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Global Translational Medicine ECM receptor pathway in endotheliocytes after MI

peptide spectrum match identification adhered to a 1% the left ventricular area (IS/LV%). The results indicated a
false discovery rate. significantly larger infarct size in the MI group compared to
the sham operation group, as depicted in Figure 1A. After
2.4. Data normalization 14 days of MI, heart samples were collected, and paraffin

Our protein normalization methodology relies on the sections were prepared. Sirius Red staining revealed
fundamental assumption that the sum of intensities collagen deposition (stained in red color) in the heart,
across six tags in the six-complex system remains observed and photographed using a light microscope. The
constant. Following normalization, we evaluated the collagen area was quantified using ImageJ software, and the
relative abundance of MI and sham in our experiment by collagen volume fraction (CVF) was calculated. Sirius Red
calculating the ratio of average reporter ion intensities to staining demonstrated a notably higher level of collagen
trypsin peptide reactions. The resulting expression ratios deposition in the MI group compared to the sham group,
for MI/sham or sham/MI in three pairs of repeat samples as illustrated in Figure 1B. The corresponding statistical
constituted our three-paired sample analysis. We set a results are presented in Figure 1C, showing IS/LV% and
1.5-fold change as our threshold for differential expression, CVF% data. In summary, the MI model was successfully
indicating that the ratio of MI/sham or sham/MI surpasses established, and evident cardiac fibrosis was observed after
1.5. Statistical significance for observed protein alterations 14 days, as evidenced by the results of infarct size analysis
was assessed using the Student’s t-test. and collagen deposition assessment.
2.5. Bio-informatics analysis 3.2. Isolation of primary cardiac ECs and
quantitative proteomic analysis of TMT
Utilizing the UniProt-GOA database, we categorized
proteins through Gene Ontology (GO) analysis, considering After 14 days, the mice were euthanized under anesthesia.
cellular components, molecular functions, or biological Heart samples were dissected and subjected to digestion.
processes. To explore functional enrichment, we employed The isolated ECs were sorted using CD31 magnetic
the Kyoto Encyclopedia of Genes and Genomes (KEGG) microbeads. Flow cytometry was employed to assess the
database, organizing pathways via the KEGG hierarchical purity of ECs. The remaining cells underwent protein
classification method. The InterPro database was used to extraction, trypsin hydrolysis, and TMT labeling and were
investigate various functional domains of differentially subsequently analyzed by mass spectrometry. The detailed
expressed proteins. Fisher’s exact test assessed the process is illustrated in Figure 2A. The results revealed that
enrichment level for the aforementioned protein functions, the proportion of ECs was 88.96 ± 0.48% (n = 3) (Figure 2B).
with P < 0.05 indicating significant differences. To unravel Employing a 1.5-fold change as the threshold for protein
potential interrelationships and discrepancies among differential expression, we identified 395 proteins in both
proteins within a specific KEGG pathway, cluster analysis the MI and sham groups. Among these, 161 proteins
based on functional enrichment was employed. We collected exhibited up-regulation, while 234 proteins displayed
functional classification data and associated enrichment down-regulation (P < 0.05) (Figure 2C). A differential
P-values, screening for significant enrichment (P < 0.05) protein volcano map, plotting the logarithm of log2 as
across at least one proteome. The P-value data matrix, the abscissa and the logarithm of -log10 as the ordinate,
converted using log10, was classified through Z-transform. was generated. In the figure, red dots signify up-regulated
For the exploration of protein-protein interaction networks, proteins with significantly different expression, while blue
we utilized the string database (v.10.5). Interactions with a dots represent down-regulated proteins with significantly
confidence level exceeding 0.7 were extracted and visualized different expression (Figure 2D).
using the R software package, networkD3. 3.3. Go analysis of differential proteins
3. Results We classified the differential proteins into GO subclasses
and presented them in terms of biological processes,
3.1. The establishment of MI model
cellular components, and molecular functions (Figure 3).
After ligating the left anterior descending coronary artery In the biological process category, 122 proteins were
for 24 h, the mice were euthanized under deep anesthesia. up-regulated in cellular processes, 105 in single-organism
Following perfusion with ice-cold PBS, the mouse heart processes, and 101 in biological regulation. Conversely,
was isolated and preserved. The non-infarction area the down-regulated proteins encompassed 189 proteins
(red area) and infarct area (white area) were distinguished in single-organism processes, 185 in cellular processes,
through TTC staining. Infarct size was semi-quantitatively and 161 in metabolic processes. Within the cellular
compared by calculating the percentage of infarct size to component classification, 151 proteins in cell components

Volume 2 Issue 4 (2023) 4 https://doi.org/10.36922/gtm.2217