High-Throughput Methylation-Specific Triplet-Primed PCR and Melting Curve Analysis for Selective and Reliable Identification of Actionable FMR1 Genotypes

Abstract Mutations in the kinase domain of BCR-ABL result in impaired drug binding and are thought to be the leading cause of acquired resistance to the tyrosine kinase inhibitor imatinib (Gleevec®). While imatinib is a highly effective therapy in all stages of chronic myelogenous leukemia (CML), relapse after an initial response is common in patients with advanced disease. The T315I point mutation is one of the most common imatinib-resistant mutations and patients with this mutation are also resistant to two second generation tyrosine kinase inhibitors, dasatinib and nilotinib. Recently, the U.S. FDA approved dasatinib for treatment of imatinib-resistant, Philadelphia chromosome-positive acute and chronic leukemias. Thus, appropriate detection of this mutation is essential to optimal management of patients with imatinib resistance and may be useful for clinical trials of agents that target patients with the T315I mutation. Current methods for mutation detection, such as direct DNA sequencing, are not sensitive enough for detection of point mutations at low levels of BCR-ABL transcript. Conversely, ultrasensitive detection methods such as allele specific PCR (AS-PCR) may be too sensitive and can be plagued by false positive test results. In addition the clinical relevance/significance of mutation detection at ultra sensitive levels ( < 1% mutant) is questionable and not yet known. We developed a novel T315I mutation detection assay, using Fluorescent Resonance Energy Transfer (FRET)-based hybridization probes and melting curve analysis. BCR-ABL amplicons generated from a first round of PCR are amplified using primers flanking the ABL kinase region encoding for codon 315. The resultant amplicon is hybridized with fluorescein-labelled anchor probe and a LC Red 640-labelled T315I mutation specific probe. Wild-type and T315I mutant amplicons are distinguished by melting curve analysis (Roche Light Cycler 480™). Using a series of plasmid and cell line dilutions we determined that the sensitivity of this assay for detection of T315I mutations was 5–10%. Using patient-derived samples we were able to successfully genotype samples containing as few as 20–50 BCR-ABL transcripts. To date, the assay sensitivity and specificity are 100%. The assay is performed in a plate based format (96 or 384 wells) and commercially available software allows automated genotype assignment. This approach is suitable for high-throughput detection of T315I mutations for clinical management of CML patients and/or screening of patients to determine eligibility for clinical studies.

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Correction: High-Throughput Genome Editing and Phenotyping Facilitated by High Resolution Melting Curve Analysis

PLoS ONE ◽

10.1371/journal.pone.0117764 ◽

2015 ◽

Vol 10 (2) ◽

pp. e0117764 ◽

Cited By ~ 1

Author(s):

Keyword(s):

High Resolution ◽

Genome Editing ◽

High Throughput ◽

High Resolution Melting ◽

Melting Curve ◽

Curve Analysis ◽

Melting Curve Analysis ◽

High Resolution Melting Curve

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High-throughput avian molecular sexing by SYBR green-based real-time PCR combined with melting curve analysis

BMC Biotechnology ◽

10.1186/1472-6750-8-12 ◽

2008 ◽

Vol 8 (1) ◽

pp. 12 ◽

Cited By ~ 42

Author(s):

Hsueh-Wei Chang ◽

Chun-An Cheng ◽

De-Leung Gu ◽

Chia-Che Chang ◽

San-Hua Su ◽

...

Keyword(s):

Real Time ◽

High Throughput ◽

Real Time Pcr ◽

Melting Curve ◽

Curve Analysis ◽

Sybr Green ◽

Melting Curve Analysis ◽

Molecular Sexing

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Description and validation of high-throughput simultaneous genotyping and mutation scanning by high-resolution melting curve analysis

European Journal of Cancer Supplements ◽

10.1016/s1359-6349(08)71558-1 ◽

2008 ◽

Vol 6 (9) ◽

pp. 100

Author(s):

T. Nguyen ◽

F. Lesueur ◽

N. Forey ◽

D. De Silva ◽

R. Weigel ◽

...

Keyword(s):

High Resolution ◽

High Throughput ◽

High Resolution Melting ◽

Melting Curve ◽

Curve Analysis ◽

Melting Curve Analysis ◽

Mutation Scanning ◽

High Resolution Melting Curve

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Coupling machine learning and high throughput multiplex digital PCR enables accurate detection of carbapenem-resistant genes in clinical isolates

10.1101/2021.04.16.21255464 ◽

2021 ◽

Author(s):

Luca Miglietta ◽

Ahmad Moniri ◽

Ivana Pennisi ◽

Kenny Malpartida Cardenas ◽

Hala Abbas ◽

...

