Functional analysis of natural microbial consortia using community proteomics

Microbial consortia-mediated arsenic bioremediation in agricultural soils: Current status, challenges, and solutions

Arsenic poisoning in agricultural soil is caused by both natural and man-made processes, and it poses a major risk to crop production and human health. Soil quality, agricultural production, runoff, ingestion, leaching, and absorption by plants are all influenced by these processes. Microbial consortia have become a feasible bioremediation technique in response to the urgent need for appropriate remediation solutions. These diverse microbial populations collaborate to combat arsenic poisoning in soil by facilitating mechanisms including oxidation-reduction, methylation-demethylation, volatilization, immobilization, and arsenic mobilization. The current state, problems, and remedies for employing microbial consortia in arsenic bioremediation in agricultural soils are examined in this review. Among the elements affecting their success include diversity, activity, community organization, and environmental conditions. Also, we emphasize the sensitivity and accuracy limits of existing assessment techniques. While earlier reviews have addressed a variety of arsenic remediation options, this study stands out by concentrating on microbial consortia as a viable strategy for arsenic removal and presents performance evaluation and technical problems. This work gives vital insights for tackling the major issue of arsenic pollution in agricultural soils by explaining the potential methods and components involved in microbial consortium-mediated arsenic bioremediation.

Pairing metagenomics and metaproteomics to characterize ecological niches and metabolic essentiality of gut microbiomes

The genome of a microorganism encodes its potential functions that can be implemented through expressed proteins. It remains elusive how a protein's selective expression depends on its metabolic essentiality to microbial growth or its ability to claim resources as ecological niches. To reveal a protein's metabolic or ecological role, we developed a computational pipeline, which pairs metagenomics and metaproteomics data to quantify each protein's gene-level and protein-level functional redundancy simultaneously. We first illustrated the idea behind the pipeline using simulated data of a consumer-resource model. We then validated it using real data from human and mouse gut microbiome samples. In particular, we analyzed ABC-type transporters and ribosomal proteins, confirming that the metabolic and ecological roles predicted by our pipeline agree well with prior knowledge. Finally, we performed in vitro cultures of a human gut microbiome sample and investigated how oversupplying various sugars involved in ecological niches influences the community structure and protein abundance. The presented results demonstrate the performance of our pipeline in identifying proteins' metabolic and ecological roles, as well as its potential to help us design nutrient interventions to modulate the human microbiome.

Microalgal co-cultivation -recent methods, trends in omic-studies, applications, and future challenges

The burgeoning human population has resulted in an augmented demand for raw materials and energy sources, which in turn has led to a deleterious environmental impact marked by elevated greenhouse gas (GHG) emissions, acidification of water bodies, and escalating global temperatures. Therefore, it is imperative that modern society develop sustainable technologies to avert future environmental degradation and generate alternative bioproduct-producing technologies. A promising approach to tackling this challenge involves utilizing natural microbial consortia or designing synthetic communities of microorganisms as a foundation to develop diverse and sustainable applications for bioproduct production, wastewater treatment, GHG emission reduction, energy crisis alleviation, and soil fertility enhancement. Microalgae, which are photosynthetic microorganisms that inhabit aquatic environments and exhibit a high capacity for CO2 fixation, are particularly appealing in this context. They can convert light energy and atmospheric CO2 or industrial flue gases into valuable biomass and organic chemicals, thereby contributing to GHG emission reduction. To date, most microalgae cultivation studies have focused on monoculture systems. However, maintaining a microalgae monoculture system can be challenging due to contamination by other microorganisms (e.g., yeasts, fungi, bacteria, and other microalgae species), which can lead to low productivity, culture collapse, and low-quality biomass. Co-culture systems, which produce robust microorganism consortia or communities, present a compelling strategy for addressing contamination problems. In recent years, research and development of innovative co-cultivation techniques have substantially increased. Nevertheless, many microalgae co-culturing technologies remain in the developmental phase and have yet to be scaled and commercialized. Accordingly, this review presents a thorough literature review of research conducted in the last few decades, exploring the advantages and disadvantages of microalgae co-cultivation systems that involve microalgae-bacteria, microalgae-fungi, and microalgae-microalgae/algae systems. The manuscript also addresses diverse uses of co-culture systems, and growing methods, and includes one of the most exciting research areas in co-culturing systems, which are omic studies that elucidate different interaction mechanisms among microbial communities. Finally, the manuscript discusses the economic viability, future challenges, and prospects of microalgal co-cultivation methods.

Monitoring of microbial proteome dynamics using Raman stable isotope probing

Abnormal protein kinetics could be a cause of several diseases associated with essential life processes. An accurate understanding of protein dynamics and turnover is essential for developing diagnostic or therapeutic tools to monitor these changes. Raman spectroscopy in combination with stable isotope probes (SIP) such as carbon-13, and deuterium has been a breakthrough in the qualitative and quantitative study of various metabolites. In this work, we are reporting the utility of Raman-SIP for monitoring dynamic changes in the proteome at the community level. We have used ¹³ C-labeled glucose as the only carbon source in the medium and verified its incorporation in the microbial biomass in a time-dependent manner. A visible redshift in the Raman spectral vibrations of major biomolecules such as nucleic acids, phenylalanine, tyrosine, amide I, and amide III were observed. Temporal changes in the intensity of these bands demonstrating the feasibility of protein turnover monitoring were also verified. Kanamycin, a protein synthesis inhibitor was used to assess the feasibility of identifying effects on protein turnover in the cells. Successful application of this work can provide an alternate/adjunct tool for monitoring proteome-level changes in an objective and nondestructive manner.

Marine Bacteria and Omic Approaches: A Novel and Potential Repository for Bioremediation Assessment

Marine environments accommodating diverse assortments of life constitute a great pool of differentiated natural resources. The cumulative need to remedy unpropitious effects of anthropogenic activities on estuaries, and coastal marine ecosystems has propelled the development of effective bioremediation strategies. Marine bacteria producing biosurfactants are promising agents for bio-remediating oil pollution in marine environments, making them prospective candidates for enhancing oil recovery. Molecular omics technologies are considered an emerging field of research in ecological and diversity assessment owing to their utility in environmental surveillance and bioremediation of polluted sites. A thorough literature review was undertaken to understand the applicability of different omic techniques employed for bioremediation assessment using marine bacteria. This review further establishes that for bioremediation of environmental pollutants (i.e., heavy metals, hydrocarbons, xenobiotic and numerous recalcitrant compounds), organisms isolated from marine environments can be better utilized for their removal. The literature survey shows that omics approaches can provide exemplary knowledge about microbial communities and their role in the bioremediation of environmental pollutants. This review centres on applications of marine bacteria in enhanced bioremediation, utilizing the omics approaches that can be a vital biological contrivance in environmental monitoring to tackle environmental degradation. The paper aims to identify the gaps in investigations involving marine bacteria to help researchers, ecologists, and decision-makers to develop a holistic understanding regarding their utility in bioremediation assessment.

