Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

CNS-Native Myeloid Cells Drive Immune Suppression in the Brain Metastatic Niche through Cxcl10

ABSTRACT: We used CITE-seq (10x Gemoics-based) to profile and compare the transcriptomes and cell surface expression of a set of immune markers of naïve brain myeloid cells from wild type C57Bl/6 mice to brain metastasis-associated myeloid cells (Br.MAM) from C57Bl/6 mice bearing E0771 brain metastases. In each sequencing round, we sequenced a total of four different mouse brains (2 naive and 2 metastasis-burdened). We created an antibody pool consisting of 6 different antibodies (CD45, CD25, CD3, CD4, CD11b, and CD86) and stained each brain individually with this antibody pool. Then, we stained each brain with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium and later prepare one library consisting of all six samples and finally separate each sample in silico by it's unique hashing antibody.

ORGANISM(S): Mus musculus

PROVIDER: GSE134284 | GEO | 2020/10/29

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

CNS-Native Myeloid Cells Drive Immune Suppression in the Brain Metastatic Niche through Cxcl10

Project description:We used CITE-seq (10x Genomics-based) to profile and compare the transcriptomes and cell surface expression of a set of immune markers of naïve brain myeloid cells from wild type C57BL/6 mice to brain metastasis-associated myeloid cells (Br.MAM) from C57BL/6 mice bearing E0771 brain metastases. In each sequencing round, we sequenced a total of four different mouse brains (2 naive and 2 metastasis-burdened). We created an antibody pool consisting of 6 different antibodies (CD45, CD25, CD3, CD4, CD11b, and CD86) and stained each brain individually with this antibody pool. Then, we stained each brain with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium and later prepare one library consisting of all six samples and finally separate each sample in silico by it's unique hashing antibody.

2020-10-29 | GSE133905 | GEO

CNS-Native Myeloid Cells Drive Immune Suppression in the Brain Metastatic Niche through Cxcl10 [R07_Cx3cr1]

Project description:We performed CITE-seq (10x Genomics-based) to profile and compare the transcriptomes and cell surface expression of immune epitopes in the brains of Cx3cr1+/- and Cx3cr1-/- mice during homeostasis or brain metastasis. We sequenced a total of eight different samples. We created an antibody pool consisting of 35 different antibodies and stained each sample individually with this antibody pool. Then, we stained each sample with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium and later prepare one library consisting of all sight samples and finally separate each sample in silico by it's unique hashing antibody. The samples are as follows: (1) HTO1: brain of naïve Cx3cr1+/- mouse; (2) HTO2: brain of naïve Cx3cr1+/- mouse; (3) HTO3: brain of metastasis-burdened Cx3cr1+/- mouse; (4) HTO4: brain of metastasis-burdened Cx3cr1+/- mouse; (5) HTO5: brain of naïve Cx3cr1-/- mouse; (6) HTO6: brain of naïve Cx3cr1-/- mouse; (7) HTO7: brain of metastasis-burdened Cx3cr1-/- mouse; (8) HTO8: brain of metastasis-burdened Cx3cr1-/- mouse. The following sample comparisons were made: HTO1 and HTO2 versus HTO5 and HTO6; HTO3 and HTO4 versus HTO7 and HTO8.

2020-10-29 | GSE139970 | GEO

CNS-Native Myeloid Cells Drive Immune Suppression in the Brain Metastatic Niche through Cxcl10 [R07_CCR2Cx3cr1B]

Project description:We performed CITE-seq (10x Genomics-based) to profile and compare the transcriptomes and cell surface expression of immune epitopes in the brains and blood of different transgenic mice (Cx3cr1+/-; Cx3cr1-/-; CCR2+/-; CCR2-/-) during homeostasis or brain metastasis. We sequenced a total of eight different samples. We created an antibody pool consisting of 35 different antibodies and stained each sample individually with this antibody pool. Then, we stained each sample with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium and later prepare one library consisting of all sight samples and finally separate each sample in silico by it's unique hashing antibody. The samples are as follows: (1) HTO1: brain of naïve CCR2+/- mouse; (2) HTO2: brain of naïve CCR2+/- mouse; (3) HTO3: brain of naïve CCR2-/- mouse; (4) HTO4: brain of naive CCR2-/-; (5) HTO5: blood of naïve Cx3cr1+/- mouse; (6) HTO6: blood of metastasis-burdened Cx3cr1+/- mouse; (7) HTO7: blood of naïve Cx3cr1-/- mouse; (8) HTO8: blood of metastasis-burdened Cx3cr1-/- mouse.The following sample comparisons were made: HTO1 and HTO2 versus HTO3 and HTO4; HTO5 versus HTO7; HTO6 versus HTO8.

