SanPy: A whole-cell electrophysiology analysis pipeline

The analysis of action potentials and other membrane voltage fluctuations provide a powerful approach for interrogating the function of excitable cells. Yet, a major bottleneck in the interpretation of this critical data is the lack of intuitive, agreed upon software tools for its analysis. Here, we present SanPy, a Python-based open-source and freely available software pipeline for the analysis and exploration of whole-cell current-clamp recordings. SanPy provides a robust computational engine with an application programming interface. Using this, we have developed a cross-platform graphical user interface that does not require programming. SanPy is designed to extract common parameters from action potentials including threshold time and voltage, peak, half-width, and interval statistics. In addition, several cardiac parameters are measured including the early diastolic duration and rate. SanPy is built to be fully extensible by providing a plugin architecture for the addition of new file loaders, analysis, and visualizations. A key feature of SanPy is its focus on quality control and data exploration. In the desktop interface, all plots of the data and analysis are linked allowing simultaneous data visualization from different dimensions with the goal of obtaining ground truth analysis. We provide documentation for all aspects of SanPy including several use cases and examples. To test SanPy, we have performed analysis on current-clamp recordings from heart and brain cells. Taken together, SanPy is a powerful tool for whole-cell current-clamp analysis and lays the foundation for future extension by the scientific community.

Photolipid excitation triggers depolarizing optocapacitive currents and action potentials

Optically-induced changes in membrane capacitance may regulate neuronal activity without requiring genetic modifications. Previously, they mainly relied on sudden temperature jumps due to light absorption by membrane-associated nanomaterials or water. Yet, nanomaterial targeting or the required high infrared light intensities obstruct broad applicability. Now, we propose a very versatile approach: photolipids (azobenzene-containing diacylglycerols) mediate light-triggered cellular de- or hyperpolarization. As planar bilayer experiments show, the respective currents emerge from millisecond-timescale changes in bilayer capacitance. UV light changes photolipid conformation, which awards embedding plasma membranes with increased capacitance and evokes depolarizing currents. They open voltage-gated sodium channels in cells, generating action potentials. Blue light reduces the area per photolipid, decreasing membrane capacitance and eliciting hyperpolarization. If present, mechanosensitive channels respond to the increased mechanical membrane tension, generating large depolarizing currents that elicit action potentials. Membrane self-insertion of administered photolipids and focused illumination allows cell excitation with high spatiotemporal control.

High-throughput combined voltage-clamp/current-clamp analysis of freshly isolated neurons

The patch-clamp technique is the gold-standard methodology for analysis of excitable cells. However, throughput of manual patch-clamp is slow, and high-throughput robotic patch-clamp, while helpful for applications like drug screening, has been primarily used to study channels and receptors expressed in heterologous systems. We introduce an approach for automated high-throughput patch-clamping that enhances analysis of excitable cells at the channel and cellular levels. This involves dissociating and isolating neurons from intact tissues and patch-clamping using a robotic instrument, followed by using an open-source Python script for analysis and filtration. As a proof of concept, we apply this approach to investigate the biophysical properties of voltage-gated sodium (Nav) channels in dorsal root ganglion (DRG) neurons, which are among the most diverse and complex neuronal cells. Our approach enables voltage- and current-clamp recordings in the same cell, allowing unbiased, fast, simultaneous, and head-to-head electrophysiological recordings from a wide range of freshly isolated neurons without requiring culturing on coverslips.

Get the rhythm: modeling neuronal activity

The simulation system NEURON is a common research tool for constructing structurally and functionally realistic models of neuronal systems. NEURON allows the development of simulations at any level of complexity, from subcellular components to single cells, cellular networks, and system-level models. Focusing on an in vitro cell model of a single, acutely isolated thalamic neuron, we used the simulation environment to address and to discuss the following questions in an undergraduate course: (i) Which parts are required to design a single compartment with passive electrical properties? (ii) Which components are necessary to model a single action potential or a train of action potentials? (iii) What can we learn from voltage-clamp and current-clamp experiments? (iv) What kind of cellular parameters are accessible from the modeling data? (v) What are the differences between single-compartment models and multi-compartment models? (vi) What are the advantages and disadvantages of artificial cell models? (vii) Can realistic modeling open up new strategies to discover the way that neurons process information?