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Overview of Mathematical Approaches Used to Model Bacterial Chemotaxis II: Bacterial Populations

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Abstract

We review the application of mathematical modeling to understanding the behavior of populations of chemotactic bacteria. The application of continuum mathematical models, in particular generalized Keller–Segel models, is discussed along with attempts to incorporate the microscale (individual) behavior on the macroscale, modeling the interaction between different species of bacteria, the interaction of bacteria with their environment, and methods used to obtain experimentally verified parameter values. We allude briefly to the role of modeling pattern formation in understanding collective behavior within bacterial populations. Various aspects of each model are discussed and areas for possible future research are postulated.

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References

  • Adler, J., 1966. Chemotaxis in bacteria. Science 153, 708–716.

    Google Scholar 

  • Adler, J., 1969. Chemoreceptors in bacteria. Science 166(3913), 1588–1597.

    Google Scholar 

  • Adler, J., Dahl, M., 1967. A method for measuring the motility of bacteria and for comparing random and non-random motility. J. Gen. Microbiol. 46(2), 161–173.

    Google Scholar 

  • Alt, W., 1980. Biased random walk models for chemotaxis and related diffusion approximations. J. Math. Biol. 9, 147–177.

    MATH  MathSciNet  Google Scholar 

  • Ben-Jacob, E., Schochet, O., Tenenbaum, A., Cohen, I., Czirok, A., Vicsek, T., 1994. Generic modelling of cooperative growth patterns in bacterial colonies. Nature 368, 46–49.

    Google Scholar 

  • Ben-Jacob, E., Cohen, I., Schochet, O., 1995. Complex bacterial patterns. Nature 373, 566–569.

    Google Scholar 

  • Berg, H., 1996. Symmetries in bacterial motility. Proc. Natl. Acad. Sci. 93, 14225–14228.

    Google Scholar 

  • Berg, H., Brown, D., 1972. Chemotaxis in Escherichia coli analyzed by three-dimensional tracking. Nature 239, 500–504.

    Google Scholar 

  • Berg, H., Turner, L., 1990. Chemotaxis of bacteria in glass capillary assays. Biophys. J. 58, 919–930.

    Google Scholar 

  • Berg, H., Turner, L., 1993. Torque generated by the flagellar motor of Escherichia coli. Biophys. J. 65, 2201–2216.

    Google Scholar 

  • Block, S., Segall, J., Berg, H., 1983. Adaptation kinetics in bacterial chemotaxis. J. Bacteriol. 154, 312–323.

    Google Scholar 

  • Boon, J.-P., Herpigny, B., 1986. Model for chemotactic bacterial bands. Bull. Math. Biol. 48, 1–19.

    MATH  Google Scholar 

  • Bray, D., Bourret, R., 1995. Computer analysis of the binding reactions leading to a transmembrane receptor-linked multiprotein complex involved in bacterial chemotaxis. Mol. Biol. Cell 6, 1367–1380.

    Google Scholar 

  • Bray, D., Bourret, R., Simon, M., 1993. Computer simulation of the phosphorylation cascade controlling bacterial chemotaxis. Mol. Biol. Cell 4, 469–482.

    Google Scholar 

  • Bray, D., Levin, M., Lipkow, K., 2007. The chemotactic behavior of computer-based surrogate bacteria. Curr. Biol. 17, 12–19.

    Google Scholar 

  • Brenner, M., Levitov, L., Budrene, E., 1998. Physical mechanisms for chemotactic pattern formation by bacteria. Biophys. J. 74(4), 1677–1693.

    Google Scholar 

  • Brosilow, B., Ford, R., Sarman, S., Cummings, P., 1996. Numerical solution of transport equations for bacterial chemotaxis: Effect of discretization of directional motion. SIAM J. Appl. Math. 56(6), 1639–1663.

    MATH  MathSciNet  Google Scholar 

  • Brown, D., Berg, H., 1974. Temporal stimulation of chemotaxis in Escherichia coli. Proc. Natl. Acad. Sci. 71(4), 1388–1392.

    Google Scholar 

  • Budrene, E., Berg, H., 1991. Complex patterns formed by motile cells of Escherichia coli. Nature 349, 630–633.

    Google Scholar 

  • Chen, K., Ford, R., Cummings, P., 1998a. The global turning probability density function for motile bacteria and its applications. J. Theor. Biol. 195, 139–155.

