Next-Generation Sequencing and Infectious Diseases

by Stephen E. Fry, MS, MD

Fry Laboratories, LLC

Scottsdale, Arizona

Introduction

Next-generation DNA sequencing: what does that mean and why would we use it?

Next-generation DNA sequencing (NGS) is a fairly new method for sequencing DNA segments in large numbers at a relatively low cost. NGS is considered by many as the second generation of DNA sequencing technologies and is sometimes referred to as massively parallel sequencing (MPS) due to the central technological advantage over the first-generation methods. It is useful for rapid and accurate characterization of nucleic acids sequences in living things. Application of NGS to infectious disease research and diagnostics will be significant for its use in rapid and accurate pathogen determination in viruses, bacteria, and protozoa.

Current clinical microbiological identification strategies generally rely on older technologies that have been in use for decades. One such technology is microbial culture, often used as a primary enrichment step that may take days. Culture, and by extension the majority of medical microbiology, assumes that a disease-causing bacterium is cultivatable. Nonculturable organisms may be entirely missed as an etiologic agent.^1–4 while emerging or unique organisms could easily be misidentified.¹ Traditional alternative technologies include microscopy, serology, and, more recently, molecular-based assays. Molecular technologies commonly rely upon the amplification of pathogen specific DNA for detection. These tests are exceptionally sensitive; however, they can only detect a limited number of organisms or genetic variants. Recently, it is becoming increasingly clear that the majority of bacteria are fastidious (i.e., uncultivatable) and present in polymicrobial communities. The true impact of uncultivable bacteria in medicine is likely significantly underestimated in addition to the ever increasing need for more rapid diagnostic methods. These concepts have not gone unrecognized, and use of rapid culture-independent diagnostics has recently gained scientific and medical attention.

To address these challenges, a number of rapid microbial detection and identification systems have or are being developed. For cultured isolates, new protein based diagnostics such as matrix-assisted laser desorption/ionization time-of-flight (MALDI TOF) mass spectroscopy systems have been approved in Europe, with approval pending in the US. Bruker and BioMérieux have MALDI TOF systems that show promise. The IRIDICA system (previously named IBIS 5000) by Abbott is a rapid MALDI TOF mass spectroscopy PCR system and has been approved for use in Europe. Lastly, a number of point-of-care PCR based systems are available, with the BioFire system representing one the most recent obtaining FDA approval. Generally, these systems require an initial culture step, rely on a limited reductionist approach, or have limited throughput.

Application

The diagnostic “holy grail” for both microbiologists and clinicians is an all-inclusive molecular approach that can be used in both acute and chronic infectious diseases. This perspective was reinforced at both the American Society of Microbiology and American Association of Clinical Chemistry conference meetings last summer. This view was again reiterated at the First ASM Conference on Rapid Next-Generation Sequencing and Bioinformatic Pipelines for Enhanced Molecular Epidemiologic Investigation of Pathogens last September. These emerging technologies and systems for infectious disease detection are rapidly becoming a reality.

Chronic diseases are also of great interest and represent an immense region of investigation. Examples of such diseases include chronic Lyme disease, chronic wounds, irritable bowel syndrome (IBS), sepsis, dental abscesses, chronic inflammatory disease, and fevers of unknown origin (FUO). Microbial involvement in these illnesses have been established or are suspected. Additionally, research suggests that these systems could have great relevance in the chronic inflammatory disease arena.

The application of molecular-based technology was well represented in recent Lyme disease research.⁵ This epidemiologic study of ticks in the San Francisco Bay Area utilized molecular-based approaches to assay for Borrelia species. This study demonstrated that 8.1% of the adult ticks harbor a Borrelia species and 1.8% have an emerging species, B. miyamotoi. This identification was made based on comparative sequence analysis and not by a matching control standard. In other words, the sequenced organism matched that of the textbook B. miyamotoi strain. Historically the “gold standard” for Borrelia detection has been antibody detection. Of course, these serologic techniques have limitations, such as antigenic cross-reactivity by of a related, or sometimes distantly related, species. In sum, identification based on sequence identity in most cases is now considered a gold standard and is sufficient for detection and identification purposes.

