<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Archiving and Interchange DTD with MathML3 v1.3 20210610//EN"  "JATS-archivearticle1-3-mathml3.dtd"><article xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.3"><front><journal-meta><journal-id journal-id-type="nlm-ta">elife</journal-id><journal-id journal-id-type="publisher-id">eLife</journal-id><journal-title-group><journal-title>eLife</journal-title></journal-title-group><issn publication-format="electronic" pub-type="epub">2050-084X</issn><publisher><publisher-name>eLife Sciences Publications, Ltd</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">96025</article-id><article-id pub-id-type="doi">10.7554/eLife.96025</article-id><article-id pub-id-type="doi" specific-use="version">10.7554/eLife.96025.4</article-id><article-version article-version-type="publication-state">version of record</article-version><article-categories><subj-group subj-group-type="display-channel"><subject>Tools and Resources</subject></subj-group><subj-group subj-group-type="heading"><subject>Cell Biology</subject></subj-group></article-categories><title-group><article-title>High-throughput expansion microscopy enables scalable super-resolution imaging</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Day</surname><given-names>John H</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0002-5515-6606</contrib-id><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="other" rid="fund1"/><xref ref-type="fn" rid="con1"/><xref ref-type="fn" rid="conf1"/></contrib><contrib contrib-type="author" equal-contrib="yes"><name><surname>Della Santina</surname><given-names>Catherine M</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="fn" rid="equal-contrib1">†</xref><xref ref-type="fn" rid="con2"/><xref ref-type="fn" rid="conf2"/></contrib><contrib contrib-type="author" equal-contrib="yes"><name><surname>Maretich</surname><given-names>Pema</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="equal-contrib1">†</xref><xref ref-type="fn" rid="con3"/><xref ref-type="fn" rid="conf3"/></contrib><contrib contrib-type="author" equal-contrib="yes"><name><surname>Auld</surname><given-names>Alexander L</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="equal-contrib1">†</xref><xref ref-type="fn" rid="con4"/><xref ref-type="fn" rid="conf4"/></contrib><contrib contrib-type="author"><name><surname>Schnieder</surname><given-names>Kirsten K</given-names></name><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="fn" rid="con5"/><xref ref-type="fn" rid="conf5"/></contrib><contrib contrib-type="author"><name><surname>Shin</surname><given-names>Tay</given-names></name><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="other" rid="fund3"/><xref ref-type="fn" rid="con6"/><xref ref-type="fn" rid="conf5"/></contrib><contrib contrib-type="author"><name><surname>Boyden</surname><given-names>Edward S</given-names></name><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff3">3</xref><xref ref-type="aff" rid="aff4">4</xref><xref ref-type="aff" rid="aff5">5</xref><xref ref-type="aff" rid="aff6">6</xref><xref ref-type="aff" rid="aff7">7</xref><xref ref-type="aff" rid="aff8">8</xref><xref ref-type="aff" rid="aff9">9</xref><xref ref-type="other" rid="fund4"/><xref ref-type="other" rid="fund5"/><xref ref-type="other" rid="fund6"/><xref ref-type="other" rid="fund7"/><xref ref-type="other" rid="fund8"/><xref ref-type="fn" rid="con7"/><xref ref-type="fn" rid="conf6"/></contrib><contrib contrib-type="author" corresp="yes"><name><surname>Boyer</surname><given-names>Laurie A</given-names></name><contrib-id authenticated="true" contrib-id-type="orcid">https://orcid.org/0000-0003-3491-4962</contrib-id><email>lboyer@mit.edu</email><xref ref-type="aff" rid="aff1">1</xref><xref ref-type="aff" rid="aff2">2</xref><xref ref-type="aff" rid="aff9">9</xref><xref ref-type="other" rid="fund9"/><xref ref-type="fn" rid="con8"/><xref ref-type="fn" rid="conf7"/></contrib><aff id="aff1"><label>1</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/042nb2s44</institution-id><institution>Department of Biological Engineering, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff><aff id="aff2"><label>2</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/042nb2s44</institution-id><institution>Department of Biology, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff><aff id="aff3"><label>3</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/042nb2s44</institution-id><institution>Department of Media Arts and Sciences, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff><aff id="aff4"><label>4</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/042nb2s44</institution-id><institution>Department of Brain and Cognitive Sciences, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff><aff id="aff5"><label>5</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/042nb2s44</institution-id><institution>McGovern Institut, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff><aff id="aff6"><label>6</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/006w34k90</institution-id><institution>Howard Hughes Medical Institute, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff><aff id="aff7"><label>7</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/042nb2s44</institution-id><institution>K Lisa Yang Center for Bionics, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff><aff id="aff8"><label>8</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/042nb2s44</institution-id><institution>Center for Neurobiological Engineering, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff><aff id="aff9"><label>9</label><institution-wrap><institution-id institution-id-type="ror">https://ror.org/042nb2s44</institution-id><institution>Koch Institute, Massachusetts Institute of Technology</institution></institution-wrap><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib-group><contrib-group content-type="section"><contrib contrib-type="editor"><name><surname>Stasevich</surname><given-names>Timothy J</given-names></name><role>Reviewing Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/03k1gpj17</institution-id><institution>Colorado State University</institution></institution-wrap><country>United States</country></aff></contrib><contrib contrib-type="senior_editor"><name><surname>Dalal</surname><given-names>Yamini</given-names></name><role>Senior Editor</role><aff><institution-wrap><institution-id institution-id-type="ror">https://ror.org/040gcmg81</institution-id><institution>National Cancer Institute</institution></institution-wrap><country>United States</country></aff></contrib></contrib-group><author-notes><fn fn-type="con" id="equal-contrib1"><label>†</label><p>These authors contributed equally to this work</p></fn></author-notes><pub-date publication-format="electronic" date-type="publication"><day>26</day><month>11</month><year>2024</year></pub-date><volume>13</volume><elocation-id>RP96025</elocation-id><history><date date-type="sent-for-review" iso-8601-date="2024-01-29"><day>29</day><month>01</month><year>2024</year></date></history><pub-history><event><event-desc>This manuscript was published as a preprint.</event-desc><date date-type="preprint" iso-8601-date="2024-01-11"><day>11</day><month>01</month><year>2024</year></date><self-uri content-type="preprint" xlink:href="https://doi.org/10.1101/2023.02.07.527509"/></event><event><event-desc>This manuscript was published as a reviewed preprint.</event-desc><date date-type="reviewed-preprint" iso-8601-date="2024-04-26"><day>26</day><month>04</month><year>2024</year></date><self-uri content-type="reviewed-preprint" xlink:href="https://doi.org/10.7554/eLife.96025.1"/></event><event><event-desc>The reviewed preprint was revised.</event-desc><date date-type="reviewed-preprint" iso-8601-date="2024-09-30"><day>30</day><month>09</month><year>2024</year></date><self-uri content-type="reviewed-preprint" xlink:href="https://doi.org/10.7554/eLife.96025.2"/></event><event><event-desc>The reviewed preprint was revised.</event-desc><date date-type="reviewed-preprint" iso-8601-date="2024-10-16"><day>16</day><month>10</month><year>2024</year></date><self-uri content-type="reviewed-preprint" xlink:href="https://doi.org/10.7554/eLife.96025.3"/></event></pub-history><permissions><copyright-statement>© 2024, Day et al</copyright-statement><copyright-year>2024</copyright-year><copyright-holder>Day et al</copyright-holder><ali:free_to_read/><license xlink:href="http://creativecommons.org/licenses/by/4.0/"><ali:license_ref>http://creativecommons.org/licenses/by/4.0/</ali:license_ref><license-p>This article is distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License</ext-link>, which permits unrestricted use and redistribution provided that the original author and source are credited.</license-p></license></permissions><self-uri content-type="pdf" xlink:href="elife-96025-v1.pdf"/><self-uri content-type="figures-pdf" xlink:href="elife-96025-figures-v1.pdf"/><abstract><p>Expansion microscopy (ExM) enables nanoscale imaging using a standard confocal microscope through the physical, isotropic expansion of fixed immunolabeled specimens. ExM is widely employed to image proteins, nucleic acids, and lipid membranes in single cells; however, current methods limit the number of samples that can be processed simultaneously. We developed High-throughput Expansion Microscopy (HiExM), a robust platform that enables expansion microscopy of cells cultured in a standard 96-well plate. Our method enables ~4.2 x expansion of cells within individual wells, across multiple wells, and between plates. We also demonstrate that HiExM can be combined with high-throughput confocal imaging platforms to greatly improve the ease and scalability of image acquisition. As an example, we analyzed the effects of doxorubicin, a known cardiotoxic agent, on human cardiomyocytes (CMs) as measured by the Hoechst signal across the nucleus. We show a dose-dependent effect on nuclear DNA that is not observed in unexpanded CMs, suggesting that HiExM improves the detection of cellular phenotypes in response to drug treatment. Our method broadens the application of ExM as a tool for scalable super-resolution imaging in biological research applications.</p></abstract><kwd-group kwd-group-type="author-keywords"><kwd>cardiomyocytes</kwd><kwd>A549 cells</kwd><kwd>cell culture</kwd></kwd-group><kwd-group kwd-group-type="research-organism"><title>Research organism</title><kwd>Human</kwd></kwd-group><funding-group><award-group id="fund1"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000052</institution-id><institution>NIH Office of the Director</institution></institution-wrap></funding-source><award-id>OD-026839-01</award-id><principal-award-recipient><name><surname>Day</surname><given-names>John H</given-names></name></principal-award-recipient></award-group><award-group id="fund2"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000001</institution-id><institution>National Science Foundation Graduate Research Fellowship Program</institution></institution-wrap></funding-source><award-id>2141064</award-id><principal-award-recipient><name><surname>Day</surname><given-names>John H</given-names></name></principal-award-recipient></award-group><award-group id="fund3"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000001</institution-id><institution>National Science Foundation Graduate Research Fellowship Program</institution></institution-wrap></funding-source><award-id>1122374</award-id><principal-award-recipient><name><surname>Shin</surname><given-names>Tay</given-names></name></principal-award-recipient></award-group><award-group id="fund4"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000052</institution-id><institution>NIH Office of the Director</institution></institution-wrap></funding-source><award-id>EB024261</award-id><principal-award-recipient><name><surname>Boyden</surname><given-names>Edward S</given-names></name></principal-award-recipient></award-group><award-group id="fund5"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000052</institution-id><institution>NIH Office of the Director</institution></institution-wrap></funding-source><award-id>1R01AG070831</award-id><principal-award-recipient><name><surname>Boyden</surname><given-names>Edward S</given-names></name></principal-award-recipient></award-group><award-group id="fund6"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000052</institution-id><institution>NIH Office of the Director</institution></institution-wrap></funding-source><award-id>1R01MH123403</award-id><principal-award-recipient><name><surname>Boyden</surname><given-names>Edward S</given-names></name></principal-award-recipient></award-group><award-group id="fund7"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000052</institution-id><institution>NIH Office of the Director</institution></institution-wrap></funding-source><award-id>R01MH124606</award-id><principal-award-recipient><name><surname>Boyden</surname><given-names>Edward S</given-names></name></principal-award-recipient></award-group><award-group id="fund8"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000052</institution-id><institution>NIH Office of the Director</institution></institution-wrap></funding-source><award-id>1R56AG069192</award-id><principal-award-recipient><name><surname>Boyden</surname><given-names>Edward S</given-names></name></principal-award-recipient></award-group><award-group id="fund9"><funding-source><institution-wrap><institution-id institution-id-type="FundRef">http://dx.doi.org/10.13039/100000052</institution-id><institution>NIH Office of the Director</institution></institution-wrap></funding-source><award-id>R01HL140471</award-id><principal-award-recipient><name><surname>Boyer</surname><given-names>Laurie A</given-names></name></principal-award-recipient></award-group><funding-statement>The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.