1887

Abstract

Symbiotic microbes from the genus Megaira' () are known to be common associates of algae and ciliates. However, genomic resources for these bacteria are scarce, limiting our understanding of their diversity and biology. We therefore utilize Sequence Read Archive and metagenomic assemblies to explore the diversity of this genus. We successfully extract four draft '. Megaira' genomes including one complete scaffold for a '. Megaira and identify an additional 14 draft genomes from uncategorized environmental metagenome-assembled genomes. We use this information to resolve the phylogeny for the hyper-diverse '. Megaira', with hosts broadly spanning ciliates, and micro- and macro-algae, and find that the current single genus designation '. Megaira' significantly underestimates their diversity. We also evaluate the metabolic potential and diversity of . Megaira' from this new genomic data and find no clear evidence of nutritional symbiosis. In contrast, we hypothesize a potential for defensive symbiosis in . Megaira. Intriguingly, one symbiont genome revealed a proliferation of ORFs with ankyrin, tetratricopeptide and leucine-rich repeats such as those observed in the genus where they are considered important for host–symbiont protein–protein interactions. Onward research should investigate the phenotypic interactions between . Megaira and their various potential hosts, including the economically important , and target acquisition of genomic information to reflect the diversity of this massively variable group.

Funding
This study was supported by the:
  • Natural Environment Research Council (Award NE/L002450/1)
    • Principle Award Recipient: HelenRebecca Davison
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License. This article was made open access via a Publish and Read agreement between the Microbiology Society and the corresponding author’s institution.
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2023-03-10
2024-05-04
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References

  1. Helen D, Greg H, Stefanos S. Candidatus Megaira’ are diverse symbionts of algae and ciliates with the potential for defensive symbiosis. Figshare 2022 [View Article]
    [Google Scholar]
  2. Hackstein JHP, Vogels GD. Endosymbiotic interactions in anaerobic protozoa. Antonie van Leeuwenhoek 1997; 71:151–158 [View Article] [PubMed]
    [Google Scholar]
  3. Watanabe K, Nakao R, Fujishima M, Tachibana M, Shimizu T et al. Ciliate Paramecium is a natural reservoir of Legionella pneumophila. Nature Publishing Group 2016; 6:24322 [View Article]
    [Google Scholar]
  4. Lanzoni O, Fokin SI, Lebedeva N, Migunova A, Petroni G et al. Rare freshwater ciliate Paramecium chlorelligerum Kahl, 1935 and its macronuclear symbiotic bacterium “Candidatus Holospora parva.”. PLoS One 2016; 11:e0167928 [View Article] [PubMed]
    [Google Scholar]
  5. Castelli M, Lanzoni O, Nardi T, Lometto S, Modeo L et al. Candidatus Sarmatiella mevalonica’ endosymbiont of the ciliate Paramecium provides insights on evolutionary plasticity among Rickettsiales. Environ Microbiol 20211462–2920
    [Google Scholar]
  6. Castelli M, Sabaneyeva E, Lanzoni O, Lebedeva N, Floriano AM et al. Deianiraea, an extracellular bacterium associated with the ciliate Paramecium, suggests an alternative scenario for the evolution of Rickettsiales. ISME J 2019; 13:2280–2294 [View Article] [PubMed]
    [Google Scholar]
  7. Vannini C, Ferrantini F, Verni F, Petroni G. A new obligate bacterial symbiont colonizing the ciliate Euplotes in brackish and freshwater: ‘Candidatus Protistobacter heckmanni. Aquat Microb Ecol 2013; 70:233–243 [View Article]
    [Google Scholar]
  8. Nozaki H, Kuroiwa H, Mita T, Kuroiwa T. Pleodorina japonica sp. nov. (Volvocales, Chlorophyta) with bacteria-like endosymbionts. Phycologia 1989; 28:252–267
    [Google Scholar]
  9. Kawafune K, Hongoh Y, Hamaji T, Sakamoto T, Kurata T et al. Two different rickettsial bacteria invading Volvox carteri. PLoS One 2015; 10:e0116192 [View Article] [PubMed]
