Analysis of secreted small extracellular vesicles from activated human microglial cell lines reveals distinct pro‐ and anti‐inflammatory proteomic profiles

Microglia are a specialized population of innate immune cells located in the central nervous system. In response to physiological and pathological changes in their microenvironment, microglia can polarize into pro‐inflammatory or anti‐inflammatory phenotypes. A dysregulation in the pro‐/anti‐inflammatory balance is associated with many pathophysiological changes in the brain and nervous system. Therefore, the balance between microglia pro‐/anti‐inflammatory polarization can be a potential biomarker for the various brain pathologies. A non‐invasive method of detecting microglia polarization in patients would have promising clinical applications. Here, we perform proteomic analysis of small extracellular vesicles (sEVs) derived from microglia cells to identify sEVs biomarkers indicative of pro‐inflammatory and anti‐inflammatory phenotypic changes. sEVs were isolated from microglia cell lines under different inflammatory conditions and analyzed by proteomics by liquid chromatography with mass spectrometry. Our findings provide the potential roles of sEVs that could be related to the pathogenesis of various brain diseases.

are two classical inflammation-related phenotypes based on in vitro studies: pro-inflammatory or anti-inflammatory phenotype microglia.However, it is essential to note that microglia exhibit more complex and intermediate activation phenotypes in vivo [6].
Pro-inflammatory microglia secret inflammatory cytokines and chemokines such as tumor necrosis factor-alpha (TNF-α), interleukin (IL)−6, IL-1β, IL-12, monocyte chemoattractant protein-1, which have been reported to result in neuronal dysfunction and neurodegenerative diseases, including Alzheimer's disease (AD) [8], Parkinson's disease (PD) [9], and multiple sclerosis (MS) [7].In contrast, antiinflammatory activation is induced by anti-inflammatory cytokines such as IL-4, IL-10, and transforming growth factor-beta (TGFβ) [7], which produce anti-inflammatory cytokines, growth factors, and neurotrophic factors leading to tissue repair, phagocytosis of cellular debris, and promoting neuronal survival.In the case of primary and secondary CNS malignancies, anti-inflammatory microglia have been implicated in promoting tumor growth through building an immunosuppressive tumor microenvironment [10], and associated with therapy resistance due to immunosuppressive properties, limiting the effectiveness of these treatments [11,12].Therefore, conducting comprehensive research to investigate microglia activation in response to various brain disorders is necessary and may potentially help guide therapeutic approaches.
To enable accurate monitoring of brain disorders without the limitations of tissue biopsies, liquid biopsies have emerged as an alternative technique that provides a non-invasive sample source, essential for longitudinal monitoring [13].Small extracellular vesicles (sEVs) can serve as indicators of the inflammatory state of microglia due to their ability to carry proteins that reflect the parental cellular condition [14].Importantly, sEVs have been shown to readily cross the bloodbrain barrier and could be utilized to understand the activation of the innate immune system in the CNS [15].In the context of inflammation, microglia could secrete sEVs containing various inflammatory proteins that are involved in immune responses and inflammatory processes [16].For example, the presence of pro-inflammatory cytokines (IL-1β, TNF-α) associated with inflammation in sEVs derived from microglia indicates an activated or inflammatory state of these cells [17].In contrast, the enrichment of anti-inflammatory factors (such as IL-4, IL -10) in sEVs may suggest an anti-inflammatory microglial state [17].The analysis of sEV proteins can provide valuable insights into the underlying mechanisms of how sEVs can reflect the activation of the innate immune system in the CNS.
A precise and comprehensive distinction of specific phenotypes of microglia-derived sEVs is important to understand microglia functions and tissue state in a complex microenvironment [3].However, the biological process and molecular composition of human microgliaderived sEVs still need to be better understood [3,16,17].Herein, we provided a broad analysis of human microglia sEVs under both proinflammatory and anti-inflammatory conditions to understand how microglia sEVs are involved in various brain diseases.In this study, we focused on proteomic analysis of differentially enriched proteins

