| 1. |
- Moussa, Ehab, et al.
(author)
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Proteomic profiling of the brain of mice with experimental cerebral malaria
- 2018
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In: Journal of Proteomics. - : Elsevier BV. - 1874-3919 .- 1876-7737. ; 180, s. 61-69
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Journal article (peer-reviewed)abstract
- Cerebral malaria (CM) is a severe neurological complication of malaria infection in both adults and children. In pursuit of effective treatment of CM, clinical studies, postmortem analysis and animal models have been employed to understand the pathology and identify effective interventions. In this study, a shotgun proteomics analysis was conducted to profile the proteomic signature of the brain tissue of mice with experimental cerebral malaria (ECM) in order to further understand the underlying pathology. To identify CM-associated response, proteomic signatures of the brains of C57/Bl6N mice infected with P. berghei ANKA that developed neurological syndrome were compared to those of mice infected with P. berghei NK65 that developed equally high parasite burdens without neurological signs, and to those of non-infected mice. The results show that the CM-associated response in mice that developed neurological signs comprise mainly acute-phase reaction and coagulation cascade activation, and indicate the leakage of plasma proteins into the brain parenchyma. SIGNIFICANCE: Cerebral malaria (CM) remains a major cause of death in children. The majority of these deaths occur in sub-Saharan Africa. Even with adequate access to treatment, mortality remains high and neurological sequelae can be found in up to 20% of survivors. No adjuvant treatment to date has been shown to reduce mortality and the pathophysiology of CM is largely unknown. Experimental cerebral malaria (ECM) is a well-established model that may contribute to identify and test druggable targets. In this study we have identified the disruption of the blood-brain barrier following inflammatory and vascular injury as a mechanism of disease. In this study we report a number of proteins that could be validated as potential biomarkers of ECM. Further studies, will be required to validate the clinical relevance of these biomarkers in human CM.
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| 2. |
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| 3. |
- Alreshidi, M. M., et al.
(author)
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Metabolomic and proteomic responses of Staphylococcus aureus to prolonged cold stress
- 2015
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In: Journal of Proteomics. - : Elsevier BV. - 1874-3919. ; 121, s. 44-55
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Journal article (peer-reviewed)abstract
- The high pathogenicity of Staphylococcus aureus is thought to be due to its extraordinary capacity to rapidly adapt to changes in environmental conditions. This study was carried out to investigate whether the cytoplasmic profiles of metabolites and proteins of Staphylococcus aureus were altered in response to prolonged exposure to cold stress. Metabolic profiling and proteomics were used to characterise alterations in cytoplasmic proteins and metabolites in cells from the mid-exponential phase of growth under ideal conditions at 37 degrees C and compared with equivalent cells exposed to prolonged cold stress for 2 weeks at 4 degrees C. Principle component analysis (PCA) of the metabolomic and proteomic data indicated that, at the mid-exponential phase of growth, prolonged cold stress conditions generated cells with different metabolite and protein profiles compared with those grown at 37 degrees C. Nine ribosomal proteins and citric acid were substantially elevated in the cytoplasmic fractions from the cells adapted to cold-stress but most amino acids showed a reduction in their concentration in cold-stressed samples. The data provided strong evidence supporting the hypothesis that specific changes in metabolic homeostasis and protein composition were critical to the adaptive processes required for survival under cold stress. Work in our laboratory has shown that prolonged exposure of Staphylococcus aureus to cold stress can result in the formation of small colony variants (SCVs) associated with significant alterations in the cell wall composition [8]. Further studies revealed that Staphylococcus aureus altered cell size and cell wall thickness in response to exposure to cold temperatures, alterations in pH and exposure to antibiotics [10]. The current study has utilised the prolonged exposure to cold stress as a model system to explore changes in the proteome and associated metabolic homeostasis following environmental challenges. The study provides an improved understanding of how Staphylococcus aureus adapts to the changing environment whilst in transition between human hosts. The results indicated an unexpected production of 9 ribosomal proteins and citric acid in response to cold stress suggesting specific survival roles for these proteins and citric acid as an adaptation mechanism for empowering survival under these conditions. Crown Copyright (C) 2015 Published by Elsevier B.V. All rights reserved.
