Ng, K. K. | Search bioRxiv

bioRxiv2022

A modular platform for bioluminescent RNA tracking

A complete understanding of RNA biology requires methods for tracking transcripts in vivo. Common strategies rely on fluorogenic probes that are limited in sensitivity, dynamic range, and depth of interrogation, owing to their need for excitation light and tissue autofluorescence. To overcome these challenges, we developed a bioluminescent platform for serial imaging of RNAs. Small RNA tags were engineered to recruit light-emitting luciferase fragments (termed RNA lanterns) upon transcription. Robust photon production was observed for RNA targets both in cells and in live animals. Importantly, only a single copy of the tag was necessary for sensitive detection, in sharp contrast to fluorescent platforms requiring multiple repeats. Overall, this work provides a foundational platform for visualizing RNA dynamics from the micro to the macro scale.

molecular biology↗

bioRxiv2022

Stage dependent differential influence of metabolic and structural networks on memory across Alzheimer's disease continuum

BackgroundLarge-scale neuronal network breakdown underlies memory impairment in Alzheimers disease (AD). However, the differential trajectories of the relationships between network organization and memory across pathology and cognitive stages in AD remain elusive. We determined whether and how the influences of individual-level structural and metabolic covariance network integrity on memory varied with amyloid pathology across clinical stages without assuming a constant relationship. Methods708 participants from the Alzheimers Disease Neuroimaging Initiative were studied. Individual-level structural and metabolic covariance scores in higher-level cognitive and hippocampal networks were derived from magnetic resonance imaging and [18F]fluorodeoxyglucose positron emission tomography using seed-based partial least square analyses. The non-linear associations between network scores and memory across cognitive stages in each pathology group were examined using sparse varying coefficient modelling. ResultsWe showed that the associations of memory with structural and metabolic networks in the hippocampal and default mode regions exhibited pathology-dependent differential trajectories across cognitive stages using sparse varying coefficient modelling. In amyloid pathology group, there was an early influence of hippocampal structural network deterioration on memory impairment in the preclinical stage, and a biphasic influence of the angular gyrus-seeded default mode network metabolism on memory in both preclinical and dementia stages. In non-amyloid pathology groups, in contrast, the trajectory of the hippocampus-memory association was opposite and weaker overall, while no metabolism covariance networks were related to memory. Key findings were replicated in a larger cohort of 1280 participants. ConclusionsOur findings highlight potential windows of early intervention targeting network breakdown at the preclinical AD stage.

neuroscience↗