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Metabolic inflammation mediated obesity requires bacterial molecules to trigger immune and adipose cells leading to inflammation and adipose depot development. Beside the established gut microbiota dysbiosis we and others identified a leaky gut in obese patients and animal models as notably characterized by the existence of a tissue microbiota in the adipose fat pads. To identify its potential role, we here sequenced the bacterial 16S rRNA genes within the visceral adipose depot of obese patients. Immense surgical, biochemical and bioinformatic care were taken to avoid environmental contaminants. We performed different statistical discriminant analyses to identify specific signatures and constructed network of interactions between variables. The data show that a specific 16SrRNA gene signature was composed of numerous bacterial families discriminating lean versus obese and extremely obese patients. Burkholderiaceae, Yearsiniaceae, and Xanthomonadaceae were the main discriminant families, notably all gram negative. Interestingly, the Morganellaceae were totally absent from non-obese while preponderant in all obese patients. To generate hypotheses regarding their potential role we inferred metabolic pathways from the 16SrRNA gene signatures. We identified several pathways associated with adenosyl-cobalamine previously described to be linked with adipose tissue development. We further identified chorismate biosynthesis involved in aromatic amino-acid metabolism which could be important players. This innovative approach generates novel hypotheses regarding the gut to adipose tissue axis in obesity.

Background IgA nephropathy (IgAN) has been associated with gut dysbiosis, intestinal membrane disruption, and translocation of bacteria into blood. Our study aimed to understand the association of gut and blood microbiomes in patients with IgAN in relation to healthy controls. Methods We conducted a case-control study with 20 patients with progressive IgAN, matched with 20 healthy controls, and analyzed bacterial DNA quantitatively in blood using 16S PCR and qualitatively in blood and stool using 16S metagenomic sequencing. We conducted between-group comparisons as well as comparisons between the blood and gut microbiomes. Results Higher median 16S bacterial DNA in blood was found in the IgAN group compared with the healthy controls group (7410 versus 6030 16S rDNA copies/μl blood, P=0.04). α- and β-Diversity in both blood and stool was largely similar between the IgAN and healthy groups. In patients with IgAN, in comparison with healthy controls, we observed higher proportions of the class Coriobacteriia and species of the genera Legionella, Enhydrobacter, and Parabacteroides in blood, and species of the genera Bacteroides, Escherichia-Shigella, and some Ruminococcus in stool. Taxa distribution were markedly different between the blood and stool samples of each subject in both IgAN and healthy groups, without any significant correlation between corresponding gut and blood phyla. Conclusions Important bacterial taxonomic differences, quantitatively in blood and qualitatively in both blood and stool samples, that were detected between IgAN and healthy groups warrant further investigation into their roles in the pathogenesis of IgAN. Although gut bacterial translocation into blood may be one of the potential sources of the blood microbiome, marked taxonomic differences between gut and blood samples in each subject in both groups confirms that the blood microbiome does not directly reflect the gut microbiome. Further research is needed into other possible sites of origin and internal regulation of the blood microbiome.

Visceral obesity is a key risk factor for type 2 diabetes (T2D). Whereas gut dysbiosis appears to be instrumental for this relationship, whether gut-associated signatures translocate to extra-intestinal tissues and how this affects host metabolism remain elusive. Here we provide a comparative analysis of the microbial profile found in plasma, liver and in three distinct adipose tissues of individuals with morbid obesity. We explored how these tissue microbial signatures vary between individuals with normoglycaemia and those with T2D that were matched for body mass index. We identified tissue-specific signatures with higher bacterial load in the liver and omental adipose tissue. Gut commensals, but also environmental bacteria, showed tissue- and T2D-specific compartmentalisation. T2D signatures were most evident in mesenteric adipose tissue, in which individuals with diabetes displayed reduced bacterial diversity concomitant with fewer Gram-positive bacteria, such as Faecalibacterium, as opposed to enhanced levels of typically opportunistic Gram-negative Enterobacteriaceae. Plasma samples of individuals with diabetes were similarly enriched in Enterobacteriaceae, including the pathobiont Escherichia-Shigella. Our work provides evidence for the presence of selective plasma and tissue microbial signatures in individuals with severe obesity and identifies new potential microbial targets and biomarkers of T2D.

