Publications by authors named "Vanessa L Paurus"

Article Synopsis
  • Biological nitrogen fixation by microbes like Burkholderia vietnamiensis can enhance nitrogen availability in non-nodulating plants, which was studied using poplar trees as a model.
  • The study found dynamic nitrogen-fixing activity in colonies of the bacteria, with only about 11% actively expressing the nifH gene, indicating uneven expression among genetically identical cells.
  • Collaborative methods including imaging and metabolomics revealed that nifH expression is localized to the root elongation zone of poplar, highlighting unique interactions between the endophyte and roots.
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Microglia, the innate immune cells of the central nervous system, have been genetically implicated in multiple neurodegenerative diseases. We previously mapped the genetic regulation of gene expression and mRNA splicing in human microglia, identifying several loci where common genetic variants in microglia-specific regulatory elements explain disease risk loci identified by GWAS. However, identifying genetic effects on splicing has been challenging due to the use of short sequencing reads to identify causal isoforms.

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  • Metabolomics offers insights into small molecules and biological processes related to human, animal, plant, and environmental health, but the usefulness of this data relies on accurately identifying metabolites.
  • There is considerable confusion surrounding which spectral similarity (SS) score to use for identifying compounds in mass spectrometry, leading to inconsistencies and potential reproducibility issues when integrating data across various domains.
  • The study evaluates 66 similarity metrics and finds that certain families (Inner Product, Correlative, and Intersection) perform better for metabolite identification, providing guidance for researchers to enhance the reliability and standardization of identification workflows in metabolomics.
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Background: Physiological and biochemical processes across tissues of the body are regulated in response to the high demands of intense physical activity in several occupations, such as firefighting, law enforcement, military, and sports. A better understanding of such processes can ultimately help improve human performance and prevent illnesses in the work environment.

Methods: To study regulatory processes in intense physical activity simulating real-life conditions, we performed a multi-omics analysis of three biofluids (blood plasma, urine, and saliva) collected from 11 wildland firefighters before and after a 45 min, intense exercise regimen.

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Building mechanistic models of kinase-driven signaling pathways requires quantitative measurements of protein phosphorylation across physiologically relevant conditions, but this is rarely done because of the insensitivity of traditional technologies. By using a multiplexed deep phosphoproteome profiling workflow, we were able to generate a deep phosphoproteomics dataset of the EGFR-MAPK pathway in non-transformed MCF10A cells across physiological ligand concentrations with a time resolution of <12 min and in the presence and absence of multiple kinase inhibitors. An improved phosphosite mapping technique allowed us to reliably identify >46,000 phosphorylation sites on >6600 proteins, of which >4500 sites from 2110 proteins displayed a >2-fold increase in phosphorylation in response to EGF.

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As metabolomics grows into a high-throughput and high demand research field, current metrics for the identification of small molecules in gas chromatography-mass spectrometry (GC-MS) still require manual verification. Though steps have been taken to improve scoring metrics by combining spectral similarity (SS) and retention index (RI), the problem persists. A large body of literature has analyzed and refined SS scores, but few studies have explicitly studied improvements to RI scores.

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The ability to reliably identify small molecules (e.g., metabolites) is key toward driving scientific advancement in metabolomics.

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Red alder (Alnus rubra Bong.) is an ecologically significant and important fast-growing commercial tree species native to western coastal and riparian regions of North America, having highly desirable wood, pigment, and medicinal properties. We have sequenced the genome of a rapidly growing clone.

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Article Synopsis
  • The study investigates the COVID-19 infection mechanisms by analyzing blood plasma from uninfected individuals and patients with mild and severe cases of SARS-CoV-2.
  • Severe patients displayed elevated levels of pulmonary surfactant, while mild cases showed increased levels of the enzyme CNDP1, suggesting different response mechanisms to the virus.
  • Elevated L-cystine and enzyme activity related to glutathione metabolism were observed in both groups, indicating potential roles for neutrophil extracellular traps (NETs) and CNDP1 in disease severity and immune response management.
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Background: Microbiomes contribute to multiple ecosystem services by transforming organic matter in the soil. Extreme shifts in the environment, such as drying-rewetting cycles during drought, can impact the microbial metabolism of organic matter by altering microbial physiology and function. These physiological responses are mediated in part by lipids that are responsible for regulating interactions between cells and the environment.

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Successful establishment of pregnancy requires adhesion of an embryo to the endometrium and subsequent invasion into the maternal tissue. Abnormalities in this critical process of implantation and placentation lead to many pregnancy complications. Here we present a microenigneered system to model a complex sequence of orchestrated multicellular events that plays an essential role in early pregnancy.

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Thiol-based post-translational modifications (PTMs) play a key role in redox-dependent regulation and signaling. Functional cysteine (Cys) sites serve as redox switches, regulated through multiple types of PTMs. Herein, we aim to characterize the complexity of thiol PTMs at the proteome level through the establishment of a direct detection workflow.

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The confident identification of metabolites and xenobiotics in biological and environmental studies is an analytical challenge due to their immense dynamic range, vast chemical space and structural diversity. Ion mobility spectrometry (IMS) is widely used for small molecule analyses since it can separate isomeric species and be easily coupled with front end separations and mass spectrometry for multidimensional characterizations. However, to date IMS metabolomic and exposomic studies have been limited by an inadequate number of accurate collision cross section (CCS) values for small molecules, causing features to be detected but not confidently identified.

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