Molecular diversity in fusidic acid-resistant Methicillin Susceptible Staphylococcus aureus.

Objectives: The recent emergence of fusidic acid (FA)-resistant Staphylococcus aureus has underscored the importance of active surveillance in isolating these strains. The molecular basis of fusidic acid resistance and the carriage of virulence factors in four borderline oxacillin-resistant Staphylococcus aureus (BORSA) clinical strains was assessed through phenotypical and genotypical methods. Methods: All S. aureus clinical strains were obtained from various hospital units in Sicily. In vitro antibiotic susceptibility testing was conducted. WGS was performed using the Illumina MiSeq Platform, and data analysis was carried out to determine ST, resistome and virulome profiles. Results: Genotypic characterization revealed that the strains belong to four STs: ST630, ST8, ST15, and ST1. FA resistance was associated with mutations in the fusA gene or fusB and fusC genes. Additionally, one case exhibited resistance to mupirocin, related to the presence of the mupA gene. Borderline MIC values were observed for cefoxitin in three out of four cases, leading to their categorization as BORSA. Virulence gene content was complex and diversified, with one testing positive for the lukS/F genes, coding for PVL toxin. Conclusions: Resistance to FA is multifactorial, involving point mutations in chromosomal genes or association with mobile genetic elements. Monitoring the resistance to these antibiotics might help to manage and eradicate mupirocin- and FA-resistant S. aureus strains, which are also known to be important carriers of virulence determinants.

Prediction of antimicrobial resistance of Klebsiella pneumoniae from genomic data through machine learning.

Antimicrobials, such as antibiotics or antivirals are medications employed to prevent and treat infectious diseases in humans, animals, and plants. Antimicrobial Resistance occurs when bacteria, viruses, and parasites no longer respond to these medicines. This resistance renders antibiotics and other antimicrobial drugs ineffective, making infections challenging or impossible to treat. This escalation in drug resistance heightens the risk of disease spread, severe illness, disability, and mortality. With datasets now containing hundreds or even thousands of pathogen genomes, machine learning techniques are on the rise for predicting antibiotic resistance in pathogens, prediction based on gene content and genome composition. Aim of this work is to combine and incorporate machine learning methods on bacterial genomic data to predict antimicrobial resistance, we will focus on the case of Klebsiella pneumoniae in order to support clinicians in selecting appropriate therapy.

Advancing Pathogen Identification: The Role of Digital PCR in Enhancing Diagnostic Power in Different Settings.

Digital polymerase chain reaction (dPCR) has emerged as a groundbreaking technology in molecular biology and diagnostics, offering exceptional precision and sensitivity in nucleic acid detection and quantification. This review highlights the core principles and transformative potential of dPCR, particularly in infectious disease diagnostics and environmental surveillance. Emphasizing its evolution from traditional PCR, dPCR provides accurate absolute quantification of target nucleic acids through advanced partitioning techniques. The review addresses the significant impact of dPCR in sepsis diagnosis and management, showcasing its superior sensitivity and specificity in early pathogen detection and identification of drug-resistant genes. Despite its advantages, challenges such as optimization of experimental conditions, standardization of data analysis workflows, and high costs are discussed. Furthermore, we compare various commercially available dPCR platforms, detailing their features and applications in clinical and research settings. Additionally, the review explores dPCR's role in water microbiology, particularly in wastewater surveillance and monitoring of waterborne pathogens, underscoring its importance in public health protection. In conclusion, future prospects of dPCR, including methodological optimization, integration with innovative technologies, and expansion into new sectors like metagenomics, are explored.

The molecular detection of carbapenem markers with a two-levels amplification screening protocol: epidemiological and resistome insights.

Objectives: Carbapenem-resistance is a challenging healthcare concern and require specific stewardship programs. Monitoring workflows include the identification from surveillance samples, such as rectal swabs. Although culture assays represent the gold standard, data report a significant effectiveness in detecting carbapenemases genes directly from rectal swabs. The aim of this study was to evaluate the REALQUALITY Carba-Screen kit (AB ANALITICA, Padova, Italy) in detecting carbapenemases genes directly from rectal swabs, also comparing its effectiveness to culture assays results. A next-generation sequencing (NGS) was performed to investigate the positive samples about resistance markers and sequence type (ST). Methods: A number of 136 rectal swabs were collected from the University Hospital Policlinico of Catania critical wards. The samples simultaneously underwent culture and molecular assays (REALQUALITY Carba-Screen kit). The molecular method included two-steps. The first step (1 h and 6 min) rapidly excluded negative samples, while the second one (1 h and 6 min) included only positive samples for a resistance confirmation. All the positive culture samples underwent NGS analysis. Results: Statistical evaluations demonstrated high sensitivity (100%) and detection rates (92.6%) for the REALQUALITY Carba-Screen kit, which mostly correlated to the standard workflow. All the culture positive results matched the positive molecular results, which were mainly confirmed by the NGS resistome analysis. The identified ST appeared to be diversified and different from the clinically significative strains of the same setting, furnishing interesting epidemiological evidence. Conclusion: The molecular detection allowed a coordinate approach in a high-prevalence multi-drug-resistance area. The rapid identification with a multi-step procedure accelerated the infection control procedures, while the preliminary negative results reduced the overtreatment episodes. The molecular method efficacy was confirmed through the NGS. In conclusion, the molecular screening could initially lead to a more conservative approach, which may be reevaluated after a culture result about the microorganisms' identification and susceptibility profile.

Interactions of Gram-Positive Bacterial Membrane Vesicles and Hosts: Updates and Future Directions.

Extracellular vesicles (EVs) are lipid bilayers derived from cell membranes, released by both eukaryotic cells and bacteria into the extracellular environment. During production, EVs carry proteins, nucleic acids, and various compounds, which are then released. While Gram-positive bacteria were traditionally thought incapable of producing EVs due to their thick peptidoglycan cell walls, recent studies on membrane vesicles (MVs) in Gram-positive bacteria have revealed their significant role in bacterial physiology and disease progression. This review explores the current understanding of MVs in Gram-positive bacteria, including the characterization of their content and functions, as well as their interactions with host and bacterial cells. It offers a fresh perspective to enhance our comprehension of Gram-positive bacterial EVs.

Evaluation of the Effects of Heteroaryl Ethylene Molecules in Combination with Antibiotics: A Preliminary Study on Control Strains.

The discovery of compounds with antibacterial activity is crucial in the ongoing battle against antibiotic resistance. We developed two QSAR models to design six novel heteroaryl drug candidates and assessed their antibacterial properties against nine ATCC strains, including Enterococcus faecalis, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and also Salmonella enterica and Escherichia coli, many of which belong to the ESKAPE group. We combined PB4, a previously tested compound from published studies, with GC-VI-70, a newly discovered compound, with the best cytotoxicity/MIC profile. By testing sub-MIC concentrations of PB4 with five antibiotics (linezolid, gentamycin, ampicillin, erythromycin, rifampin, and imipenem), we evaluated the combination's efficacy against the ATCC strains. To assess the compounds' cytotoxicity, we conducted a 24 h and 48 h 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay on colorectal adenocarcinoma (CaCo-2) cells. We tested the antibiotics alone and in combination with PB4. Encouragingly, PB4 reduced the MIC values for GC-VI-70 and for the various clinically used antibiotics. However, it is essential to note that all the compounds studied in this research exhibited cytotoxic activity against cells. These findings highlight the potential of using these compounds in combination with antibiotics to enhance their effectiveness at lower concentrations while minimizing cytotoxic effects.