Understanding Metabolism in Space and Time – Mechanistic Analysis of the Dynamic Spatial Organization of Metabolism

All living organisms are dynamic metabolic entities that balance between synthesis and breakdown of complex
biomolecules to support activities of life. While work from genetics, biochemistry, and recent omics analyses
allow us to build comprehensive 2-dimensional (2D) metabolic maps associated with normal and diseased
conditions, the results are limited due to insufficient information from the dimensions of subcellular organization
and dynamics where metabolic activities physically occur. Thus, we are still largely in dark about bridging
scales from 2D maps to 3D subcellular terrain over time, hindering a holistic understanding of metabolism. One
major issue is that much about this subcellular terrain throughout an entire cell at meaningful resolution remain
elusive. To overcome this barrier, I will apply newly developed whole-cell focus ion beam-scanning electron
microscopy (FIB-SEM) and deep learning-based automatic segmentation pipeline to systematically examine
and reconstruct subcellular organization at isotropic resolution during metabolic reprogramming, such as cell
differentiation and tumorigenesis. This approach will allow us to further develop algorithm to mathematically
define architectural features associated with specific metabolic conditions and diseases, which will generate
new hypotheses of how changes in subcellular organization can impact metabolic outcomes and provide
conceptual advances in disease diagnosis or prognosis. I will further bridge scales of liner metabolic pathways
to 3D terrain to dissect the structural-functional crosstalk by correlative super-resolution microcopy. An
evolutionarily conserved structural platform connecting metabolic pathways is contact sites, where organelles
are tethered to form nanoscale adjoining architecture within ~20 nm to direct trafficking for biomolecules.
Regulating these organelle interfaces can accelerate or limit inter-organelle material flow and thus, directly
impact metabolic outcomes. To quantitatively interrogate these dynamic nano-architecture, I will engineer a
generalizable tool platform based on reversible split fluorescent protein (FP) complementation for visualizing
contact sites using imaging technologies with a wide range of spatial and temporal resolutions. Using
orthogonal reversible split FPs, this platform will be readily applied to monitor multiple contact sites
simultaneously in different metabolic conditions. In conjunction with light-inducible protein dimerization motifs,
this platform will be modified to quantitatively manipulate the size and duration of contact sites, allowing us to
address how changes in inter-organelle logistics impact metabolic outcome. I will further combine these tools
with CRIPSR knockout screening to identify functional and structural components of organelle interfaces,
which will be mechanistically defined via an interdisciplinary approach. Build on a wealth of prior data and
newly developed technologies, I expect this proposal to significantly transform our understanding in the
dynamic spatial organization accommodating metabolism as well as generate new research directions in
advancing architecture-to-function crosstalk in various areas of cell biology.

Grant Number: 4DP2GM150192-02
NIH Institute/Center: NIH
Principal Investigator: Chi-Lun Chang