bioRxiv Science⌕ Search

Biology subjects

Cisneros-Martinez, A. M.

Publications and source records attributed to Cisneros-Martinez, A. M..

2 recordsLinked to original sources

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

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.

microbiology↗

Comparative evaluation of bioinformatic tools for virus-host prediction and their application to a highly diverse community in the Cuatro Cienegas Basin, Mexico

The sheer diversity of unculturable viruses has prompted the need to describe new viruses through culture-independent techniques. The associated host is one important phenotypic feature that can be inferred from metagenomic viral contigs -- thanks to the development of various bioinformatic tools. Here we compare the performance of recently developed tools for virus-host prediction on a dataset of 1,046 virus-host pairs and then apply the best-performing tools on a metagenomic dataset derived from a highly diverse transiently hypersaline site known as Archaean Domes within the Cuatro Cienegas Basin, Coahuila, Mexico. We also introduce a virus-host prediction tool called CrisprCustomDB, which uses specific criteria to solve controversial host assignments with custom spacers databases. Host-dependent alignment-based methods showed an average precision of 83% and a sensitivity from 13.7% to 17.7%, whereas host-dependent alignment-free methods achieved an average precision of 75.7% and a sensitivity of 57.5%. RaFAH, a virus-dependent alignment-based tool, had the best performance overall (F1_score = 95.7%). However, when applied to the highly diverse metagenomic dataset, the host-dependent alignment-based (e.g., CrisprCustomDB) and alignment-free (e.g., PHP) methods showed the greatest agreement with each other, even though they are fundamentally different methods. This is because instead of depending on known hosts or viruses-with-known-host databases, they can directly relate metagenomic viral contigs and metagenome-assembled genomes from the same dataset. Such methods also showed the greatest consistency between the source environment and the predicted host taxonomy, habitat, lifestyle, or metabolism, revealing that Archaean Domes viruses likely infect halophilic Archaea as well as a variety of Bacteria which may be halophilic, halotolerant, alkaliphilic, thermophilic, oligotrophic, sulfate-reducing or marine-related. Consequently, using a combination of methods and qualitative validations relating to the source environment and the predicted host biology will increase the number of correct predictions, mainly when dealing with novel viruses.

bioinformatics↗