SPINE bioinformatics and data-management aspects of high-throughput structural biology

Structural Molecular Biology-A Personal Reflection on the Occasion of John Kendrew's 100th Birthday

Here, I discuss the development and future of structural molecular biology, concentrating on the eukaryotic transcription machinery and reflecting on John Kendrew's legacy from a personal perspective.

The impact of structural genomics: the first quindecennial

The period 2000-2015 brought the advent of high-throughput approaches to protein structure determination. With the overall funding on the order of $2 billion (in 2010 dollars), the structural genomics (SG) consortia established worldwide have developed pipelines for target selection, protein production, sample preparation, crystallization, and structure determination by X-ray crystallography and NMR. These efforts resulted in the determination of over 13,500 protein structures, mostly from unique protein families, and increased the structural coverage of the expanding protein universe. SG programs contributed over 4400 publications to the scientific literature. The NIH-funded Protein Structure Initiatives alone have produced over 2000 scientific publications, which to date have attracted more than 93,000 citations. Software and database developments that were necessary to handle high-throughput structure determination workflows have led to structures of better quality and improved integrity of the associated data. Organized and accessible data have a positive impact on the reproducibility of scientific experiments. Most of the experimental data generated by the SG centers are freely available to the community and has been utilized by scientists in various fields of research. SG projects have created, improved, streamlined, and validated many protocols for protein production and crystallization, data collection, and functional analysis, significantly benefiting biological and biomedical research.

Crystal structure of an HD-GYP domain cyclic-di-GMP phosphodiesterase reveals an enzyme with a novel trinuclear catalytic iron centre

Bis‐(3′,5′) cyclic di‐guanylate (c‐di‐GMP) is a key bacterial second messenger that is implicated in the regulation of many crucial processes that include biofilm formation, motility and virulence. Cellular levels of c‐di‐GMP are controlled through synthesis by GGDEF domain diguanylate cyclases and degradation by two classes of phosphodiesterase with EAL or HD‐GYP domains. Here, we have determined the structure of an enzymatically active HD‐GYP domain protein from Persephonella marina (PmGH) alone, in complex with substrate (c‐di‐GMP) and final reaction product (GMP). The structures reveal a novel trinuclear iron binding site, which is implicated in catalysis and identify residues involved in recognition of c‐di‐GMP. This structure completes the picture of all domains involved in c‐di‐GMP metabolism and reveals that the HD‐GYP family splits into two distinct subgroups containing bi‐ and trinuclear metal centres.

Computational approaches to selecting and optimising targets for structural biology

Selection of protein targets for study is central to structural biology and may be influenced by numerous factors. A key aim is to maximise returns for effort invested by identifying proteins with the balance of biophysical properties that are conducive to success at all stages (e.g. solubility, crystallisation) in the route towards a high resolution structural model. Selected targets can be optimised through construct design (e.g. to minimise protein disorder), switching to a homologous protein, and selection of experimental methodology (e.g. choice of expression system) to prime for efficient progress through the structural proteomics pipeline.

Here we discuss computational techniques in target selection and optimisation, with more detailed focus on tools developed within the Scottish Structural Proteomics Facility (SSPF); namely XANNpred, ParCrys, OB-Score (target selection) and TarO (target optimisation). TarO runs a large number of algorithms, searching for homologues and annotating the pool of possible alternative targets. This pool of putative homologues is presented in a ranked, tabulated format and results are also visualised as an automatically generated and annotated multiple sequence alignment. The target selection algorithms each predict the propensity of a selected protein target to progress through the experimental stages leading to diffracting crystals. This single predictor approach has advantages for target selection, when compared with an approach using two or more predictors that each predict for success at a single experimental stage. The tools described here helped SSPF achieve a high (21%) success rate in progressing cloned targets to diffraction-quality crystals.

Characterization of the interactions between the nucleoprotein and the phosphoprotein of Henipavirus

The Henipavirus genome is encapsidated by the nucleoprotein (N) within a helical nucleocapsid that recruits the polymerase complex via the phosphoprotein (P). In a previous study, we reported that in henipaviruses, the N-terminal domain of the phosphoprotein and the C-terminal domain of the nucleoprotein (N(TAIL)) are both intrinsically disordered. Here we show that Henipavirus N(TAIL) domains are also disordered in the context of full-length nucleoproteins. We also report the cloning, purification, and characterization of the C-terminal X domains (P(XD)) of Henipavirus phosphoproteins. Using isothermal titration calorimetry, we show that N(TAIL) and P(XD) form a 1:1 stoichiometric complex that is stable under NaCl concentrations as high as 1 M and has a K(D) in the μM range. Using far-UV circular dichroism and nuclear magnetic resonance, we show that P(XD) triggers an increase in the α-helical content of N(TAIL). Using fluorescence spectroscopy, we show that P(XD) has no impact on the chemical environment of a Trp residue introduced at position 527 of the Henipavirus N(TAIL) domain, thus arguing for the lack of stable contacts between the C termini of N(TAIL) and P(XD). Finally, we present a tentative structural model of the N(TAIL)-P(XD) interaction in which a short, order-prone region of N(TAIL) (α-MoRE; amino acids 473-493) adopts an α-helical conformation and is embedded between helices α2 and α3 of P(XD), leading to a relatively small interface dominated by hydrophobic contacts. The present results provide the first detailed experimental characterization of the N-P interaction in henipaviruses and designate the N(TAIL)-P(XD) interaction as a valuable target for rational antiviral approaches.

