Detection of microorganisms with lateral flow test strips

Longitudinal Analysis of Urban Stormwater Microbiome and Resistome from Watersheds with and without Green Infrastructure using Long-Read Sequencing

Since stormwater conveys a variety of contaminants into water bodies, green infrastructure (GI) is increasingly being adopted as an on-site treatment solution in addition to controlling peak flows. The purpose of this study was to identify differences in microbial water quality of stormwater in watersheds retrofitted with GI vs. those without GI. Considering stormwater is recently recognized as a contributor to the antibiotic resistance (AR) threat, another goal of this study was to characterize changes in the microbiome and collection of AR genes (resistome) of urban stormwater with season, rainfall characteristics, and fecal contamination. MinION long-read sequencing was used to analyze stormwater microbiome and resistome from watersheds with and without GI in Columbus, Ohio, United States, over 18 months. We characterized fecal contamination in stormwater via culturing Escherichia coli and with molecular microbial source tracking (MST) to identify sources of fecal contamination. Overall, season and storm event (rainfall) characteristics had the strongest relationships with changes in the stormwater microbiome and resistome. We found no significant differences in microbial water quality or the microbiome of stormwater in watersheds with and without GI implemented. However, there were differences between the communities of microorganisms hosting antibiotic resistance genes (ARGs) in stormwater from watersheds with and without GI, indicating the potential sensitivity of AR bacteria to treatment. Stormwater was contaminated with high concentrations of human-associated fecal bacterial genes, and the ARG host bacterial community had considerable similarities to human feces/wastewater. We also identified 15 potential pathogens hosting ARGs in these stormwater resistome, including vancomycin-resistant Enterococcus faecium (VRE) and multidrug-resistant Pseudomonas aeruginosa. In summary, urban stormwater is highly contaminated and has a great potential to spread AR and microbial hazards to nearby environments. This study presents the most comprehensive analysis of stormwater microbiome and resistome to date, which is crucial to understanding the potential microbial risk from this matrix. This information can be used to guide future public health policy, stormwater reuse programs, and urban runoff treatment initiatives.

"Lock-and-key" recognizer-encoded lateral flow assays toward foodborne pathogen detection: An overview of their fundamentals and recent advances

In light of severe health risks of foodborne pathogenic bacterial diseases, the potential utility of point-of-care (POC) sensors is recognized for pathogens detection. In this regard, lateral flow assay (LFA) is a promising and user-friendly option for such application among various technological approaches. This article presents a comprehensive review of "lock-and-key" recognizer-encoded LFAs with respect to their working principles and detection performance against foodborne pathogenic bacteria. For this purpose, we describe various strategies for bacteria recognition including the antibody-based antigen-antibody interactions, nucleic acid aptamer-based recognition, and phage-mediated targeting of bacterial cells. In addition, we also outline the technological challenges along with the prospects for the future development of LFA in food analysis. The LFA devices built based upon many recognition strategies are found to have great potential for rapid, convenient, and effective POC detection of pathogens in complex food matrixes. Future developments in this field should emphasize the development of high-quality bio-probes, multiplex sensors, and intelligent portable readers.

Physico-chemical characterization studies of collagen labelled with Ru(II) polypyridyl complex

The rich luminescence behaviour exerted by transition metal complexes has found significant role in the development of biomolecular and cellular probes. The conjugation of fluorophore to a protein has its own advantage over the label-free system due to its high sensitivity. While numerous proteins have been labelled with either organic or inorganic fluorophores, the conjugation of luminescent transition metal complexes with collagen has not yet been attempted. Here, in this study, the conjugation of a Ru(II) polypyridyl complex with collagen was carried out and its physico-chemical characterization was studied. The conjugation of Ru(II) to collagen was characterized by UV-Visible, fluorescence and ATR-FT-IR spectroscopy. The conjugation of Ru(II) did not alter the triple helical structure of the collagen as evidenced from CD spectral data. The luminescence behaviour of the Ru-tagged collagen was found to be similar to that of the commercially available fluorescein isothiocyanate (FITC) tagged collagen with increase in luminescence upon addition of collagenase. Gel-based collagenase assay showed that the digestion of collagen can be vizualized using UV light due to intrinsic fluorophore tag without carrying out the staining-destaining processes. Energy dispersive X-Ray analysis (EDAX) confirms the presence of Ru in Ru-collagen fibrils. To the best of our knowledge, this is the first report on the conjugation of a Ru(II) complex with the fibrous protein collagen that exhibits similar property as of FITC-collagen and can be used as an alternative.

Development and Efficacy of Lateral Flow Point-of-Care Testing Devices for Rapid and Mass COVID-19 Diagnosis by the Detections of SARS-CoV-2 Antigen and Anti-SARS-CoV-2 Antibodies

The COVID-19 pandemic is an ongoing global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2020-2021. COVID-19 is becoming one of the most fatal pandemics in history and brings a huge challenge to the global healthcare system. Opportune detection, confinement, and early treatment of infected cases present the first step in combating COVID-19. Diagnosis via viral nucleic acid amplification tests (NAATs) is frequently employed and considered the standard procedure. However, with an increasing urge for point-of-care tests, rapid and cheaper immunoassays are widely utilized, such as lateral flow immunoassay (LFIA), which can be used for rapid, early, and large-scale detection of SARS-CoV-2 infection. In this narrative review, the principle and technique of LFIA applied in COVID-19 antigen and antibody detection are introduced. The diagnostic sensitivity and specificity of the commercial LFIA tests are outlined and compared. Generally, LFIA antigen tests for SARS-CoV-2 are less sensitive than viral NAATs, the "gold standard" for clinical COVID-19 diagnosis. However, antigen tests can be used for rapid and mass testing in high-risk congregate housing to quickly identify people with COVID-19, implementing infection prevention and control measures, thus preventing transmission. LFIA anti-SARS-CoV-2 antibody tests, IgM and/or IgG, known as serology tests, are used for identification if a person has previously been exposed to the virus or vaccine immunization. Notably, advanced techniques, such as LFT-based CRISPR-Cas9 and surface-enhanced Raman spectroscopy (SERS), have added new dimensions to the COVID-19 diagnosis and are also discussed in this review.

Rapid detection of total bacteria in foods using a poly-l-lysine-based lateral-flow assay

Food safety and freshness are evaluated according to microbiological load. To analyze this load rapidly, a poly-_l-lysine-based lateral-flow assay (PLFA) was developed. A total of 90 strains of bacteria that are often detected in spoiled foods, including Enterobacteriaceae, lactic acid bacteria, Pseudomonas, and Bacillus were detected using the PLFA. A positive signal was obtained when the bacterial concentration was ≥6 log₁₀ (cfu/test). A total of 36 fresh foods (meats, pastries, lettuces, cabbages, radishes, and sprouts) and corresponding spoiled foods were cultured for 0, 3, 6, and 9 h to investigate how many hours were required for microbial detection using PLFA. The higher the number of bacteria in a food, the shorter was the culture time required for PLFA-positive results to be obtained, so the distinction between fresh and spoiled food could be made based on the time taken for the culture to become PLFA-positive. The coefficient of determination of the least squares regression between the time to become PLFA-positive and the initial log₁₀ (cfu/g) bacterial count for the food was 0.9888. The test time for the PLFA, including pretreatment, was approximately 15-30 min. This novel method will enable the detection of total bacteria on the food processing site.