Special Issue "Advances in Proteomics Methods"

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A special issue of Biology (ISSN 2079-7737).

Deadline for manuscript submissions: closed (31 December 2013)

Special Issue Editors

Guest Editor
Prof. Dr. Stephen R. Pennington (Website)

UCD Conway Institute, School of Medicine and Medical Science, University College Dublin, Ireland
Interests: human disease biomarker discovery and translation to clinical utility; quantitative proteomics
Guest Editor
Dr. Lisa Staunton

UCD Conway Institute, School of Medicine and Medical Science, University College Dublin, Ireland
Interests: Biomarkers of human disease and proteomics
Guest Editor
Dr. David S. Gibson (Website)

Clinical Translational Research and Innovation Centre, School of Biomedical Science, University of Ulster, UK
Interests: inflammatory diseases; biomarker discovery and validation; post-translational modifications

Special Issue Information

Dear Colleagues,

The ultimate goals of proteomics methods are: Whole proteome coverage at high sensitivity and with rapid throughput and whole protein coverage both structural and functional.

Currently gel- and liquid chromatography based protein and peptide separation combined with mass spectrometry form the basis of most proteomics methods and huge progress is being made in reaching the goal of ‘routine’ whole proteome coverage and the analysis of post-translational modifications. Recent developments have been such that the field of proteomics is now beginning to impact on our understanding of disease pathogenesis and has exciting opportunities in personalised medicine. Notably, improved mass spectrometry based technologies combined with developments in chemical strategies continue to play a leading role in these advances. However, many challenges remain – not least in how to improve ‘protein coverage, increase the sensitivity and sophistication of protein analysis and reach the level of throughput that many potential applications require. At the same time the quantity of data produced and its variable quality is presenting new demands – both for the handling and reliable interpretation of the data. New methods for data storage, sharing, analysis and re-analysis are in development and much needed. This special issue aims to draw together original research articles and reviews on current and projected advances in diverse proteomics methods.

Submissions covering the following topics will be welcomed:

Sample preparation methods (LCM, protein enrichment);
Label-free and isotopic labeling strategies for LC-MS/MS;
Role of miniaturisation/amplification strategies (Achieving sensitivity with smaller/limited samples);
Protein recognition (antibody, aptamer) based approaches;
Whole proteome coverage;
Software development for handling and interpreting MS data;
MRM: development and applications;
Post-translational modifications: to phosphorylation and beyond;
Advances in MS instrumentation;
Proteomics databases: data storage and sharing, data re-analysis;
Statistical approaches and novel algorithms;
Methods and instrumentation for taking proteomics to clinical utility

Please note this is not an exhaustive list

Prof.  Stephen R. Pennington
Dr. Lisa Staunton
Dr. David S. Gibson
Guest Editors

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biology is an international peer-reviewed Open Access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 600 CHF (Swiss Francs). English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

Published Papers (5 papers)

