in

Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution

  • 1.

    Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J, Locey KJ, et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature. 2017;551:457.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 2.

    Nelson MB, Martiny AC, Martiny JBH. Global biogeography of microbial nitrogen-cycling traits in soil. Proc Natl Acad Sci USA. 2016;113:8033–40.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 3.

    Tringe SG, von Mering C, Kobayashi A, Salamov AA, Chen K, Chang HW, et al. Comparative metagenomics of microbial communities. Science. 2005;308:554–7.

    CAS 
    PubMed 

    Google Scholar 

  • 4.

    Ottesen EA, Young CR, Gifford SM, Eppley JM, Marin R, Schuster SC, et al. Ocean microbes. Multispecies diel transcriptional oscillations in open ocean heterotrophic bacterial assemblages. Science. 2014;345:207–12.

    CAS 
    PubMed 

    Google Scholar 

  • 5.

    Fierer N. Embracing the unknown: disentangling the complexities of the soil microbiome. Nat Rev Microbiol. 2017;15:579–90.

    CAS 
    PubMed 

    Google Scholar 

  • 6.

    Starnawski P, Bataillon T, Ettema TJG, Jochum LM, Schreiber L, Chen X, et al. Microbial community assembly and evolution in subseafloor sediment. Proc Natl Acad Sci USA. 2017;114:2940–5.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 7.

    Huttenhower C, Gevers D, Knight R, Abubucker S, Badger JH, Chinwalla AT, et al. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486:207–14.

    CAS 

    Google Scholar 

  • 8.

    Brulc JM, Antonopoulos DA, Miller MEB, Wilson MK, Yannarell AC, Dinsdale EA, et al. Gene-centric metagenomics of the fiber-adherent bovine rumen microbiome reveals forage specific glycoside hydrolases. Proc Natl Acad Sci USA. 2009;106:1948–53.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 9.

    Schloss PD, Handelsman J. Metagenomics for studying unculturable microorganisms: cutting the Gordian knot. Genome Biol. 2005;6:229.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 10.

    Fierer N, Leff JW, Adams BJ, Nielsen UN, Bates ST, Lauber CL, et al. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc Natl Acad Sci USA. 2012;109:21390–5.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 11.

    Almeida A, Mitchell AL, Boland M, Forster SC, Gloor GB, Tarkowska A, et al. A new genomic blueprint of the human gut microbiota. Nature. 2019;568:499–504.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 12.

    Almeida A, Nayfach S, Boland M, Strozzi F, Beracochea M, Shi ZJ, et al. A unified catalog of 204,938 reference genomes from the human gut microbiome. Nat Biotechnol. 2021;39:105–14.

    CAS 
    PubMed 

    Google Scholar 

  • 13.

    Anantharaman K, Brown CT, Hug LA, Sharon I, Castelle CJ, Probst AJ, et al. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat Commun. 2016;7:13219.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 14.

    Delmont TO, Quince C, Shaiber A, Esen OC, Lee STM, Lucker S, et al. Nitrogen-fixing populations of planctomycetes and proteobacteria are abundant in the surface ocean. bioRxiv. 2017. https://doi.org/10.1101/129791.

  • 15.

    Parks DH, Rinke C, Chuvochina M, Chaumeil P-A, Woodcroft BJ, Evans PN, et al. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nat Microbiol. 2017;2:1533–42.

    CAS 
    PubMed 

    Google Scholar 

  • 16.

    Nayfach S, Shi ZJ, Seshadri R, Pollard KS, Kyrpides NC. New insights from uncultivated genomes of the global human gut microbiome. Nature. 2019;568:505–10.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 17.

    Nayfach S, Roux S, Seshadri R, Udwary D, Varghese N, Schulz F, et al. A genomic catalog of Earth’s microbiomes. Nat Biotechnol. 2021;39:499–509.

    CAS 
    PubMed 

    Google Scholar 

  • 18.

    Eloe-Fadrosh EA, Paez-Espino D, Jarett J, Dunfield PF, Hedlund BP, Dekas AE, et al. Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs. Nat Commun. 2016;7:10476.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 19.

    Schulz F, Eloe-Fadrosh EA, Bowers RM, Jarett J, Nielsen T, Ivanova NN, et al. Towards a balanced view of the bacterial tree of life. Microbiome. 2017;5:140.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 20.

    Brown CT, Hug LA, Thomas BC, Sharon I, Castelle CJ, Singh A, et al. Unusual biology across a group comprising more than 15% of domain Bacteria. Nature. 2015;523:208–11.

    CAS 
    PubMed 

    Google Scholar 

  • 21.

