Software tools for MS-based quantitative proteomics: a brief overview

Mass spectrometry-based proteomics approaches to interrogate skeletal muscle adaptations to exercise

Acute exercise and chronic exercise training elicit beneficial whole-body changes in physiology that ultimately depend on profound alterations to the dynamics of tissue-specific proteins. Since the work accomplished during exercise owes predominantly to skeletal muscle, it has received the majority of interest from exercise scientists that attempt to unravel adaptive mechanisms accounting for salutary metabolic effects and performance improvements that arise from training. Contemporary scientists are also beginning to use mass spectrometry-based proteomics, which is emerging as a powerful approach to interrogate the muscle protein signature in a more comprehensive manner. Collectively, these technologies facilitate the analysis of skeletal muscle protein dynamics from several viewpoints, including changes to intracellular proteins (expression proteomics), secreted proteins (secretomics), post-translational modifications as well as fiber-, cell-, and organelle-specific changes. This review aims to highlight recent literature that has leveraged new workflows and advances in mass spectrometry-based proteomics to further our understanding of training-related changes in skeletal muscle. We call attention to untapped areas in skeletal muscle proteomics research relating to exercise training and metabolism, as well as basic points of contention when applying mass spectrometry-based analyses, particularly in the study of human biology. We further encourage researchers to couple the hypothesis-generating and descriptive nature of omics data with functional analyses that propel our understanding of the complex adaptive responses in skeletal muscle that occur with acute and chronic exercise.

Quantitative Peptidomics: General Considerations

Peptidomics is the detection and identification of the peptides present in a sample, and quantitative peptidomics provides additional information about the amounts of these peptides. It is possible to perform absolute quantitation of peptide levels in which the biological sample is compared to synthetic standards of each peptide. More commonly, relative quantitation is performed to compare peptide levels between two or more samples. Relative quantitation can measure differences between all peptides that are detectable, which can exceed 1000 peptides in a complex sample. In this chapter, various techniques used for quantitative peptidomics are described along with discussion of the advantages and disadvantages of each approach. A guide to selecting the optimal quantitative approach is provided, based on the goals of the experiment and the resources that are available.

HLA-DO Modulates the Diversity of the MHC-II Self-peptidome

Presentation of antigenic peptides on MHC-II molecules is essential for tolerance to self and for initiation of immune responses against foreign antigens. DO (HLA-DO in humans, H2-O in mice) is a nonclassical MHC-II protein that has been implicated in control of autoimmunity and regulation of neutralizing antibody responses to viruses. These effects likely are related to a role of DO in selecting MHC-II epitopes, but previous studies examining the effect of DO on presentation of selected CD4 T cell epitopes have been contradictory. To understand how DO modulates MHC-II antigen presentation, we characterized the full spectrum of peptides presented by MHC-II molecules expressed by DO-sufficient and DO-deficient antigen-presenting cells in vivo and in vitro using quantitative mass spectrometry approaches. We found that DO controlled the diversity of the presented peptide repertoire, with a subset of peptides presented only when DO was expressed. Antigen-presenting cells express another nonclassical MHC-II protein, DM, which acts as a peptide editor by preferentially catalyzing the exchange of less stable MHC-II peptide complexes, and which is inhibited when bound to DO. Peptides presented uniquely in the presence of DO were sensitive to DM-mediated exchange, suggesting that decreased DM editing was responsible for the increased diversity. DO-deficient mice mounted CD4 T cell responses against wild-type antigen-presenting cells, but not vice versa, indicating that DO-dependent alterations in the MHC-II peptidome could be recognized by circulating T cells. These data suggest that cell-specific and regulated expression of HLA-DO serves to fine-tune MHC-II peptidomes, in order to enhance self-tolerance to a wide spectrum of epitopes while allowing focused presentation of immunodominant epitopes during an immune response.

Comparison of sample preparation techniques and data analysis for the LC-MS/MS-based identification of proteins in human follicular fluid

The proteomic analysis of complex body fluids by liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis requires the selection of suitable sample preparation techniques and optimal parameter settings in data analysis software packages to obtain reliable results. Proteomic analysis of follicular fluid, as a representative of a complex body fluid similar to serum or plasma, is difficult as it contains a vast amount of high abundant proteins and a variety of proteins with different concentrations. However, the accessibility of this complex body fluid for LC-MS/MS analysis is an opportunity to gain insights into the status, the composition of fertility-relevant proteins including immunological factors or for the discovery of new diagnostic and prognostic markers for, for example, the treatment of infertility. In this study, we compared different sample preparation methods (FASP, eFASP and in-solution digestion) and three different data analysis software packages (Proteome Discoverer with SEQUEST, Mascot and MaxQuant with Andromeda) combined with semi- and full-tryptic databank search options to obtain a maximum coverage of the follicular fluid proteome. We found that the most comprehensive proteome coverage is achieved by the eFASP sample preparation method using SDS in the initial denaturing step and the SEQUEST-based semi-tryptic data analysis. In conclusion, we have developed a fractionation-free methodical workflow for in depth LC-MS/MS-based analysis for the standardized investigation of human follicle fluid as an important representative of a complex body fluid. Taken together, we were able to identify a total of 1392 proteins in follicular fluid.

