S1083: Ecological and genetic diversity of soilborne pathogens and indigenous microflora

(Multistate Research Project)

Status: Active

S1083: Ecological and genetic diversity of soilborne pathogens and indigenous microflora

Duration: 10/01/2018 to 09/30/2023

Administrative Advisor(s):

NIFA Reps:

Statement of Issues and Justification

Agricultural and horticultural crops are produced with an estimated market value of $212.3 billion in the United States each year (USDA, 2014). Soil-borne plant pathogens are diverse and encompass microorganisms such as fungi, oomycetes, bacteria, viruses and nematodes that cause pre- and post-emergence damping-off, root and crown rots, vascular wilts, as well as foliar blight in these crops and amenity plantings. Soil-borne pathogens often survive for long periods on host plant residue, soil organic matter, or as free-living organisms. Soil-borne pathogens may have broad host ranges, and crop species may be susceptible to several different pathogens. Due to the menagerie of plant species produced by growers, and hectares managed, soil-borne disease management is challenging. Interactions with soil texture, chemistry, and environmental conditions make soil-borne disease management challenging. Diseases caused by these pathogens reduce plant performance; increase costs to the grower and cause potential ecological damage to the natural environment. As an example, losses due to soil-borne diseases in Georgia in 2014 were estimated to be $149 million in ornamental and turf production (Little, 2014).

The National Integrated Pest Management (IPM) Road Map has listed “Develop advanced management tactics for specific settings that prevent or avoid pest/disease attack” and efforts to “Improve the efficiency of suppression tactics and demonstrate least-cost options and pest/disease management alternatives” as critical research needs (IPM, 2013). Soil-borne diseases are becoming more difficult to manage because of increased pathogen resistance and restrictions of the use of some chemicals. Conventionally, soil-borne diseases are controlled by using soil fumigants, in-furrow fungicides, or fungicide seed treatment. Once a widely used fumigant, methyl bromide, was phased out of use in 2005 due to its negative effect on the stratospheric ozone layer (Dungan et al., 2003). The loss of methyl bromide has promoted increased interest in alternative methods to control soil-borne diseases. Although safer or less environmentally impactful chemical and non-chemical plant disease management methods have been developed, their results are still inconsistent (Keinath et al., 2000) and less effective than the previous standard, methyl bromide (Gerik and Hanson, 2011).

Some soil-borne pathogens have broad host ranges, reducing the effectiveness of crop rotations in soil-borne disease management. Further, the susceptibility of plants to disease is related to their macro- and micronutrient status; both excesses and deficiencies in nutrients predispose plants to disease (Dick and McCoy, 1993; Maynard, 1994; Workneh and van Bruggen, 1994). Clearly, additional soil-borne disease management strategies suited to the practice of sustainable production are urgently needed.

Over the last 15 years there have been surprising and exciting innovative discoveries for natural methods to suppress or eliminate plant pathogens, and/or protect crop plants. Intensive studies of disease-suppressive soils have led to the development of new methods of analysis (Gross et al., 2007; Borneman et al., 2007; Bolwerk et al., 2005; Benitez et al., 2007) and new insights into the nature of soil-borne disease suppression (Hoitink and Boehm, 1999; Han et al., 2000; Krause et al., 2003; Alfano et al., 2007). Such advances indicate that active management of soil microbial communities can be an effective approach to developing natural suppression of diseases and improve crop productivity (Mazzola, 2004). This involves adjusting the types and timing of organic inputs, such as cover crops, animal manures, composts, compost teas, and crop sequencing. Such approaches have been shown to provide site-specific reductions in disease incidence (Abbasi et al., 2002; Rotenberg et al., 2005, Stone et al., 2003; Darby et al., 2006; Larkin et al.,2006; Larkin, 2008). This technology fits the general requirements of sustainable agriculture in that it utilizes natural means to control diseases. However, standardized and reliable techniques for pathogen suppression have not been developed and widely tested on different crop production systems for controlling soil-borne diseases. In part, this is due to the wide variety of organic amendments that are available and their variable effects depending on the chemical makeup of organic substrates, soil types, and/or local climatic conditions.

Soil incorporation of Brassica or other cover crops has the ability to suppress soil microorganisms through the hydrolysis of glucosinolates (GSL) into isothiocyanate, a natural biofumigant (Kirkegaard et al., 1993, Matthiessen and Kirkegaard, 2006). GSL content and concentration differs among Brassica cultivars, the development stage of the plant (Bellostas et al., 2007), and the end product formed by hydrolysis of the GSL, so that different Brassica cultivars may have different levels of potential to control pathogens (Motisi et al., 2009). Therefore, it is important to study the different GSL-hydrolyzed end products produced by different Brassica crops and their effect on major soil-borne diseases. Incorporation of biofumigant use in the crop production cycle may provide additional successful and sustainable solutions for improving soil quality and enhancing natural soil-borne disease control. The effective use of biofumigants in crop production appears to be limited by a range of factors, which needs to be examined to provide effective recommendations to growers.

