Biology subjects

Celik, N.

Publications and source records attributed to Celik, N..

9 recordsLinked to original sources

bioRxiv2026

Senescent cell networks link matrix remodeling and vascular dysfunction in human fibroids

Uterine fibroids (leiomyomas) are highly prevalent benign tumors defined by excessive extracellular matrix (ECM) deposition, altered vascular structure, and progressive tissue stiffening, yet the cellular programs that coordinate these features remain poorly understood. Cellular senescence has been implicated in fibroid biology, but whether senescence represents a uniform state or distinct, functionally specialized cell identities within fibroids is unknown. Here, we identify the distinct heterogeneous populations of senescent cells ("senotypes") present in human fibroids and characterize their role in shaping the fibroid microenvironment. Using single-cell RNA sequencing (scRNA-seq) integrated with a senescence gene signature and protein-level validation, we identify senescent cells (SnC) distributed across fibroblast, mural, and endothelial compartments, each exhibiting distinct transcriptional programs. SnC endothelial cells (ECs) are enriched in fibroids relative to matched myometrium and activate TEAD4-associated mechanosensing, angiogenic, and immune signaling pathways, despite being associated with impaired vessel maturation in situ. In parallel, SnC fibroblast and mural populations in fibroids upregulated SRF-associated cytoskeletal and ECM programs, accompanied by increased COL6A3 expression and collagen VI deposition, consistent with tissue stiffening. Ligand-receptor and spatial analyses reveal that these SnC populations function as interconnected signaling hubs, coordinating immune cell recruitment and stromal remodeling. Importantly, analysis of human fibroids treated with collagenase demonstrated a reduction in both ECM density and SnC burden, supporting a reinforcing relationship between matrix mechanics and senescence. Together, these findings establish senescence in fibroids as a heterogeneous, mechanically reinforced, and network-driven process that links vascular dysfunction, immune signaling, and fibrosis, highlighting distinct SnC states as potential translational targets for non-surgical therapies.

cell biology↗

bioRxiv2025

Murine gut microbiota dysbiosis via enteric infection modulates the foreign body response to a distal biomaterial implant

The gut microbiota influences systemic immunity and the function of distal tissues, including the brain, liver, skin, lung, and muscle. However, the role of the gut microbiota in the foreign body response (FBR) and fibrosis around medical implants is largely unexplored. To investigate this connection, we perturbed the homeostasis of the murine gut microbiota via enterotoxigenic Bacteroides fragilis (ETBF) infection and implanted the synthetic polymer polycaprolactone (PCL) into a distal muscle injury. ETBF infection in mice led to increased neutrophil and {gamma}{delta} T cell infiltration into the PCL implant site. ETBF infection alone promoted systemic inflammation and increased levels of neutrophils in the blood, spleen, and bone marrow. At the PCL implant site, we found significant changes in the transcriptome of sorted fibroblasts but did not observe gross ETBF- induced differences in the fibrosis levels after 6 weeks. These results demonstrate the ability of the gut microbiota to mediate long-distance effects such as immune and stromal responses to a distal biomaterial implant. Significance StatementThe foreign body response to implants leads to chronic inflammation and fibrosis that can be highly variable in the general patient population. Here, we demonstrate that gut dysbiosis via enteric infection promoted systemic inflammation and increased immune cell recruitment to an anatomically distant implant site. These results implicate the gut microbiota as a potential source of variability in the clinical biomaterial response and illustrate that the local tissue environment can be influenced by host factors that modulate systemic interactions.

