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  • 51. Lindsley, Dale
    et al.
    Bonthuis, Paul
    Gallant, Jonathan
    Tofoleanu, Teodora
    Elf, Johan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Faculty of Science and Technology, Biology, Department of Cell and Molecular Biology. Molekylärbiologi.
    Ehrenberg, Måns
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Faculty of Science and Technology, Biology, Department of Cell and Molecular Biology. Molekylärbiologi.
    Ribosome bypassing at serine codons as a test of the model of selective transfer RNA charging.2005In: EMBO Rep, ISSN 1469-221X, Vol. 6, no 2, p. 147-50Article in journal (Other scientific)
  • 52.
    Lindén, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Curic, Vladimir
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Amselem, Elias
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Pointwise error estimates in localization microscopy2017In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 8, article id 15115Article in journal (Refereed)
    Abstract [en]

    Pointwise localization of individual fluorophores is a critical step in super-resolution localization microscopy and single particle tracking. Although the methods are limited by the localization errors of individual fluorophores, the pointwise localization precision has so far been estimated using theoretical best case approximations that disregard, for example, motion blur, defocus effects and variations in fluorescence intensity. Here, we show that pointwise localization precision can be accurately estimated directly from imaging data using the Bayesian posterior density constrained by simple microscope properties. We further demonstrate that the estimated localization precision can be used to improve downstream quantitative analysis, such as estimation of diffusion constants and detection of changes in molecular motion patterns. Finally, the quality of actual point localizations in live cell super-resolution microscopy can be improved beyond the information theoretic lower bound for localization errors in individual images, by modelling the movement of fluorophores and accounting for their pointwise localization uncertainty.

  • 53.
    Lindén, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Single Molecule Tracking in Living Cells: Multistep Reactions, Simulated Microscopy and New Analysis Methods2015In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 108, no 2, p. 360A-360AArticle in journal (Other academic)
  • 54.
    Lindén, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Variational Algorithms for Analyzing Noisy Multistate Diffusion Trajectories2018In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 115, no 2, p. 276-282Article in journal (Refereed)
    Abstract [en]

    Single-particle tracking offers a noninvasive high-resolution probe of biomolecular reactions inside living cells. However, efficient data analysis methods that correctly account for various noise sources are needed to realize the full quantitative potential of the method. We report algorithms for hidden Markov-based analysis of single-particle tracking data, which incorporate most sources of experimental noise, including heterogeneous localization errors and missing positions. Compared to previous implementations, the algorithms offer significant speedups, support for a wider range of inference methods, and a simple user interface. This will enable more advanced and exploratory quantitative analysis of single-particle tracking data.

  • 55.
    Lindén, Martin
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Ćurić, Vladimir
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Boucharin, Alexis
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Fange, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Simulated single molecule microscopy with SMeagol2016In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 32, no 15, p. 2394-2395Article in journal (Refereed)
    Abstract [en]

    Summary: SMeagol is a software tool to simulate highly realistic microscopy data based on spatial systems biology models, in order to facilitate development, validation and optimization of advanced analysis methods for live cell single molecule microscopy data.

    Availability and implementation: SMeagol runs on Matlab R2014 and later, and uses compiled binaries in C for reaction–diffusion simulations. Documentation, source code and binaries for Mac OS, Windows and Ubuntu Linux can be downloaded from http://smeagol.sourceforge.net.

  • 56.
    Mahmutovic, Anel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Berg, Otto G.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    What matters for lac repressor search in vivo-sliding, hopping, intersegment transfer, crowding on DNA or recognition?2015In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 43, no 7, p. 3454-3464Article in journal (Refereed)
    Abstract [en]

    We have investigated which aspects of transcription factor DNA interactions are most important to account for the recent in vivo search time measurements for the dimeric lac repressor. We find the best agreement for a sliding model where non-specific binding to DNA is improbable at first contact and the sliding LacI protein binds at high probability when reaching the specific O-sym operator. We also find that the contribution of hopping to the overall search speed is negligible although physically unavoidable. The parameters that give the best fit reveal sliding distances, including hopping, close to what has been proposed in the past, i.e. similar to 40 bp, but with an unexpectedly high 1D diffusion constant on non-specific DNA sequences. Including a mechanism of inter-segment transfer between distant DNA segments does not bring down the 1D diffusion to the expected fraction of the in vitro value. This suggests a mechanism where transcription factors can slide less hindered in vivo than what is given by a simple viscosity scaling argument or that a modification of the model is needed. For example, the estimated diffusion rate constant would be consistent with the expectation if parts of the chromosome, away from the operator site, were inaccessible for searching.

