Development of a logic regression-based approach for the discovery of host- and niche-informative biomarkers in Escherichia coli and their application for microbial source tracking.

Microbial source tracking leverages a wide range of approaches designed to trace the origins of fecal contamination in aquatic environments. Although source tracking methods are typically employed within the laboratory setting, computational techniques can be leveraged to advance microbial source tracking methodology. Herein, we present a logic regression-based supervised learning approach for the discovery of source-informative genetic markers within intergenic regions across the Escherichia coli genome that can be used for source tracking. With just single intergenic loci, logic regression was able to identify highly source-specific (i.e., exceeding 97.00%) biomarkers for a wide range of host and niche sources, with sensitivities reaching as high as 30.00%-50.00% for certain source categories, including pig, sheep, mouse, and wastewater, depending on the specific intergenic locus analyzed. Restricting the source range to reflect the most prominent zoonotic sources of E. coli transmission (i.e., bovine, chicken, human, and pig) allowed for the generation of informative biomarkers for all host categories, with specificities of at least 90.00% and sensitivities between 12.50% and 70.00%, using the sequence data from key intergenic regions, including emrKY-evgAS, ibsB-(mdtABCD-baeSR), ompC-rcsDB, and yedS-yedR, that appear to be involved in antibiotic resistance. Remarkably, we were able to use this approach to classify 48 out of 113 river water E. coli isolates collected in Northwestern Sweden as either beaver, human, or reindeer in origin with a high degree of consensus-thus highlighting the potential of logic regression modeling as a novel approach for augmenting current source tracking efforts.IMPORTANCEThe presence of microbial contaminants, particularly from fecal sources, within water poses a serious risk to public health. The health and economic burden of waterborne pathogens can be substantial-as such, the ability to detect and identify the sources of fecal contamination in environmental waters is crucial for the control of waterborne diseases. This can be accomplished through microbial source tracking, which involves the use of various laboratory techniques to trace the origins of microbial pollution in the environment. Building on current source tracking methodology, we describe a novel workflow that uses logic regression, a supervised machine learning method, to discover genetic markers in Escherichia coli, a common fecal indicator bacterium, that can be used for source tracking efforts. Importantly, our research provides an example of how the rise in prominence of machine learning algorithms can be applied to improve upon current microbial source tracking methodology.

Quantitative microbial risk assessment for ingestion of antibiotic resistance genes from private wells contaminated by human and livestock fecal sources.

We used quantitative microbial risk assessment to estimate ingestion risk for intI1, erm(B), sul1, tet(A), tet(W), and tet(X) in private wells contaminated by human and/or livestock feces. Genes were quantified with five human-specific and six bovine-specific microbial source-tracking (MST) markers in 138 well-water samples from a rural Wisconsin county. Daily ingestion risk (probability of swallowing ≥1 gene) was based on daily water consumption and a Poisson exposure model. Calculations were stratified by MST source and soil depth over the aquifer where wells were drilled. Relative ingestion risk was estimated using wells with no MST detections and >6.1 m soil depth as a referent category. Daily ingestion risk varied from 0 to 8.8 × 10-1 by gene and fecal source (i.e., human or bovine). The estimated number of residents ingesting target genes from private wells varied from 910 (tet(A)) to 1,500 (intI1 and tet(X)) per day out of 12,000 total. Relative risk of tet(A) ingestion was significantly higher in wells with MST markers detected, including wells with ≤6.1 m soil depth contaminated by bovine markers (2.2 [90% CI: 1.1-4.7]), wells with >6.1 m soil depth contaminated by bovine markers (1.8 [1.002-3.9]), and wells with ≤6.1 m soil depth contaminated by bovine and human markers simultaneously (3.1 [1.7-6.5]). Antibiotic resistance genes (ARGs) were not necessarily present in viable microorganisms, and ingestion is not directly associated with infection. However, results illustrate relative contributions of human and livestock fecal sources to ARG exposure and highlight rural groundwater as a significant point of exposure.IMPORTANCEAntibiotic resistance is a global public health challenge with well-known environmental dimensions, but quantitative analyses of the roles played by various natural environments in transmission of antibiotic resistance are lacking, particularly for drinking water. This study assesses risk of ingestion for several antibiotic resistance genes (ARGs) and the class 1 integron gene (intI1) in drinking water from private wells in a rural area of northeast Wisconsin, United States. Results allow comparison of drinking water as an exposure route for antibiotic resistance relative to other routes like food and recreational water. They also enable a comparison of the importance of human versus livestock fecal sources in the study area. Our study demonstrates the previously unrecognized importance of untreated rural drinking water as an exposure route for antibiotic resistance and identifies bovine fecal material as an important exposure factor in the study setting.

