Microbial Community Analysis with Ribosomal Gene Fragments from Shotgun Metagenomes

Microbial valorization of kraft black liquor for production of platform chemicals, biofuels, and value-added products: A critical review

The proper treatment and utilization of kraft black liquor, generated from the pulp and paper industry through the kraft pulping method, is required to reduce environmental impacts prior to the final disposal. It also improves the economic performance through the utilization of waste. Microbial valorization appears to demonstrates the dual benefits of waste management and resource recovery by providing an innovative solution to convert kraft black liquor into resource for reuse. A comprehensive review on the microbial valorization of kraft black liquor, describing the role in valorization and management, is still lacking in the literature, forming the rationale of this article. Thus, the present study reviews and systematically discusses the potential of utilizing microorganisms to valorize kraft black liquor as a sustainable feedstock to develop a numerous portfolio of platform chemicals, bioenergy, and other value-added products. This work contributes to sustainability and resource efficiency within the pulp and paper industry. The recent developments in utilization of synthetic biology tools and molecular techniques, including omics approaches for engineering novel microbial strains, for enhancing kraft black liquor valorization has been presented. This review explores how the better utilization of kraft black liquor in the pulp and paper industry contributes to achieving UN Sustainable Development Goals (SDGs), particularly clean water and sanitation (SDG 6) as well as the affordable and clean energy goal (SDG 7). The current review also addresses challenges related to toxicity, impurities, low productivity, and downstream processing that serve as obstacles to the progress of developing highly efficient bioproducts. The new directions for future research efforts to fill the critical knowledge gaps are proposed. This study concludes that by implementing microbial valorization techniques, the pulp and paper industry can transition from a linear to a circular bioeconomy and eco-friendly manage the kraft black liuor. This approach showed to be effective towards resource recovery, while simultaneously minimizing the environmental burden.

Benchmarking a targeted 16S ribosomal RNA gene enrichment approach to reconstruct ancient microbial communities

The taxonomic characterization of ancient microbiomes is a key step in the rapidly growing field of paleomicrobiology. While PCR amplification of the 16S ribosomal RNA (rRNA) gene is a widely used technique in modern microbiota studies, this method has systematic biases when applied to ancient microbial DNA. Shotgun metagenomic sequencing has proven to be the most effective method in reconstructing taxonomic profiles of ancient dental calculus samples. Nevertheless, shotgun sequencing approaches come with inherent limitations that could be addressed through hybridization enrichment capture. When employed together, shotgun sequencing and hybridization capture have the potential to enhance the characterization of ancient microbial communities. Here, we develop, test, and apply a hybridization enrichment capture technique to selectively target 16S rRNA gene fragments from the libraries of ancient dental calculus samples generated with shotgun techniques. We simulated data sets generated from hybridization enrichment capture, indicating that taxonomic identification of fragmented and damaged 16S rRNA gene sequences was feasible. Applying this enrichment approach to 15 previously published ancient calculus samples, we observed a 334-fold increase of ancient 16S rRNA gene fragments in the enriched samples when compared to unenriched libraries. Our results suggest that 16S hybridization capture is less prone to the effects of background contamination than 16S rRNA amplification, yielding a higher percentage of on-target recovery. While our enrichment technique detected low abundant and rare taxa within a given sample, these assignments may not achieve the same level of specificity as those achieved by unenriched methods.

Responses of soil micro-eukaryotic communities to decadal drainage in a Siberian wet tussock tundra

Climate warming holds the potential to cause extensive drying of wetlands in the Arctic, but the warming-drying effects on belowground ecosystems, particularly micro-eukaryotes, remain poorly understood. We investigated the responses of soil micro-eukaryotic communities, including fungi, protists, and microbial metazoa, to decadal drainage manipulation in a Siberian wet tundra using both amplicon and shotgun metagenomic sequencing. Our results indicate that drainage treatment increased the abundance of both fungal and non-fungal micro-eukaryotic communities, with key groups such as Ascomycota (mostly order Helotiales), Nematoda, and Tardigrada being notably abundant in drained sites. Functional traits analysis showed an increase in litter saprotrophic fungi and protistan consumers, indicating their increased activities in drained sites. The effects of drainage were more pronounced in the surface soil layer than the deeper layer, as soils dry and warm from the surface. Marked compositional shifts were observed for both communities, with fungal communities being more strongly influenced by drainage-induced vegetation change than the lowered water table itself, while the vegetation effect on non-fungal micro-eukaryotes was moderate. These findings provide insights into how belowground micro-eukaryotic communities respond to the widespread drying of wetlands in the Arctic and improve our predictive understanding of future ecosystem changes.

Simultaneous analysis of seven 16S rRNA hypervariable gene regions increases efficiency in marine bacterial diversity detection

Environmental DNA sequencing is the gold standard to reveal microbial community structures. In most applications, a one-fragment PCR approach is applied to amplify a taxonomic marker gene, usually a hypervariable region of the 16S rRNA gene. We used a new reverse complement (RC)-PCR-based assay that amplifies seven out of the nine hypervariable regions of the 16S rRNA gene, to interrogate bacterial communities in sediment samples collected from different coastal marine sites with an impact gradient. In parallel, we employed a traditional one-fragment analysis of the hypervariable V3-V4 region to investigate whether the RC-PCR reveals more of the 'unseen' diversity obtained by the one-fragment approach. As a benchmark for the full deck of diversity, we subjected the samples to PCR-free metagenomic sequencing. None of the two PCR-based approaches recorded the full taxonomic repertoire obtained from the metagenomics datasets. However, the RC-PCR approach detected 2.8 times more bacterial genera compared to the near-saturation sequenced V3-V4 samples. RC-PCR is an ideal compromise between the standard one-fragment approach and metagenomics sequencing and may guide future environmental sequencing studies, in which bacterial diversity is a central subject.

Metagenomics reveals novel microbial signatures of farm exposures in house dust

Indoor home dust microbial communities, important contributors to human health, are shaped by environmental factors, including farm-related exposures. Advanced metagenomic whole genome shotgun sequencing (WGS) improves detection and characterization of microbiota in the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). We hypothesized that the improved characterization of indoor dust microbial communities by WGS will enhance detection of exposure-outcome associations. The objective of this study was to identify novel associations of environmental exposures with the dust microbiome from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium, and Pseudomonas, was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota. These findings can inform the design of future studies in environmental health.

Metagenomics reveals novel microbial signatures of farm exposures in house dust

Indoor home dust microbial communities, important contributors to human health outcomes, are shaped by environmental factors, including farm-related exposures. Detection and characterization of microbiota are influenced by sequencing methodology; however, it is unknown if advanced metagenomic whole genome shotgun sequencing (WGS) can detect novel associations between environmental exposures and the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). This study aimed to better depict indoor dust microbial communities using WGS to investigate novel associations with environmental risk factors from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes , and Proteobacteria . The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium , and Pseudomonas , was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota, and should be an important consideration in designing future studies in environmental health.