</funding-statement></funding-group><custom-meta-group><custom-meta specific-use="meta-only"><meta-name>Author impact statement</meta-name><meta-value>A simple and accessible method for high-throughput super-resolution fluorescence microscopy that is compatible with commonly used staining practices, 96-well cell culture plates, and confocal microscopes.</meta-value></custom-meta><custom-meta specific-use="meta-only"><meta-name>publishing-route</meta-name><meta-value>prc</meta-value></custom-meta></custom-meta-group></article-meta></front><body><sec id="s1" sec-type="intro"><title>Introduction</title><p>The ability to resolve subcellular features can greatly enhance biological discovery, identification of disease targets, and the development of targeted therapeutics. Super-resolution microscopy methods such as structured illumination microscopy (SIM), stochastic optical reconstruction microscopy (STORM), and stimulated emission depletion microscopy (STED) enable nanoscale imaging of specimens (<xref ref-type="bibr" rid="bib12">Gustafsson, 2000</xref>; <xref ref-type="bibr" rid="bib13">Hell and Wichmann, 1994</xref>; <xref ref-type="bibr" rid="bib23">Rust et al., 2006</xref>). However, these approaches require specialized expertise, costly reagents and microscopes. ExM is an inexpensive and accessible method that similarly resolves fluorescently labeled structures at subcellular resolution by isotropically enlarging specimens within a swellable polyelectrolyte hydrogel (<xref ref-type="bibr" rid="bib4">Chen et al., 2015</xref>). Images of expanded cells show a higher effective resolution due to an increase in the distance between the fluorescent molecules. Super-resolution imaging and ExM are critical tools that are widely used in biological research; however, sample processing and imaging require time-consuming manual manipulation, limiting throughput. Although there has been success in increasing the throughput of certain super-resolution microscopy techniques, these methods require highly specialized equipment and expertise which limits the accessibility of these tools (<xref ref-type="bibr" rid="bib14">Holden et al., 2014</xref>; <xref ref-type="bibr" rid="bib11">Gunkel et al., 2014</xref>; <xref ref-type="bibr" rid="bib19">Mahecic et al., 2020</xref>; <xref ref-type="bibr" rid="bib28">Xie et al., 2023</xref>). To circumvent these limitations, we developed HiExM that combines parallel sample processing and automated high-content confocal imaging in a standard 96-well cell culture plate.</p></sec><sec id="s2" sec-type="results"><title>Results</title><p>Adapting standard ExM to a 96-well plate requires the reproducible delivery of a small volume of gel solution to each well (&lt;1 µL compared to ~200 µL/sample for slide-based ExM). This small volume is necessary to allow complete gel expansion within the size constraints of wells in a 96-well plate. To achieve this goal, we engineered a device that retains small liquid droplets when dipped into a reservoir of monomeric expansion gel solution. These droplets can then be deposited into the centers of wells across the cell culture plate (<xref ref-type="fig" rid="fig1">Figure 1a and b</xref>). The retention of the gel solution is mediated by a series of reticulated grooves at the end of a cylindrical post which allows for the formation of a pendant droplet (<xref ref-type="fig" rid="fig1">Figure 1c</xref>). We estimate that each post retains ~230 nL of gel solution as measured by the mass of liquid accumulated on all post tips of a single device after dipping (Supplementary methods).</p><fig-group><fig id="fig1" position="float"><label>Figure 1.</label><caption><title>High-throughput expansion microscopy (HiExM) enables gel formation and expansion in a 96-well cell culture plate.</title><p>(<bold>a</bold>) Schematic representation of HiExM devices showing the key features highlighted in color. (<bold>b</bold>) Example devices used in 96-well cell culture plates. (<bold>c</bold>) Brightfield image of the conical post-tip shows the pattern of grooves that mediate fluid retention. (<bold>d</bold>) Fluid retention at the conical post-tip of the device. Silhouettes taken by an optical comparator of the profile of a single post suspended above a surface (left) and in contact with a surface (right) show a fluid droplet interacting with the device. Upon device insertion, the gel solution fills the space under the conical post tip, forming the toroid gel. (<bold>e–h</bold>) Schematic of HiExM gel deposition and expansion workflow. (<bold>e</bold>) The device is immersed in a shallow reservoir of gel solution. (<bold>f</bold>) Upon removal, the tip of each device post retains a small volume of gel solution. (<bold>g</bold>) Gel solution is deposited by the device into the well centers of the cell culture plate. Brightfield image (right) shows gel geometry and size prior to expansion. Note that gels deposited in HiExM cover ~1.1 mm<sup>2</sup> of the well surface to accommodate the expanded gel, and do not include cells outside the gel footprint. (<bold>h</bold>) Polymerization and expansion are performed with the device in place. Brightfield image (right) shows gel geometry and size after expansion.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig1-v1.tif"/></fig><fig id="fig1s1" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 1.</label><caption><title>Schematic depiction of high-throughput expansion microscopy (HiExM) device with displayed features.</title><p>The device was designed with three different post lengths where the four center posts are the longest, the two pairs of posts on the ends near the pressure struts are the shortest, and the middle posts are an intermediate length. When the device is inserted into the well plate, the center four posts contact the culture surface first. As downward pressure is applied to the ends of the device (by the user pressing down above the pressure struts), the spine of the device bends at the notches such that all posts contact the plate. These design features allow for the reproducible deposition of gel solution droplets and the reproducible formation of toroidal gels within the well constraints.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig1-figsupp1-v1.tif"/></fig><fig id="fig1s2" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 2.</label><caption><title>Overall schematic of high-throughput expansion microscopy (HiExM) comparing standard chemistry and photoinitiation.</title><p>(<bold>A</bold>) For standard expansion microscopy (ExM), the two initiating components (ammonium persulfate, APS and tetramethylethylenediamine, TEMED) were added to cells in wells in a two-step process to control the polymerization rate. In the first step, a droplet of TEMED-containing gel solution is deposited in the well and the device is removed. In the second step, a second identical device delivers a droplet of APS-containing gel solution to the same well with the TEMED-containing droplet to initiate polymerization. The well plate is also kept on ice for 15 min while the APS and TEMED are mixed, followed by heating the well plate at 50 °C for 5 min to initiate rapid polymerization. Additionally, the protocol is performed in a glove bag purged twice with nitrogen. (<bold>B</bold>) The use of photoinitiation HiExM as described in Methods allows for one-step polymerization. The Irgacure 2959 gel solution is deposited and polymerization is initiated by irradiation with a UVA metal halide lamp.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig1-figsupp2-v1.tif"/></fig><fig id="fig1s3" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 3.</label><caption><title>Detailed workflow of the high-throughput expansion microscopy (HiExM) protocol using photoinitiation.</title><p>HiExM can be used with cells cultured in commercially available 96-well plates. After conducting an experiment, cells can be fixed and stained as normal, followed by the addition of the anchor molecule Acryloyl-X. The following day, Acyloyl-X is aspirated, washed once with PBS and once with DI water, and then aspirated again to leave cells dry. It is important to ensure that no residual liquid remains in the well. Following aspiration, the device is used to deposit gel droplets on cells. Deposited gels are left for ~90 s followed by a 70- s exposure to UV light to initiate polymerization. Proteinase K solution is then pipetted into the wells and after 6 hr, the plate is submerged in ~4 L of water in a beaker and left suspended over a stir bar overnight. Water is then carefully aspirated from the wells and a layer of mineral oil is applied to each well to prevent evaporation and to stabilize the gel position for imaging. All steps in this procedure are performed at room temperature.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig1-figsupp3-v1.tif"/></fig><fig id="fig1s4" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 4.</label><caption><title>CF conjugated antibodies yield robust signal and resistance to photobleaching in Irgacure high-throughput expansion Microscopy microscopy (HiExM).</title><p>Representative images of A549 cells stained with α-Tubulin antibodies and secondary antibodies conjugated to CF dyes at different wavelengths before (left) and after (right) exposure to UV light as described in the HiExM protocol. Stained cells were exposed to UV light in the presence of Irgacure 2959 in 0.1% PBS. Histograms representing the raw pixel values from these images are shown on the right, where the number on each plot represents the peak pixel value for that image. Decreased peak pixel values indicate a loss of signal due to photobleaching.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig1-figsupp4-v1.tif"/></fig><fig id="fig1s5" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 5.</label><caption><title>Acryloyl-X (AcX) and ProteinaseK titration.</title><p>Signal-to-noise ratio was determined by measuring the average fluorescence intensity in an area of the cell and an area of the background for α-tubulin stained A549 cells from images obtained using the Opera Phenix. Optimum signal-to-noise was found at concentrations of 50 µg/mL AcX and 1 U/mL ProteinaseK.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig1-figsupp5-v1.tif"/></fig><fig id="fig1s6" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 6.</label><caption><title>Residual hoechst signal occasionally remains underneath high-throughput expansion microscopy (HiExM) samples.</title><p>The lowest image planes (top row) of three example images that show residual hoechst signal. Higher planes from the same images (bottom row) show nuclei within the sample.