Development of High-Content Assays for Kidney Progenitor Cell Expansion in Transgenic Zebrafish

Author:

Sanker Subramaniam1,Cirio Maria Cecilia1,Vollmer Laura L.2,Goldberg Natasha D.1,McDermott Lee A.23,Hukriede Neil A.1,Vogt Andreas24

Affiliation:

1. Department of Developmental Biology, University of Pittsburgh, Pittsburgh, PA, USA

2. University of Pittsburgh Drug Discovery Institute, Pittsburgh, PA, USA

3. Department of Pharmaceutical Sciences, University of Pittsburgh, Pittsburgh, PA, USA

4. Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, USA

Abstract

Reactivation of genes normally expressed during organogenesis is a characteristic of kidney regeneration. Enhancing this reactivation could potentially be a therapeutic target to augment kidney regeneration. The inductive events that drive kidney organogenesis in zebrafish are similar to the initial steps in mammalian kidney organogenesis. Therefore, quantifying embryonic signals that drive zebrafish kidney development is an attractive strategy for the discovery of potential novel therapeutic modalities that accelerate kidney regeneration. The Lim1 homeobox protein, Lhx1, is a marker of kidney development that is also expressed in the regenerating kidneys after injury. Using a fluorescent Lhx1a-EGFP transgene whose phenotype faithfully recapitulates that of the endogenous protein, we developed a high-content assay for Lhx1a-EGFP expression in transgenic zebrafish embryos employing an artificial intelligence–based image analysis method termed cognition network technology (CNT). Implementation of the CNT assay on high-content readers enabled automated real-time in vivo time-course, dose-response, and variability studies in the developing embryo. The Lhx1a assay was complemented with a kidney-specific secondary CNT assay that enables direct measurements of the embryonic renal tubule cell population. The integration of fluorescent transgenic zebrafish embryos with automated imaging and artificial intelligence–based image analysis provides an in vivo analysis system for structure-activity relationship studies and de novo discovery of novel agents that augment innate regenerative processes.

Publisher

Elsevier BV

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