Journal of Genetic Disorders & Genetic Reports ISSN: 2327-5790

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Research Article, J Genet Disor Genet Rep Vol: 4 Issue: 2

RPOB Gene Polymorphism and its Association with Multi Drug Resistance Pattern of Mycobacterium Tuberculosis and Associated Risk Factors among TB Patients

Tekeba Sisay and Nega Berhane*
Department of Biotechnology, University of Gondar, North Gondar, Ethiopia
Corresponding author : Nega Berhane
Department of Biotechnology, University of Gondar, Gondar, Ethiopia
Tel: 251918149759
E-mail: [email protected]
Received: February 18, 2015 Accepted: March 25, 2015 Published: March 27, 2015
Citation: Sisay T, Berhane N (2015) RPOB Gene Polymorphism and its Association with Multi Drug Resistance Pattern of Mycobacterium Tuberculosis and Associated Risk Factors among Tb Patients. J Genet Disor Genet Rep 4:2. doi:10.4172/2327-5790.1000123

Abstract

RPOB Gene Polymorphism and its Association with Multi Drug Resistance Pattern of Mycobacterium Tuberculosis and Associated Risk Factors among TB Patients

Tuberculosis (TB) is the leading cause of death in the world due to bacterial infection. Despite the use of effective chemotherapy in the past years, drug-resistant TB especially multidrug resistance (MDR) is becoming a series challenge to compact . Rifampin (RIF) is one of the most important TB chemotherapeutic agents that act by inhibiting mycobacterial transcription, targeting DNA-dependent RNA polymerase (rpoB). The aim of the present study was to determine rpoB gene polymorphism and its association with Multi Drug Resistance (MDR) pattern of MTB by PCR and to determine the associated risk factors for drug resistance development. In this study rpoB mutations in the hot spot region (511-533 codons) were detected in 32 (69.6%) out of 46 smear positive (non-converged) MDR-TB patients and 5 (10.87%) out of 46 smear negative (converged) MDR-TB patients. However, there was not detected mutant allele in smear positive susceptible counter parts. The patients’ prior anti TB treatment history, HIV infection, origin of infection and drug misuse were found significant risk factors (p=.000, .000, .004, .000, respectively) for drug resistance development. The detection of mutations at 511-533 codons by PCR in 69.6% of non-converged MDR-TB patients indicated that most of drug resistance development is due to mutation at this position and the high prevalence of mutant rpoB allele.

Keywords: Tuberculosis; rpoB; MDR-TB; Rifampin

Keywords

Tuberculosis; rpoB; MDR-TB; Rifampin

Introduction

Tuberculosis is a serious global public health problem and a major cause of death [1]. According to the 2007 report of World Health Organization (WHO), one-third of the world’s population is estimated to be infected by TB and in 2005, from 8.8 million TB annual incidences 7.4 million of these were in Asia and sub-Saharan Africa [2]. In 2012, 8.6 million people developed TB and 450 000 people developed MDR-TB [3]. One of the most alarming trends concerning TB is the emergence of drug-resistant TB [4]. MDR-TB, can be defined as a disease caused by MTB strains with resistance to, at least, isoniazid and rifampicin, is a growing public health concern [5].
HIV/MDR-TB co-infection is great challenge for TB control [6,7]. The dual epidemics of HIV infection and MDR-TB threaten global TB control, especially in sub-Saharan Africa [8]. Additional factors such as immigration, age, sex, and socioeconomic factors have been shown to be associated with the increased prevalence of MDR-TB [9]. TB is a disease of poverty (most TB deaths occur in the developing world) affecting mostly young adults [10]. Ethiopia is a high-burden country for TB, with an estimated incidence of 341 of 100,000 populations per year in 2005. In addition to high TB burden, Ethiopia has been seriously affected by HIV/AIDS [11,12]. According to the 2008 report of WHO, Ethiopia ranks seventh among the world’s 22 countries with a high TB burden [13]. The Ethiopian Federal Ministry of Health (FMOH) hospital statistics data has shown that TB is the leading cause of morbidity [14].
Rifampin has proven to be an effective anti-TB agent [15] that interferes with transcription in bacteria by binding to the β-subunit of RNA polymerase (the product of the rpoB gene) [15]. More than 90% of rifampicin-resistant MTB strains from different countries appear to harbour specific point mutations located in a 81 bp (core) region of rpoB gene (codons 511–533) [16-19].
In Ethiopia, the associated risk factors and the frequency of mutant rpoB allele have not been fully investigated. To develop reasonable health-care strategy, particularly for difficult problems such as MDR-TB, current knowledge of drug resistant TB in Ethiopia is important. Early detection of drug resistance in clinical MTB isolates is crucial for appropriate treatment to prevent the development of further resistance and the spread of resistant strains. The objective of the present study was to determine the frequency of mutant rpoB allele and its association with MDR pattern of MTB by PCR and to determine the associated risk factors for drug resistance development.

