Biology subjects

Couvillion, S. P.

Publications and source records attributed to Couvillion, S. P..

12 recordsLinked to original sources

bioRxiv2025

Endophytes induce systemic spatial reprogramming of metabolism in poplar roots under drought

Beneficial endophytes help plants thrive in challenging environments by altering their hosts metabolism, but how these cellular scale metabolic changes propagate to the systems biology scale is unknown. In this work, we employed a high-resolution chemical imaging approach to map metabolic changes at the root zone and cell type levels and found that a 9-strain consortium of beneficial endophytes differentially altered the metabolome of droughted root tissues according to cell types and locations along the root system architecture. Using machine learning (ML) models, we identified root metabolites and exudates that have predictive power over treatment class and could therefore be used as systems biology indicators of drought and endophyte inoculation status. We calculated the correlation between each endophyte and metabolite and found that this relationship shifts under drought conditions, indicating the dynamic role endophytes play in a plants microbiome and metabolism in response to environmental changes.

plant biology↗

bioRxiv2024

Environmental matrix and moisture are key determinants of microbial phenotypes expressed in a reduced complexity soil-analog

Soil moisture and porosity regulate microbial metabolism by influencing factors such as redox conditions, substrate availability, and soil connectivity. However, the inherent biological, chemical, and physical heterogeneity of soil complicates laboratory investigations into microbial phenotypes that mediate community metabolism. This difficulty arises from challenges in accurately representing the soil environment and in establishing a tractable microbial community that limits confounding variables. To address these challenges in our investigation of community metabolism, we use a reduced-complexity microbial consortium grown in a soil analog using a glass-bead matrix amended with chitin. Long-read and short-read metagenomes, metatranscriptomes, metaproteomes, and metabolomes were analyzed to test the effects of soil structure and moisture on chitin degradation. Our soil structure analog system greatly altered microbial expression profiles compared to the liquid-only incubations, emphasizing the importance of incorporating environmental parameters, like pores and surfaces, for understanding microbial phenotypes relevant to soil ecosystems. These changes were mainly driven by differences in overall expression of chitin-degrading Streptomyces species and stress-tolerant Ensifer. Our findings suggest that the success of Ensifer in a structured environment is likely related to its ability to repurpose carbon via the glyoxylate shunt while potentially using polyhydroxyalkanoate granules as a C source. We also identified traits like motility, stress resistance, and biofilm formation that underlie the degradation of chitin across our treatments and inform how they may ultimately alter carbon use efficiency. Together our results demonstrate that community functions like decomposition are sensitive to environmental conditions and more complex than the multi-enzyme pathways involved in depolymerization. ImportanceSoil moisture and porosity are critical mediators of microbial metabolism by influencing factors such as redox conditions, substrate availability, and soil connectivity. However, identifying how microbial community metabolism shifts in response to varying levels of moisture and porosity remains a challenging frontier. This difficulty arises from challenges in accurately representing the soil environment and in establishing tractable microbial communities that limit confounding variables. Moreover, inferring phenotypes based on "key" genes often fails to predict complex phenotypes that arise from cellular interactions. Here, we establish a tractably complex microbial community in a soil analog system amended with chitin and leverage it to understand how microorganisms respond to changes in porosity and moisture. By using genome-resolved metagenomics, metatranscriptomics, and metaproteomics, we report on the microbial lifestyle strategies that underpin changes in community expression like carbon conservation, biofilm production, and stress response.

microbiology↗

bioRxiv2024

Metabolomic and transcriptomic remodeling of bone marrow myeloid cells in response to maternal obesity

Maternal obesity puts the offspring at high risk of developing obesity and cardio-metabolic diseases in adulthood. Here, using a mouse model of maternal high-fat diet (HFD)-induced obesity, we show that whole body fat content of the offspring of HFD-fed mothers (Off-HFD) increases significantly from very early age when compared to the offspring regular diet-fed mothers (Off-RD). We have previously shown significant metabolic and immune perturbations in the bone marrow of newly-weaned offspring of obese mothers. Therefore, we hypothesized that lipid metabolism is altered in the bone marrow Off-HFD in newly-weaned offspring of obese mothers when compared to the Off-RD. To test this hypothesis, we investigated the lipidomic profile of bone marrow cells collected from three-week-old offspring of regular and high fat diet-fed mothers. Diacylgycerols (DAGs), triacylglycerols (TAGs), sphingolipids and phospholipids, including plasmalogen, and lysophospholipids were remarkably different between the groups, independent of fetal sex. Levels of cholesteryl esters were significantly decreased in offspring of obese mothers, suggesting reduced delivery of cholesterol to bone marrow cells. This was accompanied by age-dependent progression of mitochondrial dysfunction in bone marrow cells. We subsequently isolated CD11b+ myeloid cells from three-week-old mice and conducted metabolomics, lipidomics, and transcriptomics analyses. The lipidomic profiles of these bone marrow myeloid cells were largely similar to that seen in bone marrow cells and included increases in DAGs and phospholipids alongside decreased TAGs, except for long-chain TAGs, which were significantly increased. Our data also revealed significant sex-dependent changes in amino acids and metabolites related to energy metabolism. Transcriptomic analysis revealed altered expression of genes related to major immune pathways including macrophage alternative activation, B-cell receptor signaling, TGF{beta} signaling, and communication between the innate and adaptive immune systems. All told, this study revealed lipidomic, metabolomic, and gene expression abnormalities in bone marrow cells broadly, and in bone marrow myeloid cells particularly, in the newly-weaned offspring of obese mothers, which might at least partially explain the progression of metabolic and cardiovascular diseases in their adulthood.

