Interlaboratory Performance of a Real-Time PCR Method for Detection of Ceratocystis platani, the Agent of Canker Stain of Platanus spp.
Abstract
:1. Introduction
2. Materials and Methods
2.1. Wood Sample Collection and Assessment of Their Infectious Status
2.2. DNA Extraction
2.3. The Participating Laboratories (PL), the Real-Time PCR Methods, Master Mixes, and Cycling Protocols
2.4. Diagnostic Confirmation of DNA-Stock-Samples (Dss), Aliquoting, Homogeneity Testing, and the Shipping Material
- -
- 16 blind test samples—15 DNA extracts from wood, and one from an axenic C. platani culture.
- -
- 2 controls: PAC and NAC obtained from NI.3 and H.1 (also supplied as blind Das).
- -
- 1 positive wood extract sample for the standard curve experiments (obtained from NI.2, also supplied as a blind Das), labelled DNA-aliquot-St.Cu. (Da.St.Cu.)
- -
- The gDNA from an axenic culture of C. platani for use in the analytical sensitivity test (also supplied as a blind Das)
2.5. Stability Test
2.6. The Test Performance Study with Real-Time PCR: (i) Generating Standard Curves, (ii) Testing Blind-Coded DNA-Aliquot-Samples (iii) Testing Analytical Sensitivity
2.7. Performance Criteria, Nomenclature, and Statistical Analysis
2.8. Outliers
2.9. Disclosure Policy by the Organiser
3. Results
3.1. Sample Preparation
3.2. Thermal Cycling Adjustments
3.3. Test Performance Study: Generating Standard Curves
3.4. Test Performance Study: Blind Testing of DNA-Aliquot-Samples
3.5. Test Performance Study: Testing Analytical Sensitivity
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Appendix A
References
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Sample ID | Nature of the Sample | Number of Samples | Sample Type | Expected Detection |
---|---|---|---|---|
NI.1→ NI.3 | C. platani Naturally-Infected tree | 3 | Blind samples | Positive |
AI.1→AI.6 | C. platani Artificially-Infected tree | 6 | Blind samples | Positive |
H.1→H.3 | Healthy tree | 3 | Blind samples | Negative |
D.1→D.3 | Diseased tree infected with non-target species | 3 | Blind samples | Negative |
gDNA C.P. 32 | Pure C. platani colony | 1 | Blind sample | Positive |
NAC | Healthy tree (=H.1) | 1 | Negative amplification control | Negative |
PAC | C. platani Naturally-Infected tree (=NI.3) | 1 | Positive amplification control | Positive |
DNA-aliquot-St.Cu | C. platani Naturally-Infected tree (=NI.2) | 1 | Standard curve validation | Positive |
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dss 1 | NI.1 | NI.2 | NI3 | AI.1 | AI2 | AI3 | AI4 | AI5 | AI6 | H.1 | H.2 | H.3 | D.1 | D.2 | D.3 | gDNA C.P. 32 | PAC (=NI.3) | NAC (=H.1) | Da.St.Cu. (=NI.2) | gDNA C.P. 32 |
Z (OL) | 6 | 3 | 11 | 12 | 14 | 15 | 10 | 2 | 1 | 4 | 7 | 5 | 8 | 16 | 9 | 13 | + | + | + | + |
A | 3 | 14 | 13 | 10 | 7 | 9 | 11 | 15 | 12 | 1 | 8 | 16 | 4 | 6 | 5 | 2 | + | + | + | + |
B | 12 | 7 | 14 | 16 | 15 | 11 | 8 | 6 | 10 | 2 | 13 | 3 | 1 | 9 | 4 | 5 | + | + | + | + |
C | 11 | 12 | 15 | 14 | 6 | 4 | 3 | 10 | 7 | 9 | 1 | 2 | 16 | 5 | 13 | 8 | + | + | + | + |
