Digital Surface-Enhanced Raman Spectroscopy-Lateral Flow Test Dipstick: Ultrasensitive, Rapid Virus Quantification in Environmental Dust.

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.

Metagenomic Profiling of Internationally Sourced Sewage Influents and Effluents Yields Insight into Selecting Targets for Antibiotic Resistance Monitoring.

It has been debated whether wastewater treatment plants (WWTPs) primarily act to attenuate or amplify antibiotic resistance genes (ARGs). However, ARGs are highly diverse with respect to their resistance mechanisms, mobilities, and taxonomic hosts and therefore their behavior in WWTPs should not be expected to be universally conserved. We applied metagenomic sequencing to wastewater influent and effluent samples from 12 international WWTPs to classify the behavior of specific ARGs entering and exiting WWTPs. In total, 1079 different ARGs originating from a variety of bacteria were detected. This included ARGs that could be mapped to assembled scaffolds corresponding to nine human pathogens. While the relative abundance (per 16S rRNA gene) of ARGs decreased during treatment at 11 of the 12 WWTPs sampled and absolute abundance (per mL) decreased at all 12 WWTPs, increases in relative abundance were observed for 40% of the ARGs detected at the 12th WWTP. Also, the relative abundance of mobile genetic elements (MGE) increased during treatment, but the fraction of ARGs known to be transmissible between species decreased, thus demonstrating that increased MGE prevalence may not be generally indicative of an increase in ARGs. A distinct conserved resistome was documented in both influent and effluent across samples, suggesting that well-functioning WWTPs generally attenuate influent antibiotic resistance loads. This work helps inform strategies for wastewater surveillance of antibiotic resistance, highlighting the utility of tracking ARGs as indicators of treatment performance and relative risk reduction.

SERS-Active Printable Hydrogel for 3D Cell Culture and Imaging.

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.

Investigation of the Influence of Stress on Label-Free Bacterial Surface-Enhanced Raman Spectra.

Label-free surface-enhanced Raman spectroscopy (SERS) has been proposed as a promising bacterial detection technique. However, the quality of the collected bacterial spectra can be affected by the time between sample acquisition and the SERS measurement. This study evaluated how storage stress stimuli influence the label-free SERS spectra of Pseudomonas syringae samples stored in phosphate buffered saline. The results indicate that when faced with nutrient limitations and changes in osmatic pressure, samples at room temperature (25 °C) exhibit more significant spectral changes than those stored at cold temperature (4 °C). At higher temperatures, bacterial communities secrete extracellular biomolecules that induce programmed cell death and result in increases in the supernatant SERS signals. Surviving cells consume cellular components to support their metabolism, thus leading to measurable declines in cell SERS intensity. Two-dimensional correlation spectroscopy analysis suggests that cellular component signatures decline sequentially in the following order: proteins, nucleic acids, and lipids. Extracellular nucleic acids, proteins, and carbohydrates are secreted in turn. After subtracting the SERS changes resulting from storage, we evaluated bacterial response to viral infection. P. syringae SERS profile changes enable accurate bacteriophage Phi6 quantification over the range of 104-1010 PFU/mL. The results indicate that storage conditions impact bacterial label-free SERS signals and that such influences need to be accounted for and if possible avoided when detecting bacteria or evaluating bacterial response to stress stimuli.

Metabolite-Mediated Bacterial Antibiotic Resistance Revealed by Surface-Enhanced Raman Spectroscopy.

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.

Evaluating the Ecological Footprint of Landfills: A Framework and Case Study of Fargo, North Dakota.

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.

Structured Ethical Review for Wastewater-Based Testing in Support of Public Health.

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.

Biomimetic Transparent Nanoplasmonic Meshes by Reverse-Nanoimprinting for Bio-Interfaced Spatiotemporal Multimodal SERS Bioanalysis.

