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"Monroe, Ronald (Ronald D.)"
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What is electricity?
Introduces electricity, including how it is created, stored, and moved, and suggests related activities.
Book
A cross-sectional study to characterize local HIV-1 dynamics in Washington, DC using next-generation sequencing
Washington, DC continues to experience a generalized HIV-1 epidemic. We characterized the local phylodynamics of HIV-1 in DC using next-generation sequencing (NGS) data. Viral samples from 68 participants from 2016 through 2017 were sequenced and paired with epidemiological data. Phylogenetic and network inferences, drug resistant mutations (DRMs), subtypes and HIV-1 diversity estimations were completed. Haplotypes were reconstructed to infer transmission clusters. Phylodynamic inferences based on the HIV-1 polymerase (
pol
) and envelope genes (
env
) were compared. Higher HIV-1 diversity (n.s.) was seen in men who have sex with men, heterosexual, and male participants in DC. 54.0% of the participants contained at least one DRM. The 40–49 year-olds showed the highest prevalence of DRMs (22.9%). Phylogenetic analysis of
pol
and
env
sequences grouped 31.9–33.8% of the participants into clusters. HIV-TRACE grouped 2.9–12.8% of participants when using consensus sequences and 9.0–64.2% when using haplotypes. NGS allowed us to characterize the local phylodynamics of HIV-1 in DC more broadly and accurately, given a better representation of its diversity and dynamics. Reconstructed haplotypes provided novel and deeper phylodynamic insights, which led to networks linking a higher number of participants. Our understanding of the HIV-1 epidemic was expanded with the powerful coupling of HIV-1 NGS data with epidemiological data.
Journal Article
What are electrical circuits?
Introduces electric circuits, discussing the different types, their parts, and how they work.
Book
Mild cognitive impairment and postsurgical pain in older adults: A call for research
Both AD and MCI are linked to functional changes in the insula and anterior cingulate cortex, two key brain regions underlying the affective component of pain (i.e., pain unpleasantness). Since MCI and AD share similar alterations in pain-relevant brain regions, that MCI frequently progresses to AD, and that individuals with AD exhibit increased affective pain responsiveness on standardized psychophysical testing, we hypothesize that MCI may also be associated with altered pain experience (particularly affective pain) and opioid responses (via changes in the PAG). Results of a large clinical study indicate that ≈11 % of older adult surgical patients met criteria for MCI based on memory impairments identified during standardized cognitive assessment [1]. [...]MCI is sufficiently common that if it were found to exert significant pain-related effects, it would represent an important unrecognized comorbidity that must be addressed to insure optimal postoperative pain management. If findings observed in AD extend to MCI and people with MCI exhibit greater postsurgical pain and opioid use, the older adult population most often affected by MCI is likely to be particularly vulnerable given the potential for age-related impairments in opioid metabolism and increased risk for respiratory depression. [...]existing work indicates that both pain and opioid use may increase cognitive impairment. [...]bi-directional associations between cognitive status, pain, and opioid use in persons with MCI undergoing surgery are theoretically plausible.
Journal Article
Author Correction: A cross-sectional study to characterize local HIV-1 dynamics in Washington, DC using next-generation sequencing
An amendment to this paper has been published and can be accessed via a link at the top of the paper.An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Journal Article
Reproducible workflow for multiplexed deep-scale proteome and phosphoproteome analysis of tumor tissues by liquid chromatography–mass spectrometry
Here we present an optimized workflow for global proteome and phosphoproteome analysis of tissues or cell lines that uses isobaric tags (TMT (tandem mass tags)-10) for multiplexed analysis and relative quantification, and provides 3× higher throughput than iTRAQ (isobaric tags for absolute and relative quantification)-4-based methods with high intra- and inter-laboratory reproducibility. The workflow was systematically characterized and benchmarked across three independent laboratories using two distinct breast cancer subtypes from patient-derived xenograft models to enable assessment of proteome and phosphoproteome depth and quantitative reproducibility. Each plex consisted of ten samples, each being 300 μg of peptide derived from <50 mg of wet-weight tissue. Of the 10,000 proteins quantified per sample, we could distinguish 7,700 human proteins derived from tumor cells and 3100 mouse proteins derived from the surrounding stroma and blood. The maximum deviation across replicates and laboratories was <7%, and the inter-laboratory correlation for TMT ratio–based comparison of the two breast cancer subtypes was r > 0.88. The maximum deviation for the phosphoproteome coverage was <24% across laboratories, with an average of >37,000 quantified phosphosites per sample and differential quantification correlations of r > 0.72. The full procedure, including sample processing and data generation, can be completed within 10 d for ten tissue samples, and 100 samples can be analyzed in ~4 months using a single LC-MS/MS instrument. The high quality, depth, and reproducibility of the data obtained both within and across laboratories should enable new biological insights to be obtained from mass spectrometry-based proteomics analyses of cells and tissues together with proteogenomic data integration.
