Analysis of Plant Cell Walls by Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy.

Attenuated total reflectance Fourier transform mid-infrared (ATR-FTIR) spectroscopy is widely applicable for the chemical analysis of biological materials, relatively inexpensive, requires only simple sample preparation, and is of comparatively high-throughput compared to traditional wet chemical or chromatographic methods. It is particularly well suited for the nondestructive analysis of dried and finely ground plant samples for the subsequent prediction of cell wall and other compositional or processing parameters using chemometric regression models. Furthermore, analysis of mid IR spectra by nonregression methods (e.g., principal component analysis) provides a straightforward approach for multivariate comparison of the effects of experimental, processing, and environmental treatments, and genotypic and temporal differences on chemical composition including changes in cell wall composition. There is thus great potential for using ATR-FTIR in the lignocellulosic biomass industry at a number of levels. Here we describe methods for cell wall sample preparation and generation of ATR-FTIR spectra, and suggest techniques for the statistical analysis and/or chemometric pattern recognition between the analyzed samples.

Using 'Omic Approaches to Compare Temporal Bacterial Colonization of Lolium perenne, Lotus corniculatus, and Trifolium pratense in the Rumen.

Understanding rumen plant-microbe interactions is central for development of novel methodologies allowing improvements in ruminant nutrient use efficiency. This study investigated rumen bacterial colonization of fresh plant material and changes in plant chemistry over a period of 24 h period using three different fresh forages: Lolium perenne (perennial ryegrass; PRG), Lotus corniculatus (bird's foot trefoil; BFT) and Trifolium pratense (red clover; RC). We show using 16S rRNA gene ion torrent sequencing that plant epiphytic populations present pre-incubation (0 h) were substantially different to those attached post incubations in the presence of rumen fluid on all forages. Thereafter primary and secondary colonization events were evident as defined by changes in relative abundances of attached bacteria and changes in plant chemistry, as assessed using Fourier transform infrared (FTIR) spectroscopy. For PRG colonization, primary colonization occurred for up to 4 h and secondary colonization from 4 h onward. The changes from primary to secondary colonization occurred significantly later with BFT and RC, with primary colonization being up to 6 h and secondary colonization post 6 h of incubation. Across all 3 forages the main colonizing bacteria present at all time points post-incubation were Prevotella, Pseudobutyrivibrio, Ruminococcus, Olsenella, Butyrivibrio, and Anaeroplasma (14.2, 5.4, 1.9, 2.7, 1.8, and 2.0% on average respectively), with Pseudobutyrivibrio and Anaeroplasma having a higher relative abundance during secondary colonization. Using CowPI, we predict differences between bacterial metabolic function during primary and secondary colonization. Specifically, our results infer an increase in carbohydrate metabolism in the bacteria attached during secondary colonization, irrespective of forage type. The CowPI data coupled with the FTIR plant chemistry data suggest that attached bacterial function is similar irrespective of forage type, with the main changes occurring between primary and secondary colonization. These data suggest that the sward composition of pasture may have major implications for the temporal availability of nutrients for animal.

Temporal Metagenomic and Metabolomic Characterization of Fresh Perennial Ryegrass Degradation by Rumen Bacteria.

Understanding the relationship between ingested plant material and the attached microbiome is essential for developing methodologies to improve ruminant nutrient use efficiency. We have previously shown that perennial ryegrass (PRG) rumen bacterial colonization events follow a primary (up to 4 h) and secondary (after 4 h) pattern based on the differences in diversity of the attached bacteria. In this study, we investigated temporal niche specialization of primary and secondary populations of attached rumen microbiota using metagenomic shotgun sequencing as well as monitoring changes in the plant chemistry using mid-infrared spectroscopy (FT-IR). Metagenomic Rapid Annotation using Subsystem Technology (MG-RAST) taxonomical analysis of shotgun metagenomic sequences showed that the genera Butyrivibrio, Clostridium, Eubacterium, Prevotella, and Selenomonas dominated the attached microbiome irrespective of time. MG-RAST also showed that Acidaminococcus, Bacillus, Butyrivibrio, and Prevotella rDNA increased in read abundance during secondary colonization, whilst Blautia decreased in read abundance. MG-RAST Clusters of Orthologous Groups (COG) functional analysis also showed that the primary function of the attached microbiome was categorized broadly within "metabolism;" predominantly amino acid, carbohydrate, and lipid metabolism and transport. Most sequence read abundances (51.6, 43.8, and 50.0% of COG families pertaining to amino acid, carbohydrate and lipid metabolism, respectively) within these categories were higher in abundance during secondary colonization. Kyoto encyclopedia of genes and genomes (KEGG) pathways analysis confirmed that the PRG-attached microbiota present at 1 and 4 h of rumen incubation possess a similar functional capacity, with only a few pathways being uniquely found in only one incubation time point only. FT-IR data for the plant residues also showed that the main changes in plant chemistry between primary and secondary colonization was due to increased carbohydrate, amino acid, and lipid metabolism. This study confirmed primary and secondary colonization events and supported the hypothesis that functional changes occurred as a consequence of taxonomical changes. Sequences within the carbohydrate metabolism COG families contained only 3.2% of cellulose activities, on average across both incubation times (1 and 4 h), suggesting that degradation of the plant cell walls may be a key rate-limiting factor in ensuring the bioavailability of intra-plant nutrients in a timely manner to the microbes and ultimately the animal. This suggests that a future focus for improving ruminant nutrient use efficiency should be altering the recalcitrant plant cell wall components and/or improving the cellulolytic capacity of the rumen microbiota.

