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Schaffer LV, Shortreed MR, Smith LM. Proteoform Analysis and Construction of Proteoform Families in Proteoform Suite. Methods Mol Biol 2022; 2500:67-81. [PMID: 35657588 PMCID: PMC9694099 DOI: 10.1007/978-1-0716-2325-1_7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Proteoform Suite is an interactive software program for the identification and quantification of intact proteoforms from mass spectrometry data. Proteoform Suite identifies proteoforms observed by intact-mass (MS1) analysis. In intact-mass analysis, unfragmented experimental proteoforms are compared to a database of known proteoform sequences and to one another, searching for mass differences corresponding to well-known post-translational modifications or amino acids. Intact-mass analysis enables proteoforms observed in the MS1 data without MS/MS (MS2) fragmentation to be identified. Proteoform Suite further facilitates the construction and visualization of proteoform families, which are the sets of proteoforms derived from individual genes. Bottom-up peptide identifications and top-down (MS2) proteoform identifications can be integrated into the Proteoform Suite analysis to increase the sensitivity and accuracy of the analysis. Proteoform Suite is open source and freely available at https://github.com/smith-chem-wisc/proteoform-suite .
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Affiliation(s)
- Leah V Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | | | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
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2
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Qin Y, Huttlin EL, Winsnes CF, Gosztyla ML, Wacheul L, Kelly MR, Blue SM, Zheng F, Chen M, Schaffer LV, Licon K, Bäckström A, Vaites LP, Lee JJ, Ouyang W, Liu SN, Zhang T, Silva E, Park J, Pitea A, Kreisberg JF, Gygi SP, Ma J, Harper JW, Yeo GW, Lafontaine DLJ, Lundberg E, Ideker T. A multi-scale map of cell structure fusing protein images and interactions. Nature 2021; 600:536-542. [PMID: 34819669 PMCID: PMC9053732 DOI: 10.1038/s41586-021-04115-9] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 10/08/2021] [Indexed: 02/07/2023]
Abstract
The cell is a multi-scale structure with modular organization across at least four orders of magnitude1. Two central approaches for mapping this structure-protein fluorescent imaging and protein biophysical association-each generate extensive datasets, but of distinct qualities and resolutions that are typically treated separately2,3. Here we integrate immunofluorescence images in the Human Protein Atlas4 with affinity purifications in BioPlex5 to create a unified hierarchical map of human cell architecture. Integration is achieved by configuring each approach as a general measure of protein distance, then calibrating the two measures using machine learning. The map, known as the multi-scale integrated cell (MuSIC 1.0), resolves 69 subcellular systems, of which approximately half are to our knowledge undocumented. Accordingly, we perform 134 additional affinity purifications and validate subunit associations for the majority of systems. The map reveals a pre-ribosomal RNA processing assembly and accessory factors, which we show govern rRNA maturation, and functional roles for SRRM1 and FAM120C in chromatin and RPS3A in splicing. By integration across scales, MuSIC increases the resolution of imaging while giving protein interactions a spatial dimension, paving the way to incorporate diverse types of data in proteome-wide cell maps.
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Affiliation(s)
- Yue Qin
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
| | - Edward L Huttlin
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | - Casper F Winsnes
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Maya L Gosztyla
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Ludivine Wacheul
- RNA Molecular Biology, Fonds de la Recherche Scientifique (F.R.S./FNRS), Université Libre de Bruxelles (ULB), Charleroi-Gosselies, Belgium
| | - Marcus R Kelly
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Steven M Blue
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Fan Zheng
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Michael Chen
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Leah V Schaffer
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Katherine Licon
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Anna Bäckström
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | - John J Lee
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Wei Ouyang
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Sophie N Liu
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Tian Zhang
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | - Erica Silva
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Jisoo Park
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Adriana Pitea
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Jason F Kreisberg
- Department of Medicine, University of California San Diego, La Jolla, CA, USA
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | - Jianzhu Ma
- Institute for Artificial Intelligence, Peking University, Beijing, China
| | - J Wade Harper
- Department of Cell Biology, Harvard Medical School, Boston, MA, USA
| | - Gene W Yeo
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
- Stem Cell Program, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Denis L J Lafontaine
- RNA Molecular Biology, Fonds de la Recherche Scientifique (F.R.S./FNRS), Université Libre de Bruxelles (ULB), Charleroi-Gosselies, Belgium
| | - Emma Lundberg
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Stockholm, Sweden.
