Top 3 Tips for Successful CosMx™ SMI Single-cell Spatial Runs at 1000 plex
We are excited to share insights and recommendations to enhance your experience with CosMx™ SMI 1000-plex RNA assays. The quality of single-cell spatial data is influenced by various factors, and we aim to provide you with valuable information on experimental conditions for multiple tissue types to ensure the best results.
The CosMx™ SMI and decoder probes are not offered and/or delivered to the Federal Republic of Germany for use in the Federal Republic of Germany for the detection of cellular RNA, messenger RNA, microRNA, ribosomal RNA and any combinations thereof in a method used in fluorescence in situ hybridization for detecting a plurality of analytes in a sample without the consent of the President and Fellows of Harvard College (Harvard Corporation) as owner of the German part of EP 2 794 928 B1. The use for the detection of cellular RNA, messenger RNA, microRNA, ribosomal RNA and any combinations thereof is prohibited without the consent of the President and Fellows of Harvard College (Harvard Corporation).
CosMx 1000-plex RNA Assays: Considerations When Generating Single-Cell Spatial Data
Tip 1: Interpret Data by Tissue and Disease Type
Understanding the role of tissue/disease type is crucial for interpreting single-cell spatial data. We present mean number of transcripts (counts) detected per cell (Figure 1) and mean unique genes detected per cell (Figure 2) across various tissue/disease types. Data were collected from 210 externally-supplied tissue slides as part of the NanoString Technology Access Program (TAP), utilizing either the 1000-plex RNA Human Universal Cell Characterization (UCC) or the 1000-plex Mouse Neuroscience panel. Tissue samples presented are real-world samples that were not pre-curated for RNA quality upon receival to TAP.
Mean transcripts per cell by tissue and disease type
Mean unique genes per cell by tissue and disease type
We make two key observations from this collated data: 1) RNA signal, as measured by transcripts/cell and unique genes/cell, varies greatly by tissue type. We attribute this trend, in part, to inherent tissue biology and panel gene content. 2) Tissue block and section quality are major factors for data quality, as evidenced by the signal heterogeneity observed within tissue types. We look forward to providing future guidance on improving sample quality prior to the CosMx workflow.
Tip 2: Consider Sample Preparation Conditions
CosMx slide preparation protocol is in part defined by tissue-specific conditions. By utilizing the appropriate sample preparation and run conditions as well as contextualizing RNA signal by tissue type, users can better generate and interpret single-cell spatial data. For detailed guidance, please refer to the CosMx Slide Preparation Manual (Appendix I and II) and Sample Sectioning Tips and Tricks.
In Table 1 below, we provide a summary of various tissue types and suggested modifications to experimental conditions that may be needed to optimize data quality. For the RNA Assay, digestion buffer concentration and incubation time for target retrieval may differ for some tissue types and will need to be empirically determined. We recommend starting with default conditions as per the CosMx Slide Preparation Manual and adjusting as required. If tissue detachment is observed, begin slide preparation with a new tissue section and reduce target retrieval time. If the issue persists, consider reduction of the proteinase K concentration.
Table 1: Suggested slide prep modifications
based on tissue type and biology
Table 2 below breaks down target retrieval time, digestion conditions (concentration and time), and fiducial concentration for the various tissue types represented in Figure 1 and Figure 2 above. In addition, we provide recommended instrument pre-bleaching conditions for specific tissues. Refer to the CosMx SMI Instrument User Manual for detailed operational instructions. These conditions, empirically determined, may require user-specific adjustments.
Table 2: Sample Prep Conditions for 57 Tissue Types
Tip 3: Plan Instrument Run Conditions
Instrument run time depends on the interrogated tissue area (number of Fields of View). Presented below (Table 3) are turnaround time estimations, based on different total FOV numbers per run. Sample integrity and data quality are influenced by instrument run time.
Table 3: CosMx turnaround time estimates
For commercial software v1.4.1
| Analyte | Plex | No. of Slides | Total Number of FOVs per Run | |||||
|---|---|---|---|---|---|---|---|---|
| 100 | 200 | 400 | 800 | 1200 | 1500 | |||
| RNA | 1K | 2 slides | 2.8 | 3.2 | 4.0 | 5.9 | 8.2 | 10.0 |
| 4 slides | 3.3 | 3.7 | 4.5 | 6.7 | 9.5 | NR | ||
| 6K | 2 slides | 4.5 | 5.0 | 6.2 | 8.9 | 12.7 | NR | |
| Protein | 64 | 2 slides | 0.8 | 1.1 | 1.6 | 2.6 | 3.7 | 4.5 |
| 4 slides | 0.8 | 1.1 | 1.6 | 2.6 | 3.7 | 4.5 | ||
| Turnaround Time(Days) | ||||||||
Turnaround estimates are designed as experimental guidance and may change slightly from run-to-run.
If using a smaller or custom panel, expect a turnaround time at or below estimated value in table.
We recommend users to stay within the provided turnaround time guidance.
Thank you for choosing CosMx. If you have any further questions or need assistance, please don’t hesitate to contact our Support team (support.spatial@bruker.com).
