Environmental genomics, the big picture?

ChipFilter: Microfluidic-Based Comprehensive Sample Preparation Methodology for Microbial Consortia

The metaproteomic approach is an attractive way to describe a microbiome at the functional level, allowing the identification and quantification of proteins across a broad dynamic range as well as the detection of post-translational modifications. However, it remains relatively underutilized, mainly due to technical challenges that should be addressed, including the complexity of extracting proteins from heterogeneous microbial communities. Here, we show that a ChipFilter microfluidic device coupled to a liquid chromatography tandem mass spectrometry (LC-MS/MS) setup can be successfully used for the identification of microbial proteins. Using cultures of Escherichia coli, Bacillus subtilis, and Saccharomyces cerevisiae, we have shown that it is possible to directly lyse the cells and digest the proteins in the ChipFilter to allow the identification of a higher number of proteins and peptides than that by standard protocols, even at low cell density. The peptides produced are overall longer after ChipFilter digestion but show no change in their degree of hydrophobicity. Analysis of a more complex mixture of 17 species from the gut microbiome showed that the ChipFilter preparation was able to identify and estimate the amounts of 16 of these species. These results show that ChipFilter can be used for the proteomic study of microbiomes, particularly in the case of a low volume or cell density. The mass spectrometry data have been deposited on the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifier PXD039581.

Increasing taxonomic and functional characterization of host-microbiome interactions by DIA-PASEF metaproteomics

Introduction

Metaproteomics is a rapidly advancing field that offers unique insights into the taxonomic composition and the functional activity of microbial communities, and their effects on host physiology. Classically, data-dependent acquisition (DDA) mass spectrometry (MS) has been applied for peptide identification and quantification in metaproteomics. However, DDA-MS exhibits well-known limitations in terms of depth, sensitivity, and reproducibility. Consequently, methodological improvements are required to better characterize the protein landscape of microbiomes and their interactions with the host.

Methods

We present an optimized proteomic workflow that utilizes the information captured by Parallel Accumulation-Serial Fragmentation (PASEF) MS for comprehensive metaproteomic studies in complex fecal samples of mice.

Results and discussion

We show that implementing PASEF using a DDA acquisition scheme (DDA-PASEF) increased peptide quantification up to 5 times and reached higher accuracy and reproducibility compared to previously published classical DDA and data-independent acquisition (DIA) methods. Furthermore, we demonstrate that the combination of DIA, PASEF, and neuronal-network-based data analysis, was superior to DDA-PASEF in all mentioned parameters. Importantly, DIA-PASEF expanded the dynamic range towards low-abundant proteins and it doubled the quantification of proteins with unknown or uncharacterized functions. Compared to previous classical DDA metaproteomic studies, DIA-PASEF resulted in the quantification of up to 4 times more taxonomic units using 16 times less injected peptides and 4 times shorter chromatography gradients. Moreover, 131 additional functional pathways distributed across more and even uniquely identified taxa were profiled as revealed by a peptide-centric taxonomic-functional analysis. We tested our workflow on a validated preclinical mouse model of neuropathic pain to assess longitudinal changes in host-gut microbiome interactions associated with pain - an unexplored topic for metaproteomics. We uncovered the significant enrichment of two bacterial classes upon pain, and, in addition, the upregulation of metabolic activities previously linked to chronic pain as well as various hitherto unknown ones. Furthermore, our data revealed pain-associated dynamics of proteome complexes implicated in the crosstalk between the host immune system and the gut microbiome. In conclusion, the DIA-PASEF metaproteomic workflow presented here provides a stepping stone towards a deeper understanding of microbial ecosystems across the breadth of biomedical and biotechnological fields.

Applications of multi-omics techniques to unravel the fermentation process and the flavor formation mechanism in fermented foods

Fermented foods are important components of the human diet. There is increasing awareness of abundant nutritional and functional properties present in fermented foods that arise from the transformation of substrates by microbial communities. Thus, it is significant to unravel the microbial communities and mechanisms of characteristic flavor formation occurring during fermentation. There has been rapid development of high-throughput and other omics technologies, such as metaproteomics and metabolomics, and as a result, there is growing recognition of the importance of integrating these approaches. The successful applications of multi-omics approaches and bioinformatics analyses have provided a solid foundation for exploring the fermentation process. Compared with single-omics, multi-omics analyses more accurately delineate microbial and molecular features, thus they are more apt to reveal the mechanisms of fermentation. This review introduces fermented foods and an overview of single-omics technologies - including metagenomics, metatranscriptomics, metaproteomics, and metabolomics. We also discuss integrated multi-omics and bioinformatic analyses and their role in recent research progress related to fermented foods, as well as summarize the main potential pathways involved in certain fermented foods. In the future, multilayered analyses of multi-omics data should be conducted to enable better understanding of flavor formation mechanisms in fermented foods.

Unlocking the microbial studies through computational approaches: how far have we reached?

The metagenomics approach accelerated the study of genetic information from uncultured microbes and complex microbial communities. In silico research also facilitated an understanding of protein-DNA interactions, protein-protein interactions, docking between proteins and phyto/biochemicals for drug design, and modeling of the 3D structure of proteins. These in silico approaches provided insight into analyzing pathogenic and nonpathogenic strains that helped in the identification of probable genes for vaccines and antimicrobial agents and comparing whole-genome sequences to microbial evolution. Artificial intelligence, more precisely machine learning (ML) and deep learning (DL), has proven to be a promising approach in the field of microbiology to handle, analyze, and utilize large data that are generated through nucleic acid sequencing and proteomics. This enabled the understanding of the functional and taxonomic diversity of microorganisms. ML and DL have been used in the prediction and forecasting of diseases and applied to trace environmental contaminants and environmental quality. This review presents an in-depth analysis of the recent application of silico approaches in microbial genomics, proteomics, functional diversity, vaccine development, and drug design.

