Integrated Analysis of Global Regulators and Efflux Genes in MDR Klebsiella pneumoniae:Unlocking Targets for Antimicrobial Reversal

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Naser, Ali J. Alkawaz, Ali J. Obaid This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7168743/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Multidrug-resistant Klebsiella pneumoniae poses a growing clinical challenge due to its ability to evade antibiotic treatment, particularly through the overexpression of efflux systems. Among these, the AcrAB-TolC pump is central to resistance against fluoroquinolones. While the global regulator's MarA, SoxS, and Rob are known modulators of efflux in Enterobacteriaceae, their functional relevance in clinical K. pneumoniae remains insufficiently defined. Objective: This study aimed to elucidate the transcriptional dynamics between global regulators (marA, soxS, rob) and efflux pump components (acrA, acrB, tolC) in multidrug-resistant K. pneumoniae and to validate the functional role of efflux in fluoroquinolone resistance. Methods: Thirty clinical MDR isolates and ten susceptible controls were characterized via antibiotic susceptibility testing. Gene expression was quantified using qRT-PCR, normalized to 16S rRNA, and analyzed by the 2^–ΔΔCt method. Pearson correlation assessed relationships between gene expression and resistance. Phenotypic validation of efflux activity was performed using PAβN, an AcrAB-TolC inhibitor. Results: MDR isolates exhibited significant overexpression of marA (5.0-fold), soxS (4.0-fold), acrB (7.9-fold), and other efflux components (p < 0.001). Strong positive correlations emerged between marA/soxS and acrB expression, implicating coordinated regulatory control. PAβN exposure reduced ciprofloxacin MICs by ≥ 4-fold in 80% of high-acrB isolates, confirming active efflux involvement. Conclusion: The data establish MarA and SoxS as principal activators of the AcrAB-TolC efflux system in clinical MDR K. pneumonia , driving fluoroquinolone resistance. Rob showed minimal impact. Functional inhibition of efflux restored anti-biotic susceptibility in most isolates, highlighting global regulators and efflux pumps as promising targets for adjunctive therapy to combat resistance. General Microbiology Efflux resistance Fluoroquinolones Gene regulation RND transporters Pump inhibitors MDR bacteria Figures Figure 1 Figure 2 1. Introduction Resistant Klebsiella pneumoniae, which is a multidrug (multi-drug-resistant), has become an increasing problem worldwide with hospital-acquired Infection, with many strains being resistant to almost all therapeutic agents Currently used. [ 1 , 2 ] Because of mechanisms including but not limited to β-Lactamase production (such as KPC), changes in drug target sites, and low levels of intracellular antibiotic accumulation, it has evolved this multidrug resistance (MDR) [ 3 , 4 ]. One critical factor in lower accumulation is the activity of multidrug efflux pumps [ 5 ]. AcrAB-TolC, a member of the resistance nodulation cell division (RND) family, is one of the most studied efflux systems in enterobacteria [ 6 ]. It pumps a range of anti-biotics, including fluoroquinolones, chloramphenicol, tetracyclines, and β-lactams, thereby reducing intracellular drug concentrations and undermining treatment outcomes [ 7 ]. The mechanism of regulation for this system includes both local repressors and global transcriptional activators [ 8 ]. MarA, SoxS, and Rob -- three key global regulators have been shown to influence the Expression of efflux-related genes in Escherichia coli as well as other Gram-negative organisms [ 9 ]. These regulators activate overlapping sets of genes, including the marRAB operon, which affects AcrAB-TolC expression and the multidrug resistance (MDR) phenotype [ 10 ]. Nonetheless, their role in drug resistance in clinical K. pneumoniae isolates re-mains unclear. With the increasing threat of MDR K. pneumoniae, it is vital to understand what triggers drug efflux pump activation. This work has been designed to examine the transcription of marA, soxS, and rob in relation to acrA, acrB, and tolC in clinical MDR K. pneumoniae isolates using qRT-PCR analysis techniques, which can help identify potential pathways for regulating resistance through efflux mechanisms. As Klebsiella pneumoniae and other Gram-negative bacteria have evolved efflux mechanisms for antibiotics, the changing antibacterial environment has led to the development of new survival strategies, including altering the concentrations of fluoroquinolones within their cells. Despite providing valuable molecular insights from RNA deep sequencing, it cannot be confirmed that the activity of efflux pumps is related to the uptake of genes or their role in leading to resistance. To circumvent this restriction, phenotypic validation employing efflux pump inhibitors has become increasingly important. Among these, phenyl-arginine β-naphthylamide 4 (PAβN) is an established inhibitor of AcrAB-TolC family transporters, which are resistance-nodulation-division (RND) pumps. By blocking efflux, PAβN increases intracellular drug levels and restores susceptibility in strains resistant to efflux. PAβN is an experimental inhibitor of the AcrAB-TolC system, not approved for clinical use due to toxicity, but valuable for mechanistic studies of efflux inhibition. These inhibitors can be integrated into experimental workflows as confirmatory tools to support transcriptional data with functional evidence. In this light, the present study was also extended to encompass a phenotypic efflux assay, in which the action of PAβN on ciprofloxacin susceptibility in several clusters of multidrug-resistant K. pneumoniae, all of which had high acrB Expression, was assessed. This addition aimed to supply supporting evidence for transcript-based Analysis and add clarity to the role played by active efflux in antibiotic resistance. 2. Materials and Methods 2.1. Isolation and Characterization of Bacterial Strains Thirty MDR Klebsiella pneumoniae isolates were collected from patients at Imam Al-Sadiq Hospital, Babylon-Hillah. MDR was defined as resistance to at least one agent in three or more antibiotic classes, including β-lactams, fluoroquinolones, and aminoglycosides. Clinical sources included blood, sputum, urine, and wound swabs. Isolates were identified using standard biochemical reactions and the Vitek 2 system. Ten susceptible K. pneumoniae isolates and the reference strain K. pneumoniae ATCC 13883 were used as controls. All isolates were preserved at − 80°C in glycerol stocks and revived on Mueller-Hinton agar prior to testing [ 11 ]. 2.2. Determination of Antibiotic Resistance Profiles Susceptibility was evaluated using disk diffusion and broth microdilution MIC testing, as per CLSI guidelines (2025). For disk diffusion, bacterial suspensions (0.5 McFarland) were spread on Mueller-Hinton agar, and BD BBL™ antibiotic disks were applied. After 16–18 hours of incubation at 35°C, inhibition zones were measured. Tested antibiotics included ciprofloxacin (5 µg), gentamicin (10 µg), piperacillin-tazobactam, ceftriaxone, meropenem, and trimethoprim-sulfamethoxazole. MICs for ciprofloxacin and gentamicin were assessed using cation-adjusted Mueller-Hinton broth with two-fold serial dilutions from 0.06 to 64 µg/mL. CLSI breakpoints were used for interpretation [ 12 , 13 ]. 2.3. RNA Extraction and cDNA Synthesis for Gene Expression Analysis Total RNA was extracted from mid-log phase cultures using the GeneJET RNA Purification Kit (Thermo Scientific), quantified using a NanoDrop, and evaluated on an agarose gel. Genomic DNA was removed using DNase I. First-strand cDNA synthesis was performed using the Revert Aid First Strand cDNA Synthesis Kit (Thermo Scientific) [ 14 , 15 ]. 2.4. Quantitative Real-Time PCR (qRT-PCR) The expression levels of regulatory genes (marA, soxS, rob) and efflux pump components (acrA, acrB, tolC) were quantified using quantitative reverse transcription PCR (qRT-PCR). Gene-specific primers were designed via Primer3 software to produce amplicons of approximately 100 base pairs. Primer validation confirmed specificity and efficiency (95–100%), as shown by single-peak melt curve profiles [ 16 , 17 ]. Reactions were performed in 96-well plates on the Quant Studio 5 Real-Time PCR System using SYBR Green chemistry. Each 20 µL reaction included 2 µL of cDNA, 0.5 µM of forward and reverse primers, and 10 µL of PowerUp SYBR Green Master Mix (Thermo Scientific). The thermal protocol consisted of an initial activation step at 95°C for 2 minutes, followed by 40 cycles of denaturation at 95°C for 15 seconds and annealing and extension at 60°C for 30 seconds. All samples were analyzed in triplicate. No-template controls were included for each primer pair to monitor for nonspecific amplification [ 17 , 18 ]. The 16S rRNA-encoding rrs gene was used as the endogenous reference for normalization due to its stable Expression under experimental conditions. Although some studies recommend the use of multiple housekeeping genes to ensure normalization robustness, the 16S rRNA gene remains one of the most validated and commonly used internal controls in bacterial expression studies. Its consistent expression across diverse Klebsiella pneumoniae strains and experimental conditions justifies its use as a sole reference gene in this study, particularly given the absence of stressors known to affect ribosomal RNA stability. Threshold cycle (Ct) values were recorded for both target genes and the reference gene. The ΔCt was calculated as CT target – Ct_16S to correct for differences in RNA input. The ΔΔCt was obtained by comparing each clinical isolate's ΔCt to that of the pan-susceptible calibrator strain ( K. pneumoniae ATCC 13883). Relative gene expression was calculated using the 2^-ΔΔCt method. Fold change values greater than one were interpreted as gene overexpression, while values below one indicated downregulation compared to the reference strain [ 19 , 20 ]. 2.5. Statistical Tools and Data Interpretation Data analysis was performed using GraphPad Prism 9.0 and SPSS version 25 (IBM Corp). Gene expression and MIC values were expressed as mean ± standard deviation (SD). Two-sample t-tests were applied to compare gene expression between MDR and susceptible groups after confirming the normal distribution of ΔCt values. A p-value < 0.05 was considered statistically significant [ 21 ]. To correct for multiple comparisons across six target genes, Bonferroni adjustment was applied, setting the significance threshold at α = 0.0083 to reduce Type I error risk. Pearson’s correlation analysis was used to evaluate linear relationships between expression levels of global regulators (marA, soxS, rob) and efflux pump genes (acrA, acrB, tolC) in 30 MDR isolates. This method also assessed associations between gene expression and antibiotic minimum inhibitory concentration (MIC) values, including those for ciprofloxacin [ 22 , 23 ]. Correlation strength was interpreted as follows: r > 0.7 indicated a strong correlation, 0.4–0.7 a moderate correlation, and 0.2–0.4 a weak correlation. Statistical significance for correlations was defined as p < 0.05, with all tests being two-tailed. Reported p-values were compared against the Bonferroni-adjusted threshold, and only those < 0.0083 were considered significant. 2.6. Efflux Pump Inhibition Assay Using PaβN Phenyl-arginine-β -naphthylamide (PAβN), a pump inhibitor of efflux, was used to evaluate the functional role of active efflux in ciprofloxacin resistance. (Sigma-Aldrich, USA). Ten multidrug-resistant Klebsiella pneumoniae isolates were selected with high acrB expression levels(> 5-fold relative to a reference strain). Minimum inhibitory concentrations (MICs) of ciprofloxacin were determined by broth microdilution (CLSI, 2005) in the absence or presence of PAβN. Serial 2-fold dilutions of ciprofloxacin, ranging from 0.06 to 64 µg/mL, were prepared in 96-well microtiter plates containing Mueller-Hinton broth supplemented with cation-adjusted R2SOV broth medium. The bacterial suspension was adjusted to the 0.5 McFarland standard and incubated for 18 hours at 35°C. The MIC was visually read as the lowest concentration at which no visible growth could be observed. Each isolate was tested twice, with and without PAβN. Suppose the MIC with PAβN was ≥ 4-fold lower than that without it. The strain was then considered to possess significant efflux pump activity. Control wells without antibiotics and PAβN were used to check intrinsic growth. The assay provided actual confirmation of the involvement of the AcrAB-TolC system in ciprofloxacin resistance [ 5 ]. 