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BMC Ear Nose Throat Disord. 2006; 6: 10.
Published online 2006 May
10. doi: 10.1186/1472-6815-6-10.
Copyright [copyright]
2006 Smith-Vaughan et al; licensee BioMed Central Ltd.
Measuring nasal bacterial load and its association
with otitis media
1Menzies School of Health Research, Darwin,
Australia
2Institute for Advanced Studies, Charles
Darwin University, Darwin, Australia
3Institute of Dental Research, Westmead
Millennium Institute and Westmead Centre for Oral Health, Sydney,
Australia
4Northern Territory Clinical School,
Flinders University, Adelaide, Australia
Corresponding
author.
Heidi
Smith-Vaughan: heidi@menzies.edu.au; Roy Byun: roybyun@dental.wsahs.nsw.gov.au;
Mangala Nadkarni:
mnadkarni@dental.wsahs.nsw.gov.au; Nicholas A Jacques:
njacques@dental.wsahs.nsw.gov.au; Neil Hunter: nhunter@dental.wsahs.nsw.gov.au;
Stephen Halpin:
stephen.halpin@menzies.edu.au; Peter S Morris: peter.morris@menzies.edu.au;
Amanda J Leach:
amanda@menzies.edu.au
Received October 31, 2005; Accepted May 10, 2006. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://www.pubmedcentral.nih.gov/redirect3.cgi?&&reftype=extlink&artid=1479363&iid=127657&jid=24&&http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | ||||||||||||
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Abstract
Background
Nasal colonisation
with otitis media (OM) pathogens, particularly Streptococcus
pneumoniae, Haemophilus influenzae and Moraxella
catarrhalis, is a precursor to the onset of OM. Many children
experience asymptomatic nasal carriage of these pathogens whereas others
will progress to otitis media with effusion (OME) or suppurative OM. We
observed a disparity in the prevalence of suppurative OM between
Aboriginal children living in remote communities and non-Aboriginal
children attending child-care centres; up to 60% and <1%, respectively.
This could not be explained by the less dramatic difference in rates of
carriage of respiratory bacterial pathogens (80% vs 50%, respectively). In
this study, we measured nasal bacterial load to help explain the different
propensity for suppurative OM in these two populations.
Methods
Quantitative measures
(colony counts and real-time quantitative PCR) of the respiratory
pathogens S. pneumoniae, H. influenzae and M.
catarrhalis, and total bacterial load were analysed in nasal swabs
from Aboriginal children from remote communities, and non-Aboriginal
children attending urban child-care centres.
Results
In both populations
nearly all swabs were positive for at least one of these respiratory
pathogens. Using either quantification method, positive correlations
between bacterial load and ear state (no OM, OME, or suppurative OM) were
observed. This relationship held for single and combined bacterial
respiratory pathogens, total bacterial load, and the proportion of
respiratory pathogens to total bacterial load. Comparison of Aboriginal
and non-Aboriginal children, all with a diagnosis of OME, demonstrated
significantly higher loads of S. pneumoniae and M.
catarrhalis in the Aboriginal group. The increased bacterial load
despite similar clinical condition may predict persistence of middle ear
effusions and progression to suppurative OM in the Aboriginal population.
Our data also demonstrated the presence of PCR-detectable non-cultivable
respiratory pathogens in 36% of nasal swabs. This may have implications
for the pathogenesis of OM including persistence of infection despite
aggressive therapies.
Conclusion
Nasal bacterial load
was significantly higher among Aboriginal children and may explain their
increased risk of suppurative OM. It was also positively correlated with
ear state. We believe that a reduction in bacterial load in high-risk
populations may be required before dramatic reductions in OM can be
achieved.
