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Ferrero-Bordera B, Bartel J, van Dijl JM, Becher D, Maaß S. From the outer space to the inner cell: deconvoluting the complexity of Bacillus subtilis disulfide stress responses by redox state and absolute abundance quantification of extracellular, membrane, and cytosolic proteins. Microbiol Spectr 2024; 12:e0261623. [PMID: 38358275 PMCID: PMC10986503 DOI: 10.1128/spectrum.02616-23] [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: 06/26/2023] [Accepted: 01/22/2024] [Indexed: 02/16/2024] Open
Abstract
Understanding cellular mechanisms of stress management relies on omics data as a valuable resource. However, the lack of absolute quantitative data on protein abundances remains a significant limitation, particularly when comparing protein abundances across different cell compartments. In this study, we aimed to gain deeper insights into the proteomic responses of the Gram-positive model bacterium Bacillus subtilis to disulfide stress. We determined proteome-wide absolute abundances, focusing on different sub-cellular locations (cytosol and membrane) as well as the extracellular medium, and combined these data with redox state determination. To quantify secreted proteins in the culture medium, we developed a simple and straightforward protocol for the absolute quantification of extracellular proteins in bacteria. We concentrated extracellular proteins, which are highly diluted in the medium, using StrataClean beads along with a set of standard proteins to determine the extent of the concentration step. The resulting data set provides new insights into protein abundances in different sub-cellular compartments and the extracellular medium, along with a comprehensive proteome-wide redox state determination. Our study offers a quantitative understanding of disulfide stress management, protein production, and secretion in B. subtilis. IMPORTANCE Stress responses play a crucial role in bacterial survival and adaptation. The ability to quantitatively measure protein abundances and redox states in different cellular compartments and the extracellular environment is essential for understanding stress management mechanisms. In this study, we addressed the knowledge gap regarding absolute quantification of extracellular proteins and compared protein concentrations in various sub-cellular locations and in the extracellular medium under disulfide stress conditions. Our findings provide valuable insights into the protein production and secretion dynamics of B. subtilis, shedding light on its stress response strategies. Furthermore, the developed protocol for absolute quantification of extracellular proteins in bacteria presents a practical and efficient approach for future studies in the field. Overall, this research contributes to the quantitative understanding of stress management mechanisms and protein dynamics in B. subtilis, which can be used to enhance bacterial stress tolerance and protein-based biotechnological applications.
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Affiliation(s)
- Borja Ferrero-Bordera
- Department of Microbial Proteomics, University of Greifswald, Centre of Functional Genomics of Microbes, Institute of Microbiology, Greifswald, Germany
| | - Jürgen Bartel
- Department of Microbial Proteomics, University of Greifswald, Centre of Functional Genomics of Microbes, Institute of Microbiology, Greifswald, Germany
| | - Jan Maarten van Dijl
- Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Dörte Becher
- Department of Microbial Proteomics, University of Greifswald, Centre of Functional Genomics of Microbes, Institute of Microbiology, Greifswald, Germany
| | - Sandra Maaß
- Department of Microbial Proteomics, University of Greifswald, Centre of Functional Genomics of Microbes, Institute of Microbiology, Greifswald, Germany
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2
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Johansson C, Hunt H, Signorelli M, Edfors F, Hober A, Svensson AS, Tegel H, Forstström B, Aartsma-Rus A, Niks E, Spitali P, Uhlén M, Szigyarto CAK. Orthogonal proteomics methods warrant the development of Duchenne muscular dystrophy biomarkers. Clin Proteomics 2023; 20:23. [PMID: 37308827 DOI: 10.1186/s12014-023-09412-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 06/01/2023] [Indexed: 06/14/2023] Open
Abstract
BACKGROUND Molecular components in blood, such as proteins, are used as biomarkers to detect or predict disease states, guide clinical interventions and aid in the development of therapies. While multiplexing proteomics methods promote discovery of such biomarkers, their translation to clinical use is difficult due to the lack of substantial evidence regarding their reliability as quantifiable indicators of disease state or outcome. To overcome this challenge, a novel orthogonal strategy was developed and used to assess the reliability of biomarkers and analytically corroborate already identified serum biomarkers for Duchenne muscular dystrophy (DMD). DMD is a monogenic incurable disease characterized by progressive muscle damage that currently lacks reliable and specific disease monitoring tools. METHODS Two technological platforms are used to detect and quantify the biomarkers in 72 longitudinally collected serum samples from DMD patients at 3 to 5 timepoints. Quantification of the biomarkers is achieved by detection of the same biomarker fragment either through interaction with validated antibodies in immuno-assays or through quantification of peptides by Parallel Reaction Monitoring Mass Spectrometry assay (PRM-MS). RESULTS Five, out of ten biomarkers previously identified by affinity-based proteomics methods, were confirmed to be associated with DMD using the mass spectrometry-based method. Two biomarkers, carbonic anhydrase III and lactate dehydrogenase B, were quantified with two independent methods, sandwich immunoassays and PRM-MS, with Pearson correlations of 0.92 and 0.946 respectively. The median concentrations of CA3 and LDHB in DMD patients was elevated in comparison to those in healthy individuals by 35- and 3-fold, respectively. Levels of CA3 vary between 10.26 and 0.36 ng/ml in DMD patients whereas those of LDHB vary between 15.1 and 0.8 ng/ml. CONCLUSIONS These results demonstrate that orthogonal assays can be used to assess the analytical reliability of biomarker quantification assays, providing a means to facilitate the translation of biomarkers to clinical practice. This strategy also warrants the development of the most relevant biomarkers, markers that can be reliably quantified with different proteomics methods.
