Fly connectome over the wire
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Neuronal polyunsaturated fatty acids are protective in ALS/FTD
Here we report a conserved transcriptomic signature of reduced fatty acid and lipid metabolism gene expression in a Drosophila model of C9orf72 repeat expansion, the most common genetic cause of amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD), and in human postmortem ALS spinal cord. We performed lipidomics on C9 ALS/FTD Drosophila, induced pluripotent stem (iPS) cell neurons and postmortem FTD brain tissue. This revealed a common and specific reduction in phospholipid species containing polyunsaturated fatty acids (PUFAs). Feeding C9 ALS/FTD flies PUFAs yielded a modest increase in survival. However, increasing PUFA levels specifically in neurons of C9 ALS/FTD flies, by overexpressing fatty acid desaturase enzymes, led to a substantial extension of lifespan. Neuronal overexpression of fatty acid desaturases also suppressed stressor-induced neuronal death in iPS cell neurons of patients with both C9 and TDP-43 ALS/FTD. These data implicate neuronal fatty acid saturation in the pathogenesis of ALS/FTD and suggest that interventions to increase neuronal PUFA levels may be beneficial.
Macroevolution along developmental lines of least resistance in fly wings
Evolutionary change requires genetic variation, and a reigning paradigm in biology is that rates of microevolution can be predicted from estimates of available genetic variation within populations. However, the accuracy of such predictions should decay on longer evolutionary timescales, as the influence of genetic constraints diminishes. Here we show that intrinsic developmental variability and standing genetic variation in wing shape in two distantly related flies, Drosophila melanogaster and Sepsis punctum, are aligned and predict deep divergence in the dipteran phylogeny, spanning >900 taxa and 185 million years. This alignment cannot be easily explained by constraint hypotheses unless most of the quantified standing genetic variation is associated with deleterious side effects and is effectively unusable for evolution. However, phenotyping of 71 genetic lines of S. punctum revealed no covariation between wing shape and fitness, lending no support to this hypothesis. We also find little evidence for genetic constraints on the pace of wing shape evolution along the dipteran phylogeny. Instead, correlational selection related to allometric scaling, simultaneously shaping developmental variability and deep divergence in fly wings, emerges as a potential explanation for the observed alignment. This suggests that pervasive natural selection has the potential to shape developmental architectures of some morphological characters such that their intrinsic variability predicts their long-term evolution.
Genetically-encoded markers for confocal visualization of single dense core vesicles
Neuronal dense core vesicles (DCVs) store and release a diverse array of neuromodulators, trophic factors, and bioamines. The analysis of single DCVs has largely been possible only using electron microscopy, which makes understanding cargo segregation and DCV heterogeneity difficult. To address these limitations, we develop genetically encoded markers for DCVs that can be used in combination with standard immunohistochemistry and expansion microscopy to enable single-vesicle resolution with confocal microscopy in Drosophila.
Prediction of alcohol intake patterns with olfactory and gustatory brain connectivity networks
Craving in alcohol drinkers is often triggered by chemosensory cues, such as taste and smell, which are linked to brain network connectivity. This study aimed to investigate whether these brain connectivity patterns could predict alcohol intake in young adults. Resting-state fMRI data were obtained from the Human Connectome Project (HCP) Young Adult cohort, comprising 1003 participants. Functional connectomes generated from 100 independent components were analyzed, identifying significant connections correlated with taste and odor scores after applying a false discovery rate (FDR) correction using the Benjamini-Hochberg (BH) method. These significant connections were then utilized as predictors in general linear models for various alcohol intake metrics. The models were validated in an independent sample to assess their accuracy. The training sample (n = 702) and the validation sample (n = 117) showed no significant demographic differences. Out of 742 possible connections, 41 related to odor and 25 related to taste passed the significance threshold (P < 0.05) after FDR-BH correction. Notable predictors included visual-visual connectivity (node32-node13: β = 0.028, P = 0.02) for wine consumption and connectivity between the ventral attention network (VAN) and the frontal parietal/caudate nucleus (FP/CN) (node27-node9: β = −0.31, P = 0.04) for total alcohol intake in the past-week and maximum number of drinks per day in the past-year. The predictive models demonstrated strong accuracy, with root mean square error (RMSE) values of 5.15 for odor-related models and 5.14 for taste-related models. The F1 scores were 0.74 for the odor model and 0.71 for the taste model, indicating reliable performance. These findings suggest that specific patterns of brain connectivity associated with taste and olfactory perception may serve as predictors of alcohol consumption behaviors in young adults. Our study highlight the need for longitudinal research to evaluate the potential of taste- and smell-related brain connectivity patterns for early screening and targeted interventions, as well as their role in personalized treatment strategies for individuals at risk of AUD.
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