Antibiotic resistance and biofilm formation of Acinetobacter baumannii isolated from high-risk effluent water in tertiary hospitals in South Africa

Eze, Emmanuel C.; Zowalaty, Mohamed E. El; Pillay, Manormoney

doi:10.1016/j.jgar.2021.08.004

Cited by 26 publications

(11 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…By analyzing the risk factors, the current study revealed that frequent hospitalisation was significantly associated to the production of carbapenemase among Acinetobacter baumanii (Ajusted-OR=16.53, P-value<0.0001). According to Pillay et al in South Africa in 2021, hospital effluents pose a potential risk of multidrug-resistant biofilm formation of Acinetobacter baumanii strains [13]. The impressive spread and prevalence of A. baumannii in healthcare settings has been facilitated by its ability to withstand dry and humid environments, its resistance to disinfectants and antibiotics, and its biofilm-forming property that leads to colonization of inert surfaces and medical devices [30].…”

Section: Discussionmentioning

confidence: 99%

“…A study done by Ogbulu et al in Nigeria in 2020 showed very high resistance (55.2%) of Acinetobacter baumanii to carbapenems following which low activity was observed only for colistin and amikacin [12]. According to Pillay et al in South Africa in 2021, hospital effluents constitute a potential risk of the formation of multi-resistant biofilm of Acinetobacter baumanii strains [13].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Phenotypic Characterization and Prevalence of Carbapenemase-Producing Acinetobacter baumanii Isolates in Four Health Facilities in Cameroon

Djuikoue¹,

Benhamed²,

Djoulako³

et al. 2023

Preprint

View full text Add to dashboard Cite

Carbapenems have long been considered as treatment of choice for Gram-Negative Bacteria (GNB) infections, and today the clinical utility of this class is threatened by the emergence and spread of resistance favored by its increasing use. According to the WHO, Acinetobacter baumannii, nosocomial infection agent, tops the list of priority antibiotic-resistant pathogens, considered to be the most risky for humans. This study sought to determine the prevalence of Acinetobacter baumannii strains producing carbapenemases in four health facilities in the Center and Littoral regions of Cameroon and the associated risk factors. An analytical cross-sectional study was conducted over a six-month period from January to June 2022. All Acinetobacter baumanii or suspected strains isolated from pathological samples at the bacteriology laboratory of different health facilities were systematically collected and underwent a re-identification. After successfully subculturing and growing on nutrient agar, re-identification and antimicrobial susceptibility Testing (AST) were performed using the VITEK 2 System and the Kirby-Bauer method according to the guidelines of the Clinical and Laboratory Standards Institute (CLSI). Detection and phenotypic characterization of carbapenemases was performed according to adequate standard procedures. A total of 168/226 clinical isolates of Acinetobacter baumannii were confirmed after re-identification of which 52.69% came from male patients, and 55.09% from participants aged between 10-39 years old and 46.71% from pus samples. A very high resistance rates to all families of antibiotics was noted except to colistin (10.2%). About 40.12% of these strains produced carbapenemases with 62.69% of class B and 37.31% of class A. In addition, frequent hospitalisation was significantly associated to the production of carbapenemase among Acinetobacter baumanii (Ajusted-OR=16.53, P-value<0.0001). This study highlighted the emergence of carbapenemase-producing Acinetobacter baumannii which is increasingly growing. Continuous drug-resistant monitoring and preventive measures could help to prevent and curb the dissemination of A.baumanii resistance genes, especially in hospital settings.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Phenotypic Characterization and Prevalence of Carbapenemase-Producing Acinetobacter baumanii Isolates in Four Health Facilities in Cameroon

Djuikoue¹,

Benhamed²,

Djoulako³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…tion [43,44]. In hospital settings, the effect of antibiotic resistance levels on bio-film f mation in carbapenem-resistant Gram-negative bacteria is a serious health-care issue [4 Hospital effluent water, living tissues such as skin, mucosa, and wounds, and medi equipment such as urinary catheters and other ventilator materials are the prima sources of biofilm formation [46][47][48]. Thus, we next investigated the biofilm inhibiti capacities of R-Pro9-3D on A. baumannii and CRAB C0 strains using crystal violet stainin Treatment with all Pro9-3 peptides, including melittin, and control antibiotics killed b film-forming A. baumannii for 16 h (Figure 4A).…”

Section: Effect Of Peptides On Killing Biofilm Forming Bacteriamentioning

confidence: 99%

Antiseptic 9-Meric Peptide with Potency against Carbapenem-Resistant Acinetobacter baumannii Infection