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Affiliation(s)
- Camilla Johansson
- Department of Protein Science, School of Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Helian Hunt
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden
| | - Mirko Signorelli
- Mathematical Institute, Leiden University, Leiden, The Netherlands
| | - Fredrik Edfors
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden
| | - Andreas Hober
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden
| | - Anne-Sophie Svensson
- Department of Protein Science, School of Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Hanna Tegel
- Department of Protein Science, School of Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Björn Forstström
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden
| | - Annemieke Aartsma-Rus
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Erik Niks
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Pietro Spitali
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
| | - Mathias Uhlén
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden
| | - Cristina Al-Khalili Szigyarto
- Department of Protein Science, School of Chemistry, Biotechnology and Health, KTH - Royal Institute of Technology, Stockholm, Sweden.
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.
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3
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A Proof of Principle Proteomic Study Detects Dystrophin in Human Plasma: Implications in DMD Diagnosis and Clinical Monitoring. Int J Mol Sci 2023; 24:ijms24065215. [PMID: 36982290 PMCID: PMC10049465 DOI: 10.3390/ijms24065215] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/03/2023] [Accepted: 03/06/2023] [Indexed: 03/12/2023] Open
Abstract
Duchenne muscular dystrophy (DMD) is a rare neuromuscular disease caused by pathogenic variations in the DMD gene. There is a need for robust DMD biomarkers for diagnostic screening and to aid therapy monitoring. Creatine kinase, to date, is the only routinely used blood biomarker for DMD, although it lacks specificity and does not correlate with disease severity. To fill this critical gap, we present here novel data about dystrophin protein fragments detected in human plasma by a suspension bead immunoassay using two validated anti-dystrophin-specific antibodies. Using both antibodies, a reduction of the dystrophin signal is detected in a small cohort of plasma samples from DMD patients when compared to healthy controls, female carriers, and other neuromuscular diseases. We also demonstrate the detection of dystrophin protein by an antibody-independent method using targeted liquid chromatography mass spectrometry. This last assay detects three different dystrophin peptides in all healthy individuals analysed and supports our finding that dystrophin protein is detectable in plasma. The results of our proof-of-concept study encourage further studies in larger sample cohorts to investigate the value of dystrophin protein as a low invasive blood biomarker for diagnostic screening and clinical monitoring of DMD.
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4
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Hober A, Rekanovic M, Forsström B, Hansson S, Kotol D, Percy AJ, Uhlén M, Oscarsson J, Edfors F, Miliotis T. Targeted proteomics using stable isotope labeled protein fragments enables precise and robust determination of total apolipoprotein(a) in human plasma. PLoS One 2023; 18:e0281772. [PMID: 36791076 PMCID: PMC9931122 DOI: 10.1371/journal.pone.0281772] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 01/31/2023] [Indexed: 02/16/2023] Open
Abstract
Lipoprotein(a), also known as Lp(a), is an LDL-like particle composed of apolipoprotein(a) (apo(a)) bound covalently to apolipoprotein B100. Plasma concentrations of Lp(a) are highly heritable and vary widely between individuals. Elevated plasma concentration of Lp(a) is considered as an independent, causal risk factor of cardiovascular disease (CVD). Targeted mass spectrometry (LC-SRM/MS) combined with stable isotope-labeled recombinant proteins provides robust and precise quantification of proteins in the blood, making LC-SRM/MS assays appealing for monitoring plasma proteins for clinical implications. This study presents a novel quantitative approach, based on proteotypic peptides, to determine the absolute concentration of apo(a) from two microliters of plasma and qualified according to guideline requirements for targeted proteomics assays. After optimization, assay parameters such as linearity, lower limits of quantification (LLOQ), intra-assay variability (CV: 4.7%) and inter-assay repeatability (CV: 7.8%) were determined and the LC-SRM/MS results were benchmarked against a commercially available immunoassay. In summary, the measurements of an apo(a) single copy specific peptide and a kringle 4 specific peptide allow for the determination of molar concentration and relative size of apo(a) in individuals.
