Clinical evaluation of a novel digital microfluidic based point-of-care test platform for detection of SARS-Cov-2 and influenza A/B.

Respiratory pathogens, such as SARS-CoV-2 and influenza A/B, can cause severe illnesses in susceptible individuals. This research evaluated a novel digital microfluidic point-of-care testing platform designed to detect 23 pathogens, comparing its performance to conventional laboratory-based nucleic acid tests. The platform integrates nucleic acid extraction and amplification processes for rapid detection with only 2 min of hands-on time. Performance assays demonstrated that the platform has high sensitivity (87 %-100 %) and specificity (99 %-100 %) for the detection of the evaluated 3 viruses. Additionally, the platform can be adapted for the detection of other respiratory pathogens, aiding in the early diagnosis of respiratory diseases, identifying the source of an outbreak or epidemic, and curbing the spread of the disease.

A Food Poisoning Caused by Salmonella Enterica (S. Enteritidis) ST11 Carrying Multi-Antimicrobial Resistance Genes in 2019, China.

Purpose: This study was to identify and analyze the pathogen responsible for food poisoning in a tourist group traveling from Macao to Zhuhai. Patients and Methods: Samples were obtained from 27 patients of 96 cases, as well as samples of contaminated food in Macau. The collected samples were subjected to serological identification, drug sensitivity analysis, drug resistance gene identification, virulence factor analysis, and tracing. Results: Twenty-six isolates and the salad isolate were S. enteritidis ST11. Isolates from patients were exhibited significant resistance to Penicillin AMP (Ampicillin) and quinolones NAL (Nalidixic acid). Among these isolates, 21 strains were resistant to two or more antibiotics, indicating the multi-drug resistance (MDR). Genomic characteristics and phylogenetic analysis were performed on 9 of the isolates using whole genome sequencing (WGS). The analysis revealed that the resistance to AMP and NAL was primarily caused by a gryA mutation D87Y (9/9, 100%), and the presence of beta-lactam resistance genes blaOXA-1 (1/9, 11.11%), blaTEM-141 (1/9, 11.11%), and blaTEM-1B (8/9, 88.89%). It was also found a strains isolated from patients had two resistance genes to quinolones or beta-lactam drugs (1/8, 12.5%), respectively. The strains were found to possess 165 virulence genes, one adherence class virulence factor, one invasion class virulence factor and various pathogenicity islands, including SPI-1, SPI-2, SPI-3, SPI-4, SPI-5, SPI-9, SPI-10, SPI-13, SPI-14, SPI-15, SGI 1, CS54_island, and C63PI-1. Additionally, the virulence plasmids were detected, including IncFIB(s)-IncFII(s)-IncX1 (55.56%), IncFIB(s)-IncFII(s) (33.33%), and IncFIB(s)-IncFII(s)-IncHI2-IncHI2A (11.11%). PFGE (Pulsed Field Gel Electrophoresis) and phylogenetic tree analysis revealed a high degree of similarity between Salmonella isolates from patients and food samples from Macao. Conclusion: This study identified Salmonella enterica ST11 as the cause of the food poisoning outbreak. The findings highlight the importance of phenotypic characterization and next-generation sequencing (NGS) tools in epidemiological studies and emphasize the potential risk of a new emerging multi-antibiotic ST11 clone for S. enteritidis.

Hepatitis C virus subtype diversity and transmission clusters characteristics among drug users in Zhuhai, South China.

BACKGROUND: Hepatitis C virus (HCV) infection poses a major public health challenge globally, especially among injecting drug users. China has the world's largest burden of HCV infections. However, little is known about the characteristics of transmission networks among drug user populations. This study aims to investigate the molecular epidemiology and transmission characteristics of HCV infections among drug users in Zhuhai, a bustling port city connecting Mainland China and its Special Administrative Regions. METHODS: Participants enrolled in this study were drug users incarcerated at Zhuhai's drug rehabilitation center in 2015. Their sociodemographic and behavioral information, including gender, promiscuity, drug use method, and so forth, was collected using a standardized questionnaire. Plasmas separated from venous blood were analyzed for HCV infection through ELISA and RT-PCR methods to detect anti-HCV antibodies and HCV RNA. The 5'UTR fragment of the HCV genome was amplified and further sequenced for subtype identifications and phylogenetic analysis. The phylogenetic tree was inferred using the Maximum Likelihood method based on the Tamura-Nei model, and the transmission cluster network was constructed using Cytoscape3.8.0 software with a threshold of 0.015. Binary logistic regression models were employed to assess the factors associated with HCV infection. RESULTS: The overall prevalence of HCV infection among drug users was 44.37%, with approximately 19.69% appearing to clear the HCV virus successfully. Binary logistic regression analysis revealed that those aged over 40, engaging in injecting drug use, and being native residents were at heightened risk for HCV infection among drug user cohorts. The predominant HCV subtypes circulating among those drug users were 6a (60.26%), followed by 3b (16.7%), 3a (12.8%), 1b (6.41%) and 1a (3.85%), respectively. Molecular transmission network analysis unveiled the presence of six transmission clusters, with the largest propagation cluster consisting of 41 individuals infected with HCV subtype 6a. Furthermore, distinct transmission clusters involved eight individuals infected with subtype 3b and seven with subtype 3a were also observed. CONCLUSION: The genetic transmission networks revealed a complex transmission pattern among drug users in Zhuhai, emphasizing the imperative for a targeted and effective intervention strategy to mitigate HCV dissemination. These insights are pivotal for shaping future national policies on HCV screening, treatment, and prevention in port cities.

