An ultrasensitive fluorimetric sensor for pre-screening of water microbial contamination risk

High-throughput and specific detection of microorganisms by intelligent modular fluorescent photoelectric microbe detector

Food safety has emerged as a major global issue. Detecting foodborne pathogenic microorganisms and controlling them is vital to guard against foodborne diseases caused by microorganisms. However, the current detection methods need to meet the demand for real-time detection on the spot after a simple operation. Considering unresolved challenges, we developed an Intelligent Modular Fluorescent Photoelectric Microbe (IMFP) system containing a special detection reagent. This IMFP system can automatically monitor microbial growth in which the photoelectric detection, temperature control, fluorescent probe, and bioinformatics screen are integrated into one platform and employed to detect pathogenic microorganisms. Moreover, a specific culture medium was also developed, which matched the system platform for Coliform bacteria and Salmonella typhi. The developed IMFP system could attain a limit of detection (LOD) of about 1 CFU/mL for both bacteria, while the selectivity could reach 99%. In addition, the IMFP system was applied to detect 256 bacterial samples simultaneously. This platform reflects the high-throughput needs of fields for microbial identification and related requirements, such as the development of pathogenic microbial diagnostic reagents, antibacterial sterilization performance tests, and microbial growth kinetics. The IMFP system also confirmed the other merits, such as high sensitivity, high-throughput, and operation simplicity compared to conventional methods, and it has a high potential as a tool for application in the health and food security fields.

Biological Indicators for Fecal Pollution Detection and Source Tracking: A Review

Fecal pollution, commonly detected in untreated or less treated sewage, is associated with health risks (e.g., waterborne diseases and antibiotic resistance dissemination), ecological issues (e.g., release of harmful gases in fecal sludge composting, proliferative bacterial/algal growth due to high nutrient loads) and economy losses (e.g., reduced aqua farm harvesting). Therefore, the discharge of untreated domestic sewage to the environment and its agricultural reuse are growing concerns. The goals of fecal pollution detection include fecal waste source tracking and identifying the presence of pathogens, therefore assessing potential health risks. This review summarizes available biological fecal indicators focusing on host specificity, degree of association with fecal pollution, environmental persistence, and quantification methods in fecal pollution assessment. The development of practical tools is a crucial requirement for the implementation of mitigation strategies that may help confine the types of host-specific pathogens and determine the source control point, such as sourcing fecal wastes from point sources and nonpoint sources. Emerging multidisciplinary bacterial enumeration platforms are also discussed, including individual working mechanisms, applications, advantages, and limitations.

In-situ fluorescence spectroscopy is a more rapid and resilient indicator of faecal contamination risk in drinking water than faecal indicator organisms

Faecal indicator organisms (FIOs) are limited in their ability to protect public health from the microbial contamination of drinking water because of their transience and time required to deliver a result. We evaluated alternative rapid, and potentially more resilient, approaches against a benchmark FIO of thermotolerant coliforms (TTCs) to characterise faecal contamination over 14 months at 40 groundwater sources in a Ugandan town. Rapid approaches included: in-situ tryptophan-like fluorescence (TLF), humic-like fluorescence (HLF), turbidity; sanitary inspections; and total bacterial cells by flow cytometry. TTCs varied widely in six sampling visits: a third of sources tested both positive and negative, 50% of sources had a range of at least 720 cfu/100 mL, and a two-day heavy rainfall event increased median TTCs five-fold. Using source medians, TLF was the best predictor in logistic regression models of TTCs ≥10 cfu/100 mL (AUC 0.88) and best correlated to TTC enumeration (ρ_s 0.81), with HLF performing similarly. Relationships between TLF or HLF and TTCs were stronger in the wet season than the dry season, when TLF and HLF were instead more associated with total bacterial cells. Source rank-order between sampling rounds was considerably more consistent, according to cross-correlations, using TLF or HLF (min ρ_s 0.81) than TTCs (min ρ_s 0.34). Furthermore, dry season TLF and HLF cross-correlated more strongly (ρ_s 0.68) than dry season TTCs (ρ_s 0.50) with wet season TTCs, when TTCs were elevated. In-situ TLF or HLF are more rapid and resilient indicators of faecal contamination risk than TTCs.