16S rRNA gene sequencing of mock microbial populations- impact of DNA extraction method, primer choice and sequencing platform

peer-reviewedBackground Next-generation sequencing platforms have revolutionised our ability to investigate the microbiota composition of complex environments, frequently through 16S rRNA gene sequencing of the bacterial component of the community. Numerous factors, including DNA extraction method, primer sequences and sequencing platform employed, can affect the accuracy of the results achieved. The aim of this study was to determine the impact of these three factors on 16S rRNA gene sequencing results, using mock communities and mock community DNA. Results The use of different primer sequences (V4-V5, V1-V2 and V1-V2 degenerate primers) resulted in differences in the genera and species detected. The V4-V5 primers gave the most comparable results across platforms. The three Ion PGM primer sets detected more of the 20 mock community species than the equivalent MiSeq primer sets. Data generated from DNA extracted using the 2 extraction methods were very similar. Conclusions Microbiota compositional data differed depending on the primers and sequencing platform that were used. The results demonstrate the risks in comparing data generated using different sequencing approaches and highlight the merits of choosing a standardised approach for sequencing in situations where a comparison across multiple sequencing runs is required.This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Numbers SFI/12/RC/2273 and 11/PI/1137 and by FP7 funded CFMATTERS (Cystic Fibrosis Microbiome-determined Antibiotic Therapy Trial in Exacerbations: Results Stratified, Grant Agreement no. 603038)

Characterization of Pro-Inflammatory Flagellin Proteins Produced by Lactobacillus ruminis and Related Motile Lactobacilli

peer-reviewedLactobacillus ruminis is one of at least twelve motile but poorly characterized species found in the genus Lactobacillus. Of these, only L. ruminis has been isolated from mammals, and this species may be considered as an autochthonous member of the gastrointestinal microbiota of humans, pigs and cows. Nine L. ruminis strains were investigated here to elucidate the biochemistry and genetics of Lactobacillus motility. Six strains isolated from humans were non-motile while three bovine isolates were motile. A complete set of flagellum biogenesis genes was annotated in the sequenced genomes of two strains, ATCC25644 (human isolate) and ATCC27782 (bovine isolate), but only the latter strain produced flagella. Comparison of the L. ruminis and L. mali DSM20444T motility loci showed that their genetic content and gene-order were broadly similar, although the L. mali motility locus was interrupted by an 11.8 Kb region encoding rhamnose utilization genes that is absent from the L. ruminis motility locus. Phylogenetic analysis of 39 motile bacteria indicated that Lactobacillus motility genes were most closely related to those of motile carnobacteria and enterococci. Transcriptome analysis revealed that motility genes were transcribed at a significantly higher level in motile L. ruminis ATCC27782 than in non-motile ATCC25644. Flagellin proteins were isolated from L. ruminis ATCC27782 and from three other Lactobacillus species, while recombinant flagellin of aflagellate L. ruminis ATCC25644 was expressed and purified from E. coli. These native and recombinant Lactobacillus flagellins, and also flagellate L. ruminis cells, triggered interleukin-8 production in cultured human intestinal epithelial cells in a manner suppressed by short interfering RNA directed against Toll-Like Receptor 5. This study provides genetic, transcriptomic, phylogenetic and immunological insights into the trait of flagellum-mediated motility in the lactobacilli.This work was supported by a Principal Investigator Award (07/IN.1/B1780) from Science Foundation Ireland to PWOT. BAN was the recipient of an Embark studentship from the Irish Research Council for Science Engineering and Technology. TD and KN were supported by the Alimentary Pharmabiotic Centre, funded by Science Foundation Ireland

Phylogenomics and comparative genomics of Lactobacillus salivarius, a mammalian gut commensal

The genus Lactobacillus is a diverse group with a combined species count of over 200. They are the largest group within the lactic acid bacteria and one of the most important bacterial groups involved in food microbiology and human nutrition because of their fermentative and probiotic properties. Lactobacillus salivarius, a species commonly isolated from the gastrointestinal tract of humans and animals, has been described as having potential probiotic properties and results of previous studies have revealed considerable functional diversity existing on both the chromosomes and plasmids. Our study consists of comparative genomic analyses of the functional and phylogenomic diversity of 42 genomes of strains of L . salivarius using bioinformatic techniques. The main aim of the study was to describe intra-species diversity and to determine how this diversity is spread across the replicons. We found that multiple phylogenomic and non-phylogenomic methods used for reconstructing trees all converge on similar tree topologies, showing that different metrics largely agree on the evolutionary history of the species. The greatest genomic variation lies on the small plasmids, followed by the repA-type circular megaplasmid, with the chromosome varying least of all. Additionally, the presence of extra linear and circular megaplasmids is noted in several strains, while small plasmids are not always present. Glycosyl hydrolases, bacteriocins and proteases vary considerably on all replicons while two exopolysaccharide clusters and several clustered regularly interspaced short palindromic repeats-associated systems show a lot of variation on the chromosome. Overall, despite its reputation as a mammalian gastrointestinal tract specialist, the intra-specific variation of L. salivarius reveals potential strain-dependant effects on human health

