1887

Abstract

serves as a model chemolithoautotrophic organism in extremely acidic environments, which has attracted much attention due to its unique metabolism and strong adaptability. However, little was known about the divergences along the evolutionary process based on whole genomes. Herein, we isolated six strains of from mining areas in China and Zambia, and used comparative genomics to investigate the intra-species divergences. The results indicated that diverged into three groups from a common ancestor, and the pan-genome is ‘open’. The ancestral reconstruction of indicated that genome sizes experienced a trend of increase in the very earliest days before a decreasing tendency during the evolutionary process, suggesting that both gene gain and gene loss played crucial roles in genome flexibility. Meanwhile, 23 single-copy orthologous groups (OGs) were under positive selection. The differences of rusticyanin (Rus) sequences (the key protein in the iron oxidation pathway) and type IV secretion system (T4SS) composition in the were both related to their group divergences, which contributed to their intraspecific diversity. This study improved our understanding of the divergent evolution and environmental adaptation of at the genome level in extreme conditions, which provided theoretical support for the survival mechanism of living creatures at the extreme.

Funding
This study was supported by the:
  • National Natural Science Foundation of China (Award 42007306)
    • Principle Award Recipient: LiyuanMa
  • National Natural Science Foundation of China (Award 42277193)
    • Principle Award Recipient: LiyuanMa
  • 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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2023-06-07
2024-04-27
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References

  1. Kadnikov VV, Ivasenko DA, Beletsky AV, Mardanov AV, Danilova EV et al. Effect of metal concentration on the microbial community in acid mine drainage of a polysulfide ore deposit. Microbiology 2016; 85:745–751 [View Article]
    [Google Scholar]
  2. Zhang X, Liu X, Li L, Wei G, Zhang D et al. Phylogeny, divergent evolution, and speciation of sulfur-oxidizing Acidithiobacillus populations. BMC Genomics 2019; 20:438 [View Article] [PubMed]
    [Google Scholar]
  3. González-Rosales C, Vergara E, Dopson M, Valdés JH, Holmes DS. Integrative genomics sheds light on evolutionary forces shaping the acidithiobacillia class acidophilic lifestyle. Front Microbiol 2021; 12:822229 [View Article] [PubMed]
    [Google Scholar]
  4. Ma L, Huang S, Wu P, Xiong J, Wang H et al. The interaction of acidophiles driving community functional responses to the re-Inoculated chalcopyrite bioleaching process. Sci Total Environ 2021; 798:149186 [View Article] [PubMed]
    [Google Scholar]
  5. TEMPLE KL, COLMER AR. The autotrophic oxidation of iron by a new bacterium, Thiobacillus ferrooxidans. J Bacteriol 1951; 62:605–611 [View Article] [PubMed]
    [Google Scholar]
  6. Wang R, Lin J-Q, Liu X-M, Pang X, Zhang C-J et al. Sulfur oxidation in the acidophilic autotrophic Acidithiobacillus spp. Front Microbiol 2018; 9:3290 [View Article] [PubMed]
    [Google Scholar]
  7. Tettelin H, Riley D, Cattuto C, Medini D. Comparative genomics: the bacterial pan-genome. Curr Opin Microbiol 2008; 11:472–477 [View Article] [PubMed]
    [Google Scholar]
  8. Maistrenko OM, Mende DR, Luetge M, Hildebrand F, Schmidt TSB et al. Disentangling the impact of environmental and phylogenetic constraints on prokaryotic within-species diversity. The ISME Journal 2020; 14:1247–1259 [View Article] [PubMed]
