mTMT: An Alternative, Nonisobaric, Tandem Mass Tag Allowing for Precursor-Based Quantification

Stable isotope labeling of peptides is the basis for numerous mass-spectrometry-based quantification strategies. Isobaric tagging and metabolic labeling, namely, tandem mass tagging (TMT) and SILAC, are among the most widely used techniques for relative protein quantification. Here we report an alternative, precursor-based quantification method using nonisobaric TMT variants: TMTzero (TMT0) and superheavy TMT (shTMT). We term this strategy mass difference tandem mass tagging (mTMT). These TMT variants differ by 11 mass units; however, peptides labeled with these reagents coelute, analogous to SILAC-labeled peptide pairs. As a proof-of-concept, we profiled the proteomes of two cell lines that are frequently used in neuroscience studies, SH-SY5Y and SVGp12, using mTMT and standard SILAC-labeling approaches. We show similar quantified proteins and peptides for each method, with highly correlated fold-changes between workflows. We conclude that mTMT is a suitable alternative for precursor-based protein quantification

mTMT: An Alternative, Nonisobaric, Tandem Mass Tag Allowing for Precursor-Based Quantification

Stable isotope labeling of peptides is the basis for numerous mass-spectrometry-based quantification strategies. Isobaric tagging and metabolic labeling, namely, tandem mass tagging (TMT) and SILAC, are among the most widely used techniques for relative protein quantification. Here we report an alternative, precursor-based quantification method using nonisobaric TMT variants: TMTzero (TMT0) and superheavy TMT (shTMT). We term this strategy mass difference tandem mass tagging (mTMT). These TMT variants differ by 11 mass units; however, peptides labeled with these reagents coelute, analogous to SILAC-labeled peptide pairs. As a proof-of-concept, we profiled the proteomes of two cell lines that are frequently used in neuroscience studies, SH-SY5Y and SVGp12, using mTMT and standard SILAC-labeling approaches. We show similar quantified proteins and peptides for each method, with highly correlated fold-changes between workflows. We conclude that mTMT is a suitable alternative for precursor-based protein quantification

Inserting Pre-analytical Chromatographic Priming Runs Significantly Improves Targeted Pathway Proteomics with Sample Multiplexing

GoDig, a platform for targeted pathway proteomics without the need for manual assay scheduling or synthetic standards, is a powerful, flexible, and easy-to-use method that uses tandem mass tags to increase sample throughput up to 18-fold relative to label-free methods. Though the protein-level success rates of GoDig are high, the peptide-level success rates are more limited, hampering assays of harder-to-quantify proteins and site-specific phenomena. To guide the optimization of GoDig assays as well as improvements to the GoDig platform, we created GoDigViewer, a new stand-alone software that provides detailed visualizations of GoDig runs. GoDigViewer guided the implementation of “priming runs,” an acquisition mode with significantly higher success rates. In this mode, two or more chromatographic priming runs are automatically performed to improve the accuracy and precision of target elution orders, followed by analytical runs which quantify targets. Using priming runs, success rates exceeded 97% for a list of 400 peptide targets and 95% for a list of 200 targets that are usually not quantified using untargeted mass spectrometry. We used priming runs to establish a quantitative assay of 125 macroautophagy proteins that had a >95% success rate and revealed differences in macroautophagy expression profiles across four human cell lines

Global Analysis of Protein Expression and Phosphorylation Levels in Nicotine-Treated Pancreatic Stellate Cells

