Review ArticleReview
Open Access

Microbiota-host interaction in colorectal cancer: emerging computational technology, multi-omics integration, and mechanisms

Yinghong Lu and Jun Yu
Cancer Biology & Medicine February 2026, 20250762; DOI: https://doi.org/10.20892/j.issn.2095-3941.2025.0762

References

  1. 1.↵
    2. Siegel RL,
    3. Giaquinto AN,
    4. Jemal A.
    Cancer statistics, 2024. CA Cancer J Clin. 2024; 74: 12–49.
    OpenUrlCrossRefPubMed
  2. 2.↵
    2. Janney A,
    3. Powrie F,
    4. Mann EH.
    Host-microbiota maladaptation in colorectal cancer. Nature. 2020; 585: 509–17.
    OpenUrlCrossRefPubMed
  3. 3.↵
    2. Wong CC,
    3. Yu J.
    Gut microbiota in colorectal cancer development and therapy. Nat Rev Clin Oncol. 2023; 20: 429–52.
    OpenUrlCrossRefPubMed
  4. 4.↵
    2. White MT,
    3. Sears CL.
    The microbial landscape of colorectal cancer. Nat Rev Microbiol. 2024; 22: 240–54.
    OpenUrlCrossRefPubMed
  5. 5.↵
    2. Wong SH,
    3. Zhao L,
    4. Zhang X,
    5. Nakatsu G,
    6. Han J,
    7. Xu W, et al.
    Gavage of fecal samples from patients with colorectal cancer promotes intestinal carcinogenesis in germ-free and conventional mice. Gastroenterology. 2017; 153: 1621–33.e6.
    OpenUrlCrossRefPubMed
  6. 6.↵
    2. Nakatsu G,
    3. Zhou H,
    4. Wu WKK,
    5. Wong SH,
    6. Coker OO,
    7. Dai Z, et al.
    Alterations in enteric virome are associated with colorectal cancer and survival outcomes. Gastroenterology. 2018; 155: 529–41.e5.
    OpenUrlCrossRefPubMed
  7. 7.
    2. Li T,
    3. Coker OO,
    4. Sun Y,
    5. Li S,
    6. Liu C,
    7. Lin Y, et al.
    Multi-cohort analysis reveals altered archaea in colorectal cancer fecal samples across populations. Gastroenterology. 2025; 168: 525–38.e2.
    OpenUrlCrossRefPubMed
  8. 8.↵
    2. Lin Y,
    3. Lau HC,
    4. Liu Y,
    5. Kang X,
    6. Wang Y,
    7. Ting NL, et al.
    Altered mycobiota signatures and enriched pathogenic aspergillus rambellii are associated with colorectal cancer based on multicohort fecal metagenomic analyses. Gastroenterology. 2022; 163: 908–21.
    OpenUrlCrossRefPubMed
  9. 9.↵
    2. Long X,
    3. Wong CC,
    4. Tong L,
    5. Chu ESH,
    6. Ho Szeto C,
    7. Go MYY, et al.
    Peptostreptococcus anaerobius promotes colorectal carcinogenesis and modulates tumour immunity. Nat Microbiol. 2019; 4: 2319–30.
    OpenUrlPubMed
  10. 10.↵
    2. Rubinstein MR,
    3. Wang X,
    4. Liu W,
    5. Hao Y,
    6. Cai G,
    7. Han YW.
    Fusobacterium nucleatum promotes colorectal carcinogenesis by modulating E-cadherin/β-catenin signaling via its FadA adhesin. Cell Host Microbe. 2013; 14: 195–206.
    OpenUrlCrossRefPubMedWeb of Science
  11. 11.↵
    2. Rubinstein MR,
    3. Baik JE,
    4. Lagana SM,
    5. Han RP,
    6. Raab WJ,
    7. Sahoo D, et al.
    Fusobacterium nucleatum promotes colorectal cancer by inducing Wnt/β-catenin modulator Annexin A1. EMBO Rep. 2019; 20: e47638.
  12. 12.↵
    2. Zhang M,
    3. Liu K.
    Mechanisms of lipopolysaccharide-driven progression and metastasis of colorectal cancer. Int J Biol Macromol. 2025; 329: 147856.
  13. 13.↵
    2. Cong J,
    3. Liu P,
    4. Han Z,
    5. Ying W,
    6. Li C,
    7. Yang Y, et al.
    Bile acids modified by the intestinal microbiota promote colorectal cancer growth by suppressing CD8+ T cell effector functions. Immunity. 2024; 57: 876–89.e11.
