Abstract

Distribution of energy during the growth and formation of useful chemicals by microorganisms can define the overall performance of a biotechnological system. However, to date, this distribution has not been used to reliably predict growth characteristics of phototrophic microorganisms. The presented research addresses this application by estimating the photon-associated Gibbs energy delivered for the photoheterotrophic growth of purple non-sulfur bacteria and production of dihydrogen. The approach is successfully evaluated with the data from a fed-batch growth of Rhodopseudomonas palustris nifA∗ fixing N2 gas in phototrophic conditions and a reliable prediction of growth characteristics is demonstrated. Additionally, literature-available experimental data is collected and used for evaluation of the presented thermodynamic approach to predict photoheterotrophic growth yields. A proposed thermodynamic framework with modification to account for the phototrophic growth can be used to predict growth rates in broader environmental niches and to assess the possibility for the development of novel biotechnological applications in light-induced biological systems.

Highlights

  • In the era of extensive computational research and increasing availability of omics tools, increasingly complex models for microbial transformations have been proposed

  • This study presents an addition to the well-established thermodynamic framework to analyze microbial growth

  • The original thermodynamic framework was proposed by McCarty (McCarty, 1965) and we suggest a modification to account for the photon-associated energy available for bacterial growth

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Summary

Introduction

In the era of extensive computational research and increasing availability of omics tools, increasingly complex models for microbial transformations have been proposed. Simplified models can have particular value if the evaluated system is of biotechnological importance and a stoichiometrically reliable analysis of microbial activity is needed. A stoichiometrically correct prediction of microbial transformations in simplified models. Thermodynamics of Photoheterotrophic Growth allows accurate prediction of the rates of substrate consumption and product formation, as well as total generation of biomass. Such prediction is a necessary and powerful tool for bioprocess engineers and laboratories investigating microbial bioconversions pathways with an aim toward a complete and controlled resource recovery

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