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SCIEX sciex tripletof 6600
Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB <t>Sciex</t> TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).
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1) Product Images from "Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics"

Article Title: Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics

Journal: bioRxiv

doi: 10.1101/2020.04.13.038810

Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).
Figure Legend Snippet: Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).

Techniques Used: Liquid Chromatography with Mass Spectroscopy

2) Product Images from "A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS"

Article Title: A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS

Journal: Scientific Data

doi: 10.1038/s41597-020-00724-7

Data acquisition workflow to generate a comprehensive E. coli assay library, quality evaluation with DIALib-QC and DIA/SWATH-MS quantification by Spectronaut. A comprehensive DIA/SWATH assay library for E. coli was generated from whole cell lysate, fractionated samples, overexpressed proteins, and supplemented with synthetic peptides. Samples were analyzed with data-dependent acquisition (DDA) mass spectrometry on TripleTOF 5600+ and TripleTOF 6600 instruments resulting in 209 data files. To generate a DIA/SWATH library, the raw data files were converted to mzML format using the ABSCIEX converter with the profile mode extraction parameter. The mzML files were searched against the reference proteome using both Comet and X!Tandem search engines. The identified sequences were then statistically validated using the Trans-Proteomic Pipeline (TPP) including PeptideProphet and iProphet. MAYU was applied to control the FDR at the protein level. Using SpectraST, confidently assigned spectra were converted into a redundant spectral library and retention times are normalized in iRT space using RTCatalog, then a consensus spectrum library was generated. The assay library was extracted from the consensus library using the spectrast2tsv.py script. Libraries were evaluated with the DIA Library Quality Control (DIALib-QC, www.swathatlas.org ) tool and their assessment reports were generated. The performance of the TripleTOF E. coli spectral library was evaluated based on the identification and quantitation of peptides and proteins in data-independent acquisition (DIA) methods with different gradient lengths using the Spectronaut analysis software.
Figure Legend Snippet: Data acquisition workflow to generate a comprehensive E. coli assay library, quality evaluation with DIALib-QC and DIA/SWATH-MS quantification by Spectronaut. A comprehensive DIA/SWATH assay library for E. coli was generated from whole cell lysate, fractionated samples, overexpressed proteins, and supplemented with synthetic peptides. Samples were analyzed with data-dependent acquisition (DDA) mass spectrometry on TripleTOF 5600+ and TripleTOF 6600 instruments resulting in 209 data files. To generate a DIA/SWATH library, the raw data files were converted to mzML format using the ABSCIEX converter with the profile mode extraction parameter. The mzML files were searched against the reference proteome using both Comet and X!Tandem search engines. The identified sequences were then statistically validated using the Trans-Proteomic Pipeline (TPP) including PeptideProphet and iProphet. MAYU was applied to control the FDR at the protein level. Using SpectraST, confidently assigned spectra were converted into a redundant spectral library and retention times are normalized in iRT space using RTCatalog, then a consensus spectrum library was generated. The assay library was extracted from the consensus library using the spectrast2tsv.py script. Libraries were evaluated with the DIA Library Quality Control (DIALib-QC, www.swathatlas.org ) tool and their assessment reports were generated. The performance of the TripleTOF E. coli spectral library was evaluated based on the identification and quantitation of peptides and proteins in data-independent acquisition (DIA) methods with different gradient lengths using the Spectronaut analysis software.

Techniques Used: Generated, Mass Spectrometry, Quantitation Assay, Software

3) Product Images from "SWATH-MS dataset of heat-shock treated Drosophila melanogaster embryos"

Article Title: SWATH-MS dataset of heat-shock treated Drosophila melanogaster embryos

Journal: Data in Brief

doi: 10.1016/j.dib.2016.11.028

A) Overall strategy to characterize the dynamics of the D. melanogaster embryonic proteome after heat-shock treatment (HS) using SWATH-MS. Embryos were collected and treated for 0.5, 1 or 3 h at 37 °C or untreated. Proteins were extracted, digested with trypsin and HRM peptides were spiked into the samples before injection. The samples were analysed using SWATH acquisition mode on a Sciex Triple-TOF 6600. The resulting files were analysed with Spectronaut TM . 2529 proteins were quantified using this workflow. B) Reproducibility of the protein intensity measurements between biological replicates. The Log 10 transformed protein intensities were plotted for replicates 1 and 2 of the untreated condition. C) The Coefficient of variation (CVs) between the biological replicates were calculated for each condition.
Figure Legend Snippet: A) Overall strategy to characterize the dynamics of the D. melanogaster embryonic proteome after heat-shock treatment (HS) using SWATH-MS. Embryos were collected and treated for 0.5, 1 or 3 h at 37 °C or untreated. Proteins were extracted, digested with trypsin and HRM peptides were spiked into the samples before injection. The samples were analysed using SWATH acquisition mode on a Sciex Triple-TOF 6600. The resulting files were analysed with Spectronaut TM . 2529 proteins were quantified using this workflow. B) Reproducibility of the protein intensity measurements between biological replicates. The Log 10 transformed protein intensities were plotted for replicates 1 and 2 of the untreated condition. C) The Coefficient of variation (CVs) between the biological replicates were calculated for each condition.

Techniques Used: Mass Spectrometry, Injection, Transformation Assay

4) Product Images from "Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics"

Article Title: Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics

Journal: bioRxiv

doi: 10.1101/2020.04.13.038810

Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).
Figure Legend Snippet: Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).

Techniques Used: Liquid Chromatography with Mass Spectroscopy

5) Product Images from "A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS"

Article Title: A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS

Journal: Scientific Data

doi: 10.1038/s41597-020-00724-7

Data acquisition workflow to generate a comprehensive E. coli assay library, quality evaluation with DIALib-QC and DIA/SWATH-MS quantification by Spectronaut. A comprehensive DIA/SWATH assay library for E. coli was generated from whole cell lysate, fractionated samples, overexpressed proteins, and supplemented with synthetic peptides. Samples were analyzed with data-dependent acquisition (DDA) mass spectrometry on TripleTOF 5600+ and TripleTOF 6600 instruments resulting in 209 data files. To generate a DIA/SWATH library, the raw data files were converted to mzML format using the ABSCIEX converter with the profile mode extraction parameter. The mzML files were searched against the reference proteome using both Comet and X!Tandem search engines. The identified sequences were then statistically validated using the Trans-Proteomic Pipeline (TPP) including PeptideProphet and iProphet. MAYU was applied to control the FDR at the protein level. Using SpectraST, confidently assigned spectra were converted into a redundant spectral library and retention times are normalized in iRT space using RTCatalog, then a consensus spectrum library was generated. The assay library was extracted from the consensus library using the spectrast2tsv.py script. Libraries were evaluated with the DIA Library Quality Control (DIALib-QC, www.swathatlas.org ) tool and their assessment reports were generated. The performance of the TripleTOF E. coli spectral library was evaluated based on the identification and quantitation of peptides and proteins in data-independent acquisition (DIA) methods with different gradient lengths using the Spectronaut analysis software.
Figure Legend Snippet: Data acquisition workflow to generate a comprehensive E. coli assay library, quality evaluation with DIALib-QC and DIA/SWATH-MS quantification by Spectronaut. A comprehensive DIA/SWATH assay library for E. coli was generated from whole cell lysate, fractionated samples, overexpressed proteins, and supplemented with synthetic peptides. Samples were analyzed with data-dependent acquisition (DDA) mass spectrometry on TripleTOF 5600+ and TripleTOF 6600 instruments resulting in 209 data files. To generate a DIA/SWATH library, the raw data files were converted to mzML format using the ABSCIEX converter with the profile mode extraction parameter. The mzML files were searched against the reference proteome using both Comet and X!Tandem search engines. The identified sequences were then statistically validated using the Trans-Proteomic Pipeline (TPP) including PeptideProphet and iProphet. MAYU was applied to control the FDR at the protein level. Using SpectraST, confidently assigned spectra were converted into a redundant spectral library and retention times are normalized in iRT space using RTCatalog, then a consensus spectrum library was generated. The assay library was extracted from the consensus library using the spectrast2tsv.py script. Libraries were evaluated with the DIA Library Quality Control (DIALib-QC, www.swathatlas.org ) tool and their assessment reports were generated. The performance of the TripleTOF E. coli spectral library was evaluated based on the identification and quantitation of peptides and proteins in data-independent acquisition (DIA) methods with different gradient lengths using the Spectronaut analysis software.

