Runcharoen et al.

Genome Medicine (2017) 9:6

DOI 10.1186/s13073-017-0397-1

RESEARCH Open Access

Whole genome sequencing reveals high-

resolution epidemiological links between
clinical and environmental Klebsiella
pneumoniae
Chakkaphan Runcharoen1, Danesh Moradigaravand2*, Beth Blane3, Suporn Paksanont1, Jeeranan Thammachote4,
Suthatip Anun4, Julian Parkhill2, Narisara Chantratita1,5 and Sharon J. Peacock2,3,6*

Abstract
Background: Klebsiella pneumoniae is a gram-negative bacterial species capable of occupying a broad range of
environmental and clinical habitats. Known as an opportunistic pathogen, it has recently become a major causative
agent of clinical infections worldwide. Despite growing knowledge about the highly diverse population of K.
pneumoniae, the evolution and clinical significance of environmental K. pneumoniae, as well as the relationship
between clinical and environmental K. pneumoniae, are poorly defined.
Methods: We isolated and sequenced K. pneumoniae from in-patients in a single hospital in Thailand, as well as
hospital sewage, and surrounding canals and farms within a 20-km radius.
Results: Phylogenetic analysis of 77 K. pneumoniae (48 clinical and 29 non-clinical isolates) demonstrated that the
two groups were intermixed throughout the tree and in some cases resided in the same clade, suggesting recent
divergence from a common ancestor. Phylogenetic comparison of the 77 Thai genomes with 286 K. pneumoniae
from a global collection showed that Thai isolates were closely related to the clinical sub-population of the global
collection, indicating that Thai clinical isolates belonged to globally circulating lineages. Dating of four Thai K.
pneumoniae clades indicated that they emerged between 50 and 150 years ago. Despite their phylogenetic
relatedness, virulence factors and β-lactamase resistance genes were more numerous in clinical than in environmental
isolates. Our results indicate that clinical and environmental K. pneumoniae are closely related, but that hospitals may
select for isolates with a more resistant and virulent genotype.
Conclusions: These findings highlight the clinical relevance of environmental K. pneumoniae isolates.
Keywords: Klebsiella pneumoniae, Whole genome sequencing, Antibiotic resistance, Genomic epidemiology

Background environments [2, 3]. The emergence of multidrug-

Klebsiella pneumoniae is a clinically important gram- resistant K. pneumoniae is becoming an increasingly
negative bacterium associated with opportunistic infection serious issue for clinical practice, largely related at the
in patients with a compromised immune system or receiv- present time to isolates that express extended-spectrum
ing other forms of complex medical care [1–3]. This β-lactamase (ESBL) enzymes that hydrolyze a broad
species is disseminated in healthcare settings via person- spectrum of β-lactams [4, 5]. This is compounded by
to-person contact, medical equipment, and contaminated the emergence of K. pneumoniae that express carbape-
nemases such as KPC-type β-lactamase [5–7] and the
* Correspondence: dm16@sanger.ac.uk; sjp97@medschl.cam.ac.uk recent detection of colistin-resistant K. pneumoniae
Chakkaphan Runcharoen and Danesh Moradigaravand are joint first
author.Narisara Chantratita and Sharon J. Peacock are joint senior authors. due to the presence of the mcr-1 gene [8]. These resist-
2
Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, ance genes are carried on mobile genetic elements that
Cambridgeshire, UK facilitate their spread within and between bacterial
Full list of author information is available at the end of the article

© The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0
International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and
reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to
the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver
(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Runcharoen et al. Genome Medicine (2017) 9:6 Page 2 of 10

