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This research focuses on the direct and indirect systemic risk spillovers among East Asian, European, and U.S. stock markets under the COVID-19 pandemic. Based on the GARCH-Copula-CoVaR model, we construct the direct spillover matrix of systemic risk and further explore the indirect spillover path through R-vine. The empirical results first show via the direct path that Hong Kong exhibited the largest change in value of risk after the pandemic erupted. Second, the indirect path is that European and U.S. stock market risks are transmitted to China domestically via Hong Kong and Japan. The key nodes provide reference for risk prevention. • Focus on the direct and indirect systemic risk spillovers under the COVID-19 pandemic. • We construct the direct spillover matrix of systemic risk and further explore the indirect spillover path through R-vine. • Results first show in the direct path that Hong Kong exhibited the largest change value of risk after the pandemic erupted. • The indirect path is that European and U.S. stock market risks are transmitted to China domestically via Hong Kong and Japan. [ABSTRACT FROM AUTHOR]

Here, we report a type strain AST-10 representing a novel species Sulfurimonas hongkongensis within Epsilonproteobacteria, which is involved in marine sedimentary sulfur oxidation and denitrification. Strain AST-10 (= DSM 22096 = JCM 18418) was isolated from the coastal sediment at the Kai Tak Approach Channel connected to Victoria Harbour in Hong Kong. It grew chemolithoautotrophically using thiosulfate, sulfide or hydrogen as the sole electron donor and nitrate as the electron acceptor under anoxic conditions. It was rod-shaped and grew at 15-35°C (optimum at 30°C), pH 6.5-8.5 (optimum at 7.0-7.5), and 10-60 g L NaCl (optimum at 30 g L). Genome sequencing and annotation of strain AST-10 showed a 2,302,023 bp genome size, with 34.9% GC content, 2,290 protein-coding genes, and 42 RNA genes, including 3 rRNA genes. [ABSTRACT FROM AUTHOR]

Human sewage pollution is a major threat to public health because sewage always comes with pathogens. Human sewage is usually received and treated by wastewater treatment plants (WWTPs) to control pathogenic risks and ameliorate environmental health. However, untreated sewage that flows into water environments may cause serious waterborne diseases, as reported in India and Bangladesh. To examine the fate of the human sewage microbiome in a local municipal WWTP of Hong Kong, we used massively parallel sequencing of 16S rRNA gene to systematically profile microbial communities in samples from three sections (i.e., influent, activated sludge, and effluent) obtained monthly throughout 1 year. The results indicated that: (1) influent sewage bacterial profile reflected the human microbiome; (2) human gut bacterial community was the dominant force shaping influent sewage bacterial profile; (3) most human sewage bacteria could be effectively removed by the WWTP; (4) a total of 75 genera were profiled as potentially pathogenic bacteria, most of which were still present in the effluent although at a very low level; (5) a grouped pattern of bacterial community was observed among the same section samples but a dispersed pattern was found among the different section samples; and (6) activated sludge was less affected by the influent sewage bacteria, but it showed a significant impact on the effluent bacteria. All of these findings provide novel insights toward a mechanistic understanding of the fate of human sewage microbiome in the WWTP. [ABSTRACT FROM AUTHOR]

Abstract: In this study, solid phase extraction (SPE) and ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) were utilized to develop a rapid, sensitive and reliable method for trace analysis of 21 antibiotics belonging to 7 classes in influent and effluent of municipal wastewater treatment plant. Detection parameters for SPE preconcentration and UPLC-MS/MS analysis were optimized, including sample pH, eluant, mobile phase (solvent and formic acid concentration), column temperature, and flow rate. Under the optimal conditions, the recoveries for different antibiotics ranged from 60.5% to 109.7% and all analytes were detected within 10.0min by UPLC-MS/MS. The validation study indicated that the method detection limits (MDLs) for the 21 antibiotics were from 0.3 to 60.0ngL−1 for effluent, while higher MDLs (0.5–84.0ngL−1) for influent. Accuracy and precision for both within-run (−11.6 to 14.3% and 0.2 to 15.6%) and between-run tests (−7.2 to 8.7% and 1.9 to 16.4%) were acceptable. The analysis of influent and effluent samples of two municipal wastewater treatment plants in Hong Kong revealed the presence of 11 antibiotics, including ampicillin, cefalexin, sulfamethoxazole, sulfadiazine, norfloxacin, ciprofloxacin, ofloxacin, tetracycline, roxithromycin, erythromycin-H2O, and trimethoprim. Their concentration ranged from 3.5 to 720.0ngL−1 in influent and from 2.1 to 556.4ngL−1 in effluent. [Copyright &y& Elsevier]

