Proteogenomics for environmental microbiology

Modified N-acyl-L-homoserine lactone compounds abrogate Las-dependent quorum-sensing response in human pathogen Pseudomonas aeruginosa

Quorum sensing (QS) is a mode of cell-cell communication that bacteria use to sense population density and orchestrate collective behaviors. The common opportunistic human pathogen Pseudomonas aeruginosa employs QS to regulate a large set of genes involved in virulence and host-pathogen interactions. The Las circuit positioned on the top of the QS hierarchy in P. aeruginosa makes use of N-acyl-L-homoserine lactones (AHLs) as signal molecules, like N-3-oxo-dodecanoyl-L-homoserine lactone (3O-C12-HSL). Disabling QS circuits by certain small-molecule compounds, known as quorum-sensing inhibitors (QSIs), has been proposed as a strategy to attenuate bacterial pathogenicity. In this study, four new AHL analogs were designed by incorporating a tert-butoxycarbonyl Boc group in amide and β-keto (3-oxo) moiety. Compounds were evaluated on a molecular and phenotypic basis as a QSI using the screening strategy linked to the assignment of the Las QS system in P. aeruginosa. Using a LasR-based bioreporter, we found that the compounds decreased LasR-controlled light activity and competed efficiently with natural 3O-C12-HSL. The compounds reduced the production of the cognate 3O-C12-HSL and certain virulence traits, like total protease activity, elastase activity, pyocyanin production, and extracellular DNA release. Furthermore, a quantitative proteomic approach was used to study the effect of the compounds on QS-regulated extracellular proteins. Among the four compounds tested, one of them showed the most significant difference in the appearance of the 3O-C12-HSL-responsive reference proteins related to QS communication and virulence, i.e., a distinct activity as a QSI. Moreover, by combining experimental data with computational chemistry, we addressed the effect of LasR protein flexibility on docking precision and assessed the advantage of using a multi-conformational docking procedure for binding mode prediction of LasR modulators. Thus, the four new AHL compounds were tested for their interaction with the AHL-binding site in LasR to identify the key interferences with the activity of LasR. Our study provides further insight into molecular features that are required for small-molecule modulation of LasR-dependent QS communication in P. aeruginosa. This should facilitate rational design of the next generation of antivirulence tools to study and manipulate QS-controlled fitness in bacteria and, thereby, handle bacterial infections in a new way.

The need for an integrated multi-OMICs approach in microbiome science in the food system

Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing demand for microbiome-based technologies that provide added-value solutions. Microbiome research has expanded in the context of food systems, strongly driven by methodological advances in different -omics fields that leverage our understanding of microbial diversity and function. However, managing and integrating different complex -omics layers are still challenging. Within the Coordinated Support Action MicrobiomeSupport (https://www.microbiomesupport.eu/), a project supported by the European Commission, the workshop "Metagenomics, Metaproteomics and Metabolomics: the need for data integration in microbiome research" gathered 70 participants from different microbiome research fields relevant to food systems, to discuss challenges in microbiome research and to promote a switch from microbiome-based descriptive studies to functional studies, elucidating the biology and interactive roles of microbiomes in food systems. A combination of technologies is proposed. This will reduce the biases resulting from each individual technology and result in a more comprehensive view of the biological system as a whole. Although combinations of different datasets are still rare, advanced bioinformatics tools and artificial intelligence approaches can contribute to understanding, prediction, and management of the microbiome, thereby providing the basis for the improvement of food quality and safety.

Deep N-terminomics of Mycobacterium tuberculosis H37Rv extensively correct annotated encoding genes

Mycobacterium tuberculosis (MTB) is a severe causing agent of tuberculosis (TB). Although H37Rv, the type strain of M. tuberculosis was sequenced in 1998, annotation errors of encoding genes have been frequently reported in hundreds of papers. This phenomenon is particularly severe at the 5' end of the genes. Here, we applied a TMPP [(N-Succinimidyloxycarbonylmethyl) tris (2,4,6-trimethoxyphenyl) phosphonium bromide] labeling combined with StageTip separating strategy on M. tuberculosis H37Rv to characterize the N-terminal start sites of its annotated encoding genes. Totally, 1047 proteins were identified with 2058 TMPP labeled N-terminal peptides from all the 2625 mass spectrometer (MS) sequenced proteins. Comparative genomics analysis allowed the re-annotation of 43 proteins' N-termini in H37Rv and 762 proteins in Mycobacteriaceae. All revised N-termini start sites were distributed in 5'-UTR of annotated genes due to over-annotation of previous N-terminal initiation codon, especially the ATG. In addition, we identified and verified a novel gene Rv1078A in +3 frame different from the annotated gene Rv1078 in +2 frame. Altogether, our findings contribute to the better understanding of N-terminal of H37Rv and other species from Mycobacteriaceae that can assist future studies on biological study.

