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Emergence of heteroresistance to carbapenems in Gram-negative clinical isolates from two Egyptian hospitals

BMC Microbiology volume 24, Article number: 278 (2024) Cite this article

Abstract

Background

Antimicrobial resistance is a global concern, linking bacterial genotype and phenotype. However, variability in antibiotic susceptibility within bacterial populations can lead to misclassification. Heteroresistance exemplifies this, where isolates have subpopulations less susceptible than the main population. This study explores heteroresistance in Gram-negative bacteria, distinguishing between carbapenem-sensitive isolates and stable heteroresistant isolates (SHIs).

Methods

A total of 151 Gram-negative clinical isolates including Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii and Proteus mirabilis from various sources were included. Heteroresistant isolates and their stability were detected by disc-diffusion technique while genotypic analysis was carried out by PCR and efflux activity was assessed by ethidium bromide (EtBr)-agar cartwheel method.

Results

A total of 51 heteroresistant subpopulations were detected, producing 16 SHIs upon stability-detection. Amplified resistance genes and EtBr-agar cartwheel method showed a significant difference between resistant subpopulations and their corresponding-sensitive main populations.

Conclusion

Genotypic analysis confirmed that genetic mutation can lead to resistance development although the main populations were sensitive, thereby leading to treatment failure. This is a neglected issue which should be highly considered for better treatment outcomes.

Peer Review reports

Background

It is imperative to have a deeper comprehension of the emergence and dissemination of drug-resistant bacteria in order to address the issue of antibiotic resistance. In addition to better diagnostic instruments, new therapeutic approaches can guide the clinicians to select the most appropriate antimicrobial therapies. Heteroresistance (HR) phenomenon, in which a bacterial isolate contains subpopulations with reduced antibiotic susceptibility compared to the main population [1], can lead to treatment failure [2].

The clinical manifestation of polymicrobial illnesses may be further complicated by highly resistant subpopulations of heteroresistant bacteria [3]. One approach to frame the concept of HR is as an intermediate point between antibiotic sensitivity and resistance [4, 5].

There are two main mechanisms underlying HR as a phenomenon, the first is called polyclonal HR, in which a bacterial infection is followed by a subsequent infection with distinct bacterial isolate [1] as has been described for Mycobacterium tuberculosis and Helicobacter pylori [6, 7]. Rare spontaneous resistance mutants that are proportionately growing in the population under antimicrobial therapy can generate polyclonal HR [1]. Second, there is monoclonal HR which is generated from a single clone that differentiates into two populations (susceptible and resistant) in such case [1]. Genetic HR and physiological (non-genetic) HR are the two potential drivers of monoclonal HR. The primary source of monoclonal heterogeneity is genetic HR [1], which can also lead to point mutations, minor deletions, or tandem gene amplification [8], small deletions or point mutations [9], that lead to instability of such heterogeneous response. Therefore, a significant primary classification would be necessary to differentiate between the two possibilities [7]. It is also to be emphasized that the term “heteroresistance” has been used to describe mixed populations of bacteria with stable genetic differences, including closely related bacteria that formed co-infections with two different strains [10] or mutations [9, 11]. It is important to distinguish HR from other forms of subpopulations-mediated resistance such as persistence and tolerance [2, 12]. It is crucial to identify if subpopulations mediate resistance through tolerance, persistence, heterogeneity, or some other mechanism [4].

The clinical concern of HR detection arises from the possibility that treatment failure may occur due to the emergence of resistant subpopulations after antibiotic exposure [2]. Failure to detect HR by usual diagnostic testing, results in misclassification of some strains as susceptible [1]. In actuality, even in cases where a bacterial isolate is determined to be susceptible to a particular antibiotic, the likelihood of an antibiotic therapy successfully starts at 90% and decreases [13]. Consequently, there is a heavy cost associated with such unexplained treatment failure, and HR may be a contributing factor.

By contrast, no correlation between HR and treatment failure was defined in some studies [14] and cohort studies of vancomycin-treated heteroresistant subpopulations of vancomycin-susceptible Staphylococcus aureus (hVISA) [3, 15, 16]. So, to completely understand which HR-related factors in particular, the frequencies of heteroresistant subpopulations and their resistance levels are likely to alter the treatment outcome, further studies are required. Furthermore, at least some of the disparities between independent investigations may be explained by differences in sample sizes and detection techniques [4].

The main objective of this study was to explore the heteroresistance phenomenon in some Gram-negative isolates (GNIs) and shed the light and further characterize the difference between the carbapenems-sensitive and the heteroresistant GNIs on both phenotypic and genotypic levels.

Materials and methods

Bacterial strains consecutively, non-duplicate isolated, Klebsiella pneumoniae (n = 60), Pseudomonas aeruginosa (n = 60), Escherichia coli (n = 16), Acinetobacter baumannii (n = 9) and Proteus mirabilis (n = 6).