    [Google Scholar]
  10. Sonneborn TM. Gene and cytoplasm: i. the determination and inheritance of the killer character in variety 4 of Paramecium aurelia. Proc Natl Acad Sci 1943; 29:329–338 [View Article]
    [Google Scholar]
  11. Schrallhammer M, Castelli M, Petroni G. Phylogenetic relationships among endosymbiotic R-body producer: bacteria providing their host the killer trait. Syst Appl Microbiol 2018; 41:213–220 [View Article] [PubMed]
    [Google Scholar]
  12. Duncan AB, Fellous S, Accot R, Alart M, Chantung Sobandi K et al. Parasite-mediated protection against osmotic stress for Paramecium caudatum infected by holospora undulata is host genotype specific. FEMS Microbiol Ecol 2010; 74:353–360 [View Article] [PubMed]
    [Google Scholar]
  13. Du Y, Maslov DA, Chang KP. Monophyletic origin of beta-division proteobacterial endosymbionts and their coevolution with insect trypanosomatid protozoa Blastocrithidia culicis and Crithidia spp. Proc Natl Acad Sci 1994; 91:8437–8441 [View Article]
    [Google Scholar]
  14. van Bruggen JJA, Stumm CK, Vogels GD. Symbiosis of methanogenic bacteria and sapropelic protozoa. Arch Microbiol 1983; 136:89–95 [View Article]
    [Google Scholar]
  15. van Hoek AH, van Alen TA, Sprakel VS, Leunissen JA, Brigge T et al. Multiple acquisition of methanogenic archaeal symbionts by anaerobic ciliates. Mol Biol Evol 2000; 17:251–258 [View Article] [PubMed]
    [Google Scholar]
  16. Penard E. Faune rhizopodique du bassin du Léman Genève: H. Kündig; 1902 [View Article]
    [Google Scholar]
  17. Kochert G, Olson LW. Endosymbiotic bacteria in Volvox carteri. Trans Am Microscop Soc 1970; 89:475 [View Article]
    [Google Scholar]
  18. Pilgrim J, Thongprem P, Davison HR, Siozios S, Baylis M et al. Torix Rickettsia are widespread in arthropods and reflect a neglected symbiosis. Gigascience 2021; 10:1–19 [View Article] [PubMed]
    [Google Scholar]
  19. Weinert LA, Werren JH, Aebi A, Stone GN, Jiggins FM. Evolution and diversity of Rickettsia bacteria. BMC Biol 2009; 7:6 [View Article] [PubMed]
    [Google Scholar]
  20. Lanzoni O, Sabaneyeva E, Modeo L, Castelli M, Lebedeva N et al. Diversity and environmental distribution of the cosmopolitan endosymbiont “Candidatus Megaira.”. Sci Rep 2019; 9:1179 [View Article] [PubMed]
    [Google Scholar]
  21. Schrallhammer M, Ferrantini F, Vannini C, Galati S, Schweikert M et al. CandidatusMegaira polyxenophila’ gen. nov., sp. nov.: considerations on evolutionary history, host range and shift of early divergent Rickettsiae. PLoS One 2013; 8:e72581
    [Google Scholar]
  22. Schulz F, Martijn J, Wascher F, Lagkouvardos I, Kostanjšek R et al. A Rickettsiales symbiont of amoebae with ancient features. Environ Microbiol 2016; 18:2326–2342 [View Article] [PubMed]
    [Google Scholar]
  23. Weinert LA, Araujo-Jnr EV, Ahmed MZ, Welch JJ. The incidence of bacterial endosymbionts in terrestrial arthropods. Proc Royal Soc B Biol Sci 2015; 282:20150249 [View Article]
    [Google Scholar]
  24. Sabaneyeva E, Castelli M, Szokoli F, Benken K, Lebedeva N et al. Host and symbiont intraspecific variability: the case of Paramecium calkinsi and “Candidatus Trichorickettsia mobilis.”. Eur J Protistol 2018; 62:79–94 [View Article] [PubMed]
    [Google Scholar]
  25. Stouthamer R, Breeuwer JAJ, Hurst GDD. Wolbachia pipientis: microbial manipulator of arthropod reproduction. Annu Rev Microbiol 1999; 53:71–102 [View Article] [PubMed]
    [Google Scholar]
  26. Charlat S, Hurst GDD, Merçot H. Evolutionary consequences of Wolbachia infections. Trends Genetics 2003; 19:217–223 [View Article]
    [Google Scholar]
  27. Duron O, Bouchon D, Boutin S, Bellamy L, Zhou L et al. The diversity of reproductive parasites among arthropods: Wolbachia do not walk alone. BMC Biol 2008; 6:27 [View Article] [PubMed]
    [Google Scholar]
  28. Werren JH, Hurst GD, Zhang W, Breeuwer JA, Stouthamer R et al. Rickettsial relative associated with male killing in the ladybird beetle (Adalia bipunctata). J Bacteriol 1994; 176:388–394 [View Article] [PubMed]
