Spatiotemporally Resolved Tracking of Extracellular Vesicle Cargo via Photocatalytic Extracellular Vesicles Protein Tracking (PhoEVT)

Abstract

Extracellular vesicle (EV)‐mediated protein transport has been recognized as a crucial mechanism for intercellular communication and interaction. Proximity labeling has emerged as a promising approach to study the dynamic protein interactions in cellular activity, but tracking extracellular protein transport pathways remains to be further investigated. Here, we employ Ru(bpy)₃ ²⁺ (RU) to construct a spatiotemporally resolved Photocatalytic Extracellular Vesicles protein Tracking (PhoEVT) system. Upon 450 nm irradiation, RU generates singlet oxygen to trigger the biotinylation of EV‐associated proteins with high efficiency. The photocatalyst was used as a nongenetic alternative to enzymatic approaches for singlet oxygen generation upon 450 nm photoirradiation during EV purification, which allowed the subsequent labeling of nearby accessible proteins with the biotin‐aniline probe. Using spintip streptavidin‐mediated affinity purification followed by mass spectrometry, we tracked EV‐associated protein signals and detected EV‐derived proteins in recipient cells. Based on the PhoEVT system, we demonstrated the uptake dynamics of EV‐associated proteins in recipient cells and performed unbiased proteomic profiling of detected EV‐derived proteins. Furthermore, we monitored the presence and temporal changes of EV‐associated proteins during the interaction of tumor cell‐derived EVs with immune cells, providing an effective tool to better investigate the dynamics of EV‐associated proteins.

The spatiotemporally resolved tracking system is developed utilizing nongenetic photocatalytic proximity labeling to profile extracellular vesicle (EV)‐associated proteins. Upon blue light irradiation, the photocatalyst triggers unbiased biotinylation of accessible EV‐associated proteins, enabling visualization and proteomic analysis. This reveals differential intracellular processing and temporal persistence of EV‐associated protein signals, offering a robust tool for dissecting EV‐mediated intercellular communication.

1. Introduction

Extracellular vesicles (EVs) are lipid bilayer particles secreted by cells into the extracellular pathway. EVs contain multiple cargo molecules, including proteins, lipids, and nucleic acids, which allow them to mediate crucial intercellular communication under diverse physiological and pathological conditions [1]. These cargo molecules are selectively sorted via endosomal sorting complexes required for transport (ESCRT)‐dependent and ESCRT‐independent mechanisms during the formation of intraluminal vesicles (ILVs). Once assembled, these ILVs are secreted as EVs upon the fusion of multivesicular bodies with the plasma membrane [2]. The uptake of EVs occurs primarily via endocytic mechanisms, leading to their encapsulation within endosomes. Following internalization, a subset of EVs may release cargo molecules into the cytosol, where they may modulate gene expression or signal transduction. Conversely, a proportion of internalized EVs are trafficked to lysosomes for degradation. Additionally, some internalized EV components may be recycled or expelled through exocytosis [3]. It is also important to note that the overall efficiency of EV uptake and intracellular cargo processing is highly variable depending on the donor and recipient cell states, and this process plays a critical role in intercellular communication. The precise fate of distinct EV cargo remains an area of active investigation.

