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Tissue-Characteristic Expression of Mouse Proteome. Mol Cell Proteomics 2022; 21:100408. [PMID: 36058520 PMCID: PMC9562433 DOI: 10.1016/j.mcpro.2022.100408] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 07/23/2022] [Accepted: 08/24/2022] [Indexed: 01/18/2023] Open
Abstract
The mouse is a valuable model organism for biomedical research. Here, we established a comprehensive spectral library and the data-independent acquisition-based quantitative proteome maps for 41 mouse organs, including some rarely reported organs such as the cornea, retina, and nine paired organs. The mouse spectral library contained 178,304 peptides from 12,320 proteins, including 1678 proteins not reported in previous mouse spectral libraries. Our data suggested that organs from the nervous system and immune system expressed the most distinct proteome compared with other organs. We also found characteristic protein expression of immune-privileged organs, which may help understanding possible immune rejection after organ transplantation. Each tissue type expressed characteristic high-abundance proteins related to its physiological functions. We also uncovered some tissue-specific proteins which have not been reported previously. The testis expressed highest number of tissue-specific proteins. By comparison of nine paired organs including kidneys, testes, and adrenal glands, we found left organs exhibited higher levels of antioxidant enzymes. We also observed expression asymmetry for proteins related to the apoptotic process, tumor suppression, and organ functions between the left and right sides. This study provides a comprehensive spectral library and a quantitative proteome resource for mouse studies.
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2
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Fabre B, Choteau SA, Duboé C, Pichereaux C, Montigny A, Korona D, Deery MJ, Camus M, Brun C, Burlet-Schiltz O, Russell S, Combier JP, Lilley KS, Plaza S. In Depth Exploration of the Alternative Proteome of Drosophila melanogaster. Front Cell Dev Biol 2022; 10:901351. [PMID: 35721519 PMCID: PMC9204603 DOI: 10.3389/fcell.2022.901351] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 04/25/2022] [Indexed: 12/13/2022] Open
Abstract
Recent studies have shown that hundreds of small proteins were occulted when protein-coding genes were annotated. These proteins, called alternative proteins, have failed to be annotated notably due to the short length of their open reading frame (less than 100 codons) or the enforced rule establishing that messenger RNAs (mRNAs) are monocistronic. Several alternative proteins were shown to be biologically active molecules and seem to be involved in a wide range of biological functions. However, genome-wide exploration of the alternative proteome is still limited to a few species. In the present article, we describe a deep peptidomics workflow which enabled the identification of 401 alternative proteins in Drosophila melanogaster. Subcellular localization, protein domains, and short linear motifs were predicted for 235 of the alternative proteins identified and point toward specific functions of these small proteins. Several alternative proteins had approximated abundances higher than their canonical counterparts, suggesting that these alternative proteins are actually the main products of their corresponding genes. Finally, we observed 14 alternative proteins with developmentally regulated expression patterns and 10 induced upon the heat-shock treatment of embryos, demonstrating stage or stress-specific production of alternative proteins.
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Affiliation(s)
- Bertrand Fabre
- Laboratoire de Recherche en Sciences Végétales, UMR5546, Université de Toulouse, UPS, INP, CNRS, Auzeville-Tolosane, France,Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom,*Correspondence: Bertrand Fabre, ; Serge Plaza,
| | - Sebastien A. Choteau
- Aix-Marseille Université, INSERM, TAGC, Turing Centre for Living Systems, Marseille, France
| | - Carine Duboé
- Laboratoire de Recherche en Sciences Végétales, UMR5546, Université de Toulouse, UPS, INP, CNRS, Auzeville-Tolosane, France
| | - Carole Pichereaux
- Fédération de Recherche (FR3450), Agrobiosciences, Interactions et Biodiversité (AIB), CNRS, Toulouse, France,Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France,Infrastructure Nationale de Protéomique, ProFI, FR 2048, Toulouse, France
| | - Audrey Montigny
- Laboratoire de Recherche en Sciences Végétales, UMR5546, Université de Toulouse, UPS, INP, CNRS, Auzeville-Tolosane, France
| | - Dagmara Korona
- Cambridge Systems Biology Centre and Department of Genetics, University of Cambridge, Cambridge, United Kingdom
| | - Michael J. Deery
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
| | - Mylène Camus
- Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France,Infrastructure Nationale de Protéomique, ProFI, FR 2048, Toulouse, France
| | - Christine Brun
- Aix-Marseille Université, INSERM, TAGC, Turing Centre for Living Systems, Marseille, France,CNRS, Marseille, France
| | - Odile Burlet-Schiltz
- Institut de Pharmacologie et de Biologie Structurale (IPBS), Université de Toulouse, CNRS, UPS, Toulouse, France,Infrastructure Nationale de Protéomique, ProFI, FR 2048, Toulouse, France
| | - Steven Russell
- Cambridge Systems Biology Centre and Department of Genetics, University of Cambridge, Cambridge, United Kingdom
| | - Jean-Philippe Combier
- Laboratoire de Recherche en Sciences Végétales, UMR5546, Université de Toulouse, UPS, INP, CNRS, Auzeville-Tolosane, France
