Laboratory information management system for membrane protein structure initiative – from gene to crystal

Membrane Protein Structure Initiative (MPSI) exploits laboratory competencies to work collaboratively and distribute work among the different sites. This is possible as protein structure determination requires a series of steps, starting with target selection, through cloning, expression, purification, crystallization and finally structure determination. Distributed sites create a unique set of challenges for integrating and passing on information on the progress of targets. This role is played by the Protein Information Management System (PIMS), which is a laboratory information management system (LIMS), serving as a hub for MPSI, allowing collaborative structural proteomics to be carried out in a distributed fashion. It holds key information on the progress of cloning, expression, purification and crystallization of proteins. PIMS is employed to track the status of protein targets and to manage constructs, primers, experiments, protocols, sample locations and their detailed histories: thus playing a key role in MPSI data exchange. It also serves as the centre of a federation of interoperable information resources such as local laboratory information systems and international archival resources, like PDB or NCBI. During the challenging task of PIMS integration, within the MPSI, we discovered a number of prerequisites for successful PIMS integration. In this article we share our experiences and provide invaluable insights into the process of LIMS adaptation. This information should be of interest to partners who are thinking about using LIMS as a data centre for their collaborative efforts.     

SPINE 2: a system for collaborative structural proteomics within a federated database framework

We present version 2 of the SPINE system for structural proteomics. SPINE is available over the web at http://nesg.org. It serves as the central hub for the Northeast Structural Genomics Consortium, allowing collaborative structural proteomics to be carried out in a distributed fashion. The core of SPINE is a laboratory information management system (LIMS) for key bits of information related to the progress of the consortium in cloning, expressing and purifying proteins and then solving their structures by NMR or X-ray crystallography. Originally, SPINE focused on tracking constructs, but, in its current form, it is able to track target sample tubes and store detailed sample histories. The core database comprises a set of standard relational tables and a data dictionary that form an initial ontology for proteomic properties and provide a framework for large-scale data mining. Moreover, SPINE sits at the center of a federation of interoperable information resources. These can be divided into (i) local resources closely coupled with SPINE that enable it to handle less standardized information (e.g. integrated mailing and publication lists), (ii) other information resources in the NESG consortium that are inter-linked with SPINE (e.g. crystallization LIMS local to particular laboratories) and (iii) international archival resources that SPINE links to and passes on information to (e.g. TargetDB at the PDB).     

Managing and mining protein crystallization data

The crystallization of macromolecules remains a major bottleneck in structural biology. The routine screening of more than one thousand crystallization conditions and subsequent optimization by fine screening presents a challenge to conventional laboratory notebook keeping. In addition, the development of high-throughput robotic crystallization and imaging systems presents a pressing need for low-cost laboratory information management system (LIMS). Here we describe CLIMS2, a crystallization LIMS that features a simple, user-friendly graphical interface, allowing the storage, management, retrieval and mining of crystallization data. The CLIMS2 executable and documentation is freely available at http://clims.med.monash.edu.au.     

Focusing in on structural genomics: the University of Queensland structural biology pipeline

The flood of new genomic sequence information together with technological innovations in protein structure determination have led to worldwide structural genomics (SG) initiatives. The goals of SG initiatives are to accelerate the process of protein structure determination, to fill in protein fold space and to provide information about the function of uncharacterized proteins. In the long-term, these outcomes are likely to impact on medical biotechnology and drug discovery, leading to a better understanding of disease as well as the development of new therapeutics. Here we describe the high throughput pipeline established at the University of Queensland in Australia. In this focused pipeline, the targets for structure determination are proteins that are expressed in mouse macrophage cells and that are inferred to have a role in innate immunity. The aim is to characterize the molecular structure and the biochemical and cellular function of these targets by using a parallel processing pipeline. The pipeline is designed to work with tens to hundreds of target gene products and comprises target selection, cloning, expression, purification, crystallization and structure determination. The structures from this pipeline will provide insights into the function of previously uncharacterized macrophage proteins and could lead to the validation of new drug targets for chronic obstructive pulmonary disease and arthritis.     

