Strain-dependent diversity in the Pseudomonas
aeruginosa quorum-sensing regulon
Sudha Chugania, Byoung Sik Kimb, Somsak Phattarasukola, Mitchell. J. Brittnachera, Sang Ho Choib,
Caroline S. Harwooda, and E. Peter Greenberga,1
aDepartment of Microbiology, University of Washington, Seattle, WA 98195; andbDepartment of Agricultural Biotechnology, Seoul National University,
Seoul 151-921, South Korea
Contributed by E. Peter Greenberg, August 17, 2012 (sent for review May 21, 2012)
Quorum sensing allows bacteria to sense and respond to changes
in population density. Acyl-homoserine lactones serve as quorum-
sensing signals for many Proteobacteria, and acyl-homoserine
lactone signaling is known to control cooperative activities.
Quorum-controlled activities vary from one species to another.
Quorum-sensing controls a constellation of genes in the opportu-
nistic pathogen Pseudomonas aeruginosa, which thrives in a num-
ber of habitats ranging from soil and water to animal hosts. We
hypothesized that there would be significant variation in quorum-
sensing regulons among strains of P. aeruginosa isolated from
different habitats and that differences in the quorum-sensing reg-
ulons might reveal insights about the ecology of P. aeruginosa.
As a test of our hypothesis we used RNA-seq to identify quorum-
controlled genes in seven P. aeruginosa isolates of diverse origins.
Although our approach certainly overlooks some quorum-sensing–
regulated genes we found a shared set of genes, i.e., a core quo-
rum-controlled gene set, and we identified distinct, strain-variable
sets of quorum-controlled genes, i.e., accessory genes. Some quorum-
controlled genes in some strains were not present in the genomes
of other strains. We detected a correlation between traits encoded
by some genes in the strain-variable subsets of the quorum reg-
ulons and the ecology of the isolates. These findings indicate a role
for quorum sensing in extension of the range of habitats in which
a species can thrive. This study also provides a framework for un-
derstanding the molecular mechanisms by which quorum-sensing
systems operate, the evolutionary pressures by which they are
maintained, and their importance in disparate ecological contexts.
bacterial communication|systems biology|transcription control
other and control gene expression in a cell density-dependent
manner. Many species of Proteobacteria use diffusible acyl-homo-
serine lactones (AHLs) as quorum-sensing signals. AHLs are
produced by signal synthase enzymes and are detected by signal-
specific transcriptional regulators. AHL quorum-sensing circuits
regulate a wide spectrum of phenotypes in a diverse array of α-,
β-, and γ-Proteobacteria (1). Interspecies differences in quorum
regulons often are a reflection of the diverse habitats that bac-
teria occupy, and quorum-controlled phenotypes often play a
crucial role in niche persistence. The classic example is quorum
control of luminescence in Vibrio fischeri, which allows this bac-
terium to discriminate between its free-living, low-population-
density seawater habitat and its high-density symbiotic habitats,
the light organs of certain fish and squid (2, 3). It is well estab-
lished that there are species-specific differences in quorum reg-
ulons, but there is little information regarding the possibility
of intraspecies strain-specific differences. We hypothesized that,
particularly for versatile species that occupy diverse niches, there
might be a shared core of quorum-controlled genes and, in
addition, strain-variable quorum-regulated genes that reflect
adaptations to the habitats from which strains are isolated. We
tested our hypothesis using isolates of the metabolically versatile
γ-Proteobacteria species Pseudomonas aeruginosa.
acteria use quorum-sensing signals to communicate with each
P. aeruginosa has been isolated from diverse environments. It
can be found in soil and water, as a member of the normal
microbiota of eukaryotes or as an opportunistic pathogen in
a wide range of hosts including plants and humans. Comparative
genomic analyses of multiple P. aeruginosa strains have identified
core (shared) and accessory (strain-variable) genome sequences
(4). Evidence indicates that accessory genes encode functions as-
sociated with adaptation and niche diversification (4). P. aeruginosa
has a quorum-sensing system comprising two AHL synthases and
three receptors. The LasI synthase produces 3OC12-HSL, for
which there are two receptors, LasR and QscR. The RhlI syn-
thase produces C4-HSL, for which the receptor is RhlR. There
are indications that, although the complete complement of syn-
thase and receptor genes is conserved among strains, there are
differences in the quorum-controlled genes (5), and some strains
from certain habitats contain LasR mutations (6–8).
Much of the existing data on genes controlled by quorum
sensing in P. aeruginosa derive from studies of a single laboratory
strain, PAO1 (9-11) an extensively passaged isolate from a
wound infection (12). Here we use RNA-seq to identify genes in
the quorum regulons of seven P. aeruginosa strains isolated from
disparate environments. Specifically we use strain PAO1 as a
reference. We generated and annotated draft genome assemblies
of the other six isolates. We generated lasI, rhlI quorum-sensing
mutants of each isolate and compared the transcriptomes of lasI,
rhlI mutants of all seven strains, with and without added AHLs,
to each other. As we predicted, there was a set of core quorum-
controlled genes in the core genome, and there were elements of
the accessory genome that showed quorum-sensing control.
There also were genes in the core genome that showed strain-to-
strain variation with respect to quorum-sensing control.
Quorum-Sensing Circuit Is Conserved Among Environmental and
Clinical P. aeruginosa Isolates. We examined intraspecific diversity
in quorum-regulated gene expression by examining seven
P. aeruginosa strains, including four environmental isolates,
two clinical isolates from chronic cystic fibrosis (CF) lung
infections, and the laboratory strain, PAO1 (Table S1). Some
information regarding genome content and assembly statistics
for the draft genomes is provided in Table 1, and annotations
are available at www.ncbi.nlm.nih.gov/genome. The draft genomes
Author contributions: S.C., B.S.K., S.H.C., C.S.H., and E.P.G. designed research; S.C. and B.S.K.
performed research; S.C., S.P., and M.J.B. contributed new reagents/analytic tools; S.C.,
S.P., M.J.B., C.S.H., and E.P.G. analyzed data; and S.C., C.S.H., and E.P.G. wrote the paper.
The authors declare no conflict of interest.
Data deposition: The draft genome assemblies and annotations have been deposited in
the DNA Data Bank of Japan/European Molecular Biology Laboratory/GenBank database
(accession nos. AKZD00000000, AKZE00000000, AKZF00000000,AKZG00000000,
AKZH00000000, and AKBD00000000).
1To whom correspondence should be addressed. E-mail: email@example.com.
See Author Summary on page 16426 (volume 109, number 41).
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| Published online September 17, 2012
show a pangenome for the seven strains consisting of 7,423 genes
and a shared core genome of 4,449 genes. To determine if all
strains in our panel produced the two P. aeruginosa AHLs, we
tested stationary-phase cultures by using bioassays. All strains
exhibited generally similar growth rates and produced both
3OC12-HSL and C4-HSL at micromolar levels (Fig. 1). These
data indicate that the prototypical P. aeruginosa quorum-sensing
circuit is conserved and operational in all examined strains. We
generated lasI, rhlI signal-generation mutants (Materials and
Methods) which did not produce detectable levels of AHLs.
Identification of Quorum-Sensing–Regulated Genes by RNA-Seq. As
described in the Materials and Methods, RNA-seq libraries were
generated by selective cDNA priming with a pool of hexamers,
none of which showed a perfect match to any of the P. aeruginosa
ribosomal RNAs (rRNAs). This approach enables enrichment of
non-rRNA transcripts without a ribosome-depletion step, lower-
ing RNA input requirements and simplifying sample preparation
(13, 14). In fact, depending on the isolate examined, the reads
mapping to rRNAs ranged from about 30% to about 80%.
Overall, the RNA-seq results (Table 2) revealed that at least
89% of the genes for a given strain had their coding sequence
covered, indicating that the overall genome coverage afforded by
this method was high. Further, sequencing read depth data in-
dicated that the numbers of non-rRNA reads were largely similar
for all samples, thus enabling valid comparisons across samples.
We identified 161 genes that were AHL-activated in strain
PAO1 (Dataset S1) and 15 genes that were AHL-repressed. For
this study, we focused only on the AHL-activated genes. We note
that quorum-sensing–dependent genes show variable activation
at different points in growth (10, 11), and we assessed AHL-
dependent gene expression only at one point in growth (OD600
2). To validate our RNA-seq method, we compared our results
with previous data generated with a microarray platform. We
identified 77 of the 93 genes shown previously to be AHL-
induced at OD6002 (15). This number includes 10 genes that
showed AHL induction but with very few reads (<10) in cells
grown with AHLs and 0 or 1 reads in samples from cells grown
without AHLs. Because of the low expression of these genes, we
did not include them in our further analysis of AHL-activated
genes. Of the 16 genes identified in the microarray analysis but
not in our RNA-seq analysis, nine are in operons that were
detected as AHL-induced by RNA-seq. Thus, the RNA-seq and
Affymetrix microarray platforms show excellent concordance.
Our RNA-seq analysis identified AHL-induced genes not detected
in the microarray analysis. The enhanced sensitivity of this tech-
nique likely led to the identification of the additional 84 genes.
In strain PAO1 many quorum-controlled genes are activated
by AND logic gates. Quorum sensing is required but not suffi-
cient for activation of specific genes (16, 17). Thus, we do not
expect our analysis of transcripts in cells from a single point in
the growth curve, in a single growth medium, at a single growth
temperature to generate a list of all genes activated by quorum
sensing. Rather it provides a base of information to allow a test
of our hypotheses about strain variability and core and accessory
As noted above, we identified 161 quorum-activated genes in
PAO1. The number of quorum-activated genes for the remaining
strains were 342 for the soil isolate BE171; 301 for the air isolate
BE173; 207 for the biofilm isolate BE177; 76 for the tomato
plant isolate PaE2; 153 for the CF isolate CI27; and 31 for the
CF isolate CIG1. A list of quorum-activated genes for all strains
is provided in Dataset S1. Overall, the quorum regulons repre-
sent ∼0.5–6.2% of the coding sequences for a given genome.
