METASEED: a novel approach to full-length 16S rRNA gene reconstruction from short read data.

BACKGROUND: With the emergence of Oxford Nanopore technology, now the on-site sequencing of 16S rRNA from environments is available. Due to the error level and structure, the analysis of such data demands some database of reference sequences. However, many taxa from complex and diverse environments, have poor representation in publicly available databases. In this paper, we propose the METASEED pipeline for the reconstruction of full-length 16S sequences from such environments, in order to improve the reference for the subsequent use of on-site sequencing. RESULTS: We show that combining high-precision short-read sequencing of both 16S and full metagenome from the same samples allow us to reconstruct high-quality 16S sequences from the more abundant taxa. A significant novelty is the carefully designed collection of metagenome reads that matches the 16S amplicons, based on a combination of uniqueness and abundance. Compared to alternative approaches this produces superior results. CONCLUSION: Our pipeline will facilitate numerous studies associated with various unknown microorganisms, thus allowing the comprehension of the diverse environments. The pipeline is a potential tool in generating a full length 16S rRNA gene database for any environment.

Swarm and UNOISE outperform DADA2 and Deblur for denoising high-diversity marine seafloor samples.

The performance of sequence variant resolution analytic tools for metabarcoding has not yet been adequately benchmarked for high-diversity environmental samples. We therefore evaluated the sequence variant tools DADA2, Deblur, Swarm, and UNOISE, using high-diversity seafloor samples, resulting in comparisons of 1800 sequence variant tables. The evaluation was based on 30 sediment grab samples, for which 3 replica samples were collected. Each replica sample was extracted using 5 common DNA extraction kits, resulting in 450 DNA extracts which were 16S rRNA gene sequenced (V3-V4), using Illumina. Assessments included variation across replica samples, extraction kits, and denoising methods, in addition to applying prior knowledge about alpha diversity correlations toward the cosmopolitan marine archaeon Nitrosopumilus with high diversity and the sulfide oxidizing Sulfurovum with low diversity. DADA2 displayed the highest variance between replicates (Manhattan distance 1.14), while Swarm showed the lowest variance (Manhattan distance 0.93). For the analysis based on prior biological knowledge, UNOISE displayed the highest alpha diversity (Simpson's D) correlation toward Nitrosopumilus (Spearman rho = 0.85), while DADA2 showed the lowest (Spearman rho = 0.10). Deblur completely eliminated Nitrosopumilus from the dataset. For Sulfurovum, on the other hand, all the methods showed comparable results. In conclusion, our evaluations show that Swarm and UNOISE performed better than DADA2 and Deblur for high-diversity seafloor samples.

Stable Core Gut Microbiota across the Freshwater-to-Saltwater Transition for Farmed Atlantic Salmon.

Gut microbiota associations through habitat transitions are fundamentally important yet poorly understood. One such habitat transition is the migration from freshwater to saltwater for anadromous fish, such as salmon. The aim of the current work was therefore to determine the freshwater-to-saltwater transition impact on the gut microbiota in farmed Atlantic salmon, with dietary interventions resembling freshwater and saltwater diets with respect to fatty acid composition. Using deep 16S rRNA gene sequencing and quantitative PCR, we found that the freshwater-to-saltwater transition had a major association with the microbiota composition and quantity, while diet did not show significant associations with the microbiota. In saltwater there was a 100-fold increase in bacterial quantity, with a relative increase of Firmicutes and a relative decrease of both Actinobacteria and Proteobacteria Irrespective of an overall shift in microbiota composition from freshwater to saltwater, we identified three core clostridia and one Lactobacillus-affiliated phylotype with wide geographic distribution that were highly prevalent and co-occurring. Taken together, our results support the importance of the dominating bacteria in the salmon gut, with the freshwater microbiota being immature. Due to the low number of potentially host-associated bacterial species in the salmon gut, we believe that farmed salmon can represent an important model for future understanding of host-bacterium interactions in aquatic environments.IMPORTANCE Little is known about factors affecting the interindividual distribution of gut bacteria in aquatic environments. We have shown that there is a core of four highly prevalent and co-occurring bacteria irrespective of feed and freshwater-to-saltwater transition. The potential host interactions of the core bacteria, however, need to be elucidated further.

Cecal microbiota association with tumor load in a colorectal cancer mouse model.

Background: Colorectal cancer (CRC) is one of the most common cancer types worldwide. The role of the intestinal microbiota in CRC, however, is not well established. In particular, the co-variation between age, tumor progression and microbiota remains largely unknown. Objective and design: We therefore used a recently developed A/J Min/+ mouse model resembling human CRC to investigate how microbial composition in cecum correlates with tumor progression, butyrate and age. Results: We found that the association between the gut microbiota and tumor load was stronger, by far, than the association with both butyrate and age. The strongest direct tumor association was found for mucosal bacteria, with nearly 60% of the significantly correlating operational taxonomic units being correlated with CRC tumor load alone. Conclusion: We favor a systemic association between tumor load and microbiota, since the correlations are associated with tumor load in gut segments other than the cecum (both small and large intestine).

A genomic virulence reference map of Enterococcus faecalis reveals an important contribution of phage03-like elements in nosocomial genetic lineages to pathogenicity in a Caenorhabditis elegans infection model.

