TITLE: Cell Interaction by Multiplet sequencing (CIM-seq)
AUTHORS: Nathanael   Andrews, Jason T. Serviss, Natalie Geyer (Karolinska Institute Stockholm), Agneta B. Andersson, Ewa Dzwonkowska, Iva Šutevski, Rosan Heijboer, Ninib Baryawno (Karolinska Institute Stockholm), Marco Gerling, Martin Enge

[DESCRIPTION]
Single cell sequencing methods facilitate the study of tissues at high resolution, revealing rare cell types with varying transcriptomes or genomes, but so far have been lacking the capacity to investigate cell-cell interactions.  Here, we introduce CIM-seq, an unsupervised and high-throughput method to analyze direct physical cell-cell interactions between every cell type in a given tissue. CIM-seq is based on RNA sequencing of incompletely dissociated cells, followed by computational deconvolution of these into their constituent cell types using machine learning. CIM-seq is broadly applicable to studies that aim to simultaneously investigate the constituent cell types and the global interaction profile in a specific tissue.

[BEFORE_START]
Before preparing cell lysis plates it is recommended to thoroughly clean all equipment with 70% EtOH and RNAse away to prevent contamination and avoid RNA degradation.

[STEPS]
SECTION: Prepare Lysis buffer
1. Prepare Lysis Buffer:
 
NOTE: Reagents are prepared on ice, working quickly. ERCC is stored in single-use aliquots at -80 °C, thawed on ice and added last.

  1H201.31Inhibitor0.05ERCC (1:600000)0.0510% Triton0.0410mM dNTP0.5100uM dT0.05Total2
Add 2 µL lysis buffer mix to each well. Cover with appropriate lids. Spin down.
Snap freeze on dry ice. Store until use at -80 °C 

SECTION: Sort cells
2. Sort single cells and multiplets (aggregates of multiple cells) into 2 µL  lysis buffer mix.
Multiplets can be discerned from singlets by gating on the basis of FSC-W (Forward scatter - Width) and FSC-H (Forward scatter - Height)  (see Figure 1).

  
Following sort, immediately seal with appropriate seals (approved for -80C > 100C) and centrifuge at 2000 x g, 5 min, 4 °C.
Snap freeze on dry ice. Store until use at -80 °C .


SECTION: Reverse transcription and cDNA amplification
3. Primer annealing
Thaw plate. Spin down. Incubate in thermocycler at 72 °C for 3 min . Place on ice immediately. 

SECTION: Reverse transcription and cDNA amplification
4. Prepare RT master-mix

 Made fresh.

  SmartScribe0.475RNase Inhibitor0.1255x First Strand buffer1DTT (100mM)0.25Betaine (5M) [fridge]1MgCl2 (1M) [bench]0.03TSO (100uM)0.05H200.07Total3

Dispense 3 µL  per well.
Cover plate with new film and spin down.
SECTION: Reverse transcription and cDNA amplification
5. Incubate in thermocycler
42 °C 90 min 
70 °C 5 min 
4 °C hold

SECTION: Reverse transcription and cDNA amplification
6. cDNA preamplification

Made fresh.

 
  1RT reaction5H2O1.0688Kapa HiFi HotStart ReadyMix (2x)6.25IS_PCR primer (10uM)0.125Lambda Exonuclease0.05625Total7.5000
 
Dispense 7.5 µL  per well . Total reaction volume will be 12.5µl.
 Spin down. Cover with new lid.



SECTION: Reverse transcription and cDNA amplification
7. Incubate in thermocycler with the following program: 
 
    StepTemperatureTimeCyclesLambda exonuclease37ºC30 min1xInitial denaturation95ºC3 min1xDenaturation98ºC20 sec18-24xAnnealing67ºC15 secElongation72ºC4 minFinal elongation72ºC5 min1x4CHold
 

SECTION: Reverse transcription and cDNA amplification
8. 

cDNA cleanup

We prepare SPRI-beads in 20% PEG-8000 solution as in: https://openwetware.org/wiki/SPRI_bead_mix#Ingredients_for_50_mL_2

Using 20% SPRI-bead solution:

1. Add 0.7x the reaction volume of SPRI beads per well. Mix well by pipetting. (i.e 8.75 µL SPRI-bead solution for 12.5 µL reaction volume)
2. Incubate 5 min Room temperature 
3. Place on magnetic stand for 3 min 
4. Carefully remove supernatant
5. Add 40 µl 80% EtOH and incubate 30 s 
6. Remove EtOH (without disturbing the beads)
7. Wash again with EtOH. Make sure to remove well.
8. Allow beads to air-dry for 10 min -15 min 
9. Remove plate from magnetic stand
10. Elute beads in 15 µL  EB or TE buffer. Mix well by pipetting
11. Incubate 5 min Room temperature 
12. Place on magnetic plate for 3 min 
13. Optional: Carefully remove supernatant to the elution plate
SECTION: Reverse transcription and cDNA amplification
9. cDNA quantification

We measure concentration of random wells using Qubit HS dsDNA, adapted to a 96-well plate reader. 

