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With increasing number of novel bacteria being isolated from the human gut ecosystem, there is a greater need to study their role in the gut ecosystem and their effect on the host health. In the present study, we carried out in silico genome-wide analysis of two novel Megasphaera sp. isolates NM10 (DSM25563) and BL7 (DSM25562), isolated from feces of two healthy individuals and validated the key features by in vitro studies. The analysis revealed the general metabolic potential, adaptive features and the potential effects of these isolates on the host. The comparative genome analysis of the two human gut isolates NM10 and BL7 with ruminal isolate Megasphaera elsdenii (DSM20460) highlighted the differential adaptive features for their survival in human gut. The key findings include features like bile resistance, presence of various sensory and regulatory systems, stress response systems, membrane transporters and resistance to antibiotics. Comparison of the “glycobiome” based on the genomes of the ruminal isolate with the human gut isolates NM10 and BL revealed the presence of diverse and unique sets of Carbohydrate-Active enzymes (CAZymes) amongst these isolates, with a higher collection of CAZymes in the human gut isolates. This could be attributed to the difference in host diet and thereby the environment, consequently suggesting host specific adaptation in these isolates. In silico analysis of metabolic potential predicted the ability of these isolates to produce important metabolites like short chain fatty acids (butyrate, acetate, formate, and caproate), vitamins and essential amino acids, which was further validated by in vitro experiments. The ability of these isolates to produce important metabolites advocates for a potential healthy influence on the host. Further in vivo studies including transcriptomic and proteomic analysis will be required for better understanding the role and impact of these Megasphaera sp. isolates NM10 and BL7 on the human host.

BackgroundOver the past 75 years, human pathogens have acquired antibiotic resistance genes (ARGs), often from environmental bacteria. Integrons play a major role in the acquisition of antibiotic resistance genes. We therefore hypothesized that focused exploration of integron gene cassettes from microbial communities could be an efficient way to find novel mobile resistance genes. DNA from polluted Indian river sediments were amplified using three sets of primers targeting class 1 integrons and sequenced by long- and short-read technologies to maintain both accuracy and context.ResultsUp to 89% of identified open reading frames encode known resistance genes, or variations thereof (> 1000). We identified putative novel ARGs to aminoglycosides, beta-lactams, trimethoprim, rifampicin, and chloramphenicol, including several novel OXA variants, providing reduced susceptibility to carbapenems. One dihydropteroate synthase gene, with less than 34% amino acid identity to the three known mobile sulfonamide resistance genes (sul1–3), provided complete resistance when expressed in Escherichia coli. The mobilized gene, here named sul4, is the first mobile sulfonamide resistance gene discovered since 2003. Analyses of adjacent DNA suggest that sul4 has been decontextualized from a set of chromosomal genes involved in folate synthesis in its original host, likely within the phylum Chloroflexi. The presence of an insertion sequence common region element could provide mobility to the entire integron. Screening of 6489 metagenomic datasets revealed that sul4 is already widespread in seven countries across Asia and Europe.ConclusionsOur findings show that exploring integrons from environmental communities with a history of antibiotic exposure can provide an efficient way to find novel, mobile resistance genes. The mobilization of a fourth sulfonamide resistance gene is likely to provide expanded opportunities for sulfonamide resistance to spread, with potential impacts on both human and animal health.Electronic supplementary materialThe online version of this article (10.1186/s40168-017-0379-y) contains supplementary material, which is available to authorized users.

There is increasing concern that environmental antibiotic pollution promotes transfer of resistance genes to the human microbiota. Here, fluoroquinolone-polluted river sediment, well water, irrigated farmland, and human fecal flora of local villagers within a pharmaceutical industrial region in India were analyzed for quinolone resistance (qnr) genes by quantitative PCR. Similar samples from Indian villages farther away from industrial areas, as well as fecal samples from Swedish study participants and river sediment from Sweden, were included for comparison. Fluoroquinolones were detected by MS/MS in well water and soil from all villages located within three km from industrially polluted waterways. Quinolone resistance genes were detected in 42% of well water, 7% of soil samples and in 100% and 18% of Indian and Swedish river sediments, respectively. High antibiotic concentrations in Indian sediment coincided with high abundances of qnr, whereas lower fluoroquinolone levels in well water and soil did not. We could not find support for an enrichment of qnr in fecal samples from people living in the fluoroquinolone-contaminated villages. However, as qnr was detected in 91% of all Indian fecal samples (24% of the Swedish) it suggests that the spread of qnr between people is currently a dominating transmission route.

