Clostridium perfringens as a bacterial virulence factor able to form giant ring-shaped pores that perforate and ultimately lyse mammalian cell membranes. To resolve the kinetics of all steps in the assembly pathway, we have used single-molecule fluorescence imaging to follow the dynamics of PFO on dye-loaded liposomes that lead to opening of a pore and release of the encapsulated dye. Formation of a long-lived membrane-bound PFO dimer nucleates the growth of an irreversible oligomer. The growing oligomer can insert into the membrane and open a pore at stoichiometries ranging from tetramers to full rings (~35 mers), whereby the rate of insertion increases linearly with the number of subunits. Oligomers that insert before the ring is complete continue to grow by monomer addition post insertion. Overall, our observations suggest that PFO membrane insertion is kinetically controlled.The cholesterol-dependent cytolysin perfringolysin O (PFO) is secreted by  Pore-forming proteins (PFPs) possess an ancient and ubiquitous mechanism for forming aqueous channels in the membranes surrounding cells and organelles . The larClostridium perfringens (Perfringolysin O (PFO), a prototypical example of a CDC, is secreted by the anaerobic bacterium fringens , which ifringens . As withfringens . A smallfringens ; howeverfringens .The steps in canonical CDC pore-formation have been well characterised; the proteins are secreted as soluble monomers, monomers bind to and then oligomerise on target membranes to form a ring-shaped prepore complex, the prepore complex then undergoes a concerted conformational change and inserts in the membrane to form a large (25–30 nm) amphipathic β-barrel bilayer-spanning pore . To resoLiposome dye release assays have long been used to investigate the kinetics of PFO pore formation . This asTo overcome the limitation of ensemble averaging, imaging methods have been developed to follow PFP assembly at the level of individual pores . ImagingTo observe PFP assembly and membrane permeabilisation simultaneously at the single molecule level, we have adapted the liposome dye release assay to measure kinetics on individual liposomes. By using single molecule total internal reflection fluorescence (TIRF) microscopy, we visualised the binding, nucleation, build up and insertion of individual PFO species. These data were subsequently used to develop a mathematical model for PFO pore formation in which parameters can predict the number of subunits in PFO oligomers at the time of insertion. We have also found in our assay that inserted PFO arcs, currently thought to be kinetically trapped, can continue to grow post insertion.Here, we developed a single-molecule approach to observe in real time the dynamic interactions between PFO and dye-loaded liposomes leading to dye release from individual liposomes using total internal reflection fluorescence (TIRF) microscopy. The assay design is shown schematically in TIRF pore formation movies were analysed using automated software for tracking the fluorescence intensity over time at each liposome location in both channels to generate single-liposome AF647-PFO binding and content dye release traces. A typical dual-colour pore formation trace recorded at a single liposome (highlighted with a white box in 2). At AF647-PFO concentrations between 100 and 500 pM, most liposomes lost their dye signal in a single step (>50%)  , while ~p (>50%) . The remp (>50%) , suggestp (>50%) . At 50 pp (>50%) . We tentp (>50%) .Single-step traces were identified for further analysis and initial inspection revealed that the time for nucleation of a growing PFO oligomer and the time for poration varied between liposomes, as did the number of subunits at the time of pore opening. These processes are analysed in more detail below. As expected, the kinetics of liposome poration decreased with decreasing AF647-PFO concentration . At highThe first step of PFO pore formation involves the binding of PFO monomers to the membrane , left. TThe scatter plot of x/y-coordinates for all molecules detected in tdark is highlighted in –1 for the example liposome shown in tbright is highlighted in B=0.9 ± 0.23 nM–1 s–1) which corresponds to 7.2±1.8 nM–1 s–1 μm–2 when taking the surface area of liposomes into account . As expected, the unbinding rate distributions . As expected, these interactions did not lead to pore formation, as liposomes retained their content dye for the duration of the experiments .The fast frame rate and high laser power required to image the binding of single AF647-PFO molecules to liposomes  made it Dr = 8.6 ± 3.4 x 10–4 s–1 after correction for photobleaching , that is three orders of magnitude longer than the monomer. We conclude that dimerisation on the membrane promotes strong PFO–PFO and PFO–membrane interactions. From our data we cannot distinguish whether the dimer disappears by unbinding from the membrane, or whether it dissociates to monomers that subsequently unbind from the membrane. We also note that the half-life of the dimer state is sufficiently long such that it is essentially irreversible on the time scale of PFO assembly at concentrations of ≥100 pM, where the entire pore formation process takes on average less than 20 min .At higher concentrations (≥25 pM), the transient interactions of PFO eventually lead to nucleation of a membrane-bound oligomer that continues to grow . The nuc–1 s–1. This oligomerisation rate is essentially the product of the rate of PFO monomer binding to the membrane and the probability of finding and joining the growing oligomer. The ratio between the oligomerisation rate constant (0.23 nM–1 s–1) to the single molecule binding rate constant (0.9 nM–1 s–1) reveals that 25% of the time, a PFO monomer binding to the membrane will end up joining the oligomer  occurred after onset of the AF647-PFO signal increase . AnalysiAfter wash-out, we observed that these dye-loaded liposomes showed a wide distribution of AF647-PFO oligomer sizes between 2 and 40 subunits , as expeWhen applied to all liposomes, this analysis allowed us to determine the efficiency and kinetics of pore formation for arcs containing a defined number of subunits (oligomer size). First, only a low fraction of liposomes with AF647-PFO dimers (~12%) or trimers (~20%) released their content dye, but pore formation efficiency increased sharply with oligomer size, reaching half-maximal efficiency for tetramers and becoming size-independent for arcs containing at least six subunits . We conc–1 for the transition from the prepore to the open pore state; this analysis is shown as an Arrhenius plot in –1We repeated the wash-out experiments at a range of temperatures to determine the activation energy of PFO oligomer insertion. First, we extracted dependence of insertion rates on the number of subunits in the oligomer between 22 and 37°C . FittingThe dual-colour pore formation experiments showed that even in the continued presence of AF647-PFO in solution, arcs instead of full rings  were the most common species to perforate the liposome membrane. To obtain an estimate of the insertion rate as a function of the number of subunits in the case of a continuously growing arc, we defined a normalised rate as follows. We divided the total number of insertion events for each given oligomer size (number of subunits) by the cumulative observed time across all detected instances of AF647-PFO oligomers of that size. As observed in the wash-out experiments above, the insertion rate depended linearly on the number of subunits in the oligomer at AF647-PFO concentrations between 50 and 500 pM . SurprisTo predict the number of subunits in the oligomer and the kinetics of insertion, we developed a kinetics model  than at pH 8 (~10 subunits)  and simiOn the basis of these analyses we conclude that the overall pronounced decrease of the pore formation efficiency and kinetics with increasing pH from slightly acidic to slightly alkaline is due to reduced affinity of the monomer binding to the membrane while PFO–PFO interactions are largely unaffected. This defect propagates through other phases of the assembly pathway, slowing nucleation and oligomerisation but not the kinetics of the prepore to pore transition. As a consequence, the mean number of subunits at the time of poration decreases with increasing pH. The implication of this observation is that other parameters that affect PFO–membrane affinity (such as lipid composition) would similarly tune whether insertion occurs early during PFO arc growth or when rings are  complete.By measuring the single-molecule kinetics of PFO accumulation on liposomes together with a functional read-out for pore opening at the level of single liposomes, we were able to identify distinct stages in the pore formation pathway that would be undetectable in ensemble measurements due to dephasing. Our analysis provides a complete kinetic description of CDC pore assembly from monomer binding to pore opening with the following characteristics: (i) PFO monomers repeatedly bind to and diffuse on the membrane surface and dissociate with a half-life of 0.3 s; (ii) dimerisation of two PFO monomers on the membrane represents the committed step that nucleates a stable growing oligomer; (iii) oligomerisation occurs by addition of monomers that bind to the membrane from solution and is essentially irreversible; (iv) oligomers (arcs) with as few as four (possibly fewer) subunits can insert into the membrane and open a membrane pore, whereby the rate of insertion increases approximately linearly with the number of subunits in the arc; this transition from the prepore to the pore state constitutes the main energy barrier in the pathway; (v) oligomers continue to grow after insertion by addition of PFO monomers, presumably forming complete rings.Our experimental approach relying on immobilised liposomes is complementary to AFM  and singLimitations of our approach include the following. Unlike measurements on flat membranes, we cannot resolve separate molecules or complexes on the same liposome due to the diffraction limit. While biochemical characterisation and AFM imaging of PFPs is typically carried out in the nM range, we limited the concentrations used in this study to the pM range to enhance the probability of observing the growth of a single complex per liposome. This is initially borne out in the data: The oligomerisation rate remains constant  instead Another limitation is that non-specific labelling of PFO (resulting in a heterogeneous sample of labelled species), as well as possible fluorescence artefacts, limit the precision with which we can determine the number of subunits in PFO oligomers. For validation, we determined the oligomerisation rate and number subunits in the oligomer at the time of pore opening by detecting and counting individual PFO monomers joining the growing oligomer. This intensity-independent analysis yielded essentially the same values as the quantification based on intensity.Consistent with previous observations for PFO and other CDC/MACPF pore formers , we findIt has been shown that several MACPF/CDC PFPs can insert into the membrane as arcs before formation of the full ring is complete . Our anaRemarkably, the rate of arc insertion increased linearly with the number of subunits in the arc such that insertion of low order oligomers can only be observed in the absence of growth. One interpretation of the dependence on the number of subunits in the oligomer is that any subunit can independently trigger the process leading to insertion of the entire pore, that is the more subunits are available, the higher the probability of insertion. Overall, our interpretation fits with the sequential insertion model for β-barrel formation , wherebyOur experiments also suggested that when oligomers are continuously growing, the insertion rate increases with the concentration of PFO in solution. This unexpected observation needs further investigation and validation. While we do not yet understand the underlying mechanism, one possible hypothesis is that the binding of a monomer to the growing oligomer induces a transient activated state that is more likely to insert. More