Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics.

BACKGROUND: Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories. RESULTS: Here, we develop the Quartet standard as a proteome reference material with built-in truths, and distribute the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 mass spectrometry files are obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There is a wide dynamic range of proteomes spanning about 7 orders of magnitude, and the injection order has marked effects on quantitative instead of qualitative characteristics. CONCLUSION: Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

A modification-centric assessment tool for the performance of chemoproteomic probes.

Chemoproteomics has emerged as a key technology to expand the functional space in complex proteomes for probing fundamental biology and for discovering new small-molecule-based therapies. Here we report a modification-centric computational tool termed pChem to provide a streamlined pipeline for unbiased performance assessment of chemoproteomic probes. The pipeline starts with an experimental setting for isotopically coding probe-derived modifications that can be automatically recognized by pChem, with masses accurately calculated and sites precisely localized. pChem exports on-demand reports by scoring the profiling efficiency, modification homogeneity and proteome-wide residue selectivity of a tested probe. The performance and robustness of pChem were benchmarked by applying it to eighteen bioorthogonal probes. These analyses reveal that the formation of unexpected probe-derived modifications can be driven by endogenous reactive metabolites (for example, bioactive aldehydes and glutathione). pChem is a powerful and user-friendly tool that aims to facilitate the development of probes for the ever-growing field of chemoproteomics.

Comprehensive assessment showed no associations of variants at the SLC10A1 locus with susceptibility to persistent HBV infection among Southern Chinese.

The sodium taurocholate cotransporting polypeptide (NTCP) encoded by SLC10A1 was recently demonstrated to be a functional receptor for hepatitis B virus (HBV). The role of SLC10A1 polymorphisms, particularly the Ser267Phe variant (rs2296651) in exon 4, has been frequently investigated in regard to risk of persistent HBV infection. However, these investigations have generated conflicting results. To examine whether common genetic variation at the SLC10A1 locus is associated with risk of persistent HBV infection, haplotype-tagging and imputed single nucleotide polymorphisms (SNPs) were assessed in two case-control sample sets, totally including 2,550 cases (persistently HBV infected subjects, PIs) and 2,124 controls (spontaneously recovered subjects, SRs) of Southern Chinese ancestry. To test whether rare or subpolymorphic SLC10A1 variants are associated with disease risk, the gene's exons in 244 cases were sequenced. Overall, we found neither SNPs nor haplotypes of SLC10A1 showed significant association in the two sample sets. Furthermore, no significant associations of rare variants or copy number variation covering SLC10A1 were observed. Finally, expression quantitative trait locus analyses revealed that SNPs potentially affecting SLC10A1 expression also showed no significant associations. We conclude that genetic variation at the SLC10A1 locus is not likely a major risk factor of persistent HBV infection among Southern Chinese.

The human proteome project: current state and future direction.

After the successful completion of the Human Genome Project, the Human Proteome Organization has recently officially launched a global Human Proteome Project (HPP), which is designed to map the entire human protein set. Given the lack of protein-level evidence for about 30% of the estimated 20,300 protein-coding genes, a systematic global effort will be necessary to achieve this goal with respect to protein abundance, distribution, subcellular localization, interaction with other biomolecules, and functions at specific time points. As a general experimental strategy, HPP research groups will use the three working pillars for HPP: mass spectrometry, antibody capture, and bioinformatics tools and knowledge bases. The HPP participants will take advantage of the output and cross-analyses from the ongoing Human Proteome Organization initiatives and a chromosome-centric protein mapping strategy, termed C-HPP, with which many national teams are currently engaged. In addition, numerous biologically driven and disease-oriented projects will be stimulated and facilitated by the HPP. Timely planning with proper governance of HPP will deliver a protein parts list, reagents, and tools for protein studies and analyses, and a stronger basis for personalized medicine. The Human Proteome Organization urges each national research funding agency and the scientific community at large to identify their preferred pathways to participate in aspects of this highly promising project in a HPP consortium of funders and investigators.

Spectral quality assessment and application for gel-based matrix-assisted laser desorption ionization-time of flight tandem mass spectrometer.

Gel-based matrix-assisted laser desorption ionization-time of flight tandem mass spectrometer (MALDI TOF/TOF MS) is one of the dominant methods of current proteomics, utilizing both peptide mass fingerprinting (PMF) and peptide fragment fingerprinting (PFF) for protein identification on a spot-to-spot basis. However, the unique impact of the quality of the corresponding mass spectrometry spectra remains largely unreported, and has motivated the development and use of an automatic spectra-assessment method. In this study, a multi-variant regression approach has been utilized to assess spectral quality for both PMF and PFF spectra obtained from MALDI TOF/TOF MS. The assessment index has been applied to investigations of MASCOT search results. Systematic examination of two large-scale sets of human liver tissue data has proved that spectral quality was a key factor in significant matching. Based on large-scale investigations on individual PMF search, individual PFF search and their combination, respectively, the filtering of bad quality spectra or spots proves to be an efficient way to improve search efficiency of all search modes in MASCOT. Meanwhile, a validation method based on score differences between normal and decoy (reverse or random) database searches is proposed to precisely define the positive matches. Further analysis showed that spectral quality assessment was also efficient in representing the quality of 2-DE gel spots and promoted the discovery of potential post-translation modifications.

Bioinformatics analyses for signal transduction networks.

Research in signaling networks contributes to a deeper understanding of organism living activities. With the development of experimental methods in the signal transduction field, more and more mechanisms of signaling pathways have been discovered. This paper introduces such popular bioinformatics analysis methods for signaling networks as the common mechanism of signaling pathways and database resource on the Internet, summerizes the methods of analyzing the structural properties of networks, including structural Motif finding and automated pathways generation, and discusses the modeling and simulation of signaling networks in detail, as well as the research situation and tendency in this area. Now the investigation of signal transduction is developing from small-scale experiments to large-scale network analysis, and dynamic simulation of networks is closer to the real system. With the investigation going deeper than ever, the bioinformatics analysis of signal transduction would have immense space for development and application.