-regulation in SCCC, which might be partly responsible for its resistance to anti-angiogenic regimens. In the stratification analysis of early-stage tumors, a group of enzymes involved in the cancer metabolism was discriminated in these recurrence cases.

CONCLUSIONS

Using quantitative proteomics analysis, we first reported the whole-protein expression profiles in SCCC. Significant alterations were found in proteins associated with the enhancement of DNA replication and cellular motility. Besides the association with mitosis, a unique metabolic feature was detected in cases with tumor recurrence. These findings provided novel targets for disease surveillance and treatments, which warranted further validation in the future.

Proteomic Characterization of Acute Myeloid Leukemia for Precision Medicine

Acute myeloid leukemia (AML) is a highly heterogeneous cancer of the hematopoietic system with no cure for most patients. In addition to chemotherapy, treatment options for AML include recently approved therapies that target proteins with roles in AML pathobiology, such as FLT3, BLC2, and IDH1/2. However, due to disease complexity, these therapies produce very diverse responses, and survival rates are still low. Thus, despite considerable advances, there remains a need for therapies that target different aspects of leukemic biology and for associated biomarkers that define patient populations likely to respond to each available therapy. To meet this need, drugs that target different AML vulnerabilities are currently in advanced stages of clinical development. Here, we review proteomics and phosphoproteomics studies that aimed to provide insights into AML biology and clinical disease heterogeneity not attainable with genomic approaches. To place the discussion in context, we first provide an overview of genetic and clinical aspects of the disease, followed by a summary of proteins targeted by compounds that have been approved or are under clinical trials for AML treatment and, if available, the biomarkers that predict responses. We then discuss proteomics and phosphoproteomics studies that provided insights into AML pathogenesis, from which potential biomarkers and drug targets were identified, and studies that aimed to rationalize the use of synergistic drug combinations. When considered as a whole, the evidence summarized here suggests that proteomics and phosphoproteomics approaches can play a crucial role in the development and implementation of precision medicine for AML patients.

A guide to mass spectrometric analysis of extracellular vesicle proteins for biomarker discovery

Exosomes (small extracellular vesicles) in living organisms play an important role in processes such as cell proliferation or intercellular communication. Recently, exosomes have been extensively investigated for biomarker discoveries for various diseases. An important aspect of exosome analysis involves the development of enrichment methods that have been introduced for successful isolation of exosomes. These methods include ultracentrifugation, size exclusion chromatography, polyethylene glycol-based precipitation, immunoaffinity-based enrichment, ultrafiltration, and asymmetric flow field-flow fractionation among others. To confirm the presence of exosomes, various characterization methods have been utilized such as Western blot analysis, atomic force microscopy, electron microscopy, optical methods, zeta potential, visual inspection, and mass spectrometry. Recent advances in high-resolution separations, high-performance mass spectrometry and comprehensive proteome databases have all contributed to the successful analysis of exosomes from patient samples. Herein we review various exosome enrichment methods, characterization methods, and recent trends of exosome investigations using mass spectrometry-based approaches for biomarker discovery.

Advanced Overview of Biomarkers and Techniques for Early Diagnosis of Alzheimer's Disease

The development of early non-invasive diagnosis methods and identification of novel biomarkers are necessary for managing Alzheimer's disease (AD) and facilitating effective prognosis and treatment. AD has multi-factorial nature and involves complex molecular mechanism, which causes neuronal degeneration. The primary challenges in early AD detection include patient heterogeneity and lack of precise diagnosis at the preclinical stage. Several cerebrospinal fluid (CSF) and blood biomarkers have been proposed to show excellent diagnosis ability by identifying tau pathology and cerebral amyloid beta (Aβ) for AD. Intense research endeavors are being made to develop ultrasensitive detection techniques and find potent biomarkers for early AD diagnosis. To mitigate AD worldwide, understanding various CSF biomarkers, blood biomarkers, and techniques that can be used for early diagnosis is imperative. This review attempts to provide information regarding AD pathophysiology, genetic and non-genetic factors associated with AD, several potential blood and CSF biomarkers, like neurofilament light, neurogranin, Aβ, and tau, along with biomarkers under development for AD detection. Besides, numerous techniques, such as neuroimaging, spectroscopic techniques, biosensors, and neuroproteomics, which are being explored to aid early AD detection, have been discussed. The insights thus gained would help in finding potential biomarkers and suitable techniques for the accurate diagnosis of early AD before cognitive dysfunction.

