Abstract
In this paper, we study how chemotaxis affects the immune system by proposing a minimal mathematical model, a reaction–diffusion–advection system, describing a cross-talk between antigens and immune cells via chemokines. We analyze the stability and instability arising in our chemotaxis model and find their conditions for different chemotactic strengths by using energy estimates, spectral analysis, and bootstrap argument. Numerical simulations are also performed to the model, by using the finite volume method in order to deal with the chemotaxis term, and the fractional step methods are used to solve the whole system. From the analytical and numerical results for our model, we explain not only the effective attraction of immune cells toward the site of infection but also hypersensitivity when chemotactic strength is greater than some threshold.
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References
Akbari O, Freeman GJ, Meyer EH, Greenfield EA, Chang TT, Sharpe AH, Berry G, DeKruyff RH, Umetsu DT (2002) Antigen-specific regulatory T cells develop via the ICOS–ICOS-ligand pathway and inhibit allergen-induced airway hyperreactivity. Nat Med 8(9):1024–1032. doi:10.1038/nm745
Biler P (1999) Global solutions to some parabolic-elliptic systems of chemotaxis. Adv Math Sci Appl 9:347–359
Boyden S (1962) The chemotactic effect of mixtures of antibody and antigen on polymorphonuclear leucocytes. J Exp Med 115(3):453–466. doi:10.1084/jem.115.3.453
Callard RE, Yates AJ (2005) Immunology and mathematics: crossing the divide. Immunology 115(1):21–33. doi:10.1111/j.1365-2567.2005.02142.x
Campbell DJ, Debes GF, Johnston B, Wilson E, Butcher EC (2003) Targeting T cell responses by selective chemokine receptor expression. Semin Immunol 15(5):277–286. doi:10.1016/j.smim.2003.08.005
Carneiro J, Stewart J, Coutinho A, Coutinho G (1995) The ontogeny of class-regulation of CD4\(^+\) T lymphocyte populations. Int Immunol 7(8):1265–1277. doi:10.1093/intimm/7.8.1265
Chaplain MAJ, Stuart AM (1993) A model mechanism for the chemotactic response of endothelial cells to tumour angiogenesis factor. Math Med Biol 10(3):149–168. doi:10.1093/imammb/10.3.149
Charnick SB, Fisher ES, Lauffenburger DA (1991) Computer simulations of cell-target encounter including biased cell motion toward targets: single and multiple cell-target simulations in two dimensions. Bull Math Biol 53(4):591–621. doi:10.1016/S0092-8240(05)80157-0
Charo IF, Ransohoff RM (2006) The many roles of chemokines and chemokine receptors in inflammation. N Engl J Med 354(6):610–621. doi:10.1056/NEJMra052723
Devreotes P, Janetopoulos C (2003) Eukaryotic chemotaxis: distinctions between directional sensing and polarization. J Biol Chem 278(23):20445–20448
Evans LC (2010) Partial differential equations. American Mathematical Society, Providence
Fishman MA, Perelson AS (1993) Modeling T cell-antigen presenting cell interactions. J Theor Biol 160(3):311–342. doi:10.1006/jtbi.1993.1021
Fishman MA, Perelson AS (1994) Th1/Th2 cross regulation. J Theor Biol 170(1):25–56. doi:10.1006/jtbi.1994.1166
Fishman MA, Perelson AS (1999) Th1/Th2 differentiation and cross-regulation. Bull Math Biol 61(3):403–436. doi:10.1006/bulm.1998.0074
Gereda JE, Leung DYM, Thatayatikom A, Streib JE, Price MR, Klinnert MD, Liu AH (2000) Relation between house-dust endotoxin exposure, type 1 T-cell development, and allergen sensitisation in infants at high risk of asthma. Lancet 355(9216):610–621. doi:10.1016/S0140-6736(00)02239-X
