NanoHIV: A Bioinformatics Pipeline for Producing Accurate, Near Full-Length HIV Proviral Genomes Sequenced Using the Oxford Nanopore Technology

Comparing Gold-Standard Sanger Sequencing with Two Next-Generation Sequencing Platforms of HIV-1 gp160 Single Genome Amplicons

Our goal was to assess the accuracy of next generation sequencing (NGS) compared with Sanger. We performed single genome amplification (SGA) of HIV-1 gp160 on extracted tissue DNA from two HIV+ individuals. Amplicons (n = 30) were sequenced with Sanger or reamplified with barcoded primers and pooled before sequencing using Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PB). For each amplicon, a consensus sequence for NGS reads was obtained by (1) mapping reads to the Sanger sequence when available ("reference-based") or (2) mapping reads to a "pseudo-reference" sequence, i.e., a consensus sequence of a subset of NGS reads ("reference-free"). PB reads were clustered based on genetic similarity. A Sanger consensus sequence was obtained for 23/30 amplicons, for which all NGS consensus sequences were identical (n = 9) or nearly identical (n = 14) compared with Sanger. For the nine mismatches between Sanger/NGS, the nucleotide in the NGS sequence matched all other sequences from that patient. Of the 7/30 amplicons without a Sanger sequence, NGS sequences had ≥35 ambiguous calls in five amplicons and 0 ambiguities in two amplicons. Analysis of the electropherograms showed failure of a single sequencing primer for the latter two amplicons (consistent with a single template) and overlapping peaks for the other five (consistent with multiple templates). Clustering results closely followed the Sanger/NGS consensus results, where amplicons derived from a single template also had a single cluster and vice versa (with one exception, which could be the result of barcode misidentification). Representative sequences from the clusters contained 2-13 differences compared with Sanger/NGS. In summary, we show that both ONT and PB can produce amplicon consensus sequences with similar or higher accuracy compared with Sanger and, importantly, without the need for a known reference sequence. Clustering could be useful in some circumstances to predict or confirm the presence of multiple starting templates.

Easing genomic surveillance: A comprehensive performance evaluation of long-read assemblers across multi-strain mixture data of HIV-1 and Other pathogenic viruses for constructing a user-friendly bioinformatic pipeline

Background

Determining the appropriate computational requirements and software performance is essential for efficient genomic surveillance. The lack of standardized benchmarking complicates software selection, especially with limited resources.

Methods

We developed a containerized benchmarking pipeline to evaluate seven long-read assemblers-Canu, GoldRush, MetaFlye, Strainline, HaploDMF, iGDA, and RVHaplo-for viral haplotype reconstruction, using both simulated and experimental Oxford Nanopore sequencing data of HIV-1 and other viruses. Benchmarking was conducted on three computational systems to assess each assembler's performance, utilizing QUAST and BLASTN for quality assessment.

Results

Our findings show that assembler choice significantly impacts assembly time, with CPU and memory usage having minimal effect. Assembler selection also influences the size of the contigs, with a minimum read length of 2,000 nucleotides required for quality assembly. A 4,000-nucleotide read length improves quality further. Canu was efficient among de novo assemblers but not suitable for multi-strain mixtures, while GoldRush produced only consensus assemblies. Strainline and MetaFlye were suitable for metagenomic sequencing data, with Strainline requiring high memory and MetaFlye operable on low-specification machines. Among reference-based assemblers, iGDA had high error rates, RVHaplo showed the best runtime and accuracy but became ineffective with similar sequences, and HaploDMF, utilizing machine learning, had fewer errors with a slightly longer runtime.

Conclusions

The HIV-64148 pipeline, containerized using Docker, facilitates easy deployment and offers flexibility to select from a range of assemblers to match computational systems or study requirements. This tool aids in genome assembly and provides valuable information on HIV-1 sequences, enhancing viral evolution monitoring and understanding.

