During 2017-2018, the National Seismic Hazard Model for the conterminous United States was updated as follows: (1) an updated seismicity catalog was incorporated, which includes new earthquakes that ...occurred from 2013 to 2017; (2) in the central and eastern United States (CEUS), new ground motion models were updated that incorporate updated median estimates, modified assessments of the associated epistemic uncertainties and aleatory variabilities, and new soil amplification factors; (3) in the western United States (WUS), amplified shaking estimates of long-period ground motions at sites overlying deep sedimentary basins in the Los Angeles, San Francisco, Seattle, and Salt Lake City areas were incorporated; and (4) in the conterminous United States, seismic hazard is calculated for 22 periods (from 0.01 to 10 s) and 8 uniform VS30 maps (ranging from 1500 to 150 m/s). We also include a description of updated computer codes and modeling details. Results show increased ground shaking in many (but not all) locations across the CEUS (up to ∼30%), as well as near the four urban areas overlying deep sedimentary basins in the WUS (up to ∼50%). Due to population growth and these increased hazard estimates, more people live or work in areas of high or moderate seismic hazard than ever before, leading to higher risk of undesirable consequences from forecasted future ground shaking.
The high-resolution and mass accuracy of Fourier transform mass spectrometry (FT-MS) has made it an increasingly popular technique for discerning the composition of soil, plant and aquatic samples ...containing complex mixtures of proteins, carbohydrates, lipids, lignins, hydrocarbons, phytochemicals and other compounds. Thus, there is a growing demand for informatics tools to analyze FT-MS data that will aid investigators seeking to understand the availability of carbon compounds to biotic and abiotic oxidation and to compare fundamental chemical properties of complex samples across groups. We present ftmsRanalysis, an R package which provides an extensive collection of data formatting and processing, filtering, visualization, and sample and group comparison functionalities. The package provides a suite of plotting methods and enables expedient, flexible and interactive visualization of complex datasets through functions which link to a powerful and interactive visualization user interface, Trelliscope. Example analysis using FT-MS data from a soil microbiology study demonstrates the core functionality of the package and highlights the capabilities for producing interactive visualizations.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Soil organic matter (SOM) dynamics are central to soil biogeochemistry and fertility. The retention of SOM is governed initially by interactions with minerals, which mediate the sorption of ...chemically diverse organic matter (OM) molecules via distinct surface areas and chemical functional group availabilities. Unifying principles of mineral-OM interactions remain elusive because of the multi-layered nature of biochemical-mineral interactions that contribute to soil aggregate formation and the heterogeneous nature of soils among ecosystems. This study sought to understand how soil mineralogy as well as nitrogen (N) enrichment regulate OM composition in grassland soils. Using a multi-site grassland experiment, we demonstrate that the composition of mineral-associated OM depended on the clay content and specific mineral composition in soils across the sites. With increasing abundance of ferrihydrite (Fh) across six different grassland locations, OM in the hydrophobic zone became more enriched in lipid- and protein-like compounds, whereas the kinetic zone OM became more enriched in lignin-like molecules. These relationships suggest that the persistence of various classes of OM in soils may depend on soil iron mineralogy and provide experimental evidence to support conceptual models of zonal mineral-OM associations. Experimental N addition disrupted the accumulation of protein-like molecules in the hydrophobic zone and the positive correlation of lignin-like molecules in the kinetic zone with Fh content, compared to unfertilized soils. These data suggest that mineralogy and clay content together influence the chemical composition not only of mineral-associated OM, but also of soluble compounds within the soil matrix. If these relationships are prevalent over larger spatial and temporal scales, they provide a foundation for understanding SOM cycling and persistence under a variety of environmental contexts.
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•Beyond clay content, mineralogy strongly controlled the composition of MAOM.•Ferrihydrite accumulated proteins and lipids in the hydrophobic zone of MAOM.•The mineral core influenced biochemical persistence of OM in the kinetic zone.•Nitrogen fertilization altered carbon chemistry and organo-mineral interactions.