Multicellular systems, such as microbial biofilms and cancerous tumors, feature complex biological activities coordinated by cellular interactions mediated via different signaling and regulatory pathways, which are intrinsically heterogeneous, dynamic, and adaptive. However, due to their invasiveness or their inability to interface with native cellular networks, standard bioanalysis methods do not allow in situ spatiotemporal biochemical monitoring of multicellular systems to capture holistic spatiotemporal pictures of systems-level biology. Here, a high-throughput reverse nanoimprint lithography approach is reported to create biomimetic transparent nanoplasmonic microporous mesh (BTNMM) devices with ultrathin flexible microporous structures for spatiotemporal multimodal surface-enhanced Raman spectroscopy (SERS) measurements at the bio-interface. It is demonstrated that BTNMMs, supporting uniform and ultrasensitive SERS hotspots, can simultaneously enable spatiotemporal multimodal SERS measurements for targeted pH sensing and non-targeted molecular detection to resolve the diffusion dynamics for pH, adenine, and Rhodamine 6G molecules in agarose gel. Moreover, it is demonstrated that BTNMMs can act as multifunctional bio-interfaced SERS sensors to conduct in situ spatiotemporal pH mapping and molecular profiling of Escherichia coli biofilms. It is envisioned that the ultrasensitive multimodal SERS capability, transport permeability, and biomechanical compatibility of the BTNMMs can open exciting avenues for bio-interfaced multifunctional sensing applications both in vitro and in vivo.

Microporous Multiresonant Plasmonic Meshes by Hierarchical Micro-Nanoimprinting for Bio-Interfaced SERS Imaging and Nonlinear Nano-Optics.

Microporous mesh plasmonic devices have the potential to combine the biocompatibility of microporous polymeric meshes with the capabilities of plasmonic nanostructures to enhance nanoscale light-matter interactions for bio-interfaced optical sensing and actuation. However, scalable integration of dense and uniformly structured plasmonic hotspot arrays with microporous polymeric meshes remains challenging due to the processing incompatibility of conventional nanofabrication methods with flexible microporous substrates. Here, scalable nanofabrication of microporous multiresonant plasmonic meshes (MMPMs) is achieved via a hierarchical micro-/nanoimprint lithography approach using dissolvable polymeric templates. It is demonstrated that MMPMs can serve as broadband nonlinear nanoplasmonic devices to generate second-harmonic generation, third-harmonic generation, and upconversion photoluminescence signals with multiresonant plasmonic enhancement under fs pulse excitation. Moreover, MMPMs are employed and explored as bio-interfaced surface-enhanced Raman spectroscopy mesh sensors to enable in situ spatiotemporal molecular profiling of bacterial biofilm activity. Microporous mesh plasmonic devices open exciting avenues for bio-interfaced optical sensing and actuation applications, such as inflammation-free epidermal sensors in conformal contact with skin, combined tissue-engineering and biosensing scaffolds for in vitro 3D cell culture models, and minimally invasive implantable probes for long-term disease diagnostics and therapeutics.

mobileOG-db: a Manually Curated Database of Protein Families Mediating the Life Cycle of Bacterial Mobile Genetic Elements.

