Optical Properties of Water for Prediction of Wastewater Contamination, Human-Associated Bacteria, and Fecal Indicator Bacteria in Surface Water at Three Watershed Scales

Evaluation of real-time fluorescence sensors and benchtop fluorescence for tracking and predicting sewage contamination in the Tijuana River Estuary at the US-Mexico border

Cross-border flow of untreated sewage from Mexico into the USA via the Tijuana River is public health issue with negative consequences for coastal communities. Here we evaluate the potential application of fluorescence-based, submersible tryptophan-like (TRP) and humic-like (CDOM) fluorescence sensors for real-time tracking of wastewater pollution in an estuarine environment. Sonde fluorescence measurements were compared with benchtop fluorescence, fecal indicator bacteria (FIB) concentrations, and real-time specific conductivity measurements in the Tijuana River Estuary during dry and wet weather conditions, and with and without cross-border flow. TRP and CDOM fluorescence concentrations were low during times without cross-border flow and two-three orders of magnitude higher during storm events and after cross-border sewage flow events. Major deterioration in water quality, including hypoxic conditions, was observed after consistent, long-term cross-border sewage flow. Real-time TRP and CDOM fluorescence concentrations had a significant linear relationship with fecal indicator bacteria (FIB) concentrations during dry weather periods with cross-border flow (p < 0.001) but were poorly correlated during stormflow and during less polluted periods with no cross-border flow. TRP and CDOM fluorescence acquired on discrete samples using a benchtop fluorometer correlated significantly (p < 0.001) with FIB concentrations under all cross-border flow conditions. Based on relationships between benchtop TRP fluorescence and percent wastewater, the greatest amount of untreated wastewater in the estuary's surface layer during cross-border flow events was estimated at >80 % and occurred during neap tides, when concentrated, sewage-laden freshwater flowed over dense saline seawater due to stratification and lack of mixing in the estuary. These results are important because exposure to untreated sewage poses severe health risks for residents and visitors to adjacent coastal areas. While benchtop fluorescence was more effective for estimating the degree of wastewater pollution, submersible TRP and CDOM sensors provided a real-time alert of sewage contamination, which can be utilized in other sewage impacted estuarine environments.

Two risk assessments: Evaluating the use of indicator HF183 Bacteroides versus pathogen measurements for modelling recreational illness risks in an urban watershed

The purpose of this study was to evaluate the performance of HF183 Bacteroides for estimating pathogen exposures during recreational water activities. We compared the use of Bacteroides-based exposure assessment to exposure assessment that relied on pathogen measurements. We considered two types of recreational water sites: those impacted by combined sewer overflows (CSOs) and those not impacted by CSOs. Samples from CSO-impacted and non-CSO-impacted urban creeks were analysed by quantitative polymerase chain reaction (qPCR) for HF183 Bacteroides and eight human gastrointestinal pathogens. Exposure assessment was conducted two ways for each type of site (CSO-impacted vs. non-CSO impacted): 1) by estimating pathogen concentrations from HF183 Bacteroides concentrations using published ratios of HF183 to pathogens in sewage and 2) by estimating pathogen concentrations from qPCR measurements. QMRA (quantitative microbial risk assessment) was then conducted for swimming, wading, and fishing exposures. Overall, mean risk estimates varied from 0.27 to 53 illnesses per 1,000 recreators depending on exposure assessment, site, activity, and norovirus dose-response model. HF183-based exposure assessment identified CSO-impacted sites as higher risk, and the recommended HF183 risk-based threshold of 525 genomic copies per 100 mL was generally protective of public health at the CSO-impacted sites but was not as protective at the non-CSO-impacted sites. In the context of our urban watershed, HF183-based exposure assessment over- and under-estimated risk relative to exposure assessment based on pathogen measurements, and the etiology of predicted pathogen-specific illnesses differed significantly. Across all sites, the HF183 model overestimated risk for norovirus, adenovirus, and Campylobacter jejuni, and it underestimated risk for E. coli and Cryptosporidium. To our knowledge, this study is the first to directly compare health risk estimates using HF183 and empirical pathogen measurements from the same waterways. Our work highlights the importance of site-specific hazard identification and exposure assessment to decide whether HF183 is applicable for monitoring risk.

