Frontiers in Cellular and Infection Microbiology最新文献

Background: Due to the high sensitivity of metagenomic next-generation sequencing (mNGS), trace amounts of nucleic acid contamination can lead to false positives, posing challenges for result interpretation. This study is the first to experimentally identify and establish background microbial libraries (BML) related to periprosthetic joint infection (PJI) across different medical institutions, aiming to demonstrate the necessity of institution-specific BMLs to improve mNGS diagnostic accuracy.

Methods: Samples were taken from 3 different acetabular reamer for hip arthroplasty in 7 different hospitals. The whole process was strictly aseptic, mNGS was performed according to standard operating procedures. The sterility of instruments was confirmed by culture method. The sequencing results of specimens from different hospitals were compared to analyze the difference of background bacteria. Bioinformatics analysis and visualization were presented through R language.

Results: A total of 26 samples (24 instrument swabs and 2 negative controls) generated 254 million reads, of which 1.13% matched microbial genomes. The proportion of microbial reads (1.13%) falls within ranges typically observed for contamination in low-biomass metagenomic sequencing studies. Among these, bacteria accounted for 87.48%, fungi 11.18%, parasites 1.26%, and viruses 0.06%. The most abundant bacterial genera included Cutibacterium, Staphylococcus, and Acinetobacter. Principal component analysis revealed distinct bacterial compositions among the seven hospitals, and clustering analysis showed significant inter-hospital variation (p < 0.05). Liaocheng People's Hospital exhibited the highest species richness (340 species), followed by Guanxian County People's Hospital (169 species).

Conclusions: The composition and abundance of residual bacterial DNA vary markedly among institutions, underscoring the necessity of establishing hospital-specific BMLs. Incorporating such libraries into clinical mNGS interpretation can effectively reduce false positives and enhance the diagnostic accuracy of PJI. arthroplasty, bacterial culture, next-generation sequencing, joint replacement, periprosthetic joint infection, background microbial libraries.

In the tumor immune microenvironment, microbes promote tumor progression and metastasis by invading host cancer cells. Blocking these interactions is expected to provide new strategies for inhibiting tumor progression and metastasis, as well as opening up new avenues for immunotherapy. However, technological means of studying the interaction between microorganisms and host cancer cells are still limited. Proximity labeling, a widely used method for analyzing biomolecular and cellular interactions, has the potential to analyze microbe-host cell interactions quantitatively, uncovering the key factors that influence these interactions within the tumor immune microenvironment in order to control tumor initiation and progression. Furthermore, proximity labeling based strategies can be applied to high-throughput drug screening aimed at disrupting pathogenic microbe-host interactions, contributing to the development of therapeutics against advanced and metastatic tumors. This paper provides a systematic review of the topic, introducing cutting-edge microbiological mechanisms that have attracted the attention of oncologists.

Objective: Chimeric antigen receptor (CAR) T-cell therapy has demonstrated remarkable efficacy in hematological malignancies. However, it can also cause severe systemic toxicity, known as cytokine release syndrome (CRS). Therefore, the potential of CAR-T cells to cause toxicity in vivo should be evaluated in preclinical models prior to first-in-human trials. Although murine models exist for this purpose, they are typically complex xenograft systems available only to a limited number of laboratories. Therefore, development of an in vitro assay to assess CRS elicited by CAR-T cells is warranted.

Methods: CAR-T cells, macrophages, or immature dendritic cells (iDCs), along with tumor target cells, were co-cultured under different conditions. The release of CRS-related cytokines, IFN-γ and IL-6, was measured to simulate cytokine release during CAR-T-induced CRS. Additionally, the cellular source of the key CRS cytokine IL-6 was investigated.

Results: A co-culture system containing only CAR-T cells and tumor cells failed to recapitulate the key feature of CRS, specifically a significant elevation of IL-6. However, when CAR-T cells were co-cultured with antigen-presenting cells (macrophages or iDCs) and tumor cells, the core CRS cytokine IL-6 was significantly elevated in an in vitro cell culture model, indicating that this system effectively mimics cytokine release during CAR-T-induced CRS. Furthermore, macrophages and iDCs are the primary cellular sources of IL-6 during CRS, with macrophages playing a central role in the development of CRS. Additionally, a co-culture system involving CAR-T cells, tumor cells, and macrophages under these conditions can indicate the occurrence of clinically severe-grade CRS.

Conclusion: Macrophages and iDCs play a critical role in the development of CAR-T therapy-induced CRS. The triple-cell co-culture system, comprising CAR-T cells, macrophages or iDCs, and tumor cells, provides a viable in vitro model for assessing CAR-T cell-induced CRS.

Background: The specific gut microbial signatures and their correlation with immune-inflammatory markers in infertile women with endometriosis remain underexplored.To investigate the differences in gut microbiota and their associations with biochemical immune markers in infertile women with endometriosis compared to controls.

