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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.

The aim of this study was to elucidate the evolution of enzyme secretome of early lineage fungi to contribute to resolving the basal part of Fungal Kingdom and pave the way for industrial evaluation of their unique enzymes. By combining results of advanced sequence analysis with secretome mass spectrometry and phylogenetic trees, we provide evidence for that plant cell wall degrading enzymes of higher fungi share a common ancestor with enzymes from aerobic ancient fungi. Sequence analysis (HotPep, confirmed by dbCAN-HMM models) enabled prediction of enzyme function directly from sequence. For the first time, oxidative enzymes are described here in early lineage fungi (Chytridiomycota & Cryptomycota), which supports the conceptually new understanding that fungal LPMOs were also present in the early evolution of the Fungal Kingdom. Phylogenetic analysis of fungal AA9 proteins suggests an LPMO-common-ancestor with Ascomycetes and Basidiomycetes and describes a new clade of AA9s. We identified two very strong biomass degraders, Rhizophlyctis rosea (soil-inhabiting) and Neocallimastix californiae (rumen), with a rich spectrum of cellulolytic, xylanolytic and pectinolytic enzymes, characteristically including several different enzymes with the same function. Their secretome composition suggests horizontal gene transfer was involved in transition to terrestrial and rumen habitats. Methods developed for recombinant production and protein characterization of enzymes from zoosporic fungi pave the way for biotechnological exploitation of unique enzymes from early lineage fungi with potential to contribute to improved biomass conversion. The phyla of ancient fungi through evolution have developed to be very different and together they constitute a rich enzyme discovery pool.

Crude oil is one of the most important natural assets for humankind, yet it is a major environmental pollutant, notably in marine environments. One of the largest crude oil polluted areas in the word is the semi-enclosed Mediterranean Sea, in which the metabolic potential of indigenous microbial populations towards the large-scale chronic pollution is yet to be defined, particularly in anaerobic and micro-aerophilic sites. Here, we provide an insight into the microbial metabolism in sediments from three chronically polluted marine sites along the coastline of Italy: the Priolo oil terminal/refinery site (near Siracuse, Sicily), harbour of Messina (Sicily) and shipwreck of MT Haven (near Genoa). Using shotgun metaproteomics and community metabolomics approaches, the presence of 651 microbial proteins and 4776 metabolite mass features have been detected in these three environments, revealing a high metabolic heterogeneity between the investigated sites. The proteomes displayed the prevalence of anaerobic metabolisms that were not directly related with petroleum biodegradation, indicating that in the absence of oxygen, biodegradation is significantly suppressed. This suppression was also suggested by examining the metabolome patterns. The proteome analysis further highlighted the metabolic coupling between methylotrophs and sulphate reducers in oxygen-depleted petroleum-polluted sediments.

Motivation: With the advent of meta-‘omics’ data, the use of metabolic networks for the functional analysis of microbial communities became possible. However, while network-based methods are widely developed for single organisms, their application to bacterial communities is currently limited. Results: Herein, we provide a novel, context-specific reconstruction procedure based on metaproteomic and taxonomic data. Without previous knowledge of a high-quality, genome-scale metabolic networks for each different member in a bacterial community, we propose a meta-network approach, where the expression levels and taxonomic assignments of proteins are used as the most relevant clues for inferring an active set of reactions. Our approach was applied to draft the context-specific metabolic networks of two different naphthalene-enriched communities derived from an anthropogenically influenced, polyaromatic hydrocarbon contaminated soil, with (CN2) or without (CN1) bio-stimulation. We were able to capture the overall functional differences between the two conditions at the metabolic level and predict an important activity for the fluorobenzoate degradation pathway in CN1 and for geraniol metabolism in CN2. Experimental validation was conducted, and good agreement with our computational predictions was observed. We also hypothesize different pathway organizations at the organismal level, which is relevant to disentangle the role of each member in the communities. The approach presented here can be easily transferred to the analysis of genomic, transcriptomic and metabolomic data.