The gut–brain–beta cell glucagon-like peptide-1 (GLP-1)-dependent axis and the clock genes both control insulin secretion. Evidence shows that a keystone of this molecular interaction could be the gut microbiota. We analyzed in mice the circadian profile of GLP-1 sensitivity on insulin secretion and the impact of the autonomic neuropathy, antibiotic treated in different diabetic mouse models and in germ-free colonized mice. We show that GLP-1sensitivity is maximal during the dark feeding period, i.e., the postprandial state. Coincidently, the ileum expression of GLP-1 receptor and peripherin is increased and tightly correlated with a subset of clock gene. Since both are markers of enteric neurons, it suggests a role in the gut–brain–beta cell GLP-1-dependent axis. We evaluated the importance of gut microbiota dysbiosis and found that the abundance of ileum bacteria, particularly Ruminococcaceae and Lachnospiraceae, oscillated diurnally, with a maximum during the dark period, along with expression patterns of a subset of clock genes. This diurnal pattern of circadian gene expression and Lachnospiraceae abundance was also observed in two separate mouse models of gut microbiota dysbiosis and of autonomic neuropathy with impaired GLP-1 sensitivity (1.high-fat diet-fed type 2 diabetic, 2.antibiotic-treated/germ-free mice). Our data show that GLP-1 sensitivity relies on specific pattern of intestinal clock gene expression and specific gut bacteria. This new statement opens opportunities to treat diabetic patient with GLP-1-based therapies by using on a possible pre/probiotic co-treatment to improve the time-dependent efficiency of these therapies.

In this chapter, a theoretical study relying on the thermal modelling of a Curie wheel, used for the conversion of low-grade waste heat into electrical power, is presented. It allows understanding the thermal behaviour of a Curie wheel operating in steady state in order to optimise its design. To this end, a stationary one-dimensional analytical thermal model, based on a Lagrangian approach, was developed. It allows determining the local distribution over time of the temperature in the magnetocaloric material exposed to a periodic sinusoidal heat source. Thanks to this model, the effects of different parameters (nature of the magnetocaloric material, nature and temperature of the fluid) were determined and analysed.

The intestinal microbiota to immune system crosstalk is a major regulator of metabolism and hence metabolic diseases. An impairment of the chemokine receptor CX3CR1, as a key regulator shaping intestinal microbiota under normal chow feeding, could be one of the early events of dysglycemia. We studied the gut microbiota ecology by sequencing the gut and tissue microbiota. We studied its role in energy metabolism in CX3CR1-deficent and control mice using various bioassays notably the glycemic regulation during fasting and the respiratory quotient as two highly sensitive physiological features. We used antibiotics and prebiotics treatments, and germ free mouse colonization. We identify that CX3CR1 disruption impairs gut microbiota ecology and identified a specific signature associated to the genotype. The glycemic control during fasting and the respiratory quotient throughout the day are deeply impaired. A selected four-week prebiotic treatment modifies the dysbiotic microbiota and improves the fasting state glycemic control of the CX3CR1-deficent mice and following a glucose tolerance test. A 4 week antibiotic treatment also improves the glycemic control as well. Eventually, germ free mice colonized with the microbiota from CX3CR1-deficent mice developed glucose intolerance. CX3CR1 is a molecular mechanism in the control of the gut microbiota ecology ensuring the maintenance of a steady glycemia and energy metabolism. Its impairment could be an early mechanism leading to gut microbiota dysbiosis and the onset of metabolic disease.

[EN] Human immunodeficiency virus (HIV) infection impairs mucosal immunity and leads to bacterial translocation, fueling chronic inflammation and disease progression. While this is well established, questions remain about the compositional profile of the translocated bacteria, and to what extent it is influenced by antiretroviral therapy (ART). Using 16S ribosomal DNA targeted sequencing and shotgun proteomics, we showed that HIV increases bacterial translocation from the gut to the blood. HIV increased alpha diversity in the blood, which was dominated by aerobic bacteria belonging to Micrococcaceae (Actinobacteria) and Pseudomonadaceae (Proteobacteria) families, and the number of circulating bacterial proteins was also increased. Forty-eight weeks of ART attenuated this phenomenon. We found that enrichment with Lactobacillales order, and depletion of Actinobacteria class and Moraxellaceae and Corynebacteriacae families, were significantly associated with greater immune recovery and correlated with several inflammatory markers. Our findings suggest that the molecular cross talk between the host and the translocated bacterial products could influence ART-mediated immune recovery., This work was supported by the Instituto de Salud Carlos III (Plan Estatal de I+D+i 2013–2016, projects PI15/00345 and PI18/00154); the Fundación Asociación Española Contra el Cáncer within the European Research Era-NET aligning national/regional translational cancer research programs and activities program (grant AC17/00019) and cofinanced by the European Development Regional Fund; and Plan Estatal de I+D+i 2013–2016 (grant PT17/0019 to the Proteomics Facility of the Spanish National Center for BIotechnology).

