ABSTRACT
African swine fever virus (ASFV) is the causative agent of a severe and highly contagious viral disease of pigs that poses serious economic consequences to the swine industry due to the high mortality rate and impact on international trade. There is no effective vaccine to control African swine fever (ASF), and therefore, efficient disease control is dependent on early detection and diagnosis of ASFV. The large size of the ASFV genome (∼180 kb) has historically hindered efforts to rapidly obtain a full-genome sequence. Rapid acquisition of data is critical for characterization of the isolate and to support epidemiological efforts. Here, we investigated the capacity of the Oxford Nanopore MinION sequence sensing device to act as a rapid sequencing tool. When coupled with our novel companion software script, the African swine fever fast analysis sequencing tool (ASF-FAST), the analysis of output data was performed in real time. Complete ASFV genome sequences were generated from cell culture isolates and blood samples obtained from experimentally infected pigs. Removal of the host-methylated DNA from the extracted nucleic acid facilitated rapid ASFV sequence identification, with reads specific to ASFV detected within 6 min after the initiation of sequencing. Regardless of the starting material, sufficient sequence was available for complete genome resolution (up to 100%) within 10 min. Overall, this paper highlights the use of Nanopore sequencing technology in combination with the ASF-FAST software for the purpose of rapid and real-time resolution of the full ASFV genome from a diagnostic sample.
INTRODUCTION
African swine fever (ASF) is a highly contagious viral disease of swine characterized by fever, hemorrhage, ataxia, and severe depression. This disease causes serious economic losses due to its high mortality rate (up to 100%) and rapid spread. The causative agent, African swine fever virus (ASFV), is the only member of the genus Asfivirus within the family Asfarviridae (1). It is a large enveloped virus containing a double-stranded DNA genome of approximately 170 to 193 kbp, flanked by inverted terminal repeats. The genome contains 150 to 167 genes, including those involved in viral replication and assembly and in the modulation of host cellular functions and immune evasion (2). There are 24 genotypes described, based on the sequencing of the p72 ASFV capsid protein gene (3–5).
ASFV is endemic in several sub-Saharan African countries and in Madagascar and Sardinia (Italy). Spain and Portugal experienced recurring outbreaks from 1960 to the 1990s but have been free of disease since 1995 and 1994, respectively. More recently in 2007, ASFV was introduced into the country of Georgia and from there spread through the Caucasus region, affecting Armenia, Azerbaijan, Russia, Ukraine, Belarus, Lithuania, Latvia, Poland, Estonia, Moldova, the Czech Republic, and Romania, where the virus continues to circulate (6–8). In 2018, three other European countries, Hungary, Bulgaria, and Belgium, reported the presence of ASFV. Concordantly, China reported the first outbreaks of the disease in 2018, which spread rapidly, presenting a severe threat to the global pork supply. In 2019, ASFV was reported in Mongolia in January and in Vietnam in February (2). Subsequently, the first report of ASFV detected in imported foodstuffs was described in Japan. Additionally, new or ongoing outbreaks were reported in Zimbabwe, South Africa, Cambodia, Vietnam (9), the Philippines (10), and South Korea (11). The increased number of infected countries poses a significant threat due to possible introduction of ASFV into countries free of disease via legal and illegal importation and trade of contaminated pork products and waste (8).
Currently, there is neither effective treatment nor a commercially available vaccine against ASFV (12, 13). Outbreaks are managed by animal quarantine and elimination of the affected animals, but this is economically devastating for the swine industry, and control may require industry-wide changes in the dynamics of swine production. Currently, ASF control and eradication measures are based on classical disease control methods, including surveillance, epidemiological investigation, tracing of pig movement, personnel contacts, and depopulation and disinfection of the affected premises. These control methods are complicated by viral shedding, which occurs prior to the onset of clinical signs, as well as other viral and bacterial infections presenting with similar clinical signs. These factors may slow initial detection of the virus, increasing the risk of ASFV establishing a foothold before sufficient control measures are properly implemented. As a result, disease control is dependent on early detection, coupled with strategic surveillance, for the best chance to control spread and limit the breadth of impact (7, 14–16).
