{"paper_id":"2216ba55-683b-43dd-a202-59608c4e131c","body_text":"Using r otational integration of oblique interferometric 1 \nscattering (RO-iSCAT) to track axial spatiotemporal 2 \nresponses of membrane protrusions 3 \n 4 \nJunyu Liu1,2, Yean Jin Lim2,3, David Herrmann4,5, Paul Timpson4,5, Tri G. Phan6, Huafeng Liu1,*, 5 \nMin Guo1,* and Woei Ming Lee2,3,* 6 \n 7 \n1 State Key Laboratory of Extreme Photonics and Instrumentation, College of Optical Science and Engineering, Zhejiang University, 8 \nHangzhou, China 9 \n2 Division of Genomic Sciences and Cancer, John Curtin School of Medical Research, The Australian National University, Canberra, 10 \nACT 2601, Australia 11 \n3 ACRF INCITe Centre - ANU Node, the John Curtin School of Medical Research, The Australian National University, Canberra, 12 \nACT 2601, Australia 13 \n4 Cancer Ecosystems Program, Garvan Institute of Medical Research and The Kinghorn Cancer Centre, Darlinghurst, NSW, 14 \nAustralia.  15 \n5 School of Clinical Medicine, Faculty of Medicine, University of New South Wales (UNSW) Sydney, Kensington, NSW, Australia.  16 \n6 Precision Immunology Program, Garvan Institute of Medical Research, Sydney, NSW , Australia 17 \n 18 \n* Correspondence to: liuhf@zju.edu.cn; guom@zju.edu.cn; steve.lee@anu.edu.au 19 \n 20 \nAbstract: Despite the crucial importance of dynamic membrane protrusions for understanding  21 \nphagocytosis, cellular communication and mechanobiology, current imaging modalities struggle 22 \nto quantitatively track their real -time, 3D spatiotemporal dynamics with sufficient molecular 23 \nspecificity and minimal perturbation.  Many membrane protrusions studies still utilize confocal 24 \nmicroscopy where its axial resolution and high phototoxicity remains a key limiting factor for live 25 \naxial imaging. We discovered that multiple rotational oblique interference scattering (RO-iSCA T) 26 \nleverages off -axis illumination to induce a larger lateral shift in out -of-focus iSCAT signals 27 \ncompared to in -focus signals. This phenomenon provides a foundation to generate speckle -free 28 \nwidefield interferometric signals with a 10-fold signal to noise ratio improvement, eliminating the 29 \nneed for any background subtraction. RO -iSCAT enables real -time, label -free, and minimally 30 \ninvasive imaging of diverse membrane protrusions within complex co -cultures. RO-iSCAT 31 \nenables nanoscale-sensitive tracking of membrane protrusion dynamics along the axial direction . 32 \nThis allows for the construction of dynamic axial variance maps, facilitating quantitative 33 \nmeasurements of membrane protrusion formation at tens to hundreds of nanometer displacements, 34 \nwithout requiring 3D volumetric imaging. RO-iSCAT empowers real time quantitatively dissection 35 \nof the axial spatiotemporal complexities of membrane protrusions and unlock future insights into 36 \nfundamental processes like cell migration, durotaxis, and intercellular communication. 37 \n 38 \nKeywords: filopodia tracking, membrane protrusion, label-free microscopy 39 \n  40 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nSummary Figure 41 \n 42 \n 43 \n 44 \nKey points 45 \n• Discovered that multiple integrated rotational oblique interference scattering (RO-iSCAT) 46 \ngenerates speckle-free widefield interferometric signals with a 10-fold signal to noise ratio 47 \nimprovement, eliminating the need for any background subtraction. 48 \n• Removed need for 3D volumetric imaging  to quantified axial motion  of membrane 49 \nprotrusion forming tethers, trails and bridge with within ~ tens of nanometer accuracy. 50 \n• Enabled classification of membrane protrusions that, despite possessing identical chemical 51 \ncompositions, are differentiated by their interactions, thus offering a qualitative comparison 52 \nof membrane protrusions at the nanoscale in living cells. 53 \n 54 \n  55 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nIntroduction 56 \nMembrane protrusions (lamellipodia, pseudopodia, filopodia, microvilli, invadopodia, and 57 \npodosomes) possess dynamic three-dimensional spatiotemporal behaviours because they mediate 58 \na wide variety of extracellular interactions between a cell and its three-dimensional 59 \nmicroenvironment 1. While these dynamic protrusions are the result of cytoskeletal (e.g. actin, 60 \nmicrotubules) rearrangement, their 3D spatiotemporal relationship are initiated by the activation 61 \nand clustering of membrane receptors  2. In particular, 2D spatiotemporal tracking of filopodia - 62 \nmembrane extensions indicate their role in mechanical and chemical sensing 3, phagocytosis 4, 5 63 \nand migration 6, 7. Observations of protrusion dynamics on coated substrates, between cells and in 64 \ntissue 8 have led to discoveries on contact-dependent cell-cell communication 9, twisted tethers 10, 65 \nforming migrasomes from retraction fibers 11, and tunnelling nanotube 12 as well as gaining closer 66 \ninsight into tissue development 13. 67 \nExisting tools to track membrane protrusion, extensions and distribution in the spatiotemporal 68 \ndomain relies heavily on standard light microscopy technique (brightfield -phase contrast, 69 \nfluorescence), have inadequate resolution, are prone to phototoxicity, and lacking  specific 70 \nfluorescence markers, cannot readily classify the transient behaviors of 3D membrane protrusion 71 \nand extensions in live cell cultures. Whilst the use of volumetric imaging technologies 14 and 72 \nadvanced image processing 15 has made significant advances, the issue of phototoxicity and 73 \nphotobleaching remains a concern for longitudinal imaging  16 that is necessary for quantitative 74 \nmapping of membrane protrusions. Electron microscopy (EM), on the other hand, has become a 75 \nroutine tool to identify these protrusions that forms membrane bridges because of its ability to 76 \nmeasure physical feature membrane protrusion based on physical size, diameter (50 –200 nm 77 \ndiameter), the distance between distant cell and importantly, and their proximity with substrate for 78 \nclassification 17. Unfortunately, EM slices face methodological difficulties because membrane 79 \nprotrusion such as tethers and tunnelling nanotubes are often fragile after chemical fixation, and 80 \nprone to deform due to sample preparation.  Owing to well-defined refractive index difference in 81 \nactin and lipid in thin membrane protrusion, it is plausible that interference scattering microscopy 82 \n(iSCAT) 18-20 signals can be more effectively at quantitative tracking the transient movements of 83 \ndifferent types of membrane protrusions that form, disassemble and maintain at the nanoscale in 84 \n3D than fluorescence microscopy. However, iSCA T signals often require background subtraction 85 \n20, which can be challenging to implement and may fail to remove speckles in populated cell 86 \ncultures, thus hindering the tracking of protrusion spatiotemporal patterns in live cells.  87 \n This paper examines the optical principles of a Rotational Oblique Interferometric Scattering 88 \nsignals (RO-iSCAT) to achieve speckle free interferometric scattering signals in real time. We then 89 \nfollow on to explain how RO-iSCAT interference patterns are used to track spatiotemporal  of 90 \nmembrane protrusion; that can transits into trails (i.e. retraction fibers to  migrasomes), membrane 91 \ntethers or bridges 21. We provided evidence demonstrating that axial variation maps of interference 92 \nscattering signals are effective in accurately categorizing various membrane protrusions. The axial 93 \nvariation information possesses rich spatial temporal signature even within a single protrusion that 94 \nsurpass standard kymograph in fluorescence or scattering images which only consider rudimentary 95 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nshapes. The paper comprises of 4 main parts – numerical model of RO -iSCAT, quantification of 96 \nimaging resolution of RO-iSCAT, identification of membrane protrusion using spatial signature in 97 \nlateral interference pattern alongside with variance in axial displacement analysis of RO-iSCAT 98 \nimages, and longitudinal tracking of membrane protrusions in co-cultured cells lines. 