Techniques Used: Generated, Mass Spectrometry, Quantitation Assay, Software

6) Product Images from "A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS"

Article Title: A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS

Journal: Scientific Data

doi: 10.1038/s41597-020-00724-7

Data acquisition workflow to generate a comprehensive E. coli assay library, quality evaluation with DIALib-QC and DIA/SWATH-MS quantification by Spectronaut. A comprehensive DIA/SWATH assay library for E. coli was generated from whole cell lysate, fractionated samples, overexpressed proteins, and supplemented with synthetic peptides. Samples were analyzed with data-dependent acquisition (DDA) mass spectrometry on TripleTOF 5600+ and TripleTOF 6600 instruments resulting in 209 data files. To generate a DIA/SWATH library, the raw data files were converted to mzML format using the ABSCIEX converter with the profile mode extraction parameter. The mzML files were searched against the reference proteome using both Comet and X!Tandem search engines. The identified sequences were then statistically validated using the Trans-Proteomic Pipeline (TPP) including PeptideProphet and iProphet. MAYU was applied to control the FDR at the protein level. Using SpectraST, confidently assigned spectra were converted into a redundant spectral library and retention times are normalized in iRT space using RTCatalog, then a consensus spectrum library was generated. The assay library was extracted from the consensus library using the spectrast2tsv.py script. Libraries were evaluated with the DIA Library Quality Control (DIALib-QC, www.swathatlas.org ) tool and their assessment reports were generated. The performance of the TripleTOF E. coli spectral library was evaluated based on the identification and quantitation of peptides and proteins in data-independent acquisition (DIA) methods with different gradient lengths using the Spectronaut analysis software.
Figure Legend Snippet: Data acquisition workflow to generate a comprehensive E. coli assay library, quality evaluation with DIALib-QC and DIA/SWATH-MS quantification by Spectronaut. A comprehensive DIA/SWATH assay library for E. coli was generated from whole cell lysate, fractionated samples, overexpressed proteins, and supplemented with synthetic peptides. Samples were analyzed with data-dependent acquisition (DDA) mass spectrometry on TripleTOF 5600+ and TripleTOF 6600 instruments resulting in 209 data files. To generate a DIA/SWATH library, the raw data files were converted to mzML format using the ABSCIEX converter with the profile mode extraction parameter. The mzML files were searched against the reference proteome using both Comet and X!Tandem search engines. The identified sequences were then statistically validated using the Trans-Proteomic Pipeline (TPP) including PeptideProphet and iProphet. MAYU was applied to control the FDR at the protein level. Using SpectraST, confidently assigned spectra were converted into a redundant spectral library and retention times are normalized in iRT space using RTCatalog, then a consensus spectrum library was generated. The assay library was extracted from the consensus library using the spectrast2tsv.py script. Libraries were evaluated with the DIA Library Quality Control (DIALib-QC, www.swathatlas.org ) tool and their assessment reports were generated. The performance of the TripleTOF E. coli spectral library was evaluated based on the identification and quantitation of peptides and proteins in data-independent acquisition (DIA) methods with different gradient lengths using the Spectronaut analysis software.

Techniques Used: Generated, Mass Spectrometry, Quantitation Assay, Software

7) Product Images from "Posttranslational Modification of the NADP-Malic Enzyme Involved in C4 Photosynthesis Modulates the Enzymatic Activity during the Day"

Article Title: Posttranslational Modification of the NADP-Malic Enzyme Involved in C4 Photosynthesis Modulates the Enzymatic Activity during the Day

Journal: The Plant Cell

doi: 10.1105/tpc.19.00406

TripleTOF 6600 Tandem MS Data of the Phosphopeptide acVWLVDpSK of ZmC 4 -NADP-ME. The detected b (N-terminal, in red) and y (C-terminal, in blue) fragment ions are labeled in the spectrum. Ac denotes N terminus acetylation and pS denotes phosphorylated Ser. Precursor charge: +2; monoisotopic m/z: 484.7265 D (−1.60 milli-mass unit/−3.30 ppm). Confidence (ProteinPilot): 96.4% (confidence threshold for FDR ≤ 1% = 93.7%).
Figure Legend Snippet: TripleTOF 6600 Tandem MS Data of the Phosphopeptide acVWLVDpSK of ZmC 4 -NADP-ME. The detected b (N-terminal, in red) and y (C-terminal, in blue) fragment ions are labeled in the spectrum. Ac denotes N terminus acetylation and pS denotes phosphorylated Ser. Precursor charge: +2; monoisotopic m/z: 484.7265 D (−1.60 milli-mass unit/−3.30 ppm). Confidence (ProteinPilot): 96.4% (confidence threshold for FDR ≤ 1% = 93.7%).

Techniques Used: Labeling

8) Product Images from "Low collision energy fragmentation in structure-specific glycoproteomics analysis"

Article Title: Low collision energy fragmentation in structure-specific glycoproteomics analysis

Journal: Analytical chemistry

doi: 10.1021/acs.analchem.0c00519

MS/MS spectrum of isobaric core (A) and outer arm (B) fucosylated VVLHPNYSQVDIGLIK glycopeptides of haptoglobin recorded under low collision energy (20eV) on the 6600 tripleTOF mass spectrometer.
Figure Legend Snippet: MS/MS spectrum of isobaric core (A) and outer arm (B) fucosylated VVLHPNYSQVDIGLIK glycopeptides of haptoglobin recorded under low collision energy (20eV) on the 6600 tripleTOF mass spectrometer.

