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Kurilung, A.

Publications and source records attributed to Kurilung, A..

2 recordsLinked to original sources

A transcriptomic-driven segmentation and cell simulation framework for high-resolution spatial transcriptomics and cell-cell communication

The Visium HD spatial transcriptomics platform enables transcriptome-wide profiling at near-single-cell resolution. However, accurate segmentation of cells to define spatial boundaries relies heavily on histological images. Previous approaches struggle to define cells when the tissues have high cell density, are inflamed, or are mineralized, leading to transcriptomic bleed-through and inaccurate clustering. To address this, we developed TENGU (Transcript-signal Enrichment and Grouping Unit), a comprehensive end-to-end bioinformatic software package. Unlike existing tools, TENGU employs a transcript-first segmentation approach, prioritizing transcript-signal density as the primary modality and utilizing histological images only as a secondary supplement in unresolved regions. These initial boundaries are further optimized through a novel transcriptomic-driven cell simulation algorithm. Iterative refinement of boundaries based on localized gene expression probabilities effectively minimizes spatial scattering and preserves biologically distinct molecular signatures. The pipeline seamlessly integrates tissue segmentation, high-resolution cell-type annotation, and basic spatially aware cell-cell communication (CCC) analysis. We rigorously benchmarked TENGU against the 10X Genomics and Bin2cell pipelines for cell segmentation across diverse and technically challenging microenvironments. TENGU demonstrated superior transcriptomic distinctness in the murine brain, successfully captured matrix-embedded osteocytes, and localized critical osteoimmune CCC networks (Tgfb and Il1a) in a murine model of osteomyelitis. TENGU also resolved species-specific, pro-tumorigenic signaling hubs (MDK-SDC4) within a highly compacted human colorectal cancer xenograft. By mitigating the constraints of traditional image-dependent segmentation, TENGU provides a highly adaptable and robust computational framework that empowers researchers to accurately decode the complex functional micro-anatomy of both healthy and pathological tissues.

bioinformatics↗

An Enhancement of Extrachromosomal Circular DNA Enrichment and Amplification to Address the Extreme Low Overlap Between Replicates

Extrachromosomal circular DNA (eccDNA) of chromosomal origin is present in all eukaryotic organisms and tissues that have been tested. Populations of eccDNA exhibit immense diversity and a characteristically low degree of overlap between samples, suggesting low inheritance of eccDNA between cells or a deficiency in the methods by which eccDNA is detected. This study revisits the Circle-seq approach for enrichment of eccDNA to address these limitations, hypothesizing that experimental procedures significantly contribute to the observed low eccDNA overlap. We optimized the protocol by reducing the time needed to complete the procedure. Linear DNA is digested by increasing Exonuclease V activity. We employed CRISPR-Cas9 for mitochondrial linearization, which proved superior to using restriction enzymes. A key finding is the critical role of random hexamer primer concentration and genomic DNA input in Rolling circle amplification (RCA) for generating high-quality long amplicons from eccDNA (concatemeric tandem copy [CTC]), essential for confident de novo eccDNA construction from long-read sequencing data. Lower primer concentrations substantially increased the percentage of CTC-derived eccDNA and improved the overlap of identified eccDNAs in technical replicates. Applying this revised approach to human myeloma and breast cancer cell lines, as well as xenograft models, demonstrated >50% overlap in detected eccDNA, a substantial improvement over the <1% overlap observed in previous studies. Additionally, the oncogenic signature of eccDNAs can be identified across all replicates. These findings provide guidelines for developing standardized procedures for eccDNA profiling, advancing our understanding of eccDNA biology, and its potential clinical applications.

genomics↗