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Background
For Aboriginal children in remote communities of the Northern Territory of Australia, otitis media (OM) commences within the first weeks of life and progresses to tympanic membrane perforation in 30% of children by 6 months of age [1]. A recent cross-sectional study of Northern Territory Aboriginal children aged 6 to 30 months living in 29 remote communities demonstrated a community perforation prevalence of 0 --60% [2]. In contrast, whilst children attending urban child-care centres are also at high risk of OM, the prevalence of tympanic membrane perforation is almost 100 fold lower (less than 1%)[3,4]. For Aboriginal children, we have described simultaneous colonisation with multiple species and strains of Streptococcus pneumoniae, Haemophilus influenzae and Moraxella catarrhalis, which may contribute to persistent and progressive ear disease. Prevalence of each respiratory pathogen among young Aboriginal children is approximately 80% [1] compared to approximately 50% for non-Aboriginal attending child-care centres [5]. The risk of simultaneous nasal carriage with H. influenzae and S. pneumoniae was nearly three-fold higher in Aboriginal children [6], but these differences were not sufficient to explain the substantial variation in prevalence of suppurative disease between the two populations. We further believe that the high rates of carriage are driven by early age of colonisation with these multiple strains, acquired by infants through high rates of cross-infection in overcrowded living conditions. There is potential for colonisation in the first weeks of life to result in long carriage times, driven by immune suppression [1], inflammatory processes in direct response to bacterial virulence factors[7], reduced cilial function, and thus failure to clear the multiple strains[8,9]. Treatment failure following antibiotic therapy for otitis media is common in Aboriginal children and can only partially be attributed to low compliance and antibiotic resistance. We explored the possibility that a high nasal bacterial load is an important determinant in the progression of children to suppurative OM. Other studies have reported the relationship between bacterial load and the severity or clinical course of a number of infections including, colitis in the rat model [10], typhoid fever [11], and meningococcal disease [12]. Furthermore, there exists a relationship between bacterial load and markers of airway inflammation for the pathogenesis of bronchiectasis [13]. Inflammatory markers increased at bacterial loads of 106 to 107 cfu/ml, and continued to increase progressively with further bacterial load. Theoretically, therefore, an interruption of disease progression may be achieved by reducing bacterial load. Thus the aim of this study was to measure bacterial load in nasal swabs from two populations known to be at high and low risk of suppurative OM. Measurements were undertaken using three independent methods for bacterial enumeration; semi-quantitative bacterial culture, serial dilution, and real-time quantitative PCR (RTQ-PCR). | ||||||||||||
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Methods
Ethical approval
Ethical approval
for this study was granted in 2003 by the Human Research Ethics Committee
of the Northern Territory Department of Health and Community Services and
Menzies School of Health Research.
Participants and sample
collection This study utilised nasal swabs from previous studies in
two populations. Each swab had been stored in 1.0 ml skim
milk-tryptone-glucose-glycerin-broth (STGGB) [14] at -70[deg]C for up to
six years. Fifty-one nasal swabs were randomly selected from 59 Aboriginal
children aged 18 to 36 months living in a remote Northern Territory
community. These children were being assessed as part of the follow up of
a randomised placebo-controlled trial of long-term antibiotics for
prevention of OM in the first year of life. This cohort of Aboriginal
children was known to have a high incidence of both respiratory pathogen
carriage and suppurative OM. The second cohort consisted of 52 children
randomly selected from 235 non-Aboriginal children aged 18 to 36 months
attending Darwin child-care centres. Nasal swabs were collected from these
children at baseline (prior to randomisation) as part of a hygiene
intervention trial. Stored swabs were thawed on ice, mixed, and 200 [mu]L
aliquots removed for use in this study. All aliquots were re-labelled with
random identification numbers, thus blinding laboratory staff to the
population group, clinical and prior microbiological data. Random samples
were generated using STATA version 7 (StataCorp LP, College Station, Tx).
Ear examinations
Ears were examined
using video otoscopy and tympanometry. Tympanic membrane videos and
tympanograms were reviewed by a second independent observer. For purpose
of this analysis, the child was categorised according to their worse ear.
Categories were: No OM -- normal (neutral tympanic membrane with normal mobility and type A tympanogram or retracted tympanic membrane with normal mobility and type C tympanogram). OME -- OM with effusion (neutral, retracted or mildly bulging tympanic membrane with reduced mobility and type B tympanogram) and without symptoms of acute infection. Suppurative OM -- acute OM (moderate to marked bulging of the tympanic membrane with reduced mobility and type B tympanogram), or acute OM with perforation (fresh discharge through a recent perforation of the tympanic membrane), or dry perforation, or chronic suppurative OM (fresh discharge through a persistent perforation of the tympanic membrane).