Smoking is a risk factor in pancreatic disease; however, the biochemical mechanisms correlating smoking with pancreatic dysfunction remain poorly understood. Strategies using multiplexed isobaric tag-based mass spectrometry facilitate the study of drug-induced perturbations on biological systems. Here, we present the first large-scale analysis of the proteomic and phosphoproteomic alterations in pancreatic stellate cells following treatment with two nicotinic acetylcholine receptor (nAChR) ligands: nicotine and α-bungarotoxin. We treated cells with nicotine or α-bungarotoxin for 12 h in triplicate and compared alterations in protein expression and phosphorylation levels to mock-treated cells using a tandem mass tag (TMT9plex)-based approach. Over 8100 proteins were quantified across all nine samples, of which 46 were altered in abundance upon treatment with nicotine. Proteins with increased abundance included those associated with neurons, defense mechanisms, indicators of pancreatic disease, and lysosomal proteins. In addition, we measured differences for ∼16 000 phosphorylation sites across all nine samples using a titanium dioxide-based strategy, of which 132 sites were altered with nicotine and 451 with α-bungarotoxin treatment. Many altered phosphorylation sites were involved in nuclear function and transcriptional events. This study supports the development of future targeted investigations to establish a better understanding for the role of nicotine and associated receptors in pancreatic disease

Global Analysis of Protein Expression and Phosphorylation Levels in Nicotine-Treated Pancreatic Stellate Cells

Smoking is a risk factor in pancreatic disease; however, the biochemical mechanisms correlating smoking with pancreatic dysfunction remain poorly understood. Strategies using multiplexed isobaric tag-based mass spectrometry facilitate the study of drug-induced perturbations on biological systems. Here, we present the first large-scale analysis of the proteomic and phosphoproteomic alterations in pancreatic stellate cells following treatment with two nicotinic acetylcholine receptor (nAChR) ligands: nicotine and α-bungarotoxin. We treated cells with nicotine or α-bungarotoxin for 12 h in triplicate and compared alterations in protein expression and phosphorylation levels to mock-treated cells using a tandem mass tag (TMT9plex)-based approach. Over 8100 proteins were quantified across all nine samples, of which 46 were altered in abundance upon treatment with nicotine. Proteins with increased abundance included those associated with neurons, defense mechanisms, indicators of pancreatic disease, and lysosomal proteins. In addition, we measured differences for ∼16 000 phosphorylation sites across all nine samples using a titanium dioxide-based strategy, of which 132 sites were altered with nicotine and 451 with α-bungarotoxin treatment. Many altered phosphorylation sites were involved in nuclear function and transcriptional events. This study supports the development of future targeted investigations to establish a better understanding for the role of nicotine and associated receptors in pancreatic disease

Filter-Based Protein Digestion (FPD): A Detergent-Free and Scaffold-Based Strategy for TMT Workflows

High-throughput proteome profiling requires thorough optimization to achieve comprehensive analysis. We developed a filter aided sample preparation (FASP)-like, detergent-free method, termed Filter-Based Protein Digestion (FPD). We compared FPD to protein extraction methods commonly used in isobaric tag-based proteome profiling, namely trichloroacetic acid (TCA) and chloroform–methanol (C–M) precipitation. We divided a mammalian whole cell lysate from the SH-SY5Y neuroblastoma cell line for parallel protein processing with TCA (<i>n</i> = 3), C–M (<i>n</i> = 2), and FPD using either 10 kDa (<i>n</i> = 3) or 30 kDa (<i>n</i> = 3) molecular weight cutoff membranes. We labeled each sample with tandem mass tag (TMT) reagents to construct a TMT11-plex experiment. In total, 8654 proteins were quantified across all samples. Pairwise comparisons showed very little deviation for individual protein abundance measurements between the two FPD methods, whereas TCA and FPD showed the most difference. Specifically, membrane proteins were more readily quantified when samples were processed using TCA precipitation than other methods tested. However, globally, only 4% of proteins differed greater than 4-fold in the most divergent pair of protein extraction methods (i.e., FPD10 and TCA). We conclude that the detergent-free FPD strategy, particularly using the faster-flowing 30 kDa filter, is a seamless alteration to high-throughput TMT workflows

Global Analysis of Protein Expression and Phosphorylation Levels in Nicotine-Treated Pancreatic Stellate Cells

