Biology subjects

Bakker, R.

Publications and source records attributed to Bakker, R..

10 recordsLinked to original sources

bioRxiv2026

Senescence targeting re-enables injury-responsive repair in a human RPE aging model

Aging is associated with progressive tissue dysfunction and impaired repair after injury. In the retinal pigment epithelium (RPE), these changes contribute to age-related macular degeneration (AMD), yet the mechanisms limiting repair remain incompletely understood. Here, we establish a longitudinal human embryonic stem cell (hESC)-derived RPE aging model that recapitulates key features of aged human donor RPE and combine it with mosaic cell ablation to assess injury-responsive repair. Although aged RPE cells initiate DNA synthesis after injury, they exhibit impaired mitotic progression, uncoupling S-phase entry from epithelial repopulation. Transcriptomic profiling links this defect to a senescence-associated program marked by inflammatory signaling and suppressed mitotic networks. Pharmacologic reduction of senescent cells with Navitoclax shifts aged RPE toward a younger transcriptional profile but does not induce repopulation by itself. Instead, senolytic treatment primes aged RPE for repair, improving epithelial density and homeostatic function only in response to injury, a strategy we term "senolytic priming." These findings establish a human stem-cell-derived platform for investigating age-associated epithelial repair failure and show that aged human RPE retains latent repair capacity that can be re-enabled by targeting cellular senescence.

Cell Biology↗

bioRxiv2026

Transcriptomic analysis of organotypic porcine retina cultures

Porcine organotypic retinal explant cultures are widely used to study retinal neurodegeneration under controlled conditions, but the biological process that occurs in the retinal explant over time due to preparation-induced injury and culture are not well understood. Here, we generated a time-resolved transcriptomic reference for porcine neural retinal explants-maintained ex vivo for 10 days. Global expression profiles are strongly separated by culture time, with Day 0 clearly distinct from cultured samples and at Day 7 and Day 10 showing the highest similarity, indicating a transition toward a later stabilized state. Across the time course, 3,187 genes were differentially expressed relative to Day 0, with the largest shifts occurring at an early stage of culture (Day 1-Day 3). Pathway-level analyses revealed coordinated remodeling involving inflammatory signaling, and metabolic/bioenergetic changes, including reduced mitochondrial and oxidative phosphorylation-related programs at later time points. Here, we provide a time-resolved transcriptomics reference dataset for cultured porcine retinal explants. These data can build a foundation to interpret data generated in this model, differentiate changes inherent to the explant culture from treatment-specific effects and to select appropriate experimental windows for mechanistic studies of retinal degeneration.

molecular biology↗

bioRxiv2025

Spatial Transcriptomics of Schizophrenia Insular Cortex Reveals Blood-Brain Barrier Hyperglycolysis and Increased Parenchymal Mitochondrial Respiration

IntroductionThe blood-brain barrier (BBB) acts as the metabolic and immunological gatekeeper of the brain. Since alterations in neurometabolism and neuroimmunity are found in schizophrenia-spectrum disorders (SSD) which are hypothesised to be important disease mechanisms, we aimed to investigate whether changes in BBB function could underly these findings using a novel spatially resolved transcriptomics technique. MethodsFormalin-fixed paraffin-embedded insular cortex tissue from 8 brain donors with SSD and 8 matched controls derived from the Netherlands Brain Bank-Psychiatry were selected for whole transcriptome analysis (GeoMx Human Whole Transcriptome Atlas) on the GeoMx Digital Spatial Profiler platform. Combining nuclear staining with an endothelial cell marker (CD31) allowed for the separation of BBB and parenchyma areas of interest (AOIs) for downstream sequencing on the Illumina NextSeq 2000. For each sample, biological triplicates were sequenced. Comparing SSD to control for both the BBB and parenchyma AOIs, differentially expressed genes (DEGs) were identified using a Linear Mixed Model, a heatmap was created displaying all genes with a false-discovery rate <0.01, and Fast Gene Set Enrichment Analysis was used for pathway analysis. ResultsA total of 96 whole transcriptome profiles were generated (24 BBB and 24 parenchyma for both SSD and controls). Expression of endothelial genes (PECAM1/CD31, CLDN5, VWF, CD34, ENG) was significantly increased in BBB, confirming enrichment of endothelial cells (ECs) in this AOI. Cluster analysis showed perfect clustering of BBB versus parenchyma, and good clustering of SSD samples within the BBB cluster. At a |Log2FC| [≥] 0.25, we identify 265 significantly DEGs in the BBB AOI and 6 in the parenchyma AOI comparing SSD to control. Pathway analysis revealed a distinct metabolic transcriptional profile in SSD, characterized by hyperglycolysis in the BBB and increased mitochondrial energy metabolism in parenchyma. ConclusionOur findings implicate the BBB in the metabolic pathophysiology of SSD. Furthermore, our findings add nuance to the existing understanding of brain bioenergetic alterations in SSD, suggesting that metabolic changes may be region-specific rather than generalized. This highlights the need for a brain mapping approach examining multiple brain regions from the same donor. Finally, the distinct metabolic profiles of the BBB and brain parenchyma emphasize the importance of spatial multi-omics in post-mortem psychiatric research and the potential for therapies targeting BBB function in SSD.