99 \n 100 \nResults 101 \nRotational integration removes out-of-focus interference scattering signals 102 \nUnder off-axis illumination, we observed that out-of-focus iSCA T signal experienced a larger 103 \nlateral shift than in-focus iSCAT signal (Supplementary Video 1). To explain this effect, we began 104 \nwith a numerical model (Supplementary Note 1 and Methods) and synthesized the interference 105 \nintensity signals of RO-iSCAT. The scheme of oblique illumination  we adopted was at a single 106 \nangle, where an incoming illumination (blue line and shades) entered the sample at an oblique 107 \nangle 𝜃 along a single azimuthal orientation 𝜑 (Fig. 1a). The path length difference  arises from 108 \nrefractive index difference between glass-water interface (reference field) and scattered light that 109 \nis necessary to form an iSCA T signal. Whilst the reference field is constant (Fig. 1a, first reflecting 110 \nsurface-blue line), the scattered signal (Fig. 1a, green line) varies along the axial plane 𝑧. Because 111 \niSCAT signal is of interferometric nature, the signal is changed by the properties of scattered signal 112 \ncollected by the imaging lens. This phase delay (defocused wavefront) changes with axial distance 113 \n𝑧 of the imaging lens for each oblique angles 𝜃 and azimuthal direction 𝜑.  114 \nAt each oblique angle, an off-axis phase shift causes iSCAT interference fringe pattern to shift 115 \nlaterally away from the focal plane . We numerically calculated the phase and fringe shifts at 116 \ndifferent azimuthal angle (Fig. 1b, Supplementary Fig. 1 and Supplementary Video 2).  Each 117 \noff-axis oblique phase delay (Fig. 1b i) from different azimuthal sources (𝜑 = 0°, 90°, 120°, 200°) 118 \nis convolved with defocusing phase delay that will create nonlinear phase shifts  (Fig. 1b ii, iii), 119 \nwhich directly translate to the intensity fringes translating laterally (Fig. 1b iv).  120 \nTo confirm th e effect of lateral shifts in intensity fringes in RO-iSCAT, first we simulated 121 \nlateral shift of intensity fringes across multiple axial planes from -2 µm to 2 µm  and compared 122 \nwith the measured experimental results (Supplementary Video 3 left). From both our model and 123 \nexperiment (Fig. 1c), we observed that the  lateral fringe shifts increased further away from the 124 \nfocal plane, whereas at the focal plane, the iSCAT signal experience shift almost negligible. Then, 125 \nwe examined the modelled shift in fringes along the transvers plane at a zimuthal rotational 126 \ndirection 𝜑 = 0° and 120° (Fig. 1d i) as well as the final integrated RO-iSCAT images 𝜑 = 0° −127 \n360° (Fig. 1d ii).  The integrated RO-iSCA T shows a significant reduction of side lobe (profiles 128 \nin Fig. 1d) that indicates an increased visibility of the interference fringes at the focal plane. This 129 \nrotational oblique configuration reduces out-of-focus signal equivalent to confocal configuration 130 \n19 (Supplementary Fig. 2  and Supplementary Video 4). Hence, directly integrating multiple 131 \noblique illuminated iSCA T signals generates a high contrast iSCAT image at the focal point only, 132 \nwithout intensity losses that can occur in background subtraction 20 or pinholes 19. 133 \nNext, we turned to examine the 3D interference point spread function (iPSF) of on axis (𝜃 =134 \n0.5° ), iSCAT and off axis ( 𝜃 = 22° ), RO -iSCAT over a 4 48-micron FOV  under 1.4 NA 135 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nobjective lens ( Supplementary Fig. 3a) through a Boundary -Element-Method platform 22. RO-136 \niSCAT possess a higher lateral signal to noise ratio and narrower expansion than conventional 137 \niSCAT (Supplementary Fig. 3b and 3c). To quantity the improvement on noise rejection and SNR, 138 \nwe synthetically generated fringe by 1) the pure signal from a single particle at focal plane 139 \nalongside with  2) different levels of  speckle noise from an out -of-focus plane  (Fig. 1 e i and 140 \nMethods). RO-iSCA T effectively rejected most of the speckle artifacts from background (Fig. 1e 141 \nii) thus improved the SNR from 0.49 (Fig. 1e ii left) significantly to 5.65 (Fig. 1e ii right). Even 142 \nunder increasing noise conditions, RO-iSCA T consistently achieve high SNR when compared to 143 \nbackground substraction (Fig. 1e iii, light blue versus light red scatters) and a ten-fold higher image 144 \nSNR (Fig. 1e iii, blue versus red curve. Supplementary Fig. 4). 145 \n 146 \nRO-iSCAT imaging achieve speckle-free iSCAT without needing background subtraction 147 \nThe role of background subtraction  in majority of iSCAT methods 19, 20, 23-26 is to remove all 148 \nextrinsic factors (i.e. non-uniform illumination, and unwanted coherent noise and interference) so 149 \nas to increase SNR and reach single protein sensitivity. Background subtraction uses iSCAT images 150 \nrecorded with no focal drift and ultra clean glass slides that is free of any sample feature 20. In this 151 \nsection, we compare d SNR of RO-iSCA T versus standard background subtraction (iSCA T). The 152 \nsample was a glass coverslip dish containing surface -bound sub -diffraction limited gold 153 \nnanoparticles (37.0 nm - 43.0 nm diameter) and cancer-associated fibroblast cells (CAFs) cultured 154 \nover 7 days (Methods).  155 \nOur home -built RO-iSCA T system 18 involved a pair of galvanometer scanner to achi eve 156 \ncustomized off-axis oblique and azimuth (Fig. 2a). Two raw iSCAT image were recorded, one with 157 \n(Fig. 2b) and one without gold nanoparticles (Fig. 2c, as background), and formed the final image 158 \niSCAT image after background is manually subtracted (Fig. 2d). Each raw image was recorded by 159 \npositioning the galvanometer mirrors at a single azimuthal position. On the other hand, the  RO-160 \niSCAT image was captured after turning the galvanometer mirror at azimuthal angles 𝜑 from 0 to 161 \n360o continuously. To capture a full RO-iSCA T image, the camera exposure rate was synchronised 162 \nto integrate over a series of oblique RO-iSCAT images over a single cycle of rotation, finally get 163 \nΣ𝐼scat(𝜑) (acquisition speed up to 40 fps in our system) . Here we demonstrated four RO -iSCAT 164 \nimages at each azimuth 0°, 90°, 180° and 270° (taken without rotational integration, Fig. 2e) and 165 \nthe full-integrated image (Fig. 2f). Considering that the final iSCA T and RO-iSCA T images were 166 \nof the same field of view and taken over the same exposure time, the full RO-iSCA T images 167 \noutputted significantly lower background noise and speckle than  iSCAT background subtraction, 168 \nas well as an alignment with our numerical simulation (inset of Fig. 2f).  169 \nTo quantitate the improvement of RO-iSCAT over the background subtraction in iSCAT, we 170 \nchose a smaller field of view  (cyan dotted box in Fig. 2d and 2f) and adopted the metric to 171 \ndetermine if two closely spaced sub-diffraction limited gold nanoparticles can be resolved . From 172 \nthe line plot of intensity variation between adjacent nanoparticles (Fig. 2g and 2h), it appeared that 173 \nbackground subtraction and integration both possessed almost the same signal to noise ratio. 