Fifty-seven years ago the drug Enovid was approved for use as a female contraceptive in the USA, and most other developed nations quickly introduced similar formulations. Although this method of contraception has had enormous social impacts, allowing modern women greater access to higher education and remunerative employment, it has largely shifted the previously shared responsibility for family planning to women. Globally female hormonal methods and female sterilization are the most frequent family planning strategies adopted, and women now bear most of the financial and health-related burdens of contraception. But have the many studies over half a century linked use of ‘the pill’ and female sterilization with adverse health effects?
It has been clearly demonstrated that hormonal contraceptives have an impact on periodontal health: there is a significant increase in the prevalence of severe periodontitis and sub-gingival Candida infections in pill users. And women perceived as high risk for cardiovascular disease or breast cancer have been advised to use another form of contraception. However, although there is a plethora of anecdotal evidence concerning the pill’s association with depression and reduced libido, studies did not adequately address this problem until a nationwide prospective cohort study of over a million women living in Denmark was carried out. Recently published results reported that use of hormonal contraception was associated with a first diagnosis of depression and antidepressant use, particularly amongst very young women.
Although sterilization is applicable to both genders, globally over 80% of such procedures are carried out on women. Yet male vasectomy is simple and straightforward and, according to the UK National Health Service, is 20 times less likely to have postoperative complications and 30 times less likely to fail than the more invasive female tubal occlusion. However, in EU countries where vasectomy had become a common family planning choice, the number of couples now relying on this method has decreased in recent years. The reason could well be that as relationship break-ups become more common, men realize that a potential new partner may want children – vasectomy reversal is technically challenging and usually unsuccessful – whereas sterilized women are normally content with the family they have.
A technical solution is on the horizon, however, namely Vasalgel. This non-hormonal polymer blocks sperm flow when injected into the vas deferens, and can be flushed out again if desired. A recent trial with male rhesus monkeys demonstrated its safety and efficacy, and clinical trials have now begun. But its success depends on family planning once again becoming a shared responsibility.
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Next-generation sequencing (NGS) is a new technology that can be used for broad detection of infectious pathogens and is rapidly becoming an essential platform in clinical laboratories. This review explores the feasibility and potential for the application of NGS in clinical and public health laboratories in terms of pathogenic virus detection and diagnostics.
by Dr Jayme Parker and Prof. Jack Chen
Introduction
Methodologies to detect pathogenic viruses in clinical specimens have transitioned from classic cell culture and antibody–antigen techniques to more sensitive molecular methods such as polymerase chain reaction (PCR). The targeted nature of these methodologies inhibits their ability to accommodate the true diversity of human pathogens in a clinical specimen, especially viruses [1]. Next-generation sequencing (NGS) technologies are quickly demonstrating their ability to provide broad detection of infectious agents in a target-independent manner [2–7]. NGS has many advantages beyond the improved detection of all suspected, unsuspected, or even novel pathogens in a clinical specimen [8]. Familiarization with pathogen genomic sequences within clinical specimens enhances our understanding of infectious disease through further discovery of pathogen variability and genotyping [9–11], drug resistance or response to therapy [12], vaccine development and efficacy monitoring [13], and further characterization of the metagenome [14]. The use of NGS for routine use in clinical diagnostics is emerging with its own set of limitations and challenges [13, 15]. Focusing on viruses of public health importance, we compared the performance of NGS alongside other more common viral detection methodologies.
Conventional methods versus NGS
We investigated applications of NGS in a clinical laboratory to detect pathogenic viruses in common specimen types and compared NGS data to that which could be obtained by more conventional methods for detecting and characterizing the following viruses of public health importance: adenovirus, herpesvirus, hepatitis C virus, and influenza [16]. We compared results obtained by NGS to viral culture, immunofluorescence staining, serum neutralization, and PCR in terms of turnaround time as well as the clinical relevance of the information obtained.
Table 1 describes the turnaround time of conventional methods to NGS for detecting adenoviruses and herpesviruses, both DNA viruses. The amount of time it takes to grow a virus in culture is variable, ranging from 1 day for herpes simplex viruses to 18 days for adenoviruses. All NGS data could be obtained in 4 days, which includes nucleic acid extraction, sequencing library preparation, sequencing and data analysis. Although most laboratories are not currently equipped with in-house bioinformaticians, much of the analysis can be done simply using common sequencing analysing software and the quickly growing number of applications online. For data analysis, we used PathSeq™Virome which enabled us to feed large read files into the application which would generate a report describing the viruses present, including a ‘detection score’ to distinguish strong and weak presence. NGS data provided much more information regarding the exact isolate which may aid health professionals in tracking and relating individual cases with others. Group C adenoviruses are treatable with cidofovir and NGS data was able to identify the amino acid motif that most affects antiviral resistance.
Hepatitis C virus (HCV) is a growing concern for public health and tends to be difficult to design targeted methodologies around owing to the high variability of viral genomes known, even within the same patient. NGS is a powerful tool for characterizing HCV infections and, in our experience, more informational than targeted genotyping assays (Table 2). As we were able to sequence nearly the entire HCV genome (coverage ranged from 92.4–95.6%), data could be generated describing the mutations at key locations across the genomes that are known to cause drug resistance. Antiviral resistance is also critical when characterizing current circulating influenza virus strains and NGS was able to identify viruses that would be considered susceptible to neuraminidase inhibitors (Table 3). In two cases, the viral load of the specimen was too low to achieve good genome coverage across the neuraminidase gene, but this issue could be resolved by screening specimens for high titre (i.e. qPCR) or using enrichment techniques such as ultracentrifugation or filtration of other background nucleic acid.
In most cases, with the exception of one specimen where no cytomegalovirus was definitively identified (HSV5, Table 1), information retrieved by NGS met or exceeded that of conventional methodologies. NGS proves to be a laboratory tool capable of not only detecting pathogenic viruses in clinical specimens, but also predicting the effects of drug treatment as well.
Summary
Through increased use of NGS technologies, reference databases of whole genome sequences can grow and enhance our ability to more definitively identify sequencing reads. Although this review describes conventional methods versus NGS for detecting specific viruses, there was also evidence of the presence of co-infecting viruses such as hepatitis G and Torque Teno virus that weren’t originally targeted. The standard 4-day turnaround time needed to complete NGS could be improved with extraction and library preparation automation, as well as advances in sequencing technology (each run ~40 hours). Based on our laboratory’s experience and the growing body of literature, NGS will change our approach as clinical laboratorians and improve our ability to detect and more fully characterize agents of infectious disease in clinical specimens in a non-targeted manner.
References
1. Köser CU, Ellington MJ, Cartwright EJ, Gillespie SH, Brown NM, Farrington M, Holden MT, Dougan G, Bentley SD, Parkhill J, Peacock SJ. Routine use of microbial whole genome sequencing in diagnostic and public health microbiology. PLoS Pathogens 2012; 8(8): e1002824.
2. Bzhalava D, Johansson H, Ekström J, Faust H, Möller B, Eklund C, Nordin P, Stenquist B, Paoli J, Persson B, Forslund O, Dillner J. Unbiased approach for virus detection in skin lesions. PLoS One 2013; 8(6): e65953.
3. Cheval J, Sauvage V, Frangeul L, Dacheux L, Guigon G, Dumey N, Pariente K, Rousseaux C, Dorange F, Berthet N, Brisse S, Moszer I, Bourhy H, Manuguerra CJ, Lecuit M, Burguiere A, Caro V, Eloit M. Evaluation of high-throughput sequencing for identifying known and unknown viruses in biological samples. J Clin Microbiol 2011; 49(9): 3268–3275.
4. Chan BK, Wilson T, Fischer KF, Kriesel JD. Deep sequencing to identify the causes of viral encephalitis. PLoS One 2014; 9(4): e93993.
5. Kriesel JD, Hobbs MR, Jones BB, Milash B, Nagra RM, Fischer KF. Deep sequencing for the detection of virus-like sequences in the brains of patients with multiple sclerosis: detection of GBV-C in human brain. PLoS One 2012; 7(3): e31886.
6. Moore RA, Warren RL, Freeman JD, Gustavsen JA, Chénard C, Friedman JM, Suttle CA, Zhao Y, Holt RA. The sensitivity of massively parallel sequencing for detecting candidate infectious agents associated with human tissue. PLoS One 2011; 6(5): e19838.
7. Yozwiak NL, Skewes-Cox P, Stenglein MD, Balmaseda A, Harris E, DeRisi JL. Virus identification in unknown tropical febrile illness cases using deep sequencing. PLoS Negl Trop Dis 2012; 6(2): e1485.
8. Radford AD, Chapman D, Dixon L, Chantrey J, Darby AC, Hall N. Application of next-generation sequencing technologies in virology. J Gen Virol 2012; 93(9): 1853–1868.
9. Arroyo LS, Smelov V, Bzhalava D, Eklund C, Hultin E, Dillner J. Next generation sequencing for human papillomavirus genotyping. J Clin Virol 2013: 58(2): 437–442.
10. Flaherty P, Natsoulis G, Muralidharan O, Winters M, Buenrostro J, Bell J, Brown S, Holodniy M, Zhang N, Ji HP. Ultrasensitive detection of rare mutations using next-generation targeted resequencing. Nucleic Acids Res 2012; 40(1): e2.
11. Meiring TL, Salimo AT, Coetzee B, Maree HJ, Moodley J, Hitzeroth II, Freeborough M-J, Rybicki EP, Williamson AL. Next-generation sequencing of cervical DNA detects human papillomavirus types not detected by commercial kits. Virol J 2012; 9: 164.
12. Sijmons S, Van Ranst M, Maes P. Genomic and functional characteristics of human cytomegalovirus revealed by next-generation sequencing. Viruses 2014; 6(3): 1049–1072.
13. Watson SJ, Welkers MRA, DePledge DP, Coulter E, Breuer JM, de Jong MD, Kellam P. Viral population analysis and minority-variant detection using short read next-generation sequencing. Philos Trans R Soc Lond B Biol Sci 2013; 368(1614): 20120205.
14. Han Y, Zhang Y, Mei Y, Wang Y, Liu T, Guan Y, Tan D, Liang Y, Yang L, Yi X. Analysis of hepatitis B virus genotyping and drug resistance gene mutations based on massively parallel sequencing. J Virol Methods 2013; 193(2): 341–347.
15. Messiaen P, Verhofstede C, Vandenbroucke I, Dinakis S, Van Eygen V, Thys K, Winters B, Aerssens J, Vogelaers D, Stuyver LJ, Vandekerckhove L. Ultra-deep sequencing of HIV-1 reverse transcriptase before start of an NNRTI-based regimen in treatment-naive patients. Virology 2012; 426(1): 7–11.
16. Parker J, Chen J. Application of next generation sequencing for the detection of human viral pathogens in clinical specimens. J Clin Virol 2017; 86: 20–26.
The authors Jayme Parker1,2 PhD and Jack Chen*1,2 PhD 1Department of Biology and Wildlife, Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK 99775, USA 2Alaska State Public Health Virology Laboratory, Fairbanks, AK 99775, USA
*Corresponding author E-mail: j.chen@alaska.edu
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Current molecular diagnostics of pathogens using traditional typing methods gives limited information for outbreak investigation. Next-generation sequencing determines the DNA sequence of a complete genome and reveals information on resistance and virulence. Furthermore, it allows typing with a higher discriminatory power, which is essential for outbreak and transmission investigations.
by S. Rosema, Dr R. H. Deurenberg, Dr M. A. Chlebowicz, Dr S. García-Cobos, Dr A. C. M. Veloo, Prof. Dr A. W. Friedrich and Dr J. W. A. Rossen
Introduction
The correct identification and characterization of pathogens is essential for the successful treatment of infections and safety of patients. However, not every pathogen can be successfully cultured and the available molecular tests, mainly focusing on specific pathogens, are inadequate to detect novel genetic features in emerging pathogens. Undetected pathogens can spread easily through a hospital, resulting in a possible outbreak and putting patients admitted to hospitals at a higher risk for infections.
In recent decades, molecular diagnostic tests have improved rapidly and their role in clinical microbiology laboratories became progressively more important [1]. The turnaround time from receiving a sample to the final diagnostic result has been drastically reduced. Molecular methods, such as real-time polymerase chain reaction (PCR), Sanger sequencing and next-generation sequencing (NGS), make it possible to detect non-culturable micro-organisms. Nevertheless, some of these technologies, such as real-time PCR, require knowledge of the genomes of the micro-organisms. In addition, bioinformatics expertise is often needed to interpret the results.
This paper addresses the use of Sanger sequencing and whole genome sequencing (WGS) in the clinical microbiology laboratory for the characterization of pathogens and outbreak management, as it is used in the University Medical Center Groningen (UMCG), one of the largest university hospitals in The Netherlands. The clinical microbiology laboratory at the UMCG receives around 5750 samples per year for detailed molecular analysis, of which approximately 1500 samples are analysed by NGS [2].
Sanger sequencing
Sanger sequencing is used to answer different molecular questions, such as the identification of bacteria and fungi in patient material or pure cultures, and the identification of mutations in specific genomic regions of interest in bacteria or viruses. In general, Sanger sequencing is used to investigate a short DNA sequence (± 500 bp) after amplification of the region of interest by PCR. After amplification, two different sequence reactions (forward and reverse) are performed and can be used to identify bacterial or fungal species based on the analyses of the sequenced 16S ribosomal DNA (rDNA) and 18S rDNA of the internal transcribed spacer (ITS) region, respectively [2].
One of the disadvantages of Sanger sequencing is that species identification in clinical materials containing more than one species is difficult, if not impossible. Furthermore, the costs and the labour needed for investigating multiple genomic regions of interest makes this method of limited use in modern clinical microbiology laboratories.
Next-generation sequencing (NGS)
NGS determines the whole genome sequence of different pathogens in one single sequencing run. This technology allows sample multiplexing and, thus, simultaneously provides genomic sequence information on diverse pathogens isolated from different patients. NGS also allows determination of microbial genomes in complex multi-species patient samples by shotgun metagenomics (third generation sequencing) [3]. In comparison to Sanger sequencing, NGS is a considerable improvement owing to the usage of one protocol for all pathogens [4]. A schematic overview of the general workflow used for the sequence analysis in the UMCG is shown in Figure 1.
Using NGS, the whole genome of a pathogen is sequenced in a random way. As benchtop next-generation sequencers can sequence DNA fragments between 100 and 1000 bases, the genome is fragmented before sequencing [5, 6]. Third generation sequencers are an exception to this, as they can handle larger fragments of over 200 kb [2]. NGS requires the preparation of libraries, in which fragments of DNA or RNA are linked to adapters and barcodes. At a later stage, this enables the identification of the sequenced fragments (reads) to the pathogens. After fragmentation, clonal amplification, normalization and a sequencing run is performed. For this, a robust preparation of libraries and standardized protocols are key [3].
