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. Keywords: affinity labeling • biotinylation • membrane proteins • hydrophobic proteins • proteomics • mass spectrometr

Proteomic Analysis of Lipid Microdomains from Lipopolysaccharide-Activated Human Endothelial Cells

The endothelium plays a critical role in orchestrating the inflammatory response seen during sepsis. Many of the inflammatory effects of Gram-negative sepsis are elicited by lipopolysaccharide (LPS), a glycolipid component of bacterial cell walls. Lipid-rich microdomains have been shown to concentrate components of the LPS signaling system. However, much remains to be learned about which proteins are constituents of lipid microdomains, and how these are regulated following cell activation. Progress in this area would be accelerated by employing global proteomic analyses, but the hydrophobicity of membrane proteins presents an analytical barrier to the effective application of such approaches. Herein, we describe a method to isolate detergent-resistant membranes from endothelial cells, and prepare these samples for proteomic analysis in a way that is compatible with subsequent separations and mass spectrometric (MS) analysis. In the application of these sample preparation and MS analyses, 358 proteins from the lipid-rich microdomains of LPS-activated endothelial cell membranes have been identified of which half are classified as membrane proteins by Gene Ontology. We also demonstrate that the sample preparation method used for solubilization and trypsin digestion of lipid-rich microdomains renders the membrane spanning sequences of transmembrane proteins accessible for endoproteolytic hydrolysis. This analysis sets the analytical foundation for an in-depth probing of LPS signaling in endothelial cells. Keywords: lipopolysaccharide • endothelium • caveolae • lipid rafts • lipid-rich microdomains • inflammatio

Approaching Solid Tumor Heterogeneity on a Cellular Basis by Tissue Proteomics Using Laser Capture Microdissection and Biological Mass Spectrometry

The purpose of this study was to examine solid tumor heterogeneity on a cellular basis using tissue proteomics that relies on a functional relationship between Laser Capture Microdissection (LCM) and biological mass spectrometry (MS). With the use of LCM, homogeneous regions of cells exhibiting uniform histology were isolated and captured from fresh frozen tissue specimens, which were obtained from a human lymph node containing breast carcinoma metastasis. Six specimens ∼50 000 cell each (three from tumor proper and three from tumor stroma) were collected by LCM. Specimens were processed directly on LCM caps, using sonication in buffered methanol to lyse captured cells, solubilize, and digest extracted proteins. Prepared samples were analyzed by LC/MS/MS resulting in more than 500 unique protein identifications. Decoy database searching revealed a false-positive rate between 5 and 10%. Subcellular localization analysis for stromal cells revealed plasma membrane 14%, cytoplasm 39%, nucleus 11%, extracellular space 27%, and unknown 9%; and tumor cell results were 5%, 58%, 26%, 4%, and 7%, respectively. Western blot analysis confirmed specific linkage of validated proteins to underlying pathology and their potential role in solid tumor heterogeneity. With continued research and optimization of this method including analysis of additional clinical specimens, this approach may lead to an improved understanding of tumor heterogeneity, and serve as a platform for solid tumor biomarker discovery

Approaching Solid Tumor Heterogeneity on a Cellular Basis by Tissue Proteomics Using Laser Capture Microdissection and Biological Mass Spectrometry

The purpose of this study was to examine solid tumor heterogeneity on a cellular basis using tissue proteomics that relies on a functional relationship between Laser Capture Microdissection (LCM) and biological mass spectrometry (MS). With the use of LCM, homogeneous regions of cells exhibiting uniform histology were isolated and captured from fresh frozen tissue specimens, which were obtained from a human lymph node containing breast carcinoma metastasis. Six specimens ∼50 000 cell each (three from tumor proper and three from tumor stroma) were collected by LCM. Specimens were processed directly on LCM caps, using sonication in buffered methanol to lyse captured cells, solubilize, and digest extracted proteins. Prepared samples were analyzed by LC/MS/MS resulting in more than 500 unique protein identifications. Decoy database searching revealed a false-positive rate between 5 and 10%. Subcellular localization analysis for stromal cells revealed plasma membrane 14%, cytoplasm 39%, nucleus 11%, extracellular space 27%, and unknown 9%; and tumor cell results were 5%, 58%, 26%, 4%, and 7%, respectively. Western blot analysis confirmed specific linkage of validated proteins to underlying pathology and their potential role in solid tumor heterogeneity. With continued research and optimization of this method including analysis of additional clinical specimens, this approach may lead to an improved understanding of tumor heterogeneity, and serve as a platform for solid tumor biomarker discovery

Global Analysis of the Membrane Subproteome of <i>Pseudomonas aeruginosa</i> Using Liquid Chromatography-Tandem Mass Spectrometry

