Development of novel parameters for pathogen identification in clinical metagenomic next-generation sequencing.

Introduction: Metagenomic next-generation sequencing (mNGS) has emerged as a powerful tool for rapid pathogen identification in clinical practice. However, the parameters used to interpret mNGS data, such as read count, genus rank, and coverage, lack explicit performance evaluation. In this study, the developed indicators as well as novel parameters were assessed for their performance in bacterium detection. Methods: We developed several relevant parameters, including 10M normalized reads, double-discard reads, Genus Rank Ratio, King Genus Rank Ratio, Genus Rank Ratio*Genus Rank, and King Genus Rank Ratio*Genus Rank. These parameters, together with frequently used read indicators including raw reads, reads per million mapped reads (RPM), transcript per kilobase per million mapped reads (TPM), Genus Rank, and coverage were analyzed for their diagnostic efficiency in bronchoalveolar lavage fluid (BALF), a common source for detecting eight bacterium pathogens: Acinetobacter baumannii, Klebsiella pneumoniae, Streptococcus pneumoniae, Staphylococcus aureus, Hemophilus influenzae, Stenotrophomonas maltophilia, Pseudomonas aeruginosa, and Aspergillus fumigatus. Results: The results demonstrated that these indicators exhibited good diagnostic efficacy for the eight pathogens. The AUC values of all indicators were almost greater than 0.9, and the corresponding sensitivity and specificity values were almost greater than 0.8, excepted coverage. The negative predictive value of all indicators was greater than 0.9. The results showed that the use of double-discarded reads, Genus Rank Ratio*Genus Rank, and King Genus Rank Ratio*Genus Rank exhibited better diagnostic efficiency than that of raw reads, RPM, TPM, and in Genus Rank. These parameters can serve as a reference for interpreting mNGS data of BALF. Moreover, precision filters integrating our novel parameters were built to detect the eight bacterium pathogens in BALF samples through machine learning. Summary: In this study, we developed a set of novel parameters for pathogen identification in clinical mNGS based on reads and ranking. These parameters were found to be more effective in diagnosing pathogens than traditional approaches. The findings provide valuable insights for improving the interpretation of mNGS reports in clinical settings, specifically in BALF analysis.

Galectin-Receptor Interactions Regulates Cardiac Pathology Caused by Trichinella spiralis Infection.

The parasitic nematode Trichinella spiralis causes trichinellosis, a serious food-borne parasitic zoonosis worldwide. Infection with T. spiralis may also cause myocarditis. In the present study, we used mouse models to assess the impact of blockage of galectin-receptor interactions by α-lactose on cardiac immunopathology during acute T. spiralis experimental infection. Our data demonstrated that, after T. spiralis infection, blockage of galectin-receptor interactions resulted in cardiac dysfunction detected by transthoracic conventional echocardiography, and increased serum Gal-3 level, a biomarker of myocardial damage. In addition, there were increased eosinophil number in peripheral blood, and increased eosinophil infiltration in the heart and spleen tissues accompanied with increased mRNA levels of eosinophil granule proteins (including eosinophil cationic protein (ECP) and eosinophil peroxidase (EPO)) and IL-5 in these organs; increased cardiac fibrosis accompanied with increased Gal-3 and collagen 1 expressions in the hearts of mice with blockage of galectin-receptor interactions after T. spiralis infection. Correlation analysis showed that significant positive correlations existed between the mRNA levels of Gal-3 and ECP/EPO/eosinophil major basic protein/IL-5/CCL11/CCR3/α-SMA/collagen 1 in the hearts of both T. spiralis-infected mice and T. spiralis-infected mice with blockage of galectin-receptor interactions. Our data suggest that galectin-receptor interactions play a pivotal role during acute T. spiralis infection, and lack of galectin-receptor interactions upregulates Gal-3 which, in turn, leads to elevated heart eosinophil recruitment, exacerbated heart pathology and fibrosis, and heart functional damage.

Prognostic value of delta-like protein 3 combined with thyroid transcription factor-1 in small-cell lung cancer.

Rovalpituzumab tesirine is a promising delta-like protein 3 (DLL3)-targeted antibody-drug conjugate for the treatment of small-cell lung cancer (SCLC). Thyroid transcription factor-1 (TTF-1) and DLL3 protein are associated with SCLC, and may be used to identify patients, who respond to the DLL3-targeted therapy. However, little is known about the expression pattern of the DLL3 protein, and the prognostic value of DLL3 and TTF-1 for SCLC. A total of 335 patients with SCLC were identified, including 11 patients with paired biopsy of primary site and lobectomy specimens, and 37 patients with paired specimens of primary and metastatic site. The DLL3 expression levels of individuals were evaluated using the anti-DLL3 antibody. No differences in DLL3 expression levels were observed in paired biopsy and lobectomy specimens (P=0.774), and paired primary and metastatic sites (P=0.472). SCLC cases with high DLL3 expression levels were more frequent in male patients (P=0.041), smokers (P=0.023) and patients with positive TTF-1 expression (P=0.006) compared with DLL3-low SCLC. DLL3-high SCLC exhibited worse overall survival compared with DLL3-low SCLC (log-rank test, P=0.007). Patients with TTF-1+ SCLC experienced a significantly worse overall survival compared with patients with TTF-1- SCLC (P<0.001). DLL3-low/TTF-1- was defined as a distinct molecular subgroup of SCLC with optimal prognosis (P<0.001). DLL3-low/TTF-1- was an independent prognostic marker for SCLC (P=0.001). In conclusion, the present study, to the best of our knowledge, provided novel evidence for SCLC intratumoral and intertumoral homogeneity with the identification of DLL3 protein levels. Therefore, it is reliable to use biopsy specimens to evaluate DLL3 expression levels for identification of patients who may benefit from DLL3-targeted therapy. In addition, DLL3 and TTF-1 are two protein markers with potential clinical value in risk stratification for patients with SCLC.