Journal of Applied Crystallography

Time resolved X-ray crystallography is experiencing a resurgence, in part, because of serial methods that readily allow scientists to create stop-motion movies of macromolecular function of photoactivation, enzyme catalysed reactions, and ligand-induced conformational changes triggering further downstream signalling events. While some reactions can be initiated with light, either naturally or using photocaged compounds, a more generally applicable approach is to mix microcrystals with reagents at varying time points prior to exposure to the X-ray beam. A powerful approach has been to combine droplet on demand tape drive sample delivery with X-ray emission spectroscopy (XES) that correlates atomic structure with electronic states of metal ions within the sample. To our knowledge, such a combined methodology has not been deployed previously at a synchrotron beamline and has been restricted to XFELs. Here we describe prototype experiments along the development pathway to a combined droplet on demand diffraction and XES system at the microfocus beamline VMXi at Diamond Light Source. We demonstrate the collection of a high-quality serial diffraction data set from microcrystals within hundreds of picolitre-volume droplets deposited on a moving tape. In separate experiments at VMXi, we collected XES data from microcrystals of a copper enzyme delivered using a high viscosity extruder. Together, these results demonstrate the feasibility of combined droplet on demand serial crystallography and XES experiments using a third-generation synchrotron beamline; project work currently underway at Diamond Light Source. SynopsisWe describe proof of concept experiments towards correlated serial crystallography (SSX) and X-ray emission spectroscopy (XES) from microcrystals at a microfocus synchrotron beamline. A droplet on demand tape drive system delivers microcrystals to the beam within well-separated, hundreds of picolitre-volume droplets while XES allows validation of redox states of metals within protein crystals.

Monte Carlo neutron ray-tracing simulations of time-of-flight (TOF)-Laue neutron macromolecular crystal diffraction (n-MX) using the McStas software package were done for the upcoming NMX Macromolecular Diffractometer at the European Spallation Source. Splitting neutron rays that arrive at the crystal lead to dramatic improvements in event formation with minimal computational overhead. The simulated event probability data was sampled using a new single-pass weighted reservoir sampling method, and processed like real n-MX data using DIALS. The effects of air and beamstop scatter on simulated data was investigated. SynopsisMonte Carlo simulations of neutron protein diffraction experiments provide useful data that models instrumental components that interact with neutrons, as well as the crystal diffraction itself. These data can be applied to instrument development, such as the commissioning of the NMX Macromolecular Diffractometer at ESS.

We report on recent methodological advances at the Life Science X-ray Scattering (LiX) beamline of the National Synchrotron Light Source II (NSLS-II) to support small-angle X-ray scattering experiments on skeletal and cardiac muscle tissues. These experiments have been routinely performed at the BioCAT beamline of the Advanced Photon Source (APS) over the past two decades to measure sarcomeric protein organization within healthy and diseased muscle tissues and provide direct molecular evidence for their functional roles and dynamics. Many recent advances in our understanding of sarcomeric proteins relied on diffraction data and include, as examples, MyBP-C, crossbridge SRX/DRX states, and titin. With LiX now available for muscle experimentation, more muscle users can be supported which will speed up research of sarcomeric proteins, muscle biomechanics, and skeletal and cardiac myopathies. LiX explicitly focuses on high-throughput muscle diffraction with rapid sample turnover and semi-automated data processing. These operations have been tested and validated on skeletal and cardiac tissues sourced from both humans and multiple animal models including pig, rat, mouse, and zebrafish.

Multi-domain proteins (MDPs) adopt diverse conformations arising from cooperative inter-domain motions, and such dynamics are intimately coupled to their biological functions. Quantitative characterization of these motions is crucial for elucidating their functional mechanisms. Although small-angle X-ray scattering (SAXS) provides information on overall domain arrangement, the limited experimental constraints hinder reliable discrimination of conformational ensembles derived from molecular dynamics (MD) simulations. To address this limitation, complementary experimental constraints that enable to observe domain-selective structural information are required. Inverse contrast-matching small-angle neutron scattering (iCM-SANS), combined with segmental deuteration, enables selective visualization of individual domains and thus provides such complementary information. However, practical strategies for preparing segmentally deuterated MDPs with arbitrary domain labelling have yet to be established. Here, we develop an experimental protocol that integrates controlled protein deuteration with high-efficiency multi-step protein ligation to generate a segmentally deuterated MDP in high yield. The combined use of SAXS and iCM-SANS yields complementary structural constraints that enhance discrimination of MD-derived conformational ensembles. This protocol expands the applicability of segment-selective visualization and also provides an opportunity for high-precision analysis of dynamics in complex MDPs. SynopsisSegmental deuteration enabled by high-efficiency multi-step protein ligation, combined with inverse contrast-matching SANS and SAXS, provides structural constraints that improve discrimination of molecular dynamics ensembles of multi-domain proteins. IMPORTANTthis document contains embedded data - to preserve data integrity, please ensure where possible that the IUCr Word tools (available from http://journals.iucr.org/services/docxtemplate/) are installed when editing this document.

