Frontiers in Cellular and Infection Microbiology最新文献

Infection is one of the leading causes of death in patients with hematologic cancers. Hematologic cancer patients with compromised immune systems are already susceptible to infections, which come on even more rapidly and are difficult to control after they develop neutrophil deficiencies from high-dose chemotherapy. After patients have developed an infection, the determination of the type of infection becomes a priority for clinicians. In this review, we summarize the biomarkers currently used for the prediction of infections in patients with hematologic cancers; procalcitonin, CD64, cytokines, and CD14 et al. can be used to determine bacterial infections, and (1-3)-β-D-glucan and galactomannan et al. can be used as a determination of fungal infections. We have also focused on the use of metagenomic next-generation sequencing in infections in patients with hematologic cancers, which has excellent clinical value in infection prediction and can detect microorganisms that cannot be detected by conventional testing methods such as blood cultures. Of course, we also focused on infection biomarkers that are not yet used in blood cancer patients but could be used as a future research direction, e.g., human neutrophil lipocalin, serum amyloid A, and heparin-binding protein et al. Finally, clinicians need to combine multiple infection biomarkers, the patient's clinical condition, local susceptibility to the type of infection, and many other factors to make a determination of the type of infection.

Introduction: SARS-CoV-2 infection drove senescent cells and the senescence-associated phenotypes were reported playing roles in disease progression, which contributes to severe COVID-19 and related sequelae. Cdc42 is involved in the regulation of cellular senescence. This study, aimed to investigate the mechanism of the SARS-CoV-2 spike protein regulating cellular senescence through Cdc42.

Methods: K18-hACE2 mice were infected with SARS-CoV-2 Omicron BA.4 or stimulated with spike protein through the airway, the senescent cells and Cdc42 expression in lung tissue were detected. Overexpression of spike protein or exogenous incubation of spike protein was used to simulate the induction of cellular senescence by spike protein. Mechanistic insights into the role of Cdc42 were mainly explored using Western Blot and qRT-PCR.

Results: Spike protein, SARS-CoV-2 infection related, accelerates cell aging by upregulating Cdc42 expression, which furtherly activated the Wnt/β-catenin signaling pathway. Conversely, treatment with ML141 in animal models, a Cdc42 inhibitor, reduced cellular senescence and ameliorated lung injury and inflammation. These results suggest that the upregulation of Cdc42 by the SARS-CoV-2 spike protein induces cellular senescence and enhances β-catenin nuclear translocation.

Discussion: This study provides insights into the mechanisms underlying cellular senescence induced by the SARS-CoV-2 spike protein, offering potential strategies to mitigate the inflammatory response and complications associated with COVID-19 in both the acute and long-term phases.

Visceral leishmaniasis (VL) caused by L. donovani in South-East Asian endemic countries including India, Nepal and Bangladesh has been the primary focus of the ongoing VL elimination program. With a major reduction in VL cases resulting from the elimination program during the last two decades, the efforts are now focused on the challenges posed by potential reservoirs within the asymptomatic cases, HIV-co-infection VL cases and Post Kala-azar Dermal Leishmaniasis (PKDL) cases that continue to sustain the parasite transmission cycle in known and newer endemic zones. This article brings attention to a new potential parasite reservoir in the form of atypical cutaneous leishmaniasis (ACL) cases caused by novel L. donovani genetic variants. L. donovani mediated ACL is an emerging phenomenon in recent endemic sites that now justify a need for implementing molecular surveillance tools to identify region-specific L. donovani variants with dermotropic capabilities and potential to revert to visceral disease. A timely detection of novel ACL causing L. donovani genetic lineages in South-East Asian endemic regions is necessary to halt the spread of ACL and is potentially crucial for the sustainability of the advances made by the VL elimination.

Introduction: Immunocompromised persons are at high risk of persistent Human Papilloma Virus (HPV) infection and associated diseases. Few studies evaluated HPV vaccines in immunocompromised persons. This study aimed to evaluate the quadrivalent HPV vaccine (4vHPV) immunogenicity and safety in solid organ transplant (SOT) recipients, in comparison to immunocompetent women (IC).

Methods: Open-label clinical trial that enrolled SOT recipients and immunocompetent women aged 18 to 45 years. All participants received three doses of 4vHPV vaccine. Blood samples were drawn for evaluation of immune responses at baseline and one month after the third vaccination. Seroconversion rates and antibody geometric mean concentration (GMC) against HPV 6, 11, 16, 18, 31, 35, 52 and 58 were measured with in-house multiplexed serology assay (xMAP technology). Follow-up for the local and systemic adverse events (AEs) continued for seven days after each vaccination. Severe AEs were evaluated throughout the study.

