Is it the Genome that Throws Dice Then? Statistical Thermodynamics for Individualized Medicine
Event details
| Date | 22.05.2018 |
| Hour | 16:15 |
| Speaker | Prof. Hans V. Westerhoff, University of Amsterdam and VU University in Amsterdam (NL), and University of Manchester (UK) |
| Location | |
| Category | Conferences - Seminars |
BIOENGINEERING SEMINAR
Abstract:
Understanding how biological functions emerge from all molecular interactions is the aim of systems biology. However, the complexity of 25,000 (or even 300,000) genes and their expression products is mind-boggling. Is this complexity prohibitive? Yes, and No! I will first show how considerations of biological function, as well as newly recognized non-equilibrium thermodynamics principles, plus a focus on pinpointing what really matters, enables some modes of understanding. This may be useful, for instance, by enabling differential network-based drug design.
Some models achieve quite accurate predictions. Paradoxically these predictions are sometimes even too accurate. Predicted properties turn out to be uncertain not just due to experimental limitations, but also because of heterogeneity in cell populations. We formulate this implication of heterogeneity as an uncertainty principle, which we compare with that of Heisenberg. Indeed, even clonal cells in a tissue appear to be heterogeneous in their phenotype. We will show how an epigenetic transcription-clock mechanism could lead to transcription bursting and to substantial noise in mRNA and perhaps protein levels. We shall revive a rule that relates the variance to the mean of molecule number and that requires a limited amount of molecular information: statistical thermodynamics enters. If dynamics is slow enough, the corresponding cell-cell heterogeneity may increase drug resistance of the cell population. This type of statistical mechanical noise and uncertainty may explain why drug resistance is so hard to prevent.
Einstein long opposed the fundamental nature of Heisenberg’s uncertainty principle, contending that one should just acquire more information about the elementary particles. Bohr rightly contended that it is impossible to acquire that information without completely perturbing the system. Medicine appears to be home to an uncertainty principles that is again similar to that of Heisenberg. I shall argue that this time Einstein would have been right: By putting in more of the patient’s molecular information one should be able to remove much of the uncertainty in diagnosis and therapy outcome. I shall exemplify for inborn errors of metabolism and the metabolic map.
We shall show how an integration of precise experimentation, molecular tinkering, mathematical modelling and analysis, may enable us to understand or even revert deregulated behaviour of biological systems.
We compare this uncertainty to that of Heisenberg’s predictions. Yet, predictions In a linear metabolic pathway of 10 enzymes there is only a single flux at steady state. We will show how essentially this complexity-reducing feature of metabolic networks, with genome-wide integration of genomic and biochemical data, plus a pinch of mathematics enables the understanding of inborn errors of metabolism. Accommodating the different instantiations that individuals have of these networks, we shall illustrate how human genome functioning is ‘noisy’. This noise/diversity in network behavior makes many human diseases elusive and multifactorial, and individualized medicine crucial.
Bio:
Hans V. Westerhoff is Professor of Systems Biology at the Universities of Manchester and Amsterdam and of Molecular Cell Physiology at the VU University in Amsterdam.
He is one of the founding Fathers of Systems Biology and one of the intellectual leaders of the field.
Prof. Westerhoff obtained his Ph.D. in 1983 from the University of Amsterdam for investigations of non-equilibrium thermodynamics and the control of biological thermodynamics under the supervision of Professor Karel van Dam.
Prof. Westerhoff studies how biological functions emerge in the complex interactions between the components of living systems.
His work has resulted in more than 400 publications and seminal contributions to the Systems Biology field, including the development of biophysical models for the thermodynamics and control of biological free-energy transduction, bioenergetics, metabolic control analysis, metabolic and signaling network modeling, and the discovery of synchronisation of glycolytic oscillations in yeast cells.
Westerhoff has received numerous awards, such as the 2018 Systems Biology Foundation Award. He is a foreign member of the Italian Academy of Sciences and Fellow of the International Society for Systems Biology.
Abstract:
Understanding how biological functions emerge from all molecular interactions is the aim of systems biology. However, the complexity of 25,000 (or even 300,000) genes and their expression products is mind-boggling. Is this complexity prohibitive? Yes, and No! I will first show how considerations of biological function, as well as newly recognized non-equilibrium thermodynamics principles, plus a focus on pinpointing what really matters, enables some modes of understanding. This may be useful, for instance, by enabling differential network-based drug design.
Some models achieve quite accurate predictions. Paradoxically these predictions are sometimes even too accurate. Predicted properties turn out to be uncertain not just due to experimental limitations, but also because of heterogeneity in cell populations. We formulate this implication of heterogeneity as an uncertainty principle, which we compare with that of Heisenberg. Indeed, even clonal cells in a tissue appear to be heterogeneous in their phenotype. We will show how an epigenetic transcription-clock mechanism could lead to transcription bursting and to substantial noise in mRNA and perhaps protein levels. We shall revive a rule that relates the variance to the mean of molecule number and that requires a limited amount of molecular information: statistical thermodynamics enters. If dynamics is slow enough, the corresponding cell-cell heterogeneity may increase drug resistance of the cell population. This type of statistical mechanical noise and uncertainty may explain why drug resistance is so hard to prevent.
Einstein long opposed the fundamental nature of Heisenberg’s uncertainty principle, contending that one should just acquire more information about the elementary particles. Bohr rightly contended that it is impossible to acquire that information without completely perturbing the system. Medicine appears to be home to an uncertainty principles that is again similar to that of Heisenberg. I shall argue that this time Einstein would have been right: By putting in more of the patient’s molecular information one should be able to remove much of the uncertainty in diagnosis and therapy outcome. I shall exemplify for inborn errors of metabolism and the metabolic map.
We shall show how an integration of precise experimentation, molecular tinkering, mathematical modelling and analysis, may enable us to understand or even revert deregulated behaviour of biological systems.
We compare this uncertainty to that of Heisenberg’s predictions. Yet, predictions In a linear metabolic pathway of 10 enzymes there is only a single flux at steady state. We will show how essentially this complexity-reducing feature of metabolic networks, with genome-wide integration of genomic and biochemical data, plus a pinch of mathematics enables the understanding of inborn errors of metabolism. Accommodating the different instantiations that individuals have of these networks, we shall illustrate how human genome functioning is ‘noisy’. This noise/diversity in network behavior makes many human diseases elusive and multifactorial, and individualized medicine crucial.
Bio:
Hans V. Westerhoff is Professor of Systems Biology at the Universities of Manchester and Amsterdam and of Molecular Cell Physiology at the VU University in Amsterdam.
He is one of the founding Fathers of Systems Biology and one of the intellectual leaders of the field.
Prof. Westerhoff obtained his Ph.D. in 1983 from the University of Amsterdam for investigations of non-equilibrium thermodynamics and the control of biological thermodynamics under the supervision of Professor Karel van Dam.
Prof. Westerhoff studies how biological functions emerge in the complex interactions between the components of living systems.
His work has resulted in more than 400 publications and seminal contributions to the Systems Biology field, including the development of biophysical models for the thermodynamics and control of biological free-energy transduction, bioenergetics, metabolic control analysis, metabolic and signaling network modeling, and the discovery of synchronisation of glycolytic oscillations in yeast cells.
Westerhoff has received numerous awards, such as the 2018 Systems Biology Foundation Award. He is a foreign member of the Italian Academy of Sciences and Fellow of the International Society for Systems Biology.
Practical information
- Informed public
- Free