What does calorimetry and thermodynamics of living cells tell us?

•Calorimetric data interpretation depends on device and available additional data.•Most information from fully balanced calorimeter; metabolic fluxes quantifiable.•Constant heat per electron/per mole oxygen characterizes catabolic metabolism.•Constant heat per cell provides information only about growth and inhibition rates.•Calorimetry is more precise than common chemical analysis for anaerobic processes.

This article presents and compares several thermodynamic methods for the quantitative interpretation of data from calorimetric measurements. Heat generation and absorption are universal features of microbial growth and product formation as well as of cell cultures from animals, plants and insects. The heat production rate reflects metabolic changes in real time and is measurable on-line. The detection limit of commercially available calorimetric instruments can be low enough to measure the heat of 100,000 aerobically growing bacteria or of 100 myocardial cells. Heat can be monitored in reaction vessels ranging from a few nanoliters up to many cubic meters. Most important the heat flux measurement does not interfere with the biological process under investigation. The practical advantages of calorimetry include the waiver of labeling and reactants. It is further possible to assemble the thermal transducer in a protected way that reduces aging and thereby signal drifts. Calorimetry works with optically opaque solutions.All of these advantages make calorimetry an interesting method for many applications in medicine, environmental sciences, ecology, biochemistry and biotechnology, just to mention a few. However, in many cases the heat signal is merely used to monitor biological processes but only rarely to quantitatively interpret the data. Therefore, a significant proportion of the information potential of calorimetry remains unutilized. To fill this information gap and to motivate the reader using the full information potential of calorimetry, various methods for quantitative data interpretations are presented, evaluated and compared with each other. Possible errors of interpretation and limitations of quantitative data analysis are also discussed.

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