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Background:
Systematic Review

Prevalence of Mutated Colistin-Resistant Klebsiella pneumoniae: A Systematic Review and Meta-Analysis

by
Nik Yusnoraini Yusof
1,*,
Nur Iffah Izzati Norazzman
1,
Siti Nur’ain Warddah Ab Hakim
1,2,
Mawaddah Mohd Azlan
1,
Amy Amilda Anthony
1,
Fatin Hamimi Mustafa
1,
Naveed Ahmed
3,
Ali A. Rabaan
4,5,6,
Souad A. Almuthree
7,
Abdulsalam Alawfi
8,
Amer Alshengeti
8,9,
Sara Alwarthan
10,
Mohammed Garout
11,
Eman Alawad
12 and
Chan Yean Yean
1,3,*
1
Institute for Research in Molecular Medicine (INFORMM), Health Campus, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia
2
Faculty Science and Marine Environment, Universiti Malaysia Terengganu, Kuala Nerus 21030, Terengganu, Malaysia
3
Department of Medical Microbiology and Parasitology, School of Medical Sciences, Universiti Sains Malaysia, Kubang Kerian 16150, Kelantan, Malaysia
4
Molecular Diagnostic Laboratory, Johns Hopkins Aramco Healthcare, Dhahran 31311, Saudi Arabia
5
College of Medicine, Alfaisal University, Riyadh 11533, Saudi Arabia
6
Department of Public Health and Nutrition, The University of Haripur, Haripur 22610, Pakistan
7
Department of Infectious Disease, King Abdullah Medical City, Makkah 43442, Saudi Arabia
8
Department of Pediatrics, College of Medicine, Taibah University, Al-Madinah 41491, Saudi Arabia
9
Department of Infection Prevention and Control, Prince Mohammad Bin Abdulaziz Hospital, National Guard Health Affairs, Al-Madinah 41491, Saudi Arabia
10
Department of Internal Medicine, College of Medicine, Imam Abdulrahman Bin Faisal University, Dammam 34212, Saudi Arabia
11
Department of Community Medicine and Health Care for Pilgrims, Faculty of Medicine, Umm Al-Qura University, Makkah 21955, Saudi Arabia
12
Adult Infectious Diseases Department, Prince Mohammed Bin Abdulaziz Hospital, Riyadh 11474, Saudi Arabia
 
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*
Authors to whom correspondence should be addressed.
Trop. Med. Infect. Dis. 2022, 7(12), 414; https://doi.org/10.3390/tropicalmed7120414
Submission received: 13 October 2022 / Revised: 21 November 2022 / Accepted: 28 November 2022 / Published: 2 December 2022
(This article belongs to the Special Issue Clinically Relevant Bacterial Infections)
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Abstract

:
The emergence of genetic mutations in chromosomal genes and the transmissible plasmid-mediated colistin resistance gene may have helped in the spread of colistin resistance among various Klebsiella pneumoniae (K. pneumoniae) isolates and other different bacteria. In this study, the prevalence of mutated colistin-resistant K. pneumoniae isolates was studied globally using a systematic review and meta-analysis approach. A systematic search was conducted in databases including PubMed, ScienceDirect, Scopus and Google Scholar. The pooled prevalence of mutated colistin resistance in K. pneumoniae isolates was analyzed using Comprehensive Meta-Analysis Software (CMA). A total of 50 articles were included in this study. The pooled prevalence of mutated colistin resistance in K. pneumoniae was estimated at 75.4% (95% CI = 67.2–82.1) at high heterogeneity (I2 = 81.742%, p-value < 0.001). Meanwhile, the results of the subgroup analysis demonstrated the highest prevalence in Saudi Arabia with 97.9% (95% CI = 74.1–99.9%) and Egypt, with 4.5% (95% CI = 0.6–26.1%), had the lowest. The majority of mutations could be observed in the mgrB gene (88%), pmrB gene (54%) and phoQ gene (44%). The current study showed a high prevalence of the mutation of colistin resistance genes in K. pneumoniae. Therefore, it is recommended that regular monitoring be performed to control the spread of colistin resistance.

