A New Algorithm to Analyze the Video Data of Cell Contractions in Microfluidic Platforms
Background. One of the rapidly developing trends in science is tissue engineering with use of microfluidic platform (MP) technology. To evaluate mechanical contraction of cells, optical microscopy recordings can be used. Known methods as a matter of fact substantially distort the shape and amplitude of the signal. Therefore, a modified approach is mandatory.
Objective. The development of an algorithm for the analysis of the video data of mechanical oscillations of cardiomyocytes on a microfluidic platform in order to determine their functional and structural properties at the tissue level.
Methods. The developed algorithm for the analysis of video images was implemented by the original program code in Matlab 2016. We analyzed the data of the cardiomyocyte contraction in cells cultured in MPs. Three groups of cells were analyzed: without stimulation and stimulated with electric fields of 5 and 25 V/cm. The form of the stimulating impulses is rectangular, the frequency is 1 Hz
Results. An algorithm for the video data analysis is proposed, which allows for estimating the rate of contraction in μm/s. Moreover, it allows for decomposing the mechanical oscillations of cells into components. The algorithm has been used to evaluate the change in the contraction rate of cardiomyocytes cultured in a lab-on-chip, as a function of voltage intensity and excitation frequency under different experimental conditions.Conclusions. The proposed method does not require any auxiliary biomarkers or media. Analysis of video images allows us to estimate the amplitude and rate of oscillations, the shape of the signal, the spatial heterogeneity distribution of the mechanical activity of cells. Our results show that the pulsed electric field in the range 5–25 V/cm at frequencies of 1 Hz during cell cultivation affects negatively the mechanical functional abilities of cardiomyocytes.
Rohr S, Scholly DM, Kleber AG. Patterned growth of neonatal rat heart cells in culture morphological and electrophysiological characterization. Circulation Res. 1991;68:114-30. DOI: 10.1161/01.RES.68.1.114
Teplenin A, Krasheninnikova A, Agladze N, Sidoruk K, Agapova O, Agapov I, et al. Functional analysis of the engineered cardiac tissue grown on recombinant spidroin fiber meshes. PLoS ONE. 2015;10(3):e0121155. DOI: 10.1371/journal.pone.0121155
Wang X, Chen S, Kong M, Wang Z, Costa KD, Li RA, et al. Enhanced cell sorting and manipulation with combined optical tweezer and microfluidic chip technologies. Lab Chip. 2011;11:3656-62. DOI: 10.1039/C1LC20653B
Wikswo JP, Curtis EL, Eagleton ZE, Evans BC, Kole A, Hofmeisterab LH, et al. Scaling and systems biology for integrating multiple organs-on-a-chip. Lab Chip. 2013;13:3496-511. DOI: 10.1039/C3LC50243K
Burridge P, Thompson S, Millrod M, Weinberg S, Yuan X, Peters A, et al. A universal system for highly efficient cardiac differentiation of human induced pluripotent stem cells that eliminates interline variability. PLoS ONE. 2011;6(4):e18293. DOI: 10.1371/journal.pone.0018293
Huebsch N, Loskill P, Mandegar MA, Marks NC, Sheehan AS, Ma Z, et al. Automated video-based analysis of contractility and calcium flux in human-induced pluripotent stem cell-derived cardiomyocytes cultured over different spatial scales. Tissue Eng Part C. 2015;21(5):467-79. DOI: 10.1089/ten.TEC.2014.0283
Maddah M, Heidmann J, Mandegar M, Walker C, Bolouki S, Conklin B, et al. A non-invasive platform for functional characterization of stem-cell-derived cardiomyocytes with applications in cardiotoxicity testing. Stem Cell Reports. 2015;4(4):621-31. DOI: 10.1016/j.stemcr.2015.02.007
Marsano A, Conficconi C, Lemme M, Occhetta P, Gaudiello E, Votta E, et al. Beating heart on a chip: A novel microfluidic platform to generate functional 3D cardiac microtissues. LabChip. 2016 Feb 7;16(3):599-610. DOI: 10.1039/C5LC01356A
Werley CA, Chien MP, Gaublomme J, Shekhar K, Butty V, Yi BA, et al. Geometry-dependent functional changes in iPSC-derived cardiomyocytes probed by functional imaging and RNA sequencing. PLoS ONE. 2017;12(3):e0172671. DOI: 10.1371/journal.pone.0172671
Burridge PW, Thompson S, Millrod MA, Weinberg S, Yuan X, Peters A, et al. A universal system for highly efficient cardiac differentiation of human induced pluripotent stem cells that eliminates interline variability. PLoS ONE. 2011;6(4):e18293. DOI: 10.1371/journal.pone.0018293
– DMEM, high glucose | Thermo Fisher Scientific [Internet]. Thermofisher.com. 2018 [cited 10 April 2018]. Available from: https://www.thermofisher.com/it/en/home/technical-resources/media-formulation.170.html
Bogolyubov VM, Ponomarenko GN. General physiotherapy. 3rd ed. Moscow, SPb: SLP; 1998. 480 p.
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