Biology subjects

Götz, M.

Publications and source records attributed to Götz, M..

6 recordsLinked to original sources

bioRxiv2026

RTTN moonlights beyond the centrosome to control ribosome biogenesis and tRNA modification in human brain organoids

RTTN (rotatin) is a centrosomal protein mutated in severe malformations of cortical development, yet how its dysfunction disrupts human corticogenesis has remained unclear. Here, we show that RTTN has an unrecognized function at the core of the translation machinery. Using human telencephalic and hippocampal organoids carrying distinct RTTN alleles, together with single-cell and bulk transcriptomics, polysome profiling, and tRNA pseudouridine sequencing, we find that RTTN is enriched in cycling first-trimester neural progenitors and physically associates with ribosome-biogenesis and RNA-processing factors. RTTN mutations impair rRNA biogenesis and polysome assembly, reduce cytoplasmic ribosome density and nascent protein synthesis, and remodel the tRNA pseudouridylation landscape through both a PUS7L-dependent variable-arm signature and a broader RTTN-specific defect. These translational deficits are accompanied by prolonged mitosis, reduced entry into S-phase, and impaired interkinetic nuclear migration in mutant progenitors. Our findings redefine RTTN as a regulator of ribosome homeostasis and mRNA translation and implicate defective translational capacity as a driver of RTTN-associated microcephaly. Graphical AbstractRTTN sustains ribosome and tRNA homeostasis in human neural progenitors; its mutation disrupts mRNA translation, stalling progenitor proliferation and interkinetic nuclear migration, and driving cortical malformation and growth failure. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=151 SRC="FIGDIR/small/744412v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@16124aaorg.highwire.dtl.DTLVardef@ae23f7org.highwire.dtl.DTLVardef@bb588forg.highwire.dtl.DTLVardef@1b35028_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2026

Antagonizing niche signals regulate the emergence of postnatal neural stem cells and allow enlargement of their pool

Adult neural stem cells (aNSCs) of the lateral ventricular sub-ventricular zone (V-SVZ) are set aside during embryogenesis from a pool of slowly dividing neural stem/progenitor cells (NSPCs) residing in the lateral ganglionic eminence (LGE). The time of aNSCs specification coincides with the peak of embryonic neurogenesis, raising the question of which mechanisms allow only a subpopulation of NSPCs to retain stem cell identity while others proceed to divide and differentiate into neurons. To address this, we isolated rapidly and slowly dividing NSPCs from the mouse LGE at mid-neurogenesis, when aNSCs are specified, and profiled the transcriptome at the single cell level. We find that slowly dividing NSPCs constitute a heterogeneous population encompassing both radial glia cells (RGCs) and intermediate progenitors (IPs) and characterized by different gene signatures. Focusing on RGCs, we show that slowly and rapidly dividing RGCs differentially express genes involved in the formation - such as Lamb2 - or degradation - such as Mmp15 - of the extracellular matrix (ECM), pointing to opposite niche-remodelling strategies as a potential mechanism of fate determination. In vivo perturbation of Lamb2 and Mmp15 affects the seeding and maintenance of NSCs in an opposing manner, with knockdown of Mmp15 increasing the NSC pool as also shown by single-cell RNA-sequencing. These findings suggest that opposite ECM remodelling by slowly and rapidly dividing RGCs constitutes a novel cross-regulatory niche-level mechanism regulating aNSCs emergence, opening new avenues for regulating their numbers and thereby long-term maintenance of the brains regenerative potential.

developmental biology↗

bioRxiv2025

Fibrin-containing Hydrogels Regulate Human Astrocyte State and Neuronal Reprogramming

Astrocytes are key components in reactive gliosis after brain injury, yet defined in vitro models dissecting the influence of extracellular matrix (ECM) components enriched after injury, such as fibrin, on human astrocyte behaviour and function are still missing. Here, we use fibrinogen-derived fibrin and fibrin-alginate-RGD (FAR) 3D hydrogel substrates to examine the influence on human iPSC-derived astrocyte behaviour and their direct conversion into neurons. Astrocytes develop complex morphologies in 3D-FAR hydrogels while are more proliferative and migratory in 3D-Fibrin. Interestingly, gene expression profile analysis revealed different reactive states of astrocytes in 3D-Fibrin and 3D-FAR, which persist over time. The highly inflammatory state in 3D-FAR is largely incompatible with direct neuronal reprogramming hampering the direct conversion even at early stages. Conversely, astrocytes in 3D-Fibrin hydrogels can readily convert into neurons, demonstrating a potent influence of how fibrin is presented on eliciting distinct astrocyte states with great relevance for fate conversion. Research highlightsO_LIFirst transcriptome of human astrocytes in 3D-Fibrin hydrogel and derivative C_LIO_LIFibrin-alginate-RGD (3D-FAR) hydrogel elicits high branching complexity along with exacerbated reactive signature in astrocytes C_LIO_LI3D-Fibrin hydrogels enable proliferation and migration of astrocytes C_LIO_LIDirect conversion of human iPSC-derived astrocytes into neurons in 3D-Fibrin hydrogel C_LI

