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Our understanding of microbiology has evolved enormously over the last 150 years. Few institutions have witnessed our collective progress more closely than the National Collection of Type Cultures (NCTC). In fact, the collection itself is a record of the many milestones microbiologists have crossed, building on the discoveries of those who came before. To date, 60% of NCTC’s historic collection now has a closed, finished reference genome, thanks to PacBio Single Molecule, Real- Time (SMRT) Sequencing. We are excited to be their partner in crossing this latest milestone on their quest to improve human and animal health by understanding the microscopic world.
The UK’s National Collection of Type Cultures (NCTC) is a unique collection of more than 5,000 expertly preserved and authenticated bacterial cultures, many of historical significance. Founded in 1920, NCTC is the longest established collection of its type anywhere in the world, with a history of its own that has reflected — and contributed to — the evolution of microbiology for more than 100 years.
Discover the benefits of HiFi reads and learn how highly accurate long-read sequencing provides a single technology solution across a range of applications.
Highly accurate long reads – HiFi reads – with single-molecule resolution make Single Molecule, Real-Time (SMRT) Sequencing ideal for full-length 16S rRNA sequencing, shotgun metagenomic profiling, and metagenome assembly.
Shiga toxin-producing Escherichia coli (STEC) is an emerging pathogen. Recently there has been a global in the number of outbreaks caused by non-O157 STECs, typically involving six serogroups O26, O45, 0103, 0111, and 0145. STEC O145:H28 has been associated with severe human disease including hemolytic-uremic syndrome (HUS), and is demonstrated by the 2007 Belgian ice-cream-associated outbreak and 2010 US lettuce-associated outbreak, with over 10% of patients developing HUS in each. The goal of this work was to do comparative genomics of strains, clinical and environmental, to investigate genome diversity and virulence evolution of this important foodborne pathogen.
We sequenced complete HIV-1 genomes from single molecules using Single Molecule, Real- Time (SMRT) Sequencing and derive de novo full-length genome sequences. SMRT sequencing yields long-read sequencing results from individual DNA molecules with a rapid time-to-result. These attributes make it a useful tool for continuous monitoring of viral populations. The single-molecule nature of the sequencing method allows us to estimate variant subspecies and relative abundances by counting methods. We detail mathematical techniques used in viral variant subspecies identification including clustering distance metrics and mutual information. Sequencing was performed in order to better understand the relationships between the specific sequences of transmitted viruses in linked transmission pairs. Samples representing HIV transmission pairs were selected from the Zambia Emory HIV Research Project (Lusaka, Zambia) and sequenced. We examine Single Genome Amplification (SGA) prepped samples and samples containing complex mixtures of genomes. Whole genome consensus estimates for each of the samples were made. Genome reads were clustered using a simple distance metric on aligned reads. Appropriate thresholds were chosen to yield distinct clusters of HIV genomes within samples. Mutual information between columns in the genome alignments was used to measure dependence. In silico mixtures of reads from the SGA samples were made to simulate samples containing exactly controlled complex mixtures of genomes and our clustering methods were applied to these complex mixtures. SMRT Sequencing data contained multiple full-length (greater than 9 kb) continuous reads for each sample. Simple whole genome consensus estimates easily identified transmission pairs. The clustering of the genome reads showed diversity differences between the samples, allowing us to characterize the diversity of the individual quasi-species comprising the patient viral populations across the full genome. Mutual information identified possible dependencies of different positions across the full HIV-1 genome. The SGA consensus genomes agreed with prior Sanger sequencing. Our clustering methods correctly segregated reads to their correct originating genome for the synthetic SGA mixtures. The results open up the potential for reference-agnostic and cost effective full genome sequencing of HIV-1.