Synergistic and additive interactions between receptor signaling networks drive the regulatory T cell versus T helper 17 cell fate choice

CD4+ T cells differentiate into subsets that promote immunity or minimize damage to the host. T helper 17 cells (Th17) are effector cells that function in inflammatory responses. T regulatory cells (Tregs) maintain tolerance and prevent autoimmunity by secreting immunosuppressive cytokines and expressing check point receptors. While the functions of Th17 and Treg cells are different, both cell fate trajectories require T cell receptor (TCR) and TGF-β receptor (TGF-βR) signals, and Th17 polarization requires an additional IL-6 receptor (IL-6R) signal. Utilizing high-resolution phosphoproteomics, we identified that both synergistic and additive interactions between TCR, TGF-βR, and IL-6R shape kinase signaling networks to differentially regulate key pathways during the early phase of Treg versus Th17 induction. Quantitative biochemical analysis revealed that CD4+ T cells integrate receptor signals via SMAD3, which is a mediator of TGF-βR signaling. Treg induction potentiates the formation of the canonical SMAD3/4 trimer to activate a negative feedback loop through kinases PKA and CSK to suppress TCR signaling, phosphatidylinositol metabolism, and mTOR signaling. IL-6R signaling activates STAT3 to bind SMAD3 and block formation of the SMAD3/4 trimer during the early phase of Th17 induction, which leads to elevated TCR and PI3K signaling. These data provide a biochemical mechanism by which CD4+ T cells integrate TCR, TGF-β, and IL-6 signals via generation of alternate SMAD3 complexes that control the development of early signaling networks to potentiate the choice of Treg versus Th17 cell fate.

Proteomic Profiling of IgG1 Producing CHO Cells Using LC/LC-SPS-MS3: The Effects of Bioprocessing Conditions on Productivity and Product Quality

The biopharmaceutical market is dominated by monoclonal antibodies, the majority of which are produced in Chinese hamster ovary (CHO) cell lines. Intense cell engineering, in combination with optimization of various process parameters results in increasing product titers. To enable further improvements in manufacturing processes, detailed information about how certain parameters affect cellular mechanisms in the production cells, and thereby also the expressed drug substance, is required. Therefore, in this study the effects of commonly applied changes in bioprocessing parameters on an anti-IL8 IgG1 producing CHO DP-12 cell line were investigated on the level of host cell proteome expression combined with product quality assessment of the expressed IgG1 monoclonal antibody. Applying shifts in temperature, pH and dissolved oxygen concentration, respectively, resulted in altered productivity and product quality. Furthermore, analysis of the cells using two-dimensional liquid chromatography-mass spectrometry employing tandem mass tag based isotopic quantitation and synchronous precursor selection-MS³ detection revealed substantial changes in the protein expression profiles of CHO cells. Pathway analysis indicated that applied bioprocessing conditions resulted in differential activation of oxidative phosphorylation. Additionally, activation of ERK5 and TNFR1 signaling suggested an affected cell cycle. Moreover, in-depth product characterization by means of charge variant analysis, peptide mapping, as well as structural and functional analysis, revealed posttranslational and structural changes in the expressed drug substance. Taken together, the present study allows the conclusion that, in anti-IL8 IgG1 producing CHO DP-12 cells, an improved energy metabolism achieved by lowering the cell culture pH is favorable when aiming towards high antibody production rates while maintaining product quality.

Defining the carrier proteome limit for single-cell proteomics

Single-cell proteomics by mass spectrometry (SCoPE-MS) is a recently introduced method to quantify multiplexed single-cell proteomes. While this technique has generated great excitement, the underlying technologies (isobaric labeling and mass spectrometry (MS)) have technical limitations with the potential to affect data quality and biological interpretation. These limitations are particularly relevant when a carrier proteome, a sample added at 25-500× the amount of a single-cell proteome, is used to enable peptide identifications. Here we perform controlled experiments with increasing carrier proteome amounts and evaluate quantitative accuracy, as it relates to mass analyzer dynamic range, multiplexing level and number of ions sampled. We demonstrate that an increase in carrier proteome level requires a concomitant increase in the number of ions sampled to maintain quantitative accuracy. Lastly, we introduce Single-Cell Proteomics Companion (SCPCompanion), a software tool that enables rapid evaluation of single-cell proteomic data and recommends instrument and data analysis parameters for improved data quality.

