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Article

Molecular Epidemiology Revealed Distinct Patterns Among Multidrug Resistant Clinical Acinetobacter baumannii Strains in Different Periods in the Main Hospital in Molise Region, Central Italy

by
Manuela Tamburro
,
Adele Lombardi
,
Michela Lucia Sammarco
and
Giancarlo Ripabelli
*
Department of Medicine and Health Sciences “Vincenzo Tiberio”, University of Molise, 86100 Campobasso, Italy
*
Author to whom correspondence should be addressed.
Appl. Microbiol. 2025, 5(1), 9; https://doi.org/10.3390/applmicrobiol5010009
Submission received: 27 December 2024 / Revised: 13 January 2025 / Accepted: 16 January 2025 / Published: 18 January 2025
(This article belongs to the Special Issue Exclusive Papers Collection of Editorial Board Members and Invited Scholars in Applied Microbiology (2023, 2024))
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Abstract

:
Background: Acinetobacter baumannii is a major cause of nosocomial infections in critically ill patients, and strains are frequently multidrug resistant (MDR). This study aimed to characterize 45 clinical A. baumannii isolates collected in different periods in the main hospital in the Molise Region, central Italy. Methods: Antimicrobial susceptibility was evaluated using an automated system, and PCRs were performed to detect resistance-associated genes. Pulsed-field gel electrophoresis (PFGE) was carried out with AscI and ApaI, and Multi-locus sequence typing (MLST) was performed according to the Oxford scheme. Results: All isolates exhibited MDR profiles, showing total susceptibility towards colistin. All strains harbored the blaOXA-23, blaOXA-51, and blaAmpC genes, as well as adeB, adeJ, adeG, abeS, and soxR. Dendrogram with AscI and ApaI revealed eleven and three clusters, respectively, and twenty-three and eighteen pulsotypes (Simpson’s index 0.96 and 0.93), and isolates from different periods were clearly distinguished. MLST revealed five sequence types, which varied depending on the isolation period, and ST1720 and ST369 were prevalent, followed by ST281, ST218, and ST513. Conclusions: Molecular characterization enables the identification of distinct patterns of MDR A. baumannii over time, underscoring its usefulness for improving epidemiological surveillance and combating antimicrobial resistance. This study provides previously unavailable information regarding A. baumannii circulating in the examined setting.

1. Introduction

Antimicrobial resistance is one of the most urgent public health issues in modern times, as the occurrence of infections with multidrug-resistant (MDR), extensively drug-resistant (XDR), difficult-to-treat drug-resistant (DTR), carbapenem-resistant (CR), and pan-drug-resistant (PDR) bacteria is increasing globally [1,2]. Across 34 countries of the Organization for Economic Co-operation and Development (OECD) and the European Union/European Economic Area (EU/EEA), each year, approximately 79,000 deaths are reported to be due to infections sustained by resistant bacteria [3]. Among these, carbapenem-resistant Acinetobacter baumannii (CRAb) is a highly diverse and genetically complex bacterial species and remains an emerging threat with mortality exceeding 40% in critically ill patients [4]. The 2024 update of the Bacterial Priority Pathogens List by the World Health Organization (WHO) emphasized the critical priority status of several Gram-negative bacteria resistant to last-resort antibiotics, including CRAb [5].
Due to its genomic plasticity and capacity to acquire antibiotic resistance determinants, A. baumannii can rapidly adapt to adverse and stressful conditions and spread among patients with long-term contamination of healthcare settings [6]. Indeed, CRAb represents a common cause of healthcare-associated infections (HAIs) and outbreaks, particularly in intensive care units (ICUs) [7], and multiple studies reported a high incidence of infections during the COVID-19 pandemic [8].
Surveillance through molecular characterization is essential in the context of AMR and for outbreak control [9], providing important epidemiological information for tracking the spread within facilities, and identifying the sources of infection. To investigate this question, Pulsed-field gel electrophoresis (PFGE) and Multi-locus sequence typing (MLST) were generally used for characterizing bacterial populations, although whole-genome sequencing (WGS) has been mainly applied in recent years [10]. Information achieved through molecular epidemiology investigations needs to be combined with an appropriate assessment of the resistance profile to identify whether profiles are linked to specific resistance events and to better address antibiotic therapy. Furthermore, the integration of genotyping data with classic epidemiological methods allows for the development of more targeted interventions for infection control and prevention, ultimately contributing to HAI reduction [11]. Recently, the molecular epidemiology of CRAb isolated in Italy during 2002–2018 was reviewed, revealing a high distribution of such sequence types (STs) and the acquisition of carbapenem-hydrolyzing class D β-lactamases among the most frequent mechanism related to carbapenems resistance in A. baumannii [12]. Indeed, A. baumannii isolates can accumulate resistance traits through several mechanisms, including horizontal gene transfer, natural transformation, acquisition of mutations, and mobilization of genetic elements that modulate the expression of intrinsic and acquired genes [13].
In the present study, the molecular characterization of A. baumannii isolated in the main hospital in the Molise region, central Italy, was performed to describe the resistance phenotypes towards carbapenems and other antibiotics (i.e., penicillins, cephalosporins, monobactams, aminoglycosides, fluoroquinolones, tetracyclines, polymyxins, etc.); to assess the prevalence of the carbapenem resistance associated-genes; and to identify the clonal relationships between the isolates and the most common circulating STs in a hospital setting and geographical area never explored for CRAb epidemiology before this survey. The ultimate goal was to distinguish the isolates from different periods based on the molecular patterns exhibited.

