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Publications (10 of 23) Show all publications
Elias-Wolff, F., Lindén, M., Lyubartsev, A. P. & Brandt, E. G. (2019). Curvature sensing by cardiolipin in simulated buckled membranes. Soft Matter, 15(4), 792-802
Open this publication in new window or tab >>Curvature sensing by cardiolipin in simulated buckled membranes
2019 (English)In: Soft Matter, ISSN 1744-683X, E-ISSN 1744-6848, Vol. 15, no 4, p. 792-802Article in journal (Refereed) Published
Abstract [en]

Cardiolipin is a non-bilayer phospholipid with a unique dimeric structure. It localizes to negative curvature regions in bacteria and is believed to stabilize respiratory chain complexes in the highly curved mitochondrial membrane. Cardiolipin's localization mechanism remains unresolved, because important aspects such as the structural basis and strength for lipid curvature preferences are difficult to determine, partly due to the lack of efficient simulation methods. Here, we report a computational approach to study curvature preferences of cardiolipin by simulated membrane buckling and quantitative modeling. We combine coarse-grained molecular dynamics with simulated buckling to determine the curvature preferences in three-component bilayer membranes with varying concentrations of cardiolipin, and extract curvature-dependent concentrations and lipid acyl chain order parameter profiles. Cardiolipin shows a strong preference for negative curvatures, with a highly asymmetric chain order parameter profile. The concentration profiles are consistent with an elastic model for lipid curvature sensing that relates lipid segregation to local curvature via the material constants of the bilayers. These computations constitute new steps to unravel the molecular mechanism by which cardiolipin senses curvature in lipid membranes, and the method can be generalized to other lipids and membrane components as well.

National Category
Physical Chemistry
Identifiers
urn:nbn:se:uu:diva-377348 (URN)10.1039/c8sm02133c (DOI)000457329700020 ()30644502 (PubMedID)
Funder
Swedish Research CouncilEU, Horizon 2020Swedish Foundation for Strategic Research
Available from: 2019-02-25 Created: 2019-02-25 Last updated: 2019-02-25Bibliographically approved
Lindén, M. (2018). An early peak in ion channel research [Letter to the editor]. Nature Physics, 14(2), 105-105
Open this publication in new window or tab >>An early peak in ion channel research
2018 (English)In: Nature Physics, ISSN 1745-2473, E-ISSN 1745-2481, Vol. 14, no 2, p. 105-105Article in journal, Letter (Other academic) Published
National Category
Atom and Molecular Physics and Optics Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-350198 (URN)10.1038/nphys4347 (DOI)000423846600004 ()
Available from: 2018-05-08 Created: 2018-05-08 Last updated: 2018-05-08Bibliographically approved
Elias-Wolff, F., Lindén, M., Lyubartsev, A. P. & Brandt, E. G. (2018). Computing Curvature Sensitivity of Biomolecules in Membranes by Simulated Buckling. Journal of Chemical Theory and Computation, 14(3), 1643-1655
Open this publication in new window or tab >>Computing Curvature Sensitivity of Biomolecules in Membranes by Simulated Buckling
2018 (English)In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 14, no 3, p. 1643-1655Article in journal (Refereed) Published
Abstract [en]

Membrane curvature sensing, where the binding free energies of membrane-associated molecules depend on the local membrane curvature, is a key factor to modulate and maintain the shape and organization of cell membranes. However, the microscopic mechanisms are not well understood, partly due to absence of efficient simulation methods. Here, we describe a method to compute the curvature dependence of the binding free energy of a membrane associated probe molecule that interacts with a buckled membrane, which has been created by lateral compression of a flat bilayer patch. This buckling approach samples a wide range of curvatures in a single simulation, and anisotropic effects can be extracted from the orientation statistics. We develop an efficient and robust algorithm to extract the motion of the probe along the buckled membrane surface, and evaluate its numerical properties by extensive sampling of three coarse-grained model systems: local lipid density in a curved environment for single-component bilayers, curvature preferences of individual lipids in two-component membranes, and curvature sensing by a homotrimeric transmembrane protein. The method can be used to complement experimental data from curvature partition assays and provides additional insight into mesoscopic theories and molecular mechanisms for curvature sensing.