The metabolomic detection of lung cancer biomarkers in sputum.

OBJECTIVES: Developing screening and diagnosis methodologies based on novel biomarkers should allow for the detection of the lung cancer (LC) and possibly at an earlier stage and thereby increase the effectiveness of clinical interventions. Here, our primary objective was to evaluate the potential of spontaneous sputum as a source of non-invasive metabolomic biomarkers for LC status. MATERIALS AND METHODS: Spontaneous sputum was collected and processed from 34 patients with suspected LC, alongside 33 healthy controls. Of the 34 patients, 23 were subsequently diagnosed with LC (LC(+), 16 NSCLC, six SCLC, and one radiological diagnosis), at various stages of disease progression. The 67 samples were analysed using flow infusion electrospray ion mass spectrometry (FIE-MS) and gas-chromatography mass spectrometry (GC-MS). RESULTS: Principal component analysis identified negative mode FIE-MS as having the main separating power between samples from healthy and LC. Discriminatory metabolites were identified using ANOVA and Random Forest. Indications of potential diagnostic accuracy involved the use of receiver operating characteristic/area under the curve (ROC/AUC) analyses. This approach identified metabolites changes that were only observed with LC. Metabolites with AUC values of greater than 0.8 which distinguished between LC(+)/LC(-) binary classifications where identified and included Ganglioside GM1 which has previously been linked to LC. CONCLUSION: This study indicates that metabolomics based on sputum can yield metabolites that can be used as a diagnostic and/or discriminator tool. These could aid clinical intervention and targeted diagnosis of LC within an 'at risk' LC(-) population group. The use of sputum as a non-invasive source of metabolite biomarkers may aid in the development of an at-risk population screening programme for lung cancer or enhanced clinical diagnostic pathways.

De novo assembly of red clover transcriptome based on RNA-Seq data provides insight into drought response, gene discovery and marker identification.

BACKGROUND: Red clover (Trifolium pratense L.) is a versatile forage crop legume, which can tolerate a variety of soils and is suitable for silage production for winter feed and for grazing. It is one of the most important forage legumes in temperate livestock agriculture. Its beneficial attributes include ability to fix nitrogen, improve soil and provide protein rich animal feed. It is however, a short-lived perennial providing good biomass yield for two or three years. Improved persistency is thus a major breeding target. Better water-stress tolerance is one of the key factors influencing persistency, but little is known about how red clover tolerates water stress. RESULTS: Plants from a full sib mapping family were used in a drought experiment, in which the growth rate and relative water content (RWC) identified two pools of ten plants contrasting in their tolerance to drought. Key metabolites were measured and RNA-Seq analysis was carried out on four bulked samples: the two pools sampled before and after drought. Massively parallel sequencing was used to analyse the bulked RNA samples. A de novo transcriptome reconstruction based on the RNA-Seq data was made, resulting in 45181 contigs, representing 'transcript tags'. These transcript tags were annotated with gene ontology (GO) terms. One of the most striking results from the expression analysis was that the drought sensitive plants were characterised by having approximately twice the number of differentially expressed transcript tags than the tolerant plants after drought. This difference was evident in most of the major GO terms. Before onset of drought the sensitive plants overexpressed a number of genes annotated as senescence-related. Furthermore, the concentration of three metabolites, particularly pinitol, but also proline and malate increased in leaves after drought stress. CONCLUSIONS: This de novo assembly of a red clover transcriptome from leaf material of droughted and non-droughted plants provides a rich source for gene identification, single nucleotide polymorphisms (SNP) and short sequence repeats (SSR). Comparison of gene expression levels between pools and treatments identified candidate genes for further analysis of the genetic basis of drought tolerance in red clover.

