Bassam Tork

Inferring viral quasispecies spectra from 454 pyrosequencing reads

BackgroundRNA viruses infecting a host usually exist as a set of closely related sequences, referred to as quasispecies. The genomic diversity of viral quasispecies is a subject of great interest, particularly for chronic infections, since it can lead to resistance to existing therapies. High-throughput sequencing is a promising approach to characterizing viral diversity, but unfortunately standard assembly software was originally designed for single genome assembly and cannot be used to simultaneously assemble and estimate the abundance of multiple closely related quasispecies sequences.ResultsIn this paper, we introduce a new Vi ral Sp ectrum A ssembler (ViSpA) method for quasispecies spectrum reconstruction and compare it with the state-of-the-art ShoRAH tool on both simulated and real 454 pyrosequencing shotgun reads from HCV and HIV quasispecies. Experimental results show that ViSpA outperforms ShoRAH on simulated error-free reads, correctly assembling 10 out of 10 quasispecies and 29 sequences out of 40 quasispecies. While ShoRAH has a significant advantage over ViSpA on reads simulated with sequencing errors due to its advanced error correction algorithm, ViSpA is better at assembling the simulated reads after they have been corrected by ShoRAH. ViSpA also outperforms ShoRAH on real 454 reads. Indeed, 7 most frequent sequences reconstructed by ViSpA from a real HCV dataset are viable (do not contain internal stop codons), and the most frequent sequence was within 1% of the actual open reading frame obtained by cloning and Sanger sequencing. In contrast, only one of the sequences reconstructed by ShoRAH is viable. On a real HIV dataset, ShoRAH correctly inferred only 2 quasispecies sequences with at most 4 mismatches whereas ViSpA correctly reconstructed 5 quasispecies with at most 2 mismatches, and 2 out of 5 sequences were inferred without any mismatches. ViSpA source code is available at http://alla.cs.gsu.edu/~software/VISPA/vispa.html.ConclusionsViSpA enables accurate viral quasispecies spectrum reconstruction from 454 pyrosequencing reads. We are currently exploring extensions applicable to the analysis of high-throughput sequencing data from bacterial metagenomic samples and ecological samples of eukaryote populations.

Reconstruction of viral population structure from next-generation sequencing data using multicommodity flows

BackgroundHighly mutable RNA viruses exist in infected hosts as heterogeneous populations of genetically close variants known as quasispecies. Next-generation sequencing (NGS) allows for analysing a large number of viral sequences from infected patients, presenting a novel opportunity for studying the structure of a viral population and understanding virus evolution, drug resistance and immune escape. Accurate reconstruction of genetic composition of intra-host viral populations involves assembling the NGS short reads into whole-genome sequences and estimating frequencies of individual viral variants. Although a few approaches were developed for this task, accurate reconstruction of quasispecies populations remains greatly unresolved.ResultsTwo new methods, AmpMCF and ShotMCF, for reconstruction of the whole-genome intra-host viral variants and estimation of their frequencies were developed, based on Multicommodity Flows (MCFs). AmpMCF was designed for NGS reads obtained from individual PCR amplicons and ShotMCF for NGS shotgun reads. While AmpMCF, based on covering formulation, identifies a minimal set of quasispecies explaining all observed reads, ShotMCS, based on packing formulation, engages the maximal number of reads to generate the most probable set of quasispecies. Both methods were evaluated on simulated data in comparison to Maximum Bandwidth and ViSpA, previously developed state-of-the-art algorithms for estimating quasispecies spectra from the NGS amplicon and shotgun reads, respectively. Both algorithms were accurate in estimation of quasispecies frequencies, especially from large datasets.ConclusionsThe problem of viral population reconstruction from amplicon or shotgun NGS reads was solved using the MCF formulation. The two methods, ShotMCF and AmpMCF, developed here afford accurate reconstruction of the structure of intra-host viral population from NGS reads. The implementations of the algorithms are available at http://alan.cs.gsu.edu/vira.html (AmpMCF) and http://alan.cs.gsu.edu/NGS/?q=content/shotmcf (ShotMCF).

