A deep dive into AI integration and advanced nanobiosensor technologies for enhanced bacterial infection monitoring

1.1 Research questions

• What are the main developments in integrating AI, biosensor technology, and nanotechnology that have improved the ability to monitor, identify, and manage bacterial infections?

• In what ways have AI methods, especially ML and DL approaches, enhanced the capability of sensors to deal with bacterial infections efficiently?

• How have integrated biosensor technologies and nanotechnology-based treatments advanced the detection and control of bacterial infections, considering factors such as contamination by bacterial agents, resistance mechanisms, and biofilm formation?

• How does the combination of biosensor technologies and nanotechnology-based solutions improve the identification and management of bacterial infections, taking into account aspects such as bacterial contamination, resistance mechanisms, and the emergence of biofilms?

• How have several improvements, such as the use of photodynamics, electrochemistry, acoustics, electromagnetism, and photothermal resonance, enhancing the diagnostic and therapeutic powers of designed NBs in the treatment of bacterial infections?

• What are the challenges and future paths in advancing and utilizing intelligent nanobots for managing bacterial infections, and how can these improvements be applied to overcome these challenges for more accurate and customized diagnostic and therapeutic interventions?

1.2 Contributions

• This article offers an in-depth and comprehensive analysis of the latest advancements in AI-integrated technology and nanotechnology tools that significantly enhanced the monitoring, detection, and control of bacterial infections. By examining the specific applications of smart NBs, the study offers a detailed understanding of how these technologies have evolved and their overall impact on bacterial infection management.

• Our study explores how AI-based techniques, particularly ML and DL approaches, have improved the performance of sensors in effectively monitoring bacterial infections inside the specified period.

• We investigate how integrated biosensor and nanotechnology-based treatments advance the control and detection of bacterial infections, addressing contamination, resistance, and biofilm formation. A detailed analysis of contamination by bacterial agents, resistance mechanisms, and microorganism bio-curtains, offering insights into pathogen-based infection complexities and dynamics.

• We examined various enhancements, including photodynamics, electrochemistry, acoustics, electromagnetism, and photothermal resonance, that have improved the diagnostic and therapeutic capabilities of engineered NBs in bacterial infection management. This analysis demonstrates the multifaceted approaches used to enhance the effectiveness and functionality of NBs.

• The article identifies the current challenges in the development and application of smart NBs. We also discuss potential solutions and future directions, emphasizing the advancements that can be leveraged to address the highlighted challenges. We provided a roadmap for future research and development, aiming for more precise and tailored diagnostic and therapeutic interventions.

2.1 Conventional methods

The challenge of treating infections is significantly compounded by bacterial survival in biofilms, where populations are encased in a protective matrix, leading to heightened resistance against antimicrobial agents. Biofilms contribute to the persistence and severity of bacterial infections, particularly in healthcare settings. Despite extensive research on bacterial resistance mechanisms, the complex dynamics of biofilm formation and development have not been thoroughly explored. Traditional techniques for identifying and managing bacterial infections, such as smear microscopy, isolation cultures, biochemical tests, and histiocyte cultures, are becoming less prevalent due to their limitations. Synthetic peptides derived from natural host-defence peptides demonstrate antibiofilm activity. Combined with traditional antibiotics, these peptides exhibit a synergistic effect, reducing the required antibiotic concentration to eradicate specific bacterial strains effectively [12,13]. These methods often suffer from restricted sensitivity, prolonged processing times, and complex handling procedures, leading to inaccurate diagnoses and ineffective treatments [14]. As a result, healthcare-associated infections are frequently mismanaged. There is an urgent need to develop innovative techniques to address the challenges posed by bacterial infections, biofilm formation, and antibiotic resistance. Advanced tools and methodologies are required to combat bacterial infections and mitigate the global impact of antibiotic resistance. Researchers are leveraging AI tools, nanotechnology, and bioinformatics to develop more effective diagnostic procedures and treatments for bacterial infections [15]. Integrating advanced technologies and multidisciplinary research efforts is essential in this endeavor. Collaboration between academia, industry, and healthcare sectors is crucial for the development and implementation of specific strategies to combat bacterial infections and safeguard public health.

