Towards Clinical Molecular Diagnosis of Inherited Cardiac Conditions: A Comparison of Bench-Top Genome DNA Sequencers

Background

Molecular genetic testing is recommended for diagnosis of inherited cardiac disease, to guide prognosis and treatment, but access is often limited by cost and availability. Recently introduced high-throughput bench-top DNA sequencing platforms have the potential to overcome these limitations.

Methodology/Principal Findings

We evaluated two next-generation sequencing (NGS) platforms for molecular diagnostics. The protein-coding regions of six genes associated with inherited arrhythmia syndromes were amplified from 15 human samples using parallelised multiplex PCR (Access Array, Fluidigm), and sequenced on the MiSeq (Illumina) and Ion Torrent PGM (Life Technologies). Overall, 97.9% of the target was sequenced adequately for variant calling on the MiSeq, and 96.8% on the Ion Torrent PGM. Regions missed tended to be of high GC-content, and most were problematic for both platforms. Variant calling was assessed using 107 variants detected using Sanger sequencing: within adequately sequenced regions, variant calling on both platforms was highly accurate (Sensitivity: MiSeq 100%, PGM 99.1%. Positive predictive value: MiSeq 95.9%, PGM 95.5%). At the time of the study the Ion Torrent PGM had a lower capital cost and individual runs were cheaper and faster. The MiSeq had a higher capacity (requiring fewer runs), with reduced hands-on time and simpler laboratory workflows. Both provide significant cost and time savings over conventional methods, even allowing for adjunct Sanger sequencing to validate findings and sequence exons missed by NGS.

Conclusions/Significance

MiSeq and Ion Torrent PGM both provide accurate variant detection as part of a PCR-based molecular diagnostic workflow, and provide alternative platforms for molecular diagnosis of inherited cardiac conditions. Though there were performance differences at this throughput, platforms differed primarily in terms of cost, scalability, protocol stability and ease of use. Compared with current molecular genetic diagnostic tests for inherited cardiac arrhythmias, these NGS approaches are faster, less expensive, and yet more comprehensive.     

Quantification of epigenetic biomarkers: an evaluation of established and emerging methods for DNA methylation analysis

Background

DNA methylation is an important epigenetic mechanism in several human diseases, most notably cancer. The quantitative analysis of DNA methylation patterns has the potential to serve as diagnostic and prognostic biomarkers, however, there is currently a lack of consensus regarding the optimal methodologies to quantify methylation status. To address this issue we compared five analytical methods: (i) MethyLight qPCR, (ii) MethyLight digital PCR (dPCR), methylation-sensitive and -dependent restriction enzyme (MSRE/MDRE) digestion followed by (iii) qPCR or (iv) dPCR, and (v) bisulfite amplicon next generation sequencing (NGS). The techniques were evaluated for linearity, accuracy and precision.

Results

MethyLight qPCR displayed the best linearity across the range of tested samples. Observed methylation measured by MethyLight- and MSRE/MDRE-qPCR and -dPCR were not significantly different to expected values whilst bisulfite amplicon NGS analysis over-estimated methylation content. Bisulfite amplicon NGS showed good precision, whilst the lower precision of qPCR and dPCR analysis precluded discrimination of differences of < 25% in methylation status. A novel dPCR MethyLight assay is also described as a potential method for absolute quantification that simultaneously measures both sense and antisense DNA strands following bisulfite treatment.

Conclusions

Our findings comprise a comprehensive benchmark for the quantitative accuracy of key methods for methylation analysis and demonstrate their applicability to the quantification of circulating tumour DNA biomarkers by using sample concentrations that are representative of typical clinical isolates.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1174) contains supplementary material, which is available to authorized users.     

Applicability and Efficiency of NGS in Routine Diagnosis: In-Depth Performance Analysis of a Complete Workflow for CFTR Mutation Analysis

Background

Actually, about 2000 sequence variations have been documented in the CFTR gene requiring extensive and multi-step genetic testing in the diagnosis of cystic fibrosis and CFTR-related disorders. We present a two phases study, with validation and performance monitoring, of a single experiment methodology based on multiplex PCR and high throughput sequencing that allows detection of all variants, including large rearrangements, affecting the coding regions plus three deep intronic loci.

Methods

A total of 340 samples, including 257 patients and 83 previously characterized control samples, were sequenced in 17 MiSeq runs and analyzed with two bioinformatic pipelines in routine diagnostic conditions. We obtained 100% coverage for all the target regions in every tested sample.

Results

We correctly identified all the 87 known variants in the control samples and successfully confirmed the 62 variants identified among the patients without observing false positive results. Large rearrangements were identified in 18/18 control samples. Only 17 patient samples showed false positive signals (6.6%), 12 of which showed a borderline result for a single amplicon. We also demonstrated the ability of the assay to detect allele specific dropout of amplicons when a sequence variation occurs at a primer binding site thus limiting the risk for false negative results.

Conclusions

We described here the first NGS workflow for CFTR routine analysis that demonstrated equivalent diagnostic performances compared to Sanger sequencing and multiplex ligation-dependent probe amplification. This study illustrates the advantages of NGS in term of scalability, workload reduction and cost-effectiveness in combination with an improvement of the overall data quality due to the simultaneous detection of SNVs and large rearrangements.     

A fault-tolerant method for HLA typing with PacBio data

Background

Human leukocyte antigen (HLA) genes are critical genes involved in important biomedical aspects, including organ transplantation, autoimmune diseases and infectious diseases. The gene family contains the most polymorphic genes in humans and the difference between two alleles is only a single base pair substitution in many cases. The next generation sequencing (NGS) technologies could be used for high throughput HLA typing but in silico methods are still needed to correctly assign the alleles of a sample. Computer scientists have developed such methods for various NGS platforms, such as Illumina, Roche 454 and Ion Torrent, based on the characteristics of the reads they generate. However, the method for PacBio reads was less addressed, probably owing to its high error rates. The PacBio system has the longest read length among available NGS platforms, and therefore is the only platform capable of having exon 2 and exon 3 of HLA genes on the same read to unequivocally solve the ambiguity problem caused by the “phasing” issue.

Results

We proposed a new method BayesTyping1 to assign HLA alleles for PacBio circular consensus sequencing reads using Bayes’ theorem. The method was applied to simulated data of the three loci HLA-A, HLA-B and HLA-DRB1. The experimental results showed its capability to tolerate the disturbance of sequencing errors and external noise reads.

Conclusions

The BayesTyping1 method could overcome the problems of HLA typing using PacBio reads, which mostly arise from sequencing errors of PacBio reads and the divergence of HLA genes, to some extent.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-296) contains supplementary material, which is available to authorized users.     

The diagnostic application of targeted re-sequencing in Korean patients with retinitis pigmentosa

Background

Identification of the causative genes of retinitis pigmentosa (RP) is important for the clinical care of patients with RP. However, a comprehensive genetic study has not been performed in Korean RP patients. Moreover, the genetic heterogeneity found in sensorineural genetic disorders makes identification of pathogenic mutations challenging. Therefore, high throughput genetic testing using massively parallel sequencing is needed.

Results

Sixty-two Korean patients with nonsyndromic RP (46 patients from 18 families and 16 simplex cases) who consented to molecular genetic testing were recruited in this study and targeted exome sequencing was applied on 53 RP-related genes. Causal variants were characterised by selecting exonic and splicing variants, selecting variants with low allele frequency (below 1 %), and discarding the remaining variants with quality below 20. The variants were additionally confirmed by an inheritance pattern and cosegregation test of the families, and the rest of the variants were prioritised using in-silico prediction tools. Finally, causal variants were detected from 10 of 18 familial cases (55.5 %) and 7 of 16 simplex cases (43.7 %) in total. Novel variants were detected in 13 of 20 (65 %) candidate variants. Compound heterozygous variants were found in four of 7 simplex cases.

Conclusion

Panel-based targeted re-sequencing can be used as an effective molecular diagnostic tool for RP.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1723-x) contains supplementary material, which is available to authorized users.     

