DESCRIPTION

Foodborne diseases, also referred to as foodborne illnesses or food poisoning, represent a significant and pervasive global public health challenge （Figure 1）. These illnesses are caused by the ingestion of food contaminated with pathogenic microorganisms, viruses, parasites, or chemical substances, leading to a spectrum of conditions from gastroenteritis to severe neurological disorders and even death [1]. The World Health Organization (WHO) estimates that annually, nearly one in ten people worldwide (approximately 600 million individuals) fall ill due to consuming contaminated food, resulting in over 420,000 deaths and a loss of 33 million healthy life years [2].
The socioeconomic impact of foodborne diseases is substantial, straining healthcare systems, reducing productivity, and harming tourism and trade. While this is a global issue, the burden is disproportionately carried by low- and middle-income countries, where challenges such as limited access to clean water, inadequate food storage facilities, and insufficient enforcement of food safety regulations are more prevalent [3]. However, developed countries are not immune; for instance, in the United States, foodborne diseases cause an estimated 128,000 hospitalizations and 3,000 deaths each year, with an associated economic burden exceeding $15.5 billion [4].

Foodborne diseases pose multifaceted public health problems. They cause a wide range of illnesses, from self-limiting gastrointestinal symptoms like nausea, vomiting, abdominal cramps, and diarrhea (e.g., from Staphylococcus aureus enterotoxins) to severe and life-threatening complications such as hemolytic uremic syndrome (HUS) and kidney failure from Escherichia coli O157:H7 infections, miscarriage and stillbirth from Listeria monocytogenes, and neurological paralysis from Clostridium botulinum. Furthermore, some foodborne pathogens are associated with long-term sequelae including reactive arthritis, neurological disorders, and cancer (e.g., aflatoxins from moulds are potent hepatocarcinogens) [5]. The emergence and spread of foodborne diseases are exacerbated by factors such as increasing international trade in food products, climate change, urbanization, and the development of antimicrobial resistance.

Current bacterial detection technologies still face significant limitations. Culture-based methods, though reliable, are time-consuming, often requiring 24–72 hours to produce results—a critical delay in severe infections. They also perform poorly with fastidious or unculturable strains, leading to potential underdiagnosis [6].
Molecular techniques like PCR offer high sensitivity but are susceptible to contamination and false positives. They often require sophisticated equipment and trained operators, restricting their use in resource-limited settings. Moreover, they cannot differentiate between live and dead bacteria, which may lead to overestimation of infection severity [6].

The threat of foodborne diseases is shocking. Hundreds of millions of people around the world are affected by it every year, and the number of deaths is as high as hundreds of thousands. Facing this severe challenge, the slowness in speed, insufficient sensitivity, and lack of portability of traditional detection methods have become more and more obvious, making it difficult to meet the urgent need for real-time prevention and control. Point-of-Care Testing (POCT) is clinical laboratory testing conducted close to the site of patient care where care or treatment is provided. POCT provides rapid turnaround of test results with the potential to generate a result quickly so that appropriate treatment can be implemented, leading to improved clinical or economic outcomes compared to laboratory testing [7]. POCT delivers fast, on-site results, meeting ASSURED standards: Affordable, Sensitive, Specific, User-friendly, Rapid, Equipment-free, and Deliverable. (Figure 2)

POCT technology offers compelling advantages for bacterial detection. At the technical level, a series of key technologies have achieved breakthrough progress: The signal amplification effect of nanomaterials greatly improves the detection sensitivity, allowing even trace amounts of target substances to be accurately captured; Artificial intelligence - assisted analysis enables rapid interpretation and accurate judgment of detection results. The mature application of these technologies provides a stable and reliable guarantee for highly sensitive and highly specific detection.
In practical applications, the advantages of POCT technology are even more obvious: The operation process is extremely simple, just like "drop the sample → wait for color development → take a photo with a mobile phone", which can be completed easily in a few steps without professional personnel, perfectly meeting the easy to use standard; the cost is also effectively controlled. At the same time, most detections can yield results within 30 minutes, efficiently responding to the need for rapidity and fully demonstrating the value of immediate detection in practical scenarios [8].

