Physical and digital books, media, journals, archives, and databases.
Results include
  1. The influence of tissue mechanics and mechano-electrical transduction channel distribution on somatosensory mechanotransduction in Caenorhabditis elegans

    Katta, Samata
    [Stanford, California] : [Stanford University], 2019.

    Neurons that sense mechanical stimuli - the touch of a feather, the vibration of your phone, the sound of music, the stretch in your muscles during exercise - come in a variety of shapes and rely on a broad assortment of mechanosensitive ion channels to transduce force into electrical activity. As diverse as the ion channels and morphologies of these neurons may be, so too are the mechanical properties of the tissues that surround these cells and shape the forces that reach their mechanoreceptors. Yet the similarity of neural responses hints at common principles that govern how these neurons respond to stimuli within their native environments. Although studying mechanosensory neurons within their native environments is often difficult, the relatively simple architecture of the touch receptor neurons (TRNs) in the roundworm Caenorhabditis elegans provides a tractable model for identifying these principles. In this thesis, I integrate experimental and computational methods to investigate how tissue mechanics and the subcellular localization of mechano-electrical transduction (MeT) channels affect somatosensory mechanotransduction, and lay out three principles applicable to most if not all mechanosensory systems in animals. The first commonality between mechanosensory systems is that tissues and subcellular structures that transmit force to MeT channels act as filters to determine the temporal dynamics and adaptation characteristics of the neuron's response. To investigate how the worm body filters the force applied to it, we built a system for fast mechanical stimulation of TRNs during in vivo whole-cell patch-clamp recording. We recorded mechanoreceptor currents (MRCs) in TRNs while indenting hermaphrodite worms at high speeds and frequencies, and compared the experimental results with simulated results from a biophysical model combining body mechanics and channel gating. We find that the rapidly-adapting MRCs display velocity-dependence and that the worm body acts as a high-pass filter. The model predicts that the velocity-dependence of these currents would also depend on the internal pressure of the worm, which contributes to the stiffness of the body. We also examine the effect of changing the composition and mechanical properties of the TRN plasma membrane by removing arachidonic acid, and find that activation of MRCs appears to be faster. The second principle we see is that the spatial patterns of MeT channel localization within a neuron determine what forces they are exposed to, and the aggregate activity of their individual, varied responses is what determines the response of the neuron. In the TRNs, the MeT channels are distributed along the neurite, and we show that the ability of channels to be opened by stimuli is related to the size and position of the stimulus relative to the channels. Using the computational model, we show that both indentation and speed likely affect not only the open probabilities of individual channels but also the total number of channels that are recruited based on each channel's distance from the stimulus. Lastly, anisotropy and viscoelasticity in the encapsulating tissues can lead to asymmetrical transmission of force, and determine the direction selectivity of neurons. We find asymmetry between TRN responses at the onset and offset of stimuli that can be explained partly by asynchronous recruitment due to the spatial arrangement of channels, and partially by viscoelasticity in the tissue. The three principles illustrated here by the responses of C. elegans touch receptor neurons are also apparent in mechanosensory systems ranging from Pacinian corpuscles (where the lamella act as a high-pass filter) to Merkel cell touch domes (where channels are distributed across branched nerve endings) to Aδ-LTMRs that innervate body hairs (which respond more strongly to hair motion away from the body). Although mechanosensory neurons such as these diverge in appearance and function, their responses rely on how mechanical filtering and asymmetric force transfer through their encapsulating tissues interacts with the spatial organization of transduction channels.

Guides

Course- and topic-based guides to collections, tools, and services.
No guide results found... Try a different search

Library website

Library info; guides & content by subject specialists
No website results found... Try a different search

Exhibits

Digital showcases for research and teaching.
No exhibits results found... Try a different search

EarthWorks

Geospatial content, including GIS datasets, digitized maps, and census data.
No earthworks results found... Try a different search

More search tools

Tools to help you discover resources at Stanford and beyond.