Integrated proteomic, phosphoproteomic, and N-glycoproteomic analyses of small extracellular vesicles from C2C12 myoblasts identify specific PTM patterns in ligand-receptor interactions
对来自 C2C12 成肌细胞的小细胞外囊泡进行综合蛋白质组学、磷酸化蛋白质组学和 N-糖蛋白组学分析可识别配体-受体相互作用中的特定 PTM 模式

Isolation of small extracellular vesicles (sEVs) from C2C12 myoblasts
从 C2C12 成肌细胞中分离小细胞外囊泡 （sEV）

The isolation of sEVs from C2C12 myoblasts was performed with a standard ultracentrifugation-based method described previously [30] with minor modifications. Briefly, cell-conditioned medium was collected from approximately 90% confluent C2C12 myoblasts grown for 48 h in 100 mm cell culture dishes with DMEM medium containing FBS depleted of bovine serum extracellular vesicles by ultracentrifugation at 120,000 g for 24 h. The collected cell culture medium was first subjected to centrifugation at 400 g for 10 min to pellet and remove cells. Next, the supernatant was centrifuged at 2,000 g for 20 min to remove cell debris and apoptotic bodies. Then, the supernatant was centrifuged at 15,000 g for 40 min to remove large EVs. To remove any remaining of large EVs, the supernatant from the first 15,000 g step was passed through a 0.22 mm pore PES filter (Corning). This supernatant (pre-cleared medium) was subjected to ultracentrifugation at 120,000 g for 4 h (Rotor: 45Ti, Beckman Coulter, Fullerton, CA) to sediment small EVs (sEVs). The crude sEV pellet was re-suspended in a large volume of ice-cold PBS followed by ultracentrifugation at 120,000 g for 4 h. The pellet (sEV sample) was re-suspended in 100 μl PBS supplemented with EDTA-free complete protease inhibitor cocktail and phosphatase inhibitor cocktail. All centrifugation steps were performed at 4℃. The obtained sEV samples were stored at -80℃ for less than half a year before subsequent sample preparation and PTM enrichments.
从C2C12成肌细胞中分离sEVs是用前面描述的基于超速离心的标准方法进行的[30]，并稍作修改。简而言之，从在100 mm细胞培养皿中生长48小时的约90%汇合C2C12成肌细胞收集细胞条件培养基，DMEM培养基含有FBS的DMEM培养基通过超速离心120,000g去除牛血清细胞外囊泡24小时。首先将收集的细胞培养基以 400 g 离心 10 分钟以沉淀并除去细胞。接下来，将上清液以 2,000 g 离心 20 分钟以除去细胞碎片和凋亡小体。然后，将上清液以 15,000 g 离心 40 分钟以除去大 EV。为了除去任何残留的大型EV，将第一个15,000 g步骤中的上清液通过0.22 mm孔径PES过滤器（Corning）。将该上清液（预清除培养基）以 120,000 g 超速离心 4 小时（转子：45Ti，Beckman Coulter，Fullerton，CA）以沉淀小型 EV （sEV）。将粗的sEV颗粒重新悬浮在大量冰冷的PBS中，然后以120,000g超速离心4小时。将沉淀（sEV样品）重新悬浮在补充有不含EDTA的完全蛋白酶抑制剂混合物和磷酸酶抑制剂混合物的100μlPBS中。所有离心步骤均在4°C下进行。将获得的sEV样品在-80°C下储存不到半年，然后进行随后的样品制备和PTM富集。

Cell culture medium from 30*100 mm cell culture dishes (~ 300 ml) was collected for one purification of sEVs. Eight purifications were performed to obtain enough sEVs proteins for further characterization of sEVs, PTM (phosphorylation and N-glycosylation) enrichments, and LC–MS/MS analysis.
从30*100 mm细胞培养皿（~300 ml）中收集细胞培养基，用于一次纯化sEV。进行了八次纯化以获得足够的 sEVs 蛋白，用于进一步表征 sEV、PTM（磷酸化和 N-糖基化）富集和 LC-MS/MS 分析。

Transmission electron microscope (TEM) analysis
透射电子显微镜（TEM）分析

For negative staining TEM analysis, 5 µL sEV sample in PBS was loaded on a hydrophilized carbon-coated 230 mesh copper grid (Beijing Zhongjingkeyi Technology Co., China) and allowed to settle for 1 min. The sample was blotted and negatively stained with 3 continuous drops of 2% uranyl acetate, blotting between each drop. After staining the sample with the last drop for 1 min, the grid was blotted and air-dried. Grids were imaged with a Tecnai Spirit (FEI Co., US) TEM operating at 100 kV.
对于阴性染色TEM分析，将PBS中的5μLsEV样品加载到亲水性碳涂层230目铜网格（中国北京中景科谊科技有限公司）上，并静置1分钟。将样品吸干并用 3 滴连续的 2% 乙酸铀酰染色，每滴之间印迹。用最后一滴对样品染色1分钟后，将网格吸干并风干。使用工作电压为 100 kV 的 Tecnai Spirit（FEI Co.，US）TEM 对电网进行成像。

Nanoparticle tracking analysis (NTA)
纳米颗粒跟踪分析（NTA）

The concentration and size distribution of sEV samples was determined by ZetaView (Particle Matrix, German) equipped with a 488 nm laser. Samples were 1:10, 000 diluted in PBS to obtain around 300 particles/view. Three videos of 20 s duration were recorded for each independent replicate and used to compute the particle size and mean concentration. Data were analyzed with ZetaView 8.04.10 software.
sEV样品的浓度和大小分布由配备488 nm激光器的ZetaView（Particle Matrix，德语）测定。样品以 1：10， 000 的比例在 PBS 中稀释，以获得约 300 个颗粒/视图。为每个独立的重复记录三个持续时间为20秒的视频，并用于计算粒径和平均浓度。使用ZetaView 8.04.10软件分析数据。

Protein extraction and western blotting
蛋白质提取和蛋白质印迹

Total cell lysate (TCL) was extracted from C2C12 myoblasts as described previously [31]. Briefly, C2C12 myoblasts were collected in the lysis buffer containing 8 M urea and 100 mM Tris–HCl (pH 8.5) supplemented with EDTA-free complete protease inhibitor cocktail (Roche, Basel, Switzerland). Then, the cells were lysed with Precellys Evolution homogenizer (Bertin Technologies, Paris, France). After centrifugation at 20,000 g for 20 min at 4℃, the supernatant was collected as TCL. sEV samples were solubilized in the same lysis buffer. The protein concentration of TCL and sEVs was determined using a BCA protein assay kit (Thermo Fisher Scientific, Waltham, MA).
如前所述，从C2C12成肌细胞中提取总细胞裂解物（TCL）[31]。简而言之，将 C2C12 成肌细胞收集在含有 8 M 尿素和 100 mM Tris-HCl （pH 8.5） 的裂解缓冲液中，并补充有不含 EDTA 的完全蛋白酶抑制剂混合物（Roche，Basel，Switzerland）。然后，用Precellys Evolution匀浆器（Bertin Technologies，Paris，France）裂解细胞。在4°C下以20,000g离心20分钟后，收集上清液为TCL。将sEV样品溶解在相同的裂解缓冲液中。使用 BCA 蛋白测定试剂盒（Thermo Fisher Scientific，Waltham，MA）测定 TCL 和 sEV 的蛋白质浓度。

For western blotting, equal amounts of proteins from sEV and TCL were subjected to SDS-PAGE. After separation, proteins were transferred to Immobilon PVDF Membrane at 200 mA for 1–2 h. PVDF Membranes were blocked with 5% non-fat dry milk in TBST for 2 h at RT. After blocking, PVDF membranes were washed with TBST and incubated with primary antibodies diluted in 5% milk overnight at 4˚C. Primary antibodies used for immunoblotting were ALIX (Cat#ab186429, Abcam; 1:1,000), TSG101 (Cat# ab125011, Abcam; 1:1,000), CD9 (Cat#ab92726, Abcam; 1:1,000), HSP90 (Cat#ab203126, Abcam; 1:10,000), and HRP-conjugated GAPDH (AC035, ABclonal; 1:1,000). PVDF Membranes were then washed with TBST and incubated with secondary antibodies diluted in TBST. After washing, the secondary antibodies were detected using SuperSignal Western Blot Substrate (Thermo Fisher Scientific, Waltham, MA, USA). Four replicates of sEV samples were analyzed with western blotting.
对于蛋白质印迹，对来自 sEV 和 TCL 的等量蛋白质进行 SDS-PAGE。分离后，将蛋白质以200mA转移到Immobilon PVDF膜上1-2小时，在室温下用5%脱脂奶粉在TBST中封闭PVDF膜2小时。封闭后，用TBST洗涤PVDF膜，并与在4°C下用5%牛奶稀释的一抗孵育过夜。用于免疫印迹的一抗是 ALIX （Cat#ab186429， Abcam; 1：1,000）、TSG101 （Cat# ab125011， Abcam; 1：1,000）、CD9 （Cat#ab92726， Abcam; 1：1,000）、HSP90 （Cat#ab203126， Abcam; 1：10,000） 和 HRP 偶联的 GAPDH （AC035， ABclonal; 1：1,000）。然后用TBST洗涤PVDF膜，并与在TBST中稀释的二抗一起孵育。洗涤后，使用 SuperSignal Western Blot 底物（Thermo Fisher Scientific，Waltham，MA，USA）检测二抗。用蛋白质印迹法分析了 4 个重复的 sEV 样品。

