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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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66 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Toward Revealing Microcystin Distribution in Mouse Liver Tissue Using MALDI-MS Imaging

Cyanotoxins can be found in water and air during cyanobacterial harmful algal blooms (cHABs) in lakes and rivers. Therefore, it is very important to monitor their potential uptake by animals and humans as well as their health effects and distribution in affected organs. Herein, the distribution of hepatotoxic peptide microcystin-LR (MC-LR) is investigated in liver tissues of mice gavaged with this most common MC congener. Preliminary matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) imaging experiments performed using a non-automated MALDI matrix deposition device and a MALDI-time-of-flight (TOF) mass spectrometer yielded ambiguous results in terms of MC-LR distribution in liver samples obtained from MC-LR-gavaged mice. The tissue preparation for MALDI-MS imaging was improved by using an automated sprayer for matrix deposition, and liver sections were imaged using an Nd:YAG MALDI laser coupled to a 15 Tesla Fourier-transform ion cyclotron resonance (FT-ICR)-mass spectrometer. MALDI-FT-ICR-MS imaging provided unambiguous detection of protonated MC-LR (calculated m/z 995.5560, z = +1) and the sodium adduct of MC-LR (m/z 1017.5380, z = +1) in liver sections from gavaged mice with great mass accuracy and ultra-high mass resolution. Since both covalently bound and free MC-LR can be found in liver of mice exposed to this toxin, the present results indicate that the distribution of free microcystins in tissue sections from affected organs, such as liver, can be monitored with high-resolution MALDI-MS imaging.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Robotic Planning under Uncertainty in Spatiotemporal Environments in Expeditionary Science

In the expeditionary sciences, spatiotemporally varying environments -- hydrothermal plumes, algal blooms, lava flows, or animal migrations -- are ubiquitous. Mobile robots are uniquely well-suited to study these dynamic, mesoscale natural environments. We formalize expeditionary science as a sequential decision-making problem, modeled using the language of partially-observable Markov decision processes (POMDPs). Solving the expeditionary science POMDP under real-world constraints requires efficient probabilistic modeling and decision-making in problems with complex dynamics and observational models. Previous work in informative path planning, adaptive sampling, and experimental design have shown compelling results, largely in static environments, using data-driven models and information-based rewards. However, these methodologies do not trivially extend to expeditionary science in spatiotemporal environments: they generally do not make use of scientific knowledge such as equations of state dynamics, they focus on information gathering as opposed to scientific task execution, and they make use of decision-making approaches that scale poorly to large, continuous problems with long planning horizons and real-time operational constraints. In this work, we discuss these and other challenges related to probabilistic modeling and decision-making in expeditionary science, and present some of our preliminary work that addresses these gaps. We ground our results in a real expeditionary science deployment of an autonomous underwater vehicle (AUV) in the deep ocean for hydrothermal vent discovery and characterization. Our concluding thoughts highlight remaining work to be done, and the challenges that merit consideration by the reinforcement learning and decision-making community.

Preston, Victoria↗
DOE OSTI2024

Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region

The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.

Climate Change↗
DOE OSTI2024

Evaluating SWAT + model uncertainties for human and natural outcomes: Application in a Great Lakes agricultural watershed

Nutrient exports from agricultural lands in the Great Lakes Region pose significant threats to water quality and ecological health through eutrophication, hypoxia, and harmful algal blooms. Climate change and agricultural adaptation practices complicate future nutrient loading due to intensified hydrologic cycles and land use decisions. Our research focuses on evaluating the Soil and Water Assessment Tool (SWAT) plus model parametric uncertainties for human and natural outcomes across different scales. These factors are integral to ensuring a balance between productive agricultural practices and maintaining the health of watershed hydrology. However, uncertainties in modeling such complex interactions pose significant challenges, limiting our ability to precisely determine critical factors that influence crop yield and soil moisture. Our analysis employs Sobol global sensitivity analysis to evaluate first-order, second order, and total-order indices for SWAT crop growth parameter, ensuring comprehensive assessment of individual and interactive effects on model outputs. The objective is to identify the parameters that significantly affect model outputs for crop yield and soil moisture and improve our understanding of their interactions at the basin and hydrological response unit (HRU) scale. Our case study, the Portage River Watershed, which drains into Lake Erie, is chosen to better capture finer scale interactions crucial for predicting nutrient loading under future climate scenarios. This foundational work is aimed at setting the stage for the future development of an agent-based model (ABM). The ABM model would incorporate SWAT outputs to dynamically simulate decision-making processes.

