Biology subjects

Cakir, B.

Publications and source records attributed to Cakir, B..

16 recordsLinked to original sources

bioRxiv2026

The Human Gut Cell Atlas v1.0: A Unified, Community-BuiltReference of Cellular Diversity Across the Gut

Single-cell RNA-sequencing (scRNA-seq) studies have transformed our understanding of cellular diversity in the human intestine, but differences in anatomical sampling, experimental processing and cell-type nomenclature limit comparison across datasets. Here, we present the Human Gut Cell Atlas (HGCA) V1, a community-curated reference of 944,390 healthy and disease-adjacent intestinal cells from 502 samples, 265 donors and 24 landmark studies, linked to detailed anatomical, clinical, and technical metadata. As this metadata is of critical importance to human biology, we developed MetaManager, an open source data management framework for standardized metadata collection and tracking. A five-level consensus taxonomy resolves 94 homeostatic cell identities and enables transferrable, high-resolution annotation of new gut datasets. By assembling cell identity, sampling metadata, and independent spatial validation, intestinal segment and radial tissue depth were revealed to systematically shape cellular composition and transcriptional state, enabling inference of the presence of sampling-dependent tissue niches, including lymphoid follicles. Reference mapping accurately and rapidly recovered cohort-level Crohn's disease and treatment signatures without de novo annotation, while mapping human intestinal organoids quantified cell-type-specific identity, regional specification, maturation, and transcriptional fidelity to native tissue. The HGCA V1 provides a standardized cellular, anatomical coordinate, and metadata system for reproducible, high-quality analysis of intestinal biology across healthy tissue, disease-associated remodelling, and experimental models, providing a continuously evolving community reference for cumulative discovery in human intestinal biology.

systems biology↗

bioRxiv2026

Multi-scale modeling of human tissues from spatial transcriptomics with TERRA

Spatial transcriptomics maps gene expression at cellular resolution, revealing how cells organize into multicellular niches. Yet computational analyses remain dataset-specific, without a transferable representation of tissue organization that generalizes across datasets, tasks and tissues or predicts how tissues behave under perturbation. We present TERRA, a foundation model pretrained on 112 million human cells profiled by spatial transcriptomics. From a single pretrained backbone, TERRA yields embeddings at the scale of cells, the genes they express and the neighborhoods in which they reside, and supports spatial in silico perturbation, all applied zero-shot to unseen tissues. At the cell level, in newly generated spatial data for developing pancreas, TERRA identified an islet-associated capillary state which we posit represents a developmental precursor of the mature islet microvasculature. At the gene level, in untreated kidney sections, in silico knockout of immune-checkpoint targets predicted a gene program of immune-checkpoint-blockade-associated nephrotoxicity, which we validated in treatment-exposed tissue and recovered in blood. At the neighborhood level, TERRA mapped macrophages across tissues to identify recurring cross-organ niches, which we term archetypes, including a tumor-boundary niche associated with poor prognosis in kidney cancer. Together, TERRA captures the spatial and multicellular logic of human tissue and predicts, in silico, its response to perturbation, providing a multi-scale framework for tissue biology, therapeutic development and clinical application.

genomics↗

bioRxiv2026

Plaque-associated oligodendrocyte proteostatic failure underlies myelin loss in Alzheimers disease

Alzheimers disease (AD) features amyloid-{beta} plaques and tau pathology, yet the mechanism underlying early and clinically significant myelin loss remains unresolved. Here, we report human iPSC-derived forebrain organoids with doxycycline-inducible expression of SOX10, OLIG2, and NKX6-2 (SON), which generate robust, mature oligodendrocytes and compact myelin in vitro and in vivo. Introducing amyloid precursor protein (APP) pathogenic mutations produces extracellular amyloid-{beta} plaques and phosphorylated tau, accompanied by reduced myelin basic protein (MBP) expression and disrupted myelin ultrastructure. Single-cell and spatial transcriptomics combined with amyloid plaque imaging reveal that oligodendrocytes in plaque-dense regions show pathological changes in calcium signaling, immune activation, lipid remodeling, and protein catabolic pathways. Notably, MBP protein is reduced despite elevated myelin-related transcription, suggesting plaque-induced degradation of myelin proteins. Consistent with this, proteasomal inhibition restores MBP protein levels and improves compact myelin ultrastructure in AD organoids. In human AD brain tissue, protein catabolic pathways are similarly upregulated with increasing plaque density. Together, these findings identify plaque-associated oligodendrocyte proteostatic failure as a candidate mechanism of myelin loss and a potential therapeutic pathway in AD.

