Ontology type: schema:ScholarlyArticle Open Access: True
2014-12
AUTHORSYing Zha, Johan A Westerhuis, Bas Muilwijk, Karin M Overkamp, Bernadien M Nijmeijer, Leon Coulier, Age K Smilde, Peter J Punt
ABSTRACTBACKGROUND: 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. More... »
PAGES22
http://scigraph.springernature.com/pub.10.1186/1472-6750-14-22
DOIhttp://dx.doi.org/10.1186/1472-6750-14-22
DIMENSIONShttps://app.dimensions.ai/details/publication/pub.1037361265
PUBMEDhttps://www.ncbi.nlm.nih.gov/pubmed/24655423
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