Rapid Identification of Biofilms Using a Robust Multichannel Polymer Sensor Array

Nanotechnology improves the detection of bacteria: Recent advances and future perspectives

Nanotechnology has advanced significantly, particularly in biomedicine, showing promise for nanomaterial applications. Bacterial infections pose persistent public health challenges due to the lack of rapid pathogen detection methods, resulting in antibiotic overuse and bacterial resistance, threatening the human microbiome. Nanotechnology offers a solution through nanoparticle-based materials facilitating early bacterial detection and combating resistance. This study explores recent research on nanoparticle development for controlling microbial infections using various nanotechnology-driven detection methods. These approaches include Surface Plasmon Resonance (SPR) Sensors, Surface-Enhanced Raman Scattering (SERS) Sensors, Optoelectronic-based sensors, Bacteriophage-Based Sensors, and nanotechnology-based aptasensors. These technologies provide precise bacteria detection, enabling targeted treatment and infection prevention. Integrating nanoparticles into detection approaches holds promise for enhancing patient outcomes and mitigating harmful bacteria spread in healthcare settings.

MoS2-Based Sensor Array for Accurate Identification of Cancer Cells with Ensemble-Modified Aptamers

In this work, we present an array-based chemical nose sensor that utilizes a set of ensemble-modified aptamer (EMAmer) probes to sense subtle physicochemical changes on the cell surface for cancer cell identification. The EMAmer probes are engineered by domain-selective incorporation of different types and/or copies of positively charged functional groups into DNA scaffolds, and their differential interactions with cancer cells can be transduced through competitive adsorption of fluorophore-labeled EMAmer probes loaded on MoS2 nanosheets. We demonstrate that this MoS2-EMAmer-based sensor array enables rapid and effective discrimination among six types of cancer cells and their mixtures with a concentration of 104 cells within 60 min, achieving a 94.4% accuracy in identifying blinded unknown cell samples. The established MoS2-EMAmer sensing platform is anticipated to show significant promise in the advancement of cancer diagnostics.

Tailored chitosan/glycerol micropatterned composite dressings by 3D printing for improved wound healing

Wound infection control is a primary clinical concern nowadays. Various innovative solutions have been developed to fabricate adaptable wound dressings with better control of infected wound healing. This work presents a facile approach by leveraging 3D printing to fabricate chitosan/glycerol into composite dressings with tailored micropatterns to improve wound healing. The bioinks of chitosan/glycerol were investigated as suitable for 3D printing. Then, three tailored micropatterns (i.e., sheet, strip, and mesh) with precise geometry control were 3D printed onto a commercial dressing to fabricate the micropatterned composite dressings. In vitro and in vivo studies indicate that these micropatterned dressings could speed up wound healing due to their increased water uptake capacity (up to ca. 16-fold@2 min), benign cytotoxicity (76.7 % to 90.4 % of cell viability), minor hemolytic activity (<1 %), faster blood coagulation effects (within 76.3 s), low blood coagulation index (14.5 % to 18.7 % @ 6 min), enhanced antibacterial properties (81.0 % to 86.1 % against S. aureus, 83.7 % to 96.5 % against E. coli), and effective inhibition of wound inflammation factors of IL-1β and TNF-α. Such tailored micropatterned composite dressing is facile to obtain, highly reproducible, and cost-efficient, making it a promising implication for improved and personalized contaminated wound healing.

Point-of-care detection devices for wound care and monitoring

Healthcare resources are heavily burdened by infections that impede the wound-healing process. A wide range of advanced technologies have been developed for detecting and quantifying infection biomarkers. Finding a timely, accurate, non-invasive diagnostic alternative that does not require a high level of training is a critical step toward arresting common clinical patterns of wound health decline. There is growing interest in the development of innovative diagnostics utilizing a variety of emerging technologies, and new biomarkers have been investigated as potential indicators of wound infection. In this review, we summarize diagnostics available for wound infection, including those used in clinics and still under development.

