From saliva to SNP: non-invasive, point-of-care genotyping for precision medicine applications using recombinase polymerase amplification and giant magnetoresistive nanosensors

Abstract

Genetic testing is considered a cornerstone of the precision medicine paradigm. Genotyping of single nucleotide polymorphisms (SNPs) has been shown to provide insights into several important issues, including therapy selection and drug responsiveness. However, a scarcity of widely deployable and cost-effective genotyping tools has limited the integration of precision medicine into routine clinical practice. The objective of our work was to develop a portable, cost-effective, and automated platform that performs SNP genotyping at the point-of-care (POC). Using recombinase polymerase amplification (RPA) and giant magnetoresistive (GMR) nanosensors, we present a highly automated and multiplexed point-of-care platform that utilizes direct saliva for the qualitative genotyping of four SNPs (rs4633, rs4680, rs4818, rs6269) along the catechol-O-methyltransferase gene (COMT), which is associated with the modulation of pain sensitivity and perioperative opioid use. Using this approach, we successfully amplify, detect, and genotype all four of the SNPs, demonstrating 100% accordance between the experimental results obtained using the automated RPA and GMR genotyping assay and the results obtained using a COMT PCR genotyping assay that was formerly validated using pyrosequencing. This automated, portable, and multiplexed RPA and GMR assay shows great promise as a solution for SNP genotyping at the POC and reinforces the broad applications of magnetic nanotechnology in biomedicine.

Figure 1 -

An overview of the proposed combined RPA and GMR workflow. (a) Template gDNA is obtained from a direct saliva sample; (b) Target sequences are amplified via RPA using biotinylated primers; (c) Product of RPA reaction is denatured to obtain biotinylated ssDNA; (d) Denatured product is added to the GMR nanosensor array, where it hybridizes to complementary probes; (e) Signal is acquired by adding MNPs to the solution, wherein the MNPs bind to the biotinylated amplicons, generating a detectable signal that reflects the abundance of amplicons located on each sensor.

Figure 2 -

A schematic overview of the PCB designed for sample incubation (during RPA) and denaturation, and the temperature sensing design. (a) A top layer perspective of the PCB. (b) A bottom layer perspective of the PCB. (c) A circuit schematic of the temperature sensing and modulation system.

Figure 3 -

(a) A side view of the chip-carrying PCB showing how the reaction well temperature is modulated. (b) A circuit schematic of the hybridization temperature monitoring and control system. Sensor resistances are sampled and processed by the existing conditioning path.

Figure 4 -

An image of the proposed point-of-care assay platform in its portable housing. A schematic of the cartridge and an image of the components comprising the platform are included for further elucidation.

Figure 5 -

Sample endpoint GMR signals obtained for an experiment prepared according to the multiplexed RPA reaction protocol.

Figure 6 -

(a) Bar plot showing the mean normalized delta values calculated for the three possible genotypes (WT, HZ, MT) corresponding to each of the four SNPs. Error bars reflect one standard deviation between the three respective normalized delta values considered when calculating the corresponding mean. (b) Final numerical bounds that were used to classify each genotype for each SNP.

Figure 7 -

A summary of the genotyping results obtained for each sample during validation experiments performed using (a) the standard salivary gDNA extraction protocol and (b) the salivary quick extract solution. Each sample’s corresponding PCR genotyping assay results are included for reference/to determine accuracy. Boxes reporting experimental results are color-coded to reflect their genotyping classification based on the reference response values.

Figure 8 -

Results corresponding to hybridization time optimization experiments. Endpoint GMR signals corresponding to (a) rs4633, (b) rs4680, (c) rs4818, (d) rs6269 are plotted at each of the hybridization time periods tested. Dotted lines in (a)–(d) correspond to the respective background signals, which were obtained as discussed in Supplementary Information, Section S1.3. (e) Experimental genotyping results obtained after each hybridization period compared against PCR genotyping results.