Bacterial load estimates
S.
pneumoniae, H. influenzae, M. catarrhalis, and total bacterial load
were determined as follows:
i) Semi-quantitative colony
counts The stored swab in STGGB was thawed, a 10 [mu]l aliquot was
plated onto chocolate agar (Oxoid, Adelaide, SA) and streaked in
quadrants. Bacterial load was categorised as follows: 0, no growth; 1,
<20 bacterial colonies; 2, 20 --50 bacterial colonies; 3, 50 --100
bacterial colonies; 4, confluent growth in the primary zone; 5, confluent
growth in the primary zone and colonies in the secondary zone; 6,
confluent growth in the secondary zone and colonies in the tertiary zone;
and 7, confluent growth in the tertiary zone and colonies in final streak
zone. As previous microbiological analysis of these swabs had identified
the species present, colonies counted were selected by morphological
identification. Any colonies with uncertain identity were fully
characterized as described previously [1].
ii) Quantitative serial dilution colony
counts Serial 10-fold dilutions of 10 [mu]l aliquots were made using
Mueller-Hinton Broth (Oxoid) and lawn streaked onto chocolate agar plates.
Colonies were identified as in (i).
iii) Real-time quantitative PCR
(RTQ-PCR) Total DNA was extracted from a 50 [mu]l aliquot of the
sample. In brief, cells were incubated in 50 mM phosphate buffer pH 6.7
containing 20 mM diethyl pyrocarbonate, 1 mg lysozyme ml-1, 1
mg mutanolysin ml-1 and 2 mg Proteinase K ml-1 at
56[deg]C for 40 min and lysed with 1% (w/v) SDS, prior to DNA extraction
and purification using QIAmp DNA Mini kit (QIAGEN, Clifton Hill, Vic)
according to the manufacturer's protocol. Genomic DNA of the type strains,
S. pneumoniae ATCC 6305, H. influenzae ATCC 10211 and
M. catarrhalis ATCC 25238, was extracted from overnight cultures
using the QIAmp DNA mini kit, as described above, except that diethyl
pyrocarbonate was not included. DNA concentrations were determined with
the PicoGreen double-stranded DNA quantification kit (Invitrogen-Molecular
Probes, Mulgrave, Vic) and Luminescence spectrophotometer model LS 50B
(Perkin Elmer, Melbourne, Vic).
Total bacterial loads were determined using pre-optimised concentrations of the universal forward (5'-TCCTACGGGAGGCAGCAGT-3'; 300 nM) and reverse (5'-GGACTACCAGGGTATCTAATCCTGTT-3'; 300 nM) primers and probe (5'- [6-FAM]-CGTATTACCGCGGCTGCTGGCAC- [TAMRA]-3'; 175 nM) for the 16S rRNA gene, as previously described [15]. Purified genomic DNA of Streptococcus mitis strain NCTC 1226, in the range of 100 fg to 1 ng, was used to standardise the values. DNA quantities determined by RTQ-PCR were converted to cells (ml of sample)-1, in order to represent the number of bacterial cells per nasal swab, by assuming that 1 pg of DNA was equivalent to 447.4 cells, i.e. a genome size of 2 Mb. Total S. pneumoniae loads were determined using pre-optimised concentrations of the forward (5'-TCTTACGCAATCTAGCAGATGAAGC-3'; 100 nM) and reverse (5'-GTTGTTTGGTTGGTTATTCGTGC-3'; 100 nM) primers and probe (5'- [6-FAM]-TTTGCCGAAAACGCTTGATACAGGG- [TAMRA]-3'; 200 nM) for the autolysin gene, lytA, as described previously [16], except that the primers were modified for compatible Tms. Purified genomic DNAof S. pneumoniae ATCC 6305, in the range of 20 fg to 200 pg, was used to standardise the values. DNA loads were converted to cells (ml of sample)-1 assuming that 1 pg of DNA was equivalent to 447.4 cells, i.e. a genome size of 2 Mb. Total H. influenzae loads were determined using pre-optimised concentrations of the forward (5'-CTGGWGCAATGGCAGAAGTG-3'; 100 nM) and reverse (5'-TCTTTACGCACGGTGTAAGGATG-3'; 200 nM) primers and probe (5'- [6-FAM]-AATATGCCGATGGTGTTGGYCCAGGTT- [TAMRA]-3'; 100 nM) for the outer membrane protein D gene, glpQ, which shows limited sequence variation among H. influenzae type b and non-encapsulated strains [17]. Purified genomic DNA of H. influenzae ATCC 10211, in the range of 20 fg to 200 pg, was used to standardise the values. DNA quantities were converted to cells (ml of sample)-1 assuming that 1 pg of DNA was equivalent to 497.1 cells, i.e. a genome size of 1.8 Mb. Total M. catarrhalis loads