Frontiers in Cellular and Infection Microbiology最新文献

Objective: This study aimed to assess the association between routine cerebrospinal fluid (CSF) biochemical parameters and metagenomic next-generation sequencing (mNGS) results, and to develop a predictive model to optimize mNGS testing strategies in patients with suspected central nervous system (CNS) infections.

Methods: We retrospectively enrolled 110 patients with suspected CNS infections between December 2019 and January 2024. All underwent both CSF analysis and mNGS testing. Patients were divided into mNGS-positive (n = 62) and negative (n = 48) groups. Logistic regression identified independent predictors, and a nomogram was constructed based on CSF cell count and protein concentration. Model performance was assessed via receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Internal validation included 10-fold cross-validation and 1000-sample bootstrap. An external validation was performed using a cohort of 40 patients enrolled from another hospital campus (May-October 2024). The derivation cohort was retrospectively collected, whereas the external validation cohort was prospectively enrolled.

Results: mNGS positivity rate was 56.36%, significantly higher than CSF culture (6.36%), with an overall diagnostic concordance of 79.09%. Compared to the mNGS-negative group, positive patients had significantly higher CSF cell counts, protein levels, turbidity, ICU admission (ICUA), antimicrobial regimen adjustment (AAR), and mortality, while glucose was significantly lower (P < 0.05). Logistic regression confirmed CSF cell count binary variables (BV) and protein-BV as independent predictors (P < 0.05). The areas under curve (AUCs) for the cell-count, protein-only, and combined models were 0.827, 0.813, and 0.782, respectively. Internal validation showed stable results: 10-fold CV AUC = 0.773 ± 0.184 (95% CI: 0.641-0.904), bootstrap AUC = 0.770 ± 0.064 (95% CI: 0.766-0.774). External validation yielded an AUC of 0.763 (95% CI: 0.554-0.918), with sensitivity and specificity of 77.8% and 67.7%. Calibration and DCA demonstrated good agreement and clinical utility.

Conclusion: CSF cell count and protein are reliable predictors of mNGS positivity. The model for practice showed consistent diagnostic performance and may aid in guiding precision mNGS testing, particularly in resource-constrained settings.

Background: Chronic obstructive pulmonary disease (COPD) significantly impacts global health, primarily due to frequent acute exacerbations caused by respiratory infections. Precise microbial characterization may inform prognostic insights and optimize clinical management.

Methods: We conducted a prospective observational study from December 2023 to February 2025 involving 1146 patients (259 COPD; 887 non-COPD) with suspected respiratory infections. Bronchoalveolar lavage fluid samples underwent next-generation sequencing (NGS) and conventional microbiological testing. Multivariate logistic regression identified COPD predictors, and machine learning modeled prognostic outcomes based on microbial profiles.

Results: Distinct pathogen distributions emerged between COPD and non-COPD groups, with COPD patients exhibiting higher prevalence of gram-negative bacteria, particularly Pseudomonas aeruginosa and Haemophilus influenzae, and fungal pathogens. Non-COPD patients demonstrated increased occurrence of atypical pathogens, notably Mycoplasma pneumoniae. COPD patients also presented higher loads of traditionally commensal microorganisms, such as Veillonella parvula and Schaalia odontolytica. Age, dyspnea, smoking duration, elevated leukocyte and neutrophil counts, and decreased lymphocyte levels were significantly associated with COPD presence. Machine learning identified specific microorganisms as strong predictors of adverse outcomes, such as SARS-CoV-2, Veillonella parvula, and Achromobacter xylosoxidans.

Conclusions: Comprehensive microbial profiling using NGS effectively distinguishes pathogen differences between COPD and non-COPD patients, revealing key associations with clinical prognosis. These insights can inform tailored clinical interventions aimed at mitigating COPD exacerbations and improving patient outcomes.

Objective: To investigate the influencing factors associated with the risk of latent tuberculosis infection (LTBI) among people living with HIV/AIDS (PLWHA).

