Soil Properties Interacting With Microbial Metagenome in Decreasing CH4 Emission From Seasonally Flooded Marshland Following Different Stages of Afforestation
Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic-ecollection
Typ dokumentu časopisecké články
PubMed
35283824
PubMed Central
PMC8905362
DOI
10.3389/fmicb.2022.830019
Knihovny.cz E-zdroje
- Klíčová slova
- CH4 flux, methanogens, methanotrophs, soil metagenome, soil particle size composition,
- Publikační typ
- časopisecké články MeSH
Wetlands are the largest natural source of terrestrial CH4 emissions. Afforestation can enhance soil CH4 oxidation and decrease methanogenesis, yet the driving mechanisms leading to these effects remain unclear. We analyzed the structures of communities of methanogenic and methanotrophic microbes, quantification of mcrA and pmoA genes, the soil microbial metagenome, soil properties and CH4 fluxes in afforested and non-afforested areas in the marshland of the Yangtze River. Compared to the non-afforested land use types, net CH4 emission decreased from bare land, natural vegetation and 5-year forest plantation and transitioned to net CH4 sinks in the 10- and 20-year forest plantations. Both abundances of mcrA and pmoA genes decreased significantly with increasing plantation age. By combining random forest analysis and structural equation modeling, our results provide evidence for an important role of the abundance of functional genes related to methane production in explaining the net CH4 flux in this ecosystem. The structures of methanogenic and methanotrophic microbial communities were of lower importance as explanatory factors than functional genes in terms of in situ CH4 flux. We also found a substantial interaction between functional genes and soil properties in the control of CH4 flux, particularly soil particle size. Our study provides empirical evidence that microbial community function has more explanatory power than taxonomic microbial community structure with respect to in situ CH4 fluxes. This suggests that focusing on gene abundances obtained, e.g., through metagenomics or quantitative/digital PCR could be more effective than community profiling in predicting CH4 fluxes, and such data should be considered for ecosystem modeling.
College of Agriculture Nanjing Agricultural University Nanjing China
Department of Biology Brigham Young University Provo UT United States
Hubei Academy of Forestry Wuhan China
Hunan Academy of Forestry Changsha China
Research Institute of Forestry Chinese Academy of Forestry Beijing China
Zobrazit více v PubMed
Angel R., Claus P., Conrad R. (2012). Methanogenic archaea are globally ubiquitous in aerated soils and become active under wet anoxic conditions. ISME J. 6 847–862. 10.1038/ismej.2011.141 PubMed DOI PMC
Arbuckle J. L. (2011). IBM§SPSS§AmosTM 20 User’s Guide. New York, NY: IBM Corporation.
Benanti G., Saunders M., Tobin B., Osborne B. (2014). Contrasting impacts of afforestation on nitrous oxide and methane emissions. Agric. For. Meteorol. 198–199 82–93.
Bender M., Conrad R. (1995). Effect of CH4 concentrations and soil conditions on the induction of CH4 oxidation activity. Soil Biol. Biochem. 27 1517–1527.
Bhattacharyya P., Roy K. S., Nayak A. K., Shahid M., Lal B., Gautam P., et al. (2017). Metagenomic assessment of methane production-oxidation and nitrogen metabolism of long term manured systems in lowland rice paddy. Sci. Total Environ. 586 1245–1253. 10.1016/j.scitotenv.2017.02.120 PubMed DOI
Bodelier P. L. E. (2011). Interactions between nitrogenous fertilizers and methane cycling in wetland and upland soils. Curr. Opin. Env. Sust. 3 379–388. 10.1890/09-2185.1 PubMed DOI
Bokulich N. A., Subramanian S., Faith J. F., Gevers D., Gordon J. I., Knight R., et al. (2013). Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat. Methods 10 57–59. 10.1038/nmeth.2276 PubMed DOI PMC
Bolger A. M., Lohse M., Usadel B. (2014). Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30 2114–2120. 10.1093/bioinformatics/btu170 PubMed DOI PMC
Breiman L. (2001). Random forests. Mach. Learn. 45 5–32.
