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PubMed2004

FTICR mass spectrometry for qualitative and quantitative bioanalyses.

Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) is playing an increasing role in the characterization of cellular systems owing to its capabilities for providing higher confidence of identification, increased dynamic range and sensitivity unmatched by other MS platforms. Particularly in proteomics, where global and quantitative approaches are essential, the attributes of FTICR-MS are poised to make significant contributions. Recent advances in the field that have particular importance for proteomic applications include the use of high-performance micro-capillary column separation techniques coupled to FTICR, as well as methods that improve protein identification, sensitivity, dynamic range and throughput.

Animals↗
PubMed2006

Liquid chromatography with tandem mass spectrometry-based proteomic discovery in aging and Alzheimer's disease.

Systems biology offers enormous potential to understand the complexity of human brain aging and neurodegenerative diseases. Proteomics has an important role in these investigations because of its unique strengths and because of the potential central pathogenic contribution of pathological protein to several of these diseases. Here we have reviewed the methods and presented some examples of liquid chromatography-electrospray ionization-tandem mass spectrometry-based proteomics, with and without quantification using isotope-coded affinity tags, in the investigation of aging and Alzheimer's disease. As protocols and methods for improved quantitative high-throughput proteomics constantly improve, this approach will likely continue to provide deeper insight into human brain aging and neurodegenerative diseases.

Aging↗
PubMed2005

Biospectra analysis: model proteome characterizations for linking molecular structure and biological response.

Establishing quantitative relationships between molecular structure and broad biological effects has been a long-standing goal in drug discovery. Evaluation of the capacity of molecules to modulate protein functions is a prerequisite for understanding the relationship between molecular structure and in vivo biological response. A particular challenge in these investigations is to derive quantitative measurements of a molecule's functional activity pattern across different proteins. Herein we describe an operationally simple probabilistic structure-activity relationship (SAR) approach, termed biospectra analysis, for identifying agonist and antagonist effect profiles of medicinal agents by using pattern similarity between biological activity spectra (biospectra) of molecules as the determinant. Accordingly, in vitro binding data (percent inhibition values of molecules determined at single high drug concentration in a battery of assays representing a cross section of the proteome) are useful for identifying functional effect profile similarity between medicinal agents. To illustrate this finding, the relationship between biospectra similarity of 24 molecules, identified by hierarchical clustering of a 1567 molecule dataset as being most closely aligned with the neurotransmitter dopamine, and their agonist or antagonist properties was probed. Distinguishing the results described in this study from those obtained with affinity-based methods, the observed association between biospectra and biological response profile similarity remains intact even upon removal of putative drug targets from the dataset (four dopaminergic [D1/D2/D3/D4] and two adrenergic [alpha1 and alpha2] receptors). These findings indicate that biospectra analysis provides an unbiased new tool for forecasting structure-response relationships and for translating broad biological effect information into chemical structure design.

Brain Chemistry↗
PubMed2002

Development of improved cell lysis, solubilization and imaging approaches for proteomic analyses.

Analysis of complex biochemical processes at the level of the proteome requires methods that quantitatively solubilize cytosolic and membrane bound proteins yet are compatible with isoelectric focusing and sodium dodecyl sulfate-polyacrylamide gel electrophoresis. In addition, it is often necessary to employ several highly sensitive detection methods to identify key proteins that are modified or exhibit a change in expression levels in response to a given experimental stimulus or condition. Methods were developed that efficiently extract tissues or lyse cultured cells and quantitatively solubilize proteins in a single step without the need to shear nucleic acids. These approaches utilize urea, thiourea, a mixture of detergents, low levels of an ampholyte blend, reductant and a combination of alcohols. To aid in the detection of low abundance proteins and the accurate identification of specific proteins of interest in these samples, two approaches were pursued. In one, proteins are transferred from two-dimensional (2-D) gels to blot membranes. Proteins are then detected by staining with SYPRO Ruby and the resulting 2-D protein pattern is captured using a charge-coupled device (CCD) camera. The blots are then probed with antibodies directed against the protein(s) or functionalities of interest. The resulting chemiluminescent blot image is also generated with the CCD camera and the fluorescent SYPRO Ruby image is recaptured again without moving the membrane. It is thereby possible to generate a direct image overlay of the blot pattern on that of the stained protein pattern. This approach significantly aids in the accurate identification of the dye-stained protein that is detected by the specific antibody. In addition to detecting protein post-gel transfer, a second approach utilizes protein samples labeled with fluorescent dyes prior to 2-D electrophoresis in an effort to increase the sensitivity of protein detection and to facilitate protein quantitation. It is also possible to stain the blots with different dyes and overlay these images as well. Using these approaches, it is possible to perform more rapid and accurate comparative analyses and proteomic, post-gel characterization of proteins of interest than using comparative image analysis of multiple gels.