Near-Infrared Copper Sulfide Hollow Nanostructures with Enhanced Photothermal and Photocatalytic Performance for Effective Bacterial Sterilization

The development of nonantibiotic strategies to combat bacterial infection is highly needed, owing to the widespread infectious disease and bacterial resistance becoming a significant health threat to the world's population. In recent years, photoactivated antibacterial therapies including photocatalytic and photothermal therapies have attracted increasing attention due to their high efficiency and low side effect. Herein, we introduce a copper sulfide (Cu_2-xS) hollow nanostructure-based near-infrared antibacterial platform with synergy photothermal and photocatalytic properties for effective bacterial sterilization. Compared to traditional Cu_2-xS nanoparticles, this unique hollow Cu_2-xS nanostructure can generate multiple scattered light, which is conducive to light collection. Moreover, its thin shell can shorten the transmission distance of carrier, thus reducing the charge recombination that usually causes the greatest energy loss. As a result, such a Cu_2-xS hollow nanostructure enables enhanced photothermal and photocatalytic bacterial killing activities against both Escherichia coli and Staphylococcus aureus, showing promise for antibiotic-free infection treatment and other bacterial sterilization applications.

Direct discrimination of cell surface glycosylation signatures using a single pH-responsive boronic acid-functionalized polymer

Cell surface glycans serve fundamental roles in many biological processes, including cell-cell interaction, pathogen infection, and cancer metastasis. Cancer cell surface have alternative glycosylation to healthy cells, making these changes useful hallmarks of cancer. However, the diversity of glycan structures makes glycosylation profiling very challenging, with glycan 'fingerprints' providing an important tool for assessing cell state. In this work, we utilized the pH-responsive differential binding of boronic acid (BA) moieties with cell surface glycans to generate a high-content six-channel BA-based sensor array that uses a single polymer to distinguish mammalian cell types. This sensing platform provided efficient discrimination of cancer cells and readily discriminated between Chinese hamster ovary (CHO) glycomutants, providing evidence that discrimination is glycan-driven. The BA-functionalized polymer sensor array is readily scalable, providing access to new diagnostic and therapeutic strategies for cell surface glycosylation-associated diseases.

One-Component Multichannel Sensor Array for Rapid Identification of Bacteria

Bacterial infections routinely cause serious problems to public health. To mitigate the impact of bacterial infections, sensing systems are urgently required for the detection and subsequent epidemiological control of pathogenic organisms. Most conventional approaches are time-consuming and highly instrument- and professional operator-dependent. Here, we developed a novel one-component multichannel array constructed with complex systems made from three modified polyethyleneimine as well as negatively charged graphene oxide, which provided an information-rich multimode response to successfully identify 10 bacteria within minutes via electrostatic interactions and hydrophobic interactions. Furthermore, the concentration of bacteria (from OD₆₀₀ = 0.025 to 1) and the ratio of mixed bacteria were successfully achieved with our smart sensing system. Our designed sensor array also exhibited huge potential in biological samples, such as in urine (OD₆₀₀ = 0.125, 94% accuracy). The way to construct a sensor array with minimal sensor element with abundant signal outputs tremendously saves cost and time, providing a powerful tool for the diagnosis and assessment of bacterial infections in the clinic.

Direct Cytosolic Delivery of Proteins Using Lyophilized and Reconstituted Polymer-Protein Assemblies

PURPOSE

Cytosolic delivery of proteins accesses intracellular targets for chemotherapy and immunomodulation. Current delivery systems utilize inefficient endosomal pathways of uptake and escape that lead to degradation of delivered cargo. Cationic poly(oxanorbornene)imide (PONI) polymers enable highly efficient cytosolic delivery of co-engineered proteins, but aggregation and denaturation in solution limits shelf life. In the present study we evaluate polymer-protein nanocomposite vehicles as candidates for lyophilization and point-of-care resuspension to provide a transferrable technology for cytosolic protein delivery.

METHODS

Self-assembled nanocomposites of engineered poly(glutamate)-tagged (E-tagged) proteins and guanidinium-functionalized PONI homopolymers were generated, lyophilized, and stored for 2 weeks. After reconstitution and delivery, cytosolic access of E-tagged GFP cargo (GFPE15) was assessed through diffuse cytosolic and nuclear fluorescence, and cell killing with chemotherapeutic enzyme Granzyme A (GrAE10). Efficiency was quantified between freshly prepared and lyophilized samples.