    [Google Scholar]
  9. Valdés J, Pedroso I, Quatrini R, Holmes DS. Comparative genome analysis of Acidithiobacillus ferrooxidans, A. thiooxidans and A. caldus: insights into their metabolism and ecophysiology. Hydrometallurgy 2008; 94:180–184 [View Article]
    [Google Scholar]
  10. Zhang X, Feng X, Tao J, Ma L, Xiao Y et al. Comparative genomics of the extreme acidophile Acidithiobacillus thiooxidans reveals intraspecific divergence and niche adaptation. Int J Mol Sci 2016; 17:1355 [View Article] [PubMed]
    [Google Scholar]
  11. Guo W, Liu Y, Ng WL, Liao P-C, Huang B-H et al. Comparative transcriptome analysis of the invasive weed Mikania micrantha with its native congeners provides insights into genetic basis underlying successful invasion. BMC Genomics 2018; 19:392 [View Article] [PubMed]
    [Google Scholar]
  12. Ullrich SR, González C, Poehlein A, Tischler JS, Daniel R et al. Gene loss and horizontal gene transfer contributed to the genome evolution of the extreme acidophile “Ferrovum.”. Front Microbiol 2016; 7:797 [View Article] [PubMed]
    [Google Scholar]
  13. Li L, Liu Z, Meng D, Liu X, Li X et al. Comparative genomic analysis reveals the distribution, organization, and evolution of metal resistance genes in the genus Acidithiobacillus. Appl Environ Microbiol 2019; 85:e02153-18 [View Article] [PubMed]
    [Google Scholar]
  14. Zhang X, Liu X, Liang Y, Fan F, Zhang X et al. Metabolic diversity and adaptive mechanisms of iron- and/or sulfur-oxidizing autotrophic acidophiles in extremely acidic environments. Environ Microbiol Rep 2016; 8:738–751 [View Article] [PubMed]
    [Google Scholar]
  15. Hemme CL, Green SJ, Rishishwar L, Prakash O, Pettenato A et al. Lateral gene transfer in a heavy metal-contaminated-groundwater microbial community. mBio 2016; 7:e02234–15 [View Article] [PubMed]
    [Google Scholar]
  16. Zhang X, Liu X, Liang Y, Guo X, Xiao Y et al. Adaptive evolution of extreme acidophile Sulfobacillus thermosulfidooxidans potentially driven by horizontal gene transfer and gene loss. Appl Environ Microbiol 2017; 83:e03098-16 [View Article] [PubMed]
    [Google Scholar]
  17. Rodríguez-Beltrán J, Sørum V, Toll-Riera M, de la Vega C, Peña-Miller R et al. Genetic dominance governs the evolution and spread of mobile genetic elements in bacteria. Proc Natl Acad Sci 2020; 117:15755–15762 [View Article] [PubMed]
    [Google Scholar]
  18. Kimura M. Evolutionary rate at the molecular level. Nature 1968; 217:624–626 [View Article] [PubMed]
    [Google Scholar]
  19. Props R, Monsieurs P, Vandamme P, Leys N, Denef VJ et al. Gene expansion and positive selection as bacterial adaptations to oligotrophic conditions. mSphere 2019; 4:e00011-19 [View Article] [PubMed]
    [Google Scholar]
  20. Li L, Liu Z, Zhang M, Meng D, Liu X et al. Insights into the metabolism and evolution of the genus Acidiphilium, a typical acidophile in acid mine drainage. mSystems 2020; 5:e00867-20 [View Article] [PubMed]
    [Google Scholar]
  21. Nielsen R. Molecular signatures of natural selection. Annu Rev Genet 2005; 39:197–218 [View Article] [PubMed]
    [Google Scholar]
  22. Giovannoni SJ, Cameron Thrash J, Temperton B. Implications of streamlining theory for microbial ecology. ISME J 2014; 8:1553–1565 [View Article] [PubMed]
    [Google Scholar]
  23. Sriaporn C, Campbell KA, Van Kranendonk MJ, Handley KM. Genomic adaptations enabling Acidithiobacillus distribution across wide-ranging hot spring temperatures and pHs. Microbiome 2021; 9:135 [View Article] [PubMed]
    [Google Scholar]