One of the major applications of DNA sequencing technology is to bring together information that is distant in sequence space so that understanding genome structure and function becomes easier on a large scale. The Single Molecule Real Time (SMRT) Sequencing platform provides direct sequencing data that can span several thousand bases to tens of thousands of bases in a high-throughput fashion. In contrast to solving genomic puzzles by patching together smaller piece of information, long sequence reads can decrease potential computation complexity by reducing combinatorial factors significantly. We demonstrate algorithmic approaches to construct accurate consensus when the differences between reads are dominated by insertions and deletions. High-performance implementations of such algorithms allow more efficient de novo assembly with a pre-assembly step that generates highly accurate, consensus-based reads which can be used as input for existing genome assemblers. In contrast to recent hybrid assembly approach, only a single ~10 kb or longer SMRTbell library is necessary for the hierarchical genome assembly process (HGAP). Meanwhile, with a sensitive read-clustering algorithm with the consensus algorithms, one is able to discern haplotypes that differ by less than 1% different from each other over a large region. One of the related applications is to generate accurate haplotype sequences for HLA loci. Long sequence reads that can cover the whole 3 kb to 4 kb diploid genomic regions will simplify the haplotyping process. These algorithms can also be applied to resolve individual populations within mixed pools of DNA molecules that are similar to each, e.g., by sequencing viral quasi-species samples.
Understanding the genetic basis of infectious diseases is critical to enacting effective treatments, and several large-scale sequencing initiatives are underway to collect this information. Sequencing bacterial samples is typically performed by mapping sequence reads against genomes of known reference strains. While such resequencing informs on the spectrum of single-nucleotide differences relative to the chosen reference, it can miss numerous other forms of variation known to influence pathogenicity: structural variations (duplications, inversions), acquisition of mobile elements (phages, plasmids), homonucleotide length variation causing phase variation, and epigenetic marks (methylation, phosphorothioation) that influence gene expression to switch bacteria from non- pathogenic to pathogenic states. Therefore, sequencing methods which provide complete, de novo genome assemblies and epigenomes are necessary to fully characterize infectious disease agents in an unbiased, hypothesis-free manner. Hybrid assembly methods have been described that combine long sequence reads from SMRT DNA Sequencing with short reads (SMRT CCS (circular consensus) or second-generation reads), wherein the short reads are used to error-correct the long reads which are then used for assembly. We have developed a new paradigm for microbial de novo assemblies in which SMRT sequencing reads from a single long insert library are used exclusively to close the genome through a hierarchical genome assembly process, thereby obviating the need for a second sample preparation, sequencing run, and data set. We have applied this method to achieve closed de novo genomes with accuracies exceeding QV50 (>99.999%) for numerous disease outbreak samples, including E. coli, Salmonella, Campylobacter, Listeria, Neisseria, and H. pylori. The kinetic information from the same SMRT Sequencing reads is utilized to determine epigenomes. Approximately 70% of all methyltransferase specificities we have determined to date represent previously unknown bacterial epigenetic signatures. With relatively short sequencing run times and automated analysis pipelines, it is possible to go from an unknown DNA sample to its complete de novo genome and epigenome in about a day.
Understanding the genetic basis of infectious diseases is critical to enacting effective treatments, and several large-scale sequencing initiatives are underway to collect this information. Sequencing bacterial samples is typically performed by mapping sequence reads against genomes of known reference strains. While such resequencing informs on the spectrum of single nucleotide differences relative to the chosen reference, it can miss numerous other forms of variation known to influence pathogenicity: structural variations (duplications, inversions), acquisition of mobile elements (phages, plasmids), homonucleotide length variation causing phase variation, and epigenetic marks (methylation, phosphorothioation) that influence gene expression to switch bacteria from non-pathogenic to pathogenic states. Therefore, sequencing methods which provide complete, de novo genome assemblies and epigenomes are necessary to fully characterize infectious disease agents in an unbiased, hypothesis-free manner. Hybrid assembly methods have been described that combine long sequence reads from SMRT DNA sequencing with short, high-accuracy reads (SMRT (circular consensus sequencing) CCS or second-generation reads) to generate long, highly accurate reads that are then used for assembly. We have developed a new paradigm for microbial de novo assemblies in which long SMRT sequencing reads (average readlengths >5,000 bases) are used exclusively to close the genome through a hierarchical genome assembly process, thereby obviating the need for a second sample preparation, sequencing run and data set. We have applied this method to achieve closed de novo genomes with accuracies exceeding QV50 (>99.999%) to numerous disease outbreak samples, including E. coli, Salmonella, Campylobacter, Listeria, Neisseria, and H. pylori. The kinetic information from the same SMRT sequencing reads is utilized to determine epigenomes. Approximately 70% of all methyltransferase specificities we have determined to date represent previously unknown bacterial epigenetic signatures. The process has been automated and requires less than 1 day from an unknown DNA sample to its complete de novo genome and epigenome.
