Differential sensing, crucial for identifying complex analytes like intracellular bacteria, necessitates sensor systems with varied responses to target pathogens. Designing an effective sensor array for Bacteria Diagnosis requires careful consideration of several key processes: the interactions between recognition receptors and bacterial cells, the cellular uptake mechanisms of sensor units, and the transduction of bacterial presence into a detectable signal. Macrocyclic receptors, known for their broad encapsulation capabilities, are exceptionally well-suited for differential sensing strategies grounded in pattern recognition. Calixarenes, a family of highly customizable macrocyclic receptors, provide a versatile platform for chemical design, enabling the creation of diverse, cross-reactive sensor units. Furthermore, calixarenes possess a unique property: complexation-induced quenching of fluorescent indicators. This feature allows the sensor array to generate a pronounced fluorescent turn-on signal specifically in response to intracellular bacteria, making it a powerful tool for bacteria diagnosis.
Our research group has recently developed a series of azocalixarenes. The azo-coupling reaction on calixarenes offers a robust and straightforward method for synthesizing these compounds. These azocalixarenes, with their deepened cavities, exhibit enhanced recognition capabilities compared to conventional calixarenes. This improved recognition broadens their ability to interact with a wider range of guest molecules within complex biological systems, which is highly beneficial for bacteria diagnosis. Moreover, the azo groups in azocalixarenes are reducible by azoreductase, an enzyme prevalent in the hypoxic microenvironment induced by intracellular bacterial infections. This reduction converts azocalixarenes into aminocalixarenes. The change in binding affinity of fluorescent indicators upon this reduction leads to indicator release, providing an additional pathway for transducing output signals related to bacterial presence.
Therefore, we designed three distinct classes of azocalix[4]arenes, each with unique upper rim modifications, specifically for the discrimination of intracellular bacteria (Fig. 2a). The first class comprises carbohydrate-modified azocalix[4]arenes. These are designed to interact with receptors like mannose receptor, galactose receptor, and β-glucan receptor, which are expressed by macrophages, as well as lectins, toxins, and adhesins found on bacterial surfaces, all of which can recognize carbohydrates. The second class is amino acid-modified azocalix[4]arenes. These are intended to interact with the amino acid transporters that macrophages upregulate upon bacterial infection, affecting amino acid uptake. The third class includes carboxyl- and sulfonate-modified azocalix[4]arenes. These lack active targeting groups but are designed to provide complementary information for array-based sensing, enhancing the overall accuracy of bacteria diagnosis when used in conjunction with the first two types. The selection of these azocalix[4]arenes as recognition receptors is based on their varying degrees of interaction with macrophages and bacteria, which is fundamental for achieving differential sensing and accurate bacteria diagnosis.
Fig. 2: Construction of the sensor array and the discrimination of intracellular bacteria.
Illustration of the supramolecular sensor array for bacteria diagnosis, showing chemical structures of azocalix[4]arenes and fluorescent indicator, fluorescence response patterns against bacteria, and LDA canonical score plots for bacteria discrimination and analysis.
Six azocalix[4]arenes – ManAC4A (1), LacAC4A (2), GalAC4A (3), GluAC4A (4), CAC4A (5), and SAC4A (6) – were synthesized and purified using established procedures. Two novel macrocyclic compounds, LysAC4A (7) and SerAC4A (8), were also synthesized to generate potentially differential signal outputs crucial for bacteria diagnosis. Taking LysAC4A synthesis as an example, CAC4A was activated and condensed with n-epsilon-boc-lysine, followed by deprotection to yield LysAC4A. SerAC4A was synthesized via a similar route. Among these, ManAC4A, LacAC4A, GalAC4A, GluAC4A, LysAC4A, SerAC4A, and CAC4A spontaneously self-assemble into nanoparticles ranging from 25 to 131 nm in diameter, while SAC4A does not. Indicator displacement assays (IDA) confirmed responses in both single molecules and assemblies. For signal transduction in bacteria diagnosis, azocalix[4]arenes complex with the indicator CY5, quenching its fluorescence. Dynamic light scattering (DLS) showed that complexation with CY5 did not disrupt the assembly structure of azocalix[4]arenes. These host-guest sensor units are designed to exhibit fluorescence recovery through competitive complexation with bacterial analytes. Additionally, the reduction of azo bonds in hypoxic conditions leads to CY5 release, resulting in varying degrees of fluorescence turn-on, further enhancing the signal for bacteria diagnosis.