  • 57.
    Mahmutovic, Anel
    et al.
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Berg, Otto G
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Elf, Johan
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    What matters for lac repressor searchinvivo ––sliding, hopping, intersegment transfer, crowding on DNA or recognition?2015In: Nucleic Acids Research, ISSN 0305-1048, E-ISSN 1362-4962, Vol. 43, no 7, p. 3454-3464Article in journal (Refereed)
    Abstract [en]

    We have investigated which aspects of transcription factor DNA interactions are most important to account for the recent in vivo search time measurements for the dimeric lac repressor. We find the best agreement for a sliding model where non-specific binding to DNA is improbable at first contact and the sliding LacI protein binds at high probability when reaching the specific Osym operator. We also find that the contribution of hopping to the overall search speed is negligible although physically unavoidable. The parameters that give the best fit reveal sliding distances, including hopping, close to what has been proposed in the past, i.e. ∼40 bp, but with an unexpectedly high 1D diffusion constant on non-specific DNA sequences. Including a mechanism of inter-segment transfer between distant DNA segments does not bring down the 1D diffusion to the expected fraction of the in vitro value. This suggests a mechanism where transcription factors can slide less hindered in vivo than what is given by a simple viscosity scaling argument or that a modification of the model is needed. For example, the estimated diffusion rate constant would be consistent with the expectation if parts of the chromosome, away from the operator site, were inaccessible for searching.

  • 58. Mahmutovic, Anel
    et al.
    Fange, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Berg, Otto G
    Elf, Johan
    Lost in presumption: stochastic reactions in spatial models2012In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105Article in journal (Refereed)
  • 59.
    Mahmutovic, Anel
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Fange, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Berg, Otto G.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Lost in presumption: stochastic reactions in spatial models2012In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 9, no 12, p. 1163-1166Article in journal (Refereed)
    Abstract [en]

    Physical modeling is increasingly important for generating insights into intracellular processes. We describe situations in which combined spatial and stochastic aspects of chemical reactions are needed to capture the relevant dynamics of biochemical systems.

  • 60.
    Marklund, Emil
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Amselem, Elias
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Kipper, Kalle
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Johansson, Magnus
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Deindl, Sebastian
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Measuring the Orientation of Single Proteins Interacting with DNA using Fluorescence Polarization Microscopy2017In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 112, no 3, p. 169A-169AArticle in journal (Other academic)
  • 61.
    Marklund, Erik G.
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Mahmutovic, Anel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Berg, Otto G.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hammar, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    van der Spoel, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Fange, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Transcription-factor binding and sliding on DNA studied using micro- and macroscopic models2013In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 110, no 49, p. 19796-19801Article in journal (Refereed)
    Abstract [en]

    Transcription factors search for specific operator sequences by alternating rounds of 3D diffusion with rounds of 1D diffusion (sliding) along the DNA. The details of such sliding have largely been beyond direct experimental observation. For this purpose we devised an analytical formulation of umbrella sampling along a helical coordinate, and from extensive and fully atomistic simulations we quantified the free-energy landscapes that underlie the sliding dynamics and dissociation kinetics for the LacI dimer. The resulting potential of mean force distributions show a fine structure with an amplitude of 1 k(B)T for sliding and 12 kBT for dissociation. Based on the free-energy calculations the repressor slides in close contact with DNA for 8 bp on average before making a microscopic dissociation. By combining the microscopic molecular-dynamics calculations with Brownian simulation including rotational diffusion from the microscopically dissociated state we estimate a macroscopic residence time of 48 ms at the same DNA segment and an in vitro sliding distance of 240 bp. The sliding distance is in agreement with previous in vitro sliding-length estimates. The in vitro prediction for the macroscopic residence time also compares favorably to what we measure by single-molecule imaging of nonspecifically bound fluorescently labeled LacI in living cells. The investigation adds to our understanding of transcription-factor search kinetics and connects the macro-/mesoscopic rate constants to the microscopic dynamics.

