Chemical diversity in a metal-organic framework revealed by fluorescence lifetime imaging

The presence and variation of chemical functionality and defects in crystalline materials, such as metal–organic frameworks (MOFs), have tremendous impact on their properties. Finding a means of identifying and characterizing this chemical diversity is an important ongoing challenge. This task is complicated by the characteristic problem of bulk measurements only giving a statistical average over an entire sample, leaving uncharacterized any diversity that might exist between crystallites or even within individual crystals. Here we show that by using fluorescence imaging and lifetime analysis, both the spatial arrangement of functionalities and the level of defects within a multivariable MOF crystal can be determined for the bulk as well as for the individual constituent crystals. We apply these methods to UiO-67, to study the incorporation of functional groups and their consequences on the structural features. We believe that the potential of the techniques presented here in uncovering chemical diversity in what is generally assumed to be homogeneous systems can provide a new level of understanding of materials properties

Systematic identification of conserved motif modules in the human genome

<p>Abstract</p> <p>Background</p> <p>The identification of motif modules, groups of multiple motifs frequently occurring in DNA sequences, is one of the most important tasks necessary for annotating the human genome. Current approaches to identifying motif modules are often restricted to searches within promoter regions or rely on multiple genome alignments. However, the promoter regions only account for a limited number of locations where transcription factor binding sites can occur, and multiple genome alignments often cannot align binding sites with their true counterparts because of the short and degenerative nature of these transcription factor binding sites.</p> <p>Results</p> <p>To identify motif modules systematically, we developed a computational method for the entire non-coding regions around human genes that does not rely upon the use of multiple genome alignments. First, we selected orthologous DNA blocks approximately 1-kilobase in length based on discontiguous sequence similarity. Next, we scanned the conserved segments in these blocks using known motifs in the TRANSFAC database. Finally, a frequent pattern mining technique was applied to identify motif modules within these blocks. In total, with a false discovery rate cutoff of 0.05, we predicted 3,161,839 motif modules, 90.8% of which are supported by various forms of functional evidence. Compared with experimental data from 14 ChIP-seq experiments, on average, our methods predicted 69.6% of the ChIP-seq peaks with TFBSs of multiple TFs. Our findings also show that many motif modules have distance preference and order preference among the motifs, which further supports the functionality of these predictions.</p> <p>Conclusions</p> <p>Our work provides a large-scale prediction of motif modules in mammals, which will facilitate the understanding of gene regulation in a systematic way.</p

Signal transduction in a covalent post-assembly modification cascade

Natural reaction cascades control the movement of biomolecules between cellular compartments. Inspired by these systems, we report a synthetic reaction cascade employing post-assembly modification reactions to direct the partitioning of supramolecular complexes between phases. The system is composed of a self-assembled tetrazine-edged FeII8L12 cube and a maleimide-functionalized FeII4L6 tetrahedron. Norbornadiene (NBD) functions as the stimulus that triggers the cascade, beginning with the inverse-electron-demand Diels–Alder reaction of NBD with the tetrazine moieties of the cube. This reaction generates cyclopentadiene as a transient by-product, acting as a relay signal that subsequently undergoes a Diels–Alder reaction with the maleimide-functionalized tetrahedron. Cyclooctyne can selectively inhibit the cascade by outcompeting NBD as the initial trigger. Initiating the cascade with 2-octadecyl NBD leads to selective alkylation of the tetrahedron upon cascade completion. The increased lipophilicity of the C18-tagged tetrahedron drives this complex into a non-polar phase, allowing its isolation from the initially inseparable mixture of complexes

Many-particle Brownian and Langevin Dynamics Simulations with the Brownmove package

<p>Abstract</p> <p>Background</p> <p>Brownian Dynamics (BD) is a coarse-grained implicit-solvent simulation method that is routinely used to investigate binary protein association dynamics, but due to its efficiency in handling large simulation volumes and particle numbers it is well suited to also describe many-protein scenarios as they often occur in biological cells.</p> <p>Results</p> <p>Here we introduce our "brownmove" simulation package which was designed to handle many-particle problems with varying particle numbers and allows for a very flexible definition of rigid and flexible protein and polymer models. Both a Brownian and a Langevin dynamics (LD) propagation scheme can be used and hydrodynamic interactions are treated efficiently with our recently introduced TEA-HI ansatz [Geyer, Winter, JCP 130 (2009) 114905]. With simulations of constrained polymers and flexible models of spherical proteins we demonstrate that it is crucial to include hydrodynamics when multi-bead models are used in BD or LD simulations. Only then both the translational and the rotational diffusion coefficients and the timescales of the internal dynamics can be reproduced correctly. In the third example project we show how constant density boundary conditions [Geyer et al, JCP 120 (2004) 4573] can be used to set up a non-equilibrium simulation of diffusional transport across an array of fixed obstacles. Finally, we demonstrate how the agglomeration dynamics of multiple particles with attractive patches can be analysed conveniently with the help of a dynamic interaction network.</p> <p>Conclusions</p> <p>Combining BD and LD propagation, fast hydrodynamics, a flexible protein model, and interfaces for "open" simulation settings, our freely available "brownmove" simulation package constitutes a new platform for coarse-grained many-particle simulations of biologically relevant diffusion and transport processes.</p

Mechanosensing is critical for axon growth in the developing brain.

