1887

Abstract

The warming-induced thawing of permafrost promotes microbial activity, often resulting in enhanced greenhouse gas emissions. The ability of permafrost microorganisms to survive the sub-zero temperatures, their energetic strategies and their metabolic versatility in using soil organic materials determine their growth and functionality upon thawing. Hence, functional characterization of the permafrost microbiome, particularly in the underexplored mid-latitudinal alpine regions, is a crucial first step in predicting its responses to the changing climate, and the consequences for soil–climate feedbacks. In this study, for the first time, the functional potential and metabolic capabilities of a temperate mountain permafrost microbiome from central Europe has been analysed using shotgun metagenomics. Permafrost and active layers from the summit of Muot da Barba Peider (MBP) [Swiss Alps, 2979 m above sea level (a.s.l.)] revealed a strikingly high functional diversity in the permafrost (north-facing soils at a depth of 160 cm). Permafrost metagenomes were enriched in stress-response genes (e.g. cold-shock genes, chaperones), as well as in genes involved in cell defence and competition (e.g. antiviral proteins, antibiotics, motility, nutrient-uptake ABC transporters), compared with active-layer metagenomes. Permafrost also showed a higher potential for the synthesis of carbohydrate-active enzymes, and an overrepresentation of genes involved in fermentation, carbon fixation, denitrification and nitrogen reduction reactions. Collectively, these findings demonstrate the potential capabilities of permafrost microorganisms to thrive in cold and oligotrophic conditions, and highlight their metabolic versatility in carbon and nitrogen cycling. Our study provides a first insight into the high functional gene diversity of the central European mountain permafrost microbiome. Our findings extend our understanding of the microbial ecology of permafrost and represent a baseline for future investigations comparing the functional profiles of permafrost microbial communities at different latitudes.

Funding
This study was supported by the:
  • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (Award IZLSZ2_170941)
    • Principle Award Recipient: BeatFrey
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
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2021-04-13
2022-01-21
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References

  1. Gobiet A, Kotlarski S, Beniston M, Heinrich G, Rajczak J et al. 21st century climate change in the European Alps-a review. Sci Total Environ 2014; 493:1138–1151 [View Article][PubMed]
    [Google Scholar]
  2. Hock R, Rasul G, Adler C, Cáceres B, Gruber S. High Mountain Areas. In Pörtner H-O, Roberts DC, Masson-Delmotte V, Zhai P, Tignor M et al. (editors) IPCC Special Report on the Ocean and Cryosphere in a Changing Climate 2019 pp 131–202
    [Google Scholar]
  3. Biskaborn BK, Smith SL, Noetzli J, Matthes H, Vieira G et al. Permafrost is warming at a global scale. Nat Commun 2019; 10:264 [View Article][PubMed]
    [Google Scholar]
  4. Schuur EAG, Bockheim J, Canadell JG, Euskirchen E, Field CB. Vulnerability of permafrost carbon to climate change: implications for the global carbon cycle. Bioscience 2008; 58:701–714
    [Google Scholar]
  5. Genxu W, Yuanshou L, Yibo W, Qingbo W. Effects of permafrost thawing on vegetation and soil carbon pool losses on the Qinghai–Tibet Plateau, China. Geoderma 2008; 143:143–152
    [Google Scholar]
  6. Nikrad MP, Kerkhof LJ, Haggblom MM. The subzero microbiome: microbial activity in frozen and thawing soils. FEMS Microbiol Ecol 2016; 92:fiw081 [View Article][PubMed]