3. Results 3.1. Antimicrobial Resistance Profiles of Clinical MDR Isolates A comparison of 30 clinical MDR K. pneumoniae isolates revealed high resistance to multiple antibiotics, including ciprofloxacin and gentamicin. All MDR isolates exhibited no or minimal inhibition zones (≤15 mm) to ciprofloxacin, with MICs ≥8 µg/mL, exceeding the CLSI resistance breakpoint. In contrast, susceptible isolates exhibited inhibition zones of≥30 mm and MICs of ≤0.5 µg/mL. Gentamicin resistance followed a similar pattern, with MDR isolates exhibiting MICs between 8 and 32 µg/mL, while susceptible isolates had MICs of ≤2 µg/mL. Additionally, MDR isolates exhibited co-resistance to several antibiotic classes: 90% were ESBL producers (resistant to third-generation cephalosporins with positive clavulanate synergy), 20% were carbapenem-resistant (imipenem/meropenem MICs ≥16 µg/mL), and all showed resistance to trimethoprim-sulfamethoxazole and Tetracycline. In contrast, the control isolates, including ATCC 13883, remained broadly susceptible to the antibiotics. These phenotypic resistance patterns support further investigation into corresponding gene expression profiles. Table.1 summarizes the antibiotic resistance profiles and MICs of MDR and control isolates. Table 1. Antibiotic Resistance Profiles of MDR K . pneumoniae Isolates (n = 30) Antibiotic Class Agent(s) Resistance in MDR Isolates MIC (MDR Isolates) MIC (Control Isolates) Notes Fluoroquinolones Ciprofloxacin 100% (30/30) 8 – >64 µg/mL ≤ 0.5 µg/mL No/≤15 mm zone in disk diffusion Aminoglycosides Gentamicin 100% (30/30) 8 – 32 µg/mL ≤ 2 µg/mL Markedly elevated MICs 3rd Gen Cephalosporins CTX / CAZ 90% (27/30) Resistant (not specified) ≤ 1 µg/mL Confirmed ESBL phenotype via synergy tests Carbapenems Imipenem / Meropenem 20% (6/30) ≥ 16 µg/mL ≤ 1 µg/mL Suggests the presence of carbapenemases Folate Inhibitors & Tetracyclines TMP-SMX 100% (30/30) Not specified ≤ 0.5 µg/mL Universally resistant Tetracycline 100% (30/30) Not specified ≤ 2 µg/mL Universally resistant Abbreviations: CTX: Cefotaxime, CAZ: Ceftazidime, IPM: Imipenem, MEM: Meropenem, TMP-SMX: Trimethoprim-Sulfamethoxazole, MIC: Minimum Inhibitory Concentration, MDR: Multidrug-resistant Note: "Not specified" indicates that MIC testing for these antibiotics was not performed. Statistical significance was defined using Bonferroni correction for six comparisons (α = 0.05/6 ≈ 0.0083). 3.2. Molecular Evidence of Efflux Pump and Global Regulator Overexpression in MDR Isolates Quantitative RT-PCR revealed significantly elevated Expression of marA and soxS in MDR K. pneumoniae isolates compared to susceptible controls. On average, marA was overexpressed 5.0 ± 2.1-fold and soxS 4.0 ± 1.8-fold in MDR strains (p < 0.001), while rob showed a modest increase of 1.9 ± 0.8-fold (p < 0.001). Among efflux genes, acrA, acrB, and tolC were upregulated by 5.8 ± 2.0, 7.9 ± 3.0, and 3.9 ± 1.5-fold, respectively (p < 0.001). In contrast, susceptible isolates and the reference strain ATCC 13883 exhibited a baseline expression level of approximately 1.0-fold higher than that of the susceptible isolates. Approximately 70% of MDR isolates exhibited>4-fold MarA expression, and 63% showed similarly elevated SoxS levels, suggesting that MarA/SoxS activation is a significant resistance mechanism. However, some isolates showed low Expression of these regulators, implying alternative resistance pathways. Rob expression remained consistently low across the collection, indicating a limited role in efflux regulation among MDR strains. Figure 1 illustrates the fold-change differences in gene expression between MDR and susceptible isolates for marA, soxS, rob, and acrAB-tolC genes. Further categorical Analysis (Table 3) confirmed that most MDR isolates had strong upregulation of marA and soxS, and correlation analysis showed a significant association between their expression levels (r = 0.50, p = 0.005), suggesting co-activation in specific strains. Both genes also correlated strongly with acrB expression (marA: r = 0.75, p < 0.001; soxS: r = 0.83, p < 0.001), suggesting a potential association with the upregulation of the AcrAB-TolC efflux pump, rather than direct regulatory activation. Rob expression showed no significant correlation with acrB (r = 0.07, p = 0.70), suggesting minimal regulatory impact AcrB Expression correlated moderately with ciprofloxacin MICs (r = 0.56, p = 0.001), linking efflux pump upregulation to fluoroquinolone resistance. Similar patterns were observed for norfloxacin and levofloxacin. No correlation was observed between marA or acrB and gentamicin MICs (p > 0.5), suggesting alternative resistance mechanisms such as aminoglycoside-modifying enzymes.Table.2 presents the Pearson correlation coefficients between key genes and resistance phenotypes.) Table 2. Pearson Correlation Between Gene Expression and Ciprofloxacin Resistance in MDR K. pneumoniae (n = 30) Comparison Pearson r p-value Significance marA expression vs. soxS expression 0.50 0.005 Significant (**) marA expression vs. acrB Expression 0.75 < 0.001 Highly Significant (**) soxS Expression vs. acrB Expression 0.83 < 0.001 Highly Significant (**) rob expression vs. acrB Expression 0.07 0.70 (ns) Not Significant acrB Expression vs. Ciprofloxacin MIC 0.56 0.001 Significant (**) marA expression vs. Gentamicin MIC 0.09 0.65 (ns) Not Significant Note: ** indicates statistically significant correlation at p < 0.0083 (Bonferroni-corrected).ns indicate non-significant correlation (p ≥ 0.0083). Table 3. Distribution of marA and soxS Expression Fold Change in MDR Isolates (n = 30) Fold Change Range No. of Isolates (marA) % (marA) No. of Isolates (soxS) % (soxS) > 4× 21 70% 19 63% 2× – 4× 6 20% 8 27% < 2× 3 10% 3 10% Note: X-fold change calculated by a 2^-ΔΔCt relative to the susceptible strain Figure 2 illustrates a positive linear correlation between MarA and acrB expression levels (r = 0.75, p < 0.001), which further supports a strong association between MarA expression and increased acrB levels, indicating a possible regulatory link. While most isolates followed this trend, some with intermediate acrB Expression may involve alternative regulators such as SoxS or RamA. 3.3. Phenotypic Reversal of Ciprofloxacin Resistance by PAβN Confirms Active Efflux To functionally validate the role of active efflux in ciprofloxacin resistance, ten multidrug-resistant Klebsiella pneumoniae isolates with elevated acrB Expression were tested for susceptibility to ciprofloxacin in the presence and absence of the efflux pump inhibitor phenyl-arginine β-naphthylamide (PAβN). The addition of PAβN at 25 µg/mL resulted in a marked reduction in MIC values in most tested isolates. Specifically, 8 out of 10 isolates (80%) demonstrated a ≥4-fold reduction in ciprofloxacin MICs, indicating substantial involvement of the efflux pump. For instance, isolate KPN-12 exhibited a MIC of 32 µg/mL in the absence of PAβN, which dropped to 4 µg/mL when PAβN was added. Table 4 summarizes the changes in ciprofloxacin MICs with and without PAβN treatment in high-acrB isolates. Table 4. Effect of PAβN on Ciprofloxacin MICs in Selected MDR Klebsiella pneumoniae Isolates with High acrB Expression Isolate ID acrB Fold Expression MIC Ciprofloxacin (µg/mL) MIC + PAβN (µg/mL) Fold Reduction KPN-01 6.2× 16 2 8× KPN-03 7.5× 32 4 8× KPN-07 5.8× 16 2 8× KPN-10 8.3× 64 8 8× Note: MICs were determined using the broth microdilution method according to CLSI (2025) guidelines. PAβN was used at a final concentration of 25 µg/mL. A ≥4-fold reduction in MIC in the presence of PAβN was considered indicative of active efflux pump contribution to ciprofloxacin resistance. Two isolates showed moderate (2–3-fold) decreases in MIC, while no increase in MIC was observed in any isolate. These findings confirm that the AcrAB-TolC system actively contributes to fluoroquinolone resistance in a majority of tested MDR isolates, in concordance with the gene expression data. The results provide direct phenotypic evidence supporting the functional relevance of efflux pump upregulation in resistance mechanisms. These findings align with previously reported roles of RND-type efflux pumps in limiting the accumulation of antibiotics. 3.4. Key Findings Our findings demonstrate that most MDR K. pneumoniae isolates show elevated Expression of the global regulators MarA and SoxS, which strongly correlate with increased activity of the AcrAB-TolC efflux pump. In contrast, Rob's Expression remained low and had minimal influence on efflux gene regulation. This upregulation of efflux components, driven by MarA and SoxS, contributes directly to enhanced resistance—particularly against fluoroquinolones—highlighting the critical role of these transcriptional regulators in mediating multidrug resistance. Moreover, phenotypic validation using the efflux pump inhibitor PAβN confirmed that the elevated gene expression corresponded to functional efflux activity in the majority of tested isolates, as evidenced by significant reductions in ciprofloxacin MICs. These combined molecular and phenotypic findings provide strong support for targeting the efflux system as a potential strategy to restore antibiotic susceptibility. 4. Discussion In the current study, we investigated the role of the MarA, SoxS, and Rob transcriptional regulators in multidrug resistance in K. pneumoniae , with a primary focus on their impact on the AcrAB-TolC efflux system and antibiotic susceptibility. The essential findings are: i- an elevation of marA and soxS transcription in MDR K. pneumoniae, accompanied by a mild increase in rob; ii - this Expression was associated with an increase in acrA, acrB, and tolC transcription; iii- there was a strong correlation between the increase in marA and soxS transcription and the increase in acrB levels, suggesting a potential association, but not definitive evidence, of efflux pump activation; iv- the upregulation of acrB resulted in heightened resistance to ciprofloxacin, demonstrating the importance of efflux in drug action. Our findings highlight the significance of the mar/sox/rob regulon in K. pneumoniae’s resistance to antibiotic stress. MarA and SoxS are important regulators that promote resistance by efflux. Higher amounts of these regulators then bind to marbox sites in the promoter regions of target genes and activate the "marA/soxS/rob." Such a regulon makes bacteria resistant to antibiotics, including through the acrAB-tolC efflux operon. The relationship between marA/soxS and acrB expression in MDR isolates also suggests the in vivo function of the regulon in clinical K. pneumoniae. Common to most MDR isolates is the induction of the mar/sox regulon, resulting in increased efflux pump production and decreased antibiotic accumulation. This finding is in agreement with information from other Enterobacteriaceae, such as E. coli , which indicates that overexpression of MarA or SoxS leads to multiple antibiotic resistance (MAR) through efflux induction [4, 24, 25, 26, 27]. In addition to transcriptional profiling, we performed functional phenotypic validation to assess whether acrB overexpression corresponds to active efflux activity. The phenotypic validation using the efflux pump inhibitor PAβN provided direct functional evidence supporting the role of the AcrAB-TolC efflux system in ciprofloxacin resistance among MDR K. pneumoniae isolates. Most tested strains with elevated acrB Expression showed a ≥4-fold reduction in ciprofloxacin MICs upon PAβN treatment, strongly suggesting that the observed gene overexpression translates into actual efflux activity. These findings bridge the gap between transcriptional data and functional resistance, supporting the hypothesis that MarA and SoxS expression is associated with AcrAB-TolC upregulation, which may contribute to phenotypic resistance. Interestingly, a few isolates showed partial or no reduction in MIC values despite high acrB Expression. This variability may be attributed to additional resistance mechanisms such as target site mutations in gyrA/parC , enzymatic modifications, or the presence of other active efflux systems like OqxAB. These results highlight the multifactorial nature of antibiotic resistance in K. pneumoniae , where efflux pumps interact synergistically with other resistance determinants. Incorporating functional assays, such as PAβN testing, into routine resistance analysis could provide a