Vascular dimorphism ensured by regulated proteoglycan dynamics favors rapid umbilical artery closure at birth

  1. Sumeda Nandadasa
  2. Jason M Szafron
  3. Vai Pathak
  4. Sae-Il Murtada
  5. Caroline M Kraft
  6. Anna O'Donnell
  7. Christian Norvik
  8. Clare Hughes
  9. Bruce Caterson
  10. Miriam S Domowicz
  11. Nancy B Schwartz
  12. Karin Tran-Lundmark
  13. Martina Veigl
  14. David Sedwick
  15. Elliot H Philipson
  16. Jay D Humphrey  Is a corresponding author
  17. Suneel S Apte  Is a corresponding author
  1. Cleveland Clinic Lerner Research Institute, United States
  2. Yale University, United States
  3. Case Western Reserve University, United States
  4. Yale University School of Engineering and Applied Science, United States
  5. Lund University, Sweden
  6. Cardiff University, United Kingdom
  7. University of Chicago, United States
  8. Cleveland Clinic, United States

Abstract

The umbilical artery lumen closes rapidly at birth, preventing neonatal blood loss, whereas the umbilical vein remains patent longer. Here, analysis of umbilical cords from humans and other mammals identified differential arterial-venous proteoglycan dynamics as a determinant of these contrasting vascular responses. The umbilical artery, but not the vein, has an inner layer enriched in the hydrated proteoglycan aggrecan, external to which lie contraction-primed smooth muscle cells (SMC). At birth, SMC contraction drives inner layer buckling and centripetal displacement to occlude the arterial lumen, a mechanism revealed by biomechanical observations and confirmed by computational analyses. This vascular dimorphism arises from spatially regulated proteoglycan expression and breakdown. Mice lacking aggrecan or the metalloprotease ADAMTS1, which degrades proteoglycans, demonstrate their opposing roles in umbilical vascular dimorphism, including effects on SMC differentiation. Umbilical vessel dimorphism is conserved in mammals, suggesting that differential proteoglycan dynamics and inner layer buckling were positively selected during evolution.

Data availability

All data generated or analysed during this study are included in the manuscript and supporting files.

The following data sets were generated

Article and author information

Author details

  1. Sumeda Nandadasa

    Biomedical Engineering, Cleveland Clinic Lerner Research Institute, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  2. Jason M Szafron

    Department of Biomedical Engineering, Yale University, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9476-5175
  3. Vai Pathak

    Case Comprehensive Cancer Center, Case Western Reserve University, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Sae-Il Murtada

    Department of Biomedical Engineering, Yale University School of Engineering and Applied Science, New Haven, United States
    Competing interests
    The authors declare that no competing interests exist.
  5. Caroline M Kraft

    Biomedical Engineering, Cleveland Clinic Lerner Research Institute, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Anna O'Donnell

    Biomedical Engineering, Cleveland Clinic Lerner Research Institute, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  7. Christian Norvik

    Department of Experimental Medical Science and Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
    Competing interests
    The authors declare that no competing interests exist.
  8. Clare Hughes

    School of Biosciences, Cardiff University, Cardiff, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4726-5877
  9. Bruce Caterson

    School of Biosciences, Cardiff University, Cardiff, United Kingdom
    Competing interests
    The authors declare that no competing interests exist.
  10. Miriam S Domowicz

    Department of Pediatrics, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-7860-4427
  11. Nancy B Schwartz

    Postdoctoral Affairs and Association, University of Chicago, Chicago, United States
    Competing interests
    The authors declare that no competing interests exist.
  12. Karin Tran-Lundmark

    Department of Experimental Medical Science and Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
    Competing interests
    The authors declare that no competing interests exist.
  13. Martina Veigl

    Department of Medicine, Case Western Reserve University, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  14. David Sedwick

    Department of Medicine, Case Western Reserve University, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  15. Elliot H Philipson

    The Women's Health Institute, Department of Obstetrics and Gynecology, Cleveland Clinic, Cleveland, United States
    Competing interests
    The authors declare that no competing interests exist.
  16. Jay D Humphrey

    Department of Biomedical Engineering, Yale University School of Engineering and Applied Science, New Haven, United States
    For correspondence
    jay.humphrey@yale.edu
    Competing interests
    The authors declare that no competing interests exist.
  17. Suneel S Apte

    Biomedical Engineering, Cleveland Clinic Lerner Research Institute, Cleveland, United States
    For correspondence
    aptes@ccf.org
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8441-1226

Funding

National Institutes of Health (HL107147)

  • Suneel S Apte

National Institutes of Health (HL141130)

  • Suneel S Apte

American Heart Association (17DIA33820024)

  • Suneel S Apte

Sabrina's Foundation (None)

  • Elliot H Philipson

National Children's Study (Formative Research Project L01-3-RT-01-E,Contract # HHSN272500800009C)

  • Martina Veigl
  • David Sedwick

Mark Lauer Pediatric Research Grant (None)

  • Sumeda Nandadasa

National Institutes of Health (CA43703)

  • Martina Veigl

Swedish Heart-Lung Foundation (None)

  • Karin Tran-Lundmark

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocols: 18-1996 and 18-2045 (Cleveland Clinic IACUC), 2018-11508 (Yale University IACUC) and 43751 (University of Chicago IACUC).

