Rapid virulence prediction and identification of Newcastle disease virus genotypes using third-generation sequencing

Newcastle disease (ND) is one of the most important infectious diseases of poultry and is a major economic burden to the global poultry industry. Virulent strains of avian paramyxovirus 1 (APMV-1), commonly known as Newcastle disease virus (NDV) [1], are the cause of ND and have been recently reclassified as avian avulavirus-1 (AAvV-1) [2]. Newcastle disease viruses are a highly diverse group of viruses with two distinct classes, 19 accepted genotypes and a wide host range including domestic and wild bird species. In addition to the genotypic diversity of NDVs, these viruses are also diverse in their virulence. This includes low virulent viruses, whose replication is limited to the respiratory and digestive tracts and typically cause clinically inapparent infections, to highly virulent viruses that cause acute disease with high mortality rates [1, 3]. The global spread, constant evolution, varying virulence, and the wide host range of NDV are challenges to the control of ND [4].

Effective control of ND is dependent on specific diagnostic testing, which is typically oriented towards detection, genotyping, or prediction of virulence. Virulence of NDV is best assayed through in vivo pathogenicity studies [5], but due to the cost and time constraints associated with such methods, reverse transcriptase-quantitative PCR (RT-qPCR) and sequencing of the F gene cleavage site are used to predict NDV virulence [6, 7]. Genotyping of NDV is commonly achieved through sequencing of the coding sequence of the fusion gene [8], which also allows for prediction of virulence. Preliminary genotyping can be accomplished through partial fusion gene sequencing (i.e., variable region) [9]. For detection of NDV, PCR assays avoid the highly variable fusion gene and instead target more conservative regions of the genome (i.e., matrix and polymerase genes) [10–14]; however, while this increases the applicability of these assays across genotypes, these assays lack applicability for virulence and genotypic determination. For example, while fusion-based assays can be used for detection [10, 15], the variability of this region, which makes it useful for genotyping, hinders the universal applicability of any single primer set [11, 12] and often requires screening samples with a different PCR assay prior to pathotyping [15]. Furthermore, for most current methods, detection, genotyping, and virulence prediction rely on Sanger sequencing; thus, they lack multiplexing capability and have limited sequencing depth, which complicates detection of mixed infections. In summary, there is a need to develop a method that will sensitively and rapidly detect NDV from multiple genotypes, while also providing genotype and virulence predictions.

Rapid advances in nucleic acid sequencing have led to different sequencing platforms [16, 17] being widely applied for identification of novel viruses [18], whole genome sequencing [19], transcriptomics, and metagenomics [20, 21]. However, high capital investments and relatively long turnaround times limit the widespread use of these next-generation sequencing (NGS) platforms, especially in developing countries [22]. Recent improvements in third-generation sequencing, including those introduced by Oxford Nanopore Technologies (ONT) [23], increase the utility of high-throughput sequencing as a useful tool for surveillance and pathogen characterization [24]. Among the transformative advantages of ONT’s sequencing technology are the ability to perform real-time sequence analysis with a short turnaround time [25], the portability of the MinION device, the low startup cost compared to other high-throughput platforms, and the ability to sequence up to several thousand bases from individual RNA or DNA molecules. The MinION device has been successfully used to evaluate antibiotic resistance genes from several bacterial species [26, 27], obtain complete viral genome sequences of an influenza virus [28] and Ebola virus [29], and detect partial viral genome sequences (e.g., Zika virus [30] and poxviruses [25]) by sequencing PCR amplicons (AmpSeq). The MinION, therefore, represents an opportunity to take infectious disease diagnostics a step further and to perform rapid identification and genetic characterization of infectious agents at a lower cost.

As with any deep sequencing platform, the sequence analysis approach is integral for accurate interpretation. Primarily, two approaches for taxonomic profiling of microbial sequencing data have been employed: read-based and de novo assembly-based classifications. Read-based metagenomic classification software has been used for identification of microbial species from high-throughput sequencing data [23, 31–33]. Although the sequencing accuracy of the MinION is improving, the raw single-read error rate of nearly 10% [34] may limit the accuracy of this approach for Nanopore data [31], especially when attempting to subspecies level differentiation. De novo approaches that use quality-based filtering and clustering of reads [35], or use consensus-based error correction of Nanopore sequencing reads have been reported [36]; however, these are not optimized for amplicon sequencing data.

