About this Research Topic
The last few decades have seen the rise of molecular microbial techniques that allow determining the abundance of microbial players in their natural habitats, their coincidence and their relationships with environmental conditions. These techniques have also provided critical insights in the phylogeny and functional potentials of micro-organisms. Moreover, they contributed new bioinformatics tools to describe the genetic and functional composition of microbial communities However, this information has so far hardly be coupled to microbial physiological principles, which will be essential to provide quantitative, system-level understanding of biogeochemical processes.
Microbes play a critical role in driving and modulating biogeochemical processes and many of the ecosystem services delivered by microbes relate to this role. Already half a century ago, Monod and Pirt derived equations to quantitatively describe microbial growth and the rates of microbial biogeochemical conversions of elements. These equations were based on simple linear kinetics and analogies with enzymatic conversions. Since then, these equations and modifications thereof have been applied in almost all kinetic models developed for food technology, environmental microbiology and waste treatment technology.
At the same time though, various questions have risen on i) the applicability of equations derived for enzymes to describe complete microbes, ii) the applicability of parameters for (few) pure cultures to the entire microbial community (existing of mainly uncultivated organisms), iii) the representativeness of the laboratory-determined physiological parameters (usually high(-er) substrate concentrations) for in-situ microbial dynamics, iv) the extent to which maintenance, dormancy and mortality can be differentiated, and v) the impact of microbial interactions on metabolic networks and physiology of individual micro-organisms and the subsequent (modeled) microbial conversions. Despite these questions, the basic kinetic equations in models describing the rates of conversions through microbial communities have largely remained the same over time.
Various recent advances on experimental and modeling approaches, once further integrated, can be expected to strongly enhance quantitative insights into these questions. Microorganisms can now be grown under environmental relevant conditions, at very low growth rates and substrate concentrations, with their internal and external fluxes tracked using isotopically labeled substrates and their physiology studied at high resolution at the molecular level. Bioinformatics tools help to create, analyse and couple large microbial datasets, enabling a better use of physiological parameters that have so painstakingly collected in the 70s and 80s with chemostats and to link (meta)genome derived metabolic networks to ecology. New insights on the relation between microbial traits and kinetic trade-offs are obtained.
Therefore, within this topic, we will welcome contributions from researchers that employ interdisciplinary approaches that link these new advances to allow quantitatively describe biogeochemical processes to answer i) how we can do better in terms of quantitatively describing microbial traits, kinetic trade-offs at low and high substrate conditions, ii) how kinetic trade-offs can be incorporated in classic kinetic models, iii) which new model techniques and concepts (have) become available to quantify kinetic conversions and iv) how we can integrate molecular microbial data, physiological information and microbial kinetic models.
Microbes play a critical role in driving and modulating biogeochemical processes and many of the ecosystem services delivered by microbes relate to this role. Already half a century ago, Monod and Pirt derived equations to quantitatively describe microbial growth and the rates of microbial biogeochemical conversions of elements. These equations were based on simple linear kinetics and analogies with enzymatic conversions. Since then, these equations and modifications thereof have been applied in almost all kinetic models developed for food technology, environmental microbiology and waste treatment technology.
At the same time though, various questions have risen on i) the applicability of equations derived for enzymes to describe complete microbes, ii) the applicability of parameters for (few) pure cultures to the entire microbial community (existing of mainly uncultivated organisms), iii) the representativeness of the laboratory-determined physiological parameters (usually high(-er) substrate concentrations) for in-situ microbial dynamics, iv) the extent to which maintenance, dormancy and mortality can be differentiated, and v) the impact of microbial interactions on metabolic networks and physiology of individual micro-organisms and the subsequent (modeled) microbial conversions. Despite these questions, the basic kinetic equations in models describing the rates of conversions through microbial communities have largely remained the same over time.
Various recent advances on experimental and modeling approaches, once further integrated, can be expected to strongly enhance quantitative insights into these questions. Microorganisms can now be grown under environmental relevant conditions, at very low growth rates and substrate concentrations, with their internal and external fluxes tracked using isotopically labeled substrates and their physiology studied at high resolution at the molecular level. Bioinformatics tools help to create, analyse and couple large microbial datasets, enabling a better use of physiological parameters that have so painstakingly collected in the 70s and 80s with chemostats and to link (meta)genome derived metabolic networks to ecology. New insights on the relation between microbial traits and kinetic trade-offs are obtained.
Therefore, within this topic, we will welcome contributions from researchers that employ interdisciplinary approaches that link these new advances to allow quantitatively describe biogeochemical processes to answer i) how we can do better in terms of quantitatively describing microbial traits, kinetic trade-offs at low and high substrate conditions, ii) how kinetic trade-offs can be incorporated in classic kinetic models, iii) which new model techniques and concepts (have) become available to quantify kinetic conversions and iv) how we can integrate molecular microbial data, physiological information and microbial kinetic models.
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