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At least 19 records

Methods and systems of proteome analysis and imaging

Provided herein are methods and systems for proteome analysis that are at least partially automated and/or performed robotically. In some aspects, the methods and systems described herein can rapidly and efficiently provide protein identification of each of the proteins from a proteome, or a complement of proteins, obtained from extremely small amounts of biological samples. The identified proteins can be imaged quantitatively over a spatial region. Automation and robotics facilitates the throughput of the methods and systems, which enables protein imaging and/or rapid proteome analysis.

Piehowski, Paul D.↗

Proteomics Analysis of Human Contaminant Proteins

Complete characterization of unknowns via proteomics remains challenging. There exist regions of mass spectrometry-based proteomics data where empirical measurements are not attributed to peptides, and/or sequenced peptides from mass spectra are not attributed to any source. These uncharacterized regions are known as the “dark” proteome. Many proteomics tools rely on some a priori knowledge of sample composition; few tools allow for investigation of unknowns without relying on composition assumptions. Further, the potential low abundance of minor traces in these uncharacterized regions can make elucidation of the “dark” proteome challenging. Herein, we describe the development and evaluation of approaches to study the “dark” proteome and move towards an untargeted approach for more complete characterization, namely by studying minor human protein traces in non-human samples and combining that approach with non-human source organism identification without relying on assumptions. Human protein markers, in the form of genetically variant peptides, have been extensively examined in a variety of human matrices, including blood, plasma, and hair, but have yet to be investigated in non-human samples, such as cell cultures, as human contaminant traces. Genetically variant peptides are those that are found in proteins carrying single nucleotide polymorphisms. In this work, we aimed to (1) investigate the feasibility of detecting human contaminant genetically variant peptides (GVPs) in a diverse set of non-human organisms using public proteomics data and a computational pipeline, as well as to (2) develop a combined capability for untargeted source organism characterization and GVP detection. To our knowledge, this is the first report of applying these approaches towards a more complete proteomic characterization of unknowns. We successfully demonstrate the feasibility of broad human contaminant GVP detection in proteomics data, develop a better understanding of GVP detectability, characterize the sample-to-sample variability in GVP detection, and identify a core set of GVPs that can potentially be used as markers indicative of the human contaminant traces portion of the “dark” proteome. Further, we developed and evaluated a combined pipeline, MARLOWE-GVP, that enables both untargeted source organism characterization and GVP detection. We show high accuracy of correct source organism characterization and high degree of similarity of human contaminant GVP detection compared to the conventional approach. Success on both these efforts have allowed us to advance our understanding and characterization of the “dark” proteome.

59 BASIC BIOLOGICAL SCIENCES↗

Unusual modifications of protein biomarkers expressed by plasmid, prophage, and bacterial host of pathogenic Escherichia coli identified using top‐down proteomic analysis

Rationale Pathogenic bacteria often carry prophage (bacterial viruses) and plasmids (small circular pieces of DNA) that may harbor toxin, antibacterial, and antibiotic resistance genes. Proteomic characterization of pathogenic bacteria should include the identification of host proteins and proteins produced by prophage and plasmid genomes. Methods Protein biomarkers of two strains of Shiga toxin–producingEscherichia coli(STEC) were identified using antibiotic induction, matrix‐assisted laser desorption/ionization tandem time‐of‐flight (MALDI‐TOF‐TOF) tandem mass spectrometry (MS/MS) with post‐source decay (PSD), top‐down proteomic (TDP) analysis, and plasmid sequencing. Alphafold2 was also used to compare predicted in silico structures of the identified proteins to prominent fragment ions generated using MS/MS‐PSD. Strain samples were also analyzed with and without chemical reduction treatment to detect the attachment of pendant groups bound by thioester or disulfide bonds. Results Shiga toxin was detected and/or identified in both STEC strains. For the first time, we also identified the osmotically inducible protein (OsmY) whose sequence unexpectedly had two forms: a full and a truncated sequence. The truncated OsmY terminates in the middle of an α‐helix as determined by Alphafold2. A plasmid‐encoded colicin immunity protein was also identified with and without attachment of an unidentified cysteine‐bound pendant group (~307 Da). Plasmid sequencing confirmed top‐down analysis and the identification of a promoter upstream of the immunity gene that is activated by antibiotic induction, that is, SOS box. Conclusions TDP analysis, coupled with other techniques (e.g., antibiotic induction, chemical reduction, plasmid sequencing, and in silico protein modeling), is a powerful tool to identify proteins (and their modifications), including prophage‐ and plasmid‐encoded proteins, produced by pathogenic microorganisms.

