Måns Ehrenberg

Uppsala University, Uppsala, Uppsala, Sweden

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Publications (209)1507.99 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: The antibiotic fusidic acid (FA) targets elongation factor G (EF-G) and inhibits ribosomal peptide elongation and ribosomal recycling, but deeper mechanistic aspects of FA action have remained unknown. Using quench-flow and stopped flow experiments in a biochemical system for protein synthesis and taking advantage of separate time scales for inhibited (10 s) and uninhibited (100 ms) elongation cycles a detailed kinetic model of FA action was obtained. FA targets EF-G at an early stage in the translocation process (I), which proceeds unhindered by the presence of the drug to a later stage (II), where the ribosome stalls. Stalling may also occur at a third stage of translocation (III), just before release of EF-G from the post-translocation ribosome. We show that FA is a strong elongation inhibitor (K50% ≈ 1 μM), discuss the identity of the FA targeted states and place existing cryo-EM and crystal structures in functional context. Copyright © 2014, The American Society for Biochemistry and Molecular Biology.
    The Journal of biological chemistry. 12/2014;
  • Anneli Borg, Måns Ehrenberg
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    ABSTRACT: To study the rate of translocation of mRNA and tRNAs on the translating ribosome is technically difficult, since the rate limiting steps involve large conformational changes without covalent bond formation or disruption. Here, we have developed a unique assay system for precise estimation of the full translocation cycle time at any position in any type of open reading frame (ORF). Using a buffer system optimized for high accuracy of transfer RNA selection together with high concentration of elongation factor G we obtained in vivo compatible translocation rates. We found that translocation was comparatively slow early in the ORF and faster further downstream of the initiation codon. The maximal translocation rate decreased from the in vivo compatible value of 30 s- 1 at 1 mM free Mg2 + concentration to the detrimentally low value of 1 s- 1 at 6 mM free Mg2 + concentration. Thus, high and in vivo compatible accuracy of codon translation as well as high and in vivo compatible translocation rate required a remarkably low Mg2 + concentration. Finally, we found that the rate of translocation deep inside an ORF was not significantly affected upon variation of the standard free energy of interaction between a 6-nt upstream SD-like sequence and the anti-SD sequence of 16S rRNA in the zero to 6 kcal/mole range. Based on these experiments we discuss the optimal choice of Mg2 + concentration for maximal fitness of the living cell by taking its effects on the accuracy of translation, the peptide bond formation rate and the translocation rate into account.
    Journal of Molecular Biology. 11/2014;
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    ABSTRACT: Abstract Applications of N-methyl amino acids (NMAAs) in drug discovery are limited by their low efficiencies of ribosomal incorporation and little is known mechanistically about the steps leading to incorporation. Here, we demonstrate that a synthetic tRNA body based on a natural N-alkyl amino acid carrier, tRNAPro, increases translation incorporation rates of all three studied NMAAs compared with tRNAPhe- and tRNAAla-based bodies. We also investigate the pH dependence of the incorporation rates and find that the rates increase dramatically in the range of pH 7 to 8.5 with the titration of a single proton. Results support a rate-limiting peptidyl transfer step dependent on deprotonation of the N-nucleophile of the NMAA. Competition experiments demonstrate that several futile cycles of delivery and rejection of A-site NMAA-tRNA are required per peptide bond formed and that increasing magnesium ion concentration increases incorporation yield. Data clarify the mechanism of ribosomal NMAA incorporation and provide three generalizable ways to improve incorporation of NMAAs in translation.
