BIOE 402. Medical Technology Assessment. 2 or 3 hours. Bioentrepreneur course. Assessment of medical technology in the context of commercialization. Objectives, competition, market share, funding, pricing, manufacturing, growth, and intellectual property; many issues unique to biomedical products. Course Information: 2 undergraduate hours. 3 graduate hours. Prerequisite(s): Junior standing or above and consent of the instructor.

“Bioinformatics” 특집을 내면서

KEGG(Kyoto Encyclopedia of Genes and Genomes)〔和文〕 (特集 ゲノム医学の現在と未来--基礎と臨床) -- (データベース)

An essential prerequisite for any systems-level understanding of cellular functions is to correctly uncover and annotate all functional interactions among proteins in the cell. Toward this goal, remarkable progress has been made in recent years, both in terms of experimental measurements and computational prediction techniques. However, public efforts to collect and present protein interaction information have struggled to keep up with the pace of interaction discovery, partly because protein-protein interaction information can be error-prone and require considerable effort to annotate. Here, we present an update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING); it provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information. Interactions in STRING are provided with a confidence score, and accessory information such as protein domains and 3D structures is made available, all within a stable and consistent identifier space. New features in STRING include an interactive network viewer that can cluster networks on demand, updated on-screen previews of structural information including homology models, extensive data updates and strongly improved connectivity and integration with third-party resources. Version 9.0 of STRING covers more than 1100 completely sequenced organisms; the resource can be reached at http://string-db.org.

https://www.zora.uzh.ch/id/eprint/41629/4/21045058_V.pdf

The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored

Flux balance analysis is a mathematical approach for analyzing the flow of metabolites through a metabolic network. This primer covers the theoretical basis of the approach, several practical examples and a software toolbox for performing the calculations.

/pdf/what-is-flux-balance-analysis-4wuuwjci7s.pdf

What is flux balance analysis

Motivation: Simulation and modeling is becoming a standard approach to understand complex biochemical processes. Therefore, there is a big need for software tools that allow access to diverse simulation and modeling methods as well as support for the usage of these methods.

Results: Here, we present COPASI, a platform-independent and user-friendly biochemical simulator that offers several unique features. We discuss numerical issues with these features; in particular, the criteria to switch between stochastic and deterministic simulation methods, hybrid deterministic--stochastic methods, and the importance of random number generator numerical resolution in stochastic simulation.

Availability: The complete software is available in binary (executable) for MS Windows, OS X, Linux (Intel) and Sun Solaris (SPARC), as well as the full source code under an open source license from http://www.copasi.org.

Contact: mendes@vbi.vt.edu

/pdf/copasi-a-complex-pathway-simulator-320i5gmr5f.pdf

COPASI---a COmplex PAthway SImulator

Model-based monitoring and control of biotechnological processes

Some of the most challenging tasks of our times are to combat global warming, to avoid further contamination of the environment with plastics, and to provide enough food for an increasing world population. A promising contribution to these overwhelming problems can be made by modern biotechnology. Here, we present the concept of a modular co-culture in which the feedstock is produced from CO2 and light by a cyanobacterium and converted directly to bioplastic (PHA) by a heterotrophic strain.

Bioplastik aus Licht und Luft – das Konzept einer synthetischen Ko-Kultur

The T7 RNA polymerase is considered one of the most popular tools for heterologous gene expression in the gold standard biotechnological host Escherichia coli. However, the exploitation of this tool in other prospective hosts, such as the biotechnologically relevant bacterium Pseudomonas putida, is still very scarce. The majority of the existing T7-based systems in P. putida show low expression strengths and possess only weak controllability. A fundamental understanding of these systems is necessary in order to design robust and predictable biotechnological processes. To fill this gap, we established and characterized a modular T7 RNA polymerase-based system for heterologous protein production in P. putida, using the enhanced Green Fluorescent Protein (eGFP) as an easy-to-quantify reporter protein. We have effectively targeted the limitations associated with the initial genetic setup of the system, such as slow growth and low protein production rates. By replacing the T7 phage-inherent TΦ terminator downstream of the heterologous gene with the synthetic tZ terminator, growth and protein production rates improved drastically, and the T7 RNA polymerase system reached a productivity level comparable to that of an intrinsic RNA polymerase-based system. Furthermore, we were able to show that the system was saturated with T7 RNA polymerase by applying a T7 RNA polymerase ribosome binding site library to tune heterologous protein production. This saturation indicates an essential role for the ribosome binding sites of the T7 RNA polymerase since, in an oversaturated system, cellular resources are lost to the synthesis of unnecessary T7 RNA polymerase. Eventually, we combined the experimental data into a model that can predict the eGFP production rate with respect to the relative strength of the ribosome binding sites upstream of the T7 gene.

Targeting Transcriptional and Translational Hindrances in a Modular T7RNAP Expression System in Engineered Pseudomonas putida.

Modulare Strukturierung und Modellierung von Signaltransduktionssystemen

Metabolism and signalling are tightly coupled in bacteria. Combining several theoretical approaches, a core model is presented that describes transcriptional and allosteric control of glycolysis in Escherichia coli. Experimental data based on microarrays, signalling components and extracellular metabolites are used to estimate kinetic parameters. A newly designed strain was used that adjusts the incoming glucose flux into the system and allows a kinetic analysis. Based on the results, prediction for intracelluar metabolite concentrations over a broad range of the growth rate could be performed and compared with data from literature.

https://www.mdpi.com/2218-1989/2/4/844/pdf

Andreas Kremling

Papers

Model-based monitoring and control of biotechnological processes

Bioplastik aus Licht und Luft – das Konzept einer synthetischen Ko-Kultur

Targeting Transcriptional and Translational Hindrances in a Modular T7RNAP Expression System in Engineered Pseudomonas putida.

Modulare Strukturierung und Modellierung von Signaltransduktionssystemen

Analysis and Design of Stimulus Response Curves of E. coli