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

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.

Growth phase proteomics of the heterotrophic marine bacterium Ruegeria pomeroyi

The heterotrophic marine bacterium, Ruegeria pomeroyi, was experimentally cultured under environmentally realistic carbon conditions and with a tracer-level addition of 13C-labeled leucine to track bacterial protein biosynthesis through growth phases. A combination of methods allowed observation of real-time bacterial protein production to understand metabolic priorities through the different growth phases. Over 2000 proteins were identified in each experimental culture from exponential and stationary growth phases. Within two hours of the 13C-labeled leucine addition, R. pomeroyi significantly assimilated the newly encountered substrate into new proteins. This dataset provides a fundamental baseline for understanding growth phase differences in molecular physiology of a cosmopolitan marine bacterium.

Peptimapper: proteogenomics workflow for the expert annotation of eukaryotic genomes

Background

Accurate structural annotation of genomes is still a challenge, despite the progress made over the past decade. The prediction of gene structure remains difficult, especially for eukaryotic species, and is often erroneous and incomplete. We used a proteogenomics strategy, taking advantage of the combination of proteomics datasets and bioinformatics tools, to identify novel protein coding-genes and splice isoforms, assign correct start sites, and validate predicted exons and genes.

Results

Our proteogenomics workflow, Peptimapper, was applied to the genome annotation of Ectocarpus sp., a key reference genome for both the brown algal lineage and stramenopiles. We generated proteomics data from various life cycle stages of Ectocarpus sp. strains and sub-cellular fractions using a shotgun approach. First, we directly generated peptide sequence tags (PSTs) from the proteomics data. Second, we mapped PSTs onto the translated genomic sequence. Closely located hits (i.e., PSTs locations on the genome) were then clustered to detect potential coding regions based on parameters optimized for the organism. Third, we evaluated each cluster and compared it to gene predictions from existing conventional genome annotation approaches. Finally, we integrated cluster locations into GFF files to use a genome viewer. We identified two potential novel genes, a ribosomal protein L22 and an aryl sulfotransferase and corrected the gene structure of a dihydrolipoamide acetyltransferase. We experimentally validated the results by RT-PCR and using transcriptomics data.

Conclusions

Peptimapper is a complementary tool for the expert annotation of genomes. It is suitable for any organism and is distributed through a Docker image available on two public bioinformatics docker repositories: Docker Hub and BioShaDock. This workflow is also accessible through the Galaxy framework and for use by non-computer scientists at https://galaxy.protim.eu.

Data are available via ProteomeXchange under identifier PXD010618.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5431-9) contains supplementary material, which is available to authorized users.

Proteomics data for characterizing Microbacterium oleivorans A9, an uranium-tolerant actinobacterium isolated near the Chernobyl nuclear power plant

Microbacterium oleivorans A9 cells were exposed or not to 10 µM uranyl nitrate as resting cells in sodium chloride solution. Bacteria exposed to U(VI) and controls were harvested after 0.5, 4, and 24 h of toxicant exposure. Bacteria were subjected to high-throughput proteomics analysis using a Q-Exactive HF high resolution tandem mass spectrometer incorporating an ultra-high-field orbitrap analyzer. MS/MS spectra were assigned with a protein sequence database derived from a draft genome obtained by Illumina sequencing and systematic six-reading frame translation of all the contigs. Proteins identified in bacteria exposed to U(VI) and controls at the three time points allow defining the proteome dynamics upon uranium stress. The data reported here are related to a published study regarding the proteome dynamics of M. oleivorans A9 upon uranium stress by Gallois et al. (in press) entitled “Proteogenomic insights into uranium tolerance of a Chernobyl׳s Microbacterium bacterial isolate”. The data accompanying the manuscript describing the database searches and comparative analysis have been deposited to the ProteomeXchange with identifier PXD005794.