174 \nHowever, rotational integration was able to fully resolve adjacent 40 nm particles , where 175 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nseparation between the 40 nm particles was approximately 170 nm that was close to Abbe 176 \ndiffraction limit of 163.7 nm, which was not possible using background subtraction for the same 177 \nacquisition time (insets in Fig. 2h  and 2g). RO -iSCAT removes of the speckle noise in the 178 \nbackground without any loss to intensity. Because no subtraction is made, the full dynamic range 179 \nof the camera is preserved. Also we observed that there were spatially varying speckles intensities 180 \nin the images taken from 𝐼scat(90°), 𝐼scat(270°) to 𝐼scat(0°) and 𝐼scat(180°) profiles which were 181 \nuncorrelated and so were removed in RO-iSCAT Σ𝐼scat(𝜑) because of rotational integration (Fig. 182 \n2e).  183 \nTo further validate our numerical model that rotational integration  improves the imaging 184 \nresolution along the  axial direction (Fig. 1e  and Supplementary Fig. 3), we capture d the 185 \ninterferometric signal using a nano-stage that was moved along a  fixed step interval of 10 nm. 186 \nWhen comparing the axial intens ity profiles (Fig. 2i), the axial intensity variation of RO-iSCA T 187 \nshown higher contrast along the axial plane and matched well with Boundary-Element-Method 188 \nsimulation (Supplementary Fig. 3). Then, we evaluated the imaging performance of rotational 189 \nintegration with RO-iSCAT on membrane protrusion from adherent cells alongside with fixed 40 190 \nnm gold nanoparticles (Fig. 2j). While 40 nm gold nanoparticles (Fig. 2j, cyan boxed inset) were 191 \nmarginally visible, it was only RO-iSCAT that the fine membrane protrusions can be detected (Fig. 192 \n2j, red boxed inset). Moreover, the rotational integration effect can be more readily observed and 193 \nquantified by discretizing the integration process (Supplementary Video 5) which illustrated that 194 \nthe increasing number of azimuthal scanning angles 𝜑 for integration will form a higher final SNR 195 \n(Supplementary Fig. 5). 196 \n 197 \nDiffering spatiotemporal dynamics between membrane trails, tethers and bridges 198 \nBenefit from the high SNR fringes, we put our focus on the protrusion growth and external 199 \nconnections. First, we captured a time -lapse dataset of endothelial cells with high dynamics 200 \n(Supplementary Fig. 6, Supplementary Video 6). On the smooth cell membrane, multiple 201 \nprotrusion emerged in random directions, then converging toward another cell, with lamellipodia 202 \ndriving them aggregating toward the target location, ultimately connecting with the target cell. 203 \nDuring the growth, the interference pattern on protrusion were varying, mainly the bright -dark 204 \nperiods (yellow arrows in Supplementary Fig. 6). Here we ask if RO-iSCAT interference patterns 205 \ncan be used to identify membrane types, particular cell -substrate versus membrane bridges 206 \nbetween cells.  207 \nTo answer this question, we examine d RO-iSCAT images in a single culture of CAFs cells  208 \nthat is known to form tight networks i.e. fibrotic tissue. RO-iSCAT provided the clear FOV where 209 \na CAF cell adhered to glass coverslip and multiple CAF cells forming extensive membrane bridges 210 \nover 20-30 µm long  (Fig. 3a i and ii). We then selected three different membrane protrusion to 211 \ncharacterise which were chosen based on their distinct types of interference patterns and their 212 \nassumed spatial locations. Combining the lateral morphology (Fig. 3b) and relative axial position 213 \n(Supplementary Fig. 7 and Supplementary Video 7), we formed a biological sketch (Fig. 3c) 214 \nand shown the membrane protrusions far from the cell body exhibit uniform fringe intensity, 215 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nindicating a flat height and membrane has adhered to the glass-bottom surface (Trail, Fig. 3b top). 216 \nIn contrast, protrusions between cell bod ies (basal surface) display interference pattern s with 217 \nalternating bright and dark fringes, spaced approximately 0.5 micrometers apart.  This suggested 218 \nthat the protrusion grow s from the apical side slanting downward to the bottom surface with a 219 \nrapid height gradient (Tether, Fig. 3b middle). Additionally, fringes with membrane bridges tend 220 \ndisplay interference pattern s with alternating bright and dark fringes, spaced approximately 3 221 \nmicrometers apart, forming connections at a similar height between two cells (Bridge, Fig. 3b 222 \nbottom).   223 \nBesides the morphology characteristic, we examined the motion modalities of these 224 \nmembrane protrusions from the entire time -lapse dataset by mapping from interference signal 225 \nintensity to relative depth based on calibration data (Sup. Fig. 9, Methods). Kymograph is a classic 226 \ntool for recording motion along one line over time (Supplementary Fig. 8), however, to capture 227 \nthe spatiotemporal changes across the whole imaging field, we applied a new axial-variation map 228 \n(Fig. 3d i, ii, pixel-level standard deviation on the entire 2D image  relative depth over the time 229 \nperiod) to measure the effective  range of  axial displacement ( Fig. 3d  iii, iv ). Because axial 230 \nvariation was applied across the whole imaging field, we can directly quantitate whole membrane 231 \nprotrusion dynamics directly from the intensity mapped to the magnitude of the axial variation 232 \n(brighter intensity indicates larger axial fluctuations). To prove that this axial variation information 233 \nwas only retrieved using RO -iSCAT imaging, we also applied axial variation treatment to 234 \nscattering-only images (Supplementary Fig. 8). It shown the distinct spatial temporal intensity 235 \nchanges were only observed under RO-iSCAT but not under scattering-only imaging (only up to 236 \n87 grayscale), indicating that this was a direct consequence of interferometry ( Supplementary 237 \nVideo 8). The axial-variation map directly determined highly motile membrane bridges between 238 \nCAF cells. The large range of intensity variation in RO-iSCAT images occurs in up to 300 nm z-239 \naxis movement along membrane bridge. This observation suggest ed that membrane bridges 240 \npossess a taut behavior where axial movements are greater than lateral movements. Axial variation 241 \nresponses of the RO-iSCAT images (Fig. 3e i and ii) and the statistics of the values for all the three 242 \ntypes of membrane protrusion  (Fig. 3f) indicated a clear difference between the spatial temporal 243 \nbehavior among them. The mean values of the three grouped distributions histograms further 244 \nillustrated that the suspended cell -cell bridges showed a 2 -fold more axial movement  (averaged 245 \nrange of 142.60 nm) than tethers (77.01 nm) and 4-fold more than trails (31.08 nm), even though 246 \nthey may physically appear tight and straight along. 247 \n 248 \nRO-iSCAT’s performance in tracking membrane protrusion 249 \nCAF cells can form extensive cellular networks that will be filled with various types of 250 \nmembrane protrusions particularly cell -cell membrane bridge 27, 28.  Two separate cell co-culture 251 \nexperiments using CAF and KPC cells were adopted (Methods) here to track the formation and 252 \ntransition of protrusion and connections between identical and different cell types.  253 \nFirst, we examined whether the interferometric images from RO -iSCAT can track different 254 \nmembrane protrusions more effectively than that based on intensity-only morphological tracks in 255 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nfluorescence imaging. We co-cultured two cell populations of CAF cells: wild type (WT) CAFs 256 \nand CAF transfected with Lck10 -GFP to label the plasma membrane  (Fig. 4a i). Two separate 257 \ncultures of WT and Lck10-GFP transfected CAF cells were grown over 3 days before both cultures 258 \nwere seeded into the same culture dish.  