Far-Red Fluorescent Proteins: Tools for Advancing In Vivo Imaging

Far-red fluorescent proteins (FPs) have emerged as indispensable tools in in vivo imaging, playing a pivotal role in elucidating fundamental mechanisms and addressing application issues in biotechnology and biomedical fields. Their ability for deep penetration, coupled with reduced light scattering and absorption, robust resistance to autofluorescence, and diminished phototoxicity, has positioned far-red biosensors at the forefront of non-invasive visualization techniques for observing intracellular activities and intercellular behaviors. In this review, far-red FPs and their applications in living systems are mainly discussed. Firstly, various far-red FPs, characterized by emission peaks spanning from 600 nm to 650 nm, are introduced. This is followed by a detailed presentation of the fundamental principles enabling far-red biosensors to detect biomolecules and environmental changes. Furthermore, the review accentuates the superiority of far-red FPs in multi-color imaging. In addition, significant emphasis is placed on the value of far-red FPs in improving imaging resolution, highlighting their great contribution to the advancement of in vivo imaging.

A mica filter enables bacterial enrichment from large volumes of natural water for sensitive monitoring of pathogens by nanopore sequencing

Nanopore sequencing is extremely promising for the high-throughput detection of pathogenic bacteria in natural water; these bacteria may be transmitted to humans and cause waterborne infectious diseases. However, the concentration of pathogenic bacteria in natural water is too low to be detected directly by nanopore sequencing. Herein, we developed a mica filter to enrich over 85% of bacteria from > 10 L of natural water in 100 min, which led to a 102-fold improvement in the assay limits of the MinION sequencer for assessing pathogenic bacteria. Correspondingly, the sequencing time of S. Typhi detection at a concentration as low as 105 CFU/L was reduced from traditional 48 h to 3 h. The bacterial adsorption followed pseudo-first-order kinetics and the successful adsorption of bacteria to the mica filter was confirmed by scanning electron microscopy and Fourier infrared spectroscopy et al. The mica filter remained applicable to a range of water samples whose quality parameters were within the EPA standard limits for freshwater water. The mica filter is thus an effective tool for the sensitive and rapid monitoring of pathogenic bacteria by nanopore sequencing, which can provide timely alerts for waterborne transmission events.

A multi-marker assessment of sewage contamination in streams using human-associated indicator bacteria, human-specific viruses, and pharmaceuticals

Human sewage contaminates waterways, delivering excess nutrients, pathogens, chemicals, and other toxic contaminants. Contaminants and various sewage indicators are measured to monitor and assess water quality, but these analytes vary in their representation of sewage contamination and the inferences about water quality they support. We measured the occurrence and concentration of multiple microbiological (n = 21) and chemical (n = 106) markers at two urban stream locations in Milwaukee, Wisconsin, USA over two years. Five-day composite water samples (n = 98) were collected biweekly, and sewage influent samples (n = 25) were collected monthly at a Milwaukee, WI water reclamation facility. We found the vast majority of markers were not sensitive enough to detect sewage contamination. To compare analytes for monitoring applications, five consistently detected human sewage indicators were used to evaluate temporal patterns of sewage contamination, including microbiological (pepper mild mottle virus, human Bacteroides, human Lachnospiraceae) and chemical (acetaminophen, metformin) markers. The proportion of human sewage in each stream was estimated using the mean influent concentration from the water reclamation facility and the mean concentration of all stream samples for each sewage indicator marker. Estimates of instream sewage pollution varied by marker, differing by up to two orders of magnitude, but four of the five sewage markers characterized Underwood Creek (mean proportions of human sewage ranged 0.0025 % - 0.075 %) as less polluted than Menomonee River (proportions ranged 0.013 % - 0.14 %) by an order of magnitude more. Chemical markers correlated with each other and yielded higher estimates of sewage pollution than microbial markers, which exhibited greater temporal variability. Transport, attenuation, and degradation processes can influence chemical and microbial markers differently and cause variation in human sewage estimates. Given the range of potential human and ecological health effects of human sewage contamination, robust characterization of sewage contamination that uses multiple lines of evidence supports monitoring and research applications.

