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Additional file 2:Plots showing curvature, CpG and repeats for the Markov-permutations for Arabidopsis and rice first chromosomes. (DOC 152 KB)

Authors’ original file for figure 2

Additional file of Genome-scale computational analysis of DNA curvature and repeats in Arabidopsis and rice uncovers plant-specific genomic properties

Authors’ original file for figure 9

Additional file 4:Plots showing repeat number vs. curvature average and CpG length in 20 kilobase windows for Arabidopsis and rice first chromosomes. (DOC 141 KB)

Authors’ original file for figure 3

Authors’ original file for figure 4

Authors’ original file for figure 1

Authors’ original file for figure 5

Additional file 3:Plots showing curvature. CpG and repeats for all chromosomes of yeast and mouse. (DOC 1 MB)

Recent evidence has disclosed a connection between gut microbial glycosidase activity and adiposity in obese. Here, we measured microbial α-glucosidase and β-galactosidase activities and sorted fluorescently labeled β-galactosidase containing (βGAL) microorganisms in faecal samples of eight lean and thirteen obese adolescents that followed a controlled calorie restriction program during one year. β-galactosidase is a highly distributed functional trait, mainly expressed by members of Blautia, Bacteroides, Alcaligenes, Acinetobacter and Propionibacterium. Only long-term calorie restriction induced clear changes in the microbiota of obese adolescents. Long-term calorie restriction induced significant shifts in total and βGAL gut microbiota, reducing the Firmicutes:Bacteroidetes ratio and enhancing the growth of beneficial microorganisms such as Bacteroides, Roseburia, Faecalibacterium and Clostridium XIVa. Moreover, the structure and composition of βGAL community in obese after long-term calorie restriction was highly similar to that of lean adolescents. However, despite this high compositional similarity, microbial metabolic performance was different, split in two metabolic states at a body mass index value of 25. Our study shows that calorie restriction is a strong environmental force reshaping gut microbiota though its metabolic performance is linked to host's adiposity, suggesting that functional redundancy and metabolic plasticity are fundamental properties of gut microbial ecosystem., This work was funded by Carlos III Institute of Health, (Grants PI 051579, PI021513) and the Economy, Industry and Competitiveness Ministry (Grant AGL-11697/ALI). AR and TC received PhD FPU and FPI fellowships, respectively, from the Spanish Ministery of Economy and Competitivity. TC participated in the PhD Program in Biomedicine of the University.

The human nasal passage, from the anterior nares through the nasal vestibule to the nasal cavities, is an important habitat for opportunistic pathogens and commensals alike. This work sampled four different anatomical regions within the human nasal passage across a large cohort of individuals (n = 79) comprising individuals suffering from chronic nasal inflammation clinically known as chronic rhinosinusitis (CRS) and individuals not suffering from inflammation (CRS-free). While individuals had their own unique bacterial fingerprint that was consistent across the anatomical regions, these bacterial fingerprints formed into distinct delineated groups comprising core bacterial members, which were consistent across all four swabbed anatomical regions irrespective of health status. The most significant observed pattern was the difference between the global bacterial profiles of swabbed and tissue biopsy samples from the same individuals, being also consistent across different anatomical regions. Importantly, no statistically significant differences could be observed concerning the global bacterial communities, any of the bacterial species or the range of diversity indices used to compare between CRS and CRS-free individuals, and between two CRS phenotypes (without nasal polyps and with nasal polyps). Thus, the role of bacteria in the pathogenesis of sinusitis remains uncertain.