Oxidative cross-linking of proteins to DNA following ischemia-reperfusion injury

Myocardial infarction (MI) is a life-threatening condition that can occur when blood flow to the heart is interrupted due to a blockage in one or more of the coronary vessels. Current treatments of MI rapidly restore blood flow to the affected myocardium using thrombolytic agents or angioplasty. Adverse effects including inflammation, tissue necrosis, and ventricular dysfunction are, however, not uncommon following reperfusion therapy. These conditions are thought to be caused by a sudden influx of reactive oxygen species (ROS) to the affected myocardium. We employed the model of left anterior descending artery ligation/reperfusion surgery in a rat model to show that ischemia/reperfusion injury is associated with the formation of toxic DNA-protein cross-links (DPCs) in cardiomyocytes. Mass spectrometry based experiments have revealed that these conjugates were formed by a free radical mechanism and involved thymidine residues of DNA and tyrosine side chains of proteins (dT-Tyr). Quantitative proteomics experiments have identified nearly 90 proteins participating in hydroxyl radical-induced DPC formation, including ROS scavengers, contractile proteins, and regulators of apoptosis. Global proteome changes were less pronounced and included increased expression of mitochondrial proteins required for aerobic respiration and biomarkers of sarcomere breakdown following ischemia/reperfusion injury. Overall, our results are consistent with a model where sudden return of oxygen to ischemic tissues induces oxidative stress, inflammation, and the formation of DNA-protein cross-links that may contribute to reperfusion injury by desregulating gene expression and inducing cardiomyocyte death.

Quantitative Peptidomics: General Considerations

Peptidomics is the detection and identification of the peptides present in a sample, while quantitative peptidomics provides additional information about the amounts of these peptides. Comparison of peptide levels among two or more samples is termed relative quantitation. It is also possible to perform absolute quantitation of peptide levels in which the biological sample is compared to synthetic standards, which requires a separate standard for each peptide. In contrast, relative quantitation can compare levels of all peptides that are detectable in a sample, which can exceed 1000 peptides in a complex sample. In this chapter, various techniques used for quantitative peptidomics are described along with discussion of the advantages and disadvantages of each approach. A guide to selecting the optimal quantitative approach is provided, based on the goals of the experiment and the resources that are available.

Modifications to the composition of the hyphal outer layer of Aspergillus fumigatus modulates HUVEC proteins related to inflammatory and stress responses

Aspergillus fumigatus, the main etiologic agent causing invasive aspergillosis, can induce an inflammatory response and a prothrombotic phenotype upon contact with human umbilical vein endothelial cells (HUVECs). However, the fungal molecules involved in this endothelial response remain unknown. A. fumigatus hyphae produce an extracellular matrix composed of galactomannan, galactosaminogalactan and α-(1,3)-glucan. In this study, we investigated the consequences of UGM1 gene deletion in A. fumigatus, which produces a mutant with increased galactosaminogalactan production. The ∆ugm1 mutant exhibited an HUVEC-hyperadhesive phenotype and induced increased endothelial TNF-α secretion and tissue factor mRNA overexpression in this "semi-professional" immune host cell. Using a shotgun proteomics approach, we show that the A. fumigatus ∆ugm1 strain can modulate the levels of proteins in important endothelial pathways related to the inflammatory response mediated by TNF-α and to stress response pathways. Furthermore, a purified galactosaminogalactan fraction was also able to induce TNF-α secretion and the coincident HUVEC pathways regulated by the ∆ugm1 mutant, which overexpresses this component, as demonstrated by fluorescence microscopy. This work contributes new data regarding endothelial mechanisms in response to A. fumigatus infection.

SIGNIFICANCE

Invasive aspergillosis is the main opportunistic fungal infection described in neutropenic hematologic patients. One important clinical aspect of this invasive fungal infection is vascular thrombosis, which could be related, at least in part, to the activation of endothelial cells, as shown in previous reports from our group. It is known that direct contact between the A. fumigatus hyphal cell wall and the HUVEC cell surface is necessary to induce an endothelial prothrombotic phenotype and secretion of pro-inflammatory cytokines, though the cell surface components of this angioinvasive fungus that trigger this endothelial response are unknown. The present work employs a discovery-driven proteomics approach to reveal the role of one important cell wall polysaccharide of A. fumigatus, galactosaminogalactan, in the HUVEC interaction and the consequent mechanisms of endothelial activation. This is the first report of the overall panel of proteins related to the HUVEC response to a specific and purified cell wall component of the angioinvasive fungus A. fumigatus.

