1
|
Habeck T, Brown KA, Des Soye B, Lantz C, Zhou M, Alam N, Hossain MA, Jung W, Keener JE, Volny M, Wilson JW, Ying Y, Agar JN, Danis PO, Ge Y, Kelleher NL, Li H, Loo JA, Marty MT, Paša-Tolić L, Sandoval W, Lermyte F. Top-down mass spectrometry of native proteoforms and their complexes: a community study. Nat Methods 2024:10.1038/s41592-024-02279-6. [PMID: 38744918 DOI: 10.1038/s41592-024-02279-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 04/10/2024] [Indexed: 05/16/2024]
Abstract
The combination of native electrospray ionization with top-down fragmentation in mass spectrometry (MS) allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and cofactors. Although this approach is powerful, both native MS and top-down MS are not yet well standardized, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics initiated a study to develop and test protocols for native MS combined with top-down fragmentation of proteins and protein complexes across 11 instruments in nine laboratories. Here we report the summary of the outcomes to provide robust benchmarks and a valuable entry point for the scientific community.
Collapse
Affiliation(s)
- Tanja Habeck
- Technische Universität Darmstadt, Darmstadt, Germany
| | - Kyle A Brown
- University of Wisconsin-Madison, Madison, WI, USA
| | | | | | - Mowei Zhou
- Pacific Northwest National Laboratory, Richland, WA, USA
- Zhejiang University, Zhejiang, China
| | | | | | | | | | | | - Jesse W Wilson
- Pacific Northwest National Laboratory, Richland, WA, USA
| | - Yujia Ying
- Sun Yat-sen University, Guangzhou, China
| | - Jeffrey N Agar
- Northeastern University, Boston, MA, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Paul O Danis
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Ying Ge
- University of Wisconsin-Madison, Madison, WI, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Neil L Kelleher
- Northwestern University, Evanston, IL, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Huilin Li
- Sun Yat-sen University, Guangzhou, China
| | - Joseph A Loo
- University of California, Los Angeles, CA, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | | | - Ljiljana Paša-Tolić
- Pacific Northwest National Laboratory, Richland, WA, USA
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | | | | |
Collapse
|
2
|
Zemaitis KJ, Fulcher JM, Kumar R, Degnan DJ, Lewis LA, Liao YC, Veličković M, Williams SM, Moore RJ, Bramer LM, Veličković D, Zhu Y, Zhou M, Paša-Tolić L. Spatial top-down proteomics for the functional characterization of human kidney. bioRxiv 2024:2024.02.13.580062. [PMID: 38405958 PMCID: PMC10888776 DOI: 10.1101/2024.02.13.580062] [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] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Background The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging. Results Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions. Conclusions We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.
Collapse
Affiliation(s)
- Kevin J Zemaitis
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - James M Fulcher
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Rashmi Kumar
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - David J Degnan
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Logan A Lewis
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Yen-Chen Liao
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Marija Veličković
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Sarah M Williams
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ronald J Moore
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Lisa M Bramer
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Dušan Veličković
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ying Zhu
- Department of Microchemistry, Proteomics, Lipidomics and Next Generation Sequencing, Genentech, 1 DNA Way, San Francisco, CA 94080, United States
| | - Mowei Zhou
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| | - Ljiljana Paša-Tolić
- Environmental and Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA 99354, United States
| |
Collapse
|
3
|
Jeong K, Kaulich PT, Jung W, Kim J, Tholey A, Kohlbacher O. Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top-down proteomics. Proteomics 2024; 24:e2300068. [PMID: 37997224 DOI: 10.1002/pmic.202300068] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 11/09/2023] [Accepted: 11/13/2023] [Indexed: 11/25/2023]
Abstract
Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate.
Collapse
Affiliation(s)
- Kyowon Jeong
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
| | - Philipp T Kaulich
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Wonhyeuk Jung
- Department of Cell Biology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Jihyung Kim
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
| | - Andreas Tholey
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, Kiel, Germany
| | - Oliver Kohlbacher
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen, Germany
- Institute for Bioinformatics and Medical Informatics, University of Tübingen, Tübingen, Germany
- Translational Bioinformatics, University Hospital Tübingen, Tübingen, Germany
| |
Collapse
|
4
|
Kalailingam P, Mohd‐Kahliab K, Ngan SC, Iyappan R, Melekh E, Lu T, Zien GW, Sharma B, Guo T, MacNeil AJ, MacPherson REK, Tsiani EL, O'Leary DD, Lim KL, Su IH, Gao Y, Richards AM, Kalaria RN, Chen CP, McCarthy NE, Sze SK. Immunotherapy targeting isoDGR-protein damage extends lifespan in a mouse model of protein deamidation. EMBO Mol Med 2023; 15:e18526. [PMID: 37971164 PMCID: PMC10701600 DOI: 10.15252/emmm.202318526] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [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: 08/17/2023] [Revised: 10/21/2023] [Accepted: 10/31/2023] [Indexed: 11/19/2023] Open
Abstract
Aging results from the accumulation of molecular damage that impairs normal biochemical processes. We previously reported that age-linked damage to amino acid sequence NGR (Asn-Gly-Arg) results in "gain-of-function" conformational switching to isoDGR (isoAsp-Gly-Arg). This integrin-binding motif activates leukocytes and promotes chronic inflammation, which are characteristic features of age-linked cardiovascular disorders. We now report that anti-isoDGR immunotherapy mitigates lifespan reduction of Pcmt1-/- mouse. We observed extensive accumulation of isoDGR and inflammatory cytokine expression in multiple tissues from Pcmt1-/- and naturally aged WT animals, which could also be induced via injection of isoDGR-modified plasma proteins or synthetic peptides into young WT animals. However, weekly injection of anti-isoDGR mAb (1 mg/kg) was sufficient to significantly reduce isoDGR-protein levels in body tissues, decreased pro-inflammatory cytokine concentrations in blood plasma, improved cognition/coordination metrics, and extended the average lifespan of Pcmt1-/- mice. Mechanistically, isoDGR-mAb mediated immune clearance of damaged isoDGR-proteins via antibody-dependent cellular phagocytosis (ADCP). These results indicate that immunotherapy targeting age-linked protein damage may represent an effective intervention strategy in a range of human degenerative disorders.
Collapse
Affiliation(s)
| | | | - SoFong Cam Ngan
- Department of Health Sciences, Faculty of Applied Health SciencesBrock UniversitySt. CatharinesONCanada
| | - Ranjith Iyappan
- Department of Health Sciences, Faculty of Applied Health SciencesBrock UniversitySt. CatharinesONCanada
| | - Evelin Melekh
- Department of Health Sciences, Faculty of Applied Health SciencesBrock UniversitySt. CatharinesONCanada
| | - Tian Lu
- iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life SciencesWestlake UniversityHangzhouChina
| | - Gan Wei Zien
- School of Biological SciencesNanyang Technological UniversitySingaporeSingapore
| | - Bhargy Sharma
- School of Biological SciencesNanyang Technological UniversitySingaporeSingapore
| | - Tiannan Guo
- iMarker Lab, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School of Life SciencesWestlake UniversityHangzhouChina
| | - Adam J MacNeil
- Department of Health Sciences, Faculty of Applied Health SciencesBrock UniversitySt. CatharinesONCanada
| | - Rebecca EK MacPherson
- Department of Health Sciences, Faculty of Applied Health SciencesBrock UniversitySt. CatharinesONCanada
| | - Evangelia Litsa Tsiani
- Department of Health Sciences, Faculty of Applied Health SciencesBrock UniversitySt. CatharinesONCanada
| | - Deborah D O'Leary
- Department of Health Sciences, Faculty of Applied Health SciencesBrock UniversitySt. CatharinesONCanada
| | - Kah Leong Lim
- Lee Kong Chian School of MedicineNanyang Technological UniversitySingaporeSingapore
| | - I Hsin Su
- School of Biological SciencesNanyang Technological UniversitySingaporeSingapore
| | - Yong‐Gui Gao
- School of Biological SciencesNanyang Technological UniversitySingaporeSingapore
| | - A Mark Richards
- Department of CardiologyNational University Heart CentreSingaporeSingapore
- Department of CardiologyUniversity of OtagoChristchurchNew Zealand
| | - Raj N Kalaria
- Institute of Neuroscience, Campus for Ageing and VitalityNewcastle UniversityNewcastle upon TyneUK
| | - Christopher P Chen
- Memory, Aging and Cognition CentreNational University Health SystemSingaporeSingapore
| | - Neil E McCarthy
- Centre for Immunobiology, The Blizard Institute, Bart's and The London School of Medicine and DentistryQueen Mary University of LondonLondonUK
| | - Siu Kwan Sze
- School of Biological SciencesNanyang Technological UniversitySingaporeSingapore
- Department of Health Sciences, Faculty of Applied Health SciencesBrock UniversitySt. CatharinesONCanada
| |
Collapse
|
5
|
Po A, Eyers CE. Top-Down Proteomics and the Challenges of True Proteoform Characterization. J Proteome Res 2023; 22:3663-3675. [PMID: 37937372 PMCID: PMC10696603 DOI: 10.1021/acs.jproteome.3c00416] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Revised: 10/09/2023] [Accepted: 10/20/2023] [Indexed: 11/09/2023]
Abstract
Top-down proteomics (TDP) aims to identify and profile intact protein forms (proteoforms) extracted from biological samples. True proteoform characterization requires that both the base protein sequence be defined and any mass shifts identified, ideally localizing their positions within the protein sequence. Being able to fully elucidate proteoform profiles lends insight into characterizing proteoform-unique roles, and is a crucial aspect of defining protein structure-function relationships and the specific roles of different (combinations of) protein modifications. However, defining and pinpointing protein post-translational modifications (PTMs) on intact proteins remains a challenge. Characterization of (heavily) modified proteins (>∼30 kDa) remains problematic, especially when they exist in a population of similarly modified, or kindred, proteoforms. This issue is compounded as the number of modifications increases, and thus the number of theoretical combinations. Here, we present our perspective on the challenges of analyzing kindred proteoform populations, focusing on annotation of protein modifications on an "average" protein. Furthermore, we discuss the technical requirements to obtain high quality fragmentation spectral data to robustly define site-specific PTMs, and the fact that this is tempered by the time requirements necessary to separate proteoforms in advance of mass spectrometry analysis.
Collapse
Affiliation(s)
- Allen Po
- Centre
for Proteome Research, Faculty of Health & Life Sciences, University of Liverpool, Liverpool L69 7ZB, U.K.
- Department
of Biochemistry, Cell & Systems Biology, Institute of Systems,
Molecular & Integrative Biology, Faculty of Health & Life
Sciences, University of Liverpool, Liverpool L69 7ZB, U.K.
| | - Claire E. Eyers
- Centre
for Proteome Research, Faculty of Health & Life Sciences, University of Liverpool, Liverpool L69 7ZB, U.K.
