DATA ANALYSIS AND MICROBIOME INTERVENTION FOR PERSONALISED MEDICINE

The course belongs to the PhD course in PHYSICAL AND MATERIALS ENGINEERING - curriculum BIO AND NANOMATERIAL TECHNOLOGIES. This course provides advanced training in the analysis of microbiome data and the design of microbiome-based interventions for personalised medicine. Students will integrate computational biology, systems biology, and clinical translation to understand host–microbiome interactions and develop precision therapeutic strategies.

By the end of the course, students will be able to:

Critically evaluate microbiome datasets and experimental designs
Apply advanced statistical and machine learning methods to omics data
Analyze metagenomic, metatranscriptomic, and metabolomic datasets
Interpret host–microbiome interactions in health and disease
Design microbiome-based interventions (dietary, probiotic, FMT, etc.)
Integrate multi-omics data for personalised medicine applications.

Basic knowledge of microbiology, computer science, and molecular biology

Human Microbiome
• Human microbiome: Overview of microbiome composition; diversity of human microbiotas; the central rule of gut microbiome; microbiome-host coevolution; microbiome in health and diseases;
• Gut microbiome-organ axis: gut-brain axis, gut-skin axis; gut-vagina axis, gut-liver axis, gut-lung axis;
• Microbiome-drugs interaction;
• In vitro, in vivo and ex vivo models to study host-microbiome interaction
Microbiome data analysis
• 16S rRNA sequencing vs shotgun metagenomics
• Metatranscriptomics and Translatomics
• Sequencing platforms and biases
• Data preprocessing and quality control
• Pipeline for metagenomic data analysis
Microbiome-Based Interventions
• Probiotics, prebiotics, synbiotics
• Dietary modulation strategies
• Fecal microbiota transplantation (FMT)
• Microbiome engineering and synthetic biology

All the didactic materials will be provided by the teacher. There is no book for this course.

The assessment of learning will be conducted through a brief oral presentation, during which the following competencies will be evaluated:
-Integration of Course Content: The student’s ability to incorporate at least one relevant concept from the course into their current PhD research project, demonstrating a clear connection between theory and practice.
-Critical Thinking Skills: The candidate’s ability to engage in critical analysis of the topic presented, showcasing a depth of understanding and thoughtful evaluation of the material.
-Expository and Communication Skills: Clarity of presentation, formal and concise expression of ideas, and the use of appropriate scientific language throughout the discourse. The ability to respond effectively and coherently to questions posed by the evaluators will also be assessed.
-Participation and Engagement: Active and consistent participation in lessons will be considered in the final evaluation, reflecting the candidate's commitment to the course material.

oral

The instructor is responsible for ensuring the authenticity and originality of all examinations and coursework. In cases of suspected academic misconduct, an additional on-site assessment may be required during the exams, which may differ from the standard format.

The final grade will be calculated based on the scores achieved in each of these areas, following the criteria below:
18-23: Adequate basic knowledge with some uncertainties in presentation. The student demonstrates a general understanding of the topic, though with some gaps or difficulties in critical analysis.
24-26: Solid knowledge and the ability to apply concepts correctly. Clear presentation, with good command of scientific terminology and effective communication.
27-29: Excellent understanding and ability to connect and integrate theoretical concepts with research. Presentation is fluent, precise, and well-organized.
30 and 30L: Comprehensive knowledge, impeccable presentation, and the ability to critically analyze and establish complex connections. Honors are awarded for exceptional performance, demonstrating skills well above average.

Teaching is organized in frontal theoretical lectures. PowerPoint slides will be used during the lessons. The teaching material is present and downloadable from the University's Moodle e-learning platform.

This subject deals with topics related to the macro-area "Human capital, health, education" and contributes to the achievement of one or more goals of U. N. Agenda for Sustainable Development