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Lisa Drummond University 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.
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Lisa DrummondUniversity 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 Adapted from Kelly CP & LaMont JT (1998). Clostridium difficile infection. Annual Review of Medicine 49, 375-390.
tcdD 552bp toxB 7098bp tcdE 501bp toxA 8133bp tcdC 695bp 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
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
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
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