|Year : 2019 | Volume
| Issue : 4 | Page : 569-573
Epidemiology and phylogenetic analysis of human rhinovirus/Enterovirus in Odisha, Eastern India
Swagatika Panda1, Nirmal Kumar Mohakud2, Soumya Panda3, Subrat Kumar1
1 Infection Biology Lab, School of Biotechnology, KIIT University, Campus-XI, Bhubaneswar, Odisha, India
2 Department of Pediatrics, Kalinga Institute of Medical Sciences, KIIT University, Bhubaneswar, Odisha, India
3 School of Biotechnology, Amity Institute of Biotechnology, Amity University, Noida, Uttar Pradesh, India
|Date of Submission||18-Jan-2020|
|Date of Acceptance||08-Apr-2020|
|Date of Web Publication||18-May-2020|
Dr. Subrat Kumar
School of Biotechnology, KIIT University, Campus-XI, Patia, Bhubaneswar - 751 024, Odisha
Source of Support: None, Conflict of Interest: None
Introduction: Human rhinovirus (HRV) and Enterovirus (ENV) are the major causes of childhood acute respiratory tract infections (ARTIs). This study sought to understand the distribution pattern of HRV subgroups, their seasonality and association with respiratory complications in patients at a tertiary care hospital. Results: Of the total 332 ARTI samples, 82 (24.7%) were positive for ENV/HRV. Twenty positive samples were processed further for phylogenetic analysis. Ten of the 20 samples were identified to be HRVs (70% HRV A and 30% HRV C) and nine were enteroviruses. HRV A clustered near three distinct HRV types (A12, A78 and A82). Four of the HRV strains (represented as SEQ 137 rhino, SEQ 282 rhino, SEQ 120 rhino and SEQ 82 rhino) had high sequence similarity. HRV C showed seasonality and was associated with disease severity. Conclusion: The genotyping and phylogenetic analysis of the HRVs in the current study shows its circulatory pattern, association with risk factors and evolutionary dynamics.
Keywords: Enteroviruses, epidemiology, human rhinoviruses, phylogenetic analysis, respiratory tract infection
|How to cite this article:|
Panda S, Mohakud NK, Panda S, Kumar S. Epidemiology and phylogenetic analysis of human rhinovirus/Enterovirus in Odisha, Eastern India. Indian J Med Microbiol 2019;37:569-73
|How to cite this URL:|
Panda S, Mohakud NK, Panda S, Kumar S. Epidemiology and phylogenetic analysis of human rhinovirus/Enterovirus in Odisha, Eastern India. Indian J Med Microbiol [serial online] 2019 [cited 2020 Jun 2];37:569-73. Available from: http://www.ijmm.org/text.asp?2019/37/4/569/284525
| ~ Introduction|| |
Acute respiratory tract infections (ARTIs) pose a worldwide socioeconomic burden and are a major cause of morbidity and mortality globally. Human rhinovirus (HRV)/Enterovirus (ENV) are known to be major contributing agents for ARTIs in all age groups. In paediatric populations, rhinovirus is found to be the most frequent causative agent of lower respiratory tract infections (LRTI), wheezing and bronchiolitis.
HRVs show a high genetic and antigenic diversity. They are differentiated into three distinct subgroups based on the VP4/VP2 region as well as 5'UTR hypervariable region., Those are HRV A, HRV B and a newly discovered HRV C. Based on their capsid gene sequences, the subgroups are further subdivided into 78 A types, 30 B types and 51 C types. Although HRV A and C are most abundant, all the subgroups have been widely distributed globally. Severity of HRV-associated illness may range from mild upper respiratory tract infection to severe pneumonia and bronchiolitis. However, HRV C was shown to be most associated with severe asthma exacerbations in some studies., This study was conducted to determine the molecular typing and the distribution kinetics of the different HRV genotypes from this study period. As well some insight into the molecular basis of the symptoms associated with HRV infection was gained.