In-solution digestion of proteins
蛋白质的溶液内消化

Three biological replicates of sEVs purified from C2C12 myoblasts were combined from eight sEV purifications and used for in-solution digestion and subsequent PTMs (phosphorylation and N-glycosylation) enrichment.
从 C2C12 成肌细胞纯化的 3 个 sEV 生物学重复片段从 8 个 sEV 纯化中合并，用于溶液内消化和随后的 PTM（磷酸化和 N-糖基化）富集。

sEV proteins were in-solution digested into peptides as described previously [31]. In brief, proteins were reduced with 10 mM DTT at 30℃ for 1 h. The resulting free thiols were alkylated with 40 mM IAM for 45 min at room temperature in the dark. The same amount of DTT was subsequently added to remove excess IAM at 30℃ for 30 min. Then, proteins were digested with Lys-C (Wako Pure Chemical Industries, Osaka, Japan) at an enzyme/protein ratio of 1:100 (w/w) at 37℃ for 3 h. After dilution with 50 mM Tris–HCl (pH 8.0), samples were digested with sequencing grade modified trypsin (Promega, Madison, WI) at an enzyme/protein ratio of 1:50 (w/w) at 37℃ overnight. The enzymatic digestion was stopped with formic acid (FA), and the supernatant was collected after centrifugation at 20,000 g for 20 min. After that, peptides were desalted on HLB cartridges (Waters, Milford, MA, USA) and dried in SpeedVac (LABCONCO, Kansas City, MO, USA). After dissolving the desalted peptides with 0.1% FA, peptide concentration was determined using a BCA peptide assay kit (Thermo Fisher Scientific, Waltham, MA, USA). Then, peptides were split into different amounts according to different PTM enrichment experiments mentioned below and dried in SpeedVac.
如前所述，sEV蛋白在溶液中消化成肽[31]。简而言之，在30°C下用10mM DTT还原蛋白质1小时。将所得游离硫醇在室温下在黑暗中用40 mM IAM烷基化45分钟。随后加入相同量的DTT，以在30°C下去除多余的IAM，持续30分钟。然后，用 Lys-C（Wako Pure Chemical Industries，大阪，日本）在 37°C 下以 1：100 （w/w） 的酶/蛋白质比例消化蛋白质 3 小时。用 50 mM Tris–HCl （pH 8.0） 稀释后，在 37°C 下以 1：50 （w/w） 的酶/蛋白比用测序级修饰胰蛋白酶（Promega，Madison，WI）酶/蛋白比酶解样品过夜。用甲酸（FA）停止酶解，以20,000g离心20分钟后收集上清液。之后，肽在HLB卡式瓶（Waters，Milford，MA，USA）上脱盐，并在SpeedVac（LABCONCO，堪萨斯城，密苏里州，美国）中干燥。用 0.1% FA 溶解脱盐肽后，使用 BCA 肽测定试剂盒（Thermo Fisher Scientific，Waltham，MA，USA）测定肽浓度。然后，根据下面提到的不同PTM富集实验将肽分成不同的量，并在SpeedVac中干燥。

Phosphopeptide enrichment
磷酸肽富集

The enrichment of phosphopeptides using TiO₂ with lactic acid was performed as described previously [31]. Briefly, 200 μg dried peptides were re-solubilized in 100 μl sample loading buffer containing 70% ACN, 5% TFA, and 20% lactic acid (Sigma) to a final concentration of 2 μg/μl. TiO₂ beads (5 μm Titansphere, GL Sciences, Tokyo, Japan) were preconditioned with sample loading buffer for 5 min, and the process was repeated three times. Subsequently, the peptides were incubated with preconditioned TiO₂ beads at a peptides/TiO₂ ratio of 1:6 (w/w) for 15 min at room temperature. After pelleted TiO₂ beads, the supernatant was transferred to another tube and incubated with half of the amount of TiO₂ beads used in the first incubation. A third incubation was performed with 1/4 of the amount of TiO₂ beads used in the first incubation. TiO₂ beads from the three incubations were pooled with loading buffer and transferred to preconditioned C8 StageTips. The TiO₂ beads were sequentially washed with sample loading buffer, washing buffer 1 (30% ACN, 0.5% TFA), and washing buffer 2 (80% ACN, 0.4% TFA). Phosphopeptides on TiO₂ beads were eluted with elution buffer 1 (4% NH₃.H₂O) and elution buffer 2 (4% NH₃.H₂O and 50% ACN) sequentially. The eluted phosphopeptides were immediately acidified with 10% FA and dried in SpeedVac. Before LC–MS/MS analysis, phosphopeptides were desalted with homemade OLIGO^TM R3 StageTips.
如前所述，使用TiO ₂ 和乳酸富集磷酸肽[31]。简而言之，将 200 μg 干肽重新溶解在含有 70% 乙腈、5% TFA 和 20% 乳酸 （Sigma） 的 100 μl 样品上样缓冲液中，最终浓度为 2 μg/μl。TiO ₂ 微珠（5μm Titansphere，GL Sciences，Tokyo，Japan）用样品上样缓冲液预处理5分钟，并重复该过程三次。随后，将肽与预处理的TiO ₂ 微珠以1：6（w/w）的肽/TiO ₂ 比在室温下孵育15分钟。沉淀TiO ₂ 微珠后，将上清液转移到另一个试管中，并与第一次孵育中使用的TiO ₂ 微珠量的一半一起孵育。使用第一次孵育中使用的 1/4 的 TiO ₂ 微珠进行第三次孵育。将来自三个孵育的 TiO ₂ 微珠与上样缓冲液合并并转移到预处理的 C8 StageTips 中。用上样缓冲液、洗涤缓冲液1（30%乙腈，0.5%TFA）和洗涤缓冲液2（80%乙腈，0.4%TFA）依次洗涤TiO ₂ 微珠。TiO ₂ 微珠上的磷酸肽用洗脱缓冲液1（4%NH ₃ .H ₂ O）和洗脱缓冲液2（4%NH ₃ . ₂ H O 和 50% 乙腈）依次。洗脱的磷酸肽立即用 10% FA 酸化，并在 SpeedVac 中干燥。在LC-MS/MS分析之前，使用自制的OLIGO ^TM R3 StageTips对磷酸肽进行脱盐。

Three biological replicates of sEVs samples with two technical replicates of phosphopeptide enrichment and six LC–MS/MS analyses were performed to obtain the phosphoproteome of sEVs.
对 sEV 样品进行 3 次生物学重复，其中 2 次磷酸肽富集技术重复和 6 次 LC–MS/MS 分析，以获得 sEV 的磷酸化蛋白质组。

N-glycopeptide enrichment
N-糖肽富集

100 μg dried peptides were re-solubilized in 50 μl loading buffer (80% ACN, 1% TFA) before enrichment of glycopeptides with home-made ZIC-HILIC tips. ZIC-HILIC beads (Agela Technologies, China) were loaded onto 200 μl pipette tips with C8 3M membrane to make ZIC-HILIC tips. The ZIC-HILIC tips were sequentially conditioned with ACN, 0.1% TFA, and 80% ACN/0.1% TFA, and peptides were loaded onto ZIC-HILIC tips. After washed ZIC-HILIC tips with 1% 80% ACN/0.1%TFA, the enriched N-glycopeptides were eluted with 0.1% TFA and dried for LC–MS/MS analysis.
将 100 μg 干肽重新溶解在 50 μl 上样缓冲液（80% 乙腈、1% TFA）中，然后用自制的 ZIC-HILIC 吸头富集糖肽。将ZIC-HILIC微球（Agela Technologies，中国）加载到带有C8 3M膜的200μl移液器吸头上，以制备ZIC-HILIC吸头。用 ACN、0.1% TFA 和 80% ACN/0.1% TFA 依次对 ZIC-HILIC 吸头进行调理，并将肽加载到 ZIC-HILIC 吸头上。用 1% 80% 乙腈/0.1% TFA 洗涤 ZIC-HILIC 吸头后，用 0.1% TFA 洗脱富集的 N-糖肽并干燥用于 LC–MS/MS 分析。

Three biological replicates of sEVs samples with two technical replicates of N-glycopeptide enrichment and six LC–MS/MS analyses were performed to obtain the N-glycoproteome of sEVs.
对 sEV 样品进行 3 次生物学重复，其中 2 次 N-糖肽富集技术重复和 6 次 LC-MS/MS 分析，以获得 sEV 的 N-糖蛋白组。

LC–MS/MS analysis LC-MS/MS分析

Peptides and phosphopeptides of sEVs were analyzed on an Easy-nLC 1200 HPLC system (Thermo Fisher Scientific) coupled to an Orbitrap Exploris 480 (Thermo Fisher Scientific) with a high-field asymmetric waveform ion mobility spectrometry (FAIMS) device (Thermo Fisher Scientific). All samples were reconstituted in 0.1% FA and separated on a fused silica trap column (100 μm ID * 2 cm) in-house packed with reversed-phase silica (Reprosil-Pur C18 AQ, 5 μm, Dr. Maisch GmbH, Baden-Wuerttemberg, Germany) coupled to an analytical column (75 μm ID * 20 cm) packed with reversed-phase silica (Reprosil-Pur C18 AQ, 3 μm, Dr. Maisch GmbH). The peptides and phosphopeptides were analyzed with 103 min gradient (buffer A: 0.1% FA in H₂O, buffer B: 80% ACN, 0.1% FA in H₂O) at a flow rate of 300 nL/min (5–9% B, 4 min; 9–20% B, 32 min; 20–30% B, 31 min; 30–40% B, 23 min; 40–99% B, 4 min; 99% B, 9 min). MS data were acquired using an Orbitrap mass analyzer in data-dependent acquisition mode. The cycle time was set as 2 s. The spray voltage of the nanoelectrospray ion source was 2.0 kV, and the heated capillary temperature was 320℃. Full scan MS data were collected at a high resolution of 60,000 (m/z 200) from 350 to 1500 m/z. The automatic gain control target was 4*10⁵, dynamic exclusion was 30 s, and the intensity threshold was 5.0*10⁴. The precursor ions were selected from each MS full scan with an isolation width of 1.6 m/z for fragmentation with a normalized collision energy of 30%. For phosphopeptide analysis, MS/MS data were acquired at a resolution of 30,000 (m/z 200). The automatic gain control target was 1*10⁵, the maximum injection time was 54 ms, dynamic exclusion was 30 s, and the intensity threshold was 5.0*10⁴. For peptide analysis, MS/MS data were acquired at a resolution of 15,000 (m/z 200). The automatic gain control target was 5*10⁴; the maximum injection time was 22 ms. The compensation voltage of FAIMS was set as -45 V and -65 V.
在 Easy-nLC 1200 HPLC 系统 （Thermo Fisher Scientific） 和 Orbitrap Exploris 480 （Thermo Fisher Scientific） 上，使用高场非对称波形离子淌度光谱 （FAIMS） 设备 （Thermo Fisher Scientific） 分析 sEV 的肽和磷酸肽。将所有样品在0.1%FA中复溶，并在内部填充反相二氧化硅（Reprosil-Pur C18 AQ，5μm，Dr. Maisch GmbH，Baden-Wuerttemberg，Germany）的熔融石英捕集柱（100μmID * 20 cm）上分离，该柱装有反相二氧化硅（Reprosil-Pur C18 AQ，3μm，Dr. Maisch GmbH）。以300 nL/min（5-9%B，4分钟;9-20%B，32分钟;30-30%B，31分钟;30-40%B，23分钟;40-99%B，30-40%B，23分钟;40-99%B，30-40%B，23分钟;40-99%B，103 min _{2 2} 梯度分析肽和磷酸肽， 4 分钟;99% B，9 分钟）。MS数据是在数据依赖性采集模式下使用Orbitrap质量分析器采集的。循环时间设置为 2 秒。纳米电喷雾离子源的喷雾电压为2.0 kV，加热的毛细管温度为320°C。在350至1500 m/z范围内以60,000（m/z 200）的高分辨率收集全扫描MS数据。自动增益控制目标为4*10 ⁵ ，动态排除为30 s，强度阈值为5.0*10 ⁴ 。从每次MS全扫描中选择母离子，隔离宽度为1.6 m/z，以30%的归一化碰撞能量进行碎裂。对于磷酸肽分析，以 30,000 （m/z 200） 的分辨率采集 MS/MS 数据。自动增益控制目标为1*10 ⁵ ，最大注入时间为54 ms，动态排除为30 s，强度阈值为5.0*10 ⁴ 。 对于肽分析，以 15,000 （m/z 200） 的分辨率采集 MS/MS 数据。自动增益控制目标为5*10 ⁴ ;最长进样时间为22 ms。FAIMS的补偿电压设置为-45 V和-65 V。

