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September 22, 2019

Evaluation of PacBio sequencing for full-length bacterial 16S rRNA gene classification.

Currently, bacterial 16S rRNA gene analyses are based on sequencing of individual variable regions of the 16S rRNA gene (Kozich, et al Appl Environ Microbiol 79:5112-5120, 2013).This short read approach can introduce biases. Thus, full-length bacterial 16S rRNA gene sequencing is needed to reduced biases. A new alternative for full-length bacterial 16S rRNA gene sequencing is offered by PacBio single molecule, real-time (SMRT) technology. The aim of our study was to validate PacBio P6 sequencing chemistry using three approaches: 1) sequencing the full-length bacterial 16S rRNA gene from a single bacterial species Staphylococcus aureus to analyze error modes and to optimize the bioinformatics pipeline; 2) sequencing the full-length bacterial 16S rRNA gene from a pool of 50 different bacterial colonies from human stool samples to compare with full-length bacterial 16S rRNA capillary sequence; and 3) sequencing the full-length bacterial 16S rRNA genes from 11 vaginal microbiome samples and compare with in silico selected bacterial 16S rRNA V1V2 gene region and with bacterial 16S rRNA V1V2 gene regions sequenced using the Illumina MiSeq.Our optimized bioinformatics pipeline for PacBio sequence analysis was able to achieve an error rate of 0.007% on the Staphylococcus aureus full-length 16S rRNA gene. Capillary sequencing of the full-length bacterial 16S rRNA gene from the pool of 50 colonies from stool identified 40 bacterial species of which up to 80% could be identified by PacBio full-length bacterial 16S rRNA gene sequencing. Analysis of the human vaginal microbiome using the bacterial 16S rRNA V1V2 gene region on MiSeq generated 129 operational taxonomic units (OTUs) from which 70 species could be identified. For the PacBio, 36,000 sequences from over 58,000 raw reads could be assigned to a barcode, and the in silico selected bacterial 16S rRNA V1V2 gene region generated 154 OTUs grouped into 63 species, of which 62% were shared with the MiSeq dataset. The PacBio full-length bacterial 16S rRNA gene datasets generated 261 OTUs, which were grouped into 52 species, of which 54% were shared with the MiSeq dataset. Alpha diversity index reported a higher diversity in the MiSeq dataset.The PacBio sequencing error rate is now in the same range of the previously widely used Roche 454 sequencing platform and current MiSeq platform. Species-level microbiome analysis revealed some inconsistencies between the full-length bacterial 16S rRNA gene capillary sequencing and PacBio sequencing.

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September 22, 2019

The habu genome reveals accelerated evolution of venom protein genes.

Evolution of novel traits is a challenging subject in biological research. Several snake lineages developed elaborate venom systems to deliver complex protein mixtures for prey capture. To understand mechanisms involved in snake venom evolution, we decoded here the ~1.4-Gb genome of a habu, Protobothrops flavoviridis. We identified 60 snake venom protein genes (SV) and 224 non-venom paralogs (NV), belonging to 18 gene families. Molecular phylogeny reveals early divergence of SV and NV genes, suggesting that one of the four copies generated through two rounds of whole-genome duplication was modified for use as a toxin. Among them, both SV and NV genes in four major components were extensively duplicated after their diversification, but accelerated evolution is evident exclusively in the SV genes. Both venom-related SV and NV genes are significantly enriched in microchromosomes. The present study thus provides a genetic background for evolution of snake venom composition.

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September 22, 2019

Gut microbiota, nitric oxide, and microglia as prerequisites for neurodegenerative disorders.