molecular biology↗

bioRxiv2024

Associations between SARS-CoV-2 Infection or COVID-19 Vaccination and Human Milk Composition: A Multi-Omics Approach

The risk of contracting SARS-CoV-2 via human milk-feeding is virtually non-existent. Adverse effects of COVID-19 vaccination for lactating individuals are not different from the general population, and no evidence has been found that their infants exhibit adverse effects. Yet, there remains substantial hesitation among this population globally regarding the safety of these vaccines. Herein we aimed to determine if compositional changes in milk occur following infection or vaccination, including any evidence of vaccine components. Using an extensive multi-omics approach, we found that compared to unvaccinated individuals SARS-CoV-2 infection was associated with significant compositional differences in 67 proteins, 385 lipids, and 13 metabolites. In contrast, COVID-19 vaccination was not associated with any changes in lipids or metabolites, although it was associated with changes in 13 or fewer proteins. Compositional changes in milk differed by vaccine. Changes following vaccination were greatest after 1-6 hours for the mRNA-based Moderna vaccine (8 changed proteins), 3 days for the mRNA-based Pfizer (4 changed proteins), and adenovirus-based Johnson and Johnson (13 changed proteins) vaccines. Proteins that changed after both natural infection and Johnson and Johnson vaccine were associated mainly with systemic inflammatory responses. In addition, no vaccine components were detected in any milk sample. Together, our data provide evidence of only minimal changes in milk composition due to COVID-19 vaccination, with much greater changes after natural SARS-CoV-2 infection. IMPORTANCEThe impact of the observed changes in global milk composition on infant health remain unknown. These findings emphasize the importance of vaccinating the lactating population against COVID-19, as compositional changes in milk were found to be far less evident after vaccination compared to SARS-CoV-2 infection. Importantly, vaccine components were not detected in milk after vaccination.

molecular biology↗

bioRxiv2024

Unveiling lipid chemodiversity in root exudates: A comprehensive characterizaton of the exudate metabo-lipidome in Tall Wheatgrass

The rhizosphere, where plant roots meet soil, is a hub of biogeochemical activity with ecosystem impacts on carbon stocks. Root derived carbon has been found to contribute more to soil carbon stocks than aboveground litter. Nonetheless, the molecular chemodiversity of root exudates remains poorly understood due to limited characterization and annotation. Here our goal was to discover the molecular chemodiversity of metabolites and lipids in root exudates to advance our understanding of plant root inputs belowground. We worked with mature, field-grown tall wheatgrass (Thinopyrum ponticum) and optimized exudate collection protocols to enable the capture of non-polar lipids in addition to polar and semi-polar metabolites. Rates of carbon input via hydrophobic exudates were approximately double that of aqueous exudates and carbon/nitrogen ratios were markedly higher in hydrophobic compared to aqueous exudates, emphasizing the importance of lipids, due to their high carbon content. To maximize molecular coverage of exudate chemodiversity, we used liquid chromatography coupled tandem mass-spectrometry for paired untargeted metabolomics and lipidomics or metabo-lipidomics. We substantially increased the characterization of exudate chemodiversity by employing both tandem mass spectral library searching and deep learning-based chemical class assignment. Notably, in this unprecedented characterization of intact lipids in root exudates, we discovered a diverse variety of lipids, including substantial levels of triacylglycerols ([~]19 g/g fresh root per min), fatty acyls, sphingolipids, sterol lipids, and glycerophospholipids. Comparison of the root exudate and tissue lipidomes revealed minimum glycerophospholipids in exudates, suggesting the exudate protocol did not extract lipids from root cell membranes.

plant biology↗

bioRxiv2023

Fungal organic acid uptake of mineral derived K is dependent on distance from carbon hotspot