Characterizing the Microbial Consortium L1 Capable of Efficiently Degrading Chlorimuron-Ethyl via Metagenome Combining 16S rDNA Sequencing

Excessive application of the herbicide chlorimuron-ethyl (CE) severely harms subsequent crops and poses severe risks to environmental health. Therefore, methods for efficiently decreasing and eliminating CE residues are urgently needed. Microbial consortia show potential for bioremediation due to their strong metabolic complementarity and synthesis. In this study, a microbial consortium entitled L1 was enriched from soil contaminated with CE by a “top-down” synthetic biology strategy. The consortium could degrade 98.04% of 100 mg L−1 CE within 6 days. We characterized it from the samples at four time points during the degradation process and a sample without degradation activity via metagenome and 16S rDNA sequencing. The results revealed 39 genera in consortium L1, among which Methyloversatilis (34.31%), Starkeya (28.60%), and Pseudoxanthomonas (7.01%) showed relatively high abundances. Temporal succession and the loss of degradability did not alter the diversity and community composition of L1 but changed the community structure. Taxon-functional contribution analysis predicted that glutathione transferase [EC 2.5.1.18], urease [EC 3.5.1.5], and allophanate hydrolase [EC 3.5.1.54] are relevant for the degradation of CE and that Methyloversatilis, Pseudoxanthomonas, Methylopila, Hyphomicrobium, Stenotrophomonas, and Sphingomonas were the main degrading genera. The degradation pathway of CE by L1 may involve cleavage of the CE carbamide bridge to produce 2-amino-4-chloro-6-methoxypyrimidine and ethyl o-sulfonamide benzoate. The results of network analysis indicated close interactions, cross-feeding, and co-metabolic relationships between strains in the consortium, and most of the above six degrading genera were keystone taxa in the network. Additionally, the degradation of CE by L1 required not only “functional bacteria” with degradation capacity but also “auxiliary bacteria” without degradation capacity but that indirectly facilitate/inhibit the degradation process; however, the abundance of “auxiliary bacteria” should be controlled in an appropriate range. These findings improve the understanding of the synergistic effects of degrading bacterial consortia, which will provide insight for isolating degrading bacterial resources and constructing artificial efficient bacterial consortia. Furthermore, our results provide a new route for pollution control and biodegradation of sulfonylurea herbicides.

Metabolic Profiling of Interspecies Interactions During Sessile Bacterial Cultivation Reveals Growth and Sporulation Induction in Paenibacillus amylolyticus in Response to Xanthomonas retroflexus

The toolbox available for microbiologists to study interspecies interactions is rapidly growing, and with continuously more advanced instruments, we are able to expand our knowledge on establishment and function of microbial communities. However, unravelling molecular interspecies interactions in complex biological systems remains a challenge, and interactions are therefore often studied in simplified communities. Here we perform an in-depth characterization of an observed interspecies interaction between two co-isolated bacteria, Xanthomonas retroflexus and Paenibacillus amylolyticus. Using microsensor measurements for mapping the chemical environment, we show how X. retroflexus promoted an alkalization of its local environment through degradation of amino acids and release of ammonia. When the two species were grown in proximity, the modified local environment induced a morphological change and growth of P. amylolyticus followed by sporulation. 2D spatial metabolomics enabled visualization and mapping of the degradation of oligopeptide structures by X. retroflexus and morphological changes of P. amylolyticus through e.g. the release of membrane-associated metabolites. Proteome analysis and microscopy were used to validate the shift from vegetative growth towards sporulation. In summary, we demonstrate how environmental profiling by combined application of microsensor, microscopy, metabolomics and proteomics approaches can reveal growth and sporulation promoting effects resulting from interspecies interactions.

Quantitative metaproteomics and activity-based protein profiling of patient fecal microbiome identifies host and microbial serine-type endopeptidase activity associated with ulcerative colitis

The gut microbiota plays an important yet incompletely understood role in the induction and propagation of ulcerative colitis (UC). Organism-level efforts to identify UC-associated microbes have revealed the importance of community structure, but less is known about the molecular effectors of disease. We performed 16S rRNA gene sequencing in parallel with label-free data-dependent LC-MS/MS proteomics to characterize the stool microbiomes of healthy (n = 8) and UC (n = 10) patients. Comparisons of taxonomic composition between techniques revealed major differences in community structure partially attributable to the additional detection of host, fungal, viral, and food peptides by metaproteomics. Differential expression analysis of metaproteomic data identified 176 significantly enriched protein groups between healthy and UC patients. Gene ontology analysis revealed several enriched functions with serine-type endopeptidase activity overrepresented in UC patients. Using a biotinylated fluorophosphonate probe and streptavidin-based enrichment, we show that serine endopeptidases are active in patient fecal samples and that additional putative serine hydrolases are detectable by this approach compared with unenriched profiling. Finally, as metaproteomic databases expand, they are expected to asymptotically approach completeness. Using ComPIL and de novo peptide sequencing, we estimate the size of the probable peptide space unidentified (“dark peptidome”) by our large database approach to establish a rough benchmark for database sufficiency. Despite high variability inherent in patient samples, our analysis yielded a catalog of differentially enriched proteins between healthy and UC fecal proteomes. This catalog provides a clinically relevant jumping-off point for further molecular-level studies aimed at identifying the microbial underpinnings of UC.

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Identified 176 significantly altered protein groups between healthy and UC patients.

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Serine-type endopeptidase activity is overrepresented in UC patients.

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Fluorophosphonate ABPP shows that endopeptidases are active in fecal samples.

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ABPP enrichment helps identify additional putative serine hydrolases in samples.

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De novo sequencing used to estimate number of MS2 spectra unidentified by ComPIL.

Evaluation of RNAlater as a Field-Compatible Preservation Method for Metaproteomic Analyses of Bacterium-Animal Symbioses

Field studies are central to environmental microbiology and microbial ecology, because they enable studies of natural microbial communities. Metaproteomics, the study of protein abundances in microbial communities, allows investigators to study these communities "in situ," which requires protein preservation directly in the field because protein abundance patterns can change rapidly after sampling. Ideally, a protein preservative for field deployment works rapidly and preserves the whole proteome, is stable in long-term storage, is nonhazardous and easy to transport, and is available at low cost. Although these requirements might be met by several protein preservatives, an assessment of their suitability under field conditions when targeted for metaproteomic analyses is currently lacking. Here, we compared the protein preservation performance of flash freezing and the preservation solution RNAlater using the marine gutless oligochaete Olavius algarvensis and its symbiotic microbes as a test case. In addition, we evaluated long-term RNAlater storage after 1 day, 1 week, and 4 weeks at room temperature (22°C to 23°C). We evaluated protein preservation using one-dimensional liquid chromatography-tandem mass spectrometry. We found that RNAlater and flash freezing preserved proteins equally well in terms of total numbers of identified proteins and relative abundances of individual proteins, and none of the test time points was altered, compared to time zero. Moreover, we did not find biases against specific taxonomic groups or proteins with particular biochemical properties. Based on our metaproteomic data and the logistical requirements for field deployment, we recommend RNAlater for protein preservation of field-collected samples targeted for metaproteomic analyses. IMPORTANCE Metaproteomics, the large-scale identification and quantification of proteins from microbial communities, provide direct insights into the phenotypes of microorganisms on the molecular level. To ensure the integrity of the metaproteomic data, samples need to be preserved immediately after sampling to avoid changes in protein abundance patterns. In laboratory setups, samples for proteomic analyses are most commonly preserved by flash freezing; however, liquid nitrogen or dry ice is often unavailable at remote field locations, due to their hazardous nature and transport restrictions. Our study shows that RNAlater can serve as a low-hazard, easy-to-transport alternative to flash freezing for field preservation of samples for metaproteomic analyses. We show that RNAlater preserves the metaproteome equally well, compared to flash freezing, and protein abundance patterns remain stable during long-term storage for at least 4 weeks at room temperature.

