Light-Sheet Optics Have Outrun Single-Fibril Assembly Biology

Question: How have light-sheet and lattice light-sheet microscopy approaches resolved the dynamics of self-assembling biopolymer networks, such as amyloid fibrils or collagen, at single-fiber resolution?

Answer

Taken together, the retrieved papers support a narrower claim than the question assumes: light-sheet architectures have solved the sampling problem for single-fiber resolution of assembling biopolymer networks, but they have not yet been the modality that produces the mechanistic claims about amyloid or collagen self-assembly. The instrument literature in this window delivers exactly the spatiotemporal budget that single-fiber tracking requires — up to 1,000 volumes per second at submicrometer lateral resolution [13], wavelength-scale sheet thickness sustained over millimetre distances in a single-objective geometry [16], and ~235 nm lateral / ~350 nm axial resolution in an accessible open platform that resolves actin, microtubules, and vimentin in migrating cells [18]. Where lattice light-sheet is actually paired with a fibrillar substrate, the payoff is mechanical — fiber-level traction forces from amoeboid cells on photopolymerized fiber arrays [10]. Meanwhile, every single-fibril dynamical mechanism reported in this corpus — secondary nucleation on huntingtin fibrils, curli assembly on living bacteria, strain accommodation within individual collagen fibrils, nanoscale refractive-index heterogeneity along collagen — comes from high-speed AFM, single-molecule localization, SHG, or cryo-EM rather than from light-sheet imaging [21][1][4][11]. Light-sheet microscopy is currently an enabling technology in this field, not a discovery technology.

Light-sheet designs now meet the spatiotemporal budget that single-fiber tracking demands

Image-scanning oblique plane microscopy reaches volumetric rates up to 1,000 volumes per second while retaining submicrometer lateral resolution and photon efficiency, explicitly framed as the trade-off escape that prior fast volumetric methods could not achieve [13]. Space-time light-sheet microscopy modulates the joint spatiotemporal spectral structure of a pulse to produce sheets of wavelength-scale thickness over millimetre-scale distances, expanding the sample-accessible volume 25-fold and the field of view 10-fold relative to state-of-the-art approaches without loss of sectioning [16]. Transverse sheet illumination captures spatially separated planes on parallel sCMOS sensors, reaching 748 × 278 × 100 µm³ at 100 Hz with 1.0/1.4/4.3 µm resolution and relieving the bandwidth bottleneck rather than the optics [12]. These are the acquisition rates at which a growing fibril tip and a branching junction are separable events rather than a blurred average.

Single-objective geometries lift the sample-handling constraint that excluded hydrated fibrillar gels

Conventional dual-objective lattice light-sheet designs impose a geometry that is hard to reconcile with the sample formats used for reconstituted gels and microfluidic assembly assays; a reflective single-objective lattice implementation inside a microfluidic chip uses one high-NA objective for both illumination and detection and outperforms Gaussian sheets in useful field of view and sectioning through scattering samples [14]. An open-source sample-scanning light-sheet design reports ~235 nm lateral and ~350 nm axial resolution across a 266 µm field of view after deconvolution and demonstrates live imaging of microtubules and vimentin intermediate filaments in actively migrating cells, alongside actin filaments and Golgi [18]. Where optical heterogeneity rather than geometry is the barrier, 3D Random Illumination Microscopy maintains 110 nm transverse and 270 nm axial resolution through tens of microns of aberrant tissue and hundreds of microns of collagen scaffold [17], and a reconfigurable platform combining light-sheet, label-free, super-resolution and multi-photon channels with adaptive optics targets exactly the aberration-driven degradation seen in multicellular contexts [19].

Where lattice light-sheet meets a fibrous substrate, the resolved quantity is force, not assembly

The one paper in this corpus that couples fast volumetric lattice light-sheet imaging to an engineered fibrous matrix does so to measure tractions: two-photon-polymerized multilayer fiber arrays of defined geometry and stiffness, segmented automatically and inverted by finite element modelling, with lattice light-sheet imaging required specifically to capture the low-intensity, short-lived tractions of fast amoeboid cells such as dendritic cells [10]. Field-synthesis lattice light-sheet imaging of growing pollen tubes, analysed by volumetric spatio-temporal image correlation spectroscopy, recovers voxel-resolved velocity, diffusion and density maps and resolves a bidirectional reverse-fountain transport pattern with a ~2 µm-wide retrograde corridor [15]. In both cases lattice light-sheet supplies quantitative transport or force fields around filaments rather than the kinetics of filament self-assembly.

