Multi-laboratory assessment of reproducibility, qualitative and quantitative performance of SWATH-mass spectrometry

MS1 ion current-based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts

The rapidly-advancing field of pharmaceutical and clinical research calls for systematic, molecular-level characterization of complex biological systems. To this end, quantitative proteomics represents a powerful tool but an optimal solution for reliable large-cohort proteomics analysis, as frequently involved in pharmaceutical/clinical investigations, is urgently needed. Large-cohort analysis remains challenging owing to the deteriorating quantitative quality and snowballing missing data and false-positive discovery of altered proteins when sample size increases. MS1 ion current-based methods, which have become an important class of label-free quantification techniques during the past decade, show considerable potential to achieve reproducible protein measurements in large cohorts with high quantitative accuracy/precision. Nonetheless, in order to fully unleash this potential, several critical prerequisites should be met. Here we provide an overview of the rationale of MS1-based strategies and then important considerations for experimental and data processing techniques, with the emphasis on (i) efficient and reproducible sample preparation and LC separation; (ii) sensitive, selective and high-resolution MS detection; iii)accurate chromatographic alignment; (iv) sensitive and selective generation of quantitative features; and (v) optimal post-feature-generation data quality control. Prominent technical developments in these aspects are discussed. Finally, we reviewed applications of MS1-based strategy in disease mechanism studies, biomarker discovery, and pharmaceutical investigations.

Inter-Laboratory Comparison of Metabolite Measurements for Metabolomics Data Integration

BACKGROUND

One of the current problems in the field of metabolomics is the difficulty in integrating data collected using different equipment at different facilities, because many metabolomic methods have been developed independently and are unique to each laboratory.

METHODS

In this study, we examined whether different analytical methods among 12 different laboratories provided comparable relative quantification data for certain metabolites. Identical samples extracted from two cell lines (HT-29 and AsPc-1) were distributed to each facility, and hydrophilic and hydrophobic metabolite analyses were performed using the daily routine protocols of each laboratory.

RESULTS

The results indicate that there was no difference in the relative quantitative data (HT-29/AsPc-1) for about half of the measured metabolites among the laboratories and assay methods. Data review also revealed that errors in relative quantification were derived from issues such as erroneous peak identification, insufficient peak separation, a difference in detection sensitivity, derivatization reactions, and extraction solvent interference.

CONCLUSION

The results indicated that relative quantification data obtained at different facilities and at different times would be integrated and compared by using a reference materials shared for data normalization.

Proteome and Secretome Dynamics of Human Retinal Pigment Epithelium in Response to Reactive Oxygen Species

Age-related macular degeneration (AMD) is the leading cause of blindness in developed countries, and is characterized by slow retinal degeneration linked to chronic reactive oxygen species (ROS) in the retinal pigmented epithelium (RPE). The molecular mechanisms leading to RPE dysfunction in response to ROS are unclear. Here, human stem cell-derived RPE samples were stressed with ROS for 1 or 3 weeks, and both intracellular and secreted proteomes were quantified by mass spectrometry. ROS increased glycolytic proteins but decreased mitochondrial complex I subunits, as well as membrane proteins required for endocytosis. RPE secreted over 1,000 proteins, many of which changed significantly due to ROS. Notably, secreted APOE is decreased 4-fold, and urotensin-II, the strongest known vasoconstrictor, doubled. Furthermore, secreted TGF-beta is increased, and its cognate signaler BMP1 decreased in the secretome. Together, our results paint a detailed molecular picture of the retinal stress response in space and time.

Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data

The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.

Bioinformatics approaches for improving seminal plasma proteome analysis

Reproduction efficiency of male animals is one of the key factors influencing the sustainability of livestock. Mass spectrometry (MS) based proteomics has become an important tool for studying seminal plasma proteomes. In this review, we summarize bioinformatics analysis strategies for current proteomics approaches, for identifying novel biomarkers of reproductive robustness.

Potential Regulation of UGT2B10 and UGT2B7 by miR-485-5p in Human Liver

The UDP-glucuronosyltransferase (UGT) family of enzymes is important in the metabolic elimination of a variety of endogenous compounds such as bile acids, steroids, and fat-soluble vitamins, as well as exogenous compounds including many pharmaceuticals. The UGT2B subfamily is a major family of UGT enzymes expressed in human liver. The identification of novel mechanisms including post-transcriptional regulation by microRNA (miRNA) contributes to interindividual variability in UGT2B expression and is a crucial component in predicting patient drug response. In the present study, a high-resolution liquid chromatography-tandem mass spectrometry method was employed to measure UGT2B protein levels in a panel of human liver microsomal samples (n = 62). Concurrent in silico analysis identified eight candidate miRNAs as potential regulators of UGT2B enzymes. Comparison of UGT2B protein expression and candidate miRNA levels from human liver samples demonstrated a significant inverse correlation between UGT2B10 and UGT2B15 and one of these candidate miRNAs, miR-485-5p. A near-significant correlation was also observed between UGT2B7 and miR-485-5p expression. In vitro analysis using luciferase-containing vectors suggested an interaction of miR-485-5p within the UGT2B10 3'-untranslated region (UTR), and significant reduction in luciferase activity was also observed for a luciferase vector containing the UGT2B7 3'-UTR; however, none was observed for the UBT2B15 3'-UTR. UGT2B10 and UGT2B7 activities were probed using nicotine and 3'-azido-3'-deoxythymidine, respectively, and significant decreases in glucuronidation activity were observed for both substrates in HuH-7 and Hep3B cells upon overexpression of miR-485-5p mimic. This is the first study demonstrating a regulatory role of miR-485-5p for multiple UGT2B enzymes. SIGNIFICANCE STATEMENT: The purpose of this study was to identify novel epigenetic miRNA regulators of the UGT2B drug-metabolizing enzymes in healthy human liver samples. Our results indicate that miRNA 485-5p is a novel regulator of UGT2B7 and UGT2B10, which play an important role in the metabolism of many commonly prescribed medications, carcinogens, and endogenous compounds. This study identified potential miRNA-UGT2B mRNA interactions using a novel proteomic approach, with in vitro experiments undertaken to validate these interactions.