Novel Enzymes From the Red Sea Brine Pools: Current State and Potential

The Red Sea is a marine environment with unique chemical characteristics and physical topographies. Among the various habitats offered by the Red Sea, the deep-sea brine pools are the most extreme in terms of salinity, temperature and metal contents. Nonetheless, the brine pools host rich polyextremophilic bacterial and archaeal communities. These microbial communities are promising sources for various classes of enzymes adapted to harsh environments - extremozymes. Extremozymes are emerging as novel biocatalysts for biotechnological applications due to their ability to perform catalytic reactions under harsh biophysical conditions, such as those used in many industrial processes. In this review, we provide an overview of the extremozymes from different Red Sea brine pools and discuss the overall biotechnological potential of the Red Sea proteome.

Photoautotrophs-Bacteria Co-Cultures: Advances, Challenges and Applications

Photosynthetic microorganisms are among the fundamental living organisms exploited for millennia in many industrial applications, including the food chain, thanks to their adaptable behavior and intrinsic proprieties. The great multipotency of these photoautotroph microorganisms has been described through their attitude to become biofarm for the production of value-added compounds to develop functional foods and personalized drugs. Furthermore, such biological systems demonstrated their potential for green energy production (e.g., biofuel and green nanomaterials). In particular, the exploitation of photoautotrophs represents a concrete biorefinery system toward sustainability, currently a highly sought-after concept at the industrial level and for the environmental protection. However, technical and economic issues have been highlighted in the literature, and in particular, challenges and limitations have been identified. In this context, a new perspective has been recently considered to offer solutions and advances for the biomanufacturing of photosynthetic materials: the co-culture of photoautotrophs and bacteria. The rational of this review is to describe the recently released information regarding this microbial consortium, analyzing the critical issues, the strengths and the next challenges to be faced for the intentions attainment.

Genomics as a potential tool to unravel the rhizosphere microbiome interactions on plant health

Intense agricultural practices to meet rising food demands have caused ecosystem perturbations. For sustainable crop production, biological agents are gaining attention, but exploring their functional potential on a multi-layered complex ecosystem like the rhizosphere is challenging. This review explains the significance of genomics as a culture-independent molecular tool to understand the diversity and functional significance of the rhizosphere microbiome for sustainable agriculture. It discusses the recent significant studies in the rhizosphere environment carried out using evolving techniques like metagenomics, metatranscriptomics, and metaproteomics, their challenges, constraints infield application, and prospective solutions. The recent advances in techniques such as nanotechnology for the development of bioformulations and visualization techniques contemplating environmental safety were also discussed. The need for development of metagenomic data sets of regionally important crops, their plant microbial interactions and agricultural practices for narrowing down significant data from huge databases have been suggested. The role of taxonomical and functional diversity of soil microbiota in understanding soil suppression and part played by the microbial metabolites in the process have been analyzed and discussed in the context of 'omics' approach. 'Omics' studies have revealed important information about microbial diversity, their responses to various biotic and abiotic stimuli, and the physiology of disease suppression. This can be translated to crop sustainability and combinational approaches with advancing visualization and analysis methodologies fix the existing knowledge gap to a huge extend. With improved data processing and standardization of the methods, details of plant-microbe interactions can be successfully decoded to develop sustainable agricultural practices.

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on "omics" driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in "omics" technologies, compare the pros and cons of the different "omics" technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of "omics" technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of "omics" technologies to agricultural and food biotechnology, and review the impact of "omics" on current COVID-19 research.

Ancient protein analysis in archaeology

The analysis of ancient proteins from paleontological, archeological, and historic materials is revealing insights into past subsistence practices, patterns of health and disease, evolution and phylogeny, and past environments. This review tracks the development of this field, discusses some of the major methodological strategies used, and synthesizes recent developments in archeological applications of ancient protein analysis. Moreover, this review highlights some of the challenges faced by the field and potential future directions, arguing that the development of minimally invasive or nondestructive techniques, strategies for protein authentication, and the integration of ancient protein analysis with other biomolecular techniques are important research strategies as this field grows.

Gut-Brain Axis and Neurodegeneration: State-of-the-Art of Meta-Omics Sciences for Microbiota Characterization

Recent advances in the field of meta-omics sciences and related bioinformatics tools have allowed a comprehensive investigation of human-associated microbiota and its contribution to achieving and maintaining the homeostatic balance. Bioactive compounds from the microbial community harboring the human gut are involved in a finely tuned network of interconnections with the host, orchestrating a wide variety of physiological processes. These includes the bi-directional crosstalk between the central nervous system, the enteric nervous system, and the gastrointestinal tract (i.e., gut-brain axis). The increasing accumulation of evidence suggest a pivotal role of the composition and activity of the gut microbiota in neurodegeneration. In the present review we aim to provide an overview of the state-of-the-art of meta-omics sciences including metagenomics for the study of microbial genomes and taxa strains, metatranscriptomics for gene expression, metaproteomics and metabolomics to identify and/or quantify microbial proteins and metabolites, respectively. The potential and limitations of each discipline were highlighted, as well as the advantages of an integrated approach (multi-omics) to predict microbial functions and molecular mechanisms related to human diseases. Particular emphasis is given to the latest results obtained with these approaches in an attempt to elucidate the link between the gut microbiota and the most common neurodegenerative diseases, such as multiple sclerosis (MS), Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).

Antimicrobial Resistance in Veterinary Medicine: An Overview

Antimicrobial resistance (AMR) represents one of the most important human- and animal health-threatening issues worldwide. Bacterial capability to face antimicrobial compounds is an ancient feature, enabling bacterial survival over time and the dynamic surrounding. Moreover, bacteria make use of their evolutionary machinery to adapt to the selective pressure exerted by antibiotic treatments, resulting in reduced efficacy of the therapeutic intervention against human and animal infections. The mechanisms responsible for both innate and acquired AMR are thoroughly investigated. Commonly, AMR traits are included in mobilizable genetic elements enabling the homogeneous diffusion of the AMR traits pool between the ecosystems of diverse sectors, such as human medicine, veterinary medicine, and the environment. Thus, a coordinated multisectoral approach, such as One-Health, provides a detailed comprehensive picture of the AMR onset and diffusion. Following a general revision of the molecular mechanisms responsible for both innate and acquired AMR, the present manuscript focuses on reviewing the contribution of veterinary medicine to the overall issue of AMR. The main sources of AMR amenable to veterinary medicine are described, driving the attention towards the indissoluble cross-talk existing between the diverse ecosystems and sectors and their cumulative cooperation to this warning phenomenon.

