5 results match your criteria: "USA. Electronic address: anne@broadinstitute.org.[Affiliation]"
Pervasive mislocalization of pathogenic coding variants underlying human disorders.
Cell
November 2024
Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada; Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada. Electronic address:
Article Synopsis
- Widespread sequencing has identified thousands of missense variants linked to diseases, creating a challenge in assessing their functional impact at scale.
- A new high-throughput imaging platform was developed to evaluate the effects of 3,448 missense variants across over 1,000 genes, revealing that mislocalization of proteins is a frequent outcome.
- Mislocalization affects about one-sixth of pathogenic variants and is mainly caused by issues with protein stability and membrane insertion, which can influence disease severity and help interpret uncertain variants.
Morphology and gene expression profiling provide complementary information for mapping cell state.
Cell Syst
November 2022
Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA. Electronic address:
Morphological and gene expression profiling can cost-effectively capture thousands of features in thousands of samples across perturbations by disease, mutation, or drug treatments, but it is unclear to what extent the two modalities capture overlapping versus complementary information. Here, using both the L1000 and Cell Painting assays to profile gene expression and cell morphology, respectively, we perturb human A549 lung cancer cells with 1,327 small molecules from the Drug Repurposing Hub across six doses, providing a data resource including dose-response data from both assays. The two assays capture both shared and complementary information for mapping cell state.
View Article and Find Full Text PDFVirtual screening for small-molecule pathway regulators by image-profile matching.
Cell Syst
September 2022
Imaging Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address:
Article Synopsis
- Identifying chemical regulators in biological pathways is a slow and costly process, usually involving extensive testing of potential small molecules tailored to specific diseases.
- The authors propose a virtual, profile-based screening method that leverages public cell image data from the Cell Painting assay to identify compounds linked to biological pathways without needing extensive customization.
- Their approach successfully identified known small-molecule regulators in a substantial percentage of cases and discovered new compounds relevant to specific genes, demonstrating potential to streamline therapeutic compound discovery.
The new era of quantitative cell imaging-challenges and opportunities.
Mol Cell
January 2022
Allen Institute for Cell Science, Seattle, WA 98109, USA. Electronic address:
Quantitative optical microscopy-an emerging, transformative approach to single-cell biology-has seen dramatic methodological advancements over the past few years. However, its impact has been hampered by challenges in the areas of data generation, management, and analysis. Here we outline these technical and cultural challenges and provide our perspective on the trajectory of this field, ushering in a new era of quantitative, data-driven microscopy.
View Article and Find Full Text PDFApplications in image-based profiling of perturbations.
Curr Opin Biotechnol
June 2016
Imaging Platform of the Broad Institute of Harvard and Massachusetts Institute of Technology, 415 Main Street, Cambridge, MA, USA. Electronic address:
A dramatic shift has occurred in how biologists use microscopy images. Whether experiments are small-scale or high-throughput, automatically quantifying biological properties in images is now widespread. We see yet another revolution under way: a transition towards using automated image analysis to not only identify phenotypes a biologist specifically seeks to measure ('screening') but also as an unbiased and sensitive tool to capture a wide variety of subtle features of cell (or organism) state ('profiling').
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