The enriched N-glycopeptides of sEVs were analyzed on an Easy-nLC 1200 HPLC system (Thermo Fisher Scientific) coupled to an Orbitrap Eclipse Tribrid mass spectrometer (Thermo Fisher Scientific). N-glycopeptides were separated with trap column and analytical column mentioned above. The N-glycopeptides were analyzed with 103 min gradient at a flow rate of 300 nL/min (0–11% B, 4 min; 11–22% B, 32 min; 22–32% B, 31 min; 32–42% B, 23 min; 42–95% B, 3 min; 95% B, 10 min). MS data were acquired in data-dependent acquisition mode. The cycle time was set as 3 s. The spray voltage of the nano-electrospray ion source was 2.0 kV and the heated capillary temperature was 320 °C. An MS1 scan was acquired from 350 to 2000 m/z (60,000 resolution, 4e⁵ AGC) followed by stepped energy HCD MS/MS acquisition of the precursors and detection in the Orbitrap (30, 000 resolution, 5e⁴ AGC, maximum injection time = 100 ms, stepped collision energy = 25%, 35%, 45%).
在Easy-nLC 1200 HPLC系统（Thermo Fisher Scientific）和Orbitrap Eclipse Tribrid质谱仪（Thermo Fisher Scientific）上分析sEV的富集N-糖肽。N-糖肽用上述陷阱柱和分析柱分离。以 300 nL/min 的流速（0–11% B，4 分钟;11–22% B，32 分钟;22–32% B，31 分钟;32–42% B，23 分钟;42–95% B，3 分钟;95% B，10 分钟）以 103 分钟梯度分析 N-糖肽。MS数据以数据依赖性采集模式采集。循环时间设置为 3 秒。纳米电喷雾离子源的喷雾电压为2.0 kV，加热的毛细管温度为320 °C。 从 350 到 2000 m/z（60,000 分辨率，4e ⁵ AGC）采集 MS1 扫描，然后采集前驱体的步进能量 HCD MS/MS，并在 Orbitrap 中检测（30， 000 分辨率，5e ⁴ AGC，最大注入时间 = 100 ms，步进碰撞能量 = 25%、35%、45%）。

MS database searching MS 数据库搜索

For protein or phosphopeptide identification, LC–MS/MS raw data were processed with Proteome Discoverer (PD) (version 2.4.1.15) using SequestHT search engine. The precursor detector node in PD 2.4 was added to reduce the influence of chimeric spectra. The database was UniProt reviewed mouse protein database (updated July 2022) with 17,119 entries and common contaminants. Database searching parameters were set as following: enzyme specificity for trypsin and up to two missed cleavages were allowed, minimum peptide length was 6, and mass tolerance for precursor and fragment ions were set as 10 ppm and 0.02 Da, respectively. Cysteine carbamidomethylation was set as a fixed modification. For peptide identification, methionine oxidation and acetylation at the N-terminal of proteins were set as variable modifications. For phosphopeptide identification, phosphorylation at serine, threonine, tyrosine was also set as variable modifications besides the mentioned two variable modifications. The false discovery rate (FDR) was calculated using Percolator algorithm provided by PD. FDR on peptide and protein levels was 1%. PhosphoRS localization probability for phosphopeptides was set to greater than 0.75[32]. Only phosphopeptides with fully-localized sites were regarded as localized phosphopeptides. The number of non-redundant localized phosphopeptides and localized phosphosites were extracted with an in-house python script. The contaminating proteins were excluded from further data analysis.
对于蛋白质或磷酸肽的鉴定，使用SequestHT搜索引擎使用Proteome Discoverer（PD）（版本2.4.1.15）处理LC-MS/MS原始数据。在PD 2.4中增加了前驱体检测器节点，以减少嵌合光谱的影响。该数据库是 UniProt 审查的小鼠蛋白数据库（2022 年 7 月更新），包含 17,119 个条目和常见污染物。数据库检索参数设置如下：允许胰蛋白酶的酶特异性和最多两次漏解，最小肽长度为 6，母离子和碎片离子的质量容差分别设置为 10 ppm 和 0.02 Da。半胱氨酸氨基甲化被设定为固定修饰。对于肽鉴定，蛋白质N端的蛋氨酸氧化和乙酰化被设定为可变修饰。对于磷酸肽的鉴定，除了上述两种可变修饰外，丝氨酸、苏氨酸、酪氨酸的磷酸化也被设定为可变修饰。使用PD提供的渗滤器算法计算错误发现率（FDR），肽和蛋白质水平的FDR为1%。磷酸肽的磷酸化RS定位概率设置为大于0.75[32]。只有具有完全定位位点的磷酸肽才被视为局部磷酸肽。使用内部 python 脚本提取非冗余局部磷酸肽和局部磷酸化位点的数量。污染蛋白被排除在进一步的数据分析之外。

For N-glycopeptide identification, LC-MS/MS raw data were searched with the same database mentioned above using PTMcentric search engine Byonic (version 3.11.3, Protein Metrics) incorporated in PD 2.2. Trypsin was selected as the enzyme and up to two missed cleavages were allowed. Searches were performed with a precursor mass tolerance of 10 ppm and a fragment mass tolerance of 0.02 Da. Cysteine carbamidomethylation was set as static modification. Dynamic modifications included oxidation of methionine residues, deamidation of asparagine and glutamine, and N-glycosylation on asparagine. Oxidation and deamidation were set as “rare” modifications, and N-glycosylation was set as “common” modification. Two rare modifications and one common modification were allowed. Mammalian N-glycan database embedded in Byonic, which contains 309 glycan entities, was used. Results were filtered to 1% protein FDR as set in Byonic parameters, and data was further processed to 1% FDR at the PSM level using the 2D-FDR score (a simple variation of the standard target-decoy strategy that estimates and controls PSM and protein FDRs simultaneously) [33, 34]. Only N-glycopeptides with Byonic score > 100 and |logProb|> 1 were reported (the absolute value of the log base 10 of the protein p-value). Each N-glycopeptide identified should have the consensus motif N-X-S/T (X ≠ P). This filtering criteria has been reported to result in confident glycosite assignment at glycopeptide spectral match level [35]. The contaminating proteins were excluded from further data analysis.
对于N-糖肽鉴定，使用PD 2.2中包含的PTM中心搜索引擎Bionic（版本3.11.3，蛋白质指标）使用上述相同数据库检索LC-MS/MS原始数据。选择胰蛋白酶作为酶，最多允许两次遗漏的裂解。在母体质量数公差为10 ppm，片段质量数公差为0.02 Da的情况下进行搜索。 半胱氨酸氨基甲化被设定为静态修饰。动态修饰包括蛋氨酸残基的氧化、天冬酰胺和谷氨酰胺的脱酰胺化以及天冬酰胺的 N-糖基化。氧化和脱酰胺被设定为“罕见”修饰，N-糖基化被设定为“常见”修饰。允许进行两次罕见修改和一次常见修改。使用嵌入在 Byonic 中的哺乳动物 N-聚糖数据库，其中包含 309 个聚糖实体。按照 Byonic 参数中设置的结果过滤至 1% 的蛋白质 FDR，并使用 2D-FDR 评分（同时估计和控制 PSM 和蛋白质 FDR 的标准靶标诱饵策略的简单变体）在 PSM 水平上进一步处理数据至 1% FDR [ 33， 34]。仅报告了 Byonic 评分> 100 且 |logProb|> 1 的 N-糖肽（蛋白质 p 值的对数碱基 10 的绝对值）。鉴定出的每个 N-糖肽都应具有共识基序 N-X-S/T （X ≠ P）。据报道，该过滤标准在糖肽谱匹配水平上可产生可靠的糖位点分配[35]。污染蛋白被排除在进一步的数据分析之外。