Groß F, Metznerb G, Behn U (2011) Mathematical modelling of allergy and specific immunotherapy: Th1–Th2–Treg interactions. J Theor Biol 269(1):70–78. doi:10.1016/j.jtbi.2010.10.013
Guo Y, Strauss WA (1995) Instability of periodic BGK equilibria. Commun Pure Appl Anal 48(8):861–894. doi:10.1002/cpa.3160480803
Guo Y, Hwang HJ (2010) Pattern formation (I): the Keller–Segel model. J Differ Equ 249(7):1519–1530. doi:10.1016/j.jde.2010.07.025
Hillen T, Painter K (2001) Global existence for a parabolic chemotaxis model with prevention of overcrowding. Adv Appl Math 26(4):280–301. doi:10.1006/aama.2001.0721
Hillen T, Painter KJ (2009) A user’s guide to PDE models for chemotaxis. J Math Biol 58(1–2):183–217. doi:10.1007/s00285-008-0201-3
Hillen T, Painter K, Schmeiser C (2007) Global existence for chemotaxis with finite sampling radius. Discrete Contin Dyn Syst Ser B 7(1):125. doi:10.3934/dcdsb.2007.7.125
Horstmann D (2001) Lyapunov functions and \(l^p\)-estimates for a class of reaction-diffusion systems. Colloq Math 87(1):113–127
Horstmann D, Winkler M (2005) Boundedness vs. blow-up in a chemotaxis system. J Differ Equ 215(1):52–107. doi:10.1016/j.jde.2004.10.022
Horstmann D et al (2003) From 1970 until present: The Keller-Segel model in chemotaxis and its consequences I. Jahresber Deutsch Math-Verein 105(3):103–165
Keller EF, Segel LA (1970) Initiation of slime mold aggregation viewed as an instability. J Theor Biol 26(3):399–415. doi:10.1016/0022-5193(70)90092-5
Kim Y, Lee S, Kim YS, Lawler S, Gho YS, Kim YK, Hwang HJ (2013) Regulation of Th1/Th2 cells in asthma development: a mathematical model. Math Biosci Eng 10(4):1095–1133
Kowalczyk R (2005) Preventing blow-up in a chemotaxis model. J Math Anal Appl 305(2):566–588. doi:10.1016/j.jmaa.2004.12.009
Lee S, Hwang HJ, Kim Y (2014) Modeling the role of \({\text{ TGF }\text{- }{\upbeta }}\) in regulation of the Th17 phenotype in the LPS-driven immune system. Bull Math Biol 76(5):1045–1080. doi:10.1007/s11538-014-9946-6
LeVeque RJ (1997) Wave propagation algorithms for multidimensional hyperbolic systems. J Comput Phys 131(2):327–353. doi:10.1006/jcph.1996.5603
LeVeque RJ (2002) Finite volume methods for hyperbolic problems. Cambridge texts in applied mathematics. Cambridge University, Cambridge
LeVeque RJ (2002b) Finite-volume methods for non-linear elasticity in heterogeneous media. Int J Numer Methods Fluids 40(1–2):93–104. doi:10.1002/fld.309
Nagai T (1997) Global existence of solutions to a parabolic system for chemotaxis in two space dimensions. Pergamon 30:5381–5388. doi:10.1016/S0362-546X(97)00395-7
Pachpatte BG, Ames WF (1997) Inequalities for differential and integral equations. Mathematics in science and engineering, vol 197. Academic press, London
Pigozzo AB, Macedo GC, dos Santos RW, Lobosco M (2013) On the computational modeling of the innate immune system. BMC Bioinform 14(6):1–20. doi:10.1186/1471-2105-14-S6-S7
Segel LA, Goldbeter A, Devreotes PN, Knox BE (1986) A mechanism for exact sensory adaptation based on receptor modification. J Theor Biol 120(2):151–179. doi:10.1016/S0022-5193(86)80171-0
Sherratt JA (1994) Chemotaxis and chemokinesis in eukaryotic cells: the Keller–Segel equations as an approximation to a detailed model. Bull Math Biol 56(1):129–146. doi:10.1016/S0092-8240(05)80208-3
Snyderman R, Gewurz H, Mergenhagen SE (1968) Interactions of the complement system with endotoxic lipopolysaccharide. Generation of a factor chemotactic for polymorphonuclear leukocytes. J Exp Med 128(2):259–275. doi:10.1084/jem.128.2.259
Stein JV, Nombela-Arrieta C (2005) Chemokine control of lymphocyte trafficking: a general overview. Immunology 116(1):1–12. doi:10.1111/j.1365-2567.2005.02183.x