species, a process that is likely to result in a rise in the with positive samples processed by the diagnostic micro-
number of K. pneumoniae infections that are very difficult biology laboratory at Bhuddhasothorn Hospital, Cha-
to treat. Furthermore, multidrug-resistant K. pneumoniae choengsao, Bangkok, Thailand between December 2014
are associated with nosocomial outbreaks, particularly and April 2015. Data were collected on date of isolation
in high prevalence countries including those in East and sample type, and samples were de-duplicated so that
Asia [9, 10]. only one isolate per patient was included. Speciation and
Beyond healthcare settings and hospital patients, K. ESBL positivity were initially determined using Standard
pneumoniae is ubiquitous in nature and occupies a di- Operating Procedures supplied by the Department of
verse range of niches. These include environmental Medical Science, Ministry of Public Heath, Thailand
sources, such as soil and wastewater, mucosal surfaces and Clinical and Laboratory Standards Institute (CLSI)
and the gut of humans and animals, and food sources, guidelines (M100-S24 and M100-S25), respectively. The
such as meat [11]. Environmental K. pneumoniae is less species was subsequently confirmed using matrix-
well studied than isolate collections associated with clin- assisted laser desorption/ionization time-of-flight mass
ical disease. Some studies have shown that K. pneumo- spectrometry (MALDI-TOF MS; Biotyper version 3.1,
niae of environmental origin are highly similar to Bruker Daltonics, Coventry, UK). Antimicrobial suscep-
clinical isolates with regards to phenotypic and some tibility testing was repeated using the N206 card on the
genetic features [12–14], but others have reported differ- Vitek 2 instrument (bioMérieux, Marcy l’Étoile, France)
ences in virulence characteristics between the two calibrated against EUCAST breakpoints, and these re-
groups [15, 16]. The parallel evolution of K. pneumoniae sults were used during the analysis.
and putative acquisition of antimicrobial resistance de- Environmental and livestock-associated isolates (n = 29)
terminants and virulence factors in healthcare settings were obtained through a cross-sectional survey between
and the environment have led non-clinical habitats to be January 2015 and February 2015. Wastewater samples
considered as potential reservoirs for hyper-virulent and were collected from 27 canals and 11 farms within a 20-
hyper-resistant K. pneumoniae [15], although evidence to km radius of Bhuddhasothorn Hospital. The farms reared
support the potential clinical importance of non-clinical pigs (n = 2), chickens (n = 6), ducks (n = 2), and both
K. pneumoniae is inconclusive. A recent study of the clin- chickens and ducks (n = 1). Samples were collected from
ical relevance of meat-source K. pneumoniae showed dif- wastewater collection areas (commonly concrete gullies
ferences in antibiotic resistance but similar virulence that drained waste from animal housing). The longitude
characteristics for isolates from retail meat and those asso- and latitude of each sampling site were recorded using
ciated with urinary tract infections in humans [16]. GPSMAP 60CSx (Garmin, Taiwan). A further two waste-
Here, we report the findings of an in-depth compari- water samples were taken from the Bhuddhasothorn
son of the evolution and epidemiology of ESBL-positive Hospital wastewater treatment system (one pre-treatment
K. pneumoniae using a One Health approach [17, 18]. and one post-treatment water sample). At each site, grab
We utilized the fine-scale resolution of whole genome samples of 0.5 L each were collected into sterile bottles
sequencing to investigate genetic relatedness, antimicro- containing 9 mg of sodium thiosulfate pentahydrate
bial resistance, and the presence of genes encoding viru- (Merck, Darmstadt, Germany). All samples were trans-
lence determinants in an unbiased, prospective ported to the laboratory on ice packs in the dark and
collection of K. pneumoniae from patients in one hos- processed within 12 h.
pital, as well as from environmental water, hospital sew- One mL of triplicate serial 10-fold dilutions of wastewa-
age, and farm waste in the proximity of the hospital. ter samples were concentrated using the filtration tech-
These genomes were placed into a global context nique onto 0.45-μm pore size filter membranes (Merck,
through a comparison with isolates recovered from vari- Darmstadt, Germany). Membranes were then placed onto
ous clinical and non-clinical sources worldwide [19]. the surface of ESBL Brilliance agar (Oxoid, Basingstoke,
Our results highlight the clinical relevance of environ- UK) and incubated for 48 h at 35 °C in air. For each sam-
mental K. pneumoniae isolates, and demonstrate that pling site, up to 10 colonies suspected to be K. pneumo-
environmental and clinical K. pneumoniae are highly re- niae based on color (green) were picked and the presence
lated but that hospitals select for K. pneumoniae with a of ESBL confirmed using the combination disc test
more antimicrobial-resistant and virulent genotype. (M100-S24 and M100-S25). Escherichia coli ATCC25922
and K. pneumoniae ATCC700603 were used as negative
Methods and positive controls, respectively. Positive colonies were
Study design and bacterial isolates speciated using MALDI-TOF MS, and antimicrobial
The bacterial collection consisted of 77 ESBL-producing susceptibility testing of confirmed K. pneumoniae was
K. pneumoniae isolated between 2014 and 2015. Clinical determined using the N206 card as described above. All
isolates (n = 48) were obtained from consecutive patients isolates were stored at −80 °C until further analysis.
Runcharoen et al. Genome Medicine (2017) 9:6 Page 3 of 10