Characterization of microbial mixtures by mass spectrometry

MS applications in microbiology have increased significantly in the past 10 years, due in part to the proliferation of regulator-approved commercial MALDI MS platforms for rapid identification of clinical infections. In parallel, with the expansion of MS technologies in the "omics" fields, novel MS-based research efforts to characterize organismal as well as environmental microbiomes have emerged. Successful characterization of microorganisms found in complex mixtures of other organisms remains a major challenge for researchers and clinicians alike. Here, we review recent MS advances toward addressing that challenge. These include sample preparation methods and protocols, and established, for example, MALDI, as well as newer, for example, atmospheric pressure ionization (API) techniques. MALDI mass spectra of intact cells contain predominantly information on the highly expressed house-keeping proteins used as biomarkers. The API methods are applicable for small biomolecule analysis, for example, phospholipids and lipopeptides, and facilitate species differentiation. MS hardware and techniques, for example, tandem MS, including diverse ion source/mass analyzer combinations are discussed. Relevant examples for microbial mixture characterization utilizing these combinations are provided. Chemometrics and bioinformatics methods and algorithms, including those applied to large scale MS data acquisition in microbial metaproteomics and MS imaging of biofilms, are highlighted. Select MS applications for polymicrobial culture analysis in environmental and clinical microbiology are reviewed as well.

Proteogenomics from a bioinformatics angle: A growing field

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.

Proteogenomics data for deciphering Frankia coriariae interactions with root exudates from three host plants

Frankia coriariae BMG5.1 cells were incubated with root exudates derived from compatible (Coriaria myrtifolia), incompatible (Alnus glutinosa) and non-actinorhizal (Cucumis melo) host plants. Bacteria cells and their exoproteomes were analyzed by high-throughput proteomics using a Q-Exactive HF high resolution tandem mass spectrometer incorporating an ultra-high-field orbitrap analyzer. MS/MS spectra were assigned with two protein sequence databases derived from the closely-related genomes from strains BMG5.1 andDg1, the Frankia symbiont of Datisca glomerata. The tandem mass spectrometry data accompanying the manuscript describing the database searches and comparative analysis (Ktari et al., 2017, doi.org/10.3389/fmicb.2017.00720) [1] have been deposited to the ProteomeXchange with identifiers PXD005979 (whole cell proteomes) and PXD005980 (exoproteome data).

Exoproteomics of Pathogens: Analysis of Toxins and Other Virulence Factors by Proteomics

Pathogens are known to release in their environment a large range of toxins and other virulence factors. Their pathogenicity relies on this arsenal of exoproteins and their orchestrated release upon changing environmental conditions. Exoproteomics aims at describing and quantifying the proteins found outside of the cells, thus takes advantage of the most recent methodologies of next-generation proteomics. This approach has been applied with great success to a variety of pathogens increasing the fundamental knowledge on pathogenicity. In this chapter, we describe how the exoproteome should be prepared and handled for high-throughput identification of exoproteins and their quantitation by label-free shotgun proteomics. We also mentioned some bioinformatics tools for extracting information such as toxin similarity search.

Defining Diagnostic Biomarkers Using Shotgun Proteomics and MALDI-TOF Mass Spectrometry

Whole-cell MALDI-TOF has become a robust and widely used tool to quickly identify any pathogen. In addition to being routinely used in hospitals, it is also useful for low cost dereplication in large scale screening procedures of new environmental isolates for environmental biotechnology or taxonomical applications. Here, I describe how specific biomarkers can be defined using shotgun proteomics and whole-cell MALDI-TOF mass spectrometry. Based on MALDI-TOF spectra recorded on a given set of pathogens with internal calibrants, m/z values of interest are extracted. The proteins which contribute to these peaks are deduced from label-free shotgun proteomics measurements carried out on the same sample. Quantitative information based on the spectral count approach allows ranking the most probable candidates. Proteogenomic approaches help to define whether these proteins give the same m/z values along the whole taxon under consideration or result in heterogeneous lists. These specific biomarkers nicely complement conventional profiling approaches and may help to better define groups of organisms, for example at the subspecies level.

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/.

Ovary and embryo proteogenomic dataset revealing diversity of vitellogenins in the crustacean Gammarus fossarum

Ovaries and embryos from sexually mature Gammarus fossarum were sampled at different stages of the reproductive cycle. The soluble proteome was extracted for five biological replicates and samples were subjected to trypsin digestion. The resulting peptides were analyzed by high resolution tandem mass spectrometry with a LTQ-Orbitrap XL instrument. The MS/MS spectra were assigned with a previously described RNAseq-derived G. fossarum database. The proteins highlighted by proteogenomics were monitored and their abundance kinetics over the different stages revealed a large panel of vitellogenins. Criteria were i) accumulation during oogenesis, ii) decrease during embryogenesis, iii) classified as female-specific, and iv) sequence similarity and phylogenetic analysis. The data accompanying the manuscript describing the database searches and comparative analysis (“High-throughput proteome dynamics for discovery of key proteins in sentinel species: unsuspected vitellogenins diversity in the crustacean Gammarus fossarum” by Trapp et al. [1]) have been deposited to the ProteomeXchange via the PRIDE repository with identifiers PRIDE: PXD001002.

