Spring Conference 2011 - Society for General Microbiology

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Please note: Abstracts are published as received from the authors and are not subject to editing. 11 Spring Meeting 11–14 April 2011 Harrogate – www.sgmharrogate2011.org.uk SESSION AbSTrACTS ↑Contents HA02 Cont. organisms; (3) Phylogenetics: (a) Fox and Woese’s three superkingdoms, (b) Margulis’ endosymbiotic theory, (c) Pace and relner’s microbiome; (4) Boolean models – Operons – Jacob and Monod; (5) Fluctuation test – luria-Delbrück – Poisson distribution; (6) logistic growth– environmental carrying capacity; (7) interval graphs – Benzer – fine structure of the gene; (8) Eulerian topology – Caspar and Klug – viral capsids – self-assembly; (9) Bioinformatics – gene order and content – pathogenicity hypothesis; (10) Fluid mechanics – ‘life at low reynolds Numbers.’ See our Microbes Count project: (http://bioquest.org/microbescount/) and MathBioEd issue: (http://www.lifescied.org/ content/vol9/issue3/cover.dtl). Using maths to understand biofilms Paul Stoodley School of Engineering Sciences, University of Southampton, University Road, Southampton SO17 1BJ The development of bacterial biofilms is influenced by both genetic (internal) and environmental (external) factors. Fluid flow is an important external factor since it controls two competing influences; 1) the mechanical stresses acting on the biofilm which tend to reduce biofilm through erosion and sloughing, and 2) the delivery of nutrients which tend to increase biofilm through growth. Fluid flow can also remove metabolites such as waste products and diffusible signal molecules from the biofilm which in turn will influence the concentration gradients which build up within the biofilms. Various important parameters will be described and examples will be used to illustrate how the hydrodynamic conditions (reynolds number, wall shear stress) of laboratory systems can be calculated from a few simple parameters such as the reactor geometry and flow rate. A simple model developed by Phil Stewart at the Center for Biofilm Engineering at Montana State university will be used to illustrate how various chemicals can diffuse through biofilms as a function of biofilm thickness and the diffusion coefficient. Massively-parallel microbial search: a new platform for synthetic biology Martyn Amos Novel Computation Group, School of Computing, Mathematics & Digital Technology, Manchester Metropolitan University Synthetic biology is a new discipline that is emerging at the intersections of biology, computing science, engineering, chemistry and maths. Practitioners in the field are particularly interested in applying rational engineering principles to biological systems, with the aim of persuading them to perform ‘useful’, human-defined tasks. in this talk, i will give a brief overview of the state-of-the-art, before describing our own work (as coordinator of the Eu BACTOCOM project) on a population-based, massively-parallel microbial search algorithm. This work will, we hope, lay the foundations for rapid and reliable synthetic biology, with potential applications in areas as diverse as drug production, environmental sensing, tissue engineering and energy. Microbial evolution in theory and practice ivana Gudelj Biosciences, University of Exeter Microbes are ubiquitous in nature and occupy virtually every environmental niche on earth. Contributing to this evolutionary success are diverse metabolic strategies as well as the ability to adapt to changing environments. Experimental evolution has provided an ideal setting for studying microbial diversification in action –experiments are conducted in controlled environments using culturable strains that are easily manipulated due to their known genetic structure. However this simplified approach to evolution poses the following questions: How do we know whether a given experimental outcome is particular to the laboratory system? What can we learn from laboratory experiments about micro-organisms in the wild? in this talk i argue that through the use of mathematical models we can begin to bridge the gap between laboratory and nature. i will present a mathematical model used to study microbial cooperation and demonstrate that this model can make good quantitative predictions of a given laboratory experimental setup. Subsequently i will discuss how these predictions can be generalized to other systems. HEA perspective and comments on maths teaching and graduate skills David J. Adams UK Centre for Bioscience, Higher Education Academy The maths and stats components of modern biology degree programmes are becoming increasingly demanding. There is widespread concern that students enter uK universities ill-equipped for the challenges associated with, for example, bioinformatics or a newly emerging area associated with so-called systems biology. This problem is exacerbated by a general lack of maths content in undergraduate biology s o c i e t y f o r g e n e r a l Microbiology
