Software Lock Mass by Two-Dimensional Minimization of Peptide Mass Errors

Mass accuracy is a key parameter in proteomic experiments, improving specificity, and success rates of peptide identification. Advances in instrumentation now make it possible to routinely obtain high resolution data in proteomic experiments. To compensate for drifts in instrument calibration, a compound of known mass is often employed. This ‘lock mass’ provides an internal mass standard in every spectrum. Here we take advantage of the complexity of typical peptide mixtures in proteomics to eliminate the requirement for a physical lock mass. We find that mass scale drift is primarily a function of the m/z and the elution time dimensions. Using a subset of high confidence peptide identifications from a first pass database search, which effectively substitute for the lock mass, we set up a global mathematical minimization problem. We perform a simultaneous fit in two dimensions using a function whose parameterization is automatically adjusted to the complexity of the analyzed peptide mixture. Mass deviation of the high confidence peptides from their calculated values is then minimized globally as a function of both m/z value and elution time. The resulting recalibration function performs equal or better than adding a lock mass from laboratory air to LTQ-Orbitrap spectra. This ‘software lock mass’ drastically improves mass accuracy compared with mass measurement without lock mass (up to 10-fold), with none of the experimental cost of a physical lock mass, and it integrated into the freely available MaxQuant analysis pipeline (www.maxquant.org)

The RNA phosphatase PIR-1 regulates endogenous small RNA pathways in C. elegans [preprint]

Eukaryotic cells regulate 5\u27 triphosphorylated (ppp-) RNAs to promote cellular functions and prevent recognition by antiviral RNA sensors. For example, RNA capping enzymes possess triphosphatase domains that remove the γ phosphates of ppp-RNAs during RNA capping. Members of the closely related PIR1 family of RNA polyphosphatases remove both the β and γ phosphates from ppp-RNAs. Here we show that C. elegans PIR-1 dephosphorylates ppp-RNAs made by cellular RdRPs and is required for the maturation of 26G-RNAs, Dicer-dependent small RNAs that regulate thousands of genes during spermatogenesis and embryogenesis. PIR-1 also regulates the CSR-1 22G-RNA pathway and has critical functions in both somatic and germline development. Our findings suggest that PIR-1 modulates both Dicer-dependent and -independent Argonaute pathways, and provide insight into how cells and viruses use a conserved RNA phosphatase to regulate and respond to ppp-RNA species

GO Explorer: A gene-ontology tool to aid in the interpretation of shotgun proteomics data

<p>Abstract</p> <p>Background</p> <p>Spectral counting is a shotgun proteomics approach comprising the identification and relative quantitation of thousands of proteins in complex mixtures. However, this strategy generates bewildering amounts of data whose biological interpretation is a challenge.</p> <p>Results</p> <p>Here we present a new algorithm, termed GO Explorer (GOEx), that leverages the gene ontology (GO) to aid in the interpretation of proteomic data. GOEx stands out because it combines data from protein fold changes with GO over-representation statistics to help draw conclusions. Moreover, it is tightly integrated within the PatternLab for Proteomics project and, thus, lies within a complete computational environment that provides parsers and pattern recognition tools designed for spectral counting. GOEx offers three independent methods to query data: an interactive directed acyclic graph, a specialist mode where key words can be searched, and an automatic search. Its usefulness is demonstrated by applying it to help interpret the effects of perillyl alcohol, a natural chemotherapeutic agent, on glioblastoma multiform cell lines (A172). We used a new multi-surfactant shotgun proteomic strategy and identified more than 2600 proteins; GOEx pinpointed key sets of differentially expressed proteins related to cell cycle, alcohol catabolism, the Ras pathway, apoptosis, and stress response, to name a few.</p> <p>Conclusion</p> <p>GOEx facilitates organism-specific studies by leveraging GO and providing a rich graphical user interface. It is a simple to use tool, specialized for biologists who wish to analyze spectral counting data from shotgun proteomics. GOEx is available at <url>http://pcarvalho.com/patternlab</url>.</p

Proteomic Analysis of Cattle Tick Rhipicephalus (Boophilus) microplus Saliva: A Comparison between Partially and Fully Engorged Females

