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The Enzymatic and Metabolic Capabilities of Early Life

Overview of attention for article published in PLOS ONE, September 2012
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Title
The Enzymatic and Metabolic Capabilities of Early Life
Published in
PLOS ONE, September 2012
DOI 10.1371/journal.pone.0039912
Pubmed ID
Authors

Aaron David Goldman, John A. Baross, Ram Samudrala

Abstract

We introduce the concept of metaconsensus and employ it to make high confidence predictions of early enzyme functions and the metabolic properties that they may have produced. Several independent studies have used comparative bioinformatics methods to identify taxonomically broad features of genomic sequence data, protein structure data, and metabolic pathway data in order to predict physiological features that were present in early, ancestral life forms. But all such methods carry with them some level of technical bias. Here, we cross-reference the results of these previous studies to determine enzyme functions predicted to be ancient by multiple methods. We survey modern metabolic pathways to identify those that maintain the highest frequency of metaconsensus enzymes. Using the full set of modern reactions catalyzed by these metaconsensus enzyme functions, we reconstruct a representative metabolic network that may reflect the core metabolism of early life forms. Our results show that ten enzyme functions, four hydrolases, three transferases, one oxidoreductase, one lyase, and one ligase, are determined by metaconsensus to be present at least as late as the last universal common ancestor. Subnetworks within central metabolic processes related to sugar and starch metabolism, amino acid biosynthesis, phospholipid metabolism, and CoA biosynthesis, have high frequencies of these enzyme functions. We demonstrate that a large metabolic network can be generated from this small number of enzyme functions.

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Geographical breakdown

Country Count As %
United States 3 4%
Germany 1 1%
United Kingdom 1 1%
Peru 1 1%
Iran, Islamic Republic of 1 1%
Chile 1 1%
Spain 1 1%
Mexico 1 1%
Venezuela, Bolivarian Republic of 1 1%
Other 1 1%
Unknown 70 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 23%
Student > Ph. D. Student 18 22%
Student > Bachelor 11 13%
Professor > Associate Professor 9 11%
Student > Master 5 6%
Other 14 17%
Unknown 6 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 35 43%
Biochemistry, Genetics and Molecular Biology 12 15%
Chemistry 6 7%
Environmental Science 5 6%
Engineering 4 5%
Other 13 16%
Unknown 7 9%