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Auto Tag: Neisseria

October 23, 2019  |  

Creating and evaluating accurate CRISPR-Cas9 scalpels for genomic surgery.

The simplicity of site-specific genome targeting by type II clustered, regularly interspaced, short palindromic repeat (CRISPR)-Cas9 nucleases, along with their robust activity profile, has changed the landscape of genome editing. These favorable properties have made the CRISPR-Cas9 system the technology of choice for sequence-specific modifications in vertebrate systems. For many applications, whether the focus is on basic science investigations or therapeutic efficacy, activity and precision are important considerations when one is choosing a nuclease platform, target site and delivery method. Here we review recent methods for increasing the activity and accuracy of Cas9 and assessing the extent of off-target cleavage events.

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September 22, 2019  |  

16S rRNA long-read sequencing of the granulation tissue from nonsmokers and smokers-severe chronic periodontitis patients

Smoking has been associated with increased risk of periodontitis. The aim of the present study was to compare the periodontal disease severity among smokers and nonsmokers which may help in better understanding of predisposition to this chronic inflammation mediated diseases. We selected deep-seated infected granulation tissue removed during periodontal flap surgery procedures for identification and differential abundance of residential bacterial species among smokers and nonsmokers through long-read sequencing technology targeting full-length 16S rRNA gene. A total of 8 phyla were identified among which Firmicutes and Bacteroidetes were most dominating. Differential abundance analysis of OTUs through PICRUST showed significant (p>0.05) abundance of Phyla-Fusobacteria (Streptobacillus moniliformis); Phyla-Firmicutes (Streptococcus equi), and Phyla Proteobacteria (Enhydrobacter aerosaccus) in nonsmokers compared to smokers. The differential abundance of oral metagenomes in smokers showed significant enrichment of host genes modulating pathways involving primary immunodeficiency, citrate cycle, streptomycin biosynthesis, vitamin B6 metabolism, butanoate metabolism, glycine, serine, and threonine metabolism pathways. While thiamine metabolism, amino acid metabolism, homologous recombination, epithelial cell signaling, aminoacyl-tRNA biosynthesis, phosphonate/phosphinate metabolism, polycyclic aromatic hydrocarbon degradation, synthesis and degradation of ketone bodies, translation factors, Ascorbate and aldarate metabolism, and DNA replication pathways were significantly enriched in nonsmokers, modulation of these pathways in oral cavities due to differential enrichment of metagenomes in smokers may lead to an increased susceptibility to infections and/or higher formation of DNA adducts, which may increase the risk of carcinogenesis.

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September 22, 2019  |  

Metagenomic binning and association of plasmids with bacterial host genomes using DNA methylation.

Shotgun metagenomics methods enable characterization of microbial communities in human microbiome and environmental samples. Assembly of metagenome sequences does not output whole genomes, so computational binning methods have been developed to cluster sequences into genome ‘bins’. These methods exploit sequence composition, species abundance, or chromosome organization but cannot fully distinguish closely related species and strains. We present a binning method that incorporates bacterial DNA methylation signatures, which are detected using single-molecule real-time sequencing. Our method takes advantage of these endogenous epigenetic barcodes to resolve individual reads and assembled contigs into species- and strain-level bins. We validate our method using synthetic and real microbiome sequences. In addition to genome binning, we show that our method links plasmids and other mobile genetic elements to their host species in a real microbiome sample. Incorporation of DNA methylation information into shotgun metagenomics analyses will complement existing methods to enable more accurate sequence binning.

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September 22, 2019  |  

Profiling of oral microbiota in early childhood caries using Single-Molecule Real-Time Sequencing

Background: Alterations of oral microbiota are the main cause of the progression of caries. The goal of this study was to characterize the oral microbiota in childhood caries based on single-molecule real-time sequencing. Methods: A total of 21 preschoolers, aged 3-5 years old with severe early childhood caries, and 20 age-matched, caries-free children as controls were recruited. Saliva samples were collected, followed by DNA extraction, Pacbio sequencing and phylogenetic analyses of the oral microbial communities. Results: 876 species derived from 13 known bacterial phyla and 110 genera were detected from 41 children using Pacbio sequencing. At the species level, 38 species, including Veillonella spp., Streptococcus spp., Prevotella spp. and Lactobacillus spp., showed higher abundance in the caries group compared to the caries-free group (p<0.05). The core microbiota at the genus and species levels was more stable in the caries-free micro-ecological niche. At follow-up, oral examinations 6 months after sample collection, development of new dental caries was observed in 5 children (the transitional group) among the 21 caries free children. Compared with the caries-free children, in the transitional and caries groups, 6 species, which were more abundant in the caries-free group, exhibited a relatively low abundance in both the caries group and the transitional group (p<0.05). We conclude that Abiotrophia spp., Neisseria spp. and Veillonella spp., are essential for maintaining a healthy oral microbial ecosystem. Prevotella spp., Lactobacillus spp., Dialister spp. and Filifactor spp. may be related to the pathogenesis and progression of dental caries.

