Genes and genome-resolved metagenomics reveal the microbial functional make up of Amazon peatlands under geochemical gradients.


Journal

Environmental microbiology
ISSN: 1462-2920
Titre abrégé: Environ Microbiol
Pays: England
ID NLM: 100883692

Informations de publication

Date de publication:
11 2023
Historique:
received: 20 12 2022
accepted: 12 07 2023
medline: 15 11 2023
pubmed: 28 7 2023
entrez: 28 7 2023
Statut: ppublish

Résumé

The Pastaza-Marañón Foreland Basin (PMFB) holds the most extensive tropical peatland area in South America. PMFB peatlands store ~7.07 Gt of organic carbon interacting with multiple microbial heterotrophic, methanogenic, and other aerobic/anaerobic respirations. Little is understood about the contribution of distinct microbial community members inhabiting tropical peatlands. Here, we studied the metagenomes of three geochemically distinct peatlands spanning minerotrophic, mixed, and ombrotrophic conditions. Using gene- and genome-centric approaches, we evaluate the functional potential of the underlying microbial communities. Abundance analyses show significant differences in C, N, P, and S acquisition genes. Furthermore, community interactions mediated by toxin-antitoxin and CRISPR-Cas systems were enriched in oligotrophic soils, suggesting that non-metabolic interactions may exert additional controls in low-nutrient environments. Additionally, we reconstructed 519 metagenome-assembled genomes spanning 28 phyla. Our analyses detail key differences across the geochemical gradient in the predicted microbial populations involved in degradation of organic matter, and the cycling of N and S. Notably, we observed differences in the nitric oxide (NO) reduction strategies between sites with high and low N

Identifiants

pubmed: 37501535
doi: 10.1111/1462-2920.16469
doi:

Substances chimiques

Soil 0

Types de publication

Journal Article Research Support, U.S. Gov't, Non-P.H.S.

Langues

eng

Sous-ensembles de citation

IM

Pagination

2388-2403

Informations de copyright

© 2023 Applied Microbiology International and John Wiley & Sons Ltd.