Software for data analysis
A huge challenge for the introduction of NGS in a clinical setting is the data analysis. This requires specific software as well as scientific knowledge to interpret the results. There are, so far, only a few user-friendly software packages available to perform data analyses with little bioinformatics knowledge. However, the costs of these software packages is relatively high. However, there a numerous freely available software packages to answer different scientific questions, but knowledge of bioinformatics is often required [2].
After high-throughput sequencing, the reads can be assembled, either by mapping or de novo assembly [2]. Software packages, such as CLC Genomics Workbench (Qiagen), SPAdes and Velvet, can be used for assembly. The genetic relatedness between isolates can be investigated using a gene-by-gene approach using multi-locus sequence typing (MLST), core genome MLST (cgMLST) or whole genome MLST (wgMLST) using SeqSphere+ (Ridom), Bionummerics (Biomérieux), or online tools, such as Enterobase (https://enterobase.warwick.ac.uk) and BIGSdb (http://bigsdb.readthedocs.io). Currently, it is still a matter of debate how many alleles two genomes may differ by to call them genetically related. The same problem applies for comparing two genomes by single nucleotide polymorphism (SNP) typing.
There are a number of web-based tools to perform additional NGS analysis [2]. One of them is the website of the Centre for Genomic Epidemiology (www.genomicepidemiology.org) that can be used for the detection of resistance and virulence genes. Another web-based tool is the Rapid Annotation using Subsystem Technology (RAST) website (http://rast.nmpdr.org) for annotating bacterial genomes.
One of the advantages of web-based tools is that, in general, no knowledge of bioinformatics is necessary. However, a disadvantage may be the lack of tweaking the software settings while performing the analysis. In addition, it may be necessary to confirm the results obtained through web-based tools using other methods [2].
NGS in clinical microbiology
NGS is already applied in several medical microbiology laboratories where it is used for outbreak management, molecular case findings, characterization and surveillance of pathogens, for example [2].
Indeed NGS can be extremely useful in outbreak detection, by monitoring the evolution and dynamics of multi-drug resistant pathogens [7]. A number of studies have highlighted the effectiveness of WGS-based typing for assessing of (newly) emerging pathogens. In our hospital, NGS was used for the characterization of a newly emerging CTX-M-15 producing Klebsiella pneumoniae clone [8]. Transmission of this K. pneumoniae strain between patients has been traced using genomic phylogenetic analysis (Fig. 2). In addition, the study showed the usefulness of a unique marker PCR, in which a clone-specific PCR was developed to investigate the transmission between patients [4].
In addition to tracing and characterizing outbreaks, NGS can be used for the implementation of control measures to avoid the spread of resistance bacteria [9]. An outbreak of a colistin-resistant carbapenemase-producing K. pneumoniae (KPC) with inter-institutional spread in The Netherlands was identified and characterized using NGS and, partially based on these findings, controlled by transferring all positive patients to a separate location [9].
Furthermore, NGS data stored in databases can be used to search retrospectively for molecular case studies. A study from Bathoorn et al. showed that a New Delhi Metallo-?-lactamas-5 (NDM-5)-producing K. pneumoniae was isolated from a Dutch patient. Molecular case findings showed that the Dutch strain is clonally related to strains isolated from four Danish patients in 2014. There was no obvious epidemiological link between the cases in the Dutch and Danish hospitals [10].
These studies and many others highlight the importance of NGS in clinical microbiology. NGS can be used either as a highly discriminatory tool to discriminate between bacterial clones with specific features and to use the information for patient management, infection prevention and evolutionary studies [2] or to characterize bacterial isolates in more detail [8]. Furthermore, web-based databases can be in silico screened retrospectively for the presence of novel (antibiotic-resistance) genes.
Conclusion and outlook
Using NGS, one laboratory protocol can be used to generate sequencing data from samples obtained from different sources. After data analysis, information on the presence of virulence factors and antibiotic resistance genes, as well as other relevant genes are obtained. In addition, NGS makes it possible to standardize typing methods, although cut-off values regarding cgMLST, wgMLST and SNP analysis have to be established internationally in order to distinguish related or unrelated isolates and being able to compare results between laboratories. In the next few years, the role of NGS will surely increase in medical microbiology laboratories, both for research as well as for molecular diagnostic purposes, infection prevention and molecular-epidemiological investigations.
Nonetheless, improvement of the NGS workflow is still needed, focusing on easier and faster ways of library preparation, shorter run-times and further reduction in costs. Furthermore, automatic pipelines for data analyses and easy to use software have to be developed. In addition, the development of proficiency testing panels are important for external quality controls. Only with implementation of the above items at local, (inter)regional and international level will broad use of NGS be allowed in clinical microbiological laboratories for patient and infection control management, including defining a tailor-made antibiotic therapy for each patient, leading to personalized microbiology.
Acknowledgement
A full version of this work is published in the review ‘Application of next generation sequencing in clinical microbiology and infection prevention’, Journal of biotechnology 2017; 243: 16–24.
References
1. Buchan BW, Ledeboer NA. Emerging technologies for the clinical microbiology laboratory. Clin Microbiol Rev 2014; 27(4): 783–822.
2. Deurenberg RH, Bathoorn E, Chlebowicz MA, Couto N, Ferdous M, Garcia-Cobos S, Kooistra-Smid AM, Raangs EC, Rosema S, Veloo AC, Zhou K, Friedrich AW, Rossen JW. Application of next generation sequencing in clinical microbiology and infection prevention. J Biotechnol 2017; 243: 16–24.
3. Head SR, Komori HK, LaMere SA, Whisenant T, Van Nieuwerburgh F, Salomon DR, Ordoukhanian P. Library construction for next-generation sequencing: overviews and challenges. Biotechniques 2014; 56(2): 61–64, 6, 8, passim.
4. Zhou K, Lokate M, Deurenberg RH, Tepper M, Arends JP, Raangs EG, Lo-Ten-Foe J, Grundmann H, Rossen JW, Friedrich AW. Use of whole-genome sequencing to trace, control and characterize the regional expansion of extended-spectrum beta-lactamase producing ST15 Klebsiella pneumoniae. Sci Rep 2016; 6: 20840.
5. Junemann S, Sedlazeck FJ, Prior K, Albersmeier A, John U, Kalinowski J, Mellmann A, Goesmann A, von Haeseler A, Stoye J, Harmsen D. Updating benchtop sequencing performance comparison. Nat Biotechnol 2013; 31(4): 294–296.
6. Loman NJ, Misra RV, Dallman TJ, Constantinidou C, Gharbia SE, Wain J, Pallen MJ. Performance comparison of benchtop high-throughput sequencing platforms. Nat Biotechnol 2012; 30(5): 434–439.
7. ECDC. Expert opinion on whole genome sequencing for public health surveillance. 2016.
8. Zhou K, Lokate M, Deurenberg RH, Arends J, Lo-Ten Foe J, Grundmann H, Rossen JW, Friedrich AW. Characterization of a CTX-M-15 producing Klebsiella pneumoniae outbreak strain assigned to a novel sequence type (1427). Front Microbiol 2015; 6: 1250.
9. Weterings V, Zhou K, Rossen JW, van Stenis D, Thewessen E, Kluytmans J, Veenemans J. An outbreak of colistin-resistant Klebsiella pneumoniae carbapenemase-producing Klebsiella pneumoniae in the Netherlands (July to December 2013), with inter-institutional spread. Eur J Clin Microbiol Infect Dis 2015; 34(8): 1647–1655.
10. Bathoorn E, Rossen JW, Lokate M, Friedrich AW, Hammerum AM. Isolation of an NDM-5-producing ST16 Klebsiella pneumoniae from a Dutch patient without travel history abroad, August 2015. Euro Surveill 2015; 20(41).
The authors Sigrid Rosema BSc; Ruud H. Deurenberg PhD; Monica A. Chlebowicz PhD; Silvia García-Cobos PhD; Alida C. M. Veloo PhD; Alexander W. Friedrich MD, PhD; John W. A. Rossen PhD, MMM Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, The Netherlands
*Corresponding author E-mail: j.w.a.rossen@rug.nl
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Viral diagnostic methods have evolved greatly in recent decades, with perhaps the most significant change being the widespread use of nucleic acid amplification tests (NAAT). The introduction of next-generation sequencing methods may see a further change in the landscape of infection diagnostics. Here we discuss some of the potential benefits and challenges with this approach.
by Dr Fiona Thorburn
Background
The term ‘acute respiratory tract infection’ (ARTI) encompasses a spectrum of conditions ranging from the common cold to pneumonia. Multiple organisms may infect the human respiratory tract, such as bacteria and fungi, but the majority of episodes are thought to be viral in origin [1]. The diagnosis of ARTI is made clinically but the lack of pathognomonic features means etiology cannot be determined clinically. Identifying causative organisms is challenging owing to the number of possibilities but is important for many reasons. In severe cases identification of an organism will guide therapeutics, although specific treatments for viral ARTI are generally limited to influenza. At the other end of the clinical spectrum identifying a viral cause in mild cases allows the physician to defer treatment with antibiotics and reassure the patient. This is an essential component of antimicrobial stewardship as high rates of antibiotic use are associated with circulating antimicrobial resistance [2]. The majority of antibiotic prescriptions issued in the UK are for respiratory tract infections [3] yet antibiotic use puts patients at risk of adverse drug reactions and in many cases will not lessen the duration of symptoms [4].
Respiratory infection diagnostics
Until recently viral diagnostics relied on cell culture or animal/egg inoculation. These time-consuming and laborious methods provided only a retrospective diagnosis and were, therefore, of little use in the management of acute infections. Nucleic acid amplification tests (NAAT), directly detecting the RNA or DNA of pathogens, have largely superseded these.
Many methods of RNA/DNA detection are available (Table 1). The most widely used is polymerase chain reaction (PCR). This has the benefit of rapid turnaround times and high levels of sensitivity and specificity in comparison to cell culture [5]. A pair of primers is required for each target but it is possible to use multiple primer sets within a single reaction (up to four) without compromising test sensitivity over the monoplex assay. This chemistry is now available as closed systems providing rapid results as a near-patient test (GeneXpert by Cepheid, Cobas by Roche).
Other examples of molecular NAATs which are available but not commonplace would be loop-mediated isothermal amplification (LAMP) and microarrays. LAMP detects nucleic acids but does not rely on thermocycling. It does, however, require multiple primers for each target (usually six) and as a consequence the sensitivity is more likely to be affected by genome mutations than standard PCR. This also makes multiplexing multiple targets within a single reaction more complicated.
Microarrays (also known as DNA chips or biochips) use a collection of oligonucleotide probes, about 70 bases in length, immobilized on a solid surface. The probes are complementary portions of DNA or RNA designed to match conserved regions of a genome; thus, if present, the target will bind to the corresponding probe which can then be quantified. Multiple probes may be attached to a single surface, screening for a large number of pathogens in a single reaction. As probes are targeted against conserved regions of the pathogen genome they may also detect related but novel pathogens.
To be used as a comprehensive diagnostic test numerous targets must be included to cover the likely pathogens. In the case of respiratory infections commercial assays are available with around 33 targets over 8 reactions [6]. Despite this approach a viral pathogen is detected in only a minority of specimens [7] and it remains the case that a pathogen will only be detected if actively sought.
Several significant respiratory viruses have been identified in recent years; those which may have circulated for many years, such as the human metapneumovirus, or emerging pathogens, such as SARS and, more recently, MERS. Whereas these are related to other known pathogens they are genetically distinct and, therefore, would evade detection with molecular methods.
What is next-generation sequencing?
The term ‘next-generation sequencing’ (NGS) refers to the practice of sequencing millions of DNA fragments in parallel. Numerous platforms are available to carry this out and the exact chemistry varies greatly between each. In practice, either all genetic material within a sample can be sequenced – metagenomics; or, hybrid capture allows a more focused approach to an area or genome of interest, this is termed ‘target enrichment’.
Advantages of NGS
Applying metagenomic NGS to clinical samples would allow an untargeted approach to identify all the genetic material contained within. This method has demonstrated potential for use in a diagnostic setting [8, 9].
The lack of pathogen targeting means that multiple pathogens can be detected without selection (Fig. 1), including novel or emerging or divergent pathogens. In the case of many viral pathogens evolution and mutations over time can reduce detection with specific PCR reactions. Mutations affecting primer binding sites may reduce binding affinity during the reaction and, for this reason, the performance of diagnostic assays must be monitored closely and at times altered. NGS could, therefore, be used as an adjunct in the quality control of PCR assays.
It is possible to detect full genome sequences from diagnostic samples and even with partial genome sequence it is feasible to subtype viral pathogens. Real-time knowledge of the circulating viral subtype is of particular importance in the management of influenza where this informs anti-viral choice, potential resistance and vaccine efficacy. This is currently carried out using additional PCR assays and Sanger sequencing, although this is not always possible in real-time.
Laboratory workflow
Currently the identification of rare or unusual pathogens using molecular methods necessitates samples to be batched to make the process cost effective; alternatively the test is centralized to a single laboratory to which samples must be sent. Either results in an increase in turn-around time. The use of NGS without any enrichment or targeting would permit samples to be treated in the same manner irrespective of type or likely pathogen.
Challenges
A major barrier in introducing NGS to the diagnostic setting is cost. Although the cost of NGS is decreasing rapidly it remains considerably more expensive than multiplex PCR. It is, therefore, unlikely to be cost effective to use this method for pathogen detection in non-severe infections for the time being. However, any cost–benefit analysis on introducing NGS to a diagnostic setting should also consider, on the positive side of the balance sheet, the likely savings NGS would offer in reductions to epidemiological and public health testing.
Complexity and turnaround time
Current methods of library preparation are complex requiring multiple user interventions and additional equipment to that found in a diagnostic laboratory with attendant implications for the time and cost of the process. To be carried out as a routine diagnostic assay these processes would need to be simplified and, ideally, automated to reduce hands-on time and the potential for contamination and human error.
The commonly used sequencing platforms take several hours or even days to generate sequence information. It should be noted that the third generation platforms that use single-molecule real-time (SMRT) technology are rapid and, as the name suggests, can be analysed in almost real-time.