With recent advances, proximity labeling has evolved into a powerful tool for dynamically monitoring molecular interactions involved in multiple biological processes. Conventional enzymatic methods such as APEX and TurboID depend on genetic fusion to a protein of interest [4, 5], requiring a “bait” target to enable the labeling and identification of proximal protein interactions. Although these approaches have revolutionized protein interaction mapping, they require genetic manipulation prior to application [6]. The integration of visible‐light photoredox catalysis into proximity labeling offers a promising alternative. Originally developed for organic synthesis, this strategy enables precise spatiotemporal control of protein labeling without requiring genetic engineering [7, 8, 9]. Small‐molecule photocatalysts, such as transition metal complexes and organic photosensitizers, have been leveraged as nongenetic alternatives to enzymes for studying cell–cell interactions. These catalysts can be photoactivated to produce singlet oxygen or phenoxy radicals, which mediate the proximity labeling reaction. Notably, CAT‐Prox demonstrated the feasibility of applying photocatalytic proximity labeling within a restricted membrane‐bound organelle, enabling spatiotemporally resolved mitochondrial proteome profiling and providing a precedent for compartment‐specific photocatalytic labeling [10]. Despite the growing use of photocatalytic labeling strategies, their application in EV research is still limited. Although NHS‐biotin labeling is widely used, it lacks temporal control and may reduce trypsin cleavage efficiency because of its lysine‐biased reactivity [11]. Furthermore, unbiased labeling remains critical for deciphering extracellular signaling pathways. Bridging this gap could open new avenues for nongenetic, temporally controlled tracking of EVs.

In this work, we sought to utilize a recently developed photocatalytic proximity labeling approach to overcome this gap in EV research. When provided with the appropriate labeling probe, these photocatalysts generate singlet oxygen under photoactivation, leading to biotinylation of proximal proteins at nearby accessible amino acid residues. The biotinylated proteins can be enriched through streptavidin affinity purification and efficiently identified by mass spectrometry analysis. Biotin was selected because of its favorable biocompatibility and compatibility with both streptavidin‐mediated fluorescence detection and affinity enrichment for LC‐MS/MS analysis. Recently, Ru(bpy)₃ ²⁺ (RU) has been introduced as a biocompatible and efficient transition metal complex‐based photocatalyst suitable for cell surface labeling applications. The RU‐based photocatalytic system enables high‐resolution proximity labeling with single‐cell resolution, allowing sensitive detection of cell–cell interactions within cell populations, demonstrates enhanced compatibility with primary cells and clinical samples, and has recently been extended to in‐depth profiling of surface‐accessible proteomes through free RU‐mediated chemical labeling [11, 12]. Here, we introduce a method to profile EV‐associated protein dynamics in recipient cells by proximity labeling through the photocatalytic actions of RU, a spatiotemporally resolved Photocatalytic Extracellular Vesicles protein Tracking (PhoEVT) system. Utilizing this system, we successfully tracked the precise time course of labeled EV‐associated proteins upon their detection in recipient cells, revealing the process of EV internalization. Beyond mere entry, we also monitored the presence and temporal changes of these molecules during the interaction between tumor cell‐derived EVs and immune cells. This system provides a powerful and effective tool that enables researchers to dissect the complex behaviors of EV‐associated proteins with high spatial and temporal resolution, thereby facilitating the distinction of EV‐associated protein dynamics from other forms of intercellular communication.

2. Results and Discussion

2.1. Establishment and Validation of PhoEVT

Previous work has shown that photocatalysts, including transition metal complexes and fluorescein derivatives, are widely used in cell surface photocatalytic proximity labeling to enable the identification of antigen‐specific cells [12, 13]. Notably, ideal photocatalysts for EV protein tracking should possess not only high catalytic efficiency and biocompatibility but also minimize nonspecific labeling of recipient cells. Aiming to develop the PhoEVT system, we employed different strategies to label EVs and cell lysate proteins to validate the technical feasibility and evaluate the potential false‐positive background. Following a systematic screening of existing biocompatible photocatalysts, Ru(bpy)₃ ²⁺ (RU) was selected for tracking EV‐associated proteins based on its labeling efficiency. RU exhibited stronger labeling intensity than the negative control in SA‐HRP blotting (Figure S1A,C). Moreover, it showed nearly undetectable in‐gel fluorescence, in contrast to other tested photocatalysts, such as DBF (Figure S1B). The candidate HMME showed labeling efficiency and low in‐gel fluorescence comparable to those of RU yet was ultimately excluded owing to its previously reported potential cytotoxicity. These results demonstrate the capacity of RU to generate a robust labeling signal while reducing potential contributions from nonspecific background signals in subsequent experiments. After identifying a suitable photocatalyst, we established the PhoEVT system as outlined in the schematic diagram (Scheme 1). The cell supernatant was collected after 24 h of culture in an EV‐free medium. During the ultracentrifugation step, the RU photocatalyst was introduced. The purified RU‐labeled EVs were then mixed with the labeling probe biotin‐aniline (BA), followed by photoactivation to complete the labeling process (Figure 1A). After photoactivation, excess photocatalyst and probe were removed before recipient cell incubation to minimize nonspecific labeling. The labeled EV samples were subsequently used for recipient cell incubation and downstream validation experiments.