more accurate assessment of the contribution of efflux in clinical settings and guide the selection of combination therapies involving efflux pump inhibitors [5,24]. Analysis of clinical isolates of bacteria revealed a minor role for the regulator protein Rob. We observed only a minor, ~2-fold difference between wild-type and MDR strains expressing the rob gene and no correlation with the Expression of efflux genes or the level of drug resistance. These results suggest that Rob may already be present at high basal levels and function primarily through post-translational regulation, such as sequestration or ligand activation, rather than at the transcriptional level. Although Rob may regulate the Expression of the efflux pump, the transcript amount of Rob remains steady. The transcription factor Rob may require specific signals, including metabolic or environmental cues that may not be properly present in standard clinical or laboratory settings, to be active. Therefore, it appears likely that Rob is principally inactive and serves as a modulator of the MDR phenomenon, with MarA and SoxS as the major regulators of efflux in response to antibiotic assault [4,28,29]. The heterogeneity among MDR K. pneumoniae isolates needs to be investigated in depth. Interestingly, some MDR strains exhibited no overexpression of marA or soxS, yet they still showed resistance to antibiotics, demonstrating a variety of potential pathways through which MDR occurred. Alternative resistance mechanisms, such as the Expression of high levels of β-lactamase, including carbapenemases and extended-spectrum β-lactamases (ESBLs), or mutations in target genes for fluoroquinolone resistance, such as gyrA and parC, may be present. Furthermore, other efflux pumps or regulatory systems not included in this study, such as the RamA/RamR or OqxAB efflux pump, were likely to be at least part of the MDR phenotype expression in K. pneumoniae . Recent work has also implicated regulatory systems, such as EnvZ-OmpR and BaeSR, alongside RamA, in modulating resistance to cefiderocol [30]. Regulation in K. pneumoniae is multifaceted, and its functions appear partially redundant. AraC-family regulator RamA is a constitutive activator of the acrAB operon. Although we did not evaluate ramA expression, it may be upregulated in some isolates with low marA and soxS levels, thereby enhancing efflux pump expression, as all MDR isolates exhibited elevated acrB levels. Previous studies suggest that mutations in the ramR repressor can lead to RamA overexpression, thereby increasing AcrAB-TolC expression and contributing to resistance to tigecycline and other multidrug resistance (MDR) phenotypes. Our data support this idea, as isolates with high acrB and low marA may reflect RamA-mediated efflux mechanisms. This emphasizes the need to view MarA, SoxS, and Rob as key components of a broader regulatory network that governs efflux and multidrug resistance, recommending the inclusion of RamA and its counterpart RarA in the regulatory framework concerning K. pneumoniae [16, 31, 32, 33]. Our findings reveal both similarities and differences with previous research. In K. pneumoniae isolates from New York, a strong link was found between SoxS expression and acrB levels, whereas MarA showed no such relationship [31, 34]. They noted that many KPC-producing strains had limited regulatory and efflux activation [35,36]. Conversely, our dataset included various multidrug resistance mechanisms, predominantly lacking exclusive KPC-producing isolates, revealing a significant association between MarA, SoxS, and acrB Expression. This difference could stem from genetic diversity, as KPC carbapenemase clones may depend less on efflux mechanisms. Our samples, resistant to fluoroquinolones and aminoglycosides, showed marked involvement of these mechanisms. Mutations in gyrA were crucial, as indicated by Bratu et al., who found that gyrA mutations increased marA and acrB expression, thus enhancing fluoroquinolone resistance [23,30,35]. Our findings confirm that acrB upregulation corresponds with an increased minimum inhibitory concentration (MIC) for ciprofloxacin, suggesting that in gyrA-mutated isolates, efflux pumps considerably raise the MIC, often breaching clinical significance. This implies that efflux mechanisms may act additively or synergistically with other resistance mechanisms [37, 38, 39]. Our findings highlight the significant influence of the MarA/SoxS/Rob regulon, which extends beyond efflux mechanisms to modulate various genes crucial for oxidative stress responses and membrane permeability. MarA and Rob have been reported to downregulate porin genes, such as ompF, in Escherichia coli, thereby reducing the influx of antibiotics [40]. While porin levels were not assessed in this study, the overexpression of MarA and SoxS in multidrug-resistant isolates may contribute to reduced outer membrane permeability, potentially enhancing resistance. Furthermore, the observed positive relationship between marA and soxS expression suggests the possibility of co-activation or shared induction in response to stressors such as oxidative stress from the host's immune response and antibiotic pressure. Such concurrent activation could be associated with increased expression of defense-related genes, including those linked to efflux pump function, potentially providing the bacterium a survival advantage under hostile conditions [41,42]. From a clinical viewpoint, MarA and SoxS are critical in multidrug-resistant Klebsiella pneumoniae , as they are key regulatory proteins within a complex network that presents significant therapeutic intervention potential. Suppressing MarA or SoxS through small molecules that inhibit their DNA-binding could inactivate various resistance mechanisms, including efflux systems and alterations in porin structure, thereby potentially restoring antibiotic susceptibility. The efflux pump inhibitor phenyl-arginine β-naphthylamide (PAβN) is a prime example. Developing "anti-activators" that target the functions of MarA and SoxS is also a promising research avenue. However, Klebsiella's redundancy—such as RamA compensating for MarA inhibition—implies that a successful strategy may require a combined approach of efflux pump inhibition and decreased regulatory activity. Our findings suggest that targeting efflux mechanisms can only modestly enhance fluoroquinolone efficacy, as higher AcrB expression is associated with increased minimum inhibitory concentrations. Thus, further strategies may be essential to address resistance mechanisms beyond efflux pathways [ 4 3,44]. An analytical examination reveals that the MarA/SoxS/Rob regulon does not uniformly affect all antibiotics. Our findings indicate no association between these regulators and gentamicin resistance, suggesting that in our multi-drug-resistant isolates, gentamicin resistance likely results from enzyme-mediated mechanisms. Importantly, Klebsiella pneumoniae acquires various resistance traits, and the upregulation of efflux pumps does not exclude other resistance strategies. Therefore, addressing MDR K. pneumoniae infections should incorporate initiatives targeting efflux pump systems and their regulatory mechanisms [45, 46]. 5. Limitations This study highlights several limitations. The data were derived from relative gene expression evaluated in vitro; actual expression in a human host may differ due to environmental factors. The normalization used a single housekeeping gene, 16S rRNA; adding another reference gene could enhance the robustness of the findings. By testing 30 MDR isolates, the study may not reflect all aspects of genetic diversity associated with K. pneumoniae regulatory mutations. Furthermore, the impact of mutations in marR or soxR on this overexpression was not addressed. All isolates were collected from a single hospital center, which may limit the generalizability of the findings. Additionally, the study focused primarily on mRNA levels and did not include protein-level validation using methods such as Western blotting or ELISA, which are essential to confirm whether transcriptional changes are reflected at the protein level. Such experiments would help establish whether increased efflux activity results from gene upregulation. Finally, ramA and other regulatory elements (such as RarA) that contribute to the control of MDR in K. pneumoniae were excluded, which might also provide a more complete regulatory landscape. Our findings suggest that MarA and SoxS are linked to efflux-mediated multidrug resistance in K. pneumoniae. This provides further insight into K. pneumoniae’s response to antibiotics and the importance of intrinsic mechanisms encoded in its chromosome, particularly efflux regulation. This is especially relevant in the context of plasmid-borne carbapenemases and other acquired resistance genes. 6. Conclusion This study highlights the pivotal role of global transcriptional regulators MarA and SoxS in mediating multidrug resistance in Klebsiella pneumoniae through upregulation of the AcrAB-TolC efflux system. The strong correlation between marA/soxS and acrB expression, observed in clinical MDR isolates, underscores their contribution to fluoroquinolone resistance. Importantly, phenotypic validation using the efflux inhibitor PAβN confirmed that the transcriptional upregulation translated into active efflux activity, as evidenced by significant MIC reductions in the majority of tested isolates. These findings emphasize that resistance in K. pneumoniae is not solely determined by the presence or overexpression of genes but also by the functional Expression of efflux mechanisms. From a therapeutic perspective, combining traditional antibiotics with efflux pump inhibitors or modulators of regulatory pathways such as MarA/SoxS may offer a promising strategy to restore antimicrobial efficacy. Further investigation into alternative efflux systems and regulatory mutations is warranted to develop integrated approaches targeting multidrug resistance. Declarations Conflicts of Interest The authors declare that they have no conflicts of interest. Sources of funding: no report Acknowledgments The authors would like to thank the Department of Biology, College of Science, University of Kerbala, for their support and provision of the essential research environment. We also express our sincere appreciation to the Department of Applied Biotechnology, College of Biotechnology, AL-Qasim Green University, Babylon, Iraq, for providing laboratory facilities and technical resources that greatly supported the experimental procedures. Special thanks are extended to the staff at Imam Al-Sadiq Hospital in Hillah for their cooperation in providing clinical isolates. This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions Maryam Sabah Naser (M.S.N.) was responsible for collecting clinical samples and performing laboratory analyses, including qRT-PCR and antimicrobial susceptibility testing, and made significant contributions to data acquisition. Ali Jabbar Abd Al-Hussain Alkawaz (A.J.A.) conceptualized the study, supervised the research design, coordinated project implementation, and oversaw manuscript development and final review. Ali Jalil Obaid (A.J.O.) performed statistical analyses, handled correlation assessments, and assisted in interpreting gene expression results. All three authors participated in drafting and revising the manuscript, approved the final version for submission, and agreed to be accountable for all aspects of the work, ensuring its accuracy and integrity. Funding The authors received no specific funding for this work Ethics, Consent to Participate, and Consent to Publish declarations This study was approved by the Research Ethics Committee of the College of Science, University of Kerbala (Approval Number: 0014CSE). All clinical samples were obtained anonymously and analyzed in accordance with institutional and international ethical guidelines. Consent to participate: Not applicable (no direct patient contact or identifiable data involved). Consent to publish: Not applicable. References Russo A, Fusco P, Morrone HL, Trecarichi EM, Torti C (2023) New Advances in Management and Treatment of Multidrug-Resistant Klebsiella pneumoniae. 