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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 OSTI2023

IsoMatchMS : Open-Source Software for Automated Annotation and Visualization of High Resolution MALDI-MS Spectra

Due to its speed, accuracy, and adaptability to various sample types, matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has become a popular method to identify molecular isotope profiles from biological samples. Often MALDI-MS data do not include tandem MS fragmentation data, and thus the identification of compounds in samples requires external databases so that the accurate mass of detected signals can be matched to known molecular compounds. Most relevant MALDI-MS software tools developed to confirm compound identifications are focused on small molecules (e.g., metabolites, lipids) and cannot be easily adapted to protein data due to their more complex isotopic distributions. Here, we present an R package called IsoMatchMS for the automated annotation of MALDI-MS data for multiple datatypes: intact proteins, peptides, and glycans. This tool accepts already derived molecular formulas or, for proteomics applications, can derive molecular formulas from a list of input peptides or proteins including proteins with post-translational modifications. In conclusion, visualization of all matched isotopic profiles is provided in a highly accessible HTML format called a trelliscope display, which allows users to filter and sort by several parameters such as match scores and the number of peaks matched. IsoMatchMS simplifies the annotation and visualization of MALDI-MS data for downstream analyses.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Native Top-Down Mass Spectrometry Characterization of Model Integral Membrane Protein Bacteriorhodopsin

Bacteriorhodopsin (bR) from Halobacterium salinarum has been a model system for structural biology and is a structural template for the characterization of membrane G-protein couple receptors (GPCRs) in particular. Here, in this study, wild-type bacteriorhodopsin and two single-residue mutants were characterized by native top-down mass spectrometry (nTD-MS) with Orbitrap-based high-energy collision dissociation (HCD) and electron capture dissociation (ECD). After in-source dissociation ejected the membrane protein from detergent micelles, high-resolution native MS measurement allowed for identification of multiple proteoforms as well as lipid-bound forms. Further top-down MS measurements by HCD produced a large number of product ions for in-depth sequencing and unambiguous localization of post-translational modifications. For the first time, native TD-MS with ECD was used to characterize an integral membrane protein. ECD yielded fragments originating from all helices and loop regions, even accessing a sequence stretch that HCD could not. Combining HCD and ECD fragmentation patterns significantly enhanced the sequence coverage of bR. We propose bR to be a model analyte for testing nTD-MS performance for membrane proteins.

crystal cleavage↗
DOE OSTI2026

Leveraging 13C-Labeling to Assign Molecular Formulas to Unknown Yeast Metabolites

Mass spectrometry analyses have identified tens of thousands of unknown small molecule-associated peaks in different biological specimens. Notably, even the simplest and best studied organisms like Escherichia coli and Saccharomyces cerevisiae yield thousands of unknown peaks. A key question is how many of these reflect actual novel endogenous metabolites. To explore this, Mahieu and Patti used complete 13 C -labeling in E. coli to credential peaks as biological. This reduced the number of unknowns by more than 90%. Here, we carry out similar uniform 13 C-labeling in the Baker’s yeast S. cerevisiae and two less-studied bioenergy-relevant yeasts Rhodotorula toruloides (lipid producer) and Issatchenkia orientalis (organic acid producer). Identification of unknown metabolite peaks and their molecular formulas is facilitated through software tailored for 13 C labeling data and resulting knowledge of carbon atom count. A classification model evaluates the plausibility of each candidate formula, with peaks lacking plausible candidate formulas unlikely to reflect metabolite molecular ions. This approach prioritizes about one hundred candidate abundant unknown metabolites with logical molecular formulas. Most of these are species-specific rather than conserved across yeasts, and more are found in the nonmodel yeasts than S. cerevisiae. Thus, 13 C-labeling data on unknown metabolites highlights the potential for discovering new metabolites and pathways in nonmodel yeasts.

