Growth of RB Population in the Conversion Phase of Chlamydia Life Cycle

Frederic Y. M. Wan

Communications on Applied Mathematics and Computation ›› 2023, Vol. 6 ›› Issue (1) : 90-112. DOI: 10.1007/s42967-022-00226-w
Original Paper

Growth of RB Population in the Conversion Phase of Chlamydia Life Cycle

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Abstract

Upon infecting a host cell, the reticulate body (RB) form of the Chlamydia bacteria simply proliferates by binary fission for an extended period. Available data show only RB units in the infected cells 20 hours post infection (hpi), spanning nearly half way through the development cycle. With data collected every 4 hpi, conversion to the elementary body (EB) form begins abruptly at a rapid rate sometime around 24 hpi. By modeling proliferation and conversion as simple birth and death processes, it has been shown that the optimal strategy for maximizing the total (mean) EB population at host cell lysis time is a bang-bang control qualitatively replicating the observed conversion activities. However, the simple birth and death model for the RB proliferation and conversion to EB deviates in a significant way from the available data on the evolution of the RB population after the onset of RB-to-EB conversion. By working with a more refined model that takes into account a small size threshold eligibility requirement for conversion noted in the available data, we succeed in removing the deficiency of the previous models on the evolution of the RB population without affecting the optimal bang-bang conversion strategy.

Keywords

Chlamydia / Life cycle / Optimal control / Maximal infectious spread / Specie competitive survival

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Frederic Y. M. Wan. Growth of RB Population in the Conversion Phase of Chlamydia Life Cycle. Communications on Applied Mathematics and Computation, 2023, 6(1): 90‒112 https://doi.org/10.1007/s42967-022-00226-w

References

[1.]
Abdelrahman YM, Belland RJ. The chlamydial developmental cycle. FEMS Microbiol. Rev., 2005, 29: 949-959,
CrossRef Google scholar
[2.]
Batteiger BE, Tan M. Bennett JE, Dolin R, Blaser MJ. Chlamydia trachomatis (trachoma and urogenital infections). Mandell, Douglas, and Bennett’s Principles and Practice of Infectious Diseases, 2019 Philadelphia Elsevier Inc 2301-2319
[3.]
Belland RJ, Zhong G, Crane DD, Caldwell HD. Genomic transcriptional profiling of the developmental cycle of Chlamydia trachomatis. Proc. Natl. Acad. Sci. USA, 2003, 100: 8478-8483,
CrossRef Google scholar
[4.]
Bryson A, Ho YC. . Applied Optimal Control, 1969 Waltham Ginn and Company
[5.]
de la Maza LM, Peterson EM. Scanning electron microscopy of McCoy cells infected with Chlamydia trachomatis. Exp. Mol. Pathol., 1982, 36(2): 217-226,
CrossRef Google scholar
[6.]
Denk W, Horstmann H. Serial block-face scanning electron microscopy to reconstruct three-dimensional tissue nanostructure. PLoS Biol., 2004, 2,
CrossRef Google scholar
[7.]
Elwell C, Mirrashidi K, Engel J. Chlamydia cell biology and pathogenesis. Nat. Rev. Microbiol., 2016, 14(6): 385-400,
CrossRef Google scholar
[8.]
Enciso GA, Sütterlin C, Tan M, Wan FYM. Stochastic chlamydia dynamics and optimal spread. Bull. Math. Biol., 2021, 83: 24,
CrossRef Google scholar
[9.]
Hackstadt T, Fischer ER, Scidmore MA, Rockey DD, Heinzen RA. Origins and functions of the chlamydial inclusion. Trends Microbiol., 1997, 5: 288-293,
CrossRef Google scholar
[10.]
Hybiske K, Stephens RS. Mechanisms of host cell exit by the intracellular bacterium Chlamydia. Proc. Natl. Acad. Sci. USA, 2007, 104: 11430-11435,
CrossRef Google scholar
[11.]
Lee JK, Enciso GA, Boassa D, Chander CN, Lou TH, Pairawan SS, Guo MC, Wan FYM, Ellisman MH, Sütterlin C, Tan M. Replication-dependent size reduction precedes differentiation in Chlamydia trachomatis. Nat. Commun., 2018, 9: 45,
CrossRef Google scholar
[12.]
Leighton SB. SEM images of block faces, cut by a miniature microtome within the SEM: a technical note. Scanning Electron Microsc., 1981, 2: 73-76
[13.]
Moulder JW. Interaction of chlamydiae and host cells in vitro. Microbiol. Rev., 1991, 55: 143-190,
CrossRef Google scholar
[14.]
Newman L, Rowley J, Hoorn SV, Wijesooriya NS, Unemo M, Low N, Stevens G, Gottlieb S, Kiarie J, Temmerman M. Global estimates of the prevalence and incidence of four curable sexually transmitted infections in 2012 based on systematic review and global reporting. PLoS One, 2015, 10,
CrossRef Google scholar
[15.]
Pontryagin LS, Boltyanskii V, Gamkrelidze R, Mishchenko EF. . The Mathematical Theory of Optimal Control Processes, 1962 New York Interscience Publishers
[16.]
Shaw EI, Dooley CA, Fischer ER, Scidmore MA, Fields KA, Hackstadt T. Three temporal classes of gene expression during the Chlamydia trachomatis developmental cycle. Mol. Microbiol., 2000, 37: 913-925,
CrossRef Google scholar
[17.]
Taylor HR, Burton MJ, Haddad D, West S, Wright H. Trachoma. Lancet, 2014, 384: 2142-2152,
CrossRef Google scholar
[18.]
Wan FYM. . Introduction to the Calculus of Variations and Its Applications, 1995 New York Chapman and Hall
[19.]
Wan FYM. . Dynamical System Models in the Life Sciences, 2018 Singapore World Scientific
[20.]
Wan FYM. . Stochastic Models in the Life Sciences, 2019 Singapore World Scientific
[21.]
Wan FYM, Enciso GA. Optimal proliferation and differentiation of Chlamydia trachomatis. Stud. Appl. Math., 2017, 139(1): 129-178,
CrossRef Google scholar
[22.]
WHO: Trachoma: Fact Sheet. World Health Organization, Geneva (2017). http://www.who.int/mediacentre/factsheets/fs382/en/

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