A total of 151 different clinical GNIs were collected from the clinical pathology and pathophysiology lab in Kasr Al-Ainy Hospital and the National Cancer Institute (NCI), Cairo, Egypt, over a period of time from May 2020 to June 2021. Clinical isolates were recovered from various sources, including urine (n = 39), skin and skin structures (n = 35), blood (n = 22), respiratory samples (n = 19), pus (n = 18) and other infection sites (n = 18), using proper sampling techniques [16] from inpatients and outpatients units. The clinical isolates were purified using selective media where EMB agar and MacConkey agar were used alternatively for isolation of E. coli, A. baumannii, K. pneumoniae and P. mirabilis without prejudice, while P. aeruginosa was isolated on cetrimide agar for more specificity [17, 18]. All clinical isolates that had been purified were kept in an ultra-deep freezer (ilShin Europe B.V.) at -80 ºC as glycerol stocks for subsequent studies.

Bacterial isolates identification

Apart from the process of cultivating on selective media noticing the form, color, and appearance of the colonies, pure clinical isolates were identified using biochemical testing subsequent to Gram staining [19]. Urea agar, citrate, lysine iron agar, motility indole ornithine and triple sugar iron media were used for this purpose [20]. All aforementioned tests were performed in Kasr Al-Ainy University Hospitals and NCI, Cairo, Egypt.

Antimicrobial susceptibility testing

All clinical isolates were examined to determine whether it was susceptible to any particular class of antibacterial drug, such as cephalosporins (FEP, cefepime; FOX, cefoxitin), carbapenems (IPM, imipenem; ETP, ertapenem; MEM, meropenem; DOR, doripenem), fluoroquinolones (CIP, ciprofloxacin) aminoglycosides (CN, gentamicin), sulfonamides (SXT, trimethoprim/sulfametho-xazole), beta-lactam combination agents (AMC, amoxicillin/clavulanate), by disc diffusion method of Kirby Bauer on standard Mueller-Hinton agar (MHA) (Oxoid, England) [21].

The classification of isolates as susceptible, intermediate, or resistant was carried out as per the CLSI guidance 2020. For quality control during the entire process, three reference standard strains (E. coli ATCC 25922, K. pneumoniae ATCC 700603 and P. aeruginosa ATCC 27853) were recruited [22].

Detection of heteroresistant subpopulations

Colonies that develop within an antibiotic disc’s zone of inhibition and impact the primary populations, the latter being interpreted as susceptible isolates, were identified as heteroresistant subpopulations [23]. One colony was picked up and purified using streak plate technique [24] and stored as a glycerol stock at -80 ºC for further investigations. The size and distance of the developed colony from the antibiotic disc were not taken into consideration during the random selection process.

Heteroresistance stability detection

The resistance’s stability was examined by determining whether the pure clones isolated from the resistant subpopulations exhibited a reduced resistance phenotype after growing for 40–50 generations in the absence of antibiotics [25, 26]. All colonies, grown in the inhibition zone of a sensitive main population, were sub-cultured for 50 generations without antibiotic exposure.

Antimicrobial susceptibility testing (AST) was performed frequently against the relevant antibiotic every 5 sub-cultures to confirm HR stability. A resistant subpopulation is considered stable heteroresistant when the 10th AST (i.e. after the 50th sub-culturing), gives a resistant interpretation as per CLSI recommendations [9]. If the susceptibility in at least one of the cultures manifestly returned to that of the original parental isolate, the resistance was considered unstable [27].

Phenotypic detection of carbapenemase genes

All stable heteroresistant isolates (SHIs), detected around carbapenems discs (i.e. six isolates), were tested for carbapenemase genes production using the Carbapenem Inactivation Method (CIM) according to CLSI M100 2020 [28].

Detection of efflux pumps by cartwheel method

Efflux pumps activity was detected as previously described [29]. E. coli ATCC 25922 was used as a control. The plates were examined under a UV transilluminator. According to Patil and coworkers, the absence of fluorescence indicates the presence of a functioning efflux pump or pumps in the resistant subpopulations.

Qualitative analysis of biofilm production

All stable heteroresistant strains were tested for biofilm production in an attempt to detect the difference between the heteroresistant and sensitive populations. Production of biofilm was studied by culturing the 16 SHIs on Congo Red Agar (CRA). Inoculated agar was incubated for 48 h at 37 °C and subsequently 2–4 days at room temperature. Biofilm-producing strains grow on CRA, form colonies that are partially or entirely black, while non-producing strains produce mucoid colonies that are somewhat reddish-white [30].

Molecular detection of metallo-β-lactamase (MBL) genes by PCR

In the current work, all SHIs to carbapenems were chosen for a genotypic investigation of the HR phenomenon from species including K. pneumoniae, E. coli and P. aeruginosa.

