Despite their simplicity, these worms share many neuron-specific genes with both vertebrates and invertebrates. Thus, understanding the molecular basis of behavior in C. elegans is likely to provide many insights into the behavior of more advanced organisms. Furthermore, the operational principles that underlie the worm's neural circuits may provide a library of simple behaviorally relevant computations performed by small numbers of neurons. Thus, although behavior itself may not be conserved, an understanding of computational strategies is likely to be broadly informative.
Although C. elegans contains only 302 neurons, understanding how neural activity is shaped by sensation and how it gives rise to behavior is still technically challenging. Thus, the lab focuses on developing tools that allow improved monitoring of neural activity and of behavior. To monitor behavior, the lab has created a real-time behavioral tracking system that can follow dozens of animals simultaneously. With this system, even sophisticated or stochastic behaviors can be rapidly quantified. In collaboration with the Rankin lab at the University of British Columbia, the Kerr lab has systematically surveyed mutants in proteins predicted to have functions in the nervous system. This study has allowed the Kerr and Rankin labs to identify those genes particularly important for habituation, a simple form of learning. To monitor neural activity, the lab has created a high-speed plane illumination microscope that can follow the activity of dozens of neurons simultaneously. The lab is currently using this system to investigate how the worm decides to either go forward or backward rather than attempting to do both simultaneously and to map the full sensory experience that a worm has when its chemical environment changes.
Since tools that are applicable to C. elegans are also often applicable to Drosophila larvae, the Kerr lab is also collaborating with the Zlatic lab to apply high throughput behavioral analysis and high-speed calcium imaging to Drosophila larvae.
To help meet this challenge, we develop new instruments and techniques for behavioral analysis and neural recording and apply them to the model organism with the simplest and best-characterized nervous system, Caenorhabditis elegans. We hope that this will allow us to develop key insights into the control of behavior by neural circuits and reveal the genes required for the function of these circuits. It is our expectation that these lessons can then be applied to larger organisms, where the technical challenges are greater.
We currently focus on two areas that are essential for a detailed quantitative understanding of the relationship between neuronal activity and behavior in C. elegans.
The behavior of individual worms can be quantified by computer tracking systems that follow individual animals as they move and behave. Behavior is often variable, however, so it is necessary to collect statistics from a population of dozens of individuals to gain an accurate picture of behavior. We therefore have built a tracking system that simultaneously monitors dozens of worms and automatically analyzes their behavior. Because this method is much faster than the standard semiautomated single-worm analysis methods, we are able to screen thousands of lines of potentially mutant worms for abnormal behavior. Initially, in collaboration with Catharine Rankin (University of British Columbia), we have identified a collection of genes out of approximately 700 candidates that are specifically involved in habituating to and recovering from repeated taps. Since this simple mode of learning is widespread throughout nervous systems of all animals, it is no surprise that we identified a number of genes known to be important in learning. However, we have also discovered a number of novel genes and we expect that many of them will play important roles in learning in other organsisms.
We have also collaborated with the Zlatic lab to ensure that the software is also suited for monitoring the behavior of Drosophila larvae.
The tracking software developed by the lab is freely available under an open source license (see Tools).
Adult C. elegans have only 302 neurons, half of which are located in the animal's head. To relate behavior to neural activity, we must monitor the activity of these neurons. We are developing hardware and software that allow us to rapidly construct three-dimensional movies of the worm's head. By using fluorescent probes that indicate neuronal activity, we can simultaneously monitor and quantify the activity of a large number of neurons. Due to the small size of the organism and short exposure times, the primary technical challenge lies in capturing enough photons from the sample to obtain an accurate report of neuronal activity. We hope to utilize advanced optical techniques developed by the labs of Eric Betzig, Mats Gustafsson (at Janelia Farm Research Campus), and Charles Shank as they become available. Currently, we illuminate the worm's brain with a thin sheet of light that spares all but the in-focus portion of the sample from strong illumination, and sweep this sheet through the worm's head while imaging with fast and sensitive cameras.
This imaging system allows us to monitor up to approximately two dozen neurons simultaneously; at higher densities, it becomes difficult to accurately distinguish the neurons from each other. We thus are focusing on circuits that involve an appropriate number of neurons. In particular, we are recording from the command interneurons while delivering stimuli that should make the animal intend to change direction. By studying the activity of these command interneurons, we hope to understand how the animal regulates its direction of motion and understand why the animal devotes multiple neurons to both forward and backward movement when, logically, it would seem that one forward and one reverse neuron would be adequate. We are also recording from ciliated sensory neurons in the head while applying various chemical stimuli to try to understand what chemosensory information is collected by the worm and thus can affect the worm's behavior.
