RECOVER COMPLETE BIOLOGY
Use of the HIVE™ scRNAseq Solution: A Case Study with a Human Glioblastoma Resection
Key Takeaways
- HIVE™ scRNAseq Solution enables capture, storage, and processing of precious samples
- Integrated HIVE™ scRNAseq device storage preserves cellular complexity of glioblastoma sample
Single-cell RNA sequencing (scRNAseq) approaches can be used to understand sample heterogeneity and potential biomarker targets for cancerous tumor samples1. However, the logistics of scRNAseq experiments can be challenging to optimize. For human samples that are not collected in lab settings, fixation or freezing techniques are required to stabilize samples until sent to a centralized lab for processing. Through these methods, cells can be damaged, biological information lost, and data quality compromised – a cause for heightened concern when working with precious samples. Here, we present results from a Honeycomb beta tester laboratory demonstrating the efficacy of the HIVE™ scRNAseq Solution with a glioblastoma sample.
Freshly dissociated cells were captured in a HIVE™ device at the core facility. To accommodate the sample acquisition and preparation lead times, cell-loaded HIVE™ devices were stored after capture and the remainder of the workflow was completed one week later for convenience, without data compromise. The data show strong recovery of malignant cell types, including astro-mesenchymal and oligodendrocyte precursor cells.
Methods
Fresh human glioblastoma resections were used in this study. The sample was dissociated using Miltenyi Biotec’s Brain Tumor Dissociation Kit and gentleMACS™ Dissociator. After sample dissociation, ~20,000 cells were loaded into a single HIVE™ device. After addition of the Cell Preservation Solution, the cell-loaded HIVE™ device was frozen for one week at -20°C prior to processing and library preparation [Figure 1].
Single-cell libraries were generated using a HIVE™ scRNAseq Kit and protocol [workflow outlined in Figure 2], count matrix files were generated using BeeNet™ software, and data were analyzed using Seurat v4.0.5.
Figure 2. HIVE scRNAseq workflow
Figure 1. Experimental overview
Results
After thresholding for 500 genes and 1,000 transcripts and filtering for high quality single-cells, a UMAP plot of single cells from the HIVE™ device was generated and colored by cell type [Figure 3A]. ~4,400 high quality single-cells were recovered, with ~2,300 unique genes per cell and ~4,250 unique transcripts per cell. Sixteen cell-types were identified, including multiple distinct malignant clusters and myeloid clusters. Heterogeneity was observed within the malignant clusters. Additionally, there was robust and specific expression of marker genes for each cell type. Distinguishing between microglia and macrophage cell-types can be challenging due to their similarities in gene expression profiles. Here we see the robust expression of the microglia-specific marker P2RY12 restricted to one cluster [Figure 3B].
About 92% of the sample is composed of malignant cell-types and states, including astro-mesenchymal, proliferating, and oligodendrocyte precursor cells [Figure 4]. Frequencies of each cell class will vary depending on the biopsy.
Figure 3. A) UMAP plot of high-quality single cells from one HIVE™ device, colored by cell type identity. B) Dotplot showing the expression profile of specific marker genes (columns) for each cell type (rows)
Figure 4. Pie chart of sample composition showing proportions of cell classes recovered
Conclusions
These results demonstrate the efficacy of the HIVE™ scRNAseq Solution in capturing, storing, and processing precious samples for biomarker research. While cells are more prone to damage and incomplete recovery with other preservation methods, the HIVE™ scRNAseq Solution’s gentle capture and cell preservation enable users to see the full biological complexity of the sample. Particularly for samples which may arrive at core facilities at odd hours, integrated storage within the HIVE™ device is a verified option to decouple capture and processing workflows.
References
- Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). https://doi.org/10.1038/s41467-020-17186-5
For research use only. Not for use in diagnostic procedures.