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Dreyer A, Masanta WO, Lugert R, Bohne W, Groß U, Leha A, Dakna M, Lenz C, Zautner AE. Proteome profiling of Campylobacter jejuni 81-176 at 37 °C and 42 °C by label-free mass spectrometry. BMC Microbiol 2024; 24:191. [PMID: 38822261 PMCID: PMC11140963 DOI: 10.1186/s12866-024-03348-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2023] [Accepted: 05/22/2024] [Indexed: 06/02/2024] Open
Abstract
BACKGROUND The main natural reservoir for Campylobacter jejuni is the avian intestinal tract. There, C. jejuni multiplies optimally at 42 °C - the avian body temperature. After infecting humans through oral intake, the bacterium encounters the lower temperature of 37 °C in the human intestinal tract. Proteome profiling by label-free mass spectrometry (DIA-MS) was performed to examine the processes which enable C. jejuni 81-176 to thrive at 37 °C in comparison to 42 °C. In total, four states were compared with each other: incubation for 12 h at 37 °C, for 24 h at 37 °C, for 12 h at 42 °C and 24 h at 42 °C. RESULTS It was shown that the proteomic changes not only according to the different incubation temperature but also to the length of the incubation period were evident when comparing 37 °C and 42 °C as well as 12 h and 24 h of incubation. Altogether, the expression of 957 proteins was quantifiable. 37.1 - 47.3% of the proteins analyzed showed significant differential regulation, with at least a 1.5-fold change in either direction (i.e. log2 FC ≥ 0.585 or log2 FC ≤ -0.585) and an FDR-adjusted p-value of less than 0.05. The significantly differentially expressed proteins could be arranged in 4 different clusters and 16 functional categories. CONCLUSIONS The C. jejuni proteome at 42 °C is better adapted to high replication rates than that at 37 °C, which was in particular indicated by the up-regulation of proteins belonging to the functional categories "replication" (e.g. Obg, ParABS, and NapL), "DNA synthesis and repair factors" (e.g. DNA-polymerase III, DnaB, and DnaE), "lipid and carbohydrate biosynthesis" (e.g. capsular biosynthesis sugar kinase, PrsA, AccA, and AccP) and "vitamin synthesis, metabolism, cofactor biosynthesis" (e.g. MobB, BioA, and ThiE). The relative up-regulation of proteins with chaperone function (GroL, DnaK, ClpB, HslU, GroS, DnaJ, DnaJ-1, and NapD) at 37 °C in comparison to 42 °C after 12 h incubation indicates a temporary lower-temperature proteomic response. Additionally the up-regulation of factors for DNA uptake (ComEA and RecA) at 37 °C compared to 42 °C indicate a higher competence for the acquisition of extraneous DNA at human body temperature.
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Affiliation(s)
- Annika Dreyer
- Institute for Medical Microbiology and Virology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Wycliffe O Masanta
- Institute for Medical Microbiology and Virology, University Medical Center Göttingen, 37075, Göttingen, Germany
- Department of Medical Microbiology, Maseno University Medical School, Private Bag, Maseno, 40105, Kenya
| | - Raimond Lugert
- Institute for Medical Microbiology and Virology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Wolfgang Bohne
- Institute for Medical Microbiology and Virology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Uwe Groß
- Institute for Medical Microbiology and Virology, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Andreas Leha
- Department of Medical Statistics, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Mohammed Dakna
- Department of Medical Statistics, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Christof Lenz
- Bioanalytical Mass Spectrometry Group, Max Planck Institute for Biophysical Chemistry, 37077, Göttingen, Germany
- Institute of Clinical Chemistry, Bioanalytics, University Medical Center Göttingen, 37075, Göttingen, Germany
| | - Andreas E Zautner
- Institute for Medical Microbiology and Virology, University Medical Center Göttingen, 37075, Göttingen, Germany.
- Institute of Medical Microbiology and Hospital Hygiene, Medical Faculty, Otto-von-Guericke-University Magdeburg, Leipziger Straße 44, 39120, Magdeburg, Germany.
- CHaMP, Center for Health and Medical Prevention, Otto-von-Guericke-University Magdeburg, 39120, Magdeburg, Germany.
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2
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The Investigation of Protein Profile and Meat Quality in Bovine Longissimus thoracic Frozen under Different Temperatures by Data-Independent Acquisition (DIA) Strategy. Foods 2022; 11:foods11121791. [PMID: 35741989 PMCID: PMC9222788 DOI: 10.3390/foods11121791] [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: 05/25/2022] [Revised: 06/09/2022] [Accepted: 06/15/2022] [Indexed: 02/04/2023] Open
Abstract
The influence of freezing on the protein profile and quality traits in bovine Longissimus thoracic (LT) muscle was investigated by the data-independent acquisition (DIA) technique. Compared to fresh meat, a total of 262 proteins were identified as differential abundance proteins (DAPs) in four frozen groups (−12 °C, −18 °C, −38 °C, and −80 °C). According to the bioinformatics analysis, most of the DAPs in the significant Go terms and the KEGG pathway were structure proteins and enzymes. Proteome changes in the frozen bovine muscle at −12 °C and −18 °C were more significant than those at −38 °C and −80 °C. The result was consistent with the deterioration trend of the meat quality. The correlation analysis revealed that 17 proteins were correlated closely with the color, shear force, thawing loss, and cooking loss of the frozen meat, which could be used as putative biomarkers for frozen meat quality. MYO18A and ME3 are newly discovered proteins that are associated with frozen beef quality. In addition, CTTN and SERPINB6 were identified in frozen groups, which exhibited a significant inverse correlation with thawing loss (p < 0.01). These findings reveal the quality changes induced by freezing at the protein molecular level and provide new insights into the control of quality deterioration.