neuroscience↗

bioRxiv2025

NucleicBERT: Deciphering the language of nucleic acids

The vast majority of the human genome comprises non-protein-coding regions whose structural and functional roles remain poorly understood. Many of these regions function through RNA, yet progress in deep learning for RNA has lagged behind proteins because most methods rely on abundant structural labels or evolutionary alignments, both sparse for RNA. To address these challenges, we developed NucleicBERT, a self-supervised masked-language model that learns contextual representations capturing local and distal dependencies without requiring alignments or evolutionary information. Explainable AI analysis reveals that the model clusters RNA types in latent space and attends to structural properties like secondary structure and tertiary contacts, effectively "rediscovering" RNA biology from sequence correlations alone. When fine-tuned for downstream structural and functional tasks, NucleicBERT requires only single sequences, yet surpasses current state-of-the-art RNA models. This alignment-free framework addresses the scarcity of annotated 3D RNA data while providing a rapid, computational complement to experimental techniques. By bridging abundant unlabeled primary sequence corpora with more scarce structural annotations, NucleicBERT advances RNA structure prediction and provides insights into the working of LLMs. NucleicBERT is available at https://github.com/KIT-MBS/NucleicBERT.

biophysics↗

bioRxiv2025

A single-cell transcriptomic atlas maps cerebellar astrocyte diversity and uncovers the transcriptional code underlying their maturation trajectories

Astrocytes are increasingly recognized as key regulators of neural circuit development and function, with mounting evidence revealing substantial heterogeneity within and across brain regions. Yet, the full extent of this diversity and its developmental mechanisms remain poorly understood. To address this, we leveraged the uniqueness of the mouse cerebellum, which hosts well-defined astrocyte types and established progenitor pools. Through complementary multi-modal omic approaches, including single-cell RNA sequencing, spatial transcriptomics, trajectory inference, clonal lineage reconstruction, and gene expression and regulatory network analyses, we systematically dissected the molecular diversity and ontogenesis of cerebellar astrocytes. We identified known types and uncovered new subtypes with functional specialization, inferring their developmental trajectories from multiple embryonic niches and postnatal progenitor sources with fate divergence, convergence, and restriction. We further predicted a hierarchical transcriptional regulator code governing this diversification, operating at multiple levels: distinct regulatory modules i) reflect embryonic regionalization and lineage; ii) determine broad astroglial identity; specify iii) Bergmann versus non-Bergmann fates; and guide iv) astrocyte type and v) subtype acquisition. Our findings map and temporally organize transcriptional programs that capture key determinants of astrocyte fate, integrating them along defined trajectories toward diverse astrocyte identities. This high-resolution framework for cerebellar glial diversification offers a model to be challenged across other brain regions.

neuroscience↗

bioRxiv2021

Inferring kinetic rate constants from single-molecule FRET trajectories - a blind benchmark of kinetic analysis tools

Single-molecule FRET (smFRET) is a versatile technique to study the dynamics and function of biomolecules since it makes nanoscale movements detectable as fluorescence signals. The powerful ability to infer quantitative kinetic information from smFRET data is, however, complicated by experimental limitations. Diverse analysis tools have been developed to overcome these hurdles but a systematic comparison is lacking. Here, we report the results of a blind benchmark study assessing eleven analysis tools used to infer kinetic rate constants from smFRET trajectories. We tested them against simulated and experimental data containing the most prominent difficulties encountered in analyzing smFRET experiments: different noise levels, varied model complexity, non-equilibrium dynamics, and kinetic heterogeneity. Our results highlight the current strengths and limitations in inferring kinetic information from smFRET trajectories. In addition, we formulate concrete recommendations and identify key targets for future developments, aimed to advance our understanding of biomolecular dynamics through quantitative experiment-derived models.

biophysics↗