were determined using pre-optimised concentrations of the forward (5'- GTGAGTGCCGCTTTTACAACC-3'; 300 nM) and reverse (5'-TGTATCGCCTGCCAAGACAA-3'; 300 nM) primers and probe (5'- [6-FAM]-TGCTTTTGCAGCTGTTAGCCAGCCTAA- [TAMRA]-3'; 200 nM) for the outer membrane protein gene, copB, as described previously [18]. Purified genomic DNA of M. catarrhalis ATCC 25238, in the range of 20 fg to 200 pg, was used to standardise the values. DNA quantities were converted to cells (ml of sample)-1 assuming that 1 pg of DNA was equivalent to 497.1 cells, i.e. a genome size of 1.8 Mb. RTQ-PCR was performed with the ABI-PRISM 7700 Sequence Detection System (Applied Biosystems, Scoresby, Vic) using optical grade 96-well plates in a reaction volume of 25 [mu]l using the TaqMan PCR Core Reagent Kit (Applied Biosystems) containing the forward and reverse primers and the fluorogenic probe. The RTQ-PCR conditions were 50[deg]C for 2 min and 95[deg]C for 10 min, followed by 40 cycles of amplification at 95[deg]C for 15 s and 60[deg]C for 1 min. Reactions were performed in triplicate and the mean values calculated. Data analysis was performed using the Sequence Detection Software version 1.6.3 supplied by Applied Biosystems. Samples that were negative by RTQ-PCR for S. pneumoniae, H. influenzae or M. catarrhalis DNA were checked qualitatively by PCR in 25 [mu]l reactions containing 1 x Platinum PCR SuperMix (Invitrogen), 2 [mu]l of the sample DNA and 200 nM each of the specific primers. PCR was performed using the GeneAmp PCR System 9700 (Perkin Elmer) with an initial denaturation step of 95[deg]C for 10 min, followed by 40 cycles of 95[deg]C for 15 s and 60[deg]C for 1 min. A 10 [mu]l aliquot of the PCR reaction was subjected to electrophoresis on a 2% (w/v) agarose gel containing 1 [mu]g ethidium bromide ml-1 and the DNA bands visualized by UV illumination.
Statistical analysis
The bacterial
load dataset was anticipated to contain a large proportion of zero counts
and not to be normally distributed. Therefore non-parametric tests were
selected for measuring association between variables. The degree of
correlation between bacterial load counts estimated using colony counts
and RTQ-PCR was computed as the Spearman correlation coefficient. The
difference between groups (bacterial load estimates, ear state) was
assessed using the Kruskal-Wallis test, Chi2 exact test, or
Mann-Whitney U test. A logistic regression model was developed to predict
ear state for various levels of bacterial load estimates. The sensitivity
and specificity for predicting ear state were determined for various
levels of bacterial load. The association between multiple carriage and
ethnicity, as well as the association between cultivable bacteria and ear
state were assessed using the 2-tailed Fisher's exact test. All
statistical analyses were undertaken using STATA version 8.0 (StataCorp
LP).
Study limitations
This study was
limited by the available sampling technology that made it necessary to
assume that counts per swab represented the burden of bacterial load in
the nose; estimation of total nasal bacterial numbers could be subject to
misinterpretation if the volume of secretion in the nose varied
substantially.
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Results
Limits of bacterial
detection RTQ-PCR allowed for the detection of between 6.5 x 102
to 1.8 x 108 cells (ml of sample)-1. Samples
negative by RTQ-PCR were also negative by qualitative PCR after 40 cycles.
In the case of serial dilution colony counting, the lowest positive
estimate was 1 x 103 cells (ml of sample)-1.
Comparison of colony counts and
RTQ-PCR Comparison of serial dilution colony counts and RTQ-PCR
indicated that 70% and 85% of the 103 swabs were positive for S.
pneumoniae, 59% and 82% for H. influenzae, and 83% and 87%
for M. catarrhalis, respectively. Despite the consistently higher
detection by RTQ-PCR, a strong positive correlation was seen between this
method and the serial dilution colony counts method. Spearman correlation
coefficients for S. pneumoniae, H. influenzae and M.
catarrhalis were 0.77, 0.66 and 0.83, respectively.
Detection of pathogens by culture and
RTQ-PCR 18%, 23%, and 6% of the 103 swabs were culture-negative but
RTQ-PCR-positive for S. pneumoniae, H. influenzae and M.
catarrhalis, respectively. A single swab was negative for all three
respiratory pathogens, but was positive for other flora.
Four swabs (4%) were RTQ-PCR-negative but culture-positive; a single colony of the RTQ-PCR-negative pathogen was cultured from 3 swabs at the lowest serial dilution. The remaining swab cultured high numbers of the RTQ-PCR-negative bacterium (H. influenzae) suggesting the possible presence of an unknown inhibitor of the PCR process in this sample.
Prevalence and severity of ear disease
and diversity of species in nasal swabs Aboriginal children from
remote communities had a much lower prevalence of no OM and a higher
prevalence of OME and suppurative OM than non-Aboriginal children; 6%
Aboriginal children had bilaterally normal ears, 43% had OME, and 51% had
suppurative OM. In contrast, 65% of the non-Aboriginal group had
bilaterally normal ears, 31% OME, and only 4% suppurative OM.
Of the children with a suppurative OM diagnosis, the 2 non-Aboriginal children and 8% Aboriginal children had dry perforations, 15% Aboriginal children had AOM, 19% Aboriginal children had AOM with perforation, while 58% of Aboriginal children with a suppurative OM diagnosis had chronic suppurative OM. Respiratory bacterial counts were high in these groups, and did not differ significantly between groups (p = 0.39). All swabs tested from Aboriginal children and 50/52 swabs from non-Aboriginal children were positive for at least one of the respiratory pathogens, S. pneumoniae, H. influenzae or M. catarrhalis (Figure 1). The proportion of swabs positive for all three pathogens was significantly higher for Aboriginal children compared with non-Aboriginal children (48/51 versus 25/52, P = 0.0001).
Density of nasal bacteria measured by
RTQ-PCR Species-specific individual bacterial RTQ-PCR counts ranged
from zero to 3.9 x 107 cells (ml of sample)-1. The
geometric mean counts for Aboriginal children were generally higher than
for non-Aboriginal children (Figure 2).
For Aboriginal children, H. influenzae geometric mean counts were similar, regardless of ear state and increased by only 0.5-log for suppurative OM. M. catarrhalis geometric mean RTQ-PCR counts were considerably higher than other species, with a smaller margin of increase between ear states. The S. pneumoniae geometric mean RTQ-PCR count for no OM was considerably lower than other species and increased by 2-logs for OME and for suppurative OM. In non-Aboriginal children, geometric mean respiratory bacterial counts for all species were comparable for no OM and OME; a considerable increase (2 to 2.5-logs) for all species was detected in suppurative OM (2 children). For children with no OM or OME, Aboriginal children had higher geometric mean total bacterial loads than non-Aboriginal children (Figure 2). For Aboriginal and non-Aboriginal children, total bacterial counts were comparable with suppurative OM, and higher than no OM or OME (Figure 2).
The ratio of respiratory pathogen load to
total bacterial load The ratio of respiratory pathogen load to total
bacterial load was estimated as a percentage for each swab (Figure 3).
Total bacterial load varied between 7 x 104 and 2 x 108
cells (ml of sample)-1. S. pneumoniae, H. influenzae
or M. catarrhalis counts as a proportion of total bacterial
load reached 46%, 78%, and 65%, respectively.
In the Aboriginal children, S. pneumoniae was a small proportion of total bacterial load for no OM (<1%), increasing only slightly for OME (3%) and suppurative OM (2%). The H. influenzae ratio was higher than S. pneumoniae, increasing progressively through the ear states from 3% for no OM to 5% for OME to 13% for suppurative OM. M. catarrhalis proportions remained at approximately 10%. In the non-Aboriginal children, each of the respiratory pathogens was a low proportion of the total load for no OM and OME (<1%), but increased substantially for suppurative OM (6% for S. pneumoniae, 8% for H. influenzae and 12% for M. catarrhalis).
Comparison of Aboriginal and
non-Aboriginal groups with OME For children with OME (22 Aboriginal
and 16 non-Aboriginal), S. pneumoniae and M. catarrhalis
nasal load (Figure 2) and proportion of total load (Figure 3) were
significantly increased in the Aboriginal group (Mann-Whitney U test,
P = 0.0001 -- 0.03). Comparison of H. influenzae load
between Aboriginal and non-Aboriginal children with OME did not reach
significance due to the large variability in the H. influenzae
data for the OME group, particularly for the non-Aboriginal children.