There is no obvious correlation between genome size and the
number of quorum-controlled genes detected.
Pairwise Comparisons Between the Quorum Regulon of Strain PAO1
and Other Strains. To get a sense of the variation in quorum-
activated genes from strain to strain and to lend some validity to
conclusions that previously have been drawn about the role of
quorum sensing in the regulation of cooperative activities in
P. aeruginosa using strain PAO1, we first performed pairwise
comparisons of the P. aeruginosa PAO1 quorum regulon with the
quorum regulons of the other strains. The largest set of quorum-
activated genes (342 genes in BE171) was more than twice the
size of the PAO1 set (161 genes), suggesting that P. aeruginosa
employs quorum sensing to regulate many more traits than
previously identified. With the exception of CIG1, which has
a relatively small quorum-controlled regulon of 31 genes, there
were pronounced overlaps between the strain PAO1 regulon and
the other regulons (Fig. 2). Thus, we consider the P. aeruginosa
PAO1 quorum regulon to be reasonably representative of the
species. Well-documented examples of some quorum-controlled
Table 1. Content and assembly statistics for the draft genomes and the PAO1 reference genome
StrainSource Size (bp) Contigs
CF chronic infection
CF chronic infection
*Details for strain PAO1, included for comparison, are from the Pseudomonas genome project (www.pseudomonas.com). G+C, guanine
plus adenosine mols percent.
were not detected in cultures of lasI, rhlI mutants of any isolate.
AHL concentrations in P. aeruginosa cultures at OD6003.5. AHLs
| www.pnas.org/cgi/doi/10.1073/pnas.1214128109Chugani et al.
genes in PAO1, such as lasB, the elastase gene, the apr operon
for alkaline protease, rsaL, encoding a quorum-sensing modu-
lator protein, and cbpD encoding a putative chitin-binding pro-
tein, were activated in all strains. Genes within the shared subset
exhibited variation at levels of both quorum control and tran-
script abundance. For example, both lasB and cbpD showed
a lower quorum response in PaE2 than in PAO1, but expression
levels of both genes under non–quorum-sensing conditions were
higher in PaE2. This pattern also was noted for lasR and rhlR in
PaE2; both genes showed a small quorum response (1.8-fold for
lasR and 2.07-fold for rhlR), and neither reached our threshold
for differentially regulated genes. lasR induction in strains BE177
(2.84-fold) and CI27 (2.89-fold) was just under the threefold
threshold. The PAO1 quorum regulon showed the most overlap
(more than 110 genes; about 79%) with the environmental iso-
lates BE171, BE173, and BE177. There are many genes that
show quorum control in strains BE171 and BE173 but not in
PAO1. Among the 212-gene BE171-specific subset were genes
encoding the σ factor AlgU, alginate regulatory protein AlgP,
and the alginate and motility regulator AmrZ. Several iron-re-
sponsive genes such as PA1363 (encoding an extracytoplasmic-
function σ-70 factor), fpvR (encoding an anti-σ factor), and pvdL
and tonB1 were among the 163 genes in the BE173-specific
quorum regulon. A surprising finding was the strain-specific
regulation of several genes coding for extracellular products. For
example, phenazine biosynthesis and rhamnolipid biosynthesis
genes were quorum-activated in PAO1 but not in two other
isolates, PaE2 and CIG1.
Variations in quorum regulons may be caused by differences in
gene content between strains or by differences in gene expression.
In P. aeruginosa, both determinants appear to dictate strain-specific
quorum regulation. Although the entire set of quorum-controlled
PAO1 genes was present in all environmental isolates, some
genes were absent in one or both CF isolates. The hcnABC op-
eron for hydrogen cyanide production was among the five genes
in the pan quorum-controlled set absent in the CF infection
isolate CI27. Likewise, 13 genes were absent in the other CF
isolate CIG1. PA1874, which codes for a hypothetical protein,
was absent in both CI27 and CIG1. Conversely, we identified 48
strain-variable genes that were absent in PAO1 but were present
and quorum-activated in one or more of the remaining isolates;
these can be considered as belonging to the P. aeruginosa
Differential regulation of genes present in both genomes in
pairwise comparisons may be the result of sequence divergence
in cis-regulatory regions. Previous work indicates that some genes
are indirectly quorum-sensing–activated by other determinants
including regulators, which are themselves quorum controlled
(16, 17). Thus, differential regulation may be affected by varia-
tions in the activity or presence of transcriptional regulators or
two-component signal transduction proteins. We examined the
defined or putative promoter regions of a few genes that showed
significant strain-specific variations in quorum response relative
to PAO1. These included PA3724 (lasB) in CIG1 and BE173,
PA0143 (nuh) in PaE2, and PA2570 (lecA) in BE173 and CIG1.
In all cases examined, either the upstream regions were identical
or sequence differences could not account for the observed dif-
ferential regulation. An example of the latter case is the region
upstream of lasB. This gene shows a quorum response of about
130-fold in strain PAO1, a lower response of about threefold in
CIG1, and a higher response, about 276-fold in BE173. Thus,
there was no correlation between the intensity of the response and
Table 2. Summary of sequencing results
a read (%)
*Replicate numbers are indicated in parentheses.