- Department of Genetics, Stanford University, Stanford, CA, USA.
- Chan Zuckerberg Biohub, San Francisco, San Francisco, CA, USA.
| | - Trey Ideker
- Department of Medicine, University of California San Diego, La Jolla, CA, USA.
- Bioinformatics and Systems Biology Program, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
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3
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Weisbrod CR, Anderson LC, Hendrickson CL, Schaffer LV, Shortreed MR, Smith LM, Shabanowitz J, Hunt DF. Advanced Strategies for Proton-Transfer Reactions Coupled with Parallel Ion Parking on a 21 T FT-ICR MS for Intact Protein Analysis. Anal Chem 2021; 93:9119-9128. [PMID: 34165955 DOI: 10.1021/acs.analchem.1c00847] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Proton-transfer reactions (PTRs) have emerged as a powerful tool for the study of intact proteins. When coupled with m/z-selective kinetic excitation, such as parallel ion parking (PIP), one can exert exquisite control over rates of reaction with a high degree of specificity. This allows one to "concentrate", in the gas phase, nearly all the signals from an intact protein charge state envelope into a single charge state, improving the signal-to-noise ratio (S/N) by 10× or more. While this approach has been previously reported, here we show that implementing these technologies on a 21 T FT-ICR MS provides a tremendous advantage for intact protein analysis. Advanced strategies for performing PTR with PIP were developed to complement this unique instrument, including subjecting all analyte ions entering the mass spectrometer to PTR and PIP. This experiment, which we call "PTR-MS1-PIP", generates a pseudo-MS1 spectrum derived from ions that are exposed to the PTR reagent and PIP waveforms but have not undergone any prior true mass filtering or ion isolation. The result is an extremely rapid and significant improvement in the spectral S/N of intact proteins. This permits the observation of many more proteoforms and reduces ion injection periods for subsequent tandem mass spectrometry characterization. Additionally, the product ion parking waveform has been optimized to enhance the PTR rate without compromise to the parking efficiency. We demonstrate that this process, called "rapid park", can improve reaction rates by 5-10× and explore critical factors discovered to influence this process. Finally, we demonstrate how coupling PTR-MS1 and rapid park provides a 10-fold reduction in ion injection time, improving the rate of tandem MS sequencing.
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Affiliation(s)
- Chad R Weisbrod
- Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, 1800 E. Paul Dirac Dr., Tallahassee, Florida 32310, United States
| | - Lissa C Anderson
- Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, 1800 E. Paul Dirac Dr., Tallahassee, Florida 32310, United States
| | - Christopher L Hendrickson
- Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, 1800 E. Paul Dirac Dr., Tallahassee, Florida 32310, United States
| | - Leah V Schaffer
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Michael R Shortreed
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Jeffrey Shabanowitz
- Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States
| | - Donald F Hunt
- Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States
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4
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Abstract
Biological systems are by nature multiscale, consisting of subsystems that factor into progressively smaller units in a deeply hierarchical structure. At any level of the hierarchy, an ever-increasing diversity of technologies can be applied to characterize the corresponding biological units and their relations, resulting in large networks of physical or functional proximities-e.g., proximities of amino acids within a protein, of proteins within a complex, or of cell types within a tissue. Here, we review general concepts and progress in using network proximity measures as a basis for creation of multiscale hierarchical maps of biological systems. We discuss the functionalization of these maps to create predictive models, including those useful in translation of genotype to phenotype, along with strategies for model visualization and challenges faced by multiscale modeling in the near future. Collectively, these approaches enable a unified hierarchical approach to biological data, with application from the molecular to the macroscopic.
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Affiliation(s)
- Leah V Schaffer
- Division of Genetics, Department of Medicine, University of California San Diego, San Diego, La Jolla, CA 92093, USA
| | - Trey Ideker
- Division of Genetics, Department of Medicine, University of California San Diego, San Diego, La Jolla, CA 92093, USA.