Results: 125 SOT and 132 immunocompetent women were enrolled; 105 (84%) SOT and 119 (90%) immunocompetent women completed the study. At baseline, HPV seropositivity was not significantly different between groups. Seroconversion rates were significantly lower in SOT (HPV18, 57%; HPV6 and 16, 69%; and HPV11, 72%) than in immunocompetent women (100% seroconversion to all vaccine types) (p<0.001). Antibody GMCs of all four HPV vaccine types were also significantly lower in SOT (p<0.001). Pain in the injection site and headache were the most frequent adverse event in both groups. Local pain was more frequent in immunocompetent women than in SOT recipients. Rates of other AEs were comparable in both groups.

Conclusion: 4vHPV vaccine was well-tolerated by SOT recipients. We found strong evidence of lower humoral immune responses to 4vHPV vaccine in SOT compared to immunocompetent women, which strengthen recommendation of routine cervical cancer screening in SOT recipients regardless of HPV vaccination status.

Background: SAKI is a common and serious complication of sepsis, contributing significantly to high morbidity and mortality, especially in patients requiring RRT. Early identification of high-risk patients enables timely interventions and improvement in clinical outcomes. The objective of this study was to develop and validate a predictive model for in-hospital mortality in patients with SAKI receiving RRT.

Methods: Patients with SAKI receiving RRT from the MIMIC-IV database were retrospectively enrolled and randomly assigned to either the training cohort or the testing cohort in a 7:3 ratio. LASSO regression and Boruta algorithm were utilized for feature selection. Subsequently, three machine learning models-CART, SVM and LR-were constructed, and their predictive efficacy was assessed using a comprehensive set of performance indicators. Feature importance analysis was performed to determine the contribution of each feature to a model's predictions. Finally, DCA was employed to evaluate the clinical utility of the prediction models. Additionally, a clinical nomogram was developed to facilitate the interpretation and visualization of the LR model.

Results: A total of 1663 adults were ultimately enrolled and randomly allocated into the training cohort (n = 1164) or the testing cohort (n = 499). Twenty-eight variables were evaluated for feature selection, with eight ultimately retained in the final model: age, MAP, RR, lactate, Cr, PT-INR, TBIL and CVP. The LR model demonstrated commendable performance, exhibiting robust discrimination in both the training cohort (AUROC: 0.73 (95% CI 0.70-0.76); AUPRC: 0.75 (95% CI 0.72-0.79); accuracy: 0.66 (95% CI 0.63-0.68)) and the testing cohort (AUROC: 0.72 (95% CI 0.68-0.76); AUPRC: 0.73 (95% CI 0.67-0.79); accuracy: 0.65 (95% CI 0.61-0.69)). Furthermore, there was good concordance between predicted and observed values in both the training cohort (χ2 = 4.41, p = 0.82) and the testing cohort (χ2 = 4.16, p = 0.84). The results of the DCA revealed that the LR model provided a greater net benefit compared to other prediction models.

Conclusions: The LR model exhibited superior performance in predicting in-hospital mortality in patients with SAKI receiving RRT, suggesting its potential utility in identifying high-risk patients and guiding clinical decision-making.

Background: This study aimed to characterize the oral and gut microbiota in prediabetes mellitus (Pre-DM) and type 2 diabetes mellitus (T2DM) patients while exploring the association between tongue manifestations and the oral-gut microbiota axis in diabetes progression.

Methods: Participants included 30 Pre-DM patients, 37 individuals with T2DM, and 28 healthy controls. Tongue images and oral/fecal samples were analyzed using image processing and 16S rRNA sequencing. Machine learning techniques, including support vector machine (SVM), random forest, gradient boosting, adaptive boosting, and K-nearest neighbors, were applied to integrate tongue image data with microbiota profiles to construct predictive models for Pre-DM and T2DM classification.

Results: Significant shifts in tongue characteristics were identified during the progression from Pre-DM to T2DM. Elevated Firmicutes levels along the oral-gut axis were associated with white greasy fur, indicative of underlying metabolic changes. An SVM-based predictive model demonstrated an accuracy of 78.9%, with an AUC of 86.9%. Notably, tongue image parameters (TB-a, perALL) and specific microbiota (Escherichia, Porphyromonas-A) emerged as prominent diagnostic markers for Pre-DM and T2DM.

Conclusion: The integration of tongue diagnosis with microbiome analysis reveals distinct tongue features and microbial markers. This approach significantly improves the diagnostic capability for Pre-DM and T2DM.

Streptococcus oralis, belonging to the viridans group streptococci (VGS), has been considered a member of normal flora mainly inhabiting the oral cavity. However, more recently, there has been growing recognition of its role as a causative agent in various life-threatening infectious diseases such as infective endocarditis (IE) and meningitis. Additionally, the differences in the prevalence, clinical features, and prognosis of opportunistic infections between S. oralis and other VGS species have been addressed. Particularly the predominance of S. oralis in IE has drawn critical attention. In potentially fatal infections, clinical neglect of S. oralis as an instigating agent might significantly impede early diagnosis and treatment. Nevertheless, to date, the infectious diseases associated with S. oralis have not yet been comprehensively described. Therefore, this review will give an overview of infectious diseases caused by S. oralis to uncover its hidden role as an opportunistic pathogen.

