Mass spectrometry-based quantification of the cellular response to methyl methanesulfonate treatment in human cells

Faithful transmission of genetic material is essential for cell viability and organism health. The occurrence of DNA damage, due to either spontaneous events or environmental agents, threatens the integrity of the genome. The consequences of these insults, if allowed to perpetuate and accumulate over time, are mutations that can lead to the development of diseases such as cancer. Alkylation is a relevant DNA lesion produced endogenously as well as by exogenous agents including certain chemotherapeutics. We sought to better understand the cellular response to this form of DNA damage using mass spectrometry-based proteomics. For this purpose, we performed sub-cellular fractionation to monitor the effect of methyl methanesulfonate (MMS) treatment on protein localization to chromatin. The levels of over 500 proteins were increased in the chromatin-enriched nuclear lysate including histone chaperones. Levels of ubiquitin and subunits of the proteasome were also increased within this fraction, suggesting that ubiquitin-mediated degradation by the proteasome has an important role in the chromatin response to MMS treatment. Finally, the levels of some proteins were decreased within the chromatin-enriched lysate including components of the nuclear pore complex. Our spatial proteomics data demonstrate that many proteins that influence chromatin organization are regulated in response to MMS treatment, presumably to open the DNA to allow access by other DNA damage response proteins. To gain further insight into the cellular response to MMS-induced DNA damage, we also performed phosphorylation enrichment on total cell lysates to identify proteins regulated via post-translational modification. Phosphoproteomic analysis demonstrated that many nuclear phosphorylation events were decreased in response to MMS treatment. This reflected changes in protein kinase and/or phosphatase activity in response to DNA damage rather than changes in total protein abundance. Using these two mass spectrometry-based approaches, we have identified a novel set of MMS-responsive proteins that will expand our understanding of DNA damage signaling.     

Mass spectrometry-based plasma proteomics: state of the art and future outlook

Mass spectrometry-based plasma proteomics is a field where intense research has been performed during the last decade. Being closely linked to biomarker discovery, the field has received a fair amount of criticism, mostly due to the low number of novel biomarkers reaching the clinic. However, plasma proteomics is under gradual development with improvements on fractionation methods, mass spectrometry instrumentation and analytical approaches. These recent developments have contributed to the revival of plasma proteomics. The goal of this review is to summarize these advances, focusing in particular on fractionation methods, both for targeted and global mass spectrometry-based plasma analysis.     

Mass spectrometry-based proteomics for translational research: a technical overview

Mass spectrometry-based investigation of clinical samples enables the high-throughput identification of protein biomarkers. We provide an overview of mass spectrometry-based proteomic techniques that are applicable to the investigation of clinical samples. We address sample collection, protein extraction and fractionation, mass spectrometry modalities, and quantitative proteomics. Finally, we examine the limitations and further potential of such technologies. Liquid chromatography fractionation coupled with tandem mass spectrometry is well suited to handle mixtures of hundreds or thousands of proteins. Mass spectrometry-based proteome elucidation can reveal potential biomarkers and aid in the development of hypotheses for downstream investigation of the molecular mechanisms of disease.     

MS3 eliminates ratio distortion in isobaric multiplexed quantitative proteomics

Quantitative mass spectrometry-based proteomics is highly versatile but not easily multiplexed. Isobaric labeling strategies allow mass spectrometry-based multiplexed proteome quantification; however, ratio distortion owing to protein quantification interference is a common effect. We present a two-proteome model (mixture of human and yeast proteins) in a sixplex isobaric labeling system to fully document the interference effect, and we report that applying triple-stage mass spectrometry (MS3) almost completely eliminates interference.     

Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions

Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.     

Detection technologies in proteome analysis

Common strategies employed for general protein detection include organic dye, silver stain, radiolabeling, reverse stain, fluorescent stain, chemiluminescent stain and mass spectrometry-based approaches. Fluorescence-based protein detection methods have recently surpassed conventional technologies such as colloidal Coomassie blue and silver staining in terms of quantitative accuracy, detection sensitivity, and compatibility with modern downstream protein identification and characterization procedures, such as mass spectrometry. Additionally, specific detection methods suitable for revealing protein post-translational modifications have been devised over the years. These include methods for the detection of glycoproteins, phosphoproteins, proteolytic modifications, S-nitrosylation, arginine methylation and ADP-ribosylation. Methods for the detection of a range of reporter enzymes and epitope tags are now available as well, including those for visualizing beta-glucuronidase, beta-galactosidase, oligohistidine tags and green fluorescent protein. Fluorescence-based and mass spectrometry-based methodologies are just beginning to offer unparalleled new capabilities in the field of proteomics through the performance of multiplexed quantitative analysis. The primary objective of differential display proteomics is to increase the information content and throughput of proteomics studies through multiplexed analysis. Currently, three principal approaches to differential display proteomics are being actively pursued, difference gel electrophoresis (DIGE), multiplexed proteomics (MP) and isotope-coded affinity tagging (ICAT). New multiplexing capabilities should greatly enhance the applicability of the two-dimensional gel electrophoresis technique with respect to addressing fundamental questions related to proteome-wide changes in protein expression and post-translational modification.     

