Quantifying environmental adaptation of metabolic pathways in metagenomics

EMPathways2: Estimation of Enzyme Expression and Metabolic Pathway Activity Using RNA-Seq Reads

In this chapter, we outline an approach to analyzing metatranscriptomic data, focusing on the assessment of differential enzyme expression and metabolic pathway activities using a novel bioinformatics software tool, EMPathways2. The analysis pipeline commences with raw data originating from a sequencer and concludes with an output of enzyme expressions and an estimate of metabolic pathway activities. The initial step involves aligning specific transcriptomes assembled from RNA-Seq data using Bowtie2 and acquiring gene expression data with IsoEM2. Subsequently, the pipeline proceeds to quality assessment and preprocessing of the input data, ensuring accurate estimates of enzymes and their differential regulation. Upon completion of the preprocessing stage, EMPathways2 is employed to decipher the intricate relationships between genes, enzymes, and pathways. An online repository containing sample data has been made available, alongside custom Python scripts designed to modify the output of the programs within the pipeline for diverse downstream analyses. This chapter highlights the technical aspects and practical applications of using EMPathways2, which facilitates the advancement of transcriptome data analysis and contributes to a deeper understanding of the complex regulatory mechanisms underlying living systems.

Chronic industrial perturbation and seasonal change induces shift in the bacterial community from gammaproteobacteria to betaproteobacteria having catabolic potential for aromatic compounds at Amlakhadi canal

Escalating proportions of industrially contaminated sites are one of the major catastrophes faced at the present time due to the industrial revolution. The difficulties associated with culturing the microbes, has been circumvent by the direct use of metagenomic analysis of various complex niches. In this study, a metagenomic approach using next generation sequencing technologies was applied to exemplify the taxonomic abundance and metabolic potential of the microbial community residing in Amlakhadi canal, Ankleshwar at two different seasons. All the metagenomes revealed a predominance of Proteobacteria phylum. However, difference was observed within class level where Gammaproteobacteria was relatively high in polluted metagenome in Summer while in Monsoon the abundance shifted to Betaproteobacteria. Similarly, significant statistical differences were obtained while comparing the genera amongst contaminated sites where Serratia, Achromobacter, Stenotrophomonas and Pseudomonas were abundant in summer season and the dominance changed to Thiobacillus, Thauera, Acidovorax, Nitrosomonas, Sulfuricurvum, Novosphingobium, Hyphomonas and Geobacter in monsoon. Further upon functional characterization, the microbiomes revealed the diverse survival mechanisms, in response to the prevailing ecological conditions (such as degradation of aromatic compounds, heavy metal resistance, oxidative stress responses and multidrug resistance efflux pumps, etc.). The results have important implications in understanding and predicting the impacts of human-induced activities on microbial communities inhabiting natural niche and their responses in coping with the fluctuating pollution load.

Diversity and salinity adaptations of ammonia oxidizing archaea in three estuaries of China

Ammonia-oxidizing archaea (AOA) are ubiquitously found in diverse habitats and play pivotal roles in the nitrogen and carbon cycle, especially in estuarine and coastal environments. Despite the fact that the diversity and distribution of AOA are thought to be tightly linked to habitats, little is known about the relationship that underpins their genomic traits, adaptive potentials, and ecological niches. Here, we have characterized and compared the AOA community in three estuaries of China using metagenomics. AOA were the dominant ammonia oxidizers in the three estuaries. Through phylogenetic analyses, five major AOA groups were identified, including the Nitrosomarinus-like, Nitrosopumilus-like, Aestuariumsis-like, Nitrosarchaeum-like, and Nitrosopelagicus-like groups. Statistical analyses showed that the aquatic and sedimentary AOA communities were mainly influenced by spatial factors (latitude and water depth) and environmental factors (salinity, pH, and dissolved oxygen) in estuaries, respectively. Compared to AOA dwelling in terrestrial and marine habitats, estuarine AOA encoded more genes involved in glucose and amino acid metabolism, transport systems, osmotic control, and cell motility. The low proteome isoelectric points (pI), high content of acidic amino acids, and the presence of potassium ion and mechanosensitive channels suggest a "salt-in" strategy for estuarine AOA to counteract high osmolarity in their surroundings. Our findings have indicated potential adaptation strategies and highlighted their importance in the estuarine nitrogen and carbon cycles. KEY POINTS: • Spatial and environmental factors influence water and sediment AOA respectively. • Estuarine AOA share low proteome isoelectric value and high acid amino acids content. • AOA adaptation to estuaries is likely resulted from their unique genomic features.

DNA sequencing, microbial indicators, and the discovery of buried kimberlites

Population growth and technological advancements are placing growing demand on mineral resources. New and innovative exploration technologies that improve detection of deeply buried mineralization and host rocks are required to meet these demands. Here we used diamondiferous kimberlite ore bodies as a test case and show that DNA amplicon sequencing of soil microbial communities resolves anomalies in microbial community composition and structure that reflect the surface expression of kimberlites buried under 10 s of meters of overburden. Indicator species derived from laboratory amendment experiments were employed in an exploration survey in which the species distributions effectively delineated the surface expression of buried kimberlites. Additional indicator species derived directly from field observations improved the blind discovery of kimberlites buried beneath similar overburden types. Application of DNA sequence-based analyses of soil microbial communities to mineral deposit exploration provides a powerful illustration of how genomics technologies can be leveraged in the discovery of critical new resources.

Human-induced salinity changes impact marine organisms and ecosystems

Climate change is fundamentally altering marine and coastal ecosystems on a global scale. While the effects of ocean warming and acidification on ecology and ecosystem functions and services are being comprehensively researched, less attention is directed toward understanding the impacts of human-driven ocean salinity changes. The global water cycle operates through water fluxes expressed as precipitation, evaporation, and freshwater runoff from land. Changes to these in turn modulate ocean salinity and shape the marine and coastal environment by affecting ocean currents, stratification, oxygen saturation, and sea level rise. Besides the direct impact on ocean physical processes, salinity changes impact ocean biological functions with the ecophysiological consequences are being poorly understood. This is surprising as salinity changes may impact diversity, ecosystem and habitat structure loss, and community shifts including trophic cascades. Climate model future projections (of end of the century salinity changes) indicate magnitudes that lead to modification of open ocean plankton community structure and habitat suitability of coral reef communities. Such salinity changes are also capable of affecting the diversity and metabolic capacity of coastal microorganisms and impairing the photosynthetic capacity of (coastal and open ocean) phytoplankton, macroalgae, and seagrass, with downstream ramifications on global biogeochemical cycling. The scarcity of comprehensive salinity data in dynamic coastal regions warrants additional attention. Such datasets are crucial to quantify salinity-based ecosystem function relationships and project such changes that ultimately link into carbon sequestration and freshwater as well as food availability to human populations around the globe. It is critical to integrate vigorous high-quality salinity data with interacting key environmental parameters (e.g., temperature, nutrients, oxygen) for a comprehensive understanding of anthropogenically induced marine changes and its impact on human health and the global economy.

