Nonequilibrium Effects in DNA Microarrays: A Multiplatform Study

Abstract

It has recently been shown that in some DNA microarrays the time needed to reach thermal equilibrium may largely exceed the typical experimental time, which is about 15h in standard protocols (Hooyberghs et al. Phys. Rev. E 81, 012901 (2010)). In this paper we discuss how this breakdown of thermodynamic equilibrium could be detected in microarray experiments without resorting to real time hybridization data, which are difficult to implement in standard experimental conditions. The method is based on the analysis of the distribution of fluorescence intensities I from different spots for probes carrying base mismatches. In thermal equilibrium and at sufficiently low concentrations, log I is expected to be linearly related to the hybridization free energy ∆G with a slope equal to 1/RT exp , where T exp is the experimental temperature and R is the gas constant. The breakdown of equilibrium results in the deviation from this law. A model for hybridization kinetics explaining the observed experimental behavior is discussed, the so-called 3-state model. It predicts that deviations from equilibrium yield a proportionality of log I to ∆G/RT eff . Here, T eff is an "effective" temperature, higher than the experimental one. This behavior is indeed observed in some experiments on Agilent arrays. 16,20 We analyze experimental data from two other microarray platforms and discuss, on the basis of the results, the attainment of equilibrium in these cases. Interestingly, the same 3-state model predicts a (dynamical) saturation of the signal at values below the expected one at equilibrium.

Probing hybridization parameters from microarray experiments: nearest-neighbor model and beyond

“…A previous study [9] in which hybridizing strands were 30-mers did not provide a single straight line in a ln I versus ∆∆G plot. Deviations due to lack of thermodynamic equilibrium were observed in the high-intensity ranges, as discussed in [11,13].…”

Biophysical properties of nucleic acids at surfaces relevant to microarray performance

“…The real problem lies in assays of heterogeneous ssDNA targets where diverse sequences, lengths, mixed target and non-target concentrations and possible mismatch duplex co-equilibria confound approaches to a single equilibrium assay endpoint. [203, 211, 212]. Incubation times often vary, different even for similar concentrations of probe and target, but depending on assay conditions and largely influenced by ssDNA probe density distributions and ssDNA sequence and length.…”

“…These studies suggested the feasibility of electrostatic control for DNA hybridization and design of assays to avoid DNA secondary structure folding problems (i.e., self complimentarity). [212] They used linear Poisson–Boltzmann theory for double-layer interactions between an ion-penetrable sphere and a hard plate with variables including binding enthalpy, entropy and equilibrium reaction constants for the immobilized complex. They also developed a mean field model for Coulombic effects in two-dimensional DNA arrays to understand the binding isotherms and thermal denaturation of the double helix.…”

“…Assays that terminate before equilibrium is reached could produce an inaccurate answer. [203, 204, 212] Experimental designs including microfluidic, statistical modeling and simulation approaches should be considered to understand the kinetics of real time hybridization in microarrays in complex milieu for efficient endpoint analysis.…”

Stochastic Ratchet Mechanisms for Replacement of Proteins Bound to DNA

“…A more general (and precise) model would describe the invading protein through a binding energy ε ′ different from the binding energy ε for the bound protein in case of heterogeneous replacement, as well through its number of bound units, rather than the on/off description used here. Binding/unbinding of small DNA fragments (oligonucleotide) on a DNA under force [11] and exchange of DNA-binding oligonucleotides in DNA hybridization assays [9, 13, 14] are likely described by the Z-S-SB model. Including sequence specificity (dependence of ε on the sites) could help in modeling such experiments [12].…”