Abstract
Kinetic theory is an old subject which finds its motivations in the description of fluids at the so-called mesoscopic scale where molecules interact but are too numerous for describing the interacting particles individually. We present several examples from physics, we give some mathematical background showing that the kinetic-transport equation enjoys interesting functional analytic properties as other partial differential equations. We also describe in full generality how macroscopic models are derived from kinetic equations. This material gives us the tools to introduce models for bacterial run and tumble motion. The subject has been progressing quickly in the last decades, and a hierarchy of models are now available up to the scale of molecular pathways describing the cell decision to tumble.
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References
J. Adler, Chemotaxis in bacteria. Science 153, 708–716 (1966)
L. Almeida, C. Emako, N. Vauchelet, Existence and diffusive limit of a two-species kinetic model of chemotaxis. Kinet. Relat. Models 8, 359 (2015)
W. Alt, Biased random walk models for chemotaxis and related diffusion approximations. J. Math. Biol. 9, 147–177 (1980)
C. Bardos, R. Santos, R. Sentis, Diffusion approximation and computation of the critical size. Trans. Am. Math. Soc. 284(2), 617–649 (1984)
C. Bardos, P. Degond, Global existence for the Vlasov-Poisson equation in 3 space variables with small initial data. Ann. Inst. H. Poincaré Anal. Non Linéaire 2(2), 101–118 (1985)
N. Bellomo, M. Winkler, A degenerate chemotaxis system with flux limitation: maximally extended solutions and absence of gradient blow-up. Commun. Part. Differ. Equ. 42, 436–473 (2017)
H.C. Berg, E. coli in Motion (Springer, Berlin, 2004)
A. Blanchet, J. Dolbeault, B. Perthame, Two-dimensional Keller-Segel model: optimal critical mass and qualitative properties of the solutions. Electron. J. Differ. Equ. 2006(44), 1–32 (2006)
E. Bouin, V. Calvez, G. Nadin, Propagation in a kinetic reaction-transport equation: travelling waves and accelerating fronts. Arch. Ration. Mech. Anal. 217(2), 571–617(2015)
N. Bournaveas, V. Calvez, Global existence for the kinetic chemotaxis model without pointwise memory effects, and including internal variables. Kinet. Relat. Models 1(1), 29–48 (2008)
N. Bournaveas, V. Calvez, Critical mass phenomenon for a chemotaxis kinetic model with spherically symmetric initial data. Ann. Inst. H. Poincaré Anal. Non Linéaire 26(5), 1871–1895 (2009)
N. Bournaveas, V. Calvez, S. Gutièrrez, B. Perthame, Global existence for a kinetic model of chemotaxis via dispersion and Strichartz estimates. Commun. Partial Differ. Equ. 33, 79–95 (2008)
M.P. Brenner, L.S. Levitov, E.O. Budrene, Physical mechanisms for chemotactic pattern formation by bacteria. Biophys J. 74, 1677–1693 (1998)
E.O. Budrene, H.C. Berg, Dynamics of formation of symmetrical patterns by chemotactic bacteria. Nature 376, 49–53 (1995)
D. Cai, L. Tao, M. Shelley, D.W. McLaughlin, An effective kinetic representation of fluctuation-driven neuronal networks with application to simple and complex cells in visual cortex. PNAS 101, 7757–7762 (2004)
V. Calvez, Chemotactic waves of bacteria at the mesoscale (2016), arXiv:1607.00429
V. Calvez, B. Perthame, S. Yasuda, Traveling wave and aggregation in a flux-limited Keller-Segel model (2017, preprint), arXiv:1709.07296
