Literature DB >> 22890866

Aspergilli: systems biology and industrial applications.

Christoph Knuf1, Jens Nielsen.   

Abstract

Aspergilli are widely used as cell factories for the production of food ingredients, enzymes and antibiotics. Traditionally, improvement of these cell factories has been done using classical methods, that is, random mutagenesis and screening; however, advances in methods for performing directed genetic modifications has enabled the use of metabolic engineering strategies. Genome sequencing of Aspergilli was originally trailing behind developments in the field of bacteria and yeasts, but with the recent availability of genome sequences for several industrially relevant Aspergilli, it has become possible to implement systems biology tools to advance metabolic engineering. These tools include genome-wide transcription analysis and genome-scale metabolic models. Herein, we review achievements in the field and highlight the impact of Aspergillus systems biology on industrial biotechnology.
Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2012        PMID: 22890866     DOI: 10.1002/biot.201200169

Source DB:  PubMed          Journal:  Biotechnol J        ISSN: 1860-6768            Impact factor:   4.677


  10 in total

1.  Flow cytometry of microencapsulated colonies for genetics analysis of filamentous fungi.

Authors:  Lidia Delgado-Ramos; Ana T Marcos; María S Ramos-Guelfo; Leyre Sánchez-Barrionuevo; Francis Smet; Sebastián Chávez; David Cánovas
Journal:  G3 (Bethesda)       Date:  2014-09-19       Impact factor: 3.154

Review 2.  Ecology of aspergillosis: insights into the pathogenic potency of Aspergillus fumigatus and some other Aspergillus species.

Authors:  Caroline Paulussen; John E Hallsworth; Sergio Álvarez-Pérez; William C Nierman; Philip G Hamill; David Blain; Hans Rediers; Bart Lievens
Journal:  Microb Biotechnol       Date:  2016-06-07       Impact factor: 5.813

3.  Redesigning the Aspergillus nidulans xylanase regulatory pathway to enhance cellulase production with xylose as the carbon and inducer source.

Authors:  Patrick Ballmann; Jorge Lightfoot; Michael Müller; Stephan Dröge; Rolf Prade
Journal:  Microb Cell Fact       Date:  2019-11-07       Impact factor: 5.328

4.  Gene Expression Analysis of Non-Clinical Strain of Aspergillus fumigatus (LMB-35Aa): Does Biofilm Affect Virulence?

Authors:  Teresa D Rebaza; Yvette Ludeña; Ilanit Samolski; Gretty K Villena
Journal:  J Fungi (Basel)       Date:  2020-12-18

5.  Integration of enzyme constraints in a genome-scale metabolic model of Aspergillus niger improves phenotype predictions.

Authors:  Jingru Zhou; Yingping Zhuang; Jianye Xia
Journal:  Microb Cell Fact       Date:  2021-06-30       Impact factor: 5.328

6.  Integrated isotope-assisted metabolomics and (13)C metabolic flux analysis reveals metabolic flux redistribution for high glucoamylase production by Aspergillus niger.

Authors:  Hongzhong Lu; Xiaoyun Liu; Mingzhi Huang; Jianye Xia; Ju Chu; Yingping Zhuang; Siliang Zhang; Henk Noorman
Journal:  Microb Cell Fact       Date:  2015-09-17       Impact factor: 5.328

7.  Genome-scale analysis of the high-efficient protein secretion system of Aspergillus oryzae.

Authors:  Lifang Liu; Amir Feizi; Tobias Österlund; Carsten Hjort; Jens Nielsen
Journal:  BMC Syst Biol       Date:  2014-06-24

Review 8.  From Discovery to Production: Biotechnology of Marine Fungi for the Production of New Antibiotics.

Authors:  Johanna Silber; Annemarie Kramer; Antje Labes; Deniz Tasdemir
Journal:  Mar Drugs       Date:  2016-07-21       Impact factor: 5.118

9.  Multi-omics integrative analysis with genome-scale metabolic model simulation reveals global cellular adaptation of Aspergillus niger under industrial enzyme production condition.

Authors:  Hongzhong Lu; Weiqiang Cao; Xiaoyun Liu; Yufei Sui; Liming Ouyang; Jianye Xia; Mingzhi Huang; Yingping Zhuang; Siliang Zhang; Henk Noorman; Ju Chu
Journal:  Sci Rep       Date:  2018-09-26       Impact factor: 4.379

10.  An accurate description of Aspergillus niger organic acid batch fermentation through dynamic metabolic modelling.

Authors:  Daniel J Upton; Simon J McQueen-Mason; A Jamie Wood
Journal:  Biotechnol Biofuels       Date:  2017-11-09       Impact factor: 6.040

  10 in total

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