Village Settlements in Mountainous Tropical Areas, Hotspots of Fecal Contamination as Evidenced by Escherichia coli and Stanol Concentrations in Stormwater Pulses.

Fecal bacteria in surface water may indicate threats to human health. Our hypothesis is that village settlements in tropical rural areas are major hotspots of fecal contamination because of the number of domestic animals usually roaming in the alleys and the lack of fecal matter treatment before entering the river network. By jointly monitoring the dynamics of Escherichia coli and of seven stanol compounds during four flood events (July-August 2016) at the outlet of a ditch draining sewage and surface runoff out of a village of Northern Lao PDR, our objectives were (1) to assess the range of E. coli concentration in the surface runoff washing off from a village settlement and (2) to identify the major contributory sources of fecal contamination using stanol compounds during flood events. E. coli pulses ranged from 4.7 × 104 to 3.2 × 106 most probable number (MPN) 100 mL-1, with particle-attached E. coli ranging from 83 to 100%. Major contributory feces sources were chickens and humans (about 66 and 29%, respectively), with the highest percentage switching from the human pole to the chicken pole during flood events. Concentrations indicate a severe fecal contamination of surface water during flood events and suggest that villages may be considered as major hotspots of fecal contamination pulses into the river network and thus as point sources in hydrological models.

New insight into identifying sediment phosphorus sources in multi-source polluted urban river: Effect of environmental-induced microbial community succession on stability of microbial source tracking results.

Identifying sediment phosphorus sources, the key to control eutrophication, is hindered in multi-source polluted urban rivers by the lack of appropriate methods and data resolution. Community-based microbial source tracking (MST) offers new insight, but the bacterial communities could be affected by environmental fluctuations during the migration with sediments, which might induce instability of MST results. Therefore, the effects of environmental-induced community succession on the stability of MST were compared in this study. Liangxi River, a highly eutrophic urban river, was selected as the study area where sediment phosphorus sources are difficult to track because of multi-source pollution and complicated hydrodynamic conditions. Spearman correlation analysis (P < 0.05) was conducted to recognize a close relationship between sediment, bacterial communities and phosphorus, verifying the feasibility of MST for identify sediment phosphorus sources. Two distinct microbial community fingerprints were constructed based on whether excluded 113 vulnerable species, which were identified by analyzing the differences of microorganisms across a concentration gradient of exogenous phosphorus input in microbial environmental response experiment. Because of the lower unknown proportion and relative standard deviations, MST results were more stable and reliable when based on the fingerprints excluding species vulnerable to phosphorus. This study presents a novel insight on how to identify sediment phosphorus sources in multi-source polluted urban river, and would help to develop preferential control strategies for eutrophication management.

Vertical stratification and seasonality of fecal indicator bacteria in New York City playground sandboxes.

