Cinnamoyl-CoA reductase (CCR) catalyzes the penultimate step in monolignol biosynthesis. We show that downregulation of CCR in transgenic poplar (Populus tremula 3 Populus alba) was associated with up to 50% reduced lignin content and an orange-brown, often patchy, coloration of the outer xylem. Thioacidolysis, nuclear magnetic resonance (NMR), immunocytochemistry of lignin epitopes, and oligolignol profiling indicated that lignin was relatively more reduced in syringyl than in guaiacyl units. The cohesion of the walls was affected, particularly at sites that are generally richer in syringyl units in wild-type poplar. Ferulic acid was incorporated into the lignin via ether bonds, as evidenced independently by thioacidolysis and by NMR. A synthetic lignin incorporating ferulic acid had a red-brown coloration, suggesting that the xylem coloration was due to the presence of ferulic acid during lignification. Elevated ferulic acid levels were also observed in the form of esters. Transcript and metabolite profiling were used as comprehensive phenotyping tools to investigate how CCR downregulation impacted metabolism and the biosynthesis of other cell wall polymers. Both methods suggested reduced biosynthesis and increased breakdown or remodeling of noncellulosic cell wall polymers, which was further supported by Fourier transform infrared spectroscopy and wet chemistry analysis. The reduced levels of lignin and hemicellulose were associated with an increased proportion of cellulose. Furthermore, the transcript and metabolite profiling data pointed toward a stress response induced by the altered cell wall structure. Finally, chemical pulping of wood derived from 5-year-old, field-grown transgenic lines revealed improved pulping characteristics, but growth was affected in all transgenic lines tested.

No abstract

No abstract

No abstract

Fourier transform infrared spectroscopy (FTIR) was used to discriminate important wood-destroying fungi. Mycelia of 26 fungal strains belonging to 24 different species were grown on agar plates and subjected to FTIR attenuated total reflection (ATR) measurements. To classify the FTIR spectra, cluster analysis--an unsupervised multivariate data analysis method--was compared with artificial neural network (ANN) analysis--a supervised approach. By internal validation, both methods classified 99% of the spectra correctly. External validation with independent test set spectra resulted in 95% correctly classified spectra, demonstrating the high potential of this method for fungal strain identification.

FTIR spectroscopy was used to distinguish between beech (Fagus sylvatica L.) trees grown at five different sites; one in middle Germany close to Göttingen (forest district Reinhausen), three located in the southwest (two in Rhineland-Palatinate: forest districts Saarburg and Hochwald, and one in Luxembourg), and one in North-Rhine Westfalia. Detailed investigation of the spectra in the fingerprint region (1800–600 cm-1) revealed 16 distinct peaks and shoulders, most of which were assignable to wavenumbers previously shown to represent wood compounds. Differences in peak heights and peak ratios indicated differences in wood composition of beech trees from different sites. To determine if the wood of individual trees could be distinguished, principal component analysis (PCA) and cluster analysis were performed using FTIR spectra as input data. With both PCA and cluster analysis, trees from four of the five different sites were separated. It was not possible to distinguish between trees from Saarburg and Hochwald, where similar edaphic and climatic conditions exist, while wood spectra from trees from all other areas clearly segregated. Wood collected at different positions in the stem (bottom, crown, center and outer year rings) of trees grown at the same site was not distinguishable. Therefore, FTIR spectral analysis in combination with multivariate statistical methods can be used to distinguish wood of trees from different growth habitats. Extension of this method to other species may be of great interest for wood certification, as it may be possible to distinguish wood, of a given species, originating from different regions.

No abstract

No abstract