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Rett syndrome neurodevelopmental disorder is caused by mutations in the gene encoding the epigenetic regulator MECP2. While the MECP2 methyl-CpG binding domain (MBD) is well-characterized, the function of the adjacent intervening domain (ID) remains largely understudied. The ID has been described as a distinct RNA-binding region, yet evidence also suggests RNA competitively displaces MECP2 from DNA. Here, we address these conflicting findings by demonstrating the MBD and ID do not function in isolation but as a synergistic functional unit, establishing a new model for MECP2 function. We show the ID significantly enhances affinity of the MBD for methylated DNA by ∼35-fold. Moreover, together these two subdomains form a high-affinity, promiscuous RNA-binding module, with affinity for structured RNAs increased over 1,000-fold compared to the MBD or ID alone. We find binding to RNA precludes binding to DNA, such that the integrated MBD-ID unit explains the competition phenomenon. Analysis of Rett syndrome-associated ID mutations (R167W, K174Q, and R190H) and a therapeutic MiniGene reveals they do not disrupt methyl-DNA binding but instead selectively weaken RNA and non-methylated DNA binding, thereby disrupting the competitive balance between nucleic acid ligands. Our work establishes the MBD-ID module as MECP2's central nucleic acid interaction hub, whose disruption provides a potential molecular etiology of Rett syndrome due to mutations in the intervening domain.

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Frontotemporal lobar degeneration with tau inclusions (FTLD-tau) comprise a class of fatal heterogeneous neurodegenerative diseases. Approximately 10% arise from pathogenic MAPT mutations and often cause severe, early-onset disease with pathology that is distinct yet partially overlapping with sporadic cases. Here, we evaluated post-mortem tissue from a patient with FTLD-tau due to MAPT S305I showing neuropathology most consistent with argyrophilic grain disease (AGD), a prevalent limbic tauopathy of aging. Structures determined by cryo-electron microscopy reveal tau filament folds that differ from those found in sporadic AGD or other tauopathies and feature a 4-layer architecture stabilized by the Ile substitution within its core. Comparative structural analysis reveals conserved motifs are shared among AGD, corticobasal degeneration, and MAPT P301T. A well-defined density stacks along a cationic cleft, indicative of a bound RNA-like polyanion or small-molecule. In vitro analysis shows the S305I mutation promotes fibrilization relative to normal tau. These results demonstrate that MAPT S305I stabilizes a distinct aggregation-prone tau fold that likely contributes to disease pathology and heterogeneity beyond its known splicing defects, and underscore potential limitations of using the most pathologically similar genetic form as a model for sporadic FTLD-tau.

Motivation: Understanding protein function requires integrating diverse biological evidence while accounting for strong contextual dependence. Recent protein embedding methods increasingly leverage heterogeneous biological networks, yet their evaluation protocols often fail to reflect the specific biological tasks for which the embeddings are intended. Prediction of missing interactions, annotation of new proteins, and discovery of functional modules require fundamentally different data partitions, such as edge-masked versus node-held-out splits. Moreover, most approaches report performance primarily on well-studied proteins, where computational predictions are least needed, risking substantial overestimation of real-world utility.

Results: We introduce a graph attention-based framework (Gatsbi) to construct context-aware protein embeddings from integrated protein-protein interactions, co-expression, sequence representations, and tissue-specific associations. Using task-aligned evaluation protocols, we show that models trained with biologically appropriate partitions achieve markedly better generalization. Across interaction, function, and functional set prediction, Gatsbi consistently outperforms existing pretrained embeddings for both well-studied and understudied proteins, with the largest gains observed for the understudied regime and under inductive node-held-out evaluation. To enable broad reuse, we provide the learned embeddings for download for application to other protein prediction tasks.

Availability and implementation: Code and models for our experiments are available at https://github.com/Helix-Research-Lab/GATSBI-embedding.

