Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Mechanisms driving genome reduction of a novel Roseobacter lineage

Summary

Members of the marine Roseobacter group are key players in the global carbon and sulfur cycles. While over 300 species have been described, only 2% possess reduced genomes (mostly 3–3.5 Mbp) compared to an average roseobacter (>4 Mbp). These taxonomic minorities are phylogenetically diverse but form a Pelagic Roseobacter Cluster (PRC) at the genome content level. Here, we cultivated eight isolates constituting a novel Roseobacter lineage which we named ‘CHUG’. Metagenomic and metatranscriptomic read recruitment analyses showed that CHUG members are globally distributed and active in marine pelagic environments. CHUG members possess some of the smallest genomes (~2.6 Mb) among all known roseobacters, but they do not exhibit canonical features of typical bacterioplankton lineages theorized to have undergone genome streamlining processes, like higher coding density, fewer paralogues and rarer pseudogenes. While CHUG members form a genome content cluster with traditional PRC members, they show important differences. Unlike other PRC members, neither the relative abundances of CHUG members nor their relative gene expression levels are correlated with chlorophyll a concentration across the global samples. CHUG members cannot utilize most phytoplankton-derived metabolites or synthesize vitamin B12, a key metabolite mediating the roseobacter-phytoplankton interactions. This combination of features is evidence for the hypothesis that CHUG members may have evolved a free-living lifestyle decoupled from phytoplankton. This ecological transition was accompanied by the loss of signature genes involved in roseobacter-phytoplankton symbiosis, suggesting that relaxation of purifying selection owing to lifestyle shift is likely an important driver of genome reduction in CHUG.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Phylogenomic tree and gene content dendrogram of roseobacters.
Fig. 2: Genomic feature comparisons between CHUG, their sister group, the outgroup, seven other PRC members, and other reference roseobacters.
Fig. 3: The global distribution of CHUG and its ecological correlation with environmental factors.
Fig. 4: The phyletic pattern of select genes.
Fig. 5: Growth assay of CHUG strain HKCCA1288 and the model roseobacter Ruegeria pomeroyi DSS-3.

Data availability

Genomic sequences of the eight CHUG genomes are available at the NCBI GenBank database under the accession number PRJNA574877.

Code availability

The custom scripts used in this study are available in the online repository (https://github.com/luolab-cuhk/CHUG-genome-reduction-project).

References

  1. 1.

    Buchan A, González JM, Moran MA. Overview of the marine Roseobacter lineage. Appl Environ Microbiol. 2005;71:5665–77.

    CAS  PubMed  Article  Google Scholar 

  2. 2.

    Luo H, Moran MA. Evolutionary ecology of the marine Roseobacter clade. Microbiol Mol Biol Rev. 2014;78:573–87.

    PubMed  Article  Google Scholar 

  3. 3.

    Moran MA, Belas R, Schell MA, González JM, Sun F, Sun S, et al. Ecological genomics of marine Roseobacters. Appl Environ Microbiol. 2007;73:4559–69.

    CAS  PubMed  Article  Google Scholar 

  4. 4.

    Giebel H-A, Kalhoefer D, Lemke A, Thole S, Gahl-Janssen R, Simon M, et al. Distribution of Roseobacter RCA and SAR11 lineages in the North Sea and characteristics of an abundant RCA isolate. ISME J. 2011;5:8–19.

    PubMed  Article  Google Scholar 

  5. 5.

    Wemheuer B, Wemheuer F, Hollensteiner J, Meyer F-D, Voget S, Daniel R. The green impact: bacterioplankton response toward a phytoplankton spring bloom in the southern North Sea assessed by comparative metagenomic and metatranscriptomic approaches. Front Microbiol. 2015;6:805.

    PubMed  Article  Google Scholar 

  6. 6.

    Pujalte MJ, Lucena T, Ruvira MA, Arahal DR, Macián MC. The family rhodobacteraceae. In: Rosenberg E, DeLong EF, Lory S, Stackebrandt E, Thompson F, editors. The Prokaryotes. Berlin, Heidelberg: Springer Berlin Heidelberg; 2014. p. 439–512.

  7. 7.

    Buchan A, Hadden M, Suzuki MT. Development and application of quantitative-PCR tools for subgroups of the Roseobacter clade. Appl Environ Microbiol. 2009;75:7542–7.