SCHEME 1.

Workflow of Photocatalytic Extracellular Vesicles protein Tracking (PhoEVT) system.

FIGURE 1.

Establishment and validation of the PhoEVT system for proximity labeling of EV‐associated proteins. (A) Schematic illustration of EV‐associated protein labeling via the PhoEVT system. (B) SA‐HRP blotting of EVs derived from HEK293T cells labeled with the indicated photocatalysts including RU, DBF (4′,5′‐dibromofluorescein). EV loading was assessed by blotting for the marker ALIX. (C) Nanoparticle tracking analysis (NTA) displaying the size distribution of HEK293T cell‐derived EVs with or without RU labeling. (D) Mean size measurement of HEK293T cell‐derived EVs with or without RU labeling. Data are presented as mean ± SEM from three independent EV preparations. Each dot represents one biological replicate. Statistical significance was determined using an unpaired two‐tailed Student’s t‐test. (E) Western blotting characterized the marker protein expression in HEK293T cell‐derived EVs with or without RU labeling and HEK293T cells. (F) Transmission electron microscopy (TEM) results of HEK293T cell‐derived EVs. The red asterisk indicates the intact membrane structure of EVs. Scale bars, 50 nm. Blotting and TEM data are representative of at least three independent experiments with similar results.

To systematically optimize the photocatalytic labeling system for EV‐associated proteins, we evaluated a matrix of labeling conditions. We varied key parameters including the concentration of the photocatalyst, the concentration of the BA labeling probe, and the duration of photooxidation (Figure 1B). Labeling efficiency was evaluated by streptavidin‐HRP (SA‐HRP) blotting to detect biotinylated EV‐associated proteins. RU generated strong biotinylation signals at both 10 and 20 μM, comparable to those achieved with DBF, confirming its efficacy as a photocatalyst. Extension of the photo‐oxidation time from 5 to 20 min led to a time‐dependent increase in labeling intensity at 10 μM RU, whereas the strongest signal at 20 μM RU was observed after 10 min. In contrast, increasing the concentration of BA from 1 to 3 mM only marginally enhanced the signal intensity, indicating that probe concentration is not a major limiting factor under these conditions. Similarly, raising the RU concentration from 10 to 20 μM resulted in only a modest improvement in labeling. Based on these findings, 10 μM RU, 1 mM BA, and 20 min of photooxidation were selected as the optimal labeling conditions for subsequent experiments, providing a balance between high efficiency and minimal reagent usage.

To assess whether the RU labeling strategy impacts the properties of the EVs, we isolated EVs from the conditioned medium of HEK293T cells by differential centrifugation. As shown by nanoparticle tracking analysis (NTA), the particle sizes of the EVs ranged between 30 and 200 nm, and the mean size was approximately 150 nm (Figure 1C,D). The sample concentration was calculated by NTA and achieved a final concentration of 10¹⁰ particles/mL. Western blotting analysis of marker proteins in the EVs showed that CD9 and ALIX were enriched in EVs compared with cells, while GAPDH and GM130 in the EVs were below the detection limit (Figure 1E). The transmission electron microscopy (TEM) results of RU‐labeled EVs showed a prominent intact lipid bilayer structure (Figure 1F). These results demonstrate that the incorporation of photocatalyst RU did not have a substantial effect on the fundamental attributes of EVs in our study.