†Values indicate percent of mapped reads after eliminating tRNA reads.
Chugani et al.PNAS
| Published online September 17, 2012
levels of the generated AHLs (Fig. 1). Although the promoter
region of lasB in both CIG1 and BE173 differed from PAO1, the
mismatches in the low-responsive CIG1 promoter were identical
to those in the high-responsive BE173 promoter. Collectively,
these data suggest that differential regulation for some genes is
indirect and may be caused by variations in quorum-controlled or
other regulatory factors. For all strains except CIG1, the strain-
specific subset of the quorum regulons included transcriptional
regulators and/or two component regulatory systems.
Correlations in Quorum Regulons of the Environmental Isolates. A
comparison of the four environmental isolates revealed a set of
43 shared quorum-activated genes (Fig. 3). This subset included
genes encoding the production of a number of extracellular
factors such as the LasA and LasB proteases, ClpP2 protease,
alkaline protease, hydrogen cyanide, and the antibiotic methox-
yvinylglycine. The soil isolate BE171, the air isolate BE173, and
the biofilm isolate BE177 shared a larger set of 101 genes.
Among this set were genes in the flp-tad-rcp locus, which is
required for Flp pilus assembly and bacterial adherence, lecA,
which codes for a lectin, and the bphO-bphP genes encoding
a heme oxygenase and a phytochrome. Also included in this set
were 57 genes coding for hypothetical proteins of unknown
function including three probable transcription factors. In addi-
tion to the shared genes, quorum control of a large subset of 99
genes was unique to BE171, and quorum control of a subset of
71 genes was unique to BE173.
Perhaps the most interesting relationship emerged between
the plant isolate PaE2 and the soil isolate BE171. The quorum
regulons of these isolates showed the most extensive overlap in
pairwise comparisons. Sixty-three of the 76 quorum-activated
genes in PaE2 were shared with BE171. An interesting finding
was that, unlike other subsets of overlapping genes among the
environmental isolates, the overlap between these two strains
included genes belonging to the accessory genome. Based on
orthologs in the P. aeruginosa LESB58 genome, these 11 genes
were annotated as part of an 18-gene pyoluteorin biosynthesis
(plt) operon. Closer inspection of the genomes revealed that this
entire 31,613-bp locus was conserved in both PaE2 and BE171.
Although the remaining seven genes all exhibited some level of
quorum activation, the response was less than threefold in one or
both strains. Thus, six genes that satisfied our filtering criteria
sorted to the PaE2-unique quorum-controlled subset (Fig. 3). As
previously documented for LESB58 (18), the plt gene cluster was
found at the same chromosomal location adjacent to PA2593 in
both PaE2 and BE171.
Correlation Between the Quorum Regulons of the Clinical Isolates.
The two clinical isolates were from two different patients with
chronic CF lung infections. The CI27 quorum regulon was much
larger (153 genes) than that of CIG1 (31 genes). A comparison
of the two regulons identified an overlapping set of 25 genes. If
signal synthase levels in the wild types of both strains are similar,
it is interesting that almost all shared genes showed a signifi-
cantly lower quorum response in CIG1. Of the set of 128 genes
quorum-controlled in CI27 but not in CIG1, six were absent from
the CIG1 genome. These include PA2300, which is annotated as
a chitinase, PA2566, encoding a hypothetical protein, and genes
belonging to the amb operon for methoxyvinylglycine bio-
synthesis. A small set of six genes was quorum-controlled in CIG1
but not in CI27. Although LasR sorted to the CIG1-unique subset
of six genes, it showed a 2.89-fold induction in CI27 (just below the
threefold threshold filter used in this study). The remaining five
genes unique to CIG1 included the first two genes of the hcnABC
operon. However, hcnC is absent in CIG1, and the entire hcnABC
operon is absent in CI27. Thus, regardless of the quorum activation
of hcnA and hcnB in CIG1, both strains should have a hydrogen
cyanide-negative phenotype. Collectively, these observations in-
dicate that the only quorum-activated genes in CIG1 not shared
with CI27 belong to the P. aeruginosa quinolone signal (PQS)
biosynthesis operon (pqsA, pqsD, and pqsE).
A small number of quorum-activated genes in CI27 were in the
accessory genome. An ortholog for one of these genes, encoding
a hypothetical protein, also was present in the accessory genome
of CIG1, but it was not quorum-responsive. There were no quo-
rum-controlled genes in the CIG1 accessory genome.
One might expect that genes encoding quorum-induced viru-
lence determinants should show a robust response in both CF
isolates, but this was not the case. The pattern of expression for
these genes appears to be more complicated and dictated vari-
ously by differences in gene expression and the absence of genes.
For example, lasB, which codes for elastase, showed a 59-fold
response in CI27 but only a 3.3-fold response in CIG1. Likewise,
the apr genes encoding alkaline protease showed a greater re-
sponse in CI27 than in CIG1, and genes specifying pyocyanin
biosynthesis were quorum-induced only in CI27. As discussed
above, a noteworthy finding was that both strains had genomic
deletions that should render them incapable of producing hy-
controlled genes in P. aeruginosa PAO1 and the environmental and CF iso-
lates. Areas within the Venn diagram are drawn approximately to scale, and
the number of genes in each is indicated. The number of genes absent from
the other genome is shown in parentheses.
Venn diagram showing the relationship between quorum-sensing–
ulons of the four environmental isolates. The number of genes in each is
Venn diagram showing the relationship between the quorum reg-
| www.pnas.org/cgi/doi/10.1073/pnas.1214128109 Chugani et al.
drogen cyanide. It is possible that conserved selective pressures
contributed to the deletion of these genes within the environ-
ment of the CF lung.
Core Quorum-Controlled Regulon. All 43 quorum-controlled genes
shared by the four environmental isolates were in the core genome.
We sought to determine if this set might represent a P. aerugi-
nosa core quorum-controlled regulon. A comparison revealed
that all but two of the 43 genes also were quorum-controlled
in PAO1. One of these two genes, pheC (PA3475), is in fact
downstream of rhlI and part of the chromosomal deletion in our
lasI, rhlI mutant PAO-MW1 (19, 20). Thus, it appears that many
P. aeruginosa strains maintain quorum control of this set of about
41 or 42 genes (Table 3) even in the absence of natural selective
pressures. Is this set robust to the inclusion of the two CF iso-
lates? A comparison of the set of 41 genes with each CF isolate
revealed an overlap of 30 genes in CI27 and an even smaller
overlap of 17 genes in CIG1. Of the core genes that were quo-
rum-controlled in PAO1 and the environmental isolates but not
in the CF isolates, three were absent in CI27, and seven were
absent in CIG1. We view the 41 or 42 quorum-controlled genes
shared by strain PAO1 and the environmental isolates as a core.
The CF isolates show degraded quorum-sensing regulons. This
observation is of interest because it is consistent with previous
findings that P. aeruginosa quorum-sensing mutants are abundant
in the lungs of some chronically infected CF patients (6, 7).
Hierarchical clustering analysis (Fig. 4) supports the view that
the quorum-sensing regulon of the tomato plant isolate PaE2 is
most closely related to that of the soil isolate BE171, and the
quorum-sensing regulon of the CF isolate C1G1 shows the least
relatedness to the rest.
Overall, an integrated examination of the quorum regulons of
the seven strains revealed a pan quorum-controlled set of genes
(Dataset S1) consisting of a small set of shared genes, the core
quorum-controlled genes (Table 3), and a larger set of strain-
variable genes, including genes on the accessory rather than the
core genome (Table 4).
Our study adds substantially to the list of P. aeruginosa
quorum-controlled genes, but it does not extend the range of
functional categories to which P. aeruginosa quorum-controlled
genes have been assigned previously. Thus, we did not identify
annotated genes encoding factors involved in the following
categories: (i) cell division; (ii) chaperones and heat shock
proteins; (iii) chemotaxis; (iv) DNA replication, recombination,
modification and repair; (v) phage-, transposon-, or plasmid-
related; or (vi) RNA processing and degradation.
In most cases what we know about genes regulated by AHL
quorum sensing in a given species comes from studies on a single
strain. In the case of V. fischeri, quorum-sensing control of lumi-
nescence shows conservation, but genomic sequencing revealed
that an additional set of about 10 genes regulated by quorum
sensing in a squid light organ isolate (21) is not present in the
genome of a fish isolate. This limited information provided
impetus for our investigation of quorum-controlled genes in
P. aeruginosa, which is known to be metabolically flexible and to
thrive in diverse habitats (22). Therefore, we examined quorum-
sensing regulons of multiple P. aeruginosa isolates from different
free-living and host-associated habitats. We used high-through-
put DNA sequencing to create draft genomes of six P. aeruginosa
isolates, generated quorum-sensing signal-generation mutants of
each isolate, and compared transcriptomes of mutants grown
with and without added signals (a phenotypic complementation).
Our analysis provides a snapshot of the quorum-controlled regulons
at one point in growth. This approach certainly has limitations and
cannot provide an exhaustive census of quorum-controlled genes.
Nevertheless, it supports a view that P. aeruginosa genes con-
trolled by quorum sensing are a reflection of the habitat from
which a strain was isolated.
We found that identical quorum-sensing circuits regulate sets
of genes that partially overlap in different strains. We show that
there are quorum-controlled genes on the P. aeruginosa core ge-
nome and on accessory elements of the pan-genome. There also is
a core of quorum-controlled genes, and our limited analysis
indicates this core set of about 42 loci degenerated during evo-
lution in the specialized environment imposed by chronic coloni-
zation of the CF lung. Although deeper analyses are warranted,
our studies indicate that the accessory components of the quo-
rum regulon reflect ecologic differences in the habitats from
which isolates were obtained.
