
You have already added 0 works in your ORCID record related to the merged Research product.
You have already added 0 works in your ORCID record related to the merged Research product.
<script type="text/javascript">
<!--
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://beta.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=undefined&type=result"></script>');
-->
</script>
Identifying inhibitory compounds in lignocellulosic biomass hydrolysates using an exometabolomics approach

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.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.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.
- University of Amsterdam Netherlands
- Delft University of Technology Netherlands
- TNO TRISKELION BV Netherlands
- TNO TRISKELION BV Netherlands
- University of Amsterdam (UvA) Pure UvA Netherlands
Alkaline, Sorbic acid, Unclassified drug, Chemical composition, Biomedical Innovation, Chloroformic acid ethyl ester, Cross validation, Acetic acid ethyl ester, Lignin, 630, Life, Yeasts, Biomass, Triticum, Chromatography, Plant Stems, EC-GC-MS, 5 hydroxymethylfurfural, Straw, Salix, (n)PLS model, Wheat straw, Sawdust, Furfural, Derivatization, Wood, Hydroperoxide, Oak, Barley straw, Vanillin, Wheat, Statistical model, Double cross validation, Phenylacetaldehyde, Lignocellulose, Healthy Living, Biotechnology, Research Article, 570, Carbohydrate, Mass fragmentography, Saccharomyces cerevisiae, Batch fermentation, Zea mays, Bagasse, Partial least squares regression, Aldehyde derivative, Barley, Lignocellulosic biomass hydrolysate, Acid, Wood chip, Life and Social Sciencesb, Metabolomics, Furaldehyde, Corn stover, Cellulose, Biology, Fermentation inhibition, Models, Statistical, Chromatographic analysis, Fungal strain, Willow, Inhibitors, EA-GC-MS, Hordeum, Dilution, Sugarcane, ELSS - Earth, 540, Nonhuman, Flavones, Lignocellulosic biomass, Peracetic acid, Maize, MSB - Microbiology and Systems Biology, Wood Products, Fermentation, PLS modeling, Exometabolomics, Willow wood chip, Controlled study, Fungus growth
Alkaline, Sorbic acid, Unclassified drug, Chemical composition, Biomedical Innovation, Chloroformic acid ethyl ester, Cross validation, Acetic acid ethyl ester, Lignin, 630, Life, Yeasts, Biomass, Triticum, Chromatography, Plant Stems, EC-GC-MS, 5 hydroxymethylfurfural, Straw, Salix, (n)PLS model, Wheat straw, Sawdust, Furfural, Derivatization, Wood, Hydroperoxide, Oak, Barley straw, Vanillin, Wheat, Statistical model, Double cross validation, Phenylacetaldehyde, Lignocellulose, Healthy Living, Biotechnology, Research Article, 570, Carbohydrate, Mass fragmentography, Saccharomyces cerevisiae, Batch fermentation, Zea mays, Bagasse, Partial least squares regression, Aldehyde derivative, Barley, Lignocellulosic biomass hydrolysate, Acid, Wood chip, Life and Social Sciencesb, Metabolomics, Furaldehyde, Corn stover, Cellulose, Biology, Fermentation inhibition, Models, Statistical, Chromatographic analysis, Fungal strain, Willow, Inhibitors, EA-GC-MS, Hordeum, Dilution, Sugarcane, ELSS - Earth, 540, Nonhuman, Flavones, Lignocellulosic biomass, Peracetic acid, Maize, MSB - Microbiology and Systems Biology, Wood Products, Fermentation, PLS modeling, Exometabolomics, Willow wood chip, Controlled study, Fungus growth
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).67 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