Microbial metabolic responses and CO2 emissions differentiated by soil water content variation in subarctic tundra soils

Recent rapid air temperature increases across the northern-latitude tundra have prolonged permafrost thawing and snow melting periods, resulting in increased soil temperature (T_s) and volumetric soil water content (SWC). Under prolonged soil warming at 8°C, Alaskan tundra soils were incubated in a microcosm system and examined for the SWC differential influence on the microbial decomposition activity of large molecular weight (MW) humic substances (HS). When one microcosm soil (AKC1-1) was incubated at a constant SWC of 41% for 90 days (T = 90) and then SWC was gradually decreased from 41% to 29% for another T = 90, the initial HS was partly depolymerized. In contrast, in AKC1-2 incubated at a gradually decreasing SWC from the initial 32% to 10% for T = 90 and then increasing to 27% for another T = 90, HS depolymerization was undetected. Overall, the microbial communities in AKC1-1 could maintain metabolic activity at sufficient and constant SWC during the initial T = 90 incubation. In contrast, AKC1-2 microbes may have been damaged by drought stress during the drying SWC regimen, possibly resulting in the loss of HS decomposition activity, which did not recover even after re-wetting to an optimal SWC range (20-40%). After T = 90, the CO₂ production in both treatments was attributed to the increased decomposition of small-MW organic compounds (including aerobic HS-degradative products) within an optimal SWC range. We expect this study to provide new insights into the early effects of warming- and topography-induced SWC variations on the microbial contribution to CO₂ emissions via HS decomposition in northern-latitude tundra soil.

RiboTaxa: combined approaches for rRNA genes taxonomic resolution down to the species level from metagenomics data revealing novelties

Metagenomic classifiers are widely used for the taxonomic profiling of metagenomics data and estimation of taxa relative abundance. Small subunit rRNA genes are a gold standard for phylogenetic resolution of microbiota, although the power of this marker comes down to its use as full-length. We aimed at identifying the tools that can efficiently lead to taxonomic resolution down to the species level. To reach this goal, we benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then compiled the best tools (BBTools, FastQC, SortMeRNA, MetaRib, EMIRGE, VSEARCH, BBMap and QIIME 2’s Sklearn classifier) to build a pipeline called RiboTaxa. Using metagenomics datasets, RiboTaxa gave the best results compared to other tools (i.e. Kraken2, Centrifuge, METAXA2, phyloFlash, SPINGO, BLCA, MEGAN) with precise taxonomic identification and relative abundance description without false positive detection (F-measure of 100% and 83.7% at genus level and species level, respectively). Using real datasets from various environments (i.e. ocean, soil, human gut) and from different approaches (e.g. metagenomics and gene capture by hybridization), RiboTaxa revealed microbial novelties not discerned by current bioinformatics analysis opening new biological perspectives in human and environmental health.

Recent advances in understanding the ecology of the filamentous bacteria responsible for activated sludge bulking

Activated sludge bulking caused by filamentous bacteria is still a problem in wastewater treatment plants around the world. Bulking is a microbiological problem, and so its solution on species-specific basis is likely to be reached only after their ecology, physiology and metabolism is better understood. Culture-independent molecular methods have provided much useful information about this group of organisms, and in this review, the methods employed and the information they provide are critically assessed. Their application to understanding bulking caused by the most frequently seen filament in Japan, 'Ca. Kouleothrix', is used here as an example of how these techniques might be used to develop control strategies. Whole genome sequences are now available for some of filamentous bacteria responsible for bulking, and so it is possible to understand why these filaments might thrive in activated sludge plants, and provide clues as to how eventually they might be controlled specifically.

The ubiquitous soil verrucomicrobial clade 'Candidatus Udaeobacter' shows preferences for acidic pH

Members of the verrucomicrobial clade 'Candidatus Udaeobacter' rank among the most dominant bacterial phylotypes in soil. Nevertheless, despite this global prevalence, in-depth analyses with respect to pH preferences of 'Ca. Udaeobacter' representatives are still lacking. Here, we utilized a recently designed primer pair, specifically targeting 'Ca. Udaeobacter', to investigate links between soil pH and the abundance as well as phylotype composition of this largely unexplored verrucomicrobial clade. Based on 150 forest and 150 grassland soils, comprising a broad pH range, we determined the highest total abundance of 'Ca. Udaeobacter' in strongly acidic soil (pH, ~5.1) and, noteworthy, in ultra-acidic soil (pH < 3.5) and at a pH ≥ 7, its abundance drastically declined. When we analysed the six most dominant amplicon sequence variants affiliated with 'Ca. Udaeobacter' separately, their abundances peaked within a pH range of approximately 4.7-5.2, and only in one case at slightly acidic soil pH (pH, 6.1). Our study benefits from a combination of quantitative real-time PCR and high-throughput amplicon sequencing, enabling for the first time a highly specific abundance analysis of representatives affiliated with 'Ca. Udaeobacter', which revealed that this globally abundant verrucomicrobial clade shows preferences for acidic soil.

Identification & correlation of bacterial diversity in oral cancer and long-term tobacco chewers- A case-control pilot study

Introduction. Squamous cell carcinoma is a highly aggressive type of oral cancer (OC). It is the most common cancer among men, and accounts for almost 90 % of all oral cancers in India. Consumption of tobacco is a leading factor contributing to maximum oral cancer incidences as per the WHO.Hypothesis/Gap statement. Researchers reported a direct association of microorganisms with dysbiosis in various oral lesions including oral cancer. However, there is a dearth of information related to compositional changes in the oral microbiome in long-term tobacco chewers and the Indian oral cancer population.Aim. The aim of this study was to identify and correlate the bacterial diversity in the oral cavity of tobacco chewers, patients with oral cancer and healthy subjects in the Indian population.Methods. Oral rinse samples were collected for ten subjects in each group followed by DNA extraction. The variable regions of the bacterial 16S rRNA gene (V6-V8) were amplified, sequenced, processed, and analysed using QIIME2 platform to assess alpha and beta diversity between the study groups.Results. This pilot study showed genus Streptococcus dominated the control group (18.54 %), and the abundance decreased in tobacco and OC group (9.63 and 5.45% respectively); whereas genus Prevotella dominated the tobacco and OC group (21.01 and 26.03% respectively). A shift in abundance of microbiome was observed from control population to oral cancer via the tobacco chewing population. Maximum alpha diversity of oral microbiome was found in Indian tobacco chewers. Beta diversity of tobacco chewers was similar to both the healthy population as well as oral cancer patients suggesting transitioning of the oral microbiome from healthy to oral cancer microbiome via the tobacco chewers microbiome.Conclusion. The data provides evidence of oral bacterial dysbiosis due to tobacco chewing habits that can further lead to progression towards cancer.