Noise Exposures Causing Hearing Loss Generate Proteotoxic Stress and Activate the Proteostasis Network

Exposure to excessive sound causes noise-induced hearing loss through complex mechanisms and represents a common and unmet neurological condition. We investigate how noise insults affect the cochlea with proteomics and functional assays. Quantitative proteomics reveals that exposure to loud noise causes proteotoxicity. We identify and confirm hundreds of proteins that accumulate, including cytoskeletal proteins, and several nodes of the proteostasis network. Transcriptomic analysis reveals that a subset of the genes encoding these proteins also increases acutely after noise exposure, including numerous proteasome subunits. Global cochlear protein ubiquitylation levels build up after exposure to excess noise, and we map numerous posttranslationally modified lysines residues. Several collagen proteins decrease in abundance, and Col9a1 specifically localizes to pillar cell heads. After two weeks of recovery, the cochlea selectively elevates the abundance of the protein synthesis machinery. We report that overstimulation of the auditory system drives a robust cochlear proteotoxic stress response.

Proposing a minimal set of metrics and methods to predict probabilities of amyloidosis disease and onset age in individuals

Many amyloid-driven pathologies have both genetic and stochastic components where assessing risk of disease development requires a multifactorial assessment where many of the variables are poorly understood. Risk of transthyretin-mediated amyloidosis is enhanced by age and mutation of the transthyretin (TTR) gene, but amyloidosis is not directly initiated by mutated TTR proteins. Nearly all of the 150+ known mutations increase dissociation of the homotetrameric protein structure and increase the probability of an individual developing a TTR amyloid disease late in life. TTR amyloidosis is caused by dissociated monomers that are destabilized and refold into an amyloidogenic form. Therefore, monomer concentration, monomer proteolysis rate, and structural stability are key variables that may determine the rate of development of amyloidosis. Here we develop a unifying biophysical model that quantifies the relationships among these variables in plasma and suggest the probability of an individual developing a TTR amyloid disease can be estimated. This may allow quantification of risk for amyloidosis and provide the information necessary for development of methods for early diagnosis and prevention. Given the similar observation of genetic and sporadic amyloidoses for other diseases, this model and the measurements to assess risk may be applicable to more proteins than just TTR.

MSstatsTMT: Statistical Detection of Differentially Abundant Proteins in Experiments with Isobaric Labeling and Multiple Mixtures

Tandem mass tag (TMT) is a multiplexing technology widely-used in proteomic research. It enables relative quantification of proteins from multiple biological samples in a single MS run with high efficiency and high throughput. However, experiments often require more biological replicates or conditions than can be accommodated by a single run, and involve multiple TMT mixtures and multiple runs. Such larger-scale experiments combine sources of biological and technical variation in patterns that are complex, unique to TMT-based workflows, and challenging for the downstream statistical analysis. These patterns cannot be adequately characterized by statistical methods designed for other technologies, such as label-free proteomics or transcriptomics. This manuscript proposes a general statistical approach for relative protein quantification in MS- based experiments with TMT labeling. It is applicable to experiments with multiple conditions, multiple biological replicate runs and multiple technical replicate runs, and unbalanced designs. It is based on a flexible family of linear mixed-effects models that handle complex patterns of technical artifacts and missing values. The approach is implemented in MSstatsTMT, a freely available open-source R/Bioconductor package compatible with data processing tools such as Proteome Discoverer, MaxQuant, OpenMS, and SpectroMine. Evaluation on a controlled mixture, simulated datasets, and three biological investigations with diverse designs demonstrated that MSstatsTMT balanced the sensitivity and the specificity of detecting differentially abundant proteins, in large-scale experiments with multiple biological mixtures.

Monitoring protein communities and their responses to therapeutics

Most therapeutics are designed to alter the activities of proteins. From metabolic enzymes to cell surface receptors, connecting the function of a protein to a cellular phenotype, to the activity of a drug and to a clinical outcome represents key mechanistic milestones during drug development. Yet, even for therapeutics with exquisite specificity, the sequence of events following target engagement can be complex. Interconnected communities of structural, metabolic and signalling proteins modulate diverse downstream effects that manifest as interindividual differences in efficacy, adverse effects and resistance to therapy. Recent advances in mass spectrometry proteomics have made it possible to decipher these complex relationships and to understand how factors such as genotype, cell type, local environment and external perturbations influence them. In this Review, we explore how proteomic technologies are expanding our understanding of protein communities and their responses to large- and small-molecule therapeutics.