GeneJET Genomic DNA Purification Kit was used for DNA extraction and purification from bacterial cells. Nano-drop quantification using Q3000-Quawell 0.5-5000 ng/µl was performed to standardize the DNA amount in each sample [31].

The selection of genes for amplification was based on their incidence in Egypt and prevalence in the examined microorganisms [32,33,34,35]. Seven genes namely, blaIMP−1, blaVIM−2, blaNDM−1, blaOXA−48like, blaSIM−1, blaSPM−1 and blaGIM−1, were amplified in the stable carbapenems-heteroresistant subpopulations and their corresponding sensitive main populations.

Primers that have been used to detect carbapenems-resistant genes in the heteroresistant isolates of interest were designed as previously described by Laurent and coworkers [36] confirmed and analyzed on Primer-BLAST website.

https://www.ncbi.nlm.nih.gov/tools/primer-blast/primertool.cgi.

Primers sequences are listed in Table 1.

Table 1 List of oligonucleotides used in this study
Full size table

The PCR mixture was carried out in a final volume of 50 µl comprising 5 µl of DNA template (5–20 ng/µl), 25 µl of PCR master mix, 2.5 µl of forward primer (0.1–0.5 µM), 2.5 ml of reverse primer (0.1–0.5 µM), and 15 µl nuclease-free water. The thermal cycler (MultiGene OptiMax ThermoCycler, Labnet) was programmed with the following conditions:-

Conventional PCR

initial denaturation at 95 ºC for 5 min, followed by 35 cycles of denaturation at 94 ºC for 30 s, annealing at 56 ºC, for blaOXA−48 and blaNDM−1, and 52 ºC, for blaGIM−1 and blaVIM−2, for 40 s, extension at 72 ºC for 30 s, and final cycle of amplification at 72 ºC for 10 min [37].

Gradient PCR

was programmed for blaIMP−1, blaSIM−1 and blaSPM−1 starting from 52 ºC reaching 58 ºC in an attempt to reach the optimum annealing temperature for blaIMP−1, blaSIM−1 and blaSPM−1 genes using the touch up technique mentioned elsewhere [38]. Briefly, initial denaturation at 95 ºC for 5 min, followed by 35 cycles of denaturation at 94 ºC for 30 s, annealing starting at 52º C till reach 58 ºC, increasing by 0.5 ºC each cycle, extension at 72º C for 30 s, and final cycle of amplification at 72 ºC for 10 min.

Touchdown PCR

was programmed for the genes which are not detected by gradient PCR; in order to increase sensitivity and specificity in amplification. The annealing temperature was designed starting from 60 ºC till 53 ºC. OligoCalc, an online tool for melting temperature (Tm) calculation and oligonucleotide properties, was employed where it recommends basic, salt-adjusted and nearest-neighbor Tm estimations.

http://www.basic.northwestern.edu/biotools/oligocalc.html.

Lab positive and negative controls for each PCR were included. After agarose gel electrophoresis with EtBr, the PCR products were visualized under UV light.

Results

Identification of clinical isolates and antimicrobial susceptibility testing

A total of 151 GNIs, were identified by Gram staining and culturing methods. Additional confirmatory biochemical tests were carried to further identify the isolates. The susceptibility pattern of all collected isolates to tested antibiotics is shown below in Table 2.

Table 2 Antibiotic susceptibility pattern of the tested clinical isolates
Full size table

Heteroresistant isolates and stability detection

Heteroresistant subpopulations were detected by the growth of colonies in the inhibition zone of each antibiotic disc [23]. Table 3 shows the susceptibility pattern of tested microorganisms against the used antibiotics, the outline of SHIs of total detected HR cases against all used antibiotics and the prevalence of HR in different microorganisms and its stability.

Table 3 Antibiotic susceptibility patterns of the clinical isolates
Full size table

Repetitive susceptibility testing over 50 generations verified HR. Out of the 51 heteroresistant isolates that were found, only 16 isolates (or 31%) never reverted to susceptibility. Eleven out-patient isolates and five in-patient isolates made up the SHIs.

Phenotypic characterization of efflux pumps activity, slime formation and carbapenemase genes production reflects the resistant nature of the subpopulations

Out of 16 SHIs, five isolates (31.25%) revealed efflux pump activity upon detection by EtBr-agar cartwheel method (Fig. 1).

Fig. 1
figure 1

Efflux pumps activity detection in resistant subpopulations. a: for isolates; 119IPM, 15DOR, 15MRP, 141FOX, 141MEM, 9ETP, 24AMC and 131SXT. b: for isolates; 104CN, 104CIP, 142CIP, 9MEM, 119CIP, 3CIP, 128CN and 119FOX. Five isolates: 141FOX, 119CIP, 3CIP, 104CN and 104CIP reveal efflux pumps activity detected by absence of fluorescence upon examination by UV transilluminator (p-value > 0.05)

Full size image

The fluorescent light of 15DOR and 15MRP even in 0 mg/L EtBr is due to pigments (pyoveridin and pyocyanin) producing fluorescence under UV light. It is considered as an obstacle to detect efflux pumps activity in P. aeruginosa using this method.

