Genomic and Molecular Analysis of Multidrug-Resistant Gram-Negative Bacteria Causing Bloodstream Infections in Hospitalized Patients

Genomic and Molecular Analysis of Multidrug-Resistant Gram-Negative Bacteria Causing Bloodstream Infections in Hospitalized Patients | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Genomic and Molecular Analysis of Multidrug-Resistant Gram-Negative Bacteria Causing Bloodstream Infections in Hospitalized Patients Fatemeh Ramazan Yazdi, Mohammad Sadegh Rezai, Somayeh Sheidaei, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8106566/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Bloodstream infections caused by multidrug-resistant and extensively drug-resistant Gram-negative bacteria represent a major global health concern, particularly among hospitalized and critically ill patients. This study aimed to characterize the molecular profiles, antimicrobial resistance patterns, and phylogenetic relationships of Gram-negative isolates obtained from bloodstream infections in hospitalized patients. A cross-sectional study was conducted between September 2024 and May 2025. Bacterial identification and antimicrobial susceptibility testing were performed using the BD Phoenix M50 and BD BACTEC FX40 automated systems, and extended-spectrum β-lactamase production was confirmed by the Combined Disk Test. Resistance genes, including bla SHV , bla CTX−M , bla IMP , bla NDM , bla TEM , OqxA, OqxB, aac(1)A , and aac(1)B were detected via PCR, and the RpoB gene was sequenced for phylogenetic analysis. Among 30 isolates, Klebsiella pneumoniae (70%) was the predominant species. The highest resistance was observed to Ceftriaxone (96.7%), while Tigecycline showed the greatest activity (66.7% susceptibility). The bla SHV and bla IMP genes were detected in all isolates, and OqxB (93.3%) and bla CTX−M (80%) were highly prevalent. Phylogenetic analysis revealed close clustering of clinical isolates with the reference XDR strain K. pneumoniae CP008827.1, suggesting intra-hospital transmission. These findings highlight the urgent need for continuous molecular surveillance, strict infection control, and rational antibiotic stewardship programs. Health sciences/Diseases Health sciences/Medical research Biological sciences/Microbiology Biological sciences/Molecular biology Bloodstream infections Klebsiella pneumoniae Extensively Drug-Resistant Phoenix tanique PCR Hospital-Acquired Infections Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Bloodstream infections (BSIs) are among the most severe healthcare-associated infections, linked to high mortality, significant clinical complications, and a considerable economic impact. In 2019, BSIs were estimated to cause approximately 2.91 million deaths worldwide, with Gram-negative bacteria responsible for more than 51% of cases. The dominance of Gram-negative pathogens in BSIs is mainly due to their intrinsic structural defenses, including an outer membrane rich in lipopolysaccharides, an enhanced ability for horizontal gene transfer and acquisition of antimicrobial resistance genes, the capacity to survive and colonize indwelling medical devices, and the expression of potent virulence factors that contribute to systemic infections and sepsis 1 . BSIs are especially common in ICU patients, the elderly, and immunocompromised individuals 2 . Epidemiological studies show that E. coli is the leading Gram-negative pathogen in BSIs, accounting for about 49.9% of Gram-negative isolates. Other prevalent Gram-negative bacteria include Klebsiella spp. (21%), Enterobacter spp. (7%), Proteus mirabilis (6.1%), P. aeruginosa (5.6%), and S. marcescens (3.3%). The prevalence of these pathogens is notably higher among ICU patients and those with central venous catheters. Additional risk factors for Gram-negative BSIs include prolonged antibiotic use, urinary or gastrointestinal surgeries, and extended hospital stays 3 – 4 . The emergence and dissemination of multidrug-resistant (MDR) Gram-negative bacteria in recent years have posed major challenges for the treatment of bloodstream infections (BSIs). According to a 2017 World Health Organization (WHO) report, carbapenem-resistant Gram-negative pathogens including A. baumannii and P. aeruginosa as well as extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae, were classified as critical-priority pathogens. These bacteria acquire resistance to a wide range of antibiotics, particularly carbapenems, through mechanisms such as β-lactamase enzyme production, efflux pump overexpression, porin loss, and mutations in drug targets 5 . ESBL-producing strains are highly resistant to beta-lactams and aztreonam, while generally remaining susceptible to carbapenems. In contrast, carbapenem-resistant strains often exhibit reduced OprD porin expression and produce class A (KPC, GES), metallo-β-lactamases ( IMP -NDM -GIM - FIM -SPM -VIM ), and class D ( OXA-48 ) enzymes, conferring high-level carbapenem resistance. MDR and extensively drug-resistant (XDR) strains additionally display cephalosporin resistance via class C β-lactamases ( AmpC blaSHV blaTEM blaCTX-M ) and quinolone resistance mediated by DNA gyrase/topoisomerase IV mutations and plasmid-encoded efflux pumps ( OqxA, OqxB ) 6 – 9 . In patients with bloodstream infections (BSIs), the challenges posed by antimicrobial resistance highlight the critical importance of rapid and accurate diagnosis with high sensitivity and specificity. Traditional blood culture and microbiological methods, however, have demonstrated limited diagnostic yield. This shortcoming contributes to higher rates of hospital-acquired infections, prolonged hospital stays, increased treatment costs, and mortality rates that can reach 50–60% 10 . Therefore, it is essential to integrate automated culture systems, evaluate the phenotypic and genotypic correlations of antibiotic resistance, and implement effective infection control measures to curb the spread of resistant Gram-negative pathogens. The current study aims to characterize the genotypes and sequence multidrug-resistant Gram-negative isolates confirmed by the fully automated Phoenix M50 and BD BACTEC FX40 systems in hospitalized patients with BSIs at Bou-Ali Sina Hospital in Sari, Iran, during the period from 2024 to 2025. Results Demographic information of the pertains with BSIs In this study, blood samples were obtained from 30 hospitalized patients at Bou Ali Sina Hospital in Sari. The median age of the patients was 31 years (interquartile range [IQR]: 5–72). The youngest patient was 35 days old, and the oldest was 92 years. Among the study population, 66.7% were male and 33.3% were female (Table 2 ). Approximately 47% of the patients were admitted to the ICU. Microbiological analysis revealed that 70% of the isolates were identified as K. pneumoniae (Fig. 1 ). Table 2 The demographic data of patients Number Percent Age =10 years 21 70 Sex Male 20 66.7 Female 10 33.3 Unit ICU 14 46.7 Emergency 6 20 PICU 3 10 pediatric 2 6.7 Oncology 1 3.3 NICU 2 6.6 ENT 1 3.3 Pediatric 1 3.3 Bacteria K. pneumoniae 21 70 A. baumannii 5 16.7 P. aeruginosa 3 10 E. coli 1 3.3 Antimicrobial Susceptibility Testing of Clinical Isolates Using Phoenix M50 Automated antimicrobial susceptibility testing of clinical isolates using the Phoenix M50 system demonstrated that among 30 bacterial isolates recovered from the blood samples of patients diagnosed with sepsis, the highest level of antibiotic resistance was observed against Ceftriaxone, with 96.7% of isolates exhibiting resistance. This was followed by Ampicillin, Cefuroxime, and Cefazolin, each showing a 90% resistance rate. In contrast, the lowest resistance was observed for Tigecycline, with only 33.3% of isolates displaying resistance (Fig. 2 ). ESBL Detection in Gram-Negative Isolates Using the Combined Disk Test (CDT) In the phenotypic confirmatory test (Combined Disk Test; CDT) for the detection of ESBL-producing strains, a total of 30 isolates were examined. The results indicated that 76.7% of the isolates were ESBL-negative, while 23.3% were identified as ESBL-positive. Detection of resistance genes Figure 3 , elevated lights the frequency of antibiotic resistance genes in 15 clinical isolates of K. pneumoniae . Notably, bla SHV and bla IMP were identified in 100% of the isolates, indicating their widespread presence. Moreover, the efflux pump gene OqxB was detected in 93.33%, and the extended-spectrum β-lactamase (ESBL) gene blaCTX-M was present