Tryptophan Production Maximization in a Fed-Batch Bioreactor with Modified E. coli Cells, by Optimizing Its Operating Policy Based on an Extended Structured Cell Kinetic Model

Abstract

Hybrid kinetic models, linking structured cell metabolic processes to the dynamics of macroscopic variables of the bioreactor, are more and more used in engineering evaluations to derive more precise predictions of the process dynamics under variable operating conditions. Depending on the cell model complexity, such a math tool can be used to evaluate the metabolic fluxes in relation to the bioreactor operating conditions, thus suggesting ways to genetically modify the microorganism for certain purposes. Even if development of such an extended dynamic model requires more experimental and computational efforts, its use is advantageous. The approached probative example refers to a model simulating the dynamics of nanoscale variables from several pathways of the central carbon metabolism (CCM) of E. coli cells, linked to the macroscopic state variables of a fed-batch bioreactor (FBR) used for the tryptophan (TRP) production. The used E. coli strain was modified to replace the PTS system for glucose (GLC) uptake with a more efficient one. The study presents multiple elements of novelty: (i) the experimentally validated modular model itself, and (ii) its efficiency in computationally deriving an optimal operation policy of the FBR.

Concepts and Tools to Model GRCs, and Some Essential CCM Pathways in Living Cells 1. Generalities

“…As proved in the literature, the in-silico (math/kinetic modelbased) numerical analysis of biochemical or biological processes by using MSDKM or HSMDM models are proved to be not only an essential but also an extremely beneficial tool for engineering evaluations aiming (i) to determine with a higher accuracy the optimal operating policies of complex multi-enzymatic reactors, [5,[19][20][21][22][23], or of bioreactors including the biomass adaptation to the variable bioreactor environment over hundreds of cell cycles [2,9,[24][25][26], or even (ii) to easier and quickly simulate and analyse the performances/ characteristics of various GMO-s alternatives, by using the "metabolic flux analysis" (MFA), [26][27][28][29][30], together with the gene-knock-out technique) [9,10,14,[30][31][32].…”

“…Even if the multi-enzymatic systems are advantageous, the engineering part used to optimize such a complex process is not an easy task because it must account for the interacting enzymatic reactions, enzymes deactivation kinetics (if significant), multiple and often opposed optimization objectives, technological constraints, and uncertainties coming from multiple sources (model / constraints inaccuracies, disturbances in the control variables), and a highly nonlinear process dynamics [2,19,20,[22][23][24][33][34][35]. All these parametric/model/data uncertainties require updating (with a certain frequency) the enzymatic process model, the optimal operating policies of the reactor being determined by using rather deterministic (model-based) optimization rules [36].…”

“…Such reduced cell models are able to adequately reproduce the dynamics of some CCM complex metabolic syntheses [10,31,32,40,44,45,46,47], but also the dynamics of some GRC-s [9,11,12,14,32,] tightly controlling the metabolic processes. Even if they are rather based on sparse information from various sources, unconventional statistical identification, and lumping algorithms [11,12,14,32,15,16,48,49], such structured reduced deterministic kinetic models have been proved to be extremely useful for in-silico (a) analyse and characterize the cell CCM, (b) for designing novel GRC-s conferring new properties/functions to the mutant cells, or (c) for engineering bioreactor evaluations [10,24,11,12,14,32,50] (see the part 2 of this paper).…”

“…In fact, the use of HSMDM hybrid models realizes a valuable combination of the process modelling-scales, by linking unstructured with structured process characteristics to generate more precise predictions (see the examples given by [9,10,24]). Basically, the HSMDM hybrid models use a two-level hierarchy: the bioreactor macroscopic state variables linked with the nanoscale variables describing the cell key metabolic processes, and cell syntheses of practical interest (usually resulting in excretable valuable metabolites).…”

“…Of course, additional CCM reaction pathways modules must be added to the structured cell model (in a detailed or reduced/ lumped form) if their presence is absolutely necessary to derive consistent CCM simulations. See for instance the discussion of [10,24,31,32,44,46,61,80].…”