To understand the pathophysiological impact of liver microbiota on the early stages of fibrosis we identified the corresponding microbiota sequences and overcome the impact of different group size and patient origins with adapted statistical approaches. Liver samples with low liver fibrosis scores (F0, F1, F2) were collected from Romania(n=36), Austria(n=10), Italy(n=19), and Spain(n=17). The 16SrDNA gene was sequenced. We considered the frequency, sparsity, unbalanced sample size between cohorts to identify taxonomic profiles and statistical differences. Multivariate analyses, including adapted spectral clustering with L1-penalty fair-discriminant strategies, and predicted metagenomics were used to identify that 50 % of liver taxa were Enterobacteriaceae and Pseudomonadaceae. The Caulobacteraceae, Flavobacteriaceae and Propionibacteriaceae discriminated between F0 and F1. The preQ0 biosynthesis and pathways involving glucoryranose and glycogen degradation were negatively associated with liver fibrosis F1-F2 vs F0. Altogether, our results suggest a role of bacterial translocation to the liver in the progression of fibrosis. This statistical approach can identify microbial signatures and overcome issues regarding sample size differences, the impact of environment, and sets of analyses.

Visceral obesity is a key risk factor for type 2 diabetes (T2D). Whereas gut dysbiosis appears to be instrumental for this relationship, whether gut-associated signatures translocate to extra-intestinal tissues and how this affects host metabolism remain elusive. Here we provide a comparative analysis of the microbial profile found in plasma, liver and in three distinct adipose tissues of individuals with morbid obesity. We explored how these tissue microbial signatures vary between individuals with normoglycaemia and those with T2D that were matched for body mass index. We identified tissue-specific signatures with higher bacterial load in the liver and omental adipose tissue. Gut commensals, but also environmental bacteria, showed tissue- and T2D-specific compartmentalisation. T2D signatures were most evident in mesenteric adipose tissue, in which individuals with diabetes displayed reduced bacterial diversity concomitant with fewer Gram-positive bacteria, such as Faecalibacterium, as opposed to enhanced levels of typically opportunistic Gram-negative Enterobacteriaceae. Plasma samples of individuals with diabetes were similarly enriched in Enterobacteriaceae, including the pathobiont Escherichia-Shigella. Our work provides evidence for the presence of selective plasma and tissue microbial signatures in individuals with severe obesity and identifies new potential microbial targets and biomarkers of T2D.

International audience; This article provides guidelines to design porous silicon (PS) layers regarding optimization of small signal properties in passive structures for radio frequency (RF): insertion loss and crosstalk. Results are based on high-frequency measurements on 200-mm wafers and electromagnetic simulations up to 40 GHz. Using substrate resistivity below 1 Ohm.cm allows the best tradeoff with minimized PS thickness.

The past two decades of research have raised gut microbiota composition as a contributing factor to the development of obesity, and higher abundance of certain bacterial species has been linked to the lean phenotype, such as Akkermansia muciniphila. The ability of pre- and probiotics to affect metabolic health could be via microbial community alterations and subsequently changes in metabolite profiles, modulating for example host energy balance via complex signaling pathways. The aim of this mice study was to determine how administration of a prebiotic fiber, polydextrose (PDX) and a probiotic Bifidobacterium animalis ssp. lactis 420 (B420), during high fat diet (HFD; 60 kcal% fat) affects microbiota composition in the gastrointestinal tract and adipose tissue, and metabolite levels in gut and liver. In this study C57Bl/6J mice (N = 200) were split in five treatments and daily gavaged: 1) Normal control (NC); 2) HFD; 3) HFD + PDX; 4) HFD + B420 or 5) HFD + PDX + B420 (HFD+S). At six weeks of treatment intraperitoneal glucose-tolerance test (IPGTT) was performed, and feces were collected at weeks 0, 3, 6 and 9. At end of the intervention, ileum and colon mucosa, adipose tissue and liver samples were collected. The microbiota composition in fecal, ileum, colon and adipose tissue was analyzed using 16S rDNA sequencing, fecal and liver metabolomics were performed by nuclear magnetic resonance (NMR) spectroscopy. It was found that HFD+PDX intervention reduced body weight gain and hepatic fat compared to HFD. Sequencing the mice adipose tissue (MAT) identified Akkermansia and its prevalence was increased in HFD+S group. Furthermore, by the inclusion of PDX, fecal, lleum and colon levels of Akkermansia were increased and liver health was improved as the detoxification capacity and levels of methyl-donors were increased. These new results demonstrate how PDX and B420 can affect the interactions between gut, liver and adipose tissue.

