2015 SMRT Informatics Developers Conference Presentation Slides: Shinichi Morishita of the University of Tokyo presented on how his team has been using SMRT Sequencing to better understand methylomes, metagenomes and structural variation of various eukaryotic genomes.
Microbes play an important role in nearly every part of our world, as they affect human health, our environment, agriculture, and aid in waste management. Complete closed genome sequences, which have become the gold standard with PacBio long-read sequencing, can be key to understanding microbial functional characteristics. However, input requirements, consumables costs, and the labor required to prepare and sequence a microbial genome have in the past put PacBio sequencing out of reach for some larger projects. We have developed a multiplexed library prep approach that is simple, fast, and cost-effective, and can produce 4 to 16 closed bacterial genomes from one Sequel SMRT Cell. Additionally, we are introducing a streamlined analysis pipeline for processing multiplexed genome sequence data through de novo HGAP assembly, making the entire process easy for lab personnel to perform. Here we present the entire workflow from shearing through assembly, with times for each step. We show HGAP assembly results with single or very few contigs from bacteria from different size genomes, sequenced without or with size selection. These data illustrate the benefits and potential of the PacBio multiplexed library prep and the Sequel System for sequencing large numbers of microbial genomes.
In the past decade, the human microbiome has been increasingly shown to play a major role in health. For example, imbalances in gut microbiota appear to be associated with Type II diabetes mellitus (T2DM) and cardiovascular disease. Coronary artery disease (CAD) is a major determinant of the long-term prognosis among T2DM patients, with a 2- to 4-fold increased mortality risk when present. However, the exact microbial strains or functions implicated in disease need further investigation. From a large study with 523 participants (185 healthy controls, 186 T2DM patients without CAD, and 106 T2DM patients with CAD), 3 samples from each patient group were selected for long read sequencing. Each sample was prepared and sequenced on one Sequel II System SMRT Cell, to assess whether long accurate PacBio HiFi reads could yield additional insights to those made using short reads. Each of the 9 samples was subject to metagenomic assembly and binning, taxonomic classification and functional profiling. Results from metagenomic assembly and binning show that it is possible to generate a significant number of complete MAGs (Metagenome Assembled Genomes) from each sample, with over half of the high-quality MAGs being represented by a single circular contig. We show that differences found in taxonomic and functional profiles of healthy versus diabetic patients in the small 9-sample study align with the results of the larger study, as well as with results reported in literature. For example, the abundances of beneficial short- chain fatty acid (SCFA) producers such as Phascolarctobacterium faecium and Faecalibacterium prausnitzii were decreased in T2DM gut microbiota in both studies, while the abundances of quinol and quinone biosynthesis pathways were increased as compared to healthy controls. In conclusion, metagenomic analysis of long accurate HiFi reads revealed important taxonomic and functional differences in T2DM versus healthy gut microbiota. Furthermore, metagenome assembly of long HiFi reads led to the recovery of many complete MAGs and a significant number of complete circular bacterial chromosome sequences.
This tutorial provides an overview of the Base Modification and Motif analysis application for identifying common bacterial epigenetic modifications and analyzing methyltransferase recognition motifs. SMRT Analysis software supports epigenetic research…
In this webinar, Ben Auch, Research Scientist, Innovation Lab, University of Minnesota Genomics Center, Cody Sheik, Assistant Professor of Biology, University of Minnesota Duluth, and Harm van Bakel, Assistant Professor…
One of the longstanding challenges in infectious disease has been the lack of high-quality reference genomes. However, developments in genome sequencing are helping researchers overcome this barrier. Recently, highly contiguous…
In this AGBT presentation from AGBT 2019, Jason Underwood, shares information about single-cell isoform sequencing (scIso-Seq), focusing on a collaborative project with the labs of Evan Eichler and Alex Pollen….