Reconstructing viral quasispecies from NGS amplicon reads

This paper addresses the problem of reconstructing viral quasispecies from next-generation sequencing reads obtained from amplicons (i.e., reads generated from predefined amplified overlapping regions). We compare the parsimonious and likelihood models for this problem and propose several novel assembling algorithms. The proposed methods have been validated on simulated error-free HCV and real HBV amplicon reads. The new algorithms have been shown to outperform the method of Prosperi et. al. Our experiments also show that viral quasispecies can be reconstructed in most cases more accurately from amplicon reads rather than shotgun reads. All algorithms have been implemented and made available at https://bitbucket.org/nmancuso/bioa/.

Viral quasispecies reconstruction from amplicon 454 pyrosequencing reads

We consider the quasispecies spectrum reconstruction problem in amplicon reads. The main contribution of this paper is several methods to reconstruct HCV quasispecies from simulated error-free amplicon reads. Our comparison with existing methods for quasispecies spectrum reconstruction both based on shotgun and amplicon reads show significant advantages of the proposed technique. In most of the cases, even low coverage allows to reconstruct majority of quasispecies and very accurately estimate their frequencies in the simulated samples. The source code for all implemented algorithms is available at https://bitbucket.org/nmancuso/bioa/

Maximum likelihood estimation of incomplete genomic spectrum from HTS data

High-throughput sequencing makes possible to process samples containing multiple genomic sequences and then estimate their frequencies or even assemble them. The maximum likelihood estimation of frequencies of the sequences based on observed reads can be efficiently performed using expectation-maximization (EM) method assuming that we know sequences present in the sample. Frequently, such knowledge is incomplete, e.g., in RNA-seq not all isoforms are known and when sequencing viral quasispecies their sequences are unknown. We propose to enhance EM with a virtual string and incorporate it into frequency estimation tools for RNA-Seq and quasispecies sequencing. Our simulations show that EM enhanced with the virtual string estimates string frequencies more accurately than the original methods and that it can find the reads from missing quasispecies thus enabling their reconstruction.

Workshop: Bioinformatics methods for reconstruction of Infectious Bronchitis Virus quasispecies from next generation sequencing data

Viral infections cause a significant burden on animal health, reducing yields and increasing production costs due to expensive control programs. Vaccination is a vital part of control programs; however, its effectiveness is reduced by the quick evolution of escape viral quasispecies in animal hosts. Existing techniques for studying quasispecies evolution and response to vaccines have severely limited sensitivity and often require prior knowledge of sequence polymorphisms. By generating millions of short reads per run, with no need for culture or cloning, next-generation sequencing (NGS) technologies enable comprehensive identification of viral quasispecies infecting an animal. However, analysis of NGS data is challenging due to the huge amount of data on one hand, and to the short read lengths and high error rates on another. As a consequence, many tools developed for Sanger reads do not work at all or have impractical runtimes when applied to NGS data. Even newly developed algorithms for de novo genome assembly from NGS data are tuned for reconstruction of haploid genomes, and work poorly when the sequenced sample contains a large number of closely related sequences, as is the case in viral quasispecies. To address these shortcomings we have developed computational methods for reconstructing quasispecies sequences and estimate their frequencies from both shotgun and amplicon NGS data. Preliminary analysis of 454 sequencing reads generated from synthetic pools of Infectious Bronchitis Virus (IBV) clones and field isolates collected at various intervals after vaccination with attenuated live IBV vaccine will be presented.

Workshop: A maximum likelihood method for quasispecies spectrum assembly

A maximum-likelihood based approach for the quasispecies spectrum assembly problem inspired by minimum entropy principles is proposed. This approach is validated against simulated HCV amplicon data as well as actual HBV data.

Poster: ViSpA: Viral spectrum assembling method

Like many RNA viruses, Hepatitis C virus (HCV) exists as a set of closely related sequences (quasispecies). The diversity of the quasispecies sequences can explain vaccines failures and virus resistance to existing therapies. Would the most virulent quasispecies are known in an infected host, the more effective treatment would be given to a patient. Since the original software of next-generation sequencing systems assumes a single genome, there is a need for a new assembler that infers viral population in a host. Thus, we focus on Quasispecies Spectrum Reconstruction (QSR) Problem: given a collection of 454 pyrosequencing reads taken from a sample quasispecies population, reconstruct the quasispecies spectrum, i.e., the set of sequences and the relative frequency of each sequence in the sample population.