Su B, Zhou W, Dorman KS, Jones DE (2009) Mathematical modelling of immune response in tissues. Comput Math Methods Med 10(1):9–38. doi:10.1080/17486700801982713
Tranquillo RT, Zigmond SH, Lauffenburger DA (1988) Measurement of the chemotaxis coefficient for human neutrophils in the under-agarose migration assay. Cell Motil Cytoskelet 11(1):1–15. doi:10.1002/cm.970110102
Tyson R, Stern LG, LeVeque RJ (2000) Fractional step methods applied to a chemotaxis model. J Math Biol 41(5):455–475. doi:10.1007/s002850000038
Woodward DE, Tyson R, Myerscough MR, Murray JD, Budrene EO, Berg HC (1995) Spatio-temporal patterns generated by salmonella typhimurium. Biophys J 68(5):2181–2189. doi:10.1016/S0006-3495(95)80400-5
Wrzosek D (2004) Global attractor for a chemotaxis model with prevention of overcrowding. Nonlinear Anal Theory Methods Appl 59(8):1293–1310. doi:10.1016/j.na.2004.08.015
Wrzosek D (2006) Long-time behaviour of solutions to a chemotaxis model with volume-filling effect. Proc R Soc Edinb Math 136(2):431–444. doi:10.1017/S0308210500004649
Xiang T (2015) Boundedness and global existence in the higher-dimensional parabolic–parabolic chemotaxis system with/without growth source. J Differ Equ 258(12):4275–4323. doi:10.1016/j.jde.2015.01.032
Yates A, Bergmann C, Van Hemmen JL, Stark J, Callard R (2000) Cytokine-modulated regulation of helper T cell populations. J Theor Biol 206(4):539–560. doi:10.1006/jtbi.2000.2147
Zhang Q, Li Y (2015) Stabilization and convergence rate in a chemotaxis system with consumption of chemoattractant. J Math Phys 56(081):506. doi:10.1063/1.4929658
Zhelev DV, Alteraifi AM, Chodniewicz D (2004) Controlled pseudopod extension of human neutrophils stimulated with different chemoattractants. Biophys J 87(1):688–695. doi:10.1529/biophysj.103.036699
Zheng P, Mu C, Hu X, Tian Y (2015) Boundedness of solutions in a chemotaxis system with nonlinear sensitivity and logistic source. J Math Anal Appl 424(1):509–522. doi:10.1016/j.jmaa.2014.11.031
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Hyung Ju Hwang was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) (2015R1A2A2A0100251).
Appendix
Appendix
In this appendix, we introduce mathematical notations used in our paper and prove the local-in-time existence of the full system (11)–(14). Let \(\varOmega \subset \mathbb {R}^{d}\) be a domain with smooth boundary. The Lebesgue spaces and the Sobolev spaces on \(\varOmega \) are defined as
where
and \(0 \le n \in \mathbb {Z}\).
To prove the local well-posedness of (11)–(14), we need the next two lemmas. The first lemma is easily proved by using the Sobolev embedding theorem. For details, see Section 5 in Evans (2010).
Lemma 5
Let \(\varOmega \subset \mathbb {R}^{d}\) be a bounded domain with smooth boundary and \(u, v \in H^{n}(\varOmega )\) for , then \(uv\in H^{n}(\varOmega )\) and
for some constant \(K_{1}\) depending only on n and \(\varOmega \).
The next lemma concerns the existence and uniqueness of a linear parabolic equation. We can easily prove the lemma by using the Galerkin approximation and we skip the proof.
Lemma 6
Let \(\varOmega \subset \mathbb {R}^{d}\) (\(d = 1, 2, 3\)) be a bounded domain with smooth boundary. For \(f \in L^{2}(0, T, H^{n - 1}(\varOmega ))\), and \(u_{0}\in H^{n}(\varOmega )\), there exists a unique \(u \in X_{T}^{n}\) satisfying
where \(\mu >0\) is constant. Moreover, there exists \(K_{2} = K_{2}(\mu , \varOmega ) > 0\) such that
Using the previous two lemmas, we can show the local existence of a solution for Eqs. (1)–(4).
