Analysis of Genetic Characteristics, Biofilm Formation Ability, and Mortality Risk Factors in Patients Infected with Carbapenem-Resistant Acinetobacter baumannii

Introduction

Antimicrobial resistance (AMR) refers to the ability of bacteria to resist drugs, resulting in reduced effectiveness of medications originally used to treat infections; its emergence and spread have become one of the key public health threats of the 21st century. According to statistics, antimicrobial resistance caused 1.27 million direct deaths and 4.95 million indirect deaths worldwide in 2019.¹ Ranked by number of deaths, these six pathogens—Escherichia coli, Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Acinetobacter baumannii (Ab), and Pseudomonas aeruginosa—each caused more than 250,000 deaths associated with antimicrobial resistance.¹ In recent years, the mortality rate among patients with Acinetobacter baumannii infections has ranged from 28% to 43% for bloodstream infections and from 40% to 70% for ventilator-associated pneumonia.² Consequently, in 2024, the World Health Organization (WHO) released a new list of priority bacterial pathogens; due to its resistance to multiple antibiotics, carbapenem-resistant Acinetobacter baumannii (CRAB) was designated a priority pathogen.³

Ab is a common non-fermentative, strictly aerobic, non-motile, catalase-positive, and oxidase-negative Gram-negative bacillus.⁴ A. baumannii is a common colonizing bacterium among hospitalized patients and is widely found on the surfaces of medical devices. As an opportunistic pathogen, it frequently causes hospital-acquired infections, including ventilator-associated pneumonia, urinary tract infections, bacteremia, meningitis, and skin or soft tissue infections. It is one of the major pathogens responsible for infections in immunocompromised individuals.^5,6 In recent years, with the widespread clinical use of carbapenem antibiotics, there has been a steady increase in resistant Acinetobacter strains, including multidrug-resistant (MDR), extensively drug-resistant (XDR), and pan-drug-resistant (PDR) strains. These strains are difficult to treat with currently available medications, exacerbating the problem of hospital-acquired infections caused by this bacterium.⁷ CRAB exhibits multidrug resistance, has extremely limited treatment options, and has become widespread globally, posing a serious threat to global public health.⁸ A nationwide survey of Acinetobacter isolates in the United States, covering hospitals, long-term care facilities, and outpatients, found that the rate of multidrug resistance reached 49%.⁹ Since 2016, the overall incidence of carbapenem-resistant Acinetobacter baumannii-associated bloodstream infections at a tertiary hospital in South Korea has been estimated to exceed 87%.¹⁰ In recent years, mortality rates associated with Acinetobacter baumannii infections have remained high, ranging from 28% to 43% among patients with bloodstream infections and as high as 40% to 70% among those with ventilator-associated pneumonia.² In China, Ab exhibits high resistance (>50%) to a range of antimicrobial agents, including carbapenems, and there is a trend toward decreasing susceptibility to bactericidal agents.^11,12

The mechanisms underlying CRAB resistance to carbapenems are highly complex and primarily involve the expression of active efflux pumps; alterations in antibiotic binding sites; the production of carbapenemases; and biofilm formation.¹³ Among these, the production of carbapenemases is the primary mechanism of resistance; this enzyme hydrolyzes and inactivates carbapenem antibiotics and is often encoded by plasmids, making it highly transmissible.¹⁴ According to the Ambler classification, carbapenemases are divided into four classes: A, B, C, and D,¹⁵ Class D OXA enzymes are the most common and exhibit remarkable genetic diversity. It is worth noting that active efflux mediated by multidrug efflux pumps of the resistance-nodulation-cell division (RND) superfamily is a key mechanism by which microorganisms defend against structurally diverse antimicrobial agents; overexpression of these pumps can significantly increase a strain’s level of resistance.¹⁶ The formation of biofilms enhances the environmental tolerance and antibiotic resistance of Acinetobacter baumannii, making it easier for the bacterium to colonize the surfaces of medical devices; this is a major factor contributing to hospital-acquired infections.^17–19 Biofilms interact synergistically with β-lactamases, further exacerbating the spread of multidrug-resistant strains, leading to prolonged and difficult-to-treat infections, and increasing the burden on public health.^20,21