Several commercially available biopesticides are composed of specific isolates of soil microorganisms that were selected for their capacity to suppress a range of pathogens. These biopesticides may operate through multiple mechanisms, such as niche exclusion, biocidal/biostatic effects, antibiosis, predation, and parasitism (Handelsman and Stabb, 1996; Fravel, 2005). Some of the most common microbe-based biopesticides contain bacterial isolates of Bacillus spp., Pseudomonas spp., or Streptomyces spp., or fungal isolates of Gliocladium spp. or Trichoderma spp. (Fravel, 2005). Many of these organisms suppress disease and associated pathogen populations through multiple mechanisms. Numerous studies and reviews have documented the potential of microbe-based biopesticides to suppress both foliar and root diseases (Doumbou et al., 2001; El-Tarabily and Sivasithamparam, 2006; Emmert and Handelsman, 1999; Fravel, 2005; Jacobsen et al., 2004). However, the general consensus among these reviews is that integration is the key to obtaining consistent activity from biopesticides (Fravel, 2005; Jacobsen et al., 2004). Amongst the microorganisms developed for biological control of plant diseases, Bacillus spp. particularly have been exploited due to their stability for long periods of time and their antimicrobial activity (Fravel, 2005). Suppression has been attributed to the direct antagonism of pathogen growth through the production of various metabolic byproducts (Peypoux et al., 1999; Bonmatin et al., 2003). Additional work also demonstrated that some of these metabolites may also stimulate plant defenses, conferring an additional layer of control (Ongena et al., 2007).
Several species of Streptomyces have also been evaluated for disease control, mostly against fungal pathogens. A screen using the fermentative products from several Streptomyces spp. isolated from soil were found to inhibit several fungal pathogens, including Pyricularia grisea, Botrytis cinerea, Phytophthora infestans, Puccinia recondita, and Blumeria graminis (Park et al., 2003). Streptomyces spp. have also been evaluated as possible agents for the control of potato scab, caused by S. scabies (Liu et al., 1995).

Adoption of biopesticides has increased. But there is a need for biopesticides to provide workable disease management solutions for growers. Demand for biopesticides has continued to expand dramatically in the last 15 years. However, despite substantial growth in the industry and markets, there is still a lack of publicly available data that substantiates efficacy and return on investment for most products. There is a critical need to develop and disseminate science-based informational resources that will promote useful and sustainable adoption by growers that experience significant plant disease pressure. Lack of knowledge about disease management and fears of extensive losses due to disease and other pests contribute to lack of adoption of farming practices (Walz, 1999; Lotter, 2003). However, growers' specific knowledge gaps regarding disease management in agricultural crops are not well documented. It is critical that growers not only choose but also use biopesticides appropriately within a comprehensive disease management system or sound integrated pest management.

Given the need for sound integrated pest management, approaches coordinating chemical and biological controls are needed. Recently emphasis has been placed on understanding the phytobiome of plants or microbiome of production soils. While metagenomic techniques, in theory, should allow for identification and association with soil-borne diseases, more importantly, these techniques offer the opportunity to understand biological suppressiveness (Weller et al., 2002). However, there are limitations to these methods (Nesme et al., 2016) so evidence must be combined with spatial analysis (Liu, Griffin, and Kirkpatrick, 2014) or analyzed across multiple locations and years to limit sampling error and bias (Paul et al., 2011).
Recently, the use of indigenous vs. synthetic microbiomes to control soil-borne diseases was explored (Mazzola and Freilich, 2017). There are clear advantages with respect to survival and likely efficacy when microorganisms adapted to the specific environment or competing for a similar niche in the phytobiome are used. Numerous examples are presented in the literature (albeit determined with more traditional laboratory and field techniques). For example, fungi antagonistic to Rhizoctonia have been identified and have been shown to have the ability to reduce the severity of disease on numerous crops. Of these, some are other nonpathogenic Rhizoctonia solani, binucleate Rhizoctonia or fungi in other genera such as Trichoderma spp. or a sterile white basidiomycete. Recently, R. solani AG11 was shown to be associated with reduced soybean seedling disease caused by Pythium spp. (Spurlock et al., 2016). Ichielevich-Auster (Ichielevich-Auster et al., 1985) showed that a nonpathogenic isolate of R. solani AG4 reduced damping off in seedlings of cotton, radish, and wheat by R. solani and R. zea by 76-94%. Cardoso and Echandi (Cardoso and Echandi, 1987b) reported binucleate Rhizoctonia protected bean seedlings from a virulent root rot-causing isolate of AG4. At least one T. harzianum isolate also lessened disease. In another study (Cardoso and Echandi, 1987a), binucleate Rhizoctonia isolates protected snap bean seedlings from an isolate of AG4 causing root rot by what was deemed a metabolic mechanism of protection. Snap bean seedlings were exposed to the binucleate isolate and then replanted. Replanted seedlings maintained a level of suppression of the pathogen. Root exudates from the binucleate treated seedlings were also inhibitory to the pathogen in vitro. Burpee and Goulty (1984) also reported disease suppression by binucleate Rhizoctonia on brown patch disease caused by R. solani AG2-2 III B on creeping bentgrass. Sumner and Bell (1994) reported a significant efficacy of a binucleate Rhizoctonia AG-2 and T. hamatum against R. solani AG4, and recently Spurlock (2009) found an unidentified sterile white basidiomycete that protected zoysiagrass from R. solani AG2-2.

New project members include researchers with diverse expertise that will work together to address the objectives set from different but complementary perspectives within the context of the phytobiome initiative and IPM, including mycology, microbiology, basic molecular biology, genetics, bioinformatics, population biology, evolutionary biology, metagenomics, metatranscriptomics, plant disease monitoring, spatial analysis, as well as traditional chemical and non-chemical control. The integrated effort of our research will lead to productive collaborations of relevance at the regional and national levels. The results obtained will be reported in peer reviewed scientific journals, specialized disease management journals and on-line publications, and transferred to the broader community (such as growers, educators, academic, and industry collaborators) through extension education, college and graduate level courses, informational web pages, short video segments and fact sheets.
The long-term goals of the proposed multi-state project are to investigate the impact of rhizosphere microbial communities on plant health and on the productivity of diverse cropping systems, and to validate and evaluate different soil-borne disease management strategies under different environmental conditions. In order to coordinate multi-state efforts and provide effective and sustainable recommendations to growers at a regional level with a useful synthesis of our results, the following objectives will be pursued:

Objective 1. Evaluate the biology and diversity of soil-borne pathogens, associated antagonistic microorganisms, and environmental conditions in the context of the whole-system phytobiome. This objective includes traditional, metagenomics, and spatial/temporal methodologies to understand microbial community dynamics that determine soil-borne disease incidence and severity on economically important crops in the U.S.

