Proteogenomics of rare taxonomic phyla: A prospective treasure trove of protein coding genes

GP4: an integrated Gram-Positive Protein Prediction Pipeline for subcellular localization mimicking bacterial sorting

Subcellular localization is a critical aspect of protein function and the potential application of proteins either as drugs or drug targets, or in industrial and domestic applications. However, the experimental determination of protein localization is time consuming and expensive. Therefore, various localization predictors have been developed for particular groups of species. Intriguingly, despite their major representation amongst biotechnological cell factories and pathogens, a meta-predictor based on sorting signals and specific for Gram-positive bacteria was still lacking. Here we present GP⁴, a protein subcellular localization meta-predictor mainly for Firmicutes, but also Actinobacteria, based on the combination of multiple tools, each specific for different sorting signals and compartments. Novelty elements include improved cell-wall protein prediction, including differentiation of the type of interaction, prediction of non-canonical secretion pathway target proteins, separate prediction of lipoproteins and better user experience in terms of parsability and interpretability of the results. GP⁴ aims at mimicking protein sorting as it would happen in a bacterial cell. As GP⁴ is not homology based, it has a broad applicability and does not depend on annotated databases with homologous proteins. Non-canonical usage may include little studied or novel species, synthetic and engineered organisms, and even re-use of the prediction data to develop custom prediction algorithms. Our benchmark analysis highlights the improved performance of GP⁴ compared to other widely used subcellular protein localization predictors. A webserver running GP⁴ is available at http://gp4.hpc.rug.nl/

Advanced Proteomics as a Powerful Tool for Studying Toxins of Human Bacterial Pathogens

Exotoxins contribute to the infectious processes of many bacterial pathogens, mainly by causing host tissue damages. The production of exotoxins varies according to the bacterial species. Recent advances in proteomics revealed that pathogenic bacteria are capable of simultaneously producing more than a dozen exotoxins. Interestingly, these toxins may be subject to post-transcriptional modifications in response to environmental conditions. In this review, we give an outline of different bacterial exotoxins and their mechanism of action. We also report how proteomics contributed to immense progress in the study of toxinogenic potential of pathogenic bacteria over the last two decades.

Proteogenomic Refinement of the Neomegalonema perideroedesT Genome Annotation

Neomegalonema perideroedes (formerly Meganema perideroedes) str. G1 is the type strain and only described isolate of the genus Neomegalonema (formerly Meganema) which belongs to the Alphaproteobacteria. N. perideroedes is distinguished by the ability to accumulate high amounts of polyhydroxyalkanoates and has been associated with bulking problems in wastewater treatment plants due to its filamentous morphology. In 2013, its genome was sequenced as part of the Genomic Encyclopedia of Bacteria and Archaea (GEBA), which aims to improve the sequencing coverage of the poorly represented regions of the bacterial and archaeal branches of the tree of life. As N. perideroedes str. G1 is relatively distantly related to well described species-being the only sequenced member of its proposed family-the in silico prediction of genes by nucleotide homology to reference genes might be less reliable. Here, a proteomic dataset for the refinement of the N. perideroedes genome annotations is generated which clearly indicates the shortcomings of high-throughput in silico genome annotation.

Environmental proteomic studies: closer step to understand bacterial biofilms

Advancement in proteome analytical techniques and the development of protein databases have been helping to understand the physiology and subtle molecular mechanisms behind biofilm formation in bacteria. This review is to highlight how the evolving proteomic approaches have revealed fundamental molecular processes underlying the formation and regulation of bacterial biofilms. Based on the survey of research reports available on differential expression of proteins in biofilms of bacterial from wide range of environments, four important cellular processes viz. metabolism, motility, transport and stress response that contribute to formation of bacterial biofilms are discussed. This review might answer how proteins related to these cellular processes contribute significantly in stabilizing biofilms of different bacteria in diverse environmental conditions.

