Behavioral Assays with Smart Worm Recognition Programs Applied to Plant-parasitic and Human-parasitic Nematodes

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2016-01-01
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Njus, Zachery
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Santosh Pandey
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Electrical and Computer Engineering
Abstract

The free-living C. elegans roundworm has inspired an entire family of microfluidic devices to capture, culture or screen worm populations for a number of biological studies. Worm tracking programs also have been developed that can recognize body features and extract behavioral features relevant to the user. While the technological developments towards C. elegans research is commendable, there is far less effort in applying these technologies for parasitic nematodes. This is primarily because of the difficulty in extracting parasitic nematodes from host systems, culturing them in laboratory settings, and applying genetic techniques to a non-model organism.

The thesis starts by demonstrating our C. elegans microfluidic platform, specifically to test the effects of static magnetic fields on the worms. It had been hypothesized that adult C. elegans may possess traces of magnetite within their body that helps them guide their directionality of movement. To test this hypothesis, we encapsulated single C. elegans in straight microchannels and exposed them to varying degrees of static magnetic fields from permanent magnets. Our experiments suggested no conclusive effects of static magnetic fields on the directionality or velocity of C. elegans.

Plant-parasitic nematodes are quite lethargic and sedentary compared to their C. elegans counterparts, and we presented microfluidic devices specifically tailored to these slow-moving nematodes. The two plant-parasitic nematodes, soybean cyst nematodes and root knot nematodes, were designed to be tracked within microfluidic chips for over 18 hours with a goal to test their chemoattraction to chemical compounds and live roots. Extensive experimental runs were conducted using the microfluidic chip technology and the data was compared to runs from the greenhouse. We showed that the microfluidic chip technology provides a reliable platform for chemotaxis studies on the two plant-parasitic nematodes and a viable alternative to greenhouse tests.

The fabrication of abovementioned microfluidic chips required considerable time commitment, and made us search for alternative chip designs that could be mass manufactured. We developed two types of devices: agarose gel membranes resting on paper and Pluronic gel membranes resting on plastic. Methods of worm handling, imaging, transfer, and drug screening are shown using C. elegans as the subject of choice. Compared to agarose plate and microfluidic assays, the membrane devices are flexible, much more cost-effective, and easier for worm accessibility. A C. elegans worm tracking program is written that uses active contour model and adaptive thresholding to identify single worms from non-uniformly lit backgrounds and track their centroid as a function of time.

The human parasitic nematode, Brugia malayi, presents a far greater repertoire of behavioral patterns than those seen in the model nematode, C. elegans. Because of this reason, almost all C. elegans worm tracking software do not work effectively on brugia malayi. We built a tracking software specifically to identify movement features of brugia malayi while the nematode undergoes unconventional twists, coils, and occlusions. A number of parameters can be extracted from the body positions of the nematode, such as curvature, number of bends, forward/backward movement, and probing/cruising motion. We believe this tracking software can help differentiate movement patterns of untreated versus treated nematodes with minimal human intervention.

In summary, the thesis aimed to extend the technological developments in C. elegans microfluidics towards both plant-parasitic and human-parasitic nematodes. Through the chapters, we discussed the challenges in studying non-model organisms especially with limited information. But because of the importance of these parasitic nematodes in agriculture and human welfare, we hope the work presented here will inspire new detection and control strategies for nematodes.

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Fri Jan 01 00:00:00 UTC 2016