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Volume 6, Issue 7

Simulating the evolutionary trajectories of metabolic pathways for insect symbionts in the genus Open Access

Abstract

Insect–bacterial symbioses are ubiquitous, but there is still much to uncover about how these relationships establish, persist and evolve. The tsetse endosymbiont displays intriguing metabolic adaptations to its microenvironment, but the process by which this relationship evolved remains to be elucidated. The recent chance discovery of the free-living species of the genus , , provides a serendipitous starting point from which to investigate the evolution of this symbiosis. Here, we present a flux balance model for and empirically verify its predictions. Metabolic modelling is used in combination with a multi-objective evolutionary algorithm to explore the trajectories that may have undertaken from this starting point after becoming internalized. The order in which key genes are lost is shown to influence the evolved populations, providing possible targets for future genetic manipulation. This method provides a detailed perspective on possible evolutionary trajectories for in this fundamental process of evolutionary and ecological change.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): evolution , evolutionary algorithm , flux balance analysis , Sodalis and symbiosis
Funding
This study was supported by the:
  • Wellcome Trust (Award WT095024MA)
    • Principle Award Recipient: Stephen Thorpe
  • Biotechnology and Biological Sciences Research Council (Award BB/M011151/1)
    • Principle Award Recipient: Rebecca J Hall
© 2020 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution NonCommercial 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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2020-06-16
2024-04-24
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References

  1. Wilcox JL, Dunbar HE, Wolfinger RD, Moran NA. Consequences of reductive evolution for gene expression in an obligate endosymbiont. Mol Microbiol 2003; 48:1491–1500 [View Article]
     [Google Scholar]
  2. Dunbar HE, Wilson ACC, Ferguson NR, Moran NA. Aphid thermal tolerance is governed by a point mutation in bacterial symbionts. PLoS Biol 2007; 5:e96 [View Article]
     [Google Scholar]
  3. Oliver KM, Russell JA, Moran NA, Hunter MS. Facultative bacterial symbionts in aphids confer resistance to parasitic wasps. Proc Natl Acad Sci USA 2003; 100:1803–1807 [View Article]
     [Google Scholar]
  4. Nakabachi A, Ueoka R, Oshima K, Teta R, Mangoni A et al. Defensive bacteriome symbiont with a drastically reduced genome. Curr Biol 2013; 23:1478–1484 [View Article][PubMed]
     [Google Scholar]
  5. Aksoy S. Wigglesworthia gen. nov. and Wigglesworthia glossinidia sp. nov., taxa consisting of the mycetocyte-associated, primary endosymbionts of tsetse flies. Int J Syst Bacteriol 1995; 45:848–851 [View Article][PubMed]
     [Google Scholar]
  6. Shigenobu S, Watanabe H, Hattori M, Sakaki Y, Ishikawa H. Genome sequence of the endocellular bacterial symbiont of aphids Buchnera sp. APS. Nature 2000; 407:81–86 [View Article]
     [Google Scholar]
  7. Thomas GH, Zucker J, Macdonald SJ, Sorokin A, Goryanin I et al. A fragile metabolic network adapted for cooperation in the symbiotic bacterium Buchnera aphidicola . BMC Syst Biol 2009; 3:24 [View Article]
     [Google Scholar]
  8. Snyder AK, Rio RVM. "Wigglesworthia morsitans" folate (vitamin B9) biosynthesis contributes to tsetse host fitness. Appl Environ Microbiol 2015; 81:5375–5386 [View Article][PubMed]
     [Google Scholar]