Designing biomedical proteomics experiments: state-of-the-art and future perspectives

With the current expanded technical capabilities to perform mass spectrometry-based biomedical proteomics experiments, an improved focus on the design of experiments is crucial. As it is clear that ignoring the importance of a good design leads to an unprecedented rate of false discoveries which would poison our results, more and more tools are developed to help researchers designing proteomic experiments. In this review, we apply statistical thinking to go through the entire proteomics workflow for biomarker discovery and validation and relate the considerations that should be made at the level of hypothesis building, technology selection, experimental design and the optimization of the experimental parameters.

Mass Spectrometry-Based Protein Quantification

Quantification of individual proteins and even entire proteomes is an important theme in proteomics research. Quantitative proteomics is an approach to obtain quantitative information about proteins in a sample. Compared to qualitative or semi-quantitative proteomics, this approach can provide more insight into the effects of a specific stimulus, such as a change in the expression level of a protein and its posttranslational modifications, or to a panel of proposed biomarkers in a given disease state. Proteomics methodologies, along with a variety of bioinformatics approaches, are a major tool in quantitative proteomics. As the theory and technological aspects underlying the proteomics methodologies will be extensively described in Chap. 20 , and protein identification as a prerequisite of quantification has been discussed in Chap. 17 , we will focus on the quantitative proteomics bioinformatics algorithms and software tools in this chapter. Our goal is to provide researchers and newcomers a rational framework to select suitable bioinformatics tools for data analysis, interpretation, and integration in protein quantification. Before doing so, a brief overview of quantitative proteomics is provided.

Protein Phosphorylation: A Major Switch Mechanism for Metabolic Regulation

Metabolism research is undergoing a renaissance because many diseases are increasingly recognized as being characterized by perturbations in intracellular metabolic regulation. Metabolic changes can be conferred through changes to the expression of metabolic enzymes, the concentrations of substrates or products that govern reaction kinetics, or post-translational modification (PTM) of the proteins that facilitate these reactions. On the 60th anniversary since its discovery, reversible protein phosphorylation is widely appreciated as an essential PTM regulating metabolism. With the ability to quantitatively measure dynamic changes in protein phosphorylation on a global scale - hereafter referred to as phosphoproteomics - we are now entering a new era in metabolism research, with mass spectrometry (MS)-based proteomics at the helm.

Generation of multiple reporter ions from a single isobaric reagent increases multiplexing capacity for quantitative proteomics

Isobaric labeling strategies for mass spectrometry-based proteomics enable multiplexed simultaneous quantification of samples and therefore substantially increase the sample throughput in proteomics. However, despite these benefits, current limits to multiplexing capacity are prohibitive for large sample sizes and impose limitations on experimental design. Here, we introduce a novel mechanism for increasing the multiplexing density of isobaric reagents. We present Combinatorial Isobaric Mass Tags (CMTs), an isobaric labeling architecture with the unique ability to generate multiple series of reporter ions simultaneously. We demonstrate that utilization of multiple reporter ion series improves multiplexing capacity of CMT with respect to a commercially available isobaric labeling reagent with preserved quantitative accuracy and depth of coverage in complex mixtures. We provide a blueprint for the realization of 16-plex reagents with 1 Da spacing between reporter ions and up to 28-plex at 6 mDa spacing using only 5 heavy isotopes per reagent. We anticipate that this improvement in multiplexing capacity will further advance the application of quantitative proteomics, particularly in high-throughput screening assays.

The application of Gaussian mixture models for signal quantification in MALDI-TOF mass spectrometry of peptides

Matrix assisted laser desorption/ionization time-of-flight (MALDI-TOF) coupled with stable isotope standards (SIS) has been used to quantify native peptides. This peptide quantification by MALDI-TOF approach has difficulties quantifying samples containing peptides with ion currents in overlapping spectra. In these overlapping spectra the currents sum together, which modify the peak heights and make normal SIS estimation problematic. An approach using Gaussian mixtures based on known physical constants to model the isotopic cluster of a known compound is proposed here. The characteristics of this approach are examined for single and overlapping compounds. The approach is compared to two commonly used SIS quantification methods for single compound, namely Peak Intensity method and Riemann sum area under the curve (AUC) method. For studying the characteristics of the Gaussian mixture method, Angiotensin II, Angiotensin-2-10, and Angiotenisn-1-9 and their associated SIS peptides were used. The findings suggest, Gaussian mixture method has similar characteristics as the two methods compared for estimating the quantity of isolated isotopic clusters for single compounds. All three methods were tested using MALDI-TOF mass spectra collected for peptides of the renin-angiotensin system. The Gaussian mixture method accurately estimated the native to labeled ratio of several isolated angiotensin peptides (5.2% error in ratio estimation) with similar estimation errors to those calculated using peak intensity and Riemann sum AUC methods (5.9% and 7.7%, respectively). For overlapping angiotensin peptides, (where the other two methods are not applicable) the estimation error of the Gaussian mixture was 6.8%, which is within the acceptable range. In summary, for single compounds the Gaussian mixture method is equivalent or marginally superior compared to the existing methods of peptide quantification and is capable of quantifying overlapping (convolved) peptides within the acceptable margin of error.