Sandboxes in public play spaces afford a crucial opportunity for urban children to engage in naturalistic play that fosters development of cognitive, social, and motor skills. As open pits, sandboxes in New York City public playgrounds are potentially exposed to fecal inputs from various sources, including wild and domestic animals. A longitudinal study of thirteen sandboxes located in public playgrounds on the east side of Manhattan reveals ubiquity of the fecal indicator bacteria enterococci and Escherichia coli through all seasons. The highest concentrations of bacteria occur in surface sand (n = 42; mean enterococci 230 MPN/g and E. coli 182 MPN/g dry weight), with significantly lower levels at depths below the surface (n = 35; mean enterococci 21 MPN/g and E. coli 12 MPN/g dry weight), a stratification consistent with fecal loading at the surface. Generalized linear mixed models indicate that sand depth (surface vs. underlayers) is the most influential variable affecting bacterial levels (P <0.001 for both enterococci and E. coli), followed by sampling season (P <0.001 for both). Bacterial concentrations do not vary significantly as a function of playground location or ZIP code within the study area. Children's exposure while playing in sandboxes likely reaches 105 enterococci and 104E. coli in a typical play period. Microbial source tracking to identify fecal hosts reveals dog, bird, and human biomarkers in low concentrations. Open sandbox microcosms installed at ground level in the urban environment of Manhattan are fouled by enterococci and E. coli within two weeks, while adjacent closed microcosms exhibit no fecal contamination over a 33-day sampling period. Collectively, our results indicate that increasing the frequency of sand refills and covering sandboxes during times of disuse would be straightforward management strategies to mitigate fecal contamination in playground sandboxes.

Fecal Impairment Framework, A New Conceptual Framework for Assessing Fecal Contamination in Recreational Waters.

Fecal pollution of surface water is a pervasive problem that negatively affects waterbodies concerning both public health and ecological functions. Current assessment methods monitor fecal indicator bacteria (FIB) to identify pollution sources using culture-based quantification and microbial source tracking (MST). These types of information assist stakeholders in identifying likely sources of fecal pollution, prioritizing them for remediation, and choosing appropriate best management practices. While both culture-based quantification and MST are useful, they yield different kinds of information, potentially increasing uncertainty in prioritizing sources for management. This study presents a conceptual framework that takes separate human health risk estimates based on measured MST and E. coli concentrations as inputs and produces an estimate of the overall fecal impairment risk as its output. The proposed framework is intended to serve as a supplemental screening tool for existing monitoring programs to aid in identifying and prioritizing sites for remediation. In this study, we evaluated the framework by applying it to two primarily agricultural watersheds and several freshwater recreational beaches using existing routine monitoring data. Based on a combination of E. coli and MST results, the proposed fecal impairment framework identified four sites in the watersheds as candidates for remediation and identified temporal trends in the beach application. As these case studies demonstrate, the proposed fecal impairment framework is an easy-to-use and cost-effective supplemental screening tool that provides actionable information to managers using existing routine monitoring data, without requiring specialized expertize.

Risk of Gastroenteritis from Swimming at a Wastewater-Impacted Tropical Beach Varies across Localized Scales.

Population growth and changing climate are expected to increase human exposure to pathogens in tropical coastal waters. We examined microbiological water quality in three rivers within 2.3 km of each other that impact a Costa Rican beach and in the ocean outside their plumes during the rainy and dry seasons. We performed quantitative microbial risk assessment (QMRA) to predict the risk of gastroenteritis associated with swimming and the amount of pathogen reduction needed to achieve safe conditions. Recreational water quality criteria based on enterococci were exceeded in >90% of river samples but in only 13% of ocean samples. Multivariate analysis grouped microbial observations by subwatershed and season in river samples but only by subwatershed in the ocean. The modeled median risk from all pathogens in river samples was between 0.345 and 0.577, 10-fold above the U.S. Environmental Protection Agency (U.S. EPA) benchmark of 0.036 (36 illnesses/1,000 swimmers). Norovirus genogroup I (NoVGI) contributed most to risk, but adenoviruses raised risk above the threshold in the two most urban subwatersheds. The risk was greater in the dry compared to the rainy season, due largely to the greater frequency of NoVGI detection (100% versus 41%). Viral log10 reduction needed to ensure safe swimming conditions varied by subwatershed and season and was greatest in the dry season (3.8 to 4.1 dry; 2.7 to 3.2 rainy). QMRA that accounts for seasonal and local variability of water quality contributes to understanding the complex influences of hydrology, land use, and environment on human health risk in tropical coastal areas and can contribute to improved beach management. IMPORTANCE This holistic investigation of sanitary water quality at a Costa Rican beach assessed microbial source tracking (MST) marker genes, pathogens, and indicators of sewage. Such studies are still rare in tropical climates. Quantitative microbial risk assessment (QMRA) found that rivers impacting the beach consistently exceeded the U.S. EPA risk threshold for gastroenteritis of 36/1,000 swimmers. The study improves upon many QMRA studies by measuring specific pathogens, rather than relying on surrogates (indicator organisms or MST markers) or estimating pathogen concentrations from the literature. By analyzing microbial levels and estimating the risk of gastrointestinal illness in each river, we were able to discern differences in pathogen levels and human health risks even though all rivers were highly polluted by wastewater and were located less than 2.5 km from one another. This variability on a localized scale has not, to our knowledge, previously been demonstrated.