Biochemistry & Molecular Biology↗

Challenges and Opportunities in State‐of‐the‐Art Proteomics Analysis for Biomarker Development From Plasma Extracellular Vesicles

Extracellular vesicles (EVs) are membrane-bound particles secreted by cells, playing crucial roles in intercellular communication. The composition of EVs can undergo changes in response to stress and disease conditions, making them excellent biomarker candidates. However, extracting protein information from EVs can be challenging due to their low abundance in complex biofluids and copurification with contaminant proteins and particles. Techniques to enrich EVs have their strengths and limitations, without one being able to purify EVs to complete homogeneity. This can lead to compromised recovery rates and increased complexity, making data interpretation difficult. In this viewpoint article, we explore the concept that better characterization of EV composition, followed by quantification of EV proteins in complex samples, might be a more viable route for biomarker development. Mass spectrometers can provide reproducible deep coverage of the EV proteome, despite sample impurities. This paradigm shift presents opportunities to integrate advanced bioinformatics tools to refine the EV proteome landscape, identify novel biomarkers, and streamline validation processes in biomarker development. By focusing on leveraging technology rather than achieving absolute purity, this approach can transform current practices and open opportunities for robust biomarker discovery. Herein, we highlight not only such opportunities but also challenges to implement this concept.

Dakup, Panshak P. [Pacific Northwest National Labo↗

A fast and sensitive size-exclusion chromatography method for plasma extracellular vesicle proteomic analysis

Extracellular vesicles (EVs) carry diverse biomolecules derived from their parental cells, making their components excellent biomarker candidates. However, purifying EVs is a major hurdle in biomarker discovery since current methods require large amounts of samples, are time-consuming and typically have poor reproducibility. Here we describe a simple, fast, and sensitive EV fractionation method using size exclusion chromatography (SEC) on a fast protein liquid chromatography (FPLC) system. Our method uses a Superose 6 Increase 5/150, which has a bed volume of 2.9 mL. The FPLC system and small column size enable reproducible separation of only 50 µL of human plasma in 15 min. To demonstrate the utility of our method, we used longitudinal samples from a group of individuals who underwent intense exercise. A total of 838 proteins were identified, of which, 261 were previously characterized as EV proteins, including classical markers, such as cluster of differentiation (CD)9 and CD81. Quantitative analysis showed low technical variability with correlation coefficients greater than 0.9 between replicates. The analysis captured differences in relevant EV proteins involved in response to physical activity. Our method enables fast and sensitive fractionation of plasma EVs with low variability, which will facilitate biomarker studies in large clinical cohorts.

59 BASIC BIOLOGICAL SCIENCES↗

KRT18 as a Novel Biomarker of Urothelial Papilloma while Evaluating Low-Grade Papillary Urothelial Neoplasms: Bi-Center Analysis

Introduction: Although urothelial papilloma (UP) is an indolent papillary neoplasm that can mimic the morphology of low-grade papillary urothelial carcinoma (PUC), there is no immunomarker to differentiate reliably these two entities. In addition, the molecular characteristics of UP are not fully understood. Methods: We conducted an in-depth proteomic analysis of papillary urothelial lesions (n = 31), including UP and PUC along with normal urothelium. Protein markers distinguishing UP and PUC were selected with machine learning analysis, followed by internal and external validation using immunohistochemistry. Results: In the proteomic analysis, UP and PUC showed overlapping proteomic profiles. Here, we identified EHD4 and KRT18 as candidate diagnostic biomarkers of UP. Through immunohistochemical validation in two independent cohorts (n = 120), KRT18 was suggested as a novel UP diagnostic marker, able to differentiate UP from low-grade PUC. We also found that 3.5% of patients with UP developed urothelial carcinoma in subsequent resections, supporting the malignant potential of UP. KRT18 downregulation was significantly associated with UPs subsequently progressing to urothelial carcinoma, following their initial diagnosis. Conclusion: This is the first study that successfully revealed UPs comprehensive proteomic landscape, while it also identified KRT18 as a potential diagnostic biomarker of UP.