Capturing meta-stable conformations of enzymes and ligand complexes demands structural snapshots beyond static crystal structures. While time-resolved serial crystallography at room temperature, offers a time-resolution down to the femto-second domain it requires large amounts of micro crystals, specialized beamlines and considerable experience. Moreover, as the majority of enzymes displays turnover-times in the millisecond domain or slower, simpler methods can provide meaningful structural insight into enzyme catalysis. Vitrification of protein crystals can trap reaction intermediates by rapid cooling to {inverted exclamation} 100 K, and has traditionally been used to gain insight into long lived reaction intermediates such as product complexes. However, manual vitrification procedures are limited to long delay times of at least several seconds and heavily suffer from operator variability. A solution to this problem is provided by automatic crystal plunging devices, such as the Spitrobot, that plunge loop-mounted protein crystals into liquid nitrogen within millisecond time-scales. Versatile means of reaction initiation can be achieved either by micro dispensing a ligand droplet, or via optical excitation of light-sensitive proteins, or via the photoactivation of caged compounds. In addition to the conceptual simplicity, another benefit of cryo-trapping is that data can be collected at conventional synchrotron beamlines, exploiting their robust high-throughput capabilities. Thus, compared to room-temperature time-resolved crystallography, users not only benefit from uncoupling sample-preparation and data-collection, but also from a reduction in the required technical expertise and ready access to radiation sources. However, as cryo-trapping crystallography explores dynamic structural changes that become only visible by the comparison of several samples, experiments have to be carefully planned to carry out the necessary controls and to avoid mis- or over-interpretation of the results. Here we describe a detailed protocol for cryo-trapping time-resolved crystallography using automated crystal-plungers that enables researchers to map enzymatic reaction coordinate pathways within the millisecond domain.

Ligand binding has been shown to induce significant alterations in the conformational landscape of proteins. Traditional crystallography approaches have provided valuable input about the end states in ligand-binding reactions. However, dynamical relationships between ligand binding and backbone rearrangement often remain obscured by crystallographic structures. In the present study, we use time-resolved serial synchrotron crystallography (TR-SSX) to directly visualize indole binding in the cavity of T4 lysozyme L99A in microcrystals under controlled environmental conditions. By integrating fixed target crystallography with LAMA-based ligand delivery, we have been able to track the progression of ligand binding and backbone rearrangement. By utilizing an occupancy refinement protocol, we have been able to quantify structural populations. Our studies reveal that ligand binding for this protein cavity follows a diffusion-limited process that progressively rearranges the F -helix of the protein towards a dominant conformational state. These findings establish an observable link between ligand diffusion, occupancy evolution and conformational adaptation within a crystalline environment. More broadly, our work shows how TR-SSX can quantify ligand and conformational populations during binding, providing a framework to interpret structural adaptation in real time.

X-ray fluorescence microscopy (XFM) continues to develop as a powerful quantitative technique for high resolution, label-free, elemental mapping of biological, environmental, and material samples. Methods for rigorously fitting spectra, increasing throughput, accounting for background signals, and deconvoluting overlapping emission lines continue to evolve. We show here that quantitative fits of XFM data obtained after removing a baseline, calculated by connecting peak edges, can be unexpectedly dependent upon acquisition dwell-time and spectral aggregation leading to differences in apparent elemental content. Using mouse preimplantation embryos and ovarian follicles as model samples, we demonstrate how these variables influence quantitative comparisons between samples. We find that subtracting an empirically measured blank spectrum instead of a baseline provides quantitative XFM elemental mapping results that are independent of dwell time and spectral aggregation dependencies.

Ion mobility mass spectrometry (IM-MS) provides valuable structural information about protein shape and size through collision cross section (CCS). However, it lacks atomic level structural detail. While AlphaFold has been successful in predicting monomeric protein structure, it can struggle with modeling protein complexes. To address these limitations, we developed a method that integrates IM-MS data with AlphaFold and Rosetta to improve complex structure prediction. Our approach uses experimental CCS data to guide the assembly of AlphaFold predicted subunits using a Rosetta docking pipeline and evaluating the resulting complexes with a newly developed score. Using this strategy, we were able to improve root mean square deviation (RMSD) values for 26 of 38 (68%) complexes compared to AlphaFold-Multimer. Furthermore, 16 of these systems improved significantly from greater than 4 [A] RMSD to less than 4 [A]. This method demonstrates a robust approach to overcome limitations in complex assembly modeling. Table of Contents Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/706193v1_ufig1.gif" ALT="Figure 1"> View larger version (68K): org.highwire.dtl.DTLVardef@cf71c3org.highwire.dtl.DTLVardef@135e09aorg.highwire.dtl.DTLVardef@2cc2fcorg.highwire.dtl.DTLVardef@b53feb_HPS_FORMAT_FIGEXP M_FIG In this integrative modeling work, protein complex structures were modeled by combining AlphaFold predicted subunits with Rosetta docking. Collision cross section data from ion-mobility mass spectrometry were used as evaluation constraints and docked models were scored using the IM-complex score. The best scoring models generally represent accurate protein complex structures. C_FIG

