Microscopic Modelling of Active Bacterial Suspensions

A. Decoene; S. Martin; B. Maury

Mathematical Modelling of Natural Phenomena (2011)

  • Volume: 6, Issue: 5, page 98-129
  • ISSN: 0973-5348

Abstract

top
We present two-dimensional simulations of chemotactic self-propelled bacteria swimming in a viscous fluid. Self-propulsion is modelled by a couple of forces of same intensity and opposite direction applied on the rigid bacterial body and on an associated region in the fluid representing the flagellar bundle. The method for solving the fluid flow and the motion of the bacteria is based on a variational formulation written on the whole domain, strongly coupling the fluid and the rigid particle problems: rigid motion is enforced by penalizing the strain rate tensor on the rigid domain, while incompressibility is treated by duality. This model allows to achieve an accurate description of fluid motion and hydrodynamic interactions in moderate to concentrated active suspensions. A mesoscopic model is also used, in which the size of the bacteria is supposed to be much smaller than the elements of fluid: the perturbation of the fluid due to propulsion and motion of the swimmers is neglected, and the fluid is only subjected to the buoyant forcing induced by the presence of the bacteria, which are denser than the fluid. Although this model does not accurately take into account hydrodynamic interactions, it is able to reproduce complex collective dynamics observed in concentrated bacterial suspensions, such as bioconvection. From a mathematical point of view, both models lead to a minimization problem which is solved with a standard Finite Element Method. In order to ensure robustness, a projection algorithm is used to deal with contacts between particles. We also reproduce chemotactic behaviour driven by oxygen: an advection-diffusion equation on the oxygen concentration is solved in the fluid domain, with a source term accounting for oxygen consumption by the bacteria. The orientations of the individual bacteria are subjected to random changes, with a frequency that depends on the surrounding oxygen concentration, in order to favor the direction of the concentration gradient.

How to cite

top

Decoene, A., Martin, S., and Maury, B.. "Microscopic Modelling of Active Bacterial Suspensions." Mathematical Modelling of Natural Phenomena 6.5 (2011): 98-129. <http://eudml.org/doc/222291>.

@article{Decoene2011,
abstract = {We present two-dimensional simulations of chemotactic self-propelled bacteria swimming in a viscous fluid. Self-propulsion is modelled by a couple of forces of same intensity and opposite direction applied on the rigid bacterial body and on an associated region in the fluid representing the flagellar bundle. The method for solving the fluid flow and the motion of the bacteria is based on a variational formulation written on the whole domain, strongly coupling the fluid and the rigid particle problems: rigid motion is enforced by penalizing the strain rate tensor on the rigid domain, while incompressibility is treated by duality. This model allows to achieve an accurate description of fluid motion and hydrodynamic interactions in moderate to concentrated active suspensions. A mesoscopic model is also used, in which the size of the bacteria is supposed to be much smaller than the elements of fluid: the perturbation of the fluid due to propulsion and motion of the swimmers is neglected, and the fluid is only subjected to the buoyant forcing induced by the presence of the bacteria, which are denser than the fluid. Although this model does not accurately take into account hydrodynamic interactions, it is able to reproduce complex collective dynamics observed in concentrated bacterial suspensions, such as bioconvection. From a mathematical point of view, both models lead to a minimization problem which is solved with a standard Finite Element Method. In order to ensure robustness, a projection algorithm is used to deal with contacts between particles. We also reproduce chemotactic behaviour driven by oxygen: an advection-diffusion equation on the oxygen concentration is solved in the fluid domain, with a source term accounting for oxygen consumption by the bacteria. The orientations of the individual bacteria are subjected to random changes, with a frequency that depends on the surrounding oxygen concentration, in order to favor the direction of the concentration gradient. },
author = {Decoene, A., Martin, S., Maury, B.},
journal = {Mathematical Modelling of Natural Phenomena},
keywords = {Stokes flow; fluid-particle flows; self-propulsion; finite element method; penalty method; chemotaxis.; chemotaxis},
language = {eng},
month = {8},
number = {5},
pages = {98-129},
publisher = {EDP Sciences},
title = {Microscopic Modelling of Active Bacterial Suspensions},
url = {http://eudml.org/doc/222291},
volume = {6},
year = {2011},
}