    CAS  PubMed  Article  Google Scholar 

  8. 8.

    Luo H, Swan BK, Stepanauskas R, Hughes AL, Moran MA. Comparing effective population sizes of dominant marine alphaproteobacteria lineages. Environ Microbiol Rep. 2014;6:167–72.

    PubMed  Article  Google Scholar 

  9. 9.

    Giebel H-A, Kalhoefer D, Gahl-Janssen R, Choo Y-J, Lee K, Cho J-C, et al. Planktomarina temperata gen. nov., sp. nov., belonging to the globally distributed RCA cluster of the marine Roseobacter clade, isolated from the German Wadden Sea. Int J Syst Evol Microbiol. 2013;63:4207–17.

    CAS  PubMed  Article  Google Scholar 

  10. 10.

    Voget S, Wemheuer B, Brinkhoff T, Vollmers J, Dietrich S, Giebel H-A, et al. Adaptation of an abundant Roseobacter RCA organism to pelagic systems revealed by genomic and transcriptomic analyses. ISME J. 2015;9:371–84.

    CAS  PubMed  Article  Google Scholar 

  11. 11.

    Billerbeck S, Wemheuer B, Voget S, Poehlein A, Giebel H-A, Brinkhoff T, et al. Biogeography and environmental genomics of the Roseobacter-affiliated pelagic CHAB-I-5 lineage. Nat Microbiol. 2016;1:16063.

    CAS  PubMed  Article  Google Scholar 

  12. 12.

    Zhang Y, Sun Y, Jiao N, Stepanauskas R, Luo H. Ecological genomics of the uncultivated marine Roseobacter lineage CHAB-I-5. Appl Environ Microbiol. 2016;82:2100–11.

    CAS  PubMed  Article  Google Scholar 

  13. 13.

    Wagner-Döbler I, Ballhausen B, Berger M, Brinkhoff T, Buchholz I, Bunk B, et al. The complete genome sequence of the algal symbiont Dinoroseobacter shibae: a hitchhiker’s guide to life in the sea. ISME J. 2010;4:61–77.

    PubMed  Article  CAS  Google Scholar 

  14. 14.

    Durham BP, Sharma S, Luo H, Smith CB, Amin SA, Bender SJ, et al. Cryptic carbon and sulfur cycling between surface ocean plankton. Proc Natl Acad Sci USA. 2015;112:453–7.

    CAS  PubMed  Article  Google Scholar 

  15. 15.

    Cooper MB, Kazamia E, Helliwell KE, Kudahl UJ, Sayer A, Wheeler GL, et al. Cross-exchange of B-vitamins underpins a mutualistic interaction between Ostreococcus tauri and Dinoroseobacter shibae. ISME J. 2019;13:334–45.

    CAS  PubMed  Article  Google Scholar 

  16. 16.

    Moran MA, Buchan A, González JM, Heidelberg JF, Whitman WB, Kiene RP, et al. Genome sequence of Silicibacter pomeroyi reveals adaptations to the marine environment. Nature. 2004;432:910–3.

    CAS  PubMed  Article  Google Scholar 

  17. 17.

    Seymour JR, Amin SA, Raina J-B, Stocker R. Zooming in on the phycosphere: the ecological interface for phytoplankton-bacteria relationships. Nat Microbiol. 2017;2:17065.

    CAS  PubMed  Article  Google Scholar 

  18. 18.

    Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30:2114–20.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  19. 19.

    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  Article  Google Scholar 

  20. 20.

    Wick RR, Judd LM, Gorrie CL, Holt KE. Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol. 2017;13:e1005595.

    Article  CAS  Google Scholar 

  21. 21.

    Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068–9.

    CAS  Article  Google Scholar 

  22. 22.

    Jain C, Rodriguez-R LM, Phillippy AM, Konstantinidis KT, Aluru S. High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries. Nat Commun. 2018;9:5114.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  23. 23.

    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  Article  Google Scholar 

  24. 24.

    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  Article  Google Scholar 

  25. 25.

    Chu X, Li S, Wang S, Luo D, Luo H. Gene loss through pseudogenization contributes to the ecological diversification of a generalist Roseobacter lineage. ISME J. 2020;15:489–502.

    PubMed  Article  CAS  Google Scholar 

  26. 26.

