Enzymatic Activity Profiling Using an Ultrasensitive Array of Chemiluminescent Probes for Bacterial Classification and Characterization.
Omri ShelefTal KoppRozan TannousMaxence ArutkinMoriah Jospe-KaufmanShlomi ReuveniDoron ShabatMicha FridmanPublished in: Journal of the American Chemical Society (2024)
Identification and characterization of bacterial species in clinical and industrial settings necessitate the use of diverse, labor-intensive, and time-consuming protocols as well as the utilization of expensive and high-maintenance equipment. Furthermore, while cutting-edge identification technologies such as mass spectrometry and PCR are highly effective in identifying bacterial pathogens, they fall short in providing additional information for identifying bacteria not present in the databases upon which these methods rely. In response to these challenges, we present a robust and general approach to bacterial identification based on their unique enzymatic activity profiles. This method delivers results within 90 min, utilizing an array of highly sensitive and enzyme-selective chemiluminescent probes. Leveraging our recently developed technology of chemiluminescent luminophores, which emit light under physiological conditions, we have crafted an array of probes designed to rapidly detect various bacterial enzymatic activities. The array includes probes for detecting resistance to the important and large class of β-lactam antibiotics. The analysis of chemiluminescent fingerprints from a diverse range of prominent bacterial pathogens unveiled distinct enzymatic activity profiles for each strain. The reported universally applicable identification procedure offers a highly sensitive and expeditious means to delineate bacterial enzymatic activity fingerprints. This opens new avenues for characterizing and identifying pathogens in research, clinical, and industrial applications.
Keyphrases
- hydrogen peroxide
- small molecule
- living cells
- mass spectrometry
- high resolution
- gram negative
- high throughput
- machine learning
- deep learning
- heavy metals
- healthcare
- fluorescent probe
- high density
- nitric oxide
- antimicrobial resistance
- single cell
- quantum dots
- molecularly imprinted
- artificial intelligence
- photodynamic therapy
- nucleic acid
- gas chromatography
- capillary electrophoresis