| | - Kathryn S. Lilley
- Cambridge Centre for Proteomics, Cambridge Systems Biology Centre and Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
| | - Serge Plaza
- Laboratoire de Recherche en Sciences Végétales, UMR5546, Université de Toulouse, UPS, INP, CNRS, Auzeville-Tolosane, France,*Correspondence: Bertrand Fabre, ; Serge Plaza,
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3
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Leong AZX, Lee PY, Mohtar MA, Syafruddin SE, Pung YF, Low TY. Short open reading frames (sORFs) and microproteins: an update on their identification and validation measures. J Biomed Sci 2022; 29:19. [PMID: 35300685 PMCID: PMC8928697 DOI: 10.1186/s12929-022-00802-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 03/09/2022] [Indexed: 12/17/2022] Open
Abstract
A short open reading frame (sORFs) constitutes ≤ 300 bases, encoding a microprotein or sORF-encoded protein (SEP) which comprises ≤ 100 amino acids. Traditionally dismissed by genome annotation pipelines as meaningless noise, sORFs were found to possess coding potential with ribosome profiling (RIBO-Seq), which unveiled sORF-based transcripts at various genome locations. Nonetheless, the existence of corresponding microproteins that are stable and functional was little substantiated by experimental evidence initially. With recent advancements in multi-omics, the identification, validation, and functional characterisation of sORFs and microproteins have become feasible. In this review, we discuss the history and development of an emerging research field of sORFs and microproteins. In particular, we focus on an array of bioinformatics and OMICS approaches used for predicting, sequencing, validating, and characterizing these recently discovered entities. These strategies include RIBO-Seq which detects sORF transcripts via ribosome footprints, and mass spectrometry (MS)-based proteomics for sequencing the resultant microproteins. Subsequently, our discussion extends to the functional characterisation of microproteins by incorporating CRISPR/Cas9 screen and protein–protein interaction (PPI) studies. Our review discusses not only detection methodologies, but we also highlight on the challenges and potential solutions in identifying and validating sORFs and their microproteins. The novelty of this review lies within its validation for the functional role of microproteins, which could contribute towards the future landscape of microproteomics.
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Affiliation(s)
- Alyssa Zi-Xin Leong
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia
| | - Pey Yee Lee
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia
| | - M Aiman Mohtar
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia
| | - Saiful Effendi Syafruddin
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia
| | - Yuh-Fen Pung
- Division of Biomedical Science, School of Pharmacy, University of Nottingham Malaysia, Semenyih, 43500, Selangor, Malaysia
| | - Teck Yew Low
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia.
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4
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Siddiqui G, De Paoli A, MacRaild CA, Sexton AE, Boulet C, Shah AD, Batty MB, Schittenhelm RB, Carvalho TG, Creek DJ. A new mass spectral library for high-coverage and reproducible analysis of the Plasmodium falciparum-infected red blood cell proteome. Gigascience 2022; 11:6543637. [PMID: 35254426 PMCID: PMC8900498 DOI: 10.1093/gigascience/giac008] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 11/24/2021] [Accepted: 01/28/2022] [Indexed: 12/03/2022] Open
Abstract
Background Plasmodium falciparum causes the majority of malaria mortality worldwide, and the disease occurs during the asexual red blood cell (RBC) stage of infection. In the absence of an effective and available vaccine, and with increasing drug resistance, asexual RBC stage parasites are an important research focus. In recent years, mass spectrometry–based proteomics using data-dependent acquisition has been extensively used to understand the biochemical processes within the parasite. However, data-dependent acquisition is problematic for the detection of low-abundance proteins and proteome coverage and has poor run-to-run reproducibility. Results Here, we present a comprehensive P. falciparum–infected RBC (iRBC) spectral library to measure the abundance of 44,449 peptides from 3,113 P. falciparum and 1,617 RBC proteins using a data-independent acquisition mass spectrometric approach. The spectral library includes proteins expressed in the 3 morphologically distinct RBC stages (ring, trophozoite, schizont), the RBC compartment of trophozoite-iRBCs, and the cytosolic fraction from uninfected RBCs. This spectral library contains 87% of all P. falciparum proteins that have previously been reported with protein-level evidence in blood stages, as well as 692 previously unidentified proteins. The P. falciparum spectral library was successfully applied to generate semi-quantitative proteomics datasets that characterize the 3 distinct asexual parasite stages in RBCs, and compared artemisinin-resistant (Cam3.IIR539T) and artemisinin-sensitive (Cam3.IIrev) parasites. Conclusion A reproducible, high-coverage proteomics spectral library and analysis method has been generated for investigating sets of proteins expressed in the iRBC stage of P. falciparum malaria. This will provide a foundation for an improved understanding of parasite biology, pathogenesis, drug mechanisms, and vaccine candidate discovery for malaria.
