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September 22, 2019

Assessment of the physicochemical properties and bacterial composition of Lactobacillus plantarum and Enterococcus faecium-fermented Astragalus membranaceus using single molecule, real-time sequencing technology.

We investigated if fermentation with probiotic cultures could improve the production of health-promoting biological compounds in Astragalus membranaceus. We tested the probiotics Enterococcus faecium, Lactobacillus plantarum and Enterococcus faecium?+?Lactobacillus plantarum and applied PacBio single molecule, real-time sequencing technology (SMRT) to evaluate the quality of Astragalus fermentation. We found that the production rates of acetic acid, methylacetic acid, aethyl acetic acid and lactic acid using E. faecium?+?L. plantarum were 1866.24?mg/kg on day 15, 203.80?mg/kg on day 30, 996.04?mg/kg on day 15, and 3081.99?mg/kg on day 20, respectively. Other production rates were: polysaccharides, 9.43%, 8.51%, and 7.59% on day 10; saponins, 19.6912?mg/g, 21.6630?mg/g and 20.2084?mg/g on day 15; and flavonoids, 1.9032?mg/g, 2.0835?mg/g, and 1.7086?mg/g on day 20 using E. faecium, L. plantarum and E. faecium?+?L. plantarum, respectively. SMRT was used to analyze microbial composition, and we found that E. faecium and L. plantarum were the most prevalent species after fermentation for 3 days. E. faecium?+?L. plantarum gave more positive effects than single strains in the Astragalus solid state fermentation process. Our data demonstrated that the SMRT sequencing platform is applicable to quality assessment of Astragalus fermentation.

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September 22, 2019

The human microbiome and understanding the 16S rRNA gene in translational nursing science.

As more is understood regarding the human microbiome, it is increasingly important for nurse scientists and healthcare practitioners to analyze these microbial communities and their role in health and disease. 16S rRNA sequencing is a key methodology in identifying these bacterial populations that has recently transitioned from use primarily in research to having increased utility in clinical settings.The objectives of this review are to (a) describe 16S rRNA sequencing and its role in answering research questions important to nursing science; (b) provide an overview of the oral, lung, and gut microbiomes and relevant research; and (c) identify future implications for microbiome research and 16S sequencing in translational nursing science.Sequencing using the 16S rRNA gene has revolutionized research and allowed scientists to easily and reliably characterize complex bacterial communities. This type of research has recently entered the clinical setting, one of the best examples involving the use of 16S sequencing to identify resistant pathogens, thereby improving the accuracy of bacterial identification in infection control. Clinical microbiota research and related requisite methods are of particular relevance to nurse scientists-individuals uniquely positioned to utilize these techniques in future studies in clinical settings.

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September 22, 2019

MEGAN-LR: new algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs.

There are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing, and there is a need to adapt short read tools to long read datasets.We describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.All presented methods are implemented in the open source edition of MEGAN, and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.This article was reviewed by Nicola Segata together with Moreno Zolfo, Pete James Lockhart and Serghei Mangul.This work extends the applicability of the widely-used metagenomic analysis software MEGAN to long reads. Our study suggests that the presented LAST+MEGAN-LR pipeline is sufficiently fast and accurate.

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September 22, 2019

Interaction between the microbiome and TP53 in human lung cancer.

Lung cancer is the leading cancer diagnosis worldwide and the number one cause of cancer deaths. Exposure to cigarette smoke, the primary risk factor in lung cancer, reduces epithelial barrier integrity and increases susceptibility to infections. Herein, we hypothesize that somatic mutations together with cigarette smoke generate a dysbiotic microbiota that is associated with lung carcinogenesis. Using lung tissue from 33 controls and 143 cancer cases, we conduct 16S ribosomal RNA (rRNA) bacterial gene sequencing, with RNA-sequencing data from lung cancer cases in The Cancer Genome Atlas serving as the validation cohort.Overall, we demonstrate a lower alpha diversity in normal lung as compared to non-tumor adjacent or tumor tissue. In squamous cell carcinoma specifically, a separate group of taxa are identified, in which Acidovorax is enriched in smokers. Acidovorax temporans is identified within tumor sections by fluorescent in situ hybridization and confirmed by two separate 16S rRNA strategies. Further, these taxa, including Acidovorax, exhibit higher abundance among the subset of squamous cell carcinoma cases with TP53 mutations, an association not seen in adenocarcinomas.The results of this comprehensive study show both microbiome-gene and microbiome-exposure interactions in squamous cell carcinoma lung cancer tissue. Specifically, tumors harboring TP53 mutations, which can impair epithelial function, have a unique bacterial consortium that is higher in relative abundance in smoking-associated tumors of this type. Given the significant need for clinical diagnostic tools in lung cancer, this study may provide novel biomarkers for early detection.