Whole genome sequencing and pan-genome analysis rest of the genome [26]. The significance of the temporal
DNA extraction, sequencing, and assembly of reads signal was assessed according the R-squared value obtained
were performed as previously described [20]. Sequen- from the root-to-tip distance versus time of isolation plot.
cing was performed on an Illumina HiSeq2000. Details We generated 10,000 sample sets by bootstrapping and
of reads, depth of coverage, and N50 are provided in assessed the value of R-squared against the distribution of
Additional file 1. The sequence reads were submitted to R-squared values. Of four clades we identified on the
the European Nucleotide Archive (ENA) under acces- phylogenetic tree of the Thai and global isolates, we found
sion numbers [ENA:ERP012787 and ENA:PRJEB11403]. strong signals (>99%) for clades 1 and 3, after leaving one
An average coverage of 85-fold was achieved. Genomes isolate out from either clade. BEAST version 1.7 was used to
were assembled using Velvet [21] with the pipeline and estimate the substitution rate and date the phylogenetic tree
improvements found at https://github.com/sanger- for the clades with significant temporal signal [27], using a
pathogens/vr-codebase and https://github.com/sanger- strict molecular clock and a lognormal and uniform prior
pathogens/assembly_improvement. The de novo assem- distribution models for base frequencies with constant
blies were annotated using Prokka [22], and sequence population size. Three chains of BEAST were run for 50
types (STs) were identified from the sequence data using a million generations (sampling every 10 generations) and
multilocus sequence typing (MLST) database (http:// checked as to whether the runs had converged on similar
bigsdb.pasteur.fr/klebsiella/) and an in-house script values. Convergence was controlled using effective sample
(https://github.com/sanger-pathogens/mlst_check). size (ESS) value (we considered a cut-off of 200 ESS for
convergence). We excluded 10 million initial steps as a
Phylogenetic analysis and substitution rate calculation burn-in phase and merged the out trees with the Tree-
Study genomes were contextualized against a global Annotator program in the BEAST package, and chose the
collection. Sequence data for 286 K. pneumoniae isolates model in which convergence always occurred (for the clades
reported previously [19] were downloaded from the ENA we tested here, the strict molecular clock with a uniform
and combined with the 77 study genomes. As in our prior distribution for base frequencies always converged).
study, these isolates were also sequenced on a HiSeq se-
quencing system. Short reads for the 363 isolates were Identification of antimicrobial resistance determinants,
mapped against the reference genome K. pneumoniae virulence factors, and plasmids
Ecl8 (accession number: HF536482 CANH01000000) We employed the srst2 package [28], which takes short
using SMALT v0.7.4 (http://www.sanger.ac.uk/science/ reads and maps them to reference sequences, to find anti-
tools/smalt-0). An in-house tool that combined SAMtools biotic resistance genes, virulence factors, and plasmid
mpileup [23] and BCFtools, as detailed in [24], was used replicons. The sequences for 79 virulence genes were
to annotate single nucleotide polymorphisms (SNPs), after obtained from the Pasteur institute data repository (http://
which the pairwise SNP distances were calculated from bigsdb.web.pasteur.fr/klebsiella/klebsiella.html, http://bigs
the multiple alignment to obtain the phylogenetic tree. db.pasteur.fr/perl/bigsdb/bigsdb.pl?db=pubmlst_klebsiella_
Mapping each genome to the reference genome allowed seqdef_public&page=downloadAlleles). An in-house tool
us to identify genes that were conserved in the core gen- was used to visualize the results. To find the possible con-
ome of the study isolates and reference genome. We con- text of the virulence (i.e., chromosomal or plasmid based),
structed a maximum likelihood tree using FastTree we first found the contig in which the virulence factor was
version 2.1.3 with 100 bootstraps and a midpoint root located and then extracted the 5-kb sequences upstream
[25]. We employed FigTree (http://tree.bio.ed.ac.uk/soft- and downstream of the gene; if this exceeded the contig
ware/figtree/), Microreact (www.microreact.org), and in- size, we considered the end and start of the contig. We
house tools to visualize the results. then performed blast searches using the NCBI non-
To determine the substitution rate for each clade (see redundant nucleotide database to find out whether the hit
the Results section for more details), reads were first sequences corresponded to a chromosomal or a plasmid
mapped within each clade to the sequence obtained after region. Furthermore, we assessed the significance between
concatenating contigs for the isolate with the best con- the presence of virulence factors in the clinical/environ-
tigs statistics, i.e., the isolate with the highest N50 value. mental sub-populations by performing logistic regression.
After mapping the reads to the new references, high- To this end, we took the presence/absence of individual
density SNP regions (which are indicative of putative re- genes as the categorical predictor parameter and the en-
combination events) were removed from the multiple vironmental/clinical status as the categorical dependent
alignments using Gubbins, which works best for closely variable. Significance of association (p value < 0.05) was
related isolates and detects high SNP density regions then assessed by considering the z-statistic, which is the
based on a significantly higher number of variable sites regression coefficient divided by its standard error and has
in a sliding window across the genome compared to the a standard normal distribution.
Runcharoen et al. Genome Medicine (2017) 9:6 Page 4 of 10

