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Persistent metagenomic signatures of early-life hospitalization and antibiotic treatment in the infant gut microbiota and resistome

Abstract

Hospitalized preterm infants receive frequent and often prolonged exposures to antibiotics because they are vulnerable to infection. It is not known whether the short-term effects of antibiotics on the preterm infant gut microbiota and resistome persist after discharge from neonatal intensive care units. Here, we use complementary metagenomic, culture-based and machine learning techniques to study the gut microbiota and resistome of antibiotic-exposed preterm infants during and after hospitalization, and we compare these readouts to antibiotic-naive healthy infants sampled synchronously. We find a persistently enriched gastrointestinal antibiotic resistome, prolonged carriage of multidrug-resistant Enterobacteriaceae and distinct antibiotic-driven patterns of microbiota and resistome assembly in extremely preterm infants that received early-life antibiotics. The collateral damage of early-life antibiotic treatment and hospitalization in preterm infants is long lasting. We urge the development of strategies to reduce these consequences in highly vulnerable neonatal populations.

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Fig. 1: Clinical variables predict microbiota diversity and composition.
Fig. 2: Partial architectural recovery of preterm IGM following discharge from NICU.
Fig. 3: Preterm infants harbour an enriched gut resistome.
Fig. 4: Multidrug-resistant Enterobacteriaceae lineages persist in IGM.
Fig. 5: Enduring damage to the preterm IGM.

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Data availability

Assembled functional metagenomic contigs, shotgun metagenomic reads, shotgun genomic reads and assemblies have been deposited to NCBI GenBank and SRA under BioProject ID PRJNA489090.

Code availability

The software packages used in this study are free and open source. Analysis scripts used here (and associated usage notes) are available from the authors on reasonable request.

References

  1. Sommer, F. & Bäckhed, F. The gut microbiota—masters of host development and physiology. Nat. Rev. Microbiol. 11, 227–238 (2013).

    CAS  PubMed  Google Scholar 

  2. Pantoja-Feliciano, I. G. et al. Biphasic assembly of the murine intestinal microbiota during early development. ISME J. 7, 1112–1115 (2013).

    PubMed  PubMed Central  Google Scholar 

  3. Yatsunenko, T. et al. Human gut microbiome viewed across age and geography. Nature 486, 222–227 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. Cox, L. M. et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell 158, 705–721 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  5. Abrahamsson, T. R. et al. Low gut microbiota diversity in early infancy precedes asthma at school age. Clin. Exp. Allergy 44, 842–850 (2014).

    CAS  PubMed  Google Scholar 

  6. Livanos, A. E. et al. Antibiotic-mediated gut microbiome perturbation accelerates development of type 1 diabetes in mice. Nat. Microbiol. 1, 16140 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. Cho, I. et al. Antibiotics in early life alter the murine colonic microbiome and adiposity. Nature 488, 621–626 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. Trasande, L. et al. Infant antibiotic exposures and early-life body mass. Int. J. Obes. 37, 16–23 (2013).

    CAS  Google Scholar 

  10. Hviid, A., Svanstrom, H. & Frisch, M. Antibiotic use and inflammatory bowel diseases in childhood. Gut 60, 49–54 (2011).

    PubMed  Google Scholar 

  11. Penders, J. et al. Gut microbiota composition and development of atopic manifestations in infancy: the KOALA birth cohort study. Gut 56, 661–667 (2007).

    CAS  PubMed  Google Scholar 

  12. Arrieta, M.-C. et al. Early infancy microbial and metabolic alterations affect risk of childhood asthma. Sci. Transl. Med. 7, 307ra152 (2015).

    PubMed  Google Scholar 

  13. Ahmadizar, F. et al. Early life antibiotic use and the risk of asthma and asthma exacerbations in children. Pediatr. Allergy Immunol. 28, 430–437 (2017).

