Neurons convert synaptic or sensory inputs into cellular outputs. It is not well understood how a single neuron senses, processes multiple stimuli, and generates distinct neuronal outcomes. Here, we describe the mechanism by which the C. elegans PVD neurons sense two mechanical stimuli: external touch and proprioceptive body movement. These two stimuli are detected by distinct mechanosensitive DEG/ENaC/ASIC channels, which trigger distinct cellular outputs linked to mechanonociception and proprioception. Mechanonociception depends on DEGT-1 and activates PVD's downstream command interneurons through its axon, while proprioception depends on DEL-1, UNC-8, and MEC-10 to induce local dendritic Ca 2+ increase and dendritic release of a neuropeptide NLP-12. NLP-12 directly modulates neuromuscular junction activity through the cholecystokinin receptor homolog on motor axons, setting muscle tone and movement vigor. Thus, the same neuron simultaneously uses both its axon and dendrites as output apparatus to drive distinct sensorimotor outcomes.

A new automated microfluidic platform can deliver a wide range of mechanical stimuli for functional neural imaging in C. elegans.

Spinal muscular atrophy (SMA) is a degenerative disorder that selectively deteriorates motor neurons due to a deficiency of survival motor neuron protein (SMN). The illness is the leading genetic cause of death in infants and is difficult to study in complex biological systems such as humans. A simpler model system, such as the nematode C. elegans, can be used to study potential mechanisms underlying this disease; C. elegans expresses the smn-1 gene, a homologue of SMN; powerful genetic tools in C. elegans research can be used to discover novel genes whose effect on SMN remains unknown or uncharacterized. Currently, conventional screening methods are time-consuming and laborious, as well as being subjective and mostly qualitative. To address these issues, we engineer an automated system capable of performing genetic suppressor screens on C. elegans using microfluidics in combination with custom image analysis software. We demonstrate the utility of this system by isolating 21 alleles that significantly suppress motor neuron degeneration at a screening rate of approximately 300 worms per hour. Many of these mutants also have improved motor function. These isolated alleles can potentially be further studied to understand mechanisms of protection against neurodegeneration. Our system is easily adaptable, providing a means to saturate screens not only implicated in the smn-1 pathway, but also for genes involved in other neurodegenerative phenotypes.

As animals navigate through complex environments, they must integrate the activity of multiple mechanoreceptors, sensing forces throughout their bodies and allowing them to move in appropriate directions. In Caenorhabditis elegans, the only organism with a fully mapped connectome, the neural circuit involved in mechanosensation is well characterized. Although the general roles of the neurons in this circuit have been defined, most studies involve experiments with a small number of unnatural stimuli, leading to quantitative descriptions that may be biased towards the tested stimuli. In this work, we elucidate unbiased descriptions of the mechanosensory system in C. elegans by using reverse correlation analysis. We use a custom tracking and optogenetics platform to characterize and compare two mechanosensory systems in C. elegans: the gentle touch sensing TRNs and harsh touch sensing PVDs. This method yields linear filters that capture dynamics that are consistent with previous findings, as well as providing new insights on the spatial encoding of the TRN and PVD neurons. Our results suggest that the tiled network of the TRNs allow for spatial encoding with better resolution than PVD. Additionally, linearnonlinear models accurately predict behavioral responses based only on sensory neuron activity. Our results capture the overall dynamics of behavior induced by the activation of sensory neurons, providing simple transformations that fully characterize these systems.

The force-induced unfolding and refolding of proteins is speculated to be a key mechanism in the sensing and transduction of mechanical signals in the living cell. Yet, little evidence has been gathered for its existence in vivo. Prominently, stretch-induced unfolding is postulated to be the activation mechanism of the twitchin/titin family of autoinhibited sarcomeric kinases linked to the mechanical stress response of muscle. To test the occurrence of mechanical kinase activation in living working muscle, we generated transgenic C. elegans expressing twitchin containing FRET moieties flanking the kinase domain and developed a quantitative technique for extracting FRET signals in freely moving C. elegans, using tracking and simultaneous imaging of animals in three channels (donor fluorescence, acceptor fluorescence, and transmitted light). Computer vision algorithms were used to extract fluorescence signals and muscle contraction states in each frame, in order to obtain fluorescence and body curvature measurements with spatial and temporal precision in vivo. The data revealed statistically significant periodic changes in FRET signals during muscle activity, consistent with a periodic change in the conformation of twitchin kinase. We conclude that stretch-unfolding of twitchin kinase occurs in the active muscle, whereby mechanical activity titrates the signalling pathway of this cytoskeletal kinase. We anticipate that the methods we have developed here could be applied to obtaining in vivo evidence for force-induced conformational changes or elastic behavior of other proteins not only in C. elegans but in other animals in which there is optical transparency (e.g zebrafish).

Animals must integrate the activity of multiple mechanoreceptors to navigate complex environments. In Caenorhabditis elegans, the general roles of the mechanosensory neurons have been defined, but most studies involve end-point or single-time-point measurements, and thus lack dynamic information. Here, we formulate a set of unbiased quantitative characterizations of the mechanosensory system by using reverse correlation analysis on behavior. We use a custom tracking, selective illumination, and optogenetics platform to compare two mechanosensory systems: the gentle-touch (TRNs) and harsh-touch (PVD) circuits. This method yields characteristic linear filters that allow for the prediction of behavioral responses. The resulting filters are consistent with previous findings and further provide new insights on the dynamics and spatial encoding of the systems. Our results suggest that the tiled network of the gentle-touch neurons has better resolution for spatial encoding than the harsh-touch neurons. Additionally, linear-nonlinear models can predict behavioral responses based only on sensory neuron activity. Our results capture the overall dynamics of behavior induced by the activation of sensory neurons, providing simple transformations that quantitatively characterize these systems. Furthermore, this platform can be extended to capture the behavioral dynamics induced by any neuron or other excitable cells in the animal.

The use of lab-on-chip tools has been adopted in a wide variety of scientific fields. Hundreds of applications that speed up, miniaturize, or enable otherwise unfeasible assays have emerged in the last couple of decades [1,2]. The microfluidic toolbox offers several advantages which make it a very attractive resource for biological studies: reduced sample volume, control of spatiotemporal chemical compositions, streamlined assays, precise and predictable fluid flow regimes, portability, and integration with sensors, actuators, controllers, and automation systems [1][2][3]. The main drive of the field has thus far focused on the development of microfluidic tools that replace conventional methods with proof-ofprinciple applications. However, widespread adoption of these technologies for fundamental research is still in progress. Microfluidics has nonetheless had a significant impact in fundamental biological studies with model organisms [4,5]. In this article, we provide an overview of the current state of the field, the impacts of microfluidics in model organism research, and the outlook, challenges, and opportunities for the future.

No abstract