    OpenUrlCrossRefPubMed
  14. 14.↵
    2. Jalandra R,
    3. Dalal N,
    4. Yadav AK,
    5. Verma D,
    6. Sharma M,
    7. Singh R, et al.
    Emerging role of trimethylamine-N-oxide (TMAO) in colorectal cancer. Appl Microbiol Biotechnol. 2021; 105: 7651–60.
    OpenUrlCrossRef
  15. 15.↵
    Integrative HMP (iHMP) Research Network Consortium. The Integrative Human Microbiome Project. Nature. 2019; 569: 641–48.
    OpenUrlCrossRefPubMed
  16. 16.↵
    2. Sun Y,
    3. Zhang X,
    4. Hang D,
    5. Lau HC,
    6. Du J,
    7. Liu C, et al.
    Integrative plasma and fecal metabolomics identify functional metabolites in adenoma-colorectal cancer progression and as early diagnostic biomarkers. Cancer Cell. 2024; 42: 1386–400.e8.
    OpenUrlPubMed
  17. 17.↵
    2. Bertocchi A,
    3. Carloni S,
    4. Ravenda PS,
    5. Bertalot G,
    6. Spadoni I,
    7. Lo Cascio A, et al.
    Gut vascular barrier impairment leads to intestinal bacteria dissemination and colorectal cancer metastasis to liver. Cancer Cell. 2021; 39: 708–24.e11.
    OpenUrlCrossRefPubMed
  18. 18.↵
    2. Liu W,
    3. Zhang X,
    4. Xu H,
    5. Li S,
    6. Lau HC,
    7. Chen Q, et al.
    Microbial community heterogeneity within colorectal neoplasia and its correlation with colorectal carcinogenesis. Gastroenterology. 2021; 160: 2395–408.
    OpenUrlCrossRefPubMed
  19. 19.↵
    2. Dziubańska-Kusibab PJ,
    3. Berger H,
    4. Battistini F,
    5. Bouwman BAM,
    6. Iftekhar A,
    7. Katainen R, et al.
    Colibactin DNA-damage signature indicates mutational impact in colorectal cancer. Nat Med. 2020; 26: 1063–69.
    OpenUrlCrossRefPubMed
  20. 20.↵
    2. Kadosh E,
    3. Snir-Alkalay I,
    4. Venkatachalam A,
    5. May S,
    6. Lasry A,
    7. Elyada E, et al.
    The gut microbiome switches mutant p53 from tumour-suppressive to oncogenic. Nature. 2020; 586: 133–38.
    OpenUrlCrossRefPubMed
  21. 21.↵
    2. Chen Y,
    3. Liu S,
    4. Tan S,
    5. Zheng Y,
    6. Chen Y,
    7. Yang C, et al.
    KRAS mutations promote the intratumoral colonization of enterotoxigenic bacteroides fragilis in colorectal cancer through the regulation of the miRNA3655/SURF6/IRF7/IFNβ axis. Gut Microbes. 2024; 16: 2423043.
  22. 22.↵
    2. Zhu H,
    3. Li M,
    4. Bi D,
    5. Yang H,
    6. Gao Y,
    7. Song F, et al.
    Fusobacterium nucleatum promotes tumor progression in KRAS p.G12D-mutant colorectal cancer by binding to DHX15. Nat Commun. 2024; 15: 1688.
    OpenUrlPubMed
  23. 23.↵
    2. Li D,
    3. Zhong C,
    4. Yang M,
    5. He L,
    6. Chang H,
    7. Zhu N, et al.
    Genetic and microbial determinants of azoxymethane-induced colorectal tumor susceptibility in Collaborative Cross mice and their implication in human cancer. Gut Microbes. 2024; 16: 2341647.
  24. 24.↵
    2. Zou S,
    3. Yang C,
    4. Zhang J,
    5. Zhong D,
    6. Meng M,
    7. Zhang L, et al.
    Multi-omic profiling reveals associations between the gut microbiome, host genome and transcriptome in patients with colorectal cancer. J Transl Med. 2024; 22: 175.
    OpenUrlPubMed
  25. 25.↵
    2. Galeano Niño JL,
    3. Wu H,
    4. LaCourse KD,
    5. Kempchinsky AG,
    6. Baryiames A,
    7. Barber B, et al.
    Effect of the intratumoral microbiota on spatial and cellular heterogeneity in cancer. Nature. 2022; 611: 810–17.