Techniques Used: Tandem Mass Spectroscopy, Mass Spectrometry

9) Product Images from "A Recombinant Protein Biomarker DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins"

Article Title: A Recombinant Protein Biomarker DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins

Journal: bioRxiv

doi: 10.1101/2020.11.11.377309

Experimental workflow. (a) Construction of recombinant protein spectral library . A total of 36 cancer-associated biomarkers were selected from the literature and our own studies ( Table 1 ) and sorted into 4 groups (A - D) based on their molecular weight (M.W.). Each group of 9 proteins was spiked with vitronectin for retention time (RT) alignment. Proteins were reduced, alkylated and digested with trypsin. DDA was used for protein identification using a SCIEX TripleTOF 6600. Datasets were concatenated to generate a recombinant protein spectral library. (b) Construction of human plasma protein spectral library. CRC plasma (80 from stage I-IV CRCs) and 20 healthy plasma samples were pooled and depleted the top 14 high abundance proteins with an Agilent MARS-14 depletion column. The depleted samples were digested with trypsin followed by peptide fractionation using high pH reverse-phased HPLC. A DDA method was employed as in (a) to construct the plasma protein DDA spectral library. (c) SWATH/DIA protein identification using rPSL or merged libraries. The constructed rPSL or merged libraries (rPSL + plasma protein spectral library) were combined with SWATH/DIA MS analysis to determine whether it was possible to detect tryptic peptide spectra of the 36 cancer-associated proteins in non-depleted human plasma samples obtained from CRC patients (n=5). Following sample preparation (reduction, alkylation and tryptic digestion), SWATH/DIA MS analysis was performed for peptide/protein identification. PeakView and Skyline were employed for MS data extraction and peak selection with 1% FDR filtering. Identified proteins were further filtered using high stringency protein identification criteria (HPP guideline v3.0).
Figure Legend Snippet: Experimental workflow. (a) Construction of recombinant protein spectral library . A total of 36 cancer-associated biomarkers were selected from the literature and our own studies ( Table 1 ) and sorted into 4 groups (A - D) based on their molecular weight (M.W.). Each group of 9 proteins was spiked with vitronectin for retention time (RT) alignment. Proteins were reduced, alkylated and digested with trypsin. DDA was used for protein identification using a SCIEX TripleTOF 6600. Datasets were concatenated to generate a recombinant protein spectral library. (b) Construction of human plasma protein spectral library. CRC plasma (80 from stage I-IV CRCs) and 20 healthy plasma samples were pooled and depleted the top 14 high abundance proteins with an Agilent MARS-14 depletion column. The depleted samples were digested with trypsin followed by peptide fractionation using high pH reverse-phased HPLC. A DDA method was employed as in (a) to construct the plasma protein DDA spectral library. (c) SWATH/DIA protein identification using rPSL or merged libraries. The constructed rPSL or merged libraries (rPSL + plasma protein spectral library) were combined with SWATH/DIA MS analysis to determine whether it was possible to detect tryptic peptide spectra of the 36 cancer-associated proteins in non-depleted human plasma samples obtained from CRC patients (n=5). Following sample preparation (reduction, alkylation and tryptic digestion), SWATH/DIA MS analysis was performed for peptide/protein identification. PeakView and Skyline were employed for MS data extraction and peak selection with 1% FDR filtering. Identified proteins were further filtered using high stringency protein identification criteria (HPP guideline v3.0).

Techniques Used: Recombinant, Molecular Weight, Peptide Fractionation, High Performance Liquid Chromatography, Construct, Sample Prep, Selection

10) Product Images from "A Recombinant Protein Biomarker DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins"

Article Title: A Recombinant Protein Biomarker DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins

Journal: bioRxiv

doi: 10.1101/2020.11.11.377309

Experimental workflow.  (a) Construction of recombinant protein spectral library . A total of 36 cancer-associated biomarkers were selected from the literature and our own studies (  Table 1 ) and sorted into 4 groups (A - D) based on their molecular weight (M.W.). Each group of 9 proteins was spiked with vitronectin for retention time (RT) alignment. Proteins were reduced, alkylated and digested with trypsin. DDA was used for protein identification using a SCIEX TripleTOF 6600. Datasets were concatenated to generate a recombinant protein spectral library.  (b) Construction of human plasma protein spectral library.  CRC plasma (80 from stage I-IV CRCs) and 20 healthy plasma samples were pooled and depleted the top 14 high abundance proteins with an Agilent MARS-14 depletion column. The depleted samples were digested with trypsin followed by peptide fractionation using high pH reverse-phased HPLC. A DDA method was employed as in (a) to construct the plasma protein DDA spectral library.  (c) SWATH/DIA protein identification using rPSL or merged libraries.  The constructed rPSL or merged libraries (rPSL + plasma protein spectral library) were combined with SWATH/DIA MS analysis to determine whether it was possible to detect tryptic peptide spectra of the 36 cancer-associated proteins in non-depleted human plasma samples obtained from CRC patients (n=5). Following sample preparation (reduction, alkylation and tryptic digestion), SWATH/DIA MS analysis was performed for peptide/protein identification. PeakView and Skyline were employed for MS data extraction and peak selection with 1% FDR filtering. Identified proteins were further filtered using high stringency protein identification criteria (HPP guideline v3.0).
Figure Legend Snippet: Experimental workflow. (a) Construction of recombinant protein spectral library . A total of 36 cancer-associated biomarkers were selected from the literature and our own studies ( Table 1 ) and sorted into 4 groups (A - D) based on their molecular weight (M.W.). Each group of 9 proteins was spiked with vitronectin for retention time (RT) alignment. Proteins were reduced, alkylated and digested with trypsin. DDA was used for protein identification using a SCIEX TripleTOF 6600. Datasets were concatenated to generate a recombinant protein spectral library. (b) Construction of human plasma protein spectral library. CRC plasma (80 from stage I-IV CRCs) and 20 healthy plasma samples were pooled and depleted the top 14 high abundance proteins with an Agilent MARS-14 depletion column. The depleted samples were digested with trypsin followed by peptide fractionation using high pH reverse-phased HPLC. A DDA method was employed as in (a) to construct the plasma protein DDA spectral library. (c) SWATH/DIA protein identification using rPSL or merged libraries. The constructed rPSL or merged libraries (rPSL + plasma protein spectral library) were combined with SWATH/DIA MS analysis to determine whether it was possible to detect tryptic peptide spectra of the 36 cancer-associated proteins in non-depleted human plasma samples obtained from CRC patients (n=5). Following sample preparation (reduction, alkylation and tryptic digestion), SWATH/DIA MS analysis was performed for peptide/protein identification. PeakView and Skyline were employed for MS data extraction and peak selection with 1% FDR filtering. Identified proteins were further filtered using high stringency protein identification criteria (HPP guideline v3.0).

