Tandem Enzymatic Swarm Communication Enables Collective Nanobot Therapy in Inflammatory Bowel Disease

Tandem Enzymatic Swarm Communication Enables Collective Nanobot Therapy in Inflammatory Bowel Disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Tandem Enzymatic Swarm Communication Enables Collective Nanobot Therapy in Inflammatory Bowel Disease Sei Kwang Hahn, Hyunsik Choi, Yewon Seo, Jiwoong Kim, Hyunseo Jeon, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7461471/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Collective motion is a defining feature of living systems in nature, but has been challenging to reproduce in synthetic swarming systems. Here, we report a tandem enzymatic communication system between glucose oxidase and catalase-powered nanobot swarms for the treatment of inflammatory bowel disease (IBD). We verify in vitro coordinated swarm behavior produced by coupling propulsion through an enzymatic cascade in microchips. After intrarectal injection in mice, the collective behavior of swarms is assessed in the context of peristalsis using photoacoustic imaging, demonstrating the effective navigation of swarms within the colon. In addition, we confirm the remarkable recovery of the damaged colon, characterized by comparable levels of proinflammatory cytokines and enhanced anti-inflammatory cytokines, in both prevention and delayed treatment regimens in IBD model mice. Taken together, the tandem communication system would be harnessed as a next-generation platform for various intractable diseases, including colorectal diseases. Biological sciences/Biotechnology/Nanobiotechnology Biological sciences/Biotechnology/Biomaterials Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Collective behavior is a common phenomenon in nature. Each organism interacts with its surroundings and other individuals, and these interactions collectively display complex and intelligent behavior without requiring centralized control 1,2,3,4,5 . Inspired by nature, synthetic micro/nanobot (MNB) swarming systems have been proposed, including MNBs actuated by magnetic fields 6,7 , light 8,9 , ultrasound 10,11 , and electric fields 12,13 , as well as chemically-driven MNBs 14,15 and biohybrid MNBs 16,17 . Unlike a single unit, these synthetic swarms can address many tasks such as cargo delivery, analyte capture, and purification for biomedical applications. Recently, various enzymatic swarms have exhibited complex and intriguing coordinated behaviors, such as enhanced coverage, penetration, and convection currents, through a single enzymatic reaction within a swarm 18,19,20,21,22,23,24 . Although enzymatic swarm systems have been achieved, interactions between different enzymatic swarms have not been realized, where they can receive chemical signals from each other and potentially modify their swimming dynamics, leading to the emergent reminiscent behaviors of biological systems. In natural systems, communication between distinct populations through chemical gradients or molecular feedback is essential for collective decision-making and efficient function. Mimicking this level of interaction would enable synthetic MNBs to organize, adapt, and perform complex therapeutic tasks 25,26 . Inflammatory bowel disease (IBD) refers to a group of chronic inflammatory conditions of the gastrointestinal (GI) tract, including Crohn's disease and ulcerative colitis 27,28,29 . Damage to the intestinal barrier, hypoxic condition, and oxidative stress are known to make IBD treatment more complicated 30,31,32,33 . Although numerous oral and rectal medications have been commercially developed to alleviate hypoxic conditions and oxidative stress, their efficacy is limited by poor retention in the gut and rapid clearance through peristalsis. Accordingly, there is a strong clinical unmet need to actively scavenge ROS and deliver oxygen in the intestine for effective IBD treatment. Here, we develop a tandem communication system between glucose oxidase (GOx) and catalase (CAT) nanobots (NBs) for IBD treatment. This design introduces inter-swarm signaling as a principle to engineer nanobot collectives with emergent, systemic-like behaviors. After injection of swarms through the rectum, tandem communication repeats, allowing them to navigate actively against peristaltic flow and remain at inflamed sites. Finally, enzymatic swarms exhibit a significant therapeutic effect on IBD-induced mice, enabling ROS scavenging and oxygen delivery to alleviate hypoxic conditions and inflammatory responses in the colon. Collective behavior of swarms Fig. 1a shows a schematic illustration of the systemically linked swarming communication between GOx NBs and CAT NBs for IBD treatment: (1) GOx NBs and CAT NBs with glucose are injected in the colon; (2) GOx NBs collectively decompose glucose, generating an H₂O₂ gradient, and CAT NBs chemotactically respond to this gradient and decompose H₂O₂, releasing oxygen; (3) the released oxygen is subsequently used by GOx NBs to sustain glucose decomposition. These nanobots consist of mesoporous silica nanoparticles (MSNs) functionalized with surface-immobilized enzymes of GOx and CAT. The detailed characterization is provided in Supplementary Fig. 1–4. The molecularly asymmetric distribution of enzymes on the surface of MSNs provided sufficient driving force for the enzymatic nanobots via bio-catalytic conversion 34,35 and the generation of chemical gradients 36 . As shown in Supplementary Fig. 5 and 6, we calculated the mean squared displacement (MSD) based on the trajectory data, which reveals a linear increase over time, characteristic of enhanced diffusion of nanoparticles. To study in vitro dynamics and collective behavior of GOx and CAT NBs, we added a droplet of nanobots to a PBS solution containing 0, 50, 100, and 250 mM of fuels (i.e., glucose, H 2 O 2 ) (Supplementary Movies 1 and 2). In the presence of glucose and H 2 O 2 , nanobot swarms rapidly expanded, forming vigorous fronts and three-dimensional (3D) vortices (Fig. 1b, Supplementary Fig. 7 and 8). In contrast, without fuels, swarms quickly sedimented, showing a two-dimensional (2D) dispersion pattern. Swarm coverage was quantified from the density map per video frame, revealing expansion profiles that increased with fuel concentration (Fig. 1c and d). Particle image velocimetry analysis further confirmed the previously observed behaviors. In the absence of fuels, swarm velocities were low and disappeared within 40 s (Fig. 1e, Supplementary Fig. 9 and 10). Chemotaxis behavior of swarms We assessed the chemotaxis behavior of CAT NBs attracted by the GOx NBs (Fig. 2a). To achieve this, we designed a non-flow agar gel-based microfluidic chip (Supplementary Fig. 11) that minimized bulk flow effects, thereby establishing a controlled gradient. The device consisted of three channels, enabling a chemical gradient to be precisely induced in the middle channel by adding chemicals at side channels (Fig. 2b and Supplementary Fig. 12). Using this setup, we verified the chemotaxis behavior of CAT NBs by adding H 2 O 2 to the left channel, fluorescein isothiocyanate labelled CAT NBs in the middle channel and DI water in the right channel, respectively (Fig. 2c). Swarms in the middle channel initially presented a droplet shaped dispersion for the first 30 s. After that, a tail of swarm emerged at 40 s and gradually extended toward the left side of the middle channel, where the concentration of H 2 O 2 was higher. After 10 min, the swarm was completely biased toward the left side (Fig. 2d). As a control, we injected glucose into the left channel, which resulted in no bias (Fig. 2e and f). These results confirmed that CAT NBs were selectively attracted by the gradient of H 2 O 2 . We further investigated their chemotaxis behavior as a function of H 2 O 2 concentration.Detailed characterization and discussion can be found in Supplementary Information (Supplementary Fig. 13) After confirming positive chemotaxis towards gradients of H 2 O 2 , we directly demonstrated the interaction between GOx and CAT NBs (Fig. 2g, h and Supplementary Movie 3). In the left channel, GOx NBs and glucose were introduced to generate H 2 O 2 .After 40 s, CAT NBs in the middle channel were gradually distorted and started to migrate toward the left side. Within 10 min, the swarm was completely biased in that direction (Fig. 2h and i). To further quantify the chemotaxis of swarms, we converted the swarm distribution in the middle channel into a density map (Fig. 2j). The bright region along the left channel was gradually expanded from the bottom upwards, reaching almost 100% within 180 s (Fig. 2k), confirming that CAT NBs exhibited positive chemotaxis toward GOx NBs in the presence of glucose. Swarming communication between swarms We investigated the effect of oxygen on the navigation of GOx NBs by adjusting the oxygen supply with or without an oxygen scavenger (i.e., sodium sulfite) (Fig. 3a and b). Dissolved oxygen (DO) profile showed that the oxygen scavenger depleted DO much faster than the control, revealing that it consumed oxygen before it reached GOx NBs (Fig. 3c). To confirm the navigation of swarms, we designed intestine-shaped microchannel (Supplementary Fig. 14). After addition of the oxygen scavenger in the microchannel, swarms showed limited navigation in the microchannel due to the depletion of oxygen (Fig. 3d). In contrast, swarms navigated efficiently without the oxygen scavenger (Fig. 3e). The corresponding velocity and navigation length also decreased significantly in the presence of the oxygen scavenger, demonstrating the importance of oxygen supply to GOx NBs (Fig. 3f,g). Next, we verified the swarming communication between the swarms in the mixture of GOx and CAT NBs. We hypothesized three types of collective behaviors in the presence of glucose, including (1) the propulsion of the GOx NBs by the decomposition of glucose, (2) the chemotaxis of CAT NBs by the gradient of H 2 O 2, and (3) the boosting of GOx NBs through oxygen supply (Fig. 3h). We tagged each swarm with fluorescence dyes and measured the velocity of each swarm in the microchannel for 230 s (Fig. 3i,j). During the first 60 s, GOx NBs gradually overtook CAT NBs, because glucose decomposition dominated. After 60 s, the reaction was saturated and the CAT NBs accelerated towards GOx NBs with a higher velocity, indicating the dominant chemotaxis reaction. After 130 s, the velocity of GOx NBs increased and the distance from CAT NBs increased due to oxygen boosting in the glucose solution. After 160 s, CAT NBs again showed stronger chemotaxis, moving faster than GOx NBs. We observed two chemotactic cycles within 230 s of swarm communication. After that, we compared the navigation efficiency with a single swarm as shown in Supplementary Information (Supplementary Fig. 15 and 16). In vivo collective behavior of swarms We optimized the ratio of swarms for further in vivo experiments. Detailed characterization and discussion can be found in Supplementary information (Supplementary Fig. 17-19). With the optimized ratio of swarms, we further studied in vivo collective behavior of swarms in an intestine after intrarectal instillation. After enema with DI water, the fluorescently labelled swarms were injected with and without glucose (Fig. 4a). After 30 min, colon was excised from the mice to observe the navigation of swarms in the colon by IVIS imaging (Fig. 4b). At 250 mM of glucose, the swarms navigated along the colon with an average length of 5.95 cm, indicating the fast navigation within 30 min. In contrast, the swarms without glucose were hardly navigated in the colon and even seemed to be cleared from the colon (Fig. 4c). To monitor the swarms in real-time, we labelled the swarms with near-infrared indocyanine for photoacoustic (PA) imaging. PA imaging has recently been proposed as an emerging modality for the fast tracking of MNBs 37,38,39,40 . In the near-infrared wavelength range, PA imaging was capable of entirely noninvasive monitoring with a high contrast and a high spatiotemporal resolution 41,42,43 . We removed the residual fecal matter with an enema to empty the colon before intrarectal instillation, thereby controlling the glucose concentration precisely (0 and 250 mM). At 3 min intervals for 30 min, we monitored the abdomen of mice after intrarectal instillation of ICG-labelled swarms, both without (Fig. 4d and Supplementary Fig. 20) and with glucose (Fig. 4e and Supplementary Fig. 21). After coding by depth, we divided the colon into two parts from the rectum to the cecum. Without glucose, we observed a