Objectives: Ascites, often associated with critical pathologies such as liver cirrhosis or bowel perforation, can be complicated by fungal infection, increasing mortality especially in intensive care settings and demanding rapid diagnosis and adequate treatment. Traditional microbiological diagnostic methods have limited sensitivity in accurately identifying fungal pathogens in ascitic fluid. Alternative diagnostic methods may offer important insights to enable guiding of antifungal therapy and refining empirical treatment strategies. The objective of this study was to evaluate the potential of next-generation sequencing methods to identify specific fungal pathogens responsible for ascitic fluid infections.

Methods: We prospectively collected 50 ascitic fluid samples from ICU patients with suspected ascites infection. In addition to standard culture-based microbiological testing, an ascitic fluid aliquot underwent fungal DNA isolation and was analyzed by next-generation sequencing (NGS) methods for identification of fungal species.

Results: Of 50 ascitic samples collected, five samples showed growth of Candida spp. in culture. After DNA isolation and ITS2 PCR, detectable amplification was achieved in 10 samples. Sequencing of the 50 patients' samples identified facultative pathogenic fungi in 19 patients. In 15 cases, culture alone would not have permitted the identification of all facultative pathogenic fungi. The identification of fungal DNA by sequencing was significantly associated with poor patient outcome and a number of clinical parameters.

Conclusions: Our results show a higher sensitivity for NGS-based diagnostic methods in the identification of ascitic fluid fungal infections compared to culture-based diagnostics. This may be beneficial especially for patients in a critical care setting, who have an increased prevalence of comorbidities and high mortality. The implementation of such methods in standard diagnosis will require increased standardization of the workflows and interpretation of the sequencing results with respect to patients' clinical picture.

Chlamydia pneumoniae (C. pneumoniae) is a specialized intracellular parasitic pathogen capable of causing pneumonia, sinusitis, bronchitis, and other respiratory diseases, which pose significant public health challenges. Therefore, rapid, accurate, and sensitive diagnosis is crucial for the prevention and treatment of respiratory diseases caused by C. pneumoniae. In this study, we combined enzymatic recombination amplification (ERA) with the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) 12a system (CRISPR/Cas12a) to develop a dual detection platform termed the Cpn-ERA-CRISPR/Cas12a dual system. This system integrates both the ERA-CRISPR/Cas12a fluorescence system and the ERA-CRISPR/Cas12a lateral flow system. Detection results can be measured using a fluorescence detector or observed with the naked eye on lateral flow strips. The fluorescence system and the lateral flow system detect C. pneumoniae in 30 minutes and 15 minutes, respectively. This dual system exhibits no cross-reactivity with the other seven pathogens, demonstrating high specificity, and achieves a sensitivity of 10⁰ copies/µL. Additionally, the Cpn-ERA-CRISPR/Cas12a dual system was employed to analyze 39 clinical samples, comprising 19 positive and 20 negative samples. The detection rate for positive samples was 100%, with no positive results in the negative samples, indicating a high level of concordance with qPCR results. In summary, the Cpn-ERA-CRISPR/Cas12a dual system represents a novel tool for diagnosing C. pneumoniae and holds promising application potential in grassroots community hospitals.

The phyllospheric microbial composition of tobacco plants is influenced by multiple factors. Disease severity level is one of the main influencing factors. This study was designed to understand the microbial community in tobacco wildfire disease with different disease severity levels. Tobacco leaves at disease severity level of 1, 5, 7, and 9 (L1, L5, L7, and L9) were collected; both healthy and diseased leaf tissues for each level were collected. The community structure and diversity in tobacco leaves with different disease severity levels were compared using high-throughput technique and Biolog Eco. The results showed that in all healthy and diseased tobacco leaves, the most dominant bacterial phylum was Proteobacteria with a high prevalence of genus Pseudomonas; the relative abundance of Pseudomonas was most found at B9 diseased samples. Ascomycota represents the most prominent fungal phylum, with Blastobotrys as the predominant genus. In bacterial communities, the Alpha diversity of healthy samples was higher than that of diseased samples. In fungal community, the difference in Alpha diversity between healthy and diseased was not significant. LEfSe analysis showed that the most enriched bacterial biomarker was unclassified_Gammaproteobacteria in diseased samples; unclassified_Alcaligenaceae were the most enrich bacterial biomarker in healthy samples. FUNGuild analysis showed that saprotroph was the dominated mode in health and lower diseased samples, The abundance of pathotroph-saprotroph and pathotroph-saprotroph-symbiotroph increases at high disease levels. PICRUSt analysis showed that the predominant pathway was metabolism function, and most bacterial gene sequences seem to be independent of the disease severity level. The Biolog Eco results showed that the utilization rates of carbon sources decrease with increasing disease severity level. The current study revealed the microbial community's characteristic of tobacco wildfire disease with different disease severity levels, providing scientific references for the control of tobacco wildfire disease.