RESEARCH ARTICLE
Proteomic variation and diversity in clinical
Streptococcus pneumoniae isolates from
invasive and non-invasive sites
Mustapha Bittaye*, Phil Cash, Ken Forbes
School of Medicine, Medical Sciences & Nutrition, University of Aberdeen, Aberdeen, United Kingdom
* r02mb14@abdn.ac.uk, mustaphabittaye@yahoo.com
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OPEN ACCESS
Citation: Bittaye M, Cash P, Forbes K (2017)
Proteomic variation and diversity in clinical
Streptococcus pneumoniae isolates from invasive
and non-invasive sites. PLoS ONE 12(6):
e0179075. https://doi.org/10.1371/journal.
pone.0179075
Editor: Paulo Lee Ho, Instituto Butantan, BRAZIL
Received: March 2, 2017
Accepted: May 23, 2017
Published: June 2, 2017
Copyright: © 2017 Bittaye et al. This is an open
access article distributed under the terms of the
Creative Commons Attribution License, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the original
author and source are credited.
Abstract
Streptococcus pneumoniae is responsible for a variety of invasive and non-invasive human
infections. There are over 90 serotypes of S. pneumoniae differing in their ability to adapt to
the different niches within the host. Two-dimensional gel electrophoresis was used to discriminate clinical S. pneumoniae isolates recovered from either blood cultures (invasive site
isolates) or other sites, including sputum, tracheal aspirate, ear, eye and skin swabs (noninvasive site isolates). Global protein expression profiles for five invasive site and six noninvasive site isolates representing five different serotypes (serotypes 4, 6, 9, 14 and 23)
were obtained for each isolate and combined into a single data set using Progenesis SameSpots™ software. One-hundred and eighty six protein spots (39% of the protein spots in
the dataset) differed significantly (ANOVA, p<0.05) in abundance between the invasive site
(101 upregulated protein spots) and non-invasive site (85 upregulated protein spots) isolates. Correlations between the bacterial proteomes and their sites of isolation were determined by Principal Component Analysis (PCA) using the significantly different protein spots.
Out of the 186 variable protein spots, 105 exhibited a serotype-associated pattern of variability. The expression of the remaining 81 protein spots was concluded to be uniquely
linked to the site of bacterial isolation. Mass spectrometry was used to identify selected protein spots that showed either constant or differential abundance levels. The identified proteins had a diverse range of functions including, capsule biogenesis, DNA repair, protein
deglycation, translation, stress response and virulence as well as amino acid, carbohydrate,
lipid and nucleotide metabolism. These findings provide insight on the proteins that contribute towards the adaptation of the bacteria to different sites within the host.
Data Availability Statement: All relevant data are
within the paper and its Supporting Information
files.
Funding: Mustapha Bittaye is a PhD student
funded by the Medical Research Council Unit, The
Gambia. The funders had no role in study design,
data collection and analysis, decision to publish, or
preparation of the manuscript.
Competing interests: The authors have declared
that no competing interests exist.
Introduction
Streptococcus pneumoniae (also known as the pneumococcus) is a significant human pathogenic bacterium that remains a leading cause of morbidity and mortality worldwide. The
pneumococcus is the principal bacterial cause of community-acquired pneumonia and acute
otitis media as well as being associated with several other non-invasive infections including
sinusitis and conjunctivitis [1]. The human nasopharynx is the natural ecological niche of the
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
Abbreviations: 2-DE, two-dimensional gel
electrophoresis; LC-MS, liquid chromatographymass spectrometry; PCA, Principal Component
Analysis.
bacterium, where it exists asymptomatically in a carrier state. Migration of the bacterium
across the respiratory epithelium into the blood system and eventually the cerebro-spinal fluid
(CSF) leads to the development of severe life-threatening, invasive pneumococcal diseases
(IPDs) such as sepsis and meningitis [2]. Worldwide, pneumococcal infections are responsible
for the deaths of 1.6 million people annually [3]. Young children, particularly in low-income
countries, the elderly, the economically deprived as well as those with HIV/AIDS bear a disproportionate share of the disease burden. The highest mortality due to pneumococcal infection occurs in patients who develop pneumococcal sepsis and meningitis [4]. Immunization
and antimicrobial therapy are the cornerstones for the prevention and management of pneumococcal infections. However, the lack of a universal vaccine against the many circulating
pneumococcal serotypes, as well as the widespread prevalence of antibiotic resistance, present
specific challenges for disease control and management [5]. These obstacles are compounded
further by a lack of rapid, sensitive, and specific diagnostic tests for IPD.