[Motivation]: With the advent of meta-'omics' data, the use of metabolic networks for the functional analysis of microbial communities became possible. However, while network-based methods are widely developed for single organisms, their application to bacterial communities is currently limited., [Results]: Herein, we provide a novel, context-specific reconstruction procedure based on metaproteomic and taxonomic data. Without previous knowledge of a high-quality, genome-scale metabolic networks for each different member in a bacterial community, we propose a meta-network approach, where the expression levels and taxonomic assignments of proteins are used as the most relevant clues for inferring an active set of reactions. Our approach was applied to draft the context-specific metabolic networks of two different naphthalene-enriched communities derived from an anthropogenically influenced, polyaromatic hydrocarbon contaminated soil, with (CN2) or without (CN1) bio-stimulation. We were able to capture the overall functional differences between the two conditions at the metabolic level and predict an important activity for the fluorobenzoate degradation pathway in CN1 and for geraniol metabolism in CN2. Experimental validation was conducted, and good agreement with our computational predictions was observed. We also hypothesize different pathway organizations at the organismal level, which is relevant to disentangle the role of each member in the communities. The approach presented here can be easily transferred to the analysis of genomic, transcriptomic and metabolomic data.

Crude oil is one of the most important natural assets for humankind, yet it is a major environmental pollutant, notably in marine environments. One of the largest crude oil polluted areas in the word is the semi‐enclosed Mediterranean Sea, in which the metabolic potential of indigenous microbial populations towards the large‐scale chronic pollution is yet to be defined, particularly in anaerobic and micro‐aerophilic sites. Here, we provide an insight into the microbial metabolism in sediments from three chronically polluted marine sites along the coastline of Italy: the Priolo oil terminal/refinery site (near Siracuse, Sicily), harbour of Messina (Sicily) and shipwreck of MT Haven (near Genoa). Using shotgun metaproteomics and community metabolomics approaches, the presence of 651 microbial proteins and 4776 metabolite mass features have been detected in these three environments, revealing a high metabolic heterogeneity between the investigated sites. The proteomes displayed the prevalence of anaerobic metabolisms that were not directly related with petroleum biodegradation, indicating that in the absence of oxygen, biodegradation is significantly suppressed. This suppression was also suggested by examining the metabolome patterns. The proteome analysis further highlighted the metabolic coupling between methylotrophs and sulphate reducers in oxygen‐depleted petroleum‐polluted sediments.

We propose a joint experimental and theoretical approach to the automated reconstruction of elemental fluxes in microbial communities. While stable isotope probing of proteins (protein-SIP) has been successfully applied to study interactions and elemental carbon and nitrogen fluxes, the volume and complexity of mass spectrometric data in protein-SIP experiments pose new challenges for data analysis. Together with a flexible experimental setup, the novel bioinformatics tool MetaProSIP offers an automated high-throughput solution for a wide range of 13C or 15N protein-SIP experiments with special emphasis on the analysis of metaproteomic experiments where differential labeling of organisms can occur. The information calculated in MetaProSIP includes the determination of multiple relative isotopic abundances, the labeling ratio between old and new synthesized proteins, and the shape of the isotopic distribution. These parameters define the metabolic capacities and dynamics within the investigated microbial culture. MetaProSIP features a high degree of reproducibility, reliability, and quality control reporting. The ability to embed into the OpenMS framework allows for flexible construction of custom-tailored workflows. Software and documentation are available under an open-source license at www.openms.de/MetaProSIP.

Vancomycin is one of the few remaining treatment options for multi resistant Staphylococcus aureus infections. Several transcriptomics and proteomics studies have investigated the bacterium's cellular response to vancomycin, but quantitative proteomic studies have been limited in the number of proteins and restricted to certain sub-cellular compartments so far.Here, we combined the enrichment of different proteomic sub-fractions with in vivo metabolic labeling and shotgun proteomics to analyze the vancomycin induced stress response. Quantitative data for approximately 1400 proteins could be obtained, covering the majority of cytosolic as well as membrane localized proteins, cell surface associated and extracellular proteins. Besides major adaptive processes induced by limited growth of the cells due to the sublethal vancomycin exposure, specific cellular responses are seen on proteome level, e.g. the specific increase of proteins synthesizing amino acids which are essential for the peptidoglycan synthesis or the decrease of most proteins with a virulence related function. Most important, the influence on regulatory targets of the two-component system VraSR as the main regulatory system known for cell wall stress as well as for global regulons like SigB and SaeR was detected.

