- Hammar & Walldén et al. Nature Genetics, 2014. Non-equilibrium contributions to transcription factor mediated gene regulation.
- Marklund et al. PNAS, 2013. Transcription-factor binding and sliding on DNA studied using micro- and macroscopic models
- Grönlund et al. Nature Comm., 2013. Transcription factor binding kinetics constrain noise suppression via negative feedback.
- Persson et al. Nature Methods, 2013. Extracting intracellular diffusive states and transition rates from single molecule tracking data.
- Fange et al. Nature Methods, 2012. Lost in presumption: stochastic reactions in spatial models.
- Hammar et al. Science, 2012. The lac repressor displays facilitated diffusion in living cells.
For more information & complete list of publications, please visit the library.
The overall ambition of our research is to bridge the gap between quantitative physical models and biological observations in order to identify and resolve inconsistencies in our current understanding of life at the molecular level.
We are particularly interested in how key steps in transcription, translation and replication are regulated in the intracellular environment and at what level of physical detail these processes need to be modeled to describe their function in the living cell.
To answer these questions we use state-of-the-art single molecule microscopy methods to study kinetics and diffusion in living cells (Elf et al Science 2007, 2012, PNAS 2011, Hammar et al. Science 2012). We also develop new microfluidic techniques and corresponding analysis software to control growth conditions and enable automation. These experimental techniques are accompanied by the development of pioneering computational tools for stochastic reaction-diffusion simulation of intracellular kinetics (Fange and Elf, PLoS CB 2006, PNAS 2010, Fange et al. Nature Methods 2012) and mathematical modeling of intercellular physiology (Elf et al, Science 2003; Nature Physics 2009, PNAS 2010, Nature Communications 2011).
Read what Valda Vinson write about Petter and Mats' paper "Non-equilibrium contributions to transcription factor mediated gene regulation" in Science Magazine editors' choice, Volume 343, Number 6178, Issue of 28 March 2014.
A new method for direct measurement of transcription factor dissociation makes it possible to exclude a simple operator occupancy model for gene regulation.
One by one the mysteries of gene regulation are subject to scrutiny, and our models, the way we understand gene regulation, are put to the test. We know that lacI, the repressor of the lactose digestion machinery in the cell, searches for its binding site using a combination of 3D diffusion and sliding on the DNA, we know that it slides around 45 bases before detaching and we know that it takes less than a minute for a lacI repressor to find and bind the operator, although most of the time, the TFs slide over the binding site without binding. However, to test the prevailing model for TF mediated gene regulation, which assumes that the level of repression is determined by the equilibrium binding by the repressor to its operator, we also need to know how long the TF stays bound to the DNA before it dissociates macroscopically, e.i. leaves the immediate vicinity of the regulatory site. Using a new technique based on a single molecule chase assay we can answer this question - lacI stays bound to its specific operator for on average 5 min. So far so good, with an association time of 30 s and a repression ratio of 10 (as measured by an enzymatic reporter) the model is in no immediate danger. However, if the native operator is replaced by a stronger one, this results in a slower dissociation while the association rate stays approximately the same. Conclusion; our findings do not support the simple equilibrium model and this discrepancy has to be considered when predicting gene activity from TF binding strengths. For more details, visit Nature genetics, where the study can be read in its entirety.
Petter Hammar is awarded Bjurzons Premium for his thesis lac of time. The prize is awarded annually by the Uppsala University Vice-Chancellor in recognition of an excellent scientific thesis by a student or young lecturer.
What do elephants have to do with anything? Find out more in Petter's thesis
The Christmas spirit is particularly strong in the laser-lab where the new 638 nm laser takes up the competition with Rudolph the reindeer in Christmas-red glowiness.
We have previously shown that the lac repressor slides along the DNA to speed up the search for its specific binding site. By combining micro- and macroscopic computational models, we have now been able to investigate the details of the sliding mechanism on the atomic scale. The lac dimer follows the major groove of the DNA helix, causing it to slide in a spiral motion. It remains close to the DNA for about 8bp before making a microscopic dissociation and stays on the same DNA fragment for an average 48 ms. This corresponds to an in vitro sliding length of 240 bp which correlates well with in vitro measurements. The study presents an unique combination of theoretic tools and the results satisfyingly connect macro-/mesoscopic events at the nanometer level, which enables a deeper interpretation of experimental observations.
Petter Hammar successfully defended his thesis: lac of time.
On a rather rainy day in June, Petter Hammar and his opponent Antoine van Oijen put on a show that kept the audience enchanted for a good 3 hours. The celebration continued at the Old Fellow House well into the following morning.
Left: Petter and Antoine deep in discussion. Top right: The committee delivers the happy news that Petter has passed the examination. From the right, Antoine van Oijen (opponent), Carolina Wählby, Yu Ji, Nora Ausmees and Johan Elf (proud supervisor). Paul Blainey and Mats Nilsson were also part of the evaluation committee. Bottom Right: The defense attracted a rather large crowd.
Welcome to an afternoon with excellent talks on the topic of new techniques to study the fine details of life at the molecular level:
It is easy to imagine that the transcription factors (TFs) are superfast regulators of gene expression, but in reality it might take several minutes before a TF finds and binds its target sequence. As a result, negative feed-back (where the expression of a TF is inhibited by the TF itself) cannot at the same time be fast and strong.
If the TF binds strongly to the repressor site, most proteins are necessarily produced immediately after cell replication and if the binding is very week, the protein production is essentially linear; in both cases the negative-feedback is virtually nonexistent. In a recent paper in Nature Communications, we show that there is an optimal TF binding strength, where the time the binding site is free is not dependent on TF concentration. An important implication is that the TF binding strength is not necessarily correlated to its functional importance as a gene regulator.
Extracting information from single-molecule tracking data
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.Download MesoRD-1.1 here
Gustaf 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
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.