A chemically programmable, PPI-inspired biosensing paradigm that uses a reductionist approach and could potentially be extended to other pathogen targets is introduced and could potentially be extended to other pathogen targets.
Abstract
Rapid, selective detection of bacterial pathogens remains a central challenge. Here we report a label-free electrochemical biosensing approach that leverages protein-protein interaction (PPI)-derived peptides as recognition elements for rapid detection of Listeria monocytogenes (LM). The sensor design is inspired by the interaction between the LM virulence factor Internalin A (InlA) and the human host receptor E-cadherin (E-Cad1). Peptides derived from the InlA-binding domain of E-Cad1 were engineered as molecular recognition elements, with the E-Cad1(15-24) peptide displaying micromolar affinity and selective binding towards LM. Immobilization of these peptides on gold electrodes enabled bacterial detection by electrochemical impedance spectroscopy within 10 minutes, without labels or external signal amplification. A low peptide surface density was associated with enhanced binding-site accessibility and may facilitate multivalent interactions between the bacterial surface and the immobilized peptides. The platform produced a detectable response at experimentally tested concentrations as low as 1 CFU mL ¹ and exhibited excellent selectivity under the conditions examined. This work introduces a chemically programmable, PPI-inspired biosensing paradigm that uses a reductionist approach and could potentially be extended to other pathogen targets.
The rapid and specific detection of foodborne bacteria in complex matrices remains a critical analytical challenge. Conventional nucleic acid amplification and immunological methods offer high analytical sensitivity, but they often provide limited information on bacterial viability because nucleic acids and antigenic epitopes may persist after cell death. As obligate parasites, bacteriophages (phages) initiate infection through the adsorption stage, relying on highly specific recognition between tail proteins and host receptors. This early interaction provides a rapid recognition window before signals from downstream replication or lysis become dominant. Herein, this review presents a systematic overview of biosensors based on the bacteriophage adsorption stage for the detection of foodborne bacteria developed over the past five years. It explores how whole phages and their derived proteins can serve as biorecognition elements in combination with different transducers for bacterial capture and signal transduction, with emphasis on interface-oriented immobilization, signal attribution, matrix effects, and adaptation to point-of-care testing (POCT), especially lateral flow assays (LFAs) for instrument-free analysis. Meanwhile, it highlights that whole phages retain the native adsorption architecture and may support interpretation of viability when appropriate validation models are used, whereas phage-derived proteins provide more flexible recognition modules for interface design and signal generation but require attention to effective avidity, conformational context, and consistency between batches. Furthermore, future phage-based analytical platforms are discussed in relation to time-resolved kinetic validation, computationally assisted readout, and adsorption-coupled detection and containment.
Xingying Mou, Xinge Cui, Yongkang Zhang et al.· In Analysis· 0 citations
Rapid and reliable detection of bacterial pathogens is essential for clinical diagnostics and food safety monitoring. This study explores bacterial outer membrane vesicles (OMVs), nanoscale particles naturally released by Gram-negative bacteria such as Escherichia coli, as diagnostic surrogates for intact cells. An E. coli-specific aptamer was conjugated to indium phosphide–zinc sulphide quantum dots to evaluate its ability to recognise vesicles derived from the bacterial outer membrane. Optical measurements together with high-resolution transmission electron microscopy confirmed aptamer-mediated binding of the quantum dot-aptamer conjugates to these vesicles. To investigate biosensing performance, the same aptamer was immobilised on gold electrodes and vesicle recognition was monitored using electrochemical impedance measurements. The resulting sensor showed a concentration-dependent increase in interfacial charge-transfer resistance across a vesicle concentration range of 107−109 vesicles/ml and demonstrated strong selectivity towards E. coli-derived vesicles compared with those from Pseudomonas aeruginosa. These findings demonstrate that aptamer-functionalised nanomaterials can selectively target bacterial OMVs and highlight their potential as stable biomarkers for vesicle-based bacterial detection platforms.
Shiana Malhotra, Renee V. Goreham· Nano Express· 0 citations
Bacterial contamination remains a major threat to public health, food safety, and environmental monitoring. In this work, we report a nanobrush-structured microbial (NSM) biosensor capable of rapid, highly sensitive, and Gram-specific bacterial detection. The nanobrush geometry was optimized through controlled KOH etching and then coated with indium tin oxide layer. After that, NSM biosensor surface was functionalized with boronic acid (BA) to promote bacterial adhesion via cis-diol–mediated boronate ester bond formation. Extended Derjaguin–Landau–Verwey–Overbeek (XDLVO) analysis confirmed enhanced bacteria–surface interactions on BA-modified NSM electrodes, revealing reduced energy barriers and stronger adhesion forces. The BA-modified NSM biosensors exhibited a broad dynamic detection range (10
1
–10
7
CFU mL
-1
), a rapid response time of 9 min, and high specificity for
Escherichia coli
over
Staphylococcus aureus
, attributed to the abundant
cis
-diols on Gram-negative bacterial surfaces. Through precise tuning of nanobrush density and strategic BA surface engineering, interfacial interactions between bacterial membranes and nanostructured electrodes were significantly improved, leading to enhanced adhesion and sensing performance. This platform enables accurate detection of trace bacterial levels even in complex sample environments. Overall, this study demonstrates that nanoscale surface engineering, coupled with XDLVO-guided interfacial interaction modeling, provides a powerful framework for optimizing biosensor performance. The resulting NSM biosensor offers a versatile and label-free solution for real-time discrimination of Gram-negative foodborne pathogens.