Functional comparison of metabolic networks across species

Metabolic phenotypes are pivotal for many areas, but disentangling how evolutionary history and environmental adaptation shape these phenotypes is an open problem. Especially for microbes, which are metabolically diverse and often interact in complex communities, few phenotypes can be determined directly. Instead, potential phenotypes are commonly inferred from genomic information, and rarely were model-predicted phenotypes employed beyond the species level. Here, we propose sensitivity correlations to quantify similarity of predicted metabolic network responses to perturbations, and thereby link genotype and environment to phenotype. We show that these correlations provide a consistent functional complement to genomic information by capturing how network context shapes gene function. This enables, for example, phylogenetic inference across all domains of life at the organism level. For 245 bacterial species, we identify conserved and variable metabolic functions, elucidate the quantitative impact of evolutionary history and ecological niche on these functions, and generate hypotheses on associated metabolic phenotypes. We expect our framework for the joint interpretation of metabolic phenotypes, evolution, and environment to help guide future empirical studies.

Structural diversity of bacterial communities in two divergent sunflower rhizosphere soils

Purpose

Farming practices on farmlands aim to improve nutrients in the fields or crops, soil quality and functions, as well as boost and sustain crop yield; however, the effect of loss of ecological diversity and degradation have impacted ecosystem functions. The beneficial rhizosphere-microorganism network and crop rotation may enhance a stable ecosystem. The use of next-generation sequencing technique will help characterize the entire bacterial species in the sunflower rhizosphere compared with the nearby bulk soils. We investigated the potential of the bacterial community structure of sunflower rhizosphere and bulk soils cultivated under different agricultural practices at two geographical locations in the North West Province of South Africa.

Methods

DNA was extracted from rhizosphere and bulk soils associated with sunflower plants from the crop rotation (rhizosphere soils from Lichtenburg (LTR) and bulk soils from Lichtenburg (LTB) and mono-cropping (rhizosphere soils from Krayburg (KRPR) and bulk soils from Krayburg (KRPB) sites, and sequenced employing 16S amplicon sequencing. Bioinformatics tools were used to analyse the sequenced dataset.

Results

Proteobacteria and Planctomycetes dominated the rhizosphere, while Firmicutes and Actinobacteria were predominant in bulk soils. Significant differences in bacterial structure at phyla and family levels and predicted functional categories between soils (P < 0.05) across the sites were revealed. The effect of physicochemical parameters was observed to influence bacterial dispersal across the sites.

Conclusion

This study provides information on the predominant bacterial community structure in sunflower soils and their predictive functional attributes at the growing stage, which suggests their future study for imminent crop production and management for enhanced agricultural yields.

Discovering untapped microbial communities through metagenomics for microplastic remediation: recent advances, challenges, and way forward

Microplastics (MPs) are ubiquitous pollutants persisting almost everywhere in the environment. With the increase in anthropogenic activities, MP accumulation is increasing enormously in aquatic, marine, and terrestrial ecosystems. Owing to the slow degradation of plastics, MPs show an increased biomagnification probability of persistent, bioaccumulative, and toxic substances thereby creating a threat to environmental biota. Thus, remediation of MP-pollutants requires efficient strategies to circumvent the mobilization of contaminants leaching into the water, soil, and ultimately to human beings. Over the years, several microorganisms have been characterized by the potential to degrade different plastic polymers through enzymatic actions. Metagenomics (MGs) is an effective way to discover novel microbial communities and access their functional genetics for the exploration and characterization of plastic-degrading microbial consortia and enzymes. MGs in combination with metatranscriptomics and metabolomics approaches are a powerful tool to identify and select remediation-efficient microbes in situ. Advancement in bioinformatics and sequencing tools allows rapid screening, mining, and prediction of genes that are capable of polymer degradation. This review comprehensively summarizes the growing threat of microplastics around the world and highlights the role of MGs and computational biology in building effective response strategies for MP remediation.

Functional Diversity of Microbial Communities in the Soybean (Glycine max L.) Rhizosphere from Free State, South Africa

The plant microbiome is involved in enhancing nutrient acquisition, plant growth, stress tolerance, and reducing chemical inputs. The identification of microbial functional diversity offers the chance to evaluate and engineer them for various agricultural processes. Using a shotgun metagenomics technique, this study examined the functional diversity and metabolic potentials of microbial communities in the rhizosphere of soybean genotype link 678. The dominant genera are Geobacter, Nitrobacter, Burkholderia, Candidatus, Bradyrhizobium and Streptomyces. Twenty-one functional categories were present, with fourteen of the functions being dominant in all samples. The dominant functions include carbohydrates, fatty acids, lipids and isoprenoids, amino acids and derivatives, sulfur metabolism, and nitrogen metabolism. A Kruskal–Wallis test was used to test samples’ diversity differences. There was a significant difference in the alpha diversity. ANOSIM was used to analyze the similarities of the samples and there were significant differences between the samples. Phosphorus had the highest contribution of 64.3% and was more prominent among the soil properties that influence the functional diversity of the samples. Given the functional groups reported in this study, soil characteristics impact the functional role of the rhizospheric microbiome of soybean.

Metagenomic evidence for the microbial transformation of carboxyl-rich alicyclic molecules: A long-term macrocosm experiment

Carboxyl-rich alicyclic molecules (CRAMs) widely exist in the ocean and constitute the central part of the refractory dissolved organic matter (RDOM) pool. Although a consensus has been reached that microbial activity forms CRAMs, the detailed molecular mechanisms remain largely unexplored. To better understand the underlying genetic mechanisms driving the microbial transformation of CRAM, a long-term macrocosm experiment spanning 220 days was conducted in the Aquatron Tower Tank at Dalhousie University, Halifax, Canada, with the supply of diatom-derived DOM as a carbon source. The DOM composition, community structure, and metabolic pathways were characterised using multi-omics approaches. The addition of diatom lysate introduced a mass of labile DOM into the incubation seawater, which led to a low degradation index (I_DEG) and refractory molecular lability boundary (RMLB) on days 1 and 18. The molecular compositions of the DOM molecules in the later incubation period (from day 120 to day 220) were more similar in composition to those on day 0, suggesting a rapid turnover of phytoplankton debris by microbial communities. Taxonomically, while Alpha proteobacteria dominated during the entire incubation period, Gamma proteobacteria became more sensitive and abundant than the other bacterial groups on days 1 and 18. Recalcitrant measurements such as I_DEG and RMLB were closely related to the DOM molecules, bacterial community, and Kyoto encyclopaedia of Genes and Genomes (KEGG) modules, suggesting close associations between RDOM accumulation and microbial metabolism. KEGG modules that showed strong positive correlation with CRAMs were identified using a microbial ecological network approach. The identified KEGG modules produced the substrates, such as the acetyl-CoA or 3‑hydroxy-3-methylglutaryl-CoA, which could participate in the mevalonate pathway to generate the precursor of CRAM analogues, isopentenyl-PP, suggesting a potential generation pathway of CRAM analogues in bacteria and archaea. This study revealed the potential genetic and molecular processes involved in the microbial origin of CRAM analogues, and thus indicated a vital ecological role of bacteria and archaea in RDOM production. This study also offered new perspectives on the carbon sequestration in the ocean.

