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ObjectiveUrinary tract infection (UTI) is an inflammatory response of the urothelium to bacterial invasion and is a common complication in patients with cutaneous ureterostomy (CU). For such patients, accurate and efficient identification of pathogens remains a challenge. The aim of this study included exploring utility of metagenomic next-generation sequencing (mNGS) in assisting microbiological diagnosis of UTI among patients undergoing CU, identifying promising cytokine or microorganism biomarkers, revealing microbiome diversity change and compare virulence factors (VFs) and antibiotic resistance genes (ARGs) after infection.MethodsWe performed a case-control study of 50 consecutive CU patients from December 2020 to January 2021. According to the clinical diagnostic criteria, samples were divided into infected group and uninfected group and difference of urine culture, cytokines, microorganism, ARGs and VFs were compared between the two groups.ResultsInflammatory responses were more serious in infected group, as evidenced by a significant increase in IFN-α (p=0.031), IL-1β (0.023) and IL-6 (p=0.018). Clinical culture shows that there is higher positive rate in infected group for most clinical pathogens like Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Candida auris etc. and the top three pathogens with positive frequencies were E. coli, K. pneumoniae, and Enterococcus faecalis. Benchmarking clinical culture, the total sensitivity is 91.4% and specificity is 76.3% for mNGS. As for mNGS, there was no significant difference in microbiome α- diversity between infected and uninfected group. Three species biomarkers including Citrobacter freundii, Klebsiella oxytoca, and Enterobacter cloacae are enriched in infected group based on Lefse. E. cloacae were significantly correlated with IL-6 and IL-10. K. oxytoca were significantly correlated with IL-1β. Besides, the unweighted gene number and weighted gene abundance of VFs or ARGs are significantly higher in infected group. Notablely, ARGs belonging to fluoroquinolones, betalatmas, fosfomycin, phenicol, phenolic compound abundance is significantly higher in infected group which may have bad effect on clinical treatment for patients.ConclusionmNGS, along with urine culture, will provide comprehensive and efficient reference for the diagnosis of UTI in patients with CU and allow us to monitor microbial changes in urine of these patients. Moreover, cytokines (IL-6, IL-1β, and IFN-a) or microorganisms like C. freundii, K. oxytoca or E. cloacae are promising biomarkers for building effective UTI diagnostic model of patients with CU and seriously the VFs and ARGs abundance increase in infected group may play bad effect on clinical treatment.

Objectives. To investigate the clinical diagnostic value of differential flora as biomarkers in patients with symptomatic urinary tract infection (UTI) and asymptomatic bacteriuria (ASB) undergoing cutaneous ureterostomy based on metagenomic next-generation sequencing and construct predictive models to provide a scientific reference for clinical diagnosis and treatment. Material and Methods. According to standard procedures, samples were taken from each patient for routine tests (urine, ureteral stent, and skin swab around the stoma). Cytokine levels in the blood were also detected. Urinary microflora were measured by mNGS, and potential biomarkers for distinguishing UTI and ASB were identified by differential flora. Finally, we generated the predictive models for ASB and UTI using the Lasso method and cytokine levels. Results. Urine culture was performed for 50 patients with cutaneous ureterostomy; 44 of these patients developed bacteriuria. The incidence of symptomatic bacteriuria was 54.55%. Biomarker analysis showed that Propionimicrobium lymphophilum, Staphylococcus haemolyticus, Stenotrophomonas maltophilia, Ralstonia insidiosa, and Aspergillus sydowii all had good predictive performance and were combined in a single model. The predictive model exhibited good prediction performance (area under the curve AUC = 0.8729 , sensitivity = 80 % , specificity = 83.3 % , and cutoff = 1.855 ). We also identified a significant negative correlation between the weight sum of the abundance for these five characteristic pathogens (Sum_weighted_Reads) and levels of the cytokine IL-6 and IL-1β ( P < 0.05 ). Conclusion. mNGS had a higher positive detection rate for pathogens in urine samples. The selected differential bacteria can be used as biomarkers of ASB and UTI, and the prediction model has good predictive performance. Analysis also showed that the occurrence of symptoms was related to individual immunity. Combined with the Sum_weighted_Reads cutoff and cytokine levels (IL-6 and IL-1β) of differential flora, it was possible to judge the severity of symptoms in cutaneous ureterostomy patients with bacteriuria and provide new insights for the treatment and intervention of ASB and UTI.

Diabetic foot infections (DFIs) represent a frequent complication of diabetes and a major cause of amputations. This study aimed to evaluate the utility of 16S rRNA gene sequencing for the rapid microbiological diagnosis of DFIs and to consistently characterize the microbiome of chronic diabetic foot ulcers (DFUs) and intact skin. Wound samples were collected by ulcer swabbing and tissue biopsy, and paired swabs of intact skin were collected from 10 patients with DFIs (five were moderately infected, and the other five were severely infected). Samples were analyzed by conventional culture and using Personal Genome Machine (PGM) 16S rRNA sequencing technology. The results showed that PGM technology detected significantly more bacterial genera (66.1 vs. 1.5 per wound sample, p &lt; 0.001); more obligate anaerobes (52.5 vs. 0%, p &lt; 0.001) and more polymicrobial infections (100.0 vs. 55.0%, p &lt; 0.01) than conventional cultures. There was no statistically significant difference in bacterial richness, diversity or composition between the wound swabs and tissues (p &gt; 0.05). The bacterial community on intact skin was significantly more diverse than that in DFUs (Chao1 value, p &lt; 0.05; Shannon index value, p &lt; 0.001). Gram-positive bacteria (67.6%) and aerobes (59.2%) were predominant in contralateral intact skin, while Gram-negative bacteria (63.3%) and obligate anaerobes (50.6%) were the most ubiquitous in DFUs. The most differentially abundant taxon in skin was Bacillales, while Bacteroidia was the bacterial taxon most representative of DFUs. Moreover, Fusobacterium (ρ = 0.80, p &lt; 0.01) and Proteus (ρ = 0.78, p &lt; 0.01) were significantly correlated with the duration of DFIs. In conclusion, PGM 16S rRNA sequencing technology could be a potentially useful technique for the rapid microbiological diagnosis of DFIs. Wound swabbing may be sufficient for sampling bacterial pathogens in DFIs compared with biopsy which is an invasive technique. The empirical use of broad-spectrum antibiotics covering Gram-negative obligate anaerobes should be considered for the treatment of moderate or severe DFIs.