ORCID Profile
0000-0002-7951-2310
Current Organisation
Weill Cornell Medical College
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Publisher: Cold Spring Harbor Laboratory
Date: 20-08-2018
DOI: 10.1101/396440
Abstract: New antibiotics are needed to combat rising resistance, with new Mycobacterium tuberculosis (Mtb) drugs of highest priority. Conventional whole-cell and biochemical antibiotic screens have failed. We developed a novel strategy termed PROSPECT (PRimary screening Of Strains to Prioritize Expanded Chemistry and Targets) in which we screen compounds against pools of strains depleted for essential bacterial targets. We engineered strains targeting 474 Mtb essential genes and screened pools of 100-150 strains against activity-enriched and unbiased compounds libraries, measuring 8.5-million chemical-genetic interactions. Primary screens identified -fold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insight. We identified 40 novel compounds targeting DNA gyrase, cell wall, tryptophan, folate biosynthesis, and RNA polymerase, as well as inhibitors of a novel target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating PROSPECT’s ability to yield inhibitors against novel targets which would have eluded conventional drug discovery.
Publisher: eLife Sciences Publications, Ltd
Date: 03-02-2022
DOI: 10.7554/ELIFE.74419
Abstract: The outcome of an encounter with Mycobacterium tuberculosis ( Mtb ) depends on the pathogen’s ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically erse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to create a resource for associating bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb transposon mutant fitness (TnSeq) across the CC panel revealed that many virulence pathways are only required in specific host microenvironments, identifying a large fraction of the pathogen’s genome that has been maintained to ensure fitness in a erse population. Both immunological and bacterial traits can be associated with genetic variants distributed across the mouse genome, making the CC a unique population for identifying specific host-pathogen genetic interactions that influence pathogenesis.
Publisher: Cold Spring Harbor Laboratory
Date: 12-2020
DOI: 10.1101/2020.12.01.405514
Abstract: The outcome of an encounter with Mycobacterium tuberculosis depends on the pathogen’s ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically erse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to associate bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb mutant fitness across the CC panel revealed that many virulence pathways are only in specific host microenvironments, identifying the large fraction of the pathogen’s genome that has been maintained to ensure fitness in a erse population. Both immunological and bacterial traits were associated with genetic variants distributed across the mouse genome, identifying the specific host-pathogen genetic interactions that influence pathogenesis.
Publisher: eLife Sciences Publications, Ltd
Date: 24-01-2022
Publisher: Proceedings of the National Academy of Sciences
Date: 05-04-2022
Abstract: Efforts to improve tuberculosis therapy include optimizing multidrug regimens to take advantage of drug–drug synergies. However, the complex host environment has a profound effect on bacterial metabolic state and drug activity, making predictions of optimal drug combinations difficult. In this study, we leverage a newly developed library of conditional knockdown Mycobacterium tuberculosis mutants in which genetic depletion of essential genes mimics the effect of drug therapy. This tractable system allowed us to assess the effect of growth condition on predicted drug–drug interactions. We found that these interactions can be differentially sensitive to the metabolic state, and select in vitro–defined interactions can be leveraged to accelerate bacterial killing during infection. These findings suggest strategies for optimizing tuberculosis therapy.
No related grants have been discovered for Sabine Ehrt.