Proteomic identification of exosomes derived from psoriasis cells using DIA

doi:10.21203/rs.3.rs-3734350/v1

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Proteomic identification of exosomes derived from psoriasis cells using DIA

https://doi.org/10.21203/rs.3.rs-3734350/v1

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Psoriasis has become a common chronic disease, and protein molecules carried by exosomes play an important regulatory role in the disease. So far, there have been no reports on proteomic studies of exosomes derived from human psoriasis cells. Normal cultured keratinocyte line HaCaT was used as the control group, with a concentration of 10ng/mL of TNF α stimulating HaCaT to form psoriasis cells as the test group; Extract and prepare exosomes from the culture supernatant using magnetic bead method, and identify the exosomes using TEM, NTA, and WB; The data-independent acquisition (DIA) method was used to detect the proteomic profile of extracellular vesicles, and GO, KEGG, Rectom and PPI analyses were performed. A total of 2796 exosomal protein molecules were identified. Compared with the control group, the test group had 131 significantly differentially expressed proteins (DEPs), of which 59 were upregulated (LogFC > 1) and 72 were downregulated (LogFC<-1); Among them, upregulated proteins ADO, Cbx1, and downregulated protein ARGLU1 were first discovered as regulatory molecules related to angiogenesis, stress stress, and inflammation in psoriasis exosomes. KEGG enrichment analysis showed that DEPs in the exosomes of psoriasis cells are involved in the Focal adhesion signaling pathway of inflammation and abnormal angiogenesis crosstalk. The results of this study provide new information on proteins in the exosomes of psoriasis cells and contribute to understanding the mechanisms of psoriasis occurrence and development. The expression of proteins in exosomes derived from psoriasis cells is still poorly understood. To our knowledge, our study detected for the first time the proteomic characteristics of psoriasis cells, and for the first time discovered that psoriasis exosomes carry protein molecules ADO, Cbx1 and ARGLU1. These results provide new strategies for further studying the biological functions of exosomes in the occurrence and development of psoriasis.

DIA

psoriasis

exosomes

protemics

DEPs

Exosomes with an average diameter of about ~ 100 nanometers are important intercellular communication carriers that can regulate neighboring and distant target cells through carrying protein and nucleic acid molecules, exerting various biological effects [1]. Inflammation and abnormal angiogenesis are two pathological processes in psoriasis, which mutually promote the occurrence and development of psoriasis. Exosomes can act as mediators of the inflammatory response [2], and and mediate the regulation of angiogenesis [3].

Research has extensively reported on the main pro-inflammatory cytokinesis associated with exosomes [4, 5]. Cytokines such as interl eukins and chemokines have been shown to be associated with exosomes produced by various cell types and act on a wide range of target cells to induce inflammation or immune regulatory responses. Psoriasis is a chronic inflammatory disease characterised by sharply demarcated erythematous and scaly skin lesions accompanied by systemic manifestations [6]. So far, there are no reports on the expression profile of proteins changes of psoriasis exosomes, so it is necessary to study the proteomic and function of exosomes.

In this investigation, a new technology developed in recent years, the data-independent acquisition (DIA), was used to analyze the proteomics of exosomes derived from psoriasis HaCaT cells stimulated with TNFα, and GO, KEGG, Reactiomics, and Protein-Protein Interaction (PPI) analysis were conducted.

1. Identification of exosomes: The exosome samples in this study showed a mixed population of a large number of exosomes, with predominantly intact vesicles, consistent with the classical exosome morphology. Exosomes with the characteristic cup shape with a diameter of around 70nm were observed in each sample (Fig. 1A ). All exosomes were small vesicles with similar sizes and a consistent morphology. Cup shape structures with a double membrane were visible. The exosomal samples were identified by WB, the positive protein markers Tsg101/HSP70/CD9 were expressed, while negative marker Calnexin was not expressed (Fig. 1B). All exosome samples were also analyzed using NTA. Particles with a size of around 70nm are predominant (Fig. 1C).