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5
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Shortreed MR, Millikin RJ, Liu L, Rolfs Z, Miller RM, Schaffer LV, Frey BL, Smith LM. Binary Classifier for Computing Posterior Error Probabilities in MetaMorpheus. J Proteome Res 2021; 20:1997-2004. [PMID: 33683901 DOI: 10.1021/acs.jproteome.0c00838] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
MetaMorpheus is a free, open-source software program for the identification of peptides and proteoforms from data-dependent acquisition tandem MS experiments. There is inherent uncertainty in these assignments for several reasons, including the limited overlap between experimental and theoretical peaks, the m/z uncertainty, and noise peaks or peaks from coisolated peptides that produce false matches. False discovery rates provide only a set-wise approximation for incorrect spectrum matches. Here we implemented a binary decision tree calculation within MetaMorpheus to compute a posterior error probability, which provides a measure of uncertainty for each peptide-spectrum match. We demonstrate its utility for increasing identifications and resolving ambiguities in bottom-up, top-down, proteogenomic, and nonspecific digestion searches.
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Affiliation(s)
- Michael R Shortreed
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Robert J Millikin
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Lei Liu
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Zach Rolfs
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Rachel M Miller
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Leah V Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Brian L Frey
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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6
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Schaffer LV, Anderson LC, Butcher DS, Shortreed MR, Miller RM, Pavelec C, Smith LM. Construction of Human Proteoform Families from 21 Tesla Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Top-Down Proteomic Data. J Proteome Res 2020; 20:317-325. [PMID: 33074679 DOI: 10.1021/acs.jproteome.0c00403] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Identification of proteoforms, the different forms of a protein, is important to understand biological processes. A proteoform family is the set of different proteoforms from the same gene. We previously developed the software program Proteoform Suite, which constructs proteoform families and identifies proteoforms by intact-mass analysis. Here, we have applied this approach to top-down proteomic data acquired at the National High Magnetic Field Laboratory 21 tesla Fourier transform ion cyclotron resonance mass spectrometer (data available on the MassIVE platform with identifier MSV000085978). We explored the ability to construct proteoform families and identify proteoforms from the high mass accuracy data that this instrument provides for a complex cell lysate sample from the MCF-7 human breast cancer cell line. There were 2830 observed experimental proteforms, of which 932 were identified, 44 were ambiguous, and 1854 were unidentified. Of the 932 unique identified proteoforms, 766 were identified by top-down MS2 analysis at 1% false discovery rate (FDR) using TDPortal, and 166 were additional intact-mass identifications (∼4.7% calculated global FDR) made using Proteoform Suite. We recently published a proteoform level schema to represent ambiguity in proteoform identifications. We implemented this proteoform level classification in Proteoform Suite for intact-mass identifications, which enables users to determine the ambiguity levels and sources of ambiguity for each intact-mass proteoform identification.
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Affiliation(s)
- Leah V Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Lissa C Anderson
- Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, Tallahassee, Florida 32310, United States
| | - David S Butcher
- Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, Tallahassee, Florida 32310, United States
| | - Michael R Shortreed
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Rachel M Miller
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Caitlin Pavelec
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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7
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Gross EM, Porter LR, Stark NR, Lowry ER, Schaffer LV, Maddipati SS, Hoyt DJ, Stombaugh SE, Peila SR, Henry CS. Micromolded Carbon Paste Microelectrodes for Electrogenerated Chemiluminescent Detection on Microfluidic Devices. ChemElectroChem 2020; 7:3244-3252. [DOI: 10.1002/celc.202000366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Erin M. Gross
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Laura R. Porter
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Nicholas R. Stark
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Emily R. Lowry
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Leah V. Schaffer
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Sai Sujana Maddipati
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Dylan J. Hoyt
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Sarah E. Stombaugh
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Sarah R. Peila
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Charles S. Henry
- Department of ChemistryColorado State University Fort Collins CO 80523 USA
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8
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Gross EM, Porter LR, Stark NR, Lowry ER, Schaffer LV, Maddipati SS, Hoyt DJ, Stombaugh SE, Peila SR, Henry CS. Micromolded Carbon Paste Microelectrodes for Electrogenerated Chemiluminescent Detection on Microfluidic Devices. ChemElectroChem 2020. [DOI: 10.1002/celc.202000847] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Erin M. Gross
