Controlling neutron orbital angular momentum

Nature 525, 7570 (2015). doi:10.1038/nature15265

Authors: Charles W. Clark, Roman Barankov, Michael G. Huber, Muhammad Arif, David G. Cory & Dmitry A. Pushin

The quantized orbital angular momentum (OAM) of photons offers an additional degree of freedom and topological protection from noise. Photonic OAM states have therefore been exploited in various applications ranging from studies of quantum entanglement and quantum information science to imaging. The OAM states of electron beams have been shown to be similarly useful, for example in rotating nanoparticles and determining the chirality of crystals. However, although neutrons—as massive, penetrating and neutral particles—are important in materials characterization, quantum information and studies of the foundations of quantum mechanics, OAM control of neutrons has yet to be achieved. Here, we demonstrate OAM control of neutrons using macroscopic spiral phase plates that apply a ‘twist’ to an input neutron beam. The twisted neutron beams are analysed with neutron interferometry. Our techniques, applied to spatially incoherent beams, demonstrate both the addition of quantum angular momenta along the direction of propagation, effected by multiple spiral phase plates, and the conservation of topological charge with respect to uniform phase fluctuations. Neutron-based studies of quantum information science, the foundations of quantum mechanics, and scattering and imaging of magnetic, superconducting and chiral materials have until now been limited to three degrees of freedom: spin, path and energy. The optimization of OAM control, leading to well defined values of OAM, would provide an additional quantized degree of freedom for such studies.

Cell-fate determination by ubiquitin-dependent regulation of translation

Nature 525, 7570 (2015). doi:10.1038/nature14978

Authors: Achim Werner, Shintaro Iwasaki, Colleen A. McGourty, Sofia Medina-Ruiz, Nia Teerikorpi, Indro Fedrigo, Nicholas T. Ingolia & Michael Rape

Metazoan development depends on the accurate execution of differentiation programs that allow pluripotent stem cells to adopt specific fates. Differentiation requires changes to chromatin architecture and transcriptional networks, yet whether other regulatory events support cell-fate determination is less well understood. Here we identify the ubiquitin ligase CUL3 in complex with its vertebrate-specific substrate adaptor KBTBD8 (CUL3KBTBD8) as an essential regulator of human and Xenopus tropicalis neural crest specification. CUL3KBTBD8 monoubiquitylates NOLC1 and its paralogue TCOF1, the mutation of which underlies the neurocristopathy Treacher Collins syndrome. Ubiquitylation drives formation of a TCOF1–NOLC1 platform that connects RNA polymerase I with ribosome modification enzymes and remodels the translational program of differentiating cells in favour of neural crest specification. We conclude that ubiquitin-dependent regulation of translation is an important feature of cell-fate determination.

by Vassilios Christopoulos, Paul R. Schrater

Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation.

by Jianfei Hu, Johnathan Neiswinger, Jin Zhang, Heng Zhu, Jiang Qian

Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process.

by Suhani Nagpal, Satyam Tiwari, Koyeli Mapa, Lipi Thukral

Many proteins comprising of complex topologies require molecular chaperones to achieve their unique three-dimensional folded structure. The E.coli chaperone, GroEL binds with a large number of unfolded and partially folded proteins, to facilitate proper folding and prevent misfolding and aggregation. Although the major structural components of GroEL are well defined, scaffolds of the non-native substrates that determine chaperone-mediated folding have been difficult to recognize. Here we performed all-atomistic and replica-exchange molecular dynamics simulations to dissect non-native ensemble of an obligate GroEL folder, DapA. Thermodynamics analyses of unfolding simulations revealed populated intermediates with distinct structural characteristics. We found that surface exposed hydrophobic patches are significantly increased, primarily contributed from native and non-native β-sheet elements. We validate the structural properties of these conformers using experimental data, including circular dichroism (CD), 1-anilinonaphthalene-8-sulfonic acid (ANS) binding measurements and previously reported hydrogen-deutrium exchange coupled to mass spectrometry (HDX-MS). Further, we constructed network graphs to elucidate long-range intra-protein connectivity of native and intermediate topologies, demonstrating regions that serve as central “hubs”. Overall, our results implicate that genomic variations (or mutations) in the distinct regions of protein structures might disrupt these topological signatures disabling chaperone-mediated folding, leading to formation of aggregates.

by Vipin Narang, Muhamad Azfar Ramli, Amit Singhal, Pavanish Kumar, Gennaro de Libero, Michael Poidinger, Christopher Monterola