Capitalizing on the hydrophobic bias of electrospray ionization through chemical modification in mass spectrometry-based proteomics

Protein chemical derivatization has emerged as an invaluable bioanalytical approach in mass spectrometry-based proteomics with nearly unlimited potential. To date, derivatization strategies in proteomics have primarily focused on improving mass spectral identification and relative quantification of proteins, as well as increasing enrichment yield from complex mixtures. However, there is a great opportunity to develop and exploit front-end chemical processes to enhance the ability to detect low-abundant peptides and proteins for a large number of applications. The content of this article focuses on improvements in targeted, mass spectrometry-based proteomic strategies, achieved by taking advantage of the mechanism of ESI through the use of hydrophobic chemical derivatization.     

Production of tetraacetyl phytosphingosine (TAPS) in Wickerhamomyces ciferrii is catalyzed by acetyltransferases Sli1p and Atf2p

Wickerhamomyces ciferrii secretes tetraacetyl phytosphingosine (TAPS), and in this study, the catalyzing acetyltransferases were identified using mass spectrometry-based proteomics. The proteome of wild-type strain NRRL Y-1031 served as control and was compared to the tetraacetyl phytosphingosine defective mating type NRRL Y-1031-27. Acetylation of phytosphingosine in W. ciferrii is catalyzed by acetyltransferases Sli1p and Atf2p, encoded by genes similar to Saccharomyces cerevisiae YGR212W and YGR177C, respectively. Ablation of SLI1 resulted in an almost complete loss of tri- and tetraacetyl phytosphingosines, whereas the loss ATF2 resulted in an 15-fold increase in triacetyl phytosphingosine. Most likely, it is the concerted action of these two acetyltransferases that yields tetraacetyl phytosphingosine, in which Sli1p catalyzes initial O- and N-acetylation, producing triacetyl phytosphingosine. Finally, Atf2p catalyzes final O-acetylation to yield tetraacetyl phytosphingosine. The current study demonstrates that mass spectrometry-based proteomics can be employed to identify key steps in ill-explored metabolite biosynthesis pathways of nonconventional microorganisms. Furthermore, the identification of phytosphingosine as substrate for alcohol acetyltransferase Atf2p broadens the known substrate range of this enzyme. This interesting property of Atf2p may be exploited to enhance the secretion of heterologous compounds.     

Proteomic approaches to uncover MMP function

Proteomics has revolutionized protease research and particularly contributed to the identification of novel substrates and their sites of cleavage as key determinants of protease function. New technologies and rapid advancements in development of powerful mass spectrometers allowed unprecedented insights into activities of matrix metalloproteinases (MMPs) within their complex extracellular environments. Mass spectrometry-based proteomics extended our knowledge on MMP cleavage specificities and will help to develop more specific inhibitors as new therapeutics. Quantitative proteomics and N-terminal enrichment strategies have revealed numerous novel MMP substrates and shed light on their modes of action in vitro and in vivo. In this review, we provide an overview of current proteomic technologies in protease research and their application to the functional characterization of MMPs.     

Analysis and validation of proteomic data generated by tandem mass spectrometry

The analysis of the large amount of data generated in mass spectrometry-based proteomics experiments represents a significant challenge and is currently a bottleneck in many proteomics projects. In this review we discuss critical issues related to data processing and analysis in proteomics and describe available methods and tools. We place special emphasis on the elaboration of results that are supported by sound statistical arguments.     

Untangling multi-gene families in plants by integrating proteomics into functional genomics

The classification and study of gene families is emerging as a constructive tool for fast tracking the elucidation of gene function. A multitude of technologies can be employed to undertake this task including comparative genomics, gene expression studies, sub-cellular localisation studies and proteomic analysis. Here we focus on the growing role of proteomics in untangling gene families in model plant species. Proteomics can specifically identify the products of closely related genes, can determine their abundance, and coupled to affinity chromatography and sub-cellular fractionation studies, it can even provide location within cells and functional assessment of specific proteins. Furthermore global gene expression analysis can then be used to place a specific family member in the context of a cohort of co-expressed genes. In model plants with established reverse genetic resources, such as catalogued T-DNA insertion lines, this gene specific information can also be readily used for a wider assessment of specific protein function or its capacity for compensation through assessing whole plant phenotypes. In combination, these resources can explore partitioning of function between members and assess the level of redundancy within gene families.     