PA signal in the first region of interest (ROI) for 9 min. However, the signal was pushed toward the rectum at 12 min and completely disappeared within 15 min in corresponding to the IVIS imaging. This phenomenon may be attributed to the fact that the swarms were cleared from the intestine by the peristaltic movement of the GI tract. However, with glucose, the PA signal in the first ROI was maintained and the PA signal in the second ROI increased in strength over 30 min, demonstrating that the swarms were navigated efficiently against the peristalsis movement of the GI tract. These observations were further confirmed by analyzing the PA signal in the first ROI (Fig. 4f). After that, we verified the retention of swarms in the colon for 6 h (Supplementary Fig. 22). Most regions of the colon were covered by the swarms without clearance for 1 h, indicating efficient reflux behavior of swarms in colon. For 6 h, considerable fluorescence intensity of swarms was detected in the colon. Prevention and therapeutic effect on IBD The therapeutic effect of swarms in preventing colon inflammation was first assessed in model mice with dextran sulfate sodium (DSS)-induced IBD. Specifically, 3% DSS in drinking water was supplied for 6 d with twice rectal administration of PBS or swarms with and without glucose on 0 and 2 d (Fig. 5a). During the administration, we monitored a body weight (Fig. 5b) and evaluated several factors for disease activity index (DAI) daily (Fig. 5c). The weight was correlated with intestinal inflammation, affecting the digestion and nutrient absorption processes of mice. The DAI of the 3% DSS-supplied group was gradually increased during the first 5 d due to the induction of inflammation. While the DAI of other groups worsened, the DAI of the swarms with glucose group recovered, indicating that the swarms alleviated the abnormality of IBD. Compared with the swarms without glucose group, the continuous collective motion of the swarms with glucose group resulted in an enhanced distribution in the target region, leading to a more efficient treatment effect. On day 9, the mice were sacrificed for the collection and analysis of their colon tissue. Colon length correlates with inflammation, and thus severe inflammation causes shorter colons. Among the groups of DSS-induced colitis, only the swarms with glucose group predominantly maintained the colon length comparable to that of the healthy colon (Fig. 5d,e). With hematoxylin and eosin (H&E) staining (Fig. 5f), we scored histological damage in terms of several factors (Fig. 5g and Supplementary Fig. 23). The histological colonic damage caused by the oxidative stress was alleviated in the group of swarms with glucose, revealing the adequate protection of swarms against oxidative stress in colonic tissue. The more detailed examination was also performed via TUNEL assay and immunostaining analysis of HIF1-α, ZO-1 and occludin (Fig. 5h). The TUNEL assay and immunostaining analysis of HIF1- α revealed that the swarms with glucose effectively alleviated the apoptosis and hypoxic colonic cells with the area of 12.2 and 8.4%, respectively (Fig. 5i,j). HIF-1α expression is a key factor in the cellular response to hypoxia 44 . In addition, ZO-1 and occludin are two major intestinal tight junction proteins that are closely related to the integrity of the intestinal barrier 45 . The immunostaining verified that the swarms restored the disrupted colonic epithelium cell layer induced by acute IBD effectively. After that, we measured the levels of relevant proinflammatory and anti-inflammatory cytokines (IL-6, TNF-α, IL-1β, and IL-10) in the colonic tissue (Fig. 5k). The results showed the effective decrease of proinflammatory cytokines and the increase in anti-inflammatory cytokines in the group of swarms with glucose, thereby modulating the IBD symptoms. To further assess the capability of the enzymatic swarms to ameliorate inflammation in IBD, we investigated the efficacy via a delayed treatment regimen in the model mice of DSS-induced IBD with additional group (2-fold concentration of swarms) (Fig. 6a). Compared with other groups, the model mice in the swarms with glucose group showed a gentle decrease in the body weight and the relatively low DAI over 9 d, showing the moderate symptoms of IBD (Fig. 6b and c). The colonic length also verified that the swarms with glucose preserved the colon length at a comparable level to that of a healthy colon (Fig. 6d and e). Moreover, histological analysis confirmed the restoration of damaged colonic tissue, along with the alleviation of hypoxic conditions, by the enzymatic swarms with glucose (Fig. 6f, g, and Supplementary Fig. 24). Further analysis revealed the effective amelioration of apoptosis and hypoxic conditions, accompanied by the high expression of tight junction proteins in the colon tissues (Fig. 6h, i, and j). Specifically, the higher concentration of swarms exhibited more significant therapeutic efficacy in the presence of glucose, indicating concentration-dependent treatment efficacy. In addition, the high concentration of swarms showed the lowest proinflammatory cytokine levels and the highest aini-inflammatory cytokine levels compared to the other groups (Fig. 6k). The long-term safety assessment of swarms revealed that there was no significant difference of histopathology in the major organs between the PBS treated group and the swarms treated group after 7 days (Supplementary Fig. 25). Conclusion This study demonstrates, for the first time, that two distinct enzymatic nanobot swarms can communicate through a cascade reaction, producing emergent behaviors reminiscent of those found in biological collectives. Although several milestones towards biomedical applications have already been achieved, individual NMBs have not reached the complexity and autonomy of their biological counterparts 46,47,48,49 . To better mimic the biological counterparts, important key questions include how the NMBs interact with the environment, communicate with each other, and act collectively 50,51 . By linking GOx and CAT activities, we established a feedback loop in which one swarm generates a chemotactic signal, whereas the other responds and reinforces propulsion through oxygen release. This interaction transformed simple enzyme-driven motion into systemic swarm communication, providing a conceptual advance in the design of active matter. The functional consequences of this design are evident both in vitro and in vivo. In microchips, tandem swarms displayed coordinated navigation and extended motility compared to single-enzyme systems. These behaviors translated into enhanced navigation in the colon, even against peristaltic flow. Animals treated with GOx/CAT swarms showed reduced inflammation, preserved colon length, restored epithelial integrity, and a shift toward anti-inflammatory cytokine profiles under both preventive and therapeutic regimens. Remarkably, these outcomes were achieved without the use of conventional drugs, highlighting the potential of swarm-based nanomedicine as a stand-alone therapeutic approach. Beyond IBD, the principle of enzymatic swarm communication would be extended to other disorders characterized by hypoxia, oxidative stress, or localized inflammation. The modularity of the system suggests that other enzyme pairs can be engineered to respond to different metabolites, generate distinct chemical gradients, or trigger specific therapeutic actions. Such adaptability would allow nanobot collectives to address diverse GI conditions or even systemic diseases. While promising, our study also points to future challenges. The translation of swarm nanobots to the clinic will require detailed safety evaluations, long-term biodistribution studies, and scalable manufacturing of enzyme-functionalized carriers. Moreover, it will be essential to understand how swarm communication behaves in the heterogeneous environment of the human gut, including variable glucose levels, interactions between microbiota, and immune responses. Nevertheless, this work would lay the foundation for a next generation of collective nanomedicine by demonstrating that synthetic nanobot swarms can communicate, adapt, and deliver therapeutic benefit for colorectal diseases and other various intractable diseases. Methods Materials. Triethanolamine (TEOA), tetraethyl orthosilicate (TEOS), cetyltrimethylammonium bromide (CTAB), catalase (≥10,000 units mg -1 ), glucose oxidase (50KU, from Aspergillus), D-(+)-glucose, fluorescein isothiocyanate (FITC), rhodamine b isothiocyanate(RITC), 3-aminopropyltriethoxysilane (APTES), glutaraldehyde (GA) solution, ethanol, methanol, hydrochloric acid (HCl), sodium sulfite, rhodamine b, bovine serum albumin (BSA) were obtained from Sigma Aldrich (St. Louis, MO).Phosphate-buffered saline (PBS) and 4% paraformaldehyde were obtained from Tech&innovation (Korea). Alexa Fluor® 594 Occludin monoclonal antibody, Alexa Fluor® 488 ZO-1 monoclonal antibody, and mounting medium with 4’,6-diamidino-2-phenylindole (DAPI) were obtained from Thermo Fisher Scientific (Waltham, MA).Hydrogen peroxide (34.5%) (H 2 O 2 ) and xylene were obtained from SAMCHUN (Korea).Dextran sulfate sodium salt (DSS) was obtained from MP Biomedicals (Irvine, CA).Thiol-terminated polyethylene glycol amine (HS-PEG-NH 2 ) (MW 5k) was obtained from CreativePEGworks (Durham, NC). Indocyanine Green sulfo-NHS ester (ICG sulfo-NHS ester) was obtained from Shimadzu Corporation (Japan).Alexa Fluor® 488 anti-HIF-1 alpha antibody was obtained from Abcam (UK). Agarose was obtained from Georgiachem (Suwanee, GA). SYLGARD™ 184 Silicone Elastomer Kit was obtained from Dow Corning (Midland, MI). Synthesis of mesoporous silica nanoparticles . Mesoporous silica nanoparticles (MSNs) were synthesized following a sol-gel Stöber method. Briefly, 570 mg of CTAB and 35 g of TEOA were mixed in 20 mL of DI water. Then, the mixture was heated to 95 °C in a silicone oil bath under constant stirring for 30 min. TEOS (1.5 mL) was then added dropwise, followed by incubation at 95 °C for 2 h. The resulting particles were collected by centrifugation at 1350 g for 10 min and washed three times with ethanol. To remove the CTAB from the particles, the particles were suspended in 30 mL of a methanol/HCl mixture (10:0.6, v/v) and refluxed at 80 °C for 24 h. Then, the particles were collected by centrifugation (1,350 g, 10 min) and washed three times with ethanol. Synthesis of enzyme-powered nanobots . To modify the amine group, the prepared MSNs in ethanol (1 mg mL -1 ) were reacted with APTES (35 μL mL -1 ) at 70 °C for 2 h. The particles were then collected by centrifugation (1,150 g, 5 min) and washed three times with DI water. Amine-functionalized MSNs (MSNs-NH₂) were suspended in DI water (1 mg mL -1 ). 