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Nat Genet 55(1):112–122. https://doi.org/10.1038/s41588-022-01248-z Verma T, Nandini SS, Singh V, Raghavan A, Annappa H, Bhaskarla C, Dubey AK, Nandi D (2024) Divergent Roles of Escherichia coli Encoded Lon Protease in Imparting Resistance to Uncouplers of Oxidative Phosphorylation: Roles Of marA, rob, soxS, And acrB. Curr Microbiol 81(4). https://doi.org/10.1007/s00284-024-03632-w Anes J, Dever K, Eshwar A, Nguyen S, Cao Y, Sivasankaran SK, Sakalauskaite S, Pleguezuelos EG, Glenn SJ, Bean DC, Crook DT, McHugh TD, Gant V (2021) Analysis of The Oxidative Stress Regulon Identifies SoxS as A Genetic Target for Resistance Reversal in Multidrug-Resistant Klebsiella pneumoniae, mBio. 12(3):e00653–e00621. https://doi.org/10.1128/mbio.00867-21 Duffey M, Jumde RP, da Costa RMA, Ropponen HK, Blasco B, Piddock LJV (2024) Extending the Potency and Lifespan of Antibiotics: Inhibitors of GramNegative Bacterial Efflux Pumps. ACS Infect Dis 10(5):1458–1482. https://doi.org/10.1021/acsinfecdis.4c00091 Rivera-Galindo MA, Aguirre-Garrido F, Garza-Ramos U, Villavicencio-Pulido JG, Perrino FJF, López-Pérez M (2024) Relevance of The Adjuvant Effect Between Cellular Homeostasis and Resistance to Antibiotics in Gram-Negative Bacteria with Pathogenic Capacity: A Study of Klebsiella pneumoniae. Antibiotics 13(6):490. https://doi.org/10.3390/antibiotics13060490 Wright M, Kaur M, Thompson LK, Cox G (2025) A Historical Perspective on The Multifunctional Outer Membrane Channel Protein TolC in Escherichia coli. npj Antimicrob Resist 3(1). https://doi.org/10.1038/s44259-025-00078-3 Teng J, Imani S, Zhou A, Zhao Y, Du L, Deng S, Li J, Wang Q (2023) Combatting Resistance: Understanding Multidrug-Resistant Pathogens in Intensive Care Units. Biomed Pharmacother 167:115564. https://doi.org/10.1016/j.biopha.2023.115564 Duval V, Lister IM (2013) MarA, SoxS and Rob of Escherichia coli – Global Regulators of Multidrug Resistance, Virulence and Stress Response. Int J Biotechnol Wellness Ind 2(3). https://doi.org/10.6000/1927-3037.2013.02.03.2 Founde LEL (2024) Investigating the Role of EnvZ-OmpR, BaeSR, And RamA in The Resistance of Klebsiella pneumoniae To Cefiderocol, Master’s Thesis, University of Edinburgh, Edinburgh, UK Chiang AD, Dekker JP (2024) Efflux Pump–Mediated Resistance to New βLactam Antibiotics in MultidrugResistant GramNegative Bacteria. Commun Med 4:170. https://doi.org/10.1038/s43856-024-00591-y Chubiz LM, Sox TM, Systems R (2023) EcoSal Plus. 11(1) eesp00102022. https://doi.org/10.1128/ecosalplus.esp-0010-2022 Al-Najim AN, Hamid AT, Basheer AA, Mahmood FN, Hasan EMA (2024) Effect of Nanoparticles on The Expression of Virulence and Biofilm Genes in Klebsiella pneumoniae. Regul Mech Biosyst 15(4):826–829. https://doi.org/10.15421/0224118 Xia Z, Zhou J, Gao N, Li G, Liu R, Lu G, Shen J (2024) AcrAB-TolC Efflux Pump Overexpression And tet(A) Gene Mutation Increase Tigecycline Resistance in Klebsiella pneumoniae. World J Microbiol Biotechnol 40(8):233. https://doi.org/10.1007/s11274-024-04039-2 Di Bella S, Giacobbe DR, Maraolo AE, Viaggi V, Luzzati R, Bassetti M, Luzzaro F, Principe L (2021) Resistance to Ceftazidime/Avibactam in Infections and Colonisations By KPC-Producing Enterobacterales: A Systematic Review of Observational Clinical Studies. J Glob Antimicrob Resist 25:268–281. https://doi.org/10.1016/j.jgar.2021.04.001 de Souza GdaC, Roque-Borda CA, Pavan FR (2022) Beta-Lactam Resistance and The Effectiveness of Antimicrobial Peptides Against KPC-Producing Bacteria. Drug Dev Res 83(7):1534–1554. https://doi.org/10.1002/ddr.21990 Ciusa ML, Marshall RL, Ricci V, Stone JW, Piddock LJV, Absence (2022) Loss-Of-Function, Or Inhibition of Escherichia coli AcrB Does Not Increase Expression of Other Efflux Pump Genes Supporting the Discovery of AcrB Inhibitors as Antibiotic Adjuvants. J Antimicrob Chemother 77(3):633–640. https://doi.org/10.1093/jac/dkab452 Su Y, Kuang S, Ye J, Tao J, Li H, Peng X, Peng B (2021) Enhanced Biosynthesis of Fatty Acids Is Associated with The Acquisition of Ciprofloxacin Resistance in Edwardsiella tarda. mSystems 6(4):1128. https://doi.org/10.1128/msystems.00694-21 Zhai Y-J, Liu P-Y, Luo X-W, Liang J, Sun Y-W, Cui X-D, He D-D, Pan Y-S, Wu H, Hu G-Z (2023) Analysis of The Regulatory Mechanism of AcrB and CpxR On Colistin Susceptibility Based on Transcriptome and Metabolome of Salmonella Typhimurium. Microbiol Spectr 11(4). https://doi.org/10.1128/spectrum.00530-23 Davin-Regli A, Pagès J-M, Vergalli J (2024) The Contribution of Porins to Enterobacterial Drug Resistance. J Antimicrob Chemother 79(10):2460–2470. https://doi.org/10.1093/jac/dkae265 Ariza RR, Cohen SP, Bachhawat N, Levy SB, Demple B (1994) Repressor Mutations in the marRAB Operon That Activate Oxidative Stress Genes and Multiple Antibiotic Resistance in Escherichia coli. J Bacteriol 176(1):143–148. https://doi.org/10.1128/jb.176.1.143-148.1994 Kompaniiets D, Wang D, Yang Y, Hu Y, Liu B (2024) Structure and Molecular Mechanism of Bacterial Transcription Activation. Trends Microbiol 32(4):379–397. https://doi.org/10.1016/j.tim.2023.10.001 Ciusa ML, Marshall RL, Ricci V, Stone JW, Piddock LJV, Absence (2022) Loss-Of-Function, Or Inhibition of Escherichia coli AcrB Does Not Increase Expression of Other Efflux Pump Genes Supporting the Discovery of AcrB Inhibitors as Antibiotic Adjuvants. J Antimicrob Chemother 77(3):633–640. https://doi.org/10.1093/jac/dkab452 El-Demerdash AS, Kamel SA, Elariny EYT, Henidi H, Mahran Y, Alahdal H, Saleh AM, Ibrahim RA (2024) Natural Inhibitors of Salmonella MDR Efflux Pumps AcrAB and AcrD: An Integrated in Silico, Molecular, And In Vitro Investigation. Int J Mol Sci 25(23):12949. https://doi.org/10.3390/ijms252312949 Kirthika P, Lloren KKS, Jawalagatti V, Lee JH (2023) Structure, Substrate Specificity and Role of Lon Protease in Bacterial Pathogenesis and Survival. Int J Mol Sci 24(4). https://doi.org/10.3390/ijms24043422 Uhlich GA, Koppenhöfer HS, Gunther IV NW, Ream AR (2022) Control of Escherichia coli Serotype O157:H7 Motility and Biofilm Formation by Salicylate and Decanoate: MarA/SoxS/Rob and PchE Interactions. Appl Environ Microbiol 88(2):e01891–e01821. https://doi.org/10.1128/aem.01891-21 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7168743","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":488021774,"identity":"5e8fff04-6f13-4406-9901-a5b5c6047ec7","order_by":0,"name":"Maryam S. Naser","email":"","orcid":"https://orcid.org/0000-0003-0658-9090","institution":"Department of Applied Biotechnology, College of Biotechnology, AL-Qasim Green University, Babylon, Iraq","correspondingAuthor":false,"prefix":"","firstName":"Maryam","middleName":"S.","lastName":"Naser","suffix":""},{"id":488021775,"identity":"5059a3fd-2f0c-42f1-ac38-528bd2b7fab5","order_by":1,"name":"Ali J. Alkawaz","email":"data:image/png;base64,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","orcid":"https://orcid.org/0009-0005-1189-6361","institution":"Department of Biology, College of Science, University of Kerbala: Karbala, Iraq","correspondingAuthor":true,"prefix":"","firstName":"Ali","middleName":"J.","lastName":"Alkawaz","suffix":""},{"id":488021776,"identity":"72860022-8f95-48c1-a39c-2033c518bb65","order_by":2,"name":"Ali J. Obaid","email":"","orcid":"https://orcid.org/0000-0001-6385-8125","institution":"Department of Applied Biotechnology, College of Biotechnology, AL-Qasim Green University, Babylon, Iraq","correspondingAuthor":false,"prefix":"","firstName":"Ali","middleName":"J.","lastName":"Obaid","suffix":""}],"badges":[],"createdAt":"2025-07-20 09:31:30","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":true,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7168743/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7168743/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":87260435,"identity":"64e680ef-9eb6-4d4a-a110-726f5c9dbdf2","added_by":"auto","created_at":"2025-07-22 07:07:00","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":102014,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparative expression levels of global regulators (marA, soxS, rob) and efflux pump genes (acrA, acrB, tolC) in MDR and susceptible \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eK. pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e isolates. Data are represented as mean ± SD fold change relative to the susceptible strain, normalized to 16S rRNA. Blue bars indicate susceptible strains; orange bars represent MDR strains. All differences are statistically significant (\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ep \u0026lt; 0.001\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7168743/v1/b2c59279c2fd16e288f842f9.jpg"},{"id":87261344,"identity":"e1bd2049-9405-4972-bf7c-293fdcdd51a9","added_by":"auto","created_at":"2025-07-22 07:15:00","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":111464,"visible":true,"origin":"","legend":"\u003cp\u003eThe scatter plot presents the correlation between marA and acrB expression levels in MDR isolates. Expression data are presented as log₂-transformed fold change (log₂(2^-ΔΔCt)) relative to the susceptible reference strain\u003cem\u003e. \u003c/em\u003eThis transformation was used to linearize the distribution for regression analysis\u003cem\u003e.\u003c/em\u003e ** indicates a statistically significant difference at \u003cem\u003ep \u0026lt; 0.0083\u003c/em\u003e(Bonferroni-corrected threshold).\u003c/p\u003e","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7168743/v1/36929eec64eb7d8414108001.jpg"},{"id":87262766,"identity":"1170630b-e9cc-4189-bb79-d4a2a70e6666","added_by":"auto","created_at":"2025-07-22 07:31:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1303983,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7168743/v1/c206c49c-5feb-43e1-b92b-0e502621d56a.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eIntegrated Analysis of Global Regulators and Efflux Genes in MDR \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eKlebsiella pneumoniae\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e:Unlocking Targets for Antimicrobial Reversal\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eResistant Klebsiella pneumoniae, which is a multidrug (multi-drug-resistant), has become an increasing problem worldwide with hospital-acquired Infection, with many strains being resistant to almost all therapeutic agents Currently used. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] Because of mechanisms including but not limited to β-Lactamase production (such as KPC), changes in drug target sites, and low levels of intracellular antibiotic accumulation, it has evolved this multidrug resistance (MDR) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. One critical factor in lower accumulation is the activity of multidrug efflux pumps [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eAcrAB-TolC, a member of the resistance nodulation cell division (RND) family, is one of the most studied efflux systems in enterobacteria [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. It pumps a range of anti-biotics, including fluoroquinolones, chloramphenicol, tetracyclines, and β-lactams, thereby reducing intracellular drug concentrations and undermining treatment outcomes [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The mechanism of regulation for this system includes both local repressors and global transcriptional activators [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eMarA, SoxS, and Rob -- three key global regulators have been shown to influence the Expression of efflux-related genes in Escherichia coli as well as other Gram-negative organisms [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. These regulators activate overlapping sets of genes, including the marRAB operon, which affects AcrAB-TolC expression and the multidrug resistance (MDR) phenotype [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Nonetheless, their role in drug resistance in clinical K. pneumoniae isolates re-mains unclear.