Deep Device Mining for Carbohydrate-Active Enzymes in Pulp and Paper Mill Sludge Metagenome and Applications to Bioprocess Development | AIChE

Deep Device Mining for Carbohydrate-Active Enzymes in Pulp and Paper Mill Sludge Metagenome and Applications to Bioprocess Development

Authors 

Sharan, A. A. - Presenter, University of British Columbia
Yadav, V. G., University of British Columbia
Hallam, S. J., University of British Columbia

Biocatalyst discovery is integral to bioecomony development, enabling design of robust and scalable bioprocesses that are able to compete with the resource intensive petrochemical industry. Uncultivated microbial communities within natural and engineered ecosystems provide a near-infinite reservoir of genomic diversity and metabolic potential that can be harnessed for biocatalyst discovery1. To bridge the cultivation gap, functional metagenomic screens have been developed to recover active genes directly from environmental samples2. Here, we describe a pipeline for recovery of biomass-deconstructing biocatalysts sourced from pulp and paper mill sludge metagenomes to develop consolidated bioprocesses that convert waste streams into value-added products. High molecular weight DNA was extracted from sludge and used to construct a fosmid library containing 15,000 clones using the copy control system in EPI300™-T1 R E. coli based on established robotic methods3. Extracted DNA was also used in whole genome shotgun sequencing to compare the metabolic potential of the sludge community with fosmid screening outcomes using MetaPathways4 with specific emphasis on carbohydrate-active enzymes (CAZymes). In total, 32,232 ORF’s hits in CAZy database were obtained including glycoside hydrolases, glycosyl transferases, and carbohydrate binding module families. The fosmid library was screened for glycosidase hydrolase activities using a pool of sensitive fluorogenic glycosides of 6-chloro-4-methylumbelliferone enabling rapid recovery of β-cellobiosidase, mannosidase and xylosidase activities 5. A total of 744 clones capable of converting pooled substrates were recovered indicating an extremely high hit rate (1 hit per 43 clones). Downstream characterization including complete fosmid sequencing and subcloning results to identify specific active genes or gene cassettes is currently in progress. These results reinforce the notion that screening libraries sourced from environments naturally enriched for lignocellulosic biomass deconstruction increases screening efficieny and chances of recovering biocatalysts optimized to perform under specific environmental conditions. The combination of robotic library production and pooled screening using enriched DNA sources for lignocellulosic biomass deconstruction provides an example of high throughput experimental design extensible to a wide range of screening targets.

1. Mewis, K., Armstrong, Z., Song, Y. C., Baldwin, S. A., Withers, S. G., & Hallam, S. J. (2013). Biomining active cellulases from a mining bioremediation system. Journal of biotechnology, 167(4), 462-471.

2. Nyyssönen, M., Tran, H. M., Karaoz, U., Weihe, C., Hadi, M. Z., Martiny, J. B., ... & Brodie, E. L. (2013). Coupled high-throughput functional screening and next generation sequencing for identification of plant polymer decomposing enzymes in metagenomic libraries. Frontiers in microbiology, 4, 282.

3. Mewis, K., Taupp, M., & Hallam, S. J. (2011). A high throughput screen for biomining cellulase activity from metagenomic libraries. JoVE (Journal of Visualized Experiments), (48), e2461-e2461.

4. Hanson, N. W., Konwar, K. M., Wu, S. J., & Hallam, S. J. (2014, May). MetaPathways v2. 0: A master-worker model for environmental Pathway/Genome Database construction on grids and clouds. In Computational Intelligence in Bioinformatics and Computational Biology, 2014 IEEE Conference on(pp. 1-7). IEEE.

5. Chen, Hong-Ming, et al. "Synthesis and evaluation of a series of 6-chloro-4-methylumbelliferyl glycosides as fluorogenic reagents for screening metagenomic libraries for glycosidase activity." Carbohydrate research 421 (2016): 33-39.