Dynamic range extension of hybridization sensors

Molecular drug susceptibility testing and strain typing of tuberculosis by DNA hybridization

In Mycobacterium tuberculosis (Mtb) the detection of single nucleotide polymorphisms (SNPs) is of high importance both for diagnostics, since drug resistance is primarily caused by the acquisition of SNPs in multiple drug targets, and for epidemiological studies in which strain typing is performed by SNP identification. To provide the necessary coverage of clinically relevant resistance profiles and strain types, nucleic acid-based measurement techniques must be able to detect a large number of potential SNPs. Since the Mtb problem is pressing in many resource-poor countries, requiring low-cost point-of-care biosensors, this is a non-trivial technological challenge. This paper presents a proof-of-concept in which we chose simple DNA-DNA hybridization as a sensing principle since this can be transferred to existing low-cost hardware platforms, and we pushed the multiplex boundaries of it. With a custom designed probe set and a physicochemical-driven data analysis it was possible to simultaneously detect the presence of SNPs associated with first- and second-line drug resistance and Mtb strain typing. We have demonstrated its use for the identification of drug resistance and strain type from a panel of phylogenetically diverse clinical strains. Furthermore, reliable detection of the presence of a minority population (<5%) of drug-resistant Mtb was possible.

Sequence characteristics define trade-offs between on-target and genome-wide off-target hybridization of oligoprobes

Off-target oligoprobe's interaction with partially complementary nucleotide sequences represents a problem for many bio-techniques. The goal of the study was to identify oligoprobe sequence characteristics that control the ratio between on-target and off-target hybridization. To understand the complex interplay between specific and genome-wide off-target (cross-hybridization) signals, we analyzed a database derived from genomic comparison hybridization experiments performed with an Affymetrix tiling array. The database included two types of probes with signals derived from (i) a combination of specific signal and cross-hybridization and (ii) genomic cross-hybridization only. All probes from the database were grouped into bins according to their sequence characteristics, where both hybridization signals were averaged separately. For selection of specific probes, we analyzed the following sequence characteristics: vulnerability to self-folding, nucleotide composition bias, numbers of G nucleotides and GGG-blocks, and occurrence of probe's k-mers in the human genome. Increases in bin ranges for these characteristics are simultaneously accompanied by a decrease in hybridization specificity-the ratio between specific and cross-hybridization signals. However, both averaged hybridization signals exhibit growing trends along with an increase of probes' binding energy, where the hybridization specific signal increases significantly faster in comparison to the cross-hybridization. The same trend is evident for the S function, which serves as a combined evaluation of probe binding energy and occurrence of probe's k-mers in the genome. Application of S allows extracting a larger number of specific probes, as compared to using only binding energy. Thus, we showed that high values of specific and cross-hybridization signals are not mutually exclusive for probes with high values of binding energy and S. In this study, the application of a new set of sequence characteristics allows detection of probes that are highly specific to their targets for array design and other bio-techniques that require selection of specific probes.

Thermodynamic framework to assess low abundance DNA mutation detection by hybridization

The knowledge of genomic DNA variations in patient samples has a high and increasing value for human diagnostics in its broadest sense. Although many methods and sensors to detect or quantify these variations are available or under development, the number of underlying physico-chemical detection principles is limited. One of these principles is the hybridization of sample target DNA versus nucleic acid probes. We introduce a novel thermodynamics approach and develop a framework to exploit the specific detection capabilities of nucleic acid hybridization, using generic principles applicable to any platform. As a case study, we detect point mutations in the KRAS oncogene on a microarray platform. For the given platform and hybridization conditions, we demonstrate the multiplex detection capability of hybridization and assess the detection limit using thermodynamic considerations; DNA containing point mutations in a background of wild type sequences can be identified down to at least 1% relative concentration. In order to show the clinical relevance, the detection capabilities are confirmed on challenging formalin-fixed paraffin-embedded clinical tumor samples. This enzyme-free detection framework contains the accuracy and efficiency to screen for hundreds of mutations in a single run with many potential applications in molecular diagnostics and the field of personalised medicine.