    ACS Chemical Biology 03/2014; · 5.44 Impact Factor
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    ABSTRACT: There is evidence that tRNA bodies have evolved to reduce differences between aminoacyl-tRNAs in their affinity to EF-Tu. Here, we study the kinetics of incorporation of L-amino acids (AAs) Phe, Ala allyl-glycine (aG), methyl-serine (mS), and biotinyl-lysine (bK) using a tRNA(Ala)-based body (tRNA(AlaB)) with a high affinity for EF-Tu. Results are compared with previous data on the kinetics of incorporation of the same AAs using a tRNA(PheB) body with a comparatively low affinity for EF-Tu. All incorporations exhibited fast and slow phases, reflecting the equilibrium fraction of AA-tRNA in active ternary complex with EF-Tu:GTP before the incorporation reaction. Increasing the concentration of EF-Tu increased the amplitude of the fast phase and left its rate unaltered. This allowed estimation of the affinity of each AA-tRNA to EF-Tu:GTP during translation, showing about a 10-fold higher EF-Tu affinity for AA-tRNAs formed from the tRNA(AlaB) body than from the tRNA(PheB) body. At ∼1 µM EF-Tu, tRNA(AlaB) conferred considerably faster incorporation kinetics than tRNA(PheB), especially in the case of the bulky bK. In contrast, the swap to the tRNA(AlaB) body did not increase the fast phase fraction of N-methyl-Phe incorporation, suggesting that the slow incorporation of N-methyl-Phe had a different cause than low EF-Tu:GTP affinity. The total time for AA-tRNA release from EF-Tu:GDP, accommodation, and peptidyl transfer on the ribosome was similar for the tRNA(AlaB) and tRNA(PheB) bodies. We conclude that a tRNA body with high EF-Tu affinity can greatly improve incorporation of unnatural AAs in a potentially generalizable manner.
    RNA 03/2014; · 5.09 Impact Factor
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    ABSTRACT: Previous electron-microscopic imaging has shown high RNA polymerase occupation densities in the 16S and 23S encoding regions and low occupation densities in the noncoding leader, spacer, and trailer regions of the rRNA (rrn) operons in E. coli. This indicates slower transcript elongation within the coding regions and faster elongation within the noncoding regions of the operon. Inactivation of four of the seven rrn operons increases the transcript initiation frequency at the promoters of the three intact operons and reduces the time for RNA polymerase to traverse the operon. We have used the DNA sequence-dependent standard free energy variation of the transcription complex to model the experimentally observed changes in the elongation rate along the rrnB operon. We also model the stimulation of the average transcription rate over the whole operon by increasing rate of transcript initiation. Monte Carlo simulations, taking into account initiation of transcription, translocation, and backward and forward tracking of RNA polymerase, partially reproduce the observed transcript elongation rate variations along the rrn operon and fully account for the increased average rate in response to increased frequency of transcript initiation.
    Biophysical Journal 01/2014; 106(1):55-64. · 3.67 Impact Factor
  • Michael Y Pavlov, Måns Ehrenberg
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    ABSTRACT: Bacterial populations growing in a changing world must adjust their proteome composition in response to alterations in the environment. Rapid proteome responses to growth medium changes are expected to increase the average growth rate and fitness value of these populations. Little is known about the dynamics of proteome change, e.g., whether bacteria use optimal strategies of gene expression for rapid proteome adjustments and if there are lower bounds to the time of proteome adaptation in response to growth medium changes. To begin answering these types of questions, we modeled growing bacteria as stoichiometrically coupled networks of metabolic pathways. These are balanced during steady-state growth in a constant environment but are initially unbalanced after rapid medium shifts due to a shortage of enzymes required at higher concentrations in the new environment. We identified an optimal strategy for rapid proteome adjustment in the absence of protein degradation and found a lower bound to the time of proteome adaptation after medium shifts. This minimal time is determined by the ratio between the Kullback-Leibler distance from the pre- to the postshift proteome and the postshift steady-state growth rate. The dynamics of optimally controlled proteome adaptation has a simple analytical solution. We used detailed numerical modeling to demonstrate that realistic bacterial control systems can emulate this optimal strategy for rapid proteome adaptation. Our results may provide a conceptual link between the physiology and population genetics of growing bacteria.