    OpenUrlCrossRefPubMed
  26. 26.↵
    2. Hong J,
    3. Guo F,
    4. Lu SY,
    5. Shen C,
    6. Ma D,
    7. Zhang X, et al.
    F. nucleatum targets lncRNA ENO1-IT1 to promote glycolysis and oncogenesis in colorectal cancer. Gut. 2021; 70: 2123–37.
    OpenUrlAbstract/FREE Full Text
  27. 27.↵
    2. Yu T,
    3. Guo F,
    4. Yu Y,
    5. Sun T,
    6. Ma D,
    7. Han J, et al.
    Fusobacterium nucleatum promotes chemoresistance to colorectal cancer by modulating autophagy. Cell. 2017; 170: 548–63.e16.
    OpenUrlCrossRefPubMed
  28. 28.↵
    2. Ansari I,
    3. Raddatz G,
    4. Gutekunst J,
    5. Ridnik M,
    6. Cohen D,
    7. Abu-Remaileh M, et al.
    The microbiota programs DNA methylation to control intestinal homeostasis and inflammation. Nat Microbiol. 2020; 5: 610–19.
    OpenUrlPubMed
  29. 29.↵
    2. Xia X,
    3. Wu WKK,
    4. Wong SH,
    5. Liu D,
    6. Kwong TNY,
    7. Nakatsu G, et al.
    Bacteria pathogens drive host colonic epithelial cell promoter hypermethylation of tumor suppressor genes in colorectal cancer. Microbiome. 2020; 8: 108.
    OpenUrlCrossRefPubMed
  30. 30.↵
    2. Liu Z,
    3. Zhang Q,
    4. Zhang H,
    5. Yi Z,
    6. Ma H,
    7. Wang X, et al.
    Colorectal cancer microbiome programs DNA methylation of host cells by affecting methyl donor metabolism. Genome Med. 2024; 16: 77.
    OpenUrlPubMed
  31. 31.↵
    2. Chen S,
    3. Zhang L,
    4. Li M,
    5. Zhang Y,
    6. Sun M,
    7. Wang L, et al.
    Fusobacterium nucleatum reduces METTL3-mediated m6A modification and contributes to colorectal cancer metastasis. Nat Commun. 2022; 13: 1248.
    OpenUrlCrossRefPubMed
  32. 32.↵
    2. Gao R,
    3. Wu C,
    4. Zhu Y,
    5. Kong C,
    6. Zhu Y,
    7. Gao Y, et al.
    Integrated analysis of colorectal cancer reveals cross-cohort gut microbial signatures and associated serum metabolites. Gastroenterology. 2022; 163: 1024–37.e9.
    OpenUrlCrossRefPubMed
  33. 33.↵
    2. Xu S,
    3. Zhang Y,
    4. Ding X,
    5. Yang Y,
    6. Gao J,
    7. Zou N, et al.
    Intestinal microbiota affects the progression of colorectal cancer by participating in the host intestinal arginine catabolism. Cell Rep. 2025; 44: 115370.
  34. 34.↵
    2. Chen H,
    3. Tong T,
    4. Lu SY,
    5. Ji L,
    6. Xuan B,
    7. Zhao G, et al.
    Urea cycle activation triggered by host-microbiota maladaptation driving colorectal tumorigenesis. Cell Metab. 2023; 35: 651–66.e7.
    OpenUrlPubMed
  35. 35.↵
    2. Liu H,
    3. Du J,
    4. Chao S,
    5. Li S,
    6. Cai H,
    7. Zhang H, et al.
    Fusobacterium nucleatum promotes colorectal cancer cell to acquire stem cell-like features by manipulating lipid droplet-mediated numb degradation. Adv Sci (Weinh). 2022; 9: e2105222.
  36. 36.↵
    2. Pleguezuelos-Manzano C,
    3. Puschhof J,
    4. Rosendahl Huber A,
    5. van Hoeck A,
    6. Wood HM,
    7. Nomburg J, et al.
    Mutational signature in colorectal cancer caused by genotoxic pks+ E. coli. Nature. 2020; 580: 269–73.
    OpenUrlCrossRefPubMed
  37. 37.↵
    2. Wilson MR,
    3. Jiang Y,
    4. Villalta PW,
    5. Stornetta A,
    6. Boudreau PD,
    7. Carrá A, et al.
    The human gut bacterial genotoxin colibactin alkylates DNA. Science. 2019; 363: eaar7785.
