Comprehensive Comparison of iTRAQ and Label-free LC-Based Quantitative Proteomics Approaches Using Two <i>Chlamydomonas reinhardtii</i> Strains of Interest for Biofuels Engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approachesiTRAQ and label-freewere implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two <i>Chlamydomonas reinhardtii</i> strains in the context of alternative biofuels production. The strain comparison includes <i>sta6</i> (a starch-less mutant of <i>cw15</i>) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain <i>cw15</i> (a cell wall-deficient <i>C. reinhardtii</i> strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between <i>cw15</i> and <i>sta6</i> reveals already known but also new mechanisms likely responsible for the production of lipids in <i>sta6</i> and sets the baseline for future studies aimed at engineering these strains for high oil production

Comprehensive Comparison of iTRAQ and Label-free LC-Based Quantitative Proteomics Approaches Using Two <i>Chlamydomonas reinhardtii</i> Strains of Interest for Biofuels Engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approachesiTRAQ and label-freewere implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two <i>Chlamydomonas reinhardtii</i> strains in the context of alternative biofuels production. The strain comparison includes <i>sta6</i> (a starch-less mutant of <i>cw15</i>) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain <i>cw15</i> (a cell wall-deficient <i>C. reinhardtii</i> strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between <i>cw15</i> and <i>sta6</i> reveals already known but also new mechanisms likely responsible for the production of lipids in <i>sta6</i> and sets the baseline for future studies aimed at engineering these strains for high oil production

Comprehensive Comparison of iTRAQ and Label-free LC-Based Quantitative Proteomics Approaches Using Two <i>Chlamydomonas reinhardtii</i> Strains of Interest for Biofuels Engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approachesiTRAQ and label-freewere implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two <i>Chlamydomonas reinhardtii</i> strains in the context of alternative biofuels production. The strain comparison includes <i>sta6</i> (a starch-less mutant of <i>cw15</i>) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain <i>cw15</i> (a cell wall-deficient <i>C. reinhardtii</i> strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between <i>cw15</i> and <i>sta6</i> reveals already known but also new mechanisms likely responsible for the production of lipids in <i>sta6</i> and sets the baseline for future studies aimed at engineering these strains for high oil production

Comprehensive Comparison of iTRAQ and Label-free LC-Based Quantitative Proteomics Approaches Using Two <i>Chlamydomonas reinhardtii</i> Strains of Interest for Biofuels Engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approachesiTRAQ and label-freewere implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two <i>Chlamydomonas reinhardtii</i> strains in the context of alternative biofuels production. The strain comparison includes <i>sta6</i> (a starch-less mutant of <i>cw15</i>) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain <i>cw15</i> (a cell wall-deficient <i>C. reinhardtii</i> strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between <i>cw15</i> and <i>sta6</i> reveals already known but also new mechanisms likely responsible for the production of lipids in <i>sta6</i> and sets the baseline for future studies aimed at engineering these strains for high oil production

Comprehensive Comparison of iTRAQ and Label-free LC-Based Quantitative Proteomics Approaches Using Two <i>Chlamydomonas reinhardtii</i> Strains of Interest for Biofuels Engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approachesiTRAQ and label-freewere implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two <i>Chlamydomonas reinhardtii</i> strains in the context of alternative biofuels production. The strain comparison includes <i>sta6</i> (a starch-less mutant of <i>cw15</i>) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain <i>cw15</i> (a cell wall-deficient <i>C. reinhardtii</i> strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between <i>cw15</i> and <i>sta6</i> reveals already known but also new mechanisms likely responsible for the production of lipids in <i>sta6</i> and sets the baseline for future studies aimed at engineering these strains for high oil production

Comprehensive Comparison of iTRAQ and Label-free LC-Based Quantitative Proteomics Approaches Using Two <i>Chlamydomonas reinhardtii</i> Strains of Interest for Biofuels Engineering

Comprehensive comparisons of quantitative proteomics techniques are rare in the literature, yet they are crucially important for optimal selection of approaches and methodologies that are ideal for a given proteomics initiative. In this study, two LC-based quantitative proteomics approachesiTRAQ and label-freewere implemented using the LTQ-Orbitrap Velos platform. For this comparison, the model used was the total protein content from two <i>Chlamydomonas reinhardtii</i> strains in the context of alternative biofuels production. The strain comparison includes <i>sta6</i> (a starch-less mutant of <i>cw15</i>) that produces twice as many lipid bodies (LB) containing triacylglycerols (TAGs) as its parental strain <i>cw15</i> (a cell wall-deficient <i>C. reinhardtii</i> strain) under nitrogen starvation. Internal standard addition was used to rigorously assess the quantitation accuracy and precision of each method. Results from iTRAQ-4plex labeling using HCD (higher energy collision-induced dissociation) fragmentation were compared to those obtained using a label-free approach based on the peak area of intact peptides and collision-induced dissociation. The accuracy and precision, number of identified/quantified proteins and statistically significant protein differences detected, as well as efficiency of these two quantitative proteomics methods were evaluated and compared. Four technical and three biological replicates of each strain were performed to assess both the technical and biological variation of both approaches. A total of 896 and 639 proteins were identified with high confidence, and 329 and 124 proteins were quantified significantly with label-free and iTRAQ, respectively, using biological replicates. The results showed that both iTRAQ labeling and label-free methods provide high quality quantitative and qualitative data using nano-LC coupled with the LTQ-Orbitrap Velos mass spectrometer, but the selection of the optimal approach is dependent on experimental design and the biological question to be addressed. The functional categorization of the differential proteins between <i>cw15</i> and <i>sta6</i> reveals already known but also new mechanisms likely responsible for the production of lipids in <i>sta6</i> and sets the baseline for future studies aimed at engineering these strains for high oil production

Quantitative Proteomics-Based Analysis Supports a Significant Role of GTG Proteins in Regulation of ABA Response in <i>Arabidopsis</i> Roots

Abscisic acid (ABA) is proposed to be perceived by multiple receptors in plants. We have previously reported on the role of two GPCR-type G-proteins (GTG proteins) as plasma membrane-localized ABA receptors in <i>Arabidopsis thaliana</i>. However, due to the presence of multiple transmembrane domains, detailed structural and biochemical characterization of GTG proteins remains limited. Since ABA induces substantial changes in the proteome of plants, a labeling LC-based quantitative proteomics approach was applied to elucidate the global effects and possible downstream targets of GTG1/GTG2 proteins. Quantitative differences in protein abundance between wild-type and <i>gtg1gtg2</i> were analyzed for evaluation of the effect of ABA on the root proteome and its dependence on the presence of functional GTG1/GTG2 proteins. The results presented in this study reveal the most comprehensive ABA-responsive root proteome reported to date in <i>Arabidopsis</i>. Notably, the majority of ABA-responsive proteins required the presence of GTG proteins, supporting their key role in ABA signaling. These observations were further confirmed by additional experiments. Overall, comparison of the ABA-dependent protein abundance changes in wild-type versus <i>gtg1gtg2</i> provides clues to their possible links with some of the well-established effectors of the ABA signaling pathways and their role in mediating phytohormone cross-talk

Quantitative Proteomics-Based Analysis Supports a Significant Role of GTG Proteins in Regulation of ABA Response in <i>Arabidopsis</i> Roots

Abscisic acid (ABA) is proposed to be perceived by multiple receptors in plants. We have previously reported on the role of two GPCR-type G-proteins (GTG proteins) as plasma membrane-localized ABA receptors in <i>Arabidopsis thaliana</i>. However, due to the presence of multiple transmembrane domains, detailed structural and biochemical characterization of GTG proteins remains limited. Since ABA induces substantial changes in the proteome of plants, a labeling LC-based quantitative proteomics approach was applied to elucidate the global effects and possible downstream targets of GTG1/GTG2 proteins. Quantitative differences in protein abundance between wild-type and <i>gtg1gtg2</i> were analyzed for evaluation of the effect of ABA on the root proteome and its dependence on the presence of functional GTG1/GTG2 proteins. The results presented in this study reveal the most comprehensive ABA-responsive root proteome reported to date in <i>Arabidopsis</i>. Notably, the majority of ABA-responsive proteins required the presence of GTG proteins, supporting their key role in ABA signaling. These observations were further confirmed by additional experiments. Overall, comparison of the ABA-dependent protein abundance changes in wild-type versus <i>gtg1gtg2</i> provides clues to their possible links with some of the well-established effectors of the ABA signaling pathways and their role in mediating phytohormone cross-talk

Quantitative Proteomics-Based Analysis Supports a Significant Role of GTG Proteins in Regulation of ABA Response in <i>Arabidopsis</i> Roots

Abscisic acid (ABA) is proposed to be perceived by multiple receptors in plants. We have previously reported on the role of two GPCR-type G-proteins (GTG proteins) as plasma membrane-localized ABA receptors in <i>Arabidopsis thaliana</i>. However, due to the presence of multiple transmembrane domains, detailed structural and biochemical characterization of GTG proteins remains limited. Since ABA induces substantial changes in the proteome of plants, a labeling LC-based quantitative proteomics approach was applied to elucidate the global effects and possible downstream targets of GTG1/GTG2 proteins. Quantitative differences in protein abundance between wild-type and <i>gtg1gtg2</i> were analyzed for evaluation of the effect of ABA on the root proteome and its dependence on the presence of functional GTG1/GTG2 proteins. The results presented in this study reveal the most comprehensive ABA-responsive root proteome reported to date in <i>Arabidopsis</i>. Notably, the majority of ABA-responsive proteins required the presence of GTG proteins, supporting their key role in ABA signaling. These observations were further confirmed by additional experiments. Overall, comparison of the ABA-dependent protein abundance changes in wild-type versus <i>gtg1gtg2</i> provides clues to their possible links with some of the well-established effectors of the ABA signaling pathways and their role in mediating phytohormone cross-talk

Quantitative Proteomics-Based Analysis Supports a Significant Role of GTG Proteins in Regulation of ABA Response in <i>Arabidopsis</i> Roots

Abscisic acid (ABA) is proposed to be perceived by multiple receptors in plants. We have previously reported on the role of two GPCR-type G-proteins (GTG proteins) as plasma membrane-localized ABA receptors in <i>Arabidopsis thaliana</i>. However, due to the presence of multiple transmembrane domains, detailed structural and biochemical characterization of GTG proteins remains limited. Since ABA induces substantial changes in the proteome of plants, a labeling LC-based quantitative proteomics approach was applied to elucidate the global effects and possible downstream targets of GTG1/GTG2 proteins. Quantitative differences in protein abundance between wild-type and <i>gtg1gtg2</i> were analyzed for evaluation of the effect of ABA on the root proteome and its dependence on the presence of functional GTG1/GTG2 proteins. The results presented in this study reveal the most comprehensive ABA-responsive root proteome reported to date in <i>Arabidopsis</i>. Notably, the majority of ABA-responsive proteins required the presence of GTG proteins, supporting their key role in ABA signaling. These observations were further confirmed by additional experiments. Overall, comparison of the ABA-dependent protein abundance changes in wild-type versus <i>gtg1gtg2</i> provides clues to their possible links with some of the well-established effectors of the ABA signaling pathways and their role in mediating phytohormone cross-talk