Probing the potential of mucus permeability to signify preterm birth risk
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s41598-017-08057-z.pdf
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Checksum (MD5)
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Author(s)
Conroy, K.
Pagidas, K.
Snegovskikh, V.
House, M.
Smith-Dupont, K. B.
Wagner, Caroline E
Witten, Jacob Julian Seid
Rudoltz, Hannah R.
Ribbeck, Katharina
Date Issued
September 2017
Journal
Scientific Reports
Publisher
Nature Publishing Group
Citation
Smith-Dupont, K. B. et al. “Probing the Potential of Mucus Permeability to Signify Preterm Birth Risk.” Scientific Reports 7, 1 (September 2017) © 2017 The Author(s)
Version
Final published version
Abstract
Preterm birth is the leading cause of neonatal mortality, and is frequently associated with intra-amniotic infection hypothesized to arise from bacterial ascension across a dysfunctional cervical mucus plug. To study this dysfunction, we assessed the permeability of cervical mucus from non-pregnant ovulating (n = 20) and high-(n = 9) and low-risk (n = 16) pregnant women to probes of varying sizes and surface chemistries. We found that the motion of negatively charged, carboxylated microspheres in mucus from pregnant patients was significantly restricted compared to ovulating patients, but not significantly different between high-A nd low-risk pregnant women. In contrast, charged peptide probes small enough to avoid steric interactions, but sensitive to the biochemical modifications of mucus components exhibited significantly different transport profiles through mucus from high-A nd low-risk patients. Thus, although both microstructural rearrangements of the components of mucus as well as biochemical modifications to their adhesiveness may alter the overall permeability of the cervical mucus plug, our findings suggest that the latter mechanism plays a dominant role in the impairment of the function of this barrier during preterm birth. We expect that these probes may be readily adapted to study the mechanisms underlying disease progression on all mucosal epithelia, including those in the mouth, lungs, and gut.
MIT Department
Massachusetts Institute of Technology. Center for Environmental Health Sciences
Massachusetts Institute of Technology. Computational and Systems Biology Program
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Mechanical Engineering
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Creative Commons Attribution 4.0 International
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DOI of Published Version
https://doi.org/10.1038/s41598-017-08057-z
