Classification
1.
2.
Definition
General features — Global descriptors of the experiment
1.1. Experiment identifier or name
Regulation of proteins in AIRE-overexpressing cells
1.2. Responsible person or role
Joan Josep Bech / Francesc Canals (Laboratori de Proteòmica-VHIO).
Tef.934894174.
1.3. Quantitative approach
ICPL
Experimental design and sample description —2.1 Experimental design
2.1.1 Groups
Group 1: AIRE-overexpressing cells.
Group 2: Control cells.
2.1.2 Biological and technical replicates
Group 1: AIRE-overexpressing cells.
Group 2: Control cells.
2.
Experimental design and sample description —2.2 Sample / Assay description
Labelling protocol (if applicable)
Standard ICPL labelling protocol from the manufacturer at protein level.
2.2.2 Sample description
Sample name
AIRE: AIRE-overexpressing cells.
CTRL: Control cells.
2.2.2.2 Sample amount
100 micrograms of a mixture of both heavy- and light-labeled samples
were loaded into the 1D-gel before the first fractionation step (see
section 3.3).
2.2.2.3 Sample labelling with assay definition, i.e. MS run / data set together with reporting
ion mass, reagent or isotope labelled amino acid
ICPL-12C: 105.0215 Da
ICPL-13C: 111.0419 Da
m: 6.0204 Da
2.2.2.3 Replicates and/or groups
ICPL2: AIRE (ICPL-12C) and CTRL (ICPL-13C).
ICPL1: AIRE (ICPL-13C) and CTRL (ICPL-12C).
2.2.3 Isotopic correction coefficients
N/A
2.2.4 Internal references
N/A
3.
4.
Input data — Description and reference of the dataset used for quantitative analysis: type, format and availability of the data. No actual values are requested here.
3.1. Input data type
EICs from full MS scan
3.2. Input data format
.yep files (bruker)
3.3. Input data merging
Prior to the analysis by mass spectrometry, both AIRE and CTRL samples were
fractionated in 20 bands by using a 1D-gel. Each individual band was
subsequently digested and submitted to a second chromatography-based
fractionation step before the analysis into the mass spectrometer. Finally, the
searches for the 20 individual bands were merged in a unique compilation list
by using ProteinScape 2.0 software, before the quantification analysis.
3.4. Availability of the input data
URI
Protocol —Description of the software and methods applied in the quantitative analysis (including transformation functions, aggregation functions and statistical calculations).
4.1. Quantification software name, version and manufacturer
WARP-LC 1.2 / ProteinScape 2.0 (Bruker)
4.2. Description of the selection and/or matching method of features, together with the
Features (EICs) were selected by applying a m/z and retention time window of
1.3Da and 60 sec, respectively. Only signals from +2 and +3 species were added
to each peptide EIC. The values used for quantitation were obtained by
description of the method of the primary extracted quantification values
determination for each feature and/or peptide
integrating the chromatographic peak of each EIC.
4.3. Confidence filter of features or peptides prior to quantification
A FDR <4% is applied (Described in MIAPE-MSI xx).
4.4. Description of data calculation and transformation methods
4.4.1.
Missing values imputation and outliers removal
Outliers are automatically removed by WARP-LC 1.2 software.
4.4.2.
Quantification values calculation and / or ratio determination from the
The heavy/light ratios (H/L) of each peptide were calculated by dividing the
intensities of the EICs corresponding to the heavy (ICPL-13C) labeled- and light
(ICPL-12C) labelled- versions of each peptide.
primary extracted quantification values
4.4.3.
Replicate aggregation
N/A
4.4.4.
Normalization
The normalization is performed by using the protein quantification, which is
calculated as indicated in section 4.4.5. Then the distribution of frecuencies of
protein ratios were calculated. Finally, The Mode value of the distribution is
used to re-center the distribution to 1.
4.4.5.
Protein quantification values calculation and / or ratio determination from
the peptide quantification values
4.4.6.
5.
Protocol specific corrections
H/L ratios for proteins were calculated by performing the arithmetic mean of all
the ratios obtained at peptide level after outlier removal.
N/A
4.5. Description of methods for (statistical) estimation of correctness
A coefficient of variation (CV) was calculated and only proteins with CV<30%
were accepted.
4.6. Calibration curves of standards
N/A
Resulting data —Provide the actual quantification values resulting from your quantification software together with their estimated confidence. Depending of the quantification technique
or even of the quantification software, only some of the following items could be satisfied (e.g., for spectral counting, only quantification values at protein level can be provided)
5.1 Quantification values at peptide and/or feature level: Actual quantification values achieved for each peptide and/or, in case of feature-based quantification, for the corresponding features
(mapped back from each peptide), together with their estimated confidence.
5.1.1.
Primary extracted quantification values for each feature (e.g. area, height,
etc.), with their statistical estimation of correctness
5.1.2.
Quantification values for each peptide as a result of the aggregation of the
values of the previous section (5.1.1), with their statistical estimation of
correctness
N/A
http://proteo.cnb.csic.es/downloads/miape-quant/Peptides_ICPL1_VH.xls
http://proteo.cnb.csic.es/downloads/miape-quant/Peptides_ICPL2_VH.xls
5.2 Quantification values at protein level: Actual quantification values achieved for each protein and for each protein ambiguity group, together with the confidence in the quantification
value.
Basic / raw quantification values with statistical estimation of correctness
N/A
5.2.2. Transformed / aggregated / combined quantification values of the proteins at group
level, with their statistical estimation of correctness
http://proteo.cnb.csic.es/downloads/miape-quant/Proteins_ICPL1_VH.xls
http://proteo.cnb.csic.es/downloads/miape-quant/Proteins_ICPL2_VH.xls