    Jay ZJ, Inskeep WP. The distribution, diversity, and importance of 16S rRNA gene introns in the order Thermoproteales. Biol Direct. 2015;10:1–10.

    CAS 

    Google Scholar 

  • 22.

    Albertsen M, Hugenholtz P, Skarshewski A, Nielsen KL, Tyson GW, Nielsen PH. Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes. Nat Biotechnol. 2013;31:533–8.

    CAS 
    PubMed 

    Google Scholar 

  • 23.

    Chen L-X, Anantharaman K, Shaiber A, Eren AM, Banfield JF. Accurate and complete genomes from metagenomes. Genome Res. 2020;30:315–33.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 24.

    Tully BJ, Graham ED, Heidelberg JF. The Reconstruction of 2,631 draft metagenome-assembled genomes from the global oceans. bioRxiv. 2017. https://doi.org/10.1101/162503.

  • 25.

    Sczyrba A, Hofmann P, Belmann P, Koslicki D, Janssen S, Dröge J, et al. Critical assessment of metagenome interpretation—a benchmark of metagenomics software. Nat Methods. 2017;14:1063–71.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 26.

    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;25:1043–55.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 27.

    Bowers RM, Doud DFR, Woyke T. Analysis of single-cell genome sequences of bacteria and archaea. Emerg Top Life Sci. 2017;1:249–55.

    CAS 
    PubMed 

    Google Scholar 

  • 28.

    Labonté JM, Swan BK, Poulos B, Luo H, Koren S, Hallam SJ, et al. Single-cell genomics-based analysis of virus-host interactions in marine surface bacterioplankton. ISME J. 2015;9:2386–99.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 29.

    Roux S, Hawley AK, Torres Beltran M, Scofield M, Schwientek P, Stepanauskas R, et al. Ecology and evolution of viruses infecting uncultivated SUP05 bacteria as revealed by single-cell- and meta-genomics. Elife. 2014;3:e03125.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 30.

    Jarett JK, Džunková M, Schulz F, Roux S, Paez-Espino D, Eloe-Fadrosh E, et al. Insights into the dynamics between viruses and their hosts in a hot spring microbial mat. ISME J. 2020;14:2527–41.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 31.

    Woyke T, Doud DFR, Schulz F. The trajectory of microbial single-cell sequencing. Nat Methods. 2017;14: 1045–54.

  • 32.

    Lasken RS. Genomic sequencing of uncultured microorganisms from single cells. Nat Rev Microbiol. 2012;10:631–40.

    CAS 
    PubMed 

    Google Scholar 

  • 33.

    Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy TBK, et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol. 2017;35:725–31.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 34.

    Zaremba-Niedzwiedzka K, Viklund J, Zhao W, Ast J, Sczyrba A, Woyke T, et al. Single-cell genomics reveal low recombination frequencies in freshwater bacteria of the SAR11 clade. Genome Biol. 2013;14:R130.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 35.

    Kashtan N, Roggensack SE, Rodrigue S, Thompson JW, Biller SJ, Coe A, et al. Single-cell genomics reveals hundreds of coexisting subpopulations in wild Prochlorococcus. Science. 2014;344:416–20.

    CAS 
    PubMed 

    Google Scholar 

  • 36.

    Pachiadaki MG, Brown JM, Brown J, Bezuidt O, Berube PM, Biller SJ, et al. Charting the complexity of the marine microbiome through single-cell genomics. Cell. 2019;179:1623–35.e11.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 37.

    Ellegaard KM, Klasson L, Andersson SGE. Testing the reproducibility of multiple displacement amplification on genomes of clonal endosymbiont populations. PLoS ONE. 2013;8:e82319.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 38.

    Luo C, Knight R, Siljander H, Knip M, Xavier RJ, Gevers D. ConStrains identifies microbial strains in metagenomic datasets. Nat Biotechnol. 2015;33:1045–52.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 39.

    Milanese A, Mende DR, Paoli L, Salazar G, Ruscheweyh HJ, Cuenca M, et al. Microbial abundance, activity and population genomic profiling with mOTUs2. Nat Commun. 2019;10:1–11.

    Google Scholar 

  • 40.

    Nayfach S, Rodriguez-Mueller B, Garud N, Pollard KS. An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography. Genome Res. 2016;26:1612–25.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 41.

    Schloissnig S, Arumugam M, Sunagawa S, Mitreva M, Tap J, Zhu A, et al. Genomic variation landscape of the human gut microbiome. Nature. 2013;493:45–50.

    PubMed 

    Google Scholar 

  • 42.

