Timing the evolution of phosphorus-cycling enzymes through geological time using phylogenomics

Joanne Boden*, Juntao Zhong, Rika Anderson, Eva Elisabeth Stueeken

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Phosphorus plays a crucial role in controlling biological productivity, but geological estimates of phosphate concentrations in the Precambrian ocean, during life’s origin and early evolution, vary over several orders of magnitude. While reduced phosphorus species may have served as alternative substrates to phosphate, their bioavailability on the early Earth remains unknown. Here, we reconstruct the phylogenomic record of life on Earth and find that phosphate transporting genes (pnas) evolved in the Paleoarchean (ca. 3.6-3.2 Ga) and are consistent with phosphate concentrations above modern levels ( > 3 µM). The first gene optimized for low phosphate levels (pstS; <1 µM) appeared around the same time or in the Mesoarchean depending on the reconstruction method. Most enzymatic pathways for metabolising reduced phosphorus emerged and expanded across the tree of life later. This includes phosphonate-catabolising CP-lyases, phosphite-oxidising pathways and hypophosphite-oxidising pathways. CP-lyases are particularly abundant in dissolved phosphate concentrations below 0.1 µM. Our results thus indicate at least local regions of declining phosphate levels through the Archean, possibly linked to phosphate-scavenging Fe(III), which may have limited productivity. However, reduced phosphorus species did not become widely used until after the Paleoproterozoic Great Oxidation Event (2.3 Ga), possibly linked to expansion of the biosphere at that time.
Original languageEnglish
Article number3703
Number of pages12
JournalNature Communications
Volume15
DOIs
Publication statusPublished - 2 May 2024

Keywords

  • Evolution
  • Early life
  • Phosphorus
  • Microbiology
  • Phylogenomics
  • Molecular clock
  • Archean
  • Great Oxidation Event
  • Precambrian
  • Genome mining

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