{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,7,30]],"date-time":"2026-07-30T15:42:33Z","timestamp":1785426153855,"version":"3.56.0"},"posted":{"date-parts":[[2026,7,14]]},"group-title":"Cell Biology","reference-count":41,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T00:00:00Z","timestamp":1783987200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"id":[{"id":"https:\/\/ror.org\/027vj4x92","id-type":"ROR","asserted-by":"publisher"}]},{"award":["2141064"],"award-info":[{"award-number":["2141064"]}],"id":[{"id":"https:\/\/ror.org\/021nxhr62","id-type":"ROR","asserted-by":"publisher"}]},{"award":["P30-CA014051"],"award-info":[{"award-number":["P30-CA014051"]}],"id":[{"id":"https:\/\/ror.org\/01xd6q208","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2026,7,14]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>Quantitative image analysis of subcellular organization requires sufficient spatial resolution to resolve individual organelles and sample size to capture heterogeneity both within cells and between cells. Existing imaging approaches often force a tradeoff between spatial resolution and throughput, limiting the ability to measure organelle-level phenotypes across cell populations. Here, we establish high-throughputs expansion microscopy (HiExM) as a scalable pipeline for single-organelle analysis. As a benchmark, we focus on mapping late endosomes and lysosomes (LELs), a heterogeneous organelle class whose small size, dense intracellular distribution, and functional diversity make it difficult to quantify accurately using conventional light microscopy. HiExM increases effective spatial resolution while preserving compatibility with large-scale image acquisition, enabling robust segmentation and quantitative profiling of individual LELs across large cell populations. Using this pipeline, we identified differences in intracellular trafficking behavior among anti-transferrin receptor antibodies that could not be captured by conventional colocalization analysis alone. We further integrate spatial and morphological features with learned image-based representations that can define relationships between LEL morphology and subcellular position as well as how these relationships respond to perturbations. Together, our work establishes HiExM as a generalizable platform for scalable single-organelle profiling, enabling an analytical framework for quantifying discrete organelles across cells and conditions.<\/jats:p>","DOI":"10.64898\/2026.07.12.738053","type":"posted-content","created":{"date-parts":[[2026,7,14]],"date-time":"2026-07-14T11:45:30Z","timestamp":1784029530000},"source":"Crossref","is-referenced-by-count":0,"title":["HiExM Enables Scalable Mapping of Organelle Morphology and Spatial Heterogeneity"],"prefix":"10.64898","author":[{"given":"John H.","family":"Day","sequence":"first","affiliation":[{"name":"Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue Cambridge, MA 02139, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John","family":"Farrell","sequence":"additional","affiliation":[{"name":"Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue Cambridge, MA 02139, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dandan","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue Cambridge, MA 02139, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabricio N.","family":"Neira","sequence":"additional","affiliation":[{"name":"Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue Cambridge, MA 02139, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Elizabeth A.","family":"Allen","sequence":"additional","affiliation":[{"name":"Sanofi, 350 Water St, Cambridge, MA 02141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ann M.","family":"Byrne","sequence":"additional","affiliation":[{"name":"Sanofi, 350 Water St, Cambridge, MA 02141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nina C.","family":"Leksa","sequence":"additional","affiliation":[{"name":"Sanofi, 350 Water St, Cambridge, MA 02141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Katherine W.","family":"Klinger","sequence":"additional","affiliation":[{"name":"Sanofi, 