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MARCH 31, 2020
Web Feature

Scientists Take Aim at the Coronavirus Toolkit

A PNNL scientist is studying the structures of the proteins on the surface of the novel coronavirus, using NMR spectroscopy to reveal information about the molecular toolkit that holds the keys to a vaccine or treatment.

Tracking the Behavior of a Uranium Plume

View of Columbia River

Field research coupled with three-dimensional modeling are used to predict how groundwater and river exchange influence a contaminant plume.

March 16, 2020
March 16, 2020
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The Science
A recent paper published in Water Resources Research found that the spatial variability of subsurface sediments, and seasonal fluctuations in a river’s water level, influences the behavior of a uranium contaminant plume, particularly in rivers influenced by dams.

The research team created a complex numerical model and ran a 5-year simulation of the exchange between surface water and groundwater in a portion of the Columbia River at the Hanford Site. Model accuracy was evaluated using detailed water sampling data from the site, distributed in space and time. Both the model and data from site samples showed that the uranium can travel via multiple paths of river water and groundwater exchange.

The Impact
Predicting and modeling the evolution of a contaminant plume in a river corridor subject to rising and falling water levels from upstream dam operations is challenging. Factors such as seasonal dam discharge variation, the permeability of surface and subsurface materials, and changes in water chemistry, make river corridors a complex environment to study. This study is one of a few that have used a highly detailed three-dimensional modeling approach to simulate the migration of contaminants as influenced by the hydrologic exchanges between surface and subsurface waters at a large spatial scale. High-resolution monitoring, to ground truth the model’s accuracy, provided researchers a robust evaluation of the model’s predictive capabilities. Ultimately, the methods and findings in this study provide a foundation for designing future modeling and monitoring research to assist in environmental management and decision making.

Heatmap image of plume
Study site showing a) the uranium plume within Hanford’s 300 area, along the Columbia River, and b) the groundwater-surface water study site and water topography. Wells sampled in this study are marked with red circles.

Summary
A team of scientists led by John Zachara of Pacific Northwest National Laboratory examined the impact of river water and groundwater exchange in relation to a uranium contaminant plume migration at Hanford, Washington. The goal was to develop and improve the predictive understanding of hydrologic exchange flows and their role in changing river corridor biogeochemistry.

The team used an innovative combination of field sampling and three-dimensional mathematical models to investigate how river stage variation over seasons and subsurface hydrogeology interact to influence subsurface contaminant migration. In this work, the authors note that there are very few studies that model solute transport or plume behavior during dynamic hydrologic exchange in large river corridors, and that the model they developed can be applied to other, similar riverine systems.

According to both their model and data, river water exchange with groundwater in large, gravel-bed river corridors may create a wide interaction zone, which is different from most headwater systems. Water level variations in dam-regulated river corridors lead to changing flow directions, velocities, and sediment compositions, that influence contaminant plume behavior. The residence time and transport distance of intruded river water is controlled by both river stage and subsurface hydrogeologic features.

Funded by the Department of Energy’s Biological and Environmental Research (BER) program, this work addresses DOE’s mission to improve the predictive understanding of how watershed systems respond to environmental perturbations caused by changes in water availability/quality, land use/vegetation cover, and inorganic element/contaminant loading. Researchers used the DOE-funded NERSC, National Energy Research Scientific Computing Center, user facility in their model development.

Contact
John Zachara, Pacific Northwest National Laboratory, john.zachara@pnnl.gov

Funding
This research was supported by the U.S. Department of Energy (DOE), Office of Biological and Environmental Research (BER), as part of the Subsurface Biogeochemical Research Scientific Focus Area (SFA) at Pacific Northwest National Laboratory (PNNL).

J.M. Zachara, C. Xingyuan, S. Xuehang, P. Shuai, C. Murray, C. T. Resch. “Kilometer‐scale hydrologic exchange flows in a gravel‐bed river corridor and their implications to solute migration.” Water Resources Research, e02851-18 (2020). DOI: 10.1029/2019WR025258

Microbial diversity influences nitrogen cycling in rivers

Image of streambed

Seasonal changes affect microbiome communities, genes, and subsurface biogeochemical pathways differently

March 4, 2020
March 4, 2020
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The Science
DOE researchers investigated the role of microbial genetic diversity in two major subsurface biogeochemical processes: nitrification and denitrification. Results show that across different seasons only a few microbe species, namely Nitrosoarchaeum, carry out nitrification functions—demonstrating high resistance to environmental change. However, denitrification genes, which are more broadly distributed in the community, displayed a variety of diversity patterns and abundance dynamics—demonstrating greater microbial interactions as conditions change.

Nitrogen cycling in hyporheic zone
Figure shows nitrogen transformations in the hyporheic zone, where a vast microbiome community influences nutrient cycling. Upper layers, closer to the riverbed contain more oxygen and organic matter. Under these conditions nitrification (orange arrows) occurs. Microbes transform the nitrogen from organic matter through a variety of steps and ultimately deplete the oxygen. As oxygen depletes, denitrification (blue arrows) further transforms nitrogen, resulting in an electron acceptor for catabolism of organic matter.