frequent binding events (observed at higher PFO concentrations in solution) would then induce the activated state more frequently, leading to an overall increase in insertion kinetics.We observed that AF647-PFO accumulation on the liposome continued unabated after opening of an arc pore, which we interpret as post-insertion oligomer growth. Using single-molecule tracking on droplet interface bilayers supported on an agarose layer, Wallace and colleagues also observed that PFO oligomers continue to grow by monomer addition after insertion into the bilayer , wherebyReal-time imaging  and struAs discussed above, insertion can be observed over a wide range of oligomer sizes, ranging from ~tetramers to full rings. We propose a model in which the transition from arc or ring-shaped prepore to pore is a stochastic process that is controlled by the kinetics of the different steps in the pore formation pathway. For example, under conditions where membrane binding is slow (e.g. at low PFO concentrations or pH >7), oligomerisation is too slow to complete a full ring before insertion occurs. Since PFO monomers can continue to add after insertion, the final outcome is a ring-shaped pore, regardless of when insertion happened during arc growth. This is consistent with a predominance of ring pores in EM images, even when PFO assembly occurs at low concentrations . While tOverall, our single-molecule approach enables analysis of all steps leading to PFO pore formation to be deconvoluted and investigated separately, unlike existing ensemble assays. The assay design is simple to modify and enables multiple experimental modalities for different lines of inquiry. Further, the moderate throughput enables statistical power to quantify individual processes within the full assembly pathway. In conjunction with kinetic modelling, this analysis represents a useful method to predict and measure the effects of modification to specific steps in the pathway, with applications in drug development or biotechnology .E. coli BL21DE3 cells at 37 °C using a codon-optimised sequence cloned into the pET-15b plasmid. Cells were lysed in 20 mM HEPES pH 7.5, 150 mM NaCl, 20 mM imidazole, 0.1% Triton-X 100, protease inhibitor (Sigma) and DNAse I (Sigma). Cell debris was separated from the soluble fraction by centrifugation at 10,000 xg for 30 min at room temperature. The protein was purified by Ni2+ IMAC chromatography on a HisTrap column (Cytiva). The column was washed using 20 mM HEPES pH 7.5, 150 mM NaCl, 20 mM imidazole and bound protein eluted using 20 mM HEPES pH 7.5, 150 mM NaCl, 500 mM imidazole. Eluted protein was dialysed overnight into 25 mM HEPES pH 7.5, 150 mM NaCl, 2.5% glycerol and further purified by size exclusion chromatography on a SEC Superdex S200 16/60 column (Cytiva). Peak fractions were concentrated and stored at –80 °C.PFO C459A without signal peptide containing an amino-terminal hexahistidine tag  was used in this work. PFO C459A lacks the cysteine residue prone to oxidation (leading to inactivation) and has the same pore-forming activity as wild type PFO . The proPFO was dialysed twice for 1 hour against HBS pH 7.5  using a Slide-A-Lyzer Mini dialysis capsule (10 k MWCO) and the protein concentration (determined using the absorbance at 280 nM) was adjusted to 24 µM. The labelling reaction was carried out in the dark at room temperature. An aqueous solution of Alexa Fluor 647 (AF647) NHS ester (2.5 mM) was added to a concentration of 120 µM. The long-wavelength AF647 dye was chosen for PFO as it is less prone to self-quenching than short-wavelength dyes. After a reaction time of 1 h, HisPur Ni-NTA resin (40 µL) was added to the mixture. Beads were collected by centrifugation and washed with HBS pH 8 (3×50 µL). After elution with a 1:1 (v:v) mixture of 1 M imidazole (pH 7) and HBS (pH 7) for 10 min, the beads were pelleted by centrifugation and the supernatant containing AF647-PFO was collected. The protein concentration was determined using the Bradford assay. AF647-PFO was analysed by SDS-PAGE with fluorescence densitometry and the degree of labelling was determined to be ~1.5 fluorophores/PFO by comparison with a labelled protein standard. Analysis of AF647-PFO adsorbed onto a coverslip showed that the majority of PFO molecules (~60–85% depending on batch) were singly labelled, while the remainder had more than one label . The memSolutions of cholesterol, 1-palmitoyl-2-oleoyl-glycero-3-phosphocholine (16:0-18:1 POPC) and 1-(12-biotinyl(aminododecanoyl))–2-oleoyl-sn-glycero-3-phosphoethanolamine (12:0 Biotin-18:1 PE) in chloroform  were mixed in a 55:44:1 molar ratio. The solution was divided into 120 μL aliquots in glass vials, dried down under vacuum, overlaid with nitrogen and stored at –40 °C until use.The lipid film was allowed to equilibrate to room temperature, rehydrated in 250 μL HBS pH 7 containing 0.01 mg/mL AF488 and resuspended by forcefully passing the mixture several times through a 25 G needle. The sample was vortexed and subjected to 6 freeze-thaw cycles using liquid nitrogen. Liposomes were extruded using a LiposoFast liposome factory by passing the solution an uneven number of times (21–31) through a 0.22 μM polycarbonate membrane filter. The extruded liposomes were passed through a Sephadex G-25 column to remove free dye.–1 in PBS) was injected into the flow channels and incubated at room temperature for 5 min followed by flushing the channels with water and drying. The channels were then filled with a solution of streptavidin  for 15 min and rinsed with HBS pH 7. The channels were rinsed with isopropanol to remove air bubbles prior to treatment with blocking buffer . The microfluidic flow cell was mounted on the microscope stage and connected to tubing. Solutions were pulled through the channels using a syringe pump connected to the outlet tubing and operating in ‘withdraw’ mode.Microfluidic fabrication and TIRF assay adapted from AF488-loaded liposomes in HBS (30–100 μL) were flowed through the microfluidic channel and captured on the modified coverslip via interaction of the biotinylated lipids with the surface-bound streptavidin. Unbound liposomes were washed out with 50 μL of HBS pH 7. All experiments were carried out at room temperature unless stated otherwise.Images were collected on a custom built TIRF microscope based around an ASI-RAMM frame (Applied Scientific Instrumentation) with a Nikon 60×CFI Apochromat TIRF (1.49 NA) oil immersion objective. Solid State Lasers were incorporated using the NicoLase system . Images Experiments to measure AF647-PFO monomer binding were acquired as follows. HBS pH 7 (5 mL) containing AF647-PFO (2.5–15 pM) and BSA (0.01 mg/mL) as a blocking agent was constantly flowing through the channel at a rate of 10 µL/min. A total of 432,000 single molecule binding TIRF images were acquired for each independent experiment using a 20ms exposure and 100 mW 647 nm laser power at a frame rate of 57ms per frame.Experiments to measure the long-lived species were acquired as follows. HBS pH 7 (5 mL) containing AF647-PFO (10 pM) and BSA (0.01 mg/mL) was constantly flowing through the channel at a rate of 7 µL/min. A total of 2000 images of AF647-PFO were acquired using a 200ms exposure, 3 mW 647 nm laser power at a frame rate of 20 s per frame. In between AF647-PFO images, images of the liposome content dye were captured using 20ms exposure and 3 mW 488 nm laser power. The liposome images were used to correct for stage drift during acquisition as AF647-PFO binding was too sparse to reliably calculate drift in these experiments.Single molecule binding was detected using the Localize program in the Picasso suite  with a mSuper-resolution images were exported as a grayscale image from the Render Picasso program with a fixed 5-fold up-sampling (giving an effective pixel size of 22 nm). Particles were detected by thresholding and liposome sizes were calculated using a Feret diameter.HBS pH 7 containing AF647-PFO (50–500 pM), AF488 (100 nM) as a solution exchange marker and BSA (0.01 mg/mL) as a blocking agent was constantly flowing through the channel at a rate of 20 µL/min. TIRF images were acquired . The total duration of the experiment varied depending on the pore-formation kinetics, lasting between 15 and 240 min, whereby the total number of frames was kept at 180 frames.https://github.com/lilbutsa/JIM-Immobilized-Microscopy-Suite; copy archived at swh:1:rev:39a402c8dddcad16b15b7b5aa5994b407ec6fe3f [Image stacks of PFO assembly/dye release experiments were analysed using home-written image analysis software . Channe5. The x/y-positions of AF647-PFO oligomers diffusing on liposomes were calculated using Picasso Localize . Image stacks in both channels were corrected for stage drift using the cross-correlation calculated from the dye contents channel in JIM. The clusters of x/y-localisations of AF647-PFO oligomers detected using Picasso were aligned with the regions of interest of liposomes in the dye channel in JIM to generate dual-colour traces.TIRF imaging for detection of the arrival of single AF647-PFO molecules by step fitting  and for HBS (pH 7 and 0.01 mg/mL BSA) containing AF647-PFO (400 pM) and AF488 (100 nM) as a solution exchange marker was constantly flowing through the channel at a rate of 20 µL/min for 5 min. Flow was stopped and inlet tubing was swapped to a HBS (pH 7 and 0.01 mg/mL BSA) solution without PFO or dye and flow was resumed at 20 μL/min less than a minute after stoppage. Dual-colour TIRF imaging was conducted using a 488 nm laser and a 640 laser with 50ms exposure time. To avoid photobleaching in experiments used to measure the number of subunits in oligomers, imaging only commenced following the washout of free PFO in solution. The total duration of the experiment varied depending on the pore-formation kinetics, lasting between 15 and 240 min, whereby the total number of frames was kept at 180 frames. The temperature was controlled using an OkoLab Bold Line stage top incubator.The construction of the kinetic models is described in detail in the Appendix. This paper presents a detailed single-molecule, multi-color microscopy study of the real-time assembly of perfringolysin O, a member of the membrane attack complex perforin cholesterol-dependent cytolysin superfamily. With the ability to resolve different reaction species simultaneously with membrane leakage, this work provides key mechanistic details including identifying assemblies involved in membrane lysis, and how membrane binding, oligomerization, and pore transitioning depends on concentration and pH. This study will be of interest to many, particularly those studying cytolysin mechanisms, but also the broader field of single-molecule studies of membrane binding proteins. public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.Our editorial process produces two outputs: (i) Decision letter after peer review:eLife. Your article has been reviewed by 3 peer reviewers, including Janice L Robertson as Reviewing Editor and Reviewer #1, and the evaluation has been overseen by Nancy Carrasco as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Ana J Garcia-Saez (Reviewer #3).Thank you for submitting your article "Single-molecule analysis of the entire perfringolysin O pore formation pathway" for consideration by The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.Essential revisions:The reviewers found this to be an intriguing study, offering exquisite resolution into the complex reaction of perfringolysin O pore formation on membranes. However, all of the reviewers raised concerns about controls that are needed to interpret the data. It is anticipated that the following essential revisions can be reasonably addressed with further elaboration of the methods, revised analysis of the current data, or a limited number of control experiments. In general, the manuscript should also be revised to consider alternate interpretations of the data.1) Mapping corrections between the co-localization fields. For co-localization of single-molecules, an experimental mapping correction is often performed in order to calculate the translational and magnification transformations that may be needed