Although there have been numerous studies on the antimicrobial resistance profiles and clinical risk factors of Acinetobacter baumannii both domestically and internationally, there are significant regional variations in the epidemiological characteristics, resistance profiles, and molecular features of strains across different regions and healthcare institutions, making it difficult to generalize research findings across regions. Currently, the Zhangjiakou region lacks systematic epidemiological data on CRAB, and previous relevant studies are scarce. As a result, clear trends in antimicrobial resistance and local characteristics have not yet been established, limiting the development of precise antimicrobial therapy and strategies for the prevention and control of nosocomial infections in the region. Therefore, this study combines locally clinically isolated CRAB strains to comprehensively analyze their clinical characteristics, antimicrobial resistance phenotypes, and the distribution of genes related to efflux pumps and biofilms, while also exploring independent risk factors affecting patient prognosis. The aim is to establish epidemiological reference data for CRAB in this region, providing a scientific basis for personalized treatment of local CRAB infections and hospital infection control.

Materials and Methods

Strain Source

The study included 244 patients diagnosed with CRAB infection at our hospital between June 2021 and December 2024, along with their bacterial isolates. Samples indicating CRAB colonization were excluded. For each patient, only the first isolate obtained during a single hospitalization was included, and duplicate isolates were excluded. All strains underwent species identification and antimicrobial susceptibility testing using the BD Phoenix™ 100 fully automated bacterial identification and susceptibility testing system (Becton, Dickinson and Company, Sparks, Maryland, USA), with CRAB identification based on CLSI standards. Escherichia coli ATCC 25922 was used as the internal quality control strain.

DNA Extraction

The strains were retrieved from the −80 °C stock library and streaked onto MacConkey agar medium for isolation and culture, followed by incubation at 37 °C for 24 h in a thermostatic incubator. An appropriate amount of colonies were scraped from the agar plate using an inoculation loop and transferred into a centrifuge tube containing 500 μL of sterile water, followed by thorough mixing. The tube was then heated at 100 °C for 15 min for inactivation and centrifuged at 12 000 r/min for 5 min. The supernatant was collected into a new centrifuge tube, and the precipitate was discarded. The obtained supernatant was used as the DNA template and stored at −20 °C until further use.

Common Resistance Genes Detected by PCR

The collected CRAB isolates were analyzed for drug resistance genes, efflux pump genes, and biofilm-related genes by conventional PCR amplification of gene sequences. (Table 1) Design primer sequences for the gene based on relevant literature.^22–25The PCR reaction was performed in a total volume of 25 μL, containing 12.5 μL of 2× Taq Master Mix, 1 μL of forward primer, 1 μL of reverse primer, 1 μL of DNA template, and 9.5 μL of sterile enzyme-free water. Gene amplification was carried out under the following conditions: pre-denaturation at 95 °C for 5 min, denaturation at 95 °C for 30s, and annealing for 30s (See Table 1 for the annealing temperatures), Extension was performed at 72 °C for 30s, for a total of 35 cycles, followed by a final extension at 72 °C for 5 min. After completion of the reaction, the PCR products were stored at 4 °C or immediately subjected to agarose gel electrophoresis at 100 V for 45 min. Microscopic imaging and photographic documentation were performed after electrophoresis.

Table 1 CRAB Resistance Gene Primer Sequences

Detecting Biofilm Formation

Following revival, the strains were subcultured on MacConkey agar plates and incubated at 37 °C for 24 h overnight. Single colonies were picked and inoculated into broth medium, followed by shaking incubation at 37 °C for 24 h. The cultures were centrifuged at 3000 r/min at 4 °C for 5 min, and the supernatants were discarded. After washing with sterile PBS, 3 mL of LB broth was added and mixed thoroughly. Bacterial suspensions equivalent to 0.5 McFarland standard were prepared in normal saline and inoculated into 96-well culture plates (200 μL of LB broth per well). Twelve wells in the first row were used as negative controls. A 20 μL aliquot of bacterial suspension was added to the second well of the first column, with seven biological replicates for each strain. The plates were incubated at 37 °C for 3 days, and the medium was replaced every 24 h. After incubation, the liquid in each well was discarded. A volume of 200 μL of 100% methanol was added to each well, and fixation was performed at 37 °C for 30 min. After removing the methanol, 1% crystal violet was added for staining for 30 min. The wells were rinsed thoroughly with PBS and dried at 37 °C for 30 min. Finally, 200 μL of 95% ethanol was added for elution. The optical density (OD) of each well was measured at a wavelength of 595 nm using a microplate reader. The cutoff OD value (ODc) was defined as the mean OD of negative controls + 3SD. Biofilm formation ability was classified into four levels accordingly: Strong positive: 4×ODc < OD; Moderate positive: 2×ODc < OD ≤ 4×Odc; Weak positive: ODc < OD ≤ 2×Odc; Negative: OD ≤ Odc.²⁶

