Biology subjects

Beltran, A. A.

Publications and source records attributed to Beltran, A. A..

4 recordsLinked to original sources

bioRxiv2026

Repeat expansions in C9orf72 rewire the 3D chromatin landscape in ALS

Amyotrophic lateral sclerosis (ALS) is frequently driven by GGGGCC short tandem repeat (STR) expansions in C9orf72, yet the mechanisms by which these expansions lead to neurodegeneration remain incompletely understood. Here, we propose a novel mechanism involving higher-order chromatin architecture where C9orf72-STR expansions induce widespread, neuron-specific gains in chromatin loops that are closely linked to transcriptomic dysregulation in ALS. These ectopic loops colocalize with the genomic binding sites of C9orf72-STR RNAs and the architectural protein CTCF, supporting a model in which RNA-DNA interactions promote aberrant loop formation. Together, our findings demonstrate how C9orf72-STR expansions remodel the neuronal genome and disrupt gene expression, uncovering an RNA-driven mechanism of chromatin reorganization in C9-ALS that connects altered nuclear topology to gene dysregulation in neurodegeneration.

genomics↗

bioRxiv2025

Early cell cycle genes in cortical organoid progenitors predict interindividual variability in infant brain growth trajectories

Human induced pluripotent stem cell (iPSC) derived cortical organoids (hCOs) model neurogenesis on an individuals genetic background. The degree to which hCO phenotypes recapitulate the brain growth of the participants from which they were derived is not well established. We generated up to 3 iPSC clones from each of 18 participants in the Infant Brain Imaging Study, who have undergone longitudinal brain imaging during infancy. We identified consistent hCO morphology and cortical cell types across clones from the same participant. hCO cross-sectional area and production of cortical hem cells were associated with in vivo cortical growth rates. Cell cycle associated genes expression in early progenitors at the crux of fate decision trajectories were correlated with cortical growth rate from 6-12 months of age, and were enriched in microcephaly and neurodevelopmental disorder genes. Our data suggest the hCOs capture inter-individual variation in cortical cell types influencing infant cortical surface area expansion.

neuroscience↗

bioRxiv2022

Modulation of Tau Tubulin Kinases (TTBK1 and TTBK2) Impacts Ciliogenesis

Tau tubulin kinase 1 and 2 (TTBK1 and TTBK2) are highly homologous kinases that are expressed and mediate disease-relevant pathways predominantly in the brain. Distinct roles for TTBK1 and TTBK2 have been delineated. While efforts have been devoted to characterizing the impact to TTBK1 inhibition in diseases like Alzheimers disease and amyotrophic lateral sclerosis, TTBK2 inhibition has been less explored. TTBK2 serves a critical function during cilia assembly. Given the biological importance of these kinases, we designed a targeted library from which we identified several chemical tools that engage TTBK1 and TTBK2 in cells and inhibit their downstream signaling. Indolyl pyrimidinamine 10 significantly reduced the expression of primary cilia on the surface of human induced pluripotent stem cells (iPSCs). Furthermore, analog 10 phenocopies TTBK2 KO in iPSCs, confirming an essential role for TTBK2 in ciliogenesis.

cell biology↗

bioRxiv2021

Segmentor: A tool for manual refinement of 3D microscopy annotations

BackgroundRecent advances in tissue clearing techniques, combined with high-speed image acquisition through light sheet microscopy, enable rapid three-dimensional (3D) imaging of biological specimens, such as whole mouse brains, in a matter of hours. Quantitative analysis of such 3D images can help us understand how changes in brain structure lead to differences in behavior or cognition, but distinguishing features of interest, such as nuclei, from background can be challenging. Recent deep learning-based nuclear segmentation algorithms show great promise for automated segmentation, but require large numbers of manually and accurately labeled nuclei as training data. ResultsWe present Segmentor, an open-source tool for reliable, efficient, and user-friendly manual annotation and refinement of objects (e.g., nuclei) within 3D light sheet microscopy images. Segmentor employs a hybrid 2D-3D approach for visualizing and segmenting objects and contains features for automatic region splitting, designed specifically for streamlining the process of 3D segmentation of nuclei. We show that editing simultaneously in 2D and 3D using Segmentor significantly decreases time spent on manual annotations without affecting accuracy. ConclusionsSegmentor is a tool for increased efficiency of manual annotation and refinement of 3D objects that can be used to train deep learning segmentation algorithms, and is available at https://www.nucleininja.org/ and https://github.com/RENCI/Segmentor.

neuroscience↗