NetCom: A Network-Based Tool for Predicting Metabolic Activities of Microbial Communities Based on Interpretation of Metagenomics Data

The study of microbial activity can be viewed as a triangle with three sides: environment (dominant resources in a specific habitat), community (species dictating a repertoire of metabolic conversions) and function (production and/or utilization of resources and compounds). Advances in metagenomics enable a high-resolution description of complex microbial communities in their natural environments and support a systematic study of environment-community-function associations. NetCom is a web-tool for predicting metabolic activities of microbial communities based on network-based interpretation of assembled and annotated metagenomics data. The algorithm takes as an input, lists of differentially abundant enzymatic reactions and generates the following outputs: (i) pathway associations of differently abundant enzymes; (ii) prediction of environmental resources that are unique to each treatment, and their pathway associations; (iii) prediction of compounds that are produced by the microbial community, and pathway association of compounds that are treatment-specific; (iv) network visualization of enzymes, environmental resources and produced compounds, that are treatment specific (2 and 3D). The tool is demonstrated on metagenomic data from rhizosphere and bulk soil samples. By predicting root-specific activities, we illustrate the relevance of our framework for forecasting the impact of soil amendments on the corresponding microbial communities. NetCom is available online.

Phagotrophic protists (protozoa) in Antarctic terrestrial ecosystems: diversity, distribution, ecology, and best research practices

Phagotrophic protists (formerly protozoa) are a highly diverse, polyphyletic grouping of generally unicellular, heterotrophic eukaryotes that are key regulators of the soil microbiome. The biodiversity and ecology of soil phagotrophic protists are still largely uncharacterized, especially in the Antarctic, which possesses some of the harshest terrestrial environments known and potentially many physiologically unique and scientifically interesting species. Antarctic soil systems are also highly limited in terms of moisture, temperature, and carbon, and the resulting reduced biological complexity can facilitate fine-tuned investigation of the drivers and functioning of microbial communities. To facilitate and encourage future research into protist biodiversity and ecology, especially in context of the broader functioning of Antarctic terrestrial communities, I review the biodiversity, distribution, and ecology of Antarctic soil phagotrophic protists. Biodiversity appears to be highly structured by region and taxonomic group, with the Antarctic Peninsula having the highest taxonomic diversity and ciliates (Ciliophora) being the most diverse taxonomic group. However, richness estimates are likely skewed by disproportionate sampling (over half of the studies are from the peninsula), habitat type bias (predominately moss-associated soils), investigator bias (toward ciliates and the testate amoeba morphogroup), and methodological approach (toward cultivation and morphological identification). To remedy these biases, a standardized methodology using both morphological and molecular identification and increased emphasis on microflagellate and naked amoeba morphogroups is needed. Additionally, future research should transition away from biodiversity survey studies to dedicated ecological studies that emphasize the function, ecophysiology, endemicity, dispersal, and impact of abiotic drivers beyond moisture and temperature.

Phagotrophic Protists and Their Associates: Evidence for Preferential Grazing in an Abiotically Driven Soil Ecosystem

The complex relationship between ecosystem function and soil food web structure is governed by species interactions, many of which remain unmapped. Phagotrophic protists structure soil food webs by grazing the microbiome, yet their involvement in intraguild competition, susceptibility to predator diversity, and grazing preferences are only vaguely known. These species-dependent interactions are contextualized by adjacent biotic and abiotic processes, and thus obfuscated by typically high soil biodiversity. Such questions may be investigated in the McMurdo Dry Valleys (MDV) of Antarctica because the physical environment strongly filters biodiversity and simplifies the influence of abiotic factors. To detect the potential interactions in the MDV, we analyzed the co-occurrence among shotgun metagenome sequences for associations suggestive of intraguild competition, predation, and preferential grazing. In order to control for confounding abiotic drivers, we tested co-occurrence patterns against various climatic and edaphic factors. Non-random co-occurrence between phagotrophic protists and other soil fauna was biotically driven, but we found no support for competition or predation. However, protists predominately associated with Proteobacteria and avoided Actinobacteria, suggesting grazing preferences were modulated by bacterial cell-wall structure and growth rate. Our study provides a critical starting-point for mapping protist interactions in native soils and highlights key trends for future targeted molecular and culture-based approaches.

mTAGs: taxonomic profiling using degenerate consensus reference sequences of ribosomal RNA genes

Profiling the taxonomic composition of microbial communities commonly involves the classification of ribosomal RNA gene fragments. As a trade-off to maintain high classification accuracy, existing tools are typically limited to the genus level. Here, we present mTAGs, a taxonomic profiling tool that implements the alignment of metagenomic sequencing reads to degenerate consensus reference sequences of small subunit ribosomal RNA genes. It uses DNA fragments, that is, paired-end sequencing reads, as count units and provides relative abundance profiles at multiple taxonomic ranks, including operational taxonomic units based on a 97% sequence identity cutoff. At the genus rank, mTAGs outperformed other tools across several metrics, such as the F1 score by >11% across data from different environments, and achieved competitive (F1 score) or better results (Bray-Curtis dissimilarity) at the sub-genus level.

AVAILABILITY AND IMPLEMENTATION

The software tool mTAGs is implemented in Python. The source code and binaries are freely available (https://github.com/SushiLab/mTAGs). The data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.4352762.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Metagenomic analysis reveals the shared and distinct features of the soil resistome across tundra, temperate prairie, and tropical ecosystems

BACKGROUND

Soil is an important reservoir of antibiotic resistance genes (ARGs), but their potential risk in different ecosystems as well as response to anthropogenic land use change is unknown. We used a metagenomic approach and datasets with well-characterized metadata to investigate ARG types and amounts in soil DNA of three native ecosystems: Alaskan tundra, US Midwestern prairie, and Amazon rainforest, as well as the effect of conversion of the latter two to agriculture and pasture, respectively.

RESULTS

High diversity (242 ARG subtypes) and abundance (0.184-0.242 ARG copies per 16S rRNA gene copy) were observed irrespective of ecosystem, with multidrug resistance and efflux pump the dominant class and mechanism. Ten regulatory genes were identified and they accounted for 13-35% of resistome abundances in soils, among them arlR, cpxR, ompR, vanR, and vanS were dominant and observed in all studied soils. We identified 55 non-regulatory ARGs shared by all 26 soil metagenomes of the three ecosystems, which accounted for more than 81% of non-regulatory resistome abundance. Proteobacteria, Firmicutes, and Actinobacteria were primary ARG hosts, 7 of 10 most abundant ARGs were found in all of them. No significant differences in both ARG diversity and abundance were observed between native prairie soil and adjacent long-term cultivated agriculture soil. We chose 12 clinically important ARGs to evaluate at the sequence level and found them to be distinct from those in human pathogens, and when assembled they were even more dissimilar. Significant correlation was found between bacterial community structure and resistome profile, suggesting that variance in resistome profile was mainly driven by the bacterial community composition.

CONCLUSIONS

Our results identify candidate background ARGs (shared in all 26 soils), classify ARG hosts, quantify resistance classes, and provide quantitative and sequence information suggestive of very low risk but also revealing resistance gene variants that might emerge in the future. Video abstract.