Statistical Methods

Based on information from the CRAB pathogen database, we accessed electronic medical records to obtain various clinical data on patients and compiled this information into an electronic database (raw data). Statistical analysis was performed using SPSS 27.0 software. Continuous variables that followed a normal distribution were expressed as mean ± standard deviation (x ± s), and Student’s t-test was used for comparisons between groups; Non-normally distributed quantitative data were described as M (P25, P75), and the Mann–Whitney U-test was used for comparisons between groups. Categorical data were expressed as numbers and percentages [n(%)], and comparisons were performed using Pearson’s chi-square test or Fisher’s exact test, with continuity correction applied when the frequency was less than 5. Variables with P < 0.05 in univariate analysis were subjected to multicollinearity testing. Multivariate logistic regression was used to analyze independent risk factors for mortality in patients with CRAB infection, and odds ratios (OR) and 95% confidence intervals (CI) were calculated; a P-value < 0.05 was considered statistically significant. Correlation heatmaps, pie charts, and bar charts were generated using ChiPlot (https://www.chiplot.online/).

Results

Clinical Characteristics

The 244 patients infected with CRAB were primarily from the ICU (119, 48.77%), followed by the Department of Respiratory Medicine (76, 31.15%), Neurosurgery (14, 5.74%), and Rehabilitation Medicine (9, 3.69%); the remainder were distributed across various other departments (Figure 1a). Specimens were primarily obtained from the respiratory tract, including sputum (139, 55.33%), bronchoalveolar lavage fluid (64, 26.23%), and blood (16, 6.56%); other specimens included a small number of wound secretions, among others (Figure 1b).

Figure 1 (a) Distribution of clinical departments. (b) Distribution of clinical specimens.

CRAB infections primarily affect the elderly, with men outnumbering women by a ratio of 2:1 (178 cases vs. 66 cases). To investigate risk factors associated with mortality following CRAB infection, patients were divided into a survival group and a death group based on survival outcomes, and univariate analysis was performed. The results showed statistically significant differences between the two groups in age, white blood cell count, neutrophil percentage, lymphocyte percentage, platelet count, albumin, and total length of hospital stay (P < 0.05). In the non-survivor group, the rates of procalcitonin, blood glucose, mechanical ventilation, endotracheal intubation, central venous catheterization, hemodialysis, bronchoscopy, and the use of carbapenem antibiotics and glucocorticoids were significantly higher in the non-survivor group, while the survivor group had significantly higher rates of surgery, drainage tube placement, use of cephalosporin and fluoroquinolone antibiotics, and incidence of trauma; all intergroup differences were statistically significant (P < 0.05) (Table 2). We performed a multicollinearity test on the variables in the table with P < 0.05 and found that the variance inflation factors for both the percentage of neutrophils and the percentage of lymphocytes were greater than 5, indicating significant multicollinearity between the two variables. After excluding the percentage of lymphocytes, the remaining variables were included in a multivariate logistic regression analysis. The results showed that age (OR = 1.044, 95% CI: 1.009–1.079, P < 0.05), white blood cell count (OR = 1.106, 95% CI: 1.029–1.188, P < 0.05) were independent risk factors for death from CRAB infection. Platelet count (OR = 0.995, 95% CI: 0.991–0.999, P < 0.05) and the use of cephalosporin antibiotics (OR = 0.398, 95% CI: 0.160–0.990, P < 0.05) were independent protective factors against death from CRAB infection (Table 3). In addition, this study conducted a visual subgroup analysis of the survival and mortality groups by gender to compare differences in the distribution of age and various laboratory parameters across gender subgroups. This analysis is presented for descriptive purposes only and was not included in the multivariate regression adjustment. The results showed that in the mortality group, there were statistically significant differences in albumin levels (P < 0.01) (Figure 2a), age (P < 0.05) (Figure 2b), and hemoglobin levels (P < 0.01) (Figure 2c) between male and female patients. No significant statistical differences were observed for the remaining indicators between the two genders within the two groups.

