Proteogenomics: needs and roles to be filled by proteomics in genome annotation

While genome sequencing efforts reveal the basic building blocksof life, a genome sequence alone is insufficient for elucidatingbiological function. Genome annotation—the process ofidentifying genes and assigning function to each gene in a genomesequence—provides the means to elucidate biological functionfrom sequence. Current state-of-the-art high-throughput genomeannotation uses a combination of comparative (sequence similaritydata) and non-comparative (ab initio gene prediction algorithms)methods to identify protein-coding genes in genome sequences.Because approaches used to validate the presence of predictedprotein-coding genes are typically based on expressed RNA sequences,they cannot independently and unequivocally determine whethera predicted protein-coding gene is translated into a protein.With the ability to directly measure peptides arising from expressedproteins, high-throughput liquid chromatography-tandem massspectrometry-based proteomics approaches can be used to verifycoding regions of a genomic sequence. Here, we highlight severalways in which high-throughput tandem mass spectrometry-basedproteomics can improve the quality of genome annotations andsuggest that it could be efficiently applied during the genecalling process so that the improvements are propagated throughthe subsequent functional annotation process.      

New approaches towards integrated proteomic databases and depositories

Since the publication of the human genome, two key points have emerged. First, it is still not certain which regions of the genome code for proteins. Second, the number of discrete protein-coding genes is far fewer than the number of different proteins. Proteomics has the potential to address some of these postgenomic issues if the obstacles that we face can be overcome in our efforts to combine proteomic and genomic data. There are many challenges associated with high-throughput and high-output proteomic technologies. Consequently, for proteomics to continue at its current growth rate, new approaches must be developed to ease data management and data mining. Initiatives have been launched to develop standard data formats for exchanging mass spectrometry proteomic data, including the Proteomics Standards Initiative formed by the Human Proteome Organization. Databases such as SwissProt and Uniprot are publicly available repositories for protein sequences annotated for function, subcellular location and known potential post-translational modifications. The availability of bioinformatics solutions is crucial for proteomics technologies to fulfil their promise of adding further definition to the functional output of the human genome. The aim of the Oxford Genome Anatomy Project is to provide a framework for integrating molecular, cellular, phenotypic and clinical information with experimental genetic and proteomics data. This perspective also discusses models to make the Oxford Genome Anatomy Project accessible and beneficial for academic and commercial research and development.     

New approaches towards integrated proteomic databases and depositories

Since the publication of the human genome, two key points have emerged. First, it is still not certain which regions of the genome code for proteins. Second, the number of discrete protein-coding genes is far fewer than the number of different proteins. Proteomics has the potential to address some of these postgenomic issues if the obstacles that we face can be overcome in our efforts to combine proteomic and genomic data. There are many challenges associated with high-throughput and high-output proteomic technologies. Consequently, for proteomics to continue at its current growth rate, new approaches must be developed to ease data management and data mining. Initiatives have been launched to develop standard data formats for exchanging mass spectrometry proteomic data, including the Proteomics Standards Initiative formed by the Human Proteome Organization. Databases such as SwissProt and Uniprot are publicly available repositories for protein sequences annotated for function, subcellular location and known potential post-translational modifications. The availability of bioinformatics solutions is crucial for proteomics technologies to fulfil their promise of adding further definition to the functional output of the human genome. The aim of the Oxford Genome Anatomy Project is to provide a framework for integrating molecular, cellular, phenotypic and clinical information with experimental genetic and proteomics data. This perspective also discusses models to make the Oxford Genome Anatomy Project accessible and beneficial for academic and commercial research and development.     

Label-free quantitation, an extension to 2DB

Determining the differential expression of proteins under different conditions is of major importance in proteomics. Since mass spectrometry-based proteomics is often used to quantify proteins, several labelling strategies have been developed. While these are generally more precise than label-free quantitation approaches, they imply specifically designed experiments which also require knowledge about peptides that are expected to be measured and need to be modified. We recently designed the 2DB database which aids storage, analysis, and publication of data from mass spectrometric experiments to identify proteins. This database can aid identifying peptides which can be used for quantitation. Here an extension to the database application, named MSMAG, is presented which allows for more detailed analysis of the distribution of peptides and their associated proteins over the fractions of an experiment. Furthermore, given several biological samples in the database, label-free quantitation can be performed. Thus, interesting proteins, which may warrant further investigation, can be identified en passant while performing high-throughput proteomics studies.     