Methods: This case-control study enrolled 32 infertile women with endometriosis and 13 control women with male-factor infertility. Fecal samples were collected for 16S rRNA sequencing to profile the gut microbiota, and serum samples were obtained to measure inflammation-related biomarkers. Bioinformatics analyses were applied to compare gut microbial community structures and to examine correlations between differentially abundant bacteria and immune markers.

Results: The endometriosis group exhibited significant enrichment of Lachnospira, Bacilli, Lactobacillales, Parasutterella, Enterococcus, and Veillonella. Comparative analysis revealed significantly altered abundances of multiple taxa, including Lachnospira, Parasutterella, Alistipes, Enterococcus, Veillonella, Streptococcus, Desulfovibrionaceae, Ruminococcaceae, Bilophila, and Peptoniphilus (all P < 0.05). Several inter-species correlations were identified among these bacteria. Importantly, specific microbiota were correlated with immune markers: Streptococcus and Veillonella were positively correlated with macrophage migration inhibitory factor (MIF); Bilophila and Enterococcus were positively correlated with TNF-α and IL-6; Veillonella was positively correlated with TNF-α; Desulfovibrionaceae was negatively correlated with TNF-α and IL-6; and Parasutterella was negatively correlated with CA125.

Conclusion: In this exploratory investigation, specific gut microbial signatures were observed in infertile patients with endometriosis, showing correlations with select systemic immune-inflammatory biomarkers. These initial observations point to a possible association between gut microbiota imbalance and the inflammatory aspects of endometriosis-associated infertility. Consequently, microbial modulation merits further investigation as a potential strategy to alleviate inflammation and potentially enhance reproductive outcomes.

Background: Chikungunya fever (CHIKF) is a mosquito-borne viral disease characterized by fever, rash, and severe joint pain. However, these classical descriptions are based overwhelmingly on the Indian Ocean and Caribbean lineages. With the recent introduction and spread of the Middle Africa lineage (MAL) into Asia, understanding its clinical presentation in new populations, such as Chinese, has become a public health priority. Whether the recently introduced MAL causes comparably severe disease in China remains unknown.

Methods: We enrolled 415 laboratory-confirmed cases of Chikungunya virus (CHIKV) infection during an outbreak in Foshan, China. Clinical manifestations, laboratory parameters, and whole-genome sequencing data were integrated to quantify the symptom burden from three different perspectives using multivariate logistic regression, and to trace the viral source via maximum-likelihood phylogenetic analysis.

Results: Compared with the classical phenotype, the MAL outbreak in China was appreciably milder. The most common clinical manifestations were arthralgia (83.61%), fever (74.46%), and rash (61.93%). Multivariate logistic regression showed that older age (OR = 0.979, P = 0.029) and male sex (OR = 0.528, P = 0.038) were negatively correlated with the occurrence of higher symptom burden, while prolonged fever (OR = 8.156, P < 0.001) was a significant risk factor. Reduced estimated glomerular filtration rate and thrombocytopenia were associated with longer disease duration. Phylogenetic analysis revealed that the outbreak-associated CHIKV strains belonged to MAL and harbored the E1-A226V and E2-I211T mutations.

Conclusion: These findings provide an evidence base for clinical management and prognostic assessment during CHIKF outbreaks and underscore the importance of monitoring laboratory parameters alongside molecular surveillance.

Global public health is formidably threatened by antimicrobial resistance (AMR). Antimicrobial susceptibility testing (AST) is characterized by its long duration. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is notable for its rapid analysis and cost-effectiveness. However, its role in AST has not been fully explored. In recent years, new opportunities for predicting AMR using MALDI-TOF MS data have been provided by the development of machine learning (ML) technologies. The research progress in using MALDI-TOF MS combined with ML for AMR testing is surveyed by this review, and critical steps including raw MALDI-TOF MS data acquisition, raw data preprocessing, algorithm selection, hyperparameter optimization, among others. It was found by us that the true resistance status can be comprehensively reflected by large-scale datasets, but effective management of high-dimensional data challenges is required. Algorithm performance can be enhanced by identifying the optimal combination of hyperparameters. Better predictive performance than individual models can be achieved by stacking ensemble learning methods. Model performance and generalizability can be more effectively assessed by metrics such as the Area Under the Receiver Operating Characteristic Curve (AUROC). The decision-making process can be understood by users with the help of model interpretation, thereby increasing model transparency and acceptability. Insufficient sample size, inadequate data standardization, and limited model generalizability are included in the current challenges. Continuously optimized, the integration of MALDI-TOF MS and ML is poised to open future avenues for rapid and accurate AMR prediction.