  38. 38.↵
    2. Cornish AJ,
    3. Gruber AJ,
    4. Kinnersley B,
    5. Chubb D,
    6. Frangou A,
    7. Caravagna G, et al.
    The genomic landscape of 2,023 colorectal cancers. Nature. 2024; 633: 127–36.
    OpenUrlCrossRefPubMed
  39. 39.↵
    2. Boleij A,
    3. Hechenbleikner EM,
    4. Goodwin AC,
    5. Badani R,
    6. Stein EM,
    7. Lazarev MG, et al.
    The bacteroides fragilis toxin gene is prevalent in the colon mucosa of colorectal cancer patients. Clin Infect Dis. 2015; 60: 208–15.
    OpenUrlCrossRefPubMed
  40. 40.↵
    2. Goodwin AC,
    3. Destefano Shields CE,
    4. Wu S,
    5. Huso DL,
    6. Wu X,
    7. Murray-Stewart TR, et al.
    Polyamine catabolism contributes to enterotoxigenic bacteroides fragilis-induced colon tumorigenesis. Proc Natl Acad Sci U S A. 2011; 108: 15354–9.
    OpenUrlAbstract/FREE Full Text
  41. 41.↵
    2. Liebl MC,
    3. Hofmann TG.
    The role of p53 signaling in colorectal cancer. Cancers (Basel). 2021; 13: 2125.
    OpenUrlPubMed
  42. 42.↵
    2. Wei J,
    3. Nagy TA,
    4. Vilgelm A,
    5. Zaika E,
    6. Ogden SR,
    7. Romero-Gallo J, et al.
    Regulation of p53 tumor suppressor by Helicobacter pylori in gastric epithelial cells. Gastroenterology. 2010; 139: 1333–43.
    OpenUrlCrossRefPubMedWeb of Science
  43. 43.↵
    2. DeStefano Shields CE,
    3. White JR,
    4. Chung L,
    5. Wenzel A,
    6. Hicks JL,
    7. Tam AJ, et al.
    Bacterial-driven inflammation and mutant BRAF expression combine to promote murine colon tumorigenesis that is sensitive to immune checkpoint therapy. Cancer Discov. 2021; 11: 1792–807.
    OpenUrlAbstract/FREE Full Text
  44. 44.↵
    2. Hughes DA,
    3. Bacigalupe R,
    4. Wang J,
    5. Rühlemann MC,
    6. Tito RY,
    7. Falony G, et al.
    Genome-wide associations of human gut microbiome variation and implications for causal inference analyses. Nat Microbiol. 2020; 5: 1079–87.
    OpenUrlPubMed
  45. 45.↵
    2. Yu J,
    3. Liang Y,
    4. Zhang Q,
    5. Ding H,
    6. Xie M,
    7. Zhang J, et al.
    An interplay between human genetics and intratumoral microbiota in the progression of colorectal cancer. Cell Host Microbe. 2025; 33: 657–70.e6.
    OpenUrlPubMed
  46. 46.↵
    2. Xiang Y,
    3. Zhang C,
    4. Wang J,
    5. Cheng Y,
    6. Wang L,
    7. Tong Y, et al.
    Identification of host gene-microbiome associations in colorectal cancer patients using mendelian randomization. J Transl Med. 2023; 21: 535.
    OpenUrlCrossRefPubMed
  47. 47.↵
    2. Richards AL,
    3. Muehlbauer AL,
    4. Alazizi A,
    5. Burns MB,
    6. Findley A,
    7. Messina F, et al.
    Gut microbiota has a widespread and modifiable effect on host gene regulation. mSystems. 2019; 4: e00323-18.
  48. 48.↵
    2. Flemer B,
    3. Lynch DB,
    4. Brown JM,
    5. Jeffery IB,
    6. Ryan FJ,
    7. Claesson MJ, et al.
    Tumour-associated and non-tumour-associated microbiota in colorectal cancer. Gut. 2017; 66: 633–43.
    OpenUrlAbstract/FREE Full Text
  49. 49.↵
    2. Lötstedt B,
    3. Stražar M,
    4. Xavier R,
    5. Regev A,
    6. Vickovic S.
    Spatial host-microbiome sequencing reveals niches in the mouse gut. Nat Biotechnol. 2024; 42: 1394–403.
    OpenUrlCrossRefPubMed
  50. 50.↵
    2. Wang M,
    3. Liu K,
    4. Bao W,
    5. Hang B,
    6. Chen X,
    7. Zhu X, et al.
    Gut microbiota protect against colorectal tumorigenesis through lncRNA Snhg9. Dev Cell. 2025; 60: 1008–17.e7.