Population proteomics: the concept, attributes, and potential for cancer biomarker research

This review outlines the concept of population proteomics and its implication in the discovery and validation of cancer-specific protein modulations. Population proteomics is an applied subdiscipline of proteomics engaging in the investigation of human proteins across and within populations to define and better understand protein diversity. Population proteomics focuses on interrogation of specific proteins from large number of individuals, utilizing top-down, targeted affinity mass spectrometry approaches to probe protein modifications. Deglycosylation, sequence truncations, side-chain residue modifications, and other modifications have been reported for myriad of proteins, yet little is know about their incidence rate in the general population. Such information can be gathered via population proteomics and would greatly aid the biomarker discovery efforts. Discovery of novel protein modifications is also expected from such large scale population proteomics, expanding the protein knowledge database. In regard to cancer protein biomarkers, their validation via population proteomics-based approaches is advantageous as mass spectrometry detection is used both in the discovery and validation process, which is essential for the detection of those structurally modified protein biomarkers.     

Functional proteomics approach to investigate the biological activities of cDNAs implicated in breast cancer

Functional proteomics approaches that comprehensively evaluate the biological activities of human cDNAs may provide novel insights into disease pathogenesis. To systematically investigate the functional activity of cDNAs that have been implicated in breast carcinogenesis, we generated a collection of cDNAs relevant to breast cancer, the Breast Cancer 1000 (BC1000), and conducted screens to identify proteins that induce phenotypic changes that resemble events which occur during tumor initiation and progression. Genes were selected for this set using bioinformatics and data mining tools that identify genes associated with breast cancer. Greater than 1000 cDNAs were assembled and sequence verified with high-throughput recombination-based cloning. To our knowledge, the BC1000 represents the first publicly available sequence-validated human disease gene collection. The functional activity of a subset of the BC1000 collection was evaluated in cell-based assays that monitor changes in cell proliferation, migration, and morphogenesis in MCF-10A mammary epithelial cells expressing a variant of ErbB2 that can be inducibly activated through dimerization. Using this approach, we identified many cDNAs, encoding diverse classes of cellular proteins, that displayed activity in one or more of the assays, thus providing insights into a large set of cellular proteins capable of inducing functional alterations associated with breast cancer development.     

Bioinformatics in mass spectrometry data analysis for proteomics studies

Mass spectrometry is a technique widely employed for the identification and characterization of proteins. The role of bioinformatics is fundamental for the elaboration of mass spectrometry data due to the amount of data that this technique can produce. To process data efficiently, new software packages and algorithms are continuously being developed to improve protein identification and characterization in terms of high-throughput and statistical accuracy. However, many limitations exist concerning bioinformatics spectral data elaboration. This review aims to critically cover the recent and future developments of new bioinformatics approaches in mass spectrometry data analysis for proteomics studies.     

Bioinformatics in mass spectrometry data analysis for proteomics studies

Mass spectrometry is a technique widely employed for the identification and characterization of proteins. The role of bioinformatics is fundamental for the elaboration of mass spectrometry data due to the amount of data that this technique can produce. To process data efficiently, new software packages and algorithms are continuously being developed to improve protein identification and characterization in terms of high-throughput and statistical accuracy. However, many limitations exist concerning bioinformatics spectral data elaboration. This review aims to critically cover the recent and future developments of new bioinformatics approaches in mass spectrometry data analysis for proteomics studies.     

High-throughput proteomics using matrix-assisted laser desorption/ ionization mass spectrometry

It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ ionization in biological mass spectrometry - one of the most commonly used analytical tools in proteomics - for high-throughput analyses.     