As a nanomaterial with a unique flower-like structure, nanoflowers have shown significant advantages in the field of bacterial detection, and their related research and applications have received much attention [9]. This type of material can be prepared through various methods such as the sol-gel method, hydrothermal method, and physical vapor deposition method. The core is to guide the directional growth and assembly of nanoparticles into a flower-like structure by adjusting conditions such as temperature, pH value, and reactant concentration. The high specific surface area gives it a natural advantage in detection sensitivity.
In the field of bacterial detection and related areas, the application potential of nanoflowers is particularly prominent: nanoflowers made of silver and zinc oxide not only have strong antibacterial activity themselves and can directly inhibit common pathogenic bacteria such as E. coli and S. aureus; at the same time, nanoflowers made of gold and zinc oxide can be used as the core components of biosensors. Through the signal amplification effect, they can accurately detect substances such as glucose and hydrogen peroxide produced by bacterial metabolism, achieving rapid screening for the presence of bacteria and providing efficient tools for microbial pollution monitoring and clinical infection diagnosis.
It is important to acknowledge that nanoflowers also face certain limitations. For instance, the relatively ​​high cost of noble metal-based nanomaterials​​ may hinder their large-scale deployment in resource-limited settings. Additionally, some nanoflower-based detection platforms still exhibit ​​suboptimal sensitivity​​ when targeting low-abundance bacterial biomarkers in complex matrices, which affects their reliability in early diagnosis or trace detection. Furthermore, certain optical-based detection systems (e.g., colorimetric or fluorescence assays) are ​​susceptible to interference from background pigments​​ in real samples (e.g., food homogenates or biological fluids), potentially leading to false-positive or false-negative results [10].

To address these challenges, we developed a novel detection system based on nanoflowers. We designed a system for ultra-sensitive, rapid, and low-cost bacterial detection. It combines recognition, catalysis, and signal amplification in one platform (Figure 3).

Our integrated nanoflowers system comprises four synergistic components:
1. Phage-derived Binding Proteins (PBPs): Provide species-specific bacterial recognition.
2. Horseradish Peroxidase (HRP): Catalyzes 3,3',5,5'-Tetramethylbenzidine (TMB) oxidation for visible signal generation.
3. Gold-Platinum Nanozyme (AuPt): Enhances catalytic activity with peroxidase-like properties.
4. Calcium Phosphate Matrix (CaPO4): Forms 3D nanoflowers structure providing high surface area.

Our goal is to develop a precise bacterial detection method that is ultra-sensitive, rapid, low-cost, and widely applicable. By leveraging the efficient catalysis of AuPt nanozyme and HRP for dual-signal amplification, and their color reaction with TMB, ultra-sensitive bacterial detection is achieved. We use genetically engineered PBPs with the function of specifically binding to bacteria for recognition, enabling precise targeting. The nanoflowers shape serves as a carrier, and its porous, high specific surface area properties provide an "integrated platform" for PBP, HRP, and AuPt, promoting the synergistic effect of each module to achieve rapid detection. It increases the contact area with bacteria to improve recognition efficiency, facilitates the diffusion of substrates TMB and hydrogen peroxide, and enhances signal catalytic reactions. Combined with a mobile APP for rapid testing, it can be used by a wide range of users from professional inspectors to the general public, making it easy to popularize and use (Figure 4).


We will also develop an ​all-in-one APP that integrates ​on-site detection with science education​​, offering users a seamless and interactive experience. This program will guide users through the entire testing process with intuitive visual instructions and provide real-time, interpretable results—such as colorimetric changes readable by the naked eye or quantified via smartphone-based RGB analysis. Additionally, it will include educational modules that explain the principles behind the detection technology, the significance of bacterial biomarkers, and preventive health measures. By combining diagnostic functionality with contextual learning, the APP lowers the barrier to operation, reduces reliance on complex equipment, and enhances public awareness of microbial risks. This approach is particularly valuable in ​resource-limited settings​​, where accessible and educational point-of-care tools can significantly impact community health outcomes.

