A novel approach to determine the critical survival threshold of cellular oxygen within spheroids via integrating live/dead cell imaging with oxygen modeling.

Defining the oxygen level that induces cell death within 3-D tissues is vital for understanding tissue hypoxia; however, obtaining accurate measurements has been technically challenging. In this study, we introduce a noninvasive, high-throughput methodology to quantify critical survival partial oxygen pressure (pO 2 ) with high spatial resolution within spheroids by using a combination of controlled hypoxic conditions, semiautomated live/dead cell imaging, and computational oxygen modeling. The oxygen-permeable, micropyramid patterned culture plates created a precisely controlled oxygen condition around the individual spheroid. Live/dead cell imaging provided the geometric information of the live/dead boundary within spheroids. Finally, computational oxygen modeling calculated the pO 2  at the live/dead boundary within spheroids. As proof of concept, we determined the critical survival pO 2 in two types of spheroids: isolated primary pancreatic islets and tumor-derived pseudoislets (2.43 ± 0.08 vs. 0.84 ± 0.04 mmHg), indicating higher hypoxia tolerance in pseudoislets due to their tumorigenic origin. We also applied this method for evaluating graft survival in cell transplantations for diabetes therapy, where hypoxia is a critical barrier to successful transplantation outcomes; thus, designing oxygenation strategies is required. Based on the elucidated critical survival pO 2 , 100% viability could be maintained in a typically sized primary islet under the tissue pO 2 above 14.5 mmHg. This work presents a valuable tool that is potentially instrumental for fundamental hypoxia research. It offers insights into physiological responses to hypoxia among different cell types and may refine translational research in cell therapies. NEW & NOTEWORTHY Our study introduces an innovative combinatory approach for noninvasively determining the critical survival oxygen level of cells within small cell spheroids, which replicates a 3-D tissue environment, by seamlessly integrating three pivotal techniques: cell death induction under controlled oxygen conditions, semiautomated imaging that precisely identifies live/dead cells, and computational modeling of oxygen distribution. Notably, our method ensures high-throughput analysis applicable to various cell types, offering a versatile solution for researchers in diverse fields.