1. Introduction

Paenibacillus polymyxa, previously known as Bacillus polymyxa var. colistinus, is the source of the polymyxins, polycationic peptide antibiotic class, which were first discovered in 1947 [1]. Clinically, polymyxin B and polymyxin E (also known as colistin) are two available forms of polymyxin agents [2]. Since 1959, colistin has been prescribed to people infected with Gram-negative bacteria, including Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella spp., Escherichia coli and other Enterobacterales [1]. Considering colistin’s adverse side effects, including nephrotoxicity and neurotoxicity, the use of colistin rapidly decreased from the early 1970s to the early 2000s [3].
Colistin exerts its antibacterial action against Gram-negative bacteria via interaction with the lipid A, a component of the lipopolysaccharide (LPS) of the outer membrane (OM) [4]. The uniqueness of colistin’s chemical structure makes it an excellent amphipathic agent that can act in a detergent-like manner to alter the structure of the OM [3]. It attaches to the lipid A, replacing the phosphate groups, the membrane stabilizers of LPS, with divalent cations, Ca2+ and Mg2+ [1,5]. Subsequently, the bacterial membrane destabilizes, causing leakage of the cellular contents, resulting in bacterial lysis and death [3]. Recently, colistin has been reevaluated as a viable therapeutic choice for critically ill patients due to the widespread of multidrug-resistant (MDR) Gram-negative bacteria and the dearth of novel antibacterial agents [1,2]. Additionally, its effectiveness against almost all MDR Gram-negative bacteria, including K. pneumoniae, makes colistin a last resort drug of choice [3,6].
K. pneumoniae is a Gram-negative bacterium with a rod shape and is categorized under the Enterobacteriaceae family [7]. It causes one-third of Gram-negative infections in nosocomial and community-acquired infections globally [2,8]. A wide range of illnesses, such as bloodstream infections, wound infections, urinary tract infections (UTIs) [9], pneumonia, as well as infections at the surgical site have been reported in people infected with K. pneumoniae. Nowadays, it is progressively difficult to cure diseases caused by K. pneumoniae due to the rising incidence of antibiotic resistance isolates [5].
In 1983, K. pneumoniae was first reported to be resistant to beta-lactam antibiotics due to its ability to produce extended-spectrum beta-lactamases (ESBL). Hence, carbapenems were given to treat infections of this bacteria [2]. Unfortunately, carbapenem-resistant K. pneumoniae (CRKP) started to emerge due to the rapid spread of oxacillinase-48 (OXA-48), New Delhi metallo-beta-lactamase (NDM), and K. pneumoniae carbapenemase (KPC) [5]. The constant increase in the prevalence of CRKP infections as well as the limitation of treatment options has posed a serious menace to human health, therefore increasing the human mortality rates. Hence, tigecycline and colistin are used as the ultimate drug options in the treatment of MDR K. pneumoniae infections that are resistant to extended-spectrum cephalosporins, carbapenems, amino-glycosides, and fluoroquinolones [2,8].
Colistin-resistant K. pneumoniae (ColRkp) has sadly started to spread worldwide as a result of the overuse and improper use of colistin in human and animal medicine [6]. The development of colistin resistance in K. pneumoniae could happen due to several reasons. The most frequent mechanism is the alteration of the molecular structure of LPS, which lowers its affinity for colistin [3,10]. The genetic mutations on chromosomal genes lead to LPS modifications by inactivating the mgrB gene, upregulating the PhoP/PhoQ signaling system and PmrA-regulated pmrHFIJKLM operon [2,3]. In addition, K. pneumoniae is able to become resistant to colistin upon acquiring the plasmid gene, which is the mcr gene [3]. To date, ten mcr homologues (mcr-1 to mcr-10) have been identified [11].
The discovery of mutational chromosomal genes and plasmid-mediated colistin resistance is worrying due to its potential to expedite the transmission of colistin resistance between various K. pneumoniae strains and different bacteria [3]. Therefore, it is critical to have a better understanding of the occurrence of mutations in ColRkp to assist in the development of more effective interventional measures that are capable of reducing the spread of MDR K. pneumoniae. The current systematic review and meta-analysis aim to gather the information that is currently known on colistin resistance gene mutations in K. pneumoniae and to estimate the global prevalence of ColRkp.

2. Materials and Methods

2.1. Search Strategy

A thorough systematic literature search was performed using the keywords: (colistin resistance gene) OR (Polymyxin-E) OR (mutation in colistin resistance gene) AND (Klebsiella pneumoniae) on four databases: PubMed, ScienceDirect, Scopus, and Google Scholar. Criteria such as time of publication, study design, and language were omitted from the search filters to ensure comprehensive data collection.

2.2. Inclusion and Exclusion Criteria

The following studies were included in our study based on the following criteria: (1) study about K. pneumoniae, (2) study reporting on colistin resistance gene in K. pneumoniae, (3) study on mutation in colistin resistance gene in K. pneumoniae, (4) studies written in English. Studies with insufficient information, review papers, books, case reports, media reports, short letters, and studies not reporting K. pneumoniae and colistin resistance genes in K. pneumoniae were excluded.

2.3. Quality Assessment

The Joanna Briggs Institute’s (JBI) critical appraisal technique for studies reporting prevalence data was used to evaluate the eligibility of the studies. The appraisal checklist consists of nine key questions, which focus on the proper sample frame, study topic, and adequate data analysis. Each response is graded as “yes”, “no”, or “unclear”. The response “yes” received a score of 1, while the responses “no” and “unclear” received scores of 0. Studies deemed to be of high quality and included in the study had scores of 7 or higher from the checklist.

2.4. Data Extraction

Data from relevant studies were retrieved under the following requirements: (1) author, (2) year of publication, (3) period of study, (4) country of study, (5) type of sample (human/animal/environment), (6) number of colistin resistance isolates, (7) number of mutated cases, (8) mutation detection method, (9) genes encoded for colistin resistance, (10) mutated colistin resistance genes. Studies that analyzed colistin gene mutations from more than one country were categorized as multiple countries rather than individual countries to prevent confusion during data extraction and analysis.

2.5. Data Analysis

The Comprehensive Meta-Analysis Software (CMA) Version 3.0 (Biostat, Inc., Englewood, NJ, USA) was used to analyze the data on the prevalence of mutated ColRkp and colistin resistance gene mutations in ColRkp isolates. The subgroup analysis was carried out according to the country of study. A random-effects model using the DerSimonian–Laird method of meta-analysis at a 95% confidence interval (CI) was used to measure the pooled prevalence of the mutational colistin resistance gene in K. pneumoniae. Heterogeneity was determined using I2 test statistics. The value of I2 ≤ 25% denoted low heterogeneity, 25% < I2 ≤ 75% denoted moderate heterogeneity, and I2 > 75% denoted high heterogeneity [10]. Funnel plot diagrams and Egger’s regression test were employed to evaluate whether publication bias existed. For all tests, a p-value of < 0.05 was considered statistically significant.

3. Results

3.1. Search and Screening Results

A total of 1966 articles, as shown in Figure 1, were identified through online databases (Google Scholar = 734; PubMed = 835; ScienceDirect = 32; Scopus = 365) based on the keywords used. The screening process continued with 1688 articles involved. According to the inclusion and exclusion criteria, 1373 articles were removed from consideration after the title and abstract screening procedure, while 315 articles were accepted. Then, the remaining articles proceeded to the full-text screening process, which resulted in 207 articles being selected to proceed further for data extraction. Meanwhile, 157 articles were removed due to the high and moderate risk bias based on the quality evaluation score that was less or equal to six (≤6 score) (Supplementary Table S1). Finally, only 50 studies that portrayed all the selected criteria would be accepted for further analysis.