Biomarkers↗

Proteome-wide analysis of protein stability in Escherichia coli under acid stress

Knowledge of protein acid sensitivity remains sparse and is largely derived from low-throughput, enzyme-specific assays. We used a scalable framework to map acid stability across the Escherichia coli proteome to assess the acid stability of 1,675 unique proteins, estimating pH 50 values for over 90% of them. The parameter pH50 was defined as the pH value at which only 50% of the initial protein remains in solution following acid treatment. Proteome-wide pH 50 values ranged from 2.28 to 6.33 (median 5.11). Approximately 9% of detected proteins remained stable across all tested pH conditions. Our results align with published data and the assay of citrate synthase (GltA) performed here. Protein acid stability differed significantly by subcellular localization: periplasmic proteins were relatively more abundant in the acid-stable group, cytoplasmic proteins were abundant at pH 50 values 4.5–5.5, and inner membrane proteins at higher pH 50 between 5.5 and 6.0. Outer membrane proteins were too few to draw strong conclusions regarding enrichment within specific pH 50 groups. Notably, the periplasmic binding protein of the molybdate ABC transporter (ModA), was enriched after incubation at low pH. Estimated pH 50 values showed no correlation with protein isoelectric point and molecular weight. Together, this work provides the first proteome-wide map of protein acid stability and establishes a general framework for studying different chemical stressors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Pumping Iron: A Multi-omics Analysis of Two Extremophilic Algae Reveals Iron Economy Management

Marine algae are responsible for half of the world's primary productivity, but this critical carbonsink is often constrained by insufficient iron. One species of marine algae, Dunaliella tertiolecta, isremarkable for its ability to maintain photosynthesis and thrive in low-iron environments. A relatedspecies, Dunaliella salina Bardawil, shares this attribute but is an extremophile found in hypersaline environments. To elucidate how algae manage their iron requirements, we produced highquality genome assemblies and transcriptomes for both species to serve as a foundation for acomparative multi-omics analysis. We identified a host of iron-uptake proteins in both species,including a massive expansion of transferrins and a novel family of siderophore-iron uptakeproteins. Complementing these multiple iron-uptake routes, ferredoxin functions as a large ironreservoir that can be released by induction of flavodoxin. Proteomic analysis revealed reducedinvestment in the photosynthetic apparatus coupled with remodeling of antenna proteins bydramatic iron-deficiency induction of TIDI1, a light harvesting complex protein found also in otherchlorophytes. These combinatorial iron scavenging and sparing strategies make Dunaliellaunique among photosynthetic organisms

iron homeostasis, phytoplankton, Iron starvation i↗

MassIVE MSV000095714

Proteomic analysis reveals translation-related proteins are significantly altered in response to stabilized G4s. Identification of the importance of translation factors in overcoming G4s led to the question of how E. coli cells generally respond to chemicals that stabilize such structures. As a first step in addressing this question, a proteomic analysis was carried out to measure the quantitative effects of NMM on the levels of individual proteins in E. coli. Protein levels from early log-phase cultures of delta-tolC and delta-tolC tufA::kan strains grown in the presence or absence of NMM were measured to assess how reduced EF- Tu levels and NMM impacted expression.

