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Fig. 2 | Biotechnology for Biofuels

Fig. 2

From: Increasing proline and myo-inositol improves tolerance of Saccharomyces cerevisiae to the mixture of multiple lignocellulose-derived inhibitors

Fig. 2

The discovery of potential biomarkers involved in strain tolerance to FAP through multivariate statistical analysis. a The schematic of the adaptation process and sampling strategy for metabolomic analysis. b PLS-DA score plot and loading plot of the samples from cells of G0, G1, G2 and G3. The percentages listed in the axis labels described the fraction of variance explained by the first and second predictive component (t[1]P and t[2]P), respectively. G0 cells without inhibitors, G1 cells with inhibitors, G2 and G3 cells of transfer 1 and transfer 2. c The analysis results of minimum redundancy maximum relevance criterion (MRMR). d The metabolic pathway analysis with MetPA. All the matched pathways are displayed as circles. The color and size of each circle was based on p value (from pathway enrichment analysis), and pathway impact values (from pathway topology analysis), respectively. a Alanine, aspartate and glutamate metabolism; b glycerolipid metabolism; c arginine and proline metabolism. e Variations of the intermediates of proline synthesis metabolism, glycine, lysine and myo-inositol during the adaptation process. The levels of all metabolites were standardized by mean 0 and variance 1. The normalized level of each metabolite was indicated by the color squares at the bottom right of the map. The bright red and green colors represent the most elevated and reduced molecules

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