ABSTRACT
Activated sludge is the centerpiece of biological wastewater treatment, as it facilitates removal of sewage-associated pollutants, fecal bacteria, and pathogens from wastewater through semi-controlled microbial ecology. It has been hypothesized that horizontal gene transfer facilitates the spread of antibiotic resistance genes within the wastewater treatment plant, in part because of the presence of residual antibiotics in sewage. However, there has been surprisingly little evidence to suggest that sewage-associated antibiotics select for resistance at wastewater treatment plants via horizontal gene transfer or otherwise. We addressed the role of sewage-associated antibiotics in promoting antibiotic resistance using lab-scale sequencing batch reactors fed field-collected wastewater, metagenomic sequencing, and our recently developed bioinformatic tool Kairos. Here, we found confirmatory evidence that fluctuating levels of antibiotics in sewage are associated with horizontal gene transfer of antibiotic resistance genes, microbial ecology, and microdiversity-level differences in resistance gene fate in activated sludge.
Subject(s)
Anti-Bacterial Agents , Bacteria , Gene Transfer, Horizontal , Sewage , Wastewater , Sewage/microbiology , Wastewater/microbiology , Anti-Bacterial Agents/pharmacology , Bacteria/genetics , Bacteria/classification , Bacteria/metabolism , Water Purification/methods , Metagenomics/methods , Drug Resistance, Microbial/genetics , Waste Disposal, Fluid/methods , Drug Resistance, Bacterial/genetics , Selection, GeneticABSTRACT
Wastewater-based surveillance (WBS) has gained attention as a strategy to monitor and provide an early warning for disease outbreaks. Here, we applied an isothermal gene amplification technique, reverse-transcription loop-mediated isothermal amplification (RT-LAMP), coupled with nanopore sequencing (LAMPore) as a means to detect SARS-CoV-2. Specifically, we combined barcoding using both an RT-LAMP primer and the nanopore rapid barcoding kit to achieve highly multiplexed detection of SARS-CoV-2 in wastewater. RT-LAMP targeting the SARS-CoV-2 N region was conducted on 96 reactions including wastewater RNA extracts and positive and no-target controls. The resulting amplicons were pooled and subjected to nanopore sequencing, followed by demultiplexing based on barcodes that differentiate the source of each SARS-CoV-2 N amplicon derived from the 96 RT-LAMP products. The criteria developed and applied to establish whether SARS-CoV-2 was detected by the LAMPore assay indicated high consistency with polymerase chain reaction-based detection of the SARS-CoV-2 N gene, with a sensitivity of 89% and a specificity of 83%. We further profiled sequence variations on the SARS-CoV-2 N amplicons, revealing a number of mutations on a sample collected after viral variants had emerged. The results demonstrate the potential of the LAMPore assay to facilitate WBS for SARS-CoV-2 and the emergence of viral variants in wastewater.
ABSTRACT
This study introduces a novel surface-enhanced Raman spectroscopy (SERS)-based lateral flow test (LFT) dipstick that integrates digital analysis for highly sensitive and rapid viral quantification. The SERS-LFT dipsticks, incorporating gold-silver core-shell nanoparticle probes, enable pixel-based digital analysis of large-area SERS scans. Such an approach enables ultralow-level detection of viruses that readily distinguishes positive signals from background noise at the pixel level. The developed digital SERS-LFTs demonstrate limits of detection (LODs) of 180 fg for SARS-CoV-2 spike protein, 120 fg for nucleocapsid protein, and 7 plaque forming units for intact virus, all within <30 min. Importantly, digital SERS-LFT methods maintain their robustness and their LODs in the presence of indoor dust, thus underscoring their potential for accurate and reliable virus diagnosis and quantification in real-world environmental settings.