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September 22, 2019

Extensive horizontal gene transfer in cheese-associated bacteria.

Acquisition of genes through horizontal gene transfer (HGT) allows microbes to rapidly gain new capabilities and adapt to new or changing environments. Identifying widespread HGT regions within multispecies microbiomes can pinpoint the molecular mechanisms that play key roles in microbiome assembly. We sought to identify horizontally transferred genes within a model microbiome, the cheese rind. Comparing 31 newly sequenced and 134 previously sequenced bacterial isolates from cheese rinds, we identified over 200 putative horizontally transferred genomic regions containing 4733 protein coding genes. The largest of these regions are enriched for genes involved in siderophore acquisition, and are widely distributed in cheese rinds in both Europe and the US. These results suggest that HGT is prevalent in cheese rind microbiomes, and that identification of genes that are frequently transferred in a particular environment may provide insight into the selective forces shaping microbial communities.

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September 22, 2019

The microbiome of the leaf surface of Arabidopsis protects against a fungal pathogen.

We have explored the importance of the phyllosphere microbiome in plant resistance in the cuticle mutants bdg (BODYGUARD) or lacs2.3 (LONG CHAIN FATTY ACID SYNTHASE 2) that are strongly resistant to the fungal pathogen Botrytis cinerea. The study includes infection of plants under sterile conditions, 16S ribosomal DNA sequencing of the phyllosphere microbiome, and isolation and high coverage sequencing of bacteria from the phyllosphere. When inoculated under sterile conditions bdg became as susceptible as wild-type (WT) plants whereas lacs2.3 mutants retained the resistance. Adding washes of its phyllosphere microbiome could restore the resistance of bdg mutants, whereas the resistance of lacs2.3 results from endogenous mechanisms. The phyllosphere microbiome showed distinct populations in WT plants compared to cuticle mutants. One species identified as Pseudomonas sp isolated from the microbiome of bdg provided resistance to B. cinerea on Arabidopsis thaliana as well as on apple fruits. No direct activity was observed against B. cinerea and the action of the bacterium required the plant. Thus, microbes present on the plant surface contribute to the resistance to B. cinerea. These results open new perspectives on the function of the leaf microbiome in the protection of plants.© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

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September 22, 2019

Next generation sequencing data of a defined microbial mock community.

Generating sequence data of a defined community composed of organisms with complete reference genomes is indispensable for the benchmarking of new genome sequence analysis methods, including assembly and binning tools. Moreover the validation of new sequencing library protocols and platforms to assess critical components such as sequencing errors and biases relies on such datasets. We here report the next generation metagenomic sequence data of a defined mock community (Mock Bacteria ARchaea Community; MBARC-26), composed of 23 bacterial and 3 archaeal strains with finished genomes. These strains span 10 phyla and 14 classes, a range of GC contents, genome sizes, repeat content and encompass a diverse abundance profile. Short read Illumina and long-read PacBio SMRT sequences of this mock community are described. These data represent a valuable resource for the scientific community, enabling extensive benchmarking and comparative evaluation of bioinformatics tools without the need to simulate data. As such, these data can aid in improving our current sequence data analysis toolkit and spur interest in the development of new tools.

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September 22, 2019

Role of clinicogenomics in infectious disease diagnostics and public health microbiology.

Clinicogenomics is the exploitation of genome sequence data for diagnostic, therapeutic, and public health purposes. Central to this field is the high-throughput DNA sequencing of genomes and metagenomes. The role of clinicogenomics in infectious disease diagnostics and public health microbiology was the topic of discussion during a recent symposium (session 161) presented at the 115th general meeting of the American Society for Microbiology that was held in New Orleans, LA. What follows is a collection of the most salient and promising aspects from each presentation at the symposium. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

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September 22, 2019

Interpreting microbial biosynthesis in the genomic age: Biological and practical considerations.

