Welcome to an afternoon with excellent talks on the topic of new techniques to study the fine details of life at the molecular level:
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Single molecule tracking data usually contains large amounts of information, but extracting the data from the highly fragmented trajectories, which is often the result of SPT in vivo, can be a real challenge. Traditional methods use Mean Squared Displacement and/or Cumulative Distribution Function analysis to identify parameters in presumed underlying models, but the model has to be guessed a priori and introduction of additional states does always lead to a better fit.
In a paper that was recently published in Nature Methods, we describe an analytical tool based on a variational Bayesian treatment of hidden Markov models that combines the information from thousands of short single-molecule trajectories of intracellularly diffusing proteins. The method identifies the diffusion constants and state transition rates as well as the number of states in the model.
Using this method we have created an objective interaction map for Hfq, a protein that mediates interactions between small regulatory RNAs (green) and their mRNA targets (grey), see image to the right. Photoconvertable proteins were used to track single hfq molecules (yellow) and assign them to different kinetic states based on their diffusive properties. The diffusion constant of hfq depends on its state of binding. Free hfq diffuse fast, but when the molecule is bond to other molecules, e.g. mRNA, the molecule is slowed down. The image was featured on the cover of the March issue of Nature Methods.
After a semester of hard endeavors the Lab Elfs take off to get some well-deserved rest...
...or will they?
Johan Elf is appointed Professor in Biological Physics at Uppsala University.
During recent years, physical modeling has become increasingly important to generate insights into intracellular processes. Many times it is essential to consider both the spatial and stochastic nature of chemical reactions to be able to capture the relevant dynamics of biochemical systems. In this review, which is currently in press for Nature Methods , Fange and Mahmutovic discuss when to use, and when not to use, different models to achieve the best possible balance between speed and physical accuracy.
Different levels of quantitative modeling frameworks for intracellular chemistry.
MesoRD is a simulation tool developed in the Elf Lab. The software is used to simulate stochastic reaction-diffusion systems as modeled by the reaction diffusion master equation. The simulated systems are defined in the Systems Biology Markup Language with additions to define compartment geometries.
Apart from bugfixing, the new release of MesoRD updates the code for the microscopically treated bi-molecular reactions to also include reactants with different diffusion rates.
Aditional information can be found on the MesoRD web or in Fange at al. Bioinformatics 2012
Download MesoRD-1.1 hereGustaf and Mats' paper "Hi-throughput gene expression analysis at the level of single proteins using a microfluidic turbidostat and automated cell tracking" is published in Philosophical Transactions B.
In order to confidently draw conclusions on the nature of transcriptional diversity it is necessary to sample a large number of cells. If done manually this could easily amount to weeks of analysis. By combining automated cell tracking with a microfluidic culture chamber this method makes it possible to analyze the rate of gene expression at the level of single proteins in a sufficient number of bacterial cells.
The movie to the right shows automated tracking of E. Coli in the microfluidic turbidostat
Petter's paper "The lac Repressor Displays Facilitated Diffusion in Living Cells" is published in
Science
The lac repressor is a protein that binds to specific DNA sequences on the E. coli choromsome and regulates the activity of genes. In order to rapidly find these DNA sequenes among millions of others, we have shown that the lac repressor combines siding along the DNA sequences and free diffusion in the cytoplasm. See illustration by Tremani/Elf
Link to abstract at Science website.
Top row from left: Mats, Sorin, Anel, Petter, Fredrik, David and Johan.
Front row from left: Arash, Gustaf, Prune and Cia. Missing: Erik and Andreas.
The Elf lab got the highly competitive ERC Starting Independent Research Grant. Less than 3% of the 9200 applications were granted. The grant implies that a number of postdocs and PhD students will be recruited over the next few years.
We have started building our first single molecule microscope for live cell imaging
J Elf was awarded the Ingvar Carlsson Award (3MSEK) by the Swedish foundation for strategic reserach.
Dr. Brian English joins the Elflab as a postdoctoral fellow. Dr. English is an expert in single molecule sepectroscopy and got his PhD in chemistry at Harvard University.
Returning from
the Xie group at Harvard I am now starting my own group in the department of Cell an Molecular Biology at Uppsala University.
Our work will be focused at the development of new experimental and computational methods for analyzing intracellular transcription factor dynamics at high temporal resolution and spatial precision.
The methods will be
used to answer fundamental questions in bacterial physiology related to transcription factor mediated gene regulation in living
bacterial cells.