    [Google Scholar]
  29. Brumin M, Kontsedalov S, Ghanim M. Rickettsia influences thermotolerance in the whitefly Bemisia tabaci B biotype. Insect Sci 2011; 18:57–66 [View Article]
    [Google Scholar]
  30. Hendry TA, Hunter MS, Baltrus DA. The facultative symbiont Rickettsia protects an invasive whitefly against entomopathogenic Pseudomonas syringae strains. Appl Environ Microbiol 2014; 80:7161–7168 [View Article] [PubMed]
    [Google Scholar]
  31. Pasqualetti C, Szokoli F, Rindi L, Petroni G, Schrallhammer M. The obligate symbiont “Candidatus Megaira polyxenophila” has variable effects on the growth of different host species. Front Microbiol 2020; 11:1425 [View Article] [PubMed]
    [Google Scholar]
  32. Davison HR, Pilgrim J, Wybouw N, Parker J, Pirro S et al. Genomic diversity across the Rickettsia and “Candidatus Megaira” genera and proposal of genus status for the Torix group. Nat Commun 2022; 13:2630 [View Article] [PubMed]
    [Google Scholar]
  33. Sangwan N, Xia F, Gilbert JA. Recovering complete and draft population genomes from metagenome datasets. Microbiome 2016; 4:8 [View Article] [PubMed]
    [Google Scholar]
  34. Gruber-Vodicka HR, Seah BKB, Pruesse E. phyloFlash: rapid small-subunit rRNA profiling and targeted assembly from metagenomes. mSystems 2020; 5:e00920-20 [View Article] [PubMed]
    [Google Scholar]
  35. 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]
  36. Li H. Minimap2: pairwise alignment for nucleotide sequences. Bioinformatics 2018; 34:3094–3100 [View Article] [PubMed]
    [Google Scholar]
  37. Kang DD, Li F, Kirton E, Thomas A, Egan R et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 2019; 7:e7359 [View Article] [PubMed]
    [Google Scholar]
  38. 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]
  39. Chaumeil P-A, Mussig AJ, Hugenholtz P, Parks DH. GTDB-Tk: a toolkit to classify genomes with the genome taxonomy database. Bioinformatics 2020; 36:1925–1927 [View Article]
    [Google Scholar]
  40. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nature Methods 2012; 9:357–359 [View Article]
    [Google Scholar]
  41. Sahlin K, Vezzi F, Nystedt B, Lundeberg J, Arvestad L. BESST--efficient scaffolding of large fragmented assemblies. BMC Bioinformatics 2014; 15:281 [View Article] [PubMed]
    [Google Scholar]
  42. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J et al. BLAST+: architecture and applications. BMC Bioinformatics 2009; 10:421 [View Article] [PubMed]
    [Google Scholar]
  43. Eren AM, Kiefl E, Shaiber A, Veseli I, Miller SE et al. Community-led, integrated, reproducible multi-omics with anvi’o. Nat Microbiol 2021; 6:3–6 [View Article] [PubMed]
    [Google Scholar]
  44. Rodriguez-R LM, Konstantinidis KT. The enveomics collection: a toolbox for specialized analyses of microbial genomes and metagenomes. Epub ahead of print 27 March 2016 [View Article]
    [Google Scholar]
  45. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M et al. Versatile and open software for comparing large genomes. Genome Biol 2004; 5:R12 [View Article] [PubMed]
    [Google Scholar]
  46. Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD et al. IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol Biol Evol 2020; 37:1530–1534 [View Article] [PubMed]
    [Google Scholar]
  47. Kalyaanamoorthy S, Minh BQ, Wong TKF, von Haeseler A, Jermiin LS. ModelFinder: fast model selection for accurate phylogenetic estimates. Nat Methods 2017; 14:587–589 [View Article] [PubMed]
    [Google Scholar]
  48. Hoang DT, Chernomor O, von Haeseler A, Minh BQ, Vinh LS. UFBoot2: improving the ultrafast bootstrap approximation. Mol Biol Evol 2018; 35:518–522 [View Article] [PubMed]
    [Google Scholar]
  49. Guindon S, Dufayard J-F, Lefort V, Anisimova M, Hordijk W et al. New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst Biol 2010; 59:307–321 [View Article] [PubMed]
    [Google Scholar]
  50. Lartillot N, Rodrigue N, Stubbs D, Richer J. PhyloBayes MPI: phylogenetic reconstruction with infinite mixtures of profiles in a parallel environment. Syst Biol 2013; 62:611–615 [View Article] [PubMed]
