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Auto Tag: Circular consensus sequencing

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

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

Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells.

Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far. Although single splicing events have been described for =200 single cells with statistical confidence, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3′ sequencing enables the identification of cellular subtypes, but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-type-specific combination patterns of distant splice sites. We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms.

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September 22, 2019

A quantitative SMRT cell sequencing method for ribosomal amplicons.

Advances in sequencing technologies continue to provide unprecedented opportunities to characterize microbial communities. For example, the Pacific Biosciences Single Molecule Real-Time (SMRT) platform has emerged as a unique approach harnessing DNA polymerase activity to sequence template molecules, enabling long reads at low costs. With the aim to simultaneously classify and enumerate in situ microbial populations, we developed a quantitative SMRT (qSMRT) approach that involves the addition of exogenous standards to quantify ribosomal amplicons derived from environmental samples. The V7-9 regions of 18S SSU rDNA were targeted and quantified from protistan community samples collected in the Ross Sea during the Austral summer of 2011. We used three standards of different length and optimized conditions to obtain accurate quantitative retrieval across the range of expected amplicon sizes, a necessary criterion for analyzing taxonomically diverse 18S rDNA molecules from natural environments. The ability to concurrently identify and quantify microorganisms in their natural environment makes qSMRT a powerful, rapid and cost-effective approach for defining ecosystem diversity and function. Copyright © 2017 Elsevier B.V. All rights reserved.

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September 22, 2019

Evaluation of long-term performance of sediment microbial fuel cells and the role of natural resources

Sediment microbial fuel cells (SMFCs) are expected to be used as a renewable power source for remote environmental monitoring; therefore, evaluation of their long-term power performance is critical for their usability. In this paper, we present novel data needed to understand the long-term performance of SMFCs. We used 3-D Microemulsion (3DMe)™ doped anodes, which slowly release lactate and its fermented products. During our tests, anode-limited SMFCs with and without 3DMe-doped anodes were operated for more than 18 months with a load simulating a sensor operation. We found that doping an anode with an electron donor reduced startup time and increased maximum power (55 ± 2 µW compared to 46 ± 2 µW) in the control systems. We found that the long-term steady power performance is approximately 33% of the maximum power (~18 µW). Finally, our small-sized SMFCs generated higher power densities than those in the literature (28 mW/m2 versus 4 mW/m2). Using electron donor doped anodes can be practical when a short startup time and initial high power are needed. However, if long-term power is critical, the addition of an electron donor does not provide a practical advantage. In addition, in long-term operation enrichment of the anode surface with electrochemically active bacteria does not provide any advantage.

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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

Improving eukaryotic genome annotation using single molecule mRNA sequencing.

The advantages of Pacific Biosciences (PacBio) single-molecule real-time (SMRT) technology include long reads, low systematic bias, and high consensus read accuracy. Here we use these attributes to improve on the genome annotation of the parasitic hookworm Ancylostoma ceylanicum using PacBio RNA-Seq.We sequenced 192,888 circular consensus sequences (CCS) derived from cDNAs generated using the CloneTech SMARTer system. These SMARTer-SMRT libraries were normalized and size-selected providing a robust population of expressed structural genes for subsequent genome annotation. We demonstrate PacBio mRNA sequences based genome annotation improvement, compared to genome annotation using conventional sequencing-by-synthesis alone, by identifying 1609 (9.2%) new genes, extended the length of 3965 (26.7%) genes and increased the total genomic exon length by 1.9 Mb (12.4%). Non-coding sequence representation (primarily from UTRs based on dT reverse transcription priming) was particularly improved, increasing in total length by fifteen-fold, by increasing both the length and number of UTR exons. In addition, the UTR data provided by these CCS allowed for the identification of a novel SL2 splice leader sequence for A. ceylanicum and an increase in the number and proportion of functionally annotated genes. RNA-seq data also confirmed some of the newly annotated genes and gene features.Overall, PacBio data has supported a significant improvement in gene annotation in this genome, and is an appealing alternative or complementary technique for genome annotation to the other transcript sequencing technologies.

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September 22, 2019

Multi-platform assessment of transcriptome profiling using RNA-seq in the ABRF next-generation sequencing study.

High-throughput RNA sequencing (RNA-seq) greatly expands the potential for genomics discoveries, but the wide variety of platforms, protocols and performance capabilitites has created the need for comprehensive reference data. Here we describe the Association of Biomolecular Resource Facilities next-generation sequencing (ABRF-NGS) study on RNA-seq. We carried out replicate experiments across 15 laboratory sites using reference RNA standards to test four protocols (poly-A-selected, ribo-depleted, size-selected and degraded) on five sequencing platforms (Illumina HiSeq, Life Technologies PGM and Proton, Pacific Biosciences RS and Roche 454). The results show high intraplatform (Spearman rank R > 0.86) and inter-platform (R > 0.83) concordance for expression measures across the deep-count platforms, but highly variable efficiency and cost for splice junction and variant detection between all platforms. For intact RNA, gene expression profiles from rRNA-depletion and poly-A enrichment are similar. In addition, rRNA depletion enables effective analysis of degraded RNA samples. This study provides a broad foundation for cross-platform standardization, evaluation and improvement of RNA-seq.

