Power and limitations of electrophoretic separations in proteomics strategies

Proteomics can be defined as the large-scale analysis of proteins. Due to the complexity of biological systems, it is required to concatenate various separation techniques prior to mass spectrometry. These techniques, dealing with proteins or peptides, can rely on chromatography or electrophoresis. In this review, the electrophoretic techniques are under scrutiny. Their principles are recalled, and their applications for peptide and protein separations are presented and critically discussed. In addition, the features that are specific to gel electrophoresis and that interplay with mass spectrometry (i.e., protein detection after electrophoresis, and the process leading from a gel piece to a solution of peptides) are also discussed

Feature Detection Techniques for Preprocessing Proteomic Data

Numerous gel-based and nongel-based technologies are used to detect protein changes potentially associated with disease. The raw data, however, are abundant with technical and structural complexities, making statistical analysis a difficult task. Low-level analysis issues (including normalization, background correction, gel and/or spectral alignment, feature detection, and image registration) are substantial problems that need to be addressed, because any large-level data analyses are contingent on appropriate and statistically sound low-level procedures. Feature detection approaches are particularly interesting due to the increased computational speed associated with subsequent calculations. Such summary data corresponding to image features provide a significant reduction in overall data size and structure while retaining key information. In this paper, we focus on recent advances in feature detection as a tool for preprocessing proteomic data. This work highlights existing and newly developed feature detection algorithms for proteomic datasets, particularly relating to time-of-flight mass spectrometry, and two-dimensional gel electrophoresis. Note, however, that the associated data structures (i.e., spectral data, and images containing spots) used as input for these methods are obtained via all gel-based and nongel-based methods discussed in this manuscript, and thus the discussed methods are likewise applicable

Computational Methods on Study of Differentially Expressed Proteins in Maize Proteomes Associated with Resistance to Aflatoxin Accumulation

Plant breeders have focused on improving maize resistance to Aspergillus flavus infection and aflatoxin accumulation by breeding with genotypes having the desirable traits. Various maize inbred lines have been developed for the breeding of resistance. Identification of differentially expressed proteins among such maize inbred lines will facilitate the development of gene markers and expedite the breeding process. Computational biology and proteomics approaches on the investigation of differentially expressed proteins were explored in this research. The major research objectives included 1) application of computational methods in homology and comparative modeling to study 3D protein structures and identify single nucleotide polymorphisms (SNPs) involved in changes of protein structures and functions, which can in turn increase the efficiency of the development of DNA markers; 2) investigation of methods on total protein profiling including purification, separation, visualization, and computational analysis at the proteome level. Special research goals were set on the development of open source computational methods using Matlab image processing tools to quantify and compare protein expression levels visualized by 2D protein electrophoresis gel techniques

Applications of Mass Spectrometry to Analysis of Prodiginines, Bioactivated Methylenedianiline Intermediates, and Hypoxia Induced Changes in the Zebrafish Skeletal Muscle Proteome

Mass spectrometry coupled with liquid chromatography and gel electrophoresis enables separation and detection of components in a complex mixture. During the last two decades, its applications were dramatically extended and remarkable progress has been made in many fields, in particular, environmental and biological analyses. This dissertation focuses on identification and characterization of biologically active compounds and comparative analysis of protein expression changes. The first two projects (Chapters 2 and 3) focus on the application of LC/MS approach to profile the bioactivated intermediates of 4, 4\u27-methylenedianiline (DAPM) from rat vascular smooth muscle cells (VSMCs) and bile. In our study, several DAPM metabolites were detected and characterized in detail by liquid chromatography-electrospray tandem mass spectrometry. The structural assignments of these metabolites from VSMCs and rat bile significantly improve our understanding of DAPM biotransformations and toxicity. The third project described in Chapter 4 focuses on using electrospray tandem mass spectrometry (ES-MS/MS) and theoretical calculation (GAUSSIAN 03 program) to investigate the unusual methyl radical loss and consecutive fragment ions that dominate the low-energy collision induced dissociation (CID) mass spectra of prodiginine compounds. Structures of the fragment ions are proposed and explanations are given to rationalize the observed competition between the formation of even-electron ions and radical ions. Our study shows that the lower apparent threshold associated with methyl radical loss points to a lower kinetic barrier. In Chapter 5, hypoxia-induced changes of zebrafish skeletal muscle were studied using two-dimensional difference in-gel electrophoresis (2D-DIGE) in vivo after 48 h in hypoxia vs. normoxia. The results showed that proteins involved in mitochondrial oxidative metabolism are down-regulated, whereas glycolytic enzymes are up-regulated to compensate for the loss of ATP synthesis in aerobic metabolism. The up-regulation of two spots identified as hemoglobin variants was also observed. These protein expression changes are consistent with a hypoxic response that enhances anaerobic metabolism or O2 transport to tissues

