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There are many problems in biochemistry that are difficult to study experimentally. Simulation methods are appealing due to direct availability of atomic coordinates as a function of time. However, direct molecular simulations are challenged by the size of systems and the time scales needed to describe relevant motions. In theory, enhanced sampling algorithms can help to overcome some of the limitations of molecular simulations. Here, we discuss a problem in biochemistry that offers a significant challenge for enhanced sampling methods and that could, therefore, serve as a benchmark for comparing approaches that use machine learning to find suitable collective variables. More in particular, we study the transitions LacI undergoes upon moving between being non-specifically and specifically bound to DNA. It is found that many degrees of freedom change during this transition and that the transition does not occur reversibly in simulations if only a subset of these degrees of freedom are biased. We also explain why this problem is so important to biologists and the transformative impact that a simulation of it would have on the understanding of DNA regulation.

In the past decades, advances in microscopy have made it possible to study the dynamics of individual biomolecules in vitro and resolve intramolecular kinetics that would otherwise be hidden in ensemble averages. More recently, single-molecule methods have been used to image, localize and track individually labeled macromolecules in the cytoplasm of living cells, allowing investigations of intermolecular kinetics under physiologically relevant conditions. In this review, we illuminate the particular advantages of single-molecule techniques when studying kinetics in living cells and discuss solutions to specific challenges associated with these methods., Comment: Accepted for publication in Annual Review of Biochemistry

Series of short contributions that are part of Nobel Symposium 162 - Microfluidics arXiv:1712.08369., Comment: Nobel Symposium 162, Stockholm, Sweden, 2017 arXiv:1712.08369v1 Report-no: Nobel162/2017/00

The Nobel Foundation's Symposium programme was initiated in 1965 and since then over 160 symposia have taken place. With the Nobel symposium summarized in this proceedings volume, we had the ambition to cover the past, current and future developments of microfluidics; a highly challenging task as there are many excellent researchers in this area and only thirty slots in the program. We tried to cover the early breakthrough contributions to the field, important developments over the years and applications of microfluidics that now propagate in vastly different directions both as industrial components or processes and as tools and methods supporting fundamental research. To give the entire research community an opportunity to sample the science presented at the symposium we have compiled a symposium volume that reflects the major messages conveyed by our invited speakers. We are deeply grateful to the effort that our participants put into writing their lecture notes/abstracts., Comment: Nobel Symposium 162, Stockholm, Sweden

We introduce MINFLUX, a concept for localizing photon emitters in space. By probing the emitter with a local intensity minimum of excitation light, MINFLUX minimizes the fluorescence photons needed for high localization precision. A 22-fold reduction of photon detections over that required in popular centroid-localization is demonstrated. In superresolution microscopy, MINFLUX attained ~1 nm precision, resolving molecules only 6 nm apart. Tracking single fluorescent proteins by MINFLUX increased the temporal resolution and the localizations per trace by 100-fold, as demonstrated with diffusing 30S ribosomal subunits in living E. coli. Since conceptual limits have not been reached, we expect this localization modality to break new ground for observing the dynamics, distribution, and structure of macromolecules in living cells and beyond., Comment: Equal contributions: Francisco Balzarotti, Yvan Eilers, Klaus C. Gwosch Correspondence to: shell@gwdg.de; Phone +495512012500 Pages: 17 (main paper), Figures: 5

It is not known how a cell manages to find a specific DNA sequence sufficiently fast to repair a broken chromosome through homologous recombination. I propose that the solution is based on a parallelized search implemented by freely diffusing molecules programmed with sequences corresponding to those flanking the break site., Comment: 2 pages

Point-wise localization of individual fluorophores is a critical step in super-resolution microscopy and single particle tracking. Although the methods are limited by the accuracy in localizing individual flourophores, this point-wise accuracy has so far only been estimated by theoretical best case approximations, disregarding for example motional blur, out of focus broadening of the point spread function and time varying changes in the fluorescence background. Here, we show that pointwise localization uncertainty can be accurately estimated directly from imaging data using a Laplace approximation constrained by simple mircoscope properties. We further demonstrate that the estimated localization uncertainty can be used to improve downstream quantitative analysis, such as estimation of diffusion constants and detection of changes in molecular motion patterns. Most importantly, the accuracy 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 modeling the fluorophores' movement and accounting for their point-wise localization uncertainty., Comment: Accompanying software available at https://github.com/bmelinden/uncertainSPT

