Dynamics of microbial populations mediating biogeochemical cycling in a freshwater lake

BackgroundMicrobial processes are intricately linked to the depletion of oxygen in in-land and coastal water bodies, with devastating economic and ecological consequences. Microorganisms deplete oxygen during biomass decomposition, degrading the habitat of many economically important aquatic animals. Microbes then turn to alternative electron acceptors, which alter nutrient cycling and generate potent greenhouse gases. As oxygen depletion is expected to worsen with altered land use and climate change, understanding how chemical and microbial dynamics impact dead zones will aid modeling efforts to guide remediation strategies. More work is needed to understand the complex interplay between microbial genes, populations, and biogeochemistry during oxygen depletion.ResultsHere, we used 16S rRNA gene surveys, shotgun metagenomic sequencing, and a previously developed biogeochemical model to identify genes and microbial populations implicated in major biogeochemical transformations in a model lake ecosystem. Shotgun metagenomic sequencing was done for one time point in Aug., 2013, and 16S rRNA gene sequencing was done for a 5-month time series (Mar.–Aug., 2013) to capture the spatiotemporal dynamics of genes and microorganisms mediating the modeled processes. Metagenomic binning analysis resulted in many metagenome-assembled genomes (MAGs) that are implicated in the modeled processes through gene content similarity to cultured organism and the presence of key genes involved in these pathways. The MAGs suggested some populations are capable of methane and sulfide oxidation coupled to nitrate reduction. Using the model, we observe that modulating these processes has a substantial impact on overall lake biogeochemistry. Additionally, 16S rRNA gene sequences from the metagenomic and amplicon libraries were linked to processes through the MAGs. We compared the dynamics of microbial populations in the water column to the model predictions. Many microbial populations involved in primary carbon oxidation had dynamics similar to the model, while those associated with secondary oxidation processes deviated substantially.ConclusionsThis work demonstrates that the unique capabilities of resident microbial populations will substantially impact the concentration and speciation of chemicals in the water column, unless other microbial processes adjust to compensate for these differences. It further highlights the importance of the biological aspects of biogeochemical processes, such as fluctuations in microbial population dynamics. Integrating gene and population dynamics into biogeochemical models has the potential to improve predictions of the community response under altered scenarios to guide remediation efforts.

[1]  Satoru Miyano,et al.  Open source clustering software , 2004 .

[2]  Philippe Van Cappellen,et al.  Kinetic modeling of microbially-driven redox chemistry of subsurface environments : coupling transport, microbial metabolism and geochemistry , 1998 .

[3]  G. Pusch,et al.  Phylogenetic conservatism of functional traits in microorganisms , 2012, The ISME Journal.

[4]  Olaf Pfannkuche,et al.  A marine microbial consortium apparently mediating anaerobic oxidation of methane , 2000, Nature.

[5]  Brian D. Ondov,et al.  Mash: fast genome and metagenome distance estimation using MinHash , 2015, Genome Biology.

[6]  Katherine H. Huang,et al.  Structure, Function and Diversity of the Healthy Human Microbiome , 2012, Nature.

[7]  P. Nannipieri,et al.  Microbial diversity and soil functions , 2003 .

[8]  C. Dahl,et al.  Sirohaem sulfite reductase and other proteins encoded by genes at the dsr locus of Chromatium vinosum are involved in the oxidation of intracellular sulfur. , 1998, Microbiology.

[9]  L. Maia,et al.  How biology handles nitrite. , 2014, Chemical reviews.

[10]  M. Fukui,et al.  Sulfuricella denitrificans gen. nov., sp. nov., a sulfur-oxidizing autotroph isolated from a freshwater lake. , 2010, International journal of systematic and evolutionary microbiology.

[11]  Georgia Destouni,et al.  Hypoxia-related processes in the Baltic Sea. , 2009, Environmental science & technology.

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

[13]  D. Reed,et al.  Gene-centric approach to integrating environmental genomics and biogeochemical models , 2014, Proceedings of the National Academy of Sciences.

