In this proposed project, we plan to fill the knowledge gap of the relationships between microscopic self-assembled structures, collagen-molecule interactions and macroscopic fiber morphologies of type-I collagen, the primary component of most human tissues and a commonly used biomaterial for tissue engineering. By investigating collagen-water and collagen-protein interactions in in vitro systems that mimic basic aspects of physiologically relevant three- dimensional fibrillar tissue architectures, we aim to fill knowledge gaps in fundamental collagen research. We will achieve this goal by developing a hyperspectral imaging technique ? vibrational sum frequency generation (VSFG) microscopy ? at high repetition rates (400 kHz) and apply it to collagen. The long-term vision is to develop new biophysics methods to reveal molecular-level structures and interactions for pericellular space research and other complex biological environments, and eventually applying it to study various pericellular environment related diseases. In order to correlate spectral features to microscopic and macroscopic structures of type I collagen, we plan to apply machine-learning techniques to analyze our data and extract spectral signatures of collagen?s micro/macrostructures. We will two major scientific focuses: (A) understanding molecular signatures of microscopic self-assembly fibrils structures and its relationship to the macroscopic morphology (plan 1 and 2); and (B) investigating molecular level collagen-molecule interactions (plan 3 and 4). Specific plans include: 1. Obtaining hyperspectral VSFG images of collagen tissues to study their morphology in a label free and non-invasive manner 2. Establishing molecular spectral signatures of self-assembled collagen fibril structures 3. Understanding collagen-water interaction in first solvation layer of collagen fibers. 4. Imaging spatial locations of chemicals and peptides that interact with collagens. If successful, the significance is that a label free, vibrational mode specific imaging technique specific for pericellular space will be available, which can reveal molecular level insights of collagen structures and its interactions with surrounding molecules, pertinent to fibrosis and cell? pericellular space interaction related diseases. This proposed project contributes to the scope of NIGMS by developing new technology to reveal fundamental molecular-level principle, mechanism and signatures related to morphology of collagen I at both micro- and macroscopic scales, and collagen-molecule interactions, laying foundations for biophysical/biochemical principles for future biomedical applications related to collagens.
This proposed development of vibrational sum frequency generation microscopy, in the short term, will spatially resolve collagen tissues with chemical structure and molecular interaction information in a complicated environment. Machine learning and simulation approaches will be employed to build a data base to convert hyperspectral images of collagen into a spatial map with microscopic structures and molecular interaction information. In the long term, the fundamental biochemical knowledge learned from this development will lay foundations for rationally design biomedical approaches to monitor and control pericellular spaces and its interaction with cells, and further advance treatment to diseases related to it.
