Relevance of the microbial community to Sb and As biogeochemical cycling in natural wetlands

Abstract Background: Advances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent, however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and contributions to biogeochemical cycling. Results: We present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, identification of metabolism markers, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the community, potential microbial metabolic handoffs and metabolite exchange, and calculation of microbial community contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or from single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, and community-scale metabolic networks using a newly defined metric ‘MN-score’ (metabolic network score). METABOLIC takes ~3 hours with 40 CPU threads to process ~100 genomes and metagenomic reads within which the most compute-demanding part of hmmsearch takes ~45 mins, while it takes ~5 hours to complete hmmsearch for ~3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut.Conclusion: METABOLIC enables consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available at https://github.com/AnantharamanLab/METABOLIC under GPLv3.

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Biogeochemical Cycling by a Low-Diversity Microbial Community in Deep Groundwater

Frontiers in Microbiology ◽

10.3389/fmicb.2018.02129 ◽

2018 ◽

Vol 9 ◽

Cited By ~ 8

Author(s):

Emma Bell ◽

Tiina Lamminmäki ◽

Johannes Alneberg ◽

Anders F. Andersson ◽

Chen Qian ◽

...

Keyword(s):

Microbial Community ◽

Biogeochemical Cycling ◽

Deep Groundwater ◽

Low Diversity

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Rare Taxa Maintain Microbial Diversity and Contribute to Terrestrial Community Dynamics throughout Bark Beetle Infestation

Applied and Environmental Microbiology ◽

10.1128/aem.02245-16 ◽

2016 ◽

Vol 82 (23) ◽

pp. 6912-6919 ◽

Cited By ~ 8

Author(s):

Kristin M. Mikkelson ◽

Chelsea M. Bokman ◽

Jonathan O. Sharp

Keyword(s):

Microbial Community ◽

16S Rrna ◽

Bark Beetle ◽

Large Scale ◽

Tree Mortality ◽

Community Dynamics ◽

Alpha Diversity ◽

Biogeochemical Cycling ◽

Rrna Gene ◽

Edaphic Parameters

ABSTRACTA global phenomenon of increasing bark beetle-induced tree mortality has heightened concerns regarding ecosystem response and biogeochemical implications. Here, we explore microbial dynamics under lodgepole pines through the analysis of bulk (16S rRNA gene) and potentially active (16S rRNA) communities to understand the terrestrial ecosystem responses that are associated with this form of large-scale tree mortality. We found that the relative abundances of bulk and potentially active taxa were correlated across taxonomic levels, but at lower levels, cladal differences became more apparent. Despite this correlation, there was a strong differentiation of community composition between bulk and potentially active taxa, with further clustering associated with the stages of tree mortality. Surprisingly, community clustering as a function of tree phase had limited correlation to soil water content and total nitrogen concentrations, which were the only two measured edaphic parameters to differ in association with tree phase. Bacterial clustering is more readily explained by the observed decrease in the abundance of active, rare microorganisms after tree death in conjunction with stable alpha diversity measurements. This enables the rare fraction of the terrestrial microbial community to maintain metabolic diversity by transitioning between metabolically active and dormant states during this ecosystem disturbance and contributes disproportionately to community dynamics and archived metabolic capabilities. These results suggest that analyzing bulk and potentially active communities after beetle infestation may be a more sensitive indicator of disruption than measuring local edaphic parameters.IMPORTANCEForests around the world are experiencing unprecedented mortality due to insect infestations that are fueled in part by a changing climate. While aboveground processes have been explored, changes at the terrestrial interface that are relevant to microbial biogeochemical cycling remain largely unknown. In this study, we investigated the changing bulk and potentially active microbial communities beneath healthy and beetle-killed trees. We found that, even though few edaphic parameters were altered from beetle infestation, the rare microbes were more likely to be active and fluctuate between dormancy and metabolic activity. This indicates that rare as opposed to abundant taxa contribute disproportionately to microbial community dynamics and presumably biogeochemical cycling within these types of perturbed ecosystems.

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Spatial Variation in Microbial Community in Response to As and Pb Contamination in Paddy Soils Near a Pb-Zn Mining Site

Frontiers in Environmental Science ◽

10.3389/fenvs.2021.630668 ◽

2021 ◽

Vol 9 ◽

Author(s):

Lina Zou ◽

Yanhong Lu ◽

Yuxia Dai ◽

Muhammad Imran Khan ◽

Williamson Gustave ◽

...

Keyword(s):

Microbial Community ◽

Bacterial Community ◽

Spatial Variation ◽

Agricultural Soils ◽

Chemical Properties ◽

Biogeochemical Cycling ◽

Ammonia Nitrogen ◽

Paddy Soils ◽

Mining Site ◽

Pb Contamination

Mining activity is a growing environmental concern as it contributes to heavy metals (HMs) pollution in agricultural soils. Microbial communities play an important role in the biogeochemical cycling of HMs and have the potential to be used as bioindicators. Arsenic (As) and lead (Pb) are the most hazardous HMs and are mainly originated from mining activities. However, spatial variation in microbial community in response to As and Pb contamination in paddy soils remains overlooked. In this study, the biological and chemical properties of sixteen soil samples from four sites (N01, N02, N03, and N04) near a Pb-Zn mining site at different As and Pb levels were examined. The results showed that soil pH, total As and Pb, bioavailable As and Pb, nitrate-nitrogen (NO3−-N) and ammonia-nitrogen (NH4+-N) were the most important factors in shaping the bacterial community structure. In addition, significant correlations between various bacterial genera and As and Pb concentrations were observed, indicating their potential roles in As and Pb biogeochemical cycling. These findings provide insights into the variation of paddy soil bacterial community in soils co-contaminated with different levels of As and Pb.

