Beyond the genome: community-level analysis of the microbial world

Nematodes alter the taxonomic and functional profiles of benthic bacterial communities: A metatranscriptomic approach

Marine sediments cover 70% of the Earth's surface, and harbour diverse bacterial communities critical for marine biogeochemical processes, which affect climate change, biodiversity and ecosystem functioning. Nematodes, the most abundant and species-rich metazoan organisms in marine sediments, in turn, affect benthic bacterial communities and bacterial-mediated ecological processes, but the underlying mechanisms by which they affect biogeochemical cycles remain poorly understood. Here, we demonstrate using a metatranscriptomic approach that nematodes alter the taxonomic and functional profiles of benthic bacterial communities. We found particularly strong stimulation of nitrogen-fixing and methane-oxidizing bacteria in the presence of nematodes, as well as increased functional activity associated with methane metabolism and degradation of various carbon compounds. This study provides empirical evidence that the presence of nematodes results in taxonomic and functional shifts in active bacterial communities, indicating that nematodes may play an important role in benthic ecosystem processes.

The Raphidiopsis (= Cylindrospermopsis) raciborskii pangenome updated: Two new metagenome-assembled genomes from the South American clade

Two Raphidiopsis (=Cylindrospermopsis) raciborskii metagenome-assembled genomes (MAGs) were recovered from two freshwater metagenomic datasets sampled in 2011 and 2012 in Pampulha Lake, a hypereutrophic, artificial, shallow reservoir, located in the city of Belo Horizonte (MG), Brazil. Since the late 1970s, the lake has undergone increasing eutrophication pressure, due to wastewater input, leading to the occurrence of frequent cyanobacterial blooms. The major difference observed between PAMP2011 and PAMP2012 MAGs was the lack of the saxitoxin gene cluster in PAMP2012, which also presented a smaller genome, while PAMP2011 presented the complete sxt cluster and all essential proteins and clusters. The pangenome analysis was performed with all Raphidiopsis/Cylindrospermopsis genomes available at NCBI to date, with the addition of PAMP2011 and PAMP2012 MAGs (All33 subset), but also without the South American strains (noSA subset), and only among the South American strains (SA10 and SA8 subsets). We observed a substantial increase in the core genome size for the 'noSA' subset, in comparison to 'All33' subset, and since the core genome reflects the closeness among the pangenome members, the results strongly suggest that the conservation level of the essential gene repertoire seems to be affected by the geographic origin of the strains being analyzed, supporting the existence of a distinct SA clade. The Raphidiopsis pangenome comprised a total of 7943 orthologous protein clusters, and the two new MAGs increased the pangenome size by 11%. The pangenome based phylogenetic relationships among the 33 analyzed genomes showed that the SA genomes clustered together with 99% bootstrap support, reinforcing the metabolic particularity of the Raphidiopsis South American clade, related to its saxitoxin producing unique ability, while also indicating a different evolutionary history due to its geographic isolation.

Microbially mediated fossil concretions and their characterization by the latest methodologies: a review

The study of well-preserved organic matter (OM) within mineral concretions has provided key insights into depositional and environmental conditions in deep time. Concretions of varied compositions, including carbonate, phosphate, and iron-based minerals, have been found to host exceptionally preserved fossils. Organic geochemical characterization of concretion-encapsulated OM promises valuable new information of fossil preservation, paleoenvironments, and even direct taxonomic information to further illuminate the evolutionary dynamics of our planet and its biota. Full exploitation of this largely untapped geochemical archive, however, requires a sophisticated understanding of the prevalence, formation controls and OM sequestration properties of mineral concretions. Past research has led to the proposal of different models of concretion formation and OM preservation. Nevertheless, the formation mechanisms and controls on OM preservation in concretions remain poorly understood. Here we provide a detailed review of the main types of concretions and formation pathways with a focus on the role of microbes and their metabolic activities. In addition, we provide a comprehensive account of organic geochemical, and complimentary inorganic geochemical, morphological, microbial and paleontological, analytical methods, including recent advancements, relevant to the characterization of concretions and sequestered OM. The application and outcome of several early organic geochemical studies of concretion-impregnated OM are included to demonstrate how this underexploited geo-biological record can provide new insights into the Earth's evolutionary record. This paper also attempts to shed light on the current status of this research and major challenges that lie ahead in the further application of geo-paleo-microbial and organic geochemical research of concretions and their host fossils. Recent efforts to bridge the knowledge and communication gaps in this multidisciplinary research area are also discussed, with particular emphasis on research with significance for interpreting the molecular record in extraordinarily preserved fossils.

Marine Actinomycetes Associated with Stony Corals: A Potential Hotspot for Specialized Metabolites

Microbial secondary metabolites are an important source of antibiotics currently available for combating drug-resistant pathogens. These important secondary metabolites are produced by various microorganisms, including Actinobacteria. Actinobacteria have a colossal genome with a wide array of genes that code for several bioactive metabolites and enzymes. Numerous studies have reported the isolation and screening of millions of strains of actinomycetes from various habitats for specialized metabolites worldwide. Looking at the extent of the importance of actinomycetes in various fields, corals are highlighted as a potential hotspot for untapped secondary metabolites and new bioactive metabolites. Unfortunately, knowledge about the diversity, distribution and biochemistry of marine actinomycetes compared to hard corals is limited. In this review, we aim to summarize the recent knowledge on the isolation, diversity, distribution and discovery of natural compounds from marine actinomycetes associated with hard corals. A total of 11 new species of actinomycetes, representing nine different families of actinomycetes, were recovered from hard corals during the period from 2007 to 2022. In addition, this study examined a total of 13 new compounds produced by five genera of actinomycetes reported from 2017 to 2022 with antibacterial, antifungal and cytotoxic activities. Coral-derived actinomycetes have different mechanisms of action against their competitors.

