Robust model-based analysis of single-particle tracking experiments with Spot-On.

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants

Outils pour l'analyse de données de suivi de molécules uniques dans des cellules de mammifères

This work aims at providing tools to dissect the regulation of transcription in eukaryotic cells, with a focus on single-particle tracking of transcription factors in mammalian cells. The nucleus of an eukeryotic cell is an extremely complex medium, that contains a high concentration of macromolecules (DNA, RNA, proteins) and other small molecules (ATP, etc). How these molecules interact with transcription factors, and thus influence transcription rates is an area of intense investigations. Although some of these interactions can be captured by regular biochemistry, many of them, including weak, non-covalent interactions remain undetected by these methods. Live-cell imaging and single-particle tracking (SPT) techniques are increasingly used to characterize such effects. The inference of biophysical parameters of a given transcription factor (TF), such as its diffusion constant, the number of subpopulations or its residence time on DNA, are crucial to understanding how TF dynamics and transcription intertwine. Accurate and validated SPT analysis tools are needed. To be used by the community, SPT tools should not only be carefully validated, but also be easily accessible to non-programmers. They should also be designed to take into account known biases of the imaging techniques. In this work, we first propose a tool, accessible through a web interface, based on the modeling of the diffusion propagator. We validate it extensively and show that it exhibits state-of-the art performance. We apply this tool to two experimental settings: (1) the study of catalysis-enhanced diffusion in-vitro and (2) the analysis of the dynamics of the c-Myc transcription factor in mammalian cells.Ce travail présente des outils pour analyser la régulation de la transcription dans les cellules eucaryotes, en particulier pour le suivi de facteurs de transcription (TF) individuels dans les cellules de mammifères. Un noyau de cellule eucaryote est complexe et contient de nombreuses molécules (ADN, ARN, protéines, ATP, etc). Ces molécules interagissent avec des TF et influencent la transcription. Certaines de ces interactions peuvent être étudiées par des techniques de biochimie. La plupart, en particulier les interactions faibles, non covalentes, sont invisibles par ces méthodes. La microscopie de cellules vivantes et le suivi de molécules uniques (SPT en anglais) sont de plus en plus utilisées pour étudier ces phénomènes. L'inférence des paramètres biophysiques d'un facteur de transcription, par exemple son coefficient de diffusion, son nombre de sous-populations ou son temps de résidence sur l'ADN sont cruciaux pour comprendre sa dynamique et son influence sur la transcription. Des outils validés et précis sont donc nécessaires pour analyser les données de SPT. Pour être utile, un outil de SPT doit être non seulement validé, mais aussi accessible à des non-programmeurs. Ils doivent aussi tenir compte des biais expérimentaux présents dans les données. Nous proposons un outil d'analyse de SPT, qui se fonde sur l'estimation du propagateur de la diffusion. Ce outil a été validé et est accessible par une interface web. Nous avons montré qu'il donne des résultats proches de l'état de l'art. Il a été testé dans deux cadres : (1) l'étude de la diffusion augmentée par la catalyse enzymatique in vitro et (2) l'analyse de la dynamique du TF c-Myc dans des cellules de mammifères

Source files and reconstructions for "Simple 3D compressed sensing scheme for faster and less phototoxic fluorescence microscopy imaging"

<p>Source files and reconstructions for "Simple 3D compressed sensing scheme for faster and less phototoxic fluorescence microscopy imaging"</p> <p>The source files are to be used with the code on https://github.com/MaximeMaW/CompressedSensingMicroscopy3D (also archived in https://zenodo.org/record/439690)</p> <ol> <li>The files prefixed with "VIZ" are high resolution TIF visualizations.</li> <li>The files come from three experiments on two different setups: <ol> <li>A lattice light sheet microscope (LLSM): beads sample (filed termed "<strong>lattice-beads</strong>" and actin-labelled mESCs (files termed "<strong>lattice-phalloidin</strong>")</li> <li>An epifluorescence microscope: beads sample (files termed "<strong>epifluorescence</strong>")</li> </ol> </li> <li>The acquisitions were either performed using an identity measurement matrix (mimicking the plane-by-plane acquisition mode of a traditional z-stack): files termes "<strong>reference</strong>" or with a Fourier measurement matrix (described in the code mentioned above) with a compression ratio of 2 (files termed "<strong>compressed</strong>".</li> <li>The reconstructions were performed as described in the paper with the code mentioned above. Several reconstructions were computed from the same compressed images by simulating increasing compression ratios. To do so, reconstructions were performed by selecting a subset of the acquired planes (number indicated as "<strong>**frames</strong>")</li> <li>Reconstructions were sparsified using a 2D PSF model computed for our epifliuorescence setup and the LLSM (files termed "<strong>PSF_model</strong>"). These are provided as numpy arrays.</li> </ol> <p> </p

Protein motion in the nucleus: from anomalous diffusion to weak interactions

International audienceUnderstanding how transcription factors (TFs) regulate mammalian gene expression in space and time is a central topic in biology. To activate a gene, a TF has first to diffuse in the available space of the nucleus until it reaches a target DNA sequence or protein (target site). This eventually results in the recruitment of the whole transcriptional machinery. All these processes take place in the mammalian nucleoplasm, a highly organized and dynamic environment, in which some complexes transiently assemble and break apart, whereas others appear more stable. This diversity of dynamic behaviors arises from the number of biomolecules that make up the nucleoplasm and their pairwise interactions. Indeed, interactions energies that span several orders of magnitude, from covalent bounds to transient and dynamic interactions, can shape nuclear landscapes. Thus, the nuclear environment determines how frequently and how fast a TF contacts its target site, and it indirectly regulates gene expression. How exactly transient interactions are involved in the regulation of TF diffusion is unclear, but are reflected by live cell imaging techniques, including single-particle tracking (SPT). Overall, the macroscopic result of these microscopic interactions is almost always anomalous diffusion, a phenomenon widely studied and modeled. Here, we review the connections between the anomalous diffusion of a TF observed by SPT and the microscopic organization of the nucleus, including recently described topologically associated domains and dynamic phase-separated compartments. We propose that anomalous diffusion found in SPT data result from weak and transient interactions with dynamic nuclear substructures, and that SPT data analysis would benefit from a better description of such structures

