FluoSim: simulator of single molecule dynamics for fluorescence live-cell and super-resolution imaging of membrane proteins

Lagardère, Matthieu; Chamma, Ingrid; Bouilhol, Emmanuel; Nikolski, Macha; Thoumine, Olivier

doi:10.1038/s41598-020-75814-y

Cited by 30 publications

(30 citation statements)

References 60 publications

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“…Experiments were performed at DIV 8, 10, or 14, a time window of active excitatory synapse differentiation ( Chanda et al, 2017 ). As a control, we electroporated neurons with GFP-GPI and labeled them with an anti-GFP nanobody conjugated to Atto 647 N, as described ( Lagardère et al, 2020 ). At DIV 8, recombinant AP-MDGA1 and AP-MDGA2 diffused very fast in the dendritic membrane, showing a single peak of diffusion coefficient around 0.30 µm²/s, very similar to GFP-GPI ( Figure 3A and B ).…”

Section: Resultsmentioning

confidence: 99%

“…dSTORM stacks were analyzed using the PALM-Tracer program, allowing the reconstruction of a unique super-resolved image of 32 nm pixel size (zoom 5 compared to the original images) by summing the intensities of all localized single molecules (1 detection per frame is coded by an intensity value of 1). The localization precision of our imaging system in dSTORM conditions is around 60 nm (FWHM) ( Lagardère et al, 2020 ). To analyze protein enrichment at post-synapses, the average number of detections within Homer1c puncta was divided by the the average number of extra-synaptic detections, both normalized per unit area.…”

Section: Methodsmentioning

confidence: 99%

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MDGAs are fast-diffusing molecules that delay excitatory synapse development by altering neuroligin behavior

Toledo

Letellier

Bimbi

et al. 2022

eLife

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MDGA molecules can bind neuroligins and interfere with trans-synaptic interactions to neurexins, thereby impairing synapse development. However, the subcellular localization and dynamics of MDGAs, or their specific action mode in neurons remain unclear. Here, surface immunostaining of endogenous MDGAs and single molecule tracking of recombinant MDGAs in dissociated hippocampal neurons reveal that MDGAs are homogeneously distributed and exhibit fast membrane diffusion, with a small reduction in mobility across neuronal maturation. Knocking-down/out MDGAs using shRNAs and CRISPR/Cas9 strategies increases the density of excitatory synapses, the membrane confinement of neuroligin-1, and the phosphotyrosine level of neuroligins associated with excitatory post-synaptic differentiation. Finally, MDGA silencing reduces the mobility of AMPA receptors, increases the frequency of miniature EPSCs (but not IPSCs), and selectively enhances evoked AMPA-receptor-mediated EPSCs in CA1 pyramidal neurons. Overall, our results support a mechanism by which interactions between MDGAs and neuroligin-1 delays the assembly of functional excitatory synapses containing AMPA receptors.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

MDGAs are fast-diffusing molecules that delay excitatory synapse development by altering neuroligin behavior

Toledo

Letellier

Bimbi

et al. 2022

eLife

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“…We previously applied such a modeling approach to evaluate the mechanisms controlling AMPA receptor trafficking at synapses ( Czöndör et al, 2012 ). In this study, we took advantage of our recently released simulator of membrane protein dynamics, FluoSim, that was thoroughly validated against live-cell and super-resolution imaging experiments performed on lamellipodial contacts mediated by NRXN-NLGN adhesions in heterologous cells ( Lagardère et al, 2020 ). We extended this analysis to model NLGN1 dynamics and organization in the neuronal membrane, with a systematic comparison to single molecule tracking and localization studies, as well as long-term FRAP experiments performed in primary hippocampal neurons.…”

Section: Introductionmentioning

confidence: 99%

High-Resolution Fluorescence Imaging Combined With Computer Simulations to Quantitate Surface Dynamics and Nanoscale Organization of Neuroligin-1 at Synapses

Lagardère

Drouet

Sainlos

et al. 2022

Front. Synaptic Neurosci.

