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Kinghorn, A. B.

Publications and source records attributed to Kinghorn, A. B..

2 recordsLinked to original sources

NORAD orchestrates KLC1-mediated SFPQ transport via liquid-liquid phase separation

Neuronal function requires precise long-distance axonal transport mediated by molecular motors and RNA-binding proteins like SFPQ, though regulatory mechanisms remain poorly defined. We identify long non-coding RNA NORAD as a master regulator of this process through liquid-liquid phase separation (LLPS). While SFPQ and kinesin-1 mediate cargo delivery, the specific RNA coordinating their interaction was unknown. We demonstrate NORAD directly binds kinesin light chain 1 (KLC1) and promotes SFPQ condensation into dynamic LLPS droplets, enabling efficient transport. CRISPR-assisted mapping and functional assays show NORAD depletion disrupts granule dynamics, impairs neuroprotective mRNA localization, and induces axonal degeneration. In vitro reconstitution confirms NORAD-KLC1 synergy enhances SFPQ phase separation, and neuron-specific knockout mice exhibit motor deficits with reduced neuronal density. These findings establish the first evidence of lncRNA NORAD-mediated LLPS in axonal transport, revealing a new paradigm for RNA-guided neuronal maintenance.

molecular biology↗

Pentose Sugars Encode Sequence-Dependent DNA-RNA Segregation for Biomimetic Multiphase Condensates

The nucleus segregates DNA and RNA with high precision to safeguard genome stability and gene regulation despite their homologous structures, yet the underlying molecular principles have long evaded both understanding and synthetic translation. Here we show that a single atomic difference between the pentose sugars, a 2-OH in RNA versus a 2-H in DNA, suffices to drive their phase segregation with cationic peptides. This subtle chemical distinction makes RNA bind peptides more strongly than sequence-identical DNA, generating an asymmetry that, when modulated by sequence-encoded homotypic interactions, drives the formation of core-shell multiphase condensates. Using a supervised machine-learning approach, we distill these molecular principles into a predictive design rule and harness it to program a library of oligonucleotide pairs, termed SEGREGamers, that self-assemble into droplets with coexisting DNA- and RNA-rich domains. These synthetic condensates recapitulate nuclear compartment functions, including selective molecular partitioning and enhanced RNA catalysis. Our results establish a chemically encoded platform for engineering synthetic nuclear mimics and programmable biomolecular condensates, and suggest that sugar identity may have served as an ancient physical mechanism for organizing nucleic acids.

biophysics↗