Modeling large-scale bioreactors with diffusion equations. Part I: Predicting axial dispersion coefficient and mixing times.

Bioreactor scale-up is complicated by dynamic interactions between mixing, reaction, mass transfer, and biological phenomena, the effects of which are usually predicted with simple correlations or case-specific simulations. This two-part study investigated whether axial diffusion equations could be used to calculate mixing times and to model and characterize large-scale stirred bioreactors in a general and predictive manner without fitting the dispersion coefficient. In this first part, a resistances-in-series model analogous to basic heat transfer theory was developed to estimate the dispersion coefficient such that only available hydrodynamic numbers and literature data were needed in calculations. For model validation, over 800 previously published experimentally determined mixing times were predicted with the transient axial diffusion equation. The collected data covered reactor sizes up to 160 m3 , single- and multi-impeller configurations with diverse impeller types, aerated and non-aerated operation in turbulent and transition flow regimes, and various mixing time quantification methods. The model performed excellently for typical multi-impeller configurations as long as flooding conditions were avoided. Mixing times for single-impeller and few nonstandard bioreactors were not predicted equally well. The transient diffusion equation together with the developed transfer resistance analogy proved to be a convenient and predictive model of mixing in typical large-scale bioreactors.

Modeling large-scale bioreactors with diffusion equations. Part II: Characterizing substrate, oxygen, temperature, carbon dioxide, and pH profiles.

Large-scale fermentation processes involve complex dynamic interactions between mixing, reaction, mass transfer, and the suspended biomass. Empirical correlations or case-specific computational simulations are usually used to predict and estimate the performance of large-scale bioreactors based on data acquired at bench scale. In this two-part-study, one-dimensional axial diffusion equations were studied as a general and predictive model of large-scale bioreactors. This second part focused on typical fed-batch operations where substrate gradients are known to occur, and characterized the profiles of substrate, pH, oxygen, carbon dioxide, and temperature. The physically grounded steady-state axial diffusion equations with first- and zeroth-order kinetics yielded analytical solutions to the relevant variables. The results were compared with large-scale Escherichia coli and Saccharomyces cerevisiae experiments and simulations from the literature, and good agreement was found in substrate profiles. The analytical profiles obtained for dissolved oxygen, temperature, pH, and CO 2 ${\text{CO}}_{2}$ were also consistent with the available data. Distribution functions for the substrate were defined, and efficiency factors for biomass growth and oxygen uptake rate were derived. In conclusion, this study demonstrated that axial diffusion equations can be used to model the effects of mixing and reaction on the relevant variables of typical large-scale fed-batch fermentations.

Substantial gradient mitigation in simulated large-scale bioreactors by optimally placed multiple feed points.

The performance of large-scale stirred tank and bubble column bioreactors is often hindered by insufficient macromixing of feeds, leading to heterogeneities in pH, substrate, and oxygen, which complicates process scale-up. Appropriate feed placement or the use of multiple feed points could improve mixing. Here, theoretically optimal placement of feed points was derived using one-dimensional diffusion equations. The utility of optimal multipoint feeds was evaluated with mixing, pH control, and bioreaction simulations using three-dimensional compartment models of four industrially relevant bioreactors with working volumes ranging from 8 to 237 m3 . Dividing the vessel axially in equal-sized compartments and locating a feed point or multiple feed points symmetrically in each compartment reduced the mixing time substantially by more than a minute and mitigated gradients of pH, substrate, and oxygen. Performance of the large-scale bioreactors was consequently restored to ideal, homogeneous reactor performance: oxygen consumption and biomass yield were recovered and the phenotypical heterogeneity of the biomass population was diminished.

Characterization, genome analysis and genetic tractability studies of a new nanocellulose producing Komagataeibacter intermedius isolate.

Bacterial nanocellulose (BC) is a highly versatile biopolymer currently pursued as a material of choice in varied themes of biomedical and material science research fields. With the aim to extend the biotechnological applications, the genetic tractability of the BC producers within the Komagataeibacter genus and its potential as an alternative host chassis in synthetic biology have been extensively studied. However, such studies have been largely focused on the model Komagataeibacter spp. Here, we present a novel K. intermedius strain capable of utilizing glucose, and glycerol sources for biomass and BC synthesis. Genome assembly identified one bacterial cellulose synthetase (bcs) operon containing the complete gene set encoding the BC biogenesis machinery (bcsI) and three additional copies (bcsII-IV). Investigations on the genetic tractability confirmed plasmid transformation, propagation of vectors with pBBR1 and p15A origin of replications and constitutive and inducible induction of recombinant protein in K. intermedius ENS15. This study provides the first report on the genetic tractability of K. intermedius, serving as starting point towards future genetic engineering of this strain.