A cryptic plasmid is among the most numerous genetic elements in the human gut

Plasmids are extrachromosomal genetic elements that often encode fitness-enhancing features. However, many bacteria carry "cryptic" plasmids that do not confer clear beneficial functions. We identified one such cryptic plasmid, pBI143, which is ubiquitous across industrialized gut microbiomes and is 14 times as numerous as crAssphage, currently established as the most abundant extrachromosomal genetic element in the human gut. The majority of mutations in pBI143 accumulate in specific positions across thousands of metagenomes, indicating strong purifying selection. pBI143 is monoclonal in most individuals, likely due to the priority effect of the version first acquired, often from one's mother. pBI143 can transfer between Bacteroidales, and although it does not appear to impact bacterial host fitness in vivo, it can transiently acquire additional genetic content. We identified important practical applications of pBI143, including its use in identifying human fecal contamination and its potential as an alternative approach to track human colonic inflammatory states.

Modeled predictions of human-associated and fecal-indicator bacteria concentrations and loadings in the Menomonee River, Wisconsin using in-situ optical sensors

Human sewage contamination of waterways is a major issue in the United States and throughout the world. Models were developed for estimation of two human-associated fecal-indicator and three general fecal-indicator bacteria (HIB and FIB) using in situ optical field-sensor data for estimating concentrations and loads of HIB and FIB and the extent of sewage contamination in the Menomonee River in Milwaukee, Wisconsin. Three commercially available optical sensor platforms were installed into an unfiltered custom-designed flow-through system along with a refrigerated automatic sampler at the Menomonee River sampling location. Ten-minute optical sensor measurements were made from November 2017 to December 2018 along with the collection of 153 flow-weighted discrete water samples (samples) for HIB, FIB, dissolved organic carbon (DOC), and optical properties of water. Of those 153 samples, 119 samples were from event-runoff periods, and 34 were collected during low-flow periods. Of the 119 event-runoff samples, 43 samples were from event-runoff combined sewer overflow (CSO) influenced periods (event-CSO periods). Models included optical sensor measurements as explanatory variables with a seasonal variable as an interaction term. In some cases, separate models for event-CSO periods and non CSO-periods generally improved model performance, as compared to using all the data combined for estimates of FIB and HIB. Therefore, the CSO and non-CSO models were used in final estimations for CSO and non-CSO time periods, respectively. Estimated continuous concentrations for all bacteria markers varied over six orders of magnitude during the study period. The greatest concentrations, loads, and proportion of sewage contamination occurred during event-runoff and event-CSO periods. Comparison to water quality standards and microbial risk assessment benchmarks indicated that estimated bacteria levels exceeded recreational water quality criteria between 34 and 96% of the entire monitoring period, highlighting the benefits of high-frequency monitoring compared to traditional grab sample collection. The application of optical sensors for estimation of HIB and FIB markers provided a thorough assessment of bacterial presence and human health risk in the Menomonee River.

A highly conserved and globally prevalent cryptic plasmid is among the most numerous mobile genetic elements in the human gut

Plasmids are extrachromosomal genetic elements that often encode fitness enhancing features. However, many bacteria carry 'cryptic' plasmids that do not confer clear beneficial functions. We identified one such cryptic plasmid, pBI143, which is ubiquitous across industrialized gut microbiomes, and is 14 times as numerous as crAssphage, currently established as the most abundant genetic element in the human gut. The majority of mutations in pBI143 accumulate in specific positions across thousands of metagenomes, indicating strong purifying selection. pBI143 is monoclonal in most individuals, likely due to the priority effect of the version first acquired, often from one's mother. pBI143 can transfer between Bacteroidales and although it does not appear to impact bacterial host fitness in vivo, can transiently acquire additional genetic content. We identified important practical applications of pBI143, including its use in identifying human fecal contamination and its potential as an inexpensive alternative for detecting human colonic inflammatory states.

