Using Next-Generation Sequencing for Infectious Disease Research – Understanding Microbial Pathogens from Within

Cara N. Wilder, Ph.D.

Ever since James Watson and Francis Crick derived the double-helix model for the structure of DNA in 1953, the field of genomics has exponentially burgeoned into a vast array of molecular technologies. Of the current assortment of available genomic tools, next-generation sequencing (NGS) has proven to be of great value, particularly in the field of infectious disease. Here, the knowledge of DNA and RNA sequences has become indispensable for a variety of applications, including microbial identification and detection, evaluating the evolution and regulation of virulence, identifying drug resistance markers, detecting antigenic targets for vaccine development, and delineating community outbreaks.

NGS technologies are typically described as non-Sanger-based high-throughput DNA sequencing platforms that enable the analysis of millions of DNA fragments in parallel¹. This ability to multiplex provides unprecedented scalability and has contributed to a gradual reduction in reagent costs, allowing whole-genome sequencing (WGS) to become accessible and practical to researchers around the world. Over the last decade, a number of platforms and methods have been developed that enable de novo sequencing, re-sequencing, transcriptome profiling, and cDNA sequencing.

In the field of infectious disease, NGS affords a means for reviewing the complete genetic make-up of microbial pathogens through de novo sequencing or re-sequencing, regardless of the fastidious or non-fastidious nature of the strain. This ability to review an entire genome, or individual genes or operons, provides a unique opportunity for clinical diagnostics, the identification of potential antigenic targets for vaccine development, and epidemiological surveillance. Currently, the diagnosis of microbial infections typically begins with patient observation and the collection of specimens for microbiological processing for various diagnostic tests. Depending on the causative agent, these diagnostics tests may include serology and analyzing specimens for the presence of immune cells via microscopy. For some bacterial infections, culture-based growth techniques, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), and polymerase chain reaction (PCR) are also used for microbial identification and analysis. If employed, NGS could potentially be used to identify a pathogen without prior knowledge of the target, as well as discern the presence of any virulence determinants or genes conferring drug resistance^2-4. In turn, this would provide an additional clinical tool that may help patients receive a more precise diagnosis and efficient treatment regimen.

In addition to clinical diagnostics, NGS offers a potential tool for vaccine development and evaluation. For example, NGS can allow for the surveillance of pathogen evolution. For rapidly mutating pathogens such as the influenza virus, this could provide an opportunity to help identify antigenic drift within the microbial population and use that knowledge to create a better, more specific vaccine. NGS could also be used for reverse vaccinology, where pathogen sequences are used to identify putative surface antigens that could potentially be targeted for the development of a novel vaccine preparation⁴. In accordance with this latter application, the expression of the putative surface antigens can also be examined through the evaluation of RNA sequences during different stages throughout the pathogen life cycle. As some strains require more than one species for survival and replication, analyzing RNA expression can help ensure that the vaccine target is actively expressed in the human host to ensure an efficient immunological response. Lastly, NGS could be applied in vaccine safety analyses by detecting the presence of viral contaminants in cell culture used in vaccine development or identifying virulent mutations in live-attenuated vaccines prepared with highly pathogenic, genetically unstable strains prior to the use of the vaccine^5,6. Overall, NGS could help contribute to the development of safer vaccines that provide a more effective immune response.

Lastly, NGS is gradually being employed in the epidemiological analysis of cultures for outbreak detection and infection control. Using genomics, outbreak strains have been identified at the species level and below with extraordinarily high resolution. Through the analysis of these strains, population genetic studies can contribute to a better understanding of important genetic markers among strains while also tracking transmission events during outbreaks. In turn, this allows for the development of a tailored control program to help limit the further spread of disease⁷. A recent example of the use of NGS in epidemiological surveillance was during the analysis of a 2011 hospital outbreak of methicillin-resistant Staphylococcus aureus (MRSA)⁸. Here, WGS was used to identify hospitalized infant patients infected with MRSA and determine the source of transmission. Through this study, 26 related cases of MRSA were identified and it was demonstrated that transmission occurred within the hospital between mother and patient, among mothers on a postnatal ward, and in the community. Moreover, WGS confirmed that MRSA carriage by a staff member allowed the outbreak to persist during periods of no known infection. Overall, this study demonstrated that NGS technology enabled a more precise identification of patients involved in an outbreak, allowing for the implementation of an effective infection control program that helped halt the spread of disease.

Despite the numerous advantages of NGS in the analysis of infectious diseases, there are a few challenges that may need to be overcome. For example, for NGS data to be reliable, particularly with regard to re-sequencing and microbial identification, it is important that validated sequence data is readily accessible. Well-renowned sequence databases (e.g. GenBank) provide an annotated collection of publically available genome sequences from authenticated type strains, such as those obtained from prominent biological resource centers like ATCC. As type strains are the nomenclatural origin of a species or subspecies, they are typically fully authenticated and exhibit all of the relevant phenotypic and genotypic properties described in original taxonomic circumscriptions, making them ideal reference standards for NGS. Extensive bioinformatics to analyze sequences from assembly to annotation, which necessitates expertise and time, could pose another challenge for NGS clinical use. This can be potentially circumvented through the development of automated tools for sequence analysis combined with the assemblage of exhaustive databases containing all known genome sequences³. Lastly, there is the possibility that host DNA will be analyzed alongside microbial nucleic acids, which may make it difficult to discern the target genomics. To overcome this, the microbial to host nucleic acid ratio must be increased through procedures such as hydrolysis or chemical treatment⁴.

In conclusion, clinical microbiology laboratories face a number of challenges regarding the diagnosis and effective treatment of infectious diseases. NGS could provide an additional insight to aid in clinical diagnostics while offering an effective mechanism for the identification of potential vaccine targets and a way to track outbreaks. Only through continual efforts in the advancement of this technology can NGS become fully ingrained in the field of infectious disease as a routine diagnostic tool.

References

1. Nature. Next-generation sequencing – Definition. http://www.nature.com/subjects/next-generation-sequencing, 2015. 
2. Wain J, Mavrogiorgou E. Next-generation sequencing in clinical microbiology. Expert Rev Mol Diagn 13(3): 225-227, 2013. 
3. Fournier PE, et al. Modern clinical microbiology: new challenges and solutions. Nat Rev Microbiol 11: 574-585, 2013. 
4. Lecuit M, Eloit M. The diagnosis of infectious disease by whole genome next generation sequence: a new era is opening. Front Cell Infect Microbiol 4: 25, 2014. 
5. Luciani F, et al. Next generation deep sequencing and vaccine design: today and tomorrow. Trends in Biotechnology 30(9): 443-452, 2012. 
6. Neverov A, Chumakov K. Massively parallel sequencing for monitoring genetic consistency and quality control of live viral vaccines. Proc Natl Acad Sci 107(46): 20063-20068, 2010. 
7. Tang P, Gardy JL. Stopping outbreaks with real-time genomic epidemiology. Genome Med 6(11): 104, 2014. 
8. Harris SR, et al. Whole-genome sequencing for analysis of an outbreak of methicillin-resistant Staphylococcus aureus: a descriptive study. Lancet Infect Dis 13(2): 130-136, 2013.