Trichoderma Strains from Amazonian River Sediments with Genomic and Biocontrol Data
by Thiago Fernandes Sousa·Updated 17d ago
2.0 MB1files
Available on 1 platform
Sign in to view source links and access this dataset
Description
44 Trichoderma fungal strains isolated from sediments of three major white-water Amazonian rivers (Juruá, Madeira, and Purus). The dataset includes molecular barcoding, phylogenetic analyses, morphological studies, biocontrol assays, and comparative genomics, leading to the description of five new species and new records for Brazil. The data was authored by Thiago Fernandes Sousa and last updated on May 20, 2026.
Use Cases
Taxonomic classification and discovery of novel fungal species based on multi-locus phylogenetic analyses described.
Comparative genomic analysis of CAZyme arsenals and biosynthetic gene clusters for secondary metabolites.
Screening for biocontrol agents against phytopathogens like Colletotrichum based on reported antagonistic activity assays.
Studying fungal diversity and distribution in underexplored Amazonian riverine ecosystems.
Strengths
Includes genomic and phenotypic data for 44 isolated strains.
Led to the formal description of five novel Trichoderma species.
Reports strong biocontrol activity, with one strain achieving >95% growth inhibition against multiple pathogens.
Comparative genomic analyses reveal specific CAZyme families and secondary metabolite clusters.
Limitations
Data is presented in a 2.0 MB PDF document; structured data tables are not provided.
Row count and column-level documentation are unknown, limiting direct machine-readability.
The geographic scope is limited to three specific Amazonian river systems.
Provenance
Source
Thiago Fernandes Sousa via figshare
Collection Method
Strains were isolated from sediments collected during a systematic expedition along the Juruá, Madeira, and Purus rivers, followed by polyphasic characterization.
Freshness
Last updated 2026-05-20 05:44:14
Geography
Amazonian white-water rivers: Juruá, Madeira, and Purus in Brazil.
Primary data is embedded within a scientific publication PDF; extracting structured data may require manual effort.