    [Google Scholar]
  7. Donhauser J, Frey B. Alpine soil microbial ecology in a changing world. FEMS Microbiol Ecol 2018; 94:fiy099
    [Google Scholar]
  8. Karhu K, Auffret MD, Dungait JAJ, Hopkins DW, Prosser JI et al. Temperature sensitivity of soil respiration rates enhanced by microbial community response. Nature 2014; 513:81-+ [View Article][PubMed]
    [Google Scholar]
  9. Mackelprang R, Saleska SR, Jacobsen CS, Jansson JK, Tas N. Permafrost Meta-omics and climate change. Annu Rev earth planet Sci 2016; 44:439-+
    [Google Scholar]
  10. Chen L, Liang J, Qin S, Liu L, Fang K et al. Determinants of carbon release from the active layer and permafrost deposits on the Tibetan Plateau. Nat Commun 2016; 7:13046 [View Article][PubMed]
    [Google Scholar]
  11. Margesin R. Permafrost Soils Berlin: Springer International Publishing; 2009
    [Google Scholar]
  12. Jansson JK, Taş N, Tas N. The microbial ecology of permafrost. Nat Rev Microbiol 2014; 12:414–425 [View Article][PubMed]
    [Google Scholar]
  13. Hu W, Zhang Q, Tian T, Cheng G, An L et al. The microbial diversity, distribution, and ecology of permafrost in China: a review. Extremophiles 2015; 19:693–705 [View Article][PubMed]
    [Google Scholar]
  14. Frey B, Rime T, Phillips M, Stierli B, Hajdas I et al. Microbial diversity in European alpine permafrost and active layers. FEMS Microbiol Ecol 2016; 92:fiw018 [View Article][PubMed]
    [Google Scholar]
  15. De Maayer P, Anderson D, Cary C, Cowan DA. Some like it cold: understanding the survival strategies of psychrophiles. EMBO Rep 2014; 15:508–517 [View Article][PubMed]
    [Google Scholar]
  16. Margesin R, Collins T. Microbial ecology of the cryosphere (glacial and permafrost habitats): current knowledge. Appl Microbiol Biotechnol 2019; 103:2537–2549 [View Article][PubMed]
    [Google Scholar]
  17. Bakermans C, Bergholz PW, Rodrigues DF, Vishnivetskaya TA, Ayala-del-Río HL. Genomic and expression analyses of cold-adapted microorganisms. In Miller RV, Whyte LG. (editors) Polar Microbiology: Life in a Deep Freeze United States: American Society of Microbiology; 2012 pp 126–155
    [Google Scholar]
  18. Jansson JK, Hofmockel KS. Soil microbiomes and climate change. Nat Rev Microbiol 2020; 18:35–46 [View Article][PubMed]
    [Google Scholar]
  19. Woodcroft BJ, Singleton CM, Boyd JA, Evans PN, Emerson JB et al. Genome-centric view of carbon processing in thawing permafrost. Nature 2018; 560:49–54 [View Article][PubMed]
    [Google Scholar]
  20. Hultman J, Waldrop MP, Mackelprang R, David MM, McFarland J et al. Multi-Omics of permafrost, active layer and thermokarst bog soil microbiomes. Nature 2015; 521:208–212 [View Article][PubMed]
    [Google Scholar]
  21. Xue Y, Jonassen I, Øvreås L, Taş N. Metagenome-assembled genome distribution and key functionality highlight importance of aerobic metabolism in Svalbard permafrost. FEMS Microbiol Ecol 2020; 96: [View Article][PubMed]
    [Google Scholar]
  22. Mueller O, Bang-Andreasen T, White RA, Elberling B, Taş N, Tas N et al. Disentangling the complexity of permafrost soil by using high resolution profiling of microbial community composition, key functions and respiration rates. Environ Microbiol 2018; 20:4328–4342 [View Article][PubMed]
    [Google Scholar]
  23. Taş N, Prestat E, Wang S, Wu Y, Ulrich C et al. Landscape topography structures the soil microbiome in Arctic polygonal tundra. Nat Commun 2018; 9:777 [View Article][PubMed]
    [Google Scholar]
  24. Leewis M-C, Berlemont R, Podgorski DC, Srinivas A, Zito P et al. Life at the frozen limit: microbial carbon metabolism across a late Pleistocene permafrost chronosequence. Front Microbiol 2020; 11:11 [View Article][PubMed]
