Traditional methods of infectious disease diagnosis are Gram- staining, pathogen culturing, and study of virus morphology by inoculating culture. Conventional techniques are time-consuming and lack sensitivity. Serological and molecular markers are new diagnostic approaches that offer rapid, sensitive and more accurate diagnostic results. Molecular markers are a specific short sequence of DNA or RNA. Molecular markers are capable of detecting polymorphism in the specific chromosomal region associated with unique chromosomal locations, that can be random. On the other hand, serological markers are used to measure the concentrations of an antibody. These are potentially the most direct way to decipher the dynamics of a population’s responsiveness and diagnosis of a disease (Metcalf et al., 2016). The differences between alleles (diseased and healthy populations) are traced as molecular markers that help to identify specific gene or traits responsible for causing disease (Gupta et al., 2016). Moreover, genetic markers help in diagnosing the causative agent, by differentiating between virulent (disease-causing) and non-virulent human pathogens. This information further helps to develop a vaccine or a potential drug target. Pathogenic strains possess distinct serotypes or strains that have different virulence and show selectivity for tissues and host. Because pathogens have a relatively small genome, they easily develop resistance against the drug. Therefore, to trace the slightest change in genome molecular, markers are the most reliable. Consequently, in order to treat or find a solution to the problem, one needs to trace the root cause of the problem and serological. As discussed above both the techniques are rapid, sensitive, specific and reliable.
Application of serology in infectious disease diagnosis
Serology is defined as the study of serum as well as other bodily fluids (Ryan and Ray, 2014). The term refers to the diagnostic identification of antibodies, which are typically formed in response to an infection, in the serum or bodily fluids (Baron, 1996). It helps in identifying the viral or pathogen antigens and antibody, diagnose disease and host immunity. In terms of current serological methods use, infections can be classiﬁed into four groups (Metcalf et al., 2016):
- Acute immunizing, antigenically stable pathogens (e.g., measles, rubella, and smallpox) for which serology provide a strong signal of lifetime protection and a clear marker of past infection (or vaccination) lie under the first group,
- Immunizing, but antigenically variable pathogens e.g., inﬂuenza, invasive bacterial diseases and dengue,
- For those, in which infection-induced antibodies are not thought to be protective, e.g., tuberculosis,
- Infections for which speciﬁc antibodies presence do not protect from future infection.
The figure below shows different types of serological techniques in an application today.
Although serological methods have many advantages like rapidity and robust results, at the same time they have limitations too. For instance, monoclonal-antibody direct ﬂuorescent antibody tests have adequate speciﬁcity for a particular virus, but then there are much turnaround time and lower sensitivity (Zumla et al., 2014). There is a need for enhanced methods like multiplex test which can detect more than one pathogen simultaneously in cases of co-infections. Immunoglobulins (Ig) are used as serological markers for diagnostic and immunity check purpose. IgG and IgM are the most common serological markers used for antigen diagnosis. Serological methods have already shown its impact in diagnosing emerging infectious diseases using different techniques.
|1||HIV/HBV co-infection, May 2006-July 2011||Brazil||Hepatitis B surface antigen (HBsAg), hepatitis B “e” antigen (HBeAg).||Microparticle Enzyme Immunoassay||(Toscano Ana Luiza de Castro Conde, 2017)|
|2||HIV/HBV co-infection||Uganda, Zimbabwe, Harare||HBsAg||Enzyme immunoassay||(Price et al., 2017)|
|3||Dengue Fever, 2011-2012||Sri Lanka||IgM and IgG||ELISA||(Senaratne et al., 2016)|
|4||Zika, 2016||South Korea||IgM and IgG||ELISA||(Jeong et al., 2017)|
|5||Ebola, 2014||Gulu outbreak, 2001||Mannose-binding lectin and IgG||ELISA||(McElroy et al., 2014)|
Serological markers used in disease diagnosis.