HIV-PULSE: a long-read sequencing assay for high-throughput near full-length HIV-1 proviral genome characterization

A deep understanding of the composition of the HIV-1 reservoir is necessary for the development of targeted therapies and the evaluation of curative efforts. However, current near full-length (NFL) HIV-1 proviral genome sequencing assays are based on labor-intensive and costly principles of repeated PCRs at limiting dilution, restricting their scalability. To address this, we developed a high-throughput, long-read sequencing assay called HIV-PULSE (HIV Proviral UMI-mediated Long-read Sequencing). This assay uses unique molecular identifiers (UMIs) to tag individual HIV-1 genomes, allowing for the omission of the limiting dilution step and enabling long-range PCR amplification of many NFL genomes in a single PCR reaction, while simultaneously overcoming poor single-read accuracy. We optimized the assay using HIV-infected cell lines and then applied it to blood samples from 18 individuals living with HIV on antiretroviral therapy, yielding a total of 1308 distinct HIV-1 genomes. Benchmarking against the widely applied Full-Length Individual Proviral Sequencing assay revealed similar sensitivity (11 vs 18%) and overall good concordance, although at a significantly higher throughput. In conclusion, HIV-PULSE is a cost-efficient and scalable assay that allows for the characterization of the HIV-1 proviral landscape, making it an attractive method to study the HIV-1 reservoir composition and dynamics.

Long-Read Sequencing with Hierarchical Clustering for Antiretroviral Resistance Profiling of Mixed Human Immunodeficiency Virus Quasispecies

BACKGROUND

HIV infections often develop drug resistance mutations (DRMs), which can increase the risk of virological failure. However, it has been difficult to determine if minor mutations occur in the same genome or in different virions using Sanger sequencing and short-read sequencing methods. Oxford Nanopore Technologies (ONT) sequencing may improve antiretroviral resistance profiling by allowing for long-read clustering.

METHODS

A new ONT sequencing-based method for profiling DRMs in HIV quasispecies was developed and validated. The method used hierarchical clustering of long amplicons that cover regions associated with different types of antiretroviral drugs. A gradient series of an HIV plasmid and 2 plasma samples was prepared to validate the clustering performance. The ONT results were compared to those obtained with Sanger sequencing and Illumina sequencing in 77 HIV-positive plasma samples to evaluate the diagnostic performance.

RESULTS

In the validation study, the abundance of detected quasispecies was concordant with the predicted result with the R2 of > 0.99. During the diagnostic evaluation, 59/77 samples were successfully sequenced for DRMs. Among 18 failed samples, 17 were below the limit of detection of 303.9 copies/μL. Based on the receiver operating characteristic analysis, the ONT workflow achieved an F1 score of 0.96 with a cutoff of 0.4 variant allele frequency. Four cases were found to have quasispecies with DRMs, in which 2 harbored quasispecies with more than one class of DRMs. Treatment modifications were recommended for these cases.

CONCLUSIONS

Long-read sequencing coupled with hierarchical clustering could differentiate the quasispecies resistance profiles in HIV-infected samples, providing a clearer picture for medical care.

Nano-RECall provides an integrated pipeline for HIV-1 drug resistance testing from Oxford Nanopore sequence data

OBJECTIVES

Low-capital-layout sequencing options from Oxford Nanopore Technologies (ONT) could assist in expanding HIV drug resistance testing to resource-limited settings. HIV drug resistance mutations often occur as mixtures, but current ONT pipelines provide a consensus sequence only. Moreover, there is no integrated pipeline that provides a drug resistance report from an ONT sequence file without intervention from skilled bioinformaticists. We therefore investigated Nano-RECall, which provides seamless drug resistance interpretation while requiring low-read coverage ONT sequence data from affordable Flongle or MinION flow cells and which provides mutation mixtures similar to Sanger Sequencing.

METHODS

We compared Sanger sequencing to ONT sequencing of the same HIV-1 subtype C polymerase chain reaction (PCR) amplicons, respectively using RECall and the novel Nano-RECall bioinformatics pipelines. Amplicons were from separate assays: (a) Applied Biosystems HIV-1 Genotyping Kit (ThermoFisher) spanning protease (PR) to reverse transcriptase (RT) (PR-RT) (n = 46) and (b) homebrew integrase (IN) (n = 21). The agreement between Sanger sequences and ONT sequences was assessed at nucleotide level, and at codon level for Stanford HIV drug resistance database mutations at an optimal ONT read depth of 400 reads only.

RESULTS

The average sequence similarity between ONT and Sanger sequences was 99.3% (95% CI: 99.1%-99.4%) for PR-RT and 99.6% (95% CI: 99.4%-99.7%) for INT. Drug resistance mutations did not differ for 21 IN specimens; 8 mutations were detected by both ONT- and Sanger sequencing. For the 46 PR and RT specimens, 245 mutations were detected by either ONT or Sanger, of these 238 (97.1%) were detected by both.