The recent development of metaproteomics has enabled the direct identification and quantification of expressed proteins from microbial communities in situ, without the need for microbial enrichment. This became possible by (1) significant increases in quality and quantity of metagenome data and by improvements of (2) accuracy and (3) sensitivity of modern mass spectrometers (MS). The identification of physiologically relevant enzymes can help to understand the role of specific species within a community or an ecological niche. Beside identification, relative and absolute quantitation is also crucial. We will review label-free and label-based methods of quantitation in MS-based proteome analysis and the contribution of quantitative proteome data to microbial ecology. Additionally, approaches of protein-based stable isotope probing (protein-SIP) for deciphering community structures are reviewed. Information on the species-specific metabolic activity can be obtained when substrates or nutrients are labeled with stable isotopes in a protein-SIP approach. The stable isotopes (13C, 15N, 36S) are incorporated into proteins and the rate of incorporation can be used for assessing the metabolic activity of the corresponding species. We will focus on the relevance of the metabolic and phylogenetic information retrieved with protein-SIP studies and for detecting and quantifying the carbon flux within microbial consortia. Furthermore, the combination of protein-SIP with established tools in microbial ecology such as other stable isotope probing techniques are discussed.

The relative quantification of proteins is one of the major techniques to elucidate physiological reactions. In order to avoid artifacts due to chemical labeling the metabolic introduction of heavy isotopes into proteins and peptides is the preferred method for relative quantification. For eukaryotic cells stable isotope labeling by amino acids in cell culture (SILAC) has become the gold standard which can be readily applied to a vast number of scenarios. In the microbial realm with its highly versatile metabolic capabilities SILAC is often not feasible and using other 13C or 15N labeled substrates may not be practical. Here, the incorporation of heavy sulfur isotopes is a useful alternative. We therefore introduce 34sulfur stable isotope labeling of amino acids for quantification (SULAQ34) and the corresponding tools required for spectra extraction and disintegration of the isotopic overlaps caused by the small mass shift. As a proof of principle we investigated the proteomic changes related to naphthalene degradation in P. fluorescens ATCC 17483 and uncovered a specific oxidative stress like response.

Microbial metabolism in aromatic-contaminated environments has important ecological implications, and obtaining a complete understanding of this process remains a relevant goal. To understand the roles of biodiversity and aromatic-mediated genetic and metabolic rearrangements, we conducted ‘OMIC’ investigations in an anthropogenically influenced and polyaromatic hydrocarbon (PAH)-contaminated soil with (Nbs) or without (N) bio-stimulation with calcium ammonia nitrate, NH4NO3 and KH2PO4 and the commercial surfactant Iveysol, plus two naphthalene-enriched communities derived from both soils (CN2 and CN1, respectively). Using a metagenomic approach, a total of 52, 53, 14 and 12 distinct species (according to operational phylogenetic units (OPU) in our work equivalent to taxonomic species) were identified in the N, Nbs, CN1 and CN2 communities, respectively. Approximately 10 out of 95 distinct species and 238 out of 3293 clusters of orthologous groups (COGs) protein families identified were clearly stimulated under the assayed conditions, whereas only two species and 1465 COGs conformed to the common set in all of the mesocosms. Results indicated distinct biodegradation capabilities for the utilisation of potential growth-supporting aromatics, which results in bio-stimulated communities being extremely fit to naphthalene utilisation and non-stimulated communities exhibiting a greater metabolic window than previously predicted. On the basis of comparing protein expression profiles and metagenome data sets, inter-alia interactions among members were hypothesised. The utilisation of curated databases is discussed and used for first time to reconstruct ‘presumptive’ degradation networks for complex microbial communities.

Metaproteomics of microbial communities bears the promise to add functional information to the blueprint of genes derived from metagenomics. Right from its beginning the achievements and developments in metaproteomics were closely interlinked with metagenomics. In addition, the evaluation, visualisation and interpretation of metaproteome data demanded for the developments in bioinformatics. This review will give an overview about recent strategies to use genomic data either from public databases or organismal-specific genomes/metagenomes to increase the number of identified proteins obtained by mass spectrometric measurements. We will review different published metaproteogenomic approaches in respect to the used mass spectrometry pipeline and to the used protein identification workflow. Furthermore different approaches of data visualisation and strategies for phylogenetic interpretation of metaproteome data are discussed as well as approaches for functional mapping of the results to the investigated biological systems. This information will in the end allow to comprehensively analysing interactions and interdependencies within microbial communities.

