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Timetable (UMCW02)

PhD Summer School: Methods for Mathematical and Empirical Analysis of Microbial Communities

Monday 27th October 2014 to Wednesday 29th October 2014

Monday 27th October 2014
12:00 to 12:30 Registration
12:30 to 13:20 Lunch at Wolfson Court
13:20 to 13:30 Welcome from John Toland (INI Director)
13:30 to 14:30 S Brown (University of Edinburgh)
Plenary Lecture 3: Understanding bacterial communication and cooperation: combinatorial quorum-sensing
Quorum sensing (QS) is a cell–cell communication system that controls gene expression in many bacterial species, mediated by diffusible signal molecules. Although the intracellular regulatory mechanisms of QS are often well-understood, the functional roles of QS remain controversial. In particular, the use of multiple signals by many bacterial species poses a serious challenge to current functional theories. Here, we address this challenge by showing that bacteria can use multiple QS signals to infer both their social (density) and physical (mass-transfer) environment. Analytical and evolutionary simulation models show that the detection of, and response to, complex social/physical contrasts requires multiple signals with distinct half-lives and combinatorial (nonadditive) responses to signal concentrations. We test these predictions using the opportunistic pathogen Pseudomonas aeruginosa and demonstrate significant differences in signal decay between its two primary si gnal molecules, as well as diverse combinatorial responses to dual-signal inputs. QS is associated with the control of secreted factors, and we show that secretome genes are preferentially controlled by synergistic “AND-gate” responses to multiple signal inputs, ensuring the effective expression of secreted factors in high-density and low mass-transfer environments. Our results show that combinatorial communication is not restricted solely to primates and is computationally achievable in single-celled organisms.
INI 1
14:30 to 14:45 Contributed Talk 1: tba INI 1
15:00 to 15:15 Contributed Talk 2: tba INI 1
15:15 to 15:30 Afternoon Tea
15:30 to 16:30 J Weitz (Georgia Institute of Technology)
Plenary Lecture 4: Theoretical principles of virus-host population dynamics
In this talk I will introduce theoretical principles underlying the study of virus-host interactions from an ecological perspective. In doing so, I will show how viruses can affect population dynamics, evolutionary dynamics and ecosystem functioning.

Related Links

•http://ecotheory.biology.gatech.edu

INI 1
16:30 to 17:30 J Kreft (University of Birmingham)
Plenary Lecture 5: Are simple models more general?
Co-author: Robert J Clegg (University of Birmingham)

Using some examples I will show that simpler models can be less general and that complex models can be less realistic. It is therefore important to vary the complexity of a model to test the structural robustness of models, not just checking off the parameter sensitivity box. For example, one ought to test which processes (e.g. growth, diffusion, migration, predation, …) need to be included in a model, but having to spend a lot of time implementing further processes that may turn out not to matter means that this is often not done, especially towards the end of a project. Open-source, individual-based modelling platforms can help here if many groups contribute by implementing further processes enabling the user to quickly try out a bunch of processes. In the end, models are more useful if they are less wrong.
INI 1
17:30 to 18:30 Wine Reception and Poster Session
Tuesday 28th October 2014
09:00 to 10:00 I Klapper (Temple University)
Biofilms, particularly Biofilm Models
INI 1
10:00 to 10:15 Contributed Talk 3: tba INI 1
10:15 to 10:30 Contributed Talk 4: tba INI 1
10:30 to 11:00 Morning Coffee
11:00 to 12:00 A McKane (University of Manchester)
Plenary Lecture 6: Stochastic modelling in population biology
The use of individual-based models is becoming far more widespread in the biological sciences, largely because of the prevalent use of simulations, but also because of the many interesting phenomena which are not present in population-level models. However many of the models studied at the individual level are not analysed mathematically, and remain defined in terms of a computer algorithm. This is not surprising, since they are intrinsically stochastic and require tools and techniques for their study which may be unfamiliar to many biologists. In this talk I'll give a brief introduction to some of the ideas and methods used in stochastic modelling, and illustrate them on a number of examples, to highlight the importance of including stochastic effects in a number of different situations.
INI 1
12:00 to 12:15 Contributed Talk 5: tba INI 1
12:15 to 12:30 Contributed Talk 6: tba INI 1
12:30 to 13:30 Lunch at Wolfson Court
14:00 to 15:00 C Quince (University of Glasgow)
Plenary Lecture 7: tba
INI 1
15:00 to 15:15 Contributed Talk 7: tba INI 1
15:15 to 15:30 Contributed Talk 8: tba INI 1
15:30 to 16:00 Afternoon Tea
16:00 to 17:00 Q Jin (University of Oregon)
Plenary Lecture 8: tba
INI 1
17:00 to 18:00 T Pfeiffer (Massey University)
Game theory for modelling microbial communities
INI 1
Wednesday 29th October 2014
09:30 to 10:30 C Tarnita (Princeton University)
Plenary Lecture 9: Mathematics of social behavior
I will begin with a discussion and mathematical description of the two different types of social construction: `staying together' and `coming together' (or aggregation). Staying together means that individuals form larger units (complexes, groups) by not separating after reproduction (eg. ant colonies, most multicellular organisms), while coming together means that independent individuals form aggregates (eg. most animal groups, including humans). For each of these operations I will discuss its strengths and vulnerabilities in promoting social behavior, which will lead naturally into a discussion of the various mechanisms (and the relationships between them) that have been proposed to explain the evolution and maintenance of social behavior and cooperation: direct and indirect reciprocity, kin selection, group/multilevel selection, spatial structure, punishment/ostracism, rewards. I will discuss the theoretical frameworks in which these mechanisms are generally studied and for each mechanism I will present a simple model that captures the essence of how it can be described mathematically. Examples will be given from multicellularity, eusociality, bacterial biofilms, animal and human behavior.
INI 1
10:30 to 10:45 Contributed Talk 9: tba INI 1
10:45 to 11:00 Contributed Talk 10: tba INI 1
11:00 to 11:30 Morning Coffee
11:30 to 12:30 D Segre (Boston University)
Plenary Lecture 10: tba
INI 1
12:30 to 13:30 Lunch at Wolfson Court
19:30 to 22:00 Conference Dinner at Emmanuel College
University of Cambridge Research Councils UK
    Clay Mathematics Institute The Leverhulme Trust London Mathematical Society Microsoft Research NM Rothschild and Sons