Rapid Identification of Multiple Bacteria on a Microfluidic Chip

Microfluidics-Based Nanobiosensors for Healthcare Monitoring

Efficient healthcare management demands prompt decision-making based on fast diagnostics tools, astute data analysis, and informatics analysis. The rapid detection of analytes at the point of care is ensured using microfluidics in synergy with nanotechnology and biotechnology. The nanobiosensors use nanotechnology for testing, rapid disease diagnosis, monitoring, and management. In essence, nanobiosensors detect biomolecules through bioreceptors by modulating the physicochemical signals generating an optical and electrical signal as an outcome of the binding of a biomolecule with the help of a transducer. The nanobiosensors are sensitive and selective and play a significant role in the early identification of diseases. This article reviews the detection method used with the microfluidics platform for nanobiosensors and illustrates the benefits of combining microfluidics and nanobiosensing techniques by various examples. The fundamental aspects, and their application are discussed to illustrate the advancement in the development of microfluidics-based nanobiosensors and the current trends of these nano-sized sensors for point-of-care diagnosis of various diseases and their function in healthcare monitoring.

Fabrication of spectroscopic microfluidic chips for mastitis detection in raw milk

Mastitis is a disease that directly affects the quantity and quality of milk produced by dairy cows, which can have a negative impact on the income generated from selling the milk. Severe inflammation caused by this mammary disease can result in up to 1 × 10⁶ white blood cells per milliliter of cow milk. Currently, the California mastitis test is a popular chemical inspection test, but its error rate of over 40% is a significant factor in the ongoing spread of mastitis. In this study, a new microfluidic device was designed and fabricated to identify normal, sub-clinical, and clinical mastitis. This portable device allows for precise and analysis of results within a second. The device was designed to screen somatic cells and a staining process was added to identify somatic cells using single-cell process analysis. The fluorescence principle was used to identify the infection status of the milk, which was analyzed using a mini-spectrometer. The accuracy of the device was tested, and it was found to determine the infection status with 95% accuracy, compared to the accuracy obtained using the Fossomatic machine. By introducing this new microfluidic device, it is believed that the spread of mastitis in dairy cows can be significantly reduced, leading to higher quality and more profitable milk production.

Fast label-free identification of bacteria by synchronous fluorescence of amino acids

Fast identification of pathogenic bacteria is an essential need for patient's diagnostic in hospitals and environmental monitoring of water and air quality. Bacterial cells consist of a very high amount of biological molecules whose content changes in response to different environmental conditions. The similarity between the molecular compositions of different bacterial cells limits the possibility to find unique markers to enable differentiation among species. Although many biological molecules in the cells absorb at the UV-Vis region, only a few of them can be detected in whole cells by their intrinsic fluorescence. Among these molecules are the amino acids phenylalanine, tyrosine, and tryptophan. In this work, we develop a rapid method for bacterial identification by synchronous fluorescence. We show that we can quantify the concentration for the 3 amino acids without any significant interference from other fluorophores in the cells and that we can differentiate among 6 pathogenic bacterial species by using the concentrations of their amino acids as a bacterial fingerprint. Fluorescent amino acids exist in all living cells. Therefore, this method has the potential to be applicative for the rapid identification of cells from all kinds of organisms.