50 μL of GA solution was added, and the mixture was stirred at room temperature for 3 h. After crosslinking, the particles were collected by centrifugation (1,150 g, 5 min) and washed three times with DI water with 5 min of sonication between each wash. The resulting particles were resuspended in an enzyme solution composed of catalase (0.75 mg mL -1 ), glucose oxidase (1 mg mL -1 ), and NH₂-PEG-SH (2 μg mg -1 of MSNs) in PBS. The mixture was incubated on an end-to-end rotary shaker overnight at room temperature. The functionalized nanobots were washed three times with DI by centrifugation (1,150 g, 5 min). Characterization of enzyme-powered nanobots. The morphology and size of the synthesized nanobots were characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), zeta potential, and dynamic light scattering (DLS). For TEM analysis, a 5 μL of nanobot suspension (500 μg mL -1 in DI water) was dropped onto a carbon-coated copper grid and air-dried at room temperature for 6 h. TEM images were acquired at an accelerating voltage of 120 kV (Talos L120C, Thermo Fisher Scientific, Waltham, MA). A nanorobot solution was deposited onto a silicon wafer, dried under ambient conditions, and coated with a thin layer of gold using a sputter coater to enhance conductivity. The surface morphology and structural features of the nanobots were examined using SEM (Gemini, Carl Zeiss AG, Germany), operating at 25 kV. The hydrodynamic diameter and surface charge of the nanobots were evaluated with DLS and zeta potential analysis (Zetasizer Advance, Malvern Instruments, UK) at room temperature. To assess the surface chemistry of the nanobots, Fourier-transform infrared (FTIR) spectroscopy was conducted using an IRSpirit spectrometer equipped with a QATR-S module (Shimadzu, Japan). Surface area and porosity were determined using a Brunauer-Emmett-Teller (BET) analysis with a surface area analyzer (ASAP 2010, Micromeritics, Norcross, GA). Electron energy loss spectroscopy (EELS) was performed in conjunction with HR FE-TEM (JEM-2200FS with Image Cs Corrector, JEOL, Japan) to investigate the elemental distribution and chemical composition of the nanobots at high resolution. Quantification of immobilized enzymes on the nanobots. The concentration of catalase and glucose oxidase immobilized on the nanobots was quantified using the Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific, Waltham, MA), following the manufacturer’s protocol. A standard curve was generated using serial dilutions of bovine serum albumin (BSA, 0-2 mg mL -1 ). To remove unbound enzyme, the nanobots were centrifuged and washed three times with PBS. The enzyme-coated nanobots were resuspended in DI water and mixed with the BCA working reagent in a 96-well plate, followed by incubation at 37°C for 30 min. Absorbance was measured at 560 nm using a microplate reader (SpectraMax ABS, Molecular Devices, San Jose, CA), and protein concentration was calculated based on the BSA standard curve. Enzyme activity assay. The enzymatic activity of catalase and glucose oxidase immobilized on the nanobots was measured using Catalase Activity Assay Kit (A319666, Antibodies.com, UK) and Glucose Oxidase Activity Assay Kit (A319680, Antibodies.com, UK). Catalase activity was determined by measuring the decomposition rate of H₂O₂, while glucose oxidase activity was assessed based on the amount of H₂O₂ generated during the oxidation of glucose. Each assay was performed according to the manufacturer’s instructions. Single motion analysis of a nanobot. An inverted microscope (DMi8, Leica Microsystems, Germany) was used to observe and record the movement of nanobots. The nanobot solutions were placed on a petri dish and mixed well with glucose solution at concentrations of 0, 50, 100, and 250 mM. The movement of nanobots in a glucose solution was recorded for 120 s at a frame rate of 25 fps in bright field. The tracking path and mean-squared displacement (MSD) were automatically analyzed using Python software. Swarming behavior of nanobots. The swarming behavior of nanobots was assessed with an optical microscope equipped with a Hamamatsu high-sensitivity CCD camera. For that purpose, a petri dish was filled with 5 mL of either PBS or a glucose solution in PBS (50, 100, and 250 mM) and placed in the optical microscope. A 5 µL drop of the nanobots was then added carefully to the Petri dish, and 120-s videos were acquired at a frame rate of 25 fps. The density maps and particle image velocimetry (PIV) were obtained by using ImageJ. The expansion area was measured by converting grayscale images into binary images and subsequently summing the pixels with intensity values above a certain threshold. For PIV analysis, the video frames were converted into binary images. Then, cross-correlation analysis was performed with 64 interrogation window sizes. Fluorescent labeling of nanobots . For fluorescence labeling, FITC was used for glucose oxidase-based nanobots, and RITC was used for catalase-based nanobots. Dye solutions (0.5 mg mL -1 in DI water) were added to 1 mg of nanobots, respectively. The mixtures were incubated on an end-to-end rotary shaker in the dark at room temperature for 2 h. The labelled nanobots were washed three times with DI water, and the final particles were collected by centrifugation at 1,150 g for 5 min. Chemotaxis test in a microchip. A custom-designed three-channel fluidic mold was fabricated using a 3D printer (MakerBot SKETCH standard, MakerBot, Brooklyn, NY) to simulate a directional chemical gradient environment. The mold was printed using PLA filament and had final dimensions of 72 × 30 × 13 mm. This mold was used to cast an agarose-based fluidic system by pouring a 1% (w/v) agarose solution into a 6 cm Petri dish and allowing it to solidify at 4 °C for 1 h. The side channels of the three-lane fluidic system were filled with GOx nanobots in glucose and DI, and the central channel was filled with only DI. FITC-labelled catalase nanobots (2 μL) were introduced into the central channel. To evaluate the chemotactic behavior of catalase nanobots in response to an H₂O₂ gradient, three experimental conditions were tested: (1) glucose + GOx nanobot, (2) DI + GOx nanobot, (3) H₂O₂ solution. Their displacement was monitored using an optical microscope with an external fluorescence light source (EL6000, Leica Microsystems, Germany). Navigation test in a microchannel. A fluidic mold was fabricated using a 3D printer with dimensions of 17 × 12 × 6 mm. The mold was designed to mimic the convoluted geometry of the intestinal tract. Using this mold, a PDMS-based fluidic system was fabricated. PDMS prepolymer was prepared by mixing the base and curing agent at a 10:1 ratio (w/w). The mixture was then poured over the mold and cured at 70 °C for 4 h. After curing, the PDMS was peeled off and treated with ozone plasma for 15 min to increase surface hydrophilicity. The resulting PDMS fluidic channel was filled with either glucose solution (50 mM) or DI water. A 5 μL drop of FITC-labelled nanobot solution (1 mg mL -1 ) was introduced into the inlet, and the directional motion of nanobots was observed under an optical microscope. The displacement of the nanobots was measured to assess motility under different chemical environments. Oxygen scavenging test. The motility of nanobots was evaluated in a PDMS-based fluidic channel filled with 50 mM glucose solution. A 5 μL drop of FITC-labelled nanobot solution (1 mg mL -1 ) was introduced at the inlet of the channel, and their displacement was monitored using an optical microscope with an external fluorescence light source for FITC and RITC excitation. To assess oxygen dependency, an oxygen scavenger, sodium sulfite (1 mM), was added to the system to create a hypoxic environment. The movement of nanobots was recorded and analyzed to evaluate the catalytic communication between the swarms. Dissolved oxygen test . To evaluate the oxygen-releasing capability of nanobots through H₂O₂ decomposition, the swarm solution was first purged with nitrogen gas to remove remaining dissolved oxygen. After complete deoxygenation, 50 μL of 25 mM H₂O₂ solution was added to initiate the enzymatic reaction. The generation of oxygen was continuously monitored over 10 min using a dissolved oxygen meter (DO9100, JC Instruments, Australia) under ambient temperature. To evaluate the oxygen-releasing capability of the nanobots, a swarm solution was prepared under ambient conditions without prior deoxygenation. The enzymatic reaction was initiated by the addition of 400 μL of 250 mM glucose solution. In vivo bioluminescence imaging. Eight-week-old male nude mice were randomly divided into two groups: one with and one without fuels. All mice were anesthetized via inhalation. Prior to the administration of samples, 100 μL of DI water was intrarectally injected to remove residual fecal matter from the intestine. Subsequently, 70 μL of RITC-labeled nanobot solution was administered intrarectally with and without glucose (250 mM). The intestines were carefully excised from the mice after 30 min. The extracted intestinal tissues were gently rinsed with phosphate-buffered saline (PBS) and visualized using an in vivo imaging system (IVIS). In vivo PA imaging. PA imaging was performed using a developed PA computed tomography system 52,53 . An optical parametric oscillator (OPO) laser (PhotoSonus M-20, Ekspla, Lithuania) with a 20 Hz pulse repetition rate and a wavelength range of 690-1064 nm illuminated the target through a customized fiber bundle. The PA signal was detected by a 1024-element hemispherical array transducer (Japan Probe, Japan), and then the signal was processed by the data acquisition (DAQ) system (Vantage 256, Verasonics, Kirkland, WA). Mouse images were captured by raster scanning using a 3-axis motorized system (LSQ150A, Zaber, Canada) with the custom-built mouse holder and anesthesia mask. The PA images were reconstructed using a customized reconstruction algorithm built in MATLAB. The mouse imaging was performed using 780 and 900 nm illumination and was conducted at the pre-injection of the material and every 3 min from 0 to 30 min after injection. Depth-encoded images were generated through 3D PHOVIS 54 . IBD model preparation and treatment. Eight-week-old male nude mice were used to establish an IBD model. Colitis was induced by providing 3% (w/v) DSS in drinking water for 5 consecutive days. Control group mice received sterile water instead of DSS during the same period. The disease activity index (DAI) was monitored daily by assessing body weight loss (scored 0-4), stool consistency (scored 0-4), and the presence of fecal blood (scored 0-4). These parameters were recorded throughout the DSS feeding and treatment periods to evaluate disease progression. To assess both the preventive and therapeutic effects of nanobots in IBD, two separate experimental timelines were established. In the preventive model, drugs were administered intrarectally on 0 and 2 d, concurrently with DSS treatment, to assess the progression of colitis. In contrast, the therapeutic model involved drug administration on days 4 and 6, following DSS-induced damage, to examine the recovery of inflamed tissue. All treatments were performed under light isoflurane anesthesia to minimize discomfort. The treatment groups included nanobot without glucose (70 μL, 1 mg mL -1 ), nanobot with glucose (70 μL, 1 mg mL -1 ), and PBS. On day 9, the entire colon was excised, and the colon length was measured to assess the severity of colitis. Histological analysis of mouse colonic tissues. The collected colon samples were subjected to H&E staining and TUNEL staining (Abcam, UK). The histological samples were scored based on the histological severity, including evaluation of neutrophilic and mononuclear infiltrates (scored from 0 to 3), epithelial architecture damage (scored from 0 to 3), muscle thickening (scoring from 0 to 3), goblet cell depletion (scoring from 0 to 1), and crypt abscess (scoring from 0 to 1). For immunofluorescence imaging of ZO-1 and occludin, HIF-1 alpha proteins on mouse colonic tissues, sub-centimeter colonic tissues were fixed in 4% paraformaldehyde and embedded in a paraffin block. Before immunofluorescence staining, the colonic tissue samples were dehydrated and subjected to heat-induced antigen retrieval. After blocking with 2% BSA solution, the samples were stained with Alexa Fluor ® 488 mouse anti-ZO-1 antibodies (5 μg mL -1 ), Alexa Fluor® 594 mouse anti-occludin antibodies (1 μg mL -1 ), and Alexa Fluor® 488 anti-HIF-1 alpha antibody (10 μg mL -1 ) overnight at 4°C. For nucleus staining, the samples were stained with DAPI for 15 min at room temperature. ELISA for mouse colonic tissues. An enzyme-linked immunosorbent assay (ELISA) was conducted to measure the levels of pro-inflammatory and anti-inflammatory cytokines in the colon tissue of each group. The colon was placed on ice for homogenization with an extraction buffer. The colon was homogenized at 4°C for 2 h and then centrifuged at 15,000 g and 4°C for 20 min to collect the supernatant. The concentration of IL-1β (Cat. ab214025, Abcam, UK), IL-6 (Cat. ab178013, Abcam, UK), IL-10 (ab185986, Abcam, UK), and TNF-α (Cat. ab181421, Abcam, UK) was analyzed according to the manufacturer's instructions (Abcam, UK). Statistical analysis. Statistical analysis was carried out via the Student’s t -test using the software of SigmaPlot14.5 (Systat Software Inc., San Jose, CA). The values for * P < 0.05, ** P < 0.01, *** P < 0.005, and **** P < 0.001 were considered statistically significant. Data are expressed as means ± standard deviation (SD) from several separate experiments. Declarations Reporting summary Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article. Data availability The raw data of intensity and covering area from the density map are available from the authors upon request. Source data are provided with this paper. Acknowledgements This research was supported by the BRIDGE Research Program (RS-2022-NR067643) and (RS-2024-00460035) (H.C.) of the National Research Foundation (NRF) funded by the Ministry of Science and ICT, Korea. This research was also supported by the Korea Medical Device Development Fund grant (RS-2023-00253749) and the NRF B-IRC grant (RS-2023-00260454) funded by the Korean government. This work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 866348; i-NanoSwarms) Author information Contribution H.C. and Y.S. contributed equally to this work. S.K.H. and S.S. conceived the idea. S.K.H. and S.S. supervised the project, designed the experiment, and wrote the manuscript. H.C. and Y.S. performed all the in vitro experiments. C.K., J.K., and H.J. performed the in vivo PA imaging. H.C., Y.S., and S.M.Y. performed in vivo experiments. H.C. and Y.S. wrote the manuscript. All authors contributed to the scientific discussion and editing of the manuscript. Corresponding author Correspondence to [email protected] (S. K. H.) and [email protected] (S. S.) Competing interests The authors declare no competing interests. References Battiston, F. et al. The physics of higher-order interactions in complex systems. Nat. Phys. 17 , 1093–1098 (2021). shim, G., Devenport, D. & Cohen, D. J. 