Another rapidly expanding application of NGS-based methods is in stool microbiome analysis. NGS can allow for a comprehensive sequence based approach to studying and characterizing the plethora of bacteria in a patient’s digestive system. Few systems currently exist that can accurately process samples and generate true enterotype results as most use culture or multiplex PCR which can miss a number of important organisms. Furthermore, current methods suffer from severe limitations for the detection and identification of eukaryotic organisms including both protozoa and fungi.

Future iterations of diagnostics will rely heavily on molecular based technologies as they offer speed, inclusivity, and unparalleled accuracy. It is fortunate that these advantages are now being applied to infectious diseases enabling culture independent methods.^3,4,6–34 These emerging diagnostic systems will share certain analysis methods that combine shared processing and bioinformatics processing pipelines.

System

The majority of NGS-based approaches will likely include similar steps:

1. 

   Point of Care Sampling

   : Infected tissues, material, and/or fluid samples may be submitted for analysis. Proper collection techniques should be used to minimize contamination of the sample by nontargeted microbial populations. Blood draw sites should be cleaned thoroughly with disinfectants to remove potentially contaminating microbial DNA and cells. Tissue samples should be collected using aseptic techniques.

2. Nucleic Acid Extraction

   : Nucleic acid (DNA or RNA) content is then purified from the samples believed to contain the microbes. In the case of RNA it is converted into cDNA prior to sequencing.

3. Molecular Tagging and Amplification

   : The patient derived DNA/cDNA is then prepared by fragmenting the full length DNA into shorter segments compatible with sequencing. These fragments are often tagged with identifying sequences to allow for multiple samples to be pooled together. The subsequent DNA pool is then ready for NGS.

4. Next-Generation DNA Sequencing

   : Millions of digital DNA reads are produced by the NGS. The main NGS platforms include Illumina, Oxford-Nanopore, Thermo Fisher’s Ion Torrent, and PacBio systems.

5. Bioinformatics Analysis

   : Software is used to sort and categorize the sequences depending on the intended down-stream use. Human DNA sequences are often removed from analysis to allow for focused processing of possible infectious agents. Analysis often utilizes heavy computational analysis to identify or recreate the genetic material of nonhuman organisms in the sample.

RIDI (Rapid Infectious Disease Identification)

Our laboratory has developed a metagenomic testing method that uses direct DNA sequencing and computational analysis to enable the detection, identification, and in the case of novel or divergent organisms, the identification of the nearest characterized microbial species. According to experts at the recent American Association of Clinical Chemistry (AACC) meetings, we are the first to enter the commercial marketplace of rapid NGS infectious disease diagnostics. This stands in stark contrast to the myriad of current indirect testing technologies; including serology, T-cell stimulation assays, and ELISA. Furthermore, this method allows us to provide a relative measure of the bacterial, protozoal, or fungal contribution and diversity within a given sample. In summary, this method aims to identify the genetic composition and diversity across all microbes in a sample, simultaneously.

Our laboratory uses the Ion Torrent PGM system, clinically regulated methods, proprietary reagents, and in-house bioinformatics analysis to identify and survey the organisms of an unknown or polymicrobial infection. We call this system the Rapid Infectious Disease Identification system, or RIDI. It is important to note that the RIDI bioinformatics system has proven compatibility across other NGS systems including the Illumina and PacBio platforms. By using direct DNA sequencing from the Ion Torrent PGM coupled with computational analysis, we can identify or match a detected organism to the nearest microbial relative in a given clinical sample. Furthermore, this method allows us to provide a relative measure of the microbial contribution and diversity within a given sample. Fry Laboratories believes that wider adoption of this test in clinical use will have far reaching implications by not only providing superior, unbiased, sequence based diagnosis, but also by reducing patient mortality, morbidity, length of stay, and associated hospital and healthcare costs. This test is currently offered worldwide and is performed as a Laboratory Developed Test (LDT) in our CLIA regulated diagnostics laboratory.

Validation of Next-Gen Systems, or, How Well Do These Systems Work?