[14]  F. Chapin,et al.  EFFECTS OF BIODIVERSITY ON ECOSYSTEM FUNCTIONING: A CONSENSUS OF CURRENT KNOWLEDGE , 2005 .

[15]  Ratana Somrongthong,et al.  The Influence of Chronic Illness and Lifestyle Behaviors on Quality of Life among Older Thais , 2016, BioMed research international.

[16]  Michael Hupfer,et al.  Oxygen Controls the Phosphorus Release from Lake Sediments – a Long‐Lasting Paradigm in Limnology , 2008 .

[17]  W. Vongsangnak,et al.  Sequence- and Structure-Based Functional Annotation and Assessment of Metabolic Transporters in Aspergillus oryzae: A Representative Case Study , 2016, BioMed research international.

[18]  Blake A. Simmons,et al.  MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets , 2016, Bioinform..

[19]  M. McCrackin,et al.  Recovery of lakes and coastal marine ecosystems from eutrophication: A global meta‐analysis , 2017 .

[20]  J. Humbert,et al.  Impact of internal waves on the spatial distribution of Planktothrix rubescens (cyanobacteria) in an alpine lake , 2011, The ISME Journal.

[21]  S. Olesen,et al.  Surveys, simulation and single-cell assays relate function and phylogeny in a lake ecosystem , 2016, Nature Microbiology.

[22]  William R. Cullen,et al.  Arsenic speciation in the environment , 1989 .

[23]  S. Hallam,et al.  Integrating biogeochemistry with multiomic sequence information in a model oxygen minimum zone , 2016, Proceedings of the National Academy of Sciences.

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

[25]  C. Murrell,et al.  Diverse electron sources support denitrification under hypoxia in the obligate methanotroph Methylomicrobium album strain BG8 , 2015, Front. Microbiol..

[26]  W. Nelson,et al.  Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia , 2015, Applied and Environmental Microbiology.

[27]  Alice Carolyn McHardy,et al.  Taxator-tk: precise taxonomic assignment of metagenomes by fast approximation of evolutionary neighborhoods , 2014, Bioinform..

[28]  J. Tiedje,et al.  Microbial Community Analysis with Ribosomal Gene Fragments from Shotgun Metagenomes , 2015, Applied and Environmental Microbiology.

[29]  M. Kanehisa,et al.  BlastKOALA and GhostKOALA: KEGG Tools for Functional Characterization of Genome and Metagenome Sequences. , 2016, Journal of molecular biology.

[30]  Mike S. M. Jetten,et al.  A microbial consortium couples anaerobic methane oxidation to denitrification , 2006, Nature.

[31]  A Costello,et al.  Evidence that particulate methane monooxygenase and ammonia monooxygenase may be evolutionarily related. , 1995, FEMS microbiology letters.

[32]  Radhakrishnan Mahadevan,et al.  Genome-scale comparison and constraint-based metabolic reconstruction of the facultative anaerobic Fe(III)-reducer Rhodoferax ferrireducens , 2009, BMC Genomics.

[33]  H. Hemond,et al.  Time‐series analysis of high‐resolution ebullition fluxes from a stratified, freshwater lake , 2012 .

[34]  B. Henrissat,et al.  Metabolic Roles of Uncultivated Bacterioplankton Lineages in the Northern Gulf of Mexico “Dead Zone” , 2016, mBio.

[35]  Martin Hartmann,et al.  Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities , 2009, Applied and Environmental Microbiology.

[36]  Dongwan D. Kang,et al.  MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities , 2015, PeerJ.

[37]  Radhakrishnan Mahadevan,et al.  Genome-scale dynamic modeling of the competition between Rhodoferax and Geobacter in anoxic subsurface environments , 2011, The ISME Journal.

[38]  E. Bock,et al.  Nitrogen loss caused by denitrifying Nitrosomonas cells using ammonium or hydrogen as electron donors and nitrite as electron acceptor , 2004, Archives of Microbiology.

