1887

Abstract

Last year ActinoBase, a Wiki-style initiative supported by the UK Microbiology Society, published a review highlighting the research of particular interest to the actinomycete community. Here, we present the second ActinoBase review showcasing selected reports published in 2020 and early 2021, integrating perspectives in the actinomycete field. Actinomycetes are well-known for their unsurpassed ability to produce specialised metabolites, of which many are used as therapeutic agents with antibacterial, antifungal, or immunosuppressive activities. Much research is carried out to understand the purpose of these metabolites in the environment, either within communities or in host interactions. Moreover, many efforts have been placed in developing computational tools to handle big data, simplify experimental design, and find new biosynthetic gene cluster prioritisation strategies. Alongside, synthetic biology has provided advances in tools to elucidate the biosynthesis of these metabolites. Additionally, there are still mysteries to be uncovered in understanding the fundamentals of filamentous actinomycetes' developmental cycle and regulation of their metabolism. This review focuses on research using integrative methodologies and approaches to understand the bigger picture of actinomycete biology, covering four research areas: ) technology and methodology; ) specialised metabolites; ) development and regulation; and ) ecology and host interactions.

Funding
This study was supported by the:
  • Biotechnology and Biological Sciences Research Council (Award BB/S016651/1)
    • Principle Award Recipient: Katharina SchnieteJana
  • H2020 Marie Skłodowska-Curie Actions (Award 765147)
    • Principle Award Recipient: VindKristiina
  • Programa de Innovacion y Capital Humano para la Competitividad (PINN) (Award 2-1-4-17-1-037)
    • Principle Award Recipient: ParraJonathan
  • National Center for Genetic Engineering and Biotechnology
    • Principle Award Recipient: KruasuwanWorarat
  • Conselho Nacional de Desenvolvimento Científico e Tecnológico (Award 143700/2018-9)
    • Principle Award Recipient: F PereiraCamila
  • Fapesp (Award 2018/17502-2)
    • Principle Award Recipient: F PereiraCamila
  • Fondo Nacional de Desarrollo Científico y Tecnológico (Award 3180399)
    • Principle Award Recipient: UndabarrenaAgustina
  • This is an open-access article distributed under the terms of the Creative Commons Attribution License.
Loading

Article metrics loading...

/content/journal/micro/10.1099/mic.0.001084
2021-09-13
2022-10-06
Loading full text...

Full text loading...

/deliver/fulltext/micro/167/9/mic001084.html?itemId=/content/journal/micro/10.1099/mic.0.001084&mimeType=html&fmt=ahah

References

  1. Prudence SMM, Addington E, Castaño-Espriu L, Mark DR, Pintor-Escobar L et al. Advances in actinomycete research: An Actinobase review of 2019. Microbiology 2020; 166:683–694 [View Article] [PubMed]
    [Google Scholar]
  2. Barka EA, Vatsa P, Sanchez L, Gaveau-Vaillant N, Jacquard C et al. Taxonomy, physiology, and natural products of actinobacteria. Microbiol Mol Biol Rev 2016; 80:1–43 [View Article]
    [Google Scholar]
  3. van der Meij A, Worsley SF, Hutchings MI, van Wezel GP. Chemical ecology of antibiotic production by actinomycetes. FEMS Microbiol Rev 2017; 41:392–416 [View Article] [PubMed]
    [Google Scholar]
  4. Medema MH. Computational genomics of specialized metabolism: from natural product discovery to microbiome ecology. mSystems 2018; 3: [View Article]
    [Google Scholar]
  5. Nett M, Ikeda H, Moore BS. Genomic basis for natural product biosynthetic diversity in the actinomycetes. Nat Prod Rep 2009; 26:1362–1384 [View Article] [PubMed]
    [Google Scholar]
  6. Hutchings MI, Truman AW, Wilkinson B. Antibiotics: past, present and future. Curr Opin Microbiol 2019; 51:72–80 [View Article] [PubMed]
    [Google Scholar]