Subject(s)
Metal Nanoparticles , Spike Glycoprotein, Coronavirus , Viruses , Humans , Spectrum Analysis, Raman/methods , Metal Nanoparticles/chemistry , Limit of Detection , Gold/chemistryABSTRACT
The sampling and analysis of sewage for pathogens and other biomarkers offers a powerful tool for monitoring and understanding community health trends and potentially predicting disease outbreaks. Since the early months of the COVID-19 pandemic, the use of wastewater-based testing for public health surveillance has increased markedly. However, these efforts have focused on urban and periurban areas. In most rural regions of the world, healthcare service access is more limited than in urban areas, and rural public health agencies typically have less disease outcome surveillance data than their urban counterparts. The potential public health benefits of wastewater-based surveillance for rural communities are therefore substantial - though so too are the methodological and ethical challenges. For many rural communities, population dynamics and insufficient, aging, and inadequately maintained wastewater collection and treatment infrastructure present obstacles to the reliable and responsible implementation of wastewater-based surveillance. Practitioner observations and research findings indicate that for many rural systems, typical implementation approaches for wastewater-based surveillance will not yield sufficiently reliable or actionable results. We discuss key challenges and potential strategies to address them. However, to support and expand the implementation of responsible, reliable, and ethical wastewater-based surveillance for rural communities, best practice guidelines and standards are needed.
Subject(s)
COVID-19 , Wastewater-Based Epidemiological Monitoring , Humans , Wastewater , Rural Population , Pandemics , COVID-19/epidemiologyABSTRACT
Surveillance of airborne viruses in crowded indoor spaces is crucial for managing outbreaks, as highlighted by the SARS-CoV-2 pandemic. However, the rapid and on-site detection of fast-mutating viruses, such as SARS-CoV-2, in complex environmental backgrounds remains challenging. Our study introduces a machine learning (ML)-driven surface-enhanced Raman spectroscopy (SERS) approach for detecting viruses within environmental dust matrices. By decomposing intact virions into individual structural components via a Raman-background-free lysis protocol and concentrating them into nanogap SERS hotspots, we significantly enhance the SERS signal intensity and fingerprint information density from viral structural components. Utilizing Principal Component Analysis (PCA), we establish a robust connection between the SERS data of these structural components and their biological sequences, laying a solid foundation for virus detection through SERS. Furthermore, we demonstrate reliable quantitative detection of SARS-CoV-2 using identified SARS-CoV-2 peaks at concentrations down to 102 pfu/ml through Gaussian Process Regression (GPR) and a digital SERS methodology. Finally, applying a Principal Component Analysis-Linear Discriminant Analysis (PCA-LDA) algorithm, we identify SARS-CoV-2, influenza A virus, and Zika virus within an environmental dust background with over 86% accuracy. Therefore, our ML-driven SERS approach holds promise for rapid environmental virus monitoring to manage future outbreaks.
Subject(s)
Biosensing Techniques , COVID-19 , Zika Virus Infection , Zika Virus , Humans , SARS-CoV-2 , COVID-19/diagnosis , Spectrum Analysis, Raman , Machine Learning , Virion , DustABSTRACT
Hydrogel-based three-dimensional (3D) cell culture systems mimic the salient elements of extracellular matrices and promote native cell function. However, high-resolution 3D cell imaging that can provide biological information about multiple features of individual cells is yet to be realized. In this context, we incorporated plasmonic gold nanoparticles (AuNPs) into an alginate/gelatin hydrogel to produce surface-enhanced Raman spectroscopy (SERS)-active hydrogel inks for the 3D printing and culturing of Vero cells. Dense incorporation of AuNPs enables production of a printed 3D grid structure with 3D SERS performance, but with no measurable adverse effects on cell growth. Label-free SERS spectra were collected within a hydrogel, and a random forest binary classifier was developed to discriminate Vero cell signals from the hydrogel background with an accuracy of 87.5%. The results suggest that SERS signals from cellular components, such as proteins, lipids, and carbohydrates, account for this discrimination. We demonstrate visualization of cell shape, location, and density by combining predicted binary maps with peak feature intensity maps in 2D and 3D. SERS images with a resolution of ≈3 µm match well with the microscopy images and show clear increases in intensity with incubation time. We suggest that 3D SERS cell imaging is a promising means to examine the effect of external cell stimuli on cellular behavior for diagnostic purposes.