[39]  Y. Wang,et al.  Kinetic modeling of microbially-driven redox chemistry of radionuclides in subsurface environments: coupling transport, microbial metabolism and geochemistry. , 2001, Journal of contaminant hydrology.

[40]  C. Médigue,et al.  Genome Sequence of the Haloalkaliphilic Methanotrophic Bacterium Methylomicrobium alcaliphilum 20Z , 2012, Journal of bacteriology.

[41]  Watson W. Gregg,et al.  Interannual Variation in Phytoplankton Primary Production at A Global Scale , 2013, Remote. Sens..

[42]  Peter M. Vitousek,et al.  Biological invasion by Myrica faya in Hawai'i: plant demography, nitrogen fixation, ecosystem effects , 1989 .

[43]  R. V. van Spanning,et al.  Denitrification and ammonia oxidation by Nitrosomonas europaea wild-type, and NirK- and NorB-deficient mutants. , 2004, Microbiology.

[44]  Clifford H. Mortimer,et al.  THE EXCHANGE OF DISSOLVED SUBSTANCES BETWEEN MUD AND WATER IN LAKES, II , 1941 .

[45]  O. Ogunseitan,et al.  Tetranucleotide frequencies in microbial genomes , 1998, Electrophoresis.

[46]  J. Hollibaugh,et al.  Carbon-controlled nitrogen cycling in a marine 'macrocosm'- an ecosystem-scale model for managing cultural eutrophication , 1989 .

[47]  R. Conrad,et al.  DNA-, rRNA- and mRNA-based stable isotope probing of aerobic methanotrophs in lake sediment. , 2011, Environmental microbiology.

[48]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[49]  Anders F. Andersson,et al.  Binning metagenomic contigs by coverage and composition , 2014, Nature Methods.

[50]  T. Thomas,et al.  Bacterial community assembly based on functional genes rather than species , 2011, Proceedings of the National Academy of Sciences.

[51]  James R. Cole,et al.  Ribosomal Database Project: data and tools for high throughput rRNA analysis , 2013, Nucleic Acids Res..

[52]  J. Lloyd,et al.  Microbial detoxification of metals and radionuclides. , 2001, Current opinion in biotechnology.

[53]  N. Wrage,et al.  Nitrifier denitrification as a distinct and significant source of nitrous oxide from soil , 2011 .

[54]  James Taylor,et al.  MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis , 2018, Microbiome.

[55]  Torsten Seemann,et al.  Prokka: rapid prokaryotic genome annotation , 2014, Bioinform..

[56]  A. Findlay,et al.  Disguised as a Sulfate Reducer: Growth of the Deltaproteobacterium Desulfurivibrio alkaliphilus by Sulfide Oxidation with Nitrate , 2017, mBio.

[57]  L. Stookey Ferrozine---a new spectrophotometric reagent for iron , 1970 .

[58]  M. Fukui,et al.  Sulfuritalea hydrogenivorans gen. nov., sp. nov., a facultative autotroph isolated from a freshwater lake. , 2011, International journal of systematic and evolutionary microbiology.

[59]  Adrian W. Briggs,et al.  Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers , 2015, The ISME Journal.

[60]  V. Orphan Methods for unveiling cryptic microbial partnerships in nature. , 2009, Current opinion in microbiology.

[61]  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 .

[62]  Adam M. Phillippy,et al.  MUMmer4: A fast and versatile genome alignment system , 2018, PLoS Comput. Biol..

[63]  Natalia N. Ivanova,et al.  Insights into the phylogeny and coding potential of microbial dark matter , 2013, Nature.

[64]  S Miyano,et al.  Open source clustering software. , 2004, Bioinformatics.

[65]  D. Canfield,et al.  Heterotrophic Carbon Metabolism , 2005 .

[66]  B. Schink,et al.  Anaerobic methane oxidation coupled to denitrification is the dominant methane sink in a deep lake , 2014, Proceedings of the National Academy of Sciences.

[67]  Gerhard G. Thallinger,et al.  Wx Scout Fashion Sneaker Splash Navy Women's Keds qAS4tR1wn4 for bawln.com , 2009 .