The Core Proteome of Biofilm-Grown Clinical Pseudomonas aeruginosa Isolates

Comparative genomics has greatly facilitated the identification of shared as well as unique features among individual cells or tissues, and thus offers the potential to find disease markers. While proteomics is recognized for its potential to generate quantitative maps of protein expression, comparative proteomics in bacteria has been largely restricted to the comparison of single cell lines or mutant strains. In this study, we used a data independent acquisition (DIA) technique, which enables global protein quantification of large sample cohorts, to record the proteome profiles of overall 27 whole genome sequenced and transcriptionally profiled clinical isolates of the opportunistic pathogen Pseudomonas aeruginosa. Analysis of the proteome profiles across the 27 clinical isolates grown under planktonic and biofilm growth conditions led to the identification of a core biofilm-associated protein profile. Furthermore, we found that protein-to-mRNA ratios between different P. aeruginosa strains are well correlated, indicating conserved patterns of post-transcriptional regulation. Uncovering core regulatory pathways, which drive biofilm formation and associated antibiotic tolerance in bacterial pathogens, promise to give clues to interactions between bacterial species and their environment and could provide useful targets for new clinical interventions to combat biofilm-associated infections.

Proteomic studies of bone and skeletal health outcomes

Proteins are an essential part of essentially all biological processes, and there is enormous variation in protein forms and concentrations that is not reflected in DNA or RNA. Recently there have been rapid advances in the ability to measure protein sequence, modification and concentration, particularly with methods based in mass spectrometry. Global measures of proteins in tissues or in the circulation provide a broad assessment of the proteome that can be extremely useful for discovery, and targeted proteomic measures can yield specific and sensitive assessments of specific peptides and proteins. While most proteomic measures are directed at the detection of consensus peptide sequences, mass spectrometry based proteomic methods also allow a detailed examination of the peptide sequence differences that result from genetic variants and that may have important effects on protein function. In evaluating proteomic data, a number of analytical considerations are important, including an understanding of missing data, the challenge of multiple testing and replication, and the use of rapidly evolving methods in systems biology. While proteomics has not yet had a major impact in skeletal research, interesting recent research has used these approaches in the study of bone cell biology and the discovery of biomarkers of skeletal disorders. Proteomics can be expected to have an increasing influence in the study of bone biology and pathophysiology.

Deepening our understanding of HDL proteome

Introduction: High-density lipoprotein (HDL) particles are heterogeneous and their proteome is complex and distinct from HDL cholesterol. However, it is largely unknown whether HDL proteins are associated with cardiovascular protection. Areas covered: HDL isolation techniques and proteomic analyses are reviewed. A list of HDL proteins reported in 37 different studies was compiled and the effects of different isolation techniques on proteins attributed to HDL are discussed. Mass spectrometric techniques used for HDL analysis and the need for precise and robust methods for quantification of HDL proteins are discussed. Expert opinion: Proteins associated with HDL have the potential to be used as biomarkers and/or help to understand HDL functionality. To achieve this, large cohorts must be studied using precise quantification methods. Key factors in HDL proteome quantification are the isolation methodology and the mass spectrometry technique employed. Isolation methodology affects what proteins are identified in HDL and the specificity of association with HDL particles needs to be addressed. Shotgun proteomics yields imprecise quantification, but the majority of HDL studies relied on this approach. Few recent studies used targeted tandem mass spectrometry to quantify HDL proteins, and it is imperative that future studies focus on the application of these precise techniques.

Assessing the Relationship Between Mass Window Width and Retention Time Scheduling on Protein Coverage for Data-Independent Acquisition

Due to the technical advances of mass spectrometers, particularly increased scanning speed and higher MS/MS resolution, the use of data-independent acquisition mass spectrometry (DIA-MS) became more popular, which enables high reproducibility in both proteomic identification and quantification. The current DIA-MS methods normally cover a wide mass range, with the aim to target and identify as many peptides and proteins as possible and therefore frequently generate MS/MS spectra of high complexity. In this report, we assessed the performance and benefits of using small windows with, e.g., 5-m/z width across the peptide elution time. We further devised a new DIA method named RTwinDIA that schedules the small isolation windows in different retention time blocks, taking advantage of the fact that larger peptides are normally eluting later in reversed phase chromatography. We assessed the direct proteomic identification by using shotgun database searching tools such as MaxQuant and pFind, and also Spectronaut with an external comprehensive spectral library of human proteins. We conclude that algorithms like pFind have potential in directly analyzing DIA data acquired with small windows, and that the instrumental time and DIA cycle time, if prioritized to be spent on small windows rather than on covering a broad mass range by large windows, will improve the direct proteome coverage for new biological samples and increase the quantitative precision. These results further provide perspectives for the future convergence between DDA and DIA on faster MS analyzers.

Proteomic Profiling of Human Prostate Cancer-associated Fibroblasts (CAF) Reveals LOXL2-dependent Regulation of the Tumor Microenvironment

In prostate cancer, cancer-associated fibroblasts (CAF) exhibit contrasting biological properties to non-malignant prostate fibroblasts (NPF) and promote tumorigenesis. Resolving intercellular signaling pathways between CAF and prostate tumor epithelium may offer novel opportunities for research translation. To this end, the proteome and phosphoproteome of four pairs of patient-matched CAF and NPF were characterized to identify discriminating proteomic signatures. Samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) with a hyper reaction monitoring data-independent acquisition (HRM-DIA) workflow. Proteins that exhibited a significant increase in CAF versus NPF were enriched for the functional categories "cell adhesion" and the "extracellular matrix." The CAF phosphoproteome exhibited enhanced phosphorylation of proteins associated with the "spliceosome" and "actin binding." STRING analysis of the CAF proteome revealed a prominent interaction hub associated with collagen synthesis, modification, and signaling. It contained multiple collagens, including the fibrillar types COL1A1/2 and COL5A1; the receptor tyrosine kinase discoidin domain-containing receptor 2 (DDR2), a receptor for fibrillar collagens; and lysyl oxidase-like 2 (LOXL2), an enzyme that promotes collagen crosslinking. Increased activity and/or expression of LOXL2 and DDR2 in CAF were confirmed by enzymatic assays and Western blotting analyses. Pharmacological inhibition of CAF-derived LOXL2 perturbed extracellular matrix (ECM) organization and decreased CAF migration in a wound healing assay. Further, it significantly impaired the motility of co-cultured RWPE-2 prostate tumor epithelial cells. These results indicate that CAF-derived LOXL2 is an important mediator of intercellular communication within the prostate tumor microenvironment and is a potential therapeutic target.