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3
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Tay AP, Hamey JJ, Martyn GE, Wilson LOW, Wilkins MR. Identification of Protein Isoforms Using Reference Databases Built from Long and Short Read RNA-Sequencing. J Proteome Res 2022; 21:1628-1639. [PMID: 35612954 DOI: 10.1021/acs.jproteome.1c00968] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Alternative splicing can lead to distinct protein isoforms. These can have different functions in specific cells and tissues or in different developmental stages. In this study, we explored whether transcripts assembled from long read, nanopore-based, direct RNA-sequencing (RNA-seq) could improve the identification of protein isoforms in human K562 cells. By comparing with Illumina-based short read RNA-seq, we showed that a large proportion of Ensembl transcripts (5949/14,326) and genes expressing alternatively spliced transcripts (486/2981) identified with long direct reads were missed by short paired-end reads. By co-analyzing proteomic and transcriptomic data, we also showed that some peptides (826/35,976), proteins (262/3215), and protein isoforms arising from distinct transcript variants (574/1212) identified with isoform-specific peptides via custom long-read-based databases were missed in Illumina-derived databases. Finally, we generated unequivocal peptide evidence for a set of protein isoforms and showed that long read, direct RNA-seq allows the discovery of novel protein isoforms not already in reference databases or custom databases built from short read RNA-seq data. Our analysis highlights the benefits of long read RNA-seq data in the generation of reference databases to increase tandem mass spectrometry (MS/MS) identification of protein isoforms.
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Affiliation(s)
- Aidan P Tay
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia.,Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Sydney, New South Wales 2113, Australia.,Applied Biosciences, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Joshua J Hamey
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Gabriella E Martyn
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Laurence O W Wilson
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, Sydney, New South Wales 2113, Australia.,Applied Biosciences, Macquarie University, Sydney, New South Wales 2109, Australia
| | - Marc R Wilkins
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, Sydney, New South Wales 2052, Australia
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4
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De Marchi T, Pyl PT, Sjöström M, Klasson S, Sartor H, Tran L, Pekar G, Malmström J, Malmström L, Niméus E. Proteogenomic Workflow Reveals Molecular Phenotypes Related to Breast Cancer Mammographic Appearance. J Proteome Res 2021; 20:2983-3001. [PMID: 33855848 PMCID: PMC8155562 DOI: 10.1021/acs.jproteome.1c00243] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Indexed: 12/21/2022]
Abstract
Proteogenomic approaches have enabled the generat̲ion of novel information levels when compared to single omics studies although burdened by extensive experimental efforts. Here, we improved a data-independent acquisition mass spectrometry proteogenomic workflow to reveal distinct molecular features related to mammographic appearances in breast cancer. Our results reveal splicing processes detectable at the protein level and highlight quantitation and pathway complementarity between RNA and protein data. Furthermore, we confirm previously detected enrichments of molecular pathways associated with estrogen receptor-dependent activity and provide novel evidence of epithelial-to-mesenchymal activity in mammography-detected spiculated tumors. Several transcript-protein pairs displayed radically different abundances depending on the overall clinical properties of the tumor. These results demonstrate that there are differentially regulated protein networks in clinically relevant tumor subgroups, which in turn alter both cancer biology and the abundance of biomarker candidates and drug targets.
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Affiliation(s)
- Tommaso De Marchi
- Division
of Surgery, Oncology, and Pathology, Department of Clinical Sciences, Lund University, Solvegatan 19, Lund SE-223 62, Sweden
| | - Paul Theodor Pyl
- Division
of Surgery, Oncology, and Pathology, Department of Clinical Sciences, Lund University, Solvegatan 19, Lund SE-223 62, Sweden
| | - Martin Sjöström
- Division
of Surgery, Oncology, and Pathology, Department of Clinical Sciences, Lund University, Solvegatan 19, Lund SE-223 62, Sweden
| | - Stina Klasson
- Department
Plastic and Reconstructive Surgery, Skåne
University Hospital, Inga Marie Nilssons gata 47, Malmö SE-20502, Sweden
| | - Hanna Sartor
- Division
of Diagnostic Radiology, Department of Translational Medicine, Skåne University Hospital, Entrégatan 7, Lund SE-22185, Sweden
| | - Lena Tran
- Division
of Surgery, Oncology, and Pathology, Department of Clinical Sciences, Lund University, Solvegatan 19, Lund SE-223 62, Sweden
| | - Gyula Pekar
- Division
of Oncology and Pathology, Department of Clinical Sciences, Lund University, Skåne University Hospital, Lund SE-22185, Sweden
| | - Johan Malmström
- Division
of Infection Medicine, Department of Clinical Sciences Lund, Faculty
of Medicine, Lund University, Klinikgatan 32, Lund SE-22184, Sweden
| | - Lars Malmström
- S3IT, University of Zurich, Winterthurerstrasse 190, Zurich CH-8057, Switzerland
- Institute
for Computational Science, University of
Zurich, Winterthurerstrasse 190, Zurich CH-8057, Switzerland
| | - Emma Niméus
- Division
of Surgery, Oncology, and Pathology, Department of Clinical Sciences, Lund University, Solvegatan 19, Lund SE-223 62, Sweden
- Department
of Surgery, Skåne University Hospital, Lund 222 42, Sweden
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5