TY - JOUR
AU - Decoene, A.
AU - Martin, S.
AU - Maury, B.
TI - Microscopic Modelling of Active Bacterial Suspensions
JO - Mathematical Modelling of Natural Phenomena
DA - 2011/8//
PB - EDP Sciences
VL - 6
IS - 5
SP - 98
EP - 129
AB - We present two-dimensional simulations of chemotactic self-propelled bacteria swimming in a viscous fluid. Self-propulsion is modelled by a couple of forces of same intensity and opposite direction applied on the rigid bacterial body and on an associated region in the fluid representing the flagellar bundle. The method for solving the fluid flow and the motion of the bacteria is based on a variational formulation written on the whole domain, strongly coupling the fluid and the rigid particle problems: rigid motion is enforced by penalizing the strain rate tensor on the rigid domain, while incompressibility is treated by duality. This model allows to achieve an accurate description of fluid motion and hydrodynamic interactions in moderate to concentrated active suspensions. A mesoscopic model is also used, in which the size of the bacteria is supposed to be much smaller than the elements of fluid: the perturbation of the fluid due to propulsion and motion of the swimmers is neglected, and the fluid is only subjected to the buoyant forcing induced by the presence of the bacteria, which are denser than the fluid. Although this model does not accurately take into account hydrodynamic interactions, it is able to reproduce complex collective dynamics observed in concentrated bacterial suspensions, such as bioconvection. From a mathematical point of view, both models lead to a minimization problem which is solved with a standard Finite Element Method. In order to ensure robustness, a projection algorithm is used to deal with contacts between particles. We also reproduce chemotactic behaviour driven by oxygen: an advection-diffusion equation on the oxygen concentration is solved in the fluid domain, with a source term accounting for oxygen consumption by the bacteria. The orientations of the individual bacteria are subjected to random changes, with a frequency that depends on the surrounding oxygen concentration, in order to favor the direction of the concentration gradient.
LA - eng
KW - Stokes flow; fluid-particle flows; self-propulsion; finite element method; penalty method; chemotaxis.; chemotaxis
UR - http://eudml.org/doc/222291
ER -

