Research Projects

3D high- and super-resolution imaging at different scales

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Quantitative analysis of super-resolution data

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Single-molecule-based High Content Screening

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Correlative platform for SMLM & STED nanoscopy

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High-content screening imaging of living organoids

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Combining deep-learning with geometric and image processing for analysis of microscopy data

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Expertise

Single-Molecule Localization Microscopy

Light-Sheet Fluorescence Microscopy

High Content Screening

Bioimage Analysis

Geometry Processing

Deep Learning

Selected Publications

F. Levet, J. Tonnesen, U.V. Nagerl, J.B. Sibarita

SpineJ: A software tool for quantitative analysis of nanoscale spine morphology Methods (2020)
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S. Kedia, P. Ramakrishna, P.R. Netrakanti, M. Jose, J.B. Sibarita, S. Nadkarni, D. Nair

Real-time nanoscale organization of amyloid precursor protein Nanoscale (2020)
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D. Jullie, M. Stoeber, J.B. Sibarita, H.L. Zieger, T.M. Bartol, S. Arttamangkul, T.J. Sejnowski, E. Hosy, M. von Zastrow

A Discrete Presynaptic Vesicle Cycle for Neuromodulator Receptors Neuron (2020)
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J. Goncalves, T.M. Bartol, C. Camus, F. Levet, A.P. Menegolla, T.J. Sejnowski, J.B. Sibarita, M. Vivaudou, D. Choquet, E. Hosy

Nanoscale co-organization and coactivation of AMPAR, NMDAR, and mGluR at excitatory synapses PNAS (Proceedings of the National Academy of Sciences) (2020)
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J.S. Ferreira, J.P. Dupuis, B. Kellermayer, N. Benac, C. Manso, D. Bouchet, F. Levet, C. Butler, J.B. Sibarita, L. Groc

Distance-dependent regulation of NMDAR nanoscale organization along hippocampal neuron dendrites PNAS (Proceedings of the National Academy of Sciences) (2020)
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E. Dondi, J.B. Sibarita, N. Varin-Blank, L. Velazquez

The adaptor protein APS modulates BCR signalling in mature B cells Cellular Signaling (2020)
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L. Aoun, A. Farutin, N. Garcia-Seyda, P. Negre, M.S. Rizvi, S. Tlili, S. Song, X. Luo, M. Biarnes-Pelicot, R. Galland, J.B. Sibarita, A. Michelot, C. Hivroz, S. Rafai, M.P. Valignat, C. Misbah, O. Theodoly

Amoeboid Swimming Is Propelled by Molecular Paddling in Lymphocytes Biophysical Journal (2020)
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D. Sage, T.A. Pham, H. Babcock, T. Lukes, T. Pengo, J. Chao, R. Velmurugan, A. Herbert, A. Agrawal, S. Colabrese, A. Wheeler, A. Archetti, B. Rieger, R. Ober, G.M. Hagen, J.B. Sibarita, J. Ries, R. Henriques, M. Unser, S. Holden

Super-resolution fight club: assessment of 2D and 3D single-molecule localization microscopy software Nature Methods (2019)
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A. Mehidi, O. Rossier, M. Schaks, A. Chazeau, F. Biname, A. Remorino, M. Coppey, Z. Karatas, J.B. Sibarita, K. Rottner, V. Moreau, G. Giannone

Transient Activations of Rac1 at the Lamellipodium Tip Trigger Membrane Protrusion Current Biology (2019)
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F. Levet, G. Julien, R. Galland, C. Butler, A. Beghin, A. Chazeau, P. Hoess, J. Ries, G. Giannone, J.B. Sibarita

A tessellation-based colocalization analysis approach for single-molecule localization microscopy Nature Communications (2019)
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V. Inavalli, M.O. Lenz, C. Butler, J. Angibaud, B. Compans, F. Levet, J. Tonnesen, O. Rossier, G. Giannone, O. Thoumine, E. Hosy, D. Choquet, J.B. Sibarita*, U.V. Nagerl*

A super-resolution platform for correlative live single-molecule imaging and STED microscopy Nature Methods (2019)
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M. Letellier, F. Levet, O. Thoumine, Y. Goda

Differential role of pre- and postsynaptic neurons in the activity-dependent control of synaptic strengths across dendrites PLoS Biology (2019)
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Jobs

Software engineer in super-resolution microscopy

Open software engineer position on ANR STABLE-FP. Within the team "Quantitative Imaging of the Cell", the engineer will be tasked to develop quantitative analysis tools for high content analysis of single molecule localization microscopy data, helping to design new photo-convertible fluorescent proteins for SMLM. The expected missions are: i) to develop an analysis platform to characterize fluorophore photophysics from the single molecule localization data, under various experimental conditions; ii) to help performing and optimizing the screening using the HCS-SMLM platform developed in the team.

This work builds on 2 of our Nature Methods paper [1,2] and is part of an interdisciplinary project conducted with the teams of Daniel Choquet (IINS, Bordeaux), Dominique Bourgeois (IBS, Grenoble) and the Bordeaux Imaging Center.

For project details and all other inquiries, please contact;

Dr. Jean-Baptiste Sibarita
E-mail : jean-baptiste.sibarita@u-bordeaux.fr
Tel : +33 (0) 5 33 51 47 06

[1] Beghin, A., et al., Localization-based super-resolution imaging meets high-content screening. Nat Methods, 2017. 14(12): p. 1184-1190.

[2] Levet, F., et al., SR-Tesseler: a method to segment and quantify localization-based super-resolution microscopy data. Nat Methods, 2015. 12(11): p. 1065-71.

Postdoc in Deep Learning and Image Processing

Open Postdoc position on ANR NANO-SYNATLAS. Our goal with this project is to provide a better understanding on how specific protein-protein interactions regulate synapse dynamics and organization. Within the team "Quantitative Imaging of the Cell", the Postdoc will be tasked to process the abundant image and single molecule localization data acquired by our PALM/STED correlative platform ¹ by developing a complete analysis toolbox. This toolbox will allow: (i) efficient segmentation and classification of synapse morphology by using Deep Learning, (ii) automatic quantification of protein organization and dynamics extracted from SMLM data, and (iii) fusion of the nanoscale morpho-dynamic information and creation of an analytical models of the synapse through geometric analysis, parametrization and normalization.

This work builds on several of our highly successful recent methods (2 Nature Methods ^1,2, 1 Nature Communications ³, 1 Methods ⁴) and is part of an interdisciplinary project conducted with the team of Olivier Thoumine (IINS, Bordeaux).

For project details and all other inquiries, please contact;

Dr. Florian Levet
E-mail : florian.levet@u-bordeaux.fr
Tel : +33 (0) 5 33 51 47 47

1.           Inavalli, V.V.G.K. et al. A super-resolution platform for correlative live single-molecule imaging and STED microscopy Nat. Methods 16,  (2019). DOI:10.1038/s41592-019-0611-8

2.           Levet, F. et al. SR-Tesseler: A method to segment and quantify localization-based super-resolution microscopy data Nat. Methods 12,  (2015). DOI:10.1038/nmeth.3579

3.           Levet, F. et al. A tessellation-based colocalization analysis approach for single-molecule localization microscopy Nat. Commun. 10, 1–12 (2019). DOI:10.1038/s41467-019-10007-4

4.           Levet, F., Tønnesen, J., Nägerl, U.V. & Sibarita, J.B. SpineJ: A software tool for quantitative analysis of nanoscale spine morphology Methods 0–1 (2020).doi:10.1016/j.ymeth.2020.01.020. DOI:10.1016/j.ymeth.2020.01.020