350 Water St, Cambridge, MA 02141, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giovanni","family":"de Nola","sequence":"additional","affiliation":[{"name":"David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mushriq","family":"Al-Jazrawe","sequence":"additional","affiliation":[{"name":"David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"},{"name":"Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Laurie A.","family":"Boyer","sequence":"additional","affiliation":[{"name":"Department of Biological Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue Cambridge, MA 02139, USA"},{"name":"Department of Biology, Massachusetts Institute of Technology, 77 Massachusetts Avenue Cambridge, MA 02139, USA"},{"name":"David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA"},{"name":"Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"54368","reference":[{"key":"2026071708000880000_2026.07.12.738053v1.1","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-022-05563-7"},{"key":"2026071708000880000_2026.07.12.738053v1.2","doi-asserted-by":"publisher","DOI":"10.1002\/cpcy.68"},{"key":"2026071708000880000_2026.07.12.738053v1.3","doi-asserted-by":"publisher","DOI":"10.1038\/nrm.2017.71"},{"key":"2026071708000880000_2026.07.12.738053v1.4","doi-asserted-by":"crossref","first-page":"4550","DOI":"10.1109\/TNNLS.2017.2766168","article-title":"Deep Learning in Microscopy Image Analysis: A Survey","volume":"29","year":"2018","journal-title":"IEEE Trans. Neural Netw. Learn. Syst"},{"key":"2026071708000880000_2026.07.12.738053v1.5","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104523"},{"key":"2026071708000880000_2026.07.12.738053v1.6","doi-asserted-by":"publisher","DOI":"10.1101\/cshperspect.a016857"},{"key":"2026071708000880000_2026.07.12.738053v1.7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7091-1830-6"},{"key":"2026071708000880000_2026.07.12.738053v1.8","doi-asserted-by":"crossref","unstructured":"Asano, S. M. et al. Expansion Microscopy: Protocols for Imaging Proteins and RNA in Cells and Tissues. Curr. Protoc. Cell Biol. 80, (2018).","DOI":"10.1002\/cpcb.56"},{"key":"2026071708000880000_2026.07.12.738053v1.9","doi-asserted-by":"publisher","DOI":"10.1126\/science.1260088"},{"key":"2026071708000880000_2026.07.12.738053v1.10","doi-asserted-by":"crossref","unstructured":"Day, J. H. et al. High-throughput expansion microscopy enables scalable super-resolution imaging. eLife 13, (2024).","DOI":"10.7554\/eLife.96025"},{"key":"2026071708000880000_2026.07.12.738053v1.11","doi-asserted-by":"publisher","DOI":"10.4161\/auto.28448"},{"key":"2026071708000880000_2026.07.12.738053v1.12","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pbio.3002576"},{"key":"2026071708000880000_2026.07.12.738053v1.13","doi-asserted-by":"publisher","DOI":"10.1083\/jcb.202403116"},{"key":"2026071708000880000_2026.07.12.738053v1.14","doi-asserted-by":"publisher","DOI":"10.1109\/ISBIC56247.2022.9854534"},{"key":"2026071708000880000_2026.07.12.738053v1.15","first-page":"265","volume":"11071","year":"2018","journal-title":"Cell Detection with Star-convex Polygons"},{"key":"2026071708000880000_2026.07.12.738053v1.16","doi-asserted-by":"publisher","DOI":"10.1109\/WACV45572.2020.9093435"},{"key":"2026071708000880000_2026.07.12.738053v1.17","doi-asserted-by":"publisher","DOI":"10.1016\/j.yexcr.2008.09.020"},{"key":"2026071708000880000_2026.07.12.738053v1.18","doi-asserted-by":"publisher","DOI":"10.1074\/jbc.273.32.20121"},{"key":"2026071708000880000_2026.07.12.738053v1.19","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.88.11.4771"},{"key":"2026071708000880000_2026.07.12.738053v1.20","doi-asserted-by":"publisher","DOI":"10.1016\/j.omtm.2025.101547"},{"key":"2026071708000880000_2026.07.12.738053v1.21","doi-asserted-by":"publisher","DOI":"10.1038\/emboj.2011.286"},{"key":"2026071708000880000_2026.07.12.738053v1.22","doi-asserted-by":"publisher","DOI":"10.1186\/s12987-025-00643-y"},{"key":"2026071708000880000_2026.07.12.738053v1.23","doi-asserted-by":"crossref","first-page":"e98649","DOI":"10.7554\/eLife.98649","article-title":"Novel