Bottom-up proteomics↗

The anaerobic fungus Caecomyces churrovis produces H2 via a non-3 bifurcating NADH-dependent enzyme complex

Anaerobic fungi (AF) decompose lignocellulose-based biomass into fermentable sugars through the production of powerful biomass-degrading enzymes. AF are unusual among fungi in that they generate energy via hydrogenosomes, which are also associated with the release of H2 though yet unknown metabolic mechanisms. In particular, it remains unclear how NAD(P)+ is regenerated within hydrogenosomes and how H2 is formed. Here, we reveal the molecular mechanism for hydrogenosomal H2 production in the AF strain C. churrovis by combining genomic search, proteomic analysis, and enzymology. Our enzyme assays on the large organelle fraction of C. churrovis revealed the activity of H2:NAD+ oxidoreductase but not pyruvate:ferredoxin oxidoreductase activity. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE, NuoF) in C. churrovis, and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified proteins, we found that the assay system consisting of Hyd-Strep and NuoEF-Strep reduced NAD+ with H2. Furthermore, this system formed H2 directly from NADH independent of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is widely conserved among the early-branching AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex in eukaryotes. Moreover, this complex could be a target for controlling AF H2 production and altering fungal metabolism.

fungi↗

The anaerobic fungus Caecomyces churrovis produces H 2 via a non-bifurcating NADH-dependent enzyme complex

ABSTRACT Hydrogenosomes are mitochondria-derived organelles that produce ATP and H 2 to support energy metabolism in anaerobic eukaryotes. H 2 production allows reoxidation of reduced cofactors generated during fermentative metabolism; however, the metabolic mechanisms for H 2 production in anaerobic eukaryotes remains incompletely understood. In particular, it remains unclear whether anaerobic fungi (AF) hydrogenosomes use a ferredoxin-dependent pathway or a distinct mechanism to regenerate NAD(P) + and link electron transfer to H 2 formation. Here, by combining genomic search, proteomic analysis, and enzymology, we reveal the molecular mechanism for H 2 production in the AF strain Caecomyces churrovis . Our enzyme assays on the organelle fraction of C. churrovis revealed the activity of H 2 :NAD + oxidoreductase but not pyruvate:ferredoxin oxidoreductase, which is usually linked to H 2 formation. We identified genes encoding [FeFe] hydrogenase (Hyd) and NADH dehydrogenase subunits E and F (NuoE, NuoF) in C. churrovis , and confirmed their expression in the isolated hydrogenosomal fractions by proteomic analysis. Combining the individually purified enzymes, we found Hyd and NuoEF proteins formed H 2 directly from NADH independently of ferredoxin, functioning as a non-bifurcating NADH-dependent enzyme rather than an electron-bifurcating enzyme. We identified homologs of hydrogenosomal NuoE, NuoF, and Hyd in many other AF, indicating this pathway is commonly shared among the AF. This work demonstrates the existence of a non-bifurcating NADH-dependent enzyme complex in eukaryotes. Moreover, this complex could potentially be exploited as a target for controlling AF H 2 production and altering fungal metabolism. IMPORTANCE H 2 production is a prominent feature of anaerobic energy metabolism, yet our understanding of eukaryotic mechanisms remains limited. Anaerobic fungi (AF) are key decomposers of lignocellulose and contribute to hydrogen flux in anaerobic environments. Although it has been more than 40 years since the H 2 production from AF was first reported, the molecular mechanism for hydrogenosomal H 2 production and redox balance remains unclear. We demonstrate that AF produce H 2 from NADH utilizing a non-bifurcating NADH-dependent enzyme complex rather than an electron-bifurcating, ferredoxin-dependent variant. We show that this enzyme complex is conserved across multiple AF lineages and thus demonstrate the occurrence of a non-bifurcating NADH-dependent enzyme in eukaryotes. This discovery expands our understanding of eukaryotic hydrogenosomal metabolism, reveals a previously unknown strategy for redox balancing, and highlights potential targets for manipulating H 2 production. These insights have broad implications for microbial energy metabolism, anaerobic ecosystems, and bioengineering of H 2 -producing systems.

