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Title: A versatile 2A peptide-based bicistronic protein expressing platform for the industrial cellulase producing fungus, Trichoderma reesei

Abstract

Here, the industrial workhorse fungus, Trichoderma reesei, is typically exploited for its ability to produce cellulase enzymes, whereas use of this fungus for over-expression of other proteins (homologous and heterologous) is still very limited. Identifying transformants expressing target protein is a tedious task due to low transformation efficiency, combined with highly variable expression levels between transformants. Routine methods for identification include PCR-based analysis, western blotting, or crude activity screening, all of which are time-consuming techniques. To simplify this screening, we have adapted the 2A peptide system from the foot-and-mouth disease virus (FMDV) to T. reesei to express a readily screenable marker protein that is co-translated with a target protein. The 2A peptide sequence allows multiple independent genes to be transcribed as a single mRNA. Upon translation, the 2A peptide sequence causes a 'ribosomal skip' generating two (or more) independent gene products. When the 2A peptide is translated, the 'skip' occurs between its two C-terminal amino acids (glycine and proline), resulting in the addition of extra amino acids on the C terminus of the upstream protein and a single proline addition to the N terminus of the downstream protein. To test this approach, we have cloned two heterologous proteins on eithermore » side of a modified 2A peptide, a secreted cellobiohydrolase enzyme (Cel7A from Penicillium funiculosum) as our target protein, and an intracellular enhanced green fluorescent protein (eGFP) as our marker protein. Using straightforward monitoring of eGFP expression, we have shown that we can efficiently monitor the expression of the target Cel7A protein.« less

Authors:
ORCiD logo [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1];  [1]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Bioenergy Technologies Office (EE-3B)
OSTI Identifier:
1344327
Report Number(s):
NREL/JA-2700-67223
Journal ID: ISSN 1754-6834
Grant/Contract Number:
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Biotechnology for Biofuels
Additional Journal Information:
Journal Volume: 10; Journal Issue: 1; Journal ID: ISSN 1754-6834
Publisher:
BioMed Central
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; Trichoderma reesei; foot-and-mouth disease virus (FMDV) 2A peptide; protein expression; cellobiohydrolase; fungus; biomass hydrolysis; green fluorescence protein

Citation Formats

Subramanian, Venkataramanan, Schuster, Logan A., Moore, Kyle T., Taylor, II, Larry E., Baker, John O., Vander Wall, Todd A., Linger, Jeffrey G., Himmel, Michael E., and Decker, Stephen R.. A versatile 2A peptide-based bicistronic protein expressing platform for the industrial cellulase producing fungus, Trichoderma reesei. United States: N. p., 2017. Web. doi:10.1186/s13068-017-0710-7.
Subramanian, Venkataramanan, Schuster, Logan A., Moore, Kyle T., Taylor, II, Larry E., Baker, John O., Vander Wall, Todd A., Linger, Jeffrey G., Himmel, Michael E., & Decker, Stephen R.. A versatile 2A peptide-based bicistronic protein expressing platform for the industrial cellulase producing fungus, Trichoderma reesei. United States. doi:10.1186/s13068-017-0710-7.
Subramanian, Venkataramanan, Schuster, Logan A., Moore, Kyle T., Taylor, II, Larry E., Baker, John O., Vander Wall, Todd A., Linger, Jeffrey G., Himmel, Michael E., and Decker, Stephen R.. Mon . "A versatile 2A peptide-based bicistronic protein expressing platform for the industrial cellulase producing fungus, Trichoderma reesei". United States. doi:10.1186/s13068-017-0710-7. https://www.osti.gov/servlets/purl/1344327.
@article{osti_1344327,
title = {A versatile 2A peptide-based bicistronic protein expressing platform for the industrial cellulase producing fungus, Trichoderma reesei},
author = {Subramanian, Venkataramanan and Schuster, Logan A. and Moore, Kyle T. and Taylor, II, Larry E. and Baker, John O. and Vander Wall, Todd A. and Linger, Jeffrey G. and Himmel, Michael E. and Decker, Stephen R.},
abstractNote = {Here, the industrial workhorse fungus, Trichoderma reesei, is typically exploited for its ability to produce cellulase enzymes, whereas use of this fungus for over-expression of other proteins (homologous and heterologous) is still very limited. Identifying transformants expressing target protein is a tedious task due to low transformation efficiency, combined with highly variable expression levels between transformants. Routine methods for identification include PCR-based analysis, western blotting, or crude activity screening, all of which are time-consuming techniques. To simplify this screening, we have adapted the 2A peptide system from the foot-and-mouth disease virus (FMDV) to T. reesei to express a readily screenable marker protein that is co-translated with a target protein. The 2A peptide sequence allows multiple independent genes to be transcribed as a single mRNA. Upon translation, the 2A peptide sequence causes a 'ribosomal skip' generating two (or more) independent gene products. When the 2A peptide is translated, the 'skip' occurs between its two C-terminal amino acids (glycine and proline), resulting in the addition of extra amino acids on the C terminus of the upstream protein and a single proline addition to the N terminus of the downstream protein. To test this approach, we have cloned two heterologous proteins on either side of a modified 2A peptide, a secreted cellobiohydrolase enzyme (Cel7A from Penicillium funiculosum) as our target protein, and an intracellular enhanced green fluorescent protein (eGFP) as our marker protein. Using straightforward monitoring of eGFP expression, we have shown that we can efficiently monitor the expression of the target Cel7A protein.},
doi = {10.1186/s13068-017-0710-7},
journal = {Biotechnology for Biofuels},
number = 1,
volume = 10,
place = {United States},
year = {Mon Feb 06 00:00:00 EST 2017},
month = {Mon Feb 06 00:00:00 EST 2017}
}

