Università Roma Tre

This course is designed to equip students with key concepts for analyzing their microbiome-related multi-omics data and how to handle large datasets. It contains plenary lectures, case studies, practical lessons, and a final seminar, as follows:

Plenary lectures:
1 Introduction to the history of DNA studies and sequencing of genomes.
2 Introduction to the genomics for prokaryotes and its techniques (sequencing, annotation, gene family content, duplications, and deletions).
3 Comparing the recent next-generation sequencing (NGS) platforms; Analytical databases, tools, and pipelines (annotations); Phylogeny based on 16S, 25-28S, ITS.
4 Inferring the mechanisms of evolution from large genomic data sets: Horizontal gene transfer and mobilome; alignment; synteny detection; Multiple whole gene alignments.
5 Pan-genome and core-genome/ dispensable genome concepts.
6 Metagenomics approaches; Transcriptomics and gene chips; Proteome and interactome and Metabolomics.
7 Biotechnology and synthetic biology by omics: Genomics of single cells; Systems biology and health; Genetic Manipulations-Expression of heterologous genes in bacteria Evolution of bacterial genomes; Molecular phylogeny; Microbial taxonomy methods and species concept; Classification of prokaryotes; Culture analysis of microbial communities; Enrichment cultures; Isolation of single cells; Flow cytometry; Microfluidic techniques; High-throughput systems; Gas chromatography techniques.
8 Introduction to microbial ecology and new microbiome-related approaches.
Case studies:
Case study: Sequencing data preparation and analyses.
Cases study: Analysing microbiomes: alpha and beta diversity and main tools.
Case study: Analysing shotgun samples (Read-based and assembly-based approaches).
Case study: Studying procaryote gene virulences and antibiotic resistance genes (ARGs) and manipulating large datasets.
Case study: Cave microbiomes and omics under oligotrophic conditions.
Case study: Study of the biodegradation of hydrocarbons using NGS tools and bioremediation approaches.
Case study: Microbiota and food.
Practical classes:
- Practical classes: Introduction to Bash and Unix shell and command language.
- Practical classes: Manipulating microbial datasets with R and tidy verse:
- Practical classes: 16S metabarcoding studies and multiple profiling approaches (Alpha diversity, beta diversity, and others);
- Practical classes: Analyzing shotgun sequencing samples and different pipelines.
At the end-of-course, each student is asked to present a project during a seminar course (20 min/student). The projects will be selected during the lessons.

For any questions related to microbiomics courses, please contact us via:
Dr. Alif Chebbi, alif.chebbi@uniroma3.it (Researcher Bio19, Roma Tre university)
Dr. Irene Artuso, Irene.artuso@uniroma3.it (Postdoc and bioinformatician, Roma Tre university)

Books and basic tools:
"Brock biology of microorganisms" di Michael T. Madigan (Autore), Kelly S. Bender (Autore), Daniel H. Buckley (Autore), W. Matthew Sattley (Autore), David A. Stahl (Autore): capitoli 9.1-9.14; 12.1-12.5; 12.9; 12.11-12.13; 13.5-13.10; 19.1-19.12; 23.1; 23.12, 23.13; 24.1-24.11 (Italian or English)
Microbiota in health and disease: from pregnancy to childhood. Editors Pamela D. Browne, Eric Claassen and Michael D. Cabana Published: 2017 Pages: 344. eISBN: 978-90-8686-839-1 | ISBN: 978-90-8686-294-8 https://doi.org/10.3920/978-90-8686-839-1
The human microbiota: how microbial communities affect health and disease / edited by David N. Fredricks. ISBN 978-0-470-47989-6
Introducing the Shell (only basic command lines).
Introduction to RStudio (only basic concepts).
R packages for data science (https://www.tidyverse.org/)
QIIME 2.
DADA2.