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This study investigates agro-industrial by-products as sources of bioactive compounds, particularly focusing on phenolic compounds known for their antioxidant properties. With growing interest in natural alternatives to synthetic antioxidants due to safety concerns, this study highlights the health benefits of plant-derived phenolic compounds in food preservation and healthcare products. Traditional and advanced analytical techniques were used to obtain phytochemical profiles of various residue extracts, including espresso (SCG) and cold-brew spent coffee grounds (CBCG), pineapple peel (PP), beetroot pomace (BP), apple pomace (AP), black carrot pomace (BCP), and garlic peel (GP). Assessments of total phenolic content (TPC), total flavonoid content (TFC), and antioxidant capacity (AC) supported their revalorization. CBCG showed the highest TPC, TFC, and AC. TPC content in by-products decreased in the order CBCG > SCG > GP > BCP > PP > AP > BP, with a similar trend for TFC and AC. Phytochemical profiling via FI-ESI-FTICR-MS enabled the preliminary putative identification of a range of compounds, with polyphenols and terpenes being the most abundant. Univariate and multivariate analyses revealed key patterns among samples. Strong positive correlations (Pearson's R > 0.8) indicated significant contribution of polyphenols to antioxidant capacities. These findings highlight the potential of agro-industrial residues as natural antioxidants, advocating for their sustainable utilization. [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes (2H and 18O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems. [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) assemblages in freshwater rivers are formed from mixtures of simple to complex compounds that are highly variable across time and space. These mixtures largely form due to the environmental heterogeneity of river networks and the contribution of diverse allochthonous and autochthonous DOM sources. Most studies are, however, confined to local and regional scales, which precludes an understanding of how these mixtures arise at large, e.g., continental, spatial scales. The processes contributing to these mixtures are also difficult to study because of the complex interactions between various environmental factors and DOM. Here we propose the use of machine learning (ML) approaches to identify ecological processes contributing toward mixtures of DOM at a continental-scale. We related a dataset that characterized the molecular composition of DOM from river water and sediment with Fourier-transform ion cyclotron resonance mass spectrometry to explanatory physicochemical variables such as nutrient concentrations and stable water isotopes (2H and 18O). Using unsupervised ML, distinctive clusters for sediment and water samples were identified, with unique molecular compositions influenced by environmental factors like terrestrial input and microbial activity. Sediment clusters showed a higher proportion of protein-like and unclassified compounds than water clusters, while water clusters exhibited a more diversified chemical composition. We then applied a supervised ML approach, involving a two-stage use of SHapley Additive exPlanations (SHAP) values. In the first stage, SHAP values were obtained and used to identify key physicochemical variables. These parameters were employed to train models using both the default and subsequently tuned hyperparameters of the Histogram-based Gradient Boosting (HGB) algorithm. The supervised ML approach, using HGB and SHAP values, highlighted complex relationships between environmental factors and DOM diversity, in particular the existence of dams upstream, precipitation events, and other watershed characteristics were important in predicting higher chemical diversity in DOM. Our data-driven approach can now be used more generally to reveal the interplay between physical, chemical, and biological factors in determining the diversity of DOM in other ecosystems.

This study investigates agro-industrial by-products as sources of bioactive compounds, particularly focusing on phenolic compounds known for their antioxidant properties. With growing interest in natural alternatives to synthetic antioxidants due to safety concerns, this study highlights the health benefits of plant-derived phenolic compounds in food preservation and healthcare products. Traditional and advanced analytical techniques were used to obtain phytochemical profiles of various residue extracts, including espresso (SCG) and cold-brew spent coffee grounds (CBCG), pineapple peel (PP), beetroot pomace (BP), apple pomace (AP), black carrot pomace (BCP), and garlic peel (GP). Assessments of total phenolic content (TPC), total flavonoid content (TFC), and antioxidant capacity (AC) supported their revalorization. CBCG showed the highest TPC, TFC, and AC. TPC content in by-products decreased in the order CBCG > SCG > GP > BCP > PP > AP > BP, with a similar trend for TFC and AC. Phytochemical profiling via FI-ESI-FTICR-MS enabled the preliminary putative identification of a range of compounds, with polyphenols and terpenes being the most abundant. Univariate and multivariate analyses revealed key patterns among samples. Strong positive correlations (Pearson’s R > 0.8) indicated significant contribution of polyphenols to antioxidant capacities. These findings highlight the potential of agro-industrial residues as natural antioxidants, advocating for their sustainable utilization.

A large amount of dissolved organic matter (DOM) is transported to the ocean from terrestrial inputs each year (~0.95 Pg C per year) and undergoes a series of abiotic and biotic reactions, causing a significant release of CO2. Combined, these reactions result in variable DOM characteristics (e.g., nominal oxidation state of carbon, double-bond equivalents, chemodiversity) which have demonstrated impacts on biogeochemistry and ecosystem function. Despite this importance, however, comparatively few studies focus on the drivers for DOM chemodiversity along a riverine continuum. Here, we characterized DOM within samples collected from a stream network in the Yakima River Basin using ultrahigh-resolution mass spectrometry (i.e., FTICR-MS). To link DOM chemistry to potential function, we identified putative biochemical transformations within each sample. We also used various molecular characteristics (e.g., thermodynamic favorability, degradability) to calculate a series of functional diversity metrics. We observed that the diversity of biochemical transformations increased with increasing upstream catchment area and landcover. This increase was also connected to expanding functional diversity of the molecular formula. This pattern suggests that as molecular formulas become more diverse in thermodynamics or degradability, there is increased opportunity for biochemical transformations, potentially creating a self-reinforcing cycle where transformations in turn increase diversity and diversity increase transformations. We also observed that these patterns are, in part, connected to landcover whereby the occurrence of many landcover types (e.g., agriculture, urban, forest, shrub) could expand DOM functional diversity. For example, we observed that a novel functional diversity metric measuring similarity to common freshwater molecular formulas (i.e., carboxyl-rich alicyclic molecules) was significantly related to urban coverage. These results show that DOM diversity does not decrease along stream networks, as predicted by a common conceptual model known as the River Continuum Concept, but rather are influenced by the thermodynamic and degradation potential of molecular formula within the DOM, as well as landcover patterns.

While significant progress has been made in understanding global carbon (C) cycling, the mechanisms regulating belowground C fluxes and storage are still uncertain. New molecular technologies have the power to elucidate these processes, yet we have no widespread standardized implementation of molecular techniques. To address this gap, we introduce the Molecular Observation Network (MONet), a decadal vision from the Environmental Molecular Sciences Laboratory (EMSL), to develop a national network for understanding the molecular composition, physical structure, and hydraulic and biological properties of soil and water. These data are essential for advancing the next generation of multiscale Earth systems models. In this paper, we discuss the 1000 Soils Pilot for MONet, including a description of standardized sampling materials and protocols and a use case to highlight the utility of molecular-level and microstructural measurements for assessing the impacts of wildfire on soil. While the 1000 Soils Pilot generated a plethora of data, we focus on assessments of soil organic matter (SOM) chemistry via Fouriertransform ion cyclotron resonance-mass spectrometry and microstructural properties via X-ray computed tomography to highlight the effects of recent fire history in forested ecosystems on belowground C cycling. We observed decreases in soil respiration, microbial biomass, and potential enzyme activity in soils with high frequency burns. Additionally, the nominal oxidation state of carbon in SOM increased with burn frequency in surface soils. This results in a quantifiable shift in the molecular signature of SOM and shows that wildfire may result in oxidation of SOM and structural changes to soil pore networks that persist into deeper soils. [ABSTRACT FROM AUTHOR]

