A high-throughput yeast approach to characterize aquaporin permeabilities: Profiling the Arabidopsis PIP aquaporin sub-family.

Introduction: Engineering membrane transporters to achieve desired functionality is reliant on availability of experimental data informing structure-function relationships and intelligent design. Plant aquaporin (AQP) isoforms are capable of transporting diverse substrates such as signaling molecules, nutrients, metalloids, and gases, as well as water. AQPs can act as multifunctional channels and their transport function is reliant on many factors, with few studies having assessed transport function of specific isoforms for multiple substrates. Methods: High-throughput yeast assays were developed to screen for transport function of plant AQPs, providing a platform for fast data generation and cataloguing of substrate transport profiles. We applied our high-throughput growth-based yeast assays to screen all 13 Arabidopsis PIPs (AtPIPs) for transport of water and several neutral solutes: hydrogen peroxide (H2O2), boric acid (BA), and urea. Sodium (Na+) transport was assessed using elemental analysis techniques. Results: All AtPIPs facilitated water and H2O2 transport, although their growth phenotypes varied, and none were candidates for urea transport. For BA and Na+ transport, AtPIP2;2 and AtPIP2;7 were the top candidates, with yeast expressing these isoforms having the most pronounced toxicity response to BA exposure and accumulating the highest amounts of Na+. Linking putative AtPIP isoform substrate transport profiles with phylogenetics and gene expression data, enabled us to align possible substrate preferences with known and hypothesized biological roles of AtPIPs. Discussion: This testing framework enables efficient cataloguing of putative transport functionality of diverse AQPs at a scale that can help accelerate our understanding of AQP biology through big data approaches (e.g. association studies). The principles of the individual assays could be further adapted to test additional substrates. Data generated from this framework could inform future testing of AQP physiological roles, and address knowledge gaps in structure-function relationships to improve engineering efforts.