Results ST307, and ST16 were recently recovered from clinical

A One Health approach was taken for the sampling and settings in France, the USA, and the Netherlands, re-
isolation of ESBL-positive K. pneumoniae from clinical spectively [29–31]. Mapping the geographical distribu-
samples in a hospital in Thailand, together with hospital tion of isolates recovered from the environment
sewage, environmental (canal) water, and wastewater demonstrated that isolates from the same sampling site
from farms within a 20-km radius of the hospital. A were frequently very genetically diverse (Fig. 1).
phylogenetic tree of the whole genomes of the 77 K. To further characterize the 77 study genomes, we
pneumoniae isolates (48 clinical and 29 environmental, combined them with genomes for a global collection of
of which 24 were from canals, 3 from farms, and 2 from 286 K. pneumoniae complex isolates [19]. The resulting
untreated hospital sewage) revealed a diverse population phylogenetic tree revealed that Thai isolates were dis-
containing three major lineages, one of which contained persed across the combined population. Isolates in the
the majority of isolates (Fig. 1). Several minor clades global collection had been defined previously based on
were also apparent, some of which showed evidence of phylogroup, and Thai isolates were observed to cluster
recent expansion (Fig. 1). Clinical and environmental in phylogroups KpI, KpIIa, and KpIIb, with the majority
isolates were intermixed throughout the tree and in residing in KpI (Fig. 2a). This broader genetic context
some cases resided in the same clade, suggesting recent highlighted the presence of several clades of Thai iso-
divergence from a common ancestor (Fig. 1). The 3 iso- lates; those containing at least 4 Thai isolates (clades 1
lates of farm origin were distributed across the tree, and to 4) were subjected to more detailed analysis to uncover
clustered with canal and clinical isolates or with canal their recent evolutionary history. These clades included
isolates alone (Fig. 1). High genetic diversity was also 30 of the 77 total isolates. A strong temporal signal was
reflected by the number of STs (n = 38) to which the 77 found for clade 1 and clade 3 after removing regions of
isolates were assigned. This included STs that have been recombination. This allowed us to estimate the substitu-
isolated elsewhere in the world. For example, ST35, tion rates, which were 8.33 × 10−7 (95% confidence

Key
Hospital
Farm
Wastewater

Canals

50000 SNPs
Fig. 1 Map showing the geographical origin of study isolates. The triangle denotes Bhuddhasothorn Hospital and the maximum likelihood tree
for 77 K. pneumoniae isolates from clinical and environmental samples (canals, livestock, and hospital sewage) showing the distribution of STs
across the population. Triangle and circles correspond to clinical and environmental isolates, respectively. Wastewater isolates were recovered from
the hospital and therefore have the same location as the hospital in the map. An interactive map can be found at www.microreact.org/project/
Skog9F1ex
Runcharoen et al. Genome Medicine (2017) 9:6 Page 5 of 10

a
Clade 1

OO
OO
OO
OO O KpIIa

C
O

la
O OO

ed
OO

2
OO
OO
O OO
O

OO
O
O
O
O
O
O
O

O
O
O

O
O

O
O
O

O
O

O
O

O
O
O
O
OO O

O
O
O
O
O
O

OO
O
O
O

O
OO

OO
O
O
O

O
OO
O KpIIb

O
O

O
O

O
O

O
O

O
O

O
O
O

O
OO

O
O
O
O

O
OOO
O
O

OOOO

OOOO
O

O
OOO
O
OOOO

OO
OOOO O
O
OOO O
O
O
OO OO
OO
O O
OO
O OO
O
Clade 4 O
O
O
O
O
O
O
O O
O
O
KpIII
O
O O
O
O
O O
OO
O
O O
O
O
O
O O
O
O
O
O O O
O
O OO O O
O
O
O OO
O
O O
O
O
O
OO O
O
O
O O
O
O
O O
Key O
O
O
O
OO
O
O
O
O
O
O
O
O
O
O
O
O OO
Thailand KpI OO
O
O
OO
OOO
OOO
OO
O
O
OOO
O
O
O
O
O
O
OO
OOO OOO
OOOO
Australia
OOOOO
b
O

OO
OOOO

OOOO
OO

OO
O

O
OO
O

O
OO

O
O
OO
O
O

O
O
O

OO
OO

OO
O
O

O
O

O
O

O
O
O

UK O
O

O
O

O
O
O

O
O
O

O
O
O
O

O
O
O
O
O
O

O
O
O
O
O

O
O
O

O
O

O
O
O

O
O
O
O
O
O
O
OO
O

Indonesia
Laos
30000 SNPs
Singapore
USA Clade 3

Vietnam

Fig. 2 a Phylogenetic tree of the 77 Thai isolates placed in the context of a global collection. Each color corresponds to a country. Shaded clades
refer to those described in the text. b Dating the most recent common ancestor for clades identified on the phylogenetic tree. To calculate the
mean and upper and lower bounds of age root for clades 1 and 3, which lacked a temporal signal, we divided the root-to-tip distances of the
root by mean substitution rates (and upper and lower bounds for 95% confidence interval) of clades 1 and 3