  7. Craney A, Ahmed S, Nodwell J. Towards a new science of secondary metabolism. J Antibiot 2013; 66:387–400 [View Article]
    [Google Scholar]
  8. Kautsar SA, van der Hooft JJJ, de Ridder D, Medema MH. BiG-SLiCE: A highly scalable tool maps the diversity of 1.2 million biosynthetic gene clusters. Gigascience 2021; 10:1–17 [View Article]
    [Google Scholar]
  9. Doroghazi JR, Metcalf WW. Comparative genomics of actinomycetes with a focus on natural product biosynthetic genes. BMC Genomics 2013; 14:611 [View Article] [PubMed]
    [Google Scholar]
  10. Chater KF. Recent advances in understanding Streptomyces. F1000Res 2016; 5:2795 [View Article]
    [Google Scholar]
  11. van Bergeijk DA, Terlouw BR, Medema MH, van Wezel GP. Ecology and genomics of Actinobacteria: new concepts for natural product discovery. Nat Rev Microbiol 2020; 18:546–558 [View Article] [PubMed]
    [Google Scholar]
  12. Baltz RH. Gifted microbes for genome mining and natural product discovery. J Ind Microbiol Biotechnol 2017; 44:573–588 [View Article] [PubMed]
    [Google Scholar]
  13. Kenshole E, Herisse M, Michael M, Pidot SJ. Natural product discovery through microbial genome mining. Curr Opin Chem Biol 2021; 60:47–54 [View Article] [PubMed]
    [Google Scholar]
  14. Ziemert N, Alanjary M, Weber T. The evolution of genome mining in microbes - a review. Nat Prod Rep 2016; 33:988–1005 [View Article] [PubMed]
    [Google Scholar]
  15. Boddy CN. Bioinformatics tools for genome mining of polyketide and non-ribosomal peptides. J Ind Microbiol Biotechnol 2014; 41:443–450 [View Article] [PubMed]
    [Google Scholar]
  16. 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:E80 [View Article]
    [Google Scholar]
  17. Gummerlich N, Rebets Y, Paulus C, Zapp J, Luzhetskyy A. Targeted genome mining—from compound discovery to biosynthetic pathway elucidation. Microorganisms 2020; 8:2034 [View Article]
    [Google Scholar]
  18. Terra L, Ratcliffe N, Castro HC, Vicente ACP, Dyson P. Biotechnological potential of streptomyces siderophores as new antibiotics. CMC 2021; 28:1407–1421 [View Article]
    [Google Scholar]
  19. Aggarwal E, Chauhan S, Sareen D. Thiopeptides encoding biosynthetic gene clusters mined from bacterial genomes. J Biosci 2021; 46: [View Article]
    [Google Scholar]
  20. Arnison PG, Bibb MJ, Bierbaum G, Bowers AA, Bugni TS et al. Ribosomally synthesized and post-translationally modified peptide natural products: Overview and recommendations for a universal nomenclature. Nat Prod Rep 2013; 30:108–160 [View Article] [PubMed]
    [Google Scholar]
  21. Kittrell CG, Shah SC, Halbert ME, Scott DH, Limbrick EM. Genomic analysis suggests Salinispora is a rich source of novel lanthipeptides. Mol Genet Genomics 2020; 295:1529–1535 [View Article] [PubMed]
    [Google Scholar]
  22. Choudoir M, Rossabi S, Gebert M, Helmig D, Fierer N et al. A phylogenetic and functional perspective on volatile organic compound production by Actinobacteria. mSystems 2019; 4: [View Article]
    [Google Scholar]
  23. Weisskopf L, Schulz S, Garbeva P. Microbial volatile organic compounds in intra-kingdom and inter-kingdom interactions. Nat Rev Microbiol 2021; 19:391–404 [View Article] [PubMed]
    [Google Scholar]
  24. Quinn GA, Banat AM, Abdelhameed AM, Banat IM. Streptomyces from traditional medicine: sources of new innovations in antibiotic discovery. J Med Microbiol 2020; 69:1040–1048 [View Article] [PubMed]
    [Google Scholar]
  25. Subramani R, Sipkema D. Marine rare actinomycetes: A promising source of structurally diverse and unique novel natural products. Mar Drugs 2019; 17:E249 [View Article] [PubMed]
    [Google Scholar]
  26. Hozzein WN, Mohany M, Alhawsawi SMM, Zaky MY, Al-Rejaie SS et al. Flavonoids from marine-derived actinobacteria as anticancer drugs. Curr Pharm Des 2021; 27:505–512 [View Article] [PubMed]
    [Google Scholar]
