Special Issue "Dynamic Approaches to Metabolic Modeling and Metabolic Engineering"
A special issue of Processes (ISSN 2227-9717).
Deadline for manuscript submissions: 30 June 2014
Prof. Dr. Doraiswami Ramkrishna
Forney Hall of Chemical Engineering, 480 Stadium Mall Drive, Purdue University, West Lafayette, IN 47907, USA
Phone: +1 765 494 4066
Fax: +1 765 494 0805
Interests: metabolic modeling; metabolic engineering; particulate processes; population balances
Processes (ISSN 2227-9717), an international open access journal on processes in chemistry, biochemistry, biology, and related engineering research fields, is published by MDPI online quarterly. For more information, please refer to Processes' Aims and Scope at: http://www.mdpi.com/journal/processes/about. This Special Issue of Processes is expected to gather contributions in the general area of Dynamic Approaches to Metabolic Modeling and Metabolic Engineering.
Overall, this Special Issue is dedicated to applying mathematical models towards the translation of fundamental theory to design, optimize and control engineering systems. Specifically, it aims to promote the use of dynamic modeling from metabolic networks to metabolic engineering, then further to enable the design of organisms to maximize productivity.
While successful case studies will be of special interest, we also welcome papers that deliberate on the methodology, irrespective of whether the stipulated engineering goals have been reached successfully.
Prof. Dr. Doraiswami Ramkrishna
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed Open Access quarterly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. For the first couple of issues the Article Processing Charge (APC) will be waived for well-prepared manuscripts. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.
- metabolic networks
- metabolic Engineering
- genetic Engineering
- gene knockout
- gene insertion
- product yield and productivity
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Type of Paper: Article
Title: Unstructured Modeling of a Synthetic Microbial Consortium for Consolidated Production of Ethanol
Authors: Timothy J. Hanly and Michael A. Henson
Affiliation: Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003-3110, USA; E-Mail: email@example.com
Abstract: The conversion of lignocellulosic biomass to liquid fuels such as ethanol is required for the commercialization of second generation biofuels. Reducing operating costs by combining the saccharification and fermentation steps of this process into one reactor has long been a goal of biofuels research. A defined mixed culture of specialized microbes that exploits the native capabilities of each member species is a promising alternative to use an omnipotent, engineered microbe. We explored such a synthetic consortium that couples the high cellulolytic activity of the filamentous fungus Trichoderma reesei with the ability of the yeasts Saccharomyces cerevisiae and Pichia stipitis to ferment hexose and pentose sugars to ethanol. Consortium stability was demonstrated by culturing the three microbes on a mixture of cellulose and xylan. As a first step towards understanding and manipulating this consortium, we developed a simple dynamic model with unstructured descriptions of enzyme synthesis, cellulose and hemicellulose degradation, sugar uptake, cell growth, and ethanol production. The batch culture model contained 10 ordinary differential equations with parameters obtained from the literature and experiment to the extent possible. The dynamic model was used to predict initial concentration of each cell type that maximized ethanol productivity subject to a constraint on the total inoculum concentration. The simulated ratio of cellulose to hemicellulose in the feedstock was varied to determine the effects on the optimal inoculum and ethanol productivity. A sensitivity analysis of model parameters identified several promising experimental targets for improvement of ethanol production through metabolic engineering.
Type of Paper: Review
Title: Mathematical Modeling of Microbial Community Dynamics: Theory and Application
Authors: Hyun-Seob Song, William R. Cannon, Alexander S. Beliaev, Allan E. Konopka
Affiliation: Biological Sciences Division, Pacific Northwest National Laboratory, 902 Battelle Boulevard, Richland, WA 99352, USA; E-mail: firstname.lastname@example.org
Abstract: Microorganisms in nature form diverse communities that undergo dynamics in structure due both to the interactions between members and in response to external environmental changes. As a complex adaptive system, microbial communities exhibit properties that are uncaptured by characterizing individual microbes in isolation. Predictive mathematical models can be useful in understanding the dynamics of microbial communities. In this article, we give an overview of different potential modeling frameworks and particularly highlight multiscale approaches. We also briefly discuss how they have been applied in a wide range of settings. Therefore, this review may help to choose the most suitable framework that meets the key needs of modeling a microbial community.
Last update: 19 February 2014