Species classifier choice is a key consideration when analysing low-complexity food microbiome data

peer-reviewedBackground The use of shotgun metagenomics to analyse low-complexity microbial communities in foods has the potential to be of considerable fundamental and applied value. However, there is currently no consensus with respect to choice of species classification tool, platform, or sequencing depth. Here, we benchmarked the performances of three high-throughput short-read sequencing platforms, the Illumina MiSeq, NextSeq 500, and Ion Proton, for shotgun metagenomics of food microbiota. Briefly, we sequenced six kefir DNA samples and a mock community DNA sample, the latter constructed by evenly mixing genomic DNA from 13 food-related bacterial species. A variety of bioinformatic tools were used to analyse the data generated, and the effects of sequencing depth on these analyses were tested by randomly subsampling reads. Results Compositional analysis results were consistent between the platforms at divergent sequencing depths. However, we observed pronounced differences in the predictions from species classification tools. Indeed, PERMANOVA indicated that there was no significant differences between the compositional results generated by the different sequencers (p = 0.693, R2 = 0.011), but there was a significant difference between the results predicted by the species classifiers (p = 0.01, R2 = 0.127). The relative abundances predicted by the classifiers, apart from MetaPhlAn2, were apparently biased by reference genome sizes. Additionally, we observed varying false-positive rates among the classifiers. MetaPhlAn2 had the lowest false-positive rate, whereas SLIMM had the greatest false-positive rate. Strain-level analysis results were also similar across platforms. Each platform correctly identified the strains present in the mock community, but accuracy was improved slightly with greater sequencing depth. Notably, PanPhlAn detected the dominant strains in each kefir sample above 500,000 reads per sample. Again, the outputs from functional profiling analysis using SUPER-FOCUS were generally accordant between the platforms at different sequencing depths. Finally, and expectedly, metagenome assembly completeness was significantly lower on the MiSeq than either on the NextSeq (p = 0.03) or the Proton (p = 0.011), and it improved with increased sequencing depth. Conclusions Our results demonstrate a remarkable similarity in the results generated by the three sequencing platforms at different sequencing depths, and, in fact, the choice of bioinformatics methodology had a more evident impact on results than the choice of sequencer did.This research was funded by Science Foundation Ireland in the form of a centre grant (APC Microbiome Institute grant number SFI/12/RC/2273). Research in the Cotter laboratory is also funded by Science Foundation Ireland through the PI award “Obesibiotics” (11/PI/1137). Orla O’Sullivan is funded by Science Foundation Ireland through a Starting Investigator Research Grant award (13/SIRG/2160)

Paediatric inflammatory bowel disease and its relationship with the microbiome

Paediatric inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the digestive tract, comprising of Crohn's disease (CD), ulcerative colitis (UC), and, where classification is undetermined, inflammatory bowel disease unclassified (IBDU). Paediatric IBD incidence is increasing globally, with prevalence highest in the developed world. Though no specific causative agent has been identified for paediatric IBD, it is believed that a number of factors may contribute to the development of the disease, including genetics and the environment. Another potential component in the development of IBD is the microbiota in the digestive tract, particularly the gut. While the exact role that the microbiome plays in IBD is unclear, many studies acknowledge the complex relationship between the gut bacteria and pathogenesis of IBD. In this review, we look at the increasing number of studies investigating the role the microbiome and other biomes play in paediatric patients with IBD, particularly changes associated with IBD, varying disease states, and therapeutics. The paediatric IBD microbiome is significantly different to that of healthy children, with decreased diversity and differences in bacterial composition (such as a decrease in Firmicutes). Changes in the microbiome relating to various treatments of IBD and disease severity have also been observed in multiple studies. Changes in diversity and composition may also extend to other biomes in paediatric IBD, such as the virome and the mycobiome. Research into biome differences in IBD paediatric patients may help progress our understanding of the aetiology of the disease