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Bakochi A, Mohanty T, Pyl PT, Gueto-Tettay CA, Malmström L, Linder A, Malmström J. Cerebrospinal fluid proteome maps detect pathogen-specific host response patterns in meningitis. eLife 2021; 10:64159. [PMID: 33821792 PMCID: PMC8043743 DOI: 10.7554/elife.64159] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2020] [Accepted: 04/04/2021] [Indexed: 12/21/2022] Open
Abstract
Meningitis is a potentially life-threatening infection characterized by the inflammation of the leptomeningeal membranes. Many different viral and bacterial pathogens can cause meningitis, with differences in mortality rates, risk of developing neurological sequelae, and treatment options. Here, we constructed a compendium of digital cerebrospinal fluid (CSF) proteome maps to define pathogen-specific host response patterns in meningitis. The results revealed a drastic and pathogen-type specific influx of tissue-, cell-, and plasma proteins in the CSF, where, in particular, a large increase of neutrophil-derived proteins in the CSF correlated with acute bacterial meningitis. Additionally, both acute bacterial and viral meningitis result in marked reduction of brain-enriched proteins. Generation of a multiprotein LASSO regression model resulted in an 18-protein panel of cell- and tissue-associated proteins capable of classifying acute bacterial meningitis and viral meningitis. The same protein panel also enabled classification of tick-borne encephalitis, a subgroup of viral meningitis, with high sensitivity and specificity. The work provides insights into pathogen-specific host response patterns in CSF from different disease etiologies to support future classification of pathogen type based on host response patterns in meningitis.
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Affiliation(s)
- Anahita Bakochi
- Department of Clinical Sciences, Division of Infection Medicine, Lund University, Lund, Sweden
| | - Tirthankar Mohanty
- Department of Clinical Sciences, Division of Infection Medicine, Lund University, Lund, Sweden
| | - Paul Theodor Pyl
- Division of Surgery, Oncology, and Pathology, Department of Clinical Sciences, Biomedical Center, Lund University, Lund, Sweden
| | | | - Lars Malmström
- Department of Clinical Sciences, Division of Infection Medicine, Lund University, Lund, Sweden
| | - Adam Linder
- Department of Clinical Sciences, Division of Infection Medicine, Lund University, Lund, Sweden
| | - Johan Malmström
- Department of Clinical Sciences, Division of Infection Medicine, Lund University, Lund, Sweden
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6
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Abstract
Data-independent acquisition (DIA) is a powerful method to acquire spectra from all ionized precursors of a sample. Considering the complexity of the highly multiplexed spectral data, sophisticated workflows have been developed to obtain peptides quantification. Here we describe an open-source and easy-to-use workflow to obtain a quantitative matrix from multiple DIA runs. This workflow requires as prior information an "assay library," which contains the MS coordinates of peptides. It consists of OpenSWATH, pyProphet, and DIAlignR software. For the ease of installation and to isolate operating system-related dependency, docker-based containerization is utilized in this workflow.
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Affiliation(s)
- Shubham Gupta
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
| | - Hannes Röst
- Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada.
- Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada.
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7
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Varadarajan AR, Goetze S, Pavlou MP, Grosboillot V, Shen Y, Loessner MJ, Ahrens CH, Wollscheid B. A Proteogenomic Resource Enabling Integrated Analysis of Listeria Genotype-Proteotype-Phenotype Relationships. J Proteome Res 2020; 19:1647-1662. [PMID: 32091902 DOI: 10.1021/acs.jproteome.9b00842] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Listeria monocytogenes is an opportunistic foodborne pathogen responsible for listeriosis, a potentially fatal foodborne disease. Many different Listeria strains and serotypes exist, but a proteogenomic resource that bridges the gap in our molecular understanding of the relationships between the Listeria genotypes and phenotypes via proteotypes is still missing. Here, we devised a next-generation proteogenomics strategy that enables the community to rapidly proteotype Listeria strains and relate this information back to the genotype. Based on sequencing and de novo assembly of the two most commonly used Listeria model strains, EGD-e and ScottA, we established two comprehensive Listeria proteogenomic databases. A genome comparison established core- and strain-specific genes potentially responsible for virulence differences. Next, we established a DIA/SWATH-based proteotyping strategy, including a new and robust sample preparation workflow, that enables the reproducible, sensitive, and relative quantitative measurement of Listeria proteotypes. This reusable and publicly available DIA/SWATH library covers 70% of open reading frames of Listeria and represents the most extensive spectral library for Listeria proteotype analysis to date. We used these two new resources to investigate the Listeria proteotype in states mimicking the upper gastrointestinal passage. Exposure of Listeria to bile salts at 37 °C, which simulates conditions encountered in the duodenum, showed significant proteotype perturbations including an increase of FlaA, the structural protein of flagella. Given that Listeria is known to lose its flagella above 30 °C, this was an unexpected finding. The formation of flagella, which might have implications on infectivity, was validated by parallel reaction monitoring and light and scanning electron microscopy. flaA transcript levels did not change significantly upon exposure to bile salts at 37 °C, suggesting regulation at the post-transcriptional level. Together, these analyses provide a comprehensive proteogenomic resource and toolbox for the Listeria community enabling the analysis of Listeria genotype-proteotype-phenotype relationships.
