Lighting the Path: Raman Spectroscopy's Journey Through the Microbial Maze.

The rapid and precise identification of microorganisms is essential in environmental science, pharmaceuticals, food safety, and medical diagnostics. Raman spectroscopy, valued for its ability to provide detailed chemical and structural information, has gained significant traction in these fields, especially with the adoption of various excitation wavelengths and tailored optical setups. The choice of wavelength and setup in Raman spectroscopy is influenced by factors such as applicability, cost, and whether bulk or single-cell analysis is performed, each impacting sensitivity and specificity in bacterial detection.

Raman-Activated, Interactive Sorting of Isotope-Labeled Bacteria.

Due to its high spatial resolution, Raman microspectroscopy allows for the analysis of single microbial cells. Since Raman spectroscopy analyzes the whole cell content, this method is phenotypic and can therefore be used to evaluate cellular changes. In particular, labeling with stable isotopes (SIPs) enables the versatile use and observation of different metabolic states in microbes.

Sample-Size Planning for Multivariate Data: A Raman-Spectroscopy-Based Example.

The goal of sample-size planning (SSP) is to determine the number of measurements needed for statistical analysis. This SSP is necessary to achieve robust and significant results with a minimal number of measurements that need to be collected. SSP is a common procedure for univariate measurements, whereas for multivariate measurements, like spectra or time traces, no general sample-size-planning method exists.

Tracking active groundwater microbes with D O labelling to understand their ecosystem function.

Microbial activity is key in understanding the contribution of microbial communities to ecosystem functions. Metabolic labelling with heavy water (D O) leads to the formation of carbon-deuterium bonds in active microorganisms. We illustrated how D O labelling allows monitoring of metabolic activity combined with a functional characterization of active populations in complex microbial communities.