neuroscience↗

bioRxiv2023

MEBRAINS 1.0: a new population-based macaque atlas

Due to their fundamental relevance, the number of anatomical macaque brain templates is constantly growing. Novel templates aim to alleviate limitations of previously published atlases and offer the foundation to integrate multiscale multimodal data. Typical limitations of existing templates include their reliance on one subject, their unimodality (usually only T1 or histological images), or lack of anatomical details. The MEBRAINS template overcomes these limitations by using a combination of T1 and T2 images, from the same 10 animals (Macaca mulatta), which are averaged by the multi-brain toolbox for diffeomorphic registration and segmentation. The resulting volumetric T1 and T2 templates are supplemented with high quality white and gray matter surfaces built with FreeSurfer. Human-curated segmentations of pial surface, white/gray matter interface and major subcortical nuclei were used to analyse the relative quality of the MEBRAINS template. Recently published 3D maps of the macaque inferior parietal lobe and (pre)motor cortex were warped to the MEBRAINS surface template, thus populating it with a parcellation scheme based on cyto- and receptor architectonic analyses. Finally, 9 CT scans of the same monkeys were registered to the T1 modality and co-registered to the template. Through its main features (multi-subject, multi-modal, volume-and-surface, traditional and deep learning-based segmentations), MEBRAINS aims to improve integration of multi-modal multi-scale macaque data and is quantitatively equal or better compared to currently widely used macaque templates. The template is integrated in the EBRAINS and Scalable Brain Atlas web-based infrastructures, each of which comes with its own suite of spatial registration tools.

neuroscience↗

bioRxiv2023

Multi-Scale Spiking Network Model of Human Cerebral Cortex

Although the structure of cortical networks provides the necessary substrate for their neuronal activity, the structure alone does not suffice to understand it. Leveraging the increasing availability of human data, we developed a multi-scale, spiking network model of human cortex to investigate the relationship between structure and dynamics. In this model, each area in one hemisphere of the Desikan-Killiany parcellation is represented by a 1 mm2 column with a layered structure. The model aggregates data across multiple modalities, including electron microscopy, electrophysiology, morphological reconstructions, and DTI, into a coherent framework. It predicts activity on all scales from the single-neuron spiking activity to the area-level functional connectivity. We compared the model activity against human electrophysiological data and human resting-state fMRI data. This comparison reveals that the model can reproduce aspects of both spiking statistics and fMRI correlations if the cortico-cortical connections are sufficiently strong. Furthermore, we show that a single-spike perturbation propagates through the network within a time close to the limit imposed by the delays.

neuroscience↗

bioRxiv2020

The Wg and Dpp morphogens regulate gene expression by modulating the frequency of transcriptional bursts

Morphogen signaling contributes to the proper spatiotemporal expression of genes during development. One method of regulation of signaling-responsive genes is at the level of transcription. Single-cell quantitative studies of transcription have revealed that transcription occurs intermittently, in bursts. Although the effects of many gene regulatory mechanisms on transcriptional bursting have been studied, it remains unclear how morphogen gradients affect this dynamic property of downstream genes. Here we have adapted smFISH for use in the Drosophila wing imaginal disc in order to measure nascent and mature mRNA of genes downstream of the Wg and Dpp morphogen gradients. We compared our experimental results with predictions from stochastic models of transcription. Our results indicate that the transcription levels of these genes appear to share a common method of control via burst frequency modulation. Our data helps further elucidate the link between developmental gene regulatory mechanisms and transcriptional bursting.

developmental biology↗

bioRxiv2019

Prediction of a cell-type specific mouse mesoconnectome using gene expression data

