Expansion-enhanced super-resolution radial fluctuations enable nanoscale molecular profiling of pathology specimens
Source abstract
Abstract
Abstract Expansion microscopy physically enlarges biological specimens to achieve nanoscale resolution using diffraction-limited microscopy systems1. However, optimal performance is usually reached using laser-based systems (for example, confocal microscopy), restricting its broad applicability in clinical pathology, as most centres have access only to light-emitting diode (LED)-based widefield systems. As a possible alternative, a computational method for image resolution enhancement, namely, super-resolution radial fluctuations (SRRF)2,3, has recently been developed. However, this method has not been explored in pathology specimens to date, because on its own, it does not achieve sufficient resolution for routine clinical use. Here, we report expansion-enhanced super-resolution radial fluctuations (ExSRRF), a simple, robust, scalable and accessible workflow that provides a resolution of up to 25 nm using LED-based widefield microscopy. ExSRRF enables molecular profiling of subcellular structures from archival formalin-fixed paraffin-embedded tissues in complex clinical and experimental specimens, including ischaemic, degenerative, neoplastic, genetic and immune-mediated disorders. Furthermore, as examples of its potential application to experimental and clinical pathology, we show that ExSRRF can be used to identify and quantify classical features of endoplasmic reticulum stress in the murine ischaemic kidney and diagnostic ultrastructural features in human kidney biopsies.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Fluorescence Microscopy Techniques · Advanced Electron Microscopy Techniques and Applications · Heat shock proteins research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (45)
Show source-provided references
1. Wassie, A. T., Zhao, Y. & Boyden, E. S. Expansion microscopy: principles and uses in biological research. Nat. Methods 16, 33–41 (2019).10.1038/s41592-018-0219-4 ↗
2. Gustafsson, N. et al. Fast live-cell conventional fluorophore nanoscopy with ImageJ through super-resolution radial fluctuations. Nat. Commun. 7, 12471 (2016).10.1038/ncomms12471 ↗
3. Culley, S. et al. SRRF: universal live-cell super-resolution microscopy. Int. J. Biochem. Cell Biol. 101, 74–79 (2018).10.1016/j.biocel.2018.05.014 ↗
4. Bond, C. et al. Technological advances in super-resolution microscopy to study cellular processes. Mol. Cell 82, 315–332 (2022).10.1016/j.molcel.2021.12.022 ↗
5. Chen, F., Tillberg, P. W. & Boyden, E. S. Expansion microscopy. Science 347, 543–548 (2015).10.1126/science.1260088 ↗
6. Zhao, Y. et al. Nanoscale imaging of clinical specimens using pathology-optimized expansion microscopy. Nat. Biotechnol. 35, 757–764 (2017).10.1038/nbt.3892 ↗
7. Chang, J. B. et al. Iterative expansion microscopy. Nat. Methods 14, 593–599 (2017).10.1038/nmeth.4261 ↗
8. Gao, R. et al. Cortical column and whole-brain imaging with molecular contrast and nanoscale resolution. Science 363, eaau8302 (2019).10.1126/science.aau8302 ↗
9. Dey, G. et al. Closed mitosis requires local disassembly of the nuclear envelope. Nature 585, 119–123 (2020).10.1038/s41586-020-2648-3 ↗
10. Gabriel, TarrasonRisa et al. The proteasome controls ESCRT-III–mediated cell division in an archaeon. Science 369, eaaz2532 (2020).10.1126/science.aaz2532 ↗
11. M’Saad, O. & Bewersdorf, J. Light microscopy of proteins in their ultrastructural context. Nat. Commun. 11, 3850 (2020).10.1038/s41467-020-17523-8 ↗
12. de Boer, P., Hoogenboom, J. & Giepmans, B. Correlated light and electron microscopy: ultrastructure lights up! Nat. Methods 12, 503–513 (2015).10.1038/nmeth.3400 ↗
13. Stark, K. & Massberg, S. Interplay between inflammation and thrombosis in cardiovascular pathology. Nat. Rev. Cardiol. 18, 666–682 (2021).10.1038/s41569-021-00552-1 ↗
14. Ru, Y.-X. et al. Platelet production of megakaryocyte: A review with original observations on human in vivo cells and bone marrow. Ultrastruct. Pathol. 40, 163–170 (2016).10.3109/01913123.2016.1170744 ↗
15. Youssefian, T. et al. Platelet and megakaryocyte dense granules contain glycoproteins Ib and IIb-IIIa. Blood 89, 4047–4057 (1997).10.1182/blood.V89.11.4047 ↗
16. Ostrom, Q. T. et al. CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2013–2017. Neuro-Oncol. 22, iv1–iv96 (2020).10.1093/neuonc/noaa200 ↗
17. Zhang, P. et al. Current opinion on molecular characterization for GBM classification in guiding clinical diagnosis, prognosis, and therapy. Front. Mol. Biosci. 7, 562798 (2020).10.3389/fmolb.2020.562798 ↗