Subject(s)
Gold , Metal Nanoparticles , Animals , Chlorocebus aethiops , Gold/chemistry , Metal Nanoparticles/chemistry , Hydrogels/chemistry , Vero Cells , Spectrum Analysis, Raman/methodsABSTRACT
There is growing interest in better understanding the environmental impacts of landfills and optimizing their operation. Accordingly, we developed a holistic framework to calculate a landfill's Ecological Footprint (EF) and applied that to the Fargo, North Dakota, landfill. Parallelly, the carbon footprint and biocapacity of the landfill were calculated. We calculated the EF for six scenarios (i.e., cropland, grazing land, marine land, inland fishing ground, forest land, and built land as land types) and six operational strategies typical for landfills. Operational strategies were selected based on the variations of landfill equipment, the gas collection system, efficiency, the occurrence of fugitive emissions, and flaring. The annual EF values range from 124 to 213,717 global hectares depending on land type and operational strategy. Carbon footprints constituted 28.01-99.98% of total EF, mainly driven by fugitive emissions and landfill equipment. For example, each percent increase in Fargo landfill's fugitive emissions caused the carbon footprint to rise by 2130 global hectares (4460 tons CO2e). While the landfill has biocapacity as grazing grass in open spaces, it remains unused/inaccessible. By leveraging the EF framework for landfills, operators can identify the primary elements contributing to a landfill's environmental impact, thereby minimizing it.
Subject(s)
Refuse Disposal , Triallate , North Dakota , Forests , Waste Disposal Facilities , Carbon FootprintABSTRACT
Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user's configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem.
ABSTRACT
Freshwater Salinization Syndrome (FSS) refers to groups of biological, physical, and chemical impacts which commonly occur together in response to salinization. FSS can be assessed by the mobilization of chemical mixtures, termed "chemical cocktails", in watersheds. Currently, we do not know if salinization and mobilization of chemical cocktails along streams can be mitigated or reversed using restoration and conservation strategies. We investigated 1) the formation of chemical cocktails temporally and spatially along streams experiencing different levels of restoration and riparian forest conservation and 2) the potential for attenuation of chemical cocktails and salt ions along flowpaths through conservation and restoration areas. We monitored high-frequency temporal and longitudinal changes in streamwater chemistry in response to different pollution events (i.e., road salt, stormwater runoff, wastewater effluent, and baseflow conditions) and several types of watershed management or conservation efforts in six urban watersheds in the Chesapeake Bay watershed. Principal component analysis (PCA) indicates that chemical cocktails which formed along flowpaths (i.e., permanent reaches of a stream) varied due to pollution events. In response to winter road salt applications, the chemical cocktails were enriched in salts and metals (e.g., Na+, Mn, and Cu). During most baseflow and stormflow conditions, chemical cocktails were less enriched in salt ions and trace metals. Downstream attenuation of salt ions occurred during baseflow and stormflow conditions along flowpaths through regional parks, stream-floodplain restorations, and a national park. Conversely, chemical mixtures of salt ions and metals, which formed in response to multiple road salt applications or prolonged road salt exposure, did not show patterns of rapid attenuation downstream. Multiple linear regression was used to investigate variables that influence changes in chemical cocktails along flowpaths. Attenuation and dilution of salt ions and chemical cocktails along stream flowpaths was significantly related to riparian forest buffer width, types of salt pollution, and distance downstream. Although salt ions and chemical cocktails can be attenuated and diluted in response to conservation and restoration efforts at lower concentration ranges, there can be limitations in attenuation during road salt events, particularly if storm drains bypass riparian buffers.
ABSTRACT
A prompt on-site, real-time method to detect bacterial antibiotic resistance is crucial for controlling the spread of resistance. Herein, we report the use of surface-enhanced Raman spectroscopy (SERS) for the monitoring of bioactive metabolites produced by ampicillin-resistant Pseudomonas aeruginosa strains and identification of mechanisms underlying antibiotic resistance. The results indicate that the blue-green pigment pyocyanin (PYO) dominates the metabolite signals and is significantly enhanced upon exposure to subminimal inhibitory concentrations of ampicillin. PYO accumulates during exponential growth and subsequently either diffuses into the culture medium or is consumed in response to nutrient deprivation. The SERS spectra further reveal that the production of some intermediate substances such as polysaccharides and amino acids is minimally impacted and that nutrient consumption remains consistent. Moreover, the intensity changes and peak shifts observed in the SERS spectra of non-PYO-producing ampicillin-susceptible Escherichia coli demonstrate that exogenously added PYO enhances E. coli tolerance to ampicillin to some extent. These results indicate that PYO mediates antibiotic resistance not only in the parent species but also in cocultured bacterial strains. The metabolic SERS signal provides new insight regarding antibiotic resistance with promising applications for both environmental monitoring and rapid clinical detection.