Mass spectrometry-based quantitative proteomics

A major aim of present-day proteomics is to study changes in protein expression levels at a global level, ideally monitoring all proteins present in cells or tissue. Mass spectrometry is a well-respected technology in proteomics that is widely used for the identification of proteins. More recently, methodologies have been introduced showing that mass spectrometry can also be used for protein quantification. This article reviews various mass spectrometry-based technologies in quantitative proteomics, highlighting several interesting applications in areas ranging from cell biology to clinical applications.     

Mass spectrometry-based quantitative proteomics

A major aim of present-day proteomics is to study changes in protein expression levels at a global level, ideally monitoring all proteins present in cells or tissue. Mass spectrometry is a well-respected technology in proteomics that is widely used for the identification of proteins. More recently, methodologies have been introduced showing that mass spectrometry can also be used for protein quantification. This article reviews various mass spectrometry-based technologies in quantitative proteomics, highlighting several interesting applications in areas ranging from cell biology to clinical applications.     

Current strategies and findings in clinically relevant post-translational modification-specific proteomics

Mass spectrometry-based proteomics has considerably extended our knowledge about the occurrence and dynamics of protein post-translational modifications (PTMs). So far, quantitative proteomics has been mainly used to study PTM regulation in cell culture models, providing new insights into the role of aberrant PTM patterns in human disease. However, continuous technological and methodical developments have paved the way for an increasing number of PTM-specific proteomic studies using clinical samples, often limited in sample amount. Thus, quantitative proteomics holds a great potential to discover, validate and accurately quantify biomarkers in body fluids and primary tissues. A major effort will be to improve the complete integration of robust but sensitive proteomics technology to clinical environments. Here, we discuss PTMs that are relevant for clinical research, with a focus on phosphorylation, glycosylation and proteolytic cleavage; furthermore, we give an overview on the current developments and novel findings in mass spectrometry-based PTM research.     

High throughput proteome screening for biomarker detection

Mass spectrometry-based quantitative proteomics has become an important component of biological and clinical research. Current methods, while highly developed and powerful, are falling short of their goal of routinely analyzing whole proteomes mainly because the wealth of proteomic information accumulated from prior studies is not used for the planning or interpretation of present experiments. The consequence of this situation is that in every proteomic experiment the proteome is rediscovered. In this report we describe an approach for quantitative proteomics that builds on the extensive prior knowledge of proteomes and a platform for the implementation of the method. The method is based on the selection and chemical synthesis of isotopically labeled reference peptides that uniquely identify a particular protein and the addition of a panel of such peptides to the sample mixture consisting of tryptic peptides from the proteome in question. The platform consists of a peptide separation module for the generation of ordered peptide arrays from the combined peptide sample on the sample plate of a MALDI mass spectrometer, a high throughput MALDI-TOF/TOF mass spectrometer, and a suite of software tools for the selective analysis of the targeted peptides and the interpretation of the results. Applying the method to the analysis of the human blood serum proteome we demonstrate the feasibility of using mass spectrometry-based proteomics as a high throughput screening technology for the detection and quantification of targeted proteins in a complex system.     

Strategies for metagenomic-guided whole-community proteomics of complex microbial environments

Accurate protein identification in large-scale proteomics experiments relies upon a detailed, accurate protein catalogue, which is derived from predictions of open reading frames based on genome sequence data. Integration of mass spectrometry-based proteomics data with computational proteome predictions from environmental metagenomic sequences has been challenging because of the variable overlap between proteomic datasets and corresponding short-read nucleotide sequence data. In this study, we have benchmarked several strategies for increasing microbial peptide spectral matching in metaproteomic datasets using protein predictions generated from matched metagenomic sequences from the same human fecal samples. Additionally, we investigated the impact of mass spectrometry-based filters (high mass accuracy, delta correlation), and de novo peptide sequencing on the number and robustness of peptide-spectrum assignments in these complex datasets. In summary, we find that high mass accuracy peptide measurements searched against non-assembled reads from DNA sequencing of the same samples significantly increased identifiable proteins without sacrificing accuracy.     

Translating clinical proteomics: the importance of study design

Mass spectrometry-based clinical proteomics approaches were introduced into the biomedical field more than two decades ago. Despite recent developments both in the field of mass spectrometry and bioinformatics, the gap between proteomics results and their translation into clinical practice still needs to be closed, as implementation of proteomics results in the clinic appears to be scarce. An extra focus on the importance of the experimental design is therefore of crucial importance.