Encoding mechanical information through multimolecular structures: Lessons from directed cell migration Seminar by Vinay Swaminathan
from Wallenberg Center for Molecular Medicine Fellow, Lund University
Interactions between cells and their mechanical environment is a critical regulator of important physiological functions that gets hijacked in diseases such as cancer. One such function is directed cell migration where cells sense physical cues such as stiffness, varying topologies and fluid flow and migrate directionally in response. While we know relatively a lot about how individual molecules respond to forces, we still lack the understanding of how these “force-sensitive” proteins come together to function in a cell to allow it to sense and transmit mechanical information critical for function. In this seminar, I will first discuss the mechanical cues a cell in our body encounters and their role in normal physiology and disease. I will then introduce the primary subcellular structure that mediates interactions between the cell and its mechanical environment- Integrin-based focal adhesions. I will then describe in detail my recent findings on how integrin receptors come together in focal adhesions and act as mechanical compass where the 3-dimensional orientation of these receptors is sensitive to the magnitude and directionality of mechanical information and thus encodes it. I will also describe the unique microscopy technique that facilitated the discovery of this novel molecular organization and bridges the gap between crystal structures and resolution-limited microscopy. I will conclude by looking ahead to what such an organization of molecules tells us about building mechano-sensitive structures in cells, how we can test its role and perturb it during cell function and how this will provide us with novel insights into diseases such as cancer and immune-disorders.
Controlling the dynamics of colloidal particles by critical Casimir forces
Alessandro Magazzù, Agnese Callegari, Juan Pablo Staforelli, Andrea Gambassi, Siegfried Dietrich & Giovanni Volpe
Soft Matter (2019), accepted
We measure the time evolution of the distance between the two colloids to determine their relative diffusion and drift velocity. Furthermore, we show how critical Casimir forces change the dynamic properties of this two-colloid system by studying the temperature dependence of the distribution of the so-called first-passage time, i.e., of the time necessary for the particles to reach for the first time a certain separation, starting from an initially assigned one. These data are in good agreement with theoretical results obtained from Monte Carlo simulations and Langevin dynamics.
Fast volumetric light-sheet microscopy
Seminar by Omar E. Olarte
from Universidad ECCI, Colombia (and ICFO, Barcelona, Spain)
Light sheet fluorescence microscopy (LSFM) is a convenient tool for bio-imaging as it efficiently collects the generated fluorescence while at the same time minimizes photobleaching. For these reasons LSFM, being based on an intrinsic 2D illumination strategy, has been put forward as an interesting candidate for fast volumetric imaging.
We report on a LSFM microscope, combined with the use of wavefront coding (WFC) techniques, for fast volumetric imaging. This provides intrinsic 3D imaging capabilities as it extends the depth of field (DOF) of the microscope. In addition, because of the extended DOF, the light sheet can be axially scanned at fast speeds. As only the light sheet is moved, fast 3D imaging can be achieved without the need of any sample or objective movement. Since typical light scanning devices can run at KHz rates, 3D volumetric acquisition speeds will only be limited by the reading speed of the camera or the required signal to noise ratio.
WFC works at the expenses of introducing a controlled aberration to the system which blurs the resulting images. Then it requires a final deconvolution step to recover the image sharpness that would impose a limitation on the application. Here we present computational tools to perform real-time deconvolution and visualization of the images obtained with WFC-LSFM. To speed up such deconvolution processes, a routine directly developed in a GPUs has been developed. We present preliminary results on realistic computer generated images showing that real-time deconvolution and visualization is possible.
Effective Drifts in Generalized Langevin Systems
Seminar by Soon Hoe Lim
from Nordita, Stockholm, Sweden, EU
Generalized Langevin equations (GLEs) are stochastic integro-differential equations commonly used as models in non-equilibrium statistical mechanics to describe the dynamics of a particle coupled to a heat bath. From modeling point of view, it is often desirable to derive effective mathematical models, in the form of stochastic differential equations (SDEs), to capture the essential dynamics of the systems. In this talk, we consider effective SDEs describing the behavior of a large class of generalized Langevin systems in the limits when natural time scales become very small. It turns out that additional drift terms, called noise-induced drifts, appear in the effective SDEs. We discuss recent progress on the phenomena of noise-induced drift in these systems. This is joint work with Jan Wehr and Maciej Lowenstein.