  27. Law J-F, Law L-S, Letchumanan V, Tan L-H, Wong SH et al. Anticancer drug discovery from microbial sources: The unique mangrove streptomycetes. Molecules 2020; 25:E5365 [View Article] [PubMed]
    [Google Scholar]
  28. Hussain A, Hassan QP, Shouche YS. New approaches for antituberculosis leads from Actinobacteria. Drug Discov Today 2020; 25:2335–2342 [View Article] [PubMed]
    [Google Scholar]
  29. Silver LL. Challenges of antibacterial discovery. Clin Microbiol Rev 2011; 24:71–109 [View Article] [PubMed]
    [Google Scholar]
  30. Scherlach K, Hertweck C. Mining and unearthing hidden biosynthetic potential. Nat Commun 2021; 12:1–12 [View Article]
    [Google Scholar]
  31. Navarro-Muñoz JC, Selem-Mojica N, Mullowney MW, Kautsar SA, Tryon JH et al. A computational framework to explore large-scale biosynthetic diversity. Nat Chem Biol 2020; 16:60–68 [View Article] [PubMed]
    [Google Scholar]
  32. Crüsemann M, O’Neill EC, Larson CB, Melnik AV, Floros DJ et al. Prioritizing natural product diversity in a collection of 146 bacterial strains based on growth and extraction protocols. J Nat Prod 2017; 80:588–597 [View Article] [PubMed]
    [Google Scholar]
  33. Medema MH. Minimum information about a biosynthetic gene cluster HHS public access author manuscript. Nat Chem Biol 2015; 11:625–631
    [Google Scholar]
  34. Kautsar SA, Blin K, Shaw S, Navarro-Muñoz JC, Terlouw BR et al. MIBiG 2.0: A repository for biosynthetic gene clusters of known function. Nucleic Acids Res 2020; 48:D454–D458 [View Article] [PubMed]
    [Google Scholar]
  35. Alam K, Hao J, Zhang Y, Li A. Synthetic biology-inspired strategies and tools for engineering of microbial natural product biosynthetic pathways. Biotechnol Adv 2021; 49:107759 [View Article]
    [Google Scholar]
  36. Yeo WL, Heng E, Tan LL, Lim YW, Lim YH et al. Characterization of Cas proteins for CRISPR-Cas editing in streptomycetes. Biotechnol Bioeng 2019; 116:2330–2338 [View Article] [PubMed]
    [Google Scholar]
  37. Breitling R, Avbelj M, Bilyk O, Carratore FD, Filisetti A et al. Synthetic biology approaches to actinomycete strain improvement. FEMS Microbiol Lett 2021; 368:fnab060 [View Article] [PubMed]
    [Google Scholar]
  38. Hoskisson PA, Seipke RF, Wright GD. Cryptic or silent? The known unknowns, unknown knowns, and unknown unknowns of secondary metabolism. mBio 2020; 11:e02642-20 [View Article]
    [Google Scholar]
  39. Blin K, Shaw S, Steinke K, Villebro R, Ziemert N et al. AntiSMASH 5.0: Updates to the secondary metabolite genome mining pipeline. Nucleic Acids Res 2019; 47:W81–W87 [View Article] [PubMed]
    [Google Scholar]
  40. Skinnider MA, Dejong CA, Rees PN, Johnston CW, Li H et al. Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM). Nucleic Acids Res 2015; 43:9645–9662 [View Article] [PubMed]
    [Google Scholar]
  41. de Jong A, van Hijum S, Bijlsma JJE, Kok J, Kuipers OP. BAGEL: A web-based bacteriocin genome mining tool. Nucleic Acids Res 2006; 34:W273–9 [View Article] [PubMed]
    [Google Scholar]
  42. Agrawal P, Khater S, Gupta M, Sain N, Mohanty D. RiPPMiner: A bioinformatics resource for deciphering chemical structures of RiPPs based on prediction of cleavage and cross-links. Nucleic Acids Res 2017; 45:W80–W88 [View Article] [PubMed]
    [Google Scholar]
  43. Navarro-Muñoz JC, Selem-Mojica N, Mullowney MW, Kautsar SA, Tryon JH et al. A computational framework to explore large-scale biosynthetic diversity. Nat Chem Biol 2020; 16:60–68 [View Article] [PubMed]
    [Google Scholar]
  44. Wang M, Carver JJ, Phelan VV, Sanchez LM, Garg N et al. Sharing and community curation of mass spectrometry data with Global Natural Products Social Molecular Networking. Nat Biotechnol 2016; 34:828–837 [View Article] [PubMed]
    [Google Scholar]
  45. Kautsar SA, Blin K, Shaw S, Weber T, Medema MH. BiG-FAM: the biosynthetic gene cluster families database. Nucleic Acids Res 2021; 49:D490–D497 [View Article] [PubMed]
    [Google Scholar]