  9. Hrusa G, Farmer W, Weiss BL, Applebaum T, Roma JS et al. TonB-dependent heme iron acquisition in the tsetse fly symbiont Sodalis glossinidius . Appl Environ Microbiol 2015; 81:2900–2909 [View Article]
     [Google Scholar]
  10. Manzano-Marín A, Oceguera-Figueroa A, Latorre A, Jiménez-García LF, Moya A. Solving a bloody mess: B-vitamin independent metabolic convergence among gammaproteobacterial obligate endosymbionts from blood-feeding arthropods and the leech Haementeria officinalis . Genome Biol Evol 2015; 7:2871–2884 [View Article]
     [Google Scholar]
  11. McCutcheon JP, Moran NA. Parallel genomic evolution and metabolic interdependence in an ancient symbiosis. Proc Natl Acad Sci USA 2007; 104:19392–19397 [View Article]
     [Google Scholar]
  12. McCutcheon JP, McDonald BR, Moran NA. Convergent evolution of metabolic roles in bacterial co-symbionts of insects. Proc Natl Acad Sci USA 2009; 106:15394–15399 [View Article]
     [Google Scholar]
  13. McCutcheon JP, McDonald BR, Moran NA. Origin of an alternative genetic code in the extremely small and GC–rich genome of a bacterial symbiont. PLoS Genet 2009; 5:e1000565 [View Article]
     [Google Scholar]
  14. Wilson ACC, Ashton PD, Calevro F, Charles H, Colella S et al. Genomic insight into the amino acid relations of the pea aphid, Acyrthosiphon pisum, with its symbiotic bacterium Buchnera aphidicola . Insect Mol Biol 2010; 19:249–258 [View Article]
     [Google Scholar]
  15. McCutcheon JP, von Dohlen CD. An interdependent metabolic patchwork in the nested symbiosis of mealybugs. Curr Biol 2011; 21:1366–1372 [View Article][PubMed]
     [Google Scholar]
  16. Rio RVM, Lefevre C, Heddi A, Aksoy S. Comparative genomics of insect-symbiotic bacteria: influence of host environment on microbial genome composition. Appl Environ Microbiol 2003; 69:6825–6832 [View Article][PubMed]
     [Google Scholar]
  17. Michalkova V, Benoit JB, Weiss BL, Attardo GM, Aksoy S. Vitamin B6 generated by obligate symbionts is critical for maintaining proline homeostasis and fecundity in tsetse flies. Appl Environ Microbiol 2014; 80:5844–5853 [View Article]
     [Google Scholar]
  18. Baumann P, Baumann L, Lai C-Y, Rouhbakhsh D, Moran NA et al. Genetics, physiology, and evolutionary relationships of the genus Buchnera: intracellular symbionts of aphids. Annu Rev Microbiol 1995; 49:55–94 [View Article]
     [Google Scholar]
  19. Akman Gündüz E, Douglas AE. Symbiotic bacteria enable insect to use a nutritionally inadequate diet. Proc. R. Soc. B. 2009; 276:987–991 [View Article]
     [Google Scholar]
  20. International Aphid Genomics Consortium Genome sequence of the pea aphid Acyrthosiphon pisum . PLoS Biol 2010; 8:e1000313 [View Article][PubMed]
     [Google Scholar]
  21. Wu M, Sun LV, Vamathevan J, Riegler M, Deboy R et al. Phylogenomics of the reproductive parasite Wolbachia pipientis wMel: a streamlined genome overrun by mobile genetic elements. PLoS Biol 2004; 2:e69 [View Article]
     [Google Scholar]
  22. Pérez-Brocal V, Gil R, Ramos S, Lamelas A, Postigo M et al. A small microbial genome: the end of a long symbiotic relationship?. Science 2006; 314:312–313 [View Article]
     [Google Scholar]
  23. Moran NA, McCutcheon JP, Nakabachi A. Genomics and evolution of heritable bacterial symbionts. Annu Rev Genet 2008; 42:165–190 [View Article]
     [Google Scholar]
  24. Akman L, Yamashita A, Watanabe H, Oshima K, Shiba T et al. Genome sequence of the endocellular obligate symbiont of tsetse flies, Wigglesworthia glossinidia . Nat Genet 2002; 32:402–407 [View Article]
     [Google Scholar]
  25. Dale C, Maudlin I. Sodalis gen. nov. and Sodalis glossindius sp. nov., a microaerophilic secondary endosymbiont of the tsetse fly Glossina morsitans morsitans . Int J Syst Bacteriol 1999; 49:267–275 [View Article][PubMed]