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 recent versions of Mac OS, Windows, and Ubuntu Linux can be downloaded from http://smeagol.sourceforge.net., Comment: v2: 14 pages including supplementary text. Pre-copyedited, author-produced version of an application note published in Bioinformatics following peer review. The version of record, and additional supplementary material is available online at: https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/btw109

Isogenic Escherichia coli growing exponentially in a constant environment display large variation in growth-rates, division-sizes and generation-times. It is unclear how these seemingly random cell cycles can be reconciled with the precise regulation required under conditions where the generation time is shorter than the time to replicate the genome. Here we use single molecule microscopy to map the location of the replication machinery to the division cycle of individual cells. We find that the cell-to-cell variation in growth rate is sufficient to explain the corresponding variation in cell size and division timing assuming a simple mechanistic model. In the model, initiation of chromosome replication is triggered at a fixed volume per origin region, and associated with each initiation event is a division event at a growth rate dependent time later. The result implies that cell division in E. coli has no other regulation beyond what is needed to initiate DNA replication at the right volume.

The ribosome is one of the most important macromolecular complexes in a living cell. We have tracked individual 30S ribosomal subunits in exponentially growing E. coli cells using three-dimensional single-particle tracking, where the z-position is estimated using astigmatism. The 30S subunits are stochiometrically labeled with S2-mEos2 by replacing the rpsB gene in the E. coli chromosome by rpsB-mEos2. The spatial precision in tracking is 20 nm in xy and 70 nm in z. The average trajectory consists of 4 steps corresponding to 80 ms. The trajectories are excluded from parts of the cell, consistent with nucleoid exclusion, and display isotropic diffusion with nearly identical apparent diffusion coefficients (0.05 +/- 0.01 um^2/s) in x, y and z. The tracking data fits well to a two-state diffusion model where 46% of the molecules are diffusing at 0.02 um^2/s and 54% are diffusing at 0.14 um^2/s. These states could correspond to translating 70S ribosomes and free 30S subunits., Comment: 5 pages, 5 figures

We combine stroboscopic laser excitation with stochastic photoactivation and super-resolution fluorescence imaging. This makes it possible to record hundreds of diffusion trajectories of small protein molecules in single bacterial cells with millisecond time resolution and sub-diffraction limited spatial precision. We conclude that the small protein mEos2 exhibits normal diffusion in the bacterial cytoplasm with a diffusion coefficient of 13.1 -+ 1.2 \mu m^2 s^(-1). This investigation lays the groundwork for studying single-molecule binding and dissociation events for a wide range of intracellular processes.

The reaction-diffusion master equation (RDME) is commonly used to model processes where both the spatial and stochastic nature of chemical reactions need to be considered. We show that the RDME in many cases is inconsistent with a microscopic description of diffusion limited chemical reactions and that this will result in unphysical results. We describe how the inconsistency can be reconciled if the association and dissociation rates used in the RDME are derived from the underlying microscopic description. These rate constants will however necessarily depend on the spatial discretization. At fine spatial resolution the rates approach the microscopic rate constants defined at the reaction radius. At low resolution the rates converge to the macroscopic diffusion limited rate constants in 3D, whereas there is no limiting value in 2D. Our results make it possible to develop spatially discretized reaction-diffusion models that correspond to a well-defined microscopic description. We show that this is critical for a correct description of 2D systems and systems that require high spatial resolution in 3D.

The model of facilitated diffusion describes how DNA-binding proteins, such as transcription factors (TFs), find their chromosomal targets by combining 3D diffusion through the cytoplasm and 1D sliding along nonspecific DNA sequences. The redundant 1D diffusion near the specific binding site extends the target size and facilitates target location. While this model successfully predicts the kinetics measured in test tubes, it has not been extended to account for the highly crowded environment in living cells. Here, we investigate the effect of other DNA-binding proteins that partially occupy the bacterial chromosome. We show how they would slow down the search process, mainly through restricted sliding near the target. This implies that increasing the overall DNA-binding protein concentration would have a marginal effect in reducing the search time, because any additional proteins would restrict the search process for each other. While the presence of other proteins prevents sliding from the flanking DNA, DNA looping provides an alternative path to transfer from neighboring sites to the target efficiently. We propose that, when looping is faster than the initial search process, the auxiliary binding sites further extend the effective target region and therefore facilitate the target location., Comment: 8 pages, 6 figures