Integration of multi-modal measurements identifies critical mechanisms of tuberculosis drug action
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ABSTRACT: Treatments for tuberculosis remain lengthy, motivating a search for new drugs with novel mechanisms of action. However, it remains challenging to elucidate the direct targets of a drug, and even more so, to determine which disrupted cellular processes lead to bacterial killing. We developed a computational tool, DECIPHAER (Decoding Cross-modal Information of Pharmacologies via AutoEncodeRs), to select correlated transcriptional and morphological responses of Mycobacterium tuberculosis to drug treatments. By finding a latent space from these measurements, DECIPHAER highlighted important features of Mtb cellular damage such as phosphosugar stress and inhibition of translation and DNA replication. After training, DECIPHAER provides cell-death-relevant insight into even single-modal datasets, enabling interrogation of drug treatment responses for which transcriptional data are not available. Using only morphological data with DECIPHAER, we discovered that respiration inhibition by the poly-pharmacological drugs, SQ109 and BM212, can be their primary mechanism influencing cell death, not their effect 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.
ORGANISM(S): Mycobacterium tuberculosis
PROVIDER: GSE267556 | GEO | 2025/07/29
REPOSITORIES: GEO
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