Carbon↗
NASA NTRS1995

Identification And Survival Of Bacteriohopanepolyol In A Hot Spring Microbial Mat

The polar lipids of a hot spring microbial mat located in Yellowstone National Park were examined for the presence of bacteriohopanepolvols (BHP). BHP are a group of molecules consisting of a hopanoid (peotacyclic triterpene) linked via a n-alkyl polyhydroxylated chain to a variety of polar end groups. BHP have been isolated in varying amounts from phylogenetically diverse eubacterial groups including cyanobacteria, methanotrophs and the Rhodospirillaceae. The hopanoids are excellent biomarkers and have been detected in sedimentary rocks as old as 1.7 bya. In order to interpret the ancient organic record, it is important to understand the abundance, source and fate of such biomarker compounds in microbial mats. A 40 sq cm mat section was taken from a 52 to 55 C site in the effluent channel of Octopus Spring and was sampled vertically over approximately 16 mm. The first 5-6 mm was sectioned into a top green layer (310 mg dry weight) and several subjacent, deep orange layers (240 and 250 mg, respectively). The lower 10 mm of the mat was sectioned into two gelatinous orange layers containing a siliceous gritty material (260 and 440 mg) which increased with depth, and a bottom layer composed almost exclusively of siliceous sinter (4.1 g). The progressive decrease in total organic carbon from 45% in the top green layer to only 4% in the bottom layer reflects the observed increase in siliceous deposition. GC-MS analysis of the phospholipid and glycolipid fatty acids yielded predominantly saturated normal chain acids, n-15 to n-18, and iso-branched acids, i-15 to i-17. Small amounts of unsaturated fatty acids (16:1, two positional isomers of 18:1, and two cyclopropyl acids, C(sub 17) and C(sub 19)) were present mainly in the top layer. Esterified fatty acid which is a good index for intact cellular membrane, i.e. viable organisms, was highest in the top two layers (203 and 231 micro g/mg total lipid, respectively) and gradually decreased to 66 micro g/mg total lipid in the bottom layer. Small amounts of BHP were present in all six layers, however in this case, BHP was lowest in the top green and subjacent deep-orange layers (118 and 172 micro g/mg total lipid, respectively) and increased with depth reaching almost 400 micro g/mg in the bottom two layers. This data suggest that BHP are survivina the initial phase of mat degradation and may be preferentially enriched in any organic record of such thermal environments. The relatively low level of BHP in the top layer also suggests that cyanobacteria may not be the major source of BHP in this mat. Since Chloroflexus a major component of the deep-orange layer has been reported to lack BHP, this material may prove a valuable biomarker for some other mat inhabitant. Further isotopic characterization of this BHP should help resolve this finding.

Janke, Linda L.↗
DOE OSTI2021

How lipidomics can transform our understanding of virus infections

Traditionally, lipids have been thought of as molecules that provide structure and energy, but their functional relevance in disease mechanisms is increasingly clear, and with advancements in mass spectrometry technologies, lipidomics analyses is a tool gaining recognition. Beyond the utility of lipoprotein and fatty acid profiles in clinical diagnosis and chemotaxonomic identifications, respectively, lipidomics analysis that combines knowledge across disciplines and can resolve exact lipid structures has the potential to advance clinical diagnoses and associated treatment, differentiate pathogen types (e.g., virus vs. bacterial vs. fungal), detect natural vs lab-grown viruses, and perhaps distinguish a pathogen from a benign biological agent (i.e., threat potential). As new viruses emerge and localized outbreaks expand, lipidomics will accelerate our understanding of viral infections and aid in maximizing the discovery of novel biomarkers of pathogenicity and host response.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Carbon source–driven metabolic and regulatory remodeling defines phenomic states in Lipomyces starkeyi