2. Materials and Methods

2.1. Strains Selection and Antimicrobial Susceptibility Testing

In this study, 45 A. baumannii isolates were selected and characterized, with 24 and 21 strains isolated in 2010 and during the period 2014–2018, respectively, in the hub hospital in the Molise region. Formally defined, the hub-and-spoke organization design is a model that arranges service delivery assets into a network consisting of an anchor establishment (hub) providing a full array of services, complemented by secondary establishments (spokes) that offer limited services, routing patients needing more intensive services to the hub for treatment [14].
The strains recovered from the hospital were regenerated and cultured onto MacConkey Agar (Biolife, Milan, Italy) plates and incubated at 37 °C overnight. Antimicrobial susceptibility was performed in collaboration with the Microbiology Laboratory of the hospital, using the Phoenix Automated Microbiology System (BD Italy, Milan, Italy) instrument. Particularly, susceptibility towards Imipenem (IMP), Meropenem (MEM), Amoxicillin-Clavulanate (AMC), Amikacin (AMK), Gentamicin (GEN), Ciprofloxacin (CIP), Levofloxacin (LVX) and Colistin (COL) were tested for all 45 strains.
Additionally, other antibiotics were tested for the following strains: 44 for Cefotaxime (CTX); 43 for Piperacillin-Tazobactam (PIP-TZ); 42 for both Ceftazidime (CAZ) and Cefepime (FEP); 41 for Ampicillin (AMP); 29 for Aztreonam (ATM); 24 for Trimethoprim (TMP); 21 for Ertapenem (ETP), Cefuroxime (CFX), Tobramycin (TOB) and Trimethoprim/Sulfamethoxazole (SXT); 20 for Fosfomycin (FO); 18 for both Tetracycline (TET) and Cefoxitin (CTZ); 16 for Piperacillin (PIP), 15 for Chloramphenicol (CHL); 13 for Cefazolin (CFZ), and 4 for Tigecycline (TGC). The Minimum Inhibitory Concentration (MIC) was interpreted according to threshold or breakpoint values established by the European Committee on Antimicrobial Susceptibility Testing [15].

2.2. Molecular Typing

To appreciate the potential presence of clonal relationships between the isolates, PFGE was carried out through the CHEF-DR II System (BioRad, Milan, Italy) according to a standardized protocol [16], using separately ApaI and AscI enzymes (Promega Corporation, Milan, Italy). Interpretation of chromosomal DNA restriction patterns was performed by analyzing the dendrograms generated through the UPGMA algorithm and Dice coefficient (BioNumerics software version 5.10, Applied Maths, Sint-Martens-Latem, Belgium). To identify the prevalence of circulating STs, the MLST was performed according to the Oxford scheme [17]. Hence, the following seven housekeeping genes were sequenced: citrate synthase (gltA), DNA gyrase subunit B (gyrB), glucose dehydrogenase B (gdhB), homologous recombination factor (recA), 60-kDa chaperonin (cpn60), glucose-6-phosphate isomerase (gpi), and RNA polymerase sigma factor (rpoD).

2.3. Detection of Resistance-Associated and Coding Efflux Pumps Genes

The evaluation of resistance-associated genes was carried out through single PCR assays with 25 μL volume reactions, with 2 μL DNA template and specific primers at 0.5–1 μM concentration according to previous protocols. In particular, the presence of class D carbapenemases known as OXA β-lactamases, including the blaOXA-23 and blaOXA-24 [18] genes, and blaOXA-51 and blaOXA-58 [19] was investigated, as well as blaIMP, blaVIM, and blaNDM-1 among class B carbapenemases or metallo β-lactamases [20,21], and blaAmpC among class C carbapenemases [22]. Furthermore, the genes coding for the main efflux pumps were evaluated, such as adeB [23], adeG [24] and adeJ (resistance-nodulation-cell division, RND family) [25], abeS (small multidrug resistance protein, SMR family) [26], craA (major facilitator superfamily, MFS family) and abeM (multidrug and toxic compound extrusion, MATE family) [27], and soxR (negative regulator of efflux pumps) [26].

