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      Identifying mixed Mycobacterium tuberculosis infection and laboratory cross-contamination during Mycobacterial sequencing programs

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          Abstract

          Introduction: Detecting laboratory cross-contamination and mixed tuberculosis infection are important goals of clinical Mycobacteriology laboratories. Objectives: To develop a method detecting mixtures of different M. tuberculosis lineages in laboratories performing Mycobacterial next generation sequencing (NGS). Setting: Public Health England Regional Mycobacteriology Laboratory Birmingham, which performs Illumina sequencing on DNA extracted from positive Mycobacterial Growth Indicator tubes. Methods: We analysed 4,156 samples yielding M. tuberculosis from 663 MiSeq runs, obtained during development and production use of a diagnostic process using NGS. Counts of the most common (major) variant, and all other variants (non-major variants) were determined from reads mapping to positions defining M. tuberculosis lineages. Expected variation was estimated during process development. Results: For each sample we determined the non-major variant proportions at 55 sets of lineage defining positions. The non-major variant proportion in the two most mixed lineage defining sets (F2 metric) was compared with that in the 47 least mixed lineage defining sets (F47 metric). Three patterns were observed: (i) not mixed by either metric, (ii) high F47 metric suggesting mixtures of multiple lineages, and (iii) samples compatible with mixtures of two lineages, detected by differential F2 metric elevation relative to F47. Pattern (ii) was observed in batches, with similar patterns in the H37Rv control present in each run, and is likely to reflect cross-contamination. During production, the proportions of samples in each pattern were 97%, 2.8%, and 0.001%, respectively. Conclusion: The F2 and F47 metrics described could be used for laboratory process control in laboratories sequencing M. tuberculosis .

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          Author and article information

          Journal
          bioRxiv
          June 12 2018
          Article
          10.1101/344853
          a5cab625-f2fc-45e7-a470-986fead3f662
          © 2018
          History

          Microbiology & Virology
          Microbiology & Virology

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