The study describes a simple, quick, and partially automated protocol to isolate high-quality nuclei from frozen mammalian tissues for downstream single nuclei RNA sequencing.
Single-cell and single-nucleus RNA sequencing have become common laboratory applications due to the wealth of transcriptomic information that they provide. Single nucleus RNA sequencing, particularly, is useful for investigating gene expression in difficult-to-dissociate tissues. Furthermore, this approach is also compatible with frozen (archival) material. Here, we describe a protocol to isolate high-quality single nuclei from frozen mammalian tissues for downstream single nucleus RNA sequencing in a partially-automated manner using commercially available instruments and reagents. Specifically, a robotic dissociator is used to automate and standardize tissue homogenization, followed by an optimized chemical gradient to filter the nuclei. Lastly, we accurately and automatically count the nuclei using an automated fluorescent cell counter. The performance of this protocol is demonstrated on mouse brain, rat kidney, and cynomolgus liver and spleen tissue. This protocol is straightforward, rapid, and readily adaptable to various mammalian tissues without requiring extensive optimization and provides good quality nuclei for downstream single nuclei RNA sequencing.
Single-cell (sc) and single-nucleus (sn) RNA sequencing have become commonly used protocols in molecular and cellular biology due to the increased resolution of gene expression compared to bulk RNA sequencing. However, the isolation of good quality single cell and single nuclei preparations from solid tissues remains a challenge and is often the rate-limiting step in sc/sn-RNAseq experiments. Indeed, a plethora of protocols has been developed that use various chemical and mechanical procedures to obtain cell/nuclei suspensions1,2,3,4,5,6,7,8,9,10,11,12,13,14,15. Furthermore, strategies to clean up such preparations from debris/clumps, etc., range from flow sorting to filtration to washing. Such protocols are often manual (leading to user-related variability), can be time-consuming (leading to reduced cell/nucleus viability), and/or may require access to a flow cytometer for cell/nucleus sorting. This study focused on developing a simple, quick, and partially automated single nuclei isolation protocol from frozen mammalian tissues for downstream RNA sequencing applications. We focused specifically on nuclei isolation as opposed to cell isolation as it is compatible with the use of frozen tissues, rendering sample collection/processing more practical and enabling unbiased batching of samples, especially in time-course experiments. Furthermore, although the nuclear transcriptome does not fully reflect the cellular transcriptome, several studies have now shown that single nuclei RNA sequencing data is comparable to single cell RNA sequencing data for cell-type identification, even though the proportions of cell types can vary6,16,17,18,19.
Nuclei isolation consists of several steps: 1) mechanical or chemical disruption of the tissue to release the nuclei, 2) clean-up of debris and clumps, and 3) accurate counting of nuclei for preparation for downstream applications. In a number of protocols, step 1 frequently involves the use of a Dounce homogenizer in order to disrupt the tissue3,20. Alternatively, chemical methods can be used, although these often need to be optimized for different tissues2,5,6. We have experienced that a manual tissue disruption procedure is prone to operator-associated variability, leading to variable quality and yield of nuclei. In order to minimize technical variability and to have a more consistent and reproducible protocol that works across tissues, a protocol that uses a commercially available robotic tissue dissociator was developed21. For step 2, although buffer exchange is usually the simplest means for washing nuclei, we adopted the use of a relatively short sucrose gradient centrifugation step to have a more thorough removal of debris. For brain tissue specifically, we use a silica colloid gradient instead of a sucrose gradient for more effective myelin removal. Finally, for counting, the use of a hemocytometer is the gold standard for counting and visually inspecting the nuclei. In our protocol, this step can be reliably automated using a commercially available automated fluorescent cell counter22. This protocol has been tested and is compatible with several frozen mammalian tissues, including brain, kidney, spleen, and liver, from different mammalian species (rat, mouse, and non-human primate) and provides good quality nuclei for downstream single nuclei RNA sequencing with a droplet-based commercial platform. The protocol takes approximately 75 min from tissue preparation to the start of the single nuclei RNA sequencing workflow.
All animal studies were conducted with the approval of the cantonal veterinary authority of Basel-Stadt in strict adherence to the Swiss federal regulations on animal protection or with the approval of the Institutional Animal Care and Use Committee in compliance with the German Animal Welfare Act.