Progress and pitfalls of using isobaric mass tags for proteome profiling

Introduction: Quantitative proteomics using mass spectrometry is performed via label-free or label-based approaches. Labeling strategies rely on the incorporation of stable heavy isotopes by metabolic, enzymatic, or chemical routes. Isobaric labeling uses chemical labels of identical masses but of different fragmentation behaviors to allow the relative quantitative comparison of peptide/protein abundances between biological samples.Areas covered: We have carried out a systematic review on the use of isobaric mass tags in proteomic research since their inception in 2003. We focused on their quantitative performances, their multiplexing evolution, as well as their broad use for relative quantification of proteins in pre-clinical models and clinical studies. Current limitations, primarily linked to the quantitative ratio distortion, as well as state-of-the-art and emerging solutions to improve their quantitative readouts are discussed.Expert opinion: The isobaric mass tag technology offers a unique opportunity to compare multiple protein samples simultaneously, allowing higher sample throughput and internal relative quantification for improved trueness and precision. Large studies can be performed when shared reference samples are introduced in multiple experiments. The technology is well suited for proteome profiling in the context of proteomic discovery studies.

Insights on acetate-ethanol fermentation by hydrogen-producing Ethanoligenens under acetic acid accumulation based on quantitative proteomics

Ethanoligenens, a novel ethanologenic hydrogen-producing genus, is a representative fermenter in its unique acetate-ethanol fermentation and physiology. Acetic acid accumulation is one of major factors that affect H₂-ethanol co-production. However, sufficient information is unavailable on the tolerance mechanisms of hydrogen-producing bacterium in acetic acid stress. The fermentation process of Ethanoligenens harbinense YUAN-3 was significantly slowed down in the selection stress of exogenous acetic acid. The maximum gas production rate of strain YUAN-3 decreased from 192.15 mL·(L-culture)^-1·h^-1 to 75.2 mL·(L-culture)^-1·h^-1 with increasing exogenous acetic acid from 0 mM to 30 mM, the batch fermentation period was correspondingly expanded from 66 h to 136 h. Through iTRAQ-based quantitative proteomic approach, 78, 121 and 216 proteins were differentially expressed after strain YUAN-3 was cultured in the medium supplemented with exogenous acetic acid of 10 mM, 20 mM and 30 mM. The up-regulated proteins were mainly involved in β-alanine and pyrimidine metabolism, oxidative stress response, while the down-regulated proteins mainly participated in phosphotransferase system (PTS), fructose and mannose metabolism, phosphate uptake, ribosome, and flagellar assembly. These proteins help to maintain balance between fermentation process and alleviation of intracellular acidification in strain YUAN-3. The study indicated that response to acetic acid stress in strain YUAN-3 was a complex process, which involved multiple metabolic pathways. Reductive pyrimidine catabolic pathway played an important role in the acetic acid resistance of E. harbinense.

A Standardized and Reproducible Proteomics Protocol for Bottom-Up Quantitative Analysis of Protein Samples Using SP3 and Mass Spectrometry

The broad utility of mass spectrometry (MS) for investigating the proteomes of a diverse array of sample types has significantly expanded the use of this technology in biological studies. This widespread use has resulted in a substantial collection of protocols and acquisition approaches designed to obtain the highest-quality data for each experiment. As a result, distilling this information to develop a standard operating protocol for essential workflows, such as bottom-up quantitative shotgun whole proteome analysis, can be complex for users new to MS technology. Further complicating this matter, in-depth description of the methodological choices is seldom given in the literature. In this work, we describe a workflow for quantitative whole proteome analysis that is suitable for biomarker discovery, giving detailed consideration to important stages, including (1) cell lysis and protein cleanup using SP3 paramagnetic beads, (2) quantitative labeling, (3) offline peptide fractionation, (4) MS analysis, and (5) data analysis and interpretation. Special attention is paid to providing comprehensive details for all stages of this proteomics workflow to enhance transferability to external labs. The standardized protocol described here will provide a simplified resource to the proteomics community toward efficient adaptation of MS technology in proteomics studies.

Proteomics of nucleocytoplasmic partitioning

The partitioning of the proteome between nucleus and cytoplasm affects nearly every aspect of eukaryotic biology. Despite this central role, we still have a poor understanding of which proteins localize in the nucleus and how this varies in different cell types and conditions. Recent advances in quantitative proteomics and high-throughput imaging are starting to close this knowledge gap. Studies on protein interaction are beginning to reveal the spectrum of cargos of nuclear import and export receptors. We anticipate that it will soon be possible to predict each protein's nucleocytoplasmic localization based on its importin/exportin interactions and its estimated diffusion rate through the nuclear pore. This insight is likely to provide us with a fundamental understanding of how cells use nucleocytoplasmic partitioning to encode and relay information.