3. Results

3.1. Characteristics of Strains and Patients and Antimicrobial Susceptibility

Forty-five strains were included in this study. The age of the patients from which the A. baumannii strains were isolated causing HAI was on average 67 ± 16 years (median 69 years; range 29–90). The isolates were mainly from males (n = 29, 64.4%), from patients admitted in the ICU (n = 34, 75.6%), and from bronchial aspirate (n = 27, 60%), followed by blood (n = 8, 17.8%) and urine culture (n = 4, 8.9%) (Table 1). The A. baumannii isolates exhibited multi-resistance profiles that were highly similar, with 19 resistoypes identified and a Simpson’s index of diversity of 0.92 (Table 2).
Overall, the resistance profiles were similar according to the isolation period, as ten and nine different resistotypes were observed for strains isolated in 2010 and during 2014–2018, respectively. The common results were that all strains tested for susceptibility to Imipenem (IMP), Meropenem (MEM), Amoxicillin-Clavulanate (AMC), Amikacin (AMK), Ciprofloxacin (CIP) and Levofloxacin (LVX) were resistant, while all were susceptible to Colistin (COL) (Table 2). Furthermore, all the 44 strains tested for Cefotaxime (CTX), 43 for Piperacillin-Tazobactam (PIP-TZ), 42 for both Ceftazidime (CAZ) and Cefepime (FEP), 41 for Ampicillin (AMP), 29 for Aztreonam (ATM), 24 for Trimethoprim (TMP), 21 for Ertapenem (ETP), Cefuroxime (CFX), Tobramycin (TOB) and Trimethoprim/Sulfamethoxazole (SXT), 20 for Fosfomycin (FO), 18 for both Tetracycline (TET) and Cefoxitin (CTZ), 16 for Piperacillin (PIP), 15 for Chloramphenicol (CHL), 13 for Cefazolin (CFZ), and 4 for Tigecycline (TGC) showed resistance. In addition, 37 out of 45 isolates (82.2%) showed resistance to Gentamicin (GEN), as eight were susceptible (Table 2).

3.2. PFGE Analysis

The dendrogram generated with AscI revealed eleven clusters (I–XI) at an 80% similarity level (Figure 1), with a clear separation between isolates from different periods, I–V vs. VI–XI. Overall, the largest groups were IV and X including sixteen and thirteen strains isolated in 2010 and during 2014–2018, respectively. Twenty-three pulsotypes (PTs) were identified at 95% (PT1-PT23), and Simpson’s index was 0.96.
The most prevalent were PT7 and PT21, each related to five strains (AC14, AC16, AC20, AC22, AC38, all isolated in 2010 and from the ICU; and ACCB25, ACCB30, ACCB26, ACCB28, ACCB29, isolated during 2014–2018 and from the ICU, Internal Medicine, and Infectious Diseases wards), followed by PT4 and PT18 each correlated to four isolates (Figure 1).
Only three clusters were identified in the ApaI-based dendrogram at 80% cut-off (I-III) (Figure 2). Similarly to AscI, the isolates were grouped depending on the isolation period. Indeed, all the isolates in 2010 were grouped together in cluster I, with the only exception of ACCB14 isolated in 2016, while the strains related to the period 2014–2018 were grouped in clusters II and III (with 12 and 8 strains, respectively). Simpson’s index was 0.93. Among the 45 isolates, eighteen PTs were observed (PT1-PT18), with PT4 as the most prevalent related to six isolates (AC33, AC38, AC25, AC29, AC28, AC30 all from ICU), followed by PT1, PT2, PT7 and PT11, each related to five isolates (Figure 2).

3.3. Typing by MLST

MLST analysis of the 45 A. baumannii strains revealed only five STs (Table 3) and Simpson’s index of diversity was 0.766. Of these, ST1720 (allelic combination of 7 genes: 1-3-3-102-2-102-3) and ST369 (1-3-3-2-2-106-3) were similarly prevalent (n = 14, each 31.1%), followed by ST218 (n = 8; 17.8%), ST281 (n = 7, 15.6%) and ST513 (n = 2; 4.5%). In detail, the STs identified were different considering the isolation period, since three STs, ST1720 (58.3%), ST218 (33.3%), and ST513 (8.4%) were associated with the 24 strains of 2010, and only two were related to strains isolated during 2014–2018, with ST369 as the most frequent (66.7%) followed by ST281 (33.3%). Amongst the two prevalent ST1720 and ST369, there were two allelic differences found for recA (102 vs. 2) and gpi (102 vs. 106). Furthermore, ST218 and ST513 were observed as the monoallelic variants of ST1720 for recA (2 vs. 102 and 62 vs. 102, respectively).
The relationship between PFGE and MLST was assessed using the Comparing Partitions program (http://www.comparingpartitions.info/, accessed on 12 January 2025) and through the Adjusted Wallace coefficient, providing an easily interpretated agreement between partitions. In detail, the data obtained were Wallace PFGE AscI → ST = 0.502 (95%CI 0.339–0.666) and Wallace ST → PFGE = 0.073 (95%CI 0.000–0.149). In addition, it was observed that Wallace PFGE ApaI → ST = 0.498 (95%CI 0.308–0.687) and Wallace ST → PFGE = 0.114 (95%CI 0.027–0.201).