    Google Scholar 

  • Chen, K., Ford, R., Cummings, P., 1998b. Mathematical models for motile bacterial transport in cylindrical tubes. J. Theor. Biol. 195, 481–504.

    Google Scholar 

  • Chen, K., Ford, R., Cummings, P., 1998c. Perturbation expansion of Alt’s cell balance equations reduces to Segel’s one-dimensional equations for shallow chemoattactant gradient. SIAM J. Appl. Math. 59, 35–57.

    MathSciNet  Google Scholar 

  • Chen, K., Ford, R., Cummings, P., 1999. Spatial effect of tumbling frequences for motile bacteria on cell ball equations. Chem. Eng. Sci. 54, 593–617.

    Google Scholar 

  • Chen, K., Ford, R., Cummings, P., 2003. Cell balance equation for chemotactic bacteria with a biphasic tumbling frequency. J. Math. Biol. 47(6), 518–546.

    MATH  MathSciNet  Google Scholar 

  • Chiu, C., Hoppensteadt, F., 2001. Mathematical models and simulations of bacterial growth and chemotaxis in a diffusion gradient chamber. J. Math. Biol. 42, 120–144.

    MATH  MathSciNet  Google Scholar 

  • Clark, D., Grant, L., 2005. The bacterial chemotactic response reflects a compromise between transient and steady-state behaviour. Proc. Natl. Acad. Sci. 102(26), 9150–9155.

    Google Scholar 

  • Dahlquist, F., Elwell, R., Koshland, D., 1976. Studies of bacterial chemotaxis in defined concentration gradients. J. Supramol. Struct. 4, 329–342.

    Google Scholar 

  • Dahlquist, F., Lovely, P., Koshland, D., 1972. Quantitative analysis of bacterial migration in chemotaxis. Nat. New Biol. 236, 120–123.

    Google Scholar 

  • Davey, M., O’Toole, G., 2000. Microbial biofilms: from ecology to molecular genetics. Mol. Microbiol. 64(4), 847–867.

    Google Scholar 

  • de Gennes, P., 2004. Chemotaxis: the role of internal delays. Eur. Biophys. J. 33(8), 691–693.

    Google Scholar 

  • Dillon, R., Fauci, L., Gaver, D., 1995. A microscale model of bacterial swimming, chemotaxis and substrate transport. J. Theor. Biol. 177, 325–340.

    Google Scholar 

  • D’Orsogna, M., Suchard, M., Chou, T., 2003. Interplay of chemotaxis and chemokinesis mechanisms in bacterial dynamics. Phys. Rev. E 68, 1–10.

    Google Scholar 

  • Eisenbach, M., Lengeler, J., Varon, M., Gutnick, D., Meili, R., Firtel, R., Segall, J., Omann, G., Tamada, A., Murakami, F., 2004. Chemotaxis. Imperial College Press, London.

    Google Scholar 

  • Emerson, D., Worden, R., Breznak, J., 1994. A diffusion gradient chamber for studying microbial behavior and separating microorganism. Appl. Environ. Microbiol. 60(4), 1269–1278.

    Google Scholar 

  • Emonet, T., Macal, C., North, M., Wickersham, C., Cluzel, P., 2005. Agentcell: A digital single-cell assay for bacterial chemotaxis. Bioinformatics 21(11), 2714–2721.

    Google Scholar 

  • Engelmann, T., 1881a. Neue methode zur untersuchung der sauerstoffaussheidung pflanzlicher und thierischer organismen. Pflugers Arch. Gesamte Physiol. Menschen Tiere 25, 285–292.

    Google Scholar 

  • Engelmann, T., 1881b. Zur biologie der schizomyceten. Pflugers Arch. Gesamte Physiol. 26, 537.

    Google Scholar 

  • Erban, R., Othmer, H., 2004. From individual to collective behaviour in bacterial chemotaxis. SIAM J. Appl. Math. 65, 361–391.

    MATH  MathSciNet  Google Scholar 

  • Erban, R., Othmer, H., 2005. From signal transduction to spatial pattern formation in E. coli: A paradigm for multiscale modelling in biology. Multiscale Model. Simul. 3(2), 362–394.

    MATH  MathSciNet  Google Scholar 

  • Ford, R., Cummings, P., 1992. On the relationship between cell balance equations for chemotaxis cell populations. SIAM J. Appl. Math. 52(5), 1426–1441.

