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.

Meticillin-resistant Staphylococcus aureus (MRSA) is one of the most important infectious agents. Therefore, fast and accurate diagnosis of MRSA is utmost important. Although mecA gene detection by PCR is reference method, conventional methods are preferred in routine practices due to simplicity. As conventional methods last 48-96 hours, several chromogenic media have been developed. Our objective was to compare the methods used for meticillin resistance detection with PCR. Forty-eight S. aureus strains isolated from various clinical specimens were included. Of the 48 S. aureus strains, 19 were mecA gene-positive and 29 were negative. mecA gene-positive 19 strains were also meticillin-resistant by automated system and disk diffusion. On chromogenic agar, 15 of 19 MRSA strains were meticillin-resistant and 4 were meticillin-sensitive. Twentynine mecA gene-negative strains were susceptible to meticillin by automatized system and disk diffusion. Among 29 mecA gene-negative MSSA strains inoculated on chromogenic agar, 17 were methicillin-resistant. According to our study, chromogenic media would be ineffective to detected to meticillin-resistance because of low sensitivity and specificity in routine.

Objective: With the demonstration that the bladder is not sterile, the relationship between bladder microbiota and urinary system diseases has begun to be investigated. The aim of our study is to investigate the relationship between overactive bladder (OAB) syndrome and bladder microbiota. Methods: A total of 20 OAB syndrome patients and 20 controls were included in the study. Urine samples were taken with a transurethral catheter. We developed a modified expanded quantitative urine culture method and inoculated them into anaerobic blood culture bottles and thioglycolate medium at the bedside. The MALDI-TOF MS system was used for bacterial identification. Results: Thirty-five bacteria were identified in the patient group and 30 in the control group. As a result of culture, 16 different genera and 29 different types of bacteria were identified. Staphylococcus (25.7%) was the most common bacterial genus in the patient group, followed by Streptococcus (17.1%) and Lactobacillus (14.3%). Lactobacillus (26.7%) was the most frequently detected bacterial genus in the control group, followed by Streptococcus (13.3%) and Enterococcus (13.3%). The rate of Staphylococcus epidermidis in the patient group (22.9%) was found to be significantly higher than in the control group (0%) (P = .006). In the patient group, Lactobacillus gasseri’s incidence (2.9%) was found to be significantly lower than in the control group (20.0%) (P = .042). Conclusion: Our study shows that patients with OAB have a significantly different microbiota compared to the control group.

Carbapenem-resistant Klebsiella pneumoniae (CR-Kp) is a major healthcare-associated pathogen, and the coexistence of different carbapenemases may complicate phenotypic detection and antimicrobial treatment. This study evaluated carbapenemase profiles in 123 CR-Kp isolates from two centers in Türkiye and compared the modified carbapenem inactivation method (mCIM) and EDTA-modified carbapenem inactivation method (eCIM) with multiplex real-time PCR targeting KPC, NDM, VIM, IMP, and OXA-48. Ceftazidime-avibactam (CZA) and colistin susceptibility were also assessed. Carbapenemase genes were detected in 122/123 isolates (99.2%), predominantly NDM + OXA-48 (45.5%), followed by OXA-48 alone (26.8%), KPC alone (18.7%), and NDM alone (8.1%). mCIM showed 99.2% sensitivity, whereas eCIM showed 87.7% sensitivity and 100% specificity for NDM detection. All eight false-negative eCIM results occurred among NDM + OXA-48 co-producing isolates (8/55), whereas no false-negative results were observed among isolates carrying NDM alone (0/10); this difference was not statistically significant (p = 0.339). CZA resistance was observed in 49.6% of isolates, with a higher likelihood of resistance among NDM-positive isolates in the exploratory analysis (OR, 9.03; 95% CI, 3.97–20.54; p < 0.001). Colistin resistance was observed in 36.6% of isolates, with no statistically significant association with carbapenemase profiles in the analyses performed. These exploratory findings suggest that combined molecular and phenotypic testing may be useful for carbapenemase characterization and highlight the occurrence of false-negative eCIM results in some NDM + OXA-48 co-producing isolates. Given the absence of adjustment for multiple comparisons, the observed associations should be interpreted cautiously and considered hypothesis-generating.

Purpose: Trichosporon species are part of the human microbiota. However, their presence in urine cultures may indicate invasive infection, particularly in immunocompromised individuals. This study aimed to identify Trichosporon spp. isolated from urine cultures of hospitalized patients at the species level and to determine their antifungal susceptibility profiles.Materials and Methods: Urine samples sent to the microbiology laboratory between June 1 and December 30, 2021, were cultured using standard microbiological methods. Yeast isolates suspected as Trichosporon spp. based on colony morphology and urease positivity were identified using the BD Phoenix™ 100 automated system and MALDI-TOF MS.Results: Trichosporon spp. was isolated from 29 of 16,011 urine samples (0.18%). Using the BD Phoenix™ Yeast ID system, 22 (75.9%) isolates were identified as Trichosporon asahii (T. asahii) and 7 (24.1%) as Trichosporon inkin (T. inkin), whereas all isolates were identified as T. asahii by MALDI-TOF MS. Antifungal susceptibility testing showed the lowest MIC values for voriconazole (MIC₅₀: 0.125 µg/ml; MIC₉₀: 0.25 µg/ml) and the highest MIC values for fluconazole (MIC₅₀: 32 µg/ml; MIC₉₀: >128 µg/ml).Conclusion: Antifungal susceptibility testing may contribute to guiding antifungal therapy and epidemiological surveillance. The BD Phoenix™ system may be useful for genus-level identification. However, further studies with molecular confirmation are required to assess species-level accuracy.