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Affiliation(s)
- Andreas Hober
- Science for Life Laboratory, Solna, Sweden
- Division of Systems Biology, Department of Protein Science, School of Chemistry, Biotechnology and Health, The Royal Institute of Technology (KTH), Stockholm, Sweden
| | - Mirela Rekanovic
- Translational Science and Experimental Medicine, Cardiovascular, Renal and Metabolism, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
| | - Björn Forsström
- Science for Life Laboratory, Solna, Sweden
- Division of Systems Biology, Department of Protein Science, School of Chemistry, Biotechnology and Health, The Royal Institute of Technology (KTH), Stockholm, Sweden
| | - Sara Hansson
- Translational Science and Experimental Medicine, Cardiovascular, Renal and Metabolism, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
| | - David Kotol
- Science for Life Laboratory, Solna, Sweden
- Division of Systems Biology, Department of Protein Science, School of Chemistry, Biotechnology and Health, The Royal Institute of Technology (KTH), Stockholm, Sweden
| | - Andrew J. Percy
- Department of Applications Development, Cambridge Isotope Laboratories, Inc., Tewksbury, Massachusetts, United States of America
| | - Mathias Uhlén
- Science for Life Laboratory, Solna, Sweden
- Division of Systems Biology, Department of Protein Science, School of Chemistry, Biotechnology and Health, The Royal Institute of Technology (KTH), Stockholm, Sweden
| | - Jan Oscarsson
- Late-stage Development, Cardiovascular, Renal and Metabolism, Biopharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden
| | - Fredrik Edfors
- Science for Life Laboratory, Solna, Sweden
- Division of Systems Biology, Department of Protein Science, School of Chemistry, Biotechnology and Health, The Royal Institute of Technology (KTH), Stockholm, Sweden
| | - Tasso Miliotis
- Translational Science and Experimental Medicine, Cardiovascular, Renal and Metabolism, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
- * E-mail:
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5
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Miller RM, Jordan BT, Mehlferber MM, Jeffery ED, Chatzipantsiou C, Kaur S, Millikin RJ, Dai Y, Tiberi S, Castaldi PJ, Shortreed MR, Luckey CJ, Conesa A, Smith LM, Deslattes Mays A, Sheynkman GM. Enhanced protein isoform characterization through long-read proteogenomics. Genome Biol 2022; 23:69. [PMID: 35241129 PMCID: PMC8892804 DOI: 10.1186/s13059-022-02624-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 02/02/2022] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND The detection of physiologically relevant protein isoforms encoded by the human genome is critical to biomedicine. Mass spectrometry (MS)-based proteomics is the preeminent method for protein detection, but isoform-resolved proteomic analysis relies on accurate reference databases that match the sample; neither a subset nor a superset database is ideal. Long-read RNA sequencing (e.g., PacBio or Oxford Nanopore) provides full-length transcripts which can be used to predict full-length protein isoforms. RESULTS We describe here a long-read proteogenomics approach for integrating sample-matched long-read RNA-seq and MS-based proteomics data to enhance isoform characterization. We introduce a classification scheme for protein isoforms, discover novel protein isoforms, and present the first protein inference algorithm for the direct incorporation of long-read transcriptome data to enable detection of protein isoforms previously intractable to MS-based detection. We have released an open-source Nextflow pipeline that integrates long-read sequencing in a proteomic workflow for isoform-resolved analysis. CONCLUSIONS Our work suggests that the incorporation of long-read sequencing and proteomic data can facilitate improved characterization of human protein isoform diversity. Our first-generation pipeline provides a strong foundation for future development of long-read proteogenomics and its adoption for both basic and translational research.
