LUCApedia: a database for the study of ancient life
Aaron David Goldman1,*, Tess M. Bernhard1, Egor Dolzhenko2and
Laura F. Landweber1,*
1Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, 08542, USA and
2Department of Mathematics, University of South Florida, Tampa, FL, 33620, USA
Received August 15, 2012; Revised October 18, 2012; Accepted October 31, 2012
Organisms represented by the root of the universal
evolutionary tree were most likely complex cells
with a sophisticated protein translation system and
a DNA genome encoding hundreds of genes. The
growth of bioinformatics data from taxonomically
diverse organisms has made it possible to infer
the likely properties of early life in greater detail.
Here we present LUCApedia, (http://eeb.princeton.
edu/lucapedia), a unified framework for simultan-
eously evaluating multiple data sets related to the
Last Universal Common Ancestor (LUCA) and its
mapping eleven such data sets onto UniProt,
KEGG and BioCyc IDs. LUCApedia may be used to
rapidly acquire evidence that a certain gene or set of
genes is ancient, to examine the early evolution of
metabolic pathways, or to test specific hypotheses
related to ancient life by corroborating them against
the rest of the database.
All known life shares an ancestor at the root of the uni-
versal phylogenetic tree (1,2). This Last Universal
Common Ancestor (LUCA) is a construct that may rep-
resent a single organism (1) or may represent populations
of organisms capable of sharing large amounts of genetic
information through horizontal gene transfer (3,4). Either
way, organisms at the time of LUCA possessed many of
the fundamental features present in modern organisms
and likely exhibited a level of sophistication comparable
with modern Bacteria or Archaea (5). Over the last
decade, a number of studies have used bioinformatics
databases to characterize the minimal set of features
present in LUCA. The subjects of these surveys include
gene families, protein architectures, protein domains and
motifs and enzymatic functions.
Most of these studies identify a minimal set of hundreds
of traits present in LUCA, which also most likely had a
DNA genome, a cell membrane and a complete translation
system. This complexity implies that a significant amount
of evolutionary change must have taken place between the
first life forms and LUCA. Multiple lines of evidence
suggest that the earliest genetically encoded metabolism
was produced by an RNA-only system in which RNA
genes encoded ribozyme catalysts (6). Still more evidence
suggests that protein translation arose from this RNA-only
system (7,8) and that the DNA genome subsequently arose
from the RNA-protein system, possibly just prior to the
divergence of LUCA into the three domains of life (9,10).
The capacity of an RNA-only system to support life has
been studied by surveying the roles of naturally occurring
ribozymes and synthesizing new ribozymes in vitro that
have functions relevant to early life (11).
Non-genetically encoded catalysts, such as metal ions
(12) or mineral surfaces (13,14) may also have played an
important role in the production of large biomolecules
both before and during the RNA-only era. Modern
enzymes often use both organic and inorganic cofactors
to impart catalysis. Some inorganic cofactors might reflect
a pre-protein stage in which the reactions were catalysed
by analogousions and
nucleotide-derived cofactors may reflect a ribozyme pre-
cursor to modern protein enzymes that catalysed an
Here we describe LUCApedia, which integrates these
three lines of research into a unified framework provided
by several well-established repositories of protein data.
Users may query the database web server for a single
protein in order to collect evidence of its antiquity from
a broad range of studies. Downloadable database files
may be used to evaluate the earliest components of
modern pathways and to compare the antiquity of
similar pathways to one another in an automated
fashion. Users may also test the accuracy of previous
studies and hypotheses implemented in the database by
corroborating one of its data sets against the rest.
*To whom correspondence should be addressed. Tel: +1 609 258 6724; Fax: +1 609 258 1712; Email: firstname.lastname@example.org
Correspondence may also be addressed to Laura F. Landweber. Tel: +1 609 258 1947; Fax: +1 609 258 1682; Email: email@example.com
Published online 27 November 2012 Nucleic Acids Research, 2013, Vol. 41, Database issueD1079–D1082
? The Author(s) 2012. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/3.0/), which
permits non-commercial reuse, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact
OVERVIEW OF THE DATABASE
The central objective of the LUCApedia database is to
integrate disparate data sets related to ancient life. Entry
IDs from UniProt (16), BioCyc (17) and the Kyoto
Encyclopedia of Genes and Genomes (KEGG) (18)
supply the underlying framework. Uniprot was chosen
because it captures a broad array of proteins and their
relevant annotations. The Uniprot-based version of the
database is appropriate for users wishing to examine the
antiquity of a single protein, protein family or functional
category. KEGG and BioCyc were used as alternative
frameworks in order to facilitate studies of metabolic
pathways. LUCApedia only stores Uniprot, KEGG and
BioCyc identifiers, which are subsequently linked to early
life data sets described below. Methods for mapping these
data sets onto the three underlying databases are
illustrated in Figure 1 and described in detail in the docu-
mentation available for download on the web server.
