Life history strategies of soil bacterial communities across global terrestrial biomes.
Journal
Nature microbiology
ISSN: 2058-5276
Titre abrégé: Nat Microbiol
Pays: England
ID NLM: 101674869
Informations de publication
Date de publication:
Nov 2023
Nov 2023
Historique:
received:
22
07
2022
accepted:
08
08
2023
medline:
8
11
2023
pubmed:
6
10
2023
entrez:
5
10
2023
Statut:
ppublish
Résumé
The life history strategies of soil microbes determine their metabolic potential and their response to environmental changes. Yet these strategies remain poorly understood. Here we use shotgun metagenomes from terrestrial biomes to characterize overarching covariations of the genomic traits that capture dominant life history strategies in bacterial communities. The emerging patterns show a triangle of life history strategies shaped by two trait dimensions, supporting previous theoretical and isolate-based studies. The first dimension ranges from streamlined genomes with simple metabolisms to larger genomes and expanded metabolic capacities. As metabolic capacities expand, bacterial communities increasingly differentiate along a second dimension that reflects a trade-off between increasing capacities for environmental responsiveness or for nutrient recycling. Random forest analyses show that soil pH, C:N ratio and precipitation patterns together drive the dominant life history strategy of soil bacterial communities and their biogeographic distribution. Our findings provide a trait-based framework to compare life history strategies of soil bacteria.
Identifiants
pubmed: 37798477
doi: 10.1038/s41564-023-01465-0
pii: 10.1038/s41564-023-01465-0
doi:
Substances chimiques
Soil
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2093-2102Subventions
Organisme : DOE | SC | Biological and Environmental Research (BER)
ID : DE-SC0020382
Organisme : DOE | SC | Biological and Environmental Research (BER)
ID : DE-SC0016410
Organisme : EC | EU Framework Programme for Research and Innovation H2020 | H2020 Excellent Science (H2020 Priority Excellent Science)
ID : erc-stg-948219, EPYC
Organisme : RCUK | Biotechnology and Biological Sciences Research Council (BBSRC)
ID : BBS/e/F/000Pr10355
Informations de copyright
© 2023. The Author(s), under exclusive licence to Springer Nature Limited.
Références
Fierer, N. Embracing the unknown: disentangling the complexities of the soil microbiome. Nat. Rev. Microbiol. 15, 579–590 (2017).
pubmed: 28824177
doi: 10.1038/nrmicro.2017.87
Bahram, M. et al. Structure and function of the global topsoil microbiome. Nature 560, 233–237 (2018).
pubmed: 30069051
doi: 10.1038/s41586-018-0386-6
Delgado-Baquerizo, M. et al. A global atlas of the dominant bacteria found in soil. Science 359, 320–325 (2018).
pubmed: 29348236
doi: 10.1126/science.aap9516
Crowther, T. W. et al. The global soil community and its influence on biogeochemistry. Science 365, eaav0550 (2019).
pubmed: 31439761
doi: 10.1126/science.aav0550
Wieder, W. R., Bonan, G. B. & Allison, S. D. Global soil carbon projections are improved by modelling microbial processes. Nat. Clim. Change 3, 909–912 (2013).
doi: 10.1038/nclimate1951
Diaz, S. et al. The global spectrum of plant form and function. Nature 529, 167–171 (2016).
pubmed: 26700811
doi: 10.1038/nature16489
Grime, J. P. Evidence for the existence of three primary strategies in plants and its relevance to ecological and evolutionary theory. Am. Nat. 111, 1169–1194 (1977).
doi: 10.1086/283244
Wright, I. J. et al. The worldwide leaf economics spectrum. Nature 428, 821–827 (2004).
pubmed: 15103368
doi: 10.1038/nature02403
Southwood, T. R. Habitat, the templet for ecological strategies? J. Anim. Ecol. 46, 337–365 (1977).
doi: 10.2307/3817
Reich, P. B. et al. The evolution of plant functional variation: traits, spectra, and strategies. Int. J. Plant Sci. 164, S143–S164 (2003).
doi: 10.1086/374368
Krause, S. et al. Trait-based approaches for understanding microbial biodiversity and ecosystem functioning. Front. Microbiol. 5, 251 (2014).
pubmed: 24904563
pmcid: 4033906
doi: 10.3389/fmicb.2014.00251
Malik, A. A. et al. Defining trait-based microbial strategies with consequences for soil carbon cycling under climate change. ISME J. https://doi.org/10.1038/s41396-019-0510-0 (2019).
