DataSheet1_Correlation Network Analysis for Amino Acid Identification in Soil Samples With the ORIGIN Space-Prototype Instrument.pdf

• Main Authors: Loraine Schwander, Niels F.W. Ligterink, Kristina A. Kipfer, Rustam A. Lukmanov, Valentine Grimaudo, Marek Tulej, Coenraad P. de Koning, Peter Keresztes Schmidt, Salome Gruchola, Nikita J. Boeren, Pascale Ehrenfreund, Peter Wurz, Andreas Riedo
• Format: Dataset
• Language: unknown
• Published: 2022
• Subjects: Stellar Astronomy; Cosmology; Astrophysics; Planetary Science; Solar System; Solar Physics; Planets and Exoplanets; Space Science; High Energy Astrophysics; Cosmic Rays; Space and Solar Physics; Astronomical and Space Sciences not elsewhere classified; astrobiology; network analysis; biosignatures; mass spectrometry; laser desorption; space instrumentation; amino acids; planetary exploration; permafrost
• Online Access: https://doi.org/10.3389/fspas.2022.909193.s001; https://figshare.com/articles/dataset/DataSheet1_Correlation_Network_Analysis_for_Amino_Acid_Identification_in_Soil_Samples_With_the_ORIGIN_Space-Prototype_Instrument_pdf/19940030

The detection of biomolecules on Solar System bodies can help us to understand how life emerged on Earth and how life may be distributed in our Solar System. However, the detection of chemical signatures of life on planets or their moons is challenging. A variety of parameters must be considered, such as a suited landing site location, geological and environmental processes favourable to life, life detection strategies, and the application of appropriate and sensitive instrumentation. In this contribution, recent results obtained using our novel laser desorption mass spectrometer ORganics INformation Gathering Instrument (ORIGIN), an instrument designed for in situ space exploration, are presented. We focus in this paper on the detection and identification of amino acid extracts from a natural permafrost sample, as well as in an analogue mixture of soils and amino acids. The resulting dataset was analysed using a correlation network analysis method. Based on mass spectrometric correlation, amino acid signatures were separated from soil signatures, identifying chemically different molecular components in complex samples. The presented analysis method represents an alternative to the typically applied spectra-by-spectra analysis for the evaluation of mass spectrometric data and, therefore, is of high interest for future application in space exploration missions.