Biology subjects

Celik, C.

Publications and source records attributed to Celik, C..

9 recordsLinked to original sources

bioRxiv2025

Integrative Spatial Modelling of Cellular Plasticity using Graph Neural Networks and Geostatistics

Cellular plasticity - the ability of cells to change phenotype in response to intrinsic and environmental cues - is central to development, regeneration, and disease, but remains difficult to quantify due to its dynamic, context-dependent nature. Here we introduce a framework that unites AI and geostatistics - graph neural networks and spatial regression models - to both predict and explain cell state variation in spatial transcriptomics data. We formalize state predictability as a quantitative proxy for plasticity, where stable states are predictable and plastic states are not. Applied to epithelial-mesenchymal plasticity (EMP) in breast cancer, the framework shows that mesenchymal states are stabilized by recurrent copy number alterations and microenvironmental cues, whereas hybrid states remain unpredictable and plastic. It also uncovers a long-range influence of myofibroblasts on EMP, demonstrating that stromal remodeling can propagate plasticity across tissue regions. Our framework yields interpretable, scale-aware insights into intrinsic and extrinsic drivers of state transitions, providing a broadly applicable strategy for modelling dynamic cell states in spatial biology.

bioinformatics↗

bioRxiv2025

Enterococcus faecalis redox metabolism activates the unfolded protein response to impair wound healing

Enterococcus faecalis is an opportunistic pathogen that thrives in biofilm-associated infections and delays wound healing, yet how it impairs host tissue responses is unclear. Here, we identified extracellular electron transport (EET) as a previously unrecognized source of ROS in E. faecalis and show that this activity directly triggers the unfolded protein response (UPR) in epithelial cells and delays epithelial cell migration. ROS detoxification with catalase suppressed E. faecalis-induced UPR and rescued epithelial cell migration, while exogenous H2O2 was sufficient to restore UPR activation in EET-deficient strains. Importantly, UPR disruption by pharmacological inhibition also impaired cell migration, highlighting a critical role for UPR homeostasis in wound repair. Our findings establish EET as a novel virulence mechanism that links bacterial redox metabolism to host cell stress and impaired repair, offering new avenues for therapeutic intervention in chronic infections.

microbiology↗

bioRxiv2025

EnrichMap: Spatially informed enrichment analysis for functional interpretation of spatial transcriptomics

Advances in spatial transcriptomics (ST) allow high-resolution mapping of gene expression within intact tissues, revealing spatially regulated biology. However, accurately quantifying gene set activity in spatial contexts remains inadequate. We present EnrichMap, a Python package designed to compute gene set enrichment scores in ST data by integrating batch correction, smoothing and spatial confounder adjustment. EnrichMap generates enrichment scores for signatures or pathways, with an optional framework for incorporating gene weights. To assess performance, we benchmark EnrichMap against established scoring techniques using spatial autocorrelation metrics such as Morans I. Our results show that EnrichMap improves spatial coherence, producing scores that capture both local and global spatial patterns, while conventional approaches tend to exhibit higher heterogeneity or diminished spatial structure. EnrichMap is demonstrated to be generalisable across a variety of ST platforms, including Visium, Xenium, MERFISH and imaging mass cytometry, maintaining consistent performance despite differences in spatial resolution and detection chemistry. Our method offers a platform-agnostic, spatially and biologically meaningful representation of gene set activity across complex tissue landscapes.

bioinformatics↗

bioRxiv2025

Enterococcus faecalis-derived lactic acid facilitates persistent and polymicrobial wound infections by suppressing macrophage activation