Impact of different oral treatments on the composition of the supragingival plaque microbiome

Background

Dental plaque consists of a diverse microbial community embedded in a complex structure of exopolysaccharides. Dental biofilms form a natural barrier against pathogens but lead to oral diseases in a dysbiotic state.

Objective

Using a metaproteome approach combined with a standard plaque-regrowth study, this pilot study examined the impact of different concentrations of lactoperoxidase (LPO) on early plaque formation, and active biological processes.

Design

Sixteen orally healthy subjects received four local treatments as a randomized single-blind study based on a cross-over design. Two lozenges containing components of the LPO-system in different concentrations were compared to a placebo and Listerine®. The newly formed dental plaque was analyzed by mass spectrometry (nLC-MS/MS). 

Results

On average 1,916 metaproteins per sample were identified, which could be assigned to 116 genera and 1,316 protein functions. Listerine® reduced the number of metaproteins and their relative abundance, confirming the plaque inhibiting effect. The LPO-lozenges triggered mainly higher metaprotein abundances of early and secondary colonizers as well as bacteria associated with dental health but also periodontitis. Functional information indicated plaque biofilm growth.

Conclusion

In conclusion, the mechanisms on plaque biofilm formation of Listerine® and the LPO-system containing lozenges are different. In contrast to Listerine®, the lozenges led to a higher bacterial diversity.

Sulfamethoxazole Enhances Specific Enzymatic Activities under Aerobic Heterotrophic Conditions: A Metaproteomic Approach

The growing concern about antibiotic-resistant microorganisms has focused on the sludge from wastewater treatment plants (WWTPs) as a potential hotspot for their development and spread. To this end, it seems relevant to analyze the changes on the microbiota as a consequence of the antibiotics that wastewater may contain. This study aims at determining whether the presence of sulfamethoxazole (SMX), even in relatively low concentrations, modifies the microbial activities and the enzymatic expression of an activated sludge under aerobic heterotrophic conditions. For that purpose, we applied a metaproteomic approach in combination with genomic and transformation product analyses. SMX was biotransformed, and the metabolite 2,4(1H,3H)-pteridinedione-SMX (PtO-SMX) from the pterin-conjugation pathway was detected at all concentrations tested. Metaproteomics showed that SMX at 50-2000 μg/L slightly affected the microbial community structure, which was confirmed by DNA metabarcoding. Interestingly, an enhanced activity of the genus Corynebacterium and specifically of five enzymes involved in its central carbon metabolism was found at increased SMX concentrations. Our results suggest a role of Corynebacterium genus on SMX risks mitigation in our bioreactors.

Clinical Translation of Microbiome Research in Alopecia Areata: A New Perspective?

The continuous research advances in the microbiome field is changing clinicians’ points of view about the involvement of the microbiome in human health and disease, including autoimmune diseases such as alopecia areata (AA). Both gut and cutaneous dysbiosis have been considered to play roles in alopecia areata. A new approach is currently possible owing also to the use of omic techniques for studying the role of the microbiome in the disease by the deep understanding of microorganisms involved in the dysbiosis as well as of the pathways involved. These findings suggest the possibility to adopt a topical approach using either cosmetics or medical devices, to modulate or control, for example, the growth of overexpressed species using specific bacteriocins or postbiotics or with pH control. This will favour at the same time the growth of beneficial bacteria which, in turn, can impact positively both the structure of the scalp ecosystem on the host’s response to internal and external offenders. This approach, together with a “systemic” one, via oral supplementation, diet, or faecal transplantation, makes a reliable translation of microbiome research in clinical practice and should be taken into consideration every time alopecia areata is considered by a clinician.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Unipept Desktop: A Faster, More Powerful Metaproteomics Results Analysis Tool

Metaproteomics has become an important research tool to study microbial systems, which has resulted in increased metaproteomics data generation. However, efficient tools for processing the acquired data have lagged behind. One widely used tool for metaproteomics data interpretation is Unipept, a web-based tool that provides, among others, interactive and insightful visualizations. Due to its web-based implementation, however, the Unipept web application is limited in the amount of data that can be analyzed. In this manuscript we therefore present Unipept Desktop, a desktop application version of Unipept that is designed to drastically increase the throughput and capacity of metaproteomics data analysis. Moreover, it provides a novel comparative analysis pipeline and improves the organization of experimental data into projects, thus addressing the growing need for more efficient and versatile analysis tools for metaproteomics data.

New Frontiers of Anaerobic Hydrocarbon Biodegradation in the Multi-Omics Era

The accumulation of petroleum hydrocarbons in the environment substantially endangers terrestrial and aquatic ecosystems. Many microbial strains have been recognized to utilize aliphatic and aromatic hydrocarbons under aerobic conditions. Nevertheless, most of these pollutants are transferred by natural processes, including rain, into the underground anaerobic zones where their degradation is much more problematic. In oxic zones, anaerobic microenvironments can be formed as a consequence of the intensive respiratory activities of (facultative) aerobic microbes. Even though aerobic bioremediation has been well-characterized over the past few decades, ample research is yet to be done in the field of anaerobic hydrocarbon biodegradation. With the emergence of high-throughput techniques, known as omics (e.g., genomics and metagenomics), the individual biodegraders, hydrocarbon-degrading microbial communities and metabolic pathways, interactions can be described at a contaminated site. Omics approaches provide the opportunity to examine single microorganisms or microbial communities at the system level and elucidate the metabolic networks, interspecies interactions during hydrocarbon mineralization. Metatranscriptomics and metaproteomics, for example, can shed light on the active genes and proteins and functional importance of the less abundant species. Moreover, novel unculturable hydrocarbon-degrading strains and enzymes can be discovered and fit into the metabolic networks of the community. Our objective is to review the anaerobic hydrocarbon biodegradation processes, the most important hydrocarbon degraders and their diverse metabolic pathways, including the use of various terminal electron acceptors and various electron transfer processes. The review primarily focuses on the achievements obtained by the current high-throughput (multi-omics) techniques which opened new perspectives in understanding the processes at the system level including the metabolic routes of individual strains, metabolic/electric interaction of the members of microbial communities. Based on the multi-omics techniques, novel metabolic blocks can be designed and used for the construction of microbial strains/consortia for efficient removal of hydrocarbons in anaerobic zones.