to map a pixel from one emission field to the other. This can be calculated using a sample that is known to contain co-localized molecules and imaged in both fields. Were experimental mapping corrections carried out in this study? In the following, it sounds that this mapping is carried out by the software: "We then used a software developed for single-molecule localisation microscopy  to detect and track AF647-PFO spots appearing and disappearing at the locations of individual liposomes." If this is the case, please elaborate on how this works and whether you have data confirming that this method provides an adequate correction.2) Estimating the number of PFO molecules from intensities. Since the single-molecule intensities follow a broad distribution , it is likely that any estimation of the number of PFOs from intensities will have a large uncertainty and will have to include consideration of different labeling probabilities. Along these lines, the PFO quantities should be reported as the raw AF647 intensities in the figures. A clear description of how the number estimations are calculated along with the uncertainty on these estimates can be included in the discussion, as these number values are rough estimations.3) The effect of photobleaching. A main result of this work is that the dimer has a much higher association stability with the membrane than monomers. However, monomers and dimers were measured with widely different power intensities and at different frame rates. Hence, it should be absolutely clear to the reader that this observation does not simply reflect the different bleaching rates of the two different molecules. For example, the monomer was sampled with high wattage powers and at 17 frames per second (˜1000 per minute). The dimers are sampled at high wattage (how high?) and 3 frames per minute. Considering that the measured dwell time for monomers is 0.5 s, while the one for dimers is ˜20 min (or 1200 s), it follows that if the authors are measuring the bleaching of the molecule rather than the association of the molecules with the membranes, then there would actually be no difference between the association of monomers and dimers.To address this, more evidence is required to show that what is being measured is association and not bleaching. Specifically, what is the bleaching rate of the dye under the experimental conditions? This could be easily measured for the dimer, as single-step intensity reductions of the fluorescence should provide information on bleaching. The authors might also consider using different dyes with different bleaching rates and compare the association rates. In addition, they say that the signal disappeared in one step, which is indicative of dissociation of the dimer from the membrane, rather than a photobleaching step (perhaps the authors should mention this). It is assumed that occasionally, the signal disappeared in two steps. Please indicate how many times a two-step process was observed. The kinetics of the two-step process can also be used to characterise the photobleaching time. Please indicate here how fast is photobleaching and how that compares with the dwell time of the monomer binding. Comparison of rates measured at different fluorescent power of frames per seconds might provide a quick way to establish what is measured here.4) Possibility of multiple complexes on a single liposome. One weakness of the study is the inability to distinguish between one or more complexes simultaneously assembling in one liposome. It is unclear how one can distinguish whether the estimated PFO numbers reflect the stoichiometry of one oligomer and not multiple oligomers on one liposome? The continued growth would suggest that this cannot be distinguished. Are there any abrupt steps in the oligomerization process that could be attributed to additional pore structures growing from defined seeding points? The single-step dye loss was interpreted to mean that only one pore is likely to permeate the liposome (Pg. 6), with multi-step signals interpreted as being from multilamellar liposomes. While plausible, there is no clear evidence of this, and it remains possible that the multi-step increases are due to more than one pore forming in the liposome. To clarify this, it would be beneficial to measure the full width at half maximum of the AF647-PFO fluorescence intensity profiles on individual liposomes and plot them as a normal distribution. This would allow to exclude measurements with a full width at half maximum outside the population average (e.g. the 95th percentile of the distribution) which most likely correspond to liposomes containing more than on PFO complex. In addition, the paper requires revisions to consider the alternate possibility that the data reflect multiple pore forming reactions on the single liposomes.5) Please address the recommendations raised by the reviewers below. These suggestions are directed at clarifying the manuscript and interpretation of the results.Reviewer #1 (Recommendations for the authors):1. In Figure 1D, it will be useful to add examples of the "single step", "no step", and "other" traces directly in this main figure, as has been depicted in Figure 1 —figure supplement 3. Visualization of these representative traces is important to allow the reader to properly interpret the different behaviors.2. In 2G, the super-resolution approach for PFO monomer binding appears to outline the liposome size quite well. Can you quantify the liposome size distribution based on this approach? Do you find that there is a significant amount of non-uniformity to indicate that your results may depend on liposome size?3. Addition of uncertainty and statistical information. Much of the data presented lacks a description of the uncertainty or variability. For example, in the frequency/percentage bar plots, the binomial standard deviation could be used. In other plots, the mean is shown but without standard deviation. Please add this information and provide details in the legends about population or sample numbers.4. Revise the following paragraph on page 4 as this paper is no longer accompanying:"In an accompanying paper, Wallace and colleagues use single-molecule fluorescence tracking of PFO assembly on a droplet interface bilayer . These imaging studies support the insertion of incomplete arc-shaped membrane lesions, suggesting an alternative mechanism of pore formation that is distinct from the canonical prepore formation prior to insertion. This discrepancy raises the question as to when and how release of the membrane spanning regions is triggered, which cannot be correlated with key assembly steps using ensemble methods. Related to this matter, it is also unclear whether release and insertion of the membrane spanning regions from each of the subunits occurs in a concerted or sequential fashion."5. Further technical details would be useful in this paper, such as how the co-localization was determined and corrected for different mappings between fields, as well as how the number of PFO molecules was ascertained by intensity analysis.Reviewer #2 (Recommendations for the authors):1. Page 7. How was the surface area of the liposome established?2. Page 9-10. The authors go to a great length to describe the kinetics of oligomer formation. However, it is not clear how the authors can actually distinguish between the formation of many independent dimers and the formation of oligomers. Do they assume that once the dimers are on the membrane they will eventually meet up into oligomers? Is this a reasonable assumption given the diffusion time of the dimers and the size of the liposome?3. Furthermore, it is not clear how the authors can distinguish between the formation of conductive arc pores and full pores. Since it is only possible to observe a full liposome, all these species should have the same fluorescence properties. How can the authors know the number of subunits of a pore, considering that the fluorescent signal can only estimate the overall number of units in the membrane? How can the authors distinguish a full pore from two arcs?4. Page 10. The authors argue that the arc pores with at least four subunits can form pores. How did they come to this conclusion? Only on the basis of fluorescence intensity? If that is the case, has photobleaching taken into account? The authors identified the oligomer-length specific insertion rates from the insertion times. However, it is not clear how this was done. The authors should either point to the methods where more details should be given, or explain more in detail how this was done (e.g. is the number of subunit estimated by the fluorescence intensity?).5. The kinetic model  also assumes that a monomer is added to a nucleated pore. However, since monomers are transient and dimers rather stable, would it make more sense that dimers are constantly formed from monomers and these structures move around the membrane until they meet each other and then form full pores? Would it also not be easier for a full pore to be formed from two arc pores? The authors should spend a few arguments to convince the reader that the experimental setting can distinguish between these different scenarios?6. Pore insertion kinetics (Page 12). This connects to the arguments above. How can the authors distinguish between the growing of arc pores from the formation of unrelated structures in the same liposome? Why this cannot be explained with a new nucleation process.7. The authors observed a marked pH dependence of pore formation. How is the fluorescent signal affected by the pH? Please also indicate where the reader can find the mathematical models that allow distinguishing between membrane and lateral interactions.8. Furthermore, the authors should measure directly (on and off rates) the monomer and dimer affinity for the liposomes at different pH values by fluorescence.9. Figures. Please add the condition  in the legend of the figures.Reviewer #3 (Recommendations for the authors):Overall, the quality of the experiments and their analysis is excellent, and I have only some questions to be addressed:1. The authors attribute the heterogeneous release profiles to heterogeneity in the liposome preparation. What about the stochastic nature of pore formation? That would also support the distributions observed between time of nucleation/poration.2. The fluorescence signal of PFO on individual liposomes seems heterogeneous, which the authors attribute to differences in cholesterol distribution. However, the lipid composition is not expected to present phase separation. Could this be due to complex assembly on part of the liposome leading to heterogeneous distribution? Otherwise, the authors might test their hypothesis of inhomogeneous cholesterol distribution by fluorescence microscopy on giant unilamellar vesicles or lipid bilayers containing a lipophilic dye.3. Please explain how the different kinetics of monomer addition to the pre-pore or the pore states are considered in the mathematical model.4. Please explain how the oligomerization rate by monomer addition before and after insertion can be the same. One would expect that the energetics of the interactions of the monomers with the non-inserted and inserted oligomers would differ. This part of the model is not very convincing yet and requires elaboration.5. Do the complete rings continue to grow indefinitely? Please explain.6. While the authors nicely confirm that AF647-labelled PFO is functional and that the effect of self-quenching is small using different ratios of labelled to unlabeled PFO , this analysis also revealed that a 100% ratio of labelled PFO is more active in perforating liposomes. While this effect can be caused by an underestimation of the amount of unlabeled protein (as the authors mention), they should also discuss the option that AF647-PFO is indeed more active due to possible structural alterations caused by the label.7. The authors use photobleaching step counting of sparsely distributed AF647-PFO immobilized on glass coverslips to measure the reference monomer fluorescence intensity . Considering that AF647-PFO has an estimated labeling efficiency of ~1.5 