Objective 2. Evaluate the efficacy of soil-borne disease management strategies (chemical, biorational/biological, cultural) and characterize the associations among microbial community profile, soil physicochemical properties, environmental factors and disease suppression.

Related, Current and Previous Work

Crop damage caused by soil-borne plant pathogens is the most yield-limiting factor when producing food, fiber and ornamental crops (Weller et al., 2002). Soil-borne plant pathogens cause severe economic losses due to seed rots, pre- and post-emergence damping-off, pod rots, root and crown rots, vascular wilts, as well as foliar blight. Soil-borne pathogens often survive for long periods on host plant debris, soil organic matter, or as free-living organisms (Agrios, 2005; Shurtleff and Averre, 1998). Each crop may be susceptible to several pathogens. Many factors including soil type, texture, pH, moisture, temperature, nutrient levels, and ecology affect the activity of soil-borne pathogens. Soil fumigants, in-furrow fungicides, or fungicide seed treatments are widely used to control soil-borne diseases. The loss of methyl bromide has promoted increased interest in alternative methods to control soil-borne diseases.


A Southern Regional Project on soil-borne plant pathogens has been active since the initial project S-26 "The Relation of Soil Microorganisms to Soil-borne Plant Pathogens” was established in 1956. Throughout the series of projects it has maintained active research on important soil-borne pathogens as well as examining the role of soil microflora in moderating the effects of these organisms. Other areas of emphasis during these projects have focused on the effects of the rhizosphere, the role of crop residues, amendments, and cultural practices on pathogens and other soil microflora. In 1995, the project on soil-borne pathogens started an emphasis on the introduction and evaluation of biocontrol agents across crops and environments and received funding for these evaluations. In the project S-1028, regional evaluation of biocontrol agents was extended to broccoli. Investigators in the project conducted research under the project on chemical and biological control of pathogens on summer squash (Seebold et al. 2008), tomato (Gwinn et al. 2010), cotton (Hu et al. 2011), snap bean (Canaday and Schmitthenner, 2010, Canaday, 2011), and soybean (Mengistu et al., 2011). Amendments of Monarda, brassicas, or legumes as green manure for disease control were examined in cotton, tomato, and watermelon and additional amendments were examined in the regional broccoli experiments and a variety of organic amendment for Christmas trees. Rhizosphere microflora characterization was conducted for turf, Christmas trees, strawberries, watermelon and cotton as part of the studies (Njoroge et al., 2008). The diversity of Rhizoctonia solani, Sclerotinia sclerotiorum, Verticillium dahliae, Sclerotinia minor, and Phymatotrichopsis omnivora, and Pythium spp. was noted. A standardized protocol from the regional effort was developed for the recovery of Rhizoctonia using a toothpick baiting technique and selective media (Spurlock et al., 2011). In the S-1053 project, a team of scientists from the University of Arkansas, Mississippi State University, and Louisiana State University named a new disease of soybean prevalent in those three states taproot decline (TRD). Through phylogenetic analysis of isolates collected from Arkansas, Louisiana, and Mississippi, as well as other known species of Xylaria, it was determined that this fungus was previously undescribed. The causal agent of TRD is a member of the X. arbuscula species aggregate and closely related to X. striata. Investigators from Tennessee and Oregon conducted research on chemical and biological control for controlling soil-borne diseases such as Phytophthora and Rhizoctonia with different application methods, intervals and reduced-rate applications in ornamentals (Baysal-Gurel 2017a and b). Mycovirus epidemiology in R. solani on important row crops was examined and results indicate mycoviruses are commonly found in isolates of R. solani. More than 20 new viruses, belonging to at least three different virus families were discovered. As part of the S-1053 project, the genetic profiles of Pythium and Globisporangium isolates resistant and sensitive to mefenoxam were completed, the genetic diversity of three species of Globisporangium pathogenic on Douglas fir were examined and compared (Weiland et al., 2015). Monophyletic groups with high risk of developing mefenoxam resistance were identified within G. cryptoirregulare, as well as low-risk phylogenetic groups (Garrido et al., 2014). A draft of the genome of Sclerotinia minor was annotated and compared with the genomes of sister taxa (Espindola et al., 2015a). A bioinformatics tool for metatranscriptomic analysis for detection of soil-borne fungi and oomycetes and functional analysis was developed (Espindola et al., 2015b). The population biology analysis of Ophiosphaerella herpotricha was conducted (Iturralde et al., 2016). The SSR protocol was developed for Fusarium proliferatum (Moncrief et al., 2016). Strains isolated from onion in Oklahoma, transformed to express fluorescent proteins, were used to examine the infection process in onion and the patterns were compared microscopically between species. Strains of Fusarium spp. were tested for hormetic effects at low doses of fungicides. Low-dose growth stimulation was observed suggesting that fungicides at low doses could enhance Fusarium spp. epidemics. New protocols for testing the effects on mycotoxin production of exposure of Fusarium spp. to hormetic doses of fungicides were developed (Anasi, 2016). Differences in the patterns of infection of strains of F. oxysporum and F. proliferatum were identified by fluorescence microscopy. The protocols developed for this study will be applied to analysis of fungicide hormesis on fungal growth in planta. Investigators in Arkansas as part of S-1053 project showed that cotton seedling disease pressure varied spatially across the research field based on predictable soil factors. This information could be used for creating prescription maps for variable rate management. A multi-year, field study is being conducted in Texas to evaluate the impact of cover crops on various soil microbial populations in dryland cotton systems.  The results indicate that cover crops have the potential to increase microbial biomass and mycorrhizal colonization of cotton grown under dryland conditions, especially early in the growing season, with potential benefits to cotton resilience and productivity.

