{"entity": "researcher", "timestamp": "2026-07-18T02:23:02.676Z", "family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "affiliations": ["Clinical Proteomics Mass Spectrometry, Department of Oncology-Pathology, Science for Life Laboratory and Karolinska Institutet, Stockholm, 17176, Sweden."], "links": {"self": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}, "display": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603"}}, "publications": [{"entity": "publication", "iuid": "f3a1b1396edb4101b0575fbc43ec7415", "links": {"self": {"href": "https://publications.scilifelab.se/publication/f3a1b1396edb4101b0575fbc43ec7415.json"}, "display": {"href": "https://publications.scilifelab.se/publication/f3a1b1396edb4101b0575fbc43ec7415"}}, "title": "Comparative evaluation of Olink Explore 3072 and mass spectrometry with peptide fractionation for plasma proteomics.", "authors": [{"family": "Sissala", "given": "Noora", "initials": "N", "orcid": "0009-0000-0758-8140", "researcher": {"href": "https://publications.scilifelab.se/researcher/3a96666a6a2e478fbdd3cf33d7db1e74.json"}}, {"family": "Baba\u010di\u0107", "given": "Haris", "initials": "H", "orcid": "0000-0003-0813-0005", "researcher": {"href": "https://publications.scilifelab.se/researcher/45a1c5d3d2d34a9e96d112877632784c.json"}}, {"family": "Leo", "given": "Isabelle R", "initials": "IR", "orcid": "0000-0002-7627-6690", "researcher": {"href": "https://publications.scilifelab.se/researcher/21185d9c6a2343f189397cbbb95c6e71.json"}}, {"family": "Cao", "given": "Xiaofang", "initials": "X"}, {"family": "Forshed", "given": "Jenny", "initials": "J"}, {"family": "Eriksson", "given": "Lars E", "initials": "LE", "orcid": "0000-0001-5121-5325", "researcher": {"href": "https://publications.scilifelab.se/researcher/ebb717a9972245a5b2427a4b8421fe6f.json"}}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Fredolini", "given": "Claudia", "initials": "C", "orcid": "0000-0002-7674-2014", "researcher": {"href": "https://publications.scilifelab.se/researcher/40ac3a5823cb4f998cc8bdb96dcbf195.json"}}, {"family": "\u00c5berg", "given": "Mikael", "initials": "M", "orcid": "0000-0002-7858-8233", "researcher": {"href": "https://publications.scilifelab.se/researcher/90fa86e9aeaa43ea9547e48b4f3f24e3.json"}}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}], "type": "journal article", "published": "2025-11-04", "journal": {"title": "Commun Chem", "issn": "2399-3669", "issn-l": null, "volume": "8", "issue": "1", "pages": "327"}, "abstract": "Plasma proteomics technologies are advancing rapidly, offering new opportunities for biomarker discovery and precision medicine. Direct comparisons of available technologies are needed to understand how platform selection affects downstream findings. We compared the performance of a peptide fractionation-based mass spectrometry method (HiRIEF LC-MS/MS) and the Olink Explore 3072 proximity extension assays on 88 plasma samples, analyzing 1129 proteins with both methods. The platforms exhibited complementary proteome coverage, high precision, and concordance in estimating sex differences in protein levels. Quantitative agreement between platforms was moderate (median correlation 0.59, interquartile range 0.33-0.75), mainly influenced by technical factors. Finally, we present a publicly available tool for peptide-level analysis of platform agreement and demonstrate its utility in clarifying cross-platform discrepancies in protein and proteoform measurements. Our findings provide insights for platform selection and study design, and highlight the value of combining mass spectrometry and affinity-based approaches for more comprehensive and reliable plasma proteome profiling.", "doi": "10.1038/s42004-025-01753-2", "pmid": "41188494", "labels": {"National Genomics Infrastructure": "Service", "NGI Proteomics": "Service", "NGI Uppsala (SNP&SEQ Technology Platform)": "Service", "Affinity Proteomics Stockholm": "Collaborative", "Affinity Proteomics Uppsala": "Collaborative", "Global Proteomics and Proteogenomics": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12586489"}, {"db": "pii", "key": "10.1038/s42004-025-01753-2"}], "notes": [], "created": "2025-11-07T07:35:27.214Z", "modified": "2025-11-27T13:03:30.885Z"}, {"entity": "publication", "iuid": "d393109fcd1c4ba9be1fc99ed851ad05", "links": {"self": {"href": "https://publications.scilifelab.se/publication/d393109fcd1c4ba9be1fc99ed851ad05.json"}, "display": {"href": "https://publications.scilifelab.se/publication/d393109fcd1c4ba9be1fc99ed851ad05"}}, "title": "In-depth patient-specific analysis of tumor heterogeneity in melanoma brain metastasis: Insights from spatial transcriptomics and multi-region bulk sequencing.", "authors": [{"family": "Sharma", "given": "Nidhi", "initials": "N", "orcid": "0000-0002-2475-9340", "researcher": {"href": "https://publications.scilifelab.se/researcher/eadc0f3bfb5443e8a14af7d785085324.json"}}, {"family": "R\u00e1jov\u00e1", "given": "Jana", "initials": "J"}, {"family": "Mermelekas", "given": "Georgios", "initials": "G"}, {"family": "Thrane", "given": "Kim", "initials": "K", "orcid": "0000-0003-3109-5551", "researcher": {"href": "https://publications.scilifelab.se/researcher/f1bd1b94e1694de9a5c27fd8f331dc86.json"}}, {"family": "Lundeberg", "given": "Joakim", "initials": "J", "orcid": "0000-0003-4313-1601", "researcher": {"href": "https://publications.scilifelab.se/researcher/4a4e6ca0f29b4ead8569e2729481c3e0.json"}}, {"family": "Shamikh", "given": "Alia", "initials": "A"}, {"family": "Vikstr\u00f6m", "given": "Sofi", "initials": "S"}, {"family": "Baba\u010di\u0107", "given": "Haris", "initials": "H", "orcid": "0000-0003-0813-0005", "researcher": {"href": "https://publications.scilifelab.se/researcher/45a1c5d3d2d34a9e96d112877632784c.json"}}, {"family": "Jensdottir", "given": "Margret", "initials": "M"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}, {"family": "Eriksson", "given": "Hanna", "initials": "H"}], "type": "journal