Data analysis
Data analysis and storage is a major bottleneck in the NGS process. The computational power required for analyses would be beyond the current capabilities of diagnostic services. The methods used in data analysis pose a further challenge. Currently there is no agreed method as to the best approach for data analysis; indeed this is an entire specialty in itself, bioinformatics. Development of software programmes will both make the analysis more feasible in a diagnostic service to non-bioinformaticians and will lead to standardization of data processing.
Discussion
NGS undoubtedly has potential to dramatically change the landscape of infection diagnostics. Whether it will replace current molecular methods remains to be seen. The cost and complex sample processing remains prohibitive but these novel technologies are still in an exponential phase of development. Even current methodologies are yielding promising results in this field. The lack of pathogen targeting means that there is potential for a single work flow to be applied to all specimens, no matter what the syndrome which could even be extended to non-viral pathogens, resulting in a pan-microbial diagnostic test.
The generation of virus sequence as part of a diagnostic assay has substantial management and epidemiological benefits. In terms of respiratory infections this is currently limited to resistance testing and strain analysis of influenza. However, in the management of blood-borne viruses, particularly HIV and hepatitis C virus (HCV), point mutations and minor populations may impact greatly on the management and prognosis of patients. With the introduction of novel therapies or vaccines against viral respiratory infections NGS will have an even greater clinical benefit.
Acknowledgements
I would like to thank Dr Rory Gunson and Dr Emma Thomson for reviewing the manuscript.
References
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3. Lindbaek M. Prescribing antibiotics to patients with acute cough and otitis media. Br J Gen Pract 2010; 56(524): 164–166.
4. Butler CC, Hood K, Verheij T, Little P, Melbye H, Nuttall J, Kelly MJ, Mölstad S, Godycki-Cwirko M, Almirall J, Torres A, Gillespie D, Rautakorpi U, Coenen S, Goossens H. Variation in antibiotic prescribing and its impact on recovery in patients with acute cough in primary care: prospective study in 13 countries. BMJ 2009; 338: b2242.
5. van Elden LJ, van Kraaij MG, Nijhuis M, Hendriksen KA, Dekker AW, Rozenberg-Arska M, van Loon AM. Polymerase chain reaction is more sensitive than viral culture and antigen testing for the detection of respiratory viruses in adults with hematological cancer and pneumonia. Clin Infect Dis 2002; 34(2): 177–183.
6. FTD Respiratory Pathogens 33. Fast-track Diagnostics 2016. (http://www.fast-trackdiagnostics.com/products/ftd-respiratory-pathogens-33/)
7. Nickbakhsh S, Thorburn F, von Wissmann B, McMenamin J, Gunson RN, Murcia PR. Extensive multiplex PCR diagnostics reveal new insights into the epidemiology of viral respiratory infections. Epidemiol Infect 2016; 144(10): 2064–2076.
8. Thorburn F, Bennett S, Modha S, Murdoch D, Gunson R, Murcia PR. The use of next generation sequencing in the diagnosis and typing of respiratory infections. J Clin Virol 2015; 69: 96–100.
9. Prachayangprecha S, Schapendonk CM, Koopmans MP, Osterhaus AD, Schürch AC, Pas SD, van der Eijk AA, Poovorawan Y, Haagmans BL, Smits SL. Exploring the potential of next-generation sequencing in detection of respiratory viruses. J Clin Microbiol 2014; 52(10): 3722–3730.
The author Fiona Thorburn PhD NHS Greater Glasgow and Clyde, Glasgow G12 0XH, UK
E-mail: Fionathorburn@nhs.net
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The sequence diversity of the more than 150 currently recognized HRV genotypes poses challenges for the development of robust molecular methods that detect all genotypes with equal efficiency. Real-time reverse-transcription (RT)-PCR was compared to digital RT-PCR for quantification of HRV in clinical specimens when using type-specific and consensus primers and probes.
by Dr Jane Kuypers
Introduction
Human rhinoviruses (HRV) are small, positive-sense RNA viruses within the family Picornaviridae. Over 150 genotypes of this important human pathogen have been recognized within species HRVA, HRVB, and HRVC of the genus Enterovirus (http//:www.picornaviridae.com). HRV infections occur throughout the year and throughout the world. HRV are responsible for a high incidence and wide range of respiratory infections in all populations, including one-half to two-thirds of all common colds and many cases of otitis media and sinusitis in the upper respiratory tract. Lower tract infections include bronchiolitis, pneumonia and exacerbation of disease in children with asthma and cystic fibrosis, and in adults with chronic obstructive pulmonary disease. Cases of serious illness and even death due to HRV have been reported, especially in immunocompromised individuals, the elderly and infants [1, 2].
Laboratory detection of HRV is important for diagnosis and surveillance, especially in high risk populations. HRV are frequently detected as co-infections with other respiratory viruses and in individuals with long-term and asymptomatic shedding [3]. In addition to qualitative detection, accurate quantification of HRV RNA in clinical samples is needed for studies on the association of HRV viral load with viral transmission and with patient symptoms and outcomes. Viral-load studies of other respiratory viruses have shown that a correlation exists between quantity of virus and disease severity. HRV viral-load determinations may also be important for patient management, especially in asymptomatic patients who test positive for HRV at low levels. More importantly, accurate HRV viral-load assessments will be necessary for evaluating the performance of potential HRV antiviral drugs [4].
Detection
HRV were initially detected by growth in cell culture. Approximately 100 serotypes of HRV grown in cell culture were antigenically characterized by their reactions with various antisera. The serotypes were subsequently classified into two groups, A and B, according to their sensitivity towards antivirus agents [5] and are now included in HRV species A (80 genotypes) and B (32 genotypes) based on genetic sequencing. Cell culture is sensitive for detection of many, but not all HRV genotypes; 55 HRV that do not grow in the cell culture lines normally used in the clinical laboratory and have been detected only by molecular methods are classified in HRV species C (http//:www.picornaviridae.com).
The use of molecular methods for the detection of HRV in clinical specimens has provided more accurate information about the disease burden and epidemiology of these ubiquitous viruses. The molecular method most often used to detect HRV is real-time reverse-transcription (RT)-PCR [3]. RT-PCR assays, when accompanied by amplification of serially diluted standards of known RNA copy numbers (RT-qPCR), can be used to quantify the number of viral copies in a sample. By comparing the PCR Ct value (the PCR cycle at which fluorescence reaches a certain threshold) of a clinical specimen to the standard curve, the relative quantity of the analyte can be calculated [6].
Within the HRV genome, the region most frequently targeted for RT-PCR by clinical assays is the 5’ non-coding region (NCR), which exhibits the most sequence homology among the HRV genotypes. However, even in this region, there is a lot of sequence diversity, which makes it challenging to design a single, consensus PCR primer and probe set to amplify all HRV genotypes with equal efficiency. In order to amplify HRV genotypes with diverse sequences in the prime/probe binding regions, consensus PCR primer and probe sets have been designed with degenerate and modified bases or multiple oligonucleotides [7–10]. However, consensus RT-qPCR assays may not give accurate quantitative results for all HRV genotypes due to amplification inefficiency caused by base mismatches between the consensus primers and probe and the viral sequences [11].
Quantitation by RT-qPCR
To determine if a consensus RT-qPCR assay [7] could be used to accurately quantify all genotypes of HRV, including those with sequence differences in the primer and probe binding regions, we compared the efficiency and sensitivity of a consensus RT-qPCR assay to that of genotype-specific RT-qPCR assays [4]. In Figure 1(a), the results of RT-qPCR assays using type-specific primers and probes, which exactly match the target sequences, show standard curves indicating accurate and sensitive quantification of RNA transcripts from six specific HRV genotypes. However, RT-qPCR using a consensus HRV primer and probe set did not give accurate or sensitive quantification for some HRV genotypes, especially types A33 and A88 (Fig. 1b). RNA from HRV genotypes with base mismatches between the consensus primer and probe sequences and the specific viral sequences was inaccurately quantified using the consensus assay, most likely due to poor amplification efficiency.
Quantitation by RT-dPCR
Digital RT-PCR (RT-dPCR), which provides absolute nucleic acid quantification without the need for PCR Ct values and standard curves and is less affected by poor amplification efficiency, may perform better than RT-qPCR for quantification of HRV RNA. In dPCR, an amplification reaction, which contains fluorescent dye to measure amplification, is divided into 12?000 to 200?000 independent partitions, each ideally containing no more than one target molecule. The reaction is amplified to end point and the number of fluorescent (positive) and non-fluorescent (negative) partitions is counted. In specimens with more targets than partitions, Poisson statistics are used to calculate the average number of targets per positive partition and thus, the number of targets in the original sample [12, 13]. Compared to qPCR, dPCR is less susceptible to amplification inefficiency caused by primer/probe sequence mismatches because quantification derives from a PCR reaction that cycles to endpoint rather than from an amplification curve as in qPCR. Accurate quantification by dPCR is also not dependent on a well-calibrated standard [14]. These characteristics make dPCR especially useful for quantifying viral targets with many subtypes and high sequence diversity that leads to mismatches between targets and PCR primer and probe sequences, such as HRV.
To determine if consensus RT-dPCR would perform better than consensus RT-qPCR for quantification of HRV genotypes, we similarly tested RNA transcripts of HRV genotypes, including some with sequence variation in the consensus primer and probe binding region, by RT-dPCR using both type-specific and consensus primers and probes. In Figure 2(a), the results of RT-dPCR assays using type-specific primers and probes show good correlations between the expected number of RNA copies/reaction and the observed number. When amplified by RT-dPCR using the consensus assay (Fig. 1b), in contrast to RT-qPCR, the observed number of RNA copies/reaction was also closely correlated with the expected number for most of the HRV genotypes tested.
In a previous study [4], data from 16 HRV genotypes that represented the consensus primer and probe binding sequences of 128 genotypes indicated that, when using consensus primers and probe, RT-dPCR quantification of HRV RNA was more accurate than that of RT-qPCR for some genotypes. We found that although the consensus RT-qPCR did accurately quantify many HRV genotypes, it did not accurately quantify all genotypes of HRV due to sub-optimal amplification of genotypes with sequences that do not exactly match those of the primers and probe. Consensus RT-dPCR, however, did not overcome all sequence mismatch-induced amplification inefficiency, as evidenced by genotype A88 (Fig. 2b), which has a single mismatch near the middle of the forward primer.
Although RT-dPCR has been shown to be more accurate than RT-qPCR for quantification of HRV and may be applicable to other viruses with high sequence diversity, like HIV and HBV, it has some disadvantages for routine use in a clinical laboratory. RT-dPCR has a more limited dynamic range compared to RT-qPCR (104 for RT-qPCR compared to 108 for RT-qPCR), which would require dilution and retesting of samples with high viral loads. Running an RT-dPCR assay requires more hands-on technician time and has a lower throughput than current RT-qPCR assays. Digital PCR instruments and reagents are also currently more expensive than most qPCR systems.
Conclusion
In conclusion, dPCR was a better alternative to qPCR on RNA templates known to have significant sequence diversity that cannot be avoided during primer and probe design and should be considered the better molecular method for quantification of HRV in respiratory specimens.
References
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4. Sedlak RH, Nguyen T, Palileo I, Jerome KR, Kuypers J. Superiority of digital RT-PCR over real-time RT-PCR for quantitation of highly divergent human rhinoviruses. J Clin Microbiol 2017; 55(2): 442–449.
5. Andries K, Dewindt B, Snoeks J, Wouters L, Moereels H, Lewi PJ, Janssen PA. Two groups of rhinoviruses revealed by a panel of antiviral compounds present sequence divergence and differential pathogenicity. J Virol 1990: 64: 1117–1123.
6. Mackay IM, Arden KE, Nitsche A. Real-time PCR in virology. Nucleic Acids Res 2002: 30: 1292–1305.
7. Lu X, Holloway B, Dare RK, Kuypers J, Yagi S, Williams JV, Hall CB, Erdman DD. Real-time reverse transcription-PCR assay for comprehensive detection of human rhinoviruses. J Clin Microbiol 2008: 46(2): 533–539.
8. Granados A, Luinstra K, Chong S, Goodall E, Bahn L, Mubareka S, Smieja M, Mahony J. Use of an improved quantitative polymerase chain reaction assay to determine differences in human rhinovirus viral loads in different populations. Diagn Microbiol Infect Dis 2012: 74: 384–387.
9. Tapparel C, Cordey S, Van Belle S, Turin L, Wai-Ming L, Regamey N, Meylan P, Mühlemann K, Gobbini F, Kaiser L. New molecular detection tools adapted to emerging rhinoviruses and enterviruses. J Clin Microbiol 2009: 47(6): 1742–1749.
10. Bochkov YA, Grindle K, Vang F, Evans MD, Gern JE. Improved molecular typing for rhinovirus species A, B, and C. J Clin Microbiol 2014: 52(7): 2461–2471.
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12. Vynck M, Trypsteen W, Thas O, Vandekerckhove L, De Spiegelaere W. The future of the polymerase chain reaction in virology. Mol Diagn Ther 2016: 20: 437–447.
13. Huggett JF, Cowen S, Foy CA. Considerations for digital PCR as an accurate molecular diagnostic tool. Clin Chem 2015: 61: 79–88.
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The author Jane Kuypers PhD Department of Laboratory Medicine, University of Washington, Seattle, WA, USA Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
E-mail: kuypers@uw.edu
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Human bocavirus 1 (HBoV1) causes respiratory tract infections in infants and children. Diagnosis of acute HBoV1 infections is challenging as viral DNA is frequently detected in asymptomatic controls and as co-finding with other viruses. Recently developed novel HBoV1 mRNA and antigen tests may improve the diagnosis of acute HBoV1 infections.
by Juha M. Koskinen, Dr Andrea Bruning, Dr Petri Susi and Dr Janne O. Koskinen
Background and molecular characteristics of HBoV1
Human bocavirus 1 (HBoV1), a small single-stranded DNA (ssDNA) virus belonging to the Parvoviridae family, was described for the first time in 2005 [1]. Its genome replication is dependent on the formation of double-stranded DNA (dsDNA) intermediates in the nucleus of the host cells. The dsDNA serves as template for transcription of messenger-RNA (mRNA) by the host replication machinery. The mRNA is further translated into viral proteins, such as structural VP2 protein. Structural proteins assemble as empty capsids into which genomic ssDNA is inserted. Thus, during acute infection, the replicating virus produces mRNA transcripts from the viral dsDNA which are translated into viral proteins. Formation of viral proteins and particles are essential for the multiplication and spread of viable viruses.
