Online Data Supplement
Use of culture and molecular analysis to determine the effect of antibiotic
treatment
on
microbial
community
diversity
and
abundance
during
exacerbation in cystic fibrosis patients
M M Tunney, E R Klem, A A Fodor, D F Gilpin, T F Moriarty, S J McGrath, M S
Muhlebach, R C Boucher, C Cardwell, G Doering, J. S Elborn, M C Wolfgang
MOLECULAR DETECTION METHODS
DNA Isolation
Total DNA was extracted from approximately 200 mg aliquots of frozen (-80°C)
sputum samples using a FastPrep Instrument in combination with the FastDNA Spin
Kit (MP Biomedicals) according to the manufacturer’s protocol. Isolated DNA was
passed over a Zymo-Spin IV-HRC column to remove PCR inhibitors (Zymo
Research) and quantified with Quant-iT PicoGreen dsDNA reagent (Invitrogen).
T-RFLP Analysis
Terminal-Restriction Fragment Length Polymorphism (T-RFLP) analysis was
performed as previously described. [1 ,2] Briefly, 100 ng of isolated DNA was used
as template for PCR amplification using modified versions of the universal bacterial
16S rRNA gene specific primers Bac8f (5’-NAGRGTTTGATCCTGGCTCAG) and
Bac926r (5’- NCCGTCAATTCCTTTRAGTTT) and AmpliTaq Gold 2x PCR Master
Mix (ABI). The Bac8f and Bac926r primers were fluorescently labelled at the 5’ end
with 6FAM and HEX, respectively (Eurofins MWG Operon). For each DNA sample,
three 50 µl PCR reactions were pooled and digested with ExoSAP-IT (USB) to
1
remove excess primers and incomplete single stranded PCR fragments according to
the manufacture’s specifications. Double stranded DNA products were purified using
a Montage PCR Device (Millipore) and DNA concentration determined with QuantiT PicoGreen dsDNA reagent. For each DNA sample, 250 ng of the resulting duallabelled PCR product was digested in two separate reactions with the restriction
endonucleases HaeIII and HhaI (New England Biolabs), respectively. Digested DNA
fragments were purified and desalted with mini Quick Spin Oligo Columns (Roche)
using the manufacturer’s supplemental desalting protocol. Digested DNA (2 µl) was
added to 10 µl of a cocktail of Hi-Di Formamide (Applied Biosystems) and CSTROX-25-1000 custom sizing ladder (BioVentures). The resulting mixture was loaded
onto an ABI 3130 Genetic Analyzer, utilizing a 36 cm 4-capilary array, containing
POP-7 polymer and 1x running buffer. Foundation Data Collection 3.0 software was
used to run the Genetic Analyzer and data was viewed with GeneMapper 4.0 (Applied
Biosystems). All software was run with default factory settings although a custom
run module was created for separation of fragments up to 1000 nucleotides in length.
Traces with off-scale peaks were rerun with a shorter injection time until all peaks
were on-scale. Traces with low peak amplitude were repeated with more DNA and/or
a longer injection time. Using the above method, a total of four T-RFLP spectra
(representing both 5’ and 3’ terminal restriction fragments generated by two different
restriction endonucleases) were produced for each patient sample.
In order to identify bacterial genera within the patient T-RFLP spectra, we
created clone libraries from PCR products targeting the 16S rRNA gene in DNA
isolated from a previously collected set of CF sputum. For 33 unique clones (online
supplementary Table 2), representing the predominant aerobic and anaerobic bacterial
genera identified in previous culture and molecular-based detection studies of CF
2
sputa,[3-7] we generated both DNA sequences and T-RFLP spectra (as above). The
clone sequences were identified to genus using the Ribosome Database Project
Classifier algorithm.[8] As our classifications involve many taxa, some of which
have not been well studied and for which database characterizations are therefore
incomplete, we restricted all RDP classifications to the genus level.
To assign taxa to each patient sample, we systematically compared T-RFLP spectra
for the 33 reference clones (representing 22 different genera) samples to the spectra
generated for the 64 CF patient samples. After running all reference and patient
samples through our custom peak calling algorithm (available upon request), we
normalized our data by dividing the intensity of each peak in each spectra by the total
intensity of all peaks in that spectra. We then calculated for each reference spectra the
degree of overlap between the peaks in the reference spectra and the peaks in each
sample spectra. In the case of perfect overlap between a reference and sample spectra,
this comparison would yield a score of 1. If there were no peaks in common between
a reference and sample spectra, this comparison would yield a score of 0. We
performed this calculation independently for 3 spectra (5’ and 3’ termini for HaeIII
and the 5’ termini for HhaI; the 3’ termini for Hha contains overlapping predicted
peaks for several abundant taxa including Granulicatella, Streptococcus and
Burkholderia and was therefore not used). We summed the results for all 3 spectra to
produce a single score reflecting the degree of overlap between reference and sample
spectra.
For our T-RFLP predictions, we chose as a threshold 0.2, which corresponds to a
6.67% overlap between the peaks of the reference and sample spectra. 251 of the
scores met this threshold and hence in each of these 251 cases the genus was marked
“present” in the sample (Table 2, manuscript). There are a number of assumptions
3
that we make in our estimates that may lead to some inaccuracy. We have made no
attempt to correct for multiple taxa sharing similar peaks.
