Literature DB >> 15629852

Towards replacing closed with open target selection strategies.

Mariët J van der Werf1.   

Abstract

Increasingly, microbial production processes are being improved by targeted approaches. In directed strain improvement, the selection of the relevant targets is the limiting step in metabolic engineering. Currently, the identification of leads is still a random process relying largely on expert knowledge. Recently, this approach has been complemented by metabolic flux and control analysis approaches. However, both are closed approaches, and biological processes or interactions that are not currently known to exist, or to be important for bioproduct formation, are not taken into account. By contrast, the recently introduced functional genomics technologies enable an open approach towards target selection. In the near future, we might see that metabolomics, and its integration with transcriptomics and/or proteomics into a systems biology approach, in combination with multivariate data analysis tools, will become of increasing importance for the unbiased selection and ranking of targets, not only for strain improvement but also for bioprocess improvement.

Mesh:

Year:  2005        PMID: 15629852     DOI: 10.1016/j.tibtech.2004.11.003

Source DB:  PubMed          Journal:  Trends Biotechnol        ISSN: 0167-7799            Impact factor:   19.536


  7 in total

Review 1.  Microbial metabolomics: replacing trial-and-error by the unbiased selection and ranking of targets.

Authors:  Mariët J van der Werf; Renger H Jellema; Thomas Hankemeier
Journal:  J Ind Microbiol Biotechnol       Date:  2005-05-14       Impact factor: 3.346

2.  Centering, scaling, and transformations: improving the biological information content of metabolomics data.

Authors:  Robert A van den Berg; Huub C J Hoefsloot; Johan A Westerhuis; Age K Smilde; Mariët J van der Werf
Journal:  BMC Genomics       Date:  2006-06-08       Impact factor: 3.969

3.  Transcriptional monitoring of steady state and effects of anaerobic phases in chemostat cultures of the filamentous fungus Trichoderma reesei.

Authors:  Jari J Rautio; Bart A Smit; Marilyn Wiebe; Merja Penttilä; Markku Saloheimo
Journal:  BMC Genomics       Date:  2006-10-02       Impact factor: 3.969

4.  Standard reporting requirements for biological samples in metabolomics experiments: microbial and in vitro biology experiments.

Authors:  Mariët J van der Werf; Ralf Takors; Jørn Smedsgaard; Jens Nielsen; Tom Ferenci; Jean Charles Portais; Christoph Wittmann; Mark Hooks; Alberta Tomassini; Marco Oldiges; Jennifer Fostel; Uwe Sauer
Journal:  Metabolomics       Date:  2007-08-20       Impact factor: 4.290

5.  Effect of the storage atmosphere on metabolomics of harvested tomatoes (Solanum lycopersicum L.).

Authors:  Yuma Yokota; Takashi Akihiro; Surina Boerzhijin; Takeshi Yamada; Yoshio Makino
Journal:  Food Sci Nutr       Date:  2019-01-28       Impact factor: 2.863

Review 6.  Protein analysis-on-chip systems in foodomics.

Authors:  Filomena Nazzaro; Pierangelo Orlando; Florinda Fratianni; Aldo Di Luccia; Raffaele Coppola
Journal:  Nutrients       Date:  2012-10-16       Impact factor: 5.717

7.  Identification of biomarkers for genotyping Aspergilli using non-linear methods for clustering and classification.

Authors:  Irene Kouskoumvekaki; Zhiyong Yang; Svava O Jónsdóttir; Lisbeth Olsson; Gianni Panagiotou
Journal:  BMC Bioinformatics       Date:  2008-01-28       Impact factor: 3.169

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.