Testing biofilm formation in SHIs and their corresponding main populations revealed that none of the main populations were biofilm producers. Just four isolates (25%) of SHIs exhibited biofilm formation, as illustrated in Fig. 2.

Fig. 2
figure 2

Biofilm formation detection in resistant subpopulations. Isolates, 104CIP, 104CN, 128CN and 24AMC exhibited biofilm formation (p-value > 0.05)

Full size image

Interestingly, all the tested carbapenems-SHIs (6 isolates) were found to be positive for carbapenemase production. This was confirmed by genotypic analysis which, revealed that all tested isolates produced at least one carbapenemase as illustrated in Table 4.

Table 4 Distribution of carbapenemase genes in stable carbapenems heteroresistant isolates
Full size table

Genes of blaSPM−1, blaSIM−1 and blaIMP−1 were not detected in any of the tested 6 SHIs. On the other hand and in contrast to their sensitive main population, blaNDM−1, blaOXA−48 like, blaGIM−1 and blaVIM−2 were detected in 5, 2, 2 and 3 out of 6 SHIs, respectively.

In (Fig. 3, A-D), sensitive main populations and the associated resistant subpopulations are compared.

Fig. 3
figure 3

Carbapenemase genes amplification in resistant subpopulations and their corresponding sensitive main populations. a: Ethidium Bromide-stained gel shows PCR products of blaNDM−1 with size of 621 bp; lane 1, negative control; lane 2, positive control; M, 100 bp marker (ladder). (p-value > 0.05). b: Ethidium bromide-stained gel shows PCR products of blaOXA−48 like with size of 438 bp; lane 1, negative control; lane 2, positive control; M, 100 bp marker (ladder). (p-value > 0.05). c: Ethidium bromide-stained gel shows PCR products of blaGIM−1 with size of 477 bp; lane 1, positive control; lane 2, negative control; M, 100 bp marker (ladder). (p- value < 0.05*). d: Ethidium bromide-stained gel shows PCR products of blaVIM−2 with size of 390 bp; lane 1, positive control; lane 2, negative control; M, 100 bp marker (ladder).(p-value > 0.05)

Full size image

Carbapenem resistance genes were identified across various infection types. The blaVIM-2 gene was detected in two samples obtained from wounds and in a third sample from urine. Conversely, all instances of blaGIM-1 were associated with wound infections. The blaOXA-48 like gene was detected in only two samples: one from a urinary tract infection and another from wound pus. The blaNDM-1 gene was identified in samples from wounds, urine, and pus, as well as in two isolates obtained from blood cultures.

Just as an observation, the closest colony to the antibiotic disc exhibits a narrower zone of inhibition compared to the one nearest to the inhibition zone edge of the same antibiotic for the same isolate. This observation was detected in isolate no.15 and its subpopulations; 15MRP and 15DOR (Fig. 4), in an attempt to clarify HR mechanism.

Fig. 4
figure 4

Resistance levels differ according to the Colonies’ position away from the disc center. a: a colony appeared around meropenem disc away from the disc centre by 12 mm. b: a colony appeared around doripenem disc away from the disc centre by 10 mm

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(Fig. 3A, C and D) indicates that 15DOR were triple positive for blaNDM−1, blaGIM−1 and blaVIM−2. On the other hand, blaNDM−1 couldn’t be detected in 15MRP, while blaGIM−1 and blaVIM−2 were detected. However, a closer examination of the gene expression levels using the Q-PCR technique is required to provide a more thorough explanation for this observation.

Table 5 presents an overview of the genotypic and phenotypic traits of SHIs in our investigation.

Table 5 Phenotypic and genotypic characteristics of stable heteroresistant subpopulations
Full size table

Discussion

Although the term HR was initially used in the 1940s, some studies have looked at its genetic roots or how it may contribute to treatment failure [5]. The ongoing growth of HR and its complex regulations make its emergence deeply alarming [1]. This study comprised 151 distinct GNIs acquired from several different sources, comprising Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli, Acinetobacter baumannii, and Proteus mirabilis. Out of 51 detected heteroresistant isolates (18% of 282 susceptible bacteria-antibiotic combinations), 31% of SHIs could be identified applying the disc-diffusion approach. Using PCR for genotypic analysis and the EtBr-agar cartwheel method for efflux activity assessment, significant differences were identified between heteroresistant isolates and their related main populations.

