Soybean (Glycine max (L.) Merr.) is produced across a vast swath of North America, with the greatest concentration in the Midwest. Root rot diseases and damping-off are a major concern for production, and the primary causal agents include oomycetes and fungi. In this study, we focused on examination of oomycete species distribution in this soybean production system and how environmental and soil (edaphic) factors correlate with oomycete community composition at early plant growth stages. Using a culture-based approach, 3,418 oomycete isolates were collected from 11 major soybean-producing states and most were identified to genus and species using the internal transcribed spacer region of the ribosomal DNA. Pythium was the predominant genus isolated and investigated in this study. An ecology approach was taken to understand the diversity and distribution of oomycete species across geographical locations of soybean production. Metadata associated with field sample locations were collected using geographical information systems. Operational taxonomic units (OTU) were used in this study to investigate diversity by location, with OTU being defined as isolate sequences with 97% identity to one another. The mean number of OTU ranged from 2.5 to 14 per field at the state level. Most OTU in this study, classified as Pythium clades, were present in each field in every state; however, major differences were observed in the relative abundance of each clade, which resulted in clustering of states in close proximity. Because there was similar community composition (presence or absence) but differences in OTU abundance by state, the ordination analysis did not show strong patterns of aggregation. Incorporation of 37 environmental and edaphic factors using vector-fitting and Mantel tests identified 15 factors that correlate with the community composition in this survey. Further investigation using redundancy analysis identified latitude, longitude, precipitation, and temperature as factors that contribute to the variability observed in community composition. Soil parameters such as clay content and electrical conductivity also affected distribution of oomycete species. The present study suggests that oomycete species composition across geographical locations of soybean production is affected by a combination of environmental and edaphic conditions. This knowledge provides the basis to understand the ecology and distribution of oomycete species, especially those able to cause diseases in soybean, providing cues to develop management strategies.

Mortierella and Ilyonectria genera include common species of soil fungi that are frequently detected as root endophytes in many plants, including Populus spp. However, the ecological roles of these and other endophytic fungi with respect to plant growth and function are still not well understood. The functional ecology of two key taxa from the P. trichocarpa rhizobiome, M. elongata PMI93 and I. europaea PMI82, was studied by coupling forest soil bioassays with environmental metatranscriptomics. Using soil bioassay experiments amended with fungal inoculants, M. elongata was observed to promote the growth of P. trichocarpa. This response was cultivar independent. In contrast, I. europaea had no visible effect on P. trichocarpa growth. Metatranscriptomic studies revealed that these fungi impacted rhizophytic and endophytic activities in P. trichocarpa and induced shifts in soil and root microbial communities. Differential expression of core genes in P. trichocarpa roots was observed in response to both fungal species. Expression of P. trichocarpa genes for lipid signaling and nutrient uptake were upregulated, and expression of genes associated with gibberellin signaling were altered in plants inoculated with M. elongata, but not I. europaea. Upregulation of genes for growth promotion, downregulation of genes for several leucine-rich repeat receptor kinases, and alteration of expression of genes associated with plant defense responses (e.g., jasmonic acid, salicylic acid, and ethylene signal pathways) also suggest that M. elongata manipulates plant defenses while promoting plant growth.

Phytophthora root rot of soybean, caused by Phytophthora sojae, is one of the most important diseases in the Midwestern United States, and is estimated to cause losses of up to 1.2 million metric tons per year. Disease may also be caused by P. sansomeana; however, the prevalence and damage caused by this species is not well known, partly due to limitations of current diagnostic tools. Efficient, accurate, and sensitive detection of pathogens is crucial for management. Thus, multiplex qPCR and isothermal RPA (recombinase polymerase amplification) assays were developed using a hierarchical approach to detect these Phytophthora spp. The assays consist of a genus-specific probe and two species-specific probes that target the atp9-nad9 region of the mitochondrial genome that is highly specific for the genus Phytophthora. The qPCR approach multiplexes the three probes and a plant internal control. The RPA assays run each probe independently with a plant internal control multiplexed in one amplification, obtaining a result in as little as 20 mins. The multicopy mitochondrial genome provides sensitivity with sufficient variability to discern among different Phytophthora spp. The assays were highly specific when tested against a panel of 100 Phytophthora taxa and range of Pythium spp. The consistent detection level of the assay was 100 fg for the qPCR assay and 10 pg for the RPA assay. The assays were validated on symptomatic plants collected from Michigan (U.S.) and Ontario (Canada) during the 2013 field season, showing correlation with isolation. In 2014, the assays were validated with samples from nine soybean producing states in the U.S. The assays are valuable diagnostic tools for detection of Phytophthora spp. affecting soybean.

