Sign in
MicrobiologybioRxiv
Preprint

Energy dissipation in early detection of cellular responses to metabolic challenges

R. N. Bento, M. A. Rendas, V. A. R. Semedo, C. F. Marques, G. C. Justino, C. E. S. Bernardes, M. E. M. d. Piedade, F. Antunes

Abstract

Metabolic alterations have been recognized to underly the etiology of many diseases. Herein, cellular energy dissipation was evaluated as a novel non-specific global biomarker of metabolic alterations. Energy dissipation, measured as heat by microcalorimetry, was maximal during Saccharomyces cerevisiae adaptation to growth conditions before fast proliferation took place. This response was further augmented by 95 % in media where nutrient assimilation was more difficult, and by 133 % under sub-optimal non-carbon nutrient levels. In this last case, the increase in energy dissipation (1) reflected changes in amino acid and glycolytic metabolism and (2) anticipated changes in the growth curve significantly later observed by traditional microbiological measurements. It was, therefore, an early marker of adaptive responses that compensated for sub-optimal nutrient levels and maintained phenotypic stability. Compensatory responses buffer systems against perturbations and delay the onset of diseases. Microcalorimetry can, therefore, provide a biomarker development platform for early disease-diagnosis. HIGHLIGHTSO_LIEnergy dissipation measurements detect cell responses to metabolic challenges. C_LIO_LIThe detection by microcalorimetry occurs considerably earlier than by traditional microbiological measurements. C_LIO_LISub-optimal non-carbon nutrient levels impact energy dissipation long before cell proliferation. C_LIO_LIEnergy dissipation is highly sensitive to increased nutrient assimilation difficulty. C_LI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISBento '16Woronoff '20Devlin '26Pereira '18Vasilakou '20Cossetto '25
67% semantic matchBiochemistry
Rafael N. Bento, Miguel A. Aradhya, Valdir A. R. Semedo+3 more·bioRxiv·Jul 15, 2016