Blotting, Western↗
PubMed2025

Kinetic Redox Shotgun Proteomics Reveals Specific Lipopolysaccharide Effects on Intestinal Epithelial Cells, Mitigated by a Mn Superoxide Dismutase Mimic.

Overproduction of reactive oxygen species and antioxidant superoxide dismutases (SOD1, SOD2) dysregulation contribute to chronic inflammation such as generated in inflammatory bowel diseases (IBD). A kinetic redox shotgun proteomic strategy (OcSILAC for Oxidized cysteine Stable Isotope Labelling by Amino acids in Cell culture) was used to explore the lipopolysaccharide (LPS) effects including LPS-induced oxidation and inflammation cascades on a dedicated intestinal epithelial cell line (HT29-MD2) together with the potential mitigating role of a Mn-based SOD-mimic Mn1. While LPS induced transient oxidative damages at early times (15 min), cells incubated with Mn1 showed, in this time frame, a significantly reduced cysteine oxidation, highlighting Mn1 antioxidant properties. Over time, cysteine oxidation of LPS-treated cells was counteracted by an overexpression of antioxidant proteins (SOD1, NQO1) and a late (6 h) preponderant increase in SOD2 level. Mn1, when co-incubated with LPS, attenuated the level of most LPS-modified proteins, that is, proteins involved in the inflammatory response. Our results highlight Mn1 as a potentially effective antioxidant and anti-inflammatory agent to consider in the treatment of IBD, as well as a useful tool for exploring the interconnection between oxidative stress and inflammation.

Lipopolysaccharides↗
PubMed2026

Disentangling adiposity-related and non-adiposity-related genetic pathways for type 2 diabetes.

OBJECTIVE: To identify circulating proteins associated with type 2 diabetes (T2D) risk through pathways not fully explained by body mass index (BMI), and to assess therapeutic actionability. RESEARCH DESIGN AND METHODS: We applied GWAS-by-subtraction within a genomic structural equation model to European ancestry summary statistics for T2D (74,124 cases, 824,006 controls) and BMI (n = 681,275), partitioning T2D liability into BMI-related and BMI-subtracted components. We then performed proteome-wide Mendelian randomization (MR) using cis-protein quantitative trait loci from four plasma proteomics cohorts: ARIC, deCODE, Fenland, and the UK Biobank Pharma Proteomics Project. Prioritized proteins passed sensitivity analyses with alternative MR methods and were supported by colocalization evidence. Tissue-resolution regulatory support was assessed using cis-eQTL colocalization across GTEx and pancreatic islet, subcutaneous adipose, and whole-blood resources. Actionability was evaluated using the druggable genome and Open Targets. RESULTS: GWAS-by-subtraction attenuated the genetic correlation between BMI and BMI-subtracted T2D from 0.54 (SE 0.02) to 0.35 (SE 0.02). Proteome-wide MR prioritized 29 proteins for BMI-subtracted T2D. Thirteen showed eQTL colocalization in at least one tissue, implicating liver and intermediary metabolism (GCDH, NOTCH2), pancreatic islet biology (CTRB2, MANBA), adipose and Wnt signaling (RSPO3, GALNT3), and whole blood regulatory signals (PAM, SNUPN). Sixteen proteins were classified within druggable-genome Tiers 1-3, and five had existing Open Targets compounds. CONCLUSIONS: Integrating GWAS-by-subtraction, proteome-wide MR, and colocalization nominated 29 proteins associated with T2D liability not fully explained by BMI. These findings highlight genetically supported targets for follow-up studies of T2D therapies that complement weight-centered approaches.

