ABSTRACT Loss of diversity in the gut microbiome can persist for extended periods after antibiotic treatment, impacting microbiome function, antimicrobial resistance and probably host

health. Despite widespread antibiotic use, our understanding of the species and metabolic functions contributing to gut microbiome recovery is limited. Using data from 4 discovery cohorts in

3 continents comprising >500 microbiome profiles from 117 individuals, we identified 21 bacterial species exhibiting robust association with ecological recovery post antibiotic therapy.

Functional and growth-rate analysis showed that recovery is supported by enrichment in specific carbohydrate-degradation and energy-production pathways. Association rule mining on 782

thetaiotaomicron_ and _Bifidobacterium adolescentis_) to promote recovery with synergistic effects, providing a boost of two orders of magnitude to microbial abundance in early time points

and faster maturation of microbial diversity. The identification of specific species and metabolic functions promoting recovery opens up opportunities for rationally determining pre- and

probiotic formulations offering protection from long-term consequences of frequent antibiotic usage. Access through your institution Buy or subscribe This is a preview of subscription

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GUT MICROBIOME Article Open access 02 March 2023 LONG-TERM ECOLOGICAL AND EVOLUTIONARY DYNAMICS IN THE GUT MICROBIOMES OF CARBAPENEMASE-PRODUCING ENTEROBACTERIACEAE COLONIZED SUBJECTS

Article Open access 15 September 2022 DIFFERENTIAL RESPONSES OF THE GUT MICROBIOME AND RESISTOME TO ANTIBIOTIC EXPOSURES IN INFANTS AND ADULTS Article Open access 22 December 2023 DATA

AVAILABILITY Illumina sequencing data for this study (mouse models) are available from the Sequence Read Archive under project ID SRP142225. Samples are labelled in SRA with a shorthand (for

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study with inulin-type fructans in obese women. _Gut_ 62, 1112–1121 (2013). CAS  PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS This work was supported by funding from the

National Healthcare Group (NHG-CSCS/12008), the National Medical Research Council, the National Research Foundation and A*STAR, Singapore. AUTHOR INFORMATION Author notes * These authors

contributed equally: Kern Rei Chng, Tarini Shankar Ghosh, Yi Han Tan, Tannistha Nandi. AUTHORS AND AFFILIATIONS * Genome Institute of Singapore, Singapore, Singapore Kern Rei Chng, Tarini

Shankar Ghosh, Tannistha Nandi, Amanda Hui Qi Ng, Chenhao Li, Aarthi Ravikrishnan, Kar Mun Lim, Swaine L. Chen & Niranjan Nagarajan * APC Microbiome Ireland, University College Cork,

Cork, Ireland Tarini Shankar Ghosh * Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Yi Han Tan, Ivor Russel Lee, David Lye, Louis Chai, Yunn-Hwen Gan

 & Niranjan Nagarajan * National Centre for Infectious Disease, Singapore, Singapore David Lye & Barnaby Young * Lee Kong Chian School of Medicine, Nanyang Technological University,

Singapore, Singapore David Lye & Barnaby Young * Tan Tock Seng Hospital, Singapore, Singapore David Lye, Timothy Barkham & Barnaby Young * Department of Biotechnology, Bhupat and

Jyoti Mehta School of Biological Sciences, Indian Institute of Technology (IIT) Madras, Chennai, India Karthik Raman * Initiative for Biological Systems Engineering, IIT Madras, Chennai,

India Karthik Raman * Robert Bosch Centre for Data Science and Artificial Intelligence (RBC-DSAI), IIT Madras, Chennai, India Karthik Raman * Division of Infectious Diseases, University

Medicine Cluster, National University Health System, Singapore, Singapore Louis Chai Authors * Kern Rei Chng View author publications You can also search for this author inPubMed Google

Scholar * Tarini Shankar Ghosh View author publications You can also search for this author inPubMed Google Scholar * Yi Han Tan View author publications You can also search for this author

inPubMed Google Scholar * Tannistha Nandi View author publications You can also search for this author inPubMed Google Scholar * Ivor Russel Lee View author publications You can also search

for this author inPubMed Google Scholar * Amanda Hui Qi Ng View author publications You can also search for this author inPubMed Google Scholar * Chenhao Li View author publications You can

also search for this author inPubMed Google Scholar * Aarthi Ravikrishnan View author publications You can also search for this author inPubMed Google Scholar * Kar Mun Lim View author

publications You can also search for this author inPubMed Google Scholar * David Lye View author publications You can also search for this author inPubMed Google Scholar * Timothy Barkham

View author publications You can also search for this author inPubMed Google Scholar * Karthik Raman View author publications You can also search for this author inPubMed Google Scholar *

Swaine L. Chen View author publications You can also search for this author inPubMed Google Scholar * Louis Chai View author publications You can also search for this author inPubMed Google

Scholar * Barnaby Young View author publications You can also search for this author inPubMed Google Scholar * Yunn-Hwen Gan View author publications You can also search for this author

inPubMed Google Scholar * Niranjan Nagarajan View author publications You can also search for this author inPubMed Google Scholar CONTRIBUTIONS N.N., Y.-H.G., B.Y. and S.L.C. planned and

designed the project. B.Y., L.C., T.B. and D.L. contributed the clinical cohorts. Y.H.T. and I.R.L. performed the mouse experiments, with resulting data analysed by T.N. under the guidance

of Y.-H.G. and N.N. A.H.Q.N. and K.M.L. conducted wet-lab experiments with guidance from K.R.C. and N.N. T.S.G., K.R.C., A.R., C.L. and T.N. coordinated computational analysis with

supervision by K.R. and N.N. T.S.G., T.N., A.R., K.R.C. and N.N. wrote the manuscript with input from all authors. CORRESPONDING AUTHORS Correspondence to Barnaby Young, Yunn-Hwen Gan or

Niranjan Nagarajan. ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. ADDITIONAL INFORMATION PEER REVIEW INFORMATION Peer reviewer reports are available.

PUBLISHER’S NOTE Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. SUPPLEMENTARY INFORMATION SUPPLEMENTARY INFORMATION

Supplementary Figs. 1–11, Table 1 and Note 1. REPORTING SUMMARY PEER REVIEW INFORMATION SUPPLEMENTARY DATA 1 Species abundance profile across samples from the different cohorts.

SUPPLEMENTARY DATA 2 Differentially abundant species in recoverers versus non-recoverers. SUPPLEMENTARY DATA 3 Inferred metabolic pathway abundances across samples from the different

cohorts. SUPPLEMENTARY DATA 4 Inferred CAZyme abundances across samples from the different cohorts. SUPPLEMENTARY DATA 5 PTR values for different species and the computed community growth

rate per sample from the different cohorts. SUPPLEMENTARY DATA 6 Microbial dependency relationships in the gut microbiome predicted via association rule mining on the MEDUSA database.

SUPPLEMENTARY DATA 7 Metabolic support index values for interactions between various RAB species and the corresponding top 10% of interactions. RIGHTS AND PERMISSIONS Reprints and

permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Chng, K.R., Ghosh, T.S., Tan, Y.H. _et al._ Metagenome-wide association analysis identifies microbial determinants of post-antibiotic

ecological recovery in the gut. _Nat Ecol Evol_ 4, 1256–1267 (2020). https://doi.org/10.1038/s41559-020-1236-0 Download citation * Received: 18 December 2019 * Accepted: 28 May 2020 *

Published: 06 July 2020 * Issue Date: September 2020 * DOI: https://doi.org/10.1038/s41559-020-1236-0 SHARE THIS ARTICLE Anyone you share the following link with will be able to read this

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