Table 2 Univariate Analysis of the Survival and Mortality Groups Among Patients with CRAB Infection

Table 3 Multivariate Logistic Regression Analysis of Risk Factors for Death Following CRAB Infection

Figure 2 Differences in gender between the survival and non-survival groups of patients with CRAB infection. Note: *p<0.05; **p<0.01.

Antibiotic Susceptibility

The 244 clinically isolated CRAB strains collected in this study exhibited resistance rates as high as 90% to nine commonly used clinical antimicrobial agents. The resistance rate to piperacillin/tazobactam reached 99.58% (Figure 3a), while the resistance rates to imipenem (Figure 3b) and meropenem (Figure 3c) reached 99.15%. The resistance rates to amoxicillin/clavulanate (Figure 3d), cefepime (Figure 3e), ceftazidime (Figure 3f), ceftiofur (Figure 3g), ciprofloxacin (Figure 3h) and levofloxacin (Figure 3i) were both greater than 95%; resistance to gentamicin (Figure 3j) was 89.36%; resistance to ampicillin/ sulbactam (Figure 3k) was 79.57%, resistance to amikacin (Figure 3L) was 70.64%, resistance to co-trimoxazole (Figure 3m) was 50.64%, and resistance to tigecycline (Figure 3n) was 3.08%. However, all CRAB strains exhibited high susceptibility (100%) to polymyxin (Figure 3o).

Figure 3 Antimicrobial resistance profiles of CRAB isolates. Notes: Due to variations in the antibiotic testing panels used for some patients (differences in the types of antibiotics tested), the total number of strains detected for different antibiotics is not uniform. (a) Piperacillin/Tazobactam (n=237). (b) Imipenem (n=235). (c) Meropenem (n=233). (d) Amoxicillin/Clavulanate Potassium (n=140). (e) Cefepime (n=235). (f) Ciprofloxacin (n=233). (g) Levofloxacin (n=233). (h) Ceftazidime (n=235). (i) Cefotaxime (n=167). (j) Gentamicin (n=235). (k) Ampicillin/Sulbactam (n=230). (l) Amikacin (n=235). (m) Trimethoprim/Sulfamethoxazole (n=233). (n) Tigecycline (n=65). (o) Polymyxin (n=234).

CRAB Gene Carrier Status

The primary resistance genes identified in CRAB isolates from our hospital were blaOXA-51 and blaOXA-23, accounting for 89.3% and 87.3% of cases, respectively. The detection rates for blaNDM, blaOXA-58, and blaOXA-24 were 1.6%, 1.2%, and 0.4%, respectively. Concurrently, one strain carried blaOXA-23, blaOXA-51, and blaOXA-58; one strain carried blaOXA-51 and blaNDM; two strains carried blaOXA-23, blaOXA-51, and blaNDM; and 208 strains carried only blaOXA-23 and blaOXA-51 (Figure 4a). In this study, the detection rates of efflux pump genes were as follows: adeB (209/244, 85.7%), adeR (182/244, 74.6%), adeS (205/244, 84.0%), and adeJ (213/244, 87.3%); the adeG gene was not detected (Figure 4b). The detection rates of biofilm-related genes were generally high for bap (240/244, 98.4%), abaI (227/244, 93.0%), and ompA (223/244, 91.4%); the detection rates of the remaining genes ranged from 84.8% to 90.6% (Figure 4c).

Figure 4 CRAB resistance gene, efflux pump gene, and biofilm gene detection results. (a) drug resistance gene. (b) efflux pump gene. (c) biofilm gene.

