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Multi Drug Resistant and Heteroresistant Mycobacterium tuberculosis Isolates Variants from Patients in Rural Areas in Eastern Cape

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26 August 2023

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29 August 2023

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Abstract
Multidrug-resistant tuberculosis emerged as a serious challenge to tuberculosis management and control. In the Eastern Cape, the Beijing variants are prevalent and a driving force of multidrug-resistant tuberculosis; hence, we investigated the distribution of gene mutations in Beijing strains compared to non-Beijing strains. Multidrug-resistant tuberculosis and heteroresistant isolates were identified in 412 sputum cultures by drug susceptibility testing. The isolates were analyzed for mutations in three genes associated with resistance to antituberculosis first-line drugs: katG and inhA promoters for isoniazid and rpoB for rifampicin. All isolates were genotyped by spoligotyping. There were more males than females and a more economically active age group in the study. The most prevalent mutations in rpoB resistance were in S531L, katG in S315Tb, and inhA in c-15tb. Heteroresistance was found in 18 isolates. Beijing variants were predominant. Most of the heteroresistant isolates were INH, with heteroresistance occurring more in the inhA gene mutation region c-15tb. Beijing and LAM variants were found more frequently in INH heteroresistant isolates. Mutations in katG S315Tb and rpoB S531L were higher in Beijing variants. The Beijing family is a major contributor to the epidemiological picture and accounts for most of the multidrug-resistant tuberculosis in the study area.
Keywords: 
Subject: Public Health and Healthcare  -   Primary Health Care

1. Introduction

Tuberculosis (TB) is a preventable and treatable infectious disease and is a global human health threat. In 2019 alone, an estimated 360,000 South Africans became ill with TB, and 58,000 people were estimated to have died from the disease [1]. South Africa is known to have a high level of clonal drug-resistant tuberculosis (DR-TB) transmission and it is one of the DR-TB-burdened countries in Africa [2]. DR-TB emerged as a major risk to global TB control. The increased rate of co-infection of TB-HIV is another factor aggravating the control of multi drug resistant tuberculosis (MDR-TB) [3]. Out of the estimated 465,000 people worldwide who developed rifampicin-resistant (RR-TB) and MDR-TB, only 150,359 persons were enrolled for treatment [4,5]. An effective method to limit the spread of MDR-TB, prevent the emergence of new resistance and development of extensively drug-resistant TB (XDR-TB) is early diagnosis of patients using accurate drug susceptibility testing (DST) of M. tuberculosis in clinical specimens and culture isolates to first-line medications [4,5,6,7]. The katG and inhA mutations give rise to high-level and low-level INH resistance respectively. Recent research has revealed that different mutations in M. tuberculosis can confer varying levels of phenotypic resistance to anti-TB medications [8,9,10]. Consequently, the aggregation of mutations at several positions has a comprehensive effect on drug resistance [11]. Heteroresistant tuberculosis (HR-TB) is defined as tuberculosis where there is a coexistence of susceptible and resistant organisms to anti-tuberculosis drugs in the same patient. Heteroresistance is considered a preliminary stage to full resistance or low levels of drug-resistant TB [12]. This may result from mixed infection, whereby resistant and susceptible strains infect the same individual, or from a single clone changing from a susceptible to a resistant strain as a result of genetic mutation under antibiotic stress [13]. The population structure of RR-TB isolates in South Africa is dominated by Beijing and Euro-American (LAM, T, S, and X) strains which can be explained by the historical movement of strains as South Africa was located in a geographically central position in the historical trade route between East and West for hundreds of years [14]. Karmaka et al [15] reported that the Beijing variants is more transmissible than other families.
Several studies have been published on the prevalence of mutations causing MDR in M. tuberculosis in Eastern Cape but this is the first study to provide a distribution and frequencies of gene mutations of MDR-TB and HR -TB among Beijing and non-Beijing variants in rural Eastern Cape.

