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Biology subjects

Ezran, C.

Publications and source records attributed to Ezran, C..

5 recordsLinked to original sources

Cellular and molecular characterization of peripheral glia in the lung and other organs

Peripheral glia are important regulators of diverse physiologic functions yet their molecular distinctions and locations in almost all visceral organs are not well-understood. We performed a systematic analysis of peripheral glia, focusing on the lung and leveraging single cell RNA sequencing (scRNA-seq) analysis to characterize their cellular and molecular features. Using in vivo lineage studies, we characterized the anatomic, cellular, and molecular features of the Sox10+ glial lineage of the mouse lung. Using high-resolution imaging, we quantified the distribution and cellular morphologies of myelinating, non-myelinating, satellite, and terminal glial cells with their intricate extensions along peripheral nerves, including terminals at specialized neurosensory structures within the lung. Spatial analysis of selectively expressed myelinating (periaxin/Prx, claudin 19/Cldn) or non-myelinating (sodium channel/Scn7a) glial cell genes identified by scRNA-seq analysis revealed molecularly distinct populations surrounding myelinated nerve fibers in the lung. To extend this analysis to primates and other organs, we extracted rare peripheral glial cells in whole organism scRNA-seq atlases of mouse lemur and human. Our cross-species data analysis and integration of scRNA-seq data of [~]700 peripheral glial cells from mouse, mouse lemur, and human glial cells identified conserved gene expression of molecularly distinct peripheral glial cell populations. This foundational knowledge facilitates subsequent functional studies targeting molecularly distinct subsets of peripheral glia and integrating them into organ-specific disorders of autonomic dysregulation. In addition, our cross-species analysis identifying conserved gene expression patterns and glial networks in extrapulmonary organs provides a valuable resource for studying the functional role of peripheral glia in multiorgan human diseases.

cell biology↗

Mouse lemur transcriptomic atlas elucidates primate genes, physiology, disease, and evolution

Mouse lemurs (Microcebus spp.) are an emerging primate model organism. However, little is known about their genetics or cellular and molecular biology. In the accompanying paper, we used large-scale single cell RNA-sequencing of 27 organs and tissues to identify over 750 molecular cell types, characterize their full transcriptomic profiles, and study evolution of primate cell types. Here we use the atlas to characterize mouse lemur genes, mutations, physiology, and disease. We uncover thousands of previously unidentified lemur genes and hundreds of thousands of new splice junctions that globally define lemur gene structures and reveal over 85,000 primate splice junctions missing in mice. We systematically explore the lemur immune system, comparing the global expression profiles of key immune genes in health and disease, and molecular mapping of immune cell development, trafficking, and their local and global activation to infection. We characterize primate/lemur-specific physiology and disease including molecular features of the immune program, of lemur adipocytes that exhibit dramatic seasonal rhythms, and of metastatic endometrial cancer that resembles the human malignancy. We identify and describe the expression patterns of over 400 primate genes missing in mice, many with similar expression patterns in human and lemur and some implicated in human disease. Finally, we provide an experimental framework for reverse genetic analysis by identifying naturally-occurring nonsense (null) mutations in three primate genes missing in mice and analyzing their transcriptional phenotypes. This work establishes mouse lemur as a tractable primate model organism for genetic and molecular analysis, and it prioritizes primate genes, splice junctions, physiology, and disease for future study.

genetics↗

An organism-wide atlas of hormonal signaling based on the mouse lemur single-cell transcriptome

Hormones mediate long-range cell communication in multicellular organisms and play vital roles in normal physiology, metabolism, and health. Using the newly-completed organism-wide single cell transcriptional atlas of a non-human primate, the mouse lemur (Microcebus murinus), we have systematically identified hormone-producing and -target cells for 84 classes of hormones, and have created a browsable atlas for hormone signaling that reveals previously unreported sites of hormone regulation and species-specific rewiring. Hormone ligands and receptors exhibited cell-type-dependent, stereotypical expression patterns, and their transcriptional profiles faithfully classified the molecular cell type identities, despite their comprising less than 1% of the transcriptome. Cells of similar cell types further display stage, subtype or organ-dependent specification of hormonal signaling, reflecting the precise control of global hormonal regulation. By linking ligand-expressing cells to the cells expressing the corresponding receptor, we constructed an organism-wide map of the hormonal cell communication network. This network was remarkably densely and robustly connected and included a myriad of feedback circuits. Although it includes classical hierarchical circuits (e.g. pituitary [->] peripheral endocrine gland [->] diverse cell types), the hormonal network is overall highly distributed without obvious network hubs or axes. Cross-species comparisons among humans, lemurs, and mice suggest that the mouse lemur better models human hormonal signaling, than does the mouse. Hormonal genes show a higher evolutionary conservation between human and lemur vs. human and mouse at both the genomic level (orthology-mapping and sequence identity) and the transcriptional level (cell type expression patterns). This primate hormone atlas provides a powerful resource to facilitate discovery of regulation on an organism-wide scale and at single-cell resolution, complementing the single-site-focused strategy of classical endocrine studies. The network nature of hormone regulation and the principles discovered here further emphasize the importance of a systems approach to understanding hormone regulation.

