Fiber Tension Microscopy (FiberTM)

Measure internal tension of individual ECM fibers from confocal line scans, and paint full fields-of-view by tension.
MATLAB reference implementation + analysis utilities.

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Table of Contents

• Overview
• Repository Structure
• Installation
• Quick Start
• Workflow
• Theory (Short Version)
• Figures
• Objective
• Significance
• Citing
• License
• Acknowledgments

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Overview

Fiber Tension Microscopy (FiberTM) is a hardware + computational framework to quantify tension within individual fibers of a fibrous extracellular matrix (ECM) using any commercial laser scanning confocal microscope. The code here:

• tracks sub-diffraction centroid fluctuations of fibers from rapid line scans,
• converts the mean squared displacement (MSD) of fiber midpoints to a dimensionless tension \( \phi \) via an odd-mode sum model for semiflexible filaments,
• returns physical tension \( \tau \) (pN), and
• paints full images by stiffness/tension classification for visualization.

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Repository Structure

FTM/
├─ analyze_fiber_fluctuations.m   % line-scan → centroids → histograms (std dev)
├─ paint_fibers.m                 % paint stiff vs. floppy regions from coordinates
├─ compute_fiber_tension.m        % invert MSD → φ → τ (pN)
├─ assets/
│   ├─ overview.png
│   └─ example_results.png
└─ README.md

Requirements

• MATLAB R2019b+ (R2020b+ recommended)
• Curve Fitting Toolbox (Gaussian fits)
• Bio-Formats for MATLAB (bfopen) to read .oir files

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Installation

1. Install MATLAB (with Curve Fitting Toolbox).
2. Install the Bio-Formats Image Toolbox and add it to your MATLAB path (for .oir support).
3. Clone this repository and add it to your MATLAB path:

   addpath(genpath('/path/to/FTM'));

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Quick Start

1) Line-scan analysis → centroids (std devs)

out = analyze_fiber_fluctuations(struct( ...
  'dataDir',        'path/to/line/scans', ...
  'pix2um',         1/38.6175, ...     % µm per pixel
  'downsample',     10, ...
  'roiHalfWidthPx', 13, ...
  'gofThreshold',   0.80, ...
  'showExample',    true, ...
  'savePrefix',     'session1' ...
));

2) Field painting (stiff vs. floppy)

outPaint = paint_fibers(struct( ...
  'imageFile',  'colormap_fibers/T2_5.tif', ...
  'coordsXlsx', 'Line Scan Cords-2.xlsx', ...
  'matPath',    'matrix_to_paint_fibers.mat', ... % contains logical stiff/floppy vectors
  'indexRange', [133 143], ...
  'squareSize', 50, ...
  'shape',      'square', ... % or 'disk'
  'outDir',     'outputs', ...
  'savePrefix', 'T2_5' ...
));

3) MSD → tension (table in/out)

Tout = compute_fiber_tension(struct( ...
  'xlsxPath','CrossLinkedFibers_Tension_far.xlsx', ...
  'outputPath','Fiber_Tension_Output.xlsx' ...
));

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Workflow

1. Acquire rapid line scans over visible fibers (≥600–800 lines/s).
2. Track centroids via Gaussian fits per line → time series of midpoint position.
3. Compute MSD at the midpoint and invert the semiflexible filament model (odd-mode sum) to get \( \phi \) and tension \( \tau \).
4. Paint the field: classify or color-code fibers as floppy/low/high tension.
5. Export tables, figures, and overlays for downstream analysis.

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Theory (Short Version)

For a semiflexible filament with persistence length \( \ell_p \) and length \( L \), the midpoint MSD obeys \[ \mathrm{MSD} = \frac{2}{\pi^4}\,\frac{L^3}{\ell_p}\, S(\phi), \quad S(\phi) = \sum_{n\,\text{odd}} \frac{1}{n^4 + \phi n^2}, \quad \phi = \frac{\tau L^2}{\kappa},\; \kappa = \ell_p k_B T. \] Given \(L\) and measured MSD, we solve for \( \phi \) by bracketed bisection and then compute tension
\( \tau = (\phi\, \pi^2\, \kappa)/L^2 \). Feasibility is checked against the zero-tension ceiling \( \mathrm{MSD}_{\max} = L^3/(48\ell_p) \).

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Figures

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Objective

Cells remodel the fibrous ECM via contractile forces, enabling long-range mechanical communication that coordinates tissue-scale processes (organization, morphogenesis, and disease progression). We hypothesize that mechanical signals are transmitted before fiber realignment is detectable, i.e., Early Mechanotransduction. We will build Fiber Tension Microscopy (FTM)—a confocal-compatible hardware/software toolkit—to measure per-fiber tension at scale.

Significance

Mechanical communication in fibrous ECMs (e.g., fibrin, collagen) is directional, long-range, and functional. Existing traction/stress methods in amorphous gels do not measure internal fiber tension. FTM fills this gap with a non-invasive, confocal-based approach to quantify per-fiber tension and generate tension maps that co-register with standard fluorescence imaging.

Citing

If you use FTM or parts of this work in your research, please cite:

Eldeen, S., Bruinsma, R., Botvinick, E.L., et al. Fiber Tension Microscopy (FTM): Quantifying Force Transmission Pathways in Fibrous Extracellular Matrices. (preprint/in preparation).

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License

MIT License — see LICENSE (or update per your lab policy).

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Acknowledgments

Thanks to collaborators and advisors including Robijn Bruinsma, Elliot Botvinick, the late Alex Levin, Enrico Gratton, and colleagues who contributed to theory and imaging.