Combining Rapid Data Independent Acquisition and CRISPR Gene Deletion for Studying Potential Protein Functions: A Case of HMGN1

CRISPR-Cas gene editing holds substantial promise in many biomedical disciplines and basic research. Due to the important functional implications of non-histone chromosomal protein HMG-14 (HMGN1) in regulating chromatin structure and tumor immunity, gene knockout of HMGN1 is performed by CRISPR in cancer cells and the following proteomic regulation events are studied. In particular, DIA mass spectrometry (DIA-MS) is utilized, and more than 6200 proteins (protein- FDR 1%) and more than 82 000 peptide precursors are reproducibly measured in the single MS shots of 2 h. HMGN1 protein deletion is confidently verified by DIA-MS in all of the clone- and dish- replicates following CRISPR. Statistical analysis reveals 147 proteins change their expressions significantly after HMGN1 knockout. Functional annotation and enrichment analysis indicate the deletion of HMGN1 induces histone inactivation, various stress pathways, remodeling of extracellular proteomes, cell proliferation, as well as immune regulation processes such as complement and coagulation cascade and interferon alpha/ gamma response in cancer cells. These results shed new lights on the cellular functions of HMGN1. It is suggested that DIA-MS can be reliably used as a rapid, robust, and cost-effective proteomic-screening tool to assess the outcome of the CRISPR experiments.

Identification of potential metabolic biomarkers of polycystic ovary syndrome in follicular fluid by SWATH mass spectrometry

BACKGROUND

Polycystic ovary syndrome (PCOS) is a complex disorder associated with multiple metabolic disturbance, including defective glucose metabolism and insulin resistance. The altered metabolites caused by the related metabolic disturbance may affect ovarian follicles, which can be reflected in follicular fluid composition. The aim of this study is to investigate follicular fluid metabolic profiles in women with PCOS using an advanced sequential window acquisition of all theoretical fragment-ion spectra (SWATH) mass spectrometry.

MATERIALS AND METHODS

Nineteen women with PCOS and twenty-one healthy controls undergoing IVF/ET were recruited, and their follicular fluid samples were collected for metabolomic study. Follicular fluid metabolic profiles, including steroid hormones, free fatty acids, bioactive lipids, and amino acids were analyzed using the principal component analysis (PCA) and partial least squares to latent structure-discriminant analysis (PLS-DA) model.

RESULTS

Levels of free fatty acids, 3-hydroxynonanoyl carnitine and eicosapentaenoic acid were significantly increased (P < 0.05), whereas those of bioactive lipids, lysophosphatidylcholines (LysoPC) (16:0), phytosphingosine, LysoPC (14:0) and LysoPC (18:0) were significantly decreased in women with PCOS (P < 0.05). Additionally, levels of steroid hormone deoxycorticosterone and two amino acids, phenylalanine and leucine were higher in the PCOS patients (P < 0.05).

CONCLUSION

Women with PCOS display unique metabolic profiles in their follicular fluid, and this data may provide us with important biochemical information and metabolic signatures that enable a better understanding of the pathogenesis of PCOS.

Comprehensive Target Analysis for 484 Organic Micropollutants in Environmental Waters by the Combination of Tandem Solid-Phase Extraction and Quadrupole Time-of-Flight Mass Spectrometry with Sequential Window Acquisition of All Theoretical Fragment-Ion Spectra Acquisition

There are many thousands of chemicals in use for a wide range of purposes, and highly efficient analytical methods are required to monitor them for protection of the environment. In order to cope with this difficult task we developed a novel, comprehensive method for 484 substances in water samples. In this method target chemicals were extracted by tandem SPE and then determined by LC-QTOF-MS-SWATH. Targets were unambiguously identified using retention times, accurate masses of a precursor and two product ions, their ion ratios, and accurate MS/MS spectrum. Quantitation was achieved by the internal standard method using a precursor ion. Results of recovery tests at two concentrations (50 and 500 ng L^-1) showed average recoveries of 87.5% and 87.0% (RSD, 9.1% and 9.4%), respectively. Limits of detection of one-half of the targets were below 1.0 ng L^-1. The method was applied to the influent and effluent of a sewage treatment plant, and around 100 chemicals were detected. Results of examination on matrix effects using their extracts spiked with 209 pesticides showed that the ratios of detected amounts between the extracts and the standard solution were 89.8% (influent) and 91.7% (effluent), respectively. In addition, investigation on the stability of calibration curves by injecting the same standards for 1 year showed that their quantitative results did not change; average accuracy was 103.3% (RSD, 10.0%), indicating that the calibration curves can be used for an extended period of time without calibration, and quantitative retrospective analysis can be done after creating calibration curves for new targets.