HR has been detected in different sample types against different antibiotics. Carbapenems are examples against which microorganisms exhibit heterogeneous response with different prevalence percentages in different studies ranging from 0% of different gram-negative clinical isolates in Sweden [9] to 100% in carbapenemases-producing K. pneumoniae in Greece [39]. Several studies revealed that HR occurs relatively often in K. pneumoniae clinical isolates [40]. In this study, K. pneumoniae was more prevalent (43.8%) among the 16 detected HR isolates followed by E. coli (31.3%). Additionally, unstable HR was widespread and detected in 69% of HR cases, yielding an overall estimated frequency of unstable HR of 12.48% (35 out of 282 bacteria–antibiotic combinations). Interestingly, for drugs where frequent mutations can cause resistance or where resistance genes can be amplified, the probability of observing HR might increase, such as in meropenem and ciprofloxacin drugs where HR has been detected in 27.5% and 30.4% of sensitive clinical isolates, respectively.

Several studies proved that HR is an unstable phenomenon where 100% [40], 88% [9] and 84.6% [41] of detected heteroresistant isolates were fully or partially reverted back to the level of susceptibility of the main population. In the current study, 51 heteroresistant subpopulations have been detected within 282 susceptible (out of 1234) bacteria–antibiotic combinations. Within this context, 35 isolates (68.63%) were shown to be unstable (Table 3).

Mechanisms responsible for the surfacing of heteroresistant K. pneumoniae subpopulations have been previously identified as antibiotic-resistant factors in Klebsiella and other Enterobacterials. These mutations have often resulted in unstable HR including lipid-A modifications, over-expression of pump systems, or resistance genes amplification. In this study, different carbapenemases genes, namely, blaNDM−1, blaVIM−2, blaGIM−1, blaSIM−1, blaSPM−1, blaIMP−1 and blaOXA−48 like were amplified. As mentioned earlier, blaSPM−1, blaSIM−1 and blaIMP−1 have not been detected in any of the six stable carbapenems-heteroresistant isolates. But the remaining genes were detected in carbapenems-resistant subpopulations by different ratios while nearly all these genes were absent in the corresponding main populations as shown in Table 4. It is assumed that these mutants survived the antibiotics effect and became superbugs by the activity of resistance genes.

Other HR mechanisms are down-regulation of porins and/or over-expression and activity of efflux pumps [42, 43]. These two mechanisms contributed to carbapenems-HR in P. aeruginosa [43, 44]. In this investigation, 31.25% of the SHIs were at least partially mediated by efflux pumps; this is in contrast to the corresponding main populations that did not exhibit any efflux pump activity. Those five isolates consist of three samples (119CIP, 104CIP and 104CN) obtained from urinary tract infections, from urine samples, another (141FOX) from a purulent sample (pus), and the fifth isolate (3CIP), from a respiratory tract infection obtained via sputum sample.

With regard to bacterial biofilm, little is known about its effect on HR, despite its heterogeneous response to antibiotics. Only one example described the presence of colistin-heteroresistant subpopulations in K. pneumoniae [45, 46]. In contrast to the aforementioned studies, it was demonstrated that biofilm formation in K. pneumoniae does not link with amikacin-HR [41]. Among a variety of phenotypic methods, the Congo Red Agar (CRA) method is a simple, cost-effective, sensitive, and specific method that can be used by clinical microbiology laboratories for screening of slime or slime-like substances [29].

Some studies reported that none of the P. aeruginosa strains tested showed positivity by CRA method suggesting that the CRA test may not be useful for identifying the exopolysaccharide layer-producing non-fermenting GNIs, especially Pseudomonas species [29].

In the existing study, slime production detection using CRA method discloses a biofilm formation nature in 4/16 (25%) SHIs, three of which (24AMC, 104CIP and 104CN) were obtained from urine samples and the forth one (128CN) accounts for a blood sample, (Fig. 2) while 12 SHIs (75%) exhibiting no biofilm production.

Preliminary data in which SHIs have been screened for susceptibility to β-lactam\β-lactamase inhibitor combinations (piperacillin\tazobactam and cefoperazone\sulbactam) as treatment alternatives resulting in major foremost resistance to the used combinations (data are not shown).

It is important to underline that the frequency of detected HR will depend on the detection method (for example, PAP test, E-tests, disk diffusion or broth microdilution) and the HR definition chosen (for example, the cut-off resistance level chosen to identify a resistant subpopulation) in addition to the selected clinical strains and the antibiotics tested [8]. For example, in our study we might have missed true HR cases if HR was not assumed following the first disc diffusion test. This makes comparisons of studies difficult and emphasizes the importance of approving a standard method and definition to identify HR in clinical isolates.

