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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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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Use of Fisher's Ratio assisted multivariate curve resolution- alternating least squares for discovery-based analysis using ultrahigh pressure liquid chromatography-high resolution mass spectrometry

Non-targeted analysis of complex chemical mixtures can be difficult considering the convoluted nature of the matrix and the potential unknown chemical differences between samples or classes of samples. Ultrahigh pressure liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (UHPLC-QTOF) is an ideal technique to probe chemical differences for a wide variety of samples. While UHPLC-QTOF can discover minute chemical differences down to low part per billion (ppb) concentrations with a high degree of confidence, the application of high-resolution mass spectrometry can yield massive amounts of information (∼ 10 gb per sample) that cannot be analyzed manually. Therefore, the application of chemometric techniques is mandatory for the interrogation of complex samples. Fisher's ratio (FR) assisted multivariate curve resolution-alternating least squares (MCR-ALS) was used to the discover and identify the chemical differences between two classes of materials: 1) a pond water matrix and 2) the matrix spiked with a pharmaceutical standard mix containing 17 compounds. Thirteen of the seventeen spiked compounds were discovered using FR analysis, and then five were successfully deconvoluted using MCR-ALS wherein the number of curves chosen were automatically determined using singular value decomposition (SVD). In conclusion, the use of an automated FR assisted MCR-ALS will aid in discovering trace levels of chemical components without the need for the researcher to provide potentially biased input which will aid in non-targeted workflow.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Tandem pyrolysis evolved gas–gas chromatography–mass spectrometry

Analysis of byproducts from thermal degradation of polymer materials provides a wealth of information about a materials’ composition, thermal stability, degradation mechanisms, and kinetics. However, regardless of the instrumentation used, only limited information is obtainable from a single experiment. Microfurnace technology, when interfaced to a gas chromatography-mass spectrometry (GC-MS), can be used to obtain both thermal and chemical information via evolved gas analysis-MS (EGA-MS) and GC-MS analysis modes. While both EGA-MS and Py-GC-MS are valuable when characterizing polymer materials, at least two experiments on distinct samples are required, which can be a liability for clear interpretation of results from inhomogeneous samples. Here, we seek to overcome this limitation by combining EGA-MS and Py-GC-MS modes in a single experimental setup. Further, this was done by developing new gas line modifications to allow for tandem Pyrolysis Evolved Gas-Gas Chromatography-Mass Spectrometry (Py/EG-GC-MS) analysis. Verification of Py/EG-GC-MS analysis was performed using a polystyrene standard. Results demonstrate successful Py/EG-GC-MS analysis for the first-time showing the potential of these modifications for application in areas where sample is limited or direct correlation of products to the thermal profile is desirable such as in forensics or product-specific kinetics.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Pressure-Sensitive Adhesive Combined with Paper Spray Mass Spectrometry for Low-Cost Collection and Analysis of Drug Residues

Illicit drug use causes over half a million deaths worldwide every year. Drugs of abuse are commonly smuggled through customs and border checkpoints and, increasingly, through parcel delivery services. Improved methods for detection of trace drug residues from surfaces are needed. Such methods should be robust, fieldable, sensitive, and capable of detecting a wide range of drugs. In this work, commercially produced paper with a pressure-sensitive adhesive coating was utilized for the collection and analysis of trace drug residues by paper spray mass spectrometry (MS). This modified substrate was used to combine sample collection of drug residues from surfaces with rapid detection using a single paper spray ticket. The all-in-one ticket was used to probe different surfaces commonly encountered in forensic work including clothing, cardboard, glass, concrete, asphalt, and aluminum. A total of 10 drugs (acetyl fentanyl, fentanyl, clonazolam, cocaine, heroin, ketamine, methamphetamine, methylone, U-47700, and XLR-11) were evaluated and found to be detectable in the picogram range using a benchtop mass spectrometer and in the low nanogram range using a portable ion trap MS. Finally, the novel approach demonstrates a simple yet effective sampling strategy, allowing for rapid identification from difficult surfaces via paper spray mass spectrometry.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Rapid Automated Annotation and Analysis of N-Glycan Mass Spectrometry Imaging Data Sets Using NGlycDB in METASPACE

