Chairs
Bastiaan Cockx, Technical University of Denmark, Denmark
Dr Leonardo Erijman, Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI-CONICET), Argentina
Bastiaan Cockx, Technical University of Denmark, Denmark
Fresh out of high school, Bastiaan Cockx enjoyed the bachelor and master program Life Science & Technology with the cell factory and biochemical engineering specialization tracks at Delft University of Technology, co-hosted by Leiden University. This is where he developed a passion for computational biology, which he pursued further with his PhD studies at the Technical University of Denmark at the department of Environmental Engineering. In his project Bastiaan focuses on the physical and chemical interactions that lead to spatial and species heterogeneity within microbial aggregates (mainly concentrating on aggregates found in nitrogen removal processes). By capturing key processes and interactions in individual-based models, his research aims to unravel how seemingly simply individual properties and interactions can lead to complex structures within these aggregates. In order to do this, he has teamed up with a small but dedicated group of scientists to develop the new individual-based modelling framework iDynoMiCS 2.
Dr Leonardo Erijman, Instituto de Investigaciones en Ingeniería Genética y Biología Molecular (INGEBI-CONICET), Argentina
Leonardo Erijman obtained a degree and a doctorate in Chemistry from the University of Buenos Aires. After postdoctoral training in biophysics at the Department of Biochemistry of the University of Illinois at Urbana-Champaign and the Max Planck Institute for Biophysical Chemistry, he reengineered his career into the environmental and water resources field. After working for a few years in the private sector, he was awarded a research position at the Argentine National Research Council (INGEBI-CONICET). Currently, he leads a team focused on the microbial ecology of environmental biotechnology processes. He is also Professor of Environmental Biotechnology at the University of Buenos Aires and continues to serve as consultant for various industries, municipalities and engineering consulting firms in the water sector.
09:00-09:15
Introduction for day 2
Professor Thomas Curtis, Newcastle University, UK
Dr Jane Fowler, Simon Fraser University, Canada
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Professor Thomas Curtis, Newcastle University, UK
Dr Jane Fowler, Simon Fraser University, Canada
Professor Thomas Curtis, Newcastle University, UK
Biography not yet available
Dr Jane Fowler, Simon Fraser University, Canada
Dr Fowler obtained their PhD at the University of Calgary, Canada in 2014 where they studied syntrophic hydrocarbon biodegradation under methanogenic conditions. Dr Fowler subsequently worked as a Postdoc and Researcher at the Technical University of Denmark Department of Environmental Engineering where they shifted their focus to biological water treatment (2015–2019). From 2020, Dr Fowler will be an Assistant Professor of Environmental Microbiology at Simon Fraser University, Canada. Dr Fowler's research is focused on developing sustainable biotechnologies using mixed microbial communities. Within this, they have worked on bioplastic and third generation biofuel synthesis, bioremediation of hydrocarbons, and presently, on biological wastewater and drinking water treatment technologies. Dr Fowler's research ultimately aims to develop a mechanistic understanding of microbial community structure and function that is guided by ecological theory, microbial physiology and modelling and apply this to engineered biological systems.
09:15-09:45
Individual-based modelling: what have I learnt?
Dr Jan Ulrich Kreft, University of Birmingham, UK
Abstract
For engineering systems, it is important to be able to predict the behaviour of systems before they are being engineered as prediction can avoid costly mistakes and enables optimization of systems. Mathematical models enable true predictions rather than interpolations or extrapolations from measurements of the same system, if they are mechanistic. (A similar case can be made for causal inference.) In the case of complex systems, mechanistic models have to be bottom-up models that describe the characteristics of the parts and how they interact with each other, to predict how system level behaviour emerges from these interactions. A quintessential type of bottom-up models are individual-based models, where the ‘parts’ are individual organisms, in the case of microbes often but not necessarily single cells. But how far down the scale of organization should one go when modelling individual organisms? Use Monod kinetics or incorporate gene regulatory and stoichiometric metabolic models or dynamic metabolic models? All the way to physical laws from thermodynamics and mechanics? Drawing on two case studies, the question of how to cope with the huge diversity of microbial ecotypes with their huge phenotypic flexibility, interacting with others in spatially structured and temporally fluctuating environments will be discussed with an emphasis on metabolism. The case studies are based on competing, abstract strategies rather than detailed implementations of particular manifestations of these strategies, and this choice has advantages and disadvantages. One is based on a trade-off between specific growth rate and growth yield, demonstrating the benefits of higher yields in biofilms. The second is based on a trade-off between allocating resources into repair of damaged materials or into growth and reproduction, while getting rid of damage by asymmetric damage segregation causing ageing.
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Dr Jan Ulrich Kreft, University of Birmingham, UK
Dr Jan Ulrich Kreft, University of Birmingham, UK
Dr Jan Kreft's research interests revolve around the interactions between microorganisms with each other, the environment and host organisms. He believes the individual organism is the central unit of ecology and evolution. For this reason, he pioneered the application of individual-based modelling to microbial ecology. His group applied this to study interactions such as competition, cooperation, communication, plasmid transfer and predation. Dr Kreft studied biology at the Universities of Konstanz and Tübingen in Germany, then did his PhD with Professor Bernhard Schink at Konstanz, looking at the biochemistry of anaerobic degradation of plant compounds in the then newly discovered, weird anaerobe later named Holophaga foetida. After this, he decided to go into mathematical modelling to be able to address fundamental questions. He obtained a DFG fellowship and went to Professor Julian Wimpenny at Cardiff University, where he developed individual-based modelling of microbes. He then joined the Theoretical Biology group at the University of Bonn in Germany as a “Wissenschaftlicher Assistent”, where he broadened his research topics and mathematical methods. He joined the University of Birmingham in 2007 as a Lecturer in Computational Biology (now Senior Lecturer). He also runs a wet lab to be better able to test and parameterize his mathematical models.
