Biology subjects

Louie, K. B.

Publications and source records attributed to Louie, K. B..

10 recordsLinked to original sources

bioRxiv2026

The Sorghum Lipid Database (SoLD): population-scale lipidomics linking environmental and genetic variation in the Sorghum Association Panel

Sorghum (Sorghum bicolor) is a climate-resilient crop whose acclimation to nutrient limitation and low temperature likely involves extensive lipidome reconfiguration. Lipids are key membrane components, carbon and energy stores, and mediators of stress signaling, yet population-scale lipidomics data for sorghum are limited. We present the Sorghum Lipid Database (SoLD), a curated lipidomics resource from the Sorghum Association Panel grown under two field regimes: (i) a nutrient-sufficient with usual planting date environment (control) and (ii) a low-input treatment with reduced nitrogen and phosphorus, earlier planting, and no application of insecticides, herbicides, or pesticides (low-input). Using high-resolution LC-MS, we quantified 244 lipid species and detected broad, largely conserved compositional shifts across field trials. However, there were four major low-input-associated lipid signatures relative to control: (i) depletion of sulfoquinovosyldiacylglycerol, (ii) triacylglycerol enrichment, (iii) phospholipid redistribution centered on phosphatidylserine, and (iv) coordinated lysophospholipid remodeling, reflected in altered lysophosphatidylcholine-to-lysophosphatidylethanolamine ratios. Analyses of lipid chemical space and lipid ontology enrichment supported these compositional changes. GWAS of lipid species, class sums, and class ratios revealed recurrent, environment-specific loci. Control-associated loci were enriched for genes involved in lipid and isoprenoid metabolism, developmental regulation, and cell-wall biosynthesis and modification. Low-input-associated loci were enriched for genes involved in nutrient-stress signaling, cell-wall remodeling, defense, developmental control, and cold-related barrier formation and proteostasis. Thus, SoLD provides a framework connecting sorghum lipid diversity with environmental and genetic variation. All information regarding the database and the experiment is freely accessible through a Shiny application: https://nirwan.shinyapps.io/SAP-Lipidomics-Database/. The database enables users to move from lipid-class to individual molecular species and associated candidate loci, for hypothesis generation, comparative analyses, and prioritization of targets for functional validation.

plant biology↗

bioRxiv2026

What microbes want: exploring microbial substrate preferences with the Web of Microbes Agent

Understanding and predicting bacterial substrate preferences has broad utility from microbial interactions to selecting prebiotics. Isolate exometabolite profiling directly measures which compounds a given microbe utilizes from an array of metabolites in the environment. However, modeling, mining, and integrating these data are challenging. Here, we introduce a Bayesian Personalized Ranking (BPR) model applied to substrate preferences which we find learns to rank compounds by a given microbes preference. It was found to outperform the other ranking models (AUC = 0.93), proved robust to ablation, showed strong within-genus isolate pairs correlation (Spearman rank = 0.78) and predictive ability for new data. BPR was then used to create the Web of Microbes (WoM) Agent by integrating it with the Phydon growth model and Large Language Model (LLM) for autonomous orchestration tool calling and analysis. The WoM Agent accurately predicted substrate consumption by existing strain grown on a novel medium and correctly identified bacteria enriched in soil metabolite spike-in experiments. Additionally, the WoM Agent can use autonomous reasoning including to predict substrates that will selectively promote the growth of one clade of bacteria over another including helping interpret results and suggest new hypotheses and experiments. We anticipate broad applications in microbial cultivation, microbiome engineering, and environmental microbiology, with the agents capabilities further extensible through the integration of additional tools and use of rapidly improving LLMs.

systems biology↗

bioRxiv2025

Transcriptional and metabolic stasis define desiccation-induced dormancy in a soil bacterium until water vapor initiates resuscitation.

Microbes inhabiting soils experience periodic water deprivation. The effects of desiccation on DNA, protein, and membrane integrity are well-described. However, the effects of drying and rehydration on the composition of cellular RNA and metabolites are still poorly understood. Here, we describe how slow drying and rehydration with water vapor influence the composition of RNAs and metabolites in a soil Arthrobacter. While drying reduced cultivability relative to hydrated controls, water vapor rehydration fully restored it. Ribosomal RNA proportions remained constant throughout all treatments, and mRNA profiles showed stable composition during desiccation--changing only during transitions into and out of desiccation-induced dormancy. Six transcriptional modules displayed distinct expression patterns in desiccated-rehydrated samples relative to hydrated controls, including desiccation-rehydration responsive and rehydration-specific profiles. Targeted intracellular metabolomics revealed similarly static profiles during desiccation, with a cluster of ribonucleosides and nucleobases increasing in response to desiccation and returning to baseline levels upon rehydration with water vapor. These findings demonstrate that both mRNA and metabolite profiles remain essentially frozen in desiccated Arthrobacter, with dynamic changes occurring only during state transitions. These results have important implications in environments with frequent drying cycles where stable mRNA in dormant cells combined with intracellular RNA recycling may obscure interpretations of RNA-based environmental analyses that use RNA as a marker of microbial activity. Our results suggest that RNA-based activity assessments in periodically dry environments require careful consideration of dormancy-associated molecular preservation. SIGNIFICANCE STATEMENTMetabolic activity quickly ceases in drying bacteria as they enter desiccation-induced dormancy. We show mRNA and metabolite profiles were variable during drying and rewetting but did not change while desiccated. Additionally, water vapor stimulated the shift from the static to active state when exiting desiccation-induced dormancy. These shifts coincided with increased cultivability, indicating water vapor resuscitated dry cells. Because RNAs are transient, labile molecules that are turned over rapidly in growing bacteria, the presence of RNA in the environment is used as a marker for microbial activity. Our research shows this assumption may not hold for desiccated cells, indicating reliance on RNA as a marker of activity in environments that experience drying may obscure estimates of in situ microbial activity.