2. DAI analysis of exosomes:

2.1 BCA protein concentration measurement shows that the protein concentration in exosomes is 0.23µg/ul.

2.2 Global protein identification:

According to the use of spectronaut's built-in Pulsar for data retrieval, a spectrum library was established using DDA and DIA data, and the library identified the overall number of peptide segments and proteins, 21787 peptides and 2796 proteins were screened out. Among them, 2597 proteins were shared between the two groups, 20 proteins were found exclusively in the control group, and 92 proteins were found exclusively in the test group (Fig. 2A.). Normalize the raw data according to the median, and the corrected median is at the same horizontal position. According to the standard of significant difference of 1 times or more, a total of 131 significantly different proteins were detected in the test group and the control group, of which 59 were upregulated proteins; and of which 72 were down regulated proteins (Fig. 2B). The differential expression changes of differential proteins in the test group and control group (Fig. 2C).

2.3 We focused on analyzing differentially expressed proteins in the test group and identified the top 20 proteins with the most significant differential expression between the two groups, including 6 up-regulated proteins and 14 down-regulated proteins (Table 1).

It is worth noting that in addition to being related to cell cycle and proliferation, several potential new target protein molecules have been discovered, including ADO, Cbx1 and ARGLU1 protein molecules.

2.4 GO functional annotation analysis top 10 items with the most significant enrichment in each GO category. Perform GO annotation enrichment analysis on differentially expressed proteins. According to the GO database, differentially expressed proteins are classified into BP (biological processes), CC (cellular components), and MF (molecular functions) categories. We selected the top 10 terms with the highest enrichment in each category (Fig. 3 and Table 2). Significantly differential protein enriched GO terms in the test group compared with the control group were shown in Fig. 4.

Table 1

Top 20 proteins with the most significant differential expression
Rank	uniprot ID	Protein name	logFC	adj.P.Val
1	Q9NUQ8	ABCF3	2.218429442	0.427255926
2	Q96SZ5	ADO	4.543819901	0.711926883
3	Q8WYP5	AHCTF1	-3.509390766	0.137209698
4	P00568	AK1	1.006014887	0.73969047
5	P51857	AKR1D1	-2.130842417	0.66446882
6	P00352	ALDH1A1	-1.261601103	0.73969047
7	Q9BTT0	ANP32E	-1.759125388	0.629174083
8	P06727	APOA4	-1.96852584	0.66446882
9	Q9NRW3	APOBEC3C	2.111881947	0.711926883
10	P02656	APOC3	-3.10049461	0.711926883
11	P07741	APRT	-1.281353677	0.711926883
12	Q9NWB6	ARGLU1	-1.290280039	0.73969047
13	Q9NZN5	ARHGEF12	1.673449185	0.723871439
14	Q9UBW5	BIN2	-1.091285582	0.714418887
15	Q9NQY0	BIN3	1.145715089	0.711926883
16	P83916	CBX1	3.953528198	0.489893714
17	Q8IWP9	CCDC28A	1.221180153	0.66446882
18	Q4G0X9	CCDC40	-1.193916845	0.66446882
19	Q96MW1	CCDC43	-2.423908716	0.687735235
20	Q9Y232	CDYL	-1.41409279	0.66446882

Table 2

Top 10 items with the most significant enrichment in each GO category
GO category	Description	No. of proteins	-log10(P value)
Biological Process
	intermediate filament organization	11	1.77352E-09
	intermediate filament cytoskeleton organization	11	1.20022E-08
	intermediate filament-based process	11	1.20022E-08
	skin development	14	6.49569E-06
	epidermis development	15	6.85147E-06
	keratinization	8	2.77024E-05
	keratinocyte differentiation	10	5.49681E-05
	epidermal cell differentiation	10	0.000921715
	peptide cross-linking	4	0.020146586
	protein homotrimerization	3	0.024117141
Cellular component
	keratin filament	10	2.58014E-07
	intermediate filament	12	1.88796E-06
	intermediate filament cytoskeleton	12	6.59174E-06
	cornified envelope	7	6.59174E-06
	blood microparticle	6	0.018831382
	collagen-containing extracellular matrix	10	0.019712242
	cytosolic large ribosomal subunit	4	0.019712242
	cytosolic ribosome	5	0.019712242
	IgG immunoglobulin complex	2	0.054093395
	chylomicron	2	0.083332915
Molecular function
	structural constituent of skin epidermis	8	4.53971E-08
	structural constituent of cytoskeleton	8	0.000128151
	N6-methyladenosine-containing RNA binding	2	0.231058765
	phosphate ion binding	2	0.231058765
	intermediate filament binding	2	0.231058765
	cholesterol binding	3	0.231058765
	steroid binding	4	0.231058765
	acidic amino acid transmembrane transporter activity	2	0.231058765
	enzyme inhibitor activity	8	0.231058765
	structural constituent of ribosome	5	0.255735898