| ~ Methods|| |
Clinical specimens and study protocol
This prospective study was conducted at the Kalinga Institute of Medical Sciences, Bhubaneswar, Odisha, India. Children (<13 years age) visiting the paediatrics outpatient departments were carefully checked for the inclusion criteria. Those who fulfilled the inclusion criteria were enrolled in this study. The inclusion criteria were at least two of the following symptoms: cough, running nose, a fever (>100°F) of more than 37.7°C, throat congestion, tonsillitis, pharyngitis, chest congestion, wheezing, rhinitis, earache, body pain, weakness and vomiting. In addition, the consent and willingness of the patients and the parents of the patient to participate in the study were required. Nasal or nasopharyngeal and throat swab samples were collected from the patients suspected to have ARTIs using sterile-flocked nylon swabs (Himedia, India). Swabs were collected in a sterile tube containing 2 ml of viral transport media and were transported to the laboratory in an ice box. The study protocol was reviewed and approved by the Institutional Ethics Committee (Reference No-KIMS/KIIT/682/13). Informed consent and patient datasheets were obtained for each participant.
Extraction of viral RNA and reverse transcription-polymerase chain reaction
Total RNA was extracted from 250 μl of swab samples using TRIZOL reagent (Invitrogen, USA), according to the manufacturer instruction and suspended in 25 μl of RNAse-free TE buffer. It was quantified using nanodrop, and 1 μg of this RNA was used for c-DNA synthesis with random hexamer primers using Revertaid first-strand c-DNA synthesis kit (Thermoscientific, Waltham, Massachusetts, United States). Briefly, after the reaction mixture was prepared, it was incubated for 5 min at 25°C, and then, incubated for 60 min at 42°C. The reaction was stopped at 70°C for 5 min. A semi-nested polymerase chain reaction (PCR) was carried out using this cDNA to detect HRV/ENVs. 2 μl of cDNA was added to 20 μl of reaction mixture containing 10x PCR buffer (100 mM Tris-HCL, 500 mM KCL and 15 mM MgCl2), 25 mM MgCl2, 2 mM dNTP, 0.25–0.5 μM of specific primers, 2 units of Taq polymerase (New England Biolabs, MA, USA) and water. PCR cycling conditions were as follows: initial denaturation for 7 min at 94°C, followed by 25 cycles of 94°C for 30 s, 53°C for 30 s and 72°C for 40 s. This was followed by one cycle of final denaturation at 72°C for 3 min. A second-round PCR was setup using the same cycling conditions with 35 cycles where 2 μl from the product of first set of PCR was used as template. For typing of HRV VP2/VP4 sequence has been used extensively, but recently variable region of 5'UTR has also been used for the same. The forward primer was kept same in both set of PCR. The primers used for first set of PCR (Fw HRV UTR “GCACTTCTGTTTCCCC” and Rw HRV VP2 “AGTGATTTGYTTIAGCCTATC”) target the sequence stretch from 5'UTR to VP2 gene that yields a nearly 690 bp product., This was then used as template to amplify a hypervariable region of 5'UTR flanked by two highly conserved site. The second set of primers (Fw HRV UTR “GCACTTCTGTTTCCCC” and Rw HRV UTR “CGGACACCCAAAGTAG”) target those conserved sites and yield the final product of approximately 390 bp, which was further cloned and sequenced.
Sequencing of reverse transcription-polymerase chain reaction products
HRV/ENV-positive PCR products from the second round of PCR were purified using QiaexII Gel extraction kit (Qiagen, Hilden, Germany)and cloned into pJET1.2/blunt end-cloning vectors (Thermo Scientific, Lithuania), according to the manufacturer's protocol. Plasmids were isolated from 10 ml of bacterial culture using the Qiagen miniprep kit (Qiagen, Germany) as per the manufacturer's protocol. Due to a scarcity in the starting material (c-DNA), only 20 samples out of 82 positive cases (detected earlier) were subjected to sequencing. The plasmid clones were sequenced on both strands using the BigDye Terminator version 1.1 Cycle Sequencing Kit (Applied Biosystems, Foster city, CA, USA) on a PRISM 3100 Genetic Analyser (Applied Biosystems, Foster city, CA, USA).
