tailieunhanh - Báo cáo y học: " Systemic analysis of the response of Aspergillus niger to ambient pH"

Tuyển tập các báo cáo nghiên cứu về y học được đăng trên tạp chí y học Minireview cung cấp cho các bạn kiến thức về ngành y đề tài: Systemic analysis of the response of Aspergillus niger to ambient pH | Open Access Researc h Systemic analysis of the response of Aspergillus niger to ambient pH Mikael R Andersen Linda Lehmann and Jens Nielsen Addresses Center for Microbial Biotechnology Department of Systems Biology Technical University of Denmark DK-2800 Kgs. Lyngby Denmark. Current address Department of Chemical and Biological Engineering Chalmers University of Technology SE-412 96 Gothenburg Sweden. H These authors contributed equally to this work. Correspondence Jens Nielsen. Email nielsenj@ Published I May 2009 Received 12 February 2009 Genome Biology 2009 I0 R47 doi gb-2009- 10-5-r47 Accepted 1 May 2009 The electronic version of this article is the complete one and can be found online at http 2009 10 5 R47 2009 Keilwagen et al. licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License http licenses by which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Abstract Background The filamentous fungus Aspergillus niger is an exceptionally efficient producer of organic acids which is one of the reasons for its relevance to industrial processes and commercial importance. While it is known that the mechanisms regulating this production are tied to the levels of ambient pH the reasons and mechanisms for this are poorly understood. Methods To cast light on the connection between extracellular pH and acid production we integrate results from two genome-based strategies A novel method of genome-scale modeling of the response and transcriptome analysis across three levels of pH. Results With genome scale modeling with an optimization for extracellular proton-production it was possible to reproduce the preferred pH levels for citrate and oxalate. Transcriptome analysis and clustering expanded upon these results and allowed the identification of 162 clusters with distinct .