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Extracting Genomic DNA from Root-Knot Nematode Infested Soil using Fe3O4 Super Paramagnetic Nanoparticles
Adrienne Gorny: Cornell University, Plant Pathology & Plant Microbe Biology Section; Xiaohong Wang: USDA-ARS, Robert W. Holley Center for Agriculture and Health; Xiaohong Wang: Cornell University, School of Integrative Plant Science; Sarah Pethybridge: Cornell University, Plant Pathology & Plant Microbe Biology Section
<div>Quantifying the level of plant-parasitic nematodes in field soil prior to planting using a DNA-based soil test could result in a more accurate estimation of crop damage or yield loss observed at harvest. Incorporation of this information into management decisions may promote conservative use or targeted application of pesticides, reducing the environmental impact and cost of production. The isolation of DNA from soil is a critical first step in molecular quantification, and standard techniques for extracting DNA from soil include phenol-chloroform based methods and commercial kits. However, these are often time consuming, produce hazardous waste, are cost prohibitive, and may only be designed for isolating DNA from small volumes of soil. The variability in pathogen population density estimations may be greatly reduced when larger volumes of soil are analyzed. Recently, the use of super paramagnetic nanoparticles has been successful in genomic DNA isolation, providing a quicker, easier, and more economical protocol than traditional kit or phenol-chloroform based methods. Here, a method using Fe<sub>3</sub>O<sub>4</sub> super paramagnetic nanoparticles for the isolation of genomic DNA from soil was investigated for its utility in quantification of plant-parasitic nematodes directly from soil. DNA was isolated from 100 g of soil inoculated with a known quantity of <i>Meloidogyne hapla</i> (root-knot nematode). The method was optimized, and several permutations assaying the volume of nanoparticles used and number of nematodes in the soil were trialed. Resultant DNA was assessed for quantity and quality using spectroscopy, fluorometry, and PCR technologies. Trade-offs between parameter optimization and DNA quality and quantity are discussed.</div>

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