Our project aims to redefine food safety monitoring by creating a versatile, accessible, and high-performance POCT platform that addresses these gaps. We aim to achieve the following four interconnected objectives:
♦ Rapid Detection: We aim to achieve sample-to-result detection in under 30 minutes. The high catalytic efficiency of the nanoflowers, combined with streamlined operational procedures, enables rapid initiation of the color reaction upon bacterial binding.
♦ Ultra-Sensitive Detection: Our target is to detect bacterial concentrations as low as 10 CFU/mL. The unique structural and catalytic properties of the nanoflowers amplify the signal even at extremely low bacterial loads, ensuring high sensitivity and reducing the risk of false negatives.
♦ Specific Detection: The system is designed to accurately identify target pathogens within complex samples—such as milk, tea, or multispecies bacterial mixtures—without cross-reactivity. The specificity derives from the fusion proteins displayed on the nanoflowers, which selectively bind target bacteria and trigger a color change only in their presence.
♦ User-Friendly Detection: We strive to make the platform accessible and easy to use, requiring minimal instrumentation. Results can be interpreted visually or quantified via a smartphone application that analyzes RGB values. This eliminates the need for complex laboratory equipment and expands the system's applicability in resource-limited settings.

[1] Mi, F., Hu, C., Wang, Y., Wang, L., Peng, F., Geng, P., & Guan, M. (2022). Recent advancements in microfluidic chip biosensor detection of foodborne pathogenic bacteria: a review. Analytical and Bioanalytical Chemistry, 414(9), 2883-2902.
[2] Prabhakar, P., Sen, R. K., Mayandi, V., Patel, M., Swathi, B., Vishwakarma, J., Dhand, C. (2022). Mussel-inspired chemistry to design biodegradable food packaging films with antimicrobial properties. Process Safety and Environmental Protection, 162, 17-29.
[3] Pires, S. M., Desta, B. N., Mughini-Gras, L., Mmbaga, B. T., Fayemi, O. E., Salvador, E. M., Devleesschauwer, B. (2021). Burden of foodborne diseases: think global, act local. Current Opinion in Food Science, 39, 152-159.
[4] https://www.who.int/health-topics/foodborne-diseases
[5] Katagum, Y. M. M., Musa Moi, I. M., Ibrahim, Z., Mohammed Abubakar, B., Abdullahi, A., Yiga, G. A., Mahmud, Z. (2022). Properties of Foodborne Pathogens and Their Diseases. In A. Lamas, C. M. Franco Abuin, & P. Regal (Eds.), Foodborne Pathogens - Recent Advances in Control and Detection. Rijeka: IntechOpen.
[6] Saravanan A, Kumar PS, Hemavathy RV, et al. Methods of detection of food-borne pathogens: a review[J]. Environmental Chemistry Letters. 2021, 19 (1): 189-207.
[7] Larkins MC, Thombare A. Point-of-Care Testing. 2023 May 29. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2025 Jan–. PMID: 37276307.
[8] Samuel L. Point-of-Care Testing in Microbiology. Clin Lab Med. 2020 Dec;40(4):483-494. doi: 10.1016/j.cll.2020.08.006. PMID: 33121617.
[9] Léonard, E., & Jeux, V. (2022). 14 - Illuminating metal oxides containing luminescent probes for personalized medicine. In S. Sagadevan, J. Podder, & F. Mohammad (Eds.), Metal Oxides for Optoelectronics and Optics-Based Medical Applications (pp. 339-395)
[10] Shi, F., Zhu, H., Li, G., Peng, M., Cao, Y., Xia, Y., Yang, Z. (2025). Nanozyme Cascade Self-Powered H2O2 Strategy for Chemiluminescence Array Sensor to Monitor and Deactivate Multiple Bacteria. Analytical Chemistry, 97(13), 7128-7137.