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Kim, J. et al. 3D multiparametric photoacoustic computed tomography of primary and metastic tumors in living mice. ACS nano 18 , 18176–18190 (2024). Cho, S., Baik, J., Managuli, R. & Kim, C. 3D PHOVIS: 3D photoacoustic visualization studio. Photoacoustics 18 , 100168 (2020). Additional Declarations There is NO Competing Interest. Supplementary Files NatureNTNanobotSI.pdf Supplementary information SupplementaryMovie.3.mp4 Chemotaxis of FITC-CAT nanobots SupplementaryMovie.2.mp4 Swarming behavior of CAT nanobots SupplementaryMovie.1.mp4 Swarming behavior of GOx nanobots Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7461471","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":544435091,"identity":"baf20a1a-f59b-4072-8386-ec9ebe3e08e5","order_by":0,"name":"Sei Kwang Hahn","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA4klEQVRIiWNgGAWjYDACHh4GBsYGGwiHsQFEshGlJQ3IYiZNy2EStMj3nD34uXDH+Tx+/vMHH/zcwSDP38CW9gGfFoOzfcnSM8/cLpackcxs2HuGwXDGAbbDM/Bq4ecxkOZtu5244QYzmzRjGwPjBgb2ZvwO6+cx/s3bdi5xw/nD7L+BWuwJamE422MGtOVA4oYDyWzMQC2JGxjYDuPVYXDmjJk175lkkF+MJXvbJJJnHGZLxu+wnhzj27w77IAhdvDhh59tNrb97W3G+B0GBQlQWgIcPyRpGQWjYBSMglGACQD7NUTMo7UsEQAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0000-0002-7718-6259","institution":"Pohang University of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Sei","middleName":"Kwang","lastName":"Hahn","suffix":""},{"id":544435092,"identity":"860ec508-4a57-48c2-938e-01e2dac738ce","order_by":1,"name":"Hyunsik Choi","email":"","orcid":"","institution":"Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST)","correspondingAuthor":false,"prefix":"","firstName":"Hyunsik","middleName":"","lastName":"Choi","suffix":""},{"id":544435093,"identity":"549edaf0-4d09-40f2-b12c-72882bfa57f5","order_by":2,"name":"Yewon Seo","email":"","orcid":"","institution":"Pohang University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Yewon","middleName":"","lastName":"Seo","suffix":""},{"id":544435094,"identity":"3234ca0e-c630-46d2-a983-17508f35bed5","order_by":3,"name":"Jiwoong Kim","email":"","orcid":"","institution":"Pohang University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Jiwoong","middleName":"","lastName":"Kim","suffix":""},{"id":544435095,"identity":"bf481657-01ef-4ad6-9024-04992b530ada","order_by":4,"name":"Hyunseo Jeon","email":"","orcid":"","institution":"Pohang University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Hyunseo","middleName":"","lastName":"Jeon","suffix":""},{"id":544435096,"identity":"16416f51-c314-46d5-9bc1-8712a3c038be","order_by":5,"name":"Seung Min Yang","email":"","orcid":"","institution":"Pohang University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Seung","middleName":"Min","lastName":"Yang","suffix":""},{"id":544435097,"identity":"4398d2e0-8e61-4bc1-8f83-9adb181fd678","order_by":6,"name":"Chulhong Kim","email":"","orcid":"https://orcid.org/0000-0001-7249-1257","institution":"Pohang University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Chulhong","middleName":"","lastName":"Kim","suffix":""},{"id":544435098,"identity":"61a46285-8706-4069-b488-ab151c8c69b0","order_by":7,"name":"Jin Huh","email":"","orcid":"","institution":"Pohang University of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Jin","middleName":"","lastName":"Huh","suffix":""},{"id":544435099,"identity":"078598db-1b12-4eca-a243-0717d18d438d","order_by":8,"name":"Samuel Sánchez","email":"","orcid":"https://orcid.org/0000-0001-9713-9997","institution":"Institute for Bioengineering of Catalonia (IBEC), The Barcelona Institute of Science and Technology (BIST)","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Sánchez","suffix":""}],"badges":[],"createdAt":"2025-08-26 09:45:35","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7461471/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7461471/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":96242917,"identity":"8c900a4c-84b1-4550-9ac4-cdc62994f190","added_by":"auto","created_at":"2025-11-19 07:14:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2118666,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCollective behavior of enzymatic swarms.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, Schematic illustration for the systemically linked swarming communication between glucose oxidase nanobots (GOx NBs) and catalase nanobots (CAT NBs) for the treatment of inflammatory bowel disease (IBD). \u003cstrong\u003eb\u003c/strong\u003e, The density maps of swarming behavior with and without fuels (i.e., glucose, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e) for 60 s. The corresponding covering area of \u003cstrong\u003ec,\u003c/strong\u003e GOx NBs and \u003cstrong\u003ed,\u003c/strong\u003e CAT NBs. \u003cstrong\u003ee\u003c/strong\u003e, Particle image velocimetry analysis of swarming behavior with and without fuels for 60 s. Scale bars correspond to 2 mm. Images in \u003cstrong\u003ea\u003c/strong\u003e were created with BioRender.com.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/57c07eb5d6370b5f03f91b5c.png"},{"id":96243084,"identity":"8db720ec-d439-46e3-a870-a9de80a5ad36","added_by":"auto","created_at":"2025-11-19 07:15:29","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2153576,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePositive chemotaxis behavior of CAT NBs. a\u003c/strong\u003e, Schematic illustration for the chemotaxis of FITC-CAT NBs towards the higher concentration of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e generated by GOx NBs. \u003cstrong\u003eb\u003c/strong\u003e, Schematic illustration for chemical gradient induced microchip (left) and rhodamine intensity along the cross-sectional line in ROI for 15 min (right). Chemotaxis behavior in the middle channel after adding \u003cstrong\u003ec,\u003c/strong\u003e H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, \u003cstrong\u003ed,\u003c/strong\u003e glucose, and \u003cstrong\u003ee, \u003c/strong\u003eGOx NBs and glucose in the left channel, and CAT NBs distribution 10 min after adding \u003cstrong\u003ef,\u003c/strong\u003e H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, \u003cstrong\u003eg, \u003c/strong\u003eglucose, and \u003cstrong\u003eh, \u003c/strong\u003eGOx NBs and glucose. White dotted lines indicate LOIs. \u003cstrong\u003ei\u003c/strong\u003e, The fluorescence intensity of the corresponding LOIs from (\u003cstrong\u003eh\u003c/strong\u003e). \u003cstrong\u003ej\u003c/strong\u003e, The density maps of swarming behaviors over time. White dotted squares indicate the left wall in the middle channel. \u003cstrong\u003ek\u003c/strong\u003e, The bright area (%) change for 280 s in the corresponding white dotted square in (\u003cstrong\u003ej\u003c/strong\u003e). Scale bars in \u003cstrong\u003ef, g, and h\u003c/strong\u003e correspond to 4 mm. Images in \u003cstrong\u003ea, b, c, d, and e\u003c/strong\u003e were created with BioRender.com.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/070268c7c9f95cc87a57ee00.png"},{"id":95902852,"identity":"cbbe0ca4-288b-4048-b10d-0a4eed1a9334","added_by":"auto","created_at":"2025-11-14 08:45:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1508028,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSystemic swarming communication between enzymatic swarms.\u003c/strong\u003e Navigation of FITC-GOx NBs in the microchannel with \u003cstrong\u003ea, \u003c/strong\u003eglucose and \u003cstrong\u003eb, \u003c/strong\u003ewithout the oxygen scavenger. \u003cstrong\u003ec\u003c/strong\u003e, Dissolved oxygen profile with and without the oxygen scavenger. The resulting fluorescence in the microchannel with \u003cstrong\u003ed,\u003c/strong\u003e glucose and \u003cstrong\u003ee,\u003c/strong\u003ewithout glucose after 10 min. \u003cstrong\u003ef\u003c/strong\u003e, Velocity of navigation in the microchannel with and without the oxygen scavenger. \u003cstrong\u003eg\u003c/strong\u003e, Navigation length after 10 min. Data are presented as mean values and error bars represent the S.D. Statistical analysis was performed via the two-sided\u003cem\u003e t\u003c/em\u003e-test (n = 3). \u003cstrong\u003eh\u003c/strong\u003e, Schematic illustration for the swarming communication between RITC-CAT NBs and FITC-GOx NBs. \u003cstrong\u003ei, \u003c/strong\u003eSimultaneous navigation analysis of RITC-CAT NBs and FITC-GOx NBs for 218 s, and \u003cstrong\u003ej,\u003c/strong\u003e the corresponding navigation profile of each swarm. Scale bars in \u003cstrong\u003ed, e, \u003c/strong\u003eand\u003cstrong\u003e i\u003c/strong\u003e correspond to 2 mm.Images in \u003cstrong\u003ea \u003c/strong\u003eand\u003cstrong\u003e h\u003c/strong\u003e were created with BioRender.com.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/a2bbf2a40491ae5998859ccc.png"},{"id":95902844,"identity":"1f3761a8-36af-4deb-8a11-0602bce50898","added_by":"auto","created_at":"2025-11-14 08:45:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2847419,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnhanced navigation of enzymatic swarms in the colon. a\u003c/strong\u003e, Schematic illustration for the procedure of intrarectal injection of enzymatic swarms. \u003cstrong\u003eb\u003c/strong\u003e, IVIS images of ex vivo colons after 30 min of intrarectal injection and \u003cstrong\u003ec\u003c/strong\u003e, the corresponding navigation length from the rectum. Data are presented as mean values and error bars represent the S.D. Statistical analysis was performed via the two-sided \u003cem\u003et\u003c/em\u003e-test (n = 4 per group). PA imaging after intrarectal injection of enzymatic swarms \u003cstrong\u003ed,\u003c/strong\u003e without glucose and \u003cstrong\u003ee,\u003c/strong\u003e with glucose for 33 min. \u003cstrong\u003ef\u003c/strong\u003e, PA intensity profile in 1 ROI region without glucose (left) and with glucose (right) for 33 min. Images in \u003cstrong\u003ea\u003c/strong\u003e were created with BioRender.com.