Pulmonary non-tuberculous mycobacterial (PNTM) infections occur in patients with chronic lung disease, but also in a distinct group of elderly women without lung defects who share a common body morphology: tall and lean with scoliosis, pectus excavatum, and mitral valve prolapse. In order to characterize the human host susceptibility to PNTM, we performed whole exome sequencing (WES) of 44 individuals in extended families of patients with active PNTM as well as 55 additional unrelated individuals with PNTM. This unique collection of familial cohorts in PNTM represents an important opportunity for a high yield search for genes that regulate mucosal immunity. An average of 58 million 100bp paired-end Illumina reads per exome were generated and mapped to the hg19 reference genome. Following variant detection and classification, we identified 58,422 potentially high-impact SNPs, 97.3% of which were missense mutations. Segregating variants using the family pedigrees as well as comparisons to the unrelated individuals identified multiple potential variants associated with PNTM. Validations of these candidate variants in a larger PNTM cohort are underway. In addition to WES, we sequenced the genomes of 52 mycobacterial isolates, including 9 from these PNTM patients, to integrate host PNTM susceptibility with mycobacterial genotypes and gain insights into the key factors involved in this devastating disease. These genomes were sequenced using a combination of 454, Illumina, and PacBio platforms and assembled using multiple genome assemblers. The resulting genome sequences were used to identify mycobacterial genotypes associated with virulence, invasion, and drug resistance.
The newer hierarchical genome assembly process (HGAP) performs de novo assembly using data from a single PacBio long insert library. To assess the benefits of this method, DNA from several Salmonella enterica serovars was isolated from a pure culture. Genome sequencing was performed using Pacific Biosciences RS sequencing technology. The HGAP process enabled us to close sixteen Salmonella subsp. enterica genomes and their associated mobile elements: The ten serotypes include: Salmonella enterica subsp. enterica serovar Enteritidis (S. Enteritidis) S. Bareilly, S. Heidelberg, S. Cubana, S. Javiana and S. Typhimurium, S. Newport, S. Montevideo, S. Agona, and S. Tennessee. In addition, we were able to detect novel methyltransferases (MTases) by using the Pacific Biosciences kinetic score distributions showing that each serovar appears to have a novel methylation pattern. For example while all Salmonella serovars examined so far have methylase specific activity for 5’-GATC-3’/3’-CTAG-5’ and 5’-CAGAG-3’/3’-GTCTC-5’ (underlined base indicates a modification), S. Heidelberg is uniquely specific for 5’-ACCANCC-3’/3’-TGGTNGG-5’, while S. Typhimurium has uniquely methylase specific for 5′-GATCAG-3’/3′- CTAGTC-5′ sites, for the samples examined so far. We believe that this may be due to the unique environments and phages that these serotypes have been exposed to. Furthermore, our analysis identified and closed a variety of plasmids such as mobilization plasmids, antimicrobial resistance plasmids and IncX plasmids carrying a Type IV secretion system (T4SS). The VirB/D4 T4SS apparatus is important in that it assists with rapid dissemination of antibiotic resistance and virulence determinants. Presently, only limited information exists regarding the genotypic characterization of drug resistance in S. Heidelberg isolates derived from various host species. Here, we characterize two S. Heidelberg outbreak isolates from two different outbreaks. Both isolates contain the IncX plasmid of approximately 35 kb, and carried the genes virB1, virB2, virB3/4, virB5, virB6, virB7, virB8, virB9, virB10, virB11, virD2, and virD4, that are associated with the T4SS. In addition, the outbreak isolate associated with ground turkey carries a 4,473 bp mobilization plasmid and an incompatibility group (Inc) I1 antimicrobial resistance plasmid encoding resistance to gentamicin (aacC2), beta-lactam (bl2b_tem), streptomycin (aadAI) and tetracycline (tetA, tetR) while the outbreak isolate associated with chicken breast carries the IncI1 plasmid encoding resistance to gentamicin (aacC2), streptomycin (aadAI) and sulfisoxazole (sul1). Using this new technology we explored the genetic elements present in resistant pathogens which will achieve a better understanding of the evolution of Salmonella.
