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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

mzPeak: Designing a Scalable, Interoperable, and Future-Ready Mass Spectrometry Data Format

Advances in mass spectrometry (MS) instrumentation, such as higher resolution, faster scan speeds, and improved sensitivity, have significantly increased the volume and complexity of data. The growing adoption of imaging and ion mobility further amplifies these challenges across MS-based omics fields, including proteomics, metabolomics, and lipidomics. While these technologies unlock new possibilities, they also present significant challenges in data management, storage, and accessibility. Existing open formats, such as the XML-based community standards mzML and imzML, struggle to meet the demands of modern MS workflows due to their large file sizes, slow data access, and limited metadata support. Vendor-specific formats, while optimized for proprietary instruments, lack interoperability, comprehensive metadata support and long-term archival reliability. This white paper lays the groundwork for mzPeak, a next-generation community data format designed to address these challenges and support high-throughput, multi-dimensional MS workflows. By adopting a hybrid model that combines efficient binary storage for numerical data and both human and machine-readable metadata storage, mzPeak will reduce file sizes, accelerate data access, and offer a scalable, adaptable solution for evolving MS technologies. For researchers, mzPeak will enable enhanced interoperability across platforms, seamless support for complex workflows including ion mobility and MS imaging, and faster data access compared to existing community formats such as mzML. Its design will ensure data is managed in compliance with regulatory standards, essential for applications such as precision medicine and chemical safety, where long-term data integrity and accessibility are critical. For vendors, mzPeak provides a streamlined, open alternative to proprietary formats, reducing the burden of regulatory compliance while aligning with the industry's push for transparency and standardization. By offering a high-performance, interoperable solution, mzPeak positions vendors to meet customer demands for sustainable data management tools which will be able to handle emerging and future data types and workflows. mzPeak aspires to become the cornerstone of MS data management, empowering researchers, vendors, and developers to innovate and collaborate more effectively.

data formats↗
DOE OSTI2026

OmicsMLMentor: A Web Application for Guided Machine Learning Analysis of Omics Data

Expression-based omics technologies (e.g. proteomics, metabolomics, transcriptomics, etc.) increasingly rely on supervised and unsupervised machine learning (ML) models to find key biomolecules distinguishing conditions, identify natural groupings in biological data, or generate predictions for outcomes of interest. Fitting ML models to omics data presents several challenges, including handling missing data, selecting a normalization method, choosing a valid model, and optimizing hyperparameters, all requiring statistical programming skills to address these challenges. Thus, the open-source web application SLOPE was designed to lower the barrier to ML modeling for omics data. SLOPE supports the fitting of 15 ML models (10 supervised and 5 unsupervised) tailored to omics datasets, such as proteomics, metabolomics, lipidomics, and transcriptomics. SLOPE offers several omics-specific features, including methods for handling missingness (imputation, conversion, removal), normalization tests, ranking of models based on the structure of a user’s data and user input, and optimal hyperparameter selections using cross-validation splits. By streamlining ML workflows for omics analysis, SLOPE address critical gaps in existing online web tools, facilitating a broader adoption of these models for omics research. Here, SLOPE is applied to data from a lignin exposure study to highlight the workflow for fitting both supervised and unsupervised models to data.

lipidomics↗
DOE OSTI2024

PeakQC: A Software Tool for Omics-Agnostic Automated Quality Control of Mass Spectrometry Data

Mass spectrometry is broadly employed to study complex molecular mechanisms in various biological and environmental fields, enabling 'omics' research such as proteomics, metabolomics, and lipidomics. As study cohorts grow larger and more complex with dozens to hundreds of samples, the need for robust quality control (QC) measures through automated software tools becomes paramount to ensure the integrity, high quality, and validity of scientific conclusions from downstream analyses and minimize the waste of resources. Since existing QC tools are mostly dedicated to proteomics, automated solutions supporting metabolomics are needed. To address this need, we developed the software PeakQC, a tool for automated QC of MS data that is independent of omics molecular types (i.e., omics-agnostic). It allows automated extraction and inspection of peak metrics of precursor ions (e.g., errors in mass, retention time, arrival time) and supports various instrumentations and acquisition types, from infusion experiments or using liquid chromatography and/or ion mobility spectrometry front-end separations and with/without fragmentation spectra from data-dependent or independent acquisition analyses. Diagnostic plots for fragmentation spectra are also generated. Here, in this paper, we describe and illustrate PeakQC’s functionalities using different representative data sets, demonstrating its utility as a valuable tool for enhancing the quality and reliability of omics mass spectrometry analyses.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Physiological and metabolic responses of Zymomonas mobilis to lignocellulosic hydrolysate