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Research

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Open AccessArticle Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments
Biology 2014, 3(2), 383-402; doi:10.3390/biology3020383
Received: 17 March 2014 / Revised: 16 April 2014 / Accepted: 10 May 2014 / Published: 5 June 2014
Cited by 1 | PDF Full-text (708 KB) | HTML Full-text | XML Full-text
Abstract
Multiple Reaction Monitoring (MRM) conducted on a triple quadrupole mass spectrometer allows researchers to quantify the expression levels of a set of target proteins. Each protein is often characterized by several unique peptides that can be detected by monitoring predetermined fragment ions, [...] Read more.
Multiple Reaction Monitoring (MRM) conducted on a triple quadrupole mass spectrometer allows researchers to quantify the expression levels of a set of target proteins. Each protein is often characterized by several unique peptides that can be detected by monitoring predetermined fragment ions, called transitions, for each peptide. Concatenating large numbers of MRM transitions into a single assay enables simultaneous quantification of hundreds of peptides and proteins. In recognition of the important role that MRM can play in hypothesis-driven research and its increasing impact on clinical proteomics, targeted proteomics such as MRM was recently selected as the Nature Method of the Year. However, there are many challenges in MRM applications, especially data pre‑processing where many steps still rely on manual inspection of each observation in practice. In this paper, we discuss an analysis pipeline to automate MRM data pre‑processing. This pipeline includes data quality assessment across replicated samples, outlier detection, identification of inaccurate transitions, and data normalization. We demonstrate the utility of our pipeline through its applications to several real MRM data sets. Full article
(This article belongs to the Special Issue Advances in Proteomics Methods)
Open AccessArticle On-Beads Digestion in Conjunction with Data-Dependent Mass Spectrometry: A Shortcut to Quantitative and Dynamic Interaction Proteomics
Biology 2014, 3(2), 320-332; doi:10.3390/biology3020320
Received: 9 January 2014 / Revised: 13 March 2014 / Accepted: 25 March 2014 / Published: 16 April 2014
Cited by 7 | PDF Full-text (532 KB) | HTML Full-text | XML Full-text
Abstract
With the advent of the “-omics” era, biological research has shifted from functionally analyzing single proteins to understanding how entire protein networks connect and adapt to environmental cues. Frequently, pathological processes are initiated by a malfunctioning protein network rather than a single [...] Read more.
With the advent of the “-omics” era, biological research has shifted from functionally analyzing single proteins to understanding how entire protein networks connect and adapt to environmental cues. Frequently, pathological processes are initiated by a malfunctioning protein network rather than a single protein. It is therefore crucial to investigate the regulation of proteins in the context of a pathway first and signaling network second. In this study, we demonstrate that a quantitative interaction proteomic approach, combining immunoprecipitation, in-solution digestion and label-free quantification mass spectrometry, provides data of high accuracy and depth. This protocol is applicable, both to tagged, exogenous and untagged, endogenous proteins. Furthermore, it is fast, reliable and, due to a label-free quantitation approach, allows the comparison of multiple conditions. We further show that we are able to generate data in a medium throughput fashion and that we can quantify dynamic interaction changes in signaling pathways in response to mitogenic stimuli, making our approach a suitable method to generate data for system biology approaches. Full article
(This article belongs to the Special Issue Advances in Proteomics Methods)
Open AccessArticle Automated Sample Preparation Platform for Mass Spectrometry-Based Plasma Proteomics and Biomarker Discovery
Biology 2014, 3(1), 205-219; doi:10.3390/biology3010205
Received: 12 December 2013 / Revised: 31 January 2014 / Accepted: 27 February 2014 / Published: 11 March 2014
Cited by 2 | PDF Full-text (602 KB) | HTML Full-text | XML Full-text | Supplementary Files
Abstract
The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of [...] Read more.
The identification of novel biomarkers from human plasma remains a critical need in order to develop and monitor drug therapies for nearly all disease areas. The discovery of novel plasma biomarkers is, however, significantly hampered by the complexity and dynamic range of proteins within plasma, as well as the inherent variability in composition from patient to patient. In addition, it is widely accepted that most soluble plasma biomarkers for diseases such as cancer will be represented by tissue leakage products, circulating in plasma at low levels. It is therefore necessary to find approaches with the prerequisite level of sensitivity in such a complex biological matrix. Strategies for fractionating the plasma proteome have been suggested, but improvements in sensitivity are often negated by the resultant process variability. Here we describe an approach using multidimensional chromatography and on-line protein derivatization, which allows for higher sensitivity, whilst minimizing the process variability. In order to evaluate this automated process fully, we demonstrate three levels of processing and compare sensitivity, throughput and reproducibility. We demonstrate that high sensitivity analysis of the human plasma proteome is possible down to the low ng/mL or even high pg/mL level with a high degree of technical reproducibility. Full article
(This article belongs to the Special Issue Advances in Proteomics Methods)
Open AccessArticle Application of Fluorescence Two-Dimensional Difference In-Gel Electrophoresis as a Proteomic Biomarker Discovery Tool in Muscular Dystrophy Research
Biology 2013, 2(4), 1438-1464; doi:10.3390/biology2041438
Received: 24 September 2013 / Revised: 5 November 2013 / Accepted: 12 November 2013 / Published: 2 December 2013
Cited by 9 | PDF Full-text (1149 KB) | HTML Full-text | XML Full-text
Abstract
In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic [...] Read more.
In this article, we illustrate the application of difference in-gel electrophoresis for the proteomic analysis of dystrophic skeletal muscle. The mdx diaphragm was used as a tissue model of dystrophinopathy. Two-dimensional gel electrophoresis is a widely employed protein separation method in proteomic investigations. Although two-dimensional gels usually underestimate the cellular presence of very high molecular mass proteins, integral membrane proteins and low copy number proteins, this method is extremely powerful in the comprehensive analysis of contractile proteins, metabolic enzymes, structural proteins and molecular chaperones. This gives rise to two-dimensional gel electrophoretic separation as the method of choice for studying contractile tissues in health and disease. For comparative studies, fluorescence difference in-gel electrophoresis has been shown to provide an excellent biomarker discovery tool. Since aged diaphragm fibres from the mdx mouse model of Duchenne muscular dystrophy closely resemble the human pathology, we have carried out a mass spectrometry-based comparison of the naturally aged diaphragm versus the senescent dystrophic diaphragm. The proteomic comparison of wild type versus mdx diaphragm resulted in the identification of 84 altered protein species. Novel molecular insights into dystrophic changes suggest increased cellular stress, impaired calcium buffering, cytostructural alterations and disturbances of mitochondrial metabolism in dystrophin-deficient muscle tissue. Full article
(This article belongs to the Special Issue Advances in Proteomics Methods)
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Review

Jump to: Research

Open AccessReview Contemporary Network Proteomics and Its Requirements
Biology 2014, 3(1), 22-38; doi:10.3390/biology3010022
Received: 12 November 2013 / Revised: 15 December 2013 / Accepted: 16 December 2013 / Published: 20 December 2013
Cited by 2 | PDF Full-text (886 KB) | HTML Full-text | XML Full-text
Abstract
The integration of networks with genomics (network genomics) is a familiar field. Conventional network analysis takes advantage of the larger coverage and relative stability of gene expression measurements. Network proteomics on the other hand has to develop further on two critical factors: [...] Read more.
The integration of networks with genomics (network genomics) is a familiar field. Conventional network analysis takes advantage of the larger coverage and relative stability of gene expression measurements. Network proteomics on the other hand has to develop further on two critical factors: (1) expanded data coverage and consistency, and (2) suitable reference network libraries, and data mining from them. Concerning (1) we discuss several contemporary themes that can improve data quality, which in turn will boost the outcome of downstream network analysis. For (2), we focus on network analysis developments, specifically, the need for context-specific networks and essential considerations for localized network analysis. Full article
(This article belongs to the Special Issue Advances in Proteomics Methods)

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