The increase in active component switching frequency, via GaN technology, allows downscaling the inductor size as soon as the magnetic core-losses are controlled. However frequency induced dissipations in the magnetic material will create thermal heating, consequently complex core shapes allowing a better thermal exchange are needed. Here we propose a specific dimensioning methodology to determine the best form factor to optimise the exchange surface and verify constraints on the inductor. An inductor made of NiZn spinel ferrite powder has been manufactured by tape casting using results of calculations based on magnetic core-loss measurements.

Background The role of bacteria on the onset of cardiovascular disease has been suggested. Reciprocally, increased intestinal bacterial translocation and bloodstream infection are common comorbidities associated with heart failure and myocardial infarction ( MI ). In this context, the aim of this study was to analyze the blood microbiome in patients shortly after acute myocardial infarction. Methods and Results We carried out a case control study comparing 103 patients at high cardiovascular risk but free of coronary disease and 99 patients who had an MI . The blood microbiome was analyzed both quantitatively by 16S quantitative polymerase chain reaction and qualitatively by 16S targeted metagenomic sequencing specifically optimized for blood samples. A significant increase in blood bacterial 16S rDNA concentration was observed in patients admitted for MI . This increase in blood bacterial DNA concentration was independent of post‐ MI left ventricular function and was more marked in patients with low‐density lipoprotein cholesterol ≥1 g/L. In addition, differences in the proportion of numerous bacterial taxa in blood were significantly modified with the onset of MI , thus defining a blood microbiota signature of MI . Among the bacterial taxa whose proportions are decreased in patients with MI , at least 6 are known to include species able to metabolize cholesterol. Conclusions These results could provide the basis for the identification of blood microbiome‐based biomarkers for the stratification of MI patients. Furthermore, these findings should provide insight into the mechanism underlying the negative correlation reported between low‐density lipoprotein cholesterol concentration and the prognosis at the acute onset of MI and mortality. Clinical Trial Registration URL : http://www.clinicaltrials.gov . Unique identifier: NCT 02405468.

Some obese subjects overeat lipid-rich foods. The origin of this eating behavior is unknown. We have here tested the hypothesis that these subjects could be characterized by an impaired fatty taste sensitivity linked to a change in the gustatory papillae microbial and salivary environment. The composition of microbiota and saliva surrounding the circumvallate papillae was analyzed in combination with the orosensory lipid detection threshold in normal weight (NW) and obese (O) adults. Microbial architecture was similar to what was known in feces, but with an increased frequency of Proteobacteria. No difference in the orosensory sensitivity to lipids and composition of oral microbiota and saliva was observed between NW and O subjects. By contrast, specific bacterial and salivary signatures were found in lipid non-tasters, irrespectively of BMI. A multivariate approach highlighted that the salivary flow, lysozyme activity, total antioxidant capacity and TM7 bacterial family discriminated between tasters and non-tasters. Subgroup analysis of obese tasters (OT) versus obese non-tasters (ONT) identified specific bacterial metabolic pathways (i.e. phosphotransferase and simple sugar transport systems) as being higher in ONT. Altogether with the identification of a set of significant salivary variables, our study suggests that an “obese tongue” phenotype is associated with decreased orosensory sensitivity to lipids in some obese subjects.

In this work, we first present the composition dependence of the magnetocaloric properties in the Y2Fe17-xCox series.Then, we show preliminary results on our shaping works. In order to use the Y2Fe17-xCox compounds in magnetocaloric heat conversion systems, we applied powder metallurgy technics at a semi industrial scale to shape it. That involves milling, sintering, and heat treatments.Finally, the emphasis has been laid on the thermal properties of the sintered material, considering their decisive influence on the performance of the system.

Objective To demonstrate that glycemia and insulin resistance are controlled by a mechanism involving the adaptive immune system and gut microbiota crosstalk. Methods We triggered the immune system with microbial extracts specifically from the intestinal ileum contents of HFD-diabetic mice by the process of immunization. 35 days later, immunized mice were fed a HFD for up to two months in order to challenge the development of metabolic features. The immune responses were quantified. Eventually, adoptive transfer of immune cells from the microbiota-immunized mice to naïve mice was performed to demonstrate the causality of the microbiota-stimulated adaptive immune system on the development of metabolic disease. The gut microbiota of the immunized HFD-fed mice was characterized in order to demonstrate whether the manipulation of the microbiota to immune system interaction reverses the causal deleterious effect of gut microbiota dysbiosis on metabolic disease. Results Subcutaneous injection (immunization procedure) of ileum microbial extracts prevented hyperglycemia and insulin resistance in a dose-dependent manner in response to a HFD. The immunization enhanced the proliferation of CD4 and CD8 T cells in lymphoid organs, also increased cytokine production and antibody secretion. As a mechanism explaining the metabolic improvement, the immunization procedure reversed gut microbiota dysbiosis. Finally, adoptive transfer of immune cells from immunized mice improved metabolic features in response to HFD. Conclusions Glycemia and insulin sensitivity can be regulated by triggering the adaptive immunity to microbiota interaction. This reduces the gut microbiota dysbiosis induced by a fat-enriched diet., Highlights • Triggering adaptive immune response with ileum bacteria extracts prevents HFD-induced metabolic disease. • Triggering adaptive immune response with ileum bacteria extracts improves gut microbiota dysbiosis. • Triggering adaptive immune response with ileum bacteria extract regulates the intestinal immune system. • First microbiota based vaccination strategy of metabolic disease.