Caporaso J. G., Kuczynski J., Stombaugh J., Bittinger K., Bushman F. D., Costello E. K., et al. (2010). QIIME allows analysis of high- throughput community sequencing data. Nat. Methods 7 335–336. 10.1038/nmeth.f.303 PubMed DOI PMC
Cline L. C., Zak D. R. (2015). Soil microbial communities are shaped by plant-driven changes in resource availability during secondary succession. Ecology 96 3374–3385. 10.1890/15-0184.1 PubMed DOI
Conrad R. (1996). Soil microorganisms as controllers of atmospheric trace gases (H2, CO, CH4, OCS, N2O, and NO). Microbiol. Mol. Biol. R. 60 609–640. 10.1128/mr.60.4.609-640.1996 PubMed DOI PMC
Conrad R. (2002). Control of microbial methane production in wetland rice fields. Nutr. Cycl. Agroecosys. 64 59–69.
Dalal R. C., Allen D. E. (2008). Greenhouse gas fluxes from natural ecosystems. Aust. J. Bot. 56 369–407.
de Mendiburu F. (2012). Agricolae: Statistical Procedures for Agricultural Research. R Package Version 1.1-2. Available online at: http://CRAN.R-project.org/package=agricolae (accessed September 1, 2012).
DeSantis T. Z., Hugenholtz P., Larsen N., Rojas M., Brodie E. L., Keller K., et al. (2006). Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microb. 72 5069–5072. 10.1128/AEM.03006-05 PubMed DOI PMC
Dörr N., Glaser B., Kolb S. (2010). Methanotrophic communities in Brazilian Ferralsols from naturally forested, afforested, and agricultural sites. Appl. Environ. Microb. 76 1307–1310. 10.1128/AEM.02282-09 PubMed DOI PMC
Edgar R. C. (2013). UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10 996–998. 10.1038/nmeth.2604 PubMed DOI
Edgar R. C., Haas B. J., Clemente J. C., Quince C., Knight R. (2011). UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27 2194–2200. 10.1093/bioinformatics/btr381 PubMed DOI PMC
Emerson J. B., Varner R. K., Wik M., Parks D., Neumann R., Johnson J. E., et al. (2021). Diverse sediment microbiota shape methane emission temperature sensitivity in Arctic lakes. Nat. Commun. 12:5815. 10.1038/s41467-021-25983-9 PubMed DOI PMC
Ettwig K. F., Zhu B. L., Speth D., Keltjens J. T., Jetten M. S. M., Kartal B. (2016). Archaea catalyze iron-dependent anaerobic oxidation of methane. P. Natl. Acad. Sci. U.S.A. 113 12792–12796. 10.1073/pnas.1609534113 PubMed DOI PMC
Fierer N., Ladau J., Clemente J. C., Leff J. W., Owens S. M., Pollard K. S., et al. (2013). Reconstructing the microbial diversity and function of pre-agricultural tallgrass prairie soils in the United States. Science 342 621–624. 10.1126/science.1243768 PubMed DOI
Fortmann-Roe S. (2015). Consistent and clear reporting of results from diverse modeling techniques: the A3 method. J Stat. Softw. 66 1–23.
Freitag T. E., Prosser J. I. (2009). Correlation of methane production and functional gene transcriptional activity in a peat soil. Appl. Environ. Microb. 75 6679–6687. 10.1128/AEM.01021-09 PubMed DOI PMC
Friedrich M. W. (2005). Methyl-coenzyme M reductase genes: unique functional markers for methanogenic and anaerobic methane-oxidizing archaea. Method Enzymol. 397 428–442. 10.1016/S0076-6879(05)97026-2 PubMed DOI
Gao S. H., Zhang X. D., Tang Y. X., Zhang R., Tang J., Zhang L., et al. (2013). Short-term effects of clear-cutting of Populus deltoides plantation on methane flux on the beach land of Yangtze River. Sci. Silv. Sini. 49 7–13.
Grotenhuis J. T. C., Plugge C. M., Stams A. J. M., Zehnder A. J. B. (1992). Hydrophobicities and electrophoretic mobilities of anaerobic bacterial isolates from methanogenic granular sludge. Appl. Environ. Microb. 58 1054–1056. 10.1128/aem.58.3.1054-1056.1992 PubMed DOI PMC
Hu L., Bentler P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equat. Model. 6 1–55. 10.1080/10705519909540118 DOI
Hyatt D., Locascio P. F., Hauser L. J., Uberbacher E. C. (2012). Gene and translation initiation site prediction in metagenomic sequences. Bioinformatics 28 2223–2230. 10.1093/bioinformatics/bts429 PubMed DOI
ISO 11465 (1993). Soil Quality–Determination of Dry Matter and Water Content on a Mass Basis–Gravimetric Method. Geneva: International Organization for Standardization.
