Frontiers in Cellular and Infection Microbiology最新文献

Objective: To investigate the role of the iron-sulfur cluster assembly factor SFU1 in the virulence-related traits of Candida albicans, particularly its function within the cariogenic cross-kingdom biofilm formed with Streptococcus mutans.

Methods: The SFU1 deletion and complemented strains were constructed. Their effects on growth, acid production, morphogenesis, metabolic activity, ROS accumulation, and biofilm formation of C. albicans were evaluated. The roles of SFU1 in the development, architecture, and spatial distribution of the C. albicans-S. mutans dual-species biofilm were further analyzed. The cariogenic metabolite profile and matrix synthesis were assessed by measuring lactic acid production, lactate dehydrogenase activity, extracellular polysaccharide content, and expression levels of related genes.

Results: The SFU1 deletion strain exhibited inhibited hyphal formation, reduced metabolic activity, elevated intracellular ROS levels, impaired biofilm formation, and downregulated expression of hyphal and adhesion-related genes (ALS3, EFG1, UME6). In the cross-kingdom biofilm, the sfu1/sfu1 mutant failed to form hyphal networks, resulting in loose biofilm architecture, reduced biomass, and poor integration of S. mutans. Furthermore, the dual-species biofilm showed significantly decreased lactic acid and EPS production. Co-cultured S. mutans exhibited downregulated expression of EPS synthesis genes (gtfB/C) and upregulated expression of EPS degradation genes (dexA/B).

Conclusion: SFU1 modulates hyphal development, redox homeostasis, and biofilm formation in C. albicans, thereby profoundly affecting its pathogenic synergy with S. mutans. SFU1 deletion leads to disrupted architecture and attenuated cariogenic virulence of the dual-species biofilm. This study reveals the potential value of targeting fundamental metabolic pathways in C. albicans to interfere with the cariogenicity of cross-kingdom biofilms, and provides a novel perspective for the prevention and therapy of dental caries.

Background: The carbapenem antibiotic meropenem is often used to treat life-threatening infections caused by Pseudomonas aeruginosa. Previous studies have shown that the susceptibility of P. aeruginosa to carbapenems is differentially regulated by the RNA chaperone Hfq, depending on the availability of preferred or less preferred carbon sources, a mechanism known as carbon catabolite repression (CCR). In this regulation, Hfq plays a CCR-conditioned repressive role on outer membrane porins that act as entry ports for carbapenems. In this study, we investigated whether meropenem response is modulated by the second messenger c-di-GMP, which is known to regulate several bacterial functions.

Methods: We used P. aeruginosa strains with high or low c-di-GMP levels and their Hfq-deficient derivatives to assess the role of c-di-GMP in modulating meropenem susceptibility and tolerance.

Results: We show that low intracellular c-di-GMP levels increase meropenem resistance and tolerance at sub-inhibitory concentrations, whereas high c-di-GMP diminishes both traits. Importantly, c-di-GMP status shapes the entire response trajectory, from exponential growth to the stationary phase. Furthermore, we show that c-di-GMP modulates meropenem response through mechanism(s) independent of Hfq-mediated porin repression and exerts a dominant effect over CCR-driven regulation.

Conclusion: This study supports the notion that P. aeruginosa meropenem susceptibility and tolerance are modulated by intracellular c-di-GMP concentrations, with low c-di-GMP levels promoting higher fitness. Our findings indicate that c-di-GMP exerts its regulatory effect through mechanisms distinct from Hfq-mediated porin control, underscoring the existence of parallel regulatory pathways that shape antibiotic response.

Introduction: Preterm infants exhibit heightened vulnerability to morbidity and mortality due to their underdeveloped immune systems and immature gastrointestinal tract. The gut microbiota plays a pivotal role in neonatal health, yet its establishment is influenced by multiple factors, including prematurity, antibiotic exposure, and feeding modalities. This study aimed to examine the interactions among gut bacteriophages, bacterial communities, and clinical variables in preterm infants to identify potential microbial biomarkers associated with health outcomes.