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September 22, 2019  |  

MetaSort untangles metagenome assembly by reducing microbial community complexity.

Most current approaches to analyse metagenomic data rely on reference genomes. Novel microbial communities extend far beyond the coverage of reference databases and de novo metagenome assembly from complex microbial communities remains a great challenge. Here we present a novel experimental and bioinformatic framework, metaSort, for effective construction of bacterial genomes from metagenomic samples. MetaSort provides a sorted mini-metagenome approach based on flow cytometry and single-cell sequencing methodologies, and employs new computational algorithms to efficiently recover high-quality genomes from the sorted mini-metagenome by the complementary of the original metagenome. Through extensive evaluations, we demonstrated that metaSort has an excellent and unbiased performance on genome recovery and assembly. Furthermore, we applied metaSort to an unexplored microflora colonized on the surface of marine kelp and successfully recovered 75 high-quality genomes at one time. This approach will greatly improve access to microbial genomes from complex or novel communities.

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September 22, 2019  |  

Species-level bacterial community profiling of the healthy sinonasal microbiome using Pacific Biosciences sequencing of full-length 16S rRNA genes.

Pan-bacterial 16S rRNA microbiome surveys performed with massively parallel DNA sequencing technologies have transformed community microbiological studies. Current 16S profiling methods, however, fail to provide sufficient taxonomic resolution and accuracy to adequately perform species-level associative studies for specific conditions. This is due to the amplification and sequencing of only short 16S rRNA gene regions, typically providing for only family- or genus-level taxonomy. Moreover, sequencing errors often inflate the number of taxa present. Pacific Biosciences’ (PacBio’s) long-read technology in particular suffers from high error rates per base. Herein, we present a microbiome analysis pipeline that takes advantage of PacBio circular consensus sequencing (CCS) technology to sequence and error correct full-length bacterial 16S rRNA genes, which provides high-fidelity species-level microbiome data.Analysis of a mock community with 20 bacterial species demonstrated 100% specificity and sensitivity with regard to taxonomic classification. Examination of a 250-plus species mock community demonstrated correct species-level classification of >?90% of taxa, and relative abundances were accurately captured. The majority of the remaining taxa were demonstrated to be multiply, incorrectly, or incompletely classified. Using this methodology, we examined the microgeographic variation present among the microbiomes of six sinonasal sites, by both swab and biopsy, from the anterior nasal cavity to the sphenoid sinus from 12 subjects undergoing trans-sphenoidal hypophysectomy. We found greater variation among subjects than among sites within a subject, although significant within-individual differences were also observed. Propiniobacterium acnes (recently renamed Cutibacterium acnes) was the predominant species throughout, but was found at distinct relative abundances by site.Our microbial composition analysis pipeline for single-molecule real-time 16S rRNA gene sequencing (MCSMRT, https://github.com/jpearl01/mcsmrt ) overcomes deficits of standard marker gene-based microbiome analyses by using CCS of entire 16S rRNA genes to provide increased taxonomic and phylogenetic resolution. Extensions of this approach to other marker genes could help refine taxonomic assignments of microbial species and improve reference databases, as well as strengthen the specificity of associations between microbial communities and dysbiotic states.

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September 22, 2019  |  

A response to Lindsey et al. “Wolbachia pipientis should not be split into multiple species: A response to Ramírez-Puebla et al.”.

In Ramírez-Puebla et al. [18] we compared 34 Wolbachia genomes and constructed phylogenetic trees using genomic data. In general, our results were congruent with previously reported phy- logenetic trees [5,9]. Our datasets were carefully selected, checked and analyzed avoiding horizontally transferred genes. In the case of the wAna genome we did not use the raw data, but the assem- bled genome [22] and 31 genes were used to compare in a dataset of conserved proteins. To confirm our conclusions a new phyloge- nomic analysis was performed excluding the wAna strain in the dataset (Fig. 1). The same topology was obtained, therefore indi- cating that the results were not affected by the presence of this particular strain.

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September 22, 2019  |  

Saliva and tooth biofilm bacterial microbiota in adolescents in a low caries community.

