Soft Matter and Complex Systems Seminar

Quantitative analytical assays are important in many fields of medical diagnostics and research where they are used to estimate quantitatively the concentration of analytes in samples. In the state of art there are multiple 'analogue' assays [1,2] that use a known correlation between the amplitude of a measured signal (e.g. absorbance of light through a sample cell, electrical conductivity of the sample, time of passage of a sample through a porous bed, intensity of fluorescence, amplitude of force exerted on the sample, etc.) and the concentration of analyte in the sample. In the state of art there are also known 'digital' [3,4] assays in which the concentration of the molecules of analyte, or more generally of target particles being either molecules or colloids, is established with the use of a statistical calculation on the basis of the number of binary (negative or positive) signals recorded from a set of independent partitions of the sample. In the digital assays usually the presence of a single, or a known threshold number of particles, or a threshold concentration of particles in the partition of the sample is amplified to a measurable positive signal.

The method presented here bridges the advantages of the analogue and digital assays in an innovative way to provide for high precision of the estimate of concentration of the analyte while requiring a relatively small number of partitions of the sample. In particular the method relates to quantitation assays that i) provide amplification of a finite number (or concentration) of particles to a measurable signal, and ii) provide a signal, the amplitude of which is related to the number of particles (or their concentration) in the inspected volume. The only requirement for the amplitude is that it is an univocal and monotonically increasing function of the number of particles. The functional dependence may be of many different types, e.g. amplitude being linear in the concentration of particles, square in the concentration of particles, or exponential in the number of particles, or any other kind that satisfies the requirement.

This method is applicable to suitable particles selected from the group comprising or consisting of nucleic acids, peptides, proteins, receptors, enzymes, bacteria, pesticides, drugs, steroids, hormones, lipids, sugars, vitamins or any other suitable particles or combinations thereof.

Here we show the performance of the method for quantitative DNA and RNA assessments based on Polymerase Chain Reaction (PCR) [5]. We propose algorithms of division of the sample into compartments that allow to run such diagnostic tests using tools provided by standard Real Time and digital PCR techniques. Also, we provide analytical tools that synergistically bridge information from analogue and digital signals for improved data analysis.

We show the algorithms for optimal division of the sample and data analysis with experimental and numerical verification, also using Monte Carlo simulations.

REFERENCES:
1. “Real-time PCR in clinical microbiology: applications for routine laboratory testing”, M.J. Espy, et al., Clinical Microbiology Reviews, 19, 165 (2006).
2. “On-Chip, Real-Time, Single-Copy Polymerase Chain Reaction in Picoliter Droplets”, N.R. Beer, et al., Analytical Chemistry, 79, 8471 (2007).
3. “Digital PCR”, B. Vogelstein, K.W. Kinzler, Proceedings of the National Academy of Sciences, 96, 9236 (1999).
4. “Multiplexed Quantification of Nucleic Acids with Large Dynamic Range Using Multivolume Digital RT-PCR on a Rotational SlipChip Tested with HIV and Hepatitis C Viral Load”, F. Shen, et al., Journal of the American Chemical Society, 133, 17705 (2011).
5. “Specific synthesis of DNA in vitro via a polymerase-catalyzed chain reaction”, K.B. Mullis, F.A. Faloona, Methods in Enzymology, 155, 335, (1987).
6. “Optimized droplet digital CFU assay (ddCFU) provides precise quantification of bacteria over dynamic range of 6 logs and beyond”, Scheller, O., Pacocha, N., Debski, P.R., Ruszczak, A., Kaminski, T.S., and Garstecki P., Lab on Chip, accepted 26 Apr 2017, first published 28 Apr 2017, DOI: 10.1039/C7LC00206H
7. “Calibration-free assays on standard real-time PCR devices”, Debski, P.R., Gewartowski, K., Bajer, S., and Garstecki, P., Scientific Reports, 2017, 7, 44854
8. “Designing and interpretation of digital assays: Concentration of target in the sample and in the source of sample”, Debski, P.R., and Garstecki, P., Biomolecular Detection and Quantification, 2016, 10, 24-30
9. “Rational design of digital assays”, Debski, P.R., Gewartowski, K., Sulima, M., Kaminski, T.S., and Garstecki, P., Analytical Chemistry, 2015, 87 (16), 8203–8209