Genetically encoded (GE) libraries enable identification of high-affinity ligands for diverse molecular targets through iterative in vitro selection and DNA sequencing or next-generation sequencing (NGS). Despite their impact in therapeutic development, a systematic framework for evaluating reproducibility in GE-molecular discoveries remains limited. To aid such analysis, we introduce the concept of baseline response, which reproducibly partitions active and inactive members of in vitro selection. The baseline response is provided by spiking a random DNA-barcoded population. We calibrated the baseline concept using Bioconductor EdgeR differential enrichment (DE) analysis of NGS of phage-displayed selection on oligosaccharide chitin and hepatitis virus NS3a* protease as model targets. We further show that mixing discovery campaigns also offers an effective baseline: chitin-enriched peptides serve as a baseline for DE-analysis of NS3a* selection and NS3a*-enriched peptides serve as a baseline for chitin binders. We applied baseline-stratified DE-analysis to 66 parallel selections performed in 3-5 replicates across 22 extracellular targets, including HER1-3, EpCAM, CAIX, PD-L1, and eight integrin receptors. Automated DE-analysis across hundreds of NGS files produced hits validated in a secondary screen and yielded synthetic macrocyclic ligands with mid-nanomolar affinity confirmed in 2-3 biophysical assays. For PD-L1, we further demonstrated how baseline-calibrated NGS data provide decision-enabling information for optimization of peptide macrocycles to yield potent single-digit nanomolar ligands for the cell-surface receptor. We anticipate that baseline-based analyses of NGS data from in vitro selection procedures will offer a scalable framework for reproducible hit discovery and standardized analysis across diverse in vitro selection campaigns.

Significance statement: Genetically encoded selection technologies such as phage, mRNA and ribosome display, have produced FDA-approved therapeutics and numerous clinical candidates. Yet reproducibility in such in vitro discovery systems is rarely evaluated against a defined experimental baseline. Here, we establish a universal baseline by spiking unrelated, DNA-barcoded peptide sequences into selection libraries and quantifying their binding alongside target-enriched populations. This composition-agnostic strategy enables rigorous normalization, confidence assessment, and cross-target comparison of molecular discovery outcomes. Our framework introduces practical standards for reproducibility and statistical benchmarking across genetically encoded display platforms.

Tau pathology underlies a broad spectrum of neurodegenerative disorders, collectively termed tauopathies, yet these diseases exhibit striking heterogeneity in their biological mechanisms and clinical outcomes. The basis for this heterogeneity remains poorly understood. Here, we address this question using knock-in mouse models expressing two distinct frontotemporal dementia-associated tau mutations to define how different tau variants drive divergent pathogenic programs in vivo . We find that the two mutations give rise to fundamentally different trajectories of tau pathogenesis. One trajectory is marked by progressive tau hyperphosphorylation and cytoskeletal destabilization occurring in the absence of detectable tau seed formation. In contrast, an alternative trajectory is characterized by tau hypophosphorylation, early seed formation, and alterations in nucleotide metabolism and chromatin organization, without overt cytoskeletal disruption. With aging, tau in this latter pathway transitions to a hyperphosphorylated state and forms mature fibrillar aggregates. Genetic enhancement of β-amyloid selectively accelerates fibril formation, particularly in the model exhibiting early seeding. Together, these findings demonstrate that distinct tau mutations can engage separable pathogenic mechanisms, providing a biological framework for the heterogeneity observed across tauopathies, and highlighting the need for mechanism-informed therapeutic strategies and patient stratification.

Abstract figure:

Graphical abstract: Schematic representation comparing two trajectories of tau pathology. The S305N mutation promotes a 4R isoform shift, cytoskeletal damage and synapse loss, and accumulation of soluble hyperphosphorylated tau. Tau remains soluble even at old ages. In contrast, the P301S mutation generates hypophosphorylated, seed-competent tau that forms fibrils. The effect of amyloid is slow in the S305N, but results in accelerated acceleration of pathology in the P301S. Figure made with Biorender.com .