in 80%. These findings underscore of multidrug resistance among these strains. Figure 4 , shows the relation between the frequency of resistance genes and susceptibility to antibiotics. In k. pneumonia isolates (N = 15), no significant relationship was identified between resistance genes and antibiotic resistance. Phylogenetic analyses The three clinical isolates (Fig. 5 ), 289_RPO-F (ICU), 727_RPO-F (Oncology), and 913_RPO-F (PICU), cluster closely together. Within the same cluster, an NCBI reference isolate (CP008827.1) is located near the node encompassing these isolates. The other reference isolate (CP003200.1) is phylogenetically distant from this cluster and appears as an outgroup relative to the main group. Branch lengths indicate that the genetic distance between the clinical isolates and CP008827.1 is low, reflecting minimal genetic divergence, whereas CP003200.1 exhibits a considerably greater genetic distance. The close clustering of 289 and 727, followed by 913, indicates elevated genetic similarity among these three isolates, suggesting a likely common lineage or closely related sublineage. The tree shows that 289 and 727 are probably the most closely related, while 913 is slightly more distant but still within the same cluster. Proximity to CP008827.1, an NCBI isolate previously reported as XDR, strongly suggests that our isolates may belong to a known XDR lineage or, at a minimum, carry similar resistance genes. The large distance to CP003200.1 indicates that this reference isolate represents a different lineage, likely with distinct resistance motifs or genetic background. Discussion The results of the current study indicate that Klebsiella pneumoniae is the most common cause of bloodstream infections (BSIs) among hospitalized patients. This is followed by A. baumannii, P. aeruginosa , and E. coli . These findings align with several national and international studies that have identified K. pneumoniae and A. baumannii as significant multidrug-resistant pathogens responsible for BSIs 17 – 18 . The high prevalence of K. pneumoniae and A. baumannii observed in this study may be due to their remarkable ability to acquire and spread antimicrobial resistance genes, particularly those that encode Extended-Spectrum Beta-Lactamases and carbapenemases 19 – 20 . The extensive use of broad-spectrum antibiotics in hospitals, particularly in ICUs, likely contributes to the selection and persistence of these multidrug-resistant strains 21 . Moreover, inadequate infection control measures and environmental contamination may facilitate the transmission of these pathogens among vulnerable patients 22 , In contrast, the relatively lower prevalence of E. coli and P. aeruginosa might be attributed to differences in patient populations, underlying comorbidities, or variations in local antibiotic stewardship policies 23 – 24 , In our study in analysis of antibiotic resistance patterns, the highest resistance rates were observed against ceftriaxone, ampicillin, cefuroxime, and cefazolin, respectively. This elevated level of resistance to cephalosporins and penicillins indicates the widespread presence of ESBL–producing strains. Tigecycline, with only 33.3% resistance, was identified as the most effective antibiotic. These findings are consistent with the reports of Bhargava et al., (2019) 17 , and Rahimzadeh et al., (2024) who also elevated lighted Tigecycline and colistin as among the few remaining effective therapeutic options against extensively drug-resistant isolates 25 . Doi et al., (2019), and Tängdén et al., (2021), evaluated the performance of the automated Phoenix system in detecting antibiotic resistance and identified the evaluated resistance rates to aminoglycosides, carbapenems, and quinolones (approximately 55%). Their results demonstrated that colistin remained one of the most effective antibiotics, with a sensitivity rate of 90%. The observed resistance patterns have significant clinical implications. The limited effectiveness of commonly used antibiotics such as cephalosporins and carbapenems complicates empirical therapy and increases the risk of treatment failure and mortality 24 , 26 . The elevated resistance rates identified in the present study may be associated with the excessive and often empirical use of broad-spectrum antibiotics in hospital environments, particularly in intensive care units 19 , 24 . Inadequate antimicrobial stewardship programs and insufficient infection control measures may further accelerate the emergence and dissemination of multidrug-resistant and extensively drug-resistant strains 20 , 23 . Therefore, continuous surveillance and strict implementation of antimicrobial stewardship programs are essential to limit the spread of resistance and improve clinical outcomes 22 , 26 . Our analysis of the genetic mechanisms behind antibiotic resistance showed that PCR results detected the presence of bla SHV and bla IMP genes in 100% of K. pneumoniae isolates. The OqxB (93.3%) and bla CTX−M (80%) genes were also highly prevalent. This pattern aligns with international studies reporting the widespread dissemination of bla CTX−M , bla IMP , and OqxB genes among multidrug-resistant Gram-negative strains 27 – 28 . The simultaneous presence of β-lactamase genes and efflux pumps in these isolates contributes to combined resistance, severely limiting treatment options. The high prevalence of bla SHV , bla IMP , bla CTX−M , and OqxB genes may be driven by horizontal gene transfer through plasmids, transposons, and integrons. The co-localization of multiple resistance genes on mobile genetic elements facilitates rapid spread within hospital environments, especially under selective pressure from extensive antibiotic use. Phylogenetic analysis based on rpoB gene sequences revealed that three hospital isolates (from ICU, PICU, and Oncology) clustered closely with the reference XDR strain ( K. pneumoniae CP008827.1). This finding indicates a elevated genetic relatedness and suggests the possibility of clonal intra-hospital transmission. All clinical isolates exhibited an XDR phenotype, and their genetic proximity suggests they may share similar resistance mechanisms, potentially involving the same set of genes or plasmids. For XDR phenotypes including carbapenem and colistin resistance, two common mechanisms exist: 1) carbapenemase genes (e.g., KPC, NDM, OXA ) often plasmid-borne, and 2) colistin resistance via plasmid-mediated mcr genes or chromosomal mutations (e.g., mgrB). The genetic closeness of the isolates supports potential plasmid-mediated transfer or clonal expansion. A similar observation was reported by Kolupaeva et al., (2024) 29 , who demonstrated that A. baumannii and K. pneumoniae isolates from NICU units shared a common genetic origin and were disseminated via hospital equipment and patient contacts. The close genetic relatedness of these isolates, coupled with their XDR phenotype, elevated lights the clinical challenge in selecting effective treatment options. The potential for plasmid-mediated gene transfer further complicates therapy, emphasizing the need for judicious use of last-resort antibiotics such as Tigecycline and colistin, alongside personalized treatment strategies guided by susceptibility testing and molecular diagnostics. This study has several limitations that should be considered when interpreting the results. The sample size was relatively small, which may restrict the generalizability of the findings to other hospitals or geographic areas. Furthermore, since the study was conducted in a single tertiary care hospital, the results may not fully reflect the molecular epidemiology of multidrug-resistant Gram-negative bacteria in different healthcare settings. Future multicenter studies with larger sample sizes and whole-genome sequencing methods are recommended to provide a more comprehensive understanding of the molecular epidemiology and transmission dynamics of multidrug-resistant Gram-negative pathogens in bloodstream infections. Conclusion This study highlights K. pneumoniae as a leading cause of bloodstream infections in hospitalized patients, particularly in high-risk units. The significant prevalence of extensively drug-resistant strains, driven by extended-spectrum beta-lactamase and carbapenemase genes ( bla SHV , bla IMP , and blaCTX-M ) as well as efflux pumps ( OqXB ), underscores the crucial role of genetic factors in antibiotic resistance. Phylogenetic analysis indicates a potential