    [Google Scholar]
  51. Eddy SR. HMMER 3.2.1; 2018 http://hmmer.org/
  52. Rossum G van, Drake FL. Python 3 Reference Manual Scotts Valley, CA: CreateSpace; 2009
    [Google Scholar]
  53. Waskom M. Seaborn development team. In Mwaskom/Seaborn 2020 Epub ahead of print [View Article]
    [Google Scholar]
  54. Krassowski M, Arts M. CyrilLagger. In ComplexUpset 2020 Epub ahead of print [View Article]
    [Google Scholar]
  55. R Core Team R: a language and environment for statistical computing; 2020 https://www.r-project.org/
  56. Blin K, Shaw S, Kloosterman AM, Charlop-Powers Z, van Wezel GP et al. antiSMASH 6.0: improving cluster detection and comparison capabilities. Nucleic Acids Res 2021; 49:W29–W35 [View Article] [PubMed]
    [Google Scholar]
  57. Gilchrist CLM, Chooi Y-H, Robinson P. clinker & clustermap.js: automatic generation of gene cluster comparison figures. Bioinformatics 2021; 37:2473–2475 [View Article] [PubMed]
    [Google Scholar]
  58. Jones P, Binns D, Chang H-Y, Fraser M, Li W et al. InterProScan 5: genome-scale protein function classification. Bioinformatics 2014; 30:1236–1240
    [Google Scholar]
  59. Pilgrim J, Ander M, Garros C, Baylis M, Hurst GDD et al. Torix group Rickettsia are widespread in Culicoides biting midges (Diptera: Ceratopogonidae), reach high frequency and carry unique genomic features. Environ Microbiol 2017; 19:4238–4255
    [Google Scholar]
  60. Goh KM, Shahar S, Chan K-G, Chong CS, Amran SI et al. Current status and potential applications of underexplored prokaryotes. Microorganisms 2019; 7:468 [View Article] [PubMed]
    [Google Scholar]
  61. Ortiz M, Leung PM, Shelley G, Jirapanjawat T, Nauer PA et al. Multiple energy sources and metabolic strategies sustain microbial diversity in Antarctic desert soils. Proc Natl Acad Sci U S A 2021; 118:e2025322118 Epub ahead of print 9 November 2021 [View Article]
    [Google Scholar]
  62. Kantor RS, Miller SE, Nelson KL. The water microbiome through a pilot scale advanced treatment facility for direct potable reuse. Front Microbiol 2019; 10:993 [View Article] [PubMed]
    [Google Scholar]
  63. Vosloo S, Huo L, Anderson CL, Dai Z, Sevillano M et al. Evaluating de Novo assembly and binning strategies for time series drinking water metagenomes. Microbiol Spectr 2021; 9:e0143421 [View Article] [PubMed]
    [Google Scholar]
  64. Tully BJ, Wheat CG, Glazer BT, Huber JA. A dynamic microbial community with high functional redundancy inhabits the cold, oxic subseafloor aquifer. ISME J 2018; 12:1–16 [View Article] [PubMed]
    [Google Scholar]
  65. Rodriguez-R LM, Tsementzi D, Luo C, Konstantinidis KT. Iterative subtractive binning of freshwater chronoseries metagenomes identifies over 400 novel species and their ecologic preferences. Environ Microbiol 2020; 22:3394–3412 [View Article] [PubMed]
    [Google Scholar]
  66. McDaniel EA, Wever R, Oyserman BO, Noguera DR, McMahon KD. Genome-Resolved Metagenomics of a Photosynthetic Bioreactor Performing Biological Nutrient Removal. Microbiol Resour Announc 2021; 10:e00244-21 [View Article] [PubMed]
    [Google Scholar]
  67. Tran PQ, Bachand SC, McIntyre PB, Kraemer BM, Vadeboncoeur Y et al. Depth-discrete metagenomics reveals the roles of microbes in biogeochemical cycling in the tropical freshwater Lake Tanganyika. ISME J 2021; 15:1971–1986 [View Article] [PubMed]
    [Google Scholar]
  68. Chen Z, Zhong X, Zheng M, Liu W-S, Fei Y et al. Indicator species drive the key ecological functions of microbiota in a river impacted by acid mine drainage generated by rare earth elements mining in South China. Environ Microbiol 2022; 24:919–937 [View Article] [PubMed]
    [Google Scholar]
  69. Yancey CE, Smith DJ, Den Uyl PA, Mohamed OG, Yu F et al. Metagenomic and metatranscriptomic insights into population diversity of Microcystis blooms: spatial and temporal dynamics of mcy genotypes, including a partial operon that can be abundant and expressed. Appl Environ Microbiol 2022; 88:e0246421 [View Article] [PubMed]