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Laura R. Porter
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Nicholas R. Stark
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Emily R. Lowry
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Leah V. Schaffer
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Sai Sujana Maddipati
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Dylan J. Hoyt
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Sarah E. Stombaugh
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Sarah R. Peila
- Department of ChemistryCreighton University 2500 California Plaza Omaha NE 68178 USA
| | - Charles S. Henry
- Department of ChemistryColorado State University Fort Collins CO 80523 USA
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9
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Schaffer LV, Millikin RJ, Shortreed MR, Scalf M, Smith LM. Improving Proteoform Identifications in Complex Systems Through Integration of Bottom-Up and Top-Down Data. J Proteome Res 2020; 19:3510-3517. [PMID: 32584579 DOI: 10.1021/acs.jproteome.0c00332] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Cellular functions are performed by a vast and diverse set of proteoforms. Proteoforms are the specific forms of proteins produced as a result of genetic variations, RNA splicing, and post-translational modifications (PTMs). Top-down mass spectrometric analysis of intact proteins enables proteoform identification, including proteoforms derived from sequence cleavage events or harboring multiple PTMs. In contrast, bottom-up proteomics identifies peptides, which necessitates protein inference and does not yield proteoform identifications. We seek here to exploit the synergies between these two data types to improve the quality and depth of the overall proteomic analysis. To this end, we automated the large-scale integration of results from multiprotease bottom-up and top-down analyses in the software program Proteoform Suite and applied it to the analysis of proteoforms from the human Jurkat T lymphocyte cell line. We implemented the recently developed proteoform-level classification scheme for top-down tandem mass spectrometry (MS/MS) identifications in Proteoform Suite, which enables users to observe the level and type of ambiguity for each proteoform identification, including which of the ambiguous proteoform identifications are supported by bottom-up-level evidence. We used Proteoform Suite to find instances where top-down identifications aid in protein inference from bottom-up analysis and conversely where bottom-up peptide identifications aid in proteoform PTM localization. We also show the use of bottom-up data to infer proteoform candidates potentially present in the sample, allowing confirmation of such proteoform candidates by intact-mass analysis of MS1 spectra. The implementation of these capabilities in the freely available software program Proteoform Suite enables users to integrate large-scale top-down and bottom-up data sets and to utilize the synergies between them to improve and extend the proteomic analysis.
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Affiliation(s)
- Leah V Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Robert J Millikin
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Michael R Shortreed
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Mark Scalf
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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10
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Smith LM, Thomas PM, Shortreed MR, Schaffer LV, Fellers RT, LeDuc RD, Tucholski T, Ge Y, Agar JN, Anderson LC, Chamot-Rooke J, Gault J, Loo JA, Paša-Tolić L, Robinson CV, Schlüter H, Tsybin YO, Vilaseca M, Vizcaíno JA, Danis PO, Kelleher NL. A five-level classification system for proteoform identifications. Nat Methods 2020; 16:939-940. [PMID: 31451767 DOI: 10.1038/s41592-019-0573-x] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA.
| | - Paul M Thomas
- Department of Chemistry and Molecular Biosciences, Northwestern University, Evanston, IL, USA.,National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA
| | | | - Leah V Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Ryan T Fellers
- Department of Chemistry and Molecular Biosciences, Northwestern University, Evanston, IL, USA.,National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA
| | - Richard D LeDuc
- Department of Chemistry and Molecular Biosciences, Northwestern University, Evanston, IL, USA.,National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA
| | - Trisha Tucholski
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA
| | - Ying Ge
- Department of Cell and Regenerative Biology and Human Proteomics Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Jeffrey N Agar
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, MA, USA
| | - Lissa C Anderson
- Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, Tallahassee, FL, USA
| | | | - Joseph Gault
- Department of Chemistry, University of Oxford, Oxford, UK
| | - Joseph A Loo
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA, USA
| | - Ljiljana Paša-Tolić
- Environmental Molecular Sciences Laboratory and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | | | | | | | | | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK
| | - Paul O Danis
- Consortium for Top Down Proteomics, Cambridge, MA, USA
| | - Neil L Kelleher
- Department of Chemistry and Molecular Biosciences, Northwestern University, Evanston, IL, USA. .,National Resource for Translational and Developmental Proteomics, Northwestern University, Evanston, IL, USA.
