Enhancer-promoter interactions are reconfigured through the formation of long-range multiway hubs as mouse ES cells exit pluripotency.

Enhancers bind transcription factors, chromatin regulators, and non-coding transcripts to modulate the expression of target genes. Here, we report 3D genome structures of single mouse ES cells as they are induced to exit pluripotency and transition through a formative stage prior to undergoing neuroectodermal differentiation. We find that there is a remarkable reorganization of 3D genome structure where inter-chromosomal intermingling increases dramatically in the formative state. This intermingling is associated with the formation of a large number of multiway hubs that bring together enhancers and promoters with similar chromatin states from typically 5-8 distant chromosomal sites that are often separated by many Mb from each other. In the formative state, genes important for pluripotency exit establish contacts with emerging enhancers within these multiway hubs, suggesting that the structural changes we have observed may play an important role in modulating transcription and establishing new cell identities.

Citrullination of HP1γ chromodomain affects association with chromatin.

BACKGROUND: Stem cell differentiation involves major chromatin reorganisation, heterochromatin formation and genomic relocalisation of structural proteins, including heterochromatin protein 1 gamma (HP1γ). As the principal reader of the repressive histone marks H3K9me2/3, HP1 plays a key role in numerous processes including heterochromatin formation and maintenance. RESULTS: We find that HP1γ is citrullinated in mouse embryonic stem cells (mESCs) and this diminishes when cells differentiate, indicating that it is a dynamically regulated post-translational modification during stem cell differentiation. Peptidylarginine deiminase 4, a known regulator of pluripotency, citrullinates HP1γ in vitro. This requires R38 and R39 within the HP1γ chromodomain, and the catalytic activity is enhanced by trimethylated H3K9 (H3K9me3) peptides. Mutation of R38 and R39, designed to mimic citrullination, affects HP1γ binding to H3K9me3-containing peptides. Using live-cell single-particle tracking, we demonstrate that R38 and R39 are important for HP1γ binding to chromatin in vivo. Furthermore, their mutation reduces the residence time of HP1γ on chromatin in differentiating mESCs. CONCLUSION: Citrullination is a novel post-translational modification of the structural heterochromatin protein HP1γ in mESCs that is dynamically regulated during mESC differentiation. The citrullinated residues lie within the HP1γ chromodomain and are important for H3K9me3 binding in vitro and chromatin association in vivo.

FRET-enhanced photostability allows improved single-molecule tracking of proteins and protein complexes in live mammalian cells.

A major challenge in single-molecule imaging is tracking the dynamics of proteins or complexes for long periods of time in the dense environments found in living cells. Here, we introduce the concept of using FRET to enhance the photophysical properties of photo-modulatable (PM) fluorophores commonly used in such studies. By developing novel single-molecule FRET pairs, consisting of a PM donor fluorophore (either mEos3.2 or PA-JF549) next to a photostable acceptor dye JF646, we demonstrate that FRET competes with normal photobleaching kinetic pathways to increase the photostability of both donor fluorophores. This effect was further enhanced using a triplet-state quencher. Our approach allows us to significantly improve single-molecule tracking of chromatin-binding proteins in live mammalian cells. In addition, it provides a novel way to track the localization and dynamics of protein complexes by labeling one protein with the PM donor and its interaction partner with the acceptor dye.

Combining fluorescence imaging with Hi-C to study 3D genome architecture of the same single cell.

Fluorescence imaging and chromosome conformation capture assays such as Hi-C are key tools for studying genome organization. However, traditionally, they have been carried out independently, making integration of the two types of data difficult to perform. By trapping individual cell nuclei inside a well of a 384-well glass-bottom plate with an agarose pad, we have established a protocol that allows both fluorescence imaging and Hi-C processing to be carried out on the same single cell. The protocol identifies 30,000-100,000 chromosome contacts per single haploid genome in parallel with fluorescence images. Contacts can be used to calculate intact genome structures to better than 100-kb resolution, which can then be directly compared with the images. Preparation of 20 single-cell Hi-C libraries using this protocol takes 5 d of bench work by researchers experienced in molecular biology techniques. Image acquisition and analysis require basic understanding of fluorescence microscopy, and some bioinformatics knowledge is required to run the sequence-processing tools described here.

3D structures of individual mammalian genomes studied by single-cell Hi-C.