    OpenUrlPubMed
  51. 51.↵
    2. Tian S,
    3. Chen M.
    Global research progress of gut microbiota and epigenetics: bibliometrics and visualized analysis. Front Immunol. 2024; 15: 1412640.
  52. 52.↵
    2. Pepke ML,
    3. Hansen SB,
    4. Limborg MT.
    Unraveling host regulation of gut microbiota through the epigenome-microbiome axis. Trends Microbiol. 2024; 32: 1229–40.
    OpenUrlPubMed
  53. 53.↵
    2. Sobhani I,
    3. Bergsten E,
    4. Couffin S,
    5. Amiot A,
    6. Nebbad B,
    7. Barau C, et al.
    Colorectal cancer-associated microbiota contributes to oncogenic epigenetic signatures. Proc Natl Acad Sci U S A. 2019; 116: 24285–95.
    OpenUrlAbstract/FREE Full Text
  54. 54.↵
    2. Koi M,
    3. Okita Y,
    4. Carethers JM.
    Fusobacterium nucleatum infection in colorectal cancer: Linking inflammation, DNA mismatch repair and genetic and epigenetic alterations. J Anus Rectum Colon. 2018; 2: 37–46.
    OpenUrlPubMed
  55. 55.↵
    2. Zhang K,
    3. Dong Y,
    4. Li M,
    5. Zhang W,
    6. Ding Y,
    7. Wang X, et al.
    Clostridium butyricum inhibits epithelial-mesenchymal transition of intestinal carcinogenesis through downregulating METTL3. Cancer Sci. 2023; 114: 3114–27.
    OpenUrlPubMed
  56. 56.↵
    2. Zhu W,
    3. Si Y,
    4. Xu J,
    5. Lin Y,
    6. Wang JZ,
    7. Cao M, et al.
    Methyltransferase like 3 promotes colorectal cancer proliferation by stabilizing CCNE1 mRNA in an m6A-dependent manner. J Cell Mol Med. 2020; 24: 3521–33.
    OpenUrlPubMed
  57. 57.↵
    2. Tsoi H,
    3. Chu ESH,
    4. Zhang X,
    5. Sheng J,
    6. Nakatsu G,
    7. Ng SC, et al.
    Peptostreptococcus anaerobius induces intracellular cholesterol biosynthesis in colon cells to induce proliferation and causes dysplasia in mice. Gastroenterology. 2017; 152: 1419–33.e5.
    OpenUrlCrossRefPubMed
  58. 58.↵
    2. Wirbel J,
    3. Pyl PT,
    4. Kartal E,
    5. Zych K,
    6. Kashani A,
    7. Milanese A, et al.
    Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat Med. 2019; 25: 679–89.
    OpenUrlCrossRefPubMed
  59. 59.↵
    2. Devkota S,
    3. Wang Y,
    4. Musch MW,
    5. Leone V,
    6. Fehlner-Peach H,
    7. Nadimpalli A, et al.
    Dietary-fat-induced taurocholic acid promotes pathobiont expansion and colitis in IL10−/− mice. Nature. 2012; 487: 104–8.
    OpenUrlCrossRefPubMedWeb of Science
  60. 60.↵
    2. Armstrong G,
    3. Rahman G,
    4. Martino C,
    5. McDonald D,
    6. Gonzalez A,
    7. Mishne G, et al.
    Applications and comparison of dimensionality reduction methods for microbiome data. Front Bioinform. 2022; 2: 821861.
  61. 61.↵
    2. Jolliffe IT,
    3. Cadima J.
    Principal component analysis: a review and recent developments. Philos Trans A Math Phys Eng Sci. 2016; 374: 20150202.
  62. 62.↵
    2. Yang Y,
    3. Sun H,
    4. Zhang Y,
    5. Zhang T,
    6. Gong J,
    7. Wei Y, et al.
    Dimensionality reduction by UMAP reinforces sample heterogeneity analysis in bulk transcriptomic data. Cell Rep. 2021; 36: 109442.
  63. 63.↵
    2. Xu X,
    3. Xie Z,
    4. Yang Z,
    5. Li D,
    6. Xu X.
    A t-SNE based classification approach to compositional microbiome data. Front Genet. 2020; 11: 620143.
