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Real Time RT-PCR

Real Time RT-PCR

Real-time reverse transcription-polymerase chain reaction, or Real-time RT-PCR, is an analytical tool used to determine the expression level of target genes. The method involves converting mRNA to complementary DNA with the help of an enzyme known as reverse transcriptase, followed by the PCR amplification of the cDNA. These two processes can be performed simultaneously in a single tube or separately as a two-step reaction.
The real-time quantification of the number of amplified products is...

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Author Spotlight: Advancing Pathogen Diagnostics with Standardized LAMP

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Published on: September 8, 2023

Data treatment methods for real-time colorimetric loop-mediated isothermal amplification reactions.

Edson Yu Sin Kim¹, Louise Matiê Imamura¹, Bruna Winkert Raddatz²

¹Hilab, Rua José Altair Possebom, 800-CIC, Curitiba, Paraná, 81270-185, Brazil.

Scientific Reports

|September 1, 2023

Summary

Loop-Mediated Isothermal Amplification (LAMP) offers rapid, affordable SARS-CoV-2 testing. This study identifies the double sigmoid equation as the best model for analyzing time-course LAMP data, improving assay interpretation.

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Area of Science:

Molecular Biology
Biotechnology
Diagnostic Assays

Background:

The SARS-CoV-2 pandemic highlighted the need for accessible, rapid diagnostic testing.
Isothermal amplification reactions, like Loop-Mediated Isothermal Amplification (LAMP), are gaining prominence for their potential in mass testing.
Time-course analysis of LAMP reactions offers richer data than endpoint detection, but requires standardized quantitative analysis methods.

Purpose of the Study:

To evaluate different data treatment models for quantitative analysis of isothermal amplification curves.
To identify the most suitable model for extracting cycle threshold-like parameters from LAMP amplification data.
To advance standardized and unbiased data reporting for Reverse Transcription (RT) LAMP reactions.

Main Methods:

Evaluation of various mathematical models for fitting isothermal amplification curves.
Application of curve fitting to time-course data generated from a remote diagnostics system.
Demonstration of multimodal Gompertz regression models for data analysis.

Main Results:

The double sigmoid equation was identified as the most adequate model for describing the amplification data.
This model facilitates the extraction of quantitative parameters analogous to the cycle threshold in qPCR.
The findings support the use of advanced regression models for analyzing RT-LAMP data.

Conclusions:

Standardized quantitative analysis of RT-LAMP data is crucial for reliable assay interpretation.
The double sigmoid model provides a robust method for analyzing amplification curves from isothermal reactions.
This work paves the way for machine learning applications in RT-LAMP assay optimization and classification.