  • 62. Marklund, Erik
    et al.
    Mahmutovic, Anel
    Hammar, Petter
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    van der Spoel, David
    Berg, Otto
    Elf, Johan
    LacI follows a helical path while sliding along DNAManuscript (preprint) (Other academic)
  • 63.
    Paintdakhi, Ahmad
    et al.
    Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA..
    Parry, Bradley
    Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA.;Yale Univ, Dept Mol Cellular & Dev Biol, New Haven, CT 06520 USA..
    Campos, Manuel
    Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA.;Yale Univ, Dept Mol Cellular & Dev Biol, New Haven, CT 06520 USA..
    Irnov, Irnov
    Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA.;Yale Univ, Dept Mol Cellular & Dev Biol, New Haven, CT 06520 USA..
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Surovtsev, Ivan
    Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA.;Yale Univ, Dept Mol Cellular & Dev Biol, New Haven, CT 06520 USA..
    Jacobs-Wagner, Christine
    Yale Univ, Microbial Sci Inst, West Haven, CT 06516 USA.;Yale Univ, Howard Hughes Med Inst, New Haven, CT 06520 USA.;Yale Univ, Dept Mol Cellular & Dev Biol, New Haven, CT 06520 USA.;Yale Univ, Sch Med, Dept Microbial Pathogenesis, New Haven, CT 06510 USA..
    Oufti: an integrated software package for high-accuracy, high-throughput quantitative microscopy analysis2016In: Molecular Microbiology, ISSN 0950-382X, E-ISSN 1365-2958, Vol. 99, no 4, p. 767-777Article in journal (Refereed)
    Abstract [en]

    With the realization that bacteria display phenotypic variability among cells and exhibit complex subcellular organization critical for cellular function and behavior, microscopy has re-emerged as a primary tool in bacterial research during the last decade. However, the bottleneck in today's single-cell studies is quantitative image analysis of cells and fluorescent signals. Here, we address current limitations through the development of Oufti, a stand-alone, open-source software package for automated measurements of microbial cells and fluorescence signals from microscopy images. Oufti provides computational solutions for tracking touching cells in confluent samples, handles various cell morphologies, offers algorithms for quantitative analysis of both diffraction and non-diffraction-limited fluorescence signals and is scalable for high-throughput analysis of massive datasets, all with subpixel precision. All functionalities are integrated in a single package. The graphical user interface, which includes interactive modules for segmentation, image analysis and post-processing analysis, makes the software broadly accessible to users irrespective of their computational skills.

  • 64. Paulsson, Johan
    et al.
    Elf, Johan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Faculty of Science and Technology, Biology, Department of Cell and Molecular Biology. Molekylärbiologi.
    Stochastic Modeling of Intracellular Kinetics2006In: System Modeling in Cellular Biology: From Concepts to Nuts and Bolts, The MIT Press, Cambridge , 2006, p. 480-Chapter in book (Other (popular scientific, debate etc.))
  • 65.
    Pedersen, K
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology. MOLEKYLÄRBIOLOGI.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    The bacterial toxin RelE displays codon specific cleavage of mRNAs in the ribosomal A-site2003In: Cell, ISSN 0092-8674, E-ISSN 1097-4172, Vol. 112, no 1, p. 131-140Article in journal (Refereed)
  • 66.
    Persson, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Barkefors, Irmeli
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Single molecule methods with applications in living cells2013In: Current Opinion in Biotechnology, ISSN 0958-1669, E-ISSN 1879-0429, Vol. 24, no 4, p. 737-744Article, review/survey (Refereed)
    Abstract [en]

    Our knowledge about dynamic processes in biological cells systems has been obtained roughly on two levels of detail; molecular level experiments with purified components in test tubes and system wide experiments with indirect readouts in living cells. However, with the development of single molecule methods for application in living cells, this partition has started to dissolve. It is now possible to perform detailed biophysical experiments at high temporal resolution and to directly observe processes at the level of molecules in living cells. In this review we present single molecule methods that can easily be implemented by readers interested to venture into this exciting and expanding field. We also review some recent studies where single molecule methods have been used successfully to answer biological questions as well as some of the most common pitfalls associated with these methods.