    PubMed  Google Scholar 

  14. Stokholm, J. et al. Maturation of the gut microbiome and risk of asthma in childhood. Nat. Commun. 9, 141 (2018).

    PubMed  PubMed Central  Google Scholar 

  15. Missaghi, B., Barkema, H., Madsen, K. & Ghosh, S. Perturbation of the human microbiome as a contributor to inflammatory bowel disease. Pathogens 3, 510–527 (2014).

    PubMed  PubMed Central  Google Scholar 

  16. Tremlett, H. et al. Gut microbiota in early pediatric multiple sclerosis: a case−control study. Eur. J. Neurol. 23, 1308–1321 (2016).

    PubMed  PubMed Central  Google Scholar 

  17. Russell, S. L. et al. Early life antibiotic-driven changes in microbiota enhance susceptibility to allergic asthma. EMBO Rep. 13, 440–447 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  18. Zanvit, P. et al. Antibiotics in neonatal life increase murine susceptibility to experimental psoriasis. Nat. Commun. 6, 8424 (2015).

    CAS  PubMed  Google Scholar 

  19. Azad, M. B., Bridgman, S. L., Becker, A. B. & Kozyrskyj, A. L. Infant antibiotic exposure and the development of childhood overweight and central adiposity. Int. J. Obes. 38, 1290–1298 (2014).

    CAS  Google Scholar 

  20. Boursi, B., Mamtani, R., Haynes, K. & Yang, Y.-X. The effect of past antibiotic exposure on diabetes risk. Eur. J. Endocrinol. 172, 639–648 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Shaw, S. Y., Blanchard, J. F. & Bernstein, C. N. Association between the use of antibiotics in the first year of life and pediatric inflammatory bowel disease. Am. J. Gastroenterol. 105, 2687–2692 (2010).

    PubMed  Google Scholar 

  22. Ungaro, R. et al. Antibiotics associated with increased risk of new-onset Crohn’s disease but not ulcerative colitis: a meta-analysis. Am. J. Gastroenterol. 109, 1728–1738 (2014).

    CAS  PubMed  Google Scholar 

  23. Kronman, M. P., Zaoutis, T. E., Haynes, K., Feng, R. & Coffin, S. E. Antibiotic exposure and IBD development among children: a population-based cohort study. Pediatrics 130, e794–e803 (2012).

    PubMed  PubMed Central  Google Scholar 

  24. Lexmond, W. S. et al. Involvement of the iNKT cell pathway is associated with early-onset eosinophilic esophagitis and response to allergen avoidance therapy. Am. J. Gastroenterol. 109, 646–657 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. Blencowe, H. et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet 379, 2162–2172 (2012).

    PubMed  Google Scholar 

  26. Liu, L. et al. Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with implications for the sustainable development goals. Lancet 388, 3027–3035 (2016).

    PubMed  PubMed Central  Google Scholar 

  27. Stoll, B. J. Neurodevelopmental and growth impairment among extremely low-birth-weight infants with neonatal infection. JAMA 292, 2357 (2004).

    CAS  PubMed  Google Scholar 

  28. Flannery, D. D. et al. Temporal trends and center variation in early antibiotic use among premature infants. JAMA Netw. Open 1, e180164 (2018).

    PubMed  PubMed Central  Google Scholar 

  29. Rose, G. et al. Antibiotic resistance potential of the healthy preterm infant gut microbiome. PeerJ 5, e2928 (2017).

    PubMed  PubMed Central  Google Scholar 

  30. Rahman, S. F., Olm, M. R., Morowitz, M. J. & Banfield, J. F. Machine learning leveraging genomes from metagenomes identifies influential antibiotic resistance genes in the infant gut microbiome. mSystems 3, e00123-17 (2018).

  31. Pärnänen, K. et al. Maternal gut and breast milk microbiota affect infant gut antibiotic resistome and mobile genetic elements. Nat. Commun. 9, 3891 (2018).

    PubMed  PubMed Central  Google Scholar 

  32. Hourigan, S. K. et al. Comparison of infant gut and skin microbiota, resistome and virulome between neonatal intensive care unit (NICU) environments. Front. Microbiol. 9, 1361 (2018).