2.2. PhoEVT Enables Proximity Labeling to Track the EV Internalization Process

Since internalization of EVs into recipient cells is a spontaneous and time‐dependent process, we added the labeled EVs to recipient cells at a cell‐to‐EV ratio of 1:10,000 [14]. If the labeled EVs remained continuously present in the recipient cell culture medium, we would only be able to observe the ongoing internalization process across different time points without capturing distinct temporal phases. To model the progression from EV secretion to uptake in recipient cells and capture time‐dependent protein sorting, we pulsed recipient cells with RU‐labeled EVs for 2 h before replacing the medium with fresh EV‐free medium. The washout approach allowed us to monitor internalization dynamics without continuous exposure, thereby enabling clearer resolution of temporal uptake patterns and recipient cell processing of EV‐associated proteins. We then performed immunofluorescence imaging over a time course of 2‍–‍24 h. This approach enabled us to monitor the amount of labeled EV‐associated protein signals detected in recipient cells at specific time points, reflecting the uptake dynamics after the initial pulse of EV incubation.

To validate the fidelity of PhoEVT in tracking EV internalization and to ensure that the labeling strategy does not perturb the biological properties of EVs, we performed a dual‐labeling experiment. EVs derived from CD9‐mCherry‐overexpressing HEK293T cells were subjected to photocatalytic labeling and incubated with recipient cells. As shown in Figure 2A, the streptavidin signal exhibited high colocalization with the genetic CD9‐mCherry signal throughout the internalization process. This supports that PhoEVT labels EV‐associated signals in a manner consistent with EV markers. Crucially, to rule out potential artifacts induced by the chemical labeling procedure, we compared the uptake dynamics of these dual‐labeled EVs with nonlabeled CD9‐mCherry controls (Figure S2A). The temporal patterns of cellular entry and intracellular distribution were similar between the two groups. Collectively, these results demonstrate that PhoEVT provides visualization of EV trafficking without detectably compromising EV integrity or altering their uptake patterns.

FIGURE 2.

Temporal detection of EV‐associated proteins in recipient cells using PhoEVT. (A) Confocal images showing the temporal changes in the internalization of PhoEVT‐labeled, CD9‐mCherry‐overexpressing EVs into recipient cells. Blue, green, red and purple indicate DAPI, GLUT1, CD9‐mCherry, and Streptavidin, respectively. +BL represents blue light activation. Images are representative of three independent experiments. Scale bars, 10 μm. (B) SA‐HRP blotting of recipient cell lysates after incubation with labeled EVs derived from HEK293T cells. The level of recipient cell lysate loading was determined by western blotting for the cytosolic marker GAPDH. SA‐HRP blotting data are representative of three independent biological replicates.

As shown in Figures 2A and S2B, labeled EVs exhibited stronger streptavidin signals within recipient cells stained with an anti‐GLUT1 antibody, compared to the no‐light negative control. The streptavidin signal appeared as discrete puncta or clustered aggregates dispersed throughout the cytoplasm. Within the first 2 h after EV addition, multiple fluorescent puncta and large aggregates were observed in recipient cells, a pattern that persisted throughout 6 h. By 12 and 24 h, however, both the number of fluorescent puncta and the presence of large aggregates markedly decreased within the same field of view. Furthermore, the signal became more diffuse and predominantly localized as individual puncta within the cytoplasm, suggesting that EV‐associated protein signals may undergo intracellular processing, degradation, or redistribution over time.

