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Apr 2018 DOI 10.14302/issn.2326-0793.jpgr-18-2004
Anwar PervezCorresponding author
Department of Biochemistry and molecular Biology, University of Gujrat Sialkot subcampus, Pakistan
Human proteome project was revolutionized about 40 years ago with purpose of summarizing whole proteomic data at one place. It was launched after human genome project to map and observe all proteins. The goal related proteomic study is to draft the entire human proteome in disease diagnosis by using bioinformatics tools. Pillars of human proteome project provide different databases related to proteins at transcriptional and translational level. Human proteome organization(HUPO) published biology disease HUPO whose aim is to measure protein and proteome by life and processes related to human diseases. Different human organ like plasma, liver, brain and diabetic base project are used to characterize human disease and health. Major data resources accumulated in databases like peptides Atlas, GPMDB and neXtProt for proteins. Matrices of human proteome project identify and characterize the protein products as Post translational modification (PTM), splice various isoforms from 20,300 proteins. Matrices related to different years make proteomes counterpart by magnify the research biomedical community with high output of instruments and specimen pre-analytical protocols. CALIPHO multidisciplinary group provides information about protein complexities, interactions, function and structure complexities after Uniport and Swissprot. Different bioinformatics tools are used for structural and functional annotations of protein, disease diagnosis and mutations due to protein. Extensive study of human proteome project has been proved helpful in disease treatment at translational and post- translational levels. In future, human proteome project along with bioinformatics will include protein profiling, biomarkers, Mass spectrophotometer technique and cross analysis of different proteome projects.
Jan 2014 DOI 10.14302/issn.2326-0793.jpgr-sp1-edt-1
Leonid TarassishinCorresponding author
A primer explains how proteomics scales from single‑protein analysis to whole‑organism studies, touching on technologies, bioinformatics, and applications.
Jul 2013 DOI 10.14302/issn.2326-0793.jpgr-13-207
Floros JoannaCorresponding author
Center for Host defense, Inflammation, and Lung Disease (CHILD) Research and Departments of Pediatrics
Surfactant protein A (SP-A) plays a number of roles in lung host defense and innate immunity. There are two human genes, SFTPA1 and SFTPA2, and evidence indicates that the function of SP-A1 and SP-A2 proteins differ in several respects. To investigate the impact of SP-A1 and SP-A2 on the alveolar macrophage (AM) phenotype, we generated humanized transgenic (hTG) mice on the SP-A knockout (KO) background, each expressing human SP-A1 or SP-A2. Using two-dimensional difference gel electrophoresis (2D-DIGE) we studied the AM cellular proteome. We compared mouse lines expressing high levels of SP-A1, high levels of SP-A2, low levels of SP-A1, and low levels of SP-A2, with wild type (WT) and SP-A KO mice. AM from mice expressing high levels of SP-A2 were the most similar to WT mice, particularly for proteins related to actin and the cytoskeleton, as well as proteins regulated by Nrf2. The expression patterns from mouse lines expressing higher levels of the transgenes were almost the inverse of one another – the most highly expressed proteins in SP-A2 exhibited the lowest levels in the SP-A1 mice and vice versa. The mouse lines where each expressed low levels of SP-A1 or SP-A2 transgene had very similar protein expression patterns suggesting that responses to low levels of SP-A are independent of SP-A genotype, whereas the responses to higher amounts of SP-A are genotype-dependent. Together these observations indicate that in vivo exposure to SP-A1 or SP-A2 differentially affects the proteomic expression of AMs, with SP-A2 being more similar to WT.
May 2026 DOI 10.14302/issn.2572-3030.jcgb-26-6307
Faisst Arne-C.Corresponding author
The development of tumor biomarkers derived from blood, or its components, has become pivotal in advancing early cancer diagnosis. Malignant transformations induce cancer-specific alterations in the transcriptome, proteome, and secretome of tumor cells. Recent studies highlighted similar alterations in peripheral blood mononuclear cells (PBMCs) in cancer patients, which appear to mirror the state of transformation in tumor cells. These findings suggest an intercellular communication–driven mechanism rather than a systemic inflammatory response and, in addition to current ctDNA-based liquid biopsy biomarkers, point to a novel, simple, and highly robust approach for the early detection of cancer. Using this phenomenon to advance PBMC-based biomarker development, it will be essential to achieve 3D in vitro tumor models that reproduce a highly physiological tumor microenvironment (TME). Likewise, more enhanced 3D ex vivo models are required to enable the replication of cell-to-cell and organ-to-organ communication. These systems will guide the self-organization of mixed microenvironments derived from different tissues and enable them to accurately reproduce the molecular connections underlying these alterations. In this study, an innovative new modular 3D co-culturing approach was used to expose PBMCs to lung tumoroids, under physiologically relevant conditions. Changes in DNA fragmentation of PBMCs in the presence of lung cancer were quantified and used as a biomarker. To validate the predictiveness of this biomarker, our results were compared with clinical data from a clinical evaluation study. Similar to the clinical trial observations, PBMCs, when exposed to lung tumoroids, showed a significantly lower level of DNA fragmentation (37%). This modular 3D co-culturing model showed a predictiveness of the clinical data of > 90%, demonstrating its power to monitoring cell-to-cell communication effects and support the development of blood-based biomarkers.