- Department
of Biochemistry, Cell & Systems Biology, Institute of Systems,
Molecular & Integrative Biology, Faculty of Health & Life
Sciences, University of Liverpool, Liverpool L69 7ZB, U.K.
| |
Collapse
|
6
|
McGee JP, Su P, Durbin KR, Hollas MAR, Bateman NW, Maxwell GL, Conrads TP, Fellers RT, Melani RD, Camarillo JM, Kafader JO, Kelleher NL. Automated imaging and identification of proteoforms directly from ovarian cancer tissue. Nat Commun 2023; 14:6478. [PMID: 37838706 PMCID: PMC10576781 DOI: 10.1038/s41467-023-42208-3] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 09/28/2023] [Indexed: 10/16/2023] Open
Abstract
The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS2) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer.
Collapse
Affiliation(s)
- John P McGee
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Pei Su
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | | | | | - Nicholas W Bateman
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc, Bethesda, MD, USA
- Department of Gynecologic Surgery and Obstetrics and the Gynecologic Cancer Center of Excellence, John P. Murtha Cancer Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - G Larry Maxwell
- Department of Gynecologic Surgery and Obstetrics and the Gynecologic Cancer Center of Excellence, John P. Murtha Cancer Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Women's Health Integrated Research Center, Inova Women's Service Line, Inova Health System, Falls Church, VA, USA
| | - Thomas P Conrads
- Department of Gynecologic Surgery and Obstetrics and the Gynecologic Cancer Center of Excellence, John P. Murtha Cancer Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- Women's Health Integrated Research Center, Inova Women's Service Line, Inova Health System, Falls Church, VA, USA
| | | | - Rafael D Melani
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Jeannie M Camarillo
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Jared O Kafader
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Neil L Kelleher
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA.
- Proteomics Center of Excellence, Evanston, IL, USA.
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| |
Collapse
|
7
|
Chen W, Ding Z, Zang Y, Liu X. Characterization of Proteoform Post-Translational Modifications by Top-Down and Bottom-Up Mass Spectrometry in Conjunction with Annotations. J Proteome Res 2023; 22:3178-3189. [PMID: 37728997 PMCID: PMC10563160 DOI: 10.1021/acs.jproteome.3c00207] [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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2023] [Indexed: 09/22/2023]
Abstract
Many proteoforms can be produced from a gene due to genetic mutations, alternative splicing, post-translational modifications (PTMs), and other variations. PTMs in proteoforms play critical roles in cell signaling, protein degradation, and other biological processes. Mass spectrometry (MS) is the primary technique for investigating PTMs in proteoforms, and two alternative MS approaches, top-down and bottom-up, have complementary strengths. The combination of the two approaches has the potential to increase the sensitivity and accuracy in PTM identification and characterization. In addition, protein and PTM knowledge bases, such as UniProt, provide valuable information for PTM characterization and verification. Here, we present a software pipeline PTM-TBA (PTM characterization by Top-down and Bottom-up MS and Annotations) for identifying and localizing PTMs in proteoforms by integrating top-down and bottom-up MS as well as PTM annotations. We assessed PTM-TBA using a technical triplicate of bottom-up and top-down MS data of SW480 cells. On average, database search of the top-down MS data identified 2000 mass shifts, 814.5 (40.7%) of which were matched to 11 common PTMs and 423 of which were localized. Of the mass shifts identified by top-down MS, PTM-TBA verified 435 mass shifts using the bottom-up MS data and UniProt annotations.
Collapse
Affiliation(s)
- Wenrong Chen
- Department
of BioHealth Informatics, Indiana University-Purdue
University Indianapolis, Indianapolis, Indiana 46202, United States
| | - Zhengming Ding
- Department
of Computer Science, Tulane School of Science and Engineering, Tulane University, New Orleans, Louisiana 70118, United States
| | - Yong Zang
- Department
of Biostatics and Health Data Sciences, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
- Center
for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, Indiana 46202, United States
| | - Xiaowen Liu
- Tulane
Center for Biomedical Informatics and Genomics, Tulane University, New Orleans, Louisiana 70112, United States
- Deming Department
of Medicine, Tulane University, New Orleans, Louisiana 70112, United States
| |
Collapse
|
8
|
Yates J, Gomes F, Durbin K, Schauer K, Nwachukwu J, Russo R, Njeri J, Saviola A, McClatchy D, Diedrich J, Garrett P, Papa A, Ciolacu I, Kelleher N, Nettles K. Native top-down proteomics reveals EGFR-ERα signaling crosstalk in breast cancer cells dissociates NUTF2 dimers to modulate ERα signaling and cell growth. Res Sq 2023:rs.3.rs-3097806. [PMID: 37546719 PMCID: PMC10402242 DOI: 10.21203/rs.3.rs-3097806/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Oligomerization of proteins and their modified forms (proteoforms) produces functional protein complexes 1,2. Complexoforms are complexes that consist of the same set of proteins with different proteoforms 3. The ability to characterize these assemblies within cells is critical to understanding the molecular mechanisms involved in disease and to designing effective drugs. An outstanding biological question is how proteoforms drive function and oligomerization of complexoforms. However, tools to define endogenous proteoform-proteoform/ligand interactions are scarce 4. Here, we present a native top-down proteomics (nTDP) strategy that combines size-exclusion chromatography, nano liquid-chromatography in direct infusion mode, field asymmetric ion mobility spectrometry, and multistage mass spectrometry to identify protein assemblies (≤70 kDa) in breast cancer cells and in cells that overexpress EGFR, a resistance model of estrogen receptor-α (ER-α) targeted therapies. By identifying ~104 complexoforms from 17 protein complexes, our nTDP approach revealed several molecular features of the breast cancer proteome, including EGFR-induced dissociation of nuclear transport factor 2 (NUTF2) assemblies that modulate ER activity. Our findings show that the K4 and K55 posttranslational modification sites discovered with nTDP differentially impact the effects of NUTF2 on the inhibition of the ER signaling pathway. By characterizing endogenous proteoform-proteoform/ligand interactions, we reveal the molecular diversity of complexoforms, which allows us to propose a model for ER drug discovery in the context of designing effective inhibitors to selectively bind and disrupt the actions of targeted ER complexoforms.
Collapse
|
9
|
Tabb DL, Jeong K, Druart K, Gant MS, Brown KA, Nicora C, Zhou M, Couvillion S, Nakayasu E, Williams JE, Peterson HK, McGuire MK, McGuire MA, Metz TO, Chamot-Rooke J. Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection. J Proteome Res 2023. [PMID: 37235544 DOI: 10.1021/acs.jproteome.2c00673] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [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: 05/28/2023]
Abstract
Generating top-down tandem mass spectra (MS/MS) from complex mixtures of proteoforms benefits from improvements in fractionation, separation, fragmentation, and mass analysis. The algorithms to match MS/MS to sequences have undergone a parallel evolution, with both spectral alignment and match-counting approaches producing high-quality proteoform-spectrum matches (PrSMs). This study assesses state-of-the-art algorithms for top-down identification (ProSight PD, TopPIC, MSPathFinderT, and pTop) in their yield of PrSMs while controlling false discovery rate. We evaluated deconvolution engines (ThermoFisher Xtract, Bruker AutoMSn, Matrix Science Mascot Distiller, TopFD, and FLASHDeconv) in both ThermoFisher Orbitrap-class and Bruker maXis Q-TOF data (PXD033208) to produce consistent precursor charges and mass determinations. Finally, we sought post-translational modifications (PTMs) in proteoforms from bovine milk (PXD031744) and human ovarian tissue. Contemporary identification workflows produce excellent PrSM yields, although approximately half of all identified proteoforms from these four pipelines were specific to only one workflow. Deconvolution algorithms disagree on precursor masses and charges, contributing to identification variability. Detection of PTMs is inconsistent among algorithms. In bovine milk, 18% of PrSMs produced by pTop and TopMG were singly phosphorylated, but this percentage fell to 1% for one algorithm. Applying multiple search engines produces more comprehensive assessments of experiments. Top-down algorithms would benefit from greater interoperability.
Collapse
Affiliation(s)
- David L Tabb
- Université Paris Cité, Institut Pasteur, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France
| | - Kyowon Jeong
- Applied Bioinformatics, Computer Science Department, University of Tübingen, Tübingen 72076, Germany
| | - Karen Druart
- Université Paris Cité, Institut Pasteur, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France
| | - Megan S Gant
- Université Paris Cité, Institut Pasteur, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France
| | - Kyle A Brown
- School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin 53705, United States
| | - Carrie Nicora
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Mowei Zhou
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | - Sneha Couvillion
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ernesto Nakayasu
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Janet E Williams
- Department of Animal, Veterinary, and Food Sciences, University of Idaho, Moscow, Idaho 83844, United States
| | - Haley K Peterson
- Department of Animal, Veterinary, and Food Sciences, University of Idaho, Moscow, Idaho 83844, United States
| | - Michelle K McGuire
- Margaret Ritchie School of Family and Consumer Sciences, University of Idaho, Moscow, Idaho 83844, United States
| | - Mark A McGuire
- Department of Animal, Veterinary, and Food Sciences, University of Idaho, Moscow, Idaho 83844, United States
| | - Thomas O Metz
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Julia Chamot-Rooke
- Université Paris Cité, Institut Pasteur, CNRS UAR 2024, Mass Spectrometry for Biology Unit, Paris 75015, France
| |
Collapse
|
10
|
Campbell TL, Drown BS. Proteoforms feel the heat. Nat Chem Biol 2023:10.1038/s41589-023-01285-7. [PMID: 36941475 DOI: 10.1038/s41589-023-01285-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/23/2023]
Affiliation(s)
| | - Bryon S Drown
- Department of Chemistry Purdue University, West Lafayette, IN, USA.
| |
Collapse
|
11
|
Martin EA, Fulcher JM, Zhou M, Monroe ME, Petyuk VA. TopPICR: A Companion R Package for Top-Down Proteomics Data Analysis. J Proteome Res 2023; 22:399-409. [PMID: 36631391 DOI: 10.1021/acs.jproteome.2c00570] [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: 01/13/2023]
Abstract
Top-down proteomics is the analysis of proteins in their intact form without proteolysis, thus preserving valuable information about post-translational modifications, isoforms, and proteolytic processing. However, it is still a developing field due to limitations in the instrumentation, difficulties with the interpretation of complex mass spectra, and a lack of well-established quantification approaches. TopPIC is one of the popular tools for proteoform identification. We extended its capabilities into label-free proteoform quantification by developing a companion R package (TopPICR). Key steps in the TopPICR pipeline include filtering identifications, inferring a minimal set of protein accessions explaining the observed sequences, aligning retention times, recalibrating measured masses, clustering features across data sets, and finally compiling feature intensities using the match-between-runs approach. The output of the pipeline is an MSnSet object which makes downstream data analysis seamlessly compatible with packages from the Bioconductor project. It also provides the capability for visualizing proteoforms within the context of the parent protein sequence. The functionality of TopPICR is demonstrated on top-down LC-MS/MS data sets of 10 human-in-mouse xenografts of luminal and basal breast tumor samples.