autophagy inducers by accelerating lysosomal clustering against Parkinson\u2019s disease","volume":"13","year":"2024","journal-title":"eLife"},{"key":"2026071708000880000_2026.07.12.738053v1.24","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2018.05.079"},{"key":"2026071708000880000_2026.07.12.738053v1.25","doi-asserted-by":"publisher","DOI":"10.1083\/jcb.201507112"},{"key":"2026071708000880000_2026.07.12.738053v1.26","doi-asserted-by":"publisher","DOI":"10.1242\/jcs.196287"},{"key":"2026071708000880000_2026.07.12.738053v1.27","doi-asserted-by":"publisher","DOI":"10.1111\/tra.12587"},{"key":"2026071708000880000_2026.07.12.738053v1.28","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-019-41695-z"},{"key":"2026071708000880000_2026.07.12.738053v1.29","doi-asserted-by":"crossref","first-page":"e1009155","DOI":"10.1371\/journal.pcbi.1009155","article-title":"A deep generative model of 3D single-cell organization","volume":"18","year":"2022","journal-title":"PLOS Comput. Biol"},{"key":"2026071708000880000_2026.07.12.738053v1.30","doi-asserted-by":"crossref","first-page":"BSR20200905","DOI":"10.1042\/BSR20200905","article-title":"Chloroquine and bafilomycin A mimic lysosomal storage disorders and impair mTORC1 signalling","volume":"40","year":"2020","journal-title":"Biosci. Rep"},{"key":"2026071708000880000_2026.07.12.738053v1.31","doi-asserted-by":"publisher","DOI":"10.1111\/j.1600-0854.2009.00915.x"},{"key":"2026071708000880000_2026.07.12.738053v1.32","doi-asserted-by":"publisher","DOI":"10.1021\/nn2020858"},{"key":"2026071708000880000_2026.07.12.738053v1.33","doi-asserted-by":"crossref","first-page":"860","DOI":"10.1016\/j.medj.2022.09.007","article-title":"Enhanced delivery of antibodies across the blood-brain barrier via TEMs with inherent receptor-mediated phagocytosis","volume":"3","year":"2022","journal-title":"Med"},{"key":"2026071708000880000_2026.07.12.738053v1.34","doi-asserted-by":"crossref","first-page":"1786","DOI":"10.1093\/plphys\/kiab223","article-title":"DeepLearnMOR: a deep-learning framework for fluorescence image-based classification of organelle morphology","volume":"186","year":"2021","journal-title":"Plant Physiol"},{"key":"2026071708000880000_2026.07.12.738053v1.35","doi-asserted-by":"crossref","first-page":"1512","DOI":"10.1091\/mbc.E20-04-0269","article-title":"Deep learning approach for quantification of organelles and misfolded polypeptide delivery within degradative compartments","volume":"31","year":"2020","journal-title":"Mol. Biol. Cell"},{"key":"2026071708000880000_2026.07.12.738053v1.36","doi-asserted-by":"crossref","first-page":"767866","DOI":"10.3389\/fcell.2021.767866","article-title":"Deep Learning-Based Morphological Classification of Endoplasmic Reticulum Under Stress","volume":"9","year":"2022","journal-title":"Front. Cell Dev. Biol"},{"key":"2026071708000880000_2026.07.12.738053v1.37","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0028694"},{"key":"2026071708000880000_2026.07.12.738053v1.38","doi-asserted-by":"publisher","DOI":"10.1038\/nm.2090"},{"key":"2026071708000880000_2026.07.12.738053v1.39","doi-asserted-by":"publisher","DOI":"10.1038\/nrd4366"},{"key":"2026071708000880000_2026.07.12.738053v1.40","doi-asserted-by":"crossref","first-page":"2109252","DOI":"10.1002\/adma.202109252","article-title":"In Situ Super-Resolution Imaging of Organoids and Extracellular Matrix Interactions via Phototransfer by Allyl Sulfide Exchange-Expansion Microscopy (PhASE-ExM)","volume":"34","year":"2022","journal-title":"Adv. Mater"},{"key":"2026071708000880000_2026.07.12.738053v1.41","doi-asserted-by":"publisher","DOI":"10.1038\/s41563-023-01558-5"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.64898\/2026.07.12.738053","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T15:00:37Z","timestamp":1784300437000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.64898\/2026.07.12.738053"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,14]]},"references-count":41,"URL":"https:\/\/doi.org\/10.64898\/2026.07.12.738053","relation":{},"subject":[],"published":{"date-parts":[[2026,7,14]]},"subtype":"preprint"}}