Data from: Effect of stretching on inflammation in a subcutaneous carrageenan mouse model analyzed at single-cell resolution

Berrueta, Lisbeth1

Research facility: National Institute of Health

Published Dec 12, 2023 on Dryad. https://doi.org/10.5061/dryad.cc2fqz6ch

Data files

Dec 12, 2023 version files 5.10 MB

Abstract

Understanding the factors that influence the biological response to inflammation is crucial, due to its involvement in physiological and pathological processes, including tissue repair/healing, cancer, infections, and autoimmune diseases. We have previously demonstrated that in vivo stretching can reduce inflammation and increase local pro-resolving lipid mediators in rats, suggesting a direct mechanical effect on inflammation resolution. Here, we aimed to explore further the effects of stretching at the cellular/molecular level in a mouse subcutaneous carrageenan-inflammation model. Stretching for 10 minutes twice a day reduced inflammation, increased the production of pro-resolving mediator pathway intermediate 17-HDHA at 48h post carrageenan injection, and decreased both pro-resolving and pro-inflammatory mediators (e.g., PGE₂ and PGD₂) at 96h. ScRNAseq analysis of inflammatory lesions at 96h showed that stretching increased the expression of both pro-inflammatory (Nos2) and pro-resolution (Arg1) genes in M1 and M2 macrophages at 96 hours. An intercellular communication analysis predicted specific ligand-receptor interactions orchestrated by neutrophils and M2a macrophages, suggesting a continuous neutrophil presence recruiting immune cells such as activated macrophages to contain the antigen while promoting resolution and preserving tissue homeostasis.

README: README

#For the Ultrasound area:
#Berrueta et al_Area measured by US (ultrasound) carrageenan inflammation 24-96h. The data is organized as follow: There are 6 columns, column A describe the code assigned to each individual animal. Column B represent treatment: 0=No stretch, 1= stretch. Column C refers to the time for the treatment: from 24h to 96h. Column D refers to the batch or group of samples. Column E correspond to the weight of the tissue at the time of euthanasia in mg. Column F represent the ultrasound area of the inflammatory lesion per each sample.

#For the flow cytometry data
Neutrophils and macrophage subpopulation. Analysis was performed using Flow cytometry. The data set is organized as follow:
#Berrueta et al_neutrophils dynamics: There are 9 columns, column A indicates the code assigned to each individual animal. Column B represent treatment: 0=No stretch, 1= stretch. Column C refers to the time for the treatment: from 24h to 96h. Column D refers to the batch or group of samples. Column E indicates the type of cell. Column F is the total cell count per each sample. Column G represent the percentage of live cells per sample. Column H describes the relative number of CD45+ cells (leukocytes). Column I describe the relative number of neutrophils.

#For the macrophages: There are 8 columns, column A indicates the code assigned to each individual animal. Column B represent treatment: 0=No stretch, 1= stretch. Column C refers to the time for the treatment: from 48h to 96h. Column D refers to the batch or group of samples. Column E indicates the relative number (percentage-%) of CD45+ cells (leukocytes). Column F describe the relative number (percentage-%) of F4/80+ cells (macrophages) . Column G describe the relative number (percentage-%) of M1 macrophages. Column H describes the relative number (percentage-%) of M2 macrophages.

#Single cell and bulk library preparation and sequencing. Data set organization is as follow: For each of the cell populations:

#All.integrated.minus9.minus16.minus17.cDC1_stretch.markers.cDC1_non-stretch.markers. classic dendritic cells 1 (cDC1): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17.cDC2_stretch.markers. cDC2_non-stretch.markers. classic dendritic cells 2 (cDC2): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17.EC_stretch.markers. EC_non-stretch.markers. Endothelial cells (EC):The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. FB _stretch.markers. FB _non-stretch.markers. Fibroblasts (FB): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. iDC _stretch.markers. iDC _non-stretch.markers. inflammatory dendritic cells (iDC): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. M1 _stretch.markers. M1 _non-stretch.markers. M1 macrophages (M1): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. M2c _stretch.markers. M2c _non-stretch.markers. M2c macrophages (M2c): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. MC _stretch.markers. MC _non-stretch.markers. Mast cells (MC): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. Mo _stretch.markers. Mo _non-stretch.markers. Monocytes (Mo): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. Th1 _stretch.markers. Th1 _non-stretch.markers. T helper cells 1 (Th1): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. Th2 _stretch.markers. Th2 _non-stretch.markers. T helper cells 2 (Th2): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

#All.integrated.minus9.minus16.minus17. M2a _stretch.markers. M2a _non-stretch.markers. M2a macrophages (M2a): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

All.integrated.minus9.minus16.minus17. M2b _stretch.markers. M2b _non-stretch.markers. M2b macrophages (M2b): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

All.integrated.minus9.minus16.minus17. Nph _stretch.markers. Nph _non-stretch.markers. Neutophils (Nph): The data include 7 columns; column A include the total list of analyzed genes. Column B is the statistical significance p value, Column C represent the logarithmic of average expression or log 2FC per each gene. Column D is the actual Fold change expression per each gene. Column E is the gene expression for the Stretch sample (pct.1). Column F is the gene expression for the No stretch sample (pct.2). Column G is the adjusted p value.

For the Lipidomic data (LC-MS/MS: Liquid chromatography–mass spectrometry)
Berrueta et al Lipidomics data sharing 111723. Data set was organized as follow: There are 5 columns describing the data: Column A describe the total list of lipid mediators analyzed. Column B describe the average of each lipid mediator in No Stretch samples at 48h. Column C describe the average of each lipid mediator in Stretch samples at 48h. Column D describe the average of each lipid mediator in No Stretch samples at 96h. Column E describe the average of each lipid mediator in Stretch samples at 96h.