  24. Sabath N, Ferrada E, Barve A, Wagner A. Growth temperature and genome size in bacteria are negatively correlated, suggesting genomic streamlining during thermal adaptation. Genome Biol Evol 2013; 5:966–977 [View Article] [PubMed]
    [Google Scholar]
  25. Wang R, Lin J-Q, Liu X-M, Pang X, Zhang C-J et al. Sulfur oxidation in the acidophilic autotrophic Acidithiobacillus spp. Front Microbiol 2018; 9:3290 [View Article] [PubMed]
    [Google Scholar]
  26. Zhang X, She S, Dong W, Niu J, Xiao Y et al. Comparative genomics unravels metabolic differences at the species and/or strain level and extremely acidic environmental adaptation of ten bacteria belonging to the genus Acidithiobacillus. Syst Appl Microbiol 2016; 39:493–502 [View Article] [PubMed]
    [Google Scholar]
  27. Luo R, Liu B, Xie Y, Li Z, Huang W et al. SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler. Gigascience 2012; 1:18 [View Article] [PubMed]
    [Google Scholar]
  28. 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]
  29. Lowe TM, Chan PP. tRNAscan-SE On-line: integrating search and context for analysis of transfer RNA genes. Nucleic Acids Res 2016; 44:W54–7 [View Article] [PubMed]
    [Google Scholar]
  30. Lagesen K, Hallin P, Rødland EA, Staerfeldt HH, Rognes T et al. RNAmmer: consistent and rapid annotation of ribosomal RNA genes. Nucleic Acids Res 2007; 35:3100–3108 [View Article] [PubMed]
    [Google Scholar]
  31. Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: A fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol 2015; 32:268–274 [View Article] [PubMed]
    [Google Scholar]
  32. Letunic I, Bork P. Interactive tree of life (iTOL) V4: recent updates and new developments. Nucleic Acids Res 2019; 47:W256–W259 [View Article] [PubMed]
    [Google Scholar]
  33. Zuo G. CVTree: a parallel alignment-free phylogeny and taxonomy tool based on composition vectors of genomes. GPB 2021; 19:662–667 [View Article] [PubMed]
    [Google Scholar]
  34. Richter M, Rosselló-Móra R, Oliver Glöckner F, Peplies J. JSpeciesWS: a web server for prokaryotic species circumscription based on pairwise genome comparison. Bioinformatics 2016; 32:929–931 [View Article] [PubMed]
    [Google Scholar]
  35. Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:119 [View Article] [PubMed]
    [Google Scholar]
  36. Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res 2013; 41:D808–15 [View Article] [PubMed]
    [Google Scholar]
  37. Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000; 28:27–30 [View Article] [PubMed]
    [Google Scholar]
  38. Chaudhari NM, Gupta VK, Dutta C. BPGA- an ultra-fast pan-genome analysis pipeline. Sci Rep 2016; 6:24373 [View Article] [PubMed]
    [Google Scholar]
  39. Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 2019; 20:238 [View Article] [PubMed]
    [Google Scholar]
  40. Csurös M. Count: evolutionary analysis of phylogenetic profiles with parsimony and likelihood. Bioinformatics 2010; 26:1910–1912 [View Article] [PubMed]
    [Google Scholar]
  41. 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] [PubMed]
    [Google Scholar]
  42. Zhang Z, Xiao J, Wu J, Zhang H, Liu G et al. ParaAT: a parallel tool for constructing multiple protein-coding DNA alignments. Biochem Biophys Res Commun 2012; 419:779–781 [View Article] [PubMed]
    [Google Scholar]
  43. Yang Z. PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol 2007; 24:1586–1591 [View Article] [PubMed]
    [Google Scholar]
  44. Waterhouse AM, Procter JB, Martin DMA, Clamp M, Barton GJ. Jalview version 2--a multiple sequence alignment editor and analysis workbench. Bioinformatics 2009; 25:1189–1191 [View Article] [PubMed]