1. Tissue and reagent/instrument preparation
2. Tissue homogenization and nuclei isolation
3. Nuclei clean-up
4. Counting
5. Library preparation
6. Sequencing
The performance and versatility of this protocol are demonstrated by performing single nuclei RNA sequencing on fresh frozen brain occipital cortex tissue from three B6 mice, fresh frozen transversally cut kidney tissue from three Wistar rats, archival (11-year-old) liver and spleen tissue from three Mauritian Cynomolgus macaques. All animals were non-perfused.
As shown in Figures 1B,C, good-quality nuclei that were free of signs of blebbing, debris, and clumping were obtained. The sucrose gradient-based filtration was optimized to remove the majority of debris by testing different densities, spin speeds, and times, and assessing the nuclear purity/integrity under a microscope as well as assessing nuclei size distribution and yield (Figure 1D). This allowed us to choose a sucrose gradient density of 1.5 M and to use a short spin time of 15 min. Next, to further assess the quality of the nuclei, the data was preprocessed using 10X Cell Ranger, and further downstream data analysis was performed using Besca23. Nuclei with >5% percent mitochondrial content (as these tend to be damaged/stressed nuclei) were filtered out, and nuclei with 500-7,000 genes (to minimize empty droplets and multiplets) were retained. We only included genes that were present in at least 30 nuclei. We targeted 8,000 nuclei per brain cortex sample and 10,000 nuclei per kidney, liver, and spleen sample. After filtration, 10,644 high-quality nuclei from the three brain samples, 14,960 high-quality nuclei from the three kidney samples, 18,795 high-quality nuclei from the three liver samples, and 13,882 high-quality nuclei from the three spleen samples were obtained. Figure 2A,D,G,J show violin plots representing the distribution of UMI counts, gene counts, and mitochondrial content in each sample. The median number of counts across all brain samples was 7,563 UMI/nucleus and 3,208 genes/nucleus. The median number of counts across all kidney samples was 3,841 UMI/nucleus and 1,915 genes/nucleus. The median number of counts across all liver samples was 2,649 UMI/nuclei and 1,676 genes/nuclei. The median number of counts across all spleen samples was 1,609 UMI/nuclei and 1,138 genes/nuclei. We then generated clusters using highly variable genes and annotated them using known marker genes17,24,25,26. As seen in Figure 2B,E,H,K, we were able to identify the expected cell types from each tissue. Furthermore, as seen in Figure 2B,E,H,K, all animals contributed to all clusters, indicating overall low technical variability introduced by the protocol. Furthermore, the cellular proportions were comparable in all three samples per tissue type, as were the UMI and gene counts (Figure 2A,C,D,F,G,I,J,L). A notable exception is the liver, where the hepatocyte populations among the three liver samples were different in proportions and profile. This is most likely due to biological differences between the animals (sex, age, metabolic status).
Figure 1: Assessment of nuclei quality and sucrose gradient optimization. (A) The expected phase separation during sucrose gradient centrifugation is shown with an arrow. (B) Representative fluorescent images of propidium iodide-stained rat kidney (top) and cynomolgus spleen (bottom) nuclei obtained with the protocol. (C) Representative bright field microscopy images of nuclei isolated from mouse liver (top) and mouse brain (bottom), scale bar 500 µm. Note the regular smooth surface of nuclei indicating good nuclear quality. (D) Sucrose gradient optimization. Several sucrose densities, spin speeds, and spin times were tested. Bright-field microscopy images of nuclei, nuclei size distribution, and nuclei yield are shown for each condition. Please click here to view a larger version of this figure.
Figure 2: Representative data from snRNAseq on mouse brain occipital cortex, rat kidney (cortex and medulla), and cynomolgus macaque liver and spleen. (A) Violin plots showing the distribution of genes/nucleus, UMIs/nucleus, and percent mitochondrial content per brain sample. (B) Left panel: UMAP plot showing the contribution of each sample to the clusters identified in the brain. Right panel: UMAP showing the identities of the clusters annotated based on marker genes in brain tissue. (C) Cellular proportions observed in the 3 brain samples. (D) Violin plots showing the distribution of genes/nucleus, UMIs/nucleus, and percent mitochondrial content per kidney sample. (E) Left panel: UMAP plot showing the contribution of each sample to the clusters identified in the kidney. Right panel: UMAP showing the identities of the clusters annotated based on marker genes in kidney tissue. (F) Cellular proportions observed in the 3 kidney samples. (G) Violin plots showing the distribution of genes/nucleus, UMIs/nucleus, and percent mitochondrial content per liver sample. (H) Left panel: UMAP plot showing the contribution of each sample to the clusters identified in the liver. Right panel: UMAP showing the identities of the clusters annotated based on marker genes in liver tissue. (I) Cellular proportions observed in the 3 liver samples. (J) Violin plots showing the distribution of genes/nucleus, UMIs/nucleus, and percent mitochondrial content per spleen sample. (K) Left panel: UMAP plot showing the contribution of each sample to the clusters identified in the spleen. Right panel: UMAP showing the identities of the clusters annotated based on marker genes in spleen tissue. (L) Cellular proportions observed in the 3 spleen samples. Please click here to view a larger version of this figure.