Significance Statement
While recent advancements in neuroinflammation have implicated the important role microglia play, little is known on the protein composition of LPS-and IL-4/10/TGFβ-sEV content and how this can be exploited to further understand and monitor microglia polarization.The present study suggests that upon by LPS and IL-4/IL-10/TGFβ stimulation, HMC3 microglia release sEVs with a distinct proteomic profile reflective of inflammatory conditions.LPS-sEVs are enrichment for proinflammatory proteins, while IL-4/10/TGFβ-sEVs have a significant downregulation of protein abundance related to inflammation.These proteins can be used to identify the functional phenotype of microglia and may contribute to the understanding of the role of microglia sEVs in CNS disorders.in sEVs secreted from different states of microglia.We investigated the phenotypic plasticity of sEVs from the human microglia cell line (HMC3) stimulated with either lipopolysaccharides (LPS), or a cytokine cocktail of IL-4, IL-10, and TGFβ.sEVs were purified using size exclusion chromatography (SEC) and then characterized in terms of size, concentration and tetraspanin biomarkers by nanoflow cytometry and observed morphological changes of microglial cells after the activation.
Importantly, based on the proteomic analysis from mass spectrometry, we observed phenotypical shift from resting microglia sEVs to distinct sEVs phenotypes after microglia activation.This results in distinct protein enrichment in sEVs.Furthermore, Gene Ontology analysis of differentially abundant proteins in sEVs revealed distinct pro-and-antiinflammatory profiles reflective of the activation state in microglia.
In summary, our research findings provide comprehensive information on the proteomic levels of activated microglia sEVs and aid in biomarker discovery to understand the innate immune system in the CNS.

sEV purification
After 48 h cell culture media was collected and centrifuged at 800 × g for 10 min to remove cell debris.The supernatant was subsequently filtered through a polyethersulfone 0.22 µm sterile membrane (Merk) to remove larger vesicles.The resulting conditioned culture media was concentrated to ∼500 µL using a Centricon Plus-70 100-kDa centrifugal filter device (Merck) at 3000 × g at 4 • C, followed by SEC using qEVoriginal-70 nm columns (IZON) and elution with PBS.The first 1.6 mL of high sEV-containing fraction were collected and concentrated to ∼100 µL using an Amicon Ultra-4 10-kDa centrifugal filter device (Merck).

Nanoparticle tracking analysis
Nanoparticle tracking analysis (NTA) was used to determine sEV size.
All samples were diluted into a final volume of 1 mL.The following

Transmission electron microscopy
For electron microscopic analysis, sEVs were fixed with an equal volume of 2% glutaraldehyde for 30 min at room temperature.6 µL of fixed sample was loaded on Formvar/carbon-coated electron microscopic grids (Electron Microscopy Science) and incubated for 10 min.
Excess liquid was removed by blotting.The grid was washed three times by brief contact with 100 µL of MilliQ water, followed by blotting to remove excess liquid.To contrast the samples, the grid was placed on 30 µL of 2% uranyl acetate (w/v) for 5 min and excess fluid was removed by blotting gently on filter paper.Grids were left to air dry and observed using transmission electron microscopy (Hitachi HT7700).

RT-qPCR
Total RNA was extracted from cell lysates using the RNeasy mini kit (Qiagen, #74104) according to the manufacturer's instruction.
Genomic DNA was removed using RNase-free DNase I (Qiagen).
The concentration and purity of extracted RNA were assessed using Nanodrop 1000 spectrophotometer (Thermo Fisher Scientific).cDNA samples were synthesized from 200 ng of isolated RNA using Super-

Proteomics sample preparation
Resting, LPS-stimulated and IL-4/10/TGFβ-stimulated HMC3 sEV samples were prepared in triplicate, respectively.The protein concentration of sEVs was determined by using Micro BCA™ Protein Assay Kit (Thermo Fisher Scientific) following manufacturer guidelines.For each preparation, 5 µg of protein was reduced with 500 mM dithiothreitol for 1 h at 70

GO enrichment analysis
To determine the biological and functional properties of differentially enriched proteins, Gene Ontology (GO) analysis was performed to provide three terms, including biological process, molecular function, and cellular component by searching the GO database (https://david. ncifcrf.gov/home.jsp)[19,20].Significant GO functions and pathways were examined within different enriched proteins (FDR < 0.05).