Imaging N-glycan spatial distribution in tissues using mass spectrometry imaging (MSI) is emerging as a promising tool in biological and clinical applications. However, there is currently no high throughput tool for visualization and molecular annotation of N-glycans in MSI data, which significantly slows down data processing and hampers the applicability of this approach. In this work, we present how METASPACE, an open-source cloud engine for molecular annotation of MSI data, can be used to automatically annotate, visualize, analyze, and interpret high-resolution mass spectrometry-based spatial N-glycomics data. METASPACE is an emerging tool in spatial metabolomics, but the lack of compatible glycan databases has limited its application for comprehensive N-glycan annotations from MSI datasets. We created NGlycDB, a public database of N-glycans, by adapting available glycan databases. We demonstrate the applicability of NGlycDB in METASPACE by analyzing MALDI-MSI data from formalin-fixed paraffin-embedded (FFPE) human kidney and mouse lung tissue sections. We added NGlycDB to METASPACE for public use, thus facilitating applications of MSI in glycobiology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Anatomy of Protein Electrospray Ionization Mass Spectra by Superconducting Tunnel Junction Mass and Energy Spectrometry

Cryogenic superconducting tunnel junction (STJ) detectors have the advantage of single-particle sensitivity, high quantum efficiency, low noise, and the ability to detect the time and relative impact energy of deposited ions. This makes them attractive for use in mass spectrometry (MS) and as a form of energy spectrometry. STJ cryodetectors have been coupled to time-offlight (TOF) mass spectrometers equipped with a matrix-assisted laser desorption ionization (MALDI) source and to an electrospray ionization (ESI) TOF mass spectrometer. Here, a lab-made linear ion trap (LIT) mass spectrometer system was coupled to an ESI source and a 16-channel Nb-STJ array with improved readout electronics. The goal was to investigate fundamentals of ESI-generated protein ions by further exploiting the advantage of resolving these ions in a third dimension of the relative energy deposited into the STJs. The proteins equine cytochrome c, bovine carbonic anhydrase, bovine serum albumin, and murine immunoglobulin G were studied using this ESI-LIT-STJ-MS instrument. Multiply charged monomers, multimers, and fragments from metastable ions were resolved from monomer peaks by differences in ion deposition energy even when these ions have the same mass-to-charge ratio as the corresponding monomer. The determination of fragment mass from metastable decomposition is accomplished without knowing the charge state of the fragment. The average charge state of the multimers is reduced with each addition of a protein which is a direct reflection of the surface area available for charging. Multiply charged in-source fragments have also been observed and distinguished in the mass spectrum of carbonic anhydrase by using the differences in the energy deposited in the STJs.

42 ENGINEERING↗
DOE OSTI2023

Characterization of the In Vivo Deuteration of Native Phospholipids by Mass Spectrometry Yields Guidelines for Their Regiospecific Customization

Customization of deuterated biomolecules is vital for many advanced biological experiments including neutron scattering. However, because it is challenging to control the proportion and regiospecificity of deuterium incorporation in live systems, often only two or three synthetic lipids are mixed together to form simplistic model membranes. This limits the applicability and biological accuracy of the results generated with these synthetic membranes. Despite some limited prior examination of deuterating Escherichia coli lipids in vivo, this approach has not been widely implemented. In this report an extensive mass spectrometry-based profiling of E. coli phospholipid deuteration states with several different growth media was performed, and a computational method to describe deuterium distributions with a one-number summary is introduced. The deuteration states of 36 lipid species were quantitatively profiled in 15 different growth conditions, and tandem mass spectrometry was used to reveal deuterium localization. Regressions were employed to enable the prediction of lipid deuteration for untested conditions. Small-angle neutron scattering was performed on select deuterated lipid samples, which validated the deuteration states calculated from the mass spectral data. Based on these experiments, guidelines for the design of specifically deuterated phospholipids are described. This unlocks even greater capabilities from neutron-based techniques, enabling experiments that were formerly impossible.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Improved Characterization of Soil Organic Matter by Integrating FT-ICR MS, Liquid Chromatography Tandem Mass Spectrometry, and Molecular Networking: A Case Study of Root Litter Decay under Drought Conditions