Methods: We employed metagenomic shotgun sequencing and co-occurrence network analysis to characterize the virome and bacterial communities in 12 preterm neonates at 14 and 28 days post-birth. This approach enabled the identification of dynamic microbial colonization patterns and key bacterial species and bacteriophages associated with clinical parameters.

Results: Staphylococcus epidermidis exhibited a significant decline over time, whereas Enterococcus faecalis and its associated bacteriophages showed progressive enrichment, becoming predominant by day 28. In contrast, the relative abundances of Clostridioides difficile and Klebsiella pneumoniae remained statistically stable between the two time points (14 vs. 28 days).

Discussion: These findings suggest that microbial changes during the first month of life may reflect a combination of host developmental processes and external influences, such as antibiotic exposure or delivery mode. The observed microbial signatures provide preliminary insights into early gut microbiota and virome development in preterm infants. However, their functional relevance and long-term stability require confirmation in larger, well-powered longitudinal studies with denser temporal sampling. The enrichment of Enterococcus faecalis may indicate its opportunistic colonization potential in the preterm gut and warrants further investigation regarding its role in gut homeostasis and immune system maturation.

Background: Psittacosis pneumonia, which is caused by Chlamydia psittaci, is a systemic inflammatory disease that often results in injury to multiple organs. Although liver and heart involvement are recognized, the incidence, risk factors, and predictors for acute kidney complications are not well known.

Methods: Our retrospective cohort study included 123 patients, comprising 47 individuals diagnosed with psittacosis pneumonia and 76 individuals with typical community-acquired pneumonia (CAP). These patients were admitted to Nanjing First Hospital, affiliated with Nanjing Medical University, between June 2019 and July 2024. The study conducted an analysis of clinical profiles, laboratory markers, and patient outcomes. The predictive efficacy of the Blood Urea Nitrogen to Albumin Ratio (BAR) and Lactate Dehydrogenase (LDH) in forecasting acute kidney injury (AKI) was assessed through the application of receiver operating characteristic (ROC) curve analysis.

Results: In comparison to typical CAP, psittacosis pneumonia is characterized by markedly elevated systemic inflammation, as evidenced by increased levels of procalcitonin (PCT), C-reactive protein (CRP), and interleukin-6 (IL-6). Additionally, it presents with more severe lymphocytopenia, hypoalbuminemia, and extensive multi-organ damage, with a pronounced impact on hepatic and myocardial tissues. The incidence of AKI was significantly greater in the psittacosis group compared to the control group (34.0% versus 12.1%, P=0.003). In the psittacosis cohort, AKI demonstrated an independent association with increased levels of LDH (P = 0.01) and the BAR (P < 0.001), whereas no such association was observed with traditional inflammatory markers. The BAR (AUC = 0.88) and LDH (AUC = 0.79) demonstrated effective predictive capabilities for AKI, with their combined application enhancing sensitivity to 85.71% and specificity to 87.50%. The implementation of targeted therapy using omadacycline resulted in prompt clinical and biochemical improvements across all patients.

Conclusion: Psittacosis pneumonia constitutes a distinct systemic immuno-inflammatory syndrome that presents a significant risk for AKI. The composite biomarker BAR and the cellular injury marker LDH demonstrate superior predictive capabilities for AKI compared to traditional inflammatory indices, thereby providing accessible tools for early risk stratification. These findings emphasize the necessity of recognizing psittacosis as a unique clinical entity and advocate for vigilant monitoring of renal function in affected patients.

Objective: The increasing antimicrobial resistance in non-typhoidal Salmonella (NTS) poses a growing challenge to clinical therapy. This study reports, for the first time, a carbapenem-resistant Salmonella enterica serovar Derby isolate. Although serovar Derby accounts for a relatively small proportion of clinical NTS infections, elucidating the mechanism, origin, and dissemination potential of its carbapenem resistance is crucial for enhancing surveillance and prevention strategies against resistant NTS.