Cover crop. A field study is being conducted in Texas to evaluate the impact of cover crops on various soil microbial populations in dryland cotton systems.  Treatments include conventional tillage, no-till, and no-till with a variety of cover crops.  Following cover crop termination, cotton is planted around June and harvested around November.  Early results indicate that treatment impacts on microbial communities are occurring after only 2-3 years. Phospholipid fatty acid (PLFA) analysis results showed little difference in microbial biomass levels between conventional tillage and no-till samples; however, inclusion of a cover crop increased microbial biomass up to 2-fold.  Similarly, at mid-season (August) the use of cover crops tended to increase arbuscular mycorrhizal (AMF) colonization of cotton, being lowest in the conventional tillage plots (65%), slightly higher with no-till (75%), and increasingly higher with no-till and cover crops: mixed species (85%), wheat (88%), hairy vetch (95%), Austrian winter pea (97%), and crimson clover (98%).  However, by the end of the growing season (October), the differences had largely disappeared with conventional tillage plots having 82% colonization and the no-till and various cover crops ranging from 79 to 93% colonization.  Principal coordinate analyses of DNA sequencing results showed that AMF species in cotton roots was influenced by the different cover crop treatments.  At mid-season (August) AMF species colonizing cotton roots were similar across treatments: however, AMF species in cotton roots showed dissimilarity between conventional tillage and cover crops treatments by the end of growing season (October).  The results indicate that cover crops have the potential to increase microbial biomass and mycorrhizal colonization of cotton grown under dryland conditions, especially early in the growing season, with potential benefits to cotton resilience and productivity.  Investigation into tillage and cover crop impacts on mycorrhizal fungi will continue in future years and be expanded to also include irrigated cotton and to also determine treatment impacts on root-associated bacteria and fungi using next-generation sequencing approaches. In Tennessee, another team member will assess biofumigant cover crops (arugula, mustard, dwarf essex rape etc.) for soil-borne diseases (Phythophthora and Rhizoctonia) and improved plant growth in woody ornamentals and will characterize the linkages between microbial community structure and soil-borne disease suppression in woody ornamental nursery systems that employ biofumigant cover crops.

In the period from 2012 to 2016, 73 peer-reviewed papers, 20 abstracts, 5 book chapters, 4 extension publications, and 2 dissertations related to S-1053 project objectives were published by group members.



  1. Evaluate the biology and diversity of soil-borne pathogens, associated antagonistic microorganisms, and environmental conditions in the context of the whole-system phytobiome. This objective includes traditional, metagenomics, and spatial/temporal methodologies to understand microbial community dynamics that determine soil-borne disease incidence and severity on economically important crops in the U.S.
  2. Evaluate the efficacy of soil-borne disease management strategies (chemical, biorational/biological, cultural) and characterize the associations among microbial community profile, soil physicochemical properties, environmental factors and disease suppression.


Objective 1. Evaluate the biology and diversity of soil-borne pathogens, associated antagonistic microorganisms, and environmental conditions in the context of the whole-system phytobiome. This objective includes traditional, metagenomics, and spatial/temporal methodologies to understand microbial community dynamics that determine soil-borne disease incidence and severity on economically important crops in the U.S.

The team will conduct characterization, histological, species diversity and population biology studies of soil-borne plant pathogens (such as Phytophthora spp., Rhizoctonia spp., Fusarium spp., Xylaria sp., Verticillium dahliae etc.) and antagonistic microorganisms of multiple crops, including ornamentals, turf, vegetables, field crops, and row crops, among others. Furthermore, new diagnostic and fingerprinting methods will be developed using PCR, qPCR, next generation sequencing, and metagenomic approaches.

Determination of the identity and distribution of ectotrophic root-infecting (ERI) fungi associated with the roots of ultradwarf bermudagrasses used for putting green surfaces.  Currently, it is hypothesized that there is a complex of ERI pathogens causing root rot in contrast to current literature that reports Gaeumannomyces graminis is the causal agent of bermudagrass decline.  A fishnet grid system was established for sampling greens at a local golf course using ArcGIS. Aerification cores were collected within 2.4 m2 of each centroid. Genomic DNA will be extracted from composite root samples.  Identification of select ERI pathogens will be accomplished using multiplex qPCR.  Root populations of fungi will be compared to turfgrass quality ratings within the same grid to determine potential pathogen populations present.

Determination of factors associated with incidence and severity of Taproot decline; a newly described disease of soybean.  Over the past decade, a soybean disease that causes conspicuous interveinal chlorosis and necrosis of foliage has been predominantly observed throughout the Mississippi River Valley.  The disease was recently named taproot decline, the causal agent confirmed as a fungus belonging to the genus Xylaria, and evidence suggests the closest relative to be X. striata (Allen et al., 2017).  Taproot decline may result in plant death at any soybean growth stage.  Plants that are killed or display symptoms during seedling and early vegetative stages often go unnoticed, as neighboring plants rapidly outgrow them in addition to lower canopy diseases masking the symptoms associated with taproot decline.  When extracted from the soil profile, affected plants easily break at the soil line and exhibit a dry-rot, and excised roots appear blackened with tap and lateral root necrosis.  Stems split longitudinally near the crown oftentimes contain white mycelial growth within the pith along with mild vascular staining.  Reproductive structures or stroma that produce conidia, defined as “dead man’s fingers” are produced by the pathogen and are often observed emerging from crop debris near infected plants.  The foliar symptoms are the result of root dysfunction and may be observed between the cotyledon (VC) and beginning maturity (R7) soybean growth stages.  These symptoms are often confused with many other important root, crown and stem diseases as well as nutrient deficiencies.  To date, taproot decline has been positively confirmed in Alabama, Arkansas, Louisiana, Mississippi, and southern Missouri.  Although taproot decline may be observed every year, incidence and severity varies on an annual basis.  Xylaria sp. a soil-borne fungus and causal organism of taproot decline of soybean, is undergoing characterization to determine optimal growth, virulence, and the infection process.  Histological studies will broaden the understanding of the infection and disease cycle of this pathosystem.  There will also be continuing spatial analysis of the disease in Arkansas, Mississippi and Louisiana to determine the economic impact of the disease as well as soil edaphic factors associated with disease development.