Comparative analysis of mRNA and protein degradation in prostate tissues indicates high stability of proteins

Deterioration of biomolecules in clinical tissues is an inevitable pre-analytical process, which affects molecular measurements and thus potentially confounds conclusions from cohort analyses. Here, we investigate the degradation of mRNA and protein in 68 pairs of adjacent prostate tissue samples using RNA-Seq and SWATH mass spectrometry, respectively. To objectively quantify the extent of protein degradation, we develop a numerical score, the Proteome Integrity Number (PIN), that faithfully measures the degree of protein degradation. Our results indicate that protein degradation only affects 5.9% of the samples tested and shows negligible correlation with mRNA degradation in the adjacent samples. These findings are confirmed by independent analyses on additional clinical sample cohorts and across different mass spectrometric methods. Overall, the data show that the majority of samples tested are not compromised by protein degradation, and establish the PIN score as a generic and accurate indicator of sample quality for proteomic analyses.

Protein degradation in clinical samples is largely unexplored. Here, the authors analyze the transcriptome and proteome of clinical tissue samples and develop an algorithm to assess protein degradation, showing that protein degradation is negligible in most tissue samples and does not correlate with transcript degradation.

Oncoproteomics: Current status and future opportunities

Oncoproteomics is the systematic study of cancer samples using omics technologies to detect changes implicated in tumorigenesis. Recent progress in oncoproteomics is already opening new avenues for the identification of novel biomarkers for early clinical stage cancer detection, targeted molecular therapies, disease monitoring, and drug development. Such information will lead to new understandings of cancer biology and impact dramatically on the future care of cancer patients. In this review, we will summarize the advantages and limitations of the key technologies used in (onco)proteogenomics, (the Omics Pipeline), explain how they can assist us in understanding the biology behind the overarching "Hallmarks of Cancer", discuss how they can advance the development of precision/personalised medicine and the future directions in the field.

First Community-Wide, Comparative Cross-Linking Mass Spectrometry Study

The number of publications in the field of chemical cross-linking combined with mass spectrometry (XL-MS) to derive constraints for protein three-dimensional structure modeling and to probe protein-protein interactions has increased during the last years. As the technique is now becoming routine for in vitro and in vivo applications in proteomics and structural biology there is a pressing need to define protocols as well as data analysis and reporting formats. Such consensus formats should become accepted in the field and be shown to lead to reproducible results. This first, community-based harmonization study on XL-MS is based on the results of 32 groups participating worldwide. The aim of this paper is to summarize the status quo of XL-MS and to compare and evaluate existing cross-linking strategies. Our study therefore builds the framework for establishing best practice guidelines to conduct cross-linking experiments, perform data analysis, and define reporting formats with the ultimate goal of assisting scientists to generate accurate and reproducible XL-MS results.

Reductive Stress Selectively Disrupts Collagen Homeostasis and Modifies Growth Factor-independent Signaling Through the MAPK/Akt Pathway in Human Dermal Fibroblasts

Redox stress is a well-known contributor to aging and diseases in skin. Reductants such as dithiothreitol (DTT) can trigger a stress response by disrupting disulfide bonds. However, the quantitative response of the cellular proteome to reductants has not been explored, particularly in cells such as fibroblasts that produce extracellular matrix proteins. Here, we have used a robust, unbiased, label-free SWATH-MS proteomic approach to quantitate the response of skin fibroblast cells to DTT in the presence or absence of the growth factor PDGF. Of the 4487 proteins identified, only 42 proteins showed a statistically significant change of 2-fold or more with reductive stress. Our proteomics data show that reductive stress results in the loss of a small subset of reductant-sensitive proteins (including the collagens COL1A1/2 and COL3A1, and the myopathy-associated collagens COL6A1/2/3), and the down-regulation of targets downstream of the MAPK pathway. We show that a reducing environment alters signaling through the PDGF-associated MAPK/Akt pathways, inducing chronic dephosphorylation of ERK1/2 at Thr202/Tyr204 and phosphorylation of Akt at Ser473 in a growth factor-independent manner. Our data highlights collagens as sentinel molecules for redox stress downstream of MAPK/Akt, and identifies intervention points to modulate the redox environment to target skin diseases and conditions associated with erroneous matrix deposition.

Proteomics and phosphoproteomics in precision medicine: applications and challenges

Recent advances in proteomics allow the accurate measurement of abundances for thousands of proteins and phosphoproteins from multiple samples in parallel. Therefore, for the first time, we have the opportunity to measure the proteomic profiles of thousands of patient samples or disease model cell lines in a systematic way, to identify the precise underlying molecular mechanism and discover personalized biomarkers, networks and treatments. Here, we review examples of successful use of proteomics and phosphoproteomics data sets in as well as their integration other omics data sets with the aim of precision medicine. We will discuss the bioinformatics challenges posed by the generation, analysis and integration of such large data sets and present potential reasons why proteomics profiling and biomarkers are not currently widely used in the clinical setting. We will finally discuss ways to contribute to the better use of proteomics data in precision medicine and the clinical setting.

Regulation of UCP1 and Mitochondrial Metabolism in Brown Adipose Tissue by Reversible Succinylation

Brown adipose tissue (BAT) is rich in mitochondria and plays important roles in energy expenditure, thermogenesis, and glucose homeostasis. We find that levels of mitochondrial protein succinylation and malonylation are high in BAT and subject to physiological and genetic regulation. BAT-specific deletion of Sirt5, a mitochondrial desuccinylase and demalonylase, results in dramatic increases in global protein succinylation and malonylation. Mass spectrometry-based quantification of succinylation reveals that Sirt5 regulates the key thermogenic protein in BAT, UCP1. Mutation of the two succinylated lysines in UCP1 to acyl-mimetic glutamine and glutamic acid significantly decreases its stability and activity. The reduced function of UCP1 and other proteins in Sirt5KO BAT results in impaired mitochondria respiration, defective mitophagy, and metabolic inflexibility. Thus, succinylation of UCP1 and other mitochondrial proteins plays an important role in BAT and in regulation of energy homeostasis.

