Jorge F. Vázquez-Castellanos

Study of the viral and microbial communities associated with Crohn's disease: a metagenomic approach.

OBJECTIVES:This study aimed to analyze and compare the diversity and structure of the viral and microbial communities in fecal samples from a control group of healthy volunteers and from patients affected by Crohn’s disease (CD).METHODS:Healthy adult controls (n=8) and patients affected by ileocolic CD (n=11) were examined for the viral and microbial communities in their feces and, in one additional case, in the intestinal tissue. Using two different approaches, we compared the viral and microbial communities in several ways: by group (patients vs. controls), entity (viruses vs. bacteria), read assembly (unassembled vs. assembled reads), and methodology (our approach vs. an existing pipeline). Differences in the viral and microbial composition, and abundance between the two groups were analyzed to identify taxa that are under- or over-represented.RESULTS:A lower diversity but more variability between the CD samples in both virome and microbiome was found, with a clear distinction between groups based on the microbiome. Only ≈5% of the differential viral biomarkers are more represented in the CD group (Synechococcus phage S CBS1 and Retroviridae family viruses), compared with 95% in the control group. Unrelated patterns of bacteria and bacteriophages were observed.CONCLUSIONS:Our use of an extensive database is critical to retrieve more viral hits than in previous approaches. Unrelated patterns of bacteria and bacteriophages may be due to uneven representation of certain viruses in databases, among other factors. Further characterization of Retroviridae viruses in the CD group could be of interest, given their links with immunodeficiency and the immune responses. To conclude, some methodological considerations underlying the analysis of the viral community composition and abundance are discussed.

Comparison of different assembly and annotation tools on analysis of simulated viral metagenomic communities in the gut

BackgroundThe main limitations in the analysis of viral metagenomes are perhaps the high genetic variability and the lack of information in extant databases. To address these issues, several bioinformatic tools have been specifically designed or adapted for metagenomics by improving read assembly and creating more sensitive methods for homology detection. This study compares the performance of different available assemblers and taxonomic annotation software using simulated viral-metagenomic data.ResultsWe simulated two 454 viral metagenomes using genomes from NCBIs RefSeq database based on the list of actual viruses found in previously published metagenomes. Three different assembly strategies, spanning six assemblers, were tested for performance: overlap-layout-consensus algorithms Newbler, Celera and Minimo; de Bruijn graphs algorithms Velvet and MetaVelvet; and read probabilistic model Genovo. The performance of the assemblies was measured by the length of resulting contigs (using N50), the percentage of reads assembled and the overall accuracy when comparing against corresponding reference genomes. Additionally, the number of chimeras per contig and the lowest common ancestor were estimated in order to assess the effect of assembling on taxonomic and functional annotation. The functional classification of the reads was evaluated by counting the reads that correctly matched the functional data previously reported for the original genomes and calculating the number of over-represented functional categories in chimeric contigs. The sensitivity and specificity of tBLASTx, PhymmBL and the k-mer frequencies were measured by accurate predictions when comparing simulated reads against the NCBI Virus genomes RefSeq database.ConclusionsAssembling improves functional annotation by increasing accurate assignations and decreasing ambiguous hits between viruses and bacteria. However, the success is limited by the chimeric contigs occurring at all taxonomic levels. The assembler and its parameters should be selected based on the focus of each study. Minimos non-chimeric contigs and Genovos long contigs excelled in taxonomy assignation and functional annotation, respectively.tBLASTx stood out as the best approach for taxonomic annotation for virus identification. PhymmBL proved useful in datasets in which no related sequences are present as it uses genomic features that may help identify distant taxa. The k-frequencies underperformed in all viral datasets.

Effect of daily intake of pomegranate juice on fecal microbiota and feces metabolites from healthy volunteers

SCOPE The purpose of the study was to evaluate the effect, regarding the metabolic and microbial profile of feces, of diet supplementation of healthy adults with pomegranate juice (PJ). METHODS AND RESULTS Twelve healthy adults were recruited to the study, which consisted of the intake of 200 mL/day of PJ during 4 weeks. Feces were collected before and after the supplementation with PJ. Metabolites (phenolic catabolites, short-chain fatty acids, and fecal steroids) and microbial profile were analyzed at baseline and at 4 weeks. Fecal phenolic metabolites, 3-phenylpropionic acid, catechol, hydroxytyrosol, and urolithin A, showed a significant increase in their concentration after supplementation with PJ. Among fecal steroids, parallel to the significant increase of cholesterol concentration, a significant decrease of coprostanol was observed. Although no significant changes in the microbiota profile were observed, different relationships between initial microbiota and the metabolites produced were found. Catechol showed positive and negative correlation with Oscillospora and Paraprevotella genera, respectively, and 3-phenylpropionic acid was positively correlated with Odoribacter genus. CONCLUSION Inclusion of PJ in the diet did not significantly alter the gut microbiota composition in healthy adults, but the individual bacterial composition could contribute to the generation of potential health-promoting phenolic metabolites.

