Label-free surface-enhanced Raman spectroscopy (SERS) can interrogate systems by directly fingerprinting their components' unique physicochemical properties. In complex biological systems however, this can yield highly overlapping spectra that hinder sample identification. Here, we present an artificial-nose inspired SERS fingerprinting approach where spectral data is obtained as a function of sensor surface chemical functionality. Supported by molecular dynamics modeling, we show that mildly selective self-assembled monolayers can influence the strength and configuration in which analytes interact with plasmonic surfaces, diversifying the resulting SERS fingerprints. Since each sensor generates a modulated signature, the implicit value of increasing the dimensionality of datasets is shown using cell lysates for all possible combinations of up to 9 fingerprints. Reliable improvements in mean discriminatory accuracy towards 100% are achieved with each additional surface functionality. This arrayed label-free platform illustrates the wide-ranging potential of high-dimensionality artificial-nose based sensing systems for more reliable assessment of complex biological matrices.

CRISPR-based diagnostics enable specific sensing of DNA and RNA biomarkers associated with human diseases. This is achieved through the binding of guide RNAs to a complementary sequence which activates Cas enzymes to cleave reporter molecules. Currently, most CRISPRbased diagnostics rely on target preamplification to reach sufficient sensitivity for clinical applications. This limits quantification capability and adds complexity to the reaction chemistry. Here, we show the combination of a CRISPR/Cas-based reaction with a Nanozyme-Linked ImmunoSorbent Assay which allows for the quantitative and colorimetric readout of Cas13mediated RNA detection through catalytic metallic nanoparticles at room temperature (CrisprZyme). We demonstrate CrisprZyme is easily adaptable to a lateral-flow-based readout and different Cas enzymes, and enables the sensing of non-coding RNAs including microRNAs, long non-coding RNAs and circular RNAs. We utilise this platform to identify patients with acute myocardial infarction and to monitor cellular differentiation in vitro and in tissue biopsies from prostate cancer patients. We anticipate that CrisprZyme has significant potential as a universally applicable signal catalyst for CRISPR-based diagnostics which will expand the spectrum of targets for preamplification-free, quantitative detection.

Semiconducting polymer nanoparticles (SPNs) are explored for applications in cancer theranostics because of their high absorption coefficients, photostability, and biocompatibility. However, SPNs are susceptible to aggregation and protein fouling in physiological conditions, which can be detrimental for in vivo applications. Here, a method for achieving colloidally stable and low‐fouling SPNs is described by grafting poly(ethylene glycol) (PEG) onto the backbone of the fluorescent semiconducting polymer, poly(9,9′‐dioctylfluorene‐5‐fluoro‐2,1,3‐benzothiadiazole), in a simple one‐step substitution reaction, postpolymerization. Further, by utilizing azide‐functionalized PEG, anti‐human epidermal growth factor receptor 2 (HER2) antibodies, antibody fragments, or affibodies are site‐specifically “clicked” onto the SPN surface, which allows the functionalized SPNs to specifically target HER2‐positive cancer cells. In vivo, the PEGylated SPNs are found to have excellent circulation efficiencies in zebrafish embryos for up to seven days postinjection. SPNs functionalized with affibodies are then shown to be able to target HER2 expressing cancer cells in a zebrafish xenograft model. The covalent PEGylated SPN system described herein shows great potential for cancer theranostics.