Estimation of GFP-Nucleoporin Amount Based on Fluorescence Microscopy

Cellular structures and biomolecular complexes are not simply assemblies of proteins, but are organized with defined numbers of protein molecules in precise locations. Thus, evaluating the spatial localization and numbers of protein molecules is of fundamental importance in understanding cellular structures and functions. The amounts of proteins of interest have conventionally been determined by biochemical methods. However, biochemical measurements based on the population average have limitations: it is sometimes difficult to determine the amounts of insoluble proteins or low expression proteins localized in small portions of the cell. In contrast, microphotometric measurements using fluorescence microscopes enable us to detect the amounts of such proteins in situ in a particular subcellular region. Here, we describe a method to measure the amounts of fluorescently tagged proteins by fluorescence microscopy, and present an example of an application to nuclear pore proteins in the fission yeast Schizosaccharomyces pombe.

Integrated Omics: Tools, Advances, and Future Approaches

With the rapid adoption of high-throughput omic approaches to analyze biological samples such as genomics, transcriptomics, proteomics, and metabolomics, each analysis can generate tera- to peta-byte sized data files on a daily basis. These data file sizes, together with differences in nomenclature among these data types, make the integration of these multi-dimensional omics data into biologically meaningful context challenging. Variously named as integrated omics, multi-omics, poly-omics, trans-omics, pan-omics, or shortened to just 'omics', the challenges include differences in data cleaning, normalization, biomolecule identification, data dimensionality reduction, biological contextualization, statistical validation, data storage and handling, sharing, and data archiving. The ultimate goal is towards the holistic realization of a 'systems biology' understanding of the biological question in hand. Commonly used approaches in these efforts are currently limited by the 3 i's - integration, interpretation, and insights. Post integration, these very large datasets aim to yield unprecedented views of cellular systems at exquisite resolution for transformative insights into processes, events, and diseases through various computational and informatics frameworks. With the continued reduction in costs and processing time for sample analyses, and increasing types of omics datasets generated such as glycomics, lipidomics, microbiomics, and phenomics, an increasing number of scientists in this interdisciplinary domain of bioinformatics face these challenges. We discuss recent approaches, existing tools, and potential caveats in the integration of omics datasets for development of standardized analytical pipelines that could be adopted by the global omics research community.

Inhibition of TACC3 by a small molecule inhibitor in breast cancer

Studies have shown that transforming acidic coiled-coil protein 3 (TACC3), a key component of centrosome-microtubule dynamic networks, is significantly associated with various types of human cancer. We have recently reported that high levels of TACC3 are found in breast cancer, lead to the accumulation of spontaneous DNA damage due to defective DNA damage response signaling, and confer cellular sensitivity to radiation and poly(ADP-ribose) polymerase (PARP) inhibitors. Although our study suggests a potential role of TACC3 as a biomarker in breast cancer detection and prediction of therapy outcome, its role as a therapeutic target in breast cancer is not well studied. In this study, we show that a small molecule TACC3 inhibitor, KHS101, suppresses cell growth, motility, epithelial-mesenchymal transition (EMT), and breast cancer cell stemness while it induces apoptotic cell death. Quantitative multiplexed proteomic analysis using tandem mass tags (TMTs) revealed that KHS101 alters multiple biological processes and signaling pathways, and significantly reduces the expression of mitotic kinases Aurora A and Polo-like kinase 1 (PLK1), which are closely associated with TACC3. Our findings therefore provide a new insight into the potential mechanisms of the action of KHS101 and suggest its possible use as a dual or multi-targeting mitotic inhibitor in breast cancer.

In Vivo Quantitative Monitoring of Subunit Stoichiometry for Metabolic Complexes

Metabolic pathways often employ assemblies of individual enzymes to facilitate substrate channeling to improve thermodynamic efficiency and confer pathway directionality. It is often assumed that subunits to multienzyme complexes are coregulated and accumulate at fixed levels in vivo, reflecting complex stoichiometry. Such assumptions can be experimentally tested using modern tandem mass spectrometry, and herein we describe such an approach applied toward an important metabolic complex. The committed step of de novo fatty acid synthesis in the plastids of most plants is catalyzed by the multienzyme, heteromeric acetyl-CoA carboxylase (hetACCase). This complex is composed of four catalytic subunits and a recently discovered regulatory subunit resembling the biotin carboxyl carrier protein but lacking the biotinylation motif necessary for activity. To better understand this novel form of regulation, a targeted tandem mass-spectrometry-based assay was developed to absolutely quantify all subunits to the Arabidopsis thaliana hetACCase. After validation against pure, recombinant protein, this multiplexed assay was used to quantify hetACCase subunits in siliques in various stages of development. Quantitation provided a developmental profile of hetACCase and BADC protein expression that supports a recently proposed regulatory mechanism for hetACCase and demonstrates a promising application of targeted mass spectrometry for in vivo analysis of protein complexes.

