Isolation of Endothelial Cells from the Lumen of Mouse Carotid Arteries for Single-Cell Multi-Omics Experiments
Summary
We present a method for isolating endothelial cells and nuclei from the lumen of mouse carotid arteries exposed to stable or disturbed flow conditions to perform single-cell omics experiments.
Abstract
Atherosclerosis is an inflammatory disease of the arterial regions exposed to disturbed blood flow (d-flow). D-flow regulates the expression of genes in the endothelium at the transcriptomic and epigenomic levels, resulting in proatherogenic responses. Recently, single-cell RNA sequencing (scRNAseq) and single-cell Assay for Transposase Accessible Chromatin sequencing (scATACseq) studies were performed to determine the transcriptomic and chromatin accessibility changes at a single-cell resolution using the mouse partial carotid ligation (PCL) model. As endothelial cells (ECs) represent a minor fraction of the total cell populations in the artery wall, a luminal digestion method was used to obtain EC-enriched single-cell preparations. For this study, mice were subjected to PCL surgery to induce d-flow in the left carotid artery (LCA) while using the right carotid artery (RCA) as a control. The carotid arteries were dissected out two days or two weeks post PCL surgery. The lumen of each carotid was subjected to collagenase digestion, and endothelial-enriched single cells or single nuclei were obtained. These single-cell and single-nuclei preparations were subsequently barcoded using a 10x Genomics microfluidic setup. The barcoded single-cells and single-nuclei were then utilized for RNA preparation, library generation, and sequencing on a high-throughput DNA sequencer. Post bioinformatics processing, the scRNAseq and scATACseq datasets identified various cell types from the luminal digestion, primarily consisting of ECs. Smooth muscle cells, fibroblasts, and immune cells were also present. This EC-enrichment method aided in understanding the effect of blood flow on the endothelium, which could have been difficult with the total artery digestion method. The EC-enriched single-cell preparation method can be used to perform single-cell omics studies in EC-knockouts and transgenic mice where the effect of blood flow on these genes has not been studied. Importantly, this technique can be adapted to isolate EC-enriched single cells from human artery explants to perform similar mechanistic studies.
Introduction
This laboratory previously demonstrated that induction of d-flow leads to quick and rugged atherosclerosis development in hyperlipidemic mice1,2. The novel mouse model of d-flow-induced atherosclerosis was possible using partial carotid ligation (PCL) surgery 3. PCL surgery induces low and oscillatory blood flow condition or d-flow in the ligated left carotid artery (LCA). In contrast, the contralateral right carotid artery (RCA) continues to face stable laminar flow (s-flow). Previously, to understand the effect of d-flow on endothelial cells, the carotid arteries were dissected out after partial ligation surgery and flushed with a phenol and guanidine isothiocyanate-based lysing agent (luminal RNA/DNA flushing method)2,4, which provided endothelial-enriched "pooled bulk" RNAs or DNAs. These pooled bulk RNAs or DNAs were then processed for transcriptomic studies or epigenomic DNA methylome studies, respectively4,5,6. These studies helped discover multiple flow-sensitive genes and microRNAs whose roles in endothelial biology and atherosclerosis were extensively investigated4,6,7.
However, despite endothelial enrichment, these bulk RNA/DNA studies could not distinguish the specific role of each cell type in the artery wall in d-flow-induced atherosclerosis. Endothelial-enriched single-cell (sc) isolation and scRNA and scATAC sequencing studies were performed to overcome this limitation8. For this, C57Bl6 mice were subjected to the PCL surgery to induce d-flow in the LCA while using the s-flow-exposed RCA as control. Two days or two weeks after the PCL surgery, the mice were sacrificed, and the carotids were dissected and cleaned up. The lumen of both LCAs and RCAs were infused with collagenase, and the luminal collagenase digests containing ECs as a significant fraction and other arterial cells were collected. The single-cell suspension (scRNAseq) or single-nuclei suspension (scATACseq) were prepared and barcoded with unique identifiers for each cell or nucleus using a 10x Genomics setup. The RNAs were subjected to cDNA library preparation and sequenced.
The scRNAseq and scATACseq datasets were processed using the Cell Ranger Single-Cell Software and further analyzed by Seurat and Signac R packages9,10. Each cell and nucleus was assigned a cell type from these analyses and clustered into the cell type based on the marker genes and unique gene expression patterns. The results of the scRNAseq and scATACseq demonstrated that these single-cell preparations are enriched with ECs and also contain smooth muscle cells (SMCs), fibroblasts, and immune cells.
Further analysis revealed that the EC population in the luminal digestion is highly divergent and plastic (8 different EC clusters) and responsive to blood flow. Most importantly, these results demonstrated that d-flow reprograms ECs from an athero-protected anti-inflammatory phenotype to pro-atherogenic phenotypes, including pro-inflammatory, endothelial-to-mesenchymal transition, endothelial stem/progenitor cell transition, and most surprisingly, endothelial-to-immune cell-like transition. In addition, scATACseq data reveal novel flow-dependent chromatin accessibility changes and transcription factor binding sites in a genome-wide manner, which form the basis of several new hypotheses. The methodology and protocol for preparing single endothelial cells for single-cell multi-omics studies from the mouse carotid arteries are detailed below.
