Electrochemically enabled oxidative aromatization of pyrazolines.

Pyrazoles are a very important structural motif widely found in pharmaceuticals and agrochemicals. An electrochemically enabled approach for the sustainable synthesis of pyrazoles via oxidative aromatization of pyrazolines is presented. Inexpensive sodium chloride is employed in a dual role as a redox mediator and supporting electrolyte in a biphasic system (aqueous/organic). The method is applicable to a broad scope and can be conducted in the simplest electrolysis set-up using carbon-based electrodes. Hence, the method allows for simple work-up strategies such as extraction and crystallization, which enables application of this green synthetic route on a technically relevant scale. This is underlined by demonstration of a multi-gram scale electrolysis without loss in yield.

Electrochemical Synthesis of Pyrazolines and Pyrazoles via [3+2] Dipolar Cycloaddition.

Pyrazolines and pyrazoles are common and important motifs of pharmaceutical agents and agrochemicals. Herein, the first electrochemical approach for their direct synthesis from easily accessible hydrazones and dipolarophiles up to decagram scale is presented. The application of a biphasic system (aqueous/organic) even allows for the conversion of highly sensitive alkenes, wherein inexpensive sodium iodide is employed in a dual role as supporting electrolyte and mediator. In addition, mechanistic insight into the reaction is given by the isolation of key step intermediates. The relevance of the presented reaction is underlined by the synthesis of commercial herbicide safener mefenpyr-diethyl in good yields.

Author Correction: tRNA tracking for direct measurements of protein synthesis kinetics in live cells.

In the version of this article originally published, the values on the y axis of Fig. 6d were incorrect. They should be 0.00, 0.02, 0.04, 0.06 and 0.08 instead of the previous 0.00, 0.04, 0.08 and 0.12. The error has been corrected in the HTML and PDF versions of this paper.

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.

Curvature sensing by cardiolipin in simulated buckled membranes.

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.

Variational Algorithms for Analyzing Noisy Multistate Diffusion Trajectories.

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.

Psychosocial Factors Impacting Workplace Injury Rehabilitation: Evaluation of a Concise Screening Tool.

Purpose To determine whether the delayed recovery often observed in simple musculoskeletal injuries occurring at work is related to poor workplace and home social support. Method A four question psychosocial screening tool called the "How are you coping gauge?" (HCG) was developed. This tool was implemented as part of the initial assessment for all new musculoskeletal workplace injuries. Participants were excluded if they did not meet the strict criteria used to classify a musculoskeletal injury as simple. The HCG score was then compared to the participant's number of days until return to full capacity (DTFC). It was hypothesised that those workers indicating a poorer level of workplace and home support would take longer time to return to full capacity. Results A sample of 254 participants (316 excluded) were included in analysis. Significant correlation (p < 0.001) was observed between HCG scores for self-reported work and home support and DTFC thereby confirming the hypothesis. Path analysis found workplace support to be a significant moderate-to-strong predictor of DTFC (-0.46). Conclusion A correlation was observed between delayed workplace injury recovery and poor perceived workplace social support. The HCG may be an effective tool for identifying these factors in musculoskeletal workplace injuries of a minor pathophysiological nature. There may be merit in tailoring injury rehabilitation towards addressing psychosocial factors early in the injury recovery process to assist with a more expedient return to full work capacity following simple acute musculoskeletal injury.

Simulated single molecule microscopy with SMeagol.

UNLABELLED: 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.

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.

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.

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.

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.

Recognition of two distinct elements in the RNA substrate by the RNA-binding domain of the T. thermophilus DEAD box helicase Hera.

