The monitoring of foodborne bacterial contamination requires simple and convenient biosensors. This work describes a novel paper-based colorimetric biosensor for the rapid and sensitive bacteria detection. The biosensor was constructed via the encapsulation of D-alanyl-D-alanine capped gold nanoparticles (DADA-AuNPs) in a modified paper that was fabricated by the freeze-drying of TEMPO-oxidized cellulose nanofibers/cationic guar gum composite hydrogel-modified filter paper. The results indicated that the size of DADA-AuNPs largely determined the color of their aqueous system and they exhibited light red to dark red as their size increased from around 6 to 36 nm. All these different sized DADA-AuNPs turned into colorless when encountered with either S. aureus or E. coli. In particular, the smaller the DADA-AuNPs size, the faster the discoloration. The encapsulation of DADA-AuNPs into modified paper negligibly changed their responsiveness towards bacteria. In comparison to the original filter paper and oven-dried hydrogel-modified filter paper, the freeze-dried hydrogel-modified paper was demonstrated to be a better substrate for the encapsulation of DADA-AuNPs since they could be loaded with a larger amount of DADA-AuNPs in a faster way and showed a better perceivable color. This work demonstrated a promising paper-based colorimetric biosensor for the facile and rapid detection of bacteria.

Persistent and inappropriate use of antibiotics is causing rife antimicrobial resistance (AMR) worldwide. Common bacterial infections are thus becoming increasingly difficult to treat without the use of last resort antibiotics. This has necessitated a situation where it is imperative to confirm the infection to be bacterial, before treating it with antimicrobial speculatively. Conventional methods of bacteria detection are either culture based which take anywhere between 24 and 96 hor require sophisticated molecular analysis equipment with libraries and trained operators. These are difficult propositions for resource limited community healthcare setups of developing or less developed countries. Customized, inexpensive, point-of-care (PoC) biosensors are thus being researched and developed for rapid detection of bacterial pathogens. The development and optimization of disposable sensor substrates is the first and crucial step in development of such PoC systems. The substrates should facilitate easy charge transfer, a high surface to volume ratio, be tailorable by the various bio-conjugation chemistries, preserve the integrity of the biorecognition element, yet be inexpensive. Such sensor substrates thus need to be thoroughly investigated. Further, if such systems were made disposable, they would attain immunity to biofouling. This article discusses a few potential disposable electrochemical sensor substrates deployed for detection of bacteria for environmental and healthcare applications. The technologies have significant potential in helping reduce bacterial infections and checking AMR. This could help save lives of people succumbing to bacterial infections, as well as improve the overall quality of lives of people in low- and middle-income countries.

Accurate and effective detection is essential to against bacterial infection and contamination. Novel biosensors, which detect bacterial bioproducts and convert them into measurable signals, are attracting attention. We developed an artificial intelligence (AI)-assisted smartphone-based colorimetric biosensor for the visualized, rapid, sensitive detection of pathogenic bacteria by measuring the bacteria secreted hyaluronidase (HAase). The biosensor consists of the chlorophenol red-β-D-galactopyranoside (CPRG)-loaded hyaluronic acid (HA) hydrogel as the bioreactor and the β-galactosidase (β-gal)-loaded agar hydrogel as the signal generator. The HAase degrades the bioreactor and subsequently determines the release of CPRG, which could further react with β-gal to generate signal colors. The self-developed YOLOv5 algorithm was utilized to analyze the signal colors acquired by smartphone. The biosensor can provide a report within 60 min with an ultra-low limit of detection (LoD) of 10 CFU/mL and differentiate between gram-positive (G+) and gram-negative (G-) bacteria. The proposed biosensor was successfully applied in various areas, especially the evaluation of infections in clinical samples with 100% sensitivity. We believe the designed biosensor has the potential to represent a new paradigm of \"ASSURED\" bacterial detection, applicable for broad biomedical uses.

