Rapid Identification and Monitoring of Multiple Bacterial Infections Using Printed Nanoarrays

AI-assisted smartphone-based colorimetric biosensor for visualized, rapid and sensitive detection of pathogenic bacteria

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.

Pore-Forming Toxin-Driven Recovery of Peroxidase-Mimicking Activity in Biomass Channels for Label-Free Electrochemical Bacteria Sensing

The development of sensitive, selective, and rapid methods to detect bacteria in complex media is essential to ensuring human health. Virulence factors, particularly pore-forming toxins (PFTs) secreted by pathogenic bacteria, play a crucial role in bacterial diseases and serve as indicators of disease severity. In this study, a nanochannel-based label-free electrochemical sensing platform was developed for the detection of specific pathogenic bacteria based on their secreted PFTs. In this design, wood substrate channels were functionalized with a Fe-based metal-organic framework (FeMOF) and then protected with a layer of phosphatidylcholine (PC)-based phospholipid membrane (PM) that serves as a peroxidase mimetic and a channel gatekeeper, respectively. Using Staphylococcus aureus (S. aureus) as the model bacteria, the PC-specific PFTs secreted by S. aureus perforate the PM layer. Now exposed to the FeMOF, uncharged 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonate) (ABTS) molecules in the electrolyte undergo oxidation to cationic products (ABTS•+). The measured transmembrane ionic current indicates the presence of S. aureus and methicillin-resistant S. aureus (MRSA) with a low detection limit of 3 cfu mL-1. Besides excellent specificity, this sensing approach exhibits satisfactory performance for the detection of target bacteria in the complex media of food.

Seamless Integration of Rapid Separation and Ultrasensitive Detection for Complex Biological Samples Using Multistage Annular Functionalized Carbon Nanotube Arrays

Efficient separation, enrichment, and detection of bacteria in diverse media are pivotal for identifying bacterial diseases and their transmission pathways. However, conventional bacterial detection methods that split the separation and detection steps are plagued by prolonged processing times. Herein, a multistage annular functionalized carbon nanotube array device designed for the seamless integration of complex biological sample separation and multimarker detection is introduced. This device resorts to the supersmooth fluidity of the liquid sample in the carbon nanotubes interstice through rotation assistance, achieving the ability to quickly separate impurities and capture biomarkers (1 mL sample cost time of 2.5 s). Fluid dynamics simulations show that the reduction of near-surface hydrodynamic resistance drives the capture of bacteria and related biomarkers on the functionalized surface of carbon nanotube in sufficient time. When further assembled as an even detection device, it exhibited fast detection (<30 min), robust linear correlation (101-107 colony-forming units [CFU] mL-1, R2 = 0.997), ultrasensitivity (limit of detection = 1.7 CFU mL-1), and multitarget detection (Staphylococcus aureus, extracellular vesicles, and enterotoxin proteins). Collectively, the material and system offer an expanded platform for real-time diagnostics, enabling integrated rapid separation and detection of various disease biomarkers.

Emerging strategies and therapeutic innovations for combating drug resistance in Staphylococcus aureus strains: A comprehensive review

In recent years, antibiotic therapy has encountered significant challenges due to the rapid emergence of multidrug resistance among bacteria responsible for life-threatening illnesses, creating uncertainty about the future management of infectious diseases. The escalation of antimicrobial resistance in the post-COVID era compared to the pre-COVID era has raised global concern. The prevalence of nosocomial-related infections, especially outbreaks of drug-resistant strains of Staphylococcus aureus, have been reported worldwide, with India being a notable hotspot for such occurrences. Various virulence factors and mutations characterize nosocomial infections involving S. aureus. The lack of proper alternative treatments leading to increased drug resistance emphasizes the need to investigate and examine recent research to combat future pandemics. In the current genomics era, the application of advanced technologies such as next-generation sequencing (NGS), machine learning (ML), and quantum computing (QC) for genomic analysis and resistance prediction has significantly increased the pace of diagnosing drug-resistant pathogens and insights into genetic intricacies. Despite prompt diagnosis, the elimination of drug-resistant infections remains unattainable in the absence of effective alternative therapies. Researchers are exploring various alternative therapeutic approaches, including phage therapy, antimicrobial peptides, photodynamic therapy, vaccines, host-directed therapies, and more. The proposed review mainly focuses on the resistance journey of S. aureus over the past decade, detailing its resistance mechanisms, prevalence in the subcontinent, innovations in rapid diagnosis of the drug-resistant strains, including the applicants of NGS and ML application along with QC, it helps to design alternative novel therapeutics approaches against S. aureus infection.

Magnetic Nanoagent Coated with an Activated Macrophage Membrane for Colorimetric Detection of Bacteria

The construction of cell mimics replicating the surface landscape and biological functions of the cell membrane offers promising prospects for biomedical research and applications. Inspired by the inherent recognition capability of immune cells toward pathogens, we have fabricated activated macrophage membrane-coated magnetic silicon nanoparticles (aM-MSNPs) in this work as an isolation and recognition tool for enhanced bacterial analysis. Specifically, the natural protein receptors on the activated macrophage membrane endow the MSNPs with a broad-spectrum binding capacity to different pathogen species. By further incorporation of a tyramide amplification strategy, direct naked-eye analysis of specific bacteria with a detection limit of 10 CFU/mL can be achieved. Moreover, application to the diagnosis of urinary tract infections has also been validated, and positive samples spiked with bacteria can be clearly distinguished with an accuracy of 100%. This work may enrich cell membrane-based architectures and provide an experimental paradigm for point-of-care testing (POCT) detection of bacteria.

A novel multifunctional SERS microfluidic sensor based on ZnO/Ag nanoflower arrays for label-free ultrasensitive detection of bacteria

This study proposes a microfluidic platform for rapid enrichment and ultrasensitive SERS detection of bacteria. The platform comprises ZnO nanoflower arrays decorated with silver nanoparticles to enhance the SERS sensitivity. The ZnO nanoflower array substrate with a 3D reticular columnar structure is prepared using the hydrothermal method. SEM analysis depicts the 3.05 μm gap distribution of the substrate array to intercept the most bacteria in the particle sizes range of 0.5 to 3 μm. Then, silver nanoparticles are deposited on the ZnO nano-array surface by liquid evaporation self-assembly. TEM and SEM analysis indicate nanosize of Ag particles, evenly distributed on the substrate, enhancing the SERS efficiency and improving sensing reproducibility. The probe molecules (R6G) are tested to demonstrate the high SERS activity of the proposed microfluidic sensor. Then, Escherichia coli, Staphylococcus aureus, Enterococcus faecalis, and Bacillus subtilis are selected, demonstrating the sensor's excellent bacterial capture and sensitive recognition capabilities, with a detection limit as low as 102 CFU mL-1. Additionally, the antibacterial properties of ZnO/Ag heterojunction nanostructures are studied, suggesting their ability to inactivate bacteria. Compared with the traditional Au-enhanced chip, the sensor preparation is easy, safe, reliable, and low-cost. Moreover, the ZnO nano-array exhibits a large specific surface area, high interception ability, stronger and uniform SERS performance, and effective and reliable detection of trace pathogens. This work provides potential future ZnO/Ag microfluidic SERS sensor applications for rapid, unlabeled, and trace pathogens detection in clinical and environmental applications, potentially achieving breakthroughs in early detection, prevention, and treatment.