LIMS — a catalyst for re-engineering

This paper describes how a laboratory information management system (LIMS) can act as a catalyst for re-engineering. Some of the key issues of successful change management are described and the common pitfalls that LIMS projects can fall into are summarised.     

Combining the polymerase incomplete primer extension method for cloning and mutagenesis with microscreening to accelerate structural genomics efforts

Successful protein expression, purification, and crystallization for challenging targets typically requires evaluation of a multitude of expression constructs. Often many iterations of truncations and point mutations are required to identify a suitable derivative for recombinant expression. Making and characterizing these variants is a significant barrier to success. We have developed a rapid and efficient cloning process and combined it with a protein microscreening approach to characterize protein suitability for structural studies. The Polymerase Incomplete Primer Extension (PIPE) cloning method was used to rapidly clone 448 protein targets and then to generate 2143 truncations from 96 targets with minimal effort. Proteins were expressed, purified, and characterized via a microscreening protocol, which incorporates protein quantification, liquid chromatography mass spectrometry and analytical size exclusion chromatography (AnSEC) to evaluate suitability of the protein products for X-ray crystallography. The results suggest that selecting expression constructs for crystal trials based primarily on expression solubility is insufficient. Instead, AnSEC scoring as a measure of protein polydispersity was found to be predictive of ultimate structure determination success and essential for identifying appropriate boundaries for truncation series. Overall structure determination success was increased by at least 38% by applying this combined PIPE cloning and microscreening approach to recalcitrant targets.     

Identifying protein construct variants with increased crystallization propensity--a case study

This study describes an efficient multiparallel automated workflow of cloning, expression, purification, and crystallization of a large set of construct variants for isolated protein domains aimed at structure determination by X-ray crystallography. This methodology is applied to MAPKAP kinase 2, a key enzyme in the inflammation pathway and thus an attractive drug target. The study reveals a distinct subset of truncation variants with improved crystallization properties. These constructs distinguish themselves by increased solubility and stability during a parallel automated multistep purification process including removal of the recombinant tag. High-throughput protein melting point analysis characterizes this subset of constructs as particularly thermostable. Both parallel purification screening and melting point determination clearly identify residue 364 as the optimal C terminus for the kinase domain. Moreover, all three constructs that ultimately crystallized feature this C terminus. At the N terminus, only three amino acids differentiate a noncrystallizing from a crystallizing construct. This study addresses the very common issues associated with difficult to crystallize proteins, those of solubility and stability, and the crucial importance of particular residues in the formation of crystal contacts. A methodology is suggested that includes biophysical measurements to efficiently identify and produce construct variants of isolated protein domains which exhibit higher crystallization propensity.     

The structural genomics experimental pipeline: insights from global target lists

Structural genomics (SG) initiatives are currently attempting to achieve the high-throughput determination of protein structures on a genome-wide scale. Here we analyze the SG target data that have been publicly released over a period of 16 months to assess the potential of the SG initiatives. We use statistical techniques most commonly applied in epidemiology to describe the dynamics of targets through the experimental SG pipeline. There is no clear bottleneck among the key stages of cloning, expression, purification and crystallization. An SG target will progress through each of these steps with a probability of approximately 45%. Around 80% of targets with diffraction data will yield a crystal structure, and 20% of targets with HSQC spectra will yield an NMR structure. We also find the overlaps among SG targets: 61% of SG protein sequences share at least 30% sequence identity with one or more other SG targets. There is no significant difference in average structure quality among SG structures and other structures in the PDB determined by "traditional" methods, but on average SG structures are deposited to the PDB twice as quickly after X-ray data collection.     