Metaproteomics insights into traditional fermented foods and beverages

Traditional fermented foods and beverages (TFFB) are important dietary components. Multi-omics techniques have been applied to all aspects of TFFB research to clarify the composition and nutritional value of TFFB, and to reveal the microbial community, microbial interactions, fermentative kinetics, and metabolic profiles during the fermentation process of TFFB. Because of the advantages of metaproteomics in providing functional information, this technology has increasingly been used in research to assess the functional diversity of microbial communities. Metaproteomics is gradually gaining attention in the field of TFFB research because it can reveal the nature of microorganism function at the protein level. This paper reviews the common methods of metaproteomics applied in TFFB research; systematically summarizes the results of metaproteomics research on TFFB, such as sauces, wines, fermented tea, cheese, and fermented fish; and compares the differences in conclusions reached through metaproteomics versus other omics methods. Metaproteomics has great advantages in revealing the microbial functions in TFFB and the interaction between the materials and microbial community. In the future, metaproteomics should be further applied to the study of functional protein markers and protein interaction in TFFB; multi-omics technology requires further integration to reveal the molecular nature of TFFB fermentation.

Correlation and association analyses in microbiome study integrating multiomics in health and disease

Correlation and association analyses are one of the most widely used statistical methods in research fields, including microbiome and integrative multiomics studies. Correlation and association have two implications: dependence and co-occurrence. Microbiome data are structured as phylogenetic tree and have several unique characteristics, including high dimensionality, compositionality, sparsity with excess zeros, and heterogeneity. These unique characteristics cause several statistical issues when analyzing microbiome data and integrating multiomics data, such as large p and small n, dependency, overdispersion, and zero-inflation. In microbiome research, on the one hand, classic correlation and association methods are still applied in real studies and used for the development of new methods; on the other hand, new methods have been developed to target statistical issues arising from unique characteristics of microbiome data. Here, we first provide a comprehensive view of classic and newly developed univariate correlation and association-based methods. We discuss the appropriateness and limitations of using classic methods and demonstrate how the newly developed methods mitigate the issues of microbiome data. Second, we emphasize that concepts of correlation and association analyses have been shifted by introducing network analysis, microbe-metabolite interactions, functional analysis, etc. Third, we introduce multivariate correlation and association-based methods, which are organized by the categories of exploratory, interpretive, and discriminatory analyses and classification methods. Fourth, we focus on the hypothesis testing of univariate and multivariate regression-based association methods, including alpha and beta diversities-based, count-based, and relative abundance (or compositional)-based association analyses. We demonstrate the characteristics and limitations of each approaches. Fifth, we introduce two specific microbiome-based methods: phylogenetic tree-based association analysis and testing for survival outcomes. Sixth, we provide an overall view of longitudinal methods in analysis of microbiome and omics data, which cover standard, static, regression-based time series methods, principal trend analysis, and newly developed univariate overdispersed and zero-inflated as well as multivariate distance/kernel-based longitudinal models. Finally, we comment on current association analysis and future direction of association analysis in microbiome and multiomics studies.

Perspective and Guidelines for Metaproteomics in Microbiome Studies

The microbiome is emerging as a prominent factor affecting human health, and its dysbiosis is associated with various diseases. Compositional profiling of microbiome is increasingly being supplemented with functional characterization. Metaproteomics is intrinsically focused on functional changes and therefore will be an important tool in those studies of the human microbiome. In the past decade, development of new experimental and bioinformatic approaches for metaproteomics has enabled large-scale human metaproteomic studies. However, challenges still exist, and there remains a lack of standardizations and guidelines for properly performing metaproteomic studies on human microbiome. Herein, we provide a perspective of recent developments, the challenges faced, and the future directions of metaproteomics and its applications. In addition, we propose a set of guidelines/recommendations for performing and reporting the results from metaproteomic experiments for the study of human microbiomes. We anticipate that these guidelines will be optimized further as more metaproteomic questions are raised and addressed, and metaproteomic applications are published, so that they are eventually recognized and applied in the field.

Challenges in Clinical Metaproteomics Highlighted by the Analysis of Acute Leukemia Patients with Gut Colonization by Multidrug-Resistant Enterobacteriaceae

The microbiome has a strong impact on human health and disease and is, therefore, increasingly studied in a clinical context. Metaproteomics is also attracting considerable attention, and such data can be efficiently generated today owing to improvements in mass spectrometry-based proteomics. As we will discuss in this study, there are still major challenges notably in data analysis that need to be overcome. Here, we analyzed 212 fecal samples from 56 hospitalized acute leukemia patients with multidrug-resistant Enterobactericeae (MRE) gut colonization using metagenomics and metaproteomics. This is one of the largest clinical metaproteomic studies to date, and the first metaproteomic study addressing the gut microbiome in MRE colonized acute leukemia patients. Based on this substantial data set, we discuss major current limitations in clinical metaproteomic data analysis to provide guidance to researchers in the field. Notably, the results show that public metagenome databases are incomplete and that sample-specific metagenomes improve results. Furthermore, biological variation is tremendous which challenges clinical study designs and argues that longitudinal measurements of individual patients are a valuable future addition to the analysis of patient cohorts.

