Clinical characteristics of COVID-19 subjects
The clinical characteristics of COVID-19 patients and healthy controls are shown in Table 1. There were no significant differences regarding baseline characteristics between both groups as regards to age, gender, and smoking status. All COVID-19 patients were admitted to the intensive care unit (ICU) because of acute respiratory distress syndrome (ARDS) comorbidity, and all of them had polypnea with lymphocytopenia (0.3 × 109/L with IQR 0.25–0.55, n = 5) and extremely elevated lactate dehydrogenase (397 U/L with IQR 356–535, n = 5) and D-dimer (1390 µg/mL with IQR 741–4667, n = 5) levels. Blood laboratory tests showed elevated inflammatory indexes, including white cell count (11.1 × 109/L with IQR 7.30–12.8, n = 5) and interleukin-6 (IL-6) (22.2 pg/mL with IQR 9.40–60.0, n = 5) in COVID-19 patients. In addition, the chest CT scans of all patients revealed the characteristic imaging features of COVID-19 in the forms of consolidation, ground-glass opacity, and bilateral pulmonary infiltration.
Table 1
Demographic, clinical, laboratory and radiographic findings of patients.
| Total | COVID-19 | Healthy | p value |
| n = 10 | n = 5 | n = 5 | |
Demographics and clinical characteristics |
Age, years | | 70(66–72) | 69(63–75) | 0.94 |
Male | 7(70.0) | 5(100.0) | 2(40.0) | 0.71 |
Death | 0 | 0 | 0 | — |
ICU admission | 5(50.0) | 5(100.0) | 0 | — |
ICU length of stay, days | 37(10–43) | 37(10–43) | — | — |
Hospital length of stay, days | 45(41–48) | 45(41–48) | — | — |
Time from illness onset to | 57(53–68) | 57(53–68) | — | — |
hospital admission, days | | | | |
Severe | 5(50.0) | 5(100.0) | 0 | — |
Ever smoke | 6(60.0) | 4(80.0) | 2(40.0) | 0.87 |
ARDS comorbidity | 5(100.0) | 5(100.0) | 0 | — |
Respiratory rate | 20(14–20) | 20(14–20) | — | — |
> 24 breaths per min | 1(10.0) | 1(20.0) | 0 | — |
Pulse ≥ 100 beats per min | 1(10.0) | 1(20.0) | 0 | — |
O2 pressure | — | 82.8(69.0-110.0) | — | — |
O2 concentration | — | 95.3(93.3–95.4) | — | — |
Fever (temperature ≥ 37.3 °C) | 1(10.0) | 1(20%) | 0 | — |
Cough | 4(80.0) | 4(80.0) | 0 | — |
Sputum | 0 | 0 | 0 | — |
Myalgia | 0 | 0 | 0 | — |
Fatigue | 2(40.0) | 2(40.0) | 0 | — |
Diarrhoea | 0 | 0 | 0 | — |
Vomiting | 0 | 0 | 0 | — |
Rhinobyon | 0 | 0 | 0 | — |
Hemoptysis | 0 | 0 | 0 | — |
Headache | 0 | 0 | 0 | — |
Sorethroat | 1(10.0) | 1(20.0) | 0 | — |
Polypnea | 5(100.0) | 5(100.0) | 0 | — |
Shiver | 0 | 0 | 0 | — |
Laboratory findings |
White blood cell count, × 10⁹/L | — | 11.1(7.30–12.8) | — | — |
Lymphocyte count, × 10⁹/L | — | 0.30(0.25–0.55) | — | — |
Monocyte count, × 10⁹/L | — | 0.40(0.35–0.65) | — | — |
Platelet count, × 10⁹/L | — | 117.0(87.0-212.5) | — | — |
Lactate dehydrogenase, U/L | — | 397(356–535) | — | — |
High-sensitivity cardiac | — | 0.01(0.005–0.03) | — | — |
troponin I, pg/mL | — | | — | — |
Prothrombin time, s | — | 15.7(13.6–18.1) | — | — |
D-dimer, µg/mL | — | 1.390(0.741–4.667) | — | — |
IL-6, pg/mL | — | 22.2(9.40–60.0) | — | — |
Procalcitonin, ng/mL | — | 0.27(0.09–0.43) | — | — |
CRP, | — | 2.7(1.5–12.9) | — | — |
DBIL | — | 4.1(3.0-8.7) | — | — |
TBIL | — | 13.6(11.9–20.4) | — | — |
CK-MB | — | 11.0(7.0–18.0) | — | — |
Cr | — | 77.0(69.1–91.7) | — | — |
Imaging features | | | | |
Consolidation | 5(50.0) | 5(100.0) | 0 | — |
Ground-glass opacity | 5(50.0) | 5(100.0) | 0 | — |
Bilateral pulmonary infiltration | 5(50.0) | 5(100.0) | 0 | — |
Data are median (IQR) or n (%). P values were calculated by Mann-Whitney U test or Fisher’s exact test, as appropriate. |
Proteomic Profiling Of Airway Mucus From Covid-19 Patients
Airway mucus samples were obtained from five critical ill COVID-19 patients and 5 healthy controls. Label-free quantification of proteomic were used to analyze airway mucus from each individuals. The airway mucus from COVID-19 patients displayed distinct proteomic patterns compared to controls. In total, 2351 and 2073 proteins were identified and quantified in the airway mucus from COVID-19 patients and healthy controls, respectively. The proteomics datasets (including fold-change and p-values for the two groups comparisons) are provided in Table S1. In the quality control analysis, PCA, the median Relative SD (RSD) of all internal standards in each sample, protein mass and coverage distribution, and protein sequence distribution were calculated (Figure S1). Our data were acquired with a high degree of consistency and reproducibility.