3.2. Characteristics of the Eligible Studies

All the eligible studies included in the meta-analyses were of high methodological quality (Supplementary Table S1). From 50 studies included in this review, the highest numbers were from Italy (n = 6), India (n = 5), China (n = 5) and Korea (n = 5). The genomic data of 1215 colistin-resistant isolates were analyzed for the presence of colistin resistance genes and mutated colistin resistance genes (Table 1). Of 1215, there were 1203 and 12 isolated from humans and animals, respectively. The most frequently reported colistin resistance genes were mgrB gene (n = 44, 88%), pmrB gene (n = 27, 54%), phoQ gene (n = 24, 48%), phoP gene (n = 20, 40%) and pmrA gene (n = 11, 22%) (Figure 2A). The K. pneumoniae isolates have been found to acquire mobilized colistin resistance (mcr) genes. Two types of mcr genes were also reported, mcr-1 (n = 7, 14%) and mcr-8 (n = 3, 6%) genes. Out of 1215 isolates, 836 isolates (824 from humans and 12 from animals) were found to have mutations in their genes associated with colistin resistance. The most common method for determining mutations in colistin resistance genes of K. pneumoniae isolated from all the studies included in this systematic review and meta-analysis study was DNA sequencing (Sanger, whole-genome or next generation sequencing). From the mutational data analyzed (Figure 2B), the studies detected mutations in the mgrB gene (88%), pmrB gene (54%), and phoQ gene (44%). The ompK36 gene, arnB gene and arnT gene had the same percentage which was 6%. The detected mutations are listed in Supplementary Table S2.

3.3. The Pooled Prevalence of Mutated Colistin-Resistant K. pneumoniae (ColRkp)

Based on the random-effect model, the pooled prevalence of ColRkp mutations was estimated at 75.4% (95% CI = 67.2–82.1), with high heterogeneity (I2 = 81.742%, p-value < 0.001) (Figure 3). However, publication bias was observed, as represented in the asymmetrical funnel plot (Figure 4). Therefore, Egger’s test was used to evaluate the extent of bias. The result of this test revealed a significant publication bias (p-value < 0.001).

3.4. Subgroup Meta-Analysis

The subgroup analysis was carried out according to the country of the included studies. Fifteen countries with low heterogeneity were Chile, Croatia, Egypt, France, Greece, Japan, Nigeria, Qatar, Saudi Arabia, Spain, Tunisia, Turkey, United Kingdom, United States, and Vietnam (I2 = 0%). The result of the analysis (Table 2) showed that Saudi Arabia (n = 1) with 97.9% (95% CI = 74.1–99.9%) had the highest pooled prevalence and Egypt (n = 1) with 4.5% (95% CI = 0.6–26.1%) had the lowest. Interestingly, India and Korea, possessing the same number of studies (n = 5), had a similar prevalence, which was 68.6% (95% CI = 37.3–88.9%). Meanwhile, the heterogeneity was highest among studies conducted in multiple countries (n = 2) (I2 = 91.559%, p-value = 0.001) followed by Brazil (n = 2) (I2 = 90.805%, p-value = 0.001), India (n = 5) (I2 = 79.819%, p-value = 0.001), China (n = 5) (I2 = 79.333%, p-value = 0.001) and Iran (I2 = 75.566%, p-value = 0.006).