Collapse
Affiliation(s)
- Evan A Martin
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States
| | - James M Fulcher
- Environmental and Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington99352, United States
| | - Mowei Zhou
- Environmental and Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington99352, United States
| | - Matthew E Monroe
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States
| | - Vladislav A Petyuk
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington99352, United States
| |
Collapse
|
12
|
Liao YC, Fulcher JM, Degnan DJ, Williams SM, Bramer LM, Veličković D, Zemaitis KJ, Veličković M, Sontag RL, Moore RJ, Paša-Tolić L, Zhu Y, Zhou M. Spatially Resolved Top-Down Proteomics of Tissue Sections Based on a Microfluidic Nanodroplet Sample Preparation Platform. Mol Cell Proteomics 2023; 22:100491. [PMID: 36603806 DOI: 10.1016/j.mcpro.2022.100491] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2022] [Revised: 12/10/2022] [Accepted: 12/20/2022] [Indexed: 01/04/2023] Open
Abstract
Conventional proteomic approaches measure the averaged signal from mixed cell populations or bulk tissues, leading to the dilution of signals arising from subpopulations of cells that might serve as important biomarkers. Recent developments in bottom-up proteomics have enabled spatial mapping of cellular heterogeneity in tissue microenvironments. However, bottom-up proteomics cannot unambiguously define and quantify proteoforms, which are intact (i.e., functional) forms of proteins capturing genetic variations, alternatively spliced transcripts and posttranslational modifications. Herein, we described a spatially resolved top-down proteomics (TDP) platform for proteoform identification and quantitation directly from tissue sections. The spatial TDP platform consisted of a nanodroplet processing in one pot for trace samples-based sample preparation system and an laser capture microdissection-based cell isolation system. We improved the nanodroplet processing in one pot for trace samples sample preparation by adding benzonase in the extraction buffer to enhance the coverage of nucleus proteins. Using ∼200 cultured cells as test samples, this approach increased total proteoform identifications from 493 to 700; with newly identified proteoforms primarily corresponding to nuclear proteins. To demonstrate the spatial TDP platform in tissue samples, we analyzed laser capture microdissection-isolated tissue voxels from rat brain cortex and hypothalamus regions. We quantified 509 proteoforms within the union of top-down mass spectrometry-based proteoform identification and characterization and TDPortal identifications to match with features from protein mass extractor. Several proteoforms corresponding to the same gene exhibited mixed abundance profiles between two tissue regions, suggesting potential posttranslational modification-specific spatial distributions. The spatial TDP workflow has prospects for biomarker discovery at proteoform level from small tissue sections.
Collapse
|
13
|
Abstract
Proteins are the key biological actors within cells, driving many biological processes integral to both healthy and diseased states. Understanding the depth of complexity represented within the proteome is crucial to our scientific understanding of cellular biology and to provide disease specific insights for clinical applications. Mass spectrometry-based proteomics is the premier method for proteome analysis, with the ability to both identify and quantify proteins. Although proteomics continues to grow as a robust field of bioanalytical chemistry, advances are still necessary to enable a more comprehensive view of the proteome. In this review, we provide a broad overview of mass spectrometry-based proteomics in general, and highlight four developing areas of bottom-up proteomics: (1) protein inference, (2) alternative proteases, (3) sample-specific databases and (4) post-translational modification discovery.
Collapse
Affiliation(s)
- Rachel M Miller
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA.
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, USA.
| |
Collapse
|
14
|
Abstract
Microproteins and short open reading frame-encoded peptides (SEPs) can, like all proteins, carry numerous posttranslational modifications. Together with posttranscriptional processes, this leads to a high number of possible distinct protein molecules, the proteoforms, out of a limited number of genes. The identification, quantification, and molecular characterization of proteoforms possess special challenges to established, mainly bottom-up proteomics (BUP) based analytical approaches. While BUP methods are powerful, proteins have to be inferred rather than directly identified, which hampers the detection of proteoforms. An alternative approach is top-down proteomics (TDP) which allows to identify intact proteoforms. This perspective article provides a brief overview of modified microproteins and SEPs, introduces the proteoform terminology, and compares present BUP and TDP workflows highlighting their major advantages and caveats. Necessary future developments in TDP to fully accentuate its potential for proteoform-centric analytics of microproteins and SEPs will be discussed.
Collapse
Affiliation(s)
- Liam Cassidy
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Philipp T. Kaulich
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Andreas Tholey
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany,Corresponding author
| |
Collapse
|
15
|
Habeck T, Lermyte F. Seeing the complete picture: proteins in top-down mass spectrometry. Essays Biochem 2022. [PMID: 36468679 DOI: 10.1042/ebc20220098] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2022] [Revised: 11/11/2022] [Accepted: 11/14/2022] [Indexed: 12/12/2022]
Abstract
Abstract
Top-down protein mass spectrometry can provide unique insights into protein sequence and structure, including precise proteoform identification and study of protein–ligand and protein–protein interactions. In contrast with the commonly applied bottom-up approach, top-down approaches do not include digestion of the protein of interest into small peptides, but instead rely on the ionization and subsequent fragmentation of intact proteins. As such, it is fundamentally the only way to fully characterize the composition of a proteoform. Here, we provide an overview of how a top-down protein mass spectrometry experiment is performed and point out recent applications from the literature to the reader. While some parts of the top-down workflow are broadly applicable, different research questions are best addressed with specific experimental designs. The most important divide is between studies that prioritize sequence information (i.e., proteoform identification) versus structural information (e.g., conformational studies, or mapping protein–protein or protein–ligand interactions). Another important consideration is whether to work under native or denaturing solution conditions, and the overall complexity of the sample also needs to be taken into account, as it determines whether (chromatographic) separation is required prior to MS analysis. In this review, we aim to provide enough information to support both newcomers and more experienced readers in the decision process of how to answer a potential research question most efficiently and to provide an overview of the methods that exist to answer these questions.
Collapse
|
16
|
Babović M, Shliaha PV, Gibb S, Jensen ON. Effective Amino Acid Sequencing of Intact Filgrastim by Multimodal Mass Spectrometry with Topdownr. J Am Soc Mass Spectrom 2022; 33:2087-2093. [PMID: 36263452 DOI: 10.1021/jasms.2c00193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Therapeutic proteins, known as biologicals, are an important and growing class of drugs for treatment of a series of human ailments. Amino acid sequence variants of therapeutic proteins can affect their safety and efficacy. Top-down mass spectrometry is well suited for the sequence analysis of intact therapeutic proteins. Fine-tuning of tandem mass spectrometry (MS/MS) fragmentation conditions is essential for maximizing the amino acid sequence coverage but is often time-consuming. We used topdownr, an automated and integrated multimodal approach to systematically assess high mass accuracy MS/MS fragmentation parameters to characterize filgrastim, a 19 kDa recombinant human granulocyte colony-stimulating factor used in treating neutropenia. A total of 276 different MS/MS conditions were systematically tested, including the following parameters: protein charge state, HCD and CID collision energy, ETD reaction time, ETD supplemental activation, and UVPD activation time. Stringent and accurate evaluation and annotation of the MS/MS data was achieved by requiring a fragment ion mass error of 5 ppm, considering reproducible N- and C-terminal fragment ions only, and excluding internal fragment ion assignments. We report the first EThcD and UVPD MS/MS analysis of intact filgrastim, and these two techniques combined resulted in 98% amino acid sequence coverage. By combining all tested fragmentation modes, we obtained near-complete amino acid sequence coverage (99.4%) of intact filgrastim.
Collapse
Affiliation(s)
- Maša Babović
- Department of Biochemistry and Molecular Biology and VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, 5230 Odense, Denmark
| | - Pavel V Shliaha
- Department of Biochemistry and Molecular Biology and VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, 5230 Odense, Denmark
| | - Sebastian Gibb
- Department of Anesthesiology and Intensive Care, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Ole N Jensen
- Department of Biochemistry and Molecular Biology and VILLUM Center for Bioanalytical Sciences, University of Southern Denmark, 5230 Odense, Denmark
| |
Collapse
|
17
|
Zemaitis KJ, Veličković D, Kew W, Fort KL, Reinhardt-Szyba M, Pamreddy A, Ding Y, Kaushik D, Sharma K, Makarov AA, Zhou M, Paša-Tolić L. Enhanced Spatial Mapping of Histone Proteoforms in Human Kidney Through MALDI-MSI by High-Field UHMR-Orbitrap Detection. Anal Chem 2022; 94:12604-12613. [PMID: 36067026 PMCID: PMC10064997 DOI: 10.1021/acs.analchem.2c01034] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Core histones including H2A, H2B, H3, and H4 are key modulators of cellular repair, transcription, and replication within eukaryotic cells, playing vital roles in the pathogenesis of disease and cellular responses to environmental stimuli. Traditional mass spectrometry (MS)-based bottom-up and top-down proteomics allows for the comprehensive identification of proteins and of post-translational modification (PTM) harboring proteoforms. However, these methodologies have difficulties preserving near-cellular spatial distributions because they typically require laser capture microdissection (LCM) and advanced sample preparation techniques. Herein, we coupled a matrix-assisted laser desorption/ionization (MALDI) source with a Thermo Scientific Q Exactive HF Orbitrap MS upgraded with ultrahigh mass range (UHMR) boards for the first demonstration of complementary high-resolution accurate mass (HR/AM) measurements of proteoforms up to 16.5 kDa directly from tissues using this benchtop mass spectrometer. The platform achieved isotopic resolution throughout the detected mass range, providing confident assignments of proteoforms with low ppm mass error and a considerable increase in duty cycle over other Fourier transform mass analyzers. Proteoform mapping of core histones was demonstrated on sections of human kidney at near-cellular spatial resolution, with several key distributions of histone and other proteoforms noted within both healthy biopsy and a section from a renal cell carcinoma (RCC) containing nephrectomy. The use of MALDI-MS imaging (MSI) for proteoform mapping demonstrates several steps toward high-throughput accurate identification of proteoforms and provides a new tool for mapping biomolecule distributions throughout tissue sections in extended mass ranges.
