BactoSpin: Novel Technology for Rapid Bacteria Detection and Antibiotic Susceptibility Testing.

Inappropriate use of antibiotics is one of the leading causes of the increasing numbers of resistant bacteria strains, resulting in 700,000 deaths worldwide each year. Reducing unnecessary use of antibiotics and choosing the most effective antibiotics instead of broad-spectrum drugs will slow the arms race between germs and humans. Urinary tract infections (UTIs) are among the most common bacterial infections. Currently, accurate diagnosis of UTI requires approximately 48 h from the time of urine sample collection until antibiotic susceptibility test (AST) results. This work presents a rapid bacterial detection device that integrates a centrifuge, microscope, and incubator. Two disposable microfluidic chips were developed. The first chip was designed for bacteria concentration, detection, and medium exchange. A second multi-channel chip was developed for AST. This chip contains superhydrophobic and hydrophilic coatings to ensure liquid separation between the channels without the need for valves. The designed chips supported the detection of E. coli at a concentration as low as 5 × 103 cells/mL within 5 min and AST in under 2 h. AST was also successfully performed with Klebsiella pneumonia isolated from a human urine sample. In addition, machine-learning-based image recognition was shown to reduce the required time for AST and to provide results within 1 h for E. coli cells. Thus, the BactoSpin device can serve as an efficient and rapid platform for UTI diagnostics and AST.

A Paper-Based Near-Infrared Optical Biosensor for Quantitative Detection of Protease Activity Using Peptide-Encapsulated SWCNTs.

A protease is an enzyme that catalyzes proteolysis of proteins into smaller polypeptides or single amino acids. As crucial elements in many biological processes, proteases have been shown to be informative biomarkers for several pathological conditions in humans, animals, and plants. Therefore, fast, reliable, and cost-effective protease biosensors suitable for point-of-care (POC) sensing may aid in diagnostics, treatment, and drug discovery for various diseases. This work presents an affordable and simple paper-based dipstick biosensor that utilizes peptide-encapsulated single-wall carbon nanotubes (SWCNTs) for protease detection. Upon enzymatic digestion of the peptide, a significant drop in the photoluminescence (PL) of the SWCNTs was detected. As the emitted PL is in the near-infrared region, the developed biosensor has a good signal to noise ratio in biological fluids. One of the diseases associated with abnormal protease activity is pancreatitis. In acute pancreatitis, trypsin concentration could reach up to 84 µg/mL in the urine. For proof of concept, we demonstrate the feasibility of the proposed biosensor for the detection of the abnormal levels of trypsin activity in urine samples.

A nanoscale paper-based near-infrared optical nose (NIRON).

Electronic noses (e-nose) and optical noses (o-nose) are two emerging approaches for the development of artificial olfactory systems for flavor and smell evaluation. The current work leverages the unique optical properties of semiconducting single-wall carbon nanotubes (SWCNTs) to develop a prototype of a novel paper-based near-infrared optical nose (NIRON). We have drop-dried an array of SWCNTs encapsulated with a wide variety of peptides on a paper substrate and continuously imaged the emitted SWCNTs fluorescence using a CMOS camera. Odors and different volatile molecules were passed above the array in a flow chamber, resulting in unique modulation patterns of the SWCNT photoluminescence (PL). Quartz crystal microbalance (QCM) measurements performed in parallel confirmed the direct binding between the vapor molecules and the peptide-SWCNTs. PL levels measured before and during exposure demonstrate distinct responses to the four tested alcoholic vapors (ethanol, methanol, propanol, and isopropanol). In addition, machine learning tools directly applied to the fluorescence images allow us to distinguish between the aromas of red wine, beer, and vodka. Further, we show that the developed sensor can detect limonene, undecanal, and geraniol vapors, and differentiate between their smells utilizing the PL response pattern. This novel paper-based optical biosensor provides data in real-time, and is recoverable and suitable for working at room temperature and in a wide range of humidity levels. This platform opens new avenues for real-time sensing of volatile chemical compounds, odors, and flavors.