Materials and Methods

Characteristics of the study subjects
For molecular study early morning 92 sputum samples from clinically confirmed two category MDR-TB patients; i.e. from smear positive (non-converged) and smear negative (converged), 46 samples for each case, and 46 sputum samples, from clinically confirmed susceptible TB patients were collected from untreated and / or treated and newly diagnosed patients. The samples were stored at -20°C till DNA extraction. The socio-demographic character of 250 TB patients, 138 TB patients from whom sputum sample was collected and other 112 TB patients who were not involved during sputum sample collection, was gathered by well-structured questionnaire. Written informed consent was obtained from all cases and controls. The study was carried out after obtaining ethical approval from the ethical committee of natural and computational sciences college, University of Gondar. Moreover, a written consent form was obtained from every patient that was giving samples.
Isolation of genomic DNA
To extract genomic DNA the sputum samples were decontaminated by adding equal volume of 4% NaOH and incubating at 37°C for 30 minutes. After centrifugation the pellet was washed by distilled water followed by TE buffer [20]. 3 ml of pre-treated samples in TE buffer were placed in boiling water bath at 100°C for 10 min. Followed by incubation at 56°C for 2-3 hrs after addition of equal amount of lysis buffer (Tris 10 mM, EDTA 2 mM, NaCl, 0.4 M and 0.5% Triton X-100 (pH 8.0). DNA purification was done by addition of equal volume of Phenol: Chloroform (24:1) followed by chloroform only. The aqueous phase was finally transferred in 5 volume of chilled ethanol and sodium acetate (0.3M final conc.) was added. Tubes were kept at -20°C overnight. The samples were centrifuged at 10,000 rpm for 10 minutes and the DNA pellet was washed with 70% chilled ethanol by centrifugation. The pellet was allowed to air dry and finally suspended into 50 μl of distilled water (sterile) for PCR analysis [21].
Detection of mutant rpoB allele by PCR
The mutant rpoB allele was detected by using primers specific to 511-533bp region. The primer sequences utilized for the present study is: rpoB forward primer: 5’-GGATCGGCGATTGGGACG-3’ and rpoB reverse primer 5’-ATATCGCAGCCTCCCAGC [22] that generate 517bp product (Figure 1). The PCR reaction consists 2 μl template DNA (1/20 diluted with ddH2O) in a total of 25 ml reaction mixture containing 15.25 μl of ddH2O, 2.5 μl of 10×buffer, 1 μl of 20 mM dNTPs, 0.625 μl (10 pmol/μl) of each of the rpoB primers: rpoB forward primer: and rpoB reverse primer, 2 μl of 25 mM MgCl2 and 0.2 μl of Taq Polymerase (5 U/ml). Amplification cycles were as follows: incubation for 7 minutes at 95°C for initial denaturation, followed by 35 cycles of denaturation, annealing and polymerization (94°C for one minute, 55°C for one minute, and 72°C for two minutes respectively). 7 minutes of final extension at 72°C was done. For each set of amplification process a positive control of 16s rRNA primers (forward primer: 5’-GGGAGTGCCTTCGGGAATCAGA-3’ and reverse primer: 5’-TCACCGCAACATTCTGATTTG-3’ [23], amplify the target 16S rRNA gene expected to give 356bp PCR product, were included. A negative control was used by preparing all PCR reaction mixture components except the template DNA, instead of which DNA from susceptible TB patients was used.
Figure 1:Representative agarose gel PCR amplification of rpoB gene of M.Tuberclosis strain. (Note: Lane1=100bp DNA marker, Lanes 2-16 517bp Rpob mutant gene).
Statistical analysis
All data were statistically analyzed using Statistical Package for Social Sciences (SPSS) program version 16.0. Categorical data were presented as frequency and percentages. Cases were compared for risk factors associated with Non-MDR/MDR- TB; test of significance at 5% p value was used. Odds ratios (Or) were also calculated. Binary logistic regression analysis was used to model the predictors of Non- MDR/MDR- TB.