Several authors have described the use of next-generation sequencing (NGS) and bioinformatics analysis for the detection and identification of ASFV from clinical samples isolated from outbreaks (17–20). However, NGS requires time- and resource-intensive protocols for sample and library preparation, with a significant capital investment in instrumentation. Following the extensive sample preparation protocol, most NGS platforms require a minimum of 17 h of instrument time to obtain the raw sequence data for subsequent processing and analysis.
The utility of Nanopore sequencing technology, and specifically, the MinION sequencer from Oxford Nanopore Technologies (ONT), was evaluated as a sequencing tool for the rapid detection and characterization of ASFV. The MinION sequence sensing device has several advantages for this purpose, as follows: it is available with a low initial investment, it performs long-read sequencing, it reads double-stranded DNA (dsDNA) with minimal modification, and it generates data in real time.
The MinION sequencer, coupled with our companion real-time analysis tool (the African swine fever fast analysis sequencing tool [ASF-FAST]), rapidly produced high-quality high-volume sequence data sufficient to detect and resolve the full ASFV genome from cell culture isolates, as well as whole-blood samples from experimentally infected pigs. In a subsequent experiment, viral nucleic acid enrichment was performed by removing the host-methylated DNA from the samples (21). Enrichment resulted in a modest improvement in the total percentage of ASFV-specific reads, decreasing the time required for initial virus detection and sequence resolution of the full genome.
This is the first report combining sample enrichment with MinION technology and our novel companion analysis software to allow for true real-time detection of the ASFV genome sequence. This work demonstrates the utility of this technology for sequence-based diagnostics, supporting effective emergency management in the event of an outbreak of the disease.
MATERIALS AND METHODS
Viruses.Four ASFV strains, Georgia, Killean III, Kimakia, and Dominican Republic (DR-2), grown in primary porcine macrophage cultures were used (Table 1). Viruses were provided by the U.S. Department of Agriculture, National Veterinary Services Laboratories’ Foreign Animal Disease Diagnostic Laboratory (USDA-NVSL-FADDL) in Plum Island, NY.
Summary of ASFV samples sequenced to evaluate the competency of the MinION device as a rapid characterization toola
Titrations.Virus titration of isolates obtained from cell culture and from the blood of infected animals was performed on primary swine macrophage cultures. Primary swine macrophage cultures were prepared from defibrinated swine blood, as described elsewhere (22). The presence of virus was determined by hemadsorption (HA), and virus titers were calculated using the Reed and Muench method (23).
Porcine blood samples from ASFV experimentally infected pigs.(i) Fresh blood samples. Blood samples (EDTA stabilized) were collected from a total of six pigs, three experimentally infected with ASFV Georgia (6 days postinoculation) and three infected with ASFV Lisbon (7 days postinoculation), and processed immediately following collection. Samples were provided by the Foreign Animal Disease Diagnosticians (FADD) School, USDA-NVSL-FADDL, in Plum Island, NY (Table 1).
(ii) Frozen blood samples. Blood samples (EDTA stabilized) were collected from three pigs experimentally infected with ASFV Georgia at 7 days postinoculation. After collection, samples were stored at −70°C until processing (Table 1).
ASFV real-time PCR.Detection of ASFV in all samples was performed using specific primers and probe to amplify the gene sequence encoding the major ASFV p72 capsid protein, as a modification of Zsak et al. (24). DNA was extracted using the MagMax pathogen RNA/DNA kit (Applied Biosystems). Each 25-μl reaction mixture contained 2.5 μl of nucleic acid template, 1.25 μl of primer-probe mix, 6.25 μl of enzyme mix, and 15 μl of nuclease-free water. Real-time PCR (r-PCR) was performed using a real-time PCR system (ABI7500). Cycling conditions consisted of denaturation at 95°C for 20 s (1 cycle), 45 cycles of amplification at 95°C for 10 s, and 60°C for 30 s in standard run mode. Samples with a threshold cycle (CT) value equal to or less than 40 were considered positive, which is consistent with the USDA testing algorithm for ASFV (25).
