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COVID-19 remains an ongoing issue across the globe, highlighting the need for a rapid, selective, and accurate sensor for SARS-CoV-2 and its emerging variants. The chemical specificity and signal amplification of surface-enhanced Raman spectroscopy (SERS) could be advantageous for developing a quantitative assay for SARS-CoV-2 with improved speed and accuracy over current testing methods. Here, we have tackled the challenges associated with SERS detection of viruses. As viruses are large, multicomponent species, they can yield different SERS signals, but also other abundant biomolecules present in the sample can generate undesired signals. To improve selectivity in complex biological environments, we have employed peptides as capture probes for viral proteins and developed an angiotensin-converting enzyme 2 (ACE2) mimetic peptide-based SERS sensor for SARS-CoV-2. The unique vibrational signature of the spike protein bound to the peptide-modified surface is identified and used to construct a multivariate calibration model for quantification. The sensor demonstrates a 300 nM limit of detection and high selectivity in the presence of excess bovine serum albumin. This work provides the basis for designing a SERS-based assay for the detection of SARS-CoV-2 as well as engineering SERS biosensors for other viruses in the future.

Inspired by the role of cell-surface glycoproteins as coreceptors for pathogens, we report the development of GlycoGrip : a glycopolymer-based lateral flow assay for detecting SARS-CoV-2 and its variants. GlycoGrip utilizes glycopolymers for primary capture and antispike antibodies labeled with gold nanoparticles for signal-generating detection. A lock-step integration between experiment and computation has enabled efficient optimization of GlycoGrip test strips which can selectively, sensitively, and rapidly detect SARS-CoV-2 and its variants in biofluids. Employing the power of the glycocalyx in a diagnostic assay has distinct advantages over conventional immunoassays as glycopolymers can bind to antigens in a multivalent capacity and are highly adaptable for mutated strains. As new variants of SARS-CoV-2 are identified, GlycoGrip will serve as a highly reconfigurable biosensor for their detection. Additionally, via extensive ensemble-based docking simulations which incorporate protein and glycan motion, we have elucidated important clues as to how heparan sulfate and other glycocalyx components may bind the spike glycoprotein during SARS-CoV-2 host-cell infection. GlycoGrip is a promising and generalizable alternative to costly, labor-intensive RT-PCR, and we envision it will be broadly useful, including for rural or low-income populations that are historically undertested and under-reported in infection statistics.

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The multi-target colorimetric aptasensors can be easily fabricated by using two different aptamer sequences. However, there have been no research reports about improvement or enhancing of colorimetric signals based on the aggregation properties of AuNPs. Herein, we report a simple and efficient method to control and enhance the function of the multi-target aptasensor using an aptamer-aptamer linkage method. The aptasensor was developed for highly sensitive multiple-target detection of small molecules. The extension of aptamer DNA sequences using this method resulted in the enhanced analytical sensitivity of this aptasensor in sensing applications for two small molecule targets. Furthermore, the mechanism of the interaction between DNA aptamer and AuNPs was studied by measuring the zeta potential to explain the enhancement of the sensitivity of this multi-target aptasensor. The limit of detection of this multi-target aptasensor was found to be 1 nM and 37 nM for kanamycin (KAN) and chlortetracycline (CHLOR), respectively. It is 25-fold lower than in the previous report using an AuNP-based sensor for defining the limit of detection (LOD) of KAN and five times lower than the LOD for CHLOR. This aptasensor has great potential in the simultaneous detection of a wide range of KAN and CHLOR concentrations.