Techniques Used: Recombinant, Molecular Weight, Peptide Fractionation, High Performance Liquid Chromatography, Construct, Sample Prep, Selection

11) Product Images from "A Recombinant Protein Biomarker DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins"

Article Title: A Recombinant Protein Biomarker DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins

Journal: bioRxiv

doi: 10.1101/2020.11.11.377309

Experimental workflow. (a) Construction of recombinant protein spectral library . A total of 36 cancer-associated biomarkers were selected from the literature and our own studies ( Table 1 ) and sorted into 4 groups (A - D) based on their molecular weight (M.W.). Each group of 9 proteins was spiked with vitronectin for retention time (RT) alignment. Proteins were reduced, alkylated and digested with trypsin. DDA was used for protein identification using a SCIEX TripleTOF 6600. Datasets were concatenated to generate a recombinant protein spectral library. (b) Construction of human plasma protein spectral library. CRC plasma (80 from stage I-IV CRCs) and 20 healthy plasma samples were pooled and depleted the top 14 high abundance proteins with an Agilent MARS-14 depletion column. The depleted samples were digested with trypsin followed by peptide fractionation using high pH reverse-phased HPLC. A DDA method was employed as in (a) to construct the plasma protein DDA spectral library. (c) SWATH/DIA protein identification using rPSL or merged libraries. The constructed rPSL or merged libraries (rPSL + plasma protein spectral library) were combined with SWATH/DIA MS analysis to determine whether it was possible to detect tryptic peptide spectra of the 36 cancer-associated proteins in non-depleted human plasma samples obtained from CRC patients (n=5). Following sample preparation (reduction, alkylation and tryptic digestion), SWATH/DIA MS analysis was performed for peptide/protein identification. PeakView and Skyline were employed for MS data extraction and peak selection with 1% FDR filtering. Identified proteins were further filtered using high stringency protein identification criteria (HPP guideline v3.0).
Figure Legend Snippet: Experimental workflow. (a) Construction of recombinant protein spectral library . A total of 36 cancer-associated biomarkers were selected from the literature and our own studies ( Table 1 ) and sorted into 4 groups (A - D) based on their molecular weight (M.W.). Each group of 9 proteins was spiked with vitronectin for retention time (RT) alignment. Proteins were reduced, alkylated and digested with trypsin. DDA was used for protein identification using a SCIEX TripleTOF 6600. Datasets were concatenated to generate a recombinant protein spectral library. (b) Construction of human plasma protein spectral library. CRC plasma (80 from stage I-IV CRCs) and 20 healthy plasma samples were pooled and depleted the top 14 high abundance proteins with an Agilent MARS-14 depletion column. The depleted samples were digested with trypsin followed by peptide fractionation using high pH reverse-phased HPLC. A DDA method was employed as in (a) to construct the plasma protein DDA spectral library. (c) SWATH/DIA protein identification using rPSL or merged libraries. The constructed rPSL or merged libraries (rPSL + plasma protein spectral library) were combined with SWATH/DIA MS analysis to determine whether it was possible to detect tryptic peptide spectra of the 36 cancer-associated proteins in non-depleted human plasma samples obtained from CRC patients (n=5). Following sample preparation (reduction, alkylation and tryptic digestion), SWATH/DIA MS analysis was performed for peptide/protein identification. PeakView and Skyline were employed for MS data extraction and peak selection with 1% FDR filtering. Identified proteins were further filtered using high stringency protein identification criteria (HPP guideline v3.0).

Techniques Used: Recombinant, Molecular Weight, Peptide Fractionation, High Performance Liquid Chromatography, Construct, Sample Prep, Selection

12) Product Images from "Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics"

Article Title: Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics

Journal: bioRxiv

doi: 10.1101/2020.04.13.038810

Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).
Figure Legend Snippet: Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).

Techniques Used: Liquid Chromatography with Mass Spectroscopy

13) Product Images from "Membrane Profiling by Free Flow Electrophoresis and SWATH-MS to Characterize Subcellular Compartment Proteomes in Mesembryanthemum crystallinum"

Article Title: Membrane Profiling by Free Flow Electrophoresis and SWATH-MS to Characterize Subcellular Compartment Proteomes in Mesembryanthemum crystallinum

Journal: International Journal of Molecular Sciences

doi: 10.3390/ijms22095020

Schematic overview of sample fractionation by Free Flow Electrophoresis (FFE) and downstream analysis by mass spectrometry. ( A ) Microsomal membranes from M. crystallinum leaf tissue were fractionated by FFE into 96 fractions based on their different net surface charge; ( B ) The absorbance of FFE fractions was determined at 280 nm to identify the range of fractions with positive protein values. Fractions 15 to 70 with positive protein values at O.D. 280 were used for subsequent protein identification; ( C ) Proteins were analyzed by SCIEX TripleTOF 6600 in IDA and SWATH-MS modes for reference library generation, protein identification, and quantification; ( D ) The average protein abundance of three biological replicates of each sample was used for the “digital western” FFE profile generation. Here we use the term digital western to refer to the detection of proteins by MS/MS in specific FFE fractions, similar to a traditional Western where proteins in the wells of a gel are detected by antibodies. Different colored columns indicate different subcellular membrane origins based on marker protein profiles.
Figure Legend Snippet: Schematic overview of sample fractionation by Free Flow Electrophoresis (FFE) and downstream analysis by mass spectrometry. ( A ) Microsomal membranes from M. crystallinum leaf tissue were fractionated by FFE into 96 fractions based on their different net surface charge; ( B ) The absorbance of FFE fractions was determined at 280 nm to identify the range of fractions with positive protein values. Fractions 15 to 70 with positive protein values at O.D. 280 were used for subsequent protein identification; ( C ) Proteins were analyzed by SCIEX TripleTOF 6600 in IDA and SWATH-MS modes for reference library generation, protein identification, and quantification; ( D ) The average protein abundance of three biological replicates of each sample was used for the “digital western” FFE profile generation. Here we use the term digital western to refer to the detection of proteins by MS/MS in specific FFE fractions, similar to a traditional Western where proteins in the wells of a gel are detected by antibodies. Different colored columns indicate different subcellular membrane origins based on marker protein profiles.

Techniques Used: Fractionation, Electrophoresis, Mass Spectrometry, Western Blot, Tandem Mass Spectroscopy, Marker

14) Product Images from "A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins"

Article Title: A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins

Journal: Scientific Data

doi: 10.1038/s41597-020-00594-z

The robustness of the SWATH CHO global spectral library in quantification of CHO proteome. ( a ) The correlation between the ∆RT and the predicted retention times in three LC-MS instrumental setups. The red colored “×” represented the 11 iRT reference peptides. ( b ) The violin plot showed the distribution of observed and predicted retention times in three instrumental setups. ( c ) The bar charts showed the numbers of confidently quantified proteins (left) and peptides (right) after 20%, 10% and 5% CV cutoff. ( d ) The CV distribution of all the identified proteins (left) and peptides (right) in three LC-MS instrumental setups. The median CV values in each condition were highlighted. ( e ) Venn diagram analysis of confidently quantified protein ID (at 20% CV cutoff and 1% peptide FDR) between three CHO cell lines. The total protein IDs of respective cell lines were indicated in brackets. ( f ) The violin plot showed the distribution of the protein CV values across three CHO cell lines with the median CV values highlighted in white color. NF6600: nanoflow LC coupled to TripleTOF 6600; CF5600: capillary flow LC coupled to TripleTOF 5600 + ; MF6600: microflow LC coupled to TripleTOF 6600.
Figure Legend Snippet: The robustness of the SWATH CHO global spectral library in quantification of CHO proteome. ( a ) The correlation between the ∆RT and the predicted retention times in three LC-MS instrumental setups. The red colored “×” represented the 11 iRT reference peptides. ( b ) The violin plot showed the distribution of observed and predicted retention times in three instrumental setups. ( c ) The bar charts showed the numbers of confidently quantified proteins (left) and peptides (right) after 20%, 10% and 5% CV cutoff. ( d ) The CV distribution of all the identified proteins (left) and peptides (right) in three LC-MS instrumental setups. The median CV values in each condition were highlighted. ( e ) Venn diagram analysis of confidently quantified protein ID (at 20% CV cutoff and 1% peptide FDR) between three CHO cell lines. The total protein IDs of respective cell lines were indicated in brackets. ( f ) The violin plot showed the distribution of the protein CV values across three CHO cell lines with the median CV values highlighted in white color. NF6600: nanoflow LC coupled to TripleTOF 6600; CF5600: capillary flow LC coupled to TripleTOF 5600 + ; MF6600: microflow LC coupled to TripleTOF 6600.