• HO• and RNS during VUV photolysis of NO3− contributed to TCNM formation. • Solution pH, chloride and bicarbonate cannot effectively dimmish TCNM formation. • TCNM formation showed a linear relationship with the Hammett constant. • Newly formed 1161 nitrogen-containing compounds have higher aromaticity. • Results indicated TCNM formation risk of VUV applying in water treatment. Vacuum ultraviolet (VUV) photolysis is recognized as an environmental-friendly treatment process. Nitrate (NO 3 −) and natural organic matter (NOM) are widely present in water source. We investigated trichloronitromethane (TCNM) formation during chlorination after VUV photolysis, because TCNM is an unregulated highly toxic disinfection byproduct. In this study: (1) we found reactive nitrogen species that is generated under VUV photolysis of NO 3 − react with organic matter to form nitrogen-containing compounds and subsequently form TCNM during chlorination; (2) we found the mere presence of 0.1 mmol/L NO 3 − can result in the formation of up to 63.96 µg/L TCNM; (3) we found the changes in pH (6.0-8.0), chloride (1-4 mmol/L), and bicarbonate (1-4 mmol/L) cannot effectively diminish TCNM formation; and, (4) we established the quantitative structure-activity relationship (QSAR) model, which indicated a linear relationship between TCNM formation and the Hammett constant (σ) of model compounds; and, (5) we characterized TCNM precursors in water matrix after VUV photolysis and found 1161 much more nitrogen-containing compounds with higher aromaticity were generated. Overall, this study indicates more attention should be paid to reducing the formation risk of TCNM when applying VUV photolysis process at scale. [Display omitted]. [ABSTRACT FROM AUTHOR]

Prostate cancer (PCa) is one of the most common male malignancies worldwide. In the current study, we evaluated the effects of a natural deep eutectic solvent (NADES) extract of Pueraria lobata roots rich in isoflavones (ISF) and Phaffia rhodozyma extract rich in astaxanthin (ASX) on an N-methyl-N-nitrosourea plus testosterone PCa model in rats. ISF consisted of puerarin, daidzein, genistein, formononetin and other polyphenols, while ASX contained lipids and unsaturated species in addition to astaxanthin. Extracts were administered through a whole promotion period in daily doses shown by our group to successfully inhibit benign prostate hyperplasia (BPH) development — 200 mg/kg for ISF and 25 mg/kg for ASX. Though a similar effect was found for BPH processes accompanying PCa induction, the incidence of PCa in animals treated with placebo, ISF and ASX was 37%, 37% and 41%, respectively, showing no chemopreventive activity of ISF and ASX. PCa development was associated with a decrease in the Ca/Mg ratio in serum and an increase in prostate tissue. Treatment with both extracts produced a normalization effect on Ca balance in serum, which, combined with a decrease in the prostatic index, suggests some positive health effects of ISF and ASX. [ABSTRACT FROM AUTHOR]

While significant progress has been made in understanding global carbon (C) cycling, the mechanisms regulating belowground C fluxes and storage are still uncertain. New molecular technologies have the power to elucidate these processes, yet we have no widespread standardized implementation of molecular techniques. To address this gap, we introduce the Molecular Observation Network (MONet), a decadal vision from the Environmental Molecular Sciences Laboratory (EMSL), to develop a national network for understanding the molecular composition, physical structure, and hydraulic and biological properties of soil and water. These data are essential for advancing the next generation of multiscale Earth systems models. In this paper, we discuss the 1000 Soils Pilot for MONet, including a description of standardized sampling materials and protocols and a use case to highlight the utility of molecular-level and microstructural measurements for assessing the impacts of wildfire on soil. While the 1000 Soils Pilot generated a plethora of data, we focus on assessments of soil organic matter (SOM) chemistry via Fourier-transform ion cyclotron resonance-mass spectrometry and microstructural properties via X-ray computed tomography to highlight the effects of recent fire history in forested ecosystems on belowground C cycling. We observed decreases in soil respiration, microbial biomass, and potential enzyme activity in soils with high frequency burns. Additionally, the nominal oxidation state of carbon in SOM increased with burn frequency in surface soils. This results in a quantifiable shift in the molecular signature of SOM and shows that wildfire may result in oxidation of SOM and structural changes to soil pore networks that persist into deeper soils.

Organic sulfur compounds (S-markers) such as benzothiophene (BT), dibenzothiophene (DBT), and benzonaphtothiophene (BNT) have been used for depositional paleoenvironment interpretations. In this study, the broader range of S-markers was semi-quantified by Fourier Transform Ion Cyclotron Resonance Mass Spectrometry (FTICR-MS) using atmospheric pressure photoionization in positive ion mode (APPI-P) for the interpretation of the depositional paleoenvironment and lithology in Amaral Machado's outcrop, Irati Formation, Paraná Basin for the first time. The variations in chemical composition, aromaticity as well as alkylation degree of the monosulfur compounds (S 1) and hydrocarbons (HC) classes (radical and protonated ions) analyzed in APPI-P were discussed in detail. The S-markers were semi-quantified using the internal standard DBT-d 8. The results from both S 1 and HC showed a clear distinction in the depositional paleoenvironment of the organic matter (OM) present in the evaluated samples. The S-markers interpretations were confirmed by classical biomarkers (regular steranes C 29 /C 27 , tetracyclic polyprenoids TPP/C 27 , diasteranes DIA 27 , steranes/17α-hopanes, gammacerane/C 30 , and pristane/phytane). The similarity in depth profiles using concentrations and peak intensities indicated that the ionization of major compound classes from extracts analyzed in APPI-P mode is not compromised by ion suppression. The double bond equivalent (DBE) distribution of S 1 and HC, together with the DBT/Phen ratio, provided valuable insights into the type and source of OM contributing to the reconstruction of the depositional paleoenvironment. S-markers semi-quantification was efficient in characterizing depositional paleoenvironment and allowed evaluation of different proxies of the outcrops. The base of the Amaral Machado outcrop presents an anoxic redox condition, typically hypersaline and abundant in S 1. The middle of the outcrop shows a strong marine influence with a contribution from terrestrial OM. Towards the top of the outcrop, belonging to the Serra Alta Formation, the environment is oxidizing with low concentrations of sulfur and typically terrigenous. • Evaluation from Paleoenvironment in Irati Formation, Amaral Machado outcrop by S-markers. • Semi-quantification of organic sulfur compounds and HC class by FTICR-MS. • Paleoenvironments are distinguished by molecular composition. • S-Marker C 40 proved to be a good paleoenvironment indicator. [ABSTRACT FROM AUTHOR]

Abstract Most soil carbon (C) is in the form of soil organic matter (SOM), the composition of which is controlled by the plant–microbe–soil continuum. The extent to which plant and microbial inputs contribute to persistent SOM has been linked to edaphic properties such as mineralogy and aggregation. However, it is unknown how variation in plant inputs, microbial community structure, and soil physical and chemical attributes interact to influence the chemical classes that comprise SOM pools. We used two long‐term biofuel feedstock field experiments to test the influence of cropping systems (corn and switchgrass) and soil characteristics (sandy and silty loams) on microbial selection and SOM chemistry. Cropping system had a strong influence on water‐extractable organic C chemistry with perennial switchgrass generally having a higher chemical richness than the annual corn cropping system. Nonetheless, cropping system was a less influential driver of soil microbial community structure and overall C chemistry than soil type. Soil type was especially influential on fungal community structure and the chemical composition of the chloroform‐extractable C. Although plant inputs strongly influence the substrates available for decomposition and SOM formation, total C and nitrogen (N) did not differ between cropping systems within either site. We conclude this is likely due to enhanced microbial activity under the perennial cropping system. Silty soils also had a higher activity of phosphate and C liberating enzymes. After 8 years, silty loams still contained twice the total C and N as sandy loams, with no significant response to biofuel cropping system inputs. Together, these results demonstrate that initial site selection is critical to plant–microbe interactions and substantially impacts the potential for long‐term C accrual in soils under biofuel feedstock production.

