Biology subjects

Bilgic, M.

Publications and source records attributed to Bilgic, M..

6 recordsLinked to original sources

bioRxiv2025

Age-associated microglia populations identified from several single cell transcriptome data

Microglial senescence contributes to inflammation and various neurodegenerative diseases. Recent single-cell transcriptome data have revealed age-associated microglial substates (AAMs) and their potential roles in the development of neurodegenerative diseases. However, the characteristics identified in each study are not necessarily consistent. Here, we perform an integrative analysis of seven previously reported single-cell RNA-seq and four single-nucleus RNA-seq datasets of microglia from young and aged mouse brains. We identify four common AAMs across all datasets and two dataset-specific AAMs. Each AAM exhibits distinct transcriptomic patterns, including alterations in ribosomal genes, Apoe, cytokine genes, interferon-responsive genes, and phagocytosis-related genes. Time-series and pseudotime analyses indicate that the production of AAMs is initiated by the upregulation of ribosomal genes. Predictions based on single-cell transcriptomic data of age-associated manipulations reveal an increase in specific AAMs in a stimulation-type-dependent manner. We also identify similar AAMs in human brains. Altogether, our large-scale integrative analysis highlights promising age-associated microglial populations, which may serve as novel therapeutic targets for age-related neurodegenerative diseases.

neuroscience↗

bioRxiv2025

Non-uniform temporal scaling of neurogenesis for species-specific dosing of cortical excitatory subtypes

Mammals share a laminar cerebral cortex, with excitatory neuron subtypes organized in distinct layers. Although this framework is conserved, subtype balance varies markedly between species due to unknown mechanisms. This study shows that species-specific neuronal composition arises from non-uniform scaling of the temporal dynamics of neurogenesis. Comparative histology of eight mammalian species revealed a significant, rat-specific expansion of the cortical deeper layer (DL). This species difference results from a specific extension of the early neurogenetic phase for DL neuron production before transitioning to the upper layer (UL) in rats, as confirmed by birthdating and single-cell transcriptomics. The duration of DL neuron production is regulated by a genetic program controlling progenitor aging, including canonical Wnt signaling. Comparative single-cell transcriptomics revealed that cortical progenitors in rats exhibit significantly elevated Wnt ligand expression. Thus, while sequential cortical neurogenesis is conserved, its progression is non-uniformly scaled in each species. Such precise heterochronic fine-tuning allows evolutionary refinement of cellular configuration without drastic remodeling of the conserved corticogenesis program. TeaserDifferential temporal progression of neural progenitor program contributes to species-specific cellular composition of mammalian cerebral cortex

developmental biology↗

bioRxiv2024

Age-associated transcriptomic and epigenetic alterations in mouse hippocampus

Aging represents a major risk for human neurodegenerative disorders, such as dementia and Alzheimers disease, and is associated with a functional decline in neurons and impaired synaptic plasticity, leading to a gradual decline in memory. Previous research has identified molecular and functional changes associated with aging through transcriptomic studies and neuronal excitability measurements, while the role of chromatin-level regulation in vulnerability to aging-related diseases is not well understood. Moreover, the causal relationship between molecular alterations and aging-associated decline in functions of different cell types remains poorly understood. Here, we systematically characterized gene regulatory networks in a cell type-specific manner in the aging mouse hippocampus, a central brain region involved in learning and memory formation, by simultaneously profiling gene expression and chromatin accessibility at a single nuclei level. The analysis of multiome (RNA and ATAC) sequencing recapitulated the diversity of glial and neuronal cell types in the hippocampus, and allowed revealing transcriptomic and chromatin accessibility level changes in different cell types, among which oligodendrocytes and dentate gyrus (DG) neurons exhibited the most drastic changes. We found that aging-dependent chromatin-level changes were more pronounced than transcriptomic changes for genes related to synaptic plasticity among neurons. Our data suggest that BACH2, a candidate transcription factor in the aging- mediated functional decline of DG neurons, potentially regulates genes associated with synaptic plasticity, cell death, and inflammation during aging.

neuroscience↗

bioRxiv2022

Single cell transcriptomics of ferrets reveal a common temporal pattern of progenitors in brain development of gyrencephalic mammals

The diversity of neural stem cells is a hallmark of the cerebral cortex development in gyrencephalic mammals, such as Primates and Carnivora. Among them, ferrets are a good model for mechanistic studies. However, information on their neural progenitor cells (NPC), termed radial glia (RG), is limited. Here, we surveyed the temporal series of single-cell transcriptomes of progenitors regarding ferret corticogenesis and, found a conserved diversity and temporal trajectory between human and ferret NPC, despite the large timescale difference. We found truncated RG (tRG) in ferret cortical development, a progenitor subtype previously described in humans. The combination of in silico and in vivo analyses identified that tRG differentiate into both ependymal and astrogenic cells. Via transcriptomic comparison, we predict that this is also the case in humans. Our findings suggest that tRG plays a role in the formation of adult ventricles, thereby providing the architectural bases for brain expansion.

developmental biology↗

bioRxiv2022

OrganoID: a versatile deep learning platform for organoid image analysis

Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications.

bioengineering↗

bioRxiv2019

Deep learning reveals hidden variables underlying NF-κB activation in single cells

Individual cells show great heterogeneity when responding to environmental cues. For example, under cytokine stimulation some cells activate immune signaling pathways while others completely ignore the signal. The underlying sources of cellular variability have been inaccessible due to the destructive nature of experiments. Here we apply deep learning, live-cell analysis, and mechanistic modeling to uncover hidden variables controlling NF-{kappa}B activation in single-cells. Our computer-vision algorithm accurately predicts cells that will respond to pro-inflammatory TNF stimulation and shows that single-cell activation is pre-determined by minute amounts of \"leaky\" nuclear NF-{kappa}B localization before stimulation. Theoretical analysis predicts and experiments confirm that the ratio of NF-{kappa}B to its inhibitor I{kappa}B determines the activation probability of a given cell. Our results demonstrate how computer vision can study living-cells without the use of destructive measurements and settles the question of whether heterogenous NF-{kappa}B activation is controlled by pre-existing deterministic variables or purely stochastic ones.

systems biology↗