Estimating relative biomasses of organisms in microbiota using "phylopeptidomics"

BACKGROUND

There is an important need for the development of fast and robust methods to quantify the diversity and temporal dynamics of microbial communities in complex environmental samples. Because tandem mass spectrometry allows rapid inspection of protein content, metaproteomics is increasingly used for the phenotypic analysis of microbiota across many fields, including biotechnology, environmental ecology, and medicine.

RESULTS

Here, we present a new method for identifying the biomass contribution of any given organism based on a signature describing the number of peptide sequences shared with all other organisms, calculated by mathematical modeling and phylogenetic relationships. This so-called "phylopeptidomics" principle allows for the calculation of the relative ratios of peptide-specified taxa by the linear combination of such signatures applied to an experimental metaproteomic dataset. We illustrate its efficiency using artificial mixtures of two closely related pathogens of clinical interest, and with more complex microbiota models.

CONCLUSIONS

This approach paves the way to a new vision of taxonomic changes and accurate label-free quantitative metaproteomics for fine-tuned functional characterization. Video abstract.

Combining Molecular Observations and Microbial Ecosystem Modeling: A Practical Guide

Advances in technologies for molecular observation are leading to novel types of data, including gene, transcript, protein, and metabolite levels, which are fundamentally different from the types traditionally compared with microbial ecosystem models, such as biomass (e.g., chlorophyll a) and nutrient concentrations. A grand challenge is to use these data to improve predictive models and use models to explain observed patterns. This article presents a framework that aligns observations and models along the dimension of abstraction or biological organization-from raw sequences to ecosystem patterns for observations, and from sequence simulators to ecological theory for models. It then reviews 16 studies that compared model results with molecular observations. Molecular data can and are being combined with microbial ecosystem models, but to keep up with and take advantage of the full scope of observations, models need to become more mechanistically detailed and complex, which is a technical and cultural challenge for the ecological modeling community.

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.

Comparing DNA, RNA and protein levels for measuring microbial dynamics in soil microcosms amended with nitrogen fertilizer

To what extent multi-omic techniques could reflect in situ microbial process rates remains unclear, especially for highly diverse habitats like soils. Here, we performed microcosm incubations using sandy soil from an agricultural site in Midwest USA. Microcosms amended with isotopically labeled ammonium and urea to simulate a fertilization event showed nitrification (up to 4.1 ± 0.87 µg N-NO3- g-1 dry soil d-1) and accumulation of N2O after 192 hours of incubation. Nitrification activity (NH4+ → NH2OH → NO → NO2- → NO3-) was accompanied by a 6-fold increase in relative expression of the 16S rRNA gene (RNA/DNA) between 10 and 192 hours of incubation for ammonia-oxidizing bacteria Nitrosomonas and Nitrosospira, unlike archaea and comammox bacteria, which showed stable gene expression. A strong relationship between nitrification activity and betaproteobacterial ammonia monooxygenase and nitrite oxidoreductase transcript abundances revealed that mRNA quantitatively reflected measured activity and was generally more sensitive than DNA under these conditions. Although peptides related to housekeeping proteins from nitrite-oxidizing microorganisms were detected, their abundance was not significantly correlated with activity, revealing that meta-proteomics provided only a qualitative assessment of activity. Altogether, these findings underscore the strengths and limitations of multi-omic approaches for assessing diverse microbial communities in soils and provide new insights into nitrification.

Microfluidic cultivation and analysis tools for interaction studies of microbial co-cultures

Microbial consortia are fascinating yet barely understood biological systems with an elusive intrinsic complexity. Studying microbial consortia and the interactions of their members is of major importance for the understanding, engineering and control of synthetic and natural microbial consortia. Microfluidic cultivation and analysis devices are versatile tools for the study of microbial interactions at the single-cell level. While there is a vast amount of literature on microfluidics for the investigation of monocultures only few studies on co-cultures have been conducted in this context. Here we give an overview of different microfluidic single-cell cultivation tools for the analysis of microbial consortia with a focus on their physiology, growth dynamics and cellular interactions. Finally, central challenges and perspectives for the future application of microfluidic tools for microbial consortia investigations will be given.

FRET-based fluorescent nanoprobe platform for sorting of active microorganisms by functional properties

Fluorescence-activated cell sorting (FACS) has rarely been applied to screening of microorganisms because of poor detection resolution, which is compromised by poor stability, toxicity, or interference from background fluorescence of the fluorescence sensors used. Here, a fluorescence-based rapid high-throughput cell sorting method was first developed using a fluorescence resonance energy transfer (FRET) fluorescent nanoprobe NP-RA, which was constructed by coating a silica nanoparticle with Rhodamine B and methyl-red (an azo dye). Rhodamine B (inner layer) is the FRET donor and methyl-red (outer layer) is the acceptor. This ready-to-use NP-RA is non-fluorescent, but fluoresces once the outer layer is degraded by microorganisms. In our experiment, NP-RA was ultrasensitive to model strain Shewanella decolorationis S12, showing a broad detection range from 8.0 cfu/mL to 8.7 × 10⁸ cfu/mL under confocal laser scanning microscopy, and from 1.1 × 10⁷ to 9.36 × 10⁸ cfu/mL under a fluorometer. In addition, NP-RA bioimaging can clearly identify other azo-respiring cells in the microbial community, including Bosea thiooxidans DSM 9653 and Lysinibacillus pakistanensis NCCP-54. Furthermore, the fluorescent probe NP-RA is compatible with downstream FACS so that azo-respiring cells can be rapidly sorted out directly from an artificial microbial community. To our knowledge, no fluorescent nanoprobe has yet been designed for tracking and sorting azo-respiration functional microorganisms.

