Jean-Christophe Avarre, Head of the High Throughput qPCR Platform and Research Group Leader, University of Montpellier, France Nucleic acid characterization by High Resolution Melting (HRM) is a simple, flexible, low-cost and powerful technique for identifying sequence variations, making it attractive for a broad range of diagnostic and research applications. However, current procedures for analyzing HRM curves are not suited for large data sets. For this reason, we have developed an innovative method that enables the simultaneous discrimination of a large number of variants from their HRM profile. This method relies on the establishment of a melting profile library and offers a fully automated analysis workflow. Using this workflow, it was possible to discriminate 19 nontuberculous mycobacterial species from their HRM profile. It was also possible to design a multiplex diagnostic tool targeting five pathogens responsible for abortive diseases in cattle.

1. MelTree: A novel workflow for the automated identification
of a large number of variants through HRM
Jean-Christophe Avarre

2. Post-PCR assay that enables detection of (epi)genetic variations in
double-stranded DNA
Simple, quick, low cost, limited contamination, high throughput
 strong potential for diagnostics
High Resolution Melting
5thqPCR&dPCREurope
2Odell ID, Cloud JL, Seipp M and Wittwer CT (2005). American Journal of Clinical Pathology 123: 96-101
Wittwer CT (2009). Human Mutation 30: 857-859
04/12/2017

3. Most common HRM analysis method: difference plot
Tm shiftNormalisation
Difference from “reference”
curve
F
T
3
5thqPCR&dPCREurope04/12/2017

4. 4
Application to the discrimination of 12 species
of non-tuberculous mycobacteria
5th qPCR & dPCR Europe04/12/2017
 Sensitivity and specificity of the PCR assay
 Discriminative power of HRM

5. List of the 12 Mycobacterium species
04/12/20175thqPCR&dPCREurope
5
Strain Source
M. phlei (CIP 105389T) Pasteur Institute, Paris
M. bohemicum (CIP 105811T) Pasteur Institute, Paris
M. gastri (CIP 104530T) Pasteur Institute, Paris
M. pseudoshottsii (CIP109775 T) Pasteur Institute, Paris
M. smegmatis (CIP 104444 T) Pasteur Institute, Paris
M. fortuitum AdV Hospital, Montpellier
M. marinum AdV Hospital, Montpellier
M. chelonae AdV Hospital, Montpellier
M. abscessus AdV Hospital, Montpellier
M. gordonae AdV Hospital, Montpellier
M. avium LDV Montpellier
M. haemophilum LDV Montpellier
Amplification of the 16S-ITS region : 230-350 nt

6. Sensitivity of the PCR assay
04/12/20175thqPCR&dPCREurope
6
Serial dilutions of bacterial DNA in 100 ng of host genomic DNA
Amplification plots Gel electrophoresis
M. fortuitum
106 105 104 103 102
10 H2O1
106 105 104 103 102 10 1 H2O
106 105 104 103 102 10 1 H2O
M. marinum
106 105 104 103 102
10 1 H2O
 Detection of 10 bacterial copies

7. Specificity of the assay
04/12/20175thqPCR&dPCREurope
7
Strain Gram Source
Flavobacterium psychrophilum - LDV Montpellier
Pseudomonas fluorescens - LDV Montpellier
Aeromonas sobria - LDV Montpellier
Aeromonas hydrophila - LDV Montpellier
Vibrio vulnificus - LDV Montpellier
Citrobacter braaki - LDV Montpellier
Shewanella putrefaciens - LDV Montpellier
Photobacterium damselae - LDV Montpellier
Chryseobacterium indologenes - LDV Montpellier
Citrobacter freundii - LDV Montpellier
Lactococcus garvieae + INRA Jouy en Josas
Carnobacterium piscicola + INRA Jouy en Josas
Streptococcus parauberis + LDV Montpellier
Carnobacterium maltaromaticum + LDV Montpellier
Enterococcus faecalis + LDV Montpellier
Nocardia crassostrea + CVI Wageningen
16 non-Mycobacterium pathogenic/opportunistic species

8. Specificity of the assay
04/12/20175thqPCR&dPCREurope
8
Cyc le s
40302010
Fluorescence(483-533)
7.509
6.809
6.109
5.409
4.709
4.009
3.309
2.609
1.909
1.209
0.509
M. marinum
M. fortuitum
Non-mycobacteria
+ H2O
M. marinum
M. fortuitum non-mycobacteria
Mycobacterium-specific primers
16S universal primers
M. marinum and M. fortuitum:
~104 genome copies
Non-mycobacteria:
~106 genome copies

9. Species classification
04/12/20175thqPCR&dPCREurope
9
2 separate analyses needed
 3 groups included 2 species:
•group 1 (M. marinum and M. gordonae)
•group 2 (M. phlei and M. pseudoshottsii)
•group 3 (M. fortuitum and M. haemophilum)
5
1 2
4
3
6 7
9
8
 9 groups
Phung et al, 2013. Applied and Environmental Microbiology 79, 7837-7845

10. Melting temperature (Tm) measurement
04/12/20175thqPCR&dPCREurope
10
Species Tm
M. abscessus 86.12
M. marinum 86.71
M. gordonae 88.21
M. chelonae 87.31
M. haemophilum 87.20
M. fortuitum 89.13
M. gastri 89.46
M. avium 89.05
M. phlei 90.92
M. pseudoshottsii 89.97
M. smegmatis 90.12
M. bohemicum 89.98
 Looking at both melting profile and Tm allowed discrimination of the 12 species
group 1
group 2
group 3
Phung et al, 2013. Applied and Environmental Microbiology 79, 7837-7845