Comparing Apples and Oranges?: Next Generation Sequencing and Its Impact on Microbiome Analysis

peer-reviewedRapid advancements in sequencing technologies along with falling costs present widespread opportunities for microbiome studies across a vast and diverse array of environments. These impressive technological developments have been accompanied by a considerable growth in the number ofmethodological variables, including sampling, storage, DNA extraction, primer pairs, sequencing technology, chemistry version, read length, insert size, and analysis pipelines, amongst others. This increase in variability threatens to compromise both the reproducibility and the comparability of studies conducted. Here we perform the first reported study comparing both amplicon and shotgun sequencing for the three leading next-generation sequencing technologies. These were applied to six human stool samples using Illumina HiSeq, MiSeq and Ion PGM shotgun sequencing, as well as amplicon sequencing across two variable 16S rRNA gene regions. Notably, we found that the factor responsible for the greatest variance inmicrobiota composition was the chosen methodology rather than the natural inter-individual variance, which is commonly one of the most significant drivers in microbiome studies. Amplicon sequencing suffered from this to a large extent, and this issue was particularly apparent when the 16S rRNA V1-V2 region amplicons were sequenced withMiSeq. Somewhat surprisingly, the choice of taxonomic binning software for shotgun sequences proved to be of crucial importance with even greater discriminatory power than sequencing technology and choice of amplicon. Optimal N50 assembly values for the HiSeq was obtained for 10million reads per sample, whereas the applied MiSeq and PGM sequencing depths proved less sufficient for shotgun sequencing of stool samples. The latter technologies, on the other hand, provide a better basis for functional gene categorisation, possibly due to their longer read lengths. Hence, in addition to highlighting methodological biases, this study demonstrates the risks associated with comparing data generated using different strategies. We also recommend that laboratories with particular interests in certain microbes should optimise their protocols to accurately detect these taxa using different techniques.This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2273 and 11/PI/1137 and by FP7 funded CFMATTERS (Cystic Fibrosis Microbiome-determined Antibiotic Therapy Trial in Exacerbations: Results Stratified, Grant Agreement no. 603038)

Genome-scale analyses of health-promoting bacteria: probiogenomics

The human body is colonized by an enormous population of bacteria (microbiota) that provides the host with coding capacity and metabolic activities. Among the human gut microbiota are health-promoting indigenous species (probiotic bacteria) that are commonly consumed as live dietary supplements. Recent genomics-based studies (probiogenomics) are starting to provide insights into how probiotic bacteria sense and adapt to the gastrointestinal tract environment. In this Review, we discuss the application of probiogenomics in the elucidation of the molecular basis of probiosis using the well-recognized model probiotic bacteria genera Bifidobacterium and Lactobacillus as examples

Microbial Succession and Flavor Production in the Fermented Dairy Beverage Kefir

peer-reviewedKefir is a putatively health-promoting dairy beverage that is produced when a kefir grain, consisting of a consortium of microorganisms, is added to milk to initiate a natural fermentation. Here, a detailed analysis was carried out to determine how the microbial population, gene content, and flavor of three kefirs from distinct geographic locations change over the course of 24-h fermentations. Metagenomic sequencing revealed that Lactobacillus kefiranofaciens was the dominant bacterial species in kefir during early stages of fermentations but that Leuconostoc mesenteroides became more prevalent in later stages. This pattern is consistent with an observation that genes involved in aromatic amino acid biosynthesis were absent from L. kefiranofaciens but were present in L. mesenteroides. Additionally, these shifts in the microbial community structure, and associated pathways, corresponded to changes in the levels of volatile compounds. Specifically, Acetobacter spp. correlated with acetic acid; Lactobacillus spp. correlated with carboxylic acids, esters and ketones; Leuconostoc spp. correlated with acetic acid and 2,3-butanedione; and Saccharomyces spp. correlated with esters. The correlation data suggest a causal relationship between microbial taxa and flavor that is supported by observations that addition of L. kefiranofaciens NCFB 2797 increased the levels of esters and ketones whereas addition of L. mesenteroides 213M0 increased the levels of acetic acid and 2,3-butanedione. Finally, we detected genes associated with probiotic functionalities in the kefir microbiome. Our results illustrate the dynamic nature of kefir fermentations and microbial succession patterns therein and can be applied to optimize the fermentation processes, flavors, and health-related attributes of this and other fermented foods. IMPORTANCE Traditional fermented foods represent relatively low-complexity microbial environments that can be used as model microbial communities to understand how microbes interact in natural environments. Our results illustrate the dynamic nature of kefir fermentations and microbial succession patterns therein. In the process, the link between individual species, and associated pathways, with flavor compounds is revealed and several genes that could be responsible for the purported gut health-associated benefits of consuming kefir are identified. Ultimately, in addition to providing an important fundamental insight into microbial interactions, this information can be applied to optimize the fermentation processes, flavors, and health-related attributes of this and other fermented foods

Pro-inflammatory flagellin proteins of prevalent motile commensal bacteria are variably abundant in the intestinal microbiome of elderly humans

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