SearchGUI: An open-source graphical user interface for simultaneous OMSSA and X!Tandem searches

The identification of proteins by mass spectrometry is a standard technique in the field of proteomics, relying on search engines to perform the identifications of the acquired spectra. Here, we present a user-friendly, lightweight and open-source graphical user interface called SearchGUI (http://searchgui.googlecode.com), for configuring and running the freely available OMSSA (open mass spectrometry search algorithm) and X!Tandem search engines simultaneously. Freely available under the permissible Apache2 license, SearchGUI is supported on Windows, Linux and OSX.     

OMSSA Parser: An open‐source library to parse and extract data from OMSSA MS/MS search results

Protein identification by MS is an important technique in both gel‐based and gel‐free proteome studies. The Open Mass Spectrometry Search Algorithm (OMSSA) ( http://pubchem.ncbi.nlm.nih.gov/omssa ) is an open‐source search engine that can be used to identify MS/MS spectra acquired in these experiments. We here present a lightweight, open‐source Java software library, OMSSA Parser ( http://code.google.com/p/omssa‐parser ), which parses OMSSA omx result files into easy accessible and fully functional object models. In addition, we also provide examples illustrating the usage of our library.     

The OMSSAPercolator: An automated tool to validate OMSSA results

Protein identification by MS/MS is an important technique in proteome studies. The Open Mass Spectrometry Search Algorithm (OMSSA) is an open‐source search engine that can be used to identify MS/MS spectra acquired in these experiments. Here, we present a software tool, termed OMSSAPercolator, which interfaces OMSSA with Percolator, a post‐search machine learning method for rescoring database search results. We demonstrate that it outperforms the standard OMSSA scoring scheme, and provides reliable significant measurements. OMSSAPercolator is programmed using JAVA and can be readily used as a standalone tool or integrated into existing data analysis pipelines. OMSSAPercolator is freely available and can be downloaded at http://sourceforge.net/projects/omssapercolator/ .     

XTandem Parser: An open‐source library to parse and analyse X!Tandem MS/MS search results

Identification of proteins by MS plays an important role in proteomics. A crucial step concerns the identification of peptides from MS/MS spectra. The X!Tandem Project ( http://www.thegpm.org/tandem ) supplies an open‐source search engine for this purpose. In this study, we present an open‐source Java library called XTandem Parser that parses X!Tandem XML result files into an easily accessible and fully functional object model ( http://xtandem‐parser.googlecode.com ). In addition, a graphical user interface is provided that functions as a usage example and an end‐user visualization tool.     

Optimizing search conditions for the mass fingerprint-based identification of proteins

The two central problems in protein identification by searching a protein sequence collection with MS data are the optimal use of experimental information to allow for identification of low abundance proteins and the accurate assignment of the probability that a result is false. For comprehensive MS-based protein identification, it is necessary to choose an appropriate algorithm and optimal search conditions. We report a systematic study of the quality of PMF-based protein identifications under different sequence collection search conditions using the Probability algorithm, which assigns the statistical significance to each result. We employed 2244 PMFs from 2-DE-separated human blood plasma proteins, and performed identification under various search constraints: mass accuracy (0.01-0.3 Da), maximum number of missed cleavage sites (0-2), and size of the sequence collection searched (5.6 x 10(4)-1.8 x 10(5)). By counting the number of significant results (significance levels 0.05, 0.01, and 0.001) for each condition, we demonstrate the search condition impact on the successful outcome of proteome analysis experiments. A mass correction procedure utilizing mass deviations of albumin matching peptides was tested in an attempt to improve the statistical significance of identifications and iterative searching was employed for identification of multiple proteins from each PMF.     

IPeak: An open source tool to combine results from multiple MS/MS search engines

Liquid chromatography coupled tandem mass spectrometry (LC‐MS/MS) is an important technique for detecting peptides in proteomics studies. Here, we present an open source software tool, termed IPeak, a peptide identification pipeline that is designed to combine the Percolator post‐processing algorithm and multi‐search strategy to enhance the sensitivity of peptide identifications without compromising accuracy. IPeak provides a graphical user interface (GUI) as well as a command‐line interface, which is implemented in JAVA and can work on all three major operating system platforms: Windows, Linux/Unix and OS X. IPeak has been designed to work with the mzIdentML standard from the Proteomics Standards Initiative (PSI) as an input and output, and also been fully integrated into the associated mzidLibrary project, providing access to the overall pipeline, as well as modules for calling Percolator on individual search engine result files. The integration thus enables IPeak (and Percolator) to be used in conjunction with any software packages implementing the mzIdentML data standard. IPeak is freely available and can be downloaded under an Apache 2.0 license at https://code.google.com/p/mzidentml‐lib/ .     