Extraction and enrichment of nucleic acid.Total genomic DNA was similarly extracted from all samples using the MagMax pathogen RNA/DNA kit (Applied Biosystems) on a 96-well, magnetic bead robotic platform (MagMax Express; Applied Biosystems). Duplicate extractions of nucleic acid from each sample were processed in parallel; one aliquot of each sample was quantified using the Qubit dsDNA high-sensitivity (HS) assay kit (Invitrogen) and used for library preparation, according to the manufacturer’s guidelines. Enrichment through subtractive hybridization of methylated genomic DNA was performed on the other aliquot, using the NEBNext microbiome DNA enrichment kit (New England BioLabs). Briefly, extracted DNA was combined with the MBD2-Fc protein-bound magnetic beads on a rotating mixer for 15 min at room temperature. After incubation, samples were spun down and placed on a magnetic rack for 5 min. The supernatant, which contained the enriched DNA, was removed; cleanup was performed using AMPure XP beads and eluted in 50 μl of resuspension buffer.
MinION library preparation and sequencing.Briefly, DNA from untreated and enriched samples was enzymatically tagged and barcoded using the rapid PCR barcoding kit (SQK-RPB004). Subsequently, libraries from the untreated and enriched samples were quantified, rapid sequencing adapters were added, and samples were loaded onto the primed MinION SpotON flow cell (R9.4.1 FLO-MIN 106; ONT). Samples were individually run or multiplexed (untreated/enriched), sequenced using the 48-h script as one-dimensional (1D) libraries, and managed using the MinKNOW software (ONT).
Bioinformatics analysis.Raw reads were produced with MinKNOW with base calling enabled and with a specific designated output folder. FASTQ output was selected for simple integration of raw data into downstream analysis software. Data were initially filtered by the MinKNOW software for quality and the output placed into a “passed” folder. Analysis was performed on the FASTQ-passed data for determination of total sequence reads versus ASFV-specific reads. Files were analyzed using our customized ASF-FAST companion analysis software and processed for sequence assembly and reporting of results in real time.
Statistical analysis.Enriched versus untreated samples were compared by paired Student's t test, with a P value of <0.05 considered the minimal threshold for statistical significance, where appropriate. Statistical testing for a paired Student t test was performed using Prism version 8.0.0 for Windows (GraphPad Software, San Diego, CA, USA). For ASF genomic % coverage, the standard error was calculated and plotted for each data acquisition point on the graphs and shown as error bars.
African swine fever fast analysis sequencing tool software.A custom analysis tool was developed specifically for real-time rapid processing of the output files (.fastq) generated by the MinION instrument during the sequencing process. The MinION instrument generated a file upon reaching a threshold of 4,000 raw reads of any length containing all untrimmed raw data that pass the quality filters. Our custom analysis tool monitored the designated output data folder for .fastq files from the MinION instrument and then automatically transferred any new sequencing file into a “Que” folder for processing. The file “creation time” was recorded into a data frame for maintaining a temporal reference point for the acquisition of data and for graphically plotting the results. After transfer of raw data to the Que folder, the raw data were separated into individual samples by barcode using the Porechop tool (https://github.com/rrwick/Porechop). Each of the individual resulting files was iteratively processed using a reference-guided assembly, the Burrows-Wheeler alignment (BWA) tool, with the selected ASFV reference genome (GenBank accession no. MH910495.1 for the ASFV 2008 Georgia strain) (26). The reference-guided assembly process produced a consensus assembly of the complete genome, showed unresolved regions as ambiguous bases (N), and a generated separate statistical summary describing the coverage, including the total number of reads, ASFV-specific reads, total nucleotide length of the expected genome, nucleotide length of the resolved/aligned region, the number of individual resolved nucleotide positions, and the genome % identity. The consensus sequence was then analyzed using a local BLASTN (ftp://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/LATEST/) search against the reference strain to generate a tabular alignment output showing the sequence fragments mapped to the reference genome. This was subsequently passed through the blast-imager tool, which is a publicly available Perl script (https://resources.oreilly.com/examples/9780596002992/blob/master/examples/blast-imager.pl), to generate a graphical representation of the alignment. All of the resulting data were compiled into an output report in a PDF format and transmitted upon request through an SMS-based interface for real-time access to genome assembly data (Fig. 1). The software, comprising two Python scripts (Python 3.6.5), was built using Anaconda and is freely available as a .yml file for importing. All scripts and related software to run the tool are publicly available at https://github.com/rwbarrette/ASFV_MinION_RapidAssembler and are licensed with the MIT license.