Lipomyces is a genus of oleaginous yeasts with potential for contributing to reliable biomanufacturing supply chains. However, progress in advanced strain designs and engineering efforts are still constrained by a lack of understanding of the underlying molecular drivers of Lipomyces phenotypes. To address this gap, we collected a suite of multi-omic data to dissect how carbon source availability reshapes the metabolic network, lipid allocation, and regulatory architecture of Lipomyces starkeyi. We observed that glucose promotes biosynthetic and proliferative processes supported by abundant energy and carbon intermediates, xylose enhances redox-balancing mechanisms centered on the pentose phosphate pathway, and glycerol activates respiratory metabolism, ß-oxidation, and the glyoxylate cycle. Lipid species distributions remained consistent in both nitrogen replete and depleted conditions across the carbon sources, indicating robust production mechanisms. Regulatory protein identification and network analysis revealed glycerol-driven respiratory growth favors regulatory programs integrating stress tolerance, redox balance, and lipid-associated metabolism, whereas xylose growth activates compensatory transcriptional responses aimed at maintaining mitochondrial function. Nitrogen limitation modulates the strength of these responses but does not fundamentally alter their direction, reinforcing carbon source as the dominant driver of regulatory architecture. Taken together, this data enhances the understanding of Lipomyces molecular rearrangements and provides a foundation for further development of predictive phenotypic tools in this genus.

Biotechnology↗
DOE OSTI2020

Photodamage and Repair in Higher Plant Photosynthesis (Final Technical Report)

Elucidation of the functional properties and structural organization of membrane protein complexes is one of the central objectives of current biochemical investigation. One of the most intriguing aspects of membrane protein function is its role in the mediation of energy transduction in photosynthetic organisms. Light energy, which is the product of a most violent physical process, fusion, is transformed into biological energy equivalents utilized by the photosynthetic cell. This photosynthetic process provides both the carbohydrate that lies at the base of virtually all food chains and, as a byproduct, all of the atmospheric oxygen utilized by heterotrophic organisms. The photosynthetic apparatus, however, is quite susceptible to damage by Reactive Oxygen Species (ROS). These species include O2 ·– , ·OH, H 2 O 2 and 1 O 2 . The production of ROS is an unavoidable byproduct of electron transport under aerobic conditions and these can damage lipids, nucleic acids and proteins. Our research has centered on the identification of amino acid oxidative damage which occurs in the vicinity of photosynthetic energy transfer cofactors. These cofactors participate in excitation energy transfer and linear electron transport within Photosystem II, the Cytochrome b 6 ƒ complex and Photosystem I. Additionally, we have participated in a number of productive collaborations leveraging our expertise in photosynthetic measurements and mass spectrometry to assist other investigators in their research.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A Dual-Gated Structures for Lossless Ion Manipulations-Ion Mobility Orbitrap Mass Spectrometry Platform for Combined Ultra-High-Resolution Molecular Analysis

High-resolution ion mobility spectrometry-mass spectrometry (HR-IMS-MS) instruments have enormously advanced the ability to characterize complex biological mixtures. Unfortunately, HR-IMS and HR-MS measurements are typically performed independently due to mismatches in analysis time scales. Here we overcome this limitation by using a dual-gated ion injection approach to couple an 11-meter path length structures for lossless ion manipulations (SLIM) module to a Q-Exactive Plus Orbitrap MS. The dual-gate setup was implemented by placing one ion gate before the SLIM module and a second ion gate after. The dual-gated ion injection approach allowed the new SLIM-Orbitrap platform to simultaneously perform an 11-meter SLIM separation, Orbitrap mass analysis using the highest selectable mass resolution setting (up to 140k), and high-energy collision induced dissociation (HCD) in ~25 minutes over an $m/z$ range of ~1500 amu. The SLIM-Orbitrap was initially characterized using a mixture of standard phosphazene cations and demonstrated an average SLIM CCS resolving power (Rp CCS ) of ~218 and SLIM peak capacity of ~156 while simultaneously obtaining high mass resolutions. SLIM-Orbitrap analysis with fragmentation was then performed on mixtures of standard peptides and two reverse peptides (SDGRG 1+ , GRGDS 1+ , Rp CCS = 305) to demonstrate the utility of combined HR-IMS-MS/MS measurements for peptide identification. Our new HR-IMS-MS/MS capability was further demonstrated by analyzing a complex lipid mixture and showcasing SLIM separations on isobaric lipids. In conclusion, this new SLIM-Orbitrap platform demonstrates a critical new capability for proteomics and lipidomics applications, and the high-resolution multimodal data obtainable with this system establishes the foundation for reference-free identification of unknown ion structures.