microbiology↗

bioRxiv2024

Reduced methane emissions in transgenic rice genotypes are associated with altered rhizosphere microbial hydrogen cycling

Rice paddies contribute substantially to atmospheric methane (CH4) and these emissions are expected to increase as the need to feed the human population grows. Here, we show that two independent rice genotypes overexpressing genes for PLANT PEPTIDES CONTAINING SULFATED TYROSINE (PSY) reduced cumulative CH4 emissions by 38% (PSY1) and 58% (PSY2) over the growth period compared with controls. Genome-resolved metatranscriptomic data from rhizosphere soils reveal lower ratios of gene activities for CH4 production versus consumption, decrease in activity of H2-producing genes, and increase in bacterial H2 oxidation pathways in the PSY genotypes. Metabolic modeling using metagenomic and metabolomic data predicts elevated levels of H2 oxidation and suppressed H2 production in the PSY rhizosphere. The H2-oxidizing bacteria have more genes for utilization of gluconeogenic acids than H2-producing counterparts, and their activities were likely stimulated by the observed enrichment of gluconeogenic acids (mostly amino acids) in PSY root exudates. Together these results suggest that decreased CH4 emission is due to the reduction of H2 available for hydrogenotrophic methanogenesis. The combination of rice phenotypic characterization, microbiome multi-omic analysis, and metabolic modeling described here provides a powerful strategy to discover the mechanisms by which specific plant genotypes can alter biogeochemical cycles to reduce CH4 emissions.

microbiology↗

bioRxiv2024

Community-wide interactions sustain life in geothermal spring habitats

We investigated an alga-dominated geothermal spring community in Yellowstone National Park, USA. Our goal was to determine how cells cope with abiotic stressors during diurnal sampling that spanned over two orders of magnitude in solar irradiance. We report a community level response to toxic metal resistance and energy cycling that spans the three domains of life. Arsenic detoxification is accomplished via complementary gene expression by different lineages. Photosynthesis is dominated by Cyanidioschyzon, with the mixotroph, Galdieria, relegated to nighttime heterotrophy. Many key functions, including the cell cycle, are strongly regulated by diurnal light fluctuations. These results demonstrate that biotic interactions are highly structured in extreme habitats. We suggest this was also the case on the early Earth when geothermal springs were cradles of microbial life, prior to the origin of eukaryotes.

evolutionary biology↗

bioRxiv2024

Insights into the role of root exudates in bacteriophage infection dynamics

Bacteriophages impact soil bacteria through lysis, altering the availability of organic carbon and plant nutrients. However, the magnitude of nutrient uptake by plants from lysed bacteria remains unknown, partly because this process is challenging to investigate in the field. In this study, we extend ecosystem fabrication (EcoFAB 2.0) approaches to study plant-bacteria-phage interactions by comparing the impact of phage-lysed and uninfected 15N-labeled bacterial necromass on plant nitrogen acquisition and rhizosphere exometabolites composition. We show that grass Brachypodium distachyon derives some nitrogen from amino acids in uninfected Pseudomonas putida necromass but not from virocell necromass. Additionally, the bacterial necromass elicits the formation of rhizosphere exometabolites, some of which (guanosine), alongside tested aromatic acids (p-coumaric and benzoic acid), show distinct effects on bacteriophage-induced lysis when tested in vitro. The study highlights the dynamic feedback between bacterial necromass and plants and suggests that root exudate metabolites can impact bacteriophage infection dynamics.