Though community-based scientific approaches are becoming more common, many scientific efforts are conducted by small groups of researchers that together develop a concept, analyze data, and interpret results that ultimately translate into a publication. Here, we present a community effort that breaks these traditional boundaries of the publication process by engaging the scientific community from initial hypothesis generation to final publication. We leverage community-generated data from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to study organic matter composition through the lens of ecological theory. This community endeavor will use a suite of paired physical and chemical datasets collected from 97 river corridors across the globe. With our first step aimed at ideation, we engaged a community of scientists from over 20 countries and 60 institutions, spanning disciplines and career stages by holding a virtual workshop (April 2021). In the workshop, participants generated content for questions, hypotheses, and proposed analyses based on the WHONDRS dataset. These ideation efforts resulted in several narratives investigating different questions led by different teams, which will be the basis for research articles in a Frontiers in Water collection. Currently, the community is collectively analyzing, interpreting, and synthesizing these data that will result in six crowdsourced articles using a single, existing WHONDRS dataset. The use of a shared dataset across articles not only lowers barriers for broad participation by not requiring generation of new data, but also provides unique opportunities for emergent learning by connecting outcomes across studies. Here we will explain methods used to enable this community endeavor aimed to promote a greater diversity of thinking on river corridor biogeochemistry through crowdsourced science.

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTIfeat), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTIfeat, we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTIfeat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTIfeat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTIfeat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types. [ABSTRACT FROM AUTHOR]

Understanding the mechanisms underlying the assembly of communities has long been the goal of many ecological studies. While several studies have evaluated community wide ecological assembly, fewer have focused on investigating the impacts of individual members within a community or assemblage on ecological assembly. Here, we adapted a previous null model β-nearest taxon index (βNTI) to measure the contribution of individual features within an ecological community to overall assembly. This new metric, called feature-level βNTI (βNTIfeat), enables researchers to determine whether ecological features (e.g., individual microbial taxa) contribute to divergence, convergence, or have insignificant impacts across spatiotemporally resolved metacommunities or meta-assemblages. Using βNTIfeat, we revealed that unclassified microbial lineages often contributed to community divergence while diverse groups (e.g., Crenarchaeota, Alphaproteobacteria, and Gammaproteobacteria) contributed to convergence. We also demonstrate that βNTIfeat can be extended to other ecological assemblages such as organic molecules comprising organic matter (OM) pools. OM had more inconsistent trends compared to the microbial community though CHO-containing molecular formulas often contributed to convergence, while nitrogen and phosphorus-containing formulas contributed to both convergence and divergence. A network analysis was used to relate βNTIfeat values from the putatively active microbial community and the OM assemblage and examine potentially common contributions to ecological assembly across different communities/assemblages. This analysis revealed that P-containing formulas often contributed to convergence/divergence separately from other ecological features and N-containing formulas often contributed to assembly in coordination with microorganisms. Additionally, members of Family Geobacteraceae were often observed to contribute to convergence/divergence in conjunction with both N- and P-containing formulas, suggesting a coordinated ecological role for family members and the nitrogen/phosphorus cycle. Overall, we show that βNTIfeat offers opportunities to investigate the community or assemblage members, which shape the phylogenetic or functional landscape, and demonstrate the potential to evaluate potential points of coordination across various community types.

Micomeria fruticosa and Teucrium polium are Lamiaceae plants found throughout the Mediterranean, including Lebanon. Aerial parts of both plants were taken from a rocky mountain in Lebanon's Bekaa region and alcoholic extraction and chromatographic separation were performed. Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) was used to examine crude extracts of both plants A and B, as well as their fractions. The mass spectra of both plants revealed great chemical complexity with a total of 6352 ions (peaks) for crude extract of plant A and 5147 ions (peaks) for extract B. The majority of chemicals found in both plants are condensed aromatics, particularly polyphenols which could explain the previously documented anticancer effects of both plants. [ABSTRACT FROM AUTHOR]

We characterized the dissolved organic matter (DOM) under baseflow conditions from a set of rivers in the Mohawk and Hudson River watersheds. The rivers in this study drain a range of bedrock geologies and land cover. We identify how those factors influence riverine DOM reactivity and the source, age, and composition of the biolabile DOM. We performed laboratory incubation experiments to characterize each river's reactive and non‐reactive DOM pools. Measurements of dissolved organic carbon concentration, radiocarbon, Ultraviolet‐visible spectroscopy absorbance, and Fourier‐transform ion cyclotron resonance mass spectrometry (FTICR‐MS) analysis were performed at each incubation start and end, allowing us to determine the quantity, age, and composition of the reactive and nonreactive DOM pools. We find that lithology controls bulk DOM ages, with watersheds underlain by shale/limestone having the most aged DOM and crystalline/metasedimentary watersheds having the youngest DOM. We observe that for a given lithology, bulk DOM age increases with the proportion of agricultural land in the watershed–suggesting agricultural practices mobilize aged DOM. FTICR‐MS analysis reveals that both lithology and land cover influence DOM composition. Shale/limestone watersheds showed DOM compositions distinct from other watershed lithologies, and the percentage of nitrogen‐containing DOM correlated with agricultural influence. In two of the studied rivers we find that the biolabile DOM fraction is older than the bulk DOM (upwards of 7 kyr) revealing that aged DOM may be preferentially consumed in these rivers. Our findings provide insight into how riverine carbon cycles may respond to watershed disturbances that influence DOM inputs to rivers. Plain Language Summary: As rivers drain land areas around the globe they pick up organic matter (OM) which is then transported and transformed as water flows downstream. Through the degradation of some of this OM to carbon dioxide (CO2), rivers play a critical role in the global carbon cycle, with CO2 emissions from rivers estimated to be equivalent to >20% of the CO2 emissions from the burning of fossil fuels. Despite the importance of rivers in the global carbon cycle, many questions remain as to what controls the composition and reactivity of OM within rivers. We investigated how watershed geology and land cover (e.g., forested vs. agricultural land) influence the chemical composition, age, and reactivity of the OM in rivers. We found that rivers draining shale/limestone watersheds had chemically distinct OM that is much older and more reactive than OM from other types of watersheds. We also found that across all watersheds the age of OM increased with the proportion of the watershed that is devoted to agricultural activity and that in some watersheds the older OM was preferentially consumed. Our findings suggest that disturbances to land (e.g., agriculture) may release aged, previously buried OM that can then be transformed to CO2. Key Points: Watershed geology and land cover influence river dissolved organic matter composition and biolability under baseflow conditionsDissolved organic carbon (DOC) bulk ages are strongly influenced by watershed geology and the proportion of agricultural land coverUnder baseflow, high molecular weight compounds are preferentially consumed and aged DOC is preferentially consumed in smaller streams [ABSTRACT FROM AUTHOR]