Understanding of how soil organic matter (SOM) chemistry is altered in a changing climate has advanced considerably; however, most SOM components remain unidentified, impeding the ability to characterize a major fraction of organic matter and predict what types of molecules, and from which sources, will persist in soil. Here we present a novel approach to better characterize SOM extracts by integrating information from three types of analyses, and we deploy this method to characterize decaying root-detritus soil microcosms subjected to either drought or normal conditions. To observe broad differences in composition, we employed direct infusion Fourier-transform ion cyclotron resonance mass spectrometry (DI-FT-ICR MS). We complemented this with liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify components by library matching. Since libraries contain only a small fraction of SOM components, we also used fragment spectral cosine similarity scores to relate unknowns and library matches through molecular networks. This integrated approach allowed us to corroborate DI-FT-ICR MS molecular formulas using library matches, which included fungal metabolites and related polyphenolic compounds. We also inferred structures of unknowns from molecular networks and improved LC-MS/MS annotation rates from ~5 to 35% by considering DI-FT-ICR MS molecular formula assignments. Under drought conditions, we found greater relative amounts of lignin-like vs condensed aromatic polyphenol formulas and lower average nominal oxidation state of carbon, suggesting reduced decomposition of SOM and/or microbes under stress. Our integrated approach provides a framework for enhanced annotation of SOM components that is more comprehensive than performing individual data analyses in parallel.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Increasing the Scale of the Mass Spectrometry Query Language Compendium with Explainable AI

A significant bottleneck in metabolomics data interpretation is the effective use of domain knowledge to assign structural information based on fragmentation patterns. The mass spectrometry query language (MassQL) aims to make this process accessible and applicable across multiple analysis platforms. While advanced computational methods are capable of predicting compound structures from fragmentation data, AI/ML approaches often rely on complex, opaque criteria that are difficult to interpret or modify. As a result, their predictive patterns cannot be readily translated into human-readable rules, such as those used in MassQL. Here, in this study, we introduce ChemEcho, a machine learning embedding method that converts tandem mass spectrometry data into sparse feature vectors containing peak and neutral mass subformulae to enhance explainable AI/ML-based methods. An advantage of this approach is that decision trees trained using these feature vectors can be directly translated to MassQL. Using a battery of decision trees trained using ChemEcho embeddings to predict molecular attributes, we generated over 1500 MassQL queries for 765 molecular features and evaluated their precision and recall. From these queries, the 50 highest-performing queries were integrated into the MassQL compendium. This set of generated MassQL queries included environmentally and biologically relevant classes such as PFAS and molecules containing phosphate or sulfate substructures. To illustrate the impact these queries would have on a typical metabolomics experiment, these MassQL queries were applied to a public metabolomics data set─resulting in a marked increase in the structural information derived from tandem mass spectra. Access and reuse of these queries is expected to enhance structural annotation in untargeted experiments, leading to more specific claims and advancing many applications in metabolomics.

Harwood, Thomas V. [USDOE Joint Genome Institute (↗
DOE OSTI2019

Charge Movement and Structural Changes in the Gas-Phase Unfolding of Multimeric Protein Complexes Captured by Native Top-Down Mass Spectrometry