2.2 AI-integrated biosensor technology

The integration of AI with biosensor technology is becoming an influential factor in the constantly shifting healthcare industry, transforming the way diseases get diagnosed and managed. The use of computer-aided diagnostics and AI technologies in clinical practice is an important achievement, though it comes with major challenges [16]. It is observable that medical imaging approaches [17], such as X-ray, magnetic resonance imaging, computed tomography, and positron emission tomography, are crucial methods in detecting different diseases [18]. They offer important information about different pathological situations. The diversity of openly available imaging and biological resources improves the abilities of AI systems, making it simpler to adapt them for medical purposes. Pioneering platforms like PathAI [19], Viz.ai, and Freenome harness the power of AI to augment the diagnostic capabilities of pathologists, enhance clinical diagnostics, aid clinical trial support, and advance translational research. Moreover, entities like Freenome revolutionize cancer screening, diagnostics, prevention, and overall disease management. The pervasive adoption of AI-powered tools underscores a commitment to leveraging cutting-edge technologies across various medical domains, from diagnostic imaging to biosensors [20,21]. In tandem with the burgeoning utilization of AI in medical imaging, biosensor technology emerges as a pivotal frontier in disease detection and management. The amalgamation of AI algorithms with biosensors heralds a paradigm shift in disease diagnostics, empowering clinicians with enhanced sensitivity, specificity, and accuracy in detecting biomarkers indicative of diverse health conditions. This joint coordination not only enhances diagnostic capabilities but also paves the way for personalized healthcare, offering tailored treatment methods adapted to the unique features of each patient [22].

Applications of biosensors in conjunction with AI Figure 1 enable lightning-fast detection of diseases, enabling proactive therapy prior to the appearance of clinical symptoms. AI-enabled NBs have continuous monitoring capabilities and offer up-to-the-minute data on the progression of diseases and the effectiveness of treatments. This enables doctors to enhance therapeutic tactics and improve patient outcomes. Furthermore, the use of AI-powered inspection of biosensor data enables clinicians to promptly evaluate the efficacy of medicines in real-time [23]. This allows clinicians to promptly modify treatment regimens, and the likelihood of antibiotic resistance may be reduced, leading to enhanced patient care. The development of powered by AI biosensors that easily connect with current healthcare systems represents a new age of improved communication among medical professionals and efficient clinical operations. AI researchers may provide tailored solutions to boost diagnostic precision, optimize workflow effectiveness, and improve patient care by comprehending the specific challenges and requirements encountered by doctors in various clinical roles. The combination of AI and biosensor technology is poised to significantly alter the management of illnesses and the delivery of healthcare. This confluence has a chance to result in a substantial transformation toward more efficient, customized, and patient-centric care models. The combination of AI with biosensor innovations in health care has the promise to usher in a new age of precise treatment. This would include timely identification, customized treatment, and enhanced results for patients, eventually reshaping the criteria for achieving healthcare performance.

Figure 1

Key nanotechnology techniques in biosensing for bacterial infections.

2.3 Smart NBs in bacterial infection management

The smart NB solution is a modern invention that revolutionizes the detection and management of infections caused by bacteria. These sensors are designed to instantly and accurately detect the existence and behavior of microorganisms. Smart NBs are pivotal in diagnosing infectious diseases, offering sensitivity, selectivity, and rapid detection capabilities. Combining nanomaterials and biosensing technology, these sensors provide versatile tools for disease diagnosis, including point-of-care methods for swift pathogen detection. While offering promise in controlling disease spread, the ongoing research focuses on optimizing these sensors and exploring new opportunities for enhanced diagnosis using nanotechnology [24]. Smart NB methods are frequently employed to detect bacteria instantaneously, enabling ongoing surveillance of their development [25,26]. Smart nanobots for bacterial infection prevention can be grouped into many broad categories and have an extensive list of functions. Table 1 presents an overview of many different uses together with the corresponding NB technology. It is observable that fluorescent NBs can quickly detect the existence of microorganisms, allowing medical professionals to react immediately as necessary. Point-of-care diagnostics use paper-based NBs to swiftly and precisely identify infections caused by bacteria at the patient’s bedside. Smart nanobots play a vital role in preventing antimicrobial resistance as they examine the variables that contribute to resistance in strains of bacteria. DNA-based NBs demonstrate exceptional accuracy in detecting such markers, enabling accurate administration of antibiotics and monitoring developments in resistance. Furthermore, they suggest potential methods for destroying bacterial biofilms, which are notoriously tough to eliminate and are frequently associated with chronic infections and resistance to antibiotics. Electrochemical nanobots are designed specifically to detect and eliminate features unique to biofilms, with the capacity to avoid the emergence of permanent diseases by addressing these resilient bacterial populations as highlighted by [27]. In addition, these small devices enable remote detection of bacterial infections in individuals, utilizing functional NBs that have wireless connectivity for transmitting real-time data to medical professionals. This allows for swift intervention and personalized treatment plans tailored to the unique attributes of each patient. The researchers deeply focused on this era, however, on enhancing the versatility and specificity of detection methods, as well as exploring novel approaches for targeted treatment and prevention strategies that need to be tailored to individual patient needs. In addition, research efforts could aim to further integrate wireless connectivity and remote monitoring capabilities into smart NBs for real-time disease surveillance and personalized healthcare interventions.

