82 research outputs found

    Off-Line Multidimensional Liquid Chromatography and Auto Sampling Result in Sample Loss in LC/LC–MS/MS

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    Large-scale proteomics often employs two orthogonal separation methods to fractionate complex peptide mixtures. Fractionation can involve ion exchange separation coupled to reversed-phase separation or, more recently, two reversed-phase separations performed at different pH values. When multidimensional separations are combined with tandem mass spectrometry for protein identification, the strategy is often referred to as multidimensional protein identification technology (MudPIT). MudPIT has been used in either an automated (online) or manual (offline) format. In this study, we evaluated the performance of different MudPIT strategies by both label-free and tandem mass tag (TMT) isobaric tagging. Our findings revealed that online MudPIT provided more peptide/protein identifications and higher sequence coverage than offline platforms. When employing an off-line fractionation method with direct loading of samples onto the column from an eppendorf tube via a high-pressure device, a 5.3% loss in protein identifications is observed. When off-line fractionated samples are loaded via an autosampler, a 44.5% loss in protein identifications is observed compared with direct loading of samples onto a triphasic capillary column. Moreover, peptide recovery was significantly lower after offline fractionation than in online fractionation. Signal-to-noise (S/N) ratio, however, was not significantly altered between experimental groups. It is likely that offline sample collection results in stochastic peptide loss due to noncovalent adsorption to solid surfaces. Therefore, the use of the offline approaches should be considered carefully when processing minute quantities of valuable samples

    Putative exosomal proteins detected in the CM of BC and MCF-10A cells.

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    <p>A. The number of SCs identified in the CM of each cell line is indicated. MDA-MB-231 and MCF-10A cells are labeled as 231 and 10A, respectively. NSAF data can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158296#pone.0158296.s003" target="_blank">S3 Table</a>. B. STRING analysis illustrates the numerous complex interactions possible among the putative exosomal proteins. Thicker lines reflect a higher confidence score. (Abbreviations: CM = conditioned medium, BC = breast cancer, SC = spectral counts)</p

    Proteases detected in the CM of BC and MCF-10A cells.

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    <p>A. The number of SCs identified in the CM of each cell line is indicated. MDA-MB-231 and MCF-10A cells are labeled as 231 and 10A, respectively. NSAF data can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158296#pone.0158296.s003" target="_blank">S3 Table</a>. B. BC gene expression data was extracted from TCGA and boxplots were created for luminal A (pink) and TNBC (blue) tumors. Expression values are log2 normalized, tumor matched normal, with normal mammary tissue expression set to 0. C. Kaplan-Meier survival curves for human BC patients were created. The x axis represents the months of recurrence-free survival. Red and black curves indicate higher and lower expression, respectively. The p-value for each result is shown in the upper right quadrant. (Abbreviations: CM = conditioned medium, BC = breast cancer, SC = spectral counts, TCGA = The Cancer Genome Atlas, TNBC = triple negative breast cancer)</p

    IGFBPs, ECM proteins, and other proteins detected in the CM of BC and MCF-10A cells.

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    <p>A-C. The number of SCs identified in the CM of each cell line is indicated. MDA-MB-231 and MCF-10A cells are labeled as 231 and 10A, respectively. NSAF data can be found in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0158296#pone.0158296.s003" target="_blank">S3 Table</a>. D. BC gene expression data was extracted from TCGA and boxplots were created for luminal A (pink) and TNBC (blue) tumors. Expression values are log2 normalized, tumor matched normal, with normal mammary tissue expression set to 0. (Abbreviations: CM = conditioned medium, BC = breast cancer, SC = spectral counts, TCGA = The Cancer Genome Atlas, TNBC = triple negative breast cancer)</p

    Identification of proteins in BC and MCF-10A cell secretomes.