3.4. Prevalence of Resistance-Associated Genes

All A. baumannii harbored the blaOXA-23, blaOXA-51, and blaAmpC genes. On the contrary, blaOXA-24 and blaOXA-58 were not identified, as well as blaVIM, blaIMP, and blaNDM-1. For genes encoding for the efflux pumps, all the strains showed the presence of adeB, adeJ, adeG, abeS, and soxR, while the lack of abeM and craA genes was observed.

4. Discussion

Carbapenem-resistant A. baumannii (CRAb) is a top-priority pathogen responsible for nosocomial infections associated with increased morbidity and mortality and raising global alarm for treatment regimens [28]. Generally, CRAb can acquire various resistance genes circulating in the hospital environment and cause outbreaks difficult to control, due to their survival for prolonged periods on dry surfaces and diffusion by asymptomatic colonization, contaminating both the environment and the hands of healthcare workers [1]. Hence, both in the ICU and non-ICU wards, stringent adherence to infection control practices (IPC) is crucial to discontinue the transmission.
This study relies on clinical CRAb collected in different periods from the main hospital in the Molise region, central Italy, and provides insights into antimicrobial resistance. Most importantly, it describes the genetic characteristics underlying inter-strain relationships over time in an area never investigated before for this pathogen. Most strains (75.6%) were from the ICU, as reported in a recent review reporting data between 2002 and 2018 from 22 Italian cities [12]. Its spread represents a major issue that the COVID-19 pandemic has even worsened [29,30]. However, it should be underlined that isolation in wards other than the ICU has become frequent in recent years, especially in Internal Medicine, Infectious Diseases, and Nephrology. According to other reports [31,32], the respiratory tract was the most common site of infections, which further significantly occurred more in males (60%) than in female patients (40%).
All the isolates in this study were resistant to carbapenems (Imipenem, Meropenem, and Ertapenem), but resistance to numerous other antibiotics was also observed, including penicillins (Ampicillin, Amoxicillin-Clavulanate, Piperacillin, Piperacillin/Tazobactam), cephalosporins (Ceftazidime, Cefotaxime, Cefepime, Cefazolin, Cefuroxime), fluoroquinolones (Ciprofloxacin, Levofloxacin), aminoglycosides (Amikacin, Tobramycin), and monobactams (Aztreonam). Indeed, it has been reported that the prevalence of MDR A. baumannii in patients with hospital-acquired pneumonia ranges from 40% to 95% [33,34]. Resistance to carbapenems is generally conferred through OXA-type carbapenemases that are ubiquitous worldwide and are found both on plasmids and chromosomes [28]. In our study, all strains co-harbored the OXA types blaOXA-23 and blaOXA-51, which have been identified among CRAb isolates from hospitals [35]. As reported in Italian hospitals from multiple cities [12], the blaOXA-23 gene became more prevalent than blaOXA-58 among epidemic international clone II (ICL-II) strains. Together with these genes, studies further reported the presence of blaOXA-24 and blaOXA-58 [12,36,37], which, however, were not identified among the tested isolates, similar to another Italian study [38]. Anyway, the prevalence of blaOXA-23 was widely expected since outbreaks due to CRAb reported in Italy were mostly characterized by the production of this carbapenemase [31,39,40], leading over time to a drastic reduction of blaOXA-58 [40], which was not detected among the strains analyzed. Although more frequently associated with MDR in Klebsiella pneumoniae [41,42], metallo-beta-lactamase genes were also identified in A. baumannii, including IMP (imipenemase), VIM (Verona integron-encoded metallo-beta-lactamase), and NDM (New-Delhi metallo-beta-lactamase) [28,32], but were totally absent among CRAb tested in the present study.
Simultaneously to carbapenem-hydrolyzing oxacillinases OXA-23 and OXA-51, all the strains harbored blaAmpC, confirming its contribution in the mechanisms of resistance to oximino-cephalosporins (Ceftazidime and Cefotaxime). AmpC was also reported to contribute to resistance towards penicillins and beta-lactamase inhibitors [43]. Furthermore, the hyperproduction of AmpC-lactamases and the overexpression of efflux pumps may confer carbapenems resistance in a synergistic manner and represent a successful strategy for the pathogen in the survival and adaptation in the hospital environment [28]. Among the aims of the present work, the prevalence of genes encoding the main efflux pumps in A. baumannii was also evaluated, although the determination of the expression levels would have provided a clearer picture of their involvement in antibiotic resistance mechanisms. Indeed, it has been reported that resistance mediated by efflux pumps, particularly by the RND family largely distributed in A. baumannii, significantly contributes to reduced susceptibility to multiple antibiotics when overexpressed [23]. Genes belonging to this family, such as adeB, adeG, and adeJ, were found in all the strains examined, supporting their wide distribution and association with antibiotic resistance [44]. Among the other genes, only abeS, belonging to the SMR family, was found in all the strains, which could be linked to the resistance towards Amikacin, Chloramphenicol, and Ciprofloxacin [45]. Conversely, the abeM (MATE family) and craA (MFS family) genes were always absent, suggesting that they minimally affect resistance towards Chloramphenicol, Imipenem, and Fluoroquinolones.