• The latest version of Nanopore improves precision in wastewater viral surveillance. • Efficiency in fragmented viral genome detection is maximized with shorter amplicons. • As little as 0.001 Gb Nanopore data provides accurate real-time variant information. • Nanopore demonstrates utility in revealing dynamic SARS-CoV-2 patterns in Hong Kong. • Optimal cutoffs enable uncovering novel mutations and linking them with variants. Wastewater genomic sequencing stands as a pivotal complementary tool for viral surveillance in populations. While long-read Nanopore sequencing is a promising platform to provide real-time genomic data, concerns over the sequencing accuracy of the earlier Nanopore versions have somewhat restrained its widespread application in wastewater analysis. Here, we evaluate the latest improved version of Nanopore sequencing (R10.4.1), using SARS-CoV-2 as the model infectious virus, to demonstrate its effectiveness in wastewater viral monitoring. By comparing amplicon lengths of 400 bp and 1200 bp, we revealed that shorter PCR amplification is more suitable for wastewater samples due to viral genome fragmentation. Utilizing mock wastewater samples, we validated the reliability of Nanopore sequencing for variant identification by comparing it with Illumina sequencing results. The strength of Nanopore sequencing in generating real-time genomic data for providing early warning signals was also showcased, indicating that as little as 0.001 Gb of data can provide accurate results for variant prevalence. Our evaluation also identified optimal alteration frequency cutoffs (>50 %) for precise mutation profiling, achieving >99 % precision in detecting single nucleotide variants (SNVs) and insertions/deletions (indels). Monitoring two major wastewater treatment plants in Hong Kong from September 2022 to April 2023, covering over 4.5 million population, we observed a transition in dominant variants from BA.5 to XBB lineages, with XBB.1.5 being the most prevalent variants. Mutation detection also highlighted the potential of wastewater Nanopore sequencing in uncovering novel mutations and revealed links between signature mutations and specific variants. This study not only reveals the environmental implications of Nanopore sequencing in SARS-CoV-2 surveillance but also underscores its potential in broader applications including environmental health monitoring of other epidemic viruses, which could significantly enhance the field of wastewater-based epidemiology. [Display omitted] [ABSTRACT FROM AUTHOR]

• Testing protocols for DNA (mpox) and RNA (norovirus, rotavirus) viruses in wastewater were developed and validated. • Wastewater surveillance effectively tracked the diarrhea viruses' activity in the community. • The mpox virus signal was detectable in wastewater at a low prevalence area. • Four key components were provided to increase the values of wastewater surveillance network. The wastewater surveillance network successfully established for COVID-19 showed great potential to monitor other infectious viruses, such as norovirus, rotavirus and mpox virus. In this study, we established and validated detection methods for these viruses in wastewater. We developed a supernatant-based method to detect RNA viruses from wastewater samples and applied it to the monthly diarrhea viruses (norovirus genogroup I & II, and rotavirus) surveillance in wastewater treatment plants (WWTPs) at a city-wide level for 16 months. Significant correlations were observed between the diarrhea viruses concentrations in wastewater and detection rates in faecal specimens by clinical surveillance. The highest norovirus concentration in wastewater was obtained in winter, consistent with the seasonal pattern of norovirus outbreak in Hong Kong. Additionally, we established a pellet-based method to monitor DNA viruses in wastewater and detected weak signals for mpox virus in wastewater from a WWTP serving approximately 16,700 people, when the first mpox patient in Hong Kong was admitted to the hospital within the catchment area. Genomic sequencing provided confirmatory evidence for the validity of the results. Our findings emphasized the efficacy of the wastewater surveillance network in WWTPs as a cost-effective tool to track the transmission trend of diarrhea viruses and to provide sensitive detection of novel emerging viruses such as mpox virus in low-prevalence areas. The developed methods and surveillance results provide confidence for establishing robust wastewater surveillance programs to control infectious diseases in the post-pandemic era. [Display omitted] [ABSTRACT FROM AUTHOR]