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

Identification of triacylglycerol remodeling mechanism to synthesize unusual fatty acid containing oils

Abstract Typical plant membranes and storage lipids are comprised of five common fatty acids yet over 450 unusual fatty acids accumulate in seed oils of various plant species. Plant oils are important human and animal nutrients, while some unusual fatty acids such as hydroxylated fatty acids (HFA) are used in the chemical industry (lubricants, paints, polymers, cosmetics, etc.). Most unusual fatty acids are extracted from non-agronomic crops leading to high production costs. Attempts to engineer HFA into crops are unsuccessful due to bottlenecks in the overlapping pathways of oil and membrane lipid synthesis where HFA are not compatible. Physaria fendleri naturally overcomes these bottlenecks through a triacylglycerol (TAG) remodeling mechanism where HFA are incorporated into TAG after initial synthesis. TAG remodeling involves a unique TAG lipase and two diacylglycerol acyltransferases (DGAT) that are selective for different stereochemical and acyl-containing species of diacylglycerol within a synthesis, partial degradation, and resynthesis cycle. The TAG lipase interacts with DGAT1, localizes to the endoplasmic reticulum (with the DGATs) and to puncta around the lipid droplet, likely forming a TAG remodeling metabolon near the lipid droplet-ER junction. Each characterized DGAT and TAG lipase can increase HFA accumulation in engineered seed oils.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Fractionation of Filamentous Algae from Mixed Biofilms

Filamentous algae, which grow in long, hair-like filaments within biofilms, play a crucial role in wastewater treatment due to their ability to produce significant biomass and their resistance to predation compared to traditional microalgal treatments. These algae can effectively uptake and utilize pollutants, particularly excessive nitrogen (ammonia, nitrate, nitrite) and phosphorus (phosphate), making filamentous algae valuable for wastewater treatment, as well as bioethanol and biodiesel production due to high lipid productions. However, each algal species possesses different capacities, necessitating a thorough genetic identification and understanding of each community. A major challenge in accurately assessing these communities is the lack of coverage in large sequencing databases which can lead to misrepresentation of the true composition and abundance of organisms and overall sequencing bias. To address this, I evaluated chemical and physical techniques for separating filamentous algae from mixed biofilms to achieve clean genetic sequencing results. I employed pH washing (0.001M HCl, 0.001M HCl, DiH2O, 0.0001M HCl, 0.001M HCl) for chemical treatment, followed by physical separation through centrifugation (5000rpm, 6500rpm) or filtration (2mm, 250um, 75um). The most successful method was deionized water washing, which yielded clear differences across stacked filters; the 2mm filtrate showed high levels of filamentous algae, with microalgae eluting in the 75um filtrate or remaining within agglutinations of algae larger filters. Base washing eluted the highest concentrations of microalgae, with larger filter sizes retaining more filamentous algae, indicating the breakdown of extracellular polymeric substances (EPS). Our downstream plans include sending the high-throughput next-generation sequencing to confirm the purity and ratios of filamentous and non-filamentous algae, as well as bacteria present, thereby validating the success of our treatments. Potential applications include creating community-based fractions for analysis, refining current sequencing data with clearer isolations, and generating designer biofilms to enhance our understanding of community interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

A glimpse into the fungal metabolomic abyss: Novel network analysis reveals relationships between exogenous compounds and their outputs

