A novel synthetic nucleic acid mixture for quantification of microbes by mNGS.

Metagenomic next-generation sequencing (mNGS) provides considerable advantages in identifying emerging and re-emerging, difficult-to-detect and co-infected pathogens; however, the clinical application of mNGS remains limited primarily due to the lack of quantitative capabilities. This study introduces a novel approach, KingCreate-Quantification (KCQ) system, for quantitative analysis of microbes in clinical specimens by mNGS, which co-sequence the target DNA extracted from the specimens along with a set of synthetic dsDNA molecules used as Internal-Standard (IS). The assay facilitates the conversion of microbial reads into their copy numbers based on IS reads utilizing a mathematical model proposed in this study. The performance of KCQ was systemically evaluated using commercial mock microbes with varying IS input amounts, different proportions of human genomic DNA, and at varying amounts of sequence analysis data. Subsequently, KCQ was applied in microbial quantitation in 36 clinical specimens including blood, bronchoalveolar lavage fluid, cerebrospinal fluid and oropharyngeal swabs. A total of 477 microbe genetic fragments were screened using the bioinformatic system. Of these 83 fragments were quantitatively compared with digital droplet PCR (ddPCR), revealing a correlation coefficient of 0.97 between the quantitative results of KCQ and ddPCR. Our study demonstrated that KCQ presents a practical approach for the quantitative analysis of microbes by mNGS in clinical samples.

Case report: Intraabdominal infection of Mycobacterium syngnathidarum in an immunocompetent patient confirmed by whole-genome sequencing.

Background: The taxonomic group of non-tuberculous mycobacteria (NTM) encompasses more than 190 species and subspecies, some of which can cause pulmonary and extrapulmonary diseases across various age groups in humans. However, different subspecies exhibit differential drug sensitivities, and traditional detection techniques struggle to accurately classify NTM. Therefore, clinicians need more effective detection methods to identify NTM subtypes, thus providing personalized medication for patients. Case presentation: We present the case of a 47-year-old female patient diagnosed with an intraabdominal infection caused by Mycobacterium syngnathidarum. Despite computed tomography of the chest suggesting potential tuberculosis, tuberculosis infection was ruled out due to negative TB-DNA results for ascites fluid and sputum and limited improvement of lung lesions after treatment. Additionally, acid-fast staining and Lowenstein-Jensen culture results revealed the presence of mycobacterium in ascites fluid. Subsequent whole-genome sequencing (WGS) confirmed the DNA sequences of Mycobacterium syngnathidarum in colonies isolated from the ascites fluid, which was further corroborated by polymerase chain reaction and Sanger sequencing. Ultimately, the patient achieved a complete recovery following the treatment regimen targeting Mycobacterium syngnathidarum, which involved clarithromycin, ethambutol hydrochloride, pyrazinamide, rifampicin, and isoniazid. Conclusion: This is the first reported case of Mycobacterium syngnathidarum infection in humans. Mycobacterium syngnathidarum was detected by WGS in this case, suggesting that WGS may serve as a high-resolution assay for the diagnosis of different subtypes of mycobacterium infection.

Speculation on optimal numbers of examined lymph node for early-stage epithelial ovarian cancer from the perspective of stage migration.

Introduction: In early-stage epithelial ovarian cancer (EOC), how to perform lymphadenectomy to avoid stage migration and achieve reliable targeted excision has not been explored in depth. This study comprehensively considered the stage migration and survival to determine appropriate numbers of examined lymph node (ELN) for early-stage EOC and high-grade serous ovarian cancer (HGSOC). Methods: From the Surveillance, Epidemiology, and End Results database, we obtained 10372 EOC cases with stage T1M0 and ELN ≥ 2, including 2849 HGSOC cases. Generalized linear models with multivariable adjustment were used to analyze associations between ELN numbers and lymph node stage migration, survival and positive lymph node (PLN). LOESS regression characterized dynamic trends of above associations followed by Chow test to determine structural breakpoints of ELN numbers. Survival curves were plotted using Kaplan-Meier method. Results: More ELNs were associated with more node-positive diseases, more PLNs and better prognosis. ELN structural breakpoints were different in subgroups of early-stage EOC, which for node stage migration or PLN were more than those for improving outcomes. The meaning of ELN structural breakpoint varied with its location and the morphology of LOESS curve. To avoid stage migration, the optimal ELN for early-stage EOC was 29 and the minimal ELN for HGSOC was 24. For better survival, appropriate ELN number were 13 and 8 respectively. More ELNs explained better prognosis only at a certain range. Discussion: Neither too many nor too few numbers of ELN were ideal for early-stage EOC and HGSOC. Excision with appropriate numbers of lymph node draining the affected ovary may be more reasonable than traditional sentinel lymph node resection and systematic lymphadenectomy.

Changes in inflammatory factors, oxidative stress, glucose and lipid metabolism, and insulin resistance in patients with polycystic ovary syndrome.