To further validate the temporal dynamics observed by immunofluorescence imaging, we employed the more sensitive SA‍‐‍HRP blotting assay over an extended time course. The results demonstrated detectable biotinylated signals in recipient cells across time points ranging from 2 to 30 h under the same cell‐to‐EV ratio conditions, confirming the applicability of our labeling strategy for long‐term EV tracking. A time‐dependent decrease in biotinylation signal intensity was observed, with the strongest signal occurring at the 2 h time point. A faint yet discernible signal persisted even at 24 h, suggesting gradual degradation, redistribution, recycling, or export of EV‐associated protein signals by recipient cells over time. Importantly, all light‐induced labeling groups exhibited stronger signals than the no‐light negative control (Figure 2B). Based on these observations, we selected the 2 and 24 h time points for subsequent mass spectrometry‐based proteomic analysis. This approach allows the identification of EV‐associated proteins detected in recipient cells and facilitates the exploration of EV‐associated protein dynamics with a higher temporal resolution.

2.3. Proteomic Validation of EV‐Associated Proteins Using PhoEVT

To establish a more physiologically relevant model and better capture EV‐mediated protein interactions, we tested a variety of EV donor and recipient cell pairs, including human and murine cells as well as immortalized and primary cells. After treating the recipient cells with RU‐labeled EVs, we harvested the cells at two time points (2 and 24 h) and evaluated the labeling efficiency via SA‐HRP blotting. The HEK293T‐to‐HEK293T pairing was included as a platform validation model, whereas the tumor‐to‐immune cell pairings were included to evaluate PhoEVT in a biologically relevant context.

As shown in Figure S3, biotinylated EV‐associated proteins were successfully detected in all recipient cell types following labeled EV incubation, supporting the adaptability and applicability of the PhoEVT system across diverse biological systems, encompassing both human and murine EV subtypes and recipient cells. This approach provides a platform for comparing EV‐associated protein signal detection across different donor–recipient cell pairings. We evaluated the uptake and retention of RU‐labeled EV‐associated proteins across multiple donor–recipient cell pairings. Strong biotinylation signals were readily detected at 2 h in the HEK293T‐to‐HEK293T pairing, though the signal intensity was considerably reduced by 24 h (Figure S3A). Similarly, in the MC38‐to‐BMDM pairing, a pronounced signal was observed at 2 h that diminished by 24 h (Figure S3B). An analogous trend was observed between MC38 cell‐derived EVs and the immortalized macrophage RAW264.7 recipient cell line (Figure S3C). In the B16F10‐to‐BMDM pairing, a strong signal was present at 2 h and remained readily detectable at 24 h (Figure S3D). A comparable persistence of labeled EVs was also seen in the interaction between B16F10 cell‐derived EVs and RAW264.7 recipient cells (Figure S3E). Conversely, the HeLa‐to‐HeLa pairing exhibited limited EV‐associated protein signal detection in recipient cells at either of the two selected time points (Figure S3F). The differences in EV‐associated protein signal detection across these pairings suggest that internalization is likely driven by multifactorial elements, including cell‐type‐specific endocytic capacities, differing basal cellular states, and variations in the EV surface and cargo composition. To evaluate the PhoEVT system within a more physiologically relevant context, we focused on tumor‐to‐immune cell interactions. These results demonstrate that B16F10 cell‐derived EV‐associated protein signals exhibit enhanced detection and prolonged persistence within immune cells in the tested pairings under these conditions. Based on these observations, we selected the B16F10‐to‐immune cell models for subsequent proteomic preparation and mass spectrometry analysis.

We compared untreated recipient cells (0 h control group) with those incubated with RU‐labeled B16F10 cell‐derived EVs and collected at 2 h to assess whether our labeling strategy successfully identified EV‐associated proteins originating from EV preparations. Here, we utilized an optimized Spintip streptavidin‐mediated affinity purification followed by mass spectrometry, which was designed to reduce the loss of EV‐associated proteins and improve the yield of detectable EV‐associated protein signals. We performed proteomic analysis of biotinylated proteins enriched from the recipient RAW264.7 or BMDM cells from different groups via liquid chromatography and tandem mass spectrometry (LC‐MS/MS). For proteomic comparisons, proteins were prioritized based on reproducible detection across biological replicates together with statistical significance. Unless otherwise indicated, enriched candidates were defined as proteins with Ratio  > 1.5 and p < 0.05, as described in the Materials and Methods.