  64. 64.↵
    2. Shi Y,
    3. Zhang L,
    4. Peterson CB,
    5. Do KA,
    6. Jenq RR.
    Performance determinants of unsupervised clustering methods for microbiome data. Microbiome. 2022; 10: 25.
    OpenUrlPubMed
  65. 65.↵
    2. Berrazeg M,
    3. Drissi M,
    4. Medjahed L,
    5. Rolain JM.
    Hierarchical clustering as a rapid tool for surveillance of emerging antibiotic-resistance phenotypes in Klebsiella pneumoniae strains. J Med Microbiol. 2013; 62: 864–74.
    OpenUrlCrossRefPubMed
  66. 66.↵
    2. Koo HK,
    3. Min J,
    4. Kim HW,
    5. Ko Y,
    6. Oh JY,
    7. Jeong YJ, et al.
    Cluster analysis categorizes five phenotypes of pulmonary tuberculosis. Sci Rep. 2022; 12: 10084.
  67. 67.↵
    2. Arumugam M,
    3. Raes J,
    4. Pelletier E,
    5. Le Paslier D,
    6. Yamada T,
    7. Mende DR, et al.
    Enterotypes of the human gut microbiome. Nature. 2011; 473: 174–80.
    OpenUrlCrossRefPubMedWeb of Science
  68. 68.↵
    2. Guinney J,
    3. Dienstmann R,
    4. Wang X,
    5. de Reyniès A,
    6. Schlicker A,
    7. Soneson C, et al.
    The consensus molecular subtypes of colorectal cancer. Nat Med. 2015; 21: 1350–6.
    OpenUrlCrossRefPubMed
  69. 69.↵
    2. Salvucci M,
    3. Crawford N,
    4. Stott K,
    5. Bullman S,
    6. Longley DB,
    7. Prehn JHM.
    Patients with mesenchymal tumours and high Fusobacteriales prevalence have worse prognosis in colorectal cancer (CRC). Gut. 2022; 71: 1600–12.
    OpenUrlAbstract/FREE Full Text
  70. 70.↵
    2. Mouradov D,
    3. Greenfield P,
    4. Li S,
    5. In EJ,
    6. Storey C,
    7. Sakthianandeswaren A, et al.
    Oncomicrobial community profiling identifies clinicomolecular and prognostic subtypes of colorectal cancer. Gastroenterology. 2023; 165: 104–20.
    OpenUrlCrossRefPubMed
  71. 71.↵
    2. Zhu X,
    3. Hu M,
    4. Huang X,
    5. Li L,
    6. Lin X,
    7. Shao X, et al.
    Interplay between gut microbial communities and metabolites modulates pan-cancer immunotherapy responses. Cell Metab. 2025; 37: 806–23.e6.
    OpenUrlPubMed
  72. 72.↵
    2. Priya S,
    3. Burns MB,
    4. Ward T,
    5. Mars RAT,
    6. Adamowicz B,
    7. Lock EF, et al.
    Identification of shared and disease-specific host gene-microbiome associations across human diseases using multi-omic integration. Nat Microbiol. 2022; 7: 780–95.
    OpenUrlPubMed
  73. 73.↵
    2. Quilodrán CS,
    3. Currat M,
    4. Montoya-Burgos JI.
    Benchmarking the Mantel test and derived methods for testing association between distance matrices. Mol Ecol Resour. 2025; 25: e13898.
  74. 74.↵
    2. Mallick H,
    3. Rahnavard A,
    4. McIver LJ,
    5. Ma S,
    6. Zhang Y,
    7. Nguyen LH, et al.
    Multivariable association discovery in population-scale meta-omics studies. PLoS Comput Biol. 2021; 17: e1009442.
  75. 75.↵
    2. Marcos-Zambrano LJ,
    3. Karaduzovic-Hadziabdic K,
    4. Loncar Turukalo T,
    5. Przymus P,
    6. Trajkovik V,
    7. Aasmets O, et al.
    Applications of machine learning in human microbiome studies: a review on feature selection, biomarker identification, disease prediction and treatment. Front Microbiol. 2021; 12: 634511.
  76. 76.↵
    2. Coker OO,
    3. Liu C,
    4. Wu WKK,
    5. Wong SH,
    6. Jia W,
    7. Sung JJY, et al.
    Altered gut metabolites and microbiota interactions are implicated in colorectal carcinogenesis and can be non-invasive diagnostic biomarkers. Microbiome. 2022; 10: 35.
