Deconvoluting and Interpreting Nontargeted Chemical Data: A Data-Driven Forensic Workflow for Identifying the Most Prominent Chemical Sources in Receiving Waters.

Chemical forensics aims to identify major contamination sources, but existing workflows often rely on predefined targets and known sources, introducing bias. Here, we present a data-driven workflow that reduces this bias by applying an unsupervised machine learning technique. We applied both nonmetric multidimensional scaling (NMDS) and non-negative matrix factorization (NMF) on the same nontargeted chemical data set to compare their different interpretations of environmental sources.

Resolved genomes of wastewater ESBL-producing and metagenomic analysis of source wastewater samples.

Extended-spectrum beta-lactamase (ESBL)-producing pose a serious threat to human health because of their resistance to the most commonly prescribed antibiotics: penicillins and cephalosporins. In this study, we provide a genomic and metagenomic context for the determinant beta-lactam resistance genes of ESBL-positive isolated from various wastewater treatment utilities in Oregon, USA. Class A beta-lactamase genes on chromosomes (CTX-M, TEM) were clustered with antibiotic resistance genes associated with other classes of antibiotics (sulfonamides and aminoglycosides) along with insertional elements.

Emerging investigator series: predicted losses of sulfur and selenium in european soils using machine learning: a call for prudent model interrogation and selection.

Reductions in sulfur (S) atmospheric deposition in recent decades have been attributed to S deficiencies in crops. Similarly, global soil selenium (Se) concentrations were predicted to drop, particularly in Europe, due to increases in leaching attributed to increases in aridity. Given its international importance in agriculture, reductions of essential elements, including S and Se, in European soils could have important impacts on nutrition and human health.

Genomic fingerprints of the world's soil ecosystems.

Despite the explosion of soil metagenomic data, we lack a synthesized understanding of patterns in the distribution and functions of soil microorganisms. These patterns are critical to predictions of soil microbiome responses to climate change and resulting feedbacks that regulate greenhouse gas release from soils. To address this gap, we assay 1,512 manually curated soil metagenomes using complementary annotation databases, read-based taxonomy, and machine learning to extract multidimensional genomic fingerprints of global soil microbiomes.

Target and suspect per- and polyfluoroalkyl substances in fish from an AFFF-impacted waterway.

A major source of toxic per- and polyfluoroalkyl substances (PFAS) is aqueous film-forming foams (AFFF) used in firefighting and training at airports and military installations, however, PFAS have many additional sources in consumer products and industrial processes. A field study was conducted on fish tissues from three reaches of the Columbia Slough, located near Portland International Airport, OR, that are affected by AFFF and other PFAS sources. Fishes including largescale sucker (Catostomus macrocheilus), goldfish (Carassius auratus), and largemouth bass (Micropterus salmoides) were collected in 2019 and 2020.

Target and Suspect Screening Integrated with Machine Learning to Discover Per- and Polyfluoroalkyl Substance Source Fingerprints.

This study elucidates per- and polyfluoroalkyl substance (PFAS) fingerprints for specific PFAS source types. Ninety-two samples were collected from aqueous film-forming foam impacted groundwater (AFFF-GW), landfill leachate, biosolids leachate, municipal wastewater treatment plant effluent (WWTP), and wastewater effluent from the pulp and paper and power generation industries. High-resolution mass spectrometry operated with electrospray ionization in negative mode was used to quantify up to 50 target PFASs and screen and semi-quantify up to 2,266 suspect PFASs in each sample.

Nontarget Chemical Composition of Surface Waters May Reflect Ecosystem Processes More than Discrete Source Contributions.

We investigated environmental, landscape, and microbial factors that could structure the spatiotemporal variability in the nontarget chemical composition of four riverine systems in the Oregon Coast Range, USA. We hypothesized that the nontarget chemical composition in river water would be structured by broad-scale landscape gradients in each watershed. Instead, only a weak relationship existed between the nontarget chemical composition and land cover gradients.

Machine Learning Applications for Chemical Fingerprinting and Environmental Source Tracking Using Non-target Chemical Data.

A frequent goal of chemical forensic analyses is to select a panel of diagnostic chemical features─colloquially termed a chemical fingerprint─that can predict the presence of a source in a novel sample. However, most of the developed chemical fingerprinting workflows are qualitative in nature. Herein, we report on a quantitative machine learning workflow.

Environmental Source Tracking of Per- and Polyfluoroalkyl Substances within a Forensic Context: Current and Future Techniques.

The source tracking of per- and polyfluoroalkyl substances (PFASs) is a new and increasingly necessary subfield within environmental forensics. We define PFAS source tracking as the accurate characterization and differentiation of multiple sources contributing to PFAS contamination in the environment. PFAS source tracking should employ analytical measurements, multivariate analyses, and an understanding of PFAS fate and transport within the framework of a conceptual site model.

Arsenic in Bangladeshi soils related to physiographic region, paddy management, and mirco- and macro-elemental status.