A Novel Multiplex Tetra-Primer ARMS-PCR for the Simultaneous Genotyping of Six Single Nucleotide Polymorphisms Associated with Female Cancers

Background

The tetra-primer amplification refractory mutation system PCR (T-ARMS-PCR) is a fast and economical means of assaying SNP''s, requiring only PCR amplification and subsequent electrophoresis for the determination of genotypes. To improve the throughput and efficiency of T-ARMS-PCR, we combined T-ARMS-PCR with a chimeric primer-based temperature switch PCR (TSP) strategy, and used capillary electrophoresis (CE) for amplicon separation and identification. We assessed this process in the simultaneous genotyping of four breast cancer–and two cervical cancer risk–related SNPs.

Methods

A total of 24 T-ARMS-PCR primers, each 5′-tagged with a universal sequence and a pair of universal primers, were pooled together to amplify the 12 target alleles of 6 SNPs in 186 control female blood samples. Direct sequencing of all samples was also performed to assess the accuracy of this method.

Results

Of the 186 samples, as many as 11 amplicons can be produced in one single PCR and separated by CE. Genotyping results of the multiplex T-ARMS-PCR were in complete agreement with direct sequencing of all samples.

Conclusions

This novel multiplex T-ARMS-PCR method is the first reported method allowing one to genotype six SNPs in a single reaction with no post-PCR treatment other than electrophoresis. This method is reliable, fast, and easy to perform.     

Supply of Neuraminidase Inhibitors Related to Reduced Influenza A (H1N1) Mortality during the 2009–2010 H1N1 Pandemic: An Ecological Study

Background

The influenza A (H1N1) pandemic swept across the globe from April 2009 to August 2010 affecting millions. Many WHO Member States relied on antiviral drugs, specifically neuraminidase inhibitors (NAIs) oseltamivir and zanamivir, to treat influenza patients in critical condition. Such drugs have been found to be effective in reducing severity and duration of influenza illness, and likely reduced morbidity during the pandemic. However, it is less clear whether NAIs used during the pandemic reduced H1N1 mortality.

Methods

Country-level data on supply of oseltamivir and zanamivir were used to predict H1N1 mortality (per 100,000 people) from July 2009 to August 2010 in forty-two WHO Member States. Poisson regression was used to model the association between NAI supply and H1N1 mortality, with adjustment for economic, demographic, and health-related confounders.

Results

After adjustment for potential confounders, each 10% increase in kilograms of oseltamivir, per 100,000 people, was associated with a 1.6% reduction in H1N1 mortality over the pandemic period (relative rate (RR) = 0.84 per log increase in oseltamivir supply). While the supply of zanamivir was considerably less than that of oseltamivir in each Member State, each 10% increase in kilogram of active zanamivir, per 100,000, was associated with a 0.3% reduction in H1N1 mortality (RR = 0.97 per log increase).

Conclusion

While there are limitations to the ecologic nature of these data, this analysis offers evidence of a protective relationship between antiviral drug supply and influenza mortality and supports a role for influenza antiviral use in future pandemics.     

Group-based variant calling leveraging next-generation supercomputing for large-scale whole-genome sequencing studies

Motivation

Next-generation sequencing (NGS) technologies have become much more efficient, allowing whole human genomes to be sequenced faster and cheaper than ever before. However, processing the raw sequence reads associated with NGS technologies requires care and sophistication in order to draw compelling inferences about phenotypic consequences of variation in human genomes. It has been shown that different approaches to variant calling from NGS data can lead to different conclusions. Ensuring appropriate accuracy and quality in variant calling can come at a computational cost.

Results

We describe our experience implementing and evaluating a group-based approach to calling variants on large numbers of whole human genomes. We explore the influence of many factors that may impact the accuracy and efficiency of group-based variant calling, including group size, the biogeographical backgrounds of the individuals who have been sequenced, and the computing environment used. We make efficient use of the Gordon supercomputer cluster at the San Diego Supercomputer Center by incorporating job-packing and parallelization considerations into our workflow while calling variants on 437 whole human genomes generated as part of large association study.

Conclusions

We ultimately find that our workflow resulted in high-quality variant calls in a computationally efficient manner. We argue that studies like ours should motivate further investigations combining hardware-oriented advances in computing systems with algorithmic developments to tackle emerging ‘big data’ problems in biomedical research brought on by the expansion of NGS technologies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0736-4) contains supplementary material, which is available to authorized users.     

