A global survey of arsenic-related genes in soil microbiomes

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Abstract

Background

Environmental resistomes include transferable microbial genes. One important resistome component is resistance to arsenic, a ubiquitous and toxic metalloid that can have negative and chronic consequences for human and animal health. The distribution of arsenic resistance and metabolism genes in the environment is not well understood. However, microbial communities and their resistomes mediate key transformations of arsenic that are expected to impact both biogeochemistry and local toxicity.

Results

We examined the phylogenetic diversity, genomic location (chromosome or plasmid), and biogeography of arsenic resistance and metabolism genes in 922 soil genomes and 38 metagenomes. To do so, we developed a bioinformatic toolkit that includes BLAST databases, hidden Markov models and resources for gene-targeted assembly of nine arsenic resistance and metabolism genes: acr3, aioA, arsB, arsC (grx), arsC (trx), arsD, arsM, arrA, and arxA. Though arsenic-related genes were common, they were not universally detected, contradicting the common conjecture that all organisms have them. From major clades of arsenic-related genes, we inferred their potential for horizontal and vertical transfer. Different types and proportions of genes were detected across soils, suggesting microbial community composition will, in part, determine local arsenic toxicity and biogeochemistry. While arsenic-related genes were globally distributed, particular sequence variants were highly endemic (e.g., acr3), suggesting dispersal limitation. The gene encoding arsenic methylase arsM was unexpectedly abundant in soil metagenomes (median 48%), suggesting that it plays a prominent role in global arsenic biogeochemistry.

Conclusions

Our analysis advances understanding of arsenic resistance, metabolism, and biogeochemistry, and our approach provides a roadmap for the ecological investigation of environmental resistomes.

Electronic supplementary material

The online version of this article (10.1186/s12915-019-0661-5) contains supplementary material, which is available to authorized users.

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Most cited references 55

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The under-recognized dominance of Verrucomicrobia in soil bacterial communities.

Gaddy Bergmann, Scott T. Bates, Kathryn G. Eilers … (2011)

Verrucomicrobia are ubiquitous in soil, but members of this bacterial phylum are thought to be present at low frequency in soil, with few studies focusing specifically on verrucomicrobial abundance, diversity, and distribution. Here we used barcoded pyrosequencing to analyze verrucomicrobial communities in surface soils collected across a range of biomes in Antarctica, Europe, and the Americas (112 samples), as well as soils collected from pits dug in a montane coniferous forest (69 samples). Data collected from surface horizons indicate that Verrucomicrobia average 23% of bacterial sequences, making them far more abundant than had been estimated. We show that this underestimation is likely due to primer bias, as many of the commonly used PCR primers appear to exclude verrucomicrobial 16S rRNA genes during amplification. Verrucomicrobia were detected in 180 out of 181 soils examined, with members of the class Spartobacteria dominating verrucomicrobial communities in nearly all biomes and soil depths. The relative abundance of Verrucomicrobia was highest in grasslands and in subsurface soil horizons, where they were often the dominant bacterial phylum. Although their ecology remains poorly understood, Verrucomicrobia appear to be dominant in many soil bacterial communities across the globe, making additional research on their ecology clearly necessary.

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FunGene: the functional gene pipeline and repository

Jordan Fish, Benli Chai, Qiong Wang … (2013)

Ribosomal RNA genes have become the standard molecular markers for microbial community analysis for good reasons, including universal occurrence in cellular organisms, availability of large databases, and ease of rRNA gene region amplification and analysis. As markers, however, rRNA genes have some significant limitations. The rRNA genes are often present in multiple copies, unlike most protein-coding genes. The slow rate of change in rRNA genes means that multiple species sometimes share identical 16S rRNA gene sequences, while many more species share identical sequences in the short 16S rRNA regions commonly analyzed. In addition, the genes involved in many important processes are not distributed in a phylogenetically coherent manner, potentially due to gene loss or horizontal gene transfer. While rRNA genes remain the most commonly used markers, key genes in ecologically important pathways, e.g., those involved in carbon and nitrogen cycling, can provide important insights into community composition and function not obtainable through rRNA analysis. However, working with ecofunctional gene data requires some tools beyond those required for rRNA analysis. To address this, our Functional Gene Pipeline and Repository (FunGene; http://fungene.cme.msu.edu/) offers databases of many common ecofunctional genes and proteins, as well as integrated tools that allow researchers to browse these collections and choose subsets for further analysis, build phylogenetic trees, test primers and probes for coverage, and download aligned sequences. Additional FunGene tools are specialized to process coding gene amplicon data. For example, FrameBot produces frameshift-corrected protein and DNA sequences from raw reads while finding the most closely related protein reference sequence. These tools can help provide better insight into microbial communities by directly studying key genes involved in important ecological processes.

