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April 21, 2020  |  

MSC: a metagenomic sequence classification algorithm.

Metagenomics is the study of genetic materials directly sampled from natural habitats. It has the potential to reveal previously hidden diversity of microscopic life largely due to the existence of highly parallel and low-cost next-generation sequencing technology. Conventional approaches align metagenomic reads onto known reference genomes to identify microbes in the sample. Since such a collection of reference genomes is very large, the approach often needs high-end computing machines with large memory which is not often available to researchers. Alternative approaches follow an alignment-free methodology where the presence of a microbe is predicted using the information about the unique k-mers present in the microbial genomes. However, such approaches suffer from high false positives due to trading off the value of k with the computational resources. In this article, we propose a highly efficient metagenomic sequence classification (MSC) algorithm that is a hybrid of both approaches. Instead of aligning reads to the full genomes, MSC aligns reads onto a set of carefully chosen, shorter and highly discriminating model sequences built from the unique k-mers of each of the reference sequences.Microbiome researchers are generally interested in two objectives of a taxonomic classifier: (i) to detect prevalence, i.e. the taxa present in a sample, and (ii) to estimate their relative abundances. MSC is primarily designed to detect prevalence and experimental results show that MSC is indeed a more effective and efficient algorithm compared to the other state-of-the-art algorithms in terms of accuracy, memory and runtime. Moreover, MSC outputs an approximate estimate of the abundances.The implementations are freely available for non-commercial purposes. They can be downloaded from https://drive.google.com/open?id=1XirkAamkQ3ltWvI1W1igYQFusp9DHtVl. © The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.


April 21, 2020  |  

Confident phylogenetic identification of uncultured prokaryotes through long read amplicon sequencing of the 16S-ITS-23S rRNA operon.

Amplicon sequencing of the 16S rRNA gene is the predominant method to quantify microbial compositions and to discover novel lineages. However, traditional short amplicons often do not contain enough information to confidently resolve their phylogeny. Here we present a cost-effective protocol that amplifies a large part of the rRNA operon and sequences the amplicons with PacBio technology. We tested our method on a mock community and developed a read-curation pipeline that reduces the overall read error rate to 0.18%. Applying our method on four environmental samples, we captured near full-length rRNA operon amplicons from a large diversity of prokaryotes. The method operated at moderately high-throughput (22286-37,850 raw ccs reads) and generated a large amount of putative novel archaeal 23S rRNA gene sequences compared to the archaeal SILVA database. These long amplicons allowed for higher resolution during taxonomic classification by means of long (~1000 bp) 16S rRNA gene fragments and for substantially more confident phylogenies by means of combined near full-length 16S and 23S rRNA gene sequences, compared to shorter traditional amplicons (250 bp of the 16S rRNA gene). We recommend our method to those who wish to cost-effectively and confidently estimate the phylogenetic diversity of prokaryotes in environmental samples at high throughput. © 2019 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.


April 21, 2020  |  

Strain-level metagenomic assignment and compositional estimation for long reads with MetaMaps.

Metagenomic sequence classification should be fast, accurate and information-rich. Emerging long-read sequencing technologies promise to improve the balance between these factors but most existing methods were designed for short reads. MetaMaps is a new method, specifically developed for long reads, capable of mapping a long-read metagenome to a comprehensive RefSeq database with >12,000 genomes in <16?GB or RAM on a laptop computer. Integrating approximate mapping with probabilistic scoring and EM-based estimation of sample composition, MetaMaps achieves >94% accuracy for species-level read assignment and r2?>?0.97 for the estimation of sample composition on both simulated and real data when the sample genomes or close relatives are present in the classification database. To address novel species and genera, which are comparatively harder to predict, MetaMaps outputs mapping locations and qualities for all classified reads, enabling functional studies (e.g. gene presence/absence) and detection of incongruities between sample and reference genomes.


April 21, 2020  |  

Mobilome of Brevibacterium aurantiacum Sheds Light on Its Genetic Diversity and Its Adaptation to Smear-Ripened Cheeses.