RESULTS
As shown in Figure 1, in this study, we investigated the activation of resting microglia into pro-and ant-inflammatory states, and subsequently purified sEVs from these activated microglia.The sEVs were then subjected to proteomic profiling using LC-MS.By analyzing the differentially enriched proteins of sEVs under distinct activated conditions, we aimed to gain insights into the molecular characteristics associated with different states of microglia.This investigation of microglia sEV composition under various inflammatory conditions may contribute to our understanding of the roles of microglia in brain diseases.
To establish pro-and anti-inflammatory phenotypes of microglia, morphological changes of microglia were analyzed after treatment with either LPS (1000 ng/mL) or a cytokine cocktail consisting of IL-4 (50 ng/mL) + IL-10 (20 ng/mL) + TGFβ (20 ng/mL).The cell viability after 48 h treatment was detected using trypan blue staining to confirm the majority of microglia remained viable throughout the treatment period (Supplementary Figure 1).In the experimental design, the combination of IL-4, IL-10 and TGFβ was aimed at investigating synergistic effects on protein expression under the anti-inflammatory condition, with the aim of mimicking the in vivo environment.However, it is necessary to note that IL-10 has a fundamental role in modulating immune response and in maintaining cell homeostasis, ensuring that F I G U R E 1 Schematic of protein profiling of secreted sEVs from LPS-stimulated and IL-4/10/TGFβ-stimulated microglia.Microglia were stimulated using LPS or a combination of IL-4, IL10, and TGFβ to polarize into pro-and anti-inflammatory states, respectively.Afterward, sEVs were purified from resting and activated microglia, and their protein content was analyzed using LC-MS.The identified proteins provide biomarkers to monitor the role of microglia in the pathogenesis of various neurological disorders.they are appropriately balanced [23].Hence IL-10 potentially mitigates the anti-inflammatory effect of IL-4, which may not fully replicate the traditional anti-inflammatory polarization state.
Confocal microscopy revealed that untreated microglia exhibited an elongated morphology indicative of a resting state (Figure 2D).After stimulation with LPS, microglia cells displayed an amoeboid-like morphology, characteristic of activated microglia (Figure 2E).Stimulation with IL-4+IL-10+TGFβ, also resulted in the phenotypic change of cellular morphology to an amoeboid-like shape (Figure 2F).These distinct morphological changes indicated that resting microglia were activated in response to stimulation.

sEV characterization
We subsequently characterized the physical and biological properties of purified sEVs derived from the HMC3 cells.Using nanoflow cytometry, 11.1%, 7.94%, and 11.1% of HMC3 sEVs respectively expressed canonical EV biomarkers CD9, CD63, and CD81 (Figure 3A).Isolated sEVs also displayed typical size and morphology as seen by Figure 3B.
The images depict the presence of a lipid bilayer structure, indicative of sEVs, with sizes ranging between 30 and 150 nm.The size distribution of sEVs derived from resting and activated microglia were analyzed using the NanoSight NS300 (Figure 3C-E).We observed a consistent particle diameter between different states of microglia.The concentration of secreted sEVs showed a trend to being elevated from stimulated HMC3 cells, however this was not significant (Supplementary Figure 2).

Proteomic characterization
Given the phenotypic differences induced by pro-and-anti- the transforming growth factor beta receptor signaling pathway [29].Furthermore, proteins that regulate extracellular matrix such as Extracellular matrix protein 1 (ECM1), lumican (LUM), and SPARC are also increased in LPS sEVs compared IL-4/10/TGFβ stimulated sEVs.Interestingly, ECM1 has been implicated in regulating activated macrophage polarization through the granulocyte-macrophage colony-stimulating factor/STAT5 signaling pathway and inhibits ARG1 expression [30], and LUM and SPARC have been previously implicated in modulating AD-related neuroinflammation [31,32].
Given that distinct pro-and anti-inflammatory phenotypes of microglia might be distinguished by directly assessing sEV protein content, we confirmed pro-inflammatory MICB expression in stimulated HMC3 cells and their sEVs.Western blot revealed that MICB is elevated in both LPS stimulated HMC3 cells and their respective sEVs compared to resting and IL-4/10/TGFβ-stimulation (Figure 4D), consistent results with mass spectrometry.