ASFV real-time analysis software tool. Flowchart showing the operation and data flow through the real-time analysis tool for processing raw sequencing data (.fastq) and the steps for result and report generation. Open-source tools used in the process of generating the output are shown in red, with arrows indicating where they are integrated into the overall process.
RESULTS
Time course rapid detection of cell culture-grown ASFV Georgia.The time required to detect ASFV sequence data using cell culture-grown ASFV Georgia stocks was measured. Three independent virus stocks of cell culture isolates of ASFV Georgia were analyzed as both untreated and enriched samples. Enriched samples demonstrated a clear improvement in the generation of ASFV sequence compared to the untreated samples (Fig. 2). In the enriched samples, 99% resolution of the genome occurred with the first output file of raw data. Conversely, for the untreated samples, only 42% of the ASFV sequence was resolved within the same time frame. The time required to produce full-genome sequence resolution from the enriched samples was faster than from the untreated samples. From the untreated samples, the system generated 99% of the full genome in 64 min. With the enriched samples, the system resolved 99% of the genome under 10 min. Total read counts varied by treatment group; an untreated sample provided 4,307 total reads, with 868 reads being specific to ASFV (20.15%). An enriched sample had significantly more total reads, numbering 54,743, with 23,208 of the reads being ASFV specific (42.39% of the total). This represents an improvement in ASFV-specific signal over the unenriched sample. A reduction in methylated host DNA and enrichment of viral DNA are critical to the performance of the MinION instrument as a sequencing tool. The removal of methylated host dsDNA appears to increase the virus-specific sequencing performance (Fig. 2). Additionally, the required library preparation kit generates sequenceable species from both host and viral dsDNA, which is relative to the virus-to-host nucleic acid ratio of each. Our data demonstrate that depletion of methylated DNA permits targeted analysis of target viral sequences, resulting in faster accumulation of viral sequence data and more efficient resolution of the full-genome sequence.
ASFV Georgia time course sequencing of cell culture-grown ASFV Georgia with MinION. Shown is the accumulation of ASFV reads over time for untreated and enriched samples of ASFV Georgia grown in primary porcine macrophage cultures. Three independent viral stocks were evaluated comparing the sequencing performance of untreated to enriched samples. The data were averaged and are plotted along with the standard error.
Detection and characterization of ASFV strains.To assess the feasibility of the MinION platform to be used for rapid characterization purposes for epidemiological appraisal, we next evaluated the capacity of ASF-FAST to map sequence data from genetically distinct ASFV isolates (Killean III, Kimakia, DR-2, and Georgia against the ASFV Georgia genome sequence that serves as the single reference strain). ASFV strains were obtained from the USDA-NVSL-FADDL as primary porcine macrophage cell culture-grown viral stocks, which were maintained in long-term storage at –70°C (Table 1). Each ASFV strain sample was analyzed in duplicate as untreated and enriched. Even using the Georgia reference strain for genome assembly, we are able to achieve sequence assemblies of at least 90% of the genome from other distinct ASFV strains. All enriched samples were resolved to >90% of the genome within 10 min from initiation of the run (Fig. 3A). Enrichment of viral DNA resulted in an improvement of ASFV-targeted sequencing libraries by increasing the ratio of ASFV-specific reads to the total reads for all ASFV isolates (Fig. 3B). Here, we have established that there is a significant improvement in ASFV-specific read bias (P < 0.05), regardless of the specific ASF isolate.
