PCOMPBIOL-D-26-00827

Quantifying the Spatiotemporal Dynamics of Engineered Cardiac Microbundles

PLOS Computational Biology

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PLOS Computational Biology

Dimitrios Vavylonis

Section Editor

PLOS Computational Biology

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If the reviewer comments include a recommendation to cite specific previously published works, please review and evaluate these publications to determine whether they are relevant and should be cited. There is no requirement to cite these works unless the editor has indicated otherwise.

1) Please ensure that the CRediT author contributions listed for every co-author are completed accurately and in full.

At this stage, the following Authors/Authors require contributions: Brendon M. Baker, Samuel J. DePalma, Javiera Jilberto, Hiba Kobeissi, David Nordsletten, and Emma Lejeune. Please ensure that the full contributions of each author are acknowledged in the "Add/Edit/Remove Authors" section of our submission form.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: Comments:

It’s not really clear how this method translates from 2D to 3D systems. Has there been any validation to show that what’s measured in 2D holds up in more physiologically relevant 3D tissues?

The scalability across different tissue platforms feels underdeveloped. Tissue sizes vary a lot, and so do imaging setups. Right now, it’s not clear at what resolution this method starts to break down. There’s no guidance on minimum pixel size, no sensitivity analysis for resolution, and no real discussion of how tracking accuracy changes as resolution drops.

FWHM is introduced without explanation (Section 2.2.1) and only defined later. It would help to define it right when it first appears.

I’m also not fully clear on how to interpret FWHM. For example, stiffer pillars would likely dampen and broaden the signal differently than softer ones... so what exactly does a change in this metric mean in a mechanical or biological sense?

The beginning is a bit repetitive with all the section references. It makes the writing feel heavier than it needs to be and breaks the flow a bit.

There should be more consistency in units. Right now, pixel-based displacement isn’t really comparable across systems, which seems at odds with the idea of this being broadly applicable. Some kind of normalization or conversion to physical units would help.

It would also be helpful to know how this system behaves with mature tissue. Do these metrics hold up in more mature, aligned tissues, or are they specific to earlier stages?

The saddle point result is really interesting. It would be great to see more discussion on how to actually probe the biology behind it. For example, could drug perturbations, changes in tissue size, or different boundary conditions help unpack what’s going on?

Typos:

Page 4, Section 2.2.1: “Full Width at Half Maximum” shouldn’t be capitalized.

Page 5, Section 2.2.2: “please refer to its original publication” → “please refer to the original publication.”

Page 28, Conclusion: “Moreover” can just be removed.

Page 5, Section 2.2.3: “these tissue” → “these tissues.”

Figure 4 caption: “disaplacement” → “displacement.”

Reviewer #2: In their paper ‘Quantifying the spatiotemporal dynamics of engineered cardiac mircobundles” by H. Kobeissi et al., the authors describe a sophisticated measurement and analysis platform for the quantification of the contractile behavior of engineered cardiac microbundles. They developed an automated analysis pipeline for characterizing the contractions of a large number of engineered heart muscle bundles, and assessed the utility of various metrics across the dataset. Overall, the work is high quality, thorough, extensive, and well done. What impresses me most is that the authors demonstrate their automated pipeline across so many tissues and provide in-depth analyses of various metrics. One of the main weaknesses of the study is that it provides only limited biological insight. At the end, the sophisticated analysis can only establish a correlation between “Tissue Mean Peak Absolute Displacement” and “Pillar Mean Peak Force,” or confirm that the “tissue contraction is primarily linear and isotropic along the major axis”. However, the authors acknowledge this issue, and, in my view, it is related to the large amounts of data, to the complexity of the biology, and the variability across so many tissues, and can therefore be excused. Many other biological studies lack the quantitative rigor of this study, and it can therefore serve as a guiding example.

Comments:

Please add line numbers.

The title should be more specific: “Quantifying the spatiotemporal mechanical dynamics of engineered cardiac mircobundles” is more fitting in my opinion, because the authors quantify mechanical contraction patterns and do not measure the electrophysiology of the tissues.

