Acceleration of DNA reactions on the algae-based microrobots

Abstract

DNA reactions on solid surfaces often suffer from low efficiency due to limited mass transfer and slow reaction kinetics, which greatly limits their biomedical applications. Here, we report a strategy to construct dynamic DNA biointerfaces based on moveable algal microrobots (AMs), whose autonomous motion-generated micro-hydrodynamics profoundly affects interfacial DNA reactions. After immobilizing DNA strands on the AMs, we uncover that the swimming speed of these microrobots is positively correlated with the kinetics of different DNA reactions from simple hybridization to complex enzymatic/nonenzymatic amplification reactions. This “motion-enhanced” effect mainly stems from the convection and mixing generated around the swimming cells, which greatly improve mass transfer velocity, thereby reducing hybridization times to minutes and enhance reaction efficiency. As a result, this feature is demonstrated to be useful in achieving ultrafast molecular recognition, ultrasensitive nucleic acid detection, and autonomous cell assembly in complex biological media. Our work provides a paradigm shift for overcoming the reaction efficiency bottleneck of DNA interface and paves a new avenue for designing intelligent bio-hybrid systems.

Graphical abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s12951-026-04646-1.

Introduction

Microrobots are miniature materials that convert local fuels or diverse external energies to autonomously propel themselves [1–4]. The small size of microrobots enables them to navigate complex environments and execute biomedical tasks in a much more intelligently [5–6]. Among them, algae-based microrobots are particularly attractive because of their unique properties such as self-propulsion without external actuation, easy operation, low cost, and high sustainability and biocompatibility [7–10]. To endow algae microrobots with biological functionalities, they are frequently decorated with synthetic functional elements (e.g., nanoparticles, proteins, or drugs), and the resulting biohybrid microrobots can fulfill complex biomedical tasks, including transporting drugs to tumors [11–12], penetrating mucus for enhanced retention [13], accumulating in the dysfunctional sites [14], and collecting virus nanoparticles [15], which holds great potential in biomedical and environmental applications.

Beyond genetic information, DNA has emerged as an excellent molecular toolkit because of its highly predictable interactions and multifunctionality. Typically, DNA molecules can be modified on the surface of solid materials for endowing them with additional functionalities such as molecular recognition, controllable assembly, biocomputation, signal transduction, and cargo loading [16–19]. However, a long-lasting challenge of DNA-based biointerfaces is their compromised communication efficiency with the external environment mainly caused by surface defects, steric hindrance, and a slow vertical diffusion process. For example, the hybridization efficiency of DNA probes at solid surfaces is significantly lower than that in homogeneous solutions, thus leading to low sensitivity and long detection time of DNA-based biosensors. To increase the kinetics and thermodynamics of DNA-based interfaces, much effort has been devoted to optimizing the DNA density and surface chemistry, constructing three-dimensional DNA nanostructures, accelerating mass transfer velocity of solution, and incorporating nanoscale structures into the sensing surface [20–24]. Despite much progress, the majority of reports still focus on the development of static DNA-based bio-interfaces, which cannot break the bottleneck mentioned above.

Over million years of evolution, cells have incredible information processing ability to precisely respond to target molecules even in complex biological environment. This inspired us to explore the DNA reactions on moveable plant microrobots, which probably show distinct reaction kinetics different from traditional inorganic/organic interfaces. Herein, we report an efficient strategy to construct DNA-functionalized algae-based microrobots and then perform three representative DNA reactions on the algae surface, from simple hybridization reactions to complex amplification reactions. Interestingly, the efficiency of DNA reactions is profoundly influenced by the movement behavior of algae cells. Consequently, this feature is demonstrated to be useful in achieving ultrafast molecular recognition and cell assembly. Compared with the extensively studied DNA reactions on the static solid surfaces, movable plant microrobots build a unique microenvironment for DNA hybridization and amplification, which adds another piece of puzzle in constructing advanced DNA-cell architectures for advanced bio-applications. To the best of our knowledge, this is the first example of the fabrication of moveable DNA-algae architectures and exploration of their use in the field of biomedicine.

Methods

Algae culture

Dunaliella salina (D. salina, GY-H13) Chlamydomonas reinhardtii (GY-D8), Isochrysis galbana (GY-H3), and Platymonas sp. (GY-H5) were obtained from Shanghai Guangyu Biological Technology Co., Ltd. D. salina was used in this study. The algae were cultivated in Guillard F/2 medium. The cultures were maintained at 25 °C under a 16:8 h light: dark cycle with a light intensity of approximately 5500 lx provided by lamps. The cultures were shaken manually twice daily and subcultured every 7 days to maintain logarithmic growth phase.

Preparation of DNA-functionalized algae microrobots (DNA-AMs)

Algae cells in the logarithmic growth phase were harvested by centrifugation at 800 × g for 5 min at 25 °C. The cell pellet was washed twice with and resuspended in PBS pH 7.4) to a final density of 7.5 × 10⁵ cells mL^− 1.

To enhance DNA loading, chitosan (Chi, medium molecular weight, Sigma-Aldrich), polyethyleneimine (PEI, Aladdin), or poly(allylamine hydrochloride) (PAH, Aladdin) were added to the algae suspension at a final concentration of 0.1 mg mL^− 1. The mixture was incubated at room temperature for 30 min. The Chi-coated algae (AMs@Chi) were collected by centrifugation (1000 × g, 5 min) and washed twice with PBS to remove excess polymer. The cationic polymer-coated algae (AMs@cationic polymer) were then collected by centrifugation (1000 × g, 5 min) and washed twice with PBS to remove excess polymer.

The AMs@cationic pellets were resuspended in PBS. A heterobifunctional crosslinker, NHS-PEG₄-Azide (Thermo), was added to the AMs@cationic polymer at a final concentration of 40 µM and incubated for 1 h at room temperature to react with the primary amines on the chitosan and algal surface. After incubation, the cells were washed three times with PBS to remove unreacted linker. All used oligonucleotides (Table S1) were synthesized by Sangon Biotech Co., Ltd. Shanghai. The pellets were then resuspended in PBS, and FAM-labeled DBCO-modified DNA strands were added at a final concentration of 1 µM. The click chemistry reaction was allowed to proceed for 2 h at room temperature. The resulting DNA-AMs were washed three times with PBS to remove free DNA strands and stored in PBS for further use. After washing to remove unbound DNA, fluorescence quantification confirmed that an average of 5.5 × 10⁶ DNA stands were fixed per algal cell.