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Biochar induced soil microbial community change: Implications for biogeochemical cycling of carbon, nitrogen and phosphorus

Pedobiologia ◽

10.1016/j.pedobi.2011.07.005 ◽

2011 ◽

Vol 54 (5-6) ◽

pp. 309-320 ◽

Cited By ~ 373

Author(s):

Craig R. Anderson ◽

Leo M. Condron ◽

Tim J. Clough ◽

Mark Fiers ◽

Alison Stewart ◽

...

Keyword(s):

Microbial Community ◽

Soil Microbial Community ◽

Biogeochemical Cycling ◽

Community Change ◽

Nitrogen And Phosphorus ◽

Soil Microbial

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METABOLIC: High-throughput profiling of microbial genomes for functional traits, biogeochemistry, and community-scale metabolic networks

10.1101/761643 ◽

2019 ◽

Cited By ~ 10

Author(s):

Zhichao Zhou ◽

Patricia Q. Tran ◽

Adam M. Breister ◽

Yang Liu ◽

Kristopher Kieft ◽

...

Keyword(s):

Microbial Community ◽

Microbial Communities ◽

Microbial Ecology ◽

Single Cell ◽

Metabolic Networks ◽

Biogeochemical Cycling ◽

Microbial Interactions ◽

Microbial Genomes ◽

Biogeochemical Models ◽

Genome Scale

ABSTRACTBackgroundAdvances in microbiome science are being driven in large part due to our ability to study and infer microbial ecology from genomes reconstructed from mixed microbial communities using metagenomics and single-cell genomics. Such omics-based techniques allow us to read genomic blueprints of microorganisms, decipher their functional capacities and activities, and reconstruct their roles in biogeochemical processes. Currently available tools for analyses of genomic data can annotate and depict metabolic functions to some extent, however, no standardized approaches are currently available for the comprehensive characterization of metabolic predictions, metabolite exchanges, microbial interactions, and contributions to biogeochemical cycling.ResultsWe present METABOLIC (METabolic And BiogeOchemistry anaLyses In miCrobes), a scalable software to advance microbial ecology and biogeochemistry using genomes at the resolution of individual organisms and/or microbial communities. The genome-scale workflow includes annotation of microbial genomes, motif validation of biochemically validated conserved protein residues, identification of metabolism markers, metabolic pathway analyses, and calculation of contributions to individual biogeochemical transformations and cycles. The community-scale workflow supplements genome-scale analyses with determination of genome abundance in the community, potential microbial metabolic handoffs and metabolite exchange, and calculation of microbial community contributions to biogeochemical cycles. METABOLIC can take input genomes from isolates, metagenome-assembled genomes, or from single-cell genomes. Results are presented in the form of tables for metabolism and a variety of visualizations including biogeochemical cycling potential, representation of sequential metabolic transformations, and community-scale metabolic networks using a newly defined metric ‘MN-score’ (metabolic network score). METABOLIC takes ∼3 hours with 40 CPU threads to process ∼100 genomes and metagenomic reads within which the most compute-demanding part of hmmsearch takes ∼45 mins, while it takes ∼5 hours to complete hmmsearch for ∼3600 genomes. Tests of accuracy, robustness, and consistency suggest METABOLIC provides better performance compared to other software and online servers. To highlight the utility and versatility of METABOLIC, we demonstrate its capabilities on diverse metagenomic datasets from the marine subsurface, terrestrial subsurface, meadow soil, deep sea, freshwater lakes, wastewater, and the human gut.ConclusionMETABOLIC enables consistent and reproducible study of microbial community ecology and biogeochemistry using a foundation of genome-informed microbial metabolism, and will advance the integration of uncultivated organisms into metabolic and biogeochemical models. METABOLIC is written in Perl and R and is freely available at https://github.com/AnantharamanLab/METABOLIC under GPLv3.

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A peek in the micro-sized world: a review of design principles, engineering tools, and applications of engineered microbial community

Biochemical Society Transactions ◽

10.1042/bst20190172 ◽

2020 ◽

Vol 48 (2) ◽

pp. 399-409

Author(s):

Baizhen Gao ◽

Rushant Sabnis ◽

Tommaso Costantini ◽

Robert Jinkerson ◽

Qing Sun

Keyword(s):

Microbial Community ◽

Microbial Communities ◽

Environmental Remediation ◽

Real Life ◽

Design Principles ◽

Microbial Interactions ◽

Potential Applications ◽

New Gene ◽

Global Biogeochemical Cycles ◽

Synthetic Microbial Communities

Microbial communities drive diverse processes that impact nearly everything on this planet, from global biogeochemical cycles to human health. Harnessing the power of these microorganisms could provide solutions to many of the challenges that face society. However, naturally occurring microbial communities are not optimized for anthropogenic use. An emerging area of research is focusing on engineering synthetic microbial communities to carry out predefined functions. Microbial community engineers are applying design principles like top-down and bottom-up approaches to create synthetic microbial communities having a myriad of real-life applications in health care, disease prevention, and environmental remediation. Multiple genetic engineering tools and delivery approaches can be used to ‘knock-in' new gene functions into microbial communities. A systematic study of the microbial interactions, community assembling principles, and engineering tools are necessary for us to understand the microbial community and to better utilize them. Continued analysis and effort are required to further the current and potential applications of synthetic microbial communities.

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