Genome mining has become an increasingly powerful, scalable, and economically accessible tool for the study of natural product biosynthesis and drug discovery. However, there remain important biological and practical problems that can complicate or obscure biosynthetic analysis in genomic and metagenomic sequencing projects. Here, we focus on limitations of available technology as well as computational and experimental strategies to overcome them. We review the unique challenges and approaches in the study of symbiotic and uncultured systems, as well as those associated with biosynthetic gene cluster (BGC) assembly and product prediction. Finally, to explore sequencing parameters that affect the recovery and contiguity of large and repetitive BGCs assembled de novo, we simulate Illumina and PacBio sequencing of the Salinispora tropica genome focusing on assembly of the salinilactam (slm) BGC.

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September 22, 2019

Cow-to-mouse fecal transplantations suggest intestinal microbiome as one cause of mastitis.

Mastitis, which affects nearly all lactating mammals including human, is generally thought to be caused by local infection of the mammary glands. For treatment, antibiotics are commonly prescribed, which however are of concern in both treatment efficacy and neonate safety. Here, using bovine mastitis which is the most costly disease in the dairy industry as a model, we showed that intestinal microbiota alone can lead to mastitis.Fecal microbiota transplantation (FMT) from mastitis, but not healthy cows, to germ-free (GF) mice resulted in mastitis symptoms in mammary gland and inflammations in serum, spleen, and colon. Probiotic intake in parallel with FMT from diseased cows led to relieved mastitis symptoms in mice, by shifting the murine intestinal microbiota to a state that is functionally distinct from either healthy or diseased microbiota yet structurally similar to the latter. Despite conservation in mastitis symptoms, diseased cows and mice shared few mastitis-associated bacterial organismal or functional markers, suggesting striking divergence in mastitis-associated intestinal microbiota among lactating mammals. Moreover, an “amplification effect” of disease-health distinction in both microbiota structure and function was apparent during the cow-to-mouse FMT.Hence, dysbiosis of intestinal microbiota may be one cause of mastitis, and probiotics that restore intestinal microbiota function are an effective and safe strategy to treat mastitis.

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September 22, 2019

Quantitative metaproteomics highlight the metabolic contributions of uncultured phylotypes in a thermophilic anaerobic digester.

In this study, we used multiple meta-omic approaches to characterize the microbial community and the active metabolic pathways of a stable industrial biogas reactor with food waste as the dominant feedstock, operating at thermophilic temperatures (60°C) and elevated levels of free ammonia (367 mg/liter NH3-N). The microbial community was strongly dominated (76% of all 16S rRNA amplicon sequences) by populations closely related to the proteolytic bacterium Coprothermobacter proteolyticus. Multiple Coprothermobacter-affiliated strains were detected, introducing an additional level of complexity seldom explored in biogas studies. Genome reconstructions provided metabolic insight into the microbes that performed biomass deconstruction and fermentation, including the deeply branching phyla Dictyoglomi and Planctomycetes and the candidate phylum “Atribacteria” These biomass degraders were complemented by a synergistic network of microorganisms that convert key fermentation intermediates (fatty acids) via syntrophic interactions with hydrogenotrophic methanogens to ultimately produce methane. Interpretation of the proteomics data also suggested activity of a Methanosaeta phylotype acclimatized to high ammonia levels. In particular, we report multiple novel phylotypes proposed as syntrophic acetate oxidizers, which also exert expression of enzymes needed for both the Wood-Ljungdahl pathway and ß-oxidation of fatty acids to acetyl coenzyme A. Such an arrangement differs from known syntrophic oxidizing bacteria and presents an interesting hypothesis for future studies. Collectively, these findings provide increased insight into active metabolic roles of uncultured phylotypes and presents new synergistic relationships, both of which may contribute to the stability of the biogas reactor.Biogas production through anaerobic digestion of organic waste provides an attractive source of renewable energy and a sustainable waste management strategy. A comprehensive understanding of the microbial community that drives anaerobic digesters is essential to ensure stable and efficient energy production. Here, we characterize the intricate microbial networks and metabolic pathways in a thermophilic biogas reactor. We discuss the impact of frequently encountered microbial populations as well as the metabolism of newly discovered novel phylotypes that seem to play distinct roles within key microbial stages of anaerobic digestion in this stable high-temperature system. In particular, we draft a metabolic scenario whereby multiple uncultured syntrophic acetate-oxidizing bacteria are capable of syntrophically oxidizing acetate as well as longer-chain fatty acids (via the ß-oxidation and Wood-Ljundahl pathways) to hydrogen and carbon dioxide, which methanogens subsequently convert to methane. Copyright © 2016 American Society for Microbiology.

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September 22, 2019

PCR and omics based techniques to study the diversity, ecology and biology of anaerobic fungi: Insights, challenges andopportunities.