Additional file 1: Table S1. Characteristics of the substrate used for the mother reactors and the short-term stress test. Each analysis was carried out in triplicate, except for the cation measurements. Table S2 Characteristics of the inoculum used for the mother reactors. Each analysis was carried out in triplicate. Table S3 Characteristics of the inoculum used for the short-term stress test. This inoculum originated from the mixture of the three mother reactors. Each analysis was carried out in triplicate. Table S4 Overview of the P-values of the multivariate abundance model of the 79 phylotypes that had a relative abundance >0.1% in at least one sample, and were present in all samples. Adjusted P-values were determined for salt concentration, time, and the DNA/RNA ratio, as well as the interaction effect between salt concentration and DNA/RNA ratio and time and DNA/RNA ratio. Highlighted P-values are considered significant at α = 0.05. Table S5 Overview of the model coefficients of the multivariate abundance model of the 79 phylotypes that had a relative abundance >0.1% in at least one sample, and were present in all samples. Coefficients were determined for salt concentration, time, and the DNA/RNA ratio, as well as the interaction effect between salt concentration and DNA/RNA ratio and time and DNA/RNA ratio. A negative value indicates a negative effect of salt or time or a DNA/RNA ratio > 1. Fig. S1. Evaluation of model assumptions required to allow correct inference of the multivariate regression model with (a) residuals vs. fitted, (b) scale location, and (c) normal Q–Q results. Each label colour is associated with a single phylotype. These results show that the normality of residuals and homogeneity of variance requirements are fulfilled. Fig. S2 Overview of the main operational parameters of the triplicate mother reactors, including (a) methane production, (b) pH of the reactors (■) and the substrate (●), (c) total VFA, and (d) partial alkalinity (■), total alkalinity (●), and the Ripley index (▲). Fig. S3 Cumulative methane yield of the control treatment (□), and treatments with 5 g Na+ L-1 (○), 10 g Na+ L-1 (■), and 20 g Na+ L-1 (●). Fig. S4 Total VFA, and pH and Na+ concentration in the reactors in the stress test after 14 days of operation. Average values of the triplicate reactors are presented, and error bars show standard deviations. Fig. S5 Rarefaction curves indicating the number of resolved phylotypes against sampling depth of each of the samples (both DNA and RNA) during the 14 days short-term stress test. Fig. S6 Heat map representing the microbial community of all samples on class level at a relative abundance >0.1% averaged over all samples. The colour scale ranges from 0 to 60%. The different samples were labelled according to the time point (T0–T5) and salt concentration (0, 5, 10 and 20 g Na+ L-1). The inoculum sample (Inoc) at the start of the experiment as well as the feed sludge (Sludge) were also included in the heat map. Fig. S7 Heat map representing the microbial community of all samples on order level at a relative abundance >0.1% averaged over all samples. The colour scale ranges from 0 to 70%. The different samples were labelled according to the time point (T0–T5) and salt concentration (0, 5, 10 and 20 g Na+ L-1). The inoculum sample (Inoc) at the start of the experiment as well as the feed sludge (Sludge) were also included in the heat map. Fig. S8 Heat map representing the microbial community of all samples on family level at a relative abundance >0.1% averaged over all samples. The colour scale ranges from 0 to 60%. The different samples were labelled according to the time point (T0–T5) and salt concentration (0, 5, 10 and 20 g Na+ L-1). The inoculum sample (Inoc) at the start of the experiment as well as the feed sludge (Sludge) were also included in the heat map. Figure S9 Non-metric multidimensional scaling analysis of the Bray–Curtis dissimilarity index of the different samples on (a) DNA and (b) RNA levels. Figure S10 Overall microbial community variation between the different samples on DNA (red) and RNA (green) level, determined by the distance to the centroid. The distance to the centroid is significantly higher for the RNA samples than the DNA samples (P < 0.0001). Figure S11 Box plots of the alpha diversity metrics on (a) DNA and (b) RNA levels for the different salt additions, ranging from 0 (Control) to 20 g Na+ L-1. Samples were divided in subgroups per salt concentration for comparison of the alpha diversity metrics. A significant difference between any two salt concentrations is marked with * (P < 0.05), **(P < 0.01), or ***(P < 0.001), based on the ANOVA analysis. Figure S11 Box plots of the alpha diversity metrics on (a) DNA and (b) RNA levels for the different salt additions, ranging from 0 (Control) to 20 g Na+ L-1. Samples were divided in subgroups per salt concentration for comparison of the alpha diversity metrics. A significant difference between any two salt concentrations is marked with *(P < 0.05), **(P < 0.01), or ***(P < 0.001), based on the ANOVA analysis.