Methods: A cross-sectional study was conducted from July 2023 to July 2024, recruiting PLWHA from Wuxi City and Yangzhou City, Jiangsu Province, China. Data were collected through on-site questionnaire surveys and review of patient disease management records. QuantiFERON-TB Gold In-Tube (QFT) was used to detect LTBI. Multivariate logistic regression analysis was performed to identify factors associated with LTBI among PLWHA. Restricted cubic splines (RCS) models were employed to analyze the dose-response relationships between CD4⁺ cell count, CD8⁺ cell count, and CD4/CD8 ratio with LTBI risk.

Results: A total of 1184 PLWHA were enrolled, with 8.4% having concomitant LTBI. Multivariate logistic regression revealed that age group 45-<60 years (OR = 2.158, 95% CI: 1.339-3.478, P = 0.002) and CD4/CD8 ratio ≥1 (OR = 3.562, 95% CI: 1.627-7.800, P = 0.001) were independent factors associated with LTBI. RCS model fitting results demonstrated a gradually increasing nonlinear dose-response relationship between continuous changes in CD4/CD8 ratio and LTBI. The dose-response relationship between CD4⁺ cell count and LTBI risk exhibited an "initial increase followed by a decrease trend. The dose-response relationship between CD8⁺ cell count and LTBI risk showed a gradual declining trend.

Conclusion: This study identified that middle-aged PLWHA (45-<60 years) might represent a subgroup with relatively higher LTBI prevalence, indicating that screening in this age group may hold greater potential value. Additionally, the CD4/CD8 ratio, in conjunction with QFT findings, could serve as a supplementary reference for LTBI risk assessment. These observations support a more tailored approach to LTBI screening in PLWHA, though their implementation should be validated in prospective studies.

Introduction: HIV molecular network technology can identify HIV transmission hotspots and individuals at risk of HIV transmission, facilitating precise and targeted interventions. This study explored the molecular network parameters, namely degree centrality (DC) and betweenness centrality (BC), to effectively pinpoint individuals at high risk of HIV transmission within the network.

Methods: A previous whole-population sampling cohort comprising all newly diagnosed people living with HIV (PLWH) in Shenyang, from 2016 to 2019, was analyzed. Molecular networks based pol gene were constructed, the DC and BC of each node were calculated, and six groups of nodes were identified based on DC, BC, and DC+BC: high DC group, low DC group, high BC group, low BC group, high DC+BC group, and non-high DC+BC group. The average risk of HIV transmission in each group was calculated by dividing the total probability of recent HIV infection (identified by HIV-1 LAg-Avidity EIA) by the number of cases in each group. A multivariate logistic regression analysis was conducted to identify the characteristics of the high-risk group.

Results: Of the 2882 PLWH, 1162 were included in the molecular network. The mean DC and the mean BC of all nodes were 2.6 (range: 1-29) and 0.09 (range: 0-1), respectively. The top three groups with the highest average risk of HIV transmission were the high DC+BC group at 0.62, followed by the high BC group at 0.56, and the high DC group at 0.53. The characteristics of the high DC+BC group were low education levels, Housekeeping, housework, and unemployment, and high baseline viral load (≥10⁵copies/mL) (P<0.05).

Discussion: The combined utilization of DC and BC can effectively identify individuals at high risk of HIV transmission, enabling precisely targeted interventions using molecular network technology.

Damping-off has caused huge losses in soybean production areas of China. Based on multi-locus phylogenetic analysis and Koch's Postulates, the causal agent of soybean damping-off was identified as Globisporangium intermedium. Given the potential danger of G. intermedium, early and precise detection methods are needed for both disease management and prevention. In this study, a LAMP assay utilizing a new target gene rpb1 was developed and evaluated for the detection of G. intermedium. This rpb1 LAMP assay was found highly specific to G. intermedium. All nine tested isolates of G. intermedium yielded positive results, whereas 30 non-target isolates belonging to Globisporangium spp., Pythium spp., Phytophthora spp., Phytopythium spp., and soil-borne fungi lacked detection. The LAMP method can identify G. intermedium at DNA concentrations as low as 10 pg/μL. In terms of on-site disease diagnosis, the LAMP assay could detect G. intermedium from artificially inoculated soybean tissues and naturally infested rhizosphere soil collected from fields in soybean production regions. Consequently, this study not only stands as the first record of G. intermedium as a new soybean pathogen in China, but also provides an efficient LAMP field detection method that could significantly contribute to the management and prevention of soybean damping-off.