Protocol
Representative Results
Discussion
This paper provides a detailed protocol to isolate single-cell preparations from the mouse carotid arteries. The influence of d-flow on the endothelial cells can be accurately studied if the PCL surgery is performed correctly. It is crucial to correctly identify the branches of the common carotid, such as the external carotid, internal carotid, occipital artery, and superior thyroid artery. Validation of flow patterns by ultrasonography further validates the successful onset of d-flow conditions. Althou…
Declarações
The authors have nothing to disclose.
Acknowledgements
This work was supported by funding from National Institutes of Health grants HL119798, HL095070, and HL139757 to HJ. HJ is also supported by the Wallace H. Coulter Distinguished Faculty Chair Professorship. The services provided by the Emory Integrated Genomics Core (EIGC) were subsidized by the Emory University School of Medicine and were also partly supported by the Georgia Clinical and Translational Science Alliance of the National Institutes of Health under award no. UL1TR002378. The content provided above is solely the authors' responsibility and does not reflect the official views of the National Institutes of Health.
Materials
| Chemicals, Peptides, and Recombinant Proteins | |||
| 1x PBS (Cell Culture Grade) | Corning | 21040CMX12 | |
| 1.5 mL Protein LoBind Microcentrifuge Tubes | Eppendorf | 022-43-108-1 | |
| 15 mL Centrifuge Tube – Foam Rack, Sterile | Fablab | FL4022 | |
| 50 mL SuperClear Centrifuge Tubes | Labcon | 3191-335-028 | |
| 6-0 Silk Suture Sterile | Covidien | s-1172 c2 | |
| 70 µm Cell Strainer, White, Sterile, Individually Packaged | Thermo Fisher Scientic | 08-771-2 | |
| Accutase solution,sterile-filtered | Sigma-Aldrich | A6964-100ML | or equivalent |
| ATAC Buffer (Component I of Transposition Mix) | 10x Genomics | 2000122 | |
| ATAC Enzyme (Component II of Transposition Mix) | 10x Genomics | 2000123/ 2000138 | |
| Bovine Serum albumin | Sigma-Aldrich | A7906-500G | |
| Buprenorphine | Med-Vet International | RXBUPRENOR5-V | |
| Chromium Controller & Next GEM Accessory Kit | 10X Genomics | 1000204 | |
| Chromium Next GEM Single Cell 3' Reagent Kits v3.1 | 10X Genomics | 1000121 | |
| Chromium Next GEM Single Cell ATAC Reagent Kits v1.1 | 10X Genomics | 1000175 | |
| Collagenase II | MP Biomedicals | 2100502.5 | |
| Digitonin | Sigma-Aldrich | D141-100MG | |
| Dissecting Forceps | Roboz Surgical Instruments Co | RS-5005 | |
| Dnase1 | New England Biolabs Inc | M0303S | |
| Centrifuge (Benchtop-Model # 5425) | Eppendorf | 22620444230VR | |
| Fetal Bovine Serum – Premium Select | R&D systems | S11550 | |
| Fixed Angle Rotor | Eppendorf | FA-45-24-11-Kit Rotor | |
| HEPES buffered saline | Millipore Sigma | 51558 | |
| Insulin syringe (3/10 mL 29 G syringe) | BD | 305932 | |
| Isoflurane | Patterson vet | 789 313 89 | |
| MACs Smart Strainers (30 µm) | Miltenyi Biotec | 130-098-458 | |
| MACS SmartStrainers (100 µm) | Miltenyi Biotec | 130-098-463 | |
| Normal Saline (0.9% sodium chloride) | Baxter International Inc | 2B1323 | |
| Nuclei Buffer (20x) | 10x Genomics | PN 2000153/2000207 | |
| PBS (10x), pH 7.4 | Thermo Fisher Scientic | 70011-044 | |
| Small scissors | Roboz Surgical Instruments Co | RS-5675 | |
| Stainless Steel Micro Clip Applying Forceps With Lock | Roboz Surgical Instruments Co. | RS-5480 | or similar |
| Tissue Mend II | Webster Veteinanry | 07-856-7946 | |
| Type II Collagenase | MP biomedicals | 2100502.1 | |
| Deposited Data | |||
| scATACseq FastQ files | NCBI | www.ncbi.nlm.nih.gov/bioproject Accession # PRJNA646233 | |
| scRNAseq FastQ files | NCBI | www.ncbi.nlm.nih.gov/bioproject Accession # PRJNA646233 | |
| Software and Algorithms | |||
| Cell Ranger 3.1.0 | 10X Genomics | https://support.10xgenomics.com/ single-cell-gene-exp | |
| Cicero | Pliner et al., 2018 | https://cole-trapnell-lab.github.io/cicero-release/ | |
| Ggplot2 v3.2.1 | Hadley Wickham | https://cran.r-project.org | |
| Harmony | Korsunsky et al., 2019 | https://github.com/immunogenomics/harmony | |
| ImageJ | Schneider et al., 2012 | https://imagej.nih.gov | |
| Monocle 2.8.0 | Qiu et al., 2017 | https://github.com/cole-trapnell-lab/ monocle-release | |
| R version 3.6.2 | R Foundation | https://www.r-project.org | |
| Seurat 3.1.3 | Stuart et al., 2019 | https://github.com/satijalab/seurat | |
| Signac 0.2.5 | Stuart et al., 2019 | https://github.com/timoast/signac |
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