Edge effects in calling variants from targeted amplicon sequencing

Background

Analysis of targeted amplicon sequencing data presents some unique challenges in comparison to the analysis of random fragment sequencing data. Whereas reads from randomly fragmented DNA have arbitrary start positions, the reads from amplicon sequencing have fixed start positions that coincide with the amplicon boundaries. As a result, any variants near the amplicon boundaries can cause misalignments of multiple reads that can ultimately lead to false-positive or false-negative variant calls.

Results

We show that amplicon boundaries are variant calling blind spots where the variant calls are highly inaccurate. We propose that an effective strategy to avoid these blind spots is to incorporate the primer bases in obtaining read alignments and post-processing of the alignments, thereby effectively moving these blind spots into the primer binding regions (which are not used for variant calling). Targeted sequencing data analysis pipelines can provide better variant calling accuracy when primer bases are retained and sequenced.

Conclusions

Read bases beyond the variant site are necessary for analysis of amplicon sequencing data. Enzymatic primer digestion, if used in the target enrichment process, should leave at least a few primer bases to ensure that these bases are available during data analysis. The primer bases should only be removed immediately before the variant calling step to ensure that the variants can be called irrespective of where they occur within the amplicon insert region.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1073) contains supplementary material, which is available to authorized users.     

A powerful tool for genome analysis in maize: development and evaluation of the high density 600 k SNP genotyping array

Background

High density genotyping data are indispensable for genomic analyses of complex traits in animal and crop species. Maize is one of the most important crop plants worldwide, however a high density SNP genotyping array for analysis of its large and highly dynamic genome was not available so far.

Results

We developed a high density maize SNP array composed of 616,201 variants (SNPs and small indels). Initially, 57 M variants were discovered by sequencing 30 representative temperate maize lines and then stringently filtered for sequence quality scores and predicted conversion performance on the array resulting in the selection of 1.2 M polymorphic variants assayed on two screening arrays. To identify high-confidence variants, 285 DNA samples from a broad genetic diversity panel of worldwide maize lines including the samples used for sequencing, important founder lines for European maize breeding, hybrids, and proprietary samples with European, US, semi-tropical, and tropical origin were used for experimental validation. We selected 616 k variants according to their performance during validation, support of genotype calls through sequencing data, and physical distribution for further analysis and for the design of the commercially available Affymetrix® Axiom® Maize Genotyping Array. This array is composed of 609,442 SNPs and 6,759 indels. Among these are 116,224 variants in coding regions and 45,655 SNPs of the Illumina® MaizeSNP50 BeadChip for study comparison. In a subset of 45,974 variants, apart from the target SNP additional off-target variants are detected, which show only a minor bias towards intermediate allele frequencies. We performed principal coordinate and admixture analyses to determine the ability of the array to detect and resolve population structure and investigated the extent of LD within a worldwide validation panel.

Conclusions

The high density Affymetrix® Axiom® Maize Genotyping Array is optimized for European and American temperate maize and was developed based on a diverse sample panel by applying stringent quality filter criteria to ensure its suitability for a broad range of applications. With 600 k variants it is the largest currently publically available genotyping array in crop species.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-823) contains supplementary material, which is available to authorized users.     

Distinguishing low frequency mutations from RT-PCR and sequence errors in viral deep sequencing data

Background

RNA viruses have high mutation rates and exist within their hosts as large, complex and heterogeneous populations, comprising a spectrum of related but non-identical genome sequences. Next generation sequencing is revolutionising the study of viral populations by enabling the ultra deep sequencing of their genomes, and the subsequent identification of the full spectrum of variants within the population. Identification of low frequency variants is important for our understanding of mutational dynamics, disease progression, immune pressure, and for the detection of drug resistant or pathogenic mutations. However, the current challenge is to accurately model the errors in the sequence data and distinguish real viral variants, particularly those that exist at low frequency, from errors introduced during sequencing and sample processing, which can both be substantial.

Results

We have created a novel set of laboratory control samples that are derived from a plasmid containing a full-length viral genome with extremely limited diversity in the starting population. One sample was sequenced without PCR amplification whilst the other samples were subjected to increasing amounts of RT and PCR amplification prior to ultra-deep sequencing. This enabled the level of error introduced by the RT and PCR processes to be assessed and minimum frequency thresholds to be set for true viral variant identification. We developed a genome-scale computational model of the sample processing and NGS calling process to gain a detailed understanding of the errors at each step, which predicted that RT and PCR errors are more likely to occur at some genomic sites than others. The model can also be used to investigate whether the number of observed mutations at a given site of interest is greater than would be expected from processing errors alone in any NGS data set. After providing basic sample processing information and the site’s coverage and quality scores, the model utilises the fitted RT-PCR error distributions to simulate the number of mutations that would be observed from processing errors alone.

