Identification of weak and gender specific effects in a short 3 weeks intervention study using barley and oat mixed linkage β-glucan dietary supplements:a human fecal metabolome study by GC-MS

Introduction: Mixed-linkage (1\ue2\u86\u923),(1\ue2\u86\u924)-\uce\ub2-d-glucans (BG) reduce cholesterol level and insulin response in humans. Despite this, their role in human metabolism and a mode of action remains largely unknown. Objectives: To investigate the effects of three structurally different BG on human fecal metabolome in a full cross-over intervention using GC-MS metabolomics. Methods: Over three weeks of intervention, young healthy adults received food supplemented with BG from oat, two different BG from barley or a non-fiber control in a full cross-over design. Untargeted metabolomics and short chain fatty acid analysis was performed on day three fecal samples. ANOVA-simultaneous component analysis was applied to partition the data variation according to the study design, and PLS-DA was used to select most discriminative metabolite markers. Results: Univariate and multivariate data analysis revealed a dominating effect of inter-individual variances followed by a gender effect. Weak effects of BG intake were identified including an increased level of gamma-amino-butyrate and palmitoleic acid in males and a decreased level of enterolactone in females. Barley and oat derived BG were found to influence the human fecal metabolome differently. Barley BG increased the relative level of formate in males and isobutyrate, isovalerate, 2-methylbutyrate in females. In total 15, 3 and 11 human fecal metabolites were significantly different between control vs. BG, control vs. oat BG, and barley BG vs. oat BG, respectively. Conclusions: The study show that human fecal metabolome largely reflects individual (\ue2\u88\ubc28% variation) and gender (\ue2\u88\ubc15% variation) differences, whereas the treatment\uc2\ua0effect of the BG (\ue2\u88\ubc8% variation) only manifests in a few key metabolites (primarily by the metabolites: d-2-aminobutyric acid, palmitoleic acid, linoleic acid and 11-eicosenoic acid)

Optimizing protocols for extraction of bacteriophages prior to metagenomic analyses of phage communities in the human gut

BACKGROUND: The human gut is densely populated with archaea, eukaryotes, bacteria, and their viruses, such as bacteriophages. Advances in high-throughput sequencing (HTS) as well as bioinformatics have opened new opportunities for characterizing the viral communities harbored in our gut. However, limited attention has been given to the efficiency of protocols dealing with extraction of phages from fecal communities prior to HTS and their impact on the metagenomic dataset. RESULTS: We describe two optimized methods for extraction of phages from fecal samples based on tangential-flow filtration (TFF) and polyethylene glycol precipitation (PEG) approaches using an adapted method from a published protocol as control (literature-adapted protocol (LIT)). To quantify phage recovery, samples were spiked with low numbers of c2, ϕ29, and T4 phages (representatives of the Siphoviridae, Podoviridae, and Myoviridae families, respectively) and their concentration (plaque-forming units) followed at every step during the extraction procedure. Compared with LIT, TFF and PEG had higher recovery of all spiked phages, yielding up to 16 times more phage particles (PPs) and up to 68 times more phage DNA per volume, increasing thus the chances of extracting low abundant phages. TFF- and PEG-derived metaviromes showed 10 % increase in relative abundance of Caudovirales and unclassified phages infecting gut-associated bacteria (>92 % for TFF and PEG, 82.4 % for LIT). Our methods obtained lower relative abundance of the Myoviridae family (<16 %) as compared to the reference protocol (22 %). This decline, however, was not considered a true loss of Myoviridae phages but rather a greater level of extraction of Siphoviridae phages (TFF and PEG >32.5 %, LIT 22.6 %), which was achieved with the enhanced conditions of our procedures (e.g., reduced filter clogging). A high degree of phage diversity in samples extracted using TFF and PEG was documented by transmission electron microscopy. CONCLUSIONS: Two procedures (TFF and PEG) for extraction of bacteriophages from fecal samples were optimized using a set of spiked bacteriophages as process control. These protocols are highly efficient tools for extraction and purification of PPs prior to HTS in phage-metavirome studies. Our methods can be easily modified, being thus applicable and adjustable for in principle any solid environmental material in dissolution. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-015-0131-4) contains supplementary material, which is available to authorized users

Oligosaccharide equine feed supplement, Immulix, has minor impact on vaccine responses in mice