2.4 Nanotechnology for biosensing

The rapid evolution of molecular biological science has propelled nanotechnology into a dynamic field characterized by continuous innovation and refinement. Leveraging nanotechnology, the scientific community has achieved remarkable breakthroughs, particularly in the realms of biomedical engineering, food safety management, and environmental health monitoring [28]. Nanotechnology presents a promising avenue for addressing challenges associated with bacterial infections, antimicrobial resistance, and biofilms [29]. With its unique chemical, biological, and physical properties, nanotechnology has emerged as an indispensable tool across various medical domains [30,31]. In light of the widespread application of nanomaterials and nanotechnology in diagnosing and treating bacterial infections, a comprehensive examination of recent research findings becomes imperative. This article endeavors to scrutinize the latest advancements in crafting tailored NBs for the detection and management of bacterial diseases. These innovative biosensors harness a diverse array of nanotechnology methodologies, encompassing electrochemistry, acoustic dynamics, electromagnetism, photothermal responses, and surface plasmon resonance. The multidisciplinary nature of NB techniques holds pivotal importance in unraveling intricate facets of bacterial responses and guiding innovative approaches in diagnosis and therapy. Ongoing research endeavors in nanotechnology are dedicated to exploring novel frontiers and enhancing the efficacy of NBs for precise and efficient diagnosis and treatment of bacterial infections. Through rigorous scientific inquiry and technological advancement, the field of nanotechnology continues to pave the way for transformative solutions in biomedical science and healthcare (Table 2).

3.1 ML approaches for detecting bacterial infections

ML methods have greatly improved biosensor technologies by increasing their sensitivity, accuracy, and efficiency. Significant progress has been made in the development of customized integrated sensor arrays that combine 2D nanomaterials with fluorescently labeled single-stranded DNA. The arrays can precisely identify different bacteria, including those that are resistant to drugs, by examining the unique patterns of response that occur when bacteria contact with the sensing components. The technique has a remarkable level of accuracy, with a detection rate of 97.9%, in recognizing pathogens such as S. aureus and Escherichia at various levels of concentration. Moreover, the integration of Surface-Enhanced Raman Scattering (SERS) with ML techniques like support vector machine (SVM) and random forest has greatly enhanced the ability to identify viruses [32,33].

This combination enables the rapid and accurate identification of respiratory viruses, such as SARS-CoV-2, common human coronaviruses, and influenza viruses. By using the enhanced sensitivity of SiO2-coated silver nanorod substrates, these systems can accurately differentiate and classify virus species and strains with an accuracy above 99%. This makes them a powerful tool for managing viral epidemics. In addition, the combination of optical biosensors, nonlinear optics, and ML enhances viral detection by using multiphoton interactions to boost both sensitivity and specificity. This makes them very effective in identifying a variety of viruses, including the SARS-CoV-2 virus [47]. Through the use of ML Figure 2, these biosensors can examine complex biological data and detect mobile entities inside the human body, facilitating rapid detection of possible health problems and quick intervention [43]. ML-enhanced biosensor technologies have revolutionized pathogen detection and virus identification, offering unprecedented levels of sensitivity and accuracy. Customized integrated sensor arrays, combining nanomaterials with DNA labeling, enable precise identification of bacteria, including drug-resistant strains, with high detection accuracy.

