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Variability in single-cell oxygen consumption kinetics

Botte, E.; Cui, Y.; Magliaro, C.; Tenje, M.; Koren, K.; Rinaldo, A.; Stocker, R.; Behrendt, L.; Ahluwalia, A. D.

2023-12-11 bioengineering
10.1101/2023.12.06.570361 bioRxiv
Show abstract

We combined microfabricated devices with multiparameter identification algorithms to probe the variability in size-dependent oxygen consumption parameters of single human hepatic cells. We demonstrate that single cells exhibit an oxygen-dependent metabolic rate, typical of Michaelis-Menten kinetics, and that their maximal oxygen consumption is significantly lower than that of monolayers or 3D hepatic cell aggregates. Notably, we found that clusters of two or more cells competing for a limited oxygen supply reduced their maximal single-cell consumption rate, highlighting their ability to adapt to local resource availability and the presence of nearby cells. Next, we used our high-throughput approach to characterize the covariance of size and oxygen consumption within a cell population. The results show that cooperative behaviour emerges in cell clusters, and that single-cell size and metabolism can be described by a lognormal joint probability density. Our study thus serves as a foundation to connect the metabolic activity of single human hepatocytes to their tissue-or organ-level metabolism as well as describe its size-related variability through scaling laws.

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The top 7 journals account for 50% of the predicted probability mass.

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21
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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.