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11
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Dai Y, Buxton KE, Schaffer LV, Miller RM, Millikin RJ, Scalf M, Frey BL, Shortreed MR, Smith LM. Constructing Human Proteoform Families Using Intact-Mass and Top-Down Proteomics with a Multi-Protease Global Post-Translational Modification Discovery Database. J Proteome Res 2019; 18:3671-3680. [PMID: 31479276 DOI: 10.1021/acs.jproteome.9b00339] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Complex human biomolecular processes are made possible by the diversity of human proteoforms. Constructing proteoform families, groups of proteoforms derived from the same gene, is one way to represent this diversity. Comprehensive, high-confidence identification of human proteoforms remains a central challenge in mass spectrometry-based proteomics. We have previously reported a strategy for proteoform identification using intact-mass measurements, and we have since improved that strategy by mass calibration based on search results, the use of a global post-translational modification discovery database, and the integration of top-down proteomics results with intact-mass analysis. In the present study, we combine these strategies for enhanced proteoform identification in total cell lysate from the Jurkat human T lymphocyte cell line. We collected, processed, and integrated three types of proteomics data (NeuCode-labeled intact-mass, label-free top-down, and multi-protease bottom-up) to maximize the number of confident proteoform identifications. The integrated analysis revealed 5950 unique experimentally observed proteoforms, which were assembled into 848 proteoform families. Twenty percent of the observed proteoforms were confidently identified at a 3.9% false discovery rate, representing 1207 unique proteoforms derived from 484 genes.
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Affiliation(s)
- Yunxiang Dai
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States.,Biophysics Graduate Program , University of Wisconsin , 413 Bock Laboratories, 1525 Linden Drive , Madison , Wisconsin 53706 , United States
| | - Katherine E Buxton
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States
| | - Leah V Schaffer
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States
| | - Rachel M Miller
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States
| | - Robert J Millikin
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States
| | - Mark Scalf
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States
| | - Brian L Frey
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States
| | - Michael R Shortreed
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States
| | - Lloyd M Smith
- Department of Chemistry , University of Wisconsin , 1101 University Avenue , Madison , Wisconsin 53706 , United States
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12
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Schaffer LV, Tucholski T, Shortreed MR, Ge Y, Smith LM. Intact-Mass Analysis Facilitating the Identification of Large Human Heart Proteoforms. Anal Chem 2019; 91:10937-10942. [PMID: 31393705 DOI: 10.1021/acs.analchem.9b02343] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Proteoforms, the primary effectors of biological processes, are the different forms of proteins that arise from molecular processing events such as alternative splicing and post-translational modifications. Heart diseases exhibit changes in proteoform levels, motivating the development of a deeper understanding of the heart proteoform landscape. Our recently developed two-dimensional top-down proteomics platform coupling serial size exclusion chromatography (sSEC) to reversed-phase chromatography (RPC) expanded coverage of the human heart proteome and allowed observation of high-molecular weight proteoforms. However, most of these observed proteoforms were not identified due to the difficulty in obtaining quality tandem mass spectrometry (MS2) fragmentation data for large proteoforms from complex biological mixtures on a chromatographic time scale. Herein, we sought to identify human heart proteoforms in this data set using an enhanced version of Proteoform Suite, which identifies proteoforms by intact mass alone. Specifically, we added a new feature to Proteoform Suite to determine candidate identifications for isotopically unresolved proteoforms larger than 50 kDa, enabling subsequent MS2 identification of important high-molecular weight human heart proteoforms such as lamin A (72 kDa) and trifunctional enzyme subunit α (79 kDa). With this new workflow for large proteoform identification, endogenous human cardiac myosin binding protein C (140 kDa) was identified for the first time. This study demonstrates the integration of our sSEC-RPC-MS proteomics platform with intact-mass analysis through Proteoform Suite to create a catalog of human heart proteoforms and facilitate the identification of large proteoforms in complex systems.
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Affiliation(s)
- Leah V Schaffer
- Department of Chemistry , University of Wisconsin-Madison , Madison , Wisconsin 53706 , United States
| | - Trisha Tucholski
- Department of Chemistry , University of Wisconsin-Madison , Madison , Wisconsin 53706 , United States
| | - Michael R Shortreed
- Department of Chemistry , University of Wisconsin-Madison , Madison , Wisconsin 53706 , United States
| | - Ying Ge
- Department of Chemistry , University of Wisconsin-Madison , Madison , Wisconsin 53706 , United States.,Department of Cell and Regenerative Biology , University of Wisconsin-Madison , Madison , Wisconsin 53705 , United States.,Human Proteomics Program , University of Wisconsin-Madison , Madison , Wisconsin 53705 , United States
| | - Lloyd M Smith
- Department of Chemistry , University of Wisconsin-Madison , Madison , Wisconsin 53706 , United States
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13
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Schaffer LV, Millikin RJ, Miller RM, Anderson LC, Fellers RT, Ge Y, Kelleher NL, LeDuc RD, Liu X, Payne SH, Sun L, Thomas PM, Tucholski T, Wang Z, Wu S, Wu Z, Yu D, Shortreed MR, Smith LM. Identification and Quantification of Proteoforms by Mass Spectrometry. Proteomics 2019; 19:e1800361. [PMID: 31050378 PMCID: PMC6602557 DOI: 10.1002/pmic.201800361] [Citation(s) in RCA: 123] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 04/07/2019] [Indexed: 12/29/2022]
Abstract
A proteoform is a defined form of a protein derived from a given gene with a specific amino acid sequence and localized post-translational modifications. In top-down proteomic analyses, proteoforms are identified and quantified through mass spectrometric analysis of intact proteins. Recent technological developments have enabled comprehensive proteoform analyses in complex samples, and an increasing number of laboratories are adopting top-down proteomic workflows. In this review, some recent advances are outlined and current challenges and future directions for the field are discussed.