Gut Bacteria Metabolism Impacts Immune Recovery in HIV-infected Individuals

While changes in gut microbial populations have been described in human immuno-deficiency virus (HIV)-infected patients undergoing antiretroviral therapy (ART), the mechanisms underlying the contributions of gut bacteria and their molecular agents (metabolites and proteins) to immune recovery remain unexplored. To study this, we examined the active fraction of the gut microbiome, through examining protein synthesis and accumulation of metabolites inside gut bacteria and in the bloodstream, in 8 healthy controls and 29 HIV-infected individuals (6 being longitudinally studied). We found that HIV infection is associated to dramatic changes in the active set of gut bacteria simultaneously altering the metabolic outcomes. Effects were accentuated among immunological ART responders, regardless diet, subject characteristics, clinical variables other than immune recovery, the duration and type of ART and sexual preferences. The effect was found at quantitative levels of several molecular agents and active bacteria which were herein identified and whose abundance correlated with HIV immune pathogenesis markers. Although, we cannot rule out the possibility that some changes are partially a random consequence of the disease status, our data suggest that most likely reduced inflammation and immune recovery is a joint solution orchestrated by both the active fraction of the gut microbiota and the host.

HIV infection results in metabolic alterations in the gut microbiota different from those induced by other diseases

Imbalances in gut bacteria have been associated with multiple diseases. However, whether there are disease-specific changes in gut microbial metabolism remains unknown. Here, we demonstrate that human immunodeficiency virus (HIV) infection (n = 33) changes, at quantifiable levels, the metabolism of gut bacteria. These changes are different than those observed in patients with the auto-immune disease systemic lupus erythaematosus (n = 18), and Clostridium difficile-associated diarrhoea (n = 6). Using healthy controls as a baseline (n = 16), we demonstrate that a trend in the nature and directionality of the metabolic changes exists according to the type of the disease. The impact on the gut microbial activity, and thus the metabolite composition and metabolic flux of gut microbes, is therefore disease-dependent. Our data further provide experimental evidence that HIV infection drastically changed the microbial community, and the species responsible for the metabolism of 4 amino acids, in contrast to patients with the other two diseases and healthy controls. The identification in this present work of specific metabolic deficits in HIV-infected patients may define nutritional supplements to improve the health of these patients.

The effects of prebiotics on microbial dysbiosis, butyrate production and immunity in HIV-infected subjects

Altered interactions between the gut mucosa and bacteria during HIV infection seem to contribute to chronic immune dysfunction. A deeper understanding of how nutritional interventions could ameliorate gut dysbiosis is needed. Forty-four subjects, including 12 HIV+ viremic untreated (VU) patients, 23 antiretroviral therapy-treated (ART+) virally suppressed patients (15 immunological responders and 8 non-responders) and 9 HIV− controls (HIV−), were blindly randomized to receive either prebiotics (scGOS/lcFOS/glutamine) or placebo (34/10) over 6 weeks in this pilot study. We assessed fecal microbiota composition using deep 16S rRNA gene sequencing and several immunological and genetic markers involved in HIV immunopathogenesis. The short dietary supplementation attenuated HIV-associated dysbiosis, which was most apparent in VU individuals but less so in ART+ subjects, whose gut microbiota was found more resilient. This compositional shift was not observed in the placebo arm. Significantly, declines in indirect markers of bacterial translocation and T-cell activation, improvement of thymic output, and changes in butyrate production were observed. Increases in the abundance of Faecalibacterium and Lachnospira strongly correlated with moderate but significant increases of butyrate production and amelioration of the inflammatory biomarkers soluble CD14 and high-sensitivity C-reactive protein, especially among VU. Hence, the bacterial butyrate synthesis pathway holds promise as a viable target for interventions.

