For many years, HUVEC.com1 public database provides biological data relative to the proteome of human umbilical vein endothelial cells (HU-VECs), which are the most used human endothelial cell model in vascular biology. The proteins were identified using two-dimensional gel electrophoresis (2-DGE) for protein separation coupled with Matrix Assisted Laser Desorption-Ionization Mass Spectrometry (MALDI-TOF-MS) for identification. We present here an important update of HUVEC.com with 521 protein identifications as determined using Fourier transformed ion cyclotron resonance-mass spectrometry (FTICR-MS) applied to an unstained 2-DGE gel cut in 221 squared pieces; each identified protein being accompanied by a semi-quantitative three dimensional visualization is called “score imaging”. The squared analyzed gel and the alphabetical list of identified proteins, linked with their corresponding three-dimensional score imaging, are available at www.huvec.com. This original approach led to the establishment of the most protein-rich and informative database for HUVECs, as well as to the identification of some protein species, in particular with phosphorylation.
From 2004, HUVEC.com (www.huvec.com) shared a public database relative to human umbilical vein endothelial cells (HUVECs) proteome as assessed by the classical peptide mass fingerprinting approach combining two-dimensional gel electrophoresis (2-DGE) and Matrix Assisted Laser Desorption-Ionization Mass Spectrometry (MALDI-TOF-MS) [
We used primo-cultures of HUVECS, obtained as previously described in details [
Two identical gels were prepared as previously described [
The proteins of every unstained rectangle (0.5 mm × 6 mm × 10.5 mm, volume 31 µL) were in-gel proteolyzed [
A nano-scale capillary LC system (Ultimate 3000 Dionex, LC-Packings, The Netherlands) was used on line with a hybrid nanoESI Linear Ion Trap (LIT) FTICR mass spectrometer (LTQ-FT, Thermo Scientific, USA) using aqueous (buffer A: H2O/acetonitrile/formic acid, 98/2/0.1, v/v/v) and organic buffers (buffer B: H2O/acetonitrile/formic acid, 10/90/0.1, v/v/v). Chromatographic separations were conducted on a reverse phase capillary column (Atlantis dC18, 75 µm id., 15 cm length, Waters, UK) with a 220 nL/min flow rate. The gradient profile consisted of two linear gradients from 0 to 20% B in 10 min and from 20% B to 60% B in 35 min. Data were acquired in automatic mode as described [
In SequesTM, peptide “hits” are sorted in five subsets according to the identification rank of each peptide for a given protein. The consensus score is calculated by multiplying the first entry in the “hits” column by 10, the second entry by 8, the third by 6, the fourth by 4, and the fifth by 2, and then summing these values. To distinguish between equivalent consensus scores, the decimal number (0.1, 0.2, or 0.3) is a weighting which is calculated by dividing by 20 the top Xcorr score of the peptides and adding it to the consensus score. For example, a protein can be identified by one top hit or five 4th best hits with the same consensus score. The weighting puts the one with a top hit above the others. However with our validation criteria, the later would not be validated with five 4th hits only. SequestTM consensus score could be correlated to the relative protein abundance in the sample, according to Gao’s peptide hits technique [10-12].
For each protein identified according to the previous criteria, the values of the corresponding consensus score were stored in a matrix representing the gel (13 rows and 17 columns). The localization of the protein in the gel was visualized by a 3D representation of the matrix (x-axis for the pI, y-axis for molecular weight, z-axis for the consensus score). A linear scale for consensus scores enhanced the major focalization spot(s) for each protein in the gel. In some cases, the gel was mapped using logarithmic scale to enhance the lower scores.
Two identical gels were prepared: the first gel (or control gel) was stained successively with CCB then with silver nitrate (not shown); the second gel was cut in 221 equal rectangles without staining, the resulting grid pattern being matched against the stained control gel (
zation (xand y-axis) and corresponding consensus scores from SequestTM database search (z-axis).
This approach permitted relatively accurate protein location due to rectangle dimensions (~6.0 × 10.5 mm). Furthermore, in absence of any interferences related to the coloration process, it allowed protein detection with a high level of sensitivity. For example, while 5 spots were detected using silver nitrate in rectangle #118, 22 proteins were identified using our approach corroborating the ability of FTICR-MS for the identification of proteins in very low amounts.
It has been shown that SequestTM peptide hits and by extension the associated identification consensus scores resulting from LC-MS analysis could be used for labelfree relative protein quantification [
In the field of spot overlapping and protein background, since each protein identification was considered individually, the corresponding score imaging could not theoretically be “contaminated” by other proteins. Nevertheless, the example of rectangle #110, in which only two major actin isoforms have been detected in this wellknown “overcrowded” 2-D gel area, strongly suggests that ion suppression effects [
In biological terms, among the 521 proteins identified, FTICR-MS allowed to unveil a lot of proteins not yet known in HUVECs nor in other endothelial cells (ECs), and for many of them at low cellular concentration. As shown in
The presented 2-DGE/FTICR-MS-based method constitutes an original, sensitive, and semi-quantitative alternative to classical 2-DGE staining for the establishment of protein databases. When applied to HUVECs, i.e. the most popular endothelial cell model in humans, it allowed to unambiguously identify and further localized on a 2-D gel 521 endothelial proteins representing to date the most protein-rich and informative database for HUVECs. The grid 2-D gel with links to identified proteins and related score imaging, as well as the alphabetical list of identified proteins (also linked with score imaging), are freely available at www.huvec.com.
Financial support from the TGE FT-ICR for conducting the research is gratefully acknowledged.