GO enrichment analysis
To further evaluate if LPS-and-IL-4/10/TGFβ-sEVs reflect pro-andanti-inflammatory phenotypes from the microglia they were derived from, we sought to understand the function and pathways of differentially abundant proteins by GO enrichment analysis.Given the distinct upregulation of proteins in LPS-sEVs, we conducted GO enrichment analysis on significantly upregulated proteins from LPS-sEVs.For terms were significantly enriched (FDR < 0.05); and for GO molecular function annotations, 13 GO terms were significantly enriched (FDR < 0.05) (Figure 5).
Furthermore, the term cell surface (GO:0009986) was significantly enriched.We next wanted to further explore the relative expression of the proteins in resting and LPS-sEVs that related to the cell surface as this may provide insight into defining the microglia phenotype sEVs are derived from (Figure 5B).Interestingly, among the 19 proteins there were notable proteins involved in inflammation such as complement component C3, and major histocompatibility complex (MHC) Class I molecules [33] were significantly enriched on the surface of LPS-sEVs.Of the 8 significant GO biological process terms, fibrinolysis (GO:0042730) was the most significantly enriched term (Figure 5C) with an enrichment for plasminogen activator inhibitor-1 (PAI-1) and plasminogen (PLMN) (Figure 5D), proteins commonly upregulated in AD [34].Of the 13 significant GO molecular function terms, there is a distinct enrichment for GO terms related to protein binding (Figure 5E), including receptor binding (GO:0005102), which includes a host of proteins involved in inflammatory processes (Figure 5F).
Given the distinct downregulation of proteins in IL-4/10/TGFβ-sEVs, we instead conducted GO enrichment analysis on significantly downregulated proteins from IL-4/10/TGFβ-sEVs.For GO cellular component annotation, 21 GO terms were significantly enriched (FDR < 0.05); for GO biological process annotations, 27 GO terms were significantly enriched (FDR < 0.05); and for GO molecular function annotations, 13 GO terms were significantly enriched (FDR < 0.05) (Figure 6).Of the 21 significant GO cellular component terms, there were several similarities to GO terms enriched in LPS-sEVs (Figure 6A), however, these proteins were downregulated in IL-4/10/TGFβ-sEVs (Figure 6B), potentially reflective of anti-inflammation.To support this, there was a consistent enrichment for biological process annotations related to antigen presentation, signaling pathways, and signal transduction which modulate inflammatory processes (Figure 6C).One example is the MAPK cascade (GO:0000165) pathway being significantly downregulated in IL-4/10/TGFβ-sEVs (Figure 6D).Furthermore, of the 13 molecular function terms, there was an enrichment for terms associated with the extracellular environment (Figure 6E), including the downregulation of proteins associated with the promoting inflammation such as tenascin C in extracellular matrix (GO:0005201) (Figure 6F).Overall, these results indicated that upregulated and downregulated proteins in LPS-and IL-4/10/TGFβ-sEVs influenced similar biological properties related to pro-and-anti-inflammatory phenotypes.