The interquartile range of H. influenzae as a proportion of total
load in non-Aboriginal and Aboriginal children was 26.3 and 15.5,
respectively, compared with 2.1 and 9.5 for S. pneumoniae, and
2.2 and 12.2 for M. catarrhalis.
Association between nasal bacterial load
and ear state The Kruskal-Wallis non-parametric comparison of means
test was used to measure the association between bacterial load and ear
state severity for the combined populations. As only three children in the
Aboriginal group had a No OM ear diagnosis, and two children in the
non-Aboriginal group had a Suppurative OM diagnosis, separate analyses
within groups could not be undertaken. S. pneumoniae load,
measured by serial dilution colony counts or RTQ-PCR, was positively
associated with ear state (P = 0.0001 --0.0016; Figure 4) as were
H. influenzae and M. catarrhalis (data not shown). Total
nasal bacterial load measured by RTQ-PCR was also positively associated
with ear state (P = 0.0001), as was the ratio of respiratory
pathogens to total bacterial load (P = 0.0032).
In order to assess the utility of bacterial load as a predictor of outcome, the probability of a suppurative OM diagnosis across the range of bacterial counts was determined. The analysis showed that the probability of suppurative OM increases with the density of S. pneumoniae, H. influenzae, or M. catarrhalis, combined pathogen load, and total bacterial load as determined by RTQ-PCR (Figure 5). Compared with M. catarrhalis, both S. pneumoniae and H. influenzae were associated with a higher probability of suppurative OM at lower counts. Both the combined respiratory pathogen load and total bacterial load were only associated with a greater probability of suppurative OM at high counts (Figure 5). For swabs that were culture-negative and RTQ-PCR-positive for S. pneumoniae (18 of 103 swabs) and H. influenzae (24 of 103 swabs), there was a statistically significant association with no OM or OME (P = 0.0001). For similar samples of M. catarrhalis (6 of 103 swabs) there was no association with ear state. A further comparison was made with routine semi-quantitative assessment of bacterial load established in our laboratory. Despite the lower precision of this simple method, a significant association was demonstrated for all bacteria tested and presence and severity of ear disease (Chi2 exact; S. pneumoniae, P = 0.003; H. influenzae, P = 0.012; M. catarrhalis, P = 0.013).
Selection of a threshold load for
predicting OM Using sensitivity and specificity measures, threshold
bacterial load values that could identify children most likely to have
suppurative OM from those less likely to be affected were estimated. For
example, the sensitivity of an RTQ-PCR estimate of 105 cells
(ml of sample)-1 for predicting suppurative OM was 79% to 96%
for individual pathogenic species, and 82% for combined respiratory
pathogens (Figure 6a). Specificity ranged from 49% to 61% for individual,
and 52% for combined respiratory pathogens (Figure 6b). These analyses
showed that high nasal respiratory pathogen counts occurred in children
without OM, but that a low count was unlikely in a child with suppurative
OM. Analyses of serial dilution colony count data and RTQ-PCR data for
predicting suppurative OM or any OM showed similar results.
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Discussion
Positive correlation between nasal
bacterial load and ear state In this study, positive correlations
between nasal bacterial load and ear state (no OM, OME, or suppurative OM)
were observed. This relationship held for single and combined bacterial
respiratory pathogens (S. pneumoniae, H. influenzae, or M.
catarrhalis), total bacterial load, and the proportion of respiratory
pathogens to total bacterial load.
Nasal bacterial load as a diagnostic
marker Nasal bacterial load of respiratory pathogens was a highly
sensitive measure of suppurative OM, but had low specificity, and is
therefore not a reliable diagnostic tool. Nevertheless, the high
sensitivity supports the view that a low bacterial load makes the presence
of suppurative OM unlikely.
Comparison of nasal bacterial load in
Aboriginal and non-Aboriginal children Comparison of Aboriginal and
non-Aboriginal children with OME demonstrated significantly higher loads
of S. pneumoniae and M. catarrhalis in the Aboriginal
group. Furthermore, the proportion of swabs positive for all three
pathogens was significantly higher for Aboriginal children compared with
non-Aboriginal children. We believe that the high-density carriage of
multiple respiratory bacteria in Aboriginal children is a result of high
rates of cross-infection driven by overcrowding and poor health
infrastructure, long carriage times, and immune suppression resulting from
inadequate nutrition and early age of first infection [1,8,9].