Power of positive thinking in quantitative proteomics

Derivatization of proteins with specific isotope reagents has been widely explored for quantitative proteomics where the relative abundances of proteins present in different complex samples are compared by MS. This represents an interesting arena for innovation, where protein chemistry and MS are associated for the best of both worlds. Among the numerous reagents developed, those that introduce a permanent positive charge, such as (N-succinimidyloxycarbonylmethyl)-tris(2,4,6-trimethoxyphenyl)phosphonium bromide (TMPP), increase the ionizability of their targets and thus improve the sensitivity of the approach. TMPP labeling also modifies the hydrophobicity and changes the peptide fragmentation pattern. Because TMPP reacts preferably with the N-termini of proteins and peptides, its use has been explored for proteogenomics and de novo protein sequencing. In this issue of Proteomics, Shen et al. (Proteomics 2015, 15, 2903-2909) show that accurate quantitation of proteins can be obtained with light/heavy TMPP-labeling of peptides, which can be easily prepared and desalted in a homemade C8-SCX-C8 stagetip, and then monitored by nano-LC-MS/MS analysis. Their results demonstrate enhanced sequence coverage compared with other approaches. Combined with an efficient enrichment procedure, the higher sensitivity of this "positive attitude" reagent may facilitate much deeper investigations into the quantitative proteomics of complex samples.

Tissue-specific Proteogenomic Analysis of Plutella xylostella Larval Midgut Using a Multialgorithm Pipeline

The diamondback moth, Plutella xylostella (L.), is the major cosmopolitan pest of brassica and other cruciferous crops. Its larval midgut is a dynamic tissue that interfaces with a wide variety of toxicological and physiological processes. The draft sequence of the P. xylostella genome was recently released, but its annotation remains challenging because of the low sequence coverage of this branch of life and the poor description of exon/intron splicing rules for these insects. Peptide sequencing by computational assignment of tandem mass spectra to genome sequence information provides an experimental independent approach for confirming or refuting protein predictions, a concept that has been termed proteogenomics. In this study, we carried out an in-depth proteogenomic analysis to complement genome annotation of P. xylostella larval midgut based on shotgun HPLC-ESI-MS/MS data by means of a multialgorithm pipeline. A total of 876,341 tandem mass spectra were searched against the predicted P. xylostella protein sequences and a whole-genome six-frame translation database. Based on a data set comprising 2694 novel genome search specific peptides, we discovered 439 novel protein-coding genes and corrected 128 existing gene models. To get the most accurate data to seed further insect genome annotation, more than half of the novel protein-coding genes, i.e. 235 over 439, were further validated after RT-PCR amplification and sequencing of the corresponding transcripts. Furthermore, we validated 53 novel alternative splicings. Finally, a total of 6764 proteins were identified, resulting in one of the most comprehensive proteogenomic study of a nonmodel animal. As the first tissue-specific proteogenomics analysis of P. xylostella, this study provides the fundamental basis for high-throughput proteomics and functional genomics approaches aimed at deciphering the molecular mechanisms of resistance and controlling this pest.

Data for comparative proteomics of ovaries from five non-model, crustacean amphipods

Ovaries were taken from five sexually mature amphipods: Gammarus fossarum, Gammarus pulex, Gammarus roeseli, Hyallela azteca and Parhyale hawaiensis. The soluble proteome extracted from individual pair of ovaries from five biological replicates was trypsin digested and the resulting peptides were analyzed by high resolution tandem mass spectrometry. The spectra were assigned with four protein sequence databases with different specificities: a RNAseq-derived G. fossarum database; a RNAseq-derived P. hawaiensis database; both originating from ovaries transcriptome; the Daphnia pulex database derived from whole-genome sequencing and the NCBInr database. The best interpretation was obtained for most animals with the specific RNA-seq protein database previously established by means of RNAseq carried out on G. fossarum. Proteins identified in the five amphipod species allow defining the core-proteome of female reproductive tissues of the Senticaudata suborder. The data accompanying the manuscript describing the database searches and comparative analysis Trapp et al., 2015 [1] have been deposited to the ProteomeXchange with identifiers PXD002253 (G. fossarum), PXD002254 (G. pulex), PXD002255 (G. roeseli), PXD002256 (H. Azteca), and PXD002257 (P. hawaiensis).