Soil redox conditions exert substantial influence on biogeochemical processes in terrestrial ecosystems. Humid tropical forest soils are often characterized by fluctuating redox, yet how these dynamics affect patterns of organic matter decomposition and associated CO2 fluxes remains poorly understood. We used a 13C-label incubation experiment in a humid tropical forest soil to follow the decomposition of plant litter and soil organic matter (SOM) in response to four redox regimes—static oxic or anoxic, and two oscillating treatments. We used high-resolution mass spectrometry to characterize the relative composition of organic compound classes in the water extractable OM. CO2 production from litter and SOM showed different responses to redox treatments. While cumulative production of SOM-derived CO2 was positively correlated with the length of oxic exposure (r = 0.89, n = 20), cumulative 13C-litter-derived CO2 production was not linked to oxygen availability. Litter-derived CO2 production was highest under static anoxic conditions in the first half of the experiment, and later dropped to the lowest rate amongst the treatments. In anoxic soils, we observed depletion of more oxidized water-extractable OM (especially amino sugar-, carbohydrate-, and protein-like compounds) over the second half of the experiment, which likely served as substrates for anaerobic CO2 production. Results from two-pool kinetic modeling showed that more frequent anoxic exposure limited decomposition of a slow-cycling C pool, but not a fast-cycling pool. These results suggest that aerobic and anaerobic heterotrophs were equally effective at degrading labile substrates released from fresh plant litter in this humid tropical forest soil, while aerobic decomposers were more effective in breaking down the potentially refractory compounds found in SOM. [ABSTRACT FROM AUTHOR]

Most soil carbon (C) is in the form of soil organic matter (SOM), the composition of which is controlled by the plant–microbe–soil continuum. The extent to which plant and microbial inputs contribute to persistent SOM has been linked to edaphic properties such as mineralogy and aggregation. However, it is unknown how variation in plant inputs, microbial community structure, and soil physical and chemical attributes interact to influence the chemical classes that comprise SOM pools. We used two long‐term biofuel feedstock field experiments to test the influence of cropping systems (corn and switchgrass) and soil characteristics (sandy and silty loams) on microbial selection and SOM chemistry. Cropping system had a strong influence on water‐extractable organic C chemistry with perennial switchgrass generally having a higher chemical richness than the annual corn cropping system. Nonetheless, cropping system was a less influential driver of soil microbial community structure and overall C chemistry than soil type. Soil type was especially influential on fungal community structure and the chemical composition of the chloroform‐extractable C. Although plant inputs strongly influence the substrates available for decomposition and SOM formation, total C and nitrogen (N) did not differ between cropping systems within either site. We conclude this is likely due to enhanced microbial activity under the perennial cropping system. Silty soils also had a higher activity of phosphate and C liberating enzymes. After 8 years, silty loams still contained twice the total C and N as sandy loams, with no significant response to biofuel cropping system inputs. Together, these results demonstrate that initial site selection is critical to plant–microbe interactions and substantially impacts the potential for long‐term C accrual in soils under biofuel feedstock production. [ABSTRACT FROM AUTHOR]

A critical component of assessing the impacts of climate change on watershed ecosystems involves understanding the role that dissolved organic matter (DOM) plays in driving whole ecosystem metabolism. The hyporheic zone—a biogeochemical control point where ground water and river water mix—is characterized by high DOM turnover and microbial activity and is responsible for a large fraction of lotic respiration. Yet, the dynamic nature of this ecotone provides a challenging but important environment to parse out different DOM influences on watershed function and net carbon and nutrient fluxes. We used high-resolution Fourier-transform ion cyclotron resonance mass spectrometry to provide a detailed molecular characterization of DOM and its transformation pathways in the Columbia river watershed. Samples were collected from ground water (adjacent unconfined aquifer underlying the Hanford 300 Area), Columbia river water, and its hyporheic zone. The hyporheic zone was sampled at five locations to capture spatial heterogeneity within the hyporheic zone. Our results revealed that abiotic transformation pathways (e.g., carboxylation), potentially driven by abiotic factors such as sunlight, in both the ground water and river water are likely influencing DOM availability to the hyporheic zone, which could then be coupled with biotic processes for enhanced microbial activity. The ground water profile revealed high rates of N and S transformations via abiotic reactions. The river profile showed enhanced abiotic photodegradation of lignin-like molecules that subsequently entered the hyporheic zone as low molecular weight, more degraded compounds. While the compounds in river water were in part bio-unavailable, some were further shown to increase rates of microbial respiration. Together, river water and ground water enhance microbial activity within the hyporheic zone, regardless of river stage, as shown by elevated putative amino-acid transformations and the abundance of amino-sugar and protein-like compounds. This enhanced microbial activity is further dependent on the composition of ground water and river water inputs. Our results further suggest that abiotic controls on DOM should be incorporated into predictive modeling for understanding watershed dynamics, especially as climate variability and land use could affect light exposure and changes to ground water essential elements, both shown to impact the Columbia river hyporheic zone.

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling—termed substrate-explicit modeling—that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic models by only two parameters regardless of the complexity of OM profiles, which can greatly facilitate the integration with reactive transport models for ecosystem simulations by alleviating the difficulty in parameter identification. The two parameters include maximal growth rate (μmax) and harvest volume (Vh) (i.e., the volume that a microbe can access for harvesting energy). For every detected organic molecule in a given sample, our approach provides a systematic way to formulate reaction kinetics from chemical formula, which enables the evaluation of the impact of OM character on biogeochemical processes across conditions. In a case study of two sites with distinct OM thermodynamics using ultra high-resolution metabolomics datasets derived from Fourier transform ion cyclotron resonance mass spectrometry analyses, our method predicted how oxidative degradation is primarily driven by thermodynamic efficiency of OM consistent with experimental rate measurements (as shown by correlation coefficients of up to 0.61), and how biogeochemical reactions can vary in response to carbon and/or oxygen limitations. Lastly, we showed that incorporation of enzymatic regulations into substrate-explicit models is critical for more reasonable predictions. This result led us to present integrative biogeochemical modeling as a unifying framework that can ideally describe the dynamic interplay among microbes, enzymes, and substrates to address advanced questions and hypotheses in future studies. Altogether, the new modeling concept we propose in this work provides a foundational platform for unprecedented predictions of biogeochemical and ecosystem dynamics through enhanced integration with diverse experimental data and extant modeling approaches.

