A biologically validated mathematical model for decoding epithelial apical, basolateral, and paracellular electrical properties.

Epithelial tissues form selective barriers to ions, nutrients, waste products, and infectious agents throughout the body. Damage to these barriers is associated with conditions such as celiac disease, cystic fibrosis, diabetes, and age-related macular degeneration. Conventional electrophysiology measurements like transepithelial resistance can quantify epithelial tissue maturity and barrier integrity but are limited in differentiating between apical, basolateral, and paracellular transport pathways. To overcome this limitation, a combination of mathematical modeling, stem cell biology, and cell physiology led to the development of 3 P-EIS, a novel mathematical model and measurement technique. 3 P-EIS employs an intracellular pipette and extracellular electrochemical impedance spectroscopy to accurately measure membrane-specific properties of epithelia, without the constraints of prior models. 3 P-EIS was validated using electronic circuit models of epithelia with known resistances and capacitances, confirming a median error of 19% (interquartile range: 14%-26%) for paracellular and transcellular resistances and capacitances (n = 5). Patient stem cell-derived retinal pigment epithelium tissues were measured using 3 P-EIS, successfully isolating the cellular responses to adenosine triphosphate. 3 P-EIS enhances quality control in epithelial cell therapies and has extensive applicability in drug testing and disease modeling, marking a significant advance in epithelial physiology.NEW & NOTEWORTHY This interdisciplinary paper integrates mathematics, biology, and physiology to measure epithelial tissue's apical, basolateral, and paracellular transport pathways. A key advancement is the inclusion of intracellular voltage recordings using a sharp pipette, enabling precise quantification of relative impedance changes between apical and basolateral membranes. This enhanced electrochemical impedance spectroscopy technique offers insights into epithelial transport dynamics, advancing disease understanding, drug interactions, and cell therapies. Its broad applicability contributes significantly to epithelial physiology research.

Sodium-Iodate Injection Can Replicate Retinal Degenerative Disease Stages in Pigmented Mice and Rats: Non-Invasive Follow-Up Using OCT and ERG.

PURPOSE: The lack of suitable animal models for (dry) age-related macular degeneration (AMD) has hampered therapeutic research into the disease, so far. In this study, pigmented rats and mice were systematically injected with various doses of sodium iodate (SI). After injection, the retinal structure and visual function were non-invasively characterized over time to obtain in-depth data on the suitability of these models for studying experimental therapies for retinal degenerative diseases, such as dry AMD. METHODS: SI was injected into the tail vein (i.v.) using a series of doses (0-70 mg/kg) in adolescent C57BL/6J mice and Brown Norway rats. The retinal structure and function were assessed non-invasively at baseline (day 1) and at several time points (1-3, 5, and 10-weeks) post-injection by scanning laser ophthalmoscopy (SLO), optical coherence tomography (OCT), and electroretinography (ERG). RESULTS: After the SI injection, retinal degeneration in mice and rats yielded similar results. The lowest dose (10 mg/kg) resulted in non-detectable structural or functional effects. An injection with 20 mg/kg SI did not result in an evident retinal degeneration as judged from the OCT data. In contrast, the ERG responses were temporarily decreased but returned to baseline within two-weeks. Higher doses (30, 40, 50, and 70 mg/kg) resulted in moderate to severe structural RPE and retinal injury and decreased the ERG amplitudes, indicating visual impairment in both mice and rat strains. CONCLUSIONS: After the SI injections, we observed dose-dependent structural and functional pathological effects on the retinal pigment epithelium (RPE) and retina in the pigmented mouse and rat strains that were used in this study. Similar effects were observed in both species. In particular, a dose of 30 mg/kg seems to be suitable for future studies on developing experimental therapies. These relatively easily induced non-inherited models may serve as useful tools for evaluating novel therapies for RPE-related retinal degenerations, such as AMD.

The Lrat-/- Rat: CRISPR/Cas9 Construction and Phenotyping of a New Animal Model for Retinitis Pigmentosa.