11. Rapidity
Sensitivity
Reliability
Unsuitable analysis method
Conclusions about the assay
04/12/20175thqPCR&dPCREurope
11

12. melTree: a novel and automated procedure for
classification of HRM profiles
5th qPCR & dPCR Europe 1204/12/2017

13. How does it work ?
04/12/20175thqPCR&dPCREurope
14
Machine
learning box
Melting profiles of known
samples (genotypes, species…)
Learning
Acquisition of
reference
curves
Prediction
Melting profiles of
unknown samples
CI = 91%
Group A
Assignment of an unknown
sample to a defined group
assorted with a confidence
index
Result

14. 1504/12/2017 5th qPCR & dPCR Europe
Main features of melTree
 New descriptors of HRM profiles
 New approach for classification of melting profiles
 Constitution of an upgradable library of profiles from known samples
 Possibility to refuse to assign a new profile to any reference group
 Automatic assignment of new melting profiles with a confidence index

15. 1604/12/2017 5th qPCR & dPCR Europe
Applied to mycobacteria
19 species

16. After learning
04/12/20175thqPCR&dPCREurope
17
All species formed a separate group !!!
Whole learning dataset : 3-10 samples of each species

17. Intraspecies diversity: example of M. kansasii
04/12/20175thqPCR&dPCREurope
18

18. M. kansasii 1
M. kansasii 2
Intraspecies diversity: example of M. kansasii
04/12/20175thqPCR&dPCREurope
19

19. Species with close profiles…
04/12/20175thqPCR&dPCREurope
20
M. avium and M. szulgai

20. M.
Avium
 no need to merge the groups
M. avium
M. szulgai
…could be discriminated
04/12/20175thqPCR&dPCREurope
21

21. At the end
04/12/20175thqPCR&dPCREurope
22
91 / 95 samples were alloted to the right species

22. Detection / identification of 5 pathogens in a
multiplex format
Development of a 2nd application
04/12/2017 5th qPCR & dPCR Europe 23

23. Simplex test
04/12/20175thqPCR&dPCREurope
24

24. Multiplex test
04/12/20175thqPCR&dPCREurope
25

25. Influence of target concentration
04/12/20175thqPCR&dPCREurope
26
102 to 105
copies of
pathogen

26. Influence of target concentration
04/12/20175thqPCR&dPCREurope
27
102 to 105
copies of
pathogen

27. Limit of detection
04/12/20175thqPCR&dPCREurope
28
# positives
Pathogen 10 copies / µL 5 copies / µL
A 8/8 8/8
B 4/8 2/8
C 8/8 7/8
D 8/8 8/8
E 8/8 6/8

28. Analysis of clinical samples…
04/12/20175thqPCR&dPCREurope
29

29. …and comparison with TaqMan assays
04/12/20175thqPCR&dPCREurope
30
TaqMan
(Cq value)
HRM
# positive Assignment
31,34 4/4 A
26,6 4/4 A
- 1/4 D
- 2/4 A
- 1/4 A
32,8 4/4 A
30,33 4/4 A
30,3 4/4 A
24,8 4/4 A
18,15 4/4 A
TaqMan
(Cq value)
HRM
# positive Assignment
32,09 1/4 B
25,66 4/4 B
23,02 4/4 B
15,43 4/4 B
16,57 4/4 B
14,61 4/4 B
16,84 4/4 B
24,75 4/4 B
16,38 4/4 B
16,48 4/4 B

30. Comparison with TaqMan assays
04/12/20175thqPCR&dPCREurope
31
TaqMan
(Cq value)
HRM
# positive Assignment
- 1/4 A
33,93 4/4 C
25,59 4/4 C
28,36 4/4 C
- 4/4 E
- 4/4 E
31,17 4/4 C
33,14 4/4 C
30,63 3/4 C
TaqMan
(Cq value)
HRM
# positive Assignment
35,84 3/4 D
35,51 3/4 D
36,85 2/4 A
30,86 4/4 D
37,58 2/4 D
32,53 4/4 D
31,69 4/4 D
32,25 4/4 D
27,6 4/4 D
31,66 4/4 D
TaqMan
(Cq value)
HRM
# positive Assignment
- 3/4 E
32,92 4/4 E
30,46 4/4 E
30,24 4/4 E
28,75 4/4 E
28,98 4/4 E
26,8 4/4 E
27,69 4/4 E
31,29 4/4 E
29,12 4/4 E

31. 3204/12/2017 5th qPCR & dPCR Europe
Conclusions
Confidence index
Fully automated analysis
Upgradable reference library
Simultaneous analysis of many variants

32. 3304/12/2017 5th qPCR & dPCR Europe
melTree workflow
Database(s)Algorithm
+
qPCR
machine
Raw HRM
data
Web interface
Results
Analysis
report

33. 3404/12/2017 5th qPCR & dPCR Europe
Acknowledgments
Christelle REYNES
Lise GREWIS Matthieu VIGNOLLES Mathieu LAFFONT

34. Open to test applications
5th qPCR & dPCR
Europe
35
Requirement: at least 5-10 biological replicates for each variant
jean-christophe.avarre@ird.fr
04/12/2017