Journal Article↗
PubMed2001

Proteolytic 18O labeling for comparative proteomics: model studies with two serotypes of adenovirus.

A new method for proteolytic stable isotope labeling is introduced to provide quantitative and concurrent comparisons between individual proteins from two entire proteome pools or their subfractions. Two 18O atoms are incorporated universally into the carboxyl termini of all tryptic peptides during the proteolytic cleavage of all proteins in the first pool. Proteins in the second pool are cleaved analogously with the carboxyl termini of the resulting peptides containing two 16O atoms (i.e., no labeling). The two peptide mixtures are pooled for fractionation and separation, and the masses and isotope ratios of each peptide pair (differing by 4 Da) are measured by high-resolution mass spectrometry. Short sequences and/or accurate mass measurements combined with proteomics software tools allow the peptides to be related to the precursor proteins from which they are derived. Relative signal intensities of paired peptides quantify the expression levels of their precursor proteins from proteome pools to be compared, using an equation described in the paper. Observation of individual (unpaired) peptides is mainly interpreted as differential modification or sequence variation for the protein from the respective proteome pool. The method is evaluated here in a comparison of virion proteins for two serotypes (Ad5 and Ad2) of adenovirus, taking advantage of information already available about protein sequences and concentrations. In general, proteolytic 18O labeling enables a shotgun approach for proteomic studies with quantitation capability and is proposed as a useful tool for comparative proteomic studies of very complex protein mixtures.

Adenoviridae↗
PubMed2004

Proteomics/genomics and signaling in lymphocytes.

Recent technological advances in genomics, proteomics and bioinformatics have offered new insights into the molecular mechanisms that underlie lymphocyte signaling and function, and the development of new tools in these areas has opened up new avenues for biological investigation. By adding a quantitative dimension to lymphocyte proteome profiling, molecular machines and spatiotemporal regulatory processes can now be analyzed using such discovery-driven approaches. Biologists employing genomic and proteomic tools are gathering data at increasing speed and their struggle to extract maximal biological information is helped by new software tools that enable the detailed comparison of multiple datasets.

Animals↗
PubMed2005

Quantitative analysis of protein expression using amine-specific isobaric tags in Escherichia coli cells expressing rhsA elements.

We describe the use of amine-specific isobaric tags for protein expression quantification to study the effect of rhsA element over-expression in Escherichia coli. The use of an isobaric tagging strategy facilitates a shotgun approach to proteomic analysis and enables quantitation of up to four samples in parallel, based on the reporter ion series using tandem mass spectrometry (MS/MS). Using a liquid chromatography matrix-assisted laser desorption/ionization approach, 23,139 MS/MS spectra were collected. Five thousand sixty-three peptides derived from 780 proteins were quantified including several lower abundance proteins, such as transcription factors, DnaB and DnaG. More than 65% of the proteins had at least two high confidence peptide matches per protein (p<0.05). Further, a statistical test based on the Grubb's and Rosner's tests was able to discriminate outlier data. The removal of outlier data had no significant effect on the functional categories of proteins that were represented in the study.

Amines↗
PubMed2006

Differential analysis of membrane proteins in mouse fore- and hindbrain using a label-free approach.

The ability to quantitatively compare protein levels across different regions of the brain to identify disease mechanisms remains a fundamental research challenge. It requires both a robust method to efficiently isolate proteins from small amounts of tissue and a differential technique that provides a sensitive and comprehensive analysis of these proteins. Here, we describe a proteomic approach for the quantitative mapping of membrane proteins between mouse fore- and hindbrain regions. The approach focuses primarily on a recently developed method for the fractionation of membranes and on-membrane protein digestion, but incorporates off-line SCX-fractionation of the peptide mixture and nano-LC-MS/MS analysis using an LTQ-FT-ICR instrument as part of the analytical method. Comparison of mass spectral peak intensities between samples, mapping of peaks to peptides and protein sequences, and statistical analysis were performed using in-house differential analysis software (DAS). In total, 1213 proteins were identified and 967 were quantified; 81% of the identified proteins were known membrane proteins and 38% of the protein sequences were predicted to contain transmembrane helices. Although this paper focuses primarily on characterizing the efficiency of this purification method from a typical sample set, for many of the quantified proteins such as glutamate receptors, GABA receptors, calcium channel subunits, and ATPases, the observed ratios of protein abundance were in good agreement with the known mRNA expression levels and/or intensities of immunostaining in rostral and caudal regions of murine brain. This suggests that the approach would be well-suited for incorporation in more rigorous, larger scale quantitative analysis designed to achieve biological significance.

