Transcript Introduction

Lisa Drummond
University of Edinburgh
Antibiotics and
Clostridium difficile
Introduction
• Gram positive sporeformer
• obligately anaerobic
• first described in
asymptomatic
neonates
• increased use of
antibiotics led to an
increase in C. difficile
disease
Introduction cont.
• infection ranges from asymptomatic, mild
diarrhoea, colitis to pseudomembranous
colitis
• risk factors - antibiotics, age, environment
and virulence of infecting strain
• third generation cephalosporins,
clindamycin and amoxycillin associated
with the greatest risk
• disease occurs after depletion of patient’s
normal protective flora
Disease process
ANTIBIOTIC THERAPY

ALTERATION OF COLONIC MICROFLORA

C.difficile EXPOSURE & COLONISATION

RELEASE OF TOXIN A & TOXIN B

COLONIC MUCOSAL INJURY AND INFLAMMATION
Adapted from Kelly CP & LaMont JT (1998). Clostridium difficile infection. Annual
Review of Medicine 49, 375-390.
Incidence of C .difficile in the
population
Subject population
C. difficile positive
Pseudomembranous colitis
95-100%
Antibiotic-associated diarrhoea 10-30%
Hospital in-patients
20%
Healthy adults
0-3%
Healthy neonates and infants
25-80%
Adapted from Kelly CP & LaMont JT (1998). Clostridium difficile infection. Annual
Review of Medicine 49, 375-390.
Reports of Clostridium difficile to the Scottish Centre
for Infection and Environmental Health 1983-2002
5000
Number of reports
4000
3000
2000
1000
0
1980
1985
1990
1995
Year
2000
2005
Pathogenicity Locus (PaLoc)
tcdD
552bp
toxB
7098bp
tcdE
501bp
toxA
8133bp
tcdC
695bp
• 19.6kb element replaced by 115bp in nontoxigenic strains
• tcdD alternative sigma factor
• tcdC putative negative regulator
• toxins transcribed on entry to stationary
phase
PaLoc cont.
toxin production affected by
• glucose,
• sub-inhibitory concs. of antibiotics,
• amino acids,
• temperature,
• oxidative stress,
• biotin insufficiency,
• biocarbonate concentration...
AIMS
• to analyse MIC data, patient antibiotic
regimes, S-types, resistance
• to look at effects of sub-MICs on growth
and toxin production
• investigate toxin transcripts using RT-PCR
• investigate total cell protein between
controls and sub-MIC antibiotics using 2D
gel electrophoresis and MALDI-TOF
MICs
• 186 strains and 6 antibiotics (NCCLS)
• the two treatment agents - vancomycin and
metronidazole
• 4 precipitating agents - amoxycillin,
clindamycin, cefoxitin and ceftriaxone
• database utilised for any connections
Clindamycin resistance
• 12 isolates tested had
clindamycin MIC of
128g/ml
• all contained ermB
gene
• 2 different sizes noted
• smaller band lack
leader peptide (Farrow
et al., 2002)
Recurrences and reinfections
• some patients produced up to 12 samples
over the 18 months
• allowed comparisons of their isolates over
that time
• some patients had changing S-types over
this time
• some patients also had different isolates in
the same faecal sample
MIC conclusions
• no strains resistant to vancomycin or
metronidazole
• no significant difference of resistance
profiles between S-types
• no correlation between antibiotics given and
resistance profiles
• evidence of mixed infections or recurrences
Sub-MIC antibiotics
• antibiotics have previously been shown to
affect toxin production in C.difficile
• vast amounts of literature showing effects
on other bacteria though there’s very little
data for C. difficile
Sub-MIC experimental set-up
• used same 6 antibiotics as MIC work
• used reference strain NCTC 11223, locally
endemic strain 338a and sequenced strain
630
• 1/2, 1/4 and 1/8 sub-MIC concs. used
• sampled 3X a day for 104 hours
• OD600 measured each time and 1ml of
supernate frozen for ELISA analysis
Controls from sub-MIC experiments
