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Evolutionary adaptation of Aspergillus niger for increased ferulic acid tolerance.

Author(s): Lubbers RJM, Liwanag AJ, Peng M, Dilokpimol A, Benoit-Gelber I, de Vries RP

J Appl Microbiol. 2019 Nov 01;: Authors: Lubbers RJM, Liwanag AJ, Peng M, Dilokpimol A, Benoit-Gelber I, de Vries RP

Article GUID: 31674709
Secretion of small proteins is species-specific within Aspergillus sp.

Author(s): Valette N, Benoit-Gelber I, Falco MD, Wiebenga A, de Vries RP, Gelhaye E, Morel-Rouhier M

Microb Biotechnol. 2017 03;10(2):323-329 Authors: Valette N, Benoit-Gelber I, Falco MD, Wiebenga A, de Vries RP, Gelhaye E, Morel-Rouhier M

Article GUID: 27153937
Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

Author(s): Gruben BS, Mäkelä MR, Kowalczyk JE, Zhou M, Benoit-Gelber I, De Vries RP

BMC Genomics. 2017 Nov 23;18(1):900 Authors: Gruben BS, Mäkelä MR, Kowalczyk JE, Zhou M, Benoit-Gelber I, De Vries RP

Article GUID: 29169319
Evolutionary Adaptation to Generate Mutants.

Author(s): de Vries RP, Lubbers R, Patyshakuliyeva A, Wiebenga A, Benoit-Gelber I

Methods Mol Biol. 2018;1775:133-137 Authors: de Vries RP, Lubbers R, Patyshakuliyeva A, Wiebenga A, Benoit-Gelber I

Article GUID: 29876815
The presence of trace components significantly broadens the molecular response of Aspergillus niger to guar gum.

Author(s): Coconi Linares N, Di Falco M, Benoit-Gelber I, Gruben BS, Peng M, Tsang A, Mäkelä MR, de Vries RP

N Biotechnol. 2019 Jul 25;51:57-66 Authors: Coconi Linares N, Di Falco M, Benoit-Gelber I, Gruben BS, Peng M, Tsang A, Mäkelä MR, de Vries RP

Article GUID: 30797054
Title:Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.
Authors:Gruben BS,  Mäkelä MR,  Kowalczyk JE,  Zhou M,  Benoit-Gelber I,  De Vries RP
Link:https://www.ncbi.nlm.nih.gov/pubmed/29169319?dopt=Abstract
DOI:10.1186/s12864-017-4164-x
Category:BMC Genomics
PMID:29169319
Dept Affiliation: GENOMICS
1 Fungal Physiology, Westerdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands.
2 Microbiology, Utrecht University, Padualaan 8, 3584, CH, Utrecht, The Netherlands.
3 Fungal Molecular Physiology, Utrecht University, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands.
4 Department of Food and Environmental Sciences, Division of Microbiology and Biotechnology, Viikki Biocenter 1, University of Helsinki, Helsinki, Finland.
5 Current affiliation: ATGM, Avans University of Applied Sciences, Lovensdijkstraat 61-63, 4818, AJ, Breda, The Netherlands.
6 Current affiliation: Center for Structural and Functional Genomics, Concordia University, 7141 Sherbrooke St. W, Montreal, QC, Canada.
7 Fungal Physiology, Westerdijk Fungal Biodiversity Institute, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands. r.devries@westerdijkinstitute.nl.
8 Microbiology, Utrecht University, Padualaan 8, 3584, CH, Utrecht, The Netherlands. r.devries@westerdijkinstitute.nl.
9 Fungal Molecular Physiology, Utrecht University, Uppsalalaan 8, 3584, CT, Utrecht, The Netherlands. r.devries@westerdijkinstitute.nl.

Description:

Expression-based clustering of CAZyme-encoding genes of Aspergillus niger.

BMC Genomics. 2017 Nov 23;18(1):900

Authors: Gruben BS, Mäkelä MR, Kowalczyk JE, Zhou M, Benoit-Gelber I, De Vries RP

Abstract

BACKGROUND: The Aspergillus niger genome contains a large repertoire of genes encoding carbohydrate active enzymes (CAZymes) that are targeted to plant polysaccharide degradation enabling A. niger to grow on a wide range of plant biomass substrates. Which genes need to be activated in certain environmental conditions depends on the composition of the available substrate. Previous studies have demonstrated the involvement of a number of transcriptional regulators in plant biomass degradation and have identified sets of target genes for each regulator. In this study, a broad transcriptional analysis was performed of the A. niger genes encoding (putative) plant polysaccharide degrading enzymes. Microarray data focusing on the initial response of A. niger to the presence of plant biomass related carbon sources were analyzed of a wild-type strain N402 that was grown on a large range of carbon sources and of the regulatory mutant strains ?xlnR, ?araR, ?amyR, ?rhaR and ?galX that were grown on their specific inducing compounds.

RESULTS: The cluster analysis of the expression data revealed several groups of co-regulated genes, which goes beyond the traditionally described co-regulated gene sets. Additional putative target genes of the selected regulators were identified, based on their expression profile. Notably, in several cases the expression profile puts questions on the function assignment of uncharacterized genes that was based on homology searches, highlighting the need for more extensive biochemical studies into the substrate specificity of enzymes encoded by these non-characterized genes. The data also revealed sets of genes that were upregulated in the regulatory mutants, suggesting interaction between the regulatory systems and a therefore even more complex overall regulatory network than has been reported so far.

CONCLUSIONS: Expression profiling on a large number of substrates provides better insight in the complex regulatory systems that drive the conversion of plant biomass by fungi. In addition, the data provides additional evidence in favor of and against the similarity-based functions assigned to uncharacterized genes.

PMID: 29169319 [PubMed - indexed for MEDLINE]