A new class of protein biomarkers based on subcellular distribution: application to a mouse liver cancer model

To-date, most proteomic studies aimed at discovering tissue-based cancer biomarkers have compared the quantity of selected proteins between case and control groups. However, proteins generally function in association with other proteins to form modules localized in particular subcellular compartments in specialized cell types and tissues. Sub-cellular mislocalization of proteins has in fact been detected as a key feature in a variety of cancer cells. Here, we describe a strategy for tissue-biomarker detection based on a mitochondrial fold enrichment (mtFE) score, which is sensitive to protein abundance changes as well as changes in subcellular distribution between mitochondria and cytosol. The mtFE score integrates protein abundance data from total cellular lysates and mitochondria-enriched fractions, and provides novel information for the classification of cancer samples that is not necessarily apparent from conventional abundance measurements alone. We apply this new strategy to a panel of wild-type and mutant mice with a liver-specific gene deletion of Liver receptor homolog 1 (Lrh-1^hep−/−), with both lines containing control individuals as well as individuals with liver cancer induced by diethylnitrosamine (DEN). Lrh-1 gene deletion attenuates cancer cell metabolism in hepatocytes through mitochondrial glutamine processing. We show that proteome changes based on mtFE scores outperform protein abundance measurements in discriminating DEN-induced liver cancer from healthy liver tissue, and are uniquely robust against genetic perturbation. We validate the capacity of selected proteins with informative mtFE scores to indicate hepatic malignant changes in two independent mouse models of hepatocellular carcinoma (HCC), thus demonstrating the robustness of this new approach to biomarker research. Overall, the method provides a novel, sensitive approach to cancer biomarker discovery that considers contextual information of tested proteins.

Measuring Amber Initiator tRNA Orthogonality in a Genomically Recoded Organism

Using engineered initiator tRNA for precise control of protein translation within cells has great promise within future orthogonal translation systems to decouple housekeeping protein metabolism from that of engineered genetic systems. Previously, E. coli strain C321.ΔA. exp lacking all UAG stop codons was created, freeing this "amber" stop codon for other purposes. An engineered "amber initiator" tRNA_CUA^fMet that activates translation at UAG codons is available, but little is known about this tRNA's orthogonality. Here, we combine for the first time the amber initiator tRNA_CUA^fMet in C321.ΔA. exp and measure its cellular effects. We found that the tRNA_CUA^fMet expression resulted in a nearly 200-fold increase in fluorescent reporter expression with a unimodal population distribution and no apparent cellular fitness defects. Proteomic analysis revealed upregulated ribosome-associated, tRNA degradation, and amino acid biosynthetic proteins, with no evidence for off-target translation initiation. In contrast to previous work, we show that UAG-initiated proteins carry N-terminal methionine, but have no evidence for glutamine. Together, our results identify beneficial features of using the amber initiator tRNA_CUA^fMet to control gene expression while also revealing fundamental challenges to using engineered initiator tRNAs as the basis for orthogonal translation initiation systems.

Data Independent Acquisition Mass Spectrometry Method for Improved Neuropeptidomic Coverage in Crustacean Neural Tissue Extracts

Neuropeptides are an important class of signaling molecules in the nervous and neuroendocrine system, but they are challenging to study due to their low concentration in vivo in the presence of numerous interfering artifacts. Often the limitation of mass spectrometry analyses of neuropeptides in complex tissue extracts is not due to neuropeptides being below the detection limit but due to ions not being selected for tandem mass spectrometry during the liquid chromatography elution time and therefore not being identified. In this study, a data independent acquisition (DIA) method was developed to improve the coverage of neuropeptides in neural tissue from the model organism C. borealis. The optimal mass-to-charge ratio range and isolation window were determined and subsequently used to detect more neuropeptides in extracts from the brain and pericardial organs than the conventional data dependent acquisition method. The DIA method led to the detection of almost twice as many neuropeptides in the brain and approximately 1.5-fold more neuropeptides in the pericardial organs. The technical and biological reproducibility were also explored and found to be improved over the original method, with 56% of neuropeptides detected in 3 out of 3 replicate injections and 62% in 3 out of 3 biological replicates. Furthermore, 68 putative novel neuropeptides were detected and identified with de novo sequencing. The quantitative accuracy of the method was also explored. The developed method is anticipated to be useful for gaining a deeper profiling of neuropeptides, especially those in low abundance, in a variety of sample types.

Global Lysine Acetylation in Escherichia coli Results from Growth Conditions That Favor Acetate Fermentation

Lysine acetylation is thought to provide a mechanism for regulating metabolism in diverse bacteria. Indeed, many studies have shown that the majority of enzymes involved in central metabolism are acetylated and that acetylation can alter enzyme activity. However, the details regarding this regulatory mechanism are still unclear, specifically with regard to the signals that induce lysine acetylation. To better understand this global regulatory mechanism, we profiled changes in lysine acetylation during growth of Escherichia coli on the hexose glucose or the pentose xylose at both high and low sugar concentrations using label-free mass spectrometry. The goal was to see whether lysine acetylation differed during growth on these two different sugars. No significant differences, however, were observed. Rather, the initial sugar concentration was the principal factor governing changes in lysine acetylation, with higher sugar concentrations causing more acetylation. These results suggest that acetylation does not target specific metabolic pathways but rather simply targets accessible lysines, which may or may not alter enzyme activity. They further suggest that lysine acetylation principally results from conditions that favor accumulation of acetyl phosphate, the principal acetate donor in E. coli IMPORTANCE Bacteria alter their metabolism in response to nutrient availability, growth conditions, and environmental stresses using a number of different mechanisms. One is lysine acetylation, a posttranslational modification known to target many metabolic enzymes. However, little is known about this regulatory mode. We investigated the factors inducing changes in lysine acetylation by comparing growth on glucose and xylose. We found that the specific sugar used for growth did not alter the pattern of acetylation; rather, the amount of sugar did, with more sugar causing more acetylation. These results imply that lysine acetylation is a global regulatory mechanism that is responsive not to the specific carbon source per se but rather to the accumulation of downstream metabolites.

