Pangenomes reveal genomic signatures of microbial adaptation to chronic soil warming

Evolutionary responses to anthropogenic climate change are irreversible and largely uncaptured by climate models. Below-ground carbon transformations represent an important natural mitigation solution, but novel adaptive traits may alter microbial climate feedback mechanisms. To better define microbial evolutionary responses to warming, we study microorganisms from an ongoing in situ soil warming experiment at the Harvard Forest Long-term Ecological Research (LTER) site where, for over three decades, soils are continuously heated 5 ºC above ambient temperatures. We hypothesize that across generations of chronic warming, genomic signatures within diverse bacterial lineages reflect adaptations related to growth and carbon utilization. From our culture collection of soil bacteria isolated from experimental heated and control plots, we sequenced genomes representing taxa dominant in soil communities and sensitive to warming, including independent lineages of Alphaproteobacteria, Actinobacteria, and Betaproteobacteria. We investigated differences in genomic attributes and patterns of functional gene content to identify genetic signatures of adaptation. Comparative pangenomics revealed differently abundant gene clusters with functional annotations related to carbon and nitrogen metabolism. We also observe differences in genome-wide codon usage bias between heated and control genomes, suggesting potential adaptive traits related to growth or growth efficiency. Together, these data illustrate the emergence of diverse lineage-specific adaptive traits as well as common ecological-evolutionary microbial responses to climate change.

[1]  S. Allison,et al.  Burning Questions: How do soil microbes shape ecosystem biogeochemistry in the context of global change? , 2022, Environmental microbiology.

[2]  Boyang Hu,et al.  dbCAN-seq update: CAZyme gene clusters and substrates in microbiomes , 2022, Nucleic Acids Res..

[3]  S. Frey,et al.  Substrate availability and not thermal-acclimation controls microbial temperature sensitivity response to long term warming , 2022, bioRxiv.

[4]  J. Tiedje,et al.  Reduction of microbial diversity in grassland soil is driven by long-term climate warming , 2022, Nature Microbiology.

[5]  A. Casadevall,et al.  Microbes and Climate Change: a Research Prospectus for the Future , 2022, mBio.

[6]  J. Handelsman A World Without Soil: The Past, Present, and Precarious Future of the Earth Beneath Our Feet , 2021 .

[7]  S. Frey,et al.  Physical protection regulates microbial thermal responses to chronic soil warming , 2021, Soil Biology and Biochemistry.

[8]  J. Blanchard,et al.  Fungal community response to long‐term soil warming with potential implications for soil carbon dynamics , 2021, Ecosphere.

[9]  J. Martiny,et al.  Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient , 2021, Proceedings of the National Academy of Sciences.

[10]  T. Tuller,et al.  Codon-based indices for modeling gene expression and transcript evolution , 2021, Computational and structural biotechnology journal.

[11]  Daniel J. Blankenberg,et al.  Community-led, integrated, reproducible multi-omics with anvi’o , 2020, Nature Microbiology.

[12]  R. Maier,et al.  Life-history strategies of soil microbial communities in an arid ecosystem , 2020, The ISME Journal.

[13]  Tom O. Delmont,et al.  Functional and genetic markers of niche partitioning among enigmatic members of the human oral microbiome , 2020, Genome Biology.

[14]  K. Nealson,et al.  A Genus Definition for Bacteria and Archaea Based on a Standard Genome Relatedness Index , 2020, mBio.

[15]  J. Jansson,et al.  Soil microbiomes and climate change , 2019, Nature Reviews Microbiology.

[16]  J. Huisman,et al.  Scientists’ warning to humanity: microorganisms and climate change , 2019, Nature Reviews Microbiology.

[17]  Hiroyuki Ogata,et al.  KofamKOALA: KEGG Ortholog assignment based on profile HMM and adaptive score threshold , 2019, bioRxiv.

[18]  P. Bork,et al.  Interactive Tree Of Life (iTOL) v4: recent updates and new developments , 2019, Nucleic Acids Res..

[19]  Yu Lin,et al.  Assembly of long, error-prone reads using repeat graphs , 2018, Nature Biotechnology.

[20]  T. Crowther,et al.  Cross-biome patterns in soil microbial respiration predictable from evolutionary theory on thermal adaptation , 2018 .

[21]  Eoin L. Brodie,et al.  Defining trait-based microbial strategies with consequences for soil carbon cycling under climate change , 2018, The ISME Journal.

[22]  Zhenglu Yang,et al.  dbCAN2: a meta server for automated carbohydrate-active enzyme annotation , 2018, Nucleic Acids Res..

[23]  P. Reich,et al.  Microbial richness and composition independently drive soil multifunctionality , 2017 .

[24]  Pete Smith,et al.  Natural climate solutions , 2017, Proceedings of the National Academy of Sciences.

[25]  S. Frey,et al.  Long-term pattern and magnitude of soil carbon feedback to the climate system in a warming world , 2017, Science.

[26]  Natalia N. Ivanova,et al.  Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea , 2017, Nature Biotechnology.

[27]  J. Melillo,et al.  Changes in substrate availability drive carbon cycle response to chronic warming , 2017 .

[28]  Niranjan Nagarajan,et al.  Fast and accurate de novo genome assembly from long uncorrected reads. , 2017, Genome research.

[29]  Ryan R. Wick,et al.  Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads , 2016, bioRxiv.