Figure 2

Generic overflow of ML approaches for bacteria diagnosis.

3.2 DL techniques for detecting bacterial infections

DL algorithms have significantly transformed biosensor technology by offering advanced data analysis and prediction capabilities. Carbon nanotube (CNT)-based biosensors, when combined with deep neural networks (DNNs), have shown substantial promise in the realm of medical diagnostics, namely, for the detection of heart failure [39]. These biosensors utilize electrochemical impedance spectroscopy (EIS) data to accurately forecast B-type natriuretic peptide (BNP) levels, hence eliminating the necessity for conventional error-prone analytical methods. This method improves both the accuracy of diagnosis and the availability of the technology for point-of-care testing. Nonenzymatic electrochemical biosensors, employing a back-propagation neural network, exhibit exceptional selectivity in the detection of glucose and lactate. These sensors utilize specialized working electrodes that are incorporated into arrays of electrochemical microdroplets. When combined with neural network analysis, they can accurately forecast the levels of analytes, even in complicated biological samples, simplifying the detection process and reducing the need for sophisticated material production and selection [58].

Figure 3 illustrates the general features of DL models, such as DNN and CNNs, which have achieved great success in recognizing and measuring vitamin B6 molecules through 3D fluorescence spectra [52]. These models may attain accuracy levels of up to 100%, showing their effectiveness in distinguishing between molecules with very similar chemical structures. Possessing this skill is essential for precise medical diagnosis and treatment. In addition, advanced DL models such as LSTM networks and bidirectional LSTM (Bi-LSTM) with Bahdanau attention have demonstrated high accuracy in predicting respiratory rate using data from bio-sensors such as ECG, PPG, and surface electromyogram (sEMG) [54]. The Bi-LSTM with attention mechanisms offers very precise predictions, which are essential for monitoring patient health in real time [37]. A novel lens-free holography microscope, which incorporates DL techniques, has been created for digital single-particle counting in nucleic acid detection, without the need for pre-amplification. This cost-effective and portable technology collects three-dimensional images of small spherical objects and uses an enhanced YOLOv7-based algorithm to effectively and precisely identify minuscule items [57,59].

Figure 3

Technical overflow of DL techniques for the identification and monitoring of bacteria.

The combination of powerful ML and DL algorithms with state-of-the-art biosensor technology is resulting in significant progress in pathogen detection. ML approaches improve the sensitivity and accuracy of biosensors in identifying different pathogens, such as viruses and bacteria, by evaluating intricate data patterns and enhancing the efficiency of detection procedures. However, the ML-based approaches are not robust in complex problems as the features engineering is often manual. DL algorithms provide advanced data processing and prediction capabilities, allowing for precise diagnoses and real-time health monitoring. These technological advancements are improving the accuracy, efficiency, and accessibility of diagnostic techniques, which are vital for managing public health, detecting diseases early, and providing timely medical treatment. The integration of machine learning, deep learning, and nanotechnology is revolutionizing biosensor development, leading to diagnostic instruments that are more efficient, precise, and accessible. This advancement has substantial implications for healthcare, food safety, and disease prevention. The progress in this discipline is enhancing the existing state of pathogen detection and also creating opportunities for future study and application in other areas, such as environmental monitoring, food safety inspection, and clinical diagnostics.

4.1 Contamination by bacterial agents

It is generally acknowledged that once bacteria enter the body, they reproduce, multiply, and release toxic substances. Infection with bacteria or, in extreme circumstances, intoxication caused by germs can manifest in various pathogenic ways in the body. Bacterial infections commonly appear in two main forms: acute and persistent. The effects of different pathogenic bacteria on the host organism can differ [72]. During acute infections, bacteria trigger an immediate inflammatory reaction in the host, typically marked by symptoms such as redness, swelling, increased temperature, discomfort, and reduced functionality. In contrast, chronic infections develop slowly as bacteria gradually create biofilms, which make them more resistant to antimicrobial treatments and the host immune system. It is important to mention that although self-limiting bacterial infections might happen, most bacterial infections present considerable difficulties in terms of therapy [73]. The outcome and intensity of bacterial infections depend on the interaction between human immunity and bacterial pathogenicity. Several variables significantly impact the infection’s progression, including the infecting agent’s dosage, environmental conditions, co-infections, and associated factors. A thorough comprehension of these aspects is essential in ascertaining the result of bacterial infections and directing efficient approaches for prevention and therapy. Current research efforts strive to understand the complicated dynamics of bacterial infections, leading to progress in developing treatments and improving our capacity to deal with the intricacies of bacterial pathogenesis (Table 4).

