Vladimir Lazarevic

Responses of Gut Microbiota and Glucose and Lipid Metabolism to Prebiotics in Genetic Obese and Diet-Induced Leptin-Resistant Mice

OBJECTIVE To investigate deep and comprehensive analysis of gut microbial communities and biological parameters after prebiotic administration in obese and diabetic mice. RESEARCH DESIGN AND METHODS Genetic (ob/ob) or diet-induced obese and diabetic mice were chronically fed with prebiotic-enriched diet or with a control diet. Extensive gut microbiota analyses, including quantitative PCR, pyrosequencing of the 16S rRNA, and phylogenetic microarrays, were performed in ob/ob mice. The impact of gut microbiota modulation on leptin sensitivity was investigated in diet-induced leptin-resistant mice. Metabolic parameters, gene expression, glucose homeostasis, and enteroendocrine-related L-cell function were documented in both models. RESULTS In ob/ob mice, prebiotic feeding decreased Firmicutes and increased Bacteroidetes phyla, but also changed 102 distinct taxa, 16 of which displayed a >10-fold change in abundance. In addition, prebiotics improved glucose tolerance, increased L-cell number and associated parameters (intestinal proglucagon mRNA expression and plasma glucagon-like peptide-1 levels), and reduced fat-mass development, oxidative stress, and low-grade inflammation. In high fat–fed mice, prebiotic treatment improved leptin sensitivity as well as metabolic parameters. CONCLUSIONS We conclude that specific gut microbiota modulation improves glucose homeostasis, leptin sensitivity, and target enteroendocrine cell activity in obese and diabetic mice. By profiling the gut microbiota, we identified a catalog of putative bacterial targets that may affect host metabolism in obesity and diabetes.

Metagenomic study of the oral microbiota by Illumina high-throughput sequencing

To date, metagenomic studies have relied on the utilization and analysis of reads obtained using 454 pyrosequencing to replace conventional Sanger sequencing. After extensively scanning the 16S ribosomal RNA (rRNA) gene, we identified the V5 hypervariable region as a short region providing reliable identification of bacterial sequences available in public databases such as the Human Oral Microbiome Database. We amplified samples from the oral cavity of three healthy individuals using primers covering an approximately 82-base segment of the V5 loop, and sequenced using the Illumina technology in a single orientation. We identified 135 genera or higher taxonomic ranks from the resulting 1,373,824 sequences. While the abundances of the most common phyla (Firmicutes, Proteobacteria, Actinobacteria, Fusobacteria and TM7) are largely comparable to previous studies, Bacteroidetes were less present. Potential sources for this difference include classification bias in this region of the 16S rRNA gene, human sample variation, sample preparation and primer bias. Using an Illumina sequencing approach, we achieved a much greater depth of coverage than previous oral microbiota studies, allowing us to identify several taxa not yet discovered in these types of samples, and to assess that at least 30,000 additional reads would be required to identify only one additional phylotype. The evolution of high-throughput sequencing technologies, and their subsequent improvements in read length enable the utilization of different platforms for studying communities of complex flora. Access to large amounts of data is already leading to a better representation of sample diversity at a reasonable cost.

Microbiome of prebiotic-treated mice reveals novel targets involved in host response during obesity

The gut microbiota is involved in metabolic and immune disorders associated with obesity and type 2 diabetes. We previously demonstrated that prebiotic treatment may significantly improve host health by modulating bacterial species related to the improvement of gut endocrine, barrier and immune functions. An analysis of the gut metagenome is needed to determine which bacterial functions and taxa are responsible for beneficial microbiota–host interactions upon nutritional intervention. We subjected mice to prebiotic (Pre) treatment under physiological (control diet: CT) and pathological conditions (high-fat diet: HFD) for 8 weeks and investigated the production of intestinal antimicrobial peptides and the gut microbiome. HFD feeding significantly decreased the expression of regenerating islet-derived 3-gamma (Reg3g) and phospholipase A2 group-II (PLA2g2) in the jejunum. Prebiotic treatment increased Reg3g expression (by ∼50-fold) and improved intestinal homeostasis as suggested by the increase in the expression of intectin, a key protein involved in intestinal epithelial cell turnover. Deep metagenomic sequencing analysis revealed that HFD and prebiotic treatment significantly affected the gut microbiome at different taxonomic levels. Functional analyses based on the occurrence of clusters of orthologous groups (COGs) of proteins also revealed distinct profiles for the HFD, Pre, HFD-Pre and CT groups. Finally, the gut microbiota modulations induced by prebiotics counteracted HFD-induced inflammation and related metabolic disorders. Thus, we identified novel putative taxa and metabolic functions that may contribute to the development of or protection against the metabolic alterations observed during HFD feeding and HFD-Pre feeding.