The Impact
There is little research connecting microbiomes at the genetic level to hydrobiogeochemical modeling. This research helps broaden collective knowledge for a better understanding of the pathways affected by environmental changes. For example, under extreme environmental conditions an entire biochemical pathway could be altered or eliminated if a single step has low genetic diversity such that its loss could not be replaced.

Summary
The Pacific Northwest National Laboratory research team, led by Bill Nelson, found that major environmental processes—specifically nitrification and denitrification—are maintained through a variety of diversity strategies. Historically, the bulk of biogeochemical research has focused on microbial communities at the organismal level. But this research focused on the importance of genetic distribution and diversity.

In their recent PLoS ONE paper, the researchers discuss the roles microbes play in ecological functions; the novelty of the genetic makeup of these microbes; and future research opportunities to determine which organisms are genetically expressing nitrogen cycling functions.

The novelty of this study comes from examining the temporal dynamics of diversity at the gene level. To evaluate all genes in the nitrification and denitrification pathways, novel Hidden Markov Models (HMMs) were developed that can recognize the broad diversity found in environmental samples. They found that while different environmental conditions impair microbiome growth and the gene expression of some populations, at the same time, it can stimulate others. High biodiversity at the organism or genetic level creates more resiliency, and the microbiome community can respond more rapidly to environmental changes.

Contact
Bill Nelson, Pacific Northwest National Laboratory, William.Nelson@pnnl.gov

Funding
This research was supported by the U.S. Department of Energy (DOE), Office of Biological and Environmental Research (BER), as part of the Subsurface Biogeochemical Research Scientific Focus Area (SFA) at Pacific Northwest National Laboratory (PNNL).

W.C. Nelson, E.B. Graham, A.R. Crump, S.J. Fansler, E.V. Arntzen, D.W. Kennedy, J.C. Stegen, “Distinct temporal diversity profiles for nitrogen cycling genes in a hyporheic microbiome”. PLoS ONE 15(1) e0228165 (2020). [DOI: 10.1371/ journal.pone.0228165]

Peeking Into the Lives of Soil Microbiomes

Photo of plant in soil

SoilBox provides in-depth imaging and characterization of soil microbial communities in their native environments.

February 28, 2020
February 25, 2020
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The Science
To better characterize the vast diversity of soil microbes and their interactions, DOE researchers developed a high-tech simulated soil core called SoilBox. This 16.7-centimeter-deep box allows researchers to visualize soil microbes’ complex interactions using different imaging methods and facilitating, for the first time, visualization of the soil microbiome’s organization and community metabolism. Furthermore, SoilBox provides a tool for researchers to observe how soil microbial communities respond to environmental changes and perturbations.

The Impact
The complexity of soil makes spatial imaging of soil microbial communities challenging. Using SoilBox, researchers can now visualize the diversity and metabolic

Graphic of Soilbox
SoilBox allows researchers to characterize and image soil microbiome dynamics at a level of resolution not previously available. This especially applies to how soil microbes respond to environmental shifts.

landscape of the soil microbiome under different environmental conditions, such as soil moisture and temperature. Understanding the basic biology of the soil microbiome is necessary for understanding how native soil systems respond to environmental perturbations such as drought, lack of nutrients, and fire. 

Summary
Soil-dwelling microbes are key players in the overall health of soil ecosystems, performing critical functions like carbon and nutrient cycling. The interplay between the soil microbiome and the soil it inhabits is a dynamic relationship heavily influenced by factors such as soil acidity, organic content, and temperature. The size and distribution of soil particles also affects many soil characteristics, adding to the already complex challenge of accurately describing structure-function relationships of soil microbial communities.

To address the difficulties of studying the soil microbiome in its native state and at a microscale resolution, a team of researchers from Pacific Northwest National Laboratory, led by Arunima Bhattacharjee and Chris Anderton, developed SoilBox. This system represents a soil ecosystem by simulating an ~12-cm-deep soil core; several windows facilitate molecular and optical imaging measurements that are crucial to understanding the nuanced interactions between the soil microbiome and its environment. This novel imaging capability allows scientists to study the dynamic landscape of soil microbial communities as they relate to environmental changes, including nutrient cycling.

This work overcomes the challenge of visualizing the diversity of soil microbial communities in the complex and ever-changing environment of soil. SoilBox will be used in the near future to investigate soil microbial community dynamics.

Contact
Chris Anderton, Pacific Northwest National Laboratory, christopher.anderton@pnnl.gov

Funding
This research was supported by the Department of Energy (DOE) Office of Biological and Environmental Research (BER) and is a contribution of the Scientific Focus Area "Phenotypic response of the soil microbiome to environmental perturbations." Pacific Northwest National Laboratory (PNNL) is operated for the DOE by Battelle Memorial Institute under Contract DE-AC05-76RLO1830. A portion of the research was performed using EMSL, the Environmental Molecular Sciences Laboratory, a DOE Office of Science User Facility sponsored by BER and located at PNNL.

