NanoAmpli-Seq: a workflow for amplicon sequencing for mixed microbial communities on the nanopore sequencing platform

Background: Amplicon sequencing on Illumina sequencing platforms leverages their deep sequencing and multiplexing capacity but is limited in genetic resolution due to short read lengths. While Oxford Nanopore or Pacific Biosciences sequencing platforms overcome this limitation, their application has been limited due to higher error rates or lower data output. Results: In this study, we introduce an amplicon sequencing workflow, i.e., NanoAmpli-Seq, that builds on the intramolecular-ligated nanopore consensus sequencing (INC-Seq) approach and demonstrate its application for full-length 16S rRNA gene sequencing. NanoAmpli-Seq includes vital improvements to the INC-Seq protocol that reduces sample processing time while significantly improving sequence accuracy. The developed protocol includes chopSeq software for fragmentation and read orientation correction of INC-Seq consensus reads while nanoClust algorithm was designed for read partitioning-based de novo clustering and within cluster consensus calling to obtain accurate full-length 16S rRNA gene sequences. Conclusions: NanoAmpli-Seq accurately estimates the diversity of tested mock communities with average consensus sequence accuracy of 99.5% for 2D and 1D2 sequencing on the nanopore sequencing platform. Nearly all residual errors in NanoAmpli-Seq sequences originate from deletions in homopolymer regions, indicating that homopolymer aware base calling or error correction may allow for sequencing accuracy comparable to short-read sequencing platforms

The distinct features of microbial 'dysbiosis' of Crohn's disease do not occur to the same extent in their unaffected, genetically linked kindred

Background/Aims: Studying the gut microbiota in unaffected relatives of people with Crohn’s disease (CD) may advance our understanding of the role of bacteria in disease aetiology. Methods: Faecal microbiota composition (16S rRNA gene sequencing), genetic functional capacity (shotgun metagenomics) and faecal short chain fatty acids (SCFA) were compared in unaffected adult relatives of CD children (CDR, n = 17) and adult healthy controls, unrelated to CD patients (HUC, n = 14). The microbiota characteristics of 19 CD children were used as a benchmark of CD ‘dysbiosis’. Results: The CDR microbiota was less diverse (p = 0.044) than that of the HUC group. Local contribution of β-diversity analysis showed no difference in community structure between the CDR and HUC groups. Twenty one of 1,243 (1.8%) operational taxonomic units discriminated CDR from HUC. The metagenomic functional capacity (p = 0.207) and SCFA concentration or pattern were similar between CDR and HUC (p>0.05 for all SCFA). None of the KEGG metabolic pathways were different between these two groups. Both of these groups (HUC and CDR) had a higher microbiota α-diversity (CDR, p = 0.026 and HUC, p<0.001) with a community structure (β-diversity) distinct from that of children with CD. Conclusions: While some alterations were observed, a distinct microbial ‘dysbiosis’, characteristic of CD patients, was not observed in their unaffected, genetically linked kindred

Reagent and laboratory contamination can critically impact sequence-based microbiome analyses.

BACKGROUND: The study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents. RESULTS: In this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR-based 16S rRNA gene surveys and shotgun metagenomics. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination. CONCLUSIONS: These results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. Concurrent sequencing of negative control samples is strongly advised

Mycobacterial dihydrofolate reductase inhibitors identified using chemogenomic methods and in vitro validation.

The lack of success in target-based screening approaches to the discovery of antibacterial agents has led to reemergence of phenotypic screening as a successful approach of identifying bioactive, antibacterial compounds. A challenge though with this route is then to identify the molecular target(s) and mechanism of action of the hits. This target identification, or deorphanization step, is often essential in further optimization and validation studies. Direct experimental identification of the molecular target of a screening hit is often complex, precisely because the properties and specificity of the hit are not yet optimized against that target, and so many false positives are often obtained. An alternative is to use computational, predictive, approaches to hypothesize a mechanism of action, which can then be validated in a more directed and efficient manner. Specifically here we present experimental validation of an in silico prediction from a large-scale screen performed against Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis. The two potent anti-tubercular compounds studied in this case, belonging to the tetrahydro-1,3,5-triazin-2-amine (THT) family, were predicted and confirmed to be an inhibitor of dihydrofolate reductase (DHFR), a known essential Mtb gene, and already clinically validated as a drug target. Given the large number of similar screening data sets shared amongst the community, this in vitro validation of these target predictions gives weight to computational approaches to establish the mechanism of action (MoA) of novel screening hit

Metagenome raw sequence reads from drinking water distribution systems with and without disinfectant residual

To investigate the impact of disinfection strategy on drinking water microbiome in distribution system

