Lisa DrummondLisa DrummondUniversity of EdinburghUniversity of Edinburgh

Antibiotics and

Clostridium difficile

Introduction

• Gram positive spore- former

• 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

Year

1980 1985 1990 1995 2000 2005

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Pathogenicity Locus (PaLoc)

• 19.6kb element replaced by 115bp in non-toxigenic strains

• tcdD alternative sigma factor• tcdC putative negative regulator• toxins transcribed on entry to stationary phase

tcdD552bp

toxB7098bp

tcdE501bp

toxA8133bp

tcdC695bp

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 128g/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

• 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 control graph

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11223, clindamycin and controls

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Toxin absorbance at450/620nm

630, amoxycillin and controls

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Toxin A absorbance at450/620nm

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. 5g/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

AcknowledgementsIan Poxton

David Smith

Bob Brown

Jodie McCoubrey

Microbial Pathogenicity Research Laboratory

John Starr

Becky Graham

Functional Genomics Unit at MRI

Pilar Alberdi

MRC