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Results for “Multiplexed Metabolomics”

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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Accelerating strain phenotyping with desorption electrospray ionization-imaging mass spectrometry and untargeted analysis of intact microbial colonies

Significance Synthetic biology has entered an era in which reading and writing DNA sequences are no longer rate-limiting steps in microbial strain engineering. Indeed, analytical methods measuring the resulting metabolic outcomes of specific gene edits have lagged behind the ability to generate new recombinant strains. Herein, we report a mass spectrometry strategy to accelerate these analytical workflows by directly analyzing metabolites and molecules produced from engineered microorganisms in a multiplexed process. Using untargeted acquisitions and unsupervised analytics, we assess the molecular features that change across discrete strains including primary target species, secondary products, and species outside the engineered fatty acid biosynthesis pathway.

09 BIOMASS FUELS↗

Enhancing tandem mass spectrometry-based metabolite annotation with online chemical labeling

Abstract Metabolite identification in non-targeted mass spectrometry-based metabolomics remains a major challenge due to limited spectral library coverage and difficulties in predicting metabolite fragmentation patterns. Here, we introduce Multiplexed Chemical Metabolomics (MCheM), which employs orthogonal post-column derivatization reactions integrated into a unified mass spectrometry data framework. MCheM generates orthogonal structural information that substantially improves metabolite annotation through in silico spectrum matching and open-modification searches, offering a powerful new toolbox for the structure elucidation of unknown metabolites at scale.

Science & Technology - Other Topics↗

Single-cell spatial metabolomics with cell-type specific protein profiling for tissue systems biology

Metabolic reprogramming in cancer and immune cells occurs to support their increasing energy needs in biological tissues. Here we propose Single Cell Spatially resolved Metabolic (scSpaMet) framework for joint protein-metabolite profiling of single immune and cancer cells in male human tissues by incorporating untargeted spatial metabolomics and targeted multiplexed protein imaging in a single pipeline. We utilized the scSpaMet to profile cell types and spatial metabolomic maps of 19507, 31156, and 8215 single cells in human lung cancer, tonsil, and endometrium tissues, respectively. The scSpaMet analysis revealed cell type-dependent metabolite profiles and local metabolite competition of neighboring single cells in human tissues. Deep learning-based joint embedding revealed unique metabolite states within cell types. Trajectory inference showed metabolic patterns along cell differentiation paths. Here we show scSpaMet’s ability to quantify and visualize the cell-type specific and spatially resolved metabolic-protein mapping as an emerging tool for systems-level understanding of tissue biology.

59 BASIC BIOLOGICAL SCIENCES↗

Applications of targeted proteomics in metabolic engineering: advances and opportunities

Optimization of metabolically engineered organisms requires good understanding of producing balanced level of pathway proteins. Targeted proteomics via selected-reaction monitoring (SRM) has been increasingly used in metabolic engineering studies to detect and quantify sets of proteins with high selectivity, multiplexity, and reproducibility. In combination with metabolomics and other omics tools, targeted proteomics has helped optimize the production of many bio-based chemicals in various metabolic engineering cell factories. In this review, we present recent applications of targeted proteomics in metabolic engineering studies and highlight several successful cases of targeted proteomics in boosting production of commodity and high value chemicals. Additionally, we also discuss challenges and limitations of current targeted proteomics and map opportunities for future research.

59 BASIC BIOLOGICAL SCIENCES↗

Agilent CRADA (Abstract)

The CRADA between Agilent Technologies Inc. and Battelle will focus on five software components as listed below: Prototype 4D Feature Finding functionality with a particular focus on recovering low level features and extending the bottom end dynamic range of IM-MS technology. Compare and contrast developments to current 4D Feature Finding capabilities. Highlight important algorithmic aspects employed. Implement the PNNL saturation correction algorithm. Agilent will give PNNL the needed data file access API and assistance in understanding it implementation and any needed instrumental aspects. Supported high resolution products to include Agilent’s TOF, QTOF and IM-QTOF mass spectrometers. PNNL will then work with Agilent to benchmark performance. Implementation of the PNNL Hadamard de-multiplexing algorithm. Agilent will give provide PNNL the needed date file access API access and as needed assistance in understanding the current Agilent multiplexed IM offering. PNNL will then work with Agilent on benchmark performance. Add ion mobility collision cross sections to existing and new metabolomic libraries for data analysis with Agilent’s informatics program MPP/ID Browser. PNNL will work with Agilent to create a software pipeline that takes data from chemical and metabolic standards and properly formats it for inclusion in MPP accessible libraries, using the collision cross section as a new separation dimension. Improvements of MPP multidimensional matching to identify metabolomic features using multiple characteristics beyond retention time and accurate mass. Most significantly matching will include analyte collision cross section with proposed support for sample fraction or RapidFire cartridge and fragmentation spectra. PNNL will work with Agilent to modify and improve the current MPP analysis pipeline to allow for creating, aligning, and identifying MS features defined by accurate mass, collision cross section and chromatographic retention time. As additional criteria such as fraction or RapidFire cartridge type are supported in the identification process, then they also will become part of the automation workflow. This includes the automation of said system to work with command line program (i.e. not a GUI) sufficient for programmatic execution in a pipeline.