Genotype, development and tissue-derived variation of cell-wall properties in the lignocellulosic energy crop Miscanthus.

BACKGROUND AND AIMS: Species and hybrids of the genus Miscanthus contain attributes that make them front-runners among current selections of dedicated bioenergy crops. A key trait for plant biomass conversion to biofuels and biomaterials is cell-wall quality; however, knowledge of cell-wall composition and biology in Miscanthus species is limited. This study presents data on cell-wall compositional changes as a function of development and tissue type across selected genotypes, and considers implications for the development of miscanthus as a sustainable and renewable bioenergy feedstock. METHODS: Cell-wall biomass was analysed for 25 genotypes, considering different developmental stages and stem vs. leaf compositional variability, by Fourier transform mid-infrared spectroscopy and lignin determination. In addition, a Clostridium phytofermentans bioassay was used to assess cell-wall digestibility and conversion to ethanol. KEY RESULTS: Important cell-wall compositional differences between miscanthus stem and leaf samples were found to be predominantly associated with structural carbohydrates. Lignin content increased as plants matured and was higher in stem tissues. Although stem lignin concentration correlated inversely with ethanol production, no such correlation was observed for leaves. Leaf tissue contributed significantly to total above-ground biomass at all stages, although the extent of this contribution was genotype-dependent. CONCLUSIONS: It is hypothesized that divergent carbohydrate compositions and modifications in stem and leaf tissues are major determinants for observed differences in cell-wall quality. The findings indicate that improvement of lignocellulosic feedstocks should encompass tissue-dependent variation as it affects amenability to biological conversion. For gene-trait associations relating to cell-wall quality, the data support the separate examination of leaf and stem composition, as tissue-specific traits may be masked by considering only total above-ground biomass samples, and sample variability could be mostly due to varying tissue contributions to total biomass.

Genome-wide association studies and prediction of 17 traits related to phenology, biomass and cell wall composition in the energy grass Miscanthus sinensis.

• Increasing demands for food and energy require a step change in the effectiveness, speed and flexibility of crop breeding. Therefore, the aim of this study was to assess the potential of genome-wide association studies (GWASs) and genomic selection (i.e. phenotype prediction from a genome-wide set of markers) to guide fundamental plant science and to accelerate breeding in the energy grass Miscanthus. • We generated over 100,000 single-nucleotide variants (SNVs) by sequencing restriction site-associated DNA (RAD) tags in 138 Micanthus sinensis genotypes, and related SNVs to phenotypic data for 17 traits measured in a field trial. • Confounding by population structure and relatedness was severe in naïve GWAS analyses, but mixed-linear models robustly controlled for these effects and allowed us to detect multiple associations that reached genome-wide significance. Genome-wide prediction accuracies tended to be moderate to high (average of 0.57), but varied dramatically across traits. As expected, predictive abilities increased linearly with the size of the mapping population, but reached a plateau when the number of markers used for prediction exceeded 10,000-20,000, and tended to decline, but remain significant, when cross-validations were performed across subpopulations. • Our results suggest that the immediate implementation of genomic selection in Miscanthus breeding programs may be feasible.

Alterations in the metabolic fingerprint of Cladonia portentosa in response to atmospheric nitrogen deposition.

Nitrogen availability has profound ecological consequences in nutrient-limited systems. In terrestrial settings these would include the upland heaths, sand dunes and blanket bogs of temperate latitudes. Understanding the physiological consequences of nitrogen enrichment is a first critical step in predicting possible consequences. Results are presented from a metabolic fingerprinting study using Fourier transform-infrared spectroscopy (FTIR) to detect biochemical differences in the lichen Cladonia portentosa collected from 25 sites across mainland Britain varying in their nitrogen input. Partial least-squares regression analysis of the FTIR data demonstrated that changes in broad biochemical classes were consistently correlated with mean annual wet inorganic nitrogen deposition loads. These results demonstrated a direct coupling of a broad range of metabolic processes in C. portentosa to nitrogen deposition.