    MATH  MathSciNet  Google Scholar 

  • Ford, R., Lauffenburger, D., 1991a. Analysis of chemotactic bacterial distributions in population migration assays using a mathematical model applicable to steep or shallow or gradients. Bull. Math. Biol. 53, 721–749.

    MATH  Google Scholar 

  • Ford, R., Lauffenburger, D., 1991b. Measurement of bacterial random motility and chemotaxis coefficients I : Stopped-flow diffusion chamber assay. Biotech. Bioeng. 37, 647–660.

    Google Scholar 

  • Ford, R., Quinn, J., Philips, B., Lauffenburger, D., 1991. Measurement of bacterial random motility and chemotaxis coefficients II: Application of single cell-based mathematical model. Biotech. Bioeng. 37, 661–672.

    Google Scholar 

  • Frymier, P., Ford, R., Cummings, P., 1993. Cellular dynamics simulation of bacterial chemotaxis. Chem. Eng. Sci. 48(4), 687–699.

    Google Scholar 

  • Frymier, P., Ford, R., Cummings, P., 1994. Analysis of bacterial migration: I. Numerical solution of balance equation. AIChE J. 40(4), 704–715.

    Google Scholar 

  • Futrelle, R., Berg, H., 1972. Specification of gradients used for studies of chemotaxis. Nature 239, 517–518.

    Google Scholar 

  • Goto, T., Nakata, K., Baba, K., Nishimura, M., Magariyama, Y., 2005. A fluid-dynamic interpretation of the asymmetric motion of singly flagellated bacteria swimming close to a boundary. Biophys. J. 89(6), 3771–3779.

    Google Scholar 

  • Grimm, A., Harwood, C., 1997. Chemotaxis of Pseudomonas spp. to the polayaromatic hydrocarbon, napthalene. Appl. Environ. Microbiol. 63, 4111–4115.

    Google Scholar 

  • Grimson, M., Barker, G., 1994. Continuum model for the spatiotemporal growth of bacterial colonies. Phys. Rev. E 49(2), 1680–1684.

    Google Scholar 

  • Herpigny, B., Boon, J., Lavalle, R., 1984. Bacterial chemotaxis and band formation: Response to the simultaneous effects of two attractants. Unpublished experimental results.

  • Hillen, T., Othmer, H., 2000. The diffusion limit of transport equations derived from velocity-jump processes. SIAM J. Appl. Math. 61, 751–775.

    MATH  MathSciNet  Google Scholar 

  • Hillesdon, A., Pedley, T., Kessler, J., 1995. The development of concentration gradients in a suspension of chemotactic bacteria. Bull. Math. Biol. 57(2), 299–334.

    MATH  Google Scholar 

  • Hilpert, M., 2005. Lattice-Boltzman model for bacterial chemotaxis. J. Math. Biol. 51(3), 302–332.

    MATH  MathSciNet  Google Scholar 

  • Holz, M., Chen, S., 1979. Spatio-temporal structure of migrating chemotactic band of Escherichia coli. I. Travelling band profile. Biophys. J. 26, 243–261.

    Google Scholar 

  • Hornberger, G., Mills, A., Herman, J., 1992. Bacterial transport in porous media: Evaluation of a model using laboratory observations. Water Resour. Res. 28(3), 915–938.

    Google Scholar 

  • Horstmann, D., 2003a. From 1970 until present: The Keller–Segel model in chemotaxis and its consequences I. Jahresber. DMV 105(3), 103–165.

    MATH  MathSciNet  Google Scholar 

  • Horstmann, D., 2003b. From 1970 until present: the Keller–Segel model in chemotaxis and its consequences II. Jahresber. DMV 106(2), 51–69.

    MathSciNet  Google Scholar 

  • Keller, E., Odell, G., 1975. Necessary and sufficient conditions for chemotactic bands. Math. Biosci. 27, 309–317.

    MATH  MathSciNet  Google Scholar 

  • Keller, E., Segel, L., 1970. Initiation of slime mold aggregation viewed as an instability. J. Theor. Biol. 26, 399–415.

    Google Scholar 

  • Keller, E., Segel, L., 1971a. Model for chemotaxis. J. Theor. Biol. 30(2), 225–234.