genomics↗

Tabula Microcebus: A transcriptomic cell atlas of mouse lemur, an emerging primate model organism

Mouse lemurs are the smallest, fastest reproducing, and among the most abundant primates, and an emerging model organism for primate biology, behavior, health and conservation. Although much has been learned about their physiology and their Madagascar ecology and phylogeny, little is known about their cellular and molecular biology. Here we used droplet- and plate-based single cell RNA-sequencing to profile 226,000 cells from 27 mouse lemur organs and tissues opportunistically procured from four donors clinically and histologically characterized. Using computational cell clustering, integration, and expert cell annotation, we defined and biologically organized over 750 mouse lemur molecular cell types and their full gene expression profiles. These include cognates of most classical human cell types, including stem and progenitor cells, and the developmental programs for spermatogenesis, hematopoiesis, and other adult tissues. We also described dozens of previously unidentified or sparsely characterized cell types and subtypes. We globally compared cell type expression profiles to define the molecular relationships of cell types across the body, and explored primate cell and gene expression evolution by comparing mouse lemur cell transcriptomes to those of human, mouse, and macaque. This revealed cell type specific patterns of primate specialization, as well as many cell types and genes for which lemur provides a better human model than mouse. The atlas provides a cellular and molecular foundation for studying this primate model organism, and establishes a general approach for other emerging model organisms.

genetics↗

Index Switching Causes "Spreading-Of-Signal" Among Multiplexed Samples In Illumina HiSeq 4000 DNA Sequencing

Illumina-based next generation sequencing (NGS) has accelerated biomedical discovery through its ability to generate thousands of gigabases of sequencing output per run at a fraction of the time and cost of conventional technologies. The process typically involves four basic steps: library preparation, cluster generation, sequencing, and data analysis. In 2015, a new chemistry of cluster generation was introduced in the newer Illumina machines (HiSeq 3000/4000/X Ten) called exclusion amplification (ExAmp), which was a fundamental shift from the earlier method of random cluster generation by bridge amplification on a non-patterned flow cell. The ExAmp chemistry, in conjunction with patterned flow cells containing nanowells at fixed locations, increases cluster density on the flow cell, thereby reducing the cost per run. It also increases sequence read quality, especially for longer read lengths (up to 150 base pairs). This advance has been widely adopted for genome sequencing because greater sequencing depth can be achieved for lower cost without compromising the quality of longer reads. We show that this promising chemistry is problematic, however, when multiplexing samples. We discovered that up to 5-10% of sequencing reads (or signals) are incorrectly assigned from a given sample to other samples in a multiplexed pool. We provide evidence that this \"spreading-of-signals\" arises from low levels of free index primers present in the pool. These index primers can prime pooled library fragments at random via complementary 3 ends, and get extended by DNA polymerase, creating a new library molecule with a new index before binding to the patterned flow cell to generate a cluster for sequencing. This causes the resulting read from that cluster to be assigned to a different sample, causing the spread of signals within multiplexed samples. We show that low levels of free index primers persist after the most common library purification procedure recommended by Illumina, and that the amount of signal spreading among samples is proportional to the level of free index primer present in the library pool. This artifact causes homogenization and misclassification of cells in single cell RNA-seq experiments. Therefore, all data generated in this way must now be carefully re-examined to ensure that \"spreading-of-signals\" has not compromised data analysis and conclusions. Re-sequencing samples using an older technology that uses conventional bridge amplification for cluster generation, or improved library cleanup strategies to remove free index primers, can minimize or eliminate this signal spreading artifact.

molecular biology↗