CaptureSeq: Hybridization-Based Enrichment of cpn60 Gene Fragments Reveals the Community Structures of Synthetic and Natural Microbial Ecosystems

Background. The molecular profiling of complex microbial communities has become the basis for examining the relationship between the microbiome composition, structure and metabolic functions of those communities. Microbial community structure can be partially assessed with “universal” PCR targeting taxonomic or functional gene markers. Increasingly, shotgun metagenomic DNA sequencing is providing more quantitative insight into microbiomes. However, both amplicon-based and shotgun sequencing approaches have shortcomings that limit the ability to study microbiome dynamics. Methods. We present a novel, amplicon-free, hybridization-based method (CaptureSeq) for profiling complex microbial communities using probes based on the chaperonin-60 gene. Molecular profiles of a commercially available synthetic microbial community standard were compared using CaptureSeq, whole metagenome sequencing, and 16S universal target amplification. Profiles were also generated for natural ecosystems including antibiotic-amended soils, manure storage tanks, and an agricultural reservoir. Results. The CaptureSeq method generated a microbial profile that encompassed all of the bacteria and eukaryotes in the panel with greater reproducibility and more accurate representation of high G/C content microorganisms compared to 16S amplification. In the natural ecosystems, CaptureSeq provided a much greater depth of coverage and sensitivity of detection compared to shotgun sequencing without prior selection. The resulting community profiles provided quantitatively reliable information about all three domains of life (Bacteria, Archaea, and Eukarya) in the different ecosystems. The applications of CaptureSeq will facilitate accurate studies of host-microbiome interactions for environmental, crop, animal and human health. Conclusions: cpn60-based hybridization enriched for taxonomically informative DNA sequences from complex mixtures. In synthetic and natural microbial ecosystems, CaptureSeq provided sequences from prokaryotes and eukaryotes simultaneously, with quantitatively reliable read abundances. CaptureSeq provides an alternative to PCR amplification of taxonomic markers with deep community coverage while minimizing amplification biases.

Comparative analysis of the metabolically active microbial communities in the rumen of dromedary camels under different feeding systems using total rRNA sequencing

Breakdown of plant biomass in rumen depends on interactions between bacteria, archaea, fungi, and protozoa; however, the majority of studies of the microbiome of ruminants, including the few studies of the rumen of camels, only studied one of these microbial groups. In this study, we applied total rRNA sequencing to identify active microbial communities in 22 solid and liquid rumen samples from 11 camels. These camels were reared at three stations that use different feeding systems: clover, hay and wheat straw (G1), fresh clover (G2), and wheat straw (G3). Bacteria dominated the libraries of sequence reads generated from all rumen samples, followed by protozoa, archaea, and fungi respectively. Firmicutes, Thermoplasmatales, Diplodinium, and Neocallimastix dominated bacterial, archaeal, protozoal and fungal communities, respectively in all samples. Libraries generated from camels reared at facility G2, where they were fed fresh clover, showed the highest alpha diversity. Principal co-ordinate analysis and linear discriminate analysis showed clusters associated with facility/feed and the relative abundance of microbes varied between liquid and solid fractions. This provides preliminary evidence that bacteria dominate the microbial communities of the camel rumen and these communities differ significantly between populations of domesticated camels.

phyloFlash: Rapid Small-Subunit rRNA Profiling and Targeted Assembly from Metagenomes

To track organisms across all domains of life, the SSU rRNA gene is the gold standard. Many environmental microbes are known only from high-throughput sequence data, but the SSU rRNA gene, the key to visualization by molecular probes and link to existing literature, is often missing from metagenome-assembled genomes (MAGs). The easy-to-use phyloFlash software suite tackles this gap with rapid, SSU rRNA-centered taxonomic classification, targeted assembly, and graph-based linking to MAGs. Starting from a cleaned reference database, phyloFlash profiles the taxonomic diversity and assembles the sorted SSU rRNA reads. The phyloFlash design is domain agnostic and covers eukaryotes, archaea, and bacteria alike. phyloFlash also provides utilities to visualize multisample comparisons and to integrate the recovered SSU rRNAs in a metagenomics workflow by linking them to MAGs using assembly graph parsing.

The small-subunit rRNA (SSU rRNA) gene is the key marker in molecular ecology for all domains of life, but it is largely absent from metagenome-assembled genomes that often are the only resource available for environmental microbes. Here, we present phyloFlash, a pipeline to overcome this gap with rapid, SSU rRNA-centered taxonomic classification, targeted assembly, and graph-based binning of full metagenomic assemblies. We show that a cleanup of artifacts is pivotal even with a curated reference database. With such a filtered database, the general-purpose mapper BBmap extracts SSU rRNA reads five times faster than the rRNA-specialized tool SortMeRNA with similar sensitivity and higher selectivity on simulated metagenomes. Reference-based targeted assemblers yielded either highly fragmented assemblies or high levels of chimerism, so we employ the general-purpose genomic assembler SPAdes. Our optimized implementation is independent of reference database composition and has satisfactory levels of chimera formation. phyloFlash quickly processes Illumina (meta)genomic data, is straightforward to use, even as part of high-throughput quality control, and has user-friendly output reports. The software is available at https://github.com/HRGV/phyloFlash (GPL3 license) and is documented with an online manual.

IMPORTANCE To track organisms across all domains of life, the SSU rRNA gene is the gold standard. Many environmental microbes are known only from high-throughput sequence data, but the SSU rRNA gene, the key to visualization by molecular probes and link to existing literature, is often missing from metagenome-assembled genomes (MAGs). The easy-to-use phyloFlash software suite tackles this gap with rapid, SSU rRNA-centered taxonomic classification, targeted assembly, and graph-based linking to MAGs. Starting from a cleaned reference database, phyloFlash profiles the taxonomic diversity and assembles the sorted SSU rRNA reads. The phyloFlash design is domain agnostic and covers eukaryotes, archaea, and bacteria alike. phyloFlash also provides utilities to visualize multisample comparisons and to integrate the recovered SSU rRNAs in a metagenomics workflow by linking them to MAGs using assembly graph parsing.

Shotgun metagenomics reveal a diverse assemblage of protists in a model Antarctic soil ecosystem

The soils of the McMurdo Dry Valleys (MDV) of Antarctica are established models for understanding fundamental processes in soil ecosystem functioning (e.g. ecological tipping points, community structuring and nutrient cycling) because the extreme physical environment drastically reduces biodiversity and ecological complexity. Understanding the functioning of MDV soils requires in-depth knowledge of the diversity of MDV soil species. Protists, which contribute significantly to soil ecosystem functioning worldwide, remain poorly characterized in the MDV. To better assess the diversity of MDV protists, we performed shotgun metagenomics on 18 sites representing a variety of landscape features and edaphic variables. Our results show MDV soil protists are diverse at both the genus (155 of 281 eukaryote genera) and family (120) levels, but comprise only 6% of eukaryotic reads. Protists are structured by moisture, total N and distance from the local coast and possess limited richness in arid (< 5% moisture) and at high elevation sites, known drivers of communities in the MDV. High relative diversity and broad distribution of protists in our study promotes these organisms as key members of MDV soil microbiomes and the MDV as a useful system for understanding the contribution of soil protists to the structure of soil microbiomes.