Quantitative detection of RNA is important in molecular biology and clinical diagnostics. Nucleic acid sequence-based amplification (NASBA), a single-step method to amplify single-stranded RNA, is ...attractive for use in point-of-care (POC) diagnostics because it is an isothermal technique that is as sensitive as RT-PCR with a shorter reaction time. However, NASBA is limited in its ability to provide accurate quantitative information, such as viral load or RNA copy number. Here we test a digital format of NASBA (dNASBA) using a self-digitization (SD) chip platform, and apply it to quantifying HIV-1 RNA. We demonstrate that dNASBA is more sensitive and accurate than the real-time quantitative NASBA, and can be used to quantify HIV-1 RNA in plasma samples. Digital NASBA is thus a promising POC diagnostics tool for use in resource-limited settings.
Digital nucleic acid amplification and detection methods provide excellent sensitivity and specificity and allow absolute quantification of target nucleic acids. Isothermal methods such as digital ...loop-mediated isothermal amplification (digital LAMP) have potential for use in rapid disease diagnosis in low-resource settings due to their speed and lack of thermal cycling. We previously developed a self-digitization (SD) chip, a simple microfluidics device that automatically digitizes a sample into an array of nanoliter wells, for use in digital LAMP. In this work, we improve the SD chip design to increase sample loading efficiency, speed, and completeness, and test a range of well volumes and numbers. We demonstrate the diagnostic capability of this platform by applying it to quantifying human papillomavirus 18 gene.
Grassland soils store a substantial proportion of the global soil carbon (C) stock. The transformation of C in grassland soils with respect to chemical composition and persistence strongly regulate ...the predicted terrestrial-atmosphere C flux in global C biogeochemical cycling models. In addition, increasing atmospheric nitrogen (N) deposition alters C chemistry in grassland soils. However, there remains controversy about the importance of mineralogical versus biochemical preservation of soil C, as well as uncertainty regarding how grassland soil C chemistry responds to elevated N. This study used grassland soils with diverse soil organic matter (SOM) chemistries in an 8-month aerobic incubation experiment to evaluate whether the chemical composition of SOM converged across sites over time, and how SOM persistence responded to the N addition. This study demonstrates that over the course of incubation, the richness of labile compounds decreased in soils with less ferrihydrite content, whereas labile compounds were more persistent in ferrihydrite rich soils. In contrast, we found that the richness of more complex compounds increased over the incubation in most sites, independent of soil mineralogy. Moreover, we demonstrate the extent to which the diverse chemical composition of SOM converged among sites in response to microbial decomposition. N fertilization decreased soil respiration and inhibited the convergence of molecular composition across ecosystems by altering N demand for microbial metabolism and chemical interactions between minerals and organic molecules. This study provides original evidence that the decomposition and metabolism of labile organic molecules were largely regulated by soil mineralogy (physicochemical preservation), while the metabolism of more complex organic molecules was controlled by substrate complexity (biochemical preservation) independent to mineral-organic interactions. This study advanced our understanding of the dynamic biogeochemical cycling of C by unveiling that N addition dampened C respiration and diminished the convergence of SOM chemistry across diverse grassland ecosystems.
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•The decomposition of labile compounds is regulated by mineral association.•The metabolism of recalcitrant molecules is controlled by biochemical preservation.•Molecular composition of the persistent carbon pool is consistent across ecosystems.•N addition inhibits cumulative respiration and the convergence of SOM composition.
Prior to statistical analysis of mass spectrometry (MS) data, quality control (QC) of the identified biomolecule peak intensities is imperative for reducing process-based sources of variation and ...extreme biological outliers. Without this step, statistical results can be biased. Additionally, liquid chromatography–MS proteomics data present inherent challenges due to large amounts of missing data that require special consideration during statistical analysis. While a number of R packages exist to address these challenges individually, there is no single R package that addresses all of them. We present pmartR, an open-source R package, for QC (filtering and normalization), exploratory data analysis (EDA), visualization, and statistical analysis robust to missing data. Example analysis using proteomics data from a mouse study comparing smoke exposure to control demonstrates the core functionality of the package and highlights the capabilities for handling missing data. In particular, using a combined quantitative and qualitative statistical test, 19 proteins whose statistical significance would have been missed by a quantitative test alone were identified. The pmartR package provides a single software tool for QC, EDA, and statistical comparisons of MS data that is robust to missing data and includes numerous visualization capabilities.