Measurement of key compositional parameters in two species of energy grass by Fourier transform infrared spectroscopy.

Two energy grass species, switch grass, a North American tuft grass, and reed canary grass, a European native, are likely to be important sources of biomass in Western Europe for the production of biorenewable energy. Matching chemical composition to conversion efficiency is a primary goal for improvement programmes and for determining the quality of biomass feed-stocks prior to use and there is a need for methods which allow cost effective characterisation of chemical composition at high rates of sample through-put. In this paper we demonstrate that nitrogen content and alkali index, parameters greatly influencing thermal conversion efficiency, can be accurately predicted in dried samples of these species grown under a range of agronomic conditions by partial least square regression of Fourier transform infrared spectra (R(2) values for plots of predicted vs. measured values of 0.938 and 0.937, respectively). We also discuss the prediction of carbon and ash content in these samples and the application of infrared based predictive methods for the breeding improvement of energy grasses.

Diversity and activity of enriched ruminal cultures of anaerobic fungi and methanogens grown together on lignocellulose in consecutive batch culture.

Consecutive batch cultures (CBC), involving nine serial transfers at 3, 5 and 7d intervals (21, 45 and 63d, respectively) were established to enrich for plant fibre degrading co-cultures of anaerobic fungi and methanogens from rumen digesta. Microbial diversity and fermentation end-products were measured at appropriate intervals over each CBC time-course. While methanogenic populations remained diverse, anaerobic fungal diversity was related to transfer interval and appeared to decrease with increasing transfer number. Acetate was the principal aqueous fermentation end-product with minimal quantities of lactate and formate detected. Methane and carbon dioxide were detected in the gaseous head-space of all co-cultures and the total amounts of gas generated per transfer was greater with transfer intervals of 5 and 7d compared with a 3d interval, although the 3d interval tended to be more efficient per unit time. In conclusion, rapidly growing, methane producing co-cultures of anaerobic fungi and methanogens from rumen digesta were easy to establish on lignocellulose (barley straw) and maintain over considerable time periods. These results suggest such co-cultures have potential in industrial scale anaerobic digestion (AD) of highly fibrous substrates, which are resistant to degradation in conventional AD plants.

Quantification of hydroxycinnamic acids and lignin in perennial forage and energy grasses by Fourier-transform infrared spectroscopy and partial least squares regression.

Levels of lignin and hydroxycinnamic acid wall components in three genera of forage grasses (Lolium,Festuca and Dactylis) have been accurately predicted by Fourier-transform infrared spectroscopy using partial least squares models correlated to analytical measurements. Different models were derived that predicted the concentrations of acid detergent lignin, total hydroxycinnamic acids, total ferulate monomers plus dimers, p-coumarate and ferulate dimers in independent spectral test data from methanol extracted samples of perennial forage grass with accuracies of 92.8%, 86.5%, 86.1%, 59.7% and 84.7% respectively, and analysis of model projection scores showed that the models relied generally on spectral features that are known absorptions of these compounds. Acid detergent lignin was predicted in samples of two species of energy grass, (Phalaris arundinacea and Pancium virgatum) with an accuracy of 84.5%.

Application of gas chromatography-mass spectrometry metabolite profiling techniques to the analysis of heathland plant diets of sheep.

Little is known about how plant biochemistry influences the grazing behavior of animals consuming heterogeneous plant communities. The biochemical profiles of grassland species are mostly restricted to major nutritional characteristics, although recent developments in analytical techniques and data analysis have made possible the detailed analysis of minor components that may influence animal feeding preferences, performance, and health. In the present study, gas chromatography coupled with time-of-flight mass spectrometry (GC-TOF/MS) was used to profile the abundances of metabolites in nine specific heathland plant groups and in three mixed forage diets containing 10, 20, or 30% heather (Calluna vulgaris) and also in plasma and feces from sheep offered one of the three diets. Statistical and chemometric approaches, that is, principal component analysis (PCA) and hierarchical cluster analysis (HCA), were used to discriminate between these diets and between individual animals maintained on these diets. It is shown that GC-TOF/MS analysis of sheep plasma allowed distinction between the very similar diets by PCA and HCA, and, moreover, the plant metabolites responsible for the differences observed have been identified. Furthermore, metabolite markers of herbage mixtures and individual plant groups have been identified, and markers have been detected in sheep plasma and feces.