Abstract
The prospect of using whole genome sequence data to investigate bacterial disease outbreaks has been keenly anticipated in many quarters, and the large-scale collection and sequencing of isolates from cases is becoming increasingly feasible. While sequence data can provide many important insights into disease spread and pathogen adaptation, it remains unclear how successfully they may be used to estimate individual routes of transmission. Several studies have attempted to reconstruct transmission routes using genomic data; however, these have typically relied upon restrictive assumptions, such as a shared topology of the phylogenetic tree and a lack of within-host diversity. In this study, we investigated the potential for bacterial genomic data to inform transmission network reconstruction. We used simulation models to investigate the origins, persistence and onward transmission of genetic diversity, and examined the impact of such diversity on our estimation of the epidemiological relationship between carriers. We used a flexible distance-based metric to provide a weighted transmission network, and used receiver-operating characteristic (ROC) curves and network entropy to assess the accuracy and uncertainty of the inferred structure. Our results suggest that sequencing a single isolate from each case is inadequate in the presence of within-host diversity, and is likely to result in misleading interpretations of transmission dynamics – under many plausible conditions, this may be little better than selecting transmission links at random. Sampling more frequently improves accuracy, but much uncertainty remains, even if all genotypes are observed. While it is possible to discriminate between clusters of carriers, individual transmission routes cannot be resolved by sequence data alone. Our study demonstrates that bacterial genomic distance data alone provide only limited information on person-to-person transmission dynamics.
Highlights
Population genomic studies have become essential tools in studying the global spread [1] and evolutionary adaptation [2] of infectious agents
With the advent of affordable large-scale genome sequencing for bacterial pathogens, there is much interest in using such data to identify who infected whom in a disease outbreak
We demonstrated that failing to account for within-host diversity can lead to poor network reconstructions - even with repeated sampling of each carrier, there is still much uncertainty in the estimated structure
Summary
Population genomic studies have become essential tools in studying the global spread [1] and evolutionary adaptation [2] of infectious agents. Falling costs and technological advances offer the prospect of using whole pathogen genome sequences to investigate individual, localized outbreaks and identify chains of transmission. The ability to identify infection routes would contribute much to the understanding of transmission dynamics, contact patterns in an at-risk population and the optimization of infection control strategies [3]. Aspects of bacterial carriage and transmission are still poorly understood, making the interpretation of genomic data collected from outbreaks far from straightforward. As whole genome sequence data for bacterial pathogens become ever more abundant, it is important to understand both the potential and limitations associated with this information
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