A. Bhattacharjee et al.,“Visualizing microbial community dynamics via a controllable soil environment.” mSystems 5, 1:e00645-19 (2020). https://doi.org/10.1128/mSystems.00645-19.

Creating better models to predict subsurface water flow and transport

river soil

New framework improves the predictions of subsurface sediment permeability

February 19, 2020
February 17, 2020
Highlight

The Science
Co-authors of a paper in Water Resources Research led by PNNL researchers developed a new iterative data assimilation framework to more accurately describe the permeability of subsurface sediments in numerical models when using facies, a system that classifies dissimilar sediments into distinct geological units that share important features of interest to modelers. The iterative framework applies data from field observations and experiments to inform the delineation of facies at the start of each model run. Further refinements are achieved at each iteration through the application of statistical constraints that maintain geologic continuity among adjacent locations.

Distribution of Facies
Spatial distribution of three facies (red, yellow and blue colors) in a 2D vertical cross section of a 3D case. Figures show the new method provides a more accurate and continuous estimation of facies distribution compared to the conventional method. White colors in the figures are bore samples and black dots are the conditioning points selected by the new method.

The Impact
Spatial distribution of three facies (red, yellow and blue colors) in a 2D vertical cross section of a 3D case. Figures show the new method provides a more accurate and continuous estimation of facies distribution compared to the conventional method. White colors in the figures are bore samples and black dots are the conditioning points selected by the new method.

More realistic numerical representations of the permeability of subsurface sediments lead to improved predictions of groundwater flow and the concentration of constituents that are transported with the flow. The data assimilation framework can also be applied to estimate other subsurface properties from field measurements, or from data from other systems such as watersheds, as long as they can be categorized into a few discrete representative units.

Summary
Observational data on subsurface permeability is limited for most watersheds because of the impracticality of digging enough boreholes or wells to capture the heterogeneous nature of the subsurface environment. To solve for this limitation, researchers have widely adopted approaches that estimate permeability from field experiments such as a) measuring how water levels at a cluster of wells change when water is pumped at a nearby well, or b) monitoring how quickly a tracer released at one well reaches other wells in the aquifer. The U.S. Department of Energy’s Hanford 300 Area Integrated Field Research Challenge site, for example, is well characterized from data assimilation methods that were used to understand the long-term persistence of nuclear fuel fabrication wastes disposal from 1943 to 1975.

The use of a facies approach to segment the subsurface reduces complexity in numerical models by grouping heterogeneous sediments into distinct homogenous units defined by hydraulic, physical and or chemical properties. A major difficulty with existing facies-based approaches in numerical models is that each facies is treated as its own, independent unit. Therefore, these models fail to capture the spatial continuity of subsurface sediments. The authors of this paper developed a framework that maintains continuity between neighboring facies in numerical models and thus better reflects true subsurface geology, and thereby groundwater movement. The improvements come from an iterative data assimilation approach that incorporates direct and indirect data about subsurface permeability gathered from field observations and experiments at the start of each model run as well as the application of statistical constraints about subsurface geology. The data assimilation and statistical constraint steps are re-imposed for each iteration, leading to refined facies delineation. This framework reduces uncertainty about the spatial distribution of sediment types in the subsurface, which results in more accurate predictions of groundwater flow and constituent transport.

The authors evaluated the performance of the new framework on a two-dimensional, two-facies model and a three-dimensional, three-facies model of DOE’s well-characterized Hanford 300 Area that were conceptualized from borehole and field tracer experiments. The results of the research shows that the framework can identify facies spatial patterns and reproduce tracer breakthrough curves with much improved accuracy over facies-based approaches that lack spatial continuity constraints. With additional data, the authors say that the framework can also be used to categorize biogeochemical reactive units in an aquifer.

Contact
Xingyuan Chen, Earth Scientist, Xingyuan.Chen@pnnl.gov

Funding
Funding for this research came from DOE Office of Science BER, PNNL Subsurface Biogeochemical Research SFA.

Song, X., Chen, X., Ye, M., Dai, Z., Hammond, G., And Zachara, J.M. (2019). Delineating facies spatial distribution by integrating ensemble data assimilation and Indicator Geostatistics with level-set transformation. Water Resources Research, 55. https://doi.org/10.1029/2018WR023262

March 9, 2019
JANUARY 21, 2020
Web Feature

Forensic Proteomics: Beyond DNA Profiling

A new book by PNNL biochemist Erick Merkley details forensic proteomics, a technique that directly analyzes proteins in unknown samples, in pursuit of making proteomics a widespread forensic method when DNA is missing or ambiguous.
NOVEMBER 5, 2019
Web Feature

Magnesium Takes ShAPE™

Two forms of magnesium material were processed into tubing using PNNL’s Shear Assisted Processing and Extrusion™ technology. Both materials were found to have quite similar and improved properties—even though they began vastly different.