    PubMed  PubMed Central  Google Scholar 

  33. Gibson, M. K. et al. Developmental dynamics of the preterm infant gut microbiota and antibiotic resistome. Nat. Microbiol. 1, 16024 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Fouhy, F. et al. High-throughput sequencing reveals the incomplete, short-term recovery of infant gut microbiota following parenteral antibiotic treatment with ampicillin and gentamicin. Antimicrob. Agents Chemother. 56, 5811–5820 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  35. Greenwood, C. et al. Early empiric antibiotic use in preterm infants is associated with lower bacterial diversity and higher relative abundance of enterobacter. J. Pediatr. 165, 23–29 (2014).

    PubMed  PubMed Central  Google Scholar 

  36. Stewart, C. J. et al. Preterm gut microbiota and metabolome following discharge from intensive care. Sci. Rep. 5, 17141 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Zwittink, R. D. et al. Association between duration of intravenous antibiotic administration and early-life microbiota development in late-preterm infants. Eur. J. Clin. Microbiol. Infect. Dis. 37, 475–483 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Moles, L. et al. Preterm infant gut colonization in the neonatal ICU and complete restoration 2 years later. Clin. Microbiol. Infect. 21, 936–936 (2015).

    PubMed  Google Scholar 

  39. The American College of Obstetricians and Gynecologists Committee on Obstetric Practice Society for Maternal-Fetal Medicine Committee opinion No 579: Definition of term pregnancy. Obstet. Gynecol. 122, 1139–1140 (2013).

  40. Raju, T. N. K., Higgins, R. D., Stark, A. R. & Leveno, K. J. Optimizing care and outcome for late-preterm (near-term) infants: a summary of the workshop sponsored by the national institute of child health and human development. Pediatrics 118, 1207–1214 (2006).

    PubMed  Google Scholar 

  41. Truong, D. T. et al. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat. Methods 12, 902–903 (2015).

    CAS  PubMed  Google Scholar 

  42. Franzosa, E. A. et al. Species-level functional profiling of metagenomes and metatranscriptomes. Nat. Methods 15, 962–968 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  43. Bradley, P. H. & Pollard, K. S. Proteobacteria explain significant functional variability in the human gut microbiome. Microbiome 5, 36 (2017).

    PubMed  PubMed Central  Google Scholar 

  44. Lindberg, T. P. et al. Preterm infant gut microbial patterns related to the development of necrotizing enterocolitis. J. Matern. Fetal Neonatal Med. 18, 1–10 (2018).

  45. Warner, B. B. et al. Gut bacteria dysbiosis and necrotising enterocolitis in very low birthweight infants: a prospective case-control study. Lancet 387, 1928–1936 (2016).

    PubMed  PubMed Central  Google Scholar 

  46. Abrahamsson, T. R. et al. Low diversity of the gut microbiota in infants with atopic eczema. J. Allergy Clin. Immunol. 129, 434–440 (2012).

    PubMed  Google Scholar 

  47. Kriss, M., Hazleton, K. Z., Nusbacher, N. M., Martin, C. G. & Lozupone, C. A. Low diversity gut microbiota dysbiosis: drivers, functional implications and recovery. Curr. Opin. Microbiol. 44, 34–40 (2018).

    PubMed  PubMed Central  Google Scholar 

  48. Subramanian, S. et al. Persistent gut microbiota immaturity in malnourished Bangladeshi children. Nature 510, 417–421 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Forsberg, K. J. et al. The shared antibiotic resistome of soil bacteria and human pathogens. Science 337, 1107–1111 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Hsieh, E. et al. Medication use in the neonatal intensive care unit. Am. J. Perinatol. 31, 811–822 (2013).

    PubMed  PubMed Central  Google Scholar 

  51. Jia, B. et al. CARD 2017: expansion and model-centric curation of the comprehensive antibiotic resistance database. Nucleic Acids Res. 45, D566–D573 (2017).

