Daniel W. Meyer

Prediction of the Adaptability of Pseudomonas putida DOT-T1E to a Second Phase of a Solvent for Economically Sound Two-Phase Biotransformations

ABSTRACT The strain Pseudomonas putida DOT-T1E was tested for its ability to tolerate second phases of different alkanols for their use as solvents in two-liquid-phase biotransformations. Although 1-decanol showed an about 10-fold higher toxicity to the cells than 1-octanol, the cells were able to adapt completely to 1-decanol only and could not be adapted in order to grow stably in the presence of a second phase of 1-octanol. The main explanation for this observation can be seen in the higher water and membrane solubility of 1-octanol. The hydrophobicity (log P) of a substance correlates with a certain partitioning of that compound into the membrane. Combining the log P value with the water solubility, the maximum membrane concentration of a compound can be calculated. With this simple calculation, it is possible to predict the property of an organic chemical for its potential applicability as a solvent for two-liquid-phase biotransformations with solvent-tolerant P. putida strains. Only compounds that show a maximum membrane concentration of less than 400 mM, such as 1-decanol, seem to be tolerated by these bacterial strains when applied in supersaturating concentrations to the medium. Taking into consideration that a solvent for a two-liquid-phase system should possess partitioning properties for potential substrates and products of a fine chemical synthesis, it can be seen that 1-decanol is a suitable solvent for such biotransformation processes. This was also demonstrated in shake cultures, where increasing amounts of a second phase of 1-decanol led to bacteria tolerating higher concentrations of the model substrate 3-nitrotoluene. Transferring this example to a 5-liter-scale bioreactor with 10% (vol/vol) 1-decanol, the amount of 3-nitrotoluene tolerated by the cells is up to 200-fold higher than in pure aqueous medium. The system demonstrates the usefulness of two-phase biotransformations utilizing solvent-tolerant bacteria.

A mixing model for turbulent flows based on parameterized scalar profiles

In this paper the closure of molecular mixing in turbulent reactive flows is addressed in the context of probability density function methods. It is safe to say that the lack of a general and accurate mixing model is a major source for uncertainties in turbulent combustion simulation. Here, we propose a model based on constructing statistical distributions of one-dimensional scalar profiles, i.e., fluid particles are associated to parameterized scalar profiles (PSP). Opposed to previous approaches, the PSP model results in a simple formulation and is able to produce very accurate results at low computational cost. For validation, a two-scalar mixing problem in homogeneous isotropic turbulence was used. The accuracy of the PSP model was demonstrated by comparison with direct numerical simulation data and confirms that the intrinsic physical assumptions are justified.

Multilevel Monte Carlo for two phase flow and Buckley-Leverett transport in random heterogeneous porous media

Monte Carlo (MC) is a well known method for quantifying uncertainty arising for example in subsurface flow problems. Although robust and easy to implement, MC suffers from slow convergence. Extending MC by means of multigrid techniques yields the multilevel Monte Carlo (MLMC) method. MLMC has proven to greatly accelerate MC for several applications including stochastic ordinary differential equations in finance, elliptic stochastic partial differential equations and also hyperbolic problems. In this study, MLMC is combined with a streamline-based solver to assess uncertain two phase flow and Buckley-Leverett transport in random heterogeneous porous media. The performance of MLMC is compared to MC for a two dimensional reservoir with a multi-point Gaussian logarithmic permeability field. The influence of the variance and the correlation length of the logarithmic permeability on the MLMC performance is studied.

Suitability of Recombinant Escherichia coli and Pseudomonas putida Strains for Selective Biotransformation of m-Nitrotoluene by Xylene Monooxygenase

ABSTRACT Escherichia coli JM101(pSPZ3), containing xylene monooxygenase (XMO) from Pseudomonas putida mt-2, catalyzes specific oxidations and reductions of m-nitrotoluene and derivatives thereof. In addition to reactions catalyzed by XMO, we focused on biotransformations by native enzymes of the E. coli host and their effect on overall biocatalyst performance. While m-nitrotoluene was consecutively oxygenated to m-nitrobenzyl alcohol, m-nitrobenzaldehyde, and m-nitrobenzoic acid by XMO, the oxidation was counteracted by an alcohol dehydrogenase(s) from the E. coli host, which reduced m-nitrobenzaldehyde to m-nitrobenzyl alcohol. Furthermore, the enzymatic background of the host reduced the nitro groups of the reactants resulting in the formation of aromatic amines, which were shown to effectively inhibit XMO in a reversible fashion. Host-intrinsic oxidoreductases and their reaction products had a major effect on the activity of XMO during biocatalysis of m-nitrotoluene. P. putida DOT-T1E and P. putida PpS81 were compared to E. coli JM101 as alternative hosts for XMO. These promising strains contained an additional dehydrogenase that oxidized m-nitrobenzaldehyde to the corresponding acid but catalyzed the formation of XMO-inhibiting aromatic amines at a significantly lower level than E. coli JM101.

Process and catalyst design objectives for specific redox biocatalysis.