Macrophage activation is essential for innate immunity, and its suppression enables pathogen persistence. We show that Enterococcus faecalis suppresses macrophage activation through lactic acid-mediated extracellular acidification. Mutants lacking lactate dehydrogenase (ldh), and thus unable to acidify the environment, fail to inhibit NF-{kappa}B. E. faecalis-derived lactic acid acts via MCT-1 and GPR81 through two distinct but complementary mechanisms that culminate in the reduction of NF-{kappa}B activity. Lactic acid acts through MCT-1 to inhibit ERK and STAT3 phosphorylation, leading to reduced STAT3 binding to the Myd88 promoter, and reduced MyD88 protein levels. Lactic acid signaling to GPR81 mediates the phosphorylation of the transcriptional factor YAP, ultimately attenuating NF-{kappa}B signaling. In a murine wound infection model, this lactic acid-driven immunosuppressive niche enables prolonged E. faecalis persistence and enhances the fitness of co-infecting bacteria such as Escherichia coli. These findings reveal how bacterial lactic acid subverts innate immunity to support chronic and polymicrobial infections. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/635924v2_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@2e1565org.highwire.dtl.DTLVardef@17eaf85org.highwire.dtl.DTLVardef@356139org.highwire.dtl.DTLVardef@821581_HPS_FORMAT_FIGEXP M_FIG C_FIG Highlights- E. faecalis lactate dehydrogenase mutants fail to acidify the environment and cannot suppress NF-{kappa}B signaling. - Lactic acid is necessary and sufficient to drive NF-{kappa}B suppression in macrophages. - Lactic acid NF-{kappa}B suppression is relayed through two complementary routes: MCT- 1 transport and the lactate sensor GPR81. - MCT-1-dependent signaling blunts ERK/STAT3 phosphorylation, lowering MyD88 levels; whereas GPR81 drives YAP phosphorylation, reducing NF-{kappa}B activation. - E. faecalis-derived lactic acid drives immunosuppression, potentiates persistence, and promotes multi-species wound infection in vivo.

microbiology↗

bioRxiv2025

Balancing tumour proliferation and sustained cell cycle arrest through proteostasis remodelling drives immune niche compartmentalisation in breast cancer

Uncontrolled proliferation is a hallmark of cancer, yet tumour cells can enter G0 arrest by halting the cell cycle reversibly (quiescence) or irreversibly (senescence) to survive under stress and in hostile tumour microenvironments (TME). G0 arrested cells contribute to drug tolerance, metastasis and recurrence, but their identification remains challenging due to their rarity and elusive regulatory pathways. Here, we quantify G0 arrest and proliferation decisions in single-cell and spatially profiled breast primary tumours to unveil adaptive responses driving immune compartmentalisation. We identify a genomically-constrained and prolonged G0 arrest state resembling that of dormant precursors of cancer progression. This state featured adaptive transcriptional reprogramming, including unfolded protein response stress, reduced mitochondrial translation and epithelial-mesenchymal plasticity enabled by semaphorin signalling. Spatial transcriptomics revealed G0 arrest pockets encapsulated by APOE+ lipid-associated macrophages, myofibroblastic CAFs and immature perivascular cells, suggestive of an immunosuppressive niche contrasting with cytotoxic environments in proliferative hotspots and displaying distinct drug sensitivities. To facilitate future research, we provide a foundation model capturing G0 arrest and proliferation with 94% accuracy in single cell data, available at https://github.com/secrierlab/G0-LM. Our findings provide new insights into the spatial organisation of cell cycle arrest in breast cancer, highlighting the role of G0 states in tumour heterogeneity and adaptation.

cancer biology↗

bioRxiv2024

Genetic regulation of injury induced heterotopic ossification in adult zebrafish

Heterotopic ossification is the inappropriate formation of bone in soft tissues of the body. It can manifest spontaneously in rare genetic conditions or as a response to injury, known as acquired heterotopic ossification. There are several experimental models for studying heterotopic ossification from different sources of damage. However, their tenuous mechanistic relevance to the human condition, invasive and laborious nature and/or lack of amenability to chemical and genetic screens, limit their utility. To address these limitations, we developed a simple zebrafish injury model that manifests heterotopic ossification in response to micro-fractures in combination with muscle injury. These findings indicate that clinically-emulated injuries in zebrafish can lead to osteo-induction and proliferation as observed in heterotopic ossification in myositis ossificans traumatica. Exploiting this model, we analysed the penetrance and expressivity of heterotopic ossification and defined the transcriptional response to trauma, identifying differentially regulated genes. Taking advantage of defined mutants in several of these candidates, we explored their impact on heterotopic bone formation. Our findings revealed that an increase in potassium channel Kcnk5b activity potentiates injury response. In contrast, we demonstrate that inflammatory responses are essential for the ectopic bone growth, as mutations in Interleukin 11 receptor paralogue (Il11ra) exhibit a drastically reduced ossification response. Based on these findings, we postulate that enhanced ionic signaling, specifically through Kcnk5b, regulates the intensity of the skeletogenic injury response, which, in part, requires immune response regulated by Il11ra.