Jiang T. T., Pan J. F., Pu X. M., Wang B., Pan J. J. (2015). Current status of coastal wetlands in China: degradation, restoration, and future management. Estuar. Coast. Shelf S. 164 265–275.
Kanehisa M., Goto S. (2000). KEGG: KYOTO encyclopedia of genes and genomes. Nucleic Acids Res. 28 27–30. PubMed PMC
Kolb S. (2009). The quest for atmospheric methane oxidizers in forest soils. Environ. Microbiol. Rep. 1 336–346. 10.1111/j.1758-2229.2009.00047.x PubMed DOI
Kolb S., Knief C., Dunfield P. F., Conrad R. (2005). Abundance and activity of uncultured methanotrophic bacteria involved in the consumption of atmospheric methane in two forest soils. Environ. Microbiol. 7 1150–1161. 10.1111/j.1462-2920.2005.00791.x PubMed DOI
Kumaresan D., Cross A. T., Moreira-Grez B., Kariman K., Nevill P., Stevens J., et al. (2017). Microbial functional capacity is preserved within engineered soil formulations used in mine site restoration. Sci. Rep. 7:564. 10.1038/s41598-017-00650-6 PubMed DOI PMC
Lang R., Goldberg S. D., Blagodatsky S., Piepho H.-P., Hoyt A. M., Harrison R. D., et al. (2020). Mechanism of methane uptake in profiles of tropical soils converted from forest to rubber plantations. Soil Biol. Biochem. 145:107796.
Lee H. J., Kim S. Y., Kim P. J., Madsen E. L., Jeon C. O. (2014). Methane emission and dynamics of methanotrophic and methanogenic communities in a flooded rice field ecosystem. FEMS Microbiol. Ecol. 88 195–212. 10.1111/1574-6941.12282 PubMed DOI
Li D. H., Liu C. M., Luo R. B., Sadakane K., Lam T. W. (2015). MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31 1674–1676. 10.1093/bioinformatics/btv033 PubMed DOI
Liaw A., Wiener M. (2002). Classification and regression by random forest. R News 2 18–22.
Lu R. K. (1999). The Analysis Method of Soil Agricultural Chemistry. Beijing: China Agricultural Science and Technology Press.
Luton P. E., Wayne J. M., Sharp R. J., Riley P. W. (2002). The mcrA gene as an alternative to 16S rRNA in the phylogenetic analysis of methanogen populations in landfill. Microbiology 148 3521–3530. 10.1099/00221287-148-11-3521 PubMed DOI
Ma X., Zhang Q., Zheng M., Gao Y., Yuan T., Hale L., et al. (2019). Microbial functional traits are sensitive indicators of mild disturbance by lamb grazing. ISME J. 13 1370–1373. 10.1038/s41396-019-0354-7 PubMed DOI PMC
Menyailo O. V., Abraham W., Conrad R. (2010). Tree species affect atmospheric CH4 oxidation without altering community composition of soil methanotrophs. Soil Biol. Biochem. 42 101–107.
Meyer F., Paarmann D., D’Souza M., Olson R., Glass E. M., Kubal M., et al. (2008). The metagenomics RAST server-a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9:386. 10.1186/1471-2105-9-386 PubMed DOI PMC
Mikan M. P., Harvey H. R., Timmins-Schiffman E., Riffle M., Nunn B. L. (2020). Metaproteomics reveal that rapid perturbations in organic matter prioritize functional restructuring over taxonomy in western arctic ocean microbiomes. ISME J. 14 1–14. 10.1038/s41396-019-0503-z PubMed DOI PMC
Mitra S., Wassmann R., Jain M. C., Pathak H. (2002). Properties of rice soils affecting methane production potentials: 1. temporal patterns and diagnostic procedures. Nutr. Cycl. Agroecosys. 64 169–182.
