Laura Bianchi et al. (2006) Neuronal Development, Synaptic Function, and Behavior Meeting "Uncovering the Role of MIP-1, a Novel Protein That Interacts With DEG/ENaC Channel Subunits MEC-4 and UNC-8, in Mechanosensory Behaviors"

Lyudmila Kotlyanskaya, Laura Bianchi, Monica Driscoll, ShiLiang Wang

[Neuronal Development, Synaptic Function, and Behavior Meeting, 2006]

MEC-4 and UNC-8 are members of the DEG/ENaC family of Na+/Ca2+ channels that mediate mechanosensory behaviors in C. elegans. mec-4 is exclusively expressed in six touch-sensing neurons and mediates gentle body touch sensation and unc-8 is expressed in sensory, motor and interneurons where it is suggested to function as a stretch-sensitive channel. Both MEC-4 and UNC-8 function as parts of multimeric channel complexes in which additional proteins serve as accessory subunits to regulate permeation properties and channel gating. For example, genetic and functional studies showed that MEC-4 interacts with stomatin-like proteins MEC-2 and UNC-24, and paraoxonase-like protein MEC-6. MEC-2 and MEC-6 exert positive regulation of MEC-4 channel function by increasing channel conductance and/or open probability, whereas UNC-24 suppresses channel activity. In addition, MEC-2 participates in determining channel permeability properties. Similarly, genetic studies suggest that UNC-8 coassembles with, and is regulated by, stomatin-like proteins UNC-1 and UNC-24. Although genetic screens have contributed enormously to our understanding of mechanotransducing complexes, these screens can miss redundant genes or genes that affect behaviors or processes other than touch or stretch sensation. To identify other potential MEC-4 interacting proteins, we performed a Yeast-Two-Hybrid Screen using MEC-4 N-terminus as bait. We identified four novel MEC-4 Interacting Proteins (MIPs) and we focus here on MIP-1. MIP-1, which has a human homolog, interacts in the yeast two-hybrid and in in vitro with MEC-4 and UNC-8 N-termini. mip-1 deletion (mip-1(Delta)) mutants display abnormal response to touch. mip-1 mutants are sensitive to touch, but they "faint" (seize all movement) soon after being touched. Interestingly, we found that unc-8(n491n1193) mutants display a similar but not identical "fainting" phenotype. Moreover, we observed in both mutants abnormal movement on agar and in liquid media. We present here extensive characterization of the mip-1(Delta) mutant phenotype and comparison with the unc-8(n491n1193) phenotype. We also describe the mip-1 expression pattern and functional effect on DEG/ENaC channels expressed in Xenopus oocytes. Based on our findings, we propose a model in which MIP-1 functions as an accessory subunit of channel complexes formed by MEC-4 and UNC-8.

Gavriil Tsechpenakis et al. (2006) Neuronal Development, Synaptic Function, and Behavior Meeting "LocoWorm: A Program for Multiple Worms Tracking and Locomotion Features Extraction"

Laura Bianchi, Dimitris Metaxas, Monica Driscoll, Gavriil Tsechpenakis, Lyudmila Kotlyanskaya

[Neuronal Development, Synaptic Function, and Behavior Meeting, 2006]

Tracking deformable objects from videos, in low resolution and clutter, is an open issue in Computer Vision. Our method aims at simultaneously tracking many worms moving in a plate (swimming or crawling), often touching and occluding each other (in contrast to most existing methods that track only a single worm), and extracts the worms' locomotion parameters, both global (such as positions and movement paths) and local (magnitude of inter-frame deformations, shapes, normal and directional speeds, symmetry of deformations etc.), in contrast to commercial programs that can only provide global parameters. In our approach, "tracking" means not only the estimation of the size and position of each worm on the image plane (e.g. bounding box), but also the extraction of the exact shape of each worm. The main advantages of our approach are that enables researchers to collect more locomotion data accurately and automatically, sufficient for statistical analysis, and provides locomotion parameters over time, in terms of both displacements on the image plane (global features) and local deformations (local features). After tracking, our method is capable of estimating: (a) global motion features, such as: the positions on the image plane, movement paths over time, and distances covered, the number of frames that worms remain static, (b) local locomotion features, such as magnitude ("strength") and shape of inter-frame deformations,& magnitude and symmetry of ("absolute") deformation (compared to the straight line connecting the two ends of a worm), normal and directional speeds of movement, and (c) changes, averages, statistics of the local and global locomotion features. The aim of our method is to extract motion parameters that can be used for classifying worms according to their motion/swimming ability for behavioral and aging studies. In the near future, we plan to make the source code of our program available to the research community as a free web-download. The website can be found at: http://www.research.rutgers.edu/~gabrielt/locoworm.html.