Fungal mineral weathering processes regulate the bioavailability of inorganic nutrients from mineral surfaces to organic matter and increase the bioavailable fraction of nutrients. Fungal mineral weathering strategies can be classified as biomechanical (direct) or biochemical (indirect). In the case of fungal uptake of mineral nutrients through indirect weathering, it is widely hypothesized that uptake of mineral derived nutrients occurs through organic acid chelation, but such processes have not been directly visualized. This is in part due to challenges in probing the complex and heterogeneous soil environment. Here, using an epoxy-based mineral doped soil micromodel platform that we developed, which mimics soil mineralogy and structure, it permitted us to visualize and spatially probe the molecular mechanisms of mineral weathering. Mass spectrometry imaging revealed differences in the distribution of fungal exudates, citric acid and tartaric acid, on the soil micromodels in presence of minerals. Citric acid was detected closer to the nutrient rich inoculation point, whereas tartaric acid was highly abundant away from inoculation point. This suggested that the organic acid exuded by the fungi depended on the proximity from the carbon rich organic substrate at the point of inoculation. Using a combination of X-ray fluorescence and X-ray near edge structure analysis, we identified citric acid- and tartaric acid-bound K within fungal hyphae networks grown in the presence of minerals. Combined our results provide direct evidence that fungi uptake and transport mineral derived nutrient organic acid chelation. The results of this study provided unprecedented visualization of fungal weathering of soil minerals and hyphal K+ transport, while resolving the indirect weathering mechanism of fungal K uptake from mineral interfaces.

ecology↗

bioRxiv2021

Multi-omics profiling of Earth's biomes reveals that microbial and metabolite composition are shaped by the environment

As our understanding of the structure and diversity of the microbial world grows, interpreting its function is of critical interest for understanding and managing the many systems microbes influence. Despite advances in sequencing, lack of standardization challenges comparisons among studies that could provide insight into the structure and function of microbial communities across multiple habitats on a planetary scale. Technical variation among distinct studies without proper standardization of approaches prevents robust meta-analysis. Here, we present a multi-omics, meta-analysis of a novel, diverse set of microbial community samples collected for the Earth Microbiome Project. We include amplicon (16S, 18S, ITS) and shotgun metagenomic sequence data, and untargeted metabolomics data (liquid chromatography-tandem mass spectrometry and gas chromatography mass spectrometry), centering our description on relationships and co-occurrences of microbially-related metabolites and microbial taxa across environments. Standardized protocols and analytical methods for characterizing microbial communities, including assessment of molecular diversity using untargeted metabolomics, facilitate identification of shared microbial and metabolite features, permitting us to explore diversity at extraordinary scale. In addition to a reference database for metagenomic and metabolomic data, we provide a framework for incorporating additional studies, enabling the expansion of existing knowledge in the form of a community resource that will become more valuable with time. To provide examples of applying this database, we outline important ecological questions that can be addressed, and test the hypotheses that every microbe and metabolite is everywhere, but the environment selects. Our results show that metabolite diversity exhibits turnover and nestedness related to both microbial communities and the environment. The relative abundances of microbially-related metabolites vary and co-occur with specific microbial consortia in a habitat-specific manner, and highlight the power of certain chemistry - in particular terpenoids - in distinguishing Earths environments.

ecology↗

bioRxiv2020

Comparative molecular and immunoregulatory analysis of extracellular vesicles from Candida albicans and Candida auris.

Candida auris is a recently described multidrug-resistant pathogenic fungus that is increasingly responsible for healthcare associated outbreaks across the world. Bloodstream infections of this fungus cause death in up to 70% of the cases. Aggravating this scenario, C. auris disease-promoting mechanisms are poorly understood. Fungi release extracellular vesicles (EVs) carrying a broad range of molecules including proteins, lipids, carbohydrates, pigments, and RNA, many of which are virulence factors. Here, we carried out a comparative molecular characterization of C. auris and C. albicans EVs and evaluated their capacity to modulate effector mechanisms of host immune defense. Using proteomics, lipidomics, and transcriptomics, we found that C. auris released EVs with payloads that were strikingly different from EVs released by C. albicans. EVs released by C. auris potentiated the adhesion of this yeast to an epithelial cell monolayer. C. auris EVs also induced the expression of surface activation markers and cytokines by bone marrow-derived dendritic cells. Altogether, our findings show distinct profiles and properties of EVs released by C. auris and by C. albicans, and highlight the potential contribution of C. auris EVs to the pathogenesis of this emerging pathogen.