NGS manufactures and industry experts agree there is need for comprehensive validation and standardized control procedures in the NGS diagnostics field. Our Pan-Bacterial Metagenomics assay by RIDI has successfully and repeatedly sequenced Borrelia burgdorferi and several Bartonella species standards from the American Type Culture Collection (ATCC). Additionally, this assay has an ever increasing list of validated and control ATCC species and taxonomic groups that include Acholeplasma laidlawii, Acinetobacter baumannii, Bacillus cereus, Bartonella bacilliformis, Bartonella henselae, Bordetella pertussis, Borrelia burgdorferi, Capnocytophaga gingivalis, Clostridium difficile, Enterococcus faecalis, Escherichia coli, Gemella haemolysans, Haemophilus influenzae, Klebsiella pneumoniae, Legionella pneumophila, Mycoplasma arthritidis, Mycoplasma fermentans, Mycoplasma genitalium, Mycoplasma hominis, Mycoplasma pneumoniae, Ralstonia solanacearum, and others.

Our laboratory has undertaken the mapping of bacterial, protozoa, fungi, and simple eukaryotic populations in a variety of sample types including stool, blood, joint fluid, abscess, cerebrospinal fluid, bone, and tissues. This is especially true in certain disease states such as IBS, chronic fatigue syndrome (CFS), Lou Gehrig’s disease, multiple sclerosis, atherosclerosis, and prostate cancer. Figure 1 displays a typical report in a patient with IBS. Of note is the identification of pathogenic Shigella spp. when simple multiplex PCR and culture techniques had failed. Our ongoing research with next-gen detection systems has allowed us to verify a variety of aquatic “parasite’s” in humans. Figure 2 displays a typical result in a patient with CFS. We currently are developing a collaborative relationship with the Los Alamos National Research Laboratory investigating and documenting the presence of advanced microbes in chronic disease.

Summary

NGS systems will not replace culture systems in the near term, but it is likely that this technology will become a mainstay in the clinical microbiology arena with culture, microscopy, and serology serving as an adjunct. Eventually NGS systems will most likely replace both standard and quantitative PCR. Microscopy, serology, and emerging metabolomics will play a role in organism detection and identification; however, there is general agreement that NGS systems will dominate the infectious disease arena this decade.

Example Reports

Figure 1: Photo Stool RIDI-IBS

An example of an application is rapid stool metagenomics here showing the enterotype distribution and the actual breakdown of bacteria present. This is by technique more comprehensive than multiplex PCR.

Figure 2: Photo Blood RIDI CFS

An example is a report on a patient with CFs showing the results of eukaryotic

(protozoal and fungal) assessment.

Declarations

Dr. Fry owns and directs Fry Laboratories LLC, a clinical diagnostics laboratory, and is a central developer of the RIDI system.

Acknowledgements

I would like to thank Dr. Jeremy Ellis for review of this manuscript.

Notes

1. Brouqui P, Raoult D. Endocarditis due to rare and fastidious bacteria. Clin Microbiol Rev. 2001;14(1):177–207.

2. Singh S et al. Axenic culture of fastidious and intracellular bacteria. Trends Microbiol. 2012;21(2):92–99.

3. Bruneval P et al. Detection of fastidious bacteria in cardiac valves in cases of blood culture negative endocarditis. J Clin Pathol. 2001;54(3):238–240.

4. Levy PY, Fenollar F. The role of molecular diagnostics in implant-associated bone and joint infection. Clin Microbiol Infect. 2012;18(12):1168–1175.

5. Salkeld DJ et al. Disease risk & landscape attributes of tick-borne Borrelia pathogens in the San Francisco Bay Area, California. PLoS One. 2015;10(8):e0134812.

6. Biswas S, Rolain JM. Use of MALDI-TOF mass spectrometry for identification of bacteria that are difficult to culture. J Microbiol Methods. 2012;92(1):14–24.

7. Claesson MJ et al. Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions. Nucleic Acids Res. 2012;38(22):e200.

8. Junemann, S et al. Bacterial community shift in treated periodontitis patients revealed by ion torrent 16S rRNA gene amplicon sequencing. PLoS One. 2012;7(8):e41606.

9. Pattison SH et al. Molecular detection of CF lung pathogens: Current status and future potential. J Cyst Fibros. 2012.

10. Whiteley AS et al. Microbial 16S rRNA Ion Tag and community metagenome sequencing using the Ion Torrent (PGM) Platform. J Microbiol Methods. 2012;91(1):80–88.

11. Yergeau E et al. Next-generation sequencing of microbial communities in the athabasca river and its tributaries in relation to oil sands mining activities. Appl Environ Microbiol. 2012;78(21):7626–7637.

12. Johnson G, Nolan T, Bustin SA. Real-time quantitative PCR, pathogen detection and MIQE. Methods Mol Biol. 2013;943:1–16.