Pseudomonas aeruginosa is one of the most significant opportunistic bacterial pathogens in humans causing infections and premature death in patients with cystic fibrosis, AIDS, severe burns, organ transplants, or cancer. Liquid chromatography coupled online with tandem mass spectrometry was used for the large-scale proteomic analysis of the P. aeruginosa membrane subproteome. Concomitantly, an affinity labeling technique, using iodoacetyl-PEO biotin to tag cysteinyl-containing proteins, permitted the enrichment and detection of lower abundance membrane proteins. The application of these approaches resulted in the identification of 786 proteins. A total of 333 proteins (42%) had a minimum of one transmembrane domain (ranging from 1 to14) and 195 proteins were classified as hydrophobic based on their positive GRAVY values (ranging from 0.01 to 1.32). Key integral inner and outer membrane proteins involved in adaptation and antibiotic resistance were conclusively identified, including the detection of 53% of all predicted opr-type porins (outer integral membrane proteins) and all the components of the mexA-mexB-oprM transmembrane protein complex. This work represents one of the most comprehensive proteomic analyses of the membrane subproteome of P. aeruginosa and for prokaryotes in general. Keywords: proteome • membrane proteins • low abundance • LC−MS/MS • affinity labelin

Global Analysis of the Membrane Subproteome of <i>Pseudomonas aeruginosa</i> Using Liquid Chromatography-Tandem Mass Spectrometry

Pseudomonas aeruginosa is one of the most significant opportunistic bacterial pathogens in humans causing infections and premature death in patients with cystic fibrosis, AIDS, severe burns, organ transplants, or cancer. Liquid chromatography coupled online with tandem mass spectrometry was used for the large-scale proteomic analysis of the P. aeruginosa membrane subproteome. Concomitantly, an affinity labeling technique, using iodoacetyl-PEO biotin to tag cysteinyl-containing proteins, permitted the enrichment and detection of lower abundance membrane proteins. The application of these approaches resulted in the identification of 786 proteins. A total of 333 proteins (42%) had a minimum of one transmembrane domain (ranging from 1 to14) and 195 proteins were classified as hydrophobic based on their positive GRAVY values (ranging from 0.01 to 1.32). Key integral inner and outer membrane proteins involved in adaptation and antibiotic resistance were conclusively identified, including the detection of 53% of all predicted opr-type porins (outer integral membrane proteins) and all the components of the mexA-mexB-oprM transmembrane protein complex. This work represents one of the most comprehensive proteomic analyses of the membrane subproteome of P. aeruginosa and for prokaryotes in general. Keywords: proteome • membrane proteins • low abundance • LC−MS/MS • affinity labelin

Enrichment of Integral Membrane Proteins for Proteomic Analysis Using Liquid Chromatography−Tandem Mass Spectrometry

An increasing number of proteomic strategies rely on liquid chromatography−tandem mass spectrometry (LC−MS/MS) to detect and identify constituent peptides of enzymatically digested proteins obtained from various organisms and cell types. However, sample preparation methods for isolating membrane proteins typically involve the use of detergents and chaotropes that often interfere with chromatographic separation and/or electrospray ionization. To address this problem, a sample preparation method combining carbonate extraction, surfactant-free organic solvent-assisted solubilization, and proteolysis was developed and demonstrated to target the membrane subproteome of Deinococcus radiodurans. Out of 503 proteins identified, 135 were recognized as hydrophobic on the basis of their calculated hydropathy values (GRAVY index), corresponding to coverage of 15% of the predicted hydrophobic proteome. Using the PSORT algorithm, 53 of the proteins identified were classified as integral outer membrane proteins and 215 were classified as integral cytoplasmic membrane proteins. All identified integral cytoplasmic membrane proteins had from 1 to 16 mapped transmembrane domains (TMDs), and 65% of those containing four or more mapped TMDs were identified by at least one hydrophobic membrane spanning peptide. The extensive coverage of the membrane subproteome (24%) by identification of highly hydrophobic proteins containing multiple TMDs validates the efficacy of the described sample preparation technique to isolate and solubilize hydrophobic integral membrane proteins from complex protein mixtures.Keywords: membrane proteins • sample preparation • hydrophobic proteins • proteomics • mass spectrometr

Optimized Method for Computing ¹⁸O/¹⁶O Ratios of Differentially Stable-Isotope Labeled Peptides in the Context of Postdigestion ¹⁸O Exchange/Labeling

