Real-Time monitoring of intracellular wax ester metabolism

<p>Abstract</p> <p>Background</p> <p>Wax esters are industrially relevant molecules exploited in several applications of oleochemistry and food industry. At the moment, the production processes mostly rely on chemical synthesis from rather expensive starting materials, and therefore solutions are sought from biotechnology. Bacterial wax esters are attractive alternatives, and especially the wax ester metabolism of <it>Acinetobacter </it>sp. has been extensively studied. However, the lack of suitable tools for rapid and simple monitoring of wax ester metabolism <it>in vivo </it>has partly restricted the screening and analyses of potential hosts and optimal conditions.</p> <p>Results</p> <p>Based on sensitive and specific detection of intracellular long-chain aldehydes, specific intermediates of wax ester synthesis, bacterial luciferase (LuxAB) was exploited in studying the wax ester metabolism in <it>Acinetobacter baylyi </it>ADP1. Luminescence was detected in the cultivation of the strain producing wax esters, and the changes in signal levels could be linked to corresponding cell growth and wax ester synthesis phases.</p> <p>Conclusions</p> <p>The monitoring system showed correlation between wax ester synthesis pattern and luminescent signal. The system shows potential for real-time screening purposes and studies on bacterial wax esters, revealing new aspects to dynamics and role of wax ester metabolism in bacteria.</p

Production of long chain alkyl esters from carbon dioxide and electricity by a two-stage bacterial process

Microbial electrosynthesis (MES) is a promising technology for the reduction of carbon dioxide into value-added multicarbon molecules. In order to broaden the product profile of MES processes, we developed a two-stage process for microbial conversion of carbon dioxide and electricity into long chain alkyl esters. In the first stage, the carbon dioxide is reduced to organic compounds, mainly acetate, in a MES process by Sporomusa ovata. In the second stage, the liquid end-products of the MES process are converted to the final product by a second microorganism, Acinetobacter baylyi in an aerobic bioprocess. In this proof-of-principle study, we demonstrate for the first time the bacterial production of long alkyl esters (wax esters) from carbon dioxide and electricity as the sole sources of carbon and energy. The process holds potential for the efficient production of carbon-neutral chemicals or biofuels.acceptedVersionPeer reviewe

Method for acrylic acid monomer detection with recombinant biosensor cells for enhanced plastic degradation monitoring from water environments

Plastic debris degrades in the water environments due to various factors such as mechanical stress. Small-sized degradation products, including plastic monomers, are currently monitored using equipment which might be unsuitable for screening. Here, we developed a recombinant whole-cell bacterial biosensor, which could be used for this type of monitoring. The Escherichia coli pBAV1K-ACU-lucFF cells contain a luciferase-based reporter system under the control of acrylic acid specific promoter. The biosensor cells were used to detect acrylic acid monomers from both sterile water and spiked lake water samples, indicating usability with environmental samples. Furthermore, poly(acrylic acid) was incubated in salt water, and the biosensor cells could identify acrylic acid monomers originating from it. Thus, the cells could be used to observe similar processes in the environment. The results show that the bacterial biosensors could complement the current research methods of plastic monomer monitoring in water environments with a potential for higher throughputs.publishedVersionPeer reviewe

Engineering cell morphology by CRISPR interference in Acinetobacter baylyi ADP1

publishedVersionPeer reviewe

Playing Software

Non peer reviewe

Assessment of metabolic flux distribution in the thermophilic hydrogen producer Caloramator celer as affected by external pH and hydrogen partial pressure

Background: Caloramator celer is a strict anaerobic, alkalitolerant, thermophilic bacterium capable of converting glucose to hydrogen (H2), carbon dioxide, acetate, ethanol and formate by a mixed acid fermentation. Depending on the growth conditions C. celer can produce H2 at high yields. For a biotechnological exploitation of this bacterium for H2 production it is crucial to understand the factors that regulate carbon and electron fluxes and therefore the final distribution of metabolites to channel the metabolic flux towards the desired product. Results: Combining experimental results from batch fermentations with genome analysis, reconstruction of central carbon metabolism and metabolic flux analysis (MFA), this study shed light on glucose catabolism of the thermophilic alkalitolerant bacterium C. celer. Two innate factors pertaining to culture conditions have been identified to significantly affect the metabolic flux distribution: culture pH and partial pressures of H2 (PH2). Overall, at alkaline to neutral pH the rate of biomass synthesis was maximized, whereas at acidic pH the lower growth rate and the less efficient biomass formation are accompanied with more efficient energy recovery from the substrate indicating high cell maintenance possibly to sustain intracellular pH homeostasis. Higher H2 yields were associated with fermentation at acidic pH as a consequence of the lower synthesis of other reduced by-products such as formate and ethanol. In contrast, PH2 did not affect the growth of C. celer on glucose. At high PH2 the cellular redox state was balanced by rerouting the flow of carbon and electrons to ethanol and formate production allowing unaltered glycolytic flux and growth rate, but resulting in a decreased H2 synthesis. Conclusion: C. celer possesses a flexible fermentative metabolism that allows redistribution of fluxes at key metabolic nodes to simultaneously control redox state and efficiently harvest energy from substrate even under unfavorable conditions (i.e. low pH and high PH2). With the H2 production in mind, acidic pH and low PH2 should be preferred for a high yield-oriented process, while a high productivity-oriented process can be achieved at alkaline pH and high PH2

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.publishedVersionPeer reviewe

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.Peer reviewe

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 CO2 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.Peer reviewe

Characterization of highly ferulate-tolerant Acinetobacter baylyi ADP1 isolates by a rapid reverse-engineering method

acceptedVersionPeer reviewe