• Two preanalytical methods (supernatant-based and pellet-based) were established for influenza A/B wastewater surveillance. • Sanger sequencing confirmed the presence of influenza A/B RNA in wastewater. • Wastewater influenza A virus concentration effectively reflected influenza activity in the community. • H1pdm virus was the dominant subtype in the community at the time of this study. • Wastewater surveillance can provide virus types and subtypes information for public health actions in the future. Wastewater surveillance is considered as a powerful tool in providing cost-effective, population-wide and near real-time surveillance results for controlling infectious diseases (i.e., SARS-CoV-2, influenza virus), complementary to clinical surveillance. To facilitate the utility of this emerging tool, we developed two preanalytical protocols (supernatant-based and pellet-based) for influenza A/B virus (IAV/IBV) wastewater surveillance and applied them to the established wastewater surveillance network for large-scale longitudinal monitoring in Hong Kong. We tested 724 wastewater samples from 24 stationary sites for weekly surveillance for 8 months and 458 wastewater samples from 11 wastewater treatment plants (WWTPs) for more frequent (three times per week) city-wide surveillance for 4 months when influenza season commenced. We found the city-wide IAV virus concentration in wastewater were associated with the detection rate and influenza-like illness plus rates (ILI+) of clinical respiratory specimens and increased significantly after the cancelling of mask mandate that was in place for COVID-19. IBV was at low detection rates and low virus concentration levels, consistent with the low detection rates observed by clinical surveillance. In addition, we conducted virus subtype identification in selected wastewater samples, and observed the H1pdm was the major circulation subtype. Moreover, the obtained virus signals were confirmed by Sanger sequencing of PCR products, suggesting the feasibility and applicability of established methods for rapid detection of influenza virus types and subtypes in wastewater surveillance. This study demonstrates the applicability of IAV/IBV wastewater surveillance to current wastewater infrastructures and it could be used as a rapid and cost-effective surveillance strategy to track virus transmission patterns in the community for timely public health actions in the future. [ABSTRACT FROM AUTHOR]

• Achieving reliable results with sequencing throughput above 0.5 Gb. • Validating performance of variant deconvolution pipeline. • Deciphering the variant prevalence through wastewater genomic sequencing. • Tracking variant trends 16 days earlier than clinical data using wastewater data. • Uncovering novel SARS-CoV-2 mutations and alleles in wastewater. Wastewater-based epidemiology (WBE) has been widely used as a complementary approach to SARS-CoV-2 clinical surveillance. Wastewater genomic sequencing could provide valuable information on the genomic diversity of SARS-CoV-2 in the surveyed population. However, reliable detection and quantification of variants or mutations remain challenging. In this study, we used mock wastewater samples created by spiking SARS-CoV-2 variant standard RNA into wastewater RNA to evaluate the impacts of sequencing throughput on various aspects such as genome coverage, mutation detection, and SARS-CoV-2 variant deconvolution. We found that wastewater datasets with sequencing throughput greater than 0.5 Gb yielded reliable results in genomic analysis. In addition, using in silico mock datasets, we evaluated the performance of the adopted pipeline for variant deconvolution. By sequencing 86 wastewater samples covering more than 6 million people over 7 months, we presented two use cases of wastewater genomic sequencing for surveying COVID-19 in Hong Kong in WBE applications, including the replacement of Delta variants by Omicron variants, and the prevalence and development trends of three Omicron sublineages. Importantly, the wastewater genomic sequencing data were able to reveal the variant trends 16 days before the clinical data did. By investigating mutations of the spike (S) gene of the SARS-CoV-2 virus, we also showed the potential of wastewater genomic sequencing in identifying novel mutations and unique alleles. Overall, our study demonstrated the crucial role of wastewater genomic surveillance in providing valuable insights into the emergence and monitoring of new SARS-CoV-2 variants and laid a solid foundation for the development of genomic analysis methodologies for WBE of other novel emerging viruses in the future. [Display omitted] [ABSTRACT FROM AUTHOR]