The Tomato Brown Rugose Fruit Virus Movement Protein Gene Is a Novel Microbial Source Tracking Marker.

Microbial source tracking (MST) identifies sources of fecal contamination in the environment using host-associated fecal markers. While there are numerous bacterial MST markers that can be used herein, there are few such viral markers. Here, we designed and tested novel viral MST markers based on tomato brown rugose fruit virus (ToBRFV) genomes. We assembled eight nearly complete genomes of ToBRFV from wastewater and stool samples from the San Francisco Bay Area in the United States. Next, we developed two novel probe-based reverse transcription-PCR (RT-PCR) assays based on conserved regions of the ToBRFV genome and tested the markers' sensitivities and specificities using human and non-human animal stool as well as wastewater. The ToBRFV markers are sensitive and specific; in human stool and wastewater, they are more prevalent and abundant than a commonly used viral marker, the pepper mild mottle virus (PMMoV) coat protein (CP) gene. We used the assays to detect fecal contamination in urban stormwater samples and found that the ToBRFV markers matched cross-assembly phage (crAssphage), an established viral MST marker, in prevalence across samples. Taken together, these results indicate that ToBRFV is a promising viral human-associated MST marker. IMPORTANCE Human exposure to fecal contamination in the environment can cause transmission of infectious diseases. Microbial source tracking (MST) can identify sources of fecal contamination so that contamination can be remediated and human exposures can be reduced. MST requires the use of host-associated MST markers. Here, we designed and tested novel MST markers from genomes of tomato brown rugose fruit virus (ToBRFV). The markers are sensitive and specific to human stool and highly abundant in human stool and wastewater samples.

Characterizing Spatial Information Loss for Wastewater Surveillance Using crAssphage: Effect of Decay, Temperature, and Population Mobility.

Populations contribute information about their health status to wastewater. Characterizing how that information degrades in transit to wastewater sampling locations (e.g., wastewater treatment plants and pumping stations) is critical to interpret wastewater responses. In this work, we statistically estimate the loss of information about fecal contributions to wastewater from spatially distributed populations at the census block group resolution. This was accomplished with a hydrologically and hydraulically influenced spatial statistical approach applied to crAssphage (Carjivirus communis) load measured from the influent of four wastewater treatment plants in Hamilton County, Ohio. We find that we would expect to observe a 90% loss of information about fecal contributions from a given census block group over a travel time of 10.3 h. This work demonstrates that a challenge to interpreting wastewater responses (e.g., during wastewater surveillance) is distinguishing between a distal but large cluster of contributions and a near but small contribution. This work demonstrates new modeling approaches to improve measurement interpretation depending on sewer network and wastewater characteristics (e.g., geospatial layout, temperature variability, population distribution, and mobility). This modeling can be integrated into standard wastewater surveillance methods and help to optimize sewer sampling locations to ensure that different populations (e.g., vulnerable and susceptible) are appropriately represented.

