Browsing by Author "Gulbronson, Connor J."

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    Integrated Cytometry With Machine Learning Applied to High-Content Imaging of Human Kidney Tissue for In Situ Cell Classification and Neighborhood Analysis
    (Elsevier, 2023) Winfree, Seth; McNutt, Andrew T.; Khochare, Suraj; Borgard, Tyler J.; Barwinska, Daria; Sabo, Angela R.; Ferkowicz, Michael J.; Williams, James C., Jr.; Lingeman, James E.; Gulbronson, Connor J.; Kelly, Katherine J.; Sutton, Timothy A.; Dagher, Pierre C.; Eadon, Michael T.; Dunn, Kenneth W.; El-Achkar, Tarek M.; Medicine, School of Medicine
    The human kidney is a complex organ with various cell types that are intricately organized to perform key physiological functions and maintain homeostasis. New imaging modalities, such as mesoscale and highly multiplexed fluorescence microscopy, are increasingly being applied to human kidney tissue to create single-cell resolution data sets that are both spatially large and multidimensional. These single-cell resolution high-content imaging data sets have great potential to uncover the complex spatial organization and cellular makeup of the human kidney. Tissue cytometry is a novel approach used for the quantitative analysis of imaging data; however, the scale and complexity of such data sets pose unique challenges for processing and analysis. We have developed the Volumetric Tissue Exploration and Analysis (VTEA) software, a unique tool that integrates image processing, segmentation, and interactive cytometry analysis into a single framework on desktop computers. Supported by an extensible and open-source framework, VTEA's integrated pipeline now includes enhanced analytical tools, such as machine learning, data visualization, and neighborhood analyses, for hyperdimensional large-scale imaging data sets. These novel capabilities enable the analysis of mesoscale 2- and 3-dimensional multiplexed human kidney imaging data sets (such as co-detection by indexing and 3-dimensional confocal multiplexed fluorescence imaging). We demonstrate the utility of this approach in identifying cell subtypes in the kidney on the basis of labels, spatial association, and their microenvironment or neighborhood membership. VTEA provides an integrated and intuitive approach to decipher the cellular and spatial complexity of the human kidney and complements other transcriptomics and epigenetic efforts to define the landscape of kidney cell types.
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    Integration of spatial and single-cell transcriptomics localizes epithelial cell–immune cross-talk in kidney injury
    (American Society for Clinical Investigation, 2021-06-22) Ferreira, Ricardo Melo; Sabo, Angela R.; Winfree, Seth; Collins, Kimberly S.; Janosevic, Danielle; Gulbronson, Connor J.; Cheng, Ying-Hua; Casbon, Lauren; Barwinska, Daria; Ferkowicz, Michael J.; Xuei, Xiaoling; Zhang, Chi; Dunn, Kenneth W.; Kelly, Katherine J.; Sutton, Timothy A.; Hato, Takashi; Dagher, Pierre C.; El-Achkar, Tarek M.; Eadon, Michael T.; Medicine, School of Medicine
    Single-cell sequencing studies have characterized the transcriptomic signature of cell types within the kidney. However, the spatial distribution of acute kidney injury (AKI) is regional and affects cells heterogeneously. We first optimized coordination of spatial transcriptomics and single-nuclear sequencing data sets, mapping 30 dominant cell types to a human nephrectomy. The predicted cell-type spots corresponded with the underlying histopathology. To study the implications of AKI on transcript expression, we then characterized the spatial transcriptomic signature of 2 murine AKI models: ischemia/reperfusion injury (IRI) and cecal ligation puncture (CLP). Localized regions of reduced overall expression were associated with injury pathways. Using single-cell sequencing, we deconvoluted the signature of each spatial transcriptomic spot, identifying patterns of colocalization between immune and epithelial cells. Neutrophils infiltrated the renal medulla in the ischemia model. Atf3 was identified as a chemotactic factor in S3 proximal tubules. In the CLP model, infiltrating macrophages dominated the outer cortical signature, and Mdk was identified as a corresponding chemotactic factor. The regional distribution of these immune cells was validated with multiplexed CO-Detection by indEXing (CODEX) immunofluorescence. Spatial transcriptomic sequencing complemented single-cell sequencing by uncovering mechanisms driving immune cell infiltration and detection of relevant cell subpopulations.
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    Size, shape, and direction matters: Matching secondary genital structures in male and female mites using multiple microscopy techniques and 3D modeling
    (Public Library of Science, 2021-08-18) Cómbita-Heredia, Orlando; Gulbronson, Connor J.; Ochoa, Ronald; Quintero-Gutiérrez, Javier; Bauchan, Gary; Klompen, Hans; Medicine, School of Medicine
    Studies of female genital structures have generally lagged behind comparable studies of male genitalia, in part because of an assumption of a lower level of variability, but also because internal genitalia are much more difficult to study. Using multiple microscopy techniques, including video stereomicroscopy, fluorescence microscopy, low-temperature scanning electron microscopy (LT-SEM), and confocal laser scanning microscopy (CLSM) we examined whether the complex sperm transfer structures in males of Megalolaelaps colossus (Acari: Mesostigmata) are matched by similarly complex internal structures in the female. While both LT-SEM and CLSM are well suited for obtaining high-quality surface images, CLSM also proved to be a valuable technique for observing internal anatomical structures. The long and coiled sperm transfer organ on the chelicera of the males (spermatodactyl) largely matches an equally complex, but internal, spiral structure in the females in shape, size, and direction. This result strongly suggests some form of genital coevolution. A hypothesis of sexual conflict appears to provide the best fit for all available data (morphology and life history).