bioRxiv Science⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2021.04.16.440198

Sleep modulates alcohol toxicity in Drosophila

Noakes, E. J.·De Nobrega, A. K.·Mellers, A. P.·Lyons, L. C.
View original source ↗Export metadata ↓

Abstract

Study ObjectivesAlcohol abuse is a significant public health problem, particularly in populations in which sleep deprivation is common as such as shift workers and aged individuals. Although research demonstrates the effect of alcohol on sleep, little is known about the role of sleep in alcohol sensitivity and toxicity. We investigated sleep as a factor modulating alcohol toxicity using Drosophila melanogaster, a model system ideal for studies of sleep, alcohol and aging. MethodsFollowing 24 hours of sleep deprivation using mechanical stimulation, Drosophila were exposed to binge-like alcohol exposures. Behavioral sensitivity, tolerance, and mortality were assessed. The effects of chronic sleep deprivation on alcohol toxicity were investigated using a short sleep mutant insomniac. Pharmacological induction of sleep for prior to alcohol exposure was accomplished using a GABAA-receptor agonist, 4,5,6,7-tetrahydroisoxazolo(5,4-c)pyridin-3-ol (THIP) to determine if increased sleep mitigated the effects of alcohol toxicity on middle-aged flies and flies with environmentally disrupted circadian clocks mimicking groups more vulnerable to the effects of alcohol. ResultsAcute sleep deprivation increased alcohol-induced mortality following alcohol exposure. However, sleep deprivation had no effect on alcohol absorbance or clearance. Sleep deprivation also abolished functional tolerance measured 24 hours after the initial alcohol exposure, although tolerance at 4 h was observed. Pharmacologically increasing sleep prior to alcohol exposure decreased alcohol-induced mortality. ConclusionsSleep quantity prior to alcohol exposure affects alcohol toxicity with decreased sleep increasing alcohol toxicity and dampened 24-hour alcohol tolerance. In contrast, increased sleep mitigated alcohol-induced mortality even in vulnerable groups such as aging flies and those with circadian dysfunction. Statement of significanceWith the growing incidence of sleep deprivation and sleep disorders across adolescents and adults, it is important to understand the role of sleep in alcohol toxicity to develop future therapies for prevention and treatment of alcohol-induced pathologies. Using Drosophila melanogaster, an established model for both sleep and alcohol research, we found that acute and chronic sleep deprivation increased alcohol toxicity and eliminated long-term functional alcohol tolerance. In contrast, increased sleep prior to binge-like alcohol exposure mitigated alcohol-induced mortality even in vulnerable groups with higher susceptibility to alcohol toxicity.

Explore related subjects

neurosciencePreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Noakes, E. J., De Nobrega, A. K., Mellers, A. P., Lyons, L. C.. 2021-04-18. Sleep modulates alcohol toxicity in Drosophila. https://doi.org/10.1101/2021.04.16.440198

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience↗
bioRxiv2026

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience↗
bioRxiv2026

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience↗