Références

Alneberg, J., Bjarnason, B.S., de Bruijn, I., Schirmer, M., Quick, J., Ijaz, U.Z. et al. (2014) Binning metagenomic contigs by coverage and composition. Nature Methods, 11, 1144-1146.
Amazonas, N.T., Viani, R.A.G., Rego, M.G.A., Camargo, F.F., Fujihara, R.T. & Valsechi, O.A. (2018) Soil macrofauna density and diversity across a chronosequence of tropical forest restoration in southeastern Brazil. Brazilian Journal of Biology, 78, 449-456.
Anders, S. & Huber, W. (2010) Differential expression analysis for sequence count data. Genome Biology, 11, R106.
Andersen, R., Chapman, S.J. & Artz, R.R.E. (2013) Microbial communities in natural and disturbed peatlands: a review. Soil Biology and Biochemistry, 57, 979-994.
Anderson, M.J. & Walsh, D.C.I. (2013) PERMANOVA, ANOSIM, and the mantel test in the face of heterogeneous dispersions: what null hypothesis are you testing? Ecological Monographs, 83, 557-574.
Bowers, R.M., Kyrpides, N.C., Stepanauskas, R., Harmon-Smith, M., Doud, D., Reddy, T.B.K. et al. (2017) Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nature Biotechnology, 35, 725-731.
Brown, S.P., le Chat, L., de Paepe, M. & Taddei, F. (2006) Ecology of microbial invasions: amplification allows virus carriers to invade more rapidly when rare. Current Biology, 16, 2048-2052.
Buessecker, S., Zamora, Z., Sarno, A.F., Finn, D.R., Hoyt, A.M., van Haren, J. et al. (2021) Microbial communities and interactions of nitrogen oxides with methanogenesis in diverse peatlands of the Amazon Basin. Frontiers in Microbiology, 12, 1564.
Carr, R. & Borenstein, E. (2014) Comparative analysis of functional metagenomic annotation and the mappability of short reads. PLoS One, 9, e105776.
Chaumeil, P.-A., Mussig, A.J., Hugenholtz, P. & Parks, D.H. (2020) GTDB-Tk: a toolkit to classify genomes with the genome taxonomy database. Bioinformatics, 36, 1925-1927.
Chen, J. & Strous, M. (2013) Denitrification and aerobic respiration, hybrid electron transport chains and co-evolution. Biochimica et Biophysica Acta (BBA)-Bioenergetics, 1827, 136-144.
Cornelis, P. & Matthijs, S. (2002) Diversity of siderophore-mediated iron uptake systems in fluorescent pseudomonads: not only pyoverdines. Environmental Microbiology, 4, 787-798.
Cornforth, D.M. & Foster, K.R. (2013) Competition sensing: the social side of bacterial stress responses. Nature Reviews. Microbiology, 11, 285-293.
Davies, E.V., James, C.E., Kukavica-Ibrulj, I., Levesque, R.C., Brockhurst, M.A. & Winstanley, C. (2016) Temperate phages enhance pathogen fitness in chronic lung infection. The ISME Journal, 10, 2553-2555.
Ebrahimi, A., Schwartzman, J. & Cordero, O.X. (2019) Cooperation and spatial self-organization determine rate and efficiency of particulate organic matter degradation in marine bacteria. Proceedings of the National Academy of Sciences of the United States of America, 116, 23309-23316.
Elliott, D.R., Caporn, S.J.M., Nwaishi, F., Nilsson, R.H. & Sen, R. (2015) Bacterial and fungal communities in a degraded ombrotrophic peatland undergoing natural and managed re-vegetation. PLoS One, 10, e0124726.
Eren, A.M., Esen, O.C., Quince, C., Vineis, J.H., Morrison, H.G., Sogin, M.L. et al. (2015) Anvi'o: An advanced analysis and visualization platform for ‘omics data. PeerJ, 3, e1319.
Espenberg, M., Truu, M., Mander, Ü., Kasak, K., Nõlvak, H., Ligi, T. et al. (2018) Differences in microbial community structure and nitrogen cycling in natural and drained tropical peatland soils. Scientific Reports, 8, 1-12.
Evans, C., Brandsma, J., Meredith, M.P., Thomas, D.N., Venables, H.J., Pond, D.W. et al. (2021) Shift from carbon flow through the microbial loop to the viral shunt in coastal Antarctic waters during austral summer. Microorganisms, 9, 460.
Fasani, R.A. & Savageau, M.A. (2013) Molecular mechanisms of multiple toxin-antitoxin systems are coordinated to govern the persister phenotype. Proceedings of the National Academy of Sciences of the United States of America, 110, E2528.
Fierer, N., Leff, J.W., Adams, B.J., Nielsen, U.N., Bates, S.T., Lauber, C.L. et al. (2012) Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proceedings of the National Academy of Sciences of the United States of America, 109, 21390-21395.
Finn, D.R., Ziv-El, M., van Haren, J., Park, J.G., del Aguila-Pasquel, J., Urquiza-Muñoz, J.D. et al. (2020) Methanogens and methanotrophs show nutrient-dependent community assemblage patterns across tropical peatlands of the Pastaza-Marañón Basin, Peruvian Amazonia. Frontiers in Microbiology, 11, 746.
Garber, A.I., Nealson, K.H., Okamoto, A., McAllister, S.M., Chan, C.S., Barco, R.A. et al. (2020) FeGenie: a comprehensive tool for the identification of iron genes and iron gene neighborhoods in genome and metagenome assemblies. Frontiers in Microbiology, 11, 37.
Grein, F., Ramos, A.R., Venceslau, S.S. & Pereira, I.A.C. (2013) Unifying concepts in anaerobic respiration: insights from dissimilatory sulfur metabolism. Biochimica et Biophysica Acta (BBA)-Bioenergetics, 1827, 145-160.
Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. (2013) QUAST: quality assessment tool for genome assemblies. Bioinformatics, 29, 1072-1075.
Hättenschwiler, S. & Gasser, P. (2005) Soil animals alter plant litter diversity effects on decomposition. Proceedings of the National Academy of Sciences of the United States of America, 102, 1519-1524.
Hausmann, B., Pelikan, C., Herbold, C.W., Köstlbacher, S., Albertsen, M., Eichorst, S.A. et al. (2018) Peatland Acidobacteria with a dissimilatory sulfur metabolism. The ISME Journal, 12, 1729-1742.