article", "published": "2025-09-00", "journal": {"title": "Transl Oncol", "issn": "1936-5233", "volume": "59", "pages": "102468", "issn-l": null}, "abstract": "Melanoma brain metastases (MBM) exhibit extensive intertumor and intratumor heterogeneity (ITH), driven by a complex tumor microenvironment. The aim of this study was to perform a detailed analysis of individual MBM patient tumors using a multiomics approach, integrating spatial transcriptomics with multi-region bulk exome, proteome, and transcriptome profiling for a small group of four patient samples. We identified significant patient-specific variations in immune cell infiltration, particularly in B/plasma cells, myeloid cells, and cancer-associated fibroblasts (CAFs). Notably, immunotherapy-treated patients showed enriched pathways related to epithelial-mesenchymal transition (EMT), interferon-gamma (IFN-\u03b3) signaling, oxidative phosphorylation, T-cell signaling, inflammation and DNA damage, which aligned with distinct cellular compositions observed in the spatial analysis. We also uncovered considerable ITH, especially at the protein level, revealing differential expression patterns of key tumor and immune-related markers. The correlation between mRNA and protein data highlighted consistent enrichment of critical pathways across multiomics layers. These findings highlight the molecular and cellular landscape of individual patient MBM, underscoring the importance of addressing tumor heterogeneity in the development of effective therapeutic strategies.", "doi": "10.1016/j.tranon.2025.102468", "pmid": "40669378", "labels": {"NGI Short read": "Service", "National Genomics Infrastructure": "Service", "NGI Stockholm (Genomics Production)": "Service", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC12284558"}, {"db": "pii", "key": "S1936-5233(25)00199-8"}], "notes": [], "created": "2025-07-18T10:25:23.220Z", "modified": "2025-11-28T10:44:36.443Z"}, {"entity": "publication", "iuid": "de5f9b658ce74f6096b9c352ea946d5b", "links": {"self": {"href": "https://publications.scilifelab.se/publication/de5f9b658ce74f6096b9c352ea946d5b.json"}, "display": {"href": "https://publications.scilifelab.se/publication/de5f9b658ce74f6096b9c352ea946d5b"}}, "title": "SARS-CoV-2 and HSV-1 Induce Amyloid Aggregation in Human CSF Resulting in Drastic Soluble Protein Depletion.", "authors": [{"family": "Christ", "given": "Wanda", "initials": "W", "orcid": "0000-0003-3886-5248", "researcher": {"href": "https://publications.scilifelab.se/researcher/38fe3a44fdb547b885cce5b6f490b2bc.json"}}, {"family": "Kapell", "given": "Sebastian", "initials": "S", "orcid": "0000-0001-9304-558X", "researcher": {"href": "https://publications.scilifelab.se/researcher/cffd944f88e54ed6a910183ba49ef656.json"}}, {"family": "Sobkowiak", "given": "Michal J", "initials": "MJ", "orcid": "0000-0003-2932-1994", "researcher": {"href": "https://publications.scilifelab.se/researcher/14f1eb990edf472cac56f24d7cae330c.json"}}, {"family": "Mermelekas", "given": "Georgios", "initials": "G"}, {"family": "Evertsson", "given": "Bj\u00f6rn", "initials": "B"}, {"family": "Sork", "given": "Helena", "initials": "H", "orcid": "0000-0002-5390-4420", "researcher": {"href": "https://publications.scilifelab.se/researcher/f5d08dad4f2d4ee0a3e3a8f060383da5.json"}}, {"family": "Saher", "given": "Osama", "initials": "O"}, {"family": "Bazaz", "given": "Safa", "initials": "S"}, {"family": "Gustafsson", "given": "Oskar", "initials": "O"}, {"family": "Cardenas", "given": "Eduardo I", "initials": "EI"}, {"family": "Villa", "given": "Viviana", "initials": "V"}, {"family": "Ricciarelli", "given": "Roberta", "initials": "R"}, {"family": "Sandberg", "given": "Johan K", "initials": "JK", "orcid": "0000-0002-6275-0750", "researcher": {"href": "https://publications.scilifelab.se/researcher/7468c415a46645a3a4c3d28badcff954.json"}}, {"family": "Bergquist", "given": "Jonas", "initials": "J", "orcid": "0000-0002-4597-041X", "researcher": {"href": "https://publications.scilifelab.se/researcher/d745034529f3423abbea230b4e586d20.json"}}, {"family": "Sturchio", "given": "Andrea", "initials": "A"}, {"family": "Svenningsson", "given": "Per", "initials": "P", "orcid": "0000-0001-6727-3802", "researcher": {"href": "https://publications.scilifelab.se/researcher/5199496295334771ba3c5621a83a6f43.json"}}, {"family": "Malm", "given": "Tarja", "initials": "T", "orcid": "0000-0002-9530-7472", "researcher": {"href": "https://publications.scilifelab.se/researcher/c1ab3c9695424308b07c375901a089f4.json"}}, {"family": "Espay", "given": "Alberto J", "initials": "AJ"}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}, {"family": "Lind\u00e9n", "given": "Anders", "initials": "A"}, {"family": "Klingstr\u00f6m", "given": "Jonas", "initials": "J", "orcid": "0000-0001-9076-1441", "researcher": {"href": "https://publications.scilifelab.se/researcher/95c1b345ae434fb383b7fe6a1d053c80.json"}}, {"family": "El Andaloussi", "given": "Samir", "initials": "S", "orcid": "0000-0003-4468-9113", "researcher": {"href": "https://publications.scilifelab.se/researcher/bd1036a42043441da3e444f4eac58010.json"}}, {"family": "Ezzat", "given": "Kariem", "initials": "K", "orcid": "0000-0003-4186-0675", "researcher": {"href": "https://publications.scilifelab.se/researcher/6f2f1d3d8a5d467c8fc3b95388e4c606.json"}}], "type": "journal article", "published": "2024-11-20", "journal": {"title": "ACS Chem Neurosci", "issn": "1948-7193", "volume": "15", "issue": "22", "pages": "4095-4104", "issn-l": "1948-7193"}, "abstract": "The corona virus (SARS-CoV-2) pandemic and the resulting long-term neurological