Biology subjects

Schafer, N.

Publications and source records attributed to Schafer, N..

5 recordsLinked to original sources

bioRxiv2026

Molecular dynamics of Brodmann Area 22 in development and autism

Challenges in verbal communication are a prominent feature of autism. However, gene regulatory programs in speech-related cortical regions remain poorly characterized. In parallel, it remains unclear whether the heterogeneous genetic factors underlying autism converge on shared neurobiological mechanisms. To address these gaps, we generated paired transcriptomic and epigenomic data from post-mortem human brain tissue across 100 donors. Here, we show that transcriptional differences in the speech-related Brodmann Area 22 in individuals with neurodevelopmental conditions, including autism, are strongest among those with a known genetic diagnosis. A similar but attenuated signature is observed in those without a genetic diagnosis. These transcriptional differences are most pronounced in neurons, with glutamatergic L4/5 intratelencephalic neurons affected across multiple modalities. Finally, multimodal analysis implicates altered RFX3-dependent networks as a central hub in autism, particularly among L4/5 intratelencephalic neurons in non-verbal individuals. Together, our study identifies regulatory architecture linking chromatin state, transcriptional output, and variation in verbal ability in autism.

neuroscience↗

bioRxiv2025

Disruption of Cell-Type-Specific Molecular Programs of Medium Spiny Neurons in Autism

Autism spectrum disorders (ASD) are highly heritable neurodevelopmental conditions with major contributions from rare genetic variants. Most studies have focused on cortical mechanisms; even growing evidence implicates subcortical circuits in ASD etiology. To systematically map developmental and molecular alterations beyond the cortex, we profiled lineage relationships across five brain regions in an ASD mouse model. Most prominent changes emerged in the striatum, a hub for learning and motor control. Furthermore, we performed single-nucleus multiomic profiling of human putamen from ASD and neurotypical donors revealed cell-type-specific transcriptomic and regulatory alterations. Differential expression converged on synaptic and energy metabolic dysfunctions in D1 striosome medium spiny neurons (MSNs), coupled with astrocytic remodeling of synaptic support. Gene regulatory network analysis identified EGR3 and EGR1 as key transcriptional regulators of ASD-associated programs of D1 MSNs. Together, these results establish the striatum as a central node of ASD convergence and provide a multiomic resource for dissecting its subcortical mechanisms.

neuroscience↗

bioRxiv2021

Full bandwidth electrophysiology of seizures and epileptiform activity enabled by flexible graphene micro-transistor depth neural probes

Mapping the entire frequency bandwidth of neuronal oscillations in the brain is of paramount importance for understanding physiological and pathological states. The ability to record simultaneously infraslow activity (<0.1 Hz) and higher frequencies (0.1-600 Hz) using the same recording electrode would particularly benefit epilepsy research. However, commonly used metal microelectrode technology is not well suited for recording infraslow activity. Here we use flexible graphene depth neural probes (gDNP), consisting of a linear array of graphene microtransistors, to concurrently record infraslow and high frequency neuronal activity in awake rodents. We show that gDNPs can reliably record and map with high spatial resolution seizures, post-ictal spreading depolarisation, and high frequency epileptic activity through cortical laminae to the CA1 layer of the hippocampus in a mouse model of chemically-induced seizures. We demonstrate functionality of chronically implanted devices over 10 weeks by recording with high fidelity spontaneous spike-wave discharges and associated infraslow activity in a rat model of absence epilepsy. Altogether, our work highlights the suitability of this technology for in vivo electrophysiology research, in particular, to examine the contributions of infraslow activity to seizure initiation and termination.

neuroscience↗

bioRxiv2018

PAGE4 and Conformational Switching: Insights from Molecular Dynamics Simulations and Implications for Prostate Cancer

Prostate-Associated Gene 4 (PAGE4) is a disordered protein implicated in the progression of prostate cancer. PAGE4 can be phosphorylated at two residue sites by Homeodomain-Interacting Protein Kinase 1 (HIPK1) to facilitate its binding to the Activator Protein-1 (AP-1) transcription factor. In contrast, a further hyperphosphorylation of PAGE4 by CDC-Like Kinase 2 (CLK2) reduces its binding affinity to AP-1, thus affecting the androgen receptor (AR) activity. Both SAXS and smFRET experiments have shown a structural expansion of PAGE4 upon hyperphosphorylation and a significant increase in size at its N-terminal half than that at its C-terminus. To understand the molecular mechanism underlying this structural transition, we performed a series of constant temperature molecular dynamics simulations using Atomistic AWSEM -- a multi-scale molecular model combining detailed atomistic and coarse-grained simulation approaches. Our simulations show that electrostatic interaction drives a transient formation of an N-terminal loop, which causes the change in size for different phosphorylated forms of PAGE4. Phosphorylation also changes the preference of secondary structure formation of PAGE4, which signifies a transition between states that display different degree of disorder. Finally, we construct a mechanism-based mathematical model that allows us to capture the interactions of different forms of PAGE4 with AP-1 and AR, a key therapeutic target in prostate cancer. Our model predicts intracellular oscillatory dynamics of HIPK1-PAGE4, CLK2-PAGE4 and AR activity, indicating phenotypic heterogeneity in an isogenic cell population. Thus, conformational switching among different forms of PAGE4 may potentially affect the efficiency of therapeutic targeting of AR.

biophysics↗

bioRxiv2017

The AWSEM-Amylometer: Predicting Amyloid Propensity And Fibril Topology Using An Optimized Folding Landscape Model

Amyloids are fibrillar protein aggregates with simple repeated structural motifs in their cores, usually {beta}-strands but sometimes -helices. Identifying the amyloid-prone regions within protein sequences is important both for understanding the mechanisms of amyloid-associated diseases and for understanding functional amyloids. Based on the crystal structures of seven cross-{beta} amyloidogenic peptides with different topologies and one recently solved cross- fiber structure, we have developed a computational approach for identifying amyloidogenic segments in protein sequences using the Associative memory, Water mediated, Structure and Energy Model. The AWSEM-Amylometer performs favorably in comparison with other predictors in predicting aggregation-prone sequences in multiple datasets. The method also predicts the specific topologies (the relative arrangement of {beta}-strands in the core) of the amyloid fibrils well. An important advantage of the AWSEM-Amylometer over other existing methods is its direct connection with an efficient, optimized protein folding simulation model, AWSEM. This connection allows one to combine efficient and accurate search of protein sequences for amyloidogenic segments with the detailed study of the thermodynamic and kinetic roles that these segments play in folding and aggregation in the context of the entire protein sequence. We present new simulation results that highlight the free energy landscapes of peptides that can take on multiple fibril topologies. We also demonstrate how the Amylometer methodology can be straightforwardly extended to the study of functional amyloids that have the recently discovered cross- fibril architecture.

biophysics↗