S. pneumoniae is a genetically diverse species that exists in many different capsular and
sequence types. The ability of the bacterium to cause either invasive disease or localised infections varies markedly between individual isolates. This pathogenic variability is influenced by
both the bacterial capsular serotype and genetic background [6,7]. Moreover, the bacterial site
of isolation has also been shown to influence the virulence behaviour displayed by the bacterium [8,9]. Comparative studies on the available genome sequences of S. pneumoniae isolates
identified core genes that are common to all isolates as well as accessory regions comprising
variable genes that correlate with virulence phenotype. Both the core genome and regions of
diversity encode virulence determinants whose expression varies according to the bacterial
serotype and sites of infection [6,7]. This dynamic nature of the pneumococcal expression of
virulence factors in different host niches has been investigated in recent years using comparative transcriptomics. Both Ogunniyi et al. [8] and Orihuela et al. [9] reported niche-specific
differences in the transcriptional profiles of pneumococci recovered from the nasopharynx,
lung and blood following intranasal infection of mice. However, these transcript profiling
studies have been carried out on commonly used laboratory-adapted S. pneumoniae strains, in
mice, and cannot consider the expression levels of the related proteins and their post-translational modifications.
The comparison of pathogenic microorganisms at the proteomic level provides complementary data to those obtained using nucleic acid based methods. The availability of complete
genome sequences for many virulent and avirulent strains of S. pneumoniae provides the
basis for in depth investigations of the pneumococcal proteome, particularly for studies on
pneumococcal pathogenesis [5]. To date, several proteomic studies on S. pneumoniae have
been reported that focus primarily on identifying potential virulence determinants expressed
by laboratory type strains of pneumococcus grown in vitro under conditions that mimic specific host environments [10–13]. However, less attention has been paid towards comparative
proteomic analyses of clinical S. pneumoniae isolates recovered from different host niches in
order to identify markers correlating with specific-disease phenotypes as well as obtaining
information on pathogenic differences arising from strain variation.
In the following study, a global comparative proteomics approach using two-dimensional
gel electrophoresis (2-DE) based protein profiling was employed to differentiate invasive and
non-invasive site clinical S. pneumoniae isolates. The combination of 2-DE coupled with mass
spectrometry (MS) for protein separation and identification respectively, have been extensively
employed to study the pathogenesis for a number of important human bacterial pathogens
[14–17]. In this study, we compared invasive site pneumococcal isolates recovered from blood
cultures with non-invasive site isolates recovered from various mucosal surfaces (sputum, tracheal aspirate, ear, eye and skin swabs), in order to investigate the proteome variation and
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
diversity associated with the pneumococcal isolates from the two infection sites. Despite the
extensive heterogeneity found for the pneumococcal isolates, it was possible to discriminate
the invasive and non-invasive site isolates on the basis of their 2-dimensional (2-D) protein
profiles. Moreover, the proteins that displayed relatively constant abundance levels across the
pneumococcal isolates could in the long run be investigated for inclusion in the pipeline of
potential vaccine markers. Thus, the pan proteomic analysis of multiple pneumococcal isolates
recovered from invasive and non-invasive sites of infection is a valuable approach for identifying proteins involved in pneumococcal colonisation and virulence.
Results
Growth of S. pneumoniae in BHI-FCS broth
To optimise the bacterial culture conditions for the analysis of the pneumococcal cellular proteins, representative isolates were grown in BHI-FCS broth and assayed for bacterial cell density and viability as described in the Materials and methods section. The growth curves for
two invasive site isolates (B03 and B162) and two non-invasive site isolates (E40 and E65) are
shown in Fig 1. Under the experimental conditions used, the four pneumococcal isolates
showed similar growth characteristics with the lag-phase for each isolate lasting at least 2 h
(Fig 1A), which was followed by an increase in the bacterial cell density. All of the isolates
reached their maximum cell density at 8 h post-inoculation followed by a decline in cell density thereafter. The cell viability followed a similar pattern as cell density, although no clear lag
phase was identifiable (Fig 1B). Based on these data, the bacterial cells were routinely collected
once the inoculated cultures had reached an OD650 of 1.0 to ensure that sufficient biomass
(approximately 3 x 107 CFU/mL) was obtained for subsequent proteomic analysis.
Comparison of the pneumococcal 2-D protein profiles
To identify those pneumococcal proteins that differed significantly in abundance levels
between the invasive and non-invasive site isolates, the isolates were classified into two groups
according to their site of isolation (“invasive site” or “non-invasive site”) (Table 1). The cellular
proteins for each of the pneumococcal isolates shown in Table 1 were prepared and analysed
for 3 biological replicates; representative 2-D protein profiles for each isolate are presented in
S1 Fig. Following a manual review of the spot detection data, a total of 483 protein spots was
detected for the 33 matched 2-D protein profiles comprising triplicate 2-D gels for each of the
11 clinical pneumococcal isolates. The majority of the detected protein spots had isoelectric
points (pI) between 4.5 and 6 and molecular weights (Mr) range between 20 kDa to 55 kDa.
Principal Component Analysis (PCA) was used to determine the degree of variation between
the pneumococcal isolates and to identify those proteins that discriminated the two groups.
PCA failed to differentiate the invasive and non-invasive site pneumococcal isolates when
all of the 483 detected protein spots were used for the analysis (data not shown). Based on the
study of Smith et al. [15] PCA using those protein spots (186 protein spots) which differed significantly (ANOVA, p<0.05) in abundance between the two groups of pneumococcal isolates
clearly discriminated the two groups of isolates (Fig 2A). The PCA showed that the expression
profiles of 101 and 85 protein spots defined the invasive and non-invasive S. pneumoniae isolate groups respectively. These discriminatory protein spots (101 and 85 in the invasive and
non-invasive groups respectively) showed high abundance levels in the respective groups.
Based on the clustering of the 2-D protein profiles, those pneumococcal isolates within the
invasive site group appeared to be more heterogeneous at the proteomic level than those isolates within the non-invasive site group (Fig 2A).
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
Fig 1. Characteristic growth and viability curves of representative S. pneumoniae isolates in BHI-FCS
broth. (A) Measurement of the bacterial cell density (B) Measurement of bacterial viability.
https://doi.org/10.1371/journal.pone.0179075.g001
Table 1. Clinical S. pneumoniae isolates used in the study.
Isolate Category
Invasive
Non-invasive
Isolate ID
Serotype
Site of Isolation
B03
14
Blood culture
B40
4
Blood culture
B154
6
Blood culture
B162
9
Blood culture
B269
4
Blood culture
E22
23
Eye swab
E35
14
Sputum
E40
14
Skin swab
E47
23
Sputum
E65
9
Ear swab
E107
6
Tracheal aspirate
https://doi.org/10.1371/journal.pone.0179075.t001
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
Fig 2. Principal component analysis of the 2-D gel data. The PCA graphs displayed the clustering of the bacterial isolates
grouped according to their (A) sites of isolation and (B) capsular serotype. The PCA was plotted using those protein spots that
differed significantly in abundance levels (ANOVA, p<0.05) between isolates in the classified groups.
https://doi.org/10.1371/journal.pone.0179075.g002
The eleven pneumococcal isolates analysed in this study represented five different serotypes
(Table 1). Since capsular serotype plays a key role in pneumococcal pathogenesis [18], it was
possible that the capsular serotypes might contribute towards the discrete groups identified
above by PCA (Fig 2A). To test this, the 2-D gel images were grouped according to the pneumococcal serotypes, producing five groups. Two hundred and sixty six protein spots were
identified that showed significant differences (ANOVA, p<0.05) in abundance between the
five groups and PCA discriminated the isolates on the basis of serotype (Fig 2B). The pneumococcal isolates of serotypes 4, 6 and 23 formed separate, unique clusters, whereas serotypes 9
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
Fig 3. S. pneumoniae proteins showing constant and differential expression between the invasive and non-invasive site isolates.
https://doi.org/10.1371/journal.pone.0179075.g003
and 14 formed a fourth cluster within the analysis (Fig 2B). The pneumococcal isolates collected from the two general host niches indicated in Table 1 were distributed across each of the
four clusters identified in Fig 2B.
Within the complete dataset of 483 protein spots, a greater proportion of the protein spots
differed in abundance among the serotypes (266, 55%) than between the sites of isolation (186,
38.5%). Eighty-one of the proteins that exhibited significant differences between the sites of
isolation were not significantly different among the serotypes. These 81 proteins spots, which
uniquely discriminated the pneumococcal isolates by site of isolation (i.e. that conferred no
serotype variability), were of particular interest since they might play a role in the colonisation
and invasion of specific niches within the host during infection. Nineteen of these protein
spots were identified by LC-MS (Fig 3); 12 of the protein spots showed increased abundances
in the invasive site isolates and 7 protein spots showed the highest abundance in the non-invasive site isolates (Fig 3).
Identification of S. pneumoniae proteins
Forty selected protein spots that were either constant or variable in abundance between the
invasive and non-invasive site isolates were successfully identified by liquid chromatographymass spectrometry (LC-MS) against known S. pneumoniae proteins, based on significant
MASCOT scores. The identified protein spots represented 32 unique pneumococcal proteins
(Figs 3 and 4). Thirty-six of the identified protein spots were significantly different (ANOVA,
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
Fig 4. Annotated 2-DE protein profiles of an invasive site and non-invasive site pneumococcal isolate. Displayed are representative 2-DE
protein profiles of the pneumococcal total cellular proteins extracted from an (A) invasive site isolate (B03) and a (B) non-invasive site isolate (E35)
showing the pH range and the location of the molecular weight marker proteins. Protein spots, identified by LC-MS, are indicated using the Progenesis
SameSpots™ assigned spot numbers.
https://doi.org/10.1371/journal.pone.0179075.g004
p<0.05) in abundance between isolates for the two sites whereas 4 proteins (DnaK, SpxB, RplJ
and Eno) showed no significant differences in abundance. Fold differences between the highest
and lowest mean normalised volumes for the differentially expressed protein spots identified
using the invasive group as a reference ranged between 0.25 to 4.0 (Fig 3). The normalised volumes of the protein spots for the identified proteins across the full series of 2-D gels are presented in the form of a heat map diagram in Fig 5. Twenty of the differentially expressed
proteins identified were predominantly abundant in the invasive site isolates and 16 proteins
showed the highest abundance in isolates from the non-invasive sites (Fig 3).