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Affiliation(s)
- Rachel M. Miller
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Ben T. Jordan
- grid.27755.320000 0000 9136 933XDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA USA
| | - Madison M. Mehlferber
- grid.27755.320000 0000 9136 933XDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA USA ,grid.27755.320000 0000 9136 933XDepartment of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA USA
| | - Erin D. Jeffery
- grid.27755.320000 0000 9136 933XDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA USA
| | | | - Simi Kaur
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Robert J. Millikin
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Yunxiang Dai
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Simone Tiberi
- grid.7400.30000 0004 1937 0650Department of Molecular Life Sciences, University of Zurich, Zurich, Switzerland ,grid.7400.30000 0004 1937 0650Swiss Institute of Bioinformatics, University of Zurich, Zurich, Switzerland
| | - Peter J. Castaldi
- grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA USA ,grid.62560.370000 0004 0378 8294Division of General Medicine and Primary Care, Brigham and Women’s Hospital, Boston, MA USA
| | - Michael R. Shortreed
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Chance John Luckey
- grid.27755.320000 0000 9136 933XDepartment of Pathology, University of Virginia, Charlottesville, VA USA
| | - Ana Conesa
- grid.4711.30000 0001 2183 4846Institute for Integrative Systems Biology, Spanish National Research Council (CSIC), Paterna, Spain ,grid.15276.370000 0004 1936 8091Microbiology and Cell Science Department, Institute for Food and Agricultural Sciences, University of Florida, Gainesville, FL USA
| | - Lloyd M. Smith
- grid.14003.360000 0001 2167 3675Department of Chemistry, University of Wisconsin-Madison, Madison, WI USA
| | - Anne Deslattes Mays
- grid.420089.70000 0000 9635 8082 Office of Data Science and Sharing, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Rockville, MD USA
| | - Gloria M. Sheynkman
- grid.27755.320000 0000 9136 933XDepartment of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA USA ,grid.27755.320000 0000 9136 933XCenter for Public Health Genomics, University of Virginia, Charlottesville, VA USA ,grid.27755.320000 0000 9136 933XUVA Cancer Center, University of Virginia, Charlottesville, VA USA
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6
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Kotol D, Hober A, Strandberg L, Svensson AS, Uhlén M, Edfors F. Targeted proteomics analysis of plasma proteins using recombinant protein standards for addition only workflows. Biotechniques 2021; 71:473-483. [PMID: 34431357 DOI: 10.2144/btn-2021-0047] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
Targeted proteomics is an attractive approach for the analysis of blood proteins. Here, we describe a novel analytical platform based on isotope-labeled recombinant protein standards stored in a chaotropic agent and subsequently dried down to allow storage at ambient temperature. This enables a straightforward protocol suitable for robotic workstations. Plasma samples to be analyzed are simply added to the dried pellet followed by enzymatic treatment and mass spectrometry analysis. Here, we show that this approach can be used to precisely (coefficient of variation <10%) determine the absolute concentrations in human plasma of hundred clinically relevant protein targets, spanning four orders of magnitude, using simultaneous analysis of 292 peptides. The use of this next-generation analytical platform for high-throughput clinical proteome profiling is discussed.
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Affiliation(s)
- David Kotol
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.,Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Andreas Hober
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.,Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Linnéa Strandberg
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden
| | - Anne-Sophie Svensson
- Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Mathias Uhlén
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.,Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Fredrik Edfors
- Science for Life Laboratory, KTH - Royal Institute of Technology, Solna, Sweden.,Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
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7
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Detailed Method for Performing the ExSTA Approach in Quantitative Bottom-Up Plasma Proteomics. Methods Mol Biol 2021; 2228:353-384. [PMID: 33950503 DOI: 10.1007/978-1-0716-1024-4_25] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
The use of stable isotope-labeled standards (SIS) is an analytically valid means of quantifying proteins in biological samples. The nature of the labeled standards and their point of insertion in a bottom-up proteomic workflow can vary, with quantification methods utilizing curves in analytically sound practices. A promising quantification strategy for low sample amounts is external standard addition (ExSTA). In ExSTA, multipoint calibration curves are generated in buffer using serially diluted natural (NAT) peptides and a fixed concentration of SIS peptides. Equal concentrations of SIS peptides are spiked into experimental sample digests, with all digests (control and experimental) subjected to solid-phase extraction prior to liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis. Endogenous peptide concentrations are then determined using the regression equation of the standard curves. Given the benefits of ExSTA in large-scale analysis, a detailed protocol is provided herein for quantifying a multiplexed panel of 125 high-to-moderate abundance proteins in undepleted and non-enriched human plasma samples. The procedural details and recommendations for successfully executing all phases of this quantification approach are described. As the proteins have been putatively correlated with various noncommunicable diseases, quantifying these by ExSTA in large-scale studies should help rapidly and precisely assess their true biomarker efficacy.
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8
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Karlsson MJ, Costa Svedman F, Tebani A, Kotol D, Höiom V, Fagerberg L, Edfors F, Uhlén M, Egyhazi Brage S, Maddalo G. Inflammation and Apolipoproteins Are Potential Biomarkers for Stratification of Cutaneous Melanoma Patients for Immunotherapy and Targeted Therapy. Cancer Res 2021; 81:2545-2555. [PMID: 33574091 DOI: 10.1158/0008-5472.can-20-2000] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Revised: 09/22/2020] [Accepted: 02/09/2021] [Indexed: 11/16/2022]
Abstract
Malignant cutaneous melanoma is one of the most common cancers in young adults. During the last decade, targeted and immunotherapies have significantly increased the overall survival of patients with malignant cutaneous melanoma. Nevertheless, disease progression is common, and a lack of predictive biomarkers of patient response to therapy hinders individualized treatment strategies. To address this issue, we performed a longitudinal study using an unbiased proteomics approach to identify and quantify proteins in plasma both before and during treatment from 109 patients treated with either targeted or immunotherapy. Linear modeling and machine learning approaches identified 43 potential prognostic and predictive biomarkers. A reverse correlation between apolipoproteins and proteins related to inflammation was observed. In the immunotherapy group, patients with low pretreatment expression of apolipoproteins and high expression of inflammation markers had shorter progression-free survival. Similarly, increased expression of LDHB during treatment elicited a significant impact on response to immunotherapy. Overall, we identified potential common and treatment-specific biomarkers in malignant cutaneous melanoma, paving the way for clinical use of these biomarkers following validation on a larger cohort. SIGNIFICANCE: This study identifies a potential biomarker panel that could improve the selection of therapy for patients with cutaneous melanoma.