Proteome Analysis of Human Neutrophil Granulocytes From Patients With Monogenic Disease Using Data-independent Acquisition

Neutrophil granulocytes are critical mediators of innate immunity and tissue regeneration. Rare diseases of neutrophil granulocytes may affect their differentiation and/or functions. However, there are very few validated diagnostic tests assessing the functions of neutrophil granulocytes in these diseases. Here, we set out to probe omics analysis as a novel diagnostic platform for patients with defective differentiation and function of neutrophil granulocytes. We analyzed highly purified neutrophil granulocytes from 68 healthy individuals and 16 patients with rare monogenic diseases. Cells were isolated from fresh venous blood (purity >99%) and used to create a spectral library covering almost 8000 proteins using strong cation exchange fractionation. Patient neutrophil samples were then analyzed by data-independent acquisition proteomics, quantifying 4154 proteins in each sample. Neutrophils with mutations in the neutrophil elastase gene ELANE showed large proteome changes that suggest these mutations may affect maturation of neutrophil granulocytes and initiate misfolded protein response and cellular stress mechanisms. In contrast, only few proteins changed in patients with leukocyte adhesion deficiency (LAD) and chronic granulomatous disease (CGD). Strikingly, neutrophil transcriptome analysis showed no correlation with its proteome. In case of two patients with undetermined genetic causes, proteome analysis guided the targeted genetic diagnostics and uncovered the underlying genomic mutations. Data-independent acquisition proteomics may help to define novel pathomechanisms in neutrophil diseases and provide a clinically useful diagnostic dimension.

Label-free absolute protein quantification with data-independent acquisition

Despite data-independent acquisition (DIA) has been increasingly used for relative protein quantification, DIA-based label-free absolute quantification method has not been fully established. Here we present a novel DIA method using the TPA algorithm (DIA-TPA) for the absolute quantification of protein expressions in human liver microsomal and S9 samples. To validate this method, both data-dependent acquisition (DDA) and DIA experiments were conducted on 36 individual human liver microsome and S9 samples. The MS2-based DIA-TPA was able to quantify approximately twice as many proteins as the MS1-based DDA-TPA method, whereas protein concentrations determined by the two approaches were comparable. To evaluate the accuracy of the DIA-TPA method, we absolutely quantified carboxylesterase 1 concentrations in human liver S9 fractions using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-TPA analysis. Finally, we employed a unique algorithm in DIA-TPA to distribute the MS signals from shared peptides to individual proteins or isoforms and successfully applied the method to the absolute quantification of several drug-metabolizing enzymes in human liver microsomes. In sum, the DIA-TPA method not only can absolutely quantify entire proteomes and specific proteins, but also has the capability quantifying proteins with shared peptides. SIGNIFICANCE: Data independent acquisition (DIA) has emerged as a powerful approach for relative protein quantification at the whole proteome level. However, DIA-based label-free absolute protein quantification (APQ) method has not been fully established. In the present study, we present a novel DIA-based label-free APQ approach, named DIA-TPA, with the capability absolutely quantifying proteins with shared peptides. The method was validated by comparing the quantification results of DIA-TPA with that obtained from stable isotope-labeled internal standard-based proteomic assays.

Data-independent acquisition-based quantitative proteomic analysis reveals differences in host immune response of peripheral blood mononuclear cells to sepsis

This study was aimed to uncover proteins that are differentially expressed in sepsis. Data-independent acquisition (DIA) was used for analysis to identify differentially expressed proteins in peripheral blood mononuclear cells (PBMCs) of patients. A total of 24 non-septic intensive care unit (ICU) patients, 11 septic shock patients and 27 patients diagnosed with sepsis were recruited for the mass spectrometry (MS) discovery. PBMCs were isolated from routine blood samples and digested into peptides. A DIA workflow was developed using a quadrupole-Orbitrap liquid chromatography LC-MS system, and mass spectra peaks were extracted by Skyline software. Orthogonal partial least-squares discriminant analysis (OPLS-DA) and partial least-squares discriminant analysis (PLS-DA) were applied to distinguish the patient groups at the level of fragment ion and peptide. Differentially expressed proteins in the patient groups were verified by enzyme-linked immunosorbent assay (ELISA). Receiver-operating characteristic (ROC) curves were used to evaluate the protein expression. A total of 1062 fragment ions and 122 proteins were identified in the MS-DIA analysis conducted by Skyline software. Using gene ontology clustering analysis, we discovered that 51 of the 122 identified proteins were associated with biological processes, including carbon metabolism, biosynthesis of antibiotics, platelet activation, bacterial invasion of epithelial cells and complement, and coagulation cascades. Among them, five proteins (high-mobility group box1 [HMGB1], matrix metalloproteinase 8 [MMP8], neutrophil gelatinase-associated lipocalin [NGAL], lactotransferrin [LTF] and grancalcin [GCA]) were identified by ELISA as closely related to the development of sepsis. The ROC curves displayed good sensitivity and specificity.

A rapid methods development workflow for high-throughput quantitative proteomic applications

Recent improvements in the speed and sensitivity of liquid chromatography-mass spectrometry systems have driven significant progress toward system-wide characterization of the proteome of many species. These efforts create large proteomic datasets that provide insight into biological processes and identify diagnostic proteins whose abundance changes significantly under different experimental conditions. Yet, these system-wide experiments are typically the starting point for hypothesis-driven, follow-up experiments to elucidate the extent of the phenomenon or the utility of the diagnostic marker, wherein many samples must be analyzed. Transitioning from a few discovery experiments to quantitative analyses on hundreds of samples requires significant resources both to develop sensitive and specific methods as well as analyze them in a high-throughput manner. To aid these efforts, we developed a workflow using data acquired from discovery proteomic experiments, retention time prediction, and standard-flow chromatography to rapidly develop targeted proteomic assays. We demonstrated this workflow by developing MRM assays to quantify proteins of multiple metabolic pathways from multiple microbes under different experimental conditions. With this workflow, one can also target peptides in scheduled/dynamic acquisition methods from a shotgun proteomic dataset downloaded from online repositories, validate with appropriate control samples or standard peptides, and begin analyzing hundreds of samples in only a few minutes.

