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An observational study of M. tuberculosis transmission in Oxfordshire using whole pathogen genome sequences

ABSTRACT: An observational study of M. tuberculosis transmission in Oxfordshire using whole pathogen genome sequences

PROVIDER: PRJEB5162 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	ERR400306_1.fastq.gz	Fastqsanger.gz
	ERR400306_2.fastq.gz	Fastqsanger.gz
	ERR400307_1.fastq.gz	Fastqsanger.gz
	ERR400307_2.fastq.gz	Fastqsanger.gz
	ERR400308_1.fastq.gz	Fastqsanger.gz

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Project description:BackgroundPatients born outside the UK have contributed to a 20% rise in the UK's tuberculosis incidence since 2000, but their effect on domestic transmission is not known. Here we use whole-genome sequencing to investigate the epidemiology of tuberculosis transmission in an unselected population over 6 years.MethodsWe identified all residents with Oxfordshire postcodes with a Mycobacterium tuberculosis culture or a clinical diagnosis of tuberculosis between Jan 1, 2007, and Dec 31, 2012, using local databases and checking against the national Enhanced Tuberculosis Surveillance database. We used Illumina technology to sequence all available M tuberculosis cultures from identified cases. Sequences were clustered by genetic relatedness and compared retrospectively with contact investigations. The first patient diagnosed in each cluster was defined as the index case, with links to subsequent cases assigned first by use of any epidemiological linkage, then by genetic distance, and then by timing of diagnosis.FindingsAlthough we identified 384 patients with a diagnosis of tuberculosis, country of birth was known for 380 and we sequenced isolates from 247 of 269 cases with culture-confirmed disease. 39 cases were genomically linked within 13 clusters, implying 26 local transmission events. Only 11 of 26 possible transmissions had been previously identified through contact tracing. Of seven genomically confirmed household clusters, five contained additional genomic links to epidemiologically unidentified non-household members. 255 (67%) patients were born in a country with high tuberculosis incidence, conferring a local incidence of 109 cases per 100,000 population per year in Oxfordshire, compared with 3·5 cases per 100,000 per year for those born in low-incidence countries. However, patients born in the low-incidence countries, predominantly UK, were more likely to have pulmonary disease (adjusted odds ratio 1·8 [95% CI 1·2-2·9]; p=0·009), social risk factors (4·4 [2·0-9·4]; p<0·0001), and be part of a local transmission cluster (4·8 [1·6-14·8]; p=0·006).InterpretationAlthough inward migration has contributed to the overall tuberculosis incidence, our findings suggest that most patients born in high-incidence countries reactivate latent infection acquired abroad and are not involved in local onward transmission. Systematic screening of new entrants could further improve tuberculosis control, but it is important that health care remains accessible to all individuals, especially high-risk groups, if tuberculosis control is not to be jeopardised.FundingUK Clinical Research Collaboration (Wellcome Trust, Medical Research Council, National Institute for Health Research [NIHR]), and NIHR Oxford Biomedical Research Centre.

Project description:Recent years have seen the development of numerous methodologies for reconstructing transmission trees in infectious disease outbreaks from densely sampled whole genome sequence data. However, a fundamental and as of yet poorly addressed limitation of such approaches is the requirement for genetic diversity to arise on epidemiological timescales. Specifically, the position of infected individuals in a transmission tree can only be resolved by genetic data if mutations have accumulated between the sampled pathogen genomes. To quantify and compare the useful genetic diversity expected from genetic data in different pathogen outbreaks, we introduce here the concept of 'transmission divergence', defined as the number of mutations separating whole genome sequences sampled from transmission pairs. Using parameter values obtained by literature review, we simulate outbreak scenarios alongside sequence evolution using two models described in the literature to describe transmission divergence of ten major outbreak-causing pathogens. We find that while mean values vary significantly between the pathogens considered, their transmission divergence is generally very low, with many outbreaks characterised by large numbers of genetically identical transmission pairs. We describe the impact of transmission divergence on our ability to reconstruct outbreaks using two outbreak reconstruction tools, the R packages outbreaker and phybreak, and demonstrate that, in agreement with previous observations, genetic sequence data of rapidly evolving pathogens such as RNA viruses can provide valuable information on individual transmission events. Conversely, sequence data of pathogens with lower mean transmission divergence, including Streptococcus pneumoniae, Shigella sonnei and Clostridium difficile, provide little to no information about individual transmission events. Our results highlight the informational limitations of genetic sequence data in certain outbreak scenarios, and demonstrate the need to expand the toolkit of outbreak reconstruction tools to integrate other types of epidemiological data.

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An observational study of M. tuberculosis transmission in Oxfordshire using whole pathogen genome sequences

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