SERS-based rapid susceptibility testing of commonly administered antibiotics on clinically important bacteria species directly from blood culture of bacteremia patients.

Bloodstream infections are a growing public health concern due to emerging pathogens and increasing antimicrobial resistance. Rapid antibiotic susceptibility testing (AST) is urgently needed for timely and optimized choice of antibiotics, but current methods require days to obtain results. Here, we present a general AST protocol based on surface-enhanced Raman scattering (SERS-AST) for bacteremia caused by eight clinically relevant Gram-positive and Gram-negative pathogens treated with seven commonly administered antibiotics. Our results show that the SERS-AST protocol achieves a high level of agreement (96% for Gram-positive and 97% for Gram-negative bacteria) with the widely deployed VITEK 2 diagnostic system. The protocol requires only five hours to complete per blood-culture sample, making it a rapid and effective alternative to conventional methods. Our findings provide a solid foundation for the SERS-AST protocol as a promising approach to optimize the choice of antibiotics for specific bacteremia patients. This novel protocol has the potential to improve patient outcomes and reduce the spread of antibiotic resistance.

Deep Learning-Assisted Surface-Enhanced Raman Scattering for Rapid Bacterial Identification.

Bloodstream infection (BSI) is characterized by the presence of viable microorganisms in the bloodstream and may induce systemic immune responses. Early and appropriate antibiotic usage is crucial to effectively treating BSI. However, conventional culture-based microbiological diagnostics are time-consuming and cannot provide timely bacterial identification for subsequent antimicrobial susceptibility test (AST) and clinical decision-making. To address this issue, modern microbiological diagnostics have been developed, such as surface-enhanced Raman scattering (SERS), which is a sensitive, label-free, and quick bacterial detection method measuring specific bacterial metabolites. In this study, we aim to integrate a new deep learning (DL) method, Vision Transformer (ViT), with bacterial SERS spectral analysis to build the SERS-DL model for rapid identification of Gram type, species, and resistant strains. To demonstrate the feasibility of our approach, we used 11,774 SERS spectra obtained directly from eight common bacterial species in clinical blood samples without artificial introduction as the training dataset for the SERS-DL model. Our results showed that ViT achieved excellent identification accuracy of 99.30% for Gram type and 97.56% for species. Moreover, we employed transfer learning by using the Gram-positive species identifier as a pre-trained model to perform the antibiotic-resistant strain task. The identification accuracy of methicillin-resistant and -susceptible Staphylococcus aureus (MRSA and MSSA) can reach 98.5% with only 200-dataset requirement. In summary, our SERS-DL model has great potential to provide a quick clinical reference to determine the bacterial Gram type, species, and even resistant strains, which can guide early antibiotic usage in BSI.

Characterization of coumarin-6 polycrystalline films growth from vacuum deposition at various substrate temperatures.

Coumarin-6 polycrystalline films were fabricated from vacuum deposition at various substrate temperatures Tsub from 106 to 178 °C with a fixed source temperature of 185 °C. Because of its slenderer and more asymmetric structure, the adhered coumarin-6 molecule on top of the growing interface encounters a larger steric energetic barrier of 0.92 eV as estimated from the Arrhenius plot of growth rate versus 1/Tsub. From top-view SEM pictures, the as-deposited coumarin-6 thin films exhibit a twisted pattern and a kinematic roughness for Tsub < 150 °C; while clear facets emerge for Tsub ≥ 150 °C due to the increase of surface diffusion energy of the adhered molecules. From XRD analysis, besides the confirmation of the triclinic structure two anomalous peaks observed at 2θ ~ 9.007° and 7.260° are explained due to the co-existence of N- and S-coumarin-6-isomers within the crystalline grains. Furthermore, for coumarin-6 polycrystalline films deposited at Tsub = 150 °C with high crystallinity of the constituent grains, the bandgap determined from optical transmission is around 2.392 eV; and from photoluminescence spectra, the fitted four emission components are assigned to the Frenkel and charge transfer excitons recombination with participation of molecular vibrational states.

Role of molecular conformations in rubrene polycrystalline films growth from vacuum deposition at various substrate temperatures.

We report on the optical and structural characterization of rubrene polycrystalline films fabricated from vacuum deposition with various substrate temperatures (Tsub). Depending on Tsub, the role of twisted and planar rubrene conformational isomers on the properties of rubrene films is focused. The temperature (T)-dependent inverse optical transmission (IOT) and photoluminescence (PL) spectra were performed on these rubrene films. The origins of these IOT and PL peaks are explained in terms of the features from twisted and planar rubrene molecules and of the band characteristics from rubrene molecular solid films. Here, two rarely reported weak-peaks at 2.431 and 2.605 eV were observed from IOT spectra, which are associated with planar rubrene. Besides, the T-dependence of optical bandgap deduced from IOT spectra is discussed with respect to Tsub. Together with IOT and PL spectra, for Tsub > 170 °C, the changes in surface morphology and unit cell volume were observed for the first time, and are attributed to the isomeric transformation from twisted to planar rubrenes during the deposition processes. Furthermore, a unified schematic diagram in terms of Frenkel exciton recombination is suggested to explain the origins of the dominant PL peaks performed on these rubrene films at 15 K.