A sparse mapping of structure to function in microbial communities

The metabolic function of microbial communities emerges through a complex hierarchy of genome-encoded processes, from gene expression to interactions between diverse taxa. Therefore, a central challenge for microbial ecology is deciphering how genomic structure determines metabolic function in communities. Here we show, for the process of denitrification, that community metabolism is quantitatively predicted from the genes each member of the community possesses. Quantifying metabolite dynamics across a diverse library of bacterial isolates enables a statistical approach that reveals a sparse mapping from gene content to metabolic phenotypes. A consumer-resource model then correctly predicts community metabolism from the metabolic phenotypes of each strain. Our results enable connecting metagenomic data to metabolite dynamics, designing denitrifying communities, and discovering how genome evolution impacts metabolism.SummarySimple models quantitatively predict metabolite dynamics in denitrifying bacterial communities from gene content alone.

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Consistent responses of soil microbial communities to elevated nutrient inputs in grasslands across the globe

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1508382112 ◽

2015 ◽

Vol 112 (35) ◽

pp. 10967-10972 ◽

Cited By ~ 473

Author(s):

Jonathan W. Leff ◽

Stuart E. Jones ◽

Suzanne M. Prober ◽

Albert Barberán ◽

Elizabeth T. Borer ◽

...

Keyword(s):

Microbial Communities ◽

Bacterial Communities ◽

Soil Microbial Communities ◽

Metagenomic Data ◽

Life History Strategies ◽

Marker Genes ◽

Nutrient Inputs ◽

Soil Microbial ◽

Nutrient Additions ◽

Relative Abundances

Soil microorganisms are critical to ecosystem functioning and the maintenance of soil fertility. However, despite global increases in the inputs of nitrogen (N) and phosphorus (P) to ecosystems due to human activities, we lack a predictive understanding of how microbial communities respond to elevated nutrient inputs across environmental gradients. Here we used high-throughput sequencing of marker genes to elucidate the responses of soil fungal, archaeal, and bacterial communities using an N and P addition experiment replicated at 25 globally distributed grassland sites. We also sequenced metagenomes from a subset of the sites to determine how the functional attributes of bacterial communities change in response to elevated nutrients. Despite strong compositional differences across sites, microbial communities shifted in a consistent manner with N or P additions, and the magnitude of these shifts was related to the magnitude of plant community responses to nutrient inputs. Mycorrhizal fungi and methanogenic archaea decreased in relative abundance with nutrient additions, as did the relative abundances of oligotrophic bacterial taxa. The metagenomic data provided additional evidence for this shift in bacterial life history strategies because nutrient additions decreased the average genome sizes of the bacterial community members and elicited changes in the relative abundances of representative functional genes. Our results suggest that elevated N and P inputs lead to predictable shifts in the taxonomic and functional traits of soil microbial communities, including increases in the relative abundances of faster-growing, copiotrophic bacterial taxa, with these shifts likely to impact belowground ecosystems worldwide.

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Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

Scientific Reports ◽

10.1038/s41598-021-91615-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kazutoshi Yoshitake ◽

Gaku Kimura ◽

Tomoko Sakami ◽

Tsuyoshi Watanabe ◽

Yukiko Taniuchi ◽

...

Keyword(s):

Time Series ◽

Microbial Communities ◽

Pacific Coast ◽

Three Dimensional ◽

Amplicon Sequencing ◽

Metagenomic Data ◽

Shotgun Metagenomics ◽

Functional Features ◽

Pacific Coast Of Japan ◽

Marine Microbial Communities

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

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Diversity and Dynamics of Seaweed Associated Microbial Communities Inhabiting the Lagoon of Venice

Microorganisms ◽

10.3390/microorganisms8111657 ◽

2020 ◽

Vol 8 (11) ◽

pp. 1657

Author(s):

Abdul-Salam Juhmani ◽

Alessandro Vezzi ◽

Mohammad Wahsha ◽

Alessandro Buosi ◽

Fabio De Pascale ◽

...