Brevibacterium aurantiacum is an actinobacterium that confers key organoleptic properties to washed-rind cheeses during the ripening process. Although this industrially relevant species has been gaining an increasing attention in the past years, its genome plasticity is still understudied due to the unavailability of complete genomic sequences. To add insights on the mobilome of this group, we sequenced the complete genomes of five dairy Brevibacterium strains and one non-dairy strain using PacBio RSII. We performed phylogenetic and pan-genome analyses, including comparisons with other publicly available Brevibacterium genomic sequences. Our phylogenetic analysis revealed that these five dairy strains, previously identified as Brevibacterium linens, belong instead to the B. aurantiacum species. A high number of transposases and integrases were observed in the Brevibacterium spp. strains. In addition, we identified 14 and 12 new insertion sequences (IS) in B. aurantiacum and B. linens genomes, respectively. Several stretches of homologous DNA sequences were also found between B. aurantiacum and other cheese rind actinobacteria, suggesting horizontal gene transfer (HGT). A HGT region from an iRon Uptake/Siderophore Transport Island (RUSTI) and an iron uptake composite transposon were found in five B. aurantiacum genomes. These findings suggest that low iron availability in milk is a driving force in the adaptation of this bacterial species to this niche. Moreover, the exchange of iron uptake systems suggests cooperative evolution between cheese rind actinobacteria. We also demonstrated that the integrative and conjugative element BreLI (Brevibacterium Lanthipeptide Island) can excise from B. aurantiacum SMQ-1417 chromosome. Our comparative genomic analysis suggests that mobile genetic elements played an important role into the adaptation of B. aurantiacum to cheese ecosystems.


April 21, 2020  |  

The Not-so-Sterile Womb: Evidence That the Human Fetus Is Exposed to Bacteria Prior to Birth.

The human microbiome includes trillions of bacteria, many of which play a vital role in host physiology. Numerous studies have now detected bacterial DNA in first-pass meconium and amniotic fluid samples, suggesting that the human microbiome may commence in utero. However, these data have remained contentious due to underlying contamination issues. Here, we have used a previously described method for reducing contamination in microbiome workflows to determine if there is a fetal bacterial microbiome beyond the level of background contamination. We recruited 50 women undergoing non-emergency cesarean section deliveries with no evidence of intra-uterine infection and collected first-pass meconium and amniotic fluid samples. Full-length 16S rRNA gene sequencing was performed using PacBio SMRT cell technology, to allow high resolution profiling of the fetal gut and amniotic fluid bacterial microbiomes. Levels of inflammatory cytokines were measured in amniotic fluid, and levels of immunomodulatory short chain fatty acids (SCFAs) were quantified in meconium. All meconium samples and most amniotic fluid samples (36/43) contained bacterial DNA. The meconium microbiome was dominated by reads that mapped to Pelomonas puraquae. Aside from this species, the meconium microbiome was remarkably heterogeneous between patients. The amniotic fluid microbiome was more diverse and contained mainly reads that mapped to typical skin commensals, including Propionibacterium acnes and Staphylococcus spp. All meconium samples contained acetate and propionate, at ratios similar to those previously reported in infants. P. puraquae reads were inversely correlated with meconium propionate levels. Amniotic fluid cytokine levels were associated with the amniotic fluid microbiome. Our results demonstrate that bacterial DNA and SCFAs are present in utero, and have the potential to influence the developing fetal immune system.


April 21, 2020  |  

Genomics-driven discovery of a biosynthetic gene cluster required for the synthesis of BII-Rafflesfungin from the fungus Phoma sp. F3723.

Phomafungin is a recently reported broad spectrum antifungal compound but its biosynthetic pathway is unknown. We combed publicly available Phoma genomes but failed to find any putative biosynthetic gene cluster that could account for its biosynthesis.Therefore, we sequenced the genome of one of our Phoma strains (F3723) previously identified as having antifungal activity in a high-throughput screen. We found a biosynthetic gene cluster that was predicted to synthesize a cyclic lipodepsipeptide that differs in the amino acid composition compared to Phomafungin. Antifungal activity guided isolation yielded a new compound, BII-Rafflesfungin, the structure of which was determined.We describe the NRPS-t1PKS cluster ‘BIIRfg’ compatible with the synthesis of the cyclic lipodepsipeptide BII-Rafflesfungin [HMHDA-L-Ala-L-Glu-L-Asn-L-Ser-L-Ser-D-Ser-D-allo-Thr-Gly]. We report new Stachelhaus codes for Ala, Glu, Asn, Ser, Thr, and Gly. We propose a mechanism for BII-Rafflesfungin biosynthesis, which involves the formation of the lipid part by BIIRfg_PKS followed by activation and transfer of the lipid chain by a predicted AMP-ligase on to the first PCP domain of the BIIRfg_NRPS gene.