Emergent spatiotemporal population dynamics with cell-length control of synthetic microbial consortia

The increased complexity of synthetic microbial biocircuits highlights the need for distributed cell functionality due to concomitant increases in metabolic and regulatory burdens imposed on single-strain topologies. Distributed systems, however, introduce additional challenges since consortium composition and spatiotemporal dynamics of constituent strains must be robustly controlled to achieve desired circuit behaviors. Here, we address these challenges with a modeling-based investigation of emergent spatiotemporal population dynamics using cell-length control in monolayer, two-strain bacterial consortia. We demonstrate that with dynamic control of a strain's division length, nematic cell alignment in close-packed monolayers can be destabilized. We find that this destabilization confers an emergent, competitive advantage to smaller-length strains-but by mechanisms that differ depending on the spatial patterns of the population. We used complementary modeling approaches to elucidate underlying mechanisms: an agent-based model to simulate detailed mechanical and signaling interactions between the competing strains, and a reductive, stochastic lattice model to represent cell-cell interactions with a single rotational parameter. Our modeling suggests that spatial strain-fraction oscillations can be generated when cell-length control is coupled to quorum-sensing signaling in negative feedback topologies. Our research employs novel methods of population control and points the way to programming strain fraction dynamics in consortial synthetic biology.

Meta-omic evaluation of bacterial microbial community structure and activity for the environmental assessment of soils: overcoming protein extraction pitfalls

Microorganisms play unique, essential and integral roles in the biosphere. This work aims to assess the utility of soil's metaomics for environmental diagnosis. Doñana National Park (DNP) was selected as a natural lab since it contains a strictly protected core that is surrounded by numerous threats of pollution. Culture-independent high-throughput molecular tools were used to evaluate the alterations of the global structure and metabolic activities of the microbiome. 16S rRNA sequencing shows lower bacterial abundance and diversity in areas historically exposed to contamination that surround DNP. For metaproteomics, an innovative post-alkaline protein extraction protocol was developed. After NaOH treatment, successive washing with Tris-HCl buffer supplemented with glycerol was essential to eliminate interferences. Starting from soils with different physicochemical characteristics, the method renders proteins with a remarkable resolution on SDS-PAGE gels. The proteins extracted were analysed by using an in-house database constructed from the rRNA data. LC-MS/MS analysis identified 2182 non-redundant proteins with 135 showing significant differences in relative abundance in the soils around DNP. Relevant global biological processes were altered in response to the environmental changes, such as protective and antioxidant mechanisms, translation, folding and homeostasis of proteins, membrane transport and aerobic respiratory metabolism.

Molecular Microbial Community Analysis as an Analysis Tool for Optimal Biogas Production

The microbial diversity in anaerobic digestion (AD) is important because it affects process robustness. High-throughput sequencing offers high-resolution data regarding the microbial diversity and robustness of biological systems including AD; however, to understand the dynamics of microbial processes, knowing the microbial diversity is not adequate alone. Advanced meta-omic techniques have been established to determine the activity and interactions among organisms in biological processes like AD. Results of these methods can be used to identify biomarkers for AD states. This can aid a better understanding of system dynamics and be applied to producing comprehensive models for AD. The paper provides valuable knowledge regarding the possibility of integration of molecular methods in AD. Although meta-genomic methods are not suitable for on-line use due to long operating time and high costs, they provide extensive insight into the microbial phylogeny in AD. Meta-proteomics can also be explored in the demonstration projects for failure prediction. However, for these methods to be fully realised in AD, a biomarker database needs to be developed.

High-throughput molecular analyses of microbiomes as a tool to monitor the wellbeing of aquatic environments

Aquatic environments are the recipients of many sources of environmental stress that trigger both local and global changes. To evaluate the associated risks to organisms and ecosystems more sensitive and accurate strategies are required. The analysis of the microbiome is one of the most promising candidates for environmental diagnosis of aquatic systems. Culture-independent interconnected meta-omic approaches are being increasing used to fill the gaps that classical microbial approaches cannot resolve. Here, we provide a prospective view of the increasing application of these high-throughput molecular technologies to evaluate the structure and functional activity of microbial communities in response to changes and disturbances in the environment, mostly of anthropogenic origin. Some relevant topics are reviewed, such as: (i) the use of microorganisms for water quality assessment, highlighting the incidence of antimicrobial resistance as an increasingly serious threat to global public health; (ii) the crucial role of microorganisms and their complex relationships with the ongoing climate change, and other stress threats; (iii) the responses of the environmental microbiome to extreme pollution conditions, such as acid mine drainage or oil spills. Moreover, protists and viruses, due to their huge impacts on the structure of microbial communities, are emerging candidates for the assessment of aquatic environmental health.

New Methods, New Concepts: What Can Be Applied to Freshwater Periphyton?

Microbial interactions play an essential role in aquatic ecosystems and are of the great interest for both marine and freshwater ecologists. Recent development of new technologies and methods allowed to reveal many functional mechanisms and create new concepts. Yet, many fundamental aspects of microbial interactions have been almost exclusively studied for marine pelagic and benthic ecosystems. These studies resulted in a formulation of the Black Queen Hypothesis, a development of the phycosphere concept for pelagic communities, and a realization of microbial communication as a key mechanism for microbial interactions. In freshwater ecosystems, especially for periphyton communities, studies focus mainly on physiology, biodiversity, biological indication, and assessment, but the many aspects of microbial interactions are neglected to a large extent. Since periphyton plays a great role for aquatic nutrient cycling, provides the basis for water purification, and can be regarded as a hotspot of microbial biodiversity, we highlight that more in-depth studies on microbial interactions in periphyton are needed to improve our understanding on functioning of freshwater ecosystems. In this paper we first present an overview on recent concepts (e.g., the "Black Queen Hypothesis") derived from state-of-the-art OMICS methods including metagenomics, metatranscriptomics, and metabolomics. We then point to the avenues how these methods can be applied for future studies on biodiversity and the ecological role of freshwater periphyton, a yet largely neglected component of many freshwater ecosystems.

