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Epithelial stratification shapes infection dynamics.

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Title: Epithelial stratification shapes infection dynamics.
Authors: Murall, Carmen Lía, Jackson, Robert, Zehbe, Ingeborg, Boulle, Nathalie, Segondy, Michel, Alizon, Samuel
Source: PLoS Computational Biology; 1/23/2019, Vol. 15 Issue 1, p1-25, 25p, 2 Diagrams, 3 Charts, 3 Graphs
Subject Terms: EPITHELIAL cells, CELL culture, CHLAMYDIA trachomatis, PAPILLOMAVIRUSES, COMPUTER simulation, PATHOGENIC microorganisms, SEXUALLY transmitted diseases
Abstract: Infections of stratified epithelia contribute to a large group of common diseases, such as dermatological conditions and sexually transmitted diseases. To investigate how epithelial structure affects infection dynamics, we develop a general ecology-inspired model for stratified epithelia. Our model allows us to simulate infections, explore new hypotheses and estimate parameters that are difficult to measure with tissue cell cultures. We focus on two contrasting pathogens: Chlamydia trachomatis and Human papillomaviruses. Using cervicovaginal parameter estimates, we find that key infection symptoms can be explained by differential interactions with the layers, while clearance and pathogen burden appear to be bottom-up processes. Cell protective responses to infections (e.g. mucus trapping) generally lowered pathogen load but there were specific effects based on infection strategies. Our modeling approach opens new perspectives for 3D tissue culture experimental systems of infections and, more generally, for developing and testing hypotheses related to infections of stratified epithelia. [ABSTRACT FROM AUTHOR]
Copyright of PLoS Computational Biology is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Complementary Index
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  Data: Epithelial stratification shapes infection dynamics.
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  Data: <searchLink fieldCode="AR" term="%22Murall%2C+Carmen+Lía%22">Murall, Carmen Lía</searchLink><br /><searchLink fieldCode="AR" term="%22Jackson%2C+Robert%22">Jackson, Robert</searchLink><br /><searchLink fieldCode="AR" term="%22Zehbe%2C+Ingeborg%22">Zehbe, Ingeborg</searchLink><br /><searchLink fieldCode="AR" term="%22Boulle%2C+Nathalie%22">Boulle, Nathalie</searchLink><br /><searchLink fieldCode="AR" term="%22Segondy%2C+Michel%22">Segondy, Michel</searchLink><br /><searchLink fieldCode="AR" term="%22Alizon%2C+Samuel%22">Alizon, Samuel</searchLink>
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  Data: PLoS Computational Biology; 1/23/2019, Vol. 15 Issue 1, p1-25, 25p, 2 Diagrams, 3 Charts, 3 Graphs
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  Data: <searchLink fieldCode="DE" term="%22EPITHELIAL+cells%22">EPITHELIAL cells</searchLink><br /><searchLink fieldCode="DE" term="%22CELL+culture%22">CELL culture</searchLink><br /><searchLink fieldCode="DE" term="%22CHLAMYDIA+trachomatis%22">CHLAMYDIA trachomatis</searchLink><br /><searchLink fieldCode="DE" term="%22PAPILLOMAVIRUSES%22">PAPILLOMAVIRUSES</searchLink><br /><searchLink fieldCode="DE" term="%22COMPUTER+simulation%22">COMPUTER simulation</searchLink><br /><searchLink fieldCode="DE" term="%22PATHOGENIC+microorganisms%22">PATHOGENIC microorganisms</searchLink><br /><searchLink fieldCode="DE" term="%22SEXUALLY+transmitted+diseases%22">SEXUALLY transmitted diseases</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Infections of stratified epithelia contribute to a large group of common diseases, such as dermatological conditions and sexually transmitted diseases. To investigate how epithelial structure affects infection dynamics, we develop a general ecology-inspired model for stratified epithelia. Our model allows us to simulate infections, explore new hypotheses and estimate parameters that are difficult to measure with tissue cell cultures. We focus on two contrasting pathogens: Chlamydia trachomatis and Human papillomaviruses. Using cervicovaginal parameter estimates, we find that key infection symptoms can be explained by differential interactions with the layers, while clearance and pathogen burden appear to be bottom-up processes. Cell protective responses to infections (e.g. mucus trapping) generally lowered pathogen load but there were specific effects based on infection strategies. Our modeling approach opens new perspectives for 3D tissue culture experimental systems of infections and, more generally, for developing and testing hypotheses related to infections of stratified epithelia. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of PLoS Computational Biology is the property of Public Library of Science and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1371/journal.pcbi.1006646
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        Text: English
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      – SubjectFull: EPITHELIAL cells
        Type: general
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              M: 01
              Text: 1/23/2019
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