Zymomonas mobilis is a promising biocatalyst for the sustainable conversion of lignocellulosic sugars into biofuels and bioproducts, yet its response to lignocellulosic hydrolysates remains poorly understood. Here, we investigate the physiological response of Z. mobilis to ammonia fiber expansion (AFEX)-pretreated switchgrass hydrolysate using a systems-level approach integrating LC–MS/MS-based lipidomics and shotgun proteomics. Growth on hydrolysate induced substantial shifts in fatty acid and membrane phospholipid composition, alongside broad proteomic remodeling. Notably, Z. mobilis exhibited a stress response characterized by the upregulation of heat shock proteins and efflux transporters and the downregulation of cell motility proteins. Unexpectedly, hydrolysate exposure also led to a robust upregulation of the Entner–Doudoroff pathway, the ethanol fermentation pathway, and other central carbon metabolism enzymes, indicating a substantial cellular investment potentially driven by additional nutrient availability in hydrolysate. These findings provide new insights into the metabolic adaptations of Z. mobilis to lignocellulosic hydrolysates, informing strategies to enhance its biofuel production capabilities.

Zymomonas mobilis↗
DOE OSTI2022

Metabolic engineering of Rhodotorula toruloides IFO0880 improves C16 and C18 fatty alcohol production from synthetic media

Abstract Background The oleaginous, carotenogenic yeast Rhodotorula toruloides has been increasingly explored as a platform organism for the production of terpenoids and fatty acid derivatives. Fatty alcohols, a fatty acid derivative widely used in the production of detergents and surfactants, can be produced microbially with the expression of a heterologous fatty acyl-CoA reductase. Due to its high lipid production, R. toruloides has high potential for fatty alcohol production, and in this study several metabolic engineering approaches were investigated to improve the titer of this product. Results Fatty acyl-CoA reductase from Marinobacter aqueolei was co-expressed with SpCas9 in R. toruloides IFO0880 and a panel of gene overexpressions and Cas9-mediated gene deletions were explored to increase the fatty alcohol production. Two overexpression targets ( ACL1 and ACC1 , improving cytosolic acetyl-CoA and malonyl-CoA production, respectively) and two deletion targets (the acyltransferases DGA1 and LRO1 ) resulted in significant (1.8 to 4.4-fold) increases to the fatty alcohol titer in culture tubes. Combinatorial exploration of these modifications in bioreactor fermentation culminated in a 3.7 g/L fatty alcohol titer in the LRO1 Δ mutant. As LRO1 deletion was not found to be beneficial for fatty alcohol production in other yeasts, a lipidomic comparison of the DGA1 and LRO1 knockout mutants was performed, finding that DGA1 is the primary acyltransferase responsible for triacylglyceride production in R. toruloides , while LRO1 disruption simultaneously improved fatty alcohol production, increased diacylglyceride and triacylglyceride production, and increased glucose consumption. Conclusions The fatty alcohol titer of fatty acyl-CoA reductase-expressing R. toruloides was significantly improved through the deletion of LRO1 , or the deletion of DGA1 combined with overexpression of ACC1 and ACL1 . Disruption of LRO1 surprisingly increased both lipid and fatty alcohol production, creating a possible avenue for future study of the lipid metabolism of this yeast.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Lipid membrane remodeling and metabolic response during isobutanol and ethanol exposure in Zymomonas mobilis