A metagenomic assessment of microbial eukaryotic diversity in the global ocean

Surveying microbial diversity and function is accomplished by combining complementary molecular tools. Among them, metagenomics is a PCR free approach that contains all genetic information from microbial assemblages and is today performed at a relatively large scale and reasonable cost, mostly based on very short reads. Here, we investigated the potential of metagenomics to provide taxonomic reports of marine microbial eukaryotes. We prepared a curated database with reference sequences of the V4 region of 18S rDNA clustered at 97% similarity and used this database to extract and classify metagenomic reads. More than half of them were unambiguously affiliated to a unique reference whilst the rest could be assigned to a given taxonomic group. The overall diversity reported by metagenomics was similar to that obtained by amplicon sequencing of the V4 and V9 regions of the 18S rRNA gene, although either one or both of these amplicon surveys performed poorly for groups like Excavata, Amoebozoa, Fungi and Haptophyta. We then studied the diversity of picoeukaryotes and nanoeukaryotes using 91 metagenomes from surface down to bathypelagic layers in different oceans, unveiling a clear taxonomic separation between size fractions and depth layers. Finally, we retrieved long rDNA sequences from assembled metagenomes that improved phylogenetic reconstructions of particular groups. Overall, this study shows metagenomics as an excellent resource for taxonomic exploration of marine microbial eukaryotes.

From Seabed to Bedside: A Review on Promising Marine Anticancer Compounds

The marine environment represents an outstanding source of antitumoral compounds and, at the same time, remains highly unexplored. Organisms living in the sea synthesize a wide variety of chemicals used as defense mechanisms. Interestingly, a large number of these compounds exert excellent antitumoral properties and have been developed as promising anticancer drugs that have later been approved or are currently under validation in clinical trials. However, due to the high need for these compounds, new methodologies ensuring its sustainable supply are required. Also, optimization of marine bioactives is an important step for their success in the clinical setting. Such optimization involves chemical modifications to improve their half-life in circulation, potency and tumor selectivity. In this review, we outline the most promising marine bioactives that have been investigated in cancer models and/or tested in patients as anticancer agents. Moreover, we describe the current state of development of anticancer marine compounds and discuss their therapeutic limitations as well as different strategies used to overcome these limitations. The search for new marine antitumoral agents together with novel identification and chemical engineering approaches open the door for novel, more specific and efficient therapeutic agents for cancer treatment.

Design of targeted primers based on 16S rRNA sequences in meta-transcriptomic datasets and identification of a novel taxonomic group in the Asgard archaea

BACKGROUND

Amplification of small subunit (SSU) rRNA genes with universal primers is a common method used to assess microbial populations in various environmental samples. However, owing to limitations in coverage of these universal primers, some microorganisms remain unidentified. The present study aimed to establish a method for amplifying nearly full-length SSU rRNA gene sequences of previously unidentified prokaryotes, using newly designed targeted primers via primer evaluation in meta-transcriptomic datasets.

METHODS

Primer binding regions of universal primer 8F/Arch21F for bacteria or archaea were used for primer evaluation of SSU rRNA sequences in meta-transcriptomic datasets. Furthermore, targeted forward primers were designed based on SSU rRNA reads from unclassified groups unmatched with the universal primer 8F/Arch21F, and these primers were used to amplify nearly full-length special SSU rRNA gene sequences along with universal reverse primer 1492R. Similarity and phylogenetic analysis were used to confirm their novel status.

RESULTS

Using this method, we identified unclassified SSU rRNA sequences that were not matched with universal primer 8F and Arch21F. A new group within the Asgard superphylum was amplified by the newly designed specific primer based on these unclassified SSU rRNA sequences by using mudflat samples.

CONCLUSION

We showed that using specific primers designed based on universal primer evaluation from meta-transcriptomic datasets, identification of novel taxonomic groups from a specific environment is possible.

Community members in activated sludge as determined by molecular probe technology

The use of molecular probe technology is demonstrated for routine identification and tracking of cultured and uncultured microorganisms in an activated sludge bioreactor treating domestic wastewater. A key advantage of molecular probe technology is that it can interrogate hundreds of microbial species of interest in a single measurement. In environmental niches where a single genus (such as Competibacteraceae) dominates, it can be difficult and expensive to identify microorganisms that are present at low relative abundance. With molecular probe technology, it is straightforward. Members of the Competibacteraceae family, none of which have been grown in pure culture, are abundant in an activated sludge system in the San Francisco Bay Area, California, USA. Molecular probe ensembles with and without Competibacteraceae probes were constructed. Whereas the probe ensemble with Competibacteraceae probes identified a total of ten bacteria, the molecular probe ensemble without Competibacteraceae probes identified 29 bacteria, including many at low relative abundance and including some species of public health significance.

Soil hydrology drives ecological niche differentiation in a native prairie microbiome

While the impacts of soil moisture on soil microbiome diversity and composition are well characterized, the influence of hydrological regime has been overlooked. As precipitation patterns are altered by climate change, understanding the impact of soil hydrology on community structure and function is critical. In this work, water level was continuously monitored for over a year in a Midwestern prairie-wetland at 10 cm depth increments up to a depth of 120 cm in 10 locations. We analyzed microbiome composition and edaphic factors in soil cores collected from this unique spatially distributed, longitudinal data set. We demonstrate that the fraction of time that each sample was inundated explains more variability in diversity and composition across this site than other commonly assessed edaphic factors, such as soil pH or depth. Finally, we show that these compositional changes influence abundance of ammonia oxidizers. The observed patterns in community composition and diversity are fundamentally regulated by the interaction of water with a structured landscape, particularly an elevated sand ridge characterized by drier conditions and a lower-lying wetland with more clayey soils. Similar processes are generally expected to influence the biogeography of many terrestrial environments, as morphology, hydrology and soil properties generally co-vary.

High-throughput DNA sequencing technologies for water and wastewater analysis

Conventional microbiological water monitoring uses culture-dependent techniques to screen indicator microbial species such as Escherichia coli and fecal coliforms. With high-throughput, second-generation sequencing technologies becoming less expensive, water quality monitoring programs can now leverage the massively parallel nature of second-generation sequencing technologies for batch sample processing to simultaneously obtain compositional and functional information of culturable and as yet uncultured microbial organisms. This review provides an introduction to the technical capabilities and considerations necessary for the use of second-generation sequencing technologies, specifically 16S rDNA amplicon and whole-metagenome sequencing, to investigate the composition and functional potential of microbiomes found in water and wastewater systems.

