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| Status |
Public on Jun 21, 2024 |
| Title |
Systematic investigation of mitochondrial transfer between cancer cells and T cells at single-cell resolution |
| Organism |
Mus musculus |
| Experiment type |
Expression profiling by high throughput sequencing
Genome binding/occupancy profiling by high throughput sequencing
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| Summary |
Mitochondrion (MT) as the energy-producing organelle participates in most metabolic activities of mammalian cells. Unidirectional mitochondrial transfer from T cells to cancer cells was recently observed “metabolically empowering” cancer cells while “depleting immune cells”, providing new insights into Tumor-T cell interaction and immune evasion. Here, we leveraged the increasingly adopted single-cell RNA-seq technology and introduced MERCI, a statistical deconvolution method for tracing and quantifying the process of mitochondrial trafficking between cancer and T cells. MERCI was benchmarked using data generated from a coculture system of MT-labeled cancer and T cells to accurately predict the recipient cells and their mitochondrial compositions. We independently demonstrated the cellular MT transfer signals and validated the MERCI performance by additionally generating a gold-standard mtscATAC-seq dataset. Application of MERCI to single cell human cancer samples identified a novel MT transfer phenotype and its signature genes involved in cytoskeleton remodeling, energy production and TNFα signaling pathways. Application of MERCI to ovarian cancer spatial transcriptomes revealed the prevalence of MT transfer in the tumor tissue of high T cell infiltration, which is elevated in the endothelium-rich regions. Finally, MT transfer is associated with high cell cycle activity and poor clinical outcome in our pan-cancer analysis through MERCI. In summary, MERCI enabled systematic investigation of a novel aspect of Tumor-T cell interaction and revealed MT-transfer related genes and pathways that may lead to new therapeutic opportunities.
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| Overall design |
The KP lung cancer cells were provided initially by Dr. Esra Akbay. The KP-mito-DsRed stable cell line was generated in the lab with pDsRed2-Mito vector transfection using PEI MAX® with long-term selection using G418 following manufacture’s protocol. All cancer cell lines were grown in 5% FBS supplemented RPMI 1640. Cell lines were routinely tested using a mycoplasma contamination and cultured under 5% CO2 at 37 ֯C. Splenocytes were isolated by harvesting the spleen from 6-8 weeks old mice following red blood cell lysis with ACK buffer. CD8+ T cells were isolated by immunomagnetic negative selection using EasySepTM mouse CD8+ T cell isolation kit. Isolated T cells were then stained with MitoTrackerTM green FM at 100 nM concentration at 37°C for 30 min following the manufacturer’s instruction. MitoTrackerTM green FM at indicated concentration would not stain all T cell mitochondria positive, to avoid non-mitochondrial labeling. Stained CD8+ T cells were then washed with medium, centrifuged down, and then resuspended to remove access dye in the medium. Isolated CD8+ T cells were maintained in 10% heat deactivated FBS supplemented RPMI 1640. In the control experiment, KP-mito-DsRed cancer cells were labeled with MitoTrackerTM red CMXRos using the same procedure. scRNA-seq was performed by the 10x Genomics single-cell 5′ V(D)J library platform. Single-cell suspension of negative controls and sorted cells were counted manually under a microscope stained with trypan blue. The concentration of single-cell suspensions was adjusted to 900-1000 live cell/μl. Cells were loaded at 10,000 cells/chip position. Single-cell libraries were generated with Chromium Single Cell V(D)J Reagent Kit (10x Genomics, PN-10000006, PN-10000009) following per manufacturer’s instruction. Purified libraries were analyzed by Illumina NovaSeq with 150-bp paired-end reads at a targeted median read depth of 100,000 reads per cell. Mitochondrial single-cell assay for transposase-accessible chromatin with sequencing (mtscATAC-seq) technique was performed strictly following the revised 10x scATAC-seq protocol developed by Lareau et al. Briefly, after washing, the sorted cells were fixed in 1% formaldehyde in PBS for 10 min at RT, quenched with glycine solution to a final concentration of 0.125 M before washing cells twice in PBS via centrifugation at 400 g, 5 min, 4°C. Cells were subsequently treated with lysis buffer (10mM Tris-HCL pH 7.4, 10mM NaCl, 3mM MgCl2, 0.1% NP40, 1% BSA) for 3 min for CD8+ T cells and 5 min for KP cells on ice, followed by adding 1 ml of chilled wash buffer and inversion (10mM Tris-HCL pH 7.4, 10mM NaCl, 3mM MgCl2, 1% BSA) before centrifugation at 500 g, 5 min, 4°C. The supernatant was discarded, and cells were diluted in 1x Diluted Nuclei buffer (10x Genomics) before counting using Trypan Blue and a Countess II FL Automated Cell Counter (Invitrogen). mtscATAC-seq libraries were generated using the 10x Chromium Controller and the Chromium Next GEM Single Cell ATAC Kit v2 (PN-1000406) according to the manufacturer’s instructions (CG000496 Rev-B), and sequencing was run on Illumina NovaSeq 6000 (Novogene) using paired-end sequencing of 150-bp read length, aiming to allocate 35,000 paired-end reads per cell in a mtscATAC-seq library.