    [Google Scholar]
  45. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res 2004; 32:1792–1797 [View Article] [PubMed]
    [Google Scholar]
  46. Zhang X, Liu X, Yang F, Chen L. Pan-genome analysis links the hereditary variation of Leptospirillum ferriphilum with its evolutionary adaptation. Front Microbiol 2018; 9:577 [View Article] [PubMed]
    [Google Scholar]
  47. Zheng H, Wu H. Gene-centric association analysis for the correlation between the guanine-cytosine content levels and temperature range conditions of prokaryotic species. BMC Bioinformatics 2010; 11 Suppl 11:S7 [View Article] [PubMed]
    [Google Scholar]
  48. Richter M, Rosselló-Móra R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci 2009; 106:19126–19131 [View Article] [PubMed]
    [Google Scholar]
  49. Quatrini R, Johnson DB. Microbiomes in extremely acidic environments: functionalities and interactions that allow survival and growth of prokaryotes at low pH. Curr Opin Microbiol 2018; 43:139–147 [View Article] [PubMed]
    [Google Scholar]
  50. Zhang X, Liu X, He Q, Dong W, Zhang X et al. Gene turnover contributes to the evolutionary adaptation of Acidithiobacillus caldus: insights from comparative genomics. Front Microbiol 2016; 7:1960 [View Article] [PubMed]
    [Google Scholar]
  51. Baker-Austin C, Dopson M. Life in acid: pH homeostasis in acidophiles. Trends Microbiol 2007; 15:165–171 [View Article] [PubMed]
    [Google Scholar]
  52. Chen L, Hu M, Huang L, Hua Z, Kuang J et al. Comparative metagenomic and metatranscriptomic analyses of microbial communities in acid mine drainage. ISME J 2015; 9:1579–1592 [View Article] [PubMed]
    [Google Scholar]
  53. Zhang X, Liu Z, Wei G, Yang F, Liu X. In silico genome-wide analysis reveals the potential links between core genome of Acidithiobacillus thiooxidans and Its autotrophic lifestyle. Front Microbiol 2018; 9:1255 [View Article] [PubMed]
    [Google Scholar]
  54. Loper JE, Hassan KA, Mavrodi DV, Davis EW, Lim CK et al. Comparative genomics of plant-associated Pseudomonas spp.: insights into diversity and inheritance of traits involved in multitrophic interactions. PLoS Genet 2012; 8:e1002784 [View Article] [PubMed]
    [Google Scholar]
  55. Wani AK, Akhtar N, Sher F, Navarrete AA, Américo-Pinheiro JHP. Microbial adaptation to different environmental conditions: molecular perspective of evolved genetic and cellular systems. Arch Microbiol 2022; 204:144 [View Article] [PubMed]
    [Google Scholar]
  56. Agarwal G, Choudhary D, Stice SP, Myers BK, Gitaitis RD et al. Pan-Genome-Wide analysis of pantoea ananatis identified genes linked to pathogenicity in onion. Front Microbiol 2021; 12:684756 [View Article] [PubMed]
    [Google Scholar]
  57. de Korne-Elenbaas J, Bruisten SM, van Dam AP, Maiden MCJ, Harrison OB. The Neisseria gonorrhoeae accessory genome and its association with the core genome and antimicrobial resistance. Microbiol Spectr 2022; 10:e0265421 [View Article] [PubMed]
    [Google Scholar]
  58. Li L, Liu Z, Zhou Z, Zhang M, Meng D et al. Comparative genomics provides insights into the genetic diversity and evolution of the DPANN superphylum. mSystems 2021; 6:e0060221 [View Article] [PubMed]
    [Google Scholar]
  59. Heaps HS. Information Retrieval, Computational And Theoretical Aspects Academic Press; 1978
    [Google Scholar]
  60. Vernikos G, Medini D, Riley DR, Tettelin H. Ten years of pan-genome analyses. Curr Opin Microbiol 2015; 23:148–154 [View Article] [PubMed]
    [Google Scholar]
