DOI: 10.5061/dryad.m0cfxpp8v
title: Data from: A data-driven approach to establishing cell motility patterns as predictors of macrophage subtypes and their relation to cell morphology

description: The motility of macrophages in response to microenvironment stimuli is a
 hallmark of innate immunity, where macrophages play pro-inflammatory or
 pro-reparatory roles depending on their activation status during wound
 healing. Cell size and shape have been informative in defining macrophage
 subtypes. Studies show pro- and anti-inflammatory macrophages exhibit
 distinct migratory behaviors, in vitro, in 3D, and *in vivo, *but
 this link has not been rigorously studied. We apply both morphology and
 motility-based image processing approaches to analyze live cell images
 consisting of macrophage phenotypes. Macrophage subtypes are
 differentiated from primary murine bone marrow-derived macrophages using a
 potent lipopolysaccharide (LPS) or cytokine interleukin-4 (IL-4). We show
 that morphology is tightly linked to motility, which leads to our
 hypothesis that motility analysis could be used alone or in conjunction
 with morphological features for improved prediction of macrophage
 subtypes. We train a support vector machine (SVM) classifier to predict
 macrophage subtypes based on morphology alone, motility alone, and both
 morphology and motility combined. We show that motility has comparable
 predictive capabilities to morphology. However, using both measures can
 enhance predictive capabilities. While motility and morphological features
 can be individually ambiguous identifiers, together they provide
 significantly improved prediction accuracies (&gt;79%) from a training
 dataset of ~250 cells tracked over time using only phase contrast
 time-lapse microscopy. Thus, the approach combining cell motility and cell
 morphology information can accurately assess functionally diverse
 macrophage phenotypes quickly and efficiently. Our approach offers a
 cost-efficient and high-throughput method for screening biochemicals
 targeting macrophage polarization.
description: • Macrophage Differentiation: Naïve BMDMs (M0) were
 differentiated into M1 or M2 subtypes. For M1 differentiation, 100 ng/ml
 lipopolysaccharide (LPS) was used. For M2 differentiation, 20 ng/ml
 recombinant mouse interleukin-4 (IL-4) was employed. •
 Culturing and Activation: The macrophages were seeded in 24-well tissue
 culture-treated plates and activated as detailed in the accompanying
 manuscript. • Imaging: Time-lapse contrast images were
 captured 48 hours post-stimulation using a Carl Zeiss Observer Z1 inverted
 microscope with a motorized stage and incubation chamber. Imaging was done
 using the MetaMorph program with a Retiga R6 CCD camera, under 10× or 20×
 objective lenses.
description: # Data from: A data-driven approach to establishing cell motility patterns
 as predictors of macrophage subtypes and their relation to cell morphology
 #### Description of the data and file structure **Time-lapse Images of
 Murine Macrophages** Overview: This dataset comprises time-lapse images of
 murine macrophages cultured in vitro. The images are provided in TIFF
 format. Bone marrow was isolated from the femur bones of C57/BL6 mice to
 generate bone marrow-derived macrophages (BMDMs). We utilized a total of
 20 mice, creating five separate batches of BMDMs, with each batch derived
 from a mixture of bone marrow from 3-6 mice. These BMDMs were then
 differentiated into naïve (M0), M1, or M2 macrophages using specific
 stimuli and conditions. ### Files and variables #### Dataset Details: •
 Data Collection Period: September 2019 to May 2021. • File Naming
 Convention: Each file is named according to the Macrophage Type, Time
 Post-Differentiation, Time Interval, Magnification, and Scale. • Special
 Note for Batch 5: In this batch, time-lapse images were recorded from
 different wells. Additionally, only M1 and M2 macrophages were recorded in
 this batch. Batch File Name Description Time Interval Magnification Scale
 1 M0_16H_5m_10x.tif Naïve BMDMs 5 min 10× 2.155 pix/µm 1 M1_16H_5m_10x.tif
 M1 macrophages 5 min 10× 2.155 pix/µm 1 M2_16H_5m_10x.tif M2 macrophages 5
 min 10× 2.155 pix/µm 2 M0_48_h.tif Naïve BMDMs 5 min 20× 4.31 pix/µm 2
 M1_48_h.tif M1 macrophages 5 min 20× 4.31 pix/µm 2 M2_48_h.tif M2
 macrophages 5 min 20× 4.31 pix/µm 3 M0_BG.tif Naïve BMDMs 5 min 20× 4.31
 pix/µm 3 M1_BG.tif M1 macrophages 5 min 20× 4.31 pix/µm 3 M2_BG.tif M2
 macrophages 5 min 20× 4.31 pix/µm 4 M0.tif Naïve BMDMs 5 min 20× 4.31
 pix/µm 4 M1.tif M1 macrophages 5 min 20× 4.31 pix/µm 4 M2.tif M2
 macrophages 5 min 20× 4.31 pix/µm 5 M1_3.tif M1 macrophages 5 min 20× 4.31
 pix/µm 5 M1_4.tif M1 macrophages 5 min 20× 4.31 pix/µm 5 M2_3.tif M2
 macrophages 5 min 20× 4.31 pix/µm 5 M2_4.tif M2 macrophages 5 min 20× 4.31
 pix/µm 5 M2_5.tif M2 macrophages 5 min 20× 4.31 pix/µm 5 M2_6.tif M2
 macrophages 5 min 20× 4.31 pix/µm #### Code/software These are multiTIFF
 files that can be viewed in ImageJ. **Access Information** The article
 associated with this dataset has been published in PLOS One, and can also
 be accessed in
 [https://doi.org/10.5061/dryad.m0cfxpp8v](https://nam13.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5061%2Fdryad.m0cfxpp8v&data=05%7C02%7Cyhsun%40health.ucdavis.edu%7Cef3b79221e86427bb22f08de16f68882%7Cd791615b4e1b48b08c51101688e1999b%7C0%7C0%7C638973445275950524%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C60000%7C%7C%7C&sdata=UTM0I49YJCQpG9q5Hl%2ByBlazuY3RuLAn6aL%2FpmdLYNs%3D&reserved=0 "Original URL: https://doi.org/10.5061/dryad.m0cfxpp8v. Click or tap if you trust this link.") Contact Information: For questions or further information regarding this dataset, please contact Yao-Hui Sun at [yhsun@ucdavis.edu](mailto:yhsun@ucdavis.edu).