Prokaryotic Community Structure and Metabolisms in Shallow Subsurface of Atacama Desert Playas and Alluvial Fans After Heavy Rains: Repairing and Preparing for Next Dry Period

The Atacama Desert, the oldest and driest desert on Earth, displays significant rains only once per decade. To investigate how microbial communities take advantage of these sporadic wet events, we carried out a geomicrobiological study a few days after a heavy rain event in 2015. Different physicochemical and microbial community analyses were conducted on samples collected from playas and an alluvial fan from surface, 10, 20, 50, and 80 cm depth. Gravimetric moisture content peaks were measured in 10 and 20 cm depth samples (from 1.65 to 4.1% w/w maximum values) while, in general, main anions such as chloride, nitrate, and sulfate concentrations increased with depth, with maximum values of 13-1,125; 168-10,109; and 9,904-30,952 ppm, respectively. Small organic anions such as formate and acetate had maximum concentrations from 2.61 to 3.44 ppm and 6.73 to 28.75 ppm, respectively. Microbial diversity inferred from DNA analysis showed Actinobacteria and Alphaproteobacteria as the most abundant and widespread bacterial taxa among the samples, followed by Chloroflexi and Firmicutes at specific sites. Archaea were mainly dominated by Nitrososphaerales, Methanobacteria, with the detection of other groups such as Halobacteria. Metaproteomics showed a high and even distribution of proteins involved in primary metabolic processes such as energy production and biosynthetic pathways, and a limited but remarkable presence of proteins related to resistance to environmental stressors such as radiation, oxidation, or desiccation. The results indicated that extra humidity in the system allows the microbial community to repair, and prepare for the upcoming hyperarid period. Additionally, it supplies biomarkers to the medium whose preservation potential could be high under strong desiccation conditions and relevant for planetary exploration.

Synthetic microbial consortia for biosynthesis and biodegradation: promises and challenges

Functional differentiation and metabolite exchange enable microbial consortia to perform complex metabolic tasks and efficiently cycle the nutrients. Inspired by the cooperative relationships in environmental microbial consortia, synthetic microbial consortia have great promise for studying the microbial interactions in nature and more importantly for various engineering applications. However, challenges coexist with promises, and the potential of consortium-based technologies is far from being fully harnessed. Thorough understanding of the underlying molecular mechanisms of microbial interactions is greatly needed for the rational design and optimization of defined consortia. These knowledge gaps could be potentially filled with the assistance of the ongoing revolution in systems biology and synthetic biology tools. As current fundamental and technical obstacles down the road being removed, we would expect new avenues with synthetic microbial consortia playing important roles in biological and environmental engineering processes such as bioproduction of desired chemicals and fuels, as well as biodegradation of persistent contaminants.

Challenges and promise at the interface of metaproteomics and genomics: an overview of recent progress in metaproteogenomic data analysis

INTRODUCTION

The study of microbial communities based on the combined analysis of genomic and proteomic data - called metaproteogenomics - has gained increased research attention in recent years. This relatively young field aims to elucidate the functional and taxonomic interplay of proteins in microbiomes and its implications on human health and the environment. Areas covered: This article reviews bioinformatics methods and software tools dedicated to the analysis of data from metaproteomics and metaproteogenomics experiments. In particular, it focuses on the creation of tailored protein sequence databases, on the optimal use of database search algorithms including methods of error rate estimation, and finally on taxonomic and functional annotation of peptide and protein identifications. Expert opinion: Recently, various promising strategies and software tools have been proposed for handling typical data analysis issues in metaproteomics. However, severe challenges remain that are highlighted and discussed in this article; these include: (i) robust false-positive assessment of peptide and protein identifications, (ii) complex protein inference against a background of highly redundant data, (iii) taxonomic and functional post-processing of identification data, and finally, (iv) the assessment and provision of metrics and tools for quantitative analysis.

Advances in the technologies for studying consortia of bacteria and cyanobacteria/microalgae in wastewaters

The excessive generation and discharge of wastewaters have been serious concerns worldwide in the recent past. From an environmental friendly perspective, bacteria, cyanobacteria and microalgae, and the consortia have been largely considered for biological treatment of wastewaters. For efficient use of bacteria‒cyanobacteria/microalgae consortia in wastewater treatment, detailed knowledge on their structure, behavior and interaction is essential. In this direction, specific analytical tools and techniques play a significant role in studying these consortia. This review presents a critical perspective on physical, biochemical and molecular techniques such as microscopy, flow cytometry with cell sorting, nanoSIMS and omics approaches used for systematic investigations of the structure and function, particularly nutrient removal potential of bacteria‒cyanobacteria/microalgae consortia. In particular, the use of specific molecular techniques of genomics, transcriptomics, proteomics metabolomics and genetic engineering to develop more stable consortia of bacteria and cyanobacteria/microalgae with their improved biotechnological capabilities in wastewater treatment has been highlighted.

Metaproteomic and 16S rRNA Gene Sequencing Analysis of the Infant Fecal Microbiome

A metaproteomic analysis was conducted on the fecal microbiome of eight infants to characterize global protein and pathway expression. Although mass spectrometry-based proteomics is now a routine tool, analysis of the microbiome presents specific technical challenges, including the complexity and dynamic range of member taxa, the need for well-annotated metagenomic databases, and high inter-protein sequence redundancy and similarity. In this study, an approach was developed for assessment of biological phenotype and metabolic status, as a functional complement to DNA sequence analysis. Fecal samples were prepared and analysed by tandem mass spectrometry and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. In total, 15,250 unique peptides were sequenced and assigned to 2154 metaclusters, which were then assigned to pathways and functional groups. Differences were noted in several pathways, consistent with the dominant genera observed in different subjects. Although this study was not powered to draw conclusions from the comparisons, the results obtained demonstrate the applicability of this approach and provide the methods needed for performing semi-quantitative comparisons of human fecal microbiome composition, physiology and metabolism, as well as a more detailed assessment of microbial composition in comparison to 16S rRNA gene sequencing.

More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics

Metaproteomics, the study of protein expression in microbial communities, is a versatile tool for environmental microbiology. Achieving sufficiently high metaproteome coverage to obtain a comprehensive picture of the activities and interactions in microbial communities is one of the current challenges in metaproteomics. An essential step to maximize the number of identified proteins is peptide separation via liquid chromatography (LC) prior to mass spectrometry (MS). Thorough optimization and comparison of LC methods for metaproteomics are, however, currently lacking. Here, we present an extensive development and test of different 1D and 2D-LC approaches for metaproteomic peptide separations. We used fully characterized mock community samples to evaluate metaproteomic approaches with very long analytical columns (50 and 75 cm) and long gradients (up to 12 h). We assessed a total of over 20 different 1D and 2D-LC approaches in terms of number of protein groups and unique peptides identified, peptide spectrum matches (PSMs) generated, the ability to detect proteins of low-abundance species, the effect of technical replicate runs on protein identifications and method reproducibility. We show here that, while 1D-LC approaches are faster and easier to set up and lead to more identifications per minute of runtime, 2D-LC approaches allow for a higher overall number of identifications with up to >10,000 protein groups identified. We also compared the 1D and 2D-LC approaches to a standard GeLC workflow, in which proteins are pre-fractionated via gel electrophoresis. This method yielded results comparable to the 2D-LC approaches, however with the drawback of a much increased sample preparation time. Based on our results, we provide recommendations on how to choose the best LC approach for metaproteomics experiments, depending on the study aims.