Fungal specialized metabolites are a major source of beneficial compounds that are routinely isolated, characterized, and manufactured as pharmaceuticals, agrochemical agents, and industrial chemicals. The production of these metabolites is encoded by biosynthetic gene clusters that are often silent under standard growth conditions. There are limited resources for characterizing the direct link between abiotic stimuli and metabolite production. Herein, we introduce a network analysis-based, data-driven algorithm comprising two routes to characterize the production of specialized fungal metabolites triggered by different exogenous compounds: the direct route and the auxiliary route. Both routes elucidate the influence of treatments on the production of specialized metabolites from experimental data. The direct route determines known and putative metabolites induced by treatments and provides additional insight over traditional comparison methods. The auxiliary route is specific for discovering unknown analytes, and further identification can be curated through online bioinformatic resources. We validated our algorithm by applying chitooligosaccharides and lipids at two different temperatures to the fungal pathogen Aspergillus fumigatus. After liquid chromatography–mass spectrometry quantification of significantly produced analytes, we used network centrality measures to rank the treatments’ ability to elucidate these analytes and confirmed their identity through fragmentation patterns or in silico spiking with commercially available standards. Later, we examined the transcriptional regulation of these metabolites through real-time quantitative polymerase chain reaction. Our data-driven techniques can complement existing metabolomic network analysis by providing an approach to track the influence of any exogenous stimuli on metabolite production. Our experimental-based algorithm can overcome the bottlenecks in elucidating novel fungal compounds used in drug discovery.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Identification of the prooxidant site of human ceruloplasmin: a model for oxidative damage by copper bound to protein surfaces

Free transition metal ions oxidize lipids and lipoproteins in vitro; however, recent evidence suggests that free metal ion-independent mechanisms are more likely in vivo. We have shown previously that human ceruloplasmin (Cp), a serum protein containing seven Cu atoms, induces low density lipoprotein oxidation in vitro and that the activity depends on the presence of a single, chelatable Cu atom. We here use biochemical and molecular approaches to determine the site responsible for Cp prooxidant activity. Experiments with the His-specific reagent diethylpyrocarbonate (DEPC) showed that one or more His residues was specifically required. Quantitative [14C]DEPC binding studies indicated the importance of a single His residue because only one was exposed upon removal of the prooxidant Cu. Plasmin digestion of [14C]DEPC-treated Cp (and N-terminal sequence analysis of the fragments) showed that the critical His was in a 17-kDa region containing four His residues in the second major sequence homology domain of Cp. A full length human Cp cDNA was modified by site-directed mutagenesis to give His-to-Ala substitutions at each of the four positions and was transfected into COS-7 cells, and low density lipoprotein oxidation was measured. The prooxidant site was localized to a region containing His426 because CpH426A almost completely lacked prooxidant activity whereas the other mutants expressed normal activity. These observations support the hypothesis that Cu bound at specific sites on protein surfaces can cause oxidative damage to macromolecules in their environment. Cp may serve as a model protein for understanding mechanisms of oxidant damage by copper-containing (or -binding) proteins such as Cu, Zn superoxide dismutase, and amyloid precursor protein.

NASA Discipline Regulatory Physiology↗
DOE OSTI2023

Systematic review of type 1 diabetes biomarkers reveals regulation in circulating proteins related to complement, lipid metabolism, and immune response

