14
views
0
recommends
+1 Recommend
1 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found

      Optimization of critical medium components for enhancing antibacterial thiopeptide nocathiacin I production with significantly improved quality

      Read this article at

      ScienceOpenPublisher
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Nocathiacin I, a glycosylated thiopeptide antibiotic, displays excellent antibacterial activities against multidrug resistant bacterial pathogens. Previously, a novel nocathiacin I formulation for intravenous administration has been successfully developed and its aqueous solubility is greatly enhanced for clinical application. The purpose of the present study was to increase the fermentation titer of nocathiacin I and reduce or eliminate analogous impurities by screening the medium ingredients using response surface methodology. After a sysmatic optimization, a water-soluble medium containing quality-controllable components was developed and validated, resulting in an increase in the production of nocathiacin I from 150 to 405.8 mg·L –1 at 150-L scale. Meanwhile, the analogous impurities existed in reported processes were greatly reduced or eliminated. Using optimized medium for fermentation, nocathiacin I with pharmaceutically acceptable quality was easily obtained with a recovery of 67%. In conclusion, the results from the present study offer a practical and efficient fermentation process for the production of nocathiacin I as a therapeutic agent.

          Related collections

          Most cited references 20

          • Record: found
          • Abstract: found
          • Article: not found

          Optimization of alkaline protease production by batch culture of Bacillus sp. RKY3 through Plackett-Burman and response surface methodological approaches.

          The proteolytic enzymes are the most important group of commercially produced enzymes. The production of alkaline protease was optimized using a newly isolated Bacillus sp. RKY3. The fermentation variables were selected in accordance with the Plackett-Burman design and were further optimized via response surface methodological approach. Four significant variables (corn starch, yeast extract, corn steep liquor, and inoculum size) were selected for the optimization studies. The statistical model was constructed via central composite design (CCD) using three screened variables (corn starch, corn steep liquor, and inoculum size). An overall 2.3-fold increase in protease production was achieved in the optimized medium as compared with the unoptimized basal medium. Enzyme activity increased significantly with optimized medium (939 u ml(-1)) when compared with unoptimized medium (417 u ml(-1)).
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Application of response surface methodology and artificial neural network methods in modelling and optimization of biosorption process.

            A review on the application of response surface methodology (RSM) and artificial neural networks (ANN) in biosorption modelling and optimization is presented. The theoretical background of the discussed methods with the application procedure is explained. The paper describes most frequently used experimental designs, concerning their limitations and typical applications. The paper also presents ways to determine the accuracy and the significance of model fitting for both methodologies described herein. Furthermore, recent references on biosorption modelling and optimization with the use of RSM and the ANN approach are shown. Special attention was paid to the selection of factors and responses, as well as to statistical analysis of the modelling results. Copyright © 2014 Elsevier Ltd. All rights reserved.
              Bookmark
              • Record: found
              • Abstract: not found
              • Article: not found

              Strategies for improving fermentation medium performance: a review

                Bookmark

                Author and article information

                Journal
                CJNM
                Chinese Journal of Natural Medicines
                Elsevier
                1875-5364
                20 April 2017
                : 15
                : 4
                : 292-300
                Affiliations
                1State Key Laboratory of Natural Medicines and Laboratory of Chemical Biology, China Pharmaceutical University, Nanjing 210009, China
                Author notes
                *Corresponding author: CHEN Yi-Jun, Tel: 86-25-83271045, Fax: 86-25-83271031, E-mail: yjchen@ 123456cpu.edu.cn ; WU Xu-Ri, xuriwu@ 123456cpu.edu.cn

                These authors have no conflicts of interest to declare.

                Article
                S1875-5364(17)30047-X
                10.1016/S1875-5364(17)30047-X
                Copyright © 2017 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.
                Funding
                Funded by: National Science Foundation of China
                Award ID: 81502961
                Funded by: National Key Project of Science and Technology
                Award ID: 2012ZX09103- 101-030
                Funded by: “333” Project of Jiangsu Province
                Award ID: BRA2015321
                Funded by: Priority Academic Program Development of Jiangsu Higher Education Institutions and the Project of University Collaborative Innovation Center of Jiangsu Province (Biological Medicine Center).
                This work was supported by National Science Foundation of China (No. 81502961), National Key Project of Science and Technology (No. 2012ZX09103- 101-030), the “333” Project of Jiangsu Province (No. BRA2015321), the Priority Academic Program Development of Jiangsu Higher Education Institutions and the Project of University Collaborative Innovation Center of Jiangsu Province (Biological Medicine Center).

                Comments

                Comment on this article