(PDF) Experimental Determination and System Level Analysis of Essential Genes in Escherichia coli MG1655 (2003) | Svetlana Gerdes | 826 Citations
Experimental Determination and System Level Analysis of Essential Genes in Escherichia coli MG1655
Svetlana Gerdes, Michael D. Scholle, James W. Campbell, Gábor Balázsi, Erzsébet Ravasz, Matthew D. Daugherty, A. L. Somera, Nikos C. Kyrpides, Iain Anderson, Mikhail S. Gelfand, A. Bhattacharya, Vinayak Kapatral, Mark D'Souza, Mark V. Baev, Yuri Grechkin, Faika Mseeh, Michael Fonstein, Ross Overbeek, Albert-László Barabási, Zoltán N. Oltvai, Andrei L. Osterman +20 moreNorthwestern University, University of Notre Dame
- 01 Oct2003
- Vol. 185, Iss: 19, pp 5673-5684
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TL;DR: A genetic footprinting technique is used for a genome-wide assessment of genes required for robust aerobic growth of Escherichia coli in rich media to identify 620 genes as essential and 3,126 genes as dispensable for growth under these conditions.
Abstract: Defining the gene products that play an essential role in an organism's functional repertoire is vital to understanding the system level organization of living cells. We used a genetic footprinting technique for a genome-wide assessment of genes required for robust aerobic growth of Escherichia coli in rich media. We identified 620 genes as essential and 3,126 genes as dispensable for growth under these conditions. Functional context analysis of these data allows individual functional assignments to be refined. Evolutionary context analysis demonstrates a significant tendency of essential E. coli genes to be preserved throughout the bacterial kingdom. Projection of these data over metabolic subsystems reveals topologic modules with essential and evolutionarily preserved enzymes with reduced capacity for error tolerance.
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JOURNAL OFBACTERIOLOGY, Oct. 2003, p. 5673–5684Vol. 185, No. 19
0021-9193/03/$08.000DOI: 10.1128/JB.185.19.5673–5684.2003
Copyright © 2003, American Society for Microbiology. All Rights Reserved.
Experimental Determination and System Level Analysis of Essential
Genes inEscherichia coliMG1655
S. Y. Gerdes,1M. D. Scholle,1J. W. Campbell,1G. Bala ́zsi,2E. Ravasz,3M. D. Daugherty,1
A. L. Somera,2N. C. Kyrpides,1I. Anderson,1M. S. Gelfand,1A. Bhattacharya,1
V. Kapatral,1M. D’Souza,1M. V. Baev,1Y. Grechkin,1F. Mseeh,1
M. Y. Fonstein,1R. Overbeek,1A.-L. Baraba ́si,3Z. N. Oltvai,2*
and A. L. Osterman1*
Integrated Genomics, Inc., Chicago, Illinois 606121; Department of Pathology, Northwestern University, Chicago,
Illinois 606112; and Department of Physics, University of Notre Dame, Notre Dame, Indiana 465563
Received 26 March 2003/Accepted 14 July 2003
Defining the gene products that play an essential role in an organism’s functional repertoire is vital to
understanding the system level organization of living cells. We used a genetic footprinting technique for a
genome-wide assessment of genes required for robust aerobic growth ofEscherichia coliin rich media. We
identified 620 genes as essential and 3,126 genes as dispensable for growth under these conditions. Functional
context analysis of these data allows individual functional assignments to be refined. Evolutionary context
analysis demonstrates a significant tendency of essentialE. coligenes to be preserved throughout the bacterial
kingdom. Projection of these data over metabolic subsystems reveals topologic modules with essential and
evolutionarily preserved enzymes with reduced capacity for error tolerance.
Sequencing and comparative analysis of multiple diverse
genomes is revolutionizing contemporary biology by providing
a framework for interpreting and predicting the physiologic
properties of an organism. A variety of emerging postgenomic
techniques such as genome-wide expression profiling and mon-
itoring of macromolecular complex formation can reveal the
detailed molecular compositions of cells. New computational
approaches to exploring the inherent organization of cellular
networks, the mode and dynamics of interactions among cel-
lular constituents, are in early stages of development (14, 22,
23). These techniques allow us to begin unraveling a major
paradigm of cellular biology: how biological properties arise
from the large number of components making up an individual
cell.