Reconstructing brain connectivity at sufficient resolution for computational models designed to study the biophysical mechanisms underlying cognitive processes is extremely challenging. For such a purpose, a mesoconnectome that includes laminar and cell-type specificity would be a major step forward. We analysed the ability of gene expression patterns to predict cell-type and laminar specific projection patterns and analyzed the biological context of the most predictive groups of genes. To achieve our goal, we used publicly available volumetric gene expression and connectivity data and pre-processed it for prediction by averaging across brain regions, imputing missing values and rescaling. Afterwards, we predicted the strength of axonal projections and their binary form using expression patterns of individual genes and co-expression patterns of spatial gene modules.\n\nFor predicting projection strength, we found that ridge (L2-regularized) regression had the highest cross-validated accuracy with a median r2 score of 0.54 which corresponded for binarized predictions to a median area under the ROC value of 0.89. Next, we identified 200 spatial gene modules using the dictionary learning and sparse coding approach. We found that these modules yielded predictions of comparable accuracy, with a median r2 score of 0.51. Finally, a gene ontology enrichment analysis of the most predictive gene groups resulted in significant annotations related to postsynaptic function.\n\nTaken together, we have demonstrated a prediction pipeline that can be used to perform multimodal data integration to improve the accuracy of the predicted mesoconnectome and support other neuroscience use cases.

neuroscience↗

bioRxiv2019

Repressive gene regulation synchronizes development with cellular metabolism

Metabolic conditions affect the developmental tempo of most animal species. Consequently, developmental gene regulatory networks (GRNs) must faithfully adjust their dynamics to a variable time scale. We find evidence that layered weak repression of genes provides the necessary coupling between GRN output and cellular metabolism. Using a mathematical model that replicates such a scenario, we find that lowering metabolism corrects developmental errors that otherwise occur when different layers of repression are lost. Through mutant analysis, we show that gene expression dynamics are unaffected by loss of repressors, but only when cellular metabolism is reduced. We further show that when metabolism is lowered, formation of a variety of sensory organs in Drosophila is normal despite loss of individual repressors of transcription, mRNA stability, and protein stability. We demonstrate the universality of this phenomenon by experimentally eliminating the entire microRNA family of repressors, and find that all microRNAs are rendered unnecessary when metabolism is reduced. Thus, layered weak repression provides robustness through error frequency suppression, and may provide an evolutionary route to a shorter reproductive cycle.

developmental biology↗

bioRxiv2018

Tcf4 encodes cortical differentiation during development

Tcf4 has been linked to autism, schizophrenia, and Pitt-Hopkins Syndrome (PTHS) in humans, however, the mechanisms behind its role in disease development is still elusive. In the present study, we provide evidence that Tcf4 has a critical function in the differentiation of cortical regions during development.\n\nWe show that Tcf4 is present throughout the developing brain at the peak of neurogenesis. Deletion of Tcf4 results in mis-specification of the cortical layers, malformation of the corpus callosum and hypoplasia of the hippocampus. RNA-sequencing on E14.5 cortex material shows that Tcf4 functions as a transcriptional activator and loss of Tcf4 results in downregulation of genes linked to the emergence of other neurodevelopmental disorders. Taken together, we show that neurogenesis and differentiation are severely affected in Tcf4 mutants, phenocopying morphological brain defects detected in PTHS patients. The presented data identifies new leads to understand the mechanism of human brain defects and will assist in genetic counseling programs.

neuroscience↗

bioRxiv2018

Ratio-based sensing of two transcription factors regulates the transit to differentiation

Cell state transitions are often triggered by large changes in the absolute concentrations of transcription factors and therefore large differences in the stoichiometric ratios between these factors. Whether cells can elicit state transitions using modest changes in the relative ratios of co-expressed factors is unclear. In this study we investigate how cells in the Drosophila eye resolve cell state transitions by quantifying the expression dynamics of the ETS transcription factors Pnt and Yan. We find that eye progenitor cells maintain a relatively constant ratio of Pnt/Yan protein despite expressing both proteins with pulsatile dynamics. A rapid and sustained two-fold increase in the Pnt/Yan ratio accompanies transitions to photoreceptor fates. Genetic perturbations that modestly disrupt the Pnt/Yan ratio produce fate transition defects consistent with the hypothesis that transitions are normally driven by a two-fold shift in the ratio. A biophysical model based on cooperative Yan-DNA binding coupled with non-cooperative Pnt-DNA binding illustrates how two-fold ratio changes could generate ultrasensitive changes in target gene transcription to drive fate transitions. In this way, coupling cell state transitions to the Pnt/Yan stoichiometric ratio sensitizes the system to modest fold-changes, conferring both robustness and ultrasensitivity to the developmental program.

developmental biology↗