Molecular determinants of antimicrobial resistance in Klebsiella pneumoniae isolates among geriatric patients in Chattogram, Bangladesh: a cross-sectional study

ABSTRACT

Klebsiella pneumoniae (KPN) infections pose heightened risks in the geriatric population due to weakened immunity, prevalent comorbidities, potential exposure in long-term care settings, and increased likelihood of antibiotic resistance (ABR). The study focused on the prevalence and antibiotic resistance of KPN infections, the presence of ABR genes in KPN, and the genomic characterization of KPN obtained from geriatric patients in Chattogram. A total of 543 specimens were collected from four hospitals in Chattogram, along with demographic data from hospital records. Genomic DNA was extracted from multi-drug-resistant (MDR) KPN, and the presence of ABR genes, bla_TEM-1, sul-1, aadB, bla_NDM-1, bla_SHV-11, and phoE was identified. To characterize the KPN genomes, two MDR KPN isolates were subjected to whole-genome sequencing (WGS), and the data were analyzed using bioinformatics tools to identify genomic determinants of ABR. KPN exhibited high resistance to ceftazidime (96%), cefuroxime (92%), and cefixime (83%), but sensitivity to colistin (79%) and amikacin (75%). MDR KPN was mostly detected in sputum (36%) and urine (27%) specimens, where the prevalence of ABR genes, blaTEM-1, sul1, aadB, blaNDM-1, and blaSHV-11 were 28.2%, 17%, 6.17%, 56%, and 48% of these strains, respectively. These genomes exhibited distinct profiles for sequence types, ST420 and ST277 in Kpn007 and Kpn016, respectively, and ABR genes (qnrS1, blaCTX-M-15, and blaSHV-27), virulence factors (ybt, iuc1, iro1), and contained both K (K20, K46) and O antigens (O1, O3b). MDR KPN in the geriatric population poses a serious health concern due to their increased vulnerability to infections and limited treatment options, requiring careful management.

IMPORTANCE

Multidrug resistance (MDR) and the hypervirulence nature of Klebsiella pneumoniae (KPN) in geriatric patients pose a critical health concern in nosocomial infections worldwide and result in high clinical complexity and mortality. The study investigated the factors for KPN infections and analyzed antimicrobial resistance profiles. More than 60% of Klebsiella pneumoniae isolates from geriatric patients were resistant to third- and fourth-generation cephalosporins, and most isolates carried bla_NDM-1 and bla_SHV-11 genes. Analyzing whole genomes of two KPNs, Kpn007 (ST277) was identified as a hypervirulent strain with aerobactin and yersinia siderophores, contributing to virulence, and Kpn016 (ST420) carried fluoroquinolone (qnrS1), ESBL (bla_CTX-M-15 and bla_SHV-27) resistance. Both genomes contained K antigens (K20 and K46) and O antigens (O1 and O3b).

INTRODUCTION

Klebsiella pneumoniae (KPN), the most medically relevant Klebsiella species, is responsible for a significant proportion of hospital-acquired urinary tract infections, pneumonia, septicemia, and soft-tissue infections, and is commonly found on hospital equipment (1). Additionally, KPN is much better suited to the hospital environment than other Enterobacteriaceae due to its superior ability to survive on hands and other surfaces and to spread quickly, causing nosocomial epidemics (2). KPN is mostly found in the gastrointestinal system, digestive system, and to a lesser extent in the nasopharynx in humans, where it can cause illness by entering the bloodstream or other organs (3). However, these colonization rates in hospitalized patients significantly rise in direct proportion to the number of days spent in the hospital and the use of antibiotics (4).

Klebsiella species can form colonies on mucosal surfaces without causing pathology. It is an opportunistic pathogen that causes hospital- and community-acquired infections, particularly among geriatric patients. Elderly patients have a weakened immune response and reduced functional reserve, making them more vulnerable to bacterial infections. Due to physiological changes, weakened immune responses, comorbidities, polypharmacy, and frequent hospitalizations, elderly individuals are highly susceptible to antibiotic-resistant K. pneumoniae infections (4, 5), which often lead to prolonged hospital stays, increased morbidity, and high mortality rates, making multi-drug-resistant (MDR) K. pneumoniae a serious public health concern. Elderly patients with carbapenem-resistant infections have significantly higher risks of adverse outcomes, including ICU care, respiratory failure, septic shock, and 90-day mortality (6).