Discriminating Intracellular Bacteria in Model Samples for Enhanced Bacteria Diagnosis
Eight bacterial species were selected as target intracellular pathogens to validate the concept of our sensor array for bacteria diagnosis: SA, MRSA, LM, ST, Escherichia coli (EC), Pseudomonas aeruginosa (PA), Klebsiella pneumoniae (KP), and Streptococcus mutans (SM). SA, MRSA, LM, ST, EC, PA, and KP are known for their ability to invade and reside within host cells. SM was included to mimic bacterial phagocytosis by macrophages. Eight reporter pairs, each consisting of an azocalix[4]arene and CY5, were co-incubated with infected and blank macrophages. Fluorescence intensity, a key indicator for bacteria diagnosis, was measured using a microplate reader. As shown in Fig. 2b, each sensor unit displayed distinct fluorescence intensity levels corresponding to specific intracellular bacteria, demonstrating the sensor array’s capability for identifying different types of intracellular bacteria and its potential for comprehensive bacteria diagnosis.
To assess the sensor array’s discrimination capabilities for bacteria diagnosis, we analyzed the fluorescence response patterns of intracellular bacteria using linear discriminant analysis (LDA). LDA is a robust statistical method widely used for pattern recognition. The analysis clearly clustered the eight bacteria-infected macrophage groups and the macrophage-only group into nine distinct, fully separated clusters (Fig. 2c). Cross-validation using the leave-one-out method in LDA achieved 100% discrimination accuracy, confirming the high effectiveness of our sensor array in both detecting the presence and identifying the species of intracellular bacteria—a significant advancement in bacteria diagnosis.
Clinical bacteria diagnosis often involves samples with mixed pathogens. Therefore, we conducted further discrimination experiments using mixtures of SA– and LM-infected macrophages. These bacteria are significant as they can be transmitted through food and cause severe intracellular infections. Mixtures with varying proportions were well-classified in the LDA plot (Fig. 2d and Supplementary Table 3). We also explored the feasibility of quantitative analysis of intracellular bacteria using the supramolecular sensor array. Different concentrations of SA and LM (OD600 = 1.0, 0.5, 0.2, and 0.1) were effectively separated in their LDA score plots (Supplementary Table 4 and Supplementary Fig. 25a and b). Furthermore, the two major categories representing different concentrations of SA and LM could be distinguished using both LDA and principal component analysis (PCA) (Supplementary Fig. 25c and d), highlighting the quantitative potential for bacteria diagnosis.
To further challenge the azocalix[4]arene-based sensor array for bacteria diagnosis, we used peritoneal fluid samples from mice. Mice were infected intraperitoneally with MRSA, EC, and PA. Macrophages from the peritoneal cavity were extracted the following day. The sensor array was applied to these infected cell samples (Supplementary Table 5). LDA patterns of the three bacteria-infected cell types and cells from healthy mice showed significant distinction (Fig. 2e). These clusters, each representing a different analyte, were clearly separated, demonstrating the array’s effectiveness in real-sample bacteria diagnosis. After establishing a standard profile for intracellular bacteria in mouse peritoneal fluid samples, we validated the array’s practical diagnostic application through blind tests. As shown in Supplementary Table 6, three blind intracellular bacteria samples from mice were correctly identified as MRSA. This preliminary result strongly supports the potential of our supramolecular sensor array for practical bacteria diagnosis applications.