2020-10-29 | GSE139969 | GEO

CNS-Native Myeloid Cells Drive Immune Suppression in the Brain Metastatic Niche through Cxcl10 [R10_PD-L1+VISTA treatment]

Project description:We performed CITE-seq (10x Genomics-based) to profile and compare the transcriptomes and cell surface expression of immune epitopes in the brains of anti-VISTA+anti-PD-L1 treated (Dual TX) and control, non-treated mice. We sequenced a total of eight samples (4 control, 4 dual TX). We created an antibody pool consisting of 35 different antibodies and stained each sample individually with this antibody pool. Then, we stained each sample with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium and later prepare one library consisting of all sight samples and finally separate each sample in silico by it's unique hashing antibody. The samples are as follows: (1) HTO1: Control/Non-treated (2) HTO2: Control/Non-treated ; (3) HTO3: Control/Non-treated ; (4) Control/Non-treated ; (5) HTO5: Dual TX; (6) Dual TX; (7) HTO7: Dual TX; (8) HTO8: Dual TX. The following sample comparisons were made: HTO1 - HTO4 were compared to HTO5 - HTO8.

2020-10-29 | GSE158579 | GEO

Multi-modal single cell analysis reveals gut microbiota reshapes brain immune landscape in aged mouse model

Project description:We used CITE-seq (10x Gemoics-based) to profile and compare the transcriptomes and cell surface expression of a set of immune markers of naïve brain myeloid cells from young-adult (12 weeks old) wild type C57Bl/6 mice, aged (72 weeks old) wild type C57Bl/6 mice and young-adult and aged C57Bl/6 mice with antibiotics induced gut microbiota depletion. In one sequencing round, we sequenced a total of 12 different mouse brains (3 young control, 3 aged control, 3 young depleted gut microbiota (ABX) and 3 aged depleted gut microbiota (ABX)). We created an antibody pool consisting of 31 different antibodies (CCR2/CD192, C117/c-kit, CD11b, CD11c, CD172a/SIRPα, CD25, CD3, CD38, CD4, CD44, CD45, CD45R/B220, CD86, CD8a, CD90.1, Cx3cr1, F4/80, I-A/I-E, Ly6C, Ly6G, NK1.1, PD-1, PD-L1, CD169/Siglec-1, Siglec-H, TMEM119, XCR1, CD24, CD103, CD64, CD83) and stained each brain individually with this antibody pool. Then, we stained each brain with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium. Young Control and Young ABX brains were tagged with HTOs 1-6 (HTO 1-3 for young control and HTO 4-6 for young ABX). Aged control and Aged ABX brains were tagged with HTOs 1-6 (HTO 1-3 for aged control and HTO 4-6 for aged ABX). Young and aged were loaded in separate wells on the 10X Chromium. The samples were tagged with unique nextera index primers to allow for preparation of one sequencing library consisting of all 12 samples and were separated in silico by it's unique hashing antibody and nextera index barcode combinations.

2020-11-05 | GSE148127 | GEO

CNS-Native Myeloid Cells Drive Immune Suppression in the Brain Metastatic Niche through Cxcl10 [R08_MgliaDep]

Project description:We performed CITE-seq (10x Genomics-based) to profile and compare the transcriptomes and cell surface expression of immune epitopes in the brains and blood of different transgenic mice (Cx3cr1CreERT; Cx3cr1CreERT-ROSA-iDTR) during homeostasis or brain metastasis with or without DT-based microglia depletion. We sequenced a total of eight different samples. We created an antibody pool consisting of 35 different antibodies and stained each sample individually with this antibody pool. Then, we stained each sample with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium and later prepare one library consisting of all sight samples and finally separate each sample in silico by it's unique hashing antibody. The samples are as follows: (1) HTO1: brain of naïve Cx3cr1CreERT mouse (non-microglia depleted); (2) HTO2: brain of metastasis-burdened Cx3cr1CreERT mouse (non-microglia depleted); (3) HTO3: brain of metastasis-burdened Cx3cr1CreERT mouse (non-microglia depleted); (4) HTO4: brain of naïve Cx3cr1CreERT-ROSA-iDTR mouse (microglia depleted); (5) HTO5: brain of metastasis-burdened Cx3cr1CreERT-ROSA-iDTR mouse (microglia depleted); (6) HTO6: brain of metastasis-burdened Cx3cr1CreERT-ROSA-iDTR mouse (microglia depleted); (7) HTO7: blood of metastasis-burdened Cx3cr1CreERT mouse (non-microglia depleted); (8) HTO8: blood of metastasis-burdened Cx3cr1CreERT-ROSA-iDTR mouse (microglia depleted). The following sample comparisons were made: HTO1 versus HTO4; HTO2 and HTO3 versus HTO5 and HTO6; HTO7 versus HTO8.

