Extending the Compatibility of the SP3 Paramagnetic Bead Processing Approach for Proteomics

The diversity in protein and peptide biochemistry necessitates robust protocols and reagents for efficiently handling and enriching these molecules prior to analysis with mass spectrometry (MS) or other techniques. Further exploration of the paramagnetic bead-based approach, single-pot solid-phase-enhanced sample preparation (SP3), is carried out toward updating and extending previously described conditions and experimental workflows. The SP3 approach was tested in a wide range of experimental scenarios, including (1) binding solvents (acetonitrile, ethanol, isopropanol, acetone), (2) binding pH (acidic vs neutral), (3) solvent/lysate ratios (50–200%, v/v), (4) mixing and rinsing conditions (on-rack vs off-rack rinsing), (5) Enrichment of nondenatured proteins, and (6) capture of individual proteins from noncomplex mixtures. These results highlight the robust handling of proteins in a broad set of scenarios while also enabling the development of a modified SP3 workflow that offers extended compatibility. The modified SP3 approach is used in quantitative in-depth proteome analyses to compare it with commercial paramagnetic bead-based HILIC methods (MagReSyn) and across multiple binding conditions (e.g., pH and solvent during binding). Together, these data reveal the extensive quantitative coverage of the proteome possible with SP3 independent of the binding approach utilized. The results further establish the utility of SP3 for the unbiased handling of peptides and proteins for proteomic applications

Extending the Compatibility of the SP3 Paramagnetic Bead Processing Approach for Proteomics

The diversity in protein and peptide biochemistry necessitates robust protocols and reagents for efficiently handling and enriching these molecules prior to analysis with mass spectrometry (MS) or other techniques. Further exploration of the paramagnetic bead-based approach, single-pot solid-phase-enhanced sample preparation (SP3), is carried out toward updating and extending previously described conditions and experimental workflows. The SP3 approach was tested in a wide range of experimental scenarios, including (1) binding solvents (acetonitrile, ethanol, isopropanol, acetone), (2) binding pH (acidic vs neutral), (3) solvent/lysate ratios (50–200%, v/v), (4) mixing and rinsing conditions (on-rack vs off-rack rinsing), (5) Enrichment of nondenatured proteins, and (6) capture of individual proteins from noncomplex mixtures. These results highlight the robust handling of proteins in a broad set of scenarios while also enabling the development of a modified SP3 workflow that offers extended compatibility. The modified SP3 approach is used in quantitative in-depth proteome analyses to compare it with commercial paramagnetic bead-based HILIC methods (MagReSyn) and across multiple binding conditions (e.g., pH and solvent during binding). Together, these data reveal the extensive quantitative coverage of the proteome possible with SP3 independent of the binding approach utilized. The results further establish the utility of SP3 for the unbiased handling of peptides and proteins for proteomic applications

Parsing and Quantification of Raw Orbitrap Mass Spectrometer Data Using RawQuant

Effective analysis of protein samples by mass spectrometry (MS) requires careful selection and optimization of a range of experimental parameters. As the output from the primary detection device, the “raw” MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To ease and increase the range of analyses possible, the RawQuant tool was developed to enable parsing of raw MS files derived from Thermo Orbitrap instruments to yield meta and scan data in an openly readable text format. RawQuant can be commanded to export user-friendly files containing MS¹, MS², and MS³ metadata as well as matrices of quantification values based on isobaric tagging approaches. In this study, the utility of RawQuant is demonstrated in several scenarios: (1) reanalysis of shotgun proteomics data for the identification of the human proteome, (2) reanalysis of experiments utilizing isobaric tagging for whole-proteome quantification, and (3) analysis of a novel bacterial proteome and synthetic peptide mixture for assessing quantification accuracy when using isobaric tags. Together, these analyses successfully demonstrate RawQuant for the efficient parsing and quantification of data from raw Thermo Orbitrap MS files acquired in a range of common proteomics experiments. In addition, the individual analyses using RawQuant highlights parametric considerations in the different experimental sets and suggests targetable areas to improve depth of coverage in identification-focused studies and quantification accuracy when using isobaric tags

Parsing and Quantification of Raw Orbitrap Mass Spectrometer Data Using RawQuant

Effective analysis of protein samples by mass spectrometry (MS) requires careful selection and optimization of a range of experimental parameters. As the output from the primary detection device, the “raw” MS data file can be used to gauge the success of a given sample analysis. However, the closed-source nature of the standard raw MS file can complicate effective parsing of the data contained within. To ease and increase the range of analyses possible, the RawQuant tool was developed to enable parsing of raw MS files derived from Thermo Orbitrap instruments to yield meta and scan data in an openly readable text format. RawQuant can be commanded to export user-friendly files containing MS¹, MS², and MS³ metadata as well as matrices of quantification values based on isobaric tagging approaches. In this study, the utility of RawQuant is demonstrated in several scenarios: (1) reanalysis of shotgun proteomics data for the identification of the human proteome, (2) reanalysis of experiments utilizing isobaric tagging for whole-proteome quantification, and (3) analysis of a novel bacterial proteome and synthetic peptide mixture for assessing quantification accuracy when using isobaric tags. Together, these analyses successfully demonstrate RawQuant for the efficient parsing and quantification of data from raw Thermo Orbitrap MS files acquired in a range of common proteomics experiments. In addition, the individual analyses using RawQuant highlights parametric considerations in the different experimental sets and suggests targetable areas to improve depth of coverage in identification-focused studies and quantification accuracy when using isobaric tags