Gene ontology and pathway analysis of three proteomic data
3种蛋白质组学数据的基因本体与通路分析

Gene ontology (GO) analysis of three proteomic data (proteome, phosphoproteome, and N-glycoproteome) was performed with Panther GOSlim[36], DAVID Bioinformatics Resource [37], and ToppCluster [38]. The hypergeometric statistical test and Benjamini & Hochberg false discovery rate correction were adopted to derive overrepresented functions. The level of significance was set as P ≤ 0.05. Pathway analysis of the three proteomic data was conducted with KEGG database [39] and Reactome database [40]. ECM-receptor interaction network was retrieved from Pathview web (https://pathview.uncc.edu/) [41]. Uniprot database was used to annotate membrane proteins in the proteome of C2C12 sEVs. TOPCONS (https://topcons.cbr.su.se/) [42] was used to predict the number of transmembrane helices (TMs) of the multi-pass membrane proteins.
使用Panther GOSlim[ 36]、DAVID Bioinformatics Resource [ 37]和ToppCluster [ 38]对3个蛋白质组数据（蛋白质组、磷酸化蛋白质组和N-糖蛋白组）进行基因本体分析。采用超几何统计检验和Benjamini & Hochberg错误发现率校正来推导过表示函数。显著性水平设定为P≤0.05。利用KEGG数据库[39]和反应组数据库[40]对3个蛋白质组学数据进行通路分析。ECM-受体相互作用网络取自Pathview web（https://pathview.uncc.edu/）[41]。利用Uniprot数据库对C2C12 sEVs蛋白质组中的膜蛋白进行注释。TOPCONS （ https://topcons.cbr.su.se/） [ 42] 用于预测多通道膜蛋白的跨膜螺旋 （TM） 数量。

Phosphoproteomic analysis of C2C12 sEVs
C2C12 sEVs的磷酸化蛋白质组学分析

Localized phosphosites were mapped in PhosphoSitePlus [43] and dbPTM [44]. GPS5.0 was used to predict kinases responsible for tyrosine phosphosites. The classification of kinases identified in the three proteomic data was performed according to mouse Kinome database [45].
在PhosphoSitePlus [ 43] 和 dbPTM [ 44] 中定位了局部磷酸化位点。GPS5.0用于预测酪氨酸磷酸位点的激酶。根据小鼠Kinome数据库[45]对3种蛋白质组学数据中鉴定出的激酶进行分类。

Membrane transporters analysis
膜转运蛋白分析

Membrane transporters identified in the three proteomic data were classified according to the Transporter Classification database (TCDB) [46]. PTM information was integrated on membrane transporters and presented with circular barplot.
根据转运蛋白分类数据库（TCDB）对3种蛋白质组学数据中鉴定的膜转运蛋白进行分类[46]。PTM信息被整合到膜转运蛋白上，并以圆形条形图呈现。

Proteomic analysis of sEVs from C2C12 myoblasts
C2C12成肌细胞sEV的蛋白质组学分析

To characterize the cargos in C2C12 myoblasts-derived sEVs, we conducted a comprehensive analysis of proteins, phosphoproteins, and N-glycoproteins with LC–MS/MS. Proteins from three biological replicates of sEVs samples were digested into peptides. For each biological replicate, two technical replicates of LC–MS/MS analyses were performed. In this way, six LC–MS/MS data were obtained for each proteomic or PTMomic analysis.
为了表征 C2C12 成肌细胞衍生的 sEV 中的货物，我们使用 LC-MS/MS 对蛋白质、磷蛋白和 N-糖蛋白进行了全面分析。 将来自 sEV 样品的三个生物学重复的蛋白质消化成肽。对于每个生物学重复，进行两次LC-MS/MS分析的技术重复。通过这种方式，每个蛋白质组学或PTMomic分析都获得了6个LC-MS/MS数据。

At the proteome level, 2024 proteins were identified in C2C12 sEVs (Table S1). sEVs proteins were categorized with GO biological process (GOBP), GO cellular component (GOCC), and GO molecular function (GOMF) using GOSlim in Panther (Fig. 2A). GOBP overrepresentation analysis revealed that sEVs proteins were enriched with vesicle structure- and vesicle biogenesis-related biological processes, such as cellular localization, protein localization, intracellular transport, protein transport, and vesicle-mediated transport, which is consistent with the role of sEVs as a means of transport. Cytosol, vesicle, and endosome were the most highly represented terms in GOCC overrepresentation analysis of sEVs proteins. Certain functional activities, such as binding activities (protein-containing complex binding, nucleotide binding), were overrepresented in sEVs, suggesting that sEVs exert their functions with binding with other functional molecules.
在蛋白质组水平上，在 C2C12 sEV 中鉴定出 2024 种蛋白质（表 S 1）。在Panther中使用GOSlim对sEVs蛋白进行GO生物过程（GOBP），GO细胞成分（GOCC）和GO分子功能（GOMF）分类（图2A）。GOBP过表达分析显示，sEVs蛋白富集囊泡结构和囊泡生物发生相关生物过程，如细胞定位、蛋白质定位、细胞内转运、蛋白质转运和囊泡介导的转运，这与sEVs作为转运手段的作用一致。胞质溶胶、囊泡和内体是 sEVs 蛋白 GOCC 过表达分析中代表性最强的术语。某些功能活性，如结合活性（含蛋白质复合物结合、核苷酸结合）在 sEV 中被过度表达，表明 sEV 通过与其他功能分子结合发挥其功能。

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Fig. 2 图2

Proteomic analysis of C2C12 myoblasts-derived sEVs. A Analysis of the proteome of sEVs with GOCC, GOBP, and GOMF. B Reactome pathway analysis of the proteome of sEVs. C The classification of membrane proteins identified in sEVs. TMs, transmembrane helices
C2C12 成肌细胞衍生的 sEV 的蛋白质组学分析。具有 GOCC、GOBP 和 GOMF 的 sEV 蛋白质组分析。B sEVs蛋白质组的反应组通路分析。C 在sEV中鉴定的膜蛋白的分类。TMs，跨膜螺旋

Top10 Reactome pathways in the proteome of sEVs are shown in Fig. 2B. Endosomal sorting complexes required for transport (ESCRT), signaling by MET, and axon guidance were the most represented pathways in sEVs. ESCRT protein complex is required for both the formation of MVB vesicles and the sorting of cargos into vesicles [49], while MET signaling and axon guidance are signaling pathways specifically reported in sEVs of C2C12 myoblasts.
sEVs蛋白质组中的Top10反应组途径如图2B所示。转运所需的内体分选复合物 （ESCRT）、MET 信号传导和轴突引导是 sEV 中最具代表性的通路。ESCRT蛋白复合物是MVB囊泡形成和将货物分选到囊泡中所必需的[49]，而MET信号转导和轴突引导是在C2C12成肌细胞的sEV中特异性报道的信号通路。

As we have published a comprehensive proteomic and phosphoproteomic analysis of C2C12 myoblasts, in which 7827 proteins were identified [50], we compared the proteomes of cells and sEVs of C2C12 myoblasts. First, the number of proteins identified in sEVs was about 1/4 of that of cells, which suggested that a specific subpopulation of proteins from the cells of origin is sorted into sEVs. Second, most of proteins (1757/2024 proteins) identified in sEVs proteome were also identified in the proteome of cells, suggesting that the abundance of proteins, instead of types of proteins, accounts for the major difference of the proteomes of sEVs and cells. Furthermore, 267 proteins were exclusively identified in the proteome of sEVs (Figure S1A). GOCC analysis of these sEVs-specific proteins revealed that they were mainly from extracellular region, extracellular space, membrane, and cell surface (Figure S1B), indicating that sEVs were enriched of secreted proteins and membrane proteins. Then, we compared the proteomes of cells and sEVs with GO. GOBP analysis showed that different biological processes were overrepresented in the cells and sEVs. Vesicle structure-and vesicle biogenesis-related biological processes were overrepresented in sEVs (Fig. 2A), while different metabolic processes and organelle organization were overrepresented in the proteome of cells (Figure S1C). For GOCC analysis, cytosol and vesicles were overrepresented in sEVs (Fig. 2A), while organelle, cytoplasm, and nucleus were overrepresented in the proteome of cells (Figure S1C). These results indicated that sEVs contain a specific subpopulation of proteins, which might play specific functions for sEVs.
由于我们发表了对C2C12成肌细胞的综合蛋白质组学和磷酸化蛋白质组学分析，其中鉴定了7827种蛋白质[50]，我们比较了细胞的蛋白质组和C2C12成肌细胞的sEV。首先，在sEV中鉴定出的蛋白质数量约为细胞的1/4，这表明来自来源细胞的特定蛋白质亚群被分类到sEV中。其次，在sEVs蛋白质组中鉴定出的大多数蛋白质（1757/2024个蛋白质）也在细胞的蛋白质组中鉴定出来，这表明蛋白质的丰度，而不是蛋白质的类型，是sEVs和细胞蛋白质组的主要差异。此外，在sEV的蛋白质组中专门鉴定了267种蛋白质（图S 1A）。对这些sEVs特异性蛋白的GOCC分析显示，它们主要来自细胞外区域、细胞外空间、细胞膜和细胞表面（图S 1B），表明sEVs富集了分泌蛋白和膜蛋白。然后，我们将细胞和sEV的蛋白质组与GO进行了比较。GOBP分析表明，不同的生物过程在细胞和sEV中被过度表达。囊泡结构和囊泡生物发生相关的生物过程在sEV中过高（图2A），而不同的代谢过程和细胞器组织在细胞蛋白质组中过高（图S 1C）。对于GOCC分析，细胞质和囊泡在sEV中过高（图2A），而细胞器、细胞质和细胞核在细胞蛋白质组中过高（图S 1C）。这些结果表明，sEVs含有特定的蛋白质亚群，这些蛋白质亚群可能对sEVs起特定功能。

Since sEVs enriched of secreted proteins, we predicted classical secreted proteins in the proteome of sEVs with the workflow described previously [51]. 200 classical secreted proteins were identified in the proteome of sEV (Table S2). Functional analysis of these secreted proteins revealed that they were mainly involved in extracellular matrix organization, cell adhesion, and collagen fibril organization. They also participated in pathways of regulation of insulin-like growth factor transport and uptake by IGFBPs, and post-translational protein phosphorylation (Figure S1D), suggesting that these secreted proteins take part in signaling through post-translational protein phosphorylation.
由于sEV富集了分泌蛋白，我们用前面描述的工作流程预测了sEV蛋白质组中的经典分泌蛋白[51]。在sEV的蛋白质组中鉴定出200种经典分泌蛋白（表S 2）。对这些分泌蛋白的功能分析表明，它们主要参与细胞外基质组织、细胞粘附和胶原纤维组织。它们还参与了IGFBP调节胰岛素样生长因子转运和摄取的途径，以及翻译后蛋白质磷酸化（图S 1D），表明这些分泌的蛋白质通过翻译后蛋白质磷酸化参与信号传导。