09:45-10:15
Integrating metabolic versatility into spatially-explicit models of soil bacterial life
Benedict Borer, ETH Zürich, Switzerland
Abstract
Soil is a harsh and dynamic environment for bacterial cells due to nutrient diffusion and dispersal limitations following episodic wetting events. Nevertheless, soil hosts unparalleled diversity of bacterial life where metabolic versatility is key to their success, enabling them to exploit diverse growth strategies on a wide range of resources. Soil bacterial life is governed by localized nutrient conditions at the microscale, giving rise to complex metabolic landscapes that shape bacterially-mediated processes ranging from soil nutrient cycling to greenhouse gas emissions. Interestingly, these nutrient landscapes can trigger fundamentally different growth strategies even for the same species when residing in close proximity. Most mathematical models are currently unable to capture such versatility and local adaptation, calling for a more nuanced representation of bacterial metabolism and the soil physical structure. Benedict Borer reports a mathematical framework that considers individual bacterial cell dispersal and interaction with nutrient diffusion fields in a spatial context that embrace metabolic versatility using flux balance analysis based on genome scale metabolic networks. Benedict investigates the spatial organisation of a synthetic bacterial community in artificial pore networks and reveal mechanisms promoting spatial segregation that enable coexistence. Representing the aqueous phase architecture of soil at the cell scale offers unprecedented opportunities to interrogate bacterial life in complex habitats that is typically veiled by soil opacity.
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Benedict Borer, ETH Zürich, Switzerland
Benedict Borer, ETH Zürich, Switzerland
Benedict is an Environmental Microbiologist at the ETH Zurich with a background in hydrology. His main interest is to gain a mechanistic understanding of how soil-physical and hydrological aspects shape microbial life at the scale relevant to individual cells including potential ramifications for community structure and function. During his PhD in the lab of Dani Or, he studied the spatial organisation of bacterial populations in soil using experimental and computational approaches. Currently, his research focusses on combining individual based modelling with genome scale metabolic networks to quantify microbial metabolism in the context of structured environments such as soil and sessile microbial assemblages.
10:45-11:15
Upscaling and statistical emulation of individual based models
Professor Darren Wilkinson, Newcastle University, UK
Abstract
Modelling entire ecological communities of bacteria in large, complex open environments is extremely challenging. The NUFEB project involves a multi-disciplinary team of researchers developing methods and software for multiscale modelling of open engineered biological systems at scale. The group's exemplar project is focused on the modelling of wastewater treatment systems which have macro-scale characteristics arising from the micro-scale features of up to 10^18 individual interacting bacteria. They have developed an individual based model of bacterial communities in an active fluid environment, and they can use this to understand the small-scale features of the system, considering volumes containing up to a few million bacteria. At the system scale the group are developing continuum models which capture essential macro-scale properties. They propose a novel technique for coupling the two models to produce a multi-scale model by embedding fast statistical emulators of the individual based model into the macro-scale model. This talk will outline the current state of this work in progress on this ongoing project.
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Professor Darren Wilkinson, Newcastle University, UK
Professor Darren Wilkinson, Newcastle University, UK
Darren Wilkinson is Professor of Stochastic Modelling within the School of Mathematics, Statistics and Physics at Newcastle University, and a Fellow of the Alan Turing Institute. His current research interests involve applications of Bayesian statistics to a variety of challenging big data problems in molecular biology and engineering. He is especially interested in parameter inference for dynamic models, on-line inference for high-velocity time series data, probabilistic programming, and the use of approximate models and emulators for rendering computationally prohibitive algorithms for expensive models more tractable. He is co-Director of Newcastle's EPSRC Centre for Doctoral Training in Cloud computing for Big Data, and leads a Turing research project on streaming data modelling.
11:30-12:00
Computational modelling of microbial communities
Professor Ines Thiele, National University of Ireland, Ireland
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Professor Ines Thiele, National University of Ireland, Ireland
Professor Ines Thiele, National University of Ireland, Ireland
Professor Ines Thiele is the principal investigator of the Molecular Systems Physiology group at the National University of Ireland, Galway. Her research aims to improve the understanding of how diet influences human health. Therefore, she uses a computational modelling approach, termed constraint-based modelling, which has gained increasing importance in systems biology. Her group builds comprehensive models of human cells and human-associated microbes; then employs them together with experimental data to investigate how nutrition and genetic predisposition can affect one's health. In particular, she is interested in applying her computational modelling approach for better understanding of inherited and neurodegenerative diseases. Ines Thiele has been pioneering models and methods allowing large-scale computational modelling of the human gut microbiome and its metabolic effect on human metabolism. Ines Thiele earned her PhD in bioinformatics from the University of California, San Diego, in 2009. From 2009 until 2013, Ines Thiele was an Assistant Professor at the University of Iceland. From April 2013 until January 2019, she was an Associate Professor at the University of Luxembourg. Since February 2019, Ines Thiele has been a Professor for Systems Biomedicine at the National University of Ireland, Galway. In 2013, Ines Thiele received the ATTRACT fellowship from the Fonds National de la Recherche (Luxembourg). In 2015, she was elected as EMBO Young Investigator. In 2017, she was awarded the prestigious ERC starting grant. She is an author of over 90 international scientific papers and reviewer for multiple journals and funding agencies.