Epidemiology and clinical outcomes of HBoV1 infections
HBoV1 was originally discovered in hospitalized children with a respiratory tract infection (RTI) [1]. However, HBoV1 can cause RTI illnesses in varying severities. Mainly children at age 6–24 months are affected. By 6 years old almost all children are seropositive for HBoV1. Data on the disease pressure in adults are very scarce but apparently immunity lasts long and acute infections are rare. HBoV1 DNA is detected by PCR in 2–19% of patients with RTI worldwide. The most common symptoms of acute HBoV1 infection are common cold-like complaints, wheezing, bronchiolitis and pneumonia. HBoV1 is associated with asthma exacerbations [2]. Diagnostic positivity rate for HBoV1 has been high in some studies in summer [3]. This would differ from other RTI viruses like influenza and respiratory syncytial virus. However, most cases of HBoV1 DNA detection are reported in winter and spring [2] which may also be linked to the higher frequency of diagnostic testing during the influenza season.
HBoV1 may infect lower airways down to the bronchioles [2]. There has been no difference in HBoV1 prevalence between immunocompetent and immunocompromised patients [2]. It seems that that particularly young children who were born prematurely may be at risk in developing severe RTIs caused by HBoV1 [4, 5].
HBoV1 DNA is often found in stool samples from children. However, detection rates are similar among subjects with or without acute gastroenteritis. Also co-findings with other known gastroenteritis viruses are common. Thus, the detection of HBoV1 from stool is most probably rather a sign of respiratory tract or systemic infection, prolonged viral shedding or persistent infection than acute gastroenteritis [6].
Diagnostic methods and challenges in diagnosis of HBoV1 infections
HBoV1 infection cannot be accurately diagnosed based on clinical symptoms alone. There are four techniques to aid in the diagnosis of HBoV1 infections. These include serology [7], PCR using viral DNA as target [8], reverse transcription (RT) PCR using viral mRNA as target [9], and most recently antigen detection [10]. Also electron microscopy has been used to detect the presence of viral particles [5], although this technique is not suitable for routine diagnostics.
Serology can provide information as to whether the infection is acute or past and it can be used to confirm the findings of other methods. IgM positivity, low IgG avidity, seroconversion or a diagnostic (?4-fold) increase in the IgG level in paired sera are signs of acute HBoV1 infection [2, 7]. A major drawback of serology is that it takes the human body 1–2 weeks to produce the antibody.
A number of commercially available multiplex PCR tests have included the detection of HBoV1 DNA in their test panels and some of the tests may provide results also in stat labs. However, detection of viral DNA from nasal samples may have little clinical significance since HBoV1 DNA is frequently (10–40 %) detected in asymptomatic controls and often found as co-findings (50–70 %) with other respiratory viruses. Prolonged shedding of the virus from infected shells, or long-term presence of virus or viral DNA in the airways may explain the high co-infection rate and prevalence in asymptomatic controls observed in almost every DNA PCR cohort study [11–14]. Currently, the mechanism for persistence is unknown but one possible explanation may be that the virus exists in a latent phase where the transcription of mRNA and protein translation is inhibited by the immune system.
Quantification of viral DNA by Ct-value gives a statistical correlation with severity but is not diagnostic in individual cases owing to, for example, the semi-quantitative nature of sampling. Thus, high viral DNA load and single findings are only indicative of the etiology [3, 8]. Extensive exclusion of the presence of other potential RTI pathogens together with high genome HBoV1 DNA load as single finding, viremia or the presence of the DNA in normally sterile body fluids has shown causality [4, 5]. Instead of extensive exclusion of other RTI viruses with high-cost multiplex PCRs, direct detection of actively replicating HBoV1 viruses by mRNA PCR or an antigen test could be a more straightforward, specific and cost-efficient approach.
mRNA RT-PCR methodology was developed to specifically detect the acute HBoV1 infections before the rise in antibody levels. mRNA RT-PCR is analytically as sensitive as DNA PCR. It provides the same clinical sensitivity but higher diagnostic specificity than DNA PCR. In one HBoV1 case, mRNA was detected up to 10 days from the onset of the symptoms while the DNA was detected at least up to 2 months although the patient was already fully recovered. The time span for positivity based on the mRNA RT-PCR correlated better with acute symptoms than DNA PCR [9].
Serology, mRNA RT-PCR and DNA PCR suffer from being slow, costly and/or labour intensive techniques, and they are only available in highly specialized diagnostic laboratories. Detection of viral antigens (e.g. structural VP2 protein) from nasal samples provides a rapid and specific alternative for testing of acute HBoV1 infections (Fig. 1). Recently the first HBoV1 antigen test, to our knowledge, was introduced into the automated and multianalyte mariPOC respi test (www.arcdia.com). The test provides most of the positive results in 20 minutes and low positives in 2 hours at the point-of-care. The new test has shown similar clinical specificity compared to mRNA RT-PCR test [15]. Antigen testing is feasible only during the acute phase of the infection (active viral replication phase) which seems to be approximately 5 days from the emergence of symptoms [10], as for most of the RTI viruses. The first days are often the most crucial when making clinical decisions and have impact, for example, for the decision on whether to prescribe antibiotics or not. The features of HBoV1 diagnostic methods are compared in Table 1.
Selected diagnostic cases Case 1
A previously healthy full-term born Finnish girl developed symptoms of rhinorrhea, cough and high fever at 5 months of age. Upper RTI with no lower respiratory tract involvement or signs of otitis was diagnosed. HBoV1 secretion into nasopharyngeal samples was monitored by quantitative mariPOC antigen test up to day 5. Virus peak was at day 3 and viral levels were low at day 5, which coincided with the recovery of symptoms on day 6 [10]. The virus peak sample was estimated to contain 2×1010 viral particles per mL.
Case 2
A prematurely (week 27) born Turkish girl, at 5 months of age, after sepsis, developed high fever, wheezing and was treated for acute bronchiolitis before hospital discharge. The patient was found deceased the same night as the result of respiratory failure caused by pulmonary infection. HBoV was detected as single finding from nasopharyngeal swabs, stools and lung tissues [4].
Case 3
A prematurely (week 25) born Slovene child, at the age of 18 months, with chronic respiratory insufficiency was hospitalized. HBoV1 DNA was detected in tracheal aspirate (2.6×1010 copies/mL), in the nasopharyngeal swab (8.27×106 copies/mL), and in plasma sample (7.42×106 copies/mL). The presence of HBoV1 particles was confirmed by electron microscopy from tracheal aspirate and autologous plasma, which was taken the third day of illness [5].
Conclusions
As demonstrated above, clinical manifestations of HBoV1 range from simple common cold symptoms to fatal respiratory illnesses. Diagnosis of HBoV1 is now significantly more straightforward because of the recent advances in HBoV1 diagnostics. Rapid antigen testing and mRNA RT-PCR provide accurate non-invasive diagnostics for acute HBoV1 infections. mRNA RT-PCR is so far only available in highly specialized diagnostic laboratories while rapid antigen test is applicable at point-of-care. DNA PCR may be most suitable for the detection of viral DNA from body parts, like cerebrospinal fluid during suspected systemic infection. The use of multiple diagnostic methods will provide a more accurate picture about the clinical significance and outcomes of the HBoV1 infections. The method of choice for accurate diagnosis of HBoV1 depends on the elapsed time since the onset of the symptoms, clinical signs and other clinical or research needs. There is no specific medication or vaccine for HBoV1 yet. However, the new diagnostic tests will increase our understanding about the clinical significance of HBoV1 and open new doors for therapy development.
References
1. Allander T, Tammi MT, Eriksson M, Bjerkner A, Tiveljung-Lindell A, Andersson B. Cloning of a human parvovirus by molecular screening of respiratory tract samples. Proc Natl Acad Sci U S A 2005; 102(43): 12891–12896.
2. Jartti T, Hedman K, Jartti L, Ruuskanen O, Allander T, Söderlund-Venermo M. Human bocavirus-the first 5 years. Rev Med Virol 2012; 22(1): 46–64.
3. Zhou L, Zheng S, Xiao Q, Ren L, Xie X, Luo J, Wang L, Huang A, Liu W, Liu E. Single detection of human bocavirus 1 with a high viral load in severe respiratory tract infections in previously healthy children. BMC Infect Dis 2014; 14(424): 1–8.
4. Ziyade N, Sirin G, Elgörmüs N, Das T. Detection of human bocavirus DNA by multiplex PCR analysis: postmortem case report. Balkan Med J 2015; 32(2): 226–229.
5. Uršic T, Krivec U, Kalan G, Petrovec M. Fatal human bocavirus infection in an 18-month-old child with chronic lung disease of prematurity. Pediatr Infect Dis J 2015; 34(1): 111–112.
6. Paloniemi M. Occurrence and significance of human coronaviruses and human bocaviruses in acute gastroenteritis of childhood. Acta Electronica Universitatis Tamperensis 2016; 1652. (http://urn.fi/URN:ISBN:978-952-03-0079-1)
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8. Allander T, Jartti T, Gupta S, Niesters HG, Lehtinen P, Osterback R, Vuorinen T, Waris M, Bjerkner A, Tiveljung-Lindell A, van den Hoogen BG, Hyypiä T, Ruuskanen O. Human bocavirus and acute wheezing in children. Clin Infect Dis 2007; 44(7): 904–910.
9. Christensen A, Døllner H, Skanke LH, Krokstad S, Moe N, Nordbø SA. Detection of spliced mRNA from human bocavirus 1 in clinical samples from children with respiratory tract infections. Emerg Infect Dis 2013; 19(4): 574–580.
10. Bruning AH, Susi P, Toivola H, Christensen A, Söderlund-Venermo M, Hedman K, Aatola H, Zvirbliene A, Koskinen JO. Detection and monitoring of human bocavirus 1 infection by a new rapid antigen test. New Microbes New Infect 2016; 11: 17–19.
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14. Rhedin S, Lindstrand A, Rotzén-Östlund M, Tolfvenstam T, Ohrmalm L, Rinder MR, Zweygberg-Wirgart B, Ortqvist A, Henriques-Normark B, Broliden K, Naucler P. Clinical utility of PCR for common viruses in acute respiratory illness. Pediatrics. 2014; 133(3): e538–545.
15. Toivola H, Christensen A, Hedman K, Söderlund-Venermo M, Koskinen JM, Peltola V, Koskinen JO. Advances in the diagnosis of acute human bocavirus infections. 25th European Congress of Clinical Microbiology and Infectious Diseases, Copenhagen, Denmark, 2015. Poster abstract P0329.
The authors Juha M. Koskinen*1,2 MSc, Andrea Bruning3 MD, Petri Susi4 PhD and Janne O. Koskinen2 PhD Directorate of Laboratory Medicine and Pathology, Royal Hospital, Muscat, Oman 1Turku Doctoral Programme of Molecular Medicine, Department of Virology, University of Turku, Turku, Finland 2ArcDia International Oy Ltd, Turku, Finland 3Department of Pediatric Infectious Diseases, Emma Children’s Hospital, Academic Medical Center (AMC), Amsterdam, The Netherlands. 4Department of Virology, University of Turku, Turku, Finland
*Corresponding author E-mail: jumako@utu.fi
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Two novel mutations in the PPIB gene cause a rare pedigree of osteogenesis imperfecta type IX
BACKGROUND: Osteogenesis imperfecta (OI) is a rare genetic skeletal disorder characterized by increased bone fragility and vulnerability to fractures. PPIB is identified as a candidate gene for OI-IX, here we detect two pathogenic mutations in PPIB and analyze the genotype-phenotype correlation in a Chinese family with OI.
METHODS: Next-generation sequencing (NGS) was used to screen the whole exome of the parents of proband. Screening of variation frequency, evolutionary conservation comparisons, pathogenicity evaluation, and protein structure prediction were conducted to assess the pathogenicity of the novel mutations. Sanger sequencing was used to confirm the candidate variants. RTQ-PCR was used to analyze the PPIB gene expression.
RESULTS: All mutant genes screened out by NGS were excluded except PPIB. Two novel heterozygous PPIB mutations (father, c.25A>G; mother, c.509G>A) were identified in relation to osteogenesis imperfecta type IX. Both mutations were predicted to be pathogenic by bioinformatics analysis and RTQ-PCR analysis revealed downregulated PPIB expression in the two carriers.
CONCLUSION: We report a rare pedigree with an autosomal recessive osteogenesis imperfecta type IX (OI-IX) caused by two novel PPIB mutations identified for the first time in China. The current study expands our knowledge of PPIB mutations and their associated phenotypes, and provides new information on the genetic defects associated with this disease for clinical diagnosis.
Application of next generation sequencing in clinical microbiology and infection prevention
Deurenberg RH, Bathoorn E, Chlebowicz MA, Couto N, Ferdous M et al. J Biotechnol 2017; 243: 16–24
Current molecular diagnostics of human pathogens provide limited information that is often not sufficient for outbreak and transmission investigation. Next generation sequencing (NGS) determines the DNA sequence of a complete bacterial genome in a single sequence run, and from these data, information on resistance and virulence, as well as information for typing is obtained, useful for outbreak investigation. The obtained genome data can be further used for the development of an outbreak-specific screening test. In this review, a general introduction to NGS is presented, including the library preparation and the major characteristics of the most common NGS platforms, such as the MiSeq (Illumina) and the Ion PGM™ (ThermoFisher). An overview of the software used for NGS data analyses used at the medical microbiology diagnostic laboratory in the University Medical Center Groningen in The Netherlands is given. Furthermore, applications of NGS in the clinical setting are described, such as outbreak management, molecular case finding, characterization and surveillance of pathogens, rapid identification of bacteria using the 16S-23S rRNA region, taxonomy, metagenomics approaches on clinical samples, and the determination of the transmission of zoonotic micro-organisms from animals to humans. Finally, we share our vision on the use of NGS in personalised microbiology in the near future, pointing out specific requirements.
A targeted high-throughput next-generation sequencing panel for clinical screening of mutations, gene amplifications, and fusions in solid tumours
Clinical next-generation sequencing (NGS) assay choice requires careful consideration of panel size, inclusion of appropriate markers, ability to detect multiple genomic aberration types, compatibility with low quality and quantity of nucleic acids, and work flow feasibility. Herein, in a high-volume clinical molecular diagnostic laboratory, we have validated a targeted high-multiplex PCR-based NGS panel (OncoMine Comprehensive Assay) coupled with high-throughput sequencing using Ion Proton sequencer for routine screening of solid tumours. The panel screens 143 genes using low amounts of formalin-fixed, paraffin-embedded DNA (20 ng) and RNA (10 ng). A large cohort of 121 tumour samples representing 13 tumour types and 6 cancer cell lines was used to assess the capability of the panel to detect 148 single-nucleotide variants, 49 insertions or deletions, 40 copy number aberrations, and a subset of gene fusions. High levels of analytic sensitivity and reproducibility and robust detection sensitivity were observed. Furthermore, we demonstrated the critical utility of sequencing paired normal tissues to improve the accuracy of detecting somatic mutations in a background of germline variants. We also validated use of the Ion Chef automated bead templating and chip loading system, which represents a major work flow improvement. In summary, we present data establishing the OncoMine Comprehensive Assay-Ion Proton platform to be well suited for implementation as a routine clinical NGS test for solid tumours.