4.2 Resistance to bacterial agents

Antibiotic use is known to promote the evolution of bacteria that are resistant to their effects, which in turn leads to their eventual dominance. A major global health concern, the rise of antibiotic-resistant microorganisms has made the significant shift toward viable therapies seem like a distant dream. It is crucial to acknowledge that antibiotic resistance is an inherent and unavoidable occurrence. Bacteria have undergone ongoing evolution over billions of years, acquiring adaptations to counteract the effects of antimicrobial treatments. Bacterial resistance is influenced by a confluence of environmental and intrinsic factors. The quick spread of bacterial drug resistance is greatly influenced by environmental mechanisms, specifically the protracted process of ecological evolution. Alterations to the DNA sequence, such as genetic transfer across bacterial species, can occur when bacteria colonize or infect hosts in the environment [83,84]. Gaining a deep comprehension of the complex mechanisms behind antibiotic resistance is essential for formulating comprehensive approaches to tackle this rapidly developing worldwide health crisis. Current research efforts are focused on discovering innovative strategies to reduce antibiotic resistance, providing possible solutions to the difficulties posed by this intricate problem.

4.3 Microorganism bio-curtain

The process of bacterial biofilm formation might be described as a gripping narrative, resembling a symphony with four distinct stages. In Figure 4, microorganisms adhere to surfaces using mechanisms such as the cell’s surface charge of everything, the van der Waals force, its hydrophobicity, as well as electrostatic force [85], similar to artists using charged brushes. The story then transitions to a complex dance, as microorganisms move through liquid environments or gather on solid surfaces, resembling artists on a canvas, using the coordinated movements of rotating flagella [86]. The climax occurs during the maturity phase, where biofilm micro-colonies, resembling masterpieces, are surrounded by water transport channels. These channels facilitate the movement of nutrients and coordinate quorum sensing and gene regulation [87]. In the last stage, known as dispersion, bacteria elegantly transition between floating states and biofilm states within a complex community of many cells [88]. The fully developed biofilm serves as a channel for the transfer of energy, chemicals, and information, strengthening microorganisms underneath against unpredictable external conditions. This biofilm development pattern serves as evidence of the ability of cells to thrive in challenging conditions and spread out into new ecological habitats, similar to innovative explorers [89,90]. The composition’s subtleties are meticulously adjusted by factors such as bacterial density, duration of life, temperature, fluid flow characteristics, nutrient concentration, and the interplay of surface material qualities. The complex flagella and fimbriae on the bacterial canvas are additional decorations that play important functions in the development of biofilms. Continuing research efforts, similar to innovative composers, aim to enhance our comprehension and develop tactics for modulating or regulating the formation of biofilms in various environments. The life cycle of a microbial biofilm is illustrated with relevant features (Figure 4). where the process begins with initial attachment, where planktonic bacteria temporarily adhere to a surface through weak interactions. This progresses to irreversible attachment, where bacteria produce extracellular polymeric substances (EPS) to secure permanent adhesion. In the microcolony formation phase, bacteria proliferate, forming small clusters within the EPS matrix. During maturation, the biofilm evolves into a complex, three-dimensional structure with channels facilitating nutrient and waste flow. Finally, in the dispersal phase, cells from the mature biofilm are released as planktonic bacteria, ready to colonize new surfaces. This iterative process guarantees the persistence, expansion, and dissemination of bacterial populations across many habitats.

Figure 4

Phases overview of the biofilm cycle.

5.1 Integration of photodynamics into innovative NBs

The emergence of PDT represents a notable advancement in the targeted treatment of bacteria, propelled by the continuous advancement of technology for optics. In recent years, there has been tremendous interest in the continual development of new photosensitive substances, which offer a novel and inventive approach to antibacterial treatments. This innovative antibacterial medication employs PD principles to induce the production of reactive oxygen compounds within microbial cells, leading to their eradication. The utilization of nanotechnologies in bacterial detection and therapy by PD is becoming increasingly popular due to its advantages, such as fewer adverse effects and decreased vulnerability to medication resistance [91,92]. PDT, as a burgeoning therapeutic method, exhibits immense potential in the accurate and efficient management of bacterial infections. As research progress continues, the combination of optical technologies and nanomaterials is increasingly enabling new opportunities, enhancing the field of bacterial therapy and strengthening human defenses against infectious pathogens.