11223 control graph
Growth
Toxin
0.75
3.0
2.5
2.0
0.50
1.5
1.0
0.25
0.5
0.00
0
12
24
36
48
60
72
84
Toxin absorbance
at 620/450nm
Growth at 600nm
1.00
0.0
96 108
Time in Hours
338a control graph
Growth
Toxin
0.75
3.0
2.5
2.0
0.50
1.5
1.0
0.25
0.5
0.00
0
12
24
36
48
60
72
84
Toxin absorbance
at 620/450nm
Growth at 600nm
1.00
0.0
96 108
Time in Hours
630 control graph
Growth
Toxin
0.75
3.0
2.5
2.0
0.50
1.5
1.0
0.25
0.5
0.00
0
12
24
36
48
60
72
Time in Hours
84
0.0
96 108
Toxin absorbance
at 620/450nm
Growth at 600nm
1.00
• each strain grown 6
times in total
• growth varied little
between strains
• toxin elaborated at
slightly different times
in the growth curve
• toxin production by
338a and 630 exceeds
assay by ca. 48h
11223, clindamycin and controls
3.0
2.5
0.75
2.0
0.50
1.5
1.0
0.25
0.5
Toxin absorbance at
450/620nm
Growth at 600nm
1.00
Growth
Toxin
1/2 growth
1/4 growth
1/8 growth
1/2 toxin
1/4 toxin
1/8 toxin
0.00
0
12
24
36
48
60
72
Time in hours
84
0.0
96 108
630, amoxycillin and controls
3.0
2.5
0.75
2.0
0.50
1.5
1.0
0.25
0.5
0.00
0
0.0
12 24 36 48 60 72 84 96 108
Time in hours
Toxin A absorbance at
450/620nm
Growth at 600nm
1.00
Growth
Toxin
1/2 growth
1/4 growth
1/8 growth
1/2 toxin
1/4 toxin
1/8 toxin
Sub-MIC conclusions
• there’s often a lag in the growth of the
bacteria compared to the control
• main effect on toxin is that it’s elaborated
quicker under sub-MIC conditions
• heterogeneity common between strains for
toxin production and growth in response to
antibiotics
RT-PCR
• wanted to look for toxin transcripts to see if
they correlate to sub-MIC work
• RNA concentrations low (ca. 5g/ml)
• 16S transcripts easily seen but only with
Sensiscript enzyme
• low concentrations of RNA probably made
toxin transcripts difficult to see
Sensiscript
• Sensiscript vastly
improves ability to
pick up 16S RNA
• still no transcripts
from toxins
• decide to cut losses as
time extremely short
RT-PCR outcome
• Was unsuccessful in seeing transcripts for
toxins, tcdC, tcdD and groEL
• use of Sensiscript led to clear signal from
16S RNA
• if had more time would have tried another
technique e.g. Trizol, Tri reagent etc.
Proteomics
• use 2D gel electrophoresis and MALDI-TOF
analysis of proteins
• protein profile still largely uncharacterised in
C. difficile
• wanted to compare control vs. sub-MIC
• sample preparation reproducibility
• new MASCOT database being set-up
Control vs sub-MIC
• gels very reproducible - good for future
manipulations
• no obvious difference between two sets of
conditions (with and without ceftriaxone)
• 40 spots from 6 gels were taken for
MALDI-TOF
• data still being analysed and new MASCOT
database in the pipeline
Typical 2D gel
Conclusions - MICs
• no strains resistant to either of the treatment
agents
• no significant difference of resistance
profiles between S-types
• no correlation between antibiotics given and
resistance profiles
• evidence of mixed infections or recurrences
Conclusions - sub-MICs
• sub-MIC antibiotics often cause a growth
lag and shift forward the production of toxin
• there is heterogeneity between strains and
their response to sub-MIC antibiotics
• the effect on toxin could not be seen
mirrored in the toxin transcripts due to the
sensitivity of the RT-PCR
Conclusions - proteomics
• reproducibility - good sample preparation
• the combination of strain 630 and
ceftriaxone produced a protein profile
unchanged to that of the control
• once new database available should get
more high-scoring hits
• next stage - other antibiotics and strains
Acknowledgements
Ian Poxton
David Smith
Bob Brown
Jodie McCoubrey
Microbial Pathogenicity Research Laboratory
John Starr
Becky Graham
Functional Genomics Unit at MRI
Pilar Alberdi
MRC