Nazaries L., Murrell J. C., Millard P., Baggs E. M., Singh B. K. (2013a). Methane, microbes and models: fundamental understanding of the soil methane cycle for future predictions. Environ. Microbiol. 15 2395–2417. 10.1111/1462-2920.12149 PubMed DOI
Nazaries L., Pan Y., Bodrossy L., Baggs E. M., Millard P., Murrell J. C., et al. (2013b). Evidence of Microbial regulation of biogeochemical cycles: evidence from a study on methane flux and land-use change. Appl. Environ. Microb. 79 4031–4040. 10.1128/AEM.00095-13 PubMed DOI PMC
Nazaries L., Tate K. R., Ross D. J., Singh J., Dando J., Saggar S., et al. (2011). Response of methanotrophic communities to afforestation and reforestation in New Zealand. ISME J. 5 1832–1836. 10.1038/ismej.2011.62 PubMed DOI PMC
Nelson D. W., Sommers L. E. (1982). “Dry combustion method using medium temperature resistance furnace,” in Methods of Soil Analysis. Part 2: Chemical and Microbial Properties, 2nd Edn, ed. Page A. L. (Madison, WI: American Society of Agronomy; ), 539–579.
Oksanen J., Blanchet F. G., Kindt R., Legendre P., Minchin P. R., O’hara R. B., et al. (2013). Vegan: Community Ecology Package. R Package Version 2.0-7. Available online at: http://CRAN.R-project.org/package=vegan (accessed July 1, 2013).
Paul E. A. (2007). Soil Microbiology, Ecology and Biochemistry, 3rd Edn. London: Academic Press, 532.
Redmond M. C., Valentine D. L., Sessions A. L. (2010). Identification of novel methane-, ethane-, and propane-oxidizing bacteria at marine hydrocarbon seeps by stable isotope probing. Appl. Environ. Microb. 76:6412. 10.1128/AEM.00271-10 PubMed DOI PMC
Rocca J. D., Hall E. K., Lennon J. T., Evans S. E., Waldrop M. P., Cotner J. B., et al. (2015). Relationships between proteinencoding gene abundance and corresponding process are commonly assumed yet rarely observed. ISME J. 9 1693–1699. 10.1038/ismej.2014.252 PubMed DOI PMC
Seo J., Jang I., Gebauer G., Kang H. (2013). Abundance of methanogens, methanotrophic bacteria, and denitrifiers in rice paddy soils. Wetlands 34 213–223. 10.1007/s13157-013-0477-y DOI
Singh B. K., Tate K. R., Kolipaka G., Hedley C. B., Macdonald C. A., Millard P., et al. (2007). Effect of afforestation and reforestation of pastures on the activity and population dynamics of methanotrophic bacteria. Appl. Environ. Microb. 73 5153–5161. 10.1128/AEM.00620-07 PubMed DOI PMC
Singh B. K., Tate K. R., Ross D. J., Singh J., Dando J., Thomas N., et al. (2009). Soil methane oxidation and methanotroph responses to afforestation of pastures with pinus radiata stands. Soil Biol. Biochem. 41 2196–2205. 10.1016/j.soilbio.2009.08.004 DOI
St Pierre K. A., Danielsen B. K., Hermesdorf L., D Imperio L., Iversen L. L., Elberling B. (2019). Drivers of net methane uptake across Greenlandic dry heath tundra landscapes. Soil Biol. Biochem. 138:107605. 10.1016/j.soilbio.2019.107605 DOI
Subhajit D., Dipnarayan G., Sabyasachi C., Abhishek M., Tarun K. D. (2018). Methane flux dynamics in relation to methanogenic and methanotrophic population in the soil of Indian sundarban mangrove. Mar. Ecol. 39:e12493. 10.1111/maec.12493 DOI
Sul W. J., Cole J. R., Jesus E. C., Wang Q., Farris R., Fish J. A., et al. (2011). Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering. Proc. Natl. Acad. Sci. U.S.A. 108 14637–14642. 10.1073/pnas.1111435108 PubMed DOI PMC
Sun S., Badgley B. D. (2019). Changes in microbial functional genes within the soil metagenome during forest ecosystem restoration. Soil Biol. Biochem. 135 163–172. 10.1093/femsec/fiaa149 PubMed DOI
Tan Z., Zhuang Q., Henze D. K., Frankenberg C., Dlugokencky E., Sweeney C., et al. (2015). Mapping pan-Arctic methane emissions at high spatial resolution using an adjoint atmospheric transport and inversion method and process-based wetland and lake biogeochemical models. Atmos. Chem. Phys. 15 32469–32518.
Tate K. R. (2015). Soil methane oxidation and land-use change–from process to mitigation. Soil Biol. Biochem. 80 260–272.