Moreover, two issues may compromise the rigorous procedure and the reproducibility of this research as well as data generalization. First, the small sample size may not be representative of the population, resulting in imprecise results and questioning the validity of the study and thereby can lead to fallacious conclusions and hence underpowered studies. Second, further molecular techniques such as sequencing analysis should have been employed to confirm PCR data. Nonetheless, the findings demonstrate that resistance genes amplification could contribute to HR incidence and should be taken into account when choosing an antibiotic. Improving detection techniques to find resistant cell subpopulations is a major clinical issue, so this is not trivial issue.

To conclude, heteroresistance (HR) poses significant challenges for microbiologists, healthcare providers, and patients. Diagnosis using established methods is often inaccurate, leading to treatment failures and potential development of drug-resistant bacteria. Improved techniques are urgently needed to detect HR accurately in pathogens. Studies so far, mainly in animal models or in-vitro, may not fully reflect host environments. Factors such as pathogen-host interactions and diverse subpopulations must be further explored through additional in-vivo studies. Whole genome sequencing holds promise for distinguishing SHIs from susceptible populations in future research.

Data availability

No datasets were generated or analysed during the current study.

References

  1. Andersson DI, Nicoloff H, Hjort K. Mechanisms and clinical relevance of bacterial heteroresistance. Nat Rev Microbiol. 2019;17(8):479–96.

    Article  CAS  PubMed  Google Scholar 

  2. Band VI, Weiss DS. Heteroresistance: a cause of unexplained antibiotic treatment failure? PLoS Pathog 2019, 15(6):e1007726.

  3. Park KH, Kim ES, Kim HS, Park SJ, Bang KM, Park HJ, Park SY, Moon SM, Chong YP, Kim SH, et al. Comparison of the clinical features, bacterial genotypes and outcomes of patients with bacteraemia due to Heteroresistant Vancomycin-intermediate Staphylococcus aureus and Vancomycin-susceptible S. Aureus. J Antimicrob Chemother. 2012;67(8):1843–9.

    Article  CAS  PubMed  Google Scholar 

  4. Al-Shebiny AG, Shawky R, Emara M. Heteroresistance: a gray side of antimicrobial susceptibility testing. J Adv Pharm Res 2023, 7(2).

  5. Devi Y, Punithavathy PM, Thomas S, Veeraraghavan B. Challenges in the laboratory diagnosis and clinical management of heteroresistant Vancomycin Staphylococcus aureus (hVISA). Clin Microbiol. 2015;4(214):2.

    Google Scholar 

  6. Canetti G, Rist N, Grosset J. Measurement of sensitivity of the tuberculous bacillus to antibacillary drugs by the method of proportions. Methodology, resistance criteria, results and interpretation. Rev Tuberc Pneumol (Paris). 1963;27:217–72.

    CAS  PubMed  Google Scholar 

  7. Zheng C, Li S, Luo Z, Pi R, Sun H, He Q, Tang K, Luo M, Li Y, Couvin D, et al. Mixed infections and Rifampin Heteroresistance among Mycobacterium tuberculosis Clinical isolates. J Clin Microbiol. 2015;53(7):2138–47.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Sandegren L, Andersson DI. Bacterial gene amplification: implications for the evolution of antibiotic resistance. Nat Rev Microbiol. 2009;7(8):578–88.

    Article  CAS  PubMed  Google Scholar 

  9. Nicoloff H, Hjort K, Levin BR, Andersson DI. The high prevalence of antibiotic heteroresistance in pathogenic bacteria is mainly caused by gene amplification. Nat Microbiol. 2019;4(3):504–14.

    Article  CAS  PubMed  Google Scholar 

  10. Hofmann-Thiel S, van Ingen J, Feldmann K, Turaev L, Uzakova GT, Murmusaeva G, van Soolingen D, Hoffmann H. Mechanisms of heteroresistance to isoniazid and rifampin of Mycobacterium tuberculosis in Tashkent, Uzbekistan. Eur Respir J. 2009;33(2):368–74.

    Article  CAS  PubMed  Google Scholar 

  11. Maor Y, Hagin M, Belausov N, Keller N, Ben-David D, Rahav G. Clinical features of heteroresistant Vancomycin-intermediate Staphylococcus aureus bacteremia versus those of methicillin-resistant S. aureus bacteremia. J Infect Dis. 2009;199(5):619–24.

    Article  PubMed  Google Scholar 

  12. Brauner A, Fridman O, Gefen O, Balaban NQ. Distinguishing between resistance, tolerance and persistence to antibiotic treatment. Nat Rev Microbiol. 2016;14(5):320–30.

    Article  CAS  PubMed  Google Scholar 

  13. Kuper KM, Boles DM, Mohr JF, Wanger A. Antimicrobial susceptibility testing: a primer for clinicians. Pharmacotherapy. 2009;29(11):1326–43.