13. Hedman J, Rådström P. Overcoming inhibition in real-time diagnostic PCR. Methods Mol Biol. 2013;943:17–48.

14. Wallace PS, MacKay WG. Quality in the molecular microbiology laboratory. Methods Mol Biol. 2013;943:49–79.

15. Hansen WL, Bruggeman CA, Wolffs PF. Evaluation of new preanalysis sample treatment tools and DNA isolation protocols to improve bacterial pathogen detection in whole blood. J Clin Microbiol. 2009;47(8):2629–2631.

16. Hansen WL, Bruggeman CA, Wolffs PF. Pre-analytical sample treatment and DNA extraction protocols for the detection of bacterial pathogens from whole blood. Methods Mol Biol. 2013;943:81–90.

17. Vollmer T, Kleesiek K, Dreier J. Detection of bacterial contamination in platelet concentrates using flow cytometry and real-time PCR methods. Methods Mol Biol. 2013;943:91–103.

18. Renwick L, Holmes A, Templeton K. Multiplex real-time PCR assay for the detection of meticillin-resistant Staphylococcus aureus and Panton-Valentine leukocidin from clinical samples. Methods Mol Biol. 2013;943:105–113.

19. Abdeldaim GM, Herrmann B. PCR detection of Haemophilus influenzae from respiratory specimens. Methods Mol Biol. 2013;943:115–123.

20. Abdeldaim GM et al. Detection of Haemophilus influenzae in respiratory secretions from pneumonia patients by quantitative real-time polymerase chain reaction. Diagn Microbiol Infect Dis. 2009;64(4):366–373.

21. Ling CL, McHugh TD. Rapid detection of atypical respiratory bacterial pathogens by real-time PCR. Methods Mol Biol. 2013;943:125–133.

22. Tatti, K.M. and M.L. Tondella, Utilization of multiple real-time PCR assays for the diagnosis of Bordetella spp. in clinical specimens. Methods Mol Biol. 2013;943:135–147.

23. Winchell JM, Mitchell SL. Detection of Mycoplasma pneumoniae by real-time PCR. Methods Mol Biol. 2013;943:149–158.

24. Fillaux J, Berry A. Real-time PCR assay for the diagnosis of Pneumocystis jirovecii pneumonia. Methods Mol Biol. 2013;943:159–170.

25. Yam WC, Siu KH. Rapid identification of mycobacteria and rapid detection of drug resistance in Mycobacterium tuberculosis in cultured isolates and in respiratory specimens. Methods Mol Biol. 2013;943:171–199.

26. Lavender CJ, Fyfe JA. Direct detection of Mycobacterium ulcerans in clinical specimens and environmental samples. Methods Mol Biol. 2013;943:201–216.

27. Bergmans AM, Rossen JW. Detection of Bartonella spp. DNA in clinical specimens using an internally controlled real-time PCR assay. Methods Mol Biol. 2013;943:217–228.

28. McKechnie ML, Kong F, Gilbert GL. Simultaneous direct identification of genital microorganisms in voided urine using multiplex PCR-based reverse line blot assays. Methods Mol Biol. 2013;943:229–245.

29. Van den Berg RJ, Bakker D, Kuijper EJ. Diagnosis of Clostridium difficile infection using real-time PCR. Methods Mol Biol. 2013;943:247–256.

30. Stoddard RA. Detection of pathogenic Leptospira spp. through real-time PCR (qPCR) targeting the LipL32 gene. Methods Mol Biol. 2013;943:257–266.

31. Yamazaki W. Sensitive and rapid detection of Campylobacter jejuni and Campylobacter coli using loop-mediated isothermal amplification. Methods Mol Biol. 2013;943:267–277.

32. Rimbara E, Sasatsu M, Graham DY. PCR detection of Helicobacter pylori in clinical samples. Methods Mol Biol. 2013;943:279–287.

33. Maheux AF, Bissonnette L, Bergeron MG. Rapid detection of the Escherichia coli genospecies in water by conventional and real-time PCR. Methods Mol Biol. 2013;943:289–305.

34. Barletta F, Ochoa TJ, Cleary TG. Multiplex real-time PCR (MRT-PCR) for diarrheagenic. Methods Mol Biol. 2013;943:307–314.