A pico-calorimeter for cellular metabolism and antimicrobial susceptibility testing
Abstract
While methods exist to indirectly quantify the metabolism of biological systems, directly measuring metabolic rates in living samples remains challenging. Here, we describe a calorimetric sensor with a sensitivity of ~100 pW at 23.1 mHz, suitable for measurements on living organisms, surpassing previously reported sensitivities. The sensor measures minute temperature differences between a capillary that contains the sample and two reference capillaries, directly relating this temperature difference to the heat produced by the sample. The sensor provides high responsivity (23 to 100 nV/nW), a fast thermal response time (~7.9 s), and supports real-time, long-term monitoring of biological processes, such as the proliferation and growth of small numbers of bacteria. These capabilities offer opportunities to advance our understanding of complex biological phenomena. We demonstrate the utility of the sensor by measuring the growth rate of Escherichia coli . The technique enables estimation of the oxygen consumption rate per cell, the heat production per cell, and the associated contributions from respiration and fermentation. We further show how the growth rate changes in response to different concentrations of chloramphenicol, rifampicin, and ampicillin, three antibiotics with distinct mechanisms of action. The sensor shows significant potential for determining the minimum inhibitory concentrations of antibiotics, performing antibiotic susceptibility testing of pathogens, and enabling fundamental studies of microorganism metabolism.
Article Details
Journal Info
Proceedings of the National Academy of Sciences
National Academy of Sciences
Authors (7)
Juanjuan Zheng
State Key Laboratory of Synergistic Chem-Bio Synthesis, Frontiers Science Center for Transformative Molecules, School of Chemistry and Chemical Engineering, School of Biomedical Engineering, National Engineering Research Center of Advanced Magnetic Resonance Technologies for Diagnosis and Therapy (NERC-AMRT), National Center for Translational Medicine
Hang Yang
Adam Strandberg
Department of Molecular and Cellular Biology, Harvard University
Easun Arunachalam
Department of Molecular and Cellular Biology, Harvard University
William Ireland
John A. Paulson School of Engineering and Applied Sciences, Harvard University
Daniel J. Needleman
John A. Paulson School of Engineering and Applied Sciences, Harvard University
Joost J. Vlassak