Quantitative analysis of transporter activity biosensors

Abstract

The allocation of sugars from photosynthetic leaves to storage tissues in seeds, fruits, and tubers is an important determinant of crop yields. Genetically guided selection and transgenic modification of plant membrane transporters can help enhance crop yields and increase pathogen resistance. Yet, quantitative, systems-level models to support this effort are lacking. Recently, biosensors gained popularity for collecting spatiotemporally resolved information on cell physiology and validating computational models. Here, we report the design and use of genetically-encoded biosensors to measure the activity of SWEETs, the only family of sugar transporters known to facilitate the cellular release of sugar in plants. We created SweetTrac sensors by inserting circularly-permutated GFP into SWEET transporters, resulting in chimeras that translate substrate-triggered conformational rearrangements during the transport cycle into detectable changes in fluorescence intensity. We demonstrate that a combination of cell sorting and bioinformatics can be applied as a general approach to accelerate the design of biosensors for in vivo biochemistry. Finally, mass action kinetics analysis of the biosensors response suggests that SWEETs are low-affinity, near-symmetric transporters that can rapidly equilibrate intra- and extracellular concentrations of sugars. Significance StatementTransporters are the gatekeepers of the cell. Transporters facilitate the exchange of ions and metabolites between cellular and subcellular compartments, thus controlling processes from bacterial chemotaxis to the release of neurotransmitters. In plants, transporters play critical roles in the allocation of carbon to different organs. Biosensors derived from transporters have been generated to monitor the activity of these proteins within the complex environment of the cell. However, a quantitative framework that reconciles molecular and cellular-level events to help interpret the response of biosensors is still lacking. Here, we created novel sugar transport biosensors and formulated a mathematical model to explain their response. These types of models can help realize multiscale, dynamic simulations of metabolite allocation to guide crop improvement.