Conclusions

These data sets and models provide an effective means of separating true viral mutations from those erroneously introduced during sample processing and sequencing.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1456-x) contains supplementary material, which is available to authorized users.     

Similar Prevalence of Low-Abundance Drug-Resistant Variants in Treatment-Naive Patients with Genotype 1a and 1b Hepatitis C Virus Infections as Determined by Ultradeep Pyrosequencing

Background and Objectives

Hepatitis C virus (HCV) variants that confer resistance to direct-acting-antiviral agents (DAA) have been detected by standard sequencing technology in genotype (G) 1 viruses from DAA-naive patients. It has recently been shown that virological response rates are higher and breakthrough rates are lower in G1b infected patients than in G1a infected patients treated with certain classes of HCV DAAs. It is not known whether this corresponds to a difference in the composition of G1a and G1b HCV quasispecies in regards to the proportion of naturally occurring DAA-resistant variants before treatment.

Methods

We used ultradeep pyrosequencing to determine the prevalence of low-abundance (<25% of the sequence reads) DAA-resistant variants in 191 NS3 and 116 NS5B isolates from 208 DAA-naive G1-infected patients.

Results

A total of 3.5 million high-quality reads of ≥200 nucleotides were generated. The median coverage depth was 4150x and 4470x per NS3 and NS5B amplicon, respectively. Both G1a and G1b populations showed Shannon entropy distributions, with no difference between G1a and G1b in NS3 or NS5B region at the nucleotide level. A higher number of substitutions that confer resistance to protease inhibitors were observed in G1a isolates (mainly at amino acid 80 of the NS3 region). The prevalence of amino acid substitutions that confer resistance to NS5B non-nucleoside inhibitors was similar in G1a and G1b isolates. The NS5B S282T variant, which confers resistance to the polymerase inhibitors mericitabine and sofosbuvir, was not detected in any sample.

Conclusion

The quasispecies genetic diversity and prevalence of DAA-resistant variants was similar in G1a and G1b isolates and in both NS3 and NS5B regions, suggesting that this is not a determinant for the higher level of DAA resistance observed across G1a HCV infected patients upon treatment.     

Accurate detection of subclonal single nucleotide variants in whole genome amplified and pooled cancer samples using HaloPlex target enrichment

Background

Target enrichment and resequencing is a widely used approach for identification of cancer genes and genetic variants associated with diseases. Although cost effective compared to whole genome sequencing, analysis of many samples constitutes a significant cost, which could be reduced by pooling samples before capture. Another limitation to the number of cancer samples that can be analyzed is often the amount of available tumor DNA. We evaluated the performance of whole genome amplified DNA and the power to detect subclonal somatic single nucleotide variants in non-indexed pools of cancer samples using the HaloPlex technology for target enrichment and next generation sequencing.

Results

We captured a set of 1528 putative somatic single nucleotide variants and germline SNPs, which were identified by whole genome sequencing, with the HaloPlex technology and sequenced to a depth of 792–1752. We found that the allele fractions of the analyzed variants are well preserved during whole genome amplification and that capture specificity or variant calling is not affected. We detected a large majority of the known single nucleotide variants present uniquely in one sample with allele fractions as low as 0.1 in non-indexed pools of up to ten samples. We also identified and experimentally validated six novel variants in the samples included in the pools.

Conclusion

Our work demonstrates that whole genome amplified DNA can be used for target enrichment equally well as genomic DNA and that accurate variant detection is possible in non-indexed pools of cancer samples. These findings show that analysis of a large number of samples is feasible at low cost, even when only small amounts of DNA is available, and thereby significantly increases the chances of indentifying recurrent mutations in cancer samples.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-14-856) contains supplementary material, which is available to authorized users.     