    Article  PubMed  Google Scholar 

  14. Srinivas P, Hunt LN, Pouch SM, Thomas K, Goff DA, Pancholi P, Balada-Llasat JM, Bauer KA. Detection of colistin heteroresistance in Acinetobacter baumannii from blood and respiratory isolates. Diagn Microbiol Infect Dis. 2008;91(2):194–8.

    Article  Google Scholar 

  15. Gazel D, Erinmez M, Büyüktaş Manay A, Zer Y. Investigation of heteroresistant vancomycin intermediate Staphylococcus aureus among MRSA isolates. J Infect Dev Ctries 2021;15(1):89–94 doi: 103855/jidc12799

  16. van Hal SJ, Jones M, Gosbell IB, Paterson DL. Vancomycin heteroresistance is associated with reduced mortality in ST239 methicillin-resistant Staphylococcus aureus blood stream infections. PLoS ONE. 2011;6(6):e21217.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Brown VI, Lowbury EJ. Use of an improved cetrimide agar medium and other culture methods for Pseudomonas aeruginosa. J Clin Pathol. 1965;18(6):752–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Leininger DJ, Roberson JR, Elvinger F. Use of eosin methylene blue agar to differentiate Escherichia coli from other gram-negative mastitis pathogens. J Vet Diagn Investig. 2001;13(3):273–5.

    Article  CAS  Google Scholar 

  19. Moyes RB, Jackie R, Donald PB. Differential staining of bacteria: Gram stain. In: Current Protocols in Microbiology 2009.

  20. Stager CE, Erikson E, Davis JR. Rapid method for detection, identification, and susceptibility testing of enteric pathogens. J Clin Microbiol. 1983;17(1):79–84.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Bauer A, Kirby MM, Sherris JC, Turck M. Antibiotic susceptibility testing by a standardized single disc method. Am J Clin Pathol. 1966;45:149–58.

    Article  Google Scholar 

  22. Korgenski EK, Daly JA. Evaluation of the BIOMIC video reader system for determining interpretive categories of isolates on the basis of disk diffusion susceptibility results. J Clin Microbiol. 1998;36(1):302–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Sun JD, Huang SF, Yang SS, Pu SL, Zhang CM, Zhang LP. Impact of carbapenem heteroresistance among clinical isolates of invasive Escherichia coli in Chongqing, southwestern China. Clin Microbiol Infect. 2015;21(5):e469461–410.

    Article  Google Scholar 

  24. Van Soestbergen AA, Lee CH. Pour plates or streak plates? Appl Microbiol 1969, 18(6):1092–3.

  25. Anderson SE, Sherman EX, Weiss DS, Rather PN. Aminoglycoside Heteroresistance in Acinetobacter baumannii AB5075. mSphere 2018, 3(4).

  26. Plipat N, Livni G, Bertram H, Thomson RB Jr. Unstable Vancomycin heteroresistance is common among clinical isolates of methiciliin-resistant Staphylococcus aureus. J Clin Microbiol. 2005;43(5):2494–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Lucas AE, Ito R, Mustapha MM, McElheny CL, Mettus RT, Bowler SL, Kantz SF, Pacey MP, Pasculle AW, Cooper VS et al. Frequency and mechanisms of spontaneous Fosfomycin Nonsusceptibility observed upon Disk Diffusion Testing of Escherichia coli.J Clin Microbiol 2018, 56(1).

  28. Ghandour AM, Mohamad WA, Bakry RM, Ahmed AO, Elsherbiny NM. Performance of chromID® CARBA-SMART medium and carbapenemase inhibition method for the detection of carbapenemases among Gram negative bacilli. Microbes Infect Dis. 2022;3(2):366–77.

    CAS  Google Scholar 

  29. Patil R, Rangappa KG, Rangaiah A, Shankar SM. Ethidium bromide-agar cartwheel method in the detection of efflux pump mediated multi-drug resistance in Enterobacteriaceae. Inter J Cur Res Rev 2021, 13(17).

  30. Hrv R, Devaki R, Kandi V. Evaluation of different phenotypic techniques for the detection of Slime produced by Bacteria isolated from clinical specimens. Cureus. 2016;8(2):e505.

    PubMed  PubMed Central  Google Scholar 

  31. Sukumaran S. Concentration determination of nucleic acids and proteins using the micro-volume BioSpec-nano-spectrophotometer. J Vis Exp 2011(48).

  32. Abdeltwab NM, Emara M, El-Mahdy TS, El-Magd MA, Moustafa WH, El-domany RA. First report of imipenem-resistant Pseudomonas aeruginosa clinical isolates harboring blaGIM–1 gene in the Middle East Region. N Egypt J Microbiol 2019, 52.

  33. Elsheshtawy N. Prevalence of New Delhi Metallo-Beta lactamase gene among Klebsiella species isolates: an Egyptian study. Microbes Infect Dis. 2021;2(3):508–15.