Bayesian Inference of Microbial Community Structure from Metagenomic Data Using BioMiCo

Microbial samples taken from an environment often represent mixtures of communities, where each community is composed of overlapping assemblages of species. Such data represent a serious analytical challenge, as the community structures will be present as complex mixtures, there will be very large numbers of component species, and the species abundance will often be sparse over samples. The structure and complexity of these samples will vary according to both biotic and abiotic factors, and classical methods of data analysis will have a limited value in this setting. A novel Bayesian modeling framework, called BioMiCo, was developed to meet this challenge. BioMiCo takes abundance data derived from environmental DNA, and models each sample by a two-level mixture, where environmental OTUs contribute community structures, and those structures are related to the known biotic and abiotic features of each sample. The model is constrained by Dirichlet priors, which induces compact structures, minimizes variance, and maximizes model interpretability. BioMiCo is trained on a portion of the data, and once trained a BioMiCo model can be employed to make predictions about the features of new samples. This chapter provides a set of protocols that illustrate the application of BioMiCo to real inference problems. Each protocol is designed around the analysis of a real dataset, which was carefully chosen to illustrate specific aspects of real data analysis. With these protocols, users of BioMiCo will be able to undertake basic research into the properties of complex microbial systems, as well as develop predictive models for applied microbiomics.

An integrated insight into the response of bacterial communities to anthropogenic contaminants in a river: A case study of the Wonderfonteinspruit catchment area, South Africa

Bacterial communities in human-impacted rivers and streams are exposed to multiple anthropogenic contaminants, which can eventually lead to biodiversity loss and function. The Wonderfonteinspruit catchment area is impacted by operational and abandoned gold mines, farms, and formal and informal settlements. In this study, we used 16S rRNA gene high-throughput sequencing to characterize bacterial communities in the lower Wonderfonteinspruit and their response to various contaminant sources. The results showed that composition and structure of bacterial communities differed significantly (P<0.05) between less (downstream) and more (upstream) polluted sites. The taxonomic and functional gene dissimilarities significantly correlated with each other, while downstream sites had more distinct functional genes. The relative abundance of Proteobacteria, Bacteroidetes and Actinobacteria was higher at upstream sites, while Acidobacteria, Cyanobacteria, Firmicutes and Verrucomicrobia were prominent at downstream sites. In addition, upstream sites were rich in genera pathogenic and/or potentially pathogenic to humans. Multivariate and correlation analyses suggest that bacterial diversity was significantly (P<0.05) impacted by pH and heavy metals (cobalt, arsenic, chromium, nickel and uranium). A significant fraction (~14%) of the compositional variation was explained by a combination of anthropogenic inputs, of which mining (~6%) was the main contributor to bacterial community variation. Network analysis indicated that bacterial communities had non-random inter- and intra-phyla associations and that the main taxa showed both positive and negative linkages to environmental parameters. Our results suggest that species sorting, due to environmental parameters, was the main process that structured bacterial communities. Furthermore, upstream sites had higher relative abundances of genes involved in xenobiotic degradation, suggesting stronger removal of polycyclic aromatic hydrocarbons and other organic compounds. This study provides insights into the influences of anthropogenic land use on bacterial community structure and functions in the lower Wonderfonteinspruit.

Changes in Carbon Oxidation State of Metagenomes Along Geochemical Redox Gradients

There is widespread interest in how geochemistry affects the genomic makeup of microbial communities, but the possible impacts of oxidation-reduction (redox) conditions on the chemical composition of biomacromolecules remain largely unexplored. Here we document systematic changes in the carbon oxidation state, a metric derived from the chemical formulas of biomacromolecular sequences, using published metagenomic and metatranscriptomic datasets from 18 studies representing different marine and terrestrial environments. We find that the carbon oxidation states of DNA, as well as proteins inferred from coding sequences, follow geochemical redox gradients associated with mixing and cooling of hot spring fluids in Yellowstone National Park (USA) and submarine hydrothermal fluids. Thermodynamic calculations provide independent predictions for the environmental shaping of the gene and protein composition of microbial communities in these systems. On the other hand, the carbon oxidation state of DNA is negatively correlated with oxygen concentration in marine oxygen minimum zones. In this case, a thermodynamic model is not viable, but the low carbon oxidation state of DNA near the ocean surface reflects a low GC content, which can be attributed to genome reduction in organisms adapted to low-nutrient conditions. We also present evidence for a depth-dependent increase of oxidation state at the species level, which might be associated with alteration of DNA through horizontal gene transfer and/or selective degradation of relatively reduced (AT-rich) extracellular DNA by heterotrophic bacteria. Sediments exhibit even more complex behavior, where carbon oxidation state minimizes near the sulfate-methane transition zone and rises again at depth; markedly higher oxidation states are also associated with older freshwater-dominated sediments in the Baltic Sea that are enriched in iron oxides and have low organic carbon. This geobiochemical study of carbon oxidation state reveals a new aspect of environmental information in metagenomic sequences, and provides a reference frame for future studies that may use ancient DNA sequences as a paleoredox indicator.