Defining which gene products play an essential role and
under what conditions is vital to understanding the complexity
of living organisms. Although methods to rapidly and system-
atically determine genome-wide gene essentiality are less ad-
vanced than other functional genomic techniques, a number of
essentiality surveys involving different species have been re-
ported. Many experimental approaches have been used to pro-
duce such data, including individual knockouts inSaccharomy-
ces cerevisiae(10, 38),Caenorhabditis elegans(21), and recently
B. subtilis(22a), RNA interference inC. elegans(20), and
whole-genome transposon mutagenesis studies with several
microorganisms. In the latter group, complete or extensive lists
of essential and dispensable genes are available forMyco-
plasma pneumoniaeandMycoplasma genitalium(15),Mycobac-
terium tuberculosis(31),Haemophilus influenzae(1), andS.
cerevisiae(30). However, as of yet relatively little effort has
been committed to a system level interpretation of these data
in terms of cellular function or evolutionary relationships with
other organisms (19).
Escherichia colihas historically been the focus of intense
biochemical, genetic, and physiologic scrutiny, but genomic
essentiality data for this organism have remained incomplete.
Systematic efforts to compile genome-wide collections ofE.
colideletion mutants are under way. Two groups have reported
Tn10transposon-based genetic footprinting projects withE.
coli, but essentiality data were revealed only for a limited set of
genes (3, 13). Currently, the Profiling ofE. coliChromosome
database (available at http://www.shigen.nig.ac.jp/ecoli/pec) is
the most complete list of essential and dispensable genes inE.
coli. This list is not based on direct experimental evidence but
is derived from systematic review of the experimental litera-
ture. Although this compilation is of great value, the wide
variety of strains, conditions, and types of mutations used in
individual studies significantly complicates interpretation.
Here we report a genome-wide, comprehensive experimen-
tal assessment of theE. coliMG1655 genes necessary for
robust aerobic growth in a rich, tryptone-based medium. Of
the 4,291 protein-encoding genes inE. coli, we assessed the
essentiality of 3,746 genes (87% of the total). Individual
assessments were projected onto a whole-cell functional recon-
struction model including both metabolic and nonmetabolic
systems. Distribution of conditionally essential and dispensable
E. coligenes within functional systems was analyzed with re-
spect to the occurrence of putative orthologs across a broad
range of diverse bacterial genomes. This analysis demonstrates
a significant tendency of experimentally identified essentialE.
coligenes to be evolutionarily preserved throughout the bac-
\* Corresponding author. Mailing address for Z. N. Oltvai: Depart-
ment of Pathology, Northwestern University, 303 E. Chicago Ave.,
Chicago, IL 60611. Phone: (312) 503-1175. Fax: (312) 503-8240. E-mail:
zno008@northwestern.edu. Present address for A. L. Osterman: The
Burnham Institute, 10901 North Torrey Pines Rd., La Jolla, CA 92037.
Phone: (858) 646-3100. Fax: (858) 646-3171. E-mail: osterman@burnham
.org.
5673
terial kingdom, especially a subset of genes representing key
cellular processes such as DNA replication and protein syn-
thesis. Finally, we analyzed the conditional essentiality of met-
abolic enzymes from the perspective of cellular system level
organization, demonstrating enrichment with those enzymes
that catalyze reactions within evolutionarily conserved topo-
logic modules in the complex metabolic web ofE. coli.