Abstract Background Recent engineering efforts have targeted the ethanologenic bacterium Zymomonas mobilis for isobutanol production. However, significant hurdles remain due this organism’s vulnerability to isobutanol toxicity, adversely affecting its growth and productivity. The limited understanding of the physiological impacts of isobutanol on Z. mobilis constrains our ability to overcome these production barriers. Results We utilized a systems-level approach comprising LC–MS/MS-based lipidomics, metabolomics, and shotgun proteomics, to investigate how exposure to ethanol and isobutanol impact the lipid membrane composition and overall physiology of Z. mobilis . Our analysis revealed significant and distinct alterations in membrane phospholipid and fatty acid composition resulting from ethanol and isobutanol exposure. Notably, ethanol exposure increased membrane cyclopropane fatty acid content and expression of cyclopropane fatty acid (CFA) synthase. Surprisingly, isobutanol decreased cyclopropane fatty acid content despite robust upregulation of CFA synthase. Overexpression of the native Z. mobilis’ CFA synthase increased cyclopropane fatty acid content in all phospholipid classes and was associated with a significant improvement in growth rates in the presence of added ethanol and isobutanol. Heterologous expression of CFA synthase from Clostridium acetobutylicum resulted in a near complete replacement of unsaturated fatty acids with cyclopropane fatty acids, affecting all lipid classes. However, this did not translate to improved growth rates under isobutanol exposure. Correlating with its greater susceptibility to isobutanol, Z. mobilis exhibited more pronounced alterations in its proteome, metabolome, and overall cell morphology—including cell swelling and formation of intracellular protein aggregates —when exposed to isobutanol compared to ethanol. Isobutanol triggered a broad stress response marked by the upregulation of heat shock proteins, efflux transporters, DNA repair systems, and the downregulation of cell motility proteins. Isobutanol also elicited widespread dysregulation of Z. mobilis ’ primary metabolism evidenced by increased levels of nucleotide degradation intermediates and the depletion of biosynthetic and glycolytic intermediates. Conclusions This study provides a comprehensive, systems-level evaluation of the impact of ethanol and isobutanol exposure on the lipid membrane composition and overall physiology of Z. mobilis . These findings will guide engineering of Z. mobilis towards the creation of isobutanol-tolerant strains that can serve as robust platforms for the industrial production of isobutanol from lignocellulosic sugars.

09 BIOMASS FUELS↗
DOE OSTI2023

Systems Engineering of Rhodococcus opacus to Enable Production of Drop-in Fuels from Lignocellulose

Production of drop-in fuels from lignocellulose using Rhodococcus opacus PD630 (hereafter R. opacus) is a challenging goal. During the grant period we have pushed the field forward significantly in several areas of research. Towards the end goal of accelerating the adoption of R. opacus in biofuel production, during the grant period we have expanded the phenotypic characterization of R. opacus grown in single aromatic (model lignocellulosic) compounds or their mixtures, modeling the growth conditions in lignocellulosic biomass. Harnessing the power of adaptive evolution, we produced evolved R. opacus isolates with superior lignin valorization capabilities and identified differentially expressed genes and pathways after adaptation. We used next generation multi-omic techniques such as genomic, transcriptomic, and metabolomic analyses, to identify the catabolic pathways used by R. opacus to degrade aromatic compounds and funnel these degradation products into central metabolism, as well as the aromatic transport genes required for increased tolerance and utilization. Taking this information one step further, we identified endogenous transcription factors and regulatory mechanisms important for degradation of five model aromatic compounds. To accurately estimate R. opacus growth and consumption on model lignin compounds we pioneered the use of novel extraction procedures prior to GC-MS analysis. Alongside 13 C-metabolic flux analysis, we have elucidated the metabolic routes preferred by Rhodococcus opacus during aromatic compound degradation. Finally, we used in tandem lipidomics and high-resolution mass spectrometry to identify the modulation of mycolic acids and phospholipid membrane composition modification as a strategy for aromatic tolerance in R. opacus. Being a non-model organism, R. opacus lacks the breadth of tools and technical foundation which drive biofuel research in more well-understood microbes such as Escherichia coli. To reduce this burden for use, we designed and produced new tools for genomic manipulation and engineering in R. opacus. These engineering breakthroughs support efficient genomic editing, enabling gene overexpression, repression, and genetic alteration. Using these tools, we have generated synthetically engineered strains with increased lipogenesis and growth, both positive traits required for increased lignin valorization. Optimizing engineered strains for biofuel production from lignocellulose requires extremely sophisticated synthetic rewiring of metabolism. To facilitate systems-level reorganization of metabolism in R. opacus, we created a genome-scale model that accurately predicts metabolic flux and growth rates on the aromatic compound phenol. Lignin requires extensive pre-treatment before biological degradation by R. opacus. Towards an eventual goal of degrading real-world lignin, we developed new depolymerization processes to generate lignin breakdown products (LBP). We optimized LBP storage and composition analysis techniques, enabling accurate prediction of specific LBP compound integration into cell wall components. Overall, through the work funded by this grant we generated 20 manuscripts (17 published, 3 in review/preparation), methods for increased accuracy in metabolomics of aromatic compounds, multiple genetic tools for altering the R. opacus genome, genome scale models for predicting flux through metabolic pathways, as well as multi-omic data for community use. The work funded by this grant has increased the knowledge of aromatic degradation in bacteria and advanced our efforts to optimize R. opacus for lignin valorization.

