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Differences in Root-Zone Soil and Basal Stem Tissue Microbial Communities Between Asymptomatic and Diseased Citrus maxima var. Tomentosa Plants with Foot Rot

Oct 2026 · Microorganisms · Vol 14, pp. 2258 · 0 citations · 63 references
Medicine

TL;DR

These hypothesis-generating findings suggest microbial associations that may underlie foot rot pathogenesis and provide a basis for formulating testable hypotheses for sustainable disease management strategies, pending validation in larger, multi-site studies.

Abstract

Exocarpium Citri grandis, derived from Citrus maxima var. Tomentosa, is a precious traditional Chinese medicinal herb. However, foot rot, a severe soil-borne disease, threatens the sustainable cultivation of this crop. This exploratory study investigated microbial associations with foot rot using a limited sample set from a single orchard. Microbial communities in root-zone soil and basal stem tissues of asymptomatic and foot-rot-infected trees were analyzed via high-throughput sequencing. Significant differences in microbial diversity and community structure were observed between asymptomatic and foot-rot-infected trees. Root-zone microbial diversity was lower in diseased trees, whereas bacterial diversity increased but fungal diversity decreased in diseased basal stem tissues. Linear discriminant analysis effect size and correlation analyses revealed that beneficial prokaryotic genera, such as Bacillus, were negatively correlated with Fusarium. FUNGuild prediction indicated a functional shift in fungal communities from saprotrophic to pathogenic. Fusarium was significantly enriched in diseased samples; the HZY isolate from diseased tissues was identified as Fusarium solani-melongenae. Pathogenicity assays demonstrated that F. solani-melongenae was capable of causing foot rot symptoms. These hypothesis-generating findings suggest microbial associations that may underlie foot rot pathogenesis and provide a basis for formulating testable hypotheses for sustainable disease management strategies, pending validation in larger, multi-site studies.

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