  46. Tripathi A, Vázquez-Baeza Y, Gauglitz JM, Wang M, Dührkop K et al. Chemically informed analyses of metabolomics mass spectrometry data with Qemistree. Nat Chem Biol 2021; 17:146–151 [View Article] [PubMed]
    [Google Scholar]
  47. Medema MH. The year 2020 in natural product bioinformatics: an overview of the latest tools and databases. Nat Prod Rep 2021; 38:301–306 [View Article]
    [Google Scholar]
  48. Lee N, Hwang S, Lee Y, Cho S, Palsson B et al. Synthetic biology tools for novel secondary metabolite discovery in Streptomyces. J Microbiol Biotechnol 2019; 29:667–686 [View Article] [PubMed]
    [Google Scholar]
  49. Bertholt G, Govind C, Dagmara J, Tian Y, Bruton CJ et al. REDIRECT technology: PCR-targeting system in Streptomyces coelicolor. In Advances in Applied Microbiology pp 107–126
    [Google Scholar]
  50. Fernández-Martínez LT, Bibb MJ. Use of the Meganuclease I-SceI of Saccharomyces cerevisiae to select for gene deletions in actinomycetes. Sci Rep 2014; 4:1–6 [View Article]
    [Google Scholar]
  51. Tong Y, Whitford CM, Robertsen HL, Blin K, Jørgensen TS et al. Highly efficient DSB-free base editing for streptomycetes with CRISPR-BEST. Proc Natl Acad Sci U S A 2019; 116:20366–20375 [View Article] [PubMed]
    [Google Scholar]
  52. Medema MH, Rainer B, Eriko T. Synthetic Biology in Streptomyces Bacteria, 1st ed. Elsevier Inc; 2011 [View Article]
    [Google Scholar]
  53. Jaina M, Sara C, Lowri W, Matloob Q, Salazar Gustavo A et al. Pfam: The protein families database in 2021. Nucleic Acids Res 2021; 49:D412–D419 [View Article] [PubMed]
    [Google Scholar]
  54. Tian J, Yang G, Gu Y, Sun X, Lu Y et al. Developing an endogenous quorum-sensing based CRISPRi circuit for autonomous and tunable dynamic regulation of multiple targets in Streptomyces. Nucleic Acids Res 2020; 48:8188–8202 [View Article] [PubMed]
    [Google Scholar]
  55. Tian Z, Raghu R, Miron L. BIRCH: An Efficient Data Clustering Method for Very Large Databases 1996 [View Article]
    [Google Scholar]
  56. Jain AK. Data clustering: 50 years beyond K-means. Pattern Recognit Lett 2010; 31:651–666 [View Article]
    [Google Scholar]
  57. Blin K, Shaw S, Kautsar SA, Medema MH, Weber T. The antiSMASH database version 3: Increased taxonomic coverage and new query features for modular enzymes. Nucleic Acids Res 2021; 49:D639–D643 [View Article] [PubMed]
    [Google Scholar]
  58. Palaniappan K, Chen I-M, Chu K, Ratner A, Seshadri R et al. IMG-ABC v.5.0: An update to the Img/atlas of biosynthetic gene clusters knowledgeBase. Nucleic Acids Res 2020; 48:D422–D430 [View Article] [PubMed]
    [Google Scholar]
  59. Willett P. Similarity-based virtual screening using 2D fingerprints. Drug Discov Today 2006; 11:1046–1053 [View Article] [PubMed]
    [Google Scholar]
  60. Dührkop K, Scheubert K, Böcker S. Molecular formula identification with SIRIUS. Metabolites 2013; 3:506–516 [View Article] [PubMed]
    [Google Scholar]
  61. Dührkop K, Fleischauer M, Ludwig M, Aksenov AA, Melnik AV et al. SIRIUS 4: a rapid tool for turning tandem mass spectra into metabolite structure information. Nat Methods 2019; 16:299–302 [View Article] [PubMed]
    [Google Scholar]
  62. Dührkop K, Shen H, Meusel M, Rousu J, Böcker S. Searching molecular structure databases with tandem mass spectra using CSI:FingerID. Proc Natl Acad Sci U S A 2015; 112:12580–12585 [View Article] [PubMed]
    [Google Scholar]
  63. Djoumbou Feunang Y, Eisner R, Knox C, Chepelev L, Hastings J et al. ClassyFire: automated chemical classification with a comprehensive, computable taxonomy. J Cheminform 2016; 8:1–20 [View Article]
    [Google Scholar]
  64. Ivica L, Peer B. Gmbh Biobyte Solutions Interactive Tree Of Life (iTOL) v5: an online tool for phylogenetic tree display and annotation; 20211–4
  65. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol 2019; 37:852–857 [View Article] [PubMed]
    [Google Scholar]
