Infections caused by resistant strains of Acinetobacter baumannii are now a global problem that requires the immediate development of new antimicrobial drugs. Combination therapy is one of the strategies used to solve this problem. Based on this information, the purpose of this study was to determine whether quercetin (QUE), in combination with three antibiotics, is effective against colistin-resistant A. baumannii strains (ColR-Ab). The effects of the combination of QUE with colistin (COL), amikacin (AMK), and meropenem (MEM) were evaluated according to the checkerboard synergy test. The combinations of QUE + COL and QUE + AMK showed synergistic activity on ColR-Ab strains with FICI values in the range of 0.1875–0.5 and 0.1875–0.2825, respectively. A 4- to 16-fold decrease in COL MIC and a 16- to 64-fold decrease in AMK MIC values were detected. Synergistic activity was confirmed by the time-kill test, and these combinations were found to be bactericidal at the end of 24 h. According to spectrophotometric measurements, the combinations of QUE + COL and QUE + AMK induced membrane damage, leading to the leakage of nucleic acids. Cell lysis and cell death were confirmed with SEM observations. The detected synergy offers an opportunity for the future development of treatment strategies for potential infections caused by ColR-Ab strains.

The human microbiome is increasingly recognized as a key determinant of health and disease, yet methodological variability continues to limit reproducibility and clinical translation of findings. This review synthesizes current approaches in microbiome research, critically evaluating each step from sampling to sequencing and downstream bioinformatics. Pre-analytical factors such as sample type, collection method, preservation, and storage conditions profoundly affect microbial community profiles and remain a major source of bias. Nucleic acid extraction protocols and quality assessment strategies are discussed with emphasis on optimized lysis techniques, contamination controls, and DNA yield evaluation. Advances in sequencing technologies are highlighted, including 16S rRNA amplicon sequencing, shotgun metagenomics, third-generation long-read platforms, and emerging single-cell and minimal-input methods, each with specific advantages and limitations in taxonomic and functional resolution. Bioinformatics pipelines for taxonomic profiling, variant detection, phylogenetic inference, and functional annotation are compared, with attention to widely used reference databases such as RefSeq, GTDB, and SILVA. Integrative multi-omics approaches, including metatranscriptomics, metabolomics, and genome-scale metabolic modeling, are presented as powerful tools for linking microbial community structure to host physiology and disease mechanisms. Despite these advances, the lack of standardized workflows across pre-analytical, sequencing, and computational steps continues to hinder inter-study comparability and biomarker validation. This review aims to provide a methodological framework that highlights both strengths and limitations of current technologies while underlining the need for harmonized protocols to ensure reproducibility and accelerate the translation of microbiome research into clinical practice.

The human microbiome, which encompasses microbial communities and their genetic material, significantly influences health and disease, including cancer. The urogenital microbiota, naturally present in the urinary and genital tracts, interact with factors such as age, lifestyle, and health conditions to affect homeostasis and carcinogenesis. Studies suggest that alterations in this microbiota contribute to the development and progression of genitourinary cancers, emphasizing the concept of oncobiome, which refers to microbial genetic contributions to cancer. Similarly, gut microbiota can influence hormone levels and systemic inflammation, impacting cancers such as cervical and prostate cancer. Advanced studies indicate that microbial communities in genitourinary cancers have distinct profiles that may serve as diagnostic biomarkers or therapeutic targets. Dysbiosis of the urinary microbiota correlates with bladder and kidney cancer. Additionally, gut microbiota influence the effectiveness of cancer treatments. However, further research is necessary to clarify causality, the role of microbial metabolites, and hormonal regulation. The aim of this review is to understand that these dynamics present opportunities for innovative cancer diagnostics and therapies, highlighting the need for integration of microbiology, oncology, and genomics to explore the role of microbiota in genitourinary cancers. For this, a comprehensive search of relevant databases was conducted, applying specific inclusion and exclusion criteria to identify studies examining the association between microbiota and urogenital cancers. Research into the mechanisms by which microbiota influence urogenital cancers may pave the way for new diagnostic and therapeutic approaches, ultimately improving patient outcomes.

Infections with multidrug resistant gram-negative bacteria is a growing problem especially in health care settings. Colistin is one of the last resort antibiotics for such infections in which treatment options are limited. Increasing resistance to colistin is a global problem. Clinical and Laboratory Standards Institute (CLSI) and the European Committee on Antimicrobial Susceptibility Testing (EUCAST) study groups have recommended the ISO-standard broth microdilution method (20776-1) as the reference method for the determination of colistin susceptibility. Since the broth microdilution method is not a practical method, it is rarely used in routine clinical microbiology laboratories, yet simple and accurate phenotypic detection methods for the determination of colistin resistance in routine microbiology laboratories are not precisely defined. The aim of this study was to evaluate BD Phoenix100 (Becton Dickinson, USA) system and colistin broth disk elution method for the detection of in vitro activity of colistin against gram-negative bacteria. A total of 419 gram-negative bacteria, including 199 Klebsiella pneumoniae, 163 Acinetobacter baumannii, 34 Escherichia coli, 20 Enterobacter spp., and three Citrobacter spp. isolates which were isolated from various clinical samples in our hospital between 2016-2018 were tested. The broth microdilution method was used as the reference method applying ISO-standard broth microdilution methods (20776-1) and CLSI/EUCAST recommendations. For colistin broth disk elution method, final concentrations of 0 (growth control), 1, 2 and 4 μg/ml were obtained by adding 10 μg colistin disks to four tubes containing 10 ml cation-adjusted Mueller Hinton broth per isolate. After incubation at room temperature for 30 minutes, 50 μl of standardized inoculum suspensions were added to the tubes. Colistin minimum inhibitor concentration (MIC) values were read visually after 16-20 hours of incubation at 35°C in ambient air. Manufacturer's recommendations were followed for BD Phoenix100 system. The categorical agreement between the reference broth microdilution method and the colistin broth disk elution method was 99.3%, very major error and major error rates were 0.2% and 0.5%, respectively. For BD Phoenix100 system, the categorical agreement was 95%, with a very major error rate of 5%. Our results showed that colistin broth disc elution method worked well compared to the reference broth microdilution method. The BD Phoenix100 system, with a high very major error rate, does not reliably distinguish colistin-resistant and colistin-susceptible strains.