Components | Stock concentration | Volume per sample | Final Concentration |
Sucrose Cushion Solution | 2 M | 1500 µL | 1.5 M |
Sucrose Cushion Buffer | – | 500 µL | – |
Dithiothreitol (DTT) | 1 M | 2 µL | 1 mM |
RNAse inhibitor | 40 U/µL | 10 µL | 0.2 U/µL |
Table 1: Preparation of 1.5 M sucrose cushion solution (SCS). This solution is used for the sucrose gradient centrifugation during the clean-up in step 3.1 and should be freshly prepared each time before starting the protocol. Always keep the SCS on ice during the protocol. The solutions mentioned in this table are referenced in the Table of Materials.
Components | Stock concentration | Volume per sample | Final Concentration |
Silica colloid stock solution | 90% | 600 µL | 18% |
Nuclei Storage Reagent (S2 Genomics) | – | 2400 µL | – |
RNAse inhibitor | 40 U/µL | 15 µL | 0.2 U/µL |
Table 2: Preparation of 18% silica colloid solution. This solution is used for the silica colloid gradient centrifugation during clean-up in step 3.2 and should be freshly prepared each time before starting the protocol. Always keep the 18% silica colloid solution on ice during the protocol.
Tissue | Sample weight | Cartridge | Yield |
Rat liver | 25 mg | Nuclei Isolation Cartridge | 65,000 nuclei per mg of tissue |
Rat liver | 4 mg | Small Input Nuclei Isolation Cartridge | 32,000 nuclei per mg of tissue |
Table 3: Nuclei yield from the low input nuclei isolation cartridge versus the nuclei isolation cartridge post sucrose gradient clean-up.
Components | Stock concentration | Volume per sample | Final Concentration |
Nuclei Storage Reagent | – | 1000 µL | – |
RNAse inhibitor | 40 U/µL | 5 µL | 0.2 U/µL |
Table 4: Preparation of nuclei storage reagent (NSR). This solution is used during Nuclei Isolation in steps 3-5 as well as during the clean-up in step 3.1.8. It can be stored at 4 °C for up to 4 months. Prepare a fresh aliquot with RNase inhibitor during the centrifugation step in the clean-up step 6. The solutions mentioned in this table are referenced in the Table of Materials.
1x PBS + 0.04% BSA stock solution | |||
Components | Stock Concentration | Volume for stock | Final Concentration |
PBS (no Ca2+, no Mg2+) | 1x | 30 mL | – |
Bovine Serum Albumin (BSA) | 30% | 40 µL | 0.04% |
1x PBS + 0.04% BSA + 0.2 U/µL RNAse inhibitor | |||
Components | Stock Concentration | Volume per sample | Final Concentration |
1x PBS + 0.04% BSA Stock Solution | – | 500 µL | – |
RNAse inhibitor | 40 U/µL | 2.5 µL | 0.2 U/µL |
Table 5: Preparation of PBS + 0.04% BSA. This solution is used at the end of the clean-up in step 3.1.10 and after counting to dilute the nuclei suspension to the desired concentration for 10X single nuclei RNA sequencing (counting step 4.4). The stock solution can be stored at 4 °C for up to 1 month. Prepare a fresh aliquot with RNase inhibitor during the centrifugation step in the clean-up step 6.
We have developed a versatile and partially automated protocol to obtain high-quality single nuclei from frozen mammalian tissues and demonstrated the protocol on mouse brain, rat kidney, and cynomolgus liver and spleen tissue.