09 BIOMASS FUELS↗
DOE OSTI2026

Rhodotorula toruloides Nitrogen Limitation PTM Profiling Multi-Omics (TZ-DP1).

The purpose of this experiment was to evaluate the regulatory stress response of Oleaginous yeast species Rhodotorula toruloides NBRC 0880 (JGI strain IFFO0880 v4.0) under nitrogen-rich and nitrogen-limited conditions over time. Time course experimental samples (24, 48, and 72 hours after inoculation) were prepared using a semi-automated multi-PTM proteomic approach, using tandem mass tag 18-plex (TMT18), and lipidome remodeling for downstream multi-omics analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Omics Approaches for Understanding Biogenesis, Composition and Functions of Fungal Extracellular Vesicles

Extracellular vesicles (EVs) are lipid bilayer structures released by organisms from all kingdoms of life. The diverse biogenesis pathways of EVs result in a wide variety of physical properties and functions across different organisms. Fungal EVs were first described in 2007 and different omics approaches have been fundamental to understand their composition, biogenesis, and function. In this review, we discuss the role of omics in elucidating fungal EVs biology. Transcriptomics, proteomics, metabolomics, and lipidomics have each enabled the molecular characterization of fungal EVs, providing evidence that these structures serve a wide array of functions, ranging from key carriers of cell wall biosynthetic machinery to virulence factors. Omics in combination with genetic approaches have been instrumental in determining both biogenesis and cargo loading into EVs. We also discuss how omics technologies are being employed to elucidate the role of EVs in antifungal resistance, disease biomarkers, and their potential use as vaccines. Finally, we review recent advances in analytical technology and multi-omic integration tools, which will help to address key knowledge gaps in EVs biology and translate basic research information into urgently needed clinical applications such as diagnostics, and immuno- and chemotherapies to fungal infections.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Interrogating the role of the milk microbiome in mastitis in the multi-omics era

There is growing interest in a functional understanding of milk-associated microbiota as there is ample evidence that host-associated microbial communities play an active role in host health and phenotype. Mastitis, characterized by painful inflammation of the mammary gland, is prevalent among lactating humans and agricultural animals and is associated with significant clinical and economic consequences. The etiology of mastitis is complex and polymicrobial and correlative studies have indicated alterations in milk microbial community composition. Recent evidence is beginning to suggest that a causal relationship may exist between the milk microbiota and host phenotype in mastitis. Multi-omic approaches can be leveraged to gain a mechanistic, molecular level understanding of how the milk microbiome might modulate host physiology, thereby informing strategies to prevent and ameliorate mastitis. In this paper, we review existing studies that have utilized omics approaches to investigate the role of the milk microbiome in mastitis. We also summarize the strengths and challenges associated with the different omics techniques including metagenomics, metatranscriptomics, metaproteomics, metabolomics and lipidomics and provide perspective on the integration of multiple omics technologies for a better functional understanding of the milk microbiome.