In the present study, the commensal and pathogenic host-microbe interaction of Enterococcus faecalis was explored using a Caenorhabditis elegans model system. The virulence of 28 E. faecalis isolates representing 24 multilocus sequence types (MLSTs), including human commensal and clinical isolates as well as isolates from animals and of insect origin, was investigated using C. elegans strain glp-4 (bn2ts); sek-1 (km4). This revealed that 6 E. faecalis isolates behaved in a commensal manner with no nematocidal effect, while the remaining strains showed a time to 50% lethality ranging from 47 to 120 h. Principal component analysis showed that the difference in nematocidal activity explained 94% of the variance in the data. Assessment of known virulence traits revealed that gelatinase and cytolysin production accounted for 40.8% and 36.5% of the observed pathogenicity, respectively. However, coproduction of gelatinase and cytolysin did not increase virulence additively, accounting for 50.6% of the pathogenicity and therefore indicating a significant (26.7%) saturation effect. We employed a comparative genomic analysis approach using the 28 isolates comprising a collection of 82,356 annotated coding sequences (CDS) to identify 2,325 patterns of presence or absence among the investigated strains. Univariate statistical analysis of variance (ANOVA) established that individual patterns positively correlated (n = 61) with virulence. The patterns were investigated to identify potential new virulence traits, among which we found five patterns consisting of the phage03-like gene clusters. Strains harboring phage03 showed, on average, 17% higher killing of C. elegans (P = 4.4e(-6)). The phage03 gene cluster was also present in gelatinase-and-cytolysin-negative strain E. faecalis JH2-2. Deletion of this phage element from the JH2-2 clinical strain rendered the mutant apathogenic in C. elegans, and a similar mutant of the nosocomial V583 isolate showed significantly attenuated virulence. Bioinformatics investigation indicated that, unlike other E. faecalis virulence traits, phage03-like elements were found at a higher frequency among nosocomial isolates. In conclusion, our report provides a valuable virulence map that explains enhancement in E. faecalis virulence and contributes to a deeper comprehension of the genetic mechanism leading to the transition from commensalism to a pathogenic lifestyle.

CNOGpro: detection and quantification of CNVs in prokaryotic whole-genome sequencing data.

MOTIVATION: The explosion of whole-genome sequencing (WGS) as a tool in the mapping and understanding of genomes has been accompanied by an equally massive report of tools and pipelines for the analysis of DNA copy number variation (CNV). Most currently available tools are designed specifically for human genomes, with comparatively little literature devoted to CNVs in prokaryotic organisms. However, there are several idiosyncrasies in prokaryotic WGS data. This work proposes a step-by-step approach for detection and quantification of copy number variants specifically aimed at prokaryotes. RESULTS: After aligning WGS reads to a reference genome, we count the individual reads in a sliding window and normalize these counts for bias introduced by differences in GC content. We then investigate the coverage in two fundamentally different ways: (i) Employing a Hidden Markov Model and (ii) by repeated sampling with replacement (bootstrapping) on each individual gene. The latter bypasses the complex problem of breakpoint determination. To demonstrate our method, we apply it to real and simulated WGS data and benchmark it against two popular methods for CNV detection. The proposed methodology will in some cases represent a significant jump in accuracy from other current methods. AVAILABILITY AND IMPLEMENTATION: CNOGpro is written entirely in the R programming language and is available from the CRAN repository (http://cran.r-project.org) under the GNU General Public License.

A domain sequence approach to pangenomics: applications to Escherichia coli.

The study of microbial pangenomes relies on the computation of gene families, i.e. the clustering of coding sequences into groups of essentially similar genes. There is no standard approach to obtain such gene families. Ideally, the gene family computations should be robust against errors in the annotation of genes in various genomes. In an attempt to achieve this robustness, we propose to cluster sequences by their domain sequence, i.e. the ordered sequence of domains in their protein sequence. In a study of 347 genomes from Escherichia coli we find on average around 4500 proteins having hits in Pfam-A in every genome, clustering into around 2500 distinct domain sequence families in each genome. Across all genomes we find a total of 5724 such families. A binomial mixture model approach indicates this is around 95% of all domain sequences we would expect to see in E. coli in the future. A Heaps law analysis indicates the population of domain sequences is larger, but this analysis is also very sensitive to smaller changes in the computation procedure. The resolution between strains is good despite the coarse grouping obtained by domain sequence families. Clustering sequences by their ordered domain content give us domain sequence families, who are robust to errors in the gene prediction step. The computational load of the procedure scales linearly with the number of genomes, which is needed for the future explosion in the number of re-sequenced strains. The use of domain sequence families for a functional classification of strains clearly has some potential to be explored.

Complete genome sequence of the commensal Enterococcus faecalis 62, isolated from a healthy Norwegian infant.

The genome of Enterococcus faecalis 62, a commensal isolate from a healthy Norwegian infant, revealed multiple adaptive traits to the gastrointestinal tract (GIT) environment and the milk-containing diet of breast-fed infants. Adaptation to a commensal existence was emphasized by lactose and other carbohydrate metabolism genes within genomic islands, accompanied by the absence of virulence traits.