Fibronectin-based nanomechanical biosensors to map 3D surface strains in live cells and tissue

Mechanical forces are integral to cellular migration, differentiation and tissue morphogenesis; however, it has proved challenging to directly measure strain at high spatial resolution with minimal perturbation in living sytems. Here, we fabricate, calibrate, and test a fibronectin (FN)-based nanomechanical biosensor (NMBS) that can be applied to the surface of cells and tissues to measure the magnitude, direction, and strain dynamics from subcellular to tissue length-scales. The NMBS is a fluorescently-labeled, ultra-thin FN lattice-mesh with spatial resolution tailored by adjusting the width and spacing of the lattice from 2–100 µm. Time-lapse 3D confocal imaging of the NMBS demonstrates 2D and 3D surface strain tracking during mechanical deformation of known materials and is validated with finite element modeling. Analysis of the NMBS applied to single cells, cell monolayers, and Drosophila ovarioles highlights the NMBS’s ability to dynamically track microscopic tensile and compressive strains across diverse biological systems where forces guide structure and function.

The exact sample size (n) for each experimental group/condition, given as a discrete number and unit of measurement A statement on whether measurements were taken from distinct samples or whether the same sample was measured repeatedly The statistical test(s) used AND whether they are one-or two-sided Only common tests should be described solely by name; describe more complex techniques in the Methods section.
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Software and code
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Data analysis
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Adam Feinberg
Sep 23, 2020 For NMBS pattern design we used AutoCAD (Autodesk) 2018. To acquire atomic force microscopy images we used Asylum Research AFM Software version 14.23.153 and IGOR Pro 6.1 software (WaveMetrics) for analysis. For fluorescence imaging we used a variety of software depending on the microscope used. Widefield fluorescence imaging was performed using Nikon NIS Elements AR 4.0, and ImageJ Micromanager v1.46. Scanning confocal fluorescence imaging was acquired using Nikon NIS Elements Ar 5.11, and Zeiss Zen 2012 SP5. Spinning disk confocal fluorescence imaging was acquired using Andor IQ2.2 software. 3D CAD models were made in Fusion 360 (Autodesk) 2019 release. Finite element modeling was performed using ANSYS Mechanical 2019.
General image analysis and visualization was done in FIJI ImageJ software version 1.52t. All custom analysis code for NMBS strain identification, tracking, and 3D mapping was performed using Imaris 9.5.1 (Bitplane) and MATLAB (MathWorks)  Data Policy information about availability of data All manuscripts must include a data availability statement. This statement should provide the following information, where applicable: -Accession codes, unique identifiers, or web links for publicly available datasets -A list of figures that have associated raw data -A description of any restrictions on data availability Field-specific reporting Please select the one below that is the best fit for your research. If you are not sure, read the appropriate sections before making your selection.

Life sciences Behavioural & social sciences Ecological, evolutionary & environmental sciences
For a reference copy of the document with all sections, see nature.com/documents/nr-reporting-summary-flat.pdf

Life sciences study design
All studies must disclose on these points even when the disclosure is negative. Statistical tests were chosen based on the experimental sample size, distribution, and data requirements. In all cases, the relevant reproducibility for evaluating the NMBS as a strain sensor was our ability to apply, detect, and analyze individual segments within the NMBS lattice. Therefore, our use of statistical analysis in this manuscript was not to determine a statistical difference between two experimental groups, but rather to calculate the reproducibility of measurement for the NMBS within a given experiment. For this reason, all error bars are shown as mean with standard deviation within a given experiment over time and the n values are described as the number of individual lattice segments used for quantification. For each experiment, sample sizes were checked to insure adequate data and segment numbers were acquired and analyzed to demonstrate the capabilities of the NMBS following quantitative evaluation of the data.
No data was excluded in experiments that were deemed successful, and therefore was included in further analysis. Unsuccessful experiments were ones in which the NMBS did not transfer to cells or tissue, and there was therefore no data to collect. For all data sets analyzed in the manuscript, no data was selectively excluded.
Replication of study was not appropriate for this manuscript. In our case, validation of our NMBS platform across multiple type of cells, tissue, and materials was proof of replication and use of the method. Specifically, we validated our method for strain tracking across synthetic hydrogels, biological hydrogels, single cells, cell monolayers, and developing tissue demonstrating the reproducibility in NMBS application to a variety of materials and the robustness of our analysis in various experimental settings.
Randomization was not relevant to this study. The creation of a new strain biosensor and subsequent validation did not require experimental group randomization.
Data blinding was not relevant for this study because the analysis was unbiased and validation of a direct strain biosensor in the NMBS produced visual deformation that was computationally quantified. The process of analysis was completely automated and introduced no bias that required blinding.