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Overview: the research of MOSIMBIO group

Modelling microbial systems
Systems featuring a large number of interacting components (agents, processes or mechanisms) may show a complex behaviour, which is not easily understood, nor derivable from the sum of the activity of individual components.  Microbial biology is crowded with such complex systems and has increasingly become an exciting discipline of knowledge to be tackled from many perspectives simultaneously.
Models are simplied representations of the reality used to address specic questions regarding the systems under study. Computational models allow representing and simulating the components and processes of particular real systems.
Trial and refinement of the models is continually carried out together with real-world observations and experiments, in order to obtain insight and increase their predictive capability.
Foundations of MOSIMBIO 
The basic aim of the group MOSIMBIO (MOdeling and discrete SIMulation of BIOlogical systems) is to note general properties of microbial populations and ecosystems with models based on the individual cells: IbMs (Individual-based Models).
The research is carried out through the development of specific models addressed to particular systems. The microorganisms under study range from bacteria to fungi, yeasts and protozoa. The problems under study respond to a particular industrial demand or social concern, and the developed models pursue the improvement of the technological use of microbial systems in diverse fields such as food safety, soil quality and pharmaceutics.
Yet, an ultimate goal of the group is to acquire holistic understanding of microbial ecosystems in general; that is, to unravel the connections between the local microscopic rules (governing cells) and the macroscopic observations (regarding communities that typically contain around 109 cells).
MOSIMBIO has its origins in the fruitful collaboration of investigators studying the behaviour of liquids with techniques typically used by physics in solving N-bodies problems (Monte Carlo methods and Molecular Dynamics) with researchers that worked on the analysis of population dynamics in the framework of theoretical ecology.
The IbM approach allowed combining the techniques and experience from both disciplines: the biological rules governing the individuals could be framed with the physical laws that also describe their local environment, and the collective outcome could be drawn from the statistical treatment of the population ensemble.
This methodology provided a way to address questions that could not be covered otherwise, such as understanding the effect of the statistical distribution of individual traits among the population on the system dynamics, or proposing mechanisms for the emergence of coordinated global behaviours from the local individual interactions and including randomness.
The research group is specifically concerned with three different fields of application: biomedical sciences, food technology and environmental sciences.
Each field requires the collaboration with experts in the field, who detect and pose knotty unsolved questions and provide our group with heuristic knowledge and hypothesis to be tested by the models.
Real-world observations and experiments are designed in parallel to the building of the models and carried out at the ESAB (Escola Superior d'Agricultura de Barcelona) or at one of the collaboration centers.
Research in this field focuses on the spreading of the parasite causing malaria in different scenarios:
  •  Malaria in vitro cultures. The infection dynamics in  Red blood cell populations infected with Plasmodium falciparum in in vitro cultures are not fully understood. A better understanding of such experimental systems should be useful to improve the current techniques employed by the pharmaceutical industries to develop treatments and vaccines. 
  •  Malaria spreading and treatment strategies. The field actions carried out during the last years for malaria control and eradication in the affected areas has not successfully decreased the burden of the disease. Individual based modeling of the spreading of the epidemics can be helpful to revise and improve the current strategies.
The research in this field has been carried out in collaboration with GlaxoSmithKline. We are currently starting collaborations with Ferrer Grupo.
  • Tuberculosis. We have just started a collaboration with the Unitat de Tuberculosi Experimental in order to model in vitro and in vivo cultures of Mycobacterium tuberculosis.

The research topics in this ambit comprise different topics on predictive microbiology in foods:
  • Study of the lag phase. The lag phase in bacterial growth is one of the most important items in predictive microbiology and food safety. Our simulation studies help to interpret the different microscopic mechanisms that cause it.
  •  Growth of the yeast Saccharomyces cerevisiae. Many processes in food industry are based on the fermentation carried out by yeasts. Their behaviour is not yet fully understood. Our models study the effect of yeast flocculation, and reproduction through buds on the collective performance and on the aging, among others.
Research in this field has been carried out in collaboration with the BioTeC group from the Katholique Univerity of Leuven, the Institute of Food Research (Norwich, UK), and we are currently starting collaborations with the IRTA (Institut de Recerca i Tecnologia Agroalimentària de Catalunya, Monells).
The research topics in this ambit comprise:
  •  Dynamics of C and N in soil. Soil is a very complex system not yet fully understood. Our simulation models describe the evolutions of different pools of C and N in soil and make possible a holistic interpretation of the behaviour of real-world system.
  •  Composting process. Composting is central in the agroalimentary industry because it allows the treatment of residues and provides a source of fertilizers. Our models provide a spatially explicit representation of the composting process that should be useful to gain predictive capability.
  •  Biological depuration of waste water. The biological depuration of waste water is a complex process that involves many factors (physical, chemical and biological), with a certain structural similarity with the processes occurring in soil and compost. Our simulations build bridges between the available experimental data and the proposed mathematical models by validating, or otherwise rejecting, the modelled mechanisms.
Research in this field has been carried out in collaboration with the GIRO (Gestió Integral de Residus Orgànics), the Universitat de Lleida, the Universidad de Vigo and Ros Roca S.A.