Altered gut microbiota and endocannabinoid system tone in obese and diabetic leptin-resistant mice: impact on apelin regulation in adipose tissue

Growing evidence supports the role of gut microbiota in the development of obesity, type 2 diabetes, and low-grade inflammation. The endocrine activity of adipose tissue has been found to contribute to the regulation of glucose homeostasis and low-grade inflammation. Among the key hormones produced by this tissue, apelin has been shown to regulate glucose homeostasis. Recently, it has been proposed that gut microbiota participate in adipose tissue metabolism via the endocannabinoid system (eCB) and gut microbiota-derived compounds, namely lipopolysaccharide (LPS). We have investigated gut microbiota composition in obese and diabetic leptin-resistant mice (db/db) by combining pyrosequencing and phylogenetic microarray analysis of 16S ribosomal RNA gene sequences. We observed a significant higher abundance of Firmicutes, Proteobacteria, and Fibrobacteres phyla in db/db mice compared to lean mice. The abundance of 10 genera was significantly affected by the genotype. We identified the roles of the eCB and LPS in the regulation of apelinergic system tone (apelin and APJ mRNA expression) in genetic obese and diabetic mice. By using in vivo and in vitro models, we have demonstrated that both the eCB and low-grade inflammation differentially regulate apelin and APJ mRNA expression in adipose tissue. Finally, deep-gut microbiota profiling revealed that the gut microbial community of type 2 diabetic mice is significantly different from that of their lean counterparts. This indicates specific relationships between the gut microbiota and the regulation of the apelinergic system. However, the exact roles of specific bacteria in shaping the phenotype of db/db mice remain to be determined.

Study of inter- and intra-individual variations in the salivary microbiota

BackgroundOral bacterial communities contain species that promote health and others that have been implicated in oral and/or systemic diseases. Culture-independent approaches provide the best means to assess the diversity of oral bacteria because most of them remain uncultivable.ResultsThe salivary microbiota from five adults was analyzed at three time-points by means of the 454 pyrosequencing technology. The V1-V3 region of the bacterial 16S rRNA genes was amplified by PCR using saliva lysates and broad-range primers. The bar-coded PCR products were pooled and sequenced unidirectionally to cover the V3 hypervariable region. Of 50,708 obtained sequences, 31,860 passed the quality control. Non-bacterial sequences (2.2%) were removed leaving 31,170 reads. Samples were dominated by seven major phyla: members of Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes and candidate division TM7 were identified in all samples; Fusobacteria and Spirochaetes were identified in all individuals, but not at all time-points. The dataset was represented by 3,011 distinct sequences (100%-ID phylotypes) of ~215 nucleotides and 583 phylotypes defined at ≥97% identity (97%-ID phylotypes). We compared saliva samples from different individuals in terms of the phylogeny of their microbial communities. Based on the presence and absence of phylotypes defined at 100% or 97% identity thresholds, samples from each subject formed separate clusters. Among individual taxa, phylum Bacteroidetes and order Clostridiales (Firmicutes) were the best indicators of intraindividual similarity of the salivary flora over time. Fifteen out of 81 genera constituted 73 to 94% of the total sequences present in different samples. Of these, 8 were shared by all time points of all individuals, while 15-25 genera were present in all three time-points of different individuals. Representatives of the class Sphingobacteria, order Sphingobacteriales and family Clostridiaceae were found only in one subject.ConclusionsThe salivary microbial community appeared to be stable over at least 5 days, allowing for subject-specific grouping using UniFrac. Inclusion of all available samples from more distant time points (up to 29 days) confirmed this observation. Samples taken at closer time intervals were not necessarily more similar than samples obtained across longer sampling times. These results point to the persistence of subject-specific taxa whose frequency fluctuates between the time points. Genus Gemella, identified in all time-points of all individuals, was not defined as a core-microbiome genus in previous studies of salivary bacterial communities. Human oral microbiome studies are still in their infancy and larger-scale projects are required to better define individual and universal oral microbiome core.

