The 94th Annual Meeting of Japanese Society for Bacteriology

Presentation information

Workshop

[WS9] Selected from Oral Session: Virulence Factors and Biophylaxis: Infection Models, Parasitism, Immunity, Vaccines / Pathogens and Infectious Diseases

Thu. Mar 25, 2021 12:45 PM - 2:45 PM Channel 3

Conveners: Yukako Fujinaga (Kanazawa University), Tomoko Sumitomo (Osaka University)

[WS9-6/ODP-110] bGWAS reveals putative bacterial factors that affect pathological outcomes of MAC lung disease

○Hirokazu Yano1, Yukiko Nishiuchi2, Kentaro Arikawa3, Atsushi Ota4, Mari Miki5, Fumito Maruyama4, Hiroshi Kida5, Seigo Kitada5, Tomotada Iwamoto3 (1Grad. Sch. Life Sciences, Tohoku Univ., 2Grad Sch. Medicine, Osaka City Univ., 3Kobe Institute of Health, 4Center for Holobiome and Built Environment (CHOBE), Hiroshima Univ., 5National Hospital Organization Osaka Toneyama Medical Center)

Mycobacterium avium, the causative agent of MAC lung disease, is a recombinogenic opportunistic pathogen that has a considerable genetic diversity even in a local population. There are roughly two case types in MAC lung disease. One is the stable type that accompanies nodular bronchiectasis alone as pathological outcome. The other is the progressive type that eventually complicates fibrocavitary. What determines the case type remains an open question. In this study, we address the hypothesis that genetic factors of M. avium affect the pathological outcomes using the bacterial genome-wide association study (bGWAS) approach. We collected M. avium isolates from 107 patients falling into either of the two case types (46 stable, 61 progressive), determined their draft genome sequences, and then searched for DNA motifs associated with the case type using k-mers based GWAS. Besides known antimicrobial resistance mutations, we found the case type-associated allelic variant in the genes encoding Type I polyketide synthase, FAD-dependent monooxygenase, cytochrome P-450, and a dehydrogenase involved in arginine metabolism. This result suggests that bacterial factors in part contribute to pathological outcomes. As long-term antimicrobial treatment is a burden for patients, DNA motifs in the pathogen genome may help us design the treatment plan.