1887

Microbial Genomics logo

Volume 9, Issue 6

A panoramic view of the genomic landscape of the genus Open Access

Abstract

We delineate the evolutionary plasticity of the ecologically and biotechnologically important genus , by analysing the genomes of 213 species. Streptomycetes genomes demonstrate high levels of internal homology, whereas the genome of their last common ancestor was already complex. Importantly, we identify the species-specific fingerprint proteins that characterize each species. Even among closely related species, we observed high interspecies variability of chromosomal protein-coding genes, species-level core genes, accessory genes and fingerprints. Notably, secondary metabolite biosynthetic gene clusters (smBGCs), carbohydrate-active enzymes (CAZymes) and protein-coding genes bearing the rare TTA codon demonstrate high intraspecies and interspecies variability, which emphasizes the need for strain-specific genomic mining. Highly conserved genes, such as those specifying genus-level core proteins, tend to occur in the central region of the chromosome, whereas those encoding proteins with evolutionarily volatile species-level fingerprints, smBGCs, CAZymes and TTA-codon-bearing genes are often found towards the ends of the linear chromosome. Thus, the chromosomal arms emerge as the part of the genome that is mainly responsible for rapid adaptation at the species and strain level. Finally, we observed a moderate, but statistically significant, correlation between the total number of CAZymes and three categories of smBGCs (siderophores, e-Polylysin and type III lanthipeptides) that are related to competition among bacteria.

  • Received:
  • Accepted:
  • Published Online:
Keyword(s): adaptation , carbohydrate-active enzymes , comparative genomics , core genome , evolution , secondary metabolites , species-specific adaptations , Streptomyces and TTA codon
Funding
This study was supported by the:
  • University of Thessaly (Award DEKA-UTH-259)
    • Principle Award Recipient: MariosNikolaidis
© 2023 The Authors
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Loading

Article metrics loading...

/content/journal/mgen/10.1099/mgen.0.001028
2023-06-02
2024-04-26
Loading full text...

Full text loading...

/deliver/fulltext/mgen/9/6/mgen001028.html?itemId=/content/journal/mgen/10.1099/mgen.0.001028&mimeType=html&fmt=ahah