The Methodology Behind Network Thinking: Graphs to Analyze Microbial Complexity and Evolution

In the post genomic era, large and complex molecular datasets from genome and metagenome sequencing projects expand the limits of what is possible for bioinformatic analyses. Network-based methods are increasingly used to complement phylogenetic analysis in studies in molecular evolution, including comparative genomics, classification, and ecological studies. Using network methods, the vertical and horizontal relationships between all genes or genomes, whether they are from cellular chromosomes or mobile genetic elements, can be explored in a single expandable graph. In recent years, development of new methods for the construction and analysis of networks has helped to broaden the availability of these approaches from programmers to a diversity of users. This chapter introduces the different kinds of networks based on sequence similarity that are already available to tackle a wide range of biological questions, including sequence similarity networks, gene-sharing networks and bipartite graphs, and a guide for their construction and analyses.

Recovering Genomics Clusters of Secondary Metabolites from Lakes Using Genome-Resolved Metagenomics

Metagenomic approaches became increasingly popular in the past decades due to decreasing costs of DNA sequencing and bioinformatics development. So far, however, the recovery of long genes coding for secondary metabolites still represents a big challenge. Often, the quality of metagenome assemblies is poor, especially in environments with a high microbial diversity where sequence coverage is low and complexity of natural communities high. Recently, new and improved algorithms for binning environmental reads and contigs have been developed to overcome such limitations. Some of these algorithms use a similarity detection approach to classify the obtained reads into taxonomical units and to assemble draft genomes. This approach, however, is quite limited since it can classify exclusively sequences similar to those available (and well classified) in the databases. In this work, we used draft genomes from Lake Stechlin, north-eastern Germany, recovered by MetaBat, an efficient binning tool that integrates empirical probabilistic distances of genome abundance, and tetranucleotide frequency for accurate metagenome binning. These genomes were screened for secondary metabolism genes, such as polyketide synthases (PKS) and non-ribosomal peptide synthases (NRPS), using the Anti-SMASH and NAPDOS workflows. With this approach we were able to identify 243 secondary metabolite clusters from 121 genomes recovered from our lake samples. A total of 18 NRPS, 19 PKS, and 3 hybrid PKS/NRPS clusters were found. In addition, it was possible to predict the partial structure of several secondary metabolite clusters allowing for taxonomical classifications and phylogenetic inferences. Our approach revealed a high potential to recover and study secondary metabolites genes from any aquatic ecosystem.

Challenges and perspectives of metaproteomic data analysis

In nature microorganisms live in complex microbial communities. Comprehensive taxonomic and functional knowledge about microbial communities supports medical and technical application such as fecal diagnostics as well as operation of biogas plants or waste water treatment plants. Furthermore, microbial communities are crucial for the global carbon and nitrogen cycle in soil and in the ocean. Among the methods available for investigation of microbial communities, metaproteomics can approximate the activity of microorganisms by investigating the protein content of a sample. Although metaproteomics is a very powerful method, issues within the bioinformatic evaluation impede its success. In particular, construction of databases for protein identification, grouping of redundant proteins as well as taxonomic and functional annotation pose big challenges. Furthermore, growing amounts of data within a metaproteomics study require dedicated algorithms and software. This review summarizes recent metaproteomics software and addresses the introduced issues in detail.

The impact of zinc oxide nanoparticles on the bacterial microbiome of activated sludge systems

The expected growth in nanomaterial applications could result in increased amounts of nanoparticles entering municipal sewer systems, eventually ending up in wastewater treatment plants and therefore negatively affecting microbial populations and biological nutrient removal. The aim of this study was to ascertain the impact of zinc oxide nanoparticles (nZnO) on the bacterial microbiome of an activated sludge system. A metagenomic approach combined with the latest generation Illumina MiSeq platform and RDP pipeline tools were used to identify and classify the bacterial microbiome of the sludge. Results revealed a drastic decrease in the number of operational taxonomic units (OTUs) from 27 737 recovered in the nZnO-free sample to 23 743, 17 733, and 13 324 OTUs in wastewater samples exposed to various concentrations of nZnO (5, 10 and 100 mg/L nZnO, respectively). These represented 12 phyla, 21 classes, 30 orders, 54 families and 51 genera, completely identified at each taxonomic level in the control samples; 7-15-25-28-20 for wastewater samples exposed to 5 mg/L nZnO; 9-15-24-31-23 for those exposed to 10 mg/L and 7-11-19-26-17 for those exposed 100 mg/L nZnO. A large number of sequences could not be assigned to specific taxa, suggesting a possibility of novel species to be discovered.

Metaproteomic analysis of atmospheric aerosol samples

Metaproteomic analysis of air particulate matter provides information about the abundance and properties of bioaerosols in the atmosphere and their influence on climate and public health. We developed and applied efficient methods for the extraction and analysis of proteins from glass fiber filter samples of total, coarse, and fine particulate matter. Size exclusion chromatography was applied to remove matrix components, and sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) was applied for protein fractionation according to molecular size, followed by in-gel digestion and LC-MS/MS analysis of peptides using a hybrid Quadrupole-Orbitrap MS. Maxquant software and the Swiss-Prot database were used for protein identification. In samples collected at a suburban location in central Europe, we found proteins that originated mainly from plants, fungi, and bacteria, which constitute a major fraction of primary biological aerosol particles (PBAP) in the atmosphere. Allergenic proteins were found in coarse and fine particle samples, and indications for atmospheric degradation of proteins were observed.