Krishnan

Choi

Jang

et al. 2021

IJMS

View full text Add to dashboard Cite

Carbapenem-resistant A. baumannii (CRAB) infection can cause acute host reactions that lead to high-fatality sepsis, making it important to develop new therapeutic options. Previously, we developed a short 9-meric peptide, Pro9-3D, with significant antibacterial and cytotoxic effects. In this study, we attempted to produce safer peptide antibiotics against CRAB by reversing the parent sequence to generate R-Pro9-3 and R-Pro9-3D. Among the tested peptides, R-Pro9-3D had the most rapid and effective antibacterial activity against Gram-negative bacteria, particularly clinical CRAB isolates. Analyses of antimicrobial mechanisms based on lipopolysaccharide (LPS)-neutralization, LPS binding, and membrane depolarization, as well as SEM ultrastructural investigations, revealed that R-Pro9-3D binds strongly to LPS and impairs the membrane integrity of CRAB by effectively permeabilizing its outer membrane. R-Pro9-3D was also less cytotoxic and had better proteolytic stability than Pro9-3D and killed biofilm forming CRAB. As an LPS-neutralizing peptide, R-Pro9-3D effectively reduced LPS-induced pro-inflammatory cytokine levels in RAW 264.7 cells. The antiseptic abilities of R-Pro9-3D were also investigated using a mouse model of CRAB-induced sepsis, which revealed that R-Pro9-3D reduced multiple organ damage and attenuated systemic infection by acting as an antibacterial and immunosuppressive agent. Thus, R-Pro9-3D displays potential as a novel antiseptic peptide for treating Gram-negative CRAB infections.

show abstract

“…Acinetobacter species are widely spread via the environmental milieu and may alarmingly spread antimicrobial resistance genes in the environment 14 , 15 . In addition, wastewater treatment plants (WWTPs) feed by hospital and municipal wastewater inflows have been reported to contribute multidrug-resistant (MDR), and extensively drug-resistant (XDR) Acinetobacter isolates to their effluents receiving waterbodies compared with other sources 15 , 16 . Discharging WWTP effluents increases the prevalence of Acinetobacter in the receiving river waterbodies and promotes antimicrobial resistance and transmission to irrigated vegetables 15 .…”

Section: Introductionmentioning

confidence: 99%

Machine learning-guided determination of Acinetobacter density in waterbodies receiving municipal and hospital wastewater effluents

Ekundayo

Adewoyin

Ijabadeniyi

et al. 2023

Sci Rep

View full text Add to dashboard Cite

A smart artificial intelligent system (SAIS) for Acinetobacter density (AD) enumeration in waterbodies represents an invaluable strategy for avoidance of repetitive, laborious, and time-consuming routines associated with its determination. This study aimed to predict AD in waterbodies using machine learning (ML). AD and physicochemical variables (PVs) data from three rivers monitored via standard protocols in a year-long study were fitted to 18 ML algorithms. The models’ performance was assayed using regression metrics. The average pH, EC, TDS, salinity, temperature, TSS, TBS, DO, BOD, and AD was 7.76 ± 0.02, 218.66 ± 4.76 µS/cm, 110.53 ± 2.36 mg/L, 0.10 ± 0.00 PSU, 17.29 ± 0.21 °C, 80.17 ± 5.09 mg/L, 87.51 ± 5.41 NTU, 8.82 ± 0.04 mg/L, 4.00 ± 0.10 mg/L, and 3.19 ± 0.03 log CFU/100 mL respectively. While the contributions of PVs differed in values, AD predicted value by XGB [3.1792 (1.1040–4.5828)] and Cubist [3.1736 (1.1012–4.5300)] outshined other algorithms. Also, XGB (MSE = 0.0059, RMSE = 0.0770; R2 = 0.9912; MAD = 0.0440) and Cubist (MSE = 0.0117, RMSE = 0.1081, R2 = 0.9827; MAD = 0.0437) ranked first and second respectively, in predicting AD. Temperature was the most important feature in predicting AD and ranked first by 10/18 ML-algorithms accounting for 43.00–83.30% mean dropout RMSE loss after 1000 permutations. The two models' partial dependence and residual diagnostics sensitivity revealed their efficient AD prognosticating accuracies in waterbodies. In conclusion, a fully developed XGB/Cubist/XGB-Cubist ensemble/web SAIS app for AD monitoring in waterbodies could be deployed to shorten turnaround time in deciding microbiological quality of waterbodies for irrigation and other purposes.

show abstract

Antibiotic resistance and biofilm formation of Acinetobacter baumannii isolated from high-risk effluent water in tertiary hospitals in South Africa

Cited by 26 publications

References 33 publications

Phenotypic Characterization and Prevalence of Carbapenemase-Producing <em>Acinetobacter baumanii </em>Isolates in Four Health Facilities in Cameroon<strong> </strong>

Phenotypic Characterization and Prevalence of Carbapenemase-Producing <em>Acinetobacter baumanii </em>Isolates in Four Health Facilities in Cameroon<strong> </strong>

Antiseptic 9-Meric Peptide with Potency against Carbapenem-Resistant Acinetobacter baumannii Infection

Machine learning-guided determination of Acinetobacter density in waterbodies receiving municipal and hospital wastewater effluents

Contact Info

Product

Resources

About