In this PacBio User Group Meeting presentation, Shawn Trojahn of Washington State University describes transcriptome sequencing and analysis of grizzly bears focused on differential gene expression during hibernation and active…
Microbial Assembly is our latest pipeline, specifically designed to assemble bacterial genomes (between 2 and 10 Mb) and plasmids. This pipeline includes the implementation of a new, circular-aware read alignment…
The widespread occurrence of repetitive stretches of DNA in genomes of organisms across the tree of life imposes fundamental challenges for sequencing, genome assembly, and automated annotation of genes and proteins. This multi-level problem can lead to errors in genome and protein databases that are often not recognized or acknowledged. As a consequence, end users working with sequences with repetitive regions are faced with ‘ready-to-use’ deposited data whose trustworthiness is difficult to determine, let alone to quantify. Here, we provide a review of the problems associated with tandem repeat sequences that originate from different stages during the sequencing-assembly-annotation-deposition workflow, and that may proliferate in public database repositories affecting all downstream analyses. As a case study, we provide examples of the Atlantic cod genome, whose sequencing and assembly were hindered by a particularly high prevalence of tandem repeats. We complement this case study with examples from other species, where mis-annotations and sequencing errors have propagated into protein databases. With this review, we aim to raise the awareness level within the community of database users, and alert scientists working in the underlying workflow of database creation that the data they omit or improperly assemble may well contain important biological information valuable to others. © The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.
To track stepwise changes in genetic diversity and antimicrobial resistance in rapidly evolving OXA-232-producing Klebsiella pneumoniae ST14, an emerging carbapenem-resistant high-risk clone, in clinical settings.Twenty-six K. pneumoniae ST14 isolates were collected by the Korean Nationwide Surveillance of Antimicrobial Resistance system over the course of 1 year. Isolates were subjected to whole-genome sequencing and MIC determinations using 33 antibiotics from 14 classes.Single-nucleotide polymorphism (SNP) typing identified 72 unique SNP sites spanning the chromosomes of the isolates, dividing them into three clusters (I, II and III). The initial isolate possessed two plasmids with 18 antibiotic-resistance genes, including blaOXA-232, and exhibited resistance to 11 antibiotic classes. Four other plasmids containing 12 different resistance genes, including blaCTX-M-15 and strA/B, were introduced over time, providing additional resistance to aztreonam and streptomycin. Moreover, chromosomal integration of insertion sequence Ecp1-blaCTX-M-15 mediated the inactivation of mgrB responsible for colistin resistance in four isolates from cluster III. To the best of our knowledge, this is the first description of K. pneumoniae ST14 resistant to both carbapenem and colistin in South Korea. Furthermore, although some acquired genes were lost over time, the retention of 12 resistance genes and inactivation of mgrB provided resistance to 13 classes of antibiotics.We describe stepwise changes in OXA-232-producing K. pneumoniae ST14 in vivo over time in terms of antimicrobial resistance. Our findings contribute to our understanding of the evolution of emerging high-risk K. pneumoniae clones and provide reference data for future outbreaks.Copyright © 2019 European Society of Clinical Microbiology and Infectious Diseases. Published by Elsevier Ltd. All rights reserved.
Whole genome sequencing of bacteria has become daily routine in many fields. Advances in DNA sequencing technologies and continuously dropping costs have resulted in a tremendous increase in the amounts of available sequence data. However, comprehensive in-depth analysis of the resulting data remains an arduous and time consuming task. In order to keep pace with these promising but challenging developments and to transform raw data into valuable information, standardized analyses and scalable software tools are needed. Here, we introduce ASA3P, a fully automatic, locally executable and scalable assembly, annotation and analysis pipeline for bacterial genomes. The pipeline automatically executes necessary data processing steps, i.e. quality clipping and assembly of raw sequencing reads, scaffolding of contigs and annotation of the resulting genome sequences. Furthermore, ASA3P conducts comprehensive genome characterizations and analyses, e.g. taxonomic classification, detection of antibiotic resistance genes and identification of virulence factors. All results are presented via an HTML5 user interface providing aggregated information, interactive visualizations and access to intermediate results in standard bioinformatics file formats. We distribute ASA3P in two versions: a locally executable Docker container for small-to-medium-scale projects and an OpenStack based cloud computing version able to automatically create and manage self-scaling compute clusters. Thus, automatic and standardized analysis of hundreds of bacterial genomes becomes feasible within hours. The software and further information is available at: http://asap.computational.bio.