Characterization and stability assessment of DNA-AMs

Scanning electron microscopy (SEM, Zeiss Sigma 500) was used to examine algal surface morphology pre- and post-modification. Stability of DNA-AMs was evaluated in PBS, blood, urine, and saline over 48 h, assessing both algal viability (SYTOX Green staining) and DNA retention (fluorescence intensity measurement).

The surface charge of native algae and polymer-coated algae was measured using a Malvern Zetasizer Nano ZS instrument. Samples were diluted in PBS to an appropriate concentration for measurement.

For scanning electron microscopy (SEM) characterization, algae samples were fixed with 2.5% glutaraldehyde in PBS overnight at 4 °C. The fixed cells were then dehydrated through a graded ethanol series (30%, 50%, 70%, 80%, 90%, 95%, and 100%), each for 10 min. After critical point drying and gold sputtering, the samples were imaged using a field-emission scanning electron microscope (Hitachi SU8100).

In the stability study, DNA-AMs were incubated in different biological media: PBS, 10% fetal bovine serum (FBS), human urine, and saliva at 25 °C. Algal viability was assessed at 12 h and 48 h using a live/dead staining kit (SYTO 9 for live cells, Thermo) and counted with a hemocytometer under a fluorescence microscope (Nikon Eclipse Ti2). The fluorescence intensity of FAM-labeled DNA on DNA-AMs was monitored daily for up to 7 days using a spectrofluorometer to evaluate DNA retention. FAM-labeled DBCO-DNA was used to quantify DNA loading density via fluorescence microscopy (Olympus BX51) and flow cytometry (Beckman Coulter, CytoFLEX).

Motion control and analysis of algae

To regulate the swimming speed of DNA-AMs, cells were treated with different chemicals. For fast-moving AMs, adenosine triphosphate (ATP) was added to the PBS suspension at a final concentration of 50 µM and incubated for 20 min before experiments. For slow-moving AMs, sodium malonate was added at a final concentration of 80 µM and incubated for 20 min. Normal-moving AMs were untreated and kept in PBS.

A 10 µL aliquot of algae suspension was placed on a glass slide. The movement of algae cells was recorded for 1 min using a high-speed camera mounted on an optical microscope. The videos were analyzed using ImageJ with the MTrackJ plugin. The trajectories and instantaneous velocities of at least 50 individual cells from each group were analyzed to determine the average speed.

DNA hybridization kinetics on motile algae

The DNA hybridization kinetics experiments of motile algae and other candidates (i.e., silicon oxide microspheres and polystyrene microspheres) were performed using a fluorescent molecular beacon approach. The capture strand (DNA a) was immobilized on the algal surface. The target was a complementary single-stranded DNA (ssDNA) reporter (100 nM) labeled with a fluorophore (FAM) and quencher (BHQ1) at its two ends, forming a hairpin structure where fluorescence is quenched. Upon hybridization with the surface-bound capture strand, the hairpin opens, separating the fluorophore and quencher, resulting in fluorescence recovery.

For endpoint analysis via flow cytometry, 100 µL aliquots were taken from the bulk reaction mixture at specific time points (e.g., 0, 10, 20, 30, 40, 60 min), diluted with 400 µL of PBS, and immediately analyzed on a flow cytometer (measuring fluorescence in the FITC channel). The mean fluorescence intensity (MFI) of 10,000 events per sample was recorded.

DNA-AMs with different motilities (final concentration ~ 7.5 × 10⁵ cells mL^− 1) were incubated with the 100 nM FAM-labeled reporter in PBS (pH 7.4) at 25 °C under gentle shaking. For real-time kinetic monitoring using a spectrofluorometer, 200 µL of the reaction mixture was placed in a microcuvette, and the FAM fluorescence intensity was measured continuously. Then, the fluorescence intensity data over time was used to plot hybridization kinetic curves.

The hybridization efficiency at time t was calculated as: Hybridization Efficiency = (F_max − F₀)/k ⋅ N_cells ⋅ [P_max], where F₀ is the initial fluorescence intensity, F_max is the maximum fluorescence intensity reached at the plateau, k is the calibration factor, N_cells is the number of algal cells, [P_max] is the maximum number of DNA a molecules immobilized per algal cell.

Based on the law of mass action, the equilibrium constant (K’) for DNA hybridization reaction was calculated as follows: K’ = [H] / ([P_max]−[H]) ⋅ [T], where [H] is the concentration of bound ssDNA (molecules/cell), and [T] is the concentration of free ssDNA.

Computational fluid dynamics simulation

To investigate the influence of algal microrobot motion on its surrounding flow field structure, we employed computational fluid dynamics with a dynamic meshing technique to transiently simulate its self-propulsion. A simplified three-dimensional model representing the algal cell was first constructed and placed at the center of a rectangular computational domain. The domain dimensions were carefully designed to ensure that the boundaries did not interfere with the flow development near the cell surface. The domain was discretized using an unstructured tetrahedral mesh, with local refinement applied around the algal model to accurately resolve the boundary layer effects.

Then, the autonomous motion of the algae was implemented using the dynamic mesh model in Fluent. We defined three different uniform linear motions to simulate the slow (~ 10.3 μm/s), normal (~ 97.2 μm/s), and fast (~ 167.3 μm/s) movement modes observed experimentally. Mesh update was achieved using the diffusion-based smoothing method, which smoothly adjusts the positions of interior nodes based on boundary displacement, thereby accommodating the domain deformation caused by the algae’s motion while preserving mesh quality.