bioengineering↗

bioRxiv2024

High-Throughput Bioprinting of Spheroids for Scalable Tissue Fabrication

Tissue biofabrication that replicates an organ-specific architecture and function requires physiologically-relevant cell densities. Bioprinting using spheroids has the potential to create constructs with native cell densities, but its application is limited due to the lack of practical, scalable techniques. This study presents HITS-Bio (High-throughput Integrated Tissue Fabrication System for Bioprinting), a novel multiarray spheroid bioprinting technology enabling scalable tissue fabrication by rapidly positioning a number of spheroids simultaneously using a digitally-controlled nozzle array (DCNA) platform. HITS-Bio achieves an unprecedented speed, an order of magnitude faster compared to existing techniques while maintaining high cell viability (>90%). The platforms ability to pattern multiple spheroids simultaneously enhances fabrication rates proportionally to the size of DCNA used. The utility of HITS-Bio was exemplified in multiple applications, including intraoperative bioprinting with microRNA transfected spheroids for calvarial bone regeneration ([~]30 mm3) in a rat model achieving a near-complete defect closure ([~]91% in 3 weeks and [~]96% in 6 weeks). Additionally, the successful fabrication of scalable cartilage constructs (1 cm3) containing [~]600 chondrogenic spheroids highlights its high-throughput efficiency (under 40 min per construct) and potential for repairing volumetric tissue defects.

bioengineering↗

bioRxiv2023

Nested biofabrication: Matryoshka-inspired Intra-embedded Bioprinting

Engineering functional tissues and organs remains a fundamental pursuit in biofabrication. However, the accurate constitution of complex shapes and internal anatomical features of specific organs, including their intricate blood vessels and nerves, remains a significant challenge. Inspired by the Matryoshka doll, we here introduce a new method called Intra-Embedded Bioprinting (IEB), building upon existing embedded bioprinting methods. We used a xanthan gum-based material, which served a dual role as both a bioprintable ink and a support bath, due to its unique shear-thinning and self-healing properties. We demonstrated IEBs capabilities in organ modelling, creating a miniaturized replica of a pancreas using a photocrosslinkable silicone composite. Further, a head phantom and a Matryoshka doll were 3D printed, exemplifying IEBs capability to manufacture intricate, nested structures. Towards the use case of IEB and employing innovative coupling strategy between extrusion-based and aspiration-assisted bioprinting, we developed a breast tumor model that included a central channel mimicking a blood vessel, with tumor spheroids bioprinted in proximity. Validation using a clinically-available chemotherapeutic drug illustrated its efficacy in reducing the tumor volume via perfusion over time. This method opens a new way of bioprinting enabling the creation of complex-shaped organs with internal anatomical features.

bioengineering↗

bioRxiv2023

A 3D Printed Ventilated Perfused Lung Model Platform to Dissect the Lung's Response to Viral Infection in the Presence of Respiration

In this study, we developed a three-dimensionally (3D) printed lung model that faithfully recapitulates the intricate lung environment. This 3D model incorporated alveolar and vascular components that allow for a comprehensive exploration of lung physiology and responses to infection in vitro. In particular, we investigated the intricate role of ventilation on formation of the alveolar epithelial layer and its response to viral infections. In this regard, we subjected our 3D printed, perfused lung model to a continuous respiratory cycle at the air-liquid interface (ALI) for up to 10 days followed by infection with two viruses: influenza virus (Pr8) and respiratory syncytial virus (RSV), at two different concentrations for 24 or 48 h. The results revealed that ventilation induced increased tight-junction formation with better epithelial barrier function over time, facilitated higher expression of alveolar epithelial specific genes, enabled higher level of infection with an increased progression of viral spread and replication over time, and modulated the production of pro-inflammatory cytokines and chemokines. Our findings represent a critical step forward in advancing our understanding of lung-specific viral responses and respiratory infections in response to ventilation, which sheds light on vital aspects of pulmonary physiology and pathobiology.

bioengineering↗

bioRxiv2021

Aspiration-assisted freeform bioprinting of mesenchymal stem cell spheroids within alginate microgels

