Whole Genome Sequencing versus Traditional Genotyping for Investigation of a Mycobacterium tuberculosis Outbreak: A Longitudinal Molecular Epidemiological Study
Top Cited Papers
Open Access
- 12 February 2013
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLoS Medicine
- Vol. 10 (2) , e1001387
- https://doi.org/10.1371/journal.pmed.1001387
Abstract
Understanding Mycobacterium tuberculosis (Mtb) transmission is essential to guide efficient tuberculosis control strategies. Traditional strain typing lacks sufficient discriminatory power to resolve large outbreaks. Here, we tested the potential of using next generation genome sequencing for identification of outbreak-related transmission chains. During long-term (1997 to 2010) prospective population-based molecular epidemiological surveillance comprising a total of 2,301 patients, we identified a large outbreak caused by an Mtb strain of the Haarlem lineage. The main performance outcome measure of whole genome sequencing (WGS) analyses was the degree of correlation of the WGS analyses with contact tracing data and the spatio-temporal distribution of the outbreak cases. WGS analyses of the 86 isolates revealed 85 single nucleotide polymorphisms (SNPs), subdividing the outbreak into seven genome clusters (two to 24 isolates each), plus 36 unique SNP profiles. WGS results showed that the first outbreak isolates detected in 1997 were falsely clustered by classical genotyping. In 1998, one clone (termed “Hamburg clone”) started expanding, apparently independently from differences in the social environment of early cases. Genome-based clustering patterns were in better accordance with contact tracing data and the geographical distribution of the cases than clustering patterns based on classical genotyping. A maximum of three SNPs were identified in eight confirmed human-to-human transmission chains, involving 31 patients. We estimated the Mtb genome evolutionary rate at 0.4 mutations per genome per year. This rate suggests that Mtb grows in its natural host with a doubling time of approximately 22 h (400 generations per year). Based on the genome variation discovered, emergence of the Hamburg clone was dated back to a period between 1993 and 1997, hence shortly before the discovery of the outbreak through epidemiological surveillance. Our findings suggest that WGS is superior to conventional genotyping for Mtb pathogen tracing and investigating micro-epidemics. WGS provides a measure of Mtb genome evolution over time in its natural host context. Please see later in the article for the Editors' Summary Tuberculosis—a contagious bacterial disease that usually infects the lungs—is a major public health problem, particularly in low- and middle-income countries. In 2011, an estimated 8.7 million people developed tuberculosis globally, and 1.4 million people died from the disease. Tuberculosis is second only to HIV/AIDS in terms of global deaths from a single infectious agent. Mycobacterium tuberculosis, the bacterium that causes tuberculosis, is readily spread in airborne droplets when people with active disease cough or sneeze. The characteristic symptoms of tuberculosis include persistent cough, weight loss, fever, and night sweats. Diagnostic tests for the disease include sputum smear analysis (examination of mucus coughed up from the lungs for the presence of M. tuberculosis), mycobacterial culture (growth of M. tuberculosis from sputum), and chest X-rays. Tuberculosis can be cured by taking several antibiotics daily for at least six months, although the recent emergence of multidrug-resistant M. tuberculosis is making tuberculosis harder to treat. Although efforts to reduce the global burden of tuberculosis are showing some improvements, the annual decline in the number of people developing tuberculosis continues to be slow. To develop optimized control strategies, experts need to be able to accurately track M. tuberculosis transmission within human populations. Because M. tuberculosis, like all bacteria, accumulates genetic changes over time, there are many different strains (genetic variants) of M. tuberculosis. Genotyping methods have been developed that identify different bacterial strains by examining specific regions of the bacterial genome (blueprint), but because these methods examine only a small part of the genome, they may not distinguish between related transmission chains. That is, traditional strain genotyping methods may not be able to determine accurately where a tuberculosis outbreak started or how it spread through a population. In this longitudinal cohort study, the researchers compare the ability of whole genome sequencing (WGS), which is rapidly becoming widely available, and traditional genotyping to provide information about a recent German tuberculosis outbreak. In a longitudinal cohort study, a population is followed over time to analyze the occurrence of a specific disease. During long-term (1997–2010) population-based molecular epidemiological surveillance (disease surveillance that uses molecular techniques rather than reports of illness) in Hamburg and Schleswig-Holstein, the researchers identified a large tuberculosis outbreak caused by M. tuberculosis isolates of the Haarlem lineage using classical strain typing. The researchers examined each of the 86 isolates from this outbreak using WGS and classical genotyping and asked whether the results of these two approaches correlated with contact tracing data (information is routinely collected about the people a patient with tuberculosis has recently met so that these contacts can be tested for tuberculosis and treated if necessary) and with the spatio-temporal distribution of outbreak cases. WGS of the isolates identified 85 single nucleotide polymorphisms (SNPs; genomic sequence variants in which single building blocks, or nucleotides, are altered) that subdivided the outbreak into seven clusters of isolates and 36 unique isolates. The WGS results showed that the first isolates of the outbreak were incorrectly clustered by classical genotyping and that one strain—the “Hamburg clone”—started expanding in 1998. Notably, the genome-based clustering patterns were in better accordance with contact tracing data and with the geographical distribution of cases than clustering patterns based on classical genotyping, and they identified eight confirmed human-to-human transmission chains that involved 31 patients and a maximum of three SNPs. Finally, the researchers used their WGS results to estimate that the Hamburg clone emerged between 1993 and 1997, shortly before the discovery of the tuberculosis outbreak through epidemiological surveillance. These findings show that WGS can be used to identify specific strains within large tuberculosis outbreaks more accurately than classical genotyping. They also provide new information about the evolution of M. tuberculosis during outbreaks and indicate how WGS data should be interpreted in future genome-based molecular epidemiology studies. WGS has the potential to improve the molecular epidemiological surveillance and control of tuberculosis and of other infectious diseases. Importantly, note the researchers, ongoing reductions in the cost of WGS, the increased availability of “bench top” genome sequencers, and bioinformatics developments should all accelerate the implementation of WGS as a standard method for the identification of transmission chains in infectious disease outbreaks. Please access these websites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001387.Keywords
This publication has 40 references indexed in Scilit:
- Epidemiologic Consequences of Microvariation in Mycobacterium tuberculosisThe Journal of Infectious Diseases, 2012
- Evaluation of Mycobacterium tuberculosis Typing Methods in a 4-Year Study in Schleswig-Holstein, Northern GermanyJournal of Clinical Microbiology, 2011
- Use of whole genome sequencing to estimate the mutation rate of Mycobacterium tuberculosis during latent infectionNature Genetics, 2011
- Rapid Pneumococcal Evolution in Response to Clinical InterventionsScience, 2011
- Navigating the future of bacterial molecular epidemiologyCurrent Opinion in Microbiology, 2010
- Human T cell epitopes of Mycobacterium tuberculosis are evolutionarily hyperconservedNature Genetics, 2010
- Evolution of MRSA During Hospital Transmission and Intercontinental SpreadScience, 2010
- BEAST: Bayesian evolutionary analysis by sampling treesBMC Ecology and Evolution, 2007
- Proposal for Standardization of Optimized Mycobacterial Interspersed Repetitive Unit-Variable-Number Tandem Repeat Typing ofMycobacterium tuberculosisJournal of Clinical Microbiology, 2006
- Deciphering the biology of Mycobacterium tuberculosis from the complete genome sequenceNature, 1998