The microbial and molecular characterization of the ectorhizosphere is an important step towards developing a more complete understanding of how the cultivation of biofuel crops can be undertaken in ...nutrient poor environments. The ectorhizosphere of Setaria is of particular interest because the plant component of this plant-microbe system is an important agricultural grain crop and a model for biofuel grasses. Importantly, Setaria lends itself to high throughput molecular studies. As such, we have identified important intra- and interspecific microbial and molecular differences in the ectorhizospheres of three geographically distant Setaria italica accessions and their wild ancestor S. viridis. All were grown in a nutrient-poor soil with and without nutrient addition. To assess the contrasting impact of nutrient deficiency observed for two S. italica accessions, we quantitatively evaluated differences in soil organic matter, microbial community, and metabolite profiles. Together, these measurements suggest that rhizosphere priming differs with Setaria accession, which comes from alterations in microbial community abundances, specifically Actinobacteria and Proteobacteria populations. When globally comparing the metabolomic response of Setaria to nutrient addition, plants produced distinctly different metabolic profiles in the leaves and roots. With nutrient addition, increases of nitrogen containing metabolites were significantly higher in plant leaves and roots along with significant increases in tyrosine derived alkaloids, serotonin, and synephrine. Glycerol was also found to be significantly increased in the leaves as well as the ectorhizosphere. These differences provide insight into how C4 grasses adapt to changing nutrient availability in soils or with contrasting fertilization schemas. Gained knowledge could then be utilized in plant enhancement and bioengineering efforts to produce plants with superior traits when grown in nutrient poor soils.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Rationale
Fourier transform ion cyclotron resonance mass spectrometry (FT‐ICR‐MS) is a preferred technique for analyzing complex organic mixtures. Currently, there is no consensus normalization ...approach, nor an objective method for selecting one, for quantitative analyses of FT‐ICR‐MS data. We investigate a method to evaluate and score the amount of bias various normalization approaches introduce into the data.
Methods
We evaluate the ability of the Statistical Procedure for the Analysis of Normalization Strategies (SPANS) to guide the selection of appropriate normalization approaches for two different FT‐ICR‐MS data sets. Furthermore, we test the robustness of SPANS results to changes in SPANS parameter values and assess the impact of using various normalization approaches on downstream statistical analyses.
Results
The normalization approach identified by SPANS differed for the two data sets. Normalization methods impacted the statistical significance of peaks differently, underscoring the importance of carefully evaluating potential methods. More consistent SPANS scores resulted when at least 120 significant peaks are used, where larger sets of peaks were obtained by increasing the p‐value threshold. Interestingly, we show that total sum scaling and highest peak normalization, used in previous studies, underperformed relative to SPANS‐recommended normalization approaches.
Conclusions
Although there is no single, best normalization method for all data sets, SPANS provides a mechanism to identify an appropriate normalization method for analyzing FT‐ICR‐MS data quantitatively. The number of peaks used in the background distributions of SPANS contributes more significantly to the reproducibility of results than the p‐value thresholds used to obtain those peaks.
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.
Understanding controls on soil organic matter (SOM) composition is necessary to identify land management strategies that improve soil health and increase carbon (C) storage. While it is known that >50% of SOM is of microbial origin (e.g., microbial residues, degradation products of plant material), the relationships between soil microorganisms and SOM chemistry are largely unknown. We address this knowledge gap by coupling microbial characteristics with detailed SOM chemistry. We found that soil texture has a greater impact than crops on microbial communities and SOM chemistry. Our results challenge the notion that switchgrass increases C accrual in surface soils of marginal lands.
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