Lemma 7
(Local existence) Let \(n > d / 2\) and \(\varOmega \subset \mathbb {R}^{d}\) (\(d = 1, 2, 3\)) be a bounded domain with smooth boundary. If \((A_{0}, C_{0}, M_{0}) \in [H^{n}(\varOmega )]^{3}\) then there is \(T = T(A_{0}, C_{0}, M_{0}) > 0\) such that there exists a solution \((A, C, M) \in (X_{T}^{n})^{3}\) of Eqs. (1)–(4) where
with norm \(||{\cdot }||_{X_{T}^{n}}^{2} = \sup _{0 \le t < T} ||{\cdot }||_{H^{n}}^{2} + \int _{0}^{T} ||{\cdot }||_{H^{n + 1}}^{2} \;\mathrm {d}t\). Moreover, in \(0\le t \le T\),
Proof
Take \(\phi \in X_{T}^{n}\) with \(\phi (0, x) = M_{0}(x)\). Let \(A = A(\phi )\) denote a corresponding solution for
For this A, let \(C = C(A(\phi ))\) be a corresponding solution for
Finally for this C, let \(M = M(C(A(\phi )))\) be a corresponding solution for
Then by the linear parabolic theory, the unique existence of A, C, and M follows. Applying Lemma 6, we can deduce
The Gronwall inequality (see Section 1.2 in Pachpatte and Ames (1997)) yields
Putting it into (40), we get \(A\in X_{T}^{n}\). For C,
We also get \(C \in X_{T}^{n}\). For M,
By the Gronwall inequality,
Putting (42) into (41), we get \(M\in X_{T}^{n}\). Then we can define a mapping \(Q_{T}:X_{T}^{n} \rightarrow X_{T}^{n}\) with \(Q_{T}(\phi ) = M\). Let \((X_{T}^{n})_{R}=\{\phi \in X_{T}^{n}:{||{\phi }||_{X_{T}^{n}}<R}\}\). Choose \(R = 2||{M_{0}}||_{H^{m}}\). We will prove that \(Q_{T}\) is a contraction mapping in \((X_{T}^{n})_{R}\) for sufficiently small T. It is obvious that if we take a sufficiently small T, \(Q_{T}\) maps from \((X_{T}^{n})_{R}\) to itself by above a priori estimate (42). To show \(Q_{T}\) is a contraction in \(X_{T}^{n}\), take \(\phi _{1},\phi _{2}\in X_{T}^{n}\), and let \(M_{1} = Q_{T}(\phi _{1})\) and \(M_{2} = Q_{T}(\phi _{2})\). Then we can also get the corresponding \(A_{1}\), \(A_{2}\), \(C_{1}\), and \(C_{2}\). Consequently, we have
where \({\widetilde{\phi }} = \phi _{1} - \phi _{2}\), \({\widetilde{A}} = A_{1} - A_{2}\), \({\widetilde{C}} = C_{1}-C_{2}\), and \({\widetilde{M}} = M_{1} - M_{2}\). By using Lemma 6, we obtain the following estimate for \({\widetilde{A}}\):
The Gronwall inequality yields
with
Then we can compute
with
We can also derive the following estimate for \({\widetilde{C}}\)
with
Finally, we get an estimate for \({\widetilde{M}}\):
with
By using the Gronwall inequality,
with
Hence
with
Therefore, we can apply the contraction mapping theorem which is stated in Section 9 in Evans (2010), and we can conclude that there is the unique fixed point M of \(Q_{T}\) for sufficiently small T. \(\square \)
Remark 2
By Lemma 7, the existence and uniqueness of (a, c, m) which is a solution of (11)–(15) is also guaranteed. Moreover, it is easy to show that for sufficiently small time \(T > 0\),
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Lee, S., Kim, Sw., Oh, Y. et al. Mathematical modeling and its analysis for instability of the immune system induced by chemotaxis. J. Math. Biol. 75, 1101–1131 (2017). https://doi.org/10.1007/s00285-017-1108-7
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DOI: https://doi.org/10.1007/s00285-017-1108-7