The single-fibril assembly mechanisms are being resolved by non-light-sheet modalities

Direct, real-time, single-particle observation of huntingtin exon 1 aggregation by high-speed atomic force microscopy captures secondary nucleation, elongation, and the formation of large bundles through nucleated branching, and dissociates the N-terminal segment's primary-nucleation-enhancing role from any effect on secondary nucleation [21]. Amyloid-β secondary nucleation is traced to rare growth defects generated during original assembly, since annealing fibrils to eliminate defects without changing morphology greatly reduces both secondary nucleation capacity and site stoichiometry [20]. Functional amyloid on living bacteria is resolved by transient Nile blue binding combined with single-molecule localization and super-resolution optical fluctuation imaging, with imaging FCS supplying the binding relaxation times [1]. For collagen, polarization-controlled SHG combined with AFM on the same stretched single fibrils links an SHG intensity gradient to gradients in D-band and molecular strain and identifies a two-state transition with a 6–10 k_BT barrier, delayed by trivalent relative to divalent crosslinks [4]; single-molecule localization combined with AFM maps refractive index along isolated fibrils and finds fluctuations at length scales below 500 nm indicating heterogeneity at the single-molecule scale [11]. Fibril twist polymorphism is resolved by 3D contact-point-reconstruction AFM and X-ray fibre diffraction [3], and in-tissue spatial context by cryo-electron tomography of chemically fixed human brain [5].

Volumetric label-free and ensemble-mechanical methods are currently ahead of light-sheet on collagen assembly

Holotomography resolves fibrillar collagen networks without labels, co-registers refractive-index structure against SHG-positive collagen, converts tomograms into fiber-level descriptors of morphology, orientation and dry mass, and captures refractive-index dynamics during type I fibrillogenesis and cell-associated reorganization in a single measurement [6]. Optical multifrequency time-harmonic elastography shows that shear wave speed rises 6 ± 3 min earlier than optical density during collagen polymerization, implying a load-bearing percolating network forms before fibril thickening becomes visible in light microscopy [7]. Fibril-to-fibre mechanical coupling under load is mapped by full-field 3D small-angle X-ray scattering tomography, which is not an optical method at all [9]. Even where optical stacks exist, the bottleneck moves to reconstruction: topology-aware fiber extraction was developed because intensity thresholding fragments fibers and distorts junction connectivity in dense 3D networks from confocal data [24], and fiber-resolved force calculation in collagen hydrogels required replacing continuum assumptions with discrete networks reconstructed from confocal images [8].

Amyloid assembly is spatially segregated from the dense phase, raising the volumetric bar

Fibers of FUS grow overwhelmingly in the dilute phase surrounding condensates while the condensates concurrently arrest into a glass, so that fibers and glassy condensates coexist as distinct solid phases that do not directly interconvert [2]. Multi-component stress-granule mimics likewise suppress rather than promote amyloid formation by sequestering protein, constraining efflux-driven growth, and diluting protein at interfaces, with fibrils forming in the dilute phase even though interfaces can promote nucleation [23]. A condensation-interface picture with nucleation enhancement up to two orders of magnitude and four distinct interfacial growth morphologies is predicted only in simulation [22]. Resolving such events requires simultaneous, fast, low-phototoxicity coverage of a dilute phase and a dense phase within one volume — precisely the regime the instrument papers claim but do not demonstrate on fibrils.

Conflicts and gaps

The corpus contains no paper reporting lattice light-sheet or oblique-plane tracking of individual amyloid fibril elongation, nucleation, or branching events; the closest fibril-adjacent live-cell super-resolution work uses SMLM/SOFI, not light-sheet [1]. There is a substantive disagreement about where amyloid forms relative to condensates: fiber growth in the dilute phase [2], condensate-mediated suppression [23], and nucleation at condensate interfaces [22] are not reconciled, and none of these studies has the volumetric single-fiber resolution needed to arbitrate. A second conflict concerns the relevant observable: secondary nucleation is attributed to rare defects numbering far fewer than the molecules present [20], which makes ensemble kinetics and rare-event single-fiber imaging non-interchangeable rather than complementary. Third, holotomography's correspondence to fibrillar collagen is established only by co-registration with SHG at selected conditions, and mean fiber-associated refractive index was comparable between type I and type III despite differing network architecture [6], so fiber-level refractive-index readouts are not yet validated as mass proxies across subtypes. Finally, photobleaching and photodamage constraints at the frame rates and durations required for hours-long fibrillogenesis are asserted as motivation but never quantified against a fibril-formation timescale in this set.