complications in patients, known as long COVID, have renewed interest in the correlation between viral infections and neurodegenerative brain disorders. While many viruses can reach the central nervous system (CNS) causing acute or chronic infections (such as herpes simplex virus 1, HSV-1), the lack of a clear mechanistic link between viruses and protein aggregation into amyloids, a characteristic of several neurodegenerative diseases, has rendered such a connection elusive. Recently, we showed that viruses can induce aggregation of purified amyloidogenic proteins via the direct physicochemical mechanism of heterogeneous nucleation (HEN). In the current study, we show that the incubation of HSV-1 and SARS-CoV-2 with human cerebrospinal fluid (CSF) leads to the amyloid aggregation of several proteins known to be involved in neurodegenerative diseases, such as APLP1 (amyloid \u03b2 precursor like protein 1), ApoE, clusterin, \u03b12-macroglobulin, PGK-1 (phosphoglycerate kinase 1), ceruloplasmin, nucleolin, 14-3-3, transthyretin, and vitronectin. Importantly, UV-inactivation of SARS-CoV-2 does not affect its ability to induce amyloid aggregation, as amyloid formation is dependent on viral surface catalysis via HEN and not its ability to replicate. Additionally, viral amyloid induction led to a dramatic drop in the soluble protein concentration in the CSF. Our results show that viruses can physically induce amyloid aggregation of proteins in human CSF and result in soluble protein depletion, thus providing a potential mechanism that may account for the association between persistent and latent/reactivating brain infections and neurodegenerative diseases.", "doi": "10.1021/acschemneuro.4c00636", "pmid": "39510798", "labels": {"Bioinformatics Support, Infrastructure and Training": "Collaborative", "Bioinformatics Support and Infrastructure": "Collaborative", "Global Proteomics and Proteogenomics": "Service", "Bioinformatics (NBIS)": "Collaborative"}, "xrefs": [], "notes": [], "created": "2024-11-15T09:02:02.653Z", "modified": "2025-04-07T07:30:58.294Z"}, {"entity": "publication", "iuid": "02b4484b67ba4dba84c7818fe780b0db", "links": {"self": {"href": "https://publications.scilifelab.se/publication/02b4484b67ba4dba84c7818fe780b0db.json"}, "display": {"href": "https://publications.scilifelab.se/publication/02b4484b67ba4dba84c7818fe780b0db"}}, "title": "Defining the Soluble and Extracellular Vesicle Protein Compartments of Plasma Using In-Depth Mass Spectrometry-Based Proteomics.", "authors": [{"family": "Sharma", "given": "Nidhi", "initials": "N", "orcid": "0000-0002-2475-9340", "researcher": {"href": "https://publications.scilifelab.se/researcher/eadc0f3bfb5443e8a14af7d785085324.json"}}, {"family": "Angori", "given": "Silvia", "initials": "S"}, {"family": "Sandberg", "given": "AnnSofi", "initials": "A"}, {"family": "Mermelekas", "given": "Georgios", "initials": "G"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J"}, {"family": "Wiklander", "given": "Oscar P B", "initials": "OPB"}, {"family": "G\u00f6rgens", "given": "Andr\u00e9", "initials": "A"}, {"family": "Andaloussi", "given": "Samir El", "initials": "SE"}, {"family": "Eriksson", "given": "Hanna", "initials": "H"}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}], "type": "journal article", "published": "2024-09-06", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "23", "issue": "9", "pages": "4114-4127", "issn-l": "1535-3893"}, "abstract": "Plasma-derived extracellular vesicles (pEVs) are a potential source of diseased biomarker proteins. However, characterizing the pEV proteome is challenging due to its relatively low abundance and difficulties in enrichment. This study presents a streamlined workflow to identify EV proteins from cancer patient plasma using minimal sample input. Starting with 400 \u03bcL of plasma, we generated a comprehensive pEV proteome using size exclusion chromatography (SEC) combined with HiRIEF prefractionation-based mass spectrometry (MS). First, we compared the performance of HiRIEF and long gradient MS workflows using control pEVs, quantifying 2076 proteins with HiRIEF. In a proof-of-concept study, we applied SEC-HiRIEF-MS to a small cohort (12) of metastatic lung adenocarcinoma (LUAD) and malignant melanoma (MM) patients. We also analyzed plasma samples from the same patients to study the relationship between plasma and pEV proteomes. We identified and quantified 1583 proteins in cancer pEVs and 1468 proteins in plasma across all samples. While there was substantial overlap, the pEV proteome included several unique EV markers and cancer-related proteins. Differential analysis revealed 30 DEPs in LUAD vs the MM group, highlighting the potential of pEVs as biomarkers. This work demonstrates the utility of a prefractionation-based MS for comprehensive pEV proteomics and EV biomarker discovery. Data are available via ProteomeXchange with the identifiers PXD039338 and PXD038528.", "doi": "10.1021/acs.jproteome.4c00490", "pmid": "39141927", "labels": {"Global Proteomics and Proteogenomics": "Service"}, "xrefs": [{"db": "pmc", "key": "PMC11385381"}], "notes": [], "created": "2024-11-27T13:00:28.165Z", "modified": "2024-11-27T13:00:28.406Z"}, {"entity": "publication", "iuid": "e100499748ca4919a43efecd22554d70", "links": {"self": {"href": "https://publications.scilifelab.se/publication/e100499748ca4919a43efecd22554d70.json"}, "display": {"href": "https://publications.scilifelab.se/publication/e100499748ca4919a43efecd22554d70"}}, "title": "Comprehensive proteomics and meta-analysis of COVID-19 host