Techniques Used: Liquid Chromatography with Mass Spectroscopy

Workflow for creating and using the SWATH CHO global spectral library. The CHO-derived samples were processed using in-house multi-dimensional separation protocol. Briefly, the CHO-K1 cells were lysed and fractionated using differential ultracentrifugation to isolate nuclear (NE), mitochondrial (MITO), and heavy-membrane (HM) compartments. The protein lysates from whole cell (WCL) and subcellular-organelle compartments were tryptic digested, subsequently fractionated using basic reverse-phase liquid chromatography separation, and subjected to DDA-MS analysis. Protein digest from harvested cell culture fluid (HCCF) and downstream processing (DSP) mAb samples were directly subject to SWATH-MS in TripleTOF 6600. The raw DDA data was searched locally in ProteinPilot TM  software and the results were uploaded to OneOmics TM  for spectral library construction. The SWATH-MS data sets were processed locally using PeakView® and MarkerView TM  or using OneOmics TM . The applicability and robustness of the CHO global spectral library were evaluated with SWATH-MS data sets of different CHO-derived samples, including WCL of different cell lines, HCCF and DSP mAb samples, and using various LC-MS instrumental setups.
Figure Legend Snippet: Workflow for creating and using the SWATH CHO global spectral library. The CHO-derived samples were processed using in-house multi-dimensional separation protocol. Briefly, the CHO-K1 cells were lysed and fractionated using differential ultracentrifugation to isolate nuclear (NE), mitochondrial (MITO), and heavy-membrane (HM) compartments. The protein lysates from whole cell (WCL) and subcellular-organelle compartments were tryptic digested, subsequently fractionated using basic reverse-phase liquid chromatography separation, and subjected to DDA-MS analysis. Protein digest from harvested cell culture fluid (HCCF) and downstream processing (DSP) mAb samples were directly subject to SWATH-MS in TripleTOF 6600. The raw DDA data was searched locally in ProteinPilot TM software and the results were uploaded to OneOmics TM for spectral library construction. The SWATH-MS data sets were processed locally using PeakView® and MarkerView TM or using OneOmics TM . The applicability and robustness of the CHO global spectral library were evaluated with SWATH-MS data sets of different CHO-derived samples, including WCL of different cell lines, HCCF and DSP mAb samples, and using various LC-MS instrumental setups.

Techniques Used: Derivative Assay, Liquid Chromatography, Cell Culture, Software, Liquid Chromatography with Mass Spectroscopy

15) Product Images from "A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins"

Article Title: A comprehensive CHO SWATH-MS spectral library for robust quantitative profiling of 10,000 proteins

Journal: Scientific Data

doi: 10.1038/s41597-020-00594-z

The robustness of the SWATH CHO global spectral library in quantification of CHO proteome. ( a ) The correlation between the ∆RT and the predicted retention times in three LC-MS instrumental setups. The red colored “×” represented the 11 iRT reference peptides. ( b ) The violin plot showed the distribution of observed and predicted retention times in three instrumental setups. ( c ) The bar charts showed the numbers of confidently quantified proteins (left) and peptides (right) after 20%, 10% and 5% CV cutoff. ( d ) The CV distribution of all the identified proteins (left) and peptides (right) in three LC-MS instrumental setups. The median CV values in each condition were highlighted. ( e ) Venn diagram analysis of confidently quantified protein ID (at 20% CV cutoff and 1% peptide FDR) between three CHO cell lines. The total protein IDs of respective cell lines were indicated in brackets. ( f ) The violin plot showed the distribution of the protein CV values across three CHO cell lines with the median CV values highlighted in white color. NF6600: nanoflow LC coupled to TripleTOF 6600; CF5600: capillary flow LC coupled to TripleTOF 5600 + ; MF6600: microflow LC coupled to TripleTOF 6600.
Figure Legend Snippet: The robustness of the SWATH CHO global spectral library in quantification of CHO proteome. ( a ) The correlation between the ∆RT and the predicted retention times in three LC-MS instrumental setups. The red colored “×” represented the 11 iRT reference peptides. ( b ) The violin plot showed the distribution of observed and predicted retention times in three instrumental setups. ( c ) The bar charts showed the numbers of confidently quantified proteins (left) and peptides (right) after 20%, 10% and 5% CV cutoff. ( d ) The CV distribution of all the identified proteins (left) and peptides (right) in three LC-MS instrumental setups. The median CV values in each condition were highlighted. ( e ) Venn diagram analysis of confidently quantified protein ID (at 20% CV cutoff and 1% peptide FDR) between three CHO cell lines. The total protein IDs of respective cell lines were indicated in brackets. ( f ) The violin plot showed the distribution of the protein CV values across three CHO cell lines with the median CV values highlighted in white color. NF6600: nanoflow LC coupled to TripleTOF 6600; CF5600: capillary flow LC coupled to TripleTOF 5600 + ; MF6600: microflow LC coupled to TripleTOF 6600.

Techniques Used: Liquid Chromatography with Mass Spectroscopy

Workflow for creating and using the SWATH CHO global spectral library. The CHO-derived samples were processed using in-house multi-dimensional separation protocol. Briefly, the CHO-K1 cells were lysed and fractionated using differential ultracentrifugation to isolate nuclear (NE), mitochondrial (MITO), and heavy-membrane (HM) compartments. The protein lysates from whole cell (WCL) and subcellular-organelle compartments were tryptic digested, subsequently fractionated using basic reverse-phase liquid chromatography separation, and subjected to DDA-MS analysis. Protein digest from harvested cell culture fluid (HCCF) and downstream processing (DSP) mAb samples were directly subject to SWATH-MS in TripleTOF 6600. The raw DDA data was searched locally in ProteinPilot TM  software and the results were uploaded to OneOmics TM  for spectral library construction. The SWATH-MS data sets were processed locally using PeakView® and MarkerView TM  or using OneOmics TM . The applicability and robustness of the CHO global spectral library were evaluated with SWATH-MS data sets of different CHO-derived samples, including WCL of different cell lines, HCCF and DSP mAb samples, and using various LC-MS instrumental setups.
Figure Legend Snippet: Workflow for creating and using the SWATH CHO global spectral library. The CHO-derived samples were processed using in-house multi-dimensional separation protocol. Briefly, the CHO-K1 cells were lysed and fractionated using differential ultracentrifugation to isolate nuclear (NE), mitochondrial (MITO), and heavy-membrane (HM) compartments. The protein lysates from whole cell (WCL) and subcellular-organelle compartments were tryptic digested, subsequently fractionated using basic reverse-phase liquid chromatography separation, and subjected to DDA-MS analysis. Protein digest from harvested cell culture fluid (HCCF) and downstream processing (DSP) mAb samples were directly subject to SWATH-MS in TripleTOF 6600. The raw DDA data was searched locally in ProteinPilot TM software and the results were uploaded to OneOmics TM for spectral library construction. The SWATH-MS data sets were processed locally using PeakView® and MarkerView TM or using OneOmics TM . The applicability and robustness of the CHO global spectral library were evaluated with SWATH-MS data sets of different CHO-derived samples, including WCL of different cell lines, HCCF and DSP mAb samples, and using various LC-MS instrumental setups.