    Revell LJ. phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol Evol. 2012;3:217–23.

    Article  Google Scholar 

  27. 27.

    Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, et al. Ocean plankton. Structure and function of the global ocean microbiome. Science. 2015;348:1261359.

    PubMed  Article  CAS  Google Scholar 

  28. 28.

    Salazar G, Paoli L, Alberti A, Huerta-Cepas J, Ruscheweyh H-J, Cuenca M, et al. Gene expression changes and community turnover differentially shape the global ocean metatranscriptome. Cell. 2019;179:1068–.e21.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  29. 29.

    Vargas C, de, Audic S, Henry N, Decelle J, Mahé F, Logares R, et al. Eukaryotic plankton diversity in the sunlit ocean. Science. 2015;348:1261605.

    PubMed  Article  CAS  Google Scholar 

  30. 30.

    Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357–9.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. 31.

    Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  32. 32.

    Harrell FE Jr. Package ‘Hmisc’. CRAN2018. 2019;2019:235–6.

    Google Scholar 

  33. 33.

    Parks DH, Chuvochina M, Waite DW, Rinke C, Skarshewski A, Chaumeil P-A, et al. A standardized bacterial taxonomy based on genome phylogeny substantially revises the tree of life. Nat Biotechnol. 2018;36:996–1004.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  34. 34.

    Simon M, Scheuner C, Meier-Kolthoff JP, Brinkhoff T, Wagner-Döbler I, Ulbrich M, et al. Phylogenomics of Rhodobacteraceae reveals evolutionary adaptation to marine and non-marine habitats. ISME J. 2017;11:1483–99.

    PubMed  PubMed Central  Article  Google Scholar 

  35. 35.

    Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30:772–80.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  36. 36.

    Capella-Gutiérrez S, Silla-Martínez JM, Gabaldón T. trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses. Bioinformatics. 2009;25:1972–3.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  37. 37.

    Nguyen L-T, Schmidt HA, Haeseler A, von, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32:268–74.

    CAS  Article  Google Scholar 

  38. 38.

    Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 2019;20:238.

    PubMed  Article  Google Scholar 

  39. 39.

    Librado P, Vieira FG, Rozas J. BadiRate: estimating family turnover rates by likelihood-based methods. Bioinformatics. 2012;28:279–81.

    CAS  PubMed  Article  Google Scholar 

  40. 40.

    Luo H, Huang Y, Stepanauskas R, Tang J. Excess of non-conservative amino acid changes in marine bacterioplankton lineages with reduced genomes. Nat Microbiol. 2017;2:17091.

    CAS  PubMed  Article  Google Scholar 

  41. 41.

    Paradis E, Schliep K. ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics. 2019;35:526–8.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  42. 42.

    Wang X, Zhang Y, Ren M, Xia T, Chu X, Liu C, et al. Cryptic speciation of a pelagic Roseobacter population varying at a few thousand nucleotide sites. ISME J. 2020;14:3106–19.

    CAS  PubMed  Article  Google Scholar 

  43. 43.

    Lekunberri I, Gasol JM, Acinas SG, Gómez-Consarnau L, Crespo BG, Casamayor EO, et al. The phylogenetic and ecological context of cultured and whole genome-sequenced planktonic bacteria from the coastal NW Mediterranean Sea. Syst Appl Microbiol. 2014;37:216–28.

    PubMed  Article  Google Scholar 

  44. 44.

    Luo H, Swan BK, Stepanauskas R, Hughes AL, Moran MA. Evolutionary analysis of a streamlined lineage of surface ocean Roseobacters. ISME J. 2014;8:1428–39.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  45. 45.

    Roesler C, Uitz J, Claustre H, Boss E, Xing X, Organelli E, et al. Recommendations for obtaining unbiased chlorophyll estimates from in situ chlorophyll fluorometers: a global analysis of WET Labs ECO sensors. Limnol Oceanogr Methods. 2017;15:572–85.

    CAS  Article  Google Scholar 

  46. 46.

    Wagner-Döbler I, Biebl H. Environmental biology of the marine Roseobacter lineage. Annu Rev Microbiol. 2006;60:255–80.

    PubMed  Article  CAS  Google Scholar 

  47. 47.