Unveiling the Rationale Behind Discrimination for Advanced Bacteria Diagnosis
While the sensor array functions effectively for bacteria diagnosis, understanding the underlying mechanisms is crucial for future sensor array design and optimization. We hypothesize that three primary processes contribute to generating differential signals: (1) Competitive guest interactions on the cell surface illuminate the quenched fluorescence of CY5@azocalix[4]arene reporter pairs via indicator displacement assay (IDA). (2) Bacteria-infected macrophages exhibit varying uptake capacities for azocalix[4]arenes with different modifications. (3) The azo bonds in azocalix[4]arenes undergo reduction in the hypoxic microenvironment caused by intracellular bacteria, leading to indicator release to varying degrees (Fig. 3a). Through these combined mechanisms, the sensor array transforms inherent differences between target analytes into distinct fluorescent signals, enabling accurate bacteria diagnosis. In LDA, the magnitude of standardized coefficients indicates each variable’s contribution to discrimination. Larger absolute values signify a greater contribution to the discriminant function, aiding in pinpointing key sensors for bacteria diagnosis. As shown in Supplementary Table 7, ManAC4A, LysAC4A, SerAC4A, and CAC4A showed the largest discriminant contribution in factor 1 dimension. Therefore, these four azocalix[4]arenes and six common intracellular bacteria (SA, MRSA, LM, EC, PA, and ST) were used to validate our proposed hypothesis.
Fig. 3: Differential interactions and response signals between azocalix[4]arenes and intracellular bacteria.
Mechanism of bacteria diagnosis using azocalix[4]arene-based sensor array, showing signal transduction, uptake capacity of azocalix[4]arenes by infected macrophages, reduction kinetics, and enzyme concentration-dependent reduction rates.
First, IDA experiments were performed by analyzing fluorescence changes in bacteria-infected macrophages upon addition to host-guest complexes. Increased fluorescence indicated CY5 displacement due to competitive binding (Supplementary Fig. 26a−c). The varying extents of fluorescence change suggested differential interactions between azocalix[4]arenes and analytes, crucial for bacteria diagnosis. Notably, with CY5@ManAC4A complex, adding infected cells led to a further decrease in fluorescence intensity (Supplementary Fig. 26d). This may be due to cooperative binding between CY5@ManAC4A and cell analytes rather than competitive binding. This phenomenon, while contrasting, enhances differential sensing by promoting cross-reactivity, beneficial for robust bacteria diagnosis. In summary, azocalix[4]arenes exhibit varied supramolecular interactions with the same type of infected macrophage, and interactions between a specific azocalix[4]arene and macrophages infected with different bacteria also differ. This could be due to variations in receptor expression or quantity on the cell membrane post-infection by different bacteria, impacting bacteria diagnosis signals.
Next, we assessed the uptake capacity of bacteria-infected macrophages for these azocalix[4]arenes, a key aspect for effective bacteria diagnosis. Internalized azocalix[4]arene concentrations were quantified using UV−Vis spectra of culture media before and after co-incubation. As shown in Fig. 3b, uptake variations were observed for different azocalix[4]arenes across different bacteria-infected macrophages. ManAC4A uptake was significantly higher than amino acid- and carboxyl-modified azocalix[4]arenes. This is likely due to mannose binding to CD206, a mannose receptor highly expressed on macrophage surfaces. Furthermore, uptake of the same azocalix[4]arene varied among different intracellular bacteria types. Bacterial infection in macrophages can induce coordinated expression of transport proteins. The expression and function of these transporters can influence endocytosis rates, thereby affecting azocalix[4]arene uptake. Thus, cellular uptake contributes significantly to the cross-reactivity of sensor units, vital for reliable bacteria diagnosis.
