Improved workflow for analysis of smooth muscle calcium signals from intact arterial preparations

Intracellular Ca2+ signals are well regarded for their regulation of cellular processes ranging from myocyte contraction, hormonal secretion, neural transmission, cellular metabolism, transcriptional regulation, and cell proliferation. Measurement of cellular Ca2+ is routinely performed using fluorescent microscopy techniques with biological indicators. Analysis of deterministic signals is relatively straightforward as relevant data can be discriminated based on the timing of cellular responses. However, analysis of stochastic events in complex tissues takes considerable time and effort that often includes visual analysis by trained investigators. The purpose of the current study was to determine if the image analysis workflow could be automated without introducing errors. This evaluation was addressed by re-analyzing a published “gold standard” dataset through visual analysis of Ca2+ signals from recordings made in pulmonary arterial myocytes of en face arterial preparations. We applied a combination of data-driven and statistical approaches with comparisons to our published data to assess the fidelity of the various approaches. Regions of interest with Ca2+ oscillations were detected automatically post-hoc using the LC Pro plug-in for ImageJ. Oscillatory signals were separated based on event durations between 4 and 40 seconds. These data were filtered based on cutoffs obtained from multiple methods and compared to the published manually curated “gold standard” dataset. After filtering, the number of true positives, false positives, and false negatives were calculated through comparisons to the gold standard dataset. Positive predictive value, sensitivity and false discovery rates were calculated. There were very few significant differences between the quality of the events and no systematic biases based on the data curation or filtering techniques. The lack of difference between manual data curation and statistically derived critical cutoff techniques leads us to question the importance of manually curating stochastic Ca2+ event datasets using labor-intensive visual observation techniques. NIH R01HL155295, R01HL149608 This is the full abstract presented at the American Physiology Summit 2023 meeting and is only available in HTML format. There are no additional versions or additional content available for this abstract. Physiology was not involved in the peer review process.