     [Google Scholar]
  26. Edwards JS, Covert M, Palsson B. Metabolic modelling of microbes: the flux-balance approach. Environ Microbiol 2002; 4:133–140 [View Article]
     [Google Scholar]
  27. Kauffman KJ, Prakash P, Edwards JS. Advances in flux balance analysis. Curr Opin Biotechnol 2003; 14:491–496 [View Article]
     [Google Scholar]
  28. Lewis NE, Nagarajan H, Palsson BO. Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods. Nat Rev Microbiol 2012; 10:291–305 [View Article]
     [Google Scholar]
  29. Orth JD, Thiele I, Palsson BØ. What is flux balance analysis?. Nat Biotechnol 2010; 28:245–248 [View Article]
     [Google Scholar]
  30. Macdonald SJ, Lin GG, Russell CW, Thomas GH, Douglas AE. The central role of the host cell in symbiotic nitrogen metabolism. Proc. R. Soc. B 2012; 279:2965–2973 [View Article]
     [Google Scholar]
  31. Macdonald SJ, Thomas GH, Douglas AE. Genetic and metabolic determinants of nutritional phenotype in an insect-bacterial symbiosis. Mol Ecol 2011; 20:2073–2084 [View Article]
     [Google Scholar]
  32. Belda E, Silva FJ, Peretó J, Moya A. Metabolic networks of Sodalis glossinidius: a systems biology approach to reductive evolution. PLoS One 2012; 7:e30652 [View Article]
     [Google Scholar]
  33. Hall RJ, Flanagan LA, Bottery MJ, Springthorpe V, Thorpe S et al. A tale of three species: adaptation of Sodalis glossinidius to tsetse biology, Wigglesworthia metabolism, and host diet. mBio 2019; 10:e02106-18 [View Article][PubMed]
     [Google Scholar]
  34. Ankrah NYD, Luan J, Douglas AE. Cooperative metabolism in a three-partner insect-bacterial symbiosis revealed by metabolic modeling. J Bacteriol 2017; 199:e00872-16 [View Article]
     [Google Scholar]
  35. González-Domenech C, Belda E, Patiño-Navarrete R, Moya A, Peretó J et al. Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches. BMC Microbiol 2012; 12:S5 [View Article]
     [Google Scholar]
  36. Sørensen MES, Cameron DD, Brockhurst MA, Wood AJ. Metabolic constraints for a novel symbiosis. R Soc Open Sci 2016; 3:150708 [View Article][PubMed]
     [Google Scholar]
  37. Shastri AA, Morgan JA. Flux balance analysis of photoautotrophic metabolism. Biotechnol Prog 2005; 21:1617–1626 [View Article]
     [Google Scholar]
  38. Nogales J, Gudmundsson S, Knight EM, Palsson BO, Thiele I. Detailing the optimality of photosynthesis in cyanobacteria through systems biology analysis. Proc Natl Acad Sci USA 2012; 109:2678–2683 [View Article]
     [Google Scholar]
  39. Knoop H, Zilliges Y, Lockau W, Steuer R. The metabolic network of Synechocystis sp. PCC 6803: systemic properties of autotrophic growth. Plant Physiol 2010; 154:410–422 [View Article]
     [Google Scholar]
  40. Knoop H, Gründel M, Zilliges Y, Lehmann R, Hoffmann S et al. Flux balance analysis of cyanobacterial metabolism: the metabolic network of Synechocystis sp. PCC 6803. PLoS Comput Biol 2013; 9:e1003081 [View Article]
     [Google Scholar]
  41. Toh H et al. Massive genome erosion and functional adaptations provide insights into the symbiotic lifestyle of Sodalis glossinidius in the tsetse host. Genome Res 2006; 16:149–156 [View Article]
     [Google Scholar]
  42. Goodhead I, Blow F, Brownridge P, Hughes M, Kenny J et al. Large-scale and significant expression from pseudogenes in Sodalis glossinidius – a facultative bacterial endosymbiont. Microb Genom 2020; 6:e000285 [View Article][PubMed]
     [Google Scholar]
  43. Covert MW, Palsson BØ. Transcriptional regulation in constraints-based metabolic models of Escherichia coli . J Biol Chem 2002; 277:28058–28064 [View Article]
     [Google Scholar]
