Figure 1.
Schematic illustration of the urine proteomic screening process. (A) The workflow of MS analysis for proteomics approach. Collected urine samples were precipitated and digested by trypsin in solution. Purified peptides were injected into the MS spectrometry. (B) The data acquired by MS instrument were entered into to the database search for protein identification. Label-free semi-quantification was performed using by emPAI value and subjected to Gene Ontology (GO) annotation and KEGG pathway analysis.
Figure 1.
Schematic illustration of the urine proteomic screening process. (A) The workflow of MS analysis for proteomics approach. Collected urine samples were precipitated and digested by trypsin in solution. Purified peptides were injected into the MS spectrometry. (B) The data acquired by MS instrument were entered into to the database search for protein identification. Label-free semi-quantification was performed using by emPAI value and subjected to Gene Ontology (GO) annotation and KEGG pathway analysis.
Figure 2.
Protein identification and profile of each group. (A) Average non-redundant protein identification numbers from each group with <1% false discovery rate (FDR) at peptide level. The error bar indicated standard deviation. (B) Venn diagram of strict filtered protein group. (C) The distribution of up and down-regulated proteins between HV and DM in strict filtering. White and gray bar indicate “increase” and “decrease”, respectively.
Figure 2.
Protein identification and profile of each group. (A) Average non-redundant protein identification numbers from each group with <1% false discovery rate (FDR) at peptide level. The error bar indicated standard deviation. (B) Venn diagram of strict filtered protein group. (C) The distribution of up and down-regulated proteins between HV and DM in strict filtering. White and gray bar indicate “increase” and “decrease”, respectively.
Figure 3.
Rader graph showing the GO annotation analysis. From the left, Biological Process (BP), Cellular Component (CC) and Molecular Function (MF). HV and DM were indicated with blue and red lines, respectively.
Figure 3.
Rader graph showing the GO annotation analysis. From the left, Biological Process (BP), Cellular Component (CC) and Molecular Function (MF). HV and DM were indicated with blue and red lines, respectively.
Figure 4.
The result of pathway analysis by Reactome. (A) >2.0 increased and (B) <0.5 decreased in the diabetic mellitus (DM) patient.
Table 1.
List of the Top 10 pathways which are affected by the proteins (up- or down-regulated) for a DM patient. In total, 340 and 344 proteins were analyzed, respectively. ND, not done.
Table 1.
List of the Top 10 pathways which are affected by the proteins (up- or down-regulated) for a DM patient. In total, 340 and 344 proteins were analyzed, respectively. ND, not done.
Group | Gender | n | Age | Alb/Cre | Proteinuria | eGFR | HbA1c |
---|
DM patient | male | 5 | 68 ± 3 | 5.2 ± 3.1 | - | 2.2 ± 1 | 6.4 ± 0.7 |
HV | male | 5 | 56 ± 4.4 | ND | - | ND | ND |
Table 2.
List of the Top 10 pathways, which were affected by the up- or down-regulated proteins for the DM patient. In total, 340 and 344 proteins were analyzed, respectively.
Table 2.
List of the Top 10 pathways, which were affected by the up- or down-regulated proteins for the DM patient. In total, 340 and 344 proteins were analyzed, respectively.
Pathway (Increased) | Count | p Value |
---|
Diseases of signal transduction | 50 | 1.11 × 10−16 |
Signaling by Receptor Tyrosine Kinase | 53 | 1.11 × 10−16 |
PI3K/AKT Signaling in Cancer | 25 | 1.11 × 10−16 |
Signal Transduction | 102 | 4.44 × 10−16 |
Intracellular signaling by second messengers | 32 | 1.22 × 10−15 |
Disease | 62 | 1.78 × 10−15 |
PIP3 activates AKT signaling | 30 | 3.33 × 10−15 |
Negative regulation of the PI3K/AKT network | 21 | 6.11 × 10−15 |
Signaling by FGFR in disease | 17 | 4.52 × 10−14 |
Signaling by SCF-KIT | 14 | 1.62 × 10−13 |
Pathway (Decreased) | Count | p Value |
Neutrophil degranulation | 64 | 1.11 × 10−16 |
Platelet degranulation | 30 | 1.11 × 10−16 |
Regulation of IGF transport and uptake by IGFBPs | 31 | 1.11 × 10−16 |
Innate immune system | 100 | 1.11 × 10−16 |
Response to elevated platelet cytosolic Ca2+ | 30 | 2.22 × 10−16 |
Post-translational protein phosphorylation | 27 | 4.44 × 10−16 |
Homeostasis | 63 | 1.67 × 10−12 |
Platelet activation, signaling and aggregation | 36 | 2.70 × 10−13 |
Immune system | 121 | 4.97 × 10−10 |
Binding and Uptake of Ligands by Scavenger Receptor | 21 | 2.21 × 10−9 |