DISCUSSION
In this study, we have evaluated the physical and biological properties of sEVs that are derived from LPS-stimulated and IL-4/10/TGFβstimulated HMC3 microglia.Microglia play a crucial role in maintaining brain homeostasis and are involved in various functions essential for the CNS.They are associated with both physiological and pathological processes in the brain [35].The state of microglia, whether resting or activated, depends on the change of brain homeostasis, which has been recognized as a significant factor in the development of brain disorders [1].The activation of microglia leads to secretion of pro-or anti-inflammatory cytokines and chemokines into the microenvironment, which is implicated in various CNS pathologies.The sEVs derived from microglia can also contain these inflammatory signals to reflect the state of the parental cells and can provide insights into specific functions and signaling pathways [36].However, the composition and role of microglia-derived sEV protein content in relation to various microglia phenotypes have not been well explored.
Selective packing of molecular content, including proteins into sEVs has been previously described [37].This implies that cells are capable of enriching particular proteins in sEVs, which may be fundamental for intercellular communication.In support of this, we demonstrated that LPS-and-IL-4/10/TGFβ-sEVs have distinct protein profiles that influence specific biological pathways involved in inflammation.GO enrichment analysis of LPS-sEVs revealed an enrichment for the biological process GO term related to fibrinolysis.Specifically, five proteins associated with fibrinolysis, prothrombin (THRB), fibrinogen gamma chain (FIBG), PLMN, vitamin k-dependent proteins (PROS), and PAI.Abnormal fibrinolysis has been implicated in disease initiation and progression [38].Increased thrombin activity can lead to blood-brain barrier disruption, allowing the entry of blood components, including fibrinogen, where amyloid-beta (Aβ) is abundant.Therefore, this Aβ interacts with fibrinogen, which favors the formation of blood clots resistant to fibrinolysis, which can contribute to the development and progression of AD pathology [39,40].Upregulation of PAI-1 has also been shown in PD and AD.PAI regulates the activation of plasmin to cleave alpha-synuclein (α-syn), causing abnormal accumulation in PD patients and promotes the aggregation of α-syn.This process could further contribute to the activation of microglia and astrocytes, which exacerbates neuroinflammation and leads to disease progression [34].
It is important to note, that TGF-β has been previously shown to be a key signaling molecule involved in promoting fibrosis by stimulating the production of extracellular matrix proteins [41].However, we did not observe this in IL-4/10/TGFβ-sEVs.It is important to acknowledge certain limitations associated with using immortalized cell lines.
Immortalized microglial cell lines may respond differently to certain stimuli or lead to the alteration of certain functions or properties compared to primary microglia [42].Therefore, further validation in primary microglia or in vivo models is still necessary.
Although we did not observe an enrichment of inflammatory cytokines in sEVs in this study, several proteins that are associated with an inflammatory response including complement C1q binding protein (C1QBP), CO3, CD14, dickkopf-related protein 3 (DKK3), and PAI-1 are upregulated in LPS-sEVs or downregulated in IL-4/10/TGFβ-sEVs.C1QBP has been reported to influence the production of pro-inflammatory cytokines and is associated with mitochondria to regulate the local energy supply in neuronal cells [43].Furthermore, CO3 has been shown to be elevated in the brain of AD patients and correlate with expression of tau [44].CD14 is a co-receptor for transmembrane toll-like receptor 4 (TLR4) and endosomal TLR7/9, and mediates the innate immune response [45].Moreover, MICB can modulate immune surveillance by binding to their receptor on natural killer cells and T cells, and their genetic polymorphisms have been associated with autoimmune diseases, infections, and cancer [46,47].DKK3 can influence immune response in different inflammatory diseases c by binding to LRP5/6 co-receptors [48,49].Altogether, these changes in abundance of these proteins suggest that microglia sEVs might reflect local inflammatory states within the brain microenvironment.
GO enrichment analysis revealed the downregulation of numerous pathways involved with antigen presentation and signaling cascades involved in neuroinflammation.Specifically, the MAPK pathway is an important regulator of proinflammatory cytokine production in microglia [50].In combination with reduced antigen-presentation, IL-4/10/TGFβ-sEVs can reveal the phenotypes of their cell-of-origin which reflects an anti-inflammatory microenvironment in the CNS.
Overall, these results indicate that the activation of microglia through LPS and IL-4/10/TGFβ can lead to the secretion of sEVs reflective of the pro-and anti-inflammatory phenotype of the cells they were derived from.Although beyond the scope of this investigation, clinical analysis of proteins enriched in LPS-and IL-4/10/TGFβ-sEVs could provide important clinical information when using advanced approaches to detect trace levels of sEVs [51].This can provide critical insight in biomarker discovery to monitor pathogenesis and progression of CNS disorders.
VILO cDNA synthesis kit (Thermo Fisher Scientific) according to the manufacturer's instruction and stored at −20 • C until ready for use.qPCR was done using SYTO-9 master mix.The RT-qPCR runs were comprised of 10 min of predenaturation at 95 • C, followed by 40 cycles of two-step PCR including denaturing phase (95 • C for 30 s), and annealing and extension phase (60 • C for 2 min).The results were analyzed by the 2−ΔΔCT method.2.9 Western blot LPS-stimulated and IL-4/10/TGFβ-stimulated HMC3 cells and their sEVs were reduced and denatured by Laemmli and 2-mercaptoethanol (Bio-Rad) for 5 min at 95 • C. Protein was resolved by SDSpolyacrylamide gel electrophoresis (SDS-PAGE), and then transferred to polyvinylidene fluoride membranes (Bio-Rad).Membranes were blocked in 10% skim milk in PBS-T (0.1% Tween-20) for 30 min at room temperature, and then incubated with primary antibody for 1 h at room temperature.After incubation, membranes were washed five times with PBS-T and incubated HRP-conjugated secondary antibodies for 1 h at room temperature.Membranes were then washed five times with PBS-T and visualized using the enhanced chemiluminescence reagent (Clarity Western ECL Substrate, Bio-Rad) and Biorad ChemiDoc Imaging System.
inflammatory signals, we investigated the alterations in the proteome of sEVs derived from activated microglia.Label-free quantification by spectral intensity identified 164 proteins in LPS-sEVs, and 225 proteins in IL-4/10/TGFβ-sEVs differentially expressed at a FC > 2 and an FDR of 0.05 compared to resting sEVs (Figure4A,B; Supplementary Data 1).In response to LPS stimulation, we observed an upregulation of inflammatory proteins such as Complement C3 (CO3), Plasminogen activator inhibitor-1 (PAI-1), CD14, and MHC class I polypeptide-related sequence B (MICB).We also observed an overlap of 49 proteins that were significantly increased in LPS sEVs and significantly reduced in IL-4/10/TGFβ stimulated sEVs (Figure4A-C).These proteins were surface proteins such as Calsyntenin-1 (CSTN1), which is known to play an important role in AD by regulating the transport of amyloid precursor protein (APP)[27], and vasorin (VASN) that has been previously shown to promote migration of endothelial cells in a hepatocellular carcinoma context[28], and is involved in negatively regulating F I G U R E 2 HMC3 microglia markers identification and LPS and IL-4/10/TGFβ stimulation.(A-C) Flow cytometry analysis of microglia core marker expression in HMC3.(D-F) Representative confocal images of unstimulated and stimulated microglia labelled with Alexa Fluor 488-conjugated phalloidin (green) to reveal the cell shape and Hoechst 33342 (blue) to reveal nuclei.Scale bars, 100 µm.Different morphologies are highlighted in circles; magnified images are of the circled areas.(G-I) Gene expression profile of TNF-α, iNOS and ARG1 was evaluated by RT-qPCR.The data were normalized to the housekeeping gene GAPDH.Bars represent the mean ± SD, n = 3. *p < 0.05, **p < 0.01, ***p < 0.001.
GO cellular component annotation, 25 GO terms were significantly enriched (FDR < 0.05); for GO biological process annotations, 7 GO F I G U R E 3 Characterization of sEVs derived from HMC3 cells.(A) Nanoflow cytometry of the expression of the tetraspanins CD9, CD63, and CD81.(B) TEM image visualizes the purification of HMC3 sEVs.Scale bar, 100 nm.(C-E) Size distribution analysis of purified sEVs from resting, LPS-stimulated and IL-4/10/TGFβ-stimulated HMC3 cells.