Journal Article
Advanced multi-modal mass spectrometry imaging reveals functional differences of placental villous compartments at microscale resolution
The placenta is a complex and heterogeneous organ that links the mother and fetus, playing a crucial role in nourishing and protecting the fetus throughout pregnancy. Integrative spatial multi-omics approaches can provide a systems-level understanding of molecular changes underlying the mechanisms leading to the histological variations of the placenta during healthy pregnancy and pregnancy complications. Herein, we advance our metabolome-informed proteome imaging (MIPI) workflow to include lipidomic imaging, while also expanding the molecular coverage of metabolomic imaging by incorporating on-tissue chemical derivatization (OTCD). The improved MIPI workflow advances biomedical investigations by leveraging state-of-the-art molecular imaging technologies. Lipidome imaging identifies molecular differences between two morphologically distinct compartments of a placental villous functional unit, syncytiotrophoblast (STB) and villous core. Next, our advanced metabolome imaging maps villous functional units with enriched metabolomic activities related to steroid and lipid metabolism, outlining distinct molecular distributions across morphologically different villous compartments. Complementary proteome imaging on these villous functional units reveals a plethora of fatty acid- and steroid-related enzymes uniquely distributed in STB and villous core compartments. Integration across our advanced MIPI imaging modalities enables the reconstruction of active biological pathways of molecular synthesis and maternal-fetal signaling across morphologically distinct placental villous compartments with micrometer-scale resolution.
Spatial multi-omics methodologies are essential for capturing the molecular heterogeneity of complex biological systems. In this study, the authors introduce a multi-omics imaging workflow capable of mapping metabolite-protein interactions with spatial specificity, enabling pathway-level resolution across distinct placental tissue microenvironments.
Journal Article
Enrichment and Broad Representation of Plant Biomass-Degrading Enzymes in the Specialized Hyphal Swellings of Leucoagaricus gongylophorus, the Fungal Symbiont of Leaf-Cutter Ants
Leaf-cutter ants are prolific and conspicuous constituents of Neotropical ecosystems that derive energy from specialized fungus gardens they cultivate using prodigious amounts of foliar biomass. The basidiomycetous cultivar of the ants, Leucoagaricus gongylophorus, produces specialized hyphal swellings called gongylidia that serve as the primary food source of ant colonies. Gongylidia also contain plant biomass-degrading enzymes that become concentrated in ant digestive tracts and are deposited within fecal droplets onto fresh foliar material as ants incorporate it into the fungus garden. Although the enzymes concentrated by L. gongylophorus within gongylidia are thought to be critical to the initial degradation of plant biomass, only a few enzymes present in these hyphal swellings have been identified. Here we use proteomic methods to identify proteins present in the gongylidia of three Atta cephalotes colonies. Our results demonstrate that a diverse but consistent set of enzymes is present in gongylidia, including numerous plant biomass-degrading enzymes likely involved in the degradation of polysaccharides, plant toxins, and proteins. Overall, gongylidia contained over three quarters of all biomass-degrading enzymes identified in the L. gongylophorus genome, demonstrating that the majority of the enzymes produced by this fungus for biomass breakdown are ingested by the ants. We also identify a set of 40 of these enzymes enriched in gongylidia compared to whole fungus garden samples, suggesting that certain enzymes may be particularly important in the initial degradation of foliar material. Our work sheds light on the complex interplay between leaf-cutter ants and their fungal symbiont that allows for the host insects to occupy an herbivorous niche by indirectly deriving energy from plant biomass.
Journal Article
Mapping microhabitats of lignocellulose decomposition by a microbial consortium
The leaf-cutter ant fungal garden ecosystem is a naturally evolved model system for efficient plant biomass degradation. Degradation processes mediated by the symbiotic fungus
Leucoagaricus gongylophorus
are difficult to characterize due to dynamic metabolisms and spatial complexity of the system. Herein, we performed microscale imaging across 12-µm-thick adjacent sections of
Atta cephalotes
fungal gardens and applied a metabolome-informed proteome imaging approach to map lignin degradation. This approach combines two spatial multiomics mass spectrometry modalities that enabled us to visualize colocalized metabolites and proteins across and through the fungal garden. Spatially profiled metabolites revealed an accumulation of lignin-related products, outlining morphologically unique lignin microhabitats. Metaproteomic analyses of these microhabitats revealed carbohydrate-degrading enzymes, indicating a prominent fungal role in lignocellulose decomposition. Integration of metabolome-informed proteome imaging data provides a comprehensive view of underlying biological pathways to inform our understanding of metabolic fungal pathways in plant matter degradation within the micrometer-scale environment.
Metabolome-informed proteome imaging provides a comprehensive view of underlying biological pathways within micrometer-scale microhabitats of the fungal garden, informing the understanding of metabolic fungal pathways in plant matter degradation.
Journal Article
Integrative Analysis of the Mitochondrial Proteome in Yeast
In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans.
Journal Article