    Proceedings of the National Academy of Sciences 12/2013; · 9.81 Impact Factor
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    ABSTRACT: Inferring antibiotic mechanisms on translation through static structures has been challenging, as biological systems are highly dynamic. Dynamic single-molecule methods are also limited to few simultaneously measurable parameters. We have circumvented these limitations with a multifaceted approach to investigate three structurally distinct aminoglycosides that bind to the aminoacyl-transfer RNA site (A site) in the prokaryotic 30S ribosomal subunit: apramycin, paromomycin, and gentamicin. Using several single-molecule fluorescence measurements combined with structural and biochemical techniques, we observed distinct changes to translational dynamics for each aminoglycoside. While all three drugs effectively inhibit translation elongation, their actions are structurally and mechanistically distinct. Apramycin does not displace A1492 and A1493 at the decoding center, as demonstrated by a solution nuclear magnetic resonance structure, causing only limited miscoding; instead, it primarily blocks translocation. Paromomycin and gentamicin, which displace A1492 and A1493, cause significant miscoding, block intersubunit rotation, and inhibit translocation. Our results show the power of combined dynamics, structural, and biochemical approaches to elucidate the complex mechanisms underlying translation and its inhibition.
    Cell Reports 02/2013; 3(2):497-508. · 7.21 Impact Factor
  • Måns Ehrenberg, Michael Yu Pavlov
    Biophysical Journal 01/2013; 104(2):205-. · 3.67 Impact Factor
  • Harriet Mellenius, Måns Ehrenberg
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    ABSTRACT: Termination of messenger RNA translation in Bacteria and Archaea is initiated by release factors (RFs) 1 or 2 recognizing a stop codon in the ribosomal A site and releasing the peptide from the P-site transfer RNA. After release, RF-dissociation is facilitated by the G-protein RF3. Structures of ribosomal complexes with RF1 or RF2 alone or with RF3 alone-RF3 bound to a non-hydrolyzable GTP-analog-have been reported. Here, we present the cryo-EM structure of a post-termination ribosome containing both apo-RF3 and RF1. The conformation of RF3 is distinct from those of free RF3•GDP and ribosome-bound RF3•GDP(C/N)P. Furthermore, the conformation of RF1 differs from those observed in RF3-lacking ribosomal complexes. Our study provides structural keys to the mechanism of guanine nucleotide exchange on RF3 and to an L12-mediated ribosomal recruitment of RF3. In conjunction with previous observations, our data provide the foundation to structurally characterize the complete action cycle of the G-protein RF3. DOI:http://dx.doi.org/10.7554/eLife.00411.001.
    eLife Sciences 01/2013; 2:e00411. · 8.52 Impact Factor
  • Måns Ehrenberg, Hans Bremer, Patrick P Dennis
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    ABSTRACT: By combining results from previous studies of nutritional up-shifts we here re-investigate how bacteria adapt to different nutritional environments by adjusting their macromolecular composition for optimal growth. We demonstrate that, in contrast to the commonly held view of the bacterial growth rate as an independent variable, the macromolecular composition of bacteria depends on three factors: (i) the genetic background (i.e. the strain used), (ii) the physiological history of the bacteria used for inoculation of a given growth medium, and (iii) the kind of nutrients in the growth medium. These factors determine the ribosome concentration and the average rate of protein synthesis per ribosome, and thus the growth rate. Immediately after a nutritional up-shift, the average number of ribosomes in the bacterial population increases exponentially with time at a rate which eventually is attained as the final post-shift growth rate of all cell components. After a nutritional up-shift from one minimal medium to another of higher nutritional quality, ribosome and RNA polymerase syntheses are co-regulated and immediately increase by the same factor equal to the increase in the final growth rate. However, after an up-shift from a minimal medium to a medium containing all 20 amino acids, RNA polymerase and ribosome syntheses are no longer coregulated, but the smaller rate of synthesis of RNA polymerase is compensated by a gradual increase in the fraction of free RNA polymerase concentration, possibly due to a gradual saturation of mRNA promoters. We have also analyzed data from a recent publication, in which it was concluded that the macromolecular composition in terms of RNA/protein and RNA/DNA ratios is solely determined by the effector molecule ppGpp. Our analysis indicates that this is true only in special cases and that, in general, medium adaptation also depends on factors other than ppGpp.