The state of the art in the analysis of two-dimensional gel electrophoresis images

Software-based image analysis is a crucial step in the biological interpretation of two-dimensional gel electrophoresis experiments. Recent significant advances in image processing methods combined with powerful computing hardware have enabled the routine analysis of large experiments. We cover the process starting with the imaging of 2-D gels, quantitation of spots, creation of expression profiles to statistical expression analysis followed by the presentation of results. Challenges for analysis software as well as good practices are highlighted. We emphasize image warping and related methods that are able to overcome the difficulties that are due to varying migration positions of spots between gels. Spot detection, quantitation, normalization, and the creation of expression profiles are described in detail. The recent development of consensus spot patterns and complete expression profiles enables one to take full advantage of statistical methods for expression analysis that are well established for the analysis of DNA microarray experiments. We close with an overview of visualization and presentation methods (proteome maps) and current challenges in the field

A MASS SPECTROMETRY-BASED STUDY OF SERUM BUTYRYLCHOLINESTERASE INHIBITION FROM PESTICIDE EXPOSURE AND ORGANOPHOSPHATE PESTICIDE-INDUCED PROTEOME ALTERATION

Pesticides including organophosphates (OPs) and carbamates (CBs) are widelyused to control undesirable pests. These compounds are neurotoxic and inhibithydrolysis of the neurotransmitter acetylcholine by acetylcholinesterase. Public healthconcerns have increased with the escalating usage of pesticides. Reliable monitoringprograms are required to detect and quantify pesticide exposure, as well as to promotean understanding of their neurotoxic properties. In this dissertation, both theanticholinergic (Part I) toxicity and neurotoxicity in neuroblastoma cells (Part II) ofpesticides were explored using mass spectrometry (MS). The high sensitivity andhigh-throughput of this technique renders it well-suited for proteomics analysis.Part I describes the study of butyrylcholinesterase (BChE) inhibition resultingfrom OP and CB exposure. The main hypothesis of Part I is that the specialmodification of BChE can provide the origin and extent of pesticide exposure. A novelmethod for detection and quantification of pesticide exposure was designed using aproteomics approach and equine BChE (eBChE) as a model system. The methodologyfeatured detection and analysis of phosphorylated or carbamylated peptides at theactive site serine residue. The developed technique was successfully applied towardsthe study of human BChE (hBChE) inhibition in vitro and in serum samples. Aspecially designed affinity column enabled an isolation of BChE from serum. EnrichedBChE was subjected to enzymatic digestion by a novel on-bead double digestionprotocol. LC/MS/MS was employed to produce a calibration system for the analysis ofhBChE inhibition, which was then applied towards quantification of the enzyme.Part II describes a proteomic study of the neurotoxicity in neuroblastoma cellscaused from chlorpyrifos (CPF), an organophosphate pesticide. The concerns of CPFexposure to pregnant women, infants and children are increasing due todevelopmentally neurotoxic effects of this chemical. The main hypothesis of Part II isthat CPF can cause protein alterations and these altered proteins can be detected usingproteomics. Systematic studies at subcellular levels evaluated proteome changes inSH-SY5Y cells exposed to CPF. Two-dimensional gel electrophoresis (2DE) wasapplied with MALDI-TOF-MS to analyze differential protein expression. Thirty sevencommon unique altered proteins were identified, which play important roles inmetabolic pathway

Proteome comparison of helicobacter pylori isolates associated with four disease groups

