Biology subjects

Hart, A. C.

Publications and source records attributed to Hart, A. C..

3 recordsLinked to original sources

bioRxiv2020

Discriminating between sleep and exercise-induced fatigue using computer vision and behavioral genetics

Following prolonged swimming, Caenorhabditis elegans cycle between active swimming bouts and inactive quiescent bouts. Swimming is exercise for C. elegans and here we suggest that inactive bouts are a recovery state akin to fatigue. Previously, analysis of exercise-induced quiescent (EIQ) bouts relied on laborious manual observation, as existing automated analysis methods for C. elegans swimming either cannot analyze EIQ bouts or fail to accurately track animal posture during these bouts. It is known that cGMP-dependent kinase (PKG) activity plays a conserved role in sleep, rest, and arousal. Using C. elegans EGL-4 PKG, we first validate a novel learning-based computer vision approach to automatically analyze C. elegans locomotory behavior and distinguish between activity and inactivity during swimming for long periods of time. We find that C. elegans EGL-4 PKG function predicts EIQ first bout timing, fractional quiescence, bout number, and bout duration, suggesting that previously described pathways are engaged during EIQ bouts. However, EIQ bouts are likely not sleep as animals are feeding during the majority of EIQ bouts. We find that genetic perturbation of neurons required for other C. elegans sleep states also does not alter EIQ dynamics. Additionally, we find that EIQ onset is sensitive to age and DAF-16 FOXO function. In summary, we have validated a new behavioral analysis software that enabled a quantitative and detailed assessment of swimming behavior, including EIQ. We found novel EIQ defects in aged animals and animals with mutations in a gene involved in stress tolerance. We anticipate that further use of this software will facilitate the analysis of genes and pathways critical for fatigue and other C. elegans behaviors.

animal behavior and cognition↗

bioRxiv2019

WormCat: an online tool for annotation and visualization of Caenorhabditis elegans genome-scale data

The emergence of large gene expression datasets has revealed the need for improved tools to identify enriched gene categories and visualize enrichment patterns. While Gene Ontogeny (GO) provides a valuable tool for gene set enrichment analysis, it has several limitations. First, it is difficult to graphically compare multiple GO analyses. Second, genes from some model systems are not well represented. For example, around 30% of Caenorhabditis elegans genes are missing from analysis in commonly used databases. To allow categorization and visualization of enriched C. elegans gene sets in different types of genome-scale data, we developed WormCat, a web-based tool that uses a near-complete annotation of the C. elegans genome to identify co-expressed gene sets and scaled heat map for enrichment visualization. We tested the performance of WormCat using a variety of published transcriptomic datasets and show that it reproduces major categories identified by GO. Importantly, we also found previously unidentified categories that are informative for interpreting phenotypes or predicting biological function. For example, we analyzed published RNA-seq data from C. elegans treated with combinations of lifespan-extending drugs where one combination paradoxically shortened lifespan. Using WormCat, we identified sterol metabolism as a category that was not enriched in the single or double combinations but emerged in a triple combination along with the lifespan shortening. Thus, WormCat identified a gene set with potential phenotypic relevance that was not uncovered with previous GO analysis. In conclusion, WormCat provides a powerful tool for the analysis and visualization of gene set enrichment in different types of C. elegans datasets.

bioinformatics↗

bioRxiv2019

Disrupted Autophagy and Neuronal Dysfunction in C. elegans Knockin Models of FUS Amyotrophic Lateral Sclerosis

It remains unclear how mutations in FUS, a ribonucleoprotein, lead to neuronal dysfunction in Amyotrophic Lateral Sclerosis (ALS) patients. To examine mechanisms underlying ALS FUS dysfunction, we generated the first C. elegans knock-in models using CRISPR/Cas9-mediated genome editing, creating R524S and P525L ALS FUS models. Although FUS inclusions were not detected, ALS FUS animals showed defective neuromuscular function, as well as stress-induced locomotion defects. Unlike C. elegans lacking the endogenous FUS ortholog, ALS FUS animals had impaired neuronal autophagy and increased SQST-1 accumulation in ALS FUS motor neurons. Loss of sqst-1, the C. elegans ortholog for ALS-linked, autophagy adaptor protein SQSTM1/p62, suppressed both neuromuscular and stress-induced locomotion defects in ALS FUS animals, but did not suppress neuronal autophagy defects. Therefore, autophagy dysfunction is upstream of, and not dependent on, SQSTM1 function in ALS FUS pathogenesis. Combined, our findings demonstrate that autophagy dysfunction likely contributes to protein homeostasis and neuromuscular defects in ALS FUS knock-in animals.

neuroscience↗