The presence of several genes that code for secreted products
among the shared or core subset for all strains is consistent with
the view that P. aeruginosa quorum sensing functions to co-
ordinate the production of public goods, an argument for the
idea that quorum sensing coordinates cooperativity (23). Our
examination of the strain-variable subsets of quorum-controlled
genes was revealing. Several isolates controlled accessory genes
(plt genes, for example) by quorum sensing. With the exception
Table 3.Core quorum-controlled genes
ORF no.* Gene name Description
Chitin-binding protein CbpD precursor
Probable major facilitator superfamily
Alkaline protease biosynthesis gene
Regulatory protein RsaL
Probable acyl carrier protein
LasA protease precursor
Hydrogen cyanide synthase operon
acid biosynthesis gene cluster
Probable transcriptional regulator
Probable periplasmic spermidine/
Probable nonribosomal peptide
Conserved hypothetical protein
Cyclohexadienyl dehydratase precursor
Autoinducer synthesis protein RhlI
Probable serine protease
Conserved hypothetical protein
Probable sulfite or nitrite reductase
Probable iron-sulfur protein
Conserved hypothetical protein
The set of 42 genes activated by quorum sensing in all but the CF isolates.
*PA ORF number from the Pseudomonas genome project. (www.pseudomo-
Chugani et al.PNAS
| Published online September 17, 2012
of the CF isolate CIG1, the quorum-controlled regulons included
several known and putative transcriptional regulators and two-
component systems as accessory elements. These findings sug-
gest the existence of feed-forward systems and allude to the
possibility of strain-specific integration of quorum sensing with
other environmental cues affecting transcription. Also included
in the strain-variable subset of quorum-controlled elements were
genes for general metabolic functions, for example, PA2144,
which codes for glycogen phosphorylase, and PA3183, which
codes for glucose-6-phosphate dehydrogenase. One can imagine
circumstances in which quorum-regulated alterations in meta-
bolic versatility have implications for survival in different nutri-
tionally restricted environments (24). Given the role of quorum
sensing in coordinating the production of extracellular products,
it is of interest that some isolates had decoupled production of
specific extracellular factors from quorum sensing (e.g., the
phenazine biosynthesis operon in CIG1 and genes for rhamno-
lipid synthesis in PaE2). The selective advantage afforded by the
exclusion of these genes from quorum regulation is unclear.
With the environmental isolates, we found evidence that
P. aeruginosa can adjust its cooperation strategies via mod-
ifications of the quorum-sensing regulon. Two strains, PaE2
and BE171, isolated from geographically separate but eco-
logically related environments (tomato plant and soil) shared
an identical pyoluteorin-coding region (plt) that was not
present in other strains. Pyoluteorin is a polyketide with an-
tifungal and antibacterial activity. This antimicrobial polyke-
tide suppresses plant diseases (25–27). The plt gene cluster is
found in plant-associated pseudomonads (e.g., P. fluorescens
Pf-5 and CHAO) and contributes to the ecological fitness of
these pseudomonads in the rhizosphere (27). The plt operon
has been identified in a few P. aeruginosa isolates, namely,
PACS171b, PACS88, and LESB58 (18, 28). LESB58, the
earliest archived P. aeruginosa isolate from the Liverpool CF
epidemic, carries the plt gene cluster on a genomic island,
suggesting that it was acquired through horizontal transfer
(18). Curiously, in LESB58 there is a frameshift mutation caused
by a deletion in the pltB gene, and the operon is nonfunctional.
This finding suggests that the selective pressures that led to the
acquisition of this operon were lifted within infected patients.
Interestingly, as in the case of PACS171b, PACS88, and LESB58,
the plt gene cluster in the two environmental strains in this study is
located at the same place in the chromosome, downstream of
PA2593. This example of rapid adaptation illustrates the dexterity
with which P. aeruginosa both uses and evolves its quorum-
P. aeruginosa infections typically are acquired from environ-
mental reservoirs (29). Overall, the quorum-controlled regulon
was somewhat more conserved among the environmental strains
and strain PAO1 than it was between strain PAO1 and the CF
isolates. It is apparent from our analysis that the CF isolate CIG1
has diverged significantly from the other strains, at least with
respect to quorum sensing. Differences include its small quorum
regulon, the tempered response for most genes that remain
quorum-controlled, and deletions in a number of genes that are
quorum-controlled in one or more of the other strains. We also
found examples of strain-variable quorum regulation in the CF
isolate CI27 that were associated with gene deletions. These
findings are consistent with the genetic variations associated with
P. aeruginosa adaptation during chronic CF infections (6, 30).
Because of the small sample size of two CF isolates, our results
must be viewed with caution and must be considered as sug-
gestive. The results lead us to imagine that quorum control of
certain genes (such as the hcn genes for hydrogen cyanide pro-
duction) confers a fitness advantage in the environment or early
during infection but not during chronic CF lung infection. Traits
that otherwise are beneficial may be unnecessary or even detri-
mental in the context of a long-term infection and therefore may
be uncoupled from quorum sensing during adaptation. A finding
that argues in favor of this hypothesis is that hcnA and hcnB, the
two genes of the hcnABC operon that were not deleted in CIG1,
were in fact activated by quorum sensing. We find it interesting that
LasR quorum-sensing mutations accumulate in P. aeruginosa dur-
ing long-term CF lung colonization. Uncoupling of certain genes
from quorum-control represents a different molecular solution to
decreasing or eliminating expression of quorum-controlled genes.