Hendriks, J., Oubrie, A., Castresana, J., Urbani, A., Gemeinhardt, S. & Saraste, M. (2000) Nitric oxide reductases in bacteria. Biochimica et Biophysica Acta (BBA)-Bioenergetics, 1459, 266-273.
Hyatt, D., Chen, G.L., LoCascio, P.F., Land, M.L., Larimer, F.W. & Hauser, L.J. (2010) Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics, 11, 1-11.
Juottonen, H., Galand, P.E., Tuittila, E.S., Laine, J., Fritze, H. & Yrjälä, K. (2005) Methanogen communities and bacteria along an ecohydrological gradient in a northern raised bog complex. Environmental Microbiology, 7, 1547-1557.
Jurėnas, D., Fraikin, N., Goormaghtigh, F. & Van Melderen, L. (2022) Biology and evolution of bacterial toxin-antitoxin systems. Nature Reviews. Microbiology, 20, 335-350.
Kalam, S., Basu, A., Ahmad, I., Sayyed, R.Z., El-Enshasy, H.A., Dailin, D.J. et al. (2020) Recent understanding of soil acidobacteria and their ecological significance: a critical review. Frontiers in Microbiology, 11, 2712.
Kanehisa, M. & Goto, S. (2000) KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Research, 28, 27-30.
Kanehisa, M., Sato, Y. & Morishima, K. (2016) BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. Journal of Molecular Biology, 428, 726-731.
Kang, D.D., Froula, J., Egan, R. & Wang, Z. (2015) MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ, 2015, e1165.
Kang, D.D., Li, F., Kirton, E., Thomas, A., Egan, R., An, H. et al. (2019) MetaBAT 2: An adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ, 7, e7359.
Kanokratana, P., Uengwetwanit, T., Rattanachomsri, U., Bunterngsook, B., Nimchua, T., Tangphatsornruang, S. et al. (2011) Insights into the phylogeny and metabolic potential of a primary tropical peat swamp forest microbial community by metagenomic analysis. Microbial Ecology, 61, 518-528.
Kerfahi, D., Tripathi, B.M., Slik, J.W.F., Sukri, R.S., Jaafar, S., Dong, K. et al. (2019) Soil metagenome of tropical white sand heath forests in Borneo: what functional traits are associated with an extreme environment within the tropical rainforest? Pedosphere, 29, 12-23.
Kerou, M., Offre, P., Valledor, L., Abby, S.S., Melcher, M., Nagler, M. et al. (2016) Proteomics and comparative genomics of Nitrososphaera viennensis reveal the core genome and adaptations of archaeal ammonia oxidizers. Proceedings of the National Academy of Sciences of the United States of America, 113, E7937-E7946.
Kielak, A.M., Barreto, C.C., Kowalchuk, G.A., van Veen, J.A. & Kuramae, E.E. (2016) The ecology of Acidobacteria: moving beyond genes and genomes. Frontiers in Microbiology, 7, 7.
Klüber, H.D. & Conrad, R. (1998) Inhibitory effects of nitrate, nitrite, NO and N2O on methanogenesis by Methanosarcina barkeri and Methanobacterium bryantii. FEMS Microbiology Ecology, 25, 331-339.
Kujala, K., Mikkonen, A., Saravesi, K., Ronkanen, A.-K. & Tiirola, M. (2018) Microbial diversity along a gradient in peatlands treating mining-affected waters. FEMS Microbiology Ecology, 94, 145.
Lahteenoja, O. & Page, S. (2011) High diversity of tropical peatland ecosystem types in the Pastaza-Maraón basin, Peruvian Amazonia. Journal of Geophysical Research: Biogeosciences, 116, G02025.
Lähteenoja, O., Reátegui, Y.R., Räsänen, M., Torres, D.D.C., Oinonen, M. & Page, S. (2012) The large Amazonian peatland carbon sink in the subsiding Pastaza-Marañón foreland basin, Peru. Global Change Biology, 18, 164-178.
Lähteenoja, O., Ruokolainen, K., Schulman, L. & Alvarez, J. (2009) Amazonian floodplains harbour minerotrophic and ombrotrophic peatlands. Catena, 79, 140-145.
Langmead, B. & Salzberg, S.L. (2012) Fast gapped-read alignment with bowtie 2. Nature Methods, 9, 357-359.
Lecomte, S.M., Achouak, W., Abrouk, D., Heulin, T., Nesme, X. & Haichar, F.e.Z. (2018) Diversifying anaerobic respiration strategies to compete in the rhizosphere. Front Environmental Sciences, 6, 139.
Lee, M.D. (2019) GToTree: a user-friendly workflow for phylogenomics. Bioinformatics, 35, 4162-4164.
Li, D., Luo, R., Liu, C.M., Leung, C.M., Ting, H.F., Sadakane, K. et al. (2016) MEGAHIT v1.0: a fast and scalable metagenome assembler driven by advanced methodologies and community practices. Methods, 102, 3-11.
Lim, N.Y.N., Roco, C.A. & Frostegård, Å. (2016) Transparent DNA/RNA co-extraction workflow protocol suitable for inhibitor-rich environmental samples that focuses on complete DNA removal for transcriptomic analyses. Frontiers in Microbiology, 7, 7.
Lovley, D.R. & Klug, M.J. (1983) Sulfate reducers can outcompete methanogens at freshwater sulfate concentrations. Applied and Environmental Microbiology, 45, 187-192.
Lund, P., Tramonti, A. & de Biase, D. (2014) Coping with low pH: molecular strategies in neutralophilic bacteria. FEMS Microbiology Reviews, 38, 1091-1125.
Markowitz, V.M., Chen, I.-M.A., Palaniappan, K., Chu, K., Szeto, E., Grechkin, Y. et al. (2012) IMG: the integrated microbial genomes database and comparative analysis system. Nucleic Acids Research, 40, D115-D122.
Melton, J.R., Chan, E., Millard, K., Fortier, M., Winton, R.S., Martín-López, J.M. et al. (2022) A map of global peatland extent created using machine learning (peat-ML). Geoscientific Model Development, 15, 4709-4738.
Murphy, C.L., Sheremet, A., Dunfield, P.F., Spear, J.R., Stepanauskas, R., Woyke, T. et al. (2021) Genomic analysis of the yet-uncultured binatota reveals broad methylotrophic, alkane-degradation, and pigment production capacities. MBio, 12, 12.
