Microbead Surface Nucleic Acid Melting Curve Analysis

The MBmca package was developed for the analysis of melt curve data. Specifically, algorithms were developed for the analysis of the melting behavior of nucleic acid hybrids on the surface of microbeads.

However, the software is also useful for the analysis of data from melting curves of qPCRs. The function approximately calculates the maximum and minimum of the second derivative. These values can also be used as quantification points. For example, the maximum of the second derivative is a frequently used parameter in determining the Cq value of qPCRs. A further application can be the analysis of data from opaque isothermal amplifications.

Details on the application of the software are in the publications

  • Rödiger, Böhm, and Schimke (2013)
  • Rödiger et al. (2015)

described.

The software has been lost in conjunction with the VideoScan platform. This is a fully automatic multispectral fluorescence microscope for the multiplex analysis of biomarkers (Rödiger et al. 2013). Applications of the platform can be found in personalized medicine and life sciences (Rödiger et al. 2014, 2018; Willitzki et al. 2012).

Over the years, a lot of knowledge has accumulated on the analysis of data from quantitative PCRs and melting curves. Thus, we could show that the use of filters and smoothing functions affect the parameter estimation of amplification curves (Spiess et al. 2014). The MBmca package also applies filters and smoothing functions to melt curves. This should be taken into account when using the software.

References

Rödiger, Stefan, Alexander Böhm, and Ingolf Schimke. 2013. “Surface Melting Curve Analysis with R.” The R Journal 5 (2): 37–53. http://journal.r-project.org/archive/2013-2/roediger-bohm-schimke.pdf.
Rödiger, Stefan, Michał Burdukiewicz, Konstantin A. Blagodatskikh, and Peter Schierack. 2015. “R as an Environment for the Reproducible Analysis of DNA Amplification Experiments.” The R Journal 7 (2): 127–50. http://journal.r-project.org/archive/2015-1/RJ-2015-1.pdf.
Rödiger, Stefan, Claudia Liebsch, Carsten Schmidt, Werner Lehmann, Ute Resch-Genger, Uwe Schedler, and Peter Schierack. 2014. “Nucleic acid detection based on the use of microbeads: a review.” Microchimica Acta 181 (11-12): 1151–68. https://doi.org/10.1007/s00604-014-1243-4.
Rödiger, Stefan, Marius Liefold, Madeleine Ruhe, Mark Reinwald, Eberhard Beck, and P. Markus Deckert. 2018. “Quantification of DNA Double-Strand Breaks in Peripheral Blood Mononuclear Cells from Healthy Donors Exposed to Bendamustine by an Automated 2AX Assay—an Exploratory Study.” Journal of Laboratory and Precision Medicine 3 (5). http://jlpm.amegroups.com/article/view/4370.
Rödiger, Stefan, Peter Schierack, Alexander Böhm, Jörg Nitschke, Ingo Berger, Ulrike Frömmel, Carsten Schmidt, et al. 2013. “A highly versatile microscope imaging technology platform for the multiplex real-time detection of biomolecules and autoimmune antibodies.” Advances in Biochemical Engineering/Biotechnology 133: 35–74.
Spiess, Andrej-Nikolai, Claudia Deutschmann, Michał Burdukiewicz, Ralf Himmelreich, Katharina Klat, Peter Schierack, and Stefan Rödiger. 2014. “Impact of Smoothing on Parameter Estimation in Quantitative DNA Amplification Experiments.” Clinical Chemistry, December, clinchem.2014.230656. https://doi.org/10.1373/clinchem.2014.230656.
Willitzki, Annika, Rico Hiemann, Vanessa Peters, Ulrich Sack, Peter Schierack, Stefan Rödiger, Ursula Anderer, et al. 2012. “New Platform Technology for Comprehensive Serological Diagnostics of Autoimmune Diseases.” Clinical & Developmental Immunology 2012: 284740. https://doi.org/10.1155/2012/284740.