  • 67.
    Persson, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Linden, Martin
    Unoson, Cecilia
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    A Bayesian Approach to Single Particle Tracking Analysis2013In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 104, no 2, p. 177A-177AArticle in journal (Other academic)
  • 68.
    Persson, Fredrik
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Linden, Martin
    Unoson, Cecilia
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Extracting intracellular diffusive states and transition rates from single-molecule tracking data2013In: Nature Methods, ISSN 1548-7091, E-ISSN 1548-7105, Vol. 10, no 3, p. 265-269Article in journal (Refereed)
    Abstract [en]

    We provide an analytical tool based on a variational Bayesian treatment of hidden Markov models to combine the information from thousands of short single-molecule trajectories of intracellularly diffusing proteins. The method identifies the number of diffusive states and the state transition rates. Using this method we have created an objective interaction map for Hfq, a protein that mediates interactions between small regulatory RNAs and their mRNA targets.

  • 69.
    Sanamrad, Arash
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Persson, Fredrik
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Lundius, Ebba G.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Fange, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Gynnå, Arvid H.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Single-particle tracking reveals that free ribosomal subunits are not excluded from the Escherichia coli nucleoid2014In: Proceedings of the National Academy of Sciences of the United States of America, ISSN 0027-8424, E-ISSN 1091-6490, Vol. 111, no 31, p. 11413-11418Article in journal (Refereed)
    Abstract [en]

    Biochemical and genetic data show that ribosomes closely follow RNA polymerases that are transcribing protein-coding genes in bacteria. At the same time, electron and fluorescence microscopy have revealed that ribosomes are excluded from the Escherichia coli nucleoid, which seems to be inconsistent with fast translation initiation on nascent mRNA transcripts. The apparent paradox can be reconciled if translation of nascent mRNAs can start throughout the nucleoid before they relocate to the periphery. However, this mechanism requires that free ribosomal subunits are not excluded from the nucleoid. Here, we use single-particle tracking in living E. coli cells to determine the fractions of free ribosomal subunits, classify individual subunits as free or mRNA-bound, and quantify the degree of exclusion of bound and free subunits separately. We show that free subunits are not excluded from the nucleoid. This finding strongly suggests that translation of nascent mRNAs can start throughout the nucleoid, which reconciles the spatial separation of DNA and ribosomes with cotranscriptional translation. We also show that, after translation inhibition, free subunit precursors are partially excluded from the compacted nucleoid. This finding indicates that it is active translation that normally allows ribosomal subunits to assemble on nascent mRNAs throughout the nucleoid and that the effects of translation inhibitors are enhanced by the limited access of ribosomal subunits to nascent mRNAs in the compacted nucleoid.

  • 70. Shyp, Viktoriya
    et al.
    Tankov, Stoyan
    Ermakov, Andrey
    Kudrin, Pavel
    English, Brian P
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Ehrenberg, Måns
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Tenson, Tanel
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hauryliuk, Vasili
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Structure and Molecular Biology.
    Positive allosteric feedback regulation of the stringent response enzyme RelA by its product2012In: EMBO Reports, ISSN 1469-221X, E-ISSN 1469-3178, Vol. 13, no 9, p. 835-839Article in journal (Refereed)
    Abstract [en]

    During the stringent response, Escherichia coli enzyme RelA produces the ppGpp alarmone, which in turn regulates transcription, translation and replication. We show that ppGpp dramatically increases the turnover rate of its own ribosome-dependent synthesis by RelA, resulting in direct positive regulation of an enzyme by its product. Positive allosteric regulation therefore constitutes a new mechanism of enzyme activation. By integrating the output of individual RelA molecules and ppGpp degradation pathways, this regulatory circuit contributes to a fast and coordinated transition to stringency.