Proteomics for systems toxicology

Current toxicology studies frequently lack measurements at molecular resolution to enable a more mechanism-based and predictive toxicological assessment. Recently, a systems toxicology assessment framework has been proposed, which combines conventional toxicological assessment strategies with system-wide measurement methods and computational analysis approaches from the field of systems biology. Proteomic measurements are an integral component of this integrative strategy because protein alterations closely mirror biological effects, such as biological stress responses or global tissue alterations. Here, we provide an overview of the technical foundations and highlight select applications of proteomics for systems toxicology studies. With a focus on mass spectrometry-based proteomics, we summarize the experimental methods for quantitative proteomics and describe the computational approaches used to derive biological/mechanistic insights from these datasets. To illustrate how proteomics has been successfully employed to address mechanistic questions in toxicology, we summarized several case studies. Overall, we provide the technical and conceptual foundation for the integration of proteomic measurements in a more comprehensive systems toxicology assessment framework. We conclude that, owing to the critical importance of protein-level measurements and recent technological advances, proteomics will be an integral part of integrative systems toxicology approaches in the future.

Delineating the synovial fluid proteome: recent advancements and ongoing challenges in biomarker research

There is an urgent need for identifying novel serum biomarkers that can be used to improve diagnosis, predict disease progression or response to therapy, or serve as therapeutic targets for rheumatic diseases. Synovial fluid (SF) is secreted by and remains in direct contact with the synovial membrane, and can reflect the biochemical state of the joint under different physiological and pathological conditions. Therefore, SF is regarded as an excellent source for identifying biomarkers of rheumatologic diseases. The use of high-throughput and/or quantitative proteomics and sophisticated computational software applied to analyze the protein content of SF has been well-adopted as an approach to finding novel arthritis biomarkers. This review will focus on some of the potential pitfalls of biomarker studies using SF, summarize the status of the field of SF proteomics in general, as well as discuss some of the most promising biomarker study approaches using proteomics. A brief status of the biomarker discovery efforts in rheumatoid arthritis, osteoarthritis and juvenile idiopathic arthritis is also provided.

A multi-omic analysis of an Enterococcus faecium mutant reveals specific genetic mutations and dramatic changes in mRNA and protein expression

BACKGROUND

For a long time, Enterococcus faecium was considered a harmless commensal of the mammalian gastrointestinal (GI) tract and was used as a probiotic in fermented foods. In recent decades, E. faecium has been recognised as an opportunistic pathogen that causes diseases such as neonatal meningitis, urinary tract infections, bacteremia, bacterial endocarditis and diverticulitis. E. faecium could be taken into space with astronauts and exposed to the space environment. Thus, it is necessary to observe the phenotypic and molecular changes of E. faecium after spaceflight.

RESULTS

An E. faecium mutant with biochemical features that are different from those of the wild-type strain was obtained from subculture after flight on the SHENZHOU-8 spacecraft. To understand the underlying mechanism causing these changes, the whole genomes of both the mutant and the WT strains were sequenced using Illumina technology. The genomic comparison revealed that dprA, a recombination-mediator gene, and arpU, a gene associated with cell wall growth, were mutated. Comparative transcriptomic and proteomic analyses showed that differentially expressed genes or proteins were involved with replication, recombination, repair, cell wall biogenesis, glycometabolism, lipid metabolism, amino acid metabolism, predicted general function and energy production/conversion.

CONCLUSION

This study analysed the comprehensive genomic, transcriptomic and proteomic changes of an E. faecium mutant from subcultures that were loaded on the SHENZHOU-8 spacecraft. The implications of these gene mutations and expression changes and their underlying mechanisms should be investigated in the future. We hope that the current exploration of multiple "-omics" analyses of this E. faecium mutant will provide clues for future studies on this opportunistic pathogen.

Deciphering post-translational modification codes

Post-translational modifications (PTMs) occur on nearly all proteins. Many domains within proteins are modified on multiple amino acid sidechains by diverse enzymes to create a myriad of possible protein species. How these combinations of PTMs lead to distinct biological outcomes is only beginning to be understood. This manuscript highlights several examples of combinatorial PTMs in proteins, and describes recent technological developments, which are driving our ability to understand how PTM patterns may "code" for biological outcomes.