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.
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
| 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 |
Characteristics of included studies that reported resistance to colistin by mgrB mutation in the present meta-analysis.
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.
Statements
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.
Funding
The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
Acknowledgments
We would like to thank Mahmoud Yousefifard from the Physiology Research Center, Iran University of Medical Sciences, for supporting us during this study.
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
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Summary
Keywords
colistin, mgrB, Klebsiella pneumoniae, colistin-resistant, global prevalence
Citation
Khoshbayan A, Narimisa N, Elahi Z, Bostanghadiri N, Razavi S and Shariati A (2024) Global prevalence of mutation in the mgrB gene among clinical isolates of colistin-resistant Klebsiella pneumoniae: a systematic review and meta-analysis. Front. Microbiol. 15:1386478. doi: 10.3389/fmicb.2024.1386478
Received
15 February 2024
Accepted
22 May 2024
Published
07 June 2024
Volume
15 - 2024
Edited by
Giovanni Gherardi, Campus Bio-Medico University, Italy
Reviewed by
Ramesh N., Vellore Institute of Technology, India
Arta Karruli, University Medical Center Mother Teresa (QSUT), Albania
Updates
Copyright
© 2024 Khoshbayan, Narimisa, Elahi, Bostanghadiri, Razavi and Shariati.
This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Aref Shariati, arefshariati0111@sbmu.ac.ir; arefshariati0111@gmail.com
†These authors have contributed equally to this work
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