  61. Sweet ME, Larsen C, Zhang X, Schlame M, Pedersen BP et al. Structural basis for potassium transport in prokaryotes by KdpFABC. Proc Natl Acad Sci 2021; 118:e2105195118 [View Article] [PubMed]
    [Google Scholar]
  62. Duin EC, Madadi-Kahkesh S, Hedderich R, Clay MD, Johnson MK. Heterodisulfide reductase from Methanothermobacter marburgensis contains an active-site [4Fe-4S] cluster that is directly involved in mediating heterodisulfide reduction. FEBS Lett 2002; 512:263–268 [View Article] [PubMed]
    [Google Scholar]
  63. Wagner T, Koch J, Ermler U, Shima S. Methanogenic heterodisulfide reductase (HdrABC-MvhAGD) uses two noncubane [4Fe-4S] clusters for reduction. Science 2017; 357:699–703 [View Article] [PubMed]
    [Google Scholar]
  64. Appia-Ayme C, Guiliani N, Ratouchniak J, Bonnefoy V. Characterization of an operon encoding two c-type cytochromes, an aa(3)-type cytochrome oxidase, and rusticyanin in Thiobacillus ferrooxidans ATCC 33020. Appl Environ Microbiol 1999; 65:4781–4787 [View Article] [PubMed]
    [Google Scholar]
  65. Kucera J, Lochman J, Bouchal P, Pakostova E, Mikulasek K et al. A model of aerobic and anaerobic metabolism of hydrogen in the extremophile Acidithiobacillus ferrooxidans. Front Microbiol 2020; 11:610836 [View Article] [PubMed]
    [Google Scholar]
  66. Liu JS, Zhang YF, Geng MM, Zeng J, Qiu GZ. eds Research on Isc Operon in Acidithiobacillus Ferrooxidans ATCC 232702007 Trans Tech Publ;
    [Google Scholar]
  67. Moya-Beltrán A, Beard S, Rojas-Villalobos C, Issotta F, Gallardo Y et al. Genomic evolution of the class acidithiobacillia: deep-branching Proteobacteria living in extreme acidic conditions. ISME J 2021; 15:3221–3238 [View Article] [PubMed]
    [Google Scholar]
  68. Resch CT, Winogrodzki JL, Häse CC, Dibrov P. Insights into the biochemistry of the ubiquitous NhaP family of cation/H+ antiporters. Biochem Cell Biol 2011; 89:130–137 [View Article] [PubMed]
    [Google Scholar]
  69. Tascón I, Sousa JS, Corey RA, Mills DJ, Griwatz D et al. Structural basis of proton-coupled potassium transport in the KUP family. Nat Commun 2020; 11:626 [View Article] [PubMed]
    [Google Scholar]
  70. Hu W, Pan J, Wang B, Guo J, Li M et al. Metagenomic insights into the metabolism and evolution of a new thermoplasmata order (Candidatus Gimiplasmatales). Environ Microbiol 2021; 23:3695–3709 [View Article] [PubMed]
    [Google Scholar]
  71. Porter SL, Wadhams GH, Armitage JP. Signal processing in complex chemotaxis pathways. Nat Rev Microbiol 2011; 9:153–165 [View Article] [PubMed]
    [Google Scholar]
  72. Huang Z, Pan X, Xu N, Guo M. Bacterial chemotaxis coupling protein: structure, function and diversity. Microbiol Res 2019; 219:40–48 [View Article] [PubMed]
    [Google Scholar]
  73. Islam ZF, Welsh C, Bayly K, Grinter R, Southam G et al. A widely distributed hydrogenase oxidises atmospheric H2 during bacterial growth. ISME J 2020; 14:2649–2658 [View Article] [PubMed]
    [Google Scholar]
  74. Mielke RE, Pace DL, Porter T, Southam G. A critical stage in the formation of acid mine drainage: colonization of pyrite by Acidithiobacillus ferrooxidans under pH-neutral conditions. Geobiology 2003; 1:81–90 [View Article]
    [Google Scholar]
  75. Guinote IB, Moreira RN, Freire P, Arraiano CM. Characterization of the BolA homolog IbaG: a new gene involved in acid resistance. J Microbiol Biotechnol 2012; 22:484–493 [View Article] [PubMed]
    [Google Scholar]
  76. Tan S, Liu J, Fang Y, Hedlund BP, Lian Z-H et al. Insights into ecological role of a new deltaproteobacterial order candidatus acidulodesulfobacterales by metagenomics and metatranscriptomics. ISME J 2019; 13:2044–2057 [View Article] [PubMed]