BACKGROUND Recent studies have revealed that the blood of healthy humans is not as sterile as previously supposed. The objective of this study was to provide a comprehensive description of the microbiome present in different fractions of the blood of healthy individuals. STUDY DESIGN AND METHODS The study was conducted in 30 healthy blood donors to the French national blood collection center (Etablissement Francais du Sang). We have set up a 16S rDNA quantitative polymerase chain reaction assay as well as a 16S targeted metagenomics sequencing pipeline specifically designed to analyze the blood microbiome, which we have used on whole blood as well as on different blood fractions (buffy coat [BC], red blood cells [RBCs], and plasma). RESULTS Most of the blood bacterial DNA is located in the BC (93.74%), and RBCs contain more bacterial DNA (6.23%) than the plasma (0.03%). The distribution of 16S DNA is different for each fraction and spreads over a relatively broad range among donors. At the phylum level, blood fractions contain bacterial DNA mostly from the Proteobacteria phylum (more than 80%) but also from Actinobacteria, Firmicutes, and Bacteroidetes. At deeper taxonomic levels, there are striking differences between the bacterial profiles of the different blood fractions. CONCLUSION We demonstrate that a diversified microbiome exists in healthy blood. This microbiome has most likely an important physiologic role and could be implicated in certain transfusion-transmitted bacterial infections. In this regard, the amount of 16S bacterial DNA or the microbiome profile could be monitored to improve the safety of the blood supply.

Background and objectives The association between gut dysbiosis, high intestinal permeability, and endotoxemia-mediated inflammation is well established in CKD. However, changes in the circulating microbiome in patients with CKD have not been studied. In this pilot study, we compare the blood microbiome profile between patients with CKD and healthy controls using 16S ribosomal DNA sequencing. Design, setting, participants, & measurements Blood bacterial DNA was studied in buffy coat samples quantitatively by 16S PCR and qualitatively by 16S targeted metagenomic sequencing using a molecular pipeline specifically optimized for blood samples in a cross-sectional study comparing 20 nondiabetic patients with CKD and 20 healthy controls. Results There were 22 operational taxonomic units significantly different between the two groups. 16S metagenomic sequencing revealed a significant reduction in α diversity (Chao1 index) in the CKD group compared with healthy controls (127±18 versus 145±31; P =0.04). Proteobacteria phylum, Gammaproteobacteria class, and Enterobacteriaceae and Pseudomonadaceae families were more abundant in the CKD group compared with healthy controls. Median 16S ribosomal DNA levels did not significantly differ between CKD and healthy groups (117 versus 122 copies/ng DNA; P =0.38). GFR correlated inversely with the proportion of Proteobacteria ( r =−0.54; P ≤0.01). Conclusions Our pilot study demonstrates qualitative differences in the circulating microbiome profile with lower α diversity and significant taxonomic variations in the blood microbiome in patients with CKD compared with healthy controls.

Author Correction: obese subjects with specifc gustatory papillae microbiota and salivary cues display an impairment to sense lipids Correction to: Scientifc Reports https://doi.org/10.1038/s41598-018-24619-1, published online 30 April 2018; International audience; A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

We agree with Hornung et al 1 that studying blood microbiome is a major technical challenge with potential artefacts. At least three important challenges must be tackled: 1. Low amount of bacterial DNA in blood.2 2. High amounts of PCR inhibitors. 3. Bacterial DNA contaminants from environment, reagents and consumables. Measuring, reducing and controlling bacterial contaminants are key elements of optimisations made on the molecular pipeline used in our study3 as well as eight published studies on blood microbiome.2 4–7 The studies from Salter et al 8 and Laurence et al 9 are useful to understand the burden of bacterial contaminants when working with low bacterial abundance samples. In former publications,2 10 we have described our procedure and the controls performed to address such contamination. One must be careful when using a fixed list of bacterial contaminants, as each experiment has its own contamination burden. Therefore, two different experiments done under different conditions, will not have the same contaminants. What is essential, as pointed out by Hornung et al , is to include and analyse negative controls in each experiment. Although not explicitly mentioned before, our study3 included the following negative controls: 1. Extraction negative controls (water at DNA extraction step). 2. PCR negative controls (water at first PCR step). We …