High Genetic Diversity of HIV-1 and Active Transmission Clusters among Male-to-Male Sexual Contacts (MMSCs) in Zhuhai, China.

Monitoring genetic diversity and recent HIV infections (RHIs) is critical for understanding HIV epidemiology. Here, we report HIV-1 genetic diversity and RHIs in blood samples from 190 HIV-positive MMSCs in Zhuhai, China. MMSCs with newly reported HIV were enrolled from January 2020 to June 2022. A nested PCR was performed to amplify the HIV polymerase gene fragments at HXB2 positions 2604-3606. We constructed genetic transmission network at both 0.5% and 1.5% distance thresholds using the Tamura-Nei93 model. RHIs were identified using a recent infection testing algorithm (RITA) combining limiting antigen avidity enzyme immunoassay (LAg-EIA) assay with clinical data. The results revealed that 19.5% (37/190) were RHIs and 48.4% (92/190) were CRF07_BC. Two clusters were identified at a 0.5% distance threshold. Among them, one was infected with CRF07_BC for the long term, and the other was infected with CRF55_01B recently. We identified a total of 15 clusters at a 1.5% distance threshold. Among them, nine were infected with CRF07_BC subtype, and RHIs were found in 38.8% (19/49) distributed in eight genetic clusters. We identified a large active transmission cluster (n = 10) infected with a genetic variant, CRF79_0107. The multivariable logistic regression model showed that clusters were more likely to be RHIs (adjusted OR: 3.64, 95% CI: 1.51~9.01). The RHI algorithm can help to identify recent or ongoing transmission clusters where the prevention tools are mostly needed. Prompt public health measures are needed to contain the further spread of active transmission clusters.

A Digital Microfluidic RT-qPCR Platform for Multiple Detections of Respiratory Pathogens.

The coronavirus disease 2019 pandemic has spread worldwide and caused more than six million deaths globally. Therefore, a timely and accurate diagnosis method is of pivotal importance for controlling the dissemination and expansions. Nucleic acid detection by the reverse transcription-polymerase chain reaction (RT-PCR) method generally requires centralized diagnosis laboratories and skilled operators, significantly restricting its use in rural areas and field settings. The digital microfluidic (DMF) technique provides a better option for simultaneous detections of multiple pathogens with fewer specimens and easy operation. In this study, we developed a novel digital microfluidic RT-qPCR platform for multiple detections of respiratory pathogens. This method can simultaneously detect eleven respiratory pathogens, namely, mycoplasma pneumoniae (MP), chlamydophila pneumoniae (CP), streptococcus pneumoniae (SP), human respiratory syncytial virus A (RSVA), human adenovirus (ADV), human coronavirus (HKU1), human coronavirus 229E (HCoV-229E), human metapneumovirus (HMPV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A virus (FLUA) and influenza B virus (FLUB). The diagnostic performance was evaluated using positive plasmids samples and clinical specimens compared with off-chip individual RT-PCR testing. The results showed that the limit of detections was around 12 to 150 copies per test. The true positive rate, true negative rate, positive predictive value, negative predictive value, and accuracy of DMF on-chip method were 93.33%, 100%, 100%, 99.56%, and 99.85%, respectively, as validated by the off-chip RT-qPCR counterpart. Collectively, this study reported a cost-effective, high sensitivity and specificity on-chip DMF RT-qPCR system for detecting multiple respiratory pathogens, which will greatly contribute to timely and effective clinical management of respiratory infections in medical resource-limited settings.