Heparan sulfate induces necroptosis in murine cardiomyocytes: A medical-in silico approach combining in vitro experiments and machine learning

  • Life-threatening cardiomyopathy is a severe, but common, complication associated with severe trauma or sepsis. Several signaling pathways involved in apoptosis and necroptosis are linked to trauma- or sepsis-associated cardiomyopathy. However, the underling causative factors are still debatable. Heparan sulfate (HS) fragments belong to the class of danger/damage-associated molecular patterns liberated from endothelial-bound proteoglycans by heparanase during tissue injury associated with trauma or sepsis. We hypothesized that HS induces apoptosis or necroptosis in murine cardiomyocytes. By using a novel Medical-In silico approach that combines conventional cell culture experiments with machine learning algorithms, we aimed to reduce a significant part of the expensive and time-consuming cell culture experiments and data generation by using computational intelligence (refinement and replacement). Cardiomyocytes exposed to HS showed an activation of the intrinsic apoptosis signal pathway via cytochrome C and the activation of caspase 3 (both p < 0.001). Notably, the exposure of HS resulted in the induction of necroptosis by tumor necrosis factor α and receptor interaction protein 3 (p < 0.05; p < 0.01) and, hence, an increased level of necrotic cardiomyocytes. In conclusion, using this novel Medical-In silico approach, our data suggest (i) that HS induces necroptosis in cardiomyocytes by phosphorylation (activation) of receptor-interacting protein 3, (ii) that HS is a therapeutic target in trauma- or sepsis-associated cardiomyopathy, and (iii) indicate that this proof-of-concept is a first step toward simulating the extent of activated components in the pro-apoptotic pathway induced by HS with only a small data set gained from the in vitro experiments by using machine learning algorithms.

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Author:Elisabeth Zechendorf, Phillip Vaßen, Jieyi Zhang, Ahmed Hallawa, Antons Martincuks, Oliver Krenkel, Gerhard Müller-Newen, Tobias Schuerholz, Tim-Philipp Simon, Gernot Marx, Gerd Ascheid, Anke Schmeink, Guido Dartmann, Christoph Thiemermann, Lukas Martin
URN:urn:nbn:de:hbz:tr5-904
DOI:https://doi.org/10.3389/fimmu.2018.00393
Parent Title (German):Frontiers in Immunology
Publisher:Frontiers Media
Document Type:Article (specialist journals)
Language:English
Date of OPUS upload:2022/08/31
Date of first Publication:2018/03/20
Publishing University:Hochschule Trier
Release Date:2022/09/05
Tag:Petri nets; apoptosis; modeling; necroptosis; optimization; septic cardiomyopathy; small data
GND Keyword:Herzmuskelkrankheit; Apoptosis; Maschinelles Lernen
Volume:9
Article Number:393
Page Number:12
First Page:1
Last Page:12
Departments:FB Umweltplanung/-technik (UCB)
Dewey Decimal Classification:6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International