The culture was imaged four hours after seeding  under 259 \nscattering-only (Fig. 4a ii), fluorescence (Fig. 4a iii), alongside with RO-iSCAT all under oblique 260 \nhighly inclined thin illumination (HiLO). A sequence of membrane protrusions (red dotted box in 261 \nFig. 4a iii) over ~ 7.9 minutes, under HiLO fluorescence imaging (Fig. 4b) and RO-iSCA T (Fig. 262 \n4c), shown a transfected Lck10-GFP CAF cell protrusion its membrane towards neighboring WT-263 \nCAFs (not visible under fluorescence) imaging. Under RO-iSCAT imaging, we can readily observe 264 \nboth transfected-CAF and WT-CAF beginning to form membrane bridge ~5µm length.  265 \nWhile fluorescence imaging permitted the identification of 2D morphology of the membrane 266 \nprotrusion, in contrast under RO-iSCAT, we observed a highly complex interference scattering 267 \npatterns within the same protrusion. The intensity stripes changed from high to low spatial cycles 268 \n(all arrows in Fig. 4c i, ii compared with Fig. 4c iii, iv). At time point 349 and 584 seconds, an 269 \nadjacent stationary protrusion appeared to display a uniform dark stripe ( yellow arrow in Fig. 4c 270 \nii and red arrow in Fig. 4c  iii), suggesting the complete disassociation from the target cell  271 \nindividually. The variation of t hese intensity fringes  indicated physical axial movements of the 272 \nprotrusion 18. Over 10 mins, these interferometric intensity patterns exhibit regular axial movement 273 \nwhen associating and disassociating with neighboring cells (Supplementary Video 9).  All these 274 \nresults suggest that RO-iSCA T overcomes the limit of fluorescence modality for the purpose of 275 \nquantifying spatial temporal dynamics in 3D membrane protrusions. Besides these CAF-CAF 276 \nintercellular connections, d irect communication between CAFs and cancer cells  mediated by 277 \nsurface receptors or adhesion molecules  can play an much more important role in tumour 278 \nprogression 29. Hence, next we looked at whether CAF can form membrane bridges with pancreatic 279 \nductal adenocarcinoma (PDA) cells.  280 \nThe second co-culture involved CAF and PDA cells from the murine KPC model, where we 281 \nseeded the two cell groups separately at opposite side of the glass bottom dish  where each will 282 \nmigrate towards the center over 7 day -long culture in incubator ( Fig. 4d i). On day 7 and 8, we 283 \nimaged the proximity of the cell ( Fig. 4d ii and iii) under brightfield to observe the proximity of 284 \nthe 2 cells population indicated by  yellow and red dotted line. On day 8, we used scattering-only 285 \nimages to identify the border between a CAF and PDA cell using cell morphology (Fig. 4e). Within 286 \nthe chosen field of view, we monitored the space between CAF and PDA cell (Fig. 4e, blue dotted 287 \nbox). RO-iSCAT imaging was conducted over the same field of view over 60 mins at 10 mins 288 \nintervals (Fig. 4f and Supplementary Video 10). Using RO-iSCAT and interferometric signals, 289 \nwe identified active transition between cell -substrate connections to membrane bridges. T wo 290 \nindividual connection appeared to gradually merge to one single  protrusion through a twisting  291 \nprotrusion morphology 10. We can see that a t the initial time point (0 min), the protrusion from a 292 \nsingle CAF and PDA cell were first individually separated (yellow and red dashed box). Then at 293 \n17 min, the protrusion gradually merged to form direct membrane bridge. Starting from 31 min, 294 \nthe two separated membrane bridge  merge through high degree of axial variation that maybe 295 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nindicate large strain akin to twisting to form a single  membrane connection  at 56 min with a 296 \nstraighter morphology.  297 \nWhilst the interference intensity show n highly dynamics activities (Supplementary Video 298 \n10), it failed to reflect spatial temporal information visually. To measure the spatial temporal events, 299 \nwe applied axial-variation treatment to the RO -iSCAT images to measure fluctuation from the 300 \ninterference intensity signals (Fig. 4g), where higher value of axial variation indicates increasing 301 \nprotrusion motility. It directly indicated the increasing level of axial motion along each protrusion 302 \nacross each time point. Quantitatively, a violin plot (Fig. 4h) shows the time-variance distribution 303 \nalong the protrusion at each time point that indicates  distinguishable mean values between 304 \nmembrane bridges forming between the PDA and CAF cells. Particularly, the spatiotemporal 305 \ndynamics of the protrusion from tethers to formation of bridge between cells. N ewly connected 306 \ntether was observed at 17 min and 31 min utes displayed increasing axial motion up to 140 nm 307 \nwhich was 2 times compared to initial protrusion tethers (0 min), and at the last 56 minutes, we 308 \nobserved a bridge was formed between the cells indicated by 210 nm range of axial motion (3-fold 309 \nincrease). This result indicates that RO -iSCAT interference signal s may be used to identify 310 \nspatiotemporal behavior of membrane bridges that is otherwise missed by classical 2D intensity-311 \nimaging (fluorescence or scattering-only) techniques. 312 \n 313 \nDiscussion 314 \nIn this study, we performed two investigations: 1) eliminate out-of-focus speckle background 315 \nnoise in RO -iSCAT interferometric signatures u sing rotational integration.  2) preliminary 316 \nevidence that axial variation map of label-free RO-iSCAT images can measure and quantify spatial 317 \ntemporal membrane protrusion types that surpass conventional kymograph.  318 \n 319 \nCan RO-iSCAT operate with incoherent sources?  320 \nSNR of RO-iSCAT is defined by fringe visibility. Along the transverse and axial planes (x, y 321 \nand z), fringe visibility is generally affected by the coherence of the light source and relative 322 \ndifference of both the optical path length and intensities between reflected and scattered intensities 323 \n21. Interferometric scattering (iSCAT)  19, 20, 24, 30 -32 is gaining traction for label -free sub-cellular 324 \nimaging due to its ability to detect nanoscale scatterers.  RO-iSCA T could be treated as a partially 325 \ncoherent detection (temporal) along with the integration time of the camera.  Out-of-focus 326 \ninterference fringes are suppressed based on the difference in path length . In supplementary, we 327 \nhave done some modeling of partially coherent sources indicating coherence plays a minimal role. 328 \nWe suspect that this  rotational integral  configuration can be of use for most interferometric 329 \nmicroscopies. 330 \nWhat are the key drawbacks of RO-iSCAT modality?  331 \n A common problem in interferometric imaging is the repeating interference fringes due to 332 \nwrapped phase. This meant that direct 3D quantitative measurement of interference fringes in the 333 \naxial plane becomes a challenge.  Secondly, the axial iSCAT sections are taken with a moving 334 \nobjective lens or the first reflective surface of a glass coverslip which can incur additional phase 335 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nshifts. This is a similar issue with common path interferometry. It will refresh background artifacts 336 \nfrom optical components, and the moving length of the objective lens will not convert to the same 337 \nchange of interference intensity as described in the initial intensity-height relationship.  338 \n 339 \nTo combine with optical tweezers to study membrane tension 340 \nUsing interferometric spatiotemporal images of RO-iSCAT and in combination with optical 341 \ntweezers 33, we expect to potentially quantify membrane tension of the twisting nascent filopodia 342 \n10 (Fig. 4). More recently, Belly et al 34 showed using optogenetics that 2D actin-driven protrusions 343 \ncan elicit rapid global membrane tension propagation  resulting in long-range membrane flows . 