Collapse
Affiliation(s)
- Kevin J Zemaitis
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Dušan Veličković
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - William Kew
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Kyle L Fort
- Thermo Fisher Scientific (Bremen) GmbH, 28199 Bremen, Germany
| | | | - Annapurna Pamreddy
- Center for Renal Precision Medicine, Department of Medicine, University of Texas Health, San Antonio, Texas 78284, United States
| | - Yanli Ding
- Department of Pathology and Laboratory Medicine, University of Texas Health, San Antonio, Texas 78284, United States
| | - Dharam Kaushik
- Department of Urology, University of Texas Health, San Antonio, Texas 78284, United States
| | - Kumar Sharma
- Center for Renal Precision Medicine, Department of Medicine, University of Texas Health, San Antonio, Texas 78284, United States.,Audie L. Murphy Memorial VA Hospital, South Texas Veterans Health Care System, San Antonio, Texas 78284, United States
| | - Alexander A Makarov
- Thermo Fisher Scientific (Bremen) GmbH, 28199 Bremen, Germany.,Biomolecular Mass Spectrometry and Proteomics, Bijvoet Center for Biomolecular Research and Utrecht Institute for Pharmaceutical Sciences, University of Utrecht, Utrecht 3584, The Netherlands
| | - Mowei Zhou
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| | - Ljiljana Paša-Tolić
- Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland, Washington 99352, United States
| |
Collapse
|
18
|
Winkels K, Koudelka T, Kaulich PT, Leippe M, Tholey A. Validation of Top-Down Proteomics Data by Bottom-Up-Based N-Terminomics Reveals Pitfalls in Top-Down-Based Terminomics Workflows. J Proteome Res 2022; 21:2185-2196. [PMID: 35972260 DOI: 10.1021/acs.jproteome.2c00277] [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: 11/29/2022]
Abstract
Bottom-up proteomics (BUP)-based N-terminomics techniques have become standard to identify protein N-termini. While these methods rely on the identification of N-terminal peptides only, top-down proteomics (TDP) comes with the promise to provide additional information about post-translational modifications and the respective C-termini. To evaluate the potential of TDP for terminomics, two established TDP workflows were employed for the proteome analysis of the nematode Caenorhabditis elegans. The N-termini of the identified proteoforms were validated using a BUP-based N-terminomics approach. The TDP workflows used here identified 1658 proteoforms, the N-termini of which were verified by BUP in 25% of entities only. Caveats in both the BUP- and TDP-based workflows were shown to contribute to this low overlap. In BUP, the use of trypsin prohibits the detection of arginine-rich or arginine-deficient N-termini, while in TDP, the formation of artificially generated termini was observed in particular in a workflow encompassing sample treatment with high acid concentrations. Furthermore, we demonstrate the applicability of reductive dimethylation in TDP to confirm biological N-termini. Overall, our study shows not only the potential but also current limitations of TDP for terminomics studies and also presents suggestions for future developments, for example, for data quality control, allowing improvement of the detection of protein termini by TDP.
Collapse
Affiliation(s)
- Konrad Winkels
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Tomas Koudelka
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Philipp T Kaulich
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Matthias Leippe
- Comparative Immunobiology, Zoological Institute, Christian-Albrechts-Universität zu Kiel, 24098 Kiel, Germany
| | - Andreas Tholey
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| |
Collapse
|
19
|
Becker T, Wiest A, Telek A, Bejko D, Hoffmann-Röder A, Kielkowski P. Transforming Chemical Proteomics Enrichment into a High-Throughput Method Using an SP2E Workflow. JACS Au 2022; 2:1712-1723. [PMID: 35911458 PMCID: PMC9326820 DOI: 10.1021/jacsau.2c00284] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/12/2023]
Abstract
Protein post-translational modifications (PTMs) play a critical role in the regulation of protein catalytic activity, localization, and protein-protein interactions. Attachment of PTMs onto proteins significantly diversifies their structure and function, resulting in proteoforms. However, the sole identification of post-translationally modified proteins, which are often cell type and disease-specific, is still a highly challenging task. Substoichiometric amounts and modifications of low abundant proteins necessitate the purification or enrichment of the modified proteins. Although the introduction of mass spectrometry-based chemical proteomic strategies has enabled the screening of protein PTMs with increased throughput, sample preparation remains highly time-consuming and tedious. Here, we report an optimized workflow for the enrichment of PTM proteins in a 96-well plate format, which could be extended to robotic automation. This platform allows us to significantly lower the input of total protein, which opens up the opportunity to screen specialized and difficult-to-culture cell lines in a high-throughput manner. The presented SP2E protocol is robust and time- and cost-effective, as well as suitable for large-scale screening of proteoforms. The application of the SP2E protocol will thus enable the characterization of proteoforms in various processes such as neurodevelopment, neurodegeneration, and cancer. This may contribute to an overall acceleration of the recently launched Human Proteoform Project.
Collapse
Affiliation(s)
- Tobias Becker
- Institute
for Chemical Epigenetics Munich, LMU Munich, 81375 Munich, Germany
| | - Andreas Wiest
- Institute
for Chemical Epigenetics Munich, LMU Munich, 81375 Munich, Germany
| | - András Telek
- Institute
for Chemical Epigenetics Munich, LMU Munich, 81375 Munich, Germany
| | - Daniel Bejko
- Institute
for Chemical Epigenetics Munich, LMU Munich, 81375 Munich, Germany
| | | | - Pavel Kielkowski
- Institute
for Chemical Epigenetics Munich, LMU Munich, 81375 Munich, Germany
| |
Collapse
|
20
|
Yang M, Hu H, Su P, Thomas PM, Camarillo JM, Greer JB, Early BP, Fellers RT, Kelleher NL, Laskin J. Proteoform-Selective Imaging of Tissues Using Mass Spectrometry. Angew Chem Int Ed Engl 2022; 61:e202200721. [PMID: 35446460 PMCID: PMC9276647 DOI: 10.1002/anie.202200721] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [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: 01/17/2022] [Indexed: 01/28/2023]
Abstract
Unraveling the complexity of biological systems relies on the development of new approaches for spatially resolved proteoform‐specific analysis of the proteome. Herein, we employ nanospray desorption electrospray ionization mass spectrometry imaging (nano‐DESI MSI) for the proteoform‐selective imaging of biological tissues. Nano‐DESI generates multiply charged protein ions, which is advantageous for their structural characterization using tandem mass spectrometry (MS/MS) directly on the tissue. Proof‐of‐concept experiments demonstrate that nano‐DESI MSI combined with on‐tissue top‐down proteomics is ideally suited for the proteoform‐selective imaging of tissue sections. Using rat brain tissue as a model system, we provide the first evidence of differential proteoform expression in different regions of the brain.
Collapse
Affiliation(s)
- Manxi Yang
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN 47907USA
| | - Hang Hu
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN 47907USA
| | - Pei Su
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN 47907USA
- Departments of Chemistry and Molecular BiosciencesNorthwestern University2145 Sheridan RoadEvanstonIL 60208USA
| | - Paul M. Thomas
- Departments of Chemistry and Molecular BiosciencesNorthwestern University2145 Sheridan RoadEvanstonIL 60208USA
| | - Jeannie M. Camarillo
- Departments of Chemistry and Molecular BiosciencesNorthwestern University2145 Sheridan RoadEvanstonIL 60208USA
| | - Joseph B. Greer
- Departments of Chemistry and Molecular BiosciencesNorthwestern University2145 Sheridan RoadEvanstonIL 60208USA
| | - Bryan P. Early
- Departments of Chemistry and Molecular BiosciencesNorthwestern University2145 Sheridan RoadEvanstonIL 60208USA
| | - Ryan T. Fellers
- Departments of Chemistry and Molecular BiosciencesNorthwestern University2145 Sheridan RoadEvanstonIL 60208USA
| | - Neil L. Kelleher
- Departments of Chemistry and Molecular BiosciencesNorthwestern University2145 Sheridan RoadEvanstonIL 60208USA
| | - Julia Laskin
- Department of ChemistryPurdue University560 Oval DriveWest LafayetteIN 47907USA
| |
Collapse
|
21
|
Yang M, Hu H, Su P, Thomas PM, Camarillo JM, Greer JB, Early BP, Fellers RT, Kelleher NL, Laskin J. Proteoform‐Selective Imaging of Tissues Using Mass Spectrometry. Angew Chem Int Ed Engl 2022. [DOI: 10.1002/ange.202200721] [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: 11/10/2022]
Affiliation(s)
- Manxi Yang
- Purdue University Department of Chemistry chemistry 560 Oval Dr. 47906 West Lafayette UNITED STATES
| | - Hang Hu
- Purdue University Chemistry UNITED STATES
| | - Pei Su
- Northwestern University Chemistry and Molecular Biosciences UNITED STATES
| | - Paul M. Thomas
- Northwestern University Chemistry and Molecular Biosciences UNITED STATES
| | | | - Joseph B. Greer
- Northwestern University Chemistry and Molecular Biosciences UNITED STATES
| | - Bryan P. Early
- Northwestern University Chemistry and Molecular Biosciences UNITED STATES
| | - Ryan T. Fellers
- Northwestern University Chemistry and Molecular Biosciences UNITED STATES
| | - Neil L. Kelleher
- Northwestern University Chemistry and Molecular Biosciences UNITED STATES
| | - Julia Laskin
- Purdue University Department of Chemistry 560 Oval Dr. 47907 West Lafayette UNITED STATES
| |
Collapse
|
22
|
Abstract
A functional understanding of the human body requires structure-function studies of proteins at scale. The chemical structure of proteins is controlled at the transcriptional, translational, and post-translational levels, creating a variety of products with modulated functions within the cell. The term "proteoform" encapsulates this complexity at the level of chemical composition. Comprehensive mapping of the proteoform landscape in human tissues necessitates analytical techniques with increased sensitivity and depth of coverage. Here, we took a top-down proteomics approach, combining data generated using capillary zone electrophoresis (CZE) and nanoflow reversed-phase liquid chromatography (RPLC) hyphenated to mass spectrometry to identify and characterize proteoforms from the human lungs, heart, spleen, small intestine, and kidneys. CZE and RPLC provided complementary post-translational modification and proteoform selectivity, thereby enhancing the overall proteome coverage when used in combination. Of the 11,466 proteoforms identified in this study, 7373 (64%) were not reported previously. Large differences in the protein and proteoform level were readily quantified, with initial inferences about proteoform biology operative in the analyzed organs. Differential proteoform regulation of defensins, glutathione transferases, and sarcomeric proteins across tissues generate hypotheses about how they function and are regulated in human health and disease.
Collapse
Affiliation(s)
- Bryon S Drown
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Kevin Jooß
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Rafael D Melani
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Cameron Lloyd-Jones
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Jeannie M Camarillo
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| | - Neil L Kelleher
- Departments of Molecular Biosciences, Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, Illinois 60208, United States
| |
Collapse
|
23
|
Tucholski T, Ge Y. Fourier-transform ion cyclotron resonance mass spectrometry for characterizing proteoforms. Mass Spectrom Rev 2022; 41:158-177. [PMID: 32894796 PMCID: PMC7936991 DOI: 10.1002/mas.21653] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 08/26/2020] [Accepted: 08/26/2020] [Indexed: 05/05/2023]
Abstract
Proteoforms contribute functional diversity to the proteome and aberrant proteoforms levels have been implicated in biological dysfunction and disease. Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS), with its ultrahigh mass-resolving power, mass accuracy, and versatile tandem MS capabilities, has empowered top-down, middle-down, and native MS-based approaches for characterizing proteoforms and their complexes in biological systems. Herein, we review the features which make FT-ICR MS uniquely suited for measuring proteoform mass with ultrahigh resolution and mass accuracy; obtaining in-depth proteoform sequence coverage with expansive tandem MS capabilities; and unambiguously identifying and localizing post-translational and noncovalent modifications. We highlight examples from our body of work in which we have quantified and comprehensively characterized proteoforms from cardiac and skeletal muscle to better understand conditions such as chronic heart failure, acute myocardial infarction, and sarcopenia. Structural characterization of monoclonal antibodies and their proteoforms by FT-ICR MS and emerging applications, such as native top-down FT-ICR MS and high-throughput top-down FT-ICR MS-based proteomics at 21 T, are also covered. Historically, the information gleaned from FT-ICR MS analyses have helped provide biological insights. We predict FT-ICR MS will continue to enable the study of proteoforms of increasing size from increasingly complex endogenous mixtures and facilitate the benchmarking of sensitive and specific assays for clinical diagnostics. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.