Comet: An open‐source MS/MS sequence database search tool

Proteomics research routinely involves identifying peptides and proteins via MS/MS sequence database search. Thus the database search engine is an integral tool in many proteomics research groups. Here, we introduce the Comet search engine to the existing landscape of commercial and open‐source database search tools. Comet is open source, freely available, and based on one of the original sequence database search tools that has been widely used for many years.     

AutoAssemblyD: a graphical user interface system for several genome assemblers

Next-generation sequencing technologies have increased the amount of biological data generated. Thus, bioinformatics has become important because new methods and algorithms are necessary to manipulate and process such data. However, certain challenges have emerged, such as genome assembly using short reads and high-throughput platforms. In this context, several algorithms have been developed, such as Velvet, Abyss, Euler-SR, Mira, Edna, Maq, SHRiMP, Newbler, ALLPATHS, Bowtie and BWA. However, most such assemblers do not have a graphical interface, which makes their use difficult for users without computing experience given the complexity of the assembler syntax. Thus, to make the operation of such assemblers accessible to users without a computing background, we developed AutoAssemblyD, which is a graphical tool for genome assembly submission and remote management by multiple assemblers through XML templates.

Availability

AssemblyD is freely available at https://sourceforge.net/projects/autoassemblyd. It requires Sun jdk 6 or higher.     

MassSieve: Panning MS/MS peptide data for proteins

We present MassSieve, a Java‐based platform for visualization and parsimony analysis of single and comparative LC‐MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC‐MS/MS‐based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments.     

STEPS: A grid search methodology for optimized peptide identification filtering of MS/MS database search results

For bottom‐up proteomics, there are wide variety of database‐searching algorithms in use for matching peptide sequences to tandem MS spectra. Likewise, there are numerous strategies being employed to produce a confident list of peptide identifications from the different search algorithm outputs. Here we introduce a grid‐search approach for determining optimal database filtering criteria in shotgun proteomics data analyses that is easily adaptable to any search. Systematic Trial and Error Parameter Selection‐–referred to as STEPS‐–utilizes user‐defined parameter ranges to test a wide array of parameter combinations to arrive at an optimal “parameter set” for data filtering, thus maximizing confident identifications. The benefits of this approach in terms of numbers of true‐positive identifications are demonstrated using datasets derived from immunoaffinity‐depleted blood serum and a bacterial cell lysate, two common proteomics sample types.     

Analysis of the tryptic search space in UniProt databases

In this article, we provide a comprehensive study of the content of the Universal Protein Resource (UniProt) protein data sets for human and mouse. The tryptic search spaces of the UniProtKB (UniProt knowledgebase) complete proteome sets were compared with other data sets from UniProtKB and with the corresponding International Protein Index, reference sequence, Ensembl, and UniRef100 (where UniRef is UniProt reference clusters) organism‐specific data sets. All protein forms annotated in UniProtKB (both the canonical sequences and isoforms) were evaluated in this study. In addition, natural and disease‐associated amino acid variants annotated in UniProtKB were included in the evaluation. The peptide unicity was also evaluated for each data set. Furthermore, the peptide information in the UniProtKB data sets was also compared against the available peptide‐level identifications in the main MS‐based proteomics repositories. Identifying the peptides observed in these repositories is an important resource of information for protein databases as they provide supporting evidence for the existence of otherwise predicted proteins. Likewise, the repositories could use the information available in UniProtKB to direct reprocessing efforts on specific sets of peptides/proteins of interest. In summary, we provide comprehensive information about the different organism‐specific sequence data sets available from UniProt, together with the pros and cons for each, in terms of search space for MS‐based bottom‐up proteomics workflows. The aim of the analysis is to provide a clear view of the tryptic search space of UniProt and other protein databases to enable scientists to select those most appropriate for their purposes.     