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/1b0668c1a6d96b3ab5e2922b.png"},{"id":95902849,"identity":"d1d47ded-fca0-46a6-853b-e5a69a65ff60","added_by":"auto","created_at":"2025-11-14 08:45:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":2676522,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevention effect of enzymatic swarms on IBD. a\u003c/strong\u003e, The treatment schedule for the murine IBD model prepared by 3% DSS. Groups are randomly divided into 4 groups [Control, DSS, swarms (1 mg mL\u003csup\u003e-1\u003c/sup\u003e) w/o glucose, and swarms (1 mg mL\u003csup\u003e-1\u003c/sup\u003e) w/ glucose]. \u003cstrong\u003eb, \u003c/strong\u003eRelative weight change and \u003cstrong\u003ec, \u003c/strong\u003edisease activity index monitoring of mice during the treatment. \u003cstrong\u003ed,\u003c/strong\u003e Colon length collected from the mice on 9 d and \u003cstrong\u003ee,\u003c/strong\u003e the corresponding photo-images of colon samples. Statistical analysis was performed via the two-sided \u003cem\u003et\u003c/em\u003e-test (n = 5 mice per group). \u003cstrong\u003ef\u003c/strong\u003e, H \u0026amp; E staining of cross-sectional colon tissues (upper panel) and the magnified images of red quadrangles (lower panel). \u003cstrong\u003eg\u003c/strong\u003e, TUNEL assay (upper panel), immunostaining of HIF-α (middle panel), and immunostaining of ZO-1 and occludin (lower panel). \u003cstrong\u003eh,\u003c/strong\u003e Histological damage score, \u003cstrong\u003ei,\u003c/strong\u003e apoptotic area, and \u003cstrong\u003ej,\u003c/strong\u003e hypoxic area from the treated colon. Statistical analysis was performed via the two-sided \u003cem\u003et\u003c/em\u003e-test (n = 5 sections per group). \u003cstrong\u003ek\u003c/strong\u003e, ELISA analysis of colon tissues including IL-6, TNF-a, IL-1b and IL-10. Data are presented as mean values and error bars represent the S.D. Statistical analysis was performed via the two-sided \u003cem\u003et\u003c/em\u003e-test (n = 4 colon tissues per group). Scale bars correspond to 500 μm in \u003cstrong\u003ef\u003c/strong\u003e and 100 μm in \u003cstrong\u003eh\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/3e6bc25373c964ff0e296176.png"},{"id":95902853,"identity":"4d9f432d-33af-4936-8bb9-fc169158443a","added_by":"auto","created_at":"2025-11-14 08:45:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2552724,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTherapeutic effect of enzymatic swarms on IBD\u003c/strong\u003e. \u003cstrong\u003ea\u003c/strong\u003e, The treatment schedule for the murine IBD model prepared by 3% DSS. Groups are randomly divided into 5 groups [Control, DSS, swarms (1 mg mL\u003csup\u003e-1\u003c/sup\u003e) w/o glucose, swarms (1 mg mL\u003csup\u003e-1\u003c/sup\u003e) w/ glucose, and high swarms (2 mg mL\u003csup\u003e-1\u003c/sup\u003e) w/ glucose]. \u003cstrong\u003eb\u003c/strong\u003e, Weight change and \u003cstrong\u003ec\u003c/strong\u003e, disease activity index monitoring of mice during the treatment. \u003cstrong\u003ed\u003c/strong\u003e, Colon length collected from the mice on day 9 and \u003cstrong\u003ee\u003c/strong\u003e, the corresponding photo-images of colon samples. Statistical analysis was performed via the two-sided t-test (n = 5 mice per group). \u003cstrong\u003ef\u003c/strong\u003e, H \u0026amp; E staining of cross-sectional colon tissues (upper panel) and the magnified images of red quadrangles (lower panel). \u003cstrong\u003eg\u003c/strong\u003e, TUNEL assay (upper panel), immunostaining of HIF-α (middle panel), and immunostaining of ZO-1 and occludin (lower panel). \u003cstrong\u003eh,\u003c/strong\u003e Histological damage score, \u003cstrong\u003ei,\u003c/strong\u003e apoptotic area, and \u003cstrong\u003ej\u003c/strong\u003e, hypoxic area from the treated colon. Statistical analysis was performed via the two-sided \u003cem\u003et\u003c/em\u003e-test (n = 5 sections per group). \u003cstrong\u003ek\u003c/strong\u003e, ELISA analysis of colon tissues including IL-6, TNF-a, IL-1b and IL-10. Data are presented as mean values and error bars represent the S.D. Statistical analysis was performed via the two-sided \u003cem\u003et\u003c/em\u003e-test (n = 4 colon tissues per group). Scale bars correspond to 500 μm in \u003cstrong\u003ef\u003c/strong\u003e and 100 μm in \u003cstrong\u003eh\u003c/strong\u003e.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/ee95bfc60852c45647e65194.png"},{"id":97671917,"identity":"2b2b39d6-3e57-4df1-8152-db195bc3c3c1","added_by":"auto","created_at":"2025-12-08 09:33:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":15014929,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/318a23e9-4e31-49d1-aa16-157d2c6a33bd.pdf"},{"id":95902851,"identity":"6749e5fe-f318-42cb-bcd0-1f61548e63f7","added_by":"auto","created_at":"2025-11-14 08:45:13","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":2971427,"visible":true,"origin":"","legend":"Supplementary information","description":"","filename":"NatureNTNanobotSI.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/59b25ab7c756942bde428d2f.pdf"},{"id":95902846,"identity":"0031e9b3-8e00-4f86-945f-52378df7a4e7","added_by":"auto","created_at":"2025-11-14 08:45:13","extension":"mp4","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":4324356,"visible":true,"origin":"","legend":"Chemotaxis of FITC-CAT nanobots","description":"","filename":"SupplementaryMovie.3.mp4","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/d982703357c6f05be0d390da.mp4"},{"id":95902850,"identity":"80d28320-6eef-4002-b7f8-86acbf6fad1d","added_by":"auto","created_at":"2025-11-14 08:45:13","extension":"mp4","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":5018875,"visible":true,"origin":"","legend":"Swarming behavior of CAT nanobots","description":"","filename":"SupplementaryMovie.2.mp4","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/026160e797079f88a53ba5a6.mp4"},{"id":96242857,"identity":"0bb81a98-8f66-4db7-9c1a-fa87ecc79f2c","added_by":"auto","created_at":"2025-11-19 07:14:38","extension":"mp4","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":5190418,"visible":true,"origin":"","legend":"Swarming behavior of GOx nanobots","description":"","filename":"SupplementaryMovie.1.mp4","url":"https://assets-eu.researchsquare.com/files/rs-7461471/v1/87a956da857765f67155107a.mp4"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Tandem Enzymatic Swarm Communication Enables Collective Nanobot Therapy in Inflammatory Bowel Disease","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCollective behavior is a common phenomenon in nature. Each organism interacts with its surroundings and other individuals, and these interactions collectively display complex and intelligent behavior without requiring centralized control\u003csup\u003e1,2,3,4,5\u003c/sup\u003e. Inspired by nature, synthetic micro/nanobot (MNB) swarming systems have been proposed, including MNBs actuated by magnetic fields\u003csup\u003e6,7\u003c/sup\u003e, light\u003csup\u003e8,9\u003c/sup\u003e, ultrasound\u003csup\u003e10,11\u003c/sup\u003e, and electric fields\u003csup\u003e12,13\u003c/sup\u003e, as well as chemically-driven MNBs\u003csup\u003e14,15\u003c/sup\u003e and biohybrid MNBs\u003csup\u003e16,17\u003c/sup\u003e. Unlike a single unit, these synthetic swarms can address many tasks such as cargo delivery, analyte capture, and purification for biomedical applications.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eRecently, various enzymatic\u0026nbsp;swarms have\u0026nbsp;exhibited complex and intriguing coordinated behaviors, such as enhanced coverage, penetration, and convection currents, through a single enzymatic reaction within a swarm\u003csup\u003e18,19,20,21,22,23,24\u003c/sup\u003e. Although enzymatic swarm systems have been achieved, interactions between different enzymatic swarms have not been realized, where they can receive chemical signals from each other and potentially modify their swimming dynamics, leading to the emergent reminiscent behaviors of biological systems.\u0026nbsp;In natural systems, communication between distinct populations through chemical gradients or molecular feedback is essential for collective decision-making and efficient function. Mimicking this level of interaction would enable synthetic MNBs to organize, adapt, and perform complex therapeutic tasks\u003csup\u003e25,26\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eInflammatory bowel disease (IBD) refers to a group of chronic inflammatory conditions of the gastrointestinal (GI) tract, including Crohn\u0026apos;s disease and ulcerative colitis\u003csup\u003e27,28,29\u003c/sup\u003e. Damage to the intestinal barrier, hypoxic condition, and oxidative stress are known to make IBD treatment more complicated\u003csup\u003e30,31,32,33\u003c/sup\u003e. Although numerous oral and rectal medications have been commercially developed to alleviate hypoxic conditions and oxidative stress, their efficacy is limited by poor retention in the gut and rapid clearance through peristalsis. Accordingly, there is a strong clinical unmet need to actively scavenge ROS and deliver oxygen in the intestine for effective IBD treatment.\u003c/p\u003e\n\u003cp\u003eHere, we develop a tandem communication system between glucose oxidase (GOx) and catalase (CAT) nanobots (NBs) for IBD treatment. This design introduces inter-swarm signaling as a principle to engineer nanobot collectives with emergent, systemic-like behaviors.\u0026nbsp;After injection of swarms through the rectum, tandem communication repeats, allowing them to navigate actively against peristaltic flow and remain at inflamed sites. Finally, enzymatic swarms exhibit a significant therapeutic effect on IBD-induced mice, enabling ROS scavenging and oxygen delivery to alleviate hypoxic conditions and inflammatory responses in the colon. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCollective behavior of swarms\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFig. 1a\u0026nbsp;shows a schematic illustration of the systemically linked swarming communication between GOx NBs and CAT NBs for IBD treatment: (1)\u0026nbsp;GOx NBs and CAT NBs with glucose are injected in the colon;\u0026nbsp; (2)\u0026nbsp;GOx NBs collectively decompose glucose, generating an H₂O₂ gradient, and\u0026nbsp;CAT NBs chemotactically respond to this gradient and decompose H₂O₂, releasing oxygen; (3) the released oxygen is subsequently used by GOx NBs to sustain glucose decomposition. These nanobots consist of mesoporous silica nanoparticles (MSNs) functionalized with surface-immobilized enzymes\u0026nbsp;of GOx and CAT. The detailed characterization is provided in Supplementary Fig. 1\u0026ndash;4.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe molecularly asymmetric distribution of enzymes on the surface of MSNs provided sufficient driving force for the enzymatic nanobots via bio-catalytic conversion\u003csup\u003e34,35\u003c/sup\u003e and the generation of chemical gradients\u003csup\u003e36\u003c/sup\u003e. As shown in Supplementary Fig. 5 and 6, we calculated the mean squared displacement (MSD) based on the trajectory data, which reveals a linear increase over time, characteristic of enhanced diffusion of nanoparticles. To study in vitro dynamics and collective behavior of GOx and CAT NBs, we added a droplet of nanobots to a PBS solution containing 0, 50, 100, and 250 mM of fuels\u0026nbsp;(i.e.,\u0026nbsp;glucose, H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e)\u0026nbsp;(Supplementary Movies 1 and 2). In the presence of glucose and\u0026nbsp;H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e,\u0026nbsp;nanobot swarms rapidly expanded, forming vigorous fronts and three-dimensional (3D) vortices (Fig. 1b,\u0026nbsp;Supplementary\u0026nbsp;Fig. 7 and 8).\u0026nbsp;In contrast, without fuels, swarms quickly sedimented, showing a two-dimensional (2D) dispersion pattern. Swarm coverage was quantified\u0026nbsp;from the density map per video frame, revealing expansion profiles that increased with fuel concentration\u0026nbsp;(Fig. 1c\u0026nbsp;and\u0026nbsp;d). Particle image velocimetry analysis further confirmed the previously observed behaviors. In\u0026nbsp;the absence of fuels, swarm velocities were low and disappeared within 40 s (Fig. 1e, Supplementary Fig. 9 and 10).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChemotaxis behavior of swarms\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe assessed the chemotaxis behavior of CAT NBs attracted by the GOx NBs (Fig. 2a). To achieve this, we designed a non-flow agar gel-based microfluidic chip (Supplementary Fig. 11) that minimized bulk flow effects, thereby establishing a controlled gradient. The device consisted of three channels, enabling a chemical gradient to be precisely induced in the middle channel by adding chemicals at side channels (Fig. 2b and Supplementary\u0026nbsp;Fig. 12). Using this setup, we verified the chemotaxis behavior of CAT NBs by adding H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003eto the left channel, fluorescein isothiocyanate labelled CAT NBs in the middle channel and DI water in the right channel, respectively (Fig. 2c). Swarms in the middle channel initially presented a droplet shaped dispersion for the first 30 s. After that, a tail of swarm emerged at 40 s and gradually extended toward the left side of the middle channel, where the concentration of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u0026nbsp;\u003c/sub\u003ewas higher. After 10 min, the swarm was completely biased toward the left side (Fig. 2d). As a control, we injected glucose into the left channel, which resulted in no bias (Fig. 2e and f). These results confirmed that CAT NBs were selectively attracted by the gradient of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e. We further investigated their chemotaxis behavior as a function of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e concentration.Detailed characterization and discussion can be found in Supplementary Information (Supplementary Fig. 13)\u003c/p\u003e\n\u003cp\u003eAfter confirming positive chemotaxis towards gradients of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e, we directly demonstrated the interaction between GOx and CAT NBs (Fig. 2g, h and Supplementary Movie 3). In the left channel, GOx NBs and glucose were introduced to generate H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e.After 40 s, CAT NBs in the middle channel were gradually distorted and started to migrate toward the left side. Within 10 min, the swarm was completely biased in that direction (Fig. 2h and i). To further quantify the chemotaxis of swarms, we converted the swarm distribution in the middle channel into a density map (Fig. 2j). The bright region along the left channel was gradually expanded from the bottom upwards, reaching almost 100% within 180 s (Fig. 2k), confirming that CAT NBs exhibited positive chemotaxis toward GOx NBs in the presence of glucose. \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSwarming communication between swarms\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe investigated the effect of oxygen on the navigation of GOx NBs by adjusting the oxygen supply with or without an oxygen scavenger (i.e.,\u0026nbsp;sodium sulfite)\u0026nbsp;(Fig. 3a and b). Dissolved oxygen (DO) profile showed that the oxygen scavenger depleted DO much faster than the control, revealing that it consumed oxygen before it reached GOx NBs (Fig. 3c). To confirm the navigation of swarms, we designed intestine-shaped microchannel (Supplementary Fig. 14). After addition of the oxygen scavenger in the microchannel, swarms showed limited navigation in the microchannel due to the depletion of oxygen (Fig. 3d). In contrast, swarms navigated efficiently without the oxygen scavenger (Fig. 3e). The corresponding velocity and navigation length also decreased significantly in the presence of the oxygen scavenger, demonstrating the importance of oxygen supply to GOx NBs (Fig. 3f,g). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNext, we verified the swarming communication between the swarms in the mixture of GOx and CAT NBs. We hypothesized three types of collective behaviors in the presence of glucose, including (1) the propulsion of the GOx NBs by the decomposition of glucose, (2) the chemotaxis of CAT NBs by the gradient of H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2,\u0026nbsp;\u003c/sub\u003eand\u0026nbsp;(3) the boosting of GOx NBs through oxygen supply (Fig. 3h). We tagged each swarm with fluorescence dyes and measured the velocity of each swarm in the microchannel for 230 s (Fig. 3i,j). During the first 60 s, GOx NBs gradually overtook CAT NBs, because glucose decomposition dominated. After 60 s, the reaction was saturated and the CAT NBs accelerated towards GOx NBs with a higher velocity, indicating the dominant chemotaxis reaction. After 130 s, the velocity of GOx NBs increased and the distance from CAT NBs increased due to oxygen boosting in the glucose solution. After 160 s, CAT NBs again showed stronger chemotaxis, moving faster than GOx NBs. We observed two chemotactic cycles within 230 s of swarm communication. After that, we compared the navigation efficiency with a single swarm as shown in Supplementary Information (Supplementary\u0026nbsp;Fig. 15 and 16).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn vivo collective behavior of swarms\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe optimized the ratio of swarms for further in vivo experiments.\u0026nbsp;Detailed characterization and discussion can be found in Supplementary information (Supplementary\u0026nbsp;Fig. 17-19). With the optimized ratio of swarms, we further studied in vivo collective behavior of swarms in an intestine after intrarectal instillation. After enema with DI water, the fluorescently labelled swarms were injected with and without glucose (Fig. 4a). After 30 min, colon was excised from the mice to observe the navigation of swarms in the colon by IVIS imaging (Fig. 4b). At 250 mM of glucose, the swarms navigated along the colon with an average length of 5.95 cm, indicating the fast navigation within 30 min. In contrast, the swarms without glucose were hardly navigated in the colon and even seemed to be cleared from the colon (Fig. 4c).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo monitor the swarms in real-time, we labelled the swarms with near-infrared indocyanine for photoacoustic (PA) imaging. PA imaging has recently been proposed as an emerging modality for the fast tracking of MNBs\u003csup\u003e37,38,39,40\u003c/sup\u003e. In the near-infrared wavelength range, PA imaging was capable of entirely noninvasive monitoring with a high contrast and a high spatiotemporal resolution\u003csup\u003e41,42,43\u003c/sup\u003e. We removed the residual fecal matter with an enema to empty the colon before intrarectal instillation, thereby controlling the glucose concentration precisely (0 and 250 mM). At 3 min intervals for 30 min, we monitored the abdomen of mice after intrarectal instillation of ICG-labelled swarms, both without (Fig. 4d and Supplementary Fig. 20) and with glucose (Fig. 4e and Supplementary Fig. 21).\u003c/p\u003e\n\u003cp\u003eAfter coding by depth, we divided the colon into two parts from the rectum to the cecum. Without glucose, we observed a PA signal in the first region of interest (ROI) for 9 min. However,\u0026nbsp;the signal was pushed toward the rectum at 12 min and completely disappeared within 15 min in corresponding to the IVIS imaging. This phenomenon may be attributed to the fact that the swarms were cleared from the intestine by the peristaltic movement of the GI tract. However, with glucose, the PA signal in the first ROI was maintained and the PA signal in the second ROI increased in strength over 30 min, demonstrating that the swarms were navigated efficiently against the peristalsis movement of the GI tract.\u0026nbsp;These observations were further confirmed by analyzing the PA signal in the\u0026nbsp;first ROI (Fig. 4f). After that, we verified the retention of swarms in the colon for 6 h (Supplementary Fig. 22). Most regions of the colon were covered by the swarms without clearance for 1 h, indicating efficient reflux behavior of swarms in colon. For 6 h, considerable fluorescence intensity of swarms was detected in the colon.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevention and therapeutic effect on IBD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe therapeutic effect of swarms in preventing colon inflammation was first assessed in model mice with\u0026nbsp;dextran sulfate sodium (DSS)-induced IBD. Specifically, 3% DSS in drinking water was supplied for 6 d with twice rectal administration of PBS or swarms with and without glucose on 0 and 2 d (Fig. 5a). During the administration, we monitored a body weight (Fig. 5b) and evaluated several factors for disease activity index (DAI) daily (Fig. 5c). The weight was correlated with intestinal inflammation, affecting the digestion and nutrient absorption processes of mice. The DAI of the 3% DSS-supplied group was gradually increased during the first 5 d due to the induction of inflammation. While the DAI of other groups worsened, the DAI of the swarms with glucose group recovered, indicating that the swarms alleviated the abnormality of IBD. Compared with the swarms without glucose group, the continuous collective motion of the swarms with glucose group resulted in an enhanced distribution in the target region, leading to a more efficient treatment effect. On day 9, the mice were sacrificed for the collection and analysis of their colon tissue. Colon length correlates with inflammation, and thus severe inflammation causes shorter colons. Among the groups of DSS-induced colitis, only the swarms with glucose group predominantly maintained the colon length comparable to that of the healthy colon (Fig. 5d,e). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWith hematoxylin and eosin (H\u0026amp;E) staining (Fig. 5f), we scored histological damage in terms of several factors (Fig. 5g and Supplementary Fig. 23). The histological colonic damage caused by the oxidative stress was alleviated in the group of swarms with glucose, revealing the adequate protection of swarms against oxidative stress in colonic tissue. The more detailed examination was also performed via TUNEL assay and immunostaining analysis of HIF1-\u0026alpha;, ZO-1 and occludin (Fig. 5h). The TUNEL assay and immunostaining analysis of HIF1-\u0026nbsp;\u0026alpha;\u0026nbsp;revealed that the swarms with glucose effectively alleviated the apoptosis and hypoxic colonic cells with the area of 12.2 and 8.4%, respectively (Fig. 5i,j). HIF-1\u0026alpha; expression is a key factor in the cellular response to hypoxia\u003csup\u003e44\u003c/sup\u003e. In addition, ZO-1 and occludin are two major intestinal tight junction proteins that are closely related to the integrity of the intestinal barrier\u003csup\u003e45\u003c/sup\u003e. The immunostaining verified that the swarms restored the disrupted colonic epithelium cell layer induced by acute IBD effectively. After that, we measured the levels of relevant proinflammatory and anti-inflammatory cytokines (IL-6, TNF-\u0026alpha;, IL-1\u0026beta;, and IL-10) in the colonic tissue (Fig. 5k). The results showed the effective decrease of proinflammatory cytokines and the increase in anti-inflammatory cytokines in the group of swarms with glucose, thereby modulating the IBD symptoms.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further assess the capability of the enzymatic swarms to ameliorate inflammation in IBD, we investigated the efficacy via a delayed treatment regimen in the model mice of DSS-induced IBD with additional group (2-fold concentration of swarms) (Fig. 6a). Compared with other groups, the model mice in the swarms with glucose group showed a gentle decrease in the body weight and the relatively low DAI over 9 d, showing the moderate symptoms of IBD (Fig. 6b and c). The colonic length also verified that the swarms with glucose preserved the colon length at a comparable level to that of a healthy colon (Fig. 6d and e). Moreover, histological analysis confirmed the restoration of damaged colonic tissue, along with the alleviation of hypoxic conditions, by the enzymatic swarms with glucose (Fig. 6f, g, and Supplementary Fig. 24).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFurther analysis revealed the effective amelioration of apoptosis and hypoxic conditions, accompanied by the high expression of tight junction proteins in the colon tissues (Fig. 6h, i, and j). Specifically, the higher concentration of swarms exhibited more significant therapeutic efficacy in the presence of glucose, indicating concentration-dependent treatment efficacy. In addition, the high concentration of swarms showed the lowest proinflammatory cytokine levels and the highest aini-inflammatory cytokine levels compared to the other groups (Fig. 6k). The long-term safety assessment of swarms revealed that there was no significant difference of histopathology in the major organs between the PBS treated group and the swarms treated group after 7 days (Supplementary Fig. 25).\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates, for the first time, that two distinct enzymatic nanobot swarms can communicate through a cascade reaction, producing emergent behaviors reminiscent of those found in biological collectives. Although several milestones towards biomedical applications have already been achieved, individual NMBs have not reached the complexity and autonomy of their biological counterparts\u003csup\u003e46,47,48,49\u003c/sup\u003e.\u003csup\u003e\u0026nbsp;\u003c/sup\u003eTo better mimic the biological counterparts, important key questions include how the NMBs interact with the environment, communicate with each other, and act collectively\u003csup\u003e50,51\u003c/sup\u003e. By linking GOx and CAT activities, we established a feedback loop in which one swarm generates a chemotactic signal, whereas the other responds and reinforces propulsion through oxygen release. This interaction transformed simple enzyme-driven motion into systemic swarm communication, providing a conceptual advance in the design of active matter.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe functional consequences of this design are evident both in vitro and in vivo. In microchips, tandem swarms displayed coordinated navigation and extended motility compared to single-enzyme systems. These behaviors translated into enhanced navigation in the colon, even against peristaltic flow. Animals treated with GOx/CAT swarms showed reduced inflammation, preserved colon length, restored epithelial integrity, and a shift toward anti-inflammatory cytokine profiles under both preventive and therapeutic regimens. Remarkably, these outcomes were achieved without the use of conventional drugs, highlighting the potential of swarm-based nanomedicine as a stand-alone therapeutic approach.