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Computer Research and Modeling, 2019, Volume 11, Issue 4, Pages 723–750
DOI: https://doi.org/10.20537/2076-7633-2019-11-4-723-750
(Mi crm739)
 

ANALYSIS AND MODELING OF COMPLEX LIVING SYSTEMS

Estimation of maximal values of biomass growth yield based on the mass-energy balance of cell metabolism

I. G. Minkevich

G. K. Skryabin Institute of Biochemistry and Physiology of Microorganisms, Russian Academy of Sciences, Pushchino Center for Biological Research, Russian Academy of Sciences, 5 Pr. Nauki, Pushchino, Moscow Region, 142290, Russia
References:
Abstract: The biomass growth yield is the ratio of the newly synthesized substance of growing cells to the amount of the consumed substrate, the source of matter and energy for cell growth. The yield is a characteristic of the efficiency of substrate conversion to cell biomass. The conversion is carried out by the cell metabolism, which is a complete aggregate of biochemical reactions occurring in the cells.
This work newly considers the problem of maximal cell growth yield prediction basing on balances of the whole living cell metabolism and its fragments called as partial metabolisms (PM). The following PM’s are used for the present consideration. During growth on any substrate we consider i) the standard constructive metabolism (SCM) which consists of identical pathways during growth of various organisms on any substrate. SCM starts from several standard compounds (nodal metabolites): glucose, acetyl-CoA 2-oxoglutarate, erythrose-4-phosphate, oxaloacetate, ribose-5-phosphate, 3-phosphoglycerate, phosphoenolpyruvate, and pyruvate, and ii) the full forward metabolism (FM) — the remaining part of the whole metabolism. The first one consumes high-energy bonds (HEB) formed by the second one. In this work we examine a generalized variant of the FM, when the possible presence of extracellular products, as well as the possibilities of both aerobic and anaerobic growth are taken into account. Instead of separate balances of each nodal metabolite formation as it was made in our previous work, this work deals at once with the whole aggregate of these metabolites. This makes the problem solution more compact and requiring a smaller number of biochemical quantities and substantially less computational time. An equation expressing the maximal biomass yield via specific amounts of HEB formed and consumed by the partial metabolisms has been derived. It includes the specific HEB consumption by SCM which is a universal biochemical parameter applicable to the wide range of organisms and growth substrates. To correctly determine this parameter, the full constructive metabolism and its forward part are considered for the growth of cells on glucose as the mostly studied substrate. We used here the found earlier properties of the elemental composition of lipid and lipid-free fractions of cell biomass. Numerical study of the effect of various interrelations between flows via different nodal metabolites has been made. It showed that the requirements of the SCM in high-energy bonds and NAD(P)H are practically constants. The found HEB-to-formed-biomass coefficient is an efficient tool for finding estimates of maximal biomass yield from substrates for which the primary metabolism is known. Calculation of ATP-to-substrate ratio necessary for the yield estimation has been made using the special computer program package, GenMetPath.
Keywords: biomass growth yield, cell metabolism, constructive metabolism, nodal metabolites, high-energy bonds, reductivity carriers, mass-energy balance.
Received: 15.11.2018
Revised: 04.06.2019
Accepted: 12.07.2019
Document Type: Article
UDC: 519.8
Language: English
Citation: I. G. Minkevich, “Estimation of maximal values of biomass growth yield based on the mass-energy balance of cell metabolism”, Computer Research and Modeling, 11:4 (2019), 723–750
Citation in format AMSBIB
\Bibitem{Min19}
\by I.~G.~Minkevich
\paper Estimation of maximal values of biomass growth yield based on the mass-energy balance of cell metabolism
\jour Computer Research and Modeling
\yr 2019
\vol 11
\issue 4
\pages 723--750
\mathnet{http://mi.mathnet.ru/crm739}
\crossref{https://doi.org/10.20537/2076-7633-2019-11-4-723-750}
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