Normalizing brain activity across individuals using functional reference mapping

Neural activity can be mapped across individuals using brain atlases, but when spatial relationships are not equal, these techniques collapse. We map activity across individuals using functional registration, based on physiological responses to predetermined reference stimuli. Data from several individuals are integrated into a common multidimensional stimulus space, where dimensionality and axes are defined by these reference stimuli. We used this technique to discriminate volatile compounds with a cohort of Drosophila flies, by recording odor responses in receptor neurons on the flies' antennae. We propose this technique for the development of reliable biological sensors when activity raw data cannot be calibrated. In particular, this technique will be useful for evaluating physiological measurements in natural chemosensory systems, and therefore will allow to exploit the sensitivity and selectivity of olfactory receptors present in the animal kingdom for analytical purposes

Optimizing the Cell Painting assay for image-based profiling

AbstractIn image-based profiling, software extracts thousands of morphological features of cells from multi-channel fluorescence microscopy images, yielding single-cell profiles that can be used for basic research and drug discovery. Powerful applications have been proven, including clustering chemical and genetic perturbations based on their similar morphological impact, identifying disease phenotypes by observing differences in profiles between healthy and diseased cells, and predicting assay outcomes using machine learning, among many others. Here we provide an updated protocol for the most popular assay for image-based profiling, Cell Painting. Introduced in 2013, it uses six stains imaged in five channels and labels eight diverse components of the cell: DNA, cytoplasmic RNA, nucleoli, actin, Golgi apparatus, plasma membrane, endoplasmic reticulum, and mitochondria. The original protocol was updated in 2016 based on several years’ experience running it at two sites, after optimizing it by visual stain quality. Here we describe the work of the Joint Undertaking for Morphological Profiling (JUMP) Cell Painting Consortium, aiming to improve upon the assay via quantitative optimization, based on the measured ability of the assay to detect morphological phenotypes and group similar perturbations together. We find that the assay gives very robust outputs despite a variety of changes to the protocol and that two vendors’ dyes work equivalently well. We present Cell Painting version 3, in which some steps are simplified and several stain concentrations can be reduced, saving costs. Cell culture and image acquisition take 1–2 weeks for a typically sized batch of 20 or fewer plates; feature extraction and data analysis take an additional 1–2 weeks.Key references using this protocolVirtual screening for small-molecule pathway regulators by image-profile matching(https://doi.org/10.1016/j.cels.2022.08.003) - recent work examining the ability to use collected Cell Painting profiles to screen for regulators of a number of diverse biological pathways.JUMP Cell Painting dataset: images and profiles from two billion cells perturbed by 140,000 chemical and genetic perturbations(DOI) - the description of the main JUMP master public data set, using this protocol in the production of &gt;200 TB of image data and &gt;200 TB of measured profiles.Key data used in this protocolCell Painting, a high-content image-based assay for morphological profiling using multiplexed fluorescent dyes(https://doi.org/10.1038/nprot.2016.105) - this paper provides the first step-by-step Cell Painting protocol ever released.</jats:sec

Architecture of a mammalian glomerular domain revealed by novel volume electroporation using nanoengineered microelectrodes

Dense microcircuit reconstruction techniques have begun to provide ultrafine insight into the architecture of small-scale networks. However, identifying the totality of cells belonging to such neuronal modules, the “inputs” and “outputs,” remains a major challenge. Here, we present the development of nanoengineered electroporation microelectrodes (NEMs) for comprehensive manipulation of a substantial volume of neuronal tissue. Combining finite element modeling and focused ion beam milling, NEMs permit substantially higher stimulation intensities compared to conventional glass capillaries, allowing for larger volumes configurable to the geometry of the target circuit. We apply NEMs to achieve near-complete labeling of the neuronal network associated with a genetically identified olfactory glomerulus. This allows us to detect sparse higher-order features of the wiring architecture that are inaccessible to statistical labeling approaches. Thus, NEM labeling provides crucial complementary information to dense circuit reconstruction techniques. Relying solely on targeting an electrode to the region of interest and passive biophysical properties largely common across cell types, this can easily be employed anywhere in the CNS

JUMP Cell Painting dataset: morphological impact of 136,000 chemical and genetic perturbations

AbstractImage-based profiling has emerged as a powerful technology for various steps in basic biological and pharmaceutical discovery, but the community has lacked a large, public reference set of data from chemical and genetic perturbations. Here we present data generated by the Joint Undertaking for Morphological Profiling (JUMP)-Cell Painting Consortium, a collaboration between 10 pharmaceutical companies, six supporting technology companies, and two non-profit partners. When completed, the dataset will contain images and profiles from the Cell Painting assay for over 116,750 unique compounds, over-expression of 12,602 genes, and knockout of 7,975 genes using CRISPR-Cas9, all in human osteosarcoma cells (U2OS). The dataset is estimated to be 115 TB in size and capturing 1.6 billion cells and their single-cell profiles. File quality control and upload is underway and will be completed over the coming months at the Cell Painting Gallery:https://registry.opendata.aws/cellpainting-gallery. A portal to visualize a subset of the data is available athttps://phenaid.ardigen.com/jumpcpexplorer/.</jats:p