The Relationship Between CRAB’s Biofilm-Forming Ability and Antibiotic Resistance

The results of strain detection in this study showed that only 2.05% of CRAB isolates exhibited no biofilm formation ability, 47.54% were weak biofilm producers, 44.26% were moderate biofilm producers, and 6.15% were strong biofilm producers. Overall, the vast majority of clinically isolated CRAB strains were able to form biofilms to varying degrees.To clarify the relationship between biofilm formation capacity and antimicrobial resistance, this study analyzed the correlation between CRAB biofilm formation and resistance phenotypes to amikacin and the compound sulfonamide-trimethoxypolymyxin (piperacillin-tazobactam, ampicillin-sulbactam, cefotaxime, ceftiofur, cefepime, ciprofloxacin, levofloxacin, gentamicin, imipenem, meropenem, tigecycline, amoxicillin-clavulanate, and polymyxin; due to the small number of resistant or susceptible strains, the sample sizes were severely unbalanced, and therefore no numerical comparisons or statistical analyses were performed). Amikacin and co-trimoxazole, which had relatively balanced sample distributions, were divided into resistant and susceptible groups, and Spearman correlation analysis was performed. The results of the two analyses showed that there were no statistically significant differences in biofilm levels between the amikacin-resistant group and the susceptible group, or between the co-trimoxazole-resistant group and the susceptible group. The correlation analysis indicated that there was no significant correlation between the amikacin resistance phenotype and biofilm formation (r = −0.045, P = 0.491), nor was there a significant correlation between the co-trimoxazole resistance phenotype and biofilm formation (r = 0.09, P = 0.18) (Table 4).

Table 4 The Relationship Between Antibiotics and Biofilm Formation

Discussion

The CRAB strains collected in this study were sourced from a variety of specimens, with sputum samples accounting for the largest proportion (55.33%), followed by bronchoalveolar lavage fluid (26.23%). In terms of clinical departments, the majority of samples were collected from the ICU (48.77%), followed by the respiratory department (31.15%). These distribution patterns may be highly correlated with the immune status of patients in these departments, the types of diagnostic and therapeutic procedures performed, and environmental exposure risks. For example, ICU patients primarily consist of those with severe trauma, multiple organ dysfunction syndrome (MODS), and postoperative critical care patients. Such patients generally exhibit immunosuppression and require frequent invasive procedures (such as mechanical ventilation, central venous catheterization, and blood purification), whereas Acinetobacter baumannii possesses a strong ability to form biofilms. By secreting extracellular polysaccharides, proteins, and other substances, it can form biofilms on the surface of respiratory mucosa or the inner walls of endotracheal tubes, enabling long-term colonization. When a patient’s immune function declines or the local respiratory microecology becomes imbalanced, colonized CRAB can breach the mucosal barrier and trigger infection. This highlights the clinical need to strictly control the indications for invasive procedures and to tailor treatment plans to individual patient conditions. Whenever clinically feasible, invasive devices such as central venous catheters and endotracheal tubes should be removed as early as possible to reduce iatrogenic exposure, thereby lowering the risk of CRAB infection and nosocomial transmission.