Capability of MinION device to detect ASFV variants. (A) Enriched libraries, prepared independently from four separate ASFV stock isolates, were individually loaded onto the primed MinION SpotON flow cell. Here, we show that all four variants achieved at least 90% genome resolution within 10 min. (B) Impact of enrichment on ratios of ASFV-specific sequencing reads compared to non-ASFV reads for different ASFV stock isolates.
Time course detection of ASFV from fresh blood samples.Infection with ASFV is associated with a high viral load in the blood (up to 107 to 109 50% hemadsorption dose [HAD50]/ml) (27). Therefore, we evaluated the capability of ASF-FAST to detect and resolve full-genome sequence from whole blood collected from experimentally infected pigs. For this experiment, six whole-blood-EDTA samples, three from pigs infected with ASFV Georgia and three from pigs infected with ASFV Lisbon, were immediately processed after collection (Table 1). After extraction, nucleic acids were enriched and individually sequenced onto a single primed MinION SpotON flow cell to determine how quickly the viral genome could be resolved in blood samples. As early as 11 min after sequence initiation, more than >40% of the ASFV Georgia genome was resolved. Within 200 min (3 h 20 min) of sequence initiation, the ASF-FAST obtained complete resolution of the ASFV Georgia genome from the enriched sample (Fig. 4). Sequence data from the enriched ASFV Lisbon had 92.7% genome coverage after 334 min (5 h 34 min) of sequencing (Fig. 4).
Time course evaluation of full-genome sequencing using freshly obtained whole-blood samples for two isolates of ASFV. Shown is the % genome coverage of the ASFV Georgia strain from fresh blood samples from three pigs inoculated with Georgia ASFV and % genome coverage of the ASFV Lisbon strain from fresh blood generated from three pigs inoculated with Lisbon ASFV isolate. Data are plotted with standard errors for all three samples for each of the two isolates.
Proficiency to detect ASFV in frozen blood samples.Frozen blood samples were evaluated due to the availability of historical samples for comparison to current outbreak-associated isolates. Enriched frozen blood samples from three pigs experimentally infected with ASFV Georgia were evaluated. Samples were taken at 7 days postinfection (dpi) and kept frozen at –70°C for over 5 months (Table 1). The enriched samples were individually loaded onto the primed flow cells. Two of the three samples chosen were resolved up to 86% within an hour of sequencing. The best-performing sample was fully resolved (100%) by 179 min (2 h 59 min), while the least ideal sample required 400 min (or 6 h 40 min) to achieve 97.9% genome resolution (Fig. 5).
Comparison of performance of ASFV-infected frozen whole-blood samples. Frozen whole-blood samples obtained from three pigs experimentally infected with ASFV Georgia were sequenced to evaluate performance after extended storage under –70°C conditions.
Comparison of rapid kit versus field kit.Oxford Nanopore has recently released the field sequencing kit (SQK-LRK001), which is designed for rapid sample preparation in a field scenario independent of a cold chain. Given that ASF outbreaks are occurring in regions of the world that may have limited access to proper laboratory facilities, this kit may be preferred for sample preparation in those situations. Here, we have compared it to the laboratory-oriented rapid library preparation kit using the enriched ASFV Georgia blood samples for comparison (Fig. 6). A total of three whole-blood samples were processed by extraction and enrichment in the same manner for both kits, with only substitution of the library preparation kits. In our hands, the field sequencing kit results in a sequencer-ready library within 15 min after nucleic acid extraction and enrichment. This is in comparison to the rapid library prep kit, which requires 2 h and 15 min from nucleic acid extraction and enrichment to generate a library ready for sequencing. However, the performance of the library obtained from the rapid kit is far superior to that from the field sequencing kit. The rapid kit generated a 100% resolved genome in under 3 h and 30 min, while the field kit failed to resolve more than 55% to 81% of the complete genome even after 7 h of sequencing. Overall, the rapid library kit uniformly performed better than did the field library kit. The data show that while complete coverage may not be obtainable under field conditions, at least half of the genome can be sequenced in a few hours using this kit.
