Biology subjects

Webster, B. M.

Publications and source records attributed to Webster, B. M..

3 recordsLinked to original sources

bioRxiv2023

Germline mitochondria integrate neuronal cell nonautonomous signaling for the mitochondrial unfolded protein response

The ability of mitochondria to coordinate stress responses across tissues is critical for health. In C. elegans, neurons experiencing mitochondrial stress elicit an inter-tissue signaling pathway through the release of mitokine signals, such as serotonin or the WNT ligand EGL-20, which activate the mitochondrial unfolded protein response (UPRMT) in the periphery to promote organismal health and lifespan. We find that germline mitochondria play a surprising role in neuron-to-peripheral UPRMT signaling. Specifically, we find that germline mitochondria signal downstream of neuronal mitokines, like WNT and serotonin, and upstream of lipid metabolic pathways in the periphery to regulate UPRMT activation. We also find that the germline tissue itself is essential in UPRMT signaling. We propose that the germline has a central signaling role in coordinating mitochondrial stress responses across tissues, and germline mitochondria play a defining role in this coordination because of their inherent roles in germline integrity and inter-tissue signaling.

genetics↗

bioRxiv2023

A data-driven evaluation of Arabidopsis-centric research and the model species concept

The selection of Arabidopsis as a model organism played a pivotal role in advancing genomic science, firmly establishing the cornerstone of today s plant molecular biology. Competing frameworks to select an agricultural- or ecological-based model species, or to decentralize plant science and study a multitude of diverse species, were selected against in favor of building core knowledge in a species that would facilitate genome-enabled research that could assumedly be transferred to other plants. Here, we examine the ability of models based on Arabidopsis gene expression data to predict tissue identity in other flowering plant species. Comparing different machine learning algorithms, models trained and tested on Arabidopsis data achieved near perfect precision and recall values using the K-Nearest Neighbor method, whereas when tissue identity is predicted across the flowering plants using models trained on Arabidopsis data, precision values range from 0.69 to 0.74 and recall from 0.54 to 0.64, depending on the algorithm used. Below-ground tissue is more predictable than other tissue types, and the ability to predict tissue identity is not correlated with phylogenetic distance from Arabidopsis. This suggests that gene expression signatures rather than marker genes are more valuable to create models for tissue and cell type prediction in plants. Our data-driven results highlight that, in hindsight, the assertion that knowledge from Arabidopsis is translatable to other plants is not always true. Considering the current landscape of abundant sequencing data and computational resources, it may be prudent to reevaluate the scientific emphasis on Arabidopsis and to prioritize the exploration of plant diversity.

plant biology↗

bioRxiv2022

Lipid homeostasis is essential for a maximal ER stress response

Changes in lipid metabolism are associated with aging and age-related diseases, including proteopathies. The endoplasmic reticulum (ER) is uniquely a major hub for protein and lipid synthesis, making its function essential for both protein and lipid homeostasis. However, it is less clear how lipid metabolism and protein quality may impact each other. Here, we identity let-767, a putative hydroxysteroid dehydrogenase, as an essential gene for both lipid and ER protein homeostasis. Knockdown of let-767 reduces lipid stores, alters ER morphology in a lipid-dependent manner, and also blocks induction of the Unfolded Protein Response of the ER (UPRER). Interestingly, a global reduction in lipogenic pathways restores UPRER induction in animals with reduced let-767. Specifically, we find that supplementation of 3-oxoacyl, the predicted metabolite directly upstream of let-767, is sufficient to block induction of the UPRER. This study highlights a novel interaction through which changes in lipid metabolism can alter a cells response to protein-induced stress.

cell biology↗