When comparing the performance of this protocol to that of other published protocols for single nucleus RNA sequencing in brain, kidney, spleen, and liver tissue6,7,20,24,25,26, we observe that we are able to detect a similar number of genes and UMI counts per nucleus and are able to recover the expected cell types. Compared to existing methods, there are several advantages to this protocol. First, the protocol in this study automates tissue homogenization and isolation of single nuclei. This is achieved with the use of a robotic tissue disruptor21. In most protocols, tissue is homogenized with a Dounce homogenizer in order to liberate single nuclei3,20. However, we have noticed that this manual step can lead to experimental variability in nuclei yield and integrity depending on the amount of force exerted during homogenization, compromising the reproducibility of the experiments. Here, by using an automated tissue grinder with fixed settings, good nuclei quality and yield with greater consistency were obtained across experiments. Furthermore, automating this step also reduces the hands-on time of the protocol (the tissue disruption step takes approximately 7 min), allowing the user to prepare for the subsequent steps. Second, the protocol described in this study is versatile, i.e., it is compatible with different tissues from different species. This enables us to avoid lengthy protocol optimization, e.g., to identify homogenization buffers/detergents for different tissues2,5,6. Third, this protocol does not depend on access to a flow sorter in order to obtain clean nuclei, hence making it more accessible for laboratories that do not have the required equipment/expertise for flow sorting. Instead, we optimized the sucrose gradient-based filtration to remove most of the debris. However, for brain tissue in particular, using a silica colloid gradient instead of a sucrose gradient is recommended for more efficient myelin removal. We have also found that the use of a swinging-bucket rotor at the end of the sucrose/silica colloid gradient centrifugation step minimizes nuclei loss. Hence, the use of such a rotor is highly recommended. Fourth, after testing multiple methods to count nuclei (manual counting under the microscope, use of several automated counters), the use of an automated fluorescent cell counter22 is recommended. The use of a DNA intercalating dye, such as propidium iodide, increases the accuracy of nucleus counting. Fifth, this protocol takes about 75 min from start to loading the microfluidic chip. This helps to ensure that nuclei integrity remains high when processing multiple samples. Finally, we have found the protocol to also be compatible with optimal cutting temperature compound (OCT)-embedded tissue. If using such material, the tissue can be removed from the OCT block using a scalpel before homogenization.
One frequent challenge in single nuclei RNA sequencing datasets is the presence of ambient RNA, which can be non-nuclear (e.g., mitochondrial) as well as nuclear derived27,28. In our protocol, mitochondrial RNA (a proxy for non-nuclear ambient RNA) is low even prior to filtering (0.1-1.6% for the tissues shown). However, similar to other protocols and datasets, ambient RNA contamination from highly expressed genes in the nuclei of abundant cell types (such as hepatocytes in the liver, neurons in brains, etc.) is still present27. Several bioinformatics tools, such as CellBender, SoupX, etc., exist that can remove such ambient RNA contamination prior to nuclei annotation29,30,31. Another limitation of this protocol is that although the tissue disruption and nuclei isolation steps are automated, the throughput of this step is still limiting as only one sample can be processed at a time. However, since this step takes only approximately 7 min per piece of tissue, multiple samples can still be processed in a batch. We typically process four samples per batch but have done up to six samples per batch with good results. Recent improvements in the robotic dissociator to allow the parallel processing of two samples simultaneously will enable the processing of 8-12 samples per batch, which is compatible with the throughput of the microfluidic chip that is used for single nuclei encapsulation.
Although we have not used the nuclei isolated by this protocol for other downstream applications such as ATAC-seq or snRNAseq using other platforms, based on the quality of data obtained with the gene expression reagents used here, we believe our protocol should be compatible with additional downstream applications. However, future work will involve testing this protocol with other downstream applications, such as ATAC-seq.
In conclusion, we have developed a quick, simple, and partially automated nuclei isolation protocol for downstream single nucleus RNA sequencing that has been demonstrated to be compatible with different types of frozen mammalian tissues.
The authors have nothing to disclose.
The authors would like to thank Filip Bochner, Marion Richardson, Petra Staeuble, and Matthias Selhausen for providing the animal tissues that were analyzed in this manuscript. We would also like to thank Petra Schwalie, Klas Hatje, Roland Schmucki, and Martin Ebeling for their bioinformatics support.