response.", "authors": [{"family": "Baba\u010di\u0107", "given": "Haris", "initials": "H", "orcid": "0000-0003-0813-0005", "researcher": {"href": "https://publications.scilifelab.se/researcher/45a1c5d3d2d34a9e96d112877632784c.json"}}, {"family": "Christ", "given": "Wanda", "initials": "W", "orcid": "0000-0003-3886-5248", "researcher": {"href": "https://publications.scilifelab.se/researcher/38fe3a44fdb547b885cce5b6f490b2bc.json"}}, {"family": "Ara\u00fajo", "given": "Jos\u00e9 Eduardo", "initials": "JE"}, {"family": "Mermelekas", "given": "Georgios", "initials": "G"}, {"family": "Sharma", "given": "Nidhi", "initials": "N"}, {"family": "Tynell", "given": "Janne", "initials": "J", "orcid": "0000-0001-6930-5230", "researcher": {"href": "https://publications.scilifelab.se/researcher/fb43fb2383e047679010f0969a115f2f.json"}}, {"family": "Garc\u00eda", "given": "Marina", "initials": "M", "orcid": "0000-0002-9130-3933", "researcher": {"href": "https://publications.scilifelab.se/researcher/20fa6d5f40764b32a70f792f29d97e60.json"}}, {"family": "Varnaite", "given": "Renata", "initials": "R"}, {"family": "Asgeirsson", "given": "Hilmir", "initials": "H", "orcid": "0000-0003-3869-8021", "researcher": {"href": "https://publications.scilifelab.se/researcher/dc2be98322a74715a21f56ce31217d84.json"}}, {"family": "Glans", "given": "Hedvig", "initials": "H"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Gredmark-Russ", "given": "Sara", "initials": "S"}, {"family": "Klingstr\u00f6m", "given": "Jonas", "initials": "J", "orcid": "0000-0001-9076-1441", "researcher": {"href": "https://publications.scilifelab.se/researcher/95c1b345ae434fb383b7fe6a1d053c80.json"}}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}], "type": "meta-analysis", "published": "2023-09-22", "journal": {"title": "Nat Commun", "issn": "2041-1723", "volume": "14", "issue": "1", "pages": "5921", "issn-l": "2041-1723"}, "abstract": "COVID-19 is characterised by systemic immunological perturbations in the human body, which can lead to multi-organ damage. Many of these processes are considered to be mediated by the blood. Therefore, to better understand the systemic host response to SARS-CoV-2 infection, we performed systematic analyses of the circulating, soluble proteins in the blood through global proteomics by mass-spectrometry (MS) proteomics. Here, we show that a large part of the soluble blood proteome is altered in COVID-19, among them elevated levels of interferon-induced and proteasomal proteins. Some proteins that have alternating levels in human cells after a SARS-CoV-2 infection in vitro and in different organs of COVID-19 patients are deregulated in the blood, suggesting shared infection-related changes.The availability of different public proteomic resources on soluble blood proteome alterations leaves uncertainty about the change of a given protein during COVID-19. Hence, we performed a systematic review and meta-analysis of MS global proteomics studies of soluble blood proteomes, including up to 1706 individuals (1039 COVID-19 patients), to provide concluding estimates for the alteration of 1517 soluble blood proteins in COVID-19. Finally, based on the meta-analysis we developed CoViMAPP, an open-access resource for effect sizes of alterations and diagnostic potential of soluble blood proteins in COVID-19, which is publicly available for the research, clinical, and academic community.", "doi": "10.1038/s41467-023-41159-z", "pmid": "37739942", "labels": {"Global Proteomics and Proteogenomics": "Collaborative"}, "xrefs": [{"db": "pmc", "key": "PMC10516886"}, {"db": "pii", "key": "10.1038/s41467-023-41159-z"}], "notes": [], "created": "2023-11-29T11:54:56.281Z", "modified": "2023-11-29T11:54:56.390Z"}, {"entity": "publication", "iuid": "f8f1bd2761014d26864a172065d24b3e", "links": {"self": {"href": "https://publications.scilifelab.se/publication/f8f1bd2761014d26864a172065d24b3e.json"}, "display": {"href": "https://publications.scilifelab.se/publication/f8f1bd2761014d26864a172065d24b3e"}}, "title": "Evaluation of Spin Columns for Human Plasma Depletion to Facilitate MS-Based Proteomics Analysis of Plasma.", "authors": [{"family": "Cao", "given": "Xiaofang", "initials": "X"}, {"family": "Sandberg", "given": "AnnSofi", "initials": "A", "orcid": "0000-0002-9681-3342", "researcher": {"href": "https://publications.scilifelab.se/researcher/fd34d8e107be4a87b60c8dc525277463.json"}}, {"family": "Ara\u00fajo", "given": "Jos\u00e9 Eduardo", "initials": "JE"}, {"family": "Cvetkovski", "given": "Filip", "initials": "F"}, {"family": "Berglund", "given": "Erik", "initials": "E"}, {"family": "Eriksson", "given": "Lars E", "initials": "LE"}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}], "type": "journal article", "published": "2021-09-03", "journal": {"title": "J. Proteome Res.", "issn": "1535-3907", "volume": "20", "issue": "9", "pages": "4610-4620", "issn-l": "1535-3893"}, "abstract": "High abundant protein depletion is a common strategy applied to increase analytical depth in global plasma proteomics experiment setups. The standard strategies for depletion of the highest abundant proteins currently rely on multiple-use HPLC columns or multiple-use spin columns. Here we evaluate the performance of single-use spin columns for plasma depletion and show that the single-use spin reduces handling time by allowing parallelization and is easily adapted to a nonspecialized lab environment without reducing the high plasma proteome coverage and reproducibility. In addition, we evaluate the effect of viral heat inactivation on the plasma proteome, an additional step in the plasma preparation workflow that allows the sample preparation of SARS-Cov2-infected samples to be performed in a BSL3 laboratory, and report the advantage of performing the heat inactivation postdepletion. We further show the possibility of expanding the use of the depletion column cross-species to macaque plasma samples. In conclusion, we report that single-use spin columns for high abundant protein