A pressure-based transient solver was selected. Given the microscopic scale of the algal motion, the flow field is in a low Reynolds number regime; consequently, a laminar flow model was adopted. The pressure-velocity coupling was handled by the PISO scheme, which is well-suited for transient flow simulations. The simulation commenced after the algae reached its designated constant velocity and continued for a sufficient duration to capture a fully developed flow field. Upon completion of the simulations, the velocity and pressure field distributions around the algae at different swimming speeds were extracted. Qualitative and quantitative analyses of the vortex structures at the head and tail of the algae were performed by visualizing streamlines and velocity contours. Furthermore, a grid independence study was conducted to ensure the accuracy of the simulation results was not influenced by mesh density.

HCR on algal microrobots (HCR-AMs)

DNA-AMs (capture strand-modified) were incubated with the target miRNA-143 (at varying concentrations for detection) in hybridization chain reaction (HCR) buffer (500 mM NaCl, 50 mM Tris-HCl, pH 7.5) for 15 min at 25 °C to allow hybridization. Then, two fluorescent hairpin DNA strands (H1 and H2, each at a final concentration of 50 nM) were added to the mixture. The HCR reaction was allowed to proceed for 60 min at 25 °C. The reaction was stopped by diluting the sample with ice-cold buffer and washing the cells twice. The fluorescence intensity of the HCR-AMs was measured by fluorescence spectroscopy, flow cytometry, or observed under a fluorescence microscope.

For real sample analysis, serum samples from bladder cancer patients and healthy controls were diluted 10-fold with HCR buffer and spiked with known concentrations of synthetic miRNA-143 for calibration or used directly for blind testing. The fast-moving HCR-AMs system was used, and the fluorescence ratio (FL₅₃₀/FL₇₁₅) was calculated, where FL₅₃₀ is the FAM fluorescence from HCR and FL₇₁₅ is the chlorophyll autofluorescence of the algae serving as an internal reference.

Rolling circle amplification on algal microrobots (RCA-AMs)

DNA-AMs (primer strand-modified) were washed and resuspended in rolling circle amplification (RCA) reaction buffer (50 mM Tris-HCl). The circular template DNA (Cri, 50 nM), dNTPs (250 µM each, including Alexa Fluor 488-dUTP for fluorescent detection), and phi29 DNA polymerase (0.5 U µL^− 1) were added to the suspension. The reaction mixture was incubated at 30 °C for 40 min to 2 h. Following incubation, the reaction was terminated by centrifugation at 1000 × g for 3 min to separate the DNA-AMs from the reaction solution. The RCA-AMs were then washed three times with PBS to remove excess reagents. The formation of RCA products was verified by agarose gel electrophoresis (after releasing the products from the cells) and fluorescence microscopy.

Algal assembly and disassembly

Two populations of RCA-AMs were prepared: RCA-AMs a (displaying multi-repeat sequence a) and RCA-AMs b (displaying complementary multi-repeat sequence b). RCA-AMs b were pre-stained with Calcein-AM (green). The two populations were mixed at a 1:1 ratio (total cell density ~ 2 × 10⁶ cells mL⁻¹) in PBS and incubated at 25 °C for 30–60 min without agitation. The assembly process was monitored in real-time using optical and fluorescence microscopy. For disassembly, an excess of free single-stranded DNA complementary to sequence a (a*, 10 µM) was added to the assembled clusters and incubated for 30 min.

Cell culture

The human bladder cancer cell line HT1197 was cultured in Eagle’s minimum essential medium (EMEM). The medium was supplemented with 10% (v/v) heat-inactivated fetal bovine serum (FBS), 1% (v/v) non-essential amino acids (NEAA), 100 U mL^− 1 penicillin, and 100 µg mL^− 1 streptomycin. The human normal uroepithelial cell line SV-HUC-1 was cultured in F-12 K Medium (Kaighn’s Modification of Ham’s F-12 Medium). The medium was supplemented with 10% (v/v) heat-inactivated FBS, 100 U mL^− 1 penicillin, and 100 µg mL^− 1 streptomycin. All Cells were maintained in a humidified incubator at 37 °C with 5% CO₂. The culture medium was refreshed every 2–3 days.

Capture of exfoliated tumor cells using ETC-AMs

For the specific capture of tumor cells, RCA-AMs functionalized with EpCAM aptamers (ETC-AMs) were prepared. The circular template DNA was designed to incorporate sequences encoding the EpCAM-targeting aptamer. The RCA reaction was performed as described above. The resulting ETC-AMs were co-incubated with a suspension of target tumor cells (HT1197, pre-stained with Calcein-AM) and non-target control cells at a 10:1 ratio in urine for 60 min at 25 °C with gentle shaking. The formation of cell-algae clusters was observed under a microscope. Capture efficiency was calculated as (Number of tumor cells in clusters / Total number of tumor cells) × 100%.

Statistical analysis

All experiments were performed in triplicate. Data are presented as mean ± standard deviation. One-way Analysis of Variance (ANOVA) was used for comparisons. A P-value < 0.05 was considered statistically significant.

Results

Preparation and characterization of DNA-modified AMs

We first developed a polymer-assisted strategy to modify DNA strands on the surface algae cells, as shown in Fig. 1a. In this method, algae cells were coated with a positively charged polymer to increase the amino density, and then covalently conjugated with dibenzocyclooctyne (DBCO)-labeled DNA strands using a biofunctional linker (i.e., (N-hydroxysuccinimide) NHS-PEG4-azide). After removing excess DNA strands, DNA-modified AMs (DNA-AMs) could be obtained for subsequent use [25].

Fig. 1.