\u003c/p\u003e\n\u003cp\u003eBeyond IBD, the principle of enzymatic swarm communication would be extended to other disorders characterized by hypoxia, oxidative stress, or localized inflammation. The modularity of the system suggests that other enzyme pairs can be engineered to respond to different metabolites, generate distinct chemical gradients, or trigger specific therapeutic actions. Such adaptability would allow nanobot collectives to address diverse GI conditions or even systemic diseases.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhile promising, our study also points to future challenges. The translation of swarm nanobots to the clinic will require detailed safety evaluations, long-term biodistribution studies, and scalable manufacturing of enzyme-functionalized carriers. Moreover, it will be essential to understand how swarm communication behaves in the heterogeneous environment of the human gut, including variable glucose levels, interactions between microbiota, and immune responses. Nevertheless, this work would lay the foundation for a next generation of collective nanomedicine by demonstrating that synthetic nanobot swarms can communicate, adapt, and deliver therapeutic benefit for colorectal diseases and other various intractable diseases.\u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eMaterials.\u0026nbsp;\u003c/strong\u003eTriethanolamine (TEOA), tetraethyl orthosilicate (TEOS), cetyltrimethylammonium bromide (CTAB), catalase (\u0026ge;10,000\u0026nbsp;units mg\u003csup\u003e-1\u003c/sup\u003e), glucose oxidase (50KU, from Aspergillus), D-(+)-glucose, fluorescein isothiocyanate (FITC), rhodamine b isothiocyanate(RITC), 3-aminopropyltriethoxysilane (APTES), glutaraldehyde (GA) solution, ethanol, methanol, hydrochloric acid (HCl),\u0026nbsp;sodium sulfite,\u0026nbsp;rhodamine b, bovine serum albumin (BSA) were obtained from Sigma Aldrich (St. Louis, MO).Phosphate-buffered saline (PBS)\u0026nbsp;and 4% paraformaldehyde were obtained from Tech\u0026amp;innovation\u0026nbsp;(Korea). Alexa Fluor\u0026reg;\u0026nbsp;594\u0026nbsp;Occludin monoclonal antibody, Alexa Fluor\u0026reg;\u0026nbsp;488\u0026nbsp;ZO-1 monoclonal antibody, and mounting medium with 4\u0026rsquo;,6-diamidino-2-phenylindole (DAPI) were obtained from Thermo Fisher Scientific (Waltham, MA).Hydrogen peroxide (34.5%) (H\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e2\u003c/sub\u003e)\u0026nbsp;and xylene were obtained from SAMCHUN (Korea).Dextran sulfate sodium salt (DSS) was obtained from MP Biomedicals (Irvine, CA).Thiol-terminated polyethylene glycol amine (HS-PEG-NH\u003csub\u003e2\u003c/sub\u003e) (MW 5k) was obtained from CreativePEGworks (Durham, NC). Indocyanine Green sulfo-NHS ester (ICG sulfo-NHS ester) was obtained from Shimadzu Corporation (Japan).Alexa Fluor\u0026reg; 488 anti-HIF-1 alpha antibody was obtained from Abcam (UK). Agarose was obtained from Georgiachem (Suwanee, GA).\u0026nbsp;SYLGARD\u0026trade; 184 Silicone Elastomer Kit\u0026nbsp;was obtained from Dow Corning (Midland, MI). \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSynthesis of mesoporous silica nanoparticles\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eMesoporous silica nanoparticles (MSNs) were synthesized following a sol-gel St\u0026ouml;ber method. Briefly, 570 mg of CTAB and 35 g of TEOA were mixed in 20 mL of DI water. Then, the mixture was heated to 95 \u0026deg;C in a silicone oil bath under constant stirring for 30 min. TEOS (1.5 mL) was then added dropwise, followed by incubation at 95 \u0026deg;C for 2 h. The resulting particles were collected by centrifugation at 1350 g for 10 min and washed three times with ethanol. To remove the CTAB from the particles, the particles were suspended in 30 mL of a methanol/HCl mixture (10:0.6, v/v) and refluxed at 80 \u0026deg;C for 24 h. Then, the particles were collected by centrifugation (1,350 g, 10 min) and washed three times with ethanol.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSynthesis of enzyme-powered nanobots\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eTo modify the amine group,\u0026nbsp;the prepared MSNs in ethanol (1 mg mL\u003csup\u003e-1\u003c/sup\u003e) were reacted with APTES (35 \u0026mu;L mL\u003csup\u003e-1\u003c/sup\u003e) at 70 \u0026deg;C for 2 h. The particles were then collected by centrifugation (1,150 g, 5 min) and washed three times with DI water.\u0026nbsp;Amine-functionalized MSNs (MSNs-NH₂) were suspended in\u0026nbsp;DI\u0026nbsp;water (1 mg mL\u003csup\u003e-1\u003c/sup\u003e). 50 \u0026mu;L of GA solution was added, and the mixture was stirred at room temperature for\u0026nbsp;3\u0026nbsp;h. After crosslinking, the particles were collected by centrifugation (1,150 g, 5 min) and washed three times with DI water with 5 min\u0026nbsp;of sonication between each wash.\u0026nbsp;The resulting particles were resuspended in an enzyme solution composed of catalase (0.75 mg mL\u003csup\u003e-1\u003c/sup\u003e), glucose oxidase (1 mg mL\u003csup\u003e-1\u003c/sup\u003e), and NH₂-PEG-SH (2 \u0026mu;g mg\u003csup\u003e-1\u003c/sup\u003e of MSNs) in PBS. The mixture was incubated on an end-to-end rotary shaker overnight at room temperature. The functionalized nanobots were washed three times with\u0026nbsp;DI\u0026nbsp;by centrifugation (1,150 g, 5 min).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCharacterization of enzyme-powered\u0026nbsp;nanobots.\u0026nbsp;\u003c/strong\u003eThe morphology and size of the synthesized nanobots were characterized using transmission electron microscopy (TEM), scanning electron microscopy (SEM), zeta potential, and dynamic light scattering (DLS). For TEM analysis, a 5 \u0026mu;L of nanobot suspension (500 \u0026mu;g mL\u003csup\u003e-1\u003c/sup\u003e in DI water) was dropped onto a carbon-coated copper grid and air-dried at room temperature for 6 h. TEM images were acquired at an accelerating voltage of 120 kV (Talos L120C, Thermo Fisher Scientific, Waltham, MA). A nanorobot solution was deposited onto a silicon wafer, dried under ambient conditions, and coated with a thin layer of gold using a sputter coater to enhance conductivity. The surface morphology and structural features of the nanobots were examined using SEM (Gemini, Carl Zeiss AG, Germany), operating at 25 kV. The hydrodynamic diameter and surface charge of the nanobots were evaluated with DLS and zeta potential analysis (Zetasizer Advance, Malvern Instruments, UK) at room temperature.\u0026nbsp;To assess the surface chemistry of the nanobots, Fourier-transform infrared (FTIR) spectroscopy was conducted using an\u0026nbsp;IRSpirit spectrometer equipped with a QATR-S module (Shimadzu, Japan).\u0026nbsp;Surface area and porosity were determined using a Brunauer-Emmett-Teller (BET) analysis with a surface area analyzer (ASAP 2010,\u0026nbsp;Micromeritics, Norcross, GA). Electron energy loss spectroscopy (EELS) was performed in conjunction with HR FE-TEM (JEM-2200FS with Image Cs Corrector, JEOL, Japan) to investigate the elemental distribution and chemical composition of the nanobots at high resolution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantification of immobilized\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eenzymes on the nanobots.\u0026nbsp;\u003c/strong\u003eThe concentration of catalase and glucose oxidase immobilized on the nanobots was quantified using the Pierce\u0026trade; BCA Protein Assay Kit (Thermo Fisher Scientific, Waltham, MA), following the manufacturer\u0026rsquo;s protocol. A standard curve was generated using serial dilutions of bovine serum albumin (BSA, 0-2 mg mL\u003csup\u003e-1\u003c/sup\u003e). To remove unbound enzyme, the nanobots were centrifuged and washed three times with PBS. The enzyme-coated nanobots were resuspended in DI water and mixed with the BCA working reagent in a 96-well plate, followed by incubation at 37\u0026deg;C for 30 min. Absorbance was measured at 560 nm using a microplate reader (SpectraMax ABS, Molecular Devices, San Jose, CA), and protein concentration was calculated based on the BSA standard curve.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEnzyme activity assay.\u0026nbsp;\u003c/strong\u003eThe enzymatic activity of catalase and glucose oxidase immobilized on the nanobots was measured using Catalase Activity Assay Kit (A319666,\u0026nbsp;Antibodies.com, UK) and Glucose Oxidase\u0026nbsp;Activity Assay Kit (A319680, Antibodies.com, UK). Catalase activity was determined by measuring the decomposition rate of H₂O₂, while glucose oxidase activity was assessed based on the amount of H₂O₂ generated during the oxidation of glucose. Each assay was performed according to the manufacturer\u0026rsquo;s instructions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSingle motion analysis of a nanobot.\u0026nbsp;\u003c/strong\u003eAn inverted microscope (DMi8, Leica Microsystems, Germany)\u0026nbsp;was used to observe and record the movement of nanobots. The nanobot solutions were placed on a petri dish and mixed well with glucose solution at concentrations of 0, 50, 100, and 250 mM. The movement of nanobots in\u0026nbsp;a glucose solution was recorded for 120 s at a frame rate of 25 fps in bright field. The tracking path and mean-squared displacement (MSD) were automatically analyzed using Python software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSwarming behavior of nanobots.\u0026nbsp;\u003c/strong\u003eThe swarming behavior of nanobots was assessed with an optical microscope equipped with a Hamamatsu high-sensitivity\u0026nbsp;CCD camera.\u0026nbsp;For that purpose, a petri dish was filled with 5 mL of either PBS or a glucose solution in PBS (50, 100, and 250 mM) and placed in the optical microscope. A 5 \u0026micro;L drop of the nanobots was then added carefully to the Petri dish, and 120-s\u0026nbsp;videos were acquired at a frame rate of 25 fps. The density maps and particle image velocimetry (PIV) were obtained by using ImageJ. The expansion area was measured by converting grayscale images into binary images and subsequently summing the pixels with intensity values above a certain threshold.\u0026nbsp;For PIV analysis, the video frames were converted into binary images. Then, cross-correlation analysis was performed with 64 interrogation window sizes. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFluorescent labeling of nanobots\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eFor fluorescence labeling, FITC was used for glucose oxidase-based nanobots, and RITC was used for catalase-based nanobots. Dye solutions (0.5 mg mL\u003csup\u003e-1\u003c/sup\u003e in DI water) were added to 1 mg of nanobots, respectively. The mixtures were incubated on an end-to-end rotary shaker in the dark at room temperature for 2 h. The labelled nanobots were washed three times with DI water, and the final particles were collected by centrifugation at\u0026nbsp;1,150 g\u0026nbsp;for\u0026nbsp;5 min.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eChemotaxis test in a microchip.\u0026nbsp;\u003c/strong\u003eA custom-designed three-channel fluidic mold was fabricated using a 3D printer (MakerBot SKETCH standard, MakerBot, Brooklyn, NY) to simulate a directional chemical gradient environment. The mold was printed using PLA filament and had final dimensions of 72 \u0026times; 30 \u0026times; 13 mm. This mold was used to cast an agarose-based fluidic system by pouring a 1% (w/v) agarose solution into a 6 cm Petri dish and allowing it to solidify at 4 \u0026deg;C for 1 h. The side channels of the three-lane fluidic system were filled with GOx nanobots in glucose and DI, and the central channel was filled with only DI. FITC-labelled catalase nanobots (2 \u0026mu;L) were introduced into the central channel. To evaluate the chemotactic behavior of catalase nanobots in response to an H₂O₂ gradient, three experimental conditions were tested: (1) glucose + GOx nanobot, (2) DI + GOx nanobot, (3) H₂O₂ solution. Their displacement was monitored using an optical microscope with an external fluorescence light source (EL6000, Leica Microsystems, Germany).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNavigation test in a microchannel.