Multidomain proteins connected by flexible linkers populate conformational ensembles that are challenging to characterize using conventional structural biology methods. In domain-linker-domain (DLD) proteins, linker-mediated inter-domain relative positions and orientations are functionally relevant, yet their dynamical behavior in solution normally remain poorly described. Small-angle X-ray scattering (SAXS) provides ensemble-averaged structural information for such systems; however, coupling with computational modeling is required to accurately describe the dynamic behavior of this family of proteins in solution. Here, we present a systematic evaluation of five ensemble-generation strategies applied to a set of eighteen proteins sharing the same two globular domains, connected by naturally occurring linkers of varying length and composition. Modeling methods based on different underlying principles are compared by assessing their agreement to experimental SAXS data, showing a large disparity and systematic structural biases among them. Furthermore, for each approach, we examine the effect of refinement against SAXS restraints and assess its capacity to describe the experimental data, as well as the induced biases in global dimensions and inter-domain distance distributions. This analysis underlines the importance of the initial conformational pool for deriving experimentally compatible ensembles. Overall, this work provides a high-quality benchmark for SAXS-driven ensemble modeling of flexible, multidomain proteins and establishes a framework for the critical interpretation of solution scattering data in systems with pronounced conformational heterogeneity.

Calculation of density maps from atomic models is essential for structural studies using crystallography and electron cryo-microscopy (cryoEM). These maps serve various purposes, including atomic model building, refinement, visualization, and validation. However, accurately comparing model-calculated maps to experimental data poses challenges, particularly because the resolution of cryoEM experimental maps varies across the map. Traditional crystallography methods generate finite-resolution maps with uniform resolution throughout the unit cell volume, while most modern software in cryoEM employ Gaussian-like functions to generate these maps, which does not adequately account for atomic model parameters and resolution. Recent work by Urzhumtsev & Lunin (2022, IUCr Journal, 9, 728-734) introduces a novel method for computing atomic model maps that incorporate local resolution and can be expressed as analytically differentiable functions of all atomic parameters. This approach enhances the accuracy of matching atomic models to experimental maps. In this paper, we detail the implementation of this method in CCTBX and Phenix. SynopsisNew tools implemented in CCTBX and Phenix allow the calculation of variable-resolution maps through a sum of atomic images expressed as analytic functions of all atomic parameters, along with their associated local resolution.

We report the discovery of a new class of local minima that has severely limited the accuracy of macromolecular models. Termed density misfit barrier traps, these minima explain much of the poor fit between macromolecular models and experimental data relative to that of smaller molecules: not just high R factors, but distorted chemical geometry. We postulated that proteins exist as an ensemble of conformations that each have good geometry, but refinement algorithms have been unable to converge to them due to a tangling phenomenon arising from these traps. To demonstrate, a synthetic ground truth data set was generated, consisting of a 2-member ensemble with excellent geometry. A series of starting models, each trapped in increasingly difficult local minima, were prepared, a unified validation score defined, and an open Challenge issued. This Challenge inspired algorithms for escaping such traps, and new programs have been released that are expected to substantially improve the accuracy of macromolecular ensemble models. SynopsisA synthetic 2-member conformational ensemble of a small protein and corresponding electron density data was generated to demonstrate how topological local minima hinder simultaneous agreement with density data and chemical geometry restraints in conventional structure refinement.

As high-performance computing provides the ability to generate and analyze ever larger simulation trajectories, the challenges in learning, applying, and sharing the best analytical practices become more salient. Extracting reproducible scientific insights from simulation requires a thorough understanding of many computing topics unrelated to the molecular systems being modeled and simulated. While the rapid development of the technologies used for analysis makes previously impossible studies into routine work, the growing repertoire of software combined with the specificity of the ecosystems that they rely on can easily break the programs used in older studies. In this work, we present ST-Analyzer, a simulation trajectory analysis suite with command-line (CLI) and graphical (GUI) user interfaces. ST-Analyzer is distributed freely as an open-source conda-forge package with support for macOS, Linux, and Windows (via WSL2). Besides facilitating several common analysis tasks, the GUI shows users the exact commands necessary to repeat the same tasks on the command-line. We demonstrate ST-Analyzers capabilities by reproducing several results from previously published simulation studies on the lipid parameters of heterogeneous biomembranes and the behavior of a SARS-CoV-2 spike protein-antibody complex. We expect ST-Analyzer to be useful to experts for quickly setting up common analysis tasks and to nonexperts as a guided introduction to simulation analysis using both GUI and CLI. ST-Analyzer is freely available at https://github.com/nk53/stanalyzer.

Cryo-Focused Ion Beam Scanning Electron Microscopy (cryoFIB-SEM) using samples fixed by high-pressure freezing uniquely enables high resolution cryo-volume Electron Microscope (cvEM) images of cell ultrastructure to be obtained from whole cells and complex tissues in their near native state. As the freezing process also preserves fluorescence, the link between three-dimensional (3D) ultrastructure and biological process is also enabled by targeted cryo-Correlative Light and Electron Microscopy (CLEM). However, the overall viability of cvEM is challenged by sample preparation, charge balance during imaging, sample sensitivity to beam damage, contamination, and very long acquisition times. Here we detail new experimental workflows to significantly reduce each of these effects and demonstrate the improvement in resolