Please use this identifier to cite or link to this item:

TitleMetabolic models and gene essentiality data reveal essential and conserved metabolism in prokaryotes
Author(s)Xavier, Joana C.
Patil, Kiran Raosaheb
Rocha, I.
Issue date16-Nov-2018
PublisherPublic Library of Science
JournalPLoS Computational Biology
CitationXavier, Joana C.; Patil, Kiran Raosaheb; Rocha, Isabel, Metabolic models and gene essentiality data reveal essential and conserved metabolism in prokaryotes. PLoS Computational Biology, 14(11), 1-23, 2018
Abstract(s)If we tried to list every known chemical reaction within an organismhuman, plant or even bacteriawe would get quite a long and confusing read. But when this information is represented in so-called genome-scale metabolic networks, we have the means to access computationally each of those reactions and their interconnections. Some parts of the network have alternatives, while others are unique and therefore can be essential for growth. Here, we simulate growth and compare essential reactions and genes for the simplest type of unicellular speciesprokaryotesto understand which parts of their metabolism are universally essential and potentially ancestral. We show that similar patterns of essential reactions echo phylogenetic relationships (this makes sense, as the genome provides the building plan for the enzymes that perform those reactions). Our computational predictions correlate strongly with experimental essentiality data. Finally, we show that a crucial step of protein synthesis (tRNA charging) and the synthesis and transformation of small molecules that enzymes require (cofactors) are the most essential and conserved parts of metabolism in prokaryotes. Our results are a step further in understanding the biology and evolution of prokaryotes but can also be relevant in applied studies including metabolic engineering and antibiotic design.
Publisher version
AccessOpen access
Appears in Collections:CEB - Publicações em Revistas/Séries Internacionais / Publications in International Journals/Series

Files in This Item:
File Description SizeFormat 
document_49383_1.pdf3,58 MBAdobe PDFView/Open

Partilhe no FacebookPartilhe no TwitterPartilhe no DeliciousPartilhe no LinkedInPartilhe no DiggAdicionar ao Google BookmarksPartilhe no MySpacePartilhe no Orkut
Exporte no formato BibTex mendeley Exporte no formato Endnote Adicione ao seu ORCID