In addition, our
permutations assume that a restriction cut of any length is equally probable; this is not
necessarily true as the 16S rRNA gene has conserved and variable regions and
therefore some peaks may occur more frequently than others across all reference
spectra.
Estimation of Total Bacterial Load
Quantitative, real-time PCR (QRT-PCR) was used to determined total bacterial load
in each sputum sample. Purified DNA (described above) was analyzed in duplicate
reactions at three different template amounts (40 ng, 20 ng, and 10 ng) using a
previously published [9] set of universal primers and TaqMan probe that amplify a
conserved fragment of the bacterial 16S rRNA gene. PCR reactions were performed
using an ABI 7500 Fast Real-Time PCR System with TaqMan Gene Expression
Master Mix (Applied Biosystems). 16S rRNA gene copies per gram of sputum were
calculated using the highest average 16S rRNA gene copy number for each template.
A plasmid containing the cloned 16S rRNA gene from E.coli was used as the standard
for determining copy number in the human derived DNA samples.
Statistical analysis
Normally distributed patient characteristics were presented as mean (SD) whilst nonnormal characteristics were presented as median (inter-quartile range). Age, weight
and FEV1 were compared within participants before and after antibiotic treatment and
until stable using paired samples t-test. CRP and WCC were compared before and
after antibiotic treatment and until stable using Wilcoxon signed-rank tests.
4
Spearman’s rank correlation coefficients were calculated to measure the strength of
the linear association between T-RLFP and total viable counts. Aerobe and anaerobe
viable counts were compared at each sampling timepoint (initiation and completion of
antibiotic treatment, stable) using Wilcoxon signed-rank tests. The effect of antibiotic
treatment on bacterial abundance was determined by comparing both aerobic and
anaerobic counts before and after antibiotic treatment using Wilcoxon signed rank
tests. For the subset of patients, in which 3 samples were collected (initiation and
completion of antibiotic treatment, stable), aerobe and anaerobe total viable counts
were compared between the three groups using Friedman’s test. For those matched
sample pairs in which P. aeruginosa had been detected on admission for treatment,
total viable counts were compared before and after antibiotic treatment using
Wilcoxon signed rank test. The log10 qPCR was compared before and after antibiotic
treatment using a paired samples t-test. A Spearman’s rank correlation coefficient
was used to measure the strength of the linear association between the sum of the total
aerobe and anaerobe counts and the qPCR values. Statistical analysis was performed
with the SPSS (SPSS Version 14, Chicago, Illinois, USA) software package.
REFERENCES
1. Dicksved J, Lindberg M, Rosenquist M, et al. Molecular characterization of the
stomach microbiota in patients with gastric cancer and in controls. J Med Microbiol
2009;58(Pt 4):509-16.
2. Sibley CD, Parkins MD, Rabin HR, et al. A polymicrobial perspective of
pulmonary infections exposes an enigmatic pathogen in cystic fibrosis patients. Proc
Natl Acad Sci U S A 2008;105(39):15070-5.
3. Rogers GB, Carroll MP, Serisier DJ, et al. Characterization of bacterial community
diversity in cystic fibrosis lung infections by use of 16s ribosomal DNA terminal
5
restriction
fragment
length
polymorphism
profiling.
J
Clin
Microbiol
2004;42(11):5176-83.
4. Rogers GB, Carroll MP, Serisier DJ, et al. Use of 16S rRNA gene profiling by
terminal restriction fragment length polymorphism analysis to compare bacterial
communities in sputum and mouthwash samples from patients with cystic fibrosis. J
Clin Microbiol 2006;44(7):2601-4.
5. Rogers GB, Carroll MP, Serisier DJ, et al. Bacterial activity in cystic fibrosis lung
infections. Respir Res 2005;6:49.
6. Harris JK, De Groote MA, Sagel SD, et al. Molecular identification of bacteria in
bronchoalveolar lavage fluid from children with cystic fibrosis. Proc Natl Acad Sci U
S A 2007;104(51):20529-33.
7. Tunney MM, Field TR, Moriarty TF, et al. Detection of anaerobic bacteria in high
numbers in sputum from patients with cystic fibrosis. Am J Respir Crit Care Med
2008;177(9):995-1001.
8. Cole JR, Wang Q, Cardenas E, et al. The Ribosomal Database Project: improved
alignments and new tools for rRNA analysis. Nucleic Acids Res 2009;37(Database
issue):D141-5.
9. Nadkarni MA, Martin FE, Jacques NA, et al. Determination of bacterial load by
real-time PCR using a broad-range (universal) probe and primers set. Microbiology
2002;148(Pt 1):257-66.