Elderly patients infected with KPN in outdoor settings may face challenges in accessing timely medical care and may be at increased risk of exposure to environmental sources of the bacterium. In contrast, indoor elderly patients, particularly those residing in long-term care facilities or hospitals, may have a higher prevalence of KPN due to proximity to other infected individuals and the potential for transmission in healthcare settings, necessitating stringent infection control measures to mitigate spread and ensure effective treatment (6). While treatment options for elderly patients can be challenging to identify, the differences between them and younger individuals are minimal. One of these challenges is adjusting antibiotic dosing to account for age-related changes in pharmacodynamics and pharmacokinetics in the elderly (7). Drug absorption and compliance in the gastrointestinal tract, for example, are lower in patients with comorbidities (8). Additionally, comorbid patients typically take many drugs at the same time, emphasizing the importance of monitoring for potential drug interactions (9).

KPN exhibits high resistance to several antibiotics, including beta-lactams, fluoroquinolones, and aminoglycosides, and this resistance has been growing rapidly worldwide over the past several years due to excessive antibiotic use (10). The development of beta-lactamase enzymes that hydrolyze carbapenems is one of the main defense mechanisms used by Enterobacteriaceae against beta-lactam antibiotics (11). The primary mechanisms of resistance to aminoglycosides and fluoroquinolones include reduced uptake, poor drug absorption or accumulation in bacteria, and modification of enzymes that inactivate the antibiotic (12), especially mutations in the quinolone resistance-determining regions of the gyrA and parC genes (13). Moreover, cephalosporin resistance is frequently mediated by the production of β-lactamases, particularly extended-spectrum β-lactamases (ESBLs) and carbapenemases. Temoneria (TEM) and Klebsiella pneumoniae carbapenemase (KPC) enzymes are among the most clinically significant β-lactamases (14). TEM β-lactamases were initially narrow-spectrum but have evolved to hydrolyze extended-spectrum cephalosporins, reducing their efficacy (15). KPCs (class A carbapenemase) confer resistance to almost all β-lactam antibiotics, including carbapenems, which are often considered the last line of defense against MDR gram-negative bacterial infections. Furthermore, sul-1 encoding KPN interferes with the folic acid synthesis pathway by synthesizing sulfonamide-resistant dihydropteroate synthase enzyme, and aadB encodes an aminoglycoside adenylyl transferase, an enzyme that inactivates specific aminoglycoside antibiotics. NDM-1 is a class B group of metallo-beta-lactamase, and SHV-11 is a class A group of extended-spectrum beta-lactamase that are a major concern because of showing resistance to beta-lactam antibiotics and extended-spectrum cephalosporins. The dissemination of these resistance genes, often carried on plasmids, contributes to the rapid spread of resistance within healthcare settings (16).

The genetic composition and diversity of KPN contribute to its capacity to develop AMR and hypervirulence. Based on previous studies, the KPN genome ranges from 5 to 6 Mbp, with 5,000–5,800 protein-coding genes, including approximately 1,700 essential genes, as well as an extensive list of auxiliary genes involved in virulence, antimicrobial resistance, and environmental adaptation (17). Extensive genomic research into the comprehensive features and mechanisms of K. pneumoniae has led to its classification into specific sequence types (STs). Based on multilocus sequence typing (MLST), these categories represent a diverse range of distinct lineages, including ST11, ST14, ST15, ST17, ST23, ST29, ST45, ST66, ST101, ST147, ST149, ST231, ST258, ST307, ST380, ST627, and ST977 (18, 19). In addition, ST420 belongs to the CG420 lineage and is predominantly associated with ompK36, whereas ST277 represents an exception in ompK36 grouping (20). Among them, ST11, ST15, ST132, and ST43 were mostly common in MDR KPN strains found in Bangladesh (21, 22).