References

  1. Nikolaidis M, Hesketh A, Frangou N, Mossialos D, Van de Peer Y et al.A panoramic view of the Genomic landscape of the genus Streptomyces FigShare 2023 https://doi.org/10.6084/m9.figshare.22316791.v2
     [Google Scholar]
  2. Traxler MF, Rozen DE. Ecological drivers of division of labour in Streptomyces. Curr Opin Microbiol 2022; 67:102148 [View Article] [PubMed]
     [Google Scholar]
  3. Chater KF, Biró S, Lee KJ, Palmer T, Schrempf H. The complex extracellular biology of Streptomyces. FEMS Microbiol Rev 2010; 34:171–198 [View Article] [PubMed]
     [Google Scholar]
  4. Seshadri R, Roux S, Huber KJ, Wu D, Yu S et al. Expanding the genomic encyclopedia of Actinobacteria with 824 isolate reference genomes. Cell Genom 2022; 2:100213 [View Article] [PubMed]
     [Google Scholar]
  5. Zhou Z, Gu J, Li Y-Q, Wang Y. Genome plasticity and systems evolution in Streptomyces. BMC Bioinformatics 2012; 13: [View Article]
     [Google Scholar]
  6. Doroghazi JR, Metcalf WW. Comparative genomics of actinomycetes with a focus on natural product biosynthetic genes. BMC Genomics 2013; 14:611 [View Article]
     [Google Scholar]
  7. Antimicrobial Resistance Collaborators Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet 2022; 399:629–655
     [Google Scholar]
  8. Otani H, Udwary DW, Mouncey NJ. Comparative and pangenomic analysis of the genus Streptomyces. Sci Rep 2022; 12:18909 [View Article] [PubMed]
     [Google Scholar]
  9. Lorenzi J-N, Lespinet O, Leblond P, Thibessard A. Subtelomeres are fast-evolving regions of the Streptomyces linear chromosome. Microb Genom 2019; 7:000525 [View Article] [PubMed]
     [Google Scholar]
  10. Tidjani A-R, Lorenzi J-N, Toussaint M, van Dijk E, Naquin D et al. Massive gene flux drives genome diversity between sympatric Streptomyces conspecifics. mBio 2019; 10: [View Article]
     [Google Scholar]
  11. Land M, Hauser L, Jun S-R, Nookaew I, Leuze MR et al. Insights from 20 years of bacterial genome sequencing. Funct Integr Genomics 2015; 15:141–161 [View Article] [PubMed]
     [Google Scholar]
  12. McDonald BR, Currie CR, Keim P, Marx C, Abbot P. Lateral gene transfer dynamics in the ancient bacterial genus Streptomyces. mBio 2017; 8: [View Article]
     [Google Scholar]
  13. Bentley SD, Chater KF, Cerdeño-Tárraga A-M, Challis GL, Thomson NR et al. Complete genome sequence of the model actinomycete Streptomyces coelicolor A3(2). Nature 2002; 417:141–147 [View Article] [PubMed]
     [Google Scholar]
  14. Andam CP, Choudoir MJ, Vinh Nguyen A, Sol Park H, Buckley DH. Contributions of ancestral inter-species recombination to the genetic diversity of extant Streptomyces lineages. ISME J 2016; 10:1731–1741 [View Article] [PubMed]
     [Google Scholar]
  15. Doroghazi JR, Buckley DH. Widespread homologous recombination within and between Streptomyces species. ISME J 2010; 4:1136–1143 [View Article]
     [Google Scholar]
  16. Xu L, Ye K-X, Dai W-H, Sun C, Xu L-H et al. Comparative genomic insights into secondary metabolism biosynthetic gene cluster distributions of marine Streptomyces. Mar Drugs 2019; 17:498 [View Article] [PubMed]
     [Google Scholar]
  17. Salam N, Jiao J-Y, Zhang X-T, Li W-J. Update on the classification of higher ranks in the phylum Actinobacteria. Int J Syst Evol Microbiol 2020; 70:1331–1355 [View Article]
     [Google Scholar]
  18. Chater KF, Chandra G. The evolution of development in Streptomyces analysed by genome comparisons. FEMS Microbiol Rev 2006; 30:651–672 [View Article]
     [Google Scholar]
  19. Labeda DP, Goodfellow M, Brown R, Ward AC, Lanoot B et al. Phylogenetic study of the species within the family Streptomycetaceae. Antonie van Leeuwenhoek 2012; 101:73–104 [View Article] [PubMed]
     [Google Scholar]
  20. Han J-H, Cho M-H, Kim SB. Ribosomal and protein coding gene based multigene phylogeny on the family Streptomycetaceae. Syst Appl Microbiol 2012; 35:1–6 [View Article] [PubMed]
     [Google Scholar]