neuroscience↗

bioRxiv2026

Mitochondrial Transplantation in the Eye: A Review and Evaluation of Surgical Approaches

PurposeMitochondrial dysfunction contributes to major blinding diseases, including age-related macular degeneration and glaucoma. Although mitochondrial transplantation has shown therapeutic potential in multiple organ systems, translation to the eye remains limited, partly due to uncertainty regarding optimal delivery. We summarize the biologic rationale and preclinical evidence supporting ocular mitochondrial transplantation and present feasibility data evaluating clinically relevant delivery routes. MethodsWe conducted a focused narrative review of ocular mitochondrial transplantation. For feasibility experiments, mitochondria with an endogenous fluorescent dye were isolated from liver donor mice. Postnatal day 7 pups received subretinal injections, and adult CD1 mice received intravitreal injections, including optic nerve head directed delivery. Eyes were analyzed using fluorescence microscopy and immunohistochemistry. Mitochondrial uptake was assessed in cultured retinal pigmental epithelial (RPE) cells using co-incubation assays. Suprachoroidal delivery feasibility was evaluated in cadaveric human near-real surgical specimens using a novel dedicated suprachoroidal injector. ResultsThe literature on ocular mitochondrial transplantation remains limited and consists primarily of small preclinical studies using intravitreal delivery and imaging-based detection. In our experiments, intravitreal delivery produced donor signals predominantly within inner retinal layers, with enrichment along retinal nerve fiber bundles when directed toward the optic nerve head. Cultured RPE cells demonstrated dose-dependent uptake of exogenous mitochondria. Subretinal delivery localized donors signal to the RPE and adjacent outer retina. Suprachoroidal injections demonstrated procedural feasibility with reliable access to the suprachoroidal space and visible injectate distribution. ConclusionsOcular mitochondrial transplantation is in an early stage of investigation. Our feasibility data indicate that established posterior-segment delivery routes expose distinct retinal compartments and that route selection strongly influences anatomic distribution. Further studies are needed to verify intracellular uptake, define dosing and durability, and evaluate safety in disease-relevant models.

cell biology↗

bioRxiv2025

High-density extracellular recordings from the interior of intact brain organoids enable automated high-throughput functional assay

Bridging the gap between preclinical screening and clinical outcomes remains a major challenge in drug development for neurological disorders. Brain organoids, derived from human induced pluripotent stem cells, offer a scalable and physiologically relevant platform to model human neural circuits. We develop a fully automated system to record neural activity from the interior of intact human cortical organoids using a high-density microfabricated probe. The robotic system completes insertion within minutes while preserving organoid integrity and enables immediate recording of spontaneous spikes. We extract physiologically grounded and deterministic spike features, and train a long short-term memory classifier to distinguish between organoids derived from healthy individuals and those harboring familial Alzheimers disease (AD) mutations in the amyloid precursor protein. Despite intra-class variability, the classifier differentiates between organoid classes with 100% accuracy. The model classifies AD organoids treated with a drug candidate that reduces amyloid-{beta} levels as retaining an AD-like electrophysiological phenotype, demonstrating that functional readout can contradict molecular markers. The findings establish a high-throughput functional framework that may complement and extend existing drug screening assays.