depletion meet the requirements for reproducibly in in-depth plasma proteomics and can be applied on a common animal model while also reducing the sample handling time.", "doi": "10.1021/acs.jproteome.1c00378", "pmid": "34320313", "labels": {"Global Proteomics and Proteogenomics": "Technology development"}, "xrefs": [{"db": "pmc", "key": "PMC8419864"}], "notes": [], "created": "2021-12-10T07:05:27.995Z", "modified": "2023-06-19T12:53:14.140Z"}, {"entity": "publication", "iuid": "092a2fc7f73040e68081e9553c7bcf56", "links": {"self": {"href": "https://publications.scilifelab.se/publication/092a2fc7f73040e68081e9553c7bcf56.json"}, "display": {"href": "https://publications.scilifelab.se/publication/092a2fc7f73040e68081e9553c7bcf56"}}, "title": "Molecular evaluation of five different isolation methods for extracellular vesicles reveals different clinical applicability and subcellular origin.", "authors": [{"family": "Veerman", "given": "Rosanne E", "initials": "RE"}, {"family": "Teeuwen", "given": "Loes", "initials": "L"}, {"family": "Czarnewski", "given": "Paulo", "initials": "P", "orcid": "0000-0001-8150-4021", "researcher": {"href": "https://publications.scilifelab.se/researcher/b84309de4e3946159c374ffa6d977560.json"}}, {"family": "G\u00fccl\u00fcler Akpinar", "given": "G\u00f6zde", "initials": "G"}, {"family": "Sandberg", "given": "AnnSofi", "initials": "A", "orcid": "0000-0002-9681-3342", "researcher": {"href": "https://publications.scilifelab.se/researcher/fd34d8e107be4a87b60c8dc525277463.json"}}, {"family": "Cao", "given": "Xiaofang", "initials": "X"}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}, {"family": "Orre", "given": "Lukas M", "initials": "LM", "orcid": "0000-0002-0384-1003", "researcher": {"href": "https://publications.scilifelab.se/researcher/7b4e49a93b0143db88059c4d1e9fdc59.json"}}, {"family": "Gabrielsson", "given": "Susanne", "initials": "S", "orcid": "0000-0003-1771-1346", "researcher": {"href": "https://publications.scilifelab.se/researcher/1d446cb52d7e4a01ad8478a9cfe22ae1.json"}}, {"family": "Eldh", "given": "Maria", "initials": "M", "orcid": "0000-0003-2173-1796", "researcher": {"href": "https://publications.scilifelab.se/researcher/61b27da9f7184beab8c9a6d358a2c4df.json"}}], "type": "journal article", "published": "2021-07-00", "journal": {"title": "J Extracell Vesicles", "issn": "2001-3078", "volume": "10", "issue": "9", "pages": "e12128", "issn-l": "2001-3078"}, "abstract": "Extracellular vesicles (EVs) are increasingly tested as therapeutic vehicles and biomarkers, but still EV subtypes are not fully characterised. To isolate EVs with few co-isolated entities, a combination of methods is needed. However, this is time-consuming and requires large sample volumes, often not feasible in most clinical studies or in studies where small sample volumes are available. Therefore, we compared EVs rendered by five commonly used methods based on different principles from conditioned cell medium and 250 \u03bcl or 3 ml plasma, that is, precipitation (ExoQuick ULTRA), membrane affinity (exoEasy Maxi Kit), size-exclusion chromatography (qEVoriginal), iodixanol gradient (OptiPrep), and phosphatidylserine affinity (MagCapture). EVs were characterised by electron microscopy, Nanoparticle Tracking Analysis, Bioanalyzer, flow cytometry, and LC-MS/MS. The different methods yielded samples of different morphology, particle size, and proteomic profile. For the conditioned medium, Izon 35 isolated the highest number of EV proteins followed by exoEasy, which also isolated fewer non-EV proteins. For the plasma samples, exoEasy isolated a high number of EV proteins and few non-EV proteins, while Izon 70 isolated the most EV proteins. We conclude that no method is perfect for all studies, rather, different methods are suited depending on sample type and interest in EV subtype, in addition to sample volume and budget.", "doi": "10.1002/jev2.12128", "pmid": "34322205", "labels": {"Bioinformatics Support, Infrastructure and Training": "Collaborative", "Bioinformatics Long-term Support WABI": "Collaborative", "Global Proteomics and Proteogenomics": "Technology development", "Bioinformatics Support for Computational Resources": "Service", "Bioinformatics (NBIS)": "Collaborative"}, "xrefs": [{"db": "pii", "key": "JEV212128"}, {"db": "pmc", "key": "PMC8298890"}], "notes": [], "created": "2021-09-10T08:46:39.753Z", "modified": "2024-01-16T13:48:39.263Z"}, {"entity": "publication", "iuid": "aa033e622fbc43ffb6090c29ba97d1a8", "links": {"self": {"href": "https://publications.scilifelab.se/publication/aa033e622fbc43ffb6090c29ba97d1a8.json"}, "display": {"href": "https://publications.scilifelab.se/publication/aa033e622fbc43ffb6090c29ba97d1a8"}}, "title": "The viral protein corona directs viral pathogenesis and amyloid aggregation.", "authors": [{"family": "Ezzat", "given": "Kariem", "initials": "K", "orcid": "0000-0003-4186-0675", "researcher": {"href": "https://publications.scilifelab.se/researcher/6f2f1d3d8a5d467c8fc3b95388e4c606.json"}}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}, {"family": "P\u00e5lsson", "given": "Sandra", "initials": "S"}, {"family": "Roberts", "given": "Thomas C", "initials": "TC"}, {"family": "J\u00e4rver", "given": "Peter", "initials": "P"}, {"family": "Dondalska", "given": "Aleksandra", "initials": "A"}, {"family": "Bestas", "given": "Burcu", "initials": "B"}, {"family": "Sobkowiak", "given": "Michal J", "initials": "MJ"}, {"family": "Lev\u00e4nen", "given": "Bettina", "initials": "B"}, {"family": "Sk\u00f6ld", "given": "Magnus", "initials": "M"}, {"family": "Thompson", "given": "Elizabeth A", "initials": "EA"}, {"family": "Saher", "given": "Osama", "initials": "O"}, {"family": "Kari", "given": "Otto