[68]  G. Chadwick,et al.  Single cell activity reveals direct electron transfer in methanotrophic consortia , 2015, Nature.

[69]  Rob Patro,et al.  Salmon provides fast and bias-aware quantification of transcript expression , 2017, Nature Methods.

[70]  William A. Walters,et al.  QIIME allows analysis of high-throughput community sequencing data , 2010, Nature Methods.

[71]  Robert C. Edgar,et al.  UPARSE: highly accurate OTU sequences from microbial amplicon reads , 2013, Nature Methods.

[72]  Alejandro A. Schäffer,et al.  Database indexing for production MegaBLAST searches , 2008, Bioinform..

[73]  Eric J. Alm,et al.  Distribution-Based Clustering: Using Ecology To Refine the Operational Taxonomic Unit , 2013, Applied and Environmental Microbiology.

[74]  H. Hemond,et al.  Nitrate suppresses internal phosphorus loading in an eutrophic lake. , 2010, Water research.

[75]  Natalia N. Ivanova,et al.  Correction: Corrigendum: Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea , 2018, Nature Biotechnology.

[76]  R. Thunell,et al.  Rapid organic matter sulfurization in sinking particles from the Cariaco Basin water column , 2016 .

[77]  D. Lovley,et al.  Evolution of electron transfer out of the cell: comparative genomics of six Geobacter genomes , 2010, BMC Genomics.

[78]  J. Raes,et al.  Microbial interactions: from networks to models , 2012, Nature Reviews Microbiology.

[79]  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.

[80]  T. Thomas,et al.  Functional equivalence and evolutionary convergence in complex communities of microbial sponge symbionts , 2012, Proceedings of the National Academy of Sciences.

[81]  Jorge Nocedal,et al.  A Limited Memory Algorithm for Bound Constrained Optimization , 1995, SIAM J. Sci. Comput..

[82]  Nils Christian Stenseth,et al.  Biotic interactions and temporal dynamics of the human gastrointestinal microbiota , 2014, The ISME Journal.

[83]  Sergey I. Nikolenko,et al.  SPAdes: A New Genome Assembly Algorithm and Its Applications to Single-Cell Sequencing , 2012, J. Comput. Biol..

[84]  E. Delong,et al.  Pattern and synchrony of gene expression among sympatric marine microbial populations , 2013, Proceedings of the National Academy of Sciences.

[85]  H. Hemond,et al.  Nitrate Controls on Iron and Arsenic in an Urban Lake , 2002, Science.

[86]  T. Lyons Sulfur isotopic trends and pathways of iron sulfide formation in upper Holocene sediments of the anoxic Black Sea , 1997 .

[87]  S. Hamilton,et al.  Denitrification by sulfur-oxidizing bacteria in a eutrophic lake , 2012 .

[88]  W. Ripple,et al.  Large predators and trophic cascades in terrestrial ecosystems of the western United States , 2009 .

[89]  Muchamad Al Azhar,et al.  A model-based insight into the coupling of nitrogen and sulfur cycles in a coastal upwelling system , 2014, Journal of geophysical research. Biogeosciences.

[90]  Rob Knight,et al.  UCHIME improves sensitivity and speed of chimera detection , 2011, Bioinform..

[91]  Lynne A. Goodwin,et al.  Comparative genomics of freshwater Fe-oxidizing bacteria: implications for physiology, ecology, and systematics , 2013, Front. Microbiol..

[92]  S. Tringe,et al.  Relationship between Abundance and Specific Activity of Bacterioplankton in Open Ocean Surface Waters , 2012, Applied and Environmental Microbiology.

[93]  Philip Ineson,et al.  Stable-isotope probing as a tool in microbial ecology , 2000, Nature.

[94]  Dean Laslett,et al.  ARAGORN, a program to detect tRNA genes and tmRNA genes in nucleotide sequences. , 2004, Nucleic acids research.

[95]  R. Dickinson,et al.  Future global warming from atmospheric trace gases , 1986, Nature.