Professor Mark Fricker
IAS Fellow at the College of St Hild and St Bede, Durham University (January - March 2017)
Mark Fricker started as a plant physiologist with Colin Willmer at Stirling, following a degree in Botany at Oxford, with his research focused on dissecting signal transduction pathways in stomatal physiology. This led to the development of quantitative imaging of Ca2+, pH and redox dynamics in plant and then fungal systems in Edinburgh with Tony Trewavas and Nick Read. This naturally evolved into the current interest in signalling and transport in networked systems that he has pursued since his appointment in Oxford in 1989. His experimental investigations cover a range of scales including confocal ratio imaging on a micron scale, radiolabel scintillation imaging at an intermediate scale, and network analysis and mathematical modelling to predict behaviour at a macro-scale, with over 100 publications and book chapters.
Professor Fricker pioneered network analysis of fungal systems and demonstrated using graph-theoretic analysis of experimental networks, that indeterminate, de-centralized systems can yield adaptive networks with both high transport capacity and robustness to damage, but at a relatively low cost, through a 'Darwinian' process of selective reinforcement of key transport pathways and recycling of redundant routes (Bebber et al., 2007, Proc Roy Soc, 274, 2307). The work on fungal networks also led to collaboration with Toshiyuki Nakagaki in Hokkaido to understand network formation in the slime mold Physarum polycephalum. They reported in Science (Tero et al., 2010, Science, 327, 439) that slime molds can form networks with comparable efficiency, fault tolerance, and cost to those of real-world infrastructure networks such as the Tokyo rail system, which earned an IgNobel prize in 2010. In particular, they showed that the core mechanisms needed for adaptive network formation can be captured in a biologically inspired mathematical.
Currently network extraction is a laborious manual exercise so Professor Fricker has been working with Boguslaw Obara (Durham University, department of Computing Sciences) to develop high-throughput, automated network analysis techniques. During his IAS Fellowship, the plan is to optimise this approach for a range of biological networks at different organisational scales, including sub-cellular networks of cytoskeleton and ER, planar macroscopic networks, such as fungi, slime molds, and leaf veins, and then 3-D blood vascular networks. These networks also provide the input to predictive fluid flow models to probe the mechanisms leading to the emergence of adaptive behaviour. The working hypothesis is that bio-physical hydraulic coupling may act as the central mechanism enabling coordinated growth across the complete range of scales in networked organisms.
IAS Fellow's Public Lecture - The Third Mode of Life: information transfer in networked organisms
Fungi form extensive interconnected mycelial networks that scavenge efficiently for scarce and ephemeral resources in a patchy environment, in the face of aggressive competition from other fungi and predation by soil micro-fauna. Exploration, repair and combat require internal transport of nutrients from spatially disparate sources to these rapidly altering sinks. Thus, the network architecture and internal flows continuously adapt to local nutritional cues, damage or predation, through growth, branching, fusion or regression. As these organisms do not have any centralized control system, we infer their relatively sophisticated behavior has to emerge from parallel implementation of many local decisions that collectively manage to solve this complex, dynamic combinatorial optimization problem. To understand how such behavior is achieved and coordinated, we have developed combined imaging and modelling approaches to characterize the network structure, link the structure to predicted nutrient transport, based on models of fluid flow dynamics, and then test these predictions using experimental measurement of nutrient flows using photon-counting scintillation imaging. We have also explored control of network development in the acellular slime mold, Physarum polycephalum, which is taxonomically completely unrelated to the network forming fungi, being essentially a single giant animal cell, yet appears to exemplify common solutions to self-organised adaptive network formation driven by fluid flows, local rules and oscillatory behavior. In contrast to single celled organisms and other multicellular organisms, we propose that networked organisms constitute a ‘Third Mode of Life’ in which complex behaviour emerges as a result of intrinsically coupled, adaptive networks with a distributed processing architecture.
The IAS operated extremely well with excellent support, good facilities, an ideal central location, and a rich programme of events. I would certainly recommend others to apply to the programme.Professor Mark Fricker, University of Oxford