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Affiliation(s)
- Ghizal Siddiqui
- Drug Delivery Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Amanda De Paoli
- Drug Delivery Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Christopher A MacRaild
- Drug Delivery Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Anna E Sexton
- Drug Delivery Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Coralie Boulet
- Department of Physiology, Anatomy and Microbiology, La Trobe University, Bundoora, VIC 3086, Australia
| | - Anup D Shah
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia.,Monash Bioinformatics Platform, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Mitchell B Batty
- Drug Delivery Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
| | - Ralf B Schittenhelm
- Department of Biochemistry and Molecular Biology, Biomedicine Discovery Institute, Monash University, Clayton, VIC 3800, Australia
| | - Teresa G Carvalho
- Department of Physiology, Anatomy and Microbiology, La Trobe University, Bundoora, VIC 3086, Australia
| | - Darren J Creek
- Drug Delivery Disposition and Dynamics, Monash Institute of Pharmaceutical Sciences, Monash University, Parkville, VIC 3052, Australia
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Kute PM, Soukarieh O, Tjeldnes H, Trégouët DA, Valen E. Small Open Reading Frames, How to Find Them and Determine Their Function. Front Genet 2022; 12:796060. [PMID: 35154250 PMCID: PMC8831751 DOI: 10.3389/fgene.2021.796060] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Accepted: 12/30/2021] [Indexed: 12/12/2022] Open
Abstract
Advances in genomics and molecular biology have revealed an abundance of small open reading frames (sORFs) across all types of transcripts. While these sORFs are often assumed to be non-functional, many have been implicated in physiological functions and a significant number of sORFs have been described in human diseases. Thus, sORFs may represent a hidden repository of functional elements that could serve as therapeutic targets. Unlike protein-coding genes, it is not necessarily the encoded peptide of an sORF that enacts its function, sometimes simply the act of translating an sORF might have a regulatory role. Indeed, the most studied sORFs are located in the 5′UTRs of coding transcripts and can have a regulatory impact on the translation of the downstream protein-coding sequence. However, sORFs have also been abundantly identified in non-coding RNAs including lncRNAs, circular RNAs and ribosomal RNAs suggesting that sORFs may be diverse in function. Of the many different experimental methods used to discover sORFs, the most commonly used are ribosome profiling and mass spectrometry. These can confirm interactions between transcripts and ribosomes and the production of a peptide, respectively. Extensions to ribosome profiling, which also capture scanning ribosomes, have further made it possible to see how sORFs impact the translation initiation of mRNAs. While high-throughput techniques have made the identification of sORFs less difficult, defining their function, if any, is typically more challenging. Together, the abundance and potential function of many of these sORFs argues for the necessity of including sORFs in gene annotations and systematically characterizing these to understand their potential functional roles. In this review, we will focus on the high-throughput methods used in the detection and characterization of sORFs and discuss techniques for validation and functional characterization.
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Affiliation(s)
- Preeti Madhav Kute
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
- Sars International Centre for Marine Molecular Biology, University of Bergen, Bergen, Norway
| | - Omar Soukarieh
- Department of Molecular Epidemiology Of Vascular and Brain Disorders, INSERM, BPH, U1219, University of Bordeaux, Bordeaux, France
| | - Håkon Tjeldnes
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
| | - David-Alexandre Trégouët
- Department of Molecular Epidemiology Of Vascular and Brain Disorders, INSERM, BPH, U1219, University of Bordeaux, Bordeaux, France
| | - Eivind Valen
- Computational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway
- Sars International Centre for Marine Molecular Biology, University of Bergen, Bergen, Norway
- *Correspondence: Eivind Valen,
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6
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Modi T, Regufe da Mota S, Gervais D. l-Asparaginase and HCP quantification by SWATH LC-MS/MS for new and improved purification step in Erwinia chrysanthemil-asparaginase manufacture. J Pharm Biomed Anal 2021; 209:114537. [PMID: 34929569 DOI: 10.1016/j.jpba.2021.114537] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Revised: 12/10/2021] [Accepted: 12/10/2021] [Indexed: 11/16/2022]
Abstract
Erwinase® or Erwinaze® are the proprietary names for the L-asparaginase enzyme derived from Erwinia chrysanthemi.L-asparaginase is an integral part of the treatment of Acute Lymphoblastic Leukaemia (ALL) in children and adolescents. E. chrysanthemiL-asparaginase was first developed in the early 1970s at Porton Down and is currently manufactured by Porton Biopharma Ltd. One of the early purification steps during E. chrysanthemiL-asparaginase manufacture, involves use of batch cation exchange carboxymethyl resin, and alternatives to this older technology are currently under investigation using mass spectrometry to understand the impact of resin changes on the impurity profile. In this study, a novel SWATH library was developed for E. chrysanthemi proteome and used to evaluate this potential process change on product yield and host cell protein (HCP) profile and clearance. An ELISA assay is currently used as a quality control release test for quantifying HCPs at the Drug Substance (DS) stage, but these early extract samples are too crude for interference-free analysis by ELISA. Given that ELISA assay could not be used in the assessment of new resin options, SWATH LC-MS/MS analysis proved to be pivotal in selecting a resin for further scale-up and implementation. The data quantified that L-asparaginase from the new process step was 2.28-fold higher in concentration than in legacy-process samples. The new step, using a modern ion exchanger, was at least equivalent and in some cases outperformed the legacy resin step in terms of HCP clearance for 78.2% of total HCPs (528 of 675 total proteins).