  44. Lee JM, Gianchandani EP, Papin JA. Flux balance analysis in the era of metabolomics. Brief Bioinform 2006; 7:140–150 [View Article]
     [Google Scholar]
  45. Covert MW, Palsson BO. Constraints-based models: regulation of gene expression reduces the steady-state solution space. J Theor Biol 2003; 221:309–325 [View Article]
     [Google Scholar]
  46. Covert MW, Schilling CH, Palsson B. Regulation of gene expression in flux balance models of metabolism. J Theor Biol 2001; 213:73–88 [View Article]
     [Google Scholar]
  47. Mahadevan R, Edwards JS, Doyle FJ. Dynamic flux balance analysis of diauxic growth in Escherichia coli . Biophys J 2002; 83:1331–1340 [View Article]
     [Google Scholar]
  48. Harcombe WR, Delaney NF, Leiby N, Klitgord N, Marx CJ. The ability of flux balance analysis to predict evolution of central metabolism scales with the initial distance to the optimum. PLoS Comput Biol 2013; 9:e1003091 [View Article]
     [Google Scholar]
  49. Pfeiffer T, Soyer OS, Bonhoeffer S. The evolution of connectivity in metabolic networks. PLoS Biol 2005; 3:e228 [View Article]
     [Google Scholar]
  50. Ponce-de-Leon M, Tamarit D, Calle-Espinosa J, Mori M, Latorre A et al. Determinism and contingency shape metabolic complementation in an endosymbiotic consortium. Front Microbiol 2017; 8:2290 [View Article]
     [Google Scholar]
  51. Edwards JS, Palsson B. Metabolic flux balance analysis and the in silico analysis of Escherichia coli K-12 gene deletions. BMC Bioinformatics 2000; 1:1 [View Article]
     [Google Scholar]
  52. Feist AM, Henry CS, Reed JL, Krummenacker M, Joyce AR et al. A genome‐scale metabolic reconstruction for Escherichia coli K‐12 MG1655 that accounts for 1260 ORFs and thermodynamic information. Mol Syst Biol 2007; 3:121 [View Article]
     [Google Scholar]
  53. Reed JL, Vo TD, Schilling CH, Palsson BO. An expanded genome-scale model of Escherichia coli K-12 (iJR904 GSM/GPR). Genome Biol 2003; 4:R54 [View Article]
     [Google Scholar]
  54. Orth JD, Conrad TM, Na J, Lerman JA, Nam H et al. A comprehensive genome‐scale reconstruction of Escherichia coli metabolism—2011. Mol Syst Biol 2011; 7:535 [View Article]
     [Google Scholar]
  55. Orth JD, Palsson B. Gap-filling analysis of the iJO1366 Escherichia coli metabolic network reconstruction for discovery of metabolic functions. BMC Syst Biol 2012; 6:30 [View Article]
     [Google Scholar]
  56. Pál C, Papp B, Lercher MJ, Csermely P, Oliver SG et al. Chance and necessity in the evolution of minimal metabolic networks. Nature 2006; 440:667–670 [View Article]
     [Google Scholar]
  57. Yizhak K, Tuller T, Papp B, Ruppin E. Metabolic modeling of endosymbiont genome reduction on a temporal scale. Mol Syst Biol 2011; 7:479 [View Article]
     [Google Scholar]
  58. McNally CP, Borenstein E. Metabolic model-based analysis of the emergence of bacterial cross-feeding via extensive gene loss. BMC Syst Biol 2018; 12:69 [View Article][PubMed]
     [Google Scholar]
  59. Hindré T, Knibbe C, Beslon G, Schneider D. New insights into bacterial adaptation through in vivo and in silico experimental evolution. Nat Rev Microbiol 2012; 10:352–365 [View Article][PubMed]
     [Google Scholar]
  60. Batut B, Parsons DP, Fischer S, Beslon G, Knibbe C. In silico experimental evolution: a tool to test evolutionary scenarios. BMC Bioinformatics 2013; 14:S11 [View Article]
     [Google Scholar]
  61. François P, Hakim V. Design of genetic networks with specified functions by evolution in silico. Proc Natl Acad Sci USA 2004; 101:580–585 [View Article]
     [Google Scholar]
  62. Budinich M, Bourdon J, Larhlimi A, Eveillard D. A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems. PLoS One 2017; 12:e0171744 [View Article][PubMed]
