Trapalyzer: a computer program for quantitative analyses in fluorescent live-imaging studies of neutrophil extracellular trap formation

被引:2
|
作者
Ciach, Michal Aleksander [1 ]
Bokota, Grzegorz [1 ,2 ]
Manda-Handzlik, Aneta [3 ]
Kuzmicka, Weronika [3 ]
Demkow, Urszula [3 ]
Gambin, Anna [1 ]
机构
[1] Univ Warsaw, Fac Math Informat & Mech, Warsaw, Poland
[2] Univ Warsaw, Ctr New Technol, Warsaw, Poland
[3] Med Univ Warsaw, Dept Lab Diagnost & Clin Immunol Dev Age, Warsaw, Poland
来源
FRONTIERS IN IMMUNOLOGY | 2023年 / 14卷
关键词
neutrophil; neutrophil extracellular traps; fluorescent microscopy; digital image processing; image annotation; SYTOX & TRADE; green; chromatin; quantification;
D O I
10.3389/fimmu.2023.1021638
中图分类号
R392 [医学免疫学]; Q939.91 [免疫学];
学科分类号
100102 ;
摘要
Neutrophil extracellular traps (NETs), pathogen-ensnaring structures formed by neutrophils by expelling their DNA into the environment, are believed to play an important role in immunity and autoimmune diseases. In recent years, a growing attention has been put into developing software tools to quantify NETs in fluorescent microscopy images. However, current solutions require large, manually-prepared training data sets, are difficult to use for users without background in computer science, or have limited capabilities. To overcome these problems, we developed Trapalyzer, a computer program for automatic quantification of NETs. Trapalyzer analyzes fluorescent microscopy images of samples double-stained with a cell-permeable and a cell-impermeable dye, such as the popular combination of Hoechst 33342 and SYTOXTM Green. The program is designed with emphasis on software ergonomy and accompanied with step-by-step tutorials to make its use easy and intuitive. The installation and configuration of the software takes less than half an hour for an untrained user. In addition to NETs, Trapalyzer detects, classifies and counts neutrophils at different stages of NET formation, allowing for gaining a greater insight into this process. It is the first tool that makes this possible without large training data sets. At the same time, it attains a precision of classification on par with state-of-the-art machine learning algorithms. As an example application, we show how to use Trapalyzer to study NET release in a neutrophil-bacteria co-culture. Here, after configuration, Trapalyzer processed 121 images and detected and classified 16 000 ROIs in approximately three minutes on a personal computer. The software and usage tutorials are available at https://github.com/Czaki/Trapalyzer.
引用
收藏
页数:12
相关论文
共 10 条
  • [1] Live Imaging and Quantification of Neutrophil Extracellular Trap Formation
    Silva, Lakmali Munasinghage
    Moutsopoulos, Niki
    Bugge, Thomas H.
    Doyle, Andrew
    CURRENT PROTOCOLS, 2021, 1 (07):
  • [2] Differential Signalling and Kinetics of Neutrophil Extracellular Trap Release Revealed by Quantitative Live Imaging
    Maarten van der Linden
    Geertje H. A. Westerlaken
    Michiel van der Vlist
    Joris van Montfrans
    Linde Meyaard
    Scientific Reports, 7
  • [3] Differential Signalling and Kinetics of Neutrophil Extracellular Trap Release Revealed by Quantitative Live Imaging
    van der Linden, Maarten
    Westerlaken, Geertje H. A.
    van der Vlist, Michiel
    van Montfrans, Joris
    Meyaard, Linde
    SCIENTIFIC REPORTS, 2017, 7
  • [4] In Vitro Canine Neutrophil Extracellular Trap Formation: Dynamic and Quantitative Analysis by Fluorescence Microscopy
    Li, Ronald H. L.
    Tablin, Fern
    JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, 2018, (138):
  • [5] Integrated proteome and malonylome analyses reveal the neutrophil extracellular trap formation pathway in rheumatoid arthritis
    Hu, Biying
    Li, Dandan
    Zeng, Zhipeng
    Zhang, Zeyu
    Cao, Rui
    Dong, XiangNan
    Yun, Chen
    Li, Ling
    Kramer, Bernhard
    Morgera, Stanislao
    Hocher, Berthold
    Tang, Donge
    Yin, Lianghong
    Dai, Yong
    JOURNAL OF PROTEOMICS, 2022, 262
  • [6] In Vivo Imaging of Inflamed Glomeruli Reveals Dynamics of Neutrophil Extracellular Trap Formation in Glomerular Capillaries
    Westhorpe, Clare L. V.
    Bayard, James E.
    O'Sullivan, Kim M.
    Hall, Pam
    Cheng, Qiang
    Kitching, A. Richard
    Hickey, Michael J.
    AMERICAN JOURNAL OF PATHOLOGY, 2017, 187 (02): : 318 - 331
  • [7] Live-imaging of vertebrate morphogenesis and neural network formation by using Kaede and Dronpa, coral fluorescent proteins that can be photo-converted or reversibly highlighted
    Hatta, K.
    Tsujii, H.
    Aramaki, S.
    MECHANISMS OF DEVELOPMENT, 2005, 122 : S93 - S94
  • [8] Real-time observation of neutrophil extracellular trap formation in the inflamed mouse brain via two-photon intravital imaging
    Da Jeong Byun
    Young Min Kim
    Young-Min Hyun
    Laboratory Animal Research, 38
  • [9] Real-time observation of neutrophil extracellular trap formation in the inflamed mouse brain via two-photon intravital imaging
    Byun, Da Jeong
    Kim, Young Min
    Hyun, Young-Min
    LABORATORY ANIMAL RESEARCH, 2022, 38 (01)
  • [10] A Label-Free Quantitative Proteomic Analysis of Mouse Neutrophil Extracellular Trap Formation Induced by Streptococcus suis or Phorbol Myristate Acetate (PMA)
    Wang, Xiaoping
    Zhao, Jianqing
    Cai, Cong
    Tang, Xiaojuan
    Fu, Lei
    Zhang, Anding
    Han, Li
    FRONTIERS IN IMMUNOLOGY, 2018, 9