In this study, to investigate CRAb epidemiology, PFGE and MLST were used as they are still the traditional and widely considered methods. However, more recently, core-genome multi-locus sequence typing (cgMLST) has become the suitable typing method to trace phylogenetic relationships and investigate outbreaks [46]. Clinical A. baumannii isolates from different countries were extensively reported to belong to ICLs-I, II, and III, with ICL-II typically accounting for most strains [47], including Italy [12]. Isolates from ICL-II displayed greater resistance to antimicrobial agents than non-ICL-II, harboring more resistance genes and mobile elements [48]. In the present study, PFGE enabled the separation of strains according to the isolation period. The dendrogram analysis through ApaI highlighted a higher similarity between the strains compared to AscI, generating three clusters and 18 PTs compared to eleven clusters and 23 PTs, respectively. Overall, through AscI-restriction, thirty-one strains had the same pulsovar into specific groups. For example, PT7 and PT21 were each related to five strains, followed by PT4 and PT18, both linked to four strains (Figure 1), indicating an indistinguishable PFGE band pattern, thus the isolates could likely be considered to represent the same strain [49]. Similarly, with ApaI digestion, other pulsovars were associated with more than two strains, for a total of twenty-six strains. For example, PT4 was related to six isolates and PT1, PT2, PT7, and PT11 to five (Figure 2). For many bacterial species, it has been reported that isolates indistinguishable by PFGE are unlikely to demonstrate substantial differences by other typing techniques [49], otherwise, they could be classified as closely related (two to three band differences), possibly related (four to six band differences), and unrelated (seven or more band differences).
The MLST revealed only five STs, whose distribution also varied based on the isolation period. Indeed, ST1720 and ST369 were the most prevalent for strains isolated in 2010 and during 2014–2018, respectively; furthermore, ST218 and ST513 were only detected among strains isolated in 2010, as well as ST281 for those during 2014–2018. These findings could be explained by highly related strains that were reported to widely circulate in the hospital environment [50] and were also supported by the same or very similar MDR profile and, in most cases, even by the same pulsovar. Of note, the strains isolated in wards such as Nephrology, Infectious Diseases, or Internal Medicine, belonged to the same STs observed for those from ICU, which were more represented in the study sample, suggesting the presence of dominant clones and a close genetic relationship among the isolates.
Some of the abovementioned STs were not previously reported among CRAb isolates in Italy, except for ST281, which was prevalent in recent study using the Oxford scheme in Italy [10]. The partial inconsistency could be attributed to the availability of two MLST schemes for A. baumannii, the Pasteur and the Oxford scheme, with the latter suffering from some troubles. Hence, isolates assigned to ICL-II and ST78 clonal lineages were mainly found in Italian hospitals [10]. ST369 belonging to ICL-II was found elsewhere [51] and mainly recovered from patients admitted to the ICUs and was linked to greater virulence and higher mortality rate than other STs in a mouse infection model [52]. Furthermore, ST218 was reported in A. baumannii isolated from tracheobronchial aspirate of mechanically ventilated adult patients admitted to the ICU of a Spanish tertiary hospital during 2010–2011 [53].
As observed, the MLST data were not always in concordance with the PFGE profiles obtained for each enzyme, as previously reported [54], since strains with identical PT were assigned to different STs (Figure 1 and Figure 2), with some exceptions. For example, with AscI, PT21 was assigned for five strains all with ST369, while PT7 was linked to ST1720 for three strains and to ST218 for two strains. Furthermore, PT1 observed through ApaI digestion was linked to ST218 for three strains and to ST1720 for the remaining two, and this was similarly observed for PT2 and PT7, while all strains assigned with PT11 were linked to ST369.
The relationship between PFGE and MLST was assessed by calculating the Adjusted Wallace coefficient, which is more informative than other coefficients, providing an easily interpretable agreement between partitions (http://www.comparingpartitions.info/, accessed on 12 January 2025). Data revealed that if two strains were in the same cluster by PFGE with AscI, they had a 50% chance of having the same ST, while conversely, about a 7.3% chance. In addition, if two strains were in the same cluster by PFGE with ApaI, they had about a 50% chance of having the same ST, while conversely, an 11% chance. This reflects the fact that PFGE is more discriminatory than ST.
The observations based on PFGE and MLST results hamper the conclusion about the definitive presence of outbreaks. Therefore, outbreak investigations typically rely on spatiotemporal data, and a previous study comparing the chains of transmission of a CRAb outbreak demonstrated that using PFGE and WGS, many similarities but also major differences were found with both investigations [55]. Indeed, it is unusual to assign different PTs to strains with no single nucleotide variant, although A. baumannii can undergo significant horizontal gene transfer and genetic recombination, even over short time periods [56]. Furthermore, with A. baumannii, PFGE may be too discriminatory between isolates and distort the interpretation of phylogenetic differences, leading to “false-negative” results where WGS data may provide indistinguishable differences [55]. Using WGS subsequent to PFGE, it was observed that two epidemiologically unlinked outbreaks were genetically connected [57], and in another case, WGS allowed for the identification of unexpected transmission routes not initially suggested by the epidemiologic PFGE data [58]. Therefore, further investigations are warranted to deeply understand the relationship between the strains, also considering their MDR profiles.