Protein Stability Determination (PSD): A Tool for Proteomics Analysis

Background:

Protein Stability Determination (PSD) is a sequence-based bioinformatics tool which was developed by utilizing a large input of datasets of protein sequences in FASTA format. The PSD can be used to analyze the meta-proteomics data which will help to predict and design thermozyme and mesozyme for academic and industrial purposes. The PSD also can be utilized to analyze the protein sequence and to predict whether it will be stable in thermophilic or in the mesophilic environment. </P><P> Method and Results: This tool which is supported by any operating system is designed in Java and it provides a user-friendly graphical interface. It is a simple programme and can predict the thermostability nature of proteins with >90% accuracy. The PSD can also predict the nature of constituent amino acids i.e. acidic or basic and polar or nonpolar etc.

Conclusion:

PSD is highly capable to determine the thermostability status of a protein of hypothetical or unknown peptides as well as meta-proteomics data from any established database. The utilities of the PSD driven analyses include predictions on the functional assignment to a protein. The PSD also helps in designing peptides having flexible combinations of amino acids for functional stability. PSD is freely available at https://sourceforge.net/projects/protein-sequence-determination.

Enzymes in removal of pharmaceuticals from wastewater: A critical review of challenges, applications and screening methods for their selection

At present, the removal of trace organic chemicals such as pharmaceuticals in wastewater treatment plants is often incomplete resulting in a continuous discharge into the aqueous environment. To overcome this issue, bioremediation approaches gained significant importance in recent times, since they might have a lower carbon footprint than chemical or physical treatment methods. In this context, enzyme-based technologies represent a promising alternative since they are able to specifically target certain chemicals. For this purpose, versatile monitoring of enzymatic reactions is of great importance in order to understand underlying transformation mechanisms and estimate the suitability of various enzymes exhibiting different specificities for bioremediation purposes. This study provides a comprehensive review, summarizing research on enzymatic transformation of pharmaceuticals in water treatment applications using traditional and state-of-the-art enzyme screening approaches with a special focus on mass spectrometry (MS)-based and high-throughput tools. MS-based enzyme screening represents an approach that allows a comprehensive mechanistic understanding of enzymatic reactions and, in particular, the identification of transformation products. A critical discussion of these approaches for implementation in wastewater treatment processes is also presented. So far, there are still major gaps between laboratory- and field-scale research that need to be overcome in order to assess the viability for real applications.

Understanding and Designing the Strategies for the Microbe-Mediated Remediation of Environmental Contaminants Using Omics Approaches

Rapid industrialization and population explosion has resulted in the generation and dumping of various contaminants into the environment. These harmful compounds deteriorate the human health as well as the surrounding environments. Current research aims to harness and enhance the natural ability of different microbes to metabolize these toxic compounds. Microbial-mediated bioremediation offers great potential to reinstate the contaminated environments in an ecologically acceptable approach. However, the lack of the knowledge regarding the factors controlling and regulating the growth, metabolism, and dynamics of diverse microbial communities in the contaminated environments often limits its execution. In recent years the importance of advanced tools such as genomics, proteomics, transcriptomics, metabolomics, and fluxomics has increased to design the strategies to treat these contaminants in ecofriendly manner. Previously researchers has largely focused on the environmental remediation using single omics-approach, however the present review specifically addresses the integrative role of the multi-omics approaches in microbial-mediated bioremediation. Additionally, we discussed how the multi-omics approaches help to comprehend and explore the structural and functional aspects of the microbial consortia in response to the different environmental pollutants and presented some success stories by using these approaches.

Biomarkers for monitoring intestinal health in poultry: present status and future perspectives

Intestinal health is determined by host (immunity, mucosal barrier), nutritional, microbial and environmental factors. Deficiencies in intestinal health are associated with shifts in the composition of the intestinal microbiome (dysbiosis), leakage of the mucosal barrier and/or inflammation. Since the ban on growth promoting antimicrobials in animal feed, these dysbiosis-related problems have become a major issue, especially in intensive animal farming. The economical and animal welfare consequences are considerable. Consequently, there is a need for continuous monitoring of the intestinal health status, particularly in intensively reared animals, where the intestinal function is often pushed to the limit. In the current review, the recent advances in the field of intestinal health biomarkers, both in human and veterinary medicine are discussed, trying to identify present and future markers of intestinal health in poultry. The most promising new biomarkers will be stable molecules ending up in the feces and litter that can be quantified, preferably using rapid and simple pen-side tests. It is unlikely, however, that a single biomarker will be sufficient to follow up all aspects of intestinal health. Combinations of multiple biomarkers and/or metabarcoding, metagenomic, metatranscriptomic, metaproteomic and metabolomic approaches will be the way to go in the future. Candidate biomarkers currently are being investigated by many research groups, but the validation will be a major challenge, due to the complexity of intestinal health in the field.

Proteomic studies on lactic acid bacteria: A review

Probiotics are amongst the most common microbes in the gastro-intestinal tract of humans and other animals. Prominent among probiotics are Lactobacillus and Bifidobacterium. They offer wide-ranging health promoting benefits to the host which include reduction in pathological alterations, stimulation of mucosal immunity and interaction with mediators of inflammation among others. Proteomics plays a vital role in understanding biological functions of a cell. Proteomics is also slowly and steadily adding to the existing knowledge on role of probiotics. In this paper, the proteomics of probiotics, with special reference to lactic acid bacteria is reviewed with a view to understand i) proteome map, ii) mechanism of adaptation to harsh gut environment such as low pH and bile acid, iii) role of cell surface proteins in adhering to intestinal epithelial cells, and iv) as a tool to answer basic cell functions. We have also reviewed various analytical methods used to carry out proteome analysis, in which 2D-MS and LC-MS/MS approaches were found to be versatile methods to perform high-throughput sample analyses even for a complex gut samples. Further, we present future road map of understanding gut microbes combining meta-proteomics, meta-genomics, meta-transcriptomics and -metabolomics.

Harnessing the Power of PCR Molecular Fingerprinting Methods and Next Generation Sequencing for Understanding Structure and Function in Microbial Communities

Polymerase chain reaction (PCR) is central to methods in molecular ecology. Here, we describe PCR-dependent approaches useful for investigating microbial diversity and its function in various natural, human-associated, and built environment ecosystems. Protocols routinely used for DNA extraction, purification, cloning, and sequencing are included along with various resources for the statistical analysis following gel electrophoresis-based methods (DGGE) and sequencing. We also provide insights into eukaryotic microbiome analysis, sample preservation techniques, PCR troubleshooting, DNA quantification methods, and commonly used ordination techniques.

MPA Portable: A Stand-Alone Software Package for Analyzing Metaproteome Samples on the Go

Metaproteomics, the mass spectrometry-based analysis of proteins from multispecies samples faces severe challenges concerning data analysis and results interpretation. To overcome these shortcomings, we here introduce the MetaProteomeAnalyzer (MPA) Portable software. In contrast to the original server-based MPA application, this newly developed tool no longer requires computational expertise for installation and is now independent of any relational database system. In addition, MPA Portable now supports state-of-the-art database search engines and a convenient command line interface for high-performance data processing tasks. While search engine results can easily be combined to increase the protein identification yield, an additional two-step workflow is implemented to provide sufficient analysis resolution for further postprocessing steps, such as protein grouping as well as taxonomic and functional annotation. Our new application has been developed with a focus on intuitive usability, adherence to data standards, and adaptation to Web-based workflow platforms. The open source software package can be found at https://github.com/compomics/meta-proteome-analyzer.