Madin, J. S. et al. A synthesis of bacterial and archaeal phenotypic trait data. Sci. Data 7, 170 (2020).
pubmed: 32503990
pmcid: 7275036
doi: 10.1038/s41597-020-0497-4
Westoby, M. et al. Trait dimensions in bacteria and archaea compared to vascular plants. Ecol. Lett. 24, 1487–1504 (2021).
pubmed: 33896087
doi: 10.1111/ele.13742
Steen, A. D. et al. High proportions of bacteria and archaea across most biomes remain uncultured. ISME J. 13, 3126–3130 (2019).
pubmed: 31388130
pmcid: 6863901
doi: 10.1038/s41396-019-0484-y
Martiny, A. C. High proportions of bacteria are culturable across major biomes. ISME J. 13, 2125–2128 (2019).
pubmed: 30952994
pmcid: 6775996
doi: 10.1038/s41396-019-0410-3
Martiny, A. C. The ‘1% culturability paradigm’ needs to be carefully defined. ISME J. 14, 10–11 (2020).
pubmed: 31551529
doi: 10.1038/s41396-019-0507-8
Fierer, N., Barberán, A. & Laughlin, D. C. Seeing the forest for the genes: using metagenomics to infer the aggregated traits of microbial communities. Front. Microbiol. 5, 614 (2014).
pubmed: 25429288
pmcid: 4228856
doi: 10.3389/fmicb.2014.00614
Garnier, E. et al. Plant functional markers capture ecosystem properties during secondary succession. Ecology 85, 2630–2637 (2004).
doi: 10.1890/03-0799
Violle, C. et al. Let the concept of trait be functional! Oikos 116, 882–892 (2007).
doi: 10.1111/j.0030-1299.2007.15559.x
Fierer, N. et al. Comparative metagenomic, phylogenetic and physiological analyses of soil microbial communities across nitrogen gradients. ISME J. 6, 1007–1017 (2012).
pubmed: 22134642
doi: 10.1038/ismej.2011.159
Sorensen, J. W., Dunivin, T. K., Tobin, T. C. & Shade, A. Ecological selection for small microbial genomes along a temperate-to-thermal soil gradient. Nat. Microbiol. 4, 55–61 (2019).
pubmed: 30397342
doi: 10.1038/s41564-018-0276-6
Grime, J. P. & Pierce, S. The Evolutionary Strategies That Shape Ecosystems (John Wiley & Sons, 2012).
Liu, H. et al. Warmer and drier ecosystems select for smaller bacterial genomes in global soils. iMeta https://doi.org/10.1002/imt2.70 (2023).
Simonsen, A. K. Environmental stress leads to genome streamlining in a widely distributed species of soil bacteria. ISME J. 16, 423–434 (2021).
pubmed: 34408268
pmcid: 8776746
doi: 10.1038/s41396-021-01082-x
Chuckran, P. F. et al. Edaphic controls on genome size and GC content of bacteria in soil microbial communities. Soil Biol. Biochem. 178, 108935 (2023).
doi: 10.1016/j.soilbio.2022.108935
Guieysse, B. & Wuertz, S. Metabolically versatile large-genome prokaryotes. Curr. Opin. Biotechnol. 23, 467–473 (2012).
pubmed: 22226959
doi: 10.1016/j.copbio.2011.12.022
Konstantinidis, K. T. & Tiedje, J. M. Trends between gene content and genome size in prokaryotic species with larger genomes. Proc. Natl Acad. Sci. USA 101, 3160–3165 (2004).
pubmed: 14973198
pmcid: 365760
doi: 10.1073/pnas.0308653100
Paul, C. et al. Bacterial spores, from ecology to biotechnology. Adv. Appl. Microbiol. 106, 79–111 (2019).
pubmed: 30798805
doi: 10.1016/bs.aambs.2018.10.002
Singh, S., Datta, S., Narayanan, K. B. & Rajnish, K. N. Bacterial exo-polysaccharides in biofilms: role in antimicrobial resistance and treatments. J. Genet. Eng. Biotechnol. 19, 140 (2021).
pubmed: 34557983
pmcid: 8460681
doi: 10.1186/s43141-021-00242-y
Sinsabaugh, R. L. & Follstad Shah, J. J. Ecoenzymatic stoichiometry and ecological theory. Annu. Rev. Ecol. Evol. Syst. 43, 313–343 (2012).
doi: 10.1146/annurev-ecolsys-071112-124414
Buckeridge, K. M. et al. Environmental and microbial controls on microbial necromass recycling, an important precursor for soil carbon stabilization. Commun. Earth Environ. 1, 36 (2020).
doi: 10.1038/s43247-020-00031-4
Zheng, Q. et al. Growth explains microbial carbon use efficiency across soils differing in land use and geology. Soil Biol. Biochem. 128, 45–55 (2019).
pubmed: 31579288
doi: 10.1016/j.soilbio.2018.10.006
Gao, Y. & Wu, M. Free-living bacterial communities are mostly dominated by oligotrophs. Preprint at bioRxiv https://doi.org/10.1101/350348 (2018).