\u0026nbsp;\u003c/strong\u003eA fluidic mold was fabricated using a 3D printer with dimensions of 17 \u0026times; 12 \u0026times; 6 mm. The mold was designed to mimic the convoluted geometry of the intestinal tract. Using this mold, a PDMS-based fluidic system was fabricated. PDMS prepolymer was prepared by mixing the base and curing agent at a 10:1 ratio (w/w). The mixture was then poured over the mold and cured at 70 \u0026deg;C for 4 h. After curing, the PDMS was peeled off and treated with ozone plasma for 15 min to increase surface hydrophilicity. The resulting PDMS fluidic channel was filled with either glucose solution (50 mM) or DI water. A 5 \u0026mu;L drop of FITC-labelled nanobot solution (1 mg mL\u003csup\u003e-1\u003c/sup\u003e) was introduced into the inlet, and the directional motion of nanobots was observed under an optical microscope. The displacement of the nanobots was measured to assess motility under different chemical environments.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOxygen scavenging test.\u0026nbsp;\u003c/strong\u003eThe motility of nanobots was evaluated in a PDMS-based fluidic channel filled with 50 mM glucose solution. A 5 \u0026mu;L drop of\u0026nbsp;FITC-labelled\u0026nbsp;nanobot solution (1 mg\u0026nbsp;mL\u003csup\u003e-1\u003c/sup\u003e) was introduced at the inlet of the channel, and their displacement was monitored using an optical microscope with an external fluorescence light source for FITC and RITC excitation. To assess oxygen dependency, an oxygen scavenger, sodium sulfite (1 mM), was added to the system to create a hypoxic environment. The movement of nanobots was recorded and analyzed to evaluate the catalytic communication between the swarms.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDissolved oxygen test\u003c/strong\u003e\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eTo evaluate the oxygen-releasing capability of nanobots through H₂O₂ decomposition, the swarm solution was first purged with nitrogen gas to remove remaining dissolved oxygen. After complete deoxygenation, 50 \u0026mu;L of 25 mM H₂O₂ solution was added to initiate the enzymatic reaction. The generation of oxygen was continuously monitored over 10 min using a dissolved oxygen meter (DO9100, JC Instruments, Australia) under ambient temperature. To evaluate the oxygen-releasing capability of the nanobots, a swarm solution was prepared under ambient conditions without prior deoxygenation. The enzymatic reaction was initiated by the addition of 400 \u0026mu;L of 250 mM glucose solution.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn vivo\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ebioluminescence imaging.\u0026nbsp;\u003c/strong\u003eEight-week-old male nude mice were randomly divided into two groups: one with and one\u0026nbsp;without fuels. All mice were anesthetized via inhalation. Prior to the administration of samples, 100 \u0026mu;L of DI water was intrarectally injected to remove residual fecal matter from the intestine. Subsequently, 70 \u0026mu;L of RITC-labeled nanobot solution was administered intrarectally with and without glucose (250 mM).\u0026nbsp;The intestines were carefully excised from the mice after 30 min. The extracted intestinal tissues were gently rinsed with phosphate-buffered saline (PBS) and visualized using an in vivo imaging system (IVIS).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIn vivo\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePA imaging.\u0026nbsp;\u003c/strong\u003ePA imaging was performed using a developed PA computed tomography system\u003csup\u003e52,53\u003c/sup\u003e. An optical parametric oscillator (OPO) laser (PhotoSonus M-20, Ekspla,\u0026nbsp;Lithuania) with a 20 Hz pulse repetition rate and a wavelength range of 690-1064 nm illuminated the target through a customized fiber bundle. The PA signal was detected by a 1024-element hemispherical array transducer (Japan Probe, Japan), and then the signal was processed by the data acquisition (DAQ) system (Vantage 256, Verasonics, Kirkland, WA). Mouse images were captured by raster scanning using a 3-axis motorized system (LSQ150A, Zaber, Canada) with the custom-built mouse holder and anesthesia mask. The PA images were reconstructed using a customized reconstruction algorithm built in MATLAB. The mouse imaging was performed using 780 and 900 nm illumination and was conducted at the pre-injection of the material and every 3 min from 0 to 30 min after injection. Depth-encoded images were generated through 3D PHOVIS\u003csup\u003e54\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIBD model preparation\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;and treatment.\u003c/strong\u003e Eight-week-old male nude mice were used to establish an IBD model. Colitis was induced by providing 3% (w/v) DSS in drinking water for 5 consecutive days. Control group mice received sterile water instead of DSS during the same period. The disease activity index (DAI) was monitored daily by assessing body weight loss (scored 0-4), stool consistency (scored 0-4), and the presence of fecal blood (scored 0-4). These parameters were recorded throughout the DSS feeding and treatment periods to evaluate disease progression.\u0026nbsp;To assess both the preventive and therapeutic effects of nanobots in IBD, two separate experimental timelines were established. In the preventive model, drugs were administered intrarectally on 0 and 2 d, concurrently with DSS treatment, to assess the progression of colitis. In contrast, the therapeutic model involved drug administration on days 4 and 6, following DSS-induced damage, to examine the recovery of inflamed tissue. All treatments were performed under light isoflurane anesthesia to minimize discomfort. The treatment groups included nanobot without glucose (70 \u0026mu;L, 1 mg mL\u003csup\u003e-1\u003c/sup\u003e), nanobot with glucose (70 \u0026mu;L, 1 mg mL\u003csup\u003e-1\u003c/sup\u003e), and PBS. On day 9, the entire colon was excised, and the colon length was measured to assess the severity of colitis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHistological analysis of mouse colonic tissues.\u003c/strong\u003e The collected colon samples were subjected to H\u0026amp;E staining and TUNEL staining (Abcam, UK). The histological samples were scored based on the histological severity, including evaluation of neutrophilic and mononuclear infiltrates (scored from 0 to 3), epithelial architecture damage (scored from 0 to 3), muscle thickening (scoring from 0 to 3), goblet cell depletion (scoring from 0 to 1), and crypt abscess (scoring from 0 to 1). For immunofluorescence imaging of ZO-1 and occludin, HIF-1 alpha proteins on mouse colonic tissues, sub-centimeter colonic tissues were fixed in 4% paraformaldehyde and embedded in a paraffin block. Before immunofluorescence staining, the colonic tissue samples were dehydrated and subjected to heat-induced antigen retrieval. After blocking with 2% BSA solution, the samples were stained with Alexa Fluor\u003csup\u003e\u0026reg;\u003c/sup\u003e 488 mouse anti-ZO-1 antibodies (5 \u0026mu;g mL\u003csup\u003e-1\u003c/sup\u003e), Alexa Fluor\u0026reg;\u0026nbsp;594 mouse anti-occludin antibodies (1 \u0026mu;g mL\u003csup\u003e-1\u003c/sup\u003e), and\u0026nbsp;Alexa Fluor\u0026reg; 488 anti-HIF-1 alpha antibody (10\u0026nbsp;\u0026mu;g mL\u003csup\u003e-1\u003c/sup\u003e) overnight at 4\u0026deg;C. For nucleus staining, the samples were stained with DAPI for 15 min at room temperature.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eELISA for mouse colonic tissues.\u003c/strong\u003e An enzyme-linked immunosorbent assay (ELISA) was conducted to measure the levels of pro-inflammatory and anti-inflammatory cytokines in the colon tissue of each group. The colon was placed on ice for homogenization with an extraction buffer. The colon was homogenized at 4\u0026deg;C for 2 h and then centrifuged at 15,000 g and 4\u0026deg;C for 20 min to collect the supernatant. The concentration of IL-1\u0026beta; (Cat. ab214025, Abcam, UK), IL-6 (Cat. ab178013, Abcam, UK), IL-10 (ab185986, Abcam, UK), and TNF-\u0026alpha; (Cat. ab181421, Abcam, UK) was analyzed according to the manufacturer\u0026apos;s instructions (Abcam, UK).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis.\u0026nbsp;\u003c/strong\u003eStatistical analysis was carried out via the Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e-test using the software of SigmaPlot14.5 (Systat Software Inc., San Jose, CA). The values for *\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01, ***\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.005, and ****\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001 were considered statistically significant. Data are expressed as means \u0026plusmn; standard deviation (SD) from several separate experiments.\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eReporting summary\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFurther information on research design is available in the Nature Portfolio Reporting Summary linked to this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe raw data of intensity and covering area from the density map are available from the authors upon request. Source data are provided with this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was supported by the BRIDGE Research Program (RS-2022-NR067643) and (RS-2024-00460035) (H.C.) of the National Research Foundation (NRF) funded by the Ministry of Science and ICT, Korea. This research was also supported by the Korea Medical Device Development Fund grant (RS-2023-00253749) and the NRF B-IRC grant (RS-2023-00260454) funded by the Korean government. This work was supported by the European Research Council (ERC) under the European Union\u0026rsquo;s Horizon 2020 research and innovation programme (grant agreement No. 866348; i-NanoSwarms)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u0026nbsp;information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH.C.\u0026nbsp;and Y.S. contributed equally to this work.\u0026nbsp;S.K.H. and S.S. conceived the idea. S.K.H. and S.S. supervised the project, designed the experiment, and wrote the manuscript. H.C. and Y.S. performed all the in vitro experiments. C.K., J.K., and H.J. performed the in vivo PA imaging. H.C., Y.S., and S.M.Y. performed in vivo experiments. H.C. and Y.S.\u0026nbsp;wrote the manuscript. All authors contributed to the scientific discussion and editing of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to [email protected] (S. K. H.) and [email protected] (S. S.) \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBattiston, F. et al. The physics of higher-order interactions in complex systems. \u003cem\u003eNat. Phys.\u003c/em\u003e\u003cstrong\u003e17\u003c/strong\u003e, 1093\u0026ndash;1098 (2021).\u003c/li\u003e\n\u003cli\u003eshim, G., Devenport, D. \u0026amp; Cohen, D. J. Overriding native cell coordination enhances external programming of collective cell migration. \u003cem\u003eProc. Natl\u003c/em\u003e\u003cem\u003e.\u003c/em\u003e\u003cem\u003e Acad. Sci. 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Here, we report a tandem enzymatic communication system between glucose oxidase and catalase-powered nanobot swarms for the treatment of inflammatory bowel disease (IBD). We verify in vitro coordinated swarm behavior produced by coupling propulsion through an enzymatic cascade in microchips. After intrarectal injection in mice, the collective behavior of swarms is assessed in the context of peristalsis using photoacoustic imaging, demonstrating the effective navigation of swarms within the colon. In addition, we confirm the remarkable recovery of the damaged colon, characterized by comparable levels of proinflammatory cytokines and enhanced anti-inflammatory cytokines, in both prevention and delayed treatment regimens in IBD model mice. Taken together, the tandem communication system would be harnessed as a next-generation platform for various intractable diseases, including colorectal diseases.","manuscriptTitle":"Tandem Enzymatic Swarm Communication Enables Collective Nanobot Therapy in Inflammatory Bowel Disease","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-14 08:45:08","doi":"10.21203/rs.3.rs-7461471/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"60e081eb-61fb-4204-832d-a77d8b7dbd4a","owner":[],"postedDate":"November 14th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57925344,"name":"Biological sciences/Biotechnology/Nanobiotechnology"},{"id":57925345,"name":"Biological sciences/Biotechnology/Biomaterials"}],"tags":[],"updatedAt":"2025-12-05T13:53:05+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-14 08:45:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7461471","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7461471","identity":"rs-7461471","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}