Biology subjects

Kaya, B.

Publications and source records attributed to Kaya, B..

7 recordsLinked to original sources

bioRxiv2026

Antiviral Sulfonated Polymersomes Inhibit Corona-, Influenza-, and Alphavirus

A broad-spectrum antiviral is required to enable rapid intervention against current, newly emerging and mutating viruses. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (IAV), Sindbis virus (SINV) and chikungunya virus (CHIKV) all engage negatively charged moieties on host cells, such as heparan sulfate (HS) and sialic acid, to facilitate attachment for entry and infection. We designed HS-mimetic nanoparticles in the form of polymer vesicles (polymersomes) by blending membrane-forming and sulfonated copolymers. These biocompatible polymersomes successfully inhibited host cell infection of HS-dependent SARS-CoV-2 and HS-independent IAV in vitro with sub-nanomolar potency. Multivalent interaction of several virus ligands with a single polymersome as quantified by fluorescence correlation spectroscopy likely contributes to their potency. The sulfonated polymersomes also functioned in vivo as demonstrated by a reduction in the spread of SINV, an alphavirus model for CHIKV, in zebrafish embryos, which led to a significantly increased survival. Hence, our polymersomes could form the basis for an urgently required multifunctional broad-spectrum antiviral nanomedicine.

bioengineering↗

bioRxiv2025

Temporal Expression Prediction by Integrating Genome Dynamics via Spatio-temporal GNNs

Temporal gene expression is being analyzed via high-throughput profiling of molecular data over time. The expression values of genes are impacted by their previous expression values as well as the expression of interacting genes over time. Hi-C provides us with a broad genome-wide perspective on the interacting dynamics of genes. In this paper, we propose neural network-based spatio-temporal graph approaches STEPmr and STEPmi to predict changes in mRNA and miRNA expression over time, respectively. Both approaches can integrate a diverse set of Hi-C datasets and features obtained from Hi-C when predicting temporal expression patterns. Our methods can predict mRNA and miRNA expression with 77% and 93% correlation and ith mean squared errors of 0.21 and 0.01, explaining 59.1% and 88% of the variance, respectively. Important characteristics of the genes with the highest performances in both datasets are that they are structural signaling genes or transcriptional regulators involved in fundamental processes such as homeostasis, development, and RNA processing. Additionally, they are not limited to a specific cell type, but rather show constant expression throughout different tissues. In contrast, the lowest-performed genes generally behave in context-dependent expression patterns, where they include condition-specific biological functions instead of vital biological activities. These findings suggest a model of gene regulation and its predictability that is impacted by interacting gene dynamics. Our code and datasets are publicly available at https://github.com/seferlab/temporalhic.

bioinformatics↗

bioRxiv2025

GAT-HiC: Efficient Reconstruction of 3D Chromosome Structure via Residual Graph Attention Neural Networks

Hi-C is an experimental technique to measure the genome-wide topological dynamics and three-dimensional (3D) shape of chromosomes indirectly via counting the number of interactions between distinct sets of loci. One can estimate the 3D shape of a chromosome over these indirect interaction datasets. Here, we come up with graph attention and residual network-based GAT-HiC to predict three-dimensional chromosome structure from Hi-C interactions. GAT-HiC is distinct from the existing 3D chromosome shape prediction approaches in a way that it can generalize to data that is different than train data. So, we can train GAT-HiC on one type of Hi-C interaction matrix and infer on a completely dissimilar interaction matrix. GAT-HiC combines the unsupervised vertex embedding method Node2vec with an attention-based graph neural network when predicting each genomic locis three-dimensional coordinates from Hi-C interaction matrix. We test the performance of our method across multiple Hi-C interaction datasets, where a trained model can be generalized across distinct cell populations, distinct restriction enzymes, and distinct Hi-C resolutions over human and mouse. GAT-HiC can reconstruct accurately in all these scenarios. Our method outperforms the existing approaches in terms of the accuracy of three-dimensional chromosome shape inference over interaction datasets. Code and datasets can be found at https://github.com/beyzoskaya/GAT-HiC.

bioinformatics↗

bioRxiv2023

Delineation of the Trigeminal-Lateral Parabrachial-Central Amygdala Tract in Humans: An Ultra-High Field Diffusion MRI Study

Orofacial pain is thought to be more unpleasant than pain elsewhere in the body due to the importance of the face in social, feeding, and exploratory behaviors. Nociceptive information from the orofacial region is carried to the brain via the trigeminal nerve (CNV) via the trigeminal brainstem sensory nuclear complex (VBSNC). Pre-clinical evidence revealed a monosynaptic circuit from CNV to the lateral parabrachial nucleus (latPB), which underlies the greater unpleasantness elicited by orofacial pain. The latPB further projects to the central amygdala (CeA), which contributes to the affective component of pain in rodents. However, this circuit has yet to be delineated in humans. Here, we aimed to resolve this circuit using 7T diffusion-weighted imaging from the Human Connectome Project (HCP). We performed probabilistic tractography in 80 participants to resolve the CNV-latPB-CeA circuit. The basolateral amygdala (BLAT) was used as a negative control, given that we did not anticipate CNV-latPB-BLAT connectivity. Connectivity strengths were compared using a repeated-measures ANOVA with factors hemisphere (left; right), and target (CeA; BLAT), with sex included in the model for both pilot and validation samples. Only the target factor was significant in both samples (FPilot = 11.4804, p = 0.005; FValidation = 69.113, p < .001). Post hoc tests showed that the CeA had significantly stronger connectivity strength than the BLAT (pTukey-Pilot = 0.005; pTukey-Validation < 0.001). {square}This study delineates the human CNV-latPB-CeA circuit for the first time in vivo. This circuit may provide a neuroanatomical substrate for the affective dimensions of orofacial pain. SUMMARYThis study delineates the human trigeminal-parabrachio-amygdalar circuit in vivo. This circuit may provide a neuroanatomical substrate for the affective dimension of orofacial pain.