Collapse
Affiliation(s)
- Trisha Tucholski
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, WI, 53706
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, WI, 53706
- Human Proteomics Program, University of Wisconsin-Madison, Madison, WI, 53705
| |
Collapse
|
24
|
Lubeckyj RA, Sun L. Laser capture microdissection-capillary zone electrophoresis-tandem mass spectrometry (LCM-CZE-MS/MS) for spatially resolved top-down proteomics: a pilot study of zebrafish brain. Mol Omics 2022; 18:112-122. [PMID: 34935839 PMCID: PMC9066772 DOI: 10.1039/d1mo00335f] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Mass spectrometry (MS)-based spatially resolved top-down proteomics (TDP) of tissues is crucial for understanding the roles played by microenvironmental heterogeneity in the biological functions of organs and for discovering new proteoform biomarkers of diseases. There are few published spatially resolved TDP studies. One of the challenges relates to the limited performance of TDP for the analysis of spatially isolated samples using, for example, laser capture microdissection (LCM) because those samples are usually mass-limited. We present the first pilot study of LCM-capillary zone electrophoresis (CZE)-MS/MS for spatially resolved TDP and used zebrafish brain as the sample. The LCM-CZE-MS/MS platform employed a non-ionic detergent and a freeze-thaw method for efficient proteoform extraction from LCM isolated brain sections followed by CZE-MS/MS without any sample cleanup step, ensuring high sensitivity. Over 400 proteoforms were identified in a CZE-MS/MS analysis of one LCM brain section via consuming the protein content of roughly 250 cells. We observed drastic differences in proteoform profiles between two LCM brain sections isolated from the optic tectum (Teo) and telencephalon (Tel) regions. Proteoforms of three proteins (npy, penkb, and pyya) having neuropeptide hormone activity were exclusively identified in the isolated Tel section. Proteoforms of reticulon, myosin, and troponin were almost exclusively identified in the isolated Teo section, and those proteins play essential roles in visual and motor activities. The proteoform profiles accurately reflected the main biological functions of the Teo and Tel regions of the brain. Additionally, hundreds of post-translationally modified proteoforms were identified.
Collapse
Affiliation(s)
| | - Liangliang Sun
- Department of Chemistry, Michigan State University, 578 S Shaw Ln, East Lansing, MI 48824, USA.
| |
Collapse
|
25
|
Melani RD, Gerbasi VR, Anderson LC, Sikora JW, Toby TK, Hutton JE, Butcher DS, Negrão F, Seckler HS, Srzentić K, Fornelli L, Camarillo JM, LeDuc RD, Cesnik AJ, Lundberg E, Greer JB, Fellers RT, Robey MT, DeHart CJ, Forte E, Hendrickson CL, Abbatiello SE, Thomas PM, Kokaji AI, Levitsky J, Kelleher NL. The Blood Proteoform Atlas: A reference map of proteoforms in human hematopoietic cells. Science 2022; 375:411-418. [PMID: 35084980 PMCID: PMC9097315 DOI: 10.1126/science.aaz5284] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [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] [Indexed: 01/30/2023]
Abstract
Human biology is tightly linked to proteins, yet most measurements do not precisely determine alternatively spliced sequences or posttranslational modifications. Here, we present the primary structures of ~30,000 unique proteoforms, nearly 10 times more than in previous studies, expressed from 1690 human genes across 21 cell types and plasma from human blood and bone marrow. The results, compiled in the Blood Proteoform Atlas (BPA), indicate that proteoforms better describe protein-level biology and are more specific indicators of differentiation than their corresponding proteins, which are more broadly expressed across cell types. We demonstrate the potential for clinical application, by interrogating the BPA in the context of liver transplantation and identifying cell and proteoform signatures that distinguish normal graft function from acute rejection and other causes of graft dysfunction.
Collapse
Affiliation(s)
- Rafael D. Melani
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Vincent R. Gerbasi
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Lissa C. Anderson
- National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
| | - Jacek W. Sikora
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Timothy K. Toby
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Josiah E. Hutton
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - David S. Butcher
- National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
| | - Fernanda Negrão
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Henrique S. Seckler
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Kristina Srzentić
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Luca Fornelli
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Jeannie M. Camarillo
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Richard D. LeDuc
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Anthony J. Cesnik
- Department of Genetics, Stanford University, Stanford, CA, USA
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Emma Lundberg
- Department of Genetics, Stanford University, Stanford, CA, USA
- Science for Life Laboratory, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH-Royal Institute of Technology, Stockholm, Sweden
| | - Joseph B. Greer
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Ryan T. Fellers
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Matthew T. Robey
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Caroline J. DeHart
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | - Eleonora Forte
- Proteomics Center of Excellence, Northwestern University, Evanston, IL, USA
- Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | | | - Paul M. Thomas
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | | | - Josh Levitsky
- Comprehensive Transplant Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Neil L. Kelleher
- Department of Molecular Biosciences, Department of Chemistry, and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
- Department of Biochemistry and Molecular Genetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| |
Collapse
|
26
|
Hollas MAR, Robey M, Fellers R, LeDuc R, Thomas P, Kelleher N. The Human Proteoform Atlas: a FAIR community resource for experimentally derived proteoforms. Nucleic Acids Res 2022; 50:D526-D533. [PMID: 34986596 PMCID: PMC8728143 DOI: 10.1093/nar/gkab1086] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2021] [Revised: 10/06/2021] [Accepted: 11/14/2021] [Indexed: 01/01/2023] Open
Abstract
The Human Proteoform Atlas (HPfA) is a web-based repository of experimentally verified human proteoforms on-line at http://human-proteoform-atlas.org and is a direct descendant of the Consortium of Top-Down Proteomics' (CTDP) Proteoform Atlas. Proteoforms are the specific forms of protein molecules expressed by our cells and include the unique combination of post-translational modifications (PTMs), alternative splicing and other sources of variation deriving from a specific gene. The HPfA uses a FAIR system to assign persistent identifiers to proteoforms which allows for redundancy calling and tracking from prior and future studies in the growing community of proteoform biology and measurement. The HPfA is organized around open ontologies and enables flexible classification of proteoforms. To achieve this, a public registry of experimentally verified proteoforms was also created. Submission of new proteoforms can be processed through email vianrtdphelp@northwestern.edu, and future iterations of these proteoform atlases will help to organize and assign function to proteoforms, their PTMs and their complexes in the years ahead.
Collapse
Affiliation(s)
- Michael A R Hollas
- Departments of Molecular Biosciences, Chemistry, and the Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60208, USA
| | - Matthew T Robey
- Departments of Molecular Biosciences, Chemistry, and the Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60208, USA
| | - Ryan T Fellers
- Departments of Molecular Biosciences, Chemistry, and the Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60208, USA
| | - Richard D LeDuc
- Departments of Molecular Biosciences, Chemistry, and the Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60208, USA
| | - Paul M Thomas
- Departments of Molecular Biosciences, Chemistry, and the Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60208, USA
| | - Neil L Kelleher
- Departments of Molecular Biosciences, Chemistry, and the Chemistry of Life Processes Institute, Northwestern University, Evanston, IL 60208, USA
| |
Collapse
|
27
|
Abstract
The remarkable advancement of top-down proteomics in the past decade is driven by the technological development in separation, mass spectrometry (MS) instrumentation, novel fragmentation, and bioinformatics. However, the accurate identification and quantification of proteoforms, all clearly-defined molecular forms of protein products from a single gene, remain a challenging computational task. This is in part due to the complicated mass spectra from intact proteoforms when compared to those from the digested peptides. Herein, pTop 2.0 is developed to fill in the gap between the large-scale complex top-down MS data and the shortage of high-accuracy bioinformatic tools. Compared with pTop 1.0, the first version, pTop 2.0 concentrates mainly on the identification of the proteoforms with unexpected modifications or a terminal truncation. The quantitation based on isotopic labeling is also a new function, which can be carried out by the convenient and user-friendly "one-key operation," integrated together with the qualitative identifications. The accuracy and running speed of pTop 2.0 is significantly improved on the test data sets. This chapter will introduce the main features, step-by-step running operations, and algorithmic developments of pTop 2.0 in order to push the identification and quantitation of intact proteoforms to a higher-accuracy level in top-down proteomics.
Collapse
Affiliation(s)
- Rui-Xiang Sun
- National Institute of Biological Sciences, Beijing, China.
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
| | - Rui-Min Wang
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Lan Luo
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Chao Liu
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Hao Chi
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Wen-Feng Zeng
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| | - Si-Min He
- Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
28
|
Abstract
Top-down mass spectrometry (MS)-based analysis of larger proteoforms (>50 kDa) is typically challenging due to an exponential decay in the signal-to-noise ratio with increasing protein molecular weight (MW) and coelution with low-MW proteoforms. Size exclusion chromatography (SEC) fractionates proteins based on their size, separating larger proteoforms from those of smaller size in the proteome. In this protocol, we initially describe the use of SEC to fractionate high-MW proteoforms from low-MW proteoforms. Subsequently, the SEC fractions containing the proteoforms of interest are subjected to reverse-phase liquid chromatography (RPLC) coupled online with high-resolution MS. Finally, proteoforms are characterized using MASH Explorer, a user-friendly software environment for in-depth proteoform characterization.
Collapse
Affiliation(s)
- Timothy N. Tiambeng
- Department of Chemistry, University of Wisconsin – Madison, Madison, WI 53706
| | - Zhijie Wu
- Department of Chemistry, University of Wisconsin – Madison, Madison, WI 53706
| | - Jake A. Melby
- Department of Chemistry, University of Wisconsin – Madison, Madison, WI 53706
| | - Ying Ge
- Department of Chemistry, University of Wisconsin – Madison, Madison, WI 53706,Department of Cell and Regenerative Biology, University of Wisconsin – Madison, Madison, WI 53705,Human Proteomic Program, University of Wisconsin – Madison, Madison WI 53705,To whom correspondence may be addressed: Dr. Ying Ge, 8551 WIMR-II, 1111 Highland Ave., Madison, Wisconsin 53705, USA. ; Tel: 608-265-4744
| |
Collapse
|
29
|
Nishida H, Ishihama Y. One-Step Isolation of Protein C-Terminal Peptides from V8 Protease-Digested Proteins by Metal Oxide-Based Ligand-Exchange Chromatography. Anal Chem 2021; 94:944-951. [PMID: 34962382 DOI: 10.1021/acs.analchem.1c03722] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [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
We have developed a one-step method to isolate protein C-terminal peptides from V8 protease-digested proteins by metal oxide-based ligand-exchange (MOLEX) chromatography. V8 protease cleaves the C-terminal side of Asp and Glu, affording a digested peptide with two carboxy groups at the C-terminus, whereas the protein C-terminal peptide has only one α-carboxy group. In MOLEX chromatography, a stable chelate is formed between dicarboxylates and metal atoms, so that the nonterminal (i.e., internal) peptide is retained, whereas the protein C-terminal peptide flows through the MOLEX column. After the optimization of the MOLEX chromatographic conditions, 1619 protein C-termini were identified from 30 μg of peptides (10 μg each, in triplicate) derived from human HeLa cells by means of nanoLC/MS/MS. When the MOLEX-isolated sample from 200 μg of HeLa peptides was further divided into six fractions by high-pH reversed-phase liquid chromatography (LC) prior to nanoLC/MS/MS, 2203 protein C-termini were identified with less than 3% contamination with internal peptides. We believe that this is the largest coverage with the highest purity reported to date in human protein C-terminomics. This fast, simple, sensitive, and selective method to isolate protein C-terminal peptides should be useful for profiling protein C-termini on a proteome-wide scale.
