RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis.

Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper.

Novel methods to characterise spatial distribution and enantiomeric composition of usnic acids in four Icelandic lichens.

Usnic acid is an antibiotic metabolite produced by a wide variety of lichenized fungal lineages. The enantiomers of usnic acid have been shown to display contrasting bioactivities, and hence it is important to determine their spatial distribution, amounts and enantiomeric ratios in lichens to understand their roles in nature and grasp their pharmaceutical potential. The overall aim of the study was to characterise the spatial distribution of the predominant usnic acid enantiomer in lichens by combining spatial imaging and chiral chromatography. Specifically, separation and quantification of usnic acid enantiomers in four common lichens in Iceland was performed using a validated chiral chromatographic method. Molecular dynamics simulation was carried out to rationalize the chiral separation mechanism. Spatial distribution of usnic acid in the lichen thallus cross-sections were analysed using Desorption Electrospray Ionization-Imaging Mass Spectrometry (DESI-IMS) and fluorescence microscopy. DESI-IMS confirmed usnic acid as a cortical compound, and revealed that usnic acid can be more concentrated around the algal vicinity. Fluorescence microscopy complemented DESI-IMS by providing more detailed distribution information. By combining results from spatial imaging and chiral separation, we were able to visualize the distribution of the predominant usnic acid enantiomer in lichen cross-sections: (+)-usnic acid in Cladonia arbuscula and Ramalina siliquosa, and (-)-usnic acid in Alectoria ochroleuca and Flavocetraria nivalis. This study provides an analytical foundation for future environmental and functional studies of usnic acid enantiomers in lichens.