Animals↗
PubMed2006

Is protein overlap in two-dimensional gels a serious practical problem?

In a recently published article, Campostrini et al. [Proteomics 2005, 5, 2385-2395] raised questions regarding the utility of 2-D gels in proteomics research. We believe that the authors have overlooked several key issues including the dynamic range of protein expression and the sensitivity of the analytical methods used to explore a proteome. We argue that 2-D gels have and will continue to provide meaningful quantitative data when applied to proteomic analysis and that the practical significance of spot overlap has been overstated.

Electrophoresis, Gel, Two-Dimensional↗
PubMed2007

Evaluation of an in vitro model of androgen ablation and identification of the androgen responsive proteome in LNCaP cells.

Proteins responsive to androgen and anti-androgen may be involved in the development and progression of prostate cancer and the ultimate failure of androgen-ablation therapy. These proteins represent potential diagnostic and therapeutic targets for improved management of prostate cancer. We have investigated the effect of androgen (R1881) and anti-androgen (bicalutamide) on the androgen-responsive prostate cancer LNCaP cell line using a quantitative gel-based proteomic approach. Prior to analysis, the in vitro system was evaluated for reproducibility and validated by appropriate molecular responses to treatment. Six replicate samples were independently generated and analysed by 2-D DIGE. According to strict statistical criteria, 197 spots were differentially expressed, of which we have successfully identified 165 spots corresponding to 125 distinct proteins. Following androgen supplementation, 108 spots (68 proteins) were increased and 57 spots (39 proteins) were decreased. Essentially no difference was observed between control and anti-androgen-treated samples, confirming the absence of "off-target" effects of bicalutamide. Identified proteins were involved in diverse processes including the stress response and intracellular signalling. The potential contribution to disease of these processes and identified constituent proteins are discussed. This rigorous, statistically supported study of androgen responses has provided a number of potential candidates for development as diagnostic/prognostic markers and drug targets.

Androgens↗
PubMed2005

Bridging proteomics and systems biology: what are the roads to be traveled?

The comprehensive study of proteomes has become an important part of attempts to uncover the systemic properties of biological systems. Proteomics provides data of a quality which increasingly fulfills strict requirements of systems biology for quantitative and qualitative information. Notably, proteomics can generate rich datasets that describe dynamic changes of proteomes. On the other hand, large-scale modeling requires the development of mathematic tools that are adequate for the processing of largely uncertain biological data. In this review, recent developments that pave the way for the integration of proteomics into systems biology are discussed. These developments include the standardization of data acquisition and presentation, the increased comprehensiveness of proteomics studies in description of functional status, localization and dynamics of proteins, and advanced modeling approaches.

Animals↗
PubMed2026

From Peaks to Power: Systematic Evaluation of Chromatographic Sampling Reveals Determinants of Quantification and Biological Discovery in DIA Proteomics.

Modern DIA proteomics increasingly emphasizes throughput and depth for large-cohort studies, but methods are often optimized using proxy metrics that can mask losses in quantifiable signal and statistical power. Here, we evaluate how data points per peak and other chromatographic features jointly contribute to quantification and downstream biological discovery. Using a matrix-matched calibration curve dataset, we checked how the number of data points per peak (DPPP) affects the limits of detection and quantification (LOD/LOQ). Reduced DPPP minimally affected LOD but substantially degraded LOQ. Feature modeling and nonparametric association analyses identified precursor peak area as the strongest feature-level predictor of LOQ, whereas DPPP showed weaker and context-dependent effects. Simulations of chromatographic peak integration recapitulated these trends, showing that increased sampling primarily improves integration precision, while quantitative accuracy is strongly governed by peak height and peak shape. Finally, when comparing 20 cancer vs 20 control plasma samples processed with Seer Proteograph, the decrease in DPPP led to a loss of statistical significance for proteins with low-abundance precursors. These findings argue that DIA optimization should prioritize LOQ and statistical power metrics&#x2500;not identifications alone&#x2500;by balancing sampling density with chromatographic peak height and quality to maximize useful biological signal.

