Detection and Differentiation of Bacterial and Fungal Infection of Neutrophils from Peripheral Blood Using Raman Spectroscopy.

Neutrophils are important cells of the innate immune system and the major leukocyte subpopulation in blood. They are responsible for recognizing and neutralizing invading pathogens, such as bacteria or fungi. For this, neutrophils are well equipped with pathogen recognizing receptors, cytokines, effector molecules, and granules filled with reactive oxygen species (ROS)-producing enzymes. Depending on the pathogen type, different reactions are triggered, which result in specific activation states of the neutrophils. Here, we aim to establish a label-free method to indirectly detect infections and to identify the cause of infection by spectroscopic characterization of the neutrophils. For this, isolated neutrophils from human peripheral blood were stimulated in an in vitro infection model with heat-inactivated Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacterial pathogens as well as with heat-inactivated and viable fungi (Candida albicans). Label-free and nondestructive Raman spectroscopy was used to characterize neutrophils on a single cell level. Phagocytized fungi could be visualized in a few high-resolution false color images of individual neutrophils using label-free Raman spectroscopic imaging. Using a high-throughput screening Raman spectroscope (HTS-RS), Raman spectra of more than 2000 individual neutrophils from three different donors were collected in each treatment group, yielding a data set of almost 20 000 neutrophil spectra. Random forest classification models were trained to differentiate infected and noninfected cells with high accuracy (90%). Among the neutrophils challenged with pathogens, even the cause of infection, bacterial or fungal, was predicted correctly with 92% accuracy. Therefore, Raman spectroscopy enables reliable neutrophil phenotyping and infection diagnosis in a label-free manner. In contrast to the microbiological diagnostic standard, where the pathogen is isolated in time-consuming cultivation, this Raman-based method could potentially be blood-culture independent, thus saving precious time in bloodstream infection diagnostics.

Fabrication of micro-patterned substrates for plasmonic sensing by piezo-dispensing of colloidal nanoparticles.

In this work we describe a very fast and flexible method for fabrication of plasmon-supporting substrates with micro-patterning capability, which is optimized for plasmonic sensing. We combined a wet chemistry approach to synthesize metallic nanoparticles with a piezo-dispensing system enabling deposition of nanoparticles on the substrates with micrometer precision. In this way, an arbitrary pattern consisting of 200 µm small spots containing plasmonic nanostructures can be produced. Patterns with various nanoparticles exhibiting different plasmonic properties were combined, and the surface density of the particles could be easily varied via their solution concentrations. We showed that under controlled conditions the dispensing process caused no aggregation of the particles and it enabled full transfer of the colloidal solutions onto the substrate. This is an important condition, which enables these substrates to be used for reliable plasmonic sensing based on monitoring the spectral shift of the nanoparticles. We demonstrated the functionality of such substrates by detection of small protein adsorption on the spots based on plasmon label-free sensing method.

Plasmonic Nanosensor Array for Multiplexed DNA-based Pathogen Detection.

In this research we introduce a plasmonic nanoparticle based optical biosensor for monitoring of molecular binding events. The sensor utilizes spotted gold nanoparticle arrays as sensing platform. The nanoparticle spots are functionalized with capture DNA sequences complementary to the analyte (target) DNA. Upon incubation with the target sequence, it will bind on the respectively complementary functionalized particle spot. This binding changes the local refractive index, which is detected spectroscopically as the resulting changes of the localized surface plasmon resonance (LSPR) peak wavelength. In order to increase the signal, a small gold nanoparticle label is introduced. The binding can be reversed using chemical means (10 mM HCl). It is demonstrated that multiplexed detection and identification of several fungal pathogen DNA sequences subsequently on one sensor array are possible by this approach.