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Cellular and Molecular Bioengineering

, Volume 11, Issue 6, pp 483–494 | Cite as

Cell Sequence and Mitosis Affect Fibroblast Directional Decision-Making During Chemotaxis in Microfluidic Mazes

  • Quang Long Pham
  • Lydia N. Rodrigues
  • Max A. Maximov
  • Vishnu Deep Chandran
  • Cheng Bi
  • David Chege
  • Timothy Dijamco
  • Elisabeth Stein
  • Nhat Anh Nguyen Tong
  • Sagnik Basuray
  • Roman S. Voronov
Article

Abstract

Introduction

Directed fibroblast migration is central to highly proliferative processes in regenerative medicine and developmental biology. However, the mechanisms by which single fibroblasts affect each other’s directional decisions, while chemotaxing in microscopic pores, are not well understood.

Methods

We explored effects of cell sequence and mitosis on fibroblast platelet-derived growth factor-BB (PDGF-BB)-induced migration in microfluidic mazes with two possible through paths: short and long. Additionally, image-based modeling of the chemoattractant’s diffusion, consumption and decay, was used to explain the experimental observations.

Results

It both cases, the cells displayed behavior that is contradictory to expectation based on the global chemoattractant gradient pre-established in the maze. In case of the sequence, the cells tend to alternate when faced with a bifurcation: if a leading cell takes the shorter (steeper gradient) path, the cell following it chooses the longer (weaker gradient) path, and vice versa. Image-based modeling of the process showed that the local PDGF-BB consumption by the individual fibroblasts may be responsible for this phenomenon. Additionally, it was found that when a mother cell divides, its two daughters go in opposite directions (even if it means migrating against the chemoattractant gradient and overcoming on-going cell traffic).

Conclusions

It is apparent that micro-confined fibroblasts modify each other’s directional decisions in a manner that is counter-intuitive to what is expected from classical chemotaxis theory. Consequently, accounting for these effects could lead to a better understanding of tissue generation in vivo, and result in more advanced engineered tissue products in vitro.

Keywords

Migration Division Diffusion Fibroblast Gradient Chemotaxis PDGF-BB Proliferation Confinement Modeling 

Notes

Acknowledgments

The authors also thank Gustavus and Louise Pfeiffer Research Foundation for their gracious funding of our work. Additionally, the authors would like to thank New Jersey Institute of Technology (NJIT)’s McNair Achievement and Provost Summer Research Programs for providing student labor for this project. A fibroblast donation from Prof. Xiaoyang Xu’s laboratory at NJIT’s Department of Chemical, Biological and Pharmaceutical Engineering is greatly appreciated. Lastly, we would like to thank the anonymous reviewer who provided the order of magnitude estimate of the PDGF uptake rate by a cell in our model, which we have included into the Online Appendix.

Funding

This study was funded by the Gustavus and Louise Pfeiffer Research Foundation’s Major Investment Grant, while the custom mask aligner was in part funded by NSF I-Corps Site Award #: 1450182.

Conflict of interest

Authors Quang Long Pham, Lydia N. Rodrigues, Max A. Maximov, Vishnu Deep Chandran, Cheng Bi, David Chege, Timothy Dijamco, Elisabeth Stein, Nhat Anh Nguyen Tong, Sagnik Basuray, and Roman S. Voronov declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Supplementary material

12195_2018_551_MOESM1_ESM.docx (1.3 mb)
Supplementary material 1 (DOCX 1322 kb)
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Supplementary material 2 (TIFF 1046 kb) Supplemental Figure 1: Detailed breakdown of the directional decision sequences displayed by the fibroblasts in the maze. (A) Directional choices of the first two cells reaching the maze bifurcation, when the cell sequence is taken into account. (B) Directional choices of any two consecutive cells to reach the maze bifurcation, when the cell sequence is taken into account. N indicates the number of sequences being counted.
12195_2018_551_MOESM3_ESM.tif (133 kb)
Supplementary material 3 (TIFF 132 kb) Supplemental Figure 2: Spatial distribution of mitosis events in different maze segments, overlaid on the PDGF-BB concentration profile from COMSOL. (A) Divisions in a maze segment per total number of divisions in the whole maze. (B) Divisions in a maze segment per total number of cell visits into the same maze segment. Black lines indicate boundaries between the maze segments considered.
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Supplementary material 4 (AVI 9708 kb)Supplemental Video 1: Negative control experiment, showing that the cells do not go into the maze in the absence of a PDGF gradient.