344 \nUsing RO-iSCAT along with calibrated tweezers, one can study 3D axial membrane protrusion 345 \nwhen dynamics forces (optical forces) are applied to the actin cortex.  346 \n 347 \nIncomplete abscission , phagocytosis and cell adhesion were quantified by measuring 348 \ncytoplasmic bridge properties, 3D filopodial dynamics on bacteria and nanotopologies. 349 \nThe physical properties of membrane bridges provide insight into abscission completion 350 \nduring the final stages of cell division 35, and 3D filopodia extensions define the distinct stages of 351 \nphagocytosis as immune cells clearing bacteria 4and recognition of nanotopologies that guides cell 352 \nmigration 7. While many studies utilize confocal microscopy, its axial resolution  and high 353 \nphototoxicity remains a key limiting factor  for live axial imaging and tracking of filopodia. 354 \nROiSCAT's value lies in its axial sensitivity  and low phototoxicity, which operates below the 355 \ndiffraction limit  and require minimal power (~microwatts). Consequently, we anticipate that 356 \nROiSCAT will be highly valuable in quantifying incomplete abscission , cell migrating on nano-357 \nscale surfaces and phagocytosis. 358 \n 359 \nConclusion 360 \nWe showed that RO-iSCAT interference patterns generate highly distinctive spatial-temporal 361 \ninterference intensity patterns between different cell membrane protrusion, i.e. membrane that are 362 \ntethered onto substrates, trails (e.g. migrasomes) and membrane bridges between adherent cells  363 \nacross large physical gaps 27, 36  Unlike scattered only or fluorescence signals used in kymograph, 364 \nthe spatial temporal interference patterns create d unique axial variation  plots for image -based 365 \nclassification. These characteristics were shown to be applicable across a range of adherent cell 366 \ntypes, including endothelial, CAF and PDA cells. This pilot study has highlighted the potential of 367 \nour method in extracting membrane specific  interferometric patterns  that eludes fluorescent 368 \nimaging. This study enables the classification of membrane protrusions that, despite possessing 369 \nidentical chemical compositions, are differentiated by their interactions, thus offering a qualitative 370 \ncomparison of cell-cell communication at the nanoscale in living cells 371 \n 372 \nAuthor Contributions 373 \nConceived project and directed research: W.M.L.  374 \nPrepared samples: Y .J.L., P.T., W.M.L., D.H., T.G.P, P.T. 375 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nBuilt model and programed simulations: J.L., M.G., H.L. 376 \nDesigned and performed experiments: J.L., Y .J.L., W.M.L. 377 \nExamined and analyzed data: J.L., W.M.L. 378 \nWrote manuscript: J.L., W.M.L., with advice from all authors.  379 \nProvided biological insight and advice: Y .J.L., W.M.L.  380 \nSupervised research: M.G., H.L., W.M.L. 381 \n 382 \nAcknowledgments 383 \nWe thank Alpha Yap (IMB, UQ) and Melanie White (IMB, UQ) on membrane protrusion and 384 \nfilopodia discussions; and Hari Shroff (Janelia, HHMI) on the RO -iSCAT. We acknowledge the 385 \nAustralian Research Council  (DE160100843, DP190100039, and DP200100364) and NHMRC 386 \n(APP2000485) for their support.  H.L. acknowledges funding from the National Natural Science 387 \nFoundation of China (62427807) and the Talent Program of Zhejiang Province (2021R51004) . 388 \nM.G. acknowledges funding from the National Natural Science Foundation of China (62475232). 389 \nJ.L. acknowledges the support from Zhejiang University Global Partnership Fund.   390 \n 391 \n 392 \nMethods 393 \nExperiment setup 394 \nRO-iSCAT/Scattering data acquisition 395 \nOur rotating optical coherent scattering platform (ROCS) is equipped with 60  1.49NA oil 396 \nimmersion objective lens (Olympus) and an sCMOS camera (PCO edge 4.2) for wide field 397 \nillumination and detection resulting in a pixel size of 20 nm and a full field -of-view over 41 398 \nmicrons  41 microns. 399 \nA 488 nm laser beam is directed onto a two-axis galvanometer and conjugated onto the back 400 \nfocal plane of the objective lens to generate an oblique angle and rotational azimuth. The camera 401 \nperforms capture under a preset framerate (up to 100 fps) and duty cycle while the incident beam 402 \nseparately rotates at a fixed speed of 200 rounds per second. ROCS sets oblique illumination angles 403 \nto switch between interferometric (22 ) and scattering imaging (60 ) modes for simultaneous 404 \nmultimodal imaging. In addition, RO -iSCA T modality requires a glass bottom culture dish or 405 \ncoverglass for generating reference reflection light, so in the other scattering mode , the reflection 406 \nwill be rejected by an electronic amplitude filter (diaphragm) placed at the imaging back focal 407 \nplane.  408 \n 409 \niSCAT data acquisition and post-processing 410 \nThe iSCAT raw images were acquired from ROCS system by fixing the galvanometer with 411 \n𝜃 = 22°  and 𝜙 = 0°  under RO-iSCAT mode. Because ROCS platform adopts the strategy that 412 \nmoving the objective lens  or sample container  to adjust the focal plane, the reference field is 413 \ndifferent at different focal position s thus caused varying background images . A series of 414 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nbackground images were acquired from an empty glass dish or coverglass under different focal 415 \npositions and exposure times. 416 \nFor isolating pure background artifacts arising from optical components, we meticulously 417 \nmaintained the system’s condition, particularly the stage position, and replaced the petri dish with 418 \nanother one only with PBS as a control, then captured the background image (Fig. 2c). Noted that 419 \nthe apparent fringes in background will blur or focus and undergo overall intensity changes during 420 \nthe stage moving along the z-axis. Thus, background subtraction necessitates the 1) pre-collection 421 \nof a series of background pattern s at each z position and after each biological acquisition, 2) a 422 \nmanual selection for matched background due to the limited repeatability of the translation stage. 423 \nAfter background subtraction ( Fig. 2d), the interference image marginally excluded some 424 \nambiguous artifacts, but generally, no new fringes of gold particles emerged from the background.  425 \n 426 \nCalibration protocol  427 \nWe used 40nm AU nanoparticles in a cell culture dish full of DMEM solution to illustrate the 428 \nsinusoidal relationship between interferometric intensity and depth gradient (Supplementary Fig. 429 \n9a, 9b) in RO-iSCAT. The exposure time of the camera was set to 85ms. 430 \nThe dish was placed on a piezo nanostage that adopted axial sweeping of the sample across 431 \nthe focus at 10 nm steps. The axial intensity map of a single nanoparticle is plotted as the orange 432 \nscattered plot, and the black line indicates the moving average of  8 points (Supplementary Fig. 433 \n9c). The cursor s represent the linear region that can be used to map from intensity (ΔI) to axial 434 \ndisplacement (Δz). 435 \n 436 \nRO-iSCAT model 437 \nField model from physical optics theory 438 \nIn RO -iSCAT, particles of a sample are illuminated by incident coherent laser filed 𝐄inc 439 \npropagating from the objective lens and create a scattering field 𝐄scat. Meanwhile, the glass bottom 440 \nof petri dish or coverglass reflects part of the incident light and form a weaker reflection field 𝐄refl. 441 \nThe reflection field 𝐄refl and scattering field 𝐄scat return to the imaging plane and jointly form the 442 \ninterference pattern. 