Transregio 274: Checkpoints of Central Nervous Recovery

Aims of this project

The central nervous system (CNS), consisting of the brain and spinal cord in vertebrates, can suffer injuries through various pathways.
The tissue's response to such injury is diverse,
ranging from irreversible destruction to complete reconstitution of the nerve tissue.
The processes governing these different outcomes are largely unknown.

Our multidisciplinary research team from Munich and Göttingen, composed of experts in the fields of
immunology, neurobiology, and glial biology,
has established the TRR274 research consortium to comprehend and investigate the biology of the
intricate mechanisms that determine recovery after a CNS injury.

Our aim is to define the immunological, glial, and neuronal checkpoints that regulate the structural and
functional recovery of damaged nerve tissue.
Subsequently, these insights will be utilized to develop medical intervention strategies targeting these checkpoints,
aiming to specifically enhance neuronal regeneration potential while avoiding tissue scarring.

For more information see the official homepage TRR 274 or the DFG homepage.

Genomics and Bioinformatic Platform (Project Z02)

Strategy: We provide important expertise and have established methods in genomics and bioinformatics, which will be adapted and tailored to suit the needs of the CRC research projects and thereby enable important insights into checkpoints of central nervous system recovery. In this project, we will provide central support and training infrastructure as well as perform original research in method development as well as with integrative data analysis.

As the understanding of the multicellular response determining recovery after CNS injury, requires all PIs to have access to cutting-edge experimental and computational methods, we have centralized and integrated our expertise within a Genomics and Bioinformatics Platform Z02. Starting from the first funding period this project supports our entire consortium from experimental design to bioinformatics data analysis for genomic methods, which include bulk genomic analysis and single cell methods such as scRNAseq and snRNASeq. These technologies include 10x Genomics and flow-cytometry based isolation methods. In addition we provide training to CRC members on tissue dissociation and single-cell sorting and usage of 10x Genomics equipment to generate highquality data. By centralizing the sample preparation, sequencing and analysis, our core provides methods for rapid turnaround and high-quality data. Our analyses have provided critical insights into the complex cellular reactions that occur upon CNS injury in the various model. We have, for example, uncovered various reactive glial states that drive pathological processes in injury conditions. In the upcoming funding period we want to further expland our method development and project support and in particular focus on the development of methods and tools to integrate CRC datasets across models and species. These data range from different genomic, epigenomic, transcriptomic or proteomic data, to imaging data to complex high-dimensional spatial transcriptomics or single-cell data. Based on this datasets, data analysis methods and processing pipelines to analyze and interpret these data will be developed in order to provide a central platform that helps to standardize data analysis and facilitate data integration within the CRC. Thus, one focus will be on the integrative and comparative analyses of the responses that occur after various injuries and in the different models. Another important focus for the upcoming funding period will be to analyze human samples. One limitation, however, is that samples can be highly variable and biased by the cause of death and post-mortem time. We will, therefore, leverage information from our model organisms, and perform integrated analyses of mouse and human datasets. A second focus is the development of data acquisition and analysis pipelines for combined spatial transcriptomics and single cell sequencing data from experimental and human (in collaboration with Z01) tissue samples. The overall aim of this integrative data analysis is to help identify the checkpoints of central nervous systems recovery, understand which of these checkpoints are shared across disease models and species and determine their relevance for human CNS pathologies in situ.

Contribution of the Department of Medical Bioinformatics

Genomics and Bioinformatics Platform (Project Z02)

The constant improvements in high-throughput technologies have dramatically changed the way biological systems are studied. These technologies produce comprehensive molecular profiles at high resolution and reveal mechanistic clues for cellular responses to injury and recovery. As a large number of the CRC projects depend on various “-omics” approaches the Genomics and Bioinformatics Platform Z02 supports users on all levels from project planning to analysis support. The platform offers bulk and single-cell genomic measurements and analysis. In addition, we provide bioinformatics and data analysis expertise and training, as well as consulting for experimental design for RNASeq, proteomics, epigenomics and lipidomics datasets. This allows CRC scientists to obtain high quality and reproducible genomic data and help them share and compare datasets between projects. The goals of the Genomics and Bioinformatics Platform Z02 are:

• Aim ❶ Analysis platform: This will provide access to state-of-the-art methods and protocols in: (i) setting up the Z02 Beißbarth/Klughammer/Simons 382 experimental design, (ii) optimizing sample preparation, (iii) generating single-cell or bulk genomic data, (iv) bioinformatics support for genomic datasets, (v) bioinformatics support for non-genomic datasets. In addition, we will provide overarching and integrative analyses of datasets obtained from the different sub-projects to build overarching hypotheses and models.
   
• Aim ❷ Technology development: We will (i) establish single-molecule spatial transcriptomics technology (MERFISH) for human tissue, generate and integrate data with single nuclear RNA sequence to create a cellular map of human MS lesions in collaboration with the Bioimaging and Tissue Analysis Platform Z01. (ii) develop computational approaches for the inter-individual (e.g. groups of patients), inter-”model” (e.g. stroke vs. trauma vs. inflammation) and inter-“species” (e.g. human vs. mouse) comparison of single cell and spatial transcriptomics data, and (iii) develop computational approaches for integrative analysis of different omics data to infer molecular interaction networks

Coordination and Project Partners