Prof. Dr. med. Nikolaus Plesnila

Single-Cell Transcriptomics of Stroke and Nitric Oxide Treatment:
Investigating Microglia and Neuronal Responses in Mice

Overview: This project focuses on the analysis of single-cell sequencing (scRNA-seq) data originating from mouse brain tissue to unravel the complexity of cellular heterogeneity in mice subjected to stroke and an anti-inflammatory treatment involving inhaled nitric oxide (NO). The specific question addressed is how microglia and neurons respond to stroke and the subsequent inhalation of NO, focusing on the molecular and cellular changes that occur in these two cell types under these conditions. Single-cell sequencing is a cutting-edge technique that allows us to explore gene expression profiles at the resolution of individual cells. By leveraging this technology, we aim to answer key biological questions related to cellular function, differentiation, and communication in the context of stroke and NO treatment.

Objectives: The student will contribute to the data analysis workflow for single-cell RNA sequencing datasets. The main objectives are:

1. Data Preprocessing: Learn and apply standard methods for quality control, filtering, and normalization of raw single-cell sequencing data.
2. Dimensionality Reduction and Clustering: Use bioinformatics tools to identify cell populations (particularly microglia and neurons) and analyze their heterogeneity in response to stroke and NO treatment.
3. Differential Gene Expression Analysis: Explore genes driving differences between cell clusters (microglia and neurons) under the influence of stroke and NO inhalation.
4. Biological Interpretation: Work with the team to interpret the results in the context of the biological system being studied, focusing on the specific response of microglia and neurons to the stroke and NO intervention.

Key Responsibilities:

• Perform computational analyses using established pipelines (e.g., Seurat, Scanpy, or other single-cell analysis frameworks).
• Collaborate with lab members to generate meaningful visualizations (e.g., UMAP/t-SNE plots, heatmaps).
• Document progress and discuss results during weekly lab meetings.
• Gain an understanding of the biological context behind the dataset and integrate findings with ongoing research efforts.

Expected Outcomes: By the end of the project, the student will:

• Develop practical skills in single-cell sequencing data analysis.
• Gain proficiency in relevant bioinformatics tools and programming languages.
• Present their findings in a short presentation or written summary, particularly focusing on the cellular response of microglia and neurons to stroke and NO inhalation.

Qualifications and Skills:

• Enthusiasm for bioinformatics and computational biology.
• Basic programming experience (Python or R preferred) is beneficial but not mandatory.
• An interest in molecular biology, genetics, or related fields.
• Willingness to learn and work in an interdisciplinary environment.

This is an exciting opportunity to contribute to a real-world research project and acquire valuable skills in the rapidly growing field of single-cell transcriptomics, with a focus on understanding the cellular dynamics in stroke and inflammation.