Graphical abstract

Perspective for Aquaponic Systems: "Omic" Technologies for Microbial Community Analysis

Aquaponics is the combined production of aquaculture and hydroponics, connected by a water recirculation system. In this productive system, the microbial community is responsible for carrying out the nutrient dynamics between the components. The nutrimental transformations mainly consist in the transformation of chemical species from toxic compounds into available nutrients. In this particular field, the microbial research, the “Omic” technologies will allow a broader scope of studies about a current microbial profile inside aquaponics community, even in those species that currently are unculturable. This approach can also be useful to understand complex interactions of living components in the system. Until now, the analog studies were made to set up the microbial characterization on recirculation aquaculture systems (RAS). However, microbial community composition of aquaponics is still unknown. “Omic” technologies like metagenomic can help to reveal taxonomic diversity. The perspectives are also to begin the first attempts to sketch the functional diversity inside aquaponic systems and its ecological relationships. The knowledge of the emergent properties inside the microbial community, as well as the understanding of the biosynthesis pathways, can derive in future biotechnological applications. Thus, the aim of this review is to show potential applications of current “Omic” tools to characterize the microbial community in aquaponic systems.

The vocabulary of microbiome research: a proposal

The advancement of DNA/RNA, proteins, and metabolite analytical platforms, combined with increased computing technologies, has transformed the field of microbial community analysis. This transformation is evident by the exponential increase in the number of publications describing the composition and structure, and sometimes function, of the microbial communities inhabiting the human body. This rapid evolution of the field has been accompanied by confusion in the vocabulary used to describe different aspects of these communities and their environments. The misuse of terms such as microbiome, microbiota, metabolomic, and metagenome and metagenomics among others has contributed to misunderstanding of many study results by the scientific community and the general public alike. A few review articles have previously defined those terms, but mainly as sidebars, and no clear definitions or use cases have been published. In this editorial, we aim to propose clear definitions of each of these terms, which we would implore scientists in the field to adopt and perfect.

Synthetic microbial ecosystems for biotechnology

Most highly controlled and specific applications of microorganisms in biotechnology involve pure cultures. Maintaining single strain cultures is important for industry as contaminants can reduce productivity and lead to longer "down-times" during sterilisation. However, microbes working together provide distinct advantages over pure cultures. They can undertake more metabolically complex tasks, improve efficiency and even expand applications to open systems. By combining rapidly advancing technologies with ecological theory, the use of microbial ecosystems in biotechnology will inevitably increase. This review provides insight into the use of synthetic microbial communities in biotechnology by applying the engineering paradigm of measure, model, manipulate and manufacture, and illustrate the emerging wider potential of the synthetic ecology field. Systems to improve biofuel production using microalgae are also discussed.

Evidence for metaviromic islands in marine phages

Metagenomic islands (MGIs) have been defined as genomic regions in prokaryotic genomes that under-recruit from metagenomes where most of the same genome recruits at close to 100% identity over most of its length. The presence of MGIs in prokaryotes has been associated to the diversity of concurrent lineages that vary at this level to disperse the predatory pressure of phages that, reciprocally, maintain high clonal diversity in the population and improve ecosystem performance. This was proposed as a Constant-Diversity (C-D) model. Here we have investigated the regions of phage genomes under-recruiting in a metavirome constructed with a sample from the same habitat where they were retrieved. Some of the genes found to under-recruit are involved in host recognition as would be expected from the C-D model. Furthermore, the recruitment of intragenic regions known to be involved in molecular recognition also had a significant under-recruitment compared to the rest of the gene. However, other genes apparently disconnected from the recognition process under-recruited often, specifically the terminases involved in packaging of the phage genome in the capsid and a few others. In addition, some highly related phage genomes (at nucleotide sequence level) had no metaviromic islands (MVIs). We speculate that the latter might be generalist phages with broad infection range that do not require clone specific lineages.

Interactions in the microbiome: communities of organisms and communities of genes

A central challenge in microbial community ecology is the delineation of appropriate units of biodiversity, which can be taxonomic, phylogenetic, or functional in nature. The term 'community' is applied ambiguously; in some cases, the term refers simply to a set of observed entities, while in other cases, it requires that these entities interact with one another. Microorganisms can rapidly gain and lose genes, potentially decoupling community roles from taxonomic and phylogenetic groupings. Trait-based approaches offer a useful alternative, but many traits can be defined based on gene functions, metabolic modules, and genomic properties, and the optimal set of traits to choose is often not obvious. An analysis that considers taxon assignment and traits in concert may be ideal, with the strengths of each approach offsetting the weaknesses of the other. Individual genes also merit consideration as entities in an ecological analysis, with characteristics such as diversity, turnover, and interactions modeled using genes rather than organisms as entities. We identify some promising avenues of research that are likely to yield a deeper understanding of microbial communities that shift from observation-based questions of 'Who is there?' and 'What are they doing?' to the mechanistically driven question of 'How will they respond?'

The proteomics of heavy metal hyperaccumulation by plants

Hyperaccumulators are distinguished from non-hyperaccumulators on the basis of their capacity to extract heavy metal ions from the soil, their more efficient root-to-shoot translocation of these ions and their greater ability to detoxify and sequester heavy metals in the shoot. The understanding of the mechanisms underlying metal ion accumulation has progressed beyond the relevant biochemistry and physiology to encompass the genetic and molecular regulatory systems which differentiate hyperaccumulators from non-hyperaccumulators. This paper reviews the literature surrounding the application of proteomics technology to plant metal hyperaccumulation, in particular involving the elements As, Cd, Cu, Ni, Pb and Zn. The hyperaccumulation process across a number of unrelated plant species appears to be associated with proteins involved in energy metabolism, the oxidative stress response and abiotic and biotic stress. The relevance of transducers of the metal stress response to the phenomenon of hyperaccumulation is summarized. Proteomic data complement the more voluminous genomic and transcriptomic data sets in providing a more nuanced picture of the process, and should therefore help in the identification of the major genetic determinants of the hyperaccumulation phenomenon.