    OpenUrlCrossRefPubMed
  77. 77.↵
    2. Lo C,
    3. Marculescu R.
    MetaNN: Accurate classification of host phenotypes from metagenomic data using neural networks. BMC Bioinformatics. 2019; 20: 314.
    OpenUrlCrossRefPubMed
  78. 78.↵
    2. Bodein A,
    3. Scott-Boyer MP,
    4. Perin O,
    5. Lê Cao KA,
    6. Droit A.
    Interpretation of network-based integration from multi-omics longitudinal data. Nucleic Acids Res. 2022; 50: e27.
  79. 79.↵
    2. Silva-García O,
    3. Valdez-Alarcón JJ,
    4. Baizabal-Aguirre VM.
    Wnt/β-catenin signaling as a molecular target by pathogenic bacteria. Front Immunol. 2019; 10: 2135.
    OpenUrlCrossRefPubMed
  80. 80.↵
    2. Dai Z,
    3. Coker OO,
    4. Nakatsu G,
    5. Wu WKK,
    6. Zhao L,
    7. Chen Z, et al.
    Multi-cohort analysis of colorectal cancer metagenome identified altered bacteria across populations and universal bacterial markers. Microbiome. 2018; 6: 70.
    OpenUrlCrossRefPubMed
  81. 81.↵
    2. Quinn TP,
    3. Erb I,
    4. Richardson MF,
    5. Crowley TM.
    Understanding sequencing data as compositions: an outlook and review. Bioinformatics. 2018; 34: 2870–78.
    OpenUrlCrossRefPubMed
  82. 82.↵
    2. Lin H,
    3. Peddada SD.
    Analysis of microbial compositions: a review of normalization and differential abundance analysis. NPJ Biofilms Microbiomes. 2020; 6: 60.
    OpenUrlPubMed
  83. 83.↵
    2. Weiss S,
    3. Xu ZZ,
    4. Peddada S,
    5. Amir A,
    6. Bittinger K,
    7. Gonzalez A, et al.
    Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome. 2017; 5: 27.
    OpenUrlCrossRefPubMed
  84. 84.↵
    2. Gounot JS,
    3. Chia M,
    4. Bertrand D,
    5. Saw WY,
    6. Ravikrishnan A,
    7. Low A, et al.
    Genome-centric analysis of short and long read metagenomes reveals uncharacterized microbiome diversity in Southeast Asians. Nat Commun. 2022; 13: 6044.
    OpenUrlCrossRefPubMed
  85. 85.↵
    2. Moss EL,
    3. Maghini DG,
    4. Bhatt AS.
    Complete, closed bacterial genomes from microbiomes using nanopore sequencing. Nat Biotechnol. 2020; 38: 701–7.
    OpenUrlCrossRefPubMed
  86. 86.↵
    2. Tamburini FB,
    3. Maghini D,
    4. Oduaran OH,
    5. Brewster R,
    6. Hulley MR,
    7. Sahibdeen V, et al.
    Short- and long-read metagenomics of urban and rural South African gut microbiomes reveal a transitional composition and undescribed taxa. Nat Commun. 2022; 13: 926.
    OpenUrlCrossRefPubMed
  87. 87.↵
    2. Lai S,
    3. Wang H,
    4. Bork P,
    5. Chen WH,
    6. Zhao XM.
    Long-read sequencing reveals extensive gut phageome structural variations driven by genetic exchange with bacterial hosts. Sci Adv. 2024; 10: eadn3316.
  88. 88.↵
    2. Slizovskiy IB,
    3. Oliva M,
    4. Settle JK,
    5. Zyskina LV,
    6. Prosperi M,
    7. Boucher C, et al.
    Target-enriched long-read sequencing (TELSeq) contextualizes antimicrobial resistance genes in metagenomes. Microbiome. 2022; 10: 185.
    OpenUrlCrossRefPubMed
  89. 89.↵
    2. Zheng W,
    3. Zhao S,
    4. Yin Y,
    5. Zhang H,
    6. Needham DM,
    7. Evans ED, et al.
    High-throughput, single-microbe genomics with strain resolution, applied to a human gut microbiome. Science. 2022; 376: eabm1483.
  90. 90.↵
    2. Wu Y,
    3. Zhuang J,
    4. Song Y,
    5. Gao X,
    6. Chu J,
    7. Han S.
    Advances in single-cell sequencing technology in microbiome research. Genes Dis. 2024; 11: 101129.
