bims-prodis Biomed News
on Proteomics in disease
Issue of 2018–09–30
six papers selected by
Nancy Gough, Bioserendipity
  1. Discovery of restless legs syndrome plasmatic biomarkers by proteomic analysis.
  2. Proteomics, metabolomics and metagenomics for type 2 diabetes and its complications.
  3. PTMD: A Database of Human Disease-associated Post-translational Modifications.
  4. Phosphoproteomic analysis reveals PAK2 as a therapeutic target for lapatinib resistance in HER2-positive breast cancer cells.
  5. Leveraging proteomics to compare submerged versus air-liquid interface carbon nanotube exposure to a 3D lung cell model.
  6. Autoantibody Profiling Using Human Autoantigen Protein Array and AlphaScreen.
  1. Brain Behav. 2018 Sep 22. e01062
    Discovery of restless legs syndrome plasmatic biomarkers by proteomic analysis.
    Elisa Bellei, Emanuela Monari, Serkan Ozben, Mesrure Koseoglu Bitnel, Selma Topaloglu Tuac, Aldo Tomasi, Stefania Bergamini.
       OBJECTIVES: Restless legs syndrome (RLS) can lead to severe clinical consequences, thus negatively impacts on patients' overall health and quality of life. Nevertheless, the pathophysiology of RLS is still unclear, resulting in underestimate, incorrect, or ignored diagnosis and in limited management and treatment. The aim of this study was to compare the plasma proteome of RLS patients and healthy controls, in the search of diagnostic biomarkers related to the disease severity.
    MATERIALS AND METHODS: Two-dimensional gel electrophoresis coupled with liquid chromatography-mass spectrometry was employed to analyze plasma samples of 34 patients with primary RLS, divided into two subgroups according to the disease severity: MMS group (mild-moderate symptoms) and HS group (severe and very severe symptoms), and 17 age- and sex-matched control subjects. Sleep quality, daytime sleepiness, and the level of depression were also evaluated.
    RESULTS: We identified eight upregulated spots, corresponding to five unique proteins, in both RLS group vs. controls (alpha-1B-glycoprotein, alpha-1-acid glycoprotein 1, haptoglobin, complement C4-A, and immunoglobulin kappa constant); five increased spots, consistent with three unique proteins, only in HS-RLS (kininogen-1, immunoglobulin heavy constant alpha 1, and immunoglobulin lambda constant 2); one downregulated spot in both patient's groups (complement C3) and another one only in HS-RLS (alpha-1-antitrypsin).
    CONCLUSIONS: The significantly different plasma proteins detected in RLS were mainly associated with inflammation, immune response, and cardiovascular disorders. Particularly, the gradual increasing in immunoglobulins could be indicative of the disease severity and evolution. Accordingly, these proteins may represent a valid set of useful biomarkers for RLS diagnosis, progression and treatment.
    Keywords:  biomarkers; diagnosis; mass spectrometry; proteomics; restless legs
    DOI:  https://doi.org/10.1002/brb3.1062
  2. Life Sci. 2018 Sep 19. pii: S0024-3205(18)30587-3. [Epub ahead of print]
    Proteomics, metabolomics and metagenomics for type 2 diabetes and its complications.
    Niannian Wang, Feifei Zhu, Liang Chen, Keping Chen.
      Type 2 diabetes mellitus (T2DM) is one of the most common diseases of endocrine and metabolic disorders, whose mechanism is still largely unknown. Fortunately, various "omics" tools have been employed to better understand the progression pathologies of T2DM and its complications. More specifically, proteomics, metabolomics and metagenomics have played crucial roles in advancing deeper understanding of the physiological processes and regulatory mechanisms of T2DM, such as regulation of signaling pathways perturbed by glucose levels, intestinal microorganism, and inflammation and so on. By analyzing the dynamic change and modification of proteins, proteomics has become an important tool in biology and medicine. Metabolomic analysis can amplify and quantify metabolites in living organisms to reveal the relative relationship between metabolites and physiological and pathological changes. There are also increasing evidences that the human microbiome, specifically the gastrointestinal microbiome have a potential role in the etiology and pathological outcomes of T2DM and its complications. This article summarized and discussed the recent applications of these "omics" tools in finding biomarkers for T2DM and its complications. We also reviewed employing multiple "omics" to further advance our understanding of this pathology. This review will benefit deeper understanding in new therapeutic and/or diagnostic biological target for the discovery of T2DM and its complications.
    Keywords:  Biomarkers; Metabolomics; Metagenomics; Proteomics; T2DM
    DOI:  https://doi.org/10.1016/j.lfs.2018.09.035
  3. Genomics Proteomics Bioinformatics. 2018 Sep 20. pii: S1672-0229(18)30318-8. [Epub ahead of print]
    PTMD: A Database of Human Disease-associated Post-translational Modifications.
    Haodong Xu, Yongbo Wang, Shaofeng Lin, Wankun Deng, Di Peng, Qinghua Cui, Yu Xue.
