Dynamic change of electrostatic field in TMEM16F permeation pathway shifts its ion selectivity
Abstract
TMEM16F is activated by elevated intracellular Ca2+, and functions as a small-conductance ion channel and as a phospholipid scramblase. In contrast to its paralogs, the TMEM16A/B calcium-activated chloride channels, mouse TMEM16F has been reported as a cation-, anion-, or non-selective ion channel, without a definite conclusion. Starting with the Q559K mutant that shows no current rundown and less outward rectification in excised patch, we found that the channel shifted its ion selectivity in response to the change of intracellular Ca2+ concentration, with an increased permeability ratio of Cl- to Na+ (PCl-/PNa+) at a higher Ca2+ level. The gradual shift of relative ion permeability did not correlate with the channel activation state. Instead, it was indicative of an alteration of electrostatic field in the permeation pathway. The dynamic change of ion selectivity suggests a charge-screening mechanism for TMEM16F ion conduction, and it provides hints to the study of TMEM16F physiological functions.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files
Article and author information
Author details
Funding
National Institute of Neurological Disorders and Stroke (R01NS069229)
- Lily Yeh Jan
Jane Coffin Childs Memorial Fund for Medical Research
- Tina W Han
Eunice Kennedy Shriver National Institute of Child Health and Human Development (F32HD089639)
- Mu He
Howard Hughes Medical Institute
- Yuh Nung Jan
- Lily Yeh Jan
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Kenton Jon Swartz, National Institute of Neurological Disorders and Stroke, National Institutes of Health, United States
Version history
- Received: January 14, 2019
- Accepted: July 17, 2019
- Accepted Manuscript published: July 18, 2019 (version 1)
- Version of Record published: August 12, 2019 (version 2)
Copyright
© 2019, Ye et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,825
- views
-
- 477
- downloads
-
- 23
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Immunology and Inflammation
- Neuroscience
CD4+CD25+Foxp3+ regulatory T cells (Treg) have been implicated in pain modulation in various inflammatory conditions. However, whether Treg cells hamper pain at steady state and by which mechanism is still unclear. From a meta-analysis of the transcriptomes of murine Treg and conventional T cells (Tconv), we observe that the proenkephalin gene (Penk), encoding the precursor of analgesic opioid peptides, ranks among the top 25 genes most enriched in Treg cells. We then present various evidence suggesting that Penk is regulated in part by members of the Tumor Necrosis Factor Receptor (TNFR) family and the transcription factor Basic leucine zipper transcription faatf-like (BATF). Using mice in which the promoter activity of Penk can be tracked with a fluorescent reporter, we also show that Penk expression is mostly detected in Treg and activated Tconv in non-inflammatory conditions in the colon and skin. Functionally, Treg cells proficient or deficient for Penk suppress equally well the proliferation of effector T cells in vitro and autoimmune colitis in vivo. In contrast, inducible ablation of Penk in Treg leads to heat hyperalgesia in both male and female mice. Overall, our results indicate that Treg might play a key role at modulating basal somatic sensitivity in mice through the production of analgesic opioid peptides.
-
- Neuroscience
Biological synaptic transmission is unreliable, and this unreliability likely degrades neural circuit performance. While there are biophysical mechanisms that can increase reliability, for instance by increasing vesicle release probability, these mechanisms cost energy. We examined four such mechanisms along with the associated scaling of the energetic costs. We then embedded these energetic costs for reliability in artificial neural networks (ANNs) with trainable stochastic synapses, and trained these networks on standard image classification tasks. The resulting networks revealed a tradeoff between circuit performance and the energetic cost of synaptic reliability. Additionally, the optimised networks exhibited two testable predictions consistent with pre-existing experimental data. Specifically, synapses with lower variability tended to have (1) higher input firing rates and (2) lower learning rates. Surprisingly, these predictions also arise when synapse statistics are inferred through Bayesian inference. Indeed, we were able to find a formal, theoretical link between the performance-reliability cost tradeoff and Bayesian inference. This connection suggests two incompatible possibilities: evolution may have chanced upon a scheme for implementing Bayesian inference by optimising energy efficiency, or alternatively, energy-efficient synapses may display signatures of Bayesian inference without actually using Bayes to reason about uncertainty.