Protein crystallization: from purified protein to diffraction-quality crystal

Determining the structure of biological macromolecules by X-ray crystallography involves a series of steps: selection of the target molecule; cloning, expression, purification and crystallization; collection of diffraction data and determination of atomic positions. However, even when pure soluble protein is available, producing high-quality crystals remains a major bottleneck in structure determination. Here we present a guide for the non-expert to screen for appropriate crystallization conditions and optimize diffraction-quality crystal growth.     

生物实验信息管理模块建模技术研究

实验信息管理模块是生物实验室信息管理系统的核心,其设计的好坏直接关系到整个系统建设的成败。针对生物实验室实验流程灵活,数据流网络复杂等特点,研究设计了一套实验信息管理模块的模型,并将研究的模型用于基因测序实验室信息管理系统的开发并取得了成功。实践证明,该模型为实验室信息系统(LIMS)中实验管理模块的开发提供了理论支撑,并且提高了LIMS的开发效率。     

Evaluation of a model for seeded isothermal batch protein crystallization

Bulk protein crystallization, unlike small molecule crystallization, has found very limited use in biopharmaceutical manufacture. Most work in this area targets obtaining single large crystals for molecular structure determination by crystallography. Design and optimization of bulk crystallization for protein recovery and purification is much less common, and requires a mathematical model for analysis of laboratory data suitable for scale-up purposes. Traditionally, the crystal size distribution and method of moments is used to characterize the crystallization process. A simpler method is presented in this paper that utilizes the desupersaturation curve. The method uses an approach that does not require expensive instrumentation or characterization of the seed crystal size distribution. The method is extended to allow determination of both the mass deposition rate constant and the growth rate order from a single desuperaturation curve. Experimental data for the bulk crystallization of ovalbumin are used to validate the method. The rate constants and rate order obtained using the new method compare well with literature values. Scale-up is illustrated by prediction of the impact of changes in seed mass on protein crystallization. This new method offers a straightforward and low-cost alternative to traditional methods for the analysis and scale-up of protein crystallization data.     

A matrix for a LIMS with a strategic focus

This article focuses on the impact that a laboratory information management system (LIMS) should make on both a laboratory and an organisation but rarely does. To be effective a system should deliver benefit to both the laboratory environment and the organisation. But how should this be designed? To overcome this problem a matrix is proposed, which will allow any LIMS to be developed with a strategic focus. The matrix can be used either as an aid to system implementation and deciding which applications the LIMS should interface with. Alternatively, the matrix can be a means of evaluating the effectiveness of existing applications and to chart their further development. The aim is to give analytical chemists, managers and computer scientists a tool to enable any LIMS to reach its true potential.     

Predicting experimental properties of integral membrane proteins by a naive Bayes approach

Integral membrane proteins (iMPs) are challenging targets for structure determination because of the substantial experimental difficulties involved in their sample preparation. Accordingly, success rates of large-scale structural genomics consortia are much lower for this class of molecules compared to globular targets, underscoring the pressing need for predictive strategies to identify iMPs that are more likely to overcome laboratory bottlenecks. On the basis of the target status information available in the TargetDB repository, we describe the first large-scale analysis of experimental behavior of iMPs. Using information on recalcitrant and propagating iMP targets as negative and positive sets, respectively, we present naive Bayes classifiers capable of predicting, from sequence alone, those proteins that are more amenable to cloning, expression, and solubilization studies. Protein sequences are represented in the space of 72 features, including amino acid composition, occurrence of amino acid groups, ratios between residue groups, and hydrophobicity measures. Taking into account unequal representation of main taxonomic groups in the TargetDB, sequence database had a beneficial effect on the prediction results. The classifiers achieve accuracies of 70%, 63-70%, and 61% in predicting the amenability of iMPs for cloning, expression, and solubilization, respectively, thus making them useful tools in target selection for structure determination. Our assessment of prediction results clearly demonstrates that classifiers based on single features do not possess acceptable discriminative power and that the experimental behavior of iMPs is imprinted in their primary sequence through relationships between a restricted set of key properties. In most cases, sets of 10-20 protein features were found actually relevant, most notably, the content of isoleucine, valine, and positively-charged residues.     

