Yemen is currently experiencing, to our knowledge, the largest cholera epidemic in recent history. The first cases were declared in September 2016, and over 1.1 million cases and 2,300 deaths have since been reported1. Here we investigate the phylogenetic relationships, pathogenesis and determinants of antimicrobial resistance by sequencing the genomes of Vibrio cholerae isolates from the epidemic in Yemen and recent isolates from neighbouring regions. These 116 genomic sequences were placed within the phylogenetic context of a global collection of 1,087 isolates of the seventh pandemic V. cholerae serogroups O1 and O139 biotype El Tor2,3,4. We show that the isolates from Yemen that were collected during the two epidemiological waves of the epidemic1—the first between 28 September 2016 and 23 April 2017 (25,839 suspected cases) and the second beginning on 24 April 2017 (more than 1 million suspected cases)—are V. cholerae serotype Ogawa isolates from a single sublineage of the seventh pandemic V. cholerae O1 El Tor (7PET) lineage. Using genomic approaches, we link the epidemic in Yemen to global radiations of pandemic V. cholerae and show that this sublineage originated from South Asia and that it caused outbreaks in East Africa before appearing in Yemen. Furthermore, we show that the isolates from Yemen are susceptible to several antibiotics that are commonly used to treat cholera and to polymyxin B, resistance to which is used as a marker of the El Tor biotype.

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Data availability

The whole-genome alignment for the 1,203 genomes and other files that support the findings of this study have been deposited in FigShare: https://figshare.com/s/b70a9efac9cf2625480e. Short-read sequence data were submitted to the ENA, under study accession numbers PRJEB24611 and ERP021285 and the genome accession numbers are provided in Supplementary Table 1. Phylogeny and metadata can be viewed interactively at https://microreact.org/project/globalcholera.

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Change history

  • 12 February 2019

    In the HTML version of this Letter, the affiliations for authors Andrew S. Azman, Dhirendra Kumar and Thandavarayan Ramamurthy were inverted (the PDF and print versions of the Letter were correct); the affiliations have been corrected online.


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This study was supported by the Institut Pasteur, Santé publique France, the French government’s Investissement d’Avenir programme, Laboratoire d’Excellence ‘Integrative Biology of Emerging Infectious Diseases’ (grant number ANR-10-LABX-62-IBEID), the Wellcome Trust through grant 098051 to the Sanger Institute and the Department of Biotechnology of India. The Institut Pasteur Genomics Platform is a member of the France Génomique consortium (ANR10-INBS-09-08). We thank D. Legros, A. Fadaq, A. Alsomine, F. Bazel and H. A. Jokhdar for their support; M. Musoke and S. Vernadat for technical assistance; Z. M. Eisa for providing isolates; L. Ma, C. Fund, S. Sjunnebo and the sequencing teams at the Institut Pasteur and Wellcome Sanger Institute for sequencing the samples. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Reviewer information

Nature thanks J. Mekalanos, C. Stine, M. Waldor and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Author notes

  1. These authors contributed equally: François-Xavier Weill, Daryl Domman

  2. These authors jointly supervised this work: Nicholas R. Thomson, Marie-Laure Quilici


  1. Institut Pasteur, Unité des Bactéries Pathogènes Entériques, Paris, France

    • François-Xavier Weill
    • , Elisabeth Njamkepo
    • , Jean Rauzier
    •  & Marie-Laure Quilici
  2. Wellcome Sanger Institute, Hinxton, UK

    • Daryl Domman
    •  & Nicholas R. Thomson
  3. Bioscience Division, Los Alamos National Laboratory, Los Alamos, NM, USA

    • Daryl Domman
  4. National Centre of Public Health Laboratories (NCPHL), Sana’a, Yemen

    • Abdullrahman A. Almesbahi
    • , Mona Naji
    •  & Samar Saeed Nasher
  5. Epicentre, Paris, France

    • Ankur Rakesh
    •  & Francisco J. Luquero
  6. Ministry of Health, Riyadh, Saudi Arabia

    • Abdullah M. Assiri
  7. Maharishi Valmiki Infectious Diseases Hospital, Delhi, India

    • Naresh Chand Sharma
    •  & Dhirendra Kumar
  8. Centre for Microbiology Research, Kenya Medical Research Institute, Nairobi, Kenya

    • Samuel Kariuki
    • , Samuel M. Njoroge
    •  & John Kiiru
  9. Pasteur Institute of Iran, Department of Bacteriology, Tehran, Iran

    • Mohammad Reza Pourshafie
  10. WHO Regional Office for the Eastern Mediterranean (EMRO), Cairo, Egypt

    • Abdinasir Abubakar
    •  & Mamunur Rahman Malik
  11. Amref Health Africa, Nairobi, Kenya