Establishment of Dimethyl Labeling-based Quantitative Acetylproteomics in Arabidopsis

Protein acetylation, one of many types of post-translational modifications (PTMs), is involved in a variety of biological and cellular processes. In the present study, we applied both CsCl density gradient (CDG) centrifugation-based protein fractionation and a dimethyl-labeling-based 4C quantitative PTM proteomics workflow in the study of dynamic acetylproteomic changes in Arabidopsis. This workflow integrates the dimethyl chemical labeling with chromatography-based acetylpeptide separation and enrichment followed by mass spectrometry (MS) analysis, the extracted ion chromatogram (XIC) quantitation-based computational analysis of mass spectrometry data to measure dynamic changes of acetylpeptide level using an in-house software program, named Stable isotope-based Quantitation-Dimethyl labeling (SQUA-D), and finally the confirmation of ethylene hormone-regulated acetylation using immunoblot analysis. Eventually, using this proteomic approach, 7456 unambiguous acetylation sites were found from 2638 different acetylproteins, and 5250 acetylation sites, including 5233 sites on lysine side chain and 17 sites on protein N termini, were identified repetitively. Out of these repetitively discovered acetylation sites, 4228 sites on lysine side chain (i.e. 80.5%) are novel. These acetylproteins are exemplified by the histone superfamily, ribosomal and heat shock proteins, and proteins related to stress/stimulus responses and energy metabolism. The novel acetylproteins enriched by the CDG centrifugation fractionation contain many cellular trafficking proteins, membrane-bound receptors, and receptor-like kinases, which are mostly involved in brassinosteroid, light, gravity, and development signaling. In addition, we identified 12 highly conserved acetylation site motifs within histones, P-glycoproteins, actin depolymerizing factors, ATPases, transcription factors, and receptor-like kinases. Using SQUA-D software, we have quantified 33 ethylene hormone-enhanced and 31 hormone-suppressed acetylpeptide groups or called unique PTM peptide arrays (UPAs) that share the identical unique PTM site pattern (UPSP). This CDG centrifugation protein fractionation in combination with dimethyl labeling-based quantitative PTM proteomics, and SQUA-D may be applied in the quantitation of any PTM proteins in any model eukaryotes and agricultural crops as well as tissue samples of animals and human beings.

Recent advances in mass spectrometry-based approaches for proteomics and biologics: Great contribution for developing therapeutic antibodies

Since the turn of the century, mass spectrometry (MS) technologies have continued to improve dramatically, and advanced strategies that were impossible a decade ago are increasingly becoming available. The basic characteristics behind these advancements are MS resolution, quantitative accuracy, and information science for appropriate data processing. The spectral data from MS contain various types of information. The benefits of improving the resolution of MS data include accurate molecular structural-derived information, and as a result, we can obtain a refined biomolecular structure determination in a sequential and large-scale manner. Moreover, in MS data, not only accurate structural information but also the generated ion amount plays an important rule. This progress has greatly contributed a research field that captures biological events as a system by comprehensively tracing the various changes in biomolecular dynamics. The sequential changes of proteome expression in biological pathways are very essential, and the amounts of the changes often directly become the targets of drug discovery or indicators of clinical efficacy. To take this proteomic approach, it is necessary to separate the individual MS spectra derived from each biomolecule in the complexed biological samples. MS itself is not so infinite to perform the all peak separation, and we should consider improving the methods for sample processing and purification to make them suitable for injection into MS. The above-described characteristics can only be achieved using MS with any analytical instrument. Moreover, MS is expected to be applied and expand into many fields, not only basic life sciences but also forensic medicine, plant sciences, materials, and natural products. In this review, we focus on the technical fundamentals and future aspects of the strategies for accurate structural identification, structure-indicated quantitation, and on the challenges for pharmacokinetics of high-molecular-weight protein biopharmaceuticals.