Interkingdom microbial consortia mechanisms to guide biotechnological applications

Microbial consortia are capable of surviving diverse conditions through the formation of synergistic population-level structures, such as stromatolites, microbial mats and biofilms. Biotechnological applications are poised to capitalize on these unique interactions. However, current artificial co-cultures constructed for societal benefits, including biosynthesis, agriculture and bioremediation, face many challenges to perform as well as natural consortia. Interkingdom microbial consortia tend to be more robust and have higher productivity compared with monocultures and intrakingdom consortia, but the control and design of these diverse artificial consortia have received limited attention. Further, feasible research techniques and instrumentation for comprehensive mechanistic insights have only recently been established for interkingdom microbial communities. Here, we review these recent advances in technology and our current understanding of microbial interaction mechanisms involved in sustaining or developing interkingdom consortia for biotechnological applications. Some of the interactions among members from different kingdoms follow similar mechanisms observed for intrakingdom microbial consortia. However, unique interactions in interkingdom consortia, including endosymbiosis or interkingdom-specific cell-cell interactions, provide improved mitigation to external stresses and inhibitory compounds. Furthermore, antagonistic interactions among interkingdom species can promote fitness, diversification and adaptation, along with the production of beneficial metabolites and enzymes for society. Lastly, we shed light on future research directions to develop study methods at the level of metabolites, genes and meta-omics. These potential research methods could lead to the control and utilization of highly diverse microbial communities.

Biomarker panels for characterizing microbial community biofilm formation as composite molecular process

Microbial consortia execute collaborative molecular processes with contributions from individual species, on such basis enabling optimized molecular function. Such collaboration and synergies benefit metabolic flux specifically in extreme environmental conditions as seen in acid mine drainage, with biofilms as relevant microenvironment. However, knowledge about community species composition is not sufficient for deducing presence and efficiency of composite molecular function. For this task molecular resolution of the consortium interactome is to be retrieved, with molecular biomarkers particularly suited for characterizing composite molecular processes involved in biofilm formation and maintenance. A microbial species set identified in 18 copper environmental sites provides a data matrix for deriving a cross-species molecular process model of biofilm formation composed of 191 protein coding genes contributed from 25 microbial species. Computing degree and stress centrality of biofilm molecular process nodes allows selection of network hubs and central connectors, with the top ranking molecular features proposed as biomarker candidates for characterizing biofilm homeostasis. Functional classes represented in the biomarker panel include quorum sensing, chemotaxis, motility and extracellular polysaccharide biosynthesis, complemented by chaperones. Abundance of biomarker candidates identified in experimental data sets monitoring different biofilm conditions provides evidence for the selected biomarkers as sensitive and specific molecular process proxies for capturing biofilm microenvironments. Topological criteria of process networks covering an aggregate function of interest support the selection of biomarker candidates independent of specific community species composition. Such panels promise efficient screening of environmental samples for presence of microbial community composite molecular function.

Activity-Based Protein Profiling-Enabling Multimodal Functional Studies of Microbial Communities

Microorganisms living in community are critical to life on Earth, playing numerous and profound roles in the environment and human and animal health. Though their essentiality to life is clear, the mechanistic underpinnings of community structure, interactions, and functions are largely unexplored and in need of function-dependent technologies to unravel the mysteries. Activity-based protein profiling offers unprecedented molecular-level characterization of functions within microbial communities and provides an avenue to determine how external exposures result in functional alterations to microbiomes. Herein, we illuminate the current state and prospective contributions of ABPP as it relates to microbial communities. We provide details on the design, development, and validation of probes, challenges associated with probing in complex microbial communities, provide some specific examples of the biological applications of ABPP in microbes and microbial communities, and highlight potential areas for development. The future of ABPP holds real promise for understanding and considerable impact in microbiome studies associated with personalized medicine, precision agriculture, veterinary health, environmental studies, and beyond.

Overexpression of antibiotic resistance genes in hospital effluents over time

Objectives

Effluents contain a diverse abundance of antibiotic resistance genes that augment the resistome of receiving aquatic environments. However, uncertainty remains regarding their temporal persistence, transcription and response to anthropogenic factors, such as antibiotic usage. We present a spatiotemporal study within a river catchment (River Cam, UK) that aims to determine the contribution of antibiotic resistance gene-containing effluents originating from sites of varying antibiotic usage to the receiving environment.

Methods

Gene abundance in effluents (municipal hospital and dairy farm) was compared against background samples of the receiving aquatic environment (i.e. the catchment source) to determine the resistome contribution of effluents. We used metagenomics and metatranscriptomics to correlate DNA and RNA abundance and identified differentially regulated gene transcripts.

Results

We found that mean antibiotic resistance gene and transcript abundances were correlated for both hospital ( ρ  = 0.9, two-tailed P  <0.0001) and farm ( ρ  = 0.5, two-tailed P   <0.0001) effluents and that two β-lactam resistance genes ( bla GES and bla OXA ) were overexpressed in all hospital effluent samples. High β-lactam resistance gene transcript abundance was related to hospital antibiotic usage over time and hospital effluents contained antibiotic residues.

Conclusions

We conclude that effluents contribute high levels of antibiotic resistance genes to the aquatic environment; these genes are expressed at significant levels and are possibly related to the level of antibiotic usage at the effluent source.