Type 1 diabetes (T1D) results from an autoimmune attack of the pancreatic β cells that progresses to dysglycemia and symptomatic hyperglycemia. Current biomarkers to track this evolution are limited, with development of islet autoantibodies marking the onset of autoimmunity and metabolic tests used to detect dysglycemia. Therefore, additional biomarkers are needed to better track disease initiation and progression. Multiple clinical studies have used proteomics to identify biomarker candidates. However, most of the studies were limited to the initial candidate identification, which needs to be further validated and have assays developed for clinical use. Here we curate these studies to help prioritize biomarker candidates for validation studies and to obtain a broader view of processes regulated during disease development. This systematic review was registered with Open Science Framework (https://doi.org/10.17605/OSF.IO/N8TSA). Using PRISMA guidelines, we conducted a systematic search of proteomics studies of T1D in the PubMed to identify putative protein biomarkers of the disease. Studies that performed mass spectrometry-based untargeted/targeted proteomic analysis of human serum/plasma of control, pre-seroconversion, post-seroconversion, and/or T1D-diagnosed subjects were included. For unbiased screening, 3 reviewers screened all the articles independently using the pre-determined criteria. A total of 13 studies met our inclusion criteria, resulting in the identification of 266 unique proteins, with 31 (11.6%) being identified across 3 or more studies. The circulating protein biomarkers were found to be enriched in complement, lipid metabolism, and immune response pathways, all of which are found to be dysregulated in different phases of T1D development. We found 2 subsets: 17 proteins (C3, C1R, C8G, C4B, IBP2, IBP3, ITIH1, ITIH2, BTD, APOE, TETN, C1S, C6A3, SAA4, ALS, SEPP1 and PI16) and 3 proteins (C3, CLUS and C4A) have consistent regulation in at least 2 independent studies at post-seroconversion and post-diagnosis compared to controls, respectively, making them strong candidates for clinical assay development. Biomarkers analyzed in this systematic review highlight alterations in specific biological processes in T1D, including complement, lipid metabolism, and immune response pathways, and may have potential for further use in the clinic as prognostic or diagnostic assays.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

ToF-SIMS spectral data analysis of Paenibacillus sp. 300A biofilms and planktonic cells

Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many promising features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution and high mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Paenibacillus sp. 300A (300A) isolated from the Hanford site in Richland, WA. The strain is known to have metal and sulfur reducing properties and can be used for bioremediation, wastewater treatment, bioengineering and technology development. There is a current need to identify small molecules and fragments produced from bacterial biofilms. Static ToF-SIMS spectra of 300A were obtained using an IONTOF TOF-SIMS V instrument equipped with a 25 keV Bi 3 + metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids and fatty acids to flavonoids, quinolones, and other naturally occurring organic compounds. It is anticipated that the spectral identification of key peaks will assist detection of metabolites, extracellular polymeric substance molecules like polysaccharides, and biologically relevant small molecules using ToF-SIMS in future surface and interface research of bacterial biofilms.

Biofilms↗
DOE OSTI2024

ToF-SIMS spectral analysis of Shewanella oneidensis MR-1 biofilms

Analysis of bacterial biofilms is particularly challenging and important with diverse applications from systems biology to biotechnology. Among the variety of techniques that have been applied, time-of-flight secondary ion mass spectrometry (ToF-SIMS) has many powerful features in studying the surface characteristics of biofilms. ToF-SIMS offers high spatial resolution, mass resolution, and mass accuracy, which permit surface sensitive analysis of biofilm components. Thus, ToF-SIMS provides a powerful solution to addressing the challenge of bacterial biofilm analysis. This dataset covers ToF-SIMS analysis of Shewanella oneidensis MR-1 isolated from freshwater lake sediment in New York state. The MR-1 strain is known to have metal and sulfur reducing properties and it can be used for bioremediation and wastewater treatment. There is a current need to identify small molecules and fragments produced from bacterial biofilms, especially those from extracellular polymeric substance (EPS). Static ToF-SIMS spectra of MR-1 were obtained using an IONTOF TOF.SIMS V instrument equipped with a 25 keV Bi$^+_3$ metal ion gun. Identified molecules and molecular fragments are compared against known biological databases and the reported peaks have at least 65 ppm mass accuracy. These molecules range from lipids, fatty acids, flavonoids, and quinolones to other naturally occurring organic compounds. It is anticipated that the mass spectral identification of key peaks will assist detection of metabolites, EPS molecules like polysaccharides, and biologically relevant small organic molecules using ToF-SIMS in future surface and interface research.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1997

Mechanosensitive channels of Escherichia coli: the MscL gene, protein, and activities