Seasonal variation influences flavonoid biosynthesis path and content, and antioxidant activity of metabolites in Tetrastigma hemsleyanum Diels & Gilg

Environmental conditions contribute to plant growth and metabolism. This study aimed to determine a suitable environment and climate for large-scale artificial cultivation of an endangered plant, Tetrastigma hemsleyanum, by investigating the seasonal variations influencing the flavonoid biosynthetic selectivity and antioxidant activity of its major metabolites. Under conditions of precipitation (2.0~6.6 mm), temperature (17.5~24.1°C), humidity (67.3~80.2%), and sunshine duration (3.4~5.8 h) from April to May, the total flavonoid content in T. hemsleyanum reached higher levels between 281.3 and 392.8 μg/g. In the second half of April, the production selectivity (PS) of isoorientin (IsoO), orientin (Or), rutin (Rut), isoquercitin (IsoQ), kaempferol-3-O-rutinoside (Km3rut), astragalin (Ast), quercetin (Qu), apigenin (Ap), and kaempferol (Km) were 0.30, 0.06, 0.07, 0.07, 0.00, 0.04, 0.38, 0.05, and 0.03, respectively. Naringenin was dehydrogenated or hydroxylated to initiate two parallel reaction pathways for flavonoid biosynthesis in T. hemsleyanum: path I subsequently generated flavone derivatives including apigenin, luteolin, orientin, and isoorientin, and path II subsequently generated flavonol derivatives including Km, Qu, IsoQ, Rut, Ast, and Km3rut. The reaction selectivity of path II (RPSII) from January 1 to September 30 was considerably higher than that of path I (RPSI), except for March 16-31. In addition, either the content or antioxidant activity of three major metabolites in T. hemsleyanum followed the order of phenolic compounds > polysaccharides > sterols, and exhibited dynamic correlations with environmental factors. Naringenin favored hydroxylation and derived six flavonol compounds from January to September, and favored dehydrogenation and derived three flavone compounds from October to December. In most months of a year, Km preferentially favored hydroxylation rather than glucosylation.

Impact of cropping systems on the functional diversity of rhizosphere microbial communities associated with maize plant: a shotgun approach

Understanding the functions carried out by rhizosphere microbiomes will further explore their importance in biotechnological improvement and agricultural sustainability. This study presents one of the foremost attempts to understand the functional diversity of the rhizosphere microbiome in mono-cropping and crop rotation farming sites using shotgun metagenomic techniques. We hypothesized that the functional diversity would vary in the cropping sites and more abundant in the rotational cropping site. Hence, we carried out complete DNA extraction from the bulk and rhizospheric soils associated with maize plant cultivated on the mono-cropping farm (LT and LTc) and the crop rotation farm (VD and VDc), respectively, and sequenced employing shotgun approach. Using the SEED subsystem, our result revealed that a total of 24 functional categories dominated the rotational cropping site, while four functional categories dominated the mono-cropping sites. Alpha diversity assessment showed that no significant difference (p > 0.05) was observed across the cropping sites, while beta diversity assessment revealed a significant difference. Going by the high abundance of functional groups observed in the samples from the crop rotational site, it is evident that cropping systems influenced the functions of soil microbiomes. Worthy of note is the high abundance of unknown functions associated with these maize rhizosphere microbiomes. This is an indication that there are still some under-investigated functional genes associated with the maize rhizosphere microbiome. It is, therefore, imperative that further studies explore these functional genes for their agricultural and biotechnological potentials.

The Composition and Primary Metabolic Potential of Microbial Communities Inhabiting the Surface Water in the Equatorial Eastern Indian Ocean

Simple Summary

Marine microbes are regarded as the most diverse organisms in the biosphere and drive biogeochemical cycles through their metabolism. It is essential to understand the structure and metabolic function of microbial communities. The Indian Ocean is the third largest ocean in the world, and it possesses unique hydrographical properties. So far, assessments of microbial diversity and metabolism need to be improved in the Indian Ocean. Therefore, we carried out a series of investigations in the equatorial eastern Indian Ocean in order to clarify the local microbial communities and detect the genetic potential for microbial functions. The obtained results suggested Cyanobacteria was the dominant microbial group, and predicted the Calvin cycle and the assimilatory nitrate and nitrite reduction played important role in the pathway of carbon fixation and nitrogen metabolism respectively. This study provides insights into microbial community structures as well as the metabolic potential that may be active in the local environment, and lays the groundwork for understanding the roles of microbes in energy and resource cycling in this habitat.

Abstract

Currently, there is scant information about the biodiversity and functional diversity of microbes in the eastern Indian Ocean (EIO). Here, we used a combination of high-throughput sequencing of 16S rRNA genes and a metagenomic approach to investigate the microbial population structure and its metabolic function in the equatorial EIO. Our results show that Cyanobacterial Prochlorococcus made up the majority of the population. Interestingly, there were fewer contributions from clades SAR11 (Alphaproteobacteria) and SAR86 (Gammaproteobacteria) to microbial communities than contributions from Prochlorococcus. Based on functional gene analysis, functional genes rbcL, narB, and nasA were relatively abundant among the relevant genes. The abundance of Prochlorococcus implies its typically ecological adaptation in the local ecosystem. The microbial metabolic potential shows that in addition to the main carbon fixation pathway Calvin cycle, the rTCA cycle and the 3-HP/4-HB cycle have potential alternative carbon fixation contributions to local ecosystems. For the nitrogen cycle, the assimilatory nitrate and nitrite reduction pathway is potentially the crucial form of nitrogen utilization; unexpectedly, nitrogen fixation activity was relatively weak. This study extends our knowledge of the roles of microbes in energy and resource cycling in the EIO and provides a foundation for revealing profound biogeochemical processes driven by the microbial community in the ocean.

Biogeographic and Evolutionary Patterns of Trace Element Utilization in Marine Microbial World

Trace elements are required by all organisms, which are key components of many enzymes catalyzing important biological reactions. Many trace element-dependent proteins have been characterized; however, little is known about their occurrence in microbial communities in diverse environments, especially the global marine ecosystem. Moreover, the relationships between trace element utilization and different types of environmental stressors are unclear. In this study, we used metagenomic data from the Global Ocean Sampling expedition project to identify the biogeographic distribution of genes encoding trace element-dependent proteins (for copper, molybdenum, cobalt, nickel, and selenium) in a variety of marine and non-marine aquatic samples. More than 56,000 metalloprotein and selenoprotein genes corresponding to nearly 100 families were predicted, becoming the largest dataset of marine metalloprotein and selenoprotein genes reported to date. In addition, samples with enriched or depleted metalloprotein/selenoprotein genes were identified, suggesting an active or inactive usage of these micronutrients in various sites. Further analysis of interactions among the elements showed significant correlations between some of them, especially those between nickel and selenium/copper. Finally, investigation of the relationships between environmental conditions and metalloprotein/selenoprotein families revealed that many environmental factors might contribute to the evolution of different metalloprotein and/or selenoprotein genes in the marine microbial world. Our data provide new insights into the utilization and biological roles of these trace elements in extant marine microbes, and might also be helpful for the understanding of how these organisms have adapted to their local environments.

Sequencing effort dictates gene discovery in marine microbial metagenomes

Massive metagenomic sequencing combined with gene prediction methods were previously used to compile the gene catalogue of the ocean and host-associated microbes. Global expeditions conducted over the past 15 years have sampled the ocean to build a catalogue of genes from pelagic microbes. Here we undertook a large sequencing effort of a perturbed Red Sea plankton community to uncover that the rate of gene discovery increases continuously with sequencing effort, with no indication that the retrieved 2.83 million non-redundant (complete) genes predicted from the experiment represented a nearly complete inventory of the genes present in the sampled community (i.e., no evidence of saturation). The underlying reason is the Pareto-like distribution of the abundance of genes in the plankton community, resulting in a very long tail of millions of genes present at remarkably low abundances, which can only be retrieved through massive sequencing. Microbial metagenomic projects retrieve a variable number of unique genes per Tera base-pair (Tbp), with a median value of 14.7 million unique genes per Tbp sequenced across projects. The increase in the rate of gene discovery in microbial metagenomes with sequencing effort implies that there is ample room for new gene discovery in further ocean and holobiont sequencing studies.

