Biocatalytic Reaction And Recycling by Using CO2-Induced Organic–Aqueous Tunable Solvents

2006 ◽  
Vol 118 (28) ◽  
pp. 4786-4789 ◽  
Author(s):  
James M. Broering ◽  
Elizabeth M. Hill ◽  
Jason P. Hallett ◽  
Charles L. Liotta ◽  
Charles A. Eckert ◽  
...  
2006 ◽  
Vol 45 (28) ◽  
pp. 4670-4673 ◽  
Author(s):  
James M. Broering ◽  
Elizabeth M. Hill ◽  
Jason P. Hallett ◽  
Charles L. Liotta ◽  
Charles A. Eckert ◽  
...  

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Tai Man Louie ◽  
Kailin Louie ◽  
Samuel DenHartog ◽  
Sridhar Gopishetty ◽  
Mani Subramanian ◽  
...  

Abstract Background Xylitol is a five-carbon sugar alcohol that has numerous beneficial health properties. It has almost the same sweetness as sucrose but has lower energy value compared to the sucrose. Metabolism of xylitol is insulin independent and thus it is an ideal sweetener for diabetics. It is widely used in food products, oral and personal care, and animal nutrition as well. Here we present a two-stage strategy to produce bio-xylitol from d-xylose using a recombinant Pichia pastoris expressing a heterologous xylose reductase gene. The recombinant P. pastoris cells were first generated by a low-cost, standard procedure. The cells were then used as a catalyst to make the bio-xylitol from d-xylose. Results Pichia pastoris expressing XYL1 from P. stipitis and gdh from B. subtilis demonstrated that the biotransformation was very efficient with as high as 80% (w/w) conversion within two hours. The whole cells could be re-used for multiple rounds of catalysis without loss of activity. Also, the cells could directly transform d-xylose in a non-detoxified hemicelluloses hydrolysate to xylitol at 70% (w/w) yield. Conclusions We demonstrated here that the recombinant P. pastoris expressing xylose reductase could transform d-xylose, either in pure form or in crude hemicelluloses hydrolysate, to bio-xylitol very efficiently. This biocatalytic reaction happened without the external addition of any NAD(P)H, NAD(P)+, and auxiliary substrate as an electron donor. Our experimental design & findings reported here are not limited to the conversion of d-xylose to xylitol only but can be used with other many oxidoreductase reactions also, such as ketone reductases/alcohol dehydrogenases and amino acid dehydrogenases, which are widely used for the synthesis of high-value chemicals and pharmaceutical intermediates.


1987 ◽  
Vol 506 (1 Biochemical E) ◽  
pp. 345-356 ◽  
Author(s):  
M. VASUDEVAN ◽  
T. MATSUURA ◽  
G. K. CHOTANI ◽  
W. R. VIETH

ChemCatChem ◽  
2019 ◽  
Vol 11 (23) ◽  
pp. 5788-5793 ◽  
Author(s):  
Niklas Adebar ◽  
Ji Eun Choi ◽  
Lukas Schober ◽  
Ryoma Miyake ◽  
Takanobu Iura ◽  
...  

Author(s):  
Sarah Abou-Shehada ◽  
James H. Clark ◽  
Giulia Paggiola ◽  
James Sherwood
Keyword(s):  

Processes ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 190
Author(s):  
Moritz Schulze ◽  
René Schenkendorf

Considering the competitive and strongly regulated pharmaceutical industry, mathematical modeling and process systems engineering might be useful tools for implementing quality by design (QbD) and quality by control (QbC) strategies for low-cost but high-quality drugs. However, a crucial task in modeling (bio)pharmaceutical manufacturing processes is the reliable identification of model candidates from a set of various model hypotheses. To identify the best experimental design suitable for a reliable model selection and system identification is challenging for nonlinear (bio)pharmaceutical process models in general. This paper is the first to exploit differential flatness for model selection problems under uncertainty, and thus translates the model selection problem to advanced concepts of systems theory and controllability aspects, respectively. Here, the optimal controls for improved model selection trajectories are expressed analytically with low computational costs. We further demonstrate the impact of parameter uncertainties on the differential flatness-based method and provide an effective robustification strategy with the point estimate method for uncertainty quantification. In a simulation study, we consider a biocatalytic reaction step simulating the carboligation of aldehydes, where we successfully derive optimal controls for improved model selection trajectories under uncertainty.


2013 ◽  
Vol 97 ◽  
pp. 203-208 ◽  
Author(s):  
Andrea Martorana ◽  
Lorenzo Sorace ◽  
Harry Boer ◽  
Rafael Vazquez-Duhalt ◽  
Riccardo Basosi ◽  
...  

2012 ◽  
Vol 18 (25) ◽  
pp. 7842-7851 ◽  
Author(s):  
Liuyi Li ◽  
Jinyun Wang ◽  
Tao Wu ◽  
Ruihu Wang

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