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Affiliation(s)
- Tapasvi Modi
- Porton Biopharma Limited, Porton Down, Salisbury, Wiltshire SP4 0JG, UK
| | | | - David Gervais
- Porton Biopharma Limited, Porton Down, Salisbury, Wiltshire SP4 0JG, UK
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7
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Fabre B, Combier JP, Plaza S. Recent advances in mass spectrometry-based peptidomics workflows to identify short-open-reading-frame-encoded peptides and explore their functions. Curr Opin Chem Biol 2021; 60:122-130. [PMID: 33401134 DOI: 10.1016/j.cbpa.2020.12.002] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 11/26/2020] [Accepted: 12/03/2020] [Indexed: 12/12/2022]
Abstract
Short open reading frame (sORF)-encoded polypeptides (SEPs) have recently emerged as key regulators of major cellular processes. Computational methods for the annotation of sORFs combined with transcriptomics and ribosome profiling approaches predicted the existence of tens of thousands of SEPs across the kingdom of life. Although, we still lack unambiguous evidence for most of them. The method of choice to validate the expression of SEPs is mass spectrometry (MS)-based peptidomics. Peptides are less abundant than proteins, which tends to hinder their detection. Therefore, optimization and enrichment methods are necessary to validate the existence of SEPs. In this article, we discuss the challenges for the detection of SEPs by MS and recent developments of biochemical approaches applied to the study of these peptides. We detail the advances made in the different key steps of a typical peptidomics workflow and highlight possible alternatives that have not been explored yet.
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Affiliation(s)
- Bertrand Fabre
- Laboratoire de Recherche en Sciences Végétales, UMR5546, Université de Toulouse, UPS, CNRS, 31320, Auzeville-Tolosane, France.
| | - Jean-Philippe Combier
- Laboratoire de Recherche en Sciences Végétales, UMR5546, Université de Toulouse, UPS, CNRS, 31320, Auzeville-Tolosane, France
| | - Serge Plaza
- Laboratoire de Recherche en Sciences Végétales, UMR5546, Université de Toulouse, UPS, CNRS, 31320, Auzeville-Tolosane, France
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8
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Krasny L, Huang PH. Data-independent acquisition mass spectrometry (DIA-MS) for proteomic applications in oncology. Mol Omics 2020; 17:29-42. [PMID: 33034323 DOI: 10.1039/d0mo00072h] [Citation(s) in RCA: 90] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Data-independent acquisition mass spectrometry (DIA-MS) is a next generation proteomic methodology that generates permanent digital proteome maps offering highly reproducible retrospective analysis of cellular and tissue specimens. The adoption of this technology has ushered a new wave of oncology studies across a wide range of applications including its use in molecular classification, oncogenic pathway analysis, drug and biomarker discovery and unravelling mechanisms of therapy response and resistance. In this review, we provide an overview of the experimental workflows commonly used in DIA-MS, including its current strengths and limitations versus conventional data-dependent acquisition mass spectrometry (DDA-MS). We further summarise a number of key studies to illustrate the power of this technology when applied to different facets of oncology. Finally we offer a perspective of the latest innovations in DIA-MS technology and machine learning-based algorithms necessary for driving the development of high-throughput, in-depth and reproducible proteomic assays that are compatible with clinical diagnostic workflows, which will ultimately enable the delivery of precision cancer medicine to achieve optimal patient outcomes.
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Affiliation(s)
- Lukas Krasny
- Division of Molecular Pathology, The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK.