The initial bacterial adhesion phase is a pivotal and unstable step in the formation of biofilms. The initiation of biofilm formation is an unstable process caused by the reversible adhesion of bacteria, which is always time-consuming and yet to be elucidated. In this study, impedance-based real time cell analysis (RTCA) was employed to comprehensively investigate the initial bacterial adhesion process. Results showed that the time required for the unstable adhesion process was significantly (p

Predictive biogeochemical modeling requires data-model integration that enables explicit representation of the sophisticated roles of microbial processes that transform substrates. Data from high-resolution organic matter (OM) characterization are increasingly available and can serve as a critical resource for this purpose, but their incorporation into biogeochemical models is often prohibited due to an over-simplified description of reaction networks. To fill this gap, we proposed a new concept of biogeochemical modeling—termed substrate-explicit modeling —that enables parameterizing OM-specific oxidative degradation pathways and reaction rates based on the thermodynamic properties of OM pools. Based on previous developments in the literature, we characterized the resulting kinetic models by only two parameters regardless of the complexity of OM profiles, which can greatly facilitate the integration with reactive transport models for ecosystem simulations by alleviating the difficulty in parameter identification. The two parameters include maximal growth rate (μmax) and harvest volume (Vh) (i.e., the volume that a microbe can access for harvesting energy). For every detected organic molecule in a given sample, our approach provides a systematic way to formulate reaction kinetics from chemical formula, which enables the evaluation of the impact of OM character on biogeochemical processes across conditions. In a case study of two sites with distinct OM thermodynamics using ultra high-resolution metabolomics datasets derived from Fourier transform ion cyclotron resonance mass spectrometry analyses, our method predicted how oxidative degradation is primarily driven by thermodynamic efficiency of OM consistent with experimental rate measurements (as shown by correlation coefficients of up to 0.61), and how biogeochemical reactions can vary in response to carbon and/or oxygen limitations. Lastly, we showed that incorporation of enzymatic regulations into substrate-explicit models is critical for more reasonable predictions. This result led us to present integrative biogeochemical modeling as a unifying framework that can ideally describe the dynamic interplay among microbes, enzymes, and substrates to address advanced questions and hypotheses in future studies. Altogether, the new modeling concept we propose in this work provides a foundational platform for unprecedented predictions of biogeochemical and ecosystem dynamics through enhanced integration with diverse experimental data and extant modeling approaches. [ABSTRACT FROM AUTHOR]

[Display omitted] • The products of chlorination of AC with higher PFR intensity were more toxic. • The PRF of AC promoted the formation of N-DBPs, polycyclic aromatic compounds and polyphenols. • The PRF of AC promoted chlorine decay and induced generation of O 2 •− and Cl•. Both activated carbon (AC) and chlorine are commonly used in water treatment processes and thus the exposure of chlorine to AC surface is unavoidable under some circumstances. Therefore, evaluating the effects of AC, particularly the persistent free radicals (PFRs) of AC on the chlorination by-products is critical for drinking water safety. Here, through comparison of the chlorination process of different ACs with similar pore structure but different PFR intensities, it was found that AC with more PFRs generated more unknown by-products with lower relative cell viability (85%). The Fourier transform ion cyclotron resonance- mass spectrometry results showed that the proportions of one-chlorine and nitrogen containing by-products generated by AC with higher PFR intensity were 19.6% and 16.9%, respectively, which were higher than those generated by AC with lower PFR intensity. Furthermore, the polycyclic aromatic compounds and polyphenols with high toxicity were only found in the chlorination products of AC with high PFR intensity. The PFRs of AC could promote the chlorine decay and induce the generation of superoxide radical and chlorine radical, and thus led to the formation of more toxic by-products. This study provides new insights into the risks of water chlorination process and by-product formation in the presence of AC. [ABSTRACT FROM AUTHOR]

Lignin is the second most abundant natural biopolymer and potentially a valuable alternative energy source for conventional fossil fuels. In this study, Fourier-transform ion cyclotron resonance-mass spectrometry (FTICR-MS) in conjunction with phase correction was applied to study photooxidation products of lignin using a 7 Tesla (T) mass spectrometer. The application of 7 T FTICR-MS has often been inadequate for the analysis of complex natural organic matter because of insufficient resolving power as compared with high-field FTICR, which led to incorrect assignments of elemental formulae and discontinuous plots in graphical and statistical analyses. Here, the application of phase correction to the FTICR mass spectra of lignin oxidation products greatly improved the spectral quality, and thus, readily permitted characterization of photooxidation processes of lignin compounds under simulated solar radiation conditions.

Low-molecular-weight (LMW) aromatics are crucial in meditating fungal processes for plant biomass decomposition. Some LMW compounds are employed as electron donors for oxidative degradation in brown rot (BR), an efficient wood-degrading strategy in fungi that selectively degrades carbohydrates but leaves modified lignins. Previous understandings of LMW aromatics were primarily based on “bulk extraction”, an approach that cannot fully reflect their real-time functions during BR. Here, we applied an optimized molecular imaging method that combines matrix-assisted laser desorption ionization (MALDI) with Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) to directly measure the temporal profiles of BR aromatics as Rhodonia placenta decayed a wood wafer. We found that some phenolics were pre-existing in wood, while some (e.g., catechin-methyl ether and dihydroxy-dimethoxyflavan) were generated immediately after fungal activity. These pinpointed aromatics might be recruited to drive early BR oxidative mechanisms by generating Fenton reagents, Fe2+ and H2O2. As BR progressed, ligninolytic products were accumulated and then modified into various aromatic derivatives, confirming that R. placenta depolymerizes lignin. Together, this work confirms aromatic patterns that have been implicated in BR fungi, and it demonstrates the use of MALDI-FTICR-MS imaging as a new approach to monitor the temporal changes of LMW aromatics during wood degradation.

Photochemical production of hydroxyl radical (·OH) from algal organic matter (AOM) collected from Lake Torrens in South Australia was examined using a sunlight simulator. The two AOM isolates featured lower molecular weight, lower chromophoric content, and lower SUVA 254 (0.7 and 0.9, L mgC−1 m−1) than the reference Suwannee River hydrophobic acid (SR-HPO), they had considerably higher apparent quantum yields ( ϕ N O M O H , 3.03 × 10−5 and 2.18 × 10−5) than SR-HPO (0.84 × 10−5). Fluorescence excitation-emission matrix (FEEM) showed that the major components in the AOM were aromatic protein-like and soluble microbial substances. Unique formulas of the two AOM isolates as compared to SR-HPO were revealed using FTICR-MS and classified into four areas, namely protein-like molecules with low O/C (H/C > 1.5, O/C: 0.2–0.4), lignin-derived moieties with low O/C (H/C:1.0–1.5, O/C: 0.1–0.3), protein-like molecules with high O/C (H/C > 1.5, O/C: 0.5–0.7), and carbohydrate derivatives (H/C > 1.5, O/C > 0.7). These unique AOM moieties characterised utilizing FEEM and FTICR-MS were tentatively postulated to contribute to the high ϕ N O M O H . To the best of our knowledge, this is the first study performed to both evaluate natural AOM as an efficient photosensitiser of ·OH and propose AOM moieties responsible for the high ϕ N O M O H . Image 1 • Algal organic matter showed higher quantum yield than Suwannee River organic matter. • Algal organic matter was characterised by FEEM and FTICR-MS. • Possible sources of higher quantum yield were proposed. [ABSTRACT FROM AUTHOR]

