Biology subjects

Gurcan, M. N.

Publications and source records attributed to Gurcan, M. N..

3 recordsLinked to original sources

bioRxiv2026

Deep Learning-Based Spatial Immunoprofiling of Multiplex Immunofluorescence Images Distinguishes Tuberculosis Disease States in Diversity Outbred Mice

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M.tb), remains a major global health challenge, with approximately 10.8 million new cases and 1.25 million deaths reported in 2023. Human responses to M.tb are heterogeneous with clinical outcomes including bacterial clearance, asymptomatic latent M.tb infection, and severe fatal pulmonary TB. Here, we aim to address knowledge gaps in the organization of M.tb granulomas by identifying cell-based spatial features indicating asymptomatic lung infection. To address this gap, which cannot be directly studied in humans, we used lung sections from M.tb infected Diversity Outbred mice with acute pulmonary TB, asymptomatic M.tb infection, or chronic pulmonary TB that were stained for T cells, B cells, macrophages, and bronchiolar epithelial cells by multiplexed immunofluorescence. We first developed a new, accurate model to automatically segment lung granulomas, detect/quantify the cell types within granulomas, and extract the location of immune cells in granulomas for each disease state. Analysis of model-derived results show that lung granulomas from asymptomatic mice have a characteristic spatial profile consisting of higher CD4+ and CD8a+ T cell densities, closer B cell proximity to bronchiolar epithelium, and increased T cell-macrophage proximity in asymptomatic M.tb infection. Next, we propose a second novel approach to utilize a large language model (LLM) to independently decode complex cellular patterns within granulomas, and distinguished key immunological signatures: balanced immune expression in asymptomatic M.tb mice, dysfunctional responses with low cellularity in acute TB, and highest immune cells in chronic TB. Overall, the results from this study show that lung granulomas in asymptomatic infection are characterized by increased T cell density, increased numbers of peribronchiolar B cells, and T cells closer to macrophages as compared to acute and chronic TB. These methods and results help establish an automated pipeline to extract and analyze data from multiplexed fluorescence images and provide a foundation to better understand how granuloma architecture varies by disease state.

immunology↗

bioRxiv2023

Systems genetics uncover new loci containing functional gene candidates in Mycobacterium tuberculosis-infected Diversity Outbred mice.

Mycobacterium tuberculosis, the bacillus that causes tuberculosis (TB), infects 2 billion people across the globe, and results in 8-9 million new TB cases and 1-1.5 million deaths each year. Most patients have no known genetic basis that predisposes them to disease. We investigated the complex genetic basis of pulmonary TB by modelling human genetic diversity with the Diversity Outbred mouse population. When infected with M. tuberculosis, one-third develop early onset, rapidly progressive, necrotizing granulomas and succumb within 60 days. The remaining develop non-necrotizing granulomas and survive longer than 60 days. Genetic mapping using clinical indicators of disease, granuloma histopathological features, and immune response traits identified five new loci on mouse chromosomes 1, 2, 4, 16 and three previously identified loci on chromosomes 3 and 17. Quantitative trait loci (QTLs) on chromosomes 1, 16, and 17, associated with multiple correlated traits and had similar patterns of allele effects, suggesting these QTLs contain important genetic regulators of responses to M. tuberculosis. To narrow the list of candidate genes in QTLs, we used a machine learning strategy that integrated gene expression signatures from lungs of M. tuberculosis-infected Diversity Outbred mice with gene interaction networks, generating functional scores. The scores were then used to rank candidates for each mapped trait in each locus, resulting in 11 candidates: Ncf2, Fam20b, S100a8, S100a9, Itgb5, Fstl1, Zbtb20, Ddr1, Ier3, Vegfa, and Zfp318. Importantly, all 11 candidates have roles in infection, inflammation, cell migration, extracellular matrix remodeling, or intracellular signaling. Further, all candidates contain single nucleotide polymorphisms (SNPs), and some but not all SNPs were predicted to have deleterious consequences on protein functions. Multiple methods were used for validation including (i) a statistical method that showed Diversity Outbred mice carrying PWH/PhJ alleles on chromosome 17 QTL have shorter survival; (ii) quantification of S100A8 protein levels, confirming predicted allele effects; and (iii) infection of C57BL/6 mice deficient for the S100a8 gene. Overall, this work demonstrates that systems genetics using Diversity Outbred mice can identify new (and known) QTLs and new functionally relevant gene candidates that may be major regulators of granuloma necrosis and acute inflammation in pulmonary TB.

genetics↗

bioRxiv2022

DNA-caged Nanoparticles via Electrostatic Self-Assembly

DNA-modified nanoparticles enable DNA sensing and therapeutics in nanomedicine and are also crucial for nanoparticle self-assembly with DNA-based materials. However, methods to conjugate DNA to nanoparticle surfaces are limited, inefficient, and lack control. Inspired by DNA tile nanotechnology, we demonstrate a new approach to nanoparticle modification based on electrostatic attraction between negatively charged DNA tiles and positively charged nanoparticles. This approach does not disrupt nanoparticle surfaces and leverages the programmability of DNA nanotechnology to control DNA presentation. We demonstrated this approach using a variety of nanoparticles, including polymeric micelles, polystyrene beads, gold nanoparticles, and superparamagnetic iron oxide nanoparticles with sizes ranging from 5-20 nm in diameter. DNA cage formation was confirmed through transmission electron microscopy (TEM), neutralization of zeta potential, and a series of fluorescence experiments. DNA cages present "handle" sequences that can be used for reversible target attachment or self-assembly. Handle functionality was verified in solution, at the solid-liquid interface, and inside fixed cells, corresponding to applications in biosensing, DNA microarrays, and erasable immunocytochemistry. These experiments demonstrate the versatility of the electrostatic DNA caging approach and provide a new pathway to nanoparticle modification with DNA that will empower further applications of these materials in medicine and materials science.

bioengineering↗