RESULTS

Reconstituted nanocomposites retained key structural features of freshly prepared assemblies, with minimal loss of material. Cytosolic delivery (> 80% efficiency of freshly prepared nanocomposites) of GFPE15 was validated in several cell lines, with intracellular access validated and quantified through diffusion into the nucleus. Delivery of GrAE10 elicited significant tumorigenic cell death. Intracellular access of cytotoxic protein was validated through cell viability.

CONCLUSION

Reconstituted nanocomposites achieved efficient cytosolic delivery of protein cargo and demonstrated therapeutic applicability with delivery of GrAE10. Overall, this strategy represents a versatile and highly translatable method for cytosolic delivery of proteins.

A Polymer-Based Multichannel Sensor for Rapid Cell-Based Screening of Antibiotic Mechanisms and Resistance Development

Antibiotic resistance presents a critical threat to public health, necessitating the rapid development of novel antibiotics and an appropriate choice of therapeutics to combat refractory bacterial infections. Here, we report a high-throughput polymer-based sensor platform that rapidly (30 min) profiles mechanisms of antibiotic activity. The sensor array features three fluorophore-conjugated polymers that can detect subtle antibiotic-induced phenotypic changes on bacterial surfaces, generating distinct mechanism-based fluorescence patterns. Notably, discrimination of different generations of antibiotic resistance was achieved with high efficiency. This sensor platform combines trainability, simplicity, and rapid screening into a readily translatable platform.

Polymer-based chemical-nose systems for optical-pattern recognition of gut microbiota

Gut-microbiota analysis has been recognized as crucial in health management and disease treatment. Metagenomics, a current standard examination method for the gut microbiome, is effective but requires both expertise and significant amounts of general resources. Here, we show highly accessible sensing systems based on the so-called chemical-nose strategy to transduce the characteristics of microbiota into fluorescence patterns. The fluorescence patterns, generated by twelve block copolymers with aggregation-induced emission (AIE) units, were analyzed using pattern-recognition algorithms, which identified 16 intestinal bacterial strains in a way that correlates with their genome-based taxonomic classification. Importantly, the chemical noses classified artificial models of obesity-associated gut microbiota, and further succeeded in detecting sleep disorder in mice through comparative analysis of normal and abnormal mouse gut microbiota. Our techniques thus allow analyzing complex bacterial samples far more quickly, simply, and inexpensively than common metagenome-based methods, which offers a powerful and complementary tool for the practical analysis of the gut microbiome.

Cell-Based Chemical Safety Assessment and Therapeutic Discovery Using Array-Based Sensors

Synthetic chemicals are widely used in food, agriculture, and medicine, making chemical safety assessments necessary for environmental exposure. In addition, the rapid determination of chemical drug efficacy and safety is a key step in therapeutic discoveries. Cell-based screening methods are non-invasive as compared with animal studies. Cellular phenotypic changes can also provide more sensitive indicators of chemical effects than conventional cell viability. Array-based cell sensors can be engineered to maximize sensitivity to changes in cell phenotypes, lowering the threshold for detecting cellular responses under external stimuli. Overall, array-based sensing can provide a robust strategy for both cell-based chemical risk assessments and therapeutics discovery.

Advances in the Sensing and Treatment of Wound Biofilms

Wound biofilms represent a particularly challenging problem in modern medicine. They are increasingly antibiotic resistant and can prevent the healing of chronic wounds. However, current treatment and diagnostic options are hampered by the complexity of the biofilm environment. In this review, we present new chemical avenues in biofilm sensors and new materials to treat wound biofilms, offering promise for better detection, chemical specificity, and biocompatibility. We briefly discuss existing methods for biofilm detection and focus on novel, sensor-based approaches that show promise for early, accurate detection of biofilm formation on wound sites and that can be translated to point-of-care settings. We then discuss technologies inspired by new materials for efficient biofilm eradication. We focus on ultrasound-induced microbubbles and nanomaterials that can both penetrate the biofilm and simultaneously carry active antimicrobials and discuss the benefits of those approaches in comparison to conventional methods.