Preparation and characterization of DNA-AMs. (a) A schematic illustration of fabricating DNA-AMs. (b) Representative bright-field (BF) and fluorescent images of different AMs after modifying polymers and FAM-labeled DNA. Scale bar, 40 μm. (c) Flow cytometry histograms of different AMs after modifying polymers and FAM-labeled DNA. FAM-labeled DNA fluorescence is measured using the FITC channel. (d) Comparison of DNA density on the surfaces of different AMs after modifying polymers. (e) Representative SEM image of a DNA-AM. (f) Survival rate of DNA-AMs incubated with PBS, blood, urine, and saliva samples for 12 h. (g) DNA fluorescence changes of DNA-AMs incubated with PBS, blood and urine for 7 days. All data are presented as means ± standard deviation (S.D.), n = 4. Statistical analysis was conducted via ordinary one-way ANOVA with Tukey’s post hoc test. **P < 0.01; ****P < 0.0001; NS, no significance

Considering the potential applications of AMs in biological media, movable algae cells, including Chlamydomonas reinhardtii (C. reinhardtii), Dunaliella salina (D. salina), Isochrysis galbana (I. galbana), and Platymonas sp. were tested in this study. Among them, D. salina had a high survival rate over 80% after being cultured in physiological saline for 5 days, indicating its strong physiological adaptation (Figure S1). Thus, D. salina was chosen as the AMs material for later use. For DNA modification, D. salina has a malleable membrane without a cell wall, so a biofunctional linker was used to conjugate DBCO-modified DNA with the amino groups of proteins on the cell membrane via click chemistry. To demonstrate this, a short DNA strand labeled with a fluorophore (i.e., 5-Carboxyfluorescein, FAM) was used, and the resulting DNA-modified algae cells could be simply analyzed using fluorescence microscopy (Fig. 1b) and flow cytometry (Fig. 1c). However, compared with native algae cells, the FAM fluorescence of the DNA-modified AMs was rather weak, suggesting a low DNA density owing to the electrostatic repulsion and the limited number of amino groups on the membrane.

To address this problem, we employed three commonly used cationic polymers, namely polyethyleneimine (PEI), poly(allylamine hydrochloride) (PAH), and chitosan (Chi), to shield the intrinsic negative charge and enhance the amino density on the cell membrane [26]. After pretreatment with cationic polymers, the surface charge of the modified algae cells was − 13.64 mV (AMs@PEI), -10.35 mV (AMs@PAH), and + 2.36 mV (AMs@Chi), respectively (Figure S2), suggesting the successful surface coating of these polymers on the algae. Then, we examined the DNA modification on these polymer-coated AMs. Obviously, all of them showed detectable FAM fluorescence (Fig. 1b, c), suggesting the improved loading of DNA molecules. Of note, this decoration was not owing to the electrostatic interaction between DNA strands and cells since the solution had a high concentration of salt (NaCl, 100 mM) that efficiently shielded electrostatic force. We also found that Chi modification generated the largest FAM fluorescence compared with other groups, and the DNA density on a single cell was estimated to be 5.5 × 10⁶ strands, which was 7.6-fold higher than the DNA-modified AMs without polymer coating. Thus, we used Chi-coated AMs for DNA conjugation, and the resulting product was named DNA-AMs.

The morphologic structure of algae remained unchanged after modifying Chi and DNA, as demonstrated by scanning electron microscopy (Fig. 1e and Figure S3). Also, the survival rate and DNA stability of DNA-AMs were evaluated. As shown in Fig. 1f, DNA-AMs was incubated with complex biological media-including PBS, blood, urine and saliva-for 12 h, and its survival rate remained above 60% in all conditions, indicating that Chi modification did not affect cell motion and survival. Meanwhile, the DNA fluorescence of DNA-AMs dispersed in different media was monitored continuously. The fluorescence signal of DNA-AMs in a pure buffer and urine remained stable, and above 75% DNA signal was retained (Fig. 1g). When DNA-AMs were challenged with serum, above 50% fluorescence could still be detected after 7 days. As a comparison, DNA molecules modified on the mammalian cells were only remained within several hours [27]. Thus, these results verified the high stability of DNA molecules modified on the algae cells, making DNA-AMs a potential candidate for biological applications.

The DNA hybridization reactions on the surface of DNA-AMs

After fabricating DNA-AMs, we investigated the characteristics of DNA reactions on the surface of AMs under different movement modes (Fig. 2a). D. salina is a bi-flagellate microalga, whose movement is highly dependent on the mitochondrial respiratory chain. Exogenous supplementation of adenosine triphosphate (ATP) can enhance the energy supply of D. salina and significantly increase their motility; conversely, sodium malonate, as a competitive inhibitor of succinate dehydrogenase, can inhibit intracellular ATP levels by blocking the tricarboxylic acid cycle and disrupting the activity of the respiratory chain, thereby inhibiting flagellar movement. Consistent with this mechanism, our optimization experiments demonstrated that the addition of ATP (50 µM) remarkably promoted the speed of DNA-AMs (Figure S5), whereas their movement was significantly slowed down by adding sodium malonate (80 µM) (Figure S6). Thus, AMs with three movement modes could be achieved, i.e. slow-, normal-, or fast-moving AMs. Through tracking the movement trajectory (Fig. 2a-c and movie S1), the movement speeds of slow-, normal-, or fast-moving AMs were determined to be 10.3, 97.2, and 167.3 μm/s (Fig. 2d, f), respectively. Of note, AMs without polymer and DNA modification showed the similar speed compared to normal-moving DNA-AMs (Figure S4), indicating that the modification process had a negligible effect on the algae motility.

Fig. 2.

DNA hybridization reaction on the surface of DNA-AMs. (a-c) Swimming speed analysis of AMs presented with three movement modes. (d, f) Representative trajectories of slow-moving AMs (d), normal-moving AMs (e), and fast-moving AMs (f) over 20 seconds in PBS at 25°C. (g) Schematic diagram of DNA hybridization reactions on the DNA-AMs with three movement modes. (h) Hybridization kinetic curves of slow-, normal-, and fast-moving DNA-AMs in the presence of FAM-labeled complementary ssDNA (100 nM), determined by a spectrofluorometer. (i) Flow cytometry analysis of slow-, normal-, and fast-moving DNA-AMs in the presence of FAM-labeled complementary ssDNA (100 nM) at different time points. (j) Comparison of hybridization efficiency of DNA-AMs under different movement modes. (k) Numerical simulation of the velocity field of a freely swimming DNA-AMs with different speeds in the laboratory frame. A color scheme indicates flow speed u magnitudes. is gravity. Scale bar, 40 µm. (l) Schematic diagram of using movable DNA-AMs for detecting target miRNA. (m) Calibration curves of DNA-AMs with different speeds for quantifying miRNA-155. The inset shows the fluorescence intensities of fast-moving DNA-AMs at low miRNA-155 concentration. The dashed line (black) indicates the LOD of fast-moving DNA-AMs. BKG, background. (n) Radar plot of miRNA detection performance (i.e., LOD, hybridization efficiency, and K’) of fast-moving DNA-AMs, DNA-modified silica microspheres and DNA-modified polyacrylamide microspheres. All data are presented as means ± standard deviation (S.D.), n = 4. Statistical analysis was conducted via ordinary one-way ANOVA with Tukey’s post hoc test. a.u., arbitrary units. **P < 0.01, ****P < 0.0001