Supplementary material 5 (AVI 8015 kb) Supplemental Video 2: Control experiment, showing a correspondence between the simulated PDGF diffusion kinetics (top row) in an empty maze, and those of experimentally-diffused fluorescent dextran (bottom row) with a similar molecular weight. Left column shows the absolute concentration values, in the case of the simulated PDGF, and the fluorescence intensity, in the case of the dextran experiment; right column shows a % difference relative to the steady state values for the same.

12195_2018_551_MOESM6_ESM.avi (225.7 mb)
Supplementary material 6 (AVI 231104 kb)Supplemental Video 3: Control experiment, showing that cells do not obstruct dextran diffusion in the maze. Left – fluorescence microscopy of the dextran; Right – phase contrast microscopy of the cells. Circular markers highlight instances of the cells spreading across the maze channels.
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Supplementary material 7 (AVI 6894 kb)Video 1: Alternating patterns of cell decision making with the first cell selecting the short path
12195_2018_551_MOESM8_ESM.avi (8.4 mb)
Supplementary material 8 (AVI 8565 kb) Video 2: Alternating patterns of cell decision making with the first cell selecting the long path
12195_2018_551_MOESM9_ESM.avi (3.3 mb)
Supplementary material 9 (AVI 3423 kb) Video 3: Image-based model of fibroblasts consuming the chemoattractant in the maze. The PDGF-BB concentration scaled by the exit boundary condition concentration. Scale bar is 100 μm. Although the simulation is performed with a Δtsimulation = 1min, the frames shown in this video correspond to frequency at which the images are captured by the microscope, Δtmicroscope = 15 minutes (while the intermediate frames are omitted for clarity). The video frames correspond to the acquisition Δtmicroscope = 15 minutes, while the simulation
12195_2018_551_MOESM10_ESM.avi (4.7 mb)
Supplementary material 10 (AVI 4854 kb) Video 4: Image-based model of fibroblasts modifying the chemoattractant gradient in the maze. Scale bar is 100 μm. Although the simulation is performed with a Δtsimulation = 1min, the frames shown in this video correspond to the frequency at which the images are captured by the microscope, Δtmicroscope = 15 minutes (while the intermediate frames are omitted for clarity).
12195_2018_551_MOESM11_ESM.avi (1.6 mb)
Supplementary material 11 (AVI 1633 kb) Video 5: Daughter cells following each other in the same direction after division.
12195_2018_551_MOESM12_ESM.avi (2.1 mb)
Supplementary material 12 (AVI 2127 kb)Video 6: Daughter cells moving in the opposite directions following a cell division.

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Copyright information

© Biomedical Engineering Society 2018

Authors and Affiliations

  • Quang Long Pham
    • 1
  • Lydia N. Rodrigues
    • 1
  • Max A. Maximov
    • 1
  • Vishnu Deep Chandran
    • 1
  • Cheng Bi
    • 1
  • David Chege
    • 2
  • Timothy Dijamco
    • 3
  • Elisabeth Stein
    • 1
  • Nhat Anh Nguyen Tong
    • 1
  • Sagnik Basuray
    • 1
  • Roman S. Voronov
    • 1
  1. 1.Otto H. York Department of Chemical and Materials EngineeringNew Jersey Institute of TechnologyNewarkUSA
  2. 2.Department of Electrical and Computer EngineeringNew Jersey Institute of TechnologyNewarkUSA
  3. 3.Computer Science Dept.New Jersey Institute of TechnologyNewarkUSA

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