Biophysical JournalBiophysicsPeer-reviewed journal article
Mechanosensitive channels dominate the minimal ion channelrepertoire in prokaryotes
Cristóbal UribeiD, Luciano Pena, Samuel Morales-Navarro, Sebastian E. BrauchiiD, Gonzalo RiadiiD, Juan C. OpazoiD, Wendy GonzáleziD
Abstract
The eukaryotic genomes encode hundreds of proteins that function as ion channels and transporters. Essential for sustaining life, these proteins mediate the movement of inorganic ions (e.g., K+, Na+, Cl-, and Ca2+) across the plasma membrane according to their electrochemical gradients. In multicellular organisms, a diverse array of ion channels contributes to the maintenance of the resting membrane potential, the regulation of pH, osmolarity, and cell volume, and the control of secretion, electrical excitability, and synaptic activity, among many other fundamental physiological processes. Although independent evolutionary origins have been proposed for several ion channel families, their relative hierarchical importance for cellular viability remains poorly understood. To advance our knowledge of ion channel evolutionary history, we focused on determining the minimal combination of permeabilities that allows cellular viability. To this end, we conducted a survey of representative prokaryotes with small genomes across bacterial and archaeal phyla. By focusing on the smallest genomes, our approach enabled the identification of five ion channel architectures shared among prokaryotes. Among these, non-selective mechanosensitive channels (MscS and MscL) are the most abundant, followed by CLC-type channels, RCK-containing 2TM potassium channels, and proton channels of the MotA/TolQ/ExbB family. The conservation of the mechanosensitive protein architecture across archaeal and bacterial membranes suggests that the capacity to monitor physical membrane integrity predates the requirements for electrical communication.
- organism: bacteria (other)
- organism: yeast
- assay: proteomics
- research focus: cell type annotation
- research focus: clustering
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: experimental assay
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 16th percentile
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