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9
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Krasny L, Bland P, Burns J, Lima NC, Harrison PT, Pacini L, Elms ML, Ning J, Martinez VG, Yu YR, Acton SE, Ho PC, Calvo F, Swain A, Howard BA, Natrajan RC, Huang PH. A mouse SWATH-mass spectrometry reference spectral library enables deconvolution of species-specific proteomic alterations in human tumour xenografts. Dis Model Mech 2020; 13:dmm044586. [PMID: 32493768 PMCID: PMC7375474 DOI: 10.1242/dmm.044586] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2020] [Accepted: 05/20/2020] [Indexed: 12/11/2022] Open
Abstract
SWATH-mass spectrometry (MS) enables accurate and reproducible proteomic profiling in multiple model organisms including the mouse. Here, we present a comprehensive mouse reference spectral library (MouseRefSWATH) that permits quantification of up to 10,597 proteins (62.2% of the mouse proteome) by SWATH-MS. We exploit MouseRefSWATH to develop an analytical pipeline for species-specific deconvolution of proteomic alterations in human tumour xenografts (XenoSWATH). This method overcomes the challenge of high sequence similarity between mouse and human proteins, facilitating the study of host microenvironment-tumour interactions from 'bulk tumour' measurements. We apply the XenoSWATH pipeline to characterize an intraductal xenograft model of breast ductal carcinoma in situ and uncover complex regulation consistent with stromal reprogramming, where the modulation of cell migration pathways is not restricted to tumour cells but also operates in the mouse stroma upon progression to invasive disease. MouseRefSWATH and XenoSWATH open new opportunities for in-depth and reproducible proteomic assessment to address wide-ranging biological questions involving this important model organism.
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MESH Headings
- Animals
- Breast Neoplasms/metabolism
- Breast Neoplasms/pathology
- Carcinoma, Intraductal, Noninfiltrating/metabolism
- Carcinoma, Intraductal, Noninfiltrating/pathology
- Cell Communication
- Cell Line, Tumor
- Chromatography, Liquid
- Databases, Protein
- Female
- Heterografts
- Humans
- Male
- Mice
- Mice, Inbred C57BL
- Mice, Nude
- Mice, SCID
- NIH 3T3 Cells
- Neoplasm Proteins/metabolism
- Neoplasm Transplantation
- Proteome
- Proteomics
- Species Specificity
- Stromal Cells/metabolism
- Stromal Cells/pathology
- Tandem Mass Spectrometry
- Tumor Microenvironment
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Affiliation(s)
- Lukas Krasny
- Division of Molecular Pathology, The Institute of Cancer Research, London SW3 6JB, UK
| | - Philip Bland
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London SW3 6JB, UK
| | - Jessica Burns
- Division of Molecular Pathology, The Institute of Cancer Research, London SW3 6JB, UK
| | - Nadia Carvalho Lima
- Division of Molecular Pathology, The Institute of Cancer Research, London SW3 6JB, UK
| | - Peter T Harrison
- Division of Molecular Pathology, The Institute of Cancer Research, London SW3 6JB, UK
| | - Laura Pacini
- Division of Molecular Pathology, The Institute of Cancer Research, London SW3 6JB, UK
| | - Mark L Elms
- Division of Molecular Pathology, The Institute of Cancer Research, London SW3 6JB, UK
| | - Jian Ning
- Tumour Profiling Unit, The Institute of Cancer Research, London SW3 6JB, UK
| | - Victor Garcia Martinez
- Stromal Immunology Group, MRC Laboratory for Molecular Cell Biology, University College London WC1E 6BT, London, UK
| | - Yi-Ru Yu
- Department of Oncology, University of Lausanne, Lausanne CH-1066, Switzerland
- Ludwig Institute for Cancer Research, Lausanne CH-1066, Switzerland
| | - Sophie E Acton
- Stromal Immunology Group, MRC Laboratory for Molecular Cell Biology, University College London WC1E 6BT, London, UK
| | - Ping-Chih Ho
- Department of Oncology, University of Lausanne, Lausanne CH-1066, Switzerland
- Ludwig Institute for Cancer Research, Lausanne CH-1066, Switzerland
| | - Fernando Calvo
- The Tumour Microenvironment Team, Institute of Biomedicine and Biotechnology of Cantabria, Santander 39011, Spain
| | - Amanda Swain
- Tumour Profiling Unit, The Institute of Cancer Research, London SW3 6JB, UK
| | - Beatrice A Howard
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London SW3 6JB, UK
| | - Rachael C Natrajan
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London SW3 6JB, UK
| | - Paul H Huang
- Division of Molecular Pathology, The Institute of Cancer Research, London SW3 6JB, UK
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10
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Zhong CQ, Wu J, Qiu X, Chen X, Xie C, Han J. Generation of a murine SWATH-MS spectral library to quantify more than 11,000 proteins. Sci Data 2020; 7:104. [PMID: 32218446 PMCID: PMC7099061 DOI: 10.1038/s41597-020-0449-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Accepted: 03/06/2020] [Indexed: 12/16/2022] Open
Abstract
Targeted SWATH-MS data analysis is critically dependent on the spectral library. Comprehensive spectral libraries of human or several other organisms have been published, but the extensive spectral library for mouse, a widely used model organism is not available. Here, we present a large murine spectral library covering more than 11,000 proteins and 240,000 proteotypic peptides, which included proteins derived from 9 murine tissue samples and one murine L929 cell line. This resource supports the quantification of 67% of all murine proteins annotated by UniProtKB/Swiss-Prot. Furthermore, we applied the spectral library to SWATH-MS data from murine tissue samples. Data are available via SWATHAtlas (PASS01441). Measurement(s) | Mouse Protein • mass spectrum • spectral library | Technology Type(s) | mass spectrometry • combined ms-ms + spectral library search | Sample Characteristic - Organism | Mus musculus |
Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.11968230
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Affiliation(s)
- Chuan-Qi Zhong
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen, China.
