Intrinsic β-lactam resistance in Stenotrophomonas maltophilia S. maltophilia is caused by blaL1 and/or blaL2, a kind of metallo-β-lactamase with a broad substrate spectrum including carbapenems. A rapid and sensitive molecular method for the detection of blaL1 in clinical samples is needed to guide therapeutic treatment. In present study, we first described a loop-mediated isothermal amplification (LAMP) method for the rapid detection of blaL1 in clinical samples by using two methods including a chromogenic method using calcein/Mn2+ complex and the real-time turbidity monitoring to assess the reaction. Then dissemination of L1-producing S. maltophilia was investigated from ICU patients in three top hospital in Beijing, China. The results showed that both methods detected the target DNA within 60 min under 65°C. The detection limit of LAMP was 3.79 pg/µl DNA, and its sensitivity 100-fold greater than that of conventional PCR. All 21 test strains except for S. maltophilia were negative for blaL1, indicative of the high-specificity of the primers for the blaL1. A total of 22 L1-positive isolates were identified for LAMP-based surveillance of blaL1 from 105 ICU patients with clinically suspected multi-resistant infections. The sequences of these blaL1 genes were conservative with only a few sites mutated, and the strains had highly resistant to β-lactam antibiotics. The MLST recovered that 22 strains belonged to seven different ST types. Furthermore, co-occurrence of blaL1 and blaL2 genes were detected in all of isolates. Strikingly, S. maltophilia DCPS-01 was recovered to contain blaL1, blaL2, and blaNDM‑1 genes, possessing an ability to hydrolyse all β-lactams antibiotics. Our data showed the diversity types of S. maltophilia carrying blaL1 and co-occurrence of many resistant genes in the clinical strains signal an ongoing and fast evolution of S. maltophilia resulting from their wide spread in the respiratory infections, and therefore will be difficult to control.

Background: The early identification of pathogens and their antibiotic resistance are essential for the management and treatment of patients affected by ventilator-associated pneumonia (VAP). However, microbiological culture may be time-consuming and has a limited culturability of many potential pathogens. In this study, we developed a rapid nanopore-based metagenomic next-generation sequencing (mNGS) diagnostic assay for detection of VAP pathogens and antimicrobial resistance genes (ARGs). Patients and Methods: Endotracheal aspirate (ETA) samples from 63 patients with suspected VAP were collected between November 2021 and July 2022. Receiver operating characteristic (ROC) curves were established to compare the pathogen identification performance of the target pathogen reads, reads percent of microbes (RPM) and relative abundance (RA). The evaluation of the accuracy of mNGS was performed comparing with the gold standard and the composite standard, respectively. Then, the ARGs were analyzed by mNGS. Results: ROC curves showed that RA has the highest diagnostic value and the corresponding threshold was 9.93%. The sensitivity and specificity of mNGS test were 91.3% and 78.3%, respectively, based on the gold standard, while the sensitivity and specificity of mNGS test were 97.4% and 100%, respectively, based on the composite standard. A total of 13 patients were virus-positive based on mNGS results, while the coinfection rate increased from 27% to 46% compared to the rate obtained based on clinical findings. The mNGS test also performed well at predicting antimicrobial resistance phenotypes. Patients with a late-onset VAP had a significantly greater proportion of ARGs in their respiratory microbiome compared to those with early-onset VAP (P = 0.041). Moreover, the median turnaround time of mNGS was 4.43 h, while routine culture was 72.00 h. Conclusion: In this study, we developed a workflow that can accurately detect VAP pathogens and enable prediction of antimicrobial resistance phenotypes within 5 h of sample receipt by mNGS.

Background: Early availability of pathogen identification in urinary tract infections (UTIs) has critical importance in disease management. Metagenomic next-generation sequencing (mNGS) has the potential to transform how acute and serious infections are diagnosed by offering unbiased and culture-free pathogen detection. However, clinical experience with application of the mNGS test is relatively limited. Methods: We therefore established a MinION-based mNGS pathogens diagnostic platform and evaluated its potential for clinical implementation in UTIs with clinical samples. 213 urine samples from patients with suspected UTIs were included and subjected to mNGS testing using the MinION platform. mNGS results were compared to the gold standard of clinical culture and composite standard of combining clinical testing, confirmatory qPCR testing, and clinical adjudication by doctors. Results: The mNGS exhibited a sensitivity of 81.4% and a specificity of 92.3%, along with a positive predictive value of 96.6%, a negative predictive value of 64.9%, and an overall accuracy of 84.4%, all of which were determined based on the gold standard of routine culture results. When assessed against the composite standard, the sensitivity and specificity both increased to 89.9% and 100%, respectively, while the accuracy rose to 92.4%. Notably, the positive predictive value and negative predictive value also saw improvements, reaching 100% and 76.8%, respectively. Moreover, this diagnostic platform successfully identified dsDNA viruses. Among the 65 culture-negative samples, the viral detection rate reached 33.8% (22/65) and was subsequently validated through qPCR. Furthermore, the automatic bioinformatics pipeline we developed enabled one-click analysis from data to results, leading to a significant reduction in diagnosis time. Conclusion: These results demonstrate that the pathogen detection performance of mNGS is sufficient for diagnostic testing in clinical settings. As the method is generally unbiased, it can improve diagnostic testing of UTIs and other microbial infections.