D | 9 | 5 | 7 | 8 | 13 | 10 | 16 | 11 | 15 | 12 | 4 | 1 | 6 | 2 | 3 | 14 | + | + | + | + |
E | 7 | 9 | 2 | 5 | 12 | 1 | 4 | 13 | 3 | 11 | 6 | 8 | 15 | 14 | 16 | 10 | + | + | + | + |
F | 4 | 16 | 10 | 11 | 9 | 5 | 13 | 1 | 6 | 7 | 3 | 15 | 2 | 8 | 14 | 12 | + | + | − | + |
G | 2 | 13 | 8 | 7 | 10 | 14 | 12 | 5 | 16 | 15 | 9 | 11 | 3 | 4 | 6 | 1 | + | + | + | + |
H | 10 | 15 | 6 | 9 | 2 | 13 | 5 | 12 | 14 | 3 | 16 | 4 | 7 | 1 | 8 | 11 | + | + | − | + |
OL, PL | Taqman | EvaGreen | SYBR Green |
---|---|---|---|
Z |
|
|
|
A1 |
| ||
A2 |
| ||
A3 |
| ||
A4 |
| ||
B |
| ||
B1 |
| ||
B2 |
| ||
C1 |
| ||
C2 |
| ||
D |
|
| |
E |
|
| |
F |
|
| |
G |
|
| |
H1 |
| ||
H2 |
|
Performance Criteria | Acronyms and Calculation | Legenda | Best Performance Level (%) |
---|---|---|---|
Accuracy | AC = (NTP + NTN)/N | NTP NTN = number of true positives and true negatives N = total number of tested sample | 100 |
Diagnostic sensitivity | DSE = NTP/N+ | N+ = number of samples for which the assigned value is positive (i.e., Ceratocystis platani-positive) | 100 |
Diagnostic specificity | DSP = NTN/N− | N− = number of samples for which the assigned value is negative (i.e., Ceratocystis platani-negative) | 100 |
Repeatability | DA = (NTP/N)2 + (NTN/N)2 | See above | 1 |
Reproducibility | CO—Calculate the interlaboratory pairs sharing the same (and conforming) results and infer the percentage compared to the total number of the interlaboratory pairs | 100 |
Laboratory Code 1 | Assay | E 2 (%) | R˄2 3 | Slope 4 | Intercept |
---|---|---|---|---|---|
Z | Taqman | 96.3 | 0.999 | −3.413 | 34.041 |
A1 | Taqman | 94.9 | 0.999 | −3.451 | 34.426 |
A3 | Taqman | 95.3 | 0.999 | −3.439 | 33.987 |
A4 | Taqman | 101.4 | 0.999 | −3.288 | 31.492 |
B1 | Taqman | 99.9 | 0.999 | −3.323 | 34.102 |
B2 | Taqman | 102.3 | 0.999 | −3.269 | 34.129 |
C1 | Taqman | 97.9 | 0.999 | −3.373 | 29.367 |
C2 | Taqman | 101.4 | 0.999 | −3.288 | 29.236 |
D | Taqman | 79.7 | 0.998 | −3.930 | 35.751 |
E | Taqman | 96.3 | 0.999 | −3.413 | 33.749 |
F | Taqman | 94.1 | 0.999 | −3.472 | 34.460 |
Z | EvaGreen | 98.3 | 1.000 | −3.362 | 33.720 |
D | EvaGreen | 74.3 | 0.998 | −4.143 | 35.968 |
E | EvaGreen | 99.5 | 0.999 | −3.335 | 33.484 |
F | EvaGreen | 98.4 | 0.999 | −3.360 | 33.967 |
G | EvaGreen | 100.7 | 0.999 | −3.304 | 33.512 |
Z | SYBR Green | 98.8 | 0.999 | −3.352 | 30.738 |
B | SYBR Green | 99.1 | 0.992 | −3.343 | 30.451 |
H1 | SYBR Green | 96.7 | 0.999 | −3.404 | 32.052 |
H2 | SYBR Green | 95.8 | 0.999 | −3.427 | 32.092 |
Performance Parameters | TM.Z | TM.A1 | TM.A2 | TM.B1 | TM.B2 | TM.C1 | TM.C2 | TM.D | TM.E | TM.F | TM.G | TM Global |
---|---|---|---|---|---|---|---|---|---|---|---|---|
DSE | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 |
DSP | 100 | 100 | 100 | 100 | 88.9 * (81.2–93.7) | 100 | 100 | 100 | 100 | 100 | 100 | 99.0 (94.5–99.9) |
AC | 100 | 100 | 100 | 100 | 95.8 * (89.9–98.3) | 100 | 100 | 100 | 100 | 100 | 100 | 99.6 (95.6–99.9) |
CO | 99.2 (94.8–99.9) | |||||||||||