Determination of the fungal community compositions using Illumina sequencing methods. Over the last decade next generation sequencing has become an important tool for conducting culture-independent surveys (Hibbet et al., 2011; Brown et al., 2013).  High percentage of the fungal sequences has never been identified or are unknowns since they have never been found in nature or unculturable.  Unfortunately some of the species may be important or critical to understanding agricultural and forest microbial dynamics over time and subsequence impacts of continuous cropping, artificial management and natural inputs being added to cropland and forest health due to environmental changes such as nutrition.  Therefore, in order to track changes in the pathogen and mycorrhizal communities associated with environmental causes or specific management practices with those ecosystems, whole-community (Illumina MiSeq) data is most accurate approach for understanding microbiome fluxuations within farm sites and forest habitats.   As an example, new peanut production areas in Mississippi currently have minimal soil-borne diseases impacts and baseline data from these sites will be used to monitor continuous cropping systems to determine the microbiome community spatiotemporal changes as they impact yields.

The team members propose to utilize soil samples collected for measurement nutrient levels with the same soil samples, extract fungal DNA from these samples, and determine the fungal community compositions using Illumina sequencing methods.  To identify species, community composition and abundance Illumina sequencing will be employed using primers concentration on ITS 2 gene region for sequencing. Potentially for each sample, Illumina sequencing can identify up to 1500 fungal species (Gihring et al., 2011).  DNA will be extracted from these soil-litter samples using several protocol including Mo Bio Power® kits and CTAB as needed. The variable region ITS2 rDNA of fungi as stated above will be PCR amplified and analyzed using Illumina sequencing (Illumina Technology, Eurofin MWG). Each sequence will be assigned to its corresponding OTU (operational taxonomic unit) using the rDNA databases (RDP with 292,547 fungal ITS rDNA) for identity analysis. UNITE taxonomy reference database (http://unite.ut.ee/respository.php) will be specifically used to define specific taxa within OTU groupings.  Finally, we will perform statistical analyses to examine the relationship between nutrient data and fungal community composition and species diversity measures.  All statistical analyses will be carried out in R (version 3.1.1, Development Core Team, 2014) and used the Type 1 error rate of α = 0.05 after post-hoc statistical corrections when appropriate. Kruskal-Wallis rank sum tests and Dunn’s post-hoc corrections (posthoc.kruskal.dunn.test) will be carried out in the PMCMR package (Pohlert, 2016). Stepwise regression model selections were performed via the MASS package (Venables and Ripley, 2002). NMDS (metaMDS), perMANOVA (adonis), and environmental vector fitting (envfit) will be conducted in the vegan package (Oksanen et al., 2017) and the pairwise comparisons of sites using Bray-Curtis distances (pairwise.perm.manova) will be conducted in the RVAideMemoire package (Hervé, 2017). 

Characterization of antimicrobial bacteria. To obtain antagonistic bacteria from crop rhizospheres, soils showing disease suppressiveness will be collected from root systems associated with different soil-borne diseases.  Bacteria will be isolated using various selective culture media.  Antagonistic bacteria to major fungal and bacterial pathogens of plants will be selected using plate assays (Lu et al., 2002).  Initial identification of bacterial genera will be performed as described by Schaad et al. (2001). In addition, the bacterial isolation will be conducted from the fresh vegetable crops, which will be used for searching fresh food-associated Burkholderia spp..  To further characterize bacterial isolates, routine bacteriological analysis will be performed as described by Schaad et al. (2001), including morphology of bacterial colonies, growth on various media, and Gram staining.  Biochemical and physiological analyses will be performed using the API kits (bioMérieux, Inc. Durham, NC) as described by the manufacturer.  Molecular techniques, such as the 16S rRNA gene sequence analysis, will be conducted as described by Baker et al. (Baker et al., 2003).  To characterize the genes dedicated to antagonism, mutagenesis of the antagonistic isolates of interest will be performed using an EZ::TN transposon system (Epicentre Technologies, Madison, WI).  Plasmid rescue techniques will be used to clone the transposon-targeted genes from the resulting mutants deficient in antifungal activities as described by the manufacturer.  Partial genes associated with antifungal activity will be sequenced.  To clone the intact genes of interest, a fosmid library will be constructed using the Copy Control Fosmid Library Production Kit (Epicentre Technologies, Madison, WI) according to the kit manual.  Screening the resultant library using the DNA fragments of the targeted genes, as probes will identify the fosmids that carry the intact genes.  Complementation of mutant strains will be performed with the identified intact gene carried by appropriate expression vectors (Cardona and Valvano, 2005).  Sequence analysis of the targeted genes will provide insights for predicting the possible products contributing to antagonism.  Success of cloning the partial genes dedicated to antifungal activities of isolate MS14 demonstrates that the procedures described above work efficiently for obtaining the genes of interest from bacteria. To perform site-direct mutagenesis of the genes of interest, a standard procedure will be used as described previously (Gu et al., 2009b). In brief, the wild-type gene fragment will be disrupted by the insertion of a kanamycin cassette into its open reading frame as described previously (Lu et al., 2002).  A 1.1-kb DNA fragment, which carries the nptII gene without a transcriptional terminator, will be obtained from plasmid pBSL15 (Alexeyev, 1995).  The nptII cassette will be inserted into the appropriate site of the gene fragment, which will be transferred to pBR325 (Prentki et al., 1981).  The marker exchange procedure (Gu et al., 2009a) will be employed to generate the corresponding mutant.  CRISPR-Cas9 mutagenesis. The genes of interest will be site-specifically mutated by CRISPR-Cas system as described previously by Jiang et al. (2013). The spacer sequence will be designed for cloning into the pCRISPR and pCas9 plasmids (Addgene catalog #42875 and #42876), respectively. The mutagenesis was conducted following the procedures as described previously (Jiang et al. 2013). The editing constructs and targeting constructs, with the spacer sequence cloned into, will be co-transformed into the wild type MS14 competent cells by electroporation. The cells were recovered at 28°C for 1 hour before being plated on NBY agar. The resulting colonies will be individually picked and genomic DNA will be extracted. The region covering the targeting site will be amplified by routine PCR using appropriate primer pairs and the mutants will be screened by sequencing PCR amplicons. Plate bioassays will be used to evaluate the antimicrobial activities of the mutants as described previously (Lu et al. 2002).