Collapse
Affiliation(s)
- Hiroshi Nishida
- Department of Molecular & Cellular Bioanalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan
| | - Yasushi Ishihama
- Department of Molecular & Cellular Bioanalysis, Graduate School of Pharmaceutical Sciences, Kyoto University, Kyoto 606-8501, Japan.,National Institute of Biomedical Innovation, Health and Nutrition, Laboratory of Clinical and Analytical Chemistry, Ibaraki, Osaka 567-0085, Japan
| |
Collapse
|
30
|
Abstract
A large fraction of observed fragment ion intensity remains unidentified in top-down proteomics. The elucidation of these unknown fragment ions could enable researchers to identify additional proteoforms and reduce proteoform ambiguity in their analyses. Internal fragment ions have received considerable attention as a major source of these unidentified fragment ions. Internal fragments are product ions that contain neither protein terminus, in contrast with terminal ions that contain a single terminus. There are many more possible internal fragments than terminal fragments, and the resulting computational complexity has historically limited the application of internal fragment ions to low-complexity samples containing only one or a few proteins of interest. We implemented internal fragment ion functionality in MetaMorpheus to allow the proteome-wide annotation of internal fragment ions. MetaMorpheus first uses terminal fragment ions to identify putative proteoforms and then employs internal fragment ions to disambiguate similar proteoforms. In the analysis of mammalian cell lysates, we found that MetaMorpheus could disambiguate over half of its previously ambiguous proteoforms while also providing up to a 7% increase in proteoform-spectrum matches identified at a 1% false discovery rate.
Collapse
Affiliation(s)
- Zach Rolfs
- 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
| |
Collapse
|
31
|
Kaulich PT, Winkels K, Kaulich TB, Treitz C, Cassidy L, Tholey A. MSTopDiff: A Tool for the Visualization of Mass Shifts in Deconvoluted Top-Down Proteomics Data for the Database-Independent Detection of Protein Modifications. J Proteome Res 2021; 21:20-29. [PMID: 34818005 DOI: 10.1021/acs.jproteome.1c00766] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [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: 11/29/2022]
Abstract
Top-down proteomics analyzes intact proteoforms with all of their post-translational modifications and genetic and RNA splice variants. In addition, modifications introduced either deliberately or inadvertently during sample preparation, that is, via oxidation, alkylation, or labeling reagents, or through the formation of noncovalent adducts (e.g., detergents) further increase the sample complexity. To facilitate the recognition of protein modifications introduced during top-down analysis, we developed MSTopDiff, a software tool with a graphical user interface written in Python, which allows one to detect protein modifications by calculating and visualizing mass differences in top-down data without the prerequisite of a database search. We demonstrate the successful application of MSTopDiff for the detection of artifacts originating from oxidation, formylation, overlabeling during isobaric labeling, and adduct formation with cations or sodium dodecyl sulfate. MSTopDiff offers several modes of data representation using deconvoluted MS1 or MS2 spectra. In addition to artificial modifications, the tool enables the visualization of biological modifications such as phosphorylation and acetylation. MSTopDiff provides an overview of the artificial and biological modifications in top-down proteomics samples, which makes it a valuable tool in quality control of standard workflows and for parameter evaluation during method development.
Collapse
Affiliation(s)
- Philipp T Kaulich
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Konrad Winkels
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Tobias B Kaulich
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Christian Treitz
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Liam Cassidy
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| | - Andreas Tholey
- Systematic Proteome Research & Bioanalytics, Institute for Experimental Medicine, Christian-Albrechts-Universität zu Kiel, 24105 Kiel, Germany
| |
Collapse
|
32
|
Smith LM, Agar JN, Chamot-Rooke J, Danis PO, Ge Y, Loo JA, Paša-Tolić L, Tsybin YO, Kelleher NL. The Human Proteoform Project: Defining the human proteome. Sci Adv 2021; 7:eabk0734. [PMID: 34767442 PMCID: PMC8589312 DOI: 10.1126/sciadv.abk0734] [Citation(s) in RCA: 88] [Impact Index Per Article: 29.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Accepted: 09/23/2021] [Indexed: 05/23/2023]
Abstract
Proteins are the primary effectors of function in biology, and thus, complete knowledge of their structure and properties is fundamental to deciphering function in basic and translational research. The chemical diversity of proteins is expressed in their many proteoforms, which result from combinations of genetic polymorphisms, RNA splice variants, and posttranslational modifications. This knowledge is foundational for the biological complexes and networks that control biology yet remains largely unknown. We propose here an ambitious initiative to define the human proteome, that is, to generate a definitive reference set of the proteoforms produced from the genome. Several examples of the power and importance of proteoform-level knowledge in disease-based research are presented along with a call for improved technologies in a two-pronged strategy to the Human Proteoform Project.
Collapse
Affiliation(s)
- Lloyd M. Smith
- Department of Chemistry, University of Wisconsin, Madison, WI, USA
| | - Jeffrey N. Agar
- Departments of Chemistry and Chemical Biology and Pharmaceutical Sciences, Northeastern University, Boston, MA, USA
| | - Julia Chamot-Rooke
- Department of Structural Biology and Chemistry, Institut Pasteur, CNRS, Paris, France
| | - Paul O. Danis
- Consortium for Top-Down Proteomics, Cambridge, MA, USA
| | - Ying Ge
- Department of Cell and Regenerative Biology, Department of Chemistry, Human Proteomics Program, University of Wisconsin-Madison, Madison, WI, USA
| | - Joseph A. Loo
- Department of Chemistry and Biochemistry, University of California, Los Angeles, Los Angeles, CA, USA
| | | | | | - Neil L. Kelleher
- Departments of Chemistry, Molecular Biosciences and the Feinberg School of Medicine, Northwestern University, Evanston, IL, USA
| | | |
Collapse
|
33
|
Abstract
Proteoform identification is required to fully understand the biological diversity present in a sample. However, these identifications are often ambiguous because of the challenges in analyzing full length proteins by mass spectrometry. A five-level proteoform classification system was recently developed to delineate the ambiguity of proteoform identifications and to allow for comparisons across software platforms and acquisition methods. Widespread adoption of this system requires software tools to provide classification of the proteoform identifications. We describe here an implementation of the five-level classification system in the software program MetaMorpheus, which provides both bottom-up and top-down identifications. Additionally, we developed a stand-alone program called ProteoformClassifier that allows users to classify proteoform results from any search program, provided that the program writes output that includes the information necessary to evaluate proteoform ambiguity. This stand-alone program includes a small test file and database to evaluate if a given program provides sufficient information to evaluate ambiguity. If the program does not, then ProteoformClassifier provides meaningful feedback to assist developers with implementing the classification system. We tested currently available top-down software programs and found that none of them (other than MetaMorpheus) provided sufficient information regarding identification ambiguity to permit classification.
Collapse
Affiliation(s)
- Zach Rolfs
- 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
| |
Collapse
|
34
|
Arauz-Garofalo G, Jodar M, Vilanova M, de la Iglesia Rodriguez A, Castillo J, Soler-Ventura A, Oliva R, Vilaseca M, Gay M. Protamine Characterization by Top-Down Proteomics: Boosting Proteoform Identification with DBSCAN. Proteomes 2021; 9:21. [PMID: 33946530 DOI: 10.3390/proteomes9020021] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/25/2021] [Accepted: 04/27/2021] [Indexed: 12/12/2022] Open
Abstract
Protamines replace histones as the main nuclear protein in the sperm cells of many species and play a crucial role in compacting the paternal genome. Human spermatozoa contain protamine 1 (P1) and the family of protamine 2 (P2) proteins. Alterations in protamine PTMs or the P1/P2 ratio may be associated with male infertility. Top-down proteomics enables large-scale analysis of intact proteoforms derived from alternative splicing, missense or nonsense genetic variants or PTMs. In contrast to current gold standard techniques, top-down proteomics permits a more in-depth analysis of protamine PTMs and proteoforms, thereby opening up new perspectives to unravel their impact on male fertility. We report on the analysis of two normozoospermic semen samples by top-down proteomics. We discuss the difficulties encountered with the data analysis and propose solutions as this step is one of the current bottlenecks in top-down proteomics with the bioinformatics tools currently available. Our strategy for the data analysis combines two software packages, ProSight PD (PS) and TopPIC suite (TP), with a clustering algorithm to decipher protamine proteoforms. We identified up to 32 protamine proteoforms at different levels of characterization. This in-depth analysis of the protamine proteoform landscape of normozoospermic individuals represents the first step towards the future study of sperm pathological conditions opening up the potential personalized diagnosis of male infertility.
Collapse
|
35
|
Schmitt ND, Berger JM, Conway JB, Agar JN. Increasing Top-Down Mass Spectrometry Sequence Coverage by an Order of Magnitude through Optimized Internal Fragment Generation and Assignment. Anal Chem 2021; 93:6355-6362. [DOI: 10.1021/acs.analchem.0c04670] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Nicholas D. Schmitt
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
- Barnett Institute for Chemical and Biological Analysis, Northeastern University, Boston, Massachusetts 02115, United States
| | - Joshua M. Berger
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
- Barnett Institute for Chemical and Biological Analysis, Northeastern University, Boston, Massachusetts 02115, United States
| | - Jeremy B. Conway
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
- Barnett Institute for Chemical and Biological Analysis, Northeastern University, Boston, Massachusetts 02115, United States
| | - Jeffrey N. Agar
- Department of Chemistry and Chemical Biology, Northeastern University, Boston, Massachusetts 02115, United States
- Department of Pharmaceutical Sciences, Northeastern University, Boston, Massachusetts 02115, United States
- Barnett Institute for Chemical and Biological Analysis, Northeastern University, Boston, Massachusetts 02115, United States
| |
Collapse
|
36
|
Palafox MF, Desai HS, Arboleda VA, Backus KM. From chemoproteomic-detected amino acids to genomic coordinates: insights into precise multi-omic data integration. Mol Syst Biol 2021; 17:e9840. [PMID: 33599394 PMCID: PMC7890448 DOI: 10.15252/msb.20209840] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [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: 07/03/2020] [Revised: 01/15/2021] [Accepted: 01/18/2021] [Indexed: 12/31/2022] Open
Abstract
The integration of proteomic, transcriptomic, and genetic variant annotation data will improve our understanding of genotype-phenotype associations. Due, in part, to challenges associated with accurate inter-database mapping, such multi-omic studies have not extended to chemoproteomics, a method that measures the intrinsic reactivity and potential "druggability" of nucleophilic amino acid side chains. Here, we evaluated mapping approaches to match chemoproteomic-detected cysteine and lysine residues with their genetic coordinates. Our analysis revealed that database update cycles and reliance on stable identifiers can lead to pervasive misidentification of labeled residues. Enabled by this examination of mapping strategies, we then integrated our chemoproteomics data with computational methods for predicting genetic variant pathogenicity, which revealed that codons of highly reactive cysteines are enriched for genetic variants that are predicted to be more deleterious and allowed us to identify and functionally characterize a new damaging residue in the cysteine protease caspase-8. Our study provides a roadmap for more precise inter-database mapping and points to untapped opportunities to improve the predictive power of pathogenicity scores and to advance prioritization of putative druggable sites.
