Aberrant Zn²⁺ homeostasis is a hallmark of certain cardiomyopathies associated with altered contractile force. In this study, we addressed whether Zn²⁺ modulates cardiac ryanodine receptor gating and Ca²⁺ dynamics in isolated cardiomyocytes. We reveal that Zn²⁺ is a high affinity regulator of RyR2 displaying three modes of operation. Picomolar free Zn²⁺ concentrations potentiate RyR2 responses, but channel activation is still dependent on the presence of cytosolic Ca²⁺. At concentrations of free Zn²⁺ >1 nm, Zn²⁺ is the main activating ligand, and the dependence on Ca²⁺ is removed. Zn²⁺ is therefore a higher affinity activator of RyR2 than Ca²⁺. Millimolar levels of free Zn²⁺ were found to inhibit channel openings. In cardiomyocytes, consistent with our single channel results, we show that Zn²⁺ modulates both the frequency and amplitude of Ca²⁺ waves in a concentration-dependent manner and that physiological levels of Zn²⁺ elicit Ca²⁺ release in the absence of activating levels of cytosolic Ca²⁺. This highlights a new role for intracellular Zn²⁺ in shaping Ca²⁺ dynamics in cardiomyocytes through modulation of RyR2 gating.

Single-molecule research techniques such as patch-clamp electrophysiology deliver unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysis is event detection, so called “idealisation”, where noisy raw data are turned into discrete records of protein movement. To date there have been practical limitations in patch-clamp data idealisation; high quality idealisation is typically laborious and becomes infeasible and subjective with complex biological data containing many distinct native single-ion channel proteins gating simultaneously. Here, we show a deep learning model based on convolutional neural networks and long short-term memory architecture can automatically idealise complex single molecule activity more accurately and faster than traditional methods. There are no parameters to set; baseline, channel amplitude or numbers of channels for example. We believe this approach could revolutionise the unsupervised automatic detection of single-molecule transition events in the future.

Voltage-gated K⁺ (Kv) channels of arterial smooth muscle (ASM) modulate arterial tone and are inhibited by vasoconstrictors through protein kinase C (PKC). We aimed to determine whether endothelin-1 (ET-1) and angiotensin II (AngII), which cause similar inhibition of Kv, use the same signalling pathway and PKC isoenzyme to exert their effects on Kv and to compare the involvement of PKC isoenzymes in contractile responses to these agents. Kv currents recorded using the patch clamp technique with freshly isolated rat mesenteric ASM cells were inhibited by ET-1 or AngII. Inclusion of a PKCε inhibitor peptide in the intracellular solution substantially reduced inhibition by AngII, but did not affect that by ET-1. Kv inhibition by ET-1 was reduced by the conventional PKC inhibitor Gö 6976 but not by the PKCβ inhibitor LY333531. Selective peptide inhibitors of PKCα and PKCε were linked to a Tat carrier peptide to make them membrane permeable and used to show that inhibition of PKCα prevented ET-1 inhibition of Kv current, but did not affect that by AngII. In contrast, inhibition of PKCε prevented Kv inhibition by AngII but not by ET-1. The Tat-linked inhibitor peptides were also used to investigate the involvement of PKCα and PKCε in the contractile responses of mesenteric arterial rings, showing that ET-1 contractions were substantially reduced by inhibition of PKCα, but unaffected by inhibition of PKCε. AngII contractions were unaffected by inhibition of PKCα but substantially reduced by inhibition of PKCε. ET-1 inhibits Kv channels of mesenteric ASM through activation of PKCα, while AngII does so through PKCε. This implies that ET-1 and AngII target Kv channels of ASM through different pathways of PKC-interacting proteins, so each vasoconstrictor enables its distinct PKC isoenzyme to interact functionally with the Kv channel.