    West NJ, Obernosterer I, Zemb O, Lebaron P. Major differences of bacterial diversity and activity inside and outside of a natural iron-fertilized phytoplankton bloom in the Southern Ocean. Environ Microbiol. 2008;10:738–56.

    CAS  PubMed  Article  Google Scholar 

  48. 48.

    Rich VI, Pham VD, Eppley J, Shi Y, DeLong EF. Time-series analyses of Monterey Bay coastal microbial picoplankton using a ‘genome proxy’ microarray. Environ Microbiol. 2011;13:116–34.

    CAS  PubMed  Article  Google Scholar 

  49. 49.

    Landa M, Blain S, Christaki U, Monchy S, Obernosterer I. Shifts in bacterial community composition associated with increased carbon cycling in a mosaic of phytoplankton blooms. ISME J. 2016;10:39–50.

    CAS  PubMed  Article  Google Scholar 

  50. 50.

    Durham BP, Grote J, Whittaker KA, Bender SJ, Luo H, Grim SL, et al. Draft genome sequence of marine alphaproteobacterial strain HIMB11, the first cultivated representative of a unique lineage within the Roseobacter clade possessing an unusually small genome. Stand Genomic Sci. 2014;9:632–45.

    PubMed  PubMed Central  Article  Google Scholar 

  51. 51.

    Roth JR, Lawrence JG, Bobik TA. Cobalamin (coenzyme B12): synthesis and biological significance. Annu Rev Microbiol. 1996;50:137–81.

    CAS  PubMed  Article  Google Scholar 

  52. 52.

    Ferrer-González FX, Widner B, Holderman NR, Glushka J, Edison AS, Kujawinski EB, et al. Resource partitioning of phytoplankton metabolites that support bacterial heterotrophy. ISME J. 2021;15:762–73.

    PubMed  Article  CAS  Google Scholar 

  53. 53.

    Abreu AC, Molina-Miras A, Aguilera-Sáez LM, López-Rosales L, Del Cerón-García MC, Sánchez-Mirón A, et al. Production of amphidinols and other bioproducts of interest by the marine microalga amphidinium carterae unraveled by nuclear magnetic resonance metabolomics approach coupled to multivariate data analysis. J Agric Food Chem. 2019;67:9667–82.

    CAS  PubMed  Article  Google Scholar 

  54. 54.

    Zhou C, Luo J, Ye Y, Yan X, Liu B, Wen X. The metabolite profiling of coastal coccolithophorid species Pleurochrysis carterae (Haptophyta). Chin J Ocean Limnol 2016;34:749–56.

    CAS  Article  Google Scholar 

  55. 55.

    Bustamam MSA, Pantami HA, Azizan A, Shaari K, Min CC, Abas F, et al. Complementary analytical platforms of NMR spectroscopy and LCMS analysis in the metabolite profiling of isochrysis galbana. Mar Drugs. 2021;19:139.

    PubMed  PubMed Central  Article  Google Scholar 

  56. 56.

    Rioux L-E, Turgeon SL, Beaulieu M. Effect of season on the composition of bioactive polysaccharides from the brown seaweed Saccharina longicruris. Phytochemistry. 2009;70:1069–75.

    CAS  PubMed  Article  Google Scholar 

  57. 57.

    Ale MT, Mikkelsen JD, Meyer AS. Important determinants for fucoidan bioactivity: a critical review of structure-function relations and extraction methods for fucose-containing sulfated polysaccharides from brown seaweeds. Mar Drugs. 2011;9:2106–30.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  58. 58.

    Hada N, Nakashima T, Shrestha SP, Masui R, Narukawa Y, Tani K, et al. Synthesis and biological activities of glycosphingolipid analogues from marine sponge Aplysinella rhax. Bioorg Med Chem Lett. 2007;17:5912–5.

    CAS  PubMed  Article  Google Scholar 

  59. 59.

    Kalinin VI, Ivanchina NV, Krasokhin VB, Makarieva TN, Stonik VA. Glycosides from marine sponges (Porifera, Demospongiae): structures, taxonomical distribution, biological activities and biological roles. Mar Drugs. 2012;10:1671–710.

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  60. 60.

    Helliwell KE. The roles of B vitamins in phytoplankton nutrition: new perspectives and prospects. New Phytol. 2017;216:62–8.

    CAS  PubMed  Article  Google Scholar 

  61. 61.