Presence of cancer-associated mutations in exhaled breath condensates of healthy individuals by next generation sequencing
Youssef O, Knuuttila A, Piirilä P, Böhling T, Sarhadi V, Knuutila S. Oncotarget 2017; doi: 0.18632/oncotarget.15233 [Epub ahead of print]
Exhaled breath condensate (EBC) is a non-invasive source that can be used for studying different genetic alterations occurring in lung tissue. However, the low yield of DNA available from EBC has hampered the more detailed mutation analysis by conventional methods. We applied the more sensitive amplicon-based next generation sequencing (NGS) to identify cancer related mutations in DNA isolated from EBC. In order to apply any method for the purpose of mutation screening in cancer patients, it is important to clarify the incidence of these mutations in healthy individuals. Therefore, we studied mutations in hotspot regions of 22 cancer genes of 20 healthy, mainly non-smoker individuals, using AmpliSeq colon and lung cancer panel and sequenced on Ion PGM. In 15 individuals, we detected 35 missense mutations in TP53, KRAS, NRAS, SMAD4, MET, CTNNB1, PTEN, BRAF, DDR2, EGFR, PIK3CA, NOTCH1, FBXW7, FGFR3, and ERBB2: these have been earlier reported in different tumor tissues. Additionally, 106 novel mutations not reported previously were also detected. One healthy non-smoker subject had a KRAS G12D mutation in EBC DNA. Our results demonstrate that DNA from EBC of healthy subjects can reveal mutations that could represent very early neoplastic changes or alternatively a normal process of apoptosis eliminating damaged cells with mutations or altered genetic material. Further assessment is needed to determine if NGS analysis of EBC could be a screening method for high risk individuals such as smokers, where it could be applied in the early diagnosis of lung cancer and monitoring treatment efficacy.
Molecular testing for familial hypercholesterolaemia-associated mutations in a UK-based cohort: development of an NGS-based method and comparison with multiplex polymerase chain reaction and oligonucleotide arrays
Reiman A, Pandey S, Lloyd KL, Dyer N, Khan M, Crockard M, Latten MJ, Watson TL, Cree IA, Grammatopoulos DK. Ann Clin Biochem 2016; 53(6): 654–662
BACKGROUND: Detection of disease-associated mutations in patients with familial hypercholesterolaemia is crucial for early interventions to reduce risk of cardiovascular disease. Screening for these mutations represents a methodological challenge since more than 1200 different causal mutations in the low-density lipoprotein receptor has been identified. A number of methodological approaches have been developed for screening by clinical diagnostic laboratories.
METHODS: Using primers targeting, the low-density lipoprotein receptor, apolipoprotein B, and proprotein convertase subtilisin/kexin type 9, we developed a novel Ion Torrent-based targeted re-sequencing method. We validated this in a West Midlands-UK small cohort of 58 patients screened in parallel with other mutation-targeting methods, such as multiplex polymerase chain reaction (Elucigene FH20), oligonucleotide arrays (Randox familial hypercholesterolaemia array) or the Illumina next-generation sequencing platform.
RESULTS: In this small cohort, the next-generation sequencing method achieved excellent analytical performance characteristics and showed 100% and 89% concordance with the Randox array and the Elucigene FH20 assay. Investigation of the discrepant results identified two cases of mutation misclassification of the Elucigene FH20 multiplex polymerase chain reaction assay. A number of novel mutations not previously reported were also identified by the next-generation sequencing method.
CONCLUSIONS: Ion Torrent-based next-generation sequencing can deliver a suitable alternative for the molecular investigation of familial hypercholesterolaemia patients, especially when comprehensive mutation screening for rare or unknown mutations is required.
Analytical validation of the next-generation sequencing assay for a nationwide signal-finding clinical trial: Molecular Analysis for Therapy Choice clinical trial
The National Cancer Institute-Molecular Analysis for Therapy Choice (NCI-MATCH) trial is a national signal-finding precision medicine study that relies on genomic assays to screen and enroll patients with relapsed or refractory cancer after standard treatments. We report the analytical validation processes for the next-generation sequencing (NGS) assay that was tailored for regulatory compliant use in the trial. The Oncomine Cancer Panel assay and the Personal Genome Machine were used in four networked laboratories accredited for the Clinical Laboratory Improvement Amendments. Using formalin-fixed paraffin-embedded clinical specimens and cell lines, we found that the assay achieved overall sensitivity of 96.98% for 265 known mutations and 99.99% specificity. High reproducibility in detecting all reportable variants was observed, with a 99.99% mean interoperator pairwise concordance across the four laboratories. The limit of detection for each variant type was 2.8% for single-nucleotide variants, 10.5% for insertion/deletions, 6.8% for large insertion/deletions (gap ?4 bp), and four copies for gene amplification. The assay system from biopsy collection through reporting was tested and found to be fully fit for purpose. Our results indicate that the NCI-MATCH NGS assay met the criteria for the intended clinical use and that high reproducibility of a complex NGS assay is achievable across multiple clinical laboratories. Our validation approaches can serve as a template for development and validation of other NGS assays for precision medicine.
Targeted next-generation sequencing of FNA-derived DNA in pancreatic cancer
Sibinga Mulder BG, Mieog JS, Handgraaf HJ, Farina Sarasqueta A, Vasen H et al. J Clin Pathol 2017; 70(2): 174–178
To improve the diagnostic value of fine-needle aspiration (FNA)-derived material, we perform targeted next-generation sequencing (NGS) in patients with a suspect lesion of the pancreas. The NGS analysis can lead to a change in the treatment plan or supports inconclusive or uncertain cytology results. We describe the advantages of NGS using one particular patient with a recurrent pancreatic lesion 7 years after resection of a pancreatic ductal adenocarcinoma (PDAC). Our NGS analysis revealed the presence of a presumed second primary cancer in the pancreatic remnant, which led to a change in treatment: resection with curative intend instead of palliation. Additionally, NGS identified an unexpected germline CDKN2A 19-base pair deletion, which predisposed the patient to developing PDAC. Preoperative NGS analysis of FNA-derived DNA can help identify patients at risk for developing PDAC and define future therapeutic options.
Exome sequencing covers >98% of mutations identified on targeted next generation sequencing panels
LaDuca H, Farwell KD, Vuong H, Lu HM, Mu W, Shahmirzadi L, Tang S, Chen J, Bhide S, Chao EC. PLoS One 2017;12(2): e0170843
BACKGROUND: With the expanded availability of next generation sequencing (NGS)-based clinical genetic tests, clinicians seeking to test patients with Mendelian diseases must weigh the superior coverage of targeted gene panels with the greater number of genes included in whole exome sequencing (WES) when considering their first-tier testing approach. Here, we use an in silico analysis to predict the analytic sensitivity of WES using pathogenic variants identified on targeted NGS panels as a reference. METHODS: Corresponding nucleotide positions for 1533 different alterations classified as pathogenic or likely pathogenic identified on targeted NGS multi-gene panel tests in our laboratory were interrogated in data from 100 randomly-selected clinical WES samples to quantify the sequence coverage at each position. Pathogenic variants represented 91 genes implicated in hereditary cancer, X-linked intellectual disability, primary ciliary dyskinesia, Marfan syndrome/aortic aneurysms, cardiomyopathies and arrhythmias.
RESULTS: When assessing coverage among 100 individual WES samples for each pathogenic variant (153,300 individual assessments), 99.7% (n = 152,798) would likely have been detected on WES. All pathogenic variants had at least some coverage on exome sequencing, with a total of 97.3% (n = 1491) detectable across all 100 individuals. For the remaining 42 pathogenic variants, the number of WES samples with adequate coverage ranged from 35 to 99. Factors such as location in GC-rich, repetitive, or homologous regions likely explain why some of these alterations were not detected across all samples. To validate study findings, a similar analysis was performed against coverage data from 60,706 exomes available through the Exome Aggregation Consortium (ExAC). Results from this validation confirmed that 98.6% (91,743,296/93,062,298) of pathogenic variants demonstrated adequate depth for detection.
CONCLUSIONS: Results from this in silico analysis suggest that exome sequencing may achieve a diagnostic yield similar to panel-based testing for Mendelian diseases.
Validation of an NGS mutation detection panel for melanoma
Reiman A, Kikuchi H, Scocchia D, Smith P, Tsang YW, Snead D, Cree IA. BMC Cancer 2017;17(1): 150
BACKGROUND: Knowledge of the genotype of melanoma is important to guide patient management. Identification of mutations in BRAF and c-KIT lead directly to targeted treatment, but it is also helpful to know if there are driver oncogene mutations in NRAS, GNAQ or GNA11 as these patients may benefit from alternative strategies such as immunotherapy.
METHODS: While polymerase chain reaction (PCR) methods are often used to detect BRAF mutations, next generation sequencing (NGS) is able to determine all of the necessary information on several genes at once, with potential advantages in turnaround time. We describe here an Ampliseq hotspot panel for melanoma for use with the IonTorrent Personal Genome Machine (PGM) which covers the mutations currently of most clinical interest.
RESULTS: We have validated this in 151 cases of skin and uveal melanoma from our files, and correlated the data with PCR based assessment of BRAF status. There was excellent agreement, with few discrepancies, though NGS does have greater coverage and picks up some mutations that would be missed by PCR. However, these are often rare and of unknown significance for treatment.
CONCLUSIONS: PCR methods are rapid, less time-consuming and less expensive than NGS, and could be used as triage for patients requiring more extensive diagnostic workup. The NGS panel described here is suitable for clinical use with formalin-fixed paraffin-embedded (FFPE) samples.
Exome sequencing in a family with luminal-type breast cancer underpinned by variation in the
methylation pathway
van der Merwe N, Peeters AV, Pienaar FM, Bezuidenhout J, van Rensburg SJ, Kotze MJ. Int J Mol Sci 2017;18(2): E467
Panel-based next generation sequencing (NGS) is currently preferred over whole exome sequencing (WES) for diagnosis of familial breast cancer, due to interpretation challenges caused by variants of uncertain clinical significance (VUS). There is also no consensus on the selection criteria for WES. In this study, a pathology-supported genetic testing (PSGT) approach was used to select two BRCA1/2 mutation-negative breast cancer patients from the same family for WES. Homozygosity for the MTHFR 677 C>T mutation detected during this PSGT pre-screen step was considered insufficient to cause bilateral breast cancer in the index case and her daughter diagnosed with early-onset breast cancer (<30 years). Extended genetic testing using WES identified the RAD50 R385C missense mutation in both cases. This rare variant with a minor allele frequency (MAF) of <0.001 was classified as a VUS after exclusion in an affected cousin and extended genotyping in 164 unrelated breast cancer patients and 160 controls. Detection of functional polymorphisms (MAF > 5%) in the folate pathway in all three affected family members is consistent with inheritance of the luminal-type breast cancer in the family. PSGT assisted with the decision to pursue extended genetic testing and facilitated clinical interpretation of WES aimed at reduction of recurrence risk.
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Towards shared responsibility for family planning
, /in Featured Articles /by 3wmediaNext-generation sequencing in clinical virology diagnostics
, /in Featured Articles /by 3wmediaIntroduction
Methodologies to detect pathogenic viruses in clinical specimens have transitioned from classic cell culture and antibody–antigen techniques to more sensitive molecular methods such as polymerase chain reaction (PCR). The targeted nature of these methodologies inhibits their ability to accommodate the true diversity of human pathogens in a clinical specimen, especially viruses [1]. Next-generation sequencing (NGS) technologies are quickly demonstrating their ability to provide broad detection of infectious agents in a target-independent manner [2–7]. NGS has many advantages beyond the improved detection of all suspected, unsuspected, or even novel pathogens in a clinical specimen [8]. Familiarization with pathogen genomic sequences within clinical specimens enhances our understanding of infectious disease through further discovery of pathogen variability and genotyping [9–11], drug resistance or response to therapy [12], vaccine development and efficacy monitoring [13], and further characterization of the metagenome [14]. The use of NGS for routine use in clinical diagnostics is emerging with its own set of limitations and challenges [13, 15]. Focusing on viruses of public health importance, we compared the performance of NGS alongside other more common viral detection methodologies.
Conventional methods versus NGS
We investigated applications of NGS in a clinical laboratory to detect pathogenic viruses in common specimen types and compared NGS data to that which could be obtained by more conventional methods for detecting and characterizing the following viruses of public health importance: adenovirus, herpesvirus, hepatitis C virus, and influenza [16]. We compared results obtained by NGS to viral culture, immunofluorescence staining, serum neutralization, and PCR in terms of turnaround time as well as the clinical relevance of the information obtained.
Table 1 describes the turnaround time of conventional methods to NGS for detecting adenoviruses and herpesviruses, both DNA viruses. The amount of time it takes to grow a virus in culture is variable, ranging from 1 day for herpes simplex viruses to 18 days for adenoviruses. All NGS data could be obtained in 4 days, which includes nucleic acid extraction, sequencing library preparation, sequencing and data analysis. Although most laboratories are not currently equipped with in-house bioinformaticians, much of the analysis can be done simply using common sequencing analysing software and the quickly growing number of applications online. For data analysis, we used PathSeq™Virome which enabled us to feed large read files into the application which would generate a report describing the viruses present, including a ‘detection score’ to distinguish strong and weak presence. NGS data provided much more information regarding the exact isolate which may aid health professionals in tracking and relating individual cases with others. Group C adenoviruses are treatable with cidofovir and NGS data was able to identify the amino acid motif that most affects antiviral resistance.
Hepatitis C virus (HCV) is a growing concern for public health and tends to be difficult to design targeted methodologies around owing to the high variability of viral genomes known, even within the same patient. NGS is a powerful tool for characterizing HCV infections and, in our experience, more informational than targeted genotyping assays (Table 2). As we were able to sequence nearly the entire HCV genome (coverage ranged from 92.4–95.6%), data could be generated describing the mutations at key locations across the genomes that are known to cause drug resistance. Antiviral resistance is also critical when characterizing current circulating influenza virus strains and NGS was able to identify viruses that would be considered susceptible to neuraminidase inhibitors (Table 3). In two cases, the viral load of the specimen was too low to achieve good genome coverage across the neuraminidase gene, but this issue could be resolved by screening specimens for high titre (i.e. qPCR) or using enrichment techniques such as ultracentrifugation or filtration of other background nucleic acid.