Quantitative proteomics identify Tenascin-C as a promoter of lung cancer progression and contributor to a signature prognostic of patient survival

The extracellular microenvironment is an integral component of normal and diseased tissues that is poorly understood owing to its complexity. To investigate the contribution of the microenvironment to lung fibrosis and adenocarcinoma progression, two pathologies characterized by excessive stromal expansion, we used mouse models to characterize the extracellular matrix (ECM) composition of normal lung, fibrotic lung, lung tumors, and metastases. Using quantitative proteomics, we identified and assayed the abundance of 113 ECM proteins, which revealed robust ECM protein signatures unique to fibrosis, primary tumors, or metastases. These analyses indicated significantly increased abundance of several S100 proteins, including Fibronectin and Tenascin-C (Tnc), in primary lung tumors and associated lymph node metastases compared with normal tissue. We further showed that Tnc expression is repressed by the transcription factor Nkx2-1, a well-established suppressor of metastatic progression. We found that increasing the levels of Tnc, via CRISPR-mediated transcriptional activation of the endogenous gene, enhanced the metastatic dissemination of lung adenocarcinoma cells. Interrogation of human cancer gene expression data revealed that high TNC expression correlates with worse prognosis for lung adenocarcinoma, and that a three-gene expression signature comprising TNC, S100A10, and S100A11 is a robust predictor of patient survival independent of age, sex, smoking history, and mutational load. Our findings suggest that the poorly understood ECM composition of the fibrotic and tumor microenvironment is an underexplored source of diagnostic markers and potential therapeutic targets for cancer patients.

Proteome-wide Adaptations of Mouse Skeletal Muscles during a Full Month in Space

The safety of space flight is challenged by a severe loss of skeletal muscle mass, strength, and endurance that may compromise the health and performance of astronauts. The molecular mechanisms underpinning muscle atrophy and decreased performance have been studied mostly after short duration flights and are still not fully elucidated. By deciphering the muscle proteome changes elicited in mice after a full month aboard the BION-M1 biosatellite, we observed that the antigravity soleus incurred the greatest changes compared with locomotor muscles. Proteomics data notably suggested mitochondrial dysfunction, metabolic and fiber type switching toward glycolytic type II fibers, structural alterations, and calcium signaling-related defects to be the main causes for decreased muscle performance in flown mice. Alterations of the protein balance, mTOR pathway, myogenesis, and apoptosis were expected to contribute to muscle atrophy. Moreover, several signs reflecting alteration of telomere maintenance, oxidative stress, and insulin resistance were found as possible additional deleterious effects. Finally, 8 days of recovery post flight were not sufficient to restore completely flight-induced changes. Thus in-depth proteomics analysis unraveled the complex and multifactorial remodeling of skeletal muscle structure and function during long-term space flight, which should help define combined sets of countermeasures before, during, and after the flight.

Technologies for Proteome-Wide Discovery of Extracellular Host-Pathogen Interactions

Pathogens have evolved unique mechanisms to breach the cell surface barrier and manipulate the host immune response to establish a productive infection. Proteins exposed to the extracellular environment, both cell surface-expressed receptors and secreted proteins, are essential targets for initial invasion and play key roles in pathogen recognition and subsequent immunoregulatory processes. The identification of the host and pathogen extracellular molecules and their interaction networks is fundamental to understanding tissue tropism and pathogenesis and to inform the development of therapeutic strategies. Nevertheless, the characterization of the proteins that function in the host-pathogen interface has been challenging, largely due to the technical challenges associated with detection of extracellular protein interactions. This review discusses available technologies for the high throughput study of extracellular protein interactions between pathogens and their hosts, with a focus on mammalian viruses and bacteria. Emerging work illustrates a rich landscape for extracellular host-pathogen interaction and points towards the evolution of multifunctional pathogen-encoded proteins. Further development and application of technologies for genome-wide identification of extracellular protein interactions will be important in deciphering functional host-pathogen interaction networks, laying the foundation for development of novel therapeutics.

Multiplexed azido-group isotopic capture (MAGIC) beads: Selective analysis of azido compounds using a propargyl-based cleavable linker, a proof of concept

RATIONALE

A cleavable linker is designed and synthesized for the selective capture of azide-containing compounds. This article presents a proof of concept methodology involving the use of peptide-functionalized aminopropyl silica, on which the peptide is constructed by solid-phase peptide synthesis.

METHODS

The peptide linker has L-propargylglycine (Pra) at one terminal end to allow the conjugation of azide-containing molecules by copper assisted azide alkyne cycloaddition, also known as click reaction. L-Arginine (Arg) is placed just before Pra to permit the release of the captured product by tryptic cleavage. Three glycine (Gly) residues, as part of the linker, are appended to the silica bead to present a spacer section that allows efficient tryptic cleavage devoid of steric hindrance imposed by the bulky bead. The bead composition is Si-O-propyl-NH-Gly-Gly-Gly-Arg-Pra.