To study DNA reactions on the AMs, we first tested the performance of DNA hybridization using a fluorescent DNA reporter. As shown in Fig. 2g, the DNA reporter had a hairpin structure tagged with a fluorophore (FAM) and a quencher (BHQ1), whose close distance caused fluorescence quenching. After binding to the capture strands modified on the AMs, the conformational change of reporters separated FAM and BHQ1, resulting in fluorescence recovery. As shown in Fig. 2h, the hybridization kinetics of DNA-AMs binding to the reporters determined by a spectrofluorometer demonstrated that movement speed dictated the reaction velocity. We observed fast-moving AMs gave the fastest DNA hybridization kinetics, which reached a saturated signal within 15 min even under a low concentration of reporter (10 nM), consistent with the flow cytometry results (Fig. 2i). Accordingly, the reaction equilibrium constant (K’) of the DNA hybridization reaction on the surface of fast-moving DNA-AMs was determined to be 2.38 × 10⁸ M^{− 1}, which was 2.5- asssnd 8.8-fold higher than that of normal- and slow-moving DNA-AMs. In parallel, the hybridization efficiency of DNA-AMs under three movement modes was determined (Fig. 2j), and fast-moving DNA-AMs also showed the highest hybridization efficiency (58.5%), thus verifying the unique advantages of fast movement in DNA hybridization. Of note, slow-moving DNA-AMs were determined to be ~ 10.7%, which is similar with other static DNA-modified biointerfaces [28]. To further explore the mechanism of DNA reactions on the AMs, we used the Three-Stokes-Rayleigh model to simulate the complex flow field topology around algal cells at different swimming speeds. Compared to slow- and normal-moving AMs, there were obvious toroidal convection near the surface of the fast-moving AMs (Fig. 2k). At microscopic interfaces, the limited DNA probes modified on the surface decrease the probability of collision and binding of the probes and target molecules. Thus, it is time-consuming to use a macrosensor to detect a low concentration of target or even impossible within a practical time scale [29–30]. Nevertheless, fast-moving AMs greatly enhanced local mixing, promoted fluid exchange, and reduced diffusion limitations. As a result, DNA-AMs could serve as an autonomous molecule collector and focus DNA strands nearby towards the surface of the cell, thereby accelerating DNA collision and hybridization. Collectively, DNA hybridization reaction on the AMs was demonstrated to be controlled by regulating the swimming speed of cells.

After clarifying the hybridization mechanism, we next used DNA-AMs to detect a disease-related biomarker. MicroRNA (miRNA) is a short RNA molecule that regulates various cellular activities, which is closely associated with many major diseases such as tumor, cardiovascular disorders, Alzheimer’s disease, and so on [31–32]. As a proof-of-concept study, we chose miRNA-155 as the target since it is a known bladder cancer biomarker in urine [33]. To detect miRNA, we designed a simple sensing strategy involving the formation of a target-mediated “sandwich” structure (Fig. 2l). As depicted in Fig. 2m, different concentrations of target miRNA could be quantitatively detected using the DNA-AMs with different movement modes. Obviously, fast-moving DNA-AMs showed the best detection performance compared with the other two groups. The limit of detections (LODs) of slow-, normal-, and fast-moving DNA-AMs were determined to be 1 nM, 100 pM, and 0.1 pM, respectively, based on the background signal plus three times the standard deviation (3 S.D.). We also prepared commonly used silica microspheres and polyacrylamide microspheres to detect the same miRNA target using the same sensing principle. To ensure a rigorous comparison, DNA-modified silica and polyacrylamide microspheres were selected as static controls because their geometric dimensions closely match those of the D. salina cells, maintaining a comparable surface area and isolating biological motility as the primary variable. The detection performance in terms of LOD, reaction equilibrium constant (K’), and hybridization efficiency is summarized in Fig. 2n. Although the DNA density on these surfaces was comparable, the performance of fast-moving DNA-AMs was obviously superior to these static inorganic/organic microspheres, further revealing the unique advantages of using movable motors in DNA sensing.

HCR reaction on the surface of DNA-AMs (HCR-AMs)

Having confirmed the positive effect of AMs movement on DNA hybridization, we next explored its role in a more complex system, i.e., Hybridization chain reaction (HCR). HCR, as an enzyme-free amplification method, has been widely used in biosensing, bioimaging, and biomedical fields [34]. Typically, HCR reaction involves two DNA hairpin strands to be cross-open by one initiator DNA strand, forming an ultra-long DNA structure. This process largely depends on the random collision and interaction between freely diffusing DNA strands in the solution, resulting in low reaction efficiency and requiring several hours to complete. Therefore, a major challenge for the HCR reaction is to improve the reaction efficiency.

As shown in Fig. 3a, DNA-AMs were used to capture target DNA, which could serve as initiator strands to activate HCR in the presence of a pair of fluorescent hairpin strands (H1 and H2). Initially, the electrophoresis results confirmed the formation of HCR products when H1, H2 and target miRNA were incubated together for 6 h, confirming the feasibility of HCR (Figure S7). Then, the reaction kinetic of HCRs on the DNA-AMs with different movement speeds was investigated. Similarly, HCR on the fast-moving AMs could be completed within 60 min, which was much faster than the other two groups (Fig. 3b), suggesting that the rapid movement speed could also accelerate HCR. The reaction equilibrium constant of HCR on the slow-, normal-, and fast-moving AMs was 5.78 × 10⁶ and 1.87 × 10⁷, and 2.19 × 10⁸ M^− 1, respectively. Then, fluorescence microscopy was used to confirm the HCRs on the moving AMs. As the movement speed increased, the DNA fluorescence on the cell membrane was intensified, suggesting that more fluorescent H1 probes were brought on the cell membrane (Fig. 3c), consistent with the flow cytometry results (Fig. 3d). As a control, when the initiator DNA was replaced by a random strand (RS), no fluorescence was observed even using the fast-moving AMs, thereby verifying the occurrence of HCRs (Fig. 3e). Thus, these results indicated that the fast movement was still beneficial to this complex DNA reaction.