Human gene regulatory networks (GRN) can be difficult to interpret due to a tangle of edges interconnecting thousands of genes. We constructed a general human GRN from extensive transcription factor and microRNA target data obtained from public databases. In a subnetwork of this GRN that is active during estrogen stimulation of MCF-7 breast cancer cells, we benchmarked automated algorithms for identifying core regulatory genes (transcription factors and microRNAs). Among these algorithms, we identified K-core decomposition, pagerank and betweenness centrality algorithms as the most effective for discovering core regulatory genes in the network evaluated based on previously known roles of these genes in MCF-7 biology as well as in their ability to explain the up or down expression status of up to 70% of the remaining genes. Finally, we validated the use of K-core algorithm for organizing the GRN in an easier to interpret layered hierarchy where more influential regulatory genes percolate towards the inner layers. The integrated human gene and miRNA network and software used in this study are provided as supplementary materials (S1 Data) accompanying this manuscript.

by Chakravarthy Marella, Andrew E. Torda, Dominik Schwudke

A lipidome is the set of lipids in a given organism, cell or cell compartment and this set reflects the organism’s synthetic pathways and interactions with its environment. Recently, lipidomes of biological model organisms and cell lines were published and the number of functional studies of lipids is increasing. In this study we propose a homology metric that can quantify systematic differences in the composition of a lipidome. Algorithms were developed to 1. consistently convert lipids structure into SMILES, 2. determine structural similarity between molecular species and 3. describe a lipidome in a chemical space model. We tested lipid structure conversion and structure similarity metrics, in detail, using sets of isomeric ceramide molecules and chemically related phosphatidylinositols. Template-based SMILES showed the best properties for representing lipid-specific structural diversity. We also show that sequence analysis algorithms are best suited to calculate distances between such template-based SMILES and we adjudged the Levenshtein distance as best choice for quantifying structural changes. When all lipid molecules of the LIPIDMAPS structure database were mapped in chemical space, they automatically formed clusters corresponding to conventional chemical families. Accordingly, we mapped a pair of lipidomes into the same chemical space and determined the degree of overlap by calculating the Hausdorff distance. We named this metric the ‘Lipidome jUXtaposition (LUX) score’. First, we tested this approach for estimating the lipidome similarity on four yeast strains with known genetic alteration in fatty acid synthesis. We show that the LUX score reflects the genetic relationship and growth temperature better than conventional methods although the score is based solely on lipid structures. Next, we applied this metric to high-throughput data of larval tissue lipidomes of Drosophila. This showed that the LUX score is sufficient to cluster tissues and determine the impact of nutritional changes in an unbiased manner, despite the limited information on the underlying structural diversity of each lipidome. This study is the first effort to define a lipidome homology metric based on structures that will enrich functional association of lipids in a similar manner to measures used in genetics. Finally, we discuss the significance of the LUX score to perform comparative lipidome studies across species borders.

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b06462

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b08214

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b06839

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b06787

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b08069

Journal of the American Chemical SocietyDOI: 10.1021/jacs.5b09271

ABSTRACT

An accurate scoring function that can select near-native structure models from a pool of alternative models is key for successful protein structure prediction. For the critical assessment of techniques for protein structure prediction (CASP) 11, we have built a protocol of protein structure prediction that has novel coarse-grained scoring functions for selecting decoys as the heart of its pipeline. The score named PRESCO (Protein Residue Environment SCOre) developed recently by our group evaluates the native-likeness of local structural environment of residues in a structure decoy considering positions and the depth of side-chains of spatially neighboring residues. We also introduced a helix interaction potential as an additional scoring function for selecting decoys. The best models selected by PRESCO and the helix interaction potential underwent structure refinement, which includes side-chain modeling and relaxation with a short molecular dynamics simulation. Our protocol was successful, achieving the top rank in the free modeling category with a significant margin of the accumulated Z-score to the subsequent groups when the top 1 models were considered. Proteins 2015. © 2015 Wiley Periodicals, Inc.

ABSTRACT

The elucidation of the mutual influence between peptide bond geometry and local conformation has important implications for protein structure refinement, validation, and prediction. To gain insights into the structural determinants and the energetic contributions associated with protein/peptide backbone plasticity, we here report an extensive analysis of the variability of the peptide bond angles by combining statistical analyses of protein structures and quantum mechanics calculations on small model peptide systems. Our analyses demonstrate that all the backbone bond angles strongly depend on the peptide conformation and unveil the existence of regular trends as function of ψ and/or φ. The excellent agreement of the quantum mechanics calculations with the statistical surveys of protein structures validates the computational scheme here employed and demonstrates that the valence geometry of protein/peptide backbone is primarily dictated by local interactions. Notably, for the first time we show that the position of the Hα hydrogen atom, which is an important parameter in NMR structural studies, is also dependent on the local conformation. Most of the trends observed may be satisfactorily explained by invoking steric repulsive interactions; in some specific cases the valence bond variability is also influenced by hydrogen-bond like interactions. Moreover, we can provide a reliable estimate of the energies involved in the interplay between geometry and conformations. Proteins 2015; 83:1973–1986. © 2015 Wiley Periodicals, Inc.