Review, Evaluation, and Directions for Gene-Targeted Assembly for Ecological Analyses of Metagenomes

Shotgun metagenomics has greatly advanced our understanding of microbial communities over the last decade. Metagenomic analyses often include assembly and genome binning, computationally daunting tasks especially for big data from complex environments such as soil and sediments. In many studies, however, only a subset of genes and pathways involved in specific functions are of interest; thus, it is not necessary to attempt global assembly. In addition, methods that target genes can be computationally more efficient and produce more accurate assembly by leveraging rich databases, especially for those genes that are of broad interest such as those involved in biogeochemical cycles, biodegradation, and antibiotic resistance or used as phylogenetic markers. Here, we review six gene-targeted assemblers with unique algorithms for extracting and/or assembling targeted genes: Xander, MegaGTA, SAT-Assembler, HMM-GRASPx, GenSeed-HMM, and MEGAN. We tested these tools using two datasets with known genomes, a synthetic community of artificial reads derived from the genomes of 17 bacteria, shotgun sequence data from a mock community with 48 bacteria and 16 archaea genomes, and a large soil shotgun metagenomic dataset. We compared assemblies of a universal single copy gene (rplB) and two N cycle genes (nifH and nirK). We measured their computational efficiency, sensitivity, specificity, and chimera rate and found Xander and MegaGTA, which both use a probabilistic graph structure to model the genes, have the best overall performance with all three datasets, although MEGAN, a reference matching assembler, had better sensitivity with synthetic and mock community members chosen from its reference collection. Also, Xander and MegaGTA are the only tools that include post-assembly scripts tuned for common molecular ecology and diversity analyses. Additionally, we provide a mathematical model for estimating the probability of assembling targeted genes in a metagenome for estimating required sequencing depth.

Characterization of airborne antibiotic resistance genes from typical bioaerosol emission sources in the urban environment using metagenomic approach

The wide spread of antibiotic resistance genes (ARGs) has attracted increasing concern. However, the occurrence and diversity of ARGs in airborne particles remains to be understood. In this study, total suspended particles (TSP) in the atmosphere were collected from typical sources of ARG pollution, including animal farms and wastewater treatment plant (WWTP), as well as the downtown area in Zhuhai, China. Metagenomic profiling demonstrated that ARGs were abundant and diverse in the TSP from animal farms and WWTP, but significant differences in ARG composition pattern between these samples were observed. ARGs associated with the resistance to aminoglycoside, macrolide-lincosamide-streptogramin (MLS) and tetracycline were dominant over other ARGs in the TSP of the animal farms, whereas multidrug and bacitracin resistance genes were more abundant than other ARGs in the TSP of the WWTP. In the animal farms, ARG profiles of the TSP were consistent with those of animal feces, indicating that animal feces could be one of the most contributing sources of airborne ARGs in animal farms. In contrast to representative sources of ARG pollution, ARG abundance and diversity in the TSP collected from the downtown area was relatively low, with multidrug resistance genes being predominant. This study suggests that metagenomic profiling of the ARGs in airborne TSP could enhance our comprehensive understanding of ARGs dissemination in the environment and their potential health threats.

Dynamics of microbial populations mediating biogeochemical cycling in a freshwater lake

BACKGROUND

Microbial processes are intricately linked to the depletion of oxygen in in-land and coastal water bodies, with devastating economic and ecological consequences. Microorganisms deplete oxygen during biomass decomposition, degrading the habitat of many economically important aquatic animals. Microbes then turn to alternative electron acceptors, which alter nutrient cycling and generate potent greenhouse gases. As oxygen depletion is expected to worsen with altered land use and climate change, understanding how chemical and microbial dynamics impact dead zones will aid modeling efforts to guide remediation strategies. More work is needed to understand the complex interplay between microbial genes, populations, and biogeochemistry during oxygen depletion.

RESULTS

Here, we used 16S rRNA gene surveys, shotgun metagenomic sequencing, and a previously developed biogeochemical model to identify genes and microbial populations implicated in major biogeochemical transformations in a model lake ecosystem. Shotgun metagenomic sequencing was done for one time point in Aug., 2013, and 16S rRNA gene sequencing was done for a 5-month time series (Mar.-Aug., 2013) to capture the spatiotemporal dynamics of genes and microorganisms mediating the modeled processes. Metagenomic binning analysis resulted in many metagenome-assembled genomes (MAGs) that are implicated in the modeled processes through gene content similarity to cultured organism and the presence of key genes involved in these pathways. The MAGs suggested some populations are capable of methane and sulfide oxidation coupled to nitrate reduction. Using the model, we observe that modulating these processes has a substantial impact on overall lake biogeochemistry. Additionally, 16S rRNA gene sequences from the metagenomic and amplicon libraries were linked to processes through the MAGs. We compared the dynamics of microbial populations in the water column to the model predictions. Many microbial populations involved in primary carbon oxidation had dynamics similar to the model, while those associated with secondary oxidation processes deviated substantially.

CONCLUSIONS

This work demonstrates that the unique capabilities of resident microbial populations will substantially impact the concentration and speciation of chemicals in the water column, unless other microbial processes adjust to compensate for these differences. It further highlights the importance of the biological aspects of biogeochemical processes, such as fluctuations in microbial population dynamics. Integrating gene and population dynamics into biogeochemical models has the potential to improve predictions of the community response under altered scenarios to guide remediation efforts.

New Biological Insights Into How Deforestation in Amazonia Affects Soil Microbial Communities Using Metagenomics and Metagenome-Assembled Genomes

Deforestation in the Brazilian Amazon occurs at an alarming rate, which has broad effects on global greenhouse gas emissions, carbon storage, and biogeochemical cycles. In this study, soil metagenomes and metagenome-assembled genomes (MAGs) were analyzed for alterations to microbial community composition, functional groups, and putative physiology as it related to land-use change and tropical soil. A total of 28 MAGs were assembled encompassing 10 phyla, including both dominant and rare biosphere lineages. Amazon Acidobacteria subdivision 3, Melainabacteria, Microgenomates, and Parcubacteria were found exclusively in pasture soil samples, while Candidatus Rokubacteria was predominant in the adjacent rainforest soil. These shifts in relative abundance between land-use types were supported by the different putative physiologies and life strategies employed by the taxa. This research provides unique biological insights into candidate phyla in tropical soil and how deforestation may impact the carbon cycle and affect climate change.

Verrucomicrobia are prevalent in north-temperate freshwater lakes and display class-level preferences between lake habitats

The bacterial phylum Verrucomicrobia was formally described two decades ago and originally believed to be a minor member of many ecosystems; however, it is now recognized as ubiquitous and abundant in both soil and aquatic systems. Nevertheless, knowledge of the drivers of its relative abundance and within-phylum habitat preferences remains sparse, especially in lake systems. Here, we documented the distribution of Verrucomicrobia in 12 inland lakes in Southeastern Michigan, a Laurentian Great Lake (Lake Michigan), and a freshwater estuary, which span a gradient in lake sizes, depths, residence times, and trophic states. A wide range of physical and geochemical parameters was covered by sampling seasonally from the surface and bottom of each lake, and by separating samples into particle-associated and free-living fractions. On average, Verrucomicrobia was the 4^th most abundant phylum (range 1.7–41.7%). Fraction, season, station, and depth explained up to 70% of the variance in Verrucomicrobia community composition and preference for these habitats was phylogenetically conserved at the class-level. When relative abundance was linearly modeled against environmental data, Verrucomicrobia and non-Verrucomicrobia bacterial community composition correlated to similar quantitative environmental parameters, although there were lake system-dependent differences and > 55% of the variance remained unexplained. A majority of the phylum exhibited preference for the particle-associated fraction and two classes (Opitutae and Verrucomicrobiae) were identified to be more abundant during the spring season. This study highlights the high relative abundance of Verrucomicrobia in north temperate lake systems and expands insights into drivers of within-phylum habitat preferences of the Verrucomicrobia.

