{
  "abstract": "Bacterial responses to antimicrobial drugs are strongly influenced by environmental conditions, yet how drugs systematically reshape the contribution of individual nutrients across different growth phases remains poorly understood. Here, we investigated medium–drug interactions in Escherichia coli BW25113 using around 177 chemically defined media and six drug conditions, generating thousands of growth profiles. Lag time (t), growth rate (r), and carrying capacity (K) were analyzed to characterize responses across growth phases. By integrating large-scale growth profiling with machine learning, we quantitatively mapped how 41 medium components contributed to bacterial growth under different drug conditions. Drug exposure substantially reorganized these nutritional contributions and generally increased the number of components involved in determining growth, particularly for r and K. Glucose, isoleucine, K+, and PO₄3− emerged as common determinants, whereas their relative contributions changed with drug exposure. Importantly, drug-induced nutritional reorganization was both growth phase- and drug-specific: decreased contributions were enriched in amino acids, whereas increased contributions involved diverse nutritional categories, particularly metal ions. Thus, rather than viewing drug susceptibility as a fixed bacterial phenotype, our study provides a quantitative framework showing that antimicrobial responses emerge from dynamic interactions among drugs, nutrients, and growth phases.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "Original Research",
  "arxiv": null,
  "author_total": 3,
  "authors": [
    {
      "name": "Taro Kawano"
    },
    {
      "name": "Shunpei Araki"
    },
    {
      "name": "Bei-Wen Ying"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/51pt2ac38c47j.bib",
  "cited_by": 0,
  "doi": "10.3389/fmicb.2026.2016025",
  "fulltext_url": null,
  "id": "51pt2ac38c47j",
  "issns": [
    "1664-302X"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fmicb.2026.2016025",
  "language": null,
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "feed-journal",
      "biology/microbiology"
    ]
  ],
  "openalex": null,
  "pdf_url": null,
  "pmcid": null,
  "pmid": null,
  "published": "2026-11-05",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/51pt2ac38c47j.ris",
  "sources": [
    {
      "first_seen": "2026-11-05T12:20:12Z",
      "native_id": "10.3389/fmicb.2026.2016025",
      "source": "feed-frontiers",
      "url": "https://www.frontiersin.org/articles/10.3389/fmicb.2026.2016025"
    },
    {
      "first_seen": "2026-11-05T12:21:09Z",
      "native_id": "10.3389/fmicb.2026.2016025",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fmicb.2026.2016025/full"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "feed-journal:biology/microbiology",
      "subfield": "microbiology"
    }
  ],
  "title": "Data-driven investigation of bacterial growth dynamics in response to the medium-drug interplay",
  "title_text": "Data-driven investigation of bacterial growth dynamics in response to the medium-drug interplay",
  "type": "peer-reviewed",
  "updated_at": "2026-11-07T00:21:16Z",
  "url": "https://research.draconitic.com/paper/51pt2ac38c47j",
  "venue": "Frontiers in Microbiology",
  "versions": []
}