    Google Scholar 

  • Keller, E., Segel, L., 1971b. Travelling bands of chemotactic bacteria: A theoretical analysis. J. Theor. Biol. 30(2), 235–248.

    Google Scholar 

  • Kelly, F., Dapsis, K., Lauffenburger, D., 1988. Effect of bacterial chemotaxis on dynamics of microbial competition. Microb. Ecol. 16(2), 115–131.

    Google Scholar 

  • Kennedy, C., Aris, R., 1980. Travelling waves in a simple population model involving growth and death. B. Math. Biol. 42, 397–429.

    MATH  MathSciNet  Google Scholar 

  • Korobkova, E., Emonet, T., Vilar, J., Shimizu, T., Cluzel, P., 2004. From molecular noise to behavioural variability in a single bacterium. Nature 428, 574–578.

    Google Scholar 

  • Kreft, J., Booth, G., Wimpenny, J., 1998. Bacsim, a simulator for individual-based modelling of bacterial colony growth. Microbiology 144, 3275–3287.

    Google Scholar 

  • Lapidus, R., Schiller, R., 1974. A mathematical model for bacterial chemotaxis. Biophys. J. 14, 825–834.

    Article  Google Scholar 

  • Lapidus, R., Schiller, R., 1975. Bacterial chemotaxis in a fixed attractant gradient. J. Theor. Biol. 53, 215.

    Google Scholar 

  • Lapidus, R., Schiller, R., 1976. Model for the chemotactic response of a bacterial population. Biophys. J. 16, 779–789.

    Google Scholar 

  • Lapidus, R., Schiller, R., 1978. A model for travelling bands of chemotactic bacteria. J. Theor. Biol. 22, 1–13.

    Google Scholar 

  • Lauffenburger, D., Calcagno, B., 1983. Competition between two microbial populations in a nonmixed environment: Effect of cell random motility. Biotech. Bioeng. 25, 2103–2125.

    Google Scholar 

  • Lauffenburger, D., Aris, R., Keller, K., 1981. Effects of random motility on growth of bacterial populations. Microb. Ecol. 7(3), 207–227.

    Google Scholar 

  • Lauffenburger, D., Aris, R., Keller, K., 1982. Effects of cell motility and chemotaxis on microbial populations growth. Biophys. J. 40, 209–219.

    Google Scholar 

  • Lauffenburger, D., Kennedy, C., Aris, R., 1984. Traveling bands of chemotactic bacteria in the context of population growth. B. Math. Biol. 46(1), 19–40.

    MATH  Google Scholar 

  • Lauffenburger, D., Rivero, M., Kelly, F., Ford, R., DiRienzo, J., 1987. Bacterial chemotaxis. cell flux model, parameter measurement, population dynamics, and genetic manipulation. Ann. NY Acad. Sci. 506, 281–295.

    Google Scholar 

  • Lauga, E., DiLuzio, W., Whitesides, G., Stone, H., 2006. Swimming in circles: motion of bacteria near solid boundaries. Biophys. J. 90(2), 400–412.

    Google Scholar 

  • Lewus, P., Ford, R., 2001. Quantification of random motility and chemotaxis bacterial transport coefficients using individual-cell and population-scale assays. Biotech. Bioeng. 75(3), 292–304.

    Google Scholar 

  • Lighthill, J., 1975. Flagellar hydrodynamics: The John von Neumann lecture 1975. SIAM Rev. 18(2), 161–230.

    MathSciNet  Google Scholar 

  • Liu, Z., Papadopoulos, K., 1995. Unidirectional motility of Escherichia coli in restrictive capillaries. Appl. Environ. Microbiol. 61(10), 3567–3572.

    Google Scholar 

  • Lovely, P., Dahlquist, F., 1975. Statistical measures of bacterial motility and chemotaxis. J. Theor. Biol. 50, 477–496.

    Google Scholar 

  • Macnab, R., Koshland, D., 1972. The gradient-sensing mechanism in bacterial chemotaxis. Proc. Natl. Acad. Sci. 69(9), 2509–2512.

    Google Scholar 

  • Maini, P., Myerscough, M., Winters, K., Murray, J., 1991. Bifurcating spatially heterogenous solutions in a chemotaxis model for biological pattern formation. Bull. Math. Biol. 53(5), 701–719.

    MATH  Google Scholar 

  • Marx, R., Aitken, M., 1999. Quantification of chemotaxis to naphthalene by Pseudomonas putida G7. Appl. Environ. Microbiol. 65(7), 2847–2852.

    Google Scholar 

  • Marx, R., Aitken, M., 2000. A material balance approach for modelling bacterial chemotaxis to a consumable substrate in the capillary assay. Biotech. Bioeng. 63, 308–315.

    Google Scholar 

  • Mazzag, B., Zhulin, I., Mogilner, A., 2003. Model of bacterial band formation in aerotaxis. Biophys. J. 85, 3558–3574.

    Google Scholar 

  • Mesibov, R., Ordal, G., Adler, J., 1973. The range of attractant concentrations for bacterial chemotaxis and the threshold size of response over this range. J. Gen. Phys. 62, 203–223.

    Google Scholar 

  • Morton-Firth, C., Shimizu, T., Bray, D., 1999. A free-energy based stochastic simulation of the Tar receptor complex. J. Mol. Biol. 286, 1059–1074.

    Google Scholar 

  • Murray, J., 1993. Mathematical Biology, 2nd edn. Springer, New York.

    MATH  Google Scholar 

  • Newman, T., Grima, R., 2004. Many-body theory of chemotactic cell-cell interactions. Phys. Rev. E 70, 051916.

    Google Scholar 

  • Nossal, R., 1972. Boundary movement of chemotactic bacterial populations. Math. Biosci. 13, 397–406.

    MATH  Google Scholar 

  • Nossal, R., Weis, G., 1973. Analysis of a densitometry assay for bacterial chemotaxis. J. Theor. Biol. 41(1), 143–147.

    Google Scholar 

  • Novick-Cohen, A., Segel, L., 1984. A gradually slowly travelling band of chemotactic bacteria. J. Math. Biol. 19, 125–132.

    MATH  Google Scholar 

  • Ockendon, J., Howison, S., Lacey, A., Movchan, A., 1999. Applied Partial Differential Equations. Oxford University Press, Oxford.

    MATH  Google Scholar 

  • Odell, G., Keller, E., 1976. Travelling bands of chemotactic bacteria revisited. J. Theor. Biol. 56, 243–247.

    Google Scholar 

  • Othmer, H., Dunbar, S., Alt, W., 1988. Models of dispersal in biological systems. J. Math. Biol. 26, 263–298.

    MATH  MathSciNet  Google Scholar 

  • Patlak, C., 1953. Random walk with persistence and external bias. Bull. Math. Biophys. 15, 311–338.

    MathSciNet  Google Scholar 

  • Pedit, J., Marx, R., Miller, C., Aitken, M., 2002. Quantitative analysis of experiments on bacterial chemotaxis to naphthalene. Biotech. Bioeng. 78(6), 626–634.

    Google Scholar 

  • Pedley, T., Kessler, J., 1992. Hydrodynamic phenomena in suspensions of swimming microorganisms. Annu. Rev. Fluid Mech. 24, 313–358.

    MathSciNet  Google Scholar 

  • Pfeffer, W., 1888. Uber chemotaktische bewegungen von bacterien, flagellaten and volvocineen. Untersuch. Bot. Inst. Tübingen 2, 582.

    Google Scholar 

  • Ramia, M., Tullock, D., Phan-Thien, N., 1993. The role of hydrodynamic interaction in the locomotion of microorganisms. Biophys. J. 65, 755–778.

    Google Scholar 

  • Reynolds, P., Sharma, P., Jenneman, G., McInerney, M., 1989. Mechanisms of microbial movement in subsurface materials. Appl. Environ. Microbiol. 55(9), 2280–2286.

    Google Scholar 

  • Rivero, M., Tranquillo, R., Buettner, H., Lauffenburger, D., 1989. Transport models for chemotactic cell populations based on individual cell behaviour. Chem. Eng. Sci. 44(12), 2881–2897.

    Google Scholar 

  • Rivero-Hudec, M., Lauffenburger, D., 1986. Quantification of bacterial chemotaxis by measurement of model parameters using the capillary assay. Biotech. Bioeng. 28, 1178–1190.

    Google Scholar 

  • Romagnoli, S., 2002. Role of redoc sensing in controlling Rhodobacter sphaeroides swimming behaviour. PhD thesis, Department of Biochemistry, University of Oxford.

