A mass accuracy sensitive probability based scoring algorithm for database searching of tandem mass spectrometry data

<p>Abstract</p> <p>Background</p> <p>Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) has become one of the most used tools in mass spectrometry based proteomics. Various algorithms have since been developed to automate the process for modern high-throughput LC-MS/MS experiments.</p> <p>Results</p> <p>A probability based statistical scoring model for assessing peptide and protein matches in tandem MS database search was derived. The statistical scores in the model represent the probability that a peptide match is a random occurrence based on the number or the total abundance of matched product ions in the experimental spectrum. The model also calculates probability based scores to assess protein matches. Thus the protein scores in the model reflect the significance of protein matches and can be used to differentiate true from random protein matches.</p> <p>Conclusion</p> <p>The model is sensitive to high mass accuracy and implicitly takes mass accuracy into account during scoring. High mass accuracy will not only reduce false positives, but also improves the scores of true positive matches. The algorithm is incorporated in an automated database search program MassMatrix.</p

A Chaperone Trap Contributes to the Onset of Cystic Fibrosis

Protein folding is the primary role of proteostasis network (PN) where chaperone interactions with client proteins determine the success or failure of the folding reaction in the cell. We now address how the Phe508 deletion in the NBD1 domain of the cystic fibrosis (CF) transmembrane conductance regulator (CFTR) protein responsible for cystic fibrosis (CF) impacts the binding of CFTR with cellular chaperones. We applied single ion reaction monitoring mass spectrometry (SRM-MS) to quantitatively characterize the stoichiometry of the heat shock proteins (Hsps) in CFTR folding intermediates in vivo and mapped the sites of interaction of the NBD1 domain of CFTR with Hsp90 in vitro. Unlike folding of WT-CFTR, we now demonstrate the presence of ΔF508-CFTR in a stalled folding intermediate in stoichiometric association with the core Hsps 40, 70 and 90, referred to as a ‘chaperone trap’. Culturing cells at 30 C resulted in correction of ΔF508-CFTR trafficking and function, restoring the sub-stoichiometric association of core Hsps observed for WT-CFTR. These results support the interpretation that ΔF508-CFTR is restricted to a chaperone-bound folding intermediate, a state that may contribute to its loss of trafficking and increased targeting for degradation. We propose that stalled folding intermediates could define a critical proteostasis pathway branch-point(s) responsible for the loss of function in misfolding diseases as observed in CF

Differential Proteomic Analysis of Mammalian Tissues Using SILAM

Differential expression of proteins between tissues underlies organ-specific functions. Under certain pathological conditions, this may also lead to tissue vulnerability. Furthermore, post-translational modifications exist between different cell types and pathological conditions. We employed SILAM (Stable Isotope Labeling in Mammals) combined with mass spectrometry to quantify the proteome between mammalian tissues. Using 15N labeled rat tissue, we quantified 3742 phosphorylated peptides in nuclear extracts from liver and brain tissue. Analysis of the phosphorylation sites revealed tissue specific kinase motifs. Although these tissues are quite different in their composition and function, more than 500 protein identifications were common to both tissues. Specifically, we identified an up-regulation in the brain of the phosphoprotein, ZFHX1B, in which a genetic deletion causes the neurological disorder Mowat–Wilson syndrome. Finally, pathway analysis revealed distinct nuclear pathways enriched in each tissue. Our findings provide a valuable resource as a starting point for further understanding of tissue specific gene regulation and demonstrate SILAM as a useful strategy for the differential proteomic analysis of mammalian tissues

Analysis of Bovine Viral Diarrhea Viruses-infected monocytes: identification of cytopathic and non-cytopathic biotype differences

<p>Abstract</p> <p>Background</p> <p>Bovine Viral Diarrhea Virus (BVDV) infection is widespread in cattle worldwide, causing important economic losses. Pathogenesis of the disease caused by BVDV is complex, as each BVDV strain has two biotypes: non-cytopathic (ncp) and cytopathic (cp). BVDV can cause a persistent latent infection and immune suppression if animals are infected with an ncp biotype during early gestation, followed by a subsequent infection of the cp biotype. The molecular mechanisms that underscore the complex disease etiology leading to immune suppression in cattle caused by BVDV are not well understood.</p> <p>Results</p> <p>Using proteomics, we evaluated the effect of cp and ncp BVDV infection of bovine monocytes to determine their role in viral immune suppression and uncontrolled inflammation. Proteins were isolated by differential detergent fractionation and identified by 2D-LC ESI MS/MS. We identified 137 and 228 significantly altered bovine proteins due to ncp and cp BVDV infection, respectively. Functional analysis of these proteins using the Gene Ontology (GO) showed multiple under- and over- represented GO functions in molecular function, biological process and cellular component between the two BVDV biotypes. Analysis of the top immunological pathways affected by BVDV infection revealed that pathways representing macropinocytosis signalling, virus entry via endocytic pathway, integrin signalling and primary immunodeficiency signalling were identified only in ncp BVDV-infected monocytes. In contrast, pathways like actin cytoskeleton signalling, RhoA signalling, clathrin-mediated endocytosis signalling and interferon signalling were identified only in cp BDVD-infected cells. Of the six common pathways involved in cp and ncp BVDV infection, acute phase response signalling was the most significant for both BVDV biotypes. Although, most shared altered host proteins between both BVDV biotypes showed the same type of change, integrin alpha 2b (ITGA2B) and integrin beta 3 (ITGB3) were down- regulated by ncp BVDV and up- regulated by cp BVDV infection.</p> <p>Conclusions</p> <p>This study shows that, as we expected, there are significant functional differences in the host proteins that respond to cp or ncp BVDV infection. The combined use of GO and systems biology network modelling facilitated a better understanding of host-pathogen interactions.</p

