Archives

  • 2018-07
  • 2018-10
  • 2018-11
  • 2019-04
  • 2019-05
  • 2019-06
  • 2019-07
  • 2019-08
  • 2019-09
  • 2019-10
  • 2019-11
  • 2019-12
  • 2020-01
  • 2020-02
  • 2020-03
  • 2020-04
  • 2020-05
  • 2020-06
  • 2020-07
  • 2020-08
  • 2020-09
  • 2020-10
  • 2020-11
  • 2020-12
  • 2021-01
  • 2021-02
  • 2021-03
  • 2021-04
  • 2021-05
  • 2021-06
  • 2021-07
  • 2021-08
  • 2021-09
  • 2021-10
  • 2021-11
  • 2021-12
  • 2022-01
  • 2022-02
  • 2022-03
  • 2022-04
  • 2022-05
  • 2022-06
  • 2022-07
  • 2022-08
  • 2022-09
  • 2022-10
  • 2022-11
  • 2022-12
  • 2023-01
  • 2023-02
  • 2023-03
  • 2023-04
  • 2023-05
  • 2023-06
  • 2023-08
  • 2023-09
  • 2023-10
  • 2023-11
  • 2023-12
  • 2024-01
  • 2024-02
  • 2024-03
  • 2024-04
  • SCR7 br Value of the data br Data br

    2018-10-25


    Value of the data
    Data
    Experimental design, materials and methods
    Acknowledgments This project was sponsored by a grant from the National Natural Science Foundation of China (31271159), a Maryland TEDCO Grant (2007-MSCRFE-0139-01), a Technology Foundation for Selected Overseas Chinese Scholar (2012 No.13) Grant from Anhui HRSS, a Grant for scientific research of BSKY (XJ201105) from Anhui Medical University. We thank the help from Central Laboratory of Molecular and Cellular Biology, School of Basic Medical Sciences, Anhui Medical University.
    Data experimental design, materials and methods
    Data, experimental design, materials and methods
    Data processing protocol Raw data were processed using MaxQuant version 1.5.0.0 [5] (using the human Ensembl GRCh38 database) and Perseus version 1.4. Results were analysed using scripts written in-house in Python and R (deposited in the ProteomeXchange repository alongside data), and tested for statistical significance using the quantile function in the R statistical framework. To ensure high confidence identifications and quantification, a MaxQuant score of >50 and a minimum of two unique peptides per protein seen by tandem MS in all repeats were required. Initial analysis was undertaken using a label-free approach (two repeats) for global pairwise analyses, and data subsequently validated in a standard- and reverse-label SILAC approach (two repeats). Identified intracellular contaminants were removed and secreted proteins retained by using the cellular compartment annotations in Ensembl and PantherDB, and Gene Ontology annotation enrichment for extracellular-associated terms. Overlap between global secretome Madd Spectrometry repeats in are shown in Fig. 1a for each condition. Log2 SCR7 data of extracellular secreted proteins in pairwise analysis is shown in Fig. 1b. A full list of detected proteins and their quantitative expression is available in supplementary Table 1. The complete proteomic, bioinformatic and biological analyses are reported in Cox et al. (2015) [1].
    Conflict of interest
    Acknowledgements Mass Spectrometry experiments in the laboratory of R.L. were funded by the Lundbeck Foundation and the work was supported by the Velux Foundations (VKR)-funded Instrument Center for Systems Proteomics (VKR 022758).
    Data, experimental design, materials and methods This data article describes verification of the enriched SP-D from commercially available human pooled sera and results of N-glycomic analysis of a commercially available recombinant human SP-D produced in murine myeloma cells.
    SP-D verification The verification of SP-D was performed by resolving the enriched SP-D by SDS-PAGE, in-gel digestion of the corresponding band, peptide mass fingerprinting, and MASCOT search. Briefly, human serum SP-D was enriched as described in our main research article [1]. The enriched SP-D fraction was resolved by SDS-PAGE under reducing conditions and visualized by CBB staining. The 43-kDa band was excised from the gel, cut into 1mm3 pieces, and destained and dehydrated with 50% ACN/100mM NH4HCO3. Proteins in the gel pieces were then reduced with 10mM DTT in 100mM NH4HCO3 at 56°C for 1h and alkylated with 55mM IAA in 100mM NH4HCO3 at room temperature in the dark for 45min. The gel pieces were rinsed in 100mM NH4HCO3 and dehydrated with 50% ACN/100mM NH4HCO3, and then 100% ACN and then dried completely using a vacuum centrifuge concentrator. The dried gel pieces were rehydrated again with 10ng/μl trypsin in 50mM NH4HCO3 solution on ice, and then incubated at 37°C for 16h. The sample was heated at 90°C for 5min to inactivate trypsin and the resulting peptides were extracted with ACN/water/TFA (66:33:0.1, v/v/v). The extracts were then dried and desalted using a ZipTipμ-C18 tip (Millipore, Billerica, MA). The eluate (0.5μl) and DHB matrix solution (0.5μl) were deposited on a μFocus MALDI target plate (Hudson Surface Technology, Inc., Fort Lee, NJ) and left to dry at room temperature. All mass spectrometry was performed on a MALDI-QIT-TOF mass spectrometer (AXIMA-Resonance, Shimadzu/Kratos, U.K.). Ions were formed by a pulsed nitrogen UV laser (λ=337nm) in both the positive and negative ion modes. A pulsed gas, He, was used for ion cooling in the ion trap and Ar was used for CID fragmentation. The DHB matrix solution was prepared by dissolving 2.5mg of DHB in 1ml of ACN/0.1% TFA in water (2:3, v/v). Protein identification was performed with MASCOT search (Matrix Science, London, U.K.) using the Swiss-Prot database 2014_12 by peptide mass fingerprinting with the following MASCOT parameters; miss cleavage: 2, peptide mass tolerance: 0.1Da, taxonomy: human, fixed modifications: carbamidomethyl (C), variable modifications: oxidation (M), Pyro-Glu (N-term Q) (Figs. 1, 2).