• A PEG-precipitation method was developed for high-throughput wastewater surveillance. • The PEG-precipitation method obtained a process limit of detection of 3286 copies/L. • The PEG-precipitation method could process over 100 samples by two persons per day. • The turnaround time was optimized by reducing the centrifugation and incubation time. The effective application of wastewater surveillance is dependent on testing capacity and sensitivity to obtain high spatial resolution testing results for a timely targeted public health response. To achieve this purpose, the development of rapid, high-throughput, and sensitive virus concentration methods is urgently needed. Various protocols have been developed and implemented in wastewater surveillance networks so far, however, most of them lack the ability to scale up testing capacity or cannot achieve sufficient sensitivity for detecting SARS-CoV-2 RNA at low prevalence. In the present study, using positive raw wastewater in Hong Kong, a PEG precipitation-based three-step centrifugation method was developed, including low-speed centrifugation for large particles removal and the recovery of viral nucleic acid, and medium-speed centrifugation for the concentration of viral nucleic acid. This method could process over 100 samples by two persons per day to reach the process limit of detection (PLoD) of 3286 copies/L wastewater. Additionally, it was found that the testing capacity could be further increased by decreasing incubation and centrifugation time without significantly influencing the method sensitivity. The entire procedure uses ubiquitous reagents and instruments found in most laboratories to obtain robust testing results. This high-throughput, cost-effective, and sensitive tool will promote the establishment of nearly real-time wastewater surveillance networks for valuable public health information. [Display omitted] [ABSTRACT FROM AUTHOR]

• Eight novel assays with high predictive value for eight variants. • Near real-time monitoring for emerging variants in the community. • Reliable quantification for mutation sites even in the sewage having variants mixture. • High correlation between clinical sequencing results and sewage variant signals. • A hierarchical detection workflow for flexible deployment of the method. To effectively control the ongoing outbreaks of fast-spreading SARS-CoV-2 variants, there is an urgent need to add rapid variant detection and discrimination methods to the existing sewage surveillance systems established worldwide. We designed eight assays based on allele-specific RT-qPCR for real-time allelic discrimination of eight SARS-CoV-2 variants (Alpha, Beta, Gamma, Delta, Omicron, Lambda, Mu, and Kappa) in sewage. In silico analysis of the designed assays for identifying SARS-CoV-2 variants using more than four million SARS-CoV-2 variant sequences yielded ∼100% specificity and >90% sensitivity. All assays could sensitively discriminate and quantify target variants at levels as low as 10 viral RNA copy/µL with minimal cross-reactivity to the corresponding nontarget genotypes, even for sewage samples containing mixtures of SARS-CoV-2 variants with differential abundances. Integration of this method into the routine sewage surveillance in Hong Kong successfully identified the Beta variant in a community sewage. Complete concordance was observed between the results of viral whole-genome sequencing and those of our novel assays in sewage samples that contained exclusively the Delta variant discharged by a clinically diagnosed COVID-19 patient living in a quarantine hotel. Our assays in this method also provided real-time discrimination of the newly emerging Omicron variant in sewage two days prior to clinical test results in another quarantine hotel in Hong Kong. These novel allelic discrimination assays offer a rapid, sensitive, and specific way for detecting multiple SARS-CoV-2 variants in sewage and can be directly integrated into the existing sewage surveillance systems. [Display omitted] [ABSTRACT FROM AUTHOR]