97 MATHEMATICS AND COMPUTING↗

Improved Biofuel Production through Discovery and Engineering of Terpene Metabolism in Switchgrass

Project Objectives - Of the myriad specialized metabolites that plants deploy to adapt to environmental challenges, terpenes form the largest group. In many major crops, unique terpene blends serve as key stress defenses that directly impact plant fitness and yield. In addition, terpenes, such as bisabolene and pinene, are used for producing renewable biofuels. Essential to advancing a broader use of terpenes for biofuel feedstock engineering is a system-wide knowledge of the diverse biosynthetic machinery and defensive potential of often species-specific terpene blends. The proposed project would merge genome-wide enzyme discovery with comparative –omics, protein structural and plant microbiome studies to define the biosynthesis and stress-defensive functions of the switchgrass (Panicum virgatum) terpene network. These insights would be combined with developing and applying non-transgenic genome editing tools to design plants with desirable terpene blends for higher productivity and biofuel production on marginal lands. As a dedicated lignocellulosic feedstock for U.S. biofuel production with high net energy yield, stress tolerance, and available genome resources, switchgrass is well-suited for devising new avenues for biofuel production. Project Description – The diversity of plant terpene defenses is governed by species-specific families of terpene synthase (TPS) and cytochrome P450 monooxygenase (P450) enzymes. Mining of the switchgrass genome (genotype Alamo) identified ~100 TPS and P450 candidate genes, and combinatorial biochemical analysis of synthesized TPSs and P450s revealed more than a dozen enzymes with common and novel activities. In addition, several identified terpene metabolites and the corresponding transcripts were up-regulated in response to abiotic stressors. These findings demonstrate a unique switchgrass terpene network with probable importance to abiotic stress tolerance, thus providing a large chemical portfolio for optimizing crop resistance, yield, and biofuel composition. Leveraging these preliminary data, we propose to generate a genome-wide map of the switchgrass terpene metabolic network through multi-gene co-expression analyses that allow the efficient cross-validation of TPS and P450 functions. Key enzymes would further be applied to structure-function studies via X-ray protein crystallography, homology modeling and site-directed mutagenesis to gain mechanistic insight into the catalytic specificity of switchgrass terpene metabolism and provide gene and amino acid targets for genome editing. In tandem with terpene pathway discovery, system-wide metabolomics, transcriptomics and proteomics studies in switchgrass accessions of contrasting drought tolerance would define the role of switchgrass terpene metabolism in conferring abiotic stress resilience. Metabolic changes would be assessed in a combined approach of targeted (terpenes) and untargeted metabolite profiling using a high-resolution LC-MS/MS approach, differential gene expression analyses through multiplexed Illumina RNA sequencing, and quantitative analysis of high-priority pathway enzymes using multiple reaction monitoring (MRM). Drawing on these insights, knock-down/out mutants of stress-associated pathway nodes would be generated by optimizing transient virus-induced gene silencing (VIGS) and CRISPR/Cas9 systems under control of the Tobacco Rattle Virus (TRV). The resulting mutant lines would then be analyzed for stress susceptibility and the impact on the root microbiome to define gene functions in planta. Knowledge of terpene pathways, enzyme mechanisms and bioactivities would be applied to enhance switchgrass stress resilience and to tailor-make terpene blends for biofuel production. Here, TRV-enabled CRISPR/Cas9 genome editing, including allele-specific knock-out of redundant genes, engineering of enzyme specificity via structure-guided point mutations, and overexpression of terpene genes relevant to stress-protection or biofuel production, would be used to increase metabolic flux toward desired pathways. Broader Impacts - Integrating the system-wide discovery, mechanistic analysis and non-transgenic genome engineering of the switchgrass terpene network aligns the required steps to unlock the chemical potential of this important metabolite class to generate crops that are more resistant to stress and provide advanced biofuel production in light of rising climate pressures as foreseeable challenges for bioenergy crop cultivation. The proposed project would further offer interdisciplinary student training through active involvement in the project and integration of research concepts and outcomes into newly-developed graduate and undergraduate courses on Plant Biotechnology.

09 BIOMASS FUELS↗

Label-free nanoscopy of cell metabolism by ultrasensitive reweighted visible stimulated Raman scattering

Nanoscopic imaging of cell metabolism is hindered by the incompatibility of small metabolites with fluorescent dyes and the limited resolution of imaging mass spectrometry. We present ultrasensitive reweighted visible stimulated Raman scattering (URV-SRS), a label-free vibrational nanoscopy technique that enables multiplexed detection of metabolic nanostructures within cells. We developed an extensively chirped spectral focusing visible SRS microscope that achieves a detection limit of 4,000 molecules and introduced a self-supervised learning-based denoiser to robustly suppress non-independent SRS noise by over 7.2 dB. The instrumentation-based signal enhancement and computation-based noise suppression synergistically improved the detection sensitivity by 50 times over near-infrared SRS. Leveraging this enhanced sensitivity, we further pushed the resolution to nanoscopic levels by introducing Fourier reweighting to amplify sub-100 nm spatial frequencies previously overwhelmed by noise. Validated by Fourier ring correlation, URV-SRS achieves a lateral resolution of 86 nm in cellular imaging. Here, we applied URV-SRS to elucidate the reprogramming of metabolic nanostructures associated with virus replication in Vero E6 host cells and to compositionally delineate subcellular fatty acid synthesis in engineered Escherichia coli, demonstrating its capability towards nanoscopic spatial metabolomics.

59 BASIC BIOLOGICAL SCIENCES↗