Among the 244 patients with CRAB infection included in this study, the elderly constituted the largest group, and the male-to-female ratio was approximately 2:1. This distribution pattern is highly consistent with the results of previously reported epidemiological studies on CRAB infection both domestically and internationally, indicating its broad applicability. This study grouped patients with CRAB infection based on survival outcomes (survival/death) and conducted a multivariate analysis of risk factors. The results showed that age and white blood cell count (P < 0.05) were independent risk factors for death in patients with CRAB infection. Age, as an unmodifiable risk factor, poses a risk because the immune function of elderly patients declines with age, significantly weakening their resistance to pathogens and making them more susceptible to colonization and infection. Additionally, elderly individuals often have multiple comorbidities, such as chronic obstructive pulmonary disease (COPD), diabetes, and coronary heart disease, which impair the body’s barrier functions and create conditions conducive to pathogen invasion and colonization. Elevated white blood cell (WBC) counts serve as a key indicator of the body’s inflammatory response; abnormally high levels often signal an intensification of systemic inflammation caused by drug-resistant bacterial infections. As a core component of the human immune system, white blood cells participate in immune defense by phagocytosing pathogens. However, the drug-resistant nature of these bacteria makes infections difficult to control, stimulating the bone marrow to continuously release white blood cells. This further exacerbates multi-organ dysfunction and increases the risk of death. This study also found that the use of platelets and cephalosporin antibiotics was an independent protective factor against mortality in patients with CRAB infections. Platelets not only participate in coagulation but also play a role in innate immunity. By binding to, encapsulating, and clearing pathogens, they inhibit bacterial invasion and spread, mitigate excessive inflammatory responses, and thereby improve clinical outcomes. Clinically, for high-risk populations with CRAB infection who exhibit persistently low platelet counts, dynamic monitoring of complete blood counts should be strengthened, and coagulation disorders and immune imbalances should be actively corrected to reduce the risk of mortality in critically ill patients. Although CRAB is inherently resistant to most cephalosporin antibiotics, early empirical use of cephalosporins can effectively control early infections caused by susceptible bacteria, reduce the inflammatory response, and delay disease progression. Additionally, patients receiving cephalosporin therapy typically have relatively mild baseline infections and limited exposure to carbapenems, which provides a certain degree of protective effect.This study found that the length of hospital stay in the mortality group was significantly shorter than that in the survival group (16 days vs. 26 days, P < 0.001), suggesting a possible association with early mortality bias. It is likely that some patients in the mortality group were in critical condition early on, with their condition rapidly deteriorating and leading to death shortly after admission, resulting in a shorter overall length of stay; in contrast, surviving patients, whose conditions were relatively stable or gradually improved following treatment, had longer periods of observation and treatment during their hospital stay. This suggests that length of hospital stay is easily influenced by patient survival outcomes and the rate of disease progression, making it difficult to use solely as an indicator of disease severity or treatment efficacy. Therefore, selection bias resulting from early mortality constitutes a limitation of this study. Future studies could optimize their designs by establishing admission time screening criteria and increasing sample sizes to further enhance the reliability of their conclusions.

In terms of gender analysis, there were significant statistical differences in albumin levels, age, and hemoglobin levels between male and female CRAB patients in the mortality group, while no differences were observed in other indicators, suggesting that prognostic factors for CRAB infection exhibit gender-specific characteristics. In this study, the age and hemoglobin levels at which female patients faced a risk of death were lower than those of male patients. This may be related to women’s higher baseline risk of anemia and malnutrition. Additionally, the decline in estrogen levels after menopause weakens immune function, and combined with a higher prevalence of osteoporosis and autoimmune diseases among women, these factors collectively reduce their ability to recover from infection. Based on these gender-specific pathophysiological mechanisms, clinicians should develop individualized intervention strategies for female patients with CRAB infection.

The antimicrobial susceptibility test results from this study indicate that 99.15% of the strains exhibited high resistance to both imipenem and meropenem. This finding reflects the high prevalence of CRAB in clinical settings. Notably, no strains resistant to polymyxin were identified in this study, suggesting that polymyxin remains an effective treatment option for CRAB infections in current clinical practice. However, the widespread use of polymyxin has led to the emergence and prevalence of resistant isolates, a phenomenon that has been confirmed in Spain, South Korea, Iran, the United States, and Brazil,²⁷ It may also be co-regulated by genetic transcriptional characteristics (such as the transcriptional status of the bap gene) and environmental factors, including medium nutrient concentration, incubation temperature, and surface roughness of the carrier material.

This study systematically analyzed resistance genes, efflux pump genes, and biofilm genes in 244 CRAB isolates. The results showed that carbapenem resistance is primarily driven by OXA-type carbapenemases, particularly blaOXA-23 (87.3%), This is consistent with global trends in CRAB, where blaOXA-23 is the most common carbapenemase gene to date. This may be related to the fact that blaOXA-23 can be inserted into both chromosomes and plasmids and is typically transmitted via plasmids.²⁸ This study also showed that nearly all strains (89.3%) carried blaOXA-51, a gene inherent to the Ab chromosome. Notably, four CRAB strains (1.6%) were detected in this study that carried the blaNDM gene, of which 2 strains carried both the blaOXA-23 and blaOXA-51 genes, while 1 strain co-carried the blaOXA-51 gene alone. NDM-type metal β-lactamases can hydrolyze almost all β -lactam antibiotics (including carbapenems and cephalosporins) and can be horizontally transmitted between different strains via plasmids. Their detection in our hospital indicates that CRAB has developed a composite resistance mechanism combining OXA-type enzymes with metal-binding enzymes. Although the current detection rate is low, vigilance is required regarding the risk of widespread transmission due to plasmid-mediated spread.