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Global biogeography of microbial nitrogen-cycling traits in soil.

Michaeline Nelson, Jennifer Martiny, Adam C. Martiny (2016)

Microorganisms drive much of the Earth's nitrogen (N) cycle, but we still lack a global overview of the abundance and composition of the microorganisms carrying out soil N processes. To address this gap, we characterized the biogeography of microbial N traits, defined as eight N-cycling pathways, using publically available soil metagenomes. The relative frequency of N pathways varied consistently across soils, such that the frequencies of the individual N pathways were positively correlated across the soil samples. Habitat type, soil carbon, and soil N largely explained the total N pathway frequency in a sample. In contrast, we could not identify major drivers of the taxonomic composition of the N functional groups. Further, the dominant genera encoding a pathway were generally similar among habitat types. The soil samples also revealed an unexpectedly high frequency of bacteria carrying the pathways required for dissimilatory nitrate reduction to ammonium, a little-studied N process in soil. Finally, phylogenetic analysis showed that some microbial groups seem to be N-cycling specialists or generalists. For instance, taxa within the Deltaproteobacteria encoded all eight N pathways, whereas those within the Cyanobacteria primarily encoded three pathways. Overall, this trait-based approach provides a baseline for investigating the relationship between microbial diversity and N cycling across global soils.

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Author and article information

Contributors

Ashley Shade:

ORCID: http://orcid.org/0000-0002-7189-3067

shadeash@msu.edu

Journal

Journal ID (nlm-ta): BMC Biol

Journal ID (iso-abbrev): BMC Biol

Title: BMC Biology

Publisher: BioMed Central (London )

ISSN (Electronic): 1741-7007

Publication date (Electronic): 30 May 2019

Publication date PMC-release: 30 May 2019

Publication date Collection: 2019

Volume: 17

Electronic Location Identifier: 45

Affiliations

[1 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Department of Microbiology and Molecular Genetics, , Michigan State University, ; East Lansing, MI 48824 USA

[2 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Environmental and Integrative Toxicological Sciences Doctoral Program, , Michigan State University, ; East Lansing, MI 48824 USA

[3 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Institute for Cyber-Enabled Research, , Michigan State University, ; East Lansing, MI 48824 USA

[4 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Program in Ecology, Evolutionary Biology and Behavior, , Michigan State University, ; East Lansing, MI 48824 USA

[5 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Department of Plant, Soil, and Microbial Sciences, , Michigan State University, ; East Lansing, MI 48824 USA

[6 ]ISNI 0000 0001 2150 1785, GRID grid.17088.36, Plant Resilience Institute, , Michigan State University, ; East Lansing, MI 48834 USA

Author information

Ashley Shade http://orcid.org/0000-0002-7189-3067

Article

Publisher ID: 661

DOI: 10.1186/s12915-019-0661-5

PMC ID: 6543643

PubMed ID: 31146755

SO-VID: ef0fb9a8-c403-4394-8b33-684e5f018617

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 19 November 2018

Date accepted : 2 May 2019

Funding

Funded by: FundRef http://dx.doi.org/10.13039/100000155, Division of Environmental Biology;

Award ID: 1655425

Award ID: 1749544

Award Recipient : Ashley Shade

Funded by: FundRef http://dx.doi.org/10.13039/100000057, National Institute of General Medical Sciences;

Award ID: GM115335

Award Recipient : Ashley Shade

Funded by: FundRef http://dx.doi.org/10.13039/100005825, National Institute of Food and Agriculture;

Award ID: Hatch

Award Recipient : Ashley Shade

Funded by: FundRef http://dx.doi.org/10.13039/100006132, Office of Science;

Award ID: DE-AC02-05CH11231

Custom metadata

ScienceOpen disciplines: Life sciences

Keywords: arsenic,functional gene,bioinformatics,targeted gene assembly,horizontal gene transfer,biogeography,phylogeny,phylogenetic diversity,resistome,plasmid

Data availability:

ScienceOpen disciplines: Life sciences

Keywords: arsenic, functional gene, bioinformatics, targeted gene assembly, horizontal gene transfer, biogeography, phylogeny, phylogenetic diversity, resistome, plasmid

A global survey of arsenic-related genes in soil microbiomes

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Abstract

Background

Results

Conclusions

Electronic supplementary material

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IEEE: COVID-19 related research

Most cited references 55

The under-recognized dominance of Verrucomicrobia in soil bacterial communities.

FunGene: the functional gene pipeline and repository

Global biogeography of microbial nitrogen-cycling traits in soil.

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