1
Keywords:
nanobrush-structured microbial biosensor, XDLVO theory, interfacial interactions, bacterial detection, foodborne pathogens.
REFERENCES
(1) Kumar, N.; Vinzons, L. U.; Shia, W.-Y.; Chu, P.-H.; Liao, Y.-T.; Liu, C.-W.; Lin, S.-P. Advanced nanostructured biosensors enabled by rational surface engineering for bacterial detection.
Biosensors and Bioelectronics
2026
,
292
, 118112.
Figure 1
Rapid on-site detection of bacterial contamination remains an urgent need in public health and environmental monitoring. Herein, we report a one-step, label-free colorimetric sensor for broad-spectrum bacterial detection based on a competitive electrostatic mechanism. Cationic poly-l-lysine (PLL) induces the aggregation of anionic, citrate-capped gold nanoparticles (AuNPs), resulting in a distinct red-to-blue color change. In the presence of bacteria, their negatively charged surfaces adsorb PLL, thereby inhibiting AuNP aggregation and maintaining the red color of the dispersion. This strategy enables the visual detection of various Gram-positive and Gram-negative bacteria within 10 min. Using Escherichia coli (E. coli) as a model analyte, the assay reached a detection limit of 720 CFU/mL under the optimized conditions (5 μg/mL PLL, 3 min incubation, 20 mM phosphate buffer at pH 7.5) and exhibited a wide detection range from 102 to 107 CFU/mL (R2 > 0.99). The assay also performed reliably in spiked tap water and drinking water samples, with recoveries of 82-96% and CVs below 10%, demonstrating its potential as a rapid, low-cost screening tool for bacterial contamination in low-matrix water samples.
Viral proteases are key targets for the development of broad-spectrum antiviral drugs development. However, screening platform capable of accurately assessing inhibitor activity within physiologically relevant cellular environments remain urgently needed. Traditional methods, such as fluorescent protein assays and Förster resonance energy transfer (FRET), suffer from significant limitations, including susceptibility to non-specific conformational interference by test compounds and an inability to faithfully reflect intracellular inhibitory effects. To address these challenges, we constructed two modular biosensors (TS3AR and C3SIR) based on engineered ascorbate peroxidase (APEX). Their detection mechanism relies on specific cleavage of the substrate recognition sequence by the target protease, which triggers the reassembly of split APEX fragments, restores enzymatic activity, and generates fluorescent signals generated via cascade amplification reaction. Validation using the coronavirus main protease (Mpro) as a model showed that the TS3AR sensor achieved the signal-to-noise ratio up to 1500-fold for enzyme activity detection, while the C3SIR sensor effectively avoided the false positives caused by conformational interference seen in traditional methods and accurately identified high-potency Mpro inhibitors, including Enstrelvir, PF-00835231, and Nirmatrelvir. Moreover, by replacing the protease recognition sequence, these modular biosensors can be flexibly adapted for activity analysis and drug evaluation of Mpro from various coronaviruses (e.g., SARS-CoV-2, MERS-CoV) as well as other viral proteases (e.g., Enterovirus 71, Epstein-Barr virus and Hepatitis A virus). Overall, this platform provides a reliable, highly specific intracellular screening tool to accelerate the development of broad-spectrum therapeutics against both emerging and existing viral threats.
Biao Li, Bao Dong, Yuehong Chen et al.· Virologica Sinica· 0 citations
Ensuring rapid, reliable, and quantitative detection of foodborne pathogenic bacteria continues to be a challenge in food safety, particularly in complex matrices where traditional culture methods are time-consuming. In this study, a surface-enhanced Raman spectroscopy (SERS) sensing platform incorporating a polymer affinity agent is developed for the sensitive and quantitative detection of bacterial foodborne pathogens. A linear poly (2-hydroxyethyl methacrylate) affinity agent (pHEMA) was employed in combination with film over nanospheres (FON) substrates to facilitate detection and discrimination of Salmonella typhimurium (Gram-negative) and Listeria monocytogenes (Gram-positive). pHEMA plays an important role in mediating interactions with both extracellular metabolites and bacterial cell wall components. Characteristic vibrational bands enabled quantitative detection with a log-linear response and an observed limit of detection of 158 CFU/mL for both Salmonella typhimurium and Listeria monocytogenes in diluted apple juice. The similar sensitivities observed for both bacteria suggest effective interactions between pHEMA and chemically distinct bacterial cell walls of Gram-negative and Gram-positive organisms. This sensing approach maintained consistent performance in complex food matrices, such as pure apple juice, across a range of temperatures. Sonication experiments provided additional practical advantages: enhanced species discrimination and a strategy for combined disinfection and detection, extending the utility of this platform for food safety applications. Overall, these results show that SERS sensing platforms incorporating polymer affinity agents offer a robust and versatile analytical approach for whole cell foodborne pathogen detection.
Mahmoud Matar Abed, Katie L. Riley, Punarbasu Roy et al.· ACS Sensors· 0 citations