Subject(s)
Escherichia coli , Spectrum Analysis, Raman , Ampicillin/pharmacology , Environmental Monitoring , NutrientsABSTRACT
Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of WBT measured biomarkers for research activities and for the pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process, introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary workshop developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11 questions derived from primarily public health guidance. This study retrospectively applied these questions to SARS-CoV-2 monitoring programs covering the emergent phase of the pandemic (3/2020-2/2022 (n = 53)). Of note, 43% of answers highlight a lack of reported information to assess. Therefore, a systematic framework would at a minimum structure the communication of ethical considerations for applications of WBT. Consistent application of an ethical review will also assist in developing a practice of updating approaches and techniques to reflect the concerns held by both those practicing and those being monitored by WBT supported programs.
Subject(s)
COVID-19 , Humans , COVID-19/epidemiology , Public Health , Retrospective Studies , SARS-CoV-2 , Wastewater , Ethical ReviewABSTRACT
Wastewater-based testing (WBT) for SARS-CoV-2 has rapidly expanded over the past three years due to its ability to provide a comprehensive measurement of disease prevalence independent of clinical testing. The development and simultaneous application of the field blurred the boundary between measuring biomarkers for research activities and for pursuit of public health goals, both areas with well-established ethical frameworks. Currently, WBT practitioners do not employ a standardized ethical review process (or associated data management safeguards), introducing the potential for adverse outcomes for WBT professionals and community members. To address this deficiency, an interdisciplinary group developed a framework for a structured ethical review of WBT. The workshop employed a consensus approach to create this framework as a set of 11-questions derived from primarily public health guidance because of the common exemption of wastewater samples to human subject research considerations. This study retrospectively applied the set of questions to peer- reviewed published reports on SARS-CoV-2 monitoring campaigns covering the emergent phase of the pandemic from March 2020 to February 2022 (n=53). Overall, 43% of the responses to the questions were unable to be assessed because of lack of reported information. It is therefore hypothesized that a systematic framework would at a minimum improve the communication of key ethical considerations for the application of WBT. Consistent application of a standardized ethical review will also assist in developing an engaged practice of critically applying and updating approaches and techniques to reflect the concerns held by both those practicing and being monitored by WBT supported campaigns. Synopsis: Development of a structured ethical review facilitates retrospective analysis of published studies and drafted scenarios in the context of wastewater-based testing.
ABSTRACT
There are challenges in monitoring and managing water quality due to spatial and temporal heterogeneity in contaminant sources, transport, and transformations. We demonstrate the importance of longitudinal stream synoptic (LSS) monitoring, which can track combinations of water quality parameters along flowpaths across space and time. Specifically, we analyze longitudinal patterns of chemical mixtures of carbon, nutrients, greenhouse gasses, salts, and metals concentrations along 10 flowpaths draining 1,765 km2 of the Chesapeake Bay region. These 10 longitudinal stream flowpaths are drained by watersheds experiencing either urban degradation, forest and wetland conservation, or stream and floodplain restoration. Along the 10 longitudinal stream flowpaths, we monitored over 300 total sampling sites along a combined stream length of 337 km. Synoptic monitoring along longitudinal flowpaths revealed: (1) increasing, decreasing, piecewise, or no trends and transitions in water quality with increasing distance downstream, which provide insights into water quality processes along flowpaths; (2) longitudinal trends and transitions in water quality along flowpaths can be quantified and compared using simple linear and non-linear statistical relationships with distance downstream and/or land use/land cover attributes, (3) attenuation and transformation of chemical cocktails along flowpaths depend on: spatial scales, pollution sources, and transitions in land use and management, hydrology, and restoration. We compared our LSS patterns with others from the global literature to synthesize a typology of longitudinal water quality trends and transitions in streams and rivers based on hydrological, biological, and geochemical processes. Applications of LSS monitoring along flowpaths from our results and the literature reveal: (1) if there are shifts in pollution sources, trends, and transitions along flowpaths, (2) which pollution sources can spread further downstream to sensitive receiving waters such as drinking water supplies and coastal zones, and (3) if transitions in land use, conservation, management, or restoration can attenuate downstream transport of pollution sources. Our typology of longitudinal water quality responses along flowpaths combines many observations across suites of chemicals that can follow predictable patterns based on watershed characteristics. Our typology of longitudinal water quality responses also provides a foundation for future studies, watershed assessments, evaluating watershed management and stream restoration, and comparing watershed responses to non-point and point pollution sources along streams and rivers. LSS monitoring, which integrates both spatial and temporal dimensions and considers multiple contaminants together (a chemical cocktail approach), can be a comprehensive strategy for tracking sources, fate, and transport of pollutants along stream flowpaths and making comparisons of water quality patterns across different watersheds and regions.