fluorophores/PFO, it would be beneficial to compare the population distribution of the determined monomer intensities  to the intensity distribution measured for monomeric AF647 dye immobilized on glass.8. In order to measure the oligomeric state of AF647-PFO at different time points in the liposomes, the authors determine the ratio of the fluorescence intensity associated with the liposome to the monomer fluorescence intensity derived from single photobleaching events. Given that not all PFO molecules are labelled with one single AF647 fluorophore , the calculation of molecular units from fluorescence intensity is somewhat error prone. Labelling efficiency correction of the measured fluorescence intensities should be used to test if there is an influence of the labelling efficiency on the determined oligomeric state of AF647-PFO.9. Considering the lipid composition of the outer leaflet of the plasma membrane , a concentration of 55% cholesterol seems very high. The authors should state in the manuscript why they chose the specific lipid mixture and how it might affect the mechanistic regulation of PFO  compared to the physiological scenario of the plasma membrane.10. When discussing the possible explanations why PFO pores continue to grow over time with wit a membrane insertion rate increasing with concentration, the authors should also discuss the effect of continuous protein insertion on the physical properties of a toroidal pore. Increasing number of protein molecules inserted in a membrane increase the membrane tension and at the same time decrease the line tension at the pore rim both promoting the stabilization of an open pore.11. In this line, the authors should also include a figure showing the oligomerization characteristics of PFO  beyond the expected number of molecules required to form a full pore ring until the oligomerization reaches saturation. The possible explanation for the continuous increase in the number of PFO molecules that "eventually multiple pores form" (page 6) is contradictory to the valid assumption made later that an existing PFO oligomer in the liposome "acts as a sink for monomers" (page 12) that newly bind to the membrane.12. The authors should state in the manuscript why a Cysteine-free version of PFO (PFO(C459A)) was used.13. Quantify the percentage of unpermeabilized liposomes in Figure 2 —figure supplement 2.14. Please provide statistics  for the data shown in Figure 1 D and E, Fig, 2 E and D, and Figure 1 —figure supplement 1.15. It is misleading that PFO oligomers with a number of subunits below the reported number needed to form a full ring are referred to as arcs. There is no experimental prove in this study that these oligomeric states of PFO indeed assemble to an arc-like structure in the membrane.16. The terminology "oligomer length" implies a structural parameter. Better refer to it as "molecular size" / "oligomeric state2 / "no of subunits/molecules".17. Please clarify that Figure 3D shows the sum of individual localizations over time and not multiple simultaneous localizations of AF647-PFO to one liposome.18. The deliberate offset of the two fluorescence channels in Figure 2 —figure supplement 2 is somewhat misleading as it hinders the correct interpretation of the data. It would be better to show the correctly aligned image of the overlay and the single channel images and the merge of the cropped area for better visualization.19. Please specify the meaning of the orange line in Figure 7 F and H.20. Page 8: Please specify in the sentence "To determine the stoichiometry of AF647-PFO in the long-lived state, we measured the average intensity of all long-lived signals on liposomes." that it is averaging over time and not over several particles.21. Please include scale bars in the microscopy images in Figure 1C, Figure 2C, Figure 2B, Figure 2 —figure supplement 1, and Figure 2 —figure supplement 2.22. Refer to Table 1 also in the main text of the manuscript.23. Page 13: Please correct the referencing to the different panels in Figure 7 F-I.24. Page 6: Please correct the typos "Figur1 Figure Supplement 3" and "Figur1 Figure Supplement 3B".25. Figure 3D: Please correct the typo "AF4647-PFO" in Figure 3D. Essential revisions:1) Mapping corrections between the co-localization fields. For co-localization of single-molecules, an experimental mapping correction is often performed in order to calculate the translational and magnification transformations that may be needed to map a pixel from one emission field to the other. This can be calculated using a sample that is known to contain co-localized molecules and imaged in both fields. Were experimental mapping corrections carried out in this study? In the following, it sounds that this mapping is carried out by the software: "We then used a software developed for single-molecule localisation microscopy  to detect and track AF647-PFO spots appearing and disappearing at the locations of individual liposomes." If this is the case, please elaborate on how this works and whether you have data confirming that this method provides an adequate correction.A. PFO assembly and dye release experiments in Figures 1, 4, 5 and 6:Channel alignment and drift correction were performed as a part of the JIM trace generation pipeline using a C++ implementation of a subpixel cross-correlation algorithm ). This implementation uses the Intel Math Kernel Library (MKL) and Intel Performance Primitives (IPP) for optimization but is otherwise completely open-source and freely available as a part of the Github repository. Details on usage of the image alignment code are found in the “Basic C++ Header Libraries“ section of the JIM documentation (see link below). Validation of the channel alignment and drift correction calculations is provided in Tutorial 1 and Tutorial 2 of the JIM Analysis Suite respectively using artificially generated datasets. In general, drift correction is accurate within 0.1-0.5 pixels which is sufficient for most applications.Link to JIM documentation:https://docs.google.com/document/d/12frP6jp74eiycXxY8knR_qb27ui7Ia-RNMBuAuAHRFs/edit?usp=sharingB. Single molecule binding experiments in Figures 2 and 3:AF647-PFO image stacks were drift corrected using the redundancy cross-correlation function built into the Render program of the Picasso suite with an averaging window size of 10,000 frames. The reconstructed super-resolution image of AF647-PFO localisation was manually aligned with the diffraction-limited liposome image (drift corrected using JIM as above) for visualisation . We note that the liposome image was not used for quantification in these experiments.C. PFO polymer movement experiments in Figure 7:Image stacks were corrected for drift using JIM as described above. The two channels were then aligned using JIM as described above.The methods section of the manuscript has been updated accordingly.2) Estimating the number of PFO molecules from intensities. Since the single-molecule intensities follow a broad distribution , it is likely that any estimation of the number of PFOs from intensities will have a large uncertainty and will have to include consideration of different labeling probabilities. Along these lines, the PFO quantities should be reported as the raw AF647 intensities in the figures. A clear description of how the number estimations are calculated along with the uncertainty on these estimates can be included in the discussion, as these number values are rough estimations.Reporting of intensities:As suggested, the raw AF647-PFO intensity (a.u.) is now shown in graphs of single-liposome PFO binding traces. The downstream analysis uses the average of thousands of individual traces such that the high variability of individual fluorophores is averaged out and the quantification is robust and reproducible.How was the number of PFO molecules estimated from intensity?A description detailing the process of estimating protein numbers has been added to the Appendix under the heading “Single-Molecule photobleaching for intensity calibration”.New experiments to validate the PFO number estimates:To further validate the use of a single molecule intensity value, we performed additional experiments to independently measure the oligomerization rate without using the single-molecule intensity value. To do this, we imaged PFO binding to liposomes at a fast frame rate and with high laser intensity to observe individual molecules binding to the oligomer. The AF647-PFO intensity trace was then fitted with a step function to identify incoming PFO molecules. These experiments provided intensity-independent estimates of the oligomerization rate, the number of PFO monomers in the oligomer at the time of membrane insertion (detected via dye release) and the fraction of oligomers that reach the requisite number of subunits to insert as closed rings. The values for these parameters obtained by intensity calibration in Figure 4C and Figure 6C/D are within a factor of 1.5 or better to the values obtained by step fitting. We have described the new analysis based on step fitting to detect the arrival of single molecules in the Results section (page 9 and page 12), the Methods section and added the data as Supplementary Figure 4—figure supplement 3.Results -1 . Importantly, this measurement is independent of the single-molecule intensity calibration.”PFO dimerisation on the membrane nucleates a stably growing oligomer “Finally, we validated the oligomerisation rate by directly observing the arrival of AF647-PFO monomers using single molecule imaging conditions, which yielded a value of 0.15±0.04 nM-1 sPore insertion kinetics for continuously growing arcs “TIRF imaging at higher laser power and temporal resolution to detect the addition of single PFO monomers to oligomers yielded similar values to the ones described above for the number of PFO monomers in the oligomer at the time of membrane insertion and the fraction of oligomers that reach the requisite number of subunits to insert as closed rings . This analysis provides an intensity-independent validation of these parameters.”Methods (pg 23) "TIRF imaging for detection of the arrival of single AF647-PFO molecules by step fitting  and for tracking the localisation of AF647-PFO oligomers by point spread function fitting  were conducted with increased 640 nm laser power of 75 mW and an exposure time of 50 ms exposure. Frame rates were as follows : 100 pM, 1/9 FPS; 200 pM, 1/4.5 FPS; 300 pM, 1/3 FPS; 400 pM, 1/2.5 FPS; 500 pM, 1/2 FPS. Step fitting of the AF647-PFO traces was performed using change point analysis in Matlab with a threshold of 3x105. The x/y-positions of AF647-PFO oligomers diffusing on liposomes were calculated using Picasso Localize . Image stacks in both channels were corrected for stage drift using the cross-correlation calculated from the dye contents channel in JIM. The clusters of x/y-localisations of AF647-PFO oligomers detected using Picasso were aligned with the regions of interest of liposomes in the dye channel in JIM to generate dual-colour traces.”3) The effect of photobleaching. A main result of this work is that the dimer has a much higher association stability with the membrane than monomers. However, monomers and dimers were measured with widely different power intensities and at different frame rates. Hence, it should be absolutely clear to the reader that this observation does not simply reflect the different bleaching rates of the two different molecules. For example, the monomer was sampled with high wattage powers and at 17 frames per second (˜1000 per minute). The dimers are sampled at high wattage (how high?) and 3 frames per minute. Considering that the measured dwell time for monomers is 0.5 s, while the one for dimers is ˜20 min (or 1200 s), it follows that if the authors are measuring the bleaching of the molecule rather than the association of the molecules with the membranes, then there would actually be no difference between the association of monomers and dimers.To address this, more evidence is required to show that what is being measured is association and not bleaching. Specifically, what is the bleaching rate of the dye under the experimental