interval [CI]: 6.23 × 10−7, 1.05 × 10−6) per site per year excluded the isolates in the two clades and then used the
for clade 1 and 3.78 × 10−7 (95% CI: 7.47 × 10−8, 7.54 × average substitution rates for isolates in clades 1 and 3 to
10−7) per site per year for clade 3. The most recent com- estimate divergence times between a Thai isolate and any
mon ancestor (MRCA) for clades 1 and 3 was estimated other Thai or global isolate that was less than 250 SNPs
to exist 50 to 70 years ago (Fig. 2b). Using the average apart (this corresponds to approximately 50 years, which
substitution rates for clades 1 and 3, we also estimated is the age of the MRCA of clade 3, which is older than
the age of the MRCA for clades 2 and 4 to be 150 and clade 1). This revealed that Thai isolates appeared to have
50 years ago, respectively (Fig. 2b). We conclude that ex- diverged more recently from each other than from the
pansion of these K. pneumoniae clones has taken place global isolates (Fig. 4). The majority of recent divergences
over the past few decades. in the Thai collection occurred between isolates from the
Thai isolates residing in clades 1 and 3 were inter- same origin of isolation, i.e., environment or hospital
mixed with isolates from other countries in the global (17 out of 24). However, there were several cases of re-
collection (Fig. 3). The Thai isolates in clade 1 fell into cent divergence involving isolates of both environmen-
two sub-clades of clinical origin, both of which were es- tal and hospital origin, as well as evidence for recent
timated to have emerged in the past few decades. These divergence between isolates from different environmen-
were more distantly related to two clinical isolates from tal origins, i.e., different canals (Fig. 4). Moreover, one
community and nosocomial infection in the global col- putative transmission event may have occurred between
lection (Fig. 3). Clade 3 also contained two Thai sub- isolates of canal and farm origin (Fig. 4). The Thai iso-
clades, one of which was composed of clinical isolates. lates involved in 25 recent divergence events between a
The second sub-clade consisted largely of environmental Thai and global isolates were all of clinical origin, and
isolates but had recently diverged from a clinical Thai 15 and 7 of these isolates were recovered from invasive
isolate (Fig. 3). Global isolates in clade 3 were of hospital and non-invasive infections, respectively (Fig. 3). Fur-
origin and nosocomial infections. thermore, 19 out of 25 cases occurred between ST23
To generalize our findings about the epidemiological isolates, a well-known hyper-virulent strain. Taken to-
links between global and clinical and environmental Thai gether, these findings indicate that K. pneumoniae has
isolates for the isolates not included in clades 1 or 3, we rapidly expanded within the environment and hospitals,
Runcharoen et al. Genome Medicine (2017) 9:6 Page 6 of 10

Clade 1 ST Host Isolation site Acquisition* Origin** Infection Status**

16 Human Urine - Clinical -

16 Human Urine - Clinical -
16 Human Sputum - Clinical -
16 Human Blood - Clinical -
17 Human Nose swab Nosocomial - Human carriage
17 Human Stool sample Community - Human carriage
20 Human Urine Community - Human infection
20 Human Bronchial Nosocomial - Human infection
20 Human Ileum Community - Unknown
20 Human Urine Nosocomial - Human infection
20 Human Blood Unknown - Human invasive
17 Human Blood Community - Human invasive
336 Human Urine - Clinical -
336 Human Sputum - Clinical -
336 Human Sputum - Clinical -
5 years 336 Human Sputum - Clinical -
17 Human Blood Nosocomial - Human invasive
11 Human Foot Nosocomial - Human infection
Clade 3 11 Human Gastric Nosocomial - Human carriage
11 Human Sputum Nosocomial - Human infection
11 Human Sputum - Clinical -
11 Human Sputum - Clinical -
11 Human Dialysis fluid - Clinical -
11 Human Urine - Clinical -
11 Human Urine - Clinical -
11 Human Urine Nosocomial - Human infection
11 Human Urine Nosocomial - Human infection
11 Human Urine Nosocomial - Human infection
895 Human Canal - Environmental -
895 Human Canal - Environmental -
895 Human Canal - Environmental -
895 Human Canal - Environmental -
895 Human Canal - Environmental -
895 Human Canal - Environmental -
895 Human Pus - Clinical -
5 years 11 Human Alveolar Nosocomial - Human infection