A sensitive short read homology search tool for paired-end read sequencing data

Background

Homology search is still a significant step in functional analysis for genomic data. Profile Hidden Markov Model-based homology search has been widely used in protein domain analysis in many different species. In particular, with the fast accumulation of transcriptomic data of non-model species and metagenomic data, profile homology search is widely adopted in integrated pipelines for functional analysis. While the state-of-the-art tool HMMER has achieved high sensitivity and accuracy in domain annotation, the sensitivity of HMMER on short reads declines rapidly. The low sensitivity on short read homology search can lead to inaccurate domain composition and abundance computation. Our experimental results showed that half of the reads were missed by HMMER for a RNA-Seq dataset. Thus, there is a need for better methods to improve the homology search performance for short reads.

Results

We introduce a profile homology search tool named Short-Pair that is designed for short paired-end reads. By using an approximate Bayesian approach employing distribution of fragment lengths and alignment scores, Short-Pair can retrieve the missing end and determine true domains. In particular, Short-Pair increases the accuracy in aligning short reads that are part of remote homologs. We applied Short-Pair to a RNA-Seq dataset and a metagenomic dataset and quantified its sensitivity and accuracy on homology search. The experimental results show that Short-Pair can achieve better overall performance than the state-of-the-art methodology of profile homology search.

Conclusions

Short-Pair is best used for next-generation sequencing (NGS) data that lack reference genomes. It provides a complementary paired-end read homology search tool to HMMER. The source code is freely available at https://sourceforge.net/projects/short-pair/.

Evolutionary Biology Needs Wild Microbiomes

The microbiome is a vital component to the evolution of a host and much of what we know about the microbiome derives from studies on humans and captive animals. But captivity alters the microbiome and mammals have unique biological adaptations that affect their microbiomes (e.g., milk). Birds represent over 30% of known tetrapod diversity and possess their own suite of adaptations relevant to the microbiome. In a previous study, we showed that 59 species of birds displayed immense variation in their microbiomes and host (bird) taxonomy and ecology were most correlated with the gut microbiome. In this Frontiers Focused Review, I put those results in a broader context by discussing how collecting and analyzing wild microbiomes contributes to the main goals of evolutionary biology and the specific ways that birds are unique microbial hosts. Finally, I outline some of the methodological considerations for adding microbiome sampling to the research of wild animals and urge researchers to do so. To truly understand the evolution of a host, we need to understand the millions of microorganisms that inhabit it as well: evolutionary biology needs wild microbiomes.

Interactions of Freshwater Cyanobacteria with Bacterial Antagonists

Cyanobacterial and algal mass development, or blooms, have severe effects on freshwater and marine systems around the world. Many of these phototrophs produce a variety of potent toxins, contribute to oxygen depletion, and affect water quality in several ways. Coexisting antagonists, such as cyanolytic bacteria, hold the potential to suppress, or even terminate, such blooms, yet the nature of this interaction is not well studied. We isolated 31 cyanolytic bacteria affiliated with the genera Pseudomonas, Stenotrophomonas, Acinetobacter, and Delftia from three eutrophic freshwater lakes in Sweden and selected four phylogenetically diverse bacterial strains with strong-to-moderate lytic activity. To characterize their functional responses to the presence of cyanobacteria, we performed RNA sequencing (RNA-Seq) experiments on coculture incubations, with an initial predator-prey ratio of 1:1. Genes involved in central cellular pathways, stress-related heat or cold shock proteins, and antitoxin genes were highly expressed in both heterotrophs and cyanobacteria. Heterotrophs in coculture expressed genes involved in cell motility, signal transduction, and putative lytic activity. l,d-Transpeptidase was the only significantly upregulated lytic gene in Stenotrophomonas rhizophila EK20. Heterotrophs also shifted their central metabolism from the tricarboxylic acid cycle to the glyoxylate shunt. Concurrently, cyanobacteria clearly show contrasting antagonistic interactions with the four tested heterotrophic strains, which is also reflected in the physical attachment to their cells. In conclusion, antagonistic interactions with cyanobacteria were initiated within 24 h, and expression profiles suggest varied responses for the different cyanobacteria and studied cyanolytes.IMPORTANCE Here, we present how gene expression profiles can be used to reveal interactions between bloom-forming freshwater cyanobacteria and antagonistic heterotrophic bacteria. Species-specific responses in both heterotrophs and cyanobacteria were identified. The study contributes to a better understanding of the interspecies cellular interactions underpinning the persistence and collapse of cyanobacterial blooms.

Do biofilm communities respond to the chemical signatures of fracking? A test involving streams in North-central Arkansas

Background

Unconventional natural gas (UNG) extraction (fracking) is ongoing in 29 North American shale basins (20 states), with ~6000 wells found within the Fayetteville shale (north-central Arkansas). If the chemical signature of fracking is detectable in streams, it can be employed to bookmark potential impacts. We evaluated benthic biofilm community composition as a proxy for stream chemistry so as to segregate anthropogenic signatures in eight Arkansas River catchments. In doing so, we tested the hypothesis that fracking characteristics in study streams are statistically distinguishable from those produced by agriculture or urbanization.

Results

Four tributary catchments had UNG-wells significantly more dense and near to our sampling sites and were grouped as ‘potentially-impacted catchment zones’ (PICZ). Four others were characterized by significantly larger forested area with greater slope and elevation but reduced pasture, and were classified as ‘minimally-impacted’ (MICZ). Overall, 46 bacterial phyla/141 classes were identified, with 24 phyla (52%) and 54 classes (38%) across all samples. PICZ-sites were ecologically more variable than MICZ-sites, with significantly greater nutrient levels (total nitrogen, total phosphorous), and elevated Cyanobacteria as bioindicators that tracked these conditions. PICZ-sites also exhibited elevated conductance (a correlate of increased ion concentration) and depressed salt-intolerant Spartobacteria, suggesting the presence of brine as a fracking effect. Biofilm communities at PICZ-sites were significantly less variable than those at MICZ-sites.