metabolomics↗
DOE OSTI2023

Biological insights from multi-omics analysis strategies: Complex pleotropic effects associated with autophagy

Research strategies that combine molecular data from multiple levels of genome expression (i.e., multi-omics data), often referred to as a systems biology strategy, has been advocated as a route to discovering gene functions. In this study we conducted an evaluation of this strategy by combining lipidomics, metabolite mass-spectral imaging and transcriptomics data from leaves and roots in response to mutations in two AuTophaGy-related ( ATG ) genes of Arabidopsis . Autophagy is an essential cellular process that degrades and recycles macromolecules and organelles, and this process is blocked in the atg7 and atg9 mutants that were the focus of this study. Specifically, we quantified abundances of ~100 lipids and imaged the cellular locations of ~15 lipid molecular species and the relative abundance of ~26,000 transcripts from leaf and root tissues of WT, atg7 and atg9 mutant plants, grown either in normal (nitrogen-replete) and autophagy-inducing conditions (nitrogen-deficient). The multi-omics data enabled detailed molecular depiction of the effect of each mutation, and a comprehensive physiological model to explain the consequence of these genetic and environmental changes in autophagy is greatly facilitated by the a priori knowledge of the exact biochemical function of the ATG7 and ATG9 proteins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Complex Changes in Membrane Lipids Associated with the Modification of Autophagy in Arabidopsis

Autophagy is a conserved mechanism among eukaryotes that degrades and recycles cytoplasmic components. Autophagy is known to influence the plant metabolome, including lipid content; however, its impact on the plant lipidome is not fully understood, and most studies have analyzed a single or few mutants defective in autophagy. To gain more insight into the effect of autophagy on lipid concentrations and composition, we quantitatively profiled glycerolipids from multiple Arabidopsis thaliana mutants altered in autophagy and compared them with wild-type seedlings under nitrogen replete (+N; normal growth) and nitrogen starvation (−N; autophagy inducing) conditions. Mutants include those in genes of the core autophagy pathway, together with other genes that have been reported to affect autophagy. Using Matrix-Assisted Laser Desorption/Ionization—Mass Spectrometry (MALDI-MS), we imaged the cellular distribution of specific lipids in situ and demonstrated that autophagy and nitrogen treatment did not affect their spatial distribution within Arabidopsis seedling leaves. We observed changes, both increases and decreases, in the relative amounts of different lipid species in the mutants compared to WT both in +N and −N conditions, although more changes were seen in −N conditions. The relative amounts of polyunsaturated and very long chain lipids were significantly reduced in autophagy-disrupted mutants compared to WT plants. Collectively, our results provide additional evidence that autophagy affects plant lipid content and that autophagy likely affects lipid properties such as chain length and unsaturation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Meeting Report on the 3rd Chinese American Society for Mass Spectrometry Conference—Advancing Biological and Pharmaceutical Mass Spectrometry

Following the highly successful Chinese American Society for Mass Spectrometry (CASMS) conferences in the previous 2 years, the 3rd CASMS Conference was held virtually on August 28–31, 2023, using the Gather. Town platform to bring together scientists in the MS field. The conference offered a 4-day agenda with a scientific program consisting of two plenary lectures, and 14 parallel symposia in which a total of 70 speakers presented technological innovations and their applications in proteomics and biological MS and metabo-lipidomics and pharmaceutical MS. In addition, 16 invited speakers/panelists presented at two research-focused and three career development workshops. Moreover, 86 posters, 12 lightning talks, 3 sponsored workshops, and 11 exhibitions were presented, from which 9 poster awards and 2 lightning talk awards were selected. Furthermore, the conference featured four young investigator awardees to highlight early-career achievements in MS from our society. In conclusion, the conference provided a unique scientific platform for young scientists (i.e. graduate students, postdocs, and junior faculty/investigators) to present their research, meet with prominent scientists, learn about career development, and job opportunities (http://casms.org).