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig1-figsupp6-v1.tif"/></fig><fig id="fig1s7" position="float" specific-use="child-fig"><label>Figure 1—figure supplement 7.</label><caption><title>Schematic depiction of the 24-well plate high-throughput expansion microscopy (HiExM) device.</title><p>This device was designed to form one gel in a well of a standard 24-well cell culture plate and manufactured with injection molding (Protolabs).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig1-figsupp7-v1.tif"/></fig><media mimetype="video" mime-subtype="gif" xlink:href="elife-96025-fig1-video1.gif" id="fig1video1"><label>Figure 1—animation 1.</label><caption><title>Example of expansion process in high-throughput expansion microscopy (HiExM) with ammonium persulfate (APS)/tetramethylethylenediamine(TEMED) chemistry.</title><p>Tubulin-stained A549s were monitored after gel formation with digestion buffer on. This video, taken in real time, shows how cells treated with this protocol tend to ‘stick’ to the cell culture substrate as the gel expands. Cells are torn off the culture substrate by the expanding gel, often leaving behind residual cellular material stuck to the culture substrate.</p></caption></media><media mimetype="video" mime-subtype="gif" xlink:href="elife-96025-fig1-video2.gif" id="fig1video2"><label>Figure 1—animation 2.</label><caption><title>Example of expansion process in high-throughput expansion microscopy (HiExM) with Irgacure chemistry.</title><p>Tubulin-stained A549s were monitored after gel formation with digestion buffer on. This video, taken at 10X speed, shows cells expanding normally in HiExM in the presence of the digestion buffer. The post of the device is close to the bottom-left of the image.</p></caption></media></fig-group><p>The small volume of gel solution delivered to each well by the device forms a toroidal droplet where the inner surface is molded by the conical surface of the post-tip and the outer surface is constrained by surface tension (<xref ref-type="fig" rid="fig1">Figure 1c and d</xref>). The post-tip dimensions allow delivery of a volume of gel solution that expands relative to the diameter of the well (<xref ref-type="fig" rid="fig1">Figure 1d</xref>). The toroidal gel enables isotropic gel expansion within the well constraints while allowing for easy device removal because the inner surface of the gel expands outward away from the conical post-tip, effectively detaching the gel from the device. To achieve this toroidal geometry, our device design incorporates three key features to ensure each post of the device contacts the midpoint at the bottom of each well (<xref ref-type="fig" rid="fig1s1">Figure 1—figure supplement 1</xref>). First, two sets of three cantilevers (‘pressure struts’) are located at each end of the device and flank two rows of six posts (12 posts per device). These pressure struts apply outward force to the inside of the outer four wells ensuring that the device remains in contact with the well surface throughout the expansion process. Second, the spine of the device incorporates several notches extending through the long side of the device allowing it to bend to accommodate plate inconsistencies between the depths of individual wells. Finally, the post lengths are offset from the center four posts to allow for sequential deformation that ensures each post contacts the well surface. Together, these design features allow for reproducible deposition and expansion of gels in a 96-well plate.</p><p>To test our device for high-throughput gel expansion, we first performed ProExM using ammonium persulfate (APS) and tetramethylethylenediamine (TEMED) to initiate gel polymerization (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplement 2</xref>; <xref ref-type="bibr" rid="bib26">Tillberg et al., 2016</xref>). Since APS rapidly accelerates the polymerization of polyacrylamide hydrogels, TEMED-containing expansion gel solution is first delivered by the device and removed leaving a ≤1 µl droplet in each well of the plate on ice. Another device is then used to deliver APS-containing expansion gel solution at the same volume and the polymerization reaction is initiated by placing the plate on a 50 °C surface. Given the large air-liquid-interface of the gel, droplet delivery and polymerization are performed in a nitrogen-filled glove bag to minimize oxygen inhibition of the reaction. Although we observed gel formation across wells, polymerization and expansion were inconsistent, likely due to inconsistent radical formation and rapid evaporation of the small volume relative to the rate of polymerization (<xref ref-type="video" rid="fig1video1">Figure 1—animation 1</xref>). To overcome this limitation, we tested photochemical initiators including Lithium phenyl(2,4,6-trimethylbenzoyl)phosphinate (LAP), diphenyl(2,4,6-trimethylbenzoyl)phosphine oxide (TPO), and 1-[4-(2-Hydroxyethoxy)-phenyl]–2-hydroxy-2-methyl-1-propane-1-one (Irgacure 2959) which control polymerization of polyacrylamide gels when exposed to UV light (<xref ref-type="bibr" rid="bib18">Li et al., 2022</xref>; <xref ref-type="bibr" rid="bib22">Pawar et al., 2016</xref>). LAP has shown success in slide-based ExM using PEG-based hydrogels (<xref ref-type="bibr" rid="bib2">Blatchley et al., 2022</xref>; <xref ref-type="bibr" rid="bib10">Günay et al., 2023</xref>). We found that Irgacure 2959 allowed reproducible gel formation and expansion when compared to either APS/TEMED or other photoinitiators (<xref ref-type="video" rid="fig1video2">Figure 1—animation 2</xref>).</p><p>We next tested the ability of the HiExM platform to achieve nanoscale image resolution of biological specimens. Briefly, A549 cells were cultured, fixed, permeabilized, and immunostained with alpha-tubulin antibodies to visualize microtubules as a reference structure before and after expansion. Stained samples were then incubated with Acryloyl-X (AcX) overnight at 4 °C to allow anchoring of native proteins to the polymer matrix during gel formation. Device posts were immersed in the expansion gel solution containing 0.1% Irgacure 2959. Devices were inserted into the well plate followed by exposure to UV light (365 nm) in an anoxic environment at room temperature to initiate the polymerization reaction. Cells embedded in the resulting gels were digested with Proteinase K then expanded in deionized water overnight (<xref ref-type="fig" rid="fig1s2">Figure 1—figure supplements 2</xref> and <xref ref-type="fig" rid="fig1s3">3</xref>). Visual inspection using an epifluorescence microscope showed both robust gel formation and fluorescence signal retention across wells. Although we observed bleaching of AlexaFluor dyes in our Irgacure 2959 photopolymerized gels, Cyanine-based Fluorescent (CF) dyes are robust against bleaching in HiExM and result in reproducible signal retention (<xref ref-type="fig" rid="fig1s4">Figure 1—figure supplement 4</xref>; <xref ref-type="bibr" rid="bib15">Jiang et al., 2021</xref>). We also titrated AcX and ProteinaseK to optimize signal retention in HiExM and found the 50 µg/mL AcX and 1 U/mL ProteinaseK were most consistent for A549 cells (<xref ref-type="fig" rid="fig1s5">Figure 1—figure supplement 5</xref>). This optimization step is likely critical for different cell types. In some cases, we observed residual Hoechst signal underneath expanded cells due to digested cells that were incompletely removed during wash steps during the expansion process (<xref ref-type="fig" rid="fig1s6">Figure 1—figure supplement 6</xref>). This signal does not impact the interpretation of results.</p><p>A major workflow bottleneck associated with super-resolution imaging, including current ExM protocols, is the significant time and expertise required for image acquisition. For example, the vertical component of expansion increases the depth of the sample, necessitating more optical z-slices to image the full depth of the sample. Moreover, expansion effectively decreases the field-of-view due to increasing sample size, necessitating the acquisition of more images to analyze the same number of cells at lower resolution. To enable rapid 3D image capture of expanded cells in 96-well plates, we used a high-content confocal microscope (Opera Phenix system, Perkin Elmer) (<xref ref-type="fig" rid="fig2">Figure 2a</xref>). This approach allowed autonomous capture of images across the entire plate at a resolution of ~115 nm compared to ~463 nm for unexpanded samples using the same microscope, objective (63 X, 1.15NA water immersion), and imaging wavelength (<xref ref-type="fig" rid="fig2s1">Figure 2—figure supplement 1</xref>). Image resolution was calculated using a decorrelation analysis (<xref ref-type="bibr" rid="bib7">Descloux et al., 2019</xref>). We used the PreciScan plug-in in the Harmony analysis software to first accurately target regions of interest based on Hoechst staining to reduce acquisition times at higher magnification. Briefly, we imaged plates at 5 x across entire wells and stored the coordinates of nuclei for each well. These coordinates were then used to direct the 63 x magnification objective to the relevant fields of view.</p><fig-group><fig id="fig2" position="float"><label>Figure 2.</label><caption><title>High-throughput expansion microscopy (HiExM) is compatible with nanoscale expansion and automated image acquisition of human cells with minimal distortion.</title><p>(<bold>a</bold>) Expanded gels in a 96-well plate imaged at 5 x with an inset showing an individual gel shown on the right. (<bold>b</bold>) Imaging fields are shown for pre-expansion and post-expansion samples. Prior to expansion, 61 fields were imaged at 63 x around the center of the gel. After expansion, 12 fields were imaged at 20 x magnification. Max projections for each field were then stitched together and manually inspected to identify fields in the pre-expansion and post-expansion image sets containing matching cells. Arrows show an example of a field representing the same cells before and after expansion. (<bold>c</bold>) Representative registered fluorescence image of microtubules before (left) and after (right) expansion showing the increase in resolution conferred by expansion. In this case, both pre-expansion and post-expansion images were taken at 63 x magnification. (<bold>d</bold>) Representative error curve calculated using non-rigid registration of 43 independent fields of view. The shaded region denotes one standard error of the mean. (<bold>e</bold>) Error is not dependent on the location of a given field of view within the gel. Each data point represents the average percent error (up to 40 μm measurement length post-expansion) for a given field of view as determined by an non-rigid registration (NRR) analysis. Seven to ten fields of view were analyzed across six wells. The distance from the center of each field of view to the center of the well was measured manually in FIJI using the stitched pre-expansion image set. (<bold>f</bold>) Box plots showing the distribution of average error among gels across three plates (average = 3.63% +/- 1.39). Average error percentages for each well plate: 3.73 +/- 0.879, 3.89 +/- 1.65, and 3.43 +/- 1.44. (<bold>g</bold>) Expansion factor is not dependent on the location of a given field of view within the gel. Images taken before and after the expansion of the same cell or group of cells were used to measure the ratio of length scales in the two images. (<bold>h</bold>) Box plots showing the distribution of expansion factors of 58 gels across three plates. Expansion factors ranged from 3.5 to 5.1 x across gels with an average of 4.16 +/- 0.394. Average expansion factors for each well plate showed tight distribution with some variability across plates: 3.78 +/- 0.171, 4.26 +/- 0.171, and 4.53 +/- 0.321. Comparison of the three well plates was performed using one-way ANOVA and post-hoc Tukey HSD test (*p-value&lt;0.05).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig2-v1.tif"/></fig><fig id="fig2s1" position="float" specific-use="child-fig"><label>Figure 2—figure supplement 1.