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Lu X, Hackman GL, Saha A, Rathore AS, Collins M, Friedman C, Yi SS, Matsuda F, DiGiovanni J, Lodi A, Tiziani S. Metabolomics-based phenotypic screens for evaluation of drug synergy via direct-infusion mass spectrometry. iScience 2022; 25:104221. [PMID: 35494234 PMCID: PMC9046262 DOI: 10.1016/j.isci.2022.104221] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/22/2022] [Accepted: 04/05/2022] [Indexed: 12/15/2022] Open
Abstract
Drugs used in combination can synergize to increase efficacy, decrease toxicity, and prevent drug resistance. While conventional high-throughput screens that rely on univariate data are incredibly valuable to identify promising drug candidates, phenotypic screening methodologies could be beneficial to provide deep insight into the molecular response of drug combination with a likelihood of improved clinical outcomes. We developed a high-content metabolomics drug screening platform using stable isotope-tracer direct-infusion mass spectrometry that informs an algorithm to determine synergy from multivariate phenomics data. Using a cancer drug library, we validated the drug screening, integrating isotope-enriched metabolomics data and computational data mining, on a panel of prostate cell lines and verified the synergy between CB-839 and docetaxel both in vitro (three-dimensional model) and in vivo. The proposed unbiased metabolomics screening platform can be used to rapidly generate phenotype-informed datasets and quantify synergy for combinatorial drug discovery.
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Affiliation(s)
- Xiyuan Lu
- Department of Nutritional Sciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA,Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78723, USA
| | - G. Lavender Hackman
- Department of Nutritional Sciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA,Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78723, USA
| | - Achinto Saha
- Division of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Austin,TX 78712, USA
| | - Atul Singh Rathore
- Department of Nutritional Sciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA,Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78723, USA
| | - Meghan Collins
- Department of Nutritional Sciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA,Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78723, USA
| | - Chelsea Friedman
- Division of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Austin,TX 78712, USA
| | - S. Stephen Yi
- Department of Oncology, Dell Medical School, Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78723, USA,Institute for Cellular and Molecular Biology (ICMB), College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA,Department of Biomedical Engineering, Cockrell School of Engineering, The University of Texas at Austin, Austin, TX 78712, USA,Oden Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin, Austin, TX 78712, USA
| | - Fumio Matsuda
- Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, 1-5 Yamadaoka, Suita, Osaka, 565-0871, Japan
| | - John DiGiovanni
- Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78723, USA,Division of Pharmacology and Toxicology, College of Pharmacy, The University of Texas at Austin, Austin,TX 78712, USA,Department of Oncology, Dell Medical School, Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78723, USA
| | - Alessia Lodi
- Department of Nutritional Sciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA,Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78723, USA,Corresponding author
| | - Stefano Tiziani
- Department of Nutritional Sciences, College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA,Department of Pediatrics, Dell Medical School, The University of Texas at Austin, Austin, TX 78723, USA,Department of Oncology, Dell Medical School, Livestrong Cancer Institutes, The University of Texas at Austin, Austin, TX 78723, USA,Institute for Cellular and Molecular Biology (ICMB), College of Natural Sciences, The University of Texas at Austin, Austin, TX 78712, USA,Corresponding author
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Cliffe FE, Lyons M, Murphy DC, McInerney L, Hurley N, Galvin MA, Mulqueen J, Bible LB, Marella C, Kelleher M, O'Sullivan A, Fearnhead HO, O'Connell E, Davies M. Droplet Combinations: A Scalable Microfluidic Platform for Biochemical Assays. SLAS Technol 2019; 25:140-150. [PMID: 31665958 DOI: 10.1177/2472630319883830] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
Droplet-based microfluidics holds enormous potential for transforming high-throughput drug screening. Miniaturization through droplets in combination with automation contributes to reduce reagent use and analysis time as well as minimizing or eliminating labor-intensive steps leading to associated reductions in cost. In this paper, we demonstrate the potential of automated and cost-effective microfluidic droplet-generating technology in the context of an enzymatic activity assay for screening collagenase inhibitors. Experimental results show reproducible and accurate creation and mixing of droplet combinations resulting in biochemical data comparable to data produced by an industry standard instrument. This microfluidic platform that can generate and combine multiple droplets represents a promising tool for high-throughput drug screening.
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Affiliation(s)
| | - Mark Lyons
- Hooke Bio Ltd, Shannon, Co. Clare, Ireland
| | | | | | | | - Michael A Galvin
- Hooke Bio Ltd, Shannon, Co. Clare, Ireland.,University of Limerick, Bernal Institute, Limerick, Ireland
| | - Jane Mulqueen
- Hooke Bio Ltd, Shannon, Co. Clare, Ireland.,University of Limerick, Bernal Institute, Limerick, Ireland
| | - Lorraine B Bible
- Hooke Bio Ltd, Shannon, Co. Clare, Ireland.,University of Limerick, Bernal Institute, Limerick, Ireland
| | | | | | | | - Howard O Fearnhead
- Pharmacology and Therapeutics, Biomedical Sciences, Dangan, NUI Galway, Galway, Ireland
| | - Enda O'Connell
- Pharmacology and Therapeutics, Biomedical Sciences, Dangan, NUI Galway, Galway, Ireland
| | - Mark Davies
- University of Limerick, Bernal Institute, Limerick, Ireland
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