As membrane proteins have important functions in numerous cellular processes, such as signal transduction, cell-to-cell interaction, cell-to-matrix interaction, membrane trafficking, and transmembrane transport of ions, metabolites and proteins, we annotated the proteome of sEVs with Uniprot database, and found that there was a remarkable number of membrane proteins. 737 proteins were annotated as membrane proteins (Table S3), accounting for 36.4% of the total proteins identified in sEVs. This percentage is equivalent to the estimated percentage of membrane proteins in cell culture medium-derived EVs (34%) [52].
由于膜蛋白在信号转导、细胞间相互作用、细胞间相互作用、细胞间相互作用、膜运输以及离子、代谢物和蛋白质的跨膜转运等众多细胞过程中具有重要功能，因此我们用Uniprot数据库对sEVs的蛋白质组进行了注释，发现膜蛋白的数量非常显著。737 种蛋白质被注释为膜蛋白（表 S 3），占 sEV 中鉴定的总蛋白质的 36.4%。该百分比相当于细胞培养基衍生EV中膜蛋白的估计百分比（34%）[52]。

According to intramolecular arrangement and position in the cell, membrane proteins are generally classified into six types: single-pass type I membrane protein, single-pass type II membrane protein, multi-pass membrane protein, lipid-anchored membrane protein, glycosylphosphatidylinositol (GPI)-anchored membrane protein, and peripheral membrane protein [53]. We classified the 737 membrane proteins into four types according to the annotation in Uniprot database: single-pass membrane protein, lipid-/GPI-anchored membrane protein, peripheral membrane protein, and multi-pass membrane protein. The percentage of single-pass membrane proteins, peripheral membrane proteins, multi-pass membrane proteins, and lipid-/GPI-anchored membrane proteins of all membrane proteins is 38%, 23%, 24%, and 15%, respectively (Fig. 2C). The high percentage of GPI-anchored proteins is in agreement with previous observation that GPI-anchored proteins are enriched in exosomes/EVs [54]. These proteins might perform or mediate diverse cellular functions of EVs, such as signal transduction and cell adhesion [55]. Then, we predicted TMs of the multi-pass membrane proteins and found that about 1/4 multi-pass membrane proteins had four TMs (Fig. 2C), including some tetraspanins (TSPANs) (CD9, CD63, CD81, CD151, Tspan 2–9, Tspan 14–15). The enrichment of TSPANs in sEVs probably because TSPANs can form TSPAN-complexes/ TSPAN web with other TSPANs, integrins or signaling receptors, which locate in TSPAN-enriched microdomain, and play important roles in biogenesis of exosomes, sorting proteins into sEVs, and contribute to target cell selection and uptake [56, 57].
根据分子内排列和在细胞中的位置，膜蛋白一般分为6种类型：单程I.型膜蛋白、单程II.型膜蛋白、多程膜蛋白、脂质锚定膜蛋白、糖基磷脂酰肌醇（GPI）锚定膜蛋白和外周膜蛋白[53]。根据Uniprot数据库的注释，将737种膜蛋白分为4种类型：单程膜蛋白、脂质/GPI锚定膜蛋白、外周膜蛋白和多程膜蛋白。在所有膜蛋白中，单程膜蛋白、外周膜蛋白、多程膜蛋白和脂质/GPI锚定膜蛋白的百分比分别为38%、23%、24%和15%（图2C）。GPI锚定蛋白的高百分比与先前的观察结果一致，即GPI锚定蛋白富集于外泌体/EV中[54]。这些蛋白质可能执行或介导EV的各种细胞功能，例如信号转导和细胞粘附[55]。然后，我们预测了多通道膜蛋白的TM，发现大约1/4的多通道膜蛋白有四个TM（图2C），包括一些四跨膜蛋白（TSPAN）（CD9、CD63、CD81、CD151、Tspan 2-9、Tspan 14-15）。TSPANs在sEVs中的富集可能是因为TSPANs可以与其他TSPANs、整合素或信号受体形成TSPAN复合物/TSPAN网，它们位于TSPAN富集的微结构域中，在外泌体的生物发生中发挥重要作用，将蛋白质分类为sEVs，并有助于靶细胞的选择和摄取[56,57]。

In summary, the proteome of C2C12 sEVs is different from that of cells on the basis of GO and pathway analysis. A high percentage of membrane proteins was identified in sEVs, which is in agreement with the concept that sEVs share the same plasma membrane with their parent cells.
综上所述，基于GO和通路分析，C2C12 sEVs的蛋白质组与细胞的蛋白质组不同。在sEV中鉴定出高比例的膜蛋白，这与sEV与其亲本细胞共享同一质膜的概念一致。

Phosphoproteomic analysis of sEVs from C2C12 myoblasts
C2C12成肌细胞sEV的磷酸化蛋白质组学分析

We performed phosphoproteomic analysis of sEV samples with six LC–MS/MS analyses. 4890 phosphopeptides (including 4088 phosphopeptides with localized phosphosites), 3429 unique phosphosites, and 1434 phosphoproteins were identified in sEVs of C2C12 myoblasts (Fig. 3A; Table S4). The in-house python script for phosphoproteomic analysis is also provided in Table S4.
我们通过六次LC-MS/MS分析对sEV样品进行了磷酸化蛋白质组学分析。在 C2C12 成肌细胞的 sEV 中鉴定出 4890 个磷酸肽（包括 4088 个具有局部磷酸位点的磷酸肽）、3429 个独特磷酸位点和 1434 个磷蛋白（图 3A;表S 4）。表 S 4 中还提供了用于磷酸化蛋白质组学分析的内部 python 脚本。

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Fig. 3 图3

Phosphoproteomic analysis of C2C12 myoblasts-derived sEVs. A Phosphoproteomic results of sEVs of C2C12 myoblasts. B Reactome pathway analysis of phosphoproteins identified in sEVs. C The number and distribution of newly-identified phosphosites in sEVs. D Phosphosites identified on Alix, a marker protein of sEVs. E Comparison of the distribution of phosphosites in sEVs and cells. F Reactome pathway analysis of tyrosine-phosphorylated proteins in sEVs
C2C12 成肌细胞衍生的 sEV 的磷酸化蛋白质组学分析。A C2C12成肌细胞sEV的磷酸化蛋白质组学结果。B sEVs中鉴定的磷蛋白的反应组通路分析。C sEV中新发现的磷酸位点的数量和分布。D 在 sEV 的标记蛋白 Alix 上鉴定出的磷酸化位点。E sEVs和细胞中磷酸化位点分布的比较。F sEVs中酪氨酸磷酸化蛋白的反应组通路分析

First, we compared the phosphoproteomes of sEVs and cells [50]. The overlap of phosphoproteins with localized phosphosites in C2C12 cells and sEVs was high. About 70% phosphoproteins identified in sEVs were also identified in cells (Figure S2A), which is similar to the proteomes of sEVs and cells. However, 409 phosphoproteins were specifically identified in the phosphoproteome of sEVs. GOCC analysis revealed that these sEV-specific phosphoproteins mainly localized in membrane, endosome, and cell surface (Figure S2B). GOBP analysis of the phosphoproteomes of sEVs and cells showed that distinct biological processes were enriched in sEVs and cells. Biological processes of protein phosphorylation, cell migration, endocytosis, and cell adhesion were enriched in the phosphoproteome of sEVs, while biological processes of chromatin, cell cycle, mRNA processing, and RNA splicing were overrepresented in the phosphoproteome of cells (Figure S2C). Cytoplasm, membrane, endosome, and plasma membrane were the most highly represented GOCC terms in the phosphoproteome of sEVs, while nucleus, cytoplasm, cytosol, and cytoskeleton were enriched in the phosphoproteome of cells (Figure S2D). Focal adhesion, proteoglycans in cancer, endocytosis, axon guidance, and regulation of actin cytoskeleton were among the top 10 enriched KEGG pathways in the phosphoproteome of sEVs, while spliceosome, proteoglycans in cancer, adherens junction, and cell cycle were among the top 10 enriched KEGG pathways in the phosphoproteome of cells (Figure S2E). Reactome pathway analysis of phosphoproteins in sEVs revealed that cell–cell communication, signaling by VEGF, EPH-Ephrin signaling, axon guidance, signaling by Rho GTPases, and signaling by Rho receptor tyrosine kinases were enriched in sEVs (Fig. 3B), suggested that phosphoproteins in sEVs might play specific roles in different signaling pathways in C2C12 myoblasts.
首先，我们比较了sEV和细胞的磷酸化蛋白质组[50]。C2C12细胞和sEV中磷蛋白与局部磷酸位点的重叠度很高。在sEV中鉴定出的约70%的磷蛋白也在细胞中鉴定（图S 2A），这与sEV和细胞的蛋白质组相似。然而，在 sEV 的磷酸化蛋白质组中特异性鉴定了 409 种磷蛋白。GOCC分析显示，这些sEV特异性磷蛋白主要定位于膜、内体和细胞表面（图S 2B）。对sEVs和细胞的磷酸化蛋白质组进行GOBP分析表明，sEVs和细胞中富集了不同的生物过程。蛋白质磷酸化、细胞迁移、内吞作用和细胞粘附等生物学过程在sEV的磷酸化蛋白质组中富集，而染色质、细胞周期、mRNA加工和RNA剪接的生物学过程在细胞的磷酸化蛋白质组中被过度表达（图S 2C）。细胞质、膜、内体和质膜是sEVs磷酸化蛋白质组中最具代表性的GOCC术语，而细胞核、细胞质、胞质和细胞骨架在细胞的磷酸化蛋白质组中富集（图S 2D）。黏着斑、癌症中的蛋白聚糖、内吞作用、轴突引导和肌动蛋白细胞骨架的调节是 sEV 磷酸化蛋白质组中前 10 个富集的 KEGG 通路之一，而剪接体、癌症中的蛋白聚糖、粘附连接和细胞周期是细胞磷酸化蛋白质组中前 10 个富集的 KEGG 通路之一（图 S 2E）。sEVs中磷蛋白的反应组通路分析显示，sEVs富集了细胞间通讯、VEGF信号传导、EPH-Eph蛋白信号传导、轴突引导、Rho GTP酶信号传导和Rho受体酪氨酸激酶信号传导（图1）。 3B），表明sEV中的磷蛋白可能在C2C12成肌细胞的不同信号通路中发挥特定作用。