Reduction of pathogens in greywater with biological and sustainable treatments selected through a multicriteria approach

Non-potable reuse of greywater (GW) can represent a valid alternative to freshwater consumption, satisfying the Sustainable Development Goals promoted by United Nations. The Multi-Criteria Analysis (MCA) was applied to select the most suitable processes for the reduction of microbiological contamination in GW. A pilot plant, including horizontal flow constructed wetland (CW) and anaerobic filtration (AF) in parallel, best treatment options according to MCA results, was built to treat GW collected from a Venezuelan family. (i) The removal efficiency of microbiological parameters, and (ii) the turbidity as possible microbiological contamination indicator and possible influence factor of disinfection treatment, were investigated. Except for Escherichia coli (4.1 ± 0.9 log reduction with AF), CW achieved the best reductions yields for total coliforms, faecal coliforms, and Salmonella, respectively equal to 3.1 ± 0.5 log, 4.3 ± 0.5 log, and 2.9 ± 0.4 log. In accordance with Venezuelan legislation and WHO guidelines, GW treated with CW was found to be suitable for irrigation reuse for non-edible crops. However, the reduction of pathogens by CW should be considered as a preliminary and not complete disinfection treatment. To reuse GW, especially in the irrigation of edible crops, stronger disinfection treatment should be considered as a complement to the preliminary disinfection performed by CW, to avoid any kind of risk. No significant correlation was found for turbidity either as a possible predictor of microbiological contamination or as an influence on biological disinfection.

A continuous, in-situ, near-time fluorescence sensor coupled with a machine learning model for detection of fecal contamination risk in drinking water: Design, characterization and field validation

We designed and validated a sensitive, continuous, in-situ, remotely reporting tryptophan-like fluorescence sensor and coupled it with a machine learning model to predict high-risk fecal contamination in water (>10 colony forming units (CFU)/100mL E. coli). We characterized the sensor's response to multiple fluorescence interferents with benchtop analysis. The sensor's minimum detection limit (MDL) of tryptophan dissolved in deionized water was 0.05 ppb (p <0.01) and its MDL of the correlation to E. coli present in wastewater effluent was 10 CFU/100 mL (p <0.01). Fluorescence response declined exponentially with increased water temperature and a correction factor was calculated. Inner filter effects, which cause signal attenuation at high concentrations, were shown to have negligible impact in an operational context. Biofouling was demonstrated to increase the fluorescence signal by approximately 82% in a certain context, while mineral scaling reduced the sensitivity of the sensor by approximately 5% after 24 hours with a scaling solution containing 8 times the mineral concentration of the Colorado River. A machine learning model was developed, with TLF measurements as the primary feature, to output fecal contamination risk levels established by the World Health Organization. A training and validation data set for the model was built by installing four sensors on Boulder Creek, Colorado for 88 days and enumerating 298 grab samples for E. coli with membrane filtration. The machine learning model incorporated a proxy feature for fouling (time since last cleaning) which improved model performance. A binary classification model was able to predict high risk fecal contamination with 83% accuracy (95% CI: 78% - 87%), sensitivity of 80%, and specificity of 86%. A model distinguishing between all World Health Organization established risk categories performed with an overall accuracy of 64%. Integrating TLF measurements into an ML model allows for anomaly detection and noise reduction, permitting contamination prediction despite biofilm or mineral scaling formation on the sensor's lenses. Real-time detection of high risk fecal contamination could contribute to a major step forward in terms of microbial water quality monitoring for human health.