4. Discussion

Specific mutations in the chromosomal genes and transmissible plasmid genes are associated with colistin resistance in Enterobacteriaceae, including K. pneumoniae [62]. To the best of our knowledge, this is the first report evaluating the prevalence of mutation in colistin resistance genes in ColRkp worldwide.
In this study, 1215 ColRkp isolated from 23 countries between 2006 and 2020 were studied. The majority of ColRkp was isolated from humans (99%) and the rest was collected from animals. All isolates from animals were found to have mutations in the colistin resistance genes, whereas 68.50% of human isolated-ColRkp carried mutated colistin resistance genes. Based on our meta-analysis, the pooled prevalence of mutated ColRkp isolated from humans and animals was 75.4%. The high pooled prevalence may be the result of over-prescription of colistin in human medicine, global trade and travel to endemic countries [63]. Similarly, the long-term use of colistin in veterinary medicine may have contributed to the rise in the number of colistin-resistant isolates.
Based on country, the highest pooled prevalence was recorded in Saudi Arabia with 97.9% (95% CI = 74.1–99.9%). This result was supported by a study conducted in King Fahad Hospital, Medina, which also showed high resistance rates for colistin, 40.7% [64]. Colistin was known to be used as an alternative treatment to treat K. pneumoniae infection in Saudi Arabia when the first-choice treatments, carbapenems, imipenem and meropenem, were not effective for treating the infected patients. However, this value should be interpreted cautiously since only one study was reported in this country (n = 1). The low number of the studies included in the meta-analysis might cause over-estimation or low-estimation of pooled prevalence. Similarly, Vietnam (96.8%, 95% CI = 80.4–99.5%), Tunisia (96.4%, 95% CI = 61.6–99.8%), Qatar (96.4%, 95% CI = 61.6–99.8%), United Kingdom (96.0%, 95% CI = 76.5–99.4%) and Chile (94.4%, 95% CI = 49.5–99.7%) also reported the high pooled prevalence, but the number of studies conducted in these countries were also limited (n = 1).
It was found in the current study that eight countries in the Asian region showed high prevalence (>50%) of mutated colistin-resistant K. pneumoniae. This was followed by four countries in the Middle East (Saudi Arabia, Qatar, Tunisia and Iran) and Europe (France, Greece, Italy and United Kingdom), two in South America (Brazil and Chile), and one in Africa (Nigeria). Meanwhile, two European (Spain and Croatia) countries and one Middle Eastern (Egypt) country showed low prevalence (< 50%) of these strains. These data demonstrate the global dissemination and evolution of colistin resistance in K. pneumoniae, highlighting the necessity to evaluate antimicrobial resistance (AMR) management strategies internationally rather than localized ones. Controlling AMR necessitates looking at more than simply the quantity of antibiotics used, the types of antibiotics utilized, and the patterns of antibiotic use. There is an immediate need to learn more about the spread of AMR and how the current social, economic, and policy settings facilitate its development.
Specifically, the majority of the data was from Asia, with the highest number of reports (21/50; 42%). This was followed by Europe (11/50; 22%), the Middle East (7/50; 14%), America (5/50; 10%) and Africa (1/50; 2%). Most studies were conducted in urban areas, which have a greater accessibility to antimicrobial drugs and the mutational pattern of colistin resistance in rural areas may differ. Additionally, policies of conducting antimicrobial susceptible testing will differ regionally across hospitals and, frequently, these policies will not be applied in a consistent manner.
According to the analyses, there was significant high heterogeneity, I2 = 85.785%. Hence, subgroup analysis based on the country of the study was performed to discover the sources of heterogeneity. As a result, we were able to reduce the effect of heterogeneity for some countries, except for multiple countries (I2 = 91.559%, p-value = 0.001) and Brazil (I2 = 90.805%, p-value = 0.001) that reported higher heterogeneity compared to the pooled prevalence’s heterogeneity. We postulated that the diverse mutation detection methods used in each study may have contributed to the high heterogeneity. Some studies used both molecular techniques (including PCR, WGS and Sanger sequencing) and bioinformatics analysis (such as ResFinder, and ISfinder) while other studies used either molecular methods or bioinformatics tools to detect mutations in colistin resistance genes. Therefore, it is critically important to ensure which method provides high sensitivity and specificity for detecting both all currently known- and new-mutation colistin resistance genes in the future to improve our understanding of colistin resistance mechanisms.
Most of the reported mutations occurred in the mgrB gene (88%), followed by the pmrB gene (54%), phoQ gene (44%), phoP gene (36%) and pmrA gene (18%) (Figure 2B). The significant number of research reports on these genes’ alterations could be attributed to their high relationship with colistin-resistant isolates. Both pmrA and pmrB genes (encoded for PmrA and PmrB, respectively) work together via the PmrAB two-component system (TCS). The activated PmrAB TCS activates the transcription of the pmrCAB and pmrHFIJKLM operons, which subsequently cause LPS modifications with the addition of 4-amino-4-deoxy-L-arabinose (L-Ara4N) or phosphoethanolamine (pEtN) [7,63]. Another TCS is PhoPQ encoded by phoP and phoQ genes. The activated PhoPQ TCS activates the transcription of pmrHFIJKLM operon, resulting in modification of LPS with L-Ara4N. At the same time, the phosphorylated PhoP (the activated form of PhoP protein) also promotes the activation of PmrA via PmrD, a connector protein, hence, upregulating the PmrAB signal indirectly. Interestingly, the PhoPQ is regulated by MgrB protein (also called YobG), a small regulatory transmembrane protein constituted of 47 amino acids encoded by the mgrB gene [6,7]. MgrB acts as a negative feedback regulator of the PhoPQ TCS [6]. It represses PhoQ thus, the phosphorylation of PhoP represses and reduces the production of pEtN [6,7].
The genetic alterations of the mgrB gene are well-characterized to be responsible for acquiring colistin resistance in K. pneumoniae [7,65,66,67]. Furthermore, judging from the significant number of reports of mutations in the mgrB gene (88%), this mechanism seems to be the most common colistin resistance. Mutations in the mgrB gene upregulate the PhoPQ TCS and consequently activate the pmrHFIJKLM operon, promoting overproduction of L-Ara4N that will block the binding of colistin to LPS [63]. Various non-sense mutations causing premature termination, frameshift deletions, partial or complete deletions of mgrB locus, stop codon mutations leading to truncated gene products and amino acid substitutions were reported in the eligible study (refer to Supplementary Table S2) causing resistance to colistin.
It has been reported that insertional inactivation of the mgrB gene can be responsible for the acquired colistin resistance in K. pneumoniae [6]. Inactivation of the mgrB gene by insertion sequences (IS) of ISKpn25, ISKpn26, IS903, and ISCs68, IS5, or ISKpn14 has already been reported to cause colistin resistance in K. pneumoniae strains [6,68]. Our data showed insertion elements IS1, ISKpn14, IS903, IS903B, ISKpn28, IS10R, ISKpn26, IS5, IS26, IS1R, IS102, ISEc68, ISEcp1, IS1F, IS3, ISKpn25, IS10, ISKpn18, ISKpn13 were reported, with IS5 being the most commonly reported (Supplementary Table S2). IS are small (~0.7 to ~2.5 kbp), mobile genetic elements found in most bacterial genomes including K. pneumoniae whose presence can bring severe threat to the genome structure and gene expression [69]. IS5 element insertions in colistin-resistant derivatives are most likely endogenous, as they already exist in susceptible parental strains’ genomes [69]. Based on this finding, it reveals that the insertion of an IS5 may modulate the expression and/or function of mgrB, hence promoting colistin resistance in K. pneumoniae following exposure to colistin [23]. In this review, the insertion of various IS elements in the mgrB gene was observed to cause inactivation or truncation of mgrB, leading to loss-of-function of MgrB. IS elements are thought to be essential to adaptive evolution in bacteria by promoting genetic diversity [58]. Thus, it is crucial to keep updated on the mutations in the mgrB gene by IS monitoring in K. pneumoniae which might halt the spread of colistin resistance and reduce the risk for treatment failure [58].
Mutations in pmrB (54%) were more commonly reported than in pmrA (18%). According to Huang et al. [70], there are at least 70 nonsynonymous substitutions in pmrB related to the acquisition of colistin resistance. The substitution of threonine to proline at position 157 (Thr157Pro) in pmrB was highly reported in the eligible studies (Supplementary Table S2). A study comparing colistin-susceptible with colistin-resistant isolates collected from the same patient identified proline in the resistant isolate at position 157 instead of threonine (found in the susceptible isolate and other wild-type strains) [71]. Other studies also discovered the same mutations in their colistin-resistant isolates [72,73,74], thus strengthening the hypothesis that Thr157Pro plays an important role in acquiring colistin resistance. In pmrA, amino acid substitution Gly53Cys has been reported to confer resistance to colistin in K. pneumoniae [7,70]. However, in this review, only one study reported a mutation of Gly53Cys in ColRkp isolates [32].
Furthermore, Thr151Ala, Leu26Gln, and Arg114Ala mutations in the phoP gene were the most frequently reported in the included studies (Supplementary Table S2). Both Leu26Gln (in the N-terminal receiver domain of PhoP) and Arg114Ala mutations are known to confer colistin resistance in K. pneumoniae [70,74,75]. In contrast, there is no evidence of Thr151Ala mutation causing colistin resistance, even though it was detected in ColRkp isolates. On the other hand, in phoQ, the Asp150Gly mutation was widely observed in the eligible studies (Supplementary Table S2) and was known to cause colistin resistance [76,77]. Interestingly, this mutation was also found in the PhoQ periplasmic domain (PD) of Salmonella enterica, serotype typhimurium, resulting in higher levels of PhoQ [78].
Moreover, CrrA/CrrB is another TCS whose function appears to be linked to the PmrA/PmrB regulatory system. The function of the CrrA/CrrB TCS is unknown, but the CrrA/CrrB TCS likely influences the PmrA/PmrB TCS through CrrC, a connector protein. Some K. pneumoniae strains have CrrA/CrrB, and it has been noted those mutations in the crrB gene cause higher MICs of colistin [7]. According to our extracted data, both the crrA gene (4%) and the crrB gene (16%) (Figure 2) were found in ColRkp recorded in the included studies in which both of them were mutated. Mutations in the crrB gene that lead to amino acid substitution were reported in the eligible studies, including Leu94Met, Gln10Leu, Tyr31His, Trp140Arg, Asn141Ile, Pro151Ser, Ser195Asn and others (Supplementary Table S2).
Other than that, the plasmid-mediated colistin-resistant mcr gene is known to be one of the mechanisms of acquired colistin resistance [79]. The plasmid-mediated mcr gene was responsible for the horizontal transfer of colistin resistance, and was described recently in Enterobacteriaceae worldwide [9]. The mcr-1 gene was first discovered in 2015 in K. pneumoniae and E. coli isolates from China [7]. The mcr-1 gene encodes pEtN transferase, which adds pEtN to the lipid A moiety [7,64]. In this study, aside from the mcr-1 gene (14%), the mcr-8 gene (6%) was also reported in the included studies (Figure 2A).