Fig. 1: The left panel lacks a scale bar. Are the multiple images supposed to illustrate that each dataset is a video? Maybe add an arrow along that direction with a label ’t’ or ‘time’.What does the displacement panel show, what are the dots and green/blue/yellow colors? There are no units/ticks on the plot axes.

Fig. 2 lacks scale bars.

Fig. 3: is this data from the study or are they theoretical examples illustrating the critical point analysis? Please clarify.

Fig. 7: Are these panels all from one tissue or collected from multiple tissues?

As the microbundles contract, could there be changes in density and subsequent refractive index changes that alter the features being tracked?

In section 2.2.2, it is described that the tissue is tracked using “sparse optical flow,” but in the next sentence, it is stated that it “yields high-resolution vector maps.” Isn’t this a contradiction? It would be great to mention the temporal and spatial resolution in this section and the corresponding figures.

Are the fiducial markers on a regular or irregular grid? Eventually, a zoomed-in view showing a few of these markers would be very helpful to the reader.

In the beginning of section 2.2.2.1, the authors say that they “calculate average subdomain strain rather than full-field strain”. Please explain the difference (1-2 sentences).

Section 2.2.2.1 requires more visuals or drawings to illustrate the strain computations. It would be great to see a specific example of how strain is computed from displacements and overlaid onto parts of the microbundle.

In section 2.2.2.2, the authors mention that some movies had to be excluded, because of blurring. What else ensures that the fiducial markers can be identified properly? Is it back-illumination? This should be mentioned somewhere in the manuscript.

On p.6, the authors describe the transformation of the data into a 3D matrix with dimensions 28 x 33 x 670 matrices before PCA analysis. The first and second dimensions are the horizontal and vertical dimensions of the field, and the third is the number of samples. What about the x and y components of the displacement vectors?

The critical point analysis appears to be adopted from fluid dynamics. Is this a good approach? Aren’t fluid dynamics and mechanics two very different physical phenomena?

The authors mention in section 3.3 that the critical point analysis might be used to “reveal mechanical microenvironments or hotspots of activity” and uncover “links between topological features in displacement fields and the biological makeup of the tissue”. What do they mean by that?

Did the authors use this analysis to examine how contractile patterns change longitudinally over time? What would the authors hope to learn from such an analysis?

The study mentions other related work within the microbundle tracking field, but largely ignores other adjacent work in which tracking and motion analysis are performed with fluorescence-based imaging data. Since the authors mention calcium imaging in the Discussion, they should consider mentioning work by:

- J. Lebert et al., Real-time optical mapping of contracting cardiac tissues with GPU-accelerated numerical motion tracking, Front. Cardiovasc. Med., 2022. This study demonstrates numerical tracking and measurement of action potential waves in whole hearts and engineered cardiac tissues. It also compares different optical flow-based tracking algorithms.

- optimap: An open-source library for processing fluorescence video data: https://github.com/cardiacvision/optimap/

- L .Woodhams et al., Virtual blebbistatin: A robust and rapid software approach to motion artifact removal in optical mapping of cardiomyocytes, PNAS, 2023. This study discusses strain computations and simultaneous electrophysiology measurements in engineered cardiac tissue.

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Reviewer #1: Yes

Reviewer #2: None

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Reviewer #1: No

Reviewer #2: No

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Dear Dr. Lejeune,

We are pleased to inform you that your manuscript 'Quantifying the Spatiotemporal Mechanical Dynamics of Engineered Cardiac Microbundles' has been provisionally accepted for publication in PLOS Computational Biology.

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Anna Grosberg, Ph.D.

Academic Editor

PLOS Computational Biology

Dimitrios Vavylonis

Section Editor

PLOS Computational Biology

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Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: The authors have adequately addressed our comments, and we have no further substantive concerns.

Reviewer #2: I would like to thank the authors for their in-depth responses and for carefully revising their paper. All my comments and concerns were sufficiently addressed.

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Have the authors made all data and (if applicable) computational code underlying the findings in their manuscript fully available?

The PLOS Data policy requires authors to make all data and code underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data and code should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data or code —e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: None

Reviewer #2: Yes

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Reviewer #1: No

Reviewer #2: No