neuroscience↗

bioRxiv2025

An atlas of TF driven gene programs across human cells

Combinations of transcription factors (TFs) regulate gene expression and determine cell fate. Much effort has been devoted to understanding TF activity in different tissues and how tissue-specificity is achieved. However, ultimately gene regulation occurs at the single cell level and the recent explosion in the availability of single cell gene expression data now makes it possible to understand TF activity at this granular level of resolution. Here, we leverage a large collection of Human Cell Atlas (HCA) single cell data to explore TF activity by examining cell-type and tissue-specific sets of target genes, or regulons. We compile a regulon atlas, CellRegulon, and map the activity of TFs in an extensive set of healthy adult and foetal tissues spanning hundreds of cell types. Using CellRegulon, we describe dynamic patterns of co-regulation, associate TF-modules with different cellular functions and characterise the distribution of active TFs and TF families across cell types. We show that CellRegulon can link disease gene expression signatures to cell types and TFs relevant to the disease. Finally, using a newly generated multiome dataset of the adult lung, we show how CellRegulon can be extended into an enhancer-gene regulatory network (eGRN) to improve cell-type associations with genetic risk loci for diseases, such as childhood onset asthma, COPD and IPF, and to identify high risk gene modules. Our database for easy download and interactive exploration allows researchers to understand key gene modules activated at cell type transitions and will therefore be valuable for tasks such as cell type engineering (https://www.cellregulondb.org).

genetics↗

bioRxiv2024

inVAE: Conditionally invariant representation learning for generating multivariate single-cell reference maps

Single-cell data is driving new insights into the spatiotemporal dynamics of cells and individual disease susceptibility. However, accurately identifying cell states across diverse cohorts remains challenging, as both biological variation and technical biases cause distributional shifts in the data. Separating these effects is crucial for capturing cellular heterogeneity and ensuring interpretability. To address this, we developed inVAE, a conditionally invariant deep generative model based on variational autoencoders. inVAE models the latent space as a combination of invariant variables, encoding true biological signals, and spurious variables, capturing technical biases. By conditioning the prior distribution of cells on biological covariates, such as disease variants, inVAE identifies high-resolution cell states in the invariant representation. Enforcing independence between the two representations disentangles biological signals from noise, enabling a more interpretable and generalizable model with a causal semantic. inVAE outperformed existing methods across four human cellular atlases of the human heart and lung, while uncovering novel cell states. It precisely stratified cell atlas donors based on the genetic impact of pathogenic variants, and excelled in predicting cell types and disease in unseen data, proving its generalizability as a reference model for label transfer. Furthermore, inVAE accurately identified temporal cell states and trajectories from developmental datasets, and captured spatial cell states in a spatially-resolved atlas. In summary, inVAE provides a powerful method for integrating multivariate single-cell transcriptomics data. By leveraging prior knowledge such as metadata, it effectively accounts for biological variation and improves latent space interpretability by disentangling biological and technical sources of variation. These capabilities enable deeper insights into cellular heterogeneity and its role in disease progression.

bioinformatics↗

bioRxiv2024

Spatiotemporal map of the developing human reproductive tract at single-cell resolution

The human reproductive tract plays an essential role in species perpetuation. Its development involves complex processes of sex specification, tissue patterning and morphogenesis, which, if disrupted, can cause lifelong health issues, including infertility. Here, we generated an extensive single-cell and spatial multi-omic atlas of the human reproductive tract during prenatal development, which allowed us to answer questions that smaller-scale, organ-focused experiments could not address before. We identified potential regulators of sexual dimorphism in reproductive organs, pinpointing novel genes involved in urethral canalisation of the penis, with relevance to hypospadias. By combining histological features with gene expression data, we defined the transcription factors and cell signalling events required for the regionalisation of the Mullerian and Wolffian ducts. This led to a refinement of how the HOX code is established in the distinct reproductive organs, including increased expression of thoracic HOX genes in the rostral mesenchyme of the fallopian tube and epididymis. Our study further revealed that the epithelial regionalisation of the fallopian tube and epididymis required for sperm maturation in adulthood is established early in development. In contrast, later events in gestation or postnatally are necessary for the regionalisation of the uterocervical canal epithelium. By mapping sex-specific reproductive tract regionalisation and differentiation at the cellular level, our study offers valuable insights into the causes and potential treatments of reproductive disorders.