Täumer J., Kolb S., Boeddinghaus R. S., Wang H., Schöning I., Schrumpf M., et al. (2021). Divergent drivers of the microbial methane sink in temperate forest and grassland soils. Glob. Chang. Biol. 27 929–940. 10.1111/gcb.15430 PubMed DOI
van Loosdrecht M. C. M., Lyklema J., Norde W., Schraa G., Zehnder A. J. B. (1987b). Electrophoretic mobility and hydrophobicity as a measure to predict the initial steps of bacterial adhesion. Appl. Environ. Microbiol. 53 1898–1901. 10.1128/aem.53.8.1898-1901.1987 PubMed DOI PMC
van Loosdrecht M. C. M., Lyklema J., Norde W., Schraa G., Zehnder A. J. B. (1987a). The role of cell wall hydrophobicity in adhesion. Appl. Environ. Microb. 53 1893–1897. 10.1128/aem.53.8.1893-1897.1987 PubMed DOI PMC
Wagner D., Pfeiffer E. M., Bock E. (1999). Methane production in aerated marshland and model soils: effects of microflora and soil texture. Soil Biol. Biochem. 31 999–1006.
Wen X., Yang S., Horn F., Winkel M., Wagner D., Liebner S. (2017). Global biogeographic analysis of methanogenic archaea identifies community-shaping environmental factors of natural environments. Front. Microbiol. 8:1339. 10.3389/fmicb.2017.01339 PubMed DOI PMC
Whalen S. C., Reeburgh W. S. (1990). A methane flux transect along the trans-Alaska pipeline haul road. Tellus B. Chem. Phys. Meteor. 42 237–249.
Wilpiszeski R. L., Aufrecht J. A., Retterer S. T., Sullivan M. B., Graham D. E., Pierce E. M., et al. (2019). Soil aggregate microbial communities: towards understanding microbiome interactions at biologically relevant scales. Appl. Environ. Microb. 85 e00324–19. 10.1128/AEM.00324-19 PubMed DOI PMC
Wood S. A., Bradford M. A., Gilbert J. A., McGuire K. L., Palm C. A., Tully K. L., et al. (2015). Agricultural intensification and the functional capacity of soil microbes on smallholder African farms. J. Appl. Ecol. 52 744–752.
Wu J., Li Q., Chen J., Lei Y., Zhang Q., Yang F., et al. (2018). Afforestation enhanced soil CH4 uptake rate in subtropical China: evidence from carbon stable isotope experiments. Soil Biol. Biochem. 118 199–204.
Xie C., Mao X., Huang J., Ding Y., Wu J., Dong S., et al. (2011). KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases. Nucleic Acids Res. 39 W316–W322. 10.1093/nar/gkr483 PubMed DOI PMC
Yu X., Yang X., Wu Y., Peng Y., Yang T., Xiao F., et al. (2020). Sonneratia apetala introduction alters methane cycling microbial communities and increases methane emissions in mangrove ecosystems. Soil Biol. Biochem. 144:107775.
Yuan M., Zhu J., Wang C., Wu M., Sun F., Han X., et al. (2016). Latitudinal distribution of microbial communities in anaerobic biological stabilization ponds: effect of the mean annual temperature. Microb. Biotechnol. 9 834–845. 10.1111/1751-7915.12407 PubMed DOI PMC
Zhang L. Y., Adams J. M., Dumont M. G., Li Y. T., Shi Y., He D., et al. (2019). Distinct methanotrophic communities exist in habitats with different soil water contents. Soil Biol. Biochem. 132 143–152.
Zhou J., Theroux S. M., Bueno de Mesquita C. P., Hartman W. H., Tian Y., Tringe S. G. (2022). Microbial drivers of methane emissions from unrestored industrial salt ponds. ISME J. 16 284–295. 10.1038/s41396-021-01067-w PubMed DOI PMC
Zhou J. X., Sun Q. X., Yang Y. F. (2010). Research onsustainable use of the middle and lower beach land of the Yangtze River. Resourc. Environ. Yangtze Basin 19 878–883.
Zu Q., Zhong L., Deng Y., Shi Y., Wang B., Jia Z., et al. (2016). Geographical distribution of methanogenic archaea in nine representative paddy soils in China. Front. Microbiol. 7:1447. 10.3389/fmicb.2016.01447 PubMed DOI PMC