Detailed analysis of phosphoproteins revealed that about half of phosphoproteins in sEVs had at least two phosphosites (Figure S3A). Some important phosphoproteins in sEVs were identified with a high number of phosphosites. For example, 25 phosphosites, including 15 pS, 8 pT, and 2 pY, were identified in Tight junction protein ZO-1 (Tjp1), an important cell adhesion protein in sEVs.
对磷蛋白的详细分析表明，sEV中大约一半的磷蛋白至少具有两个磷酸位点（图S 3A）。sEV中的一些重要磷蛋白被鉴定出具有大量的磷酸位点。例如，在 sEV 中重要的细胞粘附蛋白 ZO-1 （Tjp1） 中鉴定出 25 个磷酸化位点，包括 15 个 pS、8 个 pT 和 2 个 pY。

At the level of phosphosite, 172 phosphosites (about 5% of phosphosites identified) in sEVs were novel (not described in two comprehensive PTM databases–PhosphositePlus and dbPTM). About 40% of these novel phosphosites were on threonine and tyrosine (Fig. 3C). Alix (programmed cell death 6-interacting protein), a frequently used marker of sEVs, was identified with 13 phosphosites, among which four phosphothreonine sites were not reported previously (Fig. 3D). Since Alix is an accessory ESCRT protein and plays some roles in ESCRT-mediated protein sorting [58], these novel phosphothreonine sites on Alix might provide us some clues about its role in sEVs.
在磷酸位点水平上，sEV中的172个磷酸位点（约占已鉴定磷酸位点的5%）是新的（在两个全面的PTM数据库（PhosphositePlus和dbPTM）中未描述）。这些新型磷酸化位点中约有40%位于苏氨酸和酪氨酸上（图3C）。Alix（程序性细胞死亡 6 相互作用蛋白）是 sEV 的常用标志物，鉴定有 13 个磷酸位点，其中 4 个磷酸苏氨酸位点以前未报道 （Fig. 3D）。由于Alix是一种辅助ESCRT蛋白，在ESCRT介导的蛋白质分选中起着一定的作用[58]，Alix上的这些新的磷酸苏氨酸位点可能为我们提供了一些关于其在sEV中的作用的线索。

Phosphorylation pattern of sEVs was considerably different from that of cells. The sEVs-derived phosphoproteome had a high level of tyrosine (Y)-phosphorylated sites (2.89% vs 1.06% in cellular phosphoproteome) (Fig. 3E). Reactome pathway analysis of these tyrosine-phosphorylated proteins revealed that they were enriched in EPH-Ephrin signaling pathway (Fig. 3F), which is consistent with previous report [59]. An integrated EPH-Ephrin signaling network in sEVs, including tyrosine-phosphoproteins, tyrosine kinases predicted from GPS5.0, and phosphorylation sites, was constructed from STRING (Figure S3B).
sEVs的磷酸化模式与细胞的磷酸化模式有很大不同。sEVs衍生的磷酸化蛋白质组具有高水平的酪氨酸（Y）磷酸化位点（2.89%对细胞磷酸化蛋白质组中的1.06%）（图3E）。对这些酪氨酸磷酸化蛋白的反应组通路分析显示，它们富集于EPH-Ephrin信号通路（图3F），这与先前的报道一致[59]。从 STRING 构建了 sEV 中的集成 EPH-Ephrin 信号网络，包括酪氨酸-磷蛋白、从 GPS5.0 预测的酪氨酸激酶和磷酸化位点（图 S 3B）。

In summary, phosphorylation pattern of sEVs differs from that of cells. However, this phosphorylation pattern is in agreement with sEVs from other sources, suggesting that phosphorylation on tyrosine plays some roles in the formation and function of sEVs.
总之，sEV的磷酸化模式与细胞的磷酸化模式不同。然而，这种磷酸化模式与其他来源的 sEV 一致，表明酪氨酸的磷酸化在 sEV 的形成和功能中起着一定的作用。

N-glycoproteomic analysis of sEVs from C2C12 myoblasts
C2C12成肌细胞sEVs的N-糖蛋白质组学分析

N-Glycoproteins decorate cell surface and are released in the extracellular milieu, and play an essential role in cell-to-cell communication. It has reported that EVs are enriched in glycoconjugates (glycoproteins, glycosphingolipids, and protepglycans) and exhibit specific glycosignature [23]. In this study, we conducted N-glycoproteomic analysis of sEVs by enrichment of N-glycopeptides with ZIC-HILIC. From six LC–MS/MS analyses of N-glycopeptides, we documented a total number of 8764 intact N-glycopeptides composed of 770 N-glycosites and 278 glycan composition from 267 N-glycoproteins in sEVs of C2C12 myoblasts (Fig. 4A; Table S5).
N-糖蛋白修饰细胞表面并在细胞外环境中释放，并在细胞间通讯中起着至关重要的作用。据报道，EV富含糖缀合物（糖蛋白、鞘糖脂和蛋白聚糖）并表现出特异性糖特征[23]。在这项研究中，我们通过用 ZIC-HILIC 富集 N-糖肽对 sEV 进行了 N-糖蛋白组学分析。通过对 N-糖肽的六次 LC-MS/MS 分析，我们记录了 C2C12 成肌细胞 sEV 中由 770 个 N-糖位点组成的 8764 个完整 N-糖肽和 267 个 N-糖蛋白组成的 278 个聚糖组成（图 4A;表S 5）。

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Fig. 4 图4

N-glycoproteomic analysis of C2C12 myoblasts-derived sEVs. A The number of N-glycoproteins, intact N-glycopeptides, N-glycosites, and glycan composition identified in sEVs. B Reactome pathway analysis of N-glycoproteome of sEVs. C The distribution of the number of N-glycosites on glycoproteins in sEVs. D Top10 N-glycans detected on glycoproteins of sEVs based on the numbers of their modified N-glycosites. E Distribution of N-glycan subtypes from intact glycopeptides identified in sEVs. F Distribution of N-glycans with or without sialic acids (S and G). S, N-Acetylneuraminic acid (Neu5Ac); G, N-Glycolylneuraminic acid (Neu5Gc)
C2C12 成肌细胞衍生的 sEV 的 N-糖蛋白质组学分析。A 在 sEV 中鉴定的 N-糖蛋白、完整 N-糖肽、N-糖位点和聚糖组成的数量。B sEVs的N-糖蛋白组的反应组通路分析。C sEVs中糖蛋白上N-糖位点数量的分布。D 根据其修饰的 N-糖位数在 sEV 的糖蛋白上检测到的 Top10 N-聚糖。E 来自 sEV 中鉴定的完整糖肽的 N-聚糖亚型的分布。F 含或不含唾液酸（S 和 G）的 N-聚糖的分布。S，N-乙酰神经氨酸（Neu5Ac）;G，N-羟乙基神经氨酸（Neu5Gc）

First, we performed GO analysis of N-glycoproteins of sEVs (Figure S4A). GOCC analysis showed that N-glycoproteins were mainly from cell surface, membrane, extracellular space, extracellular region, and basement membrane. Biological processes predominantly associated with N-glycoproteins were cell adhesion, cell–matrix adhesion, and cell migration, indicating that N-glycoproteins in sEVs mainly participate in cell adhesion and cell migration. Certain binding activities, including integrin binding, collagen binding, laminin binding, calcium binding, receptor binding, were significantly overrepresented in N-glycoproteome of sEVs. Reactome pathway analysis revealed that several pathways, including signaling by receptor tyrosine kinases, extracellular matrix organization, signaling by MET, integrin interactions, and laminin interactions were overrepresented in N-glycoproteome of sEVs (Fig. 4B).
首先，我们对sEV的N-糖蛋白进行了GO分析（图S 4A）。GOCC分析显示，N-糖蛋白主要来源于细胞表面、细胞膜、细胞外空间、细胞外区和基底膜。与N-糖蛋白相关的生物学过程主要为细胞粘附、细胞-基质粘附和细胞迁移，表明sEV中的N-糖蛋白主要参与细胞粘附和细胞迁移。某些结合活性，包括整合素结合、胶原结合、层粘连蛋白结合、钙结合、受体结合，在 sEV 的 N-糖蛋白组中显着过高。反应组通路分析显示，几种通路，包括受体酪氨酸激酶的信号传导、细胞外基质组织、MET 信号传导、整合素相互作用和层粘连蛋白相互作用在 sEV 的 N-糖蛋白组中过度表达（图 4B）。

Detailed analysis of N-glycoproteins in sEVs revealed that more than 60% N-glycoproteins contained at least two N-glycosites (Figure S4B). On average, three N-glycosites were identified on the glycosylated sEV proteins. Some important proteins, which mediate the attachment, migration and organization of cells, were identified as heavily-glycosylated proteins. 29, 22, and 15 N-glycosites were identified on Prolow-density lipoprotein receptor-related protein 1 (LRP1), laminin subunit alpha 5 (LAMA5), and laminin subunit alpha 2 (LAMA2), respectively (Fig. 4C), which suggests glycosylation on proteins in sEVs plays important role in cell adhesion and migration.
对sEV中N-糖蛋白的详细分析显示，超过60%的N-糖蛋白含有至少两种N-糖位（图S 4B）。平均而言，在糖基化的sEV蛋白上鉴定出3个N-糖位点。一些介导细胞附着、迁移和组织的重要蛋白质被鉴定为重糖基化蛋白质。分别在低密度脂蛋白受体相关蛋白 1 （LRP1）、层粘连蛋白亚基 α 5 （LAMA5） 和层粘连蛋白亚基 α 2 （LAMA2） 上鉴定出 29、22 和 15 个 N-糖位点（图 4C），这表明 sEV 中蛋白质的糖基化在细胞粘附和迁移中起重要作用。