2. Materials and Methods

Isolates obtained from 412 sputum samples confirmed patients with tuberculosis in National health laboratory services, TB Laboratory, Nelson Mandela Academic Hospital were tested for detection of mutations conferring resistance to anti-TB drugs. This was carried out using GenoType MTBDRplus VER 2.0 and thereafter were spoligotyped. The demographics information of patients was recorded from the laboratory requisition forms.
GenoType MTBDRplus version 2.0 [16] is a DNA strip-based method designed for simultaneous detection of the most important rpoB mutations, which confer RIF resistance and katG and inhA mutations, which confer high-level and low-level INH resistance, respectively [16,17] was used in this study. Three procedures namely DNA extraction, multiplex amplification with biotinylated primers, and reverse hybridization, were performed following the manufacturer's instructions [18]. DNA extraction was performed using a Genolyse kit [18] and following method as prescribed by [16]. Multiplex amplification was carried out in different cycles at different temperatures followed by reverse hybridization using an automated hybridization system, Auto-Lipa 48 system (Innogenetics) following the manufacturer’s instructions [18]. The tested strips were pasted on evaluation sheets provided with the kit in the designated fields by aligning the conjugate control and amplification control bands with the respective lines on the sheet. With the aid of GenoLyse package inserts, the mutation bands were interpreted; the absence of a wild-type band and the presence of a mutant band for a specific gene on the strip implied resistance.
To determine spoligotypes of M. tuberculosis isolates, spoligotyping was done on 412 isolates. The samples were heat-killed and subjected to DNA extraction. Spoligotyping was performed using microbeads from TB-SPOL Kit (Beamedex®, Orsay, France) and the fluorescence intensity was measured using Luminex 200® (Austin, TX) following manufacturer’s instructions. The hybridization patterns were translated into binary and octal formats. The generated binary codes of the isolates were entered into the SITVIT2 database of the Pasteur Institute of Guadeloupe and assigned specific shared international spoligotype signatures (SIT) [19]. Quality control was ensured by using M. tuberculosis H37Rv as a positive control.

3. Results

A total of 412 clinical isolates were analyzed. There were 394 (95,6%) MDR-TB and 18 (4,4%) heteroresistant isolates. Of these isolate patterns 406 (98,5%) isolates matched a pre-existing SIT in the SITVIT2 database, while 6 (1,6%) isolates were not in SIT in the SITVIT2. The majority, 244 (59,2%), were from males, while 168 (40.8%) were from females. The age range was 2 years to 86 years.

3.1. Demographics

Males had more HR isolates compared to females. The economically active age group was more prevalent in the study, with more HR strains (Table 1).

3.2. Resistance profile

All samples were confirmed to be multi-drug-resistant or heteroresistant by the presence of resistance-associated mutations and wild types. Of the 412 DR-TB isolates, there were 394 (95,6%) MDR isolates and 18 (4.4%) heteroresistant isolates.
In the rpoB gene, the S531L region had the highest number of mutations; katG, the S315Tb region, that confers a high level of drug resistance, had the highest number of mutations, and inhA, the c-15tb region, had the highest number of mutations (Table 2).
Most of the HR isolates were INH-HR isolates, with HR occurring more in the inhA gene in mutation region c-15tb. The Beijing variants were found more in INH-HR isolates, and the LAM variants was also more prevalent in INH-HR isolates than RIF-HR isolates (Table 3).

3.3. Genetic diversity

Beijing family was the most prevalent varient among eight varients identified (Table 4)
There were 184 (44,6%) Beijing, 82 (19,9%) LAM, 140 (34,0%) other variants, and 6 (1,5%) unknown variants. Mutations were observed more frequently in region S531L in all strains (Table 5)
We found that the most frequent mutations of katG and inhA occurred at the S315Tb and c-15tb mutation region respectively in Beijing, LAM, and non-Beijing isolates (Table 6).