5. Study Limitations

Even though we have systematized the data on the occurrence of the mutation of ColRkp, this study has a few limitations. First, due to a lack of resources in some countries, this study was unable to cover all countries in order to present a thorough overview of the prevalence of the ColRkp mutation. Second, the number of studies from some countries was exceptionally high or limited, which may affect the total estimate. In addition, the majority of the isolates were from human samples, but there were very few isolates from animal samples and none of environmental samples that were eligible for the inclusion criteria; hence, a subgroup analysis incorporating the source of samples to assess and compare the prevalence between the source of samples could not be performed as it may reduce the power of the analysis. The case reports and short communications were not included in the current study, which may have led to some data being overlooked. Furthermore, we searched data from a limited number of databases for our systematic review and meta-analysis. Articles that have appeared in other databases or that are not indexed in the indices searched may have been ignored. We have also only included items published in English; as a result, publications in other languages may have been overlooked.

6. Conclusions

In this study, a systematic review and meta-analysis study were conducted to report the worldwide prevalence of the mutation in the colistin resistance gene, estimated at 75.4%, which is considerably high. The estimated point is nevertheless a good indicator of the prevalence of the mutation in the colistin resistance gene globally, despite the considerable heterogeneity (I2 = 85.785%) that was found. Chromosome-related gene mutations, such as those in the mgrB, pmrB, phoQ, phoP and pmrA genes, were frequently observed. Additionally, the acquisition of the mcr-1 and mcr-8 genes was documented in the studies that qualified. It was thought that the colistin resistance in K. pneumoniae was caused by the mutation of these genes and the acquisition of genes from plasmids. The prevalence of this mutation must therefore be periodically evaluated in order to stop the development of ColRkp from spreading further, since its potential impact and a lack of treatment options may result in future danger. Furthermore, ColRkp belonging to sequence types often associated with human diseases (ST11, ST37 and ST15) were found among the commensal bacteria of food animals [25]. This poses a serious danger due to the possibility of these pathogens being transmitted to humans via the food chain or direct exposure.
In light of the fact that effective antimicrobial therapy has not yet been determined for ColRkp, it is important to carefully review the antimicrobial chosen for treatment. With no new antimicrobials on the horizon for treating resistant healthcare-associated infections, it is also imperative that effective preventative programs and adequate personnel be implemented to stem the tide of ColRkp. In order to control and prevent the resilience of drug-resistant pathogens, the development of rapid, low-cost, and accurate detection of determinants and mutations conferring resistance is urgently needed for routine applications of molecular analyses and to improve patient management by identifying the optimum treatment options. Consequently, it is believed that unnecessary procedures and the improper use of antibiotics should be avoided in the healthcare setting for better infectious disease surveillance and management. The high antimicrobial resistance rates are among the most serious health threats worldwide. The current study provides a thorough description of prevalence of colistin resistance among K. pneumoniae isolates throughout the world with the addition of the prevalence of drug resistance genes. Hence, it will help to the authorities to take some necessary measures in order to control antimicrobial resistance.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/tropicalmed7120414/s1, Table S1. Quality of the included studies by the JBI critical appraisal checklist for studies reporting prevalence data. Table S2. Type of mutation in colistin-resistant genes.