Allele intersection analysis: a novel tool for multi locus sequence assignment in multiply infected hosts

Wolbachia are wide-spread, endogenous α-Proteobacteria of arthropods and filarial nematodes. 15-75% of all insect species are infected with these endosymbionts that alter their host's reproduction to facilitate their spread. In recent years, many insect species infected with multiple Wolbachia strains have been identified. As the endosymbionts are not cultivable outside living cells, strain typing relies on molecular methods. A Multi Locus Sequence Typing (MLST) system was established for standardizing Wolbachia strain identification. However, MLST requires hosts to harbour individual and not multiple strains of supergroups without recombination. This study revisits the applicability of the current MLST protocols and introduces Allele Intersection Analysis (AIA) as a novel approach. AIA utilizes natural variations in infection patterns and allows correct strain assignment of MLST alleles in multiply infected host species without the need of artificial strain segregation. AIA identifies pairs of multiply infected individuals that share Wolbachia and differ in only one strain. In such pairs, the shared MLST sequences can be used to assign alleles to distinct strains. Furthermore, AIA is a powerful tool to detect recombination events. The underlying principle of AIA may easily be adopted for MLST approaches in other uncultivable bacterial genera that occur as multiple strain infections and the concept may find application in metagenomic high-throughput parallel sequencing projects.

Microbial metagenomics: beyond the genome

Metagenomics literally means "beyond the genome." Marine microbial metagenomic databases presently comprise approximately 400 billion base pairs of DNA, only approximately 3% of that found in 1 ml of seawater. Very soon a trillion-base-pair sequence run will be feasible, so it is time to reflect on what we have learned from metagenomics. We review the impact of metagenomics on our understanding of marine microbial communities. We consider the studies facilitated by data generated through the Global Ocean Sampling expedition, as well as the revolution wrought at the individual laboratory level through next generation sequencing technologies. We review recent studies and discoveries since 2008, provide a discussion of bioinformatic analyses, including conceptual pipelines and sequence annotation and predict the future of metagenomics, with suggestions of collaborative community studies tailored toward answering some of the fundamental questions in marine microbial ecology.

What's in a name? The argument for changing the name of IAEMS and its affiliated societies

We identify trends over the past decades in membership in societies affiliated with the International Association of Environmental Mutagen Societies (IAEMS), and we also highlight findings in a recent review by Claxton et al. [Environ Health Perspect, in press] regarding the numbers of papers published per year using genetic toxicology assays. These analyses reveal a decline or at best a static level of membership in IAEMS-affiliated societies, as well as a decline in the number of papers published per year using genetic toxicology assays-with the exception of those using comet assays, which already have begun to plateau. In contrast, toxicogenomics and computational toxicology are becoming increasingly prominent relative to environmental mutagenesis research in most research institutes, reflecting the ascendancy of these areas of environmental toxicology. We conclude that changing the name of IAEMS and its affiliated societies to reflect these changes might enhance membership and publication by welcoming a broader range of scientists into these societies. Although various names are possible, we think that changing the name of these societies to "Environmental Genomics Society" may help to make our societies more attractive to a broader range of scientists, resulting in an increase in membership and an acceleration of the incorporation of genomic methods into environmental research.

Metagenomic gene discovery: how far have we moved into novel sequence space?

Metagenomics emerged in the late 1990s as a tool for accessing and studying the collective microbial genetic material in the environment. The advent of the technology generated great excitement, as it has provided new opportunities and technologies for studying the wealth of microbial genetic diversity in the environment. Metagenomics has been widely predicted to access new dimensions of protein sequence space. A decade on, we review how far we have actually moved into new sequence space (and other aspects of protein space) using metagenomic tools. While several novel enzyme activities and protein structures have been identified through metagenomic strategies, the greatest advancement has been made in the isolation of novel protein sequences, some of which have no close relatives, form deeply branched lineages and even represent novel families. This is particularly true for glycosyl hydrolases and lipase/esterases, despite the fact that these activities are frequently screened for in metagenomic studies. However, there is much room for improvement in the methods employed and they will need to be addressed so that access to novel biocatalytic activities can be widened.

Survey of genome organization and gene content of Corynebacterium pseudotuberculosis

Corynebacterium pseudotuberculosis is an intracellular pathogen that causes Caseous lymphadenitis (CLA) disease in sheep and goats. The widespread occurrence and the economic importance of this pathogen have prompted investigation of its pathogenesis. We used a genomic library of C. pseudotuberculosis to generate 1440 genomic survey sequences (GSSs); these were analyzed in silico with bioinformatics tools, using public databases for comparative analyses. We employed non-redundant unique sequences as a query for BLAST searches against the genome, the translated genome and the proteome of four other Corynebacterium species that have been completely sequenced. We were able to characterize approximately 8% of the genome of C. pseudotuberculosis, including previously undescribed functional group genes, based on the COG database; the GSSs classification into categories gave 13% information storage and processing, 14% cellular processes and 23% metabolism. We found a close relation between C. pseudotuberculosis and C. diphtheriae conserved-gene synteny in Corynebacteria species.

Environmental proteomics: a paradigm shift in characterizing microbial activities at the molecular level

The increase in sequencing capacity led to a new wave of metagenomic projects, enabling and setting the prerequisite for the application of environmental proteomics technologies. This review describes the current status of environmental proteomics. It describes sample preparation as well as the two major technologies applied within this field: two-dimensional electrophoresis-based environmental proteomics and liquid chromatography-mass spectrometry-based environmental proteomics. It also highlights current publications and describes major scientific findings. The review closes with a discussion of critical improvements in the area of integrating experimental mass spectrometry technologies with bioinformatics as well as improved sample handling.