Characterization of Komagataeibacter Isolate Reveals New Prospects in Waste Stream Valorization for Bacterial Cellulose Production.

Komagataeibacter spp. has been used for the bioconversion of industrial wastes and lignocellulosic hydrolysates to bacterial cellulose (BC). Recently, studies have demonstrated the capacity of Komagataeibacter spp. in the biotransformation of inhibitors found in lignocellulosic hydrolysates, aromatic lignin-derived monomers (LDMs) and acetate. In general, detoxification and BC synthesis from lignocellulosic inhibitors requires a carbon flow from acetyl-coA towards tricarboxylic acid and gluconeogenesis, respectively. However, the related molecular aspects have not yet been identified in Komagataeibacter spp. In this study, we isolated a cellulose-producing bacterium capable of synthesizing BC in a minimal medium containing crude glycerol, a by-product from the biodiesel production process. The isolate, affiliated to Komagataeibacter genus, synthesized cellulose in a minimal medium containing glucose (3.3 ± 0.3 g/L), pure glycerol (2.2 ± 0.1 g/L) and crude glycerol (2.1 ± 0.1 g/L). Genome assembly and annotation identified four copies of bacterial cellulose synthase operon and genes for redirecting the carbon from the central metabolic pathway to gluconeogenesis. According to the genome annotations, a BC production route from acetyl-CoA, a central metabolic intermediate, was hypothesized and was validated using acetate. We identified that when K. rhaeticus ENS9b was grown in a minimal medium supplemented with acetate, BC production was not observed. However, in the presence of readily utilizable substrates, such as spent yeast hydrolysate, acetate supplementation improved BC synthesis.

Wax ester production in nitrogen-rich conditions by metabolically engineered Acinetobacter baylyi ADP1.

Metabolic engineering can be used as a powerful tool to redirect cell resources towards product synthesis, also in conditions that are not optimal for the production. An example of synthesis strongly dependent on external conditions is the production of storage lipids, which typically requires a high carbon/nitrogen ratio. This requirement also limits the use of abundant nitrogen-rich materials, such as industrial protein by-products, as substrates for lipid production. Acinetobacter baylyi ADP1 is known for its ability to produce industrially interesting storage lipids, namely wax esters (WEs). Here, we engineered A. baylyi ADP1 by deleting the gene aceA encoding for isocitrate lyase and overexpressing fatty acyl-CoA reductase Acr1 in the wax ester production pathway to allow redirection of carbon towards WEs. This strategy led to 3-fold improvement in yield (0.075 â€‹g/g glucose) and 3.15-fold improvement in titer (1.82 â€‹g/L) and productivity (0.038 â€‹g/L/h) by a simple one-stage batch cultivation with glucose as carbon source. The engineered strain accumulated up to 27% WEs of cell dry weight. The titer and cellular WE content are the highest reported to date among microbes. We further showed that the engineering strategy alleviated the inherent requirement for high carbon/nitrogen ratio and demonstrated the production of wax esters using nitrogen-rich substrates including casamino acids, yeast extract, and baker's yeast hydrolysate, which support biomass production but not WE production in wild-type cells. The study demonstrates the power of metabolic engineering in overcoming natural limitations in the production of storage lipids.

Enhanced Population Control in a Synthetic Bacterial Consortium by Interconnected Carbon Cross-Feeding.

Engineered microbial consortia can provide several advantages over monocultures in terms of utilization of mixed substrates, resistance to perturbations, and division of labor in complex tasks. However, maintaining stability, reproducibility, and control over population levels in variable conditions can be challenging in multispecies cultures. In our study, we modeled and constructed a synthetic symbiotic consortium with a genetically encoded carbon cross-feeding system. The system is based on strains of Escherichia coli and Acinetobacter baylyi ADP1, both engineered to be incapable of growing on glucose on their own. In a culture supplemented with glucose as the sole carbon source, growth of the two strains is afforded by the exchange of gluconate and acetate, resulting in inherent control over carbon availability and population balance. We investigated the system robustness in terms of stability and population control under different inoculation ratios, substrate concentrations, and cultivation scales, both experimentally and by modeling. To illustrate how the system might facilitate division of genetic circuits among synthetic microbial consortia, a green fluorescent protein sensitive to pH and a slowly maturing red fluorescent protein were expressed in the consortium as measures of a circuit's susceptibility to external and internal variability, respectively. The symbiotic consortium maintained stable and linear growth and circuit performance regardless of the initial substrate concentration or inoculation ratio. The developed cross-feeding system provides simple and reliable means for population control without expression of non-native elements or external inducer addition, being potentially exploitable in consortia applications involving precisely defined cell tasks or division of labor.