V. Calvez, G. Raoul, C. Schmeiser, Confinement by biased velocity jumps: aggregation of Escherichia coli. Kinet. Relat. Models 8(4), 651–666 (2015)
J. Caron, J.-L. Feugeas, B. Dubroca, G. Kantor, C. Dejean, T. Pichard, Ph. Nicolaï, E. D’Humières, M. Frank, V. Tikhonchuk, Deterministic model for the transport of energetic particles: application in the electron radiotherapy. Phys. Med. 31(8), 912–921 (2015)
F. Castella, B. Perthame, Estimations de Strichartz pour les équations de transport cinétique. (French) [Strichartz’ estimates for kinetic transport equations] C. R. Acad. Sci. Paris Sér. I Math. 322(6), 535–540 (1996)
C. Cercignani, The Boltzmann Equation and Its Applications. Applied Mathematical Sciences, vol. 67 (Springer, New York, 1988), xii+455 pp
C. Cercignani, R. Illner, M. Pulvirenti, The Mathematical Theory of Dilute Gases. Applied Mathematical Sciences, vol. 106 (Springer, New York, 1994), viii+347 pp
F. Chalub, P.A. Markowich, B. Perthame, C. Schmeiser, Kinetic models for chemotaxis and their drift-diffusion limits. Monatsh. Math. 142, 123–141 (2004)
A. Chertock, A. Kurganov, X. Wang, Y. Wu, On a chemotaxis model with saturated chemotactic flux. Kinet. Relat. Models 5, 51–95 (2012)
Y. Dolak, C. Schmeiser, Kinetic models for chemotaxis: hydrodynamic limits and spatio-temporal mechanisms. J. Math. Biol. 51, 595–615 (2005)
R. Eftimie, Hyperbolic and kinetic models for self-organized biological aggregations and movement: a brief review. J. Math. Biol. 65, 35–75 (2012)
C. Emako, C. Gayrard, A. Buguin, L. Almeida, N. Vauchelet, Traveling pulses for a two species chemotaxis model. PLoS Comput. Biol. 12, e1004843 (2016)
R. Erban, H. Othmer, From individual to collective behaviour in bacterial chemotaxis. SIAM J. Appl. Math. 65(2), 361–391 (2004)
R. Erban, H. Othmer, Taxis equations for amoeboid cells. J. Math. Biol. 54, 847–885 (2007)
R. Glassey, The Cauchy Problem in Kinetic Theory (SIAM, Philadelphia, 1996)
I. Golding, Y. Kozlovski, I. Cohen, E. BenJacob, Studies of bacterial branching growth using reaction-diffusion models for colonial development. Phys. A 260, 510–554 (1998)
F. Golse, Fluid dynamic limits of the kinetic theory of gases, in From Particle Systems to Partial Differential Equations. Springer Proceedings in Mathematics & Statistics, vol. 75 (Springer, Heidelberg, 2014), pp. 3–91
F. Golse, P.-L. Lions, B. Perthame, R. Sentis, Regularity of the moments of the solution of a transport equation. J. Funct. Anal. 76(1), 110–125 (1988)
G.L. Hazelbauer, Bacterial chemotaxis: the early years of molecular studies. Annu. Rev. Microbiol. 66, 285–303 (2012)
T. Hillen, M5 mesoscopic and macroscopic models for mesenchymal motion. J. Math. Biol. 53, 585–616 (2006)
T. Hillen, H.G. Othmer, The diffusion limit of transport equations derived from velocity-jump processes. SIAM J. Appl. Math. 61, 751–775 (2000)
T. Hillen, K.J. Painter, A user’s guide to PDE models for chemotaxis. J. Math. Biol. 58, 183–217 (2009)
T. Hillen, K. Painter, Transport and anisotropic diffusion models for movement in oriented habitats, in Dispersal, Individual Movement and Spatial Ecology: A mathematical perspective, ed. by M.A. Lewis, P. Maini, S. Petrowskii (Springer, Heidelberg, 2012), pp. 177–222
T. Hillen, A. Swan, The diffusion limit of transport equations in biology, in Mathematical Models and Methods for Living Systems. Lecture Notes in Mathematics, vol. 2167, Fond. CIME/CIME Foundation Subseries (Springer, Cham, 2016), pp. 73–129