Carriage of Enterobacteria Producing Extended-Spectrum β-Lactamases and Composition of the Gut Microbiota in an Amerindian Community

ABSTRACT Epidemiological and individual risk factors for colonization by enterobacteria producing extended-spectrum beta-lactamases (E-ESBL) have been studied extensively, but whether such colonization is associated with significant changes in the composition of the rest of the microbiota is still unknown. To address this issue, we assessed in an isolated Amerindian Guianese community whether intestinal carriage of E-ESBL was associated with specificities in gut microbiota using metagenomic and metatranscriptomic approaches. While the richness of taxa of the active microbiota of carriers was similar to that of noncarriers, the taxa were less homogeneous. In addition, species of four genera, Desulfovibrio, Oscillospira, Parabacteroides, and Coprococcus, were significantly more abundant in the active microbiota of noncarriers than in the active microbiota of carriers, whereas such was the case only for species of Desulfovibrio and Oscillospira in the total microbiota. Differential genera in noncarrier microbiota could either be associated with resistance to colonization or be the consequence of the colonization by E-ESBL.

Fragmentation and Coverage Variation in Viral Metagenome Assemblies, and Their Effect in Diversity Calculations

Metagenomic libraries consist of DNA fragments from diverse species, with varying genome size and abundance. High-throughput sequencing platforms produce large volumes of reads from these libraries, which may be assembled into contigs, ideally resembling the original larger genomic sequences. The uneven species distribution, along with the stochasticity in sample processing and sequencing bias, impacts the success of accurate sequence assembly. Several assemblers enable the processing of viral metagenomic data de novo, generally using overlap layout consensus or de Bruijn graph approaches for contig assembly. The success of viral genomic reconstruction in these datasets is limited by the degree of fragmentation of each genome in the sample, which is dependent on the sequencing effort and the genome length. Depending on ecological, biological, or procedural biases, some fragments have a higher prevalence, or coverage, in the assembly. However, assemblers must face challenges, such as the formation of chimerical structures and intra-species variability. Diversity calculation relies on the classification of the sequences that comprise a metagenomic dataset. Whenever the corresponding genomic and taxonomic information is available, contigs matching the same species can be classified accordingly and the coverage of its genome can be calculated for that species. This may be used to compare populations by estimating abundance and assessing species distribution from this data. Nevertheless, the coverage does not take into account the degree of fragmentation, or else genome completeness, and is not necessarily representative of actual species distribution in the samples. Furthermore, undetermined sequences are abundant in viral metagenomic datasets, resulting in several independent contigs that cannot be assigned by homology or genomic information. These may only be classified as different operational taxonomic units (OTUs), sometimes remaining inadvisably unrelated. Thus, calculations using contigs as different OTUs ultimately overestimate diversity when compared to diversity calculated from species coverage. In order to compare the effect of coverage and fragmentation, we generated three sets of simulated Illumina paired-end reads with different sequencing depths. We compared different assemblies performed with RayMeta, CLC Assembly Cell, MEGAHIT, SPAdes, Meta-IDBA, SOAPdenovo, Velvet, Metavelvet, and MIRA with the best attainable assemblies for each dataset (formed by arranging data using known genome coordinates) by calculating different assembly statistics. A new fragmentation score was included to estimate the degree of genome fragmentation of each taxon and adjust the coverage accordingly. The abundance in the metagenome was compared by bootstrapping the assembly data and hierarchically clustering them with the best possible assembly. Additionally, richness and diversity indexes were calculated for all the resulting assemblies and were assessed under two distributions: contigs as independent OTUs and sequences classified by species. Finally, we search for the strongest correlations between the diversity indexes and the different assembly statistics. Although fragmentation was dependent of genome coverage, it was not as heavily influenced by the assembler. The sequencing depth was the predominant attractor that influenced the success of the assemblies. The coverage increased notoriously in larger datasets, whereas fragmentation values remained lower and unsaturated. While still far from obtaining the ideal assemblies, the RayMeta, SPAdes, and the CLC assemblers managed to build the most accurate contigs with larger datasets while Meta-IDBA showed a good performance with the medium-sized dataset, even after the adjusted coverage was calculated. Their resulting assemblies showed the highest coverage scores and the lowest fragmentation values. Alpha diversity calculated from contigs as OTUs resulted in significantly higher values for all assemblies when compared with actual species distribution, showing an overestimation due to the increased predicted abundance. Conversely, using PHACCS resulted in lower values for all assemblers. Different association methods (random-forest, generalized linear models, and the Spearman correlation index) support the number of contigs, the coverage, and fragmentation as the assembly parameters that most affect the estimation of the alpha diversity. Coverage calculations may provide an insight into relative completeness of a genome but they overlook missing fragments or overly separated sequences in a genome. The assembly of a highly fragmented genomes with high coverage may still lead to the clustering of different OTUs that are actually different fragments of a genome. Thus, it proves useful to penalize coverage with a fragmentation score. Using contigs for calculating alpha diversity result in overestimation but it is usually the only approach available. Still, it is enough for sample comparison. The best approach may be determined by choosing the assembler that better fits the sequencing depth and adjusting the parameters for longer accurate contigs whenever possible whereas diversity may be calculated considering taxonomical and genomic information if available.