The burden of AMR is rising in South Asian countries due to excessive and irrational use of antibiotics for treating community-acquired and hospital-acquired infections, where E. coli, K. pneumoniae, S. aureus, and A. baumannii are the leading antimicrobial-resistant microorganisms (ARMs) across all age groups (23–25). Furthermore, K. pneumoniae, S. typhi, and E. coli are the predominant ARMs in geriatric patients with pneumonia, acute respiratory infections, urinary tract infections, and sepsis (23). However, ciprofloxacin-resistant S. typhi/S. paratyphi were the prevalent ARMs in South and Southeast Asian countries in 2014, according to WHO reports (24). In addition, a large proportion of patients in Bangladesh with extended-spectrum cephalosporin-resistant Enterobacterales, and the prevalence of MDR E. coli and K. pneumoniae, showed difficulty in treating resistance phenotypes among community and hospital patients in 2019 (25, 26). In elderly patients with bacteremia in the ICU in Bangladesh, Staphylococcus spp., E. coli, and K. pneumoniae were highly resistant to ceftriaxone (72.13%) (5, 27).

This study aimed to investigate the prevalence and antibiotic susceptibility of KPN in Chattogram by analyzing clinical samples and demographic data of geriatric patients. This study also checked the prevalence of several resistance-associated determinants in KPN, blaTEM-1, phoE, sul-1, blaNDM-1, blaSHV-11, and blaKPC. Furthermore, whole-genome sequencing was used to identify genetic determinants associated with antimicrobial resistance in selected MDR K. pneumoniae strains from geriatric patients.

MATERIALS AND METHODS

Study setting and clinical data collection

This study was conducted at Chittagong Medical College Hospital, Chattogram Maa O Shishu Hospital, Chevron Clinical Laboratory (Pte.) Ltd., and Epic Health Care Ltd between April 2023 and May 2024. Clinical samples were collected from 543 geriatric patients in this molecular and epidemiological investigation. The study included samples from patients aged >60 years (according to the WHO guidelines) who were either outpatients or inpatients. Sampling was continued from clinical specimens, mainly including blood, urine, tracheal aspirate, throat swab, wound swab, sputum, and pus.

Identification and selection of KPN strains

Clinical specimens were initially enriched in Luria-Bertani (HiMedia) broth and incubated at 37°C for 18 h. Following that, the samples were cultured on MacConkey agar media (HiMedia Laboratories, India) and incubated overnight at 37°C. Large, mucoid, and lactose-fermenting single colonies were selected for biochemical testing, including Triple Sugar Iron (TSI) and Simmons’s Citrate tests, which were performed to inferentially detect Klebsiella pneumoniae (KPN) (12), and the large, mucoid, and lactose-fermenting single colonies confirmed Klebsiella pneumoniae isolates were stored in skimmed milk at −20°C.

Antibiotic susceptibility assay

Antibiotic susceptibility testing of the selected strains was performed using the Kirby-Bauer disc diffusion method. The susceptibility testing results were interpreted according to the criteria recommended by the Clinical and Laboratory Standards Institute (28). K. pneumoniae ATCC70603 was used as a quality control strain for antimicrobial susceptibility testing (29). Clinically used 13 antibiotics documented in the study were cotrimoxazole (25 µg), ciprofloxacin (5 µg), gentamicin (10 µg), ceftriaxone (25 µg), cefixime (5 µg), colistin (10 µg), amikacin (30 µg), cefuroxime (30 µg), tigecycline (15 µg), nitrofurantoin (300 µg), cefepime (30 µg), levofloxacin (5 µg), and ceftazidime (30µg).

