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. 2024 Jun 7;15:1386478. doi: 10.3389/fmicb.2024.1386478

Global prevalence of mutation in the mgrB gene among clinical isolates of colistin-resistant Klebsiella pneumoniae: a systematic review and meta-analysis

Amin Khoshbayan 1,2,†, Negar Narimisa 1,2,†, Zahra Elahi 2,3, Narjess Bostanghadiri 1,2, Shabnam Razavi 1,2, Aref Shariati 4,5,*
PMCID: PMC11190090  PMID: 38912352

Abstract

Background

Colistin is used as a last resort for managing infections caused by multidrug-resistant bacteria. However, the high emergence of colistin-resistant strains has restricted the clinical use of this antibiotic in the clinical setting. In the present study, we evaluated the global prevalence of the mutation in the mgrB gene, one of the most important mechanisms of colistin resistance in Klebsiella pneumoniae.

Methods

Several databases, including Scopus, Medline (via PubMed), and Web of Science, were searched (until August 2023) to identify those studies that address the mgrB mutation in clinical isolates of K. pneumoniae. Using Stata software, the pooled prevalence of mgrB mutation and subgroup analyses for the year of publication, country, continent, mgrB mutation types, and detection methods of mgrB mutation were analyzed.

Results

Out of the 115 studies included in the analysis, the prevalence of mgrB mutations in colistin-resistant K. pneumoniae isolates was estimated at 65% of isolates, and mgrB variations with insertional inactivation had the highest prevalence among the five investigated mutations with 69%. The year subgroup analysis indicated an increase in mutated mgrB from 46% in 2014 to 61% in 2022. Europe had the highest prevalence of mutated mgrB at 73%, while Africa had the lowest at 54%.

Conclusion

Mutations in the mgrB gene are reported as one of the most common mechanisms of colistin resistance in K. pneumoniae, and the results of the present study showed that 65% of the reported colistin-resistant K. pneumoniae had a mutation in this gene.

Keywords: colistin, mgrB, Klebsiella pneumoniae, colistin-resistant, global prevalence

1. Introduction

The increasing prevalence of infections due to multidrug-resistant (MDR) bacteria is a major public health concern, and the emergence of antimicrobial resistance has created a difficult challenge for treating a wide variety of infectious diseases (Dadashi et al., 2022). Today, colistin is considered one of the last remaining options for physicians in the fight against MDR and pan-drug-resistant (PDR) bacteria (Moubareck et al., 2018; Menekşe et al., 2019; Moghadam et al., 2022). Colistin, or polymixin E, is a cationic antibiotic and belongs to the polymixin antibiotic class that has that have activity against most Gram-negative bacteria. In the past, colistin had limited use in medicine because of its toxicity, especially nephrotoxicity, but in recent years, due to the increasing rate of MDR bacteria, especially carbapenemase-producing strains, the application of colistin has become more common (Caniaux et al., 2017; Poirel et al., 2017).

However, the high prevalence of colistin-resistant (ColR) strains has restricted the clinical use of colistin. Moreover, a worrying 25–71% mortality rate is reported for colistin-resistant infections (Moubareck et al., 2018; Menekşe et al., 2019; Moghadam et al., 2022).

Enterobacteriaceae cause a wide range of infections in humans. They are capable of acquiring resistance to many antibiotics through horizontal gene transfer (Hasani et al., 2017; Dadashi et al., 2022). Among the bacteria in this family, K. pneumoniae is the most common species that has developed resistance to colistin. Colistin resistance in K. pneumoniae has been reported worldwide in Asia, Europe, North America, South America, and Africa (Ah et al., 2014; Giamarellou, 2016).

Furthermore, resistance to colistin is mainly mediated through chromosomes or horizontal gene transfer. For the first time, the plasmid-borne mcr-1 gene was reported from China, and to date, 10 different types of mcr genes have been reported (Liu et al., 2016; Caniaux et al., 2017; Aris et al., 2020; Hussein et al., 2021). Additionally, chromosomal gene mutations such as pmrA/pmrB, crrA/crrB, and phoP/phoQ, as well as variations in mgrB, are believed to be significant factors in the development of colistin resistance in K. pneumoniae (Cannatelli et al., 2014; Poirel et al., 2017).

The PmrAB and PhoPQ two-component systems are associated with bacterial survival and are usually activated when macrophages attack bacteria. The Pmr system consists of genes and operons involved in adding phosphoethanolamine and 4-amino-4-deoxy-L-arabinose to lipopolysaccharide (LPS; Gunn, 2008; Poirel et al., 2017).

