Biology subjects

Tyc, K. M.

Publications and source records attributed to Tyc, K. M..

4 recordsLinked to original sources

bioRxiv2024

Spatial Deconvolution of Cell Types and Cell States at Scale Utilizing TACIT

Identifying cell types and states remains a time-consuming and error-prone challenge for spatial biology. While deep learning is increasingly used, it is difficult to generalize due to variability at the level of cells, neighborhoods, and niches in health and disease. To address this, we developed TACIT, an unsupervised algorithm for cell annotation using predefined signatures that operates without training data, using unbiased thresholding to distinguish positive cells from background, focusing on relevant markers to identify ambiguous cells in multiomic assays. Using five datasets (5,000,000-cells; 51-cell types) from three niches (brain, intestine, gland), TACIT outperformed existing unsupervised methods in accuracy and scalability. Integration of TACIT-identified cell with a novel Shiny app revealed new phenotypes in two inflammatory gland diseases. Finally, using combined spatial transcriptomics and proteomics, we discover under- and overrepresented immune cell types and states in regions of interest, suggesting multimodality is essential for translating spatial biology to clinical applications.

bioinformatics↗

bioRxiv2023

Polybacterial intracellular coinfection of epithelial stem cells in periodontitis

Periodontitis affects billions of people worldwide. To address interkingdom relationships of microbes and niche on periodontitis, we generated the first sin-gle-cell meta-atlas of human periodontium (34-sample, 105918-cell), harmo-nizing 32 annotations across 4 studies1-4. Highly multiplexed immunofluores-cence (32-antibody; 113910-cell) revealed spatial innate and adaptive immune foci segregation around tooth-adjacent epithelial cells. Sulcular and junctional keratinocytes (SK/JKs) within epithelia skewed toward proinflammatory phe-notypes; diseased JK stem/progenitors displayed altered differentiation states and chemotactic cytokines for innate immune cells. Single-cell metagenomics utilizing unmapped reads revealed 37 bacterial species. 16S and rRNA probes detected polybacterial intracellular pathogenesis ("co-infection") of 4 species within single cells for the first time in vivo. Challenging coinfected primary human SK/JKs with lipopolysaccharide revealed solitary and synergistic ef-fects. Coinfected single-cell analysis independently displayed proinflammatory phenotypes in situ. Here, we demonstrate the first evidence of polybacterial intracellular pathogenesis in human tissues and cells--potentially influencing chronic diseases at distant sites.

cell biology↗

bioRxiv2021

Yin Yang 1 sets up the stage for cerebellar astrocyte maturation

Diverse subpopulations of astrocytes tile different brain regions to accommodate local requirements of neurons and associated neuronal circuits. Nevertheless, molecular mechanisms governing astrocyte diversity remain mostly unknown. We explored the role of a zinc finger transcription factor Yin Yang 1 (YY1) that is expressed in astrocytes. We found that specific deletion of YY1 from astrocytes causes severe motor deficits in mice, induces Bergmann gliosis, and results in simultaneous loss of GFAP expression in velate and fibrous cerebellar astrocytes. Single cell RNA-seq analysis showed that YY1 exerts specific effects on gene expression in subpopulations of cerebellar astrocytes. We found that although YY1 is dispensable for the initial stages of astrocyte development, it regulates subtype-specific gene expression during astrocyte maturation. Moreover, YY1 is continuously needed to maintain mature astrocytes in the adult cerebellum. Our findings suggest that YY1 plays critical roles regulating cerebellar astrocyte maturation during development and maintaining a mature phenotype of astrocytes in the adult cerebellum.

neuroscience↗

bioRxiv2020

Chromatin conformation capture (Hi-C) sequencing of patient-derived xenografts: analysis guidelines

Sequencing of patient-derived xenograft (PDX) mouse models allows investigation of the molecular mechanisms of human tumor samples engrafted in a mouse host. Thus, both human and mouse genetic material is sequenced. Several methods have been developed to remove mouse sequencing reads from RNA-seq or exome sequencing PDX data and improve the downstream signal. However, for more recent chromatin conformation capture technologies (Hi-C), the effect of mouse reads remains undefined. We evaluated the effect of mouse read removal on the quality of Hi-C data using in silico created PDX Hi-C data with 10% and 30% mouse reads. Additionally, we generated two experimental PDX Hi-C datasets using different library preparation strategies. We evaluated three alignment strategies (Direct, Xenome, Combined) and three processing pipelines (Juicer, HiC-Pro, HiCExplorer) on the quality of Hi-C data. Removal of mouse reads had little-to-no effect on data quality than the results obtained with Direct alignment strategy. Juicer pipeline extracted the most useful information from PDX Hi-C data. However, library preparation strategy had the largest effect on all quality metrics. Together, our study presents comprehensive guidelines on PDX Hi-C data processing.

genomics↗