Screening of phoE, bla_TEM-1, sul1, aadB, bla_NDM-1, bla_KPC, and bla_SHV-11 in KPN strains

Genomic DNA was extracted using the boiling method: large, mucoid, and lactose-fermenting single colonies were picked with a loop from bacterial cultures, suspended in 1,000 µL nuclease-free water, and centrifuged at 10,000 rpm for 10 min. After discarding the supernatant, the pellet was resuspended with nuclease-free water and heated at 95°C for 10 min, followed by a cold shock by immediately transferring it to −20°C for 30 min. The suspension was then centrifuged at 10,000 rpm for 10 min, and the supernatant containing DNA was collected and used as the PCR template. The plasmid DNA was extracted using Favorgen Plasmid DNA Extraction Mini Kit according to the manufacturer’s protocol (29, 30). Isolates were identified as Klebsiella pneumoniae through biochemical testing, and the presence of the phoE gene was confirmed in all isolates by PCR amplification (16). Multidrug-resistant genes, bla_TEM-1, sul1, aadB, and bla_NDM-1 (31), in plasmid DNA and bla_SHV-11 in bacterial genomic DNA were detected using sequence-specific target primers (Table S1).

Whole genome sequencing

Among all MDR isolates, the two MDR KPN isolates were randomly selected for whole-genome sequencing and processed for library preparation after genomic DNA extraction using a commercial DNA extraction kit (QIAamp DNA extraction kit, Qiagen, Germany) according to the manufacturer’s instructions. Immediately after this step, the DNA was subjected to library preparation using the NEBNext Ultra II FS DNA library prep kit (Illumina, San Diego, CA) following the manufacturer’s guidelines, and the library size was selected with AMPure XP beads (BECKMAN COULTER) (32). The final library was prepared and loaded on the Illumina iSeq100 by a paired-end 300-cycle protocol (33).

Quality control, trimming, assembly, and annotation

Different software was used for analysis in default settings. FASTQC v.0.11.9 (34) and Trimmomatic v0.40 (35) were used for raw sequence quality checks and low-quality read and adapter region filtering, respectively. Then, SPAdes 3.14.1 was used for the de novo assembly, followed by QUAST v5.2, which was run for genome statistics (36, 37). The CBI Prokaryotic Genome Annotation Pipeline (PGAP) was run for annotation (38). Then, the taxonomy and identification of species and associated AMR-virulence factors were determined using Kraken2 and KLEBRATE (39, 40). The Rapid Annotation using Subsystems Technology (RAST) server V.2.0 was used to identify protein-coding and RNA genes (tRNA and rRNA) from assembled genomes, assign functions, predict subsystems, and build metabolic networks. The SEED analysis was done using the RAST database (41).

Statistical analysis

Statistical analyses were conducted in GraphPad Prism 9. A Sankey plot was made using the networkD3 R package to visualize relationships in the data set. Antibiotic-resistant patterns (MDR, XDR, and DDR) were categorized, and the mean hospital stay and cost were determined using IBM SPSS Statistics Version 27 (IBM Corp., Armonk, NY, USA). Finally, R was used for linear regression to investigate correlations, and the ggplot2 package was used to present the results.

RESULTS

Demographic features of study populations

In the study, Klebsiella spp. infections were identified and cultured from clinical specimens of 543 geriatric patients at three hospitals in Chattogram. All samples were selected through a nonrandomized sampling procedure. All the patients in the entire study population were geriatric, with an average age of 71 years. Out of them, 57% were male, and 43% were female. Additionally, 44% of patients were hospitalized, while the remaining 56% were non-hospitalized.

Patients living in urban areas (61%) had a higher prevalence of Klebsiella infections than those from rural areas (39%) (Table 1). Clinical characteristics and admission history were analyzed. Most patients had respiratory tract infections (36%), followed by urinary tract infections (27%). Among patients for whom hospital stay length and patient type were available, we found that 56% of infections were community-acquired among outdoor patients, and the remaining 44% were hospital-acquired among indoor patients (Table 1).

TABLE 1.

Demographic and clinical characteristics of Klebsiella infections in the study population

Variable	Prevalence (%) (n = 543)
Age	71.39 ± 7.54a
Gender
Female	43%
Male	57%
Sample
Blood	1.70%
Pus	9.40%
Sputum	36%
Throat swab	2.80%
Tracheal aspirate	18%
Urine	27%
Wound swab	5.00%
Patients type
Indoor	44%
Outdoor	56%
Area
Rural	39%
Urban	61%
Status
Double-drug resistant (DDR)	25%
Multi-drug resistant (MDR)	29%
Single-drug resistant (SDR)	27%
Sensitive to all drugs	19%

^a Mean ± SD; %.