To this end, the inactivation of mgrB causes a negative feedback regulator of the PhoQ-PhoP signaling system, which leads to the acquisition of colistin resistance in K. pneumoniae. This phenomenon ultimately activated the Pmr system, causing modification and reduced affinity of the LPS, which is the colistin target (Cannatelli et al., 2013; Khoshbayan et al., 2021). Collectively, mgrB variation is reported as one of the most common resistance mechanisms among ColR K. pneumoniae isolates (Aghapour et al., 2019). However, there is no exact report on its prevalence among clinical isolates of K. pneumoniae. Therefore, this study aims to investigate the global prevalence of the mutation in the mgrB among clinical isolates of ColR K. pneumoniae.

2. Methods

2.1. Search strategy

A comprehensive and systematic search was conducted for relevant articles by two authors (AKH and NB) until August 2023 in the electronic databases, including Medline (via PubMed), Scopus, and Web of Science. The following search keywords were obtained from the National Library of Medicine’s medical subject heading (MeSH) terms, titles, or abstracts with the help of Boolean operators (and/or) including “Klebsiella pneumoniae” AND “mgrB” with their Mesh terms. The present study was conducted according to the Preferred Reporting Items of the Systematic Review and Meta-Analysis (PRISMA) guidelines.

2.2. Selection criteria and data extraction

Two authors (AKH and NB) worked independently to review the titles, abstracts, and full texts of all retrieved studies, and they excluded irrelevant articles (review articles, case reports, short communication, letters to the editor, brief reports, conference abstracts, and studies with ambiguous results). The search was limited to articles published in English that reported the prevalence of the mgrB in clinical isolates of ColR K. pneumoniae. Disagreements among authors were resolved through discussion and consensus. The information extracted from each of the included articles is as follows: first author name, publication year, country, continent, the total number of K. pneumoniae isolates, number of ColR isolates, number of ColR isolates carrying the mutated mgrB, the mgrB mutation types, and method used for detection of mgrB mutation.

2.3. Quality assessment

An adapted version of the Joanna Briggs Institute (JBI) checklist was used to independently assess study quality by two review authors (ZE and NN; Moola et al., 2017).

2.4. Statistical analysis

A meta-analysis was performed using Stata software v. 17, and a random-effects model estimated the pooled prevalence of the mutated mgrB in ColR K. pneumoniae isolates and the prevalence of five types of mgrB mutation (insertional inactivation, substitution, nonsense mutation, complete and partial deletion) with 95% confidence intervals (95% CI). A Freeman-Tukey double arcsine transformation was performed using the metaprop command of Stata software to estimate the weighted pooled fractions. The I2 value was used to examine statistical heterogeneity between studies. In this regard, I2 ≤ 25% was considered low homogeneity, 25% < I2 ≤ 75% shows moderate heterogeneity, and I2 > 75% indicates high heterogeneity. Potential publication bias was checked using funnel plots and Begg tests. Subgroup analyses were performed for the year of publication, country, continent, and methods used to detect mgrB variations.

3. Results

3.1. Search results

A total of 769 studies were identified in the three electronic databases up to August 2023, and 592 articles were included after duplicate removal. 258 studies after an initial screening of the title and abstract, were eligible for further analysis, of which 115 were included in the final analysis (Supplementary 2, Figure 1).