Place: Soliden 3rd floor Time: 12 December 2018, 13:00
Our Marie-Curie postdoctoral researcher Jalpa Soni becomes the #MSCA Fellow of the Week, and gets her project highlighted on Tweeter and Facebook pages of the Marie-Skłodowska-Curie Actions
Jalpa is studying the behaviour of micro swimmers like bacteria in 3D complex environments. That will give us the understanding of how they propagate in living systems, which in turn will be used to manipulate them for medicinal advantages.One such example would be to create artificial swimmers (active particles) mimicking natural bacteria for more efficient and targeted drug-delivery applications.To monitor the movement of such micro swimmers in 3D, Jalpa has developed a customised light-sheet microscope that is capable of fast volumetric imaging. The long term goal of the project is to create active particle induced drug-delivery methods for organ-on-chip devices and to monitor the drug efficacy in real time.
This is Jalpa’s insight as a MSCA fellow:
“The unique opportunity to build a new collaborative network has been the most beneficial aspect of my MSCA fellowship. The travels for the project has allowed me to experience different research organisations and to meet experts of various fields which is very important for interdisciplinary research that I love doing.”
Project Name: ActiveMotion3D – Experimental study of three-dimensional dynamics of Active particles
Digital video microscopy enhanced by deep learning
Saga Helgadottir, Aykut Argun & Giovanni Volpe
Single particle tracking is essential in many branches of science and technology, from the measurement of biomolecular forces to the study of colloidal crystals. Standard current methods rely on algorithmic approaches: by fine-tuning several user-defined parameters, these methods can be highly successful at tracking a well-defined kind of particle under low-noise conditions with constant and homogenous illumination. Here, we introduce an alternative data-driven approach based on a convolutional neural network, which we name DeepTrack. We show that DeepTrack outperforms algorithmic approaches, especially in the presence of noise and under poor illumination conditions. We use DeepTrack to track an optically trapped particle under very noisy and unsteady illumination conditions, where standard algorithmic approaches fail. We then demonstrate how DeepTrack can also be used to track multiple particles and non-spherical objects such as bacteria, also at very low signal-to-noise ratios. In order to make DeepTrack readily available for other users, we provide a Python software package, which can be easily personalized and optimized for specific applications.
Panel on the 2018 Nobel Prize in Physics Friday, December 7, 15:00 – 18:00
Oscar Klein hall, Albanova, Roslagstullsbacken 21, Stockholm
Albanova, Stockholm’s center for Physics, Astronomy and Biotechnology cordially organizes a panel discussion about this year’s Nobel Prize in Physics, followed by a social gathering with drinks and snacks.
Panel Members: Felix Ritort, University of Barcelona Cord Arnold, Lunds University Giovanni Volpe, Göteborg University Valdas Pasiskevicius, KTH Royal Institute of Technology
High-Performance Reconstruction of Microscopic Force Fields from Brownian Trajectories Laura Pérez García, Jaime Donlucas Pérez, Giorgio Volpe, Alejandro V. Arzola & Giovanni Volpe
Nature Communications 9, 5166 (2018)
The accurate measurement of microscopic force fields is crucial in many branches of science and technology, from biophotonics and mechanobiology to microscopy and optomechanics. These forces are often probed by analysing their influence on the motion of Brownian particles. Here we introduce a powerful algorithm for microscopic force reconstruction via maximum-likelihood-estimator analysis (FORMA) to retrieve the force field acting on a Brownian particle from the analysis of its displacements. FORMA estimates accurately the conservative and non-conservative components of the force field with important advantages over established techniques, being parameter-free, requiring ten-fold less data and executing orders-of-magnitude faster. We demonstrate FORMA performance using optical tweezers, showing how, outperforming other available techniques, it can identify and characterise stable and unstable equilibrium points in generic force fields. Thanks to its high performance, FORMA can accelerate the development of microscopic and nanoscopic force transducers for physics, biology and engineering.
Tuning phototactic robots with sensorial delays (Editors’ suggestion)
Maximilian Leyman, Freddie Ogemark, Jan Wehr & Giovanni Volpe
Physical Review E 98(26), 052606 (2018)
The presence of a delay between sensing and reacting to a signal can determine the long-term behavior of autonomous agents whose motion is intrinsically noisy.
In a previous work [M. Mijalkov, A. McDaniel, J. Wehr, and G. Volpe, Phys. Rev. X 6, 011008 (2016)], we have shown that sensorial delay can alter the drift and the position probability distribution of an autonomous agent whose speed depends on the illumination intensity it measures. Here, using theory, simulations, and experiments with a phototactic robot, we generalize this effect to an agent for which both speed and rotational diffusion depend on the illumination intensity and are subject to two independent sensorial delays. We show that both the drift and the probability distribution are influenced by the presence of these sensorial delays. In particular, the radial drift may have positive as well as negative sign, and the position probability distribution peaks in different regions depending on the delay.
Furthermore, the presence of multiple sensorial delays permits us to explore the role of the interaction between them.