Probing and controlling chirality across scales using nanophotonic platforms

ABSTRACT Chirality, the property of being non-superimposable on its mirror image, plays a pivotal role in biological systems. Homochirality, the exclusive use of one chiral form, shapes the structure and function of vital biomolecules like proteins and DNA. This uniform chirality raises profound questions about life’s nature and origins. However, current research faces challenges in bridging molecular and cellular understanding. Existing methods, while high in resolution, often lack the capacity to provide a comprehensive view at larger cellular scales. Conversely, tools designed for cellular-to-tissue analysis typically overlook finer molecular details. This gap hinders our full understanding and manipulation of chirality in complex biological contexts, highlighting the need for versatile tools capable of comprehensively exploring chirality across these varying scales. Central to this effort is the development of cutting-edge nanophotonic technologies tailored for probing and manipulating chirality. These advancements will enable high-resolution, label-free analysis of molecular and cellular chirality, potentially revolutionizing our comprehension of chirality in biological systems and impacting drug development and disease treatment. This research aims to provide groundbreaking insights into the interplay between molecular and cellular chirality, specifically how they affect cellular functions and disease mechanisms. It will tackle key questions about the fundamental connections between cellular and molecular chirality, define and measure molecular chirality at extremely low concentrations, and explore how altering cellular chirality could impact molecular- level mechanisms and cellular functions. The anticipated outcomes include the creation of novel diagnostic tools, safer chiral drugs, and non-invasive treatment methods, significantly advancing chirality research and bridging the divide between molecular intricacies and cellular complexity.