非限制翻译后修饰鉴定方法的研究进展

蛋白质翻译后修饰在真核生物细胞内广泛存在,对蛋白质的结构和功能有着十分重要的影响.串联质谱技术的快速发展为翻译后修饰鉴定提供了高通量、高灵敏度和高分辨率的分析平台,但传统搜索引擎鉴定修饰的方法无法满足数据分析的需求,非限制翻译后修饰鉴定已成为目前蛋白质组修饰分析的重要手段之一.非限制翻译后修饰鉴定不需要在分析前指定修饰类型,可以直接从样品中找出大量已知或未知的修饰,对提高质谱图谱解析率以及揭示蛋白质的生物学功能具有十分重要的意义.本文首先介绍了非限制翻译后修饰鉴定的定义和发展历程,然后从序列匹配和谱图匹配两个方面详细综述了目前非限制翻译后修饰鉴定的主流算法,分析了非限制翻译后修饰鉴定的质量控制问题,最后结合非限制翻译后修饰鉴定的实际应用讨论了修饰鉴定算法的不足和发展方向.     

Morpheus Spectral Counter: A computational tool for label‐free quantitative mass spectrometry using the Morpheus search engine

Label‐free quantitative MS based on the Normalized Spectral Abundance Factor (NSAF) has emerged as a straightforward and robust method to determine the relative abundance of individual proteins within complex mixtures. Here, we present Morpheus Spectral Counter (MSpC) as the first computational tool that directly calculates NSAF values from output obtained from Morpheus, a fast, open‐source, peptide‐MS/MS matching engine compatible with high‐resolution accurate‐mass instruments. NSAF has distinct advantages over other MS‐based quantification methods, including a greater dynamic range as compared to isobaric tags, no requirement to align and re‐extract MS1 peaks, and increased speed. MSpC features an easy‐to‐use graphic user interface that additionally calculates both distributed and unique NSAF values to permit analyses of both protein families and isoforms/proteoforms. MSpC determinations of protein concentration were linear over several orders of magnitude based on the analysis of several high‐mass accuracy datasets either obtained from PRIDE or generated with total cell extracts spiked with purified Arabidopsis 20S proteasomes. The MSpC software was developed in C# and is open sourced under a permissive license with the code made available at http://dcgemperline.github.io/Morpheus_SpC/ .     

Estimating false discovery rates for peptide and protein identification using randomized databases

MS‐based proteomics characterizes protein contents of biological samples. The most common approach is to first match observed MS/MS peptide spectra against theoretical spectra from a protein sequence database and then to score these matches. The false discovery rate (FDR) can be estimated as a function of the score by searching together the protein sequence database and its randomized version and comparing the score distributions of the randomized versus nonrandomized matches. This work introduces a straightforward isotonic regression‐based method to estimate the cumulative FDRs and local FDRs (LFDRs) of peptide identification. Our isotonic method not only performed as well as other methods used for comparison, but also has the advantages of being: (i) monotonic in the score, (ii) computationally simple, and (iii) not dependent on assumptions about score distributions. We demonstrate the flexibility of our approach by using it to estimate FDRs and LFDRs for protein identification using summaries of the peptide spectra scores. We reconfirmed that several of these methods were superior to a two‐peptide rule. Finally, by estimating both the FDRs and LFDRs, we showed for both peptide and protein identification, moderate FDR values (5%) corresponded to large LFDR values (53 and 60%).     

jmzTab: A Java interface to the mzTab data standard

mzTab is the most recent standard format developed by the Proteomics Standards Initiative. mzTab is a flexible tab‐delimited file that can capture identification and quantification results coming from MS‐based proteomics and metabolomics approaches. We here present an open‐source Java application programming interface for mzTab called jmzTab. The software allows the efficient processing of mzTab files, providing read and write capabilities, and is designed to be embedded in other software packages. The second key feature of the jmzTab model is that it provides a flexible framework to maintain the logical integrity between the metadata and the table‐based sections in the mzTab files. In this article, as two example implementations, we also describe two stand‐alone tools that can be used to validate mzTab files and to convert PRIDE XML files to mzTab. The library is freely available at http://mztab.googlecode.com .     

