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High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds.

ABSTRACT: Rapidly spreading antibiotic resistance and the low discovery rate of new antimicrobial compounds demand more effective strategies for early drug discovery. One bottleneck in the drug discovery pipeline is the identification of the modes of action (MoAs) of new compounds. We have developed a rapid systematic metabolome profiling strategy to classify the MoAs of bioactive compounds. The method predicted MoA-specific metabolic responses in the nonpathogenic bacterium Mycobacterium smegmatis after treatment with 62 reference compounds with known MoAs and different metabolic and nonmetabolic targets. We then analyzed a library of 212 new antimycobacterial compounds with unknown MoAs from a drug discovery effort by the pharmaceutical company GlaxoSmithKline (GSK). More than 70% of these new compounds induced metabolic responses in M. smegmatis indicative of known MoAs, seven of which were experimentally validated. Only 8% (16) of the compounds appeared to target unconventional cellular processes, illustrating the difficulty in discovering new antibiotics with different MoAs among compounds used as monotherapies. For six of the GSK compounds with potentially new MoAs, the metabolome profiles suggested their ability to interfere with trehalose and lipid metabolism. This was supported by whole-genome sequencing of spontaneous drug-resistant mutants of the pathogen Mycobacterium tuberculosis and in vitro compound-proteome interaction analysis for one of these compounds. Our compendium of drug-metabolome profiles can be used to rapidly query the MoAs of uncharacterized antimicrobial compounds and should be a useful resource for the drug discovery community.

SUBMITTER: Zampieri M

PROVIDER: S-EPMC6544516 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds.

Zampieri Mattia M Szappanos Balazs B Buchieri Maria Virginia MV Trauner Andrej A Piazza Ilaria I Picotti Paola P Picotti Paola P Gagneux Sébastien S Borrell Sonia S Gicquel Brigitte B Lelievre Joel J Papp Balazs B Sauer Uwe U

Science translational medicine 20180201 429

Rapidly spreading antibiotic resistance and the low discovery rate of new antimicrobial compounds demand more effective strategies for early drug discovery. One bottleneck in the drug discovery pipeline is the identification of the modes of action (MoAs) of new compounds. We have developed a rapid systematic metabolome profiling strategy to classify the MoAs of bioactive compounds. The method predicted MoA-specific metabolic responses in the nonpathogenic bacterium <i>Mycobacterium smegmatis</i> ...[more]

PMID: 29467300

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Project description:BACKGROUND: Benefits from high-throughput sequencing using 454 pyrosequencing technology may be most apparent for species with high societal or economic value but few genomic resources. Rapid means of gene sequence and SNP discovery using this novel sequencing technology provide a set of baseline tools for genome-level research. However, it is questionable how effective the sequencing of large numbers of short reads for species with essentially no prior gene sequence information will support contig assemblies and sequence annotation. RESULTS: With the purpose of generating the first broad survey of gene sequences in Eucalyptus grandis, the most widely planted hardwood tree species, we used 454 technology to sequence and assemble 148 Mbp of expressed sequences (EST). EST sequences were generated from a normalized cDNA pool comprised of multiple tissues and genotypes, promoting discovery of homologues to almost half of Arabidopsis genes, and a comprehensive survey of allelic variation in the transcriptome. By aligning the sequencing reads from multiple genotypes we detected 23,742 SNPs, 83% of which were validated in a sample. Genome-wide nucleotide diversity was estimated for 2,392 contigs using a modified theta (theta) parameter, adapted for measuring genetic diversity from polymorphisms detected by randomly sequencing a multi-genotype cDNA pool. Diversity estimates in non-synonymous nucleotides were on average 4x smaller than in synonymous, suggesting purifying selection. Non-synonymous to synonymous substitutions (Ka/Ks) among 2,001 contigs averaged 0.30 and was skewed to the right, further supporting that most genes are under purifying selection. Comparison of these estimates among contigs identified major functional classes of genes under purifying and diversifying selection in agreement with previous researches. CONCLUSION: In providing an abundance of foundational transcript sequences where limited prior genomic information existed, this work created part of the foundation for the annotation of the E. grandis genome that is being sequenced by the US Department of Energy. In addition we demonstrated that SNPs sampled in large-scale with 454 pyrosequencing can be used to detect evolutionary signatures among genes, providing one of the first genome-wide assessments of nucleotide diversity and Ka/Ks for a non-model plant species.

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High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds.

Publications

High-throughput metabolomic analysis predicts mode of action of uncharacterized antimicrobial compounds.

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