| | - Jianfeng Wu
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen, China
| | - Xingfeng Qiu
- Department of Gastrointestinal Surgery, Zhongshan Hospital of Xiamen University, Xiamen, China
| | - Xi Chen
- Medical Research Institute, Wuhan University, Wuhan, China.,SpecAlly Life Technology Co., Ltd, Wuhan, China
| | - Changchuan Xie
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen, China
| | - Jiahuai Han
- State Key Laboratory of Cellular Stress Biology, Innovation Center for Cellular Signaling Network, School of Life Sciences, Xiamen University, Xiamen, China.
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11
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Azimi A, Yang P, Ali M, Howard V, Mann GJ, Kaufman KL, Fernandez-Penas P. Data Independent Acquisition Proteomic Analysis Can Discriminate between Actinic Keratosis, Bowen’s Disease, and Cutaneous Squamous Cell Carcinoma. J Invest Dermatol 2020; 140:212-222.e11. [DOI: 10.1016/j.jid.2019.06.128] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 05/28/2019] [Accepted: 06/11/2019] [Indexed: 12/19/2022]
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Palmowski P, Watson R, Europe-Finner GN, Karolczak-Bayatti M, Porter A, Treumann A, Taggart MJ. The Generation of a Comprehensive Spectral Library for the Analysis of the Guinea Pig Proteome by SWATH-MS. Proteomics 2019; 19:e1900156. [PMID: 31301205 PMCID: PMC6771470 DOI: 10.1002/pmic.201900156] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2019] [Revised: 06/21/2019] [Indexed: 12/18/2022]
Abstract
Advances in liquid chromatography‐mass spectrometry have facilitated the incorporation of proteomic studies to many biology experimental workflows. Data‐independent acquisition platforms, such as sequential window acquisition of all theoretical mass spectra (SWATH‐MS), offer several advantages for label‐free quantitative assessment of complex proteomes over data‐dependent acquisition (DDA) approaches. However, SWATH data interpretation requires spectral libraries as a detailed reference resource. The guinea pig (Cavia porcellus) is an excellent experimental model for translation to many aspects of human physiology and disease, yet there is limited experimental information regarding its proteome. To overcome this knowledge gap, a comprehensive spectral library of the guinea pig proteome is generated. Homogenates and tryptic digests are prepared from 16 tissues and subjected to >200 DDA runs. Analysis of >250 000 peptide‐spectrum matches resulted in a library of 73 594 peptides from 7666 proteins. Library validation is provided by i) analyzing externally derived SWATH files (https://doi.org/10.1016/j.jprot.2018.03.023) and comparing peptide intensity quantifications; ii) merging of externally derived data to the base library. This furnishes the research community with a comprehensive proteomic resource that will facilitate future molecular‐phenotypic studies using (re‐engaging) the guinea pig as an experimental model of relevance to human biology. The spectral library and raw data are freely accessible in the MassIVE repository (MSV000083199).