Phylogenetic analysis of human rhinovirus isolates
A BLAST search was carried out with the sequencing data to confirm the identity of the strains (blast.ncbi.nlm.nih.gov). A neighbour-joining algorithm was implemented for the construction of a phylogenetic tree using MEGA7. ClustalW was used for the sequence alignment. To confirm the reliability of the pairwise comparison and phylogenetic tree analysis, bootstrap resampling was carried out on 1000 datasets. The evolutionary distances were computed using Kimura 2-parameter method and were represented in units of base substitutions per site. All positions-containing gaps and missing data were automatically eliminated during the program run keeping a final dataset of 240 positions.
| ~ Results|| |
As discussed in our previous paper, HRV/ENV was detected in 24.7% of patient samples. Positive cases had fever (82%), cough (74%) and nasal discharge (73%) as predominant symptoms. The average time of the hospital visit postonset of symptoms was 2.51 days and by that time a major portion of the patients had developed severe chest congestion (26.8%). However, 59.8% of the total HRV/ENV-positive cases were diagnosed with acute upper respiratory tract infection.
Of the 82 positive samples (detected earlier in the epidemiology study), only 20 could be processed for sequencing due to an unavailability of sufficient c-DNA of certain HRV-positive samples. Around 390 bp sequences of the 5'UTR were obtained from sequencing the plasmid clones. Upon blast analysis, they were found to be HRVs, ENVs and coxsackie/echoviruses. The ENV strains detected had highest similarity with ENV D68 and D69 genotypes. The coxsackie viruses detected shared sequence similarity with A4, A6, B2 and B4 genotypes, whereas the echoviruses detected shared similarity with echovirus genotypes E6 and E9. One sequence showed ambiguous peaks upon analysis, and therefore, it was not taken into account further. In order to clearly understand the genotypic variations of HRVs in this locality, the HRV sequences were further used to create a phylogenetic tree.
For the tree construction, complete genome sequences of the HRV subtypes were retrieved from Genbank along with the reference strains for each subgroup (www.ncbi.nlm.nih.gov). Sequences which were too highly divergent to be incorporated in the tree were excluded. Following a clustalW alignment, a neighbour-joining method with a 1000 bootstraP value was adapted as the selection parameter for tree construction. Nine rhinovirus sequences came under HRV A and one came under HRV C [Figure 1]. No HRV B was detected. However, while all sequences were analysed by BLASTn (NCBI), three sequences showed sequence identity with HRV C (percentage identity was high 98.9%–99.45%). Hence, two were misinterpreted by phylogenetic analysis to be HRV A, whereas they are HRVC as suggested by BLAST analysis. HRV sequences in this study were mostly clustered in the HRV A subgroup (70%), whereas 40% of the sequences were found to be in close proximity to strain KY369894 hV A82. Other HRV As were clustered near strain FJ445183.1 hV A78 and KX398052.1 hV A12. The HRV C found in the study (30%) was in close proximity to EF582386.1 hV C25.
|Figure 1: Phylogenetic analysis: The phylogenetic tree was generated by neighbour-joining method based on a final dataset of 240 bp nucleotide sequence of 5' UTR region of HRV. The tree is drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the kimura 2-parameter method 24 and are in the units of the number of base substitutions per site. In the tree, green triangle (green branches) corresponds to HRVA, blue triangle (blue branches) corresponds to HRV C and pink triangle (pink branches) corresponds to HRV B reference strains, respectively. While, sequences obtained from this study are shown with closed blue and green circle. Sequences of reference strains have been obtained from NCBI nucleotide database (https://www.ncbi.nlm.nih.gov). Different serotypes from each subgroup were taken in account to identify the closest neighbour|
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Despite their sequence similarity and barely differentiated disease presentation, in this study, the rate of severity varied according to HRV types. Nearly 28.6% of HRV A patients had LRTI and 14.3% presented with wheezing and bilateral crepitation. However, this percentage was even higher for HRV C patients, where 67% patients had developed wheezing and LRTIs (P < 0.001, odds ratio = 4.9707, 95% confidence interval = 2.7273–9.0597). We also found variation in the seasonal distribution of the HRV subgroups. While HRV A was detected throughout the year, HRV C was found only in autumn.