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Affiliation(s)
- Leah V. Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Robert J. Millikin
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Rachel M. Miller
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Lissa C. Anderson
- Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, Tallahassee, Florida 32310, United States
| | - Ryan T. Fellers
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208, United States
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
- Department of Cell and Regenerative Biology and Human Proteomics Program, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Neil L. Kelleher
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208, United States
- Department of Chemistry and Molecular Biosciences and the Division of Hematology-Oncology, Northwestern University, Evanston, Illinois 60208, United States
| | - Richard D. LeDuc
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208, United States
| | - Xiaowen Liu
- Department of BioHealth Informatics, Indiana University-Purdue University, Indianapolis, Indiana 46202, United States
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
| | - Samuel H. Payne
- Department of Biology, Brigham Young University, Provo, UT 84602
| | - Liangliang Sun
- Department of Chemistry, Michigan State University, East Lansing, Michigan 48824, United States
| | - Paul M. Thomas
- Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208, United States
| | - Trisha Tucholski
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Zhe Wang
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Si Wu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Zhijie Wu
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Dahang Yu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, Oklahoma 73019, United States
| | - Michael R. Shortreed
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Lloyd M. Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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14
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Zaidan NZ, Walker KJ, Brown JE, Schaffer LV, Scalf M, Shortreed MR, Iyer G, Smith LM, Sridharan R. Compartmentalization of HP1 Proteins in Pluripotency Acquisition and Maintenance. Stem Cell Reports 2019; 10:627-641. [PMID: 29358085 PMCID: PMC5830946 DOI: 10.1016/j.stemcr.2017.12.016] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 12/19/2017] [Accepted: 12/20/2017] [Indexed: 12/31/2022] Open
Abstract
The heterochromatin protein 1 (HP1) family is involved in various functions with maintenance of chromatin structure. During murine somatic cell reprogramming, we find that early depletion of HP1γ reduces the generation of induced pluripotent stem cells, while late depletion enhances the process, with a concomitant change from a centromeric to nucleoplasmic localization and elongation-associated histone H3.3 enrichment. Depletion of heterochromatin anchoring protein SENP7 increased reprogramming efficiency to a similar extent as HP1γ, indicating the importance of HP1γ release from chromatin for pluripotency acquisition. HP1γ interacted with OCT4 and DPPA4 in HP1α and HP1β knockouts and in H3K9 methylation depleted H3K9M embryonic stem cell (ESC) lines. HP1α and HP1γ complexes in ESCs differed in association with histones, the histone chaperone CAF1 complex, and specific components of chromatin-modifying complexes such as DPY30, implying distinct functional contributions. Taken together, our results reveal the complex contribution of the HP1 proteins to pluripotency. Release of HP1γ from anchoring by Senp7 increases reprogramming efficiency HP1γ switches enrichment from histone H1 to histone H3.3 in pluripotent cells HP1γ interacts with OCT4 and DPPA4 independent of HP1α, HP1β, and H3K9 methylation Proteomic characterization of HP1 protein family in pluripotent cells
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Affiliation(s)
- Nur Zafirah Zaidan
- Epigenetics Theme, Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA; Genetics Training Program, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Kolin J Walker
- Epigenetics Theme, Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Jaime E Brown
- Epigenetics Theme, Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Leah V Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Mark Scalf
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Michael R Shortreed
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Gopal Iyer
- Department of Human Oncology, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53715, USA
| | - Rupa Sridharan
- Epigenetics Theme, Wisconsin Institute for Discovery, University of Wisconsin-Madison, Madison, WI 53715, USA; Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI 53715, USA.