developmental biology↗

bioRxiv2024

Single Cell Integration Characterises Metaplasia in Inflammatory Intestinal Diseases

The gastrointestinal (GI) tract consists of connected organs, from the oral cavity to rectum, which function to ensure efficient nutrient uptake and barrier immunity. Diseases of the GI tract affect millions worldwide and as such there are now over 25 published single cell RNA-sequencing (scRNAseq) datasets surveying the GI tract, profiling specific anatomical regions, cell lineages, ages and diseases. To consolidate these efforts, we harmonised and integrated scRNAseq datasets across the whole GI tract from developing and adult human tissues, as well as newly generated data from preterm gut. We uniformly processed 385 samples from 189 healthy controls using a newly developed automated QC approach (scAutoQC). In total, our healthy reference contains [~]1.1 million cells which we annotated to a total of 137 fine-grained cell states. We anchor 13 published and 1 unpublished GI disease datasets covering gastric and colorectal (CRC) cancers, celiac disease, ulcerative colitis (UC) and Crohns disease (CD) to this reference, taking our atlas to a total of 1.6 million cells. We provide our atlas as a valuable resource to the community (available at gutcellatlas.org). Using this resource, we discover epithelial cell metaplasia arising from stem cells across intestinal inflammatory diseases (celiac, UC and CD) and CRC with transcriptional similarity to cells of the gastric and Brunners glands. Whilst previously linked to mucosal healing, we now implicate these cells in inflammation through recruitment of immune cells including T cells and neutrophils, and through direct interactions with T cells. Overall, we discover a shift in paradigm whereby changes in stem cells during inflammation lead to altered mucosal tissue architecture, which in turn contributes to ongoing inflammation. These findings highlight that in addition to barrier function, epithelial cells actively contribute to progression of inflammation which may be a function applicable to other tissues and diseases.

genomics↗

bioRxiv2024

A multiomic atlas of human early skeletal development

Bone and joint formation in the developing skeleton rely on co-ordinated differentiation of progenitors in the nascent developing limbs and joints. The cell states, epigenetic processes and key regulatory factors underlying their lineage commitment to osteogenic and other mesenchymal populations during ossification and joint formation remain poorly understood and are largely unexplored in human studies. Here, we apply paired single-nuclei transcriptional and epigenetic profiling of 336,000 droplets, in addition to spatial transcriptomics, to construct a comprehensive atlas of human bone, cartilage and joint development in the shoulder, hip, knee and cranium from 5 to 11 post-conception weeks. Spatial mapping of cell clusters to our highly multiplexed in situ sequencing (ISS) data using our newly developed tool ISS-Patcher revealed new cellular mechanisms of zonation during bone and joint formation. Combined modelling of chromatin accessibility and RNA expression allowed the identification of the transcriptional and epigenetic regulatory landscapes that drive differentiation of mesenchymal lineages including osteogenic and chondrogenic lineages, and novel chondrocyte cell states. In particular, we define regionally distinct limb and cranial osteoprogenitor populations and trajectories across the fetal skeleton and characterise differential regulatory networks that govern intramembranous and endochondral ossification. We also introduce SNP2Cell, a tool to link cell-type specific regulatory networks to numerous polygenic traits such as osteoarthritis. We also conduct in silico perturbations of genes that cause monogenic craniosynostosis and implicate potential pathogenic cell states and disease mechanisms involved. This work forms a detailed and dynamic regulatory atlas of human fetal skeletal maturation and advances our fundamental understanding of cell fate determination in human skeletal development.

developmental biology↗

bioRxiv2023

A rapid method for generating transplantable and biologically responsive colonic tissue from human induced pluripotent stem cells.