Microbial tropicalization driven by a strengthening western ocean boundary current

Western boundary currents (WBCs) redistribute heat and oligotrophic seawater from the tropics to temperate latitudes, with several displaying substantial climate change-driven intensification over the last century. Strengthening WBCs have been implicated in the poleward range expansion of marine macroflora and fauna, however, the impacts on the structure and function of temperate microbial communities are largely unknown. Here we show that the major subtropical WBC of the South Pacific Ocean, the East Australian Current (EAC), transports microbial assemblages that maintain tropical and oligotrophic (k-strategist) signatures, to seasonally displace more copiotrophic (r-strategist) temperate microbial populations within temperate latitudes of the Tasman Sea. We identified specific characteristics of EAC microbial assemblages compared with non-EAC assemblages, including strain transitions within the SAR11 clade, enrichment of Prochlorococcus, predicted smaller genome sizes and shifts in the importance of several functional genes, including those associated with cyanobacterial photosynthesis, secondary metabolism and fatty acid and lipid transport. At a temperate time-series site in the Tasman Sea, we observed significant reductions in standing stocks of total carbon and chlorophyll a, and a shift towards smaller phytoplankton and carnivorous copepods, associated with the seasonal impact of the EAC microbial assemblage. In light of the substantial shifts in microbial assemblage structure and function associated with the EAC, we conclude that climate-driven expansions of WBCs will expand the range of tropical oligotrophic microbes, and potentially profoundly impact the trophic status of temperate waters.

Gut microbiota metagenomics in aquaculture: factors influencing gut microbiome and its physiological role in fish

Fish gut microbiome confers various effects to the host fish; this includes overall size, metabolism, feeding behaviour and immune response in the fish. The emergence of antimicrobial‐resistant (AMR) bacteria and hard to cure fish diseases warrant the possible utilization of gut microbes that exhibits a positive effect on the fish and thus lead to the usage of these microbes as probiotics. The widespread and systematic use of antibiotics has led to severe biological and ecological problems, especially the development of antibiotic resistance that affects the gut microbiota of aquatic organisms. Probiotics are proposed as an effective and environmentally friendly alternative to antibiotics, known as beneficial microbes. At the same time, prebiotics are considered beneficial to the host's health and growth by decreasing the prevalence of intestinal pathogens and/or changing the development of bacterial metabolites related to health. Uprise of sequencing technology and the development of intricate bioinformatics tools has provided a way to study these gut microbes through metagenomic analysis. From various metagenomic studies, ample of information was obtained; such information includes the effect of the gut microbiome on the physiology of fish, gut microbe composition of different fish, factors affecting the gut microbial composition of the fish and the immunological effect of gut microbes in fish; such this information related to the fish gut microbiome, their function and their importance in aquaculture is discussed in this review.

Intestinal responses of the oriental fruit fly Bactrocera dorsalis (Hendel) after ingestion of an entomopathogenic bacterium strain

BACKGROUND

Bactrocera dorsalis (Hendel) is the main fruit fly pest of tropical and subtropical countries. The application of insecticides to manage this pest has led to serious resistance problems; therefore, new ways to control B. dorsalis are required. Pathogenic bacteria are sources of biocontrol agents for pest management.

RESULTS

We determined that a pathogenic bacterial strain, Serratia marcescens PS-1, isolated from a moribund striped flea beetle (Phyllotreta striolata), was lethal to B. dorsalis adults following ingestion. Histological analyses revealed that PS-1 damaged the intestinal epithelium, resulting in cell death within 24 h. We then generated a gut transcriptomic data set using RNA-Seq at two time points (6 and 24 h) after PS-1 infection. We found that genes encoding the peritrophic matrix constituent were down-regulated, whereas genes involved in lipid and glycan metabolism, and renewal of the gut epithelium, along with genes encoding digestive enzymes and stress response factors, were up-regulated. In addition, 14 cecropin genes were identified and cloned from B. dorsalis. To our knowledge, the number of cecropins identified in the present study is greater than that reported in the insects of earlier studies. Moreover, some of the cecropins identified were significantly down-regulated after PS-1 treatment.

CONCLUSION

Our findings provide new insights into the insect gut response to pathogenic bacterial invasion and may aid the development of new strategies for the biological control of B. dorsalis. © 2019 Society of Chemical Industry.

Profiling the Functional Diversity of Termite Mound Soil Bacteria as Revealed by Shotgun Sequencing

Profiling the metabolic processes performed by bacteria is vital both for understanding and for manipulating ecosystems for industrial or research purposes. In this study we aim to assess the bacterial functional diversity in termite mound soils with the assumption that significant differences will be observed in the functional diversity of bacteria between the termite mound soils and their surrounding soils and that each environment has a distinguishing metabolic profile. Here, metagenomic DNA extracted from termite mound soils and their corresponding surrounding soils, which are 10 m apart, were sequenced using a shotgun sequencing approach. Our results revealed that the relative abundances of 16 functional categories differed significantly between both habitats. The α diversity analysis indicated no significant difference in bacterial functional categories within the habitats while the β diversity showed that the bacterial functional categories varied significantly between the termite mound soils and the surrounding soil samples. The variations in soil physical and chemical properties existing between the two environments were held accountable for the differences in bacterial functional structure. With the high relative abundance of functional categories with unknown function reported in this study, this could signify the likelihood of getting novel genes from termite mound soils, which are needed for research and commercial applications.

Pangenomic Approach To Understanding Microbial Adaptations within a Model Built Environment, the International Space Station, Relative to Human Hosts and Soil

Understanding underlying mechanisms involved in microbial persistence in the built environment (BE) is essential for strategically mitigating potential health risks. To test the hypothesis that BEs impose selective pressures resulting in characteristic adaptive responses, we performed a pangenomics meta-analysis leveraging 189 genomes (accessed from GenBank) of two epidemiologically important taxa, Bacillus cereus and Staphylococcus aureus, isolated from various origins: the International Space Station (ISS; a model BE), Earth-based BEs, soil, and humans. Our objectives were to (i) identify differences in the pangenomic composition of generalist and host-associated organisms, (ii) characterize genes and functions involved in BE-associated selection, and (iii) identify genomic signatures of ISS-derived strains of potential relevance for astronaut health. The pangenome of B. cereus was more expansive than that of S. aureus, which had a dominant core component. Genomic contents of both taxa significantly correlated with isolate origin, demonstrating an importance for biogeography and potential niche adaptations. ISS/BE-enriched functions were often involved in biosynthesis, catabolism, materials transport, metabolism, and stress response. Multiple origin-enriched functions also overlapped across taxa, suggesting conserved adaptive processes. We further characterized two mobile genetic elements with local neighborhood genes encoding biosynthesis and stress response functions that distinctively associated with B. cereus from the ISS. Although antibiotic resistance genes were present in ISS/BE isolates, they were also common in counterparts elsewhere. Overall, despite differences in microbial lifestyle, some functions appear common to remaining viable in the BE, and those functions are not typically associated with direct impacts on human health. IMPORTANCE The built environment contains a variety of microorganisms, some of which pose critical human health risks (e.g., hospital-acquired infection, antibiotic resistance dissemination). We uncovered a combination of complex biological functions that may play a role in bacterial survival under the presumed selective pressures in a model built environment-the International Space Station-by using an approach to compare pangenomes of bacterial strains from two clinically relevant species (B. cereus and S. aureus) isolated from both built environments and humans. Our findings suggest that the most crucial bacterial functions involved in this potential adaptive response are specific to bacterial lifestyle and do not appear to have direct impacts on human health.