A decade of metaproteomics: where we stand and what the future holds

We are living through exciting times during which we are able to unravel the “microbial dark matter” in and around us through the application of high‐resolution “meta‐omics”. Metaproteomics offers the ability to resolve the major catalytic units of microbial populations and thereby allows the establishment of genotype‐phenotype linkages from in situ samples. A decade has passed since the term “metaproteomics” was first coined and corresponding analyses were carried out on mixed microbial communities. Since then metaproteomics has yielded many important insights into microbial ecosystem function in the various environmental settings where it has been applied. Although initial progress in analytical capacities and resulting numbers of proteins identified was extremely fast, this trend slowed rapidly. Here, we discuss several representative metaproteomic investigations of activated sludge, acid mine drainage biofilms, freshwater and seawater microbial communities, soil, and human gut microbiota. By using these case studies, we highlight current challenges and possible solutions for metaproteomics to realize its full potential, i.e. to enable conclusive links between microbial community composition, physiology, function, interactions, ecology, and evolution in situ.

Proteogenomic insights into the core-proteome of female reproductive tissues from crustacean amphipods

As a result of the poor genome sequence coverage of crustacean amphipods, characterization of their evolutionary biology relies mostly on phenotypic traits. Here, we analyzed the proteome of ovaries from five amphipods, all from the Senticaudata suborder, with the objective to obtain insights into the core-proteome of female reproductive systems. These amphipods were from either the Gammarida infraorder: Gammarus fossarum, Gammarus pulex, Gammarus roeseli, or the Talitrida infraorder: Parhyale hawaiensis and Hyalella azteca. Ovaries from animals sampled at the end of their reproductive cycle were dissected. Their whole protein contents were extracted and their proteomes were recorded by high-throughput nanoLC-MS/MS with a high-resolution mass spectrometer. We interpreted tandem mass spectrometry data with the protein sequence resource from G. fossarum and P. hawaiensis, both recently established by RNA sequencing. The large molecular biodiversity within amphipods was assessed by the ratio of MS/MS spectra assigned for each sample, which tends to diverge rapidly along the taxonomic level considered. The core-proteome was defined as the proteins conserved along all samples, thus detectable by the homology-based proteomic assignment procedure. This specific subproteome may be further enriched in the future with the analysis of new species and update of the protein sequence resource.

Proteogenomics: emergence and promise

Proteogenomics, or the integration of proteomics with genomics and transcriptomics, is emerging as the next step towards a unified understanding of cellular functions. Looking globally and simultaneously at gene structure, RNA expression, protein synthesis and post-translational modifications have become technically feasible and offer a new perspective to molecular processes. Recent publications have highlighted the value of proteogenomics in oncology for defining the molecular signature of human tumors, and translation to other areas of biomedicine and life sciences is anticipated. This mini-review will discuss recent developments, challenges and perspectives in proteogenomics.

Prioritizing targets for structural biology through the lens of proteomics: the archaeal protein TGAM_1934 from Thermococcus gammatolerans

ORFans are hypothetical proteins lacking any significant sequence similarity with other proteins. Here, we highlighted by quantitative proteomics the TGAM_1934 ORFan from the hyperradioresistant Thermococcus gammatolerans archaeon as one of the most abundant hypothetical proteins. This protein has been selected as a priority target for structure determination on the basis of its abundance in three cellular conditions. Its solution structure has been determined using multidimensional heteronuclear NMR spectroscopy. TGAM_1934 displays an original fold, although sharing some similarities with the 3D structure of the bacterial ortholog of frataxin, CyaY, a protein conserved in bacteria and eukaryotes and involved in iron-sulfur cluster biogenesis. These results highlight the potential of structural proteomics in prioritizing ORFan targets for structure determination based on quantitative proteomics data. The proteomic data and structure coordinates have been deposited to the ProteomeXchange with identifier PXD000402 (http://proteomecentral.proteomexchange.org/dataset/PXD000402) and Protein Data Bank under the accession number 2mcf, respectively.