3.2. Meta-analysis results

In the 115 studies, 2,652 ColR K. pneumoniae and 1,448 ColR isolates with a change in mgrB were found (Table 1). The pooled prevalence of mgrB variations in ColR K. pneumoniae isolates was detected in 65% of isolates (95% CI: 56–72%; I 2 = 91.67%; p < 0.001; Supplementary File 3). The results of Begg’s test (p = 0.4202) showed no publication bias in our study. Noteworthy, the result of publication bias was shown in the funnel plot (Supplementary 2, Figure 2). The year subgroup analysis indicated an increase in mutated mgrB from 46% (95% CI: 27–65%) in 2014 to 61% (95% CI: 43–78%) in 2022. However, in 2023, the results showed a decrease in the rate of mutation to 39% (95% CI: 5–80%), which could be due to the small number of studies compared to 2022 (p = 0.259; Supplementary 2, Figure 3). A subgroup meta-analysis of continents also showed that Europe had the highest rate of mutated mgrB (73%; 95% CI: 63–82%), while Africa had the lowest rate (54%; 95% CI: 9–96%; p = 0.445; Supplementary 2, Figures 4, 5). Among the countries analyzed, Tunisia (95% CI: 97–100%) and Israel (95% CI: 80–100%) with 100% had the highest prevalence of mutated mgrB, while Spain with 8% (95% CI: 0–33%) showed the lowest (p < 0.001; Supplementary 2, Figure 6). Subgroup meta-analysis based on the detection method of mutated mgrB revealed 59% (95% CI: 49–69%) for the polymerase chain reaction (PCR) method and 71% (95% CI: 57–84%) for the whole genome sequencing (WGS) method (p = 0. 219; Supplementary 2, Figure 7). The pooled prevalence of mgrB variations with insertional inactivation in the total number of mgrB variations of ColR K. pneumoniae isolates was 69% (95% CI: 56–72%; I2 = 79.37%; p < 0.001; Supplementary 2, Figure 8). The results of the subgroup meta-analysis showed the only significant difference in the subgroup of countries. Spain had the highest mutation rate with 100% (95% CI: 57–100%) and Serbia had the lowest mutation rate with 0.0% (95% CI: 0–4%), (p < 0.001; Supplementary 4, Figure 3). The pooled prevalence of mgrB variations with substitution in the total number of mgrB variations of ColR K. pneumoniae isolates was 36% (95% CI: 25–48%; I2 = 87.31%; p < 0.001; Supplementary 2, Figure 9). The results of the subgroup meta-analysis showed an increase in the substitution mutation from 18% (95% CI: 8–30%) in 2014 to 50% (95% CI: 19–81%) in 2022 (p < 0.001; Supplementary 4, Figure 5). The highest prevalence of substitution mutation was observed in Brazil at 73% (95% CI: 4–100%), while Taiwan and Greece had the lowest rates with 11% each (95% CI: 2–24% and 6–18%, respectively; p = 0.003; Supplementary 4, Figure 7). Moreover, the subgroup meta-analysis based on the diagnostic method revealed that WGS detected the mutations in 60% of cases (95% CI: 39–80%), while PCR detected mutations in 16% of cases (95% CI: 10–24%; p < 0.001; Supplementary 4, Figure 8). The pooled prevalence of mgrB variations with nonsense mutations in the total number of mgrB variations of ColR K. pneumoniae isolates was 30% (95% CI: 19–42%; I2 = 88.63%; p < 0.001; Supplementary 2, Figure 10). The results of the subgroup meta-analysis showed an increase in nonsense mutations from 18% (95% CI: 9–29%) in 2014 to 100% (95% CI: 100–100%) in 2023 (p < 0.001; Supplementary 4, Figure 9). In addition, Asia had the highest rate of nonsense mutation with 36% (95% CI: 19–55%), while South America had the lowest rate with only 7% (95% CI: 1–17%; p < 0.001; Supplementary 4, Figure 10). Of the countries studied, Iran had the highest prevalence of nonsense mutation, which was 69% (95% CI: 49–87%). On the other hand, Brazil and Serbia had the lowest rate of this mutation, which was 8% (95% CI: 1–18%) and 8% (95% CI: 0–22%), respectively (p < 0.001; Supplementary 4, Figure 11). The pooled prevalence of mgrB variations with complete deletion in the total number of mgrB variations of ColR K. pneumoniae isolates was 19% (95% CI: 11–28%; I2 = 56.99%; p < 0.001; Supplementary 2, Figure 11). The results of the subgroup meta-analysis showed an increase in complete deletion in mgrB from 9% (95% CI: 1–21%) in 2014 to 30% (95% CI: 13–49%) in 2022 (p = 0.002; Supplementary 4, Figure 13). Furthermore, the pooled prevalence of mgrB variations with partial deletion in the total number of mgrB variations of ColR K. pneumoniae isolates was 14% (95% CI: 6–22%; I2 = 69.78%; p < 0.001; Supplementary 2, Figure 12). Among the countries investigated, Brazil had the highest prevalence of partial deletion in mgrB with 52% (95% CI: 9–94%), while Taiwan had the lowest rate of this mutation with 6% (95% CI: 1–14%; p = 0.003; Supplementary 4, Figure 18).

Table 1.

Characteristics of included studies that reported resistance to colistin by mgrB mutation in the present meta-analysis.