T. Hillen, P. Hinow, Z. Wang, Mathematical analysis of a kinetic model for cell movement in network tissues. Discrete Contin. Dyn. Syst. Ser. B 14(3), 1055–1080 (2010)
H.J. Hwang, K. Kang, A. Stevens, Global solutions of nonlinear transport equations for chemosensitive movement. SIAM. J. Math. Anal. 36, 1177–1199 (2005)
F. James, N. Vauchelet, Chemotaxis: from kinetic equations to aggregate dynamics. Nonlinear Differ. Equ. Appl. 20(1), 101–127 (2013)
F. James, N. Vauchelet, Equivalence between duality and gradient flow solutions for one-dimensional aggregation equations. Discrete Contin. Dyn. Syst. 36(3), 1355–1382 (2016)
L. Jiang, Q. Ouyang, Y. Tu, Quantitative modeling of Escherichia coli chemotactic motion in environments varying in space and time. PLoS Comput. Biol. 6, e1000735 (2010)
Y.V. Kalinin, L. Jiang, Y. Tu, M. Wu, Logarithmic sensing in Escherichia coli bacterial chemotaxis. Biophys. J. 96(6), 2439–2448 (2009)
M. Keel, T. Tao, Endpoint Strichartz estimates. Am. J. Math. 120(5), 955–980 (1998)
E.F. Keller, L.A. Segel, Traveling bands of chemotactic bacteria: a theoretical analysis. J. Theor. Biol. 30, 235–248 (1971)
J. Liao, Global solution for a kinetic chemotaxis model with internal dynamics and its fast adaptation limit. J. Differ. Equ. 259(11), 6432–6458 (2015)
J.T. Locsei, Persistence of direction increases the drift velocity of run and tumble chemotaxis. J. Math. Biol. 55(1), 41–60 (2007)
B. Mazzag, I. Zhulin, A. Mogilner, Model of bacterial band formation in aerotaxis. Biophys. J. 85, 3558–3574 (2003)
N. Mittal, E.O. Budrene, M.P. Brenner, A. Van Oudenaarden, Motility of Escherichia coli cells in clusters formed by chemotactic aggregation. Proc. Natl. Acad. Sci. U. S. A. 100, 13259–13263 (2003)
M. Mizoguchi, M. Winkler, Blow-up in the two-dimensional parabolic Keller-Segel system. Personal communication
J.D. Murray, Mathematical Biology, vol. 2, 2nd edn. (Springer, Berlin, 2002)
G. Nadin, B. Perthame, L. Ryzhik, Traveling waves for the Keller-Segel system with Fisher birth terms. Interface Free Bound. 10, 517–538 (2008)
H.G. Othmer, T. Hillen, The diffusion limit of transport equations II: chemotaxis equations. SIAM J. Appl. Math. 62, 122–1250 (2002)
H. Othmer, S. Dunbar, W. Alt, Models of dispersal in biological systems. J. Math. Biol. 26, 263–298 (1988)
H.G. Othmer, X. Xin, C. Xue, Excitation and adaptation in bacteria-a model signal transduction system that controls taxis and spatial pattern formation. Int. J. Mol. Sci. 14(5), 9205–9248 (2013)
B. Perthame, Mathematics tools for kinetic equations. Bull. Am. Math. Soc. 41(2), 205–244 (2004)
B. Perthame, Transport Equations in Biology. Frontiers in Mathematics (Birkhäuser, Basel, 2007), x+198 pp
B. Perthame, Parabolic Equations in Biology. Growth, Reaction, Movement and Diffusion. Lecture Notes on Mathematical Modelling in the Life Sciences (Springer, Cham, 2015), xii+199 pp
B. Perthame, D. Salort, On a voltage-conductance kinetic system for integrate & fire neural networks. Kinet. Relat. Models 6(4), 841–864 (2013)
B. Perthame, P.E. Souganidis, A limiting case for velocity averaging. Ann. Sci. école Norm. Sup. (4) 31(4), 591–598 (1998)
B. Perthame, S. Yasuda, Stiff-response-induced instability for chemotactic bacteria and flux-limited Keller-Segel equation (2017, preprint), arXiv:1703.08386