37, 38 443 \nThe final fields reaching the camera are the convolution of the initial field in object space and 444 \nthe intrinsic coherent transfer function 𝐂 of the optical system, and we get the interference pattern 445 \nas 446 \n𝐼 = |𝐄refl ⋆ 𝐂 + 𝐄scat ⋆ 𝐂|2 1) 447 \nWe built the Cartesian coordinate system xyz where z-axis is fully aligned with the optical 448 \naxis of the objective lens, the coverglass and the focal plane of the objective lens are respectively 449 \nset as 𝑧 = 0 and 𝑧 = 𝑧𝑓. Considering that nano-scale system usually adopts high -NA design, we 450 \nassume that 𝐂  is a vector with an impulse response function as amplitude for simplicity, 451 \ncorrespondingly, the interference pattern can be treated as formed by the initial reflection and 452 \nscattering field reaching the focal plane 𝑧 = 𝑧𝑓 453 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\n𝐼(𝑥, 𝑦) = 𝐸refl\n2 (𝑥, 𝑦, 𝑧𝑓)+ 𝐸scat\n2 (𝑥, 𝑦, 𝑧𝑓)+\n2𝐸refl(𝑥, 𝑦, 𝑧𝑓)𝐸scat(𝑥, 𝑦, 𝑧𝑓)cos[𝜙scat(𝑥, 𝑦, 𝑧𝑓)− 𝜙refl(𝑥, 𝑦, 𝑧𝑓)]  2)\n 454 \nWe assumed the laser beam with constant intensity in section instead of Gaussian distribution, 455 \nand an incident at the oblique angle 𝜃 to the z axis and rotational azimuth 𝜑 around it. Ignoring 456 \nthe 𝜔𝑡 item that describes how the wave evolves over time and supposing the initial phase at 457 \n(0,0,0) as zero 458 \n𝐄inc(𝑥, 𝑦, 𝑧) = 𝐸inc𝑒𝑖𝑛𝑘(𝑥 sin 𝜃 cos𝜑+𝑦 sin 𝜃 sin 𝜑+𝑧 cos𝜃) 3) 459 \nwhere 𝑛 is the refractive index of the air and 𝑘 = 2𝜋 𝜆⁄  is the vacuum wavevector. As for the 460 \nreflection field from oblique incidence, the amplitude and phase changes are complexly 461 \ndetermined by the oblique angle according to the Fresnel formula, so we simply noted reflective 462 \nindex 𝜏𝜃 and phase shift 𝜙𝜃 as function of 𝜃 in reflection field 463 \n𝐄refl(𝑥, 𝑦, 𝑧) = 𝐸inc𝜏𝜃𝑒𝑖𝑛𝑘(𝑥 sin 𝜃 cos𝜑+𝑦 sin 𝜃 sin 𝜑−𝑧 cos𝜃)+𝜙𝜃 4) 464 \nWe consider a single nano-scale particle with sub-wavelength size and 𝑛𝑝 density located at 465 \n(𝑥𝑝, 𝑦𝑝, 𝑧𝑝). The laser is scattered by the particle with the initial phase 466 \n𝜙scat(𝑥𝑝, 𝑦𝑝, 𝑧𝑝) = 𝑛𝑚𝑘(𝑥𝑝 sin𝜃cos𝜑 + 𝑦𝑝 sin𝜃sin𝜑 + 𝑧𝑝 cos𝜃) 5) 467 \nand amplitude variation to 468 \n𝐸scat(𝑥𝑝, 𝑦𝑝, 𝑧𝑝) = 𝐸inc(1 − 𝜏𝜃) 2√2𝜋2\n(𝜆 𝑛𝑚⁄ )2 𝑎3 ( 𝑛𝑝2 − 𝑛𝑚2\n𝑛𝑝 + 2𝑛𝑚2 ) √1 + cos2 𝜃scat 6) 469 \nin which 𝑎 is the particle radius and 𝜃scatis the scattering angle for representing anisotropic 470 \nscattering efficiency. By combining the initial phase and amplitude, we can achieve the scattering 471 \nfield with spherical wavefront 472 \n𝐄scat(𝑥, 𝑦, 𝑧)= 𝐸scat(𝑥𝑝, 𝑦𝑝, 𝑧𝑝)\n𝑟(𝑥, 𝑦, 𝑧) 𝑒𝜙scat(𝑥𝑝,𝑦𝑝,𝑧𝑝)+𝑖𝑛𝑚𝑘𝑟(𝑥,𝑦,𝑧) 7) 473 \nwhere 𝑟  is the propagation length 𝑟(𝑥, 𝑦, 𝑧) = √(𝑥 − 𝑥𝑝)\n2\n+ (𝑦 − 𝑦𝑝)\n2\n+ (𝑧 − 𝑧𝑝)\n2\n 474 \nand cos𝜃scat = (𝑧𝑝 − 𝑧𝑓) 𝑟(𝑥, 𝑦, 𝑧)⁄ . 475 \nAnd finally, we obtain the constant, amplitude , and phase items of the interference field at 476 \nthe focal plane 477 \n𝐸const(𝑥, 𝑦)= (𝐸inc(1 − 𝜏𝜃) 2√2𝜋2\n(𝜆 𝑛𝑚⁄ )2 𝑎3 ( 𝑛𝑝\n2 − 𝑛𝑚\n2\n𝑛𝑝 + 2𝑛𝑚2 ) √1 + cos2 𝜃scat\n𝑟(𝑥, 𝑦, 𝑧𝑓)  )\n2\n+ (𝐸inc𝜏𝜃)2 8) 478 \n𝐸intef(𝑥, 𝑦)= 2𝐸inc\n2 𝜏𝜃(1 − 𝜏𝜃) 2√2𝜋2\n(𝜆 𝑛𝑚⁄ )2 𝑎3 ( 𝑛𝑝2 − 𝑛𝑚2\n𝑛𝑝 + 2𝑛𝑚2 ) √1 + cos2 𝜃scat\n𝑟(𝑥, 𝑦, 𝑧𝑓)  9) 479 \n𝜙intef(𝑥, 𝑦) = 𝑛𝑘𝑚{sin𝜃[(𝑥 − 𝑥𝑝)cos𝜑 + (𝑦 − 𝑦𝑝)sin𝜑]}\n−𝑛𝑘𝑚{𝑟(𝑥, 𝑦, 𝑧𝑓)+ (𝑧𝑝 − 𝑧𝑓)cos𝜃} + 𝜙𝜃 10)\n 480 \nThe equation of  the interference phase relates to two key series of var iables, (𝜃, 𝜑) for 481 \ndescribing the incidence off principle optical axis and 𝑧𝑝 − 𝑧𝑓 for measuring the defocused length. 482 \n𝑧𝑓  is typically maintained  as we usually fix the relative position between  objective lens and 483 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\ncontainer during imaging process. iPSF can be generated by changing 𝑧𝑝 − 𝑧𝑓 and 𝑧𝑓, respectively 484 \ncorresponding to the situation axial movement of 1) sample-only and 2) focal plane by adjusting 485 \nthe objective lens or the whole sample container (Supplementary Fig. 6). To visualize their roles 486 \nin phase difference, we correspondingly split it into one off-axis and one defocused item 487 \n𝜙off−axis(𝑥, 𝑦)= 𝑛𝑘𝑚 sin𝜃[(𝑥 − 𝑥𝑝)cos𝜑 + (𝑦 − 𝑦𝑝)sin𝜑] 11) 488 \n𝜙defocus(𝑥, 𝑦)= −𝑛𝑘𝑚[𝑟(𝑥, 𝑦, 𝑧𝑓)+ (𝑧𝑝 − 𝑧𝑓)cos𝜃] 12) 489 \n 490 \nLateral shift of out-of-focus pattern 491 \nIn simulation, we set 𝜃 to 22° as a constant while 𝜑 in the range of 0 °~360° as a variable 492 \nconsidering the configuration of our RO -iSCAT and place the phantom particle at the center of 493 \nFOV (0,0, 𝑧𝑝). The container position was fixed for a constant 𝑧𝑓 and we investigated the field 494 \ncreated by defocused particle at 𝑧𝑝 with ∆𝑧 = 𝑧𝑝 − 𝑧𝑓 defocused length. 495 \nTo mathematically quantify the lateral shift of pattern, we took the partial derivative of the 496 \ntotal phase difference respectively to 𝑥, 𝑦  497 \n𝜕𝜙intef(𝑥, 𝑦, 𝑧𝑓)\n𝜕𝑥 = 𝑛𝑘𝑚 (sin𝜃cos𝜑 − 𝑥\n√𝑥2 + 𝑦2 + ∆𝑧2\n)  13) 498 \n𝜕𝜙intef(𝑥, 𝑦, 𝑧𝑓)\n𝜕𝑦 = 𝑛𝑘𝑚 (sin𝜃sin𝜑 − 𝑦\n√𝑥2 + 𝑦2 + ∆𝑧2\n)  14) 499 \nFrom which we can achieve  the specific extremum point (𝑥𝑒, 𝑦𝑒, 𝑧𝑝)by setting the gradient 500 \nsimultaneously to 0 501 \n𝑥𝑒 = tan𝜃cos𝜙 ∆𝑧 15) 502 \n𝑦𝑒 = tan𝜃sin𝜙 ∆𝑧 16) 503 \nand the distance of its biased to centre point is 504 \n𝐿 = tan𝜃∆𝑧 17) 505 \n 506 \nQuantitative image quality analysis 507 \nMeasuring the radius of lateral shifting 508 \nThe focused position of 2 microns markers was set as zero axial position and gradually moved 509 \nthe along z-axis from negative 2000 nm to positive 2000 nm in 10 nm step using a high-dynamics 510 \nZ nano-positioning stage (Physikinstrumente P-736.ZR1).  511 \nAt each axial position, the camera got images from 12 azimuth points . The 12 centers of the 512 \nmarker were labeled and recorded by Manual-tracking plugin in Fiji (ImageJ2 core) , then fitted 513 \nthe circle from the shifted centers to get the radius. We use d negative and positive signs  to 514 \ndistinguish from clockwise and counterclockwise rotational shifting. 515 \n 516 \nInterference fringe contrast for azimuth-sampling dataset 517 \nThe RO -iSCAT images were used as ground truth, i.e. the pure signal, while the middle 518 \noutputs as the polluted overlay with noise and artifacts. During azimuth down sampling, due to 519 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nlateral shifting direction varying at different azimuth point, the asymmetric azimuth combination 520 \n(i.e., odd number sampling points)  will retain some of this property. This results in a  slightly 521 \ndistorted morphology that does  not perfectly match  the ground truth. Therefore, instead of 522 \nsubtracting the pure signal to determine the noise level, a common approach in SNR calculations, 523 \nwe directly use the down azimuthal sampling image to measure the level of noise. 524 \nWe respectively selected 8 rois from the empty background and signal-intensive cell regions, 525 \nthen valued the pollution of messy noise to smooth structures by 526 \n𝐶𝑜𝑛𝑡𝑟𝑎𝑠𝑡𝑛 = 𝑉𝑎𝑟(𝐼𝑅𝑂−𝑖𝑆𝐶𝐴𝑇)\n𝑉𝑎𝑟(𝐼𝑛)  18) 527 \n 528 \nSimulation and SNR-measurement for speckle-noise 529 \nAccording to experimental observation (Supplementary Video 1), speckle noise is frame-530 \nuncorrelated and reserves the property of lateral shift same as physical particles. Hence, we model 531 \nthem as random particles with varying reflectivity value at one out-of-focus plane that generate 532 \nunexpected fringes onto focal plane. For Fig. 1e , in a 200 ×200 pixels (4μm×4μm) FOV, we 533 \nuniformly set one single particle on focal plane alongside with 600 particles at 1 μm depth (speckle 534 \nnoise from out-of-focus plane), then overlap all the fringes simulated from our model.  Specifically, 535 \nwhile the reflectivity of in -focus particle is set to 1 as reference,  the relative reflectivity among 536 \nthose 600 speckles follows the Gaussian distribution  but with an absolute operation to avoid 537 \nnegative values |𝒩(0, 𝜎2)| 538 \n𝑓(𝑥)= | 1\n√2𝜋𝜎2 𝑒− 𝑥2\n2𝜎2| 539 \nwhere we use 𝜎 to measure the speckle noise level. 