5.2 NBs enhanced with electrochemistry

There has been considerable interest in using bioelectric nanotechnology techniques to address resistance genes and biofilms of bacterial species. Specifically, researchers have focused on surface modification methods that disrupt the bio-electric balance within bacteria, both internally and externally [25,99]. Moreover, the inherent benefits of electrochemical sensors, which include affordability, little energy usage, lack of intricate automation, and micro-miniaturization, make them well suited for the quick and precise detection of bacteria. When combined with microfluidic technology and nanotechnology, this becomes especially important since it allows for rapid and extremely accurate identification of intricate bacterial samples directly at the location. Furthermore, the simplicity with which electrochemical detection can be scaled down and rendered portable increases its appropriateness for swift and economical identification of bacteria in areas with restricted medical facilities. The purpose of this flexibility is to avoid significant public health incidents caused by delays in detection, highlighting the essential contribution of bioelectric nanotechnology in improving accessible and prompt bacterial detection methods. Continual research efforts are being made to improve these methods, guaranteeing their effectiveness and availability for general use in various healthcare environments. While this section focuses on bacterial detection, Table 6 provides a summarized review of advancements in NBs for the detection of transmissible and nontransmissible diseases, highlighting the broader applications of this technology. Figure 5 illustrates the integrated biosensors technology for bacterial infection management.

Figure 5

Applications of integrated biosensors technology for bacterial infection management.

5.3 Acoustic signal-enhanced NBs

Sonodynamic therapy is a treatment method that is based on PDT. It primarily employs low-frequency ultrasound (LFU) to activate sensitizers and stimulate the production of reactive oxygen species (ROS). Sonodynamic treatment involves using ultrasonic sound stimulation to activate acoustic sensitizers, resulting in the production of reactive oxygen species. These ROS have strong lethal effects on certain multidrug-resistant microbes without the establishment of resistance [112,113]. Ultrasound, a noninvasive therapeutic technique, shows great potential for use in clinical settings. This is because it has the unique capacity to deeply penetrate tissues, even when faced with difficult obstacles [114,115]. Currently, the precise mechanism of sonodynamic treatment remains unidentified. However, the prevalent viewpoint highlights ROS as the key agent responsible, independent of the specific mechanism involved. Antimicrobial sonodynamic therapy (SDT) is an advanced and revolutionary technology that has the ability to effectively combat bacterial infections. The current study in this area seeks to decipher the complexities of the sonodynamic treatment mechanism, leading to better knowledge and a wider range of applications in the field of antimicrobial therapies. The inherent nonresistance characteristic of an SDT, along with its nonintrusive nature and exceptional tissue penetration capability, establishes it as a highly promising approach in the ongoing fight against bacterial diseases.

5.4 Acoustic-responsive nanostructure for bacterial capture

An innovative approach that combines antibacterial acoustic-dynamic treatment with antivirulent immunotherapy, drawing inspiration from biological processes. A experiment was conducted to modify an antibody that specifically targets the alpha-toxin of MRSA, enabling it to attach to the outer surface of cell membrane nanovesicles. These nanovesicles were then enclosed with a substance that is responsive to sound. This novel approach goes beyond traditional passive absorption of virulence by utilizing natural red blood cell (RBC) membranes [114]. It takes advantage of the strong antiboil-toxin interaction to enhance the efficiency of nanovesicles in capturing virulence in laboratory conditions.

When ultrasound is used, acoustic sensitizers are crucial in producing reactive oxygen species, which effectively eradicate microorganisms and accelerate the removal of harmful effects. The efficacy of our antibody-based nanotrap in detecting MRSA infections and distinguishing between lesions and sterility has been validated by in vivo optical imaging. This novel combination of antimicrobial sonodynamic therapy and antivirulent immunotherapy provides a potent and antibiotic-free nanotherapeutic approach to combat multidrug-resistant bacterial infections, thereby paving the way for cutting-edge medical interventions. The generic visual overflow of the three main parts of biosensor is shown in Figure 6. Continuing research endeavors to enhance and broaden the uses of this combined treatment approach to have a more extensive and significant effect in clinical settings.