An array-based nanosensor for detecting cellular responses in macrophages induced by femtomolar levels of pesticides

Environmental agents can induce cellular responses at concentrations far below the limits of detection for current viability and biomarker-based cell sensing platforms. Hypothesis-free cell sensor platforms can be engineered to maximize sensitivity to phenotypic changes, providing a tool for lowering the threshold for detecting cellular changes. Pesticides are one of the most prevalent sources of chemical exposure due to their use in food and agriculture fields. We report here a FRET-based nanosensor array engineered to maximize responses to changes at cell surfaces after pesticide exposure. This sensor array robustly detected macrophage responses to femtomolar concentrations of common pesticides-orders of magnitude lower concentrations than traditional toxicological and biomarker-based strategies. Significantly, this platform was able to classify these responses by pesticide class, demonstrating the ability to distinguish between changes induced by these different agents. Taken together, hypothesis-free cell surface sensing is a promising tool for detecting the effects of ultra-trace environmental chemicals on human health, as well as detecting threshold responses for use in drug discovery and diagnostics.

Chemosensory Optode Array Based on Pluronic-Stabilized Microspheres for Differential Sensing

Differential sensing techniques are becoming nowadays an attractive alternative to classical selective recognition methods due to the “fingerprinting” possibility allowing identifying various analytes without the need to fabricate highly selective binding recognition sites. This work shows for the first time that surfactant-based ion-sensitive microspheres as optodes in the microscale can be designed as cross-sensitive materials; thus, they are perfect candidates as sensing elements for differential sensing. Four types of the newly developed chemosensory microspheres—anion- and cation-selective, sensitive toward amine- and hydroxyl moiety—exhibited a wide range of linear response (two to five orders of magnitude) in absorbance and/or fluorescence mode, great time stability (at least 2 months), as well as good fabrication repeatability. The array of four types of chemosensitive microspheres was capable of perfect pattern-based identification of eight neurotransmitters: dopamine, epinephrine, norepinephrine, γ-aminobutyric acid (GABA), acetylcholine, histamine, taurine, and phenylethylamine. Moreover, it allowed the quantification of neurotransmitters, also in mixtures. Its selectivity toward neurotransmitters was studied using α- and β-amino acids (Ala, Asp, Pro, Tyr, taurine) in simulated blood plasma solution. It was revealed that the chemosensory optode set could recognize subtle differences in the chemical structure based on the differential interaction of microspheres with various moieties present in the molecule. The presented method is simple, versatile, and convenient, and it could be adopted to various quantitative and qualitative analytical tasks due to the simple adjusting of microspheres components and measurement conditions.

Advances in the Sensing and Treatment of Wound Biofilms

Wound biofilms represent a particularly challenging problem in modern medicine. They are increasingly antibiotic resistant and can prevent the healing of chronic wounds. However, current treatment and diagnostic options are hampered by the complexity of the biofilm environment. In this review, we present new chemical avenues in biofilm sensors and new materials to treat wound biofilms, offering promise for better detection, chemical specificity, and biocompatibility. We briefly discuss existing methods for biofilm detection and focus on novel, sensor‐based approaches that show promise for early, accurate detection of biofilm formation on wound sites and that can be translated to point‐of‐care settings. We then discuss technologies inspired by new materials for efficient biofilm eradication. We focus on ultrasound‐induced microbubbles and nanomaterials that can both penetrate the biofilm and simultaneously carry active antimicrobials and discuss the benefits of those approaches in comparison to conventional methods.

Structural Features of a Family of Coumarin-Enamine Fluorescent Chemodosimeters for Ion Pairs

A family of coumarin-enamine chemodosimeters is evaluated for their potential use as fluorescent molecular probes for multiple analytes [cadmium(II), cobalt(II), copper(II), iron(II), nickel(II), lead(II), and zinc(II)], as their chloride and acetate salts. These fluorophores displayed excellent optical spectroscopic modulation when exposed to ion pairs with different Lewis acidic and basic properties in dimethyl sulfoxide (DMSO). The chemodosimeters were designed to undergo excited-state intramolecular proton transfer (ESIPT), which leads to significant Stokes shifts (ca. 225 nm) and lower-energy fluorescence emission (ca. 575 nm). A more basic anion, e.g., acetate, inhibited the ESIPT mechanism by deprotonation of the enol, producing a binding pocket (N^O^- chelate) that can coordinate to an appropriate metal ion. Coordination of the metal ions enhances the fluorescent intensity via the chelation-enhanced fluorescence emission mechanism. Subjecting the spectroscopic data to linear discriminant analysis provided insights into the source of these systems' markedly different behavior toward ion pairs, despite the subtle structural differences in the organic framework. These compounds are examples of versatile, low-molecular-weight, dual-channel fluorescent sensors for ion-pair recognition. This study paves the way for using these probes as practical components of a sensing array for different metal ions and their respective anions.