2.5 KEGG pathway enrichment analysis of exosomal proteins:

Using bioinformatics, KEGG pathway enrichment analysis was conducted for significantly differentially expressed proteins, and the top 20 most significant pathways were screened, including mainly biological systems, metabolism, genetic information processing and cellular processes. KEGG pathway analysis top 20 most significant pathways results are shown in a bar chart (Fig. 5A) and top 10 most significant pathways results are shown in a bubble diagram (Fig. 5B).

Multiple differentially expressed proteins in the KEGG enrichment analysis were involved in Immune infiltration pathways (Ribosome and Phenylalanine metabolism), Keratinocyte-regulating pathways (Focal adhesion pathway), angiogenesis pathways (NOD-like receptor signaling pathway and Phagosome pathway), and inflammation pathways (Neurotrophin signaling pathway and Toll − like receptor signaling pathway).

2.6 Reactome analysis of exosomal proteins:

Regarding Reactome results, Formation of the cornified envelope and Keratinization were both the most significant pathway and the most enriched. The differential proteins were analyzed using the reactive omics method, and the quantity of differential proteins on the top 20 pathways is shown in the bar chart (Fig. 6A) and top 10 most significant enrichment pathways are shown in a bubble diagram (Fig. 6B).

2.7 Analysis of protein-protein interactions (PPI) of extracellular vesicles:

The top 20 genes were identified as core genes by calculating the tightness of the connection of the Hub using the cytoHubba plug-in, namely, EXOSC5, KRT1, KRT10, KRT14, KRT16, KRT17, KRT19, KRT2, KRT5, KRT6C, KRT74, KRT78, KRT9, PDCD11, PELO, RPL23, RPL3, RPL37, RPL37A and

RPS24 (Fig. 7). There were strong interactions among these hub proteins, which may have an effect on the pathophysiological process of psoriasis. PPI network analysis reveals two core clusters, namely ribosome and keratin pathways, whose functions are involved in immune infiltration, inflammation, angiogenesis, and cell proliferation.

In psoriasis lesions, a positive feedback loop is formed between keratinocytes and immune cells. Under the stimulation of immune cytokines such as IL17 and TNFα, keratinocytes proliferate abnormally and further release inflammatory factors effectively promoting the development of psoriasis [7].

The exosome proteome provides new information for predicting the function of exosomes. Exosomes can carry proteins, lipids, and nucleic acids as signaling molecules to target cells, affecting skin homeostasis and leading to skin diseases [8].Clinical studies have confirmed that the levels of exosomal IL-17A in patients with moderate to severe psoriasis are significantly higher than those in patients with mild psoriasis [9].It can be seen that the relationship between psoriasis and exosomes is very close, and it is necessary to understand the components and function of exosomes derived from psoriasis cells.

DIA technology is currently one of the most attractive mass spectrometry acquisition technologies. It can be applied in the screening of clinical disease biomarkers, studying the mechanism of pathology, and studying drug targets. DIA has been widely used in clinical practice due to its high throughput, high resolution, and high repeatability [10]. Using TNFα inducing keratinocyte HaCat to form a psoriasis cell model is a commonly used method [11], therefore, exosomes derived from psoriasis model cells were selected in this investigation. Generally, exosomes need to be identified based on their characteristic size, morphology, and surface markers. Extracellular vesicles are small vesicles with a diameter of 30 to 150 nm and a cup-shaped cup shape appearance [12]. In this study, we observed cup-shaped vesicles through transmission electron microscopy. NTA detected the vast majority of exosomes, with a range of 70nm. These results indicate that the vesicles in the culture medium obtained in our study are exosomes. To conduct DAI analysis, we used three samples from the control group and three samples from the psoriasis cell model group for exosomes preparation and analysis. After normalizing the raw data according to the median, a total of 2796 proteins were identified, of which 131 were significantly differentially expressed protein molecules, 72 are downregulated out of 131 protein molecules, this result further supports that exosomes derived from psoriasis contain abundant protein molecules.