conditions? This could be easily measured for the dimer, as single-step intensity reductions of the fluorescence should provide information on bleaching. The authors might also consider using different dyes with different bleaching rates and compare the association rates. In addition, they say that the signal disappeared in one step, which is indicative of dissociation of the dimer from the membrane, rather than a photobleaching step (perhaps the authors should mention this). It is assumed that occasionally, the signal disappeared in two steps. Please indicate how many times a two-step process was observed. The kinetics of the two-step process can also be used to characterise the photobleaching time. Please indicate here how fast is photobleaching and how that compares with the dwell time of the monomer binding. Comparison of rates measured at different fluorescent power of frames per seconds might provide a quick way to establish what is measured here.What is the laser power used for imaging dimers on membranes?The nominal laser power is 100 mW for monomers and 3 mW for dimers. These values are stated in the Methods section.What is the bleaching rate in the experiments and how does it compare to the rate of monomer release?We have performed the additional control experiments suggested by the reviewers to show that monomer unbinding is not the result of photobleaching and that we have correctly compensated for photobleaching. This analysis has been added as Figure 2—figure supplement 3.1. Single-molecule photobleaching experiments at a range of laser powers  show that the bleaching rate (panel B) and the single-molecule intensity (panel C) is proportional to the laser power.2. We performed single-molecule AF647-PFO binding experiments at a range of laser powers  and corrected the rate of signal disappearance at each laser by the corresponding photobleaching rate determined above. This analysis shows that the monomer unbinding rate is independent of laser power in the range between 25–100 mW , We conclude that the monomer unbinding rate is not affected by photobleaching.3. For the dimer, we had already shown that changing the frame rate by a factor of 6 does not change the dissociation rate  strongly suggesting that the release of the dimer from the membrane is not the result of photobleaching.We have referred to the new Supplementary Figure showing that the monomer unbinding rate is independent of photobleaching in the Results section.Results (pg 7)”Characterisation of PFO monomer binding to liposomes “An exponential fit of this distribution then provided the AF647-PFO monomer unbinding rate after correcting for photobleaching .4) Possibility of multiple complexes on a single liposome. One weakness of the study is the inability to distinguish between one or more complexes simultaneously assembling in one liposome. It is unclear how one can distinguish whether the estimated PFO numbers reflect the stoichiometry of one oligomer and not multiple oligomers on one liposome? The continued growth would suggest that this cannot be distinguished. Are there any abrupt steps in the oligomerization process that could be attributed to additional pore structures growing from defined seeding points? The single-step dye loss was interpreted to mean that only one pore is likely to permeate the liposome (Pg. 6), with multi-step signals interpreted as being from multilamellar liposomes. While plausible, there is no clear evidence of this, and it remains possible that the multi-step increases are due to more than one pore forming in the liposome. To clarify this, it would be beneficial to measure the full width at half maximum of the AF647-PFO fluorescence intensity profiles on individual liposomes and plot them as a normal distribution. This would allow to exclude measurements with a full width at half maximum outside the population average (e.g. the 95th percentile of the distribution) which most likely correspond to liposomes containing more than on PFO complex. In addition, the paper requires revisions to consider the alternate possibility that the data reflect multiple pore forming reactions on the single liposomes.Are there features in the AF647-PFO traces that could be attributed to nucleation of additional pores?The image acquisition settings for these experiments were optimised for measuring the kinetics between nucleation and pore opening and we prefer not to interpret trends in the data beyond this range with respect to the timing of new nucleation events. Instead, reliable detection of new nucleation events would require different settings and/or complementary approaches such as imaging on flat bilayers. Please see response to point #11 from reviewer #3 for more details.Could multi-step traces arise from the opening of multiple pores on the same liposome?No. We have simulated dye release via diffusion through pores using FEM modelling, showing that the dye is completely released on a time scale (0.1–1 ms) well below the temporal resolution of our measurements . Thus, opening of the first membrane is expected to lead to release of the entire dye contents in a single frame. Please see response to point #1 from reviewer #3 for more details.Consider the possibility that the data reflect multiple pore forming reactions on the single liposomes.The experimental approach using liposomes is particularly suited to measure the early stages of the first pore nucleating on the liposome and we agree that it is difficult to distinguish the nucleation of additional independent oligomers that may occur at later stages of the process. We have added new experiments and theoretical considerations to address this question (see below). We have also modified the Discussion to better highlight the limitations of our study with respect to identifying additional nucleations.Discussion (pg 16/17)“Limitations of our approach include the following. Unlike measurements on flat membranes, we cannot resolve separate molecules or complexes on the same liposome due to the diffraction limit. While biochemical characterisation and AFM imaging of PFPs is typically carried out in the nM range, we limited the concentrations used in this study to the pM range to enhance the probability of observing the growth of a single complex per liposome. This is initially borne out in the data: The oligomerisation rate remains constant  instead of increasing (as would be expected for multiple oligomers) and the movement of the fluorescent complex on the membrane drops in a single step upon membrane insertion . Nevertheless, the fluorescence signal ultimately exceeds the levels expected for a single ring-shaped pore, suggesting that additional oligomer eventually nucleate in the liposome, whereby it remains unclear when this second nucleation event occurs. Thus, we cannot rule out the simultaneous growth of more than one oligomer, especially during later stages of the experiment. Further experiments are required to pinpoint exactly when additional oligomer appear, e.g. using conditions that are optimised to detect new nucleation events or complementary approaches such as single-particle tracking on flat bilayers.Another limitation is that non-specific labelling of PFO (resulting in a heterogeneous sample of labelled species), as well as possible fluorescence artefacts, limit the precision with which we can determine the number of subunits in PFO oligomers. For validation, we determined the oligomerisation rate and number of subunits in the oligomer at the time of pore opening by detecting and counting individual PFO monomers joining the growing oligomer. This intensity-independent analysis yielded essentially the same values as the quantification based on intensity.”New experiments to test for the simultaneous growth of two (or more) independent PFO oligomers.To further test whether multiple PFO oligomers are present on the liposome at the time of insertion, we have performed additional PFO binding/dye release TIRF experiments in which we track the movement of the AF647-PFO signal between frames. These experiments show a sudden decrease of movement that coincides with dye release. This observation is consistent with the insertion (and concomitant decrease in diffusion) of a PFO oligomer that dominates the fluorescence signal. These experiments are shown in a new Figure 7 and are described in the Results section.Results (pg 13)Pore opening coincides with a drop in PFO oligomer movement on the membrane“Membrane insertion leads to a drastic reduction of the diffusion rate of CDC complexes on the surface of flat membranes ; . To determine whether the same effect could be observed on liposomes, we imaged PFO assembly and pore formation assay with high laser intensity to accurately localise the position (projected onto the x/y-plane) of growing PFO oligomers on liposomes over time with sub-pixel resolution. The example trace in Figure 7A shows that the frame-to-frame movements of the AF647-PFO signal initially fluctuated between 0–300 nm . Pore opening (detected by dye release) led to a pronounced drop in movement . This reduction in movement is also evident in the map of all x/y-localisations. Localisations appeared as a diffuse point cloud with approximately the same size as the liposome , and formed a tight focus upon dye release.Experiments conducted at 100–500 pM AF647-PFO showed that oligomers on 85% of liposomes showed a reduction of ~41% in movement across the entire concentration range, which occurred in a stepwise fashion upon dye release . We conclude that most liposomes contain a fluorescent species that dominates the point spread functions and becomes less mobile from one frame to the next, consistent with a single oligomer becoming less diffusive upon insertion into the membrane.”Theoretical considerations to estimate the probability for nucleation of a second PFO oligomer.A key question for interpreting the continuing increase of the AF647-PFO intensity after insertion is whether a second PFO oligomer is likely to nucleate on the liposome when an actively growing oligomer is already present on the membrane. To address this question, we have calculated the probability of a second dimer forming on the membrane before insertion of the first oligomer . This analysis shows that in the lower end of the concentration range, the majority of liposomes contain only a single actively growing oligomer before insertion happens. Notably, this calculation is based on the assumption that dimers do not join the growing oligomer, i.e. the probability would be considerably lower if joining of dimers and oligomers can occur (please see response to point #2 from reviewer #2 for further discussion).Results (pg 13)“Finally, we calculated the upper limit for the probability of nucleating a second dimer on a liposome before insertion of the growing PFO oligomer . This analysis showed that the majority of liposomes are predicted to contain a single oligomer at the time of dye release at concentrations ≤100 nM, but nucleation of a new dimer become probable at higher concentrations (note that this dimer may not form an independently growing oligomer but could join the first oligomer).”5) Please address the recommendations raised by the reviewers below. These suggestions are directed at clarifying the manuscript and interpretation of the results.Please see below.Reviewer #1 (Recommendations for the authors):1. In Figure 1D, it will be useful to add examples of the "single step", "no step", and "other" traces directly in this main figure, as has been depicted in Figure 1 —figure supplement 3. Visualization of these representative traces is important to allow the reader to properly interpret the different behaviors.As suggested, the figure has been revised to include examples of “no step”  and “other”  traces. The new panels are referenced in the Results section.Results (pg 6)“At AF647-PFO concentrations between 100–500 pM, most liposomes lost their dye signal in a single step (>50%) , while ~30% of dye release traces showed partial or multi-step signal loss . The remainder (~10%) showed no or little signal loss , suggesting that these were not permeabilised despite AF647-PFO