Coupling biogeochemical process rates and metagenomic blueprints of coastal bacterial assemblages in the context of environmental change

Bacteria are major drivers of biogeochemical nutrient cycles and energy fluxes in marine environments, yet how bacterial communities respond to environmental change is not well known. Metagenomes allow examination of genetic responses of the entire microbial community to environmental change. However, it is challenging to link metagenomes directly to biogeochemical process rates. Here, we investigate metagenomic responses in natural bacterioplankton communities to simulated environmental stressors in the Baltic Sea, including increased river water input, increased nutrient concentration, and reduced oxygen level. This allowed us to identify informative prokaryotic gene markers, responding to environmental perturbation. Our results demonstrate that metagenomic and metabolic changes in bacterial communities in response to environmental stressors are influenced both by the initial community composition and by the biogeochemical factors shaping the functional response. Furthermore, the different sources of dissolved organic matter (DOM) had the largest impact on metagenomic blueprint. Most prominently, changes in DOM loads influenced specific transporter types reflecting the substrate availability and DOC assimilation and consumption pathways. The results provide new knowledge for developing models of ecosystem structure and biogeochemical cycling in future climate change scenarios and advance our exploration of the potential use of marine microorganisms as markers for environmental conditions.

The diversity of uncharacterized antibiotic resistance genes can be predicted from known gene variants-but not always

BACKGROUND

Antibiotic resistance is considered one of the most urgent threats to modern healthcare, and the role of the environment in resistance development is increasingly recognized. It is often assumed that the abundance and diversity of known resistance genes are representative also for the non-characterized fraction of the resistome in a given environment, but this assumption has not been verified. In this study, this hypothesis is tested, using the resistance gene profiles of 1109 metagenomes from various environments.

RESULTS

This study shows that the diversity and abundance of known antibiotic resistance genes can generally predict the diversity and abundance of undescribed resistance genes. However, the extent of this predictability is dependent on the type of environment investigated. Furthermore, it is shown that carefully selected small sets of resistance genes can describe total resistance gene diversity remarkably well.

CONCLUSIONS

The results of this study suggest that knowledge gained from large-scale quantifications of known resistance genes can be utilized as a proxy for unknown resistance factors. This is important for current and proposed monitoring efforts for environmental antibiotic resistance and has implications for the design of risk ranking strategies and the choices of measures and methods for describing resistance gene abundance and diversity in the environment.

Glutamate mediated metabolic neutralization mitigates propionate toxicity in intracellular Mycobacterium tuberculosis

Metabolic networks in biological systems are interconnected, such that malfunctioning parts can be corrected by other parts within the network, a process termed adaptive metabolism. Unlike Bacillus Calmette-Guérin (BCG), Mycobacterium tuberculosis (Mtb) better manages its intracellular lifestyle by executing adaptive metabolism. Here, we used metabolomics and identified glutamate synthase (GltB/D) that converts glutamine to glutamate (Q → E) as a metabolic effort used to neutralize cytoplasmic pH that is acidified while consuming host propionate carbon through the methylcitrate cycle (MCC). Methylisocitrate lyase, the last step of the MCC, is intrinsically downregulated in BCG, leading to obstruction of carbon flux toward central carbon metabolism, accumulation of MCC intermediates, and interference with GltB/D mediated neutralizing activity against propionate toxicity. Indeed, vitamin B12 mediated bypass MCC and additional supplement of glutamate led to selectively correct the phenotypic attenuation in BCG and restore the adaptive capacity of BCG to the similar level of Mtb phenotype. Collectively, a defective crosstalk between MCC and Q → E contributes to attenuation of intracellular BCG. Furthermore, GltB/D inhibition enhances the level of propionate toxicity in Mtb. Thus, these findings revealed a new adaptive metabolism and propose GltB/D as a synergistic target to improve the antimicrobial outcomes of MCC inhibition in Mtb.

Metagenomic Insights Into the Microbial Community and Nutrient Cycling in the Western Subarctic Pacific Ocean

The composition and metabolic functions of prokaryotic communities in the western subarctic Pacific (WSP), where strong mixing of waters from the Sea of Okhotsk and the East Kamchatka Current result in transfer to the Oyashio Current, were investigated using a shotgun metagenome sequencing approach. Functional metabolic genes related to nutrient cycling of nitrogen, sulfur, carbohydrates, iron and amino acids were differently distributed between the surface and deep waters of the WSP. Genes related to nitrogen metabolism were mainly found in deep waters, where Thaumarchaeaota, Sphingomonadales, and Pseudomonadales were closely associated and performing important roles in ammonia oxidation, assimilatory nitrate reduction, and dissimilatory nitrate reduction processes, respectively. In addition, orders affiliated to Spingobacteria and Alphaproteobacteria were crucial for sulfate reduction and abundant at 3000 m, whereas orders affiliated to Gammaproteobacteria, which harbored the most sulfate reduction genes, were abundant at 1000 m. Additionally, when compared with the East Kamchatka Current, the prokaryotes in the Oyashio Current were likely to consume more energy for synthesizing cellular components. Also, genes encoding iron transport and siderophore biosynthesis proteins were in low abundance, indicating that the iron was not a limiting factor in the Oyashio current. In contrast, in the East Kamchatka Current, prokaryotes were more likely to directly utilize the amino acids and absorb iron from the environment. Overall, our data indicated that the transformation from the East Kamchatka Current to the Oyashio Current reshapes not only the composition of microbial community, but also the function of the metabolic processes. These results extended our knowledge of the microbial composition and potential metabolism in the WSP.

Variability in metagenomic samples from the Puget Sound: Relationship to temporal and anthropogenic impacts

Whole-metagenome sequencing (WMS) has emerged as a powerful tool to assess potential public health risks in marine environments by measuring changes in microbial community structure and function in uncultured bacteria. In addition to monitoring public health risks such as antibiotic resistance determinants, it is essential to measure predictors of microbial variation in order to identify natural versus anthropogenic factors as well as to evaluate reproducibility of metagenomic measurements.This study expands our previous metagenomic characterization of Puget Sound by sampling new nearshore environments including the Duwamish River, an EPA superfund site, and the Hood Canal, an area characterized by highly variable oxygen levels. We also resampled a wastewater treatment plant, nearshore and open ocean sites introducing a longitudinal component measuring seasonal and locational variations and establishing metagenomics sampling reproducibility. Microbial composition from samples collected in the open sound were highly similar within the same season and location across different years, while nearshore samples revealed multi-fold seasonal variation in microbial composition and diversity. Comparisons with recently sequenced predominant marine bacterial genomes helped provide much greater species level taxonomic detail compared to our previous study. Antibiotic resistance determinants and pollution and detoxification indicators largely grouped by location showing minor seasonal differences. Metal resistance, oxidative stress and detoxification systems showed no increase in samples proximal to an EPA superfund site indicating a lack of ecosystem adaptation to anthropogenic impacts. Taxonomic analysis of common sewage influent families showed a surprising similarity between wastewater treatment plant and open sound samples suggesting a low-level but pervasive sewage influent signature in Puget Sound surface waters. Our study shows reproducibility of metagenomic data sampling in multiple Puget Sound locations while establishing baseline measurements of antibiotic resistance determinants, pollution and detoxification systems. Combining seasonal and longitudinal data across these locations provides a foundation for evaluating variation in future studies.

