Alternative workflows for plant proteomic analysis

High-throughput separations are intrinsic to the detection and analysis of peptides and proteins by mass spectrometry (MS). Together, efficient separation and MS can lead to the identification of thousands of proteins in a sample, cell or tissue and help build proteome maps that can be used to define a cell type or cellular state. Although 2D gels have been successfully used to separate proteins for subsequent MS analysis, alternative separation efficiencies and, consequently deeper results could be obtained with HPLC or other separation techniques that improve throughput. This highlight is aimed toward plant scientists who have special separation needs due to the nature of plant cells and who could benefit from knowing options and requirements for adopting alternative separation protocols. Through the various sample processing and protein separation strategies, plant biologists should be able to improve the quality of their proteomic reference maps and gain new information about the proteins that define plant cells.     

Automated manipulation of systems biology models using libSBML within Taverna workflows

Many data manipulation processes involve the use of programming libraries. These processes may beneficially be automated due to their repeated use. A convenient type of automation is in the form of workflows that also allow such processes to be shared amongst the community. The Taverna workflow system has been extended to enable it to use and invoke Java classes and methods as tasks within Taverna workflows. These classes and methods are selected for use during workflow construction by a Java Doclet application called the API Consumer. This selection is stored as an XML file which enables Taverna to present the subset of the API for use in the composition of workflows. The ability of Taverna to invoke Java classes and methods is demonstrated by a workflow in which we use libSBML to map gene expression data onto a metabolic pathway represented as a SBML model. AVAILABILITY: Taverna and the API Consumer application can be freely downloaded from http://taverna.sourceforge.net     

Integration of residue-specific acid cleavage into proteomic workflows

Microwave-accelerated proteolysis using acetic acid has been shown to occur specifically on either or both sides of aspartate residues. This chemical cleavage is applied to the yeast ribosome proteome to evaluate its suitability for incorporation into high-throughput automated workflows. Peptide product mixtures were analyzed using either an HPLC-ESI-LTQ-Orbitrap or an HPLC-MALDI-TOF2. The peptides were readily identified, using MASCOT with a modified enzyme rule, and provided information about 73% of the proteome. Implications are considered of the extended length and the presence of multiple basic residues in these peptides.     

Comparative study of [Three] LC-MALDI workflows for the analysis of complex proteomic samples

Large-scale proteomic analyses frequently rely on high-resolution peptide separation of digested protein mixtures in multiple dimensions to achieve accuracy in sample detection and sensitivity in dynamic range of coverage. This study was undertaken to demonstrate the feasibility of MALDI MS/MS with off-line coupling to HPLC for the analysis of whole cell lysates of wild-type yeast by three different workflows: SCX-RPHPLC-MS/MS, high-pH SAX-RPHPLC-MS/MS and RP (protein)-SCX-RPHPLC-MS/MS. The purpose of these experiments was to demonstrate the effect of a workflow on the end results in terms of the number of proteins detected, the average peptide coverage of proteins, and the number of redundant peptide sequencing attempts. Using 60 microg of yeast lysate, minor differences were seen in the number of proteins detected by each method (800-1200). The most significant differences were observed in redundancy of MS/MS acquisitions.     

Advances in trematode biology

edited by Bernard Fried and Thaddeus K. Graczyk, CRC Press, 1997. pound88.50 (466 pages) ISBN 0 8493 2645 1.     

Standards for systems biology

High-throughput technologies are generating large amounts of complex data that have to be stored in databases, communicated to various data analysis tools and interpreted by scientists. Data representation and communication standards are needed to implement these steps efficiently. Here we give a classification of various standards related to systems biology and discuss various aspects of standardization in life sciences in general. Why are some standards more successful than others, what are the prerequisites for a standard to succeed and what are the possible pitfalls?     

