Next-Generation Antimicrobial Resistance Surveillance System Based on the Internet-of-Things and Microfluidic Technique

Frontiers in superbug management: innovating approaches to combat antimicrobial resistance

Anti-microbial resistance (AMR) is a global health issue causing significant mortality and economic burden. Pharmaceutical companies' discontinuation of research hinders new agents, while MDR pathogens or "superbugs" worsen the problem. Superbugs pose a threat to common infections and medical procedures, exacerbated by limited antibiotic development and rapid antibiotic resistance. The rising tide of antimicrobial resistance threatens to undermine progress in controlling infectious diseases. This review examines the global proliferation of AMR, its underlying mechanisms, and contributing factors. The study explores various methodologies, emphasizing the significance of precise and timely identification of resistant strains. We discuss recent advancements in CRISPR/Cas9, nanoparticle technology, light-based techniques, and AI-powered antibiogram analysis for combating AMR. Traditional methods often fail to effectively combat multidrug-resistant bacteria, as CRISPR-Cas9 technology offers a more effective approach by cutting specific DNA sequences, precision targeting and genome editing. AI-based smartphone applications for antibiogram analysis in resource-limited settings face challenges like internet connectivity, device compatibility, data quality, energy consumption, and algorithmic limitations. Additionally, light-based antimicrobial techniques are increasingly being used to effectively kill antibiotic-resistant microbial species and treat localized infections. This review provides an in-depth overview of AMR covering epidemiology, evolution, mechanisms, infection prevention, control measures, antibiotic access, stewardship, surveillance, challenges and emerging non-antibiotic therapeutic approaches.

Microfluidic technologies for advanced antimicrobial susceptibility testing

Antimicrobial resistance is getting serious and becoming a threat to public health worldwide. The improper and excessive use of antibiotics is responsible for this situation. The standard methods used in clinical laboratories, to diagnose bacterial infections, identify pathogens, and determine susceptibility profiles, are time-consuming and labor-intensive, leaving the empirical antimicrobial therapy as the only option for the first treatment. To prevent the situation from getting worse, evidence-based therapy should be given. The choosing of effective drugs requires powerful diagnostic tools to provide comprehensive information on infections. Recent progress in microfluidics is pushing infection diagnosis and antimicrobial susceptibility testing (AST) to be faster and easier. This review summarizes the recent development in microfluidic assays for rapid identification and AST in bacterial infections. Finally, we discuss the perspective of microfluidic-AST to develop the next-generation infection diagnosis technologies.

Microfluidic advances in food safety control

Food contamination is a global concern, particularly in developing countries. Two main types of food contaminants-chemical and biological-are common problems that threaten human health. Therefore, rapid and accurate detection methods are required to address the threat of food contamination. Conventional methods employed to detect these two types of food contaminants have several limitations, including high costs and long analysis time. Alternatively, microfluidic technology, which allows for simple, rapid, and on-site testing, can enable us to control food safety in a timely, cost-effective, simple, and accurate manner. This review summarizes advances in microfluidic approaches to detect contaminants in food. Different detection methods have been applied to microfluidic platforms to identify two main types of contaminants: chemical and biological. For chemical contaminant control, the application of microfluidic approaches for detecting heavy metals, pesticides, antibiotic residues, and other contaminants in food samples is reviewed. Different methods including enzymatic, chemical-based, immunoassay-based, molecular-based, and electrochemical methods for chemical contaminant detection are discussed based on their working principle, the integration in microfluidic platforms, advantages, and limitations. Microfluidic approaches for foodborne pathogen detection, from sample preparation to final detection, are reviewed to identify foodborne pathogens. Common methods for foodborne pathogens screening, namely immunoassay, nucleic acid amplification methods, and other methods are listed and discussed; highlighted examples of recent studies are also reviewed. Challenges and future trends that could be employed in microfluidic design and fabrication process to address the existing limitations for food safety control are also covered. Microfluidic technology is a promising tool for food safety control with high efficiency and applicability. Miniaturization, portability, low cost, and samples and reagents saving make microfluidic devices an ideal choice for on-site detection, especially in low-resource areas. Despite many advantages of microfluidic technology, the wide manufacturing of microfluidic devices still demands intensive studies to be conducted for user-friendly and accurate food safety control. Introduction of recent advances of microfluidic devices will build a comprehensive understanding of the technology and offer comparative analysis for future studies and on-site application.

On-Site Remote Monitoring System with NIR Signal-Based Detection of Infectious Disease Virus in Opaque Salivary Samples

Infectious disease viruses, such as foot-and-mouth disease virus (FMDV), are highly contagious viruses that cause significant socioeconomic damage upon spreading. Developing an on-site diagnostic tool for early clinical detection and real-time surveillance of FMDV outbreaks is essential to prevent the further spread of the disease. However, early diagnosis of FMDV is still challenging due to the limited sensitivity and time-consuming manual result entry of commercial on-site tests for salivary samples. Here, we report a near-infrared (NIR) signal nanoprobe-based highly accurate detection and remote monitoring system toward FMDVs, which automates the analysis and reporting of diagnosis data. The NIR signal lateral flow immunoassay (LFA) was assembled with a nanoprobe with a stable emission intensity at 800 nm, minimizing the interference signal of opaque salivary samples. We investigated the clinical applicability of the NIR signal LFA at biosafety level 3 (BSL-3) laboratories using 147 opaque salivary samples. The NIR signal LFA achieved a 32-fold lower limit of detection (LOD) than a commercial LFA in detecting live FMDVs, including all isolates occurring in the Republic of Korea during 2010-2017. Our results showed that the NIR signal LFA successfully discriminated the FMDV-positive clinical salivary samples from healthy controls with a sensitivity of 96.9%, specificity of 100.0%, and AUC (area under the receiver operator characteristic curve) value of 0.999. Finally, we substantiated the real-time collection of diagnostic results using a customized portable NIR reader at nine different laboratories of government-certified quarantine institutions for foot-and-mouth disease (FMD).