Bacterial mobile genetic elements (MGEs) encode functional modules that perform both core and accessory functions for the element, the latter of which are often only transiently associated with the element. The presence of these accessory genes, which are often close homologs to primarily immobile genes, incur high rates of false positives and, therefore, limits the usability of these databases for MGE annotation. To overcome this limitation, we analyzed 10,776,849 protein sequences derived from eight MGE databases to compile a comprehensive set of 6,140 manually curated protein families that are linked to the "life cycle" (integration/excision, replication/recombination/repair, transfer, stability/transfer/defense, and phage-specific processes) of plasmids, phages, integrative, transposable, and conjugative elements. We overlay experimental information where available to create a tiered annotation scheme of high-quality annotations and annotations inferred exclusively through bioinformatic evidence. We additionally provide an MGE-class label for each entry (e.g., plasmid or integrative element), and assign to each entry a major and minor category. The resulting database, mobileOG-db (for mobile orthologous groups), comprises over 700,000 deduplicated sequences encompassing five major mobileOG categories and more than 50 minor categories, providing a structured language and interpretable basis for an array of MGE-centered analyses. mobileOG-db can be accessed at mobileogdb.flsi.cloud.vt.edu/, where users can select, refine, and analyze custom subsets of the dynamic mobilome. IMPORTANCE The analysis of bacterial mobile genetic elements (MGEs) in genomic data is a critical step toward profiling the root causes of antibiotic resistance, phenotypic or metabolic diversity, and the evolution of bacterial genera. Existing methods for MGE annotation pose high barriers of biological and computational expertise to properly harness. To bridge this gap, we systematically analyzed 10,776,849 proteins derived from eight databases of MGEs to identify 6,140 MGE protein families that can serve as candidate hallmarks, i.e., proteins that can be used as "signatures" of MGEs to aid annotation. The resulting resource, mobileOG-db, provides a multilevel classification scheme that encompasses plasmid, phage, integrative, and transposable element protein families categorized into five major mobileOG categories and more than 50 minor categories. mobileOG-db thus provides a rich resource for simple and intuitive element annotation that can be integrated seamlessly into existing MGE detection pipelines and colocalization analyses.

Can Common Pool Resource Theory Catalyze Stakeholder-Driven Solutions to the Freshwater Salinization Syndrome?

Freshwater salinity is rising across many regions of the United States as well as globally, a phenomenon called the freshwater salinization syndrome (FSS). The FSS mobilizes organic carbon, nutrients, heavy metals, and other contaminants sequestered in soils and freshwater sediments, alters the structures and functions of soils, streams, and riparian ecosystems, threatens drinking water supplies, and undermines progress toward many of the United Nations Sustainable Development Goals. There is an urgent need to leverage the current understanding of salinization's causes and consequences─in partnership with engineers, social scientists, policymakers, and other stakeholders─into locally tailored approaches for balancing our nation's salt budget. In this feature, we propose that the FSS can be understood as a common pool resource problem and explore Nobel Laureate Elinor Ostrom's social-ecological systems framework as an approach for identifying the conditions under which local actors may work collectively to manage the FSS in the absence of top-down regulatory controls. We adopt as a case study rising sodium concentrations in the Occoquan Reservoir, a critical water supply for up to one million residents in Northern Virginia (USA), to illustrate emerging impacts, underlying causes, possible solutions, and critical research needs.

Demonstrating a Comprehensive Wastewater-Based Surveillance Approach That Differentiates Globally Sourced Resistomes.

Wastewater-based surveillance (WBS) for disease monitoring is highly promising but requires consistent methodologies that incorporate predetermined objectives, targets, and metrics. Herein, we describe a comprehensive metagenomics-based approach for global surveillance of antibiotic resistance in sewage that enables assessment of 1) which antibiotic resistance genes (ARGs) are shared across regions/communities; 2) which ARGs are discriminatory; and 3) factors associated with overall trends in ARGs, such as antibiotic concentrations. Across an internationally sourced transect of sewage samples collected using a centralized, standardized protocol, ARG relative abundances (16S rRNA gene-normalized) were highest in Hong Kong and India and lowest in Sweden and Switzerland, reflecting national policy, measured antibiotic concentrations, and metal resistance genes. Asian versus European/US resistomes were distinct, with macrolide-lincosamide-streptogramin, phenicol, quinolone, and tetracycline versus multidrug resistance ARGs being discriminatory, respectively. Regional trends in measured antibiotic concentrations differed from trends expected from public sales data. This could reflect unaccounted uses, captured only by the WBS approach. If properly benchmarked, antibiotic WBS might complement public sales and consumption statistics in the future. The WBS approach defined herein demonstrates multisite comparability and sensitivity to local/regional factors.

Discriminatory Detection of ssDNA by Surface-Enhanced Raman Spectroscopy (SERS) and Tree-Based Support Vector Machine (Tr-SVM).