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Affiliation(s)
- Pawel Palmowski
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 4EP, Tyne and Wear, UK
| | - Rachael Watson
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 4EP, Tyne and Wear, UK
| | - G Nicholas Europe-Finner
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 4EP, Tyne and Wear, UK
| | | | - Andrew Porter
- Newcastle University Protein and Proteomic Analysis, Newcastle University, Newcastle upon Tyne, NE2 4HH, Tyne and Wear, UK
| | - Achim Treumann
- Newcastle University Protein and Proteomic Analysis, Newcastle University, Newcastle upon Tyne, NE2 4HH, Tyne and Wear, UK
| | - Michael J Taggart
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 4EP, Tyne and Wear, UK
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Prosit: proteome-wide prediction of peptide tandem mass spectra by deep learning. Nat Methods 2019; 16:509-518. [DOI: 10.1038/s41592-019-0426-7] [Citation(s) in RCA: 340] [Impact Index Per Article: 68.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Accepted: 04/18/2019] [Indexed: 11/08/2022]
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14
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Fabre B, Korona D, Lees JG, Lazar I, Livneh I, Brunet M, Orengo CA, Russell S, Lilley KS. Comparison of Drosophila melanogaster Embryo and Adult Proteome by SWATH-MS Reveals Differential Regulation of Protein Synthesis, Degradation Machinery, and Metabolism Modules. J Proteome Res 2019; 18:2525-2534. [DOI: 10.1021/acs.jproteome.9b00076] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Bertrand Fabre
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge CB2 1QR, U.K
- Department of Biochemistry, University of Cambridge, University of Cambridge, Cambridge CB2 1GA, U.K
- Cambridge Systems Biology Centre, University of Cambridge, Cambridge CB2 1GA, U.K
- Technion Integrated Cancer Center (TICC), The Rappaport Faculty of Medicine and Research Institute, Haifa, Israel
| | - Dagmara Korona
- Department of Genetics, University of Cambridge, University of Cambridge, Cambridge CB2 3EH, U.K
- Cambridge Systems Biology Centre, University of Cambridge, Cambridge CB2 1GA, U.K
| | - Jonathan G. Lees
- Institute of Structural and Molecular Biology, University College London, London WC1E 7HX, United Kingdom
| | - Ikrame Lazar
- Technion Integrated Cancer Center (TICC), The Rappaport Faculty of Medicine and Research Institute, Haifa, Israel
| | - Ido Livneh
- Technion Integrated Cancer Center (TICC), The Rappaport Faculty of Medicine and Research Institute, Haifa, Israel
| | - Manon Brunet
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge CB2 1QR, U.K
- Department of Biochemistry, University of Cambridge, University of Cambridge, Cambridge CB2 1GA, U.K
- Cambridge Systems Biology Centre, University of Cambridge, Cambridge CB2 1GA, U.K
| | - Christine A. Orengo
- Institute of Structural and Molecular Biology, University College London, London WC1E 7HX, United Kingdom
| | - Steven Russell
- Department of Genetics, University of Cambridge, University of Cambridge, Cambridge CB2 3EH, U.K
- Cambridge Systems Biology Centre, University of Cambridge, Cambridge CB2 1GA, U.K
| | - Kathryn S. Lilley
- Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge CB2 1QR, U.K
- Department of Biochemistry, University of Cambridge, University of Cambridge, Cambridge CB2 1GA, U.K
- Cambridge Systems Biology Centre, University of Cambridge, Cambridge CB2 1GA, U.K
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Generation of a zebrafish SWATH-MS spectral library to quantify 10,000 proteins. Sci Data 2019; 6:190011. [PMID: 30747917 PMCID: PMC6371892 DOI: 10.1038/sdata.2019.11] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 12/17/2018] [Indexed: 12/12/2022] Open
Abstract
Sequential window acquisition of all theoretical mass spectra (SWATH-MS) requires a spectral library to extract quantitative measurements from the mass spectrometry data acquired in data-independent acquisition mode (DIA). Large combined spectral libraries containing SWATH assays have been generated for humans and several other organisms, but so far no publicly available library exists for measuring the proteome of zebrafish, a rapidly emerging model system in biomedical research. Here, we present a large zebrafish SWATH spectral library to measure the abundance of 104,185 proteotypic peptides from 10,405 proteins. The library includes proteins expressed in 9 different zebrafish tissues (brain, eye, heart, intestine, liver, muscle, ovary, spleen, and testis) and provides an important new resource to quantify 40% of the protein-coding zebrafish genes. We employ this resource to quantify the proteome across brain, muscle, and liver and characterize divergent expression levels of paralogous proteins in different tissues. Data are available via ProteomeXchange (PXD010876, PXD010869) and SWATHAtlas (PASS01237).
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Di Silvestre D, Bergamaschi A, Bellini E, Mauri P. Large Scale Proteomic Data and Network-Based Systems Biology Approaches to Explore the Plant World. Proteomes 2018; 6:proteomes6020027. [PMID: 29865292 PMCID: PMC6027444 DOI: 10.3390/proteomes6020027] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 05/30/2018] [Accepted: 06/01/2018] [Indexed: 12/26/2022] Open
Abstract
The investigation of plant organisms by means of data-derived systems biology approaches based on network modeling is mainly characterized by genomic data, while the potential of proteomics is largely unexplored. This delay is mainly caused by the paucity of plant genomic/proteomic sequences and annotations which are fundamental to perform mass-spectrometry (MS) data interpretation. However, Next Generation Sequencing (NGS) techniques are contributing to filling this gap and an increasing number of studies are focusing on plant proteome profiling and protein-protein interactions (PPIs) identification. Interesting results were obtained by evaluating the topology of PPI networks in the context of organ-associated biological processes as well as plant-pathogen relationships. These examples foreshadow well the benefits that these approaches may provide to plant research. Thus, in addition to providing an overview of the main-omic technologies recently used on plant organisms, we will focus on studies that rely on concepts of module, hub and shortest path, and how they can contribute to the plant discovery processes. In this scenario, we will also consider gene co-expression networks, and some examples of integration with metabolomic data and genome-wide association studies (GWAS) to select candidate genes will be mentioned.