Reannotation of Genomes by Means of Proteomics Data

Omics approaches have become popular in biology as powerful discovery tools, and currently gain in interest for diagnostic applications. Establishing the accurate genome sequence of any organism is easy, but the outcome of its annotation by means of automatic pipelines remains imprecise. Some protein-encoding genes may be missed as soon as they are specific and poorly conserved in a given taxon, while important to explain the specific traits of the organism. Translational starts are also poorly predicted in a relatively important number of cases, thus impacting the protein sequence database used in proteomics, comparative genomics, and systems biology. The use of high-throughput proteomics data to improve genome annotation is an attractive option to obtain a more comprehensive molecular picture of a given organism. Here, protocols for reannotating prokaryote genomes are described based on shotgun proteomics and derivatization of protein N-termini with a positively charged reagent coupled to high-resolution tandem mass spectrometry.

GAPP: A Proteogenomic Software for Genome Annotation and Global Profiling of Post-translational Modifications in Prokaryotes

Although the number of sequenced prokaryotic genomes is growing rapidly, experimentally verified annotation of prokaryotic genome remains patchy and challenging. To facilitate genome annotation efforts for prokaryotes, we developed an open source software called GAPP for genome annotation and global profiling of post-translational modifications (PTMs) in prokaryotes. With a single command, it provides a standard workflow to validate and refine predicted genetic models and discover diverse PTM events. We demonstrated the utility of GAPP using proteomic data from Helicobacter pylori, one of the major human pathogens that is responsible for many gastric diseases. Our results confirmed 84.9% of the existing predicted H. pylori proteins, identified 20 novel protein coding genes, and corrected four existing gene models with regard to translation initiation sites. In particular, GAPP revealed a large repertoire of PTMs using the same proteomic data and provided a rich resource that can be used to examine the functions of reversible modifications in this human pathogen. This software is a powerful tool for genome annotation and global discovery of PTMs and is applicable to any sequenced prokaryotic organism; we expect that it will become an integral part of ongoing genome annotation efforts for prokaryotes. GAPP is freely available at https://sourceforge.net/projects/gappproteogenomic/.

Integrating transcriptome and proteome profiling: Strategies and applications

Discovering the gene expression signature associated with a cellular state is one of the basic quests in majority of biological studies. For most of the clinical and cellular manifestations, these molecular differences may be exhibited across multiple layers of gene regulation like genomic variations, gene expression, protein translation and post-translational modifications. These system wide variations are dynamic in nature and their crosstalk is overwhelmingly complex, thus analyzing them separately may not be very informative. This necessitates the integrative analysis of such multiple layers of information to understand the interplay of the individual components of the biological system. Recent developments in high throughput RNA sequencing and mass spectrometric (MS) technologies to probe transcripts and proteins made these as preferred methods for understanding global gene regulation. Subsequently, improvements in "big-data" analysis techniques enable novel conclusions to be drawn from integrative transcriptomic-proteomic analysis. The unified analyses of both these data types have been rewarding for several biological objectives like improving genome annotation, predicting RNA-protein quantities, deciphering gene regulations, discovering disease markers and drug targets. There are different ways in which transcriptomics and proteomics data can be integrated; each aiming for different research objectives. Here, we review various studies, approaches and computational tools targeted for integrative analysis of these two high-throughput omics methods.

Current developments to use linear MALDI-TOF spectra for the identification and typing of bacteria and the characterization of other cells/organisms related to infectious diseases

Within the past few years identification of bacteria by MALDI-TOF MS has become a standard technique in bacteriological laboratories for good reasons. MALDI-TOF MS identification is rapid, robust, automatable, and the per-sample costs are low. Yet, the spectra are very informative and the reliable identification of bacterial species is usually possible. Recently, new MS-based approaches for the identification of bacteria are emerging that are based on the detailed analysis of the bacterial proteome by high-resolution MS. These "proteotyping" approaches are highly discriminative and outperform MALDI-TOF MS-based identification in terms of specificity, but require a laborious proteomic workflow and far more expertise and sophisticated instrumentation than identification on basis of MALDI-TOF MS spectra, which can be obtained with relative simple and uncostly linear MALDI-TOF mass spectrometers. Thus MALDI-TOF MS identification of bacteria remains an attractive option for routine diagnostics. Additionally, MALDI-TOF MS identification protocols have been extended and improved in many respects making linear MALDI-TOF MS a versatile tool that can be useful beyond the identification of a bacterial species, e.g. for the characterization of leucocytes and arthropod vectors of infectious diseases. This review focuses on such improvements and extensions of the typical MALDI-TOF MS workflow in the field of infectious diseases.