title: Interpreting whole genome sequencing for investigating tuberculosis transmission: a systematic review.
abstract: BACKGROUND
  Whole genome sequencing (WGS) is becoming an important part of epidemiological investigations of infectious diseases due to greater resolution and cost reductions compared to traditional typing approaches. Many public health and clinical teams will increasingly use WGS to investigate clusters of potential pathogen transmission, making it crucial to understand the benefits and assumptions of the analytical methods for investigating the data. We aimed to understand how different approaches affect inferences of transmission dynamics and outline limitations of the methods.
  
  
  METHODS
  We comprehensively searched electronic databases for studies that presented methods used to interpret WGS data for investigating tuberculosis (TB) transmission. Two authors independently selected studies for inclusion and extracted data. Due to considerable methodological heterogeneity between studies, we present summary data with accompanying narrative synthesis rather than pooled analyses.
  
  
  RESULTS
  Twenty-five studies met our inclusion criteria. Despite the range of interpretation tools, the usefulness of WGS data in understanding TB transmission often depends on the amount of genetic diversity in the setting. Where diversity is small, distinguishing re-infections from relapses may be impossible; interpretation may be aided by the use of epidemiological data, examining minor variants and deep sequencing. Conversely, when within-host diversity is large, due to genetic hitchhiking or co-infection of two dissimilar strains, it is critical to understand how it arose. Greater understanding of microevolution and mixed infection will enhance interpretation of WGS data.
  
  
  CONCLUSIONS
  As sequencing studies have sampled more intensely and integrated multiple sources of information, the understanding of TB transmission and diversity has grown, but there is still much to be learnt about the origins of diversity that will affect inferences from these data. Public health teams and researchers should combine epidemiological, clinical and WGS data to strengthen investigations of transmission.
authors.affiliation: CoMPLEX, University College London, London, WC1E 6BT, UK. hollie-ann.hatherell.13@ucl.ac.uk.|Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK. hollie-ann.hatherell.13@ucl.ac.uk.
authors.forename: Hollie-Ann
authors.initials: HA
authors.lastname: Hatherell
authors.affiliation: Department of Mathematics, Imperial College London, London, SW7 2AZ, UK.
authors.forename: Caroline
authors.initials: C
authors.lastname: Colijn
authors.affiliation: Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK.
authors.forename: Helen R
authors.initials: HR
authors.lastname: Stagg
authors.affiliation: Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK.
authors.forename: Charlotte
authors.initials: C
authors.lastname: Jackson
authors.affiliation: Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK.
authors.forename: Joanne R
authors.initials: JR
authors.lastname: Winter
authors.affiliation: Centre for Infectious Disease Epidemiology, Infection and Population Health, University College London, London, WC1E 6JB, UK.|Medical Research Council Clinical Trials Unit, 125 Kingsway, London, WC2B 6NH, UK.
authors.forename: Ibrahim
authors.initials: I
authors.lastname: Abubakar
mesh_terms: D015373:Bacterial Typing Techniques / Q000379:methods*; D014644:Genetic Variation; D016680:Genome, Bacterial; D055106:Genome-Wide Association Study; D006801:Humans; D009169:Mycobacterium tuberculosis / Q000145:classification / Q000235:genetics*; D012008:Recurrence; D017422:Sequence Analysis, DNA; D014376:Tuberculosis / Q000235:genetics / Q000635:transmission*
keywords: Systematic review; Transmission; Tuberculosis; Whole genome sequencing