Catabolic rates, population sizes and doubling/replacement times of microorganisms in natural settings

Abstract

Directly assessing the impact of subsurface microbial activity on global element cycles is complicated by the inaccessibility of most deep biospheres and the difficulty of growing representative cultivars in the laboratory. In order to constrain the rates of biogeochemical processes in such settings, a quantitative relationship between rates of microbial catalysis, energy supply and demand and population size has been developed that complements the limited biogeochemical data describing subsurface environments. Within this formulation, rates of biomass change are determined as a function of the proportion of catabolic power that is converted into anabolism—either new microorganisms or the replacement of existing cell components—and the amount of energy that is required to synthesize biomass. Catabolic power is related to biomass through an energy-based yield coefficient that takes into account the constraints that different environments impose on biomolecule synthesis; this method is compared to other approaches for determining yield coefficients. Furthermore, so-called microbial maintenance energies that have been reported in the literature, which span many orders of magnitude, are reviewed. The equations developed in this study are used to demonstrate the interrelatedness of catabolic reaction rates, Gibbs energy of reaction, maintenance energy, biomass yield coefficients, microbial population sizes and doubling/replacement times. The number of microorganisms that can be supported by particular combinations of energy supply and demand is illustrated as a function of the catabolic rates in marine environments. Replacement/doubling times for various population sizes are shown as well. Finally, cell count and geochemical data describing two marine sedimentary environments in the South Pacific Gyre and the Peru Margin are used to constrain in situ metabolic and catabolic rates. The formulations developed in this study can be used to better define the limits and extent of life because they are valid for any metabolism under any set of conditions.