Several mammalian species are vaccinated in early life, but little is known about the effect of diet on vaccine response. Oligosaccharides are increasingly proposed as dietary supplement for young individuals due to their anti-inflammatory potential elicited through modulation of gut microbiota (GM). Also, diet, e.g. the size of the fat fraction, is known to modulate the GM. We tested if an oligosaccharide diet (Immulix) and/or increased dietary fat content affected antibody titers to a tetanus vaccine in 48 BALB/cJTac mice through GM modulation. Female mice had significantly higher IgG titers with higher variation compared to male mice. The effects of Immulix and/or increased fat content were minor. Immulix negatively affected IgG titers in male mice four weeks after secondary vaccination but upregulated Il1b gene expression in the spleen. Immulix had a downregulating effect on expression of Cd4 and Foxp3 in ileum only if the mice were fed the diet with increased fat. The diet with increased dietary fat increased Il1b but decreased Cd8a gene expression in the spleen. Immulix and diet affected GM composition significantly. Increased dietary fat content upregulated Lactobacillus animalis but downregulated an unclassified Prevotella spp. Immulix decreased Lactobacillales, Streptococcaceae and Prevotellaceae but increased Bacteroides. It is concluded that in spite of some minor influences on immune cell markers, cytokines and IgG titers Immulix feeding or increased dietary fat content did not have any biologically relevant effects on tetanus vaccine responses in this experiment in mice

Host-Specific and pH-Dependent Microbiomes of Copepods in an Extensive Rearing System

<div><p>Copepods are to an increasing extent cultivated as feed for mariculture fish larvae with variable production success. In the temperate climate zone, this production faces seasonal limitation due to changing abiotic factors, in particular temperature and light. Furthermore, the production of copepods may be influenced by biotic factors of the culture systems, such as competing microorganisms, harmful algae, or other eukaryotes and prokaryotes that may be non-beneficial for the copepods. In this study, the composition of bacteria associated with copepods was investigated in an extensive outdoor copepod production system. Light microscopy and scanning electron microscopy revealed that bacteria were primarily found attached to the exoskeleton of copepods although a few bacteria were also found in the gut as well as internally in skeletal muscle tissue. Through 16S rRNA gene-targeted denaturing gradient gel electrophoresis (DGGE) analysis, a clear difference was found between the microbiomes of the two copepod species, <i>Acartia tonsa</i> and <i>Centropages hamatus</i>, present in the system. This pattern was corroborated through 454/FLX-based 16S rRNA gene amplicon sequencing of copepod microbiomes, which furthermore showed that the abiotic parameters pH and oxygen concentration in rearing tank water were the key factors influencing composition of copepod microbiomes.</p></div

Fluorescent <i>in situ</i> hybridization of copepod (<i>C</i>. <i>hamatus</i>) thin sections stained with the universal bacterial Cy3-labelled probe EUB338.

<p>Pictures are overlays of two photographs made with filter sets for Cy3 (red) and autofluorescence (green), respectively. A. Exoskeleton with clusters of bacteria attached at outer part of depressions. B. Section of gut showing isolated rod-shaped bacteria. C. Potential bacteria (arrowhead) in skeletal muscle. Note that exoskeleton typically fluoresces with similar colour as the Cy3-labelled probe. Cop = copepod; ex = exoskeleton; lu = gut lumen; gw = gut wall.</p

PCoA plot of the microbiomes of <i>Centropages hamatus</i> under low (blue) and high pH (yellow).

<p>The plot is based on distance matrices determined by the Jackknife Beta Diversity workflow. Differences between microbiomes were assessed using ANOSIM (<i>p</i> = 0.005, <i>r</i> = 0.34). The ellipsoids depict the degree of variation for each sample.</p

Variations in operational taxonomic unit composition between the microbiomes of <i>C</i>. <i>hamatus</i> collected under low pH (<8.8) and high pH (≥8.8) conditions.

<p><i>* p-</i> and <i>q-</i>values were determined with ANOVA; <i>q-</i> values represent Bonferroni correction; ANOVA was performed using 1,000 subsampled OTU tables.</p><p>Variations in operational taxonomic unit composition between the microbiomes of <i>C</i>. <i>hamatus</i> collected under low pH (<8.8) and high pH (≥8.8) conditions.</p

Relative distribution of bacterial 16s rRNA gene sequence reads in 10 out of a total of 28 454/FLX-based 16S rRNA gene amplicon sequencing samples.

<p>Samples are (in pairs): <i>Acartia tonsa</i> from laboratory culture (left two columns), and <i>A</i>. <i>tonsa</i> and <i>Centropages hamatus</i> from large-scale outdoor cultivation tanks. Outdoor samples are from two different dates in August 2012, representing different pH-levels in cultivation tanks. See text for detailed information. *) The left <i>A</i>. <i>tonsa</i> lab culture sample yielded less than 1,405 reads and both of these were, therefore, excluded from subsequent statistical analysis. OUTs representing less than 2% of total bacteria sequences are included in the group ‘Others + unassigned’.</p