clonal spread within hospitals, likely facilitated by horizontal gene transfer. These findings emphasize the urgent need for integrated strategies, including strict infection control measures, careful use of last-resort antibiotics (Tigecycline and Colistin), and ongoing molecular surveillance to manage XDR infections and prevent their spread within hospital settings. Methods Study design and sample collection This cross-sectional study was conducted at Bou Ali Sins Hospitals in Sari, Iran, from September 17, 2024, to May 20, 2025. The study protocol received approval from the Ethics Committee of Mazandaran University of Medical Sciences (IR.MAZUMS.REC.1403.274). Demographic data were collected from patient files (see Table 2 ). On the second page of the medical report, there is a consent form for each hospitalized patient. Patients, or their parents / legal guardians if the patients are under 18 years old, confirmed their consent by signing and providing a fingerprint. This indicates that the attending physician could use their samples for this research study. The blood samples were originally sent from various clinical units to the hospital laboratory for routine diagnostic testing. Once the blood cultures were processed and sepsis was confirmed by the laboratory, only the leftover and fully anonymized samples were provided to our research team after all diagnostic procedures were completed. No patient identifiers, such as names, surnames, or national IDs, nor any clinical follow-up information, were used or included in this study. All experimental procedures and sample processing adhered to the Mazandaran University of Medical Sciences Ethics Committee guidelines and applicable national and international standards. According to the Centers for Disease Control and Prevention) CDC (guidelines and Sepsis-3 definitions, patients with confirmed infection and clinical signs such as fever or hypothermia, leukocytosis or leukopenia, and a documented focus of infection were included. Evidence of organ dysfunction (SOFA ≥ 2) or a qSOFA score ≥ 2 indicated an increased likelihood of sepsis and eligibility for enrollment (11). Based on CDC and IDSA recommendations, for patients with sepsis, two to three blood culture sets were collected from different peripheral venous sites using strict aseptic technique. In patients with central venous catheters, one set was obtained from the catheter and another from a peripheral vein to distinguish catheter-related from systemic infections. Each set included one aerobic and one anaerobic BD BACTEC bottle. For adults, 8–10 mL of blood was inoculated into each bottle. The samples were promptly transported to the laboratory and incubated in the BD BACTEC FX40 automated system for continuous monitoring of microbial growth 11 – 12 . Automated Antimicrobial Susceptibility Testing of Clinical Isolates Using Phoenix M50 Blood samples that were positive in the BD BACTEC FX40 system were tested for antimicrobial susceptibility using the BD Phoenix M50 automated system. The blood sample was first cultured on Blood agar (QUELAB, USA) and incubated at 37°C for 24 hours. A pure colony was then suspended in Phoenix M50 ID broth to achieve a turbidity equivalent to 0.5 McFarland. The suspension was inoculated into AST panels containing predefined concentrations of antibiotics and loaded into the Phoenix M50 system. The system continuously monitored bacterial growth and determined the Minimum Inhibitory Concentration (MIC) for each antibiotic. Results were interpreted according to CLSI guidelines as Sensitive (S), Intermediate (I), or Resistant (R) and recorded in the Laboratory Information System. Standard reference strains were included for quality control. Between September 17, 2024, and May 20, 2025, a total of 217 Gram-negative isolates were confirmed using the Phoenix M50 system, of which 112 were associated with bloodstream infections. Based on the study inclusion criteria, only four Gram-negative Bacteria E. coli, A. baumannii, P. aeruginosa , and K. Pneumoniae were included in the study. According to the CDC and ECDC (European Centre for Disease Prevention and Control) standards, only XDR isolates, defined as resistant to all or nearly all classes of antibiotics except one or two classes 13 – 14 , were enrolled in the study. ESBL Detection in Gram-Negative Isolates Using the Combined Disk Test (CDT) Gram-negative colonies with a turbidity of 0.5 McFarland (1.5 ×10 8 CFU/mL) were inoculated onto Muller-Hinton agar (QUELAB, USA) plates. Disks of cefotaxime (30 µg), ceftazidime (30 µg), cefotaxime/clavulanic acid (30/10 µg), and ceftazidime/clavulanic acid (30/10 µg) (PADTAN TEB Company) were placed on the agar surface. Plates were incubated at 35–37°C for 16–18 hours. An increase of ≥ 5 mm in the inhibition zone around disks containing clavulanic acid compared to cephalosporin alone was interpreted as ESBL-positive. K. pneumoniae ATCC 700603 and E. coli ATCC 25922 were used as positive and negative controls, respectively. Genomic DNA Extraction and PCR for Resistance Genes Genomic DNA from XDR isolates was extracted using a commercial kit (FAVORGEN, Taiwan) following the manufacturer’s instructions. Specific primers targeting resistance genes in the XDR Gram-negative isolates included CTX-M, OqxA, OqxB, blaNDM, aac(1)A, aac(1)B, blaSHV, blaTEM , and blaIMP (Table 1 ) (15). PCR reactions were prepared using Taq DNA polymerase (AMPLIQON, Denmark), primers (10 pM), template DNA (100 ng), and DNase-free distilled water. PCR reactions included negative controls (without template DNA) and positive controls: K. pneumoniae ATCC 7881 (harboring blaCTX-M, blaTEM , and blaSHV ) and E. coli ATCC 35218 (harboring AcrA, AcrB, aac(1)A, aac(1)B ). Amplification was performed with an initial denaturation at 94°C for 30 s, followed by 35 cycles with annealing and extension steps at 61°C and 72°C for 30 s, respectively, and a final extension at 72°C for 10 min. PCR products were separated on 1.5% agarose gel and visualized using a gel documentation system (UVIDoc HD6 Touch, USA). Table 1 Sequences of the oligonucleotide primers 15 – 16 . Resistance genes Primer sequences (5′→3′) Product size (bp) bla CTX−M15 CACACGTGGAATTTAGGGACT GCCGTCTAAGGCGATAAACA 996 bla SHV AAGATCCACTATCGCCAGCAG ATTCAGTTCCGTTTCCCAGCGG 230 bla TEM GAGTATTCAACATTTCCGTGTG TAATCAGTGAGGCACCTATCT 972 bla IMP CGGGCGGAATAGAGTGGCTTAA GTGTGTCCTGGGCCTGGATAAA 212 bla NDM GGTTTGGCGATCTGGTTTTC CGGAATGGCTCATCACGATC 621 oqxA GCATTGAAGCGGTGGAGAGTGT GCCAGACGCCCCGAGGTAA 856 oqxB CGCAACTACGCCACGCTGAA CCGATCCCGACCGCATCCTTA 410 aac3-IIa GCCGACTGGCACTGTGATGGGATAC TGCAATGCGGTAACGGAGTTTAGCG 360 aac6-Ib TATGAGTGGCTAAATCGAT CCCGCTTTCTCGTAGCA 395 rpoB CAACGGTGTGGTTACTGAC TCTACGAAGTGGCCGTTTTC 108 Phylogenetic analyses phylogenetic analysis was performed using the rpoB gene sequences. The sequences under study were first subjected to multiple sequence alignment (MSA) using MEGA software. A phylogenetic tree was then constructed based on the Neighbor-Joining method and genetic distances derived from the alignment. The tree was visualized and rendered using the Bio.Phylo module from the Biopython package in Python. The rpoB primer sequences were obtained from NCBI (Table 1 ) 15 – 16 , and PCR was performed for three clinical isolates 289-F (ICU), 727-F (Oncology), and 913-F (PICU). These isolates were selected based on their extensively drug-resistant phenotype, as confirmed by the fully automated Phoenix system. Genotypic analysis also confirmed the presence of all relevant resistance genes in these isolates. The isolates originated from ICU, Oncology, and PICU wards. Following PCR product purification, samples at a concentration of 10 pm were sent to Macrogen, South Korea, for Sanger sequencing (forward strand). For comparison and confirmation of the XDR resistance pattern in the clinical isolates, two reference K. pneumoniae strains from NCBI were included: GenBank accession numbers CP008827.1 and CP003200. Statistical analysis Data were analyzed using SPSS version 22 is IBM Corp., Armonk, NY, US—statistical analysis involved chi-square and Fisher’s exact tests. Declarations Competing interests The author(s) declare no competing interests. Funding We would like to thank the Vice Chancellor for Research and Technology at Mazandaran University of Medical Sciences for funding this project. Author Contribution Conceptualization: MA, MSR, GR; Data curation: FRY, GR; Formal analysis: FR; Investigation: MA, FRY, GR, SSH, EN; Methodology: FRY, GR, SSH, EN; Project administration: MSR, MA; Software: FR; Supervision: MA, GR, MSR, SSH; Validation: MA, GR, MSR, EN; Visualization: MA, GR, MSR; Writing—original draft: GR; Writing—review & editing: MA, GR. Acknowledgement The authors acknowledge the Pediatric Infectious Diseases Research Center Lab for providing the facilities and support to perform this study. 