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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Subnanogram proteomics: Impact of LC column selection, MS instrumentation and data analysis strategy on proteome coverage for trace samples

One of the greatest challenges for mass spectrometry (MS)-based proteomics is the limited ability to analyze small samples. Here we investigate the relative contributions of liquid chromatography (LC), MS instrumentation and data analysis methods with the aim of improving proteome coverage for sample sizes ranging from 0.5 ng to 50 ng. We show that the LC separations utilizing 30-µm-i.d. columns increase signal intensity by >3-fold relative to those using 75-µm-i.d. columns, leading to 32% increase in peptide identifications. The Orbitrap Fusion Lumos mass spectrometer significantly boosted both sensitivity and sequencing speed relative to earlier generation Orbitraps (e.g., LTQ-Orbitrap), leading to a ~3× increase in peptide identifications and 1.7× increase in identified protein groups for 2 ng tryptic digests of bacterial lysate. The Match Between Runs algorithm of open-source MaxQuant software further increased proteome coverage by ~ 95% for 0.5 ng samples and by ~42% for 2 ng samples. The present platform is capable of identifying >3000 protein groups from tryptic digestion of cell lysates equivalent to 50 HeLa cells and 100 THP-1 cells (~10 ng total proteins), respectively, and >950 proteins from subnanogram bacterial and archaeal cell lysates. The present ultrasensitive LC-MS platform is expected to enable deep proteome coverage for subnanogram samples, including single mammalian cells.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2018

Quality Control Analysis in Real-time (QC-ART): A Tool for Real-time Quality Control Assessment of Mass Spectrometry-based Proteomics Data

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics studies of large sample cohorts can easily require from months to years to complete. Acquiring consistent, high-quality data in such large-scale studies is challenging because of normal variations in instrumentation performance over time, as well as artifacts introduced by the samples themselves, such as those due to collection, storage and processing. Existing quality control methods for proteomics data primarily focus on post-hoc analysis to remove low-quality data that would degrade downstream statistics; they are not designed to evaluate the data in near real-time, which would allow for interventions as soon as deviations in data quality are detected. In addition to flagging analyses that demonstrate outlier behavior, evaluating how the data structure changes over time can aide in understanding typical instrument performance or identify issues such as a degradation in data quality due to the need for instrument cleaning and/or re-calibration. To address this gap for proteomics, we developed Quality Control Analysis in Real-Time (QC-ART), a tool for evaluating data as they are acquired in order to dynamically flag potential issues with instrument performance or sample quality. QC-ART has similar accuracy as standard post-hoc analysis methods with the additional benefit of real-time analysis. We demonstrate the utility and performance of QC-ART in identifying deviations in data quality due to both instrument and sample issues in near real-time for LC-MS-based plasma proteomics analyses of a sample subset of The Environmental Determinants of Diabetes in the Young cohort. We also present a case where QC-ART facilitated the identification of oxidative modifications, which are often underappreciated in proteomic experiments.

Stanfill, Bryan A.↗
DOE OSTI2018

Targeted brain proteomics uncover multiple pathways to Alzheimer's dementia

Objective Previous gene expression analysis identified a network of coexpressed genes that is associated with β‐amyloid neuropathology and cognitive decline in older adults. The current work targeted influential genes in this network with quantitative proteomics to identify potential novel therapeutic targets. Methods Data came from 834 community‐based older persons who were followed annually, died, and underwent brain autopsy. Uniform structured postmortem evaluations assessed the burden of β‐amyloid and other common age‐related neuropathologies. Selected reaction monitoring quantified cortical protein abundance of 12 genes prioritized from a molecular network of aging human brain that is implicated in Alzheimer's dementia. Regression and linear mixed models examined the protein associations with β‐amyloid load and other neuropathological indices as well as cognitive decline over multiple years preceding death. Results Average age at death was 88.6 years. Overall, 349 participants (41.9%) had Alzheimer's dementia at death. A higher level of PLXNB1 abundance was associated with more β‐amyloid load ( p = 1.0 × 10 −7 ) and higher PHFtau tangle density ( p = 2.3 × 10 −7 ), and the association of PLXNB1 with cognitive decline is mediated by these known Alzheimer's disease pathologies. On the other hand, higher IGFBP5, HSPB2, and AK4 and lower ITPK1 levels were associated with faster cognitive decline, and, unlike PLXNB1, these associations were not fully explained by common neuropathological indices, suggesting novel mechanisms leading to cognitive decline. Interpretation Using targeted proteomics, this work identified cortical proteins involved in Alzheimer's dementia and begins to dissect two different molecular pathways: one affecting β‐amyloid deposition and another affecting resilience without a known pathological footprint. Ann Neurol 2018;83:78–88