540 \nTo calculate the SNR of the  synthetic fringes under iSCAT and RO-iSCAT modality, we 541 \nselected the central region 𝐼𝑠 (5×5 pixels) from the on-focus particle fringe to calculate the variance 542 \nof pure si gnal. As to the variance of speckle noise, we measure the variance of the overlapped 543 \nfringe (on-focus particles and out-of-focus speckle) excluding the central region, 𝐼𝑛𝑜𝑖𝑠𝑒. 544 \n𝑆𝑁𝑅 = 𝑉𝑎𝑟(𝐼𝑠)\n𝑉𝑎𝑟(𝐼𝑛𝑜𝑖𝑠𝑒) 19) 545 \n 546 \nSample preparation 547 \nCell culture 548 \nAll reagents for cell culture were sourced from Thermo  Fisher Scientific (Waltham, MA, 549 \nUSA). CAF and PDA cells (Passage 30) were maintained in T75 flasks with DMEM supplemented 550 \nwith high glucose (4.5 g/L), 10% fetal bovine serum, L -glutamine (4 mM) and pyruvate (1 mM) 551 \nat 37°C and 5% CO2. Cells were split 1:20 at 80% confluence. Primary human lung microvascular 552 \ncells (HMVEC, Lonza) were cultured in EGM2-MV2 Bulletkit (Lonza) at 37°C and 5% CO2 and 553 \nsplit at a 1:6 ratio at 80% confluence. 554 \n 555 \nLive cell imaging 556 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nCells were first grown to 80% confluence and then 100,000 cells seeded to 29 mm glass 557 \nbottom dishes ( #1 coverslip, CellVis). Cells were incubated at 37°C and 5% CO2 for at least 1 558 \nhour prior to imaging. 559 \n 560 \nCAF cell transfection 561 \nFor fluorescent labeling of the CAF cell membrane, we used an Lck10 -GFP plasmid 562 \n(generous gift from the late Katharina Gaus). The Lck10-GFP consists of the first 10 amino acids 563 \nof the membrane protein Lck and eGFP linked to the C -terminus. Plasmids were propagated in 564 \nE.coli in LB Medium and purified using a miniprep kit (Genejet, Thermo Scientific). C AF cells 565 \nwere transfected with polyethyleneimine (40 kDA, linear, Polysciences Inc) using 9 ug PEI and 3 566 \nµg DNA per 29 mm dish over 48 hours prior to imaging. 567 \n 568 \nNanoparticles  569 \nGold nanoparticles ( 40 nm ) were diluted 1000 times in distilled water . 1 mL of  diluted 570 \nnanoparticles were then added to a dry 29 mm glass bottom dishes (#1 coverslip thickness, CellVis) 571 \nand allowed to dry for 1 hour at room temperature. Prior to imaging, 1 mL of 1X PBS was carefully 572 \npipetted along the walls of the dish.  The dish was then mounted onto a Z nano-positioning stage 573 \n(Physikinstrumente P-736.ZR1) for imaging. 574 \n 575 \nCAF cell with nanoparticle 576 \n40 nm gold nanoparticles were dried onto a glass bottom dishes (#1 coverslip thickness, 577 \nCellVis) for 1 hour as described above. The dried particles were then immersed in high glucose 578 \nDMEM prewarmed to 37°C. 1 mL of CAF cells (100,000 cells/mL) was then added dropwise 579 \nonto the dish and incubated for 1 hour at 37°C and 5% CO2 and then mounted onto a heated 580 \nstage for imaging. 581 \n 582 \nCAF cell co-culture (WT and Lck10) 583 \nWe seeded 100,000 cells into two separate 29 mm glass bottom dishes (#1 coverslip, CellVis). 584 \nAfter 24 hours, one dish was transfected with Lck10 -GFP plasmid and incubated for another 48 585 \nhours. Cells in WT and transfected dishes were then detatched with trypsin (0.25%  (w/v)) and 586 \nEDTA (1 mM) and 50,000 cells each seeded and mixed into a new 29 mm glass bottom dish. Cells 587 \nwere incubated for 4 hours at 37°C and 5% CO2 prior to imaging. 588 \n 589 \nCAF and PDA co-culture 590 \nTo create separate CAF and PDA cell populations on a single dish, cells were concentrated to 591 \n1 million cells/mL and 100 μL were pipetted to s eparate corners of a 29 mm glass bottom dish. 592 \nCells were incubated for 1 hour 37°C and 5% CO2 to allow the cells to attach to the glass dish. 593 \nCell attachment was monitored under a bright field microscope. Cells were then supplementing 594 \nwith 1 mL of DMEM and incubated for 7 days, with media changed every 2 days. 595 \n 596 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\n 597 \nData availability 598 \nThe data that support the findings of this study are included in Figs. 1–4, Supplementary Figs. 599 \n1–10 and Supplementary Videos 1 –10. All  experimental data  from figures ( Figs. 2 , 3, 600 \nSupplementary Fig s. 5-9) are publicly available at https://doi.org/10.5281/zenodo.14960905. 601 \nOther time-lapse co-culture datasets (Fig. 4) are available from the corresponding author W.M.L 602 \nupon request due to their large file size. 603 \n 604 \n 605 \nCode availability 606 \nAll numerical modelling and analysis were achieved using Python 3.11.0. Generation of iPSF by 607 \nBoundary-Element-Method was performed in MA TLAB (Mathworks, R2022b). Customized RO-608 \niSCAT model and analysis codes are available at https://github.com/ejunyuliu/RO-iSCA T. Initial 609 \nnumerical iSCAT model was installed from https://github.com/manoharan-lab/applied-optics-610 \niscat-code. iSCAT software based on Boundary-Element-Method platform was downloaded from 611 \nhttps://pubs.acs.org/doi/suppl/10.1021/acsphotonics.4c00621/suppl_file/ph4c00621_si_001.zip. 612 \n 613 \n 614 \n 615 \n  616 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nReference 617 \n1. Bruce, A. Molecular biology of the cell. (Second edition. New York : Garland Pub., [1989] 618 \n©1989, 1989). 619 \n2. Jaqaman, K. & Grinstein, S. Regulation from within: the cytoskeleton in transmembrane 620 \nsignaling. Trends in Cell Biology 22, 515-526 (2012). 621 \n3. Wood, W. & Martin, P. 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Mitochondrial transfer from cancer -associated fibroblasts increases 682 \nmigration in aggressive breast cancer. Journal of Cell Science 136 (2023). 683 \n29. Dhungel, N. & Dragoi, A.-M. Exploring the multifaceted role of direct interaction between 684 \ncancer cells and fibroblasts in cancer progression. Frontiers in Molecular Biosciences 11 685 \n(2024). 686 \n30. Hecht, E. Optics. (Pearson Education, Incorporated, 2017). 687 \n31. Dahmardeh, M., Mirzaalian Dastjerdi, H., Mazal, H., Köstler, H. & Sandoghdar, V . Self -688 \nsupervised machine learning pushes the sensitivity limit in label -free detection of single 689 \nproteins below 10 kDa. Nature Methods 20, 442-447 (2023). 690 \n32. Sheppard, C.J.R., Cogswell, C.J. & Gu, M. Signal strength and noise in confocal 691 \nmicroscopy: Factors influencing selection of an optimum detector aperture. Scanning 13, 692 \n233-240 (1991). 693 \n33. Pompeu, P. et al. Protocol to measure the membrane tension and bending modulus of cells 694 \nusing optical tweezers and scanning electron microscopy. STAR Protocols 2, 100283 (2021). 695 \n34. De Belly, H. et al. Cell protrusions and contractions generate long-range membrane tension 696 \npropagation. Cell 186, 3049-3061.e3015 (2023). 697 \n35. Chaigne, A. & Brunet, T. Incomplete abscission and cytoplasmic bridges in the evolution 698 \nof eukaryotic multicellularity. Current Biology 32, R385-R397 (2022). 699 \n36. Korenkova, O., Pepe, A. & Zurzolo, C. Fine intercellular connections in development: 700 \nTNTs, cytonemes, or intercellular bridges? Cell Stress 4, 30-43 (2020). 701 \n37. de Wit, X.M. et al. Precise characterization of nanometer -scale systems using 702 \ninterferometric scattering microscopy and Bayesian analysis. Appl. Opt.  62, 7205 -7215 703 \n(2023). 704 \n38. Gholami Mahmoodabadi, R. et al. Point spread function in interferometric scattering 705 \nmicroscopy (iSCA T). Part I: aberrations in defocusing and axial localization. Opt. Express 706 \n28, 25969-25988 (2020). 707 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\n 708 \n  709 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\n 710 \nFig. 1 Modelling and simulation of R O-iSCAT.  