| Literature DB >> 35464963 |
Yan Xie1,2,3,4, Li Yang1,2,3,4, Pengfei Cao1,4, Shen Li1,2,3,4, Wentao Zhang1,2,3,4, Wei Dang1,2,3,4, Shuyu Xin1,2,3,4, Mingjuan Jiang1,2,3,4, Yujie Xin1,2,3,4, Jing Li1,2,3,4, Sijing Long1,2,3,4, Yiwei Wang1,2,3,4, Senmiao Zhang1,2,3,4, Yang Yang1,2,3,4, Jianhong Lu1,2,3,4.
Abstract
Epstein-Barr virus (EBV)-associated hemophagocytic lymphohistiocytosis (EBV-HLH) is a life-threatening syndrome, which is caused by EBV infection that is usually refractory to treatment and shows relapse. The development of new biomarkers for the early diagnosis and clinical treatment of EBV-HLH is urgently needed. Exosomes have been shown to mediate various biological processes and are ideal non-invasive biomarkers. Here, we present the differential plasma exosomal proteome of a patient with EBV-HLH before vs. during treatment and with that of his healthy twin brother. A tandem mass tag-labeled LC-MS technique was employed for proteomic detection. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses indicated that differential proteomic profiles were related to virus infection, coagulopathy, nervous system dysfunction, imbalance of immune response, and abnormal liver function. The candidate biomarkers were first identified in the patient's plasma exosomes at different treatment and follow-up time points. Then, 14 additional EBV-HLH exosome samples were used to verify six differentially expressed proteins. The upregulation of C-reactive protein, moesin, galectin three-binding protein, and heat shock cognate 71 kDa protein and the downregulation of plasminogen and fibronectin 1 could serve as potential biomarkers of EBV-HLH. This plasma exosomal proteomic analysis provides new insights into the diagnostic and therapeutic biomarkers of EBV-HLH.Entities:
Keywords: Epstein-Barr virus; biomarker; exosomes; hemophagocytic lymphohistiocytosis; quantitative proteomics
Year: 2022 PMID: 35464963 PMCID: PMC9019563 DOI: 10.3389/fmicb.2022.821311
Source DB: PubMed Journal: Front Microbiol ISSN: 1664-302X Impact factor: 5.640
Summary of the patients’ laboratory test results.
| Inspection items | Reference range | Detection result |
| Hemoglobin (g/L) | 120∼160 | 65 |
| Reticulocyte (%) | 0.5∼1.5 | 0.41 |
| Leukocyte count (every 10^9/L) | 4–10 | 3.21 |
| Platelet count (every 10^9/L) | 100–300 | 38 |
| Aspartate aminotransferase (U/L) | 0–40 | 473.3 |
| Alanine aminotransferase (U/L) | 0–40 | 348.2 |
| Glutamine transpeptidase (U/L) | 3–50 | 204.4 |
| Alkaline phosphatase (U/L) | 45–115 | 13.9 |
| Total bilirubin (μmol/L) | 1.71–17.1 | 26.0 |
| Direct bilirubin (μmol/L) | 1.71–7 | 17.0 |
| Creatine kinase isozyme (U/L) | 0–18 | 40.6 |
| 0–0.55 | 12.725 | |
| Plasma fibrinogen (g/L) | 2–4 | 1.5 |
| Plasma prothrombin time (s) | 10–14 | 16.9 |
| Triglyceride (mmol/L) | 0.56–1.7 | 3.89 |
| Ferritin (μg/L) | 15–200 | >40,000 |
FIGURE 1Bone marrow samples and plasma exosomal samples obtained from patients. (A) Wright–Giemsa staining of a smear of bone marrow aspirate shows hemophagocytic macrophages, including one with numerous platelets and red cells. (B) Overview of methodological approaches in high-throughput mass spectrometry-based proteomic analyses of extracellular vesicles. (C) Similar protein amounts (measured with the BCA assay) of six plasma exosome samples run on 4–20% gradient SDS-PAGE gels. The protein profile in the gel was visualized by Coomassie brilliant blue staining. (D) Western blot analysis of the positive exosome markers HSP70, TSG101, and CD63 and the negative exosome marker calnexin. (E) Transmission electron microscopy appearance of exosomes (bar, 100 nm).
FIGURE 2Characteristics of the plasma exosomal proteins and protein–protein interaction mapping. (A) Length distribution of peptides detected by LC-MS/MS after trypsin digestion. (B) Venn diagram presentation of overlaps and differences between identified exosomal proteins and the ExoCarta database. (C) Statistical information of differentially expressed proteins among the three groups of samples. (D) PPI network mapping of upregulated differentially expressed proteins in patients with EBV-HLH. (E) PPI network mapping of downregulated differentially expressed proteins in patients with EBV-HLH.
FIGURE 3Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis of differentially expressed proteins. (A) Molecular function enrichment analysis of different proteins among the T1, T2, and control groups. (B) Biological process enrichment analysis of the detected differentially expressed proteins among the T1, T2, and control groups. (C) Top 14 enriched KEGG pathways are referenced among the T1, T2, and control groups.
FIGURE 4Verification of the differentially expressed proteins in plasma exosomes obtained from the patient with EBV-HLH by western blotting. (A,B) The expression levels of differentially expressed proteins during the treatment of the patient (T1–T6 represents the patient’s plasma exosome samples from the acute stage before treatment to 3 weeks after treatment and discharge, N1’ is the sample of his twin brother, N2’ is another healthy control sample). (C) The plasma exosomal protein expression level of the patient in the acute phase (T1) and 1 year after rehabilitation (R1) and that of the twin brother (N1’).
FIGURE 5Verification of differentially expressed proteins in plasma exosomes obtained from other patients with EBV-HLH by western blotting. (A,B) The expression level of differentially expressed proteins in plasma exosomes between the patients with EBV-HLH and healthy controls (H represents patients with EBV-positive HLH, N represents healthy controls). (C,D) The total protein loading amount of each sample in (A,B) was visualized by Coomassie brilliant blue staining.
FIGURE 6Statistical analysis of differentially expressed protein levels in plasma exosomes obtained from other patients with EBV-HLH. Gray value statistical analysis of differentially expressed protein levels of plasma exosomes between healthy controls (N) and other patients with EBV-positive HLH (H). A t-test was used to test the differences between groups.