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However, little attention has been given to the relationship between the secondary metabolites of actinobacteria and their stress responses compared to those of other bacteria. In this study, we examined the genomes of two\n                    <jats:italic>Streptomyces<\/jats:italic>\n                    species, along with nine reference genomes, to investigate the biosynthetic gene clusters (BGCs) responsible for secondary metabolite production, their potential roles in stress responses, and their functional diversity in this unique genus. Our approach included bioaccumulation and biosorption studies, complemented by analytical techniques such as scanning electron microscopy (SEM), energy-dispersive spectroscopy (EDS), Fourier transform infrared spectroscopy (FT-IR), and inductively coupled plasma-optical emission spectroscopy (ICP-OES). We observed strain-specific variations in tolerance to heavy metals, including zinc, cobalt, copper, and cadmium, which were validated by experimental studies across both genomes. This report represents the first genomic study of heavy metal resistance in\n                    <jats:italic>S. thermocarboxydus<\/jats:italic>\n                    , providing valuable insights into its potential applications for bioremediation in metal-contaminated environments.\n                  <\/jats:p>","DOI":"10.1007\/s11274-025-04703-1","type":"journal-article","created":{"date-parts":[[2025,12,2]],"date-time":"2025-12-02T08:17:28Z","timestamp":1764663448000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Comparative genomics of the Streptomyces genus: insights into multi-stress-resistant genes for bioremediation"],"prefix":"10.1007","volume":"41","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1150-8075","authenticated-orcid":false,"given":"Ajit Kumar","family":"Passari","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Carlos","family":"Caicedo-Montoya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Monserrat","family":"Manzo-Ruiz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mar\u00eda Paula","family":"Gomez-Roman","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Beatriz","family":"Ruiz-Villaf\u00e1n","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jos\u00e9 Fausto","family":"Rivero-Cruz","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bhim Pratap","family":"Singh","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Romina","family":"Rodr\u00edguez-Sanoja","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6350-5052","authenticated-orcid":false,"given":"Sergio","family":"Sanchez","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,12,2]]},"reference":[{"issue":"7","key":"4703_CR1","doi-asserted-by":"publisher","first-page":"2251","DOI":"10.1093\/bioinformatics\/btz859","volume":"36","author":"T Aramaki","year":"2020","unstructured":"Aramaki T, Blanc-Mathieu R, Endo H, Ohkubo K, Kanehisa M, Goto S, Valencia A (2020) KofamKOALA: KEGG ortholog assignment based on profile HMM and adaptive score threshold. 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