Antibiotic susceptibility of Klebsiella pneumoniae isolates

Analyzing the proportion of Klebsiella pneumoniae isolates susceptible to each of the 13 tested antibiotics, we found that more than 60% of isolates were resistant to ceftazidime (92%), cefuroxime (89%), cefixime (82%), ceftriaxone (68%), and cefepime (61%) (Fig. 1A). On the other hand, more than 70% of the isolates were sensitive to amikacin, colistin, tigecycline, and gentamicin (Fig. 1A). Overall, 29% of KPN isolates were MDR, 25% were DDR, and 27% were SDR (Table 1). Among outpatients, K. pneumoniae was most prevalent in sputum (22.1%) and urine (18.2%). In contrast, the most common sources of infection among inpatients were tracheal aspirates (15.5%) and sputum (13.8%) (Fig. 1B). The Sankey plot shows that MDR isolates represented the most prevalent resistance category across nearly all sample sources. Sputum and tracheal aspirates served as the primary reservoirs for these resistant strains, contributing the highest volume of isolates to both the MDR and double-drug-resistant (DDR) pools. While pus and wound swabs contributed moderately to the MDR population, blood isolates, though fewer in number, were exclusively associated with MDR and SDR profiles (Fig. 1B).

Fig 1.

Antimicrobial susceptibility profiles and distribution of clinical specimens and resistance categories. (A) Antimicrobial susceptibility testing results for the 13 tested antibiotics by disc diffusion methods. (B) Sankey diagram visualizing the association between patient type (indoor/outdoor), clinical specimen source, and antibiotic resistance classification. The width of the bands represents the proportional volume of isolates.

Figure 2 shows a positive relationship between length of stay and treatment cost, more evident for MDR infections than for DDR infections. MDR patients have a steeper, more dispersed relationship between cost and stay, suggesting higher and more dispersed resource allocation, whereas for DDR infections, the relationship is moderate and narrow. In practice, MDR infections have a significantly higher financial burden. This can be justified by the fact that 28.7% of the admitted cases belonged to the MDR group, with a median length of hospital stay of 10 days and a median treatment cost of 478 USD, followed by DDR infections, which accounted for 24.9% of cases, with a median hospital stay of 6 days and a median treatment cost of 420 USD.

Fig 2.

Correlation between treatment cost and length of hospital stay across different antibiotic resistance profiles.

Identification of phoE, bla_TEM-1, sul-1, aadB, bla_NDM-1, and bla_KPC gene in KPN isolates

A total of 100 most resistant MDR KPN isolates were selected for molecular investigation, in which all samples contained the phoE gene, with a size of 142 bp on a 1.2% agarose gel (Fig. 3A), and these 100 isolates were screened for six related AMR genes, including blaKPC, blaTEM-1, sul1, aadB, blaNDM-1, and blaSHV-11. Of the isolates, 28.2% carried the blaTEM-1 gene, as evidenced by an 861-bp band (Fig. 3). We did not find any blaKPC-positive KPN isolates in our study. Furthermore, 17% of the isolates were positive for the sul1 gene, and aadB was detected in only 6.17% of isolates. Conversely, the blaNDM-1 gene, confirmed at 631 bp on a 1.2% agarose gel, was detected in the highest proportion of isolates (56%), followed by blaSHV-11 (48%) at 858 bp.

Fig 3.

Molecular identification of the phoE gene and various antibiotic resistance determinants in K. pneumoniae isolates. Representative agarose gel electrophoresis images showing (A) phoE gene, (B) bla_TEM-1 gene, (C) sul1 gene, (D) aadB gene, (E) bla_NDM-1 gene, and (F) bla_SHV-11 gene amplification. The product size of the phoE gene was 142 bp, and the product sizes of the other antibiotic resistance genes—bla_TEM-1, sul1, aadB, bla_NDM-1, and bla_SHV-11—were 861, 436, 534, 621, and 858 bp, respectively. P denotes positive control, N for negative control, and a ladder was used as a reference to compare the bp of the target genes.