Keyword(s):

Machine Learning ◽

Real Time ◽

High Throughput ◽

Classification Accuracy ◽

Melting Curve ◽

Digital Pcr ◽

Curve Analysis ◽

Melting Curve Analysis ◽

Carbapenem Resistant ◽

Resistant Genes

Background: The emergence and spread of carbapenemase-producing organisms (CPO) are a significant clinical and public health concern. Rapid and accurate identification of patients colonised with CPO is essential to adopt prompt prevention measures in order to reduce the risk of transmission. Recent proof-of-concept studies have demonstrated the ability to combine machine learning (ML) algorithms with real-time digital PCR (dPCR) instruments to increase classification accuracy of multiplex assays. From this, we sought to determine if this ML based methodology could accurately identify five major carbapenem-resistant genes in clinical CPO-isolates. Methods: We collected 253 clinical isolates (including 221 CPO-positive samples) and developed a novel 5-plex assay for detection of blaVIM, blaOXA-48, blaNDM, blaIMP and blaKPC. Combining the recently reported ML method "Amplification and Melting Curve Analysis" (AMCA) with the abovementioned multiplex assay, we assessed the performance of the methodology in detecting these five carbapenem-resistant genes. The classification accuracy relies on the usage of real-time data from a single fluorescent channel and benefits from the kinetic and thermodynamic information encoded in the thousands of amplification events produced by high throughput dPCR. Results: The 5-plex showed a lower limit of detection of 100 DNA copies per reaction for each primer set and no cross-reactivity with other carbapenemase genes. The AMCA classifier demonstrated excellent predictive performance with 99.6% (CI 97.8-99.9%) accuracy (only one misclassified sample out of the 253, with a total of 163,966 positive amplification events), which represents a 7.9% increase compared to the conventional ML-based melting curve analysis (MCA) method. Conclusion: This work demonstrates the utility of the AMCA method to increase the throughput and performance of state-of-the-art molecular diagnostic platforms, reducing costs without any changes to instrument hardware. Our findings suggest that, pending additional validation directly from clinical samples, advanced data-driven multiplex dPCR could potentially be integrated in routine clinical diagnostic workflows.

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Coupling Machine Learning and High Throughput Multiplex Digital PCR Enables Accurate Detection of Carbapenem-Resistant Genes in Clinical Isolates

Frontiers in Molecular Biosciences ◽

10.3389/fmolb.2021.775299 ◽

2021 ◽

Vol 8 ◽

Author(s):

Luca Miglietta ◽

Ahmad Moniri ◽

Ivana Pennisi ◽

Kenny Malpartida-Cardenas ◽

Hala Abbas ◽

...

Keyword(s):

Machine Learning ◽

Real Time ◽

High Throughput ◽

Classification Accuracy ◽

Melting Curve ◽

Digital Pcr ◽

Curve Analysis ◽

Melting Curve Analysis ◽

Carbapenem Resistant ◽

Resistant Genes

Rapid and accurate identification of patients colonised with carbapenemase-producing organisms (CPOs) is essential to adopt prompt prevention measures to reduce the risk of transmission. Recent studies have demonstrated the ability to combine machine learning (ML) algorithms with real-time digital PCR (dPCR) instruments to increase classification accuracy of multiplex PCR assays when using synthetic DNA templates. We sought to determine if this novel methodology could be applied to improve identification of the five major carbapenem-resistant genes in clinical CPO-isolates, which would represent a leap forward in the use of PCR-based data-driven diagnostics for clinical applications. We collected 253 clinical isolates (including 221 CPO-positive samples) and developed a novel 5-plex PCR assay for detection of blaIMP, blaKPC, blaNDM, blaOXA-48, and blaVIM. Combining the recently reported ML method “Amplification and Melting Curve Analysis” (AMCA) with the abovementioned multiplex assay, we assessed the performance of the AMCA methodology in detecting these genes. The improved classification accuracy of AMCA relies on the usage of real-time data from a single-fluorescent channel and benefits from the kinetic/thermodynamic information encoded in the thousands of amplification events produced by high throughput real-time dPCR. The 5-plex showed a lower limit of detection of 10 DNA copies per reaction for each primer set and no cross-reactivity with other carbapenemase genes. The AMCA classifier demonstrated excellent predictive performance with 99.6% (CI 97.8–99.9%) accuracy (only one misclassified sample out of the 253, with a total of 160,041 positive amplification events), which represents a 7.9% increase (p-value <0.05) compared to conventional melting curve analysis. This work demonstrates the use of the AMCA method to increase the throughput and performance of state-of-the-art molecular diagnostic platforms, without hardware modifications and additional costs, thus potentially providing substantial clinical utility on screening patients for CPO carriage.

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