Zhang, Bo [Department of Chemical Engineering, Uni↗

Multi-Omics Reveals Temporal Scales of Carbon Metabolism in Synechococcus Elongatus PCC 7942 Under Light Disturbance

Central carbon metabolism in model cyanobacteria involves multiple pathways to adapt to energy-light limitations across diel cycles. However, the success in mechanistic modeling for phenotypic prediction of the protein regulators in the metabolic state depends on capturing the vast possibilities emerging from multiple regulatory pathways in complex biological processes. Here, we developed a physics-informed machine learning approach based on energy-landscape concepts to predict regulatory proteins responding to cyclic circadian and unforeseen light perturbations in cyanobacterial metabolic networks. Our approach provides interpretable de novo models for inferring gene expression dynamics from Synechococcus elongatus over diel cycles and using redox proteome analysis to distinguish immediate light-responsive elements from circadian-regulated processes in carbon metabolism pathways. We identified distinct temporal signatures with the analysis of the redox proteome: there was an immediate shift in cysteine redox states accompanied by a limited change in protein abundance under constant illumination and after 2 hours of darkness. This discovery indicates that the generation of reductants coordinates photoinduced electron transport with redox metabolic pathways in two discernable molecular mechanisms: fast redox-based protein modifications occur immediately after the light disturbance, followed by slow transcriptional regulations across networks. This temporal regulation reveals how metabolic networks integrate rapid light responses with programmed circadian rhythms to maintain cellular homeostasis under the light-energy limitations over the diel cycle.

Biomolecular & subcellular processes↗

PPI DataHub Project Data Package: S. elongatus PCC 7942 Limited Proteolysis and Thermal Proteome Profiling Structural Proteomics (JM-PB-DP3)

The purpose of this experiment was to investigate structural alterations in proteins involved in central carbon metabolism and photosynthetic electron transfer pathways in Synechococcus elongatus PCC 7942. Sample data was obtained from S. elongatus cell lysates using three complementary mass spectrometry (MS) techniques using limited proteolysis (LiP-MS), thermal proteome profiling (TPP-MS), and redox enrichment (Redox-MS) in evaluating alterations solvent accessibility and structural stability caused by light perturbation at the molecular level. Experimentally processed sample data for LiP and TPP proteomic datasets were derived from the same cell culture stock, prepared simultaneously in parallel, and acquired by mass spectrometry. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files, computed outputs, and supporting metadata materials. Experimental samples processed for LiP-MS label-free quantification (LFQ) or TPP-MS tandem mass tag (TMT) 10-plex were acquired using a Q-Exactive HF-X mass spectrometer and processed/compiled using either MSGF+ (v2024.03.26) or ​​​​PlexedPiper for proteome evaluation. Additional software supporting downstream proteomic analysis include FragPipe (v.4.0), MSFragger (v.22.1), and an adapted Microbial Isolate LiP Analysis Workflow (located at Zenodo). Processed proteomic data downloads include a sample naming key, normalized quantification results files, and processed protein annotated abundance files.

59 BASIC BIOLOGICAL SCIENCES↗

Comprehensive characterization of extracellular vesicles produced by environmental (Neff) and clinical (T4) strains of Acanthamoeba castellanii

We conducted a comprehensive comparative analysis of extracellular vesicles (EVs) from two Acanthamoeba castellanii strains, Neff (environmental) and T4 (clinical). Morphological analysis via transmission electron microscopy revealed slightly larger Neff EVs (average = 194.5 nm) compared to more polydisperse T4 EVs (average = 168.4 nm). Nanoparticle tracking analysis (NTA) and dynamic light scattering validated these differences. Proteomic analysis of the EVs identified 1,352 proteins, with 1,107 common, 161 exclusive in Neff, and 84 exclusively in T4 EVs. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) mapping revealed distinct molecular functions and biological processes and notably, the T4 EVs enrichment in serine proteases, aligned with its pathogenicity. Lipidomic analysis revealed a prevalence of unsaturated lipid species in Neff EVs, particularly triacylglycerols, phosphatidylethanolamines (PEs), and phosphatidylserine, while T4 EVs were enriched in diacylglycerols and diacylglyceryl trimethylhomoserine, phosphatidylcholine and less unsaturated PEs, suggesting differences in lipid metabolism and membrane permeability. Metabolomic analysis indicated Neff EVs enrichment in glycerolipid metabolism, glycolysis, and nucleotide synthesis, while T4 EVs, methionine metabolism. Furthermore, RNA-seq of EVs revealed differential transcript between the strains, with Neff EVs enriched in transcripts related to gluconeogenesis and translation, suggesting gene regulation and metabolic shift, while in the T4 EVs transcripts were associated with signal transduction and protein kinase activity, indicating rapid responses to environmental changes. In this novel study, data integration highlighted the differences in enzyme profiles, metabolic processes, and potential origins of EVs in the two strains shedding light on the diversity and complexity of A. castellanii EVs and having implications for understanding host-pathogen interactions and developing targeted interventions for Acanthamoeba-related diseases.