Oxygen homeostasis is crucial for physiological function and is disrupted in many diseases. ADO is a low oxygen affinity (high KmO2) amino terminal cysteine oxygenase that transduces the oxygen-regulated stability of proteins by the Ndegron pathway in human cells; its activity extends to other N-cysteine proteins, including the angiogenic cytokine interleukin-32[13]. Our study find that this molecule is significantly upregulated in extracellular vesicles derived from psoriasis model cells, providing a new target for studying the relationship between psoriasis and hypoxia.

ARGLU1 is a highly evolutionarily conserved transcriptional coactivator and RNA splicing modulator. The latest research indicates that ARGLU1 is a new embryonic development factor that can regulate the basal transcription and selective splicing of nerve cells [14], thereby affecting glucocorticoid signaling. The results of our study show that the ARGLU1 protein molecule in the exosomes derived from psoriasis cells is significantly downregulated, providing new insights into the relationship between stress responses such as emotions and psoriasis.

The Cbx1 protein can enhance the transcription and expression of Rev-erbα, exerting an anti-inflammatory effect[15]. This result shows that the Cbx1 protein molecule is significantly downregulated in the exosomes derived from psoriasis cells, providing a new target for elucidating the mechanism of psoriasis.

We conducted GO enrichment analysis on the screened DEPs. Our results showed that in the biological process category, the DEPs were involved mainly in skin development, keratinization, and keratinocyte differentiation. In the cellular component category, the DEPs were involved mainly in the extracellular region, and in the molecular function category, they were involved mainly in keratin filtration and extracellular matrix containing collagen, while the enriched proteins term related to molecular functions include the structural composition of the skin epidermis, enzyme inhibitor active proteins.

In the present study, we found that DEPs participated in top 10 KEGG pathways, including the

Ribosome, Phenylalanine metabolism, Purine metabolism, Long-term potentiation, Focal adhesion

Protein digestion and absorption, ECM-receptor interaction, Tyrosine metabolism, Phagosome

and Toll-like receptor signaling pathway.

Focal adhesions are closely related to cell adhesion, migration, differentiation, and apoptosis. A review suggests that focal adhesion kinase plays a crucial role in angiogenesis during embryonic development and cancer progression [16]. Focal adhesive components are targets of biochemical and mechanical stimulation, which can induce critical cell growth and differentiation, as well as regulate the extracellular micro-environment. Focal adhesion provides a flexible and specific tool for exchanging clues of vascular wall components in complex systems. It is a future target for the treatment and regulation of inflammation and vascular disorders [17]. KEGG results of this study indicate that the number of focal adhesion pathway protein components in psoriasis exosomes is the highest, with the highest level of significance. The results of this study show that exosome play a role in psoriasis through focal adhesion, which also explains the formation of the crosstalk between the complex inflammation and abnormal angiogenesis in psoriasis.

An increasing number of studies have shown that Keratin family proteins play an important regulatory role in psoriasis [18, 19]. The Reactome annotation analysis results of the present study indicate that keratinization, and formation of the cornered envelope pathway proteins are most significant, Further analysis revealed that members of the Keratin family proteins were mainly enriched in keratinization, and formation of the cored envelope pathway terms. Therefore, our result shows that exosomes play an undeniable regulatory role in psoriasis.