1. Add 97 µL of 1X Qubit HS dsDNA solution to a flat-bottom, black plate
2. Add 3 µL of cDNA sample
3. Add Standards (NOTE: We make a 8-step ladder from 0ng/µl --> 10ng/µl Qubit Standard DNA in TE buffer)
3. Read in plate reader using 485nM excitation/528nm emission 
4. Calculate cDNA concentration 
SECTION: Reverse transcription and cDNA amplification
10. (optional) cDNA quality control

Using Agilent HS 5000 DNA chips (or equivalent)


  

SECTION: Reverse transcription and cDNA amplification
11. Make cDNA dilution plate

Dilute cDNA in water based on average concentration from Qubit measurements. 
Target concentration 150pg per µl in 15 µL.

SECTION: cDNA tagmentation
13. Prepare Tn5 master mix

 


 
   ReagentReaction conc.µl per reactionNuclease free H2O-1.05TAPS-PEG (50mM TAPS, 25mM MgCl2, 40% PEG-8000)10mM TAPS, 5mM MgCl2, 8% PEG-80000.5psfTn5, loaded with 50µM MEDS-A/B0.25Total1.8
 
Dispense 1.8 µL  per well in a new plate(tagmentation plate)
SECTION: cDNA tagmentation
14. 
Add 0.7 µL cDNA (normalized to 150pg/µl)
Mix well by vortexing plate. Cover with new lid and spin down. 
SECTION: cDNA tagmentation
15. Incubate in thermocycler at 55 °C10 min
Remove immediately and stop reaction by adding 1 µL per well of 0.1% SDS. 
Vortex, spin down and incubate 7 min at 55 Room temperature

SECTION: cDNA library PCR and barcoding
16. Make PCR master-mix

 
  1H2O13.255x buffer5dNTPs0.75KAPA0.5Dispense19.50
 
 Dispense 19.5 µL per well to tagmentation plate (containing 3.5 µL sample after step 14)
SECTION: cDNA library PCR and barcoding
17. Add primers/barcodes 

2 µL per well (from 384-well index plates, with 3.75µM/each forward/reverse primers; see oligos in materials). 

Total reaction volume is 25 µL (3.5 µL sample + 19.5 µL PCR mix and 2 µL primers). 
SECTION: cDNA library PCR and barcoding
18. 
Vortex. Spin down and cover. Incubate in thermocycler as following:
 
    StepTemperatureTimeCyclesGap fill72ºC3 min1xFirst denature95ºC30 sec1xDenature95ºC15 sec12xDenature67ºC30 secDenature72ºC45 secFinal extension72ºC4 min1x4-10ºChold

SECTION: cDNA library PCR and barcoding
19. Pool 2.5 µL from each well to an 1.5ml Eppendorf tube.
SECTION: cDNA library PCR and barcoding
20. Library cleanup

1. Add 0.9x pooled library volume of SPRI-bead solution. Incubate for 5 min at Room temperature .
2. Place on magnetic rack for 3 min.
3. Remove supernatant without disturbing magnetic beads.
4. Add at least 1 mL 80% EtOH (fresh). Incubate for 30 s.
5. Remove supernatant.
6. Repeat EtOH wash.
7. Air dry for 10 min - 15 min.
8. Re-suspend beads thoroughly in 100 µl EB or TE buffer.
9. Place eppendorf on magnetic rack for 3 min. 
10. Transfer supernatant to new 1.5ml Eppendorf tube.
11. Repeat cleanup (from step 1-7) and elute in 30 µl EB or TE buffer.
12.(Optional) Place eppendorf on magnetic rack for 3 min and transfer supernatant to new tube. 
SECTION: cDNA library PCR and barcoding
21. Pooled library QC

  
SECTION: cDNA tagmentation
12. Tn5 digestion


Tn5 is produced from psfTn5 (Addgene #79107), purified to ~3mg/ml and assembled with Illumina Tn5 adapters (see oligos) as in Picelli et al, 2014.
 

SECTION: Data pre-processing
22. 
A series of pre-processing steps must be performed in order to generate a counts file:

1. Trim reads, remove adapter sequences and align RNAseq data to reference genome using STAR:
 

2. Remove duplicate reads using Picard:
 
3. Generate transcript counts file using HTSeq:
 

SECTION: Dimensionality reduction and classification
23. 

Once a counts file has been generated the data can be analyzed. CIM-seq requires four arguments in order to run:

1. The raw counts data with gene IDs as rownames and sample IDs as 
colnames. 

2. The ERCC spike-in counts data with gene IDs as rownames and sample 
IDs as colnames.

3. The dimensionality reduced representation of the data.

4. A class for each of the individual singlets.

In order to generate the last two of these we recommend using the Seurat package in R, as CIM-seq is implemented in R as well. A number of tutorials for Seurat can be found on the Satijalab website:

https://satijalab.org/seurat/vignettes.html

SECTION: CIM-seq
24. 

CIM-seq can be downloaded from:
https://github.com/EngeLab/CIMseq

Or installed directly in R using the devtools package:

devtools::install_github("EngeLab/CIMseq")

The CIM-seq vignette can be found at:

https://github.com/EngeLab/CIMseq/tree/master/vignettes