Techniques Used: Derivative Assay, Liquid Chromatography, Cell Culture, Software, Liquid Chromatography with Mass Spectroscopy

16) Product Images from "Simultaneous quantification of serum monounsaturated and polyunsaturated phosphatidylcholines as potential biomarkers for diagnosing non-small cell lung cancer"

Article Title: Simultaneous quantification of serum monounsaturated and polyunsaturated phosphatidylcholines as potential biomarkers for diagnosing non-small cell lung cancer

Journal: Scientific Reports

doi: 10.1038/s41598-018-25552-z

PCA score plots of metabolic profiles in early-stage NSCLC patients and HC with or without mean-centred (ctr) scaling. ( A ) UHPLC-Q-TOF/MS analysis in the positive mode, R 2 X = 0.627. ( B ) UHPLC-Q-TOF/MS analysis in the negative mode, R 2 X = 0.529. ( C ) GC-TOF/MS analysis, R 2 X = 0.416. Dots and boxes denote samples from early-stage NSCLC patient and HC, respectively.
Figure Legend Snippet: PCA score plots of metabolic profiles in early-stage NSCLC patients and HC with or without mean-centred (ctr) scaling. ( A ) UHPLC-Q-TOF/MS analysis in the positive mode, R 2 X = 0.627. ( B ) UHPLC-Q-TOF/MS analysis in the negative mode, R 2 X = 0.529. ( C ) GC-TOF/MS analysis, R 2 X = 0.416. Dots and boxes denote samples from early-stage NSCLC patient and HC, respectively.

Techniques Used: Mass Spectrometry

Typical TICs of metabolic profiles of early-stage NSCLC patients ( A ) positive ion mode; ( B ) negative ion mode and HC ( C ) positive ion mode; ( D ) negative ion mode based on UHPLC-Q-TOF/MS analysis.
Figure Legend Snippet: Typical TICs of metabolic profiles of early-stage NSCLC patients ( A ) positive ion mode; ( B ) negative ion mode and HC ( C ) positive ion mode; ( D ) negative ion mode based on UHPLC-Q-TOF/MS analysis.

Techniques Used: Mass Spectrometry

17) Product Images from "Simultaneous quantification of serum monounsaturated and polyunsaturated phosphatidylcholines as potential biomarkers for diagnosing non-small cell lung cancer"

Article Title: Simultaneous quantification of serum monounsaturated and polyunsaturated phosphatidylcholines as potential biomarkers for diagnosing non-small cell lung cancer

Journal: Scientific Reports

doi: 10.1038/s41598-018-25552-z

OPLS-DA score plot of metabolic profiles of early-stage NSCLC patients and HC after unit variance (uv) scaling. ( A ) UHPLC-Q-TOF/MS analysis in the positive mode. ( B ) UHPLC-Q-TOF/MS analysis in the negative mode. ( C ) GC-TOF/MS analysis.
Figure Legend Snippet: OPLS-DA score plot of metabolic profiles of early-stage NSCLC patients and HC after unit variance (uv) scaling. ( A ) UHPLC-Q-TOF/MS analysis in the positive mode. ( B ) UHPLC-Q-TOF/MS analysis in the negative mode. ( C ) GC-TOF/MS analysis.

Techniques Used: Mass Spectrometry

PCA score plots of metabolic profiles in early-stage NSCLC patients and HC with or without mean-centred (ctr) scaling. ( A ) UHPLC-Q-TOF/MS analysis in the positive mode, R 2 X = 0.627. ( B ) UHPLC-Q-TOF/MS analysis in the negative mode, R 2 X = 0.529. ( C ) GC-TOF/MS analysis, R 2 X = 0.416. Dots and boxes denote samples from early-stage NSCLC patient and HC, respectively.
Figure Legend Snippet: PCA score plots of metabolic profiles in early-stage NSCLC patients and HC with or without mean-centred (ctr) scaling. ( A ) UHPLC-Q-TOF/MS analysis in the positive mode, R 2 X = 0.627. ( B ) UHPLC-Q-TOF/MS analysis in the negative mode, R 2 X = 0.529. ( C ) GC-TOF/MS analysis, R 2 X = 0.416. Dots and boxes denote samples from early-stage NSCLC patient and HC, respectively.

Techniques Used: Mass Spectrometry

Typical TICs of metabolic profiles of early-stage NSCLC patients ( A ) positive ion mode; ( B ) negative ion mode and HC ( C ) positive ion mode; ( D ) negative ion mode based on UHPLC-Q-TOF/MS analysis.
Figure Legend Snippet: Typical TICs of metabolic profiles of early-stage NSCLC patients ( A ) positive ion mode; ( B ) negative ion mode and HC ( C ) positive ion mode; ( D ) negative ion mode based on UHPLC-Q-TOF/MS analysis.

Techniques Used: Mass Spectrometry

18) Product Images from "SWATH-MS data of Drosophila melanogaster proteome dynamics during embryogenesis"

Article Title: SWATH-MS data of Drosophila melanogaster proteome dynamics during embryogenesis

Journal: Data in Brief

doi: 10.1016/j.dib.2016.10.009

A) Overall strategy to measure changes in protein expression levels across D. melanogaster embryonic development by SWATH-MS. Embryos were collected at five 4.5 h timepoints to provide a developmental timecourse. Proteins were extracted, digested with trypsin and HRM peptides were spiked into the samples before injection. The samples were analysed using a SWATH acquisition mode on a Sciex Triple-TOF 6600. The resulting files were analysed with MaxQuant and Spectronaut TM . B) The Coefficient of variation (CV) between the biological replicates were calculated for each protein. CVs values were analysed using box plots with Excel. C) Volcano-plot representing the Benjamini–Hochberg corrected p -value as a function of the Log 2 Fold Change for each protein between each timepoint and the 0–4.5 h timepoint.
Figure Legend Snippet: A) Overall strategy to measure changes in protein expression levels across D. melanogaster embryonic development by SWATH-MS. Embryos were collected at five 4.5 h timepoints to provide a developmental timecourse. Proteins were extracted, digested with trypsin and HRM peptides were spiked into the samples before injection. The samples were analysed using a SWATH acquisition mode on a Sciex Triple-TOF 6600. The resulting files were analysed with MaxQuant and Spectronaut TM . B) The Coefficient of variation (CV) between the biological replicates were calculated for each protein. CVs values were analysed using box plots with Excel. C) Volcano-plot representing the Benjamini–Hochberg corrected p -value as a function of the Log 2 Fold Change for each protein between each timepoint and the 0–4.5 h timepoint.

Techniques Used: Expressing, Mass Spectrometry, Injection

19) Product Images from "SWATH-MS dataset of heat-shock treated Drosophila melanogaster embryos"

Article Title: SWATH-MS dataset of heat-shock treated Drosophila melanogaster embryos

Journal: Data in Brief

doi: 10.1016/j.dib.2016.11.028

A) Overall strategy to characterize the dynamics of the D. melanogaster embryonic proteome after heat-shock treatment (HS) using SWATH-MS. Embryos were collected and treated for 0.5, 1 or 3 h at 37 °C or untreated. Proteins were extracted, digested with trypsin and HRM peptides were spiked into the samples before injection. The samples were analysed using SWATH acquisition mode on a Sciex Triple-TOF 6600. The resulting files were analysed with Spectronaut TM . 2529 proteins were quantified using this workflow. B) Reproducibility of the protein intensity measurements between biological replicates. The Log 10 transformed protein intensities were plotted for replicates 1 and 2 of the untreated condition. C) The Coefficient of variation (CVs) between the biological replicates were calculated for each condition.
Figure Legend Snippet: A) Overall strategy to characterize the dynamics of the D. melanogaster embryonic proteome after heat-shock treatment (HS) using SWATH-MS. Embryos were collected and treated for 0.5, 1 or 3 h at 37 °C or untreated. Proteins were extracted, digested with trypsin and HRM peptides were spiked into the samples before injection. The samples were analysed using SWATH acquisition mode on a Sciex Triple-TOF 6600. The resulting files were analysed with Spectronaut TM . 2529 proteins were quantified using this workflow. B) Reproducibility of the protein intensity measurements between biological replicates. The Log 10 transformed protein intensities were plotted for replicates 1 and 2 of the untreated condition. C) The Coefficient of variation (CVs) between the biological replicates were calculated for each condition.

Techniques Used: Mass Spectrometry, Injection, Transformation Assay

20) Product Images from "A multi-center study benchmarks software tools for label-free proteome quantification"

Article Title: A multi-center study benchmarks software tools for label-free proteome quantification

Journal: Nature biotechnology

doi: 10.1038/nbt.3685

Protein level LFQbench benchmark results. After parameter optimization in a first iteration of analyses, intensities reported by each software tool were fitted to PeakView intensity scale using a linear model fixed in the origin ( Supplementary Figure 25 ). Intensities of multiply charged precursors were summed up, and averaged across all technical replicates of each sample. Protein quantities were estimated in each technical replicate by the average of the three most intense peptides reported for each protein. Single hit proteins (a single peptide detected in a protein) were discarded. In the present figure only data derived from TripleTOF 6600 with the 64 swath window setup are displayed. Corresponding data for the other instrument and acquisition setups are shown in Supplementary Figure 8 . (a) Log-transformed ratios (log2(A/B)) of proteins (human proteins in green, yeast proteins in orange, and E.Coli proteins in purple) were plotted for each benchmarked software tool over the log-transformed intensity of sample B for the first and second iteration (sample size n between 3,795 and 4,692 proteins). Dashed colored lines represent the expected log2(A/B) values for human, yeast, and E.Coli proteins. Black dashed lines represent the local trend along the x-axis of experimental log-transformed ratios of each population (human, yeast, and E.Coli). For a better understanding of these plots, see plots generated by simulated data ( Supplementary Figure 2 ). (b) (log2(A/B)) of the averages between technical replicates of A and B for E.coli proteins in the lowest intensity tertile. Boxes represent 25% and 75% percentiles, whiskers cover data points between 1% and 99% percentiles. Accuracy could be significantly improved in the second iteration for OpenSWATH, SWATH 2.0, Skyline, and Spectronaut [p
Figure Legend Snippet: Protein level LFQbench benchmark results. After parameter optimization in a first iteration of analyses, intensities reported by each software tool were fitted to PeakView intensity scale using a linear model fixed in the origin ( Supplementary Figure 25 ). Intensities of multiply charged precursors were summed up, and averaged across all technical replicates of each sample. Protein quantities were estimated in each technical replicate by the average of the three most intense peptides reported for each protein. Single hit proteins (a single peptide detected in a protein) were discarded. In the present figure only data derived from TripleTOF 6600 with the 64 swath window setup are displayed. Corresponding data for the other instrument and acquisition setups are shown in Supplementary Figure 8 . (a) Log-transformed ratios (log2(A/B)) of proteins (human proteins in green, yeast proteins in orange, and E.Coli proteins in purple) were plotted for each benchmarked software tool over the log-transformed intensity of sample B for the first and second iteration (sample size n between 3,795 and 4,692 proteins). Dashed colored lines represent the expected log2(A/B) values for human, yeast, and E.Coli proteins. Black dashed lines represent the local trend along the x-axis of experimental log-transformed ratios of each population (human, yeast, and E.Coli). For a better understanding of these plots, see plots generated by simulated data ( Supplementary Figure 2 ). (b) (log2(A/B)) of the averages between technical replicates of A and B for E.coli proteins in the lowest intensity tertile. Boxes represent 25% and 75% percentiles, whiskers cover data points between 1% and 99% percentiles. Accuracy could be significantly improved in the second iteration for OpenSWATH, SWATH 2.0, Skyline, and Spectronaut [p

Techniques Used: Software, Derivative Assay, Transformation Assay, Generated

21) Product Images from "Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics"

Article Title: Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics

Journal: bioRxiv

doi: 10.1101/2020.04.13.038810

Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).
Figure Legend Snippet: Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).

Techniques Used: Liquid Chromatography with Mass Spectroscopy

22) Product Images from "Posttranslational Modification of the NADP-Malic Enzyme Involved in C4 Photosynthesis Modulates the Enzymatic Activity during the Day"

Article Title: Posttranslational Modification of the NADP-Malic Enzyme Involved in C4 Photosynthesis Modulates the Enzymatic Activity during the Day

Journal: The Plant Cell

doi: 10.1105/tpc.19.00406

TripleTOF 6600 Tandem MS Data of the Phosphopeptide acVWLVDpSK of ZmC 4 -NADP-ME. The detected b (N-terminal, in red) and y (C-terminal, in blue) fragment ions are labeled in the spectrum. Ac denotes N terminus acetylation and pS denotes phosphorylated Ser. Precursor charge: +2; monoisotopic m/z: 484.7265 D (−1.60 milli-mass unit/−3.30 ppm). Confidence (ProteinPilot): 96.4% (confidence threshold for FDR ≤ 1% = 93.7%).
Figure Legend Snippet: TripleTOF 6600 Tandem MS Data of the Phosphopeptide acVWLVDpSK of ZmC 4 -NADP-ME. The detected b (N-terminal, in red) and y (C-terminal, in blue) fragment ions are labeled in the spectrum. Ac denotes N terminus acetylation and pS denotes phosphorylated Ser. Precursor charge: +2; monoisotopic m/z: 484.7265 D (−1.60 milli-mass unit/−3.30 ppm). Confidence (ProteinPilot): 96.4% (confidence threshold for FDR ≤ 1% = 93.7%).

Techniques Used: Labeling

23) Product Images from "Posttranslational Modification of the NADP-Malic Enzyme Involved in C4 Photosynthesis Modulates the Enzymatic Activity during the Day"

Article Title: Posttranslational Modification of the NADP-Malic Enzyme Involved in C4 Photosynthesis Modulates the Enzymatic Activity during the Day

Journal: The Plant Cell

doi: 10.1105/tpc.19.00406

TripleTOF 6600 Tandem MS Data of the Phosphopeptide acVWLVDpSK of ZmC 4 -NADP-ME. The detected b (N-terminal, in red) and y (C-terminal, in blue) fragment ions are labeled in the spectrum. Ac denotes N terminus acetylation and pS denotes phosphorylated Ser. Precursor charge: +2; monoisotopic m/z: 484.7265 D (−1.60 milli-mass unit/−3.30 ppm). Confidence (ProteinPilot): 96.4% (confidence threshold for FDR ≤ 1% = 93.7%).
Figure Legend Snippet: TripleTOF 6600 Tandem MS Data of the Phosphopeptide acVWLVDpSK of ZmC 4 -NADP-ME. The detected b (N-terminal, in red) and y (C-terminal, in blue) fragment ions are labeled in the spectrum. Ac denotes N terminus acetylation and pS denotes phosphorylated Ser. Precursor charge: +2; monoisotopic m/z: 484.7265 D (−1.60 milli-mass unit/−3.30 ppm). Confidence (ProteinPilot): 96.4% (confidence threshold for FDR ≤ 1% = 93.7%).

Techniques Used: Labeling

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    SCIEX sciex tripletof 6600
    Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB <t>Sciex</t> TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).
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    Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).

    Journal: bioRxiv

    Article Title: Zirconium(IV)-IMAC for phosphopeptide enrichment in phosphoproteomics

    doi: 10.1101/2020.04.13.038810

    Figure Lengend Snippet: Phosphopeptide (p-pep) profiling of MagReSyn® microparticles by LC-MS/MS on AB Sciex TripleTOF 6600. (A) Number of p-pep identified for each condition (blue bars) and the selectivity of each enrichment (orange dots). (B) Mono-(blue), di-(orange) and multi-phosphorylated (grey) peptide distribution in each condition. (C) Difference in percentage of identified p-pep between the optimized solvent (S1, S2, S3) and the standard (Std).

    Article Snippet: The enriched phosphopeptide eluates were analysed by LC-MS/MS on a Sciex TripleTOF 6600 and the raw files were processed for peptide identification using Proteome Discoverer and Mascot as the search engine ( , left branch).

    Techniques: Liquid Chromatography with Mass Spectroscopy

    Data acquisition workflow to generate a comprehensive E. coli assay library, quality evaluation with DIALib-QC and DIA/SWATH-MS quantification by Spectronaut. A comprehensive DIA/SWATH assay library for E. coli was generated from whole cell lysate, fractionated samples, overexpressed proteins, and supplemented with synthetic peptides. Samples were analyzed with data-dependent acquisition (DDA) mass spectrometry on TripleTOF 5600+ and TripleTOF 6600 instruments resulting in 209 data files. To generate a DIA/SWATH library, the raw data files were converted to mzML format using the ABSCIEX converter with the profile mode extraction parameter. The mzML files were searched against the reference proteome using both Comet and X!Tandem search engines. The identified sequences were then statistically validated using the Trans-Proteomic Pipeline (TPP) including PeptideProphet and iProphet. MAYU was applied to control the FDR at the protein level. Using SpectraST, confidently assigned spectra were converted into a redundant spectral library and retention times are normalized in iRT space using RTCatalog, then a consensus spectrum library was generated. The assay library was extracted from the consensus library using the spectrast2tsv.py script. Libraries were evaluated with the DIA Library Quality Control (DIALib-QC, www.swathatlas.org ) tool and their assessment reports were generated. The performance of the TripleTOF E. coli spectral library was evaluated based on the identification and quantitation of peptides and proteins in data-independent acquisition (DIA) methods with different gradient lengths using the Spectronaut analysis software.

    Journal: Scientific Data

    Article Title: A comprehensive spectral assay library to quantify the Escherichia coli proteome by DIA/SWATH-MS

    doi: 10.1038/s41597-020-00724-7

    Figure Lengend Snippet: Data acquisition workflow to generate a comprehensive E. coli assay library, quality evaluation with DIALib-QC and DIA/SWATH-MS quantification by Spectronaut. A comprehensive DIA/SWATH assay library for E. coli was generated from whole cell lysate, fractionated samples, overexpressed proteins, and supplemented with synthetic peptides. Samples were analyzed with data-dependent acquisition (DDA) mass spectrometry on TripleTOF 5600+ and TripleTOF 6600 instruments resulting in 209 data files. To generate a DIA/SWATH library, the raw data files were converted to mzML format using the ABSCIEX converter with the profile mode extraction parameter. The mzML files were searched against the reference proteome using both Comet and X!Tandem search engines. The identified sequences were then statistically validated using the Trans-Proteomic Pipeline (TPP) including PeptideProphet and iProphet. MAYU was applied to control the FDR at the protein level. Using SpectraST, confidently assigned spectra were converted into a redundant spectral library and retention times are normalized in iRT space using RTCatalog, then a consensus spectrum library was generated. The assay library was extracted from the consensus library using the spectrast2tsv.py script. Libraries were evaluated with the DIA Library Quality Control (DIALib-QC, www.swathatlas.org ) tool and their assessment reports were generated. The performance of the TripleTOF E. coli spectral library was evaluated based on the identification and quantitation of peptides and proteins in data-independent acquisition (DIA) methods with different gradient lengths using the Spectronaut analysis software.

    Article Snippet: Data dependent acquisition (DDA) mass spectrometry for spectral assay library generation DDA was performed on both a TripleTOF 5600+ (SCIEX) and a TripleTOF 6600 mass spectrometer (SCIEX), both interfaced with a micro-LC interfacePlus HPLC system (Eksigent) configured in either nano-flow or micro-flow mode.

    Techniques: Generated, Mass Spectrometry, Quantitation Assay, Software

    A) Overall strategy to characterize the dynamics of the D. melanogaster embryonic proteome after heat-shock treatment (HS) using SWATH-MS. Embryos were collected and treated for 0.5, 1 or 3 h at 37 °C or untreated. Proteins were extracted, digested with trypsin and HRM peptides were spiked into the samples before injection. The samples were analysed using SWATH acquisition mode on a Sciex Triple-TOF 6600. The resulting files were analysed with Spectronaut TM . 2529 proteins were quantified using this workflow. B) Reproducibility of the protein intensity measurements between biological replicates. The Log 10 transformed protein intensities were plotted for replicates 1 and 2 of the untreated condition. C) The Coefficient of variation (CVs) between the biological replicates were calculated for each condition.

    Journal: Data in Brief

    Article Title: SWATH-MS dataset of heat-shock treated Drosophila melanogaster embryos

    doi: 10.1016/j.dib.2016.11.028

    Figure Lengend Snippet: A) Overall strategy to characterize the dynamics of the D. melanogaster embryonic proteome after heat-shock treatment (HS) using SWATH-MS. Embryos were collected and treated for 0.5, 1 or 3 h at 37 °C or untreated. Proteins were extracted, digested with trypsin and HRM peptides were spiked into the samples before injection. The samples were analysed using SWATH acquisition mode on a Sciex Triple-TOF 6600. The resulting files were analysed with Spectronaut TM . 2529 proteins were quantified using this workflow. B) Reproducibility of the protein intensity measurements between biological replicates. The Log 10 transformed protein intensities were plotted for replicates 1 and 2 of the untreated condition. C) The Coefficient of variation (CVs) between the biological replicates were calculated for each condition.

    Article Snippet: The present dataset contains SWATH files acquired on a Sciex Triple-TOF 6600.

    Techniques: Mass Spectrometry, Injection, Transformation Assay