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Affiliation(s)
- Adithi R Varadarajan
- Department of Health Sciences and Technology (D-HEST), ETH Zürich, 8092 Zürich, Switzerland.,Agroscope, Molecular Diagnostics, Genomics & Bioinformatics, 8820 Wädenswil, Switzerland.,Swiss Institute of Bioinformatics (SIB), 1015 Lausanne, Switzerland
| | - Sandra Goetze
- Department of Health Sciences and Technology (D-HEST), ETH Zürich, 8092 Zürich, Switzerland.,Swiss Institute of Bioinformatics (SIB), 1015 Lausanne, Switzerland.,Institute of Translational Medicine (ITM), ETH Zürich, 8093 Zürich, Switzerland
| | - Maria P Pavlou
- Department of Health Sciences and Technology (D-HEST), ETH Zürich, 8092 Zürich, Switzerland.,Institute of Translational Medicine (ITM), ETH Zürich, 8093 Zürich, Switzerland
| | - Virginie Grosboillot
- Department of Health Sciences and Technology (D-HEST), ETH Zürich, 8092 Zürich, Switzerland.,Institute of Food, Nutrition and Health (IFNH), ETH Zürich, 8092 Zürich, Switzerland
| | - Yang Shen
- Department of Health Sciences and Technology (D-HEST), ETH Zürich, 8092 Zürich, Switzerland.,Institute of Food, Nutrition and Health (IFNH), ETH Zürich, 8092 Zürich, Switzerland
| | - Martin J Loessner
- Department of Health Sciences and Technology (D-HEST), ETH Zürich, 8092 Zürich, Switzerland.,Institute of Food, Nutrition and Health (IFNH), ETH Zürich, 8092 Zürich, Switzerland
| | - Christian H Ahrens
- Agroscope, Molecular Diagnostics, Genomics & Bioinformatics, 8820 Wädenswil, Switzerland.,Swiss Institute of Bioinformatics (SIB), 1015 Lausanne, Switzerland
| | - Bernd Wollscheid
- Department of Health Sciences and Technology (D-HEST), ETH Zürich, 8092 Zürich, Switzerland.,Swiss Institute of Bioinformatics (SIB), 1015 Lausanne, Switzerland.,Institute of Translational Medicine (ITM), ETH Zürich, 8093 Zürich, Switzerland
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8
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Erdmann J, Thöming JG, Pohl S, Pich A, Lenz C, Häussler S. The Core Proteome of Biofilm-Grown Clinical Pseudomonas aeruginosa Isolates. Cells 2019; 8:E1129. [PMID: 31547513 PMCID: PMC6829490 DOI: 10.3390/cells8101129] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Revised: 09/18/2019] [Accepted: 09/19/2019] [Indexed: 12/13/2022] Open
Abstract
Comparative genomics has greatly facilitated the identification of shared as well as unique features among individual cells or tissues, and thus offers the potential to find disease markers. While proteomics is recognized for its potential to generate quantitative maps of protein expression, comparative proteomics in bacteria has been largely restricted to the comparison of single cell lines or mutant strains. In this study, we used a data independent acquisition (DIA) technique, which enables global protein quantification of large sample cohorts, to record the proteome profiles of overall 27 whole genome sequenced and transcriptionally profiled clinical isolates of the opportunistic pathogen Pseudomonas aeruginosa. Analysis of the proteome profiles across the 27 clinical isolates grown under planktonic and biofilm growth conditions led to the identification of a core biofilm-associated protein profile. Furthermore, we found that protein-to-mRNA ratios between different P. aeruginosa strains are well correlated, indicating conserved patterns of post-transcriptional regulation. Uncovering core regulatory pathways, which drive biofilm formation and associated antibiotic tolerance in bacterial pathogens, promise to give clues to interactions between bacterial species and their environment and could provide useful targets for new clinical interventions to combat biofilm-associated infections.
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Affiliation(s)
- Jelena Erdmann
- Institute for Molecular Bacteriology, TWINCORE GmbH, Centre for Experimental and Clinical Infection Research, a joint venture of the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover 30625, Germany.
- Research Core Unit Proteomics and Institute of Toxicology, Hannover Medical School, Hannover 30625, Germany.
| | - Janne G Thöming
- Institute for Molecular Bacteriology, TWINCORE GmbH, Centre for Experimental and Clinical Infection Research, a joint venture of the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover 30625, Germany.
| | - Sarah Pohl
- Institute for Molecular Bacteriology, TWINCORE GmbH, Centre for Experimental and Clinical Infection Research, a joint venture of the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover 30625, Germany.
- Department of Molecular Bacteriology, Helmholtz Center for Infection Research, Braunschweig 38124, Germany.
| | - Andreas Pich
- Research Core Unit Proteomics and Institute of Toxicology, Hannover Medical School, Hannover 30625, Germany.
| | - Christof Lenz
- Institute of Clinical Chemistry, Bioanalytics, University Medical Center Göttingen, Göttingen 37075, Germany.
- Max Planck Institute for Biophysical Chemistry, Bioanalytical Mass Spectrometry, Göttingen 37077, Germany.
| | - Susanne Häussler
- Institute for Molecular Bacteriology, TWINCORE GmbH, Centre for Experimental and Clinical Infection Research, a joint venture of the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover 30625, Germany.