PRIDEViewer: a novel user-friendly interface to visualize PRIDE XML files

Current standardization initiatives have greatly contributed to share the information derived by proteomics experiments. One of these initiatives is the XML-based repository PRIDE (PRoteomics IDEntification database), although an XML-based document does not appear to present a user-friendly view at the first glance. PRIDEViewer is a novel Java-based application that presents the information available in a PRIDE XML file in a user-friendly manner, facilitating the interaction among end users as well as the understanding and evaluation of the compiled information. PRIDEViewer is freely available at: http://proteo.cnb.csic.es/prideviewer/.     

OVNIp: An open source application facilitating the interpretation,the validation and the edition of proteomics data generated by MS analyses and de novo sequencing

Several academic software are available to help the validation and reporting of proteomics data generated by MS analyses. However, to our knowledge, none of them have been conceived to meet the particular needs generated by the study of organisms whose genomes are not sequenced. In that context, we have developed OVNIp, an open‐source application which facilitates the whole process of proteomics results interpretation. One of its unique attributes is its capacity to compile multiple results (from several search engines and/or several databank searches) with a resolution of conflicting interpretations. Moreover, OVNIp enables automated exploitation of de novo sequences generated from unassigned MS/MS spectra leading to higher sequence coverage and enhancing confidence in the identified proteins. The exploitation of these additional spectra might also identify novel proteins through a MS‐BLAST search, which can be easily ran from the OVNIp interface. Beyond this primary scope, OVNIp can also benefit to users who look for a simple standalone application to both visualize and confirm MS/MS result interpretations through a simple graphical interface and generate reports according to user‐defined forms which may integrate the prerequisites for publication. Sources, documentation and a stable release for Windows are available at http://wwwappli.nantes.inra.fr:8180/OVNIp .     

An investigation into the use of hypertext as a user interface to taxonomic keys

In an attempt to overcome some of the drawbacks of existingtaxonomic keys, we have experimented with a computerized versionof a key, changing the interface to the key, but leaving theinformation contained in the key essentially unchanged. Thisis in contrast to most previous work on the use of computersin taxonomy, where work has concentrated on alternative identificationtechniques and techniques for manipulating taxonomic data. Hopkin's(1991) Key to the Woodlice of Britain and Ireland was converted(including the diagrams and colour photographs), into a hypertextdocument using the Unix Guide hypertext system. An experimentwas conducted where test subjects with a wide range of experienceof taxonomic keys and computing skills were asked to identifywoodlouse specimens using the paper and hypertext forms of thekeys. The results showed that test subjects were more likelyto obtain an identification with the hypertext version of thekey. they found it easier to use and preferred using it to thepaper version of the key. However, there were indications thattest subjects were more likely to obtain a misidentificationusing the hypertext key than the paper version of the key. Furtherwork is needed to discover the possible causes of the increasedfrequency of misidentifications, and ways in which the usabilityof hypertext keys can be further enhanced     

Chloroplast envelope membranes: a dynamic interface between plastids and the cytosol

Chloroplasts are bounded by a pair of outer membranes, the envelope, that is the only permanent membrane structure of the different types of plastids. Chloroplasts have had a long and complex evolutionary past and integration of the envelope membranes in cellular functions is the result of this evolution. Plastid envelope membranes contain a wide diversity of lipids and terpenoid compounds serving numerous biochemical functions and the flexibility of their biosynthetic pathways allow plants to adapt to fluctuating environmental conditions (for instance phosphate deprivation). A large body of knowledge has been generated by proteomic studies targeted to envelope membranes, thus revealing an unexpected complexity of this membrane system. For instance, new transport systems for metabolites and ions have been identified in envelope membranes and new routes for the import of chloroplast-specific proteins have been identified. The picture emerging from our present understanding of plastid envelope membranes is that of a key player in plastid biogenesis and the co-ordinated gene expression of plastid-specific protein (owing to chlorophyll precursors), of a major hub for integration of metabolic and ionic networks in cell metabolism, of a flexible system that can divide, produce dynamic extensions and interact with other cell constituents. Envelope membranes are indeed one of the most complex and dynamic system within a plant cell. In this review, we present an overview of envelope constituents together with recent insights into the major functions fulfilled by envelope membranes and their dynamics within plant cells. Special Issue of Photosynthesis Research in honor of Andrew A. Benson.