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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

Caught in the middle with multiple displacement amplification: the myth of pooling for avoiding multiple displacement amplification bias in a metagenome.

Shotgun metagenomics has become an important tool for investigating the ecology of microorganisms. Underlying these investigations is the assumption that metagenome sequence data accurately estimates the census of microbial populations. Multiple displacement amplification (MDA) of microbial community DNA is often used in cases where it is difficult to obtain enough DNA for sequencing; however, MDA can result in amplification biases that may impact subsequent estimates of population census from metagenome data. Some have posited that pooling replicate MDA reactions negates these biases and restores the accuracy of population analyses. This assumption has not been empirically tested.Using mock viral communities, we examined the influence of pooling on population-scale analyses. In pooled and single reaction MDA treatments, sequence coverage of viral populations was highly variable and coverage patterns across viral genomes were nearly identical, indicating that initial priming biases were reproducible and that pooling did not alleviate biases. In contrast, control unamplified sequence libraries showed relatively even coverage across phage genomes.MDA should be avoided for metagenomic investigations that require quantitative estimates of microbial taxa and gene functional groups. While MDA is an indispensable technique in applications such as single-cell genomics, amplification biases cannot be overcome by combining replicate MDA reactions. Alternative library preparation techniques should be utilized for quantitative microbial ecology studies utilizing metagenomic sequencing approaches.

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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

Enigmatic Diphyllatea eukaryotes: culturing and targeted PacBio RS amplicon sequencing reveals a higher order taxonomic diversity and global distribution.

The class Diphyllatea belongs to a group of enigmatic unicellular eukaryotes that play a key role in reconstructing the morphological innovation and diversification of early eukaryotic evolution. Despite its evolutionary significance, very little is known about the phylogeny and species diversity of Diphyllatea. Only three species have described morphology, being taxonomically divided by flagella number, two or four, and cell size. Currently, one 18S rRNA Diphyllatea sequence is available, with environmental sequencing surveys reporting only a single partial sequence from a Diphyllatea-like organism. Accordingly, geographical distribution of Diphyllatea based on molecular data is limited, despite morphological data suggesting the class has a global distribution. We here present a first attempt to understand species distribution, diversity and higher order structure of Diphyllatea.We cultured 11 new strains, characterised these morphologically and amplified their rRNA for a combined 18S-28S rRNA phylogeny. We sampled environmental DNA from multiple sites and designed new Diphyllatea-specific PCR primers for long-read PacBio RSII technology. Near full-length 18S rRNA sequences from environmental DNA, in addition to supplementary Diphyllatea sequence data mined from public databases, resolved the phylogeny into three deeply branching and distinct clades (Diphy I – III). Of these, the Diphy III clade is entirely novel, and in congruence with Diphy II, composed of species morphologically consistent with the earlier described Collodictyon triciliatum. The phylogenetic split between the Diphy I and Diphy II?+?III clades corresponds with a morphological division of Diphyllatea into bi- and quadriflagellate cell forms.This altered flagella composition must have occurred early in the diversification of Diphyllatea and may represent one of the earliest known morphological transitions among eukaryotes. Further, the substantial increase in molecular data presented here confirms Diphyllatea has a global distribution, seemingly restricted to freshwater habitats. Altogether, the results reveal the advantage of combining a group-specific PCR approach and long-read high-throughput amplicon sequencing in surveying enigmatic eukaryote lineages. Lastly, our study shows the capacity of PacBio RS when targeting a protist class for increasing phylogenetic resolution.

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September 22, 2019

Shannon: an information-optimal de novo RNA-Seq assembler

De novo assembly of short RNA-Seq reads into transcripts is challenging due to sequence similarities in transcriptomes arising from gene duplications and alternative splicing of transcripts. We present Shannon, an RNA-Seq assembler with an optimality guarantee derived from principles of information theory: Shannon reconstructs nearly all information-theoretically reconstructable transcripts. Shannon is based on a theory we develop for de novo RNA-Seq assembly that reveals differing abundances among transcripts to be the key, rather than the barrier, to effective assembly. The assembly problem is formulated as a sparsest-flow problem on a transcript graph, and the heart of Shannon is a novel iterative flow-decomposition algorithm. This algorithm provably solves the information-theoretically reconstructable instances in linear-time even though the general sparsest-flow problem is NP-hard. Shannon also incorporates several additional new algorithmic advances: a new error-correction algorithm based on successive cancelation, a multi-bridging algorithm that carefully utilizes read information in the k-mer de Bruijn graph, and an approximate graph partitioning algorithm to split the transcriptome de Bruijn graph into smaller components. In tests on large RNA-Seq datasets, Shannon obtains significant increases in sensitivity along with improvements in specificity in comparison to state-of-the-art assemblers.

