Current Proteomics - Volume 4, Issue 3, 2007

Proteomics is a still-evolving combination of technologies to describe and characterize all expressed proteins in a biological system. Because of upper limits on mass detection of mass spectrometers, the bottom-up approach is most widely employed in which tryptic peptides are quantified and identified from complex protein mixtures. Protein identification from tandem mass spectra is still a challenge in proteomics. Two approaches have been developed to identify proteins from tandem mass spectra, database searching and de novo sequencing. These approaches typically have positive identification rates of only ∼10-20%, and exhibit high false positive identification rates. This review surveys existing algorithms developed for database searching and de novo sequencing, with a focus on recent developments for tandem mass spectrum quality assessment, peptide identification using annotated spectra libraries, statistical approaches to assess identification quality, and methods for constrained searches. We also review research comparing the performance of existing protein identification packages.

Disease and drug-related alterations in the brain membrane proteome are of particular interest for investigations into neuropsychiatric disorders. Despite decades of research into neurotransmitters and their receptors, our understanding of complex neuropsychiatric disorders has failed to advance substantially. Therefore, global membrane protein profiling studies that are non-hypothesis driven and exploratory are a complementary approach to elucidate the underlying pathomechanisms associated with psychiatric disorders. Although membrane proteins play critical roles in almost all cellular processes, their unique biochemical properties have challenged current quantitative proteomics approaches. The aim of the present review is to critically evaluate and discuss the use and applicability of current quantitative proteomic platforms, sample preparation methods and statistical tools in view of their application to membrane proteome analysis of brain tissue.

Studies employing proteomic technologies to study interactions of host plant with pathogenic bacteria are limited. Most studies on plant-pathogen interactions usually employed genetic approaches, such as the use of in vivo expression technology (IVET) and DNA microarray. However, because of the intrinsic nature of these techniques, issues on time frame, mechanisms involved as well as localization are virtually unknown. Therefore, assimilation of knowledge in our understanding of the plant-pathogen interactions at the mechanical front and protein level is slow. Further, majority of these studies on plant-pathogen interactions focused either on the Type III secretary system (TTSS) and virulence factors of the pathogens or the activation of plant defense responses. Details of invasion strategies of microbial pathogens and the interplay between host and these pathogens are largely unknown. Investigations using proteomic technologies in these fields can provide information on subcellular localization of proteins of interest, time frame of expression, posttranslational modifications and even quantitative measurements of differentially expressed proteins. These are vital information in deciphering the biological events happening in both plant and pathogen perspectives during the invasion process. Moreover, data from proteomic investigations, in association with those obtained from DNA microarray studies could be amalgamated to construct a list of candidates whose roles in plant-pathogen interactions can be further studied. This review aims to summarize current findings on plant-pathogen interactions in compatible and incompatible systems as well as the possible contribution of proteomic investigations.

Increasing evidence demonstrated that Propionibacterium acnes (P. acnes) plays a central role in many human polymicrobial diseases including acne vulgaris, which afflicts more than one million people in the U.S. alone. To date, there are no appropriate therapeutic modalities that effectively control P. acnes succession during disease development. By taking advantage of the availability of genome and proteome of P. acnes, we have highlighted here the events of P. acnes adhesion and biofilm formation as potential targets for development of drugs or vaccines counteracting P. acnesassociated diseases.

Mass spectrometry has shown that NAP22, a neuron specific protein isolated from rat brain is myristoylated, and it was additionally demonstrated by physicochemical methods that the myristoylation functioning in tandem with the phospholipid membrane is also directly involved in the interaction with calmodulin. Furthermore, besides the myristoylated brain specific protein, Src kinase and the HIV nef gene product have been shown to interact with calmodulin in the same way. Interestingly, phosphorylation of the myristoylated proteins abolishes their interaction with calmodulin. Structural and functional studies have revealed that, besides the necessary conditions for myristoylation, the interaction requires certain additional conditions such as the co-existence of basic amino acid residues in the myristoylated domain. Thus, myristoylated proteins in cells regulate signal transduction between the membrane and cytoplasmic fractions. An algorithm we have developed to find myristoylated proteins in cells predicts hundreds of myristoylated proteins. Interestingly, a large portion of the myristoylated proteins supposed to take part in the signal transduction between the membrane and cytoplasmic fractions, such as NAP22 , are included in the the predicted myristoylated proteins. If the proteins functionally regulated by the posttranslational protein modification myristoylation are understood as cross-talk points within the intracellular signal transduction system, the known signaling pathways can be linked with each other, and a novel map of this intracellular network constructed.

Cardiac hypertrophy, interstitial fibrosis, and cardiac dysfunction ultimately lead to cardiac failure. Cardiac failure is one of the major causes of heart disease and death in our society. The molecular causes of heart diseases, like many other diseases, remain largely unknown. Recently, large-scale proteomics studies have been undertaken to better understand the underlying mechanisms of molecular causes of heart disease. Many protein alterations have already been identified in the human diseased myocardium. Further experiments on these proteins are ongoing to know their suitability for drug targets, therapeutic proteins, or disease biomarkers. This review deals with a proteomics perspective on human heart failure, and is divided into two parts. The first part provides a glimpse on proteomics technologies used for identification and quantification of proteins related to heart disease. The second part is the main focus of this review and deals with evolving biomarkers and clinical diagnostics, potential future drugs, clinical approaches in managing heart failure, and clinical shortcomings, which are discussed to some detail from the viewpoint of a medical doctor and proteomics scientists.

Although research on non-legume model species such as Arabidopsis thaliana and rice provides insight into many fundamental aspects of plant biology, it cannot address some important aspects of legume biology. Legumes are of immense importance to human and are an important crop for sustainable agriculture. Two model species, Lotus japonicas and Medicago truncatula, would have been the focus of genome sequencing and functional genomics programmes. Unfortunately, agricultural legumes are relatively poor model systems for genetics and genomics research. Even though soybean is an important crop to supply a major portion of the world's demand for vegetable oil and protein, the sequencing of the soybean genome is in its infancy. So, proteomics would be a powerful tool for its functional analysis. The purpose of this review is to discuss the strength and weaknesses of proteomics technologies and limitations of current techniques for soybean biology.