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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-8106566","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":563061560,"identity":"9fd880fc-89e8-4dfb-8211-95feb848c525","order_by":0,"name":"Fatemeh Ramazan Yazdi","email":"","orcid":"","institution":"Mazandaran University of Medical Sciences, Sari, Iran","correspondingAuthor":false,"prefix":"","firstName":"Fatemeh","middleName":"Ramazan","lastName":"Yazdi","suffix":""},{"id":563061561,"identity":"25509bdf-498c-46bf-b253-dbf5f56642e4","order_by":1,"name":"Mohammad Sadegh Rezai","email":"","orcid":"","institution":"Mazandaran University 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Iran","correspondingAuthor":false,"prefix":"","firstName":"Ebrahim","middleName":"","lastName":"Nemati","suffix":""},{"id":563061565,"identity":"6a5213a2-7554-4642-888e-813f329298b9","order_by":5,"name":"Fereshteh Rostami","email":"","orcid":"","institution":"Mazandaran University of Medical Sciences, Sari, Iran","correspondingAuthor":false,"prefix":"","firstName":"Fereshteh","middleName":"","lastName":"Rostami","suffix":""},{"id":563061566,"identity":"d5b478f7-803d-400c-85db-ce9cbf2796d4","order_by":6,"name":"Mohammad Ahanjan","email":"","orcid":"","institution":"Mazandaran University of Medical Sciences, Sari, Iran","correspondingAuthor":false,"prefix":"","firstName":"Mohammad","middleName":"","lastName":"Ahanjan","suffix":""},{"id":563061567,"identity":"44b766d7-967f-40c0-abc1-e925f3a48301","order_by":7,"name":"Golnar Rahimzadeh","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEUlEQVRIiWNgGAWjYFACHoYDQJKxQQJIPgBifgYGNhK0JACxZAMRWhhQtBgcIKDFvP3swUM3/tjJ9ku3X3yQuMMu3/hG8rMHHyoY5PnFDmDVInMmL+FwDk+y8cw5Z4oNEs8kW267kWZuOOMMg+HM2QlYtUgw5BgczpFgTtxwIydNIrGN2cDsRoKZNG8bQ4LBbRxa+N8AtRjUJ+6HaKk3MJ6R/g2/FgmQLQmHEzdIpB8DajlsYCCRQ8AWCZAtB44bz7iRw2yQ2HbcQOLMmzLJGWckcPuFP8f4c86fatn+GekPH3xsqzbgb0/fJvGhwkaeXxq7FiTAYwChBRIg4UIEYH8AofkPEKN6FIyCUTAKRhAAAFmxYkGmWqQgAAAAAElFTkSuQmCC","orcid":"","institution":"Mazandaran University of Medical Sciences, Sari, Iran","correspondingAuthor":true,"prefix":"","firstName":"Golnar","middleName":"","lastName":"Rahimzadeh","suffix":""}],"badges":[],"createdAt":"2025-11-13 14:08:27","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8106566/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8106566/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":98845919,"identity":"084a89b8-350c-4b89-826d-b3b3371f9f5d","added_by":"auto","created_at":"2025-12-23 04:30:11","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":631907,"visible":true,"origin":"","legend":"","description":"","filename":"figurs.docx","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/b0646f86d7ac9f960a192777.docx"},{"id":98845921,"identity":"35b0fd0d-64ed-4eac-9d16-d6604ed3d784","added_by":"auto","created_at":"2025-12-23 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04:30:11","extension":"xml","order_by":22,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":87875,"visible":true,"origin":"","legend":"","description":"","filename":"8e1e8bbed1c84221bb35759bc79c0a281structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/7ce2a3b1466387d4b4fd9929.xml"},{"id":99308692,"identity":"55a65c74-535d-4dc7-bfd6-9ceb587c9c62","added_by":"auto","created_at":"2025-12-31 16:08:58","extension":"html","order_by":23,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":105255,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/ad3e4414868d59e83483b811.html"},{"id":98845914,"identity":"ef754842-d45b-4d3d-b348-e632dfa4984a","added_by":"auto","created_at":"2025-12-23 04:30:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40394,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of isolates in patients with sepsis.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/c68839fb4ba4a473c63922c5.png"},{"id":98845913,"identity":"7d03cce5-a7fe-4369-9e52-2f00270b9b75","added_by":"auto","created_at":"2025-12-23 04:30:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":79278,"visible":true,"origin":"","legend":"\u003cp\u003eSusceptibility patterns to antibiotics in patients with sepsis.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/190e083e40bcfe1f9b625644.png"},{"id":98845920,"identity":"0ba09d5f-4863-4f9c-b624-ad6953f8b814","added_by":"auto","created_at":"2025-12-23 04:30:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":22917,"visible":true,"origin":"","legend":"\u003cp\u003eFrequency of positive resistance genes in k. pneumonia isolates (N = 15).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/f430a05db82fbf49f0351171.png"},{"id":98845917,"identity":"c514f154-8f17-4136-b3a8-7ee6892686ff","added_by":"auto","created_at":"2025-12-23 04:30:11","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":72697,"visible":true,"origin":"","legend":"\u003cp\u003eThe correlation between frequency of resistance genes and susceptibility to antibiotics.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/bb66dc41a5f04e30b5d168c0.png"},{"id":99308876,"identity":"caf14080-59b4-44de-bd98-cdc0b682f318","added_by":"auto","created_at":"2025-12-31 16:09:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":147026,"visible":true,"origin":"","legend":"\u003cp\u003eThe phylogenetic tree shows that clinical isolates 289_RPO-F (ICU), 727_RPO-F (Oncology), and 913_RPO-F (PICU) cluster closely with the XDR reference isolate CP008827.1, while CP003200.1 is more distant, indicating elevated genetic similarity among the clinical isolates and potential clonal relatedness.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/ed250f16cd73bffccdd71296.png"},{"id":99322319,"identity":"64ec5a86-f09e-453b-9aff-23b8108be9c9","added_by":"auto","created_at":"2025-12-31 16:43:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1135344,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8106566/v1/874113f5-735c-4a60-94eb-93f7c82326ae.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genomic and Molecular Analysis of Multidrug-Resistant Gram-Negative Bacteria Causing Bloodstream Infections in Hospitalized Patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBloodstream infections (BSIs) are among the most severe healthcare-associated infections, linked to high mortality, significant clinical complications, and a considerable economic impact. In 2019, BSIs were estimated to cause approximately 2.91\u0026nbsp;million deaths worldwide, with Gram-negative bacteria responsible for more than 51% of cases. The dominance of Gram-negative pathogens in BSIs is mainly due to their intrinsic structural defenses, including an outer membrane rich in lipopolysaccharides, an enhanced ability for horizontal gene transfer and acquisition of antimicrobial resistance genes, the capacity to survive and colonize indwelling medical devices, and the expression of potent virulence factors that contribute to systemic infections and sepsis\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. BSIs are especially common in ICU patients, the elderly, and immunocompromised individuals\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Epidemiological studies show that \u003cem\u003eE. coli\u003c/em\u003e is the leading Gram-negative pathogen in BSIs, accounting for about 49.9% of Gram-negative isolates. Other prevalent Gram-negative bacteria include \u003cem\u003eKlebsiella\u003c/em\u003e spp. (21%), \u003cem\u003eEnterobacter\u003c/em\u003e spp. (7%), \u003cem\u003eProteus mirabilis\u003c/em\u003e (6.1%), \u003cem\u003eP. aeruginosa\u003c/em\u003e (5.6%), and \u003cem\u003eS. marcescens\u003c/em\u003e (3.3%). The prevalence of these pathogens is notably higher among ICU patients and those with central venous catheters. Additional risk factors for Gram-negative BSIs include prolonged antibiotic use, urinary or gastrointestinal surgeries, and extended hospital stays \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e \u003cp\u003eThe emergence and dissemination of multidrug-resistant (MDR) Gram-negative bacteria in recent years have posed major challenges for the treatment of bloodstream infections (BSIs). According to a 2017 World Health Organization (WHO) report, carbapenem-resistant Gram-negative pathogens including \u003cem\u003eA. baumannii\u003c/em\u003e and \u003cem\u003eP. aeruginosa\u003c/em\u003e as well as extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae, were classified as critical-priority pathogens. These bacteria acquire resistance to a wide range of antibiotics, particularly carbapenems, through mechanisms such as β-lactamase enzyme production, efflux pump overexpression, porin loss, and mutations in drug targets \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. ESBL-producing strains are highly resistant to beta-lactams and aztreonam, while generally remaining susceptible to carbapenems. In contrast, carbapenem-resistant strains often exhibit reduced OprD porin expression and produce class A (KPC, GES), metallo-β-lactamases (\u003cem\u003eIMP -NDM -GIM - FIM -SPM -VIM\u003c/em\u003e), and class D (\u003cem\u003eOXA-48\u003c/em\u003e) enzymes, conferring high-level carbapenem resistance. MDR and extensively drug-resistant (XDR) strains additionally display cephalosporin resistance via class C β-lactamases (\u003cem\u003eAmpC blaSHV blaTEM blaCTX-M\u003c/em\u003e) and quinolone resistance mediated by DNA gyrase/topoisomerase IV mutations and plasmid-encoded efflux pumps (\u003cem\u003eOqxA, OqxB\u003c/em\u003e) \u003csup\u003e\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. In patients with bloodstream infections (BSIs), the challenges posed by antimicrobial resistance highlight the critical importance of rapid and accurate diagnosis with high sensitivity and specificity. Traditional blood culture and microbiological methods, however, have demonstrated limited diagnostic yield. This shortcoming contributes to higher rates of hospital-acquired infections, prolonged hospital stays, increased treatment costs, and mortality rates that can reach 50\u0026ndash;60% \u003csup\u003e10\u003c/sup\u003e. Therefore, it is essential to integrate automated culture systems, evaluate the phenotypic and genotypic correlations of antibiotic resistance, and implement effective infection control measures to curb the spread of resistant Gram-negative pathogens. The current study aims to characterize the genotypes and sequence multidrug-resistant Gram-negative isolates confirmed by the fully automated Phoenix M50 and BD BACTEC FX40 systems in hospitalized patients with BSIs at Bou-Ali Sina Hospital in Sari, Iran, during the period from 2024 to 2025.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDemographic information of the pertains with BSIs\u003c/h2\u003e \u003cp\u003eIn this study, blood samples were obtained from 30 hospitalized patients at Bou Ali Sina Hospital in Sari. The median age of the patients was 31 years (interquartile range [IQR]: 5\u0026ndash;72). The youngest patient was 35 days old, and the oldest was 92 years. Among the study population, 66.7% were male and 33.3% were female (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Approximately 47% of the patients were admitted to the ICU. Microbiological analysis revealed that 70% of the isolates were identified as \u003cem\u003eK. pneumoniae\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe demographic data of patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;=10 years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eUnit\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmergency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003epediatric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOncology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNICU\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eENT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePediatric\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eBacteria\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eK. pneumoniae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eA. baumannii\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP. aeruginosa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eE. coli\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eAntimicrobial Susceptibility Testing of Clinical Isolates Using Phoenix M50\u003c/h3\u003e\n\u003cp\u003eAutomated antimicrobial susceptibility testing of clinical isolates using the Phoenix M50 system demonstrated that among 30 bacterial isolates recovered from the blood samples of patients diagnosed with sepsis, the highest level of antibiotic resistance was observed against Ceftriaxone, with 96.7% of isolates exhibiting resistance. This was followed by Ampicillin, Cefuroxime, and Cefazolin, each showing a 90% resistance rate. In contrast, the lowest resistance was observed for Tigecycline, with only 33.3% of isolates displaying resistance (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003ch3\u003eESBL Detection in Gram-Negative Isolates Using the Combined Disk Test (CDT)\u003c/h3\u003e\n\u003cp\u003eIn the phenotypic confirmatory test (Combined Disk Test; CDT) for the detection of ESBL-producing strains, a total of 30 isolates were examined. The results indicated that 76.7% of the isolates were ESBL-negative, while 23.3% were identified as ESBL-positive.\u003c/p\u003e\n\u003ch3\u003eDetection of resistance genes\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, elevated lights the frequency of antibiotic resistance genes in 15 clinical isolates of \u003cem\u003eK. pneumoniae\u003c/em\u003e. Notably, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eSHV\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eIMP\u003c/em\u003e\u003c/sub\u003e were identified in 100% of the isolates, indicating their widespread presence. Moreover, the efflux pump gene OqxB was detected in 93.33%, and the extended-spectrum β-lactamase (ESBL) gene \u003cem\u003eblaCTX-M\u003c/em\u003e was present in 80%. These findings underscore of multidrug resistance among these strains. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, shows the relation between the frequency of resistance genes and susceptibility to antibiotics. In \u003cem\u003ek. pneumonia\u003c/em\u003e isolates (N\u0026thinsp;=\u0026thinsp;15), no significant relationship was identified between resistance genes and antibiotic resistance.\u003c/p\u003e\n\u003ch3\u003ePhylogenetic analyses\u003c/h3\u003e\n\u003cp\u003eThe three clinical isolates (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), 289_RPO-F (ICU), 727_RPO-F (Oncology), and 913_RPO-F (PICU), cluster closely together. Within the same cluster, an NCBI reference isolate (CP008827.1) is located near the node encompassing these isolates. The other reference isolate (CP003200.1) is phylogenetically distant from this cluster and appears as an outgroup relative to the main group. Branch lengths indicate that the genetic distance between the clinical isolates and CP008827.1 is low, reflecting minimal genetic divergence, whereas CP003200.1 exhibits a considerably greater genetic distance. The close clustering of 289 and 727, followed by 913, indicates elevated genetic similarity among these three isolates, suggesting a likely common lineage or closely related sublineage. The tree shows that 289 and 727 are probably the most closely related, while 913 is slightly more distant but still within the same cluster. Proximity to CP008827.1, an NCBI isolate previously reported as XDR, strongly suggests that our isolates may belong to a known XDR lineage or, at a minimum, carry similar resistance genes. The large distance to CP003200.1 indicates that this reference isolate represents a different lineage, likely with distinct resistance motifs or genetic background.