      Various posttranslational modifications (PTMs) participate in nearly all aspects of biological processes by regulating protein functions, and aberrant states of PTMs are frequently implicated in human diseases. Therefore, an integral resource of PTM-disease associations (PDAs) would be a great help for both academic research and clinical use. In this work, we reported PTMD, a well-curated database containing PTMs that are associated with human diseases. We manually collected 1950 known PDAs in 749 proteins for 23 types of PTMs and 275 types of diseases from the literature. Database analyses show that phosphorylation has the largest number of disease associations, whereas neurologic diseases have the largest number of PTM associations. We classified all known PDAs into six classes according to the PTM status in diseases and demonstrated that the upregulation and presence of PTM events account for a predominant proportion of disease-associated PTM events. By reconstructing a disease-gene network, we observed that breast cancers have the largest number of associated PTMs and AKT1 has the largest number of PTMs connected to diseases. Finally, the PTMD database was developed with detailed annotations and can be a useful resource for further analyzing the relations between PTMs and human diseases. PTMD is freely accessible at http://ptmd.biocuckoo.org.
    Keywords:  AKT1; Disease−gene network; PTM−disease association; Phosphorylation; Posttranslational modification
    DOI:  https://doi.org/10.1016/j.gpb.2018.06.004
  4. Biochem Biophys Res Commun. 2018 Sep 19. pii: S0006-291X(18)32011-4. [Epub ahead of print]
    Phosphoproteomic analysis reveals PAK2 as a therapeutic target for lapatinib resistance in HER2-positive breast cancer cells.
    Yoojin Chang, Kyong Hwa Park, Ji Eun Lee, Ki-Cheol Han.
      The human epidermal growth factor receptor 2 (HER2)-positive breast cancer with overexpression of HER2 accounts for approximately 25% of breast cancers and is more aggressive than other types of breast cancer. Lapatinib has been widely used as a HER2-targeted therapy, however, a number of patients develop lapatinib resistance and still suffer from poor prognosis. Therefore, it is essential to identify novel therapeutic targets that could overcome lapatinib resistance. In this study, we carried out phosphoproteomic analysis of lapatinib sensitive and resistant cell lines (SKBR3 and SKBR3-LR) using stable isotope labeling with amino acids in cell culture (SILAC). We identified 3808 phosphopeptides from 1807 proteins and then analyzed signaling pathways, Gene Ontology, and protein-protein interaction networks. Finally, we identified PAK2 as a therapeutic target from the network analysis and validated that PAK2 knockdown and PAK inhibitor treatment resensitize the lapatinib resistant cells to lapatinib. This results suggest that PAK2 is a potent therapeutic target to overcome acquired lapatinib resistance in HER2-positive breast cancer cells.
    Keywords:  HER2-Positive breast cancer; Lapatinib resistance; PAK2; Phosphoproteomics
    DOI:  https://doi.org/10.1016/j.bbrc.2018.09.086
  5. Toxicol In Vitro. 2018 Sep 19. pii: S0887-2333(18)30567-8. [Epub ahead of print]54 58-66
    Leveraging proteomics to compare submerged versus air-liquid interface carbon nanotube exposure to a 3D lung cell model.
    G Hilton, H Barosova, A Petri-Fink, B Rothen-Rutishauser, M Bereman.
      With the emerging concern over the potential toxicity associated with carbon nanotube inhalation exposure, several in vitro methods have been developed to evaluate cellular responses. Since the major concern for adverse effects by carbon nanotubes is inhalation, various lung cell culture models have been established for toxicity testing, thus creating a wide variation of methodology. Limited studies have conducted side-by-side comparisons of common methods used for carbon nanotube hazard testing. The aim of this work was to use proteomics to evaluate global cellular response, including pro-inflammatory and pro-fibrotic mediators, of a 3D lung model composed of macrophages, epithelial cells, and fibroblasts which mimics the human alveolar epithelial tissue barrier. The cells were exposed to Mitsui 7 (M-7) multi-walled carbon nanotubes (MWCNT) under submerged and air-liquid interface (ALI) conditions and discovery proteomics identified 3500 proteins. The M-7 ALI exposure compared to control was found to increase expression in proteins related to oxidative stress that were not found to be enriched in submerged exposure. Comparison of MWCNT exposure methods, M-7 ALI exposure versus M-7 submerged exposure, yielded protein enrichment in pathways known to be associated with carbon nanotube exposure stress response, such as acute phase response signaling and NRF2-mediated oxidative stress response. This study demonstrates a comparison of commonly deployed carbon nanotube exposure methods. These data should be considered by the nanotoxicology community when interpreting or cross comparing in vitro exposure results.
    Keywords:  Air-liquid interface; Carbon nanotubes; In vitro assay development; Label-free proteomics; Lung cell co-cultures; Toxicoproteomics
    DOI:  https://doi.org/10.1016/j.tiv.2018.09.010
  6. Methods Mol Biol. 2018 ;1868 93-112
    Autoantibody Profiling Using Human Autoantigen Protein Array and AlphaScreen.
    Hiroyuki Takeda.
      Autoantibodies that recognize self-antigens are believed to have close relationship diseases such as autoimmune diseases, cancer, and lifestyle diseases. Analysis of autoantibodies is essential for investigating pathology mechanisms, diagnosis, and therapeutics of these diseases. We developed autoantibody profiling assay using cell-free synthesized protein array and high-throughput screening technology. Our assay system can sensitively detect interaction between recombinant antigen protein and autoantibody and efficiently analyze autoantibody profiling in patients' sera.
    Keywords:  AlphaScreen; Autoantibody; Autoantibody profiling; Autoantigen; Protein array; Wheat cell-free protein synthesis
    DOI:  https://doi.org/10.1007/978-1-4939-8802-0_10
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