The migration of proteins in 2-DE gels can be altered by protein post-translational modifications (such as phosphorylation, glycosylation, acetylation and proteolysis) as well as
degradation products and covalent reaction intermediates. These processes in addition to
alternative splicing of mRNA and single-point mutations could also result in the generation of
protein isoforms, in which protein products of the same gene have different observed Mr and
pI. Four of the differentially expressed identified proteins were each present as two protein
spots exhibiting different migrations consistent with them being isoforms of the same protein,
which included Gor (Spots 890 and 894), LacB (spot 1639, 2182), LctO-2 (spots 944, 2159) and
Ssb (spots 2170 and 2175) (Fig 3). Two protein spots (spots 1635 and 1675) with increased
abundances in the invasive group were identified as Gap. However, the proteins observed Mr
and pI values were significantly different from the corresponding values for Gap (Fig 3).
Inspection of the identified peptides for Gap (S1 Table) indicates that they are derived from
the N-terminus of the protein. This would be consistent with the protein spots identified as
Gap being proteolytic degradation products of the intact protein. However, this was not the
case for the protein spot identified as Eno, since the identified peptides were distributed
throughout the intact Eno protein sequence (Fig 3, S1 Table). Consequently, the reason for
the migration of the protein at an observed Mr of 15 kDa rather than the predicted 47 kDa is
unknown.
The proteins were assigned to a number of functional groups, which included capsule biogenesis, DNA repair, protein deglycation, translation, stress response, virulence as well as
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Fig 5. A heat map representation of the 40 protein spots identified by LC-MS. The identified protein spots showing conserved and differential
abundance levels between the invasive and non-invasive site isolates were plotted on the heat map using the normalised spot volumes of the replicate
gels of each isolate in the invasive and non-invasive group. The gene locus numbers are based on the publicly available S. pneumoniae TIGR4
genome annotation.
https://doi.org/10.1371/journal.pone.0179075.g005
amino acid, carbohydrate, lipid, and nucleotide metabolism. Those proteins with unknown
functions including both hypothetical and conserved hypothetical proteins represented
13% of the identified differentially expressed proteins. Proteins predicted by PSORTb to
be localised in the pneumococcal cell envelope (i.e. membrane and extracellular proteins)
represented 8% of the identified differentially expressed proteins and all had significantly
(ANOVA, p<0.05) higher abundances in the invasive site isolates compared to the non-invasive site isolates (Fig 3).
Discussion
Proteomics is used extensively to characterize and compare the proteomes of pathogenic bacteria in order to understand infection mechanisms. In the present study, the comparison of
clinical pneumococcal isolates by 2-DE protein expression profiling, has identified proteins
associated with pneumococcal strain variability and site of infection. The selection of the bacterial isolates for analysis was primarily based on the bacterial sites of isolation, however, the
serotypes (serotypes 4, 6, 9, 14 and 23) of the selected isolates are also clinically significant
apropos of their disease potential, widespread geographical prevalence and antibiotic resistance [19,20]. The growth characteristics of the bacteria in BHI-FCS broth was studied to
ensure standard in vitro growth conditions were used to avoid previously documented growth
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
effects on proteome [13,21] and to ensure sufficient material were obtained for the proteomic
analysis.
This report demonstrates that clinical S. pneumoniae isolates recovered from different
sites within the host show characteristic cellular proteomes. Similar observations have been
reported from proteomic analyses of E. coli and H. pylori [15–17]. Proteomic discrimination
of invasive and non-invasive site isolates was due to the differential expression of 186 protein
spots: 101 invasive site and 85 non-invasive site protein spots. Eighty one of these protein
spots that were unique in discriminating the isolates by site of isolation provide an opportunity
for determining the key activities of the bacteria that define the bacterial adaptation in blood
and non-invasive sites of infection. Moreover, the clustering of the 2-D protein profiles
revealed a greater heterogeneity among isolates in the invasive group compared to their noninvasive counterparts. This variability could be attributed to the differential adaptation of the
bacteria to the challenging environment of the blood probably due to differences in the bacterial serotypes. Growing evidence suggests that pneumococci with different serotypes differ in
their invasiveness [22,23]. Thus, the proteomic data presented in the current study could serve
as a basis for defining the proteins that contribute to this variability.
Analysis of the bacterial protein profiles by PCA, according to the bacterial serotypes
revealed the relatedness of the bacterial isolates as well as those proteins that displayed a serotype-specific pattern of expression. These proteomic data indicated a clustering of the isolates
belonging to serotypes 9 and 14. This observation agrees with previous studies that used multilocus sequence typing to demonstrate that some pneumococcal serotype 14 isolates are variants of the 9V clone, especially on the basis of their antibiotic resistance profiles [24–26]. This
suggests that the discrimination of the pneumococcal isolates by PCA may also reflect other
phenotypic features of the bacteria such as antibiotic resistance.