Author Contributions

Conceptualization and methodology, N.Y.Y. and S.N.W.A.H.; data extraction, synthesis, and interpretation, N.Y.Y., S.N.W.A.H., N.I.I.N., M.M.A. and A.A.A.; formal analysis, N.I.I.N.; validation, N.Y.Y., A.A.R., S.A.A., A.A. (Abdulsalam Alawfi) and A.A. (Amer Alshengeti); writing (original draft preparation), N.Y.Y., S.N.W.A.H. and N.I.I.N.; writing (review and editing) N.Y.Y., C.Y.Y., N.A., S.A., M.G., E.A. and F.H.M.; supervision, N.Y.Y.; funding acquisition, N.Y.Y. and C.Y.Y. All authors have read and agreed to the published version of the manuscript.

Funding

We would like to thank the Fundamental Research Grant Scheme from the Ministry of Higher Education Malaysia for financial support, (Grant number FRGS/1/2022/SKK06/USM/02/7, Account No: 203.CIPPM.6712049) and Universiti Sains Malaysia (USM) Short Term Grant (grant number 304.CIPPM.6315337).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The datasets used and/or analyzed during the current study are included in the manuscript.

Acknowledgments

We would like to thank Nur Fatihah Mohd Zaidi and Basyirah Ghazali from the Institute for Research in Molecular Medicine, Universiti Sains Malaysia, Kubang Kerian 16150, Malaysia, for their technical support.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. PRISMA flowchart illustrating the process of identifying, screening and selecting the eligible articles in this study.
Figure 1. PRISMA flowchart illustrating the process of identifying, screening and selecting the eligible articles in this study.
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Figure 2. The percentage of reported (A) colistin resistance genes and (B) mutated colistin resistance genes. Others: acrS, arnA, arnC, crrA, ompK35, ompK37, pagP, phoR, pmrE, pmrF, pmrJ, pmrK and ramR.
Figure 2. The percentage of reported (A) colistin resistance genes and (B) mutated colistin resistance genes. Others: acrS, arnA, arnC, crrA, ompK35, ompK37, pagP, phoR, pmrE, pmrF, pmrJ, pmrK and ramR.
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Figure 3. Forest plot showing the pooled prevalence of mutated colistin-resistant K. pneumoniae (ColRkp) estimated by a random effect model of meta-analysis (75.4%, I2 = 81.742, 95% CI = 67.2–82.1, p-value < 0.001). The event rate was calculated to report the summary effect size. Studies are displayed as squares, and size of the square indicates the weight given to the study in meta-analysis using CMA software [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61].
Figure 3. Forest plot showing the pooled prevalence of mutated colistin-resistant K. pneumoniae (ColRkp) estimated by a random effect model of meta-analysis (75.4%, I2 = 81.742, 95% CI = 67.2–82.1, p-value < 0.001). The event rate was calculated to report the summary effect size. Studies are displayed as squares, and size of the square indicates the weight given to the study in meta-analysis using CMA software [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61].
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Figure 4. Funnel plot showing the evidence of publication bias.
Figure 4. Funnel plot showing the evidence of publication bias.
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Table
Table 1. Characteristics of the 50 included studies in this review.
Table 1. Characteristics of the 50 included studies in this review.
No.Study ID (ref)Country of StudyPeriod of StudySource of SampleNo. of Colistin-Resistant K. pneumoniaeNo. of Mutated CasesMutation Detection MethodGenes Encoded for Colistin ResistanceMutated Colistin Resistance Genes
1Avgoulea et al., 2018 [12]Greece2012–2014Human1915WGS, ResFindermgrB (15)mgrB (15)
2Azam et al., 2021 [13]India2017–2018Human1110PROVEAN, PCRmgrB (4), phoP (1), phoQ (4), pmrA (1), pmrB (7)mgrB (4), phoP (1), phoQ (4), pmrA (1), pmrB (7)
3Baron et al., 2021 [14]France2014–2017Human2214WGS, PROVEANacrS (12), crrB (10), mgrB (2), phoP (1), phoQ (2), pmrA (13), pmrB (11)acrS (12), crrB (10), mgrB (2), phoP (1), phoQ (2), pmrA (13), pmrB (11)
4Barragán-Prada et al., 2019 [15]Spain2014–2015Human214WGS, PCR, Sanger sequencing, ISMappermgrB (3), pmrA (1), pmrB (1)mgrB (3), pmrA (1), pmrB (1)
5Berglund et al., 2018 [16]Vietnam2015Human3130WGS, ResFinder, Sanger sequencing, ISFindermgrB (31)mgrB (30)
