Age and microenvironment outweigh genetic influence on the Zucker rat microbiome

Animal models are invaluable tools which allow us to investigate the microbiome-host dialogue. However, experimental design introduces biases in the data that we collect, also potentially leading to biased conclusions. With obesity at pandemic levels animal models of this disease have been developed; we investigated the role of experimental design on one such rodent model. We used 454 pyrosequencing to profile the faecal bacteria of obese (n = 6) and lean (homozygous n = 6; heterozygous n = 6) Zucker rats over a 10 week period, maintained in mixed-genotype cages, to further understand the relationships between the composition of the intestinal bacteria and age, obesity progression, genetic background and cage environment. Phylogenetic and taxon-based univariate and multivariate analyses (non-metric multidimensional scaling, principal component analysis) showed that age was the most significant source of variation in the composition of the faecal microbiota. Second to this, cage environment was found to clearly impact the composition of the faecal microbiota, with samples from animals from within the same cage showing high community structure concordance, but large differences seen between cages. Importantly, the genetically induced obese phenotype was not found to impact the faecal bacterial profiles. These findings demonstrate that the age and local environmental cage variables were driving the composition of the faecal bacteria and were more deterministically important than the host genotype. These findings have major implications for understanding the significance of functional metagenomic data in experimental studies and beg the question; what is being measured in animal experiments in which different strains are housed separately, nature or nurture?

Method for exploratory cluster analysis and visualisation of single-trial ERP ensembles

Background: The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data. New method: We propose a complete pipeline for the cluster analysis of ERP data. To increase the signalto-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA)to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA). Results: After validating the pipeline on simulated data, we tested it on data from two experiments – a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership.

Effect of azole fungicide mixtures, alternations and dose on azole sensitivity in the wheat pathogen Zymoseptoria tritici

The evolution of fungicide resistance in the cereal pathogen Zymoseptoria tritici, is a serious threat to the sustainability and profitability of wheat production in Europe. Application of azole fungicides has been shown to affect fitness of Z. tritici variants differentially, so it has been hypothesised that combinations of azoles could slow the evolution of resistance. This work was initiated to assess the effects of dose, mixtures and alternations of two azoles on selection for isolates with reduced sensitivity and on disease control. Naturally infected field trials were carried out at six sites across Ireland and the sensitivity of Z. tritici isolates monitored pre- and post-treatment. The azoles epoxiconazole and metconazole were applied as solo products, in alternation with each other and as a pre-formulated mixture. Full and half label doses were tested. The two azoles were partially cross-resistant, with a common azole resistance principal component accounting for 75% of the variation between isolates. Selection for isolates with reduced azole sensitivity was correlated with disease control. Decreased doses were related to decreases in sensitivity but the effect was barely significant (P = 0.1) and control was reduced. Single applications of an active ingredient (a.i.) caused smaller decreases in sensitivity than double applications. Shifts in sensitivity to the a.i. applied to a plot were greater than to the a.i. not applied, and the decrease in sensitivity was greater to the a.i. applied at the second timing. These results confirm the need to mix a.i.s with different modes of action.

Uptake of agri-environmental schemes in the Less-Favoured Areas of Greece: The role of corruption and farmers' responses to the financial crisis

Vine-growing in the Less-Favoured Areas of Greece is facing multiple challenges that might lead to its abandonment. In an attempt to maintain rural populations, Rural Development Schemes have been created that offer the opportunity to rural households to maintain or expand their farming businesses including vine-growing. This paper stems from a study that used data from a cross-sectional survey of 204 farmers to investigate how farming systems and farmers’ perception of corruption, amongst other socio-economic factors, affected their decisions to continue vine-growing through participation in Rural Development Schemes, in three remote Less-Favoured Areas of Greece. The Theory of Planned Behaviour was used to frame the research problem with the assumption being that an individual’s intention to participate in a Scheme is based on their prior beliefs about it. Data from the survey were reduced and simplified by the use of non-linear principal component analysis. The ensuing variables were used in selectivity corrected ordered probit models to reveal farmers’ attitudes towards viticulture and rural development. It was found that economic factors, perceived corruption and farmers’ attitudes were significant determinants on whether to participate in the Schemes. The research findings highlight the important role of perceived corruption and the need for policies that facilitate farmers’ access to decision making centres.

