PT  - JOURNAL ARTICLE
AU  - Andrea Sanchini
AU  - Christine Jandrasits
AU  - Julius Tembrockhaus
AU  - Thomas Andreas Kohl
AU  - Christian Utpatel
AU  - Florian P. Maurer
AU  - Stefan Niemann
AU  - Walter Haas
AU  - Bernhard Y. Renard
AU  - Stefan Kröger
TI  - Improving tuberculosis surveillance by detecting international transmission using publicly available whole-genome sequencing data
AID  - 10.1101/834150
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 834150
4099  - http://biorxiv.org/content/early/2019/11/08/834150.short
4100  - http://biorxiv.org/content/early/2019/11/08/834150.full
AB  - Introduction Improving the surveillance of tuberculosis (TB) is especially important for multidrug-resistant (MDR) and extensively drug-resistant (XDR)-TB. The large amount of publicly available whole-genome sequencing (WGS) data for TB gives us the chance to re-use data and to perform additional analysis at a large scale.Aim We investigated to what extent we could use globally available WGS raw data of MDR/XDR-TB isolates available from the public sequence repositories to improve TB surveillance.Methods We extracted raw WGS data and the related metadata of Mycobacterium tuberculosis isolates available from the Sequence Read Archive. We compared this public dataset with WGS data and metadata of 131 MDR- and XDR-TB isolates from Germany in 2012-2013.Results We aggregated a dataset that includes 1,081 MDR and 250 XDR isolates among which we identified 133 molecular clusters. In 16 clusters, the isolates were from at least two different countries. For example, cluster2 included 56 MDR/XDR isolates from Moldova, Georgia, and Germany. By comparing the WGS data from Germany and the public dataset, we found that 11 clusters contained at least one isolate from Germany and at least one isolate from another country. We could, therefore, connect TB cases despite missing epidemiological information.Conclusion We demonstrated the added value of using WGS raw data from public repositories to contribute to TB surveillance. By comparing the German and the public dataset, we identified potential international transmission events. Thus, using this approach might support the interpretation of national surveillance results in an international context.