Methods: Antimicrobial susceptibility testing was performed using commercial broth microdilution panels with the Beckman Coulter WalkAway 96 PLUS system. Whole-genome sequencing (WGS) and S1-pulsed-field gel electrophoresis (PFGE) were employed to characterize the chromosomes and plasmids of isolates. Conjugation assays were conducted to evaluate plasmid mobility. Additionally, the NCBI Genome and Pathogens databases were used to identify carbapenemase-producing Salmonella strains.

Results: A patient with aplastic anemia was admitted with abdominal pain and received successive treatments. During periods of recurrent fever, carbapenem-resistant S. Derby (CS_CRSA) and Escherichia coli (CS_CREco) were isolated from rectal swabs. WGS revealed that both strains carried a nearly identical IncFII plasmid (80,195/80,198 bp) harboring bla _NDM-1 and qnrS1 genes. This plasmid contained a complete conjugation module, and could be transferred from CS_CRSA and CS_CREco to the recipient at efficiencies of (4.50 ± 1.29)×10^-2 and (3.17 ± 0.74)×10^-1. Comparative analysis showed its high similarity to a resistance plasmid of Salmonella enterica serovar Typhimurium isolated from Zhejiang, China. As of June 25, 2025, 35 fully assembled Salmonella enterica strains carrying carbapenemase genes were identified, predominantly S. Typhimurium and its variants. Phylogenetic analysis indicated that most carbapenemase-producing Salmonella (CPSA) strains were scattered, while clonal dissemination was observed in some serotypes.

Conclusion: This study reports a clinical isolate of carbapenem-resistant S. Derby, likely resulting from horizontal transfer of a bla _NDM-1 -carrying plasmid, which indicates that carbapenem resistance is extending to less common and low virulence serovars of Salmonella. The emergence of such strains poses a challenge to patient care, especially for immunocompromised populations suffering from invasive infections. Additionally, clonal dissemination of CPSA in certain serotypes warrants heightened vigilance and preventive measures.

Background: Mucormycosis is a life-threatening invasive fungal infection that mainly affects individuals with weakened immune systems. Despite its clinical importance, data from Türkiye on the epidemiology and antifungal susceptibility of fungi belonging to the order Mucorales are scarce. This study aimed to describe the clinical, epidemiological, and mycological features of mucormycosis over a twenty-year period at a tertiary care hospital.

Methods: All cases of mucormycosis diagnosed between 2003 and 2022 at Bursa Uludağ University Hospital were retrospectively evaluated. Cases were classified as proven or probable according to international definitions. Molecular identification was based on internal transcribed spacer sequencing. Large subunit ribosomal DNA region sequencing and whole-genome sequencing were performed when necessary. Antifungal susceptibility testing for amphotericin B and posaconazole was performed according to the Clinical and Laboratory Standards Institute M38 guideline. Statistical analyses included chi-square, Fisher's exact, Spearman's correlation, and Wilcoxon signed-rank tests.

Results: A total of 187 cases were identified, comprising 134 proven and 53 probable. Rhino-cerebral infection was the most frequent form, followed by pulmonary disease. Hematologic malignancy was the most common underlying condition, and mortality was 52.9 percent. Molecular identification was achieved for 99 isolates, with Rhizopus arrhizus predominant and Rhizomucor pusillus second. Posaconazole exhibited greater in vitro activity than amphotericin B (p < 0.001), while Cunninghamella species showed elevated amphotericin B minimum inhibitory concentrations.

Conclusion: This single-center study provides the most comprehensive data on mucormycosis in Türkiye and highlights the importance of molecular surveillance to guide antifungal therapy and monitor regional variations.

[This corrects the article DOI: 10.3389/fcimb.2024.1421195.].