[30]  B. Fox,et al.  Evolution and Ecology of Actinobacteria and Their Bioenergy Applications. , 2016, Annual review of microbiology.

[31]  S. Frey,et al.  Long-Term Warming Alters Carbohydrate Degradation Potential in Temperate Forest Soils , 2016, Applied and Environmental Microbiology.

[32]  L. Pritchard,et al.  Genomics and taxonomy in diagnostics for food security: soft-rotting enterobacterial plant pathogens , 2016 .

[33]  Connor T. Skennerton,et al.  CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes , 2015, Genome research.

[34]  G. Bonan,et al.  Representing life in the Earth system with soil microbial functional traits in the MIMICS model , 2015 .

[35]  J. Melillo,et al.  Two decades of warming increases diversity of a potentially lignolytic bacterial community , 2015, Front. Microbiol..

[36]  J. Blanchard,et al.  Long-term forest soil warming alters microbial communities in temperate forest soils , 2015, Front. Microbiol..

[37]  Chao Xie,et al.  Fast and sensitive protein alignment using DIAMOND , 2014, Nature Methods.

[38]  William R. Wieder,et al.  Integrating microbial physiology and physio-chemical principles in soils with the MIcrobial-MIneral Carbon Stabilization (MIMICS) model , 2014 .

[39]  M. V. D. van der Heijden,et al.  Soil biodiversity and soil community composition determine ecosystem multifunctionality , 2014, Proceedings of the National Academy of Sciences.

[40]  I. Paulsen,et al.  Microbiology of the Anthropocene , 2014 .

[41]  M. Bradford Thermal adaptation of decomposer communities in warming soils , 2013, Front. Microbiol..

[42]  William R. Wieder,et al.  Global soil carbon projections are improved by modelling microbial processes , 2013 .

[43]  Diana R. Nemergut,et al.  Patterns and Processes of Microbial Community Assembly , 2013, Microbiology and Molecular Reviews.

[44]  István Nagy,et al.  Environmental shaping of codon usage and functional adaptation across microbial communities , 2013, Nucleic acids research.

[45]  Alexey A. Gurevich,et al.  QUAST: quality assessment tool for genome assemblies , 2013, Bioinform..

[46]  Didier L. Baho,et al.  Fundamentals of Microbial Community Resistance and Resilience , 2012, Front. Microbio..

[47]  Susumu Goto,et al.  KEGG for integration and interpretation of large-scale molecular data sets , 2011, Nucleic Acids Res..

[48]  Stijn van Dongen,et al.  Using MCL to extract clusters from networks. , 2012, Methods in molecular biology.

[49]  H. Margalit,et al.  Variation in global codon usage bias among prokaryotic organisms is associated with their lifestyles , 2011, Genome Biology.

[50]  J. Melillo,et al.  Soil warming alters nitrogen cycling in a New England forest: implications for ecosystem function and structure , 2011, Oecologia.

[51]  R. B. Jackson,et al.  A Large and Persistent Carbon Sink in the World’s Forests , 2011, Science.

[52]  S. Fortune,et al.  Variation among Genome Sequences of H37Rv Strains of Mycobacterium tuberculosis from Multiple Laboratories , 2010, Journal of bacteriology.

[53]  Miriam L. Land,et al.  Trace: Tennessee Research and Creative Exchange Prodigal: Prokaryotic Gene Recognition and Translation Initiation Site Identification Recommended Citation Prodigal: Prokaryotic Gene Recognition and Translation Initiation Site Identification , 2022 .

[54]  S. Frey,et al.  Thermal adaptation of soil microbial respiration to elevated temperature. , 2008, Ecology letters.

[55]  S. Frey,et al.  Microbial biomass, functional capacity, and community structure after 12 years of soil warming , 2008 .

[56]  J. Rougemont,et al.  A rapid bootstrap algorithm for the RAxML Web servers. , 2008, Systematic biology.

[57]  S. Allison,et al.  Resistance, resilience, and redundancy in microbial communities , 2008, Proceedings of the National Academy of Sciences.

[58]  R. Lal Forest soils and carbon sequestration , 2005 .

[59]  Kristian Vlahovicek,et al.  Comparison of codon usage measures and their applicability in prediction of microbial gene expressivity , 2005, BMC Bioinformatics.

[60]  K. Konstantinidis,et al.  Genomic insights that advance the species definition for prokaryotes. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[61]  Thomas Ludwig,et al.  RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees , 2005, Bioinform..

[62]  Jonathan M. Chase,et al.  The metacommunity concept: a framework for multi-scale community ecology , 2004 .

[63]  Robert C. Edgar,et al.  MUSCLE: multiple sequence alignment with high accuracy and high throughput. , 2004, Nucleic acids research.

[64]  Jeffrey A. Andrews,et al.  Soil respiration and the global carbon cycle , 2000 .

[65]  J. Aber,et al.  Responses of Trace Gas Fluxes and N Availability to Experimentally Elevated Soil Temperatures , 1994 .

[66]  R. K. Dixon,et al.  Carbon Pools and Flux of Global Forest Ecosystems , 1994, Science.

[67]  S. Goodison,et al.  16S ribosomal DNA amplification for phylogenetic study , 1991, Journal of bacteriology.

[68]  F. Wright The 'effective number of codons' used in a gene. , 1990, Gene.