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Affiliation(s)
- Max J Karlsson
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | | | - Abdellah Tebani
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - David Kotol
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Veronica Höiom
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Linn Fagerberg
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Fredrik Edfors
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
| | - Mathias Uhlén
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden
- Department of Neuroscience, Karolinska Institute, Stockholm, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kongens Lyngby, Denmark
| | | | - Gianluca Maddalo
- Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden.
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9
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Shahinnia F, Geyer M, Block A, Mohler V, Hartl L. Identification of Rf9, a Gene Contributing to the Genetic Complexity of Fertility Restoration in Hybrid Wheat. FRONTIERS IN PLANT SCIENCE 2020; 11:577475. [PMID: 33362809 PMCID: PMC7758405 DOI: 10.3389/fpls.2020.577475] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 10/14/2020] [Indexed: 06/12/2023]
Abstract
Wheat (Triticum aestivum L.) is a self-pollinating crop whose hybrids offer the potential to provide a major boost in yield. Male sterility induced by the cytoplasm of Triticum timopheevii is a powerful method for hybrid seed production. Hybrids produced by this method are often partially sterile, and full fertility restoration is crucial for wheat production using hybrid cultivars. To identify the genetic loci controlling fertility restoration in wheat, we produced two cytoplasmic male-sterile (CMS) backcross (BC1) mapping populations. The restorer lines Gerek 79 and 71R1203 were used to pollinate the male-sterile winter wheat line CMS-Sperber. Seed set and numbers of sterile spikelets per spike were evaluated in 340 and 206 individuals of the populations derived from Gerek 79 and 71R1203, respectively. Genetic maps were constructed using 930 and 994 single nucleotide polymorphism (SNP) markers, spanning 2,160 and 2,328 cM over 21 linkage groups in the two populations, respectively. Twelve quantitative trait loci (QTL) controlled fertility restoration in both BC1 populations, including a novel restorer-of-fertility (Rf) locus flanked by the SNP markers IWB72413 and IWB1550 on chromosome 6AS. The locus was mapped as a qualitative trait in the BC1 Gerek 79 population and was designated Rf9. One hundred-nineteen putative candidate genes were predicted within the QTL region on chromosome 6AS. Among them were genes encoding mitochondrial transcription termination factor and pentatricopeptide repeat-containing proteins that are known to be associated with fertility restoration. This finding is a promising step to better understand the functions of genes for improving fertility restoration in hybrid wheat.
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Affiliation(s)
| | | | | | | | - Lorenz Hartl
- Bavarian State Research Centre for Agriculture, Institute for Crop Science and Plant Breeding, Freising, Germany
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10
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Tegel H, Dannemeyer M, Kanje S, Sivertsson Å, Berling A, Svensson AS, Hober A, Enstedt H, Volk AL, Lundqvist M, Moradi M, Afshari D, Ekblad S, Xu L, Westin M, Bidad F, Schiavone LH, Davies R, Mayr LM, Knight S, Göpel SO, Voldborg BG, Edfors F, Forsström B, von Feilitzen K, Zwahlen M, Rockberg J, Takanen JO, Uhlén M, Hober S. High throughput generation of a resource of the human secretome in mammalian cells. N Biotechnol 2020; 58:45-54. [DOI: 10.1016/j.nbt.2020.05.002] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2020] [Revised: 05/04/2020] [Accepted: 05/30/2020] [Indexed: 02/07/2023]
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11
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Kotol D, Hunt H, Hober A, Karlsson MJ, Forsström B, Gummesson A, Bergström G, Fagerberg L, Uhlén M, Edfors F. Longitudinal Plasma Protein Profiling Using Targeted Proteomics and Recombinant Protein Standards. J Proteome Res 2020; 19:4815-4825. [DOI: 10.1021/acs.jproteome.0c00194] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Affiliation(s)
- David Kotol
- Department of Protein Science, School of Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), SE-10044 Stockholm, Sweden
- Science For Life Laboratory, SE-17165 Solna, Sweden
| | - Helian Hunt
- Department of Protein Science, School of Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), SE-10044 Stockholm, Sweden
- Science For Life Laboratory, SE-17165 Solna, Sweden
| | - Andreas Hober
- Department of Protein Science, School of Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), SE-10044 Stockholm, Sweden
- Science For Life Laboratory, SE-17165 Solna, Sweden
| | - Max J. Karlsson
- Department of Protein Science, School of Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), SE-10044 Stockholm, Sweden
- Science For Life Laboratory, SE-17165 Solna, Sweden
| | - Björn Forsström
- Department of Protein Science, School of Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), SE-10044 Stockholm, Sweden