4. Discussion

The effectiveness of TB treatment is significantly impacted by drug resistance; therefore, effective management of DR-TB depends on the accurate identification of resistance to inform optimal treatment [20]. Due to the high prevalence of TB in South Africa, it is crucial to keep researching the population structure of circulating M. tuberculosis strains in order to identify and comprehend their frequency and distribution. Information on the relationship between gene alterations and the many strains circulating is lacking in our study setting, particularly for the Beijing variant, which is the most common in the East Cape of South Africa and known to be linked to treatment resistance.
Comparable to the findings of [21], the prevalence of males was higher in men than in women (Table 1). This could be due to the social mixing of men, which increases contact rates with TB patients and TB transmission [22]. Men socialize more than women do, and social interaction changes the patterns of infection for infectious diseases. Men are considered to have an advantage over women when it comes to accessing medical services, which has led to an increase in the rate at which men are being diagnosed with TB [20,23], this could be another reason of having more males than females.
The prevalence of Beijing variants (Table 4) which are known to be more contagious than other families, are being explained by the effects of gender-related social mixing patterns on the spread of M. tuberculosis [24] so as HR in males, which confirms the link between socializing in this area and tuberculosis in men. The economically active age group also had prevalence of HR strains, this poses a serious challenge in this setting as transmissibility of these strains can frequently increase due to the social activity of this group. RIF and INH, the two most potent bactericidal medicines for treating TB, are currently the cornerstone of therapy.
Rifampicin and isoniazid resistance are identified using the molecular markers rpoB and katG, respectively. The prevalence of mutations in rpoB gene in this study was higher than the other genes (katG and inhA genes). Resistance to RIF is almost entirely coupled (>97%) to mutations within an 81-bp region of the rpoB gene, called the RIF resistance-determining region (RRDR) [25]. Our study revealed that INH had more mutation in katG gene compared to inhA gene. The katG is associated with high levels of isoniazid resistance. The inhA promoter is associated with a low-level drug resistance which indicates a possible benefit of a drug either with standard or increased dosing from a different drug with the same class [26]. Knowing this is crucial because if the treating clinicians are aware of which patients have the inhA promoter mutation and a significant portion of the patients have isolates with that mutation, there may be a big number of patients who could benefit from high-dose INH [27]. It is crucial that clinicians from this study area are aware of this knowledge since it will reduce the amount of ineffective ethionamide use in these patients, additionally, this gives a warning that in this study setting the treating clinicians needs to monitor closely treatment progress of patients in INH drug.
The rise of RIF-R is a critical public health issue because RIF resistance is a surrogate marker for MDR-TB [28]. This study identified M. tuberculosis as a frequent carrier of mutations in the rpoB gene, particularly in the rifampicin resistance determining region (RRDR) S531. These results concur with studies by [29,30], and they could be attributed to the spread of an established clone. Furthermore, there are instances of S531L mutations occurring often in various South African provinces, demonstrating the prevalence of these mutations in the nation [31] and other parts of the world [32,33]. INH resistance is frequently connected to the primary genetic changes in MDR-TB, notably at S315T [26], suggesting that INH is unlikely to be clinically beneficial. Patients from this region may soon need INH to be given in higher doses as HR is the start of full resistance to a medicine.
The INH had more HR incidence in the inhA gene, which is related with low level resistance. According to [34,35], HR has a role in the failure of TB treatment outcomes. The region of inhA known as c-15tb, which is also the region that is known as the marker of low-level resistance, showed a higher prevalence of HR. Patients with INH-HR TB can use low dose isoniazid but with caution and have their treatment outcomes closely monitored. The foundation of the first-line TB treatment consists of the drugs INH and RIF [36]. MDR-TB, which is resistant to both RIF and INH, typically has a poor prognosis for therapy and a higher fatality rate. It can be difficult to identify drug-resistant isolates in clinical samples when drug-susceptible and drug-resistant isolates coexist [34,35], which can lead to the masking of drug-resistant isolates by drug-susceptible ones [37]. It is thought that this process, known as HR is one of the key steps in the development of drug resistance [38]. When resistant and susceptible strains of an infection infect a person at the same time, or when a single clone undergoes genetic mutation under the influence of antibiotics, HR may result [13].
Beijing variants in this study were found more in INH-HR isolates, LAM variants were also predominating in INH-HR than RIF-HR isolates. GeneXpert can detect rifampicin resistance only when >50 per cent of MTB strains in the samples are resistant, and LPA can detect rifampicin resistance when ≥5 per cent of MTB strains in the samples are resistant [39]. In comparison to non-Beijing variants, Beijing variants are frequently shown to be more drug resistant [40]. The Beijing variant of M. tuberculosis, which was initially discovered in Beijing, China, in 1995 and is now mostly found throughout the world [41] and is the most common lineage in this area [42]. According to reports, the Beijing variant of M. tuberculosis is more lethal, pathogenic, and transmitting more quickly than other variants [15]. It also exhibits increased drug resistance, particularly MDR-TB characteristics, and has a higher fatality rate [43]. Beijing's genetic family is the global TB epidemic, M. tuberculosis is one of the most common genotypes [44], and in some places, like Beijing, it is the most common lineage among MDR-TB strains. The Beijing variants were more widespread than other variants in this study, which may be related to its recognized presence in the nearby provinces of the Eastern Cape namely KwaZulu Natal and Western Cape [15,45]. This variant family has been identified in studies from other regions of South Africa, such as Limpopo, the Western Cape, and Mpumalanga [45,46], where some residents of the rural Eastern Cape relocate in search of employment. In South Africa, it's typical for people to commute between rural and urban areas in pursuit of work; this movement acts as a bridge for the transmission of pathogens across large distances [47].