     [Google Scholar]
  63. Wang L, Maranas CD. MinGenome: an in silico top-down approach for the synthesis of minimized genomes. ACS Synth Biol 2018; 7:462–473 [View Article]
     [Google Scholar]
  64. Fong SS, Burgard AP, Herring CD, Knight EM, Blattner FR et al. In silico design and adaptive evolution of Escherichia coli for production of lactic acid. Biotechnol Bioeng 2005; 91:643–648 [View Article]
     [Google Scholar]
  65. Garcia S, Trinh CT. Comparison of multi-objective evolutionary algorithms to solve the modular cell design problem for novel biocatalysis. Processes 2019; 7:361 [View Article]
     [Google Scholar]
  66. Machado D, Herrgård MJ. Co-evolution of strain design methods based on flux balance and elementary mode analysis. Metab Eng Commun 2015; 2:85–92 [View Article]
     [Google Scholar]
  67. Clayton AL, Oakeson KF, Gutin M, Pontes A, Dunn DM et al. A novel human-infection-derived bacterium provides insights into the evolutionary origins of mutualistic insect–bacterial symbioses. PLoS Genet 2012; 8:e1002990 [View Article]
     [Google Scholar]
  68. Chari A, Oakeson KF, Enomoto S, Jackson DG, Fisher MA et al. Phenotypic characterization of Sodalis praecaptivus sp. nov., a close non-insect-associated member of the Sodalis-allied lineage of insect endosymbionts. Int J Syst Evol Microbiol 2015; 65:1400–1405 [View Article]
     [Google Scholar]
  69. WHO Control and Surveillance of African Trypanosomiasis: Report of a WHO Expert Committee (WHO Technical Report Series 881) Geneva: World Health Organization; 1998
     [Google Scholar]
  70. King ZA, Lu J, Dräger A, Miller P, Federowicz S et al. BiGG Models: a platform for integrating, standardizing and sharing genome-scale models. Nucleic Acids Res 2016; 44:D515–D522 [View Article]
     [Google Scholar]
  71. Kanehisa M, Goto S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res 2000; 28:27–30 [View Article]
     [Google Scholar]
  72. Kanehisa M, Sato Y, Furumichi M, Morishima K, Tanabe M. New approach for understanding genome variations in KEGG. Nucleic Acids Res 2019; 47:D590–D595 [View Article]
     [Google Scholar]
  73. Keseler IM, Mackie A, Santos-Zavaleta A, Billington R, Bonavides-Martínez C et al. The EcoCyc database: reflecting new knowledge about Escherichia coli K-12. Nucleic Acids Res 2017; 45:D543–D550 [View Article]
     [Google Scholar]
  74. Bateman A, Martin MJ, Orchard S, Magrane M, Alpi E et al. UniProt: a worldwide hub of protein knowledge. Nucleic Acids Res 2019; 47:D506–D515 [View Article][PubMed]
     [Google Scholar]
  75. Caspi R, Foerster H, Fulcher CA, Kaipa P, Krummenacker M et al. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res 2008; 36:D623–D631 [View Article][PubMed]
     [Google Scholar]
  76. Larkin MA, Blackshields G, Brown NP, Chenna R, McGettigan PA et al. Clustal W and Clustal X version 2.0. Bioinformatics 2007; 23:2947–2948 [View Article]
     [Google Scholar]
  77. Thiele I, Palsson BØ. A protocol for generating a high-quality genome-scale metabolic reconstruction. Nat Protoc 2010; 5:93–121 [View Article][PubMed]
     [Google Scholar]
  78. Ebrahim A, Lerman JA, Palsson BO, Hyduke DR. COBRApy: constraints-based reconstruction and analysis for python. BMC Syst Biol 2013; 7:74 [View Article]
     [Google Scholar]
  79. Deb K, Pratap A, Agarwal S, Meyarivan T. A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 2002; 6:182–197 [View Article]
     [Google Scholar]
  80. De Rainville F-M, Fortin F-A, Gardner M-A, Parizeau M, Gagné C. DEAP: a Python framework for evolutionary algorithms. In: Proceedings of the 14th International Conference on Genetic and Evolutionary Computation New York: Association for Computing Machinery; 2012 pp 85–92
