Saliva proteomics as an emerging, non-invasive tool to study livestock physiology, nutrition and diseases

Saliva is an extraordinary fluid in terms of research and diagnostic possibilities. Its composition in electrolytes, hormones and especially its proteome contains information about feeding status, nutritional requirements and adaptations to diet and environment, and also about health status of animals. It is easy to collect on a non-invasive and routine basis without any need for special training. Therefore, the analysis of salivary proteomes is going to emerge into a field of high interest with the future goal to maintain and improve livestock productivity and welfare. Moreover, the comprehensive analysis and identification of salivary proteins and peptides in whole and glandular saliva is a necessary pre-requisite to identify animal disease biomarkers and a powerful tool to better understand animal physiology. This review focuses on the different approaches used to study the salivary proteomes of farm animals, in respect to the physiology of nutrition and food perception in relation to food choices. The potential of animal saliva as a source of disease biomarkers will also be pointed out. Special emphasis is laid on the 'ruminating triad' - cattle, goat and sheep - as well as swine as major species of animal production in Western and Southern Europe.     

PatternLab for proteomics: a tool for differential shotgun proteomics

Background  

A goal of proteomics is to distinguish between states of a biological system by identifying protein expression differences. Liu et al. demonstrated a method to perform semi-relative protein quantitation in shotgun proteomics data by correlating the number of tandem mass spectra obtained for each protein, or "spectral count", with its abundance in a mixture; however, two issues have remained open: how to normalize spectral counting data and how to efficiently pinpoint differences between profiles. Moreover, Chen et al. recently showed how to increase the number of identified proteins in shotgun proteomics by analyzing samples with different MS-compatible detergents while performing proteolytic digestion. The latter introduced new challenges as seen from the data analysis perspective, since replicate readings are not acquired.     

Antibody suspension bead arrays within serum proteomics

Antibody microarrays offer a powerful tool to screen for target proteins in complex samples. Here, we describe an approach for systematic analysis of serum, based on antibodies and using color-coded beads for the creation of antibody arrays in suspension. This method, adapted from planar antibody arrays, offers a fast, flexible, and multiplexed procedure to screen larger numbers of serum samples, and no purification steps are required to remove excess labeling substance. The assay system detected proteins down to lower picomolar levels with dynamic ranges over 3 orders of magnitude. The feasibility of this workflow was shown in a study with more than 200 clinical serum samples tested for 20 serum proteins.     

Supporting tool suite for production proteomics

SUMMARY: The large amount of data produced by proteomics experiments requires effective bioinformatics tools for the integration of data management and data analysis. Here we introduce a suite of tools developed at Vanderbilt University to support production proteomics. We present the Backup Utility Service tool for automated instrument file backup and the ScanSifter tool for data conversion. We also describe a queuing system to coordinate identification pipelines and the File Collector tool for batch copying analytical results. These tools are individually useful but collectively reinforce each other. They are particularly valuable for proteomics core facilities or research institutions that need to manage multiple mass spectrometers. With minor changes, they could support other types of biomolecular resource facilities.     

High-performance proteomics as a tool in biomarker discovery

Biomarkers allowing early detection of disease or therapy control have a huge influence in curing a disease. A wide variety of methods were applied to find new biomarkers. In contrast to methods focused on DNA or mRNA techniques, approaches considering proteins as potential biomarker candidates have the advantage that proteins are more diverse than DNA or RNA and are more reflective of a biological system. Here, we present an approach for the identification of new biomarkers relying on our experience from the past 10 years of proteomics, outlining a concept of "high-performance proteomics" This approach is based on quantitative proteome analysis using a sufficient number of clinical samples and statistical validation of proteomics data by independent methods, such as Western blot analysis or immunohistochemistry.     

Mesenchymal stem cells: an emerging tool for cancer targeting and therapy

Mesenchymal stem cells (MSCs) from post-natal bone marrow possess tremendous potential for cell-mediated gene therapy in several disease processes, and recent reports have broadened the spectrum for therapeutic applications to cancer therapy. The evidence that sites of active tumorigenesis favor the homing of exogenous MSCs have support the rationale for developing engineered MSCs as a tool to track malignant tissues and deliver anticancer agents within the tumor microenvironment. Several reports have proven the efficiency of MSCs as cell carrier for in vivo delivery of various clinically relevant anticancer factors, including cytokines, interferon, pro-drugs or replicative adenovirus, and tumor growth inhibition following engraftment within or in the vicinity of tumor. The enthusiasm for MSCs is further reinforced by the striking observation that unmodified MSCs can exert antitumorigenic activity, and preliminary reports in immunocompetent animals have provided encouraging results for the use of MSCs in cancer immunotherapy. This review highlights recent works and potential clinical applications of MSCs in this field.     

Prostate cancer proteomics

Proteomics has offered the hope of biomarker discovery to improve the management of prostate cancer. Markers are needed for screening and diagnosis, distinguishing latent from aggressive disease, defining the men who will benefit from therapy, differentiating localized from metastatic disease, predicting outcome and identifying new targets for therapy. There are many potential sources of proteins derived from the prostate, including urine, prostatic fluid (expressed or ejaculate), serum, and plasma or tissue, each with distinct advantages and limitations. Equally, there are many methodological platforms for proteomic studies of the prostate. Despite the promise, protoemics has yielded little of relevance to the management of prostate cancer, and most of the work that has been published is either irreproducible or of no clinical value.     