The oral cavity harbours a complex microbiome that is linked to dental diseases and serves as a route to other parts of the body. Here, the aims were to characterize the oral microbiota by deep sequencing in a low-caries population with regular dental care since childhood and search for association with caries prevalence and incidence. Saliva and tooth biofilm from 17-year-olds and mock bacteria communities were analysed using 16S rDNA Illumina MiSeq (v3-v4) and PacBio SMRT (v1-v8) sequencing including validity and reliability estimates. Caries was scored at 17 and 19 years of age. Both sequencing platforms revealed that Firmicutes dominated in the saliva, whereas Firmicutes and Actinobacteria abundances were similar in tooth biofilm. Saliva microbiota discriminated caries-affected from caries-free adolescents, with enumeration of Scardovia wiggsiae, Streptococcus mutans, Bifidobacterium longum, Leptotrichia sp. HOT498, and Selenomonas spp. in caries-affected participants. Adolescents with B. longum in saliva had significantly higher 2-year caries increment. PacBio SMRT revealed Corynebacterium matruchotii as the most prevalent species in tooth biofilm. In conclusion, both sequencing methods were reliable and valid for oral samples, and saliva microbiota was associated with cross-sectional caries prevalence, especially S. wiggsiae, S. mutans, and B. longum; the latter also with the 2-year caries incidence.

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September 22, 2019  |  

Next-generation sequencing for pathogen detection and identification

Over the past decade, the field of genomics has seen such drastic improvements in sequencing chemistries that high-throughput sequencing, or next-generation sequencing (NGS), is being applied to generate data across many disciplines. NGS instruments are becoming less expensive, faster, and smaller, and therefore are being adopted in an increasing number of laboratories, including clinical laboratories. Thus far, clinical use of NGS has been mostly focused on the human genome, for purposes such as characterizing the molecular basis of cancer or for diagnosing and understanding the basis of rare genetic disorders. There are, however, an increasing number of examples whereby NGS is employed to discover novel pathogens, and these cases provide precedent for the use of NGS in microbial diagnostics. NGS has many advantages over traditional microbial diagnostic methods, such as unbiased rather than pathogen-specific protocols, ability to detect fastidious or non-culturable organisms, and ability to detect co-infections. One of the most impressive advantages of NGS is that it requires little or no prior knowledge of the pathogen, unlike many other diagnostic assays; therefore for pathogen discovery, NGS is very valuable. However, despite these advantages, there are challenges involved in implementing NGS for routine clinical microbiological diagnosis. We discuss these advantages and challenges in the context of recently described research studies.

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September 22, 2019  |  

Metataxonomic and metagenomic approaches vs. culture-based techniques for clinical pathology.

Diagnoses that are both timely and accurate are critically important for patients with life-threatening or drug resistant infections. Technological improvements in High-Throughput Sequencing (HTS) have led to its use in pathogen detection and its application in clinical diagnoses of infectious diseases. The present study compares two HTS methods, 16S rRNA marker gene sequencing (metataxonomics) and whole metagenomic shotgun sequencing (metagenomics), in their respective abilities to match the same diagnosis as traditional culture methods (culture inference) for patients with ventilator associated pneumonia (VAP). The metagenomic analysis was able to produce the same diagnosis as culture methods at the species-level for five of the six samples, while the metataxonomic analysis was only able to produce results with the same species-level identification as culture for two of the six samples. These results indicate that metagenomic analyses have the accuracy needed for a clinical diagnostic tool, but full integration in diagnostic protocols is contingent on technological improvements to decrease turnaround time and lower costs.

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September 22, 2019  |  

Sequencing 16S rRNA gene fragments using the PacBio SMRT DNA sequencing system.

Over the past 10 years, microbial ecologists have largely abandoned sequencing 16S rRNA genes by the Sanger sequencing method and have instead adopted highly parallelized sequencing platforms. These new platforms, such as 454 and Illumina’s MiSeq, have allowed researchers to obtain millions of high quality but short sequences. The result of the added sequencing depth has been significant improvements in experimental design. The tradeoff has been the decline in the number of full-length reference sequences that are deposited into databases. To overcome this problem, we tested the ability of the PacBio Single Molecule, Real-Time (SMRT) DNA sequencing platform to generate sequence reads from the 16S rRNA gene. We generated sequencing data from the V4, V3-V5, V1-V3, V1-V5, V1-V6, and V1-V9 variable regions from within the 16S rRNA gene using DNA from a synthetic mock community and natural samples collected from human feces, mouse feces, and soil. The mock community allowed us to assess the actual sequencing error rate and how that error rate changed when different curation methods were applied. We developed a simple method based on sequence characteristics and quality scores to reduce the observed error rate for the V1-V9 region from 0.69 to 0.027%. This error rate is comparable to what has been observed for the shorter reads generated by 454 and Illumina’s MiSeq sequencing platforms. Although the per base sequencing cost is still significantly more than that of MiSeq, the prospect of supplementing reference databases with full-length sequences from organisms below the limit of detection from the Sanger approach is exciting.

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September 22, 2019  |  

Research benefits of storing genitourinary samples: 16S rRNA sequencing to evaluate vaginal bacterial communities.