2020-10-29 | GSE139971 | GEO

Chemotherapy-mediated changes in the immune cell landscape of murine triple negative breast cancer.

Project description:We performed CITE-seq (10x Genomics-based) to profile and compare the transcriptomes and cell surface expression of immune epitopes in the primary breast tumors of transgenic mice (C3-1-TAg) with or without MCT chemotherapy. We sequenced a total of six different tumor samples. We created an antibody pool consisting of 35 different antibodies and stained each sample individually with this antibody pool. Then, we stained each sample with it's own unique hashing antibody so that we could subsequently pool the samples for loading onto the 10x Chromium and later prepare one library consisting of all sight samples and finally separate each sample in silico by it's unique hashing antibody. The samples are as follows: (1) HTO1: tumor of PBS treated C3-1-TAg mouse; (2) HTO2: tumor of PBS treated C3-1-TAg mouse; (3) HTO3: tumor of PBS treated C3-1-TAg mouse; (4) HTO4: tumor of MCT treated C3-1-TAg mouse; (5) HTO5: tumor of MCT treated C3-1-TAg mouse; (6) HTO6: tumor of MCT treated C3-1-TAg mouse. The following sample comparisons were made: HTO1, HTO2, and HTO3 versus HTO4, HTO5, and HTO6.

2023-02-26 | GSE158888 | GEO

Single cell RNA seq of Cell Multiplexing Oligo, pooled Pleurodeles waltl and Notophthalmus viridescens spleens

Project description:The goal of this study was to test if lipid-based cell hashing worked in salamander species and to test how lipid-based hashing compared to demultiplexing samples based on species origin and single nucleotide polymorphisms (SNP). Spleens were taken from four animals in total: one adult Pleurodeles waltl (female, 23.5grams and 16.1cm snout-to-tail, strain: tgSceI(CAG:loxP-GFP-loxP-Cherry)Simon), one adult Pleurodeles waltl (male, 13.95g and 15.7cm, tgSceI(CAG:loxP-GFP-loxP-Cherry)Simon), one adult Notophthalmus (female, 4.45g and 10.6cm, WT), and one adult Notophthalmus (male, 3.55g and 10.2cm, WT). Samples were stained with CM304 (Pleurodeles female), CMO305 (Pleurodeles male), and CMO306 (pool of both Notophthalmus samples) as per 10x Genomics 3’ Cellplex labeling protocol (Demonstrated Protocol, CG000391). These samples were processed through the 10x Controller and with Cellranger 7.0 using a dual species reference. The sample origin was determined by lipid-based hashing and then compared to mapping rates to each species transcriptome and using SNP-based demultiplexing.

2022-09-21 | E-MTAB-12182 | biostudies-arrayexpress

Comparison of different hashing methods on human PBMCs and primary mice tissues

Project description:the aim 1 was to evaluate hashing (sample multiplexing) accuracy of TotalSeq-B antibodies and CellPlex (a multiplexing solution from 10x Genomics) on 2 pools of PBMCs from 3 different donors. Thus the genetic difference between donors was used as a ground truth for sample demultiplexing based on antibody or lipid hashing hashing. the aim 2 was to evaluate TotalSeq antibody and lipid hashing on different mice primary tissues using different hashing protocols.

2022-02-12 | E-MTAB-11401 | biostudies-arrayexpress

Single cell RNAseq reveal covid19 vaccine response difference

Project description:Single cell RNAseq was performed on PBMC isolated from health workers who received two doses of Pfizer COVID19 vaccine and determined as either normal responders or low responders by antibody test. Each group has 4 patients. Cells from each patient were labeled with Totalseq C hashing antibodies and mixed 1:1:1:1 for each group. Single cells were further captured using 10x chromium Next GEM 5 prime kit.

2022-10-03 | GSE199123 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data