An ionic liquid-assisted quantum dot-grafted covalent organic framework-based multi-dimensional sensing array for discrimination of insecticides using principal component analysis and clustered heat map

A robust multi-dimensional sensing array based on VBimBF₄B/MAA-anchored quantum dot (QD)-grafted covalent organic frameworks (COFs) [(V-M)/QD-grafted COFs] was established via one-pot strategy. The multi-dimensional sensing array has the outstanding advantages of physicochemical and thermal stability, large specific surface area, and regular pore structures. The assistance of ionic liquid VBimBF₄B enhanced the transduction efficiency, and the synergistic effect of COFs enhanced detection efficiency. The improved multi-dimensional sensing array by COFs and ionic liquid VBimBF₄B served to identify seven insecticides by non-specific interactions via hydrogen bonding, and the differences in the kinetics of the binding to the insecticides resulted in variation of the three-output channel (fluorescence, phosphorescence, and light scattering) signals, thus generating a distinct optical fingerprint. The unique fingerprint patterns of seven kinds of common insecticides at 200 μg L^-1 were successfully discriminated using principal component analysis and clustered heat map analysis. The multi-dimensional sensing array showed a response to seven insecticides based on three spectral channels over the range of 0.001-0.4 μg mL^-1 with a limit of detection of 1.08-18.68 μg L^-1. The spiked recovery of tap water was 79.86-134.22%, with RSD ranging from 0.89-14.9%. This study broadens the applications of sensing arrays technology and provides a promising building block for insecticide determination.

Integral Multielement Signals by DNA-Programmed UCNP-AuNP Nanosatellite Assemblies for Ultrasensitive ICP-MS Detection of Exosomal Proteins and Cancer Identification

Exosomes are expected to be used as cancer biomarkers because they carry a variety of cancer-related proteins inherited from parental cells. However, it is still challenging to develop a sensitive, robust, and high-throughput technique for simultaneous detection of exosomal proteins. Herein, three aptamers specific to cancer-associated proteins (CD63, EpCAM, and HER2) are selected to connect gold nanoparticles (AuNPs) as core with three different elements (Y, Eu, and Tb) doped up-conversion nanoparticles (UCNPs) as satellites, thereby forming three nanosatellite assemblies. The presence of exosomes causes specific aptamers to recognize surface proteins and release the corresponding UCNPs, which can be simultaneously detected by inductively coupled plasma-mass spectrometry (ICP-MS). It is worth noting that rare earth elements are scarcely present in living systems, which minimize the background for ICP-MS detection and exclude potential interferences from the coexisting species. Using this method, we are able to simultaneously detect three exosomal proteins within 40 min, and the limit of detection for exosome is 4.7 × 10³ particles/mL. The exosomes from seven different cell lines (L-02, HepG2, GES-1, MGC803, AGS, HeLa, and MCF-7) can be distinguished with 100% accuracy by linear discriminant analysis. In addition, this analytical strategy is successfully used to detect exosomes in clinical samples to distinguish stomach cancer patients from healthy individuals. These results suggest that this sensitive and high-throughput analytical strategy based on ICP-MS has the potential to play an important role in the detection of multiple exosomal proteins and the identification of early cancer.

Visual sensing of multiple proteins based on three kinds of metal nanoparticles as sensor receptors

We propose a colorimetric sensing array consisting of 4-aminothiophenol (p-ATP)-modified gold nanoparticles (Au NPs), silver nanoparticles (Ag NPs), and core-shell Au@Ag nanocubes (Au@Ag NCs) as sensing elements to identify multiple proteins according to the diverse colorimetric response patterns. In the absence of proteins, the sensor element solution itself did not agglomerate. After interacting with six proteins (lysozyme (LZM), hemoglobin (HGB), peroxidase from horseradish (HRP), bovine liver from peroxidase (CAT), trypsin from bovin pancreas (TRY), and pepsin (PEP)), due to the different binding ability between the sensing elements and various proteins, the sensing array exhibits a unique pattern of colorimetric variations, linear discrimination analysis (LDA) was applied to analyze the pattern and produced a clustering map for a clearer differentiation of these proteins.

