View graph of relations

Actinomycetes are widely known for production of antibiotics, though as hosts for heterologous protein expression they show great potential which should be further developed. Streptomyces lividans is especially interesting due to very low endogenous protease activity and the capability to secrete proteins to the medium. As saprophyte it also has the ability to use a very diverse range of substrates including cellulose. Furthermore, a growing array of genetic tools has been developed, while sequencing and annotation is still to follow in the near future as various initiatives are in progress.
Medium composition can have great effect on the cellular performance, in particular on heterologous protein production. It is a parameter that can be adjusted regardless of GMO concerns or knowledge of genomic sequence. Optimizing medium composition can be labor intensive opening up for introducing automation. In this study a potential high throughput method was tested for optimizing medium composition, with respect to nitrogen, to improve heterologous protein production in S. lividans, using mRFP as a model protein. A large number of nitrogen sources were tested in an initial, highly automated, screen. Subsequently the most promising candidates were tested in milliliter scale, followed by final verification in lab-scale fermentation. The method has the great advantage that the initial steps have a high degree of automation, which allows to retain a relatively high number of candidates. A further benefit of this approach is that substantial physiological knowledge is gained from the unsequenced model producer.
Original languageEnglish
JournalNew Biotechnology
Pages (from-to)S50
StatePublished - 2012
Event15th European Congress on Biotechnology - Istanbul, Turkey


Conference15th European Congress on Biotechnology
LocationThe Grand Cevahir Hotel & Convention Center

Bibliographical note

Poster 1.2.07

CitationsWeb of Science® Times Cited: 0
Download as:
Download as PDF
Select render style:
Download as HTML
Select render style:
Download as Word
Select render style:

Download statistics

No data available

ID: 12074037