  • 71.
    Sjöberg, Paul
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Biology.
    Fokker-Planck approximation of the master equation in molecular biology2005Report (Other academic)
  • 72.
    Sjöberg, Paul
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, The Linnaeus Centre for Bioinformatics.
    Fokker-Planck approximation of the master equation in molecular biology2009In: Computing and Visualization in Science, ISSN 1432-9360, E-ISSN 1433-0369, Vol. 12, p. 37-50Article in journal (Refereed)
  • 73. Sörensen, Michael A
    et al.
    Elf, Johan
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Faculty of Science and Technology, Biology, Department of Cell and Molecular Biology. Molekylärbiologi.
    Bouakaz, Elli
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Faculty of Science and Technology, Biology, Department of Cell and Molecular Biology. Molekylärbiologi.
    Tenson, Tanel
    Sanyal, Suparna
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Faculty of Science and Technology, Biology, Department of Cell and Molecular Biology. Molekylärbiologi.
    Björk, Glenn R
    Ehrenberg, Måns
    Uppsala University, Teknisk-naturvetenskapliga vetenskapsområdet, Faculty of Science and Technology, Biology, Department of Cell and Molecular Biology. Molekylärbiologi.
    Over expression of a tRNA(Leu) isoacceptor changes charging pattern of leucine tRNAs and reveals new codon reading.2005In: J Mol Biol, ISSN 0022-2836, Vol. 354, no 1, p. 16-24Article in journal (Other scientific)
  • 74.
    Ullman, Gustaf
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computational Science.
    Walldén, Mats
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Marklund, Erik G.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Mahmutovic, Anel
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Razinkov, Ivan
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    High-throughput gene expression analysis at the level of single proteins using a microfluidic turbidostat and automated cell tracking2013In: Philosophical Transactions of the Royal Society of London. Biological Sciences, ISSN 0962-8436, E-ISSN 1471-2970, Vol. 368, no 1611, p. 20120025:1-8Article in journal (Refereed)
  • 75.
    Volkov, Ivan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Aguirre, Javier
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Lindén, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Johansson, Magnus
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    In Vivo Measurements of Protein Synthesis Kinetics using Single-Molecule Tracking of E.Coli tRNAS2016In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 110, no 3, p. 351A-351AArticle in journal (Other academic)
  • 76.
    Volkov, Ivan
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Lindén, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Aguirre, Javier
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Ieong, Ka-Weng
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Biology.
    Metelev, Mikhail
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    Johansson, Magnus
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Molecular Systems Biology.
    tRNA tracking for direct measurements of protein synthesis kinetics in live cells2018In: Nature Chemical Biology, ISSN 1552-4450, E-ISSN 1552-4469, Vol. 14, no 6, p. 618-626Article in journal (Refereed)
    Abstract [en]

    Our ability to directly relate results from test-tube biochemical experiments to the kinetics in living cells is very limited. Here we present experimental and analytical tools to directly study the kinetics of fast biochemical reactions in live cells. Dye-labeled molecules are electroporated into bacterial cells and tracked using super-resolved single-molecule microscopy.Trajectories are analyzed by machine-learning algorithms to directly monitor transitions between bound and free states. In particular, we measure the dwell time of tRNAs on ribosomes, and hence achieve direct measurements of translation rates inside living cells at codon resolution. We find elongation rates with tRNA(Phe) that are in perfect agreement with previous indirect estimates, and once fMet-tRNA(fMet) has bound to the 30S ribosomal subunit, initiation of translation is surprisingly fast and does not limit the overall rate of protein synthesis. The experimental and analytical tools for direct kinetics measurements in live cells have applications far beyond bacterial protein synthesis.

  • 77.
    Walldén, Mats
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Studying transcriptional interactions in single cells at sufficient resolution2011In: Current Opinion in Biotechnology, ISSN 0958-1669, E-ISSN 1879-0429, Vol. 22, no 1, p. 81-86Article, review/survey (Refereed)
    Abstract [en]

    Our ability to dissect and understand the principles of gene regulatory circuits is partly limited by the resolution of our experimental assays. In this brief review, we discuss aspects of gene expression in microbial organisms apparent only when increasing the experimental resolution from populations to single cells and sub-cellular structures, from snap-shots to high-speed time-lapse movies and from molecular ensembles to single molecules.

  • 78.
    Walldén, Mats
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Fange, David
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Gustaf, Ullman
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Marklund, Erik G
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Fluctuations in replication initiation determine the generation time and size distributions of E. coli cellsManuscript (preprint) (Other academic)
  • 79.
    Wang, Siyang
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hellander, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Stochastic reaction–diffusion processes with embedded lower dimensional structures2012Report (Other academic)
  • 80.
    Wang, Siyang
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Elf, Johan
    Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Hellander, Stefan
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Lötstedt, Per
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Numerical Analysis.
    Stochastic reaction–diffusion processes with embedded lower-dimensional structures2014In: Bulletin of Mathematical Biology, ISSN 0092-8240, E-ISSN 1522-9602, Vol. 76, p. 819-853Article in journal (Refereed)
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