genetics↗

bioRxiv2023

A single-cell atlas of E. faecalis wound infection reveals novel bacterial-host immunomodulatory mechanisms

Wound infections are highly prevalent, and can lead to delayed or failed healing, causing significant morbidity and adverse economic impacts. These infections occur in various contexts, including diabetic foot ulcers, burns, and surgical sites. Enterococcus faecalis is often found in persistent non-healing wounds, but its contribution to chronic wounds remains understudied. To address this, we employed single-cell RNA sequencing (scRNA-seq) on infected wounds in comparison to uninfected wounds in a mouse model. Examining over 23,000 cells, we created a comprehensive single-cell atlas that captures the cellular and transcriptomic landscape of these wounds. Our analysis revealed unique transcriptional and metabolic alterations in infected wounds, elucidating the distinct molecular changes associated with bacterial infection compared to the normal wound healing process. We identified dysregulated keratinocyte and fibroblast transcriptomes in response to infection, jointly contributing to an anti-inflammatory environment. Notably, E. faecalis infection prompted a premature, incomplete epithelial-to-mesenchymal transition in keratinocytes. Additionally, E. faecalis infection modulated M2-like macrophage polarization by inhibiting pro-inflammatory resolution in vitro, in vivo, and in our scRNA-seq atlas. Furthermore, we discovered macrophage crosstalk with neutrophils, which regulates chemokine signaling pathways, while promoting anti-inflammatory interactions with endothelial cells. Overall, our findings offer new insights into the immunosuppressive role of E. faecalis in wound infections.

microbiology↗

bioRxiv2021

Protein noise and distribution in a two-stage gene-expression model extended by an mRNA inactivation loop

Chemical reaction networks involving molecular species at low copy numbers lead to stochasticity in protein levels in gene expression at the single-cell level. Mathematical modelling of this stochastic phenomenon enables us to elucidate the underlying molecular mechanisms quantitatively. Here we present a two-stage stochastic gene expression model that extends the standard model by an mRNA inactivation loop. The extended model exhibits smaller protein noise than the original two-stage model. Interestingly, the fractional reduction of noise is a non-monotonous function of protein stability, and can be substantial especially if the inactivated mRNA is stable. We complement the noise study by an extensive mathematical analysis of the joint steady-state distribution of active and inactive mRNA and protein species. We determine its generating function and derive a recursive formula for the protein distribution. The results of the analytical formula are cross-validated by kinetic Monte-Carlo simulation.

systems biology↗

bioRxiv2020

Stationary distributions and metastable behaviour for self-regulating proteins with general lifetime distributions

Regulatory molecules such as transcription factors are often present at relatively small copy numbers in living cells. The copy number of a particular molecule fluctuates in time due to the random occurrence of production and degradation reactions. Here we consider a stochastic model for a self-regulating transcription factor whose lifespan (or time till degradation) follows a general distribution modelled as per a multidimensional phase-type process. We show that at steady state the protein copy-number distribution is the same as in a one-dimensional model with exponentially distributed lifetimes. This invariance result holds only if molecules are produced one at a time: we provide explicit counterexamples in the bursty production regime. Additionally, we consider the case of a bistable genetic switch constituted by a positively autoregulating transcription factor. The switch alternately resides in states of up- and downregulation and generates bimodal protein distributions. In the context of our invariance result, we investigate how the choice of lifetime distribution affects the rates of metastable transitions between the two modes of the distribution. The phase-type model, being non-linear and multi-dimensional whilst possessing an explicit stationary distribution, provides a valuable test example for exploring dynamics in complex biological systems.

systems biology↗