Metagenomic Analysis of Subtidal Sediments from Polar and Subpolar Coastal Environments Highlights the Relevance of Anaerobic Hydrocarbon Degradation Processes

In this work, we analyzed the community structure and metabolic potential of sediment microbial communities in high-latitude coastal environments subjected to low to moderate levels of chronic pollution. Subtidal sediments from four low-energy inlets located in polar and subpolar regions from both Hemispheres were analyzed using large-scale 16S rRNA gene and metagenomic sequencing. Communities showed high diversity (Shannon's index 6.8 to 10.2), with distinct phylogenetic structures (<40% shared taxa at the Phylum level among regions) but similar metabolic potential in terms of sequences assigned to KOs. Environmental factors (mainly salinity, temperature, and in less extent organic pollution) were drivers of both phylogenetic and functional traits. Bacterial taxa correlating with hydrocarbon pollution included families of anaerobic or facultative anaerobic lifestyle, such as Desulfuromonadaceae, Geobacteraceae, and Rhodocyclaceae. In accordance, biomarker genes for anaerobic hydrocarbon degradation (bamA, ebdA, bcrA, and bssA) were prevalent, only outnumbered by alkB, and their sequences were taxonomically binned to the same bacterial groups. BssA-assigned metagenomic sequences showed an extremely wide diversity distributed all along the phylogeny known for this gene, including bssA sensu stricto, nmsA, assA, and other clusters from poorly or not yet described variants. This work increases our understanding of microbial community patterns in cold coastal sediments, and highlights the relevance of anaerobic hydrocarbon degradation processes in subtidal environments.

Metagenomic assessment of the interplay between the environment and the genetic diversification of Acinetobacter

Most bacteria have poorly characterized environmental reservoirs and unknown closely related species. This hampers the study of bacterial evolutionary ecology because both the environment and the genetic background of ancestral lineages are unknown. We combined metagenomics, comparative genomics and phylogenomics to overcome this limitation, to identify novel taxa and to propose environments where they can be isolated. We applied this method to characterize the ecological distribution of known and novel lineages of Acinetobacter spp. We observed two major environmental transitions at deep phylogenetic levels, splitting the genus into three ecologically differentiated clades. One of these has rapidly shifted towards host‐association by acquiring genes involved in bacteria‐eukaryote interactions. We show that environmental perturbations affect species distribution in predictable ways: bovines have very diverse communities of Acinetobacter, unless they were administered antibiotics, in which case they show highly uniform communities of Acinetobacter spp. that resemble those of humans. Our results uncover the diversity of bacterial lineages, overpassing the limitations of classical cultivation methods and highlight the role of the environment in shaping their evolution.

Biosynthetic energy cost of potentially highly expressed proteins vary with niche in selected actinobacteria

Amino acid and protein biosynthesis requires a number of high energy phosphate bonds and includes a dual energy cost for the synthesis of chemical intermediates during the fueling reactions and the conversion of precursor molecules to final products. One popular hypothesis is that the proteins encoded by putative highly expressed genes (hence called PHXPs) generally utilize low energy consuming amino acids to reduce the biosynthetic cost of the essential proteins. In our study, we found that this idea was not supported in the case of actinobacteria. With the actinobacteria, the energy costs of PHXPs varied in relation to their niche. Free-living, including aquatic, soil and extremophilic, and plant-associated actinobacteria were found to use energetically expensive amino acids in their PHXPs. An exception occurred with some animal-host-associated actinobacteria that used energy efficient amino acids. One explanation for these results may be due to the diverse metabolic patterns exhibited by actinobacteria under varied niches influenced by nutritional availability and physical environment.

Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment

Our work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers following this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods.

Transport capabilities of environmental Pseudomonads for sulfur compounds

Sulfur is an essential element in plant rhizospheres and microbial activity plays a key role in increasing the biological availability of sulfur in soil environments. To better understand the mechanisms facilitating the exchange of sulfur-containing molecules in soil, we profiled the binding specificities of eight previously uncharacterized ABC transporter solute-binding proteins from plant-associated Pseudomonads. A high-throughput screening procedure indicated eighteen significant organosulfur binding ligands, with at least one high-quality screening hit for each protein target. Calorimetric and spectroscopic methods were used to validate the best ligand assignments and catalog the thermodynamic properties of the protein-ligand interactions. Two novel high-affinity ligand-binding activities were identified and quantified in this set of solute-binding proteins. Bacteria were cultured in minimal media with screening library components supplied as the sole sulfur sources, demonstrating that these organosulfur compounds can be metabolized and confirming the relevance of ligand assignments. These results expand the set of experimentally validated ligands amenable to transport by this ABC transporter family and demonstrate the complex range of protein-ligand interactions that can be accomplished by solute-binding proteins. Characterizing new nutrient import pathways provides insight into Pseudomonad metabolic capabilities which can be used to further interrogate bacterial survival and participation in soil and rhizosphere communities.

Metagenomic covariation along densely sampled environmental gradients in the Red Sea

Oceanic microbial diversity covaries with physicochemical parameters. Temperature, for example, explains approximately half of global variation in surface taxonomic abundance. It is unknown, however, whether covariation patterns hold over narrower parameter gradients and spatial scales, and extending to mesopelagic depths. We collected and sequenced 45 epipelagic and mesopelagic microbial metagenomes on a meridional transect through the eastern Red Sea. We asked which environmental parameters explain the most variation in relative abundances of taxonomic groups, gene ortholog groups, and pathways-at a spatial scale of <2000 km, along narrow but well-defined latitudinal and depth-dependent gradients. We also asked how microbes are adapted to gradients and extremes in irradiance, temperature, salinity, and nutrients, examining the responses of individual gene ortholog groups to these parameters. Functional and taxonomic metrics were equally well explained (75-79%) by environmental parameters. However, only functional and not taxonomic covariation patterns were conserved when comparing with an intruding water mass with different physicochemical properties. Temperature explained the most variation in each metric, followed by nitrate, chlorophyll, phosphate, and salinity. That nitrate explained more variation than phosphate suggested nitrogen limitation, consistent with low surface N:P ratios. Covariation of gene ortholog groups with environmental parameters revealed patterns of functional adaptation to the challenging Red Sea environment: high irradiance, temperature, salinity, and low nutrients. Nutrient-acquisition gene ortholog groups were anti-correlated with concentrations of their respective nutrient species, recapturing trends previously observed across much larger distances and environmental gradients. This dataset of metagenomic covariation along densely sampled environmental gradients includes online data exploration supplements, serving as a community resource for marine microbial ecology.

