Combining CRISPRi and metabolomics for functional annotation of compound libraries

Miquel Anglada-Girotto, Gabriel Handschin, Karin Ortmayr, Adrian I. Campos, Ludovic Gillet, Pablo Manfredi, Claire V. Mulholland, Michael Berney, Urs Jenal, Paola Picotti, Mattia Zampieri

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Molecular profiling of small molecules offers invaluable insights into the function of compounds and allows for hypothesis generation about small-molecule direct targets and secondary effects. However, current profiling methods are limited in either the number of measurable parameters or throughput. Here we developed a multiplexed, unbiased framework that, by linking genetic to drug-induced changes in nearly a thousand metabolites, allows for high-throughput functional annotation of compound libraries in Escherichia coli. First, we generated a reference map of metabolic changes from CRISPR interference (CRISPRi) with 352 genes in all major essential biological processes. Next, on the basis of the comparison of genetic changes with 1,342 drug-induced metabolic changes, we made de novo predictions of compound functionality and revealed antibacterials with unconventional modes of action (MoAs). We show that our framework, combining dynamic gene silencing with metabolomics, can be adapted as a general strategy for comprehensive high-throughput analysis of compound functionality from bacteria to human cell lines. [Figure not available: see fulltext.]

Original languageEnglish (US)
Pages (from-to)482-491
Number of pages10
JournalNature Chemical Biology
Volume18
Issue number5
DOIs
StatePublished - May 2022

ASJC Scopus subject areas

  • Molecular Biology
  • Cell Biology

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