Nayfach, S., Bradley, P.H., Wyman, S.K., Laurent, T.J., Williams, A., Eisen, J.A. et al. (2015) Automated and accurate estimation of gene family abundance from shotgun m etagenomes. PLoS Computational Biology, 11, e1004573.
Oksanen, J., Simpson, G.L., Blanchet, F.G., Kindt, R., Legendre, P., Minchin, P.R. et al. (2022) vegan: Community Ecology Package. R package version 2.6-2.
Page, S.E. & Baird, A.J. (2016) Peatlands and global change: response and resilience. Annual Review of Environment and Resources, 41, 35-57.
Page, S.E., Rieley, J.O. & Banks, C.J. (2011) Global and regional importance of the tropical peatland carbon pool. Global Change Biology, 17, 798-818.
Parks, D.H., Imelfort, M., Skennerton, C.T., Hugenholtz, P. & Tyson, G.W. (2015) CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Research, 25, 1043-1055.
Parks, D.H., Rinke, C., Chuvochina, M., Chaumeil, P.A., Woodcroft, B.J., Evans, P.N. et al. (2017) Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nature Microbiology, 2, 1533-1542.
Quinlan, A.R. & Hall, I.M. (2010) BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics, 26, 841-842.
Ribeiro, K., Pacheco, F.S., Ferreira, J.W., Sousa-Neto, E.R.d., Hastie, A., Filho, G.C.K. et al. (2021) Tropical peatlands and their contribution to the global carbon cycle and climate change. Global Change Biology, 27, 489-505.
Rieley, J. & Page, S. (2016) Tropical peatland of the world. In M. Osaki & N. Tsuji (Eds.), Tropical Peatland Ecosystems. Springer. https://doi.org/10.1007/978-4-431-55681-7_1
Rodriguez-R, L.M., Gunturu, S., Tiedje, J.M., Cole, J.R. & Konstantinidis, K.T. (2018) Nonpareil 3: fast estimation of metagenomic coverage and sequence diversity. mSystems, 3, e00039-18.
Schwarz, J., Schumacher, K., Brameyer, S. & Jung, K. (2022) Bacterial battle against acidity. FEMS Microbiology Reviews, 46, fuac037.
Sieber, C.M.K., Probst, A.J., Sharrar, A., Thomas, B.C., Hess, M., Tringe, S.G. et al. (2018) Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nature Microbiology, 3, 836-843.
Sjögersten, S., Cheesman, A.W., Lopez, O. & Turner, B.L. (2011) Biogeochemical processes along a nutrient gradient in a tropical ombrotrophic peatland. Biogeochemistry, 104, 147-163.
Sun, F.L., Fan, L.L., Wang, Y.S. & Huang, L.Y. (2019) Metagenomic analysis of the inhibitory effect of chromium on microbial communities and removal efficiency in A2O sludge. Journal of Hazardous Materials, 368, 523-529.
Sun, H., Terhonen, E., Koskinen, K., Paulin, L., Kasanen, R. & Asiegbu, F.O. (2014) Bacterial diversity and community structure along different peat soils in boreal forest. Applied Soil Ecology, 74, 37-45.
Tang, Z., Xu, W., Zhou, G., Bai, Y., Li, J., Tang, X. et al. (2018) Patterns of plant carbon, nitrogen, and phosphorus concentration in relation to productivity in China's terrestrial ecosystems. Proceedings of the National Academy of Sciences of the United States of America, 115, 4033-4038.
Taş, N., Prestat, E., Wang, S., Wu, Y., Ulrich, C., Kneafsey, T. et al. (2018) Landscape topography structures the soil microbiome in arctic polygonal tundra. Nature Communications, 9, 1-13.
Teh, Y., Murphy, W.A., Berrio, J.C., Boom, A. & Page, S.E. (2017) Seasonal variability in methane and nitrous oxide fluxes from tropical peatlands in the western Amazon basin. Biogeosciences, 14, 3669-3683.
van Haren, J., Brewer, P.E., Kurtzberg, L., Wehr, R.N., Springer, V.L., Espinoza, R.T. et al. (2021) A versatile gas flux chamber reveals high tree stem CH4 emissions in Amazonian peatland. Agricultural and Forest Meteorology, 307, 108504.
Venturini, A.M., Gontijo, J.B., Mandro, J.A., Paula, F.S., Yoshiura, C.A., da França, A.G. et al. (2022) Genome-resolved metagenomics reveals novel archaeal and bacterial genomes from Amazonian forest and pasture soils. Microbial Genomics, 8, 000853.
Wang, S., Yan, Z., Wang, P., Zheng, X. & Fan, J. (2020) Comparative metagenomics reveals the microbial diversity and metabolic potentials in the sediments and surrounding seawaters of Qinhuangdao mariculture area. PLoS One, 15, e0234128.
Wang, S., Zhuang, Q., Lähteenoja, O., Draper, F.C. & Cadillo-Quiroz, H. (2018) Potential shift from a carbon sink to a source in Amazonian peatlands under a changing climate. Proceedings of the National Academy of Sciences of the United States of America, 115, 12407-12412.
Wilson, C., Gloor, M., Gatti, L.V., Miller, J.B., Monks, S.A., McNorton, J. et al. (2016) Contribution of regional sources to atmospheric methane over the Amazon Basin in 2010 and 2011. Global Biogeochem Cycles, 30, 400-420.
Woodcroft, B.J., Singleton, C.M., Boyd, J.A., Evans, P.N., Emerson, J.B., Zayed, A.A.F. et al. (2018) Genome-centric view of carbon processing in thawing permafrost. Nature, 560, 49-54.
Wu, Y.-W., Simmons, B.A. & Singer, S.W. (2016) MaxBin2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics, 32, 605-607.
Yu, G., Jiang, Y., Wang, J., Zhang, H. & Luo, H. (2018) BMC3C: binning metagenomic contigs using codon usage, sequence composition and read coverage. Bioinformatics, 34, 4172-4179.
Yu, G., Smith, D.K., Zhu, H., Guan, Y. & Lam, T.T.Y. (2017) Ggtree: an r package for visualization and annotation of phylogenetic trees with their covariates and other associated data. Methods in Ecology and Evolution, 8, 28-36.
Zhou, X., Zhang, Z., Tian, L., Li, X. & Tian, C. (2017) Microbial communities in peatlands along a chronosequence on the Sanjiang plain, China. Scientific Reports, 7, 1-11.