Comparison of DNA Extraction Methods in Analysis of Salivary Bacterial Communities

Culture-independent high-throughput sequencing-based methods are widely used to study bacterial communities. Although these approaches are superior to traditional culture-based methods, they introduce bias at the experimental and bioinformatics levels. We assessed the diversity of the human salivary microbiome by pyrosequencing of the 16S rDNA V1–3 amplicons using metagenomic DNA extracted by two different protocols: a simple proteinase K digestion without a subsequent DNA clean-up step, and a bead-beating mechanical lysis protocol followed by column DNA purification. A high degree of congruence was found between the two extraction methods, most notably in regard to the microbial community composition. The results showed that for a given bioinformatics pipeline, all the taxa with an average proportion >0.12% in samples processed using one extraction method were also detected in samples extracted using the other method. The same taxa tended to be abundant and frequent for both extraction methods. The relative abundance of sequence reads assigned to the phyla Actinobacteria, Spirochaetes, TM7, Synergistetes, and Tenericutes was significantly higher in the mechanically-treated samples than in the enzymatically-treated samples, whereas the phylum Firmicutes showed the opposite pattern. No significant differences in diversity indices were found between the extraction methods, although the mechanical lysis method revealed higher operational taxonomic unit richness. Differences between the extraction procedures outweighed the variations due to the bioinformatics analysis pipelines used.

Analysis of the salivary microbiome using culture-independent techniques

BackgroundThe salivary microbiota is a potential diagnostic indicator of several diseases. Culture-independent techniques are required to study the salivary microbial community since many of its members have not been cultivated.MethodsWe explored the bacterial community composition in the saliva sample using metagenomic whole genome shotgun (WGS) sequencing, the extraction of 16S rRNA gene fragments from metagenomic sequences (16S-WGS) and high-throughput sequencing of PCR-amplified bacterial 16S rDNA gene (16S-HTS) regions V1 and V3.ResultsThe hierarchical clustering of data based on the relative abundance of bacterial genera revealed that distances between 16S-HTS datasets for V1 and V3 regions were greater than those obtained for the same V region with different numbers of PCR cycles. Datasets generated by 16S-HTS and 16S-WGS were even more distant. Finally, comparison of WGS and 16S-based datasets revealed the highest dissimilarity.The analysis of the 16S-HTS, WGS and 16S-WGS datasets revealed 206, 56 and 39 bacterial genera, respectively, 124 of which have not been previously identified in salivary microbiomes. A large fraction of DNA extracted from saliva corresponded to human DNA. Based on sequence similarity search against completely sequenced genomes, bacterial and viral sequences represented 0.73% and 0.0036% of the salivary metagenome, respectively. Several sequence reads were identified as parts of the human herpesvirus 7.ConclusionsAnalysis of the salivary metagenome may have implications in diagnostics e.g. in detection of microorganisms and viruses without designing specific tests for each pathogen.

Mapping axillary microbiota responsible for body odours using a culture-independent approach