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

The Future of a Myriad of Accelerated Biodiscoveries Lies in AI‐Powered Mass Spectrometry and Multiomics Integration

The intersection of modern artificial intelligence (AI) and mass spectrometry (MS) is set to transform the MS‐based “omics” research fields, particularly proteomics, metabolomics, lipidomics, and glycomics, enabling advancements across a wide range of domains, from health to environment and industrial biotechnology. Beginning with an overview of key challenges inherent in MS software pipelines, this personal perspective explores how AI‐driven solutions can address them to enhance data processing, integration and interpretation. It proposes a paradigm shift in molecular identification and quantitation algorithms, leveraging AI to enable holistic interpretation of MS‐based multiomics data. While centered on MS‐based omics, this holistic AI‐driven paradigm is also critical for connecting dynamic biochemical changes to genomics and transcriptomics contexts, reinforcing the integrative value of MS in multiomics research. Ultimately, this AI‐driven approach could enhance efficiency, accuracy, and molecular breadth of coverage, deepening our systems‐level understanding of biological processes and accelerating a myriad of biodiscoveries.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

High-resolution ion mobility based on traveling wave structures for lossless ion manipulation resolves hidden lipid features

Abstract High-resolution ion mobility (resolving power > 200) coupled with mass spectrometry (MS) is a powerful analytical tool for resolving isobars and isomers in complex samples. High-resolution ion mobility is capable of discerning additional structurally distinct features, which are not observed with conventional resolving power ion mobility (IM, resolving power ~ 50) techniques such as traveling wave IM and drift tube ion mobility (DTIM). DTIM in particular is considered to be the “gold standard” IM technique since collision cross section (CCS) values are directly obtained through a first-principles relationship, whereas traveling wave IM techniques require an additional calibration strategy to determine accurate CCS values. In this study, we aim to evaluate the separation capabilities of a traveling wave ion mobility structures for lossless ion manipulation platform integrated with mass spectrometry analysis (SLIM IM-MS) for both lipid isomer standards and complex lipid samples. A cross-platform investigation of seven subclass-specific lipid extracts examined by both DTIM-MS and SLIM IM-MS showed additional features were observed for all lipid extracts when examined under high resolving power IM conditions, with the number of CCS-aligned features that resolve into additional peaks from DTIM-MS to SLIM IM-MS analysis varying between 5 and 50%, depending on the specific lipid sub-class investigated. Lipid CCS values are obtained from SLIM IM ( TW(SLIM) CCS) through a two-step calibration procedure to align these measurements to within 2% average bias to reference values obtained via DTIM ( DT CCS). A total of 225 lipid features from seven lipid extracts are subsequently identified in the high resolving power IM analysis by a combination of accurate mass-to-charge, CCS, retention time, and linear mobility-mass correlations to curate a high-resolution IM lipid structural atlas. These results emphasize the high isomeric complexity present in lipidomic samples and underscore the need for multiple analytical stages of separation operated at high resolution. Graphical abstract

Reardon, Allison R. (ORCID:0000000165830134)↗
DOE OSTI2025

Evaluating inkjet dispenser/liquid vortex capture-mass spectrometry for single-cell metabolomics in Hep G2 steatosis caused by tamoxifen

Single-cell mass spectrometry (MS) is advancing our understanding of metabolic pathways in heterogeneous cell populations; however, many techniques are slow or require disruptive sample preparations. This study evaluated coupling a modified HP D100 single-cell inkjet dispenser with liquid vortex capture-mass spectrometry (D100/LVC-MS). The D100 is a single-cell inkjet dispenser capable of titrating solutions and isolating single cells via disposable cassettes equipped with microfluidic channels and an impedance sensor. The LVC-MS enables high-throughput capture, lysis, and ionization of analytes for mass spectrometric analysis. The D100/LVC-MS system was characterized through titration and single-cell experiments. Propranolol titration demonstrated linearity across a broad concentration range using the D100/LVC-MS system. Additionally, Hep G2 hepatocarcinoma cells and Chlamydomonas reinhardtii algae were used to showcase the D100’s high-throughput or low-buffer-volume single-cell dispensing strategies. The D100/LVC-MS system’s performance was validated by evaluating tamoxifen-induced steatosis in Hep G2 cells. Tamoxifen, associated with nonalcoholic fatty liver disease in breast cancer patients following long-term use, was tested in Hep G2 cells at 20 µM for 72 h against DMSO-treated controls. High-throughput analysis of 500 cells per condition, completed in 25 min per run, demonstrated the system’s efficiency. The D100/LVC-MS system simultaneously quantified tamoxifen and measured triglycerides and phosphatidylcholines. Triglycerides were upregulated in the tamoxifen-treated cells and the results indicated two distinct cell populations, differing in tamoxifen and phosphatidylcholines levels, suggesting heterogeneity within the treated population. In conclusion, these findings highlight the D100/LVC-MS system as a cost-effective, high-throughput platform for single-cell metabolomics and lipidomics, with significant potential for evaluating metabolic alterations.