Author and references Year Country Continent No. of K. pneumoniae isolates Number of colistin-resistant isolates Number of mgrB mutant isolates Percentage of mgrB mutants in colistin-resistant isolates Method Mutation type
Abozahra et al. (2023) 2023 Egypt Africa 82 32 4 13% PCR 4 NM
Al-Farsi et al. (2019) 2019 Sweden Europe 245 8 8 100% PCR 8 II
Arena et al. (2022) 2022 Italy Europe 19 7 2 29% WGS 2 not report
Avgoulea et al. (2018) 2018 Greece_Italy Europe 19 19 19 (10) 100% WGS 10 II
Azam et al. (2021) 2021 India Asia 335 11 4 36% PCR 3 II, 1 S
Baron et al. (2021) 2020 France Europe 5,304 14 2 14% WGS 1 II, 1 NM
Barragán-Prada et al. (2019) 2019 Spain Europe 30 21 3 14% PCR 3 II
Bathoorn et al. (2016) 2016 Greece Europe 34 19 17 89% WGS 3 S, 14 II
Becker et al. (2018) 2018 Germany Europe 53 1 1 100% WGS 1 NM
Ben-Chetrit et al. (2021) 2021 Israel Asia 7 6 6 100% WGS 2 II, 1 PD, 2 CD, 1 NM
Ben Sallem et al. (2022) 2022 Tunisia Africa 25 1 1 100% PCR 1 S
Zahedi Bialvaei et al. (2023) 2023 Iran Asia 162 161 2 1% PCR 2 NM
Bir et al. (2022) 2022 India Asia 48 7 2 29% WGS 2 S
Bolourchi et al. (2021) 2021 Iran Asia 138 14 6 43% WGS 1 II, 2 NM, 2 S, 1 PD
Bonura et al. (2015) 2015 Italy Europe 94 39 31 79% PCR 13 NM, 16 II, 2 S
Boszczowski et al. (2019) 2019 Brazil South America 28 26 5 19% WGS 4 S, 1 not report
Cabanel et al. (2021) 2021 France_Spain Europe 18 1 1 100% WGS 1 CD
Can et al. (2018) 2018 Turkey Europe 115 115 83 72% PCR 77 II, 6 point mutation and deletions
Cannatelli et al. (2014) 2014 Italy-Greece Europe 66 66 39 59% PCR 22 II, 4 CD, 6 NM, 7 S
Cejas et al. (2019) 2019 Argentina South America 76 11 7 64% PCR 4 CD, 1 NM, 2 S
Chen et al. (2021) 2021 China Asia 3 2 2 100% WGS 2 II
Chen et al. (2022) 2022 China Asia 493 11 8 73% WGS 7 II, 1 PD
Cheng et al. (2015) 2015 Taiwan Asia 26 26 10 38% PCR 8 II, 2 deletion
Cheong et al. (2020) 2020 Korea Asia 252 11 6 55% PCR 5 S, 1 II
Cienfuegos-Gallet et al. (2017) 2017 Colombia South America 156 32 24 75% PCR 22 II, 1 NM, 1 frameshift
Conceição-Neto et al. (2022) 2022 Brazil South America 502 148 39 26% PCR 28 II, 1 S and NM, 8 S, 2 NM
Di Pilato et al. (2021) 2020 Italy Europe 156 63 56 89% WGS 5 S and NM, 2 NM, 19 II, 25 S, 5 PD
Di Tella et al. (2019) 2019 Italy Europe 26 19 19 100% PCR 9 S, 6 II, 2 PD, 1 NM, 1 not reported
Dong et al. (2018) 2018 China Asia 5 2 2 100% WGS 2 II
D’Onofrio et al. (2020) 2020 Croatia Europe 6 6 3 50% WGS 1 II, 2 S
Elias et al. (2022) 2022 Portugal Europe 140 16 8 50% PCR 2 NM, 1 S, 3 II, 2 CD
Esposito et al. (2018) 2018 Italy Europe 25 25 22 88% PCR 5 II, 10 PD, 3 S, 4 NM
Főldes et al. (2022) 2022 Romania Europe 10 10 7 70% WGS 3 II, 4 S
Garcia-Fulgueiras et al. (2021) 2020 Uruguay South America 3 2 2 100% WGS 2 II
Garza-Ramos et al. (2023) 2022 Mexico South America 101 18 1 6% PCR 1 II
Gentile et al. (2020) 2020 Italy Europe 27 27 13 48% WGS 8 PD,1 CD, 1 II, 3 S