5. Conclusions

In conclusion, A. baumannii, showing intrinsic resistance to multiple antibiotics, continues to be recognized among the leading causes of HAIs, especially in ICUs, further worsened by its high persistence in the environment, allowing rapid spread. This study showed that the CRAb isolates were phenotypically resistant to multiple classes of antibiotics, including carbapenems, but were susceptible to colistin. The carbapenem-hydrolyzing oxacillinases OXA-23 and OXA-51 were the dominant carbapenemase, but simultaneously all the strains harbored the blaAmpC gene. Although more recently WGS-based typing is increasingly used, PFGE and MLST are classical methods used in hospital infection surveillance and molecular epidemiology investigations, which allowed the grouping of the examined strains and identification of clusters. Indeed, the study of A. baumannii epidemiology could involve MLST analysis to categorize isolates from common lineages, followed by PFGE for fine-scale typing. However, the definition of outbreaks needs further investigations using a WGS-based technique. Furthermore, in this context, more recent data from strains would help to assess changes in STs or permanently present STs in the same hospital. The isolation of MDR strains over time underlines the need for implementing better strategies in the study setting for rapid identification and effective control, supported by valuable information achieved from molecular typing methods to enhance surveillance for both outbreak control and AMR contrast. These points could be helpful for health policymakers to improve the implemented IPC measures.

Author Contributions

Conceptualization, M.T. and G.R.; methodology, M.T.; validation, M.T. and M.L.S.; formal analysis, M.T. and M.L.S.; investigation, A.L.; resources, G.R.; data curation, A.L. and M.L.S.; writing—original draft preparation, M.T.; writing—review and editing, G.R. and M.L.S.; supervision, G.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

This study includes all data, although the authors are available for further explanations. This was a non-interventional study, and the main findings were related to strains collected within the “alert organisms” surveillance system established in the hospital, hence for patient data anonymity was assured. Since this study focused on the molecular characterization of bacterial isolates, the research did not involve humans, and ethical approval from an ethics committee was not required.

Conflicts of Interest

The authors declare no conflicts of interest.