- Science For Life Laboratory, SE-17165 Solna, Sweden
| | - Anders Gummesson
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, and Clinical Physiology, Sahlgrenska University Hospital, SE-40530 Gothenburg, Sweden
| | - Göran Bergström
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, and Clinical Physiology, Sahlgrenska University Hospital, SE-40530 Gothenburg, Sweden
| | | | - Mathias Uhlén
- Department of Protein Science, School of Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), SE-10044 Stockholm, Sweden
- Science For Life Laboratory, SE-17165 Solna, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2970 Hørsholm, Denmark
| | - Fredrik Edfors
- Department of Protein Science, School of Chemistry, Biotechnology and Health, Royal Institute of Technology (KTH), SE-10044 Stockholm, Sweden
- Science For Life Laboratory, SE-17165 Solna, Sweden
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Dodig-Crnković T, Hong MG, Thomas CE, Häussler RS, Bendes A, Dale M, Edfors F, Forsström B, Magnusson PKE, Schuppe-Koistinen I, Odeberg J, Fagerberg L, Gummesson A, Bergström G, Uhlén M, Schwenk JM. Facets of individual-specific health signatures determined from longitudinal plasma proteome profiling. EBioMedicine 2020; 57:102854. [PMID: 32629387 PMCID: PMC7334812 DOI: 10.1016/j.ebiom.2020.102854] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 06/01/2020] [Accepted: 06/09/2020] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Precision medicine approaches aim to tackle diseases on an individual level through molecular profiling. Despite the growing knowledge about diseases and the reported diversity of molecular phenotypes, the descriptions of human health on an individual level have been far less elaborate. METHODS To provide insights into the longitudinal protein signatures of well-being, we profiled blood plasma collected over one year from 101 clinically healthy individuals using multiplexed antibody assays. After applying an antibody validation scheme, we utilized > 700 protein profiles for in-depth analyses of the individuals' short-term health trajectories. FINDINGS We found signatures of circulating proteomes to be highly individual-specific. Considering technical and longitudinal variability, we observed that 49% of the protein profiles were stable over one year. We also identified eight networks of proteins in which 11-242 proteins covaried over time. For each participant, there were unique protein profiles of which some could be explained by associations to genetic variants. INTERPRETATION This observational and non-interventional study identifyed noticeable diversity among clinically healthy subjects, and facets of individual-specific signatures emerged by monitoring the variability of the circulating proteomes over time. To enable more personal hence precise assessments of health states, longitudinal profiling of circulating proteomes can provide a valuable component for precision medicine approaches. FUNDING This work was supported by the Erling Persson Foundation, the Swedish Heart and Lung Foundation, the Knut and Alice Wallenberg Foundation, Science for Life Laboratory, and the Swedish Research Council.
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Affiliation(s)
- Tea Dodig-Crnković
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden
| | - Mun-Gwan Hong
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden
| | - Cecilia Engel Thomas
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden
| | - Ragna S Häussler
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden
| | - Annika Bendes
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden
| | - Matilda Dale
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden
| | - Fredrik Edfors
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden; Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Björn Forsström
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, Stockholm 171 77, Sweden
| | - Ina Schuppe-Koistinen
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden; Center for Translational Microbiome Research, Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Stockholm 171 77, Sweden
| | - Jacob Odeberg
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden; Department of Clinical Medicine, K.G. Jebsen Thrombosis Research and Expertise Center (TREC), UiT the Arctic University of Norway, Tromsø 9010, Norway; Coagulation unit, Department of Hematology, Karolinska University Hospital, Stockholm 171 76, Sweden
| | - Linn Fagerberg
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden
| | - Anders Gummesson
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Gothenburg University, Gothenburg 413 45, Sweden; Region Västra Götaland, Department of Clinical Genetics and Genomics, Sahlgrenska University Hospital, Gothenburg 413 45, Sweden
| | - Göran Bergström
- Department of Molecular and Clinical Medicine, Institute of Medicine, Sahlgrenska Academy, Gothenburg University, Gothenburg 413 45, Sweden; Region Västra Götaland, Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg 413 45, Sweden
| | - Mathias Uhlén
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby 2800, Denmark
| | - Jochen M Schwenk
- Science for Life Laboratory, Department of Protein Science, KTH-Royal Institute of Technology, Tomtebodavägen 23, Stockholm 171 65, Sweden.