Regulating fluctuating endogenous nitric oxide (NO) levels is necessary for proper physiological functions. Aberrant NO pathways are implicated in a number of neurological disorders, including Alzheimer’s disease (AD) and Parkinson’s disease. The mechanism of NO in oxidative and nitrosative stress with pathological consequences involves reactions with reactive oxygen species (e.g., superoxide) to form the highly reactive peroxynitrite, hydrogen peroxide, hypochloride ions and hydroxyl radical. NO levels are typically regulated by endogenous nitric oxide synthases (NOS), and inflammatory iNOS is implicated in the pathogenesis of neurodegenerative diseases, in which elevated NO mediates axonal degeneration and activates cyclooxygenases to provoke neuroinflammation. NO also instigates a down-regulated secretion of brain-derived neurotrophic factor, which is essential for neuronal survival, development and differentiation, synaptogenesis, and learning and memory. The gut-brain axis denotes communication between the enteric nervous system (ENS) of the GI tract and the central nervous system (CNS) of the brain, and the modes of communication include the vagus nerve, passive diffusion and carrier by oxyhemoglobin. Amyloid precursor protein that forms amyloid beta plaques in AD is normally expressed in the ENS by gut bacteria, but when amyloid beta accumulates, it compromises CNS functions. Escherichia coli and Salmonella enterica are among the many bacterial strains that express and secrete amyloid proteins and contribute to AD pathogenesis. Gut microbiota is essential for regulating microglia maturation and activation, and activated microglia secrete significant amounts of iNOS. Pharmacological interventions and lifestyle modifications to rectify aberrant NO signaling in AD include NOS inhibitors, NMDA receptor antagonists, potassium channel modulators, probiotics, diet, and exercise.

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September 22, 2019

PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme.

High-throughput transcriptome sequencing (RNA-seq) technology promises to discover novel protein-coding and non-coding transcripts, particularly the identification of long non-coding RNAs (lncRNAs) from de novo sequencing data. This requires tools that are not restricted by prior gene annotations, genomic sequences and high-quality sequencing.We present an alignment-free tool called PLEK (predictor of long non-coding RNAs and messenger RNAs based on an improved k-mer scheme), which uses a computational pipeline based on an improved k-mer scheme and a support vector machine (SVM) algorithm to distinguish lncRNAs from messenger RNAs (mRNAs), in the absence of genomic sequences or annotations. The performance of PLEK was evaluated on well-annotated mRNA and lncRNA transcripts. 10-fold cross-validation tests on human RefSeq mRNAs and GENCODE lncRNAs indicated that our tool could achieve accuracy of up to 95.6%. We demonstrated the utility of PLEK on transcripts from other vertebrates using the model built from human datasets. PLEK attained >90% accuracy on most of these datasets. PLEK also performed well using a simulated dataset and two real de novo assembled transcriptome datasets (sequenced by PacBio and 454 platforms) with relatively high indel sequencing errors. In addition, PLEK is approximately eightfold faster than a newly developed alignment-free tool, named Coding-Non-Coding Index (CNCI), and 244 times faster than the most popular alignment-based tool, Coding Potential Calculator (CPC), in a single-threading running manner.PLEK is an efficient alignment-free computational tool to distinguish lncRNAs from mRNAs in RNA-seq transcriptomes of species lacking reference genomes. PLEK is especially suitable for PacBio or 454 sequencing data and large-scale transcriptome data. Its open-source software can be freely downloaded from https://sourceforge.net/projects/plek/files/.

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September 22, 2019

Long-read, Single Molecule, Real-Time (SMRT) DNA Sequencing for metagenomic applications

In this chapter, we describe applications of single molecule, real-time (SMRT) DNA sequencing toward metagenomic research. The long sequence reads, combined with a lack of bias with respect to DNA sequence context or GC content, facilitate a more comprehensive analysis of the genomic constitution of microbial communities. Full-length 16S RNA gene sequencing at high (>99%) accuracy allows for species-level characterization of community members concomitant with the determination of community structure. The application of SMRT sequencing to whole-community shotgun microbial metagenomics has also been discussed.

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September 22, 2019

Soil microbial communities are shaped by plant-driven changes in resource availability during secondary succession.