Forecasting the long-term fate of plutonium (Pu) is becoming increasingly important as more worldwide military and nuclear-power waste is being generated. Nagasaki sediments containing bomb-derived Pu that was deposited in 1945 provided a unique opportunity to explore the long-term geochemical behavior of Pu. Through a combination of selective extractions and molecular characterization via electrospray ionization Fourier-transform ion cyclotron resonance mass spectrometry (ESI-FTICRMS), we determined that 55 ± 3% of the bomb-derived 239,240Pu was preferentially associated with more persistent organic matter compounds in Nagasaki sediments, particularly those natural organic matter (NOM) stabilized by Fe oxides (NOM Fe-oxide). Other organic matter compounds served as a secondary sink of these bomb-derived 239,240Pu (31 ± 2% on average), and <20% of the 239,240Pu was immobilized by inorganic mineral particles. In a narrow, 239,240Pu-enriched layer of only 9-cm depth (total core depth was 600 cm), N-containing carboxyl aliphatic and/or alicyclic molecules (CCAM) in NOM Fe-oxide and other NOM fractions immobilized the majority of 239,240Pu. Among the cluster of N-containing CCAM moieties, hydroxamate siderophores, the strongest known Pu chelators in nature, were further detected in these "aged" Nagasaki bomb residue-containing sediments. While present long-term disposal and environmental remediation modeling assume that solubility limits and sorption to mineral surfaces control Pu subsurface mobility, our observations suggest that NOM, which is present in essentially all subsurface systems, undoubtedly plays an important role in sequestrering Pu. Ignoring the role of NOM in controlling Pu fate and transport is not justified in most environmental systems. Unlabelled Image • Long-term deposited bomb-derived 239,240Pu was assessed in deep Nagasaki sediments (>400 cm) • Majority of 239,240Pu was bound to Fe oxide-occluded recalcitrant organic matter • N-containing carboxyl aliphatic molecules represent strong ligands that can bind 239,240Pu over long durations • Hydroxamate siderophores, the strongest Pu chelators in nature, were detected in Pu-carrying moieties in deep sediments [ABSTRACT FROM AUTHOR]

Graphical abstract Abstract A host of vanadyl petroporphyrins containing multiple sulfur and oxygen atoms and their combinations (C c H 2c+Z N 4 VO o S s , s = 0–3, o = 1–4, Z = −28 to −70) in a vacuum residue were observed by a combination of extensive enrichment of petroporphyrins and detailed analysis using ultra-high resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS). Many of the petroporphyrin species are being observed for the very first time. The patterns of the porphyrin type distribution revealed dramatic differences in the sulfur and oxygen atom incorporations and their impact on Z number. For each sulfur atom addition, the average Z-number was reduced by ∼4–7, implying that sulfur may be incorporated by the additions of thiophene or cyclic thiophene moieties. In contrast, oxygen addition had little to no impact on the average Z number, implying that oxygen may be incorporated as carbonyl or hydroxyl groups. The porphyrin-based structures were found to contain as many as 8 aromatic rings in addition to the porphyrin macrocycle. Petroporphyrins in longer wavelength absorption fractions were found to contain more heteroatoms and more condensed aromatic rings. [ABSTRACT FROM AUTHOR]

Interactions between dissolved organic matter (DOM) and surrounding environments are highly complex. Understanding DOM at the molecular level can contribute to the management of soil pollution and safeguarding agricultural fields. Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) has enabled a molecular-level understanding of DOM. Accordingly, in this study, we investigated soil samples from 27 different regions of mainland China with various soil types and climatic characteristics. Based on the geographical features of the four typical climatic zones in mainland China (temperate monsoon, temperate continental, subtropical monsoon, and Qinghai-Tibet Plateau climates), we employed high-resolution mass spectrometry to determine the molecular diversity of DOM under different climatic conditions. The results indicated that lignin and tannin-like substances were the most active categories of DOM in the soils. Collectively, the composition and unsaturation of DOM molecules are influenced by sunlight, precipitation, temperature, and human activity. All climatic regions contained a substantial number of characteristic molecules, with CHO and CHON constituting over 80%, and DOM containing nitrogen and sulfur was relatively more abundant in the monsoon regions. The complex composition of DOM incorporates various active functional groups, such as −NO2 and −ONO2. Furthermore, soil DOM in the monsoon regions showed higher unsaturation and facilitated various (bio) biochemical reactions in the soil. [Display omitted] • Lignin and tannins accounted for more than 80% of DOM in farmland soils. • Various irrigation methods increased the number of soil DOM molecular species. • High nitrogen and low sulfur compounds were unique to the temperate monsoon climate. • The coexistence of N and S in farmland soil DOM served as an indicator in monsoon regions. • The unsaturation of soil DOM was higher in the monsoon regions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sodium acetate supplementation enhanced DON removal up to 45% via co-metabolism. • Most sulfur-containing DON molecules were eliminated with sodium acetate addition. • DON concentration increased by 22% in the absence of sodium acetate. • Decarboxylase and deaminase genes were upregulated with sodium acetate addition. • High ammonia oxidation rate was achieved in the granular sludge reactor. Dissolved organic nitrogen (DON) comprises approximately 25% of dissolved nitrogen in landfill leachate wastewater (LLW), posing potential risks such as stimulating algal growth and forming disinfection by-products if not treated properly. While DON characterization and removal by physicochemical methods in wastewater treatment systems have been examined, biological strategies for effective DON removal remain less developed. This study explores the influence of sodium acetate addition during denitrification process on LLW DON removal. With sodium acetate addition (Stage I), we achieved 99% ammonia removal, 94% total inorganic nitrogen (TIN) removal, and 45% DON removal. Fourier-transform ion cyclotron resonance mass spectrometry (FTICR-MS) results suggested the majority of sulfur-containing DON molecules were eliminated in Stage I. Conversely, in the absence of sodium acetate (Stage II), while 99% ammonia removal was maintained, TIN removal dropped to around 10%, and DON concentrations (largely sulfur-containing DON) increased by approximately 22%. Cycle tests revealed similar DON reductions in the aerobic phase across both stages, whereas in the anoxic phase, DON concentrations decreased in Stage I but increased in Stage II. Functional gene prediction indicated higher expression of decarboxylase and deaminase genes in Stage I compared to Stage II. Consequently, this study posits that sodium acetate addition enhances DON removal, potentially via co-metabolism. [ABSTRACT FROM AUTHOR]

Abstract Many essential oils (EOs) are screened as potential sources of antimicrobial compounds. EOs from the genus Satureja have recognized biological properties, including analgesic, anti-inflammatory, immunomodulatory, anticancer, and antimicrobial activity. This study aimed to obtain a metabolite profile of commercial essential oil of S. montana L. (SEO) and to evaluate its antimicrobial properties, both alone and combined with gentamicin towards Gram-negative and Gram-positive bacterial strains. Untargeted analyses based on direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS) and on GC-MS have provided a high metabolome coverage, allowing to identify carvacrol, cymene and thymol as the major components of commercial SEO. SEO exerted an antimicrobial activity and induced a synergistic interaction with gentamicin against both reference and clinical bacterial strains. A significant reduction of Escherichia coli , Staphylococcus aureus and Listeria monocytogenes biofilm formation was induced by SEO. As a result of SEO treatment, clear morphological bacterial alterations were visualized by scanning electron microscopy: L. monocytogenes and S. aureus showed malformed cell surface or broken cells with pores formation, whereas E. coli displayed collapsed cell surface. These results encourage further studies about bactericidal and antibiotic synergistic effect of SEO for combined therapy in clinical setting as well as in agricultural systems. Graphical abstract Image 1 Highlights • Carvacrol, cymene and thymol are major components of Satureja montana essential oil. • S. montana essential oil shows antimicrobial activity. • S. montana essential oil exerts synergistic interaction with gentamicin against bacterial strains. • Reduction of bacterial biofilm formation was induced by S. montana essential oil. [ABSTRACT FROM AUTHOR]

