Cardiomyocytes: Analysis of Temperature Response and Signal Propagation between Dissociated Clusters Using Novel Video-Based Movement Analysis Software

Dhanesh Kattipparambil Rajan, Antti Juhana Mäki, Mari Pekkanen-Mattila, Joose Kreutzer, Tomi Ryynänen, Hannu Välimäki, Jarmo Verho, Jussi T. Koivumäki, Heimo Ihalainen, Katriina Aalto-Setälä, Pasi Kallio, Jukka Lekkala

Tutkimustuotos: ArtikkeliTieteellinenvertaisarvioitu

4 Sitaatiot (Scopus)
92 Lataukset (Pure)

Abstrakti

Human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) provide a great resource for functional cell and tissue models that can be applied in heart research, pharmaceutical industry, and future regenerative medicine. During cell model experiments, precise control of environmental parameters is important. Temperature is a fundamental parameter, and the acute effect of temperature on hiPSC-CM functions has previously been studied. This paper reports on long-term, systematic temperature response studies of hiPSC-CM cultures. The studies were conducted outside an incubator in a modular cell culturing system along with a temperature sensor plate (TSP) and a new beating analysis software (CMaN -cardiomyocyte function analysis tool). Temperature sensing at the actual cell location is challenging with bulky external sensors; however, a TSP with resistive microsensors provides an effortless solution. Experimental results showed that temperature nonlinearly affects the hiPSC-CM beating frequency with a Q10 temperature coefficient of 2.2. Both the active (contraction) and passive (relaxation) movements were influenced by temperature, and changes in the relaxation times were larger than the contraction times. However, the contraction amplitudes exhibited a greater spread of variation. We also present novel results on the visualization of hiPSC-CM contractile networking and non-invasive image-based measurement of signal propagation between dissociated CM clusters. Compared with previously reported tools, CMaN is an advanced and easy-to-use robust software. It is faster, more sensitive, computationally less expensive, and extracts six different signals of the contractile motion per process, providing at least one useful beating signal even in complex cases. The software also supports movement center detection and independent computation of the relaxation and contraction parameters.

AlkuperäiskieliEnglanti
Sivut109275-109288
Sivumäärä14
JulkaisuIEEE Access
Vuosikerta8
DOI - pysyväislinkit
TilaJulkaistu - 2020
OKM-julkaisutyyppiA1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä

Rahoitus

This work was supported by the Business Finland [former Finnish Funding Agency for Technology and Innovation (TEKES)] through the Human Spare Parts 2 Project.

Julkaisufoorumi-taso

  • Jufo-taso 2

!!ASJC Scopus subject areas

  • Yleinen tietojenkäsittelytiede
  • Yleinen materiaalitiede
  • Yleinen tekniikka

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