While the impact of arsenic in irrigated agriculture has become a major environmental concern in Bangladesh, to date there is still a limited understanding of arsenic in Bangladeshi paddy soils at a landscape level. A soil survey was conducted across ten different physiographic regions of Bangladesh, which encompassed six types of geomorphology (Bil, Brahmaputra floodplain, Ganges floodplain, Meghna floodplain, Karatoya-Bangali floodplain and Pleistocene terrace). A total of 1209 paddy soils and 235 matched non-paddy soils were collected.

Selenium deficiency risk predicted to increase under future climate change.

Deficiencies of micronutrients, including essential trace elements, affect up to 3 billion people worldwide. The dietary availability of trace elements is determined largely by their soil concentrations. Until now, the mechanisms governing soil concentrations have been evaluated in small-scale studies, which identify soil physicochemical properties as governing variables.

Marine Primary Productivity as a Potential Indirect Source of Selenium and Other Trace Elements in Atmospheric Deposition.

Atmospheric processes play an important role in the supply of the trace element selenium (Se) as well as other essential trace elements to terrestrial environments, mainly via wet deposition. Here we investigate whether the marine biosphere can be identified as a source of Se and of other trace elements in precipitation samples. We used artificial neural network (ANN) modeling and other statistical methods to analyze relationships between a high-resolution atmospheric deposition chemistry time series (March 2007-January 2009) from Plynlimon (UK) and exposure of air masses to marine chlorophyll a and to other source proxies.

Selenium cycling across soil-plant-atmosphere interfaces: a critical review.

Selenium (Se) is an essential element for humans and animals, which occurs ubiquitously in the environment. It is present in trace amounts in both organic and inorganic forms in marine and freshwater systems, soils, biomass and in the atmosphere. Low Se levels in certain terrestrial environments have resulted in Se deficiency in humans, while elevated Se levels in waters and soils can be toxic and result in the death of aquatic wildlife and other animals.

Surface and subsurface attenuation of trenbolone acetate metabolites and manure-derived constituents in irrigation runoff on agro-ecosystems.

Although studies have evaluated the ecotoxicity and fate of trenbolone acetate (TBA) metabolites, namely 17α-trenbolone (17α-TBOH), 17β-trenbolone (17β-TBOH), and trendione (TBO), their environmental transport processes remain poorly characterized with little information available to guide agricultural runoff management. Therefore, we evaluated TBA metabolite transport in representative agricultural systems with concurrent assessment of other manure-derived constituents. Leachate generated using manure from TBA-implanted cattle was applied to a subsurface infiltration plot (4 m) and surface vegetative filter strips (VFSs; 3, 4, and 5 m).

Trenbolone acetate metabolite transport in rangelands and irrigated pasture: observations and conceptual approaches for agro-ecosystems.

To assess the relative ecological risks of trenbolone acetate (TBA) use in agro-ecosystems, we evaluated the spatiotemporal dynamics of TBA metabolite transport during irrigation and rainfall events. Within a pasture, TBA-implanted heifers (40 mg TBA, 8 mg estradiol) were briefly penned (24 h) at high stocking densities (500 animal units (AU)/ha), prior to irrigation. Irrigation runoff concentrations of 17α-trenbolone (17α-TBOH) 0.

Mass balance approaches to characterizing the leaching potential of trenbolone acetate metabolites in agro-ecosystems.

Several studies have documented the occurrence and fate of trenbolone acetate (TBA) metabolites in soil and water. However, considerable uncertainty still exists with respect to TBA risk in agro-ecosystems because limited data are available to quantify excretion, transformation, and leaching processes. To address these uncertainties, we used experimental mesocosms and a mass balance approach to estimate the TBA metabolite leaching potential from manure excreted by implanted (40 mg TBA, 8 mg 17β-estradiol) beef cattle.

Product-to-parent reversion of trenbolone: unrecognized risks for endocrine disruption.

Trenbolone acetate (TBA) is a high-value steroidal growth promoter often administered to beef cattle, whose metabolites are potent endocrine-disrupting compounds. We performed laboratory and field phototransformation experiments to assess the fate of TBA metabolites and their photoproducts. Unexpectedly, we observed that the rapid photohydration of TBA metabolites is reversible under conditions representative of those in surface waters (pH 7, 25°C).

Identification and environmental implications of photo-transformation products of trenbolone acetate metabolites.

Despite the widespread use of the anabolic androgen trenbolone acetate (TBA) in animal agriculture, evidence demonstrating the occurrence of TBA metabolites such as 17β-trenbolone (17β-TBOH), 17α-trenbolone (17α-TBOH), and trendione (TBO) is relatively scarce, potentially due to rapid transformation processes such as direct photolysis. Therefore, we investigated the phototransformation of TBA metabolites and associated ecological implications by characterizing the photoproducts arising from the direct photolysis of 17β-TBOH, 17α-TBOH, and TBO and their associated ecotoxicity. LC-HRMS/MS analysis identified a range of hydroxylated products that were no longer photoactive, with primary photoproducts consisting of monohydroxy species and presumptive diastereomers.