The Gram-negative bacterium Helicobacter pylori is found in human gastric mucosa. H. pylori, one of the most common chronic bacterial infections of humans, is present in almost half of the world population. It is associated with chronic gastritis, non-ulcer dyspepsia, gastric and duodenal ulcers, and malignant neoplasms. The aim of this study was to detect microbial candidate protein markers whose presence might be correlated with the development of four different clinical consequences of H. pylori infection, gastric ulceration [GU], duodenal ulceration [DU], non-ulcer dyspepsia [NUD] and gastritis [GI]. Eleven H. pylori isolates associated with these outcomes were analysed. The total complement of protein from these H. pylori isolates were resolved by two-dimensional polyacrylamide gel electrophoresis (2D-PAGE) and compared using PDQUEST pattern analysis software. Relationships between the isolates associated with specific disease outcomes were determined by cluster analysis.Fifty six disease specific proteins were then characterised by tryptic peptide-mass fingerprinting using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Up to 1165 protein species were resolved from each H. pylori strain. Proteome analysis revealed that only 470 (40%) of the proteins detected were common to all eleven isolates. Twenty six of the 56 disease specific proteins that were selected for identification consisted of spots whose expression is altered in response to stress conditions or those that can affect H. pylori cell division and the cell membrane. The remaining 30 proteins had no known function. This study has provided further confirmation of the extensive variation that the bacterium H. pylori exhibits at the proteome level. Most significantly this study has found, through the application of cluster analysis and protein matching, that isolates do form disease groups. Comparative proteome analysis is a useful method for highlighting the extensive strain variation that H. pylori exhibits and to determine if any disease specific proteins exist

Integrating Micro-Scale Separations to Matrix Assisted Laser Desorption and Ioniation Time of Flight Mass Spectrometry (MALDI-TOF-MS) for Protein Analysis

This dissertation describes the integration of micro-scale separations to matrix assisted laser desorption and ionization time-of-flight mass spectrometry (MALDI TOF MS) for protein analysis. MALDI MS provides unsurpassed accurate mass measurements of intact bio-molecules, for example peptides and proteins, which in turn generate high molecular specificity enabling the identity, function and structure of these molecules to be characterized. However, in order to realize the full potential of MS in proteomic studies, integrated sample processing on automated and high throughput platforms is required to address the complexity, diversity and the dynamic range of proteomic analysis. The work described here contributes towards the development of automated and high throughput micro-total analysis systems (µ-TAS) for proteomics. An overview of mass spectrometry instrumentation and techniques used in protein analysis is presented to highlight the significance of the work described. Microfluidics devices can serve as automated and high throughput platforms for integrating proteomics sample processing steps such as whole cell lyses, enrichment, solubilization, denaturation, protein separations, proteolytic digestion and chromatographic separations of peptides prior to MALDI TOF MS analysis. Therefore, coupling microfluidics devices to biological mass spectrometry is the first logical step towards developing fully integrated and automated systems for protein analysis. On-line and off-line approaches for analysis from microfluidic devices are discussed. The development of a specially tailored rotating ball inlet for automated on-line MALDI MS sample introduction from an electrophoresis-based separation platform is described. Electrophoresis-based micro-scale separations of peptides on fused silica capillary and polymer-based microfluidic devices were coupled to on-line MALDI TOF MS using a rotating ball inlet. The rotating ball inlet allowed for individual technique optimization and automation thereby eliminating the need for fractionation and routine MALDI sample preparation. High throughput solid phase micro-reactors for efficient enzymatic cleavages and improved protein identification with MALDI MS in a microfluidic device were also developed for incorporation in an integrated protein analysis microfluidic system. Future work that outlines the framework and focus geared towards integrating the modules discussed in this dissertation into a functional micro-total analysis system for protein sample processing is discussed

High-throughput isolation and characterization of untagged membrane protein complexes: outer membrane complexes of Desulfovibrio vulgaris.

Cell membranes represent the "front line" of cellular defense and the interface between a cell and its environment. To determine the range of proteins and protein complexes that are present in the cell membranes of a target organism, we have utilized a "tagless" process for the system-wide isolation and identification of native membrane protein complexes. As an initial subject for study, we have chosen the Gram-negative sulfate-reducing bacterium Desulfovibrio vulgaris. With this tagless methodology, we have identified about two-thirds of the outer membrane- associated proteins anticipated. Approximately three-fourths of these appear to form homomeric complexes. Statistical and machine-learning methods used to analyze data compiled over multiple experiments revealed networks of additional protein-protein interactions providing insight into heteromeric contacts made between proteins across this region of the cell. Taken together, these results establish a D. vulgaris outer membrane protein data set that will be essential for the detection and characterization of environment-driven changes in the outer membrane proteome and in the modeling of stress response pathways. The workflow utilized here should be effective for the global characterization of membrane protein complexes in a wide range of organisms