| ~ Discussion|| |
Among all respiratory pathogens, viruses account for about 80% of all respiratory infections. Epidemiological studies from developing countries, especially from low-to-middle income countries like India, are rare. In our previous study, HRV was found to be the most frequent contributor toward paediatric respiratory infection followed by RSV. Majority of HRVs cases were detected as single infection, whereas about 75% of the RSV co-infection cases presented with severe LRTI leading to longer hospital stay. There are several other reports of respiratory outbreaks with associated mortality due to HRV; however, the molecular characterisation of the virus isolates has yet to be performed., In this study, we analysed the HRV genotypes isolated from ARTI cases. HRVs/ENVs were the most common viral pathogens detected in these ARTI cases, a high percentage of which were upper respiratory tract infections. This can be attributed to the virus's limited ability to grow above the optimum growth condition temperatures (32°C–33°C) and at a slightly low pH (around 7–7.2). The upper respiratory tract, unlike the lower respiratory tract, maintains these condition due to continuous inhalation of outside air and exhalation of CO2-containing air that keeps the pH lower than the general inner body pH of 7.4. However, HRV C and certain other strains of HRV can overcome these limitations to move to the lower respiratory tract to cause a LRTI.
Along with HRVs, some ENVs were also detected, as they have a high degree of sequence similarities. ENVs detected in this study include coxsackie viruses, echoviruses and other ENVs. In a previous study by L'huillier et al., it was shown that ENV D68 is associated with disease severity, as it is known to migrate to the central nervous system and cause complications to develop. However, in our study, we did not observe any association between ENV infection and disease severity. In this study, these viruses were mainly associated with upper respiratory tract infection.
HRV genotype circulation varies from region to region. While some studies suggest that HRV A is the most prevalent subgroup of HRV followed by HRV C and HRV B;,, others studies suggest that HRV C is the most frequently detected of the HRV subgroups. In our study, HRV A was the most prevalent subgroup, followed by HRV C. We could not detect HRV B.
The association of HRV genotypes with disease severity is debatable. A few studies have shown that HRV A and HRV B contribute more toward disease severity than other subgroups,, whereas some studies have found HRV C to cause more severe disease. Linsuwanon et al. found that HRV C was the only HRV subgroup to be detected in cases of acute asthma and reactive airway disease. Some studies found HRV C infection associated with acute wheezing., In this study, however, a positive association of HRV C with wheezing and LRTI was found. These data show the health burden associated with this specific subgroup of HRV.
The seasonality of HRV is a major concern and is still not clearly understood. In our study, HRV was detected in all seasons, though the highest detection rate was seen in the autumn. HRV A was consistently detected in all seasons, whereas HRV C was more prevalent during the autumn. These findings are in line with other reports where a higher prevalence of HRV C was seen during the autumn season., This report will be useful for planning early precautionary measures before the onset of severe HRV C-related diseases.
| ~ Conclusion|| |
This study reports a high prevalence of HRV in children and found to be the major cause of childhood hospitalisation for the first time from Eastern India. HRV circulation is the highest in autumn, and HRV C is associated with wheezing and acute LRTI. However, in the current study with few characterised samples, it will be difficult to conclude the findings and portray their significance. Therefore, an extensive epidemiological study as well as whole-genome sequencing of circulating viruses is necessary to clearly understand the virus's circulation patterns and association with risk factors.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
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