  66. Aron AT, Gentry EC, McPhail KL, Nothias L-F, Nothias-Esposito M et al. Reproducible molecular networking of untargeted mass spectrometry data using GNPS. Nat Protoc 2020; 15:1954–1991 [View Article] [PubMed]
    [Google Scholar]
  67. Thompson LR, Sanders JG, McDonald D, Amir A, Ladau J et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 2017; 551:457–463 [View Article] [PubMed]
    [Google Scholar]
  68. Moore SJ, Hung-En L, Soo-Mei C, Ming T, Seth C et al. A Streptomyces venezuelae cell-free toolkit for synthetic biology. ACS Synth Biol 2021; 10:402–411 [View Article] [PubMed]
    [Google Scholar]
  69. Lu Y. Cell-free synthetic biology: Engineering in an open world. Synth Syst Biotechnol 2017; 2:23–27 [View Article] [PubMed]
    [Google Scholar]
  70. Caschera F, Noireaux V. Synthesis of 2.3 mg/ml of protein with an all Escherichia coli cell-free transcription-translation system. Biochimie 2014; 99:162–168 [View Article] [PubMed]
    [Google Scholar]
  71. Kuruma Y, Ueda T. The PURE system for the cell-free synthesis of membrane proteins. Nat Protoc 2015; 10:1328–1344 [View Article] [PubMed]
    [Google Scholar]
  72. Lavickova B, Maerkl SJ. A simple, robust, and low-cost method to produce the PURE cell-free system. ACS Synth Biol 2019; 8:455–462 [View Article] [PubMed]
    [Google Scholar]
  73. Rutledge PJ, Challis GL. Discovery of microbial natural products by activation of silent biosynthetic gene clusters. Nat Rev Microbiol 2015; 13:509–523 [View Article] [PubMed]
    [Google Scholar]
  74. Cress BF, Trantas EA, Ververidis F, Linhardt RJ, Koffas MA. Sensitive cells: Enabling tools for static and dynamic control of microbial metabolic pathways. Curr Opin Biotechnol 2015; 36:205–214 [View Article] [PubMed]
    [Google Scholar]
  75. Hartline CJ, Schmitz AC, Han Y, Zhang F. Dynamic control in metabolic engineering: Theories, tools, and applications. Metab Eng 2021; 63:126–140 [View Article] [PubMed]
    [Google Scholar]
  76. Takano E. Gamma-butyrolactones: Streptomyces signalling molecules regulating antibiotic production and differentiation. Curr Opin Microbiol 2006; 9:287–294 [View Article] [PubMed]
    [Google Scholar]
  77. Nishida H, Ohnishi Y, Beppu T, Horinouchi S. Evolution of γ-butyrolactone synthases and receptors in Streptomyces. Environ Microbiol 2007; 9:1986–1994 [View Article] [PubMed]
    [Google Scholar]
  78. Malpartida F, Hopwood DA. Physical and genetic characterisation of the gene cluster for the antibiotic actinorhodin in Streptomyces coelicolor A3(2). Mol Gen Genet 1986; 205:66–73 [View Article] [PubMed]
    [Google Scholar]
  79. Tiwari K, Gupta RK. Diversity and isolation of rare actinomycetes: An overview. Crit Rev Microbiol 2013; 39:256–294 [View Article] [PubMed]
    [Google Scholar]
  80. Subramani R, Sipkema D. Marine rare actinomycetes: A promising source of structurally diverse and unique novel natural products. Mar Drugs 2019; 17:249 [View Article]
    [Google Scholar]
  81. Román-Ponce B, Millán-Aguiñaga N, Guillen-Matus D, Chase AB, Ginigini JGM et al. Six novel species of the obligate marine actinobacterium Salinispora, Salinispora cortesiana sp. nov., Salinispora fenicalii sp. nov., Salinispora goodfellowii sp. nov., Salinispora mooreana sp. nov., Salinispora oceanensis sp. nov. and Salinispora vitien. Int J Syst Evol Microbiol 2020; 70:4668–4682 [View Article] [PubMed]
    [Google Scholar]
  82. Kim H, Kim S, Kim M, Lee C, Yang I et al. Bioactive natural products from the genus Salinospora: a review. Arch Pharm Res 2020; 43:1230–1258 [View Article] [PubMed]
    [Google Scholar]
  83. Millán-Aguiñaga N, Soldatou S, Brozio S, Munnoch JT, Howe J et al. Awakening ancient polar actinobacteria: Diversity, evolution and specialized metabolite potential. Microbiology 2019; 165:1169–1180 [View Article]
    [Google Scholar]