Fig. 3.

Hybridization chain reaction (HCR) reaction on the surface of DNA-AMs. (a) Schematic diagram of HCR reaction on the surface of DNA-AMs. (b) Hybridization kinetic curves of the HCR reactions for slow-, normal-, and fast-moving DNA_initial-AMs. (c) Representative fluorescence microscopy images of slow-, normal-, and fast-moving HCR-AMs. The DNA-AMs and FAM-labeled DNA are represented by red and green, respectively. Scale bar, 20 μm. (d and e) Representative flow cytometry density plots and mean FL intensity of slow-, normal-, and fast-moving HCR-AMs with 1 nM DNA_initial (d) and with random DNA strand (e). FAM-labeled DNA is measured on the FITC channel. The autofluorescence of DNA-AMs is monitored on the PerCP channel. (f, g) Fluorescence emission spectra (f) and intensity ratio FL₅₃₀/FL₇₁₅ (g) of fast-moving HCR-AMs with varying miRNA-155 concentrations ranging from 0.1 fM to 100 pM. The inset shows the intensity ratio FL₅₃₀/FL₇₁₅ of fast-moving HCR-AMs at low miRNA-155 concentration. The dashed line (black) indicates the LOD of fast-moving HCR-AMs. (h) Fluorescence intensities of fast-moving HCR-AMs with different interfering miRNAs (1 nM). The mixture contained 1 nM target miRNA-155, along with 1 nM of each interfering miRNA (miRNA-127, miRNA-21, and miRNA-182). All data are presented as means ± standard deviation (S.D.), n = 4. Statistical analysis was conducted via ordinary one-way ANOVA with Tukey’s post hoc test. a.u., arbitrary units. ****P < 0.0001; NS, no significance

Since HCR is a typical isothermal amplification method to enhance the sensitivity of DNA sensing strategies, we explored the detection performance of the fast-moving AMs in miRNA detection. To do so, the initiator DNA was replaced by a DNA capture strand that was partially complementary to the miR-155. Then, the captured miR-155 acted as an initiator strand to activate HCR on the cell surface. As shown in Fig. 3f, fluorescence spectra showed the increase of DNA fluorescence at 530 nm as the concentration of miR-155 increased from 0 to 100 pM. Notably, the autofluorescence of AMs (i.e., chlorophyll) at 715 nm remained unchanged, which could be used as an internal reference signal. The fluorescence ratio between FAM (FL₅₃₀) and chlorophyll (FL₇₁₅) was shown in Fig. 3g when fast-moving AMs were incubated with various concentrations of miR-155 for 60 min. The regression equation was calculated as FL₅₃₀/FL₇₁₅ = 0.279lgc(miRNA-155) + 0.604 with a correlation coefficient (R²) of 0.998. The LOD was estimated to be 1 fM according to the background signal plus 3 × S.D., which was ~ 100-fold lower than that of the sensing strategy without using HCR (LOD = 0.1 pM for fast-moving DNA-AMs, Fig. 2m). The proposed method also exhibited excellent specificity, and negligible signals could be detected when the DNA-AMs were challenged with other similar miRNA sequences (Fig. 3h).

To verify the applicability of fast-moving HCR-AMs to real samples, a double-blind detection experiment was conducted to analyze miRNA-155 in serum samples from bladder cancer patients (BC, n = 15) and healthy individuals (HC, n = 10) using the fast-moving HCR-AMs system and qPCR method. The heat map visually represented the detection results (Figure S8a). The fast-moving HCR-AMs system successfully identified 10 positive samples and 10 negative samples, which was consistent with the results obtained by the qPCR method (Figure S8b and c). Of note, a typical qPCR assay needed 100 min, while HCR assay on fast-moving AMs requires a 60-minute reaction time, demonstrating its higher operation efficiency. Additionally, as shown in Figure S8d, the receiver operating characteristic (ROC) curve also proved that the fast-moving HCR-AMs system outperformed the qPCR method in detecting miRNA-155 (AUC: 0.9867 vs. 0.9500).

To further contextualize these findings within the broader field of nucleic acid biosensing, we comprehensively reviewed recent literature utilizing conventional static solid-surface interfaces (Table S2). Traditional static biosensors typically face mass transfer bottlenecks in bulk solutions, often necessitating longer incubation times or relying on complex, multi-layered signal amplification strategies (e.g., dual amplification with nicking enzymes, triple signal amplification) to reach sub-picomolar sensitivities. By utilizing the innate propulsion of algal cells to actively enhance interfacial mass transfer, our platform completes the HCR and RCA assays within 60 min, respectively.

RCA reaction on the surface of motile algae (RCA-AMs)

Besides nonenzymatic DNA reactions, we also wondered the influence of cell movement on enzymatic DNA reactions. To do so, we finally investigated a typical enzymatic reaction, i.e., Rolling circle amplification (RCA), on the movable AMs [35]. To do so, DNA primers were first anchored on the AMs surface, and then incubated with circular template DNA, DNA polymerase (phi29), and nucleotide substrate (deoxy-ribonucleoside triphosphate, dNTP) to activate polymerization reaction (Fig. 4a). The formation of ultralong DNA products in the solution through RCA was first verified by the gel electrophoresis results (Fig. 4b). Then, Alexa Fluor 488 dye-labeled nucleotide substrate (488-dUTP) was used to conveniently characterize the DNA reaction on the cell membrane. As shown in Fig. 4c, strong green fluorescence was only observed in the presence all necessary components, verifying the feasibility of polymerization reaction. Again, the increase of movement of AMs could greatly improve reaction kinetics of RCA on the cell membrane (Fig. 4d), and the reaction was completed within 60 min. To further validate the RCA reaction on moving AMs, flow cytometry was employed. The results showed that faster-moving cells exhibited stronger membrane fluorescence, which corresponded to a higher density of incorporated fluorescent probes (Fig. 4e-g). These findings were consistent with those obtained from fluorescence microscopy (Fig. 4h).