Haeili et al. (2017) 2017 Iran Asia 20 20 15 75% PCR 6 II, 9 NM
Halaby et al. (2016) 2016 Netherlands Europe 8 2 1 50% WGS 1 II
Hamel et al. (2020) 2020 Greece Europe 973 213 148 69% PCR 94 II, 24 S, 4 NM, 21 CD, 5 PD
Hu et al. (2023) 2023 China Asia 708 14 9 64% WGS 3 CD, 6 II
Huang et al. (2021) 2021 Taiwan Asia 229 24 17 71% PCR 10 II, 1 NM, 1 PD, 1 S, 4 Not detected
Huang et al. (2022) 2022 Taiwan Asia 35 35 18 51% PCR 3 S, 9 II, 1 PD, 2 frameshift, 3 not detected
Jaidane et al. (2018) 2017 Tunisia Africa 2,826 13 13 100% WGS 2 S and II, 5 S, 1 CD, 2 PD, 3 S and PD
Jayol et al. (2016) 2016 France Europe 561 35 17 49% PCR 10 II, 2 NM, 2 CD, 2 PD, 1 S
Jayol et al. (2018) 2018 Switzerland_France Europe 46 35 17 49% PCR 2 S, 3 NM, 1 PD, 11 II
Jin et al. (2021) 2021 China Asia 11 4 2 50% WGS 2 NM
Karampatakis et al. (2022) 2022 Greece Europe 4 4 4 100% PCR 4 II
Kaza et al. (2024) 2023 India Asia 775 18 7 39% WGS 5 II, 1 S, 1 PD
Khoshbayan et al. (2022) 2022 Iran Asia 195 21 19 90% PCR 19 II
Kim et al. (2020) 2019 Korea Asia 25 4 4 100% WGS 4 II
Kis et al. (2016) 2016 Hungry Europe 312 3 3 100% PCR 3 II
Kong et al. (2021) 2021 China Asia 2 1 1 100% WGS 1 NM
Kumar et al. (2018) 2018 India Asia 932 17 4 24% PCR 3 II, 1 NM
Lalaoui et al. (2019) 2018 Israel Asia 15 3 3 100% PCR 1 II, 2 S
Lee et al. (2021) 2021 Korea Asia 338 2 2 100% PCR 2 II
Leung et al. (2017) 2017 USA North America 22 11 8 73% PCR 1 S, 3 II, 1 NM, 2 deletion, 1 frameshift
Liu et al. (2022) 2022 China Asia 1884 14 7 50% WGS 1 S, 5 II, 1 NM
Lomonaco et al. (2018) 2018 Pakistan-USA Asia-North America 10 7 4 57% WGS 3 II, 1 CD
Longo et al. (2019) 2019 Brazil South America 23 23 7 30% WGS 4 II, 3 PD
López-Camacho et al. (2014) 2013 Spain Europe 26 1 1 100% WGS 1 II
Malli et al. (2018) 2018 Greece Europe 131 98 75 77% PCR 36 II, 22 NM, 6 S, 11 deletion
Mansour et al. (2017) 2017 Tunisia Africa 220 7 7 100% PCR 7 II
Markovska et al. (2022) 2022 Bulgaria Europe 100 29 9 31% PCR 5 II, 2 NM, 2 not detected
Mathur et al. (2018) 2018 India Asia 8 8 2 25% WGS 2 S
Mavroidi et al. (2016) 2016 Greece Europe 135 19 15 (2) 79% PCR 2 II
Mavroidi et al. (2020) 2019 Greece Europe 53 28 15 (4) 54% PCR 4 II
Mills et al. (2021) 2021 USA North America 27 7 5 71% WGS 2 NM, 2 II, 1 S
Mirshekar et al. (2020) 2020 Iran Asia 94 20 4 20% PCR 3 NM, 1 II
Moghimi et al. (2021) 2021 Iran Asia 5 2 2 100% PCR 2 NM
Naha et al. (2022) 2022 India Asia 240 9 3 33% WGS 2 S, 1 NM
Nawfal Dagher et al. (2019) 2019 Lebanon Asia 5 2 1 50% PCR 1 S
Ngbede et al. (2021) 2021 Nigeria-USA Africa-North America 16 16 16 100% WGS 16 S
Nguyen et al. (2021) 2021 Vietnam Asia 8 3 3 100% WGS 3 II
Niazadeh et al. (2022) 2022 Iran Asia 65 6 5 83% PCR 4 S, 1 deletion
Nirwan et al. (2021) 2021 India Asia 16 13 3 23% PCR 1 S, 2 II
Nordmann et al. (2016) 2016 Switzerland Europe 121 94 64 68% PCR 7 S, 11 NM, 33 II, 4 CD, 8 PD, 1 PD and S
Novović et al. (2017) 2017 Serbia Europe 27 27 2 7% PCR 1 II, 1 NM
