Simple Preservation of Single Cells (SENSE): One-Step Robust Whole Blood Cryopreservation Method Enables the Generation of High-Quality Single-Cell Immune Profiles
Authors: Satpathy Sarthak , Thomas Beena , Pilcher William , Bakhtiari Mojtaba , Ponder Lori A. , Pacholczyk Rafal , Prahalad Sampath , Bhasin Swati , Munn David H. , Bhasin Manoj 
Published: December 2023

Introduction: Single-cell profiling (SCP) has revolutionized our understanding of cellular and molecular states in health and disease. Current multistep methods for cryopreserving single-cell suspensions from blood for single-cell RNA sequencing (scRNA-seq) are time-consuming, require trained personnel and special equipment, limiting their clinical adoption and sample collection/availability. It is critical to develop protocols for efficient capture of precious clinical samples/implementation of SCP in clinics. We developed and validated the Simple prEservatioN of Single cElls (SENSE) method for single-step cryopreservation of whole blood (WB), which, along with granulocyte depletion during single-cell assay, generates high-quality SCPs.

Methods: Blood samples (n=6) were split into two parts and cryopreserved using the SENSE and peripheral blood mononuclear cells (PBMC) methods. In the SENSE method, WB was cryopreserved by mixing 1:1 blood and freezing solution (80% FBS, 20% DMSO) and granulocytes removed using EasySep CD15 positive selection kit. For PBMC method, density-gradient method was employed for isolating PBMCs followed by cryopreservation. Single cell assay was performed using 10x Genomics kits. The raw sequencing reads were aligned using 10x Genomics Cell Ranger (Zheng et al., Nat. Comm., 2017) to the reference human genome, and the gene-expression matrices were analyzed using the Seurat package (Hao et al., Cell, 2021). Cell markers were identified by comparing target cell types with others using the Wilcoxon Rank Sum test (adjusted P&lt;.10, average log2FC&gt;0.25, percent cell expression&gt;25%). Potential doublets were marked using the doubletFinder (McGinnis et al., Cell Syst., 2019) algorithm and batch-effect was quantified using Shannon entropy calculated by the CellMixS (Lutge et al., Life Sci Alliance. 2021) package for quality assessment of two methods. Cellular communications were assessed using CellChat, which measures cell-to-cell interactions based on the ligands and receptors expression (Jin et al., Nature Comm., 2021).

Results: Highly viable (86.3±1.51%) single-cell suspensions (22,353 cells) were obtained from the SENSE method's WB cryopreserved samples. The captured median gene counts, unique molecular identifiers (UMIs)/cell, and mitochondrial content were comparable between the two methods. Similar proportions of membrane, extracellular, and ribosomal ontology-related genes demonstrated the robustness of the SENSE method in capturing high-quality cells without introducing cellular damage artifacts. Lower doublets (2.4%) were observed with the SENSE method compared to the PBMC method (4.8%). These rigorous quality assessments demonstrated the effectiveness of the SENSE method for obtaining high-quality cells for SCP.

Both methods yielded similar transcriptomic profiles with split UMAPs of the integrated scRNA-seq data revealing similar clustering patterns except for some variations in the myeloid cells and T-cells clusters. The SENSE method cryopreserved samples exhibited significantly higher T-cell enrichment, enabling deeper characterization of T-cell subtypes. The functional landscape of T/NK cells was assessed using the CellChat tool. Most pathways showed a similar information flow pattern, indicating the capture of similar signaling networks between the cells processed using either of the two methods. However, the SENSE method captured lower number of myeloid cells, attributable to filtering out of sticky CD15+ myeloid/granulocytes that resulted in the loss of single-cells captured. Nevertheless, the SENSE method recapitulated the myeloid compartment associated with the disease as we observed similar patient-wise differences in cell types from both methods.

Finally, we compared the transcriptome profiles of both methods to a publicly available PBMC dataset (Zheng et al., Nat. Comm., 2017). Concordance between the three datasets was observed, with all cell types being consistently identified using key marker gene expression.

Conclusions: Comparative analysis of scRNA-seq datasets obtained with the two cryopreservation methods, i.e., SENSE and PBMC methods, yielded similar cellular and molecular profiles, confirming the suitability of the former method's incorporation in clinics/labs for cryopreserving and obtaining high-quality single-cells for conducting critical translational research.