Fig. 4.

Rolling circle amplification (RCA) reaction on the surface of DNA-AMs. (a) Schematic diagram of RCA reaction on the surface of motile DNA-AMs. (b) Agarose gel electrophoresis analysis of the amplification products from the DNA-AMs. Lane 1: RCA product; Lane 2: prime DNA; Lane 3: Cri DNA. (c) Representative fluorescence microscopy images of normal-moving DNA-AMs under different rolling circle amplification conditions. Scale bar, 50 μm. (d) Hybridization kinetic curves of the RCA reactions for slow-, normal-, and fast-moving RCA-AMs. (e-g) Flow cytometry histograms (left) and corresponding mean fluorescence intensity (right) of slow-moving (e), normal-moving (f), and fast-moving (g) RCA-AMs collected at different reaction times (0–60 min). (h) Representative fluorescence microscopy images of slow-, normal-, and fast-moving RCA-AMs after RCA reaction. DNA products labeled with Alexa Fluor 488 are shown in green, and algae autofluorescence is shown in red. Scale bar, 50 μm. The data are presented as means ± standard deviation (S.D.), n = 4. Statistical analysis was conducted via ordinary one-way ANOVA with Tukey’s post hoc test. a.u., arbitrary units. *P < 0.05, ***P < 0.001, ****P < 0.0001

To validate whether the motion-enhanced advantages of our DNA-AM platform can be generalized to complex amplification cascades, we systematically compared the reaction rate (half-saturation time, t_1/2) of fast-moving AMs against conventional static interfaces (silica and polyacrylamide microspheres) during HCR and RCA. Consequently, the t_1/2 for both HCR and RCA reactions on fast-moving AMs were 30 min, markedly faster than those on silica and polyacrylamide microspheres (Figure S9). It is important to note, that while biological motion accelerates the initial target recognition and collision steps, the intrinsic kinetics of the subsequent enzymatic polymerization or DNA strand displacement cascades remain governed by the fundamental rules of the respective reactions.

RCA-guided autonomous assembly and disassembly of cells

Considering that the formation of ultralong DNA strands on the AMs, we explored their application in cell assembly. Cell assembly is an emerging research direction aimed at constructing multicellular architectures with specific spatial arrangements in a controlled manner. Traditional DNA-mediated cell assembly frequently suffered from low efficiency because of the limited DNA density and large size of cells, which relied on continuous vortex or centrifugation to make cell collision and contact. Thus, we wondered whether movable AMs carrying sticky DNA strands could assemble automatically. To do so, two DNA strands (a and b) were produced on the AMs through RCA, respectively, which contained multiple complementary sequences (Fig. 5a). The resulting cells were named as RCA-AMs a and RCA-AMs b, and RCA-AMs b was stained with a green fluorophore (Calcein). After simply mixing two fast-moving AMs in PBS for 30 min, large cell aggregates could be clearly observed using fluorescence microscopy (Fig. 5b), indicating the successful assembly of two AMs. However, sodium malonate-treated RCA-AMs (slow-moving RCA-AMs) remained dispersed and did not form algae assemblies (Fig. 5c). As incubation time extended, fast-moving RCA-AMs collided with each other and gradually formed large algae clusters (Fig. 5d). However, as the large cell clusters formed, their movement speed significantly slowed down because of the size effects and anisotropic movement tendencies (Fig. 5e). Additionally, when an excess strand a* complementary to the DNA on the AMs was added, the algae clusters disassembled into single cells within 30 min, and restored the movement. These results indicate that the movement of DNA-AMs was not only beneficial to cell assembly but can also be controlled by DNA reaction, and vice versa.

Fig. 5.

RCA-guided autonomous assembly and disassembly of cells. (a) Scheme of RCA reaction-guided assembly of RCA-AMs. (b, c) Representative bright-field (BF) and fluorescence microscopy images of assembled (b) and unassembled (c) AMs guided by RCA hybridization reaction. The autofluorescence of all RCA-AMs a and RCA-AMs b is represented by red on the Cy3 channel. Calcein green-labeled RCA-AMs b are represented by green on the FITC channel. Scale bar, 50 μm. (d) Representative bright-field (BF) and fluorescence microscopy images of the assembly RCA-AMs at different time points. The autofluorescence of all RCA-AMs a and RCA-AMs b are represented by red on the Cy3 channel. Calcein green-labeled RCA-AMs b is represented by green on the FITC channel. Scale bar, 50 μm. (e) Representative trajectories of the assembly RCA-AMs at different time points. (f) Scheme of RCA reaction-guided ETC-AMs specifically recognizing exfoliated tumor cells (ETCs) in urine. (g) Quantitative analysis of capture efficiency of fast- and slow-moving ETC-AMs toward tumor cells and healthy cells. Data are presented as means ± standard deviation (S.D.), n = 4. (h) Representative bright-field (BF) and fluorescence microscopy images of ETC-AMs co-incubated suspended ETCs for 60 min. The autofluorescence of ETC-AMs is represented by red on the Cy3 channel. Calcein green-stained ETCs are represented by green on the FITC channel. Scale bar, 50 μm. (i) Representative BF and fluorescence microscopy images showing selective capture of tumor cells over healthy cells by ETC-AMs in a mixed-cell system. ETC-AMs are shown in red, tumor cells in green, and healthy cells in blue. Scale bar, 50 μm

Inspired by the facile cell assembly process of RCA-AMs, we further expanded its application to tumor cell isolation. Exfoliated tumor cells (ETCs) in urine are highly valuable non-invasive diagnostic markers; however, inefficient capture technologies in the urinary environment severely limit their clinical translation and application potential [36]. Considering that DNA aptamers specifically binding to ETCs could be integrated into the RCA products on the AMs, we prepared ETC-AMs that contained multiple epithelial cell adhesion molecule (EpCAM)-targeting aptamers to recognize and capture ETCs (Fig. 5f) [37]. In a proof-of-concept study, we co-incubated ETC-AMs with human bladder cancer cells (HT1197, stained by green) for 60 min. As anticipated, large cell clusters formed and the tumor cells were surrounded by the algae cells, implying that ETC-AMs could recognize tumor cells. The capture efficiency of this ETC-AMs-mediated strategy was calculated to be as high as 95% (Fig. 5g). In contrast, when slow-moving ETC-AMs were co-incubated with bladder cancer cells, no significant cluster formation was observed, indicating that the mobility of ETC-AMs is crucial for their capture function (Fig. 5h and Movie S3). Furthermore, when ETC-AMs were incubated with the mixture of tumor and healthy bladder epithelium immortalized cells (SV-HUC-1, low EpCAM expression), only tumor cells were captured by the ETC-AMs, suggesting the high specificity of the ETC-AMs (Fig. 5i).

