1. Dept. Diagnostic Medicine
SMBD-JewishGeneralHospital, Montreal, Qc
New method for determining real C.difficile infections by
detecting the total bacterial load in stool samples using
the universal bacterial 16S rDNA qPCR assay
Ivan Brukner Ph.D.
Lady Davis Institute for Medical
Research
Key words: total bacterial load, stool samples, qPCR assay, normalisation

2. Outline
 Limitations of qualitative PCR as a tool for precise
diagnosis of infections caused by opportunistic
pathogens
 Method proposed by JGH in collaboration with McGill
University
 Results
 Conclusions
 Advantages of the Method for Focus Diagnostics
 Current IP Status
 Suggestions for next steps

3. Limitations of qualitative PCR as a tool
for precise diagnosis of infections caused
by opportunistic pathogens
Opportunistic pathogens:
 Infectious agent that can only cause disease when the host's resistance
is low
 Found in stool, urine, respiratory samples
Ex: C.difficile, H.pylori, Haemophilus influenzae, Streptococcus
pneumoniae
Qualiative PCR :
 Detects the presence or absence of a certain sequence
 Does not distinguish samples of symptomatic vs non symptomatic
patients with opportunistic bacteria in their microbial flora
 Ex.: Detection of C.difficile: Current PCR methods targeting Toxin B or Toxin A
and B can not distinguish with certainty the sample of a patient who has CDI from
someone who is a C.difficile carrier but has a liquid stool due to either drugs,
another pathogen or laxatives.

4. How can we improve the current method
for diagnosis of infections caused by
opportunistic pathogens?
We need to determine the ‘threshold’ of concentration for different pathogen of
interest in total microbial flora which will allow us to determine when an
opportunistic pathogen otherwise not causing any symptoms becomes
pathogenic and can thus cause an infection.
 Determined for each pathogen by collection non symptomatic patients
Patient with symptoms
Relative concentration>= Threshold
Carrier ( asymptomatic patient)
Relative concentration< Threshold

Threshold of relative
concentration =
lowest amount of opportunistic pathogen to cause symptoms
total amount of microbial flora

5. Why does mass normalisation not work
with liquid stool?
 Because swab with SAME MASS can be taken from
person having 10 diarrhea per day (each ~200-400ml
volume in total) or from carrier (normal stool)
 Stool dilution effect is making normalisation based
on mass impossible to estimate clinical impact of Ct
tox B or A with Ct>=30

6. Method proposed by Jewish General
Hospital (JGH) in collaboration with McGill
University
 A novel method that allows one to determine the threshold of
relative concentration for various opportunistic pathogens in total
microbial flora. Values bellow the threshold would be relevant for
asymptomatic carriers.
 Method which will allow for the adequate normalisation of analytical
signal
 This can be done only if one takes into account total microbiota
(ex: 16S universal)
 Next (inevitable) step : Quantitative microbiology?

7. Our Methodology for detecting total
bacterial load in C.difficile samples
 Sample study size: 500 liquid C.difficile positive
stools and 50 formed C.difficile negative stools
 Study preliminary period: January-October 2014
 Identification of patients for C.difficile screening
was performed on admission according to
established hospital infection control policies.
 For measurements of wet stool mass entering the
PCR reaction, 49 stool samples were randomly
chosen and processed.

8. Stool example and C.difficile
 There is no correlation between clinical sample mass (stool) and
total bacterial load
 Total bacterial load is determined by more dominant parameters (not
mass)
Ex: drug uptake, infection status/diet/immune status…
 What type of signal normalisation is important for detection of
opportunistic pathogens?
 Relative normalisation using total bacterial load in microbial flora
 The same Ct value (ex: Ct>=32) for either Toxin A and/or toxin B
could have completely different clinical meaning if the context of total
bacterial flora is different (16S qPCR Ct=12 versus Ct=22)

9. Summary of Results
 The quantity of stool material attached to swab during “typical”
swabbing process had an average value and standard deviation of
16.5 (+/- 9.6) mg
 “Average” stool has 1012 bacteria/gram
 The average number of bacteria entering direct qPCR assay is
~107-108.
 In individual samples, the clinical variability of total bacterial load
per swab deviates from average numbers by spanning 3 log (10)
values range.
 These deviations could have significant clinical meaning, especially in
the cases where antibiotic and/or infection-induced changes in micro
biota could be relevant for diagnosis and therapy

10. Comparison of bacterial load measurement techniques
Figure 1. Stool sample mass (mg of stool entering sample buffer) and Ct value of
16S rDNA universal PCR assay (R2 = -0.12, P= 0.58)
Stool mass
CTvalueof16srDNAPCR
Total bacterial load varies between individuals and
it does not correlate with the stool mass

11. Comparison of bacterial load measurement techniques
Figure 2. Binned total bacterial counts versus Ct values of 16S rDNA qPCR
assay done with stool swab lysis protocol (Ct values above 18 have low bacterial
load and should be considered as samples with strongly reduced micro flora).
There IS correlation between total number of
bacteria in stool sample and Ct values of our
assay
logN
Ct

12. Variability of the total bacterial load among clinical
samples
Figure3. Distribution of Ct values amongst 500 stool swabs using our 16S qPCR
assay
Ct values of the 16S assay
Relativenumberofsamples(total500)
How much total bacterial load vary among clinical
samples (C difficile positive)?
1000x !!!!!!

13. LOR LOD Average efficiency (SD) r2
Nadkarni and modifications* 1000-10E8 1000 97% (2%) >0.994
mod Clifford 10000-10E8 1000 94% (4%) >0.961
Typical RFU versus cycle diagram for stool sample
Figure 4. The 10x serial dilutions of DNA isolated from stool. Excellent
correlation for both assays is in range of 12-24 Ct units
Zone masked by ‘contamination’
Reference PCR (Nadkami and
modifications)
JGH 16s qPCR( based on Modified
Clifford method)
LOR: Linear Operative Range of the assay ALOD: Average Limit of Detection
r2-value: Correlation Coefficient SD: Standard Deviation

14. Conclusion
 New short qPCR for 16S rDNA has the ability to measure total
bacterial load in the clinically relevant range
 Advantages of the new qPCR
(a) the only existing PCR assay with a short amplicon for 16S rDNA
(~200bp) compatible with hydrolysis probe technology (TaqMan-like)
and direct PCR (no nucleic acid isolation)
(b) does not show any self-priming/ false priming, thus allowing confident
resulting
 Next step: Collection of ~100 non-symptomatic C diff positive
samples in order to establish the threshold which will allow one to
determine when opportunistic pathogen starts to cause symptoms.

15. Advantages for IVD INDUSTRY in obtaining
and incorporating this method into its current
assays
Compatibility with present qPCR chemistry (TaqMan-like)
Early IP ownership and advantage over competition (not simple to
design another 16S universal assay with such good performance, with
short amplicon and without self-priming/cross-reaction)
Covering/controlling IVD diagnostics of opportune pathogens in all
microbiota samples with this IP (stool: C difficile, VRE…respiratory:
Streptococcus Pneumonia…,urine: VRE…

16. Current IP status
• US provisional filed January 13th, 2014 and will be
converted into a PCT in January 2015
• Current title of the IP: METHODS, REAGENTS AND KITS
FOR THE ASSESSMENT OF CLOSTRODIUM DIFFICILE
INFECTION
• Authors: Andre Dascal, Yves Longtin, Matthew Oughton, Ivan
Brukner

17. Possible steps going forward
Collaboration with the team to advance this assay
Licensing the technology through the purchase of
the patent from JGH