Okdah et al. (2022) 2022 Saudi Arabia Asia 10 10 4 40% WGS 2 S, 2 inactivation
Olaitan et al. (2014) 2014 - - 32 32 13 41% WGS 3 NM, 3 S, 5 II, 2 not detected
Otter et al. (2017) 2017 UK Europe 38 25 23 92% WGS 23 NM
Palani et al. (2020) 2020 India Asia - 25 11 44% PCR 8 CD, 1 NM, 2 II
Palmieri et al. (2020) 2020 Serbia Europe 2,298 45 45 100% WGS 38 S, 6 NM, 1 II
Pitt et al. (2018) 2018 Australia Oceania 24 19 17 89% PCR-WGS 14 II, 2 NM, 1 S
Poirel et al. (2015) 2014 - - 47 47 12 26% PCR 9 II, 3 NM
Popa et al. (2021) 2021 Romania Europe 23 1 1 100% WGS 1 NM
Pragasam et al. (2017) 2021 India Asia 8 8 4 50% PCR 2 NM, 2 PD
Pu et al. (2023) 2023 China Asia 12 3 2 67% WGS 2 II
Rimoldi et al. (2017) 2017 Italy Europe 68 7 2 29% WGS 2 II
Roch et al. (2022) 2022 Brazil South America 43 35 35 100% WGS 35 S
Rocha et al. (2020) 2020 Brazil South America 2 2 1 50% WGS 1 II
Rocha et al. (2022) 2022 Brazil South America 56 56 49 (13) 88% PCR 9 II, 3 NM, 1 PD
Rubic et al. (2023) 2023 Croatia Europe 34 34 34 100% PCR 34 NM
Shamina et al. (2020) 2020 Russia Europe 159 71 23 32% PCR 19 II, 4 CD
Shankar et al. (2019) 2019 India Asia 65 65 13 20% PCR 3 NM, 6 II, 3 S, 1 No amplification
Sharahi et al. (2021) 2021 Iran Asia 52 16 6 38% PCR 5 NM, 1 II
Singh et al. (2021) 2021 India Asia 22 22 3 14% PCR 3 II
Sisti et al. (2022) 2022 Italy Europe 12 4 3 75% PCR 1 NM, 1 CD, 1 PD
Snyman et al. (2021) 2021 South Africa Africa 7 7 2 29% WGS 1 CD, 1 II
Solgi et al. (2020) 2020 Iran Asia 74 1 1 100% PCR 1 II
Sonnevend et al. (2017) 2017 UAE Asia 9 9 9 100% PCR 9 II
Tietgen et al. (2022) 2022 Germany Europe 12 12 10 83% PCR 5 II, 5 CD
Torres et al. (2021) 2021 Switzerland Europe 20 11 10 91% WGS 2 II, 4 NM, 4 S
Zaman et al. (2018) 2018 Saudi Arabia Asia 23 23 18 78% PCR 17 II, 1 NM
Vendrik et al. (2022) 2022 Netherlands Europe 36 18 7 39% NGS 1 PD, 3 II, 2 S, 1 CD
Wang et al. (2023) 2023 China Asia 189 4 2 50% NGS 2 II
Wright et al. (2015) 2014 USA North America 11 9 6 67% RNA-Seq 1 S, 4 II, 1 CD
Xiao et al. (2023) 2023 China Asia 458 28 1 4% WGS 1 S
Xie et al. (2022) 2022 China Asia 2 1 1 100% ND 1 II
Yang et al. (2020) 2020 Taiwan Asia 49 49 32 65% PCR 6 NM, 17 II, 6 CD, 2 PD, 1 isolate with different pattern
Yap et al. (2020) 2019 Malaysia Asia 2 2 2 100% WGS 2 II
Yoshino et al. (2021) 2021 Japan Asia 5 1 1 100% WGS 1 CD
Yousfi et al. (2019) 2018 Algeria Africa 3 3 1 33% PCR 1 II
Zafer et al. (2019) 2019 Egypt Africa 234 22 1 5% PCR 1 S
Zhang et al. (2018) 2018 China Asia 17 8 8 100% WGS 8 II
Zhu et al. (2019) 2019 Greece Europe 16 8 8 100% PCR 8 II
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PD, Partial Deletion; CD, Complete Deletion; II, Insertional Inactivation; NM, Nonsense Mutations; S, Substitution; ND, Not Determined. In four studies number of mgrB mutated isolates were different from number of mgrB detected isolates that written in parentheses.