Results

The frequency and percentages of socio-demographic characters of TB patients
The socio demographic characteristics of study subjects is given in Table 1. When the age of patients was considered, nearly one in every 4 cases (23.2%) and one in every 23 cases (4.4%) were less than 22 years and greater than 65 years of age respectively. The oldest age group (more than 65 years) represented a minority group (4.4%) of cases. Majority of the cases lie in the age range of 22-43 years (42.2%). Regarding the gender, males constituted 68% of cases, while male to female ratio was approximately 2:1. Inversely, urban to rural residence ratio was nearly 1:1. When the occupation of study patients was analyzed, nearly one twelfths (7.6%) of cases was employed.
Table 1: The frequency and percentages of patients’ socio-demographic characters both in MDR and Non-MDR-TB patients visiting Gondar University teaching hospital in 2012/13.
With regard to opportunistic infections, one fourths (19.6%) of the TB patients were HIV positive. Whenever mode of transmission is investigated, 9.6% patients obtained the disease from family followed by friend and nosocomial which is 8.4% each. However, the higher percentages of patients (73.6%) were found that they did not know where they got infection.
Surprisingly, the present study showed that almost half (49.6%), of the patients have the history of previous anti TB drug treatment and 45.6% of the patients been illiterate.
The association of risk factors and drug resistance development in TB patients
As shown in Table 2 the age of patients is significantly associated with drug resistance development (p=0.005). In the age range of 0-21 year the percentage of Non-MDRTB patients (58.6%) is higher as compared with MDR-TB patients’ percentage (41.4%) in the same age group. However in the age range of 22-43 year the percentage of MDR-TB patients (63.1%) is greater than to Non-MDRTB patients’ percentage (36.9%). In the age ranges, 44-65 year and greater than 65 years the percentage Non-MDRTB patients’ (57.7%, 72.7% respectively) is higher as compared to the percentage of MDR-TB patients’ (42.3% and 27.3% respectively). The percentage of MDR-TB male patients’ (53.5%) is greater than to female MDR-TB patients’ percentage (42.5%) even though the percentage of Non-MDR-TB male patients’ (46.5%) is less as compared to female Non-MDR-TB patients’ percentage (57.5%).
Table 2: The distribution of MDR and Non-MDRTB in different risk factors of patients visiting Gondar University teaching hospital in 2012/13. (Note: P value; DF and χ2 test were computed by SPSS version 16.0(DF degree of freedom,*p<0.05)
HIV infection was found to strongly associated with drug resistance development (P=0.000). The prevalence of TB-HIV coinfection was 49/250 (19.6%). The percentage of TB-HIV co-infection was higher in MDR-TB patients, 36/49 (73.5%) as compared to Non MDR-TB patients, 13/49(26.5%). The origin of infection was found to be significantly risk factor for TB infection and had association with drug resistance development (P=0.004). The percentage of infection from family (79.2%) and nosocomial (61.9%) in MDR-TB patients’ is higher as compared to the percentage of infection from family (20.6%) and nosocomial (38.1%) in Non-MDR-TB patients. The history of patients’ prior TB treatment was found to be significantly associated with drug resistance development (P=0.000). Even though the percentage of Non-MDRTB patients without prior TB treatment (78.6%) exceeded the percentage of MDRTB patients with prior TB treatment (21.4%), the percentage of MDR-TB patients with prior TB treatment (79.0%) was found to be higher to that of the percentage of Non-MDRTB patients with prior TB treatment history (21%). It was found that the association between literacy, residence, employment status and sex were to be none significant for drug resistance development (p=0.475, 0.057, 0.811 and 103 respectively). However the habit of TB patients to take anti TB drugs properly was found to have strong association with drug resistance development (p=0.000). The percentage of improperly taking anti TB drugs (65.7%) by MDR-TB patients was greater than by Non-MDRTB patients (34.3%); on the other hand, the percentage of properly taking anti TB drugs (39.7%) by MDR-TB patients was less than by Non-MDR-TB patients (60.3%).
The distribution of MDR and Non-MDR TB in different risk factors of patients
As shown in Table 3, it can be noticed that age groups 22-43 years (371.1%) and 44-65 years (95.8%) more likely to develop drug resistance (OR: 4.711, 1.958 respectively) as compared with age group greater than 65 years. Infection from family (165.7%) and nosocomial infection (169.3%) are more likely to develop drug resistance (OR: 2.657 and 2.693 respectively) as compared with infection from unknown sources. HIV infection, previous anti TB drug treatment history, residence and the habit of taking drugs improperly are found significantly risk factors for the development of drug resistant TB (P values 0.004, 0.000, 0.044 and 0.001 respectively). HIV negative TB patients are 77.3% less likely to develop drug resistant TB as compared with HIV positive patients (OR=0.227). Previously untreated TB patients are 95.1% less likely to develop drug resistance as compared with previously treated TB patients (OR=0.049). TB patients from rural site are 108.5% more likely to develop drug resistant TB as compared with TB patients from urban residence (or=2.085). TB patients that take anti TB drugs improperly are 284.3% more likely to develop drug resistant TB as compared with TB patients that take the anti TB drugs properly (OR=3.843).
Table 3: Binary logistic regression analysis of risk factors for drug resistance development of TB patients visiting Gondar university teaching hospital in 2012/13. (Note : P value; β and OR were computed by SPSS version 16.0)
The frequency of mutant rpoB gene in MDR-TB patients
After amplification a sharp band of 517 bp of amplified DNA was visualized under UV light in 32 smear positive (non-converged) samples and 5 smear negative (converged) samples of MDR-TB samples after staining the gels with ethidium bromide (0.5 μg/ml) for 15 minutes and de-staining with distilled water. However there was no any PCR product that was amplified from smear positive susceptive sputum sample. The presence of a distinct band of 517 bp (rpoB) was considered as a positive PCR result for M. tuberculosis DNA to the mutant rpoB allele.
In this study 46 DNA samples were used as a negative control from smear positive (non-converged) susceptible TB patients. Out of the 46 RMP-resistant samples from smear positive (non-converged) MDR-TB patients, PCR assay confirmed the resistance in 32 (69.6%) casesand out of the 46 RMP-resistant samples from smear negative (converged) MDR-TB patients, PCR assay confirmed the resistance in 5 (10.8%) cases. There was no any PCR product obtained from smear positive (non-converge) susceptible sputum samples, indicating the absence of the mutant rpoB allele in susceptible bacilli.

