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Exploring Sequence Characteristics Related to High- Level Production of Secreted Proteins in Aspergillus niger

Author: Van den Berg, B.A. · Reinders, M.J.T. · Hulsman, M. · Wu, L. · Pel, H.J. · Roubos, J.A. · De Ridder, D.
Faculty:Electrical Engineering, Mathematics and Computer Science
Department:Computer Science & Engineering
Type:Article/Letter to the Editor
Publisher: Public Library of Science
Source:PLoS ONE, 7 (10), 2012
Identifier: doi:10.1371/journal.pone.0045869
ISSN: 1932-6203
Keywords: OA-Fund TU Delft
Rights: (c) 2012 The Author(s) · This is an open-access article distributed under the terms of the Creative Commons Attribution License


Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large set, over 600 homologous and nearly 2,000 heterologous fungal genes, were overexpressed in Aspergillus niger using a standardized expression cassette and scored for high versus no production. Subsequently, sequence-based machine learning techniques were applied for identifying relevant DNA and protein sequence features. The amino-acid composition of the protein sequence was found to be most predictive and interpretation revealed that, for both homologous and heterologous gene expression, the same features are important: tyrosine and asparagine composition was found to have a positive correlation with high-level production, whereas for unsuccessful production, contributions were found for methionine and lysine composition. The predictor is available online at http://bioinformatics.tudelft.nl/hipsec. Subsequent work aims at validating these findings by protein engineering as a method for increasing expression levels per gene copy.

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