Metagenomic Analyses of Microbiomes

By the end of the course, students are expected to be able to master:

Knowledge:

• briefly describe the main steps involved in DNA isolation from complex microbiome samples and consequences for data analysis
• describe the pros and cons of using 16S rRNA gene amplicon sequencing approaches
• describe the pros and cons of using a shotgun DNA sequencing approach
• describe the key steps involved in bioinformatic analysis of next generation sequencing data from microbiomes
• describe principles of quantitative statistical analyses of microbiome sequencing data
• describe methods to compare microbiome samples

Skills:

• perform basic bioinformatic analysis on microbiome data through the UNIX command-line interface: de novo assembly, gene detection and annotation, contigs binning in Metagenome-Assembled Genomes, read mapping, etc.
• perform basic statistical data analyses in R: contigs coverage normalization; differential abundance analysis; metabolic pathways reconstruction; etc.
• present orally and in writing key aspects of different experimental approaches to study microbiomes and their effects on the host organism.
• propose studies for microbiomes and their interactions with their living environment and potential host organisms

Competences:

• evaluate the molecular techniques used to investigate microbiomes
• evaluate the basic bioinformatic methods used to analyse microbiome sequencing data
• evaluate basic statistical methods used to analyse and draw biological inferences from microbiome data
• independently retrieve and evaluate information from peer-reviewed scientific literature

• discuss original scientific articles and reviews on the impact of microbiomes on their environments and host organisms.

• present a coherent essay on a specific topic on microbe-microbe or microbe-host interactions within microbiomes