Collapse
Affiliation(s)
- Maria F Palafox
- Department of Human GeneticsDavid Geffen School of MedicineUCLALos AngelesCAUSA
- Department of Biological ChemistryDavid Geffen School of MedicineUCLALos AngelesCAUSA
- Department of Pathology and Laboratory MedicineDavid Geffen School of MedicineUCLALos AngelesCAUSA
| | - Heta S Desai
- Department of Biological ChemistryDavid Geffen School of MedicineUCLALos AngelesCAUSA
- Molecular Biology InstituteUCLALos AngelesCAUSA
| | - Valerie A Arboleda
- Department of Human GeneticsDavid Geffen School of MedicineUCLALos AngelesCAUSA
- Department of Pathology and Laboratory MedicineDavid Geffen School of MedicineUCLALos AngelesCAUSA
- Molecular Biology InstituteUCLALos AngelesCAUSA
- Jonsson Comprehensive Cancer CenterUCLALos AngelesCAUSA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell ResearchUCLALos AngelesCAUSA
| | - Keriann M Backus
- Department of Biological ChemistryDavid Geffen School of MedicineUCLALos AngelesCAUSA
- Molecular Biology InstituteUCLALos AngelesCAUSA
- Jonsson Comprehensive Cancer CenterUCLALos AngelesCAUSA
- Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell ResearchUCLALos AngelesCAUSA
- Department of Chemistry and BiochemistryCollege of Arts and SciencesUCLALos AngelesCAUSA
- DOE Institute for Genomics and ProteomicsUCLALos AngelesCAUSA
| |
Collapse
|
37
|
Brown KA, Tucholski T, Alpert AJ, Eken C, Wesemann L, Kyrvasilis A, Jin S, Ge Y. Top-Down Proteomics of Endogenous Membrane Proteins Enabled by Cloud Point Enrichment and Multidimensional Liquid Chromatography-Mass Spectrometry. Anal Chem 2020; 92:15726-15735. [PMID: 33231430 PMCID: PMC7968110 DOI: 10.1021/acs.analchem.0c02533] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [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] [Indexed: 01/31/2023]
Abstract
Although top-down proteomics has emerged as a powerful strategy to characterize proteins in biological systems, the analysis of endogenous membrane proteins remains challenging due to their low solubility, low abundance, and the complexity of the membrane subproteome. Here, we report a simple but effective enrichment and separation strategy for top-down proteomics of endogenous membrane proteins enabled by cloud point extraction and multidimensional liquid chromatography coupled to high-resolution mass spectrometry (MS). The cloud point extraction efficiently enriched membrane proteins using a single extraction, eliminating the need for time-consuming ultracentrifugation steps. Subsequently, size-exclusion chromatography (SEC) with an MS-compatible mobile phase (59% water, 40% isopropanol, 1% formic acid) was used to remove the residual surfactant and fractionate intact proteins (6-115 kDa). The fractions were separated further by reversed-phase liquid chromatography (RPLC) coupled with MS for protein characterization. This method was applied to human embryonic kidney cells and cardiac tissue lysates to enable the identification of 188 and 124 endogenous integral membrane proteins, respectively, some with as many as 19 transmembrane domains.
Collapse
Affiliation(s)
- Kyle A. Brown
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Trisha Tucholski
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Andrew J. Alpert
- PolyLC Inc., Columbia, Maryland 21045, United States
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA
| | - Christian Eken
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Lucas Wesemann
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA
| | - Andreas Kyrvasilis
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA
| | - Song Jin
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin, 53706, USA
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA
- Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, 53705, USA
| |
Collapse
|
38
|
Abstract
We report O-Pair Search, an approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides via an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at https://github.com/smith-chem-wisc/MetaMorpheus .
Collapse
Affiliation(s)
- Lei Lu
- Department of Chemistry, University of Wisconsin, Madison, WI, USA
| | - Nicholas M Riley
- Department of Chemistry, University of Stanford, Stanford, CA, USA
| | | | - Carolyn R Bertozzi
- Department of Chemistry, University of Stanford, Stanford, CA, USA
- Howard Hughes Medical Institute, Stanford, CA, USA
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin, Madison, WI, USA.
| |
Collapse
|
39
|
Lu L, Riley NM, Shortreed MR, Bertozzi CR, Smith LM. O-Pair Search with MetaMorpheus for O-glycopeptide characterization. Nat Methods 2020; 17:1133-1138. [PMID: 33106676 PMCID: PMC7606753 DOI: 10.1038/s41592-020-00985-5] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Accepted: 09/21/2020] [Indexed: 11/23/2022]
Abstract
We report O-Pair Search, a new approach to identify O-glycopeptides and localize O-glycosites. Using paired collision- and electron-based dissociation spectra, O-Pair Search identifies O-glycopeptides using an ion-indexed open modification search and localizes O-glycosites using graph theory and probability-based localization. O-Pair Search reduces search times more than 2,000-fold compared to current O-glycopeptide processing software, while defining O-glycosite localization confidence levels and generating more O-glycopeptide identifications. Beyond the mucin-type O-glycopeptides discussed here, O-Pair Search also accepts user-defined glycan databases, making it compatible with many types of O-glycosylation. O-Pair Search is freely available within the open-source MetaMorpheus platform at https://github.com/smith-chem-wisc/MetaMorpheus.
Collapse
Affiliation(s)
- Lei Lu
- Department of Chemistry, University of Wisconsin, Madison, WI, USA
| | - Nicholas M Riley
- Department of Chemistry, University of Stanford, Stanford, CA, USA
| | | | - Carolyn R Bertozzi
- Department of Chemistry, University of Stanford, Stanford, CA, USA.,Howard Hughes Medical Institute, Stanford, CA, USA
| | - Lloyd M Smith
- Department of Chemistry, University of Wisconsin, Madison, WI, USA.
| |
Collapse
|
40
|
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.
Collapse
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
| |
Collapse
|
41
|
Srzentić K, Fornelli L, Tsybin YO, Loo JA, Seckler H, Agar JN, Anderson LC, Bai DL, Beck A, Brodbelt JS, van der Burgt YEM, Chamot-Rooke J, Chatterjee S, Chen Y, Clarke DJ, Danis PO, Diedrich JK, D'Ippolito RA, Dupré M, Gasilova N, Ge Y, Goo YA, Goodlett DR, Greer S, Haselmann KF, He L, Hendrickson CL, Hinkle JD, Holt MV, Hughes S, Hunt DF, Kelleher NL, Kozhinov AN, Lin Z, Malosse C, Marshall AG, Menin L, Millikin RJ, Nagornov KO, Nicolardi S, Paša-Tolić L, Pengelley S, Quebbemann NR, Resemann A, Sandoval W, Sarin R, Schmitt ND, Shabanowitz J, Shaw JB, Shortreed MR, Smith LM, Sobott F, Suckau D, Toby T, Weisbrod CR, Wildburger NC, Yates JR, Yoon SH, Young NL, Zhou M. Interlaboratory Study for Characterizing Monoclonal Antibodies by Top-Down and Middle-Down Mass Spectrometry. J Am Soc Mass Spectrom 2020; 31:1783-1802. [PMID: 32812765 PMCID: PMC7539639 DOI: 10.1021/jasms.0c00036] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/02/2023]
Abstract
The Consortium for Top-Down Proteomics (www.topdownproteomics.org) launched the present study to assess the current state of top-down mass spectrometry (TD MS) and middle-down mass spectrometry (MD MS) for characterizing monoclonal antibody (mAb) primary structures, including their modifications. To meet the needs of the rapidly growing therapeutic antibody market, it is important to develop analytical strategies to characterize the heterogeneity of a therapeutic product's primary structure accurately and reproducibly. The major objective of the present study is to determine whether current TD/MD MS technologies and protocols can add value to the more commonly employed bottom-up (BU) approaches with regard to confirming protein integrity, sequencing variable domains, avoiding artifacts, and revealing modifications and their locations. We also aim to gather information on the common TD/MD MS methods and practices in the field. A panel of three mAbs was selected and centrally provided to 20 laboratories worldwide for the analysis: Sigma mAb standard (SiLuLite), NIST mAb standard, and the therapeutic mAb Herceptin (trastuzumab). Various MS instrument platforms and ion dissociation techniques were employed. The present study confirms that TD/MD MS tools are available in laboratories worldwide and provide complementary information to the BU approach that can be crucial for comprehensive mAb characterization. The current limitations, as well as possible solutions to overcome them, are also outlined. A primary limitation revealed by the results of the present study is that the expert knowledge in both experiment and data analysis is indispensable to practice TD/MD MS.