Although we understand the ecological processes eliciting changes in plant community composition during secondary succession, we do not understand whether co-occurring changes in plant detritus shape saprotrophic microbial communities in soil. In this study, we investigated soil microbial composition and function across an old-field chronosequence ranging from 16 to 86 years following agricultural abandonment, as well as three forests representing potential late-successional ecosystems. Fungal and bacterial community composition was quantified from ribosomal DNA, and insight into the functional potential of the microbial community to decay plant litter was gained from shotgun metagenomics and extracellular enzyme assays. Accumulation of soil organic matter across the chronosequence exerted a positive and significant effect on fungal phylogenetic ß-diversity and the activity of extracellular enzymes with lignocellulolytic activity. In addition, the increasing abundance of lignin-rich C4 grasses was positively related to the composition of fungal genes with lignocellulolytic function, thereby linking plant community composition, litter biochemistry, and microbial community function. However, edaphic properties were the primary agent shaping bacterial communities, as bacterial ß-diversity and variation in functional gene composition displayed a significant and positive relationship to soil pH across the chronosequence. The late-successional forests were compositionally distinct from the oldest old fields, indicating that substantial changes occur in soil microbial communities as old fields give way to forests. Taken together, our observations demonstrate that plants govern the turnover of soil fungal communities and functional characteristics during secondary succession, due to the continual input of detritus and differences in litter biochemistry among plant species.

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September 22, 2019

ALE: a generic assembly likelihood evaluation framework for assessing the accuracy of genome and metagenome assemblies.

Researchers need general purpose methods for objectively evaluating the accuracy of single and metagenome assemblies and for automatically detecting any errors they may contain. Current methods do not fully meet this need because they require a reference, only consider one of the many aspects of assembly quality or lack statistical justification, and none are designed to evaluate metagenome assemblies.In this article, we present an Assembly Likelihood Evaluation (ALE) framework that overcomes these limitations, systematically evaluating the accuracy of an assembly in a reference-independent manner using rigorous statistical methods. This framework is comprehensive, and integrates read quality, mate pair orientation and insert length (for paired-end reads), sequencing coverage, read alignment and k-mer frequency. ALE pinpoints synthetic errors in both single and metagenomic assemblies, including single-base errors, insertions/deletions, genome rearrangements and chimeric assemblies presented in metagenomes. At the genome level with real-world data, ALE identifies three large misassemblies from the Spirochaeta smaragdinae finished genome, which were all independently validated by Pacific Biosciences sequencing. At the single-base level with Illumina data, ALE recovers 215 of 222 (97%) single nucleotide variants in a training set from a GC-rich Rhodobacter sphaeroides genome. Using real Pacific Biosciences data, ALE identifies 12 of 12 synthetic errors in a Lambda Phage genome, surpassing even Pacific Biosciences’ own variant caller, EviCons. In summary, the ALE framework provides a comprehensive, reference-independent and statistically rigorous measure of single genome and metagenome assembly accuracy, which can be used to identify misassemblies or to optimize the assembly process.ALE is released as open source software under the UoI/NCSA license at http://www.alescore.org. It is implemented in C and Python.

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September 22, 2019

Composition and pathogenic potential of a microbial bioremediation product used for crude oil degradation.

A microbial bioremediation product (MBP) used for large-scale oil degradation was investigated for microbial constituents and possible pathogenicity. Aerobic growth on various media yielded >108 colonies mL-1. Full-length 16S rDNA sequencing and fatty acid profiling from morphologically distinct colonies revealed =13 distinct genera. Full-length 16S rDNA library sequencing, by either Sanger or long-read PacBio technology, suggested that up to 21% of the MBP was composed of Arcobacter. Other high abundance microbial constituents (>6%) included the genera Proteus, Enterococcus, Dysgonomonas and several genera in the order Bacteroidales. The MBP was most susceptible to ciprofloxacin, doxycycline, gentamicin, and meropenam. MBP exposure of human HT29 and A549 cells caused significant cytotoxicity, and bacterial growth and adherence. An acellular MBP filtrate was also cytotoxic to HT29, but not A549. Both MBP and filtrate exposures elevated the neutrophil chemoattractant IL-8. In endotracheal murine exposures, bacterial pulmonary clearance was complete after one-week. Elevation of pro-inflammatory cytokines IL-1ß, IL-6, and TNF-a, and chemokines KC and MCP-1 occurred between 2h and 48h post-exposure, followed by restoration to baseline levels at 96h. Cytokine/chemokine signalling was accompanied by elevated blood neutrophils and monocytes at 4h and 48h, respectively. Peripheral acute phase response markers were maximal at 24h. All indicators examined returned to baseline values by 168h. In contrast to HT29, but similar to A549 observations, MBP filtrate did not induce significant murine effects with the indicators examined. The results demonstrated the potentially complex nature of MBPs and transient immunological effects during exposure. Products containing microbes should be scrutinized for pathogenic components and subjected to characterisation and quality validation prior to commercial release.