Conclusions

Study streams differed by Group according to morphology, land use, and water chemistry but not in biofilm community structure. Those at PICZ-sites covaried according to anthropogenic impact, and were qualitatively similar to communities found at sites disturbed by fracking. The hypothesis that fracking signatures in study streams are distinguishable from those produced by other anthropogenic effects was statistically rejected. Instead, alterations in biofilm community composition, as induced by fracking, may be less specific than initially predicted, and thus more easily confounded by agriculture and urbanization effects (among others). Study streams must be carefully categorized with regard to the magnitude and extent of anthropogenic impacts. They must also be segregated with statistical confidence (as herein) before fracking impacts are monitored.

Metagenomic Approaches to Identify Novel Organisms from the Soil Environment in a Classroom Setting

Molecular Microbial Metagenomics is a research-based undergraduate course developed at Georgia State University. This semester-long course provides hands-on research experience in the area of microbial diversity and introduces molecular approaches to study diversity. Students are part of an ongoing research project that uses metagenomic approaches to isolate clones containing 16S ribosomal ribonucleic acid (rRNA) genes from a soil metagenomic library. These approaches not only provide a measure of microbial diversity in the sample but may also allow discovery of novel organisms. Metagenomic approaches differ from the traditional culturing methods in that they use molecular analysis of community deoxyribonucleic acid (DNA) instead of culturing individual organisms. Groups of students select a batch of 100 clones from a metagenomic library. Using universal primers to amplify 16S rRNA genes from the pool of DNA isolated from 100 clones, and a stepwise process of elimination, each group isolates individual clones containing 16S rRNA genes within their batch of 100 clones. The amplified 16S rRNA genes are sequenced and analyzed using bioinformatics tools to determine whether the rRNA gene belongs to a novel organism. This course provides avenues for active learning and enhances students' conceptual understanding of microbial diversity. Average scores on six assessment methods used during field testing indicated that success in achieving different learning objectives varied between 84% and 95%, with 65% of the students demonstrating complete grasp of the project based on the end-of-project lab report. The authentic research experience obtained in this course is also expected to result in more undergraduates choosing research-based graduate programs or careers.

The information science of microbial ecology

A revolution is unfolding in microbial ecology where petabytes of 'multi-omics' data are produced using next generation sequencing and mass spectrometry platforms. This cornucopia of biological information has enormous potential to reveal the hidden metabolic powers of microbial communities in natural and engineered ecosystems. However, to realize this potential, the development of new technologies and interpretative frameworks grounded in ecological design principles are needed to overcome computational and analytical bottlenecks. Here we explore the relationship between microbial ecology and information science in the era of cloud-based computation. We consider microorganisms as individual information processing units implementing a distributed metabolic algorithm and describe developments in ecoinformatics and ubiquitous computing with the potential to eliminate bottlenecks and empower knowledge creation and translation.

Bacterial community composition of an urban river in the North West Province, South Africa, in relation to physico-chemical water quality

The aim of this study was to determine the impacts of anthropogenic disturbances on bacterial community composition in an urban river (Mooi River). Physico-chemical analysis, bacterial enumeration and 454-pyrosequencing were conducted on the Mooi River system upstream and downstream of an urban settlement in the North West Province, South Africa. Pyrosequencing and multivariate analysis showed that nutrient inputs and faecal pollution strongly impacted the physico-chemical and microbiological quality at the downstream sites. Also, bacterial communities showed higher richness and evenness at the downstream sites. Multivariate analysis suggested that the abundances of Betaproteobacteria, Epsilonproteobacteria, Acidobacteria, Bacteroidetes and Verrucomicrobia are related to temperature, pH, dissolved oxygen (DO), sulphate and chlorophyll-a levels. These results suggest that urbanisation caused the overall water quality of this river to deteriorate, which in turn affected the bacterial community composition. In addition, our work identified potential indicator groups that may be used to track faecal and organic pollution in freshwater systems.

Marine metagenomics as a source for bioprospecting

This review summarizes usage of genome-editing technologies for metagenomic studies; these studies are used to retrieve and modify valuable microorganisms for production, particularly in marine metagenomics. Organisms may be cultivable or uncultivable. Metagenomics is providing especially valuable information for uncultivable samples. The novel genes, pathways and genomes can be deducted. Therefore, metagenomics, particularly genome engineering and system biology, allows for the enhancement of biological and chemical producers and the creation of novel bioresources. With natural resources rapidly depleting, genomics may be an effective way to efficiently produce quantities of known and novel foods, livestock feed, fuels, pharmaceuticals and fine or bulk chemicals.

Core-satellite populations and seasonality of water meter biofilms in a metropolitan drinking water distribution system

Drinking water distribution systems (DWDSs) harbor the microorganisms in biofilms and suspended communities, yet the diversity and spatiotemporal distribution have been studied mainly in the suspended communities. This study examined the diversity of biofilms in an urban DWDS, its relationship with suspended communities and its dynamics. The studied DWDS in Urbana, Illinois received conventionally treated and disinfected water sourced from the groundwater. Over a 2-year span, biomass were sampled from household water meters (n=213) and tap water (n=20) to represent biofilm and suspended communities, respectively. A positive correlation between operational taxonomic unit (OTU) abundance and occupancy was observed. Examined under a 'core-satellite' model, the biofilm community comprised 31 core populations that encompassed 76.7% of total 16 S rRNA gene pyrosequences. The biofilm communities shared with the suspended community highly abundant and prevalent OTUs, which related to methano-/methylotrophs (i.e., Methylophilaceae and Methylococcaceae) and aerobic heterotrophs (Sphingomonadaceae and Comamonadaceae), yet differed by specific core populations and lower diversity and evenness. Multivariate tests indicated seasonality as the main contributor to community structure variation. This pattern was resilient to annual change and correlated to the cyclic fluctuations of core populations. The findings of a distinctive biofilm community assemblage and methano-/methyltrophic primary production provide critical insights for developing more targeted water quality monitoring programs and treatment strategies for groundwater-sourced drinking water systems.