Evaluation of different 16S rRNA gene V regions for exploring bacterial diversity in a eutrophic freshwater lake

Massive partial sequencing of 16S rRNA genes has become the predominant tool used for studying microbial ecology. However, determining which hypervariable regions and primer sets should be used for screening microbial communities requires extensive investigation if controversial results are to be avoided. Here, the performances of different variable regions of the 16S rRNA gene on bacterial diversity studies were evaluated in silico with respect to the SILVA non-redundant reference database (SILVA SSU Ref 123NR), and subsequently verified using samples from Lake Taihu in China, a eutrophic lake. We found that the bacterial community composition results were strongly impacted by the different V regions. The results show that V1-V2 and V1-V3 regions were the most reliable regions in the full-length 16S rRNA sequences, while most V3 to V6 regions (including V3, V4, V3-V4, V5, V4-V5, V6, V3-V6, V4-V6, and V5-V6) were more closely aligned with the SILVA SSU Ref 123NR database. Overall, V4 was the most prominent V region for achieving good domain specificity, higher coverage and a broader spectrum in the Bacteria domain, as confirmed by the validation experiments. S-D-Bact-0564-a-S-15/S-D-Bact-0785-b-A-18 is, therefore, a promising primer set for surveying bacterial diversity in eutrophic lakes.

Arbuscular mycorrhizal fungi promote coexistence and niche divergence of sympatric palm species on a remote oceanic island

Microbes can have profound effects on their hosts, driving natural selection, promoting speciation and determining species distributions. However, soil-dwelling microbes are rarely investigated as drivers of evolutionary change in plants. We used metabarcoding and experimental manipulation of soil microbiomes to investigate the impact of soil and root microbes in a well-known case of sympatric speciation, the Howea palms of Lord Howe Island (Australia). Whereas H. forsteriana can grow on both calcareous and volcanic soils, H. belmoreana is restricted to, but more successful on, volcanic soil, indicating a trade-off in adaptation to the two soil types. We suggest a novel explanation for this trade-off. Arbuscular mycorrhizal fungi (AMF) are significantly depleted in H. forsteriana on volcanic soil, relative to both H. belmoreana on volcanic soil and H. forsteriana on calcareous soil. This is mirrored by the results of survival experiments, where the sterilization of natural soil reduces Howea fitness in every soil-species combination except H. forsteriana on volcanic soil. Furthermore, AMF-associated genes exhibit evidence of divergent selection between Howea species. These results show a mechanism by which divergent adaptation can have knock-on effects on host-microbe interactions, thereby reducing interspecific competition and promoting the coexistence of plant sister species.

Taxonomy of anaerobic digestion microbiome reveals biases associated with the applied high throughput sequencing strategies

In the past few years, many studies investigated the anaerobic digestion microbiome by means of 16S rRNA amplicon sequencing. Results obtained from these studies were compared to each other without taking into consideration the followed procedure for amplicons preparation and data analysis. This negligence was mainly due to the lack of knowledge regarding the biases influencing specific steps of the microbiome investigation process. In the present study, the main technical aspects of the 16S rRNA analysis were checked giving special attention to the approach used for high throughput sequencing. More specifically, the microbial compositions of three laboratory scale biogas reactors were analyzed before and after addition of sodium oleate by sequencing the microbiome with three different approaches: 16S rRNA amplicon sequencing, shotgun DNA and shotgun RNA. This comparative analysis revealed that, in amplicon sequencing, abundance of some taxa (Euryarchaeota and Spirochaetes) was biased by the inefficiency of universal primers to hybridize all the templates. Reliability of the results obtained was also influenced by the number of hypervariable regions under investigation. Finally, amplicon sequencing and shotgun DNA underestimated the Methanoculleus genus, probably due to the low 16S rRNA gene copy number encoded in this taxon.

Total rRNA-Seq Analysis Gives Insight into Bacterial, Fungal, Protozoal and Archaeal Communities in the Rumen Using an Optimized RNA Isolation Method

Advances in high throughput, next generation sequencing technologies have allowed an in-depth examination of biological environments and phenomena, and are particularly useful for culture-independent microbial community studies. Recently the use of RNA for metatranscriptomic studies has been used to elucidate the role of active microbes in the environment. Extraction of RNA of appropriate quality is critical in these experiments and TRIzol reagent is often used for maintaining stability of RNA molecules during extraction. However, for studies using rumen content there is no consensus on (1) the amount of rumen digesta to use or (2) the amount of TRIzol reagent to be used in RNA extraction procedures. This study evaluated the effect of using various quantities of ground rumen digesta and of TRIzol reagent on the yield and quality of extracted RNA. It also investigated the possibility of using lower masses of solid-phase rumen digesta and lower amounts of TRIzol reagent than is used currently, for extraction of RNA for metatranscriptomic studies. We found that high quality RNA could be isolated from 2 g of ground rumen digesta sample, whilst using 0.6 g of ground matter for RNA extraction and using 3 mL (a 5:1 TRIzol : extraction mass ratio) of TRIzol reagent. This represents a significant savings in the cost of RNA isolation. These lower masses and volumes were then applied in the RNA-Seq analysis of solid-phase rumen samples obtained from 6 Angus X Hereford beef heifers which had been fed a high forage diet (comprised of barley straw in a forage-to-concentrate ratio of 70:30) for 102 days. A bioinformatics analysis pipeline was developed in-house that generated relative abundance values of archaea, protozoa, fungi and bacteria in the rumen and also allowed the extraction of individual rRNA variable regions that could be analyzed in downstream molecular ecology programs. The average relative abundances of rRNA transcripts of archaea, bacteria, protozoa and fungi in our samples were 1.4 ± 0.06, 44.16 ± 1.55, 35.38 ± 1.64, and 16.37 ± 0.65% respectively. This represents the first study to define the relative active contributions of these populations to the rumen ecosystem and is especially important in defining the role of the anaerobic fungi and protozoa.

