Biology subjects

Scott, G.

Publications and source records attributed to Scott, G..

5 recordsLinked to original sources

bioRxiv2022

A retrograde GCN2/eIF2α, but ATF4 independent, mechanism maintains synaptic strength under acute amino acid scarcity at the NMJ

Neuronal response to nutrient availability plays an important role in the maintenance of cellular homeostasis and behavioral response to the environment in higher eukaryotes. However, we know little about how neuronal function is influenced by acute changes in nutrients at high resolution. Taking advantage of powerful fly genetics and the amenability of the Drosophila larval neuromuscular junction (NMJ), we have investigated the synaptic response to acute amino acid restriction. Our findings indicate that the presence of general control nonderepressible 2 (GCN2) and phosphorylation of its target eukaryotic initiation factor 2 alpha (eIF2) are essential for the ability of the NMJ to maintain normal neurotransmitter output when the larvae are deprived of amino acids. Surprisingly, activating transcription factor 4 (ATF4), which normally acts downstream of GCN2/eIF2, appears dispensable in this regulation. Furthermore, we show that GCN2/eIF2 dependent cascade acts retrogradely from muscle back to motoneuron to adjust synaptic release. These results provide a mechanistic insight into the intricate regulation of synaptic strength through the action of GCN2 when organisms are faced with amino acid scarcity.

neuroscience↗

bioRxiv2022

N6-Adenosine Methylation of SARS-CoV-2 5-UTR Regulates Translation

The coronavirus disease 2019 (COVID19) led to devastating health outcomes and has continued to spread despite global vaccination efforts1. This, alongside the rapid emergence of vaccine resistant variants, creates a need for orthogonal therapeutic strategies targeting more conserved facets of severe acute respiratory syndrome coronavirus (SARS-CoV-2)2-7. The viral genome is a single positive RNA strand divided into a genomic and a subgenomic segment. All 16 non-structural viral proteins are translated from the genomic polycistronic ORFs 1a, and 1b using a single 5'-UTR leader8,9. To our surprise, the full length 5'-UTR efficiently initiates protein translation despite its predicted structural complexity. Through a combination of biochemical assays and bioinformatic analyses, we demonstrate that a single METTL3-dependent m6A methylation event in SARS-CoV-2 5'-UTR regulates the rate of translation initiation. We demonstrate that m6A likely exerts this effect by destabilizing the third stem loop (SL3) and increasing overall accessibility to protein complexes. Our discovery provides a foundational insight into the biology of SARS-CoV-2 by linking m6A modification to its translational regulation and, thus, opens a new avenue for potential novel therapeutic strategies.

molecular biology↗

bioRxiv2021

Xenotransplantation of porcine progenitor cells in an epileptic California sea lion (Zalophus californianus)

BackgroundDomoic acid (DA) is a naturally occurring neurotoxin harmful to marine animals and humans. California sea lions exposed to DA in prey during algal blooms along the Pacific coast exhibit significant neurological symptoms, including epilepsy with hippocampal atrophy. ObservationsHere we describe a xenotransplantation procedure to deliver interneuron progenitor cells into the damaged hippocampus of an epileptic sea lion with suspected DA toxicosis. The sea lion has had no evidence of seizures following the procedure, and clinical measures of well-being including weight and feeding habits have stabilized. LessonsThese preliminary results suggest xenotransplantation has improved the quality-of-life (QOL) for this animal and holds tremendous therapeutic promise.

neuroscience↗

bioRxiv2021

Identifying components that vary in space and time from resting-state functional MRI

A widespread assumption of fMRI-derived large-scale intrinsic connectivity networks (ICNs) is that they are spatially static over time. However, the assumption of spatial stationarity of ICNs has been challenged by a range of techniques that allow for time-varying connectivity between brain regions and demonstration that canonical networks like the default model network (DMN) can be fractionated according to time-varying connectivity relationships of their subcomponents. Previously, we developed a simple spatiotemporal ICA (stICA) technique to allow the discovery of patterns of spatiotemporal evolution in task fMRI data in a way that avoided the traditional constraint of spatial stationarity on brain networks, and we validated the approach in fMRI of task-to-rest transitions. Here, we apply our stICA technique to resting-state fMRI datasets to explore whether spatiotemporally evolving components of brain activity can be identified in the absence of an overt behavioural task. We found that stICA components could generally be described in terms of graded onsets and offsets of ICNs that had been calculated based on techniques that assumed spatial stationarity. Our results suggest that, to a reasonable approximation, stable ICNs can be taken to be building blocks of the spatiotemporal patterns measured with resting-state fMRI.

neuroscience↗

bioRxiv2020

Concurrent optimisation of brain states and behavioural strategies when learning complex tasks

We developed two novel self-ordered switching (SOS) fMRI paradigms to investigate how human behaviour and underlying network resources are optimised when learning to perform complex tasks with multiple goals. SOS was performed with detailed feedback and minimal pretraining (study 1) or with minimal feedback and substantial pretraining (study 2). In study 1, multiple-demand (MD) system activation became less responsive to routine trial demands but more responsive to the executive switching events with practice. Default Mode Network (DMN) activation showed the opposite relationship. Concomitantly, reaction time learning curves correlated with increased connectivity between functional brain networks and subcortical regions. This fine-tuning of network resources correlated with progressively more routine and lower complexity behavioural structure. Furthermore, overall task performance was superior for people who applied structured behavioural routines with low algorithmic complexity. These behavioural and network signatures of learning were less evident in study 2, where task structure was established prior to entering the scanner. Together, these studies demonstrate how detailed feedback monitoring enables network resources to be progressively redeployed in order to efficiently manage concurrent demands. HighlightsO_LIWe examine the optimisation of behaviour and brain-network resources during a novel "self-ordered switching" (SOS) paradigm. C_LIO_LITask performance depended on generating behavioural routines with low algorithmic complexity (i.e., structured behaviours). C_LIO_LIBehaviour became more structured and reaction time decreased as SOS was practised. C_LIO_LIAs behaviour became more structured, activation in multiple-demand regions decreased for simple trial events but increased for executive switching events C_LIO_LIIncreases in between-network functional connectivity correlate with reaction time decreases. C_LI

neuroscience↗