Back

Root rot by Phytophthora cinnamomi shifts the composition and structure of avocado rhizosphere fungal communities

Alfaro-Garcia, R. G.; Cisneros-Martinez, A. M.; Patino-Conde, V.; Rebollar, E. A.; Guerrero-Analco, J. A.; Mendez-Bravo, A.; Reverchon, F.

2026-07-11 microbiology
10.64898/2026.07.10.737851 bioRxiv
Show abstract

Rhizosphere microbial communities contribute to the growth and health of their host but may be altered by the incidence of soil-borne pathogens. In avocado, the oomycete Phytophthora cinnamomi, causal agent of Phytophthora root rot (PRR), has been shown to alter rhizosphere bacterial communities, although its effect on fungal communities has seldom been explored. Our objective was thus to determine whether P. cinnamomi induced shifts in diversity, composition and co-occurrence networks of fungal communities in the rhizosphere of avocado trees, and to identify potential antagonists of P. cinnamomi that could be further considered for disease management. Fungal communities associated with the rhizosphere of asymptomatic and PRR-symptomatic avocado trees were studied through ITS metabarcoding. Although -diversity metrics were not significantly different between asymptomatic and PRR-symptomatic trees, differences in {beta}-diversity of rhizosphere fungal communities were detected. Moreover, PRR led to the enrichment of saprotrophic taxa and opportunistic pathogens such as Fusarium, Cladosporium or Plectosphaerella in the avocado rhizosphere, which were possibly attracted by the release of resources from necrosed roots. Co-occurrence network analysis revealed that fungal networks in the rhizosphere of PRR-symptomatic trees were more complex and connected than those from asymptomatic trees, suggesting a response of fungal communities to the disturbance caused by the pathogen. Some connector taxa from the PRR-symptomatic networks (Gibellulopsis, Cladorrhinum or Mycenella) were also identified as members of the P. cinnamomi pathobiome. Their negative correlations with the pathogen indicate they may act as potential antagonists, which calls for further isolation efforts to confirm their biocontrol activity of PRR.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

1
Frontiers in Microbiology
427 papers in training set
Top 0.7%
10.4%
2
Scientific Reports
3612 papers in training set
Top 6%
8.7%
3
Environmental Microbiome
29 papers in training set
Top 0.1%
7.7%
4
PLOS ONE
5266 papers in training set
Top 22%
7.7%
5
FEMS Microbiology Ecology
54 papers in training set
Top 0.1%
6.6%
6
Fungal Ecology
12 papers in training set
Top 0.1%
5.4%
7
Microbiology Spectrum
469 papers in training set
Top 3%
4.7%
50% of probability mass above
8
Environmental Microbiology
133 papers in training set
Top 0.9%
3.4%
9
Applied and Environmental Microbiology
339 papers in training set
Top 2%
3.1%
10
Microbiological Research
22 papers in training set
Top 0.1%
3.0%
11
Microorganisms
106 papers in training set
Top 0.8%
2.7%
12
Environmental Microbiology Reports
31 papers in training set
Top 0.2%
2.4%
13
Plant and Soil
18 papers in training set
Top 0.2%
2.3%
14
FEMS Microbiology Letters
17 papers in training set
Top 0.1%
2.3%
15
Phytobiomes Journal
27 papers in training set
Top 0.2%
2.3%
16
mSystems
394 papers in training set
Top 4%
1.7%
17
The ISME Journal
228 papers in training set
Top 2%
1.7%
18
Frontiers in Plant Science
256 papers in training set
Top 3%
1.7%
19
Journal of Fungi
32 papers in training set
Top 0.4%
1.5%
20
Microbial Ecology
29 papers in training set
Top 0.5%
1.3%
21
Communications Biology
993 papers in training set
Top 23%
1.1%
22
mBio
833 papers in training set
Top 10%
1.1%
23
Molecular Plant Pathology
25 papers in training set
Top 0.3%
1.0%
24
Phytopathology®
31 papers in training set
Top 0.5%
1.0%
25
ISME Communications
120 papers in training set
Top 2%
1.0%
26
Microbial Pathogenesis
17 papers in training set
Top 0.4%
0.8%
27
Applied Soil Ecology
11 papers in training set
Top 0.2%
0.8%
28
FEMS Microbes
16 papers in training set
Top 0.3%
0.8%
29
mSphere
302 papers in training set
Top 7%
0.8%
30
Plant Pathology
18 papers in training set
Top 0.3%
0.6%