Assembly statistics

After molecular screening, two MDR KPN isolates, Kpn007 and Kpn016, were selected for WGS sequencing from the sputum specimen, the most prevalent sample type in this study. The WGS analysis further confirmed that the isolates were Klebsiella pneumoniae. Analyzing the sequencing data, it was found that the estimated genome sizes are 5,442,638 and 5,565,244 bp for Kpn007 and Kpn016, assembled into 63 and 93 contigs, respectively, with GC contents of 57.2% and 57.1%, respectively. In addition, the number of protein-coding sequences within the genomes is about 5,137 and 5,280, with 71 and 79 non-coding RNAs (including tRNA and rRNA). The N50s of the genomes are 209,534 (Kpn007) and 240,835 bp (Kpn016), while the L50 is 8 for both genomes (Table S2).

Gene prediction from KPN genomes

Phenotypic antimicrobial susceptibility testing of KPN isolates revealed that both strains have acquired resistance to a large proportion of clinically important antibiotics (Fig. 1A). On the other hand, several resistance genes were identified in the genomes of the Kpn007 and Kpn016 strains using the Kleborate tool, where the sequence types for Kpn007 and Kpn016 were found to be ST420 and ST277, respectively. The Kpn016 genome was identified as an MDR strain due to the presence of resistance genes qnrS1, blaCTX-M-15, and blaSHV-27 on the chromosome, along with K46 and O3b, which are associated with virulence and disease defense in humans. On the other hand, the Kpn007 genome has K20 and O1 antigens identified as hypervirulent because of having the ybt 9 gene in the genome, which is responsible for iron uptake, included in the yersiniabactin (Ybt) iron uptake system, and the ybt gene is most prevalent in the mobile genetic element, ICEKp3, found in KPN. In addition, the iuc1 gene is responsible for aerobactin synthesis, along with the iro1 gene, which encodes salmochelin siderophores found in hypervirulent KPN, which is responsible for iron acquisition in the bacterial genome. The wzi95 (Kpn007) and wzi97 (Kpn016) genes found in both are responsible for membrane transporter synthesis (Table S2). Moreover, these genes were annotated and categorized into 573 subsystems via the RAST server (24).

Most of the annotated genes found from both genomes were functioning in carbohydrates (837 in Kpn007; 888 in Kpn016), amino acids and derivatives (560; 547), cofactors, vitamins, prosthetic groups, and pigments (367; 365), protein metabolisms (288; 277), RNA metabolisms (253; 251), membrane transport (229; 264), cell wall and capsule (214; 213), and iron acquisition and metabolism (108; 74), which are crucial for bacterial survival and adaptation. In addition, both genomes carry 140 and 145 genes responsible for virulence, disease, and defense causing lethal effects in humans (Fig. 4 and Table S3).

Fig 4.

An overview of RAST subsystem category distribution annotation pie chart and subsystem feature count of annotated genes from the Kpn007 and Kpn016 genomes. Here, the number of genes for each category was represented in parentheses.

DISCUSSION

Klebsiella pneumoniae (KPN) is the second most prevalent cause of bloodstream infection in South Asia, including Bangladesh (42). The rise in multidrug resistance (MDR) amplifies the severity of morbidity and mortality associated with KPN infections in the elderly population. The investigation aimed to examine the frequency of KPN infections among geriatric patients in Chattogram, analyze antimicrobial resistance (AMR) patterns, and identify resistance genes and related virulence factors through whole-genome sequencing.