Moreover, a higher number of proteins differed among the serotypes analysed compared to
the isolation sites, indicating the high degree of diversity that exist among pneumococcal isolates [27,28]. Out of the 186 differentially expressed protein spots that discriminated the invasive and non-invasive site isolates, 105 proteins also differed among the pneumococcal isolates
on the basis of their serotypes. These strain variable proteins can provide useful insights into
defining the pathogenic variation that exists among clinical S. pneumoniae isolates.
Forty protein spots corresponding to 32 unique proteins were identified by LC-MS and
functionally classified using the KEGG database. Metabolic proteins accounted for 50% of the
differentially expressed proteins identified and the majority of these were involved in carbohydrate and nucleotide metabolisms. The ability of bacteria to respond to the diverse environments within the host is essential for their survival and metabolic proteins, particularly those
involved in stress response and carbohydrate utilization, are central to pathogen infectivity
[29–32].
One of the metabolic proteins identified as being upregulated in the invasive isolates was
thioredoxin reductase (spot 1188). This enzyme is an ubiquitous antioxidant that plays an
important role in the bacterial defence against extracellular oxidative stress and protects
proteins from degradation or inactivation by reactive oxygen species (ROS) [33]. The
enzyme acts by directly reducing oxidised cysteine or providing reducing equivalents to
methionine sulfoxide reductase (Msr) enzymes, which reduce oxidized methionines [34,35].
Thioredoxin reductase enzymes have been extensively studied in E. coli where they play an
anti-inflammatory role by suppressing neutrophil chemotaxis [36]. In the present study,
there was a 1.6-fold increase in thioredoxin reductase abundance in the invasive compared
to the non-invasive site isolates and the increased levels of ROS produced by host defences,
such as the lactoperoxidase system, may account for the high levels of this protein in invasive site pneumococci.
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
The carbohydrate metabolic proteins, LacA (spot 1752) and LacB (spots 1639, 2182)
showed 1.4- to 2.4-fold increase in abundance in the non-invasive site isolates. Glucose levels
in the blood are generally higher than at other host sites infected by S. pneumoniae [31]. To
thrive in low glucose host niches, pneumococci have developed metabolic mechanisms for
pursuing alternative energy sources. Both LacA and LacB are involved in the tagatose-6-phosphate pathway, which is important for the utilization of galactose and lactose [37]. The expression of both enzymes is regulated by a global protein regulator, catabolite control protein A
(CcpA; spot 2187), through a regulatory process called carbon catabolite repression. CcpA,
which represents an important virulence determinant and metabolic regulator of sugar in S.
pneumoniae [38,39] was upregulated in the non-invasive site isolates in this study. This protein
was also detected with a Mr and pI that differed significantly from the predicted values for Mr
and pI, suggesting it might undergo post-translational modification. Iyer and colleagues implicated CcpA in pneumococcal fitness during mucosal tissue infection by showing that ccpA
mutant bacteria were attenuated in nasopharyngeal colonisation and infection of the lungs in
murine models [39].
The capsular polysaccharide (CPS) biosynthesis protein, tyrosine-protein kinase (CpsD),
was increased in abundance in the invasive site isolates. The regulation of CPS production
through phosphorylation of the tyrosine residues in CpsD is crucial for the virulence of S.
pneumoniae in mice [40,41]. S. pneumoniae undergoes spontaneous phase variation in CPS
expression between an opaque and transparent form. The opaque phase is associated with
increased capsule production and predominates in the blood [42]. The CpsD protein identified
in the present study has a pI of 6.49 which differed from the theoretical pI of 8.96, thus suggesting a modification of the protein potentially by phosphorylation [43]. Tyrosine phosphorylated
CpsD acts in concert with other CPS proteins (CpsB and CpsC) to regulate the assembly,
transport and attachment of CPS to the pneumococcal cell wall [40,41,44,45]. According to
Morona et al., [44,45] tyrosine phosphorylation of CpsD negatively regulates CPS production.
In addition CpsD-deficient S. pneumoniae D39 bacteria produced a significant amount of
CPS, but were unable to cause bacteremia in a murine model. However, Bender and colleagues
[40] associated high levels of phosphorylated CpsD with increased CPS production in the S.
pneumoniae D39 strain. Despite these contrasting findings on the precise role of tyrosine phosphorylation in the regulation of CPS production in S. pneumoniae D39 strain, the increased
abundance of CpsD in the invasive site isolates in our study suggests a potential role in increasing CPS production. This proposal is consistent with the findings of the many studies that
reported an association of increased CPS production with S. pneumoniae isolated from invasive human infections such as bacteraemia, sepsis and meningitis [42,46–48].
Among the proteins that showed no differences in abundance between the pneumococcal
isolates were several proteins with well-documented roles in pneumococcal virulence and
pathogenesis. These included the stress response proteins, DnaK and SpxB and the “moonlighting protein”, Eno. Both Eno and SpxB can induce protective immune responses in mouse
infection models and could serve as potential immunogens for inclusion in a pneumococcal
protein-based vaccine [49]. Although the pneumococcal DnaK protein has been considered as
a vaccine candidate [50] it induces only a weak immune response in mice [49]. The low antigenicity of DnaK was due to the lack of surface-exposed epitopes on live intact pneumococcal
cells [51]. PSORTb analysis of the inferred protein amino acid sequence derived from the UniProt database indicated DnaK to be of cytoplasmic origin.