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of the current study indicate that Klebsiella pneumoniae is the most common cause of bloodstream infections (BSIs) among hospitalized patients. This is followed by \u003cem\u003eA. baumannii, P. aeruginosa\u003c/em\u003e, and \u003cem\u003eE. coli\u003c/em\u003e. These findings align with several national and international studies that have identified \u003cem\u003eK. pneumoniae\u003c/em\u003e and \u003cem\u003eA. baumannii\u003c/em\u003e as significant multidrug-resistant pathogens responsible for BSIs \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The high prevalence of \u003cem\u003eK. pneumoniae\u003c/em\u003e and \u003cem\u003eA. baumannii\u003c/em\u003e observed in this study may be due to their remarkable ability to acquire and spread antimicrobial resistance genes, particularly those that encode Extended-Spectrum Beta-Lactamases and carbapenemases \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The extensive use of broad-spectrum antibiotics in hospitals, particularly in ICUs, likely contributes to the selection and persistence of these multidrug-resistant strains \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Moreover, inadequate infection control measures and environmental contamination may facilitate the transmission of these pathogens among vulnerable patients \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, In contrast, the relatively lower prevalence of \u003cem\u003eE. coli\u003c/em\u003e and \u003cem\u003eP. aeruginosa\u003c/em\u003e might be attributed to differences in patient populations, underlying comorbidities, or variations in local antibiotic stewardship policies \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e ,\u003c/p\u003e \u003cp\u003eIn our study in analysis of antibiotic resistance patterns, the highest resistance rates were observed against ceftriaxone, ampicillin, cefuroxime, and cefazolin, respectively. This elevated level of resistance to cephalosporins and penicillins indicates the widespread presence of ESBL\u0026ndash;producing strains. Tigecycline, with only 33.3% resistance, was identified as the most effective antibiotic. These findings are consistent with the reports of Bhargava et al., (2019) \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and Rahimzadeh et al., (2024) who also elevated lighted Tigecycline and colistin as among the few remaining effective therapeutic options against extensively drug-resistant isolates \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDoi et al., (2019), and T\u0026auml;ngd\u0026eacute;n et al., (2021), evaluated the performance of the automated Phoenix system in detecting antibiotic resistance and identified the evaluated resistance rates to aminoglycosides, carbapenems, and quinolones (approximately 55%). Their results demonstrated that colistin remained one of the most effective antibiotics, with a sensitivity rate of 90%. The observed resistance patterns have significant clinical implications. The limited effectiveness of commonly used antibiotics such as cephalosporins and carbapenems complicates empirical therapy and increases the risk of treatment failure and mortality \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. The elevated resistance rates identified in the present study may be associated with the excessive and often empirical use of broad-spectrum antibiotics in hospital environments, particularly in intensive care units \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Inadequate antimicrobial stewardship programs and insufficient infection control measures may further accelerate the emergence and dissemination of multidrug-resistant and extensively drug-resistant strains \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Therefore, continuous surveillance and strict implementation of antimicrobial stewardship programs are essential to limit the spread of resistance and improve clinical outcomes \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur analysis of the genetic mechanisms behind antibiotic resistance showed that PCR results detected the presence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eSHV\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eIMP\u003c/em\u003e\u003c/sub\u003e genes in 100% of \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates. The \u003cem\u003eOqxB\u003c/em\u003e (93.3%) and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eCTX\u0026minus;M\u003c/em\u003e\u003c/sub\u003e (80%) genes were also highly prevalent. This pattern aligns with international studies reporting the widespread dissemination of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eCTX\u0026minus;M\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eIMP\u003c/em\u003e\u003c/sub\u003e, and \u003cem\u003eOqxB\u003c/em\u003e genes among multidrug-resistant Gram-negative strains \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. The simultaneous presence of β-lactamase genes and efflux pumps in these isolates contributes to combined resistance, severely limiting treatment options. The high prevalence of \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eSHV\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eIMP\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eCTX\u0026minus;M\u003c/em\u003e\u003c/sub\u003e, and \u003cem\u003eOqxB\u003c/em\u003e genes may be driven by horizontal gene transfer through plasmids, transposons, and integrons. The co-localization of multiple resistance genes on mobile genetic elements facilitates rapid spread within hospital environments, especially under selective pressure from extensive antibiotic use.\u003c/p\u003e \u003cp\u003ePhylogenetic analysis based on \u003cem\u003erpoB\u003c/em\u003e gene sequences revealed that three hospital isolates (from ICU, PICU, and Oncology) clustered closely with the reference XDR strain (\u003cem\u003eK. pneumoniae\u003c/em\u003e CP008827.1). This finding indicates a elevated genetic relatedness and suggests the possibility of clonal intra-hospital transmission. All clinical isolates exhibited an XDR phenotype, and their genetic proximity suggests they may share similar resistance mechanisms, potentially involving the same set of genes or plasmids. For XDR phenotypes including carbapenem and colistin resistance, two common mechanisms exist: 1) carbapenemase genes (e.g., \u003cem\u003eKPC, NDM, OXA\u003c/em\u003e) often plasmid-borne, and 2) colistin resistance via plasmid-mediated mcr genes or chromosomal mutations (e.g., mgrB). The genetic closeness of the isolates supports potential plasmid-mediated transfer or clonal expansion. A similar observation was reported by Kolupaeva et al., (2024) \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, who demonstrated that \u003cem\u003eA. baumannii\u003c/em\u003e and \u003cem\u003eK. pneumoniae\u003c/em\u003e isolates from NICU units shared a common genetic origin and were disseminated via hospital equipment and patient contacts. The close genetic relatedness of these isolates, coupled with their XDR phenotype, elevated lights the clinical challenge in selecting effective treatment options. The potential for plasmid-mediated gene transfer further complicates therapy, emphasizing the need for judicious use of last-resort antibiotics such as Tigecycline and colistin, alongside personalized treatment strategies guided by susceptibility testing and molecular diagnostics.\u003c/p\u003e \u003cp\u003eThis study has several limitations that should be considered when interpreting the results. The sample size was relatively small, which may restrict the generalizability of the findings to other hospitals or geographic areas. Furthermore, since the study was conducted in a single tertiary care hospital, the results may not fully reflect the molecular epidemiology of multidrug-resistant Gram-negative bacteria in different healthcare settings. Future multicenter studies with larger sample sizes and whole-genome sequencing methods are recommended to provide a more comprehensive understanding of the molecular epidemiology and transmission dynamics of multidrug-resistant Gram-negative pathogens in bloodstream infections.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study highlights \u003cem\u003eK. pneumoniae\u003c/em\u003e as a leading cause of bloodstream infections in hospitalized patients, particularly in high-risk units. The significant prevalence of extensively drug-resistant strains, driven by extended-spectrum beta-lactamase and carbapenemase genes (\u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eSHV\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eIMP\u003c/em\u003e\u003c/sub\u003e, and \u003cem\u003eblaCTX-M\u003c/em\u003e) as well as efflux pumps (\u003cem\u003eOqXB\u003c/em\u003e), underscores the crucial role of genetic factors in antibiotic resistance. Phylogenetic analysis indicates a potential clonal spread within hospitals, likely facilitated by horizontal gene transfer. These findings emphasize the urgent need for integrated strategies, including strict infection control measures, careful use of last-resort antibiotics (Tigecycline and Colistin), and ongoing molecular surveillance to manage XDR infections and prevent their spread within hospital settings.