Chromatography↗
DOE OSTI2025

Description of a novel extremophile green algae, Chlamydomonas pacifica , and its potential as a biotechnology host

We present the comprehensive characterization of a newly identified microalga, Chlamydomonas pacifica , originally isolated from a soil sample in San Diego, CA, USA. This species showcases remarkable biological versatility, including a broad pH range tolerance (6–11.5), high thermal tolerance (up to 42 °C), and salinity resilience (up to 2 % NaCl). Its amenability to genetic manipulation and sexual reproduction via mating, particularly between the two opposing strains CC-5697 & CC-5699, now publicly available through the Chlamydomonas Resource Center, underscores its potential as a biotechnological chassis. The biological assessment of C. pacifica revealed versatile metabolic capabilities, including diverse nitrogen assimilation capability, motility and phototaxis. Genomic and transcriptomic analyses identified 17,829 genes within a 121 Mb genome, featuring a GC content of 61 %. The codon usage of C. pacifica closely mirrors that of C. reinhardtii , indicating a conserved genetic architecture that supports a trend in codon preference with minor variations. Phylogenetic analyses position C. pacifica within the core-Reinhardtinia clade yet distinct from known Volvocales species. The lipidomic data revealed an abundance of triacylglycerols (TAGs), promising for biofuel applications and lipids for health-related benefits. Our investigation lays the groundwork for exploiting C. pacifica in biotechnological applications, from biofuel generation to synthesizing biodegradable plastics, positioning it as a versatile host for future bioengineering endeavors.

Alkali tolerant↗
DOE OSTI2021

Biophysical analysis of the plant-specific GIPC sphingolipids reveals multiple modes of membrane regulation

The plant plasma membrane (PM) is an essential barrier between the cell and the external environment, controlling signal perception and transmission. It consists of an asymmetrical lipid bilayer made up of three different lipid classes: sphingolipids, sterols, and phospholipids. The glycosyl inositol phosphoryl ceramides (GIPCs), representing up to 40% of total sphingolipids, are assumed to be almost exclusively in the outer leaflet of the PM. However, their biological role and properties are poorly defined. In this study, we investigated the role of GIPCs in membrane organization. Because GIPCs are not commercially available, we developed a protocol to extract and isolate GIPC-enriched fractions from eudicots (cauliflower and tobacco) and monocots (leek and rice). Lipidomic analysis confirmed the presence of trihydroxylated long chain bases and 2-hydroxylated very long-chain fatty acids up to 26 carbon atoms. The glycan head groups of the GIPCs from monocots and dicots were analyzed by gas chromatograph-mass spectrometry, revealing different sugar moieties. Multiple biophysics tools, namely Langmuir monolayer, ζ-Potential, light scattering, neutron reflectivity, solid state 2H-NMR, and molecular modeling, were used to investigate the physical properties of the GIPCs, as well as their interaction with free and conjugated phytosterols. We showed that GIPCs increase the thickness and electronegativity of model membranes, interact differentially with the different phytosterols species, and regulate the gel-to-fluid phase transition during temperature variations. These results unveil the multiple roles played by GIPCs in the plant PM.

59 BASIC BIOLOGICAL SCIENCES↗