microbiology↗

bioRxiv2020

A lipid metabolic map of the pathogenic fungus Histoplasma capsulatum

Lipids play a fundamental role in fungal cell biology, being essential cell membrane components and major targets of antifungal drugs. A deeper knowledge of lipid metabolism is key for developing new drugs and a better understanding of fungal pathogenesis. Here we built a comprehensive map of the Histoplasma capsulatum lipid metabolic pathway by incorporating proteomic and lipidomic analyses. We performed genetic complementation and overexpression of H. capsulatum genes in Saccharomyces cerevisiae to validate reactions identified in the map and to determine enzymes responsible for catalyzing orphan reactions. The map led to the identification of both the fatty acid desaturation and the sphingolipid biosynthesis pathways as targets for drug development. We found that the sphingolipid biosynthesis inhibitor myriocin, the fatty acid desaturase inhibitor thiocarlide and the fatty acid analog 10-thiastearic acid inhibit H. capsulatum growth in nanomolar to low micromolar concentrations. These compounds also reduced the intracellular infection in an alveolar macrophage cell line. Overall, this lipid metabolic map revealed pathways that can be targeted for drug development.

microbiology↗

bioRxiv2020

Algorithmic Learning for Auto-deconvolution of GC-MS Data to Enable Molecular Networking within GNPS.

Gas chromatography-mass spectrometry (GC-MS) represents an analytical technique with significant practical societal impact. Spectral deconvolution is an essential step for interpreting GC-MS data. No public GC-MS repositories that also enable repository-scale analysis exist, in part because deconvolution requires significant user input. We therefore engineered a scalable machine learning workflow for the Global Natural Product Social Molecular Networking (GNPS) analysis platform to enable the mass spectrometry community to store, process, share, annotate, compare, and perform molecular networking of GC-MS data. The workflow performs auto-deconvolution of compound fragmentation patterns via unsupervised non-negative matrix factorization, using a Fast Fourier Transform-based strategy to overcome scalability limitations. We introduce a "balance score" that quantifies the reproducibility of fragmentation patterns across all samples. We demonstrate the utility of the platform with breathomics analysis applied to the early detection of oesophago-gastric cancer, and by creating the first molecular spatial map of the human volatilome.

bioinformatics↗

bioRxiv2019

Candida auris: multi-omics signature of an emerging and multidrug-resistant pathogen

Candida auris is a recently described pathogenic fungus that is causing invasive outbreaks on all continents. The fungus is of high concern given the numbers of multidrug-resistant strains that have been isolated in distinct sites across the globe. The fact that its diagnosis is still problematic suggests that the spreading of the pathogen remains underestimated. Notably, the molecular mechanisms of virulence and antifungal resistance employed by this new species are largely unknown. In the present work, we compared two clinical isolates of C. auris with distinct drug susceptibility profiles and a Candida albicans reference strain using a multi-omics approach. Our results show that, despite the distinct drug-resistance profile, both C. auris strains appear to be very similar, albeit with a few notable differences. However, when compared to C. albicans both C. auris strains have major differences regarding their carbon utilization and downstream lipid and protein content, suggesting a multi-factorial mechanism of drug resistance. The molecular profile displayed by C. auris helps to explain the antifungal resistance and virulence phenotypes of this new emerging pathogen. ImportanceCandida auris was firstly described in Japan in 2009 and has now been the cause of significant outbreaks across the globe. The high number of isolates that are resistant to one or more antifungals, as well as the high mortality rates from patients with bloodstream infections, has caught the attention of the medical mycology, infectious disease and public health communities to this pathogenic fungus. In the current work, we performed a broad multi-omics approach on two clinical isolates isolated in New York, the most affected area in the USA and found that the omic profile of C. auris differs significantly from C. albicans. Besides our insights into C. auris carbon utilization and lipid and protein content, we believe that the availability of these data will enhance our ability to combat this rapidly emerging pathogenic yeast.

microbiology↗

bioRxiv2019

MetFish: A Metabolomics Platform for Studying Microbial Communities in Chemically Extreme Environments

Metabolites have essential roles in microbial communities, including as mediators of nutrient and energy exchange, cell-to-cell communication, and antibiosis. However, detecting and quantifying metabolites and other chemicals in samples having extremes in salt or mineral content using liquid chromatography-mass spectrometry (LC-MS)-based methods remains a significant challenge. Here we report a facile method based on in situ chemical derivatization followed by extraction for analysis of metabolites and other chemicals in hypersaline samples, enabling for the first time direct LC-MS-based exo-metabolomics analysis in sample matrices containing up to 2 molar total dissolved salts. The method, MetFish, is applicable to molecules containing amine, carboxylic acid, carbonyl, or hydroxyl functional groups, and can be integrated into either targeted or untargeted analysis pipelines. In targeted analyses, MetFish provided limits of quantification as low as 1 nM, broad linear dynamic ranges (up to 5-6 orders of magnitude) with excellent linearity, and low median inter-day reproducibility (e.g. 2.6%). MetFish was successfully applied in targeted and untargeted exo-metabolomics analyses of microbial consortia, quantifying amino acid dynamics in the exo-metabolome during community succession; in situ in a native prairie soil, whose exo-metabolome was isolated using a hypersaline extraction; and in input and produced fluids from a hydraulically fractured well, identifying dramatic changes in the exo-metabolome over time in the well.

microbiology↗