Discussion

In this study, Binary logistic regression analysis showed five relevant risk factors for drug resistance development which are age, HIV co-infection, origin of infection, history of prior anti TB treatment and drugs misuse. In the present study, more than half (65/125) of MDR-TB was between 22 – 43 years. Several reports found that younger age was predominantly associated with drug resistant TB [24-26]. The lowest prevalence of drug resistance in this study was observed in the elderly group, more than 65 years (27.3%) (Table 2). Other report showed that the percentage of drug resistant TB patients more than 65 years was 1.7% [24]. This might be explained by reduced exposure due to sedentary lifestyle of old people.
The high frequency of TB infection from unknown source (184/250) among TB patients in the present study may indicate the lower level of the community awareness about disease transmission means.
Gender differences in TB epidemiology may arise either as a result of differences in biological functioning (hormones role) or due to differences in exposure as a consequence of differences in the societal roles of men and women [27]. In the present study most of TB patients (68%) were male. Marahatta et al. [28] also found that 70% of TB patients were males, which is in agreement with the present study. Raziq et al. [29] found 2:1 male to female ratio in the number of TB cases which is exactly similar with this study (2:1). In the present study none of the genders were associated with drug resistance development in TB patients (p=0.103). However, Borgdorff et al. [30] and Muayad et al. [31] studies showed that male gender is associated with an increased risk for drug resistance development among tuberculosis cases (p=0.013 and 0.000 respectively).
Previous treatment of TB has been consistently reported as the risk factor within various clinical conditions and populations [28,32,33] and there is a clear association between development of drug-resistant TB and previous treatment [34]. The present study also revealed that history of previous TB treatment carried a higher risk of developing drug resistant TB (P=0.000) which agreed with [31] that showed that patients’ previous TB treatment history is significantly risk factor for drug resistance development (p=0.000). HIV infection decreases an individual’s immunity, and patients with HIV infection reportedly experience pulmonary tuberculosis [35]. The present study showed that being HIV-positive is an independent risk factor for tuberculosis drug resistance development (p=000). When studying the association between HIV status (Table 3) and drug resistance, it was found that HIV negative patients are 77.3% less likely to develop drug resistance (OR=0.227) as compared with HIV positive TB patients. The prevalence of TB-HIV co-infection was 49/250 (19.6%) which was higher in MDR-TB patients, 36/250 (36.8%) as compared with Non MDR-TB patients, 13/250 (13.25%) which is in agreement with other finding [36]. However, other studies revealed that the lack of association between MDR-TB and HIV [37,38]. It is hypothesized that HIV infection favours the transmission of MDRTB strains [24] and on an individual level, it has been suggested that immune suppression is a mechanism that may allow HIV infection to contribute to the development of MDR-TB. As individuals with HIV infection are more susceptible to new infections, the higher prevalence of MDR-TB in HIV co-infected persons could indicate more recent transmission of drug-resistant strains, compared to reactivation of infection acquired in the distant past in the non-HIV infected population [39].
The present study, surprisingly revealed that positive history of close contact with an identified TB patient made significant difference between MDR-TB and non-MDR-TB cases (p=0.004). However this finding is in contrary with other finding [40]. TB can develop resistance to an antimicrobial agent spontaneously or under the selective pressure of antibiotics, but spontaneous development of resistance to both IHN and RMP in a properly treated patient is virtually impossible [41]. The habit of taking anti TB drugs improperly was found significant risk factor (p=0.00) for the development of drug resistance in TB patients which is in agreement with other study [42].