</label><caption><title>Representative images post-expansion showing nanoscale resolution in high-throughput expansion microscopy (HiExM).</title><p>A549 cells were stained for α-Tubulin and imaged on an Opera Phenix High Content Screening System (PerkinElmer) using a 63 x objective (1.15 na) as described in <xref ref-type="fig" rid="fig2">Figure 2</xref>. Scale bar represents the real scale of the images, not corrected for expansion.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig2-figsupp1-v1.tif"/></fig><fig id="fig2s2" position="float" specific-use="child-fig"><label>Figure 2—figure supplement 2.</label><caption><title>Infrequent higher expansion error in high-throughput expansion microscopy (HiExM) is due to abnormal stretching and tearing of the gel.</title><p>(<bold>A</bold>) Arrows in the image on the right point to occasional artifacts arising during the expansion process. These rare artifacts generally occur closer to the center of the gel. (<bold>B</bold>) Arrows point to matched features in the pre-expansion and post-expansion images. These images were aligned using TurboReg as previously described (<xref ref-type="bibr" rid="bib12">Gustafsson, 2000</xref>). A comparison of the two images shows that the expanded sample was stretched anisotropically over length scales on the order of the size of the cell.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig2-figsupp2-v1.tif"/></fig><fig id="fig2s3" position="float" specific-use="child-fig"><label>Figure 2—figure supplement 3.</label><caption><title>Comparison of expansion error measurements between standard expansion microscopy (ExM) chemistry and Irgacure 2959 photoinitiation.</title><p>Consensus error curves were generated as described in <xref ref-type="fig" rid="fig2">Figure 2</xref> for ammonium persulfate (APS)/tetramethylethylenediamine (TEMED) gels (left) as compared to Irgacure 2959 gels (right). These data demonstrate that photoinitiation results in robust expansion and less error compared to the APS/TEMED chemistry in our high-throughput expansion microscopy (HiExM) method.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig2-figsupp3-v1.tif"/></fig><fig id="fig2s4" position="float" specific-use="child-fig"><label>Figure 2—figure supplement 4.</label><caption><title>High-throughput expansion microscopy (HiExM) performs robustly on cells plated at low and high confluency.</title><p>Example images of high (left) and low (center) confluent cultures of A549s. Consensus error curves (right) were calculated as described in <xref ref-type="fig" rid="fig2">Figure 2</xref>, and show minimal error within ~0.2 um (n=4 fields of view for each condition).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig2-figsupp4-v1.tif"/></fig></fig-group><p>We next benchmarked the performance of our platform relative to slide-based proExM (<xref ref-type="bibr" rid="bib26">Tillberg et al., 2016</xref>). Image distortion due to expansion was measured using a non-rigid registration (NRR) algorithm (<xref ref-type="bibr" rid="bib4">Chen et al., 2015</xref>) Prior to the application of HiExM, images of microtubule stained A549 cells were acquired using the Opera Phenix from 61 fields around the center of each well (<xref ref-type="fig" rid="fig2">Figure 2a</xref>). Cells were then expanded as above and 12 fields were imaged per well. Images from pre- and post-expansion were stitched together and the images for each well were then compared side-by-side to identify matched cells. Although we observed that gels did not maintain a fixed position pre- and post- expansion, close inspection of the images allowed us to align their orientations. Distortion was calculated using the root mean squared error (RMSE) of a two-dimensional deformation vector field by comparing microtubule morphology in the same cell before and after expansion in six to ten fields in each well across six arbitrarily selected wells (<xref ref-type="fig" rid="fig2">Figure 2c and d</xref>). The average percent error (up to 40 μm measurement length post-expansion) was plotted against the distance from the center of the gel (<xref ref-type="fig" rid="fig2">Figure 2e</xref>). Our analysis found no correlation (R<sup>2</sup>=0.003) between expansion error and distance from the gel center. In fact, we observed only a small number of outliers (&gt;3 s.d.) in any given well (&lt;2 instances per gel across six gels). These outliers are not expected to affect biological interpretation. The outliers, which are closer to the center of the gel, likely occur when the device post is not in full contact with the well surface, resulting in a higher volume of gel at the center that resists gel swelling under the device (<xref ref-type="fig" rid="fig2s2">Figure 2—figure supplement 2</xref>). Expansion error was also highly consistent when comparing wells across multiple plates (average = 3.68%), comparable to slide-based ExM (<xref ref-type="fig" rid="fig2">Figure 2f</xref>; <xref ref-type="bibr" rid="bib4">Chen et al., 2015</xref>; <xref ref-type="bibr" rid="bib26">Tillberg et al., 2016</xref>). We observed only a small number of image fields (7 of 58) with an average percent error above 6% (maximum 6.78%). Moreover, the calculated error showed that photoinitiation resulted in markedly lower spatial errors compared to APS and TEMED polymerization chemistry (<xref ref-type="fig" rid="fig2s3">Figure 2—figure supplement 3</xref>). Analyzing cell seeding densities also showed that cell confluency did not affect image distortion as measured by NRR (<xref ref-type="fig" rid="fig2s4">Figure 2—figure supplement 4</xref>).</p><p>We next measured expansion factors within individual gels, between gels, and across plates by manually measuring the distance between matched pairs of cell landmarks in FIJI before and after expansion. We found that the expansion factor was highly reproducible across different regions of the gel confirming robust expansion using our method (<xref ref-type="fig" rid="fig2">Figure 2g</xref>). The average expansion factor of gels sampled across three plates was 4.16+/-0.394 (<xref ref-type="fig" rid="fig2">Figure 2h</xref>), consistent with proExM (<xref ref-type="bibr" rid="bib26">Tillberg et al., 2016</xref>). We next compared the distributions of expansion factors across three well plates by ANOVA and found statistically significant differences between expansion factor distributions. Thus, while uniform within gels, the expansion factor is somewhat variable between gels and plates. We attribute these differences primarily to the small size of the gels, making them vulnerable to the effects of evaporation. This variability should be taken into consideration for studies where absolute length measurements between plates are important for biological interpretation. Collectively, these data show that the HiExM method results in reproducible nanoscale and isotropic expansion of cells within gels, across wells, and plates.</p><p>The ability to image cells at increased resolution using HiExM provides an opportunity to analyze nanoscale cellular features for a range of applications including cell phenotyping as well as drug and toxicology studies. As proof of concept, we analyzed the effects of the cardiotoxic chemotherapy agent doxorubicin (dox) on human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) cultured in 96-well plates (<xref ref-type="fig" rid="fig3">Figure 3a</xref>; <xref ref-type="bibr" rid="bib16">Johnson-Brbor and Dubey, 2023</xref>). Commonly used dox concentrations in in vitro cardiotoxicity studies range between 0.1 to 10 μM, depending on experimental goals (<xref ref-type="bibr" rid="bib20">Maillet et al., 2016</xref>; <xref ref-type="bibr" rid="bib29">Yu et al., 2020</xref>; <xref ref-type="bibr" rid="bib30">Zhao and Zhang, 2017</xref>; <xref ref-type="bibr" rid="bib25">Stefanova et al., 2023</xref>). Although studies largely focus on electrophysiology, structural changes at the cellular level also provide critical information for assessing cardiotoxicity. For example, changes in nuclear morphology as well as DNA damage are associated with cellular stress and apoptosis, which are commonly observed at high dox concentrations (&gt;200 nM) in in vitro studies using conventional microscopy (<xref ref-type="bibr" rid="bib20">Maillet et al., 2016</xref>; <xref ref-type="bibr" rid="bib29">Yu et al., 2020</xref>; <xref ref-type="bibr" rid="bib30">Zhao and Zhang, 2017</xref>; <xref ref-type="bibr" rid="bib25">Stefanova et al., 2023</xref>; <xref ref-type="bibr" rid="bib8">Gewirtz, 1999</xref>). In contrast, heart tissue is potentially exposed to lower dox concentrations in clinical treatments (<xref ref-type="bibr" rid="bib16">Johnson-Brbor and Dubey, 2023</xref>; <xref ref-type="bibr" rid="bib3">Chao et al., 2023</xref>; <xref ref-type="bibr" rid="bib9">Greene et al., 1983</xref>) Because HiExM has the sensitivity to detect nanoscale cellular features, we compared nuclei using Hoechst signal intensity in CMs treated with 1 nM, 10 nM, 100 nM, and 1 µM dox after 24 hr compared with DMSO (<xref ref-type="fig" rid="fig3">Figure 3b</xref>). Although we did not observe a significant change in overall nuclear morphology (<xref ref-type="fig" rid="fig3s1">Figure 3—figure supplement 1</xref>), images showed increasing Hoechst density at the nuclear periphery in a dox concentration-dependent manner.</p><fig-group><fig id="fig3" position="float"><label>Figure 3.</label><caption><title>High-throughput expansion microscopy (HiExM) shows altered nuclear morphology of cardiomyocytes treated with low doses of doxorubicin.</title><p>(<bold>a</bold>) hiPSC-CMs imaged post-expansion in HiExM. (<bold>b</bold>) Example images of human induced pluripotent stem cell derived cardiomyocyte (hiPSC-CM) nuclei after dox treatment for 24 hr before (top) and after (bottom) expansion. (<bold>c</bold>) Example images of hiPSC-CM nuclei taken before (top) and after (bottom) expansion. (<bold>d</bold>) Heatmaps of nuclei in (<bold>c</bold>) showing pixel groupings for subsequent analysis. Heatmaps were generated from the image mask after dilation, such that the outer edge represents a contour just beyond the nuclear periphery. (<bold>e</bold>) Relative Hoechst intensity plotted as a function of pixel position relative to the edge of the dilated mask in pre- (top) and post- (bottom) expansion nuclei. Colored curves represent dox concentrations or DMSO (ctrl). Shaded regions represent SEM for n=56, 71, 64, 92, and 62 nuclei in the pre-expansion images and n=4 replicates in the expanded case (118, 111, 110, 113, and 77 nuclei analyzed for DMSO control, 1 nM, 10 nM, 100 nM, and 1 µM Dox, respectively). (<bold>f</bold>) Insets of plots in (<bold>e</bold>) highlighting the nuclear periphery. (<bold>g</bold>) Rate-of-change analysis of curves for pre- (left) and post- (right) expansion images. Outer edge values were obtained by determining the maximum values of the derivatives for each condition, and inner edge values were obtained by determining the minimum values of the derivatives within the domain 0–0.4. (<bold>h</bold>) Curvature analysis for pre- (left) and post- (right) expansion data. Values represent the minima of the second derivative for curves within the domain 0–0.4. (<bold>i</bold>) Average Hoechst intensities are plotted as gradients for each dox concentration. Scale bar represents a 10 percent distance from the edge of the nucleus to the center. Error bars represent SEM as in (<bold>e</bold>). * denotes significance from an independent two-sample t-test (p&lt;0.05). *Scale bar represents biological scale assuming 4 x expansion.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig3-v1.tif"/></fig><fig id="fig3s1" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 1.</label><caption><title>Nuclear volume/area analysis of Doxorubicin-treated cardiomyocytes before and after expansion.</title><p>Nuclear area (top left) and roundness (top right) were measured in pre-expanded cardiomyocytes. Nuclear volume (bottom left) and sphericity (bottom right) were measurable in expanded cardiomyocytes due to the increased axial resolution of high-throughput expansion microscopy (HiExM). These measurements were performed in Harmony (Perkin Elmer). Error bars represent SEM and sample sizes are the same as in <xref ref-type="fig" rid="fig3">Figure 3</xref> for both unexpanded and expanded cells. * denotes significance from an ANOVA (*p&lt;0.05, **p&lt;0.005, ***p&lt;0.0005).