The extent to which noncovalent protein complexes retain native structure in the gas phase is highly dependent on experimental conditions. Energetic collisions with background gas can cause structural changes ranging from unfolding to subunit dissociation. Additionally, recent studies have highlighted the role of charge in such structural changes, but the mechanism is not completely understood. In this study, native top down (native TD) mass spectrometry was used to probe gas-phase structural changes of alcohol dehydrogenase (ADH, 4mer) under varying degrees of in-source activation. Changes in covalent backbone fragments produced by electron capture dissociation (ECD) or 193 nm ultraviolet photodissociation (UVPD) were correlated to structural changes of the ADH 4mer. ECD fragments indicated unfolding started at the N-terminus, and the charge states of UVPD fragments enabled monitoring of charge migration to the unfolded regions. Interestingly, UVPD fragments also indicated that the charge at the “unfolding” N-terminus of ADH decreased at high in-source activation energies after the initial increase. We proposed a possible “refolding-after-unfolding” mechanism, as further supported by monitoring hydrogen elimination from radical a-ions produced by UVPD at the N-terminus of ADH. However, “refolding-after-unfolding” with increasing in-source activation was not observed for charge-reduced ADH, which likely adopted compact structures that are resistant to both charge migration and unfolding. Combined, these results support a charge-directed unfolding mechanism for protein complexes. Overall, an experimental framework was outlined for utilizing native TD to generate structure-informative mass spectral signatures for protein complexes that complement other structure characterization techniques, such as ion mobility spectrometry and computational modeling.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Activation of CO 2 by Actinide Cations (Th + , U + , Pu + , and Am + ) as Studied by Guided Ion Beam and Triple Quadrupole Mass Spectrometry

Reactions of CO 2 with Th+ have been studied using guided ion beam tandem mass spectrometry (GIBMS) and with An + (An + = Th + , U + , Pu + , and Am + ) using triple quadrupole inductively coupled plasma mass spectrometry (QQQ-ICP-MS). Additionally, the reactions ThO + + CO and ThO + + CO 2 were examined using GIBMS. Modeling the kinetic energy dependent GIBMS data allowed determination of bond dissociation energies (BDEs) for D o (Th + -O) and D o (OTh + -O) that are in reasonable agreement with previous GIBMS measurements. The QQQ-ICP-MS reactions were studied at higher pressures where multiple collisions between An + and the neutral CO 2 occur. As a consequence, both AnO + and AnO 2 + products were observed for all An + except Am + , where only AmO + was observed. Here, the relative abundances of the observed monoxides compared to the dioxides are consistent with previous reports of the AnO n + (n = 1, 2) BDEs. Comparison of the periodic trends of the group 4 transition metal, lanthanide (Ln), and actinide atomic cations in reactions with CO 2 (a formally spin-forbidden reaction for most M + ground states), and O 2 (a spin unrestricted reaction) indicate that spin conservation plays a minor role, if any, for the heavier An + metals. Further correlation of Ln + and An + + CO 2 reaction efficiencies with the promotion energy (E p ) to the first electronic state with two valence d-electrons (E p (5d 2 ) for Ln + and E p (6d 2 ) for An + ) indicates that the primary limitation in the activation of CO 2 is the energetic cost to promote from the electronic ground state of the atomic metal ion to a reactive state.

bond activation↗
DOE OSTI2026

Transient Pulse-Response Time-of-Flight Mass Spectrometry for Complex, Deactivating Heterogeneous Catalytic Systems: Application to Ethane Dehydroaromatization

The study of complex, multistep bond-forming and -breaking reactions in heterogeneous catalytic systems often encounters challenges associated with the involvement of large numbers of intermediates among branching pathways. Kinetic information obtained from traditional steady-state measurements can be complemented with that from time-resolved methods to uncover details of the underlying chemistry. Herein, we describe an approach for tracking the complete time-resolved chemical composition (ca. 4–200 u) of a reactor effluent in response to a reactant pulse. We use a six-port rotary valve with a metered sampling loop to pulse reactants at ambient pressure into a flow reactor packed with a catalyst bed within the isothermal region of a heated furnace. The temporal evolution of effluent species is tracked using time-resolved molecular-beam time-of-flight mass spectrometry. We highlight the possibilities that this method has to offer by studying the complex bifunctional mechanism of ethane dehydroaromatization over an HZSM-5-supported platinum catalyst. We demonstrate that energy-tunable ionization sources, which facilitate isomer resolution, enable the measurement of the full mass spectral time-dependent system response. This includes the evolution of major products and mechanistically relevant reactive intermediates such as 1,3-butadiene and cyclopentadiene; these species have not previously been observed from this reaction. In additional studies, we also assess the role of platinum in the catalyst by examining temporal responses to ethane and ethylene feeds. Results show that two temporally distinct formation pathways exist for methane and benzene, and that their importance depends on both catalyst composition and reactant identity. Additionally, characteristics of catalyst deactivation are uniquely observable in the time-resolved mass spectral response, including the selective deactivation of a benzene formation pathway. The combination of time-of-flight mass spectrometry with tunable ionization enables the simultaneous observation of all effluents in a complex mixture of intermediates with isomer/isobar differentiation capabilities that can be applied to any complex reaction system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Ion Mobility Spectrometry Characterization of the Intermediate Hydrogen-Containing Gold Cluster Au7(PPh3)7H52+