    Garud NR, Pollard KS. Population genetics in the human microbiome. Trends Genet. 2020;36:53–67.

  • 43.

    Bushnell B, Rood J, Singer E. BBMerge—accurate paired shotgun read merging via overlap. PLoS ONE. 2017;12:e0185056.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 44.

    Grasby SE, Hutcheon I. Controls on the distribution of thermal springs in the southern Canadian Cordillera. Can J Earth Sci. 2001;38:427–40.

    CAS 

    Google Scholar 

  • 45.

    Brady AL, Sharp CE, Grasby SE, Dunfield PF. Anaerobic carboxydotrophic bacteria in geothermal springs identified using stable isotope probing. Front Microbiol. 2015;6:897.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 46.

    Rinke C, Lee J, Nath N, Goudeau D, Thompson B, Poulton N, et al. Obtaining genomes from uncultivated environmental microorganisms using FACS-based single-cell genomics. Nat Protoc. 2014;9:1038–48.

    CAS 
    PubMed 

    Google Scholar 

  • 47.

    Tremblay J, Singh K, Fern A, Kirton ES, He S, Woyke T, et al. Primer and platform effects on 16S rRNA tag sequencing. Front Microbiol. 2015;6:771.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 48.

    Bowers RM, Clum A, Tice H, Lim J, Singh K, Ciobanu D, et al. Impact of library preparation protocols and template quantity on the metagenomic reconstruction of a mock microbial community. BMC Genomics. 2015;16:856.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 49.

    Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 50.

    Amir A, McDonald D, Navas-Molina JA, Kopylova E, Morton JT, Zech Xu Z, et al. Deblur rapidly resolves single-nucleotide community sequence patterns. mSystems. 2017;2:e00191–16.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 51.

    Bokulich NA, Kaehler BD, Rideout JR, Dillon M, Bolyen E, Knight R, et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome. 2018;6:1–17.

    Google Scholar 

  • 52.

    Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 2013;41:D590–6.

    CAS 
    PubMed 

    Google Scholar 

  • 53.

    Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455–77.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 54.

    Kang DD, Froula J, Egan R, Wang Z. A robust statistical framework for reconstructing genomes from metagenomic data. bioRxiv. 2014. https://doi.org/10.1101/011460.

  • 55.

    Chen IMA, Chu K, Palaniappan K, Ratner A, Huang J, Huntemann M, et al. The IMG/M data management and analysis system v.6.0: New tools and advanced capabilities. Nucleic Acids Res. 2021;49:D751–63.

    CAS 
    PubMed 

    Google Scholar 

  • 56.

    Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High-throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. bioRxiv. 2017. https://doi.org/10.1101/225342.

  • 57.

    Chen I-MA, Markowitz VM, Chu K, Palaniappan K, Szeto E, Pillay M, et al. IMG/M: integrated genome and metagenome comparative data analysis system. Nucleic Acids Res. 2017;45:D507–16.

    CAS 
    PubMed 

    Google Scholar 

  • 58.

    Eveleigh RJM, Meehan CJ, Archibald JM, Beiko RG. Being Aquifex aeolicus: untangling a hyperthermophile’s checkered past. Genome Biol Evol. 2013;5:2478.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 59.

    Fuchsman CA, Collins RE, Rocap G, Brazelton WJ. Effect of the environment on horizontal gene transfer between bacteria and archaea. PeerJ. 2017;5:e3865.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 60.

    Boussau B, Guéguen L, Gouy M. Accounting for horizontal gene transfers explains conflicting hypotheses regarding the position of aquificales in the phylogeny of Bacteria. BMC Evol Biol. 2008;8:272.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 61.

    Yu FB, Blainey PC, Schulz F, Woyke T, Horowitz MA, Quake SR. Microfluidic-based mini-metagenomics enables discovery of novel microbial lineages from complex environmental samples. Elife. 2017;6:e26580.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 62.

    Hug LA, Baker BJ, Anantharaman K, Brown CT, Probst AJ, Castelle CJ, et al. A new view of the tree of life. Nat Microbiol. 2016;1:16048.

    CAS 
    PubMed 

    Google Scholar 

  • 63.

    Case RJ, Boucher Y, Dahllöf I, Holmström C, Doolittle WF, Kjelleberg S. Use of 16S rRNA and rpoB genes as molecular markers for microbial ecology studies. Appl Environ Microbiol. 2007;73:278–88.

    CAS 
    PubMed 

    Google Scholar 

  • 64.

    Roux S, Enault F, Hurwitz BL, Sullivan MB. VirSorter: mining viral signal from microbial genomic data. PeerJ. 2015;3:e985.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 65.