PURPOSE: We developed and phenotyped a pigmented knockout rat model for lecithin retinol acyltransferase (LRAT) using CRISPR/Cas9. The introduced mutation (c.12delA) is based on a patient group harboring a homologous homozygous frameshift mutation in the LRAT gene (c.12delC), causing a dysfunctional visual (retinoid) cycle. METHODS: The introduced mutation was confirmed by DNA and RNA sequencing. The expression of Lrat was determined on both the RNA and protein level in wildtype and knockout animals using RT-PCR and immunohistochemistry. The retinal structure and function, as well as the visual behavior of the Lrat-/- and control rats, were characterized using scanning laser ophthalmoscopy (SLO), optical coherence tomography (OCT), electroretinography (ERG) and vision-based behavioral assays. RESULTS: Wildtype animals had high Lrat mRNA expression in multiple tissues, including the eye and liver. In contrast, hardly any expression was detected in Lrat-/- animals. LRAT protein was abundantly present in wildtype animals and absent in Lrat-/- animals. Lrat-/- animals showed progressively reduced ERG potentials compared to wildtype controls from two weeks of age onwards. Vison-based behavioral assays confirmed reduced vision. Structural abnormalities, such as overall retinal thinning, were observed in Lrat-/- animals. The retinal thickness in knockout rats was decreased to roughly 80% by four months of age. No functional or structural differences were observed between wildtype and heterozygote animals. CONCLUSIONS: Our Lrat-/- rat is a new animal model for retinal dystrophy, especially for the LRAT-subtype of early-onset retinal dystrophies. This model has advantages over the existing mouse models and the RCS rat strain and can be used for translational studies of retinal dystrophies.

Machine Learning-Based Pipette Positional Correction for Automatic Patch Clamp In Vitro.

Patch clamp electrophysiology is a common technique used in neuroscience to understand individual neuron behavior, allowing one to record current and voltage changes with superior spatiotemporal resolution compared with most electrophysiology methods. While patch clamp experiments produce high fidelity electrophysiology data, the technique is onerous and labor intensive. Despite the emergence of patch clamp systems that automate key stages in the typical patch clamp procedure, full automation remains elusive. Patch clamp pipettes can miss the target cell during automated experiments because of positioning errors in the robotic manipulators, which can easily exceed the diameter of a neuron. Further, when patching in acute brain slices, the inherent light scattering from non-uniform brain tissue can complicate pipette tip identification. We present a convolutional neural network (CNN), based on ResNet101, to identify and correct pipette positioning errors before each patch clamp attempt, thereby preventing the deleterious effects of and accumulation of positioning errors. This deep-learning-based pipette detection method enabled superior localization of the pipette within 0.62 ± 0.58 µm, resulting in improved cell detection success rate and whole-cell patch clamp success rates by 71% and 59%, respectively, compared with the state-of-the-art cross-correlation method. Furthermore, this technique reduced the average time for pipette correction by 81%. This technique enables real-time correction of pipette position during patch clamp experiments with similar accuracy and quality of recording to manual patch clamp, making notable progress toward full human-out-of-the-loop automation for patch clamp electrophysiology.

Sphingomyelinase decreases transepithelial anion secretion in airway epithelial cells in part by inhibiting CFTR-mediated apical conductance.

The cystic fibrosis transmembrane conductance regulator (CFTR) is an anion channel whose dysfunction causes cystic fibrosis (CF). The loss of CFTR function in pulmonary epithelial cells causes surface dehydration, mucus build-up, inflammation, and bacterial infections that lead to lung failure. Little has been done to evaluate the effects of lipid perturbation on CFTR activity, despite CFTR residing in the plasma membrane. This work focuses on the acute effects of sphingomyelinase (SMase), a bacterial virulence factor secreted by CF relevant airway bacteria which degrades sphingomyelin into ceramide and phosphocholine, on the electrical circuitry of pulmonary epithelial monolayers. We report that basolateral SMase decreases CFTR-mediated transepithelial anion secretion in both primary bronchial and tracheal epithelial cells from explant tissue, with current CFTR modulators unable to rescue this effect. Focusing on primary cells, we took a holistic ion homeostasis approach to determine a cause for reduced anion secretion following SMase treatment. Using impedance analysis, we determined that basolateral SMase inhibits apical and basolateral conductance in non-CF primary cells without affecting paracellular permeability. In CF primary airway cells, correction with clinically relevant CFTR modulators did not prevent SMase-mediated inhibition of CFTR currents. Furthermore, SMase was found to inhibit only apical conductance in these cells. Future work should determine the mechanism for SMase-mediated inhibition of CFTR currents, and further explore the clinical relevance of SMase and sphingolipid imbalances.

Capillary-Based and Stokes-Based Trapping of Serial Sections for Scalable 3D-EM Connectomics.