For the Lipidomic data (LC-MS/MS: Liquid chromatography–mass spectrometry)
Berrueta_et_al_Table_1_Lipidomics_111723. Data set was organized as follow: There are 5 columns describing the data: Column A describe the total list of lipid mediators analyzed. Column B describe the average of each lipid mediator in No Stretch samples at 48h. Column C describe the average of each lipid mediator in Stretch samples at 48h. Column D describe the average of each lipid mediator in No Stretch samples at 96h. Column E describe the average of each lipid mediator in Stretch samples at 96h.

Methods

All ultrasound data acquisition and measurements were performed by investigators blinded to intervention condition. Ultrasound images of the back were acquired under isoflurane anesthesia. A high-frequency ultrasound scanner (Vevo 2100, Fujifilm VisualSonics, Toronto, Canada) in B mode with a 21 MHz transducer (MS 250) was used for optimal spatial resolution. A conductive gel was centrifuged for 5 minutes to remove air bubbles and spread over the skin. The transducer was stabilized with a clamp and mounted into an articulated arm to control the distance and the angle between the transducer and the skin surface. the transducer was oriented transversal or sagittal perpendicular to the skin of the back and centered on the lesion area. Total lesion area was calculated by averaging the lesion area measured at transversal and sagittal positions.

Flow cytometry

Inflammatory lesions were excised and minced in 5% FBS-DMEM, using a scalpel, then the suspension was filtered through a 70mm filter. Isolated cells were counted using an automated cell counter TC20 (Bio-Rad, CA). For surface receptors, cells at 1 × 106/mL were stained with a mix of mouse monoclonal antibodies: To detect neutrophils (N=92) we used the antibodies: APC anti-mouse Ly-6/Ly-6c(Gr1) and FITC anti-mouse CD45; for macrophage populations (N=32): we used the following combination of antibodies: APC cy7 anti-mouse CD45, APC anti-mouse F4/80, FITC anti-mouse Nos2 (iNOS), PE anti-mouse CD206. Stained cells were examined using a FACSCanto II Flow Cytometer (BD Biosciences, San Jose, CA) with FlowJo single cell analysis software.

Single cell and bulk library preparation and sequencing

Single cell library preparation was performed according to the manufacturer’s instructions for the 10× Chromium single cell kit (10x Genomics). The libraries were then pooled and sequenced on a NextSeq 2000 sequencer (Illumina). Single cell RNA seq data processing and quality control Read processing was performed using the 10x Genomics workflow (Zheng et al. 2017). Briefly, the Cell Ranger Single Cell Software Suite (v3.0.1) was used for demultiplexing, barcode assignment, and unique molecular identifier (UMI) quantification (http://software.10xgenomics.com/single cell/overview/welcome). The reads were aligned to a custom mm10 reference genome (Genome Reference Consortium Mouse Build 38) extended with additional annotation for several frequently used mouse transgenes. Both lanes per sample were merged using the ‘cellranger mkfastq’ function and processed using the ‘cellranger count’ function. In total, the Cell Ranger software detected 7,921 cells per sample, sequenced at 23,326 reads and identifying 1,611 genes derived from 4,375 UMIs per cell on average across all samples. The following metrics were used to flag poor quality cells: number of genes detected, total number of UMIs, and percentage of molecules mapped to mitochondrial genes. Within the Seurat workflow, low quality and artifact cells were excluded by removing any cells that expressed fewer than 200 genes, and removed genes expressed in less than 3 cells. Gene expression matrices were transformed for better interpretability using the Seurat function ‘NormalizeData’. A total of 51,943 cells were included in the subsequent clustering and pseudo time analyses.

For cross-condition data integration and batch correction, ‘FindIntegrationAnchors’ and ‘IntegrateData’ were applied to data in Seurat, following the data integration vignette (https://satijalab.org/seurat/archive/v3.2/immune_alignment. html)

Targeted LC-MS/MS

Supernatants from the inflammatory lesions were placed in ice cold methanol containing deuterated internal standards (d₈-5S-hydroxyeicosatetraenoic acid (5-HETE), d₄-leukotriene B₄ (LTB4), d₄-prostaglandin E₂ (PGE₂) and d₅-lipoxin A₄ (LXA₄); 500pg each) and homogenized using a PTFE Dounce (Kimble Chase). Proteins were allowed to precipitate (4oC), and lipid mediators were extracted using C18 solid-phase cartridges as described before (Dalli et al., 2018) Measurement of lipid mediators was carried out by liquid chromatography-tandem mass spectrometry (LC-MS/MS) using a QTrap 5500 (ABSciex, Framingham, MA) equipped with a Shimadzu LC-20AD HPLC and a Shimadzu SIL-20AC autoinjector (Shimadzu, Kyoto, Japan). An Agilent Eclipse Plus C18 column (100mm x 4.6 mm x 1.8 mm) maintained at 50oC was used with a gradient of methanol/water/acetic acid of 55:45:0.01 (v/v/v) to 100:0:0.01 at 0.4 ml/min flow rate. Multiple reaction monitoring (MRM) transitions were used to identify and quantify lipid mediators in samples, as compared with retention times of authentic standards run in parallel. Quantification was achieved using calibration curves constructed with synthetic standards for each mediator, after normalization to extraction recovery based on internal standards and followed by normalization to tissue weight.