In most cases, with the exception of one specimen where no cytomegalovirus was definitively identified (HSV5, Table 1), information retrieved by NGS met or exceeded that of conventional methodologies. NGS proves to be a laboratory tool capable of not only detecting pathogenic viruses in clinical specimens, but also predicting the effects of drug treatment as well.
Summary
Through increased use of NGS technologies, reference databases of whole genome sequences can grow and enhance our ability to more definitively identify sequencing reads. Although this review describes conventional methods versus NGS for detecting specific viruses, there was also evidence of the presence of co-infecting viruses such as hepatitis G and Torque Teno virus that weren’t originally targeted. The standard 4-day turnaround time needed to complete NGS could be improved with extraction and library preparation automation, as well as advances in sequencing technology (each run ~40 hours). Based on our laboratory’s experience and the growing body of literature, NGS will change our approach as clinical laboratorians and improve our ability to detect and more fully characterize agents of infectious disease in clinical specimens in a non-targeted manner.
References
1. Köser CU, Ellington MJ, Cartwright EJ, Gillespie SH, Brown NM, Farrington M, Holden MT, Dougan G, Bentley SD, Parkhill J, Peacock SJ. Routine use of microbial whole genome sequencing in diagnostic and public health microbiology. PLoS Pathogens 2012; 8(8): e1002824.
2. Bzhalava D, Johansson H, Ekström J, Faust H, Möller B, Eklund C, Nordin P, Stenquist B, Paoli J, Persson B, Forslund O, Dillner J. Unbiased approach for virus detection in skin lesions. PLoS One 2013; 8(6): e65953.
3. Cheval J, Sauvage V, Frangeul L, Dacheux L, Guigon G, Dumey N, Pariente K, Rousseaux C, Dorange F, Berthet N, Brisse S, Moszer I, Bourhy H, Manuguerra CJ, Lecuit M, Burguiere A, Caro V, Eloit M. Evaluation of high-throughput sequencing for identifying known and unknown viruses in biological samples. J Clin Microbiol 2011; 49(9): 3268–3275.
4. Chan BK, Wilson T, Fischer KF, Kriesel JD. Deep sequencing to identify the causes of viral encephalitis. PLoS One 2014; 9(4): e93993.
5. Kriesel JD, Hobbs MR, Jones BB, Milash B, Nagra RM, Fischer KF. Deep sequencing for the detection of virus-like sequences in the brains of patients with multiple sclerosis: detection of GBV-C in human brain. PLoS One 2012; 7(3): e31886.
6. Moore RA, Warren RL, Freeman JD, Gustavsen JA, Chénard C, Friedman JM, Suttle CA, Zhao Y, Holt RA. The sensitivity of massively parallel sequencing for detecting candidate infectious agents associated with human tissue. PLoS One 2011; 6(5): e19838.
7. Yozwiak NL, Skewes-Cox P, Stenglein MD, Balmaseda A, Harris E, DeRisi JL. Virus identification in unknown tropical febrile illness cases using deep sequencing. PLoS Negl Trop Dis 2012; 6(2): e1485.
8. Radford AD, Chapman D, Dixon L, Chantrey J, Darby AC, Hall N. Application of next-generation sequencing technologies in virology. J Gen Virol 2012; 93(9): 1853–1868.
9. Arroyo LS, Smelov V, Bzhalava D, Eklund C, Hultin E, Dillner J. Next generation sequencing for human papillomavirus genotyping. J Clin Virol 2013: 58(2): 437–442.
10. Flaherty P, Natsoulis G, Muralidharan O, Winters M, Buenrostro J, Bell J, Brown S, Holodniy M, Zhang N, Ji HP. Ultrasensitive detection of rare mutations using next-generation targeted resequencing. Nucleic Acids Res 2012; 40(1): e2.
11. Meiring TL, Salimo AT, Coetzee B, Maree HJ, Moodley J, Hitzeroth II, Freeborough M-J, Rybicki EP, Williamson AL. Next-generation sequencing of cervical DNA detects human papillomavirus types not detected by commercial kits. Virol J 2012; 9: 164.
12. Sijmons S, Van Ranst M, Maes P. Genomic and functional characteristics of human cytomegalovirus revealed by next-generation sequencing. Viruses 2014; 6(3): 1049–1072.
13. Watson SJ, Welkers MRA, DePledge DP, Coulter E, Breuer JM, de Jong MD, Kellam P. Viral population analysis and minority-variant detection using short read next-generation sequencing. Philos Trans R Soc Lond B Biol Sci 2013; 368(1614): 20120205.
14. Han Y, Zhang Y, Mei Y, Wang Y, Liu T, Guan Y, Tan D, Liang Y, Yang L, Yi X. Analysis of hepatitis B virus genotyping and drug resistance gene mutations based on massively parallel sequencing. J Virol Methods 2013; 193(2): 341–347.
15. Messiaen P, Verhofstede C, Vandenbroucke I, Dinakis S, Van Eygen V, Thys K, Winters B, Aerssens J, Vogelaers D, Stuyver LJ, Vandekerckhove L. Ultra-deep sequencing of HIV-1 reverse transcriptase before start of an NNRTI-based regimen in treatment-naive patients. Virology 2012; 426(1): 7–11.
16. Parker J, Chen J. Application of next generation sequencing for the detection of human viral pathogens in clinical specimens. J Clin Virol 2017; 86: 20–26.
The authors
Jayme Parker1,2 PhD and Jack Chen*1,2 PhD
1Department of Biology and Wildlife, Institute of Arctic Biology, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
2Alaska State Public Health Virology Laboratory, Fairbanks, AK 99775, USA
*Corresponding author
E-mail: j.chen@alaska.edu
Molecular diagnostics of pathogens using next-generation sequencing
, /in Featured Articles /by 3wmediaIntroduction
The correct identification and characterization of pathogens is essential for the successful treatment of infections and safety of patients. However, not every pathogen can be successfully cultured and the available molecular tests, mainly focusing on specific pathogens, are inadequate to detect novel genetic features in emerging pathogens. Undetected pathogens can spread easily through a hospital, resulting in a possible outbreak and putting patients admitted to hospitals at a higher risk for infections.
In recent decades, molecular diagnostic tests have improved rapidly and their role in clinical microbiology laboratories became progressively more important [1]. The turnaround time from receiving a sample to the final diagnostic result has been drastically reduced. Molecular methods, such as real-time polymerase chain reaction (PCR), Sanger sequencing and next-generation sequencing (NGS), make it possible to detect non-culturable micro-organisms. Nevertheless, some of these technologies, such as real-time PCR, require knowledge of the genomes of the micro-organisms. In addition, bioinformatics expertise is often needed to interpret the results.
This paper addresses the use of Sanger sequencing and whole genome sequencing (WGS) in the clinical microbiology laboratory for the characterization of pathogens and outbreak management, as it is used in the University Medical Center Groningen (UMCG), one of the largest university hospitals in The Netherlands. The clinical microbiology laboratory at the UMCG receives around 5750 samples per year for detailed molecular analysis, of which approximately 1500 samples are analysed by NGS [2].
Sanger sequencing
Sanger sequencing is used to answer different molecular questions, such as the identification of bacteria and fungi in patient material or pure cultures, and the identification of mutations in specific genomic regions of interest in bacteria or viruses. In general, Sanger sequencing is used to investigate a short DNA sequence (± 500 bp) after amplification of the region of interest by PCR. After amplification, two different sequence reactions (forward and reverse) are performed and can be used to identify bacterial or fungal species based on the analyses of the sequenced 16S ribosomal DNA (rDNA) and 18S rDNA of the internal transcribed spacer (ITS) region, respectively [2].
One of the disadvantages of Sanger sequencing is that species identification in clinical materials containing more than one species is difficult, if not impossible. Furthermore, the costs and the labour needed for investigating multiple genomic regions of interest makes this method of limited use in modern clinical microbiology laboratories.
Next-generation sequencing (NGS)
NGS determines the whole genome sequence of different pathogens in one single sequencing run. This technology allows sample multiplexing and, thus, simultaneously provides genomic sequence information on diverse pathogens isolated from different patients. NGS also allows determination of microbial genomes in complex multi-species patient samples by shotgun metagenomics (third generation sequencing) [3]. In comparison to Sanger sequencing, NGS is a considerable improvement owing to the usage of one protocol for all pathogens [4]. A schematic overview of the general workflow used for the sequence analysis in the UMCG is shown in Figure 1.
Using NGS, the whole genome of a pathogen is sequenced in a random way. As benchtop next-generation sequencers can sequence DNA fragments between 100 and 1000 bases, the genome is fragmented before sequencing [5, 6]. Third generation sequencers are an exception to this, as they can handle larger fragments of over 200 kb [2]. NGS requires the preparation of libraries, in which fragments of DNA or RNA are linked to adapters and barcodes. At a later stage, this enables the identification of the sequenced fragments (reads) to the pathogens. After fragmentation, clonal amplification, normalization and a sequencing run is performed. For this, a robust preparation of libraries and standardized protocols are key [3].
Software for data analysis
A huge challenge for the introduction of NGS in a clinical setting is the data analysis. This requires specific software as well as scientific knowledge to interpret the results. There are, so far, only a few user-friendly software packages available to perform data analyses with little bioinformatics knowledge. However, the costs of these software packages is relatively high. However, there a numerous freely available software packages to answer different scientific questions, but knowledge of bioinformatics is often required [2].
After high-throughput sequencing, the reads can be assembled, either by mapping or de novo assembly [2]. Software packages, such as CLC Genomics Workbench (Qiagen), SPAdes and Velvet, can be used for assembly. The genetic relatedness between isolates can be investigated using a gene-by-gene approach using multi-locus sequence typing (MLST), core genome MLST (cgMLST) or whole genome MLST (wgMLST) using SeqSphere+ (Ridom), Bionummerics (Biomérieux), or online tools, such as Enterobase (https://enterobase.warwick.ac.uk) and BIGSdb (http://bigsdb.readthedocs.io). Currently, it is still a matter of debate how many alleles two genomes may differ by to call them genetically related. The same problem applies for comparing two genomes by single nucleotide polymorphism (SNP) typing.
There are a number of web-based tools to perform additional NGS analysis [2]. One of them is the website of the Centre for Genomic Epidemiology (www.genomicepidemiology.org) that can be used for the detection of resistance and virulence genes. Another web-based tool is the Rapid Annotation using Subsystem Technology (RAST) website (http://rast.nmpdr.org) for annotating bacterial genomes.
One of the advantages of web-based tools is that, in general, no knowledge of bioinformatics is necessary. However, a disadvantage may be the lack of tweaking the software settings while performing the analysis. In addition, it may be necessary to confirm the results obtained through web-based tools using other methods [2].
NGS in clinical microbiology
NGS is already applied in several medical microbiology laboratories where it is used for outbreak management, molecular case findings, characterization and surveillance of pathogens, for example [2].
Indeed NGS can be extremely useful in outbreak detection, by monitoring the evolution and dynamics of multi-drug resistant pathogens [7]. A number of studies have highlighted the effectiveness of WGS-based typing for assessing of (newly) emerging pathogens. In our hospital, NGS was used for the characterization of a newly emerging CTX-M-15 producing Klebsiella pneumoniae clone [8]. Transmission of this K. pneumoniae strain between patients has been traced using genomic phylogenetic analysis (Fig. 2). In addition, the study showed the usefulness of a unique marker PCR, in which a clone-specific PCR was developed to investigate the transmission between patients [4].
In addition to tracing and characterizing outbreaks, NGS can be used for the implementation of control measures to avoid the spread of resistance bacteria [9]. An outbreak of a colistin-resistant carbapenemase-producing K. pneumoniae (KPC) with inter-institutional spread in The Netherlands was identified and characterized using NGS and, partially based on these findings, controlled by transferring all positive patients to a separate location [9].
Furthermore, NGS data stored in databases can be used to search retrospectively for molecular case studies. A study from Bathoorn et al. showed that a New Delhi Metallo-?-lactamas-5 (NDM-5)-producing K. pneumoniae was isolated from a Dutch patient. Molecular case findings showed that the Dutch strain is clonally related to strains isolated from four Danish patients in 2014. There was no obvious epidemiological link between the cases in the Dutch and Danish hospitals [10].
These studies and many others highlight the importance of NGS in clinical microbiology. NGS can be used either as a highly discriminatory tool to discriminate between bacterial clones with specific features and to use the information for patient management, infection prevention and evolutionary studies [2] or to characterize bacterial isolates in more detail [8]. Furthermore, web-based databases can be in silico screened retrospectively for the presence of novel (antibiotic-resistance) genes.
Conclusion and outlook
Using NGS, one laboratory protocol can be used to generate sequencing data from samples obtained from different sources. After data analysis, information on the presence of virulence factors and antibiotic resistance genes, as well as other relevant genes are obtained. In addition, NGS makes it possible to standardize typing methods, although cut-off values regarding cgMLST, wgMLST and SNP analysis have to be established internationally in order to distinguish related or unrelated isolates and being able to compare results between laboratories. In the next few years, the role of NGS will surely increase in medical microbiology laboratories, both for research as well as for molecular diagnostic purposes, infection prevention and molecular-epidemiological investigations.
Nonetheless, improvement of the NGS workflow is still needed, focusing on easier and faster ways of library preparation, shorter run-times and further reduction in costs. Furthermore, automatic pipelines for data analyses and easy to use software have to be developed. In addition, the development of proficiency testing panels are important for external quality controls. Only with implementation of the above items at local, (inter)regional and international level will broad use of NGS be allowed in clinical microbiological laboratories for patient and infection control management, including defining a tailor-made antibiotic therapy for each patient, leading to personalized microbiology.
Acknowledgement
A full version of this work is published in the review ‘Application of next generation sequencing in clinical microbiology and infection prevention’, Journal of biotechnology 2017; 243: 16–24.
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2. Deurenberg RH, Bathoorn E, Chlebowicz MA, Couto N, Ferdous M, Garcia-Cobos S, Kooistra-Smid AM, Raangs EC, Rosema S, Veloo AC, Zhou K, Friedrich AW, Rossen JW. Application of next generation sequencing in clinical microbiology and infection prevention. J Biotechnol 2017; 243: 16–24.
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10. Bathoorn E, Rossen JW, Lokate M, Friedrich AW, Hammerum AM. Isolation of an NDM-5-producing ST16 Klebsiella pneumoniae from a Dutch patient without travel history abroad, August 2015. Euro Surveill 2015; 20(41).