  21. Labeda DP, Dunlap CA, Rong X, Huang Y, Doroghazi JR et al. Phylogenetic relationships in the family Streptomycetaceae using multi-locus sequence analysis. Antonie van Leeuwenhoek 2017; 110:563–583 [View Article]
     [Google Scholar]
  22. Alam MT, Merlo ME, Takano E, Breitling R. Genome-based phylogenetic analysis of Streptomyces and its relatives. Mol Phylogenet Evol 2010; 54:763–772 [View Article] [PubMed]
     [Google Scholar]
  23. Nouioui I, Carro L, García-López M, Meier-Kolthoff JP, Woyke T et al. Genome-based taxonomic classification of the phylum Actinobacteria. Front Microbiol 2018; 9:2007 [View Article] [PubMed]
     [Google Scholar]
  24. Gomez-Escribano JP, Alt S, Bibb MJ. Next generation sequencing of Actinobacteria for the discovery of novel natural products. Mar Drugs 2016; 14:78 [View Article] [PubMed]
     [Google Scholar]
  25. Jackson SA, Crossman L, Almeida EL, Margassery LM, Kennedy J et al. Diverse and abundant secondary metabolism biosynthetic gene clusters in the genomes of marine sponge derived Streptomyces spp. isolates. Mar Drugs 2018; 16:67 [View Article] [PubMed]
     [Google Scholar]
  26. Belknap KC, Park CJ, Barth BM, Andam CP. Genome mining of biosynthetic and chemotherapeutic gene clusters in Streptomyces bacteria. Sci Rep 2020; 10:2003 [View Article] [PubMed]
     [Google Scholar]
  27. Lee N, Kim W, Hwang S, Lee Y, Cho S et al. Thirty complete Streptomyces genome sequences for mining novel secondary metabolite biosynthetic gene clusters. Sci Data 2020; 7:55 [View Article]
     [Google Scholar]
  28. Caicedo-Montoya C, Manzo-Ruiz M, Ríos-Estepa R. Pan-genome of the genus Streptomyces and prioritization of biosynthetic gene clusters with potential to produce antibiotic compounds. Front Microbiol 2021; 12:677558 [View Article] [PubMed]
     [Google Scholar]
  29. Seipke RF. Strain-level diversity of secondary metabolism in Streptomyces albus. PLoS One 2015; 10:e0116457 [View Article] [PubMed]
     [Google Scholar]
  30. Vicente CM, Thibessard A, Lorenzi J-N, Benhadj M, Hôtel L et al. Comparative genomics among closely related Streptomyces strains revealed specialized metabolite biosynthetic gene cluster diversity. Antibiotics 2018; 7:86 [View Article] [PubMed]
     [Google Scholar]
  31. Park CJ, Andam CP. Within-species genomic variation and variable patterns of recombination in the tetracycline producer Streptomyces rimosus. Front Microbiol 2019; 10:552 [View Article] [PubMed]
     [Google Scholar]
  32. Martinet L, Naômé A, Baiwir D, De Pauw E, Mazzucchelli G et al. On the risks of phylogeny-based strain prioritization for drug discovery: Streptomyces lunaelactis as a case study. Biomolecules 2020; 10:1027 [View Article] [PubMed]
     [Google Scholar]
  33. Chater KF, Chandra G. The use of the rare UUA codon to define “expression space” for genes involved in secondary metabolism, development and environmental adaptation in Streptomyces. J Microbiol 2008; 46:1–11 [View Article] [PubMed]
     [Google Scholar]
  34. Kim D-W, Chater KF, Lee K-J, Hesketh A. Effects of growth phase and the developmentally significant bldA-specified tRNA on the membrane-associated proteome of Streptomyces coelicolor. Microbiology 2005; 151:2707–2720 [View Article] [PubMed]
     [Google Scholar]
  35. Hesketh A, Bucca G, Laing E, Flett F, Hotchkiss G et al. New pleiotropic effects of eliminating a rare tRNA from Streptomyces coelicolor, revealed by combined proteomic and transcriptomic analysis of liquid cultures. BMC Genomics 2007; 8:261 [View Article] [PubMed]
     [Google Scholar]
  36. Bu Q-T, Li Y-P, Xie H, Wang J, Li Z-Y et al. Comprehensive dissection of dispensable genomic regions in Streptomyces based on comparative analysis approach. Microb Cell Fact 2020; 19:99 [View Article] [PubMed]
     [Google Scholar]
  37. McDaniel R, Ebert-Khosla S, Hopwood DA, Khosla C. Engineered biosynthesis of novel polyketides. Science 1993; 262:1546–1550 [View Article]
     [Google Scholar]
  38. Gomez-Escribano JP, Bibb MJ. Engineering Streptomyces coelicolor for heterologous expression of secondary metabolite gene clusters. Microb Biotechnol 2011; 4:207–215 [View Article]