We report label-free detection of 86-base single-stranded DNA (ssDNA) gene segments by surface-enhanced Raman spectroscopy (SERS). The use of a slippery liquid infused porous (SLIP) membrane induced aggregation of 43 nm gold nanoparticles and ssDNA upon pin-free droplet evaporation. The combined SLIPSERS approach generates significant numbers of SERS hot-spots and enabled detection at the 100 nM level of mecA and intI1 gene segments-two genes of interest in the context of antibiotic resistance. Tree-based multiclass support vector machine (Tr-SVM) classifiers were built to discriminate SERS spectra of 12 different gene sequences obtained by SLIPSERS: mecA, intI1, as well as analogues of mecA and intI1, respectively, with 2-10 base mismatches, and two random sequences. The trained predictive Tr-SVM classifiers correctly identified each gene sequence with a prediction accuracy of ∼90%. This study illustrates a novel means for discriminatory label-free SERS detection of ssDNA enabled by Tr-SVM.

Nanobiotechnology enabled approaches for wastewater based epidemiology.

The impacts of the ongoing coronavirus pandemic highlight the importance of environmental monitoring to inform public health safety. Wastewater based epidemiology (WBE) has drawn interest as a tool for analysis of biomarkers in wastewater networks. Wide scale implementation of WBE requires a variety of field deployable analytical tools for real-time monitoring. Nanobiotechnology enabled sensing platforms offer potential as biosensors capable of highly efficient and sensitive detection of target analytes. This review provides an overview of the design and working principles of nanobiotechnology enabled biosensors and recent progress on the use of biosensors in detection of biomarkers. In addition, applications of biosensors for analysis of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus are highlighted as they relate to the potential expanded use of biosensors for WBE-based monitoring. Finally, we discuss the opportunities and challenges in future applications of biosensors in WBE for effective monitoring and investigation of public health threats.

Implications of the Coffee-Ring Effect on Virus Infectivity.

The factors contributing to the survival of enveloped viruses (e.g., influenza and SARS-CoV-2) on fomite surfaces are of societal interest. The bacteriophage Phi6 is an enveloped viral surrogate commonly used to study viability. To investigate how viability changes during the evaporation of droplets on polypropylene, we conducted experiments using a fixed initial Phi6 concentration while systematically varying the culture concentration and composition (by amendment with 2% fetal bovine serum (FBS), 0.08 wt % BSA, or 0.5 wt % SDS). The results were consistent with the well-founded relative humidity (RH) effect on virus viability; however, the measured viability change was greater than that previously reported for droplets containing either inorganic salts or proteins alone, and the protein effects diverged in 1× Dulbecco's modified Eagle's medium (DMEM). We attribute this discrepancy to changes in virus distribution during droplet evaporation that arise due to the variable solute drying patterns (i.e., the "coffee-ring" effect) that are a function of the droplet biochemical composition. To test this hypothesis, we used surface-enhanced Raman spectroscopy (SERS) imaging and three types of gold nanoparticles (pH nanoprobe, positively charged (AuNPs(+)), and negatively charged (AuNPs(-))) as physical surrogates for Phi6 and determined that lower DMEM concentrations, as well as lower protein concentrations, suppressed the coffee-ring effect. This result was observed irrespective of particle surface charge. The trends in the coffee-ring effect correlate well with the measured changes in virus infectivity. The correlation suggests that conditions resulting in more concentrated coffee rings provide protective effects against inactivation when viruses and proteins aggregate.

Surface-Enhanced Raman Spectroscopy of Bacterial Metabolites for Bacterial Growth Monitoring and Diagnosis of Viral Infection.