    Biochimie 12/2012; · 3.14 Impact Factor
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    ABSTRACT: Translations with unnatural amino acids (AAs) are generally inefficient, and kinetic studies of their incorporations from transfer ribonucleic acids (tRNAs) are few. Here, the incorporations of small and large, non-N-alkylated, unnatural l-AAs into dipeptides were compared with those of natural AAs using quench-flow techniques. Surprisingly, all incorporations occurred in two phases: fast then slow, and the incorporations of unnatural AA-tRNAs proceeded with rates of fast and slow phases similar to those for natural Phe-tRNA(Phe). The slow phases were much more pronounced with unnatural AA-tRNAs, correlating with their known inefficient incorporations. Importantly, even for unnatural AA-tRNAs the fast phases could be made dominant by using high EF-Tu concentrations and/or lower reaction temperature, which may be generally useful for improving incorporations. Also, our observed effects of EF-Tu concentration on the fraction of the fast phase of incorporation enabled direct assay of the affinities of the AA-tRNAs for EF-Tu during translation. Our unmodified tRNA(Phe) derivative adaptor charged with a large unnatural AA, biotinyl-lysine, had a very low affinity for EF-Tu:GTP, while the small unnatural AAs on the same tRNA body had essentially the same affinities to EF-Tu:GTP as natural AAs on this tRNA, but still 2-fold less than natural Phe-tRNA(Phe). We conclude that the inefficiencies of unnatural AA-tRNA incorporations were caused by inefficient delivery to the ribosome by EF-Tu, not slow peptide bond formation on the ribosome.
    Journal of the American Chemical Society 10/2012; · 10.68 Impact Factor
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    ABSTRACT: 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.
    EMBO Reports 07/2012; 13(9):835-9. · 7.19 Impact Factor
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    Magnus Johansson, Jingji Zhang, Måns Ehrenberg
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    ABSTRACT: Rapid and accurate translation of the genetic code into protein is fundamental to life. Yet due to lack of a suitable assay, little is known about the accuracy-determining parameters and their correlation with translational speed. Here, we develop such an assay, based on Mg(2+) concentration changes, to determine maximal accuracy limits for a complete set of single-mismatch codon-anticodon interactions. We found a simple, linear trade-off between efficiency of cognate codon reading and accuracy of tRNA selection. The maximal accuracy was highest for the second codon position and lowest for the third. The results rationalize the existence of proofreading in code reading and have implications for the understanding of tRNA modifications, as well as of translation error-modulating ribosomal mutations and antibiotics. Finally, the results bridge the gap between in vivo and in vitro translation and allow us to calibrate our test tube conditions to represent the environment inside the living cell.
    Proceedings of the National Academy of Sciences 12/2011; 109(1):131-6. · 9.81 Impact Factor
  • Anders Liljas, Måns Ehrenberg, Johan Åqvist
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    ABSTRACT: Voorhees et al. (Reports, 5 November 2010, p. 835) determined the structure of elongation factor Tu (EF-Tu) and aminoacyl-transfer RNA bound to the ribosome with a guanosine triphosphate (GTP) analog. However, their identification of histidine-84 of EF-Tu as deprotonating the catalytic water molecule is problematic in relation to their atomic structure; the terminal phosphate of GTP is more likely to be the proper proton acceptor.
    Science 07/2011; 333(6038):37; author reply 37. · 31.20 Impact Factor
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    ABSTRACT: Enzyme inhibitors are used in many areas of the life sciences, ranging from basic research to the combat of disease in the clinic. Inhibitors are traditionally characterized by how they affect the steady-state kinetics of enzymes, commonly analyzed on the assumption that enzyme-bound and free substrate molecules are in equilibrium. This assumption, implying that an enzyme-bound substrate molecule has near zero probability to form a product rather than dissociate, is valid only for very inefficient enzymes. When it is relaxed, more complex but also more information-rich steady-state kinetics emerges. Although solutions to the general steady-state kinetics problem exist, they are opaque and have been of limited help to experimentalists. Here we reformulate the steady-state kinetics of enzyme inhibition in terms of new parameters. These allow for assessment of ambiguities of interpretation due to kinetic scheme degeneracy and provide an intuitively simple way to analyze experimental data. We illustrate the method by concrete examples of how to assess scheme degeneracy and obtain experimental estimates of all available rate and equilibrium constants. We suggest simple, complementary experiments that can remove ambiguities and greatly enhance the accuracy of parameter estimation.