Please note: Abstracts are published as received from the authors and are not subject to editing. 12 Spring Meeting 11–14 April 2011 Harrogate – www.sgmharrogate2011.org.uk SESSION AbSTrACTS ↑Contents HA02 Cont. programmes; industrialists and research degree supervisors alike have complained of graduates lacking basic mathematical skills in research labs or other workplace settings. During 2010, the uK Centre for Bioscience, with BBSrC, sought to address these issues by holding a one day event on Mathematical Challenges for Biologists. Some of the major issues discussed at this meeting, along with key outcomes, will be presented. in particular the Centre has commissioned a survey that will assess the maths and stats content of uK undergraduate bioscience degree programmes and preliminary results from this survey will be discussed. in addition, examples of how the Higher Education Academy has supported, and continues to support, maths and stats teaching in uK universities will be described. Emphasis will be placed on how the Academy can best support microbiologists and other bioscientists within the new structure it will adopt from 2011/12. Offered paper Developing numeracy skills in biomedical sciences- a case study Pauline Fitzgerald Leeds Metropolitan University Since 1997, and the Dearing report recommendations that higher education courses should focus on key skills such as numeracy, universities have applied themselves to looking at the different ways in which these can be embedded into courses. Numeracy is one of the skills employers value highly, and yet students find maths difficult. So how can we develop these skills and improve employability in our graduates?The approach we have adopted at leeds Metropolitan university is to have an employability/ transferable skills strand at each level of the course. At level 1, the students undertake a ‘skills audit’, which involves some maths, so they can assess their knowledge and develop their numeracy skills. At level 2 they undertake a professional practice module which starts to apply their maths skills to the working environment. At level 3 they develop this further by undertaking a project management module. Their remit is to come up with a new biotech product, then show how they would develop the product, from the science behind it through to marketing and finance. As the course progresses, the students begin to appreciate the different ways that their maths skills can be promoted to potential employers. biomathtutor: what is it and could it help? Vicki Tariq University of Central Lancashire, Preston, Lancashire PR1 2HE Biomathtutor represents a prototype multimedia e-learning resource, which aims to support mathematics learning in the biosciences. A contextual, scenario-based problem-solving learning model has been adopted, in which a case study scenario, which covers aspects of haematology and microbiology, is presented via a stimulating high quality professionally produced narrated film. linked to the content of the film are thirty-three interactive questions for students to attempt on screen. Twenty-four additional practice questions, which cover the same range of basic mathematical concepts, presented in similar biological contexts, are also available for completion. in addition, students can access five relatively short face-to-face video mathematics tutorials in which a tutor explains some of the mathematical concepts students encounter in the interactive questions. During 2006/07, a project funded by the Higher Education Academy assessed the quality of the prototype learning materials developed and investigated their potential for integration into bioscience curricula. The methodology adopted involved the analysis of both quantitative and qualitative data from undergraduates and their tutors, using questionnaires, focus groups (students) and interviews (tutors). Overall, the reactions of students and their tutors toward biomathtutor were very positive, with both groups commenting favourably on aspects of its design and its potential to support mathematics learning. Mathematical predictions of antibiotic therapy efficacy robert Beardmore Dept of Biosciences, University of Exeter, Geoffrey Pope Building, Streatham Campus, Exeter EX4 4QD One of the main goals of applied mathematical research is to identify boundaries between different behavioral regimes in physical systems. For example, the phase transitions of physics are intimately related to the mathematical descriptions of nonlinear systems provided by bifurcation theory. Evolving biological systems are far more complex still and we should not be surprised if one model system displays a multitude of different behaviors. However, mathematics is one possible tool to decipher similar systems likely to behave differently and disparate systems likely to behave in the same way.Two examples of this philosophy will be given: a study of an evolving bacteriaphage microcosm and a theoretical epidemiological drug deployment problem from the literature. in the former, experiments designed to measure genetic diversity are sensitive to molecular details, in the latter, broad-scale conclusions on optimal drug deployment policies appear insensitive to many biological details. Finally, we discuss what can go wrong if inappropriate theoretical techniques are applied to mathematical formulations of such biological problems. s o c i e t y f o r g e n e r a l Microbiology
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Spring Conference 2011 - Society for General Microbiology

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