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Single cell RNA-seq data comparing in vitro macrophages with M-CSF and M-CSF/Squalene

ABSTRACT: Single cell RNA-seq data comparing in vitro macrophages with M-CSF and M-CSF/Squalene

PROVIDER: PRJNA798676 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR17662145_1.fastq.gz	Fastqsanger.gz
	SRR17662145_2.fastq.gz	Fastqsanger.gz
	SRR17662146_1.fastq.gz	Fastqsanger.gz
	SRR17662146_2.fastq.gz	Fastqsanger.gz
	SRR17662147_1.fastq.gz	Fastqsanger.gz

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Single cell RNA-seq data comparing in vitro macrophages with M-CSF and M-CSF/Squalene

Project description:We performed single-cell RNA seq analysis on in vitro M-CSF-derived macrophages

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Integrated transcriptomic and metabolomic analysis reveals the metabolic programming of GM-CSF-and M-CSF-differentiated mouse macrophages

Project description:Macrophages play a critical role in the inflammatory response and tumor development. Macrophages are primarily divided into pro-inflammatory M1-like and anti-inflammatory M2-like macrophages based on their activation status and functions. In vitro macrophage models could be derived from mouse bone marrow cells stimulated with two types of differentiation factors: GM-CSF (GM-BMDMs) and M-CSF (M-BMDMs), to represent M1-and M2-like macrophages, respectively. Since macrophage differentiation requires coordinated metabolic reprogramming and transcriptional rewiring in order to fulfill their distinct roles, we combined both transcriptome and metabolome analysis, coupled with experimental validation, to gain insight into the metabolic status of GM-and M-BMDMs. The data revealed higher levels of the tricarboxylic acid cycle (TCA cycle), oxidative phosphorylation (OXPHOS), fatty acid oxidation (FAO), and urea and ornithine production from arginine in GM-BMDMs, and a preference for glycolysis, fatty acid storage, bile acid metabolism, and citrulline and nitric oxide (NO) production from arginine in M-BMDMs. Correlation analysis with the proteomic data showed high consistency in the mRNA and protein levels of metabolic genes. Similar results were also obtained when compared to RNA-seq data of human monocyte derived macrophages from the GEO database. Furthermore, canonical macrophage functions such as inflammatory response and phagocytosis were tightly associated with the representative metabolic pathways. In the current study, we identified the core metabolites, metabolic genes, and functional terms of the two distinct mouse macrophage populations. We also distinguished the metabolic influences of the differentiation factors GM-CSF and M-CSF, and wish to provide valuable information for in vitro macrophage studies.

2023-09-19 | MTBLS6502 | MetaboLights

Human Monocytes to M-CSF differentiated Macrophages

2011-11-07 | GSE9801 | GEO

RNAseq of human macrophages obtained from in vitro treatments with M-CSF/GM-CSF/CM-WSU-FSCCL

Project description:RNAseq of human macrophages obtained from in vitro treatments with M-CSF/GM-CSF/CM-WSU-FSCCL

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Human Monocytes to M-CSF differentiated Macrophages

Project description:This dataset was created to study M-CSF dependent in vitro differentiation of human monocytes to macrophages as a model process to demonstrate that independent component analysis (ICA) is a useful tool to support and extend knowledge-based strategies and to identify complex regulatory networks or novel regulatory candidate genes. Keywords: M-CSF, Monocytes, Macrophages Samples for microarray analysis were isolated from healthy donors and from donors with Niemann-Pick type C disease. Monocytes were differentiated to macrophages for 4 days in the presence of M-CSF (50 ng/ml,R\&D Systems). Differentiation was confirmed by phase contrast microscopy. Total RNA was extracted from the tissue biopsies according to the manufacturerM-BM-4s instructions using the RNeasy Protect Midi Kit (Qiagen). Purity and integrity of the RNA was assessed on the Agilent 2100 bioanalyzer with the RNA 6000 Nano LabChip reagent set (Agilent Technologies, BM-CM-6blingen, Germany). The RNA was quantified spectrophotometrically and then stored at M-bM-^HM-^R80M-BM-0C. Gene expression profiles were determined using Affymetrix HG-U133A and HG-U133plus2.0. Array scanning and expression analysis was performed using Microarray Analysis Suite 5.0 software. Each array was scaled to a target intensity of 100 (scaling to all probesets). *** CEL files not provided for GSM247170 and GSM247407

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Project description:Bone marrow cells were isolated, primed with M-CSF (M-BMDM) or GM-CSF (GM-BMDM) and cultured for 7 days. The proteomic difference between GM-BMDM and M-BMDM were analyzed to describe the phenotye and function of two types of macrophages.

2023-03-29 | PXD041180 |

Next Generation Sequencing For Quantitative Analysis Of Hepatic Transcriptomes In Response To Squalene

Project description:Purpose: The goal of this study was to determine squalene effect on hepatic transcriptome by comparing high-throughput data for tested group vs. control group in Wildtype New Zealand white rabbits. Method: Hepatic mRNA profile of two Wildtype New Zealand white rabbits groups fed over 4 weeks with 1% of sunflower oil and the second fed with purified 1% of sunflower oil and 0.5% of squalene was analysed by Transcriptome sequencing using DNBseq platform. Sequence reads that passed quality filters were mapped onto reference genome, followed by SNP & INDEL calling and Gene expression detection. Results: Squalene intake did not significantly influence single nucleotide polymorphisms. When alternative splicing events were tested, squalene administration had significant influence on splicing events, alternative 5' splicing, alternative 3' splicing Site and retained intron while no effect was found on skipped exons or mutually exclusive exons. Splicing patterns led to variety of differentially splicing genes and a variety of different isoforms from one gene. Differentially expressed genes were 18,485 in the squalene group and 18,286 in the control group. Conclusions: This study represents the first analysis of hepatic transcriptome in respond to squalene. Result data confirm that RNA-Sequencing is a sensitive and accurate tool that provides a framework for comparative investigations of known and novel DEGs.

2024-12-19 | GSE191236 | GEO

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