    Biochimie 06/2011; 93(9):1623-9. · 3.14 Impact Factor
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    ABSTRACT: Direct measurements of the rates of dissociation of dipeptidyl-tRNA from the ribosome show that hyperaccurate SmP and SmD ribosomes have unstable A-site binding of peptidyl-tRNA, while P-site binding is extremely stable in relation to the wild type. Error-prone Ram ribosomes, on the other hand, have stable A-site and unstable P-site binding of peptidyl-tRNA. At least for these mutant ribosomes, we conclude that stabilization of peptidyl-tRNA in one site destabilizes binding in the other. Elongation factor Tu (EF-Tu) undergoes a dramatic structural transition from its GDP-bound form to its active GTP-bound form, in which it binds aa-tRNA (aminoacyl-tRNA) in ternary complex. The effects of substitution mutations at three sites in domain I of EF-Tu, Gln124, Leu120, and Tyr160, all of which point into the domain I-domain III interface in both the GTP and GDP conformations of EF-Tu, were examined. Mutations at each position cause large reductions in aa-tRNA binding. An attractive possibility is that the mutations alter the domain I-domain III interface such that the switching of EF-Tu between different conformations is altered, decreasing the probability of aa-tRNA binding. We have previously found that two GTPs are hydrolyzed per peptide bond on EF-Tu, the implication being that two molecules of EF-Tu may interact on the ribosome to catalyze the binding of a single aa-tRNA to the A-site. More recently we found that ribosomes programmed with mRNA constructs other than poly(U), including the sequence AUGUUUACG, invariably use two GTPs per peptide bond in EF-Tu function. Other experiments measuring the protection of aa-tRNA from deacylation or from RNAse A attack show that protection requires two molecules of EF-Tu, suggesting an extended ternary complex. To remove remaining ambiguities in the interpretion of these experiments, we are making direct molecular weight determinations with neutron scattering and sedimentation-diffusion techniques.
    Biochemistry and Cell Biology 01/2011; 73(11-12):1049-54. · 2.92 Impact Factor
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    ABSTRACT: We previously identified mutations in the GTPase initiation factor 2 (IF2), located outside its tRNA-binding domain, compensating strongly (A-type) or weakly (B-type) for initiator tRNA formylation deficiency. We show here that rapid docking of 30S with 50S subunits in initiation of translation depends on switching 30S subunit-bound IF2 from its inactive to active form. Activation of wild-type IF2 requires GTP and formylated initiator tRNA (fMet-tRNA(i)). In contrast, extensive activation of A-type IF2 occurs with only GTP or with GDP and fMet-tRNA(i), implying a passive role for initiator tRNA as activator of IF2 in subunit docking. The theory of conditional switching of GTPases quantitatively accounts for all our experimental data. We find that GTP, GDP, fMet-tRNA(i) and A-type mutations multiplicatively increase the equilibrium ratio, K, between active and inactive forms of IF2 from a value of 4 × 10(-4) for wild-type apo-IF2 by factors of 300, 8, 80 and 20, respectively. Functional characterization of the A-type mutations provides keys to structural interpretation of conditional switching of IF2 and other multidomain GTPases.
    The EMBO Journal 01/2011; 30(2):289-301. · 9.82 Impact Factor
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    ABSTRACT: We studied the pH-dependence of ribosome catalyzed peptidyl transfer from fMet-tRNA(fMet) to the aa-tRNAs Phe-tRNA(Phe), Ala-tRNA(Ala), Gly-tRNA(Gly), Pro-tRNA(Pro), Asn-tRNA(Asn), and Ile-tRNA(Ile), selected to cover a large range of intrinsic pK(a)-values for the α-amino group of their amino acids. The peptidyl transfer rates were different at pH 7.5 and displayed different pH-dependence, quantified as the pH-value, pK(a)(obs), at which the rate was half maximal. The pK(a)(obs)-values were downshifted relative to the intrinsic pK(a)-value of aa-tRNAs in bulk solution. Gly-tRNA(Gly) had the smallest downshift, while Ile-tRNA(Ile) and Ala-tRNA(Ala) had the largest downshifts. These downshifts correlate strongly with molecular dynamics (MD) estimates of the downshifts in pK(a)-values of these aa-tRNAs upon A-site binding. Our data show the chemistry of peptide bond formation to be rate limiting for peptidyl transfer at pH 7.5 in the Gly and Pro cases and indicate rate limiting chemistry for all six aa-tRNAs.