Finally, we examined the reduction kinetics of azocalix[4]arenes under hypoxic conditions, another critical factor in bacteria diagnosis. Sodium dithionite (SDT), mimicking azoreductase, was introduced into azocalix[4]arene solutions. Intensity attenuation curves for azo bond reduction fitted well to a quasi-first-order reaction decay model. Rate constants for ManAC4A, LysAC4A, SerAC4A, and CAC4A were 0.28, 2.05, 1.63, and 3.57 min−1, respectively (Fig. 3c). Corresponding half-lives were 2.48, 0.34, 0.43, and 0.19 min, indicating distinct reduction kinetics for macrocycles with different modifications. Enzyme-linked immunosorbent assay (ELISA) confirmed that hypoxia inducible factor-1α (HIF-1α) accumulation varied in infected macrophages depending on bacterial species (Supplementary Fig. 27). Bacterial infection upregulates HIF-1α expression in macrophages, indicating cellular hypoxia. To simulate the reduction response of each azocalix[4]arene to intracellular bacteria with varying hypoxia levels, we treated azocalix[4]arenes with rat liver microsomes, rich in redox enzymes. Reduction rates of azocalix[4]arenes depended on enzyme concentrations, correlating with fluorescence signal differences in microenvironments (Fig. 3d), highlighting the importance of hypoxia-responsive elements in bacteria diagnosis.
Our meticulously designed sensor units facilitate intracellular bacteria diagnosis through a combination of interactions with bacteria-infected macrophages, cellular uptake, and hypoxia response. These processes involve both thermodynamic factors, like intermolecular interactions and gene transcription, and kinetic factors, such as uptake and azocalix[4]arene reduction rates. While sensor arrays often utilize thermodynamic factors, our findings emphasize the importance of kinetic information for enhancing differential sensing based on cross-reactivity, thus improving bacteria diagnosis. Notably, ManAC4A exhibited the highest cellular uptake by bacteria-infected macrophages, significantly surpassing LysAC4A, SerAC4A, and CAC4A (Fig. 3b). Compared to CAC4A, ManAC4A uptake increased by approximately 4 to 24 times. These results underscore ManAC4A’s potential as a drug delivery carrier for treating intracellular bacterial infections, complementing its role in bacteria diagnosis.
In Vitro Anti-intracellular Bacterial Activity of Host-Guest DDS for Bacteria Diagnosis and Therapy
Hypoxia-responsive azocalix[4]arenes not only enable bacteria diagnosis through integrated signal changes but also show promise in drug delivery for treating bacterial infections. To validate the therapeutic potential against intracellular bacterial infections, we used MRSA blind samples, identified earlier by our sensor array, as a model. ManAC4A, exhibiting the highest uptake, serves as a hypoxia-responsive drug delivery carrier. The hydrophilic mannose modification in ManAC4A forms an amphiphilic molecule that self-assembles into nanoparticles (~80 nm at 20 μM) (Supplementary Fig. 21d). ManAC4A nanoparticle size varies with concentration, reaching ~120 nm at 0.5–1.0 mM. Static light scattering (SLS) and DLS confirmed a vesicular morphology (Rg/Rh ≈ 1.06) (Supplementary Fig. 28). This structure enhances multivalent interactions with mannose receptors on macrophages and bacteria due to its amphiphilic nature. The deep cavity of azocalix[4]arene enhances antibiotic binding, and its sensitivity to bacterial intracellular azoreductase enables controlled release. Thus, ManAC4A integrates loading, targeting, and controlled release, offering significant potential in combating intracellular bacterial infections and bridging bacteria diagnosis with therapy. CAC4A, lacking mannose, served as a control.
To assess ManAC4A’s role in antibiotic internalization into MRSA, we observed co-localization using confocal laser scanning microscopy (CLSM). CY5, forming fluorescence-quenched complexes with ManAC4A and CAC4A, tracked azocalix[4]arene localization. Complexation was validated by 1H NMR spectroscopy (Supplementary Figs. 29 and 30). CY5 protons showed upfield shifts in the presence of ManAC4A or CAC4A, indicating encapsulation within the azocalix[4]arene cavity. Under hypoxia, FITC-labeled MRSA (green) and CY5@ManAC4A (red) were co-incubated and observed via CLSM (Supplementary Fig. 31). Substantial overlap between green and red signals indicated carrier-mediated antibiotic delivery into bacteria. Mannose modification enhanced binding compared to CAC4A. Free CY5 showed minimal bacterial presence, as did CY5 under normoxic conditions. This suggests azocalix[4]arene aids small molecule penetration and responds to hypoxic release, enhancing drug bactericidal effect, linking bacteria diagnosis to targeted treatment.