BackgroundHuman axillary odour is commonly attributed to the bacterial degradation of precursors in sweat secretions. To assess the role of bacterial communities in the formation of body odours, we used a culture-independent approach to study axillary skin microbiota and correlated these data with olfactory analysis.ResultsTwenty-four Caucasian male and female volunteers and four assessors showed that the underarms of non-antiperspirant (non-AP) users have significantly higher global sweat odour intensities and harboured on average about 50 times more bacteria than those of AP users. Global sweat odour and odour descriptors sulfury-cat urine and acid-spicy generally increased from the morning to the afternoon sessions. Among non-AP users, male underarm odours were judged higher in intensity with higher fatty and acid-spicy odours and higher bacterial loads. Although the content of odour precursors in underarm secretions varied widely among individuals, males had a higher acid: sulfur precursor ratio than females did. No direct correlations were found between measured precursor concentration and sweat odours. High-throughput sequencing targeting the 16S rRNA genes of underarm bacteria collected from 11 non-AP users (six females and five males) confirmed the strong dominance of the phyla Firmicutes and Actinobacteria, with 96% of sequences assigned to the genera Staphylococcus, Corynebacterium and Propionibacterium. The proportion of several bacterial taxa showed significant variation between males and females. The genera Anaerococcus and Peptoniphilus and the operational taxonomic units (OTUs) from Staphylococcus haemolyticus and the genus Corynebacterium were more represented in males than in females. The genera Corynebacterium and Propionibacterium were correlated and anti-correlated, respectively, with body odours. Within the genus Staphylococcus, different OTUs were either positively or negatively correlated with axillary odour. The relative abundance of five OTUs (three assigned to S. hominis and one each to Corynebacterium tuberculostearicum and Anaerococcus) were positively correlated with at least one underarm olfactory descriptor.ConclusionsPositive and negative correlations between bacterial taxa found at the phylum, genus and OTU levels suggest the existence of mutualism and competition among skin bacteria. Such interactions, and the types and quantities of underarm bacteria, affect the formation of body odours. These findings open the possibility of developing new solutions for odour control.

Collateral damage from oral ciprofloxacin versus nitrofurantoin in outpatients with urinary tract infections: a culture-free analysis of gut microbiota.

Recent treatment guidelines for uncomplicated urinary tract infections (UTIs) discourage fluoroquinolone prescription because of collateral damage to commensal microbiota, but the ecologic impact of alternative agents has not been evaluated by culture-free techniques. We prospectively collected faecal samples at three time points from ambulatory patients with UTIs treated with ciprofloxacin or nitrofurantoin, patients not requiring antibiotics and household contacts of ciprofloxacin-treated patients. We described changes in gut microbiota using a culture-independent approach based on pyrosequencing of the V3-V4 region of the bacterial 16S rRNA gene. All groups were similar at baseline. Ciprofloxacin had a significant global impact on the gut microbiota whereas nitrofurantoin did not. The end of ciprofloxacin treatment correlated with a reduced proportion of Bifidobacterium (Actinobacteria), Alistipes (Bacteroidetes) and four genera from the phylum Firmicutes (Faecalibacterium, Oscillospira, Ruminococcus and Dialister) and an increased relative abundance of Bacteroides (Bacteroidetes) and the Firmicutes genera Blautia, Eubacterium and Roseburia. Substantial recovery had occurred 4 weeks later. Nitrofurantoin treatment correlated with a reduced relative proportion of the genus Clostridium and an increased proportion of the genus Faecalibacterium. This study supports use of nitrofurantoin over fluoroquinolones for treatment of uncomplicated UTIs to minimize perturbation of intestinal microbiota.

Decontamination of 16S rRNA gene amplicon sequence datasets based on bacterial load assessment by qPCR

BackgroundIdentification of unexpected taxa in 16S rRNA surveys of low-density microbiota, diluted mock communities and cultures demonstrated that a variable fraction of sequence reads originated from exogenous DNA. The sources of these contaminants are reagents used in DNA extraction, PCR, and next-generation sequencing library preparation, and human (skin, oral and respiratory) microbiota from the investigators.ResultsFor in silico removal of reagent contaminants, a pipeline was used which combines the relative abundance of operational taxonomic units (OTUs) in V3–4 16S rRNA gene amplicon datasets with bacterial DNA quantification based on qPCR targeting of the V3 segment of the 16S rRNA gene. Serially diluted cultures of Escherichia coli and Staphylococcus aureus were used for 16S rDNA profiling, and DNA from each of these species was used as a qPCR standard. OTUs assigned to Escherichia or Staphylococcus were virtually unaffected by the decontamination procedure, whereas OTUs from Pseudomonas, which is a major reagent contaminant, were completely or nearly completely removed. The decontamination procedure also attenuated the trend of increase in OTU richness in serially diluted cultures.ConclusionsRemoval of contaminant sequences derived from reagents based on use of qPCR data may improve taxonomic representation in samples with low DNA concentration. Using the described pipeline, OTUs derived from cross-contamination of negative extraction controls were not recognized as contaminants and not removed from the sample dataset.