    Krawczyk PS, Lipinski L, Dziembowski A. PlasFlow: predicting plasmid sequences in metagenomic data using genome signatures. Nucleic Acids Res. 2018;46:e35.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 66.

    Cock PJA, Antao T, Chang JT, Chapman BA, Cox CJ, Dalke A, et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009;25:1422–3.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 67.

    Paez-Espino D, Chen I-MA, Palaniappan K, Ratner A, Chu K, Szeto E, et al. IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses. Nucleic Acids Res. 2017;45:D457–65.

    CAS 
    PubMed 

    Google Scholar 

  • 68.

    Bland C, Ramsey TL, Sabree F, Lowe M, Brown K, Kyrpides NC, et al. CRISPR Recognition Tool (CRT): a tool for automatic detection of clustered regularly interspaced palindromic repeats. BMC Bioinforma. 2007;8:209.

    Google Scholar 

  • 69.

    Edgar RC. PILER-CR: Fast and accurate identification of CRISPR repeats. BMC Bioinforma. 2007;8:18.

    Google Scholar 

  • 70.

    Sharp CE, Brady AL, Sharp GH, Grasby SE, Stott MB, Dunfield PF. Humboldt’s spa: microbial diversity is controlled by temperature in geothermal environments. ISME J. 2014;8:1166–74.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 71.

    Eloe-Fadrosh EA, Ivanova NN, Woyke T, Kyrpides NC. Metagenomics uncovers gaps in amplicon-based detection of microbial diversity. Nat Microbiol. 2016;1:15032.

    CAS 
    PubMed 

    Google Scholar 

  • 72.

    Clingenpeel S, Clum A, Schwientek P, Rinke C, Woyke T. Reconstructing each cell’s genome within complex microbial communities-dream or reality? Front Microbiol. 2014;5:771.

    PubMed 

    Google Scholar 

  • 73.

    Westoby M, Nielsen DA, Gillings MR, Litchman E, Madin JS, Paulsen IT, et al. Cell size, genome size, and maximum growth rate are near-independent dimensions of ecological variation across bacteria and archaea. Ecol Evol. 2021;11:3956–76.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 74.

    Bendall ML, Stevens SL, Chan L-K, Malfatti S, Schwientek P, Tremblay J, et al. Genome-wide selective sweeps and gene-specific sweeps in natural bacterial populations. ISME J. 2016;10:1589–601.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 75.

    Meziti A, Tsementzi D, Rodriguez-R LM, Hatt JK, Karayanni H, Kormas KA, et al. Quantifying the changes in genetic diversity within sequence-discrete bacterial populations across a spatial and temporal riverine gradient. ISME J. 2019;13:767–79.

    PubMed 

    Google Scholar 

  • 76.

    Achtman M, Wagner M. Microbial diversity and the genetic nature of microbial species. Nat Rev Microbiol. 2008;6:431–40.

  • 77.

    Reysenbach A-L. Aquificales ord. nov. Bergey’s manual of systematics of archaea and bacteria. Chichester: John Wiley & Sons, Ltd; 2015. p. 1.

  • 78.

    McKay LJ, Nigro OD, Dlakić M, Luttrell KM, Rusch DB, Fields MW, et al. Sulfur cycling and host-virus interactions in Aquificales-dominated biofilms from Yellowstone’s hottest ecosystems. ISME J. 2021;2021:1–14.

    Google Scholar 

  • 79.

    Hügler M, Huber H, Molyneaux SJ, Vetriani C, Sievert SM. Autotrophic CO2 fixation via the reductive tricarboxylic acid cycle in different lineages within the phylum Aquificae: evidence for two ways of citrate cleavage. Environ Microbiol. 2007;9:81–92.

    PubMed 

    Google Scholar 

  • 80.

    Alneberg J, Karlsson CMG, Divne AM, Bergin C, Homa F, Lindh MV, et al. Genomes from uncultivated prokaryotes: a comparison of metagenome-assembled and single-amplified genomes. Microbiome. 2018;6:173.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 81.

    Nelson WC, Tully BJ, Mobberley JM. Biases in genome reconstruction from metagenomic data. PeerJ. 2020;8:e10119.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 82.

    Golicz AA, Bayer PE, Bhalla PL, Batley J, Edwards D. Pangenomics comes of age: from bacteria to plant and animal applications. Trends Genet. 2020;36:132–45.

  • 83.

    Maguire F, Jia B, Gray KL, Lau WYV, Beiko RG, Brinkman FSL. Metagenome-assembled genome binning methods with short reads disproportionately fail for plasmids and genomic islands. Micro Genomics. 2020;6:1–12.

