Inferring the presence of aflatoxin-producing Aspergillus flavus strains using RNA sequencing and electronic probes as a transcriptomic screening tool

Abstract

E-probe Diagnostic for Nucleic acid Analysis (EDNA) is a bioinformatic tool originally developed to detect plant pathogens in metagenomic databases. However, enhancements made to EDNA increased its capacity to conduct hypothesis directed detection of specific gene targets present in transcriptomic databases. To target specific pathogenicity factors used by the pathogen to infect its host or other targets of interest, e-probes need to be developed for transcripts related to that function. In this study, EDNA transcriptomics (EDNAtran) was developed to detect the expression of genes related to aflatoxin production at the transcriptomic level. E-probes were designed from genes up-regulated during A. flavus aflatoxin production. EDNAtran detected gene transcripts related to aflatoxin production in a transcriptomic database from corn, where aflatoxin was produced. The results were significantly different from e-probes being used in the transcriptomic database where aflatoxin was not produced (atoxigenic AF36 strain and toxigenic AF70 in Potato Dextrose Broth).

A comparative assessment of conventional and molecular methods, including MinION nanopore sequencing, for surveying water quality

“…This makes it clear why the average MinION read accuracy (89% in our study) would make it difficult to reliably distinguish related species, such as those within the Enterobacteriaceae , that share a high sequence similarity. Recently developed methods such as Metagenomic phylogenetic analysis (MetaPhlAn) for species-level profiling in large scale microbial community studies 36 or Electronic probe Diagnostic for Nucleic acid Analysis (EDNA) to detect pathogens in metagenomics database 37 might overcome these challenges and contribute in reliably detecting putative pathogens at species level. In addition, both of these techniques use species-specific markers, and can decrease the probability of both false positive and false negative profiling of microorganisms.…”

Microbe Finder (MiFi®): Implementation of an Interactive Pathogen Detection Tool in Metagenomic Sequence Data

“…After the target and near neighbors are in the system, the developer can select the length of the e-probe sequences to be generated, starting at 20 nt up to 120 nt. Based on previous findings, we suggest using short e-probe sequences (20–60 nt) for viruses and long e-probe sequences (60–100 nt) for bacteria, fungi and oomycetes [ 6 , 20 ].…”

“…MiFi ® is a bioinformatic graphical user interface built to close the gap between HTS and pathogen detection. MiFi ® uses, as a founding concept, the E-probe Diagnostics for Nucleic acid Analysis (EDNA) process [ 5 , 6 ] that queries the metagenome raw data of the sample tissue and all resident microbes, to identify known pathogen sequences. The MiFi ® platform comprises two parts.…”

α-Amylase Production by Toxigenic Strains ofAspergillusandPenicillium

“…They proposed future directions for elucidating future relationship between resistance and susceptibility to the fungus' colonization, abiotic stress and its relationship to oxidative stress in which its aflatoxin B1 production may function as a form of antioxidant protection to the producing fungus. In a known positive transcriptomic database, E-probe Diagnostic for Nucleic acid Analysis (EDNA), a bioinformatic tool, originally developed to detect plant pathogens in mutagenomic databases, is capable of discriminating between production and non-production of aflatoxin B1 by Aspergillus flavus [119]. Substrate-induced lipase gene expression might be indirectly related to aflatoxin formation by providing the basic building block "acetate" for aflatoxin B1 synthesis in aflatoxin-producing Aspergillus flavus and Aspergillus parasiticus [120].…”