Proteomics↗
PubMed2003

Proteomics and systems biology approaches to signal transduction in sepsis.

Sepsis and resulting multiple system organ failure are the leading causes of mortality in intensive care units. Although it is generally appreciated that rampant, deregulated inflammatory pathways play a major role in sepsis, a comprehensive understanding based on the integrated response of multiple signal transduction pathways has remained elusive. Here we review the main signal transduction pathways involved in the progression from inflammation to sepsis and discuss emerging genomic, proteomic, and systems biology approaches to decipher how these signaling pathways converge to cause the septic state. We propose that an integrative approach involving functional proteomics will provide a quantitative and mechanistic description that unifies inflammatory signaling networks in sepsis and will identify critical regulatory nodes for therapeutic manipulation. These types of systems biology-based approaches may lead to more effective therapies than those currently available.

Humans↗
PubMedDate not supplied

Affinity labeling of highly hydrophobic integral membrane proteins for proteome-wide analysis.

The ability to identify and quantitate integral membrane proteins is an analytical challenge for mass spectrometry-based proteomics. The use of surfactants to solubilize and facilitate derivatization of these proteins can suppress peptide ionization and interfere with chromatographic separations during microcapillary reversed-phase liquid chromatography-electrospray-tandem mass spectrometry. To circumvent the use of surfactants and increase proteome coverage, an affinity labeling method has been developed to target highly hydrophobic integral membrane proteins using organic-assisted extraction and solubilization followed by cysteinyl-specific labeling using biotinylation reagents. As demonstrated on the membrane subproteome of Deinococcus radiodurans, specific and quantitative labeling of integral membrane proteins was achieved using a 60% methanol-aqueous buffer system and (+)-biotinyl-iodoacetamidyl-3,6-dioxaoctanediamine as the cysteinyl-alkylating reagent. From a total of 220 unique Cys-labeled peptides, 89 proteins were identified, of which 40 were integral membrane proteins containing from one to nine mapped transmembrane domains with a maximum positive GRAVY of 1.08. The protocol described can be used with other stable isotope labeling reagents (e.g., ICAT) to enable comparative measurements to be made on differentially expressed hydrophobic membrane proteins from various organisms (e.g., pathogenic bacteria) and cell types and provide a viable method for comparative proteome-wide analyses.

Affinity Labels↗
PubMed2007

Evaluation of two proteomics technologies used to screen the membrane proteomes of wild-type Corynebacterium glutamicum and an L-lysine-producing strain.

The membrane proteomes of a wild-type Corynebacterium glutamicum and an L-lysine-producing strain were quantitatively analyzed by two complementary proteomics techniques -- anion exchange chromatography AIEC/SDS-PAGE and 16BAC-PAGE/SDS-PAGE -- and the results were compared. Although both techniques allow for the fast screening of differences in protein abundance, AIEC/SDS-PAGE was superior to 16BAC-PAGE/SDS-PAGE with respect to protein separation, it was more suitable for relative protein quantification, and allowed more differentially regulated proteins to be detected (the succinate dehydrogenase complex, an ABC-type cobalamin/Fe(3+) siderophore transport system, the maltose binding protein, and a subunit of the cytochrome bc-aa(3) supercomplex were upregulated, while a periplasmic component of an ABC-type transporter and an iron-regulated ABC-type transporter were downregulated in the producer). The results indicate the important role of tricarboxylic acid cycle enzymes as well as the adaptation of transport processes in L-lysine-producing cells. Since the only genetic differences between the wild type and the L-lysine producer occur between four central metabolic enzymes in the cytoplasm, our study illustrates the complex effects of metabolic engineering on cell physiology and the power of the new AIEC/SDS-PAGE proteomics approach to detect these effects.

ATP-Binding Cassette Transporters↗