• We collected time-series influent, AS and effluent for metagenomic sequencing. • Prevalence of ARGs and MGEs was examined in effluents from global cities. • An online platform integrating the resistome risk ranking scheme was developed. • ARG variants with high risk were characterized in effluents. Wastewater treatment plants (WWTPs) are regarded as critical points in disseminating antibiotic resistance genes (ARGs). In particular, the discharging effluents from WWTPs generally bring downstream catchment areas exogenous ARGs and resistant bacteria. However, there lacks a sufficient assessment of the resistome and mobilome in effluents. In this study, a consecutive monthly sampling was conducted over 13 months in three Hong Kong (HK) WWTPs for metagenomic sequencing. Prevalence information of ARGs and mobile genetic elements (MGEs) was compared with counterparts in effluents from cities of North America, South America, Europe, and Asia. Moreover, a publicly accessible platform integrating the exposure ranking scheme, which was based on the global archive of ARG abundance, and a readily implementable online pipeline was developed to benefit communication in academia and government consultancy. Results demonstrated HK WWTPs were featured high ARG removal efficiency of 2.34–2.43 log reduction rate, and effluents were ranked in moderate levels of Level 2 and Level 3 in the exposure prioritizing scheme based on total ARG abundance. Moreover, absolute quantification of temporal variations of effluent resistome disclosed distinct changes over time among varied ARG types which were associated with prevalently used antibiotics, including quinolone and sulfonamide. This reinforces the need for real-time management of WWTP systems. Notably, ARGs of anthropogenic prevalence, high mobility, and potential pathogenicity were found to be present in HK effluents, drawing attention to the necessity for improved risk management. In addition, source tracking of effluent resistome and structural equation model analysis was conducted to explore the disparity in ARG abundance and diversity in different samples. The discovery of this study and the recommendation of a comprehensive exposure assessment will facilitate decision-making in resistome management in WWTPs to reduce the ARG and antibiotic resistant bacteria (ARB) contamination in the receiving environments. [Display omitted] [ABSTRACT FROM AUTHOR]

• High-resolution temporal profile of a broad-spectrum of ARGs in AS was obtained. • Both abundance and composition of ARGs changed significantly every two-three years. • The core resistome were found disseminated broadly in other ecotypes. • Structural linkages of AS resistomes and the contributing factors were built. • The HGT potential between AS bacteria was higher than that in soil. The spread of antibiotic resistance genes (ARGs) is a growing global problem. Activated sludge (AS) in wastewater treatment plants (WWTPs) has been proposed as a hotspot for ARGs. However, few studies have been conducted to uncover the temporal dynamics of the resistome of AS in WWTPs by long-term longitudinal sampling. In this study, we quantified ARGs and identified their host microbiome in a Hong Kong WWTP in 97 monthly AS samples spanning 9 years. Throughout this analysis, we demonstrated that both the abundance and structures of the resistome changed significantly every two to three years, implying that there was a successive selection of resistomes in the AS system over the study period. The detection of genes of antibiotic-resistant pathogens that are emerging major threats to public health in the AS samples, including mcr , CRE (carbapenem-resistant Enterobacteriaceae) and MRSA (methicillin-resistant Staphylococcus aureus)-related genes, highlight the role of WWTPs as reservoirs of ARGs. In addition, the core resistome (abundant and persistent genes) in AS were found to overlap with those in other ecosystems such as urban sewage, livestock feces, and fishpond sediments, revealing the broad dissemination of ARGs in WWTPs and other environments. Annual variation of resistomes were explained via structural equation modeling (SEM), which deciphered the structural linkages of determining factors such as the operational parameters, microbial community composition and horizontal gene transfer (HGT). Specifically, potentially relevant antibiotic resistance bacteria (ARBs) were explored and discussed based on assembly-based analyses and network correlations. Moreover, consistent with the clear relationship between resistomes and mobile genetic elements (MGEs), it was found that there was a relatively high potential for gene exchange in AS in comparison with soil genomes, which could be explained by the engineering features of WWTPs. Based on these findings, longitudinal monitoring of WWTPs is warranted for risk assessment to reveal emerging ARGs, resistome evolution, correlations with ARBs, and the potential for spread in downstream environments and concomitant exposure risks for humans. [ABSTRACT FROM AUTHOR]