- Department of Molecular Bacteriology, Helmholtz Center for Infection Research, Braunschweig 38124, Germany.
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9
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A quantitative Streptococcus pyogenes-human protein-protein interaction map reveals localization of opsonizing antibodies. Nat Commun 2019; 10:2727. [PMID: 31227708 PMCID: PMC6588558 DOI: 10.1038/s41467-019-10583-5] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2018] [Accepted: 05/17/2019] [Indexed: 12/01/2022] Open
Abstract
A fundamental challenge in medical microbiology is to characterize the dynamic protein–protein interaction networks formed at the host–pathogen interface. Here, we generate a quantitative interaction map between the significant human pathogen, Streptococcus pyogenes, and proteins from human saliva and plasma obtained via complementary affinity-purification and bacterial-surface centered enrichment strategies and quantitative mass spectrometry. Perturbation of the network using immunoglobulin protease cleavage, mixtures of different concentrations of saliva and plasma, and different S. pyogenes serotypes and their isogenic mutants, reveals how changing microenvironments alter the interconnectivity of the interaction map. The importance of host immunoglobulins for the interaction with human complement proteins is demonstrated and potential protective epitopes of importance for phagocytosis of S. pyogenes cells are localized. The interaction map confirms several previously described protein–protein interactions; however, it also reveals a multitude of additional interactions, with possible implications for host–pathogen interactions involving other bacterial species. Characterizing host-pathogen protein interactions can help elucidate the molecular basis of bacterial infections. Here, the authors use an integrative proteomics approach to generate a quantitative map of protein interactions between Streptococcus pyogenes and human saliva and plasma.
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10
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Computational Health Engineering Applied to Model Infectious Diseases and Antimicrobial Resistance Spread. APPLIED SCIENCES-BASEL 2019. [DOI: 10.3390/app9122486] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Infectious diseases are the primary cause of mortality worldwide. The dangers of infectious disease are compounded with antimicrobial resistance, which remains the greatest concern for human health. Although novel approaches are under investigation, the World Health Organization predicts that by 2050, septicaemia caused by antimicrobial resistant bacteria could result in 10 million deaths per year. One of the main challenges in medical microbiology is to develop novel experimental approaches, which enable a better understanding of bacterial infections and antimicrobial resistance. After the introduction of whole genome sequencing, there was a great improvement in bacterial detection and identification, which also enabled the characterization of virulence factors and antimicrobial resistance genes. Today, the use of in silico experiments jointly with computational and machine learning offer an in depth understanding of systems biology, allowing us to use this knowledge for the prevention, prediction, and control of infectious disease. Herein, the aim of this review is to discuss the latest advances in human health engineering and their applicability in the control of infectious diseases. An in-depth knowledge of host–pathogen–protein interactions, combined with a better understanding of a host’s immune response and bacterial fitness, are key determinants for halting infectious diseases and antimicrobial resistance dissemination.
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11
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Weldatsadik R, Datta N, Kolmeder C, Vuopio J, Kere J, Wilkman S, Flatt J, Vuento R, Haapasalo K, Keskitalo S, Varjosalo M, Jokiranta T. Pool-seq driven proteogenomic database for Group G Streptococcus. J Proteomics 2019; 201:84-92. [DOI: 10.1016/j.jprot.2019.04.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2019] [Revised: 03/29/2019] [Accepted: 04/17/2019] [Indexed: 02/07/2023]
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12
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Khakzad H, Malmström J, Malmström L. Greedy de novo motif discovery to construct motif repositories for bacterial proteomes. BMC Bioinformatics 2019; 20:141. [PMID: 30999854 PMCID: PMC6471678 DOI: 10.1186/s12859-019-2686-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Bacterial surfaces are complex systems, constructed from membranes, peptidoglycan and, importantly, proteins. The proteins play crucial roles as critical regulators of how the bacterium interacts with and survive in its environment. A full catalog of the motifs in protein families and their relative conservation grade is a prerequisite to target the protein-protein interaction that bacterial surface protein makes to host proteins. RESULTS In this paper, we propose a greedy approach to identify conserved motifs in large sequence families iteratively. Each iteration discovers a motif de novo and masks all occurrences of that motif. Remaining unmasked sequences are subjected to the next round of motif detection until no more significant motifs can be found. We demonstrate the utility of the method through the construction of a proteome-wide motif repository for Group A Streptococcus (GAS), a significant human pathogen. GAS produce numerous surface proteins that interact with over 100 human plasma proteins, helping the bacteria to evade the host immune response. We used the repository to find that proteins part of the bacterial surface has motif architectures that differ from intracellular proteins. CONCLUSIONS We elucidate that the M protein, a coiled-coil homodimer that extends over 500 A from the cell wall, has a motif architecture that differs between various GAS strains. As the M protein is known to bind a variety of different plasma proteins, the results indicate that the different motif architectures are responsible for the quantitative differences of plasma proteins that various strains bind. The speed and applicability of the method enable its application to all major human pathogens.