     [Google Scholar]
  39. Komatsu M, Uchiyama T, Ōmura S, Cane DE, Ikeda H. Genome-minimized Streptomyces host for the heterologous expression of secondary metabolism. Proc Natl Acad Sci 2010; 107:2646–2651 [View Article]
     [Google Scholar]
  40. Myronovskyi M, Rosenkränzer B, Nadmid S, Pujic P, Normand P et al. Generation of a cluster-free Streptomyces albus chassis strains for improved heterologous expression of secondary metabolite clusters. Metab Eng 2018; 49:316–324 [View Article]
     [Google Scholar]
  41. Ahmed Y, Rebets Y, Estévez MR, Zapp J, Myronovskyi M et al. Engineering of Streptomyces lividans for heterologous expression of secondary metabolite gene clusters. Microb Cell Fact 2020; 19:5 [View Article] [PubMed]
     [Google Scholar]
  42. Huguet-Tapia JC, Lefebure T, Badger JH, Guan D, Pettis GS et al. Genome content and phylogenomics reveal both ancestral and lateral evolutionary pathways in plant-pathogenic Streptomyces species. Appl Environ Microbiol 2016; 82:2146–2155 [View Article] [PubMed]
     [Google Scholar]
  43. Nikolaidis M, Hesketh A, Mossialos D, Iliopoulos I, Oliver SG et al. A comparative analysis of the core proteomes within and among the Bacillus subtilis and Bacillus cereus evolutionary groups reveals the patterns of lineage- and species-specific adaptations. Microorganisms 2022; 10:1720 [View Article]
     [Google Scholar]
  44. Nikolaidis M, Mossialos D, Oliver SG, Amoutzias GD. Comparative analysis of the core proteomes among the Pseudomonas major evolutionary groups reveals species-specific adaptations for Pseudomonas aeruginosa and Pseudomonas chlororaphis. Diversity 2020; 12:289 [View Article]
     [Google Scholar]
  45. Emms DM, Kelly S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol 2019; 20:238 [View Article] [PubMed]
     [Google Scholar]
  46. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Research 2004; 32:1792–1797 [View Article]
     [Google Scholar]
  47. Castresana J. Selection of conserved blocks from multiple alignments for their use in phylogenetic analysis. Mol Biol Evol 2000; 17:540–552 [View Article] [PubMed]
     [Google Scholar]
  48. Minh BQ, Schmidt HA, Chernomor O, Schrempf D, Woodhams MD et al. Corrigendum to: 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]
  49. Chevenet F, Brun C, Bañuls A-L, Jacq B, Christen R. TreeDyn: towards dynamic graphics and annotations for analyses of trees. BMC Bioinformatics 2006; 7:439 [View Article] [PubMed]
     [Google Scholar]
  50. Letunic I, Bork P. Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res 2021; 49:W293–W296 [View Article]
     [Google Scholar]
  51. Anisimova M, Gascuel O. Approximate likelihood-ratio test for branches: a fast, accurate, and powerful alternative. Syst Biol 2006; 55:539–552 [View Article] [PubMed]
     [Google Scholar]
  52. 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 [View Article]
     [Google Scholar]
  53. Enright AJ, Van Dongen S, Ouzounis CA. An efficient algorithm for large-scale detection of protein families. Nucleic Acids Res 2002; 30:1575–1584 [View Article]
     [Google Scholar]
  54. Vlastaridis P, Kyriakidou P, Chaliotis A, Van de Peer Y, Oliver SG et al. Estimating the total number of phosphoproteins and phosphorylation sites in eukaryotic proteomes. GigaScience 2017; 6: [View Article]
     [Google Scholar]
  55. Cantalapiedra CP, Hernández-Plaza A, Letunic I, Bork P, Huerta-Cepas J. eggNOG-mapper v2: functional annotation, orthology assignments, and domain prediction at the metagenomic scale. Mol Biol Evol 2021; 38:5825–5829 [View Article] [PubMed]
     [Google Scholar]
  56. Huerta-Cepas J, Szklarczyk D, Heller D, Hernández-Plaza A, Forslund SK et al. eggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res 2019; 47:D309–D314 [View Article]
     [Google Scholar]
  57. Kanehisa M, Furumichi M, Tanabe M, Sato Y, Morishima K. KEGG: new perspectives on genomes, pathways, diseases and drugs. Nucleic Acids Res 2017; 45:D353–D361 [View Article] [PubMed]