National Category
Physical Chemistry Biophysics
Identifiers
urn:nbn:se:uu:diva-351091 (URN)10.1021/acs.jctc.7b00878 (DOI)000427661400043 ()29350922 (PubMedID)
Funder
Swedish Research CouncilEU, Horizon 2020
Available from: 2018-05-18 Created: 2018-05-18 Last updated: 2018-05-18Bibliographically approved
Volkov, I., Lindén, M., Aguirre, J., Ieong, K.-W., Metelev, M., Elf, J. & Johansson, M. (2018). tRNA tracking for direct measurements of protein synthesis kinetics in live cells. Nature Chemical Biology, 14(6), 618-626
Open this publication in new window or tab >>tRNA tracking for direct measurements of protein synthesis kinetics in live cells
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2018 (English)In: Nature Chemical Biology, ISSN 1552-4450, E-ISSN 1552-4469, Vol. 14, no 6, p. 618-626Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
NATURE PUBLISHING GROUP, 2018
National Category
Biochemistry and Molecular Biology Cell and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-359663 (URN)10.1038/s41589-018-0063-y (DOI)000435445100019 ()29769736 (PubMedID)
Funder
Swedish Research Council, 2015-04111EU, European Research Council, ERC-2013-CoG 616047 SMILEKnut and Alice Wallenberg FoundationWenner-Gren FoundationsCarl Tryggers foundation , CTS 15:243
Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-09-05Bibliographically approved
Lindén, M. & Elf, J. (2018). Variational Algorithms for Analyzing Noisy Multistate Diffusion Trajectories. Paper presented at Biophysical-Society Thematic Meeting on Single-Cell Biophysics - Mearurement, Modulation, and Modeling, JUN, 2017, Natl Taiwan Univ, Acad Sinica, Inst Atom & Mol Sci, Taipei, TAIWAN. Biophysical Journal, 115(2), 276-282
Open this publication in new window or tab >>Variational Algorithms for Analyzing Noisy Multistate Diffusion Trajectories
2018 (English)In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 115, no 2, p. 276-282Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
CELL PRESS, 2018
National Category
Biophysics
Identifiers
urn:nbn:se:uu:diva-361691 (URN)10.1016/j.bpj.2018.05.027 (DOI)000438958800014 ()29937205 (PubMedID)
Conference
Biophysical-Society Thematic Meeting on Single-Cell Biophysics - Mearurement, Modulation, and Modeling, JUN, 2017, Natl Taiwan Univ, Acad Sinica, Inst Atom & Mol Sci, Taipei, TAIWAN
Funder
Knut and Alice Wallenberg FoundationEU, European Research Council, ERC-2013-CoG 616047 SMILE
Available from: 2018-10-03 Created: 2018-10-03 Last updated: 2018-10-03Bibliographically approved
Lindén, M., Curic, V., Amselem, E. & Elf, J. (2017). Pointwise error estimates in localization microscopy. Nature Communications, 8, Article ID 15115.
Open this publication in new window or tab >>Pointwise error estimates in localization microscopy
2017 (English)In: Nature Communications, ISSN 2041-1723, E-ISSN 2041-1723, Vol. 8, article id 15115Article in journal (Refereed) Published
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.

Place, publisher, year, edition, pages
Nature Publishing Group, 2017
National Category
Cell and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-322671 (URN)10.1038/ncomms15115 (DOI)000400487500002 ()28466844 (PubMedID)
Available from: 2017-05-29 Created: 2017-05-29 Last updated: 2018-01-13Bibliographically approved
Gomez-Llobregat, J., Elias-Wolff, F. & Lindén, M. (2016). Anisotropic Membrane Curvature Sensing by Amphipathic Peptides. Biophysical Journal, 110(1), 197-204
Open this publication in new window or tab >>Anisotropic Membrane Curvature Sensing by Amphipathic Peptides
2016 (English)In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 110, no 1, p. 197-204Article in journal (Refereed) Published
Abstract [en]

Many proteins and peptides have an intrinsic capacity to sense and induce membrane curvature, and play crucial roles for organizing and remodeling cell membranes. However, the molecular driving forces behind these processes are not well understood. Here, we describe an approach to study curvature sensing by simulating the interactions of single molecules with a buckled lipid bilayer. We analyze three amphipathic antimicrobial peptides, a class of membrane-associated molecules that specifically target and destabilize bacterial membranes, and find qualitatively different sensing characteristics that would be difficult to resolve with other methods. Our findings provide evidence for direction-dependent curvature sensing mechanisms in amphipathic peptides and challenge existing theories of hydrophobic insertion. The buckling approach is generally applicable to a wide range of curvature-sensing molecules, and our results provide strong motivation to develop new experimental methods to track position and orientation of membrane proteins.