Doxycycline (Dox) is effective against MRSA, while ciprofloxacin (Cip) shows limited efficacy. We compared their bactericidal effects (Supplementary Fig. 32a and b). Dox significantly inhibited MRSA growth at micromolar concentrations, while Cip needed much higher concentrations. At equivalent drug concentrations, Dox-DDS eradicated most bacteria, whereas Cip-DDS showed partial inhibition (Supplementary Fig. 32c). These findings underscore accurate bacteria diagnosis to guide antibiotic selection.
We evaluated azocalix[4]arene antibiotic loading capacity. Dox loading into azocalix[4]arene assemblies was confirmed by Rhodamine B (RhB) displacement from CAC4A (Supplementary Figs. 33 and 34). Drug-loaded CAC4A and ManAC4A were prepared (Supplementary Figs. 34 and 35). 1H NMR spectroscopy studied Dox-azocalix[4]arene complexation (Supplementary Figs. 36 and 37). Dox benzene ring protons shifted upfield upon ManAC4A and CAC4A addition, indicating benzene ring entry into the cavities. DLS showed unchanged assembly sizes with Dox, indicating structure preservation (Supplementary Fig. 24). Geometry optimizations of Dox@ManAC4A and CY5@ManAC4A complexes using B3LYP-D3/6-31 G(d, p)/SMD (water) method, and MEP mapping, revealed favorable binding geometries (Supplementary Fig. 38). Dox amide moiety likely interacts with ManAC4A amide moiety, with the aromatic ring penetrating the cavity. CY5 likely forms π−π stacking interactions with ManAC4A aromatic rings (Supplementary Fig. 38b).
Next, we investigated ManAC4A’s antibacterial activity as a Dox carrier using plate counting (Fig. 4a). Dox@ManAC4A significantly reduced MRSA viability compared to PBS, Dox, and ManAC4A groups under hypoxia (Fig. 4b). While CAC4A alone showed bactericidal activity, ManAC4A was superior in enhancing antibiotic efficacy. Under normoxia, Dox@ManAC4A showed less pronounced bactericidal effect, highlighting hypoxia-specific release for targeted bacteria diagnosis and therapy. CLSM with acridine orange (AO, green, live) and ethidium bromide (EB, red, dead) staining visualized bacterial viability (Fig. 4c). Control group bacteria were mostly green; Dox@ManAC4A group bacteria were mostly red, indicating effective MRSA damage by released Dox, consistent with plate counting results, and demonstrating therapeutic efficacy alongside bacteria diagnosis.
Fig. 4: The antibacterial application of Dox@ManAC4A in vitro.
In vitro antibacterial efficacy of Dox@ManAC4A, showing MRSA colony images after treatment, quantification of remaining MRSA, and CLSM images of MRSA viability under hypoxic and normoxic conditions.
To evaluate ManAC4A’s ability to recognize intracellular bacteria, we used three-channel CLSM to observe MRSA-infected macrophages (Fig. 5a). Macrophages (DAPI-labeled, blue) infected with MRSA (FITC-labeled, green) were treated with azocalix[4]arenes (CY5-complexed, red). ManAC4A distribution significantly overlapped with MRSA, showing bright yellow fluorescence after superposition. CAC4A, lacking targeting groups, showed weaker red fluorescence than ManAC4A, highlighting mannose motifs’ crucial role in intracellular bacterial targeting and internalization, essential for effective bacteria diagnosis and targeted therapy.
Fig. 5: The ability of Dox@ManAC4A to promote clearance of intracellular MRSA in vitro.
In vitro efficacy of Dox@ManAC4A against intracellular MRSA, showing CLSM images of MRSA-infected macrophages with different treatments, MRSA colony images, quantification of remaining intracellular MRSA, ELISA results for cytokine expression, and CLSM observation of MRSA-infected macrophages.