     [Google Scholar]
  58. Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res 2000; 28:33–36
     [Google Scholar]
  59. Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T et al. Author correction: SciPy 1.0: fundamental algorithms for scientific computing in python. Nat Methods 2020; 17:261–272 [View Article] [PubMed]
     [Google Scholar]
  60. 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]
     [Google Scholar]
  61. Zhang H, Yohe T, Huang L, Entwistle S, Wu P et al. dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res 2018; 46:W95–W101 [View Article]
     [Google Scholar]
  62. Drula E, Garron M-L, Dogan S, Lombard V, Henrissat B et al. The carbohydrate-active enzyme database: functions and literature. Nucleic Acids Res 2022; 50:D571–D577 [View Article] [PubMed]
     [Google Scholar]
  63. Cabanettes F, Klopp C. D-GENIES: dot plot large genomes in an interactive, efficient and simple way. PeerJ 2018; 6:e4958 [View Article] [PubMed]
     [Google Scholar]
  64. Li H, Alkan C. New strategies to improve minimap2 alignment accuracy. Bioinformatics 2021; 37:4572–4574 [View Article]
     [Google Scholar]
  65. Altenhoff AM, Levy J, Zarowiecki M, Tomiczek B, Warwick Vesztrocy A et al. OMA standalone: orthology inference among public and custom genomes and transcriptomes. Genome Res 2019; 29:1152–1163 [View Article] [PubMed]
     [Google Scholar]
  66. Train C-M, Pignatelli M, Altenhoff A, Dessimoz C, Schwartz R. iHam and pyHam: visualizing and processing hierarchical orthologous groups. Bioinformatics 2019; 35:2504–2506 [View Article]
     [Google Scholar]
  67. Vela Gurovic MS, Díaz ML, Gallo CA, Dietrich J. Phylogenomics, CAZyome and core secondary metabolome of Streptomyces albus species. Mol Genet Genomics 2021; 296:1299–1311 [View Article] [PubMed]
     [Google Scholar]
  68. Komaki H, Ichikawa N, Oguchi A, Hamada M, Tamura T et al. Genome analysis-based reclassification of Streptomyces endus and Streptomyces sporocinereus as later heterotypic synonyms of Streptomyces hygroscopicus subsp. hygroscopicus. Int J Syst Evol Microbiol 2017; 67:343–345 [View Article] [PubMed]
     [Google Scholar]
  69. Komaki H, Tamura T. Reclassification of Streptomyces rimosus subsp. paromomycinus as Streptomyces paromomycinus sp. nov. Int J Syst Evol Microbiol 2019; 69:2577–2583 [View Article] [PubMed]
     [Google Scholar]
  70. Madhaiyan M, Saravanan VS, See-Too W-S. Genome-based analyses reveal the presence of 12 heterotypic synonyms in the genus Streptomyces and emended descriptions of Streptomyces bottropensis, Streptomyces celluloflavus, Streptomyces fulvissimus, Streptomyces glaucescens, Streptomyces murinus, and Streptomyces variegatus. Int J Syst Evol Microbiol 2020; 70:3924–3929 [View Article] [PubMed]
     [Google Scholar]
  71. Lee N, Choi M, Kim W, Hwang S, Lee Y et al. Re-classification of Streptomyces venezuelae strains and mining secondary metabolite biosynthetic gene clusters. iScience 2021; 24:103410 [View Article] [PubMed]
     [Google Scholar]
  72. Kim J-N, Kim Y, Jeong Y, Roe J-H, Kim B-G et al. Comparative genomics reveals the core and accessory genomes of Streptomyces species. J Microbiol Biotechnol 2015; 25:1599–1605 [View Article] [PubMed]
     [Google Scholar]
  73. Ranea JAG, Grant A, Thornton JM, Orengo CA. Microeconomic principles explain an optimal genome size in bacteria. Trends Genet 2005; 21:21–25 [View Article] [PubMed]
     [Google Scholar]
  74. Levine M, Tjian R. Transcription regulation and animal diversity. Nature 2003; 424:147–151 [View Article] [PubMed]
     [Google Scholar]
  75. van Nimwegen E. Scaling laws in the functional content of genomes. Trends Genet 2003; 19:479–484 [View Article] [PubMed]
     [Google Scholar]
  76. Freeling M, Thomas BC. Gene-balanced duplications, like tetraploidy, provide predictable drive to increase morphological complexity. Genome Res 2006; 16:805–814 [View Article]
     [Google Scholar]