Human subjects: Human umbilical cord samples were collected under an IRB exemption (EX-0118) from Cleveland Clinic for use of discarded tissue without patient identifiers. These cords were used for histological/immunohistologic analysis, in situ hybridization, and transcriptomics of inner vs outer umbilical artery TM. For microarray analysis of umbilical cord artery versus vein, human umbilical cords were collected separately through the National Children's Study under University Hospitals-Case Medical Center approved IRB protocol 01-11-28.

Copyright

© 2020, Nandadasa et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,736
    views
  • 251
    downloads
  • 13
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Sumeda Nandadasa
  2. Jason M Szafron
  3. Vai Pathak
  4. Sae-Il Murtada
  5. Caroline M Kraft
  6. Anna O'Donnell
  7. Christian Norvik
  8. Clare Hughes
  9. Bruce Caterson
  10. Miriam S Domowicz
  11. Nancy B Schwartz
  12. Karin Tran-Lundmark
  13. Martina Veigl
  14. David Sedwick
  15. Elliot H Philipson
  16. Jay D Humphrey
  17. Suneel S Apte
(2020)
Vascular dimorphism ensured by regulated proteoglycan dynamics favors rapid umbilical artery closure at birth
eLife 9:e60683.
https://doi.org/10.7554/eLife.60683

Share this article

https://doi.org/10.7554/eLife.60683

Further reading

    1. Cancer Biology
    2. Computational and Systems Biology
    Rosalyn W Sayaman, Masaru Miyano ... Mark LaBarge
    Research Article

    Effects from aging in single cells are heterogenous, whereas at the organ- and tissue-levels aging phenotypes tend to appear as stereotypical changes. The mammary epithelium is a bilayer of two major phenotypically and functionally distinct cell lineages: luminal epithelial and myoepithelial cells. Mammary luminal epithelia exhibit substantial stereotypical changes with age that merit attention because these cells are the putative cells-of-origin for breast cancers. We hypothesize that effects from aging that impinge upon maintenance of lineage fidelity increase susceptibility to cancer initiation. We generated and analyzed transcriptomes from primary luminal epithelial and myoepithelial cells from younger <30 (y)ears old and older >55y women. In addition to age-dependent directional changes in gene expression, we observed increased transcriptional variance with age that contributed to genome-wide loss of lineage fidelity. Age-dependent variant responses were common to both lineages, whereas directional changes were almost exclusively detected in luminal epithelia and involved altered regulation of chromatin and genome organizers such as SATB1. Epithelial expression of gap junction protein GJB6 increased with age, and modulation of GJB6 expression in heterochronous co-cultures revealed that it provided a communication conduit from myoepithelial cells that drove directional change in luminal cells. Age-dependent luminal transcriptomes comprised a prominent signal that could be detected in bulk tissue during aging and transition into cancers. A machine learning classifier based on luminal-specific aging distinguished normal from cancer tissue and was highly predictive of breast cancer subtype. We speculate that luminal epithelia are the ultimate site of integration of the variant responses to aging in their surrounding tissue, and that their emergent phenotype both endows cells with the ability to become cancer-cells-of-origin and represents a biosensor that presages cancer susceptibility.

    1. Computational and Systems Biology
    2. Microbiology and Infectious Disease
    Gaetan De Waele, Gerben Menschaert, Willem Waegeman
    Research Article

    Timely and effective use of antimicrobial drugs can improve patient outcomes, as well as help safeguard against resistance development. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is currently routinely used in clinical diagnostics for rapid species identification. Mining additional data from said spectra in the form of antimicrobial resistance (AMR) profiles is, therefore, highly promising. Such AMR profiles could serve as a drop-in solution for drastically improving treatment efficiency, effectiveness, and costs. This study endeavors to develop the first machine learning models capable of predicting AMR profiles for the whole repertoire of species and drugs encountered in clinical microbiology. The resulting models can be interpreted as drug recommender systems for infectious diseases. We find that our dual-branch method delivers considerably higher performance compared to previous approaches. In addition, experiments show that the models can be efficiently fine-tuned to data from other clinical laboratories. MALDI-TOF-based AMR recommender systems can, hence, greatly extend the value of MALDI-TOF MS for clinical diagnostics. All code supporting this study is distributed on PyPI and is packaged at https://github.com/gdewael/maldi-nn.