The data presented in this study have demonstrated the potential of proteomics to not only
discriminate clinical S. pneumoniae isolates recovered from invasive and non-invasive sites in
the host, but also to identify candidate proteins that may be implicated in these two different
aspects of the biology of S. pneumoniae. However, establishing the relationship between
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
differential patterns of bacterial protein synthesis and the clinical phenotypes requires the
inclusion of more pneumococcal isolates representing other serotypes and sites of isolation
such as CSF, although isolates from these different niches may well have their own specific
protein requirements. The proteomic analyses used in this study were biased towards the cytoplasmic proteins as evident by the small number of extracellular proteins identified. Given the
significance of extracellular proteins in pneumococcal virulence and as potential vaccine antigens, their selective recovery and analysis will provide improved proteomic coverage to define
further the clinical phenotypes. Further characterisation and confirmation of the proteins’ variation will be required using complementary techniques (for example by Western blotting or
qPCR), although these approaches have limitations when investigating variable clinically relevant bacterial isolates as discussed elsewhere [15]. These difficulties will be increased in studies
of genetically diverse bacteria such as S. pneumoniae. Nevertheless, the data presented above
demonstrate the capacity of proteomics to differentiate clinical S. pneumoniae isolates according to their sites of isolation and to identify some of the proteins involved, and will lead to a
better understanding of this significant human pathogen as well as the identification of new
diagnostic and therapeutic markers.
Materials and methods
Origin of S. pneumoniae isolates
The S. pneumoniae isolates used in this study were selected from a collection of clinical pneumococcal isolates available from Aberdeen Royal Infirmary, Scotland; information was
available on the isolate serotypes and sites of isolation [52]. The S. pneumoniae isolates characterised in the following study were isolated from “invasive” (blood) and “non-invasive”
(sputum, tracheal aspirate, ear, eye and skin swabs) sites and included 5 different capsular
serotypes of pneumococcus (Table 1). The bacterial isolates were originally serotyped by the
Scottish Pneumococcal Reference Laboratory, Stobhill Hospital, Glasgow, United Kingdom,
by coagglutination [53]. All of the S. pneumoniae isolates were stored at -70˚C in microorganism preservation vials, PROTECT™ (Technical Service Consultants Ltd, Lancashire, UK) and
recovered as described in the following section. The bacteria were grown on a blood agar plate
together with a 5 μg Optochin disk to confirm their identity as S. pneumoniae by optochin sensitivity. The serotypes of the recovered isolates were confirmed by molecular serotyping as
described in the Materials an methods section.
Growth of S. pneumoniae isolates
Viable bacteria were recovered from the storage medium by inoculation onto 5% Columbia
Blood Agar plates (E & O Laboratories Ltd, Bonnybridge, Scotland), and incubated at 37˚C for
2–3 days in an anaerobic jar containing a CampyGen™ gas pack (Oxoid Ltd, Basingstoke, UK)
for the generation of a microaerophilic atmosphere (5% Oxygen, 10% Carbon dioxide, and
85% Nitrogen). Between 20 and 30 S. pneumoniae colonies were passaged initially into 10 mL
Brain Heart Infusion (BHI) broth (Oxoid, UK) supplemented with 5% (v/v) Foetal Calf Serum
(FCS). The inoculated BHI-FCS broth medium was incubated stationary at 37˚C for 15 h in an
anaerobic jar containing a CampyGen™ gas pack. In order to generate a sufficient number of
bacterial cells for the analysis of S. pneumoniae cellular proteins, a subculture in BHI-FCS
broth from the first bacterial passage was performed. Briefly, 3 mL of bacterial suspension
from the 10 mL broth culture (OD650 of 1.2) was added into 20 mL fresh BHI-FCS broth to
give a starting OD650 of 0.1 and incubated stationary at 37˚C under a microaerophilic atmosphere until an OD650 of 1.0 was reached.
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Monitoring the growth of S. pneumoniae isolates in vitro
The bacterial growth and viability were determined as follows. The S. pneumoniae isolates
were grown in 20 mL BHI-FCS broth at 37˚C in two independent biological replicates as previously described. Optical density measurements at 650 nm wavelength (OD650) were taken at 2
h intervals between 0 h and 16 h post-inoculation to determine the bacterial cell density. Serial
10-fold dilutions of the growth media ranging from 10−1 to 10−7 were prepared at times postinoculation shown in Fig 1B to determine the bacterial viability. Five microliters of each dilution were plated onto blood agar plates and colony counts determined after 15 h incubation of
the agar plates at 37˚C in an anaerobic jar containing a CampyGen™ gas pack.
