Deciphering the Duality of Clock and Growth Metabolism in a Cell Autonomous System Using NMR Profiling of the Secretome

Abstract

Oscillations in circadian metabolism are crucial to the well being of organism. Our understanding of metabolic rhythms has been greatly enhanced by recent advances in high-throughput systems biology experimental techniques and data analysis. In an in vitro setting, metabolite rhythms can be measured by time-dependent sampling over an experimental period spanning one or more days at sufficent resolution to elucidate rhythms. We hypothesized that cellular metabolic effects over such a time course would be influenced by both oscillatory and circadian-independent cell metabolic effects. Here we use nuclear magnetic resonance (NMR) spectroscopy-based metabolic profiling of mammalian cell culture media of synchronized U2 OS cells containing an intact transcriptional clock. The experiment was conducted over 48 h, typical for circadian biology studies, and samples collected at 2 h resolution to unravel such non-oscillatory effects. Our data suggest specific metabolic activities exist that change continuously over time in this settting and we demonstrate that the non-oscillatory effects are generally monotonic and possible to model with multivariate regression. Deconvolution of such non-circadian persistent changes are of paramount importance to consider while studying circadian metabolic oscillations.

Continuous in vivo Metabolism by NMR

“…Each replicate can be formulated as a single, complete model with different initial conditions, which is more appropriate for kinetic modeling applications than a time series of averages. Previous real-time methods have equal or greater temporal resolution at the expense of disadvantages such as being destructive (Link et al, 2014), limitation to cell suspensions (Link et al, 2014; Koczula et al, 2016), primarily measuring the media (Koczula et al, 2016; Sengupta et al, 2016), measuring broad classes of metabolites (Kang et al, 2012; Shalabaeva et al, 2017), or having combined biological and technical variance. CIVM-NMR minimizes noise by eliminating sampling and extraction variance.…”

“…While many studies employ sample preparation and extraction approaches effectively, direct or in vivo measurements are fundamentally simpler to obtain and interpret. Likewise, while carefully designed (Rhoades et al, 2017) and executed studies with large sample sizes yield powerful insights into the dynamics of biological systems (Sengupta et al, 2016; Krishnaiah et al, 2017; Cannon et al, 2018), continuous and repeated measurements on the same living sample are invaluable for monitoring and confirming these dynamics.…”

Systems Biology-Derived Discoveries of Intrinsic Clocks

“…Metabolic profiling is still quite noisy compared to transcriptome data at least for identifying tissue-specific signatures ( 300 ), and many challenges remain including identification of unknown metabolites, standardization of data repositories and reporting methods, and integration with other types of data. Researchers are beginning to use metabolic profiling over larger time courses and with higher resolution in cell culture lines ( 301 ). In the future, coupling these methods with gene knockout or knockdown of core clock components will enable researchers to identify connections between circadian rhythms and metabolism.…”

Time is ripe: maturation of metabolomics in chronobiology

“…Recently, we have used high temporal resolution (2 hour sampling) NMR-based targeted profiling of culture media and cells from human osteosarcoma (U2 OS) cell lines to demonstrate that circadian rhythms of glucose and glutamine metabolism are strongly affected by Myc oncogene expression[38]. We have also used quantitative targeted profiling of the secretome of U2 OS cells to show the presence of linear metabolic patterns latent in a typical circadian metabolic experiment, and suggest that detrending of such data prior to circadian analysis is potentially advantageous[39]. …”