Li, J. et al. Predictive genomic traits for bacterial growth in culture versus actual growth in soil. ISME J. 13, 2162–2172 (2019).
pubmed: 31053828
pmcid: 6776108
doi: 10.1038/s41396-019-0422-z
Quince, C., Walker, A. W., Simpson, J. T., Loman, N. J. & Segata, N. Shotgun metagenomics, from sampling to analysis. Nat. Biotechnol. 35, 833–844 (2017).
pubmed: 28898207
doi: 10.1038/nbt.3935
Lobb, B., Tremblay, B. J.-M., Moreno-Hagelsieb, G. & Doxey, A. C. An assessment of genome annotation coverage across the bacterial tree of life. Microb. Genom. 6, e000341 (2020).
Coelho, L. P. et al. Towards the biogeography of prokaryotic genes. Nature 601, 252–256 (2022).
pubmed: 34912116
doi: 10.1038/s41586-021-04233-4
Martiny, J. B., Jones, S. E., Lennon, J. T. & Martiny, A. C. Microbiomes in light of traits: a phylogenetic perspective. Science 350, aac9323 (2015).
pubmed: 26542581
doi: 10.1126/science.aac9323
Allison, S. D. & Martiny, J. B. Resistance, resilience, and redundancy in microbial communities. Proc. Natl Acad. Sci. USA 105, 11512–11519 (2008).
pubmed: 18695234
pmcid: 2556421
doi: 10.1073/pnas.0801925105
Jones, D. L., Cooledge, E. C., Hoyle, F. C., Griffiths, R. I. & Murphy, D. V. pH and exchangeable aluminum are major regulators of microbial energy flow and carbon use efficiency in soil microbial communities. Soil Biol. Biochem. 138, 107584 (2019).
Fernández-Calviño, D. & Bååth, E. Growth response of the bacterial community to pH in soils differing in pH. FEMS Microbiol. Ecol. 73, 149–156 (2010).
pubmed: 20455934
Auger, C. et al. Metabolic reengineering invoked by microbial systems to decontaminate aluminum: implications for bioremediation technologies. Biotechnol. Adv. 31, 266–273 (2013).
pubmed: 23201464
doi: 10.1016/j.biotechadv.2012.11.008
Bruelheide, H. et al. Global trait–environment relationships of plant communities. Nat. Ecol. Evol. 2, 1906–1917 (2018).
pubmed: 30455437
doi: 10.1038/s41559-018-0699-8
Tedersoo, L. et al. Regional-scale in-depth analysis of soil fungal diversity reveals strong pH and plant species effects in Northern Europe. Front. Microbiol. 11, 1953 (2020).
pubmed: 33013735
pmcid: 7510051
doi: 10.3389/fmicb.2020.01953
Bagousse-Pinguet, Y. L. et al. Testing the environmental filtering concept in global drylands. J. Ecol. 105, 1058–1069 (2017).
pmcid: 5476209
doi: 10.1111/1365-2745.12735
Lauber, C. L., Hamady, M., Knight, R. & Fierer, N. Pyrosequencing-based assessment of soil pH as a predictor of soil bacterial community structure at the continental scale. Appl. Environ. Microbiol. 75, 5111–5120 (2009).
pubmed: 19502440
pmcid: 2725504
doi: 10.1128/AEM.00335-09
Meyer, F. et al. The metagenomics RAST server–a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9, 386 (2008).
pubmed: 18803844
pmcid: 2563014
doi: 10.1186/1471-2105-9-386
Chen, I.-M. A. et al. IMG/M v. 5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Res. 47, D666–D677 (2019).
pubmed: 30289528
doi: 10.1093/nar/gky901
Lozupone, C. & Knight, R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl. Environ. Microbiol. 71, 8228–8235 (2005).
pubmed: 16332807
pmcid: 1317376
doi: 10.1128/AEM.71.12.8228-8235.2005
Lombard, V., Golaconda Ramulu, H., Drula, E., Coutinho, P. M. & Henrissat, B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 42, D490–D495 (2014).
pubmed: 24270786
doi: 10.1093/nar/gkt1178
Nguyen, L. T. et al. Responses of the soil microbial community to nitrogen fertilizer regimes and historical exposure to extreme weather events: flooding or prolonged-drought. Soil Biol. Biochem. 118, 227–236 (2018).
doi: 10.1016/j.soilbio.2017.12.016
Berlemont, R. & Martiny, A. C. Genomic potential for polysaccharide deconstruction in bacteria. Appl. Environ. Microbiol. 81, 1513–1519 (2015).
pubmed: 25527556
pmcid: 4309713
doi: 10.1128/AEM.03718-14
López-Mondéjar, R. et al. Metagenomics and stable isotope probing reveal the complementary contribution of fungal and bacterial communities in the recycling of dead biomass in forest soil. Soil Biol. Biochem. 148, 107875 (2020).