Thermodynamics and H2 Transfer in a Methanogenic, Syntrophic Community

Microorganisms in nature do not exist in isolation but rather interact with other species in their environment. Some microbes interact via syntrophic associations, in which the metabolic by-products of one species serve as nutrients for another. These associations sustain a variety of natural communities, including those involved in methanogenesis. In anaerobic syntrophic communities, energy is transferred from one species to another, either through direct contact and exchange of electrons, or through small molecule diffusion. Thermodynamics plays an important role in governing these interactions, as the oxidation reactions carried out by the first community member are only possible because degradation products are consumed by the second community member. This work presents the development and analysis of genome-scale network reconstructions of the bacterium Syntrophobacter fumaroxidans and the methanogenic archaeon Methanospirillum hungatei. The models were used to verify proposed mechanisms of ATP production within each species. We then identified additional constraints and the cellular objective function required to match experimental observations. The thermodynamic S. fumaroxidans model could not explain why S. fumaroxidans does not produce H₂ in monoculture, indicating that current methods might not adequately estimate the thermodynamics, or that other cellular processes (e.g., regulation) play a role. We also developed a thermodynamic coculture model of the association between the organisms. The coculture model correctly predicted the exchange of both H₂ and formate between the two species and suggested conditions under which H₂ and formate produced by S. fumaroxidans would be fully consumed by M. hungatei.

Natural and engineered microbial communities can contain up to hundreds of interacting microbes. These interactions may be positive, negative, or neutral, as well as obligate or facultative. Syntrophy is an obligate, positive interaction, in which one species lives off the metabolic by-products of another. Syntrophic associations play an important role in sustaining a variety of natural communities, including those involved in the breakdown and conversion of short-chain fatty acids (e.g., propionate) to methane. In many syntrophic communities, electrons are transferred from one species to the other through small molecule diffusion. In this work, we expand the study of a two-member syntrophic, methanogenic community through the development and analysis of computational models for both species: the bacterium Syntrophobacter fumaroxidans and the methanogenic archaeon Methanospirillum hungatei. These models were used to analyze energy conservation mechanisms within each species, as well as small molecule exchange between the two organisms in coculture. The coculture model correctly predicted the exchange of both H₂ and formate between the two species and suggested conditions under which these molecules would be fully metabolized within the community.

Metagenome Skimming of Insect Specimen Pools: Potential for Comparative Genomics

Metagenomic analyses are challenging in metazoans, but high-copy number and repeat regions can be assembled from low-coverage sequencing by "genome skimming," which is applied here as a new way of characterizing metagenomes obtained in an ecological or taxonomic context. Illumina shotgun sequencing on two pools of Coleoptera (beetles) of approximately 200 species each were assembled into tens of thousands of scaffolds. Repeated low-coverage sequencing recovered similar scaffold sets consistently, although approximately 70% of scaffolds could not be identified against existing genome databases. Identifiable scaffolds included mitochondrial DNA, conserved sequences with hits to expressed sequence tag and protein databases, and known repeat elements of high and low complexity, including numerous copies of rRNA and histone genes. Assemblies of histones captured a diversity of gene order and primary sequence in Coleoptera. Scaffolds with similarity to multiple sites in available coleopteran genome sequences for Dendroctonus and Tribolium revealed high specificity of scaffolds to either of these genomes, in particular for high-copy number repeats. Numerous "clusters" of scaffolds mapped to the same genomic site revealed intra- and/or intergenomic variation within a metagenome pool. In addition to effect of taxonomic composition of the metagenomes, the number of mapped scaffolds also revealed structural differences between the two reference genomes, although the significance of this striking finding remains unclear. Finally, apparently exogenous sequences were recovered, including potential food plants, fungal pathogens, and bacterial symbionts. The "metagenome skimming" approach is useful for capturing the genomic diversity of poorly studied, species-rich lineages and opens new prospects in environmental genomics.

Integrated omics for the identification of key functionalities in biological wastewater treatment microbial communities

Biological wastewater treatment plants harbour diverse and complex microbial communities which prominently serve as models for microbial ecology and mixed culture biotechnological processes. Integrated omic analyses (combined metagenomics, metatranscriptomics, metaproteomics and metabolomics) are currently gaining momentum towards providing enhanced understanding of community structure, function and dynamics in situ as well as offering the potential to discover novel biological functionalities within the framework of Eco-Systems Biology. The integration of information from genome to metabolome allows the establishment of associations between genetic potential and final phenotype, a feature not realizable by only considering single ‘omes’. Therefore, in our opinion, integrated omics will become the future standard for large-scale characterization of microbial consortia including those underpinning biological wastewater treatment processes. Systematically obtained time and space-resolved omic datasets will allow deconvolution of structure–function relationships by identifying key members and functions. Such knowledge will form the foundation for discovering novel genes on a much larger scale compared with previous efforts. In general, these insights will allow us to optimize microbial biotechnological processes either through better control of mixed culture processes or by use of more efficient enzymes in bioengineering applications.

BioMiCo: a supervised Bayesian model for inference of microbial community structure

BACKGROUND

Microbiome samples often represent mixtures of communities, where each community is composed of overlapping assemblages of species. Such mixtures are complex, the number of species is huge and abundance information for many species is often sparse. Classical methods have a limited value for identifying complex features within such data.