Analysis of Microbial Functions in the Rhizosphere Using a Metabolic-Network Based Framework for Metagenomics Interpretation

Advances in metagenomics enable high resolution description of complex bacterial communities in their natural environments. Consequently, conceptual approaches for community level functional analysis are in high need. Here, we introduce a framework for a metagenomics-based analysis of community functions. Environment-specific gene catalogs, derived from metagenomes, are processed into metabolic-network representation. By applying established ecological conventions, network-edges (metabolic functions) are assigned with taxonomic annotations according to the dominance level of specific groups. Once a function-taxonomy link is established, prediction of the impact of dominant taxa on the overall community performances is assessed by simulating removal or addition of edges (taxa associated functions). This approach is demonstrated on metagenomic data describing the microbial communities from the root environment of two crop plants – wheat and cucumber. Predictions for environment-dependent effects revealed differences between treatments (root vs. soil), corresponding to documented observations. Metabolism of specific plant exudates (e.g., organic acids, flavonoids) was linked with distinct taxonomic groups in simulated root, but not soil, environments. These dependencies point to the impact of these metabolite families as determinants of community structure. Simulations of the activity of pairwise combinations of taxonomic groups (order level) predicted the possible production of complementary metabolites. Complementation profiles allow formulating a possible metabolic role for observed co-occurrence patterns. For example, production of tryptophan-associated metabolites through complementary interactions is unique to the tryptophan-deficient cucumber root environment. Our approach enables formulation of testable predictions for species contribution to community activity and exploration of the functional outcome of structural shifts in complex bacterial communities. Understanding community-level metabolism is an essential step toward the manipulation and optimization of microbial function. Here, we introduce an analysis framework addressing three key challenges of such data: producing quantified links between taxonomy and function; contextualizing discrete functions into communal networks; and simulating environmental impact on community performances. New technologies will soon provide a high-coverage description of biotic and a-biotic aspects of complex microbial communities such as these found in gut and soil. This framework was designed to allow the integration of high-throughput metabolomic and metagenomic data toward tackling the intricate associations between community structure, community function, and metabolic inputs.

Large-scale differences in microbial biodiversity discovery between 16S amplicon and shotgun sequencing

Modern metagenomic environmental DNA studies are almost completely reliant on next-generation sequencing, making evaluations of these methods critical. We compare two next-generation sequencing techniques – amplicon and shotgun – on water samples across four of Brazil’s major river floodplain systems (Amazon, Araguaia, Paraná, and Pantanal). Less than 50% of phyla identified via amplicon sequencing were recovered from shotgun sequencing, clearly challenging the dogma that mid-depth shotgun recovers more diversity than amplicon-based approaches. Amplicon sequencing also revealed ~27% more families. Overall the amplicon data were more robust across both biodiversity and community ecology analyses at different taxonomic scales. Our work doubles the sampling size in similar environmental studies, and novelly integrates environmental data (e.g., pH, temperature, nutrients) from each site, revealing divergent correlations depending on which data are used. While myriad variants on NGS techniques and bioinformatic pipelines are available, our results point to core differences that have not been highlighted in any studies to date. Given the low number of taxa identified when coupling shotgun data with clade-based taxonomic algorithms, previous studies that quantified biodiversity using such bioinformatic tools should be viewed cautiously or re-analyzed. Nonetheless, shotgun has complementary advantages that should be weighed when designing projects.

Uncovering the trimethylamine-producing bacteria of the human gut microbiota

BACKGROUND

Trimethylamine (TMA), produced by the gut microbiota from dietary quaternary amines (mainly choline and carnitine), is associated with atherosclerosis and severe cardiovascular disease. Currently, little information on the composition of TMA producers in the gut is available due to their low abundance and the requirement of specific functional-based detection methods as many taxa show disparate abilities to produce that compound.

RESULTS

In order to examine the TMA-forming potential of microbial communities, we established databases for the key genes of the main TMA-synthesis pathways, encoding choline TMA-lyase (cutC) and carnitine oxygenase (cntA), using a multi-level screening approach on 67,134 genomes revealing 1107 and 6738 candidates to exhibit cutC and cntA, respectively. Gene-targeted assays enumerating the TMA-producing community by quantitative PCR and characterizing its composition via Illumina sequencing were developed and applied on human fecal samples (n = 50) where all samples contained potential TMA producers (cutC was detected in all individuals, whereas only 26% harbored cntA) constituting, however, only a minor part of the total community (below 1% in most samples). Obtained cutC amplicons were associated with various taxa, in particular with Clostridium XIVa strains and Eubacterium sp. strain AB3007, though a bulk of sequences displayed low nucleotide identities to references (average 86% ± 7%) indicating that key human TMA producers are yet to be isolated. Co-occurrence analysis revealed specific groups governing the community structure of cutC-exhibiting taxa across samples. CntA amplicons displayed high identities (~99%) to Gammaproteobacteria-derived references, primarily from Escherichia coli. Metagenomic analysis of samples provided by the Human Microbiome Project (n = 154) confirmed the abundance patterns as well as overall taxonomic compositions obtained with our assays, though at much lower resolution, whereas 16S ribosomal RNA gene sequence analysis could not adequately uncover the TMA-producing potential.

CONCLUSIONS

In this study, we developed a diagnostic framework that enabled the quantification and comprehensive characterization of the TMA-producing potential in human fecal samples. The key players were identified, and together with predictions on their environmental niches using functional genomics on most closely related reference strains, we provide crucial information for the development of specific treatment strategies to restrain TMA producers and limit their proliferation.

MIPE: A metagenome-based community structure explorer and SSU primer evaluation tool

An understanding of microbial community structure is an important issue in the field of molecular ecology. The traditional molecular method involves amplification of small subunit ribosomal RNA (SSU rRNA) genes by polymerase chain reaction (PCR). However, PCR-based amplicon approaches are affected by primer bias and chimeras. With the development of high-throughput sequencing technology, unbiased SSU rRNA gene sequences can be mined from shotgun sequencing-based metagenomic or metatranscriptomic datasets to obtain a reflection of the microbial community structure in specific types of environment and to evaluate SSU primers. However, the use of short reads obtained through next-generation sequencing for primer evaluation has not been well resolved. The software MIPE (MIcrobiota metagenome Primer Explorer) was developed to adapt numerous short reads from metagenomes and metatranscriptomes. Using metagenomic or metatranscriptomic datasets as input, MIPE extracts and aligns rRNA to reveal detailed information on microbial composition and evaluate SSU rRNA primers. A mock dataset, a real Metagenomics Rapid Annotation using Subsystem Technology (MG-RAST) test dataset, two PrimerProspector test datasets and a real metatranscriptomic dataset were used to validate MIPE. The software calls Mothur (v1.33.3) and the SILVA database (v119) for the alignment and classification of rRNA genes from a metagenome or metatranscriptome. MIPE can effectively extract shotgun rRNA reads from a metagenome or metatranscriptome and is capable of classifying these sequences and exhibiting sensitivity to different SSU rRNA PCR primers. Therefore, MIPE can be used to guide primer design for specific environmental samples.

RiboTagger: fast and unbiased 16S/18S profiling using whole community shotgun metagenomic or metatranscriptome surveys

Background

Taxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis. Large shotgun datasets contain a significant number of SSU sequences and these can be exploited to perform an unbiased SSU--based taxonomic analysis.

Results

Here we present a new program called RiboTagger that identifies and extracts taxonomically informative ribotags located in a specified variable region of the SSU gene in a high-throughput fashion.

Conclusions

RiboTagger permits fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. The program targets all three domains of life, exhibits high sensitivity and specificity and is substantially faster than comparable programs.