What is the role of the metabolic activity of the gut microbiota in inflammatory bowel disease? Probing for answers with stable isotopes

The pathogenesis of inflammatory bowel disease remains obscure. However, there has been increasing interest in the role of the gut microbiota, focusing in particular on the "unculturable majority" of luminal and mucosal bacteria, which until recently have been difficult to study owing to the technical challenges of identification and elucidating function. Bacterial components and metabolites have been implicated in signalling to host immune systems and regulating inflammatory responses. Although the rapid expansion in techniques of molecular microbiology has increased our understanding of bacterial diversity, the tools to assess bacterial metabolic activity, and to link the 2, lag behind. Stable isotope probing is a powerful technique to link the metabolic activity and diversity of "unculturable" bacteria through isotopic labelling of biomarkers such as DNA and RNA. Progression of current stable isotope probing methodology with high-resolution oligonucleotide 16s rRNA probe technology and high precision liquid chromatographic isotope ratio mass spectrometry may facilitate application in human microbial ecology. Progress towards stable isotope probing use in vivo, in concert with other advances in bacterial metabolome analysis, will lead to the development of a dynamic picture of the metabolic activity and diversity of intestinal bacteria in inflammatory bowel disease. Such insights will, over time, lead to fuller understanding of inflammatory bowel disease pathogenesis and the development of targeted therapies to reverse the "dysbiosis" that precedes disease relapse.

The tryptophan pathway genes of the Sargasso Sea metagenome: new operon structures and the prevalence of non-operon organization

BACKGROUND

The enormous database of microbial DNA generated from the Sargasso Sea metagenome provides a unique opportunity to locate genes participating in different biosynthetic pathways and to attempt to understand the relationship and evolution of those genes. In this article, an analysis of the Sargasso Sea metagenome is made with respect to the seven genes of the tryptophan pathway.

RESULTS

At least 5% of all the genes that are related to amino acid biosynthesis are tryptophan (trp) genes. Many contigs and scaffolds contain whole or split operons that are similar to previously analyzed trp gene organizations. Only two scaffolds discovered in this analysis possess a different operon organization of tryptophan pathway genes than those previously known. Many marine organisms lack an operon-type organization of these genes or have mini-operons containing only two trp genes. In addition, the trpB genes from this search reveal that the dichotomous division between trpB_1 and trpB_2 also occurs in organisms from the Sargasso Sea. One cluster was found to contain trpB sequences that were closely related to each other but distinct from most known trpB sequences.

CONCLUSION

The data show that trp genes are widely dispersed within this metagenome. The novel organization of these genes and an unusual group of trpB_1 sequences that were found among some of these Sargasso Sea bacteria indicate that there is much to be discovered about both the reason for certain gene orders and the regulation of tryptophan biosynthesis in marine bacteria.

Differences in vegetation composition and plant species identity lead to only minor changes in soil-borne microbial communities in a former arable field

To examine the relationship between plant species composition and microbial community diversity and structure, we carried out a molecular analysis of microbial community structure and diversity in two field experiments. In the first experiment, we examined bacterial community structure in bulk and rhizosphere soils in fields exposed to different plant diversity treatments, via a 16S rRNA gene clone library approach. Clear differences were observed between bacterial communities of the bulk soil and the rhizosphere, with the latter containing lower bacterial diversity. The second experiment focused on the influence of 12 different native grassland plant species on bacterial community size and structure in the rhizosphere, as well as the structure of Acidobacteria and Verrucomicrobia community structures. In general, bacterial and phylum-specific quantitative PCR and PCR-denaturing gradient gel electrophoresis revealed only weak influences of plant species on rhizosphere communities. Thus, although plants did exert an influence on microbial species composition and diversity, these interactions were not specific and selective enough to lead to major impacts of vegetation composition and plant species on below-ground microbial communities.

Metagenomics and biological ontology

Metagenomics is an emerging microbial systems science that is based on the large-scale analysis of the DNA of microbial communities in their natural environments. Studies of metagenomes are revealing the vast scope of biodiversity in a wide range of environments, as well as new functional capacities of individual cells and communities, and the complex evolutionary relationships between them. Our examination of this science focuses on the ontological implications of these studies of metagenomes and metaorganisms, and what they mean for common sense and philosophical understandings of multicellularity, individuality and organism. We show how metagenomics requires us to think in different ways about what human beings are and what their relation to the microbial world is. Metagenomics could also transform the way in which evolutionary processes are understood, with the most basic relationship between cells from both similar and different organisms being far more cooperative and less antagonistic than is widely assumed. In addition to raising fundamental questions about biological ontology, metagenomics generates possibilities for powerful technologies addressed to issues of climate, health and conservation. We conclude with reflections about process-oriented versus entity-oriented analysis in light of current trends towards systems approaches.

Genomics of Actinobacteria: tracing the evolutionary history of an ancient phylum

Actinobacteria constitute one of the largest phyla among bacteria and represent gram-positive bacteria with a high G+C content in their DNA. This bacterial group includes microorganisms exhibiting a wide spectrum of morphologies, from coccoid to fragmenting hyphal forms, as well as possessing highly variable physiological and metabolic properties. Furthermore, Actinobacteria members have adopted different lifestyles, and can be pathogens (e.g., Corynebacterium, Mycobacterium, Nocardia, Tropheryma, and Propionibacterium), soil inhabitants (Streptomyces), plant commensals (Leifsonia), or gastrointestinal commensals (Bifidobacterium). The divergence of Actinobacteria from other bacteria is ancient, making it impossible to identify the phylogenetically closest bacterial group to Actinobacteria. Genome sequence analysis has revolutionized every aspect of bacterial biology by enhancing the understanding of the genetics, physiology, and evolutionary development of bacteria. Various actinobacterial genomes have been sequenced, revealing a wide genomic heterogeneity probably as a reflection of their biodiversity. This review provides an account of the recent explosion of actinobacterial genomics data and an attempt to place this in a biological and evolutionary context.