What would change the answer

A correlative experiment would settle most of this: lattice light-sheet or oblique-plane acquisition with sparse, transiently binding labels of the kind already validated for curli [1], applied to a three-dimensional reconstituted amyloid system, tracking tip positions and branch points frame-by-frame and validating them against simultaneous high-speed AFM on the same field [21]. For collagen, the decisive test is volumetric pulse-chase labelling of newly synthesized fibers using the two-probe allysine chemistry already demonstrated to label nascent collagen and permit chase discrimination [25], imaged in 3D at rates that resolve individual fibril addition against the stiffness onset measured independently by shear-wave elastography [7]. Benchmarking topology-aware extraction [24] directly on light-sheet rather than confocal stacks, and reporting segmentation fidelity as a function of sheet thickness and scattering depth, would convert the instrument claims into usable fiber-level measurements. An adaptive-optics light-sheet system with refractive-index-matched collagen gels and a fibril phantom of known persistence length would isolate optical from biological limits on resolvable fiber diameter.

References

[1] Foust, D. J., Kolli, D., Jessel, K., Hu, Z., Chapman, M. R., Biteen, J. S.. "Transient binding facilitates super-resolution imaging of functional amyloid fibrils on living bacteria". bioRxiv. 2025-06-21T00:00:00.000Z. URL: https://doi.org/10.1101/2025.06.19.660547

[2] Feng, L., Muntz, I., Takaki, R., Ndamba, L., Ruer-Gruss, M., Julicher, F., Jawerth, L.. "Fibers and Glasses are Competing Material States in FUS Protein Condensation". bioRxiv. 2026-09-28T00:00:00.000Z. URL: https://doi.org/10.64898/2026.09.28.754945

[3] Farinas, I., Al-Hilaly, Y., Lutter, L., Xue, W.-F., Serpell, L.. "The architecture of amyloid fibrils formed by a human tau-derived hexapeptide VQIVYK". bioRxiv. 2025-03-12T00:00:00.000Z. URL: https://doi.org/10.1101/2025.03.11.642642

[4] MacAulay Harvey, Konstantin Roeder, Richard Cisek, Danielle Tokarz, Laurent Kreplak. "Polarization controlled second harmonic generation imaging of stretched collagen fibrils reveals collagen deformation pathway in situ". arxiv. 2026-08-20T00:00:00.000Z. URL: https://arxiv.org/abs/2608.18898

[5] van den Heuvel, L., Staehli, D. A., Radecke, J., Daraspe, J., Shafiei, N., Lewis, A. J., van de Berg, W. D. J., Genoud, C., Mahul-Melier, A.-L., Stahlberg, H., Chung, W.-L.. "Cryo-ET and Sub-Volume Analysis of Fibrillar Pathology in the Neurodegenerative Human Brain". bioRxiv. 2026-09-11T00:00:00.000Z. URL: https://doi.org/10.64898/2026.09.04.749518

[6] Lee, S., Park, W. S., Lee, J., Park, J., Park, H., Ahn, E. H., Kim, D.-H., Park, Y.. "Label-free volumetric refractive-index imaging of fibrillar collagen architecture, assembly, and cell-associated remodeling". bioRxiv. 2026-07-08T00:00:00.000Z. URL: https://doi.org/10.64898/2026.05.05.722893

[7] Sauer, F., Jordan, J., Meyer, T., de Moraes, P. A. D., Fle, G., Kaes, J. A., Sack, I.. "Spatiotemporal mapping of microscale stiffness during collagen polymerization and crosslinking by optical multifrequency time-harmonic elastography". bioRxiv. 2025-12-18T00:00:00.000Z. URL: https://doi.org/10.64898/2025.12.16.694603

[8] Barrasa-Fano, J., Kimps, L., Apolinar-Fernandez, A., Linhares, D., Muntz, I., Nunez Ortega, E., Vaes, N., Shapeti, A., Cardinaels, R., Koenderink, G., Sanz-Herrera, J., Van Oosterwyck, H.. "Data-driven traction force microscopy in 3D collagen hydrogels". bioRxiv. 2026-10-05T00:00:00.000Z. URL: https://doi.org/10.1101/2025.11.17.688772