    [Google Scholar]
  25. Van Goethem MW, Pierneef R, Bezuidt OKI, Van De Peer Y, Cowan DA et al. A reservoir of 'historical' antibiotic resistance genes in remote pristine Antarctic soils. Microbiome 2018; 6:40 [View Article][PubMed]
    [Google Scholar]
  26. Coolen MJ, Orsi WD. The transcriptional response of microbial communities in thawing Alaskan permafrost soils. Front Microbiol 2015; 6:197 [View Article][PubMed]
    [Google Scholar]
  27. Mackelprang R, Burkert A, Haw M, Mahendrarajah T, Conaway CH et al. Microbial survival strategies in ancient permafrost: insights from metagenomics. Isme J 2017; 11:2305–2318 [View Article][PubMed]
    [Google Scholar]
  28. Zhang SH, Yang GL, Hou SG, Zhang T, Li Z et al. Distribution of ARGs and MGEs among glacial soil, permafrost, and sediment using metagenomic analysis. Environ Pollut 2018; 234:339–346 [View Article][PubMed]
    [Google Scholar]
  29. Gruber S, Haeberli W. Permafrost in steep bedrock slopes and its temperature-related destabilization following climate change. J Geophys Res Earth Surf 2007; 112(F2):
    [Google Scholar]
  30. Yang Y, Gao Y, Wang S, Xu D, Yu H et al. The microbial gene diversity along an elevation gradient of the Tibetan grassland. Isme J 2014; 8:430–440 [View Article][PubMed]
    [Google Scholar]
  31. Guo G, Kong W, Liu J, Zhao J, Du H et al. Diversity and distribution of autotrophic microbial community along environmental gradients in grassland soils on the Tibetan Plateau. Appl Microbiol Biotechnol 2015; 99:8765–8776 [View Article][PubMed]
    [Google Scholar]
  32. Fontaine S, Barot S, Barre P, Bdioui N, Mary B et al. Stability of organic carbon in deep soil layers controlled by fresh carbon supply. Nature 2007; 450:277–280 [View Article][PubMed]
    [Google Scholar]
  33. Adamczyk M, Hagedorn F, Wipf S, Donhauser J, Vittoz P et al. The soil microbiome of GLORIA mountain summits in the Swiss Alps. Front Microbiol 2019; 10:1080 [View Article][PubMed]
    [Google Scholar]
  34. Liang Y, Jiang Y, Wang F, Wen C, Deng Y et al. Long-Term soil transplant simulating climate change with latitude significantly alters microbial temporal turnover. Isme J 2015; 9:2561–2572 [View Article][PubMed]
    [Google Scholar]
  35. Haeberli W, Gruber S. Global warming and mountain permafrost. In Margesin R. editor Permafrost Soils Berlin: Heidelberg: Springer Berlin Heidelberg; 2009 pp 205–218
    [Google Scholar]
  36. Zenklusen Mutter E, Blanchet J, Phillips M. Analysis of ground temperature trends in alpine permafrost using generalized least squares. J Geophys Res 2010; 115:F04009
    [Google Scholar]
  37. PERMOS Permafrost in Switzerland 2010/2011 to 2013/2014. Cryospheric Commission of the Swiss Academy of Sciences 2016; 85:
    [Google Scholar]
  38. Beniston M, Keller F, Goyette S. Snow pack in the Swiss Alps under changing climatic conditions: an empirical approach for climate impacts studies. Theor Appl Climatol 2003; 74:19–31
    [Google Scholar]
  39. Rodder T, Kneisel C. Influence of snow cover and grain size on the ground thermal regime in the discontinuous permafrost zone, Swiss Alps. Geomorphology 2012; 175:176–189
    [Google Scholar]
  40. Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for illumina sequence data. Bioinformatics 2014; 30:2114–2120 [View Article][PubMed]
    [Google Scholar]
  41. Li D, Liu C-M, Luo R, Sadakane K, Lam T-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 2015; 31:1674–1676 [View Article][PubMed]
    [Google Scholar]
  42. Zhu W, Lomsadze A, Borodovsky M. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res 2010; 38:e132 [View Article][PubMed]