A total of 350 and 417 biotinylated EV‐associated proteins were identified in the recipient RAW264.7 cells and BMDMs, respectively, following a 2 h incubation with RU‐labeled EVs (Figure 3A). Quantitative analysis indicated that 103 out of the 350 proteins associated with the EVs had increased (ratio > 1.5, p < 0.05) ion intensity after 2 h of labeled EV incubation in RAW264.7 cells, whereas 205 of the 417 proteins exhibited a comparable increase (ratio > 1.5, p < 0.05) in BMDMs (Figure 3B,C). These results demonstrate differential detection and enrichment patterns of EV‐associated protein signals in distinct immune cells under identical incubation conditions and with EVs from the same source. Gene Ontology (GO) analysis showed that translation and ribosome biogenesis were enriched in recipient RAW cells after 2 h of incubation with B16F10 cell‐derived EVs (Figure 3D), whereas cytoplasmic translation was enriched in the 2 h B16F10 cell‐derived EV incubation recipient BMDMs (Figure 3E). These enrichment patterns suggest that distinct recipient immune cell types may differentially process EV‐associated proteins, potentially reflecting differences in their cellular states.

FIGURE 3.

Proteomic validation of EV‐associated proteins using PhoEVT. (A) Table of EV‐associated proteins identified in two distinct cell pairings. (B) Volcano plot of upregulated (red) and downregulated (blue) proteins of recipient RAW264.7 cells incubated with B16F10 cell‐derived EVs for 2 h. (C) Volcano plot of upregulated (red) and downregulated (blue) proteins of recipient BMDMs incubated with B16F10 cell‐derived EVs for 2 h. (D) Gene ontology (GO) enrichment of upregulated proteins in recipient RAW264.7 cells incubated with B16F10 cell‐derived EVs for 2 h. The top 20 most significant enrichment GO terms are shown here. Bubble color denotes enrichment significance as −log 10 (p value), redder color indicates higher significance with a smaller p value. The size of bubbles represents the number of proteins in each term. (E) Gene ontology (GO) enrichment of upregulated proteins in recipient BMDMs incubated with B16F10 cell‐derived EVs for 2 h. The top 20 most significant enrichment GO terms are shown here. Bubble color denotes enrichment significance as −log 10 (p value), redder color indicates higher significance with a smaller p value. The size of bubbles represents the number of proteins in each term. Significantly enriched proteins were defined as proteins quantified reproducibly across replicates with a ratio > 1.5 and p < 0.05 unless otherwise indicated.

Of the total proteins identified, 207 overlapping proteins were detected between the two different cell pairings (Figure S4A). When further filtered with a threshold of Ratio > 1.5 and p value < 0.05 at the 2 h time point, 47 significantly upregulated proteins were found to be common to both cell types (Figure S4B). Gene Ontology (GO) analysis of these overlapping proteins revealed significant enrichment for cytoplasmic translation (Figure S4C). These results suggest that EV‐associated protein signals are linked to protein synthesis‐related pathways in recipient immune cells under these conditions. Based on the detection of ribosomal proteins and translation factors, tumor EV‐associated protein signals may be linked to changes in immune cells within the tumor microenvironment, including pathways related to protein secretion and metabolic activity [1, 15, 16, 17, 18].