In the PPI network analysis of this study, 20 hub proteins with the highest correlation were selected to draw interaction diagrams, including EXOSC5, KRT1, KRT10, KRT14, KRT16, KRT17, KRT19, KRT2, KRT5, KRT6C, KRT74, KRT78, KRT9, PDCD11, PELO, RPL23, RPL3, RPL37, RPL37A and RPS24. The protein with the closest connection is usually the most important and is widely involved in cellular processes. The results of this study show that the two protein clusters, mainly composed of keratin protein family and ribosomal protein family, are closely related, indicating that these two protein family proteins play important roles in the occurrence and development of psoriasis.

In conclusion, proteins derived from psoriasis modeling cells stimulated by TNFα were significantly changed. We screened out the proteins that might affect the occurrence and development of psoriasis. The DEPs were involved in pathways such as keratinization, skin development, keratinocyte differentiation, collagen containing extracellar matrix, and structural constitution of skin epididymis, focal adhesion, etc, which is a key target in the interaction of multiple protein molecules in psoriasis. To our knowledge, our study for the first time detected the proteomic characteristics of psoriasis cells and found for the first time that psoriasis extracellular vesicles carry protein molecules ADO, ARGLU1, and Cbx1, the data obtained in this study lays the foundation for further studying the biological functions of exosomes in the formation of psoriasis.

1. Cell culture and reagents:

1.1 HaCaT cell line: immortalized keratinocyte cell line, cultured using HaCaT complete medium (SUNNCELL, China).

1.2 Modeling of psoriasis cells: According to reference [11], normal HaCaT cells were cultured in T25 culture bottles until 80% confluence, and a final concentration of TNF at 10 ng/mL was used α (Sigma) stimulates HaCaT cells for 24 hours.

2. Experimental grouping and preparation of cell culture supernatant:

Cultivate 3 samples for normal HaCaT as control group and cultivate 3 samples for modeling of psoriasis cells as test group, respectively, and finally collect cell culture supernatant. The collected culture supernatant was centrifuged at 300g for 10 minutes, followed by centrifugation at 3000g for 10 minutes. Finally, cell fragments were removed by filtration with a 0.22-micron filter membrane to obtain the supernatant for preparation of exosomes.

3. Preparation of exsomal protein samples:

3.1 Isolation, preparation, and identification of exosomes:

It uses the magnetic bead method kit (EVLiXiR # EV02-01-01, China) to extract extracellular vesicles from cell culture supernatant. To characterize the exosomes, transmission electron microscopy, particle size, and protein markers were performed.

3.2 Protein extraction: 300 µL of 8M urea was added to the sample and the protease inhibitor was added at 10% of the lysate. After centrifuging at 14,100×g for 20 min, the supernatant was collected. The protein concentration was determined using Bradford method, the rest was frozen to -80℃.

3.3 Protein digestion and desalination: A 100 µg aliquot of extracted proteins from each sample was then subjected to reduction. Adding 200 mM dithiothreitol (DTT) solution and incubating at 37°C for 1 h. The sample was diluted 4 times by adding 25 mM ammonium bicarbonate (ABC) buffer. Then adding trypsin (trypsin: protein = 1:50) and incubating at 37℃ overnight. The next day, adding 50µL 0.1% FA to terminate the digestion. Take 100µl 100% ACN to wash the C18 column, and centrifuge at 1200rpm for 3min. Wash the column once with 100 µl of 0.1% FA and centrifuge at 1200 rpm for 3 min. Replace the EP tube, add the sample, and centrifuge at 1200rpm for 3min. Wash the column twice with 100 µl of 0.1% FA and centrifuge at 1200 rpm for 3 min. Wash once with 100 µl of pH 10 water. Replace the EP tube and elute with 70% ACN. The eluents of each sample were combined and lyophilized. Store at -80°C until loading.