The Protein Information Management System (PiMS): a generic tool for any structural biology research laboratory

The Protein Information Management System (PiMS) is described together with a discussion of how its features make it well suited to laboratories of all sizes.

The techniques used in protein production and structural biology have been developing rapidly, but techniques for recording the laboratory information produced have not kept pace. One approach is the development of laboratory information-management systems (LIMS), which typically use a relational database schema to model and store results from a laboratory workflow. The underlying philosophy and implementation of the Protein Information Management System (PiMS), a LIMS development specifically targeted at the flexible and unpredictable workflows of protein-production research laboratories of all scales, is described. PiMS is a web-based Java application that uses either Postgres or Oracle as the underlying relational database-management system. PiMS is available under a free licence to all academic laboratories either for local installation or for use as a managed service.

Unmet challenges of structural genomics

Structural genomics (SG) programs have developed during the last decade many novel methodologies for faster and more accurate structure determination. These new tools and approaches led to the determination of thousands of protein structures. The generation of enormous amounts of experimental data resulted in significant improvements in the understanding of many biological processes at molecular levels. However, the amount of data collected so far is so large that traditional analysis methods are limiting the rate of extraction of biological and biochemical information from 3D models. This situation has prompted us to review the challenges that remain unmet by SG, as well as the areas in which the potential impact of SG could exceed what has been achieved so far.

TarO: a target optimisation system for structural biology

TarO (http://www.compbio.dundee.ac.uk/taro) offers a single point of reference for key bioinformatics analyses relevant to selecting proteins or domains for study by structural biology techniques. The protein sequence is analysed by 17 algorithms and compared to 8 databases. TarO gathers putative homologues, including orthologues, and then obtains predictions of properties for these sequences including crystallisation propensity, protein disorder and post-translational modifications. Analyses are run on a high-performance computing cluster, the results integrated, stored in a database and accessed through a web-based user interface. Output is in tabulated format and in the form of an annotated multiple sequence alignment (MSA) that may be edited interactively in the program Jalview. TarO also simplifies the gathering of additional annotations via the Distributed Annotation System, both from the MSA in Jalview and through links to Dasty2. Routes to other information gateways are included, for example to relevant pages from UniProt, COG and the Conserved Domains Database. Open access to TarO is available from a guest account with private accounts for academic use available on request. Future development of TarO will include further analysis steps and integration with the Protein Information Management System (PIMS), a sister project in the BBSRC ‘Structural Proteomics of Rational Targets’ initiative

Purification, crystallization and preliminary X-ray characterization of a human mitochondrial phenylalanyl-tRNA synthetase

Human monomeric mitochondrial phenylalanyl-tRNA synthetase (mitPheRS) is an enzyme that catalyzes the charging of tRNA with the cognate amino acid phenylalanine. Human mitPheRS is a chimera of the bacterial alpha-subunit of PheRS and the B8 domain of its beta-subunit. Together, the alpha-subunit and the 'RNP-domain' (B8 domain) at the C-terminus form the minimal structural set to construct an enzyme with phenylalanylation activity. The recombinant human mitPheRS was purified to homogeneity and crystallized in complex with phenylalanine and ATP. The crystals diffracted to 2.2 A resolution and belonged to space group P2(1)2(1)2(1), with unit-cell parameters a = 55, b = 90, c = 96 A.

A versatile ligation-independent cloning method suitable for high-throughput expression screening applications

This article describes the construction of a set of versatile expression vectors based on the In-Fusion™ cloning enzyme and their use for high-throughput cloning and expression screening. Modifications to commonly used vectors rendering them compatible with In-Fusion™ has produced a ligation-independent cloning system that is (1) insert sequence independent (2) capable of cloning large PCR fragments (3) efficient over a wide (20-fold) insert concentration range and (4) applicable to expression in multiple hosts. The system enables the precise engineering of (His₆-) tagged constructs with no undesirable vector or restriction-site-derived amino acids added to the expressed protein. The use of a multiple host-enabled vector allows rapid screening in both E. coli and eukaryotic hosts (HEK293T cells and insect cell hosts, e.g. Sf9 cells). These high-throughput screening activities have prompted the development and validation of automated protocols for transfection of mammalian cells and Ni-NTA protein purification.

Lysine methylation as a routine rescue strategy for protein crystallization

Crystallization remains a critical step in X-ray structure determination. Because it is not generally possible to rationally predict crystallization conditions, commercial screens have been developed which sample a wide range of crystallization space. While this approach has proved successful in many cases, a significant number of proteins fail to crystallize despite being soluble and monodispersed. It is established that chemical modification can facilitate the crystallization of otherwise intractable proteins. Here we describe a method for the reductive methylation of lysine residues which is simple, inexpensive, and efficient, and report on its application to ten proteins. We describe the effect of methylation on the physico-chemical properties of these proteins, and show that it led to diffraction-quality crystals from four proteins and structures for three that had hitherto proved refractory to crystallization. The method is suited to both low- and high-throughput laboratories.

MACSIMS: multiple alignment of complete sequences information management system

BACKGROUND

In the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family.

RESULTS

MACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis.

CONCLUSION

MACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at http://bips.u-strasbg.fr/MACSIMS/.