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Table 1 Antibiotic regimens used to treat infective pulmonary exacerbations
Antibiotic regimen
Number of exacerbations
treated
Tobramycin, ceftazidime
9
Tobramycin, piperacillin/tazobactam
8
Tobramycin, meropenem
1
Tobramycin, temocillin, ciprofloxacin
1
Tobramycin, ciprofloxacin, colomycin
1
Temocillin, colomycin
2
Temocillin, meropenem
1
Piperacillin/tazobactam, colomycin, ciprofloxacin
1
Amikacin, meropenem
1
Amikacin, clindamycin, moxifloxacin, clarithromycin
1
7
Table 2 Reference clones generated from sequenced 16S rRNA genes used to identify
bacterial genera present in T-RFLP spectra from CF sputa samples
Clone ID
UNCCF0001
UNCCF0002
UNCCF0003
UNCCF0004
UNCCF0005
UNCCF0006
UNCCF0007
UNCCF0008
UNCCF0009
UNCCF0010
UNCCF0011
UNCCF0012
UNCCF0013
UNCCF0014
UNCCF0015
UNCCF0016
UNCCF0017
UNCCF0018
UNCCF0019
UNCCF0020
UNCCF0021
UNCCF0023
UNCCF0024
UNCCF0025
UNCCF0026
UNCCF0027
UNCCF0028
UNCCF0029
UNCCF0030
UNCCF0031
UNCCF0032
UNCCF0033
UNCCF0034
Accession
GU361868
GU361872
GU361876
GU361860
GU361873
GU361864
GU361880
GU361884
GU361888
GU361874
GU361882
GU361861
GU361887
GU361871
GU361879
GU361859
GU361862
GU361869
GU361870
GU361890
GU361883
GU361886
GU361889
GU361863
GU361878
GU361866
GU361881
GU361877
GU361875
GU361865
GU361891
GU361867
GU361885
RDP Classification
Haemophilus; 100%
Fusobacterium; 100%
Neisseria; 100%
Porphyromonas; 100%
Granulicatella; 100%
Rothia; 100%
Actinomyces; 100%
Streptococcus; 100%
Streptococcus; 100%
Streptococcus; 100%
Gemella; 100%
Propionibacterium; 100%
Burkholderia; 100%
Prevotella; 100%
Prevotella; 100%
Pseudomonas; 100%
Corynebacterium; 100%
Veillonella; 100%
Atopobium; 100%
Streptococcus; 100%
Actinomyces; 100%
Actinomyces; 100%
Devosia; 100%
Pasteuriaceae Incertae Sedis; 100%
Planomicrobium; 97%
Prevotella; 100%
Ralstonia; 100%
Actinomyces; 100%
Achromobacter; 100%
Prevotella; 100%
Prevotella; 100%
Prevotella; 100%
Staphylococcus; 100%
8
Table 3: Summary of bacterial genera detected by culture and T-RFLP in CF sputum
at initiation and completion of IV antibiotic treatment for an exacerbation and when
stable
Key
genera detected by culture
genera detected by T-RFLP
Ex: initiation of antibiotic treatment for an exacerbation (for the 3 patients treated
twice for an exacerbation, samples denoted as 1 and 2)
EOT: completion of antibiotic treatment for an exacerbation
ST: stable
*No quantitative culture results available
#
No T-RFLP results available
9
Figure 1
10
Figure 1 Summary of bacterial genera detected by culture and T-RFLP in sputum
samples collected from 23 adult CF patients on initiation of antibiotic treatment (Ex)
and completion of antibiotic treatment (EOT) for an exacerbation and when stable
(ST). Three of the patients (patients 1, 11 and 19) were treated twice for exacerbation
during the course of the study resulting in a total of 26 matched initiation/completion
of treatment sample pairs. The legend shows the different bacterial genera detected by
either method and is sorted by known or observed culture conditions for the
respective organisms. Genera marked with an asterisk (*) could not be identified by
T-RFLP analysis due to the lack of corresponding reference spectra (online
supplementary Table 2).
A) Total viable counts (TVC) of bacteria detected by both aerobic and anaerobic
culture. The y-axis shows the cumulative sum of log10 (TVC) for all cultured
microbes.
B) Culture-independent T-RFLP analysis of microbial community composition. The
y-axis indicates the cumulative T-RFLP prediction score for each of the bacterial
genera identified in a patient sample. In order to reduce false positive identification of
bacterial genera, a prediction score cutoff of 0.2 was applied, which requires at least
5% of the peak area in a patient sample to match the corresponding peaks in a given
reference spectra.
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Figure 2. Representative T-RFLP spectra from patient 11 generated at each of the
indicated timepoints. At each time point, 4 T-RFLP spectra were generated using two
different enzymes (Hae and Hha) with both the 5’ and 3’ end carrying the fluorophore
label.
Both exacerbations in this patient were treated with a combination of
tobramycin and ceftazidime.
12
P*=0.01
1012
Total bacterial concentration
concentration
(16S rRNA gene copies/G)
1011
1010
109
108
107
P†=0.05
End of treatment
Exacerbation
Stable
* Comparing two groups using paired samples t-test.
†
Comparing 3 groups using multivariate analysis of variance.
Figure 3 Quantitative PCR (qPCR) measurements of the 16S rRNA gene copy
number from CF sputum samples collected from adult patients with CF at initiation
(Exacerbation) and completion of IV antibiotic treatment (End of Treatment) for an
exacerbation and when stable (Stable).
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