Biology subjects

Przytycki, P.

Publications and source records attributed to Przytycki, P..

4 recordsLinked to original sources

bioRxiv2025

A multimodal approach for visualization and identification of electrophysiological cell types in vivo

Neurons of different types perform diverse computations and coordinate their activity during sensation, perception, and action. While electrophysiological recordings can measure the activity of many neurons simultaneously, identifying cell types during these experiments remains difficult. To identify cell types, we developed PhysMAP, a framework that weighs multiple electrophysiological modalities simultaneously to obtain interpretable multimodal representations. We apply PhysMAP to seven datasets and demonstrate that these multimodal representations are better aligned with known transcriptomically-defined cell types than any single modality alone. We then show that such alignment allows PhysMAP to better identify putative cell types in the absence of ground truth. We also demonstrate how annotated datasets can be used to infer multiple cell types simultaneously in unannotated datasets and show that the properties of inferred types are consistent with the known properties of these cell types. Finally, we provide a first-of-its-kind demonstration of how PhysMAP can help understand how multiple cell types interact to drive circuit dynamics. Collectively, these results demonstrate that multimodal representations from PhysMAP enable the study of multiple cell types simultaneously, thus providing insight into neural circuit dynamics.

neuroscience↗

bioRxiv2024

PhysMAP - interpretable in vivo neuronal cell type identification using multi-modal analysis of electrophysiological data

Cells of different types perform diverse computations and coordinate their activity during sensation, perception, and action. While electrophysiological approaches can measure the activity of many neurons simultaneously, assigning cell type labels to these neurons is an open problem. Here, we develop PhysMAP, a framework that weighs multiple electrophysiological modalities simultaneously in an unsupervised manner and obtain an interpretable representation that separates neurons by cell type. PhysMAP is superior to any single electrophysiological modality in identifying neuronal cell types such as excitatory pyramidal, PV+ interneurons, and SOM+ interneurons with high confidence in both juxtacellular and extracellular recordings and from multiple areas of the mouse brain. PhysMAP built on ground truth data can be used for classifying cell types in new and existing electrophysiological datasets, and thus facilitate simultaneous assessment of the coordinated dynamics of multiple neuronal cell types during behavior.

neuroscience↗

bioRxiv2022

Single Cell Epigenetics Reveal Cell-Cell Communication Networks in Normal and Abnormal Cardiac Morphogenesis

Communication between myriad cell types during organ formation underlies proper morphogenesis1. In cardiac development, reciprocal signaling between mesoderm progenitors and neural crest cells is essential, and its disruption leads to congenital heart malformations, the most common human birth defect. However, mechanistic interrogation of temporal gene networks and cis regulatory elements in this crosstalk is limited2,3. Here, we integrated single cell chromatin accessibility and transcriptomics to establish an unbiased and temporal epigenomic map of the embryonic mouse heart over multiple stages and developed machine learning models to predict enhancers for heart and neural crest. We leveraged these advances to determine the consequences of dysregulated signaling at single cell resolution caused by deletion of TBX1, a transcription factor that causes morphogenetic defects of the cardiac outflow tract in humans and functions non-cell autonomously in cardiac mesodermal progenitors to direct pharyngeal neural crest differentiation4-6. Loss of Tbx1 in mice led to broad closure of chromatin regions enriched in cardiac progenitor transcription factor motifs within a narrow subset of cardiac mesodermal progenitors and correlated with diminished expression of numerous members of the fibroblast growth factor, retinoic acid, Notch and Semaphorin pathways. In affected progenitors, ectopic accessibility and expression of posterior heart field factors in the anterior heart field suggested impaired axial patterning. In response, a subset of cardiac neural crest cells displayed epigenomic and transcriptional defects, indicating a failure of differentiation corresponding to dysregulation of the anterior-posterior gradient of pharyngeal Hox gene expression. This study demonstrates that single-cell genomics and machine learning can generate a mechanistic model for how disruptions in cell communication selectively affect spatiotemporally dynamic regulatory networks in cardiogenesis.

developmental biology↗

bioRxiv2019

A Chromatin Accessibility Atlas of the Developing Human Telencephalon

Gene expression differs between cell types and regions within complex tissues such as the developing brain. To discover regulatory elements underlying this specificity, we generated genome-wide maps of chromatin accessibility in eleven anatomically-defined regions of the developing human telencephalon, including upper and deep layers of the prefrontal cortex. We predicted a subset of open chromatin regions (18%) that are most likely to be active enhancers, many of which are dynamic with 26% differing between early and late mid-gestation and 28% present in only one brain region. These region-specific predicted regulatory elements (pREs) are enriched proximal to genes with expression differences across regions and developmental stages and harbor distinct sequence motifs that suggest potential upstream regulators of regional and temporal transcription. We leverage this atlas to identify regulators of genes associated with autism spectrum disorder (ASD) including an enhancer of BCL11A, validated in mouse, and two functional de novo mutations in individuals with ASD in an enhancer of SLC6A1, validated in neuroblastoma cells. These applications demonstrate the utility of this atlas for decoding neurodevelopmental gene regulation in health and disease.\n\nSummaryTo discover regulatory elements driving the specificity of gene expression in different cell types and regions of the developing human brain, we generated an atlas of open chromatin from eleven dissected regions of the mid-gestation human telencephalon, including upper and deep layers of the prefrontal cortex. We identified a subset of open chromatin regions (OCRs), termed predicted regulatory elements (pREs), that are likely to function as developmental brain enhancers. pREs showed regional differences in chromatin accessibility, including many specific to one brain region, and were correlated with gene expression differences across the same regions and gestational ages. pREs allowed us to map neurodevelopmental disorder risk genes to developing telencephalic regions, and we identified three functional de novo noncoding variants in pREs that alter enhancer function. In addition, transgenic experiments in mouse validated enhancer activity for a pRE proximal to BCL11A, showing how this atlas serves as a resource for decoding neurodevelopmental gene regulation in health and disease.

neuroscience↗