April 21, 2020  |  

Metaepigenomic analysis reveals the unexplored diversity of DNA methylation in an environmental prokaryotic community.

DNA methylation plays important roles in prokaryotes, and their genomic landscapes-prokaryotic epigenomes-have recently begun to be disclosed. However, our knowledge of prokaryotic methylation systems is focused on those of culturable microbes, which are rare in nature. Here, we used single-molecule real-time and circular consensus sequencing techniques to reveal the ‘metaepigenomes’ of a microbial community in the largest lake in Japan, Lake Biwa. We reconstructed 19 draft genomes from diverse bacterial and archaeal groups, most of which are yet to be cultured. The analysis of DNA chemical modifications in those genomes revealed 22 methylated motifs, nine of which were novel. We identified methyltransferase genes likely responsible for methylation of the novel motifs, and confirmed the catalytic specificities of four of them via transformation experiments using synthetic genes. Our study highlights metaepigenomics as a powerful approach for identification of the vast unexplored variety of prokaryotic DNA methylation systems in nature.


April 21, 2020  |  

Assignment of virus and antimicrobial resistance genes to microbial hosts in a complex microbial community by combined long-read assembly and proximity ligation.

We describe a method that adds long-read sequencing to a mix of technologies used to assemble a highly complex cattle rumen microbial community, and provide a comparison to short read-based methods. Long-read alignments and Hi-C linkage between contigs support the identification of 188 novel virus-host associations and the determination of phage life cycle states in the rumen microbial community. The long-read assembly also identifies 94 antimicrobial resistance genes, compared to only seven alleles in the short-read assembly. We demonstrate novel techniques that work synergistically to improve characterization of biological features in a highly complex rumen microbial community.


April 21, 2020  |  

Complete genome sequence of 3-chlorobenzoate-degrading bacterium Cupriavidus necator NH9 and reclassification of the strains of the genera Cupriavidus and Ralstonia based on phylogenetic and whole-genome sequence analyses.

Cupriavidus necator NH9, a 3-chlorobenzoate (3-CB)-degrading bacterium, was isolated from soil in Japan. In this study, the complete genome sequence of NH9 was obtained via PacBio long-read sequencing to better understand the genetic components contributing to the strain’s ability to degrade aromatic compounds, including 3-CB. The genome of NH9 comprised two circular chromosomes (4.3 and 3.4 Mb) and two circular plasmids (427 and 77 kb) containing 7,290 coding sequences, 15 rRNA and 68 tRNA genes. Kyoto Encyclopedia of Genes and Genomes pathway analysis of the protein-coding sequences in NH9 revealed a capacity to completely degrade benzoate, 2-, 3-, or 4-hydroxybenzoate, 2,3-, 2,5-, or 3,4-dihydroxybenzoate, benzoylformate, and benzonitrile. To validate the identification of NH9, phylogenetic analyses (16S rRNA sequence-based tree and multilocus sequence analysis) and whole-genome sequence analyses (average nucleotide identity, percentage of conserved proteins, and tetra-nucleotide analyses) were performed, confirming that NH9 is a C. necator strain. Over the course of our investigation, we noticed inconsistencies in the classification of several strains that were supposed to belong to the two closely-related genera Cupriavidus and Ralstonia. As a result of whole-genome sequence analysis of 46 Cupriavidus strains and 104 Ralstonia strains, we propose that the taxonomic classification of 41 of the 150 strains should be changed. Our results provide a clear delineation of the two genera based on genome sequences, thus allowing taxonomic identification of strains belonging to these two genera.


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