At the level of glycoform, 6474 glycoforms were identified on 770 N-glycosites of glycoproteins. About 28% N-glycosites had only one glycoform, while 72% N-glycosites had at least two glycoforms. On average, 8.4 glycoforms existed on one N-glycosite, indicating complex micro-heterogeneity of glycosylation on glycoproteins of sEVs (Figure S4C). Some N-glycoproteins in sEVs displayed a highly diverse microheterogeneity. For example, 119 glycoforms were identified on glycosite N316 of lactadherin protein (MFGE8), a peripheral surface protein that binds to phosphatidylserine in the outer leaflet of exosomes [60].
在糖型水平上，在 770 个糖蛋白的 N-糖位上鉴定出 6474 个糖型。大约 28% 的 N-糖位只有一种糖型，而 72% 的 N-糖位至少具有两种糖型。平均而言，一个N-糖位上存在8.4个糖型，表明sEV糖蛋白上的糖基化具有复杂的微异质性（图S 4C）。sEV中的一些N-糖蛋白表现出高度多样化的微异质性。例如，在乳粘蛋白（MFGE8）的糖位N316上鉴定出119种糖型，MFGE8是一种外周表面蛋白，与外泌体外叶中的磷脂酰丝氨酸结合[60]。

At the level of N-glycan, top10 glycan structures appeared at different N-glycosites were high-mannose glycans and complex glycans (Fig. 4D). For the 278 N-glycans, the majority of glycans were complex glycans (81.7%) (Fig. 4E), which is in agreement with previous observation that complex N-linked glycans serve as key determination of glycoprotein sorting into EVs[22]. Detailed analysis of the composition of glycans revealed that most of N-glycans contained at least one sialic acid: Neu5Ac (S) or Neu5Gc (G) (Fig. 4F). Sialylation plays a critical role in cell recognition, cell adhesion, and cell signaling. It has reported that sialic acids are enriched in exosomes from mesenchymal stem cells compared with cell membranes and sialic acids on exosomes promoted the interaction between exosomes and cells [61]. EV sialylation also seems to play a role during EV uptake by recipient cells [62]. We speculate that the enrichment of sialic acids in the sEVs of C2C12 myoblasts would be related to sialic acid-mediated uptake of sEVs by target cells.
在N-聚糖水平上，出现不同N-糖位的top10聚糖结构是高甘露糖聚糖和复合聚糖（图4D）。对于278种N-聚糖，大多数聚糖是复合聚糖（81.7%）（图4E），这与先前的观察结果一致，即复合N-连接聚糖是糖蛋白分选为EV的关键决定[22]。对聚糖组成的详细分析表明，大多数N-聚糖至少含有一种唾液酸：Neu5Ac（S）或Neu5Gc（G）（图4F）。唾液酸化在细胞识别、细胞粘附和细胞信号传导中起着关键作用。据报道，与细胞膜相比，间充质干细胞的外泌体富含唾液酸，外泌体上的唾液酸促进了外泌体与细胞之间的相互作用[61]。EV唾液酸化似乎也在受体细胞摄取EV的过程中发挥作用[62]。我们推测 C2C12 成肌细胞 sEV 中唾液酸的富集与唾液酸介导的靶细胞对 sEV 的摄取有关。

The surface of EVs is enriched with glycoproteins. CD63, a widely known marker of sEVs, was identified with three N-glycosites (N130, N150, and N172), which is in agreement with previous result [63]. The three N-glycosites located on the large extracellular loop of CD63 [64] and glycosylation of CD63 plays critical role in mediating its interaction with other proteins [63, 65]. The three N-glycosites of CD63 displayed a high degree of glycan heterogeneity. 55 glycans existed on the three N-glycosites. Glycosylation micro-heterogeneity on each N-glycosite of CD63 is shown in Figure S4D. Besides that, CD82 was identified to be glycosylated on N157. It has reported that glycosylation of CD82 at N157 is necessary for CD82-mediated inhibition of ovarian cancer cells migration and metastasis[66]. Except CD63 and CD82, another six TSPANs including TSPAN3, TSPAN6, TSPAN9, TSPAN14, TSPAN15, and CD151 were also identified as glycoproteins.
EV的表面富含糖蛋白。CD63是一种广为人知的sEV标志物，与3个N-糖位（N130、N150和N172）鉴定一致，与先前的结果一致[63]。位于CD63大细胞外环上的三个N-糖位[64]和CD63的糖基化在介导其与其他蛋白质的相互作用中起着关键作用[63,65]。CD63的3个N-糖位表现出高度的聚糖异质性。3 个 N-糖位上存在 55 种聚糖。CD63的每个N-糖位的糖基化微异质性如图S 4D所示。除此之外，CD82 被鉴定为在 N157 上糖基化。据报道，CD82在N157位点的糖基化是CD82介导的抑制卵巢癌细胞迁移和转移所必需的[66]。除CD63和CD82外，TSPAN3、TSPAN6、TSPAN9、TSPAN14、TSPAN15和CD151等另外6个TSPAN也被鉴定为糖蛋白。

Integrated analysis of the three proteomes of sEVs from C2C12 myoblasts
C2C12成肌细胞sEVs的三种蛋白质组的综合分析

We performed a comparative and integrated analysis of the three proteomes (proteome, phosphoproteome, N-glycoproteome) of sEVs. In total, 2780 proteins were identified in the three proteomes of C2C12 myoblast sEVs (Table S6). The overlap of proteins identified in the three proteomes is shown in Fig. 5A. 70% proteins were identified in only one proteome, suggesting that integrated proteomic and PTMomic analyses could expand the identification of cargos in sEVs. Next, we compared our dataset with Vesiclepedia database [67] (http://microvesicles.org/, accessed on 20 September 2022), which included 4937 genes of encoding exosomal proteins. 1779 proteins identified in our dataset were overlapped with Vesiclepedia database (Figure S5A) and 90 of the top100 EV proteins in Vesiclepedia database were identified in our dataset (Figure S5B), indicating a good enrichment of EV proteins.
我们对sEV的三种蛋白质组（蛋白质组、磷酸化蛋白质组、N-糖蛋白组）进行了比较和综合分析。在C2C12成肌细胞sEV的三个蛋白质组中总共鉴定出2780种蛋白质（表S 6）。在三个蛋白质组中鉴定出的蛋白质重叠如图5A所示，仅在一个蛋白质组中鉴定出70%的蛋白质，这表明综合蛋白质组学和PTM组学分析可以扩大sEV中货物的鉴定。接下来，我们将我们的数据集与 Vesiclepedia 数据库 [ 67] （ http://microvesicles.org/， 2022 年 9 月 20 日访问） 进行了比较，该数据库包括 4937 个编码外泌体蛋白的基因。在我们的数据集中鉴定出的 1779 种蛋白质与 Vesiclepedia 数据库重叠（图 S 5A），在我们的数据集中鉴定出 Vesiclepedia 数据库中前 100 种 EV 蛋白中的 90 种（图 S 5B），表明 EV 蛋白的富集良好。

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Fig. 5 图5

Integrated analysis of proteomic, phosphoproteomic, and N-glycoproteomic results of C2C12 myoblasts-derived sEVs. A The overlap of proteins identified in the three proteomes (proteome, phosphoproteome, and N-glycoproteome) of sEVs. B Comparative GOBP enrichment analysis of the proteome, phosphoproteome, and N-glycoproteome of sEVs with ToppCluster. C Kinase groups identified in the three-proteome dataset. D KEGG pathway and GOBP analysis of the kinases identified in the three-proteome dataset
C2C12 成肌细胞衍生的 sEV 的蛋白质组学、磷酸化蛋白质组学和 N-糖蛋白组学结果的综合分析。A 在 sEV 的三个蛋白质组（蛋白质组、磷酸化蛋白质组和 N-糖蛋白组）中鉴定的蛋白质重叠。B 使用 ToppCluster 对 sEV 的蛋白质组、磷酸化蛋白组和 N-糖蛋白组进行比较 GOBP 富集分析。在三蛋白质组数据集中鉴定的 C 激酶组。三蛋白质组数据集中鉴定的激酶的 D KEGG 通路和 GOBP 分析

Next, we compared our dataset with published EV proteomes of C2C12 myoblasts. In 2014, Forterre et al. [28] identified 344 proteins from EVs secreted from C2C12 myoblasts, among which 319 proteins (95.5%) were found in our results. In 2022, Watanabe et al. [29] identified 984 proteins from EVs secreted from C2C12 myoblasts, among which 795 protein (80.8%) were identified in our results. The overlap of the two published datasets with our data is shown in Figure S5C. 1985 proteins were specifically identified in our dataset, including 1244 proteins from proteome, 713 proteins from phosphoproteome, 19 proteins from N-glycoproteome, and 9 proteins from both phosphoproteome and N-glycoproteome (Figure S5C). Reactome pathway analysis of the proteins specifically identified in our data (1985 proteins) revealed that they were mainly involved in different signaling pathways, including integrin signaling, signaling by MET, signaling by EGFR, EPH-Ephrin signaling, RHOB GTPase cycle, signaling by TGFB family members, axon guidance, signaling by Rho GTPases, suggesting that integration analysis of proteomic and PTMomic data could provide more information about the role of sEVs in different signaling pathways (Figure S5D).
接下来，我们将我们的数据集与已发表的 C2C12 成肌细胞的 EV 蛋白质组进行了比较。2014年，Forterre等[28]从C2C12成肌细胞分泌的EV中鉴定出344种蛋白质，其中319种蛋白质（95.5%）在我们的结果中被发现。2022年，Watanabe等[29]从C2C12成肌细胞分泌的EV中鉴定出984种蛋白质，其中795种（80.8%）蛋白质被鉴定出来。图S 5C显示了两个已发表的数据集与我们的数据的重叠。 在我们的数据集中特别鉴定了1985种蛋白质，包括来自蛋白质组的1244种蛋白质，来自磷酸化蛋白质组的713种蛋白质，来自N-糖蛋白组的19种蛋白质，以及来自磷酸化蛋白质组和N-糖蛋白组的9种蛋白质（图S 5C）。对数据中特异鉴定的蛋白质（1985 种蛋白质）的反应组通路分析表明，它们主要参与不同的信号通路，包括整合素信号转导、MET 信号转导、EGFR 信号转导、EPH-Ephrin 信号转导、RHOB GTP 酶循环、TGFB 家族成员信号转导、轴突引导、Rho GTP 酶信号转导，表明蛋白质组学和 PTMomic 数据的整合分析可以提供更多关于 sEV 在不同信号转导中的作用的信息通路（图S 5D）。