International audience; A theoretical study relying on the thermal modelling of a Curie wheel, used for the conversion of low-grade waste heat into electrical power, is presented in this paper. It allows understanding the thermal behaviour of a Curie wheel operating in steady state in order to optimise its design. To this end, a stationary one-dimensional analytical thermal model, based on a Lagrangian approach, was developed. It allows determining the local distribution over time of the temperature in the magnetocaloric material exposed to a periodic sinusoidal heat source. Thanks to this model, the effects of different parameters (nature of the magnetocaloric material, nature and temperature of the fluid) were highlighted and studied.

The early detection of liver fibrosis among patients with nonalcoholic fatty liver disease (NAFLD) is an important clinical need. In view of the suggested role played by bacterial translocation in liver disease and obesity, we sought to investigate the relationship between blood microbiota and liver fibrosis (LF) in European cohorts of patients with severe obesity. We carried out a cross-sectional study of obese patients, well characterized with respect to the severity of the NAFLD, in the cohort FLORINASH. This cohort has been divided into a discovery cohort comprising 50 Spanish patients and then in a validation cohort of 71 Italian patients. Blood bacterial DNA was analyzed both quantitatively by 16S ribosomal DNA (rDNA) quantitative polymerase chain reaction and qualitatively by 16S rDNA targeted metagenomic sequencing and functional metagenome prediction. Spanish plasma bile acid contents were analyzed by liquid chromatography/mass spectrometry. The 16S rDNA concentration was significantly higher in patients of the discovery cohort with LF. By 16S sequencing, we found specific differences in the proportion of several bacterial taxa in both blood and feces that correlate with the presence of LF, thus defining a specific signature of the liver disease. Several secondary/primary bile acid ratios were also decreased with LF in the discovery cohort. We confirmed, in the validation cohort, the correlation between blood 16S rDNA concentration and LF, whereas we did not confirm the specific bacterial taxa signature, despite a similar trend in patients with more-severe fibrosis.Changes in blood microbiota are associated with LF in obese patients. Blood microbiota analysis provides potential biomarkers for the detection of LF in this population. (Hepatology 2016;64:2015-2027).

Recent studies have revealed that the blood of healthy humans is not as sterile as previously supposed. The objective of this study was to provide a comprehensive description of the microbiome present in different fractions of the blood of healthy individuals.The study was conducted in 30 healthy blood donors to the French national blood collection center (Établissement Français du Sang). We have set up a 16S rDNA quantitative polymerase chain reaction assay as well as a 16S targeted metagenomics sequencing pipeline specifically designed to analyze the blood microbiome, which we have used on whole blood as well as on different blood fractions (buffy coat [BC], red blood cells [RBCs], and plasma).Most of the blood bacterial DNA is located in the BC (93.74%), and RBCs contain more bacterial DNA (6.23%) than the plasma (0.03%). The distribution of 16S DNA is different for each fraction and spreads over a relatively broad range among donors. At the phylum level, blood fractions contain bacterial DNA mostly from the Proteobacteria phylum (more than 80%) but also from Actinobacteria, Firmicutes, and Bacteroidetes. At deeper taxonomic levels, there are striking differences between the bacterial profiles of the different blood fractions.We demonstrate that a diversified microbiome exists in healthy blood. This microbiome has most likely an important physiologic role and could be implicated in certain transfusion-transmitted bacterial infections. In this regard, the amount of 16S bacterial DNA or the microbiome profile could be monitored to improve the safety of the blood supply.

SummaryA high-fat diet (HFD) induces metabolic disease and low-grade metabolic inflammation in response to changes in the intestinal microbiota through as-yet-unknown mechanisms. Here, we show that a HFD-derived ileum microbiota is responsible for a decrease in Th17 cells of the lamina propria in axenic colonized mice. The HFD also changed the expression profiles of intestinal antigen-presenting cells and their ability to generate Th17 cells in vitro. Consistent with these data, the metabolic phenotype was mimicked in RORγt-deficient mice, which lack IL17 and IL22 function, and in the adoptive transfer experiment of T cells from RORγt-deficient mice into Rag1-deficient mice. We conclude that the microbiota of the ileum regulates Th17 cell homeostasis in the small intestine and determines the outcome of metabolic disease.