Molecular capsular typing
The serotypes of the pneumococcal isolates used in this study were confirmed by PCR using
primers published by the Centre for Disease Control (http://www.cdc.gov/streplab/pcr.html)
shown in S2 Table. Bacterial DNA was extracted from one blood agar plate showing a confluent growth of bacteria by a boiling method. Briefly the bacterial cells were resuspended in 1
mL of molecular grade water and washed twice by centrifugation at 14000 x g for 10 min. The
cell pellet was resuspended in 200 uL of molecular grade water and incubated in a boiling
water bath for 10 min. The sample was cooled in ice for 5 min and then clarified at 14000 x g
for 10 min. The extracted bacterial DNA was used in a duplex PCR reaction for the simultaneous detection of the serotype-specific genes and the pneumococcal capsular wxg gene,
which was used as a positive control. Each 25 uL PCR reaction contained 12.5 uL of 2X
MyTaq™ Red Mix (Bioline, UK), 500 nM of each primer and 25 ng bacterial DNA and was
amplified using a GeneAmp™ PCR System 9700 thermal cycler (Applied Biosystems, USA)
according to the following thermal cycling steps: 95˚C for 5 min; 35 amplification cycles of
94˚C for 30 s, 54˚C for 1 min, and 72˚C for 1 min; and a final extension step at 72˚C for 7 min.
The PCR products were separated on a 3% (w/v) Agarose LE gel (Sigma-Aldrich, UK) containing 10 uL of SYBR1 Safe DNA gel stain (Thermo Fisher Scientific, UK) at 110 volts for 45 min
and visualised using a UV illuminator.
Extraction of total bacterial cellular proteins and analysis by 2-DE
Whole cell protein extracts were prepared from three independent cultures of each pneumococcal isolate prepared as previously described. The bacterial cells were pelleted from the culture media by centrifugation at 2500 x g for 10 min and washed twice with sterile PBS. The cell
pellets were resuspended in lysis buffer (7 M urea, 2 M thiourea, 4% (w/v) CHAPS, 0.3% (w/v)
DTT, 1% (v/v) IPG buffer, pH gradient 4–7) (GE Healthcare, Buckinghamshire, UK) and incubated with lysozyme (10 μg/μL) and a nuclease cocktail containing DNase I (3 μg/μL) and
RNase A (1.5 μg/μL) (Sigma-Aldrich, St. Louis, USA) for 30 min on ice. The enzyme treated
cell suspensions were then frozen overnight at -20˚C to enhance cell disruption. The treated
cell suspensions were sonicated six times by continuous pulse at 90% power for 30 s each using
an Ultrason 250 Sonicator (LabPlant, UK) fitted with a microprobe. To minimise protein degradation by proteolysis, the cell lysates were cooled for 30 s on ice between each pulse of sonication. Finally, the cell lysates were clarified at 16200 x g for 10 min and the soluble proteins in
the supernatants concentrated using the ReadyPrep™ 2-D Cleanup Kit (Bio-Rad Laboratories
Ltd, Hertfordshire, UK) according to the manufacturer’s instructions. The protein concentrations were determined by RC DC Protein assay using BSA (Bio-Rad Laboratories, Hercules,
USA) as the standard. The bacterial proteins (100 μg) were analysed by 2-DE using small format 2-DE gels according to the protocol described by Cash and Argo [54]. The proteins were
separated on 7 cm IPG gel strips (Bio-Rad Laboratories Ltd, Hertfordshire, UK) with a pH
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
gradient of 4–7 in the first dimension and the second dimension separation was carried out on
12% single concentration polyacrylamide slab gels (Bio-Rad Laboratories Ltd, Hertfordshire,
UK). The resolved proteins were detected by Colloidal Coomassie Blue G250 staining as
described by Cash and Argo [54].
Imaging and analysis of the 2-DE protein profiles
The 2-DE protein profiles were scanned at 600 dpi using an Image Scanner III (GE Healthcare
Ltd, UK) supported by Labscan software. The 16 bit gel image files were transferred to the
Progenesis SameSpots™ software, version 4.5 (Nonlinear Dynamics, Newcastle, UK) for spot
detection and analysis as a single data set according to the method described by Smith et al.
[15]. Briefly, gel images representing three biological replicates for each bacterial isolate were
reviewed and cropped as required. A reference gel image was selected for the data set of 2-DE
gel images. The remaining gels were sequentially matched against the reference gel and spots
on the 2-DE profiles were detected and transformed into normalised abundances using the
inbuilt routines provided by the Progenesis SameSpots™ software. The detected spots were
automatically assigned numbers by the software and these are used to refer to the spots in the
text. Statistical differences in normalised spot abundance between the groups were detected
by ANOVA (p<0.05) using the software’s statistical package. Further analysis of the data by
Principal Component Analysis (PCA), using the inbuilt software routines was carried out as
described by Smith et al. [15]. Fold-differences in the mean normalised protein spot volumes
between the invasive and non-invasive site isolates were calculated relative to the values for the
invasive group, which was used as a reference.