Performance parameters | EG.Z | EG.D | EG.E | EG.F | EG.G | EG global | SG.Z | SG.B | SG.H1 | SG.H2 | SG global | |
DSE | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | |
DSP | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 66.7 * (57.0–75.2) | 91.7 (84.6–95.7) | |
AC | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 100 | 87.5 * (79.6–92.6) | 96.9 (91.4–98.9) | |
CO | 100 | 93.2 (86.5–96.7) |
Performance Parameters at 15fg 1 | TM.Z | TM.A1 | TM.A2 | TM.B | TM.C | TM.E | TM.F | TM.G | TM. Global |
---|---|---|---|---|---|---|---|---|---|
DSE | 100 | 100 | 100 | 100 | 100 | 100 | 83.3 * (74.8–89.3) | 83.3 * (74.8–89.3) | 95.7 (89.8–98.3) |
DA | 1 | 1 | 1 | 1 | 1 | 1 | 0.7 * (0.10–0.98) | 0.7 * (0.10–0.98) | N.E.2 |
AC | 100 | 100 | 100 | 100 | 100 | 100 | 83.3 * (74.8–89.3) | 83.3 * (74.8–89.3) | 95.7 (89.8–98.3) |
CO | 92.9 (86.1–96.5) | ||||||||
Performance parameters at 15fg 1 | EG.Z | EG.E | EG. global | SG.Z | SG.H1 | SG.H2 | SG. global | ||
DSE | 100 | 100 | 100 | 100 | 100 | 100 | 100 | ||
DA | 1 | 1 | N.E. 2 | 1 | 1 | 1 | N.E. 2 | ||
AC | 100 | 100 | 100 | 100 | 100 | 100 | 100 | ||
CO | 100 | 100 | |||||||
Performance parameters at 3 fg 1 | TM.Z | TM.A1 | TM.A2 | TM.B | TM.C | TM.E | TM.F | TM.G | TM. global |
DSE | 100 | 50 * (40.3–59.6) | 83.3 * (74.8–89.3) | 100 | 100 | 83.3 * (74.8–89.3) | 83.3 * (74.8–89.3) | 100 | 87.2 (79.2–92.4) |
DA | 1 | 0.2 * (0.01–0.86) | 0.7 * (0.1–0.98) | 1 | 1 | 0.7 * (0.1–0.98) | 0.7 * (0.1–0.98) | 1 | N.E. 2 |
AC | 100 | 50 * (40.3–59.6) | 83.3 * (74.8–89.3) | 100 | 100 | 83.3 * (74.8–89.3) | 83.3 * (74.8–89.3) | 100 | 87.2 (79.2–92.4) |
CO | 76.2 (67.0–83.4) | ||||||||
Performance parameters at 3 fg 1 | EG.Z | EG.E | EG. global | SG.Z | SG.H1 | SG.H2 | SG. global | ||
DSE | 100 | 100 | 100 | 100 | 100 | 100 | 100 | ||
DA | 1 | 1 | N.E. 2 | 1 | 1 | 1 | N.E. 2 | ||
AC | 100 | 100 | 100 | 100 | 100 | 100 | 100 | ||
CO | 100 | 100 |
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Brunetti, A.; Heungens, K.; Hubert, J.; Ioos, R.; Bianchi, G.L.; De Amicis, F.; Chandelier, A.; Van Der Linde, S.; Perez-Sierra, A.; Gualandri, V.; et al. Interlaboratory Performance of a Real-Time PCR Method for Detection of Ceratocystis platani, the Agent of Canker Stain of Platanus spp. J. Fungi 2022, 8, 778. https://doi.org/10.3390/jof8080778
Brunetti A, Heungens K, Hubert J, Ioos R, Bianchi GL, De Amicis F, Chandelier A, Van Der Linde S, Perez-Sierra A, Gualandri V, et al. Interlaboratory Performance of a Real-Time PCR Method for Detection of Ceratocystis platani, the Agent of Canker Stain of Platanus spp. Journal of Fungi. 2022; 8(8):778. https://doi.org/10.3390/jof8080778
Chicago/Turabian StyleBrunetti, Angela, Kurt Heungens, Jacqueline Hubert, Renaud Ioos, Gian Luca Bianchi, Francesca De Amicis, Anne Chandelier, Sietse Van Der Linde, Ana Perez-Sierra, Valeria Gualandri, and et al. 2022. "Interlaboratory Performance of a Real-Time PCR Method for Detection of Ceratocystis platani, the Agent of Canker Stain of Platanus spp." Journal of Fungi 8, no. 8: 778. https://doi.org/10.3390/jof8080778