Disentangling the influence of earthworms in sugarcane rhizosphere

For the last 150 years many studies have shown the importance of earthworms for plant growth, but the exact mechanisms involved in the process are still poorly understood. Many important functions required for plant growth can be performed by soil microbes in the rhizosphere. To investigate earthworm influence on the rhizosphere microbial community, we performed a macrocosm experiment with and without Pontoscolex corethrurus (EW+ and EW−, respectively) and followed various soil and rhizosphere processes for 217 days with sugarcane. In EW+ treatments, N₂O concentrations belowground (15 cm depth) and relative abundances of nitrous oxide genes (nosZ) were higher in bulk soil and rhizosphere, suggesting that soil microbes were able to consume earthworm-induced N₂O. Shotgun sequencing (total DNA) revealed that around 70 microbial functions in bulk soil and rhizosphere differed between EW+ and EW− treatments. Overall, genes indicative of biosynthetic pathways and cell proliferation processes were enriched in EW+ treatments, suggesting a positive influence of worms. In EW+ rhizosphere, functions associated with plant-microbe symbiosis were enriched relative to EW− rhizosphere. Ecological networks inferred from the datasets revealed decreased niche diversification and increased keystone functions as an earthworm-derived effect. Plant biomass was improved in EW+ and worm population proliferated.

The Role of Ocean Currents in the Temperature Selection of Plankton: Insights from an Individual-Based Model

Biogeography studies that correlate the observed distribution of organisms to environmental variables are typically based on local conditions. However, in cases with substantial translocation, like planktonic organisms carried by ocean currents, selection may happen upstream and local environmental factors may not be representative of those that shaped the local population. Here we use an individual-based model of microbes in the global surface ocean to explore this effect for temperature. We simulate up to 25 million individual cells belonging to up to 50 species with different temperature optima. Microbes are moved around the globe based on a hydrodynamic model, and grow and die based on local temperature. We quantify the role of currents using the “advective temperature differential” metric, which is the optimum temperature of the most abundant species from the model with advection minus that from the model without advection. This differential depends on the location and can be up to 4°C. Poleward-flowing currents, like the Gulf Stream, generally experience cooling and the differential is positive. We apply our results to three global datasets. For observations of optimum growth temperature of phytoplankton, accounting for the effect of currents leads to a slightly better agreement with observations, but there is large variability and the improvement is not statistically significant. For observed Prochlorococcus ecotype ratios and metagenome nucleotide divergence, accounting for advection improves the correlation significantly, especially in areas with relatively strong poleward or equatorward currents.

Metagenomics and Bioinformatics in Microbial Ecology: Current Status and Beyond

Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.

Aerobically respiring prokaryotic strains exhibit a broader temperature-pH-salinity space for cell division than anaerobically respiring and fermentative strains

Biological processes on the Earth operate within a parameter space that is constrained by physical and chemical extremes. Aerobic respiration can result in adenosine triphosphate yields up to over an order of magnitude higher than those attained anaerobically and, under certain conditions, may enable microbial multiplication over a broader range of extremes than other modes of catabolism. We employed growth data published for 241 prokaryotic strains to compare temperature, pH and salinity values for cell division between aerobically and anaerobically metabolizing taxa. Isolates employing oxygen as the terminal electron acceptor exhibited a considerably more extensive three-dimensional phase space for cell division (90% of the total volume) than taxa using other inorganic substrates or organic compounds as the electron acceptor (15% and 28% of the total volume, respectively), with all groups differing in their growth characteristics. Understanding the mechanistic basis of these differences will require integration of research into microbial ecology, physiology and energetics, with a focus on global-scale processes. Critical knowledge gaps include the combined impacts of diverse stress parameters on Gibbs energy yields and rates of microbial activity, interactions between cellular energetics and adaptations to extremes, and relating laboratory-based data to in situ limits for cell division.

Belowground Response to Drought in a Tropical Forest Soil. I. Changes in Microbial Functional Potential and Metabolism

Global climate models predict a future of increased severity of drought in many tropical forests. Soil microbes are central to the balance of these systems as sources or sinks of atmospheric carbon (C), yet how they respond metabolically to drought is not well-understood. We simulated drought in the typically aseasonal Luquillo Experimental Forest, Puerto Rico, by intercepting precipitation falling through the forest canopy. This approach reduced soil moisture by 13% and water potential by 0.14 MPa (from -0.2 to -0.34). Previous results from this experiment have demonstrated that the diversity and composition of these soil microbial communities are sensitive to even small changes in soil water. Here, we show prolonged drought significantly alters the functional potential of the community and provokes a clear osmotic stress response, including the production of compatible solutes that increase intracellular C demand. Subsequently, a microbial population emerges with a greater capacity for extracellular enzyme production targeting macromolecular carbon. Significantly, some of these drought-induced functional shifts in the soil microbiota are attenuated by prior exposure to a short-term drought suggesting that acclimation may occur despite a lack of longer-term drought history.

Plankton networks driving carbon export in the oligotrophic ocean

The biological carbon pump is the process by which CO₂ is transformed to organic carbon via photosynthesis, exported through sinking particles, and finally sequestered in the deep ocean. While the intensity of the pump correlates with plankton community composition, the underlying ecosystem structure driving the process remains largely uncharacterised. Here we use environmental and metagenomic data gathered during the Tara Oceans expedition to improve our understanding of carbon export in the oligotrophic ocean. We show that specific plankton communities, from the surface and deep chlorophyll maximum, correlate with carbon export at 150 m and highlight unexpected taxa such as Radiolaria, alveolate parasites, as well as Synechococcus and their phages, as lineages most strongly associated with carbon export in the subtropical, nutrient-depleted, oligotrophic ocean. Additionally, we show that the relative abundance of just a few bacterial and viral genes can predict most of the variability in carbon export in these regions.

Are freshwater bacterioplankton indifferent to variable types of amino acid substrates?

A wide range of carbon compounds sustain bacterial activity and growth in freshwater ecosystems and the amount and quality of these substrates influence bacterial diversity and metabolic function. Biologically labile low-molecular-weight compounds, such as dissolved free amino acids, are particularly important substrates and can fuel as much as 20% of the total heterotrophic production. In this study, we show that extensive laboratory incubations with variable amino acids as substrates caused only minimal differences in bacterial growth rate, growth yield, quantitative amino acid usage, community composition and diversity. This was in marked contrast to incubations under dark or light regimes, where significant responses were observed in bacterial community composition and with higher diversity in the dark incubations. While a few individual taxa still responded to amendment with specific amino acids, our results suggest that compositional shifts in the specific supply of amino acids and possibly also other labile organic substrates have a minor impact on heterotrophic bacterioplankton communities, at least in nutrient rich lakes and compared to other prevailing environmental factors.

Ocean plankton. Structure and function of the global ocean microbiome

Microbes are dominant drivers of biogeochemical processes, yet drawing a global picture of functional diversity, microbial community structure, and their ecological determinants remains a grand challenge. We analyzed 7.2 terabases of metagenomic data from 243 Tara Oceans samples from 68 locations in epipelagic and mesopelagic waters across the globe to generate an ocean microbial reference gene catalog with >40 million nonredundant, mostly novel sequences from viruses, prokaryotes, and picoeukaryotes. Using 139 prokaryote-enriched samples, containing >35,000 species, we show vertical stratification with epipelagic community composition mostly driven by temperature rather than other environmental factors or geography. We identify ocean microbial core functionality and reveal that >73% of its abundance is shared with the human gut microbiome despite the physicochemical differences between these two ecosystems.

Natural bacterial communities serve as quantitative geochemical biosensors

Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive.

IMPORTANCE

Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.