    CAS  PubMed  Google Scholar 

  52. Crofts, T. S., Gasparrini, A. J. & Dantas, G. Next-generation approaches to understand and combat the antibiotic resistome. Nat. Rev. Microbiol. 15, 422–434 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Wyres, K. L. & Holt, K. E. Klebsiella pneumoniae as a key trafficker of drug resistance genes from environmental to clinically important bacteria. Curr. Opin. Microbiol. 45, 131–139 (2018).

    CAS  PubMed  Google Scholar 

  54. Navon-Venezia, S., Kondratyeva, K. & Carattoli, A. Klebsiella pneumoniae: a major worldwide source and shuttle for antibiotic resistance. FEMS Microbiol. Rev. 41, 252–275 (2017).

    CAS  PubMed  Google Scholar 

  55. Goldstone, R. J. & Smith, D. G. E. A population genomics approach to exploiting the accessory ‘resistome’ of Escherichia coli. Microb. Genom. 3, e000108 (2017).

    PubMed  PubMed Central  Google Scholar 

  56. Kaminski, J. et al. High-specificity targeted functional profiling in microbial communities with ShortBRED. PLoS Comput. Biol. 11, e1004557 (2015).

    PubMed  PubMed Central  Google Scholar 

  57. Breiman, L. Random Forests. Mach. Learn. 45, 5–32 (2001).

    Google Scholar 

  58. Carl, M. A. et al. Sepsis from the gut: the enteric habitat of bacteria that cause late-onset neonatal bloodstream infections. Clin. Infect. Dis. 58, 1211–1218 (2014).

    PubMed  PubMed Central  Google Scholar 

  59. Zhang, X., Feng, Y., Zhou, W., McNally, A. & Zong, Z. Cryptic transmission of ST405 Escherichia coli carrying bla NDM-4 in hospital. Sci. Rep. 8, 390 (2018).

    PubMed  PubMed Central  Google Scholar 

  60. Izdebski, R. et al. MLST reveals potentially high-risk international clones of Enterobacter cloacae. J. Antimicrob. Chemother. 70, 48–56 (2015).

    CAS  PubMed  Google Scholar 

  61. Gurnee, E. A. et al. Gut colonization of healthy children and their mothers with pathogenic ciprofloxacin-resistant Escherichia coli. J. Infect. Dis. 212, 1862–1868 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Kim, H. B. et al. oqxAB encoding a multidrug efflux pump in human clinical isolates of Enterobacteriaceae. Antimicrob. Agents Chemother. 53, 3582–3584 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Fevre, C., Passet, V., Weill, F.-X., Grimont, P. A. D. & Brisse, S. Variants of the Klebsiella pneumoniae OKP Chromosomal beta-lactamase are divided into two main groups, OKP-A and OKP-B. Antimicrob. Agents Chemother. 49, 5149–5152 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Gasparrini, A. J. et al. Antibiotic perturbation of the preterm infant gut microbiome and resistome. Gut Microbes 7, 443–449 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. Furtado, I. et al. Enterococcus faecium and Enterococcus faecalis in blood of newborns with suspected nosocomial infection. Rev. Inst. Med. Trop. Sao Paulo 56, 77–80 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Akturk, H. et al. Vancomycin resistant Enterococci colonization in a neonatal intensive care unit: who will be infected? J. Matern. Fetal Neonatal Med. 29, 3478–3482 (2016).

  67. Brooks, B. et al. Microbes in the neonatal intensive care unit resemble those found in the gut of premature infants. Microbiome 2, 1 (2014).

    PubMed  PubMed Central  Google Scholar 

  68. Fernández-Canigia, L., Cejas, D., Gutkind, G. & Radice, M. Detection and genetic characterization of β-lactamases in Prevotella intermedia and Prevotella nigrescens isolated from oral cavity infections and peritonsillar abscesses. Anaerobe 33, 8–13 (2015).

    PubMed  Google Scholar 

  69. Singh, B. et al. Probiotics for preterm infants: a national retrospective cohort study. J. Perinatol. 39, 533–539 (2019).