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Neuroligins (NLGNs) form a family of cell adhesion molecules implicated in synapse development, but the mechanisms that retain these proteins at synapses are still incompletely understood. Recent studies indicate that surface-associated NLGN1 is diffusionally trapped at synapses, where it interacts with quasi-static scaffolding elements of the post-synaptic density. Whereas single molecule tracking reveals rapid diffusion and transient immobilization of NLGN1 at synapses within seconds, fluorescence recovery after photobleaching experiments indicate instead a long-term turnover of NLGN1 at synapse, in the hour time range. To gain insight into the mechanisms supporting NLGN1 anchorage at post-synapses and try to reconcile those experimental paradigms, we quantitatively analyzed here live-cell and super-resolution imaging experiments performed on NLGN1 using a newly released simulator of membrane protein dynamics for fluorescence microscopy, FluoSim. Based on a small set of parameters including diffusion coefficients, binding constants, and photophysical rates, the framework describes fairly well the dynamic behavior of extra-synaptic and synaptic NLGN1 over both short and long time ranges, and provides an estimate of NLGN1 copy numbers in post-synaptic densities at steady-state (around 50 dimers). One striking result is that the residence time of NLGN1 at synapses is much longer than what can be expected from extracellular interactions with pre-synaptic neurexins only, suggesting that NLGN1 is stabilized at synapses through multivalent interactions with intracellular post-synaptic scaffolding proteins.

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“…The execution of thought experiments is essential in developing reliable experimental strategies and is especially important for data processing-intensive assays. To allow for the freehand design of ground-truth data while simulating realistic experimental output, we included a simulation module similar to FluoSim (Lagardère et al, 2020). This module allows the generation of user-defined clusters of molecules combined with a selected level of randomly placed background molecules.…”

Section: Resultsmentioning

confidence: 99%

An efficient GUI-based clustering software for simulation and Bayesian cluster analysis of single-molecule localization microscopy data

Kutz¹,

Zehrer²,

Svetlitckii³

et al. 2021

Preprint

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Ligand binding of membrane proteins triggers many important cellular signaling events by the lateral aggregation of ligand-bound and other membrane proteins in the plane of the plasma membrane. This local clustering can lead to the co-enrichment of molecules that create an intracellular signal or bring sufficient amounts of activity together to shift an existing equilibrium towards the execution of a signaling event. In this way, clustering can serve as a cellular switch. The underlying uneven distribution and local enrichment of the signaling cluster's constituting membrane proteins can be used as a functional readout. This information is obtained by combining single-molecule fluorescence microscopy with cluster algorithms that can reliably and reproducibly distinguish clusters from fluctuations in the background noise to generate quantitative data on this complex process. Cluster analysis of single-molecule fluorescence microscopy data has emerged as a proliferative field, and several algorithms and software solutions have been put forward. However, in most cases, such cluster algorithms require multiple analysis parameters to be defined by the user, which may lead to biased results. Furthermore, most cluster algorithms neglect the individual localization precision connected to every localized molecule, leading to imprecise results. Bayesian cluster analysis has been put forward to overcome these problems, but so far, it has entailed high computational cost, increasing runtime drastically. Finally, most software is challenging to use as they require advanced technical knowledge to operate. Here we combined three advanced cluster algorithms with the Bayesian approach and parallelization in a user-friendly GUI and achieved up to an order of magnitude faster processing than for previous approaches. Our work will simplify access to a well-controlled analysis of clustering data generated by SMLM and significantly accelerate data processing. The inclusion of a simulation mode aids in the design of well-controlled experimental assays.

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FluoSim: simulator of single molecule dynamics for fluorescence live-cell and super-resolution imaging of membrane proteins

Cited by 30 publications

References 60 publications

MDGAs are fast-diffusing molecules that delay excitatory synapse development by altering neuroligin behavior

MDGAs are fast-diffusing molecules that delay excitatory synapse development by altering neuroligin behavior

High-Resolution Fluorescence Imaging Combined With Computer Simulations to Quantitate Surface Dynamics and Nanoscale Organization of Neuroligin-1 at Synapses

An efficient GUI-based clustering software for simulation and Bayesian cluster analysis of single-molecule localization microscopy data

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