Comparison of rapid library prep kit to field library prep kit. Sequence data acquisition rate differences were compared between the standard “lab-optimized” rapid library kit and the cold-chain optional field library preparation kit using three whole-blood-EDTA samples from pigs experimentally infected with ASFV Georgia.
DISCUSSION
The recent rapid spread of ASFV to Western Europe and throughout Asia emphasizes the need to develop faster diagnostic tests capable of early detection and real-time characterization of the circulating viruses. The optimization of diagnostic methods, which can be broadly applied, will be critical in the event of an outbreak for limiting economic losses and ensuring adequate intervention of disease control measures. Previous studies have examined the use of NGS and bioinformatics analysis for the detection and identification of ASFV from clinical samples isolated from various outbreaks (17–20). Most modern NGS instruments require significant capital investment. Additionally, the processing of the samples for standard NGS after arrival at the laboratory requires time- and resource-intensive laboratory preparations. Widely used protocols require a 17-h processing time on commercial sequencers, delaying the start of critical analyses and interpretation.
In this study, we evaluated the use of Nanopore technology, the MinION device, coupled with ASF-FAST, a companion analysis script generated at the FADDL, to identify and characterize ASFV in real time. By using the MinION technology with a rapid sequencing kit, and in combination with an enrichment treatment and automated analysis, we successfully identified sequence reads specific to ASFV as early as 6 min after the initiation of sequencing, with a full-genome sequence from multiple ASFV cell culture-grown strains and whole blood obtained in about 4 h. While analysis represents a minimal portion of the time required to generate the final results, it can vary depending on the amount of data. Nanopore data analysis can be somewhat variable and can be impacted by whether the user is relying on cloud-based analysis and the type of computing resources that are being leveraged for the analysis (Fig. 7).
Comparison of different ASFV characterization/diagnostic method process timelines. The total time from the beginning of sample preparation to the earliest possible time point for acquisition of actionable results is illustrated. Seq, sequencing.
One of the greatest advantages of the Oxford Nanopore MinION platform is the ability to generate data in real time, thus facilitating the rapid analysis that is critical during an investigation of high-consequence pathogens such as ASFV. While it may be valuable for other DNA viruses using these methods, here, we only consider ASFV as a target pathogen. Another advantage of the MinION platform over other systems is the capability for rapid sample preparation. In our hands, libraries were ready to load into the primed flow cell within 2 h and 15 min following nucleic acid extraction and enrichment. Since PCR is faster and less expensive to perform, it remains the test of choice for screening samples. However, sequencing has the advantage of providing enhanced data and the ability to detect variants or sequences that may not be reactive by PCR testing.
Another advantage of the system described herein is the improvement of ASFV-targeted sequencing libraries by increasing the number of ASFV-specific reads in relation to the total reads. This is accomplished using a methylated DNA enrichment kit to specifically reduce the host DNA while leaving the unmethylated ASF viral DNA (28) intact within the sample extract (21). This has the effect of rapidly generating ASFV genomic data due to the modest shift in the ratio of virus to host nucleic acid. This method also utilizes the near-real-time data processing and data generation associated with Oxford Nanopore platforms and their ability to rapidly produce FASTQ files with raw sequence data. This is a valuable improvement over many other sequencing platforms, as high-quality samples that have been successfully enriched can generate actionable raw data representing up to 100% of the ASFV Georgia genome in under 10 min from the initiation of sequencing. This, coupled with our companion analysis software (ASF-FAST) that monitors the data output folders, allows for rapid sequence assembly and characterization of the ASFV genome in a diagnostic setting.
Whole-blood-EDTA samples are commonly used as a reference sample for the diagnosis of ASFV (29). While we evaluated both EDTA- and heparin-treated blood samples (data not shown), we did not find significant differences in outcome and cannot make a clear recommendation for either for sample submission of ASFV where NGS is the goal.