    [Google Scholar]
  77. Olson MV. When less is more: gene loss as an engine of evolutionary change. Am J Hum Genet 1999; 64:18–23 [View Article] [PubMed]
    [Google Scholar]
  78. Cole ST, Eiglmeier K, Parkhill J, James KD, Thomson NR et al. Massive gene decay in the leprosy bacillus. Nature 2001; 409:1007–1011 [View Article] [PubMed]
    [Google Scholar]
  79. Albalat R, Cañestro C. Evolution by gene loss. Nat Rev Genet 2016; 17:379–391 [View Article] [PubMed]
    [Google Scholar]
  80. Morris JJ, Lenski RE, Zinser ER. The Black Queen Hypothesis: evolution of dependencies through adaptive gene loss. mBio 2012; 3:e00036-12 [View Article] [PubMed]
    [Google Scholar]
  81. Kazazian HH. Mobile elements: drivers of genome evolution. Science 2004; 303:1626–1632 [View Article] [PubMed]
    [Google Scholar]
  82. Ma L, Yang W, Huang S, Liu R, Li H et al. Integrative assessments on molecular taxonomy of Acidiferrobacter thiooxydans ZJ and its environmental adaptation based on mobile genetic elements. Front Microbiol 2022; 13:826829 [View Article] [PubMed]
    [Google Scholar]
  83. Jeffares DC, Tomiczek B, Sojo V, dos Reis M. A beginners guide to estimating the non-synonymous to synonymous rate ratio of all protein-coding genes in a genome. Methods Mol Biol 2015; 1201:65–90 [View Article] [PubMed]
    [Google Scholar]
  84. Sghaier H, Ghedira K, Benkahla A, Barkallah I. Basal DNA repair machinery is subject to positive selection in ionizing-radiation-resistant bacteria. BMC Genomics 2008; 9:297 [View Article] [PubMed]
    [Google Scholar]
  85. Jin J, Chen H, Wang N, Zhu K, Liu H et al. A novel lipoate-protein ligase, Mhp-LplJ, is required for lipoic acid metabolism in Mycoplasma hyopneumoniae. Front Microbiol 2020; 11:631433 [View Article] [PubMed]
    [Google Scholar]
  86. Vu HN, Ito T, Downs DM. The role of yggs in vitamin B(6) homeostasis in Salmonella enterica is informed by heterologous expression of yeast SNZ3. J Bacteriol 2020; 202:22 [View Article]
    [Google Scholar]
  87. Sugimoto R, Saito N, Shimada T, Tanaka K. Identification of YbhA as the pyridoxal 5’-phosphate (PLP) phosphatase in Escherichia coli: Importance of PLP homeostasis on the bacterial growth. J Gen Appl Microbiol 2018; 63:362–368 [View Article] [PubMed]
    [Google Scholar]
  88. Fujishiro T, Shimada Y, Nakamura R, Ooi M. Structure of sirohydrochlorin ferrochelatase SirB: the last of the structures of the class II chelatase family. Dalton Trans 2019; 48:6083–6090 [View Article] [PubMed]
    [Google Scholar]
  89. Kirschning A. The coenzyme/protein pair and the molecular evolution of life. Nat Prod Rep 2021; 38:993–1010 [View Article] [PubMed]
    [Google Scholar]
  90. Wen Q, Liu X, Wang H, Lin J. A versatile and efficient markerless gene disruption system for Acidithiobacillus thiooxidans: application for characterizing a copper tolerance related multicopper oxidase gene. Environ Microbiol 2014; 16:3499–3514 [View Article] [PubMed]
    [Google Scholar]
  91. Méndez-García C, Peláez AI, Mesa V, Sánchez J, Golyshina OV et al. Microbial diversity and metabolic networks in acid mine drainage habitats. Front Microbiol 2015; 6:475 [View Article] [PubMed]
    [Google Scholar]
  92. Gebhard S, Tran SL, Cook GM. The Phn system of Mycobacterium smegmatis: a second high-affinity ABC-transporter for phosphate. Microbiol 2006; 152:Pt 113453–65
    [Google Scholar]
  93. Stasi R, Neves HI, Spira B. Phosphate uptake by the phosphonate transport system Phncde. BMC Microbiol 2019; 19:79 [View Article] [PubMed]
