Whole genome sequencing of bacterial genomes - tools and applications

Course Overview

This course provides an overview of Whole Genome Sequencing (WGS) of bacterial genomes and its applications in the medical sector. Learners will gain an understanding of WGS technology and its applications in surveillance of bacteria, including species identification, typing and characterization of antimicrobial resistance and virulence traits, as well as plasmid characterization. Through demonstrations and exercises, learners will learn how to use online tools and apply them to analyze data and obtain results that can be interpreted and used for different purposes. By the end of the course, learners should be able to describe the general principles in typing of bacteria, apply genomic tools for sub-typing and surveillance, define the concept of Next-Generation Sequencing and describe the sequencing data from NGS, enumerate the methods behind the tools for species identification, MLST typing and resistance gene detection, and utilize the tools for Salmonella and E.coli typing, plasmid replicon detection and plasmid typing in real cases of other bacterial and pathogen genomes. Learners will also be able to explain the concept and use the integrated bacterial analysis pipeline for batch analysis and typing of genomic data, construct phylogenetic trees and explain the relatedness of bacterial or pathogen strains, create their own sequence database, and use the MyDbFinder tool to detect genetic markers of interest from whole genome sequencing.

[Applications]
Upon completion of this course, learners should be able to apply the knowledge and skills acquired to the analysis of bacterial genomes using WGS technology. They should be able to use the tools and applications discussed in the course to identify species, type and characterize antimicrobial resistance and virulence traits, and detect plasmid replicons and plasmid typing. Learners should also be able to construct phylogenetic trees based on SNPs and create their own sequence databases. Additionally, learners should be able to use the MyDbFinder tool to detect genetic markers of interest from whole genome sequencing.

[Career Paths]
One job position path that could be recommended to learners of this course is a Bioinformatics Analyst. A Bioinformatics Analyst is responsible for analyzing and interpreting biological data using computer software and algorithms. They use their knowledge of computer science, mathematics, and statistics to develop and maintain databases, analyze data, and create models to solve biological problems. They also develop software and algorithms to analyze and interpret biological data. Bioinformatics Analysts are employed in a variety of industries, including pharmaceuticals, biotechnology, healthcare, and research.

The development trend of this job position is very positive. With the increasing demand for data analysis and interpretation in the medical sector, the need for Bioinformatics Analysts is expected to grow. Additionally, the development of new technologies and software is creating more opportunities for Bioinformatics Analysts to develop and maintain databases, analyze data, and create models to solve biological problems. As the demand for data analysis and interpretation continues to grow, the need for Bioinformatics Analysts is expected to increase.

[Education Paths]
The recommended educational path for learners interested in this course is to pursue a degree in Bioinformatics. Bioinformatics is a field of study that combines computer science, mathematics, and biology to analyze and interpret biological data. It is used to develop and apply computational methods to analyze and interpret biological data, such as DNA sequences, protein sequences, and gene expression data. Bioinformatics is a rapidly growing field, and the demand for professionals with expertise in this area is increasing.

A degree in Bioinformatics typically requires a bachelor's degree in a related field, such as computer science, mathematics, or biology. Students may also need to complete courses in computer programming, data analysis, and statistics. In addition, students may need to take courses in molecular biology, genetics, and biochemistry. After completing a bachelor's degree, students may pursue a master's degree in Bioinformatics. This degree typically requires two to three years of study and includes courses in advanced topics such as machine learning, data mining, and bioinformatics algorithms.

The development trend of Bioinformatics is towards the use of artificial intelligence and machine learning to analyze and interpret biological data. This trend is driven by the increasing availability of large datasets and the need to develop more efficient methods for analyzing and interpreting these datasets. In addition, the development of new technologies, such as next-generation sequencing, is driving the need for more sophisticated bioinformatics tools and techniques. As the field of Bioinformatics continues to evolve, the demand for professionals with expertise in this area is expected to increase.