Meta-analysis of microbial source tracking for the identification of fecal contamination in aquatic environments based on data-mining.

Microbial source tracking (MST) technology represents an innovative approach employed to trace fecal contamination in environmental water systems. The performance of primers may be affected by amplification techniques, target primer categories, and regional differences. To investigate the influence of these factors on primer recognition performance, a meta-analysis was conducted on the application of MST in water environments using three databases: Web of Science, Scopus, and PubMed (n = 2291). After data screening, 46 studies were included in the final analysis. The investigation encompassed Polymerase Chain Reaction (PCR)/quantitative PCR (qPCR) methodologies, dye-based (SYBR)/probe-based (TaqMan) techniques, and geographical differences of a human host-specific (HF183) primer and other 21 additional primers. The results indicated that the primers analyzed were capable of differentiating host specificity to a certain degree. Nonetheless, by comparing sensitivity and specificity outcomes, it was observed that virus-based primers exhibited superior specificity and recognition capacity, as well as a stronger correlation with human pathogenicity in water environments compared to bacteria-based primers. This finding highlights an important direction for future advancements. Moreover, within the same category, qPCR did not demonstrate significant benefits over conventional PCR amplification methods. In comparing dye-based and probe-based techniques, it was revealed that the probe-based method's advantage lay primarily in specificity, which may be associated with the increased propensity of dye-based methods to produce false positives. Furthermore, the heterogeneity of the HF183 primer was not detected in China, Canada, and Singapore respectively, indicating a low likelihood of regional differences. The variation among the 21 other primers may be attributable to regional differences, sample sources, detection techniques, or alternative factors. Finally, we identified that economic factors, climatic conditions, and geographical distribution significantly influence primer performance.

Using watershed characteristics to enhance fecal source identification.

Fecal pollution is one of the most prevalent forms of pollution affecting waterbodies worldwide, threatening public health and negatively impacting aquatic environments. Microbial source tracking (MST) applies polymerase chain reaction (PCR) technology to help identify the source of fecal pollution. In this study, we combine spatial data for two watersheds with general and host-associated MST markers to target human (HF183/BacR287), bovine (CowM2), and general ruminant (Rum2Bac) sources. Concentrations of MST markers in samples were determined with droplet digital PCR (ddPCR). The three MST markers were detected at all sites (n = 25), but bovine and general ruminant markers were significantly associated with watershed characteristics. MST results, combined with watershed characteristics, suggest that streams draining areas with low-infiltration soil groups and high agricultural land use are at an increased risk for fecal contamination. Microbial source tracking has been applied in numerous studies to aid in identifying the sources of fecal contamination, but these studies usually lack information on the involvement of watershed characteristics. Our study combined watershed characteristics with MST results to provide more comprehensive insight into the factors that influence fecal contamination in order to implement the most effective best management practices.

Tracking the sources of Leptospira and nutrient flows in two urban watersheds of Puerto Rico.

This study investigated the relationship between nutrient levels, source of fecal contamination, and pathogenic Leptospira in Puerto Rico's northern coast and San Juan Bay Estuary (SJBE) aquatic ecosystems. Microbial source tracking (MST) was also used to investigate the connections between sources of feces contamination and the presence of Leptospira. Eighty-seven water samples were collected during the June (n=44) and August (n=43) in 2020. To quantify phosphorus and nitrogen concentrations, standard USEPA protocols were utilized, specifically Methods 365.4 for total and dissolved phosphorus, 351.2 for total Kjeldahl nitrogen and ammonium, and 353.2 for nitrate. Lipl32 gene-specific quantitative polymerase chain reaction (qPCR) was used to detect the presence of Leptospira. Human (HF183), canine (BacCan-UCD), and equine (HoF597) MST assays were utilized to trace the origins of fecal contamination. Forty one percent of the locations exceeded Puerto Rico's authorized total phosphorus limit of 160 g L-1, while 34% exceeded the total nitrogen limit of 1700 g L-1. Nearly half of the streams examined are affected by eutrophication. The MST analysis identified human and canine feces as the most prevalent contaminants, affecting approximately 50% of the sites. In addition, Leptospira was detected in 32% of the June samples. There was a significant correlation (r = 0.79) between the incidence of pathogenic Leptospira and the human bacterial marker (HF183). This study illuminates the central role of anthropogenic inputs in nutrient enrichment and pathogen proliferation in Puerto Rico's aquatic ecosystems.

