Identification of a Drug Candidate against Mycobacterium avium Using Pandemic Response Box
- Authors
- Jeon, Seunghyeon; Lee, Yubin; Yun, Jihyeon; Heo, Bo Eun; Ash, Anwesha; Moon, Cheol; Yang, Chul-Su; Jang, Jichan
- Issue Date
- Aug-2025
- Publisher
- 한국미생물·생명공학회
- Keywords
- Mycobacterium avium complex (MAC); nontuberculous mycobacteria (NTM); extrapulmonary infections; clorhexidine (CHX); alexidine (AX); skin infections
- Citation
- Journal of Microbiology and Biotechnology, v.35, pp 1 - 10
- Pages
- 10
- Indexed
- SCIE
SCOPUS
KCI
- Journal Title
- Journal of Microbiology and Biotechnology
- Volume
- 35
- Start Page
- 1
- End Page
- 10
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/79893
- DOI
- 10.4014/jmb.2506.06006
- ISSN
- 1017-7825
1738-8872
- Abstract
- MAC (Mycobacterium avium complex) is a naturally occurring environmental microorganism found worldwide in sources such as soil and water. Among nontuberculous mycobacteria (NTM), MAC is the species most commonly responsible for pulmonary infections, particularly in immunocompromised individuals. In addition to pulmonary disease, extrapulmonary M. avium infections can present as disseminated, cutaneous, or lymphatic diseases. Skin infections caused by M. avium can vary significantly between patients, with both localized and disseminated forms observed. Despite the increasing prevalence of extrapulmonary NTM infections, treatment outcomes remain suboptimal, underscoring the need for novel therapeutic strategies. In this study, we conducted in vitro dual-screening using the Pandemic Response Box against M. avium 104, and identified alexidine (AX) as a promising candidate for therapy. Further evaluation demonstrated that chlorhexidine (CHX), a structurally distinct bis-biguanide compound, also exhibited potent inhibitory activity against M. avium growth in vitro, as well as in a zebrafish model of M. avium infection and treatment. These findings suggest that CHX may be a potential therapeutic candidate for treating M. avium skin infections.
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- 학과간협동과정 > 바이오의료빅데이터학과 > Journal Articles

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