2.4. Long‐Term Tracking of PhoEVT in Recipient Cells

To further evaluate the capability of the PhoEVT system for long‐term EV‐associated protein tracking, we analyzed the 24 h group using the identical experimental procedure and analysis strategy as that applied for the 2 h group. We compared the ratio values derived from mass spectrometry data at 2 and 24 h against the corresponding 0 h control across multiple cellular pairings. This comparison yielded average 2/24 h ratios for each cell pairing. Most labeled EV‐associated proteins detected at 24 h displayed reduced ratios relative to the 2 h time point, reflecting potential differences in intracellular processing dynamics, including lysosomal trafficking, recycling, or export from recipient cells over time. Although many proteins showed no statistical significance (p > 0.05), which may indicate differences in recycling and degradation of proteins, we identified a subset of labeled EV‐associated proteins with 2/24 h ratios between 0.9 and 1.0 that were statistically significant (p < 0.05) (Figure 4A,B). Among these, 5 proteins in RAW264.7 cells and 12 proteins in BMDM cells showed sustained detection in recipient cells (Table S1A,B). These persistent proteins play roles in the core cellular metabolism and fundamental processes. The ribosomal proteins Rpl19, Rps13, and ubiquitin‐ribosomal fusion protein Uba52 enriched in BMDMs are core components of the protein synthesis machinery [19, 20, 21]. This is complemented by the persistence of the eukaryotic translation initiation factor 1A in RAW264.7 cells. Based on protein annotation and pathway association, and as a hypothesis‐generating interpretation, the sustained presence of these proteins suggests that tumor‐derived EVs may be associated with the maintenance or enhancement of protein synthesis‐related capacity in recipient macrophages over an extended period, thereby supporting their potential involvement in pro‐tumorigenic secretory functions [22, 23, 24]. Because macrophage activation and secretory phenotypes require coordinated protein synthesis, the persistence of these translation‐related EV‐associated protein signals may indicate a possible link between tumor EV uptake and translational state changes in recipient macrophages. Furthermore, we detected methylcrotonoyl‐CoA carboxylase 1 in both cell pairings and propionyl‐CoA carboxylase alpha chain specifically in BMDMs. These enzymes are critical for mitochondrial branched‐chain amino acid metabolism [16, 25]. Because amino acid metabolism is closely linked to macrophage activation and bioenergetic remodeling, the persistence of these enzymes may suggest a possible association with metabolic state changes in macrophages. As a representative validation, a limited but detectable MCCC1‐EGFP signal was observed in recipient HEK293T cells after incubation with EVs derived from MCCC1‐EGFP‐expressing donor cells (Figure S5). The weak signal likely reflects the limited abundance of MCCC1‐EGFP in EVs and the partial uptake of donor‐cell‐derived EVs by recipient cells. As a critical adaptor linking the actin cytoskeleton to focal adhesions, the persistence of Vinculin in RAW264.7 cells may suggest a possible connection between tumor EV‐associated protein signals and macrophage adhesion or migratory behavior [26, 27, 28, 29]. While our data demonstrate the temporal persistence and differential enrichment of these EV‐associated proteins, they do not definitively prove their direct biological function. The observed long‐term detection could alternatively reflect their retention in endosomal compartments, recycling, or re‐secretion. The identification of persistently retained proteins reveals the utility of the PhoEVT system in long‐term EV‐associated protein tracking and provides a basis for further investigating how EV‐associated protein dynamics may be linked to changes in recipient macrophages.

FIGURE 4.

Long‐term tracking of PhoEVT in recipient cells. (A) Scatter plot showing the 2/24 h ratio of labeled B16F10 cell‐derived EV‐associated proteins in recipient RAW264.7 cells. Points are categorized by color and shape; red squares represent features with persistent detection and green triangles represent features with statistically significant persistent detection. The dashed line indicates the p = 0.05 significance threshold. (B) Scatter plot showing the 2/24 h ratio of labeled B16F10 cell‐derived EV‐associated proteins in recipient BMDMs. Points are categorized by color and shape; red squares represent features with persistent detection and green triangles represent features with statistically significant persistent detection. The dashed line indicates the p = 0.05 significance threshold. Long‐term persistence analysis was performed using the same biological replicate structure and statistical workflow as the previous proteomic analysis. Proteins with statistically significant 2/24 h ratios were used to define persistently detected EV‐associated protein signals.