4. LC-MS/MS:

For spectral library generation, samples were fractionated using a high pH reversed-phase. fractionator as previously described and measured in DDA mode. Briefly, the mass spectrometer was operated on a quadrupole Orbitrap mass spectrometer (Q Exactive HF-X, Thermo Fisher Scientific, Bremen, Germany) coupled to an EASY nLC 1200 ultra-high. pressure system (Thermo Fisher Scientific) via a nano-electrospray ion source. 500 ng of peptides were loaded on a 25 cm column (150 µm inner diameter, packed using ReproSil-Pur C18-AQ 1.9- µm silica beads; Beijing Qinglian Biotech Co.,Ltd, Beijing, China). Peptides were separated using a gradient from 8–12% B in 7 min, then12–30% B in 48 min and stepped up to 40% in 10 min followed by a 15 min wash at 95% B at 600 nl per minute where. solvent A was 0.1% formic acid in water and solvent B was 80% ACN and 0.1% formic acid in water. The total duration of the run was 80 min. Column temperature was kept at 60°C using. an in-house-developed oven. Briefly, the mass spectrometer was operated in “top-40” data-dependent mode, collecting MS spectra in the Orbitrap mass analyzer (120,000 resolution, 350–1500 m/z range) with an automatic gain control (AGC) target of 3E6 and a maximum ion injection time of 80 ms. The most intense ions from the full scan were isolated with an isolation. width of 1.6 m/z. Following higher-energy collisional dissociation (HCD) with a normalized collision energy (NCE) of 27, MS/MS spectra were collected in the Orbitrap (15,000 resolution) with an AGC target of 5E4 and a maximum ion injection time of 45 ms. Precursor dynamic exclusion was enabled with a duration of 16 s. For DIA, the acquisition method consisted of one MS1 scan (350 to 1500 m/z, resolution 60,000, maximum injection time 50 ms, AGC target 3E6) and 42 segments at varying isolation windows from 14 m/z to 312 m/z (resolution 30,000, maximum injection time 54 ms, AGC target 1E6). Stepped normalized collision energy was 25, 27.5 and 30. The default charge state for MS2 was set to 3.

5. Data analysis

5.1 The identification and quantitation of protein:

Mass spectrometry data processing The MS data of the fractionated pools (DDA MS data, 6 fractions) and the single-shot subject samples (DIA MS data) were used to generate a DDA library and direct-DIA-library, respectively, which were computationally merged into a hybrid library in the Spectronaut software (Biognosys, version 15.7.220308.50606). The hybrid spectral library was used to search the MS data of the single-shot samples in the Spectronaut software, for final protein identification and quantitation. All searches were performed against the uniprot Homo sapiens SP proteome database (20,407 target sequences downloaded on 2023-03–07). Searches used carbamidomethylation as fixed odification and acetylation of the protein N-terminus, oxidation of methionines as variable modifications. Default settings were used for other parameters. In brief, a trypsin/P proteolytic cleavage rule was used, permitting a maximum of two miscleavages and a peptide length of 7–52 amino acids. Protein intensities were normalized using the “Local Normalization” algorithm in Spectronaut based on a local regression model (Callister et al, 2006). Spectral library generation stipulated a minimum of three fragments per peptide, and maximally, the six best fragments were included. A protein and precursor FDR of 1% were used and protein quantities were reported in samples only if the protein passed the filter (“Q-value sparse” mode data filtering).

5.2 The functional analysis of protein:

Gene Ontology (GO) and InterPro (IPR) analysis were conducted using the interproscan-5 program against the non-redundant protein database, and the databases COG (Clusters of Orthologous Groups) and KEGG (Kyoto Encyclopedia of Genes and Genomes) were used to analyze the protein family and pathway. The probable interacting partners were predicted using the STRING-db server (http://string.embl.de/) based on the related species. STRING is a database of both known and predicted protein-protein interactions. The enrichment pipeline was used to perform the enrichment analysis of GO, and KEGG, respectively. Further Reactome and PPI analysis were conducted.

Conflicts of Interest

All authors declare that they have no conflict of interest. Please see original article for full author disclosures.

Fundings

This work was supported by the National Natural Science Foundation of China (82172107), Shenzhen Municipal Science and Technology Innovation Committee (JCYJ20210324135014040, JCYJ20220818103407016), and Longgang District Special Fund for Economic and Technological Development (LGKCYLWS2022007).

Author Contribution

Boping Zhang conducted all the experiments and authored the research manuscript, while Fenfang Wu provided the protocol design.

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Proteomic identification of exosomes derived from psoriasis cells using DIA

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