BackgroundThe colonic mucosa consists of cell populations derived from multiple lineages. Induced pluripotent stem cells (iPSCs) are capable of generating large numbers of differentiated cells from any lineage. Thus, iPSCs are highly versatile for derivation of intestinal cells for generation of colonic mucosal tissue for clinical and biological applications. ObjectiveWe set out to create a human iPSC (hiPSC) multi-lineage co-differentiation platform capable of generating colonic mucosal tissue in vitro. DesignWe used hiPSCs and designed a differentiation protocol consisting of small molecules and recombinant growth factors to generate multiple cell lineages. Cells were seeded onto collagen hydrogels (forming colonic patches - CoPs) and modulated with multiple growth factors important in intestinal biology. CoPs were transplanted into immunosuppressed mice. Generated cells and tissues were profiled with transcriptomic analysis. ResultshiPSC co-differentiation led to multiple intestinal epithelial, mesenchymal and endothelial cell populations. Seeded onto collagen scaffolds these cells created CoPs, which were transplanted into mouse subcutis. Engrafted CoPs developed into normal-looking colonic mucosa containing epithelial crypts (with enterocytes, goblet cells and neuroendocrine cells), multiple lamina propria-resident stromal populations and muscularis mucosae smooth muscle. They anastomosed to murine vasculature and maintained in-vitro for several weeks. We demonstrated that CoPs respond to known signalling pathways important in colonic mucosal biology and fibrogenesis, showing potential to provide a complex model of colonic pathobiology. ConclusionThis platform could offer an accurate model of intestinal pathobiology, supply cells for regenerative cell therapies to treat intestinal disease, and provide therapeutic autologous grafts to repair damaged colon.

cell biology↗

bioRxiv2023

CZ CELLxGENE Discover: A single-cell data platform for scalable exploration, analysis and modeling of aggregated data

Hundreds of millions of single cells have been analyzed to date using high throughput transcriptomic methods, thanks to technological advances driving the increasingly rapid generation of single-cell data. This provides an exciting opportunity for unlocking new insights into health and disease, made possible by meta-analysis that span diverse datasets building on recent advances in large language models and other machine learning approaches. Despite the promise of these and emerging analytical tools for analyzing large amounts of data, a major challenge remains the sheer number of datasets and inconsistent format, data models and accessibility. Many datasets are available via unique portals platforms that often lack interoperability. Here, we present CZ CellxGene Discover (cellxgene.cziscience.com), a data platform that provides curated and interoperable data. This single-cell data resource, available via a free-to-use online data portal, hosts a growing corpus of community contributed data that spans more than 50 million unique cells. Curated, standardized, and associated with consistent cell-level metadata, this collection of interoperable single-cell transcriptomic data is the largest of its kind. A suite of tools and features enables accessibility and reusability of the data via both computational and visual interfaces to allow researchers to rapidly explore individual datasets and perform cross-corpus analysis. This functionality is enabling meta-analyses of tens of millions of cells across studies and tissues and providing global views of human cells at the resolution of single cells.

cell biology↗

bioRxiv2023

Multi-scale spatial mapping of cell populations across anatomical sites in healthy human skin and basal cell carcinoma

Our understanding of how human skin cells differ according to anatomical site and tumour formation is limited. To address this we have created a multi-scale spatial atlas of healthy skin and basal cell carcinoma (BCC), incorporating in vivo optical coherence tomography, single cell RNA sequencing, spatial global transcriptional profiling and in situ sequencing. Computational spatial deconvolution and projection revealed the localisation of distinct cell populations to specific tissue contexts. Although cell populations were conserved between healthy anatomical sites and in BCC, mesenchymal cell populations including fibroblasts and pericytes retained signatures of developmental origin. Spatial profiling and in silico lineage tracing support a hair follicle origin for BCC and demonstrate that cancer-associated fibroblasts are an expansion of a POSTN+ subpopulation associated with hair follicles in healthy skin. RGS5+ pericytes are also expanded in BCC suggesting a role in vascular remodelling. We propose that the identity of mesenchymal cell populations is regulated by signals emanating from adjacent structures and that these signals are repurposed to promote the expansion of skin cancer stroma. The resource we have created is publicly available in an interactive format for the research community. Significance statementSingle cells RNA sequencing has revolutionised cell biology, enabling high resolution analysis of cell types and states within human tissues. Here, we report a comprehensive spatial atlas of adult human skin across different anatomical sites and basal cell carcinoma (BCC) - the most common form of skin cancer - encompassing in vivo optical coherence tomography, single cell RNA sequencing, global spatial transcriptomic profiling and in situ sequencing. In combination these modalities have allowed us to assemble a comprehensive nuclear-resolution atlas of cellular identity in health and disease.