B. Perthame, M. Tang, N. Vauchelet, Derivation of the bacterial run-and-tumble kinetic equation from a model with biochemical pathway. J. Math. Biol. 73(5), 1161–1178 (2016)
B. Perthame, Z. Wang, N. Vauchelet, Modulation of stiff response in E. coli bacterial motion. Revista Matemática Iberoamericana. In press
S.L. Porter, G.H. Wadhams, J.P. Armitage, Rhodobacter sphaeroides: complexity in chemotactic signalling. Trends Microbiol. 16(6), 251–260 (2008)
A.B. Potapov, T. Hillen, Metastability in chemotaxis model. J. Dyn. Differ. Equ. 17(2), 293–330 (2005)
C.V. Rao, J.R. Kirby, A.P. Arkin, Design and diversity in bacterial chemotaxis: a comparative study in Escherichia coli and Bacillus subtilis. PLoS Biol 2(2), E49 (2004)
J. Saragosti, V. Calvez, N. Bournaveas, A. Buguin, P. Silberzan, B. Perthame, Mathematical description of bacterial traveling pulses. PLoS Comput Biol. 6(8), e1000890 (2010)
J. Saragosti, V. Calvez, N. Bournaveas, B. Perthame, A. Buguin, P. Silberzan, Directional persistence of chemotactic bacteria in a traveling concentration wave. Proc. Natl. Acad. Sci. 108(39), 16235–16240 (2011)
G. Si, T. Wu, Q. Ouyang, Y. Tu, A pathway-based mean-field model for Escherichia coli chemotaxis. Phys. Rev. Lett. 109, 048101 (2012)
G. Si, M. Tang, X. Yang, A pathway-based mean-field model for E. coli chemo- taxis: mathematical derivation and Keller-Segel limit. Multiscale Model Simul. 12(2), 907–926 (2014)
Y. Tu, T.S. Shimizu, H.C. Berg, Modeling the chemotactic response of Escherichia coli to time-varying stimuli. Proc. Natl. Acad. Sci. U. S. A. 105(39), 14855–14860 (2008)
M.J. Tindall, P.K. Maini, S.L. Porter, J.P. Armitage, Overview of mathematical approaches used to model bacterial chemotaxis II: bacterial populations. Bull. Math. Biol. 70, 1570–1607 (2008)
N. Vauchelet, Numerical simulation of a kinetic model for chemotaxis. Kinet. Relat. Models 3(3), 501–528 (2010)
C. Villani, A review of mathematical topics in collisional kinetic theory, in Handbook of Mathematical Fluid Dynamics, ed. by S. Friedlander, D. Serre (Elsevier, Amsterdam, 2002)
X. Xin, H.G. Othmer, A trimer of dimers-based model for the chemotactic signal transduction network in bacterial chemotaxis. Bull. Math. Biol. 74(10), 2339–2382 (2012)
C. Xue, H.G. Othmer, Multiscale models of taxis-driven patterning in bacterial populations. SIAM J. Appl. Math. 70(1), 133–167 (2009)
C. Xue Macroscopic equations for bacterial chemotaxis: integration of detailed biochemistry of cell signaling. J. Math. Biol. 70, 1–44 (2015)
C. Yang, F. Filbet, Numerical simulations of kinetic models for chemotaxis. SIAM J. Sci. Comput. 36, B348 (2014)
S. Yasuda, Monte Carlo simulation for kinetic chemotaxis model: an application to the traveling population wave. J. Comput. Phys. 330, 1022–1042 (2017)
X. Zhu, G. Si, N. Deng, Q. Ouyang, T. Wu, Z. He, L. Jiang, C. Luo, Y. Tu, Frequency-dependent Escherichia coli chemotaxis behavior. Phys. Rev. Lett. 108, 128101 (2012)
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Perthame, B. (2019). Kinetic Equations and Cell Motion: An Introduction. In: Bianchi, A., Hillen, T., Lewis, M., Yi, Y. (eds) The Dynamics of Biological Systems. Mathematics of Planet Earth, vol 4. Springer, Cham. https://doi.org/10.1007/978-3-030-22583-4_9
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