Proteome-wide 3D structure prediction provides insights into the ancestral metabolism of ancient archaea and bacteria

Weishu Zhao, Bozitao Zhong, Lirong Zheng, Pan Tan, Yinzhao Wang, Hao Leng, Nicolas Souza, Zhuo Liu, Liang Hong () and Xiang Xiao ()
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Weishu Zhao: Shanghai Jiao Tong University
Bozitao Zhong: Shanghai Jiao Tong University
Lirong Zheng: Shanghai Jiao Tong University
Pan Tan: Shanghai Jiao Tong University
Yinzhao Wang: Shanghai Jiao Tong University
Hao Leng: Shanghai Jiao Tong University
Nicolas Souza: Australian Nuclear Science and Technology (ANSTO)
Zhuo Liu: Shanghai Jiao Tong University
Liang Hong: Shanghai Jiao Tong University
Xiang Xiao: Shanghai Jiao Tong University

Nature Communications, 2022, vol. 13, issue 1, 1-14

Abstract: Abstract Ancestral metabolism has remained controversial due to a lack of evidence beyond sequence-based reconstructions. Although prebiotic chemists have provided hints that metabolism might originate from non-enzymatic protometabolic pathways, gaps between ancestral reconstruction and prebiotic processes mean there is much that is still unknown. Here, we apply proteome-wide 3D structure predictions and comparisons to investigate ancestorial metabolism of ancient bacteria and archaea, to provide information beyond sequence as a bridge to the prebiotic processes. We compare representative bacterial and archaeal strains, which reveal surprisingly similar physiological and metabolic characteristics via microbiological and biophysical experiments. Pairwise comparison of protein structures identify the conserved metabolic modules in bacteria and archaea, despite interference from overly variable sequences. The conserved modules (for example, middle of glycolysis, partial TCA, proton/sulfur respiration, building block biosynthesis) constitute the basic functions that possibly existed in the archaeal-bacterial common ancestor, which are remarkably consistent with the experimentally confirmed protometabolic pathways. These structure-based findings provide a new perspective to reconstructing the ancestral metabolism and understanding its origin, which suggests high-throughput protein 3D structure prediction is a promising approach, deserving broader application in future ancestral exploration.

Date: 2022
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DOI: 10.1038/s41467-022-35523-8

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