1 M DTT | Thermo Fisher Scientific | P2325 | |
10% Tween 20 | Bio-Rad | 1662404 | |
10x Magnetic Separator | 10x genomics | PN-120250 | |
10x Vortex Adapter | 10x genomics | PN-120251 | |
1x DPBS (10x), no calcium, no magnesium | Thermo Fisher Scientific | 14190144 | stored at 4°C |
30% Bovine Serum Albumin | Sigma-Aldrich | A9576_50ML | |
400 mM Tris-HCl, pH 8.0 | Thermo Fisher Scientific | 15568025 | |
40U/μl RNaseOUT Recombinant Ribonuclease Inhibitor | Thermo Fisher Scientific | 10777019 | Stored at -20 °C |
Agilent High Sensitivity DNA Kit | Agilent | 5067-4626 | |
Cellaca MX High-throughput Automated Cell Counter | Nexcelom Bioscience | CELMXSYSF2 | Automated fluorescent cell counter |
Chromium Next GEM Chip G Single Cell Kit, 16 rxns | 10x genomics | PN-1000127 | Single cell gene expression reagent, stored at room temperature |
Chromium Next GEM Secondary Holder | 10x genomics | PN-1000195 | |
Chromium Next GEM Single Cell 3' Gel Bead Kit v3.1, 4 rxns | 10x genomics | PN-1000129 | Single cell gene expression reagent, stored at -80 °C |
Chromium Next GEM Single Cell 3' GEM, Library & Gel Bead Kit v3.1, 4 rxns | 10x genomics | PN-1000128 | Single cell gene expression reagent |
Chromium Next GEM Single Cell 3' Library Kit v3.1 4 rxns | 10x genomics | PN-1000158 | Single cell gene expression reagent, stored at -20 °C |
Chromium Next GEM Single Cell 3'GEM Kit v3.1 4 rxns | 10x genomics | PN-1000130 | Single cell gene expression reagent, stored at -20 °C |
Divided Polystyrene Reservoirs | VWR | 41428-958 | |
DNA LoBind Tubes 1.5ml Eppendorf | Sigma-Aldrich | EP0030108051 | |
DNA LoBind Tubes 2ml Eppendorf | Sigma-Aldrich | EP0030108078 | |
Dry ice | – | – | |
Dynabeads MyOne SILANE | 10x genomics | PN-2000048 | Single cell gene expression reagent, stored at 4 °C |
Ethanol Pure | Sigma-Aldrich | E7023 | |
Glycerin (Glycerol), 50% (v/v) | Ricca Chemical Company | 3290-16 | |
Heatblock | |||
High-Throughput Nexcelom Counting Plates | Nexcelom Bioscience | CHM24-A100-001 | Cell counter counting plate |
Low TE Buffer (10 mM Tris-HCl pH 8.0, 0.1 mM EDTA) | Thermo Fisher Scientific | 12090015 | |
Mini Centrifuge | – | – | |
NovaSeq 6000 SP Reagent Kit v1.5 (100 cycles) | Illumina | 2002840 | |
Nuclei Isolation Buffer | S2 Genomics | 100-063-396 | Stored at 4 °C |
Nuclei Isolation Cartridge | S2 Genomics | 100-063-287 | Precooled at 4 °C before use |
Nuclei PURE 2 M Sucrose Cushion Solution | Sigma-Aldrich | NUC201-1KT | Sucrose cushion solution |
Nuclei PURE Sucrose Cushion Buffer | Sigma-Aldrich | NUC201-1KT | |
Nuclei Storage Reagent | S2 Genomics | 100-063-405 | Stored at 4 °C |
PCR Tubes 0.2 ml 8-tube strips | Eppendorf | 30124359 | |
Percoll | GE Healthcare | 17-0891-02 | Silica colloid solution |
PhiX Control v3 | Illumina | FC-110-3001 | |
Qiagen Buffer EB | Qiagen | 19086 | |
Qubit dsDNA HS Assay Kit | Thermo Fisher Scientific | Q32854 | |
Refrigerated Centrifuge (Eppendorf 5804R) | Eppendorf | 5805000010 | |
Refrigerated Centrifuge with Swinging-Bucket Rotor (Eppendorf 5810R) | Eppendorf | 5811000015 | |
RNAseZap | Ambion | AM9780 | RNAse decontamination solution |
Round cell culture petri dish | SPL | 330005 | |
Scalpel disposable | Aesculap AG | BA210 | pre-cooled on dry ice before use |
Single Index Kit T Set A, 96 rxns | 10x genomics | PN-1000213 | Single cell gene expression reagent, stored at -20 °C |
Singulator 100 System | S2 Genomics | – | Commercially available robotic tissue dissociator |
Sodium Hydroxide 1M | Sigma-Aldrich | 72068 | |
SPRIselect Reagent Kit | Beckman Coulter | b23318 | |
Sterile tweezers | – | – | |
UltraPure DNase/RNase-Free Distilled Water | Thermo Fisher Scientific | 10977049 | |
ViaStain PI Staining Solution | Nexcelom Bioscience | CS1-0109-5mL | Propidium iodide staining solution |
Vortex Mixer+A2:D44 | VWR | – |