Coupling a Detergent Lysis/Cleanup Methodology with Intact Protein Fractionation for Enhanced Proteome Characterization

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four detergent cleanup methods (trichloroacetic acid (TCA) precipitation, chloroform/methanol/water (CMW) extraction, a commercial detergent removal spin column method (DRS) and filter-aided sample preparation (FASP)) to provide efficiency benchmarks with respect to protein, peptide, and spectral identifications in each case. Our results show that for protein-limited samples, FASP outperforms the other three cleanup methods, while at high protein amounts, all the methods are comparable. This information was used to investigate and contrast molecular weight-based fractionated with unfractionated lysates from three increasingly complex samples (Escherichia coli K-12, a five microbial isolate mixture, and a natural microbial community groundwater sample), all of which were prepared with an SDS-FASP approach. The additional fractionation step enhanced the number of protein identifications by 8% to 25% over the unfractionated approach across the three samples

Coupling a Detergent Lysis/Cleanup Methodology with Intact Protein Fractionation for Enhanced Proteome Characterization

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four detergent cleanup methods (trichloroacetic acid (TCA) precipitation, chloroform/methanol/water (CMW) extraction, a commercial detergent removal spin column method (DRS) and filter-aided sample preparation (FASP)) to provide efficiency benchmarks with respect to protein, peptide, and spectral identifications in each case. Our results show that for protein-limited samples, FASP outperforms the other three cleanup methods, while at high protein amounts, all the methods are comparable. This information was used to investigate and contrast molecular weight-based fractionated with unfractionated lysates from three increasingly complex samples (Escherichia coli K-12, a five microbial isolate mixture, and a natural microbial community groundwater sample), all of which were prepared with an SDS-FASP approach. The additional fractionation step enhanced the number of protein identifications by 8% to 25% over the unfractionated approach across the three samples

Coupling a Detergent Lysis/Cleanup Methodology with Intact Protein Fractionation for Enhanced Proteome Characterization

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four detergent cleanup methods (trichloroacetic acid (TCA) precipitation, chloroform/methanol/water (CMW) extraction, a commercial detergent removal spin column method (DRS) and filter-aided sample preparation (FASP)) to provide efficiency benchmarks with respect to protein, peptide, and spectral identifications in each case. Our results show that for protein-limited samples, FASP outperforms the other three cleanup methods, while at high protein amounts, all the methods are comparable. This information was used to investigate and contrast molecular weight-based fractionated with unfractionated lysates from three increasingly complex samples (Escherichia coli K-12, a five microbial isolate mixture, and a natural microbial community groundwater sample), all of which were prepared with an SDS-FASP approach. The additional fractionation step enhanced the number of protein identifications by 8% to 25% over the unfractionated approach across the three samples

Coupling a Detergent Lysis/Cleanup Methodology with Intact Protein Fractionation for Enhanced Proteome Characterization

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four detergent cleanup methods (trichloroacetic acid (TCA) precipitation, chloroform/methanol/water (CMW) extraction, a commercial detergent removal spin column method (DRS) and filter-aided sample preparation (FASP)) to provide efficiency benchmarks with respect to protein, peptide, and spectral identifications in each case. Our results show that for protein-limited samples, FASP outperforms the other three cleanup methods, while at high protein amounts, all the methods are comparable. This information was used to investigate and contrast molecular weight-based fractionated with unfractionated lysates from three increasingly complex samples (Escherichia coli K-12, a five microbial isolate mixture, and a natural microbial community groundwater sample), all of which were prepared with an SDS-FASP approach. The additional fractionation step enhanced the number of protein identifications by 8% to 25% over the unfractionated approach across the three samples

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study

Coupling a Detergent Lysis/Cleanup Methodology with Intact Protein Fractionation for Enhanced Proteome Characterization

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four detergent cleanup methods (trichloroacetic acid (TCA) precipitation, chloroform/methanol/water (CMW) extraction, a commercial detergent removal spin column method (DRS) and filter-aided sample preparation (FASP)) to provide efficiency benchmarks with respect to protein, peptide, and spectral identifications in each case. Our results show that for protein-limited samples, FASP outperforms the other three cleanup methods, while at high protein amounts, all the methods are comparable. This information was used to investigate and contrast molecular weight-based fractionated with unfractionated lysates from three increasingly complex samples (Escherichia coli K-12, a five microbial isolate mixture, and a natural microbial community groundwater sample), all of which were prepared with an SDS-FASP approach. The additional fractionation step enhanced the number of protein identifications by 8% to 25% over the unfractionated approach across the three samples

Coupling a Detergent Lysis/Cleanup Methodology with Intact Protein Fractionation for Enhanced Proteome Characterization

The expanding use of surfactants for proteome sample preparations has prompted the need to systematically optimize the application and removal of these MS-deleterious agents prior to proteome measurements. Here we compare four detergent cleanup methods (trichloroacetic acid (TCA) precipitation, chloroform/methanol/water (CMW) extraction, a commercial detergent removal spin column method (DRS) and filter-aided sample preparation (FASP)) to provide efficiency benchmarks with respect to protein, peptide, and spectral identifications in each case. Our results show that for protein-limited samples, FASP outperforms the other three cleanup methods, while at high protein amounts, all the methods are comparable. This information was used to investigate and contrast molecular weight-based fractionated with unfractionated lysates from three increasingly complex samples (Escherichia coli K-12, a five microbial isolate mixture, and a natural microbial community groundwater sample), all of which were prepared with an SDS-FASP approach. The additional fractionation step enhanced the number of protein identifications by 8% to 25% over the unfractionated approach across the three samples

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study

Systematic Comparison of Label-Free, Metabolic Labeling, and Isobaric Chemical Labeling for Quantitative Proteomics on LTQ Orbitrap Velos

A variety of quantitative proteomics methods have been developed, including label-free, metabolic labeling, and isobaric chemical labeling using iTRAQ or TMT. Here, these methods were compared in terms of the depth of proteome coverage, quantification accuracy, precision, and reproducibility using a high-performance hybrid mass spectrometer, LTQ Orbitrap Velos. Our results show that (1) the spectral counting method provides the deepest proteome coverage for identification, but its quantification performance is worse than labeling-based approaches, especially the quantification reproducibility; (2) metabolic labeling and isobaric chemical labeling are capable of accurate, precise, and reproducible quantification and provide deep proteome coverage for quantification; isobaric chemical labeling surpasses metabolic labeling in terms of quantification precision and reproducibility; and (3) iTRAQ and TMT perform similarly in all aspects compared in the current study using a CID-HCD dual scan configuration. On the basis of the unique advantages of each method, we provide guidance for selection of the appropriate method for a quantitative proteomics study

Strigolactone-Regulated Proteins Revealed by iTRAQ-Based Quantitative Proteomics in <i>Arabidopsis</i>

Strigolactones (SLs) are a new class of plant hormones. In addition to acting as a key inhibitor of shoot branching, SLs stimulate seed germination of root parasitic plants and promote hyphal branching and root colonization of symbiotic arbuscular mycorrhizal fungi. They also regulate many other aspects of plant growth and development. At the transcription level, SL-regulated genes have been reported. However, nothing is known about the proteome regulated by this new class of plant hormones. A quantitative proteomics approach using an isobaric chemical labeling reagent, iTRAQ, to identify the proteome regulated by SLs in <i>Arabidopsis</i> seedlings is presented. It was found that SLs regulate the expression of about three dozen proteins that have not been previously assigned to SL pathways. These findings provide a new tool to investigate the molecular mechanism of action of SLs