Significance: Electric fields control embryonic development and wound healing through directing and enhancing cell migration and proliferation. However, details pertaining to electric sensing of cells remain unclear. Many studies have reported involvement of different cell surface proteins, yet the identity of the electric field sensor is unknown. We demonstrate that the detergent-resistant membrane nanodomains, known as lipid rafts, act as the primary sensor to electric field-induced directional cell migration. These nanodomains respond to electric fields as mobile complexes that polarize, coalesce, and partition membrane proteins and in turn activate intracellular signaling events to orient cell migration.

Raman spectroscopy in biological applications faces challenges due to complex spectra, characterized by peaks of varying widths and significant biological background noise. Convolutional neural networks (CNNs) are widely used for spectrum classification due to their ability to capture local peak features. In this study, we introduce a multiscale CNN designed to detect weak biomolecule signals and differentiate spectra with features that cannot be statistically distinguished. The approach is further enhanced by a new visualization technique tailored for multiscale spectral analysis, providing clear insights into classification results. Using the classification of cholera toxin B subunit (CTB)-treated versus untreated cell membrane samples, whose spectra cannot be statistically differentiated, the optimized multiscale CNN achieved superior performance compared to traditional machine learning methods and existing multiscale CNNs, with accuracy (99.22%), sensitivity (99.27%), specificity (99.16%), and precision (99.20%). Our new visualization method, based on gradients of activation maps with respect to class scores, generates saliency scores that capture sample variations, with decision-making relying on consistently identified peak features. By visualizing the effects of different kernel sizes, Grad-AM highlights features at varying scales, aligning closely with spectral features and enhancing CNN interpretability in complex biomolecular analysis. These advancements demonstrate the potential of our method to improve spectral analysis and reveal previously hidden peaks in complex biological environments.

Being able to directly obtain micron-sized cell blebs, giant plasma membrane vesicles (GPMVs), with native membrane proteins and deposit them on a planar support to form supported plasma membranes could allow the membrane proteins to be studied by various surface analytical tools in native-like bilayer environments. However, GPMVs do not easily rupture on conventional supports because of their high protein and cholesterol contents. Here, we demonstrate the possibility of using compression generated by the air-water interface to efficiently rupture GPMVs to form micron-sized supported membranes with native plasma membrane proteins. We demonstrated that not only lipid but also a native transmembrane protein in HeLa cells, Aquaporin 3 (AQP3), is mobile in the supported membrane platform. This convenient method for generating micron-sized supported membrane patches with mobile native transmembrane proteins could not only facilitate the study of membrane proteins by surface analytical tools, but could also enable us to use native membrane proteins for bio-sensing applications.