Cell wall peptidoglycan binding domains (CBDs) of cell lytic enzymes, including bacteriocins, autolysins and bacteriophage endolysins, enable highly selective bacterial binding, and thus, have potential as biorecognition molecules for nondestructive bacterial detection. Here, a novel design for a self-complementing split fluorescent protein (FP) complex is proposed, where a multimeric FP chain fused with specific CBDs ((FP-CBD)n) is assembled inside the cell, to improve sensitivity by enhancing the signal generated upon Staphylococcus aureus or Bacillus anthracis binding. Flow cytometry shows enhanced fluorescence on the cell surface with increasing FP stoichiometry and surface plasmon resonance reveals nanomolar binding affinity to isolated peptidoglycan. The breadth of function of these complexes is demonstrated through the use of CBD modularity and the ability to attach enzymatic detection modalities. Horseradish peroxidase-coupled (FP-CBD)n complexes generate a catalytic amplification, with the degree of amplification increasing as a function of FP length, reaching a limit of detection (LOD) of 103 cells/droplet (approximately 0.1 ng S. aureus or B. anthracis) within 15 min on a polystyrene surface. These fusion proteins can be multiplexed for simultaneous detection. Multimeric split FP-CBD fusions enable use as a biorecognition molecule with enhanced signal for use in bacterial biosensing platforms.

Label-free measurement and analysis of single bacterial cells are essential for food safety monitoring and microbial disease diagnosis. We report a microwave flow cytometric sensor with a microstrip sensing device with reduced channel height for bacterial cell measurement. Escherichia coli B and Escherichia coli K-12 were measured with the sensor at frequencies between 500 MHz and 8 GHz. The results show microwave properties of E. coli cells are frequency-dependent. A LightGBM model was developed to classify cell types at a high accuracy of 0.96 at 1 GHz. Thus, the sensor provides a promising label-free method to rapidly detect and differentiate bacterial cells. Nevertheless, the method needs to be further developed by comprehensively measuring different types of cells and demonstrating accurate cell classification with improved machine-learning techniques.

Surface-enhanced Raman spectroscopic (SERS) approaches are emerging for bacteria analysis whereby bacteria cells can be measured based on their biochemical composition (label-free) or with the aid of a chemical label to enhance the SERS signal. Combining a microscope, SERS microscopy is capable of imaging bacteria populations en masse based on specific spectrophotometric peaks. Here, we compared the label-free and label-based approaches to study Escherichia coli O157:H7 that was utilized as a model bacterium for SERS imaging analyses. Gold (Au) nanoparticles were utilized to enhance Raman scattering during this study and 3-mercaptophenylboronic acid was utilized as a model chemical label for comparison against label-free conditions. The result shows that SERS images of bacteria cells yielded measurable differences in precision, depending on the application of chemical labels. Chemical labels enabled SERS imaging of whole bacteria populations with single-cell precision. Bacteria coated with labels were also easier to bring into focus using high-magnification optical microscopy, without the need for immersion oil. Label-free analyses of single-cells were lower in geographic precision but provided opportunities to study the natural biochemistry of bacteria cells with strong accuracy. SERS analyses of label-free bacteria cell components were conclusively improved in vitro on a time-dependent basis. This concept can serve as an important benchmark when biochemically profiling or characterizing bacteria cells based on SERS. Electron micrographs proved that chemical labels can be utilized to increase nanoparticle contact with bacteria cells and reduce free nanoparticles that contribute to background noise in SERS spectra. We also demonstrate the use of both 3-mercaptophenylboronic acid and propidium iodide to discriminate live and dead bacteria through the simultaneous collection of data from these two chemical labels. Label-free approaches to SERS bacteria analyses are better suited for biochemical characterization and label-based approaches are better suited when accounting for individual cells among a population.

Efficient tools for rapid antibiotic susceptibility testing (AST) are crucial for appropriate use of antibiotics, especially colistin, which is now often considered a last resort therapy with extremely drug resistant Gram-negative bacteria. Here, we developed a rapid, easy and miniaturized colistin susceptibility assay based on microfluidics, which allows for culture and high-throughput analysis of bacterial samples. Specifically, a simple microfluidic platform that can easily be operated was designed to encapsulate bacteria in nanoliter droplets and perform a fast and automated bacterial growth detection in 2 h, using standardized samples. Direct bright-field imaging of compartmentalized samples proved to be a faster and more accurate detection method as compared to fluorescence-based analysis. A deep learning powered approach was implemented for the sensitive detection of the growth of several strains in droplets. The DropDeepL AST method (Droplet and Deep learning-based method for AST) developed here allowed the determination of the colistin susceptibility profiles of 21 fast-growing Enterobacterales (E. coli and K. pneumoniae), including clinical isolates with different resistance mechanisms, showing 100 % categorical agreement with the reference broth microdilution (BMD) method performed simultaneously. Direct AST of bacteria in urine samples on chip also provided accurate results in 2 h, without the need of complex sample preparation procedures. This method can easily be implemented in clinical microbiology laboratories, and has the potential to be adapted to a variety of antibiotics, especially for last-line antibiotics to optimize treatment of patients infected with multi-drug resistant strains.