  • Rosen, G., 1973. Fundamental theoretical aspects of bacterial chemotaxis. J. Theor. Biol. 41, 201–208.

    Google Scholar 

  • Rosen, G., 1974. On the propagation theory for bands of chemotactic bacteria. Math. Biosci. 20, 185–189.

    MATH  Google Scholar 

  • Rosen, G., 1975. Analytical solution to the initial value problem for traveling bands of chemotactic bacteria. J. Theor. Biol. 49, 311–321.

    Google Scholar 

  • Rosen, G., 1976. Existence and nature of band solutions to generic chemotactic transport equations. J. Theor. Biol. 59, 243–246.

    Google Scholar 

  • Rosen, G., 1983. Theoretical significance of the condition δ=2μ in bacterial chemotaxis. Bull. Math. Biol. 45(2), 151–153.

    MATH  Google Scholar 

  • Rosen, G., Baloga, S., 1975. On the stability of steadily propagating rings of chemotactic bacteria. Math. Biosci. 24, 273–279.

    MATH  MathSciNet  Google Scholar 

  • Rosen, G., Baloga, S., 1976. On the structure of steadily propagating rings of chemotactic bacteria. J. Mechanochem. Cell Motility 3, 225–228.

    Google Scholar 

  • Schnitzer, M., 1993. Theory of continuum random walks and application to chemotaxis. Phys. Rev. E 48(4), 2553–2568.

    MathSciNet  Google Scholar 

  • Schnitzer, M., Block, S., Berg, H., Purcell, E., 1990. Strategies for chemotaxis. Symp. Soc. Gen. Microbiol. 46, 15–34.

    Google Scholar 

  • Scribner, T., Segel, L., Rogers, E., 1974. A numerical study of the formation and propagation of travelling bands of chemotactic bacteria. J. Theor. Biol. 46, 189–219.

    Google Scholar 

  • Segel, L., 1976. Incorporation of receptor kinetics into a model for bacterial chemotaxis. J. Theor. Biol. 57, 23–42.

    MathSciNet  Google Scholar 

  • Segel, L., 1977. A theoretical study of receptor mechanisms in bacterial chemotaxis. SIAM J. Appl. Math. 32(3), 653–665.

    MATH  MathSciNet  Google Scholar 

  • Segel, L., Jackson, L., 1973. Theoretical analysis of chemotactic movements in bacteria. J. Mechanochem. Cell Motility 2, 25–34.

    Google Scholar 

  • Setayeshgar, S., Gear, C., Othmer, H., Kevrekidis, I., 2005. Application of coarse integration to bacterial chemotaxis. Multiscale Model. Simul. 4(1), 307–327.

    MATH  MathSciNet  Google Scholar 

  • Stroock, D., 1974. Some stochastic processes which arise from a model of the motion of a bacterium. Z. Wahrsch. Verw. Geb. 28, 305–315.

    MATH  Google Scholar 

  • Tindall, M., Porter, S., Maini, P., Gaglia, G., Armitage, J., 2007. Overview of mathematical approaches used to model bacterial chemotaxis I: The single cell. Bull. Math. Biol., submitted.

  • Wadhams, G., Armitage, J., 2004. Making sense of it all: bacterial chemotaxis. Nat. Rev. Mol. Cell Biol. 5(12), 1024–1037.

    Google Scholar 

  • Widman, M., Emerson, D., Chiu, C., Worden, R., 1997. Modelling microbial chemotaxis in a diffusion gradient chamber. Biotech. Bioeng. 55(1), 191–205.

    Google Scholar 

  • Zhu, M., Murray, J., 1995. Parameter domains for generating spatial pattern: A comparison of reaction-diffusion and cell-chemotaxis models. Int. J. Bifurc. Chaos 5(6), 1503–1524.

    MATH  MathSciNet  Google Scholar 

  • Zhulin, I., Bespalov, V., Johnson, M., Taylor, B., 1996. Oxygen taxis and proton motive force in Azospirillum brasilense. J. Bacteriol. 178, 5199–5204.

    Google Scholar 

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Tindall, M.J., Maini, P.K., Porter, S.L. et al. Overview of Mathematical Approaches Used to Model Bacterial Chemotaxis II: Bacterial Populations. Bull. Math. Biol. 70, 1570–1607 (2008). https://doi.org/10.1007/s11538-008-9322-5

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