Biology subjects

Hunt, D. K.

Publications and source records attributed to Hunt, D. K..

3 recordsLinked to original sources

bioRxiv2026

Large-Scale Chemical-Genetic Interaction Profiling Identifies a Novel Small-Molecule Inhibitor of Mycobacterium tuberculosis Polyketide Synthase 13

PROSPECT (PRimary screening Of Strains to Prioritize Expanded Chemistry and Targets) is an antimicrobial discovery platform based on chemical-genetic interaction (CGI) profiling of compounds against a pool of Mycobacterium tuberculosis (Mtb) hypomorphs, each depleted of an essential gene. From prior screening data, we have now identified a novel N-oxolan-3-yl pyrazole carboxamide inhibitor (BRD1554) that had increased, selective activity against strains depleted of polyketide synthase 13 (Pks13), an essential enzyme in mycolic acid synthesis, and Rv2581c, an uncharacterized protein similar to glyoxylase II enzymes. Perturbagen CLass (PCL) analysis, a reference-based approach to mechanism of action (MOA) assignment from PROSPECT, predicted Pks13, a polyketide synthase with five catalytic domains responsible for the terminal condensation step in mycolic acid biosynthesis, was the likely target, potentially implicating the thioesterase domain. We synthesized a more active analogue while assigning the absolute stereochemistry of the active diastereomer, resulting in 1554-06-3R,4S with an MIC90 of 3.0 {micro}M against Mtb H37Rv. Exposure to 1554-06 led to the upregulation of the pks13 operon along with the iniBAC operon and other genes linked to mycolic acid synthesis. Isolation of mutants resistant to 1554-06 revealed single nucleotide polymorphisms in the thioesterase domain of Pks13. Finally, we biochemically confirmed that 1554-06 inhibits the activity of recombinant Pks13 thioesterase domain, with computational docking of 1554-06 steroisomers consistent with the stereospecific activity seen in whole cell assays. We found unique chemical genetic interactions between inhibitors of the different Pks13 domains and different detoxifying enzymes of Mtb, thus revealing novel gene-gene interactions. These results highlight how PROSPECT can not only immediately reveal, with domain-level resolution, the MOA of new whole-cell active chemical inhibitors of Mtb, allowing the integration of biological insight into compound triage and accelerated early development, but can also illuminate genetic interactions linked to those mechanisms that could inform predictions of synergy for antitubercular drug development. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/704361v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@9a4f38org.highwire.dtl.DTLVardef@c70cd2org.highwire.dtl.DTLVardef@1ac2e1org.highwire.dtl.DTLVardef@f06df0_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2025

Reference-based chemical-genetic interaction profiling to elucidate small molecule mechanism of action in Mycobacterium tuberculosis

In an era of increasing resistance, new and effective strategies are needed for antibiotic discovery. Whole-cell active screens yield candidate compounds lacking mechanism-of-action (MOA) information and thus do not provide biological insight for prioritization. We previously reported PROSPECT (PRimary screening Of Strains to Prioritize Expanded Chemistry and Targets), an antimicrobial discovery strategy that measures chemical-genetic interactions between small molecules and a pool of Mycobacterium tuberculosis mutants, each depleted of a different essential protein target. PROSPECT facilitates efficient hit prioritization by simultaneously identifying whole-cell active compounds with high sensitivity and providing early insights into their MOA. Here, we report a reference-based approach to infer MOA from often complex PROSPECT data. For this aim, we curated a reference set of 437 compounds with published, annotated MOA and known or suspected antitubercular activity, and applied PROSPECT to it. We then developed Perturbagen CLass (PCL) analysis, a computational method that predicts MOA by comparing chemical-genetic interaction profiles of unknown compounds to those of this reference set. In leave-one-out cross-validation, PCL analysis correctly predicted MOA with 70% sensitivity and 75% precision. When applied to 75 antitubercular leads with known MOA previously reported by GlaxoSmithKline (GSK), PCL analysis similarly achieved 69% sensitivity and 87% precision. We also analyzed 98 GSK compounds lacking MOA information, predicting 60 of them to act via a reference MOA, and followed up with functional validation of 29 compounds predicted to target respiration-related MOAs. Finally, we applied PROSPECT and PCL analysis to [~]5,000 compounds from larger unbiased libraries that had not been preselected for antitubercular activity. PCL analysis identified a novel scaffold lacking wild-type activity but predicted to inhibit respiration via QcrB, and we confirmed this prediction while chemically optimizing this scaffold to achieve wild-type activity. PCL analysis of PROSPECT data thus enables rapid MOA assignment and hit prioritization, advancing the discovery of new, potent antitubercular compounds.

microbiology↗

bioRxiv2024

Massively parallel combination screen reveals small molecule sensitization of antibiotic-resistant Gram-negative ESKAPE pathogens

Antibiotic resistance, especially in multidrug-resistant ESKAPE pathogens, remains a worldwide problem. Combination antimicrobial therapies may be an important strategy to overcome resistance and broaden the spectrum of existing antibiotics. However, this strategy is limited by the ability to efficiently screen large combinatorial chemical spaces. Here, we deployed a high-throughput combinatorial screening platform, DropArray, to evaluate the interactions of over 30,000 compounds with up to 22 antibiotics and 6 strains of Gram-negative ESKAPE pathogens, totaling to over 1.3 million unique strain-antibiotic-compound combinations. In this dataset, compounds more frequently exhibited synergy with known antibiotics than single-agent activity. We identified a compound, P2-56, and developed a more potent analog, P2-56-3, which potentiated rifampin (RIF) activity against Acinetobacter baumannii and Klebsiella pneumoniae. Using phenotypic assays, we showed P2-56-3 disrupts the outer membrane of A. baumannii. To identify pathways involved in the mechanism of synergy between P2-56-3 and RIF, we performed genetic screens in A. baumannii. CRISPRi-induced partial depletion of lipooligosaccharide transport genes (lptA-D, lptFG) resulted in hypersensitivity to P2-56-3/RIF treatment, demonstrating the genetic dependency of P2-56-3 activity and RIF sensitization on lpt genes in A. baumannii. Consistent with outer membrane homeostasis being an important determinant of P2-56-3/RIF tolerance, knockout of maintenance of lipid asymmetry complex genes and overexpression of certain resistance-nodulation-division efflux pumps - a phenotype associated with multidrug-resistance - resulted in hypersensitivity to P2-56-3. These findings demonstrate the immense scale of phenotypic antibiotic combination screens using DropArray and the potential for such approaches to discover new small molecule synergies against multidrug-resistant ESKAPE strains. Significance StatementThere is an unmet need for new antibiotic therapies effective against the multidrug-resistant, Gram-negative ESKAPE pathogens. Combination therapies have the potential to overcome resistance and broaden the spectrum of existing antibiotics. In this study, we use DropArray, a massively parallel combinatorial screening tool, to assay more than 1.3 million combinations of small molecules against the Gram-negative ESKAPE pathogens, Acinetobacter baumannii, Klebsiella pneumoniae, and Pseudomonas aeruginosa. We discovered a synthetic small molecule potentiator, P2-56, of the antibiotic rifampin effective in A. baumannii and K. pneumoniae. We generated P2-56-3, a more potent derivative of P2-56, and found that it likely potentiates rifampin by compromising the outer membrane integrity. Our study demonstrates a high-throughput strategy for identifying antibiotic potentiators against multidrug-resistant bacteria.

microbiology↗