18. Knopman, D. S. et al. Alzheimer disease. Nat. Rev. Dis. Primers 7, 33 (2021).10.1038/s41572-021-00269-y ↗
19. Sweeney, M. D., Sagare, A. P. & Zlokovic, B. V. Blood–brain barrier breakdown in Alzheimer disease and other neurodegenerative disorders. Nat. Rev. Neurol. 14, 133–150 (2018).10.1038/nrneurol.2017.188 ↗
20. Gkanatsiou, E. et al. A distinct brain beta amyloid signature in cerebral amyloid angiopathy compared to Alzheimer’s disease. Neurosci. Lett. 701, 125–131 (2019).10.1016/j.neulet.2019.02.033 ↗
21. Maltepe, E. & Fisher, S. J. Placenta: the forgotten organ. Annu. Rev. Cell Dev. Biol. 31, 523–552 (2015).10.1146/annurev-cellbio-100814-125620 ↗
22. Denorme, F., Vanhoorelbeke, K. & De Meyer, S. F. von Willebrand factor and platelet glycoprotein Ib: a thromboinflammatory axis in stroke. Front. Immunol. 10, 2884 (2019).10.3389/fimmu.2019.02884 ↗
23. Naß, J., Terglane, J. & Gerke, V. Weibel Palade bodies: unique secretory organelles of endothelial cells that control blood vessel homeostasis. Front. Cell Dev. Biol. 9, 813995 (2021).10.3389/fcell.2021.813995 ↗
24. Lewis, C. V. & Taylor, W. R. Intestinal barrier dysfunction as a therapeutic target for cardiovascular disease. Am. J. Physiol. Heart Circ. Physiol. 319, H1227–H1233 (2020).10.1152/ajpheart.00612.2020 ↗
25. Claesson-Welsh, L., Dejana, E. & McDonald, D. M. Permeability of the endothelial barrier: identifying and reconciling controversies. Trends Mol. Med. 27, 314–331 (2021).10.1016/j.molmed.2020.11.006 ↗
26. Kiesler, P., Fuss, I. J. & Strober, W. Experimental models of inflammatory bowel diseases. Cell Mol. Gastroenterol. Hepatol. 1, 154–170 (2015).10.1016/j.jcmgh.2015.01.006 ↗
27. Aypek, H. et al. Loss of the collagen IV modifier prolyl 3-hydroxylase 2 causes thin basement membrane nephropathy. J. Clin. Invest. 132, e147253 (2022).10.1172/JCI147253 ↗
28. Schmied, J. J. et al. DNA origami–based standards for quantitative fluorescence microscopy. Nat. Protoc. 9, 1367–1391 (2014).10.1038/nprot.2014.079 ↗
29. Scheckenbach, M. et al. DNA origami nanorulers and emerging reference structures. APL Mater. 8, 110902 (2020).10.1063/5.0022885 ↗
30. Grahammer, F. et al. A flexible, multilayered protein scaffold maintains the slit in between glomerular podocytes. JCI Insight 1, e86177 (2016).10.1172/jci.insight.86177 ↗
31. Culley, S. et al. Quantitative mapping and minimization of super-resolution optical imaging artifacts. Nat. Methods 15, 263–266 (2018).10.1038/nmeth.4605 ↗
32. Sharfuddin, A. A. & Molitoris, B. A. Pathophysiology of ischemic acute kidney injury. Nat. Rev. Nephrol. 7, 189–200 (2011).10.1038/nrneph.2011.16 ↗
33. Heusch, G. Myocardial ischaemia–reperfusion injury and cardioprotection in perspective. Nat. Rev. Cardiol. 17, 773–789 (2020).10.1038/s41569-020-0403-y ↗
34. Daniele, S. G. et al. Brain vulnerability and viability after ischaemia. Nat. Rev. Neurosci. 22, 553–572 (2021).10.1038/s41583-021-00488-y ↗
35. Schroeder, L. K. et al. Dynamic nanoscale morphology of the ER surveyed by STED microscopy. J. Cell Biol. 218, 83–96 (2019).10.1083/jcb.201809107 ↗
36. Ron, D. & Walter, P. Signal integration in the endoplasmic reticulum unfolded protein response. Nat. Rev. Mol. Cell Biol. 8, 519–529 (2007).10.1038/nrm2199 ↗
37. Garg, P. A review of podocyte biology. Am. J. Nephrol. 47, 3–13 (2018).10.1159/000481633 ↗
38. Grahammer, F., Schell, C. & Huber, T. B. The podocyte slit diaphragm—from a thin grey line to a complex signalling hub. Nat. Rev. Nephrol. 9, 587–598 (2013).10.1038/nrneph.2013.169 ↗
39. Rinschen, M. M. et al. A multi-layered quantitative in vivo expression atlas of the podocyte unravels kidney disease candidate genes. Cell Rep. 23, 2495–2508 (2018).10.1016/j.celrep.2018.04.059 ↗
40. Butt, L. et al. A molecular mechanism explaining albuminuria in kidney disease. Nat. Metab. 2, 461–474 (2020).10.1038/s42255-020-0204-y ↗
41. Solomon, L. et al. The dextran sulphate sodium (DSS) model of colitis: an overview. Comp. Clin. Pathol. 19, 235–239 (2010).10.1007/s00580-010-0979-4 ↗
42. Wang, F. et al. RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues. J. Mol. Diagn. 14, 22–29 (2012).10.1016/j.jmoldx.2011.08.002 ↗
43. van der Walt, Stéfan et al. scikit-image: image processing in Python. PeerJ 2, e453 (2014).10.7717/peerj.453 ↗
44. Meijering, E. et al. Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images. Cytometry 58A, 167–176 (2004).10.1002/cyto.a.20022 ↗
45. Hildebrand, T. & Rüegsegger, P. A new method for the model-independent assessment of thickness in three-dimensional images. J. Microsc. 185, 67–75 (1997).10.1046/j.1365-2818.1997.1340694.x ↗