    CAS 

    Google Scholar 

  • 84.

    Shmakov SA, Sitnik V, Makarova KS, Wolf YI, Severinov KV, Koonin EV. The CRISPR spacer space is dominated by sequences from species-specific mobilomes. mBio. 2017;8:e01397–17.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 85.

    Weinberger AD, Wolf YI, Lobkovsky AE, Gilmore MS, Koonin EV. Viral diversity threshold for adaptive immunity in prokaryotes. MBio. 2012;3:e00456–12.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 86.

    Drake JW. Avoiding dangerous missense: thermophiles display especially low mutation rates. PLoS Genet. 2009;5:1000520.

    Google Scholar 

  • 87.

    Wozniak RA, Waldor MK. Integrative and conjugative elements: mosaic mobile genetic elements enabling dynamic lateral gene flow. Nat Rev Microbiol. 2010;8:552–63.

    CAS 
    PubMed 

    Google Scholar 

  • 88.

    Soto-Perez P, Bisanz JE, Berry JD, Lam KN, Bondy-Denomy J, Turnbaugh PJ. CRISPR-Cas system of a prevalent human gut bacterium reveals hyper-targeting against phages in a human virome catalog. Cell Host Microbe. 2019;26:325–35.e5.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 89.

    Stern A, Keren L, Wurtzel O, Amitai G, Sorek R. Self-targeting by CRISPR: gene regulation or autoimmunity? Trends Genet. 2010;26:335–40.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 90.

    Nobrega FL, Walinga H, Dutilh BE, Brouns SJJ. Prophages are associated with extensive CRISPR-Cas auto-immunity. Nucleic Acids Res. 2020;48:12074–84.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 91.

    Edgar R, Qimron U. The Escherichia coli CRISPR system protects from λ lysogenization, lysogens, and prophage induction. J Bacteriol. 2010;192:6291–4.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 92.

    Vercoe RB, Chang JT, Dy RL, Taylor C, Gristwood T, Clulow JS, et al. Cytotoxic chromosomal targeting by CRISPR/Cas systems can reshape bacterial genomes and expel or remodel pathogenicity islands. PLoS Genet. 2013;9:e1003454.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 93.

    Wiedenbeck J, Cohan FM. Origins of bacterial diversity through horizontal genetic transfer and adaptation to new ecological niches. FEMS Microbiol Rev. 2011;35:957–76.

  • 94.

    Cheng L, Connor TR, Siren J, Aanensen DM, Corander J. Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Mol Biol Evol. 2013;30:1224–8.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 

  • 95.

    Tonkin-Hill G, Lees JA, Bentley SD, Frost SDW, Corander J. RhierBAPS: An R implementation of the population clustering algorithm hierBAPS. Wellcome Open Res. 2018;3:93.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 96.

    Rosen MJ, Davison M, Bhaya D, Fisher DS. Fine-scale diversity and extensive recombination in a quasisexual bacterial population occupying a broad niche. Science. 2015;348:1019–23.

    CAS 
    PubMed 

    Google Scholar 

  • 97.

    Bubendorfer S, Krebes J, Yang I, Hage E, Schulz TF, Bahlawane C, et al. Genome-wide analysis of chromosomal import patterns after natural transformation of Helicobacter pylori. Nat Commun. 2016;7:1–12.

    Google Scholar 

  • 98.

    Hanage WP, Fraser C, Spratt BG. Fuzzy species among recombinogenic bacteria. BMC Biol. 2005;3:6.

    PubMed 
    PubMed Central 

    Google Scholar 

  • 99.

    Sakoparnig T, Field C, van Nimwegen E. Whole genome phylogenies reflect the distributions of recombination rates for many bacterial species. Elife. 2021;10:1–61.

    Google Scholar 

  • 100.

    Koonin EV, Makarova KS, Wolf YI, Krupovic M. Evolutionary entanglement of mobile genetic elements and host defence systems: guns for hire. Nat Rev Genet. 2020;21:119–31.

    CAS 
    PubMed 

    Google Scholar 

  • 101.

    Iranzo J, Cuesta JA, Manrubia S, Katsnelson MI, Koonin EV. Disentangling the effects of selection and loss bias on gene dynamics. Proc Natl Acad Sci USA. 2017;114:E5616–24.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar 


  • Source: Ecology - nature.com

    Assessing the influence of the amount of reachable habitat on genetic structure using landscape and genetic graphs

    Biodiversity and ecosystem functions depend on environmental conditions and resources rather than the geodiversity of a tropical biodiversity hotspot