DOI: 10.5061/dryad.cc2fqz6ch
title: Data from: Effect of stretching on inflammation in a subcutaneous carrageenan mouse model analyzed at single-cell resolution

description: 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.
description: 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 (d<sub>8</sub>-5S-hydroxyeicosatetraenoic acid (5-HETE), d<sub>4</sub>-leukotriene B<sub>4</sub> (LTB4), d<sub>4</sub>-prostaglandin E<sub>2</sub> (PGE<sub>2</sub>) and d<sub>5</sub>-lipoxin A<sub>4</sub> (LXA<sub>4</sub>); 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. 
description: # 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.