Disinfection exhibits systematic impacts on the drinking water microbiome

Limiting microbial growth during drinking water distribution is achieved either by maintaining a disinfectant residual or through nutrient limitation without using a disinfectant. The impact of these contrasting approaches on the drinking water microbiome is not systematically understood. We use genome-resolved metagenomics to compare the structure, metabolic traits, and population genomes of drinking water microbiome samples from bulk drinking water across multiple full-scale disinfected and non-disinfected drinking water systems. Microbial communities cluster at the structural- and functional potential-level based on the presence/absence of a disinfectant residual. Disinfectant residual alone explained 17 and 6.5% of the variance in structure and functional potential of the drinking water microbiome, respectively, despite including multiple drinking water systems with variable source waters and source water communities and treatment strategies. The drinking water microbiome is structurally and functionally less diverse and variable across disinfected compared to non-disinfected systems. While bacteria were the most abundant domain, archaea and eukaryota were more abundant in non-disinfected and disinfected systems, respectively. Community-level differences in functional potential were driven by enrichment of genes associated with carbon and nitrogen fixation in non-disinfected systems and γ-aminobutyrate metabolism in disinfected systems likely associated with the recycling of amino acids. Genome-level analyses for a subset of phylogenetically-related microorganisms suggests that disinfection selects for microorganisms capable of using fatty acids, presumably from microbial decay products, via the glyoxylate cycle. Overall, we find that disinfection exhibits systematic selective pressures on the drinking water microbiome and may select for microorganisms able to utilize microbial decay products originating from disinfection-inactivated microorganisms. [MediaObject not available: see fulltext.]</p

Disinfection exhibits systematic impacts on the drinking water microbiome

Abstract Limiting microbial growth during drinking water distribution is achieved either by maintaining a disinfectant residual or through nutrient limitation without using a disinfectant. The impact of these contrasting approaches on the drinking water microbiome is not systematically understood. We use genome-resolved metagenomics to compare the structure, metabolic traits, and population genomes of drinking water microbiome samples from bulk drinking water across multiple full-scale disinfected and non-disinfected drinking water systems. Microbial communities cluster at the structural- and functional potential-level based on the presence/absence of a disinfectant residual. Disinfectant residual alone explained 17 and 6.5% of the variance in structure and functional potential of the drinking water microbiome, respectively, despite including multiple drinking water systems with variable source waters and source water communities and treatment strategies. The drinking water microbiome is structurally and functionally less diverse and variable across disinfected compared to non-disinfected systems. While bacteria were the most abundant domain, archaea and eukaryota were more abundant in non-disinfected and disinfected systems, respectively. Community-level differences in functional potential were driven by enrichment of genes associated with carbon and nitrogen fixation in non-disinfected systems and γ-aminobutyrate metabolism in disinfected systems likely associated with the recycling of amino acids. Genome-level analyses for a subset of phylogenetically-related microorganisms suggests that disinfection selects for microorganisms capable of using fatty acids, presumably from microbial decay products, via the glyoxylate cycle. Overall, we find that disinfection exhibits systematic selective pressures on the drinking water microbiome and may select for microorganisms able to utilize microbial decay products originating from disinfection-inactivated microorganisms. Video abstracthttp://deepblue.lib.umich.edu/bitstream/2027.42/173978/1/40168_2020_Article_813.pd

Subject characteristics.

<p>Subject characteristics.</p

Microbiota composition and functionality characteristics of unaffected relatives of children with Crohn’s disease, their unaffected relatives and healthy controls with no familial history of IBD.

<p>A) Non-metric multidimensional scaling (NMDS) plot using Bray-Curtis dissimilarity index which considers bacterial taxon presence and abundance. B) Non-metric multidimensional scaling (NMDS) plot using Unifrac phylogenetic distances which takes into account the phylogenetic distances (relatedness) of the bacterial taxa, without accounting for their abundance; The ellipses in A and B represent the 95% confidence intervals based on the standard errors of the average of the axis scores for each group using the ordiellipse function of the R's vegan package C) Local contribution of β-diversity (LCBD) analysis which considers the contribution of each sample to the total OTU β-diversity, calculated from all study samples together (% of total community dispersion); D) Shannon α-diversity (expressed in richness equivalents) based on operational taxonomic unit assignments (OTU) (p = 0.039 when accounting for the genetic relatedness of the participants in the CDR and CD group using paired data analysis); E) Diversity of KEGG metabolic pathways based on metagenomics sequencing (p = 0.127 when accounting for the genetic relatedness of the participants in the CDR and CD group using paired data analysis); F) Faecal short chain fatty acids (μmol/g and % of total SCFA); The size of the dot is proportional to the concentration of faecal calprotectin; CD: Children with Crohn’s disease, CDR: Unaffected blood relatives of children with Crohn’s disease, HUC: Healthy controls unrelated to patients with inflammatory bowel disease.</p

Log-relative abundances of OTUs which differentiated unaffected relatives of children with Crohn’s disease and healthy controls with no familial history of the disease.

<p>Taxonomic classification is given at the highest level of phylogenetic resolution. Within red box frames those OTUs which were identical to the ones which differed between children with CD and healthy paediatric controls in a previous study [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0172605#pone.0172605.ref003" target="_blank">3</a>]^. CDR: Unaffected blood relatives of children with Crohn’s disease, HUC: Healthy controls unrelated to patients with inflammatory bowel disease.</p