Bunyon, Enock↗
DOE OSTI2024

Detection of Anatoxins in Human Urine by Liquid Chromatography Triple Quadrupole Mass Spectrometry and ELISA

Harmful cyanobacterial blooms are becoming more common and persistent around the world. When in bloom, various cyanobacterial strains can produce anatoxins in high concentrations, which, unlike other cyanobacterial toxins, may be present in clear water. Potential human and animal exposures to anatoxins occur mainly through unintentional ingestion of contaminated algal mats and water. To address this public health threat, we developed and validated an LC-MS/MS method to detect anatoxins in human urine to confirm exposures. Pooled urine was fortified with anatoxin-a and dihydroanatoxin at concentrations from 10.0 to 500 ng/mL to create calibrators and quality control samples. Samples were diluted with isotopically labeled anatoxin and solvent prior to LC-MS/MS analysis. This method can accurately quantitate anatoxin-a with inter- and intraday accuracies ranging from 98.5 to 103% and relative standard deviations < 15%, which is within analytical guidelines for mass spectrometry methods. Additionally, this method qualitatively detects a common degradation product of anatoxin, dihydroanatoxin, above 10 ng/mL. We also evaluated a commercial anatoxin-a ELISA kit for potential diagnostic use; however, numerous false positives were detected from unexposed individual human urine samples. In conclusion, we have developed a method to detect anatoxins precisely and accurately in urine samples, addressing a public health area of concern, which can be applied to future exposure events.

urine↗
DOE OSTI2024

Microbiome processing of organic nitrogen input supports growth and cyanotoxin production of Microcystis aeruginosa cultures

Abstract Nutrient-induced blooms of the globally abundant freshwater toxic cyanobacterium Microcystis cause worldwide public and ecosystem health concerns. The response of Microcystis growth and toxin production to new and recycled nitrogen (N) inputs and the impact of heterotrophic bacteria in the Microcystis phycosphere on these processes are not well understood. Here, using microbiome transplant experiments, cyanotoxin analysis, and nanometer-scale stable isotope probing to measure N incorporation and exchange at single cell resolution, we monitored the growth, cyanotoxin production, and microbiome community structure of several Microcystis strains grown on amino acids or proteins as the sole N source. We demonstrate that the type of organic N available shaped the microbial community associated with Microcystis, and external organic N input led to decreased bacterial colonization of Microcystis colonies. Our data also suggest that certain Microcystis strains could directly uptake amino acids, but with lower rates than heterotrophic bacteria. Toxin analysis showed that biomass-specific microcystin production was not impacted by N source (i.e. nitrate, amino acids, or protein) but rather by total N availability. Single-cell isotope incorporation revealed that some bacterial communities competed with Microcystis for organic N, but other communities promoted increased N uptake by Microcystis, likely through ammonification or organic N modification. Our laboratory culture data suggest that organic N input could support Microcystis blooms and toxin production in nature, and Microcystis-associated microbial communities likely play critical roles in this process by influencing cyanobacterial succession through either decreasing (via competition) or increasing (via biotransformation) N availability, especially under inorganic N scarcity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Molecular Insights into Novel Struvite–Hydrogel Composites for Simultaneous Ammonia and Phosphate Removal

Struvite (NH 4 MgPO 4 ·6H 2 O) mineralization is an effective technique for removing ammonium and phosphate species from wastewater. However, its wider use faces obstacles because of the copresence of various pollutants in wastewater and the additional requirement for magnesium to achieve proper supersaturation conditions. To address these challenges, this study developed novel mineral–hydrogel composites that can remove ammonium and phosphate simultaneously via heterogeneous struvite and calcium phosphate (CaP) mineralization in hydrogel matrices. The composites include in situ formed struvite and CaP mineral seeds, decreasing the nucleation energy barrier of struvite and CaP formation and promoting their heterogeneous nucleation kinetics even under undersaturation conditions in bulk solution. The dual struvite and CaP seeded composites can simultaneously reduce the ammonium and total phosphate concentrations up to 60% (26.3 mg of N/g) and 91% (9.54 mg of P/g), respectively. Furthermore, the average particle sizes in composites were increased from 6.12 to 14.8 nm after wastewater treatment. Moreover, various ions commonly existing in wastewater did not significantly interfere with the removal of ammonium and phosphate. Thus, these new mineral–hydrogel composites can provide an innovative way to lower nutrient levels before discharge to streams. Moreover, encapsulating ammonium and phosphate in mineral-hydrogel composites enables their upcycling in agricultural or biorefinery applications.