Serial section electron microscopy (ssEM), a technique where volumes of tissue can be anatomically reconstructed by imaging consecutive tissue slices, has proven to be a powerful tool for the investigation of brain anatomy. Between the process of cutting the slices, or "sections," and imaging them, however, handling 10°-106 delicate sections remains a bottleneck in ssEM, especially for batches in the "mesoscale" regime, i.e., 102-103 sections. We present a tissue section handling device that transports and positions sections, accurately and repeatability, for automated, robotic section pick-up and placement onto an imaging substrate. The device interfaces with a conventional ultramicrotomy diamond knife, accomplishing in-line, exact-constraint trapping of sections with 100-µm repeatability. An associated mathematical model includes capillary-based and Stokes-based forces, accurately describing observed behavior and fundamentally extends the modeling of water-air interface forces. Using the device, we demonstrate and describe the limits of reliable handling of hundreds of slices onto a variety of electron and light microscopy substrates without significant defects (n = 8 datasets composed of 126 serial sections in an automated fashion with an average loss rate and throughput of 0.50% and 63 s/section, respectively. In total, this work represents an automated mesoscale serial sectioning system for scalable 3D-EM connectomics.

High-yield, automated intracellular electrophysiology in retinal pigment epithelia.

BACKGROUND: Recent advancements with induced pluripotent stem cell-derived (iPSC) retinal pigment epithelium (RPE) have made disease modeling and cell therapy for macular degeneration feasible. However, current techniques for intracellular electrophysiology - used to validate epithelial function - are painstaking and require manual skill; limiting experimental throughput. NEW METHOD: A five-stage algorithm, leveraging advances in automated patch clamping, systematically derived and optimized, improves yield and reduces skill when compared to conventional, manual techniques. RESULTS: The automated algorithm improves yield per attempt from 17% (manually, n = 23) to 22% (automated, n = 120) (chi-squared, p = 0.004). Specifically for RPE, depressing the local cell membrane by 6 µm and electroporating (buzzing) just prior to this depth (5 µm) maximized yield. COMPARISON WITH EXISTING METHOD: Conventionally, intracellular epithelial electrophysiology is performed by manually lowering a pipette with a micromanipulator, blindly, towards a monolayer of cells and spontaneously stopping when the magnitude of the instantaneous measured membrane potential decreased below a predetermined threshold. The new method automatically measures the pipette tip resistance during the descent, detects the cell surface, indents the cell membrane, and briefly buzzes to electroporate the membrane while descending, overall achieving a higher yield than conventional methods. CONCLUSIONS: This paper presents an algorithm for high-yield, automated intracellular electrophysiology in epithelia; optimized for human RPE. Automation reduces required user skill and training while, simultaneously, improving yield. This algorithm could enable large-scale exploration of drug toxicity and physiological function verification for numerous kinds of epithelia.

PatcherBot: a single-cell electrophysiology robot for adherent cells and brain slices.

OBJECTIVE: Intracellular patch-clamp electrophysiology, one of the most ubiquitous, high-fidelity techniques in biophysics, remains laborious and low-throughput. While previous efforts have succeeded at automating some steps of the technique, here we demonstrate a robotic 'PatcherBot' system that can perform many patch-clamp recordings sequentially, fully unattended. APPROACH: Comprehensive automation is accomplished by outfitting the robot with machine vision, and cleaning pipettes instead of manually exchanging them. MAIN RESULTS: the PatcherBot can obtain data at a rate of 16 cells per hour and work with no human intervention for up to 3 h. We demonstrate the broad applicability and scalability of this system by performing hundreds of recordings in tissue culture cells and mouse brain slices with no human supervision. Using the PatcherBot, we also discovered that pipette cleaning can be improved by a factor of three. SIGNIFICANCE: The system is potentially transformative for applications that depend on many high-quality measurements of single cells, such as drug screening, protein functional characterization, and multimodal cell type investigations.

Transport and trapping of nanosheets via hydrodynamic forces and curvature-induced capillary quadrupolar interactions.

HYPOTHESIS: The manipulation of nanosheets on a fluid-fluid interface remains a significant challenge. At this interface, hydrodynamic forces can be used for long-range transport (>1× capillary length) but are difficult to utilize for accurate and repeatable positioning. While capillary multipole interactions have been used for particle trapping, how these interactions manifest on large but thin objects, i.e., nanosheets, remains an open question. Hence, we posit hydrodynamic forces in conjunction with capillary multipole interactions can be used for nanosheet transport and trapping. EXPERIMENTS: We designed and characterized a fluidic device for transporting and trapping nanosheets on the water-air interface. Analytical models were compared against optical measurements of the nanosheet behavior to investigate capillary multipole interactions. Energy-based modeling and dimensional analysis were used to study trapping stability. FINDINGS: Hydrodynamic forces and capillary interactions successfully transported and trapped nanosheets at a designated trapping location with a repeatability of 10% of the nanosheet's length and 12% of its width (length = 1500 µm, width = 1000 µm) and an accuracy of 20% of their length and width. Additionally, this is the first report that surface tension forces acting upon nanoscale-thick objects manifest as capillary quadrupolar interactions and can be used for precision manipulation of nanosheets.