Active and Secretory IgA-Coated Bacterial Fractions Elucidate Dysbiosis in Clostridium difficile Infection

C. difficile is a major enteric pathogen with worldwide distribution. Its expansion is associated with broad-spectrum antibiotics which disturb the normal gut microbiome. In this study, the DNA sequencing of highly active bacteria and bacteria opsonized by intestinal secretory immunoglobulin A (SIgA) separated from the whole bacterial community by FACS elucidated how the gut dysbiosis promotes C. difficile infection (CDI). Bacterial groups with inhibitory effects on C. difficile growth, such as Lactobacillales, were mostly inactive in the CDI patients. C. difficile was typical for the bacterial fraction opsonized by SIgA in patients with CDI, while Fusobacterium was characteristic for the SIgA-opsonized fraction of the controls. The study demonstrates that sequencing of specific bacterial fractions provides additional information about dysbiotic processes in the gut. The detected patterns have been confirmed with the whole patient cohort independently of the taxonomic differences detected in the nonfractionated microbiomes. ABSTRACT The onset of Clostridium difficile infection (CDI) has been associated with treatment with wide-spectrum antibiotics. Antibiotic treatment alters the activity of gut commensals and may result in modified patterns of immune responses to pathogens. To study these mechanisms during CDI, we separated bacteria with high cellular RNA content (the active bacteria) and their inactive counterparts by fluorescence-activated cell sorting (FACS) of the fecal bacterial suspension. The gut dysbiosis due to the antibiotic treatment may result in modification of immune recognition of intestinal bacteria. The immune recognition patterns were assessed by FACS of bacterial fractions either coated or not with intestinal secretory immunoglobulin A (SIgA). We described the taxonomic distributions of these four bacterial fractions (active versus inactive and SIgA coated versus non-SIgA coated) by massive 16S rRNA gene amplicon sequencing and quantified the proportion of C. difficile toxin genes in the samples. The overall gut microbiome composition was more robustly influenced by antibiotics than by the C. difficile toxins. Bayesian networks revealed that the C. difficile cluster was preferentially SIgA coated during CDI. In contrast, in the CDI-negative group Fusobacterium was the characteristic genus of the SIgA-opsonized fraction. Lactobacillales and Clostridium cluster IV were mostly inactive in CDI-positive patients. In conclusion, although the proportion of C. difficile in the gut is very low, it is able to initiate infection during the gut dysbiosis caused by environmental stress (antibiotic treatment) as a consequence of decreased activity of the protective bacteria. IMPORTANCE C. difficile is a major enteric pathogen with worldwide distribution. Its expansion is associated with broad-spectrum antibiotics which disturb the normal gut microbiome. In this study, the DNA sequencing of highly active bacteria and bacteria opsonized by intestinal secretory immunoglobulin A (SIgA) separated from the whole bacterial community by FACS elucidated how the gut dysbiosis promotes C. difficile infection (CDI). Bacterial groups with inhibitory effects on C. difficile growth, such as Lactobacillales, were mostly inactive in the CDI patients. C. difficile was typical for the bacterial fraction opsonized by SIgA in patients with CDI, while Fusobacterium was characteristic for the SIgA-opsonized fraction of the controls. The study demonstrates that sequencing of specific bacterial fractions provides additional information about dysbiotic processes in the gut. The detected patterns have been confirmed with the whole patient cohort independently of the taxonomic differences detected in the nonfractionated microbiomes.

Interplay between gut microbiota metabolism and inflammation in HIV infection

HIV infection causes a disruption of gut-associated lymphoid tissue, driving a shift in the composition of gut microbiota. A deeper understanding of the metabolic changes and how they affect the interplay with the host is needed. Here, we assessed functional modifications of HIV-associated microbiota by combining metagenomic and metatranscriptomic analyses. The transcriptionally active microbiota was well-adapted to the inflamed environment, overexpressing pathways related to resistance to oxidative stress. Furthermore, gut inflammation was maintained by the Gram-negative nature of the HIV-associated microbiota and underexpression of anti-inflammatory processes, such as short chain fatty acid biosynthesis or indole production. We performed co-occurrence and metabolic network analyses that showed relevance in the microbiota structure of both taxonomic and metabolic HIV-associated biomarkers. The Bayesian network revealed the most determinant pathways for maintaining the structure stability of the bacterial community. In addition, we identified the taxa’s contribution to metabolic activities and their interactions with host health.