High-throughput chemical genomic screening: a step-by-step workflow from plate to phenotype

High-throughput chemical genomics uses phenotypic profiling of strain libraries under defined chemical and environmental conditions to identify gene functions. This approach enables the mapping of biological pathways and can potentially highlight drug targets. Chemical genomic data sets have been springboards for numerous hypothesis-driven research projects, with direct implications for antimicrobial resistance and clinical outcomes. High-throughput phenotypic profiles are valuable tools for enriching microbial sequence data with functional annotations and benefiting the broader scientific community. This work provides a step-by-step guide for conducting chemical genomics screens from start to finish.IMPORTANCEChemical genomic screening is a powerful systems biology approach for linking gene function to phenotype under diverse chemical and environmental stressors. However, its broader use in microbial research has been limited by the lack of standardized, reproducible workflows. Our study introduces a scalable, end-to-end protocol that integrates experimental, imaging, and computational steps into a cohesive framework for high-throughput screening across a range of microbial species. This enables researchers to generate consistent, high-quality phenotypic data suitable for large-scale analyses. The protocol supports systematic exploration of gene-environment interactions, microbial stress responses, and antimicrobial resistance. Its adaptability and troubleshooting guidance make it especially useful for groups working in microbiome research, synthetic biology, and microbial community studies. By bridging benchwork and computational analysis, this workflow expands the technical toolkit available to microbial systems biologists. Our work contributes to the development of robust methods for functional genomics and supports the core mission of mSystems to advance microbial systems biology.

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Publication Details

Journal
mSystems
Published
2025-11-28
DOI
https://doi.org/10.1128/msystems.00885-25
Citations
2
Primary Topic
Bioinformatics and Genomic Networks
Type
article
Field-Weighted Citation Impact
1.61
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article

High-throughput chemical genomic screening: a step-by-step workflow from plate to phenotype

Patrick J. Moynihan, Hannah M. Doherty, Danesh Moradigaravand, Micheal B. Alao et al.
2 citations
mSystems
Bioinformatics and Genomic Networks
1.61
article

High-throughput chemical genomic screening: a step-by-step workflow from plate to phenotype

Patrick J. Moynihan, Hannah M. Doherty, Danesh Moradigaravand, Micheal B. Alao, Monika Katarzyna Glinkowska, Peter Banks, Xuyu Ma, Jack Alfred Bryant, Huda Ahmad, Manuel Banzhaf, Rudi Sullivan, Qianhui Xu, Mathew Milner, James R. J. Haycocks, G.D. Williams, Susan Sutherland, Stephen H. Benedict, Ailsa Hart
article en
2 citations

Abstract

High-throughput chemical genomics uses phenotypic profiling of strain libraries under defined chemical and environmental conditions to identify gene functions. This approach enables the mapping of biological pathways and can potentially highlight drug targets. Chemical genomic data sets have been springboards for numerous hypothesis-driven research projects, with direct implications for antimicrobial resistance and clinical outcomes. High-throughput phenotypic profiles are valuable tools for enriching microbial sequence data with functional annotations and benefiting the broader scientific community. This work provides a step-by-step guide for conducting chemical genomics screens from start to finish.IMPORTANCEChemical genomic screening is a powerful systems biology approach for linking gene function to phenotype under diverse chemical and environmental stressors. However, its broader use in microbial research has been limited by the lack of standardized, reproducible workflows. Our study introduces a scalable, end-to-end protocol that integrates experimental, imaging, and computational steps into a cohesive framework for high-throughput screening across a range of microbial species. This enables researchers to generate consistent, high-quality phenotypic data suitable for large-scale analyses. The protocol supports systematic exploration of gene-environment interactions, microbial stress responses, and antimicrobial resistance. Its adaptability and troubleshooting guidance make it especially useful for groups working in microbiome research, synthetic biology, and microbial community studies. By bridging benchwork and computational analysis, this workflow expands the technical toolkit available to microbial systems biologists. Our work contributes to the development of robust methods for functional genomics and supports the core mission of mSystems to advance microbial systems biology.

mSystemsVol. 10(12)
University of Nottingham (GB), University of Gdańsk (PL), King Abdullah University of Science and Technology (SA), University of Birmingham (GB), Newcastle University (GB)
Openalex Percentile: Top 14%
Bioinformatics and Genomic Networks
1.61
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