Image analysis tools and emerging algorithms for expression proteomics

Since their origins in academic endeavours in the 1970s, computational analysis tools have matured into a number of established commercial packages that underpin research in expression proteomics. In this paper we describe the image analysis pipeline for the established 2-DE technique of protein separation, and by first covering signal analysis for MS, we also explain the current image analysis workflow for the emerging high-throughput 'shotgun' proteomics platform of LC coupled to MS (LC/MS). The bioinformatics challenges for both methods are illustrated and compared, whereas existing commercial and academic packages and their workflows are described from both a user's and a technical perspective. Attention is given to the importance of sound statistical treatment of the resultant quantifications in the search for differential expression. Despite wide availability of proteomics software, a number of challenges have yet to be overcome regarding algorithm accuracy, objectivity and automation, generally due to deterministic spot-centric approaches that discard information early in the pipeline, propagating errors. We review recent advances in signal and image analysis algorithms in 2-DE, MS, LC/MS and Imaging MS. Particular attention is given to wavelet techniques, automated image-based alignment and differential analysis in 2-DE, Bayesian peak mixture models, and functional mixed modelling in MS, and group-wise consensus alignment methods for LC/MS.     

Affinity chromatography: a useful tool in proteomics studies

Separation or fractionation of a biological sample in order to reduce its complexity is often a prerequisite to qualitative or quantitative proteomic approaches. Affinity chromatography is an efficient protein separation method based on the interaction between target proteins and specific immobilized ligands. The large range of available ligands allows to separate a complex biological extract in different protein classes or to isolate the low abundance species such as post-translationally modified proteins. This method plays an essential role in the isolation of protein complexes and in the identification of protein-protein interaction networks. Affinity chromatography is also required for quantification of protein expression by using isotope-coded affinity tags.     

Viral proteomics: The emerging cutting-edge of virus research

Viruses replicate and proliferate in host cells while continuously adjusting to and modulating the host environment. They encode a wide spectrum of multifunctional proteins, which interplay with and modify proteins in host cells. Viral genomes were chronologically the first to be sequenced. However, the corresponding viral proteomes, the alterations of host proteomes upon viral infection, and the dynamic nature of proteins, such as post-translational modifications, enzymatic cleavage, and activation or destruction by proteolysis, remain largely unknown. Emerging high-throughput techniques, in particular quantitative or semi-quantitative mass spectrometry-based proteomics analysis of viral and cellular proteomes, have been applied to define viruses and their interactions with their hosts. Here, we review the major areas of viral proteomics, including virion proteomics, structural proteomics, viral protein interactomics, and changes to the host cell proteome upon viral infection.     

Current perspectives in cancer proteomics

Proteome technology has been used widely in cancer research and is a useful tool for the identification of new cancer markers and treatment-related changes in cancer. This article details the use of proteome technology in cancer research, and laboratory-based and clinical cancer research studies are described. New developments in proteome technology that enable higher sample-throughput are evaluated and methods for enhancing conventional proteome analysis (based on two-dimensional electrophoresis) discussed. The need to couple laboratory-based proteomics research with clinically relevant models of the disease is also considered, as this remains the next main challenge of cancer-related proteome research.     

The emerging role of mass spectrometry-based proteomics in molecular pharming practices

Molecular pharming relies on the integration of foreign genes into a plant system for production of the desired recombinant protein. The speed, scalability, and lack of contaminating human pathogens highlights plants as an enticing and feasible system to produce diverse protein-based products, including vaccines, antibodies, and enzymes. However, limitations of expression levels, host defense responses, and production irregularities underscore distinct areas for improvement within the molecular pharming pipeline. Within the past five years, mass spectrometry-based proteomics has begun to address these critical areas and show promise in advancing our understanding of the complex biological systems driving molecular pharming. Further, opportunities to leverage comprehensive proteome profiling have surfaced to meet good manufacturing practice regulations and move biopharmaceuticals derived from plants into mainstream production.     

Metal-enhanced fluorescence: an emerging tool in biotechnology

Over the past 15 years, fluorescence has become the dominant detection/sensing technology in medical diagnostics and biotechnology. Although fluorescence is a highly sensitive technique, where single molecules can readily be detected, there is still a drive for reduced detection limits. The detection of a fluorophore is usually limited by its quantum yield, autofluorescence of the samples and/or the photostability of the fluorophores; however, there has been a recent explosion in the use of metallic nanostructures to favorably modify the spectral properties of fluorophores and to alleviate some of these fluorophore photophysical constraints. The use of fluorophore-metal interactions has been termed radiative decay engineering, metal-enhanced fluorescence or surface-enhanced fluorescence.     

Structural proteomics: a tool for genome annotation

In any newly sequenced genome, 30% to 50% of genes encode proteins with unknown molecular or cellular function. Fortunately, structural genomics is emerging as a powerful approach of functional annotation. Because of recent developments in high-throughput technologies, ongoing structural genomics projects are generating new structures at an unprecedented rate. In the past year, structural studies have identified many new structural motifs involved in enzymatic catalysis or in binding ligands or other macromolecules (DNA, RNA, protein). The efficiency by which function is deduced from structure can be further improved by the integration of structure with bioinformatics and other experimental approaches, such as screening for enzymatic activity or ligand binding.     

Population proteomics: an emerging discipline to study metapopulation ecology

Proteomics research has developed until recently in a relative isolation from other fast-moving disciplines such as ecology and evolution. This is unfortunate since applying proteomics to these disciplines has apparently the potential to open new perspectives. The huge majority of species indeed exhibit over their entire geographic range a metapopulation structure, occupying habitats that are fragmented and heterogeneous in space and/or through time. Traditionally, population genetics is the main tool used to studying metatopulations, as it describes the spatial structure of populations and the level of gene flow between them. In this Viewpoint, we present the reasons why we think that proteomics, because of the level of integration it promotes, has the potential to resolve interesting issues specific to metapopulation biology and adaptive processes.