Systems-based approaches to unravel multi-species microbial community functioning

Some of the most transformative discoveries promising to enable the resolution of this century's grand societal challenges will most likely arise from environmental science and particularly environmental microbiology and biotechnology. Understanding how microbes interact in situ, and how microbial communities respond to environmental changes remains an enormous challenge for science. Systems biology offers a powerful experimental strategy to tackle the exciting task of deciphering microbial interactions. In this framework, entire microbial communities are considered as metaorganisms and each level of biological information (DNA, RNA, proteins and metabolites) is investigated along with in situ environmental characteristics. In this way, systems biology can help unravel the interactions between the different parts of an ecosystem ultimately responsible for its emergent properties. Indeed each level of biological information provides a different level of characterisation of the microbial communities. Metagenomics, metatranscriptomics, metaproteomics, metabolomics and SIP-omics can be employed to investigate collectively microbial community structure, potential, function, activity and interactions. Omics approaches are enabled by high-throughput 21st century technologies and this review will discuss how their implementation has revolutionised our understanding of microbial communities.

Proteogenomics in microbiology: taking the right turn at the junction of genomics and proteomics

High-accuracy and high-throughput proteomic methods have completely changed the way we can identify and characterize proteins. MS-based proteomics can now provide a unique supplement to genomic data and add a new level of information to the interpretation of genomic sequences. Proteomics-driven genome annotation has become especially relevant in microbiology where genomes are sequenced on a daily basis and limitations of an in silico driven annotation process are well recognized. In this review paper, we outline different strategies on how one can design a proteogenomic experiment, for example on genome-sequenced (synonymous proteogenomics) versus unsequenced organisms (ortho-proteogenomics) or with the aid of other "omic" data such as RNA-seq. We touch upon many challenges that are encountered during a typical proteogenomic study, mostly concerning bioinformatics methods and downstream data analysis, but also related to creation and use of sequence databases. A large list of proteogenomic case studies of different microorganisms is provided to illustrate the mapping of MS/MS-derived peptide spectra to genomic DNA sequences. These investigations have led to accurate determination of translational initiation sites, pointed out eventual read-throughs or programmed frameshifts, detected signal peptide processing or other protein maturation events, removed questionable annotation assignments, and provided evidence for predicted hypothetical proteins.

Flexible and accessible workflows for improved proteogenomic analysis using the Galaxy framework

Proteogenomics combines large-scale genomic and transcriptomic data with mass-spectrometry-based proteomic data to discover novel protein sequence variants and improve genome annotation. In contrast with conventional proteomic applications, proteogenomic analysis requires a number of additional data processing steps. Ideally, these required steps would be integrated and automated via a single software platform offering accessibility for wet-bench researchers as well as flexibility for user-specific customization and integration of new software tools as they emerge. Toward this end, we have extended the Galaxy bioinformatics framework to facilitate proteogenomic analysis. Using analysis of whole human saliva as an example, we demonstrate Galaxy’s flexibility through the creation of a modular workflow incorporating both established and customized software tools that improve depth and quality of proteogenomic results. Our customized Galaxy-based software includes automated, batch-mode BLASTP searching and a Peptide Sequence Match Evaluator tool, both useful for evaluating the veracity of putative novel peptide identifications. Our complex workflow (approximately 140 steps) can be easily shared using built-in Galaxy functions, enabling their use and customization by others. Our results provide a blueprint for the establishment of the Galaxy framework as an ideal solution for the emerging field of proteogenomics.

Proteogenomics of Gammarus fossarum to document the reproductive system of amphipods

Because of their ecological importance, amphipod crustacea are employed worldwide as test species in environmental risk assessment. Although proteomics allows new insights into the molecular mechanisms related to the stress response, such investigations are rare for these organisms because of the lack of comprehensive protein sequence databases. Here, we propose a proteogenomic approach for identifying specific proteins of the freshwater amphipod Gammarus fossarum, a keystone species in European freshwater ecosystems. After deep RNA sequencing, we created a comprehensive ORF database. We identified and annotated the most relevant proteins detected through a shotgun tandem mass spectrometry analysis carried out on the proteomes from three major tissues involved in the organism's reproductive function: the male and female reproductive systems, and the cephalon, where different neuroendocrine glands are present. The 1,873 mass-spectrometry-certified proteins represent the largest crustacean proteomic resource to date, with 218 proteins being lineage specific. Comparative proteomics between the male and female reproductive systems indicated key proteins with strong sexual dimorphism. Protein expression profiles during spermatogenesis at seven different stages highlighted the major gammarid proteins involved in the different facets of reproduction.

