The bacterial proteogenomic pipeline

Uszkoreit, Julian; Plohnke, Nicole; Rexroth, Sascha; Marcus, Katrin; Eisenacher, Martin

doi:10.1186/1471-2164-15-s9-s19

Cited by 19 publications

(11 citation statements)

References 19 publications

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“…Tools such as PGTools [ 180 ], Galaxy-P [ 39 ], ProteoAnnotator [ 186 ], IPAW [ 13 ], JUMPg [ 187 ], Graph2Pro/Var2Pep [ 188 ], NextSearch [ 189 ], and PGP [ 190 ] support execution on distributed memory environment using job scheduling frameworks such as PBS or Torque etc. Peppy [ 8 ], PGMiner [ 191 ], and PGA [ 192 ] only support multi-core processing while GenoSuite [ 193 ], Enosi [ 4 ], Bacterial Proteogenomic Pipeline [ 194 ], and MSProGene [ 195 ] only use single execution core. For the selection of our tools we consider the following components to be included in the pipeline:…”

Section: Proteogenomicsmentioning

confidence: 99%

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

et al. 2021

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Big Data Proteogenomics lies at the intersection of high-throughput Mass Spectrometry (MS) based proteomics and Next Generation Sequencing based genomics. The combined and integrated analysis of these two high-throughput technologies can help discover novel proteins using genomic, and transcriptomic data. Due to the biological significance of integrated analysis, the recent past has seen an influx of proteogenomic tools that perform various tasks, including mapping proteins to the genomic data, searching experimental MS spectra against a six-frame translation genome database, and automating the process of annotating genome sequences. To date, most of such tools have not focused on scalability issues that are inherent in proteogenomic data analysis where the size of the database is much larger than a typical protein database. These state-of-the-art tools can take more than half a month to process a small-scale dataset of one million spectra against a genome of 3 GB. In this article, we provide an up-to-date review of tools that can analyze proteogenomic datasets, providing a critical analysis of the techniques’ relative merits and potential pitfalls. We also point out potential bottlenecks and recommendations that can be incorporated in the future design of these workflows to ensure scalability with the increasing size of proteogenomic data. Lastly, we make a case of how high-performance computing (HPC) solutions may be the best bet to ensure the scalability of future big data proteogenomic data analysis.

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Section: Proteogenomicsmentioning

confidence: 99%

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

et al. 2021

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“… Delmotte et al (2009) have successfully used community proteogenomics to identify the unique traits of phyllosphere bacteria. Bacterial proteogenomic pipeline and other tools are available for proteogenomic analysis studies ( Uszkoreit et al, 2014 ). The technique offers insights into possible strategies adopted for endophytic lifestyle.…”

Section: Metaproteogenomicsmentioning

confidence: 99%

“Omics” Tools for Better Understanding the Plant–Endophyte Interactions

2016

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Endophytes, which mostly include bacteria, fungi and actinomycetes, are the endosymbionts that reside asymptomatically in plants for at least a part of their life cycle. They have emerged as a valuable source of novel metabolites, industrially important enzymes and as stress relievers of host plant, but still many aspects of endophytic biology are unknown. Functions of individual endophytes are the result of their continuous and complex interactions with the host plant as well as other members of the host microbiome. Understanding plant microbiomes as a system allows analysis and integration of these complex interactions. Modern genomic studies involving metaomics and comparative studies can prove to be helpful in unraveling the gray areas of endophytism. A deeper knowledge of the mechanism of host infestation and role of endophytes could be exploited to improve the agricultural management in terms of plant growth promotion, biocontrol and bioremediation. Genome sequencing, comparative genomics, microarray, next gen sequencing, metagenomics, metatranscriptomics are some of the techniques that are being used or can be used to unravel plant–endophyte relationship. The modern techniques and approaches need to be explored to study endophytes and their putative role in host plant ecology. This review highlights “omics” tools that can be explored for understanding the role of endophytes in the plant microbiome.

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“…All steps (decoy DB generation, DB search and PSM validation) are automatically executed ensuring a list of identifications at the desired FDR cut‐off. Other complete pipelines, applying a similar methodology, but focusing on the analysis of prokaryotic genomes, are available (GenoSuite(Kumar et al, ) and bacterial‐proteogenomic‐pipeline (Uszkoreit et al, )). ENOSI, another complete proteogenomics package initially used the same strategy in creating a genome‐derived search database to help genome (re) annotation.…”

Section: Tools Databases and Pipelines For Proteogenomics Studiesmentioning

confidence: 99%

Proteogenomics from a bioinformatics angle: A growing field

Menschaert

Fenyö

2015

Mass Spectrometry Reviews

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Proteogenomics is a research area that combines areas as proteomics and genomics in a multi‐omics setup using both mass spectrometry and high‐throughput sequencing technologies. Currently, the main goals of the field are to aid genome annotation or to unravel the proteome complexity. Mass spectrometry based identifications of matching or homologues peptides can further refine gene models. Also, the identification of novel proteoforms is also made possible based on detection of novel translation initiation sites (cognate or near‐cognate), novel transcript isoforms, sequence variation or novel (small) open reading frames in intergenic or un‐translated genic regions by analyzing high‐throughput sequencing data from RNAseq or ribosome profiling experiments. Other proteogenomics studies using a combination of proteomics and genomics techniques focus on antibody sequencing, the identification of immunogenic peptides or venom peptides. Over the years, a growing amount of bioinformatics tools and databases became available to help streamlining these cross‐omics studies. Some of these solutions only help in specific steps of the proteogenomics studies, e.g. building custom sequence databases (based on next generation sequencing output) for mass spectrometry fragmentation spectrum matching. Over the last few years a handful integrative tools also became available that can execute complete proteogenomics analyses. Some of these are presented as stand‐alone solutions, whereas others are implemented in a web‐based framework such as Galaxy. In this review we aimed at sketching a comprehensive overview of all the bioinformatics solutions that are available for this growing research area. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 36:584–599, 2017

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The bacterial proteogenomic pipeline

Cited by 19 publications

References 19 publications

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

“Omics” Tools for Better Understanding the Plant–Endophyte Interactions

Proteogenomics from a bioinformatics angle: A growing field

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