Bioinformatics for LC-MS/MS-based proteomics

Precision Profiling of the Cardiovascular Post-Translationally Modified Proteome: Where There Is a Will, There Is a Way

There is an exponential increase in biological complexity as initial gene transcripts are spliced, translated into amino acid sequence, and post-translationally modified. Each protein can exist as multiple chemical or sequence-specific proteoforms, and each has the potential to be a critical mediator of a physiological or pathophysiological signaling cascade. Here, we provide an overview of how different proteoforms come about in biological systems and how they are most commonly measured using mass spectrometry-based proteomics and bioinformatics. Our goal is to present this information at a level accessible to every scientist interested in mass spectrometry and its application to proteome profiling. We will specifically discuss recent data linking various protein post-translational modifications to cardiovascular disease and conclude with a discussion for enablement and democratization of proteomics across the cardiovascular and scientific community. The aim is to inform and inspire the readership to explore a larger breadth of proteoform, particularity post-translational modifications, related to their particular areas of expertise in cardiovascular physiology.

Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Seed proteomics

Rather than providing a single specific protocol, the inclusive area of seed proteomics is reviewed; methods are described and compared and primary literature citations are provided. The limitations and challenges of proteomics as an approach to study seed biology are emphasized. The proteomic analysis of seeds encounters some specific problems that do not impinge on analyses of other plant cells, tissues, or organs. There are anatomic considerations. Seeds comprise the seed coat, the storage organ(s), and the embryonic axis. Are these to be studied individually or as a composite? The physiological status of the seeds must be considered; developing, mature, or germinating? If mature, are they quiescent or dormant? If mature and quiescent, then orthodox or recalcitrant? The genetic uniformity of the population of seeds being compared must be considered. Finally, seeds are protein-rich and the extreme abundance of the storage proteins results in a study-subject with a dynamic range that spans several orders of magnitude. This represents a problem that must be dealt with if the study involves analysis of proteins that are of "normal" to low abundance. Several different methods of prefractionation are described and the results compared.

PTMTreeSearch: a novel two-stage tree-search algorithm with pruning rules for the identification of post-translational modification of proteins in MS/MS spectra

MOTIVATION

Tandem mass spectrometry has become a standard tool for identifying post-translational modifications (PTMs) of proteins. Algorithmic searches for PTMs from tandem mass spectrum data (MS/MS) tend to be hampered by noisy data as well as by a combinatorial explosion of search space. This leads to high uncertainty and long search-execution times.

RESULTS

To address this issue, we present PTMTreeSearch, a new algorithm that uses a large database of known PTMs to identify PTMs from MS/MS data. For a given peptide sequence, PTMTreeSearch builds a computational tree wherein each path from the root to the leaves is labeled with the amino acids of a peptide sequence. Branches then represent PTMs. Various empirical tree pruning rules have been designed to decrease the search-execution time by eliminating biologically unlikely solutions. PTMTreeSearch first identifies a relatively small set of high confidence PTM types, and in a second stage, performs a more exhaustive search on this restricted set using relaxed search parameter settings. An analysis of experimental data shows that using the same criteria for false discovery, PTMTreeSearch annotates more peptides than the current state-of-the-art methods and PTM identification algorithms, and achieves this at roughly the same execution time. PTMTreeSearch is implemented as a plugable scoring function in the X!Tandem search engine.

AVAILABILITY

The source code of PTMTreeSearch and a demo server application can be found at http://net.icgeb.org/ptmtreesearch

A tutorial for software development in quantitative proteomics using PSI standard formats

The Human Proteome Organisation — Proteomics Standards Initiative (HUPO-PSI) has been working for ten years on the development of standardised formats that facilitate data sharing and public database deposition. In this article, we review three HUPO-PSI data standards — mzML, mzIdentML and mzQuantML, which can be used to design a complete quantitative analysis pipeline in mass spectrometry (MS)-based proteomics. In this tutorial, we briefly describe the content of each data model, sufficient for bioinformaticians to devise proteomics software. We also provide guidance on the use of recently released application programming interfaces (APIs) developed in Java for each of these standards, which makes it straightforward to read and write files of any size. We have produced a set of example Java classes and a basic graphical user interface to demonstrate how to use the most important parts of the PSI standards, available from http://code.google.com/p/psi-standard-formats-tutorial. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

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A tutorial to help software developers use PSI standard formats.

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A description of programming interfaces and tools available.

