Quantitative Analysis of Glycated Proteins

The proposed protocol presents a comprehensive approach for large-scale qualitative and quantitative analysis of glycated proteins (GP) in complex biological samples including biological fluids and cell lysates such as plasma and red blood cells. The method, named glycation isotopic labeling (GIL), is based on the differential labeling of proteins with isotopic [¹³C₆]-glucose, which supports quantitation of the resulting glycated peptides after enzymatic digestion with endoproteinase Glu-C. The key principle of the GIL approach is the detection of doublet signals for each glycated peptide in MS precursor scanning (glycated peptide with <i>in vivo</i> [¹²C₆]- and <i>in vitro</i> [¹³C₆]-glucose). The mass shift of the doublet signals is +6, +3 or +2 Da depending on the peptide charge state and the number of glycation sites. The intensity ratio between doublet signals generates quantitative information of glycated proteins that can be related to the glycemic state of the studied samples. Tandem mass spectrometry with high-energy collisional dissociation (HCD–MS2) and data-dependent methods with collision-induced dissociation (CID–MS3 neutral loss scan) are used for qualitative analysis

Quantitative Analysis of Glycated Proteins

The proposed protocol presents a comprehensive approach for large-scale qualitative and quantitative analysis of glycated proteins (GP) in complex biological samples including biological fluids and cell lysates such as plasma and red blood cells. The method, named glycation isotopic labeling (GIL), is based on the differential labeling of proteins with isotopic [¹³C₆]-glucose, which supports quantitation of the resulting glycated peptides after enzymatic digestion with endoproteinase Glu-C. The key principle of the GIL approach is the detection of doublet signals for each glycated peptide in MS precursor scanning (glycated peptide with <i>in vivo</i> [¹²C₆]- and <i>in vitro</i> [¹³C₆]-glucose). The mass shift of the doublet signals is +6, +3 or +2 Da depending on the peptide charge state and the number of glycation sites. The intensity ratio between doublet signals generates quantitative information of glycated proteins that can be related to the glycemic state of the studied samples. Tandem mass spectrometry with high-energy collisional dissociation (HCD–MS2) and data-dependent methods with collision-induced dissociation (CID–MS3 neutral loss scan) are used for qualitative analysis

MOESM1 of Proteomic discovery and verification of serum amyloid A as a predictor marker of patients at risk of post-stroke infection: a pilot study

Additional file 1. List of proteins identified when comparing the proteomes of five infected and five non-infected patients

Quantitative Analysis of Glycated Proteins

The proposed protocol presents a comprehensive approach for large-scale qualitative and quantitative analysis of glycated proteins (GP) in complex biological samples including biological fluids and cell lysates such as plasma and red blood cells. The method, named glycation isotopic labeling (GIL), is based on the differential labeling of proteins with isotopic [¹³C₆]-glucose, which supports quantitation of the resulting glycated peptides after enzymatic digestion with endoproteinase Glu-C. The key principle of the GIL approach is the detection of doublet signals for each glycated peptide in MS precursor scanning (glycated peptide with <i>in vivo</i> [¹²C₆]- and <i>in vitro</i> [¹³C₆]-glucose). The mass shift of the doublet signals is +6, +3 or +2 Da depending on the peptide charge state and the number of glycation sites. The intensity ratio between doublet signals generates quantitative information of glycated proteins that can be related to the glycemic state of the studied samples. Tandem mass spectrometry with high-energy collisional dissociation (HCD–MS2) and data-dependent methods with collision-induced dissociation (CID–MS3 neutral loss scan) are used for qualitative analysis

Blood concentration of the 5 best molecules in early and late stroke patients.

*<p>Significant concentration was set at 0.01 after Bonferroni correction (Mann-Whitney U tests, two-tailed tests).</p

Clinical performances of the molecules for discriminating tPA treated (N = 12) vs. ineligible patients (N = 104).

*<p>The AUC of GST-π was significantly better than AUC of DJ-1 (p = 0.016). No significant difference was obtained between GST-π vs. NDKA (p = 0.11) and NDKA vs. DJ-1 (p = 0.14).</p><p>An AUC above 0.80 was estimated as significant (significance 0.05 and power 0.95, made with Power tests/Sample size item from pROC software).</p

Clinical performances of the 3 best molecules for discriminating early (blood sampling between 0 and 3 h after symptoms onset, N = 22) vs. late stroke patients (blood sampling strictly after 3 h, N = 81).

<p>NPV: negative predictive value/PPV: positive predictive value.</p>*<p>The AUC of GST-π was significantly better than AUC of NDKA and DJ-1 (p = 0.034 and 0.020 respectively). No significant difference was obtained between AUC of NDKA and of DJ-1 (p = 0.63).</p><p>An AUC above 0.74 was estimated as significant (significance 0.05 and power 0.95, made with Power tests/Sample size item from pROC software).</p

General characteristics of the 2 cohorts.

<p>NA: not available.</p>▵<p>: All patients were collected within the first 3 h after symptom onset.</p

IL-10 and S100B capacity to differentiate CT scan results in patients younger and older than 65.

<p>IL-10 and S100B capacity to differentiate CT scan results in patients younger and older than 65.</p

The seven significantly different expressed proteins between CT-positive and CT-negative patients, of the 92 inflammation biomarkers tested.

<p>The median protein ratio between CT-positive and CT-negative patients was calculated and the specificity (SP) of each protein was investigated with sensitivity (SE) set at 100%. All results are shown as normalised protein expression (NPX).</p