doi: 10.1016/j.soilbio.2020.107875
Nayfach, S. & Pollard, K. S. Toward accurate and quantitative comparative metagenomics. Cell 166, 1103–1116 (2016).
pubmed: 27565341
pmcid: 5080976
doi: 10.1016/j.cell.2016.08.007
Chávez, J., Devos, D. P. & Merino, E. Complementary tendencies in the use of regulatory elements (transcription factors, sigma factors, and riboswitches) in bacteria and archaea. J. Bacteriol. 203, 413–20 (2020).
doi: 10.1128/JB.00413-20
Cania, B. et al. Site-specific conditions change the response of bacterial producers of soil structure-stabilizing agents such as exopolysaccharides and lipopolysaccharides to tillage intensity. Front. Microbiol. 11, 568 (2020).
pubmed: 32318044
pmcid: 7154075
doi: 10.3389/fmicb.2020.00568
Finn, D., Yu, J. & Penton, C. R. Soil quality shapes the composition of microbial community stress response and core cell metabolism functional genes. Appl. Soil Ecol. 148, 103483 (2020).
doi: 10.1016/j.apsoil.2019.103483
Sharma, M. P. et al. Deciphering the role of trehalose in tripartite symbiosis among rhizobia, arbuscular mycorrhizal fungi, and legumes for enhancing abiotic stress tolerance in crop plants. Front. Microbiol 11, 509919 (2020).
pubmed: 33042042
pmcid: 7527417
doi: 10.3389/fmicb.2020.509919
Yaakop, A. S. et al. Characterization of the mechanism of prolonged adaptation to osmotic stress of Jeotgalibacillus malaysiensis via genome and transcriptome sequencing analyses. Sci. Rep. 6, 33660 (2016).
pubmed: 27641516
pmcid: 5027565
doi: 10.1038/srep33660
Wargo, M. J. Homeostasis and catabolism of choline and glycine betaine: lessons from Pseudomonas aeruginosa. Appl. Environ. Microbiol. 79, 2112–2120 (2013).
pubmed: 23354714
pmcid: 3623244
doi: 10.1128/AEM.03565-12
Boch, J., Kempf, B., Schmid, R. & Bremer, E. Synthesis of the osmoprotectant glycine betaine in Bacillus subtilis: characterization of the gbsAB genes. J. Bacteriol. 178, 5121–5129 (1996).
pubmed: 8752328
pmcid: 178307
doi: 10.1128/jb.178.17.5121-5129.1996
Nayfach, S. & Pollard, K. S. Average genome size estimation improves comparative metagenomics and sheds light on the functional ecology of the human microbiome. Genome Biol. 16, 51 (2015).
pubmed: 25853934
pmcid: 4389708
doi: 10.1186/s13059-015-0611-7
Pereira-Flores, E., Glöckner, F. O. & Fernandez-Guerra, A. Fast and accurate average genome size and 16S rRNA gene average copy number computation in metagenomic data. BMC Bioinformatics 20, 453 (2019).
pubmed: 31488068
pmcid: 6727555
doi: 10.1186/s12859-019-3031-y
Chessel, D. & Hanafi, M. Analyses de la co-inertie de K nuages de points. Rev. Stat. Appl. 44, 35–60 (1996).
Piton, G. et al. Using proxies of microbial community-weighted means traits to explain the cascading effect of management intensity, soil and plant traits on ecosystem resilience in mountain grasslands. J. Ecol. 108, 876–893 (2020).
doi: 10.1111/1365-2745.13327
Meng, C., Kuster, B., Culhane, A. C. & Gholami, A. M. A multivariate approach to the integration of multi-omics datasets. BMC Bioinformatics 15, 162 (2014).
pubmed: 24884486
pmcid: 4053266
doi: 10.1186/1471-2105-15-162
Dray, S., Dufour, A. B. & Chessel, D. The ade4 package-II: two-table and K-table methods. R News 7, 47–52 (2007).
Dormann, C. F. et al. Collinearity: a review of methods to deal with it and a simulation study evaluating their performance. Ecography 36, 27–46 (2013).
doi: 10.1111/j.1600-0587.2012.07348.x
Genuer, R., Poggi, J.-M. & Tuleau-Malot, C. VSURF: an R package for variable selection using random forests. R J. 7, 19–33 (2015).
doi: 10.32614/RJ-2015-018
Kuhn, M. Building predictive models in R using the caret package. J. Stat. Softw. https://doi.org/10.18637/jss.v028.i05 (2008).
Poggio, L. et al. SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty. Soil 7, 217–240 (2021).
doi: 10.5194/soil-7-217-2021