MATERIALS AND METHODS
Transposon mutagenesis.E. colistrain MG1655 (FilvG rfb-50 rph-1) (16)
was used throughout this work. Genetic footprinting with the use of the plasmid
pMODMCScontaining the artificial transposon EZ::TNKAN-2(Epicen-
tre Technologies, Madison, Wis.) and identification of chromosomal insertion
sites were previously described (9) and are detailed in the supplementary data
(supplementary data for this paper are available at http://www.integratedgenomics
.com/online_material/gerdes and on the University of Notre Dame and North-
westernUniversitywebsites[http://www.umsl.edu/balazsi/JBact2003/and\
http://www.oltvailab.northwestern.edu/Pubs/JBact2003/\]). Cells were grown in an
enriched Luria-Bertani (LB) medium composed of 10 g of tryptone/liter, 5 g of
yeast extract/liter, 50 mM NaCl, 9.5 mM NH4Cl, 0.528 mM MgCl2, 0.276 mM
K2SO4, 0.01 mM FeSO4, 5104mM CaCl2, and 1.32 mM K2HPO4. The
growth medium also included the following micronutrients: 3106mM
(NH4)6(MoO7)24, 4104mM H3BO3, 3105mM CoCl2, 105mM CuSO4,
8105mM MnCl2, and 105mM ZnSO4. The following vitamins were added
(concentrations are in milligrams per liter): biotin, 0.12; riboflavin, 0.8; panto-
thenic acid, 10.8; niacinamide, 12.0; pyridoxine, 2.8; thiamine, 4.0; lipoic acid, 2.0;
folic acid, 0.08; andp-aminobenzoic acid, 1.37. Kanamycin was added to 10
g/ml.
As with any high-throughput technique, genetic footprinting is subject to a
certain degree of experimental and analytical error. A variety of validation
techniques indicate the overall error rate of our assignments to be well within
10% (9). The actual experimental detection and insert mapping error rate is
much lower (within 1 to 2%). The major source of ambiguity is associated with
data interpretation (see below). In the supplementary data, we include the insert
distribution within each open reading frame (ORF) (raw data, including insert
distribution within intergenic regions, are available upon request).
Statistical analyses of transposon insertion frequency.Essential and ambig-
uous ORFs introduce a bias into the density of transposon insertions due to the
fact that they“lose”the insertions incorporated within them during selective
outgrowth. There were also unmapped genomic regions where transposon inser-
tions could not be detected. To reconstruct insert distribution prior to selective
outgrowth, and to account for the contribution of unmapped regions, we re-
moved from theE. colichromosomal map every ORF with a function asserted to
be essential, ambiguous, or not determined, as well as the regions not covered by
the mapping process, and joined together the rest of the chromosome. We
analyzed the original and corrected insertion location data assuming that the
insertions appear as a result of a Poisson process with an overall raterof
3.218/kb. Based on this hypothesis, the probability tofindMinsertions within a
DNA region of lengthLis given by
PMLrLM
M!erL
ThePvalues corresponding to this hypothesis for the corrected data were
calculated to estimate the statistical significance of the deviations from a Poisson
process, for a threshold ofPof 105(see Fig. 1).
If the insertion locations are approximated by a Poisson process, the statistical
reliability of essentiality calls depends on two factors: the overall insertion den-
sityrin the region where the ORF is located and the lengthLof the ORF. More
specifically, the probability that an ORF is missed by chance is given as follows:
P0(L)erL, whereris the corrected density of insertions in the 10-kb region
centered on the ORF on the chromosome. For example, to assure that the
probabilityP0that no transposon insertion is detected in the given gene by
chance alone is0.5, we need the following:rLlog(2)0.639. In our case,
604 of the 620 genes asserted to be essential satisfy this condition withrLof
0.639, indicating that97% of all essential genes have a reliability of essen-
tiality calls expressed by aP0of0.5. The number of essential genes withP0
smaller than afixed value is given in Table 1. A detailed list for each gene is
presented in the supplementary data (see Table S1).
Identification of putative orthologs ofE. coligenes in diverse set of microbial
genomes.Putative orthologs ofE. coligenes were identified by using the ERGO
database (http://ergo.integratedgenomics.com/ERGO/) (26). Protein families in
ERGO correspond to homologous ORFs with identical assigned functions (24).