Jul 2017 DOI 10.14302/issn.2326-0793.JPGR-17-1571
C. P. Figueiredo HenriqueCorresponding author
AQUACEN, National Reference Laboratory for Aquatic Animal Diseases, Ministry of Agriculture, Livestock and Food Supply, Federal University of Minas Gerais, Belo Horizonte, Brazil
Perkinsus marinus is an intracellular parasitic protozoan that is responsible for serious disease epizootics in marine bivalve mollusks worldwide. Despite all available information on P. marinus genomics, more baseline data is required at the proteomic level. Our aim was to study the proteome profile of in vitro cultured P. marinus isolated from oysters Crassostrea spp. using a label-free shotgun UDMSE approach. A total of 4073 non-redundant proteins were identified across three biological replicates with stringent identification. Proteins specifically related to adaptive survival, cell recognition, antioxidants, regulation of apoptosis and others were detected. Important virulence factors of P. marinus were identified including serine protease and iron-dependent superoxide dismutase. Other proteins with involvement in several pathogens invasion strategies were rhoptries, serine-threonine kinases, and protein phosphatases. Interestingly, peptides corresponding to retroviruses polyproteins were identified in all replicates. The interactomic analysis of P. marinus proteins demonstrated extensive clusters network related to biological processes. In conclusion, we provide the first comprehensive proteomic profile of P. marinus that can be useful for further investigations on Perkinsus biology and virulence mechanisms.
Jan 2014 DOI 10.14302/issn.2326-0793.jpgr-13-357
I. Chen EmilyCorresponding author
Proteomics Shared Resource at the Columbia University Medical Center, Herbert Irvine Comprehensive Cancer Center, New York, NY 10032.
Mass spectrometry (MS) has been successfully used to analyze biological samples and advances of MS-based approaches have turn MS data from largely qualitative to quantitative. These MS-based quantitative approaches using label-free, tags, or stable isotope labeling have their own strengths and limitations. The variability introduced by different methods prior to quantitative mass spectrometry should be considered, and accuracy and precision of MS measurements can also vary depending on the strategy used for MS quantification. Therefore, the development of methods for accurate protein quantitation is one of the most challenging areas of proteomics. Using these quantitative approaches, one can investigate the dynamics of proteome through differential protein expression in normal biological processes and diseases.
Sep 2013 DOI 10.14302/issn.2326-0793.jpgr-13-257
O’Connell KathleenCorresponding author
Department of Chemistry and Biochemistry, University of South Carolina, Columbia, SC,
Lapatinib, a small molecule tyrosine kinase inhibitor is currently used in the treatment of HER2-positive breast cancer. The aim of this study was to further understanding of lapatinib response for the development of novel treatment lapatinib-focussed treatment strategies. HER2-overexpressing SKBR3 breast cancer cells were treated with lapatinib for 12 hours and the resultant proteome analyzed by a comprehensive ion-current-based LC-MS strategy. Among the 1224 unique protein identified from SKBR3 cell lysates, 67 showed a significant change in protein abundance in response to lapatinib. Of these, CENPE a centromeric protein with increased abundance, was chosen for further validation. Knockdown and inhibition of CENPE demonstrated that CENPE enhances SKBR3 cell survival in the presence of lapatinib. Based on this study, CENPE inhibitors may warrant further investigation for use in combination with lapatinib.
Jul 2013 DOI 10.14302/issn.2326-0793.jpgr-13-252
I. Chen EmilyCorresponding author
Stony Brook University, Proteomics Center, School Of Medicine, NY
In biomedical research the use of mammalian tissues is crucial to increase our understanding of complex human diseases. Mass spectrometry-based proteomic approach has become the most powerful tool of studying large-scale protein expression profiles in mammalian tissues. To perform global proteome analysis quantification of mammalian tissues, we generated 15N SILAC mice to obtain tissue-matched labeled peptide libraries for mass spectrometry-based quantitative proteomic analysis. We developed a new labeling protocol to circumvent adverse effects of introducing 15N labeled diet to mice, and showed that the new labeling scheme has no significant effect on the fertility and reproduction of C57/BL6 mice. Using labeled tissues from these mice, we compared the reproducibility of mass spectrometry-based quantification with or without 15N labeled internal standards among biological replicates of young and old brains. We found that labeled-based quantification is less susceptible to variations from instrument conditions and produces more consistent quantifications among biological replicates than label-free quantification. Lastly, we showed that over 60% of peptides from the human brain are quantifiable with internal standards from 15N labeled mouse brain and therefore present a promising alternative of quantifying human tissues that do not have existing cell lines available for SILAC labeling.