Six of the early life data sets are derived from studies in
which features of LUCA were inferred by surveying a
taxonomically broad range of organisms for universal
‘Harris et al. (19)’. The COG database (20) was used to
distributed and have a similar phylogenetic pattern
to ribosomal RNAs.
that are universally
‘Mirkin et al. (21)’. The COG database was used to
generate models of gene gain and loss as well as hori-
zontal gene transfer. The model corresponding to a
gain penalty of one was used to reconstruct a LUCA
gene set of 571 families.
‘Delaye et al. (22)’. All-against-all BLAST (23) searches
were performed in both directions between the genomes
of 20 taxonomically diverse organisms. The resulting
common Pfam (24) domains were identified.
‘Yang et al. (25)’. A phylogeny of 174 taxonomically
diverse organisms was produced using a quantitative
classification system based on protein domain content.
The method identified
superfamilies (defined by SCOP) (26).
‘Wang et al. (27)’. A phylogeny of protein folds (defined
by SCOP) was generated using a quantitative classifi-
cation system based on genomic surveys, and a
branch on the resulting phylogeny was identified that
represents the divergence of LUCA into the three
taxonomic domains. The 165 deeper branching pro-
tein folds were predicted to have been present in
‘Srinivasan and Morowitz (28)’. Metabolic pathways
bacteria and one chemoautotrophic archaean were
compared, and 286 common reactions were identified.
Figure 1. An overview of methods used to map the eleven early life data sets onto the underlying database framework of Uniprot, KEGG and
Biocyc IDs. Initial data sets extracted either from previous studies or generated by the authors are highlighted in blue. Line thickness corresponds
directly to the number of files at each methodological step. A complete description of ID mapping for each data set can be found in the LUCApedia
documentation available for download from the web server.
D1080Nucleic AcidsResearch, 2013,Vol. 41,Database issue
Five other early life data sets are original to this
database and pertain to published hypotheses regarding
the origin and early evolution of life:
‘Ribozyme functional analogs’. The RNA world hypoth-
esis (6) predicts that most essential enzyme functions
were performed by ribozymes prior to the establish-
ment of protein translation. Thirty-three in vivo and
in vitro ribozyme functions were collated through lit-
‘Nucleotide cofactor usage’. Enzyme functions requiring
nucleotide-derived cofactors may reflect a transition
from an RNA-only system to a system of RNA and
protein enzymes (29). Cofactors derived from nucleo-
tides were identified through literature review from
the complete pool of cofactors used in Uniprot
‘Amino acid cofactor usage’. Amino acid cofactors may
have played an early role in the transition out of an
RNA-only system, initiating the transition to protein
enzymes (30). Cofactors derived from amino acids
were identified as above.
‘Iron–sulfur cofactor usage’. Iron–sulfur cofactors have
been proposed to reflect an important early role of
iron–sulfur mineral surfaces in producing small mol-
ecules and facilitating polymerization (14). Cofactors
containing iron–sulfur clusters
‘Zinc cofactor usage’. Zinc cofactors have been proposed
to reflect an important early role of zinc ions in nucleic
acid chemistry and energy production (31). Zinc cofac-
tors were identified as above.
THE LUCAPEDIA WEB SERVER
The web server is designed for users interested in quickly
collecting evidence of deep ancestry for a small number of
protein families. Proteins can be searched by name or
Uniprot ID (Figure 2). A single name may correspond
to multiple Uniprot IDs representing orthologs of the
same protein in different species. A single Uniprot ID
may also correspond to multiple names that are directly
synonymous with one another. Proteins can also be found
Figure 2. A screen shot of the LUCApedia web server search function. Protein names can be entered into the search field and the search will return
all corresponding Uniprot IDs along with evidence of their relevance to ancient life. Searches may be conducted for either exact or partial protein
names. If a name search does not return any results, Uniprot IDs may also be directly queried.
Nucleic Acids Research, 2013,Vol. 41,Database issueD1081
by way of the ‘Browse’ page, where they are listed by name
in alphabetical order. The ‘About’ page features an
abridged documentation explaining the core organization
of the database and a description of each data set. More
advanced users interested in performing detailed analysis
may use the ‘Download’ page to acquire flat text files of
each data set mapped to Uniprot, KEGG and Biocyc IDs,
as well as the complete database documentation and
MySQL dumps of the tables used to serve the database
and to implement the web server’s search function.
Inferring likely characteristics of early life forms with any
statistical confidence prior to and during the stage of the
last universal common ancestor has only recently become
a tractable problem. Even so, it is usually not possible to
prove the conclusions of studies in this discipline. In lieu
of definitive proof, an understanding of ancient life can be
built from the consensus of diverse and independent
methods. LUCApedia creates an unprecedented ability
to corroborate the results from independent studies, to
evaluate early life hypotheses, and to direct future experi-
ments toward understudied areas, all in an objective,
quantitative and systematic manner.
The authors thank the members of the Landweber lab for
useful comments and for help testing the web server. The
authors also thank John Baross and Ram Samudrala for
early discussions of the LUCApedia concept.
NASA postdoctoral fellowship (to A.D.G.); National
Science Foundation (NSF) [0900544 to L.F.L]. Funding
for open access charge: NSF .
Conflict of interest statement. None declared.
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