(in Polish) Metagenomics 2600-OG-EN-MET

https://moodle.umk.pl/course/view.php?id=5746 (term 2023/24Z)

C1. Introduction to metagenomics. Matagenomics as a tool in microbial ecology. Importance of metagenomics and prospects for development.
C2. Isolation of biological material for metagenomic analyses. Methods and tools for DNA/RNA isolation. Requirements and quality of genetic material.
C3. Early stages of NGS data processing.
C4. Metataxonomic studies. Abundant and rare OTUs, Venn diagrams. Taxonomy visualization.
C5. Rarefaction curves. Subsampling
C6. Alpha diversity metrics (Shannon-Wiener index, Simpson index, Simpson).
C7. Beta diversity. Distance, similarity/dissimilarity. Cluster analysis
C8. Beta diversity. Ordination methods (PCA, PCoA)
C9. Hypothesis testing (ANOSIM, SIMPER, PERMANOVA)
C10. Correlations, microbiome network
C11. Genome sequencing
C12. Using genome information for identification (ANI, in silico DDH).
C13. Genome annotation in Rast Server. The role of microorganisms in the environment.
C 14-15. Students' own work. Development of analytical results, preparation of a report, and presentation of conclusions.

Term 2023/24Z:

None

Total student workload

Contact hours with teacher: - participation laboratory 30 hrs - consultations- 1 hr Self-study hours: np. - preparation for laboratory 20 hrs - writing essays/ papers/ projects- 5 hrs Altogether: 61 hrs (2 ECTS)

Learning outcomes - knowledge

Student W1: Describes and explains complex phenomena occurring in microbial communities. W2: Explains the interactions between the environment and the organisms living in it. W3: Demonstrates knowledge of statistical analysis and specialized computer tools to describe the course of natural phenomena. W4: Has knowledge of molecular biology to evaluate biological material W5: Has up-to-date knowledge in biological sciences (biochemistry, genetics, microbiology, and physiology) Translated with www.DeepL.com/Translator (free version)

Learning outcomes - skills

Student U1: Applies advanced statistical knowledge in the description of biological phenomena. U2: Uses a computer to find information, communicate, organize and analyze data, prepare reports, and present results U3: Uses source information in English, analyzes, synthesizes, summarizes, and makes a critical evaluation that allows for correct conclusions

Learning outcomes - social competencies

Atudent K1: Understands the need for continuous improvement of knowledge through scientific and popular scientific journals. K2: Is aware of the responsibility for the reliability of the analysis and expertise carried out K3: Shows criticism towards the results of his work K4: Demonstrates the ability to use mathematical, statistical and computer methods to develop and present results and analyses K5 Is aware of the importance of language skills in communication and information acquisition

Teaching methods

- informative lecture - theoretical and practical classes using the Moodle platform

Expository teaching methods

- informative (conventional) lecture

Exploratory teaching methods

- seminar
- practical
- project work

Online teaching methods

- methods referring to authentic or fictitious situations
- content-presentation-oriented methods
- exchange and discussion methods

Type of course

elective course

Prerequisites

Basic knowledge of molecular biology and statistics. Working with R and Past v4.03. Proficiency in spoken and written English.

Course coordinators

Agnieszka Kalwasińska

Assessment criteria

Assessment methods:
- activity (12 tasks to perform)
- final project

Assessment criteria:

fail- 0-50%
satisfactory- 55-64 %
satisfactory plus- 65-73%
good – 74-82%
good plus- 83-91%
very good- 92-100%

Practical placement

not applicable

Bibliography

1. Benedetti C (Ed) Metagenomics, Methods, Application and Perspectives (2014) Nova Publishers, New York
2. Taş N., de Jong A. E. E., et al. (2021). Metagenomic tools in microbial ecology research. Current Opinion in Biotechnology.
3. Kim N., et al. (2024). Genome-resolved metagenomics: a game changer for microbiome medicine. Experimental & Molecular Medicine.
4. Nam N. N. (2023). Metagenomics: An effective approach for exploring microbial diversity and functions. (Review, open access, PMC).

Term 2023/24Z:

None

Notes

Term 2023/24Z:

None

Additional information

Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system:

Description of 2600-OG-EN-MET in USOSweb