Hydrogen peroxide (H2O2) is the most common chemical threat that organisms face. Here, we show that H2O2 alters the bacterial food preference of Caenorhabditis elegans, enabling the nematodes to find a safe environment with food. H2O2 induces the nematodes to leave food patches of laboratory and microbiome bacteria when those bacterial communities have insufficient H2O2-degrading capacity. The nematode’s behavior is directed by H2O2-sensing neurons that promote escape from H2O2 and by bacteria-sensing neurons that promote attraction to bacteria. However, the input for H2O2-sensing neurons is removed by bacterial H2O2-degrading enzymes and the bacteria-sensing neurons’ perception of bacteria is prevented by H2O2. The resulting cross-attenuation provides a general mechanism that ensures the nematode’s behavior is faithful to the lethal threat of hydrogen peroxide, increasing the nematode’s chances of finding a niche that provides both food and protection from hydrogen peroxide.

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Tracking body parts in behaving animals, extracting fluorescence signals from cells embedded in deforming tissue, and analyzing cell migration patterns during development all require tracking objects with partially correlated motion. As dataset sizes increase, manual tracking of objects becomes prohibitively inefficient and slow, necessitating automated and semi-automated computational tools. Unfortunately, existing methods for multiple object tracking (MOT) are either developed for specific datasets and hence do not generalize well to other datasets, or require large amounts of training data that are not readily available. This is further exacerbated when tracking fluorescent sources in moving and deforming tissues, where the lack of unique features and sparsely populated images create a challenging environment, especially for modern deep learning techniques. By leveraging technology recently developed for spatial transformer networks, we propose ZephIR, an image registration framework for semi-supervised MOT in 2D and 3D videos. ZephIR can generalize to a wide range of biological systems by incorporating adjustable parameters that encode spatial (sparsity, texture, rigidity) and temporal priors of a given data class. We demonstrate the accuracy and versatility of our approach in a variety of applications, including tracking the body parts of a behaving mouse and neurons in the brain of a freely moving C. elegans. We provide an open-source package along with a web-based graphical user interface that allows users to provide small numbers of annotations to interactively improve tracking results.

SUMMARYAnimals integrate external stimuli to shape their physiological responses throughout development. In adverse environments, Caenorhabditis elegans larvae can enter a stress-resistant diapause state with arrested metabolism and reproductive physiology. Amphid sensory neurons feed into both rapid chemotactic and short-term foraging mode decisions, mediated by amphid and premotor interneurons, as well as the long-term diapause decision. We identify amphid interneurons that integrate pheromone cues and propagate this information via a neuropeptidergic pathways to influence larval developmental fate, bypassing the pre-motor system. AIA interneuron-derived FLP-2 neuropeptide signaling promotes reproductive growth and AIA activity is suppressed by pheromone. FLP-2 acts antagonistically to the insulin-like INS-1. FLP-2’s growth promoting effects are inhibited by upstream metabotropic glutamatergic signaling and mediated by the broadly-expressed neuropeptide receptor NPR-30. Conversely, the AIB interneurons and their neuropeptide receptor NPR-9/GALR2 promote diapause entry. These neuropeptidergic outputs allow reuse of parts of a sensory system for a decision with a distinct timescale.

Hydrogen peroxide (H2O2) is the most common chemical threat that organisms face. Here, we show that H2O2 alters the bacterial food preference of Caenorhabditis elegans, enabling the nematodes to find a safe environment with food. H2O2 induces the nematodes to leave food patches of laboratory and microbiome bacteria when those bacterial communities have insufficient H2O2-degrading capacity. The nematode's behavior is directed by H2O2-sensing neurons that promote escape from H2O2 and by bacteria-sensing neurons that promote attraction to bacteria. However, the input for H2O2-sensing neurons is removed by bacterial H2O2-degrading enzymes and the bacteria-sensing neurons' perception of bacteria is prevented by H2O2. The resulting cross-attenuation provides a general mechanism that ensures the nematode's behavior is faithful to the lethal threat of hydrogen peroxide, increasing the nematode's chances of finding a niche that provides both food and protection from hydrogen peroxide.