September 2006 - August 2013
How does an organism compute its behavior? The Kerr lab seeks to answer this question for one of the simplest model organisms, the nematode worm Caenorhabditis elegans.
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.
Understanding how the collective activity of neurons gives rise to behavior is one of the great challenges for biology in this century. This task is especially daunting because it is difficult both to quantify behavior precisely and to monitor the activity of neurons relevant to a particular behavior.
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.
Population-wide Behavioral Quantification
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).
Advanced Volumetric Microscopy
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 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.