    Google Scholar 

  34. Emara M, El-Domany RA, El-Magd MA, Moustafa WH, Abdeltwab NM. Detection of blaSPM–1 and blaSIM–2 metallo-β-lactamases genes in imipenem-resistant pseudomonas aeruginosa clinical isolates recovered from two University hospitals in Egypt. J Adv Pharm Res. 2020;4(3):111–8.

    Google Scholar 

  35. Raheel A, Azab H, Hessam W, Abbadi S, Ezzat A. Detection of carbapenemase enzymes and genes among carbapenem-resistant Enterobacteriaceae isolates in Suez Canal University Hospitals in Ismailia, Egypt. Microbes Infect Dis. 2020;1(1):24–33.

    CAS  Google Scholar 

  36. Poirel L, Walsh TR, Cuvillier V, Nordmann P. Multiplex PCR for detection of acquired carbapenemase genes. Diagn Microbiol Infect Dis. 2011;70(1):119–23.

    Article  CAS  PubMed  Google Scholar 

  37. El-Domany RA, Emara M, El-Magd MA, Moustafa WH, Abdeltwab NM. Emergence of Imipenem-Resistant Pseudomonas aeruginosa Clinical isolates from Egypt Coharboring VIM and IMP carbapenemases. Microb Drug Resist. 2017;23(6):682–6.

    Article  CAS  PubMed  Google Scholar 

  38. Rowther FB, Kardooni H, Warr T. TOUCH-UP gradient amplification method. J Biomol Tech. 2012;23(1):1–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Pournaras S, Kristo I, Vrioni G, Ikonomidis A, Poulou A, Petropoulou D, Tsakris A. Characteristics of meropenem heteroresistance in Klebsiella pneumoniae carbapenemase (KPC)-producing clinical isolates of K. pneumoniae. J Clin Microbiol. 2010;48(7):2601–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Stojowska-Swedrzynska K, Lupkowska A, Kuczynska-Wisnik D, Laskowska E. Antibiotic Heteroresistance in Klebsiella pneumoniae. Int J Mol Sci 2022, 23(1).

  41. Zhang F, Li Q, Bai J, Ding M, Yan X, Wang G, Zhu B, Zhou Y. Heteroresistance to Amikacin in Carbapenem-resistant Klebsiella pneumoniae strains. Front Microbiol. 2021;12:682239.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Chen Y, Hu D, Zhang Q, Liao XP, Liu YH, Sun J. Efflux Pump Overexpression Contributes to Tigecycline Heteroresistance in Salmonella enterica Serovar Typhimurium. Front Cell Infect Microbiol. 2017;7:37.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Mmatli M, Mbelle NM, Maningi NE, Osei Sekyere J. Emerging Transcriptional and Genomic Mechanisms Mediating Carbapenem and Polymyxin Resistance in Enterobacteriaceae: a Systematic Review of Current Reports. mSystems 2020, 5(6).

  44. Ikonomidis A, Tsakris A, Kantzanou M, Spanakis N, Maniatis AN, Pournaras S. Efflux system overexpression and decreased OprD contribute to the carbapenem heterogeneity in Pseudomonas aeruginosa. FEMS Microbiol Lett. 2008;279(1):36–9.

    Article  CAS  PubMed  Google Scholar 

  45. Lopes SP, Jorge P, Sousa AM, Pereira MO. Discerning the role of polymicrobial biofilms in the ascent, prevalence, and extent of heteroresistance in clinical practice. Crit Rev Microbiol. 2021;47(2):162–91.

    Article  CAS  PubMed  Google Scholar 

  46. Silva A, Sousa AM, Alves D, Lourenco A, Pereira MO. Heteroresistance to colistin in Klebsiella pneumoniae is triggered by small colony variants sub-populations within biofilms. Pathog Dis 2016, 74(5).

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  1. Faculty of Pharmacy, Department of Microbiology and Immunology, Helwan University, P. O. Box: 11795, Ain-Helwan, Cairo, 01060564729, Egypt

    Alaa G. Al-Shebiny, Riham M. Shawky & Mohamed Emara

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  1. Alaa G. Al-Shebiny
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ME conceived of the presented idea, ME and AA planned the experimental work, AA carried out the experimental work. AA and ME wrote and designed the original paper, All authors have analyzed the data, read and approved the final version of the manuscript.

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Correspondence to Mohamed Emara.

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Not applicable because all clinical isolates were obtained through hospital-mediated means and without direct patient contact.

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Al-Shebiny, A.G., Shawky, R.M. & Emara, M. Emergence of heteroresistance to carbapenems in Gram-negative clinical isolates from two Egyptian hospitals. BMC Microbiol 24, 278 (2024). https://doi.org/10.1186/s12866-024-03417-y

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BMC Microbiology

ISSN: 1471-2180

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