Biology subjects

Bray, M.-A.

Publications and source records attributed to Bray, M.-A..

3 recordsLinked to original sources

bioRxiv2024

Use of machine learning for quantification of retinal pigment epithelium tight junctions improves assay sensitivity

The retinal pigment epithelium (RPE) is critical for maintaining outer retinal barrier homeostasis. In age-related macular degeneration (AMD), the RPE can undergo a dedifferentiation process that includes tight junction (TJ) loss and displacement of zonula occludens-1 (ZO-1), which may impair structural and functional integrity of the RPE barrier and contribute to disease pathogenesis. Our objective was to develop an automated and sensitive quantification method for TJ aberrations in an RPE immunofluorescence imaging assay, following treatment with TNF or TGF{beta}2. However, quantifying ZO-1 morphological changes in the RPE using standard image analysis methods did not provide a satisfactory assay window. To address this challenge, we developed an imaging assay to quantify ZO-1 changes using a machine learning approach, enabling enhanced phenotypic characterization of the ZO-1 changes in RPE cells and improved assay sensitivity. We were also able to capture and quantify the reversal of these changes using etanercept, an TNF inhibitor, with this imaging assay. Our findings indicated that this machine learning ZO-1 quantification assay could serve as a potential phenotypic readout for RPE dedifferentiation and enabling large-scale mechanistic studies.

bioinformatics↗

bioRxiv2021

Cell Painting predicts impact of lung cancer variants

Most variants in most genes across most organisms have an unknown impact on the function of the corresponding gene. This gap in knowledge is especially acute in cancer, where clinical sequencing of tumors now routinely reveals patient-specific variants whose functional impact on the corresponding gene is unknown, impeding clinical utility. Transcriptional profiling was able to systematically distinguish these variants of unknown significance (VUS) as impactful vs. neutral in an approach called expression-based variant-impact phenotyping (eVIP). We profiled a set of lung adenocarcinoma-associated somatic variants using Cell Painting, a morphological profiling assay that captures features of cells based on microscopy using six stains of cell and organelle components. Using deep-learning-extracted features from each cells image, we found that cell morphological profiling (cmVIP) can predict variants functional impact and, particularly at the single-cell level, reveals biological insights into variants which can be explored in our public online portal. Given its low cost, convenient implementation, and single-cell resolution, cmVIP profiling therefore seems promising as an avenue for using non-gene-specific assays to systematically assess the impact of variants, including disease-associated alleles, on gene function.

cancer biology↗

bioRxiv2016

Systematic morphological profiling of human gene and allele function reveals Hippo-NF-κB pathway connectivity

We hypothesized that human genes and disease-associated alleles might be systematically functionally annotated using morphological profiling of cDNA constructs, via a microscopy-based Cell Painting assay. Indeed, 50% of the 220 tested genes yielded detectable morphological profiles, which grouped into biologically meaningful gene clusters consistent with known functional annotation (e.g., the RAS-RAF-MEK-ERK cascade). We used novel subpopulation-based visualization methods to interpret the morphological changes for specific clusters. This unbiased morphologic map of gene function revealed TRAF2/C-REL negative regulation of YAP 1/WWTR1-responsive pathways. We confirmed this discovery of functional connectivity between the O_SCPCAPNF-C_SCPCAP{kappa}O_SCPCAPBC_SCPCAP pathway and Hippo pathway effectors at the transcriptional level, thereby expanding knowledge of these two signaling pathways that critically regulate tumor initiation and progression. We make the images and raw data publicly available, providing an initial morphological map of major biological pathways for future study.

systems biology↗