Presentation Title

Development of a simple and streamlined bioinformatics pipeline to extract custom database sequences from next-generation sequencing data

Faculty Mentor

Dr. Becket, Elinne

Start Date

23-11-2019 8:00 AM

End Date

23-11-2019 8:45 AM

Location

69

Session

poster 1

Type of Presentation

Poster

Subject Area

biological_agricultural_sciences

Abstract

Development of a simple and streamlined bioinformatics pipeline to extract custom database sequences from next-generation sequencing data

The transfer of antibiotic resistance genes in microbial communities is of great importance to study because they effect many aspects of human and ecological health. Using next-generation sequencing (NGS) of microbial communities, one is able to investigate which antibiotic resistance genes occur in that population. Currently, bioinformatic pipelines exist that align DNA sequences to antibiotic gene databases and then utilize visualization tools for the analyses of that DNA sequence. However, these tools are often not user-friendly, are computationally intensive, and are prone to sequence alignment errors. Therefore, we sought to develop a user-friendly streamlined code that could rapidly extract antibiotic resistance genes from any reference database using basic terminal commands. To accomplish this, we initially developed a set of Linux-based commands by combining Bowtie2, Samtools, and GROOT, while utilizing the Comprehensive Antibiotic Resistance Database (CARD) as reference for NGS datasets. This resulted in rapid and effective analyses of antibiotic resistance genes from Southern California coastal water samples. The pipeline was further improved by piping multiple steps into one single command, reducing large datafile outputs and hard disk space. We also included the option to run multiple samples in parallel, which can easily be utilized on machines with stronger computing power. Future goals include compiling these codes into a single executable file for any novice researcher to use in analyzing next-generation sequencing data. The completed bioinformatics pipeline may be used to produce comprehensive antibiotic resistome gene profiles, or it can be customized to use with any desired database.

This document is currently not available here.

Share

COinS
 
Nov 23rd, 8:00 AM Nov 23rd, 8:45 AM

Development of a simple and streamlined bioinformatics pipeline to extract custom database sequences from next-generation sequencing data

69

Development of a simple and streamlined bioinformatics pipeline to extract custom database sequences from next-generation sequencing data

The transfer of antibiotic resistance genes in microbial communities is of great importance to study because they effect many aspects of human and ecological health. Using next-generation sequencing (NGS) of microbial communities, one is able to investigate which antibiotic resistance genes occur in that population. Currently, bioinformatic pipelines exist that align DNA sequences to antibiotic gene databases and then utilize visualization tools for the analyses of that DNA sequence. However, these tools are often not user-friendly, are computationally intensive, and are prone to sequence alignment errors. Therefore, we sought to develop a user-friendly streamlined code that could rapidly extract antibiotic resistance genes from any reference database using basic terminal commands. To accomplish this, we initially developed a set of Linux-based commands by combining Bowtie2, Samtools, and GROOT, while utilizing the Comprehensive Antibiotic Resistance Database (CARD) as reference for NGS datasets. This resulted in rapid and effective analyses of antibiotic resistance genes from Southern California coastal water samples. The pipeline was further improved by piping multiple steps into one single command, reducing large datafile outputs and hard disk space. We also included the option to run multiple samples in parallel, which can easily be utilized on machines with stronger computing power. Future goals include compiling these codes into a single executable file for any novice researcher to use in analyzing next-generation sequencing data. The completed bioinformatics pipeline may be used to produce comprehensive antibiotic resistome gene profiles, or it can be customized to use with any desired database.