    PubMed  Google Scholar 

  70. Kerr-Wilson, C. O., Mackay, D. F., Smith, G. C. S. & Pell, J. P. Meta-analysis of the association between preterm delivery and intelligence. J. Publ. Health 34, 209–216 (2012).

    CAS  Google Scholar 

  71. Johnson, S. et al. Academic attainment and special educational needs in extremely preterm children at 11 years of age: the EPICure study. Arch. Dis. Child. Fetal Neonatal Ed. 94, F283–F289 (2009).

    CAS  PubMed  Google Scholar 

  72. Bhutta, A. T., Cleves, M. A., Casey, P. H., Cradock, M. M. & Anand, K. J. S. Cognitive and behavioral outcomes of school-aged children who were born preterm: a meta-analysis. JAMA 288, 728–737 (2002).

    PubMed  Google Scholar 

  73. Tinnion, R., Gillone, J., Cheetham, T. & Embleton, N. Preterm birth and subsequent insulin sensitivity: a systematic review. Arch. Dis. Child. 99, 362–368 (2014).

    PubMed  Google Scholar 

  74. Parkinson, J. R. C., Hyde, M. J., Gale, C., Santhakumaran, S. & Modi, N. Preterm birth and the metabolic syndrome in adult life: a systematic review and meta-analysis. Pediatrics 131, e1240–e1263 (2013).

    PubMed  Google Scholar 

  75. Crump, C., Winkleby, M. A., Sundquist, K. & Sundquist, J. Risk of hypertension among young adults who were born preterm: a Swedish national study of 636,000 births. Am. J. Epidemiol. 173, 797–803 (2011).

    PubMed  PubMed Central  Google Scholar 

  76. Kowalski, R. R. et al. Elevated blood pressure with reduced left ventricular and aortic dimensions in adolescents born extremely preterm. J. Pediatr. 172, 75–80 (2016).

    PubMed  Google Scholar 

  77. Crump, C., Winkleby, M. A., Sundquist, J. & Sundquist, K. Risk of asthma in young adults who were born preterm: a Swedish national cohort study. Pediatrics 127, e913–e920 (2011).

    PubMed  PubMed Central  Google Scholar 

  78. Lum, S. et al. Nature and severity of lung function abnormalities in extremely pre-term children at 11 years of age. Eur. Respir. J. 37, 1199–1207 (2011).

    CAS  PubMed  Google Scholar 

  79. La Rosa, P. S. et al. Patterned progression of bacterial populations in the premature infant gut. Proc. Natl Acad. Sci. USA 111, 12522–12527 (2014).

    PubMed  PubMed Central  Google Scholar 

  80. Planer, J. D. et al. Development of the gut microbiota and mucosal IgA responses in twins and gnotobiotic mice. Nature 534, 263–266 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Baym, M. et al. Inexpensive multiplexed library preparation for megabase-sized genomes. PLoS ONE 10, e0128036 (2015).

    PubMed  PubMed Central  Google Scholar 

  82. Bolger, A. M., Lohse, M. & Usadel, B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30, 2114–2120 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Zhu, W., Lomsadze, A. & Borodovsky, M. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res. 38, e132 (2010).

    PubMed  PubMed Central  Google Scholar 

  84. Gibson, M. K., Forsberg, K. J. & Dantas, G. Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology. ISME J. 9, 207–216 (2015).

    CAS  PubMed  Google Scholar 

  85. Finn, R. D., Clements, J. & Eddy, S. R. HMMER web server: interactive sequence similarity searching. Nucleic Acids Res. 39, W29–W37 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. & Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403–410 (1990).

    CAS  PubMed  Google Scholar 

  87. Rice, P., Longden, I. & Bleasby, A. EMBOSS: the European molecular biology open software suite. Trends Genet. 16, 276–277 (2000).

    CAS  PubMed  Google Scholar 

  88. Schmieder, R. & Edwards, R. Fast identification and removal of sequence contamination from genomic and metagenomic datasets. PLoS ONE 6, e17288 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Bankevich, A. et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J. Comput. Biol. 19, 455–477 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Gurevich, A., Saveliev, V., Vyahhi, N. & Tesler, G. QUAST: quality assessment tool for genome assemblies. Bioinformatics 29, 1072–1075 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).