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13
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Hober A, Edfors F, Ryaboshapkina M, Malmqvist J, Rosengren L, Percy AJ, Lind L, Forsström B, Uhlén M, Oscarsson J, Miliotis T. Absolute Quantification of Apolipoproteins Following Treatment with Omega-3 Carboxylic Acids and Fenofibrate Using a High Precision Stable Isotope-labeled Recombinant Protein Fragments Based SRM Assay. Mol Cell Proteomics 2019; 18:2433-2446. [PMID: 31591263 PMCID: PMC6885709 DOI: 10.1074/mcp.ra119.001765] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2019] [Indexed: 11/20/2022] Open
Abstract
Stable isotope-labeled standard (SIS) peptides are used as internal standards in targeted proteomics to provide robust protein quantification, which is required in clinical settings. However, SIS peptides are typically added post trypsin digestion and, as the digestion efficiency can vary significantly between peptides within a protein, the accuracy and precision of the assay may be compromised. These drawbacks can be remedied by a new class of internal standards introduced by the Human Protein Atlas project, which are based on SIS recombinant protein fragments called SIS PrESTs. SIS PrESTs are added initially to the sample and SIS peptides are released on trypsin digestion. The SIS PrEST technology is promising for absolute quantification of protein biomarkers but has not previously been evaluated in a clinical setting. An automated and scalable solid phase extraction workflow for desalting and enrichment of plasma digests was established enabling simultaneous preparation of up to 96 samples. Robust high-precision quantification of 13 apolipoproteins was achieved using a novel multiplex SIS PrEST-based LC-SRM/MS Tier 2 assay in non-depleted human plasma. The assay exhibited inter-day coefficients of variation between 1.5% and 14.5% (median = 3.5%) and was subsequently used to investigate the effects of omega-3 carboxylic acids (OM3-CA) and fenofibrate on these 13 apolipoproteins in human plasma samples from a randomized placebo-controlled trial, EFFECT I (NCT02354976). No significant changes were observed in the OM3-CA arm, whereas treatment with fenofibrate significantly increased apoAII and reduced apoB, apoCI, apoE and apoCIV levels. The reduction in apoCIV following fenofibrate treatment is a novel finding. The study demonstrates that SIS PrESTs can facilitate the generation of robust multiplexed biomarker Tier 2 assays for absolute quantification of proteins in clinical studies.
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Affiliation(s)
- Andreas Hober
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden; Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Fredrik Edfors
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden; Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Maria Ryaboshapkina
- Translational Science, Cardiovascular, Renal and Metabolism, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
| | - Jonas Malmqvist
- Translational Science, Cardiovascular, Renal and Metabolism, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
| | - Louise Rosengren
- Translational Science, Cardiovascular, Renal and Metabolism, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden
| | - Andrew J Percy
- Department of Applications Development, Cambridge Isotope Laboratories, Inc., Tewksbury, MA 01876
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Björn Forsström
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden; Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Mathias Uhlén
- Science for Life Laboratory, KTH - Royal Institute of Technology, Stockholm, Sweden; Department of Protein Science, KTH - Royal Institute of Technology, Stockholm, Sweden
| | - Jan Oscarsson
- Global Medicines Development, Cardiovascular, Renal and Metabolism, AstraZeneca, Gothenburg, Sweden
| | - Tasso Miliotis
- Translational Science, Cardiovascular, Renal and Metabolism, IMED Biotech Unit, AstraZeneca, Gothenburg, Sweden.
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Ignjatovic V, Geyer PE, Palaniappan KK, Chaaban JE, Omenn GS, Baker MS, Deutsch EW, Schwenk JM. Mass Spectrometry-Based Plasma Proteomics: Considerations from Sample Collection to Achieving Translational Data. J Proteome Res 2019; 18:4085-4097. [PMID: 31573204 DOI: 10.1021/acs.jproteome.9b00503] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
The proteomic analysis of human blood and blood-derived products (e.g., plasma) offers an attractive avenue to translate research progress from the laboratory into the clinic. However, due to its unique protein composition, performing proteomics assays with plasma is challenging. Plasma proteomics has regained interest due to recent technological advances, but challenges imposed by both complications inherent to studying human biology (e.g., interindividual variability) and analysis of biospecimens (e.g., sample variability), as well as technological limitations remain. As part of the Human Proteome Project (HPP), the Human Plasma Proteome Project (HPPP) brings together key aspects of the plasma proteomics pipeline. Here, we provide considerations and recommendations concerning study design, plasma collection, quality metrics, plasma processing workflows, mass spectrometry (MS) data acquisition, data processing, and bioinformatic analysis. With exciting opportunities in studying human health and disease though this plasma proteomics pipeline, a more informed analysis of human plasma will accelerate interest while enhancing possibilities for the incorporation of proteomics-scaled assays into clinical practice.