Genotypic microbial community profiling: a critical technical review

Microbial ecology has undergone a profound change in the last two decades with regard to methods employed for the analysis of natural communities. Emphasis has shifted from culturing to the analysis of signature molecules including molecular DNA-based approaches that rely either on direct cloning and sequencing of DNA fragments (shotgun cloning) or often rely on prior amplification of target sequences by use of the polymerase chain reaction (PCR). The pool of PCR products can again be either cloned and sequenced or can be subjected to an increasing variety of genetic profiling methods, including amplified ribosomal DNA restriction analysis, automated ribosomal intergenic spacer analysis, terminal restriction fragment length polymorphism, denaturing gradient gel electrophoresis, temperature gradient gel electrophoresis, single strand conformation polymorphism, and denaturing high-performance liquid chromatography. In this document, we present and critically compare these methods commonly used for the study of microbial diversity.

Genomics, environmental genomics and the issue of microbial species

A microbial species concept is crucial for interpreting the variation detected by genomics and environmental genomics among cultivated microorganisms and within natural microbial populations. Comparative genomic analyses of prokaryotic species as they are presently described and named have led to the provocative idea that prokaryotes may not form species as we think about them for plants and animals. There are good reasons to doubt whether presently recognized prokaryotic species are truly species. To achieve a better understanding of microbial species, we believe it is necessary to (i) re-evaluate traditional approaches in light of evolutionary and ecological theory, (ii) consider that different microbial species may have evolved in different ways and (iii) integrate genomic, metagenomic and genome-wide expression approaches with ecological and evolutionary theory. Here, we outline how we are using genomic methods to (i) identify ecologically distinct populations (ecotypes) predicted by theory to be species-like fundamental units of microbial communities, and (ii) test their species-like character through in situ distribution and gene expression studies. By comparing metagenomic sequences obtained from well-studied hot spring cyanobacterial mats with genomic sequences of two cultivated cyanobacterial ecotypes, closely related to predominant native populations, we can conduct in situ population genetics studies that identify putative ecotypes and functional genes that determine the ecotypes' ecological distinctness. If individuals within microbial communities are found to be grouped into ecologically distinct, species-like populations, knowing about such populations should guide us to a better understanding of how genomic variation is linked to community function.

Molecular approaches: advantages and artifacts in assessing bacterial diversity

Bacteria account for a major proportion of Earth's biological diversity. They play essential roles in quite diverse environments and there has been an increasing interest in bacterial biodiversity. Research using novel and efficient tools to identify and characterize bacterial communities has been the key for elucidating biological activities with potential for industrial application. The current approach used for defining bacterial species is based on phenotypic and genomic properties. Traditional and novel DNA-based molecular methods are improving our knowledge of bacterial diversity in nature. Advances in molecular biology have been important for studies of diversity, considerably improving our knowledge of morphological, physiological, and ecological features of bacterial taxa. DNA-DNA hybridization, which has been used for many years, is still considered the golden standard for bacteria species identification. PCR-based methods investigating 16S rRNA gene sequences, and other approaches, such as the metagenome, have been used to study the physiology and diversity of bacteria and to identify novel genes with potential pharmaceutical and other biotechnological applications. We examined the advantages and limitations of molecular methods currently used to analyze bacterial diversity; these are mainly based on the 16S rRNA gene. These methods have allowed us to examine microorganisms that cannot be cultivated by routine methods and have also been useful for phylogenetic studies. We also considered the importance of improvements in microbe culture techniques and how we can combine different methods to allow a more appropriate assessment of bacterial diversity and to determine their real potential for industrial applications.

The study of socioethical issues in systems biology

Systems biology is the rapidly growing and heavily funded successor science to genomics. Its mission is to integrate extensive bodies of molecular data into a detailed mathematical understanding of all life processes, with an ultimate view to their prediction and control. Despite its high profile and widespread practice, there has so far been almost no bioethical attention paid to systems biology and its potential social consequences. We outline some of systems biology's most important socioethical issues by contrasting the concept of systems as dynamic processes against the common static interpretation of genomes. New issues arise around systems biology's capacities for in silico testing, changing cultural understandings of life, synthetic biology, and commercialization. We advocate an interdisciplinary and interactive approach that integrates social and philosophical analysis and engages closely with the science. Overall, we argue that systems biology socioethics could stimulate new ways of thinking about socioethical studies of life sciences.

Protein extraction and fingerprinting optimization of bacterial communities in natural environment

Recent development in molecular approaches allows access to genetic structure and diversity of indigenous microbial communities. In contrast, the functional analysis of microorganisms in their environment is still hampered by methodological limitations. Analysis of total proteins expressed at the whole community level (metaproteome) has been proposed to characterize the functional structure of microbial communities in their environment. However, developments are still required to perform such analysis. Our aim was to optimize methods to extract and characterize metaproteome of indigenous microbial communities. Experiments were first conducted in monoxenic bacterial cultures, and various methods were examined to define a procedure of protein extraction ensuring an efficient recovery regardless of the taxonomic affiliation of the cells. These developments were next applied to characterize the metaproteome from indigenous bacterial communities in freshwater samples. Bacterial cells were recovered from water using a high-speed density gradient centrifugation method before protein extraction and fingerprinting. The reactivity and sensitivity of this metaproteomic approach were tested by analyzing the variations of protein fingerprints according to perturbations (cadmium or mercury contamination). The genetic structure of the corresponding communities was also characterized by automated ribosomal spacer analysis (ARISA) DNA fingerprinting. Both protein and DNA fingerprints were statistically analyzed. Results obtained showed that the method developed for protein recovery and fingerprinting was efficient, sensitive, and reproducible. Both the functional and genetic structures of the freshwater bacterial community were complex and varied with perturbations. These variations occurred at both population and protein expression levels and were specific to the perturbation applied.