The efflux pump system is another important resistance mechanism in Ab, aside from β-lactamases. This study showed that the adeB and adeJ genes had the highest detection rates (85.7% and 87.3%, respectively), followed by adeS (84.0%), while the detection rate for adeR was 74.6%. Accumulated genomic studies have confirmed that the adeIJK efflux pump operon is highly conserved and represents a core genetic component ubiquitously distributed across the genus Acinetobacter.²⁹ However, in the present study, adeJ was detected in only 87.3% of the isolates, while adeG was undetectable in all strains, which was inconsistent with previous literature. This discrepancy is primarily attributable to methodological limitations. In this study, routine PCR was used for gene screening, and subtle sequence variations within the primer-binding regions of clinical isolates may inhibit amplification and cause false-negative results. Meanwhile, the interpretation threshold for positivity, partial genomic recombination or fragment deletion could also reduce the detection efficiency of target genes. Furthermore, geographical genetic characteristics of isolates from this single-center cohort may contribute to such deviations. Whole-genome sequencing will be adopted in future studies to achieve accurate verification.In clinical isolates of Acinetobacter baumannii, studies have shown that overexpression of any of the three major RND family efflux pumps (AdeABC, AdeFGH, and AdeIJK) is associated with antibiotic resistance in these strains. The expression of AdeABC is strictly regulated by the two-component regulatory system AdeR-AdeS.³⁰ When associated with various class D carbapenemase The correlation between adeB gene overexpression and the level of resistance in clinical isolates further supports the evidence that carbapenem efflux is mediated by the AdeABC system. Overexpression of AdeABC leads to significantly higher levels of carbapenem resistance, particularly resistance to imipenem and meropenem.³¹ The AdeIJK efflux pump is encoded by the AdeIJK operon and mediates the intrinsic resistance of Acinetobacter baumannii to β-lactam antibiotics.³² Studies have shown that the AdeIJK and AdeABC efflux pumps exhibit functional synergy and jointly participate in the active efflux of antimicrobial compounds such as tigecycline: Inactivating AdeIJK alone or overexpressing AdeABC reduces the minimum inhibitory concentration (MIC) of tigecycline by 3-fold and 8-fold, respectively; however, when both efflux pumps are inactivated simultaneously, the tigecycline MIC decreases significantly by 85-fold, fully confirming their synergistic effect in mediating tigecycline resistance.³²