Auteurs

Michael J Pavia (MJ)

School of Life Sciences, Arizona State University, Tempe, Arizona, USA.
Swette Center for Environmental Biotechnology, Biodesign Institute, Arizona State University, Tempe, Arizona, USA.

Damien Finn (D)

School of Life Sciences, Arizona State University, Tempe, Arizona, USA.

Franco Macedo-Tafur (F)

Laboratory of Soil Research, Research Institute of Amazonia's Natural Resources, National University of the Peruvian Amazon, Iquitos, Loreto, Peru.

Rodil Tello-Espinoza (R)

Laboratory of Soil Research, Research Institute of Amazonia's Natural Resources, National University of the Peruvian Amazon, Iquitos, Loreto, Peru.
School of Forestry, National University of the Peruvian Amazon, Iquitos, Loreto, Peru.

Christa Penaccio (C)

Joint Genome Institute, Lawrence Berkeley National Laboratory, Berkeley, California, USA.

Nicholas Bouskill (N)

Climate and Ecosystem Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA.

Hinsby Cadillo-Quiroz (H)

School of Life Sciences, Arizona State University, Tempe, Arizona, USA.
Swette Center for Environmental Biotechnology, Biodesign Institute, Arizona State University, Tempe, Arizona, USA.

Articles similaires

Populus Soil Microbiology Soil Microbiota Fungi
Aerosols Humans Decontamination Air Microbiology Masks
Coal Metagenome Phylogeny Bacteria Genome, Bacterial
Semiconductors Photosynthesis Polymers Carbon Dioxide Bacteria

Classifications MeSH