Differential 18O/16O stable isotope labeling of peptides that relies on enzyme-catalyzed oxygen exchange at their carboxyl termini in the presence of H218O has been widely used for relative quantitation of peptides/proteins. The role of tryptic proteolysis in bottom-up shotgun proteomics and low reagent costs have made trypsin-catalyzed 18O postdigestion exchange a convenient and affordable stable isotope labeling approach. However, it is known that trypsin-catalyzed 18O exchange at the carboxyl terminus is in many instances inhomogeneous/incomplete. The extent of the 18O exchange/incorporation fluctuates from peptide to peptide mostly due to variable enzyme−substrate affinity. Thus, accurate calculation and interpretation of peptide ratios are analytically complicated and in some regard deficient. Therefore, a computational approach capable of improved measurement of actual 18O incorporation for each differentially labeled peptide pair is needed. In this regard, we have developed an algorithmic method that relies on the trapezoidal rule to integrate peak intensities of all detected isotopic species across a particular peptide ion over the retention time, which fits the isotopic manifold to Poisson distributions. Optimal values for manifold fitting were calculated and then 18O/16O ratios derived via evolutionary programming. The algorithm is tested using trypsin-catalyzed 18O postdigestion exchange to differentially label bovine serum albumin (BSA) at a priori determined ratios. Both accuracy and precision are improved utilizing this rigorous mathematical approach. We further demonstrate the effectiveness of this method to accurately calculate 18O/16O ratios in a large scale proteomic quantitation of detergent resistant membrane microdomains (DRMMs) isolated from cells expressing wild-type HIV-1 Gag and its nonmyristylated mutant

Optimized Method for Computing ¹⁸O/¹⁶O Ratios of Differentially Stable-Isotope Labeled Peptides in the Context of Postdigestion ¹⁸O Exchange/Labeling

Differential 18O/16O stable isotope labeling of peptides that relies on enzyme-catalyzed oxygen exchange at their carboxyl termini in the presence of H218O has been widely used for relative quantitation of peptides/proteins. The role of tryptic proteolysis in bottom-up shotgun proteomics and low reagent costs have made trypsin-catalyzed 18O postdigestion exchange a convenient and affordable stable isotope labeling approach. However, it is known that trypsin-catalyzed 18O exchange at the carboxyl terminus is in many instances inhomogeneous/incomplete. The extent of the 18O exchange/incorporation fluctuates from peptide to peptide mostly due to variable enzyme−substrate affinity. Thus, accurate calculation and interpretation of peptide ratios are analytically complicated and in some regard deficient. Therefore, a computational approach capable of improved measurement of actual 18O incorporation for each differentially labeled peptide pair is needed. In this regard, we have developed an algorithmic method that relies on the trapezoidal rule to integrate peak intensities of all detected isotopic species across a particular peptide ion over the retention time, which fits the isotopic manifold to Poisson distributions. Optimal values for manifold fitting were calculated and then 18O/16O ratios derived via evolutionary programming. The algorithm is tested using trypsin-catalyzed 18O postdigestion exchange to differentially label bovine serum albumin (BSA) at a priori determined ratios. Both accuracy and precision are improved utilizing this rigorous mathematical approach. We further demonstrate the effectiveness of this method to accurately calculate 18O/16O ratios in a large scale proteomic quantitation of detergent resistant membrane microdomains (DRMMs) isolated from cells expressing wild-type HIV-1 Gag and its nonmyristylated mutant

Optimized Method for Computing ¹⁸O/¹⁶O Ratios of Differentially Stable-Isotope Labeled Peptides in the Context of Postdigestion ¹⁸O Exchange/Labeling

Differential 18O/16O stable isotope labeling of peptides that relies on enzyme-catalyzed oxygen exchange at their carboxyl termini in the presence of H218O has been widely used for relative quantitation of peptides/proteins. The role of tryptic proteolysis in bottom-up shotgun proteomics and low reagent costs have made trypsin-catalyzed 18O postdigestion exchange a convenient and affordable stable isotope labeling approach. However, it is known that trypsin-catalyzed 18O exchange at the carboxyl terminus is in many instances inhomogeneous/incomplete. The extent of the 18O exchange/incorporation fluctuates from peptide to peptide mostly due to variable enzyme−substrate affinity. Thus, accurate calculation and interpretation of peptide ratios are analytically complicated and in some regard deficient. Therefore, a computational approach capable of improved measurement of actual 18O incorporation for each differentially labeled peptide pair is needed. In this regard, we have developed an algorithmic method that relies on the trapezoidal rule to integrate peak intensities of all detected isotopic species across a particular peptide ion over the retention time, which fits the isotopic manifold to Poisson distributions. Optimal values for manifold fitting were calculated and then 18O/16O ratios derived via evolutionary programming. The algorithm is tested using trypsin-catalyzed 18O postdigestion exchange to differentially label bovine serum albumin (BSA) at a priori determined ratios. Both accuracy and precision are improved utilizing this rigorous mathematical approach. We further demonstrate the effectiveness of this method to accurately calculate 18O/16O ratios in a large scale proteomic quantitation of detergent resistant membrane microdomains (DRMMs) isolated from cells expressing wild-type HIV-1 Gag and its nonmyristylated mutant