    [Google Scholar]
  43. Huerta-Cepas J, Szklarczyk D, Forslund K, Cook H, Heller D et al. eggNOG 4.5: a hierarchical orthology framework with improved functional annotations for eukaryotic, prokaryotic and viral sequences. Nucleic Acids Res 2016; 44:D286–293 [View Article][PubMed]
    [Google Scholar]
  44. Huerta-Cepas J, Forslund K, Coelho LP, Szklarczyk D, Jensen LJ et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-mapper. Mol Biol Evol 2017; 34:2115–2122 [View Article][PubMed]
    [Google Scholar]
  45. Wilke A, Harrison T, Wilkening J, Field D, Glass EM et al. The M5nr: a novel non-redundant database containing protein sequences and annotations from multiple sources and associated tools. BMC Bioinformatics 2012; 13:141 [View Article][PubMed]
    [Google Scholar]
  46. Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V et al. The carbohydrate-active enzymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res 2009; 37:D233–238 [View Article][PubMed]
    [Google Scholar]
  47. Tu Q, Lin L, Cheng L, Deng Y, He Z. NCycDB: a curated integrative database for fast and accurate metagenomic profiling of nitrogen cycling genes. Bioinformatics 2019; 35:1040–1048 [View Article][PubMed]
    [Google Scholar]
  48. Vaser R, Pavlovic D, Sikic M. SWORD-a highly efficient protein database search. Bioinformatics 2016; 32:i680–i684 [View Article][PubMed]
    [Google Scholar]
  49. Anwar MZ, Lanzen A, Bang-Andreasen T, Jacobsen CS. To assemble or not to resemble-A validated comparative Metatranscriptomics workflow (CoMW). Gigascience 2019; 8: [View Article][PubMed]
    [Google Scholar]
  50. Li H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. bioRxiv 2013
    [Google Scholar]
  51. Liao Y, Smyth GK, Shi W. featureCounts: an efficient General purpose program for assigning sequence reads to genomic features. Bioinformatics 2014; 30:923–930 [View Article][PubMed]
    [Google Scholar]
  52. Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 2015; 3:e1165 [View Article][PubMed]
    [Google Scholar]
  53. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res 2015; 25:1043–1055 [View Article][PubMed]
    [Google Scholar]
  54. Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol 2017; 35:725–731 [View Article][PubMed]
    [Google Scholar]
  55. Pruesse E, Peplies J, Glockner FO. Sina: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 2012; 28:1823–1829 [View Article][PubMed]
    [Google Scholar]
  56. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T et al. The Silva ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 2013; 41:D590–D596 [View Article][PubMed]
    [Google Scholar]
  57. R Core Team R: A language and environment for statistical computing Vienna, Austria: R Foundation for Statistical Computing; 2017
  58. Wickham H. ggplot2: Elegant Graphics for Data Analysis New York: Springer-Verlag; 2016
    [Google Scholar]
  59. Abrams ZB, Johnson TS, Huang K, Payne PRO, Coombes K. A protocol to evaluate RNA sequencing normalization methods. BMC Bioinformatics 2019; 20:679 [View Article][PubMed]
    [Google Scholar]
  60. Oksanen J, Blanchet GF, Friendly M, Kindt R, Legendre P. vegan: community ecology package R package2.5-5 2019
    [Google Scholar]
  61. Clarke KR, Gorley RN. PRIMER v7: User Manual/Tutorial United Kingdom: PRIMER-E, Plymouth; 2015
    [Google Scholar]
  62. Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome Biol 2014; 15:550 [View Article][PubMed]
    [Google Scholar]
  63. Zaikova E, Goerlitz DS, Tighe SW, Wagner NY, Bai Y. Antarctic relic microbial mat community revealed by metagenomics and metatranscriptomics. Front Ecol Evol 2019; 7:
    [Google Scholar]
  64. Koo H, Hakim JA, Morrow CD, Crowley MR, Andersen DT et al. Metagenomic analysis of microbial community compositions and cold-responsive stress genes in selected Antarctic lacustrine and soil ecosystems. Life 2018; 8:E29 [View Article][PubMed]
    [Google Scholar]
  65. Keto-Timonen R, Hietala N, Palonen E, Hakakorpi A, Lindstrm M et al. Cold shock proteins: A minireview with special emphasis on csp-family of enteropathogenic Yersinia . Front Microbiol 2016; 7:1151 [View Article][PubMed]
    [Google Scholar]
  66. Bowman JP. Genomics of psychrophilic Bacteria and Archaea. In Margesin R. editor Psychrophiles: From biodiversity to biotechnology Cham: Springer International Publishing; 2017 pp 345–387
    [Google Scholar]
  67. Mykytczuk NCS, Foote SJ, Omelon CR, Southam G, Greer CW et al. Bacterial growth at -15 °C; molecular insights from the permafrost bacterium Planococcus halocryophilus OR1. Isme J 2013; 7:1211–1226 [View Article][PubMed]
    [Google Scholar]
  68. Ayala-del-Río HL, Chain PS, Grzymski JJ, Ponder MA, Ivanova N et al. The genome sequence of Psychrobacter arcticus 273-4, a psychroactive Siberian permafrost bacterium, reveals mechanisms for adaptation to low-temperature growth. Appl Environ Microbiol 2010; 76:2304–2312 [View Article][PubMed]
    [Google Scholar]
  69. Tuorto SJ, Darias P, McGuinness LR, Panikov N, Zhang TJ et al. Bacterial genome replication at subzero temperatures in permafrost. Isme J 2014; 8:139–149 [View Article][PubMed]
    [Google Scholar]
  70. Burkert A, Douglas TA, Waldrop MP, Mackelprang R. Changes in the active, dead, and dormant microbial community structure across a Pleistocene permafrost chronosequence. Appl Environ Microbiol 2019; 85: [View Article][PubMed]
    [Google Scholar]
  71. Wunderlin T, Junier T, Roussel-Delif L, Jeanneret N, Junier P. Stage 0 sporulation gene A as a molecular marker to study diversity of endospore-forming Firmicutes. Environ Microbiol Rep 2013; 5:911–924 [View Article][PubMed]
    [Google Scholar]
  72. Mackelprang R, Waldrop MP, DeAngelis KM, David MM, Chavarria KL et al. Metagenomic analysis of a permafrost microbial community reveals a rapid response to thaw. Nature 2011; 480:368–U120 [View Article][PubMed]
    [Google Scholar]
  73. Ernakovich JG, Wallenstein MD. Permafrost microbial community traits and functional diversity indicate low activity at in situ thaw temperatures. Soil Biol Biochem 2015; 87:78–89
    [Google Scholar]
  74. Morgalev YN, Lushchaeva IV MTG, Kolesnichenko LG, Loiko SV et al. Bacteria primarily metabolize at the active layer/permafrost border in the peat core from a permafrost region in Western Siberia. Polar Biol 2017; 40:1645–1659
    [Google Scholar]
  75. Willerslev E, Hansen AJ, Ronn R, Brand TB, Barnes I et al. Long-Term persistence of bacterial DNA. Curr Biol 2004; 14:R9–R10 [View Article][PubMed]
    [Google Scholar]
  76. Bellemain E, Davey ML, Kauserud H, Epp LS, Boessenkool S et al. Fungal palaeodiversity revealed using high-throughput metabarcoding of ancient DNA from Arctic permafrost. Environ Microbiol 2013; 15:1176–1189 [View Article][PubMed]
    [Google Scholar]
  77. Tveit A, Schwacke R, Svenning MM, Urich T. Organic carbon transformations in high-Arctic peat soils: key functions and microorganisms. Isme J 2013; 7:299–311 [View Article][PubMed]
    [Google Scholar]
  78. Ward LM, Cardona T, Holland-Moritz H. Evolutionary implications of anoxygenic phototrophy in the bacterial phylum Candidatus Eremiobacterota (WPS-2). Front Microbiol 2019; 10:
    [Google Scholar]
