- Project Title
- Finding the naturally evolved design principles of prevalent metabolic circuits
- Project Type
- Nacional / Public
- Funding Body
- Funding Program
- CEB: 14 774,00
- Total: 154 000,00
- Centro de Neurociências e Biologia Celular
Universidade de Coimbra
Universidade do Minho
- External link
Team Members - CEB
Research in molecular systems biology has revealed the following two key features of biochemical systems. First, biochemical
networks are mostly composed of a few prevalent elementary circuits (e.g. network motifs). Second, natural selection for robust performance strongly constrains the design of these circuits. As consequence we may expect, and are indeed finding, some principles (design principles) that associate design of biochemical circuits to their function to hold widely. The discovery and understanding of these principles will have important implications, for instance as follows. In circuit instances whose interaction structure is known, knowledge of the design principles helps clarifying function, functional consequences of perturbation and directions for reengineering. In circuit instances whose function is known, it helps identifying missing interactions and indicates
semi-quantitative relationships among kinetic parameters and state variables.
This project will address design principles of prevalent elementary metabolic circuits. (These circuits are defined as patterns of stoichiometric coupling between small sets of metabolic reactions.) Design principles for some circuits that were recognized early on were addressed before. However, a systematic survey remains do be done. In this context, our main goals are to: (a) identify the most frequent elementary circuits in metabolic networks, (b) identify the regulatory patterns (allosteric interactions) that are most frequently associated to the most prevalent circuits, and (c) elucidate the design principles of the three most prevalent hitherto uncharacterized circuits both at the level of regulatory “diagram” and at a semi-quantitative level. The latter
principles of quantitative design are constraints among enzyme kinetic parameters, metabolite concentrations and/or fluxes that must hold so that the circuits function effectively.
Substantial preliminary results [1-5,6 and unpublished] support the concepts underlying this proposal and demonstrate the
effectiveness of our approaches. We identified moiety-transfer cycles, whereby a moiety is transferred from a moiety-donor metabolite to an acceptor molecule by way of a cycled carrier, as a very prevalent metabolic circuit: ~70% of the reactions in the metabolic networks of several organisms participate in such cycles. Most of these cycles play a role analogous to that of power-supply units in electronics: they must reliably supply a moiety at the required rate while buffering the concentration of moiety-loaded carrier against fluctuations. We have derived a set of principles of quantitative design for idealized “moietysupply
units”. Detailed examination of concrete biological instances [1-4,6] and a broad data survey reveal that these principles
hold widely, across processes and phylogenetically distant organisms.
In order to accomplish goal (a) we will draw on available metabolic network reconstructions at the stoichiometry level. For goal (b) we will draw on a database assembled by the research team  that integrates metabolic regulation and enzyme kinetics information from multiple sources. We will seek recurrent patterns associating regulatory structure to stoichiometric-level circuits. For goal (c) we will use both standard and novel (as per next paragraph) systems-theory approaches. We will first try to understand the functional role of recurrent interactions and the possible functional underpinnings of observed variation in design
for the most representative patterns. Then, we will derive the principles of quantitative design for the most representative
regulatory circuits and modes of coupling thereof. Finally, we will validate the design principles both through detailed
computational analysis of well-characterized biological instances of each circuit and through broad surveys of kinetic
parameters, concentrations and fluxes. The “catalogue” of circuit designs thus produced will also describe the conditions leading to and functional consequences of performance breakdowns caused by mutations or stresses, as exemplified in [4,6].
The investigation of design principles requires good tools for outlining the regions of the parameters space that ensure effective operation. We have recently developed an approach for this purpose based on piecewise power-law approximations of the kinetics [4,5]. In this project we will also devise and implement numerical algorithms that will allow analyzing more-complex circuits and exploring circuit properties in a more automated way. These algorithms will draw on the emerging field of robust optimization and will be applicable to other kinds of biochemical networks as well.
We have assembled a multi-disciplinary consortium of three research groups that altogether cover the necessary skills to tackle the problems involved in timely accomplishing the proposed goals.