BackgroundMetallo-β-lactamases are bacterial enzymes that provide resistance to carbapenems, the most potent class of antibiotics. These enzymes are commonly encoded on mobile genetic elements, which, together with their broad substrate spectrum and lack of clinically useful inhibitors, make them a particularly problematic class of antibiotic resistance determinants. We hypothesized that there is a large and unexplored reservoir of unknown metallo-β-lactamases, some of which may spread to pathogens, thereby threatening public health. The aim of this study was to identify novel metallo-β-lactamases of class B1, the most clinically important subclass of these enzymes.ResultsBased on a new computational method using an optimized hidden Markov model, we analyzed over 10,000 bacterial genomes and plasmids together with more than 5 terabases of metagenomic data to identify novel metallo-β-lactamase genes. In total, 76 novel genes were predicted, forming 59 previously undescribed metallo-β-lactamase gene families. The ability to hydrolyze imipenem in an Escherichia coli host was experimentally confirmed for 18 of the 21 tested genes. Two of the novel B1 metallo-β-lactamase genes contained atypical zinc-binding motifs in their active sites, which were previously undescribed for metallo-β-lactamases. Phylogenetic analysis showed that B1 metallo-β-lactamases could be divided into five major groups based on their evolutionary origin. Our results also show that, except for one, all of the previously characterized mobile B1 β-lactamases are likely to have originated from chromosomal genes present in Shewanella spp. and other Proteobacterial species.ConclusionsThis study more than doubles the number of known B1 metallo-β-lactamases. The findings have further elucidated the diversity and evolutionary history of this important class of antibiotic resistance genes and prepare us for some of the challenges that may be faced in clinics in the future.Electronic supplementary materialThe online version of this article (10.1186/s40168-017-0353-8) contains supplementary material, which is available to authorized users.

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BackgroundThe healthy human intestine is represented by the presence of bacterial communities predominantly belonging to obligate anaerobes; however disparity and dysanaerobiosis in intestinal microflora may lead to the progression of ulcerative colitis (UC). The foremost aim of this study is to consider and compare the gut microbiota composition in patients suffering from different stages of UC.MethodsThis study represents data from the biopsy samples of six individuals suffering from UC. The samples were collected by colonoscopy and were processed immediately for isolation of DNA. Mucosal microbiota was analyzed by means of 16S rRNA gene-based Illumina high throughput sequencing. Quantitative real-time PCR (qPCR) was performed to determine total bacterial abundances.ResultsAnalysis of 23,927 OTUs demonstrated a significant reduction of bacterial diversity consistently from phylum to species level (p < 0.05) for individuals suffering from severe stage of UC. Significant increase in abundance of unusual aerobes and facultative anaerobes, including members from the phylum Proteobacteria (p- = 0.031) was also observed. A 10 fold increase in the total bacterial count was detected in patients suffering from severe inflammatory stage (2.98 +/-0.49 E + 09/ml) when compared with patients with moderate (1.03+/-0.29 E + 08/ml) and mild (1.76 +/-0.34 E + 08/ml) stages of inflammation.ConclusionThe reduction of bacterial diversity with an increase in the total bacterial count indicates a shift of bacterial communities which signifies dysbiosis and dysanaerobiosis at the mucosal level for patients suffering from UC.

Background Environmental and commensal bacteria maintain a diverse and largely unknown collection of antibiotic resistance genes (ARGs) that, over time, may be mobilized and transferred to pathogens. Metagenomics enables cultivation-independent characterization of bacterial communities but the resulting data is noisy and highly fragmented, severely hampering the identification of previously undescribed ARGs. We have therefore developed fARGene, a method for identification and reconstruction of ARGs directly from shotgun metagenomic data. Results fARGene uses optimized gene models and can therefore with high accuracy identify previously uncharacterized resistance genes, even if their sequence similarity to known ARGs is low. By performing the analysis directly on the metagenomic fragments, fARGene also circumvents the need for a high-quality assembly. To demonstrate the applicability of fARGene, we reconstructed β-lactamases from five billion metagenomic reads, resulting in 221 ARGs, of which 58 were previously not reported. Based on 38 ARGs reconstructed by fARGene, experimental verification showed that 81% provided a resistance phenotype in Escherichia coli . Compared to other methods for detecting ARGs in metagenomic data, fARGene has superior sensitivity and the ability to reconstruct previously unknown genes directly from the sequence reads. Conclusions We conclude that fARGene provides an efficient and reliable way to explore the unknown resistome in bacterial communities. The method is applicable to any type of ARGs and is freely available via GitHub under the MIT license. Electronic supplementary material The online version of this article (10.1186/s40168-019-0670-1) contains supplementary material, which is available to authorized users.