  79. Lambrechts S, Willems A, Tahon G. Uncovering the uncultivated majority in Antarctic soils: toward a synergistic approach. Front Microbiol 2019; 10:242 [View Article][PubMed]
    [Google Scholar]
  80. Ji M, Greening C, Vanwonterghem I, Carere CR, Bay SK et al. Atmospheric trace gases support primary production in Antarctic desert surface soil. Nature 2017; 552:400-+ [View Article][PubMed]
    [Google Scholar]
  81. Chauhan A, Layton AC, Vishnivetskaya TA, Williams D, Pfiffner SM et al. Metagenomes from thawing low-soil-organic-carbon mineral cryosols and permafrost of the Canadian high Arctic. Genome Announc 2014; 2:e01217-14 [View Article][PubMed]
    [Google Scholar]
  82. Pontes A, Ruethi J, Frey B, Aires A, Thomas A et al. Cryolevonia gen. nov. and Cryolevonia schafbergensis sp. nov., a cryophilic yeast from ancient permafrost and melted sea ice. Int J Syst Evol Microbiol 2020; 70:2334–2338 [View Article][PubMed]
    [Google Scholar]
  83. Greening C, Biswas A, Carere CR, Jackson CJ, Taylor MC et al. Genomic and metagenomic surveys of hydrogenase distribution indicate H2 is a widely utilised energy source for microbial growth and survival. Isme J 2016; 10:761–777 [View Article][PubMed]
    [Google Scholar]
  84. Yang ZF, Zhang Y, Lv Y, Yan WK, Xiao X et al. H2 metabolism revealed by metagenomic analysis of subglacial sediment from East Antarctica. J Microbiol 2019; 57:1095–1104 [View Article][PubMed]
    [Google Scholar]
  85. Ortiz M, Leung PM, Shelley G, Van Goethem MW, Bay SK. A genome compendium reveals diverse metabolic adaptations of Antarctic soil microorganisms. bioRxiv 2020
    [Google Scholar]
  86. Steinbauer MJ, Grytnes JA, Jurasinski G, Kulonen A, Lenoir J et al. Accelerated increase in plant species richness on mountain summits is linked to warming. Nature 2018; 556:231-+ [View Article][PubMed]
    [Google Scholar]
  87. Luláková P, Perez-Mon C, antrůčková H, Ruethi J, Frey B. High-alpine permafrost and active-layer soil microbiomes differ in their response to elevated temperatures. Front Microbiol 10.3389/fmicb.2019.00668 2019; 10:
    [Google Scholar]
  88. Adamczyk M, Ruthi J, Frey B. Root exudates increase soil respiration and alter microbial community structure in alpine permafrost and active layer soils. Environ Microbiol 2021 [View Article][PubMed]
    [Google Scholar]
  89. Donhauser J, Niklaus PA, Rousk J, Larose C, Frey B. Temperatures beyond the community optimum promote the dominance of heat-adapted, fast growing and stress resistant bacteria in alpine soils. Soil Biol Biochem 2020; 107873:
    [Google Scholar]
  90. Donhauser J, Qi W, Bergk-Pinto B, Frey B. High temperatures enhance the microbial genetic potential to recycle C and N from necromass in high-mountain soils. Glob Chang Biol 2020
    [Google Scholar]
  91. Adamczyk M, Perez-Mon C, Gunz S, Frey B. Strong shifts in microbial community structure are associated with increased litter input rather than temperature in high Arctic soils. Soil Biol Biochem 2020; 151:108054
    [Google Scholar]
  92. Xue K, Yuan MM, Shi ZJ, Qin YJ, Deng Y. Tundra soil carbon is vulnerable to rapid microbial decomposition under climate warming. Nat Clim Change 2016; 6:595-+
    [Google Scholar]
  93. Johnston ER, Hatt JK, He Z, Wu L, Guo X et al. Responses of tundra soil microbial communities to half a decade of experimental warming at two critical depths. Proc Natl Acad Sci U S A 2019; 116:15096–15105 [View Article][PubMed]
    [Google Scholar]
  94. Feng J, Wang C, Lei J, Yang Y, Yan Q et al. Warming-induced permafrost thaw exacerbates tundra soil carbon decomposition mediated by microbial community. Microbiome 2020; 8:3 [View Article][PubMed]
    [Google Scholar]
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