Highly pathogenic avian influenza (HPAI) viruses of clade 2.3.4.4b continue to diversify through reassortment with co-circulating low-pathogenic avian influenza (LPAI) viruses and are repeatedly introduced into South Korea via migratory flyways. During national wild bird surveillance in October 2025, two HPAI viruses of different subtypes, H5N1 and H5N9, were detected in Common teals in the southwestern Korea. Whole-genome sequencing confirmed both isolates as clade 2.3.4.4b viruses belonging to the G2c sub-lineage. Phylogenetic analysis showed that the H5N1 virus possessed a genomic backbone related to the 22G4 genotype circulating in Korea during the 2022-2023 season, incorporating a PB1 segment derived from LPAI viruses. The H5N9 virus represented a distinct reassortant carrying an NA gene closely related to H11N9 LPAI viruses and internal segments associated with KorD and KorC genotypes prevalent in the same season. Bayesian time-scaled analysis indicated that both isolates originated from an East Asian H5Nx lineage with a common ancestor around 2019, and that the H5N1 virus diverged from a closely related Chinese strain in late 2023. Both viruses harbored multiple mammalian-adaptation markers, including substitutions commonly detected in recent East Asian HPAI strains. These findings demonstrate ongoing inter-lineage reassortment between regional HPAI and LPAI gene pools, emphasizing the continued role of migratory waterfowl in introducing emerging variants into Korea. The early-season detection of genetically distinct reassortants highlights the importance of sustained wild bird surveillance, rapid genomic characterization, and international data sharing to track the evolution and spread of newly emerging HPAI lineages.

Background: Infectious bovine rhinotracheitis virus (IBRV) is a primary pathogen causing bovine respiratory disease syndrome. This virus can cause rhinotracheitis and vaginitis in cattle, resulting in high mortality and posing a serious threat to bovine production. MicroRNAs (miRNAs), a class of regulatory non-coding small RNAs, can modulate viral replication by influencing host immune responses. However, reports on the association between host miRNAs and IBRV infection are limited.

Methods: In this study, we screened differentially expressed miRNAs in MDBK cells after IBRV infection and determined that the expression of bta-miR-146b was significantly increased. We investigated the effects of bta-miR-146b on IBRV replication and its underlying molecular mechanisms using molecular biological techniques such as luciferase activity assays, Western Blot, and qRT-PCR, together with bioinformatics approaches.

Results: We found that bta-miR-146b expression was up-regulated in IBRV-infected MDBK cells. Furthermore, transfection with bta-miR-146b mimics promoted IBRV replication in MDBK cells, whereas transfection with bta-miR-146b inhibitors inhibited IBRV replication, indicating that bta-miR-146b is a pro-infection factor. Additional studies showed that bta-miR-146b mimics inhibited type I interferon expression in MDBK cells, whereas its inhibitors enhanced it. Moreover, we identified IRAK1 as a direct target of bta-miR-146b and found that silencing IRAK1 expression rescued the effects of bta-miR-146b on viral replication and type I interferon expression.

Conclusion: These results suggest that bta-miR-146b regulates type I interferon expression and IBRV replication in MDBK cells by targeting IRAK1, and plays a key role in IBRV infection.

Objective: This study aimed to compare the effects of clear aligners (CA) and fixed appliances (FA) on periodontal indices, oral microbiota, and oxidative stress markers. Potential associations between microbial changes, oxidative stress, and periodontal health were also explored.

Methods: Twenty-four orthodontic patients matched at baseline were randomly allocated to the CA (n = 12) and FA (n = 12) groups. Saliva, supragingival plaque, and gingival crevicular fluid (GCF) were collected at baseline (T0), 3 months (T1), and 6 months (T2). Periodontal indices, including plaque index (PI), gingival index (GI), probing depth (PD), bleeding on probing (BOP) were recorded. Microbial composition was assessed via 16S rDNA sequencing. 8-Hydroxy-2'-deoxyguanosine (8-OHdG, a stable biomarker of oxidative DNA damage reflecting ROS levels) in saliva and GCF was quantified using double-antibody sandwich ELISA. Associations were analyzed using Spearman correlation.

Results: PI was significantly higher in the FA group than CA group at T1 (P < 0.01) and T2 (P < 0.05). BOP was higher in the FA group than CA group at T2 (P < 0.05). Pathogenic genera (Prevotella, Veillonella) were enriched in the FA group, while health-associated Rothia and Lautropia predominated in the CA group (P < 0.05). In GCF, 8-OHdG levels were higher in the FA group than CA group at T2 (P < 0.001). In saliva, Prevotella positively correlated with 8-OHdG in the FA group (r = 0.61, P < 0.05); Prevotella negatively correlated with Rothia in both groups (r = -0.90, P < 0.001).

Conclusions: Fixed appliances were associated with enrichment of pathogenic taxa, elevated oxidative stress markers, and worse periodontal indices, potentially linked to higher periodontitis risk. Clear aligners showed less microbial disruption and health-associated taxa enrichment. The Prevotella-8-OHdG-Rothia axis highlights microbiota and oxidative stress interactions as promising targets for preventing orthodontic treatment related periodontal complications.