The findings that both CF isolates in our panel harbored
deletions in the hcn operon and that many CF isolates have lasR
mutations also are of clinical significance. There has been recent
interest in using the cyanogenic properties of P. aeruginosa to
develop a rapid method for its detection in CF patients (31, 32).
Although further work with a larger collection of strains is re-
quired, the reliability of this approach is brought into question by
This study extends the list of genes reported to be quorum-
controlled in P. aeruginosa and demonstrates that quorum control
of gene expression has a strain-variable component. We expect
that an extension of this analysis to a larger collection of strains
not only will identify additional strain-variable quorum-responsive
genes but also will allow a correlation of the variations with
Materials and Methods
Bacterial Strains, Plasmids, and Growth Conditions. Bacterial strains and
plasmids used are listed in Table S1. For plasmid and strain constructions,
bacteria were grown in LB broth, supplemented with antibiotics when ap-
for each gene are depicted in the heat map. The genes are displayed in the
order of the hierarchical clustering of their fold changes according to the
Spearman correlation coefficient. Quorum-activated genes are depicted in
green, and genes that are absent or do not satisfy our filtering criteria are
depicted in black.
Relative expression profiles of quorum-activated genes. Fold changes
| www.pnas.org/cgi/doi/10.1073/pnas.1214128109 Chugani et al.
propriate at the following concentrations (per mL): 10 μg of gentamicin, 10 μg
of tetracycline, and 100 μg of ampicillin for Escherichia coli and 100 μg of
gentamicin, 100 μg of tetracycline, and 150 μg of carbenicillin for P. aeru-
ginosa. For transcript profiling, midlogarithmic-phase cells were used to in-
oculate LB broth buffered with 50 mM 3-(N-morpholino) propanesulfonic
acid (MOPS) (pH 7.0). The optical densities (OD600) at inoculation were 0.05.
When appropriate, synthetic AHLs were added to the medium at final
concentrations of 2 μM for 3OC12-HSL and 10 μM for C4-HSL before
Chromosomal deletions were constructed using either pEXG2- or pEX18Tc-
derived plasmids (33, 34). PCR-amplified DNA fragments flanking lasI and rhlI
from P. aeruginosa PAO1 were cloned into pEXG2 and pEX18Tc, resulting in
a deletion of codons 31–191 in lasI and codons 34–184 in rhlI. The resulting
plasmids were used to construct lasI, rhlI mutants using standard methods.
Candidate mutants were screened by PCR and by demonstrating that
mutants did not make detectable 3OC12 and C4-HSL in stationary-phase
culture extracts. The lasI, rhlI mutants had no discernible growth defects
compared with their respective parents.
Measurement of AHLs. Cells were grown to an OD600of 3.5 in LB broth
buffered with 50 mM MOPS (pH 7.0). Concentrations of 3OC12-HSL and
C4-HSL were measured with bioassays as described previously (35, 36).
Sequencing, Assembly, and Annotation of P. aeruginosa Strains. DNA Se-
quencing for the six previously unsequenced isolates was done with the
Illumina Genome Analyzer according to the manufacturer’s instructions
(Illumina). A random fragment library was constructed by using a custom
paired-end protocol. The genomes were assembled from 76-bp paired-end
Table 4. Quorum-controlled accessory genes in the pangenome
ORF no.* DescriptionStrain
cbb3-type cytochrome c oxidase subunit I
Transport protein HasD
Protein of unknown function DUF932
Helicase domain-containing protein
Secreted protein Hcp
Putative nucleoside-binding outer membrane protein
Periplasmic spermidine/putrescine-binding protein
Putative alkylhalidase PltM
Putative halogenase, PltA
Polyketide synthase type I, PltB
Polyketide synthase type I, PltC
Putative halogenase, PltD
Putative acyl-CoA dehydrogenase, PltE
Putative acyl-CoA synthetase, PltF
Putative thioesterase, PltG
Membrane fusion protein, PltH
ATP-binding protein, PltI
Inner membrane permease protein, PltJ
Inner membrane permease protein, PltK
Outer membrane channel protein, PltN
Putative transmembrane protein, PltO
*ORF number from draft genomes in the PGAT database (http://tools.nwrce.org/pgat/). ORF numbers for both homologs are listed for
ORFs that were quorum-activated in two strains.
Chugani et al. PNAS
| Published online September 17, 2012
reads using Velvet (37). Genome annotation was predicted by a software
annotation pipeline associated with the Prokaryotic Genome Analysis Tool
(PGAT) (38). Manual annotation of the genome assemblies also was per-
formed using PGAT and the Pseudomonas genome database (www.pseu-
domonas.com) (39). The first version draft assemblies and annotation of the
six genomes sequenced in this study have been deposited at DNA Data Bank
of Japan/European Molecular Biology Laboratory/GenBank (www.ncbi.nlm.
nih.gov/genome). PGAT also was used to determine the presence and absence
of genes and for interstrain comparisons of promoter sequences (http://tools.