Keyword(s):

Microbial Communities ◽

Bacterial Communities ◽

Host Response ◽

Environmental Parameters ◽

16S Rrna Genes ◽

Rrna Genes ◽

Nutrient Concentrations ◽

Lagoon Of Venice ◽

Anthropogenic Stressors ◽

Rich Diversity

Seaweeds are a group of essential photosynthetic organisms that harbor a rich diversity of associated microbial communities with substantial functions related to host health and defense. Environmental and anthropogenic stressors may disrupt the microbial communities and their metabolic activity, leading to host physiological alterations that negatively affect seaweeds’ performance and survival. Here, the bacterial communities associated with one of the most common seaweed, Ulva laetevirens Areshough, were sampled over a year at three sites of the lagoon of Venice affected by different environmental and anthropogenic stressors. Bacterial communities were characterized through Illumina sequencing of the V4 hypervariable region of 16S rRNA genes. The study demonstrated that the seaweed associated bacterial communities at sites impacted by environmental stressors were host-specific and differed significantly from the less affected site. Furthermore, these communities were significantly distinct from those of the surrounding seawater. The bacterial communities’ composition was significantly correlated with environmental parameters (nutrient concentrations, dissolved oxygen saturation, and pH) across sites. This study showed that several more abundant bacteria on U. laetevirens at stressed sites belonged to taxa related to the host response to the stressors. Overall, environmental parameters and anthropogenic stressors were shown to substantially affect seaweed associated bacterial communities, which reflect the host response to environmental variations.

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Microbial drivers of methane emissions from unrestored industrial salt ponds

The ISME Journal ◽

10.1038/s41396-021-01067-w ◽

2021 ◽

Author(s):

Jinglie Zhou ◽

Susanna M. Theroux ◽

Clifton P. Bueno de Mesquita ◽

Wyatt H. Hartman ◽

Ye Tian ◽

...

Keyword(s):

Microbial Communities ◽

Methane Flux ◽

Methane Emissions ◽

Metagenomic Data ◽

Rrna Gene ◽

Salt Ponds ◽

Salt Pond ◽

Reference Wetlands ◽

Reference Wetland ◽

The Impact

AbstractWetlands are important carbon (C) sinks, yet many have been destroyed and converted to other uses over the past few centuries, including industrial salt making. A renewed focus on wetland ecosystem services (e.g., flood control, and habitat) has resulted in numerous restoration efforts whose effect on microbial communities is largely unexplored. We investigated the impact of restoration on microbial community composition, metabolic functional potential, and methane flux by analyzing sediment cores from two unrestored former industrial salt ponds, a restored former industrial salt pond, and a reference wetland. We observed elevated methane emissions from unrestored salt ponds compared to the restored and reference wetlands, which was positively correlated with salinity and sulfate across all samples. 16S rRNA gene amplicon and shotgun metagenomic data revealed that the restored salt pond harbored communities more phylogenetically and functionally similar to the reference wetland than to unrestored ponds. Archaeal methanogenesis genes were positively correlated with methane flux, as were genes encoding enzymes for bacterial methylphosphonate degradation, suggesting methane is generated both from bacterial methylphosphonate degradation and archaeal methanogenesis in these sites. These observations demonstrate that restoration effectively converted industrial salt pond microbial communities back to compositions more similar to reference wetlands and lowered salinities, sulfate concentrations, and methane emissions.

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Metagenomic data of free cyanide and thiocyanate degrading bacterial communities

Data in Brief ◽

10.1016/j.dib.2017.06.049 ◽

2017 ◽

Vol 13 ◽

pp. 738-741 ◽

Cited By ~ 5

Author(s):

Lukhanyo Mekuto ◽

Seteno K.O. Ntwampe ◽

John B.N. Mudumbi ◽

Enoch A. Akinpelu ◽

Maxwell Mewa-Ngongang

Keyword(s):

Bacterial Communities ◽

Metagenomic Data ◽

Free Cyanide

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The Microbiome Modeling Toolbox: from microbial interactions to personalized microbial communities

Bioinformatics ◽

10.1093/bioinformatics/bty941 ◽

2018 ◽

Vol 35 (13) ◽

pp. 2332-2334 ◽

Cited By ~ 16

Author(s):

Federico Baldini ◽

Almut Heinken ◽

Laurent Heirendt ◽

Stefania Magnusdottir ◽

Ronan M T Fleming ◽

...