Pattern-Based Recognition Systems: Overcoming the Problem of Mixtures

The transformative potential of pattern-based sensing techniques is often hampered by their difficulty in dealing with mixtures of analytes, a drawback that severely limits the applications of this sensing approach (the "problem of mixtures"). We show here that this is not an intrinsic limitation of the pattern sensing method. Indeed, we developed general guidelines for the design of the sensing, signal detection, and data interpretation methods to avoid this constraint, which resulted in chemical fingerprinting systems capable of recognizing unknown mixtures of analytes in a single experiment, without separation or pre-treatment before data acquisition. In support of these design principles, we report their successful application to an important analytical problem, metal ion discrimination and quantitation, by constructing a sensor array that provided a linear colorimetric response over a wide range of analyte concentrations. The resulting data set was interpreted using common multivariate data processing algorithms to achieve quantitative identification and concentration determination for pure and mixture samples, with excellent predictive ability on unknowns. Separation and detection methods for analyte mixtures, normally envisioned as independent processes, were successfully integrated in a single system.

Remote near infrared identification of pathogens with multiplexed nanosensors

Infectious diseases are worldwide a major cause of morbidity and mortality. Fast and specific detection of pathogens such as bacteria is needed to combat these diseases. Optimal methods would be non-invasive and without extensive sample-taking/processing. Here, we developed a set of near infrared (NIR) fluorescent nanosensors and used them for remote fingerprinting of clinically important bacteria. The nanosensors are based on single-walled carbon nanotubes (SWCNTs) that fluoresce in the NIR optical tissue transparency window, which offers ultra-low background and high tissue penetration. They are chemically tailored to detect released metabolites as well as specific virulence factors (lipopolysaccharides, siderophores, DNases, proteases) and integrated into functional hydrogel arrays with 9 different sensors. These hydrogels are exposed to clinical isolates of 6 important bacteria (Staphylococcus aureus, Escherichia coli,…) and remote (≥25 cm) NIR imaging allows to identify and distinguish bacteria. Sensors are also spectrally encoded (900 nm, 1000 nm, 1250 nm) to differentiate the two major pathogens P. aeruginosa as well as S. aureus and penetrate tissue (>5 mm). This type of multiplexing with NIR fluorescent nanosensors enables remote detection and differentiation of important pathogens and the potential for smart surfaces.

Fast and specific detection of pathogenic bacteria is needed to combat infections. Here the authors generate an array of near-infrared biosensors based on carbon nanotubes to detect released metabolites and virulence factors and use them to distinguish pathogens such as S. aureus and P. aeruginosa.

A Multichannel Pattern-Recognition-Based Protein Sensor with a Fluorophore-Conjugated Single-Stranded DNA Set

Recently, pattern-recognition-based protein sensing has received considerable attention because it offers unique opportunities that complement more conventional antibody-based detection methods. Here, we report a multichannel pattern-recognition-based sensor using a set of fluorophore-conjugated single-stranded DNAs (ssDNAs), which can detect various proteins. Three different fluorophore-conjugated ssDNAs were placed into a single microplate well together with a target protein, and the generated optical response pattern that corresponds to each environment-sensitive fluorophore was read via multiple detection channels. Multivariate analysis of the resulting optical response patterns allowed an accurate detection of eight different proteases, indicating that fluorescence signal acquisition from a single compartment containing a mixture of ssDNAs is an effective strategy for the characterization of the target proteins. Additionally, the sensor could identify proteins, which are potential targets for disease diagnosis, in a protease and inhibitor mixture of different composition ratios. As our sensor benefits from simple construction and measurement procedures, and uses accessible materials, it offers a rapid and simple platform for the detection of proteins.

Pattern-recognition-based Sensor Arrays for Cell Characterization: From Materials and Data Analyses to Biomedical Applications

To capture a broader scope of complex biological phenomena, alternatives to conventional sensing based on specificity for cell detection and characterization are needed. Pattern-recognition-based sensing is an analytical method designed to mimic mammalian sensory systems for analyte identification based on the pattern recognition of multivariate data, which are generated using an array of multiple probes that cross-reactively interact with analytes. This sensing approach is significantly different from conventional specific cell sensing based on highly specific probes, including antibodies against biomarkers. Encouraged by the advantages of this technique, such as the simplicity, rapidity, and tunability of the systems without requiring a priori knowledge of biomarkers, numerous sensor arrays have been developed over the past decade and used in a variety of cell sensing applications; these include disease diagnosis, drug discovery, and fundamental research. This review summarizes recent progress in pattern-recognition-based cell sensing, with a particular focus on guidelines for designing materials and arrays, techniques for analyzing response patterns, and applications of sensor systems that are focused primarily for the biomedical field.