  84. Axenov-Gribanov DV, Voytsekhovskaya IV, Tokovenko BT, Protasov ES, Gamaiunov SV et al. Correction: Actinobacteria isolated from an underground lake and moonmilk speleothem from the biggest conglomeratic karstic cave in Siberia as sources of novel biologically active compounds. PLoS One 2016; 11:e0152957 [View Article]
    [Google Scholar]
  85. Adam D, Maciejewska M, Naômé A, Martinet L, Coppieters W et al. Isolation, characterization, and antibacterial activity of hard-to-culture actinobacteria from cave moonmilk deposits. Antibiotics 2018; 7:1–20 [View Article]
    [Google Scholar]
  86. Long Y, Jiang J, Hu X, Zhou J, Hu J et al. Actinobacterial community in Shuanghe Cave using culture-dependent and -independent approaches. World J Microbiol Biotechnol 2019; 35: [View Article]
    [Google Scholar]
  87. Sayed AM, Hassan MHA, Alhadrami HA, Hassan HM, Goodfellow M et al. Extreme environments: microbiology leading to specialized metabolites. J Appl Microbiol 2020; 128:630–657 [View Article] [PubMed]
    [Google Scholar]
  88. Goodfellow M, Nouioui I, Sanderson R, Xie F, Bull AT. Rare taxa and dark microbial matter: novel bioactive actinobacteria abound in Atacama Desert soils. Antonie van Leeuwenhoek 2018; 111:1315–1332 [View Article]
    [Google Scholar]
  89. Benaud N, Edwards RJ, Amos TG, D’Agostino PM, Gutiérrez-Chávez C et al. Antarctic desert soil bacteria exhibit high novel natural product potential, evaluated through long-read genome sequencing and comparative genomics. Environ Microbiol 2021; 23:3646–3664 [View Article]
    [Google Scholar]
  90. Männle D, McKinnie SMK, Mantri SS, Steinke K, Lu Z et al. Comparative genomics and metabolomics in the genus Nocardia. mSystems 2020; 5:1–19 [View Article]
    [Google Scholar]
  91. Soldatou S, Eldjárn GH, Ramsay A, van der Hooft JJJ, Hughes AH et al. Comparative metabologenomics analysis of polar Actinomycetes. Mar Drugs 2021; 19:103 [View Article] [PubMed]
    [Google Scholar]
  92. Culp EJ, Waglechner N, Wang W, Fiebig-Comyn AA, Hsu Y-P et al. Evolution-guided discovery of antibiotics that inhibit peptidoglycan remodelling. Nature 2020; 578:582–587 [View Article] [PubMed]
    [Google Scholar]
  93. Zdouc MM, Alanjary MM, Zarazúa GS, Maffioli SI, Crüsemann M et al. A biaryl-linked tripeptide from Planomonospora reveals a widespread class of minimal RiPP gene clusters. Cell Chem Biol 2021; 28:733–739 [View Article]
    [Google Scholar]
  94. van der Hooft JJJ, Mohimani H, Bauermeister A, Dorrestein PC, Duncan KR et al. Linking genomics and metabolomics to chart specialized metabolic diversity. Chem Soc Rev 2020; 49:3297–3314 [View Article] [PubMed]
    [Google Scholar]
  95. Hjörleifsson EG, Andrew R, van der Hooft JJJ, Duncan KR, Sylvia S et al. Ranking microbial metabolomic and genomic links in the NPLinker framework using complementary scoring functions. bioRxiv 2020; 2020.06.12.148205:
    [Google Scholar]
  96. Ernst M, Kang KB, Caraballo-Rodríguez AM, Nothias L-F, Wandy J et al. MolNetEnhancer: Enhanced molecular networks by integrating metabolome mining and annotation tools. Metabolites 2019; 9:E144 [View Article]
    [Google Scholar]
  97. Medema MH, Kottmann R, Glöckner FO et al. The Minimum Information about a Biosynthetic Gene cluster (MIBiG) specification. Nat Chem Biol 2015; 11:625–631 [View Article]
    [Google Scholar]
  98. Waglechner N, McArthur AG, Wright GD. Phylogenetic reconciliation reveals the natural history of glycopeptide antibiotic biosynthesis and resistance. Nat Microbiol 2019; 4:1862–1871 [View Article] [PubMed]
    [Google Scholar]
  99. Blackman SA, Smith TJ, Foster SJ. The role of autolysins during vegetative growth of Bacillus subtilis 168. Microbiology 1998; 144:73–82 [View Article] [PubMed]
    [Google Scholar]
  100. Funk MA, van der Donk WA. Ribosomal natural products, tailored to fit. Acc Chem Res 2017; 50:1577–1586 [View Article] [PubMed]
    [Google Scholar]