    Luo H, Csuros M, Hughes AL, Moran MA. Evolution of divergent life history strategies in marine alphaproteobacteria. MBio. 2013;4:e00373–13.

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  62. 62.

    Durham BP, Dearth SP, Sharma S, Amin SA, Smith CB, Campagna SR, et al. Recognition cascade and metabolite transfer in a marine bacteria-phytoplankton model system. Environ Microbiol. 2017;19:3500–13.

    CAS  PubMed  Article  Google Scholar 

  63. 63.

    Shibl AA, Isaac A, Ochsenkühn MA, Cárdenas A, Fei C, Behringer G, et al. Diatom modulation of select bacteria through use of two unique secondary metabolites. Proc Natl Acad Sci USA. 2020;117:27445–55.

    CAS  PubMed  Article  Google Scholar 

  64. 64.

    Qu L, Feng X, Chen Y, Li L, Wang X, Hu Z et al. Metapopulation structure of diatom-associated marine bacteria. bioRxiv https://doi.org/10.1101/2021.03.10.434754 (2021).

  65. 65.

    Moore CM, Mills MM, Arrigo KR, Berman-Frank I, Bopp L, Boyd PW, et al. Processes and patterns of oceanic nutrient limitation. Nat Geosci. 2013;6:701–10.

    CAS  Article  Google Scholar 

  66. 66.

    Veaudor T, Cassier-Chauvat C, Chauvat F. Genomics of urea transport and catabolism in Cyanobacteria: biotechnological implications. Front Microbiol. 2019;10:2052.

    PubMed  Article  Google Scholar 

  67. 67.

    Luo H, Benner R, Long RA, Hu J. Subcellular localization of marine bacterial alkaline phosphatases. Proc Natl Acad Sci USA. 2009;106:21219–23.

    CAS  PubMed  Article  Google Scholar 

  68. 68.

    Sebastián M, Smith AF, González JM, Fredricks HF, van Mooy B, Koblížek M, et al. Lipid remodelling is a widespread strategy in marine heterotrophic bacteria upon phosphorus deficiency. ISME J. 2016;10:968–78.

    PubMed  Article  CAS  Google Scholar 

  69. 69.

    Geng H, Belas R. Molecular mechanisms underlying Roseobacterphytoplankton symbioses. Curr Opin Biotechnol. 2010;21:332–8.

    CAS  PubMed  Article  Google Scholar 

  70. 70.

    Luo H, Moran MA. How do divergent ecological strategies emerge among marine bacterioplankton lineages? Trends Microbiol. 2015;23:577–84.

    CAS  PubMed  Article  Google Scholar 

  71. 71.

    Biers EJ, Wang K, Pennington C, Belas R, Chen F, Moran MA. Occurrence and expression of gene transfer agent genes in marine bacterioplankton. Appl Environ Microbiol. 2008;74:2933–9.

    CAS  PubMed  Article  Google Scholar 

  72. 72.

    Giovannoni SJ, Cameron Thrash J, Temperton B. Implications of streamlining theory for microbial ecology. ISME J. 2014;8:1553–65.

    PubMed  PubMed Central  Article  Google Scholar 

  73. 73.

    Giovannoni SJ, Tripp HJ, Givan S, Podar M, Vergin KL, Baptista D, et al. Genome streamlining in a cosmopolitan oceanic bacterium. Science. 2005;309:1242–5.

    CAS  PubMed  Article  Google Scholar 

  74. 74.

    Swan BK, Tupper B, Sczyrba A, Lauro FM, Martinez-Garcia M, González JM, et al. Prevalent genome streamlining and latitudinal divergence of planktonic bacteria in the surface ocean. Proc Natl Acad Sci USA. 2013;110:11463–8.

    CAS  PubMed  Article  Google Scholar 

  75. 75.

    Luo H, Thompson LR, Stingl U, Hughes AL. Selection maintains low genomic GC content in marine SAR11 lineages. Mol Biol Evol. 2015;32:2738–48.

    CAS  PubMed  Article  Google Scholar 

  76. 76.

    Mende DR, Bryant JA, Aylward FO, Eppley JM, Nielsen T, Karl DM, et al. Environmental drivers of a microbial genomic transition zone in the ocean’s interior. Nat Microbiol. 2017;2:1367–73.

    CAS  PubMed  Article  Google Scholar 

  77. 77.

