Interrogation of the perturbed gut microbiota in gouty arthritis patients through in silico metabolic modeling

Recent studies have shown perturbed gut microbiota associated with gouty arthritis, a metabolic disease characterized by an imbalance between uric acid production and excretion. To mechanistically investigate altered microbiota metabolism associated with gout disease, 16S rRNA gene amplicon sequence data from stool samples of gout patients and healthy controls were computationally analyzed through bacterial community metabolic models. Patient-specific community models constructed with the metagenomics modeling pipeline, mgPipe, were used to perform k-means clustering of samples according to their metabolic capabilities. The clustering analysis generated statistically significant partitioning of samples into a Bacteroides-dominated, high gout cluster and a Faecalibacterium-elevated, low gout cluster. The high gout cluster was predicted to allow elevated synthesis of the amino acids D-alanine and L-alanine and byproducts of branched-chain amino acid catabolism, while the low gout cluster allowed higher production of butyrate, the sulfur-containing amino acids L-cysteine and L-methionine, and the L-cysteine catabolic product H2S. By expanding the capabilities of mgPipe to provide taxa-level resolution of metabolite exchange rates, acetate, D-lactate and succinate exchanged from Bacteroides to Faecalibacterium were predicted to enhance butyrate production in the low gout cluster. Model predictions suggested that sulfur-containing amino acid metabolism generally and H2S more specifically could be novel gout disease markers

Genetic complexity of miscanthus cell wall composition and biomass quality for biofuels

BACKGROUND: Miscanthus sinensis is a high yielding perennial grass species with great potential as a bioenergy feedstock. One of the challenges that currently impedes commercial cellulosic biofuel production is the technical difficulty to efficiently convert lignocellulosic biomass into biofuel. The development of feedstocks with better biomass quality will improve conversion efficiency and the sustainability of the value-chain. Progress in the genetic improvement of biomass quality may be substantially expedited by the development of genetic markers associated to quality traits, which can be used in a marker-assisted selection program. RESULTS: To this end, a mapping population was developed by crossing two parents of contrasting cell wall composition. The performance of 182 F1 offspring individuals along with the parents was evaluated in a field trial with a randomized block design with three replicates. Plants were phenotyped for cell wall composition and conversion efficiency characters in the second and third growth season after establishment. A new SNP-based genetic map for M. sinensis was built using a genotyping-by-sequencing (GBS) approach, which resulted in 464 short-sequence uniparental markers that formed 16 linkage groups in the male map and 17 linkage groups in the female map. A total of 86 QTLs for a variety of biomass quality characteristics were identified, 20 of which were detected in both growth seasons. Twenty QTLs were directly associated to different conversion efficiency characters. Marker sequences were aligned to the sorghum reference genome to facilitate cross-species comparisons. Analyses revealed that for some traits previously identified QTLs in sorghum occurred in homologous regions on the same chromosome. CONCLUSION: In this work we report for the first time the genetic mapping of cell wall composition and bioconversion traits in the bioenergy crop miscanthus. These results are a first step towards the development of marker-assisted selection programs in miscanthus to improve biomass quality and facilitate its use as feedstock for biofuel production

Photosynthetic efficiency and mesophyll conductance are unaffected in Arabidopsis thaliana aquaporin knock-out lines

Improving photosynthetic efficiency is widely regarded as a major route to achieving much-needed yield gains in crop plants. In plants with C3 photosynthesis, increasing the diffusion conductance for CO2 transfer from substomatal cavity to chloroplast stroma (gm) could help to improve the efficiencies of CO2 assimilation and photosynthetic water use in parallel. The diffusion pathway from substomatal cavity to chloroplast traverses cell wall, plasma membrane, cytosol, chloroplast envelope membranes, and chloroplast stroma. Specific membrane intrinsic proteins of the aquaporin family can facilitate CO2 diffusion across membranes. Some of these aquaporins, such as PIP1;2 in Arabidopsis thaliana, have been suggested to exert control over gm and the magnitude of the CO2 assimilation flux, but the evidence for a direct physiological role of aquaporins in determining gm is limited. Here, we estimated gm with four different methods under a range of light intensities and CO2 concentrations in two previously characterized pip1;2 knock-out lines as well as pip1;3 and pip2;6 knock-out lines, which have not been previously evaluated for a role in gm. This study presents the most in-depth analysis of gm in Arabidopsis aquaporin knock-out mutants to date. Surprisingly, all methods failed to show any significant differences between the pip1;2, pip1;3, or pip2;6 mutants and the Col-0 control