Fig. 3 Dated trees for clades with a temporal signal. The numbers on the nodes signify the node age (in years), and the bars show 95% confidence
intervals. The symbols * and ** signify the specific features of the Thai and the global collection, respectively

and that in some instances, isolates of different origins present in the clinical isolate collection (Additional file 2:
have only recently diverged. Furthermore, Thai isolates Figure S2), including genes involved in capsule synthesis
were closely related to the clinical sub-population of (rmpA) [33], iron transport (iro), phospholipid transport
the global collection, suggesting that the clinical collec- (mce), regulation and transport (multiple clb genes), and
tion is a part of a global circulation of hyper-virulent K. transcription regulation (kvgA). Multiple iron metabolism-
pneumoniae (Fig. 3). related and siderophore genes including ybt, irp, and fyuA
We then investigated the distribution of plasmid repli- were more common (statistical significance level for z-
cons and virulence factors in the Thai isolates. The pre- statistic of logistic regression: p value < 0.05) in clinical
dominant plasmid replicons were KpN3 and ColMG828 isolates and were incorporated into the chromosome.
and less frequently the R plasmid, all of which are The higher number of virulence factors in clinical ver-
known to carry multiple resistance and virulence genes sus environmental isolates (Additional file 2: Figure S2),
(Additional file 2: Figure S1). The majority of the global especially those involved in iron uptake, is suggestive of
K. pneumoniae isolates also harbored these plasmid hyper-mucoviscous and hyper-virulent strains that may
replicons (results not shown), indicating their global dis- be more efficient in iron uptake and capsule production
tribution. These replicons were present in isolates from [34]. Some virulence genes were integrated into the
both the environment and clinical samples (Additional chromosome while others were plasmid-mediated, im-
file 2: Figure S1). Of the 75 virulence factors considered, plying that multiple mechanisms mediate their acquisi-
10 were present in >95% of isolates, examples being the tion. Some virulence genes were also present in the
mrk genes encoding fimbrial biosynthesis proteins and genome of other gram-negative bacteria such as E. coli
iutA encoding ferric aerobactin receptor [32]. By con- and Citrobacter koseri, indicating sharing both within
trast, more than 40% of virulence genes were exclusively and between species. A full list of the virulence factors
Runcharoen et al. Genome Medicine (2017) 9:6 Page 7 of 10

150
Divergence (Year) 100
50
0

1330

1318

1966
101

661

307
307
307
323
307
307
307

231
231

656
ST

23
23
23
23
23
48
23
23
48
23
23
23
23

48

35
35
35
35

35
35
35

35
35
35
23
23

48
23
23
23
23
48
23
23
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
1st isolate country

Singapore
Singapore
Singapore
Singapore
Singapore
Singapore
Singapore
Singapore
Singapore
Australia
Australia
Australia

Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Thailand
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
Vietnam
2nd isolate country
Human infection
Human infection
Human infection

Human infection

Human infection

Human infection

Human infection
Human infection
Human invasive
Human invasive
Human invasive
Human invasive
Human invasive
Human invasive
Human invasive
Human invasive
Human invasive

Human invasive

Human invasive

Human invasive
Human invasive
Human invasive

Human invasive
Human carriage

Human carriage
2nd infection status*

-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Environmental

Environmental

Environmental
Environmental
Environmental
Environmental
Environmental
Environmental
Environmental
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical

Clinical

Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical

Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
Clinical
2nd origin status*
Environmental

Environmental
Environmental
Environmental
Environmental
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Environmental

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1st isolate isolation site**

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2nd isolate isolation site**
0.0
2.5
Geographical
distance (Km) ** 5.0
7.5
Fig. 4 Origin, sample type, and isolate features for divergences between a Thai isolate and any other isolate from the Thai or global collection for
non-clade 1 and 3 isolates over the past 50 years. This time corresponds to the formation of clade 1. To obtain the age and the upper and lower
bounds for the 95% confidence interval, we divided the SNP distance by the mean substitution rates of clades 1 and 3 and the means of the
lower and upper values for the 95 confidence intervals of the substitution rates estimated for clades 1 and 3. Each color corresponds to one
country. The symbols ** and * signify the specific features of the Thai and the global collection, respectively. The lower bar plot shows geographical
distance for Thai isolate pairs