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September 22, 2019

Metagenomic SMRT sequencing-based exploration of novel lignocellulose-degrading capability in wood detritus from Torreya nucifera in Bija forest on Jeju Island.

Lignocellulose, mostly composed of cellulose, hemicellulose and lignin generated through secondary growth of woody plant, is considered as promising resources for bio-fuel. In order to use lignocellulose as a biofuel, the biodegradation besides high-cost chemical treatments were applied, but its knowledge on decomposition of lignocellulose occurring in a natural environment were insufficient. We analyzed 16S rRNA gene and metagenome to understand how the lignocellulose are decomposed naturally in decayed Torreya nucifera (L) of Bija forest (Bijarim) in Gotjawal, an ecologically distinct environment. A total of 464,360 reads were obtained from 16S rRNA gene sequencing, representing diverse phyla; Proteobacteria (51%), Bacteroidetes (11%) and Actinobacteria (10%). The metagenome analysis using Single Molecules Real-Time Sequencing revealed that the assembled contigs determined by originated from Proteobacteria (58%) and Actinobacteria (10.3%). Carbohydrate Active enZYmes (CAZy) and Protein families (Pfam) based analysis showed that Proteobacteria was involved in degrading whole lignocellulose and Actinobacteria played a role only in a part of hemicellulose degradation. Combining these results, it suggested that Proteobacteria and Actinobacteria had selective biodegradation potential for different lignocellulose substrate. Thus, it is considered that understanding of the systemic microbial degradation pathways may be a useful strategy for recycle of lignocellulosic biomass and the microbial enzymes in Bija forest can be useful natural resources in industrial processes.

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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

Effects of antibiotic on microflora in ileum and cecum for broilers by 16S rRNA sequence analysis.

An experiment was conducted to analyze and compare the microbial composition, abundance, dynamic distribution, and functions without and with antibiotic fed to broilers. A 16S rRNA-sequencing approach was used to evaluate the bacterial composition of the gut of male broilers under different groups. A total of 240 1-day old AA male broilers were randomly assigned to two groups, with 120 broilers per group. The treatment group was administered an antibiotic with their feed, while the control group was not administered antibiotic (control group). A total of 10 replicates were assessed per treatment. The control group was fed a basal diet containing corn, soybean meal, and cottonseed meal and met the nutritional requirement. The antibiotic group was fed 100 mg/kg aureomycin (based on the basal diet). The trial lasted 42 days. Operational taxonomic unit partition and classification, alpha diversity, taxonomic composition, beta diversity, and microflora comparative analyses along with key species screening were performed for all of the treatment groups. Our data indicate that aureomycin treatment in broilers is directly correlated with variations of the gut content of specific bacterial taxa, and herein provide insights into the impact of antibiotic on microbial communities in cecum and ileum of broiler chickens.© 2018 Japanese Society of Animal Science.

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September 22, 2019

Single cell genomic study of Dehalococcoidetes species from deep-sea sediments of the Peruvian Margin.

The phylum Chloroflexi is one of the most frequently detected phyla in the subseafloor of the Pacific Ocean margins. Dehalogenating Chloroflexi (Dehalococcoidetes) was originally discovered as the key microorganisms mediating reductive dehalogenation via their key enzymes reductive dehalogenases (Rdh) as sole mode of energy conservation in terrestrial environments. The frequent detection of Dehalococcoidetes-related 16S rRNA and rdh genes in the marine subsurface implies a role for dissimilatory dehalorespiration in this environment; however, the two genes have never been linked to each other. To provide fundamental insights into the metabolism, genomic population structure and evolution of marine subsurface Dehalococcoidetes sp., we analyzed a non-contaminated deep-sea sediment core sample from the Peruvian Margin Ocean Drilling Program (ODP) site 1230, collected 7.3?m below the seafloor by a single cell genomic approach. We present for the first time single cell genomic data on three deep-sea Chloroflexi (Dsc) single cells from a marine subsurface environment. Two of the single cells were considered to be part of a local Dehalococcoidetes population and assembled together into a 1.38-Mb genome, which appears to be at least 85% complete. Despite a high degree of sequence-level similarity between the shared proteins in the Dsc and terrestrial Dehalococcoidetes, no evidence for catabolic reductive dehalogenation was found in Dsc. The genome content is however consistent with a strictly anaerobic organotrophic or lithotrophic lifestyle.