N-terminomics and proteogenomics, getting off to a good start

Proteogenomics consists of the annotation or reannotation of protein-coding nucleic acid sequences based on the empirical observation of their gene products. While functional annotation of predicted genes is increasingly feasible given the multiplicity of genomes available for many branches of the tree of life, the accurate annotation of the translational start sites is still a point of contention. Extensive coverage of the proteome, including specifically the N-termini, is now possible, thanks to next-generation mass spectrometers able to record data from thousands of proteins at once. Efforts to increase the peptide coverage of protein sequences and to detect low abundance proteins are important to make proteomic and proteogenomic studies more comprehensive. In this review, we present the panoply of N-terminus-oriented strategies that have been developed over the last decade.

Proteomics meets blue biotechnology: a wealth of novelties and opportunities

Blue biotechnology, in which aquatic environments provide the inspiration for various products such as food additives, aquaculture, biosensors, green chemistry, bioenergy, and pharmaceuticals, holds enormous promise. Large-scale efforts to sequence aquatic genomes and metagenomes, as well as campaigns to isolate new organisms and culture-based screenings, are helping to push the boundaries of known organisms. Mass spectrometry-based proteomics can complement 16S gene sequencing in the effort to discover new organisms of potential relevance to blue biotechnology by facilitating the rapid screening of microbial isolates and by providing in depth profiles of the proteomes and metaproteomes of marine organisms, both model cultivable isolates and, more recently, exotic non-cultivable species and communities. Proteomics has already contributed to blue biotechnology by identifying aquatic proteins with potential applications to food fermentation, the textile industry, and biomedical drug development. In this review, we discuss historical developments in blue biotechnology, the current limitations to the known marine biosphere, and the ways in which mass spectrometry can expand that knowledge. We further speculate about directions that research in blue biotechnology will take given current and near-future technological advancements in mass spectrometry.

Next-generation snake venomics: protein-locus resolution through venom proteome decomplexation

Venom research has been continuously enhanced by technological advances. High-throughput technologies are changing the classical paradigm of hypothesis-driven research to technology-driven approaches. However, the thesis advocated in this paper is that full proteome coverage at locus-specific resolution requires integrating the best of both worlds into a protocol that includes decomplexation of the venom proteome prior to liquid chromatography-tandem mass spectrometry matching against a species-specific transcriptome. This approach offers the possibility of proof-checking the species-specific contig database using proteomics data. Immunoaffinity chromatography constitutes the basis of an antivenomics workflow designed to quantify the extent of cross-reactivity of antivenoms against homologous and heterologous venom toxins. In the author's view, snake venomics and antivenomics form part of a biology-driven conceptual framework to unveil the genesis and natural history of venoms, and their within- and between-species toxicological and immunological divergences and similarities. Understanding evolutionary trends across venoms represents the Rosetta Stone for generating broad-ranging polyspecific antivenoms.

Assessing the exoproteome of marine bacteria, lesson from a RTX-toxin abundantly secreted by Phaeobacter strain DSM 17395

Bacteria from the Roseobacter clade are abundant in surface marine ecosystems as over 10% of bacterial cells in the open ocean and 20% in coastal waters belong to this group. In order to document how these marine bacteria interact with their environment, we analyzed the exoproteome of Phaeobacter strain DSM 17395. We grew the strain in marine medium, collected the exoproteome and catalogued its content with high-throughput nanoLC-MS/MS shotgun proteomics. The major component represented 60% of the total protein content but was refractory to either classical proteomic identification or proteogenomics. We de novo sequenced this abundant protein with high-resolution tandem mass spectra which turned out being the 53 kDa RTX-toxin ZP_02147451. It comprised a peptidase M10 serralysin domain. We explained its recalcitrance to trypsin proteolysis and proteomic identification by its unusual low number of basic residues. We found this is a conserved trait in RTX-toxins from Roseobacter strains which probably explains their persistence in the harsh conditions around bacteria. Comprehensive analysis of exoproteomes from environmental bacteria should take into account this proteolytic recalcitrance.

Non-model organisms, a species endangered by proteogenomics

Previously, large-scale proteomics was possible only for organisms whose genomes were sequenced, meaning the most common model organisms. The use of next-generation sequencers is now changing the deal. With "proteogenomics", the use of experimental proteomics data to refine genome annotations, a higher integration of omics data is gaining ground. By extension, combining genomic and proteomic data is becoming routine in many research projects. "Proteogenomic"-flavored approaches are currently expanding, enabling the molecular studies of non-model organisms at an unprecedented depth. Today draft genomes can be obtained using next-generation sequencers in a rather straightforward way and at a reasonable cost for any organism. Unfinished genome sequences can be used to interpret tandem mass spectrometry proteomics data without the need for time-consuming genome annotation, and the use of RNA-seq to establish nucleotide sequences that are directly translated into protein sequences appears promising. There are, however, certain drawbacks that deserve further attention for RNA-seq to become more efficient. Here, we discuss the opportunities of working with non-model organisms, the proteomic methods that have been used until now, and the dramatic improvements proffered by proteogenomics. These put the distinction between model and non-model organisms in great danger, at least in terms of proteomics!