with their frequencies in clinical and environmental and blaSHV had been sporadically gained by both environ-
isolates is provided in Additional file 3. mental and clinical isolates. Nineteen isolates (25%) were
With the exception of carbapenems, trimethoprim, tige- found to be multidrug-resistant (resistant to three or more
cycline, and aminoglycosides, the Thai isolates exhibited drug classes), all of which were clinical isolates. Four
intermediate to high resistance levels to the antibiotics isolates were resistant to the carbapenem drugs. Resist-
tested. This finding, along with a correlation between in- ance in these isolates was associated with the presence of
creased minimum inhibitory concentration (MIC) values plasmid-associated genes encoding carbapenamases, spe-
and antibiotics with a similar mechanism of action, is indi- cifically New Delhi metallo-β-lactamase (NDM) (in two
cative of a limited number of effective antibiotics to treat multidrug-resistant clinical isolates) and GES (in two non-
infections (Additional file 2: Figure S3 and Figure S4). All multidrug-resistant isolates from the hospital sewer).
isolates were ESBL-positive based on phenotypic testing. These genes appear to have been acquired in different
A genome-wide screen for known ESBLs as defined by the lineages across the phylogenetic tree (Additional file 2:
Comprehensive Antibiotic Resistance Database (https:// Figures S5 and S6). Isolation of Klebsiella oxytoca and
card.mcmaster.ca/) demonstrated that blaCTX-M-15, blaSHV, Enterobacter cloacae from hospital sewers that harbor
blaVEB, and blaGES accounted for the ESBL phenotypes in GES has been reported previously [35] and indirectly re-
the population. blaGES and blaVEB gene copies were found flects its presence in the hospital population or environ-
exclusively in the environmental hospital sewer isolates ment. Additional file 4 provides a list of β-lactamases and
and clinical isolates, respectively. By contrast, blaCTX-M-15 ESBLs in the collection.
Runcharoen et al. Genome Medicine (2017) 9:6 Page 8 of 10

Our results indicated that isolates with an increase in recent divergence events between clinical and environ-
MIC values and resistant phenotypes occurred in mental isolates, our results suggest that the selective
different lineages throughout the phylogenetic tree pressure imposed upon clinical isolates is sufficient to
(Additional file 2: Figure S4). However, the MIC values result in significant changes in the genome of clinical
for β-lactams (especially cephalosporins and aztreonam) isolates within a few decades. It has been reported
were significantly higher in clinical isolates compared previously that the prevalence of antibiotic resistance
with environment isolates (Additional file 2: Figure S5). of food-borne isolates is higher for meat-source K.
Consistent with this, clinical isolates carried more copies pneumoniae isolates than for human clinical isolates
of β-lactamase genes (Additional file 2: Figure S6). [16]. However, due to the lack of sufficient data about
Besides the chromosomally encoded blaLEN, blaSHV, and the strength of selective antibiotic pressure in food-
blaOKP that were present in every isolate, blaOXA , animal production versus hospitals, it is not possible
blaTEM, and blaCTX occurred throughout the tree, and to draw a definitive conclusion about antibiotic use
these genes, in combination with other β-lactamases, and resistance [16].
were more common in clinical isolates (Additional file 2: The detection of carbapenem-resistant isolates in pre-
Figure S6), which is consistent with reports from numer- treated hospital wastewater reiterates the importance of
ous countries. the treatment of hospital wastewater prior to release into
No patterns were observed in the presence/absence of the environment [40, 41]. Our study also highlights the
resistance genes for the non-β-lactam antibiotics in en- role of environmental water as a potential reservoir for
vironmental versus hospital isolates (Additional file 2: K. pneumoniae, where antibiotic resistant isolates may
Figure S6). The oqx efflux pump gene was present in emerge. Antibiotic resistance genes present in environ-
every isolate and was not correlated with ciprofloxacin mental isolates were present in the founder lineage in
resistance. However, non-synonymous SNP densities some cases, for instance, in isolates in the mixed envir-
within DNA topoisomerase IV genes (parE and parC) onmental and clinical clade 3 (Fig. 3 and Additional file
and point mutations in D87 DNA gyrase A, as well as in 2: Figure S3), which is consistent with contamination of
the E84 DNA topoisomerase IV genes, were exclusively such reservoirs. Resistance was also noted to have
present in two isolates with high MIC values for cipro- emerged in some environmental lineages against various
floxacin. Both mutations occurred in the quinolone antibiotics, for instance, ertapenem, cefoxitin, amikacin,
resistance-determining region (QRDR) of gyrA and parC and amoxicillin-clavulanic acid in sewage water isolates
[36, 37]. These point mutations were only found in clin- (Additional file 2: Figure S3), which presumably arises in
ical isolates, although both have been detected previ- response to antibiotics in environmental wastewater, as
ously in E. coli isolated from aquatic environments [38]. reported previously [42, 43]. Several studies have shown
The aminoglycoside resistance genes were noted to the presence of highly antibiotic-resistant bacteria and
have been acquired on multiple occasions throughout resistance genes in sewage released into aquatic environ-
the phylogenetic tree. Even though K. pneumoniae is ments [42, 44–46]. In line with these findings, our re-
reported to be intrinsically resistant to tetracyclines, sults suggest that the release of untreated hospital
the acquisition of further copies of tetracycline resist- sewage may play a role in the environmental emergence
ance genes occurred across the tree in both clinical and and spread of multiresistant pathogenic bacteria, and
environmental isolates (Additional file 2: Figure S6). that wastewater (including hospital waste) warrants
treatment to eliminate these organisms prior to release.
Discussion This may be of particular importance in low-income
In this study we investigated the epidemiology of K. rural areas and countries, where people are in greater
pneumoniae in a defined geographic area that included a contact with wastewater and may consume contaminated
general hospital and surrounding canals and farms. Our food and water containing high levels of antibiotic-
findings support the suggestion that clinical K. pneumo- resistant bacteria. Of note, wastewater is treated prior to
niae have evolved mechanisms to better adapt to sur- release from Bhuddhasothorn Hospital, and no ESBL-
vival in the clinical setting. Virulence factors were more positive K. pneumoniae were isolated from post-treated
frequent in clinical isolates and had been acquired on waste.
more than one occasion. This indicates the selection and
dissemination of virulent strains in hospitals. Further- Conclusions
more, the higher number of β-lactam resistance genes in In this study the availability of epidemiologic informa-
clinical isolates together with higher absolute MIC tion and the high resolution of whole genome sequen-
values for some β-lactams for K. pneumoniae of clinical cing allowed us to discover epidemiologic links between
origin can be attributed to higher exposure to antibi- clinical and non-clinical K. pneumoniae. Limitations of
otics, as proposed previously [39]. Given our finding of the collection were the sparseness of the environmental
Runcharoen et al. Genome Medicine (2017) 9:6 Page 9 of 10