5. Conclusions

This first report on understanding M. tuberculosis variants association with gene mutations of MDR-TB and heteroresistant cases in rural Eastern Cape and serves as a foundation for future research into the association between gene alterations and the Beijing family, which is more common in this study setting. The future of INH use in this region is in jeopardy due to increased katG gene mutations and increased HR in inhA, which suggest that INH at low doses may no longer help treat patients. Since HR is an important stage in the development of full drug resistance in isolates in our investigation, its influence on treatment progression needs to be watched carefully.

Author Contributions

Conceptualization, L.M.F.; methodology, L.M.F, C.B. and Y.M.; formal analysis, L.M.F., T.K.G., N.S. and N.L.; writing—original draft preparation, L.M.F. and M.C.H.; writing—review and editing, L.M.F., N.D. and M.C.H.; supervision, S.V., and T.A.; project administration, L.M.F., N.D. and B.I.; funding acquisition, L.M.F. All authors have read and agreed to the published version of the manuscript.

Funding

Financial support for this study was obtained from the South African Medical Research Council (SAMRC) Research development grant (Pilot grant).

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Research Ethics and Biosafety Committee of the Faculty of Health Sciences of Walter Sisulu University (Ref. No. 026/2019) and Eastern Cape Department of Health (Ref No EC_201904_011).

Informed Consent Statement

Not applicable. This study used routine samples received in National Health Laboratory Services (NHLS) TB laboratory.

Data Availability Statement

Data can be requested from the corresponding author.