Molecular markers in diagnosing emerging and re-emerging pathogens
- A genetic marker is a DNA sequence of known chromosomal location, which is used to identify an organism. Sequencing offers an excellent resolution of genotype, but it can be time-consuming and labour-intensive. And the accuracy of results is not guaranteed either. These limitations can be overcome with molecular markers to map gene as well as diagnosis, as they are very specific, highly sensitive and less time consuming, which are as follows: Random amplification of polymorphic DNA (RAPD)
- Amplified Fragment Length Polymorphism (AFLP)
- Single Nucleotide Polymorphism (SNP)
- Restriction Fragment Length Polymorphism (RFLP)
For example, IS6110- RFLP is being widely used to diagnose different strains of Mycobacterium tuberculosis (Desikan and Narayanan, 2015). The main advantage of this technique is its high-resolution power. Few of the molecular markers are listed below which were used to diagnose emerging infectious diseases.
|1||Dengue, 2016||Pakistan||Random Amplified Polymorphic DNA||Polymerase chain reaction (PCR)||(Muhammad Ashraf et al., 2016)|
|2||Malaria Infections, 2015||Myanmar||artemisinin-resistance marker K13 (kelch 13 gene)||Polymerase chain reaction, nested PCR||(Nyunt et al., 2017)|
|3||Zika, 2016||KDCC||Envelope “E” gene||real-time reverse transcription-polymerase||(Jeong et al., 2017)|
|4||Dengue Fever, 2011-2012||Sri Lanka||Capsid gene and envelope||RT-PCR||(Senaratne et al., 2016)|
|5||Dengue, 2007||India||Capsid gene||Duplex RT-PCR, nested PCR||(Neeraja et al., 2013)|
Molecular markers used in disease diagnosis.
Two case studies are discussed below, explaining the crucial role of serological and genetic markers in disease detection.
Serological markers in HIV and HBV (Toscano Ana Luiza de Castro Conde, 2017):
- Pathogen: Human immunodeficiency virus (HIV) and hepatitis B virus (HBV).
- Disease: HIV and HBV coinfected, São Paulo, Brazil, May 2006-July 2011.
The study was conducted from June 2011 to July 2012.
- Serology marker: Hepatitis B surface antigen (HBsAg), hepatitis B “e” antigen (HBeAg).
- Findings: 2,242 HIV infected patients out of which 105 (i.e., 4.7%) were identified with chronic hepatitis B. All patients were given antiretroviral (ARV) therapy during follow-up, follow-up time varied from six months to 20.5 years. 58% of patients with chronic hepatitis B were found hepatitis B “e” antigen positive. 16 out of 105 of the patients with chronic hepatitis B were found to be HBsAg cleared, and 8/16 of these patients showed subsequent reactivation or seroreversion of HBsAg. Among HBeAg infected patients, 57% (35/61) presented the clearance of same serologic marker. During clinical follow-up, those who initially cleared HBeAg, 28.5% (10/35) of them showed sero-reversion or reactivation of this marker. Among HIV co-infected patients undergoing ARV therapy, the evolution of HBV serological markers was frequently observed.
Genetic Markers for Dengue (Muhammad Ashraf et al., 2016):
- Pathogen: Dengue virus, genetic analysis of Aedes aegypti.
- Disease: Dengue fever, Pakistan.
- The method used: Random Amplified Polymorphic DNA (RAPD) Markers from Dengue Outbreaks.
- Advantage: As it used to amplify DNA randomly, a specific primer is not required. Also, it requires only one primer.
- Findings: The study proposed of the existence of genetic diversity in Aedes aegypti population of Lahore is causing the havoc and hence analyzed the genetic variability by RAPD-PCR using 10 oligonucleotide primers. Eighteen populations of mosquitoes were sampled from Faisalabad and Lahore. Polymorphic loci amplified by each primer varied from 22.5% to 51%. The UPGMA (unweight pair-group mean analysis) dendrogram demonstrated two distinct groups of populations. The genetic variation ranged from 0.260 in Faisalabad to 0.294 in Lahore and 0.379 heterozygosity (a different pair of alleles). The overall genetic variation among eighteen populations showed GST (inbreeding indices) = 0.341 and Nm (migration rate) = 1.966. The statistics showed thataegypti populations had intra-population genetic drift between Faisalabad and Lahore. It was also concluded that aegypti populations were reportedly genetically more diverse as that of the previous population.