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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

De novo clustering of long-read transcriptome data using a greedy, quality-value based algorithm

Long-read sequencing of transcripts with PacBio Iso-Seq and Oxford Nanopore Technologies has proven to be central to the study of complex isoform landscapes in many organisms. However, current de novo transcript reconstruction algorithms from long-read data are limited, leaving the potential of these technologies unfulfilled. A common bottleneck is the dearth of scalable and accurate algorithms for clustering long reads according to their gene family of origin. To address this challenge, we develop isONclust, a clustering algorithm that is greedy (in order to scale) and makes use of quality values (in order to handle variable error rates). We test isONclust on three simulated and five biological datasets, across a breadth of organisms, technologies, and read depths. Our results demonstrate that isONclust is a substantial improvement over previous approaches, both in terms of overall accuracy and/or scalability to large datasets. Our tool is available at https://github.com/ksahlin/isONclust.

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September 22, 2019

Metagenomic approaches to assess bacteriophages in various environmental niches.

Bacteriophages are ubiquitous and numerous parasites of bacteria and play a critical evolutionary role in virtually every ecosystem, yet our understanding of the extent of the diversity and role of phages remains inadequate for many ecological niches, particularly in cases in which the host is unculturable. During the past 15 years, the emergence of the field of viral metagenomics has drastically enhanced our ability to analyse the so-called viral ‘dark matter’ of the biosphere. Here, we review the evolution of viral metagenomic methodologies, as well as providing an overview of some of the most significant applications and findings in this field of research.

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September 22, 2019

Discovery of enzymes for toluene synthesis from anoxic microbial communities.

Microbial toluene biosynthesis was reported in anoxic lake sediments more than three decades ago, but the enzyme catalyzing this biochemically challenging reaction has never been identified. Here we report the toluene-producing enzyme PhdB, a glycyl radical enzyme of bacterial origin that catalyzes phenylacetate decarboxylation, and its cognate activating enzyme PhdA, a radical S-adenosylmethionine enzyme, discovered in two distinct anoxic microbial communities that produce toluene. The unconventional process of enzyme discovery from a complex microbial community (>300,000 genes), rather than from a microbial isolate, involved metagenomics- and metaproteomics-enabled biochemistry, as well as in vitro confirmation of activity with recombinant enzymes. This work expands the known catalytic range of glycyl radical enzymes (only seven reaction types had been characterized previously) and aromatic-hydrocarbon-producing enzymes, and will enable first-time biochemical synthesis of an aromatic fuel hydrocarbon from renewable resources, such as lignocellulosic biomass, rather than from petroleum.

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September 22, 2019

Capturing single cell genomes of active polysaccharide degraders: an unexpected contribution of Verrucomicrobia.

Microbial hydrolysis of polysaccharides is critical to ecosystem functioning and is of great interest in diverse biotechnological applications, such as biofuel production and bioremediation. Here we demonstrate the use of a new, efficient approach to recover genomes of active polysaccharide degraders from natural, complex microbial assemblages, using a combination of fluorescently labeled substrates, fluorescence-activated cell sorting, and single cell genomics. We employed this approach to analyze freshwater and coastal bacterioplankton for degraders of laminarin and xylan, two of the most abundant storage and structural polysaccharides in nature. Our results suggest that a few phylotypes of Verrucomicrobia make a considerable contribution to polysaccharide degradation, although they constituted only a minor fraction of the total microbial community. Genomic sequencing of five cells, representing the most predominant, polysaccharide-active Verrucomicrobia phylotype, revealed significant enrichment in genes encoding a wide spectrum of glycoside hydrolases, sulfatases, peptidases, carbohydrate lyases and esterases, confirming that these organisms were well equipped for the hydrolysis of diverse polysaccharides. Remarkably, this enrichment was on average higher than in the sequenced representatives of Bacteroidetes, which are frequently regarded as highly efficient biopolymer degraders. These findings shed light on the ecological roles of uncultured Verrucomicrobia and suggest specific taxa as promising bioprospecting targets. The employed method offers a powerful tool to rapidly identify and recover discrete genomes of active players in polysaccharide degradation, without the need for cultivation.

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