Dataset Information

Design of Bacterial Strain-Specific qPCR Assays Using NGS Data and Publicly Available Resources and Its Application to Track Biocontrol Strains.

ABSTRACT: Biological control is emerging as a feasible alternative to chemical pesticides in agriculture. Measuring the microbial biocontrol agent (mBCA) populations in the environment is essential for an accurate environmental and health risk assessment and for optimizing the usage of an mBCA-based plant protection product. We hereby show a workflow to obtain a large number of qPCR markers suitable for robust strain-specific quantification. The workflow starts from whole genome sequencing data and consists of four stages: (i) identifying the strain-specific sequences, (ii) designing specific primer/probe sets for qPCR, and (iii) empirically verifying the performance of the assays. The first two stages involve exclusively computer work, but they are intended for researchers with little or no bioinformatic background: Only a knowledge of the BLAST suite tools and work with spreadsheets are required; a familiarity with the Galaxy environment and next-generation sequencing concepts are strongly advised. All bioinformatic work can be implemented using publicly available resources and a regular desktop computer (no matter the operating system) connected to the Internet. The workflow was tested with five bacterial strains from four different genera under development as mBCAs and yielded thousands of candidate markers and a triplex qPCR assay for each candidate mBCA. The qPCR assays were successfully tested in soils of different natures, water from different sources, and with samples from different plant tissues. The mBCA detection limits and population dynamics in the different matrices are similar to those in qPCR assays designed by other means. In summary, a new accessible, cost-effective, and robust workflow to obtain a large number of strain-specific qPCR markers is presented.

SUBMITTER: Hernandez I

PROVIDER: S-EPMC7077341 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Design of Bacterial Strain-Specific qPCR Assays Using NGS Data and Publicly Available Resources and Its Application to Track Biocontrol Strains.

Hernández Iker I Sant Clara C Martínez Raquel R Fernández Carolina C

Frontiers in microbiology 20200310

Biological control is emerging as a feasible alternative to chemical pesticides in agriculture. Measuring the microbial biocontrol agent (mBCA) populations in the environment is essential for an accurate environmental and health risk assessment and for optimizing the usage of an mBCA-based plant protection product. We hereby show a workflow to obtain a large number of qPCR markers suitable for robust strain-specific quantification. The workflow starts from whole genome sequencing data and consis ...[more]

PMID: 32210925

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Project description:The DC Cohort is an ongoing longitudinal observational study of persons living with HIV. To better understand HIV-1 drug resistance and potential transmission clusters among these participants, we performed targeted, paired-end next-generation sequencing (NGS) of protease, reverse transcriptase and integrase amplicons. We elected to use free, publicly-available software (HyDRA Web, Stanford HIVdb and HIV-TRACE) for data analyses so that laboratory personnel without extensive bioinformatics expertise could use it; making the approach accessible and affordable for labs worldwide. With more laboratories transitioning away from Sanger-based chemistries to NGS platforms, lower frequency drug resistance mutations (DRMs) can be detected, yet their clinical relevance is uncertain. We looked at the impact choice in cutoff percentage had on number of DRMs detected and found an inverse correlation between the two. Longitudinal studies will be needed to determine whether low frequency DRMs are an early indicator of emerging resistance. We successfully validated this pipeline against a commercial pipeline, and another free, publicly-available pipeline. RT DRM results from HyDRA Web were compared to both SmartGene and PASeq Web; using the Mantel test, R2 values were 0.9332 (p<0.0001) and 0.9097 (p<0.0001), respectively. PR and IN DRM results from HyDRA Web were then compared with PASeq Web only; using the Mantel test, R2 values were 0.9993 (p<0.0001) and 0.9765 (p<0.0001), respectively. Drug resistance was highest for the NRTI drug class and lowest for the PI drug class in this cohort. RT DRM interpretation reports from this pipeline were also highly correlative compared to SmartGene pipeline; using the Spearman's Correlation, rs value was 0.97757 (p<0.0001). HIV-TRACE was used to identify potential transmission clusters to better understand potential linkages among an urban cohort of persons living with HIV; more individuals were male, of black race, with an HIV risk factor of either MSM or High-risk Heterosexual. Common DRMs existed among individuals within a cluster. In summary, we validated a comprehensive, easy-to-use and affordable NGS approach for tracking HIV-1 drug resistance and identifying potential transmission clusters within the community.

Dataset Information

Design of Bacterial Strain-Specific qPCR Assays Using NGS Data and Publicly Available Resources and Its Application to Track Biocontrol Strains.

Publications

Design of Bacterial Strain-Specific qPCR Assays Using NGS Data and Publicly Available Resources and Its Application to Track Biocontrol Strains.

Similar Datasets

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