Cations↗
DOE OSTI2025

A bloom of a single bacterium shapes the microbiome during outdoor diatom cultivation collapse

Algae-dominated ecosystems are fundamentally influenced by their microbiome. We lack information on the identity and function of bacteria that specialize in consuming algal-derived dissolved organic matter in high algal density ecosystems such as outdoor algal ponds used for biofuel production. Here, we describe the metagenomic and metaproteomic signatures of a single bacterial strain that bloomed during a population-wide crash of the diatom, Phaeodactylum tricornutum, grown in outdoor ponds. 16S rRNA gene data indicated that a single Kordia sp. strain (family Flavobacteriaceae) contributed up to 93% of the bacterial community during P. tricornutum demise. Kordia sp. expressed proteins linked to microbial antagonism and biopolymer breakdown, which likely contributed to its dominance over other microbial taxa during diatom demise. Analysis of accompanying downstream microbiota (primarily of the Rhodobacteraceae family) provided evidence that cross-feeding may be a pathway supporting microbial diversity during diatom demise. In situ and laboratory data with a different strain suggested that Kordia was a primary degrader of biopolymers during algal demise, and co-occurring Rhodobacteraceae exploited degradation molecules for carbon. An analysis of 30 Rhodobacteraceae metagenome assembled genomes suggested that algal pond Rhodobacteraceae commonly harbored pathways to use diverse carbon and energy sources, including carbon monoxide, which may have contributed to the prevalence of this taxonomic group within the ponds. These observations further constrain the roles of functionally distinct heterotrophic bacteria in algal microbiomes, demonstrating how a single dominant bacterium, specialized in processing senescing or dead algal biomass, shapes the microbial community of outdoor algal biofuel ponds.

Kordia↗
DOE OSTI2019

In marine Bacteroidetes the bulk of glycan degradation during algae blooms is mediated by few clades using a restricted set of genes

We investigated Bacteroidetes during spring algae blooms in the southern North Sea in 2010–2012 using a time series of 38 deeply sequenced metagenomes. Initial partitioning yielded 6455 bins, from which we extracted 3101 metagenome-assembled genomes (MAGs) including 1286 Bacteroidetes MAGs covering ~120 mostly uncultivated species. We identified 13 dominant, recurrent Bacteroidetes clades carrying a restricted set of conserved polysaccharide utilization loci (PULs) that likely mediate the bulk of bacteroidetal algal polysaccharide degradation. The majority of PULs were predicted to target the diatom storage polysaccharide laminarin, alpha-glucans, alpha-mannose-rich substrates, and sulfated xylans. Metaproteomics at 14 selected points in time revealed expression of SusC-like proteins from PULs targeting all of these substrates. Analyses of abundant key players and their PUL repertoires over time furthermore suggested that fewer and simpler polysaccharides dominated early bloom stages, and that more complex polysaccharides became available as blooms progressed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Contrary effects of phytoplankton Chlorella vulgaris and its exudates on mercury methylation by iron- and sulfate-reducing bacteria

Mercury (Hg) is a pervasive environmental pollutant and poses serious health concerns as inorganic Hg(II) can be converted to the neurotoxin methylmercury (MeHg), which bioaccumulates and biomagnifies in food webs. Phytoplankton, representing the base of aquatic food webs, can take up Hg(II) and influence MeHg production, but currently little is known about how and to what extent phytoplankton may impact Hg(II) methylation by itself or by methylating bacteria it harbors. This study investigated whether some species of phytoplankton could produce MeHg and how the live or dead phytoplankton cells and excreted algal organic matter (AOM) impact Hg(II) methylation by several known methylators, including iron-reducing bacteria (FeRB), Geobacter anodireducens SD-1 and Geobacter sulfurreducens PCA, and the sulfate-reducing bacterium (SRB) Desulfovibrio desulfuricans ND132 (or Pseudodesulfovibrio mercurii). Here our results indicate that, among the 4 phytoplankton species studied, none were capable of methylating Hg(II). However, the presence of phytoplankton cells (either live or dead) from Chlorella vulgaris (CV) generally inhibited Hg(II) methylation by FeRB but substantially enhanced methylation by SRB D. desulfuricans ND132. Enhanced methylation was attributed in part to CV-excreted AOM, which increased Hg(II) complexation and methylation by ND132 cells. In contrast, inhibition of methylation by FeRB was attributed to these bacteria incapable of competing with phytoplankton for Hg(II) binding and uptake. These observations suggest that phytoplankton could play different roles in affecting Hg(II) methylation by the two groups of anaerobic bacteria, FeRB and SRB, and thus shed additional light on how phytoplankton blooms may modulate MeHg production and bioaccumulation in the aquatic environment.

59 BASIC BIOLOGICAL SCIENCES↗