The ability to engineer synthetic biomolecular condensates in living cells offers new opportunities to control intracellular organization, yet robust and programmable RNA-based systems have remained limited. Here, we introduce genetically encoded, modular platforms that generate RNA-driven condensates using nanostar-derived scaffolds. Systematic comparison of repeat-based and de novo designs identified nanostar variants that reliably assemble nuclear condensates in mammalian cells. Unexpectedly, condensate formation in cells is governed primarily by double-stranded RNA stems that recruit endogenous RNA-binding proteins, rather than by the kissing-loop interactions that drive assembly in vitro . This mechanistic shift highlights the divergence between cellular and in vitro environments and accounts for the limited orthogonality among scaffolds. Sequence refinement to reduce nonspecific pairing improved homotypic assembly and enhanced orthogonality. We further demonstrated functional compartmentalization by recruiting protein and RNA clients to modulate their stability and activity, and we incorporated an acyclovir-responsive allosteric switch to achieve reversible, small-molecule control of condensation. Together, this work establishes a versatile RNA-based toolkit for constructing programmable cellular compartments, advancing strategies for controlling RNA-protein organization and enabling new biosensing and therapeutic applications.

Background: Post-transcriptional modifications are those made to the RNA transcript, which can modulate RNA stability and function. Despite robust investigation of the genome, transcriptome, and proteome, little is known about post-transcriptional modifications during normal aging or Alzheimer's disease (AD) pathogenesis. Several studies have shown epitranscriptomic changes in AD brains for certain modification types, establishing epitranscriptomic links to the disease; however, the complete set of post-transcriptional modifications have not been assessed in the context of AD. Furthermore, it is not understood which genes or pathways are under epitranscriptomic regulation, how conserved and sporadic modifications are distributed, or which conserved sites are differentially modified in diseased brains. Therefore, there is a need for a more complete analysis to describe the full landscape of the epitranscriptome in AD, helping to bridge the knowledge gap between post-transcriptional modifications and the molecular etiology of AD.

Methods: We designed and implemented a novel bioinformatics pipeline for complex epitranscriptome-wide analysis of potential RNA modification sites in sample-matched, whole-genome sequencing-filtered variant calls from RNA sequencing data. Using parametric and non-parametric tests, we tested differences in patterns for all detectable variant calls between postmortem brains of AD and cognitively normal, aged individuals.

Results: We identified 544 genes with hyper-modified transcripts in AD samples compared with cognitively normal controls, a notable observation being high enrichment of genes in the "Kaposi's sarcoma-associated herpesvirus" pathway. We also identified patterns of recurring and sporadic modification sites that differed complementarily between disease and non-disease conditions. We found 17 genes (33 total sites) that were differentially modified between conditions including several sites found exclusively in the AD epitranscriptome.

Conclusions: These findings provide a more complete profile of the potential molecular underpinnings which differentiate AD brains from their non-diseased, aged counterparts and reveal patterns and modification sites which can be further investigated for how they contribute to the network of molecular interactions underlying AD. These elements are likely to be valuable candidates for investigations that aim to further the search for biomarkers and therapeutic targets.

Oncogene amplification on extrachromosomal DNA (ecDNA) is a common driver of tumor progression and is associated with acquired drug resistance and poor patient survival. While whole genome sequencing (WGS) studies have revealed the landscape of genes amplified on ecDNA in tumors, it remains challenging to study the subclonal heterogeneity and functional (e.g., transcriptomic) consequences of ecDNA on tumors. To address this, we introduce scAmp : a probabilistic algorithm for detecting and analyzing ecDNA from single-cell datasets. We demonstrate scAmp's improved accuracy over WGS approaches on well-characterized cell-lines and its applicability to clinical histopathology. We further showcase scAmp by analyzing 73 patient tumors profiled with single-cell ATAC-seq, where we analyze the subclonal evolution of ecDNA+ subclones and identify the effect of ecDNA amplifications on the chromatin accessibility landscape of cancer cells. Together, we anticipate that scAmp will broadly enable further studies - both retrospective and prospective - that dissect critical questions of how ecDNA affect cancer cells and the tumors in which they reside.

