Tanimoto, H. | bioRxiv Science

bioRxiv2018

MECHANOSENSATION DYNAMICALLY COORDINATES POLAR GROWTH AND CELL WALL ASSEMBLY TO PROMOTE CELL SURVIVAL

How growing cells cope with size expansion while ensuring mechanical integrity is not known. In walled cells, such as those of microbes and plants, growth and viability are both supported by a thin and rigid encasing cell wall (CW). We deciphered the dynamic mechanisms controlling wall surface assembly during cell growth, using a novel sub-resolution microscopy approach to monitor CW thickness in live rod-shaped fission yeast cells. We found that polar cell growth yielded wall thinning, and that thickness negatively influenced growth. Thickness at growing tips exhibited oscillating behavior with thickening phases followed by thinning phases, indicative of a delayed feedback promoting thickness homeostasis. This feedback was mediated by mechanosensing through the cell wall integrity pathway, which probes strain in the wall to adjust synthase localization and activity to surface growth. Mutants defective in thickness homeostasis lysed by rupturing the wall demonstrating its essential role for walled cell survival.

cell biology↗

bioRxiv2018

Data-driven analysis of motor activity implicated 5-HT2A neurons in backward locomotion of larval Drosophila

Rhythmic animal behaviors are regulated in part by neural circuits called the central pattern generators (CPGs). Classifying neural population activities correlated with body movements and identifying the associated component neurons are critical steps in understanding CPGs. Previous methods that classify neural dynamics obtained by dimension reduction algorithms often require manual optimization which could be laborious and preparation-specific. Here, we present a simpler and more flexible method that is based on the pre-trained convolutional neural network model VGG-16 and unsupervised learning, and successfully classifies the fictive motor patterns in Drosophila larvae under various imaging conditions. We also used voxel-wise correlation mapping to identify neurons associated with motor patterns. By applying these methods to neurons targeted by 5-HT2A-GAL4, which we generated by the CRISPR/Cas9-system, we identified two classes of interneurons, termed Seta and Leta, which are specifically active during backward but not forward fictive locomotion. Optogenetic activation of Seta and Leta neurons increased backward locomotion. Conversely, thermogenetic inhibition of 5-HT2A-GAL4 neurons or application of a 5-HT2 antagonist decreased backward locomotion induced by noxious light stimuli. This study establishes an accelerated pipeline for activity profiling and cell identification in larval Drosophila and implicates the serotonergic system in the modulation of backward locomotion.

neuroscience↗