Background: Genotypic testing of chronic viral infections is an important part of patient therapy and requires assays capable of detecting the entire spectrum of viral mutations. Single Molecule, Real-Time (SMRT) sequencing offers several advantages to other sequencing technologies, including superior resolution of mixed populations and long read lengths capable of spanning entire viral protein coding regions. We examined detection sensitivity of SMRT sequencing using a mixture of HIV-1 RT gene coding regions containing single NNRTI mutations. Methodology: SMRTbell templates were prepared from PCR products generated from a prospective reference material being developed by BC Center of Excellence for HIV/AIDS, and contained a mixture of fifteen infectious viruses containing single NNRTI resistance mutations (viz V90I, K101E, K103N, V108I, E138A/G/K/Q, V179D, Y181C, Y188C, G190A/S, M230L and P236L) built upon the HIV-1LAI molecular clone. Templates were sequenced on the PacBio RS II to obtain single molecule long reads using P4/C2 chemistry, using 180 minute movie collection without stage start. The relative abundances of the mutant viruses were then estimated using codon-aware analysis methods. Results: Sequencing of these templates produced average read lengths of 5.0 KB, comprising 40,000-fold coverage across the entire amplicon per SMRT Cell. All the expected mutations in the mixture of mutant viruses were accurately identified. Frequencies of NNRTI variants estimated ranged from 0.5% to 12.5%. Conclusions: Codon analysis revealed a number of variants across the amplicon with highly consistent results across SMRT Cells. From a single SMRT Cell, variants were accurately and reliably detected down to 0.5% with simple analyses. Long polymerase reads and high accuracy reads make it possible to call variants from just a few molecules. SMRT Sequencing can identify species comprising a mixed viral population, with granularity and low cost of consumables allowing for smaller multiplexing of samples and first-in-first-out processing.
Background: The use of next generation sequencing (NGS) to examine circulating HIV env variants has been limited due to env’s length (2.6 kb), extensive indel polymorphism, GC deficiency, and long homopolymeric regions. We developed and standardized protocols for isolation, RT-PCR amplification, single molecule real-time (SMRT) sequencing, and haplotype analysis of circulating HIV-1 env variants to evaluate viral diversity in primary infection. Methodology: HIV RNA was extracted from 7 blood plasma samples (1 mL) collected from 5 subjects (one individual sampled and sequenced at 3 time points) in the San Diego Primary Infection Cohort between 3-33 months from their estimated date of infection (EDI). Median viral load per sample was 50,118 HIV RNA copies/mL (range: 22,387-446,683). Full-length (3.2 kb) env amplicons were constructed into SMRTbell templates without shearing, and sequenced on the PacBio RS II using P4/C2 chemistry and 180 minute movie collection without stage start. To examine viral diversity in each sample, we determined haplotypes by clustering circular consensus sequences (CCS), and reconstructing a cluster consensus sequence using a partial order alignment approach. We measured sample diversity both as the mean pairwise distance among reads, and the fraction of reads containing indel polymorphisms. Results: We collected a median of 8,775 CCS reads per SMRT Cell (range: 4243-12234). A median of 7 haplotypes per subject (range: 1-55) were inferred at baseline. For the one subject with longitudinal samples analyzed, we observed an increasing number of distinct haplotypes (8 to 55 haplotypes over the course of 30 months), and an increasing mean pairwise distance among reads (from 0.8% to 1.6%, Tamura-Nei 93). We also observed significant indel polymorphism, with 16% of reads from one sample later in infection (33 months post-EDI) exhibiting deletions of more than 10% of env with respect to the reference strain, HXB2. Conclusions: This study developed a standardized NGS procedure (PacBio SMRT) to deep sequence full-length HIV RNA env variants from the circulating viral population, achieving good coverage, confirming low env diversity during primary infection that increased over time, and revealing significant indel polymorphism that highlights structural variation as important to env evolution. The long, accurate reads greatly simplified downstream bioinformatics analyses, especially haplotype phasing, increasing our confidence in the results. The sequencing methodology and analysis tools developed here could be successfully applied to any area for which full-length HIV env analysis would be useful.
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