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Affiliation(s)
- Hamed Khakzad
- Faculty of Science, Institute for Computational Science, University of Zurich, 429 Winterthurerstrasse, 190, Zurich, CH-8057, Switzerland.,Service and Support 430 for Science IT (S3IT), University of Zurich, Winterthurerstrasse, 190, Zurich, CH-8057 431, Switzerland.,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland
| | - Johan Malmström
- Division of Infection Medicine, Department of Clinical 432 Sciences, Lund University, Tornavagen, 10, Lund, SE-22184, Sweden
| | - Lars Malmström
- Faculty of Science, Institute for Computational Science, University of Zurich, 429 Winterthurerstrasse, 190, Zurich, CH-8057, Switzerland. .,Service and Support 430 for Science IT (S3IT), University of Zurich, Winterthurerstrasse, 190, Zurich, CH-8057 431, Switzerland. .,Swiss Institute of Bioinformatics (SIB), Lausanne, Switzerland. .,Division of Infection Medicine, Department of Clinical 432 Sciences, Lund University, Tornavagen, 10, Lund, SE-22184, Sweden.
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13
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Low TY, Mohtar MA, Ang MY, Jamal R. Connecting Proteomics to Next‐Generation Sequencing: Proteogenomics and Its Current Applications in Biology. Proteomics 2018; 19:e1800235. [DOI: 10.1002/pmic.201800235] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2018] [Revised: 10/09/2018] [Indexed: 12/17/2022]
Affiliation(s)
- Teck Yew Low
- 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
| | - Mia Yang Ang
- UKM Medical Molecular Biology Institute (UMBI)Universiti Kebangsaan Malaysia 56000 Kuala Lumpur Malaysia
| | - Rahman Jamal
- UKM Medical Molecular Biology Institute (UMBI)Universiti Kebangsaan Malaysia 56000 Kuala Lumpur Malaysia
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14
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Haddad N, Johnson N, Kathariou S, Métris A, Phister T, Pielaat A, Tassou C, Wells-Bennik MH, Zwietering MH. Next generation microbiological risk assessment—Potential of omics data for hazard characterisation. Int J Food Microbiol 2018; 287:28-39. [DOI: 10.1016/j.ijfoodmicro.2018.04.015] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2017] [Revised: 03/31/2018] [Accepted: 04/10/2018] [Indexed: 12/18/2022]
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15
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Omasits U, Varadarajan AR, Schmid M, Goetze S, Melidis D, Bourqui M, Nikolayeva O, Québatte M, Patrignani A, Dehio C, Frey JE, Robinson MD, Wollscheid B, Ahrens CH. An integrative strategy to identify the entire protein coding potential of prokaryotic genomes by proteogenomics. Genome Res 2017; 27:2083-2095. [PMID: 29141959 PMCID: PMC5741054 DOI: 10.1101/gr.218255.116] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Accepted: 10/25/2017] [Indexed: 12/18/2022]
Abstract
Accurate annotation of all protein-coding sequences (CDSs) is an essential prerequisite to fully exploit the rapidly growing repertoire of completely sequenced prokaryotic genomes. However, large discrepancies among the number of CDSs annotated by different resources, missed functional short open reading frames (sORFs), and overprediction of spurious ORFs represent serious limitations. Our strategy toward accurate and complete genome annotation consolidates CDSs from multiple reference annotation resources, ab initio gene prediction algorithms and in silico ORFs (a modified six-frame translation considering alternative start codons) in an integrated proteogenomics database (iPtgxDB) that covers the entire protein-coding potential of a prokaryotic genome. By extending the PeptideClassifier concept of unambiguous peptides for prokaryotes, close to 95% of the identifiable peptides imply one distinct protein, largely simplifying downstream analysis. Searching a comprehensive Bartonella henselae proteomics data set against such an iPtgxDB allowed us to unambiguously identify novel ORFs uniquely predicted by each resource, including lipoproteins, differentially expressed and membrane-localized proteins, novel start sites and wrongly annotated pseudogenes. Most novelties were confirmed by targeted, parallel reaction monitoring mass spectrometry, including unique ORFs and single amino acid variations (SAAVs) identified in a re-sequenced laboratory strain that are not present in its reference genome. We demonstrate the general applicability of our strategy for genomes with varying GC content and distinct taxonomic origin. We release iPtgxDBs for B. henselae, Bradyrhizobium diazoefficiens and Escherichia coli and the software to generate both proteogenomics search databases and integrated annotation files that can be viewed in a genome browser for any prokaryote.