    [Google Scholar]
  70. Schneider D, Aßmann N, Wicke D, Poehlein A, Daniel R. Metagenomes of wastewater at different treatment stages in central Germany. Microbiol Resour Announc 2020; 9:e00201-20 [View Article] [PubMed]
    [Google Scholar]
  71. McDaniel EA, Wever R, Oyserman BO, Noguera DR, McMahon KD. Genome-resolved metagenomics of a photosynthetic bioreactor performing biological nutrient removal. Microbiol Resour Announc 2021; 10:e00244-21 [View Article] [PubMed]
    [Google Scholar]
  72. Yuan C, Lei J, Cole J, Sun Y. Reconstructing 16S rRNA genes in metagenomic data. Bioinformatics 2015; 31:i35–43 [View Article] [PubMed]
    [Google Scholar]
  73. Tandon P, Jin Q, Huang L. A promising approach to enhance microalgae productivity by exogenous supply of vitamins. Microb Cell Fact 2017; 16:219 [View Article] [PubMed]
    [Google Scholar]
  74. Karimi E, Keller-Costa T, Slaby BM, Cox CJ, da Rocha UN et al. Genomic blueprints of sponge-prokaryote symbiosis are shared by low abundant and cultivatable Alphaproteobacteria. Sci Rep 2019; 9:1999 [View Article] [PubMed]
    [Google Scholar]
  75. Wei G, Jia Q, Chen X, Köllner TG, Bhattacharya D et al. Terpene biosynthesis in red algae is catalyzed by microbial type but not typical plant terpene synthases. Plant Physiol 2019; 179:382–390 [View Article] [PubMed]
    [Google Scholar]
  76. French KE. Engineering mycorrhizal symbioses to alter plant metabolism and improve crop health. Front Microbiol 2017; 8:1403 [View Article] [PubMed]
    [Google Scholar]
  77. Ma Y, Pan F, McNeil M. Formation of dTDP-rhamnose is essential for growth of mycobacteria. J Bacteriol 2002; 184:3392–3395 [View Article] [PubMed]
    [Google Scholar]
  78. Jofré E, Lagares A, Mori G. Disruption of dTDP-rhamnose biosynthesis modifies lipopolysaccharide core, exopolysaccharide production, and root colonization in Azospirillum brasilense. FEMS Microbiol Lett 2004; 231:267–275 [View Article] [PubMed]
    [Google Scholar]
  79. van der Beek SL, Zorzoli A, Çanak E, Chapman RN, Lucas K et al. Streptococcal dTDP-L-rhamnose biosynthesis enzymes: functional characterization and lead compound identification. Mol Microbiol 2019; 111:951–964 [View Article] [PubMed]
    [Google Scholar]
  80. Massey JH, Newton ILG. Diversity and function of arthropod endosymbiont toxins. Trends Microbiol 2022; 30:185–198 [View Article] [PubMed]
    [Google Scholar]
  81. Wenski SL, Thiengmag S, Helfrich EJN. Complex peptide natural products: biosynthetic principles, challenges and opportunities for pathway engineering. Synth Syst Biotechnol 2022; 7:631–647 [View Article] [PubMed]
    [Google Scholar]
  82. Hegemann JD, Zimmermann M, Xie X, Marahiel MA. Lasso peptides: an intriguing class of bacterial natural products. Acc Chem Res 2015; 48:1909–1919 [View Article] [PubMed]
    [Google Scholar]
  83. Todorova AK, Juettner F, Linden A, Pluess T, von Philipsborn W. Nostocyclamide: a new macrocyclic, thiazole-containing allelochemical from Nostoc sp. 31 (Cyanobacteria). J Org Chem 1995; 60:7891–7895 [View Article]
    [Google Scholar]
  84. Siozios S, Ioannidis P, Klasson L, Andersson SGE, Braig HR et al. The diversity and evolution of Wolbachia ankyrin repeat domain genes. PLoS One 2013; 8:e55390 [View Article] [PubMed]
    [Google Scholar]
  85. Rice DW, Sheehan KB, Newton ILG. Large-scale identification of Wolbachia pipientis effectors. Genome Biol Evol 2017; 9:1925–1937 [View Article] [PubMed]
    [Google Scholar]
  86. Vannini C, Boscaro V, Ferrantini F, Benken KA, Mironov TI et al. Flagellar movement in two bacteria of the family Rickettsiaceae: a re-evaluation of motility in an evolutionary perspective. PLoS One 2014; 9:e87718 [View Article] [PubMed]
    [Google Scholar]
  87. Martijn J, Schulz F, Zaremba-Niedzwiedzka K, Viklund J, Stepanauskas R et al. Single-cell genomics of a rare environmental alphaproteobacterium provides unique insights into Rickettsiaceae evolution. ISME J 2015; 9:2373–2385 [View Article] [PubMed]
    [Google Scholar]
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