The folding of genomic DNA from the beads-on-a-string-like structure of nucleosomes into higher-order assemblies is crucially linked to nuclear processes. Here we calculate 3D structures of entire mammalian genomes using data from a new chromosome conformation capture procedure that allows us to first image and then process single cells. The technique enables genome folding to be examined at a scale of less than 100 kb, and chromosome structures to be validated. The structures of individual topological-associated domains and loops vary substantially from cell to cell. By contrast, A and B compartments, lamina-associated domains and active enhancers and promoters are organized in a consistent way on a genome-wide basis in every cell, suggesting that they could drive chromosome and genome folding. By studying genes regulated by pluripotency factor and nucleosome remodelling deacetylase (NuRD), we illustrate how the determination of single-cell genome structure provides a new approach for investigating biological processes.

CcpNmr AnalysisAssign: a flexible platform for integrated NMR analysis.

NMR spectroscopy is an indispensably powerful technique for the analysis of biomolecules under ambient conditions, both for structural- and functional studies. However, in practice the complexity of the technique has often frustrated its application by non-specialists. In this paper, we present CcpNmr version-3, the latest software release from the Collaborative Computational Project for NMR, for all aspects of NMR data analysis, including liquid- and solid-state NMR data. This software has been designed to be simple, functional and flexible, and aims to ensure that routine tasks can be performed in a straightforward manner. We have designed the software according to modern software engineering principles and leveraged the capabilities of modern graphics libraries to simplify a variety of data analysis tasks. We describe the process of backbone assignment as an example of the flexibility and simplicity of implementing workflows, as well as the toolkit used to create the necessary graphics for this workflow. The package can be downloaded from www.ccpn.ac.uk/v3-software/downloads and is freely available to all non-profit organisations.

Treatment of Mental or Physical Health Problems in a Combat Zone: Comparisons of Postdeployment Mental Health and Early Separation From Service.

The primary aim of this study was to evaluate whether being treated for mental health or nonbattle physical injury during military combat deployment was associated with higher risk for postdeployment mental disorders and poorer career outcomes than seen in the general combat-deployed population. Service members treated in theater for mental health (n = 964) or noncombat injury (n = 853) were compared with randomly sampled personnel (n = 7,220) from the general deployed population on diagnosed mental disorders and early separation from service. Deployment, medical, and career information were obtained from Department of Defense archival databases. Over half of the personnel who received mental health treatment while deployed were diagnosed with 1 or more mental disorders postdeployment and/or were separated from service before completing their full-term enlistment. This was significantly higher than expected compared to the general deployed group, adjusting for demographic/military characteristics and mental health history (adjusted odds ratios [ORs] ranging 1.62 to 2.96). Frequencies of problems also were higher in the mental health-treated group than in the group treated for nonbattle physical injuries (significant adjusted ORs ranging 1.65 to 2.58). The documented higher risks for postdeployment adjustment problems suggested that especially those treated in theater by mental health providers might benefit from postdeployment risk-reduction programs.

Structure calculation, refinement and validation using CcpNmr Analysis.

CcpNmr Analysis provides a streamlined pipeline for both NMR chemical shift assignment and structure determination of biological macromolecules. In addition, it encompasses tools to analyse the many additional experiments that make NMR such a pivotal technique for research into complex biological questions. This report describes how CcpNmr Analysis can seamlessly link together all of the tasks in the NMR structure-determination process. It details each of the stages from generating NMR restraints [distance, dihedral, hydrogen bonds and residual dipolar couplings (RDCs)], exporting these to and subsequently re-importing them from structure-calculation software (such as the programs CYANA or ARIA) and analysing and validating the results obtained from the structure calculation to, ultimately, the streamlined deposition of the completed assignments and the refined ensemble of structures into the PDBe repository. Until recently, such solution-structure determination by NMR has been quite a laborious task, requiring multiple stages and programs. However, with the new enhancements to CcpNmr Analysis described here, this process is now much more intuitive and efficient and less error-prone.

High-resolution heteronuclear multidimensional NMR of proteins in living insect cells using a baculovirus protein expression system.

Recent developments in in-cell NMR techniques have allowed us to study proteins in detail inside living eukaryotic cells. In order to complement the existing protocols, and to extend the range of possible applications, we introduce a novel approach for observing in-cell NMR spectra using the sf9 cell/baculovirus system. High-resolution 2D (1)H-(15)N correlation spectra were observed for four model proteins expressed in sf9 cells. Furthermore, 3D triple-resonance NMR spectra of the Streptococcus protein G B1 domain were observed in sf9 cells by using nonlinear sampling to overcome the short lifetime of the samples and the low abundance of the labeled protein. The data were processed with a quantitative maximum entropy algorithm. These were assigned ab initio, yielding approximately 80% of the expected backbone NMR resonances. Well-resolved NOE cross peaks could be identified in the 3D (15)N-separated NOESY spectrum, suggesting that structural analysis of this size of protein will be feasible in sf9 cells.

Psychiatric diagnoses and treatment of U.S. military personnel while deployed to Iraq.

Military personnel deployed in support of combat operations are at significantly higher risk for mental health problems. However, much of what we know about combat-related mental health comes from postdeployment assessments. This study describes the mental health of 1,336 treatment-seeking deployed U.S. military personnel and interventions recommended by military mental health providers in Iraq from January 2006 to January 2007. Cases were primarily young enlisted men, most of whom were on their first combat deployment. Marines made up the majority of the cases (60%), but there were also large numbers of Army and Navy personnel. The most common psychiatric diagnoses were anxiety disorders (31%, including 11% with posttraumatic stress disorder), followed by adjustment (27%) and mood disorders (25%, including 22% with depression). Medication was the most commonly prescribed treatment for patients with psychiatric diagnoses but was often combined with recommendations for psychotherapy/counseling and/or behavioral modifications. The findings illustrate the distribution of mental health conditions seen among treatment-seeking troops while actively serving in a combat environment and the interventions recommended for them. Further examination of postdeployment health outcomes may help to facilitate the development of more effective acute intervention strategies in theater.

Theater Mental Health Encounter Data (TMHED): overview of study design and methods.

Research has documented higher risks for mental health problems among service members deployed to war zones, yet a research limitation has been that assessment has generally occurred often years after combat exposure. The Operational Stress Control and Readiness program integrated mental health practitioners with 1st Marine Division units serving in Iraq. This team documented mental health visits between January 2006 and January 2007 and developed the Theater Mental Health Encounter Database (TMHED). This report describes the TMHED study design, measures, and cases. Of 1336 patients (3180 patient visits), 10% were women, 75% were high school educated, 55% were mid-paygrade enlisted, and 63% were on their first combat deployment. Compared with the overall deployed population, patient percentages included higher percentages of Marines and Navy personnel but lower percentages of Army and Air Force personnel, more junior enlisted but fewer officers, and fewer college graduates. TMHED provides an unprecedented opportunity to study early psychiatric intervention in a combat zone and prospectively examines postdeployment health and career outcomes.

A software framework for analysing solid-state MAS NMR data.

Solid-state magic-angle-spinning (MAS) NMR of proteins has undergone many rapid methodological developments in recent years, enabling detailed studies of protein structure, function and dynamics. Software development, however, has not kept pace with these advances and data analysis is mostly performed using tools developed for solution NMR which do not directly address solid-state specific issues. Here we present additions to the CcpNmr Analysis software package which enable easier identification of spinning side bands, straightforward analysis of double quantum spectra, automatic consideration of non-uniform labelling schemes, as well as extension of other existing features to the needs of solid-state MAS data. To underpin this, we have updated and extended the CCPN data model and experiment descriptions to include transfer types and nomenclature appropriate for solid-state NMR experiments, as well as a set of experiment prototypes covering the experiments commonly employed by solid-sate MAS protein NMR spectroscopists. This work not only improves solid-state MAS NMR data analysis but provides a platform for anyone who uses the CCPN data model for programming, data transfer, or data archival involving solid-state MAS NMR data.

The CCPN Metabolomics Project: a fast protocol for metabolite identification by 2D-NMR.

SUMMARY: We present here the freely available Metabolomics Project resource specifically designed to work under the CcpNmr Analysis program produced by CCPN (Collaborative Computing Project for NMR) (Vranken et al., 2005, The CCPN data model for NMR spectroscopy: development of a software pipeline. Proteins, 59, 687-696). The project consists of a database of assigned 1D and 2D spectra of many common metabolites. The project aims to help the user to analyze and assign 1D and 2D NMR spectra of unknown metabolite mixtures. Spectra of unknown mixtures can be easily superimposed and compared with the database spectra, thus facilitating their assignment and identification. AVAILABILITY: The CCPN Metabolomics Project, together with an annotated example dataset, is freely available via: http://www.ccpn.ac.uk/metabolomics/.

MEMOPS: data modelling and automatic code generation.