High-throughput proteomics using matrix-assisted laser desorption/ ionization mass spectrometry

It has become evident that the mystery of life will not be deciphered just by decoding its blueprint, the genetic code. In the life and biomedical sciences, research efforts are now shifting from pure gene analysis to the analysis of all biomolecules involved in the machinery of life. One area of these postgenomic research fields is proteomics. Although proteomics, which basically encompasses the analysis of proteins, is not a new concept, it is far from being a research field that can rely on routine and large-scale analyses. At the time the term proteomics was coined, a gold-rush mentality was created, promising vast and quick riches (i.e., solutions to the immensely complex questions of life and disease). Predictably, the reality has been quite different. The complexity of proteomes and the wide variations in the abundances and chemical properties of their constituents has rendered the use of systematic analytical approaches only partially successful, and biologically meaningful results have been slow to arrive. However, to learn more about how cells and, hence, life works, it is essential to understand the proteins and their complex interactions in their native environment. This is why proteomics will be an important part of the biomedical sciences for the foreseeable future. Therefore, any advances in providing the tools that make protein analysis a more routine and large-scale business, ideally using automated and rapid analytical procedures, are highly sought after. This review will provide some basics, thoughts and ideas on the exploitation of matrix-assisted laser desorption/ ionization in biological mass spectrometry – one of the most commonly used analytical tools in proteomics – for high-throughput analyses.     

Moss (Physcomitrella patens) functional genomics--Gene discovery and tool development, with implications for crop plants and human health.

Recently, the moss Physcomitrella patens was established as a versatile tool in plant functional genomics. Mosses represent the oldest living clade of land plants, separated by approximately 450 million years of evolution from crop plants. Consequently, mosses contain metabolites and genes not known from these seed plants. In Physcomitrella, nuclear genes can be targeted by homologous recombination as efficiently as in yeast, allowing reverse genetics approaches in plants at high-throughput levels for the first time. Comprehensive expressed sequence tag databases gave new insights into the levels of diversity in land plants which are now ready to be exploited in plant biotechnology. In forward genetics screens, saturated tagged mutant collections help to unravel novel gene - function relationships. Additionally, proteomics tools are at hand to analyse subcellular proteomes, as well as the phosphoproteome, as the core of eukaryotic signal transduction. Moreover, specifically designed Physcomitrella strains can produce human therapeutic proteins safely and cost-effectively in bioreactors.     

Experimental standards for high-throughput proteomics

Proteome analysis, utilizing high-throughput proteomics approaches, involves studying proteins that a whole organism (or specific tissue or cellular compartment) expresses under certain conditions. Intrinsic difficulties of these studies, as well as the enormous volumes of data they typically produce, make the proteome analysis and interpretation very difficult. As with any high-throughput approach, proteomics experiments should be carefully designed, analyzed, and verified. In addition to computational standards,experimental standards--simple and complex mixtures of known proteins--for high-throughput proteomics have to be developed and utilized. This article discusses such experimental standards and their implementations.     

Comparison of the electron capture dissociation fragmentation behavior of doubly and triply protonated peptides from trypsin, Glu-C, and chymotrypsin digestion

In bottom-up proteomics, proteolytically derived peptides from proteins of interest are analyzed to provide sequence information for protein identification and characterization. Electron capture dissociation (ECD), which provides more random cleavages compared to "slow heating" techniques such as collisional activation, can result in greater sequence coverage for peptides and proteins. Most bottom-up proteomics approaches rely on tryptic doubly protonated peptides for generating sequence information. However, the effectiveness, in terms of peptide sequence coverage, of tryptic doubly protonated peptides in ECD remains to be characterized. Herein, we examine the ECD fragmentation behavior of 64 doubly- and 64 triply protonated peptides (i.e., a total of 128 peptide ions) from trypsin, Glu-C, and chymotrypsin digestion in a Fourier transform ion cyclotron resonance mass spectrometer. Our findings indicate that when triply protonated peptides are fragmented in ECD, independent of which proteolytic enzyme was used for protein digestion, more c- and z-type product ions are observed, and the number of complementary fragment pairs increases dramatically (44%). In addition, triply protonated peptides provide an increase (26%) in peptide sequence coverage. ECD of tryptic peptides, in both charge states, resulted in higher sequence coverage compared to chymotryptic and Glu-C digest peptides. The peptide sequence coverage we obtained in ECD of tryptic doubly protonated peptides (64%) is very similar to that reported for electron transfer dissociation of the same peptide type (63%).     