Smoking is a risk factor in pancreatic disease; however, the biochemical mechanisms correlating smoking with pancreatic dysfunction remain poorly understood. Strategies using multiplexed isobaric tag-based mass spectrometry facilitate the study of drug-induced perturbations on biological systems. Here, we present the first large-scale analysis of the proteomic and phosphoproteomic alterations in pancreatic stellate cells following treatment with two nicotinic acetylcholine receptor (nAChR) ligands: nicotine and α-bungarotoxin. We treated cells with nicotine or α-bungarotoxin for 12 h in triplicate and compared alterations in protein expression and phosphorylation levels to mock-treated cells using a tandem mass tag (TMT9plex)-based approach. Over 8100 proteins were quantified across all nine samples, of which 46 were altered in abundance upon treatment with nicotine. Proteins with increased abundance included those associated with neurons, defense mechanisms, indicators of pancreatic disease, and lysosomal proteins. In addition, we measured differences for ∼16 000 phosphorylation sites across all nine samples using a titanium dioxide-based strategy, of which 132 sites were altered with nicotine and 451 with α-bungarotoxin treatment. Many altered phosphorylation sites were involved in nuclear function and transcriptional events. This study supports the development of future targeted investigations to establish a better understanding for the role of nicotine and associated receptors in pancreatic disease

Phosphoproteome Analysis of Fission Yeast

Phosphorylation is a key regulator of many events in eukaryotic cells. The acquisition of large-scale phosphorylation data sets from model organisms can pinpoint conserved regulatory inputs and reveal kinase−substrate relationships. Here, we provide the first large-scale phosphorylation analysis of the fission yeast, Schizosaccharomyces pombe. Protein from thiabendazole-treated cells was separated by preparative SDS-PAGE and digested with trypsin. The resulting peptides were subjected to either IMAC or TiO2 phosphopeptide enrichment methods and then analyzed by LC−MS/MS using an LTQ-Orbitrap mass spectrometer. In total, 2887 distinct phosphorylation sites were identified from 1194 proteins with an estimated false-discovery rate of <0.5% at the peptide level. A comparison of the two different enrichment methods is presented, supporting the finding that they are complementary. Finally, phosphorylation sites were examined for phosphorylation-specific motifs and evolutionary conservation. These analyses revealed both motifs and specific phosphorylation events identified in S. pombe were conserved and predicted novel phosphorylation in mammals

Filter-Based Protein Digestion (FPD): A Detergent-Free and Scaffold-Based Strategy for TMT Workflows

High-throughput proteome profiling requires thorough optimization to achieve comprehensive analysis. We developed a filter aided sample preparation (FASP)-like, detergent-free method, termed Filter-Based Protein Digestion (FPD). We compared FPD to protein extraction methods commonly used in isobaric tag-based proteome profiling, namely trichloroacetic acid (TCA) and chloroform–methanol (C–M) precipitation. We divided a mammalian whole cell lysate from the SH-SY5Y neuroblastoma cell line for parallel protein processing with TCA (<i>n</i> = 3), C–M (<i>n</i> = 2), and FPD using either 10 kDa (<i>n</i> = 3) or 30 kDa (<i>n</i> = 3) molecular weight cutoff membranes. We labeled each sample with tandem mass tag (TMT) reagents to construct a TMT11-plex experiment. In total, 8654 proteins were quantified across all samples. Pairwise comparisons showed very little deviation for individual protein abundance measurements between the two FPD methods, whereas TCA and FPD showed the most difference. Specifically, membrane proteins were more readily quantified when samples were processed using TCA precipitation than other methods tested. However, globally, only 4% of proteins differed greater than 4-fold in the most divergent pair of protein extraction methods (i.e., FPD10 and TCA). We conclude that the detergent-free FPD strategy, particularly using the faster-flowing 30 kDa filter, is a seamless alteration to high-throughput TMT workflows