Discussion

In this study, we have successfully constructed a dynamic DNA-functionalized microrobot platform based on motile algae and systematically demonstrated the unique advantages of autonomous biological motion in accelerating interfacial DNA reactions. By precisely regulating the swimming speed of the algal microrobots, we uncovered a direct positive correlation between their motility and the kinetics/efficiency of three representative DNA reactions, including DNA hybridization, HCR, and RCA. Rapidly moving algae cells generate significant micro-hydrodynamic effects, such as convection and mixing near their surface, which effectively focus target molecules toward the cell membrane, thereby greatly enhancing molecular collision frequency and reaction rates. This intrinsic propulsion mechanism enables fast-moving microrobots to complete hybridization reactions within minutes and significantly shortens the duration required for complex isothermal amplification reactions (e.g., HCR and RCA), ultimately achieving ultrasensitive (fM level) and rapid (within 60 min) detection of disease-related miRNA biomarkers. Furthermore, we extended this DNA-AMs to more advanced biological functions. By generating ultralong DNA strands on the surface of fast-moving algae via RCA, we achieved efficient and autonomous directional assembly of microrobots and demonstrated their high potential for specific recognition and capture of tumor cells in complex biological environments such as urine.

Compared to traditional synthetic microrobots driven by external physical fields (e.g., magnetic, acoustic, or light fields), our live algae-based microrobots exhibit unparalleled autonomy and superior biocompatibility. They can self-propel in complex physiological fluids without the need for bulky external equipment, making them highly suitable for on-site biomedical applications. However, we also acknowledge that the inherent biological metabolism of living algae, such as the secretion of nucleases or local pH fluctuations, may pose challenges to the long-term stability of the interfaced DNA. Although our chitosan coating strategy provides a robust physical and electrostatic shield that preserves DNA integrity for up to seven days, future long-term monitoring applications could be further optimized by employing nuclease-resistant nucleic acid analogs (e.g., locked nucleic acid or peptide nucleic acid) or implementing mild cell-fixation techniques that preserve flagellar motility while halting destructive metabolic processes [38–40].

Looking forward, the integration of functional nanomaterials opens exciting avenues for upgrading our DNA-AM platform into a multimodal theragnostic system. For instance, recent advancements in photothermal agents have demonstrated the immense potential of light-responsive materials in precise disease localization and treatment. Typical examples include chemical-exfoliated borophene for light-induced tumor theragnostic and black phosphorus-based photothermal therapy combined with αCD47-mediated immune checkpoint blockade [41–42]. By co-modifying the algal surface with such highly efficient photothermal nanomaterials, we could utilize high-resolution photothermal imaging to track the microrobots’ trajectories in vivo without background fluorescence interference. Moreover, localized photothermal effects could act as a precise switch to dynamically control DNA hybridization/dehybridization thermodynamics or trigger drug release, offering unprecedented spatiotemporal control for targeted cancer therapy.

In addition to multimodal imaging and therapy, the diagnostic capabilities of our platform could be further pushed to the single-molecule level by coupling the motion-enhanced mass transfer with advanced nucleic acid cleavage systems. For example, CRISPR/Cas systems have revolutionized molecular diagnostics, as evidenced by a recent CRISPR/Cas12a-empowered surface plasmon resonance platform that achieved rapid and highly specific diagnosis of the SARS-CoV-2 Omicron variant [43]. While CRISPR-based assays exhibit exceptional enzymatic amplification sensitivity, they are often physically limited by the slow diffusion of target molecules in complex bulk samples. By immobilizing CRISPR/Cas complexes on our fast-moving AMs, the robust micro-hydrodynamic mixing generated by the swimming algae could act as an active molecular sweeper, continuously enriching target nucleic acids onto the Cas enzymes. This synergy between motile bio-interfaces and CRISPR collateral cleavage would drastically minimize the reaction dead-time, providing an ultra-sensitive, amplification-free tool for the rapid on-site typing of pathogens or tumor mutations.

In summary, we have leveraged the innate motility of living organisms to create dynamic, environmentally responsive bio-interfaces. This “motion-enhanced” effect provides a novel paradigm for addressing the classical challenge of low efficiency in interfacial biochemical reactions.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

M.L. and C.L. conceived the study and designed the experiments. M.L., Z.J., Y.L., C.Z., D.H., and Y.Z. performed the investigations and data collection. M.L., Z.J., S.Z., and C.L. analyzed the data. M.L. and C.L. wrote the original manuscript. N.F. supervised the project, acquired funding, and administered the project.

Funding

This work was supported by the National Natural Science Foundation of China (82302654, 82472103, 82370777, 82570904), Jiangsu Provincial Natural Science Foundation (BK20230188), Anhui Provincial Natural Science Foundation (2308085MB55), “San Ming” Strategic Talent Project of Wuxi Municipal Health Commission (No. HB2023032), and Fundamental Research Funds for the Central Universities (JZ2025HGTG0284).

Data availability

No datasets were generated or analysed during the current study.

Declarations

Ethics approval and consent to participate

This research complies with all relevant ethical regulations. All human plasma and urine samples were provided by Jiangnan University Medical Center (approval No. 2022 − 339). Collect the informed written consent from all patients and anonymize the samples.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.