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Applmicrobiol 05 00009 g001
Figure 1. AscI-based dendrogram for 45 A. baumannii isolates including PTs, clusters, and STs.
Figure 1. AscI-based dendrogram for 45 A. baumannii isolates including PTs, clusters, and STs.
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Applmicrobiol 05 00009 g002
Figure 2. ApaI-based dendrogram for 45 A. baumannii isolates including PTs, clusters, and STs.
Figure 2. ApaI-based dendrogram for 45 A. baumannii isolates including PTs, clusters, and STs.
Applmicrobiol 05 00009 g002
Table 1. Selection of A. baumannii strains and characteristics of patients.
Table 1. Selection of A. baumannii strains and characteristics of patients.
StrainsSamplesSexPatient AgesWardsCollection Dates
AC1Bronchial aspirateFemale78ICUApril 2010
AC2Bronchial aspirateMale53ICUMay 2010
AC3NephrostomyMale90NephrologyJune 2010
AC4Bronchial aspirateFemale90ICUJune 2010
AC5Bronchial aspirateFemale77ICUJune 2010
AC6Bronchial aspirateFemale79ICUJune 2010
AC7Bronchial aspirateMale74ICUJuly 2010
AC8Bronchial aspirateMale50ICUJuly 2010
AC11Urine cultureMale65ICUAugust 2010
AC12Bronchial aspirateMale80ICUAugust 2010
AC14Bronchial aspirateMale30ICUAugust 2010
AC15Bronchial aspirateFemale58ICUSeptember 2010
AC16Bronchial aspirateMale49ICUSeptember 2010
AC19Bronchial aspirateFemale74ICUOctober 2010
AC20Bronchial aspirateMale69ICUOctober 2010
AC22Bronchial aspirateFemale74ICUOctober 2010
AC25Bronchial aspirateMale45ICUOctober 2010
AC27Bronchial aspirateMale84ICUOctober 2010
AC28Bronchial aspirateFemale88ICUNovember 2010
AC29Bronchial aspirateMale57ICUNovember 2010
AC30Bronchial aspirateFemale75ICUNovember 2010
AC33Bronchial aspirateMale42ICUNovember 2010
AC38Bronchial aspirateMale52ICUNovember 2010
AC39Bronchial aspirateMale87ICUNovember 2010
ACCB2Central venous catheterMale78NephrologyJuly 2014
ACCB6Bladder catheterMale57ICUAugust 2014
ACCB7Bronchial aspirateFemale73ICUAugust 2014
ACCB9Central venous catheterMale29ICUAugust 2014
ACCB11Bladder catheterMale79ICUAugust 2014
ACCB14Bronchial aspirateMale61ICUFebruary 2016
ACCB15Bronchial aspirateMale64ICUJanuary 2017
ACCB16Bronchial aspirateMale82ICUJanuary 2017
ACCB17Bronchial aspirateMale75ICUJanuary 2017
ACCB19Blood cultureMale69Internal MedicineApril 2017
ACCB20Blood cultureMale56Internal MedicineApril 2017
ACCB21Urine cultureMale31ICUJanuary 2018
ACCB22Blood cultureMale58NephrologyFebruary 2018
ACCB23Blood cultureFemale62ICUMarch 2018
ACCB24Urine cultureFemale89Internal MedicineJuly 2018
ACCB25Blood cultureMale66 Internal MedicineJuly 2018
ACCB26Blood cultureFemale77Infectious DiseasesJune 2018
ACCB27Urine cultureFemale56NephrologyJuly 2018
ACCB28Blood cultureFemale84Internal MedicineJuly 2018
ACCB29Blood cultureFemale57Internal MedicineAugust 2018
ACCB30Rectal swabMale86ICUSeptember 2018
Table 2. Antimicrobials susceptibility in A. baumannii strains ordered based on resistotypes.
Table 2. Antimicrobials susceptibility in A. baumannii strains ordered based on resistotypes.
StrainsIMPMEMAMPAMCPIPPIP-TZCAZCTXFEPCFZCTZAMKGENCIPLVXATMTETCOLCHLTMPETPCFXFOTOBSXTTGCResistotype
AC1RRRRRRRRRRRRRRRRRSRR 1
AC3RRRRRRRRRRRRRRRRRSRR 1
AC7RRRRRRRRRRRRRRRRRSRR 1
AC8RRRRRRRRRRRRRRRRRSRR 1
AC14RRRRRRRRRRRRRRRRRSRR 1
AC15RRRRRRRRRRRRRRRRRSRR 1
AC16RRRRRRRRRRRRRRRRRSRR 1
AC20RRRRRRRRRRRRRRRRRSRR 1
AC2RRRRRRRRRRRRSRRRRSRR 2
AC4RRRRRRRRRRRRSRRRRSRR 2
AC6RRRRRRRRRRRRSRRRRSRR 2
AC19RRRRRRRRRRRRSRRRRSRR 2
AC12RRRRRRRRR RSRRRRSRR 3
AC5RR RRRRRR RSRRRRSRR 4
AC 39RRRR RRRR RRSRRR S R 5
AC22RRRR RRRR RRRRRR S R 6
AC 27RRRR RRRR RRRRRR S R 6
AC30RRRR RRRR RRRRRR S R 6
AC33RRRR RRRR RRRRRR S R 6
AC28RR R RRRR RRRRRR S R 7
AC29RRRR RRRR RRRRR S R 8
AC25RR R RRRR RRRRR S R 9
AC38RR R RRRR RRRRR S R 9
AC11RRRRRR R RRRRRRSRR 10
ACCB2RRRR RRRR RRRRR S RRRRRR11
ACCB6RRRR RRRR RRRRR S RRRRRR11
ACCB7RRRR RRRR RRRRR S RRRRRR11
ACCB9RRRR RRRR RRRRR S RRRRRR11
ACCB11RRRR RRRR RRRRR S RRRRRR11
ACCB20RRRR RRRR RRRR S RRRRR 12