We reviewed epidemiological data for study patients to determine the age and sex distribution of KPN-infected individuals among hospitalized and outpatient patients. The demographic analysis revealed a higher susceptibility among males (57%). The higher incidence of KPN infection in males compared with females may vary due to a combination of behavioral, physiological, and immunological factors (43). These findings align with previous studies in Bangladesh, where the male patients are more likely to have higher exposure to healthcare facilities because of infections, underlying comorbidities like cardiovascular diseases, or elevated exposure to risk behaviors and repeated antibiotic use, contributing to the higher prevalence of antimicrobial resistance (25, 44). Patients living in urban areas (61%) had a higher prevalence of Klebsiella infection than those in rural areas (39%) due to increased urbanization and poverty. Furthermore, people are sharing their environments with urban terrestrial mammals, which are a common source of bacterial infection. It was found in one previous study that three serotypes of hypervirulent Kpn, for instance, K5, K20, and K57, were detected in community-acquired human infections, and these strains had potential transmitted sequence types of ST 23, ST35, and ST37 among them (45). Additionally, the transmission of mobile genetic elements in Kpn-positive isolates derived from urban people was highly prevalent compared to those from rural people in the farming sector, due to increased antibiotic use, self-medication, and non-prescribed antibiotic use, and human-created pollution at an accelerated rate (46). Furthermore, the higher population density and frequent hospital visits in urban settings may facilitate the transmission and spread of antimicrobial-resistant K. pneumoniae strains (47). In terms of overall frequency, KPN infections were most common in the intensive care unit (ICU), medicine wards, and adult surgery wards. Sputum (36%), followed by urine (27%) and tracheal aspirate (18%), was the most common source of infections (Table 1). Similar observations regarding specimen sources have also been identified in ICU units of the Surgery, Gynecology and Obstetrics, and geriatric sources of the hospital in China (48).

A similar study was conducted in Chattogram on patients across different age groups, in which KPN infections in urine (39.9%) were detected in patients under 15 years (49). Moreover, the infection rates from urine (18.2%) and sputum (22.1%) were observed among outdoor patients. On the other hand, tracheal aspirate was the source of infections among indoor patients (18.8%) (Fig. 1B). This may explain the high incidence of lung infections, cough, breathing difficulties, and urinary tract infections in the majority of patients, originating from the community or acquired in hospital settings. As a result, they are either admitted to the hospital for treatment or prescribed various medicines. Due to mismanagement or the dissemination of MDR bacterial strains in hospital settings, the treatment costs for patients infected with MDR KPN strains have been a global burden (50). In our study, patients with blood infections or bacteremia were uncommon in the study population. These results may have stemmed from the low usage of blood cultures in Bangladesh or from the potential use or administration of antibiotics prior to sample collection (51). KPN is a clinically important nosocomial pathogen that has developed resistance to antibiotics, particularly carbapenems, making KPN infections challenging to treat. The current study on KPN and its antibiotic resistance pattern shows that KPN isolates have developed resistance to second-generation and even third-generation cephalosporins, e.g., ceftazidime (92%), cefuroxime (89%), cefixime (82%), ceftriaxone (68%), and cefepime (61%), and are sensitive to colistin (82%), amikacin (78%), tigecycline (75%), and gentamicin (75%) (Fig. 1A). In a previous study, KPN isolates were resistant to cefepime, cefixime, and azithromycin and sensitive to amikacin, nitrofurantoin among neonates and adolescents (50). The study used molecular analysis to focus on KPN isolates and identified the phoE gene in all isolates. The investigation revealed the prevalence of beta-lactamase genes blaTEM-1, blaNDM-1, and blaSHV-11, indicating the intricate nature of these genes and their role in conferring multi-drug resistance. The study also revealed the aadB gene, conferring resistance to aminoglycosides, and the sul-1 gene, conferring resistance to sulfonamides, which aligns with the previous studies conducted in Bangladesh. KPN encoding TEM-1, SHV variants, sul-1, and NDM-1 were found in clinical and environmental samples (canal water) and detected by whole-genome analysis and molecular experiments (52–54). Moreover, the samples studied tested negative for the blaKPC-2 gene. The gene encodes the KPC enzyme, which hydrolyzes carbapenems and causes hospital-acquired infections via plasmid-mediated horizontal gene transfer (55).