The cattle tick Rhipicephalus (Boophilus) microplus is one of the most harmful parasites affecting bovines. Similarly to other hematophagous ectoparasites, R. microplus saliva contains a collection of bioactive compounds that inhibit host defenses against tick feeding activity. Thus, the study of tick salivary components offers opportunities for the development of immunological based tick control methods and medicinal applications. So far, only a few proteins have been identified in cattle tick saliva. The aim of this work was to identify proteins present in R. microplus female tick saliva at different feeding stages. Proteomic analysis of R. microplus saliva allowed identifying peptides corresponding to 187 and 68 tick and bovine proteins, respectively. Our data confirm that (i) R. microplus saliva is complex, and (ii) that there are remarkable differences in saliva composition between partially engorged and fully engorged female ticks. R. microplus saliva is rich mainly in (i) hemelipoproteins and other transporter proteins, (ii) secreted cross-tick species conserved proteins, (iii) lipocalins, (iv) peptidase inhibitors, (v) antimicrobial peptides, (vii) glycine-rich proteins, (viii) housekeeping proteins and (ix) host proteins. This investigation represents the first proteomic study about R. microplus saliva, and reports the most comprehensive Ixodidae tick saliva proteome published to date. Our results improve the understanding of tick salivary modulators of host defense to tick feeding, and provide novel information on the tick-host relationship

Distinct Argonaute-mediated 22G-RNA pathways direct genome surveillance in the C. elegans germline

Endogenous small RNAs (endo-siRNAs) interact with Argonaute (AGO) proteins to mediate sequence-specific regulation of diverse biological processes. Here, we combine deep-sequencing and genetic approaches to explore the biogenesis and function of endo-siRNAs in C. elegans. We describe conditional alleles of the dicer-related helicase, drh-3, that abrogate both RNA interference and the biogenesis of endo-siRNAs, called 22G-RNAs. DRH-3 is a core component of RNA-dependent RNA polymerase (RdRP) complexes essential for several distinct 22G-RNA systems. We show that in the germ-line, one system is dependent on worm-specific AGOs, including WAGO-1, which localizes to germ-line nuage structures called P-granules. WAGO-1 silences certain genes, transposons, pseudogenes and cryptic loci. Finally, we demonstrate that components of the nonsense-mediated decay pathway function in at least one WAGO-mediated surveillance pathway. These findings broaden our understanding of the biogenesis and diversity of 22G-RNAs and suggest novel regulatory functions for small RNAs

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

Overexpression of LASP-1 mediates migration and proliferation of human ovarian cancer cells and influences zyxin localisation

LIM and SH3 protein 1 (LASP-1), initially identified from human breast cancer, is a specific focal adhesion protein involved in cell proliferation and migration. In the present work, we analysed the effect of LASP-1 on biology and function of human ovarian cancer cell line SKOV-3 using small interfering RNA technique (siRNA).Transfection with LASP-1-specific siRNA resulted in a reduced protein level of LASP-1 in SKOV-3 cells. The siRNA-treated cells were arrested in G2/M phase of the cell cycle and proliferation of the tumour cells was suppressed by 60–90% corresponding to around 70% of the cells being transfected successfully as seen by immunofluorescence. Moreover, transfected tumour cells showed a 40% reduced migration. LASP-1 silencing is accompanied by a reduced binding of the LASP-1-binding partner zyxin to focal contacts without changes in actin stress fibre and microtubule organisation or focal adhesion morphology as observed by immunofluorescence. In contrast, silencing of zyxin is not influencing cell migration and had neither influence on LASP-1 expression nor actin cytoskeleton and focal contact morphology suggesting that LASP-1 is necessary and sufficient for recruiting zyxin to focal contacts.The data provide evidence for an essential role of LASP-1 in tumour cell growth and migration, possibly through influencing zyxin localization

Computational Methods for Protein Identification from Mass Spectrometry Data

Protein identification using mass spectrometry is an indispensable computational tool in the life sciences. A dramatic increase in the use of proteomic strategies to understand the biology of living systems generates an ongoing need for more effective, efficient, and accurate computational methods for protein identification. A wide range of computational methods, each with various implementations, are available to complement different proteomic approaches. A solid knowledge of the range of algorithms available and, more critically, the accuracy and effectiveness of these techniques is essential to ensure as many of the proteins as possible, within any particular experiment, are correctly identified. Here, we undertake a systematic review of the currently available methods and algorithms for interpreting, managing, and analyzing biological data associated with protein identification. We summarize the advances in computational solutions as they have responded to corresponding advances in mass spectrometry hardware. The evolution of scoring algorithms and metrics for automated protein identification are also discussed with a focus on the relative performance of different techniques. We also consider the relative advantages and limitations of different techniques in particular biological contexts. Finally, we present our perspective on future developments in the area of computational protein identification by considering the most recent literature on new and promising approaches to the problem as well as identifying areas yet to be explored and the potential application of methods from other areas of computational biology