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig3-figsupp1-v1.tif"/></fig><fig id="fig3s2" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 2.</label><caption><title>Nuclear edge analysis at different optical slices of Doxorubicin-treated cardiomyocytes.</title><p>Defining the optical plane that intersects the nucleus at a right angle in the z-axis is necessary for nuclear edge analysis. Orthogonal view of a DMSO-treated nucleus. Colored lines represent optical slices corresponding to the analysis results below the image (top). Absolute signal intensity as a function of relative position at 12 different z-slices using the ‘ring-scan’ analysis (bottom left). Relative signal intensity as a function of relative position at the same 12 z-slices using the same analysis (bottom right).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig3-figsupp2-v1.tif"/></fig><fig id="fig3s3" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 3.</label><caption><title>Line-scan analysis of Doxorubicin-treated cardiomyocytes.</title><p>An orthogonal line-scan analysis shows similar results in <xref ref-type="fig" rid="fig3">Figure 3</xref>. Briefly, the centroid of the nucleus was found and 180 lines were drawn through the image at one-degree increments. The pixel intensities from these scans were then interpolated (linear) to normalize their lengths to 500. The scans were then cut in half, the second half of the scans were mirrored, and the two halves were averaged to give a representation of Hoechst intensity as a function of distance from the center of the nucleus. Shaded region represents SEM as in <xref ref-type="fig" rid="fig3">Figure 3e</xref>. First and second derivatives were calculated as in <xref ref-type="fig" rid="fig3">Figure 3g and h</xref>. Error bars represent SEM, asterisks denote significance from an independent two-sample t-test (p&lt;0.05).</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig3-figsupp3-v1.tif"/></fig><fig id="fig3s4" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 4.</label><caption><title>Comparison of derivative curves from <xref ref-type="fig" rid="fig3">Figure 3</xref> and <xref ref-type="fig" rid="fig3s3">Figure 3—figure supplement 3</xref>.</title><p>Curves on the left are described in <xref ref-type="fig" rid="fig3">Figure 3</xref> (ring scan), and on the right are described in <xref ref-type="fig" rid="fig3s3">Figure 3—figure supplement 3</xref> (line-scan). Top eight curves represent pre-expansion, bottom eight curves represent post-expansion analyses.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig3-figsupp4-v1.tif"/></fig><fig id="fig3s5" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 5.</label><caption><title>Nuclear edge analysis of H<sub>2</sub>O<sub>2</sub>-treated cardiomyocytes.</title><p>Example images of cardiomyocyte nuclei across different conditions and associated curves (top). Analyses were carried out as in <xref ref-type="fig" rid="fig3">Figure 3</xref>. First derivative inflection-point-slope extremes (middle) show a significant reduction at the outer side only between the control and the highest concentration of hydrogen peroxide. Second derivative minima (bottom) show no significant differences between conditions.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig3-figsupp5-v1.tif"/></fig><fig id="fig3s6" position="float" specific-use="child-fig"><label>Figure 3—figure supplement 6.</label><caption><title>Example of a cell expanded in high-throughput expansion microscopy (HiExM) using Photo-expansion microscopy (ExM) gel chemistry.</title><p>Photo-ExM does not require an anoxic environment for gel deposition and polymerization, improving the ease of use of HiExM. Mitochondria were stained with an Alexa 647 conjugated secondary antibody, demonstrating that HiExM is compatible with additional fluorophores when combined with Photo-ExM.</p></caption><graphic mimetype="image" mime-subtype="tiff" xlink:href="elife-96025-fig3-figsupp6-v1.tif"/></fig><media mimetype="video" mime-subtype="gif" xlink:href="elife-96025-fig3-video1.gif" id="fig3video1"><label>Figure 3—animation 1.</label><caption><title>Animation of nuclear periphery analysis employed in <xref ref-type="fig" rid="fig3">Figure 3</xref>.</title><p>This animation depicts an analysis of an example nucleus, where each frame is a single iteration of the analysis. The red ring overlay indicates the current group of pixels being averaged. The mean intensity of these pixels is plotted on the y-axis in the graph on the right, with the x-axis representing the progression of iterations from the outer edge of the nucleus to its center.</p></caption></media></fig-group><p>To quantify this effect, we measured the gradient slope of Hoechst intensity around the nuclear periphery. To this end, we masked 529 nuclei from the background in dox-treated and control samples (<xref ref-type="fig" rid="fig3">Figure 3c</xref>). We selected a single optical slice that intersected the nucleus perpendicularly along the z-axis for our analysis to avoid an out-of-focus signal at the nuclear edge (<xref ref-type="fig" rid="fig3s2">Figure 3—figure supplement 2</xref>). To account for irregular nuclear shapes, we iteratively grouped pixels into rings for each nucleus starting with the edge of the mask (<xref ref-type="fig" rid="fig3">Figure 3d</xref>). The mask is dilated outward from the edge of the nucleus to include a background reading as a reference. The average pixel intensity value for each ring represents the average Hoechst intensity as a function of the relative distance from the edge of the nucleus to its center (<xref ref-type="fig" rid="fig3">Figure 3e</xref>, <xref ref-type="video" rid="fig3video1">Figure 3—animation 1</xref>). Notably, HiExM revealed a peak of Hoechst intensity at the edge of the nucleus that is not resolved in pre-expansion images (<xref ref-type="fig" rid="fig3">Figure 3f</xref>). A line-scan-based analysis showed the same trend (<xref ref-type="fig" rid="fig3s3">Figure 3—figure supplement 3</xref>). To further evaluate these differences, we next calculated the first derivative of each curve and found the maximum and minimum values, which correspond to the gradient slopes on either side of the peak (<xref ref-type="fig" rid="fig3">Figure 3g</xref>, <xref ref-type="fig" rid="fig3s4">Figure 3—figure supplement 4</xref>). In this case, a higher magnitude of gradient slope reflects a ‘sharper’ transition from the nuclear edge to the background (outside) or from the nuclear edge to the nucleoplasm (inside). Post-expansion, the gradient slopes on both sides of the peak showed a significant increase at dox concentrations as low as 10 nM compared to DMSO, whereas no trend is observed in pre-expansion images (<xref ref-type="fig" rid="fig3">Figure 3g</xref>).</p><p>In addition to gradient slopes at the nuclear edge, we also quantified the pattern of Hoechst signal at the nuclear edge by calculating the curvature of the peak using the second derivative (<xref ref-type="fig" rid="fig3">Figure 3h</xref>). These data also showed a significant increase in Hoechst intensity at 10 nM dox compared to DMSO, whereas no significant difference is observed using conventional confocal microscopy (<xref ref-type="fig" rid="fig3">Figure 3i</xref>). We note that, for both the outer gradient slope and peak curvature, values decrease from 100 nM to 1 µM dox, consistent with increased chromatin condensation associated with apoptosis typically observed at higher dox concentrations (<xref ref-type="bibr" rid="bib30">Zhao and Zhang, 2017</xref>; <xref ref-type="bibr" rid="bib27">Toné et al., 2007</xref>). In contrast, CMs treated with increasing concentrations of H<sub>2</sub>O<sub>2</sub>, another cellular stressor, did not show similar differences in Hoechst patterns (<xref ref-type="fig" rid="fig3s5">Figure 3—figure supplement 5</xref>). Although direct evidence specifically linking dox to increased DNA condensation at the nuclear periphery is limited, the known pro-apoptotic effects of dox strongly suggest that our observations correlate with these changes (<xref ref-type="bibr" rid="bib20">Maillet et al., 2016</xref>; <xref ref-type="bibr" rid="bib30">Zhao and Zhang, 2017</xref>; <xref ref-type="bibr" rid="bib21">Mobaraki et al., 2017</xref>). Thus, we suggest that HiExM can detect early alterations in response to dox treatment using the Hoechst signal, setting the stage for further investigation to understand the consequences across a range of drugs and conditions. Overall, our analysis demonstrates the ability of HiExM to detect subtle cellular changes compared to standard confocal microscopy that could improve the resolution of drug screening approaches.</p></sec><sec id="s3" sec-type="discussion"><title>Discussion</title><p>Our work demonstrates that HiExM is a simple and inexpensive method that can increase the throughput of expansion microscopy. Another recent method also reports a scalable ExM-based method with comparable throughput, albeit this approach requires the use of a custom cell culture microplate and manual imaging (<xref ref-type="bibr" rid="bib28">Xie et al., 2023</xref>) Our device is fabricated with CNC milling, a common fabrication technique available in most academic settings, making our method widely accessible. The HiExM device can also be produced by injection molding which can further extend its accessibility and distribution in research settings. We have also adapted our device to fit cell culture plates of varying dimensions including a 24-well plate which can accommodate greater expansion and significantly higher resolution (<xref ref-type="fig" rid="fig1s7">Figure 1—figure supplement 7</xref>; <xref ref-type="bibr" rid="bib5">Damstra et al., 2022</xref>). Moreover, the use of a photo-active gel solution enabled consistent expansion in our HiExM workflow. In this work, we found that the use of photoinitiation with irgacure caused signal loss for to varying degrees depending on the fluorophore; coupled with the signal dilution inherent to the expansion process, signal intensity is an important consideration when using HiExM. Our platform is amenable to other photo-active expansion chemistries such as the Photo-ExM chemistry which does not require CF dyes or an anoxic environment (<xref ref-type="fig" rid="fig3s6">Figure 3—figure supplement 6</xref>; <xref ref-type="bibr" rid="bib2">Blatchley et al., 2022</xref>; <xref ref-type="bibr" rid="bib10">Günay et al., 2023</xref>).</p><p>Another advantage of HiExM is that it is fully compatible with autonomous imaging, allowing data acquisition of thousands of cells within a day. HiExM achieved a resolution of ~115 nm in a 96-well culture plate using a 63 x water immersion objective with a 1.15 numerical aperture. By employing microscopes with a higher numerical aperture, we expect our platform can achieve significantly greater resolution. We also show that HiExM error measurements are similar to proExM and suggest that expansion distortions should be considered for robust data interpretation. Recent innovative work that developed a microplate-based ExM protocol maintains hydrogel geometry and orientation improves coordinate-based imaging to accurately assess distortions with ease (<xref ref-type="bibr" rid="bib24">Seehra et al., 2023</xref>). Another recent work used micropatterning to apply expandable protein grids to coverslips for local expansion factor measurement. This method could be adapted to HiExM to enable expansion measurements in large datasets where non-rigid registration is impractical (<xref ref-type="bibr" rid="bib6">Damstra et al., 2023</xref>) Taken together, HiExM is an accessible nanoscale imaging platform designed for scalable sample preparation and autonomous imaging, broadening the use of ExM in biological research and pharmaceutical applications.</p></sec><sec id="s4" sec-type="materials|methods"><title>Materials and methods</title><sec id="s4-1"><title>Cell culture</title><p>Human A549 cells were maintained in culture at a density between 2×10<sup>3</sup> and 1×10<sup>4</sup> cells/cm<sup>2</sup> in DMEM modified with 10% fetal bovine serum and 1% penicillin-streptomycin. Glass and plastic 96-well plates (Cellvis, P96-1.5H-N or P96-1.5P) were seeded at ~1×10<sup>4</sup> and 7×10<sup>4</sup> cells/cm<sup>2</sup> for expansion experiments.</p><p>Induced pluripotent stem cell-derived cardiomyocytes were purchased from Cellular Dynamics and cultured on glass-bottom 96-well plates at 30,000 cells/well. For drug treatment, CMs were plated on gelatin for 7 d (Cellular Dynamics) prior to drug treatment and incubated with varying concentrations of Doxorubicin (Tocris 2252) for 24 hr prior to fixation and subsequent sample preparation.</p></sec><sec id="s4-2"><title>Immunofluorescence</title><p>Briefly, cells were fixed with 4% PFA for 15 minutes at room temperature and then blocked (1% bovine serum albumin and 0.1% Triton X100 in PBS) for 1 hr. Cells were then incubated for 1 hr at 37 °C with primary antibodies in a blocking solution followed by incubation with secondary antibodies in a blocking solution for 1 hr at 37 °C. Cells were washed between each stage in PBS three times at 0-, 5-, and 10 min intervals.</p><table-wrap id="inlinetable1" position="anchor"><table frame="hsides" rules="groups"><thead><tr><th align="left" valign="bottom">Primary Antibodies</th><th align="left" valign="bottom">Vendor</th><th align="left" valign="bottom">Cat. Number</th><th align="left" valign="bottom">Concentration</th></tr></thead><tbody><tr><td align="left" valign="bottom">Monoclonal anti-alpha-Tubulin antibody</td><td align="left" valign="bottom">MilliporeSigma</td><td align="left" valign="bottom">T5168</td><td align="char" char="." valign="bottom">1:1000</td></tr><tr><td align="left" valign="bottom">Cardiac troponin T (TNNT2) Rabbit mAb</td><td align="left" valign="bottom">ABclonal</td><td align="left" valign="bottom">A4914</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">Monoclonal Anti-α-Actinin (Sarcomeric) antibody</td><td align="left" valign="bottom">MilliporeSigma</td><td align="left" valign="bottom">A7811</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">Secondary Antibodies</td><td align="left" valign="bottom">Vendor</td><td align="left" valign="bottom">Cat. Number</td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">CF633 Chicken Anti-Mouse IgG (H+L)</td><td align="left" valign="bottom">Biotium</td><td align="char" char="." valign="bottom">20222</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">CF568 Donkey Anti-Rabbit IgG (H+L)</td><td align="left" valign="bottom">Biotium</td><td align="char" char="." valign="bottom">20098</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">CF350 Goat Anti-Mouse IgG (H+L)</td><td align="left" valign="bottom">Biotium</td><td align="char" char="ndash" valign="bottom">20140–1</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">CF488 Goat Anti-Mouse IgG (H+L)</td><td align="left" valign="bottom">Biotium</td><td align="char" char="ndash" valign="bottom">20010–1</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">CF543 Goat Anti-Mouse IgG (H+L)</td><td align="left" valign="bottom">Biotium</td><td align="char" char="ndash" valign="bottom">20306–1</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">CF555 Goat Anti-Mouse IgG (H+L)</td><td align="left" valign="bottom">Biotium</td><td align="char" char="ndash" valign="bottom">20030–1</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">CF568 Goat Anti-Mouse IgG (H+L)</td><td align="left" valign="bottom">Biotium</td><td align="char" char="ndash" valign="bottom">20100–1</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">CF633 Goat Anti-Mouse IgG (H+L)</td><td align="left" valign="bottom">Biotium</td><td align="char" char="ndash" valign="bottom">20120–1</td><td align="char" char="." valign="bottom">1:500</td></tr><tr><td align="left" valign="bottom">Stains</td><td align="left" valign="bottom">Vendor</td><td align="left" valign="bottom">Cat. Number</td><td align="left" valign="bottom"/></tr><tr><td align="left" valign="bottom">Hoechst 33342</td><td align="left" valign="bottom">ThermoFisher Scientific</td><td align="char" char="." valign="bottom">62249</td><td align="char" char="." valign="bottom">1:5000</td></tr></tbody></table></table-wrap></sec><sec id="s4-3"><title>HiExM device fabrication</title><sec id="s4-3-1"><title>96-well plate HiExM devices</title><p>HiExM devices were fabricated from polysulfone (McMaster-Carr 86735K74) using a Trak DPM2 CNC milling machine using the design provided in the supplementary files.</p></sec><sec id="s4-3-2"><title>24-well plate HiExM devices</title><p>24-well plate HiExM devices were fabricated by Proto Labs with injection molding. The device design can be found using the following link:</p></sec><sec id="s4-3-3"><title>Measurement of volume collected by devices</title><p>To estimate the volume of liquid collected by the HiExM device, the mass of water was measured on a sartorius TE64 before and after dipping the device into the reservoir. The difference in mass was measured 18 times for an average collected mass of 2806 ug +/-482 ug. The average total mass retained by the device was divided by 12 (the number of posts per device) yielding an estimate of 234 ug or 234 nL per post.</p></sec></sec><sec id="s4-4"><title>HiExM workflow</title><sec id="s4-4-1"><title>Irgacure workflow</title><p>Cells were fixed with 4% paraformaldehyde (PFA) and immunostained as described above and treated with 50 µM (A549 cells) or 100 µM (cardiomyocytes) Acryloyl-X, SE (6-((Acryloyl)amino)hexanoic acid, succinimidyl ester abbreviated as AcX (Invitrogen A20770)) overnight at 4 °C. Cells were then washed twice with PBS, once with DI water, and the remaining liquid was gently aspirated from the wells. Gel solution composed of 4.04 M sodium acrylate (AK Scientific R624), 0.506 M acrylamide (MilliporeSigma A4058), 0.00934 M n, n’-methylenebisacrylamide (MilliporeSigma M1533), 1.84 M sodium chloride (Invitrogen AM9759) and 1.45 X PBS 1 mL (Invitrogen AM9625) was prepared in a light-protected tube. 1-[4-(2-Hydroxyethoxy)-phenyl]–2-hydroxy-2-methyl-1-propane-1-one (Irgacure 2959, MilliporeSigma 410896) was dissolved in DMSO at a concentration of 1.64 M and this solution was mixed with the gel solution to a final Irgacure 2959 concentration of 0.0328 M at room temperature. The HiExM protocol was performed in a glove bag purged two times with dry nitrogen (MilliporeSigma Z530112). The gel solution was poured onto an absorbent pad at room temperature to form a fluid reservoir. Devices were dipped into the gel solution and immediately inserted into the well plate. The plate was then irradiated for 60 seconds with UVA light using a Uvitron Portaray curing lamp placed 20 inches beneath the plate (Uvitron International UV2270). Approximately 100 µL of Proteinase K (NEB P8107S) digestion solution was added to each gel-containing well and incubated for ~6 hr at room temperature. After digestion, Hoechst 33324 (Fisher Scientific #62249) in DI water (1:5000 dilution) was added to wells for 5 min, then the 96-well plate was submerged in ~4 liters of DI water overnight under constant agitation while the gels were held in place by the device. Finally, the plate was removed from the water bath, and devices were removed from the well plate for imaging. For each well, excess water was aspirated and two drops of mineral oil was added to secure the expanded gel within the well.</p></sec><sec id="s4-4-2"><title>APS/TEMED workflow</title><p>Fixed cells were stained using standard immunofluorescence protocols and treated with anchor solution (6-((Acryloyl)amino)hexanoic acid, abbreviated AcX) (Invitrogen A20770) for at least 3 hr at RT prior to gelation according to standard ExM protocols (<xref ref-type="bibr" rid="bib1">Asano et al., 2018</xref>). Cells were then washed twice with PBS (Invitrogen AM9625) and aspirated dry. Two 2 mL vials of stock X, TEMED (Bio-Rad 1610800), and APS (Millipore Sigma A7460) (40 g/100 mL) were prepared and placed on ice with an aluminum block in a nitrogen glove bag (MilliporeSigma Z530112). The glove bag was purged and backfilled with dry nitrogen twice. 40 uL of APS or TEMED were added to 2 mL of stock X followed by gentle mixing. Both stock X solutions (one containing APS and the other containing TEMED) were poured onto separate absorbent pads. The first device was dipped into the TEMED-containing solution, and stamped into a set of wells, and the process was repeated with the same device to load droplets of TEMED harboring stock X in all wells. Five separate devices were then dipped in the APS-containing solution, then immediately inserted into rows of the well plate. The plate was left on ice for 15 min, then inverted and placed in a glove bag. The underside of the well plate was covered in ~2 mL of water (for thermal conduction) and ~50 °C water bag was laid over the top of the inverted well plate to warm the gels for 5 min. The well plate was removed and 100 uL of digestion solution containing proteinase K (NEB P8107S) was added to each gel-containing well overnight at room temperature. The following day, the well plate was submerged in ~4 liters of DI water under constant agitation for 2 hr, exchanging the water after the first 2 hr. Finally, the plate was removed from the water bath and devices removed from the well plate. Gentle aspiration of the remaining water from the well followed by the addition of ~100 uL of heavy mineral oil over the gel was sufficient to restrict gel movement to allow for automated imaging in a 96-well plate.</p></sec><sec id="s4-4-3"><title>Photo-ExM workflow</title><p>Photo-ExM gel solutions were prepared as previously described (<xref ref-type="bibr" rid="bib2">Blatchley et al., 2022</xref>; <xref ref-type="bibr" rid="bib10">Günay et al., 2023</xref>). The protocol for device use with Photo-ExM is the same as the Irgacure protocol with two exceptions. First, gel polymerization in Photo-ExM is not oxygen-inhibited, so the protocol does not require a glove bag. Second, Gel solutions (2 µL) are pipetted into the wells of a custom 3D printed chip (Supplementary File PhotoExM_Gel_Reservoir.SLDPRT) designed for small-volume gel solution storage in HiExM. HiExM devices are applied to the loaded chip such that each post of the device collects gel solution from one of the loaded wells.</p></sec></sec><sec id="s4-5"><title>Image acquisition</title><p>Confocal imaging was performed on an Opera Phenix imaging system (PerkinElmer). For NRR analysis, pre-expansion images were acquired with a 63 x water objective (NA 1.15) in stacks of six planes spaced 0.5 microns apart and post-expansion images of the same plate were acquired using a 20 x water objective (NA 1.0) in stacks of 50 planes spaced one micron apart. Prior to expansion, 61 tiled fields at the center of each well were imaged at 63 x to capture cells that would be incorporated into the gel. After expansion, 12 fields in a cross pattern were imaged at 20 x to capture a representative set of images for each gel across multiple wells. Based on our analysis, the centers of gels in HiExM should be avoided in imaging as these regions can include cells that are torn and disfigured due to detaching the gels from the device. <xref ref-type="video" rid="fig1video1 fig1video2">Figure 1—animations 1; 2</xref> were obtained on an EVOS M5000 epifluorescence microscope (Thermo Fisher Scientific).</p><p>For drug treatment experiments, expanded images were acquired at 63 x magnification using the PreciScan plugin. First, each well was imaged for Hoechst at 5 x in 4 quadrants to cover the full footprint of the well. An analysis in Harmony determined the coordinates of each nucleus in three dimensions and selected a subset of those coordinates to image again at 63 x. The sample sizes for each condition in expanded samples were as follows: 118, 111, 110, 113, and 77 cells for DMSO control, 1 nM, 10 nM, 100 nM, and 1 µM Doxorubuicn (dox), respectively across the four independent experiments. Pre-expansion images were acquired at 63 x magnification without the PreciScan plugin. Sample sizes for each condition in pre-expansion samples were as follows: 56, 71, 64, 92, and 62 for DMSO control, 1 nM, 10 nM, 100 nM, and 1 µM Doxorubuicn (dox), respectively.