Ute Neugebauer

Raman spectroscopic cytometry for the detection and characterization of bacterial infection

Infectious diseases are one of the leading causes for deaths worldwide. In order to efficiently treat an infection, physicians need to know which pathogen is causing the infection and –in case of a bacterial infection – the pathogen’s antibiotic susceptibility. Established microbiological methods used in routine clinical diagnostics are mainly based on cultivation to detect the bacteria and to generate enough biological material for subsequent analysis, such as antibiotic susceptibility testing. Thus, they need at least a full day to provide the result. Faster methods are urgently needed to administer tailored antibiotic therapy already early on.

In this presentation, a new Raman spectroscopy-based approach is presented which holds the potential to dramatically reduce diagnosis times. By means of Raman spectroscopy (individual) cells can be characterized without the need of any external label making sample preparation very easy. The inelastic scattered light provides highly specific information of the overall molecular composition of the investigated cells yielding a so-called “spectroscopic fingerprint”. This spectroscopic fingerprint in combination with multivariate statistical data analysis can be used to characterize immune cells from the host, but also to characterize the pathogen causing the infection.

Here, we will focus on the characterization of the bacterial pathogen and present how Raman spectroscopy can be used to distinguish different pathogens. This will exemplarily be shown for bacteria from patient’s urine samples. Furthermore, Raman spectroscopy can be applied to differentiate the bacteria’s response to antibiotic treatment. From this response valuable information on the pathogen’s antibiotic susceptibility can be extracted. This can be done in a qualitative manner to classify the bacteria as sensitive or resistant; as well as in a quantitative manner yielding the antibiotic’s minimal inhibitory concentration (MIC).