    Grzymski JJ, Dussaq AM. The significance of nitrogen cost minimization in proteomes of marine microorganisms. ISME J. 2012;6:71–80.

    CAS  PubMed  Article  Google Scholar 

  78. 78.

    Lee MD, Ahlgren NA, Kling JD, Walworth NG, Rocap G, Saito MA, et al. Marine Synechococcus isolates representing globally abundant genomic lineages demonstrate a unique evolutionary path of genome reduction without a decrease in GC content. Environ Microbiol. 2019;21:1677–86.

    CAS  PubMed  Article  Google Scholar 

  79. 79.

    Hessen DO, Jeyasingh PD, Neiman M, Weider LJ. Genome streamlining and the elemental costs of growth. Trends Ecol Evol. 2010;25:75–80.

    PubMed  Article  Google Scholar 

  80. 80.

    Vieira-Silva S, Touchon M, Rocha EPC. No evidence for elemental-based streamlining of prokaryotic genomes. Trends Ecol Evol. 2010;25:319–20. author reply 320-1

    PubMed  Article  Google Scholar 

  81. 81.

    Thingstad T, Rassoulzadegan F. Conceptual models for the biogeochemical role of the photic zone microbial food web, with particular reference to the Mediterranean Sea. Prog Oceanogr. 1999;44:271–86.

    Article  Google Scholar 

  82. 82.

    Batut B, Knibbe C, Marais G, Daubin V. Reductive genome evolution at both ends of the bacterial population size spectrum. Nat Rev Microbiol. 2014;12:841–50.

    CAS  PubMed  Article  Google Scholar 

  83. 83.

    Bourguignon T, Kinjo Y, Villa-Martín P, Coleman NV, Tang Q, Arab DA, et al. Increased mutation rate is linked to genome reduction in prokaryotes. Curr Biol. 2020;30:3848–.e4.

    CAS  PubMed  Article  Google Scholar 

  84. 84.

    Viklund J, Ettema TJG, Andersson SGE. Independent genome reduction and phylogenetic reclassification of the oceanic SAR11 clade. Mol Biol Evol. 2012;29:599–615.

    CAS  PubMed  Article  Google Scholar 

  85. 85.

    Zuckerkandl E, Pauling L, Bryson V, Vogel HJ. Evolving genes and proteins. Science American Association for the Advancement of Science; 1965. p. 68–71.

  86. 86.

    Dayhoff MO. Atlas of Protein Sequence And Structure. Silver Spring, MD, USA: National Biomedical Research Foundation; 1972. p. 89–100.

  87. 87.

    Dufresne A, Garczarek L, Partensky F. Accelerated evolution associated with genome reduction in a free-living prokaryote. Genome Biol. 2005;6:R14.

    PubMed  Article  Google Scholar 

  88. 88.

    Marais GAB, Calteau A, Tenaillon O. Mutation rate and genome reduction in endosymbiotic and free-living bacteria. Genetica. 2008;134:205–10.

    PubMed  Article  Google Scholar 

  89. 89.

    Gu J, Wang X, Ma X, Sun Y, Xiao X, Luo H. Unexpectedly high mutation rate of a deep-sea hyperthermophilic anaerobic archaeon. ISME J. 2021;15:1862–9.

  90. 90.

    Luo H, Friedman R, Tang J, Hughes AL. Genome reduction by deletion of paralogs in the marine cyanobacterium Prochlorococcus. Mol Biol Evol. 2011;28:2751–60.

    CAS  PubMed  Article  Google Scholar 

Download references

Acknowledgements

This research was funded by the National Science Foundation of China (41776129), the Hong Kong Research Grants Council General Research Fund (14163917), the Hong Kong Research Grants Council Area of Excellence Scheme (AoE/M-403/16), and the Direct Grant of CUHK (4053257 & 3132809). The research was also supported by a Louisiana Board of Regents grant (LEQSF(2014-17)-RD-A-06) and a Simons Early Career Investigator in Marine Microbial Ecology and Evolution Award to JCT.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Haiwei Luo.

Ethics declarations

Conflict of interest

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Feng, X., Chu, X., Qian, Y. et al. Mechanisms driving genome reduction of a novel Roseobacter lineage. ISME J (2021). https://doi.org/10.1038/s41396-021-01036-3

Download citation

Search

Quick links