3. Conclusion

Extracellular vesicle research has increasingly focused on understanding EV uptake specificity and the downstream consequences in recipient cells. Most available tools require genetic modification of donor or recipient cells, limiting their use in EV studies. However, proximity labeling techniques have transformed our ability to study protein interactions. The emergence of photocatalytic systems offers a promising alternative by enabling nongenetic and spatiotemporally precise protein labeling. In this study, we employed a RU‐based photocatalytic labeling strategy to trace accessible EV‐associated protein signals without genetic manipulation.

The PhoEVT system we developed enables the labeling and tracking of EV‐associated proteins. It is expected to capture surface exposed or membrane proximal EV‐associated proteins that are accessible to photocatalyst‐mediated singlet oxygen generation and biotin‐aniline tagging. This system allows not only for the in situ observation of EV‐associated protein signals detected in recipient cells over extended periods but also for the detection of changes in the abundance of these proteins through Spintip‐based enrichment followed by mass spectrometry. We applied the system to investigate the proteomic profiling of tumor cell‐derived EV‐associated proteins detected in immune cells. Our results identified hundreds of biotinylated EV‐associated proteins in recipient macrophages, providing evidence for their detection and intracellular presence. Notably, we observed that the same population of EVs was processed differently by the distinct immune cell types. The differences observed among donor–recipient pairings may reflect the combined outcome of donor cell‐dependent EV properties and recipient cell‐dependent uptake or processing capacity. This suggests a potential association between the recipient cell state and the differential handling of EV‐associated protein signals. Furthermore, the temporal tracking capability of the PhoEVT system allowed us to distinguish different types of EV‐associated protein signals based on their persistence. The identification of a subset of proteins that persisted in recipient cells for up to 24 h points to their distinct intracellular stabilities, generating hypotheses regarding the potential role of these molecules. For example, the persistence of translation‐related proteins and metabolic enzymes may indicate possible links between tumor EV‐associated protein signals and macrophage protein synthesis or metabolic states, which can be further examined through targeted validation. More importantly, the favorable biocompatibility of the PhoEVT system provides a robust platform to investigate EV‐associated protein dynamics within the tumor microenvironment or other complex biological systems.

The PhoEVT system also has certain limitations. Although the system allows us to trace the journey of EVs from their release to uptake by recipient cells, our current data do not directly demonstrate the cytosolic release or biological activity of these proteins. The complete intracellular trafficking routes post‐uptake, including potential outcomes such as endosomal retention, recycling, or re‐secretion, as well as the specific functional roles of these EV‐associated proteins within recipient cells, remain to be fully elucidated in future investigations. Because PhoEVT relies on singlet oxygen generation, oxidative modifications or photodamage to EV‐associated proteins cannot be fully excluded. Furthermore, endogenous biotinylated proteins and nonspecific binding to streptavidin beads may contribute to background signals. During the pulldown of labeled proteins from recipient cells, nonspecific enrichment may contribute to false‐positive candidates. Therefore, the specificity of PhoEVT depends not only on the labeling chemistry but also on appropriate experimental controls and data filtering. Future studies will be required to directly test whether these EV‐associated proteins exert functional activity in recipient cells and to validate candidates using targeted approaches.

Funding

This study was supported by the National Natural Science Foundation of China (22137004, 82430109, and 22541704), the Noncommunicable Chronic Diseases‐National Science and Technology Major Project (2023ZD0501500), and the National Key Research and Development Program of China (2023YFC3605400).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supplementary Material

Yan Shuai‐Ting, Liu Yi‐Ting, Zhang Ying, Qin Wei, Yin Hang, Spatiotemporally Resolved Tracking of Extracellular Vesicle Cargo via Photocatalytic Extracellular Vesicles Protien Tracking (PhoEVT), ChemBioChem 2026, 27, e70515. 10.1002/cbic.70515

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.