Abstract

BackgroundThe development of biological processes that replace the existing petrochemical-based industry is one of the biggest challenges in biotechnology. Aspergillus niger is one of the main industrial producers of lignocellulolytic enzymes, which are used in the conversion of lignocellulosic feedstocks into fermentable sugars. Both the hydrolytic enzymes responsible for lignocellulose depolymerisation and the molecular mechanisms controlling their expression have been well described, but little is known about the transport systems for sugar uptake in A. niger. Understanding the transportome of A. niger is essential to achieve further improvements at strain and process design level. Therefore, this study aims to identify and classify A. niger sugar transporters, using newly developed tools for in silico and in vivo analysis of its membrane-associated proteome.ResultsIn the present research work, a hidden Markov model (HMM), that shows a good performance in the identification and segmentation of functionally validated glucose transporters, was constructed. The model (HMMgluT) was used to analyse the A. niger membrane-associated proteome response to high and low glucose concentrations at a low pH. By combining the abundance patterns of the proteins found in the A. niger plasmalemma proteome with their HMMgluT scores, two new putative high-affinity glucose transporters, denoted MstG and MstH, were identified. MstG and MstH were functionally validated and biochemically characterised by heterologous expression in a S. cerevisiae glucose transport null mutant. They were shown to be a high-affinity glucose transporter (Km = 0.5 ± 0.04 mM) and a very high-affinity glucose transporter (Km = 0.06 ± 0.005 mM), respectively.ConclusionsThis study, focusing for the first time on the membrane-associated proteome of the industrially relevant organism A. niger, shows the global response of the transportome to the availability of different glucose concentrations. Analysis of the A. niger transportome with the newly developed HMMgluT showed to be an efficient approach for the identification and classification of new glucose transporters.Electronic supplementary materialThe online version of this article (doi:10.1186/s13068-015-0317-9) contains supplementary material, which is available to authorized users.

Highlights

  • The development of biological processes that replace the existing petrochemical-based industry is one of the biggest challenges in biotechnology

  • In silico transportome analysis and construction of a hidden Markov model specific for glucose transporters As an integral part of the membrane, transporters must contain at least one protein domain that is thermodynamically stable in the hydrophobic environment of the phospholipid tails

  • A comprehensive list of A. niger sugar transporters can be made by applying hidden Markov models for both the major facilitator superfamily (HMMMFS), and sugar porters (HMMSP)

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Summary

Introduction

The development of biological processes that replace the existing petrochemical-based industry is one of the biggest challenges in biotechnology. Aspergillus niger is one of the main industrial producers of lignocellulolytic enzymes, which are used in the conversion of lignocellulosic feedstocks into fermentable sugars. A. niger is of significant industrial relevance and has been exploited as a production platform for both organic acids and hydrolytic enzymes [1]. It is an efficient degrader of the major plant cell wall polysaccharides cellulose, hemicellulose and pectin [2], and is one of the main industrial producers of commercial enzymes for plant biomass conversion due to its high enzyme secretory capacity [3].

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