In recent years the amount of biological data has exploded to the point where much useful information can only be extracted by complex computational analyses. Such analyses are greatly facilitated by metadata standards, both in terms of the ability to compare data originating from different sources, and in terms of exchanging data in standard forms, e.g. when running processes on a distributed computing infrastructure. However, standards thrive on stability whereas science tends to constantly move, with new methods being developed and old ones modified. Therefore maintaining both metadata standards, and all the code that is required to make them useful, is a non-trivial problem. Memops is a framework that uses an abstract definition of the metadata (described in UML) to generate internal data structures and subroutine libraries for data access (application programming interfaces--APIs--currently in Python, C and Java) and data storage (in XML files or databases). For the individual project these libraries obviate the need for writing code for input parsing, validity checking or output. Memops also ensures that the code is always internally consistent, massively reducing the need for code reorganisation. Across a scientific domain a Memops-supported data model makes it easier to support complex standards that can capture all the data produced in a scientific area, share them among all programs in a complex software pipeline, and carry them forward to deposition in an archive. The principles behind the Memops generation code will be presented, along with example applications in Nuclear Magnetic Resonance (NMR) spectroscopy and structural biology.

A nomenclature and data model to describe NMR experiments.

Despite ongoing efforts in organising NMR information, there is no consistent and well-described generic standard for naming NMR experiments. The main reason for the absence of a universal naming system is that the information content of the coherence pathways is difficult to describe in full detail. We propose a system that describes the common and generic elements of the coherence pathways produced by pulse sequences. The system itself is formalised by an 'NMR experiment protocol' model, which is described in the Universal Modelling Language (UML) as part of the CCPN data model. Furthermore, normalized experiment names can be derived from this proposed model. We hope this article will stimulate discussion to organise the wealth of NMR experiments, and that by bringing this discussion into the public domain we can improve and expand our proposed system to include as much information and as many NMR experiments as possible.

The CCPN data model for NMR spectroscopy: development of a software pipeline.

To address data management and data exchange problems in the nuclear magnetic resonance (NMR) community, the Collaborative Computing Project for the NMR community (CCPN) created a "Data Model" that describes all the different types of information needed in an NMR structural study, from molecular structure and NMR parameters to coordinates. This paper describes the development of a set of software applications that use the Data Model and its associated libraries, thus validating the approach. These applications are freely available and provide a pipeline for high-throughput analysis of NMR data. Three programs work directly with the Data Model: CcpNmr Analysis, an entirely new analysis and interactive display program, the CcpNmr FormatConverter, which allows transfer of data from programs commonly used in NMR to and from the Data Model, and the CLOUDS software for automated structure calculation and assignment (Carnegie Mellon University), which was rewritten to interact directly with the Data Model. The ARIA 2.0 software for structure calculation (Institut Pasteur) and the QUEEN program for validation of restraints (University of Nijmegen) were extended to provide conversion of their data to the Data Model. During these developments the Data Model has been thoroughly tested and used, demonstrating that applications can successfully exchange data via the Data Model. The software architecture developed by CCPN is now ready for new developments, such as integration with additional software applications and extensions of the Data Model into other areas of research.

Design of a data model for developing laboratory information management and analysis systems for protein production.

Data management has emerged as one of the central issues in the high-throughput processes of taking a protein target sequence through to a protein sample. To simplify this task, and following extensive consultation with the international structural genomics community, we describe here a model of the data related to protein production. The model is suitable for both large and small facilities for use in tracking samples, experiments, and results through the many procedures involved. The model is described in Unified Modeling Language (UML). In addition, we present relational database schemas derived from the UML. These relational schemas are already in use in a number of data management projects.

A framework for scientific data modeling and automated software development.

MOTIVATION: The lack of standards for storage and exchange of data is a serious hindrance for the large-scale data deposition, data mining and program interoperability that is becoming increasingly important in bioinformatics. The problem lies not only in defining and maintaining the standards, but also in convincing scientists and application programmers with a wide variety of backgrounds and interests to adhere to them. RESULTS: We present a UML-based programming framework for the modeling of data and the automated production of software to manipulate that data. Our approach allows one to make an abstract description of the structure of the data used in a particular scientific field and then use it to generate fully functional computer code for data access and input/output routines for data storage, together with accompanying documentation. This code can be generated simultaneously for different programming languages from a single model, together with, for example for format descriptions and I/O libraries XML and various relational databases. The framework is entirely general and could be applied in any subject area. We have used this approach to generate a data exchange standard for structural biology and analysis software for macromolecular NMR spectroscopy. AVAILABILITY: The framework is available under the GPL license, the data exchange standard with generated subroutine libraries under the LGPL license. Both may be found at http://www.ccpn.ac.uk; http://sourceforge.net/projects/ccpn CONTACT: ccpn@mole.bio.cam.ac.uk.

The CCPN project: an interim report on a data model for the NMR community.

A recent workshop discusses the progress toward integrating NMR data into a unifying data model.