Collapse
Affiliation(s)
- Kristina Srzentić
- Northwestern University, Evanston, Illinois 60208-0001, United States
| | - Luca Fornelli
- Northwestern University, Evanston, Illinois 60208-0001, United States
| | - Yury O Tsybin
- Spectroswiss, EPFL Innovation Park, Building I, 1015 Lausanne, Switzerland
| | - Joseph A Loo
- University of California-Los Angeles, Los Angeles, California 90095, United States
| | - Henrique Seckler
- Northwestern University, Evanston, Illinois 60208-0001, United States
| | - Jeffrey N Agar
- Northeastern University, Boston, Massachusetts 02115, United States
| | - Lissa C Anderson
- National High Magnetic Field Laboratory, Tallahassee, Florida 32310, United States
| | - Dina L Bai
- University of Virginia, Charlottesville, Virginia 22901, United States
| | - Alain Beck
- Centre d'immunologie Pierre Fabre, 74160 Saint-Julien-en-Genevois, France
| | | | | | | | | | - Yunqiu Chen
- Biogen, Inc., Cambridge, Massachusetts 02142-1031, United States
| | - David J Clarke
- The University of Edinburgh, EH9 3FJ Edinburgh, United Kingdom
| | - Paul O Danis
- Consortium for Top-Down Proteomics, Cambridge, Massachusetts 02142, United States
| | - Jolene K Diedrich
- The Scripps Research Institute, La Jolla, California 92037, United States
| | | | | | - Natalia Gasilova
- Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Ying Ge
- University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Young Ah Goo
- University of Maryland, Baltimore, Maryland 21201, United States
| | - David R Goodlett
- University of Maryland, Baltimore, Maryland 21201, United States
| | - Sylvester Greer
- University of Texas at Austin, Austin, Texas 78712-1224, United States
| | | | - Lidong He
- National High Magnetic Field Laboratory, Tallahassee, Florida 32310, United States
| | | | - Joshua D Hinkle
- University of Virginia, Charlottesville, Virginia 22901, United States
| | - Matthew V Holt
- Baylor College of Medicine, Houston, Texas 77030-3411, United States
| | - Sam Hughes
- The University of Edinburgh, EH9 3FJ Edinburgh, United Kingdom
| | - Donald F Hunt
- University of Virginia, Charlottesville, Virginia 22901, United States
| | - Neil L Kelleher
- Northwestern University, Evanston, Illinois 60208-0001, United States
| | - Anton N Kozhinov
- Spectroswiss, EPFL Innovation Park, Building I, 1015 Lausanne, Switzerland
| | - Ziqing Lin
- University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | | | - Alan G Marshall
- National High Magnetic Field Laboratory, Tallahassee, Florida 32310, United States
- Florida State University, Tallahassee, Florida 32310-4005, United States
| | - Laure Menin
- Ecole Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - Robert J Millikin
- University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | | | - Simone Nicolardi
- Leiden University Medical Centre, 2300 RC Leiden, The Netherlands
| | - Ljiljana Paša-Tolić
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | | | - Neil R Quebbemann
- University of California-Los Angeles, Los Angeles, California 90095, United States
| | | | - Wendy Sandoval
- Genentech, Inc., South San Francisco, California 94080-4990, United States
| | - Richa Sarin
- Biogen, Inc., Cambridge, Massachusetts 02142-1031, United States
| | | | | | - Jared B Shaw
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| | | | - Lloyd M Smith
- University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Frank Sobott
- University of Antwerp, 2000 Antwerp, Belgium
- University of Leeds, LS2 9JT Leeds, United Kingdom
| | | | - Timothy Toby
- Northwestern University, Evanston, Illinois 60208-0001, United States
| | - Chad R Weisbrod
- National High Magnetic Field Laboratory, Tallahassee, Florida 32310, United States
| | - Norelle C Wildburger
- Washington University School of Medicine, St. Louis, Missouri 63110, United States
| | - John R Yates
- The Scripps Research Institute, La Jolla, California 92037, United States
| | - Sung Hwan Yoon
- University of Maryland, Baltimore, Maryland 21201, United States
| | - Nicolas L Young
- Baylor College of Medicine, Houston, Texas 77030-3411, United States
| | - Mowei Zhou
- Pacific Northwest National Laboratory, Richland, Washington 99354, United States
| |
Collapse
|
42
|
Wu Z, Roberts DS, Melby JA, Wenger K, Wetzel M, Gu Y, Ramanathan SG, Bayne EF, Liu X, Sun R, Ong IM, McIlwain SJ, Ge Y. MASH Explorer: A Universal Software Environment for Top-Down Proteomics. J Proteome Res 2020; 19:3867-3876. [PMID: 32786689 DOI: 10.1021/acs.jproteome.0c00469] [Citation(s) in RCA: 57] [Impact Index Per Article: 14.3] [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
Top-down mass spectrometry (MS)-based proteomics enable a comprehensive analysis of proteoforms with molecular specificity to achieve a proteome-wide understanding of protein functions. However, the lack of a universal software for top-down proteomics is becoming increasingly recognized as a major barrier, especially for newcomers. Here, we have developed MASH Explorer, a universal, comprehensive, and user-friendly software environment for top-down proteomics. MASH Explorer integrates multiple spectral deconvolution and database search algorithms into a single, universal platform which can process top-down proteomics data from various vendor formats, for the first time. It addresses the urgent need in the rapidly growing top-down proteomics community and is freely available to all users worldwide. With the critical need and tremendous support from the community, we envision that this MASH Explorer software package will play an integral role in advancing top-down proteomics to realize its full potential for biomedical research.
Collapse
Affiliation(s)
- Zhijie Wu
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - David S Roberts
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Jake A Melby
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Kent Wenger
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Molly Wetzel
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Yiwen Gu
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | | | - Elizabeth F Bayne
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Xiaowen Liu
- Department of BioHealth Informatics, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana 46202, United States.,Center for Computational Biology and Bioinformatics, Indiana University-Purdue University Indianapolis, Indianapolis, Indiana 46202, United States
| | - Ruixiang Sun
- National Institute of Biological Sciences, Beijing, 102206, China
| | - Irene M Ong
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Department of Obstetrics and Gynecology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Sean J McIlwain
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,University of Wisconsin Carbone Cancer Center, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Ying Ge
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| |
Collapse
|
43
|
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.
Collapse
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
| |
Collapse
|
44
|
Boeri Erba E, Signor L, Petosa C. Exploring the structure and dynamics of macromolecular complexes by native mass spectrometry. J Proteomics 2020; 222:103799. [DOI: 10.1016/j.jprot.2020.103799] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 03/23/2020] [Accepted: 04/25/2020] [Indexed: 12/15/2022]
|
45
|
Williams JP, Morrison LJ, Brown JM, Beckman JS, Voinov VG, Lermyte F. Top-Down Characterization of Denatured Proteins and Native Protein Complexes Using Electron Capture Dissociation Implemented within a Modified Ion Mobility-Mass Spectrometer. Anal Chem 2020; 92:3674-3681. [PMID: 31999103 DOI: 10.1021/acs.analchem.9b04763] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
Electron-based fragmentation methods have revolutionized biomolecular mass spectrometry, in particular native and top-down protein analysis. Here, we report the use of a new electromagnetostatic cell to perform electron capture dissociation (ECD) within a quadrupole/ion mobility/time-of-flight mass spectrometer. This cell was installed between the ion mobility and time-of-flight regions of the instrument, and fragmentation was fast enough to be compatible with mobility separation. The instrument was already fitted with electron transfer dissociation (ETD) between the quadrupole and mobility regions prior to modification. We show excellent fragmentation efficiency for denatured peptides and proteins without the need to trap ions in the gas phase. Additionally, we demonstrate native top-down backbone fragmentation of noncovalent protein complexes, leading to comparable sequence coverage to what was achieved using the instrument's existing ETD capabilities. Limited collisional ion activation of the hemoglobin tetramer before ECD was reflected in the observed fragmentation pattern, and complementary ion mobility measurements prior to ECD provided orthogonal evidence of monomer unfolding within this complex. The approach demonstrated here provides a powerful platform for both top-down proteomics and mass spectrometry-based structural biology studies.
Collapse
Affiliation(s)
- Jonathan P Williams
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, United Kingdom
| | - Lindsay J Morrison
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, United Kingdom
| | - Jeffery M Brown
- Waters Corporation, Stamford Avenue, Altrincham Road, Wilmslow SK9 4AX, United Kingdom
| | - Joseph S Beckman
- e-MSion Inc., 2121 NE Jack London Drive, Corvallis, Oregon 97330, United States.,Linus Pauling Institute and the Department of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon 97331, United States
| | - Valery G Voinov
- e-MSion Inc., 2121 NE Jack London Drive, Corvallis, Oregon 97330, United States.,Linus Pauling Institute and the Department of Biochemistry and Biophysics, Oregon State University, Corvallis, Oregon 97331, United States
| | - Frederik Lermyte
- School of Engineering, University of Warwick, Coventry CV4 7AL, United Kingdom.,Department of Chemistry, University of Warwick, Coventry CV4 7AL, United Kingdom
| |
Collapse
|
46
|
Fornelli L, Srzentić K, Toby TK, Doubleday PF, Huguet R, Mullen C, Melani RD, Dos Santos Seckler H, DeHart CJ, Weisbrod CR, Durbin KR, Greer JB, Early BP, Fellers RT, Zabrouskov V, Thomas PM, Compton PD, Kelleher NL. Thorough Performance Evaluation of 213 nm Ultraviolet Photodissociation for Top-down Proteomics. Mol Cell Proteomics 2020; 19:405-420. [PMID: 31888965 PMCID: PMC7000117 DOI: 10.1074/mcp.tir119.001638] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [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: 06/23/2019] [Revised: 11/29/2019] [Indexed: 11/06/2022] Open
Abstract
Top-down proteomics studies intact proteoform mixtures and offers important advantages over more common bottom-up proteomics technologies, as it avoids the protein inference problem. However, achieving complete molecular characterization of investigated proteoforms using existing technologies remains a fundamental challenge for top-down proteomics. Here, we benchmark the performance of ultraviolet photodissociation (UVPD) using 213 nm photons generated by a solid-state laser applied to the study of intact proteoforms from three organisms. Notably, the described UVPD setup applies multiple laser pulses to induce ion dissociation, and this feature can be used to optimize the fragmentation outcome based on the molecular weight of the analyzed biomolecule. When applied to complex proteoform mixtures in high-throughput top-down proteomics, 213 nm UVPD demonstrated a high degree of complementarity with the most employed fragmentation method in proteomics studies, higher-energy collisional dissociation (HCD). UVPD at 213 nm offered higher average proteoform sequence coverage and degree of proteoform characterization (including localization of post-translational modifications) than HCD. However, previous studies have shown limitations in applying database search strategies developed for HCD fragmentation to UVPD spectra which contains up to nine fragment ion types. We therefore performed an analysis of the different UVPD product ion type frequencies. From these data, we developed an ad hoc fragment matching strategy and determined the influence of each possible ion type on search outcomes. By paring down the number of ion types considered in high-throughput UVPD searches from all types down to the four most abundant, we were ultimately able to achieve deeper proteome characterization with UVPD. Lastly, our detailed product ion analysis also revealed UVPD cleavage propensities and determined the presence of a product ion produced specifically by 213 nm photons. All together, these observations could be used to better elucidate UVPD dissociation mechanisms and improve the utility of the technique for proteomic applications.
Collapse
Affiliation(s)
- Luca Fornelli
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Kristina Srzentić
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Timothy K Toby
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Peter F Doubleday
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Romain Huguet
- Thermo Fisher Scientific, San Jose, California 95134
| | | | - Rafael D Melani
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Henrique Dos Santos Seckler
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Caroline J DeHart
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | | | - Kenneth R Durbin
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208; Proteinaceous Inc., Evanston, Illinois 60201
| | - Joseph B Greer
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Bryan P Early
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Ryan T Fellers
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | | | - Paul M Thomas
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Philip D Compton
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208
| | - Neil L Kelleher
- Departments of Chemistry and Molecular Biosciences, and the Proteomics Center of Excellence, Northwestern University, Evanston, Illinois 60208.
| |
Collapse
|
47
|
Affiliation(s)
| | | | - Jennifer S. Brodbelt
- Department of Chemistry, University of Texas at Austin, Austin, Texas 78712, United States
| |
Collapse
|