Yu, Lei↗
DOE OSTI2016

Advances in targeted proteomics and applications to biomedical research

Targeted proteomics technique has emerged as a powerful protein quantification tool in systems biology, biomedical research, and increasing for clinical applications. The most widely used targeted proteomics approach, selected reaction monitoring (SRM), also known as multiple reaction monitoring (MRM), can be used for quantification of cellular signaling networks and preclinical verification of candidate protein biomarkers. As an extension to our previous review on advances in SRM sensitivity (Shi et al., Proteomics , 12, 1074–1092, 2012) herein we review recent advances in the method and technology for further enhancing SRM sensitivity (from 2012 to present), and highlighting its broad biomedical applications in human bodily fluids, tissue and cell lines. Furthermore, we also review two recently introduced targeted proteomics approaches, parallel reaction monitoring (PRM) and data‐independent acquisition (DIA) with targeted data extraction on fast scanning high‐resolution accurate‐mass (HR/AM) instruments. Such HR/AM targeted quantification with monitoring all target product ions addresses SRM limitations effectively in specificity and multiplexing; whereas when compared to SRM, PRM and DIA are still in the infancy with a limited number of applications. Thus, for HR/AM targeted quantification we focus our discussion on method development, data processing and analysis, and its advantages and limitations in targeted proteomics. Finally, general perspectives on the potential of achieving both high sensitivity and high sample throughput for large‐scale quantification of hundreds of target proteins are discussed.

Shi, Tujin↗
DOE OSTI2018

Irradiation of rainbow trout at early life stages results in a proteomic legacy in adult gills. Part A; proteomic responses in the irradiated fish and in non-irradiated bystander fish

Highlights: • The effects of early life irradiation on the trout gill proteome was investigated. • The bystander effect proteomic responses in non-irradiated fish were investigated. • Proteomic responses of embryonic irradiation were anti-tumorigenic or anti-oxidant. • Proteomic responses of larval or first feeder irradiation were “dual function”. • Bystander effect proteomic responses were anti-tumorigenic or protective. Exposure to a single 0.5 Gy X-ray dose of eggs at 48 h after fertilisation (48 h egg), eyed eggs, yolk sac larvae (YSL) and first feeders induces a legacy effect in adult rainbow trout. This includes the transmission of a bystander effect to non-irradiated adult trout which had swam with the irradiated fish. The aim of this study was to investigate this legacy by analysing the gill proteome of these irradiated and bystander fish. Irradiation at all of the early life stages resulted in changes to proteins which play a key role in development but are also known to be anti-tumorigenic and anti-oxidant: upregulation of haemoglobin subunit beta (48 h egg), haemoglobin, serum albumin 1 precursor (eyed eggs), clathrin heavy chain 1 isoform X10 (eyed eggs and first feeders), and actin-related protein 2/3 complex subunit 4 (first feeders), downregulation of pyruvate dehydrogenase, histone 1 (48 h egg), triosephosphate isomerase (TPI), collagen alpha-1(1) chain like proteins (YSL), pyruvate kinase PKM-like protein (YSL and first feeders), ubiquitin-40S ribosomal proteins S27 and eukaryotic translation initiation factor 4 A isoform 1B (first feeders). However irradiation of YSL and first feeders (post hatching early life stages) also induced proteomic changes which have a complex relationship with tumorigenesis or cancer progression; downregulation of alpha-1-antiprotease-like protein precursor, vigilin isoform X2 and nucleoside diphosphate kinase (YSL) and upregulation of hyperosmotic glycine rich protein (first feeders). In bystander fish some proteomic changes were similar to those induced by irradiation: upregulation of haemoglobin subunit beta (48 h egg), haemoglobin (eyed eggs), actin-related protein 2/3 complex subunit 4, hyperosmotic glycine rich protein (first feeders), and downregulation of alpha-1-antiprotease-like protein, vigilin isoform X2, nucleoside diphosphate kinase (YSL), pyruvate kinase PKM-like protein and ubiquitin-40S ribosomal protein S27a-like (first feeders). Other proteomic changes were unique to bystander fish; downregulation of TPI, ubiquitin-40S ribosomal protein S2 (eyed egg), cofilin-2, cold-inducible RNA-binding protein B-like isoform X3 (YSL) and superoxide dismutase (first feeder), and upregulation of haemoglobin subunit alpha, collagen 1a1 precursor, apolipoprotein A-1-1 and A-1–2 precursor (first feeders). These bystander effect proteomic changes have been shown to be overwhelmingly anti-tumorigenic or protective of the fish gill.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2017