Publisher Summary This chapter discusses selected targets for intensification of redox bioprocesses. Advances in the field of microbiology may provide an increasing number of enzymes and microorganisms potentially useful for redox biocatalysis. The use of host bacteria optimized for both the catalysis of the desired reaction and the applicability in an appropriate process setup may further improve the productivity of redox biocatalysis. A wide range of cytotoxic chemicals such as phenol, catechol, toluene, styrene, and xylenes are highly interesting starting compounds in redox biocatalysis. The chapter describes gene expression, cell metabolism, cofactor availability, oxygen transfer, and catalyst stability as possible targets for improving catalyst efficiency. Integrating these aspects on a molecular, physiological, and reaction-engineering level allows increasing the productivity of bioprocesses. In this respect, the selection of organic solvents and recombinant host strains is critically discussed in the chapter—in particular, the applicability of solvent-tolerant bacteria in two liquid-phase biotransformation is evaluated.

Pore-scale dispersion: Bridging the gap between microscopic pore structure and the emerging macroscopic transport behavior

We devise an efficient methodology to provide a universal statistical description of advection-dominated dispersion (Péclet→∞) in natural porous media including carbonates. First, we investigate the dispersion of tracer particles by direct numerical simulation (DNS). The transverse dispersion is found to be essentially determined by the tortuosity and it approaches a Fickian limit within a dozen characteristic scales. Longitudinal dispersion was found to be Fickian in the limit for bead packs and superdiffusive for all other natural media inspected. We demonstrate that the Lagrangian velocity correlation length is a quantity that characterizes the spatial variability for transport. Finally, a statistical transport model is presented that sheds light on the connection between pore-scale characteristics and the resulting macroscopic transport behavior. Our computationally efficient model accurately reproduces the transport behavior in longitudinal direction and approaches the Fickian limit in transverse direction.

Solver-based vs. grid-based multilevel Monte Carlo for two phase flow and transport in random heterogeneous porous media

Abstract We consider two phase flow and transport in heterogeneous porous media with uncertain permeability distribution. The resulting transport uncertainty is assessed by means of multilevel Monte Carlo (MLMC). In contrast to the Monte Carlo (MC) method, which operates on one specific numerical grid with one numerical solver, MLMC samples from a hierarchy of grids or numerical solvers. In this work, the MLMC performance resulting from a hierarchy consisting of a finite volume transport solver and a streamline-based solver is compared to a purely grid-based hierarchy. Unlike the established grid-based MLMC method, our solver-based MLMC method operates on the same numerical grid and therefore avoids difficulties related to the upscaling of permeability fields or boundary conditions on coarser grids. For a two dimensional test case with log-normal permeability distribution, both MLMC approaches are compared to a MC reference run. At equivalent accuracy, significant speedups of MLMC with respect to MC are achieved.

Making variability less variable: matching expression system and host for oxygenase-based biotransformations

Abstract Variability in whole-cell biocatalyst performance represents a critical aspect for stable and productive bioprocessing. In order to investigate whether and how oxygenase-catalyzed reactions are affected by such variability issues in solvent-tolerant Pseudomonas, different inducers, expression systems, and host strains were tested for the reproducibility of xylene and styrene monooxygenase catalyzed hydroxylation and epoxidation reactions, respectively. Significantly higher activity variations were found for biocatalysts based on solvent-tolerant Pseudomonasputida DOT-TIE and S12 compared with solvent-sensitive P. putida KT2440, Escherichiacoli JM101, and solvent-tolerant Pseudomonas taiwanensis VLB120. Specific styrene epoxidation rates corresponded to cellular styrene monooxygenase contents. Detected variations in activity strictly depended on the type of regulatory system employed, being high with the alk- and low with the lac-system. These results show that the occurrence of clonal variability in recombinant gene expression in Pseudomonas depends on the combination of regulatory system and host strain, does not correlate with a general phenotype such as solvent tolerance, and must be evaluated case by case.

Consistent inflow and outflow boundary conditions for transported probability density function methods

In transported probability density function (PDF) methods, the PDF transport equations are most often solved with realization based techniques using particles. In this paper, a consistent treatment of particle in- and outflow boundary conditions for transported PDF methods is devised. It is shown that the presented approach is simple and, most important, consistent with the underlying Eulerian PDF transport equation. This is not the case for other boundary condition implementations discussed in the literature, especially if the fluctuating particle velocities are high compared with the averaged ones.

Modeling molecular mixing in a spatially inhomogeneous turbulent flow

Simulations of spatially inhomogeneous turbulent mixing in decaying grid turbulence with a joint velocity–concentration probability density function (PDF) method were conducted. The inert mixing scenario involves three streams with different compositions. The mixing model of Meyer [“A new particle interaction mixing model for turbulent dispersion and turbulent reactive flows,” Phys. Fluids 22(3), 035103 (2010)], the interaction by exchange with the mean (IEM) model and its velocity-conditional variant, i.e., the IECM model, were applied. For reference, the direct numerical simulation data provided by Sawford and de Bruyn Kops [“Direct numerical simulation and lagrangian modeling of joint scalar statistics in ternary mixing,” Phys. Fluids 20(9), 095106 (2008)] was used. It was found that velocity conditioning is essential to obtain accurate concentration PDF predictions. Moreover, the model of Meyer provides significantly better results compared to the IECM model at comparable computational expense.