Martin Lindén

extracting intracellular diffusive states and transition rates from single-molecule tracking data

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.

Sequence dependence of transcription factor-mediated DNA looping

DNA is subject to large deformations in a wide range of biological processes. Two key examples illustrate how such deformations influence the readout of the genetic information: the sequestering of eukaryotic genes by nucleosomes and DNA looping in transcriptional regulation in both prokaryotes and eukaryotes. These kinds of regulatory problems are now becoming amenable to systematic quantitative dissection with a powerful dialogue between theory and experiment. Here, we use a single-molecule experiment in conjunction with a statistical mechanical model to test quantitative predictions for the behavior of DNA looping at short length scales and to determine how DNA sequence affects looping at these lengths. We calculate and measure how such looping depends upon four key biological parameters: the strength of the transcription factor binding sites, the concentration of the transcription factor, and the length and sequence of the DNA loop. Our studies lead to the surprising insight that sequences that are thought to be especially favorable for nucleosome formation because of high flexibility lead to no systematically detectable effect of sequence on looping, and begin to provide a picture of the distinctions between the short length scale mechanics of nucleosome formation and looping.

Entropic Tension in Crowded Membranes

Unlike their model membrane counterparts, biological membranes are richly decorated with a heterogeneous assembly of membrane proteins. These proteins are so tightly packed that their excluded area interactions can alter the free energy landscape controlling the conformational transitions suffered by such proteins. For membrane channels, this effect can alter the critical membrane tension at which they undergo a transition from a closed to an open state, and therefore influence protein function in vivo. Despite their obvious importance, crowding phenomena in membranes are much less well studied than in the cytoplasm. Using statistical mechanics results for hard disk liquids, we show that crowding induces an entropic tension in the membrane, which influences transitions that alter the projected area and circumference of a membrane protein. As a specific case study in this effect, we consider the impact of crowding on the gating properties of bacterial mechanosensitive membrane channels, which are thought to confer osmoprotection when these cells are subjected to osmotic shock. We find that crowding can alter the gating energies by more than in physiological conditions, a substantial fraction of the total gating energies in some cases. Given the ubiquity of membrane crowding, the nonspecific nature of excluded volume interactions, and the fact that the function of many membrane proteins involve significant conformational changes, this specific case study highlights a general aspect in the function of membrane proteins.

Multiple LacI-mediated loops revealed by Bayesian statistics and tethered particle motion

The bacterial transcription factor LacI loops DNA by binding to two separate locations on the DNA simultaneously. Despite being one of the best-studied model systems for transcriptional regulation, the number and conformations of loop structures accessible to LacI remain unclear, though the importance of multiple coexisting loops has been implicated in interactions between LacI and other cellular regulators of gene expression. To probe this issue, we have developed a new analysis method for tethered particle motion, a versatile and commonly used in vitro single-molecule technique. Our method, vbTPM, performs variational Bayesian inference in hidden Markov models. It learns the number of distinct states (i.e. DNA–protein conformations) directly from tethered particle motion data with better resolution than existing methods, while easily correcting for common experimental artifacts. Studying short (roughly 100 bp) LacI-mediated loops, we provide evidence for three distinct loop structures, more than previously reported in single-molecule studies. Moreover, our results confirm that changes in LacI conformation and DNA-binding topology both contribute to the repertoire of LacI-mediated loops formed in vitro, and provide qualitatively new input for models of looping and transcriptional regulation. We expect vbTPM to be broadly useful for probing complex protein–nucleic acid interactions.

Anisotropic Membrane Curvature Sensing by Amphipathic Peptides

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.

Pointwise error estimates in localization microscopy

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.

Simulated single molecule microscopy with SMeagol

Abstract 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. Contact: johan.elf@icm.uu.se Supplementary information: Supplementary data are available at Bioinformatics online.

Membrane remodeling capacity of a vesicle‐inducing glycosyltransferase

Intracellular vesicles are abundant in eukaryotic cells but absent in the Gram‐negative bacterium Escherichia coli. However, strong overexpression of a monotopic glycolipid‐synthesizing enzyme, monoglucosyldiacylglycerol synthase from Acholeplasma laidlawii (alMGS), leads to massive formation of vesicles in the cytoplasm of E. coli. More importantly, alMGS provides a model system for the regulation of membrane properties by membrane‐bound enzymes, which is critical for maintaining cellular integrity. Both phenomena depend on how alMGS binds to cell membranes, which is not well understood. Here, we carry out a comprehensive investigation of the membrane binding of alMGS by combining bioinformatics methods with extensive biochemical studies, structural modeling and molecular dynamics simulations. We find that alMGS binds to the membrane in a fairly upright manner, mainly by residues in the N‐terminal domain, and in a way that induces local enrichment of anionic lipids and a local curvature deformation. Furthermore, several alMGS variants resulting from substitution of residues in the membrane anchoring segment are still able to generate vesicles, regardless of enzymatic activity. These results clarify earlier theories about the driving forces for vesicle formation, and shed new light on the membrane binding properties and enzymatic mechanism of alMGS and related monotopic GT‐B fold glycosyltransferases.

tRNA tracking for direct measurements of protein synthesis kinetics in live cells

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 tRNAPhe that are in perfect agreement with previous indirect estimates, and once fMet-tRNAfMet 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.Combination of single-molecule tracking experiments and machine-learning approaches to monitor diffusional state transitions between ribosome-bound and free tRNAs allows codon resolution measurements of translation kinetics.

Curvature Sensing by a Viral Scission Protein

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.