Molecular and serological techniques have set a turning point in discovering and characterizing many emerging infectious agents. Challenges are still there for the widespread use of cost-effective, validated, and commercially available molecular tools. A multiplex test is another advanced technique that detects more than one pathogen at the same time during co-infections. As pathogens are evolving continuously, through mutation, rapid diagnostic tests are much needed which, from single blood, saliva or any sample will be able to identify infection cause, identify any virus to the species level.
- Baron, S. (1996) Medical Microbiology, Medical Microbiology. Available at: http://www.ncbi.nlm.nih.gov/pubmed/21413252.
- Desikan, S. and Narayanan, S. (2015) ‘Genetic markers, genotyping methods & next generation sequencing in Mycobacterium tuberculosis.’, The Indian journal of medical research. Wolters Kluwer — Medknow Publications, 141(6), pp. 761–74. doi: 10.4103/0971-5916.160695.
- Gupta, V. et al. (2016) ‘Basic and applied aspects of biotechnology’, Basic and Applied Aspects of Biotechnology, pp. 1–520. doi: 10.1007/978-981-10-0875-7.
- Jeong, Y. E. et al. (2017) ‘Viral and serological kinetics in Zika virus-infected patients in South Korea’, Virology Journal. Virology Journal, 14(1), p. 70. doi: 10.1186/s12985-017-0740-6.
- McElroy, A. K. et al. (2014) ‘Biomarker correlates of survival in pediatric patients with ebola virus disease’, Emerging Infectious Diseases, 20(10), pp. 1683–1690. doi: 10.3201/eid2010.140430.
- Metcalf, C. J. E. et al. (2016) ‘Use of serological surveys to generate key insights into the changing global landscape of infectious disease’, The Lancet. Elsevier Ltd, 388(10045), pp. 728–730. doi: 10.1016/S0140-6736(16)30164-7.
- Muhammad Ashraf, H. et al. (2016) ‘Genetic Analysis of Aedes aegypti using Random Amplified Polymorphic DNA (RAPD) Markers from Dengue Outbreaks in Pakistan’, J Arthropod-Borne Dis, 10(4), pp. 546–559.
- Neeraja, M. et al. (2013) ‘The clinical, serological and molecular diagnosis of emerging dengue infection at a tertiary care institute in Southern, India’, Journal of Clinical and Diagnostic Research, 7(3), pp. 457–461. doi: 10.7860/JCDR/2013/4786.2798.
- Nyunt, M. H. et al. (2017) ‘Molecular evidence of drug resistance in asymptomatic malaria infections, Myanmar, 2015’, Emerging Infectious Diseases, 23(3), pp. 517–520. doi: 10.3201/eid2303.161363.
- Peng, X. et al. (2016) ‘Molecular characterization of a novel reassortant H1N2 influenza virus containing genes from the 2009 pandemic human H1N1 virus in swine from eastern China’, Virus Genes. Springer US, 52(3), pp. 405–410. doi: 10.1007/s11262-016-1303-4.
- Price, H. et al. (2017) ‘Hepatitis B serological markers and plasma DNA concentrations.’, AIDS (London, England), 31(8), pp. 1109–1117. doi: 10.1097/QAD.0000000000001454.
- Ryan, K. J. and Ray, C. G. (2014) Sherris medical microbiology, 6th Ed., Sherris medical microbiology. doi: 10.1017/CBO9781107415324.004.
- Senaratne, T. et al. (2016) ‘Characterization of Dengue Virus Infections in a Sample of Patients Suggests Unique Clinical, Immunological, and Virological Proﬁles That Impact on the Diagnosis of Dengue and Dengue Hemorrhagic Fever’, Journal of Medical Virology, pp. 1–8. doi: 10.1002/jmv.
- Toscano Ana Luiza de Castro Conde, C. M. C. M. (2017) ‘Evolution of hepatitis B serological markers in HIV coinfected patients: a case study’, Revista de Saúde Pública, 51, pp. 1–8. doi: 10.1590/s1518-8787.2017051006693.
- Zumla, A. et al. (2014) ‘Emerging respiratory tract infections 4 Rapid point of care diagnostic tests for viral and bacterial respiratory tract infections — needs , advances , and future’, 3099(14), pp. 1123–1135. doi: 10.1016/S1473-3099(14)70827-8.
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