2025-08-25 タフツ大学
A “death portrait” of TB bacteria treated with an antibiotic and stained to show physical features of individual cells. Image: Courtesy of the Aldridge Lab
<関連情報>
- https://now.tufts.edu/2025/08/25/new-ai-tool-reveals-how-drugs-kill-tuberculosis
- https://www.cell.com/cell-systems/fulltext/S2405-4712(25)00181-4
多模態測定の統合により、結核薬の作用メカニズムの重要な要因を特定 Integration of multi-modal measurements identifies critical mechanisms of tuberculosis drug action
William C. Johnson ∙ Ares Alivisatos ∙ Trever C. Smith, II ∙ … ∙ Dirk Schnappinger ∙ Kyu Y. Rhee ∙ Bree B. Aldridge
Cell Systems Published:July 29, 2025
DOI:https://doi.org/10.1016/j.cels.2025.101348
Highlights
- Measurement of multi-omic antibiotic response profiles for tuberculosis
- Integration of multi-omic data highlights core treatment-response features
- A shared space enables translation from morphological to transcriptomic responses
- Discovery of complex mechanisms of action of antibiotics with polypharmacologies
Summary
Treatments for tuberculosis remain lengthy, motivating a search for new drugs with novel mechanisms of action. However, it remains challenging to determine the direct targets of a drug and which disrupted cellular processes lead to bacterial killing. We developed a computational tool, DECIPHAER (decoding cross-modal information of pharmacologies via autoencoders), to select the important correlated transcriptional and morphological responses of Mycobacterium tuberculosis to treatment. By finding a reduced feature space, DECIPHAER highlighted essential features of cellular damage. DECIPHAER provides cell-death-relevant insight into uni-modal datasets, enabling interrogation of drug treatment responses for which transcriptional data are unavailable. Using morphological data alone with DECIPHAER, we discovered that respiration inhibition by the polypharmacological drugs SQ109 and BM212 can influence cell death more than their effects on the cell wall. This study demonstrates that DECIPHAER can extract the critical shared information from multi-modal measurements to identify cell-death-relevant mechanisms of TB drugs. A record of this paper’s transparent peer review process is included in the supplemental information.