Although the genotypic assays are very useful for rapid detection of drug resistance, there are some limitations. Firstly, not all MTB drug resistant isolates have mutations in the so-called hot spots of the genes associated with resistance [41]. The rapid detection of MTB by PCR or gene amplification techniques may be the standard laboratory method for diagnosing tuberculosis and offer new opportunities for laboratory testing to improve the diagnosis and management of illness in patients with tuberculosis. The newly designed primer sequence gave reproducible results [43]. In this study 92 M. tuberculosis MDR-TB clinical samples’ DNA expected to carry mutations in rpoB gene within codons 511-533 region [22] had been selected. Resistance-associated mutations in rpoB were found in 32 (69.6%) out of 46 isolates in smear positive MDR-TB samples and 5(10.87%) out of 46 for smear negative MDR-TB samples. It was found that for RMP resistance, the concordance between the observed phenotypic MDR TB and detection of mutation in rpoB by PCR was 69.6% which is less than expected value. This is no entirely unexpected, because mutations outside the hot spot, are also enough to generate a resistant phenotype. This finding was in agreement with other findings [22,44]. There was great difference that has been appeared in the ability of PCR method to detect the frequency of drug resistance between isolates from smear positive (non-converged) and negative (converged) MDR-TB cases with 6:1 ratio. This is because of the microbial load difference between the two cases being low load, even absent absolutely in smear negative cases. Yet, MDR-TB smear negative patients are still in risk of developing XDR-TB if they stop taking drugs. In the present work there was no detection of mutation in all rifampin susceptible samples which is in line with the results obtained from DNA sequencing and probe based assay [45-47].
Although the small sample size in this study may have influenced the results and the definitive conclusion, this study yields several interesting findings. Based on the obtained data, history of anti TB drug treatment, HIV infection, drug misuse, age and history of contact with TB patients are important risk factors for drug resistance development in TB patients. This may be attributed to several possible rationalizations including facilitate the spread of drug resistant bacilli and the problems associated with drug misuse. The higher prevalence of MDR-TB among HIV/TB co-infected patients than non-MDR-TB/ HIV positive and low percentage in HIV negative individuals indicates that MDR-TB cases are higher in HIV patients than in the general population.
Based on our experience, PCR assay could be used to detect mutations in M. tuberculosis rpoB gene for clinical practice, the outcome can be used to guide the start of therapy especially in patients with prior inadequate anti tuberculosis treatment and HIV positive patients. MDR-TB smear negative (converged) patients will be in risk of developing XDR-TB if they stop their medication. In conclusion, the present study shows that the frequency of mutant rpoB allele is high considerably in MDR M. tuberculosis isolates obtained from smear positive (no-converged) MDR-TB patients. The data have important implications for designing region-specific rapid methods for detecting majority of RIF-resistance development which can be serve as MDR-TB marker.
Since drug resistance can also be developed due to mutations in the locus outside the hot spot region, investigation of mutations outside the hot spot region in addition to the hot spot region would be accurate to predict the prevalence mutant rpoB gene. Molecular analysis of rpoB gene of M. tuberculosis by sequencing is required to predict mutations responsible for drug resistance development outside the hot spot region. Drug resistance development has association with the patients’socio-demographic factors. Therefore further investigations of patient socio-demographic factors like alcoholism, diabetes status, living style and smoking cigarettes are required to propose a more vivid justification. Careful monitoring of transmission trends of drug resistant strains should be considered a priority for ensuring a successful TB control. This could be done by increasing the public awareness, early case detection, rapid drug susceptibility testing and a full course of effective anti-TB treatment.

Acknowledgments

The authors are very much great full for DR. Deepak K Verma, Department of Biotechnology for bringing primers. Dr. Erimias Dino, Department of Internal medicine College of Medicine and health sciences, deserves acknowledgment as he was very kind in providing samples for this study.

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