binding to many of these liposomes .”2. In 2G, the super-resolution approach for PFO monomer binding appears to outline the liposome size quite well. Can you quantify the liposome size distribution based on this approach? Do you find that there is a significant amount of non-uniformity to indicate that your results may depend on liposome size?We have quantified the diameters of liposomes using super-resolution reconstruction. The resulting size distributions have been added to Figure 1 – Supplementary Figure 1 as panel B to allow for direct comparison to the dynamic light scattering (DLS) measurement. Overall, the super-resolution diameter measurement of 172 (±18) nm is consistent with the DLS measurement of 183 (±37) nm. We have revised the Results and Methods accordingly.Results (pg 5)“The liposomes had an average diameter of ~200 nm  and were captured on the surface of a streptavidin-coated glass coverslip at the bottom of a microfluidic channel device.”Methods (pg 22)“Liposome diameter measurements using super-resolution TIRF microscopy. Super-resolution images were exported as a grayscale image from the Render Picasso program with a fixed 5-fold up-sampling (giving an effective pixel size of 22 nm). Particles were detected by thresholding and liposome sizes were calculated using a Feret diameter.”3. Addition of uncertainty and statistical information. Much of the data presented lacks a description of the uncertainty or variability. For example, in the frequency/percentage bar plots, the binomial standard deviation could be used. In other plots, the mean is shown but without standard deviation. Please add this information and provide details in the legends about population or sample numbers.We have updated the legends for all figures to specify the number of independent experiments for each condition.We have updated plots that previously showed mean values  to include individual data points derived from independent experiments to show the spread in the data.Dot plots of the values derived from independent experiments for the kinetic parameters determined in this work are shown in Appendix Figure A2. Mean and standard deviation obtained from this analysis are listed in Table 1.4. Revise the following paragraph on page 4 as this paper is no longer accompanying:"In an accompanying paper, Wallace and colleagues use single-molecule fluorescence tracking of PFO assembly on a droplet interface bilayer . These imaging studies support the insertion of incomplete arc-shaped membrane lesions, suggesting an alternative mechanism of pore formation that is distinct from the canonical prepore formation prior to insertion. This discrepancy raises the question as to when and how release of the membrane spanning regions is triggered, which cannot be correlated with key assembly steps using ensemble methods. Related to this matter, it is also unclear whether release and insertion of the membrane spanning regions from each of the subunits occurs in a concerted or sequential fashion."We have revised this sentence.Introduction (pg 4)“Imaging modalities applied to CDC assembly on planar lipid bilayers include high speed atomic force microscopy, as shown for suilysin  and listeriolysin O  and single-molecule fluorescence tracking, as shown for PFO assembly on a droplet interface bilayer . These imaging studies support the insertion of incomplete arc-shaped membrane lesions, suggesting an alternative mechanism of pore formation that is distinct from the canonical prepore formation prior to insertion. This discrepancy raises the question as to when and how release of the membrane spanning regions is triggered, which cannot be correlated with key assembly steps using ensemble methods. Related to this matter, it is also unclear whether release and insertion of the membrane spanning regions from each of the subunits occurs in a concerted or sequential fashion.5. Further technical details would be useful in this paper, such as how the co-localization was determined and corrected for different mappings between fields, as well as how the number of PFO molecules was ascertained by intensity analysis.Mapping between channels: Please see response to point #1 of the essential revisions.Intensity analysis: Additional information on the quantification of single-molecule intensities has been added in the Appendix section “Single-Molecule photobleaching for intensity calibration”.Reviewer #2 (Recommendations for the authors):1. Page 7. How was the surface area of the liposome established?The surface area of a liposome was approximated using the surface area of a 200 nm sphere. The relevant sentence has now been reworded to state this.Results (pg 7)B = 0.9±0.23 nM-1 s-1) which corresponds to 7.2±1.8 nM-1 s-1 μm-2 when taking the surface area of liposomes into account .”“This analysis allowed us to obtain the monomer binding rate constant . This suggests that the signal increase after nucleation is primarily driven by monomer addition to an existing oligomer rather than formation of new dimers.2. The movement of the PFO species on liposomes shows a sharp transition from high to low upon poreopening . This sudden drop in movement would not be observed if there were several independently diffusing species.Can newly formed dimers join an existing oligomer?As shown by tracking movements of PFO oligomers on liposomes  and flat bilayers  dimers and oligomers in the prepore state diffuse readily on the membrane such that these entities can collide on the liposome surface. On the basis of these observations, we think that it is plausible that dimers could add to an existing oligomer on the membrane. Nevertheless, this remains an open question which requires further investigation.Both of these questions are relevant in the context of whether a second PFO oligomer is likely to nucleate on the liposome when an actively growing oligomer is already present on the membrane. Please see our response to point #4 of the essential revisions for additional discussion.3. Furthermore, it is not clear how the authors can distinguish between the formation of conductive arc pores and full pores. Since it is only possible to observe a full liposome, all these species should have the same fluorescence properties. How can the authors know the number of subunits of a pore, considering that the fluorescent signal can only estimate the overall number of units in the membrane? How can the authors distinguish a full pore from two arcs?Please see response to point #2 of the essential revisions.4. Page 10. The authors argue that the arc pores with at least four subunits can form pores. How did they come to this conclusion? Only on the basis of fluorescence intensity? If that is the case, has photobleaching taken into account? The authors identified the oligomer-length specific insertion rates from the insertion times. However, it is not clear how this was done. The authors should either point to the methods where more details should be given, or explain more in detail how this was done (e.g. is the number of subunit estimated by the fluorescence intensity?).Has photobleaching been taken into account when using intensity for determining the minimum oligomer length required for insertion?To avoid photobleaching, the experiments used to measure oligomer lengths were conducted as follows: (1) Assembly of AF647-PFO oligomers on liposomes in the absence of laser illumination. (2) Removal of AF647-PFO from solution (wash-out) to halt oligomer growth and start of imaging to measure the intensities of PFO oligomers and their insertion kinetics. This protocol ensures that the number of subunits is determined at a time when no photobleaching has occured. We note that a different protocol was used for Figure 5A. In this case, imaging commenced at the beginning of the experiment to acquire complete traces that also include the PFO build-up during the first stage. We have added a sentence to the Methods to clarify this point.Methods (pg 23)“Dual-colour TIRF imaging was conducted using a 488 nm laser and a 640 laser with 50 ms exposure time. To avoid photobleaching in experiments used to measure the number of subunits in oligomers, imaging only commenced following the washout of free PFO in solution”How was the number of subunits determined from the fluorescence intensity?Additional information on the quantification of single-molecule intensities has been added in the appendix .5. The kinetic model  also assumes that a monomer is added to a nucleated pore. However, since monomers are transient and dimers rather stable, would it make more sense that dimers are constantly formed from monomers and these structures move around the membrane until they meet each other and then form full pores? Would it also not be easier for a full pore to be formed from two arc pores? The authors should spend a few arguments to convince the reader that the experimental setting can distinguish between these different scenarios?Formation of pores from dimers?Please see response to point #2 from this reviewer.Formation of pores by coalescence of two arc pores?We cannot rule out the formation of coalesced arc pores on the basis of the fluorescence intensity data. This process would be dependent on the nucleation of a second independent PFO oligomer; please see response to point #4 of the essential revisions for further discussion.However, we suggest that the formation of different types of structures  is kinetically controlled (see Discussion). In the low concentration range used here , we think that nucleation of an independent second structure before insertion of the first structure is unlikely in our experiments such that coalesced arcs are presumably also unlikely. This is supported by the negative staining EM analysis of PFO structures on liposomes  showing complete rings, but not coalesced arcs, consistent with our interpretation that arc pores continue to add monomers to form full rings.6. Pore insertion kinetics (Page 12). This connects to the arguments above. How can the authors distinguish between the growing of arc pores from the formation of unrelated structures in the same liposome? Why this cannot be explained with a new nucleation process.Please see our response to point #4 of the essential revisions.7. The authors observed a marked pH dependence of pore formation. How is the fluorescent signal affected by the pH? Please also indicate where the reader can find the mathematical models that allow distinguishing between membrane and lateral interactions.Dependence of AF647 intensity on pH:We have measured the fluorescence intensity of the dye between pH 5–8 and found that it is constant in this range. This data has been added as Figure 8—figure supplement 2 and is referred to in the legend for Figure 8.Legend for Figure 8.“Control experiments confirmed that the intensity of AF647-PFO was independent of pH .”Mathematical models:An additional section has been added to the appendix (“The effect of pH on nucleation”) to provide details of these models.8. Furthermore, the authors should measure directly (on and off rates) the monomer and dimer affinity for the liposomes at different pH values by fluorescence.We agree that measuring on- and off-rates of the monomer as a function of pH would further validate our model. However, the focus of this paper is on a complete kinetic description of the PFO pore formation pathway, whereby the pH experiments were included in this paper as a case study to demonstrate the utility of the kinetic model. As such, further experiments dissecting specific perturbations of the pathway are beyond the scope of this study, especially since the monomer binding experiments are very time consuming.9. Figures. Please add the condition  in the legend of the figures.We have added buffer conditions to the legend of Figure 1. The buffer conditions remain the same throughout the remainder of the manuscript .