BackgroundSubstantial progress in high-throughput metagenomic sequencing methodologies has enabled the characterisation of bacteria from various origins (for example gut and skin). However, the recently-discovered bacterial microbiota present within animal internal tissues has remained unexplored due to technical difficulties associated with these challenging samples.ResultsWe have optimized a specific 16S rDNA-targeted metagenomics sequencing (16S metabarcoding) pipeline based on the Illumina MiSeq technology for the analysis of bacterial DNA in human and animal tissues. This was successfully achieved in various mouse tissues despite the high abundance of eukaryotic DNA and PCR inhibitors in these samples. We extensively tested this pipeline on mock communities, negative controls, positive controls and tissues and demonstrated the presence of novel tissue specific bacterial DNA profiles in a variety of organs (including brain, muscle, adipose tissue, liver and heart).ConclusionThe high throughput and excellent reproducibility of the method ensured exhaustive and precise coverage of the 16S rDNA bacterial variants present in mouse tissues. This optimized 16S metagenomic sequencing pipeline will allow the scientific community to catalogue the bacterial DNA profiles of different tissues and will provide a database to analyse host/bacterial interactions in relation to homeostasis and disease.

InterPro, an integrated documentation resource of protein families, domains and functional sites, was created in 1999 as a means of amalgamating the major protein signature databases into one comprehensive resource. PROSITE, Pfam, PRINTS, ProDom, SMART and TIGRFAMs have been manually integrated and curated and are available in InterPro for text- and sequence-based searching. The results are provided in a single format that rationalises the results that would be obtained by searching the member databases individually. The latest release of InterPro contains 5629 entries describing 4280 families, 1239 domains, 95 repeats and 15 post-translational modifications. Currently, the combined signatures in InterPro cover more than 74% of all proteins in SWISS-PROT and TrEMBL, an increase of nearly 15% since the inception of InterPro. New features of the database include improved searching capabilities and enhanced graphical user interfaces for visualisation of the data. The database is available via a webserver (http://www.ebi.ac.uk/interpro) and anonymous FTP (ftp://ftp.ebi.ac.uk/pub/databases/interpro).

International audience; Recent progress in genotyping and resequencing techniques have opened new opportunities for deciphering quantitative trait variation by looking for associations between traits of interest and polymorphisms in panels of diverse inbred lines. Association mapping raises specific issues related to the choice of appropriate (i) panels and marker-densities and (ii) statistical methods to capture associations. In this study, we used a panel of 314 maize inbred lines from the dent pool, composed of inbred material from public institutes (113 inbred lines) and a private company (201 inbred lines). We showed that local LD was higher and genetic diversity lower in the material of private origin than in the public material. We compared the results obtained by different software for identifying population structure and computing relatedness among lines, and ran association tests for earliness related traits. Our results confirmed the importance of the mite polymorphism of Vgt1 on flowering time, but also showed that its effect can be captured by zmRap2.7 polymorphisms located 70 kb apart. We also highlighted associations with polymorphisms within genes putatively involved in lignin biosynthesis pathway, which deserve further investigations.

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In brain, mRNAs are transported from the cell body to the processes, allowing for local protein translation at sites distant from the nucleus. Using subcellular fractionation, we isolated a fraction from rat embryonic day 18 brains enriched for structures that resemble amorphous collections of ribosomes. This fraction was enriched for the mRNA encoding beta-actin, an mRNA that is transported in dendrites and axons of developing neurons. Abundant protein components of this fraction, determined by tandem mass spectrometry, include ribosomal proteins, RNA-binding proteins, microtubule-associated proteins (including the motor protein dynein), and several proteins described only as potential open reading frames. The conjunction of RNA-binding proteins, transported mRNA, ribosomal machinery, and transporting motor proteins defines these structures as RNA granules. Expression of a subset of the identified proteins in cultured hippocampal neurons confirmed that proteins identified in the proteomics were present in neurites associated with ribosomes and mRNAs. Moreover many of the expressed proteins co-localized together. Time lapse video microscopy indicated that complexes containing one of these proteins, the DEAD box 3 helicase, migrated in dendrites of hippocampal neurons at the same speed as that reported for RNA granules. Although the speed of the granules was unchanged by activity or the neurotrophin brain-derived neurotrophic factor, brain-derived neurotrophic factor, but not activity, increased the proportion of moving granules. These studies define the isolation and composition of RNA granules expressed in developing brain.