4. Discussion

In recent years, the effectiveness of antibiotics against MDR pathogens has decreased, leaving colistin as the last available option (Lim et al., 2010). Numerous mechanisms in Gram-negative bacteria result in changes to the outer membrane, which are the main causes of colistin resistance (Li et al., 2006). As mentioned, mgrB inactivation leads to dysregulation of the PhoQ-PhoP signaling system, eventually leading to LPS modification (Cannatelli et al., 2013).

A recent study declared that MgrB alteration could create a fitness cost in K. pneumoniae related to the bacteria’s environmental survival. This phenomenon could pose a silent threat to hospital transmission, as the physical changes resulting from the mgrB mutation seem to cause resistance to disinfectants.

Furthermore, during a two-year period, Xie et al. isolated one colistin-susceptible isolate and one mgrB-mutated ColR isolate from a patient. The ColR isolate exhibits an increased growth rate, but the colistin-susceptible isolate showed significantly decreased growth during a three-hour period, indicating that colistin resistance might result in resistance to human serum (Xie et al., 2022; Yap et al., 2022). Furthermore, the results of a recently published study showed that mutation of mgrB led to resistance to the Galleria mellonella antimicrobial peptides, and in both in vivo and in vitro experiments, it stimulated little activation of inflammatory responses. This phenomenon could be related to the increased virulence associated with this mutation, as many studies have shown the importance of an inflammatory response for K. pneumoniae clearance (Kidd et al., 2017). Interestingly, another study demonstrated that MgrB-dependent ColR K. pneumoniae isolates exhibit increased survival outside the host, leading to enhanced host-to-host transmission (Bray et al., 2022). Therefore, physicians and researchers must appreciate the importance of mgrB mutant isolates for cautious consideration of colistin utilization in K. pneumoniae infections. The significant rise in ColR isolates observed in recent years is related to the rapidly increasing use of colistin in hospital settings, which eventually accelerates the selection pressure for resistance (Wang et al., 2017; Liu and Liu, 2018). Nevertheless, the precise prevalence of mgrB variations was not reported in the recently published studies, therefore, the current study investigates the prevalence of mutated mgrB among the clinical isolates of ColR K. pneumoniae worldwide.

According to our analysis, 65% of all the ColR K. pneumoniae isolates carried mutated mgrB. Furthermore, the prevalence of the mgrB mutation has steadily increased from 46% in 2014 to 61% in 2022, which is a 15% increase. Similarly, a recent study demonstrates an increase in ColR from 4.8% in 2013–2018 to 8.2% in 2019–2021 in Iran (Narimisa et al., 2022). Moreover, the annual report of the European Antimicrobial Resistance Surveillance Network (EARS-Net) declared that ColR K. pneumoniae has reached a high level of more than 20% in Italy and Greece (Prevention ECfD, Control, 2017; Liu and Liu, 2018). The increasing global use of colistin could lead to an enhanced increase in resistance to the antibiotic, as shown by our analysis of a 15% increase. This phenomenon highlights the urgent need to evaluate the strategies of antimicrobial resistance management internationally (Yusof et al., 2022).

Our results showed that Europe showed the highest rate of mutated mgrB among the continents with 73%, and Africa had the lowest prevalence, with 54%. In 2012, Jaidane et al. demonstrated the emergence of colistin resistance in Tunisia and showed the critical role of MgrB in ColR K. pneumoniae isolates (Jaidane et al., 2018). Furthermore, of the 47 ColR K. pneumoniae isolates in Thailand, mutated mgrB was the leading cause of ColR, which was observed among 43 (91.5%) isolates (Shein et al., 2022). Moreover, a recently published study declared that the most common resistance mechanism among ColR K. pneumoniae isolates in the Middle East is mutations and insertion sequence transpositions in the mgrB (Aris et al., 2020). Moreover, a recent study investigating the prevalence of mutated ColR K. pneumoniae reported that four countries in the Middle East had a high prevalence (>50%) of mutated ColR K. pneumoniae (Saudi Arabia, Qatar, Tunisia, and Iran; Yusof et al., 2022). We observed various mutations in the mgrB locus and categorized them into five groups: insertional inactivation, substitution, nonsense mutation, complete deletion, and partial deletion To view the details, you can refer to the Supplementary Excel file. The prevalence of substitution and complete deletion increased from 2014 to 2022 from 18 to 50% and 9 to 30%, respectively. Additionally, the prevalence of nonsense mutations has increased from 18% in 2014 to 100% in 2023. Insertional inactivation had the highest pooled prevalence among the mgrB variations, at 69%. These small mobile genetic elements are found in the genomes of most bacteria and pose a severe danger to gene structure and expression (Consuegra et al., 2021).