Environmental risk assessment for fecal contamination sources in urban and peri-urban estuaries, in Escambia and Santa Rosa counties, FL, USA.

Fecal pollution of estuaries and adjacent creeks and streams is of significant concern along the Gulf of Mexico. The prospective threat to human life and water quality impairment via fecal pollution is a substantial danger to the strength and resistance of coastline areas. Pensacola, FL, has a prosperous coastal tourism industry that is utilized for numerous other uses, such as recreational watersports and boating, seafood, and shellfish harvesting. However, the frequency and severity of fecal contamination present possible socio-economic issues, specifically financial hardships. Therefore, understanding the source, abundance, and fate of fecal microbial pollutants in aquatic systems signifies an imperative initial stage for detecting the host sources and techniques to lessen their transport from the landscape. This research aimed to quantify the fecal indicator bacteria (FIB), Escherichia coli, and perform microbiological fecal source tracking to verify if the fecal inputs are of either animal or human host origin. Surface water samples were taken from urban and peri-urban creeks for two sampling periods (February 2021 and January 2022), and IDEXX Colilert-18 (USEPA Standard Method 9223) was used for E. coli enumeration. DNA extractions were obtained from each sample, and quantitative PCR was utilized for fecal microbial source tracking (MST) to detect human, dog, ruminant, and bird host-specific Bacteroides DNA. The result indicates elevated quantities of FIB, E. coli, that surpass the threshold considered safe regarding human health. E. coli at six sites over the two sampling periods exceeded the impairment threshold, reaching as high as 866.4 MPN/100 ml. Fecal source tracking identified human host fecal contamination at four of nine sites, dogs at three of nine, and birds at one site. However, those sites with sources identified via MST all had E. coli levels below impairment thresholds. No sites were determined to be positive for ruminant as a source or for the pathogen Helicobacter pylori. No canine host fecal inputs were found in January 2022, and only one site with human sewage. Our results highlight the utility of MST in assessing bacterial inputs to water bodies and the challenges.

Characterizing Differences in Sources of and Contributions to Fecal Contamination of Sediment and Surface Water with the Microbial FIT Framework.

Surface water monitoring and microbial source tracking (MST) are used to identify host sources of fecal pollution and protect public health. However, knowledge of the locations of spatial sources and their relative impacts on the environment is needed to effectively mitigate health risks. Additionally, sediment samples may offer time-integrated information compared to transient surface water. Thus, we implemented the newly developed microbial find, inform, and test framework to identify spatial sources and their impacts on human (HuBac) and bovine (BoBac) MST markers, quantified from both riverbed sediment and surface water in a bovine-dense region. Dairy feeding operations and low-intensity developed land-cover were associated with 99% (p-value < 0.05) and 108% (p-value < 0.05) increases, respectively, in the relative abundance of BoBac in sediment, and with 79% (p-value < 0.05) and 39% increases in surface water. Septic systems were associated with a 48% increase in the relative abundance of HuBac in sediment and a 56% increase in surface water. Stronger source signals were observed for sediment responses compared to water. By defining source locations, predicting river impacts, and estimating source influence ranges in a Great Lakes region, this work informs pollution mitigation strategies of local and global significance.

Microbial L-asparaginase as a promising enzyme for treatment of various cancers.