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Affiliation(s)
- Vera Ignjatovic
- Haematology Research , Murdoch Children's Research Institute , Parkville , VIC 3052 , Australia.,Department of Paediatrics , The University of Melbourne , Parkville , VIC 3052 , Australia
| | - Philipp E Geyer
- NNF Center for Protein Research, Faculty of Health Sciences , University of Copenhagen , 2200 Copenhagen , Denmark.,Department of Proteomics and Signal Transduction , Max Planck Institute of Biochemistry , 82152 Martinsried , Germany
| | - Krishnan K Palaniappan
- Freenome , 259 East Grand Avenue , South San Francisco , California 94080 , United States
| | - Jessica E Chaaban
- Haematology Research , Murdoch Children's Research Institute , Parkville , VIC 3052 , Australia
| | - Gilbert S Omenn
- Departments of Computational Medicine & Bioinformatics, Human Genetics, and Internal Medicine and School of Public Health , University of Michigan , 100 Washtenaw Avenue , Ann Arbor , Michigan 48109-2218 , United States
| | - Mark S Baker
- Department of Biomedical Sciences, Faculty of Medicine & Health Sciences , Macquarie University , 75 Talavera Road , North Ryde , NSW 2109 , Australia
| | - Eric W Deutsch
- Institute for Systems Biology , 401 Terry Avenue North , Seattle , Washington 98109 , United States
| | - Jochen M Schwenk
- Affinity Proteomics, SciLifeLab , KTH Royal Institute of Technology , 171 65 Stockholm , Sweden
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15
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Häussler RS, Bendes A, Iglesias M, Sanchez-Rivera L, Dodig-Crnković T, Byström S, Fredolini C, Birgersson E, Dale M, Edfors F, Fagerberg L, Rockberg J, Tegel H, Uhlén M, Qundos U, Schwenk JM. Systematic Development of Sandwich Immunoassays for the Plasma Secretome. Proteomics 2019; 19:e1900008. [PMID: 31278833 DOI: 10.1002/pmic.201900008] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 06/17/2019] [Indexed: 12/15/2022]
Abstract
The plasma proteome offers a clinically useful window into human health. Recent advances from highly multiplexed assays now call for appropriate pipelines to validate individual candidates. Here, a workflow is developed to build dual binder sandwich immunoassays (SIA) and for proteins predicted to be secreted into plasma. Utilizing suspension bead arrays, ≈1800 unique antibody pairs are first screened against 209 proteins with recombinant proteins as well as EDTA plasma. Employing 624 unique antibodies, dilution-dependent curves in plasma and concentration-dependent curves of full-length proteins for 102 (49%) of the targets are obtained. For 22 protein assays, the longitudinal, interindividual, and technical performance is determined in a set of plasma samples collected from 18 healthy subjects every third month over 1 year. Finally, 14 of these assays are compared with with SIAs composed of other binders, proximity extension assays, and affinity-free targeted mass spectrometry. The workflow provides a multiplexed approach to screen for SIA pairs that suggests using at least three antibodies per target. This design is applicable for a wider range of targets of the plasma proteome, and the assays can be applied for discovery but also to validate emerging candidates derived from other platforms.
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Affiliation(s)
- Ragna S Häussler
- Division of Affinity Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Annika Bendes
- Division of Affinity Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - MariaJesus Iglesias
- Division of Cellular and Clinical Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
- K.G. Jebsen - Thrombosis Research and Expertise Center (TREC), Department of Clinical Medicine, UiT - The Arctic University of Norway, 9010, Tromsø, Norway
- Division of Internal Medicine, University Hospital of North Norway, 9010, Tromsø, Norway
| | - Laura Sanchez-Rivera
- Division of Cellular and Clinical Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Tea Dodig-Crnković
- Division of Affinity Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Sanna Byström
- Division of Affinity Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Claudia Fredolini
- Division of Affinity Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Elin Birgersson
- Division of Affinity Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Matilda Dale
- Division of Affinity Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Fredrik Edfors
- Division of Systems Biology, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Linn Fagerberg
- Division of Systems Biology, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
| | - Johan Rockberg
- Division of Protein Technology, Department of Protein Science, KTH - Royal Institute of Technology, 106 91, Stockholm, Sweden
| | - Hanna Tegel
- Division of Protein Technology, Department of Protein Science, KTH - Royal Institute of Technology, 106 91, Stockholm, Sweden
| | - Mathias Uhlén
- Division of Systems Biology, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, 2970, Hørsholm, Denmark
| | | | - Jochen M Schwenk
- Division of Affinity Proteomics, Science for Life Laboratory, KTH - Royal Institute of Technology, Box 1031, 171 21, Solna, Sweden
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