TEM ExosomeAnalyzer: a computer‐assisted software tool for quantitative evaluation of extracellular vesicles in transmission electron microscopy images. Issue 1 (21st January 2019)

• Record Type: Journal Article
• Authors: Kotrbová, Anna; Štěpka, Karel; Maška, Martin; Pálenik, Jakub Jozef; Ilkovics, Ladislav; Klemová, Dobromila; Kravec, Marek; Hubatka, František; Dave, Zankruti; Hampl, Aleš; Bryja, Vítězslav; Matula, Pavel; Pospíchalová, Vendula
• Is Part Of: Journal of extracellular vesicles. Volume 8:Issue 1(2019)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2019-01-21
• Subjects: Exosome -- transmission electron microscopy -- negative staining -- cryo‐electron microscopy -- extracellular vesicles -- semi‐automatic detection -- segmentation -- image analysis -- morphological seeded watershed -- size distribution profile; Cells -- Mechanical properties -- Periodicals; Transport Vesicles; Cells -- Mechanical properties; Periodicals; Fulltext; Internet Resources; Periodicals; Electronic journals; Periodicals; 571.63
• DOI: 10.1080/20013078.2018.1560808
• Languages: English
• ISSNs: 2001-3078

Abstract

ABSTRACT: Extracellular vesicles (EVs) function as important conveyers of information between cells and thus can be exploited as drug delivery systems or disease biomarkers. Transmission electron microscopy (TEM) remains the gold standard method for visualisation of EVs, however the analysis of individual EVs in TEM images is time‐consuming if performed manually. Therefore, we present here a software tool for computer‐assisted evaluation of EVs in TEM images. TEM ExosomeAnalyzer detects EVs based on their shape and edge contrast criteria and subsequently analyses their size and roundness. The software tool is compatible with common negative staining protocols and isolation methods used in the field of EV research; even with challenging TEM images (EVs both lighter and darker than the background, images containing artefacts or precipitated stain, etc .). If the fully‐automatic analysis fails to produce correct results, users can promptly adjust the detected seeds of EVs as well as their boundaries manually. The performance of our tool was evaluated for three different modes with variable levels of human interaction, using two datasets with various heterogeneity. The semi‐automatic mode analyses EVs with high success rate in the homogenous dataset (F1 score 0.9094, Jaccard coefficient 0.8218) as well as in the highly heterogeneous dataset containing EVs isolated from cell culture medium and patient samples (F1 score 0.7619, Jaccard coefficient 0.7553). Moreover, the extracted size distribution profiles of EVs isolated from malignant ascites of ovarian cancer patients overlap with those derived by cryo‐EM and are comparable to NTA‐ and TRPS‐derived data. In summary, TEM ExosomeAnalyzer is an easy‐to‐use software tool for evaluation of many types of vesicular microparticles and is available at http://cbia.fi.muni.cz/exosome‐analyzer free of charge for non‐commercial and research purposes. The web page contains also detailed description how to use the software tool including a video tutorial.