We employ ion mobility spectrometry and density functional theory to determine the structure of Au7(PPh3)7H52+ (PPh3 = triphenylphosphine) which was recently identified by high mass resolution mass spectrometry. Experimental ion-neutral collision cross sections represent the momentum transfer between the ionic clusters and gas molecules averaged over the relative thermal velocities of the colliding pair, thereby providing structural insights. Theoretical calculations indicate the geometry of Au7(PPh3)7H52+ is similar to Au7(PPh3)7+, with three hydrogen atoms bridging two gold atoms and two hydrogen atoms forming single Au–H bonds. Collision induced dissociation products observed during IMS experiments reveal that smaller hydrogen containing clusters may be produced through fragmentation of Au7(PPh3)7H52+. Our findings indicate that hydrogen containing species like Au7(PPh3)7H52+ act as intermediates in the formation of larger phosphine ligated gold clusters. These results advance the understanding and ability to control the mechanisms of size selective cluster formation which is necessary for scalable synthesis of clusters with tailored properties. This work was supported by the U.S. Department of Energy (DOE), Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. M.A.H. acknowledges support from the DOE Science Undergraduate Laboratory Internship (SULI) program. H.H. acknowledges support from the DOE Office of Workforce Development for Teachers and Scientist (WDTS) under the Visiting Faculty Program (VFP). The efforts of K.A.M. and B.H.C. were supported by the Defense Threat Reduction Agency (Grant No. HDTRA1-14-1-0023). The research was performed using EMSL, a national scientific user facility sponsored by the DOE’s Office of Biological and Environmental Research and located at Pacific Northwest National Laboratory (PNNL). PNNL is operated by Battelle for DOE under Contract DE-AC05-76RL01830.

Ligare, Marshall R.↗
DOE OSTI2023

Array-Based Machine Learning for Functional Group Detection in Electron Ionization Mass Spectrometry

Mass spectrometry is a ubiquitous technique capable of complex chemical analysis. The fragmentation patterns that appear in mass spectrometry are an excellent target for artificial intelligence methods to automate and expedite the analysis of data to identify targets such as functional groups. To develop this approach, we trained models on electron ionization (a reproducible hard fragmentation technique) mass spectra so that not only the final model accuracies but also the reasoning behind model assignments could be evaluated. The convolutional neural network (CNN) models were trained on 2D images of the spectra using transfer learning of Inception V3, and the logistic regression models were trained using array-based data and Scikit Learn implementation in Python. Our training dataset consisted of 21,166 mass spectra from the United States’ National Institute of Standards and Technology (NIST) Webbook. The data was used to train models to identify functional groups, both specific (e.g., amines, esters) and generalized classifications (aromatics, oxygen-containing functional groups, and nitrogen-containing functional groups). We found that the highest final accuracies on identifying new data were observed using logistic regression rather than transfer learning on CNN models. It was also determined that the mass range most beneficial for functional group analysis is 0–100 m/z. We also found success in correctly identifying functional groups of example molecules selected from both the NIST database and experimental data. Beyond functional group analysis, we also have developed a methodology to identify impactful fragments for the accurate detection of the models’ targets. The results demonstrate a potential pathway for analyzing and screening substantial amounts of mass spectral data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Applying Multimodal Mass Spectrometry to Image Tumors Undergoing Ferroptosis Following In Vivo Treatment with a Ferroptosis Inducer