Virus genome dynamics under different propagation pressures: reconstruction of whole genome haplotypes of west nile viruses from NGS data

Background

Extensive focus is placed on the comparative analyses of consensus genotypes in the study of West Nile virus (WNV) emergence. Few studies account for genetic change in the underlying WNV quasispecies population variants. These variants are not discernable in the consensus genome at the time of emergence, and the maintenance of mutation-selection equilibria of population variants is greatly underestimated. The emergence of lineage 1 WNV strains has been studied extensively, but recent epidemics caused by lineage 2 WNV strains in Hungary, Austria, Greece and Italy emphasizes the increasing importance of this lineage to public health. In this study we explored the quasispecies dynamics of minority variants that contribute to cell-tropism and host determination, i.e. the ability to infect different cell types or cells from different species from Next Generation Sequencing (NGS) data of a historic lineage 2 WNV strain.

Results

Minority variants contributing to host cell membrane association persist in the viral population without contributing to the genetic change in the consensus genome. Minority variants are shown to maintain a stable mutation-selection equilibrium under positive selection, particularly in the capsid gene region.

Conclusions

This study is the first to infer positive selection and the persistence of WNV haplotype variants that contribute to viral fitness without accompanying genetic change in the consensus genotype, documented solely from NGS sequence data. The approach used in this study streamlines the experimental design seeking viral minority variants accurately from NGS data whilst minimizing the influence of associated sequence error.     

Reassortant between Human-Like H3N2 and Avian H5 Subtype Influenza A Viruses in Pigs: A Potential Public Health Risk

Background

Human-like H3N2 influenza viruses have repeatedly been transmitted to domestic pigs in different regions of the world, but it is still uncertain whether any of these variants could become established in pig populations. The fact that different subtypes of influenza viruses have been detected in pigs makes them an ideal candidate for the genesis of a possible reassortant virus with both human and avian origins. However, the determination of whether pigs can act as a “mixing vessel” for a possible future pandemic virus is still pending an answer. This prompted us to gather the epidemiological information and investigate the genetic evolution of swine influenza viruses in Jilin, China.

Methods

Nasopharyngeal swabs were collected from pigs with respiratory illness in Jilin province, China from July 2007 to October 2008. All samples were screened for influenza A viruses. Three H3N2 swine influenza virus isolates were analyzed genetically and phylogenetically.

Results

Influenza surveillance of pigs in Jilin province, China revealed that H3N2 influenza viruses were regularly detected from domestic pigs during 2007 to 2008. Phylogenetic analysis revealed that two distinguishable groups of H3N2 influenza viruses were present in pigs: the wholly contemporary human-like H3N2 viruses (represented by the Moscow/10/99-like sublineage) and double-reassortant viruses containing genes from contemporary human H3N2 viruses and avian H5 viruses, both co-circulating in pig populations.

Conclusions

The present study reports for the first time the coexistence of wholly human-like H3N2 viruses and double-reassortant viruses that have emerged in pigs in Jilin, China. It provides updated information on the role of pigs in interspecies transmission and genetic reassortment of influenza viruses.     

Specific Recognition of Influenza A/H1N1/2009 Antibodies in Human Serum: A Simple Virus-Free ELISA Method

Background

Although it has been estimated that pandemic Influenza A H1N1/2009 has infected millions of people from April to October 2009, a more precise figure requires a worldwide large-scale diagnosis of the presence of Influenza A/H1N1/2009 antibodies within the population. Assays typically used to estimate antibody titers (hemagglutination inhibition and microneutralization) would require the use of the virus, which would seriously limit broad implementation.

Methodology/Principal Findings

An ELISA method to evaluate the presence and relative concentration of specific Influenza A/H1N1/2009 antibodies in human serum samples is presented. The method is based on the use of a histidine-tagged recombinant fragment of the globular region of the hemagglutinin (HA) of the Influenza A H1N1/2009 virus expressed in E. coli.

Conclusions/Significance

The ELISA method consistently discerns between Inf A H1N1 infected and non-infected subjects, particularly after the third week of infection/exposure. Since it does not require the use of viral particles, it can be easily and quickly implemented in any basic laboratory. In addition, in a scenario of insufficient vaccine availability, the use of this ELISA could be useful to determine if a person has some level of specific antibodies against the virus and presumably at least partial protection.