RESULTS

This solid-phase material can be used to capture and release azide-functionalized compounds. The beads are first tested on three azido compounds, 2-azido-2-deoxyglucose (ADG), BOC-p-azido-Phe-OH (BAzPhe), where BOC = tert-butoxycarbonyl, and tetraacetylated-N-azidomannosamine (Ac₄ ManNAz). Copper-mediated click reaction conditions are used and released products are characterized by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and tandem MS (MS/MS).

CONCLUSIONS

This method allows easy identification of captured compounds based on mass and fragmentation analysis. Moreover, it is useful for the analysis of small azide-containing compounds by MALDI-TOF-MS which may not be possible otherwise due to matrix interferences. The insertion of isotopically labeled Arg residues provides the possibility of multiplex analysis, from which the beads have been called MAGIC (for Multiplexed Azido-Group Isotopic Capture). Copyright © 2016 John Wiley & Sons, Ltd.

A SILAC-Based Method for Quantitative Proteomic Analysis of Intestinal Organoids

Organoids have the potential to bridge 3D cell culture to tissue physiology by providing a model resembling in vivo organs. Long-term growing organoids were first isolated from intestinal crypt cells and recreated the renewing intestinal epithelial niche. Since then, this technical breakthrough was applied to many other organs, including prostate, liver, kidney and pancreas. We describe here how to apply a SILAC-based quantitative proteomic approach to measure protein expression changes in intestinal organoids under different experimental conditions. We generated SILAC organoid media that allow organoids to grow and differentiate normally, and confirmed the incorporation of isotopically labelled amino acids. Furthermore, we used a treatment reported to affect organoid differentiation to demonstrate the reproducibility of the quantification using this approach and to validate the identification of proteins that correlate with the inhibition of cellular growth and development. With the combined use of quantitative mass spectrometry, SILAC and organoid culture, we validated this approach and showed that large-scale proteome variations can be measured in an “organ-like” system.

Deciphering lymphoma pathogenesis via state-of-the-art mass spectrometry-based quantitative proteomics

Mass spectrometry-based quantitative proteomics specifically applied to comprehend the pathogenesis of lymphoma has incremental value in deciphering the heterogeneity in complex deregulated molecular mechanisms/pathways of the lymphoma entities, implementing the current diagnostic and therapeutic strategies. Essential global, targeted and functional differential proteomics analyses although still evolving, have been successfully implemented to shed light on lymphoma pathogenesis to discover and explore the role of potential lymphoma biomarkers and drug targets. This review aims to outline and appraise the present status of MS-based quantitative proteomic approaches in lymphoma research, introducing the current state-of-the-art MS-based proteomic technologies, the opportunities they offer in biological discovery in human lymphomas and the related limitation issues arising from sample preparation to data evaluation. It is a synopsis containing information obtained from recent research articles, reviews and public proteomics repositories (PRIDE). We hope that this review article will aid, assimilate and assess all the information aiming to accelerate the development and validation of diagnostic, prognostic or therapeutic targets for an improved and empowered clinical proteomics application in lymphomas in the nearby future.

Proteomic Substrate Identification for Membrane Proteases in the Brain

Cell-cell communication in the brain is controlled by multiple mechanisms, including proteolysis. Membrane-bound proteases generate signaling molecules from membrane-bound precursor proteins and control the length and function of cell surface membrane proteins. These proteases belong to different families, including members of the “a disintegrin and metalloprotease” (ADAM), the beta-site amyloid precursor protein cleaving enzymes (BACE), membrane-type matrix metalloproteases (MT-MMP) and rhomboids. Some of these proteases, in particular ADAM10 and BACE1 have been shown to be essential not only for the correct development of the mammalian brain, but also for myelination and maintaining neuronal connections in the adult nervous system. Additionally, these proteases are considered as drug targets for brain diseases, including Alzheimer’s disease (AD), schizophrenia and cancer. Despite their biomedical relevance, the molecular functions of these proteases in the brain have not been explored in much detail, as little was known about their substrates. This has changed with the recent development of novel proteomic methods which allow to identify substrates of membrane-bound proteases from cultured cells, primary neurons and other primary brain cells and even in vivo from minute amounts of mouse cerebrospinal fluid (CSF). This review summarizes the recent advances and highlights the strengths of the individual proteomic methods. Finally, using the example of the Alzheimer-related proteases BACE1, ADAM10 and γ-secretase, as well as ADAM17 and signal peptide peptidase like 3 (SPPL3), we illustrate how substrate identification with novel methods is instrumental in elucidating broad physiological functions of these proteases in the brain and other organs.