  101. Zdouc MM, Iorio M, Maffioli SI, Crüsemann M, Donadio S et al. Planomonospora: A metabolomics perspective on an underexplored actinobacteria genus. J Nat Prod 2021; 84:204–219 [View Article]
    [Google Scholar]
  102. Chen CW, Huang CH, Lee HH, Tsai HH, 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]
  103. Zheren Z, Chao D, Frederique de B, Michael L, Apostolos L et al. Antibiotic production in Streptomyces is organized by a division of labour through terminal genomic differentiation. bioRxiv 20191–10
    [Google Scholar]
  104. Kelemen GH, Viollier PH, Tenor J, Marri L, Buttner MJ et al. A connection between stress and development in the multicellular prokaryote Streptomyces coelicolor A3(2). Mol Microbiol 2001; 40:804–814 [View Article] [PubMed]
    [Google Scholar]
  105. McLean TC, Lo R, Tschowri N, Hoskisson PA, Al Bassam MM et al. Sensing and responding to diverse extracellular signals: An updated analysis of the sensor kinases and response regulators of Streptomyces species. Microbiology 2019; 165:929–952 [View Article]
    [Google Scholar]
  106. McCormick JR, Flärdh K. Signals and regulators that govern Streptomyces development. FEMS Microbiol Rev 2012; 36:206–231 [View Article] [PubMed]
    [Google Scholar]
  107. Hutchings MI, Hoskisson PA, Chandra G, Buttner MJ. Sensing and responding to diverse extracellular signals? Analysis of the sensor kinases and response regulators of Streptomyces coelicolor A3(2). Microbiology 2004; 150:2795–2806 [View Article] [PubMed]
    [Google Scholar]
  108. Latoscha A, Wörmann ME, Tschowri N. Nucleotide second messengers in Streptomyces. Microbiology 2019; 165:1153–1165 [View Article]
    [Google Scholar]
  109. Haist J, Neumann SA, Al-Bassam MM, Lindenberg S, Elliot MA et al. Specialized and shared functions of diguanylate cyclases and phosphodiesterases in Streptomyces development. Mol Microbiol 2020; 114:808–822 [View Article] [PubMed]
    [Google Scholar]
  110. Dyson P, Schrempf H. Genetic instability and DNA amplification in Streptomyces lividans 66. J Bacteriol 1987; 169:4796–4803 [View Article] [PubMed]
    [Google Scholar]
  111. Bush MJ, Tschowri N, Schlimpert S, Flärdh K, Buttner MJ. C-di-GMP signalling and the regulation of developmental transitions in streptomycetes. Nat Rev Microbiol 2015; 13:749–760 [View Article] [PubMed]
    [Google Scholar]
  112. Tschowri N, Schumacher MA, Schlimpert S, Chinnam NB, Findlay KC et al. Tetrameric c-di-GMP mediates effective transcription factor dimerization to control Streptomyces development. Cell 2014; 158:1136–1147 [View Article] [PubMed]
    [Google Scholar]
  113. Gallagher KA, Schumacher MA, Bush MJ, Bibb MJ, Chandra G et al. c-di-GMP arms an anti-σ to control progression of multicellular differentiation in Streptomyces. Mol Cell 2020; 77:586–599 [View Article] [PubMed]
    [Google Scholar]
  114. Al-Bassam MM, Haist J, Neumann SA, Lindenberg S, Tschowri N. Expression patterns, genomic conservation and input into developmental regulation of the GGDEF/EAL/HD-GYP domain proteins in Streptomyces. Front Microbiol 2018; 9:1–11 [View Article]
    [Google Scholar]
  115. Jenal U, Reinders A, Lori C. Cyclic di-GMP: Second messenger extraordinaire. Nat Rev Microbiol 2017; 15:271–284 [View Article] [PubMed]
    [Google Scholar]
  116. Fernández-Martínez LT, Borsetto C, Gomez-Escribano JP, Bibb MJ, Al-Bassam MM et al. New insights into chloramphenicol biosynthesis in Streptomyces venezuelae ATCC 10712. Antimicrob Agents Chemother 2014; 58:7441–7450 [View Article] [PubMed]
    [Google Scholar]
  117. Makitrynskyy R, Tsypik O, Nuzzo D, Paululat T, Zechel DL et al. Secondary nucleotide messenger c-di-GMP exerts a global control on natural product biosynthesis in streptomycetes. Nucleic Acids Res 2020; 48:1583–1598 [View Article] [PubMed]
    [Google Scholar]
  118. van Wezel GP, McDowall KJ. The regulation of the secondary metabolism of Streptomyces: New links and experimental advances. Nat Prod Rep 2011; 28:1311–1333 [View Article] [PubMed]
