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LETTER The Phylogenetic Extent of Metabolic Enzymes and PathwaysComputational Genomics Group, The European Bioinformatics Institute, EMBL Cambridge Outstation, Cambridge CB10 1SD, UK
The evolution of metabolic enzymes and pathways has been a subject of intense study for more than half a century. Yet, so far, previous studies have focused on a small number of enzyme families or biochemical pathways. Here, we examine the phylogenetic distribution of the full-known metabolic complement of Escherichia coli, using sequence comparison against taxa-specific databases. Half of the metabolic enzymes have homologs in all domains of life, representing families involved in some of the most fundamental cellular processes. We thus show for the first time and in a comprehensive way that metabolism is conserved at the enzyme level. In addition, our analysis suggests that despite the sequence conservation and the extensive phylogenetic distribution of metabolic enzymes, their groupings into biochemical pathways are much more variable than previously thought.
One of the fundamental tenets in molecular biology was expressed by Monod, in his famous phrase "What is true for Escherichia coli is true for the elephant" (Jacob 1988  ). For
a long time, this statement has inspired generations of molecular
biologists, who have used Bacteria as model organisms to understand the
basic principles of life. The discovery of the three domains of life
(Woese and Fox 1977) testified that there exist some pronounced
differences between organisms, for example in transcription regulation
(Struhl 1999). Paradoxically, metabolism has always been considered as
one of the most conserved cellular processes (Lehninger 1979), that
remains invariable from Bacteria to Eucarya, but no quantification of
this view has been provided.
Instead, the phylogenetic extent of metabolism has been assessed by
experimental case studies of individual biochemical pathways (Crawford
1989
A comprehensive analysis of metabolism has not been performed until
now, possibly due to the scarcity of systematically collected
information on genome sequences and metabolic pathways. Metabolic
enzyme families are considered to be highly conserved and have been
used to reconstruct the deep branching patterns of the tree of life
(Doolittle et al. 1996
We set out to address the phylogenetic extent and conservation of
enzymes and pathways by using a highly curated, reliable source of
metabolic information. The EcoCyc database holds information about the
full genome and all known metabolic pathways of Escherichia
coli (Karp et al. 2000
We have searched the nonredundant protein sequence database, previously partitioned in seven major taxonomic groups, with all 548 enzymes from the known metabolic complement of Escherichia coli. Whenever a homolog of each query enzyme is found in the corresponding taxonomic group, this is recorded into a binary vector (see Methods). Conceptually, this approach is similar to a low-resolution version of the phylogenetic profile method (Pellegrini et al. 1999 ). Instead of searching individual species, however, we
focus on major taxonomic groups and we seek enzymes that "travel
together" within or across these groups. No assumptions about
functional roles or associations are made (Pellegrini et al. 1999): We
only examine the phylogenetic extent of the query set, in this case the
entire known metabolic complement of E. coli. The end result
is a matrix of 548 genes across all the taxonomic combinations; in all,
37 (out of 128 possible) such combinations can be observed. Genes that
have the same distribution pattern (i.e., identical binary vectors) in
each taxonomic category are collected accordingly.
The majority of E. coli enzymes (274 of them, or 50%) have
homologs in all domains of life, Bacteria, Archaea, and Eucarya,
covering six taxonomic combinations (Fig.
1). Furthermore, there are an additional 13
enzymes (2%) which are universally present in all seven taxa,
including the viruses (Table 1). This
universal set represents enzyme families involved in various
biochemical processes, including amino acid, cofactor, and nucleotide
biosynthesis (Kyrpides et al. 1999
To assess whether the observed patterns of phylogenetic distribution for metabolic enzymes are different from any other proteins, we have performed simulations of this analysis using protein sets of equal size, randomly selected from the E. coli genome (see Methods). Because some of the eukaryotic taxa (e.g., Protista or Fungi) may be significantly underrepresented in terms of the amount of available sequence data, we have assessed the gross pattern of taxonomic distributions by combining all four eukaryotic taxa (Protista, Fungi, Plants, Metazoa) into one group. It is striking that the 71 Bacteria-specific enzymes are significantly underrepresented compared to the control set (with an average of 195 proteins that are Bacteria-specific; Fig. 2A). The 52 enzymes with homologs in Archaea but not Eucarya are slightly underrepresented (with an average of 63 proteins in the control sets for this taxonomic grouping; Fig. 2B). Finally, if we take enzymes with homologs in Archaea, Bacteria, all four eukaryotic taxa, and viruses (170 in total, or 31%), it is evident that this set of proteins stands out as being overrepresented in this universal taxonomic pattern compared with random (Fig. 2C). It is thus evident that randomly selected proteins from a bacterial genome tend to be confined within the corresponding taxonomic group, while metabolic enzymes are expected to be present across a much wider phylogenetic spectrum (Fig. 2). Enzymes with homologs in other taxonomic group combinations exhibit similarly strong deviations from a random background being either over- or underrepresented in the corresponding combination (Fig. 3).
To examine which enzymes are actually most conserved at the sequence level, we recorded all pairwise sequence identity values between the E. coli enzymes and their homologs from Homo sapiens (Table 2), as an indicative measure of protein sequence conservation. There are 11 E. coli metabolic enzymes which have similar lengths (±10%) and have sequence identity  55% to the corresponding human proteins (Table 2). The most
conserved known metabolic enzyme appears to be guanosine 5'
monophosphate oxidoreductase, with 68% identity shared between the
E. coli and H. sapiens sequences, followed by
glyceraldehyde 3-phosphate dehydrogenase and succinyl-CoA synthetase
 chain (Table 2). This is the first time, to our knowledge, that
such a simple comparison has been performed.