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    <p>A. A workflow was established to analyze the secretomes of BC and benign mammary epithelial cells. B. Benign (MCF-10A), ERα-positive BC (MCF-7), and TNBC (MDA-MB-231, DT22, and DT28) cells were established in 3D cultures using Matrigel extracellular matrix. Live (top row) and fixed (bottom row) cultures were imaged by phase contrast or immunofluorescence, respectively. Markers of proliferation (Ki67-red), basement membrane (laminin-green), and nuclei (DAPI-blue) were utilized. C. 3D cultures of MCF-10A cells were exposed to CM from MCF-10A, MCF-7, MDA-MB-231, DT22, or DT28 cells. Proliferation (red) and nuclei (blue) are indicated by Ki67 and DAPI staining, respectively. Scale bars indicate 25 μm. D. 3D cultures described in panel C were analyzed to determine the percent of proliferating MCF-10A cells for each treatment. An asterisk (*) indicates a p-value <0.05. E. CM from each cell line was subjected to MS and compiled results are shown. F. CM from 3D cultures of BC and MCF-10A cells were subjected to Western blotting analysis using antibodies to cathepsin D (CTSD), extracellular matrix protein 1 (ECM1), peroxiredoxin 1 (PRDX1), or 14-3-3 sigma (SFN). The number of spectral counts (SCs) is indicated above each lane. To visualize SFN, the CM was concentrated before blotting. MDA-MB-231 and MCF-10A cells are labeled as 231 and 10A, respectively. (Abbreviations: BC = breast cancer, TNBC = triple negative breast cancer, 3D = three dimensional, CM = conditioned medium, MS = mass spectroscopy)</p

    Workflow outlines process of obtaining plasma membrane proteome of multiple BC cell lines.

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    <p>After establishing an effective method for isolating plasma membrane proteins, representatives from each of the currently defined classes of BC were cultured and plasma membranes were isolated and subjected to MS, yielding a comprehensive list of protein identifications having an FDR ≤1%. These data were biologically validated and the data were mined for relevant protein candidates.</p

    Plasma Membrane Proteomics of Human Breast Cancer Cell Lines Identifies Potential Targets for Breast Cancer Diagnosis and Treatment

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    <div><p>The use of broad spectrum chemotherapeutic agents to treat breast cancer results in substantial and debilitating side effects, necessitating the development of targeted therapies to limit tumor proliferation and prevent metastasis. In recent years, the list of approved targeted therapies has expanded, and it includes both monoclonal antibodies and small molecule inhibitors that interfere with key proteins involved in the uncontrolled growth and migration of cancer cells. The targeting of plasma membrane proteins has been most successful to date, and this is reflected in the large representation of these proteins as targets of newer therapies. In view of these facts, experiments were designed to investigate the plasma membrane proteome of a variety of human breast cancer cell lines representing hormone-responsive, ErbB2 over-expressing and triple negative cell types, as well as a benign control. Plasma membranes were isolated by using an aqueous two-phase system, and the resulting proteins were subjected to mass spectrometry analysis. Overall, each of the cell lines expressed some unique proteins, and a number of proteins were expressed in multiple cell lines, but in patterns that did not always follow traditional clinical definitions of breast cancer type. From our data, it can be deduced that most cancer cells possess multiple strategies to promote uncontrolled growth, reflected in aberrant expression of tyrosine kinases, cellular adhesion molecules, and structural proteins. Our data set provides a very rich and complex picture of plasma membrane proteins present on breast cancer cells, and the sorting and categorizing of this data provides interesting insights into the biology, classification, and potential treatment of this prevalent and debilitating disease.</p></div

    RT-PCR demonstrates the quantitative nature of the MS data.

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    <p>RNA was isolated from each of the cell lines, cDNA was made, and RT-PCR was performed to determine whether the spectral ID numbers were correlated to transcript levels of selected genes. Spectral ID numbers are displayed above each graph and the gene symbol is below those numbers.</p

    Western blots and immunofluorescence demonstrate that protein levels are accurately reflected in the MS data.

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    <p>A. For Western analysis, PMs were isolated from each of the cell lines, solubilized in detergent buffer, and fractionated on SDS-PAGE gels. Blots were probed with an ErbB2- or KRT17-specific antibody and imaged with the Licor Infrared Imaging System. Spectral ID numbers and cell lines are indicated for each lane on the blot. B. For immunofluorescence, cells were grown in chamber slides, treated with an antibody to ErbB2 or KRT17 (red), and cell nuclei were stained with DAPI (blue). Cells were examined with confocal microscopy. All scale bars  = 25 µ.</p
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