Tami-35. Detecting Single-cell Interactions in Organotypic Cultures of Glioblastoma Using Barcoded Rabies Virus
Year: 2021
Type: conference-abstract
Abstract: Cell-cell interactions are thought to drive tumor-promoting signals in the microenvironment of glioblastoma, but standard approaches for single cell analysis do not directly identify cell interactions and the mechanisms that mediate them. We recently developed a novel method to analyze cell-cell interactions—rabies barcode interaction detection followed by sequencing (RABID-seq), which combines barcoded viral tracing and single-cell RNA sequencing (scRNAseq). RABID-seq was first implemented in transgenic mice to investigate the interactions of astrocytes with other cells in the CNS enabling the study of astrocyte connectome perturbations and candidate therapeutic targets in multiple sclerosis and its pre-clinical model, experimental autoimmune encephalomyelitis (EAE). Here, we report the first use of RABID-seq in human tissues in organotypic cultures established from three IDH-wildtype glioblastoma (GBM) patients. In organotypic GBM cultures, initial infection by pseudotyped barcoded rabies virus deficient for viral glycoprotein was achieved after previous culture transduction with a lentivirus containing the avian TVA receptor and rabies glycoprotein under the human EF1a promoter. We employed this system to initially infect approximately 1,000 malignant or non malignant cells in the tumor microenvironment. After five days, infected cells were isolated from cultures and processed for single cell analysis using SMART seq. We were able to capture at least 6,000 interacting cells per tumor specimen, from which barcodes were recovered and cDNA was sent for sequencing. Here we present connectomic data from our initial cohort of three glioblastoma patients as an introduction to RABID-seq, with a focus on astrocyte-tumor interactions. Candidate mechanisms of cellular interactions will undergo functional validation in murine models of glioblastoma.
Source: Neuro-Oncology
Authors: Brian Andersen, Michael Wheeler, Zhaorong Li, E Antonio Chiocca, David Reardon, Francisco Quintana
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: bronze
OpenAlex ID: W3215875756