plant biology↗

bioRxiv2024

Rendering the metabolic wiring powering wetland soil methane production

Accounting for only 8% of Earths land coverage, freshwater wetlands remain the foremost contributor to global methane emissions. Yet the microorganisms and processes underlying methane emissions from wetland soils remain poorly understood. Over a five-year period, we surveyed the microbial membership and in situ methane measurements from over 700 samples in one of the most prolific methane-emitting wetlands in the United States. We constructed a catalog of 2,502 metagenome-assembled genomes (MAGs), with more than half of the 70 bacterial and archaeal phyla sampled containing novel lineages. Integration of these data with 133 soil metatranscriptomes provided a genome-resolved view of the biogeochemical specialization and versatility expressed over wetland soil spatial and temporal gradients. Centimeter-scale depth differences best explained patterns of microbial community structure and transcribed functionalities, even more so than land coverage or temporal information. Moreover, while extended flooding restructured soil redox, this perturbation failed to reconfigure the transcriptional profiles of methane cycling microorganisms, contrasting with theoretical expected responses to hydrological perturbations. Co-expression analyses coupled to depth resolved methane measurements exposed the metabolisms and trophic structures most predictive of methane hotspots. Mapping the spatiotemporal transcriptional patterns on this compendium of biogeochemically classified soil derived genomes begins to untangle the microbial carbon, energy, and nutrient processing contributing to wetland methane production. ImportanceSoil microbial ecology is increasingly recognized as essential to climate mitigation, but realizing its full potential requires shifting from static genome inventories to dynamic assessments of microbial activity. This study shows that methane-cycling microbes exhibit stable, depth-stratified expression patterns, even in response to major redox and flooding shifts, undermining assumptions that water-table manipulations common in wetland management can alone reduce methanogenesis. Instead, methane cycling is shaped by spatially organized, transcriptionally active networks involving not only methanogens but also methanotrophs, fermenters, and iron reducers. These findings expose the limitations of genome-only models and highlight the need for soil diagnostics that capture in situ activity. Together, we provide a foundation for developing activity-based microbiome tools, embedding microbial functions into Earth system models, and designing interventions that move beyond "single lever" strategies and instead work with the structure and dynamics of microbial communities as complex, layered systems.

microbiology↗

bioRxiv2023

Powdery mildew infection induces a non-canonical route to storage lipid formation at the expense of host thylakoid lipids to fuel its spore production

Powdery mildews are obligate biotrophic fungi that manipulate plant metabolism to supply lipids, particularly during fungal asexual reproduction when fungal lipid demand is extensive. The mechanism for host response to fungal lipid demand has not been resolved. We found storage lipids, triacylglycerols (TAGs), increase by 3.5-fold in powdery mildew-infected tissue. In addition, lipid bodies, not observable in uninfected mature leaves, are present in both cytosol and chloroplasts at the infection site. This is concurrent with decreased thylakoid membrane lipids and thylakoid disassembly. Together, these findings indicate that the powdery mildew induces localized thylakoid membrane degradation to promote storage lipid formation. Genetic analyses show the canonical ER pathway for TAG synthesis does not support powdery mildew spore production. Instead, Arabidopsis DIACYLGLYCEROL ACYLTRANSFERASE 3 (DGAT3), shown to be chloroplast-localized and to be largely responsible for powdery mildew-induced chloroplast TAGs, promotes fungal asexual reproduction. Powdery mildew-induced leaf TAGs are enriched in thylakoid associated fatty acids, which are also present in the produced spores. This research provides new insights on obligate biotrophy and plant lipid metabolism plasticity and function. Furthermore, by understanding how photosynthetically active leaves can be converted into TAG producers, more sustainable and environmentally benign plant oil production could be facilitated.

plant biology↗

bioRxiv2021

GNPS Dashboard: Collaborative Analysis of Mass Spectrometry Data in the Web Browser

Access to web-based platforms has enabled scientists to perform research remotely. A critical aspect of mass spectrometry data analysis is the inspection, analysis, and visualization of the raw data to validate data quality and confirm statistical observations. We developed the GNPS Dashboard, a web-based data visualization tool, to facilitate synchronous collaborative inspection, visualization, and analysis of private and public mass spectrometry data remotely.

bioinformatics↗

bioRxiv2017

MAGI: A Bayesian-like method for metabolite, annotation, and gene integration

Metabolomics is a widely used technology for obtaining direct measures of metabolic activities from diverse biological systems. However, ambiguous metabolite identifications are a common challenge and biochemical interpretation is often limited by incomplete and inaccurate genome-based predictions of enzyme activities (i.e. gene annotations). Metabolite, Annotation, and Gene Integration (MAGI) generates a metabolite-gene association score using a biochemical reaction network. This is calculated by a method that emphasizes consensus between metabolites and genes via biochemical reactions. To demonstrate the potential of this method, we applied MAGI to integrate sequence data and metabolomics data collected from Streptomyces coelicolor A3(2), an extensively characterized bacterium that produces diverse secondary metabolites. Our findings suggest that coupling metabolomics and genomics data by scoring consensus between the two increases the quality of both metabolite identifications and gene annotations in this organism. MAGI also made biochemical predictions for poorly annotated genes that were consistent with the extensive literature on this important organism. This limited analysis suggests that using metabolomics data has the potential to improve annotations in sequenced organisms and also provides testable hypotheses for specific biochemical functions. MAGI is freely available for academic use both as an online tool at https://magi.nersc.gov and with source code available at https://github.com/biorack/magi.

bioinformatics↗