National Category
Biophysics
Identifiers
urn:nbn:se:uu:diva-275546 (URN)10.1016/j.bpj.2015.11.3512 (DOI)000367783900012 ()26745422 (PubMedID)
Funder
Wenner-Gren FoundationsSwedish Foundation for Strategic Research Swedish National Infrastructure for Computing (SNIC), SNIC 2014/1-236
Available from: 2016-02-04 Created: 2016-02-04 Last updated: 2017-11-30
Martyna, A., Gomez-Llobregat, J., Lindén, M. & Rossman, J. S. (2016). Curvature Sensing by a Viral Scission Protein. Biochemistry, 55(25), 3493-3496
Open this publication in new window or tab >>Curvature Sensing by a Viral Scission Protein
2016 (English)In: Biochemistry, ISSN 0006-2960, E-ISSN 1520-4995, Vol. 55, no 25, p. 3493-3496Article in journal (Refereed) Published
Abstract [en]

Membrane scission is the final step in all budding processes wherein a membrane neck is sufficiently constricted so as to allow for fission and the release of the budded particle. For influenza viruses, membrane scission is mediated by an amphipathic helix (AH) domain in the viral M2 protein. While it is known that the M2AH alters membrane curvature, it is not known how the protein is localized to the center neck of budding virions where it would be able to cause membrane scission. Here, we use molecular dynamics simulations on buckled lipid bilayers to show that the M2AH senses membrane curvature and preferentially localizes to regions of high membrane curvature, comparable to that seen at the center neck of budding influenza viruses. These results were then validated using in vitro binding assays to show that the M2AH senses membrane curvature by detecting lipid packing defects in the membrane. Our results show that the M2AH senses membrane curvature and suggest that the AH domain may localize the protein at the viral neck where it can then mediate membrane scission and the release of budding viruses.

National Category
Biochemistry and Molecular Biology
Identifiers
urn:nbn:se:uu:diva-300063 (URN)10.1021/acs.biochem.6b00539 (DOI)000378973500001 ()27299375 (PubMedID)
Funder
EU, FP7, Seventh Framework Programme, FP7-PEOPLE-2012-CIG: 333955Wenner-Gren FoundationsSwedish Foundation for Strategic Research
Available from: 2016-08-02 Created: 2016-08-02 Last updated: 2017-11-28Bibliographically approved
Volkov, I., Aguirre, J., Lindén, M., Elf, J. & Johansson, M. (2016). In Vivo Measurements of Protein Synthesis Kinetics using Single-Molecule Tracking of E.Coli tRNAS. Paper presented at 60th Annual Meeting of the Biophysical-Society, FEB 27-MAR 02, 2016, Los Angeles, CA. Biophysical Journal, 110(3), 351A-351A
Open this publication in new window or tab >>In Vivo Measurements of Protein Synthesis Kinetics using Single-Molecule Tracking of E.Coli tRNAS
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2016 (English)In: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 110, no 3, p. 351A-351AArticle in journal, Meeting abstract (Other academic) Published
National Category
Biophysics
Identifiers
urn:nbn:se:uu:diva-299291 (URN)000375142200202 ()
Conference
60th Annual Meeting of the Biophysical-Society, FEB 27-MAR 02, 2016, Los Angeles, CA
Available from: 2016-07-18 Created: 2016-07-18 Last updated: 2017-11-28Bibliographically approved
Lindén, M., Ćurić, V., Boucharin, A., Fange, D. & Elf, J. (2016). Simulated single molecule microscopy with SMeagol. Bioinformatics, 32(15), 2394-2395
Open this publication in new window or tab >>Simulated single molecule microscopy with SMeagol
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2016 (English)In: Bioinformatics, ISSN 1367-4803, E-ISSN 1367-4811, Vol. 32, no 15, p. 2394-2395Article in journal (Refereed) Published
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.

Keywords
single particle tracking, microscopy, simulations
National Category
Biophysics
Research subject
Biology; Physics with specialization in Biophysics
Identifiers
urn:nbn:se:uu:diva-282965 (URN)10.1093/bioinformatics/btw109 (DOI)000383184500030 ()27153711 (PubMedID)
Funder
eSSENCE - An eScience CollaborationEU, European Research Council, 616047Swedish Research CouncilKnut and Alice Wallenberg FoundationSwedish Foundation for Strategic Research
Available from: 2016-04-08 Created: 2016-04-08 Last updated: 2017-11-30Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4200-0191

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