    [Google Scholar]
  119. van der Heul HU, Bilyk BL, McDowall KJ, Seipke RF, van Wezel GP. Regulation of antibiotic production in Actinobacteria: new perspectives from the post-genomic era. Nat Prod Rep 2018; 35:575–604 [View Article] [PubMed]
    [Google Scholar]
  120. Seipke RF, Kaltenpoth M, Hutchings MI. Streptomyces as symbionts: An emerging and widespread theme?. FEMS Microbiol Rev 2012; 36:862–876 [View Article] [PubMed]
    [Google Scholar]
  121. Chhun A, Sousoni D, Aguiló-Ferretjans MDM, Song L, Corre C et al. Phytoplankton trigger the production of cryptic metabolites in the marine actinobacterium Salinispora tropica. Microb Biotechnol 2021; 14:291–306 [View Article] [PubMed]
    [Google Scholar]
  122. Becher PG, Verschut V, Bibb MJ, Bush MJ, Molnár BP et al. Developmentally regulated volatiles geosmin and 2-methylisoborneol attract a soil arthropod to Streptomyces bacteria promoting spore dispersal. Nat Microbiol 2020; 5:821–829 [View Article] [PubMed]
    [Google Scholar]
  123. Martin K. Actinobacteria as mutualists: general healthcare for insects?. Trends Microbiol 2009; 17:529–535 [View Article] [PubMed]
    [Google Scholar]
  124. Viaene T, Langendries S, Beirinckx S, Maes M, Goormachtig S. Rhizobacteria Growth-promoting. Streptomyces as a plant’s best friend? 20161–10
    [Google Scholar]
  125. Worsley SF, Newitt J, Rassbach J, Batey SFD, Holmes NA et al. Streptomyces endophytes promote host health and enhance growth across plant species. Appl Environ Microbiol 2020; 86:1–17 [View Article]
    [Google Scholar]
  126. Patin NV, Duncan KR, Dorrestein PC, Jensen PR. Competitive strategies differentiate closely related species of marine actinobacteria. ISME J 2016; 10:478–490 [View Article] [PubMed]
    [Google Scholar]
  127. Patin NV, Floros DJ, Hughes CC, Dorrestein PC, Jensen PR. The role of inter-species interactions in Salinispora specialized metabolism. Microbiology 2018; 164:946–955 [View Article]
    [Google Scholar]
  128. Gerber NN, Lechevalier HA. Geosmin, an earthly-smelling substance isolated from actinomycetes. Appl Microbiol 1965; 13:935–938 [View Article] [PubMed]
    [Google Scholar]
  129. Jiang J, He X, Cane DE. Biosynthesis of the earthy odorant geosmin by a bifunctional Streptomyces coelicolor enzyme. Nat Chem Biol 2007; 3:711–715 [View Article] [PubMed]
    [Google Scholar]
  130. Rabe P, Citron CA, Dickschat JS. Volatile terpenes from actinomycetes: A biosynthetic study correlating chemical analyses to genome data. ChemBioChem 2013; 14:2345–2354 [View Article] [PubMed]
    [Google Scholar]
  131. Al-Bassam MM, Bibb MJ, Bush MJ, Chandra G, Buttner MJ. Response regulator heterodimer formation controls a key stage in streptomyces development. PLoS Genet 2014; 10:e1004554 [View Article] [PubMed]
    [Google Scholar]
  132. Persson J, Chater KF, Flärdh K. Molecular and cytological analysis of the expression of Streptomyces sporulation regulatory gene whiH. FEMS Microbiol Lett 2013; 341:96–105 [View Article] [PubMed]
    [Google Scholar]
  133. Schrey SD, Tarkka MT. Friends and foes: Streptomycetes as modulators of plant disease and symbiosis. Antonie van Leeuwenhoek 2008; 94:11–19 [View Article]
    [Google Scholar]
  134. Bulgarelli D, Rott M, Schlaeppi K, Ver Loren van Themaat E, Ahmadinejad N et al. Revealing structure and assembly cues for Arabidopsis root-inhabiting bacterial microbiota. Nature 2012; 488:91–95 [View Article] [PubMed]
    [Google Scholar]
  135. Lundberg DS, Lebeis SL, Paredes SH, Yourstone S, Gehring J et al. Defining the core Arabidopsis thaliana root microbiome. Nature 2012; 488:86–90 [View Article] [PubMed]
    [Google Scholar]
http://instance.metastore.ingenta.com/content/journal/micro/10.1099/mic.0.001084
Loading
/content/journal/micro/10.1099/mic.0.001084
Loading

Data & Media loading...

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