Using well-characterised, but old and carefully frozen genital tract research samples may be a cost-effective way of performing metagenomic studies, but risks loss of low abundance (but relevant) bacterial species DNA. Moi et al.1 used 16S rRNA and UreDNA sequencing to detect ureaplasmas in frozen urine samples collected from 362 men with NGU in 2010–2011. They found that urethral inflammatory responses to ureaplasmas were less severe than to Chlamydia trachomatis and Mycoplasma genitalium.

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September 22, 2019  |  

Accurate determination of bacterial abundances in human metagenomes using full-length 16S sequencing reads

DNA sequencing of PCR-amplified marker genes, especially but not limited to the 16S rRNA gene, is perhaps the most common approach for profiling microbial communities. Due to technological constraints of commonly available DNA sequencing, these approaches usually take the form of short reads sequenced from a narrow, targeted variable region, with a corresponding loss of taxonomic resolution relative to the full length marker gene. We use Pacific Biosciences single-molecule, real-time circular consensus sequencing to sequence amplicons spanning the entire length of the 16S rRNA gene. However, this sequencing technology suffers from high sequencing error rate that needs to be addressed in order to take full advantage of the longer sequence. Here, we present a method to model the sequencing error process using a generalized pair hidden Markov chain model and estimate bacterial abundances in microbial samples. We demonstrate, with simulated and real data, that our model and its associated estimation procedure are able to give accurate estimates at the species (or subspecies) level, and is more flexible than existing methods like SImple Non-Bayesian TAXonomy (SINTAX).

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September 22, 2019  |  

Genomics and host specialization of honey bee and bumble bee gut symbionts.

Gilliamella apicola and Snodgrassella alvi are dominant members of the honey bee (Apis spp.) and bumble bee (Bombus spp.) gut microbiota. We generated complete genomes of the type strains G. apicola wkB1(T) and S. alvi wkB2(T) (isolated from Apis), as well as draft genomes for four other strains from Bombus. G. apicola and S. alvi were found to occupy very different metabolic niches: The former is a saccharolytic fermenter, whereas the latter is an oxidizer of carboxylic acids. Together, they may form a syntrophic network for partitioning of metabolic resources. Both species possessed numerous genes [type 6 secretion systems, repeats in toxin (RTX) toxins, RHS proteins, adhesins, and type IV pili] that likely mediate cell-cell interactions and gut colonization. Variation in these genes could account for the host fidelity of strains observed in previous phylogenetic studies. Here, we also show the first experimental evidence, to our knowledge, for this specificity in vivo: Strains of S. alvi were able to colonize their native bee host but not bees of another genus. Consistent with specific, long-term host association, comparative genomic analysis revealed a deep divergence and little or no gene flow between Apis and Bombus gut symbionts. However, within a host type (Apis or Bombus), we detected signs of horizontal gene transfer between G. apicola and S. alvi, demonstrating the importance of the broader gut community in shaping the evolution of any one member. Our results show that host specificity is likely driven by multiple factors, including direct host-microbe interactions, microbe-microbe interactions, and social transmission.

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September 22, 2019  |  

Different next generation sequencing platforms produce different microbial profiles and diversity in cystic fibrosis sputum.

Cystic fibrosis (CF) is an autosomal recessive disease characterized by recurrent lung infections. Studies of the lung microbiome have shown an association between decreasing diversity and progressive disease. 454 pyrosequencing has frequently been used to study the lung microbiome in CF, but will no longer be supported. We sought to identify the benefits and drawbacks of using two state-of-the-art next generation sequencing (NGS) platforms, MiSeq and PacBio RSII, to characterize the CF lung microbiome. Each has its advantages and limitations.Twelve samples of extracted bacterial DNA were sequenced on both MiSeq and PacBio NGS platforms. DNA was amplified for the V4 region of the 16S rRNA gene and libraries were sequenced on the MiSeq sequencing platform, while the full 16S rRNA gene was sequenced on the PacBio RSII sequencing platform. Raw FASTQ files generated by the MiSeq and PacBio platforms were processed in mothur v1.35.1.There was extreme discordance in alpha-diversity of the CF lung microbiome when using the two platforms. Because of its depth of coverage, sequencing of the 16S rRNA V4 gene region using MiSeq allowed for the observation of many more operational taxonomic units (OTUs) and higher Chao1 and Shannon indices than the PacBio RSII. Interestingly, several patients in our cohort had Escherichia, an unusual pathogen in CF. Also, likely because of its coverage of the complete 16S rRNA gene, only PacBio RSII was able to identify Burkholderia, an important CF pathogen.When comparing microbiome diversity in clinical samples from CF patients using 16S sequences, MiSeq and PacBio NGS platforms may generate different results in microbial community composition and structure. It may be necessary to use different platforms when trying to correctly identify dominant pathogens versus measuring alpha-diversity estimates, and it would be important to use the same platform for comparisons to minimize errors in interpretation. Copyright © 2016 Elsevier B.V. All rights reserved.

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