Metabolic drivers of co-expressed biological rhythms in vitro

• Main Author: Ting, Isaiah
• Format: Conference Object
• Language: unknown
• Published: 2021
• Subjects: Common vole; Microtus arvalis
• Online Access: https://zenodo.org/record/4940127; https://doi.org/10.5281/zenodo.4940127

Rapid biological rhythms with periods from milliseconds to hours (ultradian rhythms) have been uncovered in many physiological processes such as the feeding and activity behaviours in the common vole (Microtus arvalis) 1,2, human temperature regulation 3 and NREM-REM cycles 4. Van der Veen and Gerkema have unmasked widespread ultradian gene expression in vitro, that are co-expressed with daily, 24-hour rhythms 5. Gene Ontology analysis of the probe list that express ultradian gene expression in the mouse in vivo and in NIH 3T3 cells in vitro revealed a significant enrichment for metabolic process was observed which further provides evidence of the presence of ultradian rhythms within metabolic processes. One particularly ultradian gene is pdcd5, which exhibited robust ultradian rhythmicity, and is involved with programmed cell death 5. A recent PubMed search with quoted search phrases “circadian rhythm” and “ultradian rhythm” yielded 32,265 and 788 articles, respectively, in the period between 2006 and 2021 showing “experimental neglect” of ultradian rhythms 6. Thus, more research is needed, specifically on the interactions of ultradian rhythms with metabolic processes and their contribution to maintenance of metabolic health. We therefore hypothesise that altering metabolic conditions can alter the balance between circadian and ultradian rhythms in several processes 7,8, including in pdcd5. NIH 3T3 cells (mouse embryonic fibroblasts) that have been transduced with our custom-made Pdcd5::Luc reporter construct were used for in vitro tracking of ultradian rhythms in real-time. To address our hypothesis on metabolic challenge, cells were incubated with or without low glucose (0.5 mM) for 18- and 24-hours pre-measurement as well as low glucose during measurement. Bioluminescence recordings were undertaken at 10-minute intervals using a LumiCycle. The resulting data were analysed in MATLAB2019a© by detrending the data to a 12-h running average, a high-pass filter in order to remove unwanted slower rhythms, a sample ...