We demonstrated that enrichment of samples, using the methylated kit, is particularly critical for use in the Oxford Nanopore platform, as the sequence sensing device is sensitive to the reduced sample quality, resulting in a lower total output for all samples included in the run. Enrichment treatment is effective at improving ASFV sequencing by improving the ratio of ASFV-specific reads to the total reads. We have also observed, along with others, that performing subtractive hybridization of methylated DNA appears to improve sequencing performance in general (30). The measured ratio of ASFV reads to the total reads usually resulted in roughly a doubling of ASFV-specific reads. Although the overall percentage of ASFV-specific sequences was relatively low, there was a clear improvement with enrichment for both fresh and frozen blood samples, as well as with virus grown on cell culture.
The decision to multiplex samples must be weighed against the expected quality of the sample, as the total throughput of high-quality samples is impacted by the presence of low-quality samples. For the purpose of rapid sequence-based characterization, multiplexing of samples may be sufficient to characterize the ASFV strain phylogenetically, but it becomes less likely that the full genome will be completely resolved, as there may be a substantial delay for sequence resolution as more samples are included on the flow cell (data not shown). Sequencing, like PCR, is susceptible to sample quality issues, including overall sample condition, presence or absence of inhibitors, and initial concentration of virus in the sample. The fact that we were able to see high-quality sequence results from whole blood, which is the sample of choice for diagnostics for this disease, indicates that this procedure meets the “fit-for-purpose” criteria.
One valuable aspect of the MinION sequencer is its portability and the potential applications for field-based analysis. This has led to the development of the field sequencing kit (ONT), which has the dual advantages of (i) not requiring a cold chain due to lyophilization, and (ii) more rapid processing times than with other available library preparation kits. We found that library preparation was more rapid with the field sequencing kit, requiring only 15 min to generate the libraries after nucleic acid extraction and enrichment. However, the performance of the MinION sequencer with a sample prepared with the field sequencing kit demonstrated longer delays for sequence generation, with increased latency between available data files. Additionally, sequence data could not be fully resolved from samples processed with the field sequencing kit, in contrast to the rapid library prep kit. Nevertheless, use of the field sequencing kit as a simple library preparation kit, along with the MinION system as a portable real-time sequencer, could be employed in the event of high suspicion of disease and when laboratory facilities or infrastructure are not available. Although the field kit will not provide the same degree of comprehensive genome coverage, the kit allows the user to obtain a result in a short time in relation to when the sample is obtained.
We show that the Nanopore technology is an important tool that may be leveraged for rapid surveillance in many locations and regions around the world at significant risk for ASFV. The MinION sequencer is accessible to most laboratories at a reduced initial capital investment. The platform can be used in regions that are performing testing, in laboratories without a sophisticated infrastructure, and in the field. As such, other laboratories may be able to rapidly expand their capability to leverage sequence-based characterization of ASFV.
In conclusion, we have developed a fast and reliable methodology for sequencing ASFV in real time, which along with our ASF-FAST companion software allows acquisition of data in minutes. This is essential for effective emergency management in the event of a disease outbreak and leads to a reduction in economic losses and faster intervention for disease control.
ACKNOWLEDGMENTS
We thank Fawzi Mohammed for providing frozen blood samples. We thank Elizabeth Fernandez for providing fresh blood samples from the FADD School, and Philip Doucette and Brian Sites for animal handling and sample collection. We also thank Doug Gladue and Manuel Borca for providing primary swine macrophage culture plates and flow cells.
This project was funded by the USDA Animal and Plant Health Inspection Service through the Foreign Animal Disease Diagnostic Laboratory.
FOOTNOTES
- Received 9 July 2019.
- Returned for modification 27 July 2019.
- Accepted 26 October 2019.
- Accepted manuscript posted online 6 November 2019.
This is a work of the U.S. Government and is not subject to copyright protection in the United States. Foreign copyrights may apply.