    CAS  PubMed  Google Scholar 

  92. Ondov, B. D. et al. Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol. 17, 132 (2016).

    PubMed  PubMed Central  Google Scholar 

  93. Page, A. J. et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 31, 3691–3693 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. Mohamed, J. A., Huang, W., Nallapareddy, S. R., Teng, F. & Murray, B. E. Influence of origin of isolates, especially endocarditis isolates, and various genes on biofilm formation by enterococcus faecalis. Infect. Immun. 72, 3658–3663 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work is supported in part by awards to G.D. through the National Institute of General Medical Sciences of the National Institutes of Health (R01 GM099538), the National Institute of Allergy and Infectious Diseases of the National Institutes of Health (R01 AI123394) and the US Centers for Disease Control and Prevention (200-2016-91955); to P.I.T. through the National Institutes of Health (5P30 DK052574 (Biobank, DDRCC)); to G.D., P.I.T. and B.B.W. through the Eunice Kennedy Shriver National Institute Of Child Health and Human Development of the National Institutes of Health (R01 HD092414); to P.I.T. and B.B.W. through the Children’s Discovery Institute at St Louis Children’s Hospital and Washington University School of Medicine; and to A.J.G. through a NIGMS training grant award number T32 GM007067 (J. Skeath, principal investigator) and from the NIDDK Pediatric Gastroenterology Research Training Program award number T32 DK077653 (P.I.T., principal investigator). The content is solely the responsibility of the authors and does not necessarily represent the official views of the funding agencies. We thank members of the Dantas laboratory for helpful discussion of the manuscript, and staff from the Edison Family Center for Genome Sciences & Systems Biology, E. Martin, B. Koebbe and J. Hoisington-López for technical support and sequencing expertise.

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Contributions

A.J.G. and G.D. conceived and designed the study. P.I.T., B.B.W. and I.M.N. assembled the cohorts, collected the specimens and biological data and maintained the database, oversaw the transfer of specimens and clinical metadata and provided clinical insights. A.J.G. and B.W. extracted metagenomic DNA from stools and prepared shotgun metagenomic sequencing libraries. A.J.G., B.W. and A.H.-L. performed stool culturing experiments and isolate genomic DNA extraction. A.J.G. and B.W. prepared isolate genome sequencing libraries. E.A.K. performed Enterococcus phenotyping experiments. X.S. created functional metagenomic libraries, performed functional selections and prepared functional metagenomic sequencing libraries. A.J.G. analysed clinical metadata, shotgun metagenomic sequencing data, isolate genome sequencing data and functional metagenomic data. A.J.G. wrote the manuscript with input from G.D., B.B.W. and P.I.T.

Corresponding author

Correspondence to Gautam Dantas.

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Competing interests

P.I.T. is a member of the Scientific Advisory Board of, holds equity in and is a consultant to MediBeacon. P.I.T. is a coinventor on a filed patent application (US Patent application no. 16/200353) to test intestinal permeability in humans that might generate royalty payments. This involvement is not directly relevant to this manuscript. P.I.T. is also a consultant to Takeda Pharmaceuticals on pediatric gastrointestinal disorders and to the Bill & Melinda Gates Foundation on neonatal infections.

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Supplementary Information

Supplementary Figs. 1–7, and Supplementary Tables 2 and 3.

Reporting Summary

Supplementary Table 1

Clinical and experimental metadata for infants and samples included in this study.

Supplementary Table 4

Statistics for infant gut isolates sequenced in this study.

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Gasparrini, A.J., Wang, B., Sun, X. et al. Persistent metagenomic signatures of early-life hospitalization and antibiotic treatment in the infant gut microbiota and resistome. Nat Microbiol 4, 2285–2297 (2019). https://doi.org/10.1038/s41564-019-0550-2

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