Although mechanosensory responses are ubiquitous and diverse, the molecular bases of mechanosensation in most cases remain mysterious MscL, a mechanosensitive channel of large conductance of Escherichia coli and its bacterial homologues are the first and currently only channel molecules shown to directly sense mechanical stretch of the membrane. In response to the tension conveyed via the lipid bilayer, MscL increases its open probability by several orders of magnitude. In the present review we describe the identification, cloning, and first sets of biophysical and structural data on this simplest mechanosensory molecule. We discovered a 2.5-ns mechanosensitive conductance in giant E. coli spheroplasts. Using chromatographies to enrich the target and patch clamp to assay the channel activity in liposome-reconstituted fractions, we identified the MscL protein and cloned the mscL gene. MscL comprises 136 amino acid residues (15 kDa), with two highly hydrophobic regions, and resides in the inner membrane of the bacterium. PhoA-fusion experiments indicate that the protein spans the membrane twice with both termini in the cytoplasm. Spectroscopic techniques show that it is highly helical. Expression of MscL tandems and covalent cross-linking suggest that the active channel complex is a homo-hexamer. We have identified several residues, which when deleted or substituted, affect channel kinetics or mechanosensitivity. Although unique when discovered, highly conserved MscL homologues in both gram-negative and gram-positive bacteria have been found, suggesting their ubiquitous importance among bacteria.

Non-NASA Center↗
DOE OSTI2021

Interpreting the Lipidome: Bioinformatic Approaches to Embrace the Complexity

Background Improvements in mass spectrometry (MS) technologies coupled with bioinformatics developments have allowed considerable advancement in the measurement and interpretation of lipidomics data in recent years. Since research areas employing lipidomics are rapidly increasing, there is a great need for bioinformatic tools that capture and utilize the complexity of the data. Currently, the diversity and complexity within the lipidome is often concealed by summing over or averaging individual lipids up to (sub)class-based descriptors, losing valuable information about biological function and interactions with other distinct lipids molecules, proteins and/or metabolites. Aim of review To address this gap in knowledge, novel bioinformatics methods are needed to improve identification, quantification, integration and interpretation of lipidomics data. The purpose of this mini-review is to summarize exemplary methods to explore the complexity of the lipidome. Key scientific concepts of review Here we describe six approaches that capture three core focus areas for lipidomics: (1) lipidome annotation including a resolvable database identifier, (2) interpretation via pathway- and enrichment-based methods, and (3) understanding complex interactions to emphasize specific steps in the analytical process and highlight challenges in analyses associated with the complexity of lipidome data.

Kyle, Jennifer E.↗
DOE OSTI2021

Identification and analysis of stem‐specific promoters from sugarcane and energy cane for oil accumulation in their stems

Abstract Considerable recent progress has been achieved in bioengineering oil accumulation in the vegetative tissues of plants, opening an opportunity for large scale production of biodiesel, jet fuel, lubricants, and high‐value lipid bioproducts. For the highly productive C4 crops, such as sugarcane, energy cane, Miscanthus, and fiber sorghums, the bulk of the biomass is the stem. However, little success has been made in accumulating oil in the stem. Since engineering a trait with a constitutive promoter often results in pleiotropic effects that counter trait improvement, identification of stem parenchyma‐specific promoters is a prerequisite for efficient use of the ample photoassimilates stored in mature stem parenchyma cells. In this study, we first identified two TST genes encoding homologues of tonoplast sugar transporters that were strongly and almost exclusively expressed in the stems of canes via a combination of RNA‐seq atlas analysis, in silico analysis of a sugarcane genome, phylogenetic analysis, and quantitative PCR analysis. They were further confirmed in the pith parenchyma cells of the mature stem by RNA in situ hybridization. When fused with the β‐Glucuronidase (GUS) reporter gene, the promoters of two alleles, TST2b‐1A and TST2b‐1C , from one TST gene demonstrated that they could drive the GUS expression exclusively in the stem in Arabidopsis.

09 BIOMASS FUELS↗