Bacterial metabolites are intermediate products of bacterial metabolism and their production reflects metabolic activity. Herein, we report the use of surface-enhanced Raman spectroscopy (SERS) for detection of both volatile and nonvolatile metabolites and the application of this approach for bacterial growth quantification and diagnosis of viral infection. The time-dependent SERS signal of the volatile metabolite dimethyl disulfide in the headspace above bacteria growing on an agar plate was detected and quantified. In addition, SERS signals arising from the plate reflected nutrient consumption and production of nonvolatile metabolites. The measurement of metabolite accumulation can be used for bacterial quantification. In the presence of bacteriophage virus, bacterial metabolism is suppressed, and the relative decrease in SERS intensity reflects the initial virus concentration. Using multivariate analysis, we detect viral infection with a prediction accuracy of 93%. Our SERS-based approach for metabolite production monitoring provides new insights toward viral infection diagnosis.

Data Analytics for Environmental Science and Engineering Research.

The advent of new data acquisition and handling techniques has opened the door to alternative and more comprehensive approaches to environmental monitoring that will improve our capacity to understand and manage environmental systems. Researchers have recently begun using machine learning (ML) techniques to analyze complex environmental systems and their associated data. Herein, we provide an overview of data analytics frameworks suitable for various Environmental Science and Engineering (ESE) research applications. We present current applications of ML algorithms within the ESE domain using three representative case studies: (1) Metagenomic data analysis for characterizing and tracking antimicrobial resistance in the environment; (2) Nontarget analysis for environmental pollutant profiling; and (3) Detection of anomalies in continuous data generated by engineered water systems. We conclude by proposing a path to advance incorporation of data analytics approaches in ESE research and application.

Direct Quantification of the Effect of Ammonium on Aerosol Droplet pH.

Ammonium is an important atmospheric constituent that dictates many environmental processes. The impact of the ammonium ion concentration on 10-50 µm aerosol droplet pH was quantified using pH nanoprobes and surface-enhanced Raman spectroscopy (SERS). Sample solutions were prepared by mixing 1 M ammonium sulfate (AS), ammonium nitrate (AN), sodium sulfate (SS), or sodium nitrate (SN) solutions with 1 M phosphate buffer (PB) at different volume ratios. Stable pH values were measured for pure PB, AS, and AN droplets at different concentrations. The centroid pH of 1 M PB droplets was ∼11, but when PB was systematically replaced with ammonium (AS- or AN-PB), the centroid pH within the droplets decreased from ≈11 to 5.5. Such a decrease was not observed in sodium (SS- or SN-PB) droplets, and no pH differences were observed between sulfate and nitrate salts. Ammonia partitioning to the gas phase in ammonium-containing droplets was evaluated to be negligible. Raman sulfate peak (∼980 cm-1) intensity measurements and surface tension measurements were conducted to investigate changes in ion distribution. The pH difference between ammonium-containing droplets and ammonium-free droplets is attributed to the alteration of the ion distribution in the presence of ammonium.

Aerosol microdroplets exhibit a stable pH gradient.

Suspended aqueous aerosol droplets (<50 µm) are microreactors for many important atmospheric reactions. In droplets and other aquatic environments, pH is arguably the key parameter dictating chemical and biological processes. The nature of the droplet air/water interface has the potential to significantly alter droplet pH relative to bulk water. Historically, it has been challenging to measure the pH of individual droplets because of their inaccessibility to conventional pH probes. In this study, we scanned droplets containing 4-mercaptobenzoic acid-functionalized gold nanoparticle pH nanoprobes by 2D and 3D laser confocal Raman microscopy. Using surface-enhanced Raman scattering, we acquired the pH distribution inside approximately 20-µm-diameter phosphate-buffered aerosol droplets and found that the pH in the core of a droplet is higher than that of bulk solution by up to 3.6 pH units. This finding suggests the accumulation of protons at the air/water interface and is consistent with recent thermodynamic model results. The existence of this pH shift was corroborated by the observation that a catalytic reaction that occurs only under basic conditions (i.e., dimerization of 4-aminothiophenol to produce dimercaptoazobenzene) occurs within the high pH core of a droplet, but not in bulk solution. Our nanoparticle probe enables pH quantification through the cross-section of an aerosol droplet, revealing a spatial gradient that has implications for acid-base-catalyzed atmospheric chemistry.