Keyword(s):

Microbial Communities ◽

Microbial Interactions ◽

Microbial Genome ◽

Metagenomic Data ◽

Metabolic Interactions ◽

Constraint Based Modeling ◽

Genome Scale

Abstract Motivation The application of constraint-based modeling to functionally analyze metagenomic data has been limited so far, partially due to the absence of suitable toolboxes. Results To address this gap, we created a comprehensive toolbox to model (i) microbe–microbe and host–microbe metabolic interactions, and (ii) microbial communities using microbial genome-scale metabolic reconstructions and metagenomic data. The Microbiome Modeling Toolbox extends the functionality of the constraint-based reconstruction and analysis toolbox. Availability and implementation The Microbiome Modeling Toolbox and the tutorials at https://git.io/microbiomeModelingToolbox.

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Oral Spirochetes Implicated in Dental Diseases Are Widespread in Normal Human Subjects and Carry Extremely Diverse Integron Gene Cassettes

Applied and Environmental Microbiology ◽

10.1128/aem.00564-12 ◽

2012 ◽

Vol 78 (15) ◽

pp. 5288-5296 ◽

Cited By ~ 17

Author(s):

Yu-Wei Wu ◽

Mina Rho ◽

Thomas G. Doak ◽

Yuzhen Ye

Keyword(s):

Microbial Communities ◽

De Novo ◽

Human Subjects ◽

Human Microbiome ◽

Metagenomic Data ◽

De Bruijn Graph ◽

Content Type ◽

Gene Cassettes ◽

Dental Diseases ◽

Normal Human

ABSTRACTThe NIH Human Microbiome Project (HMP) has produced several hundred metagenomic data sets, allowing studies of the many functional elements in human-associated microbial communities. Here, we survey the distribution of oral spirochetes implicated in dental diseases in normal human individuals, using recombination sites associated with the chromosomal integron inTreponemagenomes, taking advantage of the multiple copies of the integron recombination sites (repeats) in the genomes, and using a targeted assembly approach that we have developed. We find that integron-containingTreponemaspecies are present in ∼80% of the normal human subjects included in the HMP. Further, we are able tode novoassemble the integron gene cassettes using our constrained assembly approach, which employs a unique application of the de Bruijn graph assembly information; most of these cassette genes were not assembled in whole-metagenome assemblies and could not be identified by mapping sequencing reads onto the known referenceTreponemagenomes due to the dynamic nature of integron gene cassettes. Our study significantly enriches the gene pool known to be carried byTreponemachromosomal integrons, totaling 826 (598 97% nonredundant) genes. We characterize the functions of these gene cassettes: many of these genes have unknown functions. The integron gene cassette arrays found in the human microbiome are extraordinarily dynamic, with different microbial communities sharing only a small number of common genes.

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Do soil bacterial communities respond differently to abrupt or gradual additions of copper?

FEMS Microbiology Ecology ◽

10.1093/femsec/fiy212 ◽

2018 ◽

Vol 95 (1) ◽

Cited By ~ 2

Author(s):

Michael McTee ◽

Lorinda Bullington ◽

Matthias C Rillig ◽

Philip W Ramsey

Keyword(s):

Heavy Metals ◽

Soil Respiration ◽

Microbial Communities ◽

Bacterial Communities ◽

Diversity Indices ◽

Microbial Populations ◽

Metal Concentrations ◽

Soil Bacterial Communities ◽

Bacterial Richness

ABSTRACTMany experiments that measure the response of microbial communities to heavy metals increase metal concentrations abruptly in the soil. However, it is unclear whether abrupt additions mimic the gradual and often long-term accumulation of these metals in the environment where microbial populations may adapt. In a greenhouse experiment that lasted 26 months, we tested whether bacterial communities and soil respiration differed between soils that received an abrupt or a gradual addition of copper or no copper at all. Bacterial richness and other diversity indices were consistently lower in the abrupt treatment compared to the ambient treatment that received no copper. The abrupt addition of copper yielded different initial bacterial communities than the gradual addition; however, these communities appeared to converge once copper concentrations were approximately equal. Soil respiration in the abrupt treatment was initially suppressed but recovered after four months. Afterwards, respiration in both the gradual and abrupt treatments wavered between being below or equal to the ambient treatment. Overall, our study indicates that gradual and abrupt additions of copper can yield similar bacterial communities and respiration, but these responses may drastically vary until copper concentrations are equal.