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| 4. |
- Andersson, Björn, 1977, et al.
(author)
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Protein profiling identified dissociations between growth hormone-mediated longitudinal growth and bone mineralization in short prepubertal children
- 2011
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In: Journal of Proteomics. - : Elsevier BV. - 1876-7737 .- 1874-3919. ; 74:1
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Journal article (peer-reviewed)abstract
- Growth hormone (GH) promotes longitudinal growth and bone mineralization. In this study, a proteomic approach was used to analyze the association between serum protein expression pattern and height-adjusted bone mineralization in short prepubertal children receiving GH treatment. Patterns of protein expression were compared with those associated with longitudinal bone growth. Specific protein expression patterns associated with changes in height-adjusted bone mineralization in response to GH treatment were identified. Out of the 37 peaks found in significant regression models, 27 were uniquely present in models correlated with changes in bone mineralization and 7 peaks were uniquely present in models correlated with changes in height. The peaks identified corresponded to apolipoproteins, transthyretin, serum amyloid A4 and hemoglobin beta. We conclude that a proteomic approach could be used to identify specific protein expression patterns associated with bone mineralization in response to GH treatment and that height-adjusted bone mineralization and longitudinal bone growth are regulated partly by the same and partly by different mechanisms. Protein isoforms with different post-translational modifications might be of importance in the regulation of these processes. However, further validation is needed to assess the clinical significance of the results.
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| 5. |
- Artemenko, Konstantin, et al.
(author)
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A proteomic approach to monitor the dynamic response of the female oviductal epithelial cell surface to male gametes
- 2015
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In: Journal of Proteomics. - : Elsevier BV. - 1874-3919 .- 1876-7737. ; 113, s. 1-14
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Journal article (peer-reviewed)abstract
- UNLABELLED: Sophisticated strategies to analyze cell surface proteins are indispensable to study fundamental biological processes, such as the response of cells to environmental changes or cell-cell communication. Herein, we describe a refined mass spectrometry-based approach for the specific characterization and quantitation of cell surface proteins expressed in the female reproductive tract. The strategy is based on in situ biotinylation of rabbit oviducts, affinity enrichment of surface exposed biotin tagged proteins and dimethyl labeling of the obtained tryptic peptides followed by LC-MS/MS analysis. This approach proved to be sensitive enough to analyze small sample amounts (<1mug) and allowed further to trace the dynamic composition of the surface proteome of the oviductal epithelium in response to male gametes. The relative protein expression ratios of 175 proteins were quantified. Thirty-one of them were found to be altered over time, namely immediately, 1h and 2h after insemination compared to the time-matched control groups. Functional analysis demonstrated that structural reorganization of the oviductal epithelial cell surface was involved in the early response of the female organ to semen. In summary, this study outlines a workflow that is capable to monitor alterations in the female oviduct that are related to key reproductive processes in vivo. BIOLOGICAL SIGNIFICANCE: The proper interaction between the female reproductive tract, in particular, the oviduct and the male gametes, is fundamental to fertilization and embryonic development under physiological conditions. Thereby the oviductal epithelial cell surface proteins play an important role. Besides their direct interaction with male gametes, these molecules participate in signal transduction and, thus, are involved in the mandatory cellular response of the oviductal epithelium. In this study we present a refined LC-MS/MS based workflow that is capable to quantitatively analyze the expression of oviductal epithelial cell surface proteins in response to insemination in vivo. A special focus was on the very early interaction between the female organ and the male gametes. At first, this study clearly revealed an immediate response of the surface proteome to semen, which was modulated over time. The described methodology can be applied for studies of further distinct biological events in the oviduct and therefore contribute to a deeper insight into the formation of new life.