Objectives: Nirmatrelvir/ritonavir (N/R) is an effective antiviral for treating COVID-19. However, evidence supporting therapeutic drug monitoring (TDM) for N/R remains limited, potentially increasing the risk of adverse reactions and compromising efficacy. This study aims to identify factors influencing N/R plasma exposure and to develop and internally validate a machine learning model for predicting N/R concentrations, thereby supporting individualized therapy.

Methods: We retrospectively analyzed data from 139 patients who received N/R at two centers. Baseline clinical and laboratory variables were collected, and steady-state trough concentrations of nirmatrelvir and ritonavir were measured on day 3 of treatment. Logistic regression was used to examine the association between drug concentration and prognosis. After excluding highly correlated features, a random forest model identified key factors affecting drug exposure. An XGBoost regression model was then constructed with the selected features, and its predictive performance was evaluated using mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and R². Five-fold cross-validation was applied for internal validation.

Results: Nirmatrelvir trough concentration was not predictive of patient outcomes (AUC = 0.467). Six factors were consistently identified as important determinants of N/R exposure: estimated glomerular filtration rate (eGFR), creatine kinase (CK), aspartate aminotransferase (AST), alanine aminotransferase (ALT), lymphocyte count (Lymph), and procalcitonin (PCT). Ultimately, the evaluation of the predictive model resulted in a mean absolute error (MAE) of 0.717, mean squared error (MSE) of 1.328, root mean squared error (RMSE) of 1.152, and coefficient of determination (R-squared) of 0.779. The prediction model performs well and can provide risk prediction for medication management for N/R, as well as assist in personalized medication.

Conclusions: We identified a set of variables that affect the treatment of N/R through therapeutic drug monitoring and established a machine learning model capable of predicting N/R concentrations with satisfactory performance. These findings provide a basis for integrating TDM with multivariable prediction tools to personalize N/R dosing and improve medication safety.

Introduction: Postoperative pulmonary complications (PPCs) significantly impact the prognosis of elderly patients undergoing laparoscopic surgery, yet reliable tools for early risk stratification are lacking. This study aimed to develop and externally validate a machine learning (ML) model to predict PPCs using preoperative and intraoperative data available at the point of surgical closure.

Methods: A multicenter retrospective cohort study was conducted involving 1,415 elderly patients (age >60 years) from two tertiary hospitals in China. The primary outcome was clinically significant PPCs (Clavien-Dindo Grade ≥ II) within 7 days postoperatively. Nine ML algorithms were trained and optimized using a nested 5-fold cross-validation framework. The Synthetic Minority Over-sampling Technique (SMOTE) and Boruta algorithm were employed to address class imbalance and feature selection, respectively. The model's performance was evaluated in an internal development cohort and an independent external validation cohort (n=102).

Results: Among the evaluated algorithms, the Gradient Boosting Machine (GBM) demonstrated superior performance, achieving an Area Under the Curve (AUC) of 0.691(95% CI: 0.617-0.762) (Sensitivity 65.2%, Specificity 83.4%) in the internal cohort, Notably, the model exhibited superior performance in the external validation cohort with an AUC: 0.755 (95% CI: 0.652-0.849), indicating excellent generalizability without overfitting. The decision curve analysis confirmed that the GBM model provided a higher net clinical benefit than the default strategies. SHAP (SHapley Additive exPlanations) analysis identified Surgery Duration, Preoperative Albumin, and inflammatory markers (CRP, WBC) as top predictors, reflecting the interplay between surgical stress and physiological reserve. Decision Curve Analysis (DCA) confirmed the model's clinical utility, showing a net benefit across a threshold probability range of 30%-90%.

Conclusion: The GBM-based dynamic model offers a robust, interpretable, and generalizable tool for the early prediction of PPCs in elderly laparoscopic surgery patients. By enabling risk assessment immediately upon surgical completion, this tool facilitates the shift from reactive treatment to proactive prevention and personalized perioperative management.