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MetaDEGalaxy: Galaxy workflow for differential abundance analysis of 16s metagenomic data

F1000Research ◽

10.12688/f1000research.18866.2 ◽

2019 ◽

Vol 8 ◽

pp. 726

Author(s):

Mike W.C. Thang ◽

Xin-Yi Chua ◽

Gareth Price ◽

Dominique Gorse ◽

Matt A. Field

Keyword(s):

Microbial Communities ◽

Sequence Data ◽

Metagenomic Data ◽

Marker Genes ◽

Metagenomic Sequencing ◽

Differential Analysis ◽

Biomedical Sciences ◽

Metagenomic Sequence ◽

Differential Abundance ◽

Differential Abundance Analysis

Metagenomic sequencing is an increasingly common tool in environmental and biomedical sciences. While software for detailing the composition of microbial communities using 16S rRNA marker genes is relatively mature, increasingly researchers are interested in identifying changes exhibited within microbial communities under differing environmental conditions. In order to gain maximum value from metagenomic sequence data we must improve the existing analysis environment by providing accessible and scalable computational workflows able to generate reproducible results. Here we describe a complete end-to-end open-source metagenomics workflow running within Galaxy for 16S differential abundance analysis. The workflow accepts 454 or Illumina sequence data (either overlapping or non-overlapping paired end reads) and outputs lists of the operational taxonomic unit (OTUs) exhibiting the greatest change under differing conditions. A range of analysis steps and graphing options are available giving users a high-level of control over their data and analyses. Additionally, users are able to input complex sample-specific metadata information which can be incorporated into differential analysis and used for grouping / colouring within graphs. Detailed tutorials containing sample data and existing workflows are available for three different input types: overlapping and non-overlapping read pairs as well as for pre-generated Biological Observation Matrix (BIOM) files. Using the Galaxy platform we developed MetaDEGalaxy, a complete metagenomics differential abundance analysis workflow. MetaDEGalaxy is designed for bench scientists working with 16S data who are interested in comparative metagenomics. MetaDEGalaxy builds on momentum within the wider Galaxy metagenomics community with the hope that more tools will be added as existing methods mature.

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The impact of sequencing depth on the inferred taxonomic composition and AMR gene content of metagenomic samples

10.1101/593301 ◽

2019 ◽

Author(s):

H. Soon Gweon ◽

Liam P. Shaw ◽

Jeremy Swann ◽

Nicola De Maio ◽

Manal AbuOun ◽

...

Keyword(s):

Data Processing ◽

Open Source ◽

Open Source Software ◽

River Sediment ◽

Taxonomic Composition ◽

Sequencing Depth ◽

Gene Content ◽

Metagenomic Data ◽

Software Pipeline ◽

Shotgun Metagenomics

ABSTRACTBackgroundShotgun metagenomics is increasingly used to characterise microbial communities, particularly for the investigation of antimicrobial resistance (AMR) in different animal and environmental contexts. There are many different approaches for inferring the taxonomic composition and AMR gene content of complex community samples from shotgun metagenomic data, but there has been little work establishing the optimum sequencing depth, data processing and analysis methods for these samples. In this study we used shotgun metagenomics and sequencing of cultured isolates from the same samples to address these issues. We sampled three potential environmental AMR gene reservoirs (pig caeca, river sediment, effluent) and sequenced samples with shotgun metagenomics at high depth (∼200 million reads per sample). Alongside this, we cultured single-colony isolates ofEnterobacteriaceaefrom the same samples and used hybrid sequencing (short- and long-reads) to create high-quality assemblies for comparison to the metagenomic data. To automate data processing, we developed an open-source software pipeline, ‘ResPipe’.ResultsTaxonomic profiling was much more stable to sequencing depth than AMR gene content. 1 million reads per sample was sufficient to achieve <1% dissimilarity to the full taxonomic composition. However, at least 80 million reads per sample were required to recover the full richness of different AMR gene families present in the sample, and additional allelic diversity of AMR genes was still being discovered in effluent at 200 million reads per sample. Normalising the number of reads mapping to AMR genes using gene length and an exogenous spike ofThermus thermophilusDNA substantially changed the estimated gene abundance distributions. While the majority of genomic content from cultured isolates from effluent was recoverable using shotgun metagenomics, this was not the case for pig caeca or river sediment.ConclusionsSequencing depth and profiling method can critically affect the profiling of polymicrobial animal and environmental samples with shotgun metagenomics. Both sequencing of cultured isolates and shotgun metagenomics can recover substantial diversity that is not identified using the other methods. Particular consideration is required when inferring AMR gene content or presence by mapping metagenomic reads to a database. ResPipe, the open-source software pipeline we have developed, is freely available (https://gitlab.com/hsgweon/ResPipe).

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