Tandem mass spectrometry followed by data base search is the preferred method for protein identification in high throughput proteomics. However, standard analysis methods give rise to highly redundant lists of proteins with many proteins identified by the same sets of peptides. In essence, this is a list of all proteins that might be present in the sample. Here we present an algorithm that eliminates redundancy and determines the minimum number of proteins needed to explain the peptides observed. We demonstrate that application of the algorithm results in a significantly smaller set of proteins and greatly reduces the number of "shared" peptides.

The human genome sequence defines our inherent biological potential; the realization of the biology encoded therein requires knowledge of the function of each gene. Currently, our knowledge in this area is still limited. Several lines of investigation have been used to elucidate the structure and function of the genes in the human genome. Even so, gene prediction remains a difficult task, as the varieties of transcripts of a gene may vary to a great extent. We thus performed an exhaustive integrative characterization of 41,118 full-length cDNAs that capture the gene transcripts as complete functional cassettes, providing an unequivocal report of structural and functional diversity at the gene level. Our international collaboration has validated 21,037 human gene candidates by analysis of high-quality full-length cDNA clones through curation using unified criteria. This led to the identification of 5,155 new gene candidates. It also manifested the most reliable way to control the quality of the cDNA clones. We have developed a human gene database, called the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/). It provides the following: integrative annotation of human genes, description of gene structures, details of novel alternative splicing isoforms, non-protein-coding RNAs, functional domains, subcellular localizations, metabolic pathways, predictions of protein three-dimensional structure, mapping of known single nucleotide polymorphisms (SNPs), identification of polymorphic microsatellite repeats within human genes, and comparative results with mouse full-length cDNAs. The H-InvDB analysis has shown that up to 4% of the human genome sequence (National Center for Biotechnology Information build 34 assembly) may contain misassembled or missing regions. We found that 6.5% of the human gene candidates (1,377 loci) did not have a good protein-coding open reading frame, of which 296 loci are strong candidates for non-protein-coding RNA genes. In addition, among 72,027 uniquely mapped SNPs and insertions/deletions localized within human genes, 13,215 nonsynonymous SNPs, 315 nonsense SNPs, and 452 indels occurred in coding regions. Together with 25 polymorphic microsatellite repeats present in coding regions, they may alter protein structure, causing phenotypic effects or resulting in disease. The H-InvDB platform represents a substantial contribution to resources needed for the exploration of human biology and pathology., An international team has systematically validated and annotated just over 21,000 human genes using full-length cDNA, thereby providing a valuable new resource for the human genetics community

The Proteome Analysis database (http://www.ebi.ac.uk/proteome/) has been developed by the Sequence Database Group at EBI utilizing existing resources and providing comparative analysis of the predicted protein coding sequences of the complete genomes of bacteria, archeae and eukaryotes. Three main projects are used, InterPro, CluSTr and GO Slim, to give an overview on families, domains, sites, and functions of the proteins from each of the complete genomes. Complete proteome analysis is available for a total of 89 proteome sets. A specifically designed application enables InterPro proteome comparisons for any one proteome against any other one or more of the proteomes in the database.

The applications of InterPro span a range of biologically important areas that includes automatic annotation of protein sequences and genome analysis. In automatic annotation of protein sequences InterPro has been utilised to provide reliable characterisation of sequences, identifying them as candidates for functional annotation. Rules based on the InterPro characterisation are stored and operated through a database called RuleBase. RuleBase is used as the main tool in the sequence database group at the EBI to apply automatic annotation to unknown sequences. The annotated sequences are stored and distributed in the TrEMBL protein sequence database. InterPro also provides a means to carry out statistical and comparative analyses of whole genomes. In the Proteome Analysis Database, InterPro analyses have been combined with other analyses based on CluSTr, the Gene Ontology (GO) and structural information on the proteins.

Signature databases are vital tools for identifying distant relationships in novel sequences and hence for inferring protein function. InterPro is an integrated documentation resource for protein families, domains and functional sites, which amalgamates the efforts of the PROSITE, PRINTS, Pfam and ProDom database projects. Each InterPro entry includes a functional description, annotation, literature references and links back to the relevant member database(s). Release 2.0 of InterPro (October 2000) contains over 3000 entries, representing families, domains, repeats and sites of post-translational modification encoded by a total of 6804 different regular expressions, profiles, fingerprints and Hidden Markov Models. Each InterPro entry lists all the matches against SWISS-PROT and TrEMBL (more than 1 000 000 hits from 462 500 proteins in SWISS-PROT and TrEMBL). The database is accessible for text- and sequence-based searches at http://www.ebi.ac.uk/interpro/. Questions can be emailed to interhelp@ebi.ac.uk.