Spatial/temporal analysis from diversified cropping systems. Plant and soil sampling schemes will be designed to evaluate spatial variation within and between field sites, as well as within and between seasons (temporal variation and microbial succession).  These diversity surveys, coupled with soil and agronomic data, will provide information on field management and soil conditions at which particular microbial taxa, or groups of taxa, either pathogenic or beneficial, are predominant. Further, research will be focused on microbial groups consistently showing responses across field sites and years, and will relate to dynamics of core plant microbiome establishment. Rhizospheric and endophytic bacterial and fungal isolates will be used in order to monitor dynamics of plant infection by different organisms. These experiments will be performed in greenhouse settings and microbial colonization will be measured through molecular approaches such as quantitative PCR.  This work will likely include multiple crops across participating states.  Exact locations and production systems have yet to be determined.


Objective 2. Evaluate the efficacy of soil-borne disease management strategies (chemical, biorational, biological, cultural) and characterize the associations among microbial community profile, soil physicochemical properties, environmental factors and disease suppression.

The team will evaluate the efficacy of chemical, biorational/biological products; cultural approaches (cover crop/crop rotation, variety/cultivar screening etc.) for controlling soil-borne diseases caused by oomycetes (such as Phytophthora, Pythium) and fungi (such as Rhizoctonia) and characterize the associations between microbial community profile, soil physicochemical properties, environmental factors and soil-borne disease suppression of multiple crops.

Chemical and biorational products. The team member will study the effects of subinhibitory doses of fungicides and other antimicrobial agents on plant pathogenic fungi and bacteria in vitro and in planta in Oklahoma. Previous research demonstrated that sublethal doses of fungicides stimulated radial growth of oomycetes and fungi (Pradhan and Garzon, 2016; Pradhan et al., 2017), and increased the virulence of Pythium aphanidermatum (Flores and Garzon, 2013). Future research will focus on examination of new pathosystems, identification of fungicides with high risk for inducing hormetic responses, and metabolic pathways involved in growth stimulation during hormetic stimulation. In Tennessee, another team member will evaluate the efficacy of chemical and biorational products for controlling soil-borne diseases with different application methods, intervals and reduced-rate applications in woody ornamentals.

Plant growth-promoting rhizobacteria. The use of microorganisms, such as plant growth-promoting rhizobacteria (PGPR), in sustainable productions is promising (Adesemoye et al., 2008; Raupach and Kloepper, 1998; Pal and Gardener, 2006) and has great potential in organic and conventional productions. There are many biological products currently available on the market which are based on PGPR. There is limited information on their efficacy against soil-borne pathogens such as Fusarium and Rhizoctonia species. Although there is substantial published literature on the effectiveness of PGPR conducted under laboratory and greenhouse environments but information on field applications are limited. More field studies as well as more greenhouse research will be conducted to better understand the factors that may affect the practical application of these biological control methods and how efficacy could be improved. Studies will examine possible mechanism used by PGPR, so that the knowledge from the studies could be leveraged to improve efficacy. Metabolite production is an important mechanism that will be studied. Bacillomycin, fengycin, iturin, surfactin, and difficidin, are examples of antifungal lipopeptides produced by PGPR (He et al., 2012; Bais, et al., 2004), which play roles in biological control. The practical applications of important metabolites in terms of their roles will be studied and findings will be helpful in developing sustainable management strategies for soil-borne pathogens.

Variety/cultivar screening. Cultivar/variety screening for soil-borne pathogens including but not limited to Rhizoctonia spp. and Phytophthora spp. will be done in natural and artificially infested field/greenhouse environments. Field crops would be planted early season (prior to optimal planting dates) and irrigated to provide conducive environment for disease development. Visual observation of disease and in season/throughout experimental period evaluations will be recorded to determine effects of pathogen on varieties/cultivars.  Harvest/plant growth data will be used to determine losses/damage associated with disease.  Pathogen isolations will be completed to confirm a particular microorganism has caused the observed symptoms.