Highlights • Petroleomic was applied to 69 off-shore Brazilian crude oils samples. • Kerogen type plays an important control on NSO compounds. • Clear separation based on polar species found in marine and lacustrine oils. • Negative ESI FTICR-MS can be used to perform geochemical assessment in crude oils. Abstract Lacustrine and marine crude oils from different off-shore Brazilian basins were analyzed using a 7.2 Tesla LTQ FTICR-MS instrument. The samples were analyzed via electrospray ionization in the negative ion mode focusing on the polar compounds, i.e., nitrogen-, sulfur-, and oxygen-containing (NSO) compounds. We also employed a combination of other geochemical methods, such as GC-FID and GC-MS analyses, to characterize and assess the depositional environments of the different oil families. The results indicate that lacustrine oils tend to be enriched in Nx compounds, while marine oils show preference for Ox compounds. The dominant heteroatomic classes in crude oils are N1, followed by O1, O2, and N1O1 with remarkable differences in their distributions between marine and lacustrine, strongly suggesting the control by the kerogen type of the heteroatomic compounds found in these crude oils. Considerable differences in the DBE distribution of the main classes analyzed between the crude oils allowed an efficient geochemical characterization regarding their origin. The use of negative ESI FTICR-MS as a geochemistry tool can provide additional information beyond that obtained with currently employed geochemical methods, resulting in the full comprehension of crude oil composition. [ABSTRACT FROM AUTHOR]

Analysis of singly glycosylated peptides has evolved to a point where large-scale LC-MS analyses can be performed at almost the same scale as proteomics experiments. While collisionally activated dissociation (CAD) remains the mainstay of bottom-up analyses, it performs poorly for the middle-down analysis of multiply glycosylated peptides. With improvements in instrumentation, electron-activated dissociation (ExD) modes are becoming increasingly prevalent for proteomics experiments and for the analysis of fragile modifications such as glycosylation. While these methods have been applied for glycopeptide analysis in isolated studies, an organized effort to compare their efficiencies, particularly for analysis of multiply glycosylated peptides (termed here middle-down glycoproteomics), has not been made. We therefore compared the performance of different ExD modes for middle-down glycopeptide analyses. We identified key features among the different dissociation modes and show that increased electron energy and supplemental activation provide the most useful data for middle-down glycopeptide analysis.Graphical Abstract [ABSTRACT FROM AUTHOR]

Abstract: The path of carbon (C) from plant litter to soil organic matter (SOM) is key to understanding how soil C stocks and microbial decomposition will respond to climate change and whether soil C sinks can be enhanced. Long‐term ecosystem‐scale litter manipulations and molecular characterization of SOM provide a unique opportunity to explore these issues. We incubated soils from a 20‐year litter input experiment for 525 days and asked how litter quantity and source (i.e., roots versus aboveground litter) affected C cycling, microbial function, and the size and molecular composition of C pools. Input exclusion led to a 30% loss of soil C, attributable largely to the nonmineral‐associated C fraction, and to declines in soil C decomposition. The absence of roots caused a shift in the microbial catabolic profile, though there was little evidence that root litter was preferentially stabilized. Although C pool size did not change with litter additions, Fourier transform ion cyclotron resonance mass spectrometry analysis of the finest mineral fraction revealed dramatic changes to the chemical composition of carbon. Lipid content increased proportionally with input addition and was subsequently mineralized during incubation, indicating that this fraction was metabolically active. Moreover, nonmetric dimensional scaling showed that both litter treatments and incubation caused the molecular composition of SOM to change. We conclude that the path of C from litter to soil may involve labile pools and root‐driven microbial activity associated directly with SOM in the soil mineral matrix otherwise previously hypothesized to be stable. [ABSTRACT FROM AUTHOR]

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is well-renowned for its ultrahigh resolving power and mass measurement accuracy. As with other types of analytical instrumentation, achievable signal-to-noise ratio (S/N) is an important analytical figure of merit with FTICR-MS. S/N can be improved with higher magnetic fields and longer time-domain signal acquisition periods. However, serial signal averaging of spectra or time-domain signals acquired with multiple ion populations is most commonly used to improve S/N. On the other hand, serial acquisition and averaging of multiple scans significantly increases required data acquisition time and is often incompatible with on-line chromatographic separations. In this study, we investigated the potential for increased S/N by averaging 4 spectra that were acquired in parallel with a single ICR cell with 4 pairs of dipole detection electrodes, each with an independent pre-amplifier. This spectral averaging was achieved with no need for multiple ion accumulation events nor multiple, serial excitation and detection events. These efforts demonstrated that parallel signal acquisition with 4 detector electrode pairs produces S/N 1.76-fold higher than that from a single detection electrode pair. With parallel detection, improved S/N was achieved with no observable loss in resolving power (100,000) as compared with that from a single detection electrode pair. These results demonstrate that parallel detection of multiple induced image current signals with multiple preamplifiers exists as a viable option for future instrumentation to increase achievable S/N and sensitivity. This approach may have general utility especially where conventional serial signal averaging is impractical. [ABSTRACT FROM AUTHOR]

Purpose: Dissolved organic matter (DOM) composition is influenced by and modulates biogeochemical processes, yet DOM characterization techniques are challenged by its heterogeneous properties and structures. In this paper, ultrahigh electrospray ionization Fourier transform ion cyclotron resonance (ESI-FTICR) mass spectrometry is used to characterize previously isolated and well-characterized four DOM fractions from a water reservoir in the southwestern part of the USA.Materials and methods: About 50-60 L water samples were collected from Lake Pleasant (a water reservoir of Colorado River) and isolated and fractionated using a sequential isolation and fractionation procedure. DOM was firstly fractionated to the colloids and soluble permeate, then hydrophobic acids (HPO-A) and neutrals (HPO-N) plus amphiphilic acids (AMP-A) and neutrals (AMP-N) were fractionated using the resin-in-tandem procedure. Approximately 0.7 mg sample was dissolved in 250 μL methanol/water mixture (1:1, v/v) and diluted twice with 0.1 % (by volume) NH4OH (in 1:1 methanol/water, v/v) and measured by ESI-FTICR in negative ion mode.Results and discussion: In the m/z range of <700, among the sum of 4107 peaks, HPO-N contained the most assigned 1763 molecules and HPO-A, AMP-N, and AMP-A contained 971, 990, and 293, respectively. Acid fractions were relatively more oxygenated than the corresponding neutrals. Except for the major assigned CHO molecules, a high portion of heteroatom-containing molecules were assigned in the neutral fractions. Van Krevelen and Venn diagrams analyses showed significant molecular differentiation among the fractions. Among the assigned formulas, the Venn diagram indicated only a small portion (<4 %) of distinct formulas overlapped. S-containing molecules were efficiently ionized and identified in the neutrals. Some of the S1-containing compounds with high signal magnitudes are tentatively assigned to alkylbenzene sulfonates and their biodegradation and biotransformation derivatives indicating anthropogenic input on site.Conclusions: By using the XAD resin-in-tandem approach and FTICR-MS, numbers of DOM molecules in fractions were distinctly separated, accordingly the complexity of DOM was reduced. Furthermore, to a great extent, the compositions and structures of each fraction in the molecular level are remarkably different as evidenced by only small portion of molecules overlapping. [ABSTRACT FROM AUTHOR]