  91. 91.↵
    2. Sarfatis A,
    3. Wang Y,
    4. Twumasi-Ankrah N,
    5. Moffitt JR.
    Highly multiplexed spatial transcriptomics in bacteria. Science. 2025; 387: eadr0932.
  92. 92.↵
    2. Zhang Y,
    3. Song W,
    4. Zhou L,
    5. Wei S,
    6. Xu L,
    7. Li X, et al.
    Bacteria-metabolite butyrate boosts anti-PD1 efficacy in colorectal cancer patient-derived organoids through activating autologous tumour-infiltrating GNLY+CD8+ T cells. Gut. 2025; 74: 1755–58.
    OpenUrlFREE Full Text
  93. 93.↵
    2. Ugolini GS,
    3. Wang M,
    4. Secchi E,
    5. Pioli R,
    6. Ackermann M,
    7. Stocker R.
    Microfluidic approaches in microbial ecology. Lab Chip. 2024; 24: 1394–418.
    OpenUrlCrossRefPubMed
  94. 94.↵
    2. Asnicar F,
    3. Thomas AM,
    4. Passerini A,
    5. Waldron L,
    6. Segata N.
    Machine learning for microbiologists. Nat Rev Microbiol. 2024; 22: 191–205.
    OpenUrlCrossRefPubMed
  95. 95.↵
    2. Zhou T,
    3. Zhao F.
    AI-empowered human microbiome research. Gut. 2025 doi:10.1136/gutjnl-2025-335946
    OpenUrlAbstract/FREE Full Text
  96. 96.↵
    2. Wang Y,
    3. Zhao L,
    4. Li Z,
    5. Xi Y,
    6. Pan Y,
    7. Zhao G, et al.
    A generative artificial intelligence approach for the discovery of antimicrobial peptides against multidrug-resistant bacteria. Nat Microbiol. 2025; 10: 2997–3012.
    OpenUrlPubMed
  97. 97.↵
    2. Novielli P,
    3. Romano D,
    4. Magarelli M,
    5. Bitonto PD,
    6. Diacono D,
    7. Chiatante A, et al.
    Explainable artificial intelligence for microbiome data analysis in colorectal cancer biomarker identification. Front Microbiol. 2024; 15: 1348974.
  98. 98.↵
    2. Rynazal R,
    3. Fujisawa K,
    4. Shiroma H,
    5. Salim F,
    6. Mizutani S,
    7. Shiba S, et al.
    Leveraging explainable AI for gut microbiome-based colorectal cancer classification. Genome Biol. 2023; 24: 21.
    OpenUrlCrossRefPubMed
  99. 99.↵
    2. Caminero A,
    3. Tropini C,
    4. Valles-Colomer M,
    5. Shung DL,
    6. Gibbons SM,
    7. Surette MG, et al.
    Credible inferences in microbiome research: ensuring rigour, reproducibility and relevance in the era of AI. Nat Rev Gastroenterol Hepatol. 2025; 22: 788–803.
    OpenUrlPubMed
  100. 100.↵
    2. Ding X,
    3. Ting NL,
    4. Wong CC,
    5. Huang P,
    6. Jiang L,
    7. Liu C, et al.
    Bacteroides fragilis promotes chemoresistance in colorectal cancer, and its elimination by phage VA7 restores chemosensitivity. Cell Host Microbe. 2025; 33: 941–56.e10.
    OpenUrlPubMed
  101. 101.↵
    2. Kuntz TM,
    3. Gilbert JA.
    Introducing the microbiome into precision medicine. Trends Pharmacol Sci. 2017; 38: 81–91.
    OpenUrlCrossRef
  102. 102.↵
    2. Lam KN,
    3. Alexander M,
    4. Turnbaugh PJ.
    Precision medicine goes microscopic: engineering the microbiome to improve drug outcomes. Cell Host Microbe. 2019; 26: 22–34.
    OpenUrlCrossRefPubMed
  103. 103.↵
    2. Gurbatri CR,
    3. Arpaia N,
    4. Danino T.
    Engineering bacteria as interactive cancer therapies. Science. 2022; 378: 858–64.
    OpenUrlCrossRefPubMed
  104. 104.↵
    2. Liu S,
    3. Rodriguez JS,
    4. Munteanu V,
    5. Ronkowski C,
    6. Sharma NK,
    7. Alser M, et al.
    Analysis of metagenomic data. Nat Rev Methods Primers. 2025; 5: 5.
    OpenUrlPubMed
Back to top

In this issue

Print
Download PDF
Email Article
Citation Tools

Jump to section

Keywords