High-resolution ultrahigh-pressure long column reversed-phase liquid chromatography for top-down proteomics

We report development of an approach providing high-resolution RPLC of proteins and its utility for mass spectrometry-based top-down proteomics. A chromatographic peak capacity of ~450 was achieved for proteins and large polypeptides having MWs up to 43 kDa in the context of proteomics applications. RPLC column lengths from 20 to 200 cm, particle sizes from 1.5 to 5 m, bonding alkyl chains from C1 to C2, C4, C8, and C18, and particle surface structures that spanned porous, superficially porous (porous shell, core-shell), and nonporous were investigated at pressures up to14K psi. Column length was found as the most important factor for >20 kDa proteins in gradient RPLC, and shortening column length degraded RPLC resolution and sensitivity regardless of the size and surface structure of the packing particles used. The alkyl chains bonded to the silica particle surface significantly affected the RPLC recovery and efficiency, and short alkyl C1-C4 phases provided higher sensitivity and resolution than C8 and C18 phases. Long gradient separations (e.g., >10 hours) with long columns (e.g., 100 cm) were particularly effective in conjunction with use of high accuracy mass spectrometers (e.g., the Orbitrap Elite) for top-down proteomics with improved proteoform coverage by allowing multiple HCD, CID, and ETD dissociation modes. It was also found that HCD produced small fragments useful for proteoform identification, while low energy CID and ETD often complemented HCD by providing large fragments.

columns and stationary phases↗
DOE OSTI2020

Proximity-based proteomics reveals the thylakoid lumen proteome in the cyanobacterium Synechococcus sp. PCC 7002

Abstract Cyanobacteria possess unique intracellular organization. Many proteomic studies have examined different features of cyanobacteria to learn about the intracellular structures and their respective functions. While these studies have made great progress in understanding cyanobacterial physiology, the conventional fractionation methods used to purify cellular structures have limitations; specifically, certain regions of cells cannot be purified with existing fractionation methods. Proximity-based proteomics techniques were developed to overcome the limitations of biochemical fractionation for proteomics. Proximity-based proteomics relies on spatiotemporal protein labeling followed by mass spectrometry of the labeled proteins to determine the proteome of the region of interest. We performed proximity-based proteomics in the cyanobacterium Synechococcus sp. PCC 7002 with the APEX2 enzyme, an engineered ascorbate peroxidase. We determined the proteome of the thylakoid lumen, a region of the cell that has remained challenging to study with existing methods, using a translational fusion between APEX2 and PsbU, a lumenal subunit of photosystem II. Our results demonstrate the power of APEX2 as a tool to study the cell biology of intracellular features and processes, including photosystem II assembly in cyanobacteria, with enhanced spatiotemporal resolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Proximity-based proteomics reveals the thylakoid lumen proteome in the cyanobacterium Synechococcus sp. PCC 7002

Cyanobacteria possess unique intracellular organization. Many proteomic studies have examined different features of cyanobacteria to learn about the intracellular structures and their respective functions. While these studies have made great progress in understanding cyanobacterial physiology, the conventional fractionation methods used to purify cellular structures have limitations; specifically, certain regions of cells cannot be purified with existing fractionation methods. Proximity-based proteomics techniques were developed to overcome the limitations of biochemical fractionation for proteomics. Proximity-based proteomics relies on spatiotemporal protein labeling followed by mass spectrometry of the labeled proteins to determine the proteome of the region of interest. We performed proximity-based proteomics in the cyanobacterium Synechococcus sp. PCC 7002 with the APEX2 enzyme, an engineered ascorbate peroxidase. We determined the proteome of the thylakoid lumen, a region of the cell that has remained challenging to study with existing methods, using a translational fusion between APEX2 and PsbU, a lumenal subunit of photosystem II. Our results demonstrate the power of APEX2 as a tool to study the cell biology of intracellular features and processes, including photosystem II assembly in cyanobacteria, with enhanced spatiotemporal resolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

