Performing Department
(N/A)
Non Technical Summary
Modern agriculture often relies on heavy chemical inputs that can be detrimental to the surrounding ecosystem. Sustainable cropping practices attempt to limit the negative impact of agriculture. Management practices designed to improve soil health are beneficial to cropyield through changes in soil microbial communities. These soil microbes can also alter the plant's ability to defend against insect pests. However, it is unclear how these soil microbes affect plant defenseandinsect pest management. The goal of this project is to investigate how soil microbes from soil health conservation fields alter corn root lignin content, an insect anti-nutritive compound. We will test how altered lignin content affects the growth and development of western corn rootworm (WCR), a damaging pest of corn. We will then measure the response of corn roots to different soil microbialcommunities to identify microbes involved with lignin production. This knowledge will provide breeders valuable information on how plants can defend against pests and identify new targets for seed development.Additionally, understanding these interactions isimportant for farmers who are using sustainable cropping practices on their farms.
Animal Health Component
50%
Research Effort Categories
Basic
50%
Applied
50%
Developmental
(N/A)
Goals / Objectives
The goal of this postdoctoral fellowship is to understand how soil microbiomes from fields underlong-term soil health conservation management alters corn root lignin content, an anti-nutritive compound that can reduce western corn rootworm (WCR) fitness.Specifically, my objectives are to investigate the impact of lignin on WCR growth and development, and understand the interaction between root ligninifcation and soil microbiomes.Progress in this area will greatly contribute to the plant health and production priority of AFRI. The project also aligns with the NIFA project goals concerning the sustainable intensification of agriculture by expanding our knowledge of how sustainable management tactics alter agricultural microbiomes across domains. Through my mentorship by Dr. Barros-Rios and Dr. Braun, I will complete professional development activities to build an independent research program, expand leadership skills, and improve sciencecommunication skills. Completion of this project will help prepare me for a successful career as an agricultural research scientist in academia, government, and/or industry.Specific objectives:Knowledge of microbiomes and plant-pest interactions through experimentationDirect mentorship of student and leadership training coursePresentation of results at scientific confernces
Project Methods
Aim 1: Does lignin impact WCR growth and developmentWe hypothesize lignin is a significant anti-nutritive to western corn rootworm (WCR). When feeding on roots with high lignin content, WCR must feed more to compensate for decreased nutrient uptake (i.e. compensatory feeding). This may lead to increased plant damage, but decreased WCR weight. To follow up our artificial diet experiment and more thoroughly test the effect of corn root lignin on WCR fitness, we will conduct feeding experiments with three lignin mutant lines (bm1, bm3, bm5) that differ in their lignin content and composition. Our preliminary work confirmed the three mutant corn lines have reduced root lignin content and display differences in the ratio of their main lignin monomers (p-hydroxyphenyl [H], guaiacyl [G], and syringyl [S]) due to mutations in key enzymes in the phenylpropanoid pathway. Comparisons will be made between the mutant lines and one control line (B73). A separate uninfested plant will be paired with each infested plant to measure plant damage. The experiment will be a 4x2 design with 4 genotypes and 2 infestation levels with 10 replicates for each treatment for a total of 80 experimental units. A single sterilized seed will be planted in 32 oz plastic container (Placon Co., Madison, WI, USA) with autoclaved soil mix (2:1 soil:promix), as previously conducted.Ten days after germination, ten neonate WCR larvae will be added to the container and allowed to feed for ten days. Containers will be placed in growth chambers at 25 °C with a photoperiod of 14:10 (L:D) and watered as needed for the duration of the bioassay. This set-up allows us to generate strong, reproducible data with high levels of replication in a small space that is highly controlled. After ten days of feeding, living larvae will be collected using modified Berlese funnels, counted, and weighed. Survival data will be analyzed using a binomial logistic regression. Head capsule width and dry weight of insects will be analyzed using a general linear mixed model. Head capsule width is used to differentiate between instars, allowing us to observe differences in development rates between treatments. Concurrently, roots will be rinsed, dried, and weighed to compare feeding damage between treatments. Relative root weight values will be generated by dividing individual infested plant root weights by the paired uninfested plant root weight within each treatment. These values will be compared between treatments using a general linear mixed model.The expectedoutcomes will increase our understanding of how root lignin content effects WCR growth and development. This provides important information for breeders looking to identify new targets to limit the population size of this destructive pest. Aim 2: Can soil microbiomes alter root lignin content?We will leverage the same USDA-LTAR sites near Centralia, MO from our previous study where we identified soil health practices altered the soil microbiome and pest fitness.The top 10 cm of soils will be sampled in early April from three replicate plots of two treatments: a crop rotation under no-till planted with a mixed cover crop and a crop rotation under mulch-till without cover crops. Four locations at least 50 m apart will be sampled per plot for a total of 12 samples per treatment. Microbial fractions will be separated from soils by mixing 1 g of soil with 2.5 mL 1× PBS and centrifuging at 600 × g to pellet particulate.The lignin mutant line displaying the largest impact on WCR weight from Aim 1 will be examined for microbiome-induced changes alongside a wild-type corn line. A single sterilized seed will be planted in 50 mL tubes with autoclaved soil mix (2:1 top soil:promix) and then inoculated with isolated soil microbiomes from soil health conservation fields or traditional fields. After 10 days, rhizosphere soils (~1mm from surface) will be collected from roots using published methods.2,50 Bacterial (16S) and fungal (ITS) amplicon libraries will be generated for the two genotypes and two treatments for a total of 96 samples (12 replicates × two amplicon targets). A blank negative control and a mock community positive control will be sequenced in parallel. Root lignin content and composition will be analyzed by thioacidolysis followed by (GC-MS) for a total of 48 samples.Lignin phenotypes will be visualized on transverse stem sections using UV-autofluorescence and phloroglucinol-HCl staining. Analytical Methods: Richness and alpha diversity of fungal and bacterial communities as measured by Chao-1 and inverse Simpson's D, respectively, will be compared using a general linear mixed model. Differences in beta-diversity of fungal and bacterial communities between treatments will be analyzed using a permutational ANOVA and visualized using an nMDS. Differences in communities will be investigated further to identify differentially abundant microbial taxa present between treatments. Total lignin content and differences in composition will be compared using a general linear mixed model. Because rhizosphere samples will be collected from the same sample used to analyze lignin content, we can use Kendall correlations to identify potential bacterial and fungal genera that impact lignification in roots.Linking bacterial and fungal genera to lignification will be an important step to further elucidating the mechanism by which soil microbiomes impact management practices.