    Proceedings of the National Academy of Sciences 01/2011; 108(1):79-84. · 9.81 Impact Factor
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    ABSTRACT: In addition to their natural substrates GDP and GTP, the bacterial translational GTPases initiation factor (IF) 2 and elongation factor G (EF-G) interact with the alarmone molecule guanosine tetraphosphate (ppGpp), which leads to GTPase inhibition. We have used isothermal titration calorimetry to determine the affinities of ppGpp for IF2 and EF-G at a temperature interval of 5-25 °C. We find that ppGpp has a higher affinity for IF2 than for EF-G (1.7-2.8 μM K(d)versus 9.1-13.9 μM K(d) at 10-25 °C), suggesting that during stringent response in vivo, IF2 is more responsive to ppGpp than to EF-G. We investigated the effects of ppGpp, GDP, and GTP on IF2 interactions with fMet-tRNA(fMet) demonstrating that IF2 binds to initiator tRNA with submicromolar K(d) and that affinity is altered by the G nucleotides only slightly. This--in conjunction with earlier reports on IF2 interactions with fMet-tRNA(fMet) in the context of the 30S initiation complex, where ppGpp was suggested to strongly inhibit fMet-tRNA(fMet) binding and GTP was suggested to strongly promote fMet-tRNA(fMet) binding--sheds new light on the mechanisms of the G-nucleotide-regulated fMet-tRNA(fMet) selection.
    Journal of Molecular Biology 10/2010; 402(5):838-46. · 3.91 Impact Factor

Publication Stats

8k Citations
1,507.99 Total Impact Points


  • 1982–2014
    • Uppsala University
      • • Department of Cell and Molecular Biology
      • • Department of Pharmaceutical Biosciences
      Uppsala, Uppsala, Sweden
  • 2003–2013
    • Howard Hughes Medical Institute
      Ashburn, Virginia, United States
    • State University of New York
      New York City, New York, United States
    • University of Southern Denmark
      • Department of Biochemistry and Molecular Biology
      Copenhagen, Capital Region, Denmark
  • 2009
    • National Science Foundation
      Arlington, Virginia, United States
    • University of Illinois, Urbana-Champaign
      Urbana, Illinois, United States
  • 2002–2009
    • University of Tartu
      • • Institute of Technology
      • • Institute of Molecular and Cell Biology
      Tartu, Tartumaa, Estonia
  • 1995–2009
    • University of Texas at Dallas
      • • Department of Molecular and Cell Biology
      • • Molecular Biology
      Richardson, Texas, United States
  • 2008
    • Columbia University
      • Department of Biochemistry and Molecular Biophysics
      New York City, NY, United States
  • 1971–2007
    • Karolinska Institutet
      Solna, Stockholm, Sweden
  • 2005
    • University at Albany, The State University of New York
      New York City, New York, United States
    • IT University of Copenhagen
      København, Capital Region, Denmark
    • University of Washington Seattle
      • Department of Genome Sciences
      Seattle, WA, United States
  • 2002–2004
    • Institute of Physical and Chemical Biology
      Lutetia Parisorum, Île-de-France, France
  • 2001
    • Universität Basel
      Bâle, Basel-City, Switzerland
    • Princeton University
      • Department of Molecular Biology
      Princeton, New Jersey, United States
  • 2000
    • The University of Tokyo
      Tōkyō, Japan
  • 1997
    • Washington State University
      Pullman, Washington, United States
  • 1984–1986
    • Uppsala Monitoring Centre
      Uppsala, Uppsala, Sweden