Epithelial ovarian cancer (EOC) is the most common form of ovarian cancer. The poor prognosis generally associated with this disease has led to the search for improved therapies such as ferroptosis-inducing agents. Ferroptosis is a form of regulated cell death that is dependent on iron and is characterized by lipid peroxidation. Precise mapping of lipids and iron within tumors exposed to ferroptosis-inducing agents may provide insight into processes of ferroptosis in vivo and ultimately assist in the optimal deployment of ferroptosis inducers in cancer therapy. In this work, we present a method for combining matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) with secondary ion mass spectrometry (SIMS) to analyze changes in spatial lipidomics and metal composition, respectively, in ovarian tumors following exposure to a ferroptosis inducer. Tumors were obtained by injecting human ovarian cancer tumor-initiating cells into mice, followed by treatment with the ferroptosis inducer erastin. SIMS imaging detected iron accumulation in the tumor tissue, and sequential MALDI-MS imaging of the same tissue section displayed two chemically distinct regions of lipids. Additionally, one region was associated with the iron-rich area detected with SIMS, and the other region encompassed the remainder of the tissue section. Bulk lipidomics confirmed the lipid assignments putatively assigned from the MALDI-MS data. Overall, we demonstrate the ability of multimodal MSI to identify the spatial locations of iron and lipids in the same tissue section and associate these regions with clinical pathology.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

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↗
DOE OSTI2020

Toward nanoscale molecular mass spectrometry imaging via physically constrained machine learning on co-registered multimodal data

Mass spectrometry imaging (MSI) plays a pivotal role in investigating the chemical nature of complex systems that underly our understanding in biology and medicine. Multiple fields of life science such as proteomics, lipidomics and metabolomics benefit from the ability to simultaneously identify molecules and pinpoint their distribution across a sample. However, achieving the necessary submicron spatial resolution to distinguish chemical differences between individual cells and generating intact molecular spectra is still a challenge with any single imaging approach. Here, we developed an approach that combines two MSI techniques, matrix-assisted laser desorption/ionization (MALDI) and time-of-flight secondary ion mass spectrometry (ToF-SIMS), one with low spatial resolution but intact molecular spectra and the other with nanometer spatial resolution but fragmented molecular signatures, to predict molecular MSI spectra with submicron spatial resolution. The known relationships between the two MSI channels of information are enforced via a physically constrained machine-learning approach and directly incorporated in the data processing. We demonstrate the robustness of this method by generating intact molecular MALDI-type spectra and chemical maps at ToF-SIMS resolution when imaging mouse brain thin tissue sections. This approach can be readily adopted for other types of bioimaging where physical relationships between methods have to be considered to boost the confidence in the reconstruction product.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

GNPS Dashboard: collaborative exploration 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.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

A multiplexed nanostructure-initiator mass spectrometry (NIMS) assay for simultaneously detecting glycosyl hydrolase and lignin modifying enzyme activities

Lignocellulosic biomass is composed of three major biopolymers: cellulose, hemicellulose and lignin. Analytical tools capable of quickly detecting both glycan and lignin deconstruction are needed to support the development and characterization of efficient enzymes/enzyme cocktails. Previously we have described nanostructure-initiator mass spectrometry-based assays for the analysis of glycosyl hydrolase and most recently an assay for lignin modifying enzymes. Here we integrate these two assays into a single multiplexed assay against both classes of enzymes and use it to characterize crude commercial enzyme mixtures. Application of our multiplexed platform based on nanostructure-initiator mass spectrometry enabled us to characterize crude mixtures of laccase enzymes from fungi Agaricus bisporus (Ab) and Myceliopthora thermophila (Mt) revealing activity on both carbohydrate and aromatic substrates. Using time-series analysis we determined that crude laccase from Ab has the higher GH activity and that laccase from Mt has the higher activity against our lignin model compound. Inhibitor studies showed a significant reduction in Mt GH activity under low oxygen conditions and increased activities in the presence of vanillin (common GH inhibitor). Ultimately, this assay can help to discover mixtures of enzymes that could be incorporated into biomass pretreatments to deconstruct diverse components of lignocellulosic biomass.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