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15
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Schaffer LV, Rensvold JW, Shortreed MR, Cesnik AJ, Jochem A, Scalf M, Frey BL, Pagliarini DJ, Smith LM. Identification and Quantification of Murine Mitochondrial Proteoforms Using an Integrated Top-Down and Intact-Mass Strategy. J Proteome Res 2018; 17:3526-3536. [PMID: 30180576 PMCID: PMC6201694 DOI: 10.1021/acs.jproteome.8b00469] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The development of effective strategies for the comprehensive identification and quantification of proteoforms in complex systems is a critical challenge in proteomics. Proteoforms, the specific molecular forms in which proteins are present in biological systems, are the key effectors of biological function. Thus, knowledge of proteoform identities and abundances is essential to unraveling the mechanisms that underlie protein function. We recently reported a strategy that integrates conventional top-down mass spectrometry with intact-mass determinations for enhanced proteoform identifications and the elucidation of proteoform families and applied it to the analysis of yeast cell lysate. In the present work, we extend this strategy to enable quantification of proteoforms, and we examine changes in the abundance of murine mitochondrial proteoforms upon differentiation of mouse myoblasts to myotubes. The integrated top-down and intact-mass strategy provided an increase of ∼37% in the number of identified proteoforms compared to top-down alone, which is in agreement with our previous work in yeast; 1779 unique proteoforms were identified using the integrated strategy compared to 1301 using top-down analysis alone. Quantitative comparison of proteoform differences between the myoblast and myotube cell types showed 129 observed proteoforms exhibiting statistically significant abundance changes (fold change >2 and false discovery rate <5%).
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Affiliation(s)
- Leah V. Schaffer
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | | | - Michael R. Shortreed
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Anthony J. Cesnik
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Adam Jochem
- Morgridge Institute for Research, Madison, WI 53715, USA
| | - Mark Scalf
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Brian L. Frey
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - David J. Pagliarini
- Morgridge Institute for Research, Madison, WI 53715, USA
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Lloyd M. Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI 53706, USA
- Genome Center of Wisconsin, University of Wisconsin-Madison, Madison, WI 53706, USA
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16
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Schaffer LV, Shortreed MR, Cesnik AJ, Frey BL, Solntsev SK, Scalf M, Smith LM. Expanding Proteoform Identifications in Top-Down Proteomic Analyses by Constructing Proteoform Families. Anal Chem 2017; 90:1325-1333. [PMID: 29227670 DOI: 10.1021/acs.analchem.7b04221] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
In top-down proteomics, intact proteins are analyzed by tandem mass spectrometry and proteoforms, which are defined forms of a protein with specific sequences of amino acids and localized post-translational modifications, are identified using precursor mass and fragmentation data. Many proteoforms that are detected in the precursor scan (MS1) are not selected for fragmentation by the instrument and therefore remain unidentified in typical top-down proteomic workflows. Our laboratory has developed the open source software program Proteoform Suite to analyze MS1-only intact proteoform data. Here, we have adapted it to provide identifications of proteoform masses in precursor MS1 spectra of top-down data, supplementing the top-down identifications obtained using the MS2 fragmentation data. Proteoform Suite performs mass calibration using high-scoring top-down identifications and identifies additional proteoforms using calibrated, accurate intact masses. Proteoform families, the set of proteoforms from a given gene, are constructed and visualized from proteoforms identified by both top-down and intact-mass analyses. Using this strategy, we constructed proteoform families and identified 1861 proteoforms in yeast lysate, yielding an approximately 40% increase over the original 1291 proteoform identifications observed using traditional top-down analysis alone.
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Affiliation(s)
- Leah V Schaffer
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Michael R Shortreed
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Anthony J Cesnik
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Brian L Frey
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Stefan K Solntsev
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Mark Scalf
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States.,Genome Center of Wisconsin, University of Wisconsin , 425G Henry Mall, Room 3420, Madison, Wisconsin 53706, United States
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17
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Cesnik AJ, Shortreed MR, Schaffer LV, Knoener RA, Frey BL, Scalf M, Solntsev SK, Dai Y, Gasch AP, Smith LM. Proteoform Suite: Software for Constructing, Quantifying, and Visualizing Proteoform Families. J Proteome Res 2017; 17:568-578. [PMID: 29195273 DOI: 10.1021/acs.jproteome.7b00685] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
We present an open-source, interactive program named Proteoform Suite that uses proteoform mass and intensity measurements from complex biological samples to identify and quantify proteoforms. It constructs families of proteoforms derived from the same gene, assesses proteoform function using gene ontology (GO) analysis, and enables visualization of quantified proteoform families and their changes. It is applied here to reveal systemic proteoform variations in the yeast response to salt stress.
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Affiliation(s)
- Anthony J Cesnik
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Michael R Shortreed
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Leah V Schaffer
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Rachel A Knoener
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Brian L Frey
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Mark Scalf
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Stefan K Solntsev
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Yunxiang Dai
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Audrey P Gasch
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
| | - Lloyd M Smith
- Department of Chemistry, ‡Laboratory of Genetics, and §Genome Center of Wisconsin, University of Wisconsin-Madison , Madison, Wisconsin 53706, United States
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Dai Y, Shortreed MR, Scalf M, Frey BL, Cesnik AJ, Solntsev S, Schaffer LV, Smith LM. Elucidating Escherichia coli Proteoform Families Using Intact-Mass Proteomics and a Global PTM Discovery Database. J Proteome Res 2017; 16:4156-4165. [PMID: 28968100 PMCID: PMC5679780 DOI: 10.1021/acs.jproteome.7b00516] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
A proteoform family is a group of related molecular forms of a protein (proteoforms) derived from the same gene. We have previously described a strategy to identify proteoforms and elucidate proteoform families in complex mixtures of intact proteins. The strategy is based upon measurements of two properties for each proteoform: (i) the accurate proteoform intact-mass, measured by liquid chromatography/mass spectrometry (LC-MS), and (ii) the number of lysine residues in each proteoform, determined using an isotopic labeling approach. These measured properties are then compared with those extracted from a catalog of theoretical proteoforms containing protein sequences and localized post-translational modifications (PTMs) for the organism under study. A match between the measured properties and those in the catalog constitutes an identification of the proteoform. In the present study, this strategy is extended by utilizing a global PTM discovery database and is applied to the widely studied model organism Escherichia coli, providing the most comprehensive elucidation of E. coli proteoforms and proteoform families to date.
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Affiliation(s)
- Yunxiang Dai
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Michael R. Shortreed
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Mark Scalf
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Brian L. Frey
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Anthony J. Cesnik
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Stefan Solntsev
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Leah V. Schaffer
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Lloyd M. Smith
- Department of Chemistry, University of Wisconsin, 1101 University Avenue, Madison, Wisconsin 53706, United States
- Genome Center of Wisconsin, University of Wisconsin, 425G Henry Mall, Room 3420, Madison, Wisconsin 53706, United States
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19
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Abstract
A new global post-translational modification (PTM) discovery strategy, G-PTM-D, is described. A proteomics database containing UniProt-curated PTM information is supplemented with potential new modification types and sites discovered from a first-round search of mass spectrometry data with ultrawide precursor mass tolerance. A second-round search employing the supplemented database conducted with standard narrow mass tolerances yields deep coverage and a rich variety of peptide modifications with high confidence in complex unenriched samples. The G-PTM-D strategy represents a major advance to the previously reported G-PTM strategy and provides a powerful new capability to the proteomics research community.
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Affiliation(s)
- Qiyao Li
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Michael R Shortreed
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | | | - Brian L Frey
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Leah V Schaffer
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Mark Scalf
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin , 1101 University Avenue, Madison, Wisconsin 53706, United States
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Abstract
Ten Holstein cows in mid-lactation which had been fed only stored feeds for several years were paired on milk production. One cow from each pair was assigned to either the control or group treated with supplemental vitamin E for a 12-wk experiment. All cows were fed 3 kg alfalfa-brome hay, corn silage ad libitum, and concentrate at 1 kg/3 kg milk produced daily. This ration provided about 500 mg of vitamin E (total tocopherols) daily. Five cows were fed an additional 300 mg vitamin E daily as D-alpha-tocopherol acetate in their concentrate mix. Feeding the supplemental vitamin E increased the vitamin E content of milk fat 15 to 20% from 18 microgram/g fat to over 21 microgram/g fat. However, this change in vitamin E content of milk was not sufficient to improve the oxidative stability of the milk. Blood characteristics indicative of vitamin E status generally were unaffected by vitamin E supplementation although red cell hemolysis, glutamic oxaloacetic transaminase, and lactate dehydrogenase of serum were lower in blood of supplemented cows.
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