Prior Publications (5)
Fast Monte Carlo Simulation Methods For Biological Reaction-Diffusion Systems in Solution and on Surfaces.SIAM Journal on Scientific Computing: A Publication of the Society for Industrial and Applied Mathematics 2008
R. A. Kerr, T. M. Bartol, B. Kaminsky, M. Dittrich, J. Chang, S. B. Baden, T. J. Sejnowski, and J. R. Stiles SIAM Journal on Scientific Computing: A Publication of the Society for Industrial and Applied Mathematics, 30:3126 (2008)
Many important physiological processes operate at time and space scales far beyond those accessible to atom-realistic simulations, and yet discrete stochastic rather than continuum methods may best represent finite numbers of molecules interacting in complex cellular spaces. We describe and validate new tools and algorithms developed for a new version of the MCell simulation program (MCell3), which supports generalized Monte Carlo modeling of diffusion and chemical reaction in solution, on surfaces representing membranes, and combinations thereof. A new syntax for describing the spatial directionality of surface reactions is introduced, along with optimizations and algorithms that can substantially reduce computational costs (e.g., event scheduling, variable time and space steps). Examples for simple reactions in simple spaces are validated by comparison to analytic solutions. Thus we show how spatially realistic Monte Carlo simulations of biological systems can be far more cost-effective than often is assumed, and provide a level of accuracy and insight beyond that of continuum methods.
Division accuracy in a stochastic model of Min oscillations in Escherichia coli.Proceedings of the National Academy of Sciences of the United States of America 2006
R. A. Kerr, H. Levine, T. J. Sejnowski, and W. Rappel Proceedings of the National Academy of Sciences of the United States of America, 103:347-52 (2006)
Accurate cell division in Escherichia coli requires the Min proteins MinC, MinD, and MinE as well as the presence of nucleoids. MinD and MinE exhibit spatial oscillations, moving from pole to pole of the bacterium, resulting in an average MinD concentration that is low at the center of the cell and high at the poles. This concentration minimum is thought to signal the site of cell division. Deterministic models of the Min oscillations reproduce many observed features of the system, including the concentration minimum of MinD. However, there are only a few thousand Min proteins in a bacterium, so stochastic effects are likely to play an important role. Here, we show that Monte Carlo simulations with a large number of proteins agree well with the results from a deterministic treatment of the equations. The location of minimum local MinD concentration is too variable to account for cell division accuracy in wild type but is consistent with the accuracy of cell division in cells without nucleoids. This finding confirms the need to include additional mechanisms, such as reciprocal interactions with the cell division ring or positioning of the nucleoids, to explain wild-type accuracy.
In the nematode C. elegans, genes encoding components of a putative mechanotransducing channel complex have been identified in screens for light-touch-insensitive mutants. A long-standing question, however, is whether identified MEC proteins act directly in touch transduction or contribute indirectly by maintaining basic mechanoreceptor neuron physiology. In this study, we used the genetically encoded calcium indicator cameleon to record cellular responses of mechanosensory neurons to touch stimuli in intact, behaving nematodes. We defined a gentle touch sensory modality that adapts with a time course of approximately 500 ms and primarily senses motion rather than pressure. The DEG/ENaC channel subunit MEC-4 and channel-associated stomatin MEC-2 are specifically required for neural responses to gentle mechanical stimulation but do not affect the basic physiology of touch neurons or their in vivo responses to harsh mechanical stimulation. These results distinguish a specific role for the MEC channel proteins in the process of gentle touch mechanosensation.
Two methods for rapid characterization of molecular shape are presented. Both techniques are based on the density of atoms near the molecular surface. The Fast Atomic Density Evaluation (FADE) algorithm uses fast Fourier transforms to quickly estimate densities. The Pairwise Atomic Density Reverse Engineering (PADRE) method derives modified density measures from the relationship between atomic density and total potentials. While many shape-characterization techniques define shape relative to a surface, the descriptors returned by FADE and PADRE can measure local geometry from points within the three-dimensional space surrounding a molecule. The methods can be used to find crevices and protrusions near the surface of a molecule and to test shape complementarity at the interface between docking molecules.
Electrophysiology and optical indicators have been used in vertebrate systems to investigate excitable cell firing and calcium transients, but both techniques have been difficult to apply in organisms with powerful reverse genetics. To overcome this limitation, we expressed cameleon proteins, genetically encoded calcium indicators, in the pharyngeal muscle of the nematode worm Caenorhabditis elegans. In intact transgenic animals expressing cameleons, fluorescence ratio changes accompanied muscular contraction, verifying detection of calcium transients. By comparing the magnitude and duration of calcium influx in wild-type and mutant animals, we were able to determine the effects of calcium channel proteins on pharyngeal calcium transients. We also successfully used cameleons to detect electrically evoked calcium transients in individual C. elegans neurons. This technique therefore should have broad applications in analyzing the regulation of excitable cell activity in genetically tractable organisms.