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Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP).

ABSTRACT: The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which remains to be elucidated. To address this challenge, we have developed an Activity-Correlated Quantitative Proteomics Platform (ACPP) that systematically correlates protein-level enzymatic activity patterns and protein elution profiles using a label-free quantitative proteomics approach. The ACPP optimized a high performance anion exchange separation for efficiently fractionating complex protein samples while preserving enzymatic activities. The detected enzymatic activity patterns in sequential fractions using microplate-based assays were cross-correlated with protein elution profiles using a customized pattern-matching algorithm with a correlation R-score. The ACPP has been successfully applied to the identification of two types of "active" biomass-degrading enzymes (i.e., starch hydrolysis enzymes and cellulose hydrolysis enzymes) from Aspergillus niger secretome in a multiplexed fashion. By determining protein elution profiles of 156 proteins in A. niger secretome, we confidently identified the 1,4-?-glucosidase as the major "active" starch hydrolysis enzyme (R = 0.96) and the endoglucanase as the major "active" cellulose hydrolysis enzyme (R = 0.97). The results demonstrated that the ACPP facilitated the discovery of bioactive enzymes from complex protein samples in a high-throughput, multiplexing, and untargeted fashion. Graphical Abstract ?.

SUBMITTER: Ma H

PROVIDER: S-EPMC5373979 | biostudies-literature | 2017 Apr

REPOSITORIES: biostudies-literature

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Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP).

Ma Hongyan H Delafield Daniel G DG Wang Zhe Z You Jianlan J Wu Si S

Journal of the American Society for Mass Spectrometry 20170112 4

The microbial secretome, known as a pool of biomass (i.e., plant-based materials) degrading enzymes, can be utilized to discover industrial enzyme candidates for biofuel production. Proteomics approaches have been applied to discover novel enzyme candidates through comparing protein expression profiles with enzyme activity of the whole secretome under different growth conditions. However, the activity measurement of each enzyme candidate is needed for confident "active" enzyme assignments, which ...[more]

PMID: 28083757

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Project description:BackgroundFor enzymes with buried active sites, transporting substrates/products ligands between active sites and bulk solvent via access tunnels is a key step in the catalytic cycle of these enzymes. Thus, tunnel engineering is becoming a powerful strategy to refine the catalytic properties of these enzymes. The tunnel-like structures have been described in enzymes catalyzing bulky substrates like glycosyl hydrolases, while it is still uncertain whether these structures involved in ligands exchange. Till so far, no studies have been reported on the application of tunnel engineering strategy for optimizing properties of enzymes catalyzing biopolymers.ResultsIn this study, xylanase S7-xyl (PDB: 2UWF) with a deep active cleft was chosen as a study model to evaluate the functionalities of tunnel-like structures on the properties of biopolymer-degrading enzymes. Three tunnel-like structures in S7-xyl were identified and simultaneously reshaped through multi-sites saturated mutagenesis; the most advantageous mutant 254RL1 (V207N/Q238S/W241R) exhibited 340% increase in specific activity compared to S7-xyl. Deconvolution analysis revealed that all three mutations contributed synergistically to the improved activity of 254RL1. Enzymatic characterization showed that larger end products were released in 254RL1, while substrate binding and structural stability were not changed. Dissection of the structural alterations revealed that both the tun_1 and tun_2 in 254RL1 have larger bottleneck radius and shorter length than those of S7-xyl, suggesting that these tunnel-like structures may function as products transportation pathways. Attributed to the improved catalytic efficiency, 254RL1 represents a superior accessory enzyme to enhance the hydrolysis efficiency of cellulase towards different pretreated lignocellulose materials. In addition, tunnel engineering strategy was also successfully applied to improve the catalytic activities of three other xylanases including xylanase NG27-xyl from Bacillus sp. strain NG-27, TSAA1-xyl from Geobacillus sp. TSAA1 and N165-xyl from Bacillus sp. N16-5, with 80%, 20% and 170% increase in specific activity, respectively.ConclusionsThis study represents a pilot study of engineering and functional verification of tunnel-like structures in enzymes catalyzing biopolymer. The specific activities of four xylanases with buried active sites were successfully improved by tunnel engineering. It is highly likely that tunnel reshaping can be used to engineer better biomass-degrading abilities in other lignocellulolytic enzymes with buried active sites.

Dataset Information

Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP).

Publications

Finding Biomass Degrading Enzymes Through an Activity-Correlated Quantitative Proteomics Platform (ACPP).

Similar Datasets

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