Bacterial infections, increasingly resistant to common antibiotics, pose a global health challenge. Traditional diagnostics often depend on slow cell culturing, leading to empirical treatments that accelerate antibiotic resistance. We present a novel large-volume microscopy (LVM) system for rapid, point-of-care bacterial detection. This system, using low magnification (1-2×), visualizes sufficient sample volumes, eliminating the need for culture-based enrichment. Employing deep neural networks, our model demonstrates superior accuracy in detecting uropathogenic Escherichia coli compared to traditional machine learning methods. Future endeavors will focus on enriching our datasets with mixed samples and a broader spectrum of uropathogens, aiming to extend the applicability of our model to clinical samples.

In this report, gold nanoparticles (GNPS) were synthesized using cell-free extracts of seven different isolates, namely, Pseudomonas aerogenosa CEBP2, Pseudomonas sp. CEBP1, Pseudomonas pseudoalcaligenes CEB1G, Acinetobactor baumani CEBS1, Cuprividus sp. CEB3, Micrococcus luteus CUB12, and Pandoraea sp. CUB2S. The spectroscopic (UV-vis, FTIR, DLS, XRD, EDS) and microscopic (FESEM, TEM) results confirm the reduction of Au3+ to Au0 in the presence of biomolecules having reducing as well as self-stabilizing activity. In this green synthesis approach, the average particle size of biosynthesized GNPS might vary (4-60 nm) depending on the bacterial species, pH of the media, incubation time, and temperature. In this study, GSH-modified BSGNPs (Au-GSH) have shown antimicrobial activity with better stability against Gram-positive bacteria. After conjugation of lysozyme with Au-GSH (lyso@Au-GSH), the zone of inhibition was enhanced from 12 to 23 mm (Au-GSH). The TEM study shows the spherical GNP (16.65 ± 2.84) turns into a flower-shaped GNP (22.22 ± 3.12) after conjugation with lysozyme due to the formation of the protein corona. Furthermore, the nanobioconjugate (lyso@Au-GSH) was immobilized with Nafion on a glassy carbon electrode to fabricate a label-free impedance biosensor that is highly sensitive to monitor changes in the transducer surface due to biomolecular interactions. The uniquely designed biosensor could selectively detect Gram-positive bacteria in the linear range of 3.0 × 101-3 × 1010 cfu mL-1 with RE <5%. The proposed simplest biosensor exhibited good reproducibility (RSD = 3.1%) and excellent correlation (R2 = 0.999) with the standard plate count method, making it suitable for monitoring Gram-positive bacterial contamination in biofluids, food, and environmental samples.

In this study, we proposed an innovative application of porcine immunoglobulin G (IgG)-functionalized Fe3O4 (IgG-Fe3O4) specifically designed to target and capture Staphylococcus aureus (S. aureus). In addition, aminophenylboronic acid-modified tetraphenylethylene nanoparticles (APBA-TPE NPs) were utilized, establishing a sandwich-type dual recognition system via interactions with the bacteria\'s extracellular glycolipids. This approach enables highly sensitive and precise detection of bacterial presence, with a limit of detection (LOD) reaching down to 5.0 CFU/mL. Specifically, the prepared APBA-TPE NPs achieved 99.99% bacterial inactivation within 60 min at a concentration of 200 µg/mL. The results showed that APBA-TPE NPs possess a remarkable capacity for reactive oxygen species (ROS) production, which could attack the bacterial cell membrane, leading to bacterial lysis and content leakage, and ultimately to bacterial death. Furthermore, the material still showed good recoveries ranging from 88.5% to 93.5% in actual water samples, as well as a favorable sterilizing effect of killing all microorganisms for 60 min. This research provides new strategies and insights into the construction of methods for the specific capture, detection, and inactivation of S. aureus.