</p><p>HiExM samples were imaged on the Opera Phenix at 63 x with the following parameters: 100% laser power for all channels; 200 ms exposure for Hoechst, 500–1000+ ms exposure for other channels depending on the strength of the stain and the laser; 60 optical sections with 1- micron spacing; and 4–20 fields of view per well depending on the cell density and sample size requirements. Therefore, imaging one full 96-well plate (60 wells total to avoid outer wells) requires 3 to 64 hr depending on the combination of parameters used.</p></sec><sec id="s4-6"><title>Distortion and expansion factor analysis</title><sec id="s4-6-1"><title>Pre-expansion/post-expansion image curation</title><p>Prior to applying HiExM, 61 fields of view were imaged at 63 x centered in each well. After expansion, gels were imaged at 20 x in 12 fields of view centered in each well in a cross pattern as in <xref ref-type="fig" rid="fig2">Figure 2b</xref>. All images were converted to maximum projections. Images from pre-expansion and post-expansion were stitched and examined to find matching cells. For fields of view with matching cells, the corresponding maximum projections for the individual fields of view in pre- and post-expansion were used for subsequent analyses. This image curation is the rate-limiting step in our NRR and expansion factor data analyses due to the time required to identify matched cells.</p></sec></sec><sec id="s4-7"><title>Non-rigid registration</title><p>Non-rigid registration was performed to measure isotropic expansion within individual gels and across gels. For analysis represented in <xref ref-type="fig" rid="fig2">Figure 2d</xref>, all fields of view were used in which a cell or group of cells could be identified in both the pre-expansion and the post-expansion image sets. The distance from the center of the analyzed field of view to the center of the well was measured in the pre-expansion image set. For <xref ref-type="fig" rid="fig2">Figure 2f and a</xref> single field of view near the periphery of the gel was arbitrarily chosen to represent the whole gel. Non-rigid registration was performed using a custom MATLAB analysis pipeline as described (<xref ref-type="bibr" rid="bib4">Chen et al., 2015</xref>). Briefly, pre and post-expansion images are coarsely aligned using the TurboReg plugin for ImageJ (<xref ref-type="bibr" rid="bib15">Jiang et al., 2021</xref>). This pair of outputs is then histogram normalized and masks are generated to exclude regions with no features by applying a Gaussian blur. B-spline-based registration package in MATLAB was used to do non-rigid registration between the images. This procedure was performed on image fields measuring 400px×400px for all analyses.</p><p>The resulting data from a non-rigid registration analysis is a curve that represents measurement error as a function of measurement length. To synthesize these curves into single points (as represented in <xref ref-type="fig" rid="fig2">Figure 2c–f</xref>), The average percent error up to 40 µm measurement length (as measured after expansion) was used. The average percent error is represented as the mean of the ratios of error to measurement length for each individual data point in the error curve up to 40 µm measurement length.</p></sec><sec id="s4-8"><title>Expansion factor</title><p>To calculate expansion factors, images taken before and after the expansion of the same cell or group of cells were compared. In both images, the distance between two easily identifiable features was measured manually in FIJI, and the ratio of those measurements was used to calculate the expansion factor.</p></sec><sec id="s4-9"><title>Nuclear periphery analysis</title><p>Image stacks of Hoechst-stained nuclei were compiled and the midplane of each nucleus was manually identified as the plane with the largest nuclear cross-sectional area. Images containing no nucleus or clearly distorted nuclei were omitted from the analysis. A threshold was applied to midplane images to generate masks. These masks as well as their respective raw midplane images were further analyzed using a custom Python script as follows: First, the mask was dilated to encompass the background signal outside of the nucleus. Second, the pixels at the edge of the mask were identified and their position and intensity information were stored. Third, pixels in the 4-neighborhood of each pixel from the outer-edge pixel group were identified and their position and intensity information stored (note that only pixels inside the boundary defined by the outer-edge pixel group were stored in this way). This third step was iterated for each new ‘ring’ until all pixels in the dilated mask were grouped. Finally, the mean pixel intensity values of each group were used and the list of mean values was run through linear interpolation to arrive at a list of length 500. To determine the inflection-point slopes of the resulting curves, the first derivative of each curve was calculated using the finite difference approximation. To determine the curvature at the peak intensities of each curve, the second derivative was calculated in the same way. Significance was determined using a two-sample t-test (p&lt;0.05).</p></sec></sec></body><back><sec sec-type="additional-information" id="s5"><title>Additional information</title><fn-group content-type="competing-interest"><title>Competing interests</title><fn fn-type="COI-statement" id="conf1"><p>John H Day is an inventor on a provisional patent filed for the HiExM device (MIT-064US(02))</p></fn><fn fn-type="COI-statement" id="conf2"><p>Catherine M Della Santina is an inventor on a provisional patent filed for the HiExM device. (MIT-064US(02))</p></fn><fn fn-type="COI-statement" id="conf3"><p>Pema Maretich is an inventor on a provisional patent filed for the HiExM device.(MIT-064US(02))</p></fn><fn fn-type="COI-statement" id="conf4"><p>Alex L Auld is an inventor on a provisional patent filed for the HiExM device.(MIT-064US(02))</p></fn><fn fn-type="COI-statement" id="conf5"><p>No competing interests declared</p></fn><fn fn-type="COI-statement" id="conf6"><p>Edward S Boyden is an inventor on a provisional patent filed for the HiExM device.(MIT-064US(02))</p></fn><fn fn-type="COI-statement" id="conf7"><p>Laurie A Boyer is an inventor on a provisional patent filed for the HiExM device.(MIT-064US(02))</p></fn></fn-group><fn-group content-type="author-contribution"><title>Author contributions</title><fn fn-type="con" id="con1"><p>Conceptualization, Data curation, Software, Formal analysis, Validation, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing</p></fn><fn fn-type="con" id="con2"><p>Software, Formal analysis, Visualization, Writing – original draft</p></fn><fn fn-type="con" id="con3"><p>Conceptualization</p></fn><fn fn-type="con" id="con4"><p>Conceptualization</p></fn><fn fn-type="con" id="con5"><p>Investigation, Methodology</p></fn><fn fn-type="con" id="con6"><p>Resources, Software</p></fn><fn fn-type="con" id="con7"><p>Resources, Supervision, Funding acquisition</p></fn><fn fn-type="con" id="con8"><p>Supervision, Funding acquisition, Project administration</p></fn></fn-group></sec><sec sec-type="supplementary-material" id="s6"><title>Additional files</title><supplementary-material id="mdar"><label>MDAR checklist</label><media xlink:href="elife-96025-mdarchecklist1-v1.pdf" mimetype="application" mime-subtype="pdf"/></supplementary-material></sec><sec sec-type="data-availability" id="s7"><title>Data availability</title><p>Solidworks files for our devices as well as code for our analysis are available at the following link: <ext-link ext-link-type="uri" xlink:href="https://github.com/lboyerlab/hiExM_Supplementary_Files">https://github.com/lboyerlab/hiExM_Supplementary_Files</ext-link> (copy archived at <xref ref-type="bibr" rid="bib17">lboyerlab, 2024</xref>). Raw data produced from this work are accessible through Dryad (<ext-link ext-link-type="uri" xlink:href="https://doi.org/10.5061/dryad.fbg79cp57">https://doi.org/10.5061/dryad.fbg79cp57</ext-link>).</p><p>The following dataset was generated:</p><p><element-citation publication-type="data" specific-use="isSupplementedBy" id="dataset1"><person-group person-group-type="author"><name><surname>John</surname><given-names>D</given-names></name></person-group><year iso-8601-date="2024">2024</year><data-title>Data for: High-throughput expansion microscopy enables scalable super-resolution imaging</data-title><source>Dryad Digital Repository</source><pub-id pub-id-type="doi">10.5061/dryad.fbg79cp57</pub-id></element-citation></p></sec><ack id="ack"><title>Acknowledgements</title><p>We thank Paul Tillberg and members of the Boyer and Boyden labs, especially Shiwei Wang, Chi Zhang, and Asmamaw Wassie for helpful discussions. We also thank the Edgerton Student Shop and Mark Belanger for assisting in the fabrication of devices. We thank the Center for the Development of Therapeutics at the Broad Institute and acknowledge funding through the S10 grant NIH OD-026839–01. This material is based upon work supported by the National Science Foundation Graduate Research Fellowship under Grant No. 2141064 and 1122374 to JHD and TS, respectively. This work is supported by NIH EB024261, NIH 1R01AG070831, HHMI, NIH 1R01MH123403, NIH R01MH124606, and NIH 1R56AG069192 to ESB. This research is supported in part by the National Research Foundation, Prime Minister’s Office, Singapore under its Campus for Research Excellence and Technological Enterprise (CREATE) programme, through Singapore MIT Alliance for Research and Technology (SMART): Critical Analytics for Manufacturing Personalised-Medicine (CAMP) Inter-Disciplinary Research Group. ESB acknowledges funding from Lisa Yang, Lore McGovern, and John Doerr. 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article-type="editor-report" id="sa0"><front-stub><article-id pub-id-type="doi">10.7554/eLife.96025.4.sa0</article-id><title-group><article-title>eLife Assessment</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Stasevich</surname><given-names>Timothy J</given-names></name><role specific-use="editor">Reviewing Editor</role><aff><institution>Colorado State University</institution><country>United States</country></aff></contrib></contrib-group><kwd-group kwd-group-type="evidence-strength"><kwd>Convincing</kwd><kwd>Solid</kwd></kwd-group><kwd-group kwd-group-type="claim-importance"><kwd>Important</kwd></kwd-group></front-stub><body><p>This <bold>important</bold> study develops a high throughput version of expansion microscopy that can be performed in 96-well plates. The engineered technology is <bold>convincing</bold> and compatible with standard microplates and automated microscopes and thus will be of broad interest. The application to hiPCS-derived cardiomyocytes treated with doxorubicin provides a <bold>solid</bold> proof-of-concept demonstrating the potential for high-throughput analysis.</p></body></sub-article><sub-article article-type="referee-report" id="sa1"><front-stub><article-id pub-id-type="doi">10.7554/eLife.96025.4.sa1</article-id><title-group><article-title>Reviewer #1 (Public review):</article-title></title-group><contrib-group><contrib contrib-type="author"><anonymous/><role specific-use="referee">Reviewer</role></contrib></contrib-group></front-stub><body><p>Summary</p><p>In this manuscript, Day et al. present a high-throughput version of expansion microscopy to increase the throughput of this well-established super-resolution imaging technique. Through technical innovations in liquid handling with custom-fabricated tools and modifications to how the expandable hydrogels are polymerized, the authors show robust ~4-fold expansion of cultured cells in 96-well plates. They go on to show that HiExM can be used for applications such as drug screens by testing the effect of doxorubicin on human cardiomyocytes. Interestingly, the effects of this drug on changing DNA organization were only detectable by ExM, demonstrating the utility of HiExM for such studies.</p><p>Overall, this is a very well-written manuscript presenting an important technical advance that overcomes a major limitation of ExM - throughput. As a method, HiExM appears extremely useful and the data generally support the conclusions.