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Affiliation(s)
- Dario Di Silvestre
- Institute for Biomedical Technologies-National Research Council; F.lli Cervi 93, 20090 Segrate, Milan, Italy.
| | - Andrea Bergamaschi
- Institute for Biomedical Technologies-National Research Council; F.lli Cervi 93, 20090 Segrate, Milan, Italy.
| | - Edoardo Bellini
- Institute for Biomedical Technologies-National Research Council; F.lli Cervi 93, 20090 Segrate, Milan, Italy.
| | - PierLuigi Mauri
- Institute for Biomedical Technologies-National Research Council; F.lli Cervi 93, 20090 Segrate, Milan, Italy.
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Braccia C, Espinal MP, Pini M, De Pietri Tonelli D, Armirotti A. A new SWATH ion library for mouse adult hippocampal neural stem cells. Data Brief 2018; 18:1-8. [PMID: 29896482 PMCID: PMC5995750 DOI: 10.1016/j.dib.2018.02.062] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Revised: 02/07/2018] [Accepted: 02/22/2018] [Indexed: 12/31/2022] Open
Abstract
Over the last years, the SWATH data-independent acquisition protocol (Sequential Window acquisition of All THeoretical mass spectra) has become a cornerstone for the worldwide proteomics community (Collins et al., 2017) [1]. In this approach, a high-resolution quadrupole-ToF mass spectrometer acquires thousands of MS/MS data by selecting not just a single precursor at a time, but by allowing a broad m/z range to be fragmented. This acquisition window is then sequentially moved from the lowest to the highest mass selection range. This technique enables the acquisition of thousands of high-resolution MS/MS spectra per minute in a standard LC–MS run. In the subsequent data analysis phase, the corresponding dataset is searched in a “triple quadrupole-like” mode, thus not considering the whole MS/MS scan spectrum, but by searching for several precursor to fragment transitions that identify and quantify the corresponding peptide. This search is made possible with the use of an ion library, previously acquired in a classical data dependent, full-spectrum mode (Fabre et al., 2017; Wu et al., 2017) [2], [3]. The SWATH protocol, combining the protein identification power of high-resolution MS/MS spectra with the robustness and accuracy in analyte quantification of triple-quad targeted workflows, has become very popular in proteomics research. The major drawback lies in the ion library itself, which is normally demanding and time-consuming to build. Conversely, through the realignment of chromatographic retention times, an ion library of a given proteome can relatively easily be tailored upon “any” proteomics experiment done on the same proteome. We are thus hereby sharing with the worldwide proteomics community our newly acquired ion library of mouse adult hippocampal neural stem cells. Given the growing effort in neuroscience research involving proteomics experiments (Pons-Espinal et al., 2017; Sarnyai and Guest, 2017; Sethi et al., 2015; Bramini et al., 2016) [4,[5], [6], [7], we believe that this data might be of great help for the neuroscience community. All the here reported data (RAW files, results and ion library) can be freely downloaded from the SWATHATLAS (Deutsch et al., 2008) [8] website (http://www.peptideatlas.org/PASS/PASS01110)
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Key Words
- ACN, Acetonitrile
- DDA, Data dependent acquisition
- DTT, Dithiothreitol
- EGF, Epidermal growth factor
- FA, Formic acid
- FGF, Fibroblast growth factor
- IAA, Iodoacetamide
- Neural stem cells
- Neuroscience
- PDL, Poly-D-Lysine
- PSM, Peptide spectrum match
- PTMs, Post translational modifications
- Proteomics
- SWATH
- TEA, Triethylamine
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Affiliation(s)
- Clarissa Braccia
- D3 PharmaChemistry, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Meritxell Pons Espinal
- Neurobiology of miRNA Lab, Neuroscience and Brain Technologies Department, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Mattia Pini
- D3 PharmaChemistry, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Davide De Pietri Tonelli
- Neurobiology of miRNA Lab, Neuroscience and Brain Technologies Department, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
| | - Andrea Armirotti
- D3 PharmaChemistry, Fondazione Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
- Corresponding author.
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