DEAD box helicases catalyze the ATP-dependent destabilization of RNA duplexes. Whereas duplex separation is mediated by the helicase core shared by all members of the family, flanking domains often contribute to binding of the RNA substrate. The Thermus thermophilus DEAD-box helicase Hera (for "heat-resistant RNA-binding ATPase") contains a C-terminal RNA-binding domain (RBD). We have analyzed RNA binding to the Hera RBD by a combination of mutational analyses, nuclear magnetic resonance and X-ray crystallography, and identify residues on helix α1 and the C-terminus as the main determinants for high-affinity RNA binding. A crystal structure of the RBD in complex with a single-stranded RNA resolves the RNA-protein interactions in the RBD core region around helix α1. Differences in RNA binding to the Hera RBD and to the structurally similar RBD of the Bacillus subtilis DEAD box helicase YxiN illustrate the versatility of RNA recognition motifs as RNA-binding platforms. Comparison of chemical shift perturbation patterns elicited by different RNAs, and the effect of sequence changes in the RNA on binding and unwinding show that the RBD binds a single-stranded RNA region at the core and simultaneously contacts double-stranded RNA through its C-terminal tail. The helicase core then unwinds an adjacent RNA duplex. Overall, the mode of RNA binding by Hera is consistent with a possible function as a general RNA chaperone.

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 [Formula: see text] 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.

Matching Soulmates.

We study iterated matching of soulmates [IMS], a recursive process of forming coalitions that are mutually preferred by members to any other coalition containing individuals as yet unmatched by this process. If all players can be matched this way, preferences are IMS-complete. A mechanism is a soulmate mechanism if it allows the formation of all soulmate coalitions. Our model follows Banerjee, Konishi and Sönmez (2001), except reported preferences are strategic variables. We investigate the incentive and stability properties of soulmate mechanisms. In contrast to prior literature, we do not impose conditions that ensure IMS-completeness. A fundamental result is that, (1) any group of players who could change their reported preferences and mutually benefit does not contain any players who were matched as soulmates and reported their preferences truthfully. As corollaries, (2) for any IMS-complete profile, soulmate mechanisms have a truthful strong Nash equilibrium, and (3) as long as all players matched as soulmates report their preferences truthfully, there is no incentive for any to deviate. Moreover, (4) soulmate coalitions are invariant core coalitions - that is, any soulmate coalition will be a coalition in every outcome in the core. To accompany our theoretical results, we present real-world data analysis and simulations that highlight the prevalence of situations in which many, but not all, players can be matched as soulmates. In an Appendix we relate IMS to other well-known coalition formation processes.

The putative RNase P motif in the DEAD box helicase Hera is dispensable for efficient interaction with RNA and helicase activity.

DEAD box helicases use the energy of ATP hydrolysis to remodel RNA structures or RNA/protein complexes. They share a common helicase core with conserved signature motifs, and additional domains may confer substrate specificity. Identification of a specific substrate is crucial towards understanding the physiological role of a helicase. RNA binding and ATPase stimulation are necessary, but not sufficient criteria for a bona fide helicase substrate. Here, we report single molecule FRET experiments that identify fragments of the 23S rRNA comprising hairpin 92 and RNase P RNA as substrates for the Thermus thermophilus DEAD box helicase Hera. Both substrates induce a switch to the closed conformation of the helicase core and stimulate the intrinsic ATPase activity of Hera. Binding of these RNAs is mediated by the Hera C-terminal domain, but does not require a previously proposed putative RNase P motif within this domain. ATP-dependent unwinding of a short helix adjacent to hairpin 92 in the ribosomal RNA suggests a specific role for Hera in ribosome assembly, analogously to the Escherichia coli and Bacillus subtilis helicases DbpA and YxiN. In addition, the specificity of Hera for RNase P RNA may be required for RNase P RNA folding or RNase P assembly.

Decay times in turnover statistics of single enzymes.

The first passage times for enzymatic turnovers in nonequilibrium steady state display a statistical symmetry property related to nonequilibrium fluctuation theorems, which makes it possible to extract the chemical driving force from single molecule trajectories in nonequilibrium steady state. Below, we show that the number of decay constants needed to describe the first passage time distribution of this system is not equal to the number of states in the first passage problem, as one would generally expect. Instead, the structure of the kinetic mechanism makes half of the decay times vanish identically from the turnover time distribution. The terms that cancel out correspond to the eigenvalues of a certain submatrix of the master equation matrix for the first exit time problem. We discuss how these results make modeling and data analysis easier for such systems, and how the turnovers can be measured.

Computing Curvature Sensitivity of Biomolecules in Membranes by Simulated Buckling.

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.