Science and Technology Center for Quantitative Cell Biology

点击翻译按钮获取中文摘要

The Science and Technology Center for Quantitative Cell Biology (QCB) aims to revolutionize our understanding of cells via the creation of whole-cell models that faithfully capture all aspects of cell function and emergent behavior. QCB will leverage the newest advances in computing, artificial intelligence, and super-resolution imaging, as well as the state of the art -omics and cellular measurements, to develop models with novel details and predictive capabilities. Ultimately, QCB aspires to unlock the secrets of living cells, to predict normal and abnormal cellular functions, and to design single cells and multicellular systems that provide solutions for human health, climate change and agriculture, fueling the U.S. bioeconomy. QCB’s education, broadening participation, and knowledge sharing programs will ensure that a diverse workforce is well-trained in quantitative cell biology. The goal of this center is to bring together a community of experimentalists who will study key “modules” of the cell with a community of computational scientists who will build a unified model of the cell, comprising all fundamental processes, including gene expression, metabolism, and division, for both eukaryotic and bacterial cells under the influence of their environment. Unified models have the potential to make predictions of the time-dependent behavior for every modeled biochemical species – a quantity of data akin to performing hundreds of simultaneous experiments. The time is ripe for attempting a synthesis of the comprehensive knowledge we have from molecular biology, chemistry, and physics into a complete model of the cell. On the technology side, the University of Illinois at Urbana-Champaign has a strong history of tracking single molecules, and is a collaborative adopter of a facility that uses minimal photon fluxes (MINFLUX) microscopy to locate biomolecules to 2 nanometer spatial resolution and track them with 100 microsecond time resolution within the context of a living cell. MINFLUX represents a 10-fold improvement over all other existing single-molecule techniques, making the dynamical connection with structural electron microscopy and IR metabolomics techniques. On the cell biology side, examples of “modules” of the cell are molecular motors as they transport cargo across the cell, formation of spliceosomes through assembly of RNA-protein transcriptional complexes within the nucleus, chromosome dynamics and interactions with nuclear condensates during gene expression, changes in organelle networks as they transition from healthy and to unhealthy states, and interactions of eukaryotic and bacterial cells and their organelle networks. These cellular dynamical processes studied by MINFLUX will be complemented by cryogenic electron microscopy (CEM) measurements of large functional intermediates/complexes, and molecular dynamics and coarse-grained simulations to determine essential mechanistic states. Dynamical infrared microscopy will focus on the often-neglected small metabolites inside cells. Regions of the entire cell captured by cryogenic electron tomography (CET) will serve as the basis for the ultrastructure in cell simulations, with resolutions ranging from 8-32 nanometers in space and 50-100 microsecond time steps. Cell simulations of the reaction-diffusion processes will integrate metabolic kinetics with the dynamics of genetic information processes obtained from MINFLUX measurements to create a unified model of cellular function, from the molecular level up to cell division.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.