ABSTRACT

Amyloid fibers, implicated in a wide range of diseases, are formed when proteins misfold and stick together in long rope-like structures. As a natural mechanism, osmolytes can be used to modulate protein aggregation pathways with no interference with other cellular functions. The osmolyte sucrose delays fibrillation of the ribosomal protein S6 leading to softer and less shaped-defined fibrils. The molecular mechanism used by sucrose to delay S6 fibrillation was studied based on the two-state unfolding kinetics of the secondary and tertiary structures. It was concluded that the delay in S6 fibrillation results from stabilization and compaction of the slightly expanded tertiary native structure formed under fibrillation conditions. Interestingly, this compaction extends to almost all S6 tertiary structure but hardly affects its secondary structure. The part of the S6 tertiary structure that suffered more compaction by sucrose is known to be the first part to unfold, indicating that the native S6 has entered the unfolding pathway under fibrillation conditions. Proteins 2015; 83:2039–2051. © 2015 Wiley Periodicals, Inc.

Abstract

The importance of protonation states and proton transfer in pyridoxal 5’-phosphate (PLP)-chemistry can hardly be overstated. Although experimental approaches to investigate pKa values can provide general guidance for assigning proton locations, only static pictures of the chemical species are available. To obtain the overall protein dynamics for the interpretation of detailed enzyme catalysis in this study, guided by information from solid-state NMR, we performed molecular dynamics (MD) simulations for the PLP-dependent enzyme tryptophan synthase (TRPS), whose catalytic mechanism features multiple quasi-stable intermediates. The primary objective of this work is to elucidate how the position of a single proton on the reacting substrate affects local and global protein dynamics during the catalytic cycle. In general, proteins create a chemical environment and an ensemble of conformational motions to recognize different substrates with different protonations. The study of these interactions in TRPS shows that functional groups on the reacting substrate, such as the phosphoryl group, pyridine nitrogen, phenolic oxygen and carboxyl group, of each PLP-bound intermediate play a crucial role in constructing an appropriate molecular interface with TRPS. In particular, the protonation states of the ionizable groups on the PLP cofactor may enhance or weaken the attractions between the enzyme and substrate. In addition, remodulation of the charge distribution for the intermediates may help generate a suitable environment for chemical reactions. The results of our study enhance knowledge of protonation states for several PLP intermediates and help to elucidate their effects on protein dynamics in the function of TRPS and other PLP-dependent enzymes.

Abstract

We have developed an online NMR / X-ray Structure Pair Data Repository. The NIGMS Protein Structure Initiative (PSI) has provided many valuable reagents, 3D structures, and technologies for structural biology. The Northeast Structural Genomics Consortium was one of several PSI centers. NESG used both X-ray crystallography and NMR spectroscopy for protein structure determination. A key goal of the PSI was to provide experimental structures for at least one representative of each of hundreds of targeted protein domain families. In some cases, structures for identical (or nearly identical) constructs were determined by both NMR and X-ray crystallography. NMR spectroscopy and X-ray diffraction data for 41 of these “NMR / X-ray” structure pairs determined using conventional triple-resonance NMR methods with extensive sidechain resonance assignments have been organized in an online NMR / X-ray Structure Pair Data Repository. In addition, several NMR data sets for perdeuterated, methyl-protonated protein samples are included in this repository. As an example of the utility of this repository, these data were used to revisit questions about the precision and accuracy of protein NMR structures first outlined by Levy and coworkers several years ago (Andrec et al., Proteins 2007;69:449–465). These results demonstrate that the agreement between NMR and X-ray crystal structures is improved using modern methods of protein NMR spectroscopy. The NMR / X-ray Structure Pair Data Repository will provide a valuable resource for new computational NMR methods development.

Abstract

Nitrate reductases (NR) belong to the DMSO reductase family of Mo-containing enzymes and perform key roles in the metabolism of the nitrogen cycle, reducing nitrate to nitrite. Due to variable cell location, structure and function, they have been divided into periplasmic (Nap), cytoplasmic, and membrane-bound (Nar) nitrate reductases. The first crystal structure obtained for a NR was that of the monomeric NapA from Desulfovibrio desulfuricans in 1999. Since then several new crystal structures were solved providing novel insights that led to the revision of the commonly accepted reaction mechanism for periplasmic nitrate reductases. The two crystal structures available for the NarGHI protein are from the same organism (Escherichia coli) and the combination with electrochemical and spectroscopic studies also lead to the proposal of a reaction mechanism for this group of enzymes. Here we present an overview on the current advances in structural and functional aspects of bacterial nitrate reductases, focusing on the mechanistic implications drawn from the crystallographic data.

In the name of beauty

Nature 525, 7570 (2015). doi:10.1038/525425a

The ugly truth is that the plastic microbeads found in many skin scrubs and other personal-care products are a serious pollutant of the marine environment. They should be phased out rapidly.