Aspiration-assisted freeform bioprinting (AAfB) has emerged as a promising technique for precise placement of tissue spheroids in three-dimensional (3D) space for fabrication of tissues. For successful embedded bioprinting using AAfB, an ideal support bath should possess shear-thinning behavior and yield-stress to obtain tightly fused assembly of bioprinted spheroids. Several studies have demonstrated support baths for embedded bioprinting, but these materials pose major challenges due to their low biocompatibility, opaqueness, complex and prolonged preparation procedures, and limited spheroid fusion efficacy. In this study, to circumvent the aforementioned limitations, we present the feasibility of AAfB of human mesenchymal stem cell (hMSC) spheroids in alginate microgels as a support bath. First, alginate microgels were prepared with different particle sizes modulated by blending time and concentration, followed by determination of the optimal bioprinting conditions by the assessment of rheological properties, bioprintability, and spheroid fusion efficiency. The bioprinted and consequently self-assembled tissue structures made of hMSC spheroids were osteogenically induced for bone tissue formation. Alongside, we investigated the effects of peripheral blood monocyte-derived osteoclast incorporation into the hMSC spheroids in heterotypic bone tissue formation. We demonstrated that alginate microgels enabled unprecedented positional accuracy (~5%), transparency for visualization, and improved fusion efficiency (~97%) of bioprinted hMSC spheroids for bone fabrication. This study demonstrates the feasibility of using alginate microgels as a support bath for many different applications including but not limited to freeform bioprinting of spheroids, cell-laden hydrogels, and fugitive inks to form viable tissue constructs.

bioengineering↗

bioRxiv2020

DeepGANnel: Synthesis of fully annotated single molecule patch-clamp data using generative adversarial networks

Development of automated analysis tools for "single ion channel" recording is hampered by the lack of available training data. For machine learning based tools, very large training sets are necessary with sample-by-sample point labelled data (e.g., 1 sample point every 100microsecond). In an experimental context, such data are labelled with human supervision, and whilst this is feasible for simple experimental analysis, it is infeasible to generate the enormous datasets that would be necessary for a big data approach using hand crafting. In this work we aimed to develop methods to generate simulated ion channel data that is free from assumptions and prior knowledge of noise and underlying hidden Markov models. We successfully leverage generative adversarial networks (GANs) to build an end-to-end pipeline for generating an unlimited amount of labelled training data from a small annotated ion channel "seed" record, and this needs no prior knowledge of theoretical dynamical ion channel properties. Our method utilises 2D CNNs to maintain the synchronised temporal relationship between the raw and idealised record. We demonstrate the applicability of the method with 5 different data sources and show authenticity with t-SNE and UMAP projection comparisons between real and synthetic data. The model would be easily extendable to other time series data requiring parallel labelling, such as labelled ECG signals or raw nanopore sequencing data.

physiology↗

bioRxiv2020

Aspiration-assisted Freeform Bioprinting of Tissue Spheroids in a Yield-stress Gel

Bioprinting of cellular aggregates, such as tissue spheroids or organoids, in complex three-dimensional (3D) arrangements has been a major obstacle for scaffold-free fabrication of tissues and organs. In this research, we unveiled a new approach to the bioprinting of tissue spheroids in a yield stress granular gel, which exhibited unprecedented capabilities in freeform positioning of spheroids in 3D. Due to its Herschel-Bulkley and self-healing properties as well as its biological inertness, the granular gel supported both the positioning and self-assembly of tissue spheroids. We studied the underlying physical mechanism of the approach to elucidate the interactions between the aspirated spheroids and the gels yield-stress during the transfer of spheroids from cell media to the gel. We demonstrate the application of the proposed approach in the realization of various freeform shapes and self-assembly of human mesenchymal stem cell spheroids for the construction of cartilage and bone tissues.

bioengineering↗

bioRxiv2019

Deep-Channel: A Deep Convolution and Recurrent Neural Network for Detection of Single Molecule Events

Single-molecule research such as patch-clamp recording delivers unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysis is event detection, so called "idealisation", where noisy raw data are turned into discrete records of protein movement. To date there have been practical limitations in patch-clamp data idealisation; high quality idealisation is typically laborious and becomes infeasible and subjective with complex biological data containing many distinct native single ion channel proteins gating simultaneously. Here we show a deep learning model based on convolutional neural networks and long short-term memory architecture can automatically idealise complex single molecule activity more accurately and faster than traditional methods. There are no parameters to set; baseline, channel amplitude or numbers of channels for example. We believe this approach could revolutionise the unsupervised automatic detection of single-molecule transition events in the future.

physiology↗