\u003c/p\u003e\u003cp\u003eWith the increasing threat of MDR K. pneumoniae, it is vital to understand what triggers drug efflux pump activation. This work has been designed to examine the transcription of marA, soxS, and rob in relation to acrA, acrB, and tolC in clinical MDR K. pneumoniae isolates using qRT-PCR analysis techniques, which can help identify potential pathways for regulating resistance through efflux mechanisms. As Klebsiella pneumoniae and other Gram-negative bacteria have evolved efflux mechanisms for antibiotics, the changing antibacterial environment has led to the development of new survival strategies, including altering the concentrations of fluoroquinolones within their cells. Despite providing valuable molecular insights from RNA deep sequencing, it cannot be confirmed that the activity of efflux pumps is related to the uptake of genes or their role in leading to resistance. To circumvent this restriction, phenotypic validation employing efflux pump inhibitors has become increasingly important. Among these, phenyl-arginine β-naphthylamide 4 (PAβN) is an established inhibitor of AcrAB-TolC family transporters, which are resistance-nodulation-division (RND) pumps. By blocking efflux, PAβN increases intracellular drug levels and restores susceptibility in strains resistant to efflux. PAβN is an experimental inhibitor of the AcrAB-TolC system, not approved for clinical use due to toxicity, but valuable for mechanistic studies of efflux inhibition. These inhibitors can be integrated into experimental workflows as confirmatory tools to support transcriptional data with functional evidence. In this light, the present study was also extended to encompass a phenotypic efflux assay, in which the action of PAβN on ciprofloxacin susceptibility in several clusters of multidrug-resistant K. pneumoniae, all of which had high acrB Expression, was assessed. This addition aimed to supply supporting evidence for transcript-based Analysis and add clarity to the role played by active efflux in antibiotic resistance.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003e2.1. Isolation and Characterization of Bacterial Strains\u003c/h2\u003e\u003cp\u003eThirty MDR \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e isolates were collected from patients at Imam Al-Sadiq Hospital, Babylon-Hillah. MDR was defined as resistance to at least one agent in three or more antibiotic classes, including β-lactams, fluoroquinolones, and aminoglycosides. Clinical sources included blood, sputum, urine, and wound swabs. Isolates were identified using standard biochemical reactions and the Vitek 2 system. Ten susceptible \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates and the reference strain \u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 13883 were used as controls. All isolates were preserved at \u0026minus;\u0026thinsp;80\u0026deg;C in glycerol stocks and revived on Mueller-Hinton agar prior to testing [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003e2.2. Determination of Antibiotic Resistance Profiles\u003c/h2\u003e\u003cp\u003eSusceptibility was evaluated using disk diffusion and broth microdilution MIC testing, as per CLSI guidelines (2025). For disk diffusion, bacterial suspensions (0.5 McFarland) were spread on Mueller-Hinton agar, and BD BBL\u0026trade; antibiotic disks were applied. After 16\u0026ndash;18 hours of incubation at 35\u0026deg;C, inhibition zones were measured. Tested antibiotics included ciprofloxacin (5 \u0026micro;g), gentamicin (10 \u0026micro;g), piperacillin-tazobactam, ceftriaxone, meropenem, and trimethoprim-sulfamethoxazole. MICs for ciprofloxacin and gentamicin were assessed using cation-adjusted Mueller-Hinton broth with two-fold serial dilutions from 0.06 to 64 \u0026micro;g/mL. CLSI breakpoints were used for interpretation [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003e2.3. RNA Extraction and cDNA Synthesis for Gene Expression Analysis\u003c/h2\u003e\u003cp\u003eTotal RNA was extracted from mid-log phase cultures using the GeneJET RNA Purification Kit (Thermo Scientific), quantified using a NanoDrop, and evaluated on an agarose gel. Genomic DNA was removed using DNase I. First-strand cDNA synthesis was performed using the Revert Aid First Strand cDNA Synthesis Kit (Thermo Scientific) [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003e2.4. Quantitative Real-Time PCR (qRT-PCR)\u003c/h2\u003e\u003cp\u003eThe expression levels of regulatory genes (marA, soxS, rob) and efflux pump components (acrA, acrB, tolC) were quantified using quantitative reverse transcription PCR (qRT-PCR). Gene-specific primers were designed via Primer3 software to produce amplicons of approximately 100 base pairs. Primer validation confirmed specificity and efficiency (95\u0026ndash;100%), as shown by single-peak melt curve profiles [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eReactions were performed in 96-well plates on the Quant Studio 5 Real-Time PCR System using SYBR Green chemistry. Each 20 \u0026micro;L reaction included 2 \u0026micro;L of cDNA, 0.5 \u0026micro;M of forward and reverse primers, and 10 \u0026micro;L of PowerUp SYBR Green Master Mix (Thermo Scientific). The thermal protocol consisted of an initial activation step at 95\u0026deg;C for 2 minutes, followed by 40 cycles of denaturation at 95\u0026deg;C for 15 seconds and annealing and extension at 60\u0026deg;C for 30 seconds. All samples were analyzed in triplicate. No-template controls were included for each primer pair to monitor for nonspecific amplification [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe 16S rRNA-encoding rrs gene was used as the endogenous reference for normalization due to its stable Expression under experimental conditions. Although some studies recommend the use of multiple housekeeping genes to ensure normalization robustness, the 16S rRNA gene remains one of the most validated and commonly used internal controls in bacterial expression studies. Its consistent expression across diverse \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e strains and experimental conditions justifies its use as a sole reference gene in this study, particularly given the absence of stressors known to affect ribosomal RNA stability. Threshold cycle (Ct) values were recorded for both target genes and the reference gene. The ΔCt was calculated as CT target \u0026ndash; Ct_16S to correct for differences in RNA input. The ΔΔCt was obtained by comparing each clinical isolate's ΔCt to that of the pan-susceptible calibrator strain (\u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 13883). Relative gene expression was calculated using the 2^-ΔΔCt method. Fold change values greater than one were interpreted as gene overexpression, while values below one indicated downregulation compared to the reference strain [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003e2.5. Statistical Tools and Data Interpretation\u003c/h2\u003e\u003cp\u003eData analysis was performed using GraphPad Prism 9.0 and SPSS version 25 (IBM Corp). Gene expression and MIC values were expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Two-sample t-tests were applied to compare gene expression between MDR and susceptible groups after confirming the normal distribution of ΔCt values. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo correct for multiple comparisons across six target genes, Bonferroni adjustment was applied, setting the significance threshold at α\u0026thinsp;=\u0026thinsp;0.0083 to reduce Type I error risk. Pearson\u0026rsquo;s correlation analysis was used to evaluate linear relationships between expression levels of global regulators (marA, soxS, rob) and efflux pump genes (acrA, acrB, tolC) in 30 MDR isolates. This method also assessed associations between gene expression and antibiotic minimum inhibitory concentration (MIC) values, including those for ciprofloxacin [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eCorrelation strength was interpreted as follows: r\u0026thinsp;\u0026gt;\u0026thinsp;0.7 indicated a strong correlation, 0.4\u0026ndash;0.7 a moderate correlation, and 0.2\u0026ndash;0.4 a weak correlation. Statistical significance for correlations was defined as p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, with all tests being two-tailed. Reported p-values were compared against the Bonferroni-adjusted threshold, and only those\u0026thinsp;\u0026lt;\u0026thinsp;0.0083 were considered significant.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003e2.6. Efflux Pump Inhibition Assay Using PaβN\u003c/h2\u003e\u003cp\u003ePhenyl-arginine-β -naphthylamide (PAβN), a pump inhibitor of efflux, was used to evaluate the functional role of active efflux in ciprofloxacin resistance. (Sigma-Aldrich, USA). Ten multidrug-resistant Klebsiella pneumoniae isolates were selected with high acrB expression levels(\u0026gt;\u0026thinsp;5-fold relative to a reference strain). Minimum inhibitory concentrations (MICs) of ciprofloxacin were determined by broth microdilution (CLSI, 2005) in the absence or presence of PAβN. Serial 2-fold dilutions of ciprofloxacin, ranging from 0.06 to 64 \u0026micro;g/mL, were prepared in 96-well microtiter plates containing Mueller-Hinton broth supplemented with cation-adjusted R2SOV broth medium. The bacterial suspension was adjusted to the 0.5 McFarland standard and incubated for 18 hours at 35\u0026deg;C. The MIC was visually read as the lowest concentration at which no visible growth could be observed. Each isolate was tested twice, with and without PAβN. Suppose the MIC with PAβN was \u0026ge;\u0026thinsp;4-fold lower than that without it. The strain was then considered to possess significant efflux pump activity. Control wells without antibiotics and PAβN were used to check intrinsic growth. The assay provided actual confirmation of the involvement of the AcrAB-TolC system in ciprofloxacin resistance [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003e3.1. Antimicrobial Resistance Profiles of Clinical MDR Isolates\u003c/p\u003e\n\u003cp\u003eA comparison of 30 clinical MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates revealed high resistance to multiple antibiotics, including ciprofloxacin and gentamicin. All MDR isolates exhibited no or minimal inhibition zones (\u0026le;15 mm) to ciprofloxacin, with MICs \u0026ge;8 \u0026micro;g/mL, exceeding the CLSI resistance breakpoint. In contrast, susceptible isolates exhibited inhibition zones of\u0026ge;30 mm and MICs of \u0026le;0.5 \u0026micro;g/mL. Gentamicin resistance followed a similar pattern, with MDR isolates exhibiting MICs between 8 and 32 \u0026micro;g/mL, while susceptible isolates had MICs of \u0026le;2 \u0026micro;g/mL.\u003c/p\u003e\n\u003cp\u003eAdditionally, MDR isolates exhibited co-resistance to several antibiotic classes: 90% were ESBL producers (resistant to third-generation cephalosporins with positive clavulanate synergy), 20% were carbapenem-resistant (imipenem/meropenem MICs \u0026ge;16 \u0026micro;g/mL), and all showed resistance to trimethoprim-sulfamethoxazole and Tetracycline. In contrast, the control isolates, including ATCC 13883, remained broadly susceptible to the antibiotics. These phenotypic resistance patterns support further investigation into corresponding gene expression profiles. Table.1 summarizes the antibiotic resistance profiles and MICs of MDR and control isolates.\u003c/p\u003e\n\u003cp\u003eTable\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e1. Antibiotic Resistance Profiles of MDR \u003cem\u003eK\u003c/em\u003e. \u003cem\u003epneumoniae\u003c/em\u003e Isolates (n = 30)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.6718%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAntibiotic Class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3375%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAgent(s)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8607%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResistance in MDR Isolates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6223%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIC (MDR Isolates)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0031%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIC (Control Isolates)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5046%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.6718%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFluoroquinolones\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3375%;\"\u003e\n \u003cp\u003eCiprofloxacin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8607%;\"\u003e\n \u003cp\u003e100% (30/30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6223%;\"\u003e\n \u003cp\u003e8 \u0026ndash; \u0026gt;64 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0031%;\"\u003e\n \u003cp\u003e\u0026le; 0.5 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5046%;\"\u003e\n \u003cp\u003eNo/\u0026le;15 mm zone in disk diffusion\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.6718%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAminoglycosides\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3375%;\"\u003e\n \u003cp\u003eGentamicin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8607%;\"\u003e\n \u003cp\u003e100% (30/30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6223%;\"\u003e\n \u003cp\u003e8 \u0026ndash; 32 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0031%;\"\u003e\n \u003cp\u003e\u0026le; 2 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5046%;\"\u003e\n \u003cp\u003eMarkedly elevated MICs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.6718%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3rd Gen Cephalosporins\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3375%;\"\u003e\n \u003cp\u003eCTX / CAZ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8607%;\"\u003e\n \u003cp\u003e90% (27/30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6223%;\"\u003e\n \u003cp\u003eResistant (not specified)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0031%;\"\u003e\n \u003cp\u003e\u0026le; 1 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5046%;\"\u003e\n \u003cp\u003eConfirmed ESBL phenotype via synergy tests\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.6718%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCarbapenems\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3375%;\"\u003e\n \u003cp\u003eImipenem / Meropenem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8607%;\"\u003e\n \u003cp\u003e20% (6/30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6223%;\"\u003e\n \u003cp\u003e\u0026ge; 16 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0031%;\"\u003e\n \u003cp\u003e\u0026le; 1 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5046%;\"\u003e\n \u003cp\u003eSuggests the presence of carbapenemases\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.6718%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFolate Inhibitors \u0026amp; Tetracyclines\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3375%;\"\u003e\n \u003cp\u003eTMP-SMX\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8607%;\"\u003e\n \u003cp\u003e100% (30/30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6223%;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0031%;\"\u003e\n \u003cp\u003e\u0026le; 0.5 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5046%;\"\u003e\n \u003cp\u003eUniversally resistant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.6718%;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3375%;\"\u003e\n \u003cp\u003eTetracycline\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.8607%;\"\u003e\n \u003cp\u003e100% (30/30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.6223%;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.0031%;\"\u003e\n \u003cp\u003e\u0026le; 2 \u0026micro;g/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.5046%;\"\u003e\n \u003cp\u003eUniversally resistant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eAbbreviations:\u0026nbsp;\u003c/strong\u003eCTX: Cefotaxime, CAZ: Ceftazidime, IPM: Imipenem, MEM: Meropenem, TMP-SMX: Trimethoprim-Sulfamethoxazole, MIC: Minimum Inhibitory Concentration, MDR: Multidrug-resistant\u003c/p\u003e\n\u003cp\u003eNote: \u0026quot;Not specified\u0026quot; indicates that MIC testing for these antibiotics was not performed. Statistical significance was defined using Bonferroni correction for six comparisons (\u0026alpha; = 0.05/6 \u0026asymp; 0.0083).\u003c/p\u003e\n\u003cp\u003e3.2. Molecular Evidence of Efflux Pump and Global Regulator Overexpression in MDR Isolates\u003c/p\u003e\n\u003cp\u003eQuantitative RT-PCR revealed significantly elevated Expression of marA and soxS in MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates compared to susceptible controls. On average, marA was overexpressed 5.0 \u0026plusmn; 2.1-fold and soxS 4.0 \u0026plusmn; 1.8-fold in MDR strains (p \u0026lt; 0.001), while rob showed a modest increase of 1.9 \u0026plusmn; 0.8-fold (p \u0026lt; 0.001). Among efflux genes, acrA, acrB, and tolC were upregulated by 5.8 \u0026plusmn; 2.0, 7.9 \u0026plusmn; 3.0, and 3.9 \u0026plusmn; 1.5-fold, respectively (p \u0026lt; 0.001). In contrast, susceptible isolates and the reference strain ATCC 13883 exhibited a baseline expression level of approximately 1.0-fold higher than that of the susceptible isolates.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eApproximately 70% of MDR isolates exhibited\u0026gt;4-fold MarA expression, and 63% showed similarly elevated SoxS levels, suggesting that MarA/SoxS activation is a significant resistance mechanism. However, some isolates showed low Expression of these regulators, implying alternative resistance pathways. Rob expression remained consistently low across the collection, indicating a limited role in efflux regulation among MDR strains. Figure 1 illustrates the fold-change differences in gene expression between MDR and susceptible isolates for marA, soxS, rob, and acrAB-tolC genes.\u003c/p\u003e\n\u003cp\u003eFurther categorical Analysis (Table 3) confirmed that most MDR isolates had strong upregulation of marA and soxS, and correlation analysis showed a significant association between their expression levels (r = 0.50, p = 0.005), suggesting co-activation in specific strains. Both genes also correlated strongly with acrB expression (marA: r = 0.75, p \u0026lt; 0.001; soxS: r = 0.83, p \u0026lt; 0.001), suggesting a potential association with the upregulation of the AcrAB-TolC efflux pump, rather than direct regulatory activation. Rob expression showed no significant correlation with acrB (r = 0.07, p = 0.70), suggesting minimal regulatory impact\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAcrB Expression correlated moderately with ciprofloxacin MICs (r = 0.56, p = 0.001), linking efflux pump upregulation to fluoroquinolone resistance. Similar patterns were observed for norfloxacin and levofloxacin. No correlation was observed between marA or acrB and gentamicin MICs (p \u0026gt; 0.5), suggesting alternative resistance mechanisms such as aminoglycoside-modifying enzymes.Table.2 presents the Pearson correlation coefficients between key genes and resistance phenotypes.)\u003c/p\u003e\n\u003cp\u003eTable 2. Pearson Correlation Between Gene Expression and Ciprofloxacin Resistance in MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e (n = 30)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4037%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9441%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ePearson r\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2609%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSignificance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4037%;\"\u003e\n \u003cp\u003e\u003cstrong\u003emarA expression vs. soxS expression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9441%;\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2609%;\"\u003e\n \u003cp\u003eSignificant (**)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4037%;\"\u003e\n \u003cp\u003e\u003cstrong\u003emarA expression vs. acrB Expression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9441%;\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2609%;\"\u003e\n \u003cp\u003eHighly Significant (**)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4037%;\"\u003e\n \u003cp\u003e\u003cstrong\u003esoxS Expression vs. acrB Expression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9441%;\"\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e\u0026lt; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2609%;\"\u003e\n \u003cp\u003eHighly Significant (**)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4037%;\"\u003e\n \u003cp\u003e\u003cstrong\u003erob expression vs. acrB Expression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9441%;\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e0.70 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2609%;\"\u003e\n \u003cp\u003eNot Significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4037%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eacrB Expression vs. Ciprofloxacin MIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9441%;\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2609%;\"\u003e\n \u003cp\u003eSignificant (**)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 35.4037%;\"\u003e\n \u003cp\u003e\u003cstrong\u003emarA expression vs. Gentamicin MIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9441%;\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e0.65 (ns)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 28.2609%;\"\u003e\n \u003cp\u003eNot Significant\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote:\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e** indicates statistically significant correlation at p \u0026lt; 0.0083 (Bonferroni-corrected).ns indicate non-significant correlation (p \u0026ge; 0.0083).\u003c/p\u003e\n\u003cp\u003eTable 3. Distribution of marA and soxS Expression Fold Change in MDR Isolates (n = 30)\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.6804%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFold Change Range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7113%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. of Isolates (marA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.4948%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% (marA)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.6804%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo. of Isolates (soxS)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.433%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% (soxS)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.6804%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026gt; 4\u0026times;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7113%;\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.4948%;\"\u003e\n \u003cp\u003e70%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.6804%;\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.433%;\"\u003e\n \u003cp\u003e63%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.6804%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u0026times; \u0026ndash; 4\u0026times;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7113%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.4948%;\"\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.6804%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.433%;\"\u003e\n \u003cp\u003e27%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 22.6804%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 2\u0026times;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 23.7113%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.4948%;\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.6804%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.433%;\"\u003e\n \u003cp\u003e10%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: X-fold change calculated by a 2^-\u0026Delta;\u0026Delta;Ct relative to the susceptible strain\u003c/p\u003e\n\u003cp\u003eFigure 2 illustrates a positive linear correlation between MarA and acrB expression levels (r = 0.75, p \u0026lt; 0.001),\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003ewhich further supports a strong association between MarA expression and increased acrB levels, indicating a possible regulatory link. While most isolates followed this trend, some with intermediate acrB Expression may involve alternative regulators such as SoxS or RamA.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e3.3. Phenotypic Reversal of Ciprofloxacin Resistance by PA\u0026beta;N Confirms Active Efflux\u003c/p\u003e\n\u003cp\u003eTo functionally validate the role of active efflux in ciprofloxacin resistance, ten multidrug-resistant Klebsiella pneumoniae isolates with elevated acrB Expression were tested for susceptibility to ciprofloxacin in the presence and absence of the efflux pump inhibitor phenyl-arginine \u0026beta;-naphthylamide (PA\u0026beta;N). The addition of PA\u0026beta;N at 25 \u0026micro;g/mL resulted in a marked reduction in MIC values in most tested isolates. Specifically, 8 out of 10 isolates (80%) demonstrated a \u0026ge;4-fold reduction in ciprofloxacin MICs, indicating substantial involvement of the efflux pump. For instance, isolate KPN-12 exhibited a MIC of 32 \u0026micro;g/mL in the absence of PA\u0026beta;N, which dropped to 4 \u0026micro;g/mL when PA\u0026beta;N was added.\u0026nbsp;Table 4 summarizes the changes in ciprofloxacin MICs with and without PA\u0026beta;N treatment in high-acrB isolates.