June 1, 2021  |  

A comparison of 454 GS FLX Ti and PacBio RS in the context of characterizing HIV-1 intra-host diversity.

PacBio 2013 User Group Meeting Presentation Slides: Lance Hepler from UC San Diego’s Center for AIDS Research used the PacBio RS to study intra-host diversity in HIV-1. He compared PacBio’s performance to that of 454® sequencer, the platform he and his team previously used. Hepler noted that in general, there was strong agreement between the platforms; where results differed, he said that PacBio data had significantly better reproducibility and accuracy. “PacBio does not suffer from local coverage loss post-processing, whereas 454 has homopolymer problems,” he noted. Hepler said they are moving away from using 454 in favor of the PacBio system.


June 1, 2021  |  

Characterization of NNRTI mutations in HIV-1 RT using Single Molecule, Real-Time SMRT Sequencing.

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.


June 1, 2021  |  

Next generation sequencing of full-length HIV-1 env during primary infection.

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.


June 1, 2021  |  

An improved circular consensus algorithm with an application to detection of HIV-1 Drug-Resistance Associated Mutations (DRAMs)

Scientists who require confident resolution of heterogeneous populations across complex regions have been unable to transition to short-read sequencing methods. They continue to depend on Sanger Sequencing despite its cost and time inefficiencies. Here we present a new redesigned algorithm that allows the generation of circular consensus sequences (CCS) from individual SMRT Sequencing reads. With this new algorithm, dubbed CCS2, it is possible to reach arbitrarily high quality across longer insert lengths at a lower cost and higher throughput than Sanger Sequencing. We apply this new algorithm, dubbed CCS2, to the characterization of the HIV-1 K103N drug-resistance associated mutation, which is both important clinically, and represents a challenge due to regional sequence context. A mutation was introduced into the 3rd position of amino acid position 103 (A>C substitution) of the RT gene on a pNL4-3 backbone by site-directed mutagenesis. Regions spanning ~1,300 bp were PCR amplified from both the non-mutated and mutant (K103N) plasmids, and were sequenced individually and as a 50:50 mixture. Sequencing data were analyzed using the new CCS2 algorithm, which uses a fully-generative probabilistic model of our SMRT Sequencing process to polish consensus sequences to arbitrarily high accuracy. This result, previously demonstrated for multi-molecule consensus sequences with the Quiver algorithm, is made possible by incorporating per-Zero Mode Waveguide (ZMW) characteristics, thus accounting for the intrinsic changes in the sequencing process that are unique to each ZMW. With CCS2, we are able to achieve a per-read empirical quality of QV30 with 19X coverage. This yields ~5000 1.3 kb consensus sequences with a collective empirical quality of ~QV40. Additionally, we demonstrate a 0% miscall rate in both unmixed samples, and estimate a 48:52% frequency for the K103N mutation in the mixed sample, consistent with data produced by orthogonal platforms.


June 1, 2021  |  

An improved circular consensus algorithm with an application to detect HIV-1 Drug Resistance Associated Mutations (DRAMs)

Scientists who require confident resolution of heterogeneous populations across complex regions have been unable to transition to short-read sequencing methods. They continue to depend on Sanger sequencing despite its cost and time inefficiencies. Here we present a new redesigned algorithm that allows the generation of circular consensus sequences (CCS) from individual SMRT Sequencing reads. With this new algorithm, dubbed CCS2, it is possible to reach high quality across longer insert lengths at a lower cost and higher throughput than Sanger sequencing. We applied CCS2 to the characterization of the HIV-1 K103N drug-resistance associated mutation in both clonal and patient samples. This particular DRAM has previously proved to be clinically relevant, but challenging to characterize due to regional sequence context. First, a mutation was introduced into the 3rd position of amino acid position 103 (A>C substitution) of the RT gene on a pNL4-3 backbone by site-directed mutagenesis. Regions spanning ~1.3 kb were PCR amplified from both the non-mutated and mutant (K103N) plasmids, and were sequenced individually and as a 50:50 mixture. Additionally, the proviral reservoir of a subject with known dates of virologic failure of an Efavirenz-based regimen and with documented emergence of drug resistant (K103N) viremia was sequenced at several time points as a proof-of-concept study to determine the kinetics of retention and decay of K103N.Sequencing data were analyzed using the new CCS2 algorithm, which uses a fully-generative probabilistic model of our SMRT Sequencing process to polish consensus sequences to high accuracy. With CCS2, we are able to achieve a per-read empirical quality of QV30 (99.9% accuracy) at 19X coverage. A total of ~5000 1.3 kb consensus sequences with a collective empirical quality of ~QV40 (99.99%) were obtained for each sample. We demonstrate a 0% miscall rate in both unmixed control samples, and estimate a 48:52 frequency for the K103N mutation in the mixed (50:50) plasmid sample, consistent with data produced by orthogonal platforms. Additionally, the K103N escape variant was only detected in proviral samples from time points subsequent (19%) to the emergence of drug resistant viremia. This tool might be used to monitor the HIV reservoir for stable evolutionary changes throughout infection.


April 21, 2020  |  

High-Resolution Evolutionary Analysis of Within-Host Hepatitis C Virus Infection.

Despite recent breakthroughs in treatment of hepatitis C virus (HCV) infection, we have limited understanding of how virus diversity generated within individuals impacts the evolution and spread of HCV variants at the population scale. Addressing this gap is important for identifying the main sources of disease transmission and evaluating the risk of drug-resistance mutations emerging and disseminating in a population.We have undertaken a high-resolution analysis of HCV within-host evolution from 4 individuals coinfected with human immunodeficiency virus 1 (HIV-1). We used long-read, deep-sequenced data of full-length HCV envelope glycoprotein, longitudinally sampled from acute to chronic HCV infection to investigate the underlying viral population and evolutionary dynamics.We found statistical support for population structure maintaining the within-host HCV genetic diversity in 3 out of 4 individuals. We also report the first population genetic estimate of the within-host recombination rate for HCV (0.28 × 10-7 recombination/site/year), which is considerably lower than that estimated for HIV-1 and the overall nucleotide substitution rate estimated during HCV infection.Our findings indicate that population structure and strong genetic linkage shapes within-host HCV evolutionary dynamics. These results will guide the future investigation of potential HCV drug resistance adaptation during infection, and at the population scale. © The Author(s) 2019. Published by Oxford University Press for the Infectious Diseases Society of America.


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