cell biology↗

bioRxiv2022

Inhibition of Fas Receptor Endocytosis Sensitizes Cancer Cells to Fas-induced Apoptosis

The transmembrane death receptor Fas transduces apoptotic signals upon binding its ligand, FasL. Although Fas is highly expressed in cancer cells, insufficient cell surface Fas expression desensitizes cancer cells to Fas-induced apoptosis. Here, we show that the increase in Fas microaggregate formation on the plasma membrane in response to the inhibition of endocytosis sensitizes cancer cells to Fas-induced apoptosis. We used a clinically accessible Rho-kinase inhibitor, fasudil, that reduces endocytosis dynamics by increasing plasma membrane tension. In combination with exogenous soluble FasL (sFasL), fasudil promoted cancer cell apoptosis, but this collaborative effect was substantially weaker in nonmalignant cells. The combination of sFasL and fasudil prevented glioblastoma cell growth in embryonic stem cell-derived brain organoids and induced tumor regression in a xenograft mouse model. Our results demonstrate that sFasL has strong potential for apoptosis-directed cancer therapy when Fas microaggregate formation is augmented by mechano-inhibition of endocytosis.

cancer biology↗

bioRxiv2022

Dyslexia associated gene, KIAA0319, regulates cell cycle during human neuroepithelium development

Reading Disability (RD), also known as dyslexia, is defined as difficulty processing written language in individuals with normal intellectual capacity and educational opportunity. The prevalence of RD is between 5% and 17%, and the heritability ranges from 44% to 75%. Genetic linkage analysis and genome-wide association studies (GWAS) have identified several genes and regulatory elements linked to RD and reading ability. However, their functions and molecular mechanisms are not well understood. Prominent among these is KIAA0319, encoded in the DYX2 locus of human chromosome 6p22. Association of KIAA0319 has been independently replicated in multiple independent studies and languages. Rodent models suggest that KIAA0319 is involved in neuronal migration, but its precise function is unknown. This studies aim to determine the mechanisms by which KIAA0319 affects reading and language performance. We hypothesize that KIAA0319 plays a critical role in neuronal development. RT-qPCR and quantitative immunofluorescence in the cortical neurons differentiated from H7 hESC show regulatory effects on proliferation and differentiation of neuronal progenitor cells. Knockdown of KIAA0319 expression promotes early exit from the neuroepithelial cell stage and drives cells into cell cycle arrested neuronal progenitor cell stage. This suggests that KIAA0319 act by regulating neurogenesis in the reading related centers of the brain by targeting the cell cycle of proliferative cells. This demonstrates how subtle changes in expression could affect an isolated trait such as reading without global brain effects.

developmental biology↗

bioRxiv2020

Comparison of visualisation tools for single-cell RNAseq data

In the last decade, single cell RNAseq (scRNAseq) datasets have grown from a single cell to millions of cells. Due to its high dimensionality, the scRNAseq data contains a lot of valuable information, however, it is not always feasible to visualise and share it in a scientific report or an article publication format. Recently, a lot of interactive analysis and visualisation tools have been developed to address this issue and facilitate knowledge transfer in the scientific community. In this study, we review and compare several of the currently available analysis and visualisation tools and benchmark those that allow to visualize the scRNAseq data on the web and share it with others. To address the problem of format compatibility for most visualisation tools, we have also developed a user-friendly R package, sceasy, which allows users to convert their own scRNAseq datasets into a specific data format for visualisation.

bioinformatics↗