The authors
Sigrid Rosema BSc; Ruud H. Deurenberg PhD; Monica A. Chlebowicz PhD; Silvia García-Cobos PhD; Alida C. M. Veloo PhD; Alexander W. Friedrich MD, PhD; John W. A. Rossen PhD, MMM
Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, The Netherlands
*Corresponding author
E-mail: j.w.a.rossen@rug.nl
Next-generation sequencing as a diagnostic tool in respiratory infections
, /in Featured Articles /by 3wmediaBackground
The term ‘acute respiratory tract infection’ (ARTI) encompasses a spectrum of conditions ranging from the common cold to pneumonia. Multiple organisms may infect the human respiratory tract, such as bacteria and fungi, but the majority of episodes are thought to be viral in origin [1]. The diagnosis of ARTI is made clinically but the lack of pathognomonic features means etiology cannot be determined clinically. Identifying causative organisms is challenging owing to the number of possibilities but is important for many reasons. In severe cases identification of an organism will guide therapeutics, although specific treatments for viral ARTI are generally limited to influenza. At the other end of the clinical spectrum identifying a viral cause in mild cases allows the physician to defer treatment with antibiotics and reassure the patient. This is an essential component of antimicrobial stewardship as high rates of antibiotic use are associated with circulating antimicrobial resistance [2]. The majority of antibiotic prescriptions issued in the UK are for respiratory tract infections [3] yet antibiotic use puts patients at risk of adverse drug reactions and in many cases will not lessen the duration of symptoms [4].
Respiratory infection diagnostics
Until recently viral diagnostics relied on cell culture or animal/egg inoculation. These time-consuming and laborious methods provided only a retrospective diagnosis and were, therefore, of little use in the management of acute infections. Nucleic acid amplification tests (NAAT), directly detecting the RNA or DNA of pathogens, have largely superseded these.
Many methods of RNA/DNA detection are available (Table 1). The most widely used is polymerase chain reaction (PCR). This has the benefit of rapid turnaround times and high levels of sensitivity and specificity in comparison to cell culture [5]. A pair of primers is required for each target but it is possible to use multiple primer sets within a single reaction (up to four) without compromising test sensitivity over the monoplex assay. This chemistry is now available as closed systems providing rapid results as a near-patient test (GeneXpert by Cepheid, Cobas by Roche).
Other examples of molecular NAATs which are available but not commonplace would be loop-mediated isothermal amplification (LAMP) and microarrays. LAMP detects nucleic acids but does not rely on thermocycling. It does, however, require multiple primers for each target (usually six) and as a consequence the sensitivity is more likely to be affected by genome mutations than standard PCR. This also makes multiplexing multiple targets within a single reaction more complicated.
Microarrays (also known as DNA chips or biochips) use a collection of oligonucleotide probes, about 70 bases in length, immobilized on a solid surface. The probes are complementary portions of DNA or RNA designed to match conserved regions of a genome; thus, if present, the target will bind to the corresponding probe which can then be quantified. Multiple probes may be attached to a single surface, screening for a large number of pathogens in a single reaction. As probes are targeted against conserved regions of the pathogen genome they may also detect related but novel pathogens.
To be used as a comprehensive diagnostic test numerous targets must be included to cover the likely pathogens. In the case of respiratory infections commercial assays are available with around 33 targets over 8 reactions [6]. Despite this approach a viral pathogen is detected in only a minority of specimens [7] and it remains the case that a pathogen will only be detected if actively sought.
Several significant respiratory viruses have been identified in recent years; those which may have circulated for many years, such as the human metapneumovirus, or emerging pathogens, such as SARS and, more recently, MERS. Whereas these are related to other known pathogens they are genetically distinct and, therefore, would evade detection with molecular methods.
What is next-generation sequencing?
The term ‘next-generation sequencing’ (NGS) refers to the practice of sequencing millions of DNA fragments in parallel. Numerous platforms are available to carry this out and the exact chemistry varies greatly between each. In practice, either all genetic material within a sample can be sequenced – metagenomics; or, hybrid capture allows a more focused approach to an area or genome of interest, this is termed ‘target enrichment’.
Advantages of NGS
Applying metagenomic NGS to clinical samples would allow an untargeted approach to identify all the genetic material contained within. This method has demonstrated potential for use in a diagnostic setting [8, 9].
The lack of pathogen targeting means that multiple pathogens can be detected without selection (Fig. 1), including novel or emerging or divergent pathogens. In the case of many viral pathogens evolution and mutations over time can reduce detection with specific PCR reactions. Mutations affecting primer binding sites may reduce binding affinity during the reaction and, for this reason, the performance of diagnostic assays must be monitored closely and at times altered. NGS could, therefore, be used as an adjunct in the quality control of PCR assays.
It is possible to detect full genome sequences from diagnostic samples and even with partial genome sequence it is feasible to subtype viral pathogens. Real-time knowledge of the circulating viral subtype is of particular importance in the management of influenza where this informs anti-viral choice, potential resistance and vaccine efficacy. This is currently carried out using additional PCR assays and Sanger sequencing, although this is not always possible in real-time.
Laboratory workflow
Currently the identification of rare or unusual pathogens using molecular methods necessitates samples to be batched to make the process cost effective; alternatively the test is centralized to a single laboratory to which samples must be sent. Either results in an increase in turn-around time. The use of NGS without any enrichment or targeting would permit samples to be treated in the same manner irrespective of type or likely pathogen.
Challenges
A major barrier in introducing NGS to the diagnostic setting is cost. Although the cost of NGS is decreasing rapidly it remains considerably more expensive than multiplex PCR. It is, therefore, unlikely to be cost effective to use this method for pathogen detection in non-severe infections for the time being. However, any cost–benefit analysis on introducing NGS to a diagnostic setting should also consider, on the positive side of the balance sheet, the likely savings NGS would offer in reductions to epidemiological and public health testing.
Complexity and turnaround time
Current methods of library preparation are complex requiring multiple user interventions and additional equipment to that found in a diagnostic laboratory with attendant implications for the time and cost of the process. To be carried out as a routine diagnostic assay these processes would need to be simplified and, ideally, automated to reduce hands-on time and the potential for contamination and human error.
The commonly used sequencing platforms take several hours or even days to generate sequence information. It should be noted that the third generation platforms that use single-molecule real-time (SMRT) technology are rapid and, as the name suggests, can be analysed in almost real-time.
Data analysis
Data analysis and storage is a major bottleneck in the NGS process. The computational power required for analyses would be beyond the current capabilities of diagnostic services. The methods used in data analysis pose a further challenge. Currently there is no agreed method as to the best approach for data analysis; indeed this is an entire specialty in itself, bioinformatics. Development of software programmes will both make the analysis more feasible in a diagnostic service to non-bioinformaticians and will lead to standardization of data processing.
Discussion
NGS undoubtedly has potential to dramatically change the landscape of infection diagnostics. Whether it will replace current molecular methods remains to be seen. The cost and complex sample processing remains prohibitive but these novel technologies are still in an exponential phase of development. Even current methodologies are yielding promising results in this field. The lack of pathogen targeting means that there is potential for a single work flow to be applied to all specimens, no matter what the syndrome which could even be extended to non-viral pathogens, resulting in a pan-microbial diagnostic test.
The generation of virus sequence as part of a diagnostic assay has substantial management and epidemiological benefits. In terms of respiratory infections this is currently limited to resistance testing and strain analysis of influenza. However, in the management of blood-borne viruses, particularly HIV and hepatitis C virus (HCV), point mutations and minor populations may impact greatly on the management and prognosis of patients. With the introduction of novel therapies or vaccines against viral respiratory infections NGS will have an even greater clinical benefit.
Acknowledgements
I would like to thank Dr Rory Gunson and Dr Emma Thomson for reviewing the manuscript.
References
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2. Linares J, Ardanuy C, Pallares R, Fenoll A. Changes in antimicrobial resistance, serotypes and genotypes in Streptococcus pneumoniae over a 30-year period. Clin Microbiol Infect 2006; 16(5): 402–410.
3. Lindbaek M. Prescribing antibiotics to patients with acute cough and otitis media. Br J Gen Pract 2010; 56(524): 164–166.
4. Butler CC, Hood K, Verheij T, Little P, Melbye H, Nuttall J, Kelly MJ, Mölstad S, Godycki-Cwirko M, Almirall J, Torres A, Gillespie D, Rautakorpi U, Coenen S, Goossens H. Variation in antibiotic prescribing and its impact on recovery in patients with acute cough in primary care: prospective study in 13 countries. BMJ 2009; 338: b2242.
5. van Elden LJ, van Kraaij MG, Nijhuis M, Hendriksen KA, Dekker AW, Rozenberg-Arska M, van Loon AM. Polymerase chain reaction is more sensitive than viral culture and antigen testing for the detection of respiratory viruses in adults with hematological cancer and pneumonia. Clin Infect Dis 2002; 34(2): 177–183.
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7. Nickbakhsh S, Thorburn F, von Wissmann B, McMenamin J, Gunson RN, Murcia PR. Extensive multiplex PCR diagnostics reveal new insights into the epidemiology of viral respiratory infections. Epidemiol Infect 2016; 144(10): 2064–2076.
8. Thorburn F, Bennett S, Modha S, Murdoch D, Gunson R, Murcia PR. The use of next generation sequencing in the diagnosis and typing of respiratory infections. J Clin Virol 2015; 69: 96–100.
9. Prachayangprecha S, Schapendonk CM, Koopmans MP, Osterhaus AD, Schürch AC, Pas SD, van der Eijk AA, Poovorawan Y, Haagmans BL, Smits SL. Exploring the potential of next-generation sequencing in detection of respiratory viruses. J Clin Microbiol 2014; 52(10): 3722–3730.
The author
Fiona Thorburn PhD
NHS Greater Glasgow and Clyde, Glasgow G12 0XH, UK
E-mail: Fionathorburn@nhs.net
Molecular detection and quantification of human rhinoviruses
, /in Featured Articles /by 3wmediaIntroduction
Human rhinoviruses (HRV) are small, positive-sense RNA viruses within the family Picornaviridae. Over 150 genotypes of this important human pathogen have been recognized within species HRVA, HRVB, and HRVC of the genus Enterovirus (http//:www.picornaviridae.com). HRV infections occur throughout the year and throughout the world. HRV are responsible for a high incidence and wide range of respiratory infections in all populations, including one-half to two-thirds of all common colds and many cases of otitis media and sinusitis in the upper respiratory tract. Lower tract infections include bronchiolitis, pneumonia and exacerbation of disease in children with asthma and cystic fibrosis, and in adults with chronic obstructive pulmonary disease. Cases of serious illness and even death due to HRV have been reported, especially in immunocompromised individuals, the elderly and infants [1, 2].
Laboratory detection of HRV is important for diagnosis and surveillance, especially in high risk populations. HRV are frequently detected as co-infections with other respiratory viruses and in individuals with long-term and asymptomatic shedding [3]. In addition to qualitative detection, accurate quantification of HRV RNA in clinical samples is needed for studies on the association of HRV viral load with viral transmission and with patient symptoms and outcomes. Viral-load studies of other respiratory viruses have shown that a correlation exists between quantity of virus and disease severity. HRV viral-load determinations may also be important for patient management, especially in asymptomatic patients who test positive for HRV at low levels. More importantly, accurate HRV viral-load assessments will be necessary for evaluating the performance of potential HRV antiviral drugs [4].
Detection
HRV were initially detected by growth in cell culture. Approximately 100 serotypes of HRV grown in cell culture were antigenically characterized by their reactions with various antisera. The serotypes were subsequently classified into two groups, A and B, according to their sensitivity towards antivirus agents [5] and are now included in HRV species A (80 genotypes) and B (32 genotypes) based on genetic sequencing. Cell culture is sensitive for detection of many, but not all HRV genotypes; 55 HRV that do not grow in the cell culture lines normally used in the clinical laboratory and have been detected only by molecular methods are classified in HRV species C (http//:www.picornaviridae.com).
The use of molecular methods for the detection of HRV in clinical specimens has provided more accurate information about the disease burden and epidemiology of these ubiquitous viruses. The molecular method most often used to detect HRV is real-time reverse-transcription (RT)-PCR [3]. RT-PCR assays, when accompanied by amplification of serially diluted standards of known RNA copy numbers (RT-qPCR), can be used to quantify the number of viral copies in a sample. By comparing the PCR Ct value (the PCR cycle at which fluorescence reaches a certain threshold) of a clinical specimen to the standard curve, the relative quantity of the analyte can be calculated [6].
Within the HRV genome, the region most frequently targeted for RT-PCR by clinical assays is the 5’ non-coding region (NCR), which exhibits the most sequence homology among the HRV genotypes. However, even in this region, there is a lot of sequence diversity, which makes it challenging to design a single, consensus PCR primer and probe set to amplify all HRV genotypes with equal efficiency. In order to amplify HRV genotypes with diverse sequences in the prime/probe binding regions, consensus PCR primer and probe sets have been designed with degenerate and modified bases or multiple oligonucleotides [7–10]. However, consensus RT-qPCR assays may not give accurate quantitative results for all HRV genotypes due to amplification inefficiency caused by base mismatches between the consensus primers and probe and the viral sequences [11].
Quantitation by RT-qPCR
To determine if a consensus RT-qPCR assay [7] could be used to accurately quantify all genotypes of HRV, including those with sequence differences in the primer and probe binding regions, we compared the efficiency and sensitivity of a consensus RT-qPCR assay to that of genotype-specific RT-qPCR assays [4]. In Figure 1(a), the results of RT-qPCR assays using type-specific primers and probes, which exactly match the target sequences, show standard curves indicating accurate and sensitive quantification of RNA transcripts from six specific HRV genotypes. However, RT-qPCR using a consensus HRV primer and probe set did not give accurate or sensitive quantification for some HRV genotypes, especially types A33 and A88 (Fig. 1b). RNA from HRV genotypes with base mismatches between the consensus primer and probe sequences and the specific viral sequences was inaccurately quantified using the consensus assay, most likely due to poor amplification efficiency.