BIOLOGICAL SIGNIFICANCE

Model organisms have been crucial for in-depth analysis of cellular and molecular processes of life. Focusing the efforts of thousands of researchers on the Escherichia coli bacterium, Saccharomyces cerevisiae yeast, Arabidopsis thaliana plant, Danio rerio fish and other models for which genetic manipulation was possible was certainly worthwhile in terms of fundamental and invaluable biological insights. Until recently, proteomics of non-model organisms was limited to tedious, homology-based techniques, but today draft genomes or RNA-seq data can be straightforwardly obtained using next-generation sequencers, allowing the establishment of a draft protein database for any organism. Thus, proteogenomics opens new perspectives for molecular studies of non-model organisms, although they are still difficult experimental organisms. This article is part of a Special Issue entitled: Proteomics of non-model organisms.

Evaluating the impact of different sequence databases on metaproteome analysis: insights from a lab-assembled microbial mixture

Metaproteomics enables the investigation of the protein repertoire expressed by complex microbial communities. However, to unleash its full potential, refinements in bioinformatic approaches for data analysis are still needed. In this context, sequence databases selection represents a major challenge. This work assessed the impact of different databases in metaproteomic investigations by using a mock microbial mixture including nine diverse bacterial and eukaryotic species, which was subjected to shotgun metaproteomic analysis. Then, both the microbial mixture and the single microorganisms were subjected to next generation sequencing to obtain experimental metagenomic- and genomic-derived databases, which were used along with public databases (namely, NCBI, UniProtKB/SwissProt and UniProtKB/TrEMBL, parsed at different taxonomic levels) to analyze the metaproteomic dataset. First, a quantitative comparison in terms of number and overlap of peptide identifications was carried out among all databases. As a result, only 35% of peptides were common to all database classes; moreover, genus/species-specific databases provided up to 17% more identifications compared to databases with generic taxonomy, while the metagenomic database enabled a slight increment in respect to public databases. Then, database behavior in terms of false discovery rate and peptide degeneracy was critically evaluated. Public databases with generic taxonomy exhibited a markedly different trend compared to the counterparts. Finally, the reliability of taxonomic attribution according to the lowest common ancestor approach (using MEGAN and Unipept software) was assessed. The level of misassignments varied among the different databases, and specific thresholds based on the number of taxon-specific peptides were established to minimize false positives. This study confirms that database selection has a significant impact in metaproteomics, and provides critical indications for improving depth and reliability of metaproteomic results. Specifically, the use of iterative searches and of suitable filters for taxonomic assignments is proposed with the aim of increasing coverage and trustworthiness of metaproteomic data.

Proteogenomic definition of biomarkers for the large Roseobacter clade and application for a quick screening of new environmental isolates

Whole-cell, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry has become a routine and reliable method for microbial characterization due to its simplicity, low cost, and high reproducibility. The identification of microbial isolates relies on the spectral resemblance of low-molecular-weight proteins to already-existing isolates within the databases. This is a gold standard for clinicians who have a finite number of well-defined pathogenic strains but represents a problem for environmental microbiologists with an overwhelming number of organisms to be defined. Here we set a milestone for implementing whole-cell MALDI-TOF mass spectrometry to identify isolates from the biosphere. To make this technique accessible for environmental studies, we propose to (i) define biomarkers that will always show up with an intense m/z signal in the MALDI-TOF spectra and (ii) create a database with all the possible m/z values that these biomarkers can generate to screen new isolates. We tested our method with the relevant marine Roseobacter lineage. The use of shotgun nanoLC-MS/MS proteomics on the small proteome fraction of nine Roseobacter strains and the proteogenomic toolbox helped us to identify potential biomarkers in terms of protein abundance and low variability among strains. We show that the DNA binding protein, HU, and the ribosomal proteins, L29 and L30, are the most robust biomarkers within the Roseobacter clade. The molecular weights of these three biomarkers, as for other conserved homologous proteins, vary due to sequence variation above the genus level. Therefore, we calculated the m/z values expected for each one of the known Roseobacter genera and tested our strategy during an extensive screening of natural marine isolates obtained from coastal waters of the Western Mediterranean Sea. The use of this technique versus standard sequencing methods is discussed.