Oomycete pathogens are commonly associated with soybean root rot and have been estimated to reduce soybean yields in the United States by 1.5 million tons on an annual basis. Limited information exists regarding the frequency and diversity of oomycete species across the major soybean-producing regions in North America. A survey was conducted across 11 major soybean-producing states in the United States and the province of Ontario, Canada. In 2011, 2,378 oomycete cultures were isolated from soybean seedling roots on a semiselective medium (CMA-PARPB) and were identified by sequencing of the internal transcribed spacer region of rDNA. Sequence results distinguished a total of 51 Pythium spp., three Phytophthora spp., three Phytopythium spp., and one Aphanomyces sp. in 2011, with Pythium sylvaticum (16%) and P. oopapillum (13%) being the most prevalent. In 2012, the survey was repeated, but, due to drought conditions across the sampling area, fewer total isolates (n = 1,038) were collected. Additionally, in 2012, a second semiselective medium (V8-RPBH) was included, which increased the Phytophthora spp. isolated from 0.7 to 7% of the total isolates. In 2012, 54 Pythium spp., seven Phytophthora spp., six Phytopythium spp., and one Pythiogeton sp. were recovered, with P. sylvaticum (14%) and P. heterothallicum (12%) being recovered most frequently. Pathogenicity and virulence were evaluated with representative isolates of each of the 84 species on soybean cv. Sloan. A seed-rot assay identified 13 and 11 pathogenic species, respectively, at 13 and 20°C. A seedling-root assay conducted at 20°C identified 43 species as pathogenic, having a significantly detrimental effect on the seedling roots as compared with the noninoculated control. A total of 15 species were pathogenic in both the seed and seedling assays. This study provides a comprehensive characterization of oomycete species present in soybean seedling roots in the major production areas in the United States and Ontario, Canada and provides a basis for disease management and breeding programs.

Accelerating the pace of microbiome science to enhance crop productivity and agroecosystem health will require transdisciplinary studies, comparisons among datasets, and synthetic analyses of research from diverse crop management contexts. However, despite the widespread availability of crop-associated microbiome data, variation in field sampling and laboratory processing methodologies, as well as metadata collection and reporting, significantly constrains the potential for integrative and comparative analyses. Here we discuss the need for agriculture-specific metadata standards for microbiome research, and propose a list of “required” and “desirable” metadata categories and ontologies essential to be included in a future minimum information metadata standards checklist for describing agricultural microbiome studies. We begin by briefly reviewing existing metadata standards relevant to agricultural microbiome research, and describe ongoing efforts to enhance the potential for integration of data across research studies. Our goal is not to delineate a fixed list of metadata requirements. Instead, we hope to advance the field by providing a starting point for discussion, and inspire researchers to adopt standardized procedures for collecting and reporting consistent and well-annotated metadata for agricultural microbiome research.

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Corn is a staple feed and biofuel crop with a value close to $3.7 billion dollars for Michigan’s economy. Knowledge about distribution and abundance of seedling pathogens in Michigan corn fields is limited. Here we used a combination of culture-based and next-generation sequencing of soil samples to determine the extent of species associated with diseased corn seedlings and those present in soil. Over 2 years, symptomatic seedlings and associated soil samples were collected from 11 Michigan fields. A total of 170 oomycete cultures were obtained from seedlings using a semiselective medium (CMA-PARPB) and identified using the internal transcribed spacer region. Thirty-three species were isolated, with Pythium inflatum (25%; clade B) and P. sylvaticum (12%; clade F) being the most abundant species. For the amplicon-based approach, the cytochrome oxidase subunit I marker (COI) mitochondrial region was amplified from soil samples and sequenced using Illumina MiSeq. The dominant Pythium clades present in the soil were F, I, D, and B and accounted for at least 75% of the abundance in all locations. Pythium clades F, I, and D were recovered with similar trends with the culture and amplicon approach; however, clade B was highly abundant in plant isolation, but not in soil. The 20 most abundant species were characterized for pathogenicity and fungicide sensitivity. P. irregulare and P. ultimum var. ultimum were the most virulent at both 15 and 20°C. Isolates were tested for their sensitivity to mefenoxam and ethaboxam. Most isolates were sensitive to both chemistries, but P. rostratifingens and P. aff. torulosum were less sensitive to ethaboxam and P. ultimum var. ultimum less sensitive to mefenoxam. The survey and isolate characterization provides a better understanding of seedling and root rot disease of corn and opportunities to improve management of this disease complex.

Hoeksema et al. Ecosystem Consequences of Ectomycorrhizal Invasions controlled laboratory experiments. Finally, we illustrate how ecosystem modeling can be used to link fungal traits to their consequences for ecosystem N and C cycling in the context of biological invasions, and we highlight exciting avenues for future directions in understanding EM invasion.