Analyzing whole genomes of KPN, we identified ST420 and ST277 in Kpn007 and Kpn016, respectively, with ST420 associated with multidrug-resistant KPN strains that contribute to the spread of antibiotic-resistant genes or transposable elements through horizontal gene transfer among bacterial populations, specifically targeting the carbapenem class of antibiotics (56). However, Kpn016, identified as ST277, is an MDR strain that carries the fluoroquinolone resistance gene qnrS1, which confers resistance to fluoroquinolones, e.g., ciprofloxacin and levofloxacin, and also harbors extended-spectrum beta-lactamase and virulence factors K46 and O3b (Table S2) (57). In addition, the strain carries the blaCTX-M-15 and blaSHV-27 genes, which confer resistance to beta-lactam antibiotics and contribute to the rapid global spread of high-risk clones such as ST11 in KPN (58). On the other hand, Kpn007 is a hypervirulent strain that carries the genes ybt9 and iuc1, which encode the synthesis of the siderophores yersiniabactin and aerobactin and the iron uptake systems (Table S2). Additionally, the maximum number of genes predicted in both genomes by the RAST server were involved in carbohydrates, amino acids and derivatives, cofactors, vitamins, prosthetic groups, cell wall and capsule synthesis, and iron uptake and acquisition systems, which are necessary for bacterial survival (Fig. 4).

According to our study (Fig. 2), MDR infections accounted for the highest proportion of cases (28.7%) and were associated with the longest hospital stay, expending a high amount of money (478 USD), indicating that the increase in treatment cost and duration of hospitalization is strongly associated with the degree of antimicrobial resistance, while SDR or DDR patients stayed for a shorter duration in the hospital with lower costs. These findings are consistent with studies showing that infections caused by MDR organisms, including MRSA, are associated with higher hospitalization costs and longer lengths of stay than those caused by susceptible organisms (59, 60). Similar observations have also been reported in systematic reviews, which showed that resistant infections incur additional treatment costs of several thousand US dollars and extended hospital stays (61, 62).

However, the study has some limitations. The sample size was limited, with isolates being collected from only four hospitals in Chattogram. A larger sample size would yield a larger dataset of genomic data, providing a more thorough understanding of bacterial genomes, AMR, and transmission patterns.

Implementing robust infection control strategies is critical to mitigating the dissemination of high-risk K. pneumoniae sequence types within the population. Future efforts should prioritize establishing a national antimicrobial resistance (AMR) surveillance network in Bangladesh to monitor longitudinal shifts in resistance genes and carbapenem susceptibility. Besides, future studies with large sample sizes are required to understand the devastating impact of antibiotic resistance nationwide and to take cautious measures in the use of antibiotics.

Conclusion

This study investigated ESBL-producing K. pneumoniae isolates from geriatric patients in southern Bangladesh. The analysis allowed us to pinpoint the earliest occurrences of blaTEM-1, blaNDM-1, blaSHV-11, sul-1, and aadB, which encode β-lactamases and antibiotic resistance. The risk of bacterial infections among the geriatric population will increase significantly if specific Klebsiella strains resistant to antibiotics become more prevalent in the environment and hospital settings. This might intensify the persistence of the entire antibiotic resistance threat through horizontal and vertical gene transfer. To develop and implement plans to limit the abuse of antibiotics on a large scale and to provide alternative treatment options in cases of resistance, ESBL-producing organisms must undergo rigorous screening for TEM-1, KPC, and other antibiotic resistance genes (SHV-11 and NDM-1) in Bangladeshi hospitals and community settings.

DATA AVAILABILITY

The data used to support the findings of this study are included within the article. The Whole Genome Sequences of two KPN have been deposited in GenBank under the accession JBBMLU000000000.1 and JBBMLQ000000000.1. The Illumina Sequence reads are available in the NCBI Sequence Reads Archive (SRA) under accession numbers SRR25920011 and SRR25920015.

ETHICS APPROVAL

This study protocol was approved by the Ethical Review Committee of Chittagong Medical College (59.27.0000.013.19.PG.2023.009/273). The study protocol was explained to all participants in their local language (Bengali), and written informed consent was obtained before the collection of clinical samples and data.

SUPPLEMENTAL MATERIAL

The following material is available online at https://doi.org/10.1128/spectrum.00145-26.

Table S1. spectrum.00145-26-s0001.xlsx.

Primers and PCR conditions for the amplification of selected K. pneumoniae genes.

Table S2. spectrum.00145-26-s0002.xlsx.

Genomic information and Kleborate results of KPN.

Table S3. spectrum.00145-26-s0003.xlsx.

List of predicted genes and their functions_Kpn016 genome.

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