Comparative GOBP and GOMF enrichment analyses of the three proteomic data were conducted with ToppCluster [38], a tool for performing multi-cluster gene functional enrichment analyses. Proteins shared by all three proteomes, or two proteomes, or specifically identified in one proteome, were associated with specific biological processes (Fig. 5B). Proteins identified by all three proteomes were mainly involved in cell morphogenesis. Proteins identified in both proteome and phosphoproteome were enriched with actin filament-based process, actin cytoskeleton organization, and regulation of cellular component biogenesis. Proteins shared by proteome and N-glycoproteome were mainly involved in cell-substrate adhesion and regulation of locomotion, while proteins specifically identified in each proteome were enriched with unique processes, for example, proteins specifically identified in the phosphoproteome were mainly involved in signaling transduction, such as small GTPase mediated signaling transduction, enzyme-linked receptor protein signaling pathway. Proteins specifically identified in the N-glycoproteome were mainly involved in extracellular matrix organization, cell–matrix adhesion and integrin-mediated signaling pathway. Proteins specifically identified in the proteome were mainly involved in metabolic process and intracellular protein transport.
使用ToppCluster[38]对三种蛋白质组学数据进行了GOBP和GOMF富集的比较分析，ToppCluster是一种用于进行多簇基因功能富集分析的工具。所有三个蛋白质组或两个蛋白质组共享的蛋白质，或在一个蛋白质组中特异性鉴定的蛋白质，都与特定的生物过程有关（图5B）。所有三个蛋白质组鉴定的蛋白质主要参与细胞形态发生。在蛋白质组和磷酸化蛋白质组中鉴定的蛋白质富含基于肌动蛋白丝的过程、肌动蛋白细胞骨架组织和细胞成分生物发生的调节。蛋白质组和N-糖蛋白组共享的蛋白质主要参与细胞-底物粘附和运动调控，而每个蛋白质组中特异性鉴定的蛋白质富集了独特的过程，例如，磷酸化蛋白质组中特异性鉴定的蛋白质主要参与信号转导，如小GTP酶介导的信号转导、酶联受体蛋白信号转导通路。在N-糖蛋白组中特异性鉴定的蛋白质主要参与细胞外基质组织、细胞-基质粘附和整合素介导的信号通路。在蛋白质组中特异性鉴定的蛋白质主要参与代谢过程和细胞内蛋白质转运。

At GOMF level, different molecular functions were overrepresented in proteins identified in different parts. Proteins shared by the three proteomes were associated with growth factor binding, cell adhesion molecule binding, and cadherin binding, proteins identified in both proteome and phosphoproteome were mainly enriched for kinase binding, actin binding and small GTPase binding, and proteins identified in both proteome and N-glycoproteome were mainly involved in collagen binding, laminin binding, integrin binding (Figure S5E).
在GOMF水平上，不同的分子功能在不同部位鉴定的蛋白质中被过度表达。3种蛋白质组共有的蛋白质与生长因子结合、细胞粘附分子结合和钙粘蛋白结合有关，蛋白质组和磷酸化蛋白质组鉴定的蛋白质主要富集激酶结合、肌动蛋白结合和小GTP酶结合，蛋白质组和N-糖蛋白组鉴定的蛋白质主要参与胶原结合、层粘连蛋白结合、整合素结合（图S 5E）。

Since EVs have been reported to carry active kinases, which can be transferred to recipient cells and exert different functions through phosphorylation events [20], we focused our analysis on protein kinases detected in the three proteomic dataset. 121 kinases were identified (Table S7), among which 104 kinases were identified as phosphoproteins and 7 kinases were identified as N-glycoproteins. Three dominant groups of kinases identified in sEVs were: (I) tyrosine kinases, including receptor tyrosine kinase (e.g. ERBB2, ERBB3, EPHA2, EPHA7, EPHB2-4, MET, EGFR), and non-receptor tyrosine kinases (e.g. SRC, FAK, FYN, YES); (II) serine/threonine protein kinases or dual specificity kinases from CMGC group (e.g. GSK3A, GSK3B, ERK1, ERK2, CDC2, CDK2, CDK4, CDK7); (III) serine/threonine protein kinases from AGC group (e.g. AKT1, PRKACa, PRKCb) (Fig. 5C). The biological processes predominantly associated with these kinases were transmembrane receptor protein tyrosine kinases signaling pathway, MAPK cascade, and insulin receptor signaling pathway. KEGG pathways linked to these kinases were ErbB signaling pathway, EGFR tyrosine kinase inhibitor resistance, and MAPK signaling pathway (Fig. 5D), suggesting that sEVs regulate signaling pathways through these kinases.
据报道，EV携带活性激酶，这些激酶可以转移到受体细胞中，并通过磷酸化事件发挥不同的功能[20]，因此我们将分析重点放在三个蛋白质组学数据集中检测到的蛋白激酶上。鉴定出121种激酶（表S 7），其中104种激酶鉴定为磷蛋白，7种激酶鉴定为N-糖蛋白。在sEV中鉴定出的三组显性激酶是：（I）酪氨酸激酶，包括受体酪氨酸激酶（如ERBB2、ERBB3、EPHA2、EPHA7、EPHB2-4、MET、EGFR）和非受体酪氨酸激酶（如SRC、FAK、FYN、YES）;（II）来自CMGC组的丝氨酸/苏氨酸蛋白激酶或双特异性激酶（例如GSK3A、GSK3B、ERK1、ERK2、CDC2、CDK2、CDK4、CDK7）;（III）来自AGC组的丝氨酸/苏氨酸蛋白激酶（例如AKT1，PRKACa，PRKCb）（图5C）。与这些激酶主要相关的生物过程是跨膜受体蛋白酪氨酸激酶信号通路、MAPK级联反应和胰岛素受体信号通路。与这些激酶相关的KEGG通路是ErbB信号通路、EGFR酪氨酸激酶抑制剂耐药性和MAPK信号通路（图5D），表明sEV通过这些激酶调节信号通路。

As sEVs have reported to contain certain populations of membrane transporters to transport of substances across cells, we classified membrane transporters identified in C2C12 sEVs according to the Transporter Classification database (TCDB)[46]. 325 membrane transporters were identified in C2C12 sEV proteome and PTMomes, which mainly belonged to five classes: channels/pores, electrochemical potential-driven transporters, primary active transporters, accessory factors involved in transport, and incompletely characterized transport systems (Figure S6; Table S8). Proteins in the class of channels/pores facilitate translocation of molecules across membrane. For example, Aquaporin-1 (Aqp1) and Aquaporin-5 (Aqp5) are water channel proteins, which facilitate the transport of water across membrane. Proteins in the class of electrochemical potential-driven transporters utilize electrochemical potential to facilitate the transport of molecules across membrane. For example, some amino acid transports, including Slc1a4, Slc1a5, Slc7a5, Slc43a2, Slc38a1, mediate the uptake of amino acids across membrane. Proteins in the class of primary active transporters directly use chemical energy to transport solutes across membrane. Furthermore, about 40% of membrane transporters belong to the class of Accessory factors involved in transport, including sixteen TSPANs, such as known exosome marker proteins CD9, CD63, CD81, and CD82.
由于sEVs已经报道含有某些膜转运蛋白群，以跨细胞转运物质，因此我们根据转运蛋白分类数据库（TCDB）对C2C12 sEV中鉴定的膜转运蛋白进行了分类[46]。在C2C12 sEV蛋白质组和PTMomes中鉴定出325个膜转运蛋白，主要分为通道/孔隙、电化学势驱动转运蛋白、初级活性转运蛋白、参与转运的辅助因子和不完全表征的转运系统（图S 6;表S 8）。通道/孔类中的蛋白质促进分子跨膜易位。例如，水通道蛋白-1 （Aqp1） 和水通道蛋白-5 （Aqp5） 是水通道蛋白，可促进水跨膜运输。电化学势驱动转运蛋白类中的蛋白质利用电化学势来促进分子跨膜的转运。例如，一些氨基酸转运，包括 Slc1a4、Slc1a5、Slc7a5、Slc43a2、Slc38a1，介导氨基酸跨膜的摄取。初级活性转运蛋白类的蛋白质直接利用化学能跨膜运输溶质。此外，大约 40% 的膜转运蛋白属于参与转运的辅助因子类，包括 16 种 TSPAN，例如已知的外泌体标记蛋白 CD9、CD63、CD81 和 CD82。

Integration of phosphorylation and glycosylation information on these membrane transports revealed that glycosylation mainly occurred on membrane transporters in the class of Accessory factors involved in transport, while phosphorylation occurred evenly on membrane transporters of the five classes (Fig. S6), which suggested that phosphorylation and glycosylation in sEVs play specific roles in transporting different substances between cells.
对这些膜转运的磷酸化和糖基化信息的整合表明，糖基化主要发生在参与转运的辅助因子类的膜转运蛋白上，而磷酸化均匀地发生在五类膜转运蛋白上（图S6），这表明sEV中的磷酸化和糖基化在细胞间运输不同物质中起着特定的作用。

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Fig. 6 图6

Ligand-receptor interactions identified in sEVs of C2C12 myoblasts. Ligand-receptor interactions were retrieved from CellTalk DB and constructed with R using hierarchical edge bundling. The classification of receptor or ligand categories was annotated with Uniport database. Outermost circle indicates receptors or ligands identified. Phosphorylated proteins and glycosylated proteins identified in the receptors or ligands are shown in the middle layer, with the dots color-coded. The inner layer contains gene names, color-coded for the corresponding ligand or receptor categories. Connections are marked as lines between ligands and receptors
在 C2C12 成肌细胞的 sEV 中鉴定的配体-受体相互作用。从CellTalk DB中检索配体-受体相互作用，并使用分层边缘捆绑使用R构建。使用Uniport数据库对受体或配体类别的分类进行注释。最外层的圆圈表示已鉴定的受体或配体。在受体或配体中鉴定的磷酸化蛋白和糖基化蛋白显示在中间层，点用颜色编码。内层包含基因名称，针对相应的配体或受体类别进行颜色编码。连接被标记为配体和受体之间的线

We would like to thank all members in the Laboratory of Proteomics, Institute of Biophysics, Chinese Academy of Sciences for their help.
我们要感谢中国科学院生物物理研究所蛋白质组学实验室的所有成员的帮助。