6Bonura et al., 2015 [17]Italy2014Human4032PCR, sequencingmgrB (40)mgrB (32)
7Can et al., 2018 [18]Turkey2015–2016Human11583SequencingmgrB (83)mgrB (83)
8Cannatelli et al., 2014 [19]Multiple countries2010–2012Human6639PCRmgrB (66)mgrB (39)
9Chen et al., 2021 [20]China2020Human22WGS, ResFinder, ISfindermgrB (2)mgrB (2)
10Cheng et al., 2016 [21]TaiwanNAHuman88PCR, sequencingcrrB (8)crrB (8)
11Choi & Ko, 2015 [22]KoreaNAHuman1212SequencingphoP (4), phoQ (12), pmrB (12)phoP (4), phoQ (12), pmrB (12)
12Choi & Ko, 2020 [23]Korea2006–2007Human52WGSmgrB (2), phoQ (1)mgrB (2), phoQ (1)
13da Silva et al., 2020 [24]Brazil2015–2016Human3029WGS, ISfindermgrB (29)mgrB (29)
14Di Tella et al., 2019 [25]Italy2014–2017Human1918PCR, Sanger sequencingmgrB (18)mgrB (18)
15D’Onofrio et al., 2020 [26]Croatia2013–2018Human146WGSmgrB (3), phoP (6), phoQ (6), pmrB (6)mgrB (3), phoP (6), phoQ (6), pmrB (6)
16Eltai et al., 2020 [27]Qatar2020Human1313WGSmcr-1 (1), mcr-8 (2), mgrB (4), phoP (13)mgrB (4), phoP (13)
17Esposito et al., 2018 [28]Italy2015–2016Human2525PCR, sequencingcrrB (21), mgrB (25), phoQ (4), pmrA (4), pmrB (4)crrB (3), mgrB (22), phoQ (4), pmrA (1), pmrB (1)
18Gentile et al., 2020 [29]Italy2013–2014Human2726NGS, ResFindermgrB (27), phoQ (27), pmrB (27)mgrB (14), phoQ (12), pmrB (2)
19Giordano et al., 2018 [30]Italy2015–2016Human2924WGS, ResFinder, ISfindermcr-1 (1), mgrB (22), phoP (2), pmrA (3), pmrB (3)mgrB (22), phoP (2), pmrA (3), pmrB (3)
20Haeili et al., 2017 [31]Iran2015–2017Human2020PCR, sequencingmgrB (20), phoP (20), phoQ (20), pmrA (20), pmrB (20)mgrB (15), pmrB (19)
21Huang et al., 2021 [32]Taiwan2016–2019Human2420PCR, Sanger sequencing, ISfindercrrA (1), mgrB (13), phoP (1), phoQ (2), pmrA (1), pmrB (3)crrA (1), mgrB (13), phoP (1), phoQ (2), pmrA (1), pmrB (3)
22Jaidane et al., 2018 [33]Tunisia2012–2016Human1313WGS, ResFinder,mgrB (13), phoP (13), phoQ (13), pmrA (13), pmrB (13), pmrC (13)mgrB (13), phoQ (9), pmrA (5), pmrB (9), pmrC (13)
23Kim & Ko, 2018 [34]KoreaNAHuman4032PCR, sequencingcrrA (4), crrB (5), mgrB (17), phoP (1), phoQ (7), pmrB (3)crrA (2), crrB (5), mgrB (17), phoP (1), phoQ (7), pmrB (3)
24Lagerbäck et al., 2016 [35]United StateNAHuman22PCR, sequencingmgrB (1), pmrB (2)mgrB (1), pmrB (2)
25Lee et al., 2021 [36]Korea2008–2018Human22PCR, sequencingmgrB (2), ompK35 (1), ompK36 (2), pmrB (2), pmrC (2), pmrE (2), pmrK (2)mgrB (2), ompK35 (1), ompK36 (2), pmrB (2), pmrC (2), pmrE (2), pmrK (2)
26Leung et al., 2017 [37]United State2008–2012Human119PCR, NGScrrB (4), mgrB (9), pmrB (3), pmrF (2), pmrJ (4), pmrK (3)crrB (4), mgrB (7), pmrB (3), pmrF (2), pmrJ (1), pmrK (1)
27Liu et al., 2021 [38]China2017–2019Human5313WGSmcr-1 (3), mcr-8 (1), mgrB (3), phoQ (1), pmrA (1), pmrB (11)mgrB (3), phoQ (1), pmrA (1), pmrB (11)
28Longo et al., 2019 [39]Brazil2016Human2310WGS, PROVEANcrrB (3), mgrB (10), phoQ (10), pmrB (10)crrB (3), mgrB (7), phoQ (6), pmrB (9)
29Lu et al., 2018 [40]China2015–2016Human53WGS, ResFindermcr-1 (1), phoQ (3)phoQ (3)
30Malli et al., 2018 [41]Greece2016–2017Human9875PCR, sequencingmgrB (98)mgrB (75)
31Mathur et al., 2018 [42]IndiaNAHuman88WGSarnA (8), arnB (4), arnC (8), arnT (8), mgrB (2), pagP (6), phoP (8), phoQ (8), pmrB (8), pmrC (8), pmrJ (6)arnA (8), arnB (4), arnC (8), arnT (8), mgrB (2), pagP (6), phoP (8), phoQ (8), pmrB (8), pmrC (8), pmrJ (6)
32Mirshekar et al., 2020 [43]Iran2018–2019Human204PCR, sequencing, ISfindermgrB (20)mgrB (4)
33Moghimi, Haeili & Mohajjel Shoja, 2021 [44]IranNAHuman95PCR, sequencingmgrB (9)mgrB (5)
34Morales-León et al., 2020 [45]Chile2011–2014Human88WGS, ResFinder, PROVEANmgrB (4), phoP (4), phoQ (1), pmrB (3)mgrB (4), phoP (4), phoQ (1), pmrB (3)
35Ngbede et al., 2021 [46]Nigeria2016–2019Human and animal1717WGS, PROVEANarnT (1), crrB (17), mcr-1 (3), mcr-8 (5), mgrB (17), ompK36 (10), ompK37 (17), ramR (17)arnT (1), crrB (17), mgrB (17), ompK36 (10), ompK37 (17), ramR (17)
36Otter et al., 2017 [47]United Kingdom2014–2015Human2524WGSmgrB (23), phoQ (1)mgrB (23), phoQ (1)
37Palani et al., 2020 [48]India2017–2018Human2511PCR, sequencingmgrB (25)mgrB (11)
38Poirel et al., 2015 [49]Multiple countriesNAHuman4712PCR, sequencing, ISfindermgrB (12)mgrB (12)
