Development and evaluation of Microbe Finder (MiFi)®: a novel in silico diagnostic platform for pathogen detection from metagenomic data.

Introduction. With expanding demand for diagnostics, newer methodologies are needed for faster, user-friendly and multiplexed pathogen detection. Metagenome-based diagnostics offer potential solutions to address these needs as sequencing technologies have become affordable. However, the diagnostic utility of sequencing technologies is currently limited since analysis of the large amounts of data generated, are either computationally expensive or carry lower sensitivity and specificity for pathogen detection.Hypothesis/Gap Statement. There is a need for novel, user friendly, and computationally inexpensive platforms for metagenome sequence analysis for diagnostic applications.Methods. In this study, we report the use of MiFi® (Microbe Finder), a computationally inexpensive algorithm with a user-friendly online interface, for accurate, rapid and multiplexed pathogen detection from metagenome sequence data. Detection is accomplished based on identification of signature genomic sequence segments of the target pathogen in metagenome sequence data. In this study we used bovine respiratory disease (BRD) complex as a model.Results and Conclusions. Using MiFi®, multiple target bacteria and a DNA virus were successfully detected in a multiplex format from metagenome sequences acquired from bovine lung tissue. Overall, 51 clinical samples were assessed and MiFi® showed 100 % analytical specificity and varying levels of analytical sensitivity (62.5 %-100 %) when compared with other traditional pathogen detection techniques, such as PCR. Consistent detection of bacteria was possible from lung samples artificially spiked with 109-104 c.f.u. of Mannheimia haemolytica.

A Step Towards Validation of High-Throughput Sequencing for the Identification of Plant Pathogenic Oomycetes.

The advancement in high-throughput sequencing (HTS) technology allows the detection of pathogens without the need for isolation or template amplification. Plant regulatory agencies worldwide are adopting HTS as a prescreening tool for plant pathogens in imported plant germplasm. The technique is a multipronged process and, often, the bioinformatic analysis complicates detection. Previously, we developed E-probe diagnostic nucleic acid analysis (EDNA), a bioinformatic tool that detects pathogens in HTS data. EDNA uses custom databases of signature nucleic acid sequences (e-probes) to reduce computational effort and subjectivity when determining pathogen presence in a sample. E-probes of Pythium ultimum and Phytophthora ramorum were previously validated only using simulated HTS data. However, HTS samples generated from infected hosts or pure culture may vary in pathogen concentration, sequencing bias, and data quality, suggesting that each pathosystem requires further validation. Here, we used metagenomic and genomic HTS data generated from infected hosts and pure culture, respectively, to further validate and curate e-probes of Pythium ultimum and Phytophthora ramorum. E-probe length was found to be a determinant of diagnostic sensitivity and specificity; 80-nucleotide e-probes increased the diagnostic specificity to 100%. Curating e-probes to increase specificity affected diagnostic sensitivity only for 80-nucleotide Pythium ultimum e-probes. Comparing e-probes with alternative databases and bioinformatic tools in their speed and ability to find Pythium ultimum and Phytophthora ramorum demonstrated that, although pathogen sequence reads were detected by other methods, they were less specific and slower when compared with e-probes.

An In Silico Detection of a Citrus Viroid from Raw High-Throughput Sequencing Data.

E-probe Diagnostic for Nucleic Acid Analysis (EDNA) is a user-friendly bioinformatic tool that has been adapted for the detection and identification of citrus exocortis viroid (CEVd). Here, we describe the procedures for RNA extraction from citrus tissues, library and sequencing preparation, and the utilization of EDNA Mi-Finder online platform on raw high-throughput sequencing (HTS) data.

TASPERT: Target-Specific Reverse Transcript Pools to Improve HTS Plant Virus Diagnostics.