During nervous system development, neurons extend axons along well-defined pathways. The current understanding of axon pathfinding is based mainly on chemical signaling. However, growing neurons interact not only chemically but also mechanically with their environment. Here we identify mechanical signals as important regulators of axon pathfinding. In vitro, substrate stiffness determined growth patterns of Xenopus retinal ganglion cell axons. In vivo atomic force microscopy revealed a noticeable pattern of stiffness gradients in the embryonic brain. Retinal ganglion cell axons grew toward softer tissue, which was reproduced in vitro in the absence of chemical gradients. To test the importance of mechanical signals for axon growth in vivo, we altered brain stiffness, blocked mechanotransduction pharmacologically and knocked down the mechanosensitive ion channel piezo1. All treatments resulted in aberrant axonal growth and pathfinding errors, suggesting that local tissue stiffness, read out by mechanosensitive ion channels, is critically involved in instructing neuronal growth in vivo.This work was supported by the German National Academic Foundation (scholarship to D.E.K.), Wellcome Trust and Cambridge Trusts (scholarships to A.J.T.), Winston Churchill Foundation of the United States (scholarship to S.K.F.), Herchel Smith Foundation (Research Studentship to S.K.F.), CNPq 307333/2013-2 (L.d.F.C.), NAP-PRP-USP and FAPESP 11/50761-2 (L.d.F.C.), UK EPSRC BT grant (J.G.), Wellcome Trust WT085314 and the European Research Council 322817 grants (C.E.H.); an Alexander von Humboldt Foundation Feodor Lynen Fellowship (K.F.), UK BBSRC grant BB/M021394/1 (K.F.), the Human Frontier Science Program Young Investigator Grant RGY0074/2013 (K.F.), the UK Medical Research Council Career Development Award G1100312/1 (K.F.) and the Eunice Kennedy Shriver National Institute Of Child Health & Human Development of the National Institutes of Health under Award Number R21HD080585 (K.F.).This is the author accepted manuscript. The final version is available from Nature Publishing Group via https://doi.org/10.1038/nn.439

Determination of Specific Electrocatalytic Sites in the Oxidation of Small Molecules on Crystalline Metal Surfaces

The identification of active sites in electrocatalytic reactions is part of the elucidation of mechanisms of catalyzed reactions on solid surfaces. However, this is not an easy task, even for apparently simple reactions, as we sometimes think the oxidation of adsorbed CO is. For surfaces consisting of non-equivalent sites, the recognition of specific active sites must consider the influence that facets, as is the steps/defect on the surface of the catalyst, cause in its neighbors; one has to consider the electrochemical environment under which the “active sites” lie on the surface, meaning that defects/steps on the surface do not partake in chemistry by themselves. In this paper, we outline the recent efforts in understanding the close relationships between site-specific and the overall rate and/or selectivity of electrocatalytic reactions. We analyze hydrogen adsorption/desorption, and electro-oxidation of CO, methanol, and ammonia. The classical topic of asymmetric electrocatalysis on kinked surfaces is also addressed for glucose electro-oxidation. The article takes into account selected existing data combined with our original works.M.J.S.F. is grateful to PNPD/CAPES (Brazil). J.M.F. thanks the MCINN (FEDER, Spain) project-CTQ-2016-76221-P

How reproducible are surface areas calculated from the BET equation?

Porosity and surface area analysis play a prominent role in modern materials science. At the heart of this sits the Brunauer-Emmett-Teller (BET) theory, which has been a remarkably successful contribution to the field of materials science. The BET method was developed in the 1930s for open surfaces but is now the most widely used metric for the estimation of surface areas of micro- and mesoporous materials. Despite its widespread use, the calculation of BET surface areas causes a spread in reported areas, resulting in reproducibility problems in both academia and industry. To prove this, for this analysis, 18 already-measured raw adsorption isotherms were provided to sixty-one labs, who were asked to calculate the corresponding BET areas. This round-robin exercise resulted in a wide range of values. Here, the reproducibility of BET area determination from identical isotherms is demonstrated to be a largely ignored issue, raising critical concerns over the reliability of reported BET areas. To solve this major issue, a new computational approach to accurately and systematically determine the BET area of nanoporous materials is developed. The software, called "BET surface identification" (BETSI), expands on the well-known Rouquerol criteria and makes an unambiguous BET area assignment possible

Micro-connectomics: probing the organization of neuronal networks at the cellular scale.

Defining the organizational principles of neuronal networks at the cellular scale, or micro-connectomics, is a key challenge of modern neuroscience. In this Review, we focus on graph theoretical parameters of micro-connectome topology, often informed by economical principles that conceptually originated with Ramón y Cajal's conservation laws. First, we summarize results from studies in intact small organisms and in samples from larger nervous systems. We then evaluate the evidence for an economical trade-off between biological cost and functional value in the organization of neuronal networks. Various results suggest that many aspects of neuronal network organization are indeed the outcome of competition between these two fundamental selection pressures.This work was supported by the National Institute of Health Research (NIHR) Cambridge Biomedical Research Centre.This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by the Nature Publishing Group