    [Google Scholar]
  94. Gueiros-Filho FJ, Losick R. A widely conserved bacterial cell division protein that promotes assembly of the tubulin-like protein FtsZ. Genes Dev 2002; 16:2544–2556 [View Article] [PubMed]
    [Google Scholar]
  95. Perez AJ, Villicana JB, Tsui H-CT, Danforth ML, Benedet M et al. FtsZ-Ring regulation and cell division are mediated by essential EzrA and accessory proteins ZapA and ZapJ in Streptococcus pneumoniae. Front Microbiol 2021; 12:780864 [View Article] [PubMed]
    [Google Scholar]
  96. Lovett ST. DNA polymerase III protein, HolC, helps resolve replication/transcription conflicts. Microb Cell 2021; 8:143–145 [View Article] [PubMed]
    [Google Scholar]
  97. Nakahigashi K, Kubo N, Narita S, Shimaoka T, Goto S et al. HemK, a class of protein methyl transferase with similarity to DNA methyl transferases, methylates polypeptide chain release factors, and hemK knockout induces defects in translational termination. Proc Natl Acad Sci 2002; 99:1473–1478 [View Article] [PubMed]
    [Google Scholar]
  98. Jia M, Hu Y, Jin C. 1H, 13C and 15N resonance assignments of the second peptidyl-prolyl isomerase domain of chaperone SurA from Escherichia coli. Biomol NMR Assign 2019; 13:183–186 [View Article]
    [Google Scholar]
  99. Castelle C, Guiral M, Malarte G, Ledgham F, Leroy G et al. A new iron-oxidizing/O2-reducing supercomplex spanning both inner and outer membranes, isolated from the extreme acidophile Acidithiobacillus ferrooxidans. J Biol Chem 2008; 283:25803–25811 [View Article] [PubMed]
    [Google Scholar]
  100. Alcaraz LA, Donaire A. Unfolding process of rusticyanin: evidence of protein aggregation. Eur J Biochem 2004; 271:4284–4292 [View Article] [PubMed]
    [Google Scholar]
  101. Navarro CA, von Bernath D, Martínez-Bussenius C, Castillo RA, Jerez CA. Cytoplasmic CopZ-Like protein and periplasmic rusticyanin and AcoP proteins as possible copper resistance determinants in Acidithiobacillus ferrooxidans ATCC 23270. Appl Environ Microbiol 2016; 82:1015–1022 [View Article] [PubMed]
    [Google Scholar]
  102. Ccorahua-Santo R, Eca A, Abanto M, Guerra G, Ramírez P. Physiological and comparative genomic analysis of Acidithiobacillus ferrivorans PQ33 provides psychrotolerant fitness evidence for oxidation at low temperature. Res Microbiol 2017; 168:482–492 [View Article] [PubMed]
    [Google Scholar]
  103. Amouric A, Brochier-Armanet C, Johnson DB, Bonnefoy V, Hallberg KB. Phylogenetic and genetic variation among Fe(II)-oxidizing Acidithiobacilli supports the view that these comprise multiple species with different ferrous iron oxidation pathways. Microbiology 2011; 157:111–122 [View Article] [PubMed]
    [Google Scholar]
  104. Cascales E, Christie PJ. The versatile bacterial type IV secretion systems. Nat Rev Microbiol 2003; 1:137–149 [View Article] [PubMed]
    [Google Scholar]
  105. Backert S, Grohmann E. Erratum to: type IV secretion in Gram-negative and Gram-positive bacteria. Curr Top Microbiol Immunol 2017; 413:E1 [View Article] [PubMed]
    [Google Scholar]
  106. Grohmann E, Christie PJ, Waksman G, Backert S. Type IV secretion in Gram-negative and Gram-positive bacteria. Mol Microbiol 2018; 107:455–471 [View Article] [PubMed]
    [Google Scholar]
  107. Wu Y, Xiang L, Wang H, Ma L, Qiu X et al. Transcriptome analysis of an arsenite-/antimonite-oxidizer, Bosea SP. AS-1 reveals the importance of the type 4 secretion system in antimony resistance. Sci Total Environ 2022; 826:154168 [View Article] [PubMed]
    [Google Scholar]
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