With each update of the database, grouping of proteins into families is refigured
through a multistep process including (i) formation of a family core from pro-
teins corresponding to several ORFs that are bidirectional best FASTA hits for
one another in their respective genomes, (ii) family extension by adding proteins
with identical assigned functions and by performing FASTA searches (27) and
adding matches with expectation values of less than a preset threshold, as de-
scribed earlier (12), and (iii) refinement of a family grouping based on multiple
ClustalW alignments (36) of all included sequences. To identify putative or-
thologs ofE. coliproteins, all protein families in ERGO were automatically
queried for the simultaneous presence of a protein(s) corresponding to anE. coli
ORF(s) and proteins corresponding to ORFs from the genomes of 32 diverse
bacterial species (Agrobacterium tumefaciens,Anabaenasp.,Aquifex aeolicus,
Bacillus subtilis,Borrelia burgdorferi,Brucella melitensis,Buchnerasp.,Campy-
lobacter jejuni,Caulobacter crescentus,Chlamydia trachomatis,Clostridium aceto-
butylicum,Corynebacterium glutamicum,Deinococcus radiodurans,Fusobacterium
nucleatum,Haemophilus influenzae,Helicobacter pylori,Listeria monocytogenes,
Mesorhizobium loti,Mycobacterium tuberculosis,Mycoplasma pneumoniae,Neis-
seria gonorrhoeae,Pseudomonas aeruginosa,Ralstonia solanacearum,Rickettsia
prowazekii,Sinorhizobium meliloti,Staphylococcus aureus,Streptococcus pneu-
moniae,Synechocystissp.,Thermotoga maritima,Treponema pallidum,Vibrio
cholerae, andXylella fastidiosa). Results of this search were further supplemented
by addition of ORFs from each of these genomes that are bidirectional best
FASTA hits with correspondingE. coligenes.
Densities of essential genes and evolutionary retention indexes (ERIs) along
the chromosome.The densities of essential genes along theE. colichromosome
(see Fig. 1B) were calculated within overlapping 100-kb regions displaced 1 kb
from one another. For each 100-kb region, the essentiality was defined as the
ratio of the number of essential genes to the total number of genes found in the
region (NE/NT). The significance of essentiality for each 100-kb region was
determined based on the hypergeometric distribution. Given that 620 of 4,291E.
coligenes were found to be essential, the probability of havingNEessential genes
out of a total number ofNTgenes within a 100-kb region is given by
P
620
NE 3,671
NTNE
4,291
NT
wherea
bdenotes the number of ways to choosebout ofaelements.
We determined the ERI for each of the 4,291E. coliORFs by calculating the
fraction of genomes in the group that have an ortholog of the given ORF, with
the number of representative organisms (NO) equal to 33. Thus, if the number of
organisms that contain an ortholog of theE. coliORF isNC, the ERI is given by
the following formula: ERINC/NO. The ERIs along theE. colichromosome
were calculated within overlapping 100-kb chromosomal regions, displaced 1 kb
from one another (see Fig. 1C). The ERI of each 100-kb region was determined
by calculating the average of the ERIs for all ORFs located completely inside the
region.
Data analysis within the context of system level metabolic organization.Using
the information about theE. colienzymes for all metabolic reactions available in
the ERGO database, together with the essentiality data for the corresponding
genes, we analyzed the correlation of enzyme essentialities within the known
hierarchical structure of theE. colimetabolic organization. We have previously
established a global topologic representation of theE. colimetabolic network, in
which each branch on the hierarchical tree corresponds to a group of metabolites
that are at its endpoints. Thus, each junction represents the module made up of
the substrates that were clustered together up to that stage (28). For each branch,
we can define an essentiality ratio based on the metabolic reactions present
among the group of metabolites it represents.
To treat each reaction equally, we considered all links present between any two
metabolites in the group, and for each of these links we took into account all the
reactions that created the link. Specifically, for all pairs in the group, we included
those metabolic reactions that transformed one of the substrates into another,
according to a reaction list in which generic donor and acceptor moieties, such as
H2O and ATP, are not considered (see reference 28 for details) and to which an
unambiguous insertion phenotype has been assigned (NRall). Next, we counted
those reactions whose corresponding catalytic enzymes proved to be essential
(NRlethal). Note that since the hierarchical tree is constructed according to a
two-step network complexity reduction procedure (28), there can be arcs be-
tween pairs of substrates that the tally does not include. To account for these, we
5674GERDES ET AL.J. BACTERIOL.
examined each metabolic reaction with a known catalytic enzyme insertion phe-
notype on these internal arcs and incorporated them into the analysis. The
essentiality of the branch (or module) is given by the fraction NRlethal/NRalland
represents the fraction of essential enzymes of all biochemical reactions within a
given metabolic module (branch). For additional details, see the supplementary
data.