collection and the lack of non-ESBL-producing strains. Availability of data and materials
This happened because our isolates were selected using Sequence data have been submitted to the European Nucleotide Archive
(ENA) (www.ebi.ac.uk/ena) under the accession numbers listed in Additional
media that were selective for ESBL production. The file 1: Table S1.
isolation of K. pneumoniae from highly contaminated
samples is challenging without the use of selective cul- Authors’ contributions
DM designed the genomic data analysis framework and developed scripts to
ture, but our approach means that the environmental analyze the data and to interpret the results. DM and CR undertook the
collection was biased towards clinically important iso- genomic analysis of the data. CR, SJP, and NC designed the sampling
lates, i.e., ESBL-producing strains. This facilitated the framework, and CR collected the isolates. SJP and NC were responsible for
managing the project. JP was responsible for managing the project at the
identification of distinct genomic patterns relating to the Wellcome Trust Sanger Institute, Hinxton, UK. DM, SJP, and NC wrote the
distribution of antimicrobial resistance and virulence paper. BB, SP, JT, and SA undertook laboratory work including phenotypic
factor genes in clinical isolates, but the inclusion of susceptibility testing and DNA extraction. All authors read and approved the
final manuscript.
non-ESBL isolates, particularly from environmental
sites, is required to obtain a broader assessment of clin- Competing interests
ical and non-clinical populations. The inclusion of sus- The authors declare that they have no competing interests.
ceptible isolates from the environment and hospital
Consent for publication
may reduce the difference in antibiotic resistance ob- Since there are no details on individuals reported within the manuscript, the
served here between clinical and environmental iso- consent for publication is not applicable.
lates, although the effect on virulence gene pattern is
Ethics approval and consent to participate
difficult to predict. Future studies based on larger and The study was approved by the Ethics Committee of Bhuddhasothorn
deeper collections will be required to gain a detailed Hospital (BSH-IRB007/2558) and the Faculty of Tropical Medicine, Mahidol
understanding of global transmission of K. pneumoniae University (MUTM 2014-086-01). The research followed the principles of the
Helsinki Declaration. Written informed consent was obtained from the partic-
at different geographical scales. ipants. All patient information was anonymised at source and unique ID
codes were used to identify cases.

Additional files Author details

1
Department of Microbiology and Immunology, Faculty of Tropical Medicine,
Additional file 1: Table S1. Supplemental Table S1, which includes Mahidol University, Bangkok 10400, Thailand. 2Wellcome Trust Sanger
accession numbers and the metadata for the studies on isolates here. Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, UK.
3
(CSV 33 kb) Department of Medicine, University of Cambridge, Addenbrooke’s Hospital,
Box 157Hills Road, Cambridge CB2 0QQ, UK. 4Division of Clinical
Additional file 2: Figures S1–S6. Figures and descriptions of Microbiology, Medical Technology Department, Buddhasothorn hospital,
Supplemental Figures S1–S6 mentioned throughout the manuscript. Chachoengsao 24000, Thailand. 5Mahidol-Oxford Tropical Medicine Research
(DOCX 1927 kb) Unit, Faculty of Tropical Medicine, Mahidol University, Bangkok 10400,
Additional file 3: Table S2. Supplemental Table S2, which includes the Thailand. 6London School of Hygiene and Tropical Medicine, London WC1E
list of putative virulence factor genes. (CSV 9 kb) 7HT, UK.
Additional file 4: Table S3. Supplemental Table S3, which includes the
list of β-lactamase genes and ESBLs. (CSV 5 kb) Received: 11 August 2016 Accepted: 3 January 2017

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