NEAP24: Understanding metabolic diseases
We want to understand metabolic disease progression.
Nowadays the creation of multi-modal data sets is becoming increasingly simple: the relevant
techniques (e.g. 10X Genomics scRNA-seq, Visium spatial RNA-seq, etc.) are mostly
commercially available, and thus easy to use by a wetlab. However, shedding light into the stack of data is extremely
complicated.
Student Group 1
In the NEAP summer of 2023 a group of highly dedicated students created a multi-modal data set for atherosclerosis.
This year, we want to extend this data set to cardio-vascular diseases (CVDs) in general and create a whole single-cell atlas for CVDs using mainly multi-modal data sets from diseased and normal conditions.
Integrative tools, such as SCENIC+, MetaCells or scKINETICS (and others), shall be applied to gain relevant insight into the different diseases.
Student Group 2
Moreover, researchers aim to include different kinds of measurements: transcriptomics, proteomics and
metabolomics. While gene expression and protein abundance are meant to be well correlated, the inclusion
of metabolomics is a new topic when it comes to analyses.
We thus want to explore existing models and shape new analysis methods for analysing multi-modal datasets by combining transcriptomics, proteomics and metabolomics. The overall goal will be the development of a new method which predicts active metabolites and metabolic programs from (single cell) gene expression data only. This is not only an interesting scientific question, but it has been shown that metabolites releases from dying cells are used as "good-bye" signals to actively modulate outcomes in tissues. Thus, understanding which reaction is induced by which metabolite is of high relevance for understanding complex human diseases, such as cardio-vascular diseases.
By combining both projects we want to answer (some of) the following questions: Which CVDs are similar, which ones are very different? In which pathways or gene clusters can these CVDs be differentiated? Which genes correspond with which proteins and which metabolic compounds? Is it possible to describe the different CVDs in terms of different metabolic compositions?
This course is very much research oriented. Experience with sc/sn/spatialRNA-seq analyses is welcome, but not required beforehands.
This practical lab may have some joint presentations with the practical course by Prof. Zimmer.
LiteraturLiterature
- Metabolites released from apoptotic cells act as tissue messengers
- Using Gene Expression to Study Specialized Metabolism—A Practical Guide
- Metacells untangle large and complex single-cell transcriptome networks
- scKINETICS: inference of regulatory velocity with single-cell transcriptomics data