Biofilm formation is one of the major characteristics underlying the colonization of Acinetobacter baumannii in healthcare settings and the development of chronic infections. It acts as a physical barrier to reduce antibiotic penetration, ultimately leading to treatment failure. The process of biofilm formation is complex and involves multiple key factors, including bacterial aggregation, collagen adhesion, fimbrial expression, and iron acquisition.³³ Among the 244 carbapenem-resistant Acinetobacter baumannii isolates in this study, biofilm-associated genes exhibited high detection rates, predominated by the bap, abaI, ompA, and csu gene families. These findings indicate that biofilm formation-related systems are widely distributed and highly prevalent among local CRAB strains, and may play an important role in bacterial adhesion, colonization, biofilm maturation, and the development of antimicrobial resistance. Most Acinetobacter baumannii strains encode and express the CsuA/BABCDE usher-chaperone fimbrial assembly system, which mediates biofilm formation of A. baumannii on abiotic surfaces.³⁴ Its expression is regulated by the BfmRS two-component regulatory system and is crucial for the formation and maintenance of biofilms.³⁵ The fimbriae encoded by the csuA/BABCDE gene cluster consist of two structural subassemblies. The short, slender tip fimbrial fiber encoded by csuE is anchored to the helical rod subassembly encoded by csuA/B. These components serve as surface recognition and adhesion sites and support fimbrial biogenesis, and their phenotypic expression is highly regulated by environmental conditions. Studies have demonstrated that the absence of CsuA/BABCDE-mediated fimbrial biosynthesis results in impaired adherence to abiotic plastic surfaces and defective biofilm formation in mutant strains.⁸ Acinetobacter baumannii also produces biofilm-associated protein, a class of large surface-exposed macromolecular proteins that share homology with the Bap protein initially identified in Staphylococcus aureus.³⁶ It participates in intercellular adhesion and supports the development and maturation of biofilms on various substrates. Combined with the biofilm formation assay results of CRAB isolates, most strains exhibited biofilm-producing ability. Weakly and moderately biofilm-forming strains accounted for up to 91.8% (224/244), and the detection rates of biofilm-associated genes in these strains all exceeded 85%. This indicates that the carriage of biofilm-associated genes may serve as a necessary prerequisite for biofilm formation. However, the magnitude of biofilm production is not determined merely by the detection of these genes; instead, it is co-regulated by transcriptional profiles (such as the mRNA expression level of the bap gene) and environmental factors, including nutrient concentration in the medium, incubation temperature, and surface roughness of substrates.

The present study showed that there was no statistically significant difference in the level of biofilm formation between the amikacin- and co-trimoxazole-resistant groups and the corresponding susceptible groups. Additionally, no significant correlation was observed between the resistance phenotypes of these two agents and biofilm production. These findings suggest that biofilm-forming capacity is not a major factor mediating resistance to amikacin and co-trimoxazole among the CRAB isolates in this cohort. It is traditionally believed that biofilms reduce bacterial susceptibility to antimicrobial agents by acting as a physical barrier to block drug penetration and by reducing bacterial metabolic activity, thereby making it easier for bacteria to develop resistance. However, this study did not observe such an association. This may be attributed to the high baseline level of multidrug resistance among the strains in this study, as they commonly carried multiple resistance elements, thereby weakening the additional effect of biofilms on resistance and making it difficult to detect a correlation. On the other hand, the fact that biofilm levels were similar across most strains and showed little variation may also have resulted in low correlation coefficients, making it difficult to achieve statistical significance. It should be noted that, given the prevalence of CRAB in this hospital, relying solely on anti-biofilm interventions is unlikely to reverse resistance to amikacin and co-trimoxazole. Clinical prevention and control efforts should not focus excessively on inhibiting biofilms; instead, they should prioritize strengthening hospital-acquired infection control, standardizing antimicrobial use, monitoring the spread of resistant clones, and rationally selecting susceptible drugs for combination therapy, thereby reducing the risk of CRAB colonization and infection. However, as this study was limited to genetic qualitative screening and did not further assess gene expression levels, the underlying mechanisms linking these factors remain unclear. Consequently, it is difficult to determine whether high biofilm-forming capacity is more likely to induce the development of resistance, nor can we rule out inherent differences in biofilm formation among resistant strains themselves.

This study has certain limitations. As a single-center retrospective study, its findings may not fully reflect the epidemiological characteristics of the strain across different regions and hospitals of varying levels. Due to study constraints, this study only used PCR to detect the presence of target genes; it did not perform mRNA expression analysis, MLST typing, or whole-genome sequencing. Consequently, it was unable to assess transcriptional activity, and the analysis of resistance mechanisms was relatively limited. Future studies could adopt a multicenter design to expand the sample size and combine gene expression analysis with molecular typing to further elucidate the epidemiological characteristics and mechanisms of local CRAB.

Conclusion

This study confirms that CRAB exhibits extremely high levels of resistance, which is primarily mediated by carbapenemases and may be synergized by factors such as the overexpression of efflux pumps and biofilm formation. Clinically, it is essential to prioritize the prevention of CRAB infections to avoid the development of multidrug resistance caused by the widespread use of antibiotics. At the same time, strict adherence to antimicrobial stewardship guidelines, enhanced resistance monitoring, and the implementation of standardized prevention and control measures are crucial for controlling CRAB-associated nosocomial infections.