A meta-proteomics approach to study the interspecies interactions affecting microbial biofilm development in a model community

Microbial biofilms are omnipresent in nature and relevant to a broad spectrum of industries ranging from bioremediation and food production to biomedical applications. To date little is understood about how multi-species biofilm communities develop and function on a molecular level, due to the complexity of these biological systems. Here we apply a meta-proteomics approach to investigate the mechanisms influencing biofilm formation in a model consortium of four bacterial soil isolates; Stenotrophomonas rhizophila, Xanthomonas retroflexus, Microbacterium oxydans and Paenibacillus amylolyticus. Protein abundances in community and single species biofilms were compared to describe occurring inter-species interactions and the resulting changes in active metabolic pathways. To obtain full taxonomic resolution between closely related species and empower correct protein quantification, we developed a novel pipeline for generating reduced reference proteomes for spectral database searches. Meta-proteomics profiling indicated that community development is dependent on cooperative interactions between community members facilitating cross-feeding on specific amino acids. Opposite regulation patterns of fermentation and nitrogen pathways in Paenibacillus amylolyticus and Xanthomonas retroflexus may, however, indicate that competition for limited resources also affects community development. Overall our results demonstrate the multitude of pathways involved in biofilm formation in mixed communities.

Differences in protein expression among five species of stream stonefly (Plecoptera) along a latitudinal gradient in Japan

Proteome variation among natural populations along an environmental gradient may provide insights into how the biological functions of species are related to their local adaptation. We investigated protein expression in five stream stonefly species from four geographic regions along a latitudinal gradient in Japan with varying climatic conditions. The extracted proteins were separated by two-dimensional gel electrophoresis and identified by matrix-assisted laser desorption/ionization of time-of-flight (MALDI TOF/TOF), yielding 446 proteins. Low interspecies variation in the proteome profiles was observed among five species within geographical regions, presumably due to the co-occurring species sharing the environments. However, large spatial variations in protein expression were found among four geographic regions, suggesting strong regulation of protein expression in heterogeneous environments, where the spatial variations were positively correlated with water temperature. We identified 21 unique proteins expressed specifically in a geographical region and six common proteins expressed throughout all regions. In warmer regions, metabolic proteins were upregulated, whereas proteins related to cold stress, the photoperiod, and mating were downregulated. Oxygen-related and energy-production proteins were upregulated in colder regions with higher altitudes. Thus, our proteomic approach is useful for identifying and understanding important biological functions related to local adaptations by populations of stoneflies.

Effects of salinity on the performance, microbial community, and functional proteins in an aerobic granular sludge system

The response mechanism of aerobic granular sludge (AGS) systems to salt stress in high-salinity wastewater treatment processes has not been fully elucidated in current studies. The aim of this study was to reveal the comprehensive effects of salinity on AGS characteristics using microbial community and metaproteomics analyses. The results showed that the removal efficiency of COD, TN and TP decreased significantly with increasing salinity. Under salt stress, the Na⁺ content in AGS decreased, while the K⁺ and Ca²⁺ contents increased. This was because the salt-tolerant mechanism of the microorganisms was dependent on the uptake of K⁺ and ejection of Na⁺via K⁺/Na⁺ pumps, Na⁺/H⁺ reversed transport proteins, and K⁺ channels. Compared with the salt-free condition, 14 of 25 different protein spots were identified successfully by metaproteomic analysis, including porin, periplasmic-binding protein, and ATP-binding cassette-type for phosphonate transporter, which were expressed mainly by members of γ-Proteobacteria and α-Proteobacteria. The variations in functional proteins and microbial community revealed that α- and γ-Proteobacteria had disproportionally active and the metabolic activity of β-Proteobacteria was inhibited by increasing salinity. Additionally, Psychrobacter sp. was confirmed to be a predominant bacterium at 15 g/L NaCl, as the porin was strongly expressed.

Schrödinger's microbes: Tools for distinguishing the living from the dead in microbial ecosystems

While often obvious for macroscopic organisms, determining whether a microbe is dead or alive is fraught with complications. Fields such as microbial ecology, environmental health, and medical microbiology each determine how best to assess which members of the microbial community are alive, according to their respective scientific and/or regulatory needs. Many of these fields have gone from studying communities on a bulk level to the fine-scale resolution of microbial populations within consortia. For example, advances in nucleic acid sequencing technologies and downstream bioinformatic analyses have allowed for high-resolution insight into microbial community composition and metabolic potential, yet we know very little about whether such community DNA sequences represent viable microorganisms. In this review, we describe a number of techniques, from microscopy- to molecular-based, that have been used to test for viability (live/dead determination) and/or activity in various contexts, including newer techniques that are compatible with or complementary to downstream nucleic acid sequencing. We describe the compatibility of these viability assessments with high-throughput quantification techniques, including flow cytometry and quantitative PCR (qPCR). Although bacterial viability-linked community characterizations are now feasible in many environments and thus are the focus of this critical review, further methods development is needed for complex environmental samples and to more fully capture the diversity of microbes (e.g., eukaryotic microbes and viruses) and metabolic states (e.g., spores) of microbes in natural environments.

Potential and active functions in the gut microbiota of a healthy human cohort

BACKGROUND

The study of the gut microbiota (GM) is rapidly moving towards its functional characterization by means of shotgun meta-omics. In this context, there is still no consensus on which microbial functions are consistently and constitutively expressed in the human gut in physiological conditions. Here, we selected a cohort of 15 healthy subjects from a native and highly monitored Sardinian population and analyzed their GMs using shotgun metaproteomics, with the aim of investigating GM functions actually expressed in a healthy human population. In addition, shotgun metagenomics was employed to reveal GM functional potential and to compare metagenome and metaproteome profiles in a combined taxonomic and functional fashion.

RESULTS

Metagenomic and metaproteomic data concerning the taxonomic structure of the GM under study were globally comparable. On the contrary, a considerable divergence between genetic potential and functional activity of the human healthy GM was observed, with the metaproteome displaying a higher plasticity, compared to the lower inter-individual variability of metagenome profiles. The taxon-specific contribution to functional activities and metabolic tasks was also examined, giving insights into the peculiar role of several GM members in carbohydrate metabolism (including polysaccharide degradation, glycan transport, glycolysis, and short-chain fatty acid production). Noteworthy, Firmicutes-driven butyrogenesis (mainly due to Faecalibacterium spp.) was shown to be the metabolic activity with the highest expression rate and the lowest inter-individual variability in the study cohort, in line with the previously reported importance of the biosynthesis of this microbial product for the gut homeostasis.

CONCLUSIONS

Our results provide detailed and taxon-specific information regarding functions and pathways actively working in a healthy GM. The reported discrepancy between expressed functions and functional potential suggests that caution should be used before drawing functional conclusions from metagenomic data, further supporting metaproteomics as a fundamental approach to characterize the human GM metabolic functions and activities.