    • Jane Y. Carter
  12. WHO, Juba, South Sudan

    • Joseph F. Wamala
  13. Médecins Sans Frontières (MSF), Dubai, United Arab Emirates

    • Caroline Seguin
  14. Institut Pasteur, Plate-forme Génomique (PF1), Paris, France

    • Christiane Bouchier
  15. Unité de Bioinformatique Structurale, UMR 3528, CNRS; C3BI, USR 3756, Institut Pasteur, Paris, France

    • Thérèse Malliavin
  16. Department of Bacteriology, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran

    • Bita Bakhshi
  17. Central Public Health Laboratory (CPHL), Baghdad, Iraq

    • Hayder H. N. Abulmaali
  18. Translational Health Science and Technology Institute (THSTI), Faridabad, Haryana, India

    • Dhirendra Kumar
    •  & Thandavarayan Ramamurthy
  19. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    • Andrew S. Azman
  20. London School of Hygiene and Tropical Medicine, London, UK

    • Nicholas R. Thomson


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F.-X.W. and M.-L.Q. designed the study. A.A.A., M.N., S.S.N., A.R., A.M.A., N.C.S., S.K., M.R.P., A.A., J.Y.C., J.F.W., C.S., B.B., H.H.N.A., D.K., S.M.N., M.R.M., J.K., F.J.L., A.S.A., T.R. and M.-L.Q. collected, selected and provided characterized isolates and their corresponding epidemiological information. J.R. performed the DNA extractions and phenotypic and molecular typing experiments. T.M. analysed protein data. C.B. performed the whole-genome sequencing. F.-X.W., D.D. and E.N. analysed the genomic sequencing data. F.-X.W. and D.D. wrote the manuscript, with major contributions from N.R.T. All authors contributed to the editing of the manuscript.

Competing interests

The authors declare no competing interests.

Corresponding author

Correspondence to François-Xavier Weill.

Extended data figures and tables

  1. Extended Data Fig. 1 Geographic location of the sequenced V. cholerae O1 El Tor isolates and number of reported cholera cases.

    a, Geographic location of the 116 V. cholerae O1 El Tor isolates sequenced. The number of isolates collected per country is indicated. The three isolates collected in Jizan, Saudi Arabia (denoted by an asterisk) were from Yemeni refugees originating from Hajjah District. The map is a cropped version of the one available at https://commons.wikimedia.org/wiki/File:BlankMap-World.png. b, Number of cholera cases per country reported to the WHO (World Health Organisation) between 2014 and 2016. The total number of cholera cases reported to the WHO by the countries was 268,337. The maps were created using Paintmaps, a free online map generating tool (http://www.paintmaps.com/).

  2. Extended Data Fig. 2 Assessment of the temporal signal within the dataset.

    a, Linear regression of the root-to-tip distance against sampling time obtained with TempEst29 using a maximum-likelihood phylogeny of 81 representative seventh pandemic V. cholerae O1 isolates (that is, those used for the BEAST analysis). Bars on nodes indicate the precision of the isolation date (for example, if only the year of isolation is known, the bar spans the entire year). b, Comparison of the ucld.mean parameter estimated from 20 date-randomization BEAST experiments and the original dataset. The rate for the correctly dated tree is shown in red. The median and 95% Bayesian credible interval for the ucld.mean parameter are provided.

  3. Extended Data Fig. 3 Timed phylogeny of the ctxB7 clade.

    Maximum clade credibility tree produced with BEAST28 for a subset of 81 representative isolates of the distal part of the genomic wave 3 (that is, those with the ctxB7 allele). The nodes supported by posterior probability values ≥0.5 are indicated.

  4. Extended Data Fig. 4 Visualization of the posterior distribution of trees from the BEAST Markov chain Monte Carlo analysis.

    The opacity of the branches is scaled according to the number of times a clade is seen in the distribution. There is high support for the East Africa/Yemen clade. The uncertainty in the placement of the node for the Indian/East African isolates is the reason for the low posterior support value for this node in Extended Data Fig. 3.

  5. Extended Data Fig. 5 Multiple sequence alignment of VprA (VC1320) with two-component response regulators.

    A non-synonymous mutation at position 89 of VC1320 that resulted in a D-to-N amino acid change was associated with a phenotype of polymyxin B susceptibility.

  6. Extended Data Table 1 Summary of the Bayesian models used for BEAST28 analyses
  7. Extended Data Table 2 Gene alteration frequencies in isolates susceptible or resistant to certain antibiotics

Supplementary information

  1. Reporting Summary

  2. Supplementary Table

    This file contains Supplementary Table S1, which includes the details of Vibrio cholerae El Tor isolates and genomes used in this study

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