Generation of a zebrafish SWATH-MS spectral library to quantify 10,000 proteins

Sequential window acquisition of all theoretical mass spectra (SWATH-MS) requires a spectral library to extract quantitative measurements from the mass spectrometry data acquired in data-independent acquisition mode (DIA). Large combined spectral libraries containing SWATH assays have been generated for humans and several other organisms, but so far no publicly available library exists for measuring the proteome of zebrafish, a rapidly emerging model system in biomedical research. Here, we present a large zebrafish SWATH spectral library to measure the abundance of 104,185 proteotypic peptides from 10,405 proteins. The library includes proteins expressed in 9 different zebrafish tissues (brain, eye, heart, intestine, liver, muscle, ovary, spleen, and testis) and provides an important new resource to quantify 40% of the protein-coding zebrafish genes. We employ this resource to quantify the proteome across brain, muscle, and liver and characterize divergent expression levels of paralogous proteins in different tissues. Data are available via ProteomeXchange (PXD010876, PXD010869) and SWATHAtlas (PASS01237).

Comparing SRM and SWATH Methods for Quantitation of Bovine Muscle Proteomes

Mass spectrometry (MS) has become essential for efficient and accurate quantification of proteins and proteomes and, thus, a key technology throughout all biosciences. However, validated MS methods are still scarce for meat quality research applications. The objective of this work was to develop and compare two targeted proteomic methods, namely, selected reaction monitoring (SRM) and sequential window acquisition of all theoretical spectra (SWATH), for the quantification of 11 bovine muscle proteins that may be indicators of meat color. Both methods require evaluation of spectra from proteotypic and quantotypic peptides, and we here report our evaluation of which peptides and MS parameters are best suited for robust quantification of these 11 proteins. We observed that the SRM approach provides better reproducibility, linearity, and sensitivity than SWATH and is therefore ideal for targeted quantification of low-abundance proteins, while the SWATH approach provides a more time-efficient method for targeted protein quantification of high-abundance proteins and, additionally, supports the search for novel biomarkers.

Complex-centric proteome profiling by SEC-SWATH-MS

Proteins are major effectors and regulators of biological processes that can elicit multiple functions depending on their interaction with other proteins. The organization of proteins into macromolecular complexes and their quantitative distribution across these complexes is, therefore, of great biological and clinical significance. In this paper, we describe an integrated experimental and computational technique to quantify hundreds of protein complexes in a single operation. The method consists of size exclusion chromatography (SEC) to fractionate native protein complexes, SWATH/DIA mass spectrometry to precisely quantify the proteins in each SEC fraction, and the computational framework CCprofiler to detect and quantify protein complexes by error‐controlled, complex‐centric analysis using prior information from generic protein interaction maps. Our analysis of the HEK293 cell line proteome delineates 462 complexes composed of 2,127 protein subunits. The technique identifies novel sub‐complexes and assembly intermediates of central regulatory complexes while assessing the quantitative subunit distribution across them. We make the toolset CCprofiler freely accessible and provide a web platform, SECexplorer, for custom exploration of the HEK293 proteome modularity.

Discovery and Qualification of Candidate Urinary Biomarkers of Disease Activity in Lupus Nephritis

Lupus nephritis (LN) is a severe clinical manifestation of systemic lupus erythematosus (SLE) associated with significant morbidity and mortality. Assessment of severity and activity of renal involvement in SLE requires a kidney biopsy, an invasive procedure with limited prognostic value. Noninvasive biomarkers are needed to inform treatment decisions and to monitor disease activity. Proteinuria is associated with disease progression in LN; however, the composition of the LN urinary proteome remains incompletely characterized. To address this, we profiled LN urine samples using complementary mass spectrometry-based methods:  protein gel fractionation, chemical labeling using tandem mass tags, and data-independent acquisition. Combining results from these approaches yielded quantitative information on 2573 unique proteins in urine from LN patients. A multiple-reaction monitoring (MRM) method was established to confirm eight proteins in an independent cohort of LN patients, and seven proteins (transferrin, α-2-macroglobulin, haptoglobin, afamin, α-1-antitrypsin, vimentin, and ceruloplasmin) were confirmed to be elevated in LN urine compared to healthy controls. In this study, we demonstrate that deep mass spectrometry profiling of a small number of patient samples can identify high-quality biomarkers that replicate in an independent LN disease cohort. These biomarkers are being used to inform clinical biomarker strategies to support longitudinal and interventional studies focused on evaluating disease progression and treatment efficacy of novel LN therapeutics.

An Overview of Mass Spectrometry-Based Methods for Functional Proteomics

The mechanism underlying many biological phenotypes remains unknown despite the increasing availability of whole genome and transcriptome sequencing. Direct measurement of changes in protein expression is an attractive alternative and has the potential to reveal novel processes. Mass spectrometry has become the standard method for proteomics, allowing both the confident identification and quantification of thousands of proteins from biological samples. In this review, mass spectrometry-based proteomic methods and their applications are described.

Immunoproteomics Methods and Techniques

The varied landscape of the adaptive immune response is determined by the peptides presented by immune cells, derived from viral or microbial pathogens or cancerous cells. The study of immune biomarkers or antigens is not new, and classical methods such as agglutination, enzyme-linked immunosorbent assay, or Western blotting have been used for many years to study the immune response to vaccination or disease. However, in many of these traditional techniques, protein or peptide identification has often been the bottleneck. Recent progress in genomics and mass spectrometry have led to many of the rapid advances in proteomics approaches. Immunoproteomics describes a rapidly growing collection of approaches that have the common goal of identifying and measuring antigenic peptides or proteins. This includes gel-based, array-based, mass spectrometry-based, DNA-based, or in silico approaches. Immunoproteomics is yielding an understanding of disease and disease progression, vaccine candidates, and biomarkers. This review gives an overview of immunoproteomics and closely related technologies that are used to define the full set of protein antigens targeted by the immune system during disease.