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Affiliation(s)
- Ulrich Omasits
- Agroscope, Research Group Molecular Diagnostics, Genomics and Bioinformatics & SIB Swiss Institute of Bioinformatics, CH-8820 Wädenswil, Switzerland
| | - Adithi R Varadarajan
- Agroscope, Research Group Molecular Diagnostics, Genomics and Bioinformatics & SIB Swiss Institute of Bioinformatics, CH-8820 Wädenswil, Switzerland.,Department of Health Sciences and Technology, Institute of Molecular Systems Biology, Swiss Federal Institute of Technology Zurich, CH-8093 Zurich, Switzerland
| | - Michael Schmid
- Agroscope, Research Group Molecular Diagnostics, Genomics and Bioinformatics & SIB Swiss Institute of Bioinformatics, CH-8820 Wädenswil, Switzerland
| | - Sandra Goetze
- Department of Health Sciences and Technology, Institute of Molecular Systems Biology, Swiss Federal Institute of Technology Zurich, CH-8093 Zurich, Switzerland
| | - Damianos Melidis
- Agroscope, Research Group Molecular Diagnostics, Genomics and Bioinformatics & SIB Swiss Institute of Bioinformatics, CH-8820 Wädenswil, Switzerland
| | - Marc Bourqui
- Agroscope, Research Group Molecular Diagnostics, Genomics and Bioinformatics & SIB Swiss Institute of Bioinformatics, CH-8820 Wädenswil, Switzerland
| | - Olga Nikolayeva
- Institute for Molecular Life Sciences & SIB Swiss Institute of Bioinformatics, University of Zurich, CH-8057 Zurich, Switzerland
| | | | - Andrea Patrignani
- Functional Genomics Center Zurich, ETH & UZH Zurich, CH-8057 Zurich, Switzerland
| | | | - Juerg E Frey
- Agroscope, Research Group Molecular Diagnostics, Genomics and Bioinformatics & SIB Swiss Institute of Bioinformatics, CH-8820 Wädenswil, Switzerland
| | - Mark D Robinson
- Institute for Molecular Life Sciences & SIB Swiss Institute of Bioinformatics, University of Zurich, CH-8057 Zurich, Switzerland
| | - Bernd Wollscheid
- Department of Health Sciences and Technology, Institute of Molecular Systems Biology, Swiss Federal Institute of Technology Zurich, CH-8093 Zurich, Switzerland
| | - Christian H Ahrens
- Agroscope, Research Group Molecular Diagnostics, Genomics and Bioinformatics & SIB Swiss Institute of Bioinformatics, CH-8820 Wädenswil, Switzerland
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16
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Meyer JG, Schilling B. Clinical applications of quantitative proteomics using targeted and untargeted data-independent acquisition techniques. Expert Rev Proteomics 2017; 14:419-429. [PMID: 28436239 PMCID: PMC5671767 DOI: 10.1080/14789450.2017.1322904] [Citation(s) in RCA: 100] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
INTRODUCTION While selected/multiple-reaction monitoring (SRM or MRM) is considered the gold standard for quantitative protein measurement, emerging data-independent acquisition (DIA) using high-resolution scans have opened a new dimension of high-throughput, comprehensive quantitative proteomics. These newer methodologies are particularly well suited for discovery of biomarker candidates from human disease samples, and for investigating and understanding human disease pathways. Areas covered: This article reviews the current state of targeted and untargeted DIA mass spectrometry-based proteomic workflows, including SRM, parallel-reaction monitoring (PRM) and untargeted DIA (e.g., SWATH). Corresponding bioinformatics strategies, as well as application in biological and clinical studies are presented. Expert commentary: Nascent application of highly-multiplexed untargeted DIA, such as SWATH, for accurate protein quantification from clinically relevant and disease-related samples shows great potential to comprehensively investigate biomarker candidates and understand disease.
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Affiliation(s)
- Jesse G Meyer
- a Mass Spectrometry Core , Buck Institute for Research on Aging , Novato , CA , USA
| | - Birgit Schilling
- a Mass Spectrometry Core , Buck Institute for Research on Aging , Novato , CA , USA
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17
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Sjöholm K, Kilsgård O, Teleman J, Happonen L, Malmström L, Malmström J. Targeted Proteomics and Absolute Protein Quantification for the Construction of a Stoichiometric Host-Pathogen Surface Density Model. Mol Cell Proteomics 2017; 16:S29-S41. [PMID: 28183813 PMCID: PMC5393399 DOI: 10.1074/mcp.m116.063966] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2016] [Revised: 01/23/2017] [Indexed: 11/06/2022] Open
Abstract
Sepsis is a systemic immune response responsible for considerable morbidity and mortality. Molecular modeling of host-pathogen interactions in the disease state represents a promising strategy to define molecular events of importance for the transition from superficial to invasive infectious diseases. Here we used the Gram-positive bacterium Streptococcus pyogenes as a model system to establish a mass spectrometry based workflow for the construction of a stoichiometric surface density model between the S. pyogenes surface, the surface virulence factor M-protein, and adhered human blood plasma proteins. The workflow relies on stable isotope labeled reference peptides and selected reaction monitoring mass spectrometry analysis of a wild-type strain and an M-protein deficient mutant strain, to generate absolutely quantified protein stoichiometry ratios between S. pyogenes and interacting plasma proteins. The stoichiometry ratios in combination with a novel targeted mass spectrometry method to measure cell numbers enabled the construction of a stoichiometric surface density model using protein structures available from the protein data bank. The model outlines the topology and density of the host-pathogen protein interaction network on the S. pyogenes bacterial surface, revealing a dense and highly organized protein interaction network. Removal of the M-protein from S. pyogenes introduces a drastic change in the network topology, validated by electron microscopy. We propose that the stoichiometric surface density model of S. pyogenes in human blood plasma represents a scalable framework that can continuously be refined with the emergence of new results. Future integration of new results will improve the understanding of protein-protein interactions and their importance for bacterial virulence. Furthermore, we anticipate that the general properties of the developed workflow will facilitate the production of stoichiometric surface density models for other types of host-pathogen interactions.