CONCLUSIONS

The Nano-RECall pipeline, freely available as a downloadable application on a Windows computer, provides Sanger-equivalent HIV drug resistance interpretation. This novel pipeline combined with a simple workflow and multiplexing samples on ONT flow-cells would contribute to making HIV drug resistance sequencing feasible for resource-limited settings.

HIV-PULSE: A long-read sequencing assay for high-throughput near full-length HIV-1 proviral genome characterization

A deep understanding of the composition of the HIV-1 reservoir is necessary for the development of targeted therapies and the evaluation of curative efforts. However, current near full-length (NFL) HIV-1 proviral genome sequencing assays are based on labor-intensive and costly principles of repeated PCRs at limiting dilution, restricting their scalability. To address this, we developed a high-throughput, long-read sequencing assay called HIV-PULSE (HIV P roviral U MI-mediated L ong-read Se quencing). This assay uses unique molecular identifiers (UMIs) to tag individual HIV-1 genomes, allowing for the omission of the limiting dilution step and enabling long-range PCR amplification of many NFL genomes in a single PCR reaction, while simultaneously overcoming poor single-read accuracy. We optimized the assay using HIV-infected cell lines and then applied it to blood samples from 18 individuals living with HIV on antiretroviral therapy, yielding a total of 1,308 distinct HIV-1 genomes. Benchmarking against the widely applied Full-Length Individual Proviral Sequencing assay revealed similar sensitivity (11% vs 18%) and overall good concordance, though at a significantly higher throughput. In conclusion, HIV-PULSE is a cost-efficient and scalable assay that allows for the characterization of the HIV-1 proviral landscape, making it an attractive method to study the HIV-1 reservoir composition and dynamics.

Nanopore Sequencing for Characterization of HIV-1 Recombinant Forms

High genetic diversity, including the emergence of recombinant forms (RFs), is one of the most prominent features of human immunodeficiency virus type 1 (HIV-1). Conventional detection of HIV-1 RFs requires pretreatments, i.e., cloning or single-genome amplification, to distinguish them from dual- or multiple-infection variants. However, these processes are time-consuming and labor-intensive. Here, we constructed a new nanopore sequencing-based platform that enables us to obtain distinctive genetic information for intersubtype RFs and dual-infection HIV-1 variants by using amplicons of HIV-1 near-full-length genomes or two overlapping half-length genome fragments. Repeated benchmark tests of HIV-1 proviral DNA revealed consensus sequence inference with a reduced error rate, allowing us to obtain sufficiently accurate sequence data. In addition, we applied the platform for sequence analyses of 9 clinical samples with suspected HIV-1 RF infection or dual infection according to Sanger sequencing-based genotyping tests for HIV-1 drug resistance. For each RF infection case, replicated analyses involving our nanopore sequencing-based platform consistently produced long consecutive analogous consensus sequences with mosaic genomic structures consisting of two different subtypes. In contrast, we detected multiple heterologous sequences in each dual-infection case. These results demonstrate that our new nanopore sequencing platform is applicable to identify the full-length HIV-1 genome structure of intersubtype RFs as well as dual-infection heterologous HIV-1. Since the genetic diversity of HIV-1 continues to gradually increase, this system will help accelerate full-length genome analysis and molecular epidemiological surveillance for HIV-1. IMPORTANCE HIV-1 is characterized by large genetic differences, including HIV-1 recombinant forms (RFs). Conventional genetic analyses require time-consuming pretreatments, i.e., cloning or single-genome amplification, to distinguish RFs from dual- or multiple-infection cases. In this study, we developed a new analytical system for HIV-1 sequence data obtained by nanopore sequencing. The error rate of this method was reduced to ~0.06%. We applied this system for sequence analyses of 9 clinical samples with suspected HIV-1 RF infection or dual infection, which were extracted from 373 cases of HIV patients based on our retrospective analysis of HIV-1 drug resistance genotyping test results. We found that our new nanopore sequencing platform is applicable to identify the full-length HIV-1 genome structure of intersubtype RFs as well as dual-infection heterologous HIV-1. Our protocol will be useful for epidemiological surveillance to examine HIV-1 transmission as well as for genotypic tests of HIV-1 drug resistance in clinical settings.