Furthermore, we hypothesise that high-density carriage of S.
pneumoniae, H. influenzae, and M. catarrhalis predicts
persistence of OME, and progression to suppurative OM.
Superior detection of bacterial
respiratory pathogens by RTQ-PCR RTQ-PCR proved to be the more
sensitive method for quantifying S. pneumoniae, H. influenzae,
and M. catarrhalis in nasal swabs. For S. pneumoniae,
this may be due to diplococci or chains of diplococci counted as a single
colony on culture plates, compared to more precise enumeration by PCR
[19]. Bacterial death in storage may be a contributing factor. However, we
have detected only a minor change in viable counts over 6 years of
storage. Another explanation may be the detection of released DNA in the
nose. However, evidence suggests that DNA is cleared efficiently from
mucosal surfaces through a combination of bacterial lysis and immune
clearance mechanisms, since bacterial DNA does not survive in an
amplifiable form for more than three days in the presence of a middle ear
effusion[20]. Antibiotic use within 4 weeks of swab collection was
documented for only 3 children and does not explain this phenomenon. Thus
the most likely explanation for the culture-negative, RTQ-PCR-positive
events relates to the suppressed metabolic state which enables many
different bacterial species to survive in a non-cultivable state [21,22].
Several hypotheses exist to explain this phenomenon[23].
Clinical relevance of non-cultivable
bacteria Non-cultivable forms of S. pneumoniae and H.
influenzae in middle ear effusions elicit an immune response and may
have a crucial role in the pathogenesis of OME [24]. In our study, the
presence of these bacteria in nasal swabs was associated with no OM or
non-acute OM (OME). Others have demonstrated that whilst culture-negative,
PCR-positive pneumococcal acute OM does occur, this is clinically less
severe than culture-positive pneumococcal acute OM[19].
Of particular interest is whether non-cultivable bacteria can recrudesce or have a direct pathogenic role in persistence of effusions, or in recurrent acute OM. With an increasing trend towards the use of PCR-based diagnostics, it is important to clarify the role of non-cultivable organisms in disease. | ||||||||||||
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Conclusion
This study demonstrated a significant association between nasal bacterial load and the presence and severity of current ear disease in individuals. These associations persisted whether bacterial load was measured by a semi-quantitative culture method, serial colony counts, or by RTQ-PCR. Detection of non-cultivable bacteria by RTQ-PCR may have implications for the pathogenesis of OM including persistence of infection despite aggressive therapies. Swabs with higher bacterial loads were more likely to have been obtained from Aboriginal children with suppurative OM. However, bacterial load measurements were not reliable enough in distinguishing children with suppurative OM to be of diagnostic use. Notwithstanding the low specificity of bacterial load as a measure of ear state, the high sensitivity supports the view that a low bacterial load makes the presence of suppurative OM unlikely. This observation also suggests that reductions in bacterial load may be essential before dramatic reductions in suppurative OM can be achieved for Aboriginal children living in remote communities of Australia. | ||||||||||||
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Authors'
contributions
HS-V participated in the design of the study, carried out the microbiological analysis, and drafted the manuscript. RB developed and carried out the molecular analysis. MN developed and carried out the molecular analysis, and participated in the design of the study. NAJ and NH coordinated the development of the molecular techniques, and participated in the design of the study. SH performed the statistical analysis. AJL and PSM conceived the study, were chief investigators of the original studies from which the swabs were derived, and participated in the design of the study. | ||||||||||||
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Pre-publication history
The pre-publication history for this paper can be accessed here: http://www.pubmedcentral.nih.gov/redirect3.cgi?&&reftype=extlink&artid=1479363&iid=127657&jid=24&&http://www.biomedcentral.com/1472-6815/6/10/prepub | ||||||||||||
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Acknowledgements
We are grateful to the Menzies School of Health Research Ear Health and Education Unit members involved in the provision of nasal swabs, and clinical and microbiological data used in this study; in particular, Elizabeth Stubbs, Cate Wilson, and Brooke Harrington. We are also grateful to Robyn Marsh for commenting on the manuscript. We would also like to thank the families who participated in the original studies, the study community health board, council and clinic, and Darwin and Palmerston Child-Care Centre directors and staff. Financial support for this study was provided by the National Health and Medical Research Council (Australia). | ||||||||||||
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References
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Figures and
Tables
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