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and sample collection\u003c/h2\u003e \u003cp\u003eThis cross-sectional study was conducted at Bou Ali Sins Hospitals in Sari, Iran, from September 17, 2024, to May 20, 2025. The study protocol received approval from the Ethics Committee of Mazandaran University of Medical Sciences (IR.MAZUMS.REC.1403.274). Demographic data were collected from patient files (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e). On the second page of the medical report, there is a consent form for each hospitalized patient. Patients, or their parents / legal guardians if the patients are under 18 years old, confirmed their consent by signing and providing a fingerprint. This indicates that the attending physician could use their samples for this research study. The blood samples were originally sent from various clinical units to the hospital laboratory for routine diagnostic testing. Once the blood cultures were processed and sepsis was confirmed by the laboratory, only the leftover and fully anonymized samples were provided to our research team after all diagnostic procedures were completed. No patient identifiers, such as names, surnames, or national IDs, nor any clinical follow-up information, were used or included in this study.\u003c/p\u003e \u003cp\u003e All experimental procedures and sample processing adhered to the Mazandaran University of Medical Sciences Ethics Committee guidelines and applicable national and international standards.\u003c/p\u003e \u003cp\u003e According to the Centers for Disease Control and Prevention) CDC (guidelines and Sepsis-3 definitions, patients with confirmed infection and clinical signs such as fever or hypothermia, leukocytosis or leukopenia, and a documented focus of infection were included. Evidence of organ dysfunction (SOFA\u0026thinsp;\u0026ge;\u0026thinsp;2) or a qSOFA score\u0026thinsp;\u0026ge;\u0026thinsp;2 indicated an increased likelihood of sepsis and eligibility for enrollment (11). Based on CDC and IDSA recommendations, for patients with sepsis, two to three blood culture sets were collected from different peripheral venous sites using strict aseptic technique. In patients with central venous catheters, one set was obtained from the catheter and another from a peripheral vein to distinguish catheter-related from systemic infections. Each set included one aerobic and one anaerobic BD BACTEC bottle. For adults, 8\u0026ndash;10 mL of blood was inoculated into each bottle. The samples were promptly transported to the laboratory and incubated in the BD BACTEC FX40 automated system for continuous monitoring of microbial growth \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eAutomated Antimicrobial Susceptibility Testing of Clinical Isolates Using Phoenix M50\u003c/h2\u003e \u003cp\u003eBlood samples that were positive in the BD BACTEC FX40 system were tested for antimicrobial susceptibility using the BD Phoenix M50 automated system. The blood sample was first cultured on Blood agar (QUELAB, USA) and incubated at 37\u0026deg;C for 24 hours. A pure colony was then suspended in Phoenix M50 ID broth to achieve a turbidity equivalent to 0.5 McFarland. The suspension was inoculated into AST panels containing predefined concentrations of antibiotics and loaded into the Phoenix M50 system. The system continuously monitored bacterial growth and determined the Minimum Inhibitory Concentration (MIC) for each antibiotic. Results were interpreted according to CLSI guidelines as Sensitive (S), Intermediate (I), or Resistant (R) and recorded in the Laboratory Information System. Standard reference strains were included for quality control. Between September 17, 2024, and May 20, 2025, a total of 217 Gram-negative isolates were confirmed using the Phoenix M50 system, of which 112 were associated with bloodstream infections. Based on the study inclusion criteria, only four Gram-negative Bacteria \u003cem\u003eE. coli, A. baumannii, P. aeruginosa\u003c/em\u003e, and \u003cem\u003eK. Pneumoniae\u003c/em\u003e were included in the study. According to the CDC and ECDC (European Centre for Disease Prevention and Control) standards, only XDR isolates, defined as resistant to all or nearly all classes of antibiotics except one or two classes \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, were enrolled in the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eESBL Detection in Gram-Negative Isolates Using the Combined Disk Test (CDT)\u003c/h2\u003e \u003cp\u003eGram-negative colonies with a turbidity of 0.5 McFarland (1.5 \u0026times;10\u003csup\u003e8\u003c/sup\u003e CFU/mL) were inoculated onto Muller-Hinton agar (QUELAB, USA) plates. Disks of cefotaxime (30 \u0026micro;g), ceftazidime (30 \u0026micro;g), cefotaxime/clavulanic acid (30/10 \u0026micro;g), and ceftazidime/clavulanic acid (30/10 \u0026micro;g) (PADTAN TEB Company) were placed on the agar surface. Plates were incubated at 35\u0026ndash;37\u0026deg;C for 16\u0026ndash;18 hours. An increase of \u0026ge;\u0026thinsp;5 mm in the inhibition zone around disks containing clavulanic acid compared to cephalosporin alone was interpreted as ESBL-positive. \u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 700603 and \u003cem\u003eE. coli\u003c/em\u003e ATCC 25922 were used as positive and negative controls, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eGenomic DNA Extraction and PCR for Resistance Genes\u003c/h2\u003e \u003cp\u003eGenomic DNA from XDR isolates was extracted using a commercial kit (FAVORGEN, Taiwan) following the manufacturer\u0026rsquo;s instructions. Specific primers targeting resistance genes in the XDR Gram-negative isolates included \u003cem\u003eCTX-M, OqxA, OqxB, blaNDM, aac(1)A, aac(1)B, blaSHV, blaTEM\u003c/em\u003e, and \u003cem\u003eblaIMP\u003c/em\u003e (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) (15). PCR reactions were prepared using Taq DNA polymerase (AMPLIQON, Denmark), primers (10 pM), template DNA (100 ng), and DNase-free distilled water. PCR reactions included negative controls (without template DNA) and positive controls: \u003cem\u003eK. pneumoniae\u003c/em\u003e ATCC 7881 (harboring \u003cem\u003eblaCTX-M, blaTEM\u003c/em\u003e, and \u003cem\u003eblaSHV\u003c/em\u003e) and \u003cem\u003eE. coli\u003c/em\u003e ATCC 35218 (harboring \u003cem\u003eAcrA, AcrB, aac(1)A, aac(1)B\u003c/em\u003e). Amplification was performed with an initial denaturation at 94\u0026deg;C for 30 s, followed by 35 cycles with annealing and extension steps at 61\u0026deg;C and 72\u0026deg;C for 30 s, respectively, and a final extension at 72\u0026deg;C for 10 min. PCR products were separated on 1.5% agarose gel and visualized using a gel documentation system (UVIDoc HD6 Touch, USA).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSequences of the oligonucleotide primers \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResistance genes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimer sequences (5\u0026prime;\u0026rarr;3\u0026prime;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eProduct size (bp)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eCTX\u0026minus;M15\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCACACGTGGAATTTAGGGACT\u003c/p\u003e \u003cp\u003eGCCGTCTAAGGCGATAAACA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e996\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eSHV\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAAGATCCACTATCGCCAGCAG\u003c/p\u003e \u003cp\u003eATTCAGTTCCGTTTCCCAGCGG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e230\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eTEM\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGAGTATTCAACATTTCCGTGTG\u003c/p\u003e \u003cp\u003eTAATCAGTGAGGCACCTATCT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eIMP\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGGGCGGAATAGAGTGGCTTAA\u003c/p\u003e \u003cp\u003eGTGTGTCCTGGGCCTGGATAAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e212\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eNDM\u003c/em\u003e\u003c/sub\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGGTTTGGCGATCTGGTTTTC\u003c/p\u003e \u003cp\u003eCGGAATGGCTCATCACGATC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e621\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eoqxA\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCATTGAAGCGGTGGAGAGTGT\u003c/p\u003e \u003cp\u003eGCCAGACGCCCCGAGGTAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e856\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eoqxB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCGCAACTACGCCACGCTGAA\u003c/p\u003e \u003cp\u003eCCGATCCCGACCGCATCCTTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e410\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eaac3-IIa\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGCCGACTGGCACTGTGATGGGATAC\u003c/p\u003e \u003cp\u003eTGCAATGCGGTAACGGAGTTTAGCG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e360\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eaac6-Ib\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTATGAGTGGCTAAATCGAT\u003c/p\u003e \u003cp\u003eCCCGCTTTCTCGTAGCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e395\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003erpoB\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCAACGGTGTGGTTACTGAC\u003c/p\u003e \u003cp\u003eTCTACGAAGTGGCCGTTTTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003ePhylogenetic analyses\u003c/h2\u003e \u003cp\u003ephylogenetic analysis was performed using the rpoB gene sequences. The sequences under study were first subjected to multiple sequence alignment (MSA) using MEGA software. A phylogenetic tree was then constructed based on the Neighbor-Joining method and genetic distances derived from the alignment. The tree was visualized and rendered using the Bio.Phylo module from the Biopython package in Python. The \u003cem\u003erpoB\u003c/em\u003e primer sequences were obtained from NCBI (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e) \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, and PCR was performed for three clinical isolates 289-F (ICU), 727-F (Oncology), and 913-F (PICU). These isolates were selected based on their extensively drug-resistant phenotype, as confirmed by the fully automated Phoenix system. Genotypic analysis also confirmed the presence of all relevant resistance genes in these isolates. The isolates originated from ICU, Oncology, and PICU wards. Following PCR product purification, samples at a concentration of 10 pm were sent to Macrogen, South Korea, for Sanger sequencing (forward strand). For comparison and confirmation of the XDR resistance pattern in the clinical isolates, two reference \u003cem\u003eK. pneumoniae\u003c/em\u003e strains from NCBI were included: GenBank accession numbers CP008827.1 and CP003200.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eData were analyzed using SPSS version 22 is IBM Corp., Armonk, NY, US\u0026mdash;statistical analysis involved chi-square and Fisher\u0026rsquo;s exact tests.\u003c/p\u003e \u003c/div\u003e "},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe author(s) declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eWe would like to thank the Vice Chancellor for Research and Technology at Mazandaran University of Medical Sciences for funding this project.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization: MA, MSR, GR; Data curation: FRY, GR; Formal analysis: FR; Investigation: MA, FRY, GR, SSH, EN; Methodology: FRY, GR, SSH, EN; Project administration: MSR, MA; Software: FR; Supervision: MA, GR, MSR, SSH; Validation: MA, GR, MSR, EN; Visualization: MA, GR, MSR; Writing\u0026mdash;original draft: GR; Writing\u0026mdash;review \u0026amp; editing: MA, GR.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors acknowledge the Pediatric Infectious Diseases Research Center Lab for providing the facilities and support to perform this study. We thank the clinical laboratory of Buo Ali Sina Hospital for providing the data and the clinical isolates collection.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analysed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eZha, L. et al. Global and regional burden of bloodstream infections in 2019: a systematic analysis. \u003cem\u003eLancet Infect. Dis.\u003c/em\u003e \u003cb\u003e25\u003c/b\u003e, 107769 (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDard\u0026oacute;n-Fierro, F. E. et al. Epidemiology of ICU-onset bloodstream infection: prevalence, pathogens, and risk factors among 150,948 ICU patients at 85 US hospitals. \u003cem\u003eCrit. 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Acinetobacter baumannii and \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e isolates obtained from intensive care unit patients in 2024: general characterization, prophages, depolymerases, and esterases of phage origin. \u003cem\u003eViruses\u003c/em\u003e. 17, 623 (2025).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Bloodstream infections, Klebsiella pneumoniae, Extensively Drug-Resistant, Phoenix tanique, PCR, Hospital-Acquired Infections","lastPublishedDoi":"10.21203/rs.3.rs-8106566/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8106566/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBloodstream infections caused by multidrug-resistant and extensively drug-resistant Gram-negative bacteria represent a major global health concern, particularly among hospitalized and critically ill patients. This study aimed to characterize the molecular profiles, antimicrobial resistance patterns, and phylogenetic relationships of Gram-negative isolates obtained from bloodstream infections in hospitalized patients. A cross-sectional study was conducted between September 2024 and May 2025. Bacterial identification and antimicrobial susceptibility testing were performed using the BD Phoenix M50 and BD BACTEC FX40 automated systems, and extended-spectrum β-lactamase production was confirmed by the Combined Disk Test. Resistance genes, including \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eSHV\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eCTX\u0026minus;M\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eIMP\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eNDM\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eTEM\u003c/em\u003e\u003c/sub\u003e, \u003cem\u003eOqxA, OqxB, aac(1)A\u003c/em\u003e, and \u003cem\u003eaac(1)B\u003c/em\u003e were detected via PCR, and the \u003cem\u003eRpoB\u003c/em\u003e gene was sequenced for phylogenetic analysis. Among 30 isolates, \u003cem\u003eKlebsiella pneumoniae\u003c/em\u003e (70%) was the predominant species. The highest resistance was observed to Ceftriaxone (96.7%), while Tigecycline showed the greatest activity (66.7% susceptibility). The \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eSHV\u003c/em\u003e\u003c/sub\u003e and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eIMP\u003c/em\u003e\u003c/sub\u003e genes were detected in all isolates, and \u003cem\u003eOqxB\u003c/em\u003e (93.3%) and \u003cem\u003ebla\u003c/em\u003e\u003csub\u003e\u003cem\u003eCTX\u0026minus;M\u003c/em\u003e\u003c/sub\u003e (80%) were highly prevalent. Phylogenetic analysis revealed close clustering of clinical isolates with the reference XDR strain \u003cem\u003eK. pneumoniae\u003c/em\u003e CP008827.1, suggesting intra-hospital transmission. These findings highlight the urgent need for continuous molecular surveillance, strict infection control, and rational antibiotic stewardship programs.\u003c/p\u003e","manuscriptTitle":"Genomic and Molecular Analysis of Multidrug-Resistant Gram-Negative Bacteria Causing Bloodstream Infections in Hospitalized Patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-23 04:30:06","doi":"10.21203/rs.3.rs-8106566/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"58050924930363485503418114669849203331","date":"2025-12-29T13:07:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-19T07:41:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-19T07:38:03+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-08T16:52:50+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-05T12:59:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-11-27T10:44:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c04b6ef-3aa9-40f4-a023-b79f52aa15b2","owner":[],"postedDate":"December 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":59963802,"name":"Health sciences/Diseases"},{"id":59963803,"name":"Health sciences/Medical research"},{"id":59963804,"name":"Biological sciences/Microbiology"},{"id":59963805,"name":"Biological sciences/Molecular biology"}],"tags":[],"updatedAt":"2025-12-23T04:30:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-23 04:30:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8106566","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8106566","identity":"rs-8106566","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}