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Code snippets and a basic graphical interface to assist understanding.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics has evolved as a high-throughput research field over the past decade. Significant advances in instrumentation, and the ability to produce huge volumes of data, have emphasized the need for adequate data analysis tools, which are nowadays often considered the main bottleneck for proteomics development. This review highlights important issues that directly impact the effectiveness of proteomic quantitation and educates software developers and end-users on available computational solutions to correct for the occurrence of these factors. Potential sources of errors specific for stable isotope-based methods or label-free approaches are explicitly outlined. The overall aim focuses on a generic proteomic workflow.

Environmental proteomics, biodiversity statistics and food-web structure

Pioneering studies in environmental proteomics have revealed links between protein diversity and ecological function in simple ecological communities, such as microbial biofilms. In the near future, high-throughput proteomic methods will be applied to more complex ecological systems in which microbes and macrobes interact. Data structures in biodiversity and protein surveys have many similarities, so the statistical methods that ecologists use for analyzing biodiversity data should be adapted for use with quantitative surveys of protein diversity. However, increasing quantities of protein and bioinformatics data will not, by themselves, reveal the functional significance of proteins. Instead, ecologists should be measuring changes in the abundance of protein cohorts in response to replicated field manipulations, including nutrient enrichment and removal of top predators.

Annotator: postprocessing software for generating function-based signatures from quantitative mass spectrometry

Mass spectrometry is used to investigate global changes in protein abundance in cell lysates. Increasingly powerful methods of data collection have emerged over the past decade, but this has left researchers with the task of sifting through mountains of data for biologically significant results. Often, the end result is a list of proteins with no obvious quantitative relationships to define the larger context of changes in cell behavior. Researchers are often forced to perform a manual analysis from this list or to fall back on a range of disparate tools, which can hinder the communication of results and their reproducibility. To address these methodological problems, we developed Annotator, an application that filters validated mass spectrometry data and applies a battery of standardized heuristic and statistical tests to determine significance. To address systems-level interpretations, we incorporated UniProt and Gene Ontology keywords as statistical units of analysis, yielding quantitative information about changes in abundance for an entire functional category. This provides a consistent and quantitative method for formulating conclusions about cellular behavior, independent of network models or standard enrichment analyses. Annotator allows for "bottom-up" annotations that are based on experimental data and not inferred by comparison to external or hypothetical models. Annotator was developed as an independent postprocessing platform that runs on all common operating systems, thereby providing a useful tool for establishing the inherently dynamic nature of functional annotations, which depend on results from ongoing proteomic experiments. Annotator is available for download at http://people.cs.uchicago.edu/∼tyler/annotator/annotator_desktop_0.1.tar.gz .

Microwave-assisted protein staining, destaining, and in-gel/in-solution digestion of proteins

Rapid evolution of state-of-the-art proteomic analyses has encompassed development of high-throughput analytical instrumentation and bioinformatic tools. However, recently, there has been a particular emphasis on increasing the throughput of sample preparation, which has become one of the rate-limiting steps in protein characterization workflows. Researchers have been investigating alternative methods to conventional convection oven incubations to try and reduce sample preparation time for protein characterization. Several protocols have appeared in the literature, which employ microwave irradiation as a tool for the preparation of biological samples for subsequent characterization by a variety of analytical techniques. In this chapter, techniques for microwave-assisted protein staining, destaining, and digestion are described. In general, the application of microwave-assisted technologies resulted in the drastic reduction of overall sample preparation time, though discrepancies in the reproducibility of several published digestion protocols still remain to be clarified.

Skeletal muscle proteomics: current approaches, technical challenges and emerging techniques

Background

Skeletal muscle fibres represent one of the most abundant cell types in mammals. Their highly specialised contractile and metabolic functions depend on a large number of membrane-associated proteins with very high molecular masses, proteins with extensive posttranslational modifications and components that exist in highly complex supramolecular structures. This makes it extremely difficult to perform conventional biochemical studies of potential changes in protein clusters during physiological adaptations or pathological processes.

Results

Skeletal muscle proteomics attempts to establish the global identification and biochemical characterisation of all members of the muscle-associated protein complement. A considerable number of proteomic studies have employed large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography, and combined them with mass spectrometry as the method of choice for high-throughput protein identification. Muscle proteomics has been applied to the comprehensive biochemical profiling of developing, maturing and aging muscle, as well as the analysis of contractile tissues undergoing physiological adaptations seen in disuse atrophy, physical exercise and chronic muscle transformation. Biomedical investigations into proteome-wide alterations in skeletal muscle tissues were also used to establish novel biomarker signatures of neuromuscular disorders. Importantly, mass spectrometric studies have confirmed the enormous complexity of posttranslational modifications in skeletal muscle proteins.

Conclusions

This review critically examines the scientific impact of modern muscle proteomics and discusses its successful application for a better understanding of muscle biology, but also outlines its technical limitations and emerging techniques to establish new biomarker candidates.