In this study, a specific and rapid protocol, using the MinION sequencer, was developed to detect representative isolates from all currently circulating (excluding the Madagascar-limited genotype XI) genotypes of NDV. This protocol was also tested on 15 clinical swab samples collected from chickens during disease outbreaks. Additionally, a Galaxy-based, de novo AmpSeq workflow is presented that results in accurate final consensus sequences allowing for accurate genotype and virulence prediction. This study represents the first step towards developing AmpSeq as a diagnostic tool for NDV.

This study describes the development of a single protocol for rapid and accurate detection, virulence determination, and preliminary genotype identification (with sub-genotype resolution) of NDV utilizing the low-cost MinION sequencer. Additionally, an assembly-based sequence analysis workflow for MinION amplicon sequencing data was developed. This MinION AmpSeq workflow detected all currently circulating genotypes when using egg-grown viruses. Furthermore, clinical swab samples were used to demonstrate proof of concept that such samples contained sufficient NDV nucleic acid for detection, and interestingly AmpSeq detected 2 NDV genotypes (vaccine and virulent strains) in several clinical swab samples. These capabilities suggest this protocol may be useful for research and ancillary diagnostic procedures and indicates that further development and validation of NDV AmpSeq would be useful, especially in developing countries where NDV is endemic and there is a need for affordable epidemiological surveillance to track reservoirs and disease outbreaks.

The sequence heterogeneity among AAvV-1 genomes, which hinders the ability to develop a single test that sensitively detects NDV while also predicting the genotypic classification and virulence, is well known [4, 51, 52]. Currently, an RT-qPCR targeting the M gene [10] is most sensitive and is used for screening samples, but this assay only provides positive and negative results of the samples. RT-qPCRs that predict virulence based on the fusion gene are available [10, 54]; however, the lower sensitivity of these assays and the inability of at least one of these assays to detect viruses of all genotypes (e.g., genotypes Va and VI) [10, 12, 13] complicate diagnostic interpretation when the matrix and fusion tests have conflicting results. Thus, the only truly reliable option to detect a broad range of viruses and to determine virulence from some strains is to design multiple tests that include genotype-specific primers and probes [7, 12, 53]. Recently, Miller et al. reported that the primer set used in this study detected Class I and all nine of the tested class II genotypes [38]; however, this primer set was not tested against other currently circulating genotypes. The current study includes six additional genotypes, collectively representing all currently circulating genotypes (excluding the Madagascar-limited genotype XI). Furthermore, the ability to use AmpSeq as the final measure of a PCR allows for larger amplicon sizes as compared to RT-qPCR. As such, there will be one less restriction on primer site design when trying to create a pan-NDV primer set. Work is in progress to utilize the ability of MinION to sequence longer amplicon fragments, which will provide more complete phylogenetic information. After optimizing pan-NDV primer design for AmpSeq, sensitivity of pan-NDV AmpSeq will need to be further evaluated.

Additionally, while the preliminary analytical sensitivity of this protocol was determined using only one NDV genotype, the sensitivity of the MinION AmpSeq was comparable to the matrix RT-qPCR test, which does not allow inference of virulence. Further testing of the NDV AmpSeq sensitivity to current virulence-predicting RT-qPCR tests are warranted [14, 15]; however, even these tests lack the genotyping capability of AmpSeq. The ability of this AmpSeq method to detect different genotypes of NDV was further aided by barcoding PCR, which adds another round of PCR to the assay and the ability to adjust the concentration of samples during the library preparation phase. This latter step allows for more volume of low concentration (i.e., weak positives) samples to be added to the library pool. While the additional steps for library synthesis provide these advantages, they also add time to the assay (see below for further discussion of time efficiency). However, the benefit of implementing detection, genotype prediction, and virulence prediction into a single test adds value to this assay.