K", "initials": "OK"}, {"family": "Lajunen", "given": "Tatu", "initials": "T", "orcid": "0000-0001-6234-9193", "researcher": {"href": "https://publications.scilifelab.se/researcher/55d9cb27b0734ca496514762ed1627f0.json"}}, {"family": "Sverremark Ekstr\u00f6m", "given": "Eva", "initials": "E", "orcid": "0000-0001-6271-8681", "researcher": {"href": "https://publications.scilifelab.se/researcher/d7519ea4bf1f43dcab124c3d62b489db.json"}}, {"family": "Nilsson", "given": "Caroline", "initials": "C"}, {"family": "Ishchenko", "given": "Yevheniia", "initials": "Y"}, {"family": "Malm", "given": "Tarja", "initials": "T"}, {"family": "Wood", "given": "Matthew J A", "initials": "MJA"}, {"family": "Power", "given": "Ultan F", "initials": "UF", "orcid": "0000-0003-3246-3774", "researcher": {"href": "https://publications.scilifelab.se/researcher/e0d135555da74520a0d4b7733cd6ddd7.json"}}, {"family": "Masich", "given": "Sergej", "initials": "S"}, {"family": "Lind\u00e9n", "given": "Anders", "initials": "A"}, {"family": "Sandberg", "given": "Johan K", "initials": "JK", "orcid": "0000-0002-6275-0750", "researcher": {"href": "https://publications.scilifelab.se/researcher/7468c415a46645a3a4c3d28badcff954.json"}}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Spetz", "given": "Anna-Lena", "initials": "AL", "orcid": "0000-0003-3964-9512", "researcher": {"href": "https://publications.scilifelab.se/researcher/70270e32d48d486799cc9dd61e36a4f1.json"}}, {"family": "El Andaloussi", "given": "Samir", "initials": "S"}], "type": "journal article", "published": "2019-05-27", "journal": {"volume": "10", "issn": "2041-1723", "issue": "1", "pages": "2331", "title": "Nat Commun", "issn-l": "2041-1723"}, "abstract": "Artificial nanoparticles accumulate a protein corona layer in biological fluids, which significantly influences their bioactivity. As nanosized obligate intracellular parasites, viruses share many biophysical properties with artificial nanoparticles in extracellular environments and here we show that respiratory syncytial virus (RSV) and herpes simplex virus type 1 (HSV-1) accumulate a rich and distinctive protein corona in different biological fluids. Moreover, we show that corona pre-coating differentially affects viral infectivity and immune cell activation. In addition, we demonstrate that viruses bind amyloidogenic peptides in their corona and catalyze amyloid formation via surface-assisted heterogeneous nucleation. Importantly, we show that HSV-1 catalyzes the aggregation of the amyloid \u03b2-peptide (A\u03b242), a major constituent of amyloid plaques in Alzheimer's disease, in vitro and in animal models. Our results highlight the viral protein corona as an acquired structural layer that is critical for viral-host interactions and illustrate a mechanistic convergence between viral and amyloid pathologies.", "doi": "10.1038/s41467-019-10192-2", "pmid": "31133680", "labels": {"Global Proteomics and Proteogenomics": "Technology development", "Bioinformatics Support for Computational Resources": "Service"}, "xrefs": [{"db": "pii", "key": "10.1038/s41467-019-10192-2"}, {"db": "pmc", "key": "PMC6536551"}], "notes": [], "created": "2020-01-07T12:31:23.818Z", "modified": "2024-01-16T13:48:44.332Z"}, {"entity": "publication", "iuid": "9e94dfa9b92d448eabccf47bb68156e2", "links": {"self": {"href": "https://publications.scilifelab.se/publication/9e94dfa9b92d448eabccf47bb68156e2.json"}, "display": {"href": "https://publications.scilifelab.se/publication/9e94dfa9b92d448eabccf47bb68156e2"}}, "title": "Ultrasensitive Immunoprofiling of Plasma Extracellular Vesicles Identifies Syndecan-1 as a Potential Tool for Minimally Invasive Diagnosis of Glioma.", "authors": [{"family": "Indira Chandran", "given": "Vineesh", "initials": "V"}, {"family": "Welinder", "given": "Charlotte", "initials": "C", "orcid": "0000-0001-9626-0576", "researcher": {"href": "https://publications.scilifelab.se/researcher/924dc427398e4ba7b31eb5b4b47a89ca.json"}}, {"family": "M\u00e5nsson", "given": "Ann-Sofie", "initials": "AS"}, {"family": "Offer", "given": "Svenja", "initials": "S"}, {"family": "Freyhult", "given": "Eva", "initials": "E", "orcid": "0000-0003-0226-1047", "researcher": {"href": "https://publications.scilifelab.se/researcher/be110f11a53d4dcfa3bfd1657167895e.json"}}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}, {"family": "Lund", "given": "Sigrid M", "initials": "SM"}, {"family": "Pedersen", "given": "Shona", "initials": "S", "orcid": "0000-0001-6636-0293", "researcher": {"href": "https://publications.scilifelab.se/researcher/0c9565eb33bc4f15bdefeb1e796a728f.json"}}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Marko-Varga", "given": "Gyorgy", "initials": "G"}, {"family": "Johansson", "given": "Maria C", "initials": "MC"}, {"family": "Englund", "given": "Elisabet", "initials": "E", "orcid": "0000-0002-2708-2443", "researcher": {"href": "https://publications.scilifelab.se/researcher/8c98fa2b2e7e4e318cd00eb1e8e3ac7a.json"}}, {"family": "Sundgren", "given": "Pia C", "initials": "PC", "orcid": "0000-0001-9237-1236", "researcher": {"href": "https://publications.scilifelab.se/researcher/e7c755205abb4ecfabb3d5f021b7a1f6.json"}}, {"family": "Belting", "given": "Mattias", "initials": "M"}], "type": "journal article", "published": "2019-05-15", "journal": {"volume": "25", "issn": "1557-3265", "issue": "10", "title": "Clin. Cancer Res.", "pages": "3115-3127", "issn-l": "1078-0432"}, "abstract": "Liquid biopsy has great potential to improve the management of brain tumor patients at high risk of surgery-associated complications. Here, the aim was to explore plasma extracellular vesicle (plEV) immunoprofiling as a tool for noninvasive diagnosis of glioma.