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High-Throughput Screening for Insulin Secretion Modulators

  • Michael A. KalwatEmail author
Protocol
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Part of the Methods in Molecular Biology book series (MIMB, volume 2233)

Abstract

The application of forward chemical genetics to insulin secretion in high-throughput has been uncommon because of high costs and technical challenges. However, with the advancement of secreted luciferase tools, it has become feasible for small laboratories to screen large numbers of compounds for effects on insulin secretion. The purpose of this chapter is to outline the methods involved in high-throughput screening for small molecules that chronically impact pancreatic beta cell function. Attention is given to specific points in the protocol that help to improve the dynamic range and reduce variability in the assay. Using this approach in 384-well format, at least 48 and as many as 144 plates can theoretically be processed per week. This protocol serves as a guideline and can be modified as required for alternate stimulation paradigms and improved upon as new technologies become available.

Key words

High-throughput screening Insulin secretion Gaussia luciferase Small molecules Pancreatic beta cells 

Notes

Acknowledgments

Thanks to Derk Binns for technical assistance and proofreading this manuscript. Thank you to the UTSW High-Throughput Screening Core facility, especially Shuguang Wei, for helpful discussions and advice. Thank you to Magdalena Grzemska for technical assistance. This work was supported by a Juvenile Diabetes Research Foundation Strategic Research Award 2-SRA-2019-702-Q-R (to MAK). Early parts of the development of this methodology were supported by an F32 DK100113 to Michael A. Kalwat and an R37 DK034128 and Welch (I-1243) to Melanie H. Cobb. The UTSW HTS facility is supported by an NIH NCI grant P30 CA142543.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2021

Authors and Affiliations

  1. 1.Lilly Diabetes Center of ExcellenceBiosciences Research InstituteIndianapolisUSA

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