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Affiliation(s)
- Kristoffer Sjöholm
- From the ‡Department of Immunotechnology, Faculty of Engineering, Lund University, Sweden
- §Division of Infection Medicine, Department of Clinical Sciences, Lund University, Sweden
| | - Ola Kilsgård
- §Division of Infection Medicine, Department of Clinical Sciences, Lund University, Sweden
| | - Johan Teleman
- §Division of Infection Medicine, Department of Clinical Sciences, Lund University, Sweden
| | - Lotta Happonen
- §Division of Infection Medicine, Department of Clinical Sciences, Lund University, Sweden
| | | | - Johan Malmström
- §Division of Infection Medicine, Department of Clinical Sciences, Lund University, Sweden;
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18
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van Ooijen MP, Jong VL, Eijkemans MJC, Heck AJR, Andeweg AC, Binai NA, van den Ham HJ. Identification of differentially expressed peptides in high-throughput proteomics data. Brief Bioinform 2017; 19:971-981. [DOI: 10.1093/bib/bbx031] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Indexed: 12/25/2022] Open
Affiliation(s)
| | - Victor L Jong
- Department of Biostatistics and Research Support, Julius Center, UMC Utrecht, Netherlands
| | - Marinus J C Eijkemans
- Julius Center for Health Sciences and Primary Care of the University Medical Center Utrecht, Netherlands
| | - Albert J R Heck
- Biomolecular Mass Spectrometry and Proteomics, Utrecht University, Netherlands
| | - Arno C Andeweg
- Department of Viroscience, Erasmus MC, CA Rotterdam, Netherlands
| | - Nadine A Binai
- Biomolecular Mass Spectrometry Group, Utrecht University, Netherlands
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19
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Fu S, Liu X, Luo M, Xie K, Nice EC, Zhang H, Huang C. Proteogenomic studies on cancer drug resistance: towards biomarker discovery and target identification. Expert Rev Proteomics 2017; 14:351-362. [PMID: 28276747 DOI: 10.1080/14789450.2017.1299006] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
INTRODUCTION Chemoresistance is a major obstacle for current cancer treatment. Proteogenomics is a powerful multi-omics research field that uses customized protein sequence databases generated by genomic and transcriptomic information to identify novel genes (e.g. noncoding, mutation and fusion genes) from mass spectrometry-based proteomic data. By identifying aberrations that are differentially expressed between tumor and normal pairs, this approach can also be applied to validate protein variants in cancer, which may reveal the response to drug treatment. Areas covered: In this review, we will present recent advances in proteogenomic investigations of cancer drug resistance with an emphasis on integrative proteogenomic pipelines and the biomarker discovery which contributes to achieving the goal of using precision/personalized medicine for cancer treatment. Expert commentary: The discovery and comprehensive understanding of potential biomarkers help identify the cohort of patients who may benefit from particular treatments, and will assist real-time clinical decision-making to maximize therapeutic efficacy and minimize adverse effects. With the development of MS-based proteomics and NGS-based sequencing, a growing number of proteogenomic tools are being developed specifically to investigate cancer drug resistance.
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Affiliation(s)
- Shuyue Fu
- a State Key Laboratory of Biotherapy and Cancer Center , West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy , Chengdu , P.R. China
| | - Xiang Liu
- b Department of Pathology , Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital , Chengdu , P.R. China
| | - Maochao Luo
- c West China School of Public Health, Sichuan University , Chengdu , P.R.China
| | - Ke Xie
- d Department of Oncology , Sichuan Academy of Medical Sciences, Sichuan Provincial People's Hospital , Chengdu , P.R. China
| | - Edouard C Nice
- e Department of Biochemistry and Molecular Biology , Monash University , Clayton , Australia
| | - Haiyuan Zhang
- f School of Medicine , Yangtze University , P. R. China
| | - Canhua Huang
- a State Key Laboratory of Biotherapy and Cancer Center , West China Hospital, Sichuan University, and Collaborative Innovation Center for Biotherapy , Chengdu , P.R. China
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20
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Röst HL, Aebersold R, Schubert OT. Automated SWATH Data Analysis Using Targeted Extraction of Ion Chromatograms. Methods Mol Biol 2017; 1550:289-307. [PMID: 28188537 DOI: 10.1007/978-1-4939-6747-6_20] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
Targeted mass spectrometry comprises a set of methods able to quantify protein analytes in complex mixtures with high accuracy and sensitivity. These methods, e.g., Selected Reaction Monitoring (SRM) and SWATH MS, use specific mass spectrometric coordinates (assays) for reproducible detection and quantification of proteins. In this protocol, we describe how to analyze, in a targeted manner, data from a SWATH MS experiment aimed at monitoring thousands of proteins reproducibly over many samples. We present a standard SWATH MS analysis workflow, including manual data analysis for quality control (based on Skyline) as well as automated data analysis with appropriate control of error rates (based on the OpenSWATH workflow). We also discuss considerations to ensure maximal coverage, reproducibility, and quantitative accuracy.
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Affiliation(s)
- Hannes L Röst
- Institute of Molecular Systems Biology, ETH Zurich, CH-8093, Zurich, Switzerland.
- Department of Genetics, Stanford University, Stanford, CA, 94305, USA.
| | - Ruedi Aebersold
- Institute of Molecular Systems Biology, ETH Zurich, CH-8093, Zurich, Switzerland.
- Faculty of Science, University of Zurich, CH-8057, Zurich, Switzerland.
| | - Olga T Schubert
- Institute of Molecular Systems Biology, ETH Zurich, CH-8093, Zurich, Switzerland.
- Department of Human Genetics, University of California Los Angeles, Los Angeles, CA, 90095, USA.
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21
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Kilsgård O, Karlsson C, Malmström E, Malmström J. Differential compartmentalization of Streptococcus pyogenes virulence factors and host protein binding properties as a mechanism for host adaptation. Int J Med Microbiol 2016; 306:504-516. [DOI: 10.1016/j.ijmm.2016.06.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Revised: 06/28/2016] [Accepted: 06/28/2016] [Indexed: 10/21/2022] Open
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