Identification And Enrichment Analyses Of Covid-19 Unique Proteins
In the proteomic datasets, there was a total of 375 proteins uniquely present in the mucus from COVID-19 patients but not in controls (Table S2, Fig. 1-A). Out of them, 28.19% were located in the cytoplasm, 20.48% in extracellular, and 16.22% in the nucleus (Fig. 1-B, E). As illustrated in Fig. 1-D and G, the biological process analysis revealed that these proteins were enriched in granulocyte activation, neutrophil mediated immunity, myeloid leukocyte activation, and carboxylic acid metabolic processes. The molecular function analysis indicated that they were mainly distributed in three function processes: hydrogen ion transmembrane transporter activity, electron carrier activity, and antigen binding. KEGG pathway analyses demonstrated that there were five pathways enriched: amino acid degradation (valine, leucine and isoleucine degradation), amino acid metabolism (beta-Alanine, tryptophan, cysteine and methionine metabolism), oxidative phosphorylation, phagosome, and cholesterol metabolism (Fig. 1-C). From these pathway analyses, the proteins with high frequency existence in at least two pathways were ACADS, ACAT1, ACTG1, ALDH2, ALDH3A2, ALDH6A1, ATP5F1C, CASP8, COX5B, COX6B1, CYC1, DLD, HADH, HADHA, HLA-DMB, HLA-DRB1, MT-CO3, NDUFS1, SLC25A5, SLC25A6, UQCRC2, VDAC1 and VDAC1-3 (Fig. 1-H).
Identification And Enrichment Analyses Of These Differential Expressed Proteins
In the above proteomic datasets, 92 differential expressed proteins (DEPs) between two groups were identified (Fig. 2A-D ), including 46 up-regulated and 46 down-regulated proteins in the mucus from COVID-19 group with a fold change ≥ 1.5 or ≤ 0.67 and a p-value < 0.05 (Fig. 2A-D ). A total of 43.48% of these proteins were distributed in extracellular compartment, 25% in cytoplasm, and 13.04% in nucleus (Fig. 2-E). Out of the 92 DEPs, 33 of them (35%) were present in at least two pathways (Fig. 3A). Pathway and network enrichment analyses revealed that most of these DEPs were associated with metabolic, complement and coagulation cascades, lysosome, and cholesterol metabolism pathways (Fig. 3B). Among them, the top ten ranked proteins were LAMP2, TYMP, CTSS, PLTP, HBA1, and RAB11B according to differential significance level (Fig. 3C) and ASS1, FGG, GOT1 and ALDH3A1 by high-frequency existence in at least two pathways (Fig. 3D).
Next, GO and KEGG functional enrichment analyses were performed to annotate the potential functional implication of these differently grouped DEPs, which revealed that protein activation cascade, immunoglobulin mediated immune response, B cell mediated immunity, and leukocyte migration processes were enriched; most of these proteins were also located in extracellular space, cytoplasm, and extracellular. The molecular function of these proteins was primarily distributed on three function processes: serine-type peptidase activity, serine-type endopeptidase activity, and serine hydrolase activity (Fig. 4-A-C). KEGG pathway and heatmap analyses revealed that these DEPs were significantly enriched in amino acid metabolism (phenylalanine/ arginine biosynthesis/tyrosine) and cholesterol metabolism (Fig. 4-D and Fig. 5). Therefore, the final dysregulated proteins were selected, including GOT1, ALDH3A1, ASS1, APOH, PLTP1, and APOB from KEGG (Fig. 4-E, F); SERPINA1, FGG, FGB, ORM1, and AHSG based on PPI networks, which had maximum number of nodes (Fig. 4-H, G).
GO enrichment analysis was also conducted for the 46 up-regulated proteins and the 46 down-regulated proteins, respectively (Fig. 6-A, C). For the 46 up-regulated proteins, the significantly altered molecular function terms comprised: (a) Serine-type endopeptidase activity, (b) Serine-type peptidase activity, serine hydrolase activity, and (c) Antigen binding; the biological process terms comprised: (a) Blood coagulation, fibrin clot formation, (b) Regulation of blood vessel size, (c) Antimicrobial humoral response, (d) Protein activation cascade, (e) Immunoglobulin mediated immune response, (f) B cell mediated immunity, and (g) Feceptor-mediated endocytosis. Most of them were located in extracellular space. For the 46 down-regulated proteins, the molecular function terms mainly involved: growth factor activity. The biological process terms involved: (a) Maintenance of apical/basal cell polarity, (b) Retrograde tansport, endosome to plasma membrane, (c) Plasma membrane tubulation, and (d) Fructose 1,6-bisphosphate metabolic process. As shown in Fig. 6-B, D, the network was enriched for the following pathways (for the up-regulated proteins): (a) Arginine biosynthesis, (b) Alanine, aspartate and glutamate metabolism, (c) Cholesterol metabolism, and (d) Complement and coagulation cascades. Pathway enrichment for the 46 down-regulated proteins were primarily distributed on Glycolysis/ Gluconeogenesis.