Biomineralisation by earthworms: an investigation into the stability and distribution of amorphous calcium carbonate

Background Many biominerals form from amorphous calcium carbonate (ACC), but this phase is highly unstable when synthesised in its pure form inorganically. Several species of earthworm secrete calcium carbonate granules which contain highly stable ACC. We analysed the milky fluid from which granules form and solid granules for amino acid (by liquid chromatography) and functional group (by Fourier transform infrared (FTIR) spectroscopy) compositions. Granule elemental composition was determined using inductively coupled plasma-optical emission spectroscopy (ICP-OES) and electron microprobe analysis (EMPA). Mass of ACC present in solid granules was quantified using FTIR and compared to granule elemental and amino acid compositions. Bulk analysis of granules was of powdered bulk material. Spatially resolved analysis was of thin sections of granules using synchrotron-based μ-FTIR and EMPA electron microprobe analysis. Results The milky fluid from which granules form is amino acid-rich (≤ 136 ± 3 nmol mg−1 (n = 3; ± std dev) per individual amino acid); the CaCO3 phase present is ACC. Even four years after production, granules contain ACC. No correlation exists between mass of ACC present and granule elemental composition. Granule amino acid concentrations correlate well with ACC content (r ≥ 0.7, p ≤ 0.05) consistent with a role for amino acids (or the proteins they make up) in ACC stabilisation. Intra-granule variation in ACC (RSD = 16%) and amino acid concentration (RSD = 22–35%) was high for granules produced by the same earthworm. Maps of ACC distribution produced using synchrotron-based μ-FTIR mapping of granule thin sections and the relative intensity of the ν2: ν4 peak ratio, cluster analysis and component regression using ACC and calcite standards showed similar spatial distributions of likely ACC-rich and calcite-rich areas. We could not identify organic peaks in the μ-FTIR spectra and thus could not determine whether ACC-rich domains also had relatively high amino acid concentrations. No correlation exists between ACC distribution and elemental concentrations determined by EMPA. Conclusions ACC present in earthworm CaCO3 granules is highly stable. Our results suggest a role for amino acids (or proteins) in this stability. We see no evidence for stabilisation of ACC by incorporation of inorganic components.

Impact of dietary polydextrose fiber on the human gut metabolome

The aim of the present study was to elucidate the impact of polydextrose PDX an soluble fiber, on the human fecal metabolome by high-resolution nuclear magnetic resonance (NMR) spectroscopy-based metabolomics in a dietary intervention study (n = 12). Principal component analysis (PCA) revealed a strong effect of PDX consumption on the fecal metabolome, which could be mainly ascribed to the presence of undigested fiber and oligosaccharides formed from partial degradation of PDX. Our results demonstrate that NMR-based metabolomics is a useful technique for metabolite profiling of feces and for testing compliance to dietary fiber intake in such trials. In addition, novel associations between PDX and the levels of the fecal metabolites acetate and propionate could be identified. The establishment of a correlation between the fecal metabolome and levels of Bifidobacterium (R2 = 0.66) and Bacteroides (R2 = 0.46) demonstrates the potential of NMR-based metabolomics to elucidate metabolic activity of bacteria in the gut.

A five-dimensional model of attributes: some precursors of executive coach selection

The purpose of this study was to specify a set of attributes, identified as important precursors to coach selection. Executive coaching has grown exponentially, but there have been few studies as to the efficacy of coaching, including the factors that influence a manager's choice of coach. This study sought to identify these factors. The 45-item, online survey produced 267 useable responses. Results of the principal component analysis suggested a five-factor solution, with women showing a statistically significant preference over men for coaches who have the Ability to Develop Critical Thinking and Action, the Ability to Forge the Coaching Partnership and Coach Experience and Qualifications. The impact of coachee age was not significant in selecting executive coaches. The findings show a statistically significant relationship between coach attributes and the intention to continue with coaching. The implications of these findings for the selection of coaches, and for the coaching profession are discussed.