  77. Maere S, De Bodt S, Raes J, Casneuf T, Van Montagu M et al. Modeling gene and genome duplications in eukaryotes. Proc Natl Acad Sci 2005; 102:5454–5459 [View Article] [PubMed]
     [Google Scholar]
  78. Gevers D, Vandepoele K, Simillon C, Van de Peer Y. Gene duplication and biased functional retention of paralogs in bacterial genomes. Trends Microbiol 2004; 12:148–154 [View Article] [PubMed]
     [Google Scholar]
  79. Gogarten JP, Townsend JP. Horizontal gene transfer, genome innovation and evolution. Nat Rev Microbiol 2005; 3:679–687 [View Article] [PubMed]
     [Google Scholar]
  80. Kunin V, Ouzounis CA. The balance of driving forces during genome evolution in prokaryotes. Genome Res 2003; 13:1589–1594 [View Article] [PubMed]
     [Google Scholar]
  81. Amoutzias GD, Van de Peer Y, Mossialos D. Evolution and taxonomic distribution of nonribosomal peptide and polyketide synthases. Fute Microb 2008; 3:361–370 [View Article] [PubMed]
     [Google Scholar]
  82. Amoutzias GD, Chaliotis A, Mossialos D. Discovery strategies of bioactive compounds synthesized by nonribosomal peptide synthetases and type-I polyketide synthases derived from marine microbiomes. Mar Drugs 2016; 14:80 [View Article] [PubMed]
     [Google Scholar]
  83. Kramer J, Özkaya Ö, Kümmerli R. Bacterial siderophores in community and host interactions. Nat Rev Microbiol 2020; 18:152–163 [View Article] [PubMed]
     [Google Scholar]
  84. Wang L, Zhang C, Zhang J, Rao Z, Xu X et al. Epsilon-poly-L-lysine: recent advances in biomanufacturing and applications. Front Bioeng Biotechnol 2021; 9:748976 [View Article]
     [Google Scholar]
  85. Gomes KM, Duarte RS, de Freire Bastos M do C. Lantibiotics produced by Actinobacteria and their potential applications (a review). Microbiology 2017; 163:109–121 [View Article]
     [Google Scholar]
  86. Chandra G, Chater KF. Developmental biology of Streptomyces from the perspective of 100 actinobacterial genome sequences. FEMS Microbiol Rev 2014; 38:345–379 [View Article] [PubMed]
     [Google Scholar]
  87. Rabyk M, Yushchuk O, Rokytskyy I, Anisimova M, Ostash B. Genomic insights into evolution of AdpA family master regulators of morphological differentiation and secondary metabolism in Streptomyces. J Mol Evol 2018; 86:204–215 [View Article] [PubMed]
     [Google Scholar]
  88. Choulet F, Aigle B, Gallois A, Mangenot S, Gerbaud C et al. Evolution of the terminal regions of the Streptomyces linear chromosome. Mol Biol Evol 2006; 23:2361–2369 [View Article] [PubMed]
     [Google Scholar]
  89. Volff JN, Altenbuchner J. Genetic instability of the Streptomyces chromosome. Mol Microbiol 1998; 27:239–246 [View Article] [PubMed]
     [Google Scholar]
  90. Chen CW, Huang C-H, Lee H-H, Tsai H-H, Kirby R. Once the circle has been broken: dynamics and evolution of Streptomyces chromosomes. Trends Genet 2002; 18:522–529 [View Article] [PubMed]
     [Google Scholar]
  91. Kirby R. Chromosome diversity and similarity within the Actinomycetales. FEMS Microbiol Lett 2011; 319:1–10 [View Article] [PubMed]
     [Google Scholar]
  92. Hoff G, Bertrand C, Piotrowski E, Thibessard A, Leblond P. Genome plasticity is governed by double strand break DNA repair in Streptomyces. Sci Rep 2018; 8:5272 [View Article] [PubMed]
     [Google Scholar]
  93. Musialowski MS, Flett F, Scott GB, Hobbs G, Smith CP et al. Functional evidence that the principal DNA replication origin of the Streptomyces coelicolor chromosome is close to the dnaA-gyrB region. J Bacteriol 1994; 176:5123–5125 [View Article] [PubMed]
     [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/mgen/10.1099/mgen.0.001028
Loading
A panoramic view of the genomic landscape of the genus Streptomyces
M Gen 9, 001028 (2023); https://doi.org/10.1099/mgen.0.001028
/content/journal/mgen/10.1099/mgen.0.001028
/content/journal/mgen/10.1099/mgen.0.001028
Loading

Data & Media loading...

Supplements

Supplementary material 1

PDF

Supplementary material 2

EXCEL

Supplementary material 3

MOVIE

Most cited Most Cited RSS feed

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error