Metabolic differences between normal and cancerous cells have been used as a point of view for developing anticancer drugs. Some degrading enzymes of certain amino acids have been regarded to kill cancerous cells. L-Asparaginase (ASNase) has shown an excellent therapeutic response to asparagine-auxotrophic cancers such as acute lymphoblastic leukemia (ALL). Some bacteria, yeasts, molds, plants, and animals produce ASNase. Bacterial ASNases from Escherichia coli and Erwinia chrysanthemi are the FDA-approved drugs for ALL treatment. Here, we review new natural prokaryotic and eukaryotic sources of ASNases, recent advances to introduce improvement strategies for the production of recombinant ASNases as well as their chemical modifications, immobilization, nanoencapsulation, and in silico studies to increase efficiency and decrease side effects. Recent studies for application of ASNases to treatment of asparagine-auxotrophic cancers, especially solid cancers, have been reviewed. Furthermore, challenges and future perspectives are discussed for this promising therapeutic enzyme. KEY POINTS: • Review recent advances to introduce new sources of microbial L-asparaginases. • Review improvement strategies for the development of stable and non-toxic L-asparaginases. • Review microbial L-asparaginase application in various cancers' treatment.

Recent paradigm shifts in the perception of the role of Bacillus thuringiensis in foodborne disease.

Plant protection products based on Bacillus thuringiensis have been used to fight agricultural pests for decades and are the world's most frequently applied biopesticide. However, there is growing concern that B. thuringiensis residues in food may occasionally cause diarrheal illness in humans. This has recently sparked a plethora of research activities and vivid discussions across the scientific community, competent authorities, and the public. To support this discussion, we provide a structured overview of the current knowledge on the role of B. thuringiensis as a causative agent of foodborne infections in humans and pinpoint research gaps that need to be addressed for improved risk assessment. We review (i) recent taxonomic changes in the B. cereus group; (ii) the role of B. thuringiensis in transforming agrosystems; and (iii) key considerations for assessing the hazard potential of B. thuringiensis strains detected in foods. We conclude that (i) the taxonomy of the B. cereus group is collapsing, (ii) B. thuringiensis based biopesticides play a key role in realizing the UN's sustainable development goals, and (iii) risk assessment needs to move from taxonomy-driven considerations to strain-specific identification of virulence and pathogenicity traits We also provide an overview of relevant risk-related data for commonly used biopesticide strains.

Evaluation of crAssphage as a human-specific microbial source-tracking marker in the Republic of Korea.

CrAssphage is a novel and by far the most abundant bacteriophage in the human gut and has been proposed as a human-specific microbial source tracking (MST) marker. However, its global use as a human-specific MST marker requires validation in more extensive regions. The purpose of this study was to evaluate the specificity and abundance of the human-specific MST marker crAssphage with PCR and RT-PCR assays in human and animal feces in Korea. The prevalence of crAssphage was confirmed in 94 human feces samples (subjects: 19 to 45 years old) and 56 animal feces samples (from birds, raccoons, squirrels, weasels, deer, wild boars, hares, cats, and dogs). CrAssphage showed sensitivity of 0.39 and specificity of 1.00 in Korea, with a sequencing analysis showing that genotype II was dominant at 71.9%. The quantitative analysis showed that crAssphage is sufficiently abundant in human feces given the high concentration range of 4.26 to 8.25 log gene copies (GC)/ng in human feces. In conclusion, this study confirmed the crAssphage as a specific and abundant MST marker with which to identify human fecal contamination in Korea.

DNA fingerprinting using BOX-A1R and (GTG)5 primers identify spatial variations of fecal contamination along Pasig River, Philippines.

Pasig River is one of the most economically important rivers in Metro Manila, Philippines. It traverses some of the region's major cities, and because of its strategic location, it is utilized as a means of transportation, as a source of water for domestic and industrial uses, and for recreational purposes. However, due to population growth, industrialization, and land use, the river's water quality is deteriorating. Wastes that pollute the river pose health risks to the people that benefit from it. To prevent the river's further degradation, it is essential to identify the origin of contamination. In this study, the sources of fecal contamination in Pasig River were identified using BOX-A1R and (GTG)5 primers in the DNA fingerprinting of Escherichia coli isolated from the river. Results showed the dominance of human contamination (percent composition = 65.55%), followed by agricultural sources (percent composition = 23.48%), and the lowest was from sewage (percent composition = 10.98%). The results of this research can help in evaluating public health risks and can be used as a scientific basis for policymaking and implementation for the rehabilitation and improvement of Pasig River.