Anaerobic fungi (phylum Neocallimastigomycota) are common inhabitants of the digestive tract of mammalian herbivores, and in the rumen, can account for up to 20% of the microbial biomass. Anaerobic fungi play a primary role in the degradation of lignocellulosic plant material. They also have a syntrophic interaction with methanogenic archaea, which increases their fiber degradation activity. To date, nine anaerobic fungal genera have been described, with further novel taxonomic groupings known to exist based on culture-independent molecular surveys. However, the true extent of their diversity may be even more extensively underestimated as anaerobic fungi continue being discovered in yet unexplored gut and non-gut environments. Additionally many studies are now known to have used primers that provide incomplete coverage of the Neocallimastigomycota. For ecological studies the internal transcribed spacer 1 region (ITS1) has been the taxonomic marker of choice, but due to various limitations the large subunit rRNA (LSU) is now being increasingly used. How the continued expansion of our knowledge regarding anaerobic fungal diversity will impact on our understanding of their biology and ecological role remains unclear; particularly as it is becoming apparent that anaerobic fungi display niche differentiation. As a consequence, there is a need to move beyond the broad generalization of anaerobic fungi as fiber-degraders, and explore the fundamental differences that underpin their ability to exist in distinct ecological niches. Application of genomics, transcriptomics, proteomics and metabolomics to their study in pure/mixed cultures and environmental samples will be invaluable in this process. To date the genomes and transcriptomes of several characterized anaerobic fungal isolates have been successfully generated. In contrast, the application of proteomics and metabolomics to anaerobic fungal analysis is still in its infancy. A central problem for all analyses, however, is the limited functional annotation of anaerobic fungal sequence data. There is therefore an urgent need to expand information held within publicly available reference databases. Once this challenge is overcome, along with improved sample collection and extraction, the application of these techniques will be key in furthering our understanding of the ecological role and impact of anaerobic fungi in the wide range of environments they inhabit.

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September 22, 2019

High-resolution characterization of the human microbiome.

The human microbiome plays an important and increasingly recognized role in human health. Studies of the microbiome typically use targeted sequencing of the 16S rRNA gene, whole metagenome shotgun sequencing, or other meta-omic technologies to characterize the microbiome’s composition, activity, and dynamics. Processing, analyzing, and interpreting these data involve numerous computational tools that aim to filter, cluster, annotate, and quantify the obtained data and ultimately provide an accurate and interpretable profile of the microbiome’s taxonomy, functional capacity, and behavior. These tools, however, are often limited in resolution and accuracy and may fail to capture many biologically and clinically relevant microbiome features, such as strain-level variation or nuanced functional response to perturbation. Over the past few years, extensive efforts have been invested toward addressing these challenges and developing novel computational methods for accurate and high-resolution characterization of microbiome data. These methods aim to quantify strain-level composition and variation, detect and characterize rare microbiome species, link specific genes to individual taxa, and more accurately characterize the functional capacity and dynamics of the microbiome. These methods and the ability to produce detailed and precise microbiome information are clearly essential for informing microbiome-based personalized therapies. In this review, we survey these methods, highlighting the challenges each method sets out to address and briefly describing methodological approaches. Copyright © 2016 Elsevier Inc. All rights reserved.

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September 22, 2019

Recent developments in using advanced sequencing technologies for the genomic studies of lignin and cellulose degrading microorganisms.

Lignin is a complex polyphenyl aromatic compound which exists in tight associations with cellulose and hemicellulose to form plant primary and secondary cell wall. Lignocellulose is an abundant renewable biomaterial present on the earth. It has gained much attention in the scientific community in recent years because of its potential applications in bio-based industries. Microbial degradation of lignocellulose polymers was well studied in wood decaying fungi. Based on the plant materials they degrade these fungi were classified as white rot, brown rot and soft rot. However, some groups of bacteria belonging to the actinomycetes, a-proteobacteria and ß-proteobacteria were also found to be efficient in degrading lignocellulosic biomass but not well understood unlike the fungi. In this review we focus on recent advancements deployed for finding and understanding the lignocellulose degradation by microorganisms. Conventional molecular methods like sequencing 16s rRNA and Inter Transcribed Spacer (ITS) regions were used for identification and classification of microbes. Recent progression in genomics mainly next generation sequencing technologies made the whole genome sequencing of microbes possible in a great ease. The whole genome sequence studies reveals high quality information about genes and canonical pathways involved in the lignin and other cell wall components degradation.

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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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