Here, we present the complete genome sequence of Rothia mucilaginosa NUM-Rm6536, a strain isolated from the tongue plaque of a healthy human adult. This strain is amenable to genetic manipulation by transformation and so provides a useful foundation for more detailed investigation of this species. Copyright © 2015 Nambu et al.
The chicken has long served as an important model organism in many fields, and continues to aid our understanding of animal development. Functional genomics studies aimed at probing the mechanisms that regulate development require high-quality genomes and transcript annotations. The quality of these resources has improved dramatically over the last several years, but many isoforms and genes have yet to be identified. We hope to contribute to the process of improving these resources with the data presented here: a set of long cDNA sequencing reads, and a curated set of new genes and transcript isoforms not currently represented in the most up-to-date genome annotation currently available to the community of researchers who rely on the chicken genome.
The Papaver spp. (Papaver rhoeas (Corn poppy) and Papaver nudicaule (Iceland poppy)) genera are ornamental and medicinal plants that are used for the isolation of alkaloid drugs. In this study, we generated 700 Mb of transcriptome sequences with the PacBio platform. They were assembled into 120,926 contigs, and 1185 (82.2%) of the benchmarking universal single-copy orthologs (BUSCO) core genes were completely present in our assembled transcriptome. Furthermore, using 128 Gb of Illumina sequences, the transcript expression was assessed at three stages of Papaver plant development (30, 60, and 90 days), from which we identified 137 differentially expressed transcripts. Furthermore, three co-occurrence heat maps are generated from 51 different plant genomes along with the Papaver transcriptome, i.e., secondary metabolite biosynthesis, isoquinoline alkaloid biosynthesis (BIA) pathway, and cytochrome. Sixty-nine transcripts in the BIA pathway along with 22 different alkaloids (quantified with LC-QTOF-MS/MS) were mapped into the BIA KEGG map (map00950). Finally, we identified 39 full-length cytochrome transcripts and compared them with other genomes. Collectively, this transcriptome data, along with the expression and quantitative metabolite profiles, provides an initial recording of secondary metabolites and their expression related to Papaver plant development. Moreover, these profiles could help to further detail the functional characterization of the various secondary metabolite biosynthesis and Papaver plant development associated problems.
W64A, as a member of non-stiff stalk maize, has been used to develop current corn in plant breeding, and serving as one of broadest parent line for the commercial hybrid seed production (Huffman, 1984). The inbred had the characteristics of early flowering, average plant and ear height at its maturity, very strong roots and good stalks (Runge, 2004). In addition, W64A serves as an invaluable germplasm to study gene functions especially in the field of corn nutrition and endosperm texture given its nearly complete vitreousness and hardness (Figure 1a). However, little is known about the background of genetic and genomic information for W64A. With the advent of the revolutionary technology of PacBio long-read sequencing, we can simultaneously obtain a large amount of full-length cDNA up to 20 kb (An et al., 2018). This article is protected by copyright. All rights reserved.This article is protected by copyright. All rights reserved.
The Pacific Biosciences (Menlo Park, CA) single molecule, real-time sequencing technology (SMRT) was reported to have some advantages in analyzing the bacterial profile of environmental samples. In this study, the presence of bacterial contaminants in raw milk, UHT milk, and infant formula was determined by SMRT sequencing of the full length 16S rRNA gene. The bacterial profiles obtained at different taxonomic levels revealed clear differences in bacterial community structure across the 16 analyzed dairy samples. No indicative pathogenic bacteria were found in any of these tested samples. However, some of the detected bacterial species (e.g., Bacillus cereus, Enterococcus casseliflavus, and Enterococcus gallinarum) might potentially relate with product quality defects and bacterial antibiotic gene transfer. Although only a limited number of dairy samples were analyzed here, our data have demonstrated for the first time the feasibility of using the SMRT sequencing platform in detecting bacterial contamination. Our paper also provides interesting reference information for future development of new precautionary strategies for controlling the dairy safety in large-scale industrialized production lines. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
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.
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.
