Title: Insights into cellulase-lignin non-specific binding revealed by computational redesign of the surface of green fluorescent protein

Abstract

Biological-mediated conversion of pretreated lignocellulosic biomass to biofuels and biochemicals is a promising avenue towards energy sustainability. However, a critical impediment to the commercialization of cellulosic biofuel production is the high cost of cellulase enzymes needed to deconstruct biomass into fermentable sugars. One major factor driving cost is cellulase adsorption and inactivation in the presence of lignin, yet we currently have a poor understanding of the protein structure-function relationships driving this adsorption. In this work, we have systematically investigated the role of protein surface potential on lignin adsorption using a model monomeric fluorescent protein. We have designed and experimentally characterized 16 model protein variants spanning the physiological range of net charge (-24 to +16 total charges) and total charge density (0.28 to 0.40 charges per sequence length) typical for natural proteins. Protein designs were expressed, purified, and subjected to in silico and in vitro biophysical measurements to evaluate the relationship between protein surface potential and lignin adsorption properties. The designs were comparable to model fluorescent protein in terms of thermostability and heterologous expression yield, although the majority of the designs unexpectedly formed homodimers. Protein adsorption to lignin was studied at two different temperatures using Quartz Crystal Microbalance with Dissipation Monitoringmore » and a subtractive mass balance assay. We found a weak correlation between protein net charge and protein-binding capacity to lignin. No other single characteristic, including apparent melting temperature and 2nd virial coefficient, showed correlation with lignin binding. Analysis of an unrelated cellulase dataset with mutations localized to a family I carbohydrate-binding module showed a similar correlation between net charge and lignin binding capacity. Altogether, our study provides strategies to identify highly active, low lignin-binding cellulases by either rational design or by computational screening genomic databases.« less

Authors:

Haarmeyer, Carolyn N. ^[1]; Smith, Matthew D. ^[1]; Chundawat, Shishir P. S. ^[2]; Sammond, Deanne ^[3]; Whitehead, Timothy A. ^[1]

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+ Show Author Affiliations

1. Michigan State Univ., East Lansing, MI (United States)
2. Michigan State Univ., East Lansing, MI (United States); Rutgers, The State Univ. of New Jersey, Piscataway, NJ (United States)
3. National Renewable Energy Lab. (NREL), Golden, CO (United States)

Publication Date:

Mon Oct 17 00:00:00 EDT 2016

Research Org.:

National Renewable Energy Laboratory (NREL), Golden, CO (United States)

Sponsoring Org.:

USDOE Office of Energy Efficiency and Renewable Energy (EERE), Sustainable Transportation Office. Bioenergy Technologies Office (BETO)

OSTI Identifier:

1345115

Report Number(s):

NREL/JA-2700-66896
Journal ID: ISSN 0006-3592

Grant/Contract Number:  

AC36-08GO28308

Resource Type:

Accepted Manuscript

Journal Name:

Biotechnology and Bioengineering

Additional Journal Information:

Journal Volume: 114; Journal Issue: 4; Journal ID: ISSN 0006-3592

Publisher:

Wiley

Country of Publication:

United States

Language:

English

Subject:

09 BIOMASS FUELS; computational protein design; cellulase; lignin; biomass deconstruction; protein engineering