Natural bacterial communities serve as quantitative geochemical biosensors

Biological sensors can be engineered to measure a wide range of environmental conditions. Here we show that statistical analysis of DNA from natural microbial communities can be used to accurately identify environmental contaminants, including uranium and nitrate at a nuclear waste site. In addition to contamination, sequence data from the 16S rRNA gene alone can quantitatively predict a rich catalogue of 26 geochemical features collected from 93 wells with highly differing geochemistry characteristics. We extend this approach to identify sites contaminated with hydrocarbons from the Deepwater Horizon oil spill, finding that altered bacterial communities encode a memory of prior contamination, even after the contaminants themselves have been fully degraded. We show that the bacterial strains that are most useful for detecting oil and uranium are known to interact with these substrates, indicating that this statistical approach uncovers ecologically meaningful interactions consistent with previous experimental observations. Future efforts should focus on evaluating the geographical generalizability of these associations. Taken as a whole, these results indicate that ubiquitous, natural bacterial communities can be used as in situ environmental sensors that respond to and capture perturbations caused by human impacts. These in situ biosensors rely on environmental selection rather than directed engineering, and so this approach could be rapidly deployed and scaled as sequencing technology continues to become faster, simpler, and less expensive.

Here we show that DNA from natural bacterial communities can be used as a quantitative biosensor to accurately distinguish unpolluted sites from those contaminated with uranium, nitrate, or oil. These results indicate that bacterial communities can be used as environmental sensors that respond to and capture perturbations caused by human impacts.

Sequencing and beyond: integrating molecular 'omics' for microbial community profiling

High-throughput DNA sequencing has proven invaluable for investigating diverse environmental and host-associated microbial communities. In this Review, we discuss emerging strategies for microbial community analysis that complement and expand traditional metagenomic profiling. These include novel DNA sequencing strategies for identifying strain-level microbial variation and community temporal dynamics; measuring multiple 'omic' data types that better capture community functional activity, such as transcriptomics, proteomics and metabolomics; and combining multiple forms of omic data in an integrated framework. We highlight studies in which the 'multi-omics' approach has led to improved mechanistic models of microbial community structure and function.

Comparative analysis of sugarcane bagasse metagenome reveals unique and conserved biomass-degrading enzymes among lignocellulolytic microbial communities

BACKGROUND

As one of the most abundant agricultural wastes, sugarcane bagasse is largely under-exploited, but it possesses a great potential for the biofuel, fermentation, and cellulosic biorefinery industries. It also provides a unique ecological niche, as the microbes in this lignocellulose-rich environment thrive in relatively high temperatures (50°C) with varying microenvironments of aerobic surface to anoxic interior. The microbial community in bagasse thus presents a good resource for the discovery and characterization of new biomass-degrading enzymes; however, it remains largely unexplored.

RESULTS

We have constructed a fosmid library of sugarcane bagasse and obtained the largest bagasse metagenome to date. A taxonomic classification of the bagasse metagenome reviews the predominance of Proteobacteria, which are also found in high abundance in other aerobic environments. Based on the functional characterization of biomass-degrading enzymes, we have demonstrated that the bagasse microbial community benefits from a large repertoire of lignocellulolytic enzymes, which allows them to digest different components of lignocelluoses into single molecule sugars. Comparative genomic analyses with other lignocellulolytic and non-lignocellulolytic metagenomes show that microbial communities are taxonomically separable by their aerobic "open" or anoxic "closed" environments. Importantly, a functional analysis of lignocellulose-active genes (based on the CAZy classifications) reveals core enzymes highly conserved within the lignocellulolytic group, regardless of their taxonomic compositions. Cellulases, in particular, are markedly more pronounced compared to the non-lignocellulolytic group. In addition to the core enzymes, the bagasse fosmid library also contains some uniquely enriched glycoside hydrolases, as well as a large repertoire of the newly defined auxiliary activity proteins.

CONCLUSIONS

Our study demonstrates a conservation and diversification of carbohydrate-active genes among diverse microbial species in different biomass-degrading niches, and signifies the importance of taking a global approach to functionally investigate a microbial community as a whole, as compared to focusing on individual organisms.

BiomeNet: a Bayesian model for inference of metabolic divergence among microbial communities

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic subnetworks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems). The metabosystems are composed of mixtures of tightly connected metabolic subnetworks. BiomeNet differs from other unsupervised methods by allowing researchers to discriminate groups of samples through the metabolic patterns it discovers in the data, and by providing a framework for interpreting them. We describe a collapsed Gibbs sampler for inference of the mixture weights under BiomeNet, and we use simulation to validate the inference algorithm. Application of BiomeNet to human gut metagenomes revealed a metabosystem with greater prevalence among inflammatory bowel disease (IBD) patients. Based on the discriminatory subnetworks for this metabosystem, we inferred that the community is likely to be closely associated with the human gut epithelium, resistant to dietary interventions, and interfere with human uptake of an antioxidant connected to IBD. Because this metabosystem has a greater capacity to exploit host-associated glycans, we speculate that IBD-associated communities might arise from opportunist growth of bacteria that can circumvent the host's nutrient-based mechanism for bacterial partner selection.

Metagenomic studies of microbial communities yield enormous numbers of gene sequences that have a known enzymatic function, and thus have potential to contribute to community-level metabolic activities. Ecologically divergent microbial communities are presumed to differ in metabolic repertoire and function, but detecting such differences is challenging because the required analytical methodology is complex. Here, we present a novel Bayesian model suitable for this task. Our model, BiomeNet, does not assume that microbiome samples of a certain type are the same; rather, a sample is modeled as a unique mixture of complex metabolic systems referred to as “metabosystems”. The metabosystems are composed of mixtures of subnetworks, where subnetworks are mixtures of reactions related by function. Application of BiomeNet to human gut metagenomes revealed a metabosystem with greater prevalence among IBD patients. We inferred that this metabosystem is likely to be closely associated with the human gut epithelium, resistant to dietary interventions, and interfere with human uptake of an important antioxidant, possibly contributing to gut inflammation associated with IBD.

Adaptation to environmental factors shapes the organization of regulatory regions in microbial communities

Background

It has been shown in a number of metagenomic studies that the addition and removal of specific genes have allowed microbiomes to adapt to specific environmental conditions by losing and gaining specific functions. But it is not known whether and how the regulation of gene expression also contributes to adaptation.

Results

We have here characterized and analyzed the metaregulome of three different environments, as well as their impact in the adaptation to particular variable physico-chemical conditions. For this, we have developed a computational protocol to extract regulatory regions and their corresponding transcription factors binding sites directly from metagenomic reads and applied it to three well known environments: Acid Mine, Whale Fall, and Waseca Farm. Taking the density of regulatory sites in promoters as a measure of the potential and complexity of gene regulation, we found it to be quantitatively the same in all three environments, despite their different physico-chemical conditions and species composition. However, we found that each environment distributes their regulatory potential differently across their functional space. Among the functions with highest regulatory potential in each niche, we found significant enrichment of processes related to sensing and buffering external variable factors specific to each environment, like for example, the availability of co-factors in deep sea, of oligosaccharides in soil and the regulation of pH in the acid mine.

Conclusions

These results highlight the potential impact of gene regulation in the adaptation of bacteria to the different habitats through the distribution of their regulatory potential among specific functions, and point to critical environmental factors that challenge the growth of any microbial community.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-877) contains supplementary material, which is available to authorized users.