Tigecycline is one of the last-resort antibiotics to treat complicated infections caused by both multidrug-resistant Gram-negative and Gram-positive bacteria1. Tigecycline resistance has sporadically occurred in recent years, primarily due to chromosome-encoding mechanisms, such as overexpression of efflux pumps and ribosome protection2,3. Here, we report the emergence of the plasmid-mediated mobile tigecycline resistance mechanism Tet(X4) in Escherichia coli isolates from China, which is capable of degrading all tetracyclines, including tigecycline and the US FDA newly approved eravacycline. The tet(X4)-harbouring IncQ1 plasmid is highly transferable, and can be successfully mobilized and stabilized in recipient clinical and laboratory strains of Enterobacteriaceae bacteria. It is noteworthy that tet(X4)-positive E.?coli strains, including isolates co-harbouring mcr-1, have been widely detected in pigs, chickens, soil and dust samples in China. In vivo murine models demonstrated that the presence of Tet(X4) led to tigecycline treatment failure. Consequently, the emergence of plasmid-mediated Tet(X4) challenges the clinical efficacy of the entire family of tetracycline antibiotics. Importantly, our study raises concern that the plasmid-mediated tigecycline resistance may further spread into various ecological niches and into clinical high-risk pathogens. Collective efforts are in urgent need to preserve the potency of these essential antibiotics.
The antimicrobial resistance (AMR) crisis represents a serious threat to public health and has resulted in concentrated efforts to accelerate development of rapid molecular diagnostics for AMR. In combination with publicly-available web-based AMR databases, whole genome sequencing (WGS) offers the capacity for rapid detection of antibiotic resistance genes. Here we studied the concordance between WGS-based resistance prediction and phenotypic susceptibility testing results for methicillin-resistant Staphylococcus aureus (MRSA) and vancomycin resistant Enterococcus (VRE) clinical isolates using publicly-available tools and databases.Clinical isolates prospectively collected at the University of Pittsburgh Medical Center between December 2016 and December 2017 underwent WGS. Antibiotic resistance gene content was assessed from assembled genomes by BLASTn search of online databases. Concordance between WGS-predicted resistance profile and phenotypic susceptibility as well as sensitivity, specificity, positive and negative predictive values (NPV, PPV) were calculated for each antibiotic/organism combination, using the phenotypic results as the gold standard.Phenotypic susceptibility testing and WGS results were available for 1242 isolate/antibiotic combinations. Overall concordance was 99.3% with a sensitivity, specificity, PPV, NPV of 98.7% (95% CI, 97.2-99.5%), 99.6% (95 % CI, 98.8-99.9%), 99.3% (95% CI, 98.0-99.8%), 99.2% (95% CI, 98.3-99.7%), respectively. Additional identification of point mutations in housekeeping genes increased the concordance to 99.4% and the sensitivity to 99.3% (95% CI, 98.2-99.8%) and NPV to 99.4% (95% CI, 98.4-99.8%).WGS can be used as a reliable predicator of phenotypic resistance for both MRSA and VRE using readily-available online tools.Copyright © 2019. Published by Elsevier Ltd.
Long-read genome assembly tools are expected to reconstruct bacterial genomes nearly perfectly, however they still produce fragmented assemblies in some cases. It would be beneficial to understand whether these cases are intrinsically impossible to resolve, or if assemblers are at fault, implying that genomes could be refined or even finished with little to no additional experimental cost.We propose a set of computational techniques to assist inspection of fragmented bacterial genome assemblies, through careful analysis of assembly graphs. By finding paths of overlapping raw reads between pairs of contigs, we recover potential short-range connections between contigs that were lost during the assembly process. We show that our procedure recovers 45% of missing contig adjacencies in fragmented Canu assemblies, on samples from the NCTC bacterial sequencing project. We also observe that a simple procedure based on enumerating weighted Hamiltonian cycles can suggest likely contig orderings. In our tests, the correct contig order is ranked first in half of the cases and within the top-3 predictions in nearly all evaluated cases, providing a direction for finishing fragmented long-read assemblies.https://gitlab.inria.fr/pmarijon/knot.Supplementary data are available at Bioinformatics online. © The Author(s) (2019). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
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