F I G U R E 5
GO enrichment analysis of upregulated LPS-sEV proteins.(A) Top 20 GO analysis enrichment terms on cellular component.(B) Heatmap of specific proteins related to the cell surface cellular component GO term.(C) Top 20 GO analysis enrichment terms on biological process.(D) Heatmap of specific proteins related to the fibrinolysis biological process GO Term.(E) Top 20 GO analysis enrichment terms on molecular function.(F) Heatmap of specific proteins related to the receptor binding molecular function GO term.F I G U R E 6 GO enrichment analysis of upregulated IL-4/10/TGFβ-sEV proteins.(A) Top 20 GO analysis enrichment terms on cellular component.(B) Heatmap of specific proteins related to the cell surface cellular component GO term.(C) Top 20 GO analysis enrichment terms on biological process.(D) Heatmap of specific proteins related to the fibrinolysis biological process GO Term.(E) Top 20 GO analysis enrichment terms on molecular function.(F) Heatmap of specific proteins related to the receptor binding molecular function GO term.
Data analysis was performed with Spectronaut version 18 (Biognosys) using direct DIA and default settings.Spectra were searched against the Homo sapiens (Human) proteome with 1% false discovery rate (FDR) cut-offs at the peptide spectral match, peptide, and protein group levels.Quantitation was performed at the MS2 level with Q-value filtering < 0.05 and p-value filtering < 0.05.
• C, then alkylated by 500 mM iodoacetamide for 30 min in the dark at room temperature.The pH was adjusted to ≈8 by 100 mM ammonium bicarbonate and further digested by incubation with 0.5 µg of trypsin at 37 • C overnight for liquid chromatography-mass spectrometry (LC-MS/MS) analysis.Digested peptides were analyzed by LC-MS, an Orbitrap Exploris 480 mass spectrometer (Thermo Fisher Scientific) equipped with a FAIMS Pro interface (Thermo Fisher Scientific).Initially, 2 µL of sample was loaded onto Thermo Fisher Acclaim PepMap C18 trap reversed-phase column (300 µm × 5 mm nano viper, 5 µm particle size, 100 Å pore diameter) at a rate of 15 µL/min using 2% Acetonitrile (ACN) in 0.1% trifluoroacetic acid (TFA, aq) as solvent.The trap column was switched in-line with the resolving column, and peptides were separated using mobile phase solutions: solvent A (H2O) and solvent B (80% ACN (aq)), formed at a resolution of 120,000 with a scan range of 340-1110 m/z.Three time spans were employed with different mass windows: m/z 350-470 with windows of 10 Da, m/z 465-645 with windows of 5 Da, and m/z 640-1100 with windows of 46 Da.All windows were set to 15,000 resolution and a collision energy of normalized 30.AGC and IT targets were both set at standard.