In-Gel protein digestion
Protein spots, selected according to the criteria described in the Results section, were excised
as 1 mm diameter gel plugs from dried Coomassie Blue stained 2-DE gels and transferred into
a 96 well reaction plate for in-gel digestion using a ProGest digestor robot (Genome solutions,
Huntingdon, UK). The gel plugs were first equilibrated in water, destained with acetonitrile
and then sequentially washed in 25mM ammonium bicarbonate (AMBIC), acetonitrile and 50
mM AMBIC. The gel pieces were finally dehydrated with acetonitrile and the cysteine residues
of the proteins reductively alkylated by incubating for 10 mins at 60˚C in 30 μL reducing solution (10 mM dithiothreitol in 50 mM AMBIC), followed by incubation at room temperature
(RT) for 15 min in 30 μL alkylating solution (55 mM iodoacetamide in 50 mM AMBIC). This
was followed by washing and drying of the gel pieces with 50 mM AMBIC and acetonitrile
respectively. The proteins within the gel pieces were digested with 15 μL trypsin (20 ng/μl in
sequencing grade water, Promega, UK) for 8 h at 37˚C. The peptide digests were eluted in a
mixture of 10% formic acid and acetonitrile and dried in a SpeedVac (Savant, USA). The dried
peptides were reconstituted in 50 μL loading buffer (98% water, 2% acetonitrile and 0.1% formic acid) and dissolved at RT by shaking for 15 mins at 1800 rpm. The tryptic peptide digests
were clarified at 18,800 x g for 5 min and the peptides analysed by LC-MS.
Protein identification by LC-MS
The tryptic peptide digests were analysed using an UltiMate 3000 ultra-high-pressure nano
HPLC system (Dionex (UK) Ltd., Camberley, Surrey, UK) interfaced with a HCTultra PTM
Discovery System (Bruker Daltonics Ltd., Coventry, UK). The peptides were separated on a
PepSwift monolithic PS-DVB capillary column (200 μm i.d. x 5 cm; Dionex (UK) Ltd.) at a
flow rate of 2.0 μL/min using a linear gradient of acetonitrile provided by solvent A (3%
acetonitrile in 0.05% formic acid) and solvent B (80% acetonitrile in 0.04% formic acid). The
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
peptide separation was carried out using a gradient of 3–45% solvent B for 12 minutes, followed by a column wash in 90% solvent B for 1 minute and then equilibration in 3% solvent B
for 5 minutes. MS/MS data, averaged from two spectra, with a scan range of 100–2200 m/z,
were acquired in data-dependent Auto MS2 mode. Up to 3 precursor ions were selected from
the MS scan (range 300–1500 m/z, averages 3) in each Auto MS2 cycle. Precursors were
actively excluded after selection twice within a 1.0 min window, and singly-charged ions were
also excluded. Peptide peaks were detected and deconvoluted automatically using Data Analysis Software (Bruker). Mass lists in the form of Mascot Generic Files were created automatically and used as the input for the MS/MS ion searches in the NCBIprot database. The search
was performed by a local MASCOT server (version 2.2) using the Matrix Science web server
(www.matrixscience.com) and the search parameters were as follows: Taxonomy—S. pneumoniae; Enzyme—Trypsin; Fixed modifications—Carbamidomethyl (C); Variable modification
—Oxidation (M); Mass values—Monoisotopic; Peptide mass tolerance– 1.5 Da; Fragment
mass tolerance– 0.5 Da; Max missed cleavages– 1; Peptide charge– 2+ and 3+; Instrument type
—ESI-TRAP. The MASCOT significance threshold p<0.05 was used for peptide identification
and a false discovery rate (FDR) of less than 1% using a target decoy search was used for the
peptide validation.
Bioinformatic analysis of identified proteins
The identified proteins were categorised into their respective biological functions using the
Kyoto Encyclopedia of Genes and Genome (KEGG) database (http://www.genome.jp/kegg/
pathway.html). The association of the proteins with the KEGG pathways was determined
using S. pneumoniae TIGR4 as the reference organism. The subcellular localizations of the
identified proteins were predicted using the web-based algorithm PSORTb 3.0 (http://www.
psort.org/psortb/index.html). Since PSORTb cannot predict lipoprotein motifs, the subcellular
localizations of the proteins predicted as unknown by PSORTb were further characterised
using CELLO2GO (http://cello.life.nctu.edu.tw/cello2go/).
Supporting information
S1 Table. Peptides identified by LC-MS analysis of selected S. pneumoniae proteins.
(PDF)
S2 Table. Primers used for the molecular capsular typing.
(TIF)
S1 Fig. Representative global proteome profiles of invasive (B) and non-invasive (E) site
isolates grown in BHI-FCS broth and resolved on small format 2-D gels.
(TIF)
Acknowledgments
The authors thank Evelyn Argo and Craig Pattinson for their excellent technical support and
advice.
Author Contributions
Conceptualization: MB PC.
Funding acquisition: MB.
Investigation: MB.
PLOS ONE | https://doi.org/10.1371/journal.pone.0179075 June 2, 2017
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Comparative proteomics of clinical Streptococcus pneumoniae isolates
Methodology: MB.
Project administration: MB.
Resources: PC KF.
Supervision: PC KF.
Writing – original draft: MB.
Writing – review & editing: MB PC KF.
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