Biology subjects

Ness-Cohn, E.

Publications and source records attributed to Ness-Cohn, E..

3 recordsLinked to original sources

bioRxiv2022

Benzimidazoles cause lethality by inhibiting the function of Caenorhabditis elegans neuronal beta-tubulin

Parasitic nematode infections cause an enormous global burden to both human and livestock populations. Resistance to the limited arsenal of anthelmintic drugs used to combat these infections is widespread, including resistance to benzimidazole (BZ) compounds commonly found in livestock parasites. Previous studies using the free-living nematode Caenorhabditis elegans to model parasitic nematode resistance have shown that loss-of-function mutations in the beta-tubulin gene ben-1 confer resistance to BZ drugs. However, the mechanism of resistance and the tissue-specific susceptibility are not well known in any nematode species. To identify in which tissue(s) ben-1 function underlies BZ susceptibility, transgenic strains that express ben-1 in different tissues, including hypodermis, muscles, neurons, intestine, and ubiquitous expression were generated. High-throughput fitness assays were performed to measure and compare the quantitative responses to BZ compounds among different transgenic lines. Significant BZ susceptibility was observed in animals expressing ben-1 in neurons, comparable to expression using the ben-1 promoter. This result suggests that ben-1 function in neurons underlies susceptibility to BZ. Subsetting neuronal expression of ben-1 based on neurotransmitter system further restricted ben-1 function in cholinergic neurons to cause BZ susceptibility. These results better inform our current understanding of the cellular mode of action of BZ and also suggest additional treatments that might potentiate the effects of BZs. HighlightsO_LIExpressing wild-type ben-1 only in neurons restores susceptibility to benzimidazoles C_LIO_LIExpression of ben-1 in cholinergic neurons restores susceptibility to benzimidazoles C_LIO_LIGABAergic neurons might also play a role in benzimidazole sensitivity C_LIO_LIBroad implications for molecular mechanisms of benzimidazole mode of action C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC="FIGDIR/small/500991v1_ufig1.gif" ALT="Figure 1"> View larger version (23K): org.highwire.dtl.DTLVardef@161cbb7org.highwire.dtl.DTLVardef@18578cforg.highwire.dtl.DTLVardef@1be80aaorg.highwire.dtl.DTLVardef@1f15236_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2020

TimeCycle: Topology Inspired MEthod for the Detection of Cycling Transcripts in Circadian Time-Series Data

MotivationThe circadian rhythm drives the oscillatory expression of thousands of genes across all tissues. The recent revolution in high-throughput transcriptomics, coupled with the significant implications of the circadian clock for human health, has sparked an interest in circadian profiling studies to discover genes under circadian control. ResultWe present TimeCycle: a topology-based rhythm detection method designed to identify cycling transcripts. For a given time-series, the method reconstructs the state space using time-delay embedding, a data transformation technique from dynamical systems theory. In the embedded space, Takens theorem proves that the dynamics of a rhythmic signal will exhibit circular patterns. The degree of circularity of the embedding is calculated as a persistence score using persistent homology, an algebraic method for discerning the topological features of data. By comparing the persistence scores to a bootstrapped null distribution, cycling genes are identified. Results in both synthetic and biological data highlight Time-Cycles ability to identify cycling genes across a range of sampling schemes, number of replicates, and missing data. Comparison to competing methods highlights their relative strengths, providing guidance as to the optimal choice of cycling detection method. Availability and ImplementationA fully documented open-source R package implementing Time-Cycle is available at: https://nesscoder.github.io/TimeCycle/.

bioinformatics↗

bioRxiv2020

TimeTrial: An Interactive Application for Optimizing the Design and Analysis of Transcriptomic Times-Series Data in CircadianBiology Research

The circadian rhythm drives the oscillatory expression of thousands of genes across all tissues, coordinating physiological processes. The effect of this rhythm on health has generated increasing interest in discovering genes under circadian control by searching for periodic patterns in transcriptomic time-series experiments. While algorithms for detecting cycling transcripts have advanced, there remains little guidance quantifying the effect of experimental design and analysis choices on cycling detection accuracy. We present TimeTrial, a user-friendly benchmarking framework using both real and synthetic data to investigate cycle detection algorithms performance and improve circadian experimental design. Results show that the optimal choice of analysis method depends on the sampling scheme, noise level, and shape of the waveform of interest; and provides guidance on the impact of sampling frequency and duration on cycling detection accuracy. The TimeTrial software is freely available for download and may also be accessed through a web interface. By supplying a tool to vary and optimize experimental design considerations, TimeTrial will enhance circadian transcriptomics studies.

bioinformatics↗