neuroscience↗

bioRxiv2021

Epithelial GPR35 protects from Citrobacter rodentium infection by preserving goblet cells and mucosal barrier integrity

Goblet cells secrete mucin to create a protective mucus layer against invasive bacterial infection and are therefore essential for maintaining intestinal health. However, the molecular pathways that regulate goblet cell function remain largely unknown. Although GPR35 is highly expressed in colonic epithelial cells, its importance in promoting the epithelial barrier is unclear. In this study, we show that epithelial Gpr35 plays a critical role in goblet cell function. In mice, cell type-specific deletion of Gpr35 in epithelial cells but not in macrophages results in goblet cell depletion and dysbiosis, rendering these animals more susceptible to Citrobacter rodentium infection. Mechanistically, scRNA-seq analysis indicates that signaling of epithelial Gpr35 is essential to maintain normal pyroptosis levels in goblet cells. Our work shows that the epithelial presence of Gpr35 is a critical element for the function of goblet cell-mediated symbiosis between host and microbiota.

immunology↗

bioRxiv2020

Lysophosphatidic acid-mediated GPR35 signaling in CX3CR1+ macrophages regulates the intestinal cytokine milieu

Single nucleotide polymorphisms in the gene encoding G protein-coupled receptor 35 (GPR35) are associated with increased risk of inflammatory bowel disease. However, the mechanism(s) by which GPR35 modulates the intestinal milieu remain undefined. Here we demonstrate in zebrafish and mice that expression of Gpr35 is microbiota-dependent and is enhanced upon inflammation. We identify a GPR35+ colonic macrophage population in mice that is characterized by increased production of pro-inflammatory cytokines, and determine that lysophosphatidic acid (LPA) acts as an endogenous GPR35 ligand to induce Tnf expression. Mice lacking Gpr35 in CX3CR1+ macrophages have aggravated colitis when exposed to dextran sodium sulfate, have decreased transcript levels of the corticosterone-generating gene Cyp11b1, and reduced levels of macrophage-derived TNF. Administration of TNF in these mice restores Cyp11b1 expression and intestinal corticosterone production, and ameliorates DSS-induced colitis. These findings suggest that LPA signals through GPR35 in CX3CR1+ macrophages to control the intestinal cytokine milieu. HighlightsO_LIInflammatory cues and the microbiota modulate Gpr35 expression across species C_LIO_LILPA modulates GPR35-dependent functions in zebrafish and mice macrophages C_LIO_LIGPR35 expressing macrophages have a protective role during intestinal inflammation C_LIO_LIGPR35 control intestinal inflammation by inducing TNF and corticosterone synthesis C_LI eTOC BlurbGPR35 have been associated with IBD, but how GPR35 may influence macrophage-mediated intestinal homeostasis remains unclear. Using zebrafish and mice genetic tools, Niess, Villablanca, and colleagues have identified that LPA triggers GPR35 activity, and loss of macrophage GPR35 signaling confers intrinsic dysfunctions with effects on cytokine production and intestinal homeostasis.

immunology↗

bioRxiv2018

Spheroid culture of mesenchymal stromal cells results in morpho-rheological properties appropriate for improved microcirculation

Human bone marrow mesenchymal stromal cells (MSCs) have been used in clinical trials for the treatment of systemic inflammatory diseases due to their regenerative and immunomodulatory properties. However, intravenous administration of MSCs is hampered by cell trapping within the pulmonary capillary networks. Here, we hypothesize that traditional twodimensional (2D) plastic-adherent cell expansion fails to result in appropriate morphorheological properties required for cell-circulation. To address this issue, we adapted a novel method to culture MSCs in non-adherent three-dimensional (3D) spheroids (mesenspheres). The biological properties of mesensphere-cultured MSCs remained identical to conventional 2D cultures. Morpho-rheological analyses revealed a smaller size and lower cell stiffness of mesensphere-derived MSCs compared to plastic-adherent MSCs, measured using real-time deformability cytometry (RT-DC) and atomic force microscopy, resulting in an increased ability to pass through micro-constrictions in an ex vivo microcirculation assay. This ability was confirmed in vivo by analysis of cell accumulation in various organ capillary networks after intravenous injection of mesensphere-derived MSCs in mouse. Our findings generally identify cellular morpho-rheological properties as attractive targets to improve microcirculation and specifically suggest mesensphere cultures as a promising approach for optimized MSC-based therapies.

biophysics↗