RESULTS
Genome-scale genetic footprinting inE. coli.Genetic foot-
printing wasfirst introduced for analysis of gene essentiality in
S. cerevisiae(33). A modification of this technique using a
Tn5-based in vitro transposome system (11) inE. coliwas
previously described, and gene essentiality within three cofac-
tor biosynthetic pathways has been analyzed (9). Here we have
extended this pilot analysis to the whole-genome level by using
the same standardized growth conditions. The general exper-
imentalschemeisillustratedinthesupplementarydata.
Briefly, following transposon mutagenesis, a population of2
105independent mutants was grown aerobically for 23 dou-
blings in enriched LB medium supplemented with kanamycin.
Genomic DNA was isolated from the whole population and
used to map individual transposon inserts with a nested PCR
approach.
Distribution of the 1.8104distinct insert locations de-
tected along theE. colichromosome is illustrated in Fig. 1A.
FIG. 1. Distribution of transposon insertion densities, densities of essential genes, and ERIs along theE. colichromosome. (A) Gray lines show
the transposon insertion densities calculated as the number of transposition events per 100-kb sliding window over the entireE. coliMG1655
chromosome. Values indicated by the blue lines were computed in a similar manner, except that all chromosomal regions corresponding to
essential and ambiguous genes were excluded from the calculations in order to reconstruct insert distribution prior to selective outgrowth (see also
Materials and Methods). Gaps in the data (chromosomal regions where transposition events could not be detected due to technical reasons) are
indicated by short vertical lines along thexaxis. These regions were excluded from all analyses. Nucleotide positions of theE. coligenome sequence
correspond to those in reference 4. The regions where the distributions of transposition events significantly deviate (P0.01) from a Poisson
process are marked by horizontal green lines.oriCshows the origin of chromosomal replication, anddifdenotes thediflocus within the replication
termination area. (B) Distribution of essential genes along theE. colichromosome, defined as a percentage of essential genes in the total number
of genes within a 100-kb-long chromosomal region (calculated per sliding window as described above). The regions where the numbers of essential
genes significantly deviate (P0.01) from values that could arise by chance are marked by horizontal green lines. (C) ERIs along theE. coli
chromosome, defined as the average ERI for all genes within each 100-kb region. The ERI for a gene is defined as the fraction of organisms in
a diverse set of 33 bacterial species which contain an ortholog of the gene in their genomes.
TABLE 1. Number of essential genes withP0smaller than a
fixed value
P0
No. of
essential genes
% of
essential genes
0.0115926
0.0528145
0.136759
0.247677
0.355089
0.458795
0.560497
0.661098
VOL. 185, 2003GENETIC FOOTPRINTING INESCHERICHIA COLI5675
The densities of transposon insertion events are randomly dis-
tributed, with two notable exceptions: an overall maximum
around the origin of replication (oriC) and a minimum around
the terminus (dif). This may reflect increased target copy num-
ber at the origin of replication in the actively dividing bacterial
population used in this experiment. The overall insertion den-
sity is 3.218/kb, without appreciable variation between coding
(3.221/kb) and noncoding (3.193/kb) regions.
Assessment of conditional gene essentiality based on genetic
footprinting data.Unambiguous essentiality assessments were
made for 3,746 (or 87% of the total)E. coliprotein-encoding
genes or ORFs (Table 2). Of these, 620 (14%) were asserted to
be essential, and 3,126 (73%) were asserted to be nonessential
(dispensable) based on the occurrence of transposon inserts
within each ORF and the overall insertion density in the local
environment, as described in the supplementary data. The
complete essentiality list is reported in the supplementary data
(see Table S1). No assertions could be made for 327 genes for
technical reasons, such as limited efficiency of PCRs in certain
regions of theE. colichromosome or nonspecific primer an-
nealing in areas of DNA repeats. For 218 genes, we considered
the evidence to be insufficient for a specific conclusion about
essentiality. These genes were systematically called ambiguous,
according to the criteria listed in the supplementary data. For
example, ORFs shorter than 240 bp (80 aa) and with no
inserts were consistently classified as ambiguous rather than
essential. In certain cases, relatively long ORFs (900 bp)
containing only a single transposon were designated ambigu-
ous rather than nonessential.