[9] Newham, E., Parmenter, A. L., Chen, J., Disney, C., Snow, T., Brunet, J., Vinci, V., Drnec, J., Sherratt, M. J., Hoyland, J. A., BELLIER, A., Bay, B. K., Terrill, N., Lee, P. D., Gupta, H. S.. "Multimodal X-ray imaging reveals hierarchical fibre mechanics". bioRxiv. 2025-09-21T00:00:00.000Z. URL: https://doi.org/10.1101/2025.09.19.677294

[10] Ucla, P., Le Chesnais, J., Ver Hulst, H., Ju, X., Calvente, I., Leconte, L., Salamero, J., Bonnet, I., Monnot, C., Moreau, H. D., Landoulsi, J., Semetey, V., Coscoy, S.. "Quantifying Cell Traction Forces at the Individual Fiber Scale in 3D: A Novel Approach Based on Deformable Photopolymerized Fiber Arrays". bioRxiv. 2024-11-15T00:00:00.000Z. URL: https://doi.org/10.1101/2024.11.14.623421

[11] Jaritz, S., Velas, L., Gaugutz, A., Rufin, M., Thurner, P. J., Andriotis, O. G., Maloberti, J. G., Moser, S., Jesacher, A., Schuetz, G. J.. "Refractive index mapping below the diffraction limit via single molecule localization microscopy". bioRxiv. 2025-08-24T00:00:00.000Z. URL: https://doi.org/10.1101/2025.08.20.670782

[12] Carmona, J., Madruga, B. A., Mendoza, S. A., Jeong, J. B., Bentolila, L., Arisaka, K.. "Transverse Sheet Illumination Microscopy (TranSIM): A High-Speed Platform for Large-Scale Volumetric Imaging". bioRxiv. 2025-03-17T00:00:00.000Z. URL: https://doi.org/10.1101/2025.03.14.642160

[13] Tomina, Y., Ishijima, A., Toyoshima, Y., Shishido, H., Hirooka, R., Mukumoto, K., Wen, C., Kanamori, M., Kuze, K., Murakami, Y., Oe, S., Tanaka, S., Yonamine, Y., Nishigami, Y., Goda, K., Ijiro, K., Nakagaki, T., Arakawa, K., Ishihara, T., Onami, S., Iino, Y., Mikami, H.. "Image-scanning light-sheet microscopy for high-speed volumetric imaging of complex biological dynamics". bioRxiv. 2026-04-09T00:00:00.000Z. URL: https://doi.org/10.64898/2026.04.07.716805

[14] Cheng, S., Saliba, N., Gagliano, G., Joshi, P., Gustavsson, A.-K.. "Single-objective lattice light sheet microscopy with microfluidics for single-molecule super-resolution imaging of mammalian cells". bioRxiv. 2025-07-23T00:00:00.000Z. URL: https://doi.org/10.1101/2025.07.18.665606

[15] Ahmad Mahmood, Paul W. Wiseman. "Quantitative mapping of dynamic 3D transport in growing cells via volumetric spatio-temporal image correlation spectroscopy (vSTICS)". arxiv. 2026-03-31T00:00:00.000Z. URL: https://arxiv.org/abs/2603.27484

[16] Vasdekis, A. E., Zhang, J., Luo, H., Mitchell, D., Luckhart, S., Khajavikhan, M., Abouraddy, A., Christodoulides, D.. "Space-Time Light-Sheet Microscopy". bioRxiv. 2026-04-14T00:00:00.000Z. URL: https://doi.org/10.64898/2026.04.10.717581

[17] Mangeat, T., Mazzella, L., Rogez, B., Giroussens, G., Li, X., Bernard, M., Vargas, P., Allain, M., Labouesse, S., Idier, J., LeGoff, L., Sentenac, A.. "Super-resolved live imaging of thick biological samples with 3D Random Illumination Microscopy (3D-RIM)". bioRxiv. 2025-09-16T00:00:00.000Z. URL: https://doi.org/10.1101/2025.08.06.668879

[18] Haug, J., Gałecki, S., Lin, H.-Y., Wang, X., Dean, K. M.. "Altair-LSFM: A High-Resolution, Easy-to-Build Light-Sheet Microscope for Sub-Cellular Imaging". bioRxiv. 2025-11-07T00:00:00.000Z. URL: https://doi.org/10.1101/2025.04.08.647739

