Quantitative proteomics based on 2D electrophoresis (2-DE) coupled with peptide mass fingerprinting is still one of the most widely used quantitative proteomics approaches in microbiology research. Our view on the exploitation of this global expression analysis technique and its contribution and potential to push forward the field of molecular microbial physiology towards a molecular systems microbiology perspective is discussed in this article. The advances registered in 2-DE-based quantitative proteomic analysis leading to increased protein resolution, sensitivity and accuracy, and the promising use of 2-DE to gain insights into post-translational modifications at a proteome-wide level (considering all the proteins/protein forms expressed by the genome) are focused on. Given the progress made in this field, it is foreseen that the 2-DE-based approach to quantitative proteomics will continue to be a fundamental tool for microbiologists working at a genome-wide scale. Guidelines are also provided for the exploitation of expression proteomics data, based on useful computational tools, and for the integration of these data with other genome-wide expression information. The advantages and limitations of a complete 2-DE-based expression proteomics analysis, envisaging the quantification of the global changes occurring in the proteome of a given cell depending on environmental or genetic manipulations, are discussed from the microbiologist's perspective. Particular focus is given to the emerging field of toxicoproteomics, a new systems toxicity approach that offers a powerful tool to directly monitor the earliest stages of the toxicological response by identifying critical proteins and pathways that are affected by, and respond to, a chemical stress. The experimental design and the bioinformatics analysis of data used in our laboratory to gain mechanistic insights through expression proteomics into the responses of the eukaryotic model Saccharomyces cerevisiae or of Pseudomonas strains to environmental toxicants are presented as case studies.
|Evidence ID||Analyze ID||Interactor||Interactor Systematic Name||Interactor||Interactor Systematic Name||Type||Assay||Annotation||Action||Modification||Phenotype||Source||Reference||Note|
|Evidence ID||Analyze ID||Gene||Gene Systematic Name||Gene Ontology Term||Gene Ontology Term ID||Qualifier||Aspect||Method||Evidence||Source||Assigned On||Annotation Extension||Reference|
|Evidence ID||Analyze ID||Gene||Gene Systematic Name||Phenotype||Experiment Type||Experiment Type Category||Mutant Information||Strain Background||Chemical||Details||Reference|
|Evidence ID||Analyze ID||Regulator||Regulator Systematic Name||Target||Target Systematic Name||Experiment||Assay||Construct||Conditions||Strain Background||Reference|