Current challenges in software solutions for mass spectrometry-based quantitative proteomics

This work was in part supported by the PRIME-XS project, grant agreement number 262067, funded by the European Union seventh Framework Programme; The Netherlands Proteomics Centre, embedded in The Netherlands Genomics Initiative; The Netherlands Bioinformatics Centre; and the Centre for Biomedical Genetics (to S.C., B.B. and A.J.R.H); by NIH grants NCRR RR001614 and RR019934 (to the UCSF Mass Spectrometry Facility, director: A.L. Burlingame, P.B.); and by grants from the MRC, CR-UK, BBSRC and Barts and the London Charity (to P.C.

Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational proteomics

<p>Abstract</p> <p>Background</p> <p>High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination with database searching algorithms. A major problem with existing methods lies within the significant number of false positive and false negative annotations. So far, standard algorithms for protein identification do not use the information gained from separation processes usually involved in peptide analysis, such as retention time information, which are readily available from chromatographic separation of the sample. Identification can thus be improved by comparing measured retention times to predicted retention times. Current prediction models are derived from a set of measured test analytes but they usually require large amounts of training data.</p> <p>Results</p> <p>We introduce a new kernel function which can be applied in combination with support vector machines to a wide range of computational proteomics problems. We show the performance of this new approach by applying it to the prediction of peptide adsorption/elution behavior in strong anion-exchange solid-phase extraction (SAX-SPE) and ion-pair reversed-phase high-performance liquid chromatography (IP-RP-HPLC). Furthermore, the predicted retention times are used to improve spectrum identifications by a <it>p</it>-value-based filtering approach. The approach was tested on a number of different datasets and shows excellent performance while requiring only very small training sets (about 40 peptides instead of thousands). Using the retention time predictor in our retention time filter improves the fraction of correctly identified peptide mass spectra significantly.</p> <p>Conclusion</p> <p>The proposed kernel function is well-suited for the prediction of chromatographic separation in computational proteomics and requires only a limited amount of training data. The performance of this new method is demonstrated by applying it to peptide retention time prediction in IP-RP-HPLC and prediction of peptide sample fractionation in SAX-SPE. Finally, we incorporate the predicted chromatographic behavior in a <it>p</it>-value based filter to improve peptide identifications based on liquid chromatography-tandem mass spectrometry.</p

Proteomics-Based Systems Biology Modeling of Bovine Germinal Vesicle Stage Oocyte and Cumulus Cell Interaction

BACKGROUND: Oocytes are the female gametes which establish the program of life after fertilization. Interactions between oocyte and the surrounding cumulus cells at germinal vesicle (GV) stage are considered essential for proper maturation or 'programming' of oocytes, which is crucial for normal fertilization and embryonic development. However, despite its importance, little is known about the molecular events and pathways involved in this bidirectional communication. METHODOLOGY/PRINCIPAL FINDINGS: We used differential detergent fractionation multidimensional protein identification technology (DDF-Mud PIT) on bovine GV oocyte and cumulus cells and identified 811 and 1247 proteins in GV oocyte and cumulus cells, respectively; 371 proteins were significantly differentially expressed between each cell type. Systems biology modeling, which included Gene Ontology (GO) and canonical genetic pathway analysis, showed that cumulus cells have higher expression of proteins involved in cell communication, generation of precursor metabolites and energy, as well as transport than GV oocytes. Our data also suggests a hypothesis that oocytes may depend on the presence of cumulus cells to generate specific cellular signals to coordinate their growth and maturation. CONCLUSIONS/SIGNIFICANCE: Systems biology modeling of bovine oocytes and cumulus cells in the context of GO and protein interaction networks identified the signaling pathways associated with the proteins involved in cell-to-cell signaling biological process that may have implications in oocyte competence and maturation. This first comprehensive systems biology modeling of bovine oocytes and cumulus cell proteomes not only provides a foundation for signaling and cell physiology at the GV stage of oocyte development, but are also valuable for comparative studies of other stages of oocyte development at the molecular level

Proteomic Interrogation of Human Chromatin

Chromatin proteins provide a scaffold for DNA packaging and a basis for epigenetic regulation and genomic maintenance. Despite understanding its functional roles, mapping the chromatin proteome (i.e. the “Chromatome”) is still a continuing process. Here, we assess the biological specificity and proteomic extent of three distinct chromatin preparations by identifying proteins in selected chromatin-enriched fractions using mass spectrometry-based proteomics. These experiments allowed us to produce a chromatin catalog, including several proteins ranging from highly abundant histone proteins to less abundant members of different chromatin machinery complexes. Using a Normalized Spectral Abundance Factor approach, we quantified relative abundances of the proteins across the chromatin enriched fractions giving a glimpse into their chromosomal abundance. The large-scale data sets also allowed for the discovery of a variety of novel post-translational modifications on the identified chromatin proteins. With these comparisons, we find one of the probed methods to be qualitatively superior in specificity for chromatin proteins, but inferior in proteomic extent, evidencing a compromise that must be made between biological specificity and broadness of characterization. Additionally, we attempt to identify proteins in eu- and heterochromatin, verifying the enrichments by characterizing the post-translational modifications detected on histone proteins from these chromatin regions. In summary, our results provide insights into the value of different methods to extract chromatin-associated proteins and provide starting points to study the factors that may be involved in directing gene expression and other chromatin-related processes