Surpassing 10 000 identified and quantified proteins in a single run by optimizing current LC-MS instrumentation and data analysis strategy

Optimization of chromatography and data analysis resulted in more than 10 000 proteins in a single shot at a validated FDR of 1% (two-species test) and revealed deep insights into the testis cancer physiology.

Optimization of Protein-Protein Interaction Measurements for Drug Discovery Using AFM Force Spectroscopy

Increasingly targeted in drug discovery, protein-protein interactions challenge current high throughput screening technologies in the pharmaceutical industry. Developing an effective and efficient method for screening small molecules or compounds is critical to accelerate the discovery of ligands for enzymes, receptors and other pharmaceutical targets. Here, we report developments of methods to increase the signal-to-noise ratio (SNR) for screening protein-protein interactions using atomic force microscopy (AFM) force spectroscopy. We have demonstrated the effectiveness of these developments on detecting the binding process between focal adhesion kinases (FAK) with protein kinase B (Akt1), which is a target for potential cancer drugs. These developments include optimized probe and substrate functionalization processes and redesigned probe-substrate contact regimes. Furthermore, a statistical-based data processing method was developed to enhance the contrast of the experimental data. Collectively, these results demonstrate the potential of the AFM force spectroscopy in automating drug screening with high throughput.

Temporal dynamics of liver mitochondrial protein acetylation and succinylation and metabolites due to high fat diet and/or excess glucose or fructose

Dietary macronutrient composition alters metabolism through several mechanisms, including post-translational modification (PTM) of proteins. To connect diet and molecular changes, here we performed short- and long-term feeding of mice with standard chow diet (SCD) and high-fat diet (HFD), with or without glucose or fructose supplementation, and quantified liver metabolites, 861 proteins, and 1,815 protein level-corrected mitochondrial acetylation and succinylation sites. Nearly half the acylation sites were altered by at least one diet; nutrient-specific changes in protein acylation sometimes encompass entire pathways. Although acetyl-CoA is an intermediate in both sugar and fat metabolism, acetyl-CoA had a dichotomous fate depending on its source; chronic feeding of dietary sugars induced protein hyperacetylation, whereas the same duration of HFD did not. Instead, HFD resulted in citrate accumulation, anaplerotic metabolism of amino acids, and protein hypo-succinylation. Together, our results demonstrate novel connections between dietary macronutrients, protein post-translational modifications, and regulation of fuel selection in liver.

Data-Independent Acquisition Mass Spectrometry To Quantify Protein Levels in FFPE Tumor Biopsies for Molecular Diagnostics

Mass spectrometry-based protein quantitation is currently used to measure therapeutically relevant protein biomarkers in CAP/CLIA setting to predict likely responses of known therapies. Selected reaction monitoring (SRM) is the method of choice due to its outstanding analytical performance. However, data-independent acquisition (DIA) is now emerging as a proteome-scale clinical assay. We evaluated the ability of DIA to profile the patient-specific proteomes of sample-limited tumor biopsies and to quantify proteins of interest in a targeted fashion using formalin-fixed, paraffin-embedded (FFPE) tumor biopsies ( n = 12) selected from our clinical laboratory. DIA analysis on the tumor biopsies provided 3713 quantifiable proteins including actionable biomarkers currently in clinical use, successfully separated two gastric cancers from colorectal cancer specimen solely on the basis of global proteomic profiles, and identified subtype-specific proteins with prognostic or diagnostic value. We demonstrate the potential use of DIA-based quantitation to inform therapeutic decision-making using TUBB3, for which clinical cutoff expression levels have been established by SRM. Comparative analysis of DIA-based proteomic profiles and mRNA expression levels found positively and negatively correlated protein-gene pairs, a finding consistent with previously reported results from fresh-frozen tumor tissues.

Obesity shows preserved plasma proteome in large independent clinical cohorts

Holistic human proteome maps are expected to complement comprehensive profile assessment of health and disease phenotypes. However, methodologies to analyze proteomes in human tissue or body fluid samples at relevant scale and performance are still limited in clinical research. Their deployment and demonstration in large enough human populations are even sparser. In the present study, we have characterized and compared the plasma proteomes of two large independent cohorts of obese and overweight individuals using shotgun mass spectrometry (MS)-based proteomics. Herein, we showed, in both populations from different continents of about 500 individuals each, the concordance of plasma protein MS measurements in terms of variability, gender-specificity, and age-relationship. Additionally, we replicated several known and new associations between proteins, clinical and molecular variables, such as insulin and glucose concentrations. In conclusion, our MS-based analyses of plasma samples from independent human cohorts proved the practical feasibility and efficiency of a large and unified discovery/replication approach in proteomics, which was also recently coined “rectangular” design.

The codon sequences predict protein lifetimes and other parameters of the protein life cycle in the mouse brain

The homeostasis of the proteome depends on the tight regulation of the mRNA and protein abundances, of the translation rates, and of the protein lifetimes. Results from several studies on prokaryotes or eukaryotic cell cultures have suggested that protein homeostasis is connected to, and perhaps regulated by, the protein and the codon sequences. However, this has been little investigated for mammals in vivo. Moreover, the link between the coding sequences and one critical parameter, the protein lifetime, has remained largely unexplored, both in vivo and in vitro. We tested this in the mouse brain, and found that the percentages of amino acids and codons in the sequences could predict all of the homeostasis parameters with a precision approaching experimental measurements. A key predictive element was the wobble nucleotide. G-/C-ending codons correlated with higher protein lifetimes, protein abundances, mRNA abundances and translation rates than A-/U-ending codons. Modifying the proportions of G-/C-ending codons could tune these parameters in cell cultures, in a proof-of-principle experiment. We suggest that the coding sequences are strongly linked to protein homeostasis in vivo, albeit it still remains to be determined whether this relation is causal in nature.