Finally, we have examined the conservation of pathways using the detection of enzyme homologs in the corresponding taxonomic partitions. Interestingly, only five of 87 pathways (less than 6%) whose enzymes have homologs in all seven taxa are completely conserved. In fact, these correspond only to short interconversion reactions defined as pathways (not shown). If we relax this strict criterion and admit enzymes with homologs in all three domains of life, that is, in any eukaryotic group, 23 pathways with more than four enzymes and 70% coverage are detected (Table 3). The three invariant pathways correspond to biosynthetic pathways for tryptophan, leucine, and arginine (Table 3). Other pathways in this list include metabolic reactions for cofactor biosynthesis and central metabolism (Table 3). In general, conserved pathways appear to be involved in energy metabolism, central intermediary metabolism, sugar degradation, cofactor biosynthesis, and the processing of amino acids and nucleotides. This observation lends support to the hypothesis that this set of processes is one of the most ancient aspects of cellular physiology, possibly present in the universal ancestor (Woese 1998 ).
In conclusion, it appears that although metabolic enzymes are widely distributed and highly conserved during evolution, their corresponding participation as groupings in pathways might vary significantly. In that sense, pathways appear to be more variable than previously thought, and pathway evolution exhibits a primarily "mosaic" pattern (Teichmann et al. 2001 ; Tsoka and Ouzounis 2001), with
homologous enzymes being reused in different cellular roles (Jensen
1976).
We have shown that the known metabolic complement of E. coli is highly conserved, with half of the enzymes being present in at least one species from the three domains of life, thus considered universal. With statistical simulations, we have also shown that the universal enzymes are much more conserved than the ones absent from Eucarya. The high coverage of the database and the presence of homologs in multiple species eliminates to a significant extent the possibility of detecting lateral gene transfers, also supported by recent, independent analyses (Salzberg et al. 2001 ; Stanhope et al. 2001).
Thus, the observed taxonomic patterns of enzyme distribution are most
likely to reflect genuine divergent relationships, tracing the origins
of metabolic enzymes and pathways back in time. In particular, the set
of universal enzymes may be used for deep phylogeny studies to assess
robustness of phylogenetic trees (Huelsenbeck et al. 2001), the
determination of divergence times (Feng et al. 1997), and hypotheses
for lateral gene transfer (Brown et al. 2001). Finally, we have
examined the conservation of biochemical pathways across species and
have found that the pathways in which the universal enzymes participate
correspond to reactions metabolizing small molecules, such as sugars,
amino acids, and nucleotides, as previously suggested (Kyrpides et al.
1999).
The topology and functional diversification of biochemical pathways is
yet to be explored, given that the experimentally determined
information available is confined to only a few model species, such as
E. coli, and processes, such as metabolism. It remains to be
seen how representative the metabolism of E. coli is and
whether our conclusions will hold for other species, or indeed for
other cellular processes. Much more work is necessary to validate the
metabolic reconstructions currently based on sequence homology (Tsoka
and Ouzounis 2000b
We have extracted the sequences of all enzymes (548 in total) from EcoCyc (Karp et al. 2000 ), both the monomeric enzymes (208 in total)
and the components of enzyme complexes (348 in total; some monomeric
enzymes can also be found as enzyme complex components; Tsoka and
Ouzounis 2000a). To address the generic phylogenetic distribution of
enzymes, we have subsequently divided the nonredundant protein sequence
database SwAll (SwissProt+TrEMBL; Bairoch and Apweiler 2000)—(602,333
entries in total) into seven major taxonomic groups: Archaea (A),
Bacteria (B), Fungi (F), Metazoa (M), Protista (P), Viridiplantae (Vp),
and Viruses (Vr). The section of the database containing these groups
covers 582,638 sequences or 97% of the total number of entries (the
3% remainder represents vector data, artificial sequences, insertion
sequences, transposons, and other unclassified entries). The
partitioning was greatly facilitated by SRS (Etzold and Argos 1993),
using the taxonomic records from the SwAll database (SwissProt+TrEMBL;
Bairoch and Apweiler 2000). All E. coli entries were excluded
from this target database.
The E. coli enzymes were subsequently used as queries to
search against the seven taxonomic partitions using BLAST (Altschul et
al. 1997
To assess the statistical significance of these measurements, 30
samples of equal size were taken from the E. coli genome as
control sets and were subjected to an identical analysis—as previously
described (Tsoka and Ouzounis 2000a
We thank Peter D. Karp (SRI International) for comments and members of the Computational Genomics Group for discussions. This work was supported by the European Molecular Biology Laboratory, the TMR Programme of the European Commission (DGXII—Science, Research and Development) and the Ministry of Science and Technology, Spain. S.T. acknowledges support from the UK Medical Research Council. C.A.O. thanks IBM Research for additional support. The publication costs of this article were defrayed in part by payment of page charges. This article must therefore be hereby marked "advertisement" in accordance with 18 USC section 1734 solely to indicate this fact.
1 Corresponding author.  E-MAIL ouzounis{at}ebi.ac.uk; FAX 44-1223-494471. Article and publication are at http://www.genome.org/cgi/doi/10.1101/gr.246903.
Received March 6, 2002; accepted in revised format December 11, 2002. 13:422-427 © by 2003 Cold Spring Harbor Laboratory Press ISSN 1088-9051/03 $5.00  CiteULike  Connotea  Del.icio.us  Digg  Reddit  Technorati What's this?
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ABSTRACT
RESULTS