While the multifaceted nature of this MinION AmpSeq protocol is an advantage, time and cost efficiency must be maintained for it to be useful. MinION is inherently rapid due to the real-time nature of the sequencing. For example, this method identified the correct NDV genotype in all serial dilutions, with an accuracy of 98.37–100%, after only 7 min of sequencing. Because the MinION provides real-time sequence data, it is possible to monitor the sequencing run to determine the optimal run length for each library. Additionally, samples can be multiplexed into a single sequencing run, which reduces time and cost [55]. Recently, multiplexing and MinION sequencing of the PCR products from a panel of 5 samples was reported [55]. Here a panel of 33 samples was multiplexed while maintaining successful NDV genotyping from data collected within 3 h and 10 min of sequencing and without affecting mean read quality and percentage of high-quality reads. Thus, this protocol provides the flexibility to rapidly and economically obtain accurate sequence data for a preliminary genotyping and virulence prediction.

While Nanopore sequencing has numerous benefits, the high error rate poses unique challenges to data analysis. Thus, it is important to extract accurate consensus sequences from raw sequencing data [56]. As previously discussed, pathogen typing from sequencing data can be done with read count-based profiling or de novo assembly approaches [31]. However, there are a limited number of available tools suitable for handling the noisy reads currently produced by the MinION platform. The approach in this study takes advantage of the fact that single MinION reads often represent full-length amplicon sequences. By clustering full-length reads based on pairwise identity and subsequently performing consensus calling using standard multiple alignment software, this method quickly and reliably generates accurate (consistently greater than 99% sequence identity to paired MiSeq) de novo assemblies from amplicon datasets using as few as twenty reads per amplicon, and correct genotypic prediction with as few as five reads per amplicon. Thus, this approach overcomes the inherently high error rate (~ 90% accuracy) of Nanopore sequencing [57] and sequence identification and differentiation at the sub-genotype level can be highly reliable.

One known source of error in Nanopore sequencing is that 5-mers of A and T in the individual reads are difficult to identify accurately with MinION sequencing [58]. Importantly, a 5-mer run of a single base is not present in the cleavage site of the Fusion gene, however, two positions on the consensus sequence where there are 5-mers of A and C are present. Because of 2 instances in which only 4 nucleotides were read (one two nucleotide gap at 153–57 bp position and second on 233 bp) on 5-mer site, sample #37 had less than 100% identity to the respective Miseq data. It should be noted that this type of system error can be easily detected and manually corrected for a paramyxovirus (including NDV), which are viruses that do not tolerate single nucleotide deletions or insertions (rule of six) [59]. Because of the consensus-based approach, despite the relatively high, read-based error rate, the cleavage site was accurately determined.

Because this protocol relies on identity-based clustering prior to assembly, it maintains the ability to detect samples with mixed NDV genotypes. For example, in this study four clinical samples had two different genotypes as detected by MiSeq analysis, two of which were correctly identified by the MinION AmpSeq workflow. In a fifth case, a mixed sample was detected by MinION AmpSeq, but not by MiSeq. A potential explanation for these differences could be that the MiSeq sequencing was performed on egg-amplified samples, which may have altered the relative levels of the two genotypes, as compared to the direct clinical swab sample used for MinION sequencing. Additionally, the differences in molecular techniques (i.e., MinION: targeted; MiSeq: random) may have altered the relative abundance of the genotypes within the sequencing libraries. While further studies into the ability of this workflow to sensitively detect and differentiate NDV in samples with more than one genotype are ongoing, rapid NDV genotyping from clinical samples without culturing the virus in SPF eggs has the potential to facilitate disease diagnostics.

Taken together, this protocol reliably detected, genotyped, and predicted the virulence of NDV using laboratory stocks of all genetic variants currently circulating worldwide. Furthermore, preliminary testing of clinical-based samples suggests its feasibility using clinical swab samples. This assay can be used for research purposes and as an ancillary test in field investigations; however, further testing, including sensitivity validation on clinical samples and testing the effect of multiple isolates on sensitivity are warranted. Furthermore, the advantages of MinION AmpSeq allow for further optimization not possible with other techniques. For example, PCR product length is less of a restriction with MinION AmpSeq as compared to RT-qPCR. Overall, MinION AmpSeq improves the depth of information obtained from PCRs and allows for more flexibility in assay design, which can be broadly applied to the detection and characterization of numerous infectious agents.