Lipidic Cubic Phases as a Versatile Platform for the Rapid Detection of Biomarkers, Viruses, Bacteria, and Parasites

Rapid and affordable detection of analytes is critical in diagnostic technologies, but current methods are typically expensive and unsuitable for field detection. Lipidic cubic phases are optically isotropic, transparent lyotropic liquid crystals (LC), containing highly confined water nanochannels in‐between percolating lipid bilayers following defined space groups. Due to this nanoconfinement, the water in these systems provides a unique environment for chemical and enzymatic reactions. Here, it is shown that during the in meso peroxidase enzymatic reaction, the converted product crystallizes within the mesophase domains, generating a detectable birefringence signal and a new general assay principle is presented for the detection of an unprecedented vast class of analytes using such birefringence as sole optical output signal. By exploiting bienzymatic cascade reactions or introducing an enzyme‐linked immunosorbent assay based on birefringence (Birefringent‐ELISA), this approach is used for real‐time detection of exemplary analytes, such as glucose and cholesterol, model pathogenic microorganisms, Escherichia coli, and viruses such as Ebola and HIV. It is also shown how the same technology enables the rapid, naked‐eye screening of malaria infection via in meso detection of hemozoin crystallites. This new technology is general and readily adaptable to the rapid detection of virtually any type of analyte, such as disease biomarkers, viruses, bacteria, and parasites. Lipidic cubic mesophases are proposed as a general tool to detect analytes of biomedical and epidemic significance by exploiting in meso enzymatic reactions. Due to nanoconfinement effects, the converted substrates crystallize, generating a detectable birefringence. By exploiting this optical signal, it is shown that enzymatic assays can be designed for simple, real‐time detection of analytes comprising biomarkers, bacteria, viruses, and parasites, illuminating new pathways toward scalable detection technologies.