Atomic force microscopy combined with human pluripotent stem cell derived cardiomyocytes for biomechanical sensing

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This publication doesn't include Faculty of Arts. It includes Faculty of Medicine. Official publication website can be found on muni.cz.
Authors

PEŠL Martin PŘIBYL Jan AĆIMOVIĆ Ivana VILOTIĆ Aleksandra JELÍNKOVÁ Šárka SALYKIN Anton LACAMPAGNE Alain DVOŘÁK Petr MELI Albano SKLÁDAL Petr ROTREKL Vladimír

Year of publication 2016
Type Article in Periodical
Magazine / Source Biosensors & Bioelectronics
MU Faculty or unit

Faculty of Medicine

Citation
Web http://www.sciencedirect.com/science/article/pii/S0956566316305036
Doi http://dx.doi.org/10.1016/j.bios.2016.05.073
Field Biotechnology
Keywords Micromechanical biosensor; Human stem cell; Cardiomyocyte contraction; Drug testing
Attached files
Description Cardiomyocyte contraction and relaxation are important parameters of cardiac function altered in many heart pathologies. Biosensing of these parameters represents an important tool in drug development and disease modeling. Human embryonic stem cells and especially patient specific induced pluripotent stem cell-derived cardiomyocytes are well established as cardiac disease model.. Here, a live stem cell derived embryoid body (EB) based cardiac cell syncytium served as a biorecognition element coupled to the microcantilever probe from atomic force microscope thus providing reliable micromechanical cellular biosensor suitable for whole-day testing. The biosensor was optimized regarding the type of cantilever, temperature and exchange of media; in combination with standardized protocol, it allowed testing of compounds and conditions affecting the biomechanical properties of EB. The studied effectors included calcium , drugs modulating the catecholaminergic fight-or-flight stress response such as the beta-adrenergic blocker metoprolol and the beta-adrenergic agonist isoproterenol. Arrhythmogenic effects were studied using caffeine. Furthermore, with EBs originating from patient's stem cells, this biosensor can help to characterize heart diseases such as dystrophies.
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