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Zhao L.,University of Minnesota | Fu H.-Y.,University of Minnesota | Zhou W.,Biologics Process Development | Hu W.-S.,University of Minnesota
Engineering in Life Sciences | Year: 2015

The productivity of cell culture manufacturing for biologics has increased momentously in the past decades. Increasingly, the process research efforts are devoted into improving product quality and consistency. Consistent process performance and successful implementation of quality by design practice requires well-utilized process analytical technology. This review summarizes recent progress and current status of bioprocess monitoring. Many sensors for bioprocess monitoring have been available for decades while new ones, especially spectrometric sensors, are making their way into cell culture bioprocesses. On-line sampling devices have grown mature in the past decade thus making many instruments traditionally used for off-line analysis available for at-line use. With a general trend of using better defined medium for cell cultivation and increasing emphasis of process analytical tools, the spectrometric methods are also making headway in cell culture process monitoring. The integration of those sensing technologies will be important to advance the real-time monitoring of the state of cellular physiology for the control for process consistency and product quality. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source


Nakazawa T.,University of Shizuoka | Ishiuchi K.,University of Shizuoka | Praseuth A.,Biologics Process Development | Noguchi H.,University of Shizuoka | And 2 more authors.
ChemBioChem | Year: 2012

Fungal genomes carry many gene clusters seemingly capable of natural product biosynthesis, yet most clusters remain silent. This places a major constraint on the conventional approach of cloning these genes in more amenable heterologous host for the natural product biosynthesis. One way to overcome this difficulty is to activate the silent gene clusters within the context of the target fungus. Here, we successfully activated a silent polyketide biosynthetic gene cluster in Aspergillus oryzae by overexpressing a transcriptional regulator found within the cluster from a plasmid. This strategy allowed us to isolate a new polyketide product and to efficiently decipher its biosynthetic pathway. Through this exercise, we also discovered unexpected activities of the biosynthetic enzymes found in the cluster. These results indicate that our approach would be valuable for isolating novel natural products and engineering analogues of comparable, if not more potent, bioactivity. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source


Villiger-Oberbek A.,Genzyme | Yang Y.,Genzyme | Zhou W.,Genzyme | Zhou W.,Biologics Process Development | And 2 more authors.
Journal of Biotechnology | Year: 2015

A high-throughput (HT) cell culture model has been established for the support of perfusion-based cell culture processes operating at high cell densities. To mimic perfusion, the developed platform takes advantage of shake tubes and operates them in a batch-refeed mode with daily medium exchange to supply the cultures with nutrients and remove toxic byproducts. By adjusting the shaking parameters, such as the speed and setting angle, we have adapted the shake tubes to a semi-continuous production of a recombinant enzyme in a perfusion-like mode. We have demonstrated that the developed model can be used to select clones and cell culture media ahead of process optimization studies in bioreactors and confirmed the applicability of shake tubes to a perfusion-like cell culture reaching ~50E6 viable cells/mL. Furthermore, through regular cell mass removal and periodic medium exchange we have successfully maintained satellite cultures of bench-top perfusion bioreactors, achieving a sustainable cell culture performance at ≥30E6 viable cells/mL and viabilities >80% for over 58 days. The established HT model is a unique and powerful tool that can be used for the development and screening of media formulations, or for testing selected process parameters during both process optimization and manufacturing support campaigns. © 2015 Elsevier B.V. Source


Otero J.M.,Chalmers University of Technology | Otero J.M.,Technical University of Denmark | Otero J.M.,Biologics Process Development | Cimini D.,The Second University of Naples | And 7 more authors.
PLoS ONE | Year: 2013

Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the α-keto-glutarate dehydrogenase catalyzed conversion of α-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2nd-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals. © 2013 Otero et al. Source


Agren R.,Chalmers University of Technology | Otero J.M.,Chalmers University of Technology | Otero J.M.,Biologics Process Development | Nielsen J.,Chalmers University of Technology
Journal of Industrial Microbiology and Biotechnology | Year: 2013

In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δmdh1, Δoac1, and Δdic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δmdh1 and Δoac1 strains failed to produce succinate, Δdic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies. © 2013 Society for Industrial Microbiology and Biotechnology. Source

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