     [Google Scholar]
  81. Moran NA. Accelerated evolution and Muller's rachet in endosymbiotic bacteria. Proc Natl Acad Sci USA 1996; 93:2873–2878 [View Article]
     [Google Scholar]
  82. Novakova E, Hypsa V. A new Sodalis lineage from bloodsucking fly Craterina melbae (Diptera, Hippoboscoidea) originated independently of the tsetse flies symbiont Sodalis glossinidius. FEMS Microbiol Lett 2007; 269:131–135 [View Article][PubMed]
     [Google Scholar]
  83. Chrudimský T, Husník F, Nováková E, Hypša V. Candidatus Sodalis melophagi sp. nov.: phylogenetically independent comparative model to the tsetse fly symbiont Sodalis glossinidius . PLoS One 2012; 7:e40354 [View Article]
     [Google Scholar]
  84. Boyd BM, Allen JM, Koga R, Fukatsu T, Sweet AD et al. Two bacterial genera, Sodalis and Rickettsia, associated with the seal louse Proechinophthirus fluctus (Phthiraptera: Anoplura). Appl Environ Microbiol 2016; 82:3185–3197 [View Article][PubMed]
     [Google Scholar]
  85. Oakeson KF, Gil R, Clayton AL, Dunn DM, von Niederhausern AC et al. Genome degeneration and adaptation in a nascent stage of symbiosis. Genome Biol Evol 2014; 6:76–93 [View Article]
     [Google Scholar]
  86. Szklarzewicz T, Kalandyk-Kołodziejczyk M, Michalik K, Jankowska W, Michalik A. Symbiotic microorganisms in Puto superbus (Leonardi, 1907) (Insecta, Hemiptera, Coccomorpha: Putoidae). Protoplasma 2018; 255:129–138 [View Article]
     [Google Scholar]
  87. Koga R, Bennett GM, Cryan JR, Moran NA. Evolutionary replacement of obligate symbionts in an ancient and diverse insect lineage. Environ Microbiol 2013; 15:2073–2081 [View Article]
     [Google Scholar]
  88. Koga R, Moran NA. Swapping symbionts in spittlebugs: evolutionary replacement of a reduced genome symbiont. Isme J 2014; 8:12371246 [View Article]
     [Google Scholar]
  89. Michalik A, Jankowska W, Kot M, Gołas A, Szklarzewicz T. Symbiosis in the green leafhopper, Cicadella viridis (Hemiptera, Cicadellidae). Association in statu nascendi?. Arthropod Struct Dev 2014; 43:579–587 [View Article]
     [Google Scholar]
  90. Kaiwa N, Hosokawa T, Kikuchi Y, Nikoh N, Meng XY et al. Primary gut symbiont and secondary, Sodalis-allied symbiont of the Scutellerid stinkbug Cantao ocellatus . Appl Environ Microbiol 2010; 76:3486–3494 [View Article]
     [Google Scholar]
  91. Hosokawa T, Kaiwa N, Matsuura Y, Kikuchi Y, Fukatsu T. Infection prevalence of Sodalis symbionts among stinkbugs. Zoological Lett 2015; 1:5 [View Article][PubMed]
     [Google Scholar]
  92. Snyder AK, Deberry JW, Runyen-Janecky L, Rio RVM. Nutrient provisioning facilitates homeostasis between tsetse fly (Diptera: Glossinidae) symbionts. Proc Biol Sci 2010; 277:2389–2397 [View Article][PubMed]
     [Google Scholar]
  93. Muller HJ. The relation of recombination to mutational advance. Mutat Res 1964; 106:2–9 [View Article][PubMed]
     [Google Scholar]
  94. Login FH, Balmand S, Vallier A, Vincent-Monégat C, Vigneron A et al. Antimicrobial peptides keep insect endosymbionts under control. Science 2011; 334:362–365 [View Article]
     [Google Scholar]
  95. Ankrah NYD, Chouaia B, Douglas AE. The cost of metabolic interactions in symbioses between insects and bacteria with reduced genomes. mBio 2018; 9:e01433-18 [View Article][PubMed]
     [Google Scholar]
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Simulating the evolutionary trajectories of metabolic pathways for insect symbionts in the genus Sodalis
M Gen 6, e000378 (2020); https://doi.org/10.1099/mgen.0.000378
/content/journal/mgen/10.1099/mgen.0.000378
/content/journal/mgen/10.1099/mgen.0.000378
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