Comparative Omics and Trait Analyses of Marine Pseudoalteromonas Phages Advance the Phage OTU Concept

Viruses influence the ecology and evolutionary trajectory of microbial communities. Yet our understanding of their roles in ecosystems is limited by the paucity of model systems available for hypothesis generation and testing. Further, virology is limited by the lack of a broadly accepted conceptual framework to classify viral diversity into evolutionary and ecologically cohesive units. Here, we introduce genomes, structural proteomes, and quantitative host range data for eight Pseudoalteromonas phages isolated from Helgoland (North Sea, Germany) and use these data to advance a genome-based viral operational taxonomic unit (OTU) definition. These viruses represent five new genera and inform 498 unaffiliated or unannotated protein clusters (PCs) from global virus metagenomes. In a comparison of previously sequenced Pseudoalteromonas phage isolates (n = 7) and predicted prophages (n = 31), the eight phages are unique. They share a genus with only one other isolate, Pseudoalteromonas podophage RIO-1 (East Sea, South Korea) and two Pseudoalteromonas prophages. Mass-spectrometry of purified viral particles identified 12–20 structural proteins per phage. When combined with 3-D structural predictions, these data led to the functional characterization of five previously unidentified major capsid proteins. Protein functional predictions revealed mechanisms for hijacking host metabolism and resources. Further, they uncovered a hybrid sipho-myovirus that encodes genes for Mu-like infection rarely described in ocean systems. Finally, we used these data to evaluate a recently introduced definition for virus populations that requires members of the same population to have >95% average nucleotide identity across at least 80% of their genes. Using physiological traits and genomics, we proposed a conceptual model for a viral OTU definition that captures evolutionarily cohesive and ecologically distinct units. In this trait-based framework, sensitive hosts are considered viral niches, while host ranges and infection efficiencies are tracked as viral traits. Quantitative host range assays revealed conserved traits within virus OTUs that break down between OTUs, suggesting the defined units capture niche and fitness differentiation. Together these analyses provide a foundation for model system-based hypothesis testing that will improve our understanding of marine copiotrophs, as well as phage–host interactions on the ocean particles and aggregates where Pseudoalteromonas thrive.

Linking Genes to Microbial Biogeochemical Cycling: Lessons from Arsenic

The biotransformation of arsenic is highly relevant to the arsenic biogeochemical cycle. Identification of the molecular details of microbial pathways of arsenic biotransformation coupled with analyses of microbial communities by meta-omics can provide insights into detailed aspects of the complexities of this biocycle. Arsenic transformations couple to other biogeochemical cycles, and to the fate of both nutrients and other toxic environmental contaminants. Microbial redox metabolism of iron, carbon, sulfur, and nitrogen affects the redox and bioavailability of arsenic species. In this critical review we illustrate the biogeochemical processes and genes involved in arsenic biotransformations. We discuss how current and future metagenomic-, metatranscriptomic-, metaproteomic-, and metabolomic-based methods will help to decipher individual microbial arsenic transformation processes, and their connections to other biogeochemical cycle. These insights will allow future use of microbial metabolic capabilities for new biotechnological solutions to environmental problems. To understand the complex nature of inorganic and organic arsenic species and the fate of environmental arsenic will require integrating systematic approaches with biogeochemical modeling. Finally, from the lessons learned from these studies of arsenic biogeochemistry, we will be able to predict how the environment changes arsenic, and, in response, how arsenic biotransformations change the environment.

Proteomics progresses in microbial physiology and clinical antimicrobial therapy

Clinical microbial identification plays an important role in optimizing the management of infectious diseases and provides diagnostic and therapeutic support for clinical management. Microbial proteomic research is aimed at identifying proteins associated with microbial activity, which has facilitated the discovery of microbial physiology changes and host–pathogen interactions during bacterial infection and antimicrobial therapy. Here, we summarize proteomic-driven progresses of host–microbial pathogen interactions at multiple levels, mass spectrometry-based microbial proteome identification for clinical diagnosis, and antimicrobial therapy. Proteomic technique progresses pave new ways towards effective prevention and drug discovery for microbial-induced infectious diseases.

An introduction to microbiome analysis for human biology applications

Research examining the gut microbiota is currently exploding, and results are providing new perspectives on human biology. Factors such as host diet and physiology influence the composition and function of the gut microbiota, which in turn affects human nutrition, health, and behavior via interactions with metabolism, the immune system, and the brain. These findings represent an exciting new twist on familiar topics, and as a result, gut microbiome research is likely to provide insight into unresolved biological mechanisms driving human health. However, much remains to be learned about the broader ecological and evolutionary contexts within which gut microbes and humans are affecting each other. Here, I outline the procedures for generating data describing the gut microbiota with the goal of facilitating the wider integration of microbiome analyses into studies of human biology. I describe the steps involved in sample collection, DNA extraction, PCR amplification, high-throughput sequencing, and bioinformatics. While this review serves only as an introduction to these topics, it provides sufficient resources for researchers interested in launching new microbiome initiatives. As knowledge of these methods spreads, microbiome analysis should become a standard tool in the arsenal of human biology research.

Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks

Peptide and protein identification remains challenging in organisms with poorly annotated or rapidly evolving genomes, as are commonly encountered in environmental or biofuels research. Such limitations render tandem mass spectrometry (MS/MS) database search algorithms ineffective as they lack corresponding sequences required for peptide-spectrum matching. We address this challenge with the spectral networks approach to (1) match spectra of orthologous peptides across multiple related species and then (2) propagate peptide annotations from identified to unidentified spectra. We here present algorithms to assess the statistical significance of spectral alignments (Align-GF), reduce the impurity in spectral networks, and accurately estimate the error rate in propagated identifications. Analyzing three related Cyanothece species, a model organism for biohydrogen production, spectral networks identified peptides from highly divergent sequences from networks with dozens of variant peptides, including thousands of peptides in species lacking a sequenced genome. Our analysis further detected the presence of many novel putative peptides even in genomically characterized species, thus suggesting the possibility of gaps in our understanding of their proteomic and genomic expression. A web-based pipeline for spectral networks analysis is available at http://proteomics.ucsd.edu/software.

Environmental Microbial Community Proteomics: Status, Challenges and Perspectives

Microbial community proteomics, also termed metaproteomics, is an emerging field within the area of microbiology, which studies the entire protein complement recovered directly from a complex environmental microbial community at a given point in time. Although it is still in its infancy, microbial community proteomics has shown its powerful potential in exploring microbial diversity, metabolic potential, ecological function and microbe-environment interactions. In this paper, we review recent advances achieved in microbial community proteomics conducted in diverse environments, such as marine and freshwater, sediment and soil, activated sludge, acid mine drainage biofilms and symbiotic communities. The challenges facing microbial community proteomics are also discussed, and we believe that microbial community proteomics will greatly enhance our understanding of the microbial world and its interactions with the environment.