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.

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.

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.

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.

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

spp. has been used for the bioconversion of industrial wastes and lignocellulosic hydrolysates to bacterial cellulose (BC). Recently, studies have demonstrated the capacity of spp.

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

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.