Automatic deep learning-driven label-free image-guided patch clamp system

Patch clamp recording of neurons is a labor-intensive and time-consuming procedure. Here, we demonstrate a tool that fully automatically performs electrophysiological recordings in label-free tissue slices. The automation covers the detection of cells in label-free images, calibration of the micropipette movement, approach to the cell with the pipette, formation of the whole-cell configuration, and recording. The cell detection is based on deep learning. The model is trained on a new image database of neurons in unlabeled brain tissue slices. The pipette tip detection and approaching phase use image analysis techniques for precise movements. High-quality measurements are performed on hundreds of human and rodent neurons. We also demonstrate that further molecular and anatomical analysis can be performed on the recorded cells. The software has a diary module that automatically logs patch clamp events. Our tool can multiply the number of daily measurements to help brain research. Patch clamp recording of neurons is slow and labor-intensive. Here the authors present a method for automated deep learning driven label-free image guided patch clamp physiology to perform measurements on hundreds of human and rodent neurons.Peer reviewe

Molecular Determinants of Vectofusin-1 and Its Derivatives for the Enhancement of Lentivirally Mediated Gene Transfer into Hematopoietic Stem/Progenitor Cells

International audienceGene delivery into hCD34+ hematopoietic stem/progenitor cells (HSPCs) using human immunodeficiency virus, type 1-derived lentiviral vectors (LVs) has several promising therapeutic applications. Numerous clinical trials are currently underway. However, the efficiency, safety, and cost of LV gene therapy could be ameliorated by enhancing target cell transduction levels and reducing the amount of LV used on the cells. Several transduction enhancers already exist, such as fibronectin fragments or cationic compounds. Recently, we discovered Vectofusin-1, a new transduction enhancer, also called LAH4-A4, a short histidine-rich amphipathic peptide derived from the LAH4 family of DNA transfection agents. Vectofusin-1 enhances the infectivity of lentiviral and gamma-retroviral vectors pseudotyped with various envelope glycoproteins. In this study, we compared a family of Vectofusin-1 isomers and showed that Vectofusin-1 remains the lead peptide for HSPC transduction enhancement with LVs pseudotyped with vesicular stomatitis virus glycoproteins and also with modified gibbon ape leukemia virus glycoproteins. By comparing the capacity of numerous Vectofusin-1 variants to promote the modified gibbon ape leukemia virus glycoprotein-pseudotyped lentiviral vector infectivity of HSPCs, the lysine residues on the N-terminal extremity of Vectofusin-1, a hydrophilic angle of 140 degrees formed by the histidine residues in the Schiffer-Edmundson helical wheel representation, hydrophobic residues consisting of leucine were all found to be essential and helped to define a minimal active sequence. The data also show that the critical determinants necessary for lentiviral transduction enhancement are partially different from those necessary for efficient antibiotic or DNA transfection activity of LAH4 derivatives. In conclusion, these results help to decipher the action mechanism of Vectofusin-1 in the context of hCD34+ cell-based gene therapy