Figure 6

The three parts of a biosensor – the detector, the transducer, and the output system.

5.5 Nano-biotechnological sensors operating on electromagnetic forces

Magnetic nanoparticles are small, uniform particles with a size between 1 and 100 nm. Particles with these unusual properties exhibit features seen in other nanomaterials as well as those associated with quantum size and surface effects. Through the integration of superpara magnetization with the inherent magnetic conductivity of magnetic materials, and more especially magnetic nanoparticles, exhibit extraordinary characteristics. Their advantages also include a straightforward preparation process, high surface reactivity, and exceptional compatibility with living things. Conductive nanoparticles [122], magnetic iron oxide (Fe₃O₄) particles, for example, which are nanometer-sized, have lately garnered a lot of attention from scientists. The surface effects and superparamagnetism of magnetic Fe₃O₄ nanoparticles make them very interesting and have great potential for many uses in fields as diverse as biomedicine and sewage treatment. At room temperature, an external magnetic field improves the surface modification of Fe₃O₄ which allows it to incorporate distinct functionalities like adsorption and separation. In addition, Fe₃O₄ nanoparticles find widespread application in the realm of water and food safety monitoring. To aid in bacterial enrichment and separation in complex substrates, magnetic nanoparticles are frequently employed. In addition, they make it possible to directly test clinical specimens for microorganisms with low abundance. The distinctive properties of Fe₃O₄ nanoparticles make them stand out among the other magnetic nanophase materials. Their magnetic field reactivity and surface modifiability make them very flexible tools. Their adaptability and practicality in various scientific fields are evident from this [123,124].

5.6 Nano-biosensing with photothermal resonance

Photothermal therapy (PTT) is a highly regarded and extensively studied method for identifying and treating bacterial infections. It is noninvasive and has the ability to selectively target the disease. PTT, utilizes physical mechanisms along with chemical approaches [132,133]. Microorganisms, as living organisms with complex cellular structures, experience protein denaturation and subsequent death when exposed to high temperatures. The sterilizing process based on this idea is widely known as heat sterilization technology. This innovative approach has significant promise for revolutionizing bacterial diagnostic and treatment protocols, marking a pivotal advancement in the realm of medical technologies.

5.7 Bacterial disease theranostics facilitated by nano-sensors assembled in situ

One new way to image and identify cancer cells, tissues, and microbes is with in situ synthesis technology. Incorporating metal elements chemically into live organisms to form functional nanocluster probes accomplishes this [140]. Among these methods is fluorescence in situ hybridization (FISH), a new tool for determining the spatial distribution of microbes in biofilms and quantifying microbial communities. There is no need to extract nucleic acids while using FISH, which differs from previous approaches. To conduct in situ hybridization, it substitutes fluorescent oligonucleotide probe labeling. Multiple populations can be identified at once by marking the probes with fluorescent dyes with distinct excitation and emission spectra [141]. Using in situ synthesis extends beyond enhancing antimicrobial permeability in biofilms and has wider implications. It may cause biochemical or physical processes, like photothermal conversion, that compromise biofilm integrity. Chemically linking nanoclusters of gold with the antibacterial peptide daptomycin demonstrated the production of a very efficient antibacterial molecule. The synthesized conjugated structure significantly boosts the synergistic impact by fusing the two parts’ best qualities. The structure effectively eliminates bacterial biofilms by creating membrane holes through localized daptomycin action [142,143]. By using in situ chemical synthesis techniques, the authors created bioresponsive nanocomposite materials for disinfection and bacterial bioimaging. The novel biofilm microenvironment was used to construct a nanoheating platform with multiple applications. The nanoclusters, which were sensitive to the microenvironment, were able to detect bacteria and promote sterilization through electrostatic interactions, breakdown of the cell membrane, suppression of biofilm formation, and accumulation of reactive oxygen species (ROS) [144]. The particular interactions with bacteria emphasize the promise of in situ synthesis as a versatile instrument for accurate detection and treatment of bacterial infections [145].