Production and Preservation of Lipid Biosignatures in SO4-Rich Hypersaline Lakes of the Cariboo Plateau

Abstract

Modern and ancient hypersaline lakes and oceans have been identified across the solar system, but the habitability and potential of these environments to preserve organic matter remain unknown. Here, we evaluate organic matter production and preservation potential in hypersaline lakes whose chemistries resemble deposits on Mars. We focus our analysis on lipid biomarkers including fatty acids, alkanes, and ether-bound lipids in modern brines, salt deposits, and surface sediments. We also report total organic carbon (TOC), carbon/nitrogen (C/N) ratios, and bulk OC (δ13C and δ15N) isotopes to contextualize the lipid data. In all lakes, the predominant biosignatures include short chain fatty acids (C<23) suggesting microbial origin. Sediments also incorporate a diversity of microbially and terrestrially derived lipids. Ether-bound lipids derived from archaea and bacteria constitute a minor but measurable fraction of the lipids in brines. This result contrasts with typical results from NaCl brines which contain significant archaeal biomass. TOC concentrations in sediments are universally high, ranging from 0.7% to 12% with sulfate-rich sediments having the highest concentrations. The isotopic composition of TOC corroborates the biomarker results, showing δ13C values and C/N values indicative of aquatic microbial origin. This richness of organic material and in situ microbial biosignatures differ from previously studied Cl-dominated Mars-analog sites which have shown limited organic matter production and preservation and acidic SO4-rich hypersaline environments which were dominated by terrestrial inputs. Overall, our results suggest that Mg-SO4-rich hypersaline environments harbor a rich microbial biomarker landscape and are ideal locations for preserving these signatures, potentially over geological timescales.

Lipid Biosignatures From SO4‐Rich Hypersaline Lakes of the Cariboo Plateau

“…All data, R, and Python scripts written for data analysis and visualization are hosted at https://zenodo.org/ record/8169323 and can be cited as "F. Nichols (2023).…”