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| 6. |
- Audain, Enrique, et al.
(author)
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In-depth analysis of protein inference algorithms using multiple search engines and well-defined metrics
- 2017
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In: Journal of Proteomics. - : Elsevier BV. - 1874-3919. ; 150, s. 170-182
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Journal article (peer-reviewed)abstract
- In mass spectrometry-based shotgun proteomics, protein identifications are usually the desired result. However, most of the analytical methods are based on the identification of reliable peptides and not the direct identification of intact proteins. Thus, assembling peptides identified from tandem mass spectra into a list of proteins, referred to as protein inference, is a critical step in proteomics research. Currently, different protein inference algorithms and tools are available for the proteomics community. Here, we evaluated five software tools for protein inference (PIA, ProteinProphet, Fido, ProteinLP, MSBayesPro) using three popular database search engines: Mascot, X!Tandem, and MS-GF +. All the algorithms were evaluated using a highly customizable KNIME workflow using four different public datasets with varying complexities (different sample preparation, species and analytical instruments). We defined a set of quality control metrics to evaluate the performance of each combination of search engines, protein inference algorithm, and parameters on each dataset. We show that the results for complex samples vary not only regarding the actual numbers of reported protein groups but also concerning the actual composition of groups. Furthermore, the robustness of reported proteins when using databases of differing complexities is strongly dependant on the applied inference algorithm. Finally, merging the identifications of multiple search engines does not necessarily increase the number of reported proteins, but does increase the number of peptides per protein and thus can generally be recommended. Significance Protein inference is one of the major challenges in MS-based proteomics nowadays. Currently, there are a vast number of protein inference algorithms and implementations available for the proteomics community. Protein assembly impacts in the final results of the research, the quantitation values and the final claims in the research manuscript. Even though protein inference is a crucial step in proteomics data analysis, a comprehensive evaluation of the many different inference methods has never been performed. Previously Journal of proteomics has published multiple studies about other benchmark of bioinformatics algorithms (PMID: 26585461; PMID: 22728601) in proteomics studies making clear the importance of those studies for the proteomics community and the journal audience. This manuscript presents a new bioinformatics solution based on the KNIME/OpenMS platform that aims at providing a fair comparison of protein inference algorithms (https://github.com/KNIME-OMICS). Six different algorithms - ProteinProphet, MSBayesPro, ProteinLP, Fido and PIA- were evaluated using the highly customizable workflow on four public datasets with varying complexities. Five popular database search engines Mascot, X!Tandem, MS-GF + and combinations thereof were evaluated for every protein inference tool. In total > 186 proteins lists were analyzed and carefully compare using three metrics for quality assessments of the protein inference results: 1) the numbers of reported proteins, 2) peptides per protein, and the 3) number of uniquely reported proteins per inference method, to address the quality of each inference method. We also examined how many proteins were reported by choosing each combination of search engines, protein inference algorithms and parameters on each dataset. The results show that using 1) PIA or Fido seems to be a good choice when studying the results of the analyzed workflow, regarding not only the reported proteins and the high-quality identifications, but also the required runtime. 2) Merging the identifications of multiple search engines gives almost always more confident results and increases the number of peptides per protein group. 3) The usage of databases containing not only the canonical, but also known isoforms of proteins has a small impact on the number of reported proteins. The detection of specific isoforms could, concerning the question behind the study, compensate for slightly shorter reports using the parsimonious reports. 4) The current workflow can be easily extended to support new algorithms and search engine combinations.
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| 7. |
- Azimzadeh, Omid, et al.