Recovery of Nucleic Acids of Enteric Viruses and Host-Specific Bacteroidales from Groundwater by Using an Adsorption-Direct Extraction Method.

In this study, the adsorption-elution method was modified to concentrate viral particles in water samples and investigate the contamination of groundwater with norovirus genogroup II (NoV GII), rotavirus A (RVA), and Pepper mild mottle virus (PMMoV). The mean recovery rate of a murine norovirus strain, which was inoculated into groundwater samples collected from a deep well, was the highest (39%) when the viral RNA was directly extracted from the membrane instead of eluting the adsorbed viral particles. This adsorption-direct extraction method was applied to groundwater samples (20 liters) collected from deep wells used for the public drinking water supply (n = 22) and private wells (n = 9). RVA (85 copies/liter) and NoV GII (35 copies/liter) were detected in water samples from a deep well and a private well, respectively. PMMoV was detected in 95% and 89% of water samples from deep wells and private wells, respectively, at concentrations of up to 990 copies/liter. The modified method was also used to extract bacterial DNA from the membrane (recovery rate of inoculated Escherichia coli K-12 was 22%). The Bacteroidales genetic markers specific to ruminants (BacR) and pigs (Pig2Bac) were detected in samples from a deep well and a private well, respectively. The modified virus concentration method has important implications for the management of microbiological safety in the groundwater supply. IMPORTANCE We investigated the presence of enteric viruses and bacterial genetic markers to determine fecal contamination in groundwater samples from deep wells used for the public drinking water supply and private wells in Japan. Groundwater is often subjected to chlorination; malfunctions in chlorine treatment result in waterborne disease outbreaks. The modified method successfully concentrated both viruses and bacteria in 20-liter groundwater samples. Norovirus genogroup II (GII), rotavirus A, Pepper mild mottle virus, and Bacteroidales genetic markers specific to ruminants and pigs were detected. Frequent flooding caused by increased incidences of extreme rainfall events promotes the infiltration of surface runoff containing livestock wastes and untreated wastewater into wells, possibly increasing groundwater contamination risk. The practical and efficient method developed in this study will enable waterworks and the environmental health departments of municipal/prefectural governments to monitor water quality. Additionally, the modified method will contribute to improving the microbiological safety of groundwater.

Fire alters plant microbiome assembly patterns: integrating the plant and soil microbial response to disturbance.

It is increasingly evident that the plant microbiome is a strong determinant of plant health. While the ability to manipulate the microbiome in plants and ecosystems recovering from disturbance may be useful, our understanding of the plant microbiome in regenerating plant communities is currently limited. Using 16S ribosomal RNA (rRNA) gene and internal transcribed spacer (ITS) region amplicon sequencing, we characterized the leaf, stem, fine root, rhizome, and rhizosphere microbiome of < 1-yr-old aspen saplings and the associated bulk soil after a recent high-intensity prescribed fire across a burn severity gradient. Consistent with previous studies, we found that soil microbiomes are responsive to fire. We extend these findings by showing that certain plant tissue microbiomes also change in response to fire. Differences in soil microbiome compositions could be attributed to soil chemical characteristics, but, generally, plant tissue microbiomes were not related to plant tissue elemental concentrations. Using source tracking modeling, we also show that fire influences the relative dominance of microbial inoculum and the vertical inheritance of the sapling microbiome from the parent tree. Overall, our results demonstrate how fire impacts plant microbiome assembly, diversity, and composition and highlights potential for further research towards increasing plant fitness and ecosystem recovery after fire events.