Advances in proteomic prostate cancer biomarker discovery

Prostate cancer is the most common non-cutaneous cancer in men in the United States. For reasons largely unknown, the incidence of prostate cancer has increased in the last two decades, in spite or perhaps because of a concomitant increase in serum prostate-specific antigen (PSA) screening. While PSA is acknowledged not to be an ideal biomarker for prostate cancer detection, it is however widely used by physicians due to lack of an alternative. Thus, the identification of a biomarker(s) that can complement or replace PSA represents a major goal for prostate cancer research. Screening complex biological specimens such as blood, urine, and tissue to identify protein biomarkers has become increasingly popular over the last decade thanks to advances in proteomic discovery methods. The completion of human genome sequence together with new development in mass spectrometry instrumentation and bioinformatics has been a major driving force in biomarker discovery research. Here we review the current state of proteomic applications as applied to various sample sources including blood, urine, tissue, and “secretome” for the purpose of prostate cancer biomarker discovery. Additionally, we review recent developments in validation of putative markers, efforts at systems biology approach, and current challenges of proteomics in biomarker discovery.     

植物与病原菌互作的蛋白质组学研究进展

蛋白质组学作为功能基因组学研究的主要内容之一,在阐述基因功能、了解生命现象和本质的分子机制等方面发挥着重要作用。植物蛋白质组学作为蛋白质组学的一个分支,研究应用也越来越广泛,尤其是探索植物与病原菌互作机制是其中的一个研究热点。本文就多年来植物与真菌、病毒、细菌互作的蛋白质组学研究做一综述,并对当前该领域今后的研究方向进行展望,以期为相关研究提供一些参考和理论基础。     

苔藓植物的分子生物学研究

苔藓植物是一类较低等的陆生植物,但由于它生存环境的特殊性及物种本身的特性,在多种领域均具有重要的应用价值。主要从苔藓植物分子生物学的角度介绍国际和我国研究概况．以期为进一步加强认识、提高其利用价值提供帮助。     

Interaction networks for systems biology

Cellular functions are almost always the result of the coordinated action of several proteins, interacting in protein complexes, pathways or networks. Progress made in devising suitable tools for analysis of protein-protein interactions, have recently made it possible to chart interaction networks on a large-scale. The aim of this review is to provide a short overview of the most promising contributions of interaction networks to human biology, structural biology and human genetics.     

Imaging methodologies for systems biology

Systems biology has recently achieved significant success in the understanding of complex interconnected phenomena such as cell polarity and migration. In this context, the definition of systems biology has come to encompass the integration of quantitative measurements with sophisticated modeling approaches. This article will review recent progress in live cell imaging technologies that have expanded the possibilities of quantitative in vivo measurements, particularly in regards to molecule counting and quantitative measurements of protein concentration and dynamics. These methods have gained and continue to gain popularity with the biological community. In general, we will discuss three broad categories: protein interactions, protein quantitation, and protein dynamics.     

Pathway information for systems biology

Pathway information is vital for successful quantitative modeling of biological systems. The almost 170 online pathway databases vary widely in coverage and representation of biological processes, making their use extremely difficult. Future pathway information systems for querying, visualization and analysis must support standard exchange formats to successfully integrate data on a large scale. Such integrated systems will greatly facilitate the constructive cycle of computational model building and experimental verification that lies at the heart of systems biology.     

Mining literature for systems biology

Currently, literature is integrated in systems biology studies in three ways. Hand-curated pathways have been sufficient for assembling models in numerous studies. Second, literature is frequently accessed in a derived form, such as the concepts represented by the Medical Subject Headings (MeSH) and Gene Ontologies (GO), or functional relationships captured in protein-protein interaction (PPI) databases; both of these are convenient, consistent reductions of more complex concepts expressed as free text in the literature. Moreover, their contents are easily integrated into computational processes required for dealing with large data sets. Last, mining text directly for specific types of information is on the rise as text analytics methods become more accurate and accessible. These uses of literature, specifically manual curation, derived concepts captured in ontologies and databases, and indirect and direct application of text mining, will be discussed as they pertain to systems biology.