References

top
  1. H.C. Berg. Random walks in biology. Princeton University Press, Princeton, 1983.  
  2. H.C. Berg. E. Coli in Motion. Springer Verlag, New York, 2004.  
  3. B.M. Haines, I.S. Aranson, L. Berlyand and D.A. Karpeev. Effective viscosity of dilute bacterial suspensions: a two-dimensional model. Physical Biology, 5 (2008), No. 4.  
  4. P. G. Ciarlet. Introduction à l’analyse numérique matricielle et à l’optimisation. Masson, Paris, 1990.  
  5. L.H. Cisneros, R. Cortez, C. Dombrowski, R.E. Goldstein, J.O. Kessler. Fluid dynamics of self-propelled microorganisms. from individual to concentrated populations. Exp Fluids, 43 (2007), 737–753.  
  6. Darnton NC, Turner L, Rojevsky S, Berg HC. Dynamics of bacterial swarming. Biophys J.98 (2010), No. 10, 2082–90.  
  7. A. Decoene, A. Lorz, S. Martin, B. Maury, M. Tang. Simulation of self-propelled chemotactic bacteria in a Stokes flow. ESAIM: Proc, 30 (2010), 104–123 .  
  8. C. Dombrowski, L. Cisneros, S. Chatkaew, R. E. Goldstein, J. O. Kessler. Self-concentration and large-scale coherence in bacteria dynamics. Phys. Rev. Lett., 93 (2004), No. 9.  
  9. D. Gérard-Varet, M. Hillairet. Regularity Issues in the Problem of Fluid Structure Interaction. to appear in Arch. Rational Mech. Anal.  
  10. R. Glowinski, T. W. Pan, T. I. Hesla, D. D. Joseph & J. Périaux. A fictitious domain approach to the direct numerical simulation of incompressible viscous flow past moving rigid bodies: application to particulate flow. J. Comp. Phys., 169 (2001), 363–427.  
  11. R. Glowinski. Finite element methods for incompressible viscous flow. In: Handbook of Numerical Analysis, Vol. IX, P. G. Ciarlet and J.-L. Lions eds., Ed. North-Holland, Amsterdam, 2003.  
  12. V. Gyrya, K. Lipnikov, I. Aranson, L. Berlyand. Effective shear viscosity and dynamics of suspensions of micro-swimmers from small to moderate suspensions. Journal of Mathematical Biology (accepted, 2011).  
  13. Hernandez-Ortiz J.P., C. Stoltz and M.D. Graham. Transport and col lective dynamics in suspensions of confined swimming particles. Phys. Rev. Lett., 95 (2005), pp. 204501.  
  14. J. Happel, H. Brenner. Low Reynolds Number Hydrodynamics. Dordrecht, Kluwer, 1991.  
  15. M. Hillairet. Lack of collision between solid bodies in a 2D constant-density incompressible flow. Communications in Partial Differential Equations32 (2007), 1345-1371.  
  16. J. Janela, A. Lefebvre, B. Maury. A penalty method for the simulation of fluid-rigid body interaction. ESAIM: Proc., 1 (2007), 115–123.  
  17. D. Kaiser. Bacterial swarming, a re-examination of cell movement patterns. Curr Biol, 17 (2007), R561-R570.  
  18. S. Kim, S.J. Karrila. Microhydrodynamics: Principles and Selected Applications. Dover, New York, 2005.  
  19. E. Lauga and T.R. Powers. The hydrodynamics of swimming microorganisms. Rep. Prog. Phys., 72 (2009).  
  20. A. Lefebvre. Fluid-particle simulations with Freefem++. ESAIM: Proc., 18 (2007), 120–132.  
  21. A. Lefebvre, B. Maury. Apparent viscosity of a mixture of a Newtonian fluid and interacting particles. Fluid-solid interactions: modeling, simulation, bio-mechanical applications. Comptes Rendus MŐcanique, 333 (2005), No. 12.  
  22. B. Maury. A time-stepping scheme for inelastic collisions. Numerische Mathematik, 102 (2006), No. 4, 649–679.  
  23. B. Maury. Numerical Analysis of a Finite Element / Volume Penalty Method. SIAM J. Numer. Anal.47 (2009), No. 2, 1126–1148.  
  24. J.T. Locsei, T.J. Pedley. Run and Tumble in Chemotaxis in a Shear Flow; The Effect of Temporal Comparisons, Persistence, Rotational Diffusion, and Cell Shape. Bulletin of Mathematical Biology, 71 (2009), 1089–1116.  
  25. J.O. Kessler, T.J. Pedley. Hydrodynamic phenomena in suspensions of swimming microorganisms. Annu. Rev. Fluid Mech.24 (1992), 313–58.  
  26. F. Peruani, L. G. Morelli. Self-propelled particles with fluctuating speed and direction of motion in two dimensions. PRL 99 (2007), 010602, 2007.  
  27. S. Rafai, L. Jibuti, P. Peyla. Effective viscosity of microswimmer suspensions. Phys. Rev. Lett., 104 (2010), 098102.  
  28. D. Saintillan, M. J. Shelley. Orientational order and instabilities in suspensions of self-locomoting rods. Phys. Rev. Lett., 99 (2007), 058102.  
  29. J. E. Segall, S.M. Block, H.C. Berg. Temporal comparisons in bacterial chemotaxis. Proc. Natl . Acad. Sci. USA, 83 (1986), 8987–8991.  
  30. A. Sokolov, I. S. Aranson. Reduction of viscosity in suspension of swimming bacteria. Phys. Rev. Lett.103 (2009), 148101.  
  31. A. Sokolov, R. E. Goldstein, F. I. Feldchtein, and I. S. Aranson. Enhanced mixing and spatial instability in concentrated bacterial suspensions. Phys. Rev. E80 (2009), 031903.  
  32. R. Temam, A. Miranville. Mathematical modeling in continuum mechanics. Cambridge University press, 2001.  
  33. L. Turner, W.S. Ryu, H.C. Berg. Real-time imaging of fluorescent flagellar filaments. J. Bacteriol., 182 (2000), No. 10, 2793–2801.  
  34. I. Tuval, L. Cisneros, C. Dombrowski, C. W. Wolgemuth, J.O. Kessler, R. E. Goldstein. Bacterial swimming and oxygen transport near contact lines. Proc. Natl. Acad. Sci. USA, 102 (2005), 2277–2282.  
  35. S. Vincent, J. P. Caltagirone, P. Lubin & T. N. Randrianarivelo. An adaptative augmented Lagrangian method for three-dimensional multimaterial flows. Computers and Fluids, 33 (2004), 1273–1289.  
  36. X.-L. Wu, A. Libchaber. Particle diffusion in a quasi-two-dimensional bacterial bath. Physical Review Letters, 84 (2000), 3017–3020.  
  37. Y. Wu, D. Kaiser, Y. Jiang, M. S. Alber. Periodic reversal of direction allows Myxobacteria to swarm. Proc. Natl. Acad. Sci. USA, 106 (2009), No. 4, 1222–1227.  

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.