Cardiovascular proteomic analysis

Here, we report on our proteomic studies in the field of cardiovascular medicine. Our research has been focused on understanding the role of proteins in cardiovascular disease with a particular focus on epigenetic regulation and biomarker discovery, with the objective of better understanding cardiovascular pathophysiology to lead to the development of new and better diagnostic and therapeutic methods. We have used mass spectrometry for over 5 years as a viable method to investigate protein-protein interactions and post-translational modifications in cellular proteins as well as a method to investigate the role of extra-cellular proteins. Use of mass spectrometry not only as a research tool but also as a potential diagnostic tool is a topic of interest. In addition to these functional proteomics studies, structural proteomic studies are also done with expectations to allow for pinpoint drug design and therapeutic intervention. Collectively, our proteomics studies are focused on understanding the functional role and potential therapeutically exploitable property of proteins in cardiovascular disease from both intra-cellular and extra-cellular aspects with both functional as well as structural proteomics approaches to allow for comprehensive analysis.     

Advanced nanoscale separations and mass spectrometry for sensitive high-throughput proteomics

Recent developments in combined separations with mass spectrometry for sensitive and high-throughput proteomic analyses are reviewed herein. These developments primarily involve high-efficiency (separation peak capacities of approximately 10(3)) nanoscale liquid chromatography (flow rates extending down to approximately 20 nl/min at optimal liquid mobile-phase separation linear velocities through narrow packed capillaries) in combination with advanced mass spectrometry and in particular, high-sensitivity and high-resolution Fourier transform ion cyclotron resonance mass spectrometry. Such approaches enable analysis of low nanogram level proteomic samples (i.e., nanoscale proteomics) with individual protein identification sensitivity at the low zeptomole level. The resultant protein measurement dynamic range can approach 10(6) for nanogram-sized proteomic samples, while more abundant proteins can be detected from subpicogram-sized (total) proteome samples. These qualities provide the foundation for proteomics studies of single or small populations of cells. The instrumental robustness required for automation and providing high-quality routine performance nanoscale proteomic analyses is also discussed.     

Ion mobility–mass spectrometry for structural proteomics

Ion mobility coupled to mass spectrometry has been an important tool in the fields of chemical physics and analytical chemistry for decades, but its potential for interrogating the structure of proteins and multiprotein complexes has only recently begun to be realized. Today, ion mobility–mass spectrometry is often applied to the structural elucidation of protein assemblies that have failed high-throughput crystallization or NMR spectroscopy screens. Here, we highlight the technology, approaches and data that have led to this dramatic shift in use, including emerging trends such as the integration of ion mobility–mass spectrometry data with more classical (e.g., ‘bottom-up’) proteomics approaches for the rapid structural characterization of protein networks.     

A wiring of the human nucleolus

Recent proteomic efforts have created an extensive inventory of the human nucleolar proteome. However, approximately 30% of the identified proteins lack functional annotation. We present an approach of assigning function to uncharacterized nucleolar proteins by data integration coupled to a machine-learning method. By assembling protein complexes, we present a first draft of the human ribosome biogenesis pathway encompassing 74 proteins and hereby assign function to 49 previously uncharacterized proteins. Moreover, the functional diversity of the nucleolus is underlined by the identification of a number of protein complexes with functions beyond ribosome biogenesis. Finally, we were able to obtain experimental evidence of nucleolar localization of 11 proteins, which were predicted by our platform to be associates of nucleolar complexes. We believe other biological organelles or systems could be "wired" in a similar fashion, integrating different types of data with high-throughput proteomics, followed by a detailed biological analysis and experimental validation.     

Retroviral vectors for homologous recombination provide efficient cloning and expression in mammalian cells

Homologous recombination technologies enable high-throughput cloning and the seamless insertion of any DNA fragment into expression vectors. Additionally, retroviral vectors offer a fast and efficient method for transducing and expressing genes in mammalian cells, including lymphocytes. However, homologous recombination cannot be used to insert DNA fragments into retroviral vectors; retroviral vectors contain two homologous regions, the 5′- and 3′-long terminal repeats, between which homologous recombination occurs preferentially. In this study, we have modified a retroviral vector to enable the cloning of DNA fragments through homologous recombination. To this end, we inserted a bacterial selection marker in a region adjacent to the gene insertion site. We used the modified retroviral vector and homologous recombination to clone T-cell receptors (TCRs) from single Epstein Barr virus-specific human T cells in a high-throughput and comprehensive manner and to efficiently evaluate their function by transducing the TCRs into a murine T-cell line through retroviral infection. In conclusion, the modified retroviral vectors, in combination with the homologous recombination method, are powerful tools for the high-throughput cloning of cDNAs and their efficient functional analysis.