Peptide Nucleic Acid Clamp-Assisted Photothermal Multiplexed Digital PCR for Identifying SARS-CoV-2 Variants of Concern

The unprecedented demand for variants diagnosis in response to the COVID-19 epidemic has brought the spotlight onto rapid and accurate detection assays for single nucleotide polymorphisms (SNPs) at multiple locations. However, it is still challenging to ensure simplicity, affordability, and compatibility with multiplexing. Here, a novel technique is presented that combines peptide nucleic acid (PNA) clamps and near-infrared (NIR)-driven digital polymerase chain reaction (dPCR) to identify the Omicron and Delta variants. This is achieved by simultaneously identifying highly conserved mutated signatures at codons 19, 614, and 655 of the spike protein gene. By microfluidically introducing graphene-oxide-nanocomposite into the assembled gelatin microcarriers, they achieved a rapid temperature ramping-up rate and switchable gel-to-sol phase transformation synchronized with PCR activation under NIR irradiation. Two sets of duplex PCR reactions, each classifying respective PNA probes, are emulsified in parallel and illuminated together using a homemade vacuum-based droplet generation device and a programmable NIR control module. This allowed for selective amplification of mutant sequences due to single-base-pair mismatch with PNA blockers. Sequence-recognized bioreactions and fluorescent-color scoring enabled quick identification of variants. This technique achieved a detection limit of 5,100 copies and a 5-fold quantitative resolution, which is promising to unfold minor differences and dynamic changes. PNA-assisted NIR photothermal multiplexed dPCR technique recognizes SNPs at codons T19R, O614G, and H655Y of the spike protein gene, thereby discriminating Omicron and Delta variants from the wild-type of SARS-CoV-2. Gelatin microcarriers loaded with GO nanocomposite assist PCR thermocycling under NIR irradiation, where three PNA probes target against SNPs to selectively amplify mutated templates via replication with multi-color labeling.image