Soyasaponins are oleanene-type triterpenoid saponins, naturally occurring in many edible plants that have attracted a great deal of attention for their role in preventing chronic diseases. The aim of this study was to establish the distribution and the content of soyasaponins in 21 ecotypes of Fagioli di Sarconi beans (Phaseolus vulgaris, Leguminosae). High-performance reversed-phase liquid chromatography (RPLC) with positive electrospray ionization (ESI(+)) and Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS) in conjunction with infrared multiphoton dissociation (IRMPD) was applied for the unambiguous identification of soyasaponins Ba (m/z 959.5213, [C48H79O19]+), Bb (m/z 943.5273, [C48H79O18]+), Bd (m/z 957.5122, [C48H77O19]+), and Be (m/z 941.5166, [C48H77O18]+), which are the only commercially available reference standards. In addition, the several diagnostic product ions generated by IRMPD in the ICR-MS cell allowed us the putative identification of soyasaponins Bb' (m/z 797.4680, [C42H69O14]+), αg (m/z 1085.5544, [C54H85O22]+), βg (m/z 1069.5600, [C54H85O21]+), and γg (m/z 923.5009, [C48H75O17]+), establishing thus their membership in the soyasaponin group. Quantitative and semiquantitative analysis of identified soyasaponins were also performed by RPLC-ESI(+) FTICR-MS; the total concentration levels were found ranging from 83.6 ± 9.3 to 767 ± 37 mg/kg. In vitro hypoglycemic outcomes of four soyasaponin standards were evaluated; significant inhibitory activities were obtained with IC50 values ranging from 1.5 ± 0.1 to 2.3 ± 0.2 μg/mL and 12.0 ± 1.1 to 29.4 ± 1.4 μg/mL for α-glucosidase and α-amylase, respectively. This study represents the first detailed investigation on the antidiabetic activity of bioactive constituents found in Fagioli di Sarconi beans.The first detailed RPLC-ESI(+) FTICR-MS investigation of the qualitative and semiquantitative profile of soyasaponins, occurring in 21 ecotypes of Fagioli di Sarconi beans (P. vulgaris L.). [ABSTRACT FROM AUTHOR]

Dissolved organic matter (DOM) contained in lake sediments is a carbon source for many microbial degradation processes, including aerobic and anaerobic mineralization. During anaerobic degradation, DOM is partially consumed and transformed into new molecules while the greenhouse gases methane (CH 4 ) and carbon dioxide (CO 2 ) are produced. In this study, we used ultrahigh resolution mass spectrometry to trace differences in the composition of solid-phase extractable (PPL resin) pore water DOM (SPE-DOM) isolated from surface sediments of three boreal lakes before and after 40 days of anoxic incubation, with concomitant determination of CH 4 and CO 2 evolution. CH 4 and CO 2 production detected by gas chromatography varied considerably among replicates and accounted for fractions of ∼2–4 × 10 −4 of sedimentary organic carbon for CO 2 and ∼0.8–2.4 × 10 −5 for CH 4 . In contrast, the relative changes of key bulk parameters during incubation, such as relative proportions of molecular series, elemental ratios, average mass and unsaturation, were regularly in the percent range (1–3% for compounds decreasing and 4–10% for compounds increasing), i.e. several orders of magnitude higher than mineralization alone. Computation of the average carbon oxidation state in CHO molecules of lake pore water DOM revealed rather non-selective large scale transformations of organic matter during incubation, with depletion of highly oxidized and highly reduced CHO molecules, and formation of rather non-labile fulvic acid type molecules. In general, proportions of CHO compounds slightly decreased. Nearly saturated CHO and CHOS lipid-like substances declined during incubation: these rather commonplace molecules were less specific indicators of lake sediment alteration than the particular compounds, such as certain oxygenated aromatics and carboxyl-rich alicyclic acids (CRAM) found more abundant after incubation. There was a remarkable general increase in many CHNO compounds during incubation across all lakes. Differences in DOM transformation between lakes corresponded with lake size and water residence time. While in the small lake Svarttjärn, CRAM increased during incubation, lignin-and tannin-like compounds were enriched in the large lake Bisen, suggesting selective preservation of these rather non-labile aromatic compounds rather than recent synthesis. SPE-DOM after incubation may represent freshly synthesized compounds, leftover bulk DOM which is primarily composed of intrinsically refractory molecules and/or microbial metabolites which were not consumed in our experiments. In spite of a low fraction of the total DOM being mineralized to CO 2 and CH 4 , the more pronounced change in molecular DOM composition during the incubation indicates that diagenetic modification of organic matter can be substantial compared to complete mineralization. [ABSTRACT FROM AUTHOR]

This work reports the monitoring and assessment of naphthenic acids (NAs) in oil sands process-affected water (OSPW), Pleistocene channel aquifer groundwater (PLCA), and oil sands basal aquifer groundwater (OSBA) from an active oil sands development in Alberta, Canada, using ultra performance liquid chromatography time-of-flight mass spectrometry (UPLC-TOF-MS) analysis with internal standard (ISTD) and external standard (ESTD) calibration methods and Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) for compositional analysis. PLCA was collected at 45–51 m depth and OSBA was collected at 67–144 m depth. Results of O x −NA concentrations follow an order as OSPW > OSBA > PLCA, indicating that occurrences of NAs in OSBA were likely related to natural bitumen deposits instead of OSPW. Liquid-liquid extraction (LLE) was applied to avoid the matrix effect for the ESTD method. Reduced LLE efficiency accounted for the divergence of the ISTD and ESTD calibrated results for oxidized NAs. Principle component analysis results of O 2 and O 4 species could be employed for differentiation of water types, while classical NAs with C13−15 and Z (-4)−(-6) and aromatic O 2 −NAs with C16−18 and Z (-14)−(-16) could be measured as marker compounds to characterize water sources and potential temporal variations of samples, respectively. FTICR-MS results revealed that compositions of NA species varied greatly among OSPW, PLCA, and OSBA, because of NA transfer and transformation processes. This work contributed to the understanding of the concentration and composition of NAs in various types of water, and provided a useful combination of analytical and statistical tools for monitoring studies, in support of future safe discharge of treated OSPW. [ABSTRACT FROM AUTHOR]

The thermal maturity level impact on polar compounds was analyzed for a suite of hydrous pyrolysis (HP) products using a 7.2 Tesla LTQ FTICR-MS instrument. The sample suite was analyzed via electrospray ionization in the negative ion mode focusing on the polar compounds, i.e., nitrogen-, sulfur-, and oxygen-containing (NSO) compounds. The HP experiments were performed under isothermal conditions for 2 h at eleven different temperatures (300, 310, 320, 325, 330, 340, 345, 350, 355, 360 and 365 °C) to simulate the full range of thermal levels starting at early bitumen generation to maximum oil generation. The maturity suite samples consist of one immature bitumen (original sample), eleven expelled oil samples and eight residual bitumen samples. In general, O x compounds are destroyed by decarboxylation and dehydration with increasing maturity; sulfur compounds decrease; the aromaticity and degree of condensation increase; and steranoic and hopanoic acids decrease. Additionally, we investigated fluid retention properties comparing the carbon number distribution between the expelled oil and residual bitumen samples from each experiment. The maturity related changes of the acidic O 2 compounds in the expelled oil samples led us to create several regressions that we propose as new maturity parameters covering the full range of oil generation. [ABSTRACT FROM AUTHOR]