a) Schematic diagram of incident, reflection, 711 \nscattering fields, and several reference planes in azimuthal iSCA T. b) Numerical simulation with 712 \n14 microns FOV and 70 nm step based on the modelling. Including i, off-axis oblique phase and 713 \nii, oblique convolved with defocused phase, respectively at 0 /90120 with a 10 μm 714 \ndefocused length and 22 oblique angle. iii, Profiles of off-axis oblique, defocused, and total phase 715 \ndifference along the horizontal cent ral axis of FOV. iv, Interference pattern  at corresponding 716 \nazimuth angle. c) The radius of lateral shifting under defocused length ranging from -2.5 μm to 717 \n2.5 μm in ~290 nm step extracted from simulation and experimental data. The experiments were 718 \nrepeated five times independently, as indicated by error bars (mean +/- SD). d) i, Circumferential 719 \nlateral-shifting related to illumination azimuth and defocused length . ii, Azimuthally integrated 720 \ninterference pattern. Also attached the corresponding intensity profile along the horizontal central 721 \naxis of FOV. e) i, Sketch presentation to show the strategy of simulating different speckle noise 722 \nlevel. One single particle at in-focus plane as signal source, while a series of speckles are placed 723 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nat 10-micron depth with their reflectivity value following the Gaussian distribution . ii, In-focus 724 \nfringes from iSCAT versus RO-iSCAT based on the object  in i. Inserted ground truths are pure 725 \ninterference fringe only from the in-focus particle. iii, Noise variance and fringe SNR curve with 726 \nvarying reflectivity levels of speckle sources, both in iSCAT versus RO-iSCAT. Scale bars: b), d) 727 \n3 μm, e) 1 μm. 728 \n 729 \n  730 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\n 731 \nFig. 2 Reduction of speckle background through rotational integration . a)  Diagrammatic 732 \nsketch of conventional iSCAT and RO-iSCAT imaging method. Bottom right is the sketch map of 733 \northogonal galvos and the transition from flipping at the galvo to lateral circling at the back focal 734 \nplane, and finally to illumination with specific tilting angle and varying azimuth emitted from the 735 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nobjective lens. b) Raw iSCAT image of 40nm gold particles with 500  ms exposure time. Gold 736 \nparticles were dried thus adhered to the inner glass bottom, then PBS for 1:20 dilution to the initial 737 \nstorage liquid of particles. c) Manually selected background pattern from PBS -only control dish 738 \nunder the same exposure time. d) Final iSCA T image after post -processing of background 739 \nsubtraction. The d ashed rectangle region highlights the blurring pattern in iSCAT but well -740 \ndistinguished by RO -iSCAT. e)  RO-iSCA T images from different incoming azimuths  without 741 \nintegration. f) Final RO -iSCA T image with time -integrating during rotational scanning.  g) 742 \nIntensity profile of raw image, background and the final result after subtraction, along the dashed 743 \nline in magnified image cropped from d), the orange and background scatters are labeled by left y 744 \naxis while the blue curve is by right y axis.  h) Intensity profile of image at azimuth position of 0, 745 \n90, 180, 270 and final integrated result along the f) region that corresponds to the dashed line, 746 \nthe blue curve is by right y axis while the scatters in other colours are labelled by left y axis.  i) Z 747 \nsection and the corresponding profile along z axis from interference PSF captured from 40 nm 748 \nparticles, individually without rotational integration and with rotational integration configuration. 749 \nj) Without rotational integration (top) against with rotational integration (bottom) modality of CAF 750 \ncells seeded with 40 nm particles. Scale bars: b)-d), f) 250 nm, e) 500 nm, g)-i) 400 nm, j) 5 μm. 751 \n  752 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\n 753 \nFig. 3 Identifying types of membrane trails and connections with RO -iSCAT. a) i and ii are 754 \nraw RO-iSCAT of CAF cell membrane trails and connections from RO-iSCAT captured at 5 fps 755 \n(50% duty cycle) over 10 seconds. b), Magnified images of the cyan rectangle regions in a). Top, 756 \ncell membrane trails observed directly on substrates . Middle, cell membrane tethers mixed with 757 \nmembrane trails on substrates. Bottom, direct cell-cell tethers without any membrane trails on the 758 \nsurface. c) Proposed concept of biological diagrammatic sketch of neighbouring cells cultured on 759 \nglass bottom dish, in which each main membrane protrusion type  will create different scattering 760 \nfield. d) Procedure of calculating axial-variation map. i, RO-iSCAT fringe along one single 761 \nprotrusion at 0  s, 3 s and 6  s time points. ii, Axial distribution of this protrusion  at several time 762 \npoints. Profiles were fitted from raw curve only for better presentation here (8th degree polynomial 763 \nwith R2=0.94, 0.96, 0.92, 0.82 separately). iii, Standard deviation measuring the effective axial 764 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\ndisplacement at each pixel. iv. Pixel-level standard deviation on the entire 2D image relative depth 765 \nover the time period . e) Calculated axial-variation maps of respective raw RO -iSCAT images in 766 \na). f) Histograms counted from the trails and connections regions in b), with mean values noted 767 \nfor membrane trail, tether and bridge groups. Scale bars: a), e) 3 μm, b), d) 500 nm. 768 \n  769 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\n 770 \nFig. 4 Tracking and quantifying protrusion between trails and connections with RO-iSCAT. 771 \na) i, Experiment time sequence of co-culturing Lck10-GFP transfected and non -transfected WT 772 \nCAF cells. On day 1, WT CAF cells were seeded into 2 dishes and only one of them was transfected 773 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint \n\nby Lck10-GFP dye. On day 3, we transferred the transfected cells  into the WT CAF cell dish . 4 774 \nhours later, the mixed dish was uploaded for imaging. ii, Scattering-only image captured at 4th hour 775 \non day 3  containing only one transfected cell  (marked by light blue circle) . iii , Magnified 776 \nfluorescence image of the Lck10 -GFP transfected cell in FOV (dashed light blue circle  in ii. b) 777 \nTime-lapse fluorescent images of the red rectangle region in a). c) The comparative RO -iSCAT 778 \nimages where the two different arrows consistently track the same protrusion across different time 779 \npoints. d) i, Experiment time sequence of PDA and CAF cells co-culture. On day 1, we seeded 780 \nCAF and PDA cells separately at opposite side of one dish. During day 1 to 8, each will migrate 781 \ntowards the center over 7 day-long culture in incubator. On day 8, imaging was performed where 782 \nthe two cell populations intersected . ii, iii, Bright field images under stereo microscope of PDA-783 \nCAF co-culture dish at day 7 and 8 after seeding. e) Scattering-only image of a FOV containing 784 \none PDA and CAF cell. f) Snapshots in time -lapse stack of the cyan rectangle region in e), 785 \nindividually displaying the filopodia interacting, connecting, merging and the final merged 786 \ndynamics. g) Axial variation map of f) counting from 50 frames (5 fps) around each time point. h) 787 \nViolin plot of axial variation distribution along membrane protrusion in each time point. Cyan and 788 \nred lines represent median and quartiles, respectively. Counted protrusions have been pointed out 789 \nby yellow arrows. Scale bars, a), e), 5 μm, b), f) 1 μm. 790 \n 791 \n.CC-BY 4.0 International licenseavailable under a \n(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made \nThe copyright holder for this preprintthis version posted March 25, 2025. ; https://doi.org/10.1101/2025.03.23.644841doi: bioRxiv preprint","source_license":"CC-BY-4.0","license_restricted":false}