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↗
DOE OSTI2018

Irradiation of rainbow trout at early life stages results in a proteomic legacy in adult gills. Part B; the effect of a second radiation dose, after one year, on the proteomic responses in the irradiated and non-irradiated bystander fish

Highlights: • The effects of a 2nd radiation dose at one year were investigated. • The bystander effect proteomic responses in non-irradiated fish were investigated. • The effects of a 2nd radiation dose differed to those of early life irradiation only. • Proteomic responses of irradiated fish indicated tumorigenesis or cancer progression. • Bystander effect proteomic responses were tumorigenic, detrimental or uncertain. This study extends the investigation of the legacy effects of exposure to a single radiation dose at one of four early life stages, in adult rainbow trout (Part A), by examining the effects of a second identical dose after one year; i.e. egg 48 h after fertilisation (48 h egg) + 1 year, eyed egg + 1 year, yolk sac larvae (YSL) + 1 year and first feeder + 1 year. This included the induction of a bystander effect in non-irradiated trout which had swam with the irradiated fish. The second radiation dose negated any beneficial proteomic responses following early life stage irradiation only, particularly irradiation of 48 h eggs and eyed eggs (Part A). Instead the responses after early life stage + 1 year irradiation are consistently associated with tumorigenesis, cancer progression, or are otherwise damaging: upregulation of alpha-globin 1 (YSL + 1 year and first feeders + 1 year) and downregulation of histone H1, type II keratin, malate dehydrogenase 2–2, Na/K ATPase alpha subunit isoform 1b, nucleoside diphosphate kinase (48 h egg + 1 year), electron transfer flavoprotein subunit alpha (eyed egg + 1 year), 60 S ribosomal protein L30 (YSL + 1 year) and haemoglobin subunit beta-4 (first feeder + 1 year). Most significantly the second radiation dose also negated the overwhelmingly beneficial bystander effect proteomic responses induced by trout irradiated at an early life stage only (Part A). Instead the bystander effect proteomic changes induced by trout irradiated at an early life stage and again at 1 year have been associated with uncertain, with respect to tumorigenesis, or detrimental effects; upregulation of alpha-globin 1 (YSL + 1 year and first feeder + 1 year) and downregulation of malate dehydrogenase 2–2, nucleoside diphosphate kinase (48 h egg + 1 year), transferrin precursor (eyed egg + 1 year), 60 S ribosomal protein L30 (YSL + 1 year) and serine / threonine-protein phosphatase 2 A 65 kDa (first feeder + 1 year). This difference between the bystander effect induced proteomic changes following early life stage irradiation only and early life stage + 1 year irradiation may indicate a fundamental change in the non-targeted effects of radiation following multiple exposure to radiation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Principles of proteome allocation are revealed using proteomic data and genome-scale models

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Mass spectrometry-based proteomics for system-level characterization of biological responses to engineered nanomaterials

The widespread applications of engineered nanomaterials or nanotechnology make the characterization of biological responses to nanomaterials as an important area of research. The applications of omics-based approaches such as mass spectrometry-based proteomics have revealed new insights into the cellular responses upon exposure to nanomaterials, including how nanomaterials interact and alter cellular pathways. For instance, a redox-dependent response is often associated with exposure of nanomaterials, which leads to the generation of reactive oxygen species. In this review, we discuss the general quantitative proteomics approaches, with an emphasis on redox proteomics and their applications for characterizing the biological responses to nanomaterials.

Zhang, Tong↗
DOE OSTI2025

The promising role of proteomes and metabolomes in defining the single-cell landscapes of plants

The plant community has a strong track-record of RNA sequencing technology deployment, which combined with the recent advent of spatial platforms (e.g., 10x genomics), has resulted in an explosion of outstanding single cell and nuclei datasets that can be put in an in situ context within tissues (e.g., a cell atlas)1. In the genomics era, application of proteomics technologies in the plant sciences has always trailed behind that of RNA sequencing technologies, largely due to accessibility, ease-of-use and access to expertise along with depth of analysis benefits. On the other hand, the use of early analytical tools for characterizing small molecules (metabolites) from plant systems predates nucleic acid sequencing and proteomics analysis2, as the search for plant-based natural products has played a significant role in improving human health throughout history. However, the employment of proteomics and metabolomics assays for characterizing plant cell processes now remains significantly behind transcriptional approaches, even though both provide a direct functional readout of cell states and phenotypes.