Our results are generally consistent with previously pub-
lished data on individual genes and with data from currently
available collections of systematic gene deletions inE. coli. For
example, of the 1,379 individual gene deletion mutants listed at
the University of WisconsinE. coliGenome Project website
(http://www.genome.wisc.edu/functional/tnmutagenesis.htm),
only 12% produced apparently conflicting designations of
genes as essential (for a detailed list of the discrepancies, see
Table S2 in the supplementary data). Although we have not
attempted to reconcile each individual case, several reasons for
discrepancies can be envisioned. Most importantly, the term
essential, which intuitively suggests an absolute requirement
for cell viability, also applies to any gene that imparts a sub-
stantialfitness advantage. Thus, mutants lacking gene products
necessary for maintaining vigorous growth fall into the same
category as those with“true lethal”mutations. Therefore, cer-
tain genes may be classified as essential by genetic footprinting,
yet corresponding viable deletion mutants may be obtained. In
addition, differences in medium compositions, aeration levels,
temperatures, and cell densities may account for many incon-
sistencies. Surprisingly, polar effects, in which transposon in-
sertion into dispensable genes disrupts transcription of essen-
tial genes, are relatively rare in genetic footprinting. This may
be due to the presence of weakly active promoter-like se-
quences within the transposon used in these experiments (9,
11). Most examples of polar effects are associated with genes
that may require high levels of expression to sustain rapid
growth rates.
Discrepancies resulting from inserts detected in the genes
otherwise considered to be essential also occur. In some cases,
single inserts occur close to protein termini or in interdomain
boundary regions in multidomain proteins. For proteins con-
sisting of two or more independently functioning domains,
inserts may be tolerated within the 3portion of the gene if the
C-terminal domain of the protein it encodes is associated with
a dispensable function. This can occur even when a function
associated with the N-terminal domain (from the 5region of
the gene) is genuinely essential (as withftsX[9]). Small, local-
ized chromosomal duplications may account for inserts in
genes otherwise recognized as essential (2). In this scenario,
one copy of a duplicated gene provides the essential function
while the other copy containing the transposon is stabilized by
selection for kanamycin resistance. Large genes with only a
small number of inserts may fall into this category since the
TABLE 2. Distribution of essential and nonessential genes and average ERIs in selected functional categoriesa
Functional
categoryDescriptionTotal no. of
ORFsNo. ENo. NNo. ?No. ND% EMean ERI
AAMAmino acid metabolism1382110818150.5
CHMCarbohydrate metabolism21921178317100.4
NCMNucleotide and cofactor metabolism1815311927290.5
LPCLipid, lipopolysaccharide, lipoprotein, peptidoglycan,
and cell wall biosynthesis
1263473514270.5
NAMNucleic acid metabolism1564396512280.6
PMSProtein metabolism and secretion16780571812480.7
MSMMiscellaneous metabolism94147226150.4
BENBioenergetics100157546150.3
SMCSignaling, motility, and chemotaxis1531212531380.3
RCDExpression regulation and cell cycle and division177301181316170.2
MTRMembrane transport276222443780.3
PHTPhage- and transposase-related processes621235213190.3
CATAll categorized1,8493571,30061131190.4
UNCUncategorized2,4422631,826157196110.2
TotalCategorized and uncategorized4,2916203,126218327140.3
aAbbreviations are as follows: E, essential; N, nonessential; ND, not determined; ?, ambiguous.
5676GERDES ET AL.J. BACTERIOL.
total number of specific duplications within the population
prior to transformation is probably very small (25).
