Physico-chemical foundations underpinning microarray and next-generation sequencing experiments

Hybridization of nucleic acids on solid surfaces is a key process involved in high-throughput technologies such as microarrays and, in some cases, next-generation sequencing (NGS). A physical understanding of the hybridization process helps to determine the accuracy of these technologies. The goal of a widespread research program is to develop reliable transformations between the raw signals reported by the technologies and individual molecular concentrations from an ensemble of nucleic acids. This research has inputs from many areas, from bioinformatics and biostatistics, to theoretical and experimental biochemistry and biophysics, to computer simulations. A group of leading researchers met in Ploen Germany in 2011 to discuss present knowledge and limitations of our physico-chemical understanding of high-throughput nucleic acid technologies. This meeting inspired us to write this summary, which provides an overview of the state-of-the-art approaches based on physico-chemical foundation to modeling of the nucleic acids hybridization process on solid surfaces. In addition, practical application of current knowledge is emphasized.     

An algorithm and program for finding sequence specific oligo-nucleotide probes for species identification

Background

The identification of species or species groups with specific oligo-nucleotides as molecular signatures is becoming increasingly popular for bacterial samples. However, it shows also great promise for other small organisms that are taxonomically difficult to tract.

Results

We have devised here an algorithm that aims to find the optimal probes for any given set of sequences. The program requires only a crude alignment of these sequences as input and is optimized for performance to deal also with very large datasets. The algorithm is designed such that the position of mismatches in the probes influences the selection and makes provision of single nucleotide outloops. Program implementations are available for Linux and Windows.     

Revision of the nonequilibrium thermal dissociation and stringent washing approaches for identification of mixed nucleic acid targets by microarrays

Microarray experiments typically involve washing steps that remove hybridized nonspecific targets with the purpose of improving the signal-to-noise ratio. The quality of washing ultimately affects downstream analysis of the microarray and interpretation. The paucity of fundamental studies directed towards understanding the dissociation of mixed targets from microarrays makes the development of meaningful washing/dissociation protocols difficult. To fill the void, we examined activation energies and preexponential coefficients of 47 perfect match (PM) and double-mismatch (MM) duplex pairs to discover that there was no statistical difference between the kinetics of the PM and MM duplexes. Based on these findings, we evaluated the nonequilibrium thermal dissociation (NTD) approach, which has been used to identify specific microbial targets in mixed target samples. We found that the major premises for various washing protocols and the NTD approach might be seriously compromised because: (i) nonspecific duplexes do not always dissociate before specific ones, and (ii) the relationship between dissociation rates of the PM and MM duplexes depends on temperature and duplex sequence. Specifically for the NTD, we show that previously suggested use of reference curves, indices of curves and temperature ramps lead to erroneous conclusions.     

An algorithm for the determination and quantification of components of nucleic acid mixtures based on single sequencing reactions

Background  

Determination and quantification of nucleic acid components in a mixture is usually accomplished by microarray approaches, where the mixtures are hybridized against specific probes. As an alternative, we propose here that a single sequencing reaction from a mixture of nucleic acids holds enough information to potentially distinguish the different components, provided it is known which components can occur in the mixture.     

Constructing a fish metabolic network model

We report the construction of a genome-wide fish metabolic network model, MetaFishNet, and its application to analyzing high throughput gene expression data. This model is a stepping stone to broader applications of fish systems biology, for example by guiding study design through comparison with human metabolism and the integration of multiple data types. MetaFishNet resources, including a pathway enrichment analysis tool, are accessible at .     

Linking probe thermodynamics to microarray quantification

Understanding the difference in probe properties holds the key to absolute quantification of DNA microarrays. So far, Langmuir-like models have failed to link sequence-specific properties to hybridization signals in the presence of a complex hybridization background. Data from washing experiments indicate that the post-hybridization washing has no major effect on the specifically bound targets, which give the final signals. Thus, the amount of specific targets bound to probes is likely determined before washing, by the competition against nonspecific binding. Our competitive hybridization model is a viable alternative to Langmuir-like models.     

Effect of high pressure and reversed micelles on the fluorescent proteins

Two physico-chemical perturbations were applied to ECFP, EGFP, EYFP and DsRed fluorescent proteins: high hydrostatic pressure and encapsulation in reversed micelles. The observed fluorescence changes were described by two-state model and quantified by thermodynamic formalism. ECFP, EYFP and DsRed exhibited similar reaction volumes under pressure. The changes of the chemical potentials of the chromophore in bis(2-ethylhexyl)sulfosuccinate (AOT) micelles caused apparent chromophore protonation changes resulting in a fluorescence decrease of ECFP and EYFP. In contrast to the remarkable stability of DsRed, the highest sensitivity of EYFP fluorescence under pressure and in micelles is attributed to its chromophore structure.     

Concentration dependency of nonequilibrium thermal dissociation curves in complex target samples

The nonequilibrium thermal dissociation (NTD) methodology has been proposed to provide a superior discrimination between specific and nonspecific hybridizations than the commonly used array techniques involving hybridization followed by a single stringent wash. Multiple studies have used this method on gel-pad, planar, and nylon membrane arrays to identify specific microbial targets in complex target mixtures. A recent physicochemical study revealed several problems, particularly when the method was used to examine complex target samples. In the present study, we investigated the effect of target concentration on NTD of complex target samples obtained from an anaerobic bioreactor. Our purpose was to experimentally demonstrate that variation in the concentrations of both specific and nonspecific targets determines the course of dissociation, which was not evaluated in initial microbiological studies. We also present an approach for analyzing the dissociation curves that is less error prone compared to those used in the previous studies. Our results show that: (i) a specific target in a mixture, at a certain concentration, may have a higher dissociation temperature/time than that of the same pure target, and (ii) the concentration dependence of the dissociation precludes usage of reference curves for identifying a target. Contrary to the previous studies, an explicit calibration is required, which makes the NTD approach impractical for high throughput analysis.