Email updates

Keep up to date with the latest news and content from BMC Biotechnology and BioMed Central.

Open Access Highly Accessed Research article

Identifying inhibitory compounds in lignocellulosic biomass hydrolysates using an exometabolomics approach

Ying Zha12, Johan A Westerhuis23, Bas Muilwijk4, Karin M Overkamp1, Bernadien M Nijmeijer1, Leon Coulier25, Age K Smilde23 and Peter J Punt12*

Author Affiliations

1 TNO Microbiology & Systems Biology, Utrechtsweg 48, Zeist 3704 HE, The Netherlands

2 Netherlands Metabolomics Centre (NMC), Einsteinweg 55, Leiden 2333 CC, The Netherlands

3 Biosystems Data Analysis, Swammerdam Institute for Life Sciences, University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands

4 TNO Triskelion BV, Utrechtseweg 48, Zeist 3700 AV, The Netherlands

5 TNO Quality & Safety, Utrechtseweg 48, 3704 HE Zeist, The Netherlands

For all author emails, please log on.

BMC Biotechnology 2014, 14:22  doi:10.1186/1472-6750-14-22

Published: 21 March 2014

Abstract

Background

Inhibitors are formed that reduce the fermentation performance of fermenting yeast during the pretreatment process of lignocellulosic biomass. An exometabolomics approach was applied to systematically identify inhibitors in lignocellulosic biomass hydrolysates.

Results

We studied the composition and fermentability of 24 different biomass hydrolysates. To create diversity, the 24 hydrolysates were prepared from six different biomass types, namely sugar cane bagasse, corn stover, wheat straw, barley straw, willow wood chips and oak sawdust, and with four different pretreatment methods, i.e. dilute acid, mild alkaline, alkaline/peracetic acid and concentrated acid. Their composition and that of fermentation samples generated with these hydrolysates were analyzed with two GC-MS methods. Either ethyl acetate extraction or ethyl chloroformate derivatization was used before conducting GC-MS to prevent sugars are overloaded in the chromatograms, which obscure the detection of less abundant compounds. Using multivariate PLS-2CV and nPLS-2CV data analysis models, potential inhibitors were identified through establishing relationship between fermentability and composition of the hydrolysates. These identified compounds were tested for their effects on the growth of the model yeast, Saccharomyces. cerevisiae CEN.PK 113-7D, confirming that the majority of the identified compounds were indeed inhibitors.

Conclusion

Inhibitory compounds in lignocellulosic biomass hydrolysates were successfully identified using a non-targeted systematic approach: metabolomics. The identified inhibitors include both known ones, such as furfural, HMF and vanillin, and novel inhibitors, namely sorbic acid and phenylacetaldehyde.

Keywords:
Lignocellulosic biomass hydrolysate; Inhibitor; Metabolomics; Fermentation; EA-GC-MS; EC-GC-MS; (n)PLS model; Double cross validation