Structural motifs for subtype-specific pH-sensitive gating of vertebrate otopetrin proton channels

Otopetrin (OTOP) channels are proton-selective ion channels conserved among vertebrates and invertebrates, with no structural similarity to other ion channels. There are three vertebrate OTOP channels (OTOP1, OTOP2, and OTOP3), of which one (OTOP1) functions as a sour taste receptor. Whether extracellular protons gate OTOP channels, in addition to permeating them, was not known. Here, we compare the functional properties of the three murine OTOP channels using patch-clamp recording and cytosolic pH microfluorimetry. We find that OTOP1 and OTOP3 are both steeply activated by extracellular protons, with thresholds of pH_o <6.0 and 5.5, respectively, and kinetics that are pH-dependent. In contrast, OTOP2 channels are broadly active over a large pH range (pH 5 pH 10) and carry outward currents in response to extracellular alkalinization (>pH 9.0). Strikingly, we could change the pH-sensitive gating of OTOP2 and OTOP3 channels by swapping extracellular linkers that connect transmembrane domains. Swaps of extracellular linkers in the N domain, comprising transmembrane domains 1-6, tended to change the relative conductance at alkaline pH of chimeric channels, while swaps within the C domain, containing transmembrane domains 7-12, tended to change the rates of OTOP3 current activation. We conclude that members of the OTOP channel family are proton-gated (acid-sensitive) proton channels and that the gating apparatus is distributed across multiple extracellular regions within both the N and C domains of the channels. In addition to the taste system, OTOP channels are expressed in the vertebrate vestibular and digestive systems. The distinct gating properties we describe may allow them to subserve varying cell-type specific functions in these and other biological systems.

High-throughput, microscope-based sorting to dissect cellular heterogeneity

Microscopy is a powerful tool for characterizing complex cellular phenotypes, but linking these phenotypes to genotype or RNA expression at scale remains challenging. Here, we present Visual Cell Sorting, a method that physically separates hundreds of thousands of live cells based on their visual phenotype. Automated imaging and phenotypic analysis directs selective illumination of Dendra2, a photoconvertible fluorescent protein expressed in live cells; these photoactivated cells are then isolated using fluorescence-activated cell sorting. First, we use Visual Cell Sorting to assess hundreds of nuclear localization sequence variants in a pooled format, identifying variants that improve nuclear localization and enabling annotation of nuclear localization sequences in thousands of human proteins. Second, we recover cells that retain normal nuclear morphologies after paclitaxel treatment, and then derive their single-cell transcriptomes to identify pathways associated with paclitaxel resistance in cancers. Unlike alternative methods, Visual Cell Sorting depends on inexpensive reagents and commercially available hardware. As such, it can be readily deployed to uncover the relationships between visual cellular phenotypes and internal states, including genotypes and gene expression programs.