Characterization of endophytic bacteria associated with soybean resistance to charcoal rot disease. Endophytic bacteria of soybean root systems will be isolated and characterized using a routine culture-dependent method. When charcoal rot symptoms are visible, stems (10 grams, 5 cm above soil line) from the two types of plants (symptomatic or asymptomatic) will be collected and the composition and population of bacteria will be analyzed using routine methods as described by Schaad et al. (2001).  Soybean root parts will be washed and surface sterilized using 70% alcohol and bleach (3% sodium hypochlorite) with Tween 20 (0.1%).  Plant tissues will be broken into fine pieces and suspended in 10 ml of 0.01M phosphate buffer for 10 minutes.  The resulting bacterial suspension will be serially diluted and spread onto different types of rich culture media, such as NBY for most bacteria (Vidaver, 1967) and NPPC for Actinomycetes (Williams and Davies, 1965). Sequencing the 16S rDNA of the isolates will be performed for bacterial identification using universal primers 27F and 1492R (Tanner et al., 2000) to confirm their identity.   Symptomatic and asymptomatic plants (at least six of each type in each year) collected from diseased patches will be analyzed.  All plants will be collected from the same soybean field to reduce possible variations caused by soil textures and culture conditions.  Soybean stems will be collected and treated as stated above. Tissue homogenates will be fractionated by a series of differential centrifugations followed by a Nycodenz density gradient centrifugation (Ikeda et al., 2009). After a series of centrifugation, the whitish band located at the interface of the upper and lower phases will be collected as a bacterial cell fraction. The bacterial suspension (~500 µl) will be mixed with an equal volume of sterilized water in a 1.5-ml microtube and centrifuged. The resulting bacterial pellet will be used for the extraction of genomic DNA.

PCR amplification of the V2 region of 16S rDNA and Illumina sequencing. Bacterial DNA will be extracted using a CTAB protocol (Ausubel, 1988). The variable regions (V1-2) of bacterial 16S rDNA will be PCR amplified using the primers 27F and 338R (Ravel et al., 2011). The 338R primer includes a unique sequence tag to barcode each sample as described previously (Ravel et al., 2011). The primers are as follows: 27F-5’-GCCTTGCCAGCCCGC TCAGTCAGAGTTTGATCCTGGCTCAG-3’ and 338R-5’-GCCTCCCTCGCGCCATCAG NNNNNNNNCATGCTGCCTCCCGTAGGAGT-3’, where the underlined sequences are the sequencing primers in 27F and 338R, respectively, and the underlined letters denote the universal 16S rRNA primers 27F and 338R. The 8-bp barcode within primer 338R described by Ravel et al. (Ravel et al., 2011) will be adapted and is denoted by 8 Ns. To recover as many 16S rDNAs as possible, gradient PCR will be performed with annealing temperatures between 48-58°C (Sagaram et al., 2009).  The PCR products will be analyzed using Illumina sequencing. The sequencing run generates more than 1,000,000 single reads with an average read length of 310 bases, which is good enough for computation of bacterial richness and abundance. In order to reduce costs, six samples from three healthy plants and three diseased plants will be PCR amplified with the bar-coded reverse primers (Miller et al., 2009, Ravel et al., 2011). Equimolar amounts (100 ng) of the PCR amplicons from six samples will be mixed in a single tube. Pooled PCR products will be purified using a Promega PCR purification kit. Sequencing raw data will be trimmed and filtered using a customized Perl script to minimize the effects of poor sequence quality and sequencing errors by removing (i) barcoding and adapter sequences; (ii) sequences containing more than one ambiguous base call, (iii) sequences that are shorter than 300 nucleotides (excluding bar-coded primers); and (iv) the reads having less than 60% match to a previously determined 16S rRNA gene sequence.  The whole data set will be divided into six subdata sets based on their bar codes, which will be used for further computation of bacterial richness and diversity. To assign each sequence to its corresponding OTU (operational taxonomic unit), sequence identity will be calculated as described previously (Turnbaugh et al., 2009). We will group the 16S rDNA region into OTU using a customized Perl script or other algorithms, such as Cd-Hit (Li & Godzik, 2006), with a sequence identity threshold of 97%, which is commonly used to define species-level phylotypes.  The bacterial 16S rDNA database (Cole et al., 2009), which has 1,418,497 16S rRNAs so far, will be used for identity analysis. To determine the abundance of individual OTUs in each sample, a customized Perl script will be written to identify the membership of each sequence by performing a local BLAST similarity search against each of the trimmed subdata bases of the corresponding sample. Alternatively, we may adapt the methods described by Ravel et al. (Ravel et al., 2011).  In that case, each processed 16S rRNA gene sequence read will be classified using the RDP Naïve Bayesian Classifier (Wang et al., 2007). This should result in almost all reads being assigned to a specific genus.  Assignment at the species level for sequences mapping to a bacterial genus of interest will be accomplished by building a hidden Markov Model for each known species using the software HMMER and identifying the model with the highest score for each 16S rDNA sequencing read. Statistical analyses will be conducted on community clustering, diversity, and correlation as described by Ravel et al. (Ravel et al., 2011).

Investigation of the effects of inoculation of endophytic bacteria on the fungal pathogen, disease reaction, and soybean growth. Plate bioassays will be used to evaluate direct interactions of the endophytic bacteria with the fungal pathogen M. phaseolina (Lu et al., 2005). The inhibitory zones of the bacteria on the fungal pathogens will be recorded to evaluate direct effects on the pathogen growth. Soil with the pathogenic fungus M. phaseolina will be used as described previously (Su et al., 2001). The inoculum density (CFU per gram of inoculum mixture) will be determined by dilution plating. Soil will be infested with inoculum to yield 10 CFU/g of soil prior to filling pots. This level will be chosen because it represents an average level for M. phaseolina infestation in soil at previous collections. To evaluate the roles of endophytic bacteria of interest, soybean variety Asgrow 4651 will be used for these experiments in a greenhouse.  Endophytic bacteria will be cultured to log phase and then washed twice-using phosphate buffer. The selected bacteria will be used to inoculate the soils to reach a final concentration of 107 bacteria per gram of soil.  Various combinations of endophytic bacteria of interest will be tested and appropriate controls (ex. phosphate buffer) will be included.  Disease development will be recorded by using the rating scale described previously (Mengistu et al., 2007). Species-specific PCR primers will be developed based on the sequence data in NCBI, and the resulting primers will be used for detection of the targeted bacteria and for quantification of the bacteria in plants.  The population of the charcoal rot pathogen M. phaseolina also will be measured using quantitative real-time PCR with the specific primers of the pathogen and program described previously (Kishore et al., 2007). Correlation analysis between population of the fungal pathogen, disease development and population of the bacteria will be performed. It is expected to find possible interaction relationships of these organisms.