[19] Fu, T.-M., Liu, G., Milkie, D. E., Ruan, X., Gorlitz, F., Shi, Y., Ferro, V., Divekar, N. S., Wang, W., York, H. M., Kilic, V., Mueller, M., Liang, Y., Daugird, T. A., Gacha-Garay, M. J., Larkin, K. A., Adikes, R. C., Harrison, N., Shirazinejad, C., Williams, S., Nourse, J. L., Sheu, S.-H., Gao, L., Li, T., Mondal, C., Achour, K., Hercule, W., Stabley, D., Emmerich, K., Dong, P., Drubin, D., Liu, Z. J., Clapham, D., Mumm, J. S., Koyama, M., Killilea, A., Bravo-Cordero, J. J., Keene, C. D., Luo, L., Kirchhausen, T., Pathak, M. M., Arumugam, S., Nunez, J. K., Gao, R. G., Matus, D. Q., Martin, B.. "A Multimodal Adaptive Optical Microscope For In Vivo Imaging from Molecules to Organisms". bioRxiv. 2025-06-16T00:00:00.000Z. URL: https://doi.org/10.1101/2025.06.02.657494

[20] Hu, J., Scheidt, T. J., Thacker, D., Axell, E., Stemme, E., Lapinska, U., Wennmalm, S., Meisl, G., Curk, S., Andreasen, M., Vendruscolo, M., Arosio, P., Saric, A., Schmit, J., Knowles, T., Sparr, E., Linse, S., Michaels, T. C. T., Dear, A. J.. "Structural defects in amyloid-β fibrils drive secondary nucleation". bioRxiv. 2025-04-01T00:00:00.000Z. URL: https://doi.org/10.1101/2025.03.31.646415

[21] van Ewijk, C., Jain, G., Knelissen, Y., Maity, S., van der Wel, P. C. A., Roos, W.. "Direct observation of secondary nucleation in huntingtin amyloid formation by High-Speed Atomic Force Microscopy". bioRxiv. 2024-11-05T00:00:00.000Z. URL: https://doi.org/10.1101/2024.11.05.622155

[22] Biswas, S., Potoyan, D. A.. "β-motifs and molecular flux promote amyloid nucleation at condensate interfaces". bioRxiv. 2026-04-13T00:00:00.000Z. URL: https://doi.org/10.64898/2026.04.09.717507

[23] Mahendran, T. S., Gui, X., Bremer, A., Singh, A., Zaidi, F. K., Tesei, G., Basalla, J. L., Chittori, S., Marzahn, M. R., Gindra, B., Davis, R. B., Das, T., Lindorff-Larsen, K., Potoyan, D. A., Mittag, T., Banerjee, P. R.. "Viscoelasticity and interface properties of multi-component condensates govern protein sequestration and suppression of amyloid formation". bioRxiv. 2026-07-09T00:00:00.000Z. URL: https://doi.org/10.64898/2025.12.29.695806

[24] Risa Togo, Sara Cardona, Irène Nagle, Gijsje H. Koenderink, Behrooz Fereidoonnezhad, Mathias Peirlinck. "ToFiE, a Topology-aware Fiber Extraction workflow for 3D reconstruction of dense and heterogeneous biological fiber networks from microscopy images". arxiv. 2026-04-21T00:00:00.000Z. URL: https://arxiv.org/abs/2604.1823

[25] Kuroda, J., Fujii, K. K., Futaki, S., Hirata, A., Taga, Y., Koide, T.. "A facile method for fluorescent visualization of newly synthesized fibrous collagen by capturing the allysine aldehyde groups serving as cross-link precursors". bioRxiv. 2026-02-09T00:00:00.000Z. URL: https://doi.org/10.1101/2025.06.19.660320

How this survey was made

This survey answers one question: “How have light-sheet and lattice light-sheet microscopy approaches resolved the dynamics of self-assembling biopolymer networks, such as amyloid fibrils or collagen, at single-fiber resolution?”

We keep our own collection of recent preprints and refresh it every day from bioRxiv, medRxiv, arXiv, PsyArXiv, SocArXiv and ChemRxiv. For each survey, we search that collection for recent work and keep the strongest matches: papers that use the same terms as the question, and papers on the same topic in different words.

The text was written from the titles and abstracts of those papers; the full texts were not read. Statements that draw on a particular paper are marked with a number in brackets. The reference list just above is the 25 papers whose work this text draws on, chosen from the 106 papers those searches returned; the rest of the shortlist is not printed. It is not a complete review of everything published on the question.

Treat this as a starting point and a reading list, not a peer-reviewed review. The searches behind this survey ran on October 22, 2026 and covered work from the previous two years.