Anderton, Christopher R. [BATTELLE (PACIFIC NW LAB↗
DOE OSTI2017

Identification of Hip BMD Loss and Fracture Risk Markers Through Population-Based Serum Proteomics: HIP BMD LOSS & FRACTURE RISK MARKERS BY POPULATION-BASED SERUM PROTEOMICS

Accelerated bone loss significantly increases the risk of osteoporosis and fracture. The mechanisms underlying bone loss remain incompletely understood, and there are few available biomarkers. We utilized a novel proteomics approach to identify serum peptides and proteins associated with bone loss in 1967 older men who were randomly chosen from the Osteoporotic Fracture in Men Study (MrOS study) (age ≥ 65 yrs). Men had 2-3 measures of femoral neck BMD over an average follow-up of 4.6 years. Change in BMD was estimated and then categorized into three groups: maintained BMD (n=453), expected loss (n=1185) and accelerated loss (n=237). A liquid chromatography–ion mobility separation-mass spectrometry (LC-IMS-MS) proteomics platform was used to identify and quantify peptides from serum proteins. The whole cohort was randomly divided into discovery (N= 960) and validation (N= 915) sub-cohorts. Linear regression models and a random forest approach were used to discover differentially abundant individual peptides and a proteomic signature that distinguished individuals with accelerated bone loss from those who maintained BMD. Network analyses were performed using the MetaCore knowledgebase. We identified 12 peptides that were associated with BMD loss in both discovery (P< 0.1 FDR) and replication sub-cohorts (P<0.05). Those 12 peptides mapped to the following proteins: ALS, LYVE1, RNAS1, C2, ICOSL, C163A, C7, HEMO, CD14, CERU, CRAC1 and CD59. Meta-analysis of peptidesassociated with bone loss identified 6 additional proteins including GRP78, IGF-2, SHBG, ENPP2, IBP2 and IBP6. We also identified a proteomic signature that was predictive of BMD loss with a discriminative value similar to serum bone marker carboxy-terminal collagen crosslink peptide (CTX). Interestingly, combining the proteomic signature with CTX significantly improved the ability to discriminate men with accelerated loss. In summary, we have identified potential new biomarkers for bone loss that provide a more in depth understanding of its pathophysiology.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Evaluation of the cytotoxic and cellular proteome impacts of food-grade TiO2 (E171) using simulated gastrointestinal digestions and a tri-culture small intestinal epithelial model

Engineered nanomaterials (ENMs) are widely used in the food industry; however, regulations for ENMs in food are still in the early stages of development due to insufficient health data. This study investigated the cytotoxicity and changes to the proteomic profile in an in vitro small intestinal epithelium model after exposure to digested food models containing the ubiquitous engineered particulate food additive, TiO2 (E171). TiO2 at 0.75% or 1.5% (w/w) concentrations in either a fasting food model (FFM) or a standardized food model (SFM) based on American diet were digested using an in vitro oral-gastric-small intestinal simulator, and the resulting digestas were applied to a small intestinal epithelium tri-culture cellular model. Effects on cell layer integrity, cytotoxicity, and oxidative stress were assessed. In order to explore impact on cellular processes beyond basic cytotoxicity, mass spectrometrybased quantitative proteomic analyses of control and exposed tri-culture cells was performed. TiO2 in FFM, but not in SFM, produced significant, dose-dependent cytotoxicity, and at the higher dose caused significant oxidative stress, indicative of a food matrix effect. No significant perturbations of the cellular proteome were observed with TiO2 in either FFM or SFM food models. However, proteins involved in the tricarboxylic acid (TCA) cycle, gluconeogenesis, and translation were up-regulated by digestas from SFM compared to those from FFM, also indicative of food matrix effects in the case of food models alone. Interestingly, the differences in profiles between the two food models was more pronounced in the presence of TiO2 indicative of food matrix effects. Together, these results indicate that TiO2 in a fasting diet may be slightly cytotoxic, and that ingested TiO2 does not significantly alter the epithelial proteome, whereas the food matrix alone can have a dramatic effect on the proteome.

Cao, Xiaoqiong↗