The idea that worms can be seen as waveforms has allowed scientists at Rice University’s Zhong Lab in Houston to find new links in gene networks that control movement.
The work led by Rice Assistant Professor of Biochemistry and Cell Biology Weiwei Zhong, which will appear online this week in the Proceedings of the National Academy of Sciences Early Edition, involves analyzing video records of the movement of thousands of mutant worms of the species Caenorhabditis elegans to identify the neuronal pathways that drive locomotion.
A Rice U. release notes that one result was discovery by the researchers of 87 genes that, when inactivated, caused movement defects in worms. Fifty of those genes had never been associated with such defects, with 37 having known implications in human diseases. Another discovery was the existence of several network modules among these genes. One module detects environmental conditions. Another resides in all “excitable cells” – those types that respond to electrical signals — in the worm’s neurons, muscles and digestive tracts. Another coordinates signals in the motor neurons. The team also uncovered new details about a protein-signaling pathway found in all animals. The National Institutes of Health, the Searle Scholar Program and HHMI supported the research.
In the PNAS paper, entitled “Systematic profiling of Caenorhabditis elegans locomotive behaviors reveals additional components in G-protein – Gaq signaling,” First authors Boanerges Aleman-Meza, a research scientist in Dr. Zhong’s lab, and Hui Yu, a former postdoctoral researcher now at Baylor College of Medicine; and co-authors former Rice postdoctoral researcher Marta Labocha; CalTech research technicians also associated with the Howard Hughes Medical Institute (HHMI) Shahla Gharib and Christopher Cronin; and Paul Sternberg, the Thomas Hunt Morgan Professor of Biology at CalTech and an HHMI investigator; note that Genetic screens have been widely applied to uncover genetic mechanisms of movement disorders. However, most screens rely on human observations of qualitative differences. In their paper they demonstrate the application of an automatic imaging system to conduct a quantitative screen for genes regulating the locomotive behavior in Caenorhabditis elegans.
Two hundred twenty-seven neuronal signaling genes with viable homozygous mutants were selected for the study, and the researchers tracked and recorded each animal for 4 minutes, and analyzed over 4,400 animals of 239 genotypes to obtain a quantitative, 10-parameter behavioral profile for each genotype. The worms were filmed one at a time. Each was placed in a petri dish (seeded with E. coli bacteria for food) on a motorized platform and filmed by a computer-controlled camera/microscope. The computer re-centered the camera on the worms any time they moved near the edge of the camera’s field of view. It took nearly a year to capture all 4,400 mutants in motion.
Researchers at Rice University looked at 13 points of moving mutant worms when measuring 10 parameters — amplitude, flex, frequency, velocity and wavelength, both forward and backward — to learn about the gene networks that control their locomotion.
Credit: Zhong Lab/Rice University
The researchers analyzed at least 10 worms of each mutant type to see if their particular mutations caused the animals to move in similar ways, which, for the most part, they did. Then they analyzed all mutant data to see whether different mutants move in similar ways. “If they have the same symptoms, then we think these genes are probably involved in the same disorder,” Dr. Zhong said.
The Zhong Lab research team discovered 87 genes whose inactivation causes movement defects, including 50 genes that had never been associated with locomotive defects. Computational analysis of the high-content behavioral profiles predicted 370 genetic interactions among these genes, while network partition revealed several functional modules regulating locomotive behaviors, including sensory genes that detect environmental conditions, genes that function in multiple types of excitable cells, and genes in the signaling pathway of the G protein Gaq, a protein that is essential for animal life and behavior.
The Rice researchers developed quantitative epistasis analysis methods to analyze the locomotive profiles and validated the prediction of the isoform of phospholipase C as a component in the Gaq pathway. These results provided a system-level understanding of how neuronal signaling genes coordinate locomotive behaviors, and also demonstrated the power of quantitative approaches in genetic studies.
Dr. Zhong, who is also a member of the Institute of Biosciences and Bioengineering and the Systems, Synthetic, and Physical Biology program at Rice notes in the release that the study is the first to provide a system-level understanding of how neuronal signaling genes coordinate movement and shows the value of a quantitative approach to genetic studies, and says the approach could be useful in studies of gene-to-drug or drug-to-drug interactions.
“What made the research possible is the fact that cameras and computers are able to see variations in movement that are too small for eyes and minds to notice, says Dr. Zhong. “The idea is that if a gene is required for maintaining normal movement and we pick a mutant, the computer should be able to detect the defects. I’m very observant, and I thought I could tell the worms with abnormal behaviors. I was surprised to see there were so many things I missed that the computer picked up.”
Dr. Zhong notes that the computer tracked 13 points along the length of each worm to analyze 10 parameters of its sine wave-like movement: velocity, flex, frequency, amplitude and wavelength, both forward and backward. “Some moved slower; some moved faster; some had exaggerated body bends. But in our database, it all turns into numbers to describe the abnormalities,” she says. “It gives us a detailed profile of the worm’s movement that’s almost like a fingerprint.” To find how gene networks control particular movements, the team cross-matched metrics that were captured by the computer with data about each gene. “Once we knew how many genes were required for maintaining normal locomotion, we then tried to figure out how these genes interact with each other, how they function together as networks.”
The computed gene networks showed interesting features, Dr. Zhong continues. “Some genes are closely connected to each other but loosely connected to others. When we grouped them, we found several communities,. One appears to sense environment via sensory neurons; a second connects neurons, muscles and the digestive tract, “probably encoding some basic machinery in excitable cells.” The third network contains genes in “the motor neurons that we expected.”
Dr. Zhong was most interested to see that the third network revealed evidence that a protein known as G-alpha-Q that also appears in other species — including humans — has a previously unknown target in a signaling pathway that regulates locomotion. The team conducted further experiments to confirm the existence of the new target gene, PLC-gamma. She says previous studies likely missed this target because they were too coarse to detect the subtle movement abnormalities caused by a defect in PLC-gamma — the kind of revelation that could help prioritize genetic tests in humans. “You don’t have to test 30,000 genes if we can give you one or two candidates,” Dr. Zhong says. “At the molecular level, it’s likely a lot of these gene-gene interactions are also conserved in humans.”
All of the data, including 300 hours of video, is available to researchers in a public database at:
You can watch the worms in motion below: