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 (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).
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.
•We study effect of barriers on exponent χ in irreversible submonolayer growth•Effective value of χ depends on attachment barrier strength and ratio R = D/F•Asymptotic value of χ only reached in ...limit of very large R and barrier strength•A scaling analysis is presented for dependence of Rmax on barrier strength•We find good agreement between simulations and self-consistent rate-equations
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A variety of effects can lead to short-range attachment barriers in thin-film growth. While it has been predicted that the exponent χ which describes the dependence of the island density N on deposition rate F in the submonolayer regime (where N∼Fχ) crosses over from the diffusion-limited value i/(i+2) (where i is the critical island size) in the absence of an attachment barrier to the attachment-limited value 2i/(i+3) for a strong attachment barrier, this prediction has not been confirmed. Furthermore, the dependence of the effective value of χ on the barrier strength and ratio R=D/F (where D is the monomer hopping rate) has not been studied. Here we consider the effects of attachment barriers in irreversible growth (i=1) for both the case of a barrier to island nucleation and attachment as well as that of an island attachment barrier but no nucleation barrier. Our results indicate that in both cases the effective value of χ increases with increasing R to a maximum value χmax(Rmax) which depends on barrier strength before decreasing very slowly toward the diffusion-limited value. In addition, both χmax and Rmax increase as the barrier strength increases. The results of self-consistent rate-equation calculations are also presented and good agreement is found with our simulations. We also present a scaling analysis for the dependence of Rmax on the barrier strength for arbitrary critical island-size i and good agreement is found with our simulation results for the case in which there is both a nucleation barrier and a barrier to island attachment.
Substantial 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.
We 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).
The 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.
More than several hundreds of millions of people will be diabetic and obese over the next decades in front of which the actual therapeutic approaches aim at treating the consequences rather than ...causes of the impaired metabolism. This strategy is not efficient and new paradigms should be found. The wide analysis of the genome cannot predict or explain more than 10–20% of the disease, whereas changes in feeding and social behavior have certainly a major impact. However, the molecular mechanisms linking environmental factors and genetic susceptibility were so far not envisioned until the recent discovery of a hidden source of genomic diversity, i.e., the metagenome. More than 3 million genes from several hundreds of species constitute our intestinal microbiome. First key experiments have demonstrated that this biome can by itself transfer metabolic disease. The mechanisms are unknown but could be involved in the modulation of energy harvesting capacity by the host as well as the low-grade inflammation and the corresponding immune response on adipose tissue plasticity, hepatic steatosis, insulin resistance and even the secondary cardiovascular events. Secreted bacterial factors reach the circulating blood, and even full bacteria from intestinal microbiota can reach tissues where inflammation is triggered. The last 5 years have demonstrated that intestinal microbiota, at its molecular level, is a causal factor early in the development of the diseases. Nonetheless, much more need to be uncovered in order to identify first, new predictive biomarkers so that preventive strategies based on pre- and probiotics, and second, new therapeutic strategies against the cause rather than the consequence of hyperglycemia and body weight gain.
We recently described a human blood microbiome and a connection between this microbiome and the onset of diabetes. The aim of the current study was to assess the association between blood microbiota ...and incident cardiovascular disease.
D.E.S.I.R. is a longitudinal study with the primary aim of describing the natural history of the metabolic syndrome and its complications. Participants were evaluated at inclusion and at 3-, 6-, and 9-yearly follow-up visits. The 16S ribosomal DNA bacterial gene sequence, that is common to the vast majority of bacteria (Eubac) and a sequence that mostly represents Proteobacteria (Pbac), were measured in blood collected at baseline from 3936 participants. 73 incident cases of acute cardiovascular events, including 30 myocardial infarctions were recorded. Eubac was positively correlated with Pbac (r = 0.59; P<0.0001). In those destined to have cardiovascular complications, Eubac was lower (0.14±0.26 vs 0.12±0.29 ng/µl; P = 0.02) whereas a non significant increase in Pbac was observed. In multivariate Cox analysis, Eubac was inversely correlated with the onset of cardiovascular complications, (hazards ratio 0.50 95% CI 0.35-0.70) whereas Pbac (1.56, 95%CI 1.12-2.15) was directly correlated.
Pbac and Eubac were shown to be independent markers of the risk of cardiovascular disease. This finding is evidence for the new concept of the role played by blood microbiota dysbiosis on atherothrombotic disease. This concept may help to elucidate the relation between bacteria and cardiovascular disease.
A fat‐enriched diet modifies intestinal microbiota and initiates a low‐grade inflammation, insulin resistance and type‐2 diabetes. Here, we demonstrate that before the onset of diabetes, after only ...one week of a high‐fat diet (HFD), live commensal intestinal bacteria are present in large numbers in the adipose tissue and the blood where they can induce inflammation. This translocation is prevented in mice lacking the microbial pattern recognition receptors Nod1 or CD14, but overtly increased in Myd88 knockout and ob/ob mouse. This ‘metabolic bacteremia’ is characterized by an increased co‐localization with dendritic cells from the intestinal lamina propria and by an augmented intestinal mucosal adherence of non‐pathogenic Escherichia coli. The bacterial translocation process from intestine towards tissue can be reversed by six weeks of treatment with the probiotic strain Bifidobacterium animalis subsp. lactis 420, which improves the animals' overall inflammatory and metabolic status. Altogether, these data demonstrate that the early onset of HFD‐induced hyperglycemia is characterized by an increased bacterial translocation from intestine towards tissues, fuelling a continuous metabolic bacteremia, which could represent new therapeutic targets.
Over the last decade, the research community has revealed the role of a new organ: the intestinal microbiota. It is considered as a symbiont that is part of our organism since, at birth, it educates ...the immune system and contributes to the development of the intestinal vasculature and most probably the nervous system. With the advent of new generation sequencing techniques, a catalogue of genes that belong to this microbiome has been established that lists more than 5 million non‐redundant genes called the metagenome. Using germ free mice colonized with the microbiota from different origins, it has been formally demonstrated that the intestinal microbiota causes the onset of metabolic diseases. Further to the role of point mutations in our genome, the microbiota can explain the on‐going worldwide pandemic of obesity and diabetes, its dissemination and family inheritance, as well as the diversity of the associated metabolic phenotypes. More recently, the discovery of bacterial DNA within host tissues, such as the liver, the adipose tissue and the blood, which establishes a tissue microbiota, introduces new opportunities to identify targets and predictive biomarkers based on the host to microbiota interaction, as well as to define new strategies for pharmacological, immunomodulatory vaccines and nutritional applications.
Diabetes and obesity are two metabolic diseases characterized by insulin resistance and a low-grade inflammation. Seeking an inflammatory factor causative of the onset of insulin resistance, obesity, ...and diabetes, we have identified bacterial lipopolysaccharide (LPS) as a triggering factor. We found that normal endotoxemia increased or decreased during the fed or fasted state, respectively, on a nutritional basis and that a 4-week high-fat diet chronically increased plasma LPS concentration two to three times, a threshold that we have defined as metabolic endotoxemia. Importantly, a high-fat diet increased the proportion of an LPS-containing microbiota in the gut. When metabolic endotoxemia was induced for 4 weeks in mice through continuous subcutaneous infusion of LPS, fasted glycemia and insulinemia and whole-body, liver, and adipose tissue weight gain were increased to a similar extent as in high-fat-fed mice. In addition, adipose tissue F4/80-positive cells and markers of inflammation, and liver triglyceride content, were increased. Furthermore, liver, but not whole-body, insulin resistance was detected in LPS-infused mice. CD14 mutant mice resisted most of the LPS and high-fat diet-induced features of metabolic diseases. This new finding demonstrates that metabolic endotoxemia dysregulates the inflammatory tone and triggers body weight gain and diabetes. We conclude that the LPS/CD14 system sets the tone of insulin sensitivity and the onset of diabetes and obesity. Lowering plasma LPS concentration could be a potent strategy for the control of metabolic diseases.
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