Functional context analyses of essentiality data.The inter-
pretation of genomic essentiality data can be approached in a
number of alternate ways, such as by using chromosomal (po-
sitional), functional (system level), or phylogenetic (evolution-
ary) context analysis. In addition to refining initial essentiality
assignments and reconciling apparent discrepancies with exist-
ing knowledge, such analyses can improve and expand existing
understanding of the systemic behavior of the cell at various
levels. Without attempting a comprehensive analysis, we have
limited the scope of our efforts to (i) prototyping and illustrat-
ing such analysis by using selected examples from various func-
tional systems, (ii) evaluating the internal consistency of our
data, and (iii) developing preliminary observations at the sys-
tem level, as presented below.
Initially, we analyzed the data in a functional context, which
involved dividing the overall physiology of the organism into
smaller, internally coherent subsystems such as amino acid
biosynthesis, nucleotide metabolism, and other broad func-
tional categories (Table 2). This approach mirrors the standard
didactic subdivision of microbial biochemistry and physiology.
It also provides an organizational framework with which to
analyze total genomic data and allows specific metabolic ques-
tions to be addressed.
For consistency, our functional analysis is based exclusively
on SWISS-PROT functional annotations (8). Each of the 1,849
gene products with specific SWISS-PROT annotations and
defined biochemical functions supported by solid experimental
evidence was placed into one of the 12 functional categories
(Table 2 and supplementary data [see Table S1]). Among the
remaining 2,242 uncategorized protein-encoding genes, many
have been tentatively annotated in SWISS-PROT and other
databases, but most of these annotations either fall short of
giving a specific testable function or have not been confirmed
by direct experiments. As expected, the ratios of essential
genes within various functional categories are rather uneven
(Table 2). Categories that include gene products involved with
key aspects of cellular metabolism (such as nucleic acid and
protein metabolism) contain a substantially higher percentage
of essential genes (28 and 48%, respectively) than the average
for the entire genome (14%). The percentages of essential
genes in categories such as signaling, motility, and chemotaxis
(8%) and membrane transport (8%) are substantially below
the whole-genome benchmark. The average essentiality for the
subset of 2,242 uncategorized genes (11%) is substantially
lower than the average for the subset of categorized genes
(19%). Several representative metabolic and nonmetabolic sys-
tems (7 of 12 functional categories) were selected for use as
examples of functional context analysis and for evaluation of
the internal consistency of the data. Here we describe one such
analysis, with additional detailed interpretations presented in
the supplementary data.
Amino acid metabolism: lysine biosynthesis.Most of the
genes responsible for biosynthesis of various amino acids were
expected to be nonessential since the medium contains most of
the amino acids required for growth. With a few notable ex-
ceptions, this expectation was confirmed by our results. Of the
91 genes with specific SWISS-PROT annotations indicating
involvement in amino acid biosynthesis, only 16 appear to be
essential (Fig. 2A). Six of these genes are involved in lysine
biosynthesis.E. coliproduces lysine from aspartate via the
nine-step pathway (Fig. 2B). Although lysine is available in the
growth medium, its immediate precursor, diaminopimelate
(DAP), which is required for cell wall biosynthesis, is not. The
lysAgene encoding the enzyme that converts DAP to lysine at
the last step of this pathway is dispensable. Analysis of DAP-
lysine biosynthesis provides an example of refining pathway
reconstruction and individual functional assignments based on
genome-scale essentiality data. Genes (asd,dapA,dapB,dapD,
dapE,anddapF)encodingmostoftheenzymesleading
to DAP production are essential. Thefirst gene in this path-
way (lysC), encoding aspartokinase III, is dispensable due to
the functional redundancy of the additional aspartokinase
isozymes (encoded bymetLandthrA). In contrast, theasdand
dapAgenes involved with the second and the third steps of
DAP-lysine biosynthesis are essential in spite of the existence
of apparent paralogs. Proteins encoded by theyjhHandyagE
functionally uncharacterized genes are often annotated as po-
tential dihydrodipicolinate synthases based on their high se-
quence similarities with thedapAgene product (BLAST E
scores of 4e33and 2e28, respectively). However, genetic
footprinting data suggest that under our experimental condi-
tions neither is capable of complementing loss of the essential
dapAfunction. The opposite situation is observed with succi-
nyl-DAP aminotransferase (encoded byargD), which isfirmly
defined as dispensable in our data. This apparent inconsistency
can be resolved by assuming functional complementation by
theargMgene product. TheargMgene is known to encode
succinyl-ornithine transaminase, which is primarily involved in
arginine biosynthesis. However, this enzyme is closely related
to succinyl-DAP aminotransferase by sequence, and the ami-
notransferases are known to possess rather broad substrate
specificities, especially for structurally similar substrates (such
as succinyl-DAP and succinyl-ornithine). Overexpression of
theargMgene has been demonstrated to suppress anargD
mutation inE. coli(32).
