Variation in antibiotic-induced microbial recolonization impacts on the host metabolic phenotypes of rats

The interaction between the gut microbiota and their mammalian host is known to have far-reaching consequences with respect to metabolism and health. We investigated the effects of eight days of oral antibiotic exposure (penicillin and streptomycin sulfate) on gut microbial composition and host metabolic phenotype in male Han-Wistar rats (n = 6) compared to matched controls. Early recolonization was assessed in a third group exposed to antibiotics for four days followed by four days recovery (n = 6). Fluorescence in situ hybridization analysis of the intestinal contents collected at eight days showed a significant reduction in all bacterial groups measured (control, 1010.7 cells/g feces; antibiotic-treated, 108.4). Bacterial suppression reduced the excretion of mammalian-microbial urinary cometabolites including hippurate, phenylpropionic acid, phenylacetylglycine and indoxyl-sulfate whereas taurine, glycine, citrate, 2-oxoglutarate, and fumarate excretion was elevated. While total bacterial counts remained notably lower in the recolonized animals (109.1 cells/g faeces) compared to the controls, two cage-dependent subgroups emerged with Lactobacillus/Enterococcus probe counts dominant in one subgroup. This dichotomous profile manifested in the metabolic phenotypes with subgroup differences in tricarboxylic acid cycle metabolites and indoxyl-sulfate excretion. Fecal short chain fatty acids were diminished in all treated animals. Antibiotic treatment induced a profound effect on the microbiome structure, which was reflected in the metabotype. Moreover, the recolonization process was sensitive to the microenvironment, which may impact on understanding downstream consequences of antibiotic consumption in human populations.

Flanking SNP markers for vicine–convicine concentration in faba bean (Vicia faba L).

The pyrimidine glycosides, vicine and convicine, limit the use of faba bean (Vicia faba L.) as food and feed. A single recessive gene, vc-, is responsible for a lowered vicine–convicine concentration. The biosynthetic pathway of these closely related compounds is not known, and the nearest available markers are several cM away from vc-. Improved markers would assist breeding and help to identify candidate genes. A segregating population of 210 F5 recombinant inbred lines was developed from the cross of Mélodie/2 (low vicine–convicine) × ILB 938/2 (normal vicine–convicine), and vicine–convicine concentrations were determined twice on each line. The population was genotyped with a set of 188 SNPs. A strong, single QTL for vicine–convicine concentration was identified on chromosome I, flanked by markers 1.0 cM away on one side and 2.6 cM on the other. The interval defined by these markers in the model species Medicago truncatula includes about 340 genes, but no candidate genes were identified. Further fine mapping should lead to the identification of tightly linked markers as well as narrowing down the search for candidate regulatory or biosynthetic genes which could underlie the vc- locus.

Advancing polar prediction capabilities on daily to seasonal time scales

It is argued that existing polar prediction systems do not yet meet users’ needs; and possible ways forward in advancing prediction capacity in polar regions and beyond are outlined. The polar regions have been attracting more and more attention in recent years, fuelled by the perceptible impacts of anthropogenic climate change. Polar climate change provides new opportunities, such as shorter shipping routes between Europe and East Asia, but also new risks such as the potential for industrial accidents or emergencies in ice-covered seas. Here, it is argued that environmental prediction systems for the polar regions are less developed than elsewhere. There are many reasons for this situation, including the polar regions being (historically) lower priority, with less in situ observations, and with numerous local physical processes that are less well-represented by models. By contrasting the relative importance of different physical processes in polar and lower latitudes, the need for a dedicated polar prediction effort is illustrated. Research priorities are identified that will help to advance environmental polar prediction capabilities. Examples include an improvement of the polar observing system; the use of coupled atmosphere-sea ice-ocean models, even for short-term prediction; and insight into polar-lower latitude linkages and their role for forecasting. Given the enormity of some of the challenges ahead, in a harsh and remote environment such as the polar regions, it is argued that rapid progress will only be possible with a coordinated international effort. More specifically, it is proposed to hold a Year of Polar Prediction (YOPP) from mid-2017 to mid-2019 in which the international research and operational forecasting community will work together with stakeholders in a period of intensive observing, modelling, prediction, verification, user-engagement and educational activities.