Biogenic origin of preserved organic molecules in volcanic caves by ultra-high resolution analytical pyrolysis and chemometrics

Siliceous speleothems, formed by mineral deposition in lava tubes, are vital for understanding past volcanic eruptions, assessing environmental conditions, and investigating extreme life forms. Molecular characterization of cave samples is also relevant, needing the use of cuttingedge analytical techniques. The analytical pyrolysis (Py) coupled with exact-mass spectrometry (Py-GC/Q-TOF) is a promising one. Analytical Py involves thermal decomposition of organic matter (OM) at high temperatures without oxygen, enabling chromatographic separation and providing valuable information about complex mixtures’ composition and molecular structure, including natural and synthetic macromolecules. Advantages of analytical Py include minimal sample preparation, small sample sizes, and detection of various organic materials, even those with low solubility or resistance to degradation. This technique facilitates rapid analysis of scarce or unique organic samples found in extreme environments and Mars analogues. Ultra-high resolution analytical pyrolysis (UH-Py) allows the identification of numerous distinct organic molecules in a sample without pre-treatment. However, due to the large number of chemical structures discovered, investigating each molecule separately is unfeasible. To address this, novel graphical-statistical tools are needed to identify primary chemical and biogenic families in a sample and investigate microorganisms’ adaptations to environmental or anthropogenic factors. This communication introduces the integration of UH-Py with multivariate statistical analysis and graphic-statistical tools as an innovative strategy for unsupervised classification and visual analysis of preserved organic matrices in siliceous speleothems from diverse lava tubes. The study focuses on samples from Selvagens Islands, La Palma (Canary Island), Easter Island, and the Galapagos Islands. By combining these analytical techniques, it becomes possible to identify biosignatures, such as mic