A Perl toolkit for LIMS development

Background  

High throughput laboratory techniques generate huge quantities of scientific data. Laboratory Information Management Systems (LIMS) are a necessary requirement, dealing with sample tracking, data storage and data reporting. Commercial LIMS solutions are available, but these can be both costly and overly complex for the task. The development of bespoke LIMS solutions offers a number of advantages, including the flexibility to fulfil all a laboratory's requirements at a fraction of the price of a commercial system. The programming language Perl is a perfect development solution for LIMS applications because of Perl's powerful but simple to use database and web interaction, it is also well known for enabling rapid application development and deployment, and boasts a very active and helpful developer community. The development of an in house LIMS from scratch however can take considerable time and resources, so programming tools that enable the rapid development of LIMS applications are essential but there are currently no LIMS development tools for Perl.     

Current trends in α-helical membrane protein crystallization: An update

α-Helical membrane proteins (MPs) are the targets for many pharmaceutical drugs and play important roles in human physiology. In recent years, significant progress has been made in determining their atomic structure using X-ray crystallography. However, a major bottleneck in MP crystallography still remains, namely, the identification of conditions that give crystals that are suitable for structural determination. In 2008, we undertook an analysis of the crystallization conditions for 121 α-helical MPs to design a rationalized sparse matrix crystallization screen, MemGold. We now report an updated analysis that includes a further 133 conditions. The results reveal the current trends in α-helical MP crystallization with notable differences since 2008. The updated information has been used to design new crystallization and additive screens that should prove useful for both initial crystallization scouting and subsequent crystal optimization.     

A fully integrated protein crystallization platform for small-molecule drug discovery

Structure-based drug discovery in the pharmaceutical industry benefits from cost-efficient methodologies that quickly assess the feasibility of specific, often refractory, protein targets to form well-diffracting crystals. By tightly coupling construct and purification diversity with nanovolume crystallization, the Structural Biology Group at Syrrx has developed such a platform to support its small-molecule drug-discovery program. During the past 18 months of operation at Syrrx, the Structural Biology Group has executed several million crystallization and imaging trials on over 400 unique drug-discovery targets. Here, key components of the platform, as well as an analysis of some experimental results that allowed for platform optimization, will be described.     

LIMS — beyond CSV: a strategy for LIMS data quality assurance

Computer system validation of a LIMS is often confused with the ongoing task of entering and quality-assuring the material, instrument, specification, method, calculation, and study data required for laboratory sample and results management. A practical approach to LIMS template data quality assurance includes preparation of one or more standard operating procedures for entry and quality assurance of material specifications, test limits, secondary calculation formulae, and other analytical laboratory testing information.     

ISPyB: an information management system for synchrotron macromolecular crystallography

MOTIVATION: Individual research groups now analyze thousands of samples per year at synchrotron macromolecular crystallography (MX) resources. The efficient management of experimental data is thus essential if the best possible experiments are to be performed and the best possible data used in downstream processes in structure determination pipelines. Information System for Protein crystallography Beamlines (ISPyB), a Laboratory Information Management System (LIMS) with an underlying data model allowing for the integration of analyses down-stream of the data collection experiment was developed to facilitate such data management. RESULTS: ISPyB is now a multisite, generic LIMS for synchrotron-based MX experiments. Its initial functionality has been enhanced to include improved sample tracking and reporting of experimental protocols, the direct ranking of the diffraction characteristics of individual samples and the archiving of raw data and results from ancillary experiments and post-experiment data processing protocols. This latter feature paves the way for ISPyB to play a central role in future macromolecular structure solution pipelines and validates the application of the approach used in ISPyB to other experimental techniques, such as biological solution Small Angle X-ray Scattering and spectroscopy, which have similar sample tracking and data handling requirements.