Acknowledgments

The authors are grateful to the NHLS TB laboratory staff and participating clinics for their support during sample analysis and data collection.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of this study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Table 1. Characteristics of study subjects and their association with MDR and HR resistance among isolates.
Table 1. Characteristics of study subjects and their association with MDR and HR resistance among isolates.
Patient characteristics Total (n) MDR-TB (n) HR-TB (n)
Sex
Male 244 231 13
Female 168 163 5
Age category, years
≤25 103 100 3
26–45 207 194 13
46 – 60 63 62 1
≥ 61 40 38 2
Table 2. Number of isolates per region of mutation in rpoB, katG and inhA genes.
Table 2. Number of isolates per region of mutation in rpoB, katG and inhA genes.
rpoB KatG inhA
Region of mutation Number of isolates Region of
mutation		 Number of isolates Region of
mutation		 Number of isolates
D516V 124 S315Tb 338 c-15tb 40
S531L 216 Missing 74 t-8c 4
H526Y 3 t-8a 2
H526D 3 Missing 366
H526D & S531L 2
D516V & S531L 1
Missing 64
Table 3. Variants and heteroresistant genes Isolates.
Table 3. Variants and heteroresistant genes Isolates.
LPA score of HR isolates Region of HR Variant
rpoB WT-MUT/katG MUT/inhA WT rpoB D516V LAM
rpoB WT/ katG WT/ inhA WT-MUT inhA c-15tb T
rpoB WT- MUT/ katG WT/ inhA WT- MUT rpoB H526Y and inhA c-15tb T
rpoB MUT/ katG WT- MUT/ inhA WT katG S315Tb X
rpoB MUT/ katG MUT/ inhA WT-MUT inhA c-15tb LAM
rpoB WT-MUT/ katG MUT/ inhA MUT rpoB H526D LAM
rpoB WT/katG WT/inhA WT-MUT inhA c-15tb Beijing
rpoB MUT/katG WT/inhA WT-MUT inhA c-15tb Beijing
rpoB WT/ katG WT/ inhA WT-MUT inhA c-15tb X
rpoB WT-MUT/ katG MUT/ inhA WT-MUT rpoB S531L inhA c-15tb X
rpoB WT-MUT/ katG WT-MUT/ inhA MUT rpoB S531L katG S315Tb T
rpoB MUT/ katG WT-MUT/ inhA WT katG S315Tb Beijing
rpoB MUT/ katG WT/ inhA WT-MUT inhA c-15tb Beijing
rpoB MUT/ katG WT- MUT/ inhA WT katG S315Tb LAM
rpoB MUT/ katG WT-MUT/ inhA WT-MUT katG S315Tb and inhA c-15tb T
rpoB WT/ katG WT/ inhA WT-MUT inhA c-15tb X
rpoB WT/katG WT-MUT/inhA WT katG S315Tb LAM
rpoB MUT/ katG WT-MUT/ inhA WT-MUT katG S315Tb and inhA c-15tb Beijing
Table 4. Prevalence of variants.
Table 4. Prevalence of variants.
Variant Number of isolates n (%)
Beijing 184 (44,6%)
LAM 82 (19,9%)
X 48 (11,7%)
T 34 (8,3%)
S 31 (7,5%)
EAI 16 (3.9%)
H 6 (1.5%)
CAS
UNKNOWN		 5 (1.2%)
6 (1,5%)
Table 5. Distribution and Frequency of rpoB gene Mutations Among Beijing and Non-Beijing Isolates.
Table 5. Distribution and Frequency of rpoB gene Mutations Among Beijing and Non-Beijing Isolates.
rpoB mutation region Beijing
(n= 184)		 LAM
(n = 82)		 Other
(n =140)		 Unknown
(n=6)
D516V 60 21 42 1
S531L 105 40 66 5
H526Y 1 1 1 0
H526D 2 1 0 0
H526D & S531L 1 0 1 0
D516V & S531L 0 0 1 0
Missing mutation 15 19 30 0
Table 6. Distribution of different mutations conferring INH resistance among Beijing and non-Beijing genotype.
Table 6. Distribution of different mutations conferring INH resistance among Beijing and non-Beijing genotype.
katGmutation region Beijing
(n = 184) 		LAM
(n = 82) 		Other
(n =140) 		Unknown
(n = 6)
S315Tb 152 65 115 6
Missing 32 17 25 0
inhAmutation region Beijing
(n = 184) 		LAM
(n = 82) 		Other
(n = 140) 		Unknown
(n = 6)
c-15tb 20 4 16 0
t-8c 1 3 0 0
t-8a 1 1 0 0
Missing 162 74 124 6
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