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Circadian disruption, as occurs in shift work, is associated with metabolic diseases often attributed to a discordance between internal clocks and environmental timekeepers. REV-ERB nuclear receptors are key components of the molecular clock, but their specific role in the SCN master clock is unknown. We report here that mice lacking circadian REV-ERB nuclear receptors in the SCN maintain free-running locomotor and metabolic rhythms, but these rhythms are notably shortened by 3 hours. When housed under a 24-hour light:dark cycle and fed an obesogenic diet, these mice gained excess weight and accrued more liver fat than controls. These metabolic disturbances were corrected by matching environmental lighting to the shortened endogenous 21-hour clock period, which decreased food consumption. Thus, SCN REV-ERBs are not required for rhythmicity but determine the freerunning period length. Moreover, these results support the concept that dissonance between environmental conditions and endogenous time periods causes metabolic disruption.

The distinction between biological processes of adipose tissue expansion is crucial to understanding metabolic derangements, but a robust method for quantifying adipocyte size has yet to be standardized. Here, we compared three methods for histological analysis in situ: one conventional approach using individual micrographs acquired by digital camera, and two with wholeslide image analysis pipelines involving proprietary (Visiopharm) and open-source software (QuPath with a novel ImageJ plugin). We found that micrograph analysis identified 10-40 times fewer adipocytes than whole-slide methods, and this small sample size resulted in high variances that could lead to statistical errors. The agreement of the micrograph method to measure adipocyte area with each of the two whole-slide methods was substantially less (R 2 of 0.6644 and 0.7125) than between the two whole-slide methods (R 2 of 0.9402). These inconsistencies were more pronounced in samples from high-fat diet fed mice. While the use of proprietary software resulted in the highest adipocyte count, the lower cost, ease of use, and minimal variances of the open-source software provided a distinct advantage for measuring the number and size of adipocytes. In conclusion, we recommend whole-slide image analysis methods to consistently measure adipocyte area and avoid unintentional errors due to small sample sizes.