Quantitation by RT-dPCR
Digital RT-PCR (RT-dPCR), which provides absolute nucleic acid quantification without the need for PCR Ct values and standard curves and is less affected by poor amplification efficiency, may perform better than RT-qPCR for quantification of HRV RNA. In dPCR, an amplification reaction, which contains fluorescent dye to measure amplification, is divided into 12?000 to 200?000 independent partitions, each ideally containing no more than one target molecule. The reaction is amplified to end point and the number of fluorescent (positive) and non-fluorescent (negative) partitions is counted. In specimens with more targets than partitions, Poisson statistics are used to calculate the average number of targets per positive partition and thus, the number of targets in the original sample [12, 13]. Compared to qPCR, dPCR is less susceptible to amplification inefficiency caused by primer/probe sequence mismatches because quantification derives from a PCR reaction that cycles to endpoint rather than from an amplification curve as in qPCR. Accurate quantification by dPCR is also not dependent on a well-calibrated standard [14]. These characteristics make dPCR especially useful for quantifying viral targets with many subtypes and high sequence diversity that leads to mismatches between targets and PCR primer and probe sequences, such as HRV.
To determine if consensus RT-dPCR would perform better than consensus RT-qPCR for quantification of HRV genotypes, we similarly tested RNA transcripts of HRV genotypes, including some with sequence variation in the consensus primer and probe binding region, by RT-dPCR using both type-specific and consensus primers and probes. In Figure 2(a), the results of RT-dPCR assays using type-specific primers and probes show good correlations between the expected number of RNA copies/reaction and the observed number. When amplified by RT-dPCR using the consensus assay (Fig. 1b), in contrast to RT-qPCR, the observed number of RNA copies/reaction was also closely correlated with the expected number for most of the HRV genotypes tested.
In a previous study [4], data from 16 HRV genotypes that represented the consensus primer and probe binding sequences of 128 genotypes indicated that, when using consensus primers and probe, RT-dPCR quantification of HRV RNA was more accurate than that of RT-qPCR for some genotypes. We found that although the consensus RT-qPCR did accurately quantify many HRV genotypes, it did not accurately quantify all genotypes of HRV due to sub-optimal amplification of genotypes with sequences that do not exactly match those of the primers and probe. Consensus RT-dPCR, however, did not overcome all sequence mismatch-induced amplification inefficiency, as evidenced by genotype A88 (Fig. 2b), which has a single mismatch near the middle of the forward primer.
Although RT-dPCR has been shown to be more accurate than RT-qPCR for quantification of HRV and may be applicable to other viruses with high sequence diversity, like HIV and HBV, it has some disadvantages for routine use in a clinical laboratory. RT-dPCR has a more limited dynamic range compared to RT-qPCR (104 for RT-qPCR compared to 108 for RT-qPCR), which would require dilution and retesting of samples with high viral loads. Running an RT-dPCR assay requires more hands-on technician time and has a lower throughput than current RT-qPCR assays. Digital PCR instruments and reagents are also currently more expensive than most qPCR systems.
Conclusion
In conclusion, dPCR was a better alternative to qPCR on RNA templates known to have significant sequence diversity that cannot be avoided during primer and probe design and should be considered the better molecular method for quantification of HRV in respiratory specimens.
References
1. Brownlee JW, Turner RB. New developments in the epidemiology and clinical spectrum of rhinovirus infections. Curr Opin Pediatr 2008: 20: 67–71.
2. Gern JE. The ABCs of rhinoviruses, wheezing, and asthma. J Virol 2010: 84(15): 7418–7426.
3. Mackay IM. Human rhinoviruses: The cold wars resume. J Clin Virol 2008: 42: 297–320.
4. Sedlak RH, Nguyen T, Palileo I, Jerome KR, Kuypers J. Superiority of digital RT-PCR over real-time RT-PCR for quantitation of highly divergent human rhinoviruses. J Clin Microbiol 2017; 55(2): 442–449.
5. Andries K, Dewindt B, Snoeks J, Wouters L, Moereels H, Lewi PJ, Janssen PA. Two groups of rhinoviruses revealed by a panel of antiviral compounds present sequence divergence and differential pathogenicity. J Virol 1990: 64: 1117–1123.
6. Mackay IM, Arden KE, Nitsche A. Real-time PCR in virology. Nucleic Acids Res 2002: 30: 1292–1305.
7. Lu X, Holloway B, Dare RK, Kuypers J, Yagi S, Williams JV, Hall CB, Erdman DD. Real-time reverse transcription-PCR assay for comprehensive detection of human rhinoviruses. J Clin Microbiol 2008: 46(2): 533–539.
8. Granados A, Luinstra K, Chong S, Goodall E, Bahn L, Mubareka S, Smieja M, Mahony J. Use of an improved quantitative polymerase chain reaction assay to determine differences in human rhinovirus viral loads in different populations. Diagn Microbiol Infect Dis 2012: 74: 384–387.
9. Tapparel C, Cordey S, Van Belle S, Turin L, Wai-Ming L, Regamey N, Meylan P, Mühlemann K, Gobbini F, Kaiser L. New molecular detection tools adapted to emerging rhinoviruses and enterviruses. J Clin Microbiol 2009: 47(6): 1742–1749.
10. Bochkov YA, Grindle K, Vang F, Evans MD, Gern JE. Improved molecular typing for rhinovirus species A, B, and C. J Clin Microbiol 2014: 52(7): 2461–2471.
11. Hoffman NG, Cook L, Atienza EE, Limaye AP, Jerome KR. Marked variability of BK virus load measurement using quantitative real-time PCR among commonly used assays. J Clin Microbiol 2008: 46(8): 2671–80.
12. Vynck M, Trypsteen W, Thas O, Vandekerckhove L, De Spiegelaere W. The future of the polymerase chain reaction in virology. Mol Diagn Ther 2016: 20: 437–447.
13. Huggett JF, Cowen S, Foy CA. Considerations for digital PCR as an accurate molecular diagnostic tool. Clin Chem 2015: 61: 79–88.
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The author
Jane Kuypers PhD
Department of Laboratory Medicine, University of Washington, Seattle, WA, USA
Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
E-mail: kuypers@uw.edu
Diagnosis of respiratory tract infections caused by human bocavirus 1
, /in Featured Articles /by 3wmediaHuman bocavirus 1 (HBoV1), a small single-stranded DNA (ssDNA) virus belonging to the Parvoviridae family, was described for the first time in 2005 [1]. Its genome replication is dependent on the formation of double-stranded DNA (dsDNA) intermediates in the nucleus of the host cells. The dsDNA serves as template for transcription of messenger-RNA (mRNA) by the host replication machinery. The mRNA is further translated into viral proteins, such as structural VP2 protein. Structural proteins assemble as empty capsids into which genomic ssDNA is inserted. Thus, during acute infection, the replicating virus produces mRNA transcripts from the viral dsDNA which are translated into viral proteins. Formation of viral proteins and particles are essential for the multiplication and spread of viable viruses.
Epidemiology and clinical outcomes of HBoV1 infections
HBoV1 was originally discovered in hospitalized children with a respiratory tract infection (RTI) [1]. However, HBoV1 can cause RTI illnesses in varying severities. Mainly children at age 6–24 months are affected. By 6 years old almost all children are seropositive for HBoV1. Data on the disease pressure in adults are very scarce but apparently immunity lasts long and acute infections are rare. HBoV1 DNA is detected by PCR in 2–19% of patients with RTI worldwide. The most common symptoms of acute HBoV1 infection are common cold-like complaints, wheezing, bronchiolitis and pneumonia. HBoV1 is associated with asthma exacerbations [2]. Diagnostic positivity rate for HBoV1 has been high in some studies in summer [3]. This would differ from other RTI viruses like influenza and respiratory syncytial virus. However, most cases of HBoV1 DNA detection are reported in winter and spring [2] which may also be linked to the higher frequency of diagnostic testing during the influenza season.
HBoV1 may infect lower airways down to the bronchioles [2]. There has been no difference in HBoV1 prevalence between immunocompetent and immunocompromised patients [2]. It seems that that particularly young children who were born prematurely may be at risk in developing severe RTIs caused by HBoV1 [4, 5].
HBoV1 DNA is often found in stool samples from children. However, detection rates are similar among subjects with or without acute gastroenteritis. Also co-findings with other known gastroenteritis viruses are common. Thus, the detection of HBoV1 from stool is most probably rather a sign of respiratory tract or systemic infection, prolonged viral shedding or persistent infection than acute gastroenteritis [6].
Diagnostic methods and challenges in diagnosis of HBoV1 infections
HBoV1 infection cannot be accurately diagnosed based on clinical symptoms alone. There are four techniques to aid in the diagnosis of HBoV1 infections. These include serology [7], PCR using viral DNA as target [8], reverse transcription (RT) PCR using viral mRNA as target [9], and most recently antigen detection [10]. Also electron microscopy has been used to detect the presence of viral particles [5], although this technique is not suitable for routine diagnostics.
Serology can provide information as to whether the infection is acute or past and it can be used to confirm the findings of other methods. IgM positivity, low IgG avidity, seroconversion or a diagnostic (?4-fold) increase in the IgG level in paired sera are signs of acute HBoV1 infection [2, 7]. A major drawback of serology is that it takes the human body 1–2 weeks to produce the antibody.
A number of commercially available multiplex PCR tests have included the detection of HBoV1 DNA in their test panels and some of the tests may provide results also in stat labs. However, detection of viral DNA from nasal samples may have little clinical significance since HBoV1 DNA is frequently (10–40 %) detected in asymptomatic controls and often found as co-findings (50–70 %) with other respiratory viruses. Prolonged shedding of the virus from infected shells, or long-term presence of virus or viral DNA in the airways may explain the high co-infection rate and prevalence in asymptomatic controls observed in almost every DNA PCR cohort study [11–14]. Currently, the mechanism for persistence is unknown but one possible explanation may be that the virus exists in a latent phase where the transcription of mRNA and protein translation is inhibited by the immune system.
Quantification of viral DNA by Ct-value gives a statistical correlation with severity but is not diagnostic in individual cases owing to, for example, the semi-quantitative nature of sampling. Thus, high viral DNA load and single findings are only indicative of the etiology [3, 8]. Extensive exclusion of the presence of other potential RTI pathogens together with high genome HBoV1 DNA load as single finding, viremia or the presence of the DNA in normally sterile body fluids has shown causality [4, 5]. Instead of extensive exclusion of other RTI viruses with high-cost multiplex PCRs, direct detection of actively replicating HBoV1 viruses by mRNA PCR or an antigen test could be a more straightforward, specific and cost-efficient approach.
mRNA RT-PCR methodology was developed to specifically detect the acute HBoV1 infections before the rise in antibody levels. mRNA RT-PCR is analytically as sensitive as DNA PCR. It provides the same clinical sensitivity but higher diagnostic specificity than DNA PCR. In one HBoV1 case, mRNA was detected up to 10 days from the onset of the symptoms while the DNA was detected at least up to 2 months although the patient was already fully recovered. The time span for positivity based on the mRNA RT-PCR correlated better with acute symptoms than DNA PCR [9].
Serology, mRNA RT-PCR and DNA PCR suffer from being slow, costly and/or labour intensive techniques, and they are only available in highly specialized diagnostic laboratories. Detection of viral antigens (e.g. structural VP2 protein) from nasal samples provides a rapid and specific alternative for testing of acute HBoV1 infections (Fig. 1). Recently the first HBoV1 antigen test, to our knowledge, was introduced into the automated and multianalyte mariPOC respi test (www.arcdia.com). The test provides most of the positive results in 20 minutes and low positives in 2 hours at the point-of-care. The new test has shown similar clinical specificity compared to mRNA RT-PCR test [15]. Antigen testing is feasible only during the acute phase of the infection (active viral replication phase) which seems to be approximately 5 days from the emergence of symptoms [10], as for most of the RTI viruses. The first days are often the most crucial when making clinical decisions and have impact, for example, for the decision on whether to prescribe antibiotics or not. The features of HBoV1 diagnostic methods are compared in Table 1.
Selected diagnostic cases
Case 1
A previously healthy full-term born Finnish girl developed symptoms of rhinorrhea, cough and high fever at 5 months of age. Upper RTI with no lower respiratory tract involvement or signs of otitis was diagnosed. HBoV1 secretion into nasopharyngeal samples was monitored by quantitative mariPOC antigen test up to day 5. Virus peak was at day 3 and viral levels were low at day 5, which coincided with the recovery of symptoms on day 6 [10]. The virus peak sample was estimated to contain 2×1010 viral particles per mL.
Case 2
A prematurely (week 27) born Turkish girl, at 5 months of age, after sepsis, developed high fever, wheezing and was treated for acute bronchiolitis before hospital discharge. The patient was found deceased the same night as the result of respiratory failure caused by pulmonary infection. HBoV was detected as single finding from nasopharyngeal swabs, stools and lung tissues [4].
Case 3
A prematurely (week 25) born Slovene child, at the age of 18 months, with chronic respiratory insufficiency was hospitalized. HBoV1 DNA was detected in tracheal aspirate (2.6×1010 copies/mL), in the nasopharyngeal swab (8.27×106 copies/mL), and in plasma sample (7.42×106 copies/mL). The presence of HBoV1 particles was confirmed by electron microscopy from tracheal aspirate and autologous plasma, which was taken the third day of illness [5].
Conclusions
As demonstrated above, clinical manifestations of HBoV1 range from simple common cold symptoms to fatal respiratory illnesses. Diagnosis of HBoV1 is now significantly more straightforward because of the recent advances in HBoV1 diagnostics. Rapid antigen testing and mRNA RT-PCR provide accurate non-invasive diagnostics for acute HBoV1 infections. mRNA RT-PCR is so far only available in highly specialized diagnostic laboratories while rapid antigen test is applicable at point-of-care. DNA PCR may be most suitable for the detection of viral DNA from body parts, like cerebrospinal fluid during suspected systemic infection. The use of multiple diagnostic methods will provide a more accurate picture about the clinical significance and outcomes of the HBoV1 infections. The method of choice for accurate diagnosis of HBoV1 depends on the elapsed time since the onset of the symptoms, clinical signs and other clinical or research needs. There is no specific medication or vaccine for HBoV1 yet. However, the new diagnostic tests will increase our understanding about the clinical significance of HBoV1 and open new doors for therapy development.
References
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The authors
Juha M. Koskinen*1,2 MSc, Andrea Bruning3 MD, Petri Susi4 PhD and Janne O. Koskinen2 PhD
Directorate of Laboratory Medicine and Pathology, Royal Hospital, Muscat, Oman
1Turku Doctoral Programme of Molecular Medicine, Department of Virology, University of Turku, Turku, Finland
2ArcDia International Oy Ltd, Turku, Finland
3Department of Pediatric Infectious Diseases, Emma Children’s Hospital, Academic Medical Center (AMC), Amsterdam, The Netherlands.
4Department of Virology, University of Turku, Turku, Finland
*Corresponding author
E-mail: jumako@utu.fi
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