ABSTRACT
Efficient spread of respiratory viruses requires the virus to maintain infectivity in the environment. Environmental stability of viruses can be influenced by many factors, including temperature and humidity. Our study measured the impact of initial droplet volume (50, 5, and 1 µL) and relative humidity (RH; 40%, 65%, and 85%) on the stability of influenza A virus, bacteriophage Phi6 (a common surrogate for enveloped viruses), and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) under a limited set of conditions. Our data suggest that the drying time required for the droplets to reach quasi-equilibrium (i.e., a plateau in mass) varied with RH and initial droplet volume. The macroscale physical characteristics of the droplets at quasi-equilibrium varied with RH but not with the initial droplet volume. Virus decay rates differed between the wet phase, while the droplets were still evaporating, and the dry phase. For Phi6, decay was faster in the wet phase than in the dry phase under most conditions. For H1N1pdm09, decay rates between the two phases were distinct and initial droplet volume had an effect on virus viability within 2 h. Importantly, we observed differences in virus decay characteristics by droplet size and virus. In general, influenza virus and SARS-CoV-2 decayed similarly, whereas Phi6 decayed more rapidly under certain conditions. Overall, this study suggests that virus decay in media is related to the extent of droplet evaporation, which is controlled by RH. Importantly, accurate assessment of transmission risk requires the use of physiologically relevant droplet volumes and careful consideration of the use of surrogates. IMPORTANCE During the COVID-19 pandemic, policy decisions were being driven by virus stability experiments with SARS-CoV-2 in different droplet volumes under various humidity conditions. Our study, the first of its kind, provides a model for the decay of multiple enveloped RNA viruses in cell culture medium deposited in 50-, 5-, and 1-µL droplets at 40%, 65%, and 85% RH over time. The results of our study indicate that determination of half-lives for emerging pathogens in large droplets may overestimate transmission risk for contaminated surfaces, as observed during the COVID-19 pandemic. Our study implicates the need for the use of physiologically relevant droplet sizes with use of relevant surrogates in addition to what is already known about the importance of physiologically relevant media for risk assessment of future emerging pathogens.
Subject(s)
COVID-19 , Orthomyxoviridae , Viruses , Humans , SARS-CoV-2 , PandemicsABSTRACT
In situ spatiotemporal biochemical characterization of the activity of living multicellular biofilms under external stimuli remains a significant challenge. Surface-enhanced Raman spectroscopy (SERS), combining the molecular fingerprint specificity of vibrational spectroscopy with the hotspot sensitivity of plasmonic nanostructures, has emerged as a promising noninvasive bioanalysis technique for living systems. However, most SERS devices do not allow reliable long-term spatiotemporal SERS measurements of multicellular systems because of challenges in producing spatially uniform and mechanically stable SERS hotspot arrays to interface with large cellular networks. Furthermore, very few studies have been conducted for multivariable analysis of spatiotemporal SERS datasets to extract spatially and temporally correlated biological information from multicellular systems. Here, we demonstrate in situ label-free spatiotemporal SERS measurements and multivariate analysis of Pseudomonas syringae biofilms during development and upon infection by bacteriophage virus Phi6 by employing nanolaminate plasmonic crystal SERS devices to interface mechanically stable, uniform, and spatially dense hotspot arrays with the P. syringae biofilms. We exploited unsupervised multivariate machine learning methods, including principal component analysis (PCA) and hierarchical cluster analysis (HCA), to resolve the spatiotemporal evolution and Phi6 dose-dependent changes of major Raman peaks originating from biochemical components in P. syringae biofilms, including cellular components, extracellular polymeric substances (EPS), metabolite molecules, and cell lysate-enriched extracellular media. We then employed supervised multivariate analysis using linear discriminant analysis (LDA) for the multiclass classification of Phi6 dose-dependent biofilm responses, demonstrating the potential for viral infection diagnosis. We envision extending the in situ spatiotemporal SERS method to monitor dynamic, heterogeneous interactions between viruses and bacterial networks for applications such as phage-based anti-biofilm therapy development and continuous pathogenic virus detection.