“All experiments were conducted at room temperature using a 20 mM HEPES buffer (pH 7) containing 100 mM NaCl and 0.01 mg/mL BSA.”Reviewer #3 (Recommendations for the authors):Overall, the quality of the experiments and their analysis is excellent, and I have only some questions to be addressed:1. The authors attribute the heterogeneous release profiles to heterogeneity in the liposome preparation. What about the stochastic nature of pore formation? That would also support the distributions observed between time of nucleation/poration.Stochasticity/time distributions:We absolutely agree that the pore formation process is inherently stochastic. Indeed, that is what necessitates studying the pore formation pathway at the single-molecule level, as each pore does not undergo the same process at the same time. As the reviewer points out, this dephasing leads to the distributions of times between different steps in the pathway.Heterogeneous (multi-step) dye release profiles:In addition to heterogeneity in the liposome preparation, multi-step dye release profiles could possibly arise if pore opening is transient, releasing only part of the dye before the membrane reseals. This would require the lifetime of the transient pore to be shorter than the time required for dye release. To get an understanding of the time scales involved in this process, we have simulated dye release via diffusion through pores of different diameters using FEM modelling. This analysis shows that dye release occurs on time scales of 100 μs to ~1 ms for pores with diameters between 35 nm and 2.5 nm. We have added the simulation of dye release as Figure 1—figure supplement 4 and added a sentence to the Results section (pg 6) referring to this new Figure.Results (pg 6)“For example, aggregated liposomes and multilamellar liposomes would be expected to give rise to traces with multiple steps or partial release of dye. Alternatively, multiple dye release steps could arise from transient pore opening events with a lifetime in the range of 0.1–1 ms .”2. The fluorescence signal of PFO on individual liposomes seems heterogeneous, which the authors attribute to differences in cholesterol distribution. However, the lipid composition is not expected to present phase separation. Could this be due to complex assembly on part of the liposome leading to heterogeneous distribution? Otherwise, the authors might test their hypothesis of inhomogeneous cholesterol distribution by fluorescence microscopy on giant unilamellar vesicles or lipid bilayers containing a lipophilic dye.We agree. We do not know what has caused these hot spots, and we should have been more circumspect in suggesting any underlying mechanism. The relevant section (pg 7) has been rewritten to reflect this:Results (pg 7)“Interestingly, many liposomes displayed bright spots in the reconstruction images suggesting that liposome membranes may have a spatially inhomogeneous affinity for binding PFO, but the underlying mechanism for this observation remains unclear.”3. Please explain how the different kinetics of monomer addition to the pre-pore or the pore states are considered in the mathematical model.The model contains steps only up to pore formation, i.e. monomer addition to the pore state is not part of the model.4. Please explain how the oligomerization rate by monomer addition before and after insertion can be the same. One would expect that the energetics of the interactions of the monomers with the non-inserted and inserted oligomers would differ. This part of the model is not very convincing yet and requires elaboration.We agree that addition of monomers to PFO oligomers post insertion requires further investigation to validate this finding and to identify the interactions that drive this process. One possible model to explain the observation that oligomerisation rates are the same before and after insertion is that oligomerisation is effectively a diffusion-controlled reaction. That is to say, the rate-limiting step in oligomerisation is a monomer diffusing close enough to the end of an arc to interact. If this is the case, then the difference in binding affinity of a monomer with an oligomer before and after insertion would have little impact on the observed oligomerisation rate. This scenario is plausible given the tight binding of monomers adding to a growing oligomer and the very low concentrations used in this study. We have not included this model in the paper as it is highly speculative.5. Do the complete rings continue to grow indefinitely? Please explain.Complete rings are stable structures and do not continue to grow. Our data nevertheless suggest that PFO can accumulate on liposomes after the number of subunits required to form a complete ring has been reached. This continued increase in PFO signal is likely due to the growth of an additional PFO oligomer on the same liposome; please see also our response to point #11 from this reviewer.6. While the authors nicely confirm that AF647-labelled PFO is functional and that the effect of self-quenching is small using different ratios of labelled to unlabeled PFO , this analysis also revealed that a 100% ratio of labelled PFO is more active in perforating liposomes. While this effect can be caused by an underestimation of the amount of unlabeled protein (as the authors mention), they should also discuss the option that AF647-PFO is indeed more active due to possible structural alterations caused by the label.The relevant section in the figure legend now reads:“The slight increase in the rate of poration in the 100% labelled sample (maroon curve) in comparison to lower labelled percentage samples suggests that the actual concentration of the labelled sample may be slightly higher than the unlabelled sample. Alternatively, this could be the result of fluorescent labelling increasing the activity of PFO. Regardless, the activity of all samples is reasonably similar and we conclude that the labelled PFO is functional.”7. The authors use photobleaching step counting of sparsely distributed AF647-PFO immobilized on glass coverslips to measure the reference monomer fluorescence intensity . Considering that AF647-PFO has an estimated labeling efficiency of ~1.5 fluorophores/PFO, it would be beneficial to compare the population distribution of the determined monomer intensities  to the intensity distribution measured for monomeric AF647 dye immobilized on glass.We analysed the first frame from photobleaching experiments with Picasso using the same parameters as in the liposome binding experiments, which should equally account for labelling efficiency. This is the distribution shown in Figure 2D.8. In order to measure the oligomeric state of AF647-PFO at different time points in the liposomes, the authors determine the ratio of the fluorescence intensity associated with the liposome to the monomer fluorescence intensity derived from single photobleaching events. Given that not all PFO molecules are labelled with one single AF647 fluorophore , the calculation of molecular units from fluorescence intensity is somewhat error prone. Labelling efficiency correction of the measured fluorescence intensities should be used to test if there is an influence of the labelling efficiency on the determined oligomeric state of AF647-PFO.Please see response to point #2 of the essential revisions.9. Considering the lipid composition of the outer leaflet of the plasma membrane , a concentration of 55% cholesterol seems very high. The authors should state in the manuscript why they chose the specific lipid mixture and how it might affect the mechanistic regulation of PFO  compared to the physiological scenario of the plasma membrane.This mixture is frequently used in in vitro studies of PFO and we have used it here to facilitate comparison with the literature. We have added the following sentence to the Results section (pg 5):Results (pg 5)“The high cholesterol content facilitates PFO activity on model membranes and is consistent with previous biochemical studies .”10. When discussing the possible explanations why PFO pores continue to grow over time with wit a membrane insertion rate increasing with concentration, the authors should also discuss the effect of continuous protein insertion on the physical properties of a toroidal pore. Increasing number of protein molecules inserted in a membrane increase the membrane tension and at the same time decrease the line tension at the pore rim both promoting the stabilization of an open pore.We agree that there are likely to be effects of membrane tension and line tension on the stability of an open pore. Since our method does not measure pore stability (i.e. closing of the pore is not detectable), we would prefer not to speculate on this aspect.11. In this line, the authors should also include a figure showing the oligomerization characteristics of PFO  beyond the expected number of molecules required to form a full pore ring until the oligomerization reaches saturation. The possible explanation for the continuous increase in the number of PFO molecules that "eventually multiple pores form" (page 6) is contradictory to the valid assumption made later that an existing PFO oligomer in the liposome "acts as a sink for monomers" (page 12) that newly bind to the membrane.Plots of the mean of all AF647-PFO intensity traces aligned at the time of nucleation see  that ext12. The authors should state in the manuscript why a Cysteine-free version of PFO (PFO(C459A)) was used.We have added this information to the Methods section.Methods (pg 19)“PFO C459A lacks the cysteine residue prone to oxidation (leading to inactivation) and has the same pore-forming activity as wild type PFO .”13. Quantify the percentage of unpermeabilized liposomes in Figure 2 —figure supplement 2.We have quantified the proportion of unpermeabilized liposomes by counting the fraction of liposomes that retain at least 25% of their initial intensity. From this analysis, we have determined that on average 91% of liposomes remain unpermeabilized over the course of the experiment. This analyis has been added as panel D to Figure 2—figure supplement 2.14. Please provide statistics  for the data shown in Figure 1 D and E, Fig, 2 E and D, and Figure 1 —figure supplement 1.We have added the requested information to the corresponding figure legends.15. It is misleading that PFO oligomers with a number of subunits below the reported number needed to form a full ring are referred to as arcs. There is no experimental prove in this study that these oligomeric states of PFO indeed assemble to an arc-like structure in the membrane.We agree and have added the following sentence (pg 10) to address this point:Results (pg 10)“While the fluorescence data do not provide structural information, we interpret these low stoichiometry PFO oligomers as arcs since wild type PFO assembly intermediates appear as arc-shaped structures in AFM images .”16. The terminology "oligomer length" implies a structural parameter. Better refer to it as "molecular size" / "oligomeric state2 / "no of subunits/molecules".As suggested, we have replaced the term “oligomer length” with “number of subunits”.17. Please clarify that Figure 3D shows the sum of individual localizations over time and not multiple simultaneous localizations of AF647-PFO to one liposome.The legend now reads:“ Diffraction-limited TIRF image of the AF488 content dye (C) and corresponding map of all x/y-localisations over time of the single AF647-PFO species (D) that remains bound to the liposome for the duration of the peak in panel A. The scatter of localisations reflects the diffusion of the species on the liposome surface.”18. The deliberate offset of the two fluorescence channels in Figure 2 —figure supplement 2 is somewhat misleading as it hinders the correct interpretation of the data. It would be better to show the correctly aligned image of the overlay and the single channel images and the merge of the cropped area for better visualization.As suggested, Figure 2—figure supplement 1 now shows the correctly aligned images.19. Please specify the meaning of the orange line in Figure 7 F and H.Specified in the main text (pg 14) and the corresponding Figure legend .Results (pg 14)“When we simply introduced the pH-dependent differences in the oligomerisation rate  (which in turn result from the defect in membrane binding) into the oligomerisation/insertion kinetic model , the model was able to reproduce the decrease in mean number of subunits  and complete ring formation  and the increase in the time from nucleation to poration  with increasing pH (See appendix “The effect of pH on growth and insertion” for model details).”Figure 8.“The orange lines in panels F-H represent fits of the model in Figure 6B using the pH-dependent oligomerisation rates in panel C.”20. Page 8: Please specify in the sentence "To determine the stoichiometry of AF647-PFO in the long-lived state, we measured the average intensity of all long-lived signals on liposomes." that it is averaging over time and not over several particles.The sentence now reads:Results (pg 8)“To determine the stoichiometry of AF647-PFO in the long-lived state, we measured the average intensity over time of each long-lived liposome-bound signal.”21. Please include scale bars in the microscopy images in Figure 1C, Figure 2C, Figure 2B, Figure 2 —figure supplement 1, and Figure 2 —figure supplement 2.Scale bars have been added to Figure 2—figure supplement 1 and Figure 2—figure supplement 2. Given the small size of the snapshots in Figure 1C, 2C and 3B, we have stated the width of the snapshots in the corresponding legends to provide a reference for the scale of these images.22. Refer to Table 1 also in the main text of the manuscript.References to Table 1 added on page 7, 8, 9 and 10.23. Page 13: Please correct the referencing to the different panels in Figure 7 F-I.Corrected.24. Page 6: Please correct the typos "Figur1 Figure Supplement 3" and "Figur1 Figure Supplement 3B".Corrected.25. Figure 3D: Please correct the typo "AF4647-PFO" in Figure 3D.Corrected.