Background: Intracranial infection caused by Streptococcus pyogenes is extremely rare in adults. We report a case of Streptococcus pyogenes combined with Epstein-Barr virus (EBV) infection in cerebrospinal fluid (CSF), which was diagnosed by targeted next-generation sequencing (tNGS). The findings were subsequently confirmed by capillary electrophoresis (CE) and quantitative real-time PCR (qPCR), respectively. Meanwhile, digital PCR (dPCR) detection indicated the presence of Streptococcus species DNA in the blood. Brain magnetic resonance imaging (MRI) suggested the possibility of meningitis. The patient's condition improved significantly following combined antibacterial and antiviral therapy.

Case summary: A 67-year-old female patient with a history of diabetes mellitus for over ten years presented with fever, vomiting, and impaired consciousness. CSF analysis showed significantly elevated cell count, elevated neutrophil percentage, and increased lactate dehydrogenase (LDH) levels. The tNGS result of CSF indicated Streptococcus pyogenes and EBV coinfection, meanwhile, dPCR of peripheral blood suggested the presence of Streptococcus species. The patient was therefore diagnosed with intracranial infection, sepsis, and septic shock. The antimicrobial therapy was promptly adjusted to include combined antibacterial and antiviral treatment. Following intervention, the patient's symptoms gradually improved. Subsequent CSF analysis and tNGS testing demonstrated normalization of cell count and LDH levels, a significant decrease in the detection level of Streptococcus pyogenes, and negative detection of EBV.

Conclusion: Intracranial coinfection involving Streptococcus pyogenes and EBV is exceptionally rare in adults. Early clinical manifestations are often nonspecific, yet the disease can progress rapidly, underscoring the critical importance of prompt and accurate pathogen identification. The widespread application of tNGS has significantly enhanced early diagnostic capabilities in cases of intracranial infection.

Background: Elderly adults with complicated intra-abdominal infection (cIAI) represent a functionally immunocompromised population due to immunosenescence, multimorbidity, and frailty. Optimizing empirical antibiotic therapy in this group is essential to improve outcomes while minimizing unnecessary broad-spectrum antimicrobial exposure and antimicrobial resistance (AMR) selection pressure. Ertapenem is a once-daily carbapenem with favorable pharmacological properties, yet contemporary real-world comparative data in older adults are limited.

Methods: We conducted a retrospective, real-world comparative-effectiveness study of hospitalized adults aged ≥65 years with cIAI at a tertiary academic medical center from 2019 to 2025. Eligible patients received empirical monotherapy with ertapenem, meropenem, cefoperazone-sulbactam, or moxifloxacin for ≥72 hours. A multinomial propensity score-based inverse probability of treatment weighting (IPTW) approach was used to balance baseline covariates across the four regimens. The primary outcome was clinical cure or improvement. Secondary outcomes included all-cause in-hospital mortality, infection-related mortality, intra-abdominal infection-related mortality, duration of antibiotic treatment, and length of hospitalization. Prespecified subgroup analyses were conducted by age group (65-70, 71-80, ≥81 years) and infection source (gastrointestinal vs non-gastrointestinal).

Results: A total of 609 patients met eligibility criteria: 129 received ertapenem, 135 meropenem, 125 cefoperazone-sulbactam, and 220 moxifloxacin. IPTW achieved excellent covariate balance, with all standardized mean differences <0.10. In IPTW-adjusted analyses, clinical cure or improvement did not differ significantly between ertapenem and comparator regimens, with adjusted risk differences ranging from 1.80% to 6.44% (all 95% confidence intervals including zero). Mortality outcomes were likewise comparable across groups. Subgroup analyses suggested that ertapenem was associated with higher cure rates and lower mortality in patients aged 65-70 years and those with non-gastrointestinal infection sources, although confidence intervals were wide, and these findings should be interpreted as exploratory. Differences in secondary outcomes varied across regimens.