High-content and high-throughput identification of macrophage polarization phenotypes

Macrophages are plastic cells of the innate immune system that perform a wide range of immune- and homeostasis-related functions. Due to their plasticity, macrophages can polarize into a spectrum of activated phenotypes. Rapid identification of macrophage polarization states provides valuable information for drug discovery, toxicological screening, and immunotherapy evaluation. The complexity associated with macrophage activation limits the ability of current biomarker-based methods to rapidly identify unique activation states. In this study, we demonstrate the ability of a 2-element sensor array that provides an information-rich 5-channel output to successfully determine macrophage polarization phenotypes in a matter of minutes. The simple and robust sensor generates a high dimensional data array which enables accurate macrophage evaluations in standard cell lines and primary cells after cytokine treatment, as well as following exposure to a model disease environment.

Sensor Array Based Determination of Edman Degradated Amino Acids Using Poly(p-phenyleneethynylene)s

A cross‐reactive optical sensor array based on poly(p‐phenyleneethynylene)s (PPEs) determines Edman degraded amino acids. We report a sensor array composed of three anionic PPEs P1–P3, and their electrostatic complexes with metal ions (Fe²⁺, Cu²⁺, Co²⁺). We recorded distinct fluorescence intensity response patterns as “fingerprints” of this chemical tongue toward standard phenylthiohydantoin (PTH) amino acids—degradation products of the Edman process. These “fingerprints” were converted into canonical scores by linear discrimination analysis (LDA), which differentiates all of the PTH‐amino acids. This array discriminates PTH‐amino acid residues degraded from an oligopeptide through Edman sequencing. This approach is complementary to chromatography approaches which rely on mass spectrometry; our array offers the advantage of simplicity.

Discrimination of antibiotic-resistant Gram-negative bacteria with a novel 3D nano sensing array

Triple optical response of a nano-composite facilitates discrimination of antibiotic-resistant Gram-negative bacteria from normal ones based on a sensing array technique.

Aggregation-induced emission based one-step “lighting up” sensor array for rapid protein identification

Based on the distinct fingerprint-like fluorescence responses generated by different electrostatic and hydrophobic interactions, a “lighting up” aggregation-induced emission (AIE) sensor array was developed for rapid protein discrimination.

Multichannel DNA Sensor Array Fingerprints Cell States and Identifies Pharmacological Effectors of Catabolic Processes

Cells at disease onset are often associated with subtle changes in the expression level of a single or few molecular components, making traditionally used biomarker-driven clinical diagnosis a challenging task. We demonstrate here the design of a DNA nanosensor array with multichannel output that identifies the normal or pathological state of a cell based on the alteration of its global proteomic signature. Fluorophore-encoded single-stranded DNA (ssDNA) strands were coupled via supramolecular interaction with a surface-functionalized gold nanoparticle quencher to generate this integrated sensor array. In this design, ssDNA sequences exhibit dual roles, where they provide differential affinities with the receptor gold nanoparticle as well as act as transducer elements. The unique interaction mode of the analyte molecules disrupts the noncovalent supramolecular complexation, generating simultaneous multichannel fluorescence output to enable signature-based analyte identification via a linear discriminant analysis-based machine learning algorithm. Different cell types, particularly normal and cancerous cells, were effectively distinguished using their fluorescent fingerprints. Additionally, this DNA sensor array displayed excellent sensitivity to identify cellular alterations associated with chemical modulation of catabolic processes. Importantly, pharmacological effectors, which could modulate autophagic flux, have been effectively distinguished by generating responses from their global protein signatures. Taken together, these studies demonstrate that our multichannel DNA nanosensor is well suited for rapid identification of subtle changes in a complex mixture and thus can be readily expanded for point-of-care clinical diagnosis, high-throughput drug screening, or predicting the therapeutic outcome from a limited sample volume.