How the Genome Folds: The Biophysics of Four-Dimensional Chromatin Organization

International audienceThe genetic information that instructs transcription and other cellular functions is carried by the chromosomes, polymers of DNA in complex with histones and other proteins. These polymers are folded inside nuclei five orders of magnitude smaller than their linear length, and many facets of this folding correlate with or are causally related to transcription and other cellular functions. Recent advances in sequencing and imaging-based techniques have enabled new views into several layers of chromatin organization. These experimental findings are accompanied by computational modeling efforts based on polymer physics that can provide mechanistic insights and quantitative predictions. Here, we review current knowledge of the main levels of chromatin organization, from the scale of nucleosomes to the entire nucleus, our current understanding of their underlying biophysical and molecular mechanisms, and some of their functional implications

Faster and less phototoxic 3D fluorescence microscopy using a versatile compressed sensing scheme

International audienceThree-dimensional fluorescence microscopy based on Nyquist sampling of focal planes faces harsh trade-offs between acquisition time, light exposure, and signal-to-noise. We propose a 3D compressed sensing approach that uses temporal modulation of the excitation intensity during axial stage sweeping and can be adapted to fluorescence microscopes without hardware modification. We describe implementations on a lattice light sheet microscope and an epifluorescence microscope, and show that images of beads and biological samples can be reconstructed with a 5-10 fold reduction of light exposure and acquisition time. Our scheme opens a new door towards faster and less damaging 3D fluorescence microscopy., "Metamaterial apertures for computational imaging," Science 310, 399 (2013). 12. J. Shin, B. T. Bosworth, and M. A. Foster, "Compressive fluorescence imaging using a multi-core fiber and spatially dependent scattering," Opt Lett 109, 42 (2017). 13. L. Gao, J. Liang, C. Li, and L. V. Wang, "Single-shot compressed ultrafast photography at one hundred billion frames per second," Nature 516, 74-77 (2014). 14. J. Liang, C. Ma, L. Zhu, Y. Chen, L. Gao, and L. V. Wang, "Single-shot real-time video recording of a photonic Mach cone induced by a scattered light pulse," Sci Adv 3, e1601814 (2017). 15. E. McLeod and A. Ozcan, "Unconventional methods of imaging: computational microscopy and compact implementations ,

Anomalous Subdiffusion in Living Cells: Bridging the Gap Between Experiments and Realistic Models Through Collaborative Challenges

International audienceThe life of a cell is governed by highly dynamical microscopic processes. Two notable examples are the diffusion of membrane receptors and the kinetics of transcription factors governing the rates of gene expression. Different fluorescence imaging techniques have emerged to study molecular dynamics. Among them, fluorescence correlation spectroscopy (FCS) and single-particle tracking (SPT) have proven to be instrumental to our understanding of cell dynamics and function. The analysis of SPT and FCS is an ongoing effort, and despite decades of work, much progress remains to be done. In this paper, we give a quick overview of the existing techniques used to analyze anomalous diffusion in cells and propose a collaborative challenge to foster the development of state-of-the-art analysis algorithms. We propose to provide labeled (training) and unlabeled (evaluation) simulated data to competitors all over the world in an open and fair challenge. The goal is to offer unified data benchmarks based on biologically-relevant metrics in order to compare the diffusion analysis software available for the community

Compartmental models for seasonal hyperendemic bacterial meningitis in the African meningitis belt

International audienceThe pathophysiological mechanisms underlying the seasonal dynamic and epidemic occurrence of bacterial meningitis in the African meningitis belt remain unknown. Regular seasonality (seasonal hyperendemicity) is observed for both meningococcal and pneumococcal meningitis and understanding this is critical for better prevention and modelling. The two principal hypotheses for hyperendemicity during the dry season imply (1) an increased risk of invasive disease given asymptomatic carriage of meningococci and pneumococci; or (2) an increased transmission of these bacteria from carriers and ill individuals. In this study, we formulated three compartmental deterministic models of seasonal hyperendemicity, featuring one (model1-‘inv’ or model2-‘transm’), or a combination (model3-‘inv-transm’) of the two hypotheses. We parameterised the models based on current knowledge on meningococcal and pneumococcal biology and pathophysiology. We compared the three models' performance in reproducing weekly incidences of suspected cases of acute bacterial meningitis reported by health centres in Burkina Faso during 2004–2010, through the meningitis surveillance system. The three models performed well (coefficient of determination R2, 0.72, 0.86 and 0.87, respectively). Model2-‘transm’ and model3-‘inv-transm’ better captured the amplitude of the seasonal incidence. However, model2-‘transm’ required a higher constant invasion rate for a similar average baseline transmission rate. The results suggest that a combination of seasonal changes of the risk of invasive disease and carriage transmission is involved in the hyperendemic seasonality of bacterial meningitis in the African meningitis belt. Consequently, both interventions reducing the risk of nasopharyngeal invasion and the bacteria transmission, especially during the dry season are believed to be needed to limit the recurrent seasonality of bacterial meningitis in the meningitis belt