Elucidating the effect of spatial localization on metabolic systems

Spatial biology, both natural and engineered, is a rapidly developing area, propelled by the advent of new tools and technologies. At the intracellular level, this has recently involved the use of advanced techniques in spatial imaging, measurement and data processing, in systems biology and the creation of different types of artificial compartments in synthetic biology. However, there are still major gaps in our understanding of the effect of spatial organization on intracellular biomolecular networks. In this study, we focus on metabolic systems and combine bottom-up studies of basic building blocks and top-down studies of concrete exemplar cases to understand the effect of spatial localization/compartmentalization of species. We develop a systems framework with multiple strands. (i) Assessing the effect of localization of enzymes and substrates on a variety of metabolic motifs, revealing both structural invariants (shown analytically) and multiple unintuitive effects, specifically traced to localization (by analytically ruling out their presence in well-mixed systems). (ii) Assessing and revealing the hidden impact of spatial localization on standard metabolic control coefficients, while also introducing and analysing spatial control coefficients. (iii) Analysing how localization can be used in engineering metabolic networks, uncovering various kinds of trade-offs in the process. (iv) Examining the effect of localization in concrete exemplar cases. In so doing, we develop contrasts with analysis of systems which treat them as well mixed. Our analysis combining top-down approaches and bottom-up approaches from multiple perspectives transparently reveals a number of basic as well as subtle ways in which compartmentalization and spatial localization can impact metabolic networks. The results and the methods of analysis have important implications for systems and synthetic biology in a variety of settings.