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September 22, 2019

LSCplus: a fast solution for improving long read accuracy by short read alignment.

The single molecule, real time (SMRT) sequencing technology of Pacific Biosciences enables the acquisition of transcripts from end to end due to its ability to produce extraordinarily long reads (>10 kb). This new method of transcriptome sequencing has been applied to several projects on humans and model organisms. However, the raw data from SMRT sequencing are of relatively low quality, with a random error rate of approximately 15 %, for which error correction using next-generation sequencing (NGS) short reads is typically necessary. Few tools have been designed that apply a hybrid sequencing approach that combines NGS and SMRT data, and the most popular existing tool for error correction, LSC, has computing resource requirements that are too intensive for most laboratory and research groups. These shortcomings severely limit the application of SMRT long reads for transcriptome analysis.Here, we report an improved tool (LSCplus) for error correction with the LSC program as a reference. LSCplus overcomes the disadvantage of LSC’s time consumption and improves quality. Only 1/3-1/4 of the time and 1/20-1/25 of the error correction time is required using LSCplus compared with that required for using LSC.LSCplus is freely available at http://www.herbbol.org:8001/lscplus/ . Sample calculations are provided illustrating the precision and efficiency of this method regarding error correction and isoform detection.

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September 22, 2019

The Florida manatee (Trichechus manatus latirostris) immunoglobulin heavy chain suggests the importance of clan III variable segments in repertoire diversity.

Manatees are a vulnerable, charismatic sentinel species from the evolutionarily divergent Afrotheria. Manatee health and resistance to infectious disease is of great concern to conservation groups, but little is known about their immune system. To develop manatee-specific tools for monitoring health, we first must have a general knowledge of how the immunoglobulin heavy (IgH) chain locus is organized and transcriptionally expressed. Using the genomic scaffolds of the Florida manatee (Trichechus manatus latirostris), we characterized the potential IgH segmental diversity and constant region isotypic diversity and performed the first Afrotherian repertoire analysis. The Florida manatee has low V(D)J combinatorial diversity (3744 potential combinations) and few constant region isotypes. They also lack clan III V segments, which may have caused reduced VH segment numbers. However, we found productive somatic hypermutation concentrated in the complementarity determining regions. In conclusion, manatees have limited IGHV clan and combinatorial diversity. This suggests that clan III V segments are essential for maintaining IgH locus diversity. Copyright © 2017 Elsevier Ltd. All rights reserved.

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September 22, 2019

PacBio sequencing and its applications.

Single-molecule, real-time sequencing developed by Pacific BioSciences offers longer read lengths than the second-generation sequencing (SGS) technologies, making it well-suited for unsolved problems in genome, transcriptome, and epigenetics research. The highly-contiguous de novo assemblies using PacBio sequencing can close gaps in current reference assemblies and characterize structural variation (SV) in personal genomes. With longer reads, we can sequence through extended repetitive regions and detect mutations, many of which are associated with diseases. Moreover, PacBio transcriptome sequencing is advantageous for the identification of gene isoforms and facilitates reliable discoveries of novel genes and novel isoforms of annotated genes, due to its ability to sequence full-length transcripts or fragments with significant lengths. Additionally, PacBio’s sequencing technique provides information that is useful for the direct detection of base modifications, such as methylation. In addition to using PacBio sequencing alone, many hybrid sequencing strategies have been developed to make use of more accurate short reads in conjunction with PacBio long reads. In general, hybrid sequencing strategies are more affordable and scalable especially for small-size laboratories than using PacBio Sequencing alone. The advent of PacBio sequencing has made available much information that could not be obtained via SGS alone. Copyright © 2015 The Authors. Production and hosting by Elsevier Ltd.. All rights reserved.

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September 22, 2019

Periodic pattern of genetic and fitness diversity during evolution of an artificial cell-like system.

Genetic and phenotypic diversity are the basis of evolution. Despite their importance, however, little is known about how they change over the course of evolution. In this study, we analyzed the dynamics of the adaptive evolution of a simple evolvable artificial cell-like system using single-molecule real-time sequencing technology that reads an entire single artificial genome. We found that the genomic RNA population increases in fitness intermittently, correlating with a periodic pattern of genetic and fitness diversity produced by repeated diversification and domination. In the diversification phase, a genomic RNA population spreads within a genetic space by accumulating mutations until mutants with higher fitness are generated, resulting in an increase in fitness diversity. In the domination phase, the mutants with higher fitness dominate, decreasing both the fitness and genetic diversity. This study reveals the dynamic nature of genetic and fitness diversity during adaptive evolution and demonstrates the utility of a simplified artificial cell-like system to study evolution at an unprecedented resolution. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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