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  • Trichoderma reesei (teleomorph Hypocrea jecorina) is the main industrial source of cellulases and hemicellulases harnessed for the hydrolysis of biomass to simple sugars, which can then be converted to biofuels, such as ethanol, and other chemicals. The highly productive strains in use today were generated by classical mutagenesis. To learn how cellulase production was improved by these techniques, we performed massively parallel sequencing to identify mutations in the genomes of two hyperproducing strains (NG14, and its direct improved descendant, RUT C30). We detected a surprisingly high number of mutagenic events: 223 single nucleotides variants, 15 small deletions or insertions andmore » 18 larger deletions leading to the loss of more than 100 kb of genomic DNA. From these events we report previously undocumented non-synonymous mutations in 43 genes that are mainly involved in nuclear transport, mRNA stability, transcription, secretion/vacuolar targeting, and metabolism. This homogeneity of functional categories suggests that multiple changes are necessary to improve cellulase production and not simply a few clear-cut mutagenic events. Phenotype microarrays show that some of these mutations result in strong changes in the carbon assimilation pattern of the two mutants with respect to the wild type strain QM6a. Our analysis provides the first genome-wide insights into the changes induced by classical mutagenesis in a filamentous fungus, and suggests new areas for the generation of enhanced T. reesei strains for industrial applications such as biofuel production.« less
  • The filamentous fungus Trichoderma parareesei is the asexually reproducing ancestor of Trichoderma reesei, the holomorphic industrial producer of cellulase and hemicellulase. Here, we present the genome sequence of the T. parareesei type strain CBS 125925, which contains genes for 9,318 proteins.
  • Steady and dynamic shear measurements are utilized to characterize the rheological behavior of Trichoderma reesei RUT-C30 fungal suspensions during batch growth on xylose (soluble substrate) or cellulose (particulate solid substrate) at three different fermentor impeller speeds (250, 400, and 550 rpm). Biomass concentrations versus time were unimodal on xylose and bimodal on cellulose. This behavior is consistent with relatively rapid, early growth on easily metabolized growth medium components (yeast extract), followed by a second, slower growth phase due to hydrolysis of recalcitrant cellulose by increasing cellulose concentrations. Critical dissolved oxygen (DO) concentration for T. reesei growth on cellulose was foundmore » to be 0.073 mmol/L. The DO was kept above this level by supplementing the air feed with pure oxygen, implying that mass transfer limitations were not the cause of bimodal cell growth. Steady shear rheological data showed shear thinning behavior and a yield stress for all broth samples regardless of substrate. Dynamic shear measurements on broth suspensions indicated `gel-like` behavior at low strains, with microstructural breakdown at larger displacements. Time variations of the Casson model parameters (yield stress and Casson viscosity) and dynamic moduli (elastic and viscous modulus) followed both cell mass and morphology. 45 refs., 14 figs.« less
  • The enzyme cellulase, a multienzyme complex made up of several proteins, catalyzes the conversion of cellulose to glucose in an enzymatic hydrolysis-based biomass-to-ethanol process. Production of cellulase enzyme proteins in large quantities using the fungus Trichoderma reesei requires understanding the dynamics of growth and enzyme production. The method of neural network parameter function modeling, which combines the approximation capabilities of neural networks with fundamental process knowledge, is utilized to develop a mathematical model of this dynamic system. In addition, kinetic models are also developed. Laboratory data from bench-scale fermentations involving growth and protein production by T. reesei on lactose andmore » xylose are used to estimate the parameters in these models. The relative performance of the various models and the results of optimizing these models on two different performance measures are presented. An approximately 33% lower root-mean-squared error (RMSE) in protein predictions and about 40% lower total RMSE is obtained with the neural network-based model, the RMSE in predicting optimal conditions for two performance indices, is about 67% and 40% lower, respectively, when compared with the kinetic models. Thus, both model predictions and optimization results from the neural network-based model are found to be closer to the experimental data than the kinetic models developed in this work. It is shown that the neural network parameter function modeling method can be useful as a macromodeling technique to rapidly develop dynamic models of a process.« less