(author)
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Label-free protein profiling of formalin-fixed paraffin-embedded (FFPE) heart tissue reveals immediatemitochondrial impairment after ionising radiation
- 2012
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In: Journal of Proteomics. - : Elsevier BV. - 1874-3919 .- 1876-7737. ; 75:8, s. 2384-2395
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Journal article (peer-reviewed)abstract
- Qualitative proteome profiling of formalin-fixed, paraffin-embedded (FFPE) tissue is advancing the field of clinical proteomics. However, quantitative proteome analysis of FFPE tissue is hampered by the lack of an efficient labelling method. The usage of conventional protein labelling on FFPE tissue has turned out to be inefficient. Classical labelling targets lysine residues that are blocked by the formalin treatment. The aim of this study was to establish a quantitative proteomics analysis of FFPE tissue by combining the label-free approach with optimised protein extraction and separation conditions. As a model system we used FFPE heart tissue of control and exposed C57BL/6 mice after total body irradiation using a gamma ray dose of 3 gray. We identified 32 deregulated proteins (p <= 0.05) in irradiated hearts 24 h after the exposure. The proteomics data were further evaluated and validated by bioinformatics and immunoblotting investigation. In good agreement with our previous results using fresh-frozen tissue, the analysis indicated radiation-induced alterations in three main biological pathways: respiratory chain, lipid metabolism and pyruvate metabolism. The label-free approach enables the quantitative measurement of radiation-induced alterations in FFPE tissue and facilitates retrospective biomarker identification using clinical archives.
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| 8. |
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| 9. |
- Baldetorp, Bo, et al.
(author)
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Analysis of protein expression in pure cell nuclei populations isolated from human breast cancer tissue by DNA flow cytometric sorting.
- 2010
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In: Journal of Proteomics. - : Elsevier BV. - 1874-3919. ; 73, s. 1111-1116
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Journal article (peer-reviewed)abstract
- In this study, cell nuclei from aneuploid breast cancer samples were sorted with respect to DNA content into pure diploid and aneuploid fractions using flow cytometry. The nuclear proteins were then separated by one-dimensional gel electrophoresis (1D-PAGE) and differences in protein expression patterns, between diploid and aneuploid nuclei from the same tumours, were compared. Using a combination of peptide finger printing and peptide identification by MALDI-TOF mass spectrometry, we identified proteins and confirmed that the proteins were of nuclear origins. The results in this study add further information to the knowledge about the breast cancer disease complexity and heterogeneity at molecular level. For some of the tumours studied different nuclei protein patterns were obtained, in the diploid respective aneuploid nuclei populations, whilst other tumours did not show these differences.
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| 10. |
- Bayram, Helen L., et al.
(author)
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Cross-species proteomics in analysis of mammalian sperm proteins
- 2016
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In: Journal of Proteomics. - : Elsevier BV. - 1874-3919 .- 1876-7737. ; 135, s. 38-50
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Journal article (peer-reviewed)abstract
- Many proteomics studies are conducted in model organisms for which fully annotated, detailed, high quality proteomes are available. By contrast, many studies in ecology and evolution are conducted in species which lack high quality proteome data, limiting the perceived value of a proteomic approach for protein discovery and quantification. This is particularly true of rapidly evolving proteins in the reproductive system, such as those that have an immune function or are under sexual selection, and can compromise the potential for cross-species proteomics to yield confident identification. In this investigation we analysed the sperm proteome, from a range of ungulates and rodents, and explored the potential of routine proteomic workflows to yield characterisation and quantification in non-model organisms. We report that database searching is robust to cross-species matching for a mammalian core sperm proteome, comprising 623 proteins that were common to most of the 19 species studied here, suggesting that these proteins are likely to be present and identifiable across many mammalian sperm. Further, label-free quantification reveals a consistent pattern of expression level. Functional analysis of this core proteome suggests consistency with previous studies limited to model organisms and has value as a quantitative reference for analysis of species-specific protein characterisation.Significance: From analysis of the sperm proteome for diverse species (rodents and ungulates) using LC-MS/MS workflows and standard data processing, we show that it is feasible to obtain cross-species matches for a large number of proteins that can be filtered stringently to yield a highly expressed mammalian sperm core proteome, for which label-free quantitative data are also used to inform protein function and abundance.
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