RNA Isolation. Approximately 1 × 109cells at OD6002 were mixed with RNA
Protect Bacteria reagent (Qiagen) and stored at −80 °C. Thawed cells were
resuspended in QIAzol reagent and disrupted by bead beating. RNA was
purified using a miRNeasy minikit (Qiagen) according to the manufacturer’s
instructions. RNA was treated with Turbo DNase (Ambion) and purified us-
ing a RNeasy MinElute cleanup kit (Qiagen). Two biological replicates were
processed for each condition (without and with added AHLs).
RNA-Seq Library Construction and Sequencing. P. aeruginosa-specific selective
primers were based on the genome sequences of seven P. aeruginosa strains
(PAO1, PA14, PA7, LESB58, PACS2, C3719, and 2192). We used a pool of
1,507 selective hexamers with no perfect match to any rRNA genes. An
additional set of 200 hexamers, responsible for the majority of rRNA-priming
events in test libraries, was removed, leaving a final set of 1,307 selective
hexamers. The hexamer sequences of the final primer pool, the forward and
reverse adaptor sequences, and the PCR primer sequences are given in Table
S2. An in silico assessment of selective hexamer-binding sites in P. aeruginosa
PAO1 mRNA showed that there was an average of one binding site for every
five bases of potential template sequence. A detailed description of the
multiplexed library generation protocol is provided in SI Materials and
Methods. Briefly, first- and second-strand syntheses were carried out by
using the pool of selective primers and RNA template to create double-
stranded cDNA. Subsequent adaptor ligation and PCR-amplification steps
were used to generate DNA libraries with sample-specific 3-bp barcode tags.
Eight uniquely barcoded DNA libraries were sequenced per lane as 36-mers
on an Illumina Genome Analyzer II flowcell using the standard Illumina
protocol at the University of Washington Genome Center.
Sequence Mapping and Analysis. Raw sequencing reads (36 nucleotides in
length) were first sorted on the basis of their barcodes. For PAO1 samples,
reads were mapped to the PAO1 genome (sequence downloaded from www.
pseudomonas.com) and analyzed using Avadis NGS software (version 1.2.3,
Build 149378; Strand Scientific Intelligence, Inc.). For all other P. aeruginosa
samples, reads were mapped to the corresponding strain’s draft genome
using Burrows–Wheeler alignment (40) and were analyzed using custom
Python scripts (http://nwrce.org/nwrce-org/resources/web-resources/software-
utilities). For each sample, a set of input reads for comparison analyses was
generated in two steps. First, we derived a set of uniquely mapped reads,
defined as reads that mapped to the non-rRNA regions of the genome with
two or fewer mismatches. Next, we filtered this set to eliminate reads that
mapped to tRNA genes. For comparisons, we used sample pairs with generally
similar numbers of mRNA sequencing reads in the two conditions (without
and with added AHLs). Sequence-read mapping and genome coverage
information are summarized in Table 2.
Identification of Differentially Expressed Genes. For all samples, the number of
raw reads mapping to each gene was normalized based on the total number
of input reads (non-rRNA and non-tRNA reads) for that sample. This nor-
malizationprocedureallowed comparison ofgene-expression patterns across
strains, within and between experiments. Reads that partially overlapped
a gene contributed to its total raw read value. The raw read value for each
gene was incremented by 1 before normalization to avoid errors caused
by instances of division by 0. The fold-change values for each gene were
computed by first calculating the geometric mean across replicate samples
and then calculating ratios across conditions. We chose geometric averaging
to dampen the effects of possible outlying values in transcript abundances
between replicates on fold-change estimates. Next, we applied filtering
criteria designed to allow a more robust estimation of the quorum-activated
component of the quorum regulon. Only genes that had an average of >10
reads in the two replicates for the plus AHL condition were considered for
further analyses, and genes with at least a threefold change between con-
ditions were considered differentially expressed. Avadis NGS was used to
compare differentially expressed genes between strains and for visualization
of reads mapped to the PAO1 genome.
ACKNOWLEDGMENTS. We thank Chris Armour for invaluable technical as-
sistance and discussions, the staff at the University of Washington Genome
Center for their contributions, and Matthew Radey for help with data anal-
ysis. This work was supported by US Public Health Service (USPHS) Grants
GM-59026 (to E.P.G.) and GM-56665 (to C.S.H.) and by resources from the
Microbiology and Genomics Cores of USPHS Grant P30DK089507. B.S.K. and
S.H.C. were supported by the Korea Research Foundation Grant KRF-2009-
013-F00014 (Republic of Korea). We also acknowledge the services and use
of software developed by the Data Integration Core of the Northwest Re-
gional Center of Excellence for Biodefense and Emerging Infectious Diseases
Research funded by the National Institutes of Health, National Institute of
Allergy and Infectious Diseases Grant U54 AI057141.
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Chugani et al.PNAS
| Published online September 17, 2012