</p><p>Strengths</p><p>Hi-ExM overcomes a major limitation of ExM by increasing the throughput and reducing the need for manual handling of gels. The authors do an excellent job of explaining each variation introduced to HiExM to make this work and thoroughly characterize the impressive expansion isotropy. The dox experiments are generally well-controlled and the comparison to an alternative stressor (H2O2) significantly strengthens the conclusions.</p><p>Weaknesses</p><p>(1) It is still unclear to me whether or not cells that do not expand remain in the well given the response to point 1. The authors say the cells are digested and washed away but then say that there is a remaining signal from the unexpanded DNA in some cases. I believe this is still a concern that potential users of the protocol should be aware of.</p><p>Editor note: this comment has been addressed in the latest version.</p><p>(2) Regarding the response to point 9, I think this information should be included in the manuscript, possibly in the methods. It is important for others to have a sense of how long imaging may take if they were to adopt this method.</p><p>Editor note: this comment has been addressed in the latest version.</p></body></sub-article><sub-article article-type="referee-report" id="sa2"><front-stub><article-id pub-id-type="doi">10.7554/eLife.96025.4.sa2</article-id><title-group><article-title>Reviewer #2 (Public review):</article-title></title-group><contrib-group><contrib contrib-type="author"><anonymous/><role specific-use="referee">Reviewer</role></contrib></contrib-group></front-stub><body><p>Summary:</p><p>In the present work, the authors present an engineering solution to sample preparation in 96-well plates for high-throughput super resolution microscopy via Expansion Microscopy. This is not a trivial problem, as the well cannot be filled with the gel, which would prohibit expansion of the gel. They thus engineered a device that can spot a small droplet of hydrogel solution and keep it in place as it polymerises. It occupies only a small portion space at the center of each well, the gel can expand into all directions and imaging and staining can proceed by liquid handling robots and an automated microscope.</p><p>Strengths:</p><p>In contrast to Reference 8, the authors system is compatible with standard 96 well imaging plates for high-throughput automated microscopy and automated liquid handling for most parts of the protocol. They thus provide a clear path towards high throughput exM and high throughout super resolution microscopy, which is a timely and important goal.</p><p>Addition upon revision:</p><p>The authors addressed this reviewer's suggestions.</p></body></sub-article><sub-article article-type="referee-report" id="sa3"><front-stub><article-id pub-id-type="doi">10.7554/eLife.96025.4.sa3</article-id><title-group><article-title>Reviewer #3 (Public review):</article-title></title-group><contrib-group><contrib contrib-type="author"><anonymous/><role specific-use="referee">Reviewer</role></contrib></contrib-group></front-stub><body><p>Summary:</p><p>Day et al. introduced high-throughput expansion microscopy (HiExM), a method facilitating the simultaneous adaptation of expansion microscopy for cells cultured in a 96-well plate format. The distinctive features of this method include: (1) the use of a specialized device for delivering a minimal amount (~230 nL) of gel solution to each well of a conventional 96-well plate, and (2) the application of the photochemical initiator, Irgacure 2959, to successfully form and expand toroidal gel within each well.</p><p>Addition upon revision:</p><p>Overall, the authors have adequately addressed most of the concerns raised. There are a few minor issues that require attention.</p><p>Minor comments:</p><p>Figure S10: There appears to be a discrepancy in the panel labeling. The current labels are E-H, but it is unclear whether panels A-D exist. Also, this reviewer thought that panels G and H would benefit from statistical testing to strengthen the conclusions. As a general rule for scientific graph presentation, the y-axis of all graphs should start at zero unless there is a compelling reason not to do so.</p><p>Editor note: this comment has been addressed in the latest version.</p></body></sub-article><sub-article article-type="author-comment" id="sa4"><front-stub><article-id pub-id-type="doi">10.7554/eLife.96025.4.sa4</article-id><title-group><article-title>Author response</article-title></title-group><contrib-group><contrib contrib-type="author"><name><surname>Day</surname><given-names>John H</given-names></name><role specific-use="author">Author</role><aff><institution>Massachusetts Institute of Technology</institution><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Della Santina</surname><given-names>Catherine M</given-names></name><role specific-use="author">Author</role><aff><institution>Massachusetts Institute of Technology</institution><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Maretich</surname><given-names>Pema</given-names></name><role specific-use="author">Author</role><aff><institution>Massachusetts Institute of Technology</institution><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Auld</surname><given-names>Alexander L</given-names></name><role specific-use="author">Author</role><aff><institution>Massachusetts Institute of Technology</institution><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Schnieder</surname><given-names>Kirsten K</given-names></name><role specific-use="author">Author</role><aff><institution>Massachusetts Institute of Technology</institution><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Shin</surname><given-names>Tay</given-names></name><role specific-use="author">Author</role><aff><institution>Massachusetts Institute of Technology</institution><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Boyden</surname><given-names>Edward S</given-names></name><role specific-use="author">Author</role><aff><institution>Massachusetts Institute of Technology</institution><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib><contrib contrib-type="author"><name><surname>Boyer</surname><given-names>Laurie A</given-names></name><role specific-use="author">Author</role><aff><institution>Massachusetts Institute of Technology</institution><addr-line><named-content content-type="city">Cambridge</named-content></addr-line><country>United States</country></aff></contrib></contrib-group></front-stub><body><p>The following is the authors’ response to the previous reviews.</p><disp-quote content-type="editor-comment"><p><bold>Public Reviews:</bold></p><p><bold>Reviewer #1 (Public review):</bold></p><p>Summary</p><p>In this manuscript, Day et al. present a high-throughput version of expansion microscopy to increase the throughput of this well-established super-resolution imaging technique. Through technical innovations in liquid handling with custom-fabricated tools and modifications to how the expandable hydrogels are polymerized, the authors show robust ~4-fold expansion of cultured cells in 96-well plates. They go on to show that HiExM can be used for applications such as drug screens by testing the effect of doxorubicin on human cardiomyocytes. Interestingly, the effects of this drug on changing DNA organization were only detectable by ExM, demonstrating the utility of HiExM for such studies.</p><p>Overall, this is a very well-written manuscript presenting an important technical advance that overcomes a major limitation of ExM - throughput. As a method, HiExM appears extremely useful and the data generally support the conclusions.</p><p>Strengths</p><p>Hi-ExM overcomes a major limitation of ExM by increasing the throughput and reducing the need for manual handling of gels. The authors do an excellent job of explaining each variation introduced to HiExM to make this work and thoroughly characterize the impressive expansion isotropy. The dox experiments are generally well-controlled and the comparison to an alternative stressor (H2O2) significantly strengthens the conclusions.</p><p>Weaknesses</p><p>(1) It is still unclear to me whether or not cells that do not expand remain in the well given the response to point 1. The authors say the cells are digested and washed away but then say that there is a remaining signal from the unexpanded DNA in some cases. I believe this is still a concern that potential users of the protocol should be aware of.</p></disp-quote><p>Although ProteinaseK digestion removes most of the unexpanded cells, DNA can sometimes persist. As such, we occasionally observe Hoechst signal underneath cells. The residual DNA is easily differentiated from nuclear Hoechst signal and does not confound interpretation of results. We have added a new supplementary figure that further clarifies this point.</p><disp-quote content-type="editor-comment"><p>(2) Regarding the response to point 9, I think this information should be included in the manuscript, possibly in the methods. It is important for others to have a sense of how long imaging may take if they were to adopt this method.</p></disp-quote><p>We have added detailed information to the methods section to address this point as shown below. In general, we image HiExM samples on the Opera Phenix at 63x with the following parameters: 100% laser power for all channels; 200 ms exposure for Hoechst, 500-1000+ ms exposure for immunostained channels depending on the strength of the stain and the laser; 60 optical sections with 1 micron spacing; and 4-20 fields of view per well depending on the cell density and sample size requirements. Therefore, imaging one full 96-well plate (60 wells total as we avoid the outer wells) takes anywhere from 3 hr to 64 hr depending on the combination of parameters used.</p><disp-quote content-type="editor-comment"><p><bold>Reviewer #2 (Public review):</bold></p><p>Summary:</p><p>In the present work, the authors present an engineering solution to sample preparation in 96-well plates for high-throughput super resolution microscopy via Expansion Microscopy. This is not a trivial problem, as the well cannot be filled with the gel, which would prohibit expansion of the gel. They thus engineered a device that can spot a small droplet of hydrogel solution and keep it in place as it polymerises. It occupies only a small portion space at the center of each well, the gel can expand into all directions and imaging and staining can proceed by liquid handling robots and an automated microscope.</p><p>Strengths:</p><p>In contrast to Reference 8, the authors system is compatible with standard 96 well imaging plates for high-throughput automated microscopy and automated liquid handling for most parts of the protocol. They thus provide a clear path towards high throughput exM and high throughout super resolution microscopy, which is a timely and important goal.</p><p>Addition upon revision:</p><p>The authors addressed this reviewer's suggestions.</p><p><bold>Reviewer #3 (Public review):</bold></p><p>Summary:</p><p>Day et al. introduced high-throughput expansion microscopy (HiExM), a method facilitating the simultaneous adaptation of expansion microscopy for cells cultured in a 96-well plate format. The distinctive features of this method include: (1) the use of a specialized device for delivering a minimal amount (~230 nL) of gel solution to each well of a conventional 96-well plate, and (2) the application of the photochemical initiator, Irgacure 2959, to successfully form and expand toroidal gel within each well.</p><p>Addition upon revision:</p><p>Overall, the authors have adequately addressed most of the concerns raised. There are a few minor issues that require attention.</p><p>Minor comments:</p><p>Figure S10: There appears to be a discrepancy in the panel labeling. The current labels are EH, but it is unclear whether panels A-D exist. Also, this reviewer thought that panels G and H would benefit from statistical testing to strengthen the conclusions. As a general rule for scientific graph presentation, the y-axis of all graphs should start at zero unless there is a compelling reason not to do so.</p></disp-quote><p>We have revised Figure S10 to address your comments.</p></body></sub-article></article>