\n\nPlEV isolation and analysis were optimized using advanced mass spectrometry, nanoparticle tracking analysis, and electron microscopy. We then established a new procedure that combines size exclusion chromatography isolation and proximity extension assay-based ultrasensitive immunoprofiling of plEV proteins that was applied on a well-defined glioma study cohort (n = 82).\n\nAmong potential candidates, we for the first time identify syndecan-1 (SDC1) as a plEV constituent that can discriminate between high-grade glioblastoma multiforme (GBM, WHO grade IV) and low-grade glioma [LGG, WHO grade II; area under the ROC curve (AUC): 0.81; sensitivity: 71%; specificity: 91%]. These findings were independently validated by ELISA. Tumor SDC1 mRNA expression similarly discriminated between GBM and LGG in an independent glioma patient population from The Cancer Genome Atlas cohort (AUC: 0.91; sensitivity: 79%; specificity: 91%). In experimental studies with GBM cells, we show that SDC1 is efficiently sorted to secreted EVs. Importantly, we found strong support of plEVSDC1 originating from GBM tumors, as plEVSDC1 correlated with SDC1 protein expression in matched patient tumors, and plEVSDC1 was decreased postoperatively depending on the extent of surgery.\n\nOur studies support the concept of circulating plEVs as a tool for noninvasive diagnosis and monitoring of gliomas and should move this field closer to the goal of improving the management of cancer patients.", "doi": "10.1158/1078-0432.CCR-18-2946", "pmid": "30679164", "labels": {"Bioinformatics Support, Infrastructure and Training": "Collaborative", "Bioinformatics Support and Infrastructure": "Collaborative", "Global Proteomics and Proteogenomics": "Technology development", "Structural Proteomics": "Service", "Bioinformatics (NBIS)": "Collaborative"}, "xrefs": [{"db": "pii", "key": "1078-0432.CCR-18-2946"}], "notes": [], "created": "2019-02-01T09:02:21.138Z", "modified": "2021-07-08T11:26:52.783Z"}, {"entity": "publication", "iuid": "481f7584fddd4db2a5d9f3833a7ed7e8", "links": {"self": {"href": "https://publications.scilifelab.se/publication/481f7584fddd4db2a5d9f3833a7ed7e8.json"}, "display": {"href": "https://publications.scilifelab.se/publication/481f7584fddd4db2a5d9f3833a7ed7e8"}}, "title": "Silencing FLI or targeting CD13/ANPEP lead to dephosphorylation of EPHA2, a mediator of BRAF inhibitor resistance, and induce growth arrest or apoptosis in melanoma cells.", "authors": [{"family": "Azimi", "given": "Alireza", "initials": "A"}, {"family": "Tuominen", "given": "Rainer", "initials": "R"}, {"family": "Costa Svedman", "given": "Fernanda", "initials": "F"}, {"family": "Caramuta", "given": "Stefano", "initials": "S"}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}, {"family": "Frostvik Stolt", "given": "Marianne", "initials": "M"}, {"family": "Kanter", "given": "Lena", "initials": "L"}, {"family": "Kharaziha", "given": "Pedram", "initials": "P"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Hertzman Johansson", "given": "Carolina", "initials": "C"}, {"family": "H\u00f6iom", "given": "Veronica", "initials": "V"}, {"family": "Hansson", "given": "Johan", "initials": "J"}, {"family": "Egyhazi Brage", "given": "Suzanne", "initials": "S", "orcid": "0000-0002-0524-2346", "researcher": {"href": "https://publications.scilifelab.se/researcher/40eddeacb66f490089dbf72978d20721.json"}}], "type": "journal article", "published": "2017-08-31", "journal": {"volume": "8", "issn": "2041-4889", "issue": "8", "pages": "e3029", "title": "Cell Death Dis", "issn-l": "2041-4889"}, "abstract": "A majority of patients with BRAF-mutated metastatic melanoma respond to therapy with BRAF inhibitors (BRAFi), but relapses are common owing to acquired resistance. To unravel BRAFi resistance mechanisms we have performed gene expression and mass spectrometry based proteome profiling of the sensitive parental A375 BRAF V600E-mutated human melanoma cell line and of daughter cell lines with induced BRAFi resistance. Increased expression of two novel resistance candidates, aminopeptidase-N (CD13/ANPEP) and ETS transcription factor FLI1 was observed in the BRAFi-resistant daughter cell lines. In addition, increased levels of the previously reported resistance mediators, receptor tyrosine kinase ephrine receptor A2 (EPHA2) and the hepatocyte growth factor receptor MET were also identified. The expression of these proteins was assessed in matched tumor samples from melanoma patients obtained before BRAFi and after disease progression. MET was overexpressed in all progression samples while the expression of the other candidates varied between the individual patients. Targeting CD13/ANPEP by a blocking antibody induced apoptosis in both parental A375- and BRAFi-resistant daughter cells as well as in melanoma cells with intrinsic BRAFi resistance and led to dephosphorylation of EPHA2 on S897, previously demonstrated to cause inhibition of the migratory capacity. AKT and RSK, both reported to induce EPHA2 S897 phosphorylation, were also dephosphorylated after inhibition of CD13/ANPEP. FLI1 silencing also caused decreases in EPHA2 S897 phosphorylation and in total MET protein expression. In addition, silencing of FLI1 sensitized the resistant cells to BRAFi. Furthermore, we show that BRAFi in combination with the multi kinase inhibitor dasatinib can abrogate BRAFi resistance and decrease both EPHA2 S897 phosphorylation and total FLI1 protein expression. This is the first report presenting CD13/ANPEP and FLI1 as important mediators of resistance to BRAF inhibition with potential as drug targets in BRAFi refractory melanoma.", "doi": "10.1038/cddis.2017.406", "pmid": "29048432", "labels": {"NGI Uppsala (Uppsala Genome Center)": "Service", "Clinical Proteomics Mass spectrometry": "Service", "NGI Stockholm (Genomics Applications)": "Service", "NGI Stockholm (Genomics Production)": "Service", "National Genomics Infrastructure": "Service", "Global