The insertion of IS elements leads to the inactivation or truncation of mgrB, resulting in the malfunction of MgrB (Yang et al., 2020). On many occasions, IS elements are carried by Inc. plasmid groups, and some studies indicate that these plasmids may also carry other resistance genes, like carbapenemase (Fordham et al., 2022). The presence of multidrug-resistant IS-carrying plasmids is a significant concern. The emergence of antimicrobial resistance can lead to colistin therapy, which can mobilize IS elements and potentially create extensively drug-resistant (XDR) or PDR isolates (Fordham et al., 2022). Therefore, monitoring the mutations caused by IS elements in K. pneumoniae is crucial to prevent the worldwide spread of colistin resistance (Yang et al., 2020; Yusof et al., 2022).

Generally, in the analysis of detection methods, it was found that both PCR and WGS methods were equally effective in detecting mutations, with no clear superiority of one over the other. However, WGS was more effective in detecting substitution mutations in 60% of cases, while PCR was effective only in 16%. Therefore, WGS can be considered to be the ideal method for detecting this specific mutation. In combination with Sanger sequencing, PCR has been traditionally used as the gold standard for mutation detection for many years due to its high specificity and low rate of false positives. Although this method has some limitations, such as low sensitivity, it is also time-consuming because of the need for manual analysis of sequencing chromatograms (Gao et al., 2016). Despite these limitations, due to its accessibility and low cost, PCR is still a reasonable and affordable method, especially in developing countries.

5. Limitations

Our study has certain limitations. Because only one study was conducted on the Oceania continent, we could not compare the prevalence of the mgrB mutation in ColR K. pneumoniae with other continents. We did not investigate the sequence type (ST) of resistant isolates because some studies did not report or determine the ST type. In addition, the heterogeneity among studies was relatively high; therefore, subgroup analysis was used to find and reduce the source of heterogeneity.

6. Conclusion

Given the high importance and rise in the global prevalence of ColR K. pneumoniae isolates, it is vital to know the underlying mechanisms related to colistin resistance. The results of the present study showed that 65% of the ColR K. pneumoniae had variation in this gene. Collectively, these findings emphasize the importance of regular monitoring of ColR isolates in clinical settings to stop the spread of ColR isolates. Additionally, adopting innovative screening techniques, practicing antibiotic stewardship, lowering the usage of antibiotics in agriculture, and emphasizing the urgent need to design an organized plan to measure the colistin resistance level are effective strategies to combat antibiotic resistance. In this concept, the exact detection of mechanisms that lead to the mutation in mgrB could significantly decrease the extension of ColR K. pneumoniae. However, more confirmatory studies are needed to advance our knowledge in this field.

Data availability statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary material.

Author contributions

AK: Investigation, Writing – original draft, Writing – review & editing. NN: Writing – original draft, Writing – review & editing. ZE: Writing – review & editing. NB: Writing – review & editing. SR: Writing – review & editing. AS: Writing – review & editing.

Acknowledgments

We would like to thank Mahmoud Yousefifard from the Physiology Research Center, Iran University of Medical Sciences, for supporting us during this study.

Funding Statement

The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision.

Publisher’s note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2024.1386478/full#supplementary-material

Table_1.XLSX (23.3KB, XLSX)
Data_Sheet_1.PDF (213.6KB, PDF)
Data_Sheet_2.PDF (1.9MB, PDF)
Data_Sheet_3.PDF (81.1KB, PDF)
Data_Sheet_4.PDF (1.7MB, PDF)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Table_1.XLSX (23.3KB, XLSX)
Data_Sheet_1.PDF (213.6KB, PDF)
Data_Sheet_2.PDF (1.9MB, PDF)
Data_Sheet_3.PDF (81.1KB, PDF)
Data_Sheet_4.PDF (1.7MB, PDF)

Data Availability Statement

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary material.

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