Measurement of Progress and Results


  • Understanding of the differences and similarities among particular agricultural and natural ecosystems regarding the genetic diversity of soil-borne pathogens.
  • Improved control of soil-borne diseases of different crops through usage of cultural methods.
  • Understanding of the interactions between fungi/oomycetes and bacteria present in soil and plant microbial populations.
  • Understanding of the usefulness and feasibility of inoculation of plant endophytes for management of soil-borne diseases
  • Optimized disease management protocols, using targeted management of field soil-borne diseases according to spatial distribution of inocula.
  • Understanding of the impact of exposure to subinhibitory fungicides on the pathogenicity of soil-borne plant pathogens.
  • Understanding of the impact of different application methods, intervals and reduced-rate applications of chemical, biorational/biological products for controlling soil-borne diseases.
  • Awareness of the available germplasm and the tolerance level to disease with and without chemical treatment.
  • Improved protocols for collection, detection and diagnosis of soil-borne pathogens.

Outcomes or Projected Impacts

  • Awareness of the diversity of soil-borne plant pathogens will allow effective disease management by taking into account the differences in sensitivity of each pathogenic species to particular chemical and biological treatments.
  • Changes in soil-borne disease management recommendations with improved, efficacious, cost-effective and sustainable approaches will reduce plant losses, increase yields, and increase grower profits. This will lead to outcomes of growers changing their behavior to include more sustainable production practices and reduction in the amount of fungicides applied in agriculture production
  • Understanding of plant pathogen interactions with soil and plant microbial communities will result in identification of new biological control agents and management protocols.
  • Understanding the effects of subinhibitory effects of fungicides on diverse soil-borne plant pathogens will create awareness of the risks involved in the misuse of chemical control.
  • Developing unique information on cover crop usage and innovative protocols by characterizing the impact of cover crops on soil-borne plant pathogenic populations and demonstrating the role of microbial diversity and ecology of the pathogenic genera in disease suppression.
  • Improved protocols for detection and diagnosis of soil-borne plant pathogens will result in more effective management practices and higher crop productivity.


(2018):Collection, isolation and identification of fungal and microbial strains interacting in each of the systems under study - Changes to extension publications will be recommended and manuscripts submitted to refereed journals. - Assessment of effects of subinhibitory fungicides on multiple fungal plant pathogens - Evaluation of current collection, detection and diagnosis protocols

(2019):Identification of microbial communities suppressive to soilborne plant pathogens - Evaluation of modified collection, detection and diagnostic protocols - Assessment of responses to subinhibitory fungicides in fungal plant pathogen populations - Data analyses, publication of scientific reports and outreach materials - Progress reports at APS national and regional meetings as well as in the annual project meeting

(2020):Identification of microbial species with potential for biological control of soilborne plant pathogens - Development of new collection, detection and diagnostic protocols - Assessment of responses to subinhibitory fungicides in fungal plant pathogen populations – Updated management of Taproot decline in soybean - Data analyses, publication of scientific reports and outreach materials - Progress reports at APS national and regional meetings as well as in the annual project meeting

(2021):Evaluation of microbial species with potential for biological control of soilborne plant pathogens - Validation of new collection, detection and diagnostic protocols - Assessment of responses to subinhibitory fungicides in fungal plant pathogen populations - Data analyses, publication of scientific reports and outreach materials - Progress reports at APS national and regional meetings as well as in the annual project meeting - Development and delivery of extension education and outreach materials

(2022):Completion of data analyses, publication of scientific reports and outreach materials - Extension education and outreach presentations and delivery of educational materials - New project / objectives writing

Projected Participation

View Appendix E: Participation

Outreach Plan

Research results will be published in a combination of extension publications, non-refereed but peer reviewed reports, and refereed journal articles to ensure access to research results by growers, the agricultural industry, other scientists, and interested parties. The results obtained and protocols developed will be reported in peer reviewed scientific journals, specialized disease management journals and on-line publications, and transferred to the broader community through extension education, college and graduate level courses, informational web pages and fact sheets.


This project has a very simplified organization. There are two officers: the meeting chair and the meeting secretary. The meeting secretary becomes the meeting chair at the subsequent annual meeting. Thus, there is only one 'elected' position each year. The meeting secretary records the minutes of the annual meeting of the project membership and submits the minutes to the chairman within 30 days of the close of the meeting. The chairman (1) obtains approval for the annual meeting from the project administrative advisor (PAA), (2) prepares the annual meeting agenda, (3) notifies the membership and interested parties of the date, location, and time of the annual meeting at least 30 days in advance, (4) presides over the annual meeting, and (5) submits the annual report to the PAA within 60 days of the meeting.
There is one annual committee with one or more members - the local arrangements committee. Once the site (i.e., city and state) and date for the next annual meeting has been identified by the project membership attending the current meeting, this committee (1) identifies the specific location for the annual meeting (building, room, time, etc.), (2) obtains approval for its use from the appropriate local authorities, (3) identifies local accommodations and reserves (if possible) a block of rooms for meeting attendees, and (4) identifies appropriate locations for meals, etc.
Other committees may be formed as identified by the needs of the membership, e.g. to facilitate publication of project research results or to identify or formulate standard research procedures.

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