Conclusion: In this IPTW-adjusted real-world analysis of elderly adults with cIAI, ertapenem demonstrated clinical effectiveness comparable to meropenem, cefoperazone-sulbactam, and moxifloxacin. Given its once-daily dosing convenience and narrower ecological impact, ertapenem may represent a reasonable and stewardship-aligned empirical option for selected older patients. Prospective and multicenter studies incorporating microbiological and illness severity data are needed to validate these findings.

Introduction: Hypervirulent Klebsiella pneumoniae (hvKp) has emerged as a significant public health threat owing to its ability to cause invasive infections. This study aimed to investigate the clinical characteristics and epidemiological associations of hypervirulent Klebsiella pneumoniae (hvKp) and classical K. pneumoniae (cKp) among patients treated at a tertiary hospital in Zhuhai City, Guangdong Province, China, during the period from January to December 2022, in the context of the ongoing COVID-19 pandemic.

Method: A total of 97 non-duplicated K. pneumoniae isolates and corresponding clinical data were collected. Antimicrobial susceptibility testing, hypermucoviscosity phenotyping, sequence typing, capsular serotyping, and whole-genome sequencing were performed. Hypervirulent strains were identified by the presence of the rmpA, rmpA2, iucA, iroB, peg-344, and peg-589 genes.

Results: Among the 97 isolates, 40 (41.2%) were classified as hvKp. Compared with cKp, hvKp was significantly more likely to cause bacteraemia (P < 0.05) and less likely to cause urinary tract infections (P < 0.05). The K20 capsular serotype was significantly associated with hvKp isolates (P < 0.05). The multidrug resistance rate among hvKp strains (22.5%) was markedly lower than that among cKp strains (56.63%), and extended-spectrum β-lactamase production was more common in cKp strains. Multilocus sequence typing identified 29 sequence types, including 24 novel types. Whole-genome sequencing of a multidrug-resistant hvKp isolate (Kp00198874) revealed an ST11-K64 strain resistant to all tested antibiotics.

Discussion: The prevalence of hvKp increased during the COVID-19 pandemic in Guangdong, China. The isolates identified in this study represent sporadic infections, and the emergence of ST11-K64 hypervirulent carbapenem-resistant K. pneumoniae (hv-CRKp) highlights the urgent need for continued surveillance and vigilance regarding hvKp-associated bacteraemia.

Purpose: To examine the alterations in the ocular surface microbiota and microbial diversity in patients with pterygium after different durations of electronic device use.

Methods: This study involved 31 individuals diagnosed with unilateral pterygium. Conjunctival sac swabs were collected from both eyes, and 16S rRNA sequencing was used to identify the species and quantity of bacteria. The microbial composition was annotated and represented through comprehensive bioinformatics analysis.

Results: The alpha diversity did not differ significantly between the eyes with pterygium and the contralateral eyes. The Chao1 and Shannon indices for the eyes with pterygium of the patients who used electronic devices for extended periods were significantly higher than those for their contralateral eyes. Principal coordinate analysis revealed that the beta diversity of the eyes with pterygium was similar to that of the contralateral eyes. Genus-level differential analysis revealed that the relative abundance of Pseudomonas was significantly increased and that of Bacteroides was significantly decreased in the eyes with pterygium. The relative abundance of Comamonas was significantly higher in the eyes with pterygium than in the contralateral eyes of the patients who used electronic devices for more than 4 h per day.

Conclusion: The ocular surface of eyes with pterygium had increased colonization by opportunistic pathogenic bacteria. Excessive exposure to blue light, which may result from prolonged use of electronic devices, may be a risk factor for the development of pterygium.