\u003c/p\u003e\n\u003cp\u003eTable 4. Effect of PA\u0026beta;N on Ciprofloxacin MICs in Selected MDR \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e Isolates with High \u003cem\u003eacrB\u003c/em\u003e Expression\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1491%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIsolate ID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eacrB Fold Expression\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.8447%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIC Ciprofloxacin (\u0026micro;g/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMIC + PA\u0026beta;N (\u0026micro;g/mL)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1863%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFold Reduction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1491%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKPN-01\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e6.2\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.8447%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1863%;\"\u003e\n \u003cp\u003e8\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1491%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKPN-03\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e7.5\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.8447%;\"\u003e\n \u003cp\u003e32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1863%;\"\u003e\n \u003cp\u003e8\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1491%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKPN-07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e5.8\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.8447%;\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1863%;\"\u003e\n \u003cp\u003e8\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 16.1491%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eKPN-10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 21.4286%;\"\u003e\n \u003cp\u003e8.3\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24.8447%;\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 17.3913%;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.1863%;\"\u003e\n \u003cp\u003e8\u0026times;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: MICs were determined using the broth microdilution method according to CLSI (2025) guidelines. PA\u0026beta;N was used at a final concentration of 25 \u0026micro;g/mL. A\u0026nbsp;\u0026ge;4-fold reduction in MIC in the presence of PA\u0026beta;N was considered indicative of active efflux pump contribution to ciprofloxacin resistance.\u003c/p\u003e\n\u003cp\u003eTwo isolates showed moderate (2\u0026ndash;3-fold) decreases in MIC, while no increase in MIC was observed in any isolate. These findings confirm that the AcrAB-TolC system actively contributes to fluoroquinolone resistance in a majority of tested MDR isolates, in concordance with the gene expression data. The results provide direct phenotypic evidence supporting the functional relevance of efflux pump upregulation in resistance mechanisms. These findings align with previously reported roles of RND-type efflux pumps in limiting the accumulation of antibiotics.\u003c/p\u003e\n\u003cp\u003e3.4. Key Findings\u003c/p\u003e\n\u003cp\u003eOur findings demonstrate that most MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates show elevated Expression of the global regulators MarA and SoxS, which strongly correlate with increased activity of the AcrAB-TolC efflux pump. In contrast, Rob\u0026apos;s Expression remained low and had minimal influence on efflux gene regulation. This upregulation of efflux components, driven by MarA and SoxS, contributes directly to enhanced resistance\u0026mdash;particularly against fluoroquinolones\u0026mdash;highlighting the critical role of these transcriptional regulators in mediating multidrug resistance. Moreover, phenotypic validation using the efflux pump inhibitor PA\u0026beta;N confirmed that the elevated gene expression corresponded to functional efflux activity in the majority of tested isolates, as evidenced by significant reductions in ciprofloxacin MICs. These combined molecular and phenotypic findings provide strong support for targeting the efflux system as a potential strategy to restore antibiotic susceptibility.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn the current study, we investigated the role of the MarA, SoxS, and Rob transcriptional regulators in multidrug resistance in \u003cem\u003eK. pneumoniae\u003c/em\u003e, with a primary focus on their impact on the AcrAB-TolC efflux system and antibiotic susceptibility. The essential findings are: i- an elevation of marA and soxS transcription in MDR K. pneumoniae, accompanied by a mild increase in rob; ii - this Expression was associated with an increase in acrA, acrB, and tolC transcription; iii- there was a strong correlation between the increase in marA and soxS transcription and the increase in acrB levels, suggesting a potential association, but not definitive evidence, of efflux pump activation; iv- the upregulation of acrB resulted in heightened resistance to ciprofloxacin, demonstrating the importance of efflux in drug action.\u003c/p\u003e\n\u003cp\u003eOur findings highlight the significance of the mar/sox/rob\u0026ensp;regulon in \u003cem\u003eK. pneumoniae\u0026rsquo;s\u003c/em\u003e resistance to antibiotic stress. MarA and SoxS are important regulators that promote resistance by\u0026ensp;efflux. Higher amounts of these regulators then bind to marbox sites in the promoter regions of target genes and activate the \u0026quot;marA/soxS/rob.\u0026quot; Such a regulon makes bacteria resistant to antibiotics, including through the acrAB-tolC efflux operon. The relationship between marA/soxS and acrB expression in MDR isolates also suggests the in vivo function of the regulon in clinical K. pneumoniae. Common to most MDR isolates is the induction of the mar/sox regulon, resulting in increased efflux pump production and decreased antibiotic accumulation. This finding is in agreement with information from other Enterobacteriaceae, such as \u003cem\u003eE. coli\u003c/em\u003e, which indicates that overexpression of MarA or SoxS leads to multiple antibiotic resistance (MAR) through efflux induction [4, 24, 25, 26, 27].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn addition to transcriptional profiling, we performed functional phenotypic validation to assess whether acrB overexpression corresponds to active efflux activity.\u0026nbsp;The phenotypic validation using the efflux pump inhibitor PA\u0026beta;N provided direct functional evidence supporting the role of the AcrAB-TolC efflux system in ciprofloxacin resistance among MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates. Most tested strains with elevated \u003cem\u003eacrB\u003c/em\u003e Expression showed a \u0026ge;4-fold reduction in ciprofloxacin MICs upon PA\u0026beta;N treatment, strongly suggesting that the observed gene overexpression translates into actual efflux activity. These findings bridge the gap between transcriptional data and functional resistance, supporting the hypothesis that MarA and SoxS expression is associated with AcrAB-TolC upregulation, which may contribute to phenotypic resistance.\u003c/p\u003e\n\u003cp\u003eInterestingly, a few isolates showed partial or no reduction in MIC values despite high \u003cem\u003eacrB\u003c/em\u003e Expression. This variability may be attributed to additional resistance mechanisms such as target site mutations in \u003cem\u003egyrA/parC\u003c/em\u003e, enzymatic modifications, or the presence of other active efflux systems like OqxAB. These results highlight the multifactorial nature of antibiotic resistance in \u003cem\u003eK. pneumoniae\u003c/em\u003e, where efflux pumps interact synergistically with other resistance determinants. Incorporating functional assays, such as PA\u0026beta;N testing, into routine resistance analysis could provide a more accurate assessment of the contribution of efflux in clinical settings and guide the selection of combination therapies involving efflux pump inhibitors\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003e[5,24]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAnalysis of clinical isolates of bacteria revealed a minor role for the regulator protein Rob. We observed only a minor, ~2-fold difference between wild-type and MDR strains expressing the rob gene and no correlation with the Expression of efflux genes or the level of drug resistance. These results suggest that Rob may already be present at high basal levels and function primarily through post-translational regulation, such as sequestration or ligand activation, rather than at the transcriptional level. Although Rob may regulate the Expression of the efflux pump, the transcript amount of Rob remains steady. The transcription factor Rob may require specific signals, including metabolic or environmental cues that may not be properly present in standard clinical or laboratory settings, to be active. Therefore, it appears likely that Rob is principally inactive and serves as a modulator of the MDR phenomenon, with MarA and SoxS as the major regulators of efflux in response to antibiotic assault [4,28,29]. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe heterogeneity among MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e\u0026ensp;isolates needs to be investigated in depth. Interestingly, some MDR strains exhibited no overexpression of marA or soxS, yet they still showed resistance to antibiotics, demonstrating a variety of potential pathways through which MDR occurred. Alternative resistance mechanisms, such as the Expression of high levels of \u0026beta;-lactamase, including carbapenemases and extended-spectrum \u0026beta;-lactamases (ESBLs), or mutations in target genes for fluoroquinolone resistance, such as gyrA and parC, may be present. Furthermore, other efflux pumps or regulatory systems not included in this study, such as the RamA/RamR or OqxAB efflux pump, were likely to be at least part of the MDR phenotype expression in \u003cem\u003eK. pneumoniae\u003c/em\u003e. Recent work has also implicated regulatory systems, such as EnvZ-OmpR and BaeSR, alongside RamA, in modulating resistance to cefiderocol [30]. Regulation in \u003cem\u003eK. pneumoniae\u003c/em\u003e is multifaceted, and its functions appear partially redundant.\u003c/p\u003e\n\u003cp\u003eAraC-family regulator RamA is a constitutive activator of the acrAB operon. Although we did not evaluate ramA expression, it may be upregulated in some isolates with low marA and soxS levels, thereby enhancing efflux pump expression, as all MDR isolates exhibited elevated acrB levels. Previous studies suggest that mutations in the ramR repressor can lead to RamA overexpression, thereby increasing AcrAB-TolC expression and contributing to resistance to tigecycline and other multidrug resistance (MDR) phenotypes. Our data support this idea, as isolates with high acrB and low marA may reflect RamA-mediated efflux mechanisms. This emphasizes the need to view MarA, SoxS, and Rob as key components of a broader regulatory network that governs efflux and multidrug resistance, recommending the inclusion of RamA and its counterpart RarA in the regulatory framework concerning \u003cem\u003eK. pneumoniae\u003c/em\u003e [16, 31, 32, 33].\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings reveal both similarities and differences with previous research. In \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates from New York, a strong link was found between SoxS expression and acrB levels, whereas MarA showed no such relationship [31, 34]. They noted that many KPC-producing strains had limited regulatory and efflux activation [35,36]. Conversely, our dataset included various multidrug resistance mechanisms, predominantly lacking exclusive KPC-producing isolates, revealing a significant association between MarA, SoxS, and acrB Expression. This difference could stem from genetic diversity, as KPC carbapenemase clones may depend less on efflux mechanisms. Our samples, resistant to fluoroquinolones and aminoglycosides, showed marked involvement of these mechanisms. Mutations in gyrA were crucial, as indicated by Bratu et al., who found that gyrA mutations increased marA and acrB expression, thus enhancing fluoroquinolone resistance [23,30,35]. Our findings confirm that acrB upregulation corresponds with an increased minimum inhibitory concentration (MIC) for ciprofloxacin, suggesting that in gyrA-mutated isolates, efflux pumps considerably raise the MIC, often breaching clinical significance. This implies that efflux mechanisms may act additively or synergistically with other resistance mechanisms [37, 38, 39]. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings highlight the significant influence of the MarA/SoxS/Rob regulon, which extends beyond efflux mechanisms to modulate various genes crucial for oxidative stress responses and membrane permeability. MarA and Rob have been reported to downregulate porin genes, such as ompF, in Escherichia coli, thereby reducing the influx of antibiotics [40]. While porin levels were not assessed in this study, the overexpression of MarA and SoxS in multidrug-resistant isolates may contribute to reduced outer membrane permeability, potentially enhancing resistance. Furthermore, the observed positive relationship between marA and soxS expression suggests the possibility of co-activation or shared induction in response to stressors such as oxidative stress from the host\u0026apos;s immune response and antibiotic pressure. Such concurrent activation could be associated with increased expression of defense-related genes, including those linked to efflux pump function, potentially providing the bacterium a survival advantage under hostile conditions [41,42].\u003c/p\u003e\n\u003cp\u003eFrom a clinical viewpoint, MarA and SoxS are critical in multidrug-resistant \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e, as they are key regulatory proteins within a complex network that presents significant therapeutic intervention potential. Suppressing MarA or SoxS through small molecules that inhibit their DNA-binding could inactivate various resistance mechanisms, including efflux systems and alterations in porin structure, thereby potentially restoring antibiotic susceptibility. The efflux pump inhibitor phenyl-arginine \u0026beta;-naphthylamide (PA\u0026beta;N) is a prime example. Developing \u0026quot;anti-activators\u0026quot; that target the functions of MarA and SoxS is also a promising research avenue. However, Klebsiella\u0026apos;s redundancy\u0026mdash;such as RamA compensating for MarA inhibition\u0026mdash;implies that a successful strategy may require a combined approach of efflux pump inhibition and decreased regulatory activity. Our findings suggest that targeting efflux mechanisms can only modestly enhance fluoroquinolone efficacy, as higher AcrB expression is associated with increased minimum inhibitory concentrations. Thus, further strategies may be essential to address resistance mechanisms beyond efflux pathways [\u003cspan dir=\"RTL\"\u003e4\u003c/span\u003e3,44].\u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAn analytical examination reveals that the MarA/SoxS/Rob regulon does not uniformly affect all antibiotics. Our findings indicate no association between these regulators and gentamicin resistance, suggesting that in our multi-drug-resistant isolates, gentamicin resistance likely results from enzyme-mediated mechanisms. Importantly, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e acquires various resistance traits, and the upregulation of efflux pumps does not exclude other resistance strategies. Therefore, addressing MDR \u003cem\u003eK. pneumoniae\u003c/em\u003e infections should incorporate initiatives targeting efflux pump systems and their regulatory mechanisms [45, 46].\u003c/p\u003e"},{"header":"5. Limitations","content":"\u003cp\u003eThis study highlights several limitations. The data were derived from relative gene expression evaluated in vitro; actual expression in a human host may differ due to environmental factors. The normalization used a single housekeeping gene, 16S rRNA; adding another reference gene could enhance the robustness of the findings. By testing 30 MDR isolates, the study may not reflect all aspects of genetic diversity associated with K. pneumoniae regulatory mutations. Furthermore, the impact of mutations in marR or soxR on this overexpression was not addressed. All isolates were collected from a single hospital center, which may limit the generalizability of the findings. Additionally, the study focused primarily on mRNA levels and did not include protein-level validation using methods such as Western blotting or ELISA, which are essential to confirm whether transcriptional changes are reflected at the protein level. Such experiments would help establish whether increased efflux activity results from gene upregulation. Finally, ramA and other regulatory elements (such as RarA) that contribute to the control of MDR in K. pneumoniae were excluded, which might also provide a more complete regulatory landscape.\u003c/p\u003e\n\u003cp\u003eOur findings suggest that MarA and SoxS are linked to efflux-mediated multidrug resistance in K. pneumoniae. This provides further insight into K. pneumoniae\u0026rsquo;s response to antibiotics and the importance of intrinsic mechanisms encoded in its chromosome, particularly efflux regulation. This is especially relevant in the context of plasmid-borne carbapenemases and other acquired resistance genes.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eThis study highlights the pivotal role of global transcriptional regulators MarA and SoxS in mediating multidrug resistance in \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e through upregulation of the AcrAB-TolC efflux system. The strong correlation between marA/soxS and acrB expression, observed in clinical MDR isolates, underscores their contribution to fluoroquinolone resistance. Importantly, phenotypic validation using the efflux inhibitor PA\u0026beta;N confirmed that the transcriptional upregulation translated into active efflux activity, as evidenced by significant MIC reductions in the majority of tested isolates.\u003c/p\u003e\n\u003cp\u003eThese findings emphasize that resistance in \u003cem\u003eK. pneumoniae\u003c/em\u003e is not solely determined by the presence or overexpression of genes but also by the functional Expression of efflux mechanisms. From a therapeutic perspective, combining traditional antibiotics with efflux pump inhibitors or modulators of regulatory pathways such as MarA/SoxS may offer a promising strategy to restore antimicrobial efficacy. Further investigation into alternative efflux systems and regulatory mutations is warranted to develop integrated approaches targeting multidrug resistance.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eConflicts of Interest\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors declare that they have no conflicts of interest. Sources of funding: no report\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank the Department of Biology, College of Science, University of Kerbala, for their support and provision of the essential research environment. We also express our sincere appreciation to the Department of Applied Biotechnology, College of Biotechnology, AL-Qasim Green University, Babylon, Iraq, for providing laboratory facilities and technical resources that greatly supported the experimental procedures. Special thanks are extended to the staff at Imam Al-Sadiq Hospital in Hillah for their cooperation in providing clinical isolates. This study did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u003c/p\u003e\n\u003cp\u003eMaryam Sabah Naser (M.S.N.) was responsible for collecting clinical samples and performing laboratory analyses, including qRT-PCR and antimicrobial susceptibility testing, and made significant contributions to data acquisition.\u003cbr\u003e\u0026nbsp;Ali Jabbar Abd Al-Hussain Alkawaz (A.J.A.) conceptualized the study, supervised the research design, coordinated project implementation, and oversaw manuscript development and final review.\u003cbr\u003eAli Jalil Obaid (A.J.O.) performed statistical analyses, handled correlation assessments, and assisted in interpreting gene expression results.\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eAll three authors participated in drafting and revising the manuscript, approved the final version for submission, and agreed to be accountable for all aspects of the work, ensuring its accuracy and integrity.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThe authors received no specific funding for this work\u003c/p\u003e\n\u003cp\u003eEthics, Consent to Participate, and Consent to Publish declarations\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Research Ethics Committee of the College of Science, University of Kerbala (Approval Number: 0014CSE). All clinical samples were obtained anonymously and analyzed in accordance with institutional and international ethical guidelines.\u003c/p\u003e\n\u003cp\u003eConsent to participate: Not applicable (no direct patient contact or identifiable data involved).\u003c/p\u003e\n\u003cp\u003eConsent to publish: Not applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eRusso A, Fusco P, Morrone HL, Trecarichi EM, Torti C (2023) New Advances in Management and Treatment of Multidrug-Resistant Klebsiella pneumoniae. 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Appl Environ Microbiol 88(2):e01891\u0026ndash;e01821. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/aem.01891-21\u003c/span\u003e\u003cspan address=\"10.1128/aem.01891-21\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Kerbala","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Efflux resistance, Fluoroquinolones, Gene regulation, RND transporters, Pump inhibitors, MDR bacteria","lastPublishedDoi":"10.21203/rs.3.rs-7168743/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7168743/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e\u003cp\u003eMultidrug-resistant Klebsiella pneumoniae poses a growing clinical challenge due to its ability to evade antibiotic treatment, particularly through the overexpression of efflux systems. Among these, the AcrAB-TolC pump is central to resistance against fluoroquinolones. While the global regulator's MarA, SoxS, and Rob are known modulators of efflux in Enterobacteriaceae, their functional relevance in clinical K. pneumoniae remains insufficiently defined.\u003c/p\u003e\u003ch2\u003eObjective:\u003c/h2\u003e\u003cp\u003eThis study aimed to elucidate the transcriptional dynamics between global regulators (marA, soxS, rob) and efflux pump components (acrA, acrB, tolC) in multidrug-resistant K. pneumoniae and to validate the functional role of efflux in fluoroquinolone resistance.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e\u003cp\u003eThirty clinical MDR isolates and ten susceptible controls were characterized via antibiotic susceptibility testing. Gene expression was quantified using qRT-PCR, normalized to 16S rRNA, and analyzed by the 2^\u0026ndash;ΔΔCt method. Pearson correlation assessed relationships between gene expression and resistance. Phenotypic validation of efflux activity was performed using PAβN, an AcrAB-TolC inhibitor.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e\u003cp\u003eMDR isolates exhibited significant overexpression of marA (5.0-fold), soxS (4.0-fold), acrB (7.9-fold), and other efflux components (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Strong positive correlations emerged between marA/soxS and acrB expression, implicating coordinated regulatory control. PAβN exposure reduced ciprofloxacin MICs by \u0026ge;\u0026thinsp;4-fold in 80% of high-acrB isolates, confirming active efflux involvement.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e\u003cp\u003eThe data establish MarA and SoxS as principal activators of the AcrAB-TolC efflux system in clinical \u003cem\u003eMDR K. pneumonia\u003c/em\u003e, driving fluoroquinolone resistance. Rob showed minimal impact. Functional inhibition of efflux restored anti-biotic susceptibility in most isolates, highlighting global regulators and efflux pumps as promising targets for adjunctive therapy to combat resistance.\u003c/p\u003e","manuscriptTitle":"Integrated Analysis of Global Regulators and Efflux Genes in MDR Klebsiella pneumoniae:Unlocking Targets for Antimicrobial Reversal","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-22 07:06:56","doi":"10.21203/rs.3.rs-7168743/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"60d1b212-f5fa-4004-b212-7d9510549061","owner":[],"postedDate":"July 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":51806145,"name":"General Microbiology"}],"tags":[],"updatedAt":"2025-07-22T07:06:56+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-22 07:06:56","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7168743","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7168743","identity":"rs-7168743","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}