59 BASIC BIOLOGICAL SCIENCES↗

Human Lung Cellular Response to HCoV-229E Infection, Post-Translational Modification Proteomics Time Course (ACS-TZ-DP6)

The purpose of this experiment was to evaluate the human lung cellular response to wild type human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock-infected and HCoV-229E infected immortalized human lung epithelial cells (A549) (MOI 3) and immortalized human lung fibroblasts (MRC-5) (MOI 3). Whole cell lysates were collected at 8, 16, and 24 hours post infection and were processed for post translational modification (PTM) proteomics analysis to determine the HCoV-229E phosphoproteome, redox proteome, and acetylation proteome.

Sims, Amy C [Pacific Northwest National Laboratory↗

Single‐Cell Nanodroplet Processing Proteomics Pipeline for Analysis of Human‐Derived Microglia

Single-cell omics tools provide unique insights into heterogeneous cell populations and their responses to stimuli. For example, single-cell RNA sequencing has identified several transcriptionally distinct populations of microglia, which are resident immune cells of the central nervous system (CNS) that are responsive to CNS injury, infection, and neurodegeneration. To date, single-cell studies of microglia have focused on RNA-sequencing or cytometry by time of flight (CyTOF), which provide indirect readouts of protein abundance or quantification of a limited number of targets. Herein, we present a workflow based on FACS-assisted isolation, cryopreservation, and nanodroplet-based processing for single-cell mass spectrometry proteomics analysis of the postmortem human brain cortex-derived microglia. From a single microglial cell, 1039 proteins could be identified on average. As a proof-of-principle, we applied single-cell proteomics for exploring the heterogeneity of brain microglia at the cellular level. This pilot proteomics data partially recapitulates the prior microglia subtypes. Specifically, we determined that mitochondrial proteins, in particular members of NADH dehydrogenase (Complex I), cytochrome b-c1 (Complex III), cytochrome c oxidase (Complex IV), F1-ATPase (Complex V), and Na+/K+-ATPase complex, drive variation across microglia. This pipeline offers the potential for identifying functionally and analytically relevant protein targets for microglia in Alzheimer's disease and other neurological disorders.

59 BASIC BIOLOGICAL SCIENCES↗

Human Host Cellular Response to HCoV-229E Infection Proteomics (ACS-JM-DP2)

The purpose of this experiment was to evaluate the human host cellular response to wild-type Human coronavirus strain 229E (HCoV-229E) infection. Sample data was obtained for mock and infected immortalized human lung epithelial cells (A549) (MOI 5) nuclear extracts, immortalized human lung fibroblasts cells (MRC5) (MOI5) nuclear extracts, and primary human airway epithelial (HAE) (MOI 3) cells from lung tissue and processed for proteome analysis. Processed datasets are openly accessible from the download button and contain secondary processed proteomic results files and supporting metadata materials. Experimental proteomics samples were prepared using Limited Proteolysis (LiP) methods for Label-free quantification (LFQ) and global proteomic evaluation. Sample data was acquired using a Q-Exactive HF-X mass spectrometer and was processed and compiled using MaxQuant software (v.1.6.17.0). Processed proteomic data downloads include a sample naming key, processed MaxQuant results/parameters, and protein annotated relative abundance files. See corresponding primary data accessions below and Viral Experiment LiP Analysis source code supporting data transparency and reuse. Experimental transcriptomics samples were collected in parallel and processed for RNA sequencing (RNA-Seq) as summarized under ACS-DP1 (https://data.pnnl.gov/group/nodes/dataset/34069).

59 BASIC BIOLOGICAL SCIENCES↗