From pathogen to endophyte: an endophytic population of Verticillium dahliae evolved from a sympatric pathogenic population.

The fungus Verticillium dahliae causes wilts of several hundred plant species, including potato and mint. Verticillium spp. also colonize sympatric hosts such as mustards and grasses as endophytes. The evolutionary history of and interactions between pathogenic and endophytic of this fungus are unknown. Verticillium dahliae isolates recovered from sympatric potato, mint, mustard and grasses were characterized genotypically with microsatellite markers and phenotypically for pathogenicity. The evolutionary history of pathogenic and endophytic populations was reconstructed and gene flow between populations quantified. Verticillium dahliae was recovered from all hosts. Endophytic populations were genetically and genotypically similar to but marginally differentiated from the potato population, from which they evolved. Bidirectional migration was detected between these populations and endophytic isolates were pathogenic to potato and behaved as endophytes in mustard and barley. Verticillium dahliae colonizes plants as both endophytes and pathogens. A historical host-range expansion together with endophytic and pathogenic capabilities are likely to have enabled infection of and gene flow between asymptomatic and symptomatic host populations despite minor differentiation. The ability of hosts to harbor asymptomatic infections and the stability of asymptomatic infections over time warrants investigation to elucidate the mechanisms involved in the maintenance of endophytism and pathogenesis.

Does Coinoculation with Different Verticillium dahliae Genotypes Affect the Host or Fungus?

Inferences about Verticillium dahliae are often deduced from experiments where hosts are inoculated with one isolate. The assumption that the outcomes from these experiments scale with V. dahliae diversity is untested. The objectives of this research were to test the hypotheses that (i) coinoculation with combinations of isolates affects plant biomass, disease expression, and fungal colonization; and (ii) hosts select for the specific isolates. Potato, mustard, and barley plants were coinoculated with seven combinations of three isolates. Genotypes recovered from infected plants were genotyped with microsatellite markers. Disease expression and fungal colonization but not plant biomass of potato was affected by coinoculation (F = 7.07, P < 0.0001; F = 2.36, P = 0.0427) and depended on the isolates with which plants were inoculated. One genotype was disproportionately selected for by all hosts. Putative heterokaryons were recovered from mustard plants coinoculated with isolates of different vegetative compatibility groups (VCG). These results support the assumption that mixed infections have marginal impacts on plant biomass but challenge the assumption that they do not affect disease expression and fungal colonization. Finally, this research provides evidence that plants select for specific V. dahliae genotypes and isolates from different VCGs can anastomose in planta.

Verticillium isaacii is a Pathogen and Endophyte of Potato and Sunflower in the Columbia Basin of Washington.

The objective of this research was to test the hypothesis that Verticillium isaacii causes diseases of sunflower and potato plants. Two sunflower genotypes and one potato cultivar were inoculated with five V. isaacii isolates and three pathogenic V. dahliae isolates. Biomass, disease expression, and stem colonization were quantified. Overt wilt symptoms were observed on both sunflower genotypes and potato plants inoculated with a subset of the V. isaacii isolates. Biomass of both sunflower genotypes was not affected by V. isaacii infection. Tuber yields either decreased in response to infection by one V. isaacii isolate or were not affected by infection. Stems of sunflower and potato plants were infected by at least four of the five V. isaacii isolates. A new disease of sunflower and potato is documented. Evidence that V. isaacii exhibits different lifestyles including pathogenicity and endophytism is presented. Finally, this research documents variation in fungal lifestyles that can exist in samples from a single field.

Evidence of a trans-kingdom plant disease complex between a fungus and plant-parasitic nematodes.

Disease prediction tools improve management efforts for many plant diseases. Prediction and downstream prevention demand information about disease etiology, which can be complicated for some diseases, like those caused by soilborne microorganisms. Fortunately, the availability of machine learning methods has enabled researchers to elucidate complex relationships between hosts and pathogens without invoking difficult-to-satisfy assumptions. The etiology of a destructive plant disease, Verticillium wilt of mint, caused by the fungus Verticillium dahliae was reevaluated with several supervised machine learning methods. Specifically, the objective of this research was to identify drivers of wilt in commercial mint fields, describe the relationships between these drivers, and predict wilt. Soil samples were collected from commercial mint fields. Wilt foci, V. dahliae, and plant-parasitic nematodes that can exacerbate wilt were quantified. Multiple linear regression, a generalized additive model, random forest, and an artificial neural network were fit to the data, validated with 10-fold cross-validation, and measures of explanatory and predictive performance were compared. All models selected nematodes within the genus Pratylenchus as the most important predictor of wilt. The fungus after which this disease is named, V. dahliae, was the fourth most important predictor of wilt, after crop age and cultivar. All models explained around 50% of the total variation (R2 ≤ 0.46), and exhibited comparable predictive error (RMSE ≤ 1.21). Collectively, these models revealed that the quantitative relationships between two pathogens, mint cultivars and age are required to explain wilt. The ascendance of Pratylenchus spp. in predicting symptoms of a disease assumed to primarily be caused by V. dahliae exposes the underestimated contribution of these nematodes to wilt. This research provides a foundation on which predictive forecasting tools can be developed for mint growers and reminds us of the lessons that can be learned by revisiting assumptions about disease etiology.