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September 22, 2019

The effects of probiotics administration on the milk production, milk components and fecal bacteria microbiota of dairy cows

Probiotics administration can improve host health. This study aims to determine the effects of probiotics (Lactobacillus casei Zhang and Lactobacillus plantarum P-8) administration on milk production, milk functional components, milk composition, and fecal microbiota of dairy cows. Variations in the fecal bacteria microbiota between treatments were assessed based on 16S rRNA profiles determined by PacBio single molecule real-time sequencing technology. The probiotics supplementation significantly increased the milk production and the contents of milk immunoglobulin G (IgG), lactoferrin (LTF), lysozyme (LYS) and lactoperoxidase (LP), while the somatic cell counts (SCC) significantly decreased (P < 0.01). However, no significant difference was found in the milk fat, protein and lactose contents (P > 0.05). Although the probiotics supplementation did not change the fecal bacteria richness and diversity, significantly more rumen fermentative bacteria (Bacteroides, Roseburia, Ruminococcus, Clostridium, Coprococcus and Dorea) and beneficial bacteria (Faecalibacterium prausnitzii) were found in the probiotics treatment group. Meanwhile, some opportunistic pathogens e.g. Bacillus cereus, Cronobacter sakazakii and Alkaliphilus oremlandii, were suppressed. Additionally, we found some correlations between the milk production, milk components and fecal bacteria. To sum up, our study demonstrated the beneficial effects of probiotics application in improving the quality and quantity of cow milk production.

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September 22, 2019

A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling.

In the last 5 years, the rapid pace of innovations and improvements in sequencing technologies has completely changed the landscape of metagenomic and metagenetic experiments. Therefore, it is critical to benchmark the various methodologies for interrogating the composition of microbial communities, so that we can assess their strengths and limitations. The most common phylogenetic marker for microbial community diversity studies is the 16S ribosomal RNA gene and in the last 10 years the field has moved from sequencing a small number of amplicons and samples to more complex studies where thousands of samples and multiple different gene regions are interrogated.We assembled 2 synthetic communities with an even (EM) and uneven (UM) distribution of archaeal and bacterial strains and species, as metagenomic control material, to assess performance of different experimental strategies. The 2 synthetic communities were used in this study, to highlight the limitations and the advantages of the leading sequencing platforms: MiSeq (Illumina), The Pacific Biosciences RSII, 454 GS-FLX/+ (Roche), and IonTorrent (Life Technologies). We describe an extensive survey based on synthetic communities using 3 experimental designs (fusion primers, universal tailed tag, ligated adaptors) across the 9 hypervariable 16S rDNA regions. We demonstrate that library preparation methodology can affect data interpretation due to different error and chimera rates generated during the procedure. The observed community composition was always biased, to a degree that depended on the platform, sequenced region and primer choice. However, crucially, our analysis suggests that 16S rRNA sequencing is still quantitative, in that relative changes in abundance of taxa between samples can be recovered, despite these biases.We have assessed a range of experimental conditions across several next generation sequencing platforms using the most up-to-date configurations. We propose that the choice of sequencing platform and experimental design needs to be taken into consideration in the early stage of a project by running a small trial consisting of several hypervariable regions to quantify the discriminatory power of each region. We also suggest that the use of a synthetic community as a positive control would be beneficial to identify the potential biases and procedural drawbacks that may lead to data misinterpretation. The results of this study will serve as a guideline for making decisions on which experimental condition and sequencing platform to consider to achieve the best microbial profiling.

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