Toll-like receptor 9 (TLR9) recognises unmethylated CpG DNA and activates a signalling cascade, leading to the production of inflammatory cytokines such as TNF-α, IL-1, IL-6 and IL-12 via the adaptor protein MyD88. However, the specific sequence and structural requirements of the CpG DNA for the recognition of and binding to TLR9 are unknown. Moreover, the 3D structures of TLR9 and the TLR9-ODN complex have not been determined. In this study, we propose a reliable model of the interaction of the TLR9 ECD with CpG ODN using bioinformatics tools.

Purpose: To evaluate the clinical significance of pro-inflammatory cytokines for disease severity and coagulation in septic patients with bacterial co-infection. Methods: A total of 92 patients with sepsis admitted to intensive care unit (ICU) from January 2017 to August 2020 were enrolled and their clinical data were retrospectively analyzed. Forty-seven patients (51.1%) had a single infection by Klebsiella pneumoniae or Acinetobacter baumannii (single-infection group), and 45 patients (48.9%) were infected by both species (co-infection group). We compared the clinical characteristics and disease severity among the 92 patients. Disease severity was defined as ICU stay time and 30-day mortality. Plasma concentrations of pro-inflammatory cytokines and their correlation with disease severity and blood coagulation were analyzed. Results: The 30-day mortality in the co-infection group (35.5%) was significantly higher than in the single-infection group (19.1%). The levels of IL-6 and TNF-α in the co-infection group were higher than in the single-infection group. Moreover, high levels of IL-6, IL-8, and TNF-α were positively correlated with disease severity (Spearman P value < 0.05). High levels of IL-6 and TNF-α were negatively correlated with the platelet count (Spearman P value < 0.05) and positively correlated with prothrombin time, and plasma levels of fibrin degradation product and D-dimer levels (Spearman P value < 0.05 for all). Conclusion: Septic patients with bacterial co-infection had increased plasma levels of pro-inflammatory cytokines. Furthermore, a positive correlation between high levels of pro-inflammatory cytokines and increased disease severity and depressed blood coagulation function for septic patients with co-infection was identified.

Objective: Influenza B virus (IBV) is highly contagious, spreads rapidly, and causes seasonal epidemic respiratory disease in the human population, especially in immunocompromised people and young children. Clinical manifestations in this high-risk population are often more severe than in immunocompetent hosts and sometimes atypical. Therefore, rapid, and accurate detection of IBV is important.Methods: An amplified luminescent proximity homogeneous assay linked immunosorbent assay (AlphaLISA) was developed for detection of IBV by optimizing the ratio of IBV antibody-labeled receptor beads, streptavidin-conjugated donor beads and biotinylated IBV antibody, as well as the optimal temperature and time conditions for incubation. Assay sensitivity, specificity and reproducibility were evaluated. A total of 228 throat swab samples and inactivated influenza B virus were tested by AlphaLISA and lateral flow colloidal gold-based immunoassay (LFIA).Results: AlphaLISA produced the best results for detection of inactivated influenza B virus when IBV antibody-labeled acceptor beads were 50 μg/ mL, streptavidin-conjugated donor beads were 40 μg/mL, and biotinylated IBV antibody was 0.5 μg/mL at 37°C for 15–10 min. Under these conditions, AlphaLISA had a limit of detection of 0.24 ng/mL for the detection of influenza B nucleoprotein, did not cross react with other common respiratory viruses, and showed good reproducibility with inter-assay coefficient of variation (CV) and intra-assay CV < 5%. The results of 228 clinical throat swab samples showed good agreement between AlphaLISA and LFIA (Kappa = 0.982), and AlphaLISA showed better sensitivity than LFIA for detecting inactivated influenza B virus.Conclusion: AlphaLISA showed higher sensitivity and throughput in the detection of IBV and can be used for IBV diagnosis and epidemic control.