ACCB23RRRR RRRR RRRR S RRRRR 12
ACCB24RRRR RRRR RRRR S RRRRR 12
ACCB25RRRR RRRR RRRR S RRRRR 12
ACCB26RRRR RRRR RRRR S RRRRR 12
ACCB27RRRR RRRR RRRR S RRRRR 12
ACCB28RRRR RRRR RRRR S RRRRR 12
ACCB29RRRR RRRR RRRR S RRRRR 12
ACCB14RRRRRRRRR RRRR S RRRRR 13
ACCB15RRRR RRR RRRR S RRRRR 14
ACCB16RRRR R RR RRRR S RRRRR 15
ACCB17RRRR RRRR RRRR S RR RR 16
ACCB19RRRR RRRR RSRR S RRRRR 17
ACCB21RRRR RRRR RRRR S RRRRR 17
ACCB22RRRR R RRRR S RRRRR 18
ACCB30RRRR RRR RRRR S RRRRR 19
N. strains454541451643424442131845454545291545152421212021214
Abbreviations: R: Resistant; S: Sensitive; empty square: untested antibiotic; IMP: Imipenem; MEM: Meropenem; AMP: Ampicillin; AMC: Amoxicillin-Clavulanate; PIP: Piperacillin; PIP-TZ: Piperacillin-Tazobactam; CAZ: Ceftazidime; CTX: Cefotaxime; FEP: Cefepime; CFZ: Cefazolin; CTZ: Cefoxitin; AMK: Amikacin; GEN: Gentamicin; CIP: Ciprofloxacin; LVX: Levofloxacin; ATM: Aztreonam; TET: Tetracycline; COL: Colistin; CHL: Chloramphenicol; TMP: Trimethoprim; ETP: Ertapenem; CFX: Cefuroxime; FO: Fosfomycin; TOB: Tobramycin; SXT: Trimethoprim/Sulfamethoxazole; TGC: Tigecycline.
Table 3. Allelic designation and ST identified among 45 A. baumannii strains.
Table 3. Allelic designation and ST identified among 45 A. baumannii strains.
StrainsWardsgltAgyrBgdhBrecAcpn60gpirpoDST
AC1ICU133102210231720
AC2ICU133102210231720
AC3Nephrology133102210231720
AC4ICU133221023218
AC5ICU133102210231720
AC6ICU133102210231720
AC7ICU133102210231720
AC8ICU133221023218
AC11ICU133221023218
AC12ICU133102210231720
AC14ICU133102210231720
AC15ICU133221023218
AC16ICU133102210231720
AC19ICU133221023218
AC20ICU133102210231720
AC22ICU133221023218
AC25ICU133102210231720
AC27ICU133221023218
AC28ICU133102210231720
AC29ICU133102210231720
AC30ICU133102210231720
AC33ICU1336221023513
AC38ICU133221023218
AC39ICU1336221023513
ACCB2 Nephrology117322993281
ACCB6ICU117322993281
ACCB7ICU117322993281
ACCB9ICU117322993281
ACCB11ICU133221063369
ACCB14ICU133221063369
ACCB15ICU133221063369
ACCB16ICU133221063369
ACCB17ICU133221063369
ACCB19Internal Medicine133221063369
ACCB20Internal Medicine133221063369
ACCB21ICU117322993281
ACCB22Nephrology133221063369
ACCB23ICU117322993281
ACCB24Internal Medicine133221063369
ACCB25Internal Medicine133221063369
ACCB26Infectious Diseases133221063369
ACCB27Nephrology117322993281
ACCB28Internal Medicine133221063369
ACCB29Internal Medicine133221063369
ACCB30ICU133221063369
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Tamburro, M.; Lombardi, A.; Sammarco, M.L.; Ripabelli, G. Molecular Epidemiology Revealed Distinct Patterns Among Multidrug Resistant Clinical Acinetobacter baumannii Strains in Different Periods in the Main Hospital in Molise Region, Central Italy. Appl. Microbiol. 2025, 5, 9. https://doi.org/10.3390/applmicrobiol5010009

AMA Style

Tamburro M, Lombardi A, Sammarco ML, Ripabelli G. Molecular Epidemiology Revealed Distinct Patterns Among Multidrug Resistant Clinical Acinetobacter baumannii Strains in Different Periods in the Main Hospital in Molise Region, Central Italy. Applied Microbiology. 2025; 5(1):9. https://doi.org/10.3390/applmicrobiol5010009

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Tamburro, Manuela, Adele Lombardi, Michela Lucia Sammarco, and Giancarlo Ripabelli. 2025. "Molecular Epidemiology Revealed Distinct Patterns Among Multidrug Resistant Clinical Acinetobacter baumannii Strains in Different Periods in the Main Hospital in Molise Region, Central Italy" Applied Microbiology 5, no. 1: 9. https://doi.org/10.3390/applmicrobiol5010009

APA Style

Tamburro, M., Lombardi, A., Sammarco, M. L., & Ripabelli, G. (2025). Molecular Epidemiology Revealed Distinct Patterns Among Multidrug Resistant Clinical Acinetobacter baumannii Strains in Different Periods in the Main Hospital in Molise Region, Central Italy. Applied Microbiology, 5(1), 9. https://doi.org/10.3390/applmicrobiol5010009

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