DATA ANALYSIS AND MICROBIOME INTERVENTION FOR PERSONALISED MEDICINE

The course belongs to the PhD course in Engineering Physics and Materials inside the curriculum of Technologies of Bio and Nanomaterials. This course explores the intersection of microbiome research, data analysis, and personalized medicine. Students will learn how to analyze microbiome data and develop personalized intervention strategies based on microbiome profiles. The course combines theoretical concepts with practical applications, emphasizing computational approaches to microbiome data analysis.

By the end of this course, students will be able to:
1. Understand the fundamental concepts of the human microbiome and its role in health and disease
2. Apply statistical and computational methods to analyze microbiome datasets
3. Interpret microbiome data in the context of personalized medicine
4. Design microbiome-based interventions for specific health conditions
5. Critically evaluate current research in microbiome science and personalized medicine
6. Communicate microbiome analysis results effectively to both scientific and clinical audiences

Knowledge of statistics and biology

This course explores the intersection of microbiome research, data analysis, and personalized medicine. Students will learn what is the microbiome and how to analyze microbiome data and develop personalized intervention strategies based on microbiome profiles. The course combines theoretical concepts with practical applications.
-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;
-Based therapeutics for microbiome intervention: prebiotics, probiotics, postbiotics, fecal microbial transplantation;
-Experimental methods and models to study gut microbiome complexity in vitro
-Computational methods to unravel microbiome. Analysis of Methods for microbiome sampling and sample preparation: 16S rRNA gene library preparation and metagenomic library preparation. Analysis of sequencing data (16S rRNA, metagenomic, metatranscriptomic) and their applications. Approaches for integrating microbiome with other omics data.

All the didactic materials will be provided by the teacher, such as scientific articles and research papers, online tutorials for relevant software tools (R, QIIME2, Python), access to public microbiome datasets.

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 final grade will be calculated based on the scores achieved during the oral presentation, 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 theoretical and practical lectures. During the lessons, PowerPoint slides and tutorials for the analysis of the microbiota will be used. 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