Current knowledge of the physiology and phylogeny of polycyclic aromatic hydrocarbon (PAH) degrading bacteria often relies on laboratory enrichments and isolations. In the present study, in situ microcosms consisting of activated carbon pellets (BACTRAP®s) were loaded with either 13C-naphthalene or 13C-fluorene and were subsequently exposed in the contaminant source and plume fringe region of an PAH contaminated aquifer. Metaproteomic analysis and protein-SIP revealed Burkholderiales, Actinomycetales and Rhizobiales as the most active microorganisms in the groundwater communities. Proteins identified of the naphthalene degradation pathway showed a relative 13C isotope abundance of approximately 50 atom% demonstrating that the identified naphthalene degrading bacteria gained at least 80% of their carbon by PAH degradation. Although the microbial community grown on the fluorene-BACTRAPs showed a structure similar to the naphthalene-BACTRAPs, the identification of fluorene degraders and degradation pathways failed in situ. In complementary laboratory microcosms, a clear enrichment in proteins related to Rhodococcus and possible fluorene degradation enzymes was observed. This result demonstrates the impact of laboratory conditions on microbial community structure and activity of certain species and underlines the need on in situ exploration of microbial community functions. In situ microcosms in combination with protein-SIP may be a significant tool for in situ identification of metabolic key players as well as degradation pathways.

Metaproteomics of microbial communities promises to add functional information to the blueprint of genes derived from metagenomics. Right from its beginning, the achievements and developments in metaproteomics were closely interlinked with metagenomics. In addition, the evaluation, visualization, and interpretation of metaproteome data demanded for the developments in bioinformatics. This review will give an overview about recent strategies to use genomic data either from public databases or organismal specific genomes/metagenomes to increase the number of identified proteins obtained by mass spectrometric measurements. We will review different published metaproteogenomic approaches in respect to the used MS pipeline and to the used protein identification workflow. Furthermore, different approaches of data visualization and strategies for phylogenetic interpretation of metaproteome data are discussed as well as approaches for functional mapping of the results to the investigated biological systems. This information will in the end allow a comprehensive analysis of interactions and interdependencies within microbial communities.

We introduce a universal metabolic labeling strategy using elemental heavy 36Sulfur (36S) called 36Sulfur stable isotope labeling of amino acids for quantification (SULAQ). In the proof of principle experiment, Pseudomonas putida KT2440 was grown in defined minimal medium with sodium benzoate or sodium succinate as the sole carbon and 32S- or 36S-sodium sulfate as the sole sulfur sources. Quantification using mass spectrometry resulted in 562 proteins with 1991 unique peptides. SULAQ technology can be a valuable alternative strategy for the quantitative comparisons in MS-based proteomics approaches characterizing bacterial and other biological samples in different growth conditions.

Staphylococcus aureus is capable of colonizing and infecting humans by its arsenal of surface-exposed and secreted proteins. Iron-limited conditions in mammalian body fluids serve as a major environmental signal to bacteria to express virulence determinants. Here we present a comprehensive, gel-free, and GeLC-MS/MS-based quantitative proteome profiling of S. aureus under this infection-relevant situation. 14N15N metabolic labeling and three complementing approaches were combined for relative quantitative analyses of surface-associated proteins. The surface-exposed and secreted proteome profiling approaches comprise trypsin shaving, biotinylation, and precipitation of the supernatant. By analysis of the outer subproteomic and cytoplasmic protein fraction, 1210 proteins could be identified including 221 surface-associated proteins. Thus, access was enabled to 70% of the predicted cell wall-associated proteins, 80% of the predicted sortase substrates, two/thirds of lipoproteins and more than 50% of secreted and cytoplasmic proteins. For iron-deficiency, 158 surface-associated proteins were quantified. Twenty-nine proteins were found in altered amounts showing particularly surface-exposed proteins strongly induced, such as the iron-regulated surface determinant proteins IsdA, IsdB, IsdC and IsdD as well as lipid-anchored iron compound-binding proteins. The work presents a crucial subject for understanding S. aureus pathophysiology by the use of methods that allow quantitative surface proteome profiling.

Functional genomics of the Gram-positive model organism Bacillus subtilis reveals valuable insights into basic concepts of cell physiology. In this study, we monitor temporal changes in the proteome, transcriptome and extracellular metabolome of B. subtilis caused by glucose starvation. For proteomic profiling, a combination of in vivo metabolic labelling and shotgun mass spectrometric analysis was carried out for five different proteomic subfractions (cytosolic, integral membrane, membrane, surface and extracellular proteome fraction), leading to the identification of ~52% of the predicted proteome of B. subtilis. Quantitative proteomic and corresponding transcriptomic data were analysed with Voronoi treemaps linking functional classification and relative expression changes of gene products according to their fate in the stationary phase. The obtained data comprise the first comprehensive profiling of changes in the membrane subfraction and allow in-depth analysis of major physiological processes, including monitoring of protein degradation.