Kisspeptin neurons in the rostral hypothalamus are hypothesized to initiate preovulatory gonadotropin-releasing hormone (GnRH) surges by causing estradiol-dependent activation of GnRH neuron action potential firing and subsequent GnRH release. To determine if estradiol or ovarian cycle stage modulates functional connectivity in this circuit, we used optogenetics to photostimulate anteroventral-periventricular (AVPV) area kisspeptin neurons while recording electrical activity and/or evoked synaptic currents from preoptic area GnRH neurons in acutely-prepared mouse brain slices. Slices were prepared from mice in multiple hormonal states, including 2-days post ovariectomy (OVX) and OVX plus estradiol during the morning or afternoon, diestrus, proestrus and 1-week post OVX, and 6-weeks post OVX with or without 1 week of estradiol replacement. Photostimulation induced a sustained, frequency-dependent increase in GnRH neuron firing rate. This neuromodulatory-typical response was not different in diestrous vs proestrous mice but was blunted in 1-week OVX mice, suggesting ovarian steroids amplify this response. Neuromodulatory responses were infrequent in 6-week OVX mice even with 1-week of estradiol treatment. A minority of GnRH neurons exhibited a substantial and near-immediate increase in firing rate typical of fast synaptic transmission. Monosynaptic connectivity was low and stable across the hormone states tested and mediated by GABA. Interestingly, evidence of a monosynaptic connection was not a requirement for GnRH neurons to exhibit a sustained increase in firing rate, suggesting non-synaptic or volume transmission occurs in this system. Synaptic connectivity did, however, amplify the increase in firing rate observed in GnRH neurons from proestrous mice, indicating proestrous hormonal conditions can amplify this response.

Significance statement: Ovulation is initiated by central positive feedback effects of estradiol stimulating a surge of gonadotropin-releasing hormone (GnRH) release. Estradiol feedback is conveyed to GnRH neurons by afferents expressing estrogen receptor alpha, including kisspeptin-expressing neurons in the anteroventral periventricular (AVPV) area. To determine if endocrine milieu modulates functional interactions between AVPV kisspeptin and GnRH neurons, optogenetics was used to stimulate AVPV kisspeptin neurons while recording GnRH neuron spiking activity or synaptic currents in brain slices from ovariectomized, estradiol-treated, and ovary-intact mice. Stimulation (20Hz) increased GnRH neuron firing rate in all hormone conditions. This effect was stronger during proestrus and was further increased in GnRH neurons receiving fast-synaptic transmission. A synaptic connection was not required, however, suggesting volume transmission occurs.

Recent advances in machine learning (ML)-based protein design methods have enabled the rapid in silico generation of large libraries of miniprotein binders with minimal manual input. While computational design capacity has scaled rapidly, experimental validation methods have lagged, creating a bottleneck in binder discovery pipelines. Here, we apply mRNA display to screen an ML-designed miniprotein binder library and directly compare its performance with the more widely used yeast surface display platform using a single shared DNA library. We screened 2,009 designs targeting the platelet receptor TLT-1 and 3,159 designs targeting the immune receptor B7-H3 across both platforms. While both selection methods reliably identified functional binders, we found that mRNA display preferentially enriched binders with slower dissociation rates. In addition, mRNA display achieved higher library coverage than yeast display, likely rescuing functional designs that are penalized in a cell-based expression system. Biophysical characterization of selected binders from both platforms revealed strong binding affinities and high thermal stabilities. These results showcase the power of integrating ML-based computational design tools with rapid in vitro selection technologies, providing a scalable framework for therapeutic miniprotein discovery.

Importance: Miniprotein binders offer major advantages as next-generation therapeutics, including small size, high stability, and efficient production. In this work, we conduct a side-by-side comparison of mRNA and yeast display as platforms for high-throughput evaluation of de novo miniprotein binders. The binders generated here serve as starting points for therapeutics targeting TLT-1 or B7-H3, two clinically relevant molecules.