RESULTS

Here, we describe a novel hierarchical model for Bayesian inference of microbial communities (BioMiCo). The model takes abundance data derived from environmental DNA, and models the composition of each sample by a two-level hierarchy of mixture distributions constrained by Dirichlet priors. BioMiCo is supervised, using known features for samples and appropriate prior constraints to overcome the challenges posed by many variables, sparse data, and large numbers of rare species. The model is trained on a portion of the data, where it learns how assemblages of species are mixed to form communities and how assemblages are related to the known features of each sample. Training yields a model that can predict the features of new samples. We used BioMiCo to build models for three serially sampled datasets and tested their predictive accuracy across different time points. The first model was trained to predict both body site (hand, mouth, and gut) and individual human host. It was able to reliably distinguish these features across different time points. The second was trained on vaginal microbiomes to predict both the Nugent score and individual human host. We found that women having normal and elevated Nugent scores had distinct microbiome structures that persisted over time, with additional structure within women having elevated scores. The third was trained for the purpose of assessing seasonal transitions in a coastal bacterial community. Application of this model to a high-resolution time series permitted us to track the rate and time of community succession and accurately predict known ecosystem-level events.

CONCLUSION

BioMiCo provides a framework for learning the structure of microbial communities and for making predictions based on microbial assemblages. By training on carefully chosen features (abiotic or biotic), BioMiCo can be used to understand and predict transitions between complex communities composed of hundreds of microbial species.

Gut Health in the era of the human gut microbiota: from metaphor to biovalue

The human intestinal ecosystem, previously called the gut microflora is now known as the Human Gut Microbiota (HGM). Microbiome research has emphasized the potential role of this ecosystem in human homeostasis, offering unexpected opportunities in therapeutics, far beyond digestive diseases. It has also highlighted ethical, social and commercial concerns related to the gut microbiota. As diet factors are accepted to be the major regulator of the gut microbiota, the modulation of its composition, either by antibiotics or by food intake, should be regarded as a fascinating tool for improving the human health. Scientists, the food industry, consumers and policymakers alike are involved in this new field of nutrition. Defining how knowledge about the HGM is being translated into public perception has never been addressed before. This raises the question of metaphors associated with the HGM, and how they could be used to improve public understanding, and to influence individual decision-making on healthcare policy. This article suggests that a meeting of stakeholders from the social sciences, basic research and the food industry, taking an epistemological approach to the HGM, is needed to foster close, innovative partnerships that will help shape public perception and enable novel behavioural interventions that would benefit public health.

Random whole metagenomic sequencing for forensic discrimination of soils

Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.

Marine coastal sediments microbial hydrocarbon degradation processes: contribution of experimental ecology in the omics'era

Coastal marine sediments, where important biological processes take place, supply essential ecosystem services. By their location, such ecosystems are particularly exposed to human activities as evidenced by the recent Deepwater Horizon disaster. This catastrophe revealed the importance to better understand the microbial processes involved on hydrocarbon degradation in marine sediments raising strong interests of the scientific community. During the last decade, several studies have shown the key role played by microorganisms in determining the fate of hydrocarbons in oil-polluted sediments but only few have taken into consideration the whole sediment’s complexity. Marine coastal sediment ecosystems are characterized by remarkable heterogeneity, owning high biodiversity and are subjected to fluctuations in environmental conditions, especially to important oxygen oscillations due to tides. Thus, for understanding the fate of hydrocarbons in such environments, it is crucial to study microbial activities, taking into account sediment characteristics, physical-chemical factors (electron acceptors, temperature), nutrients, co-metabolites availability as well as sediment’s reworking due to bioturbation activities. Key information could be collected from in situ studies, which provide an overview of microbial processes, but it is difficult to integrate all parameters involved. Microcosm experiments allow to dissect in-depth some mechanisms involved in hydrocarbon degradation but exclude environmental complexity. To overcome these lacks, strategies have been developed, by creating experiments as close as possible to environmental conditions, for studying natural microbial communities subjected to oil pollution. We present here a review of these approaches, their results and limitation, as well as the promising future of applying “omics” approaches to characterize in-depth microbial communities and metabolic networks involved in hydrocarbon degradation. In addition, we present the main conclusions of our studies in this field.

Research on neonatal microbiomes: what neonatologists need to know

The aim of this article is to educate neonatal caregivers about metagenomics. This scientific field uses novel and ever changing molecular methods to identify how infants become colonized with microbes after birth. Publications using metagenomics appear infrequently in the neonatal literature because clinicians are unaccustomed to the analytical techniques, data interpretation, and illustration of the results. This review covers those areas. After a brief introduction of neonatal citations forthcoming from metagenomic studies, the following topics are covered: (1) the history of metagenomics, (2) a description of current and emerging instruments used to define microbial populations in human organs, and (3) how extensive databases generated by genome analyzers are examined and presented to readers. Clinicians may feel like they are learning a new language; however, they will appreciate this task is essential to understanding and practicing neonatal medicine in the future.

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?'

Linking microbial community structure, interactions and function in anaerobic digesters using new molecular techniques

Over the last decade there has been a rapid development in culture-independent techniques for exploring microbial communities, which have led to new insights into their structure and function in both natural environments and engineered systems. This review focuses on some of the most important recent advances and their applications to the diverse microbial communities associated with anaerobic digestion. The use of these approaches in combination with complementary imaging techniques, chemical isotope analyses and detailed reactor performance measurements provides a new opportunity to develop a fundamental understanding of how microbial community dynamics, interactions and functionality influence digester efficiency and stability.