Proteomics and Proteogenomics": "Service"}, "xrefs": [{"db": "pii", "key": "cddis2017406"}, {"db": "pmc", "key": "PMC5596587"}], "notes": [], "created": "2017-10-17T07:53:20.719Z", "modified": "2021-07-08T11:36:54.639Z"}, {"entity": "publication", "iuid": "a70aaaa7899f4e879e6ae51fb735c04a", "links": {"self": {"href": "https://publications.scilifelab.se/publication/a70aaaa7899f4e879e6ae51fb735c04a.json"}, "display": {"href": "https://publications.scilifelab.se/publication/a70aaaa7899f4e879e6ae51fb735c04a"}}, "title": "Identifying and Assessing Interesting Subgroups in a Heterogeneous Population.", "authors": [{"family": "Lee", "given": "Woojoo", "initials": "W"}, {"family": "Alexeyenko", "given": "Andrey", "initials": "A"}, {"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}, {"family": "Guegan", "given": "Justine", "initials": "J"}, {"family": "Dessen", "given": "Philippe", "initials": "P"}, {"family": "Lazar", "given": "Vladimir", "initials": "V"}, {"family": "Lehti\u00f6", "given": "Janne", "initials": "J", "orcid": "0000-0002-8100-9562", "researcher": {"href": "https://publications.scilifelab.se/researcher/8406a97bac744a59b1bc951978994581.json"}}, {"family": "Pawitan", "given": "Yudi", "initials": "Y"}], "type": "journal article", "published": "2015-08-03", "journal": {"volume": "2015", "issn": "2314-6141", "issue": null, "pages": "462549", "title": "Biomed Res Int", "issn-l": "2314-6133"}, "abstract": "Biological heterogeneity is common in many diseases and it is often the reason for therapeutic failures. Thus, there is great interest in classifying a disease into subtypes that have clinical significance in terms of prognosis or therapy response. One of the most popular methods to uncover unrecognized subtypes is cluster analysis. However, classical clustering methods such as k-means clustering or hierarchical clustering are not guaranteed to produce clinically interesting subtypes. This could be because the main statistical variability--the basis of cluster generation--is dominated by genes not associated with the clinical phenotype of interest. Furthermore, a strong prognostic factor might be relevant for a certain subgroup but not for the whole population; thus an analysis of the whole sample may not reveal this prognostic factor. To address these problems we investigate methods to identify and assess clinically interesting subgroups in a heterogeneous population. The identification step uses a clustering algorithm and to assess significance we use a false discovery rate- (FDR-) based measure. Under the heterogeneity condition the standard FDR estimate is shown to overestimate the true FDR value, but this is remedied by an improved FDR estimation procedure. As illustrations, two real data examples from gene expression studies of lung cancer are provided.", "doi": "10.1155/2015/462549", "pmid": "26339613", "labels": {"Bioinformatics Support, Infrastructure and Training": null, "Bioinformatics Support and Infrastructure": null, "Bioinformatics (NBIS)": null}, "xrefs": [{"db": "pmc", "key": "PMC4539210"}], "notes": [], "created": "2017-05-02T12:57:46.628Z", "modified": "2021-07-08T11:36:54.648Z"}, {"entity": "publication", "iuid": "2e1fe44fabcf483abdd700396ed83d4e", "links": {"self": {"href": "https://publications.scilifelab.se/publication/2e1fe44fabcf483abdd700396ed83d4e.json"}, "display": {"href": "https://publications.scilifelab.se/publication/2e1fe44fabcf483abdd700396ed83d4e"}}, "title": "Narrow-range peptide isoelectric focusing as peptide prefractionation method prior to tandem mass spectrometry analysis.", "authors": [{"family": "Pernemalm", "given": "Maria", "initials": "M", "orcid": "0000-0003-4624-031X", "researcher": {"href": "https://publications.scilifelab.se/researcher/f15f303cb2044cfa81719700137e3603.json"}}], "type": "journal article", "published": "2013-06-15", "journal": {"volume": "1023", "issn": "1940-6029", "issue": null, "pages": "3-11", "title": "Methods Mol. Biol.", "issn-l": "1064-3745"}, "abstract": "High sample complexity is one of the major challenges in mass spectrometry-based proteomics today. Despite massive improvement in instrumentation, sample prefractionation is still needed to reduce sample complexity and improve proteome coverage. Isoelectric focusing (IEF) has been traditionally used as a first-dimension protein separation technique in two-dimensional gel electrophoresis-based proteomics. Recently, peptide IEF has emerged as appealing alternative for anion exchange chromatography in multidimensional LC-MS/MS workflows. The rationale behind using narrow-range peptide isoelectric focusing as a prefractionation method prior to ms/ms is to reduce the complexity induced by tryptic digestion. This is done by selectively analyzing a sub-fraction of peptides with an acidic pI. The pI range is chosen as it has previously been shown that 96 % of human proteins have at least one tryptic peptide between pH 3.4 and 4.9. This ensures high proteome coverage while reducing the number of peptides with 2/3. In addition the focusing precision is optimal in this range. Therefore, by analyzing this sub-fraction of peptides the complexity of the sample can be reduced without significant loss of proteome coverage. As the theoretical pI of peptides can be calculated, the pI of the identified peptides can be used to validate the peptide sequence (identified peptides with pI outside the pH range 3.4-4.9 are more likely to be false positives). In addition, this approach is compatible with iTRAQ labelling as the different iTRAQ labels migrate similarly in IEF.", "doi": "10.1007/978-1-4614-7209-4_1", "pmid": "23765616", "labels": {"Clinical Proteomics Mass spectrometry": null}, "xrefs": [], "notes": [], "created": "2017-05-04T15:03:24.100Z", "modified": "2021-07-08T11:36:54.632Z"}]}