Digital models in Standard Tessellation Language (STL) were created. The master model with the scan bodies was scanned (×10) with a computerized numerical control 3D Coordinate Measuring Machine (CMM). The short (distances of adjacent scan posts) and long distances (distances of the scan posts with non-adjacent sites in the arch) among the centroids of the four analogues were calculated using CMM special software. Trueness (comparisons with the master model) and precision (intragroup comparisons) were statistically compared with ANOVA, chi-square and Tukey tests. (3) Results: Laboratory scanners had the best trueness and precision compared to all IOSs for long distances. Only iTero  had comparable trueness with one laboratory scanner in short and long distances. For short distances, CS3600 , Omnicam, Primescan  and TRIOS 4  had similar trueness to one laboratory scanner. From those, only Omnicam and Primescan had similar precision as the same laboratory scanner. Most IOSs seem to work better for smaller distances and are less precise in cross-arch distances. (4) Conclusions: The laboratory scanners showed significantly higher trueness and precision than all IOSs tested for the long-distance group; for the short distance, some IOSs were not different in trueness and precision than the laboratory scanners. It has been suggested that Intraoral Scanners (IOSs) can provide both the patient and the clinician with pleasant experiences with short appointments ,2. The uAccording to ISO specifications ,8, accurThe literature supports the use of IOSs for creating short-span restorations, such as single crowns and short-fixed partial dentures ,9, but tKim et al. measured trueness and precision of implant centroids of full-arch implant impressions using IOSs  and showed that conventional implant-level impressions with open-tray and splinted implants were more accurate than digital impressions . Tan et It seems that different brands of IOSs can differ significantly in terms of accuracy ,9,15 andMangano et al. measured the trueness and precision for four IOSs and found values from 60.6 to 112.4 μm  and 204.2 to 253.4 μm for Planscan . ImbrugiSince new IOSs come on the market and software evolves, there is a continued need for evaluation of newer IOS models for their trueness and precision in comparison to laboratory scanners. The most demanding experimental model for comparing them is the complete-arch implant model, which is better than the complete-arch dentate model since it contains shapes of regular geometry rendering measurements easier to perform. The null hypotheses of this investigation were that there is no significant difference in the trueness and precision among several intraoral and laboratory scanners in an in vitro setting of a four-implant complete-arch model. Additional null hypotheses were that there is no difference in the trueness and precision between short and long implant distances among implants in complete-arch implant impressions.Seven intraoral scanners  and two laboratory scanners  were selected to compare their trueness and precision in an in vitro setup .A mandibular arch edentulous model made out of type III dental stone was used to drill 4 close-to-parallel sites for implant placement in the positions of right and left canines and molars . CyanoacThe master model with the scan bodies was scanned (×10) with a computerized numerical control 3D Coordinate Measuring Machine (CMM)  at the Mechanical Design and Control Systems Division, School of Mechanical Engineering, National Technical University of Athens, 3 weeks after fabrication and storage in controlled environmental conditions . Dimensional changes were observed in the first two weeks after pouring, but dimensions remained stable later .The CMM has a verified performance in accordance with industry-standard verification tests as per ISO 10360-2:2009  and ISO In each implant scan body, 8 contact points were collected on its cylindrical outer surface and 6 contact points on its planar surface at the top of the cylindrical element . The numx, y, z, coordinates and the distances between them were calculated using the formula:Using standardized mathematical algorithms, the CMM special software performed the numerical fitting of cylindrical features to the sets of the 8 contact points and of planar features to the sets of the 6 contact points. The numerical intersection of the planar feature and the axis derived by the cylindrical feature in each scan body produced a “pierce point”, hereafter referred to as scan-body centroid. A number was assigned to each implant scan body . All scaThe distances were assigned to two groups: the short-distance group (distances of adjacent scan posts during scan progression) D1–2, D2–3, D3–4, and the long-distance group (distances of the scan posts with non-adjacent sites in the arch) D1–3, D1–4, and D2–4 . The samTherefore, 10 scans from each of the tested IOSs were obtained by one operator (DS) with the same digital scanning protocol. Each scanner was calibrated according to manufacturer’s instructions. Starting from the distal area of the most distal implant on the right occlusal surface capturing images occlusally until the left distal implant turning to the buccal of the left implant and capturing until the buccal area of the right distal implant and finishing by capturing the lingual side of the model and the scan bodies. All scans were obtained in a 3-month period (October–December 2019) with the latest acquisition software available at that time for each digital scanner. The scans were obtained at room temperature (20 + 1 °C) with the same conditions regarding light and humidity (50%). Each scan was saved as a Standard Tessellation Language (STL) file, having 90 STL files from the 9 digital scanners tested. Laboratory scanners were used according to manufacturer instructions.n = 10) and precision  of the measurements, using the absolute values of these differences, were examined. Separate general linear models (LMs) were constructed, with the scanner and implant distances as fixed factors, as well as their interaction. Box-cox-transformed trueness and precision values were used to fulfil normality assumptions.Trueness  obtained from the ANOVA summaries. For post hoc comparisons the emmeans function was used with the Tukey method of the emmeans package (v. 1. 5. 0) [All statistical analyses for trueness and precision for short and long distances were performed in R v.3.6.3 . Statistical models were fitted with the lme4 package (v. 1.1-23)  and appr1. 5. 0) . Power aAnalysis of variance showed that the factor scanner was significant for both trueness and precision. The factor distance was not significant; however, the factor scanner had an interaction with distance . DescripStatistical analysis showed that trueness and precision measurements of laboratory scanners and IOSs were significantly different from the master model measured with the CMM. The laboratory scanners showed significantly higher trueness and precision than all IOSs tested for the long-distance group. i500 (259 μm) and Emerald (236 μm) had the worst trueness results compared to all the other IOSs. Only IOS iTero had no different trueness than one of the laboratory scanners (Aman). For the long-distance group, precision differed among the IOSs and the least-precise seemed to be Emerald (185 μm) and statistically significant to all the other scanners .For the short distance, some IOSs were not different in trueness and precision compared to the laboratory scanners. Emerald had the worst trueness 158 μm, followed by i500 99 μm. All the other scanners showed variation with no statistically significant differences in terms of trueness . In termThe null hypothesis was rejected since significant differences in the trueness and precision between the different intraoral and laboratory scanners exist. Since intraoral scanners use optical systems for recording geometry, it is expected that their accuracy and precision may be affected by the optical properties of the object being scanned ,29. MostIn this in vitro study, a type IV stone model was chosen to simulate a clinical case of an edentulous patient with four implants. A dentate model was not selected since we opted for a reference model simulating an edentulous patient with scan bodies of simple geometry, that allow for measurements across well-defined points, avoiding errors due to landmark identification. Many in vitro studies conduct a superimposition of the reference STL model with the STL models produced from the scanners . This alThe basic requirement for an impression of the complete arch with implants is the choice of scan post. In this case, the Elos Medtech scan posts were adopted. PEEK scan posts with a titanium base seem to have good results in terms of accuracy in digital implant impression  and seemAn important issue is the use of the absolute distance differences for statistical analyses. By not using absolute values, negative and positive values in one scanner would neutralize each other and provide a lower mean. Additionally, scanners with the same absolute value but opposite signs would present as significantly different, even if the clinical effect would be exactly the same.In the statistical results, we can see in the ANOVA  that disIn our study, both laboratory scanners were statistically different from the master model in trueness and precision. Since we know from the literature ,40,41 thFrom the group of intraoral scanners, Emerald showed the highest deviation in trueness and precision from all the other IOSs; other studies agree with our findings ,43. SamiAll IOSs except Emerald in short distances and Emerald and i500 in long distances had trueness values lower than 150 μm, which is a proposed threshold for one historic implant system to achieve a clinical acceptable outcome ,44. ThesIn our in vitro study, a mandibular model was used and this could be a limitation for our results . In a cl1.Laboratory scanners have the best trueness and precision compared to all IOSs for long distances. Only iTero had comparable trueness with one laboratory scanner in short and long distances.2.For short distances, CS360, Omnicam, Primescan, and TRIOS 4 had similar trueness to one laboratory scanner. From those, only Omnicam and Primescan had similar precision as the same laboratory scanner.3.Most IOSs seem to work better in smaller distances and are less reliable in cross-arch distances.Within the limitations of the present in vitro study, we could conclude that: