Alan Perelson’s 70th Birthday Conference: Viral Dynamics: Past, Present and Future

Sankalp and I have just returned from a weekend trip to Santa Fe for the Viral Dynamics conference in honour of Alan Perelson’s 70th birthday.

The conference itself was very high quality – excellent talks throughout from some extremely eminent people in virus research. I particularly appreciated David Ho’s opening talk and Alan Perelson’s closing keynote; David’s talk on HIV dynamics reminding me just how good Alan and Avidan Neumann’s modelling contribution was: it wasn’t about developing big complex models, or doing very fancy mathematics; it was about doing the right simple model to make the most use of the data. Alan’s talk focussed on his earlier work in theoretical immunology – very many interesting examples showing how much you can learn by thinking in mathematical/computational ways.

The best part of the conference was meeting up with people – whether old friends from the short time I spent in LANL (Alan, Jack) and my PhD days (Ruy, Sebastian) – or brilliant people I hadn’t met before with whom I had some very stimulating conversations.

What was also evident was the warmth felt by so many people towards Alan. I only spent 3 months in the lab in 1994 – in between my degree and PhD – and went back for another month in the summer of 1995 – and yet when Ruy Ribeiro sent the invitation I immediately felt that this was a meeting I couldn’t miss. Many people there had collaborated with Alan for many years. And while Alan’s contribution to science is enormous, the plaque that the organizers made for him was for friendship, collaboration and mentorship, with a network graph of his collaborative research outputs. In this, Alan is a positive example for us all.

We went with a poster:


which was Sankalp’s first conference poster presentation! I thought that this would be a good opportunity for him; although Sankalp’s model is about bacteriophage in the context of AMR, while the conference focussed on human disease viruses, the conference attendees mainly worked in mathematical models of virus dynamics. This meant that Sankalp was among people who understood what he was doing and why he was doing it, speaking the same language. Sankalp was busy – he had people speaking with him for the full 2 hours of the poster session – and we received many interesting ideas and suggestions from these conversations.

Modelling Biological Evolution 2013: Conference Highlights

Over the last couple of days I have been attending the Modelling Biological Evolution conference at the University of Leicester organized by Andrew Morozov.

For me, the most interesting theme to have emerged is work on evolutionary branching: conditions under which polymorphisms (or even speciation) might arise. These were all talked about in the context of mathematical models (ODE-type formulations based on generalized Lotka-Volterra systems). The best talk I attended was by Andrew White (Heriot Watt University). He described various system of parasite-host co-evolution, the most interesting of which demonstrated increases in diversity: a new host could emerge that was resistant to current parasites, following which a new parasite could emerge that would infect that host. He rather nicely linked that work to experimental work from Mike Brockhurst (University of York) on phage infections of bacteria showing similar patterns. The results could of course be interpreted at a speciation level, or, probably more fairly, at the level of molecular diversification (e.g. of MHC types in an immune system). What I really appreciated about this resut is that it spoke to the idea that increased diversity can result through a positive feedback mechanism: diversification leads to new niches and thus the potential for further diversification. I have thought for some time that this is the most important mechanism that drives diversification / speciation in natural systems and it was nice to see an example of the mechanism in action.

The other talk I particularly appreciated on the subject was by Claus Rueffler (University of Vienna). He spoke about a result on complexity and diversity in Doebeli and Ispolatov 2010 that also contains this feedback idea. This paper relies on a specific model to obtain its result on conditions for evolutionary branching. Rueffler demonstrated general conditions under which branching might take place that depend only upon the properties of the Hessian matrix associated with key parameters in model space. The important point is that the analysis is model-independent: it only considers the properties of the model forms needed to obtain the result.

Similar ideas were presented by Eva Kisdi (University of Helsinki). She focussed on models that include evolutionary trade-offs (e.g. between virulence and transmissibility): her point was that instead of choosing a function and analyzing its consequences, one could consider desired properties of a model (e.g. branching or limit cycles) and then use “critical function analysis” to derive conditions for possible trade-off functions that would admit the desired behaviour. Eva made the important point that many models make ad hoc choices of functions and thus lead to ad hoc results of little predictive value.

I think Eva’s point really touched on some of the weaknesses that emerged in many of the talks that I attended: there was a great deal of theory (some of which was very good), but very little interface with real biological data. I find this somewhat surprising: modelling in ecology and evolution has been around for very much longer that modelling in say molecular biology (where I currently work), and yet seems to be less mature. I think that the field would really benefit from far greater interaction between theoretical and experimental researchers. Ideally, models should be looking to generate empirically falsifiable hypotheses.

Perhaps the most entertaining talks were given by Nadav Shnerb and David Kessler (both Bar Ilan University). Nadav’s first talk was about power-law-like distributions observed in genus/species distributions. Core to his work is Stephen Hubbell’s neutral theory of biodiversity.
Nadav showed that distributions of number of species within genera could be explained by a neutral model for radiation and the genus and species level coupled with extinction. Nadav’s most important point was that if you wish to make an argument that a certain observed trait is adaptive, then you have to rule out the null hypothesis that it could arise neutrally through mutation/drift. I hope that is something we addressed with regards global regulators in gene regulatory networks in Jenkins and Stekel 2010. David spoke about biodiversity distributions also, showing that adaptive forces could explain biodiversity data (they are generally poor at this due to competitive exclusion that occurs in many models) if the fitness trait is allowed a continuous rather than discrete distribution.

Nadav’s second talk was about first names of babies. This was very interesting – especially as I have a young family (and a daughter with a very old-fashioned name). He looked at the error distribution (easily shown to be binomial-like noise proportional to square root of mean) that is superimposed on a deterministic increase and decrease in popularity of a name over a 60 year period. His thesis was that the error distribution due to external events would be proportional to mean (not root mean), and, as only 5 names in his data set (Norwegian names in ~ 20th Century) did not fit binomial noise, he ruled out external events (e.g. celebrity) as being a major driver. The problem I have with this is that he didn’t rule out external events in the deterministic part of the data (e.g. initiating a rise in popularity of a name that then follows the deterministic feedback law he proposed).

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.


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


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.


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.

Invitation to speak at IUMS 2011 Congress

Today I received an invitation to give a presentation at the International Union of Microbiological Societies Congress 2011 which will take place in Sapporo on the island of Hokkaido, Japan. I will be speaking in part of the ‘Bioinformatics for Microbiology’ symposium. The meeting will be from 6th-10th September.

I’m very much looking forward to the visit. The conference is nearly 400 miles from the stricken Fukushima plant so should be entirely safe – but will obviously take advice nearer the time. The conference organizers have linked to a very interesting talk on the nuclear reactor melt-down that includes helpful calculations of risk:

I am particularly keen to show support to Japanese science at this difficult time for Japan.