Phylogenetic analysis of essentiality data within functional
groups.To assess the data set from an evolutionary perspec-
tive, we examined the distribution of conditionally essential
and dispensableE. coligenes with respect to the occurrence of
putative orthologs across a broad range of diverse bacterial
genomes. Putative orthologs within a reference set of 32 com-
plete bacterial genomes chosen to represent maximum phylo-
genetic diversity were identified based on protein families,
supplemented by bidirectional best hits (see Materials and
Methods). For this analysis we introduce a simple parameter:
an ERI computed for eachE. coligene as the fraction of
genomes from the reference set containing a putative ortholog
of the gene. ERI values varying from 0 (for genes unique toE.
coli) to 1.0 (for omnipresent genes) are provided in the sup-
plementary data (see Table S1). In a recent study, the Profiling
ofE. coliChromosome data (http://www.shigen.nig.ac.jp/ecoli
/pec) were used to demonstrate a remarkable tendency of
essential gene sequences to be more evolutionarily conserved
than those of nonessential genes (19). In our analysis, we used
ERI values to focus on occurrence of essential and nonessen-
tial genes (preservation of orthologs) rather than on conserva-
tion of their respective sequences.
Figure 3A depicts the overall number ofE. coligenes in
VOL. 185, 2003GENETIC FOOTPRINTING INESCHERICHIA COLI5677
FIG. 2. Essentiality of genes controlling amino acid biosynthesis inE. coli. (A) Functional overview of amino acid biosynthesis. Each block
represents one or more pathways leading to production of a particular amino acid or its key intermediates (shown in smaller boxes). Within each
block, stacked bars represent the gene products involved in the pathway (according to SWISS-PROT release of June 2002). Bars are colored
according to gene essentiality (green, nonessential; red, essential; gray, undefined). (B) Detailed representation of the lysine biosynthetic pathway.
Genes predicted in the ERGO database to be paralogs in this pathway are shown, in addition to genes whose roles in the biosynthesis of lysine
have been experimentally verified (in bold).
5678GERDES ET AL.J. BACTERIOL.
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Julie D. Thompson, Desmond G. Higgins, Toby J. Gibson +2 more
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TL;DR: The sensitivity of the commonly used progressive multiple sequence alignment method has been greatly improved and modifications are incorporated into a new program, CLUSTAL W, which is freely available.
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Improved tools for biological sequence comparison.
William R. Pearson, David J. Lipman +1 moreUniversity of Virginia
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TL;DR: Three computer programs for comparisons of protein and DNA sequences can be used to search sequence data bases, evaluate similarity scores, and identify periodic structures based on local sequence similarity.
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•Journal Article• 10.1126/SCIENCE.277.5331.1453
The Complete Genome Sequence of Escherichia coli K-12
Frederick R. Blattner, Guy Plunkett, Craig A. Bloch, Nicole T. Perna, Valerie Burland, Monica Riley, Julio Collado-Vides, Jeremy D. Glasner, Christopher K. Rode, George F. Mayhew, Jason Gregor, Nelson Wayne Davis, Heather A. Kirkpatrick, Michael A. Goeden, Debra J. Rose, Bob Mau, Ying Shao +16 moreUniversity of Wisconsin-Madison
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TL;DR: The 4,639,221-base pair sequence of Escherichia coli K-12 is presented and reveals ubiquitous as well as narrowly distributed gene families; many families of similar genes within E. coli are also evident.
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Escherichia Coli and Salmonella: Typhimurium Cellular and Molecular Biology
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- 25 Jul2002
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TL;DR: It is shown that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment, and less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal Growth in four of the tested conditions.
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