» Articles » PMID: 37476002

Rianú: Multi-tissue Tracking Software for Increased Throughput of Engineered Cardiac Tissue Screening

Overview
Authors
Affiliations
Soon will be listed here.
Abstract

Background: The field of tissue engineering has provided valuable three-dimensional species-specific models of the human myocardium in the form of human Engineered Cardiac Tissues (hECTs) and similar constructs. However, hECT systems are often bottlenecked by a lack of openly available software that can collect data from multiple tissues at a time, even in multi-tissue bioreactors, which limits throughput in phenotypic and therapeutic screening applications.

Methods: We developed Rianú, an open-source web application capable of simultaneously tracking multiple hECTs on flexible end-posts. This software is operating system agnostic and deployable on a remote server, accessible via a web browser with no local hardware or software requirements. The software incorporates object-tracking capabilities for multiple objects simultaneously, an algorithm for twitch tracing analysis and contractile force calculation, and a data compilation system for comparative analysis within and amongst groups. Validation tests were performed using in-silico and in-vitro experiments for comparison with established methods and interventions.

Results: Rianú was able to detect the displacement of the flexible end-posts with a sub-pixel sensitivity of 0.555 px/post (minimum increment in post displacement) and a lower limit of 1.665 px/post (minimum post displacement). Compared to our established reference for contractility assessment, Rianú had a high correlation for all parameters analyzed (ranging from to ), demonstrating its high accuracy and reliability.

Conclusions: Rianú provides simultaneous tracking of multiple hECTs, expediting the recording and analysis processes, and simplifies time-based intervention studies. It also allows data collection from different formats and has scale-up capabilities proportional to the number of tissues per field of view. These capabilities will enhance throughput of hECTs and similar assays for in-vitro analysis in disease modeling and drug screening applications.

References
1.
Teles D, Kim Y, Ronaldson-Bouchard K, Vunjak-Novakovic G . Machine Learning Techniques to Classify Healthy and Diseased Cardiomyocytes by Contractility Profile. ACS Biomater Sci Eng. 2021; 7(7):3043-3052. PMC: 9188827. DOI: 10.1021/acsbiomaterials.1c00418. View

2.
Goldfracht I, Protze S, Shiti A, Setter N, Gruber A, Shaheen N . Generating ring-shaped engineered heart tissues from ventricular and atrial human pluripotent stem cell-derived cardiomyocytes. Nat Commun. 2020; 11(1):75. PMC: 6946709. DOI: 10.1038/s41467-019-13868-x. View

3.
Turnbull I, Mayourian J, Murphy J, Stillitano F, Ceholski D, Costa K . Cardiac Tissue Engineering Models of Inherited and Acquired Cardiomyopathies. Methods Mol Biol. 2018; 1816:145-159. PMC: 6561092. DOI: 10.1007/978-1-4939-8597-5_11. View

4.
Serrao G, Turnbull I, Ancukiewicz D, Kim D, Kao E, Cashman T . Myocyte-depleted engineered cardiac tissues support therapeutic potential of mesenchymal stem cells. Tissue Eng Part A. 2012; 18(13-14):1322-33. PMC: 3397121. DOI: 10.1089/ten.TEA.2011.0278. View

5.
Murphy J, Mayourian J, Stillitano F, Munawar S, Broughton K, Agullo-Pascual E . Adult human cardiac stem cell supplementation effectively increases contractile function and maturation in human engineered cardiac tissues. Stem Cell Res Ther. 2019; 10(1):373. PMC: 6894319. DOI: 10.1186/s13287-019-1486-4. View