Abstract EANA2025-77

Intro: Microbial life on Earth utilises numerous metabolic by-products including volatile organic compounds (VOCs). Produced as a physiological response to environmental conditions, including extremes of pH, salinity, desiccation, or temperature1, the mechanisms for survival can be explored by investigating these by-products. Using a multi ‘omic (integration of data across multiple levels of biochemistry to gain a comprehensive understanding of biological/chemical systems) approach a robust picture can be formulated of compound utilisation, the adaptation of microbial life to extreme environments; and how survival is facilitated. In this case volatilomics, metabolomics and metagenomics were investigated using samples collected from the Makgadikgadi basin (MB) in Botswana. This hypersaline salt pan has fluctuating temperatures, and high levels of UV radiation2 where microbial life in saline conditions can be investigated. 3,4  These conditions are relevant to those predicted on ancient Mars5.  Biofilms were investigated in the MB from 3 different locations in the pan with varying water availability. For metabolomics biofilms were also compared between the separate areas of the pan and between dry season (April) and the wet season (January). Methods: While in-situ, gas samples was collected from separate biofilms onto Thermal Desorption (TD) tubes using a nalophan bag system. A physical sample of biofilm was also collected for metabolomic analysis and metagenomics. TD-Gas Chromatography-Mass Spectrometry (TD-GC-MS) and GC-Time of Flight (TOF)-MS were utilised for volatilome and metabolome analysis. DNA was extracted from each sample, and shotgun metagenomic sequencing was performed. Reads were then run through the MetaWrap pipeline to construct metagenomic assemblies before binning. Assemblies and MAGs were annotated using DRAM.  Volatilomic and metabolomic results were analysed with a combination of ChromCompare+ and Metaboanalyst platforms for uni- and multi-variate outputs.   Water content was calculated after freeze drying the samples. Results: Clear differences could be distinguished between the different biofilm groups, controls and sediment samples. Total VOC emissions were reduced in the biofilm samples as the water content increased. Over 350 compounds were identifiable after background subtraction and deconvolution in both volatilome and metabolome data, with a number showing clearly different concentrations between biofilms but also the sediment group. When biofilms from wet and dry seasons were compared, different metabolomic profiles were determined with some key metabolites identified as different between groups. Metagenome analysis revealed distinct taxonomic profiles for each site. Taxonomic profiling of short read sequences indicated Methanobacteriota and Pseudomonadota dominated wet biofilms, while Bacteroidota and Cyanobacteriota dominated the dry biofilm. Annotation of metagenome assemblies and metagenome-assembled genomes (MAGs) was performed before being screened for genes associated with VOC production and utilisation. Within metagenomes, genes associated with the degradation of several relevant compounds were identified. Conclusions: The multi’omic approach gives a starting point to expand and link large datasets and characterise an environmental system relevant to a Mars analogue. Preliminary data suggest that water content may influence VOC production with metabolomic and metagenomic differences evident. Future work will focus on these key interactions within the environment to determine microbial involvement. From these results classification models can be prepared to add unknown samples to – which can then be used to predict what or where the unknown sample came from.

[1]  C. A. Batty, V. K. Pearson, K. Olsson-Francis and G. Morgan, Royal Society of Chemistry, 2024, preprint, DOI: 10.1039/d4np00037d. [2]  T. H. Kahsay, A. Asrat and F. Franchi, Planet Space Sci, 2024, 249, 105943.  [3] F. Franchi, B. Cassaro, B. Cavalazzi, L. Lebogang, A. Tarrozi, T. H. Kahsay and C. Pacelli, Planet Space Sci, 2025, 255, 106028.  [4]  S. Filippidou, A. Price, C. Spencer-Jones, A. Scales, M. C. Macey, F. Franchi, L. Lebogang, B. Cavalazzi, S. P. Schwenzer and K. Olsson-Francis, Microorganisms, DOI:10.3390/microorganisms12010147.  [5] J. M. McGonigle, J. A. Bernau, B. B. Bowen and W. J. Brazelton, mSystems, DOI:10.1128/msystems.00846-22.