High-throughput sequencing (HTS) is becoming the new norm of diagnostics in plant quarantine settings. HTS can be used to detect, in theory, all pathogens present in any given sample. The technique's success depends on various factors, including methods for sample management/preparation and suitable bioinformatic analysis. The Limit of Detection (LoD) of HTS for plant diagnostic tests can be higher than that of PCR, increasing the risk of false negatives in the case of low titer of the target pathogen. Several solutions have been suggested, particularly for RNA viruses, including rRNA depletion of the host, dsRNA, and siRNA extractions, which increase the relative pathogen titer in a metagenomic sample. However, these solutions are costly and time-consuming. Here we present a faster and cost-effective alternative method with lower HTS-LoD similar to or lower than PCR. The technique is called TArget-SPecific Reverse Transcript (TASPERT) pool. It relies on pathogen-specific reverse primers, targeting all RNA viruses of interest, pooled and used in double-stranded cDNA synthesis. These reverse primers enrich the sample for only pathogens of interest. Evidence on how TASPERT is significantly superior to oligodT, random 6-mer, and 20-mer in generating metagenomic libraries containing the pathogen of interest is presented in this proof of concept.

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

Agricultural high throughput diagnostics need to be fast, accurate and have multiplexing capacity. Metagenomic sequencing is being widely evaluated for plant and animal diagnostics. Bioinformatic analysis of metagenomic sequence data has been a bottleneck for diagnostic analysis due to the size of the data files. Most available tools for analyzing high-throughput sequencing (HTS) data require that the user have computer coding skills and access to high-performance computing. To overcome constraints to most sequencing-based diagnostic pipelines today, we have developed Microbe Finder (MiFi®). MiFi® is a web application for quick detection and identification of known pathogen species/strains in raw, unassembled HTS metagenomic data. HTS-based diagnostic tools developed through MiFi® must pass rigorous validation, which is outlined in this manuscript. MiFi® allows researchers to collaborate in the development and validation of HTS-based diagnostic assays using MiProbe™, a platform used for developing pathogen-specific e-probes. Validated e-probes are made available to diagnosticians through MiDetect™. Here we describe the e-probe development, curation and validation process of MiFi® using grapevine pathogens as a model system. MiFi® can be used with any pathosystem and HTS platform after e-probes have been validated.

Draft Genome Sequences of Three Isolates of Coniothyrium glycines, Causal Agent of Red Leaf Blotch of Soybean.

Coniothyrium glycines, the causal agent of red leaf blotch in soybeans, is considered a high-consequence biological agent. With limited genomic information known, there are no molecular genotyping or detection methods available. We report the draft genome sequences of three C. glycines isolates, greatly enhancing our knowledge of this species.

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

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).

Postweaning exposure to aflatoxin results in impaired child growth: a longitudinal study in Benin, West Africa.

Aflatoxins are dietary contaminants that are hepatocarcinogenic and immunotoxic and cause growth retardation in animals, but there is little evidence concerning the latter two parameters in exposed human populations. Aflatoxin exposure of West African children is known to be high, so we conducted a longitudinal study over an 8-month period in Benin to assess the effects of exposure on growth. Two hundred children 16-37 months of age were recruited from four villages, two with high and two with low aflatoxin exposure (50 children per village). Serum aflatoxin-albumin (AF-alb) adducts, anthropometric parameters, information on food consumption, and various demographic data were measured at recruitment (February) and at two subsequent time points (June and October). Plasma levels of vitamin A and zinc were also measured. AF-alb adducts increased markedly between February and October in three of the four villages, with the largest increases in the villages with higher exposures. Children who were fully weaned at recruitment had higher AF-alb than did those still partially breast-fed (p < 0.0001); the major weaning food was a maize-based porridge. There was no association between AF-alb and micronutrient levels, suggesting that aflatoxin exposure was not accompanied by a general nutritional deficiency. There was, however, a strong negative correlation (p < 0.0001) between AF-alb and height increase over the 8-month follow-up after adjustment for age, sex, height at recruitment, socioeconomic status, village, and weaning status; the highest quartile of AF-alb was associated with a mean 1.7 cm reduction in growth over 8 months compared with the lowest quartile. This study emphasizes the association between aflatoxin and stunting, although the underlying mechanisms remain unclear. Aflatoxin exposure during the weaning period may be critical in terms of adverse health effects in West African children, and intervention measures to reduce exposure merit investigation.