Polycystic ovary syndrome (PCOS) is a common disease in women, affecting women's menstruation and significantly impacting women's physical and mental health. Studies have shown that insulin resistance has an important relationship with polycystic ovary. It is of great significance to explore the changes of inflammatory factors, oxidative stress, glucose and lipid metabolism, and insulin resistance in patients with PCOS. In the study process, 642 polycystic ovary patients in the first half of 2019 were divided into insulin resistance (n=357) and non-insulin resistance (n=285) groups. Oxidative stress index, glucose, and lipid metabolism index, and inflammatory factors were detected during the study process. The results showed that the levels of hs-CRP, TNF- α, and IL-6 in the IR group were 5.9mg/L, 9.2µg/L, and 87.2ng /ml, while those in the non-IR group were 4.6mg/L, 6.3µg/L and 51.5ng/ml, respectively. Thus, IL-6 and insulin levels maintain a dynamic balance. Low levels of IL-6 can promote insulin secretion, while high levels can inhibit its secretion. The results of this study will provide a specific clinical reference value for the prevention and treatment of polycystic ovary syndrome.

Integrating the salivary microbiome in the forensic toolkit by 16S rRNA gene: potential application in body fluid identification and biogeographic inference.

Saliva is a common body fluid with significant forensic value used to investigate criminal cases such as murder and assault. In the past, saliva identification often relied on the α-amylase test; however, this method has low specificity and is prone to false positives. Accordingly, forensic researchers have been working to find new specific molecular markers to refine the current saliva identification approach. At present, research on immunological methods, mRNA, microRNA, circRNA, and DNA methylation is still in the exploratory stage, and the application of these markers still has various limitations. It has been established that salivary microorganisms exhibit good specificity and stability. In this study, 16S rDNA sequencing technology was used to sequence the V3-V4 hypervariable regions in saliva samples from five regions to reveal the role of regional location on the heterogeneity in microbial profile information in saliva. Although the relative abundance of salivary flora was affected to a certain extent by geographical factors, the salivary flora of each sample was still dominated by Streptococcus, Neisseria, and Rothia. In addition, the microbial community in the saliva samples in this study was significantly different from that in the vaginal secretions, semen, and skin samples reported in our previous studies. Accordingly, saliva can be distinguished from the other three body fluids and tissues. Moreover, we established a prediction model based on the random forest algorithm that could distinguish saliva between different regions at the genus level even though the model has a certain probability of misjudgment which needs more in-depth research. Overall, the microbial community information in saliva stains might have prospects for potential application in body fluid identification and biogeographic inference.

Development and identification of a prognostic nomogram model for patients with mixed cell adenocarcinoma of the ovary.

BACKGROUND: Mixed cell ovarian adenocarcinoma (MCOA) is a malignant gynecologic tumor consisting of serous, mucous, and papillary tumor cells. However, the clinical features and prognosis of MCOA patients are unclear. METHODS: In this study, univariate and multivariate Cox proportional risk models were performed to identify independent prognostic factors. The Kaplan-Meier method was used to assess the relationship between clinical characteristics and patient survival. Finally, a nomogram was constructed and validated to predict patient survival time, and the C-index was used to evaluate the efficacy of the nomogram. RESULTS: A total of 2,818 patients diagnosed with MCOA were identified, and the 5-year survival rate was 62%. Univariate and multivariate Cox models suggested that age (HR=1.28, 95% CI[1.15,1.44]), grade (HR=1.26, 95% CI[1.12,1.41]), SEER stage (HR=1.63, 95% CI[1.25,2.13]) and AJCC (American Joint Committee on Cancer) stage (HR=1.59, 95% CI[1.36,1.86]) were independent prognostic factors for MCOA patients. After propensity score matching for age, grade, SEER stage, and AJCC stage, the 5-year survival rate was 69.7% for ovarian serous cystadenocarcinoma and 62.9% for ovarian papillary serous cystadenocarcinoma. These results mean that serous adenocarcinoma had the best prognosis of the three pathologic types of ovarian carcinoma (p<0.0001), with no significant difference between papillary serous cystadenocarcinoma and MCOA (p=0.712). Finally, a nomogram consisting of age, grade, SEER stage, and AJCC stage was established and validated to predict the survival time, with C-indices of 0.743 and 0.731, respectively. CONCLUSIONS: In summary, MCOA is uncommon, and age, grade, SEER stage, and AJCC stage are independent prognostic factors. Compared with other common malignant ovarian tumors, MCOA has a poor prognosis.

Genetic composition of Teochew population in Chaozhou revealed by 19 STR loci: population polymorphism and interpopulation comparisons.

Aim: To investigate the genetic polymorphisms of 19 STR loci in the Teochew population of Chaozhou. Subjects and methods: Nineteen STR loci of 631 unrelated Teochew people in Chaozhou were detected by using the AGCU Expressmarker 20 kit. Results: The allele frequency ranged from 0.0008-0.5577. The combined power of discrimination and combined probability of excluding paternity is over 0.999,999,999,999,999,999,999,999,999,999 and 0.999,999,992,549,546, respectively. The principal component analysis based on the 11 shared STR loci showed the Teochew population was most genetically related to the Fujian Han population. Conclusion: The results demonstrate the set of 19 autosomal STRs could provide robust genetics information for individual identification, paternity testing and human genetics research in the Teochew population.