Invitation to Contribute a Talk to Modelling Biological Evolution 2013: Recent Progress, Current Challenges and Future Directions

The International Conference Modelling Biological Evolution 2013: Recent Progress, Current Challenges and Future Directions will be held at the University of Leicester on May 1-3, 2013. The topics sound very interesting, and are:

  • Evolutionary Epidemiology of Infectious Disease
  • Models of Somatic Evolution of Cancer
  • Evolutionary Population Ecology
  • Models in Behavioural Ecology and Sociobiology
  • Solving Social Dilemmas
  • Models of Evolution of Language
  • Population and Quantitative Genetics

I have been invited to contribute a talk and will give a talk with the following title and abstract:

Title:

Adaptation for protein synthesis efficiency in natural and artificial gene regulatory networks

Authors:

Dorota Herman, Dafyd Jenkins, Chris Thomas and Dov Stekel

Abstract:

In this talk, we will summarize work on the use of mathematical and computer models to explore the evolution and adaptation of gene regulatory network architectures.

First, we will look at a natural system, the korAB operon in RK2 plasmids, which is a beautiful natural example of a negatively and cooperatively self-regulating operon. We use a biologically grounded mechanistic multi-scale stochastic model to compare four hypotheses for the action of the regulatory mechanism: increased robustness to extrinsic factors, decreased protein fluctuations, faster response-time of the operon and reduced host burden through improved efficiency of protein production. We find that the strongest impact of all elements of the regulatory architecture is on improving the efficiency of protein synthesis by reduction in the number of mRNA molecules needed to be produced, leading to a greater than ten-fold reduction in host energy required to express these plasmid proteins.

Next, we summarize results from two different artificial gene regulatory network models that are free to evolve: a fine-grained model that allows detailed molecular interactions, and a coarse-grained model that allows rapid evolution of many generations. A similar theme emerges in these models too: the control of cell energy and resources is a major driver of gene network topology and function. This is demonstrated in the fine-grained model with the emergence of biologically realistic mRNA and protein turnover rates that optimize energy usage and cell division time, and the evolution of basic repressor activities, and in the coarse-grained model by emergence of global regulators keeping all cellular systems under negative control.o

 

So far as I am aware, the conference organizers have extended their registration deadline, so places are still available for the next few days.

Advertisements

New Publication: Adaptation for Protein Synthesis Efficiency in a Naturally Occurring Self-Regulating Operon

Dorota’s second paper has just been published in PLoS ONE as:

Herman, D., Thomas, C.M. and Stekel, D.J. 2012. Adaptation for Protein Synthesis Efficiency in a Naturally Occurring Self-Regulating Operon. PLoS ONE 7(11): e49678.

We are particularly pleased with this work, and had some very nice comments from the reviewers. The quotes (from two different reviewers) here are reproduced with permission from PLoS ONE:

“the kinds of questions the authors address appear to be the most rewarding uses of computational/mathematical uses in biology”

“I found this paper important because it investigates a system with biological plausible parameters, thus, revealing whether the results of previous purely theoretical studies are biologically plausible.”

We are hoping for that sort of reception more generally in the community!

The abstract of the paper is:

The korAB operon in RK2 plasmids is a beautiful natural example of a negatively and cooperatively self-regulating operon. It has been particularly well characterized both experimentally and with mathematical models. We have carried out a detailed investigation of the role of the regulatory mechanism using a biologically grounded mechanistic multi-scale stochastic model that includes plasmid gene regulation and replication in the context of host growth and cell division. We use the model to compare four hypotheses for the action of the regulatory mechanism: increased robustness to extrinsic factors, decreased protein fluctuations, faster response-time of the operon and reduced host burden through improved efficiency of protein production. We find that the strongest impact of all elements of the regulatory architecture is on improving the efficiency of protein synthesis by reduction in the number of mRNA molecules needed to be produced, leading to a greater than ten-fold reduction in host energy required to express these plasmid proteins. A smaller but still significant role is seen for speeding response times, but this is not materially improved by the cooperativity. The self-regulating mechanisms have the least impact on protein fluctuations and robustness. While reduction of host burden is evident in a plasmid context, negative self-regulation is a widely seen motif for chromosomal genes. We propose that an important evolutionary driver for negatively self-regulated genes is to improve the efficiency of protein synthesis.

Speaking at Workshop: Recent Advances in Statistical Inference for Mathematical Biology

Today I will be presenting at at the Mathematical Biosciences Institute at Ohio State University which this week is hosting the workshop Recent Advances in Statistical Inference for Mathematical Biology. I will be giving a talk about Hiroki’s work (abstract here and below), while Dorota will be presenting a poster about her work.

I am very excited about this workshop as it is the first to my knowledge to bring together mathematical modelling with statistical inference. In my view, this marriage is crucial to the future development of mathematical biology as a field.

Title:

Inferring the gap between mechanism and phenotype in dynamical models of gene regulation

Abstract:

Dynamical (differential equation) models in molecular biology are often cast in terms of biological mechanisms such as transcription, translation and protein-protein and protein-DNA interactions. However, most molecular biological measurements are at the phenotypic level, such as levels of gene or protein expression in wild type and chemically or genetically perturbed systems. Mechanistic parameters are often difficult or impossible to measure. We have been combining dynamical models with statistical inference as a means to integrate phenotypic data with mechanistic hypotheses. In doing so we are able to identify key parameters that determine system behaviour, and parameters with insufficient evidence to estimate, and thus make informed predictions for further experimental work. We are also able to use inferred parameters to build stochastic and multi-scale models to investigate behaviour at single-cell level. We apply these ideas to two systems in microbiology: global gene regulation in the antibiotic-resistance bearing RK2 plasmids, and zinc uptake and efflux regulation in Escherichia coli.

 

EPSRC Research Development Fund – Monte Carlo estimation of parameters for large data biological data sets using graphical processing units.

Together with Theodore Kypraios we have been awarded £8699 from the EPSRC Research Development Fund for the project:

Monte Carlo estimation of parameters for large data biological data sets using graphical processing units.

This award will start with immediate effect and will support Dorota Herman for a period of three  months to carry out this work. Thanks also to Matthias Gerstgrasser who was involved in initiating this project and who will work together with Dorota in this area.

We look forward to welcoming Dorota back to Nottingham for a short period!

 

 

Poster at ICSB 2011

This week Dorota has been presenting a poster at the 12th International Conference on Systems Biology in Heidelberg/Mannheim.

Cooperative regulation speeds up initiation of plasmid RK2 conjugative transfer

Dorota Herman1, Christopher M Thomas2 and Dov J Stekel3

1Center for Systems Biology, School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK

2School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK

3Integrative Systems Biology, School of Biosciences, University of Nottingham, LE12 5RD, UK

 

Plasmid RK2 belongs to the group of broad host range plasmids and encodes for multi-antibiotic resistance. They can transfer themselves horizontally by conjugative transfer. A switch between expression of proteins involved either in replication or conjugation is regulated by two global regulators, KorA and KorB, which are encoded in the central control operon. This operon is autoregulated negatively and cooperatively by dimers of KorA and KorB. We seek to explore a hypothesis that could explain the evolution of cooperative autoregulation of the central control operon: a speed-up of conjugative transfer after plasmid transjection to a new host.

We have built a multi-scale model of the RK2 central control operon and its regulation of the switch between expression of proteins involved either in replication (TrfA) or conjugative transfer (Trb proteins). The model also includes plasmid replication, host cell growth and cell division. The comparison analyses were conducted between models with cooperative and non-cooperative KorA and KorB regulation of the central control operon and the switch. The analyses concerned the dynamics of protein expression of both the regulators and the conjugative transfer proteins after plasmid transjection to a new host.  For the regulatory proteins KorA and KorB, the cooperative model shows a slightly faster rise time than the model without cooperativity. However, considering the time of first expression of the conjugative transfer proteins, the cooperative model is considerably faster than the model without cooperative regulation.

In conclusion, the cooperative regulation between KorA and KorB on the central control operon could have evolved as a mechanism to speed up the preparation for conjugative plasmid transfer. We also show that a small speed-up of regulatory protein expression can result in a faster speed-up of the expression of the regulated proteins.

 

New Publication: Global transcription regulation of RK2 plasmids: a case study in the combined use of dynamical mathematical models and statistical inference for integration of experimental data and hypothesis exploration.

Today we have published a new article in BMC Systems Biology:

Herman, D., Thomas, C.M. and Stekel, D.J. 2011. Global transcription regulation of RK2 plasmids: a case study in the combined use of dynamical mathematical models and statistical inference for integration of experimental data and hypothesis exploration. BMC Systems Biology 2011, 5:119.

This is Dorota’s first published research article so big congratulations to due to her: a very well-deserved achievement! The paper abstract is:

Background

IncP-1 plasmids are broad host range plasmids that have been found in clinical and environmental bacteria. They often carry genes for antibiotic resistance or catabolic pathways. The archetypal IncP-1 plasmid RK2 is a well-characterized biological system, with a fully sequenced and annotated genome and wide range of experimental measurements. Its central control operon, encoding two global regulators KorA and KorB, is a natural example of a negatively self-regulated operon. To increase our understanding of the regulation of this operon, we have constructed a dynamical mathematical model using Ordinary Differential Equations, and employed a Bayesian inference scheme, Markov Chain Monte Carlo (MCMC) using the Metropolis-Hastings algorithm, as a way of integrating experimental measurements and a priori knowledge. We also compared MCMC and Metabolic Control Analysis (MCA) as approaches for determining the sensitivity of model parameters.

Results

We identified two distinct sets of parameter values, with different biological interpretations, that fit and explain the experimental data. This allowed us to highlight the proportion of repressor protein as dimers as a key experimental measurement defining the dynamics of the system. Analysis of joint posterior distributions led to the identification of correlations between parameters for protein synthesis and partial repression by KorA or KorB dimers, indicating the necessary use of joint posteriors for correct parameter estimation. Using MCA, we demonstrated that the system is highly sensitive to the growth rate but insensitive to repressor monomerization rates in their selected value regions; the latter outcome was also confirmed by MCMC. Finally, by examining a series of model refinements for partial repression by KorA or KorB dimers alone, we showed that a model including partial repression by KorA and KorB was most compatible with existing experimental data.

Conclusions

We have demonstrated that the combination of dynamical mathematical models with Bayesian inference is valuable in integrating diverse experimental data and identifying key determinants and parameters for the IncP-1 central control operon. Moreover, we have shown that Bayesian inference and MCA are complementary methods for identification of sensitive parameters. We propose that this demonstrates generic value in applying this combination of approaches to systems biology dynamical modelling.

Poster at the Third Biennial Workshop on Statistical Bioinformatics and Stochastic Systems Biology

Dorota Herman is attending the Third Biennial Workshop on Statistical Bioinformatics and Stochastic Systems Biology at the University of Newcastle today and tomorrow where she is presenting a poster:

Bayesian inference and evolutionary optimization of negative and cooperative autoregulation of plasmid RK2

Dorota Herman1, Christopher M Thomas2 and Dov J Stekel3

1Center for Systems Biology, School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK

2School of Biosciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, UK

3Integrative Systems Biology, School of Biosciences, University of Nottingham, LE12 5RD, UK

Poster Abstract

The central control operon of plasmid RK2 is an example of a natural system of negative and co-operatively autoregulation. The available data of the operon regulation by dimers of two global regulators, KorA and KorB, are insufficient for full reconstruction of the system. Therefore, we aim to explore possible dynamics of the system and to estimate unknown parameters. Additionally, we would like to contribute to the scientific discussion about the roles of negative loop in biosystems. We present possible reasons for optimization of the central control operon through comparative analyses of the wild type system with a progression of simpler systems.

Analyses of the RK2 central control operon regulation were carried out by considering the steady state of a deterministic model of the system during exponential host bacterial growth. Using the Metropolis-Hastings algorithm we have estimated protein synthesis rates and revealed insignificance of monomerization rates to the model. For evolutionary optimization analyses, we have built a stochastic multi-scale model, which includes operon regulation, plasmid replication and host cell growth and division. We have examined the architecture of the central control operon regulation and its simpler equivalents, in terms of noise, robustness, speed up in response time and burden for a host. Results have shown that possible evolutionary optimization of the central control operon might be speed up in response time and decrease in burden for a host, as indicated by a decrease in number of produced mRNA. Fluctuations and robustness do not seem to play a significant role in this case.

In summary, we have explored possible dynamics of the RK2 central control operon regulation using Bayesian framework and demonstrated possible reasons for evolution of the regulatory architecture of the naturally occuring negative and cooperative autoregulation.