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| Contributor(s) |
Hongyi Z, Xuein Y, Jianfeng Y, Anli Z, Bo L |
| Citation(s) |
37816332 |
| NIH grant(s) |
| Grant ID |
Grant title |
Affiliation |
Name |
| R01 CA245318 |
Antigen-independent prediction and biomarker identification of cancer-specific T cells |
UT SOUTHWESTERN MEDICAL CENTER |
Bo Li |
| R01 CA258524 |
Tracking Peripheral T-Cell Repertoire Changes for Preoperative and Early Ovarian Cancer Diagnosis |
UT SOUTHWESTERN MEDICAL CENTER |
Bo Li |
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| Submission date |
Jun 23, 2023 |
| Last update date |
Jul 27, 2024 |
| Contact name |
Bo Li |
| E-mail(s) |
lib3@chop.edu
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| Phone |
7345467574
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| Organization name |
The Children’s Hospital of Philadelphia, University of Pennsylvania
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| Department |
Department of Pathology and Laboratory Medicine
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| Lab |
Bo Li lab
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| Street address |
3501 Civic Center Blvd
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| City |
Philadelphia |
| State/province |
PA |
| ZIP/Postal code |
19104 |
| Country |
USA |
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| Platforms (1) |
| GPL24247 |
Illumina NovaSeq 6000 (Mus musculus) |
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| Samples (9)
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| GSM7507497 |
KP_cells, cocultured, scRNA-seq, bechmark1 |
| GSM7507498 |
KP_cells, monocultured, scRNA-seq, bechmark1 |
| GSM7507499 |
T_cells, monocultred, scRNA-seq, benchmark1 |
| GSM7507500 |
KP_cells, cocultured, mtscATAC-seq, bechmark2 |
| GSM7507501 |
KP_cells, monocultured, mtscRNA-seq, bechmark2 |
| GSM7507502 |
T_cells, monocultred, mtscATAC-seq, benchmark2 |
| GSM7507503 |
KP_cells, cocultured, scRNA-seq, bechmark2 |
| GSM7507504 |
KP_cells, monocultured, scRNA-seq, bechmark2 |
| GSM7507505 |
T_cells, monocultured, scRNA-seq, bechmark2 |
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| Relations |
| BioProject |
PRJNA986887 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE235675_MT_covearge_cells_bench1_scRNAseq_.txt.gz |
133.6 Mb |
(ftp)(http) |
TXT |
| GSE235675_MT_covearge_cells_bench2_mtscATACseq_.txt.gz |
260.9 Mb |
(ftp)(http) |
TXT |
| GSE235675_MT_covearge_cells_bench2_scRNAseq_.txt.gz |
44.9 Mb |
(ftp)(http) |
TXT |
| GSE235675_cell_information_bench1_scRNAseq_.txt.gz |
106.6 Kb |
(ftp)(http) |
TXT |
| GSE235675_cell_information_bench2_mtscATACseq_.txt.gz |
147.7 Kb |
(ftp)(http) |
TXT |
| GSE235675_cell_information_bench2_scRNAseq_.txt.gz |
41.5 Kb |
(ftp)(http) |
TXT |
| GSE235675_mtSNV_profile_bench1_scRNAseq_.txt.gz |
14.1 Mb |
(ftp)(http) |
TXT |
| GSE235675_mtSNV_profile_bench2_mtscATACseq_.txt.gz |
33.4 Mb |
(ftp)(http) |
TXT |
| GSE235675_mtSNV_profile_bench2_scRNAseq_.txt.gz |
4.9 Mb |
(ftp)(http) |
TXT |
| GSE235675_normalized_exp_matrix_bench1_scRNAseq_.txt.gz |
444.5 Mb |
(ftp)(http) |
TXT |
| GSE235675_normalized_exp_matrix_bench2_scRNAseq_.txt.gz |
231.5 Mb |
(ftp)(http) |
TXT |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data are available on Series record |
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