After confirming ManAC4A’s targeting ability, we further investigated Dox@ManAC4A’s efficacy in eradicating intracellular bacteria. MRSA-infected RAW 264.7 macrophages were treated with PBS, Dox, ManAC4A, and Dox@ManAC4A, followed by lysis and intracellular MRSA quantification using plate colony counting (Fig. 5b and c). Dox treatment inhibited intracellular MRSA compared to PBS. Dox@ManAC4A showed enhanced inhibition over free Dox due to improved internalization via mannose receptor-mediated endocytosis. Dox@ManAC4A treatment also reduced macrophage TNF-α and IL-6 expression, indicative of inflammation alleviation (Fig. 5d). CLSM observation of MRSA-infected RAW 264.7 cells showed a significant decrease in intracellular bacteria in the Dox@ManAC4A group, consistent with plate counting results (Fig. 5e), demonstrating its combined diagnostic and therapeutic potential.
Biocompatibility and In Vivo Antibacterial Efficacy for Clinical Translation of Bacteria Diagnosis and Therapy
Biosafety assessment of ManAC4A is crucial before in vivo therapeutic use. RAW 264.7 macrophages evaluated ManAC4A cytotoxicity. Even at high concentrations (0-500 μM for 24 h), ManAC4A had negligible impact on cell viability, remaining above 90% (Supplementary Fig. 39). In vivo toxicity was assessed in mice via intraperitoneal injection daily for three days. No mortality or weight loss was observed across treatment groups. Histomorphological examination (H&E staining) showed no significant pathological abnormalities in major organs (heart, liver, spleen, lung, kidney) (Supplementary Fig. 40), indicating ManAC4A biocompatibility, essential for clinical translation of bacteria diagnosis and therapy.
Peritonitis, a severe intracellular bacterial infection, requires rapid macrophage response. We assessed Dox@ManAC4A’s antimicrobial efficacy in MRSA-induced peritonitis in mice. Female Balb/C mice were intraperitoneally injected with MRSA and treated twice at 12-hour intervals with PBS, Dox, ManAC4A, or Dox@ManAC4A. 48 hours post-infection, peritoneal fluid was collected, and intracellular, extracellular, and total MRSA CFUs were quantified (Fig. 6b). Dox@ManAC4A effectively cleared extracellular MRSA and outperformed free Dox, consistent with in vitro results. Dox@ManAC4A also showed enhanced in vivo antimicrobial activity against intracellular MRSA due to ManAC4A-mediated targeting (Fig. 6c and Supplementary Fig. 41). The overall bactericidal effect aligned with intracellular and extracellular trends, highlighting Dox@ManAC4A’s superior therapeutic efficacy for bacteria diagnosis-guided treatment.
Fig. 6: The ability of Dox@ManAC4A to treat MRSA-infected peritonitis in vivo.
In vivo therapeutic efficacy of Dox@ManAC4A in MRSA-induced peritonitis, showing schematic of mouse infection model, MRSA colony images, CFUs in intracellular fraction, ELISA results for cytokine expression, and H&E staining of major tissues.
Pro- and anti-inflammatory cytokine assays showed Dox@ManAC4A regulated inflammation (Fig. 6d). It reduced pro-inflammatory IL-6 and TNF-α levels and increased anti-inflammatory IL-10 levels, indicating inflammation attenuation and tissue recovery promotion. H&E analysis revealed liver and lung damage in PBS-treated mice, including sinusoidal dilatation and alveolar duct widening (Fig. 6e). Dox@ManAC4A treatment significantly mitigated tissue damage, yielding histological results comparable to healthy controls. Routine blood examination (Supplementary Fig. 42) showed white blood cell count and neutrophil proportion decreased most significantly in the Dox@ManAC4A group, reflecting reduced systemic inflammation. These findings demonstrate Dox@ManAC4A’s remarkable in vivo efficacy for intracellular infection treatment due to active targeting and controlled release, paving the way for advanced bacteria diagnosis and targeted therapies.