Mixed fibrolamellar hepatocellular carcinoma (mFL-HCC) is a rare liver tumor defined by the presence of both pure FL-HCC and conventional HCC components, represents up to 25% of cases of FL-HCC, and has been associated with worse prognosis. Recent genomic characterization of pure FL-HCC identified a highly recurrent transcript fusion (DNAJB1:PRKACA) not found in conventional HCC.We performed exome and transcriptome sequencing of a case of mFL-HCC. A novel BAC-capture approach was developed to identify a 400 kb deletion as the underlying genomic mechanism for a DNAJB1:PRKACA fusion in this case. A sensitive Nanostring Elements assay was used to screen for this transcript fusion in a second case of mFL-HCC, 112 additional HCC samples and 44 adjacent non-tumor liver samples.We report the first comprehensive genomic analysis of a case of mFL-HCC. No common HCC-associated mutations were identified. The very low mutation rate of this case, large number of mostly single-copy, long-range copy number variants, and high expression of ERBB2 were more consistent with previous reports of pure FL-HCC than conventional HCC. In particular, the DNAJB1:PRKACA fusion transcript specifically associated with pure FL-HCC was detected at very high expression levels. Subsequent analysis revealed the presence of this fusion in all primary and metastatic samples, including those with mixed or conventional HCC pathology. A second case of mFL-HCC confirmed our finding that the fusion was detectable in conventional components. An expanded screen identified a third case of fusion-positive HCC, which upon review, also had both conventional and fibrolamellar features. This screen confirmed the absence of the fusion in all conventional HCC and adjacent non-tumor liver samples.These results indicate that mFL-HCC is similar to pure FL-HCC at the genomic level and the DNAJB1:PRKACA fusion can be used as a diagnostic tool for both pure and mFL-HCC.© The Author 2016. Published by Oxford University Press on behalf of the European Society for Medical Oncology.
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.
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.
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.
Two distinct subgroups of genotype A2 small ruminant lentiviruses (SRLVs) have been identified in the United States that infect sheep with specific host transmembrane protein 154 (TMEM154) diplotypes. Here, we report the first two complete genome sequences of SRLV strains infecting U.S. sheep belonging to genotype A2, subgroups 1 and 2. Copyright © 2017 Workman et al.
Alternative isoform regulation (AIR) vastly increases transcriptome diversity and plays an important role in numerous biological processes and pathologies. However, the detection and analysis of isoform-level differential regulation is difficult, particularly in the face of complex and incompletely-annotated transcriptomes. Here we have used Illumina short-read/high-throughput RNA-Seq to identify 55 genes that exhibit neurally-regulated AIR in the pineal gland, and then used two other complementary experimental platforms to further study and characterize the Ttc8 gene, which is involved in Bardet-Biedl syndrome and non-syndromic retinitis pigmentosa. Use of the JunctionSeq analysis tool led to the detection of several novel exons and splice junctions in this gene, including two novel alternative transcription start sites which were found to display disproportionately strong neurally-regulated differential expression in several independent experiments. These high-throughput sequencing results were validated and augmented via targeted qPCR and long-read Pacific Biosciences SMRT sequencing. We confirmed the existence of numerous novel splice junctions and the selective upregulation of the two novel start sites. In addition, we identified more than 20 novel isoforms of the Ttc8 gene that are co-expressed in this tissue. By using information from multiple independent platforms we not only greatly reduce the risk of errors, biases, and artifacts influencing our results, we also are able to characterize the regulation and splicing of the Ttc8 gene more deeply and more precisely than would be possible via any single platform. The hybrid method outlined here represents a powerful strategy in the study of the transcriptome.
Neurexins are evolutionarily conserved presynaptic cell-adhesion molecules that are essential for normal synapse formation and synaptic transmission. Indirect evidence has indicated that extensive alternative splicing of neurexin mRNAs may produce hundreds if not thousands of neurexin isoforms, but no direct evidence for such diversity has been available. Here we use unbiased long-read sequencing of full-length neurexin (Nrxn)1a, Nrxn1ß, Nrxn2ß, Nrxn3a, and Nrxn3ß mRNAs to systematically assess how many sites of alternative splicing are used in neurexins with a significant frequency, and whether alternative splicing events at these sites are independent of each other. In sequencing more than 25,000 full-length mRNAs, we identified a novel, abundantly used alternatively spliced exon of Nrxn1a and Nrxn3a (referred to as alternatively spliced sequence 6) that encodes a 9-residue insertion in the flexible hinge region between the fifth LNS (laminin-a, neurexin, sex hormone-binding globulin) domain and the third EGF-like sequence. In addition, we observed several larger-scale events of alternative splicing that deleted multiple domains and were much less frequent than the canonical six sites of alternative splicing in neurexins. All of the six canonical events of alternative splicing appear to be independent of each other, suggesting that neurexins may exhibit an even larger isoform diversity than previously envisioned and comprise thousands of variants. Our data are consistent with the notion that a-neurexins represent extracellular protein-interaction scaffolds in which different LNS and EGF domains mediate distinct interactions that affect diverse functions and are independently regulated by independent events of alternative splicing.
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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