39Pragasam et al., 2017 [50]India2013–2015Human88PCR, WGSarnA (8), arnB (7), arnC (8), arnT (8), mgrB (4), pagP (6), phoP (8), phoQ (8), phoR (3), pmrB (7), pmrC (8)arnA (8), arnB (7), arnC (8), arnT (8), mgrB (4), pagP (4), phoP (8), phoQ (8), phoR (3), pmrB (7), pmrC (8)
40Sato et al., 2020 [51]Japan2017Human43WGS, ResFinderphoP (1), pmrB (2)phoP (1), pmrB (2)
41Seo et al., 2021 [52]KoreaNAHuman3515SequencingphoP (14), phoQ (10), pmrB (9)phoP (14), phoQ (10), pmrB (9)
42Shankar et al., 2019 [53]India2016–2017Human6519PCR, sequencing, ISfindermgrB (12), phoP (3) phoQ (9)mgrB (12), phoP (3), phoQ (9)
43Sharahi et al., 2021 [54]Iran2016–2018Human166PCR, ISfindermgrB (16), phoP (16), phoQ (16), pmrA (16), pmrB (16)mgrB (6), phoP (1), phoQ (1), pmrB (1)
44Uz Zaman et al., 2018 [55]Saudi Arabia2011–2015Human2323PCR, Sanger sequencing, ISfindermgrB (18), phoP (6)mgrB (18), phoP (6)
45Venditti et al., 2021 [56]Italy2019–2020Human66WGSmgrB (6), ompK35 (6), ompK36 (6)mgrB (6), ompK35 (6), ompK36 (6)
46Wang et al., 2017 [57]China2011–2014Human and animal1716PCR, WGSmcr-1 (4), mgrB (17), phoQ (17), pmrB (17)mgrB (6), pmrB (16)
47Yang et al., 2020 [58]Taiwan2012–2015Human4948PCR, sequencingcrrB (28), mgrB (32), phoP (4), phoQ (10), pmrA (5), pmrB (16)crrB (28), mgrB (31), phoP (4), phoQ (10), pmrA (5), pmrB (16)
48Zafer et al., 2019 [59]Egypt2016–2017Human221PCR, sequencingmcr-1 (1), mgrB (12)mgrB (1)
49Zhang et al., 2019 [60]China2015Human33PCR, sequencingpmrB (3)pmrB (3)
50Zhu et al., 2019 [61]GreeceNAHuman88PCR, Sanger sequencingarnB (1), mgrB (8), phoP (8), phoQ (3), pmrB (1), pmrC (1),arnB (1), mgrB (8), phoP (8), phoQ (3), pmrB (1), pmrC (1)
(n): number of isolates. NA: not applicable. NGS: next generation sequencing. PCR: polymerase chain reaction. PROVEAN: Protein Variation Effect Analyzer.
Table
Table 2. Subgroup analysis of prevalence of mutated colistin-resistant K. pneumoniae (ColRkp) according to countries of studies.
Table 2. Subgroup analysis of prevalence of mutated colistin-resistant K. pneumoniae (ColRkp) according to countries of studies.
Country of StudyNo. of StudyPrevalence (%)95% CII2QHeterogeneity Test
DFp
Brazil280.810.8–99.390.80510.87510.001
Chile194.449.5–99.70.0000.00001.000
China571.329.3–93.779.33319.35540.001
Croatia142.920.6–68.40.0000.00001.000
Egypt14.50.6–26.10.0000.00001.000
France163.642.3–80.70.0000.00001.000
Greece377.569.3–84.10.0001.27920.528
India568.637.3–88.979.81919.82140.001
Iran451.020.7–80.675.56612.27830.006
Italy688.478.6–94.128.4376.98750.222
Japan175.023.8–96.60.0000.00001.000
Korea568.639.9–87.774.00415.38740.004
Multiple countries241.714.9–74.591.55911.84710.001
Nigeria197.267.8–99.80.0000.00001.000
Qatar196.461.6–99.80.0000.00001.000
Saudi Arabia197.974.1–99.90.0000.00001.000
Spain119.07.3–41.20.0000.00001.000
Taiwan392.873.6–98.351.0714.08820.130
Tunisia196.461.6–99.80.0000.00001.000
Turkey172.263.3–79.60.0000.00001.000
United Kingdom196.076.5–99.40.0000.00001.000
United States282.153.9–94.80.0000.00410.952
Vietnam196.880.4–99.50.0000.00001.000
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Yusof, N.Y.; Norazzman, N.I.I.; Hakim, S.N.W.A.; Azlan, M.M.; Anthony, A.A.; Mustafa, F.H.; Ahmed, N.; Rabaan, A.A.; Almuthree, S.A.; Alawfi, A.; et al. Prevalence of Mutated Colistin-Resistant Klebsiella pneumoniae: A Systematic Review and Meta-Analysis. Trop. Med. Infect. Dis. 2022, 7, 414. https://doi.org/10.3390/tropicalmed7120414

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Yusof NY, Norazzman NII, Hakim SNWA, Azlan MM, Anthony AA, Mustafa FH, Ahmed N, Rabaan AA, Almuthree SA, Alawfi A, et al. Prevalence of Mutated Colistin-Resistant Klebsiella pneumoniae: A Systematic Review and Meta-Analysis. Tropical Medicine and Infectious Disease. 2022; 7(12):414. https://doi.org/10.3390/tropicalmed7120414

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Yusof, Nik Yusnoraini, Nur Iffah Izzati Norazzman, Siti Nur’ain Warddah Ab Hakim, Mawaddah Mohd Azlan, Amy Amilda Anthony, Fatin Hamimi Mustafa, Naveed Ahmed, Ali A. Rabaan, Souad A. Almuthree, Abdulsalam Alawfi, and et al. 2022. "Prevalence of Mutated Colistin-Resistant Klebsiella pneumoniae: A Systematic Review and Meta-Analysis" Tropical Medicine and Infectious Disease 7, no. 12: 414. https://doi.org/10.3390/tropicalmed7120414

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