Frontiers in Microbiology (Apr 2022)

Comprehensive Metabolic and Taxonomic Reconstruction of an Ancient Microbial Mat From the McMurdo Ice Shelf (Antarctica) by Integrating Genetic, Metaproteomic and Lipid Biomarker Analyses

  • María Ángeles Lezcano,
  • Laura Sánchez-García,
  • Antonio Quesada,
  • Antonio Quesada,
  • Daniel Carrizo,
  • Miguel Ángel Fernández-Martínez,
  • Erika Cavalcante-Silva,
  • Víctor Parro

DOI
https://doi.org/10.3389/fmicb.2022.799360
Journal volume & issue
Vol. 13

Abstract

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Paleobiological reconstructions based on molecular fossils may be limited by degradation processes causing differential preservation of biomolecules, the distinct taxonomic specificity of each biomolecule type, and analytical biases. Here, we combined the analysis of DNA, proteins and lipid biomarkers using 16S and 18S rRNA gene metabarcoding, metaproteomics and lipid analysis to reconstruct the taxonomic composition and metabolisms of a desiccated microbial mat from the McMurdo Ice Shelf (MIS) (Antarctica) dated ~1,000 years BP. The different lability, taxonomic resolution and analytical bias of each biomolecule type led to a distinct microbial community profile. DNA analysis showed selective preservation of DNA remnants from the most resistant taxa (e.g., spore-formers). In contrast, the proteins profile revealed microorganisms missed by DNA sequencing, such as Cyanobacteria, and showed a microbial composition similar to fresh microbial mats in the MIS. Lipid hydrocarbons also confirmed Cyanobacteria and suggested the presence of mosses or vascular plant remnants from a period in Antarctica when the climate was warmer (e.g., Mid-Miocene or Eocene). The combined analysis of the three biomolecule types also revealed diverse metabolisms that operated in the microbial mat before desiccation: oxygenic and anoxygenic photosynthesis, nitrogen fixation, nitrification, denitrification, sulfur reduction and oxidation, and methanogenesis. Therefore, the joint analysis of DNA, proteins and lipids resulted in a powerful approach that improved taxonomic and metabolic reconstructions overcoming information gaps derived from using individual biomolecules types.

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