Versatile multiple object tracking in sparse 2D/3D videos via deformable image registration.

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.

Modulation of sensory perception by hydrogen peroxide enables Caenorhabditis elegans to find a niche that provides both food and protection from hydrogen peroxide.

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.

Interneuron control of C. elegans developmental decision-making.

Natural environments are highly dynamic, and this complexity challenges animals to accurately integrate external cues to shape their responses. Adaptive developmental plasticity enables organisms to remodel their physiology, morphology, and behavior to better suit the predicted future environment and ultimately enhance their ecological success.1 Understanding how an animal generates a neural representation of current and forecasted environmental conditions and converts these circuit computations into a predictive adaptive physiological response may provide fundamental insights into the molecular and cellular basis of decision-making over developmentally relevant timescales. Although it is known that sensory cues usually trigger the developmental switch and that downstream inter-tissue signaling pathways enact the alternative developmental phenotype, the integrative neural mechanisms that transduce external inputs into effector pathways are less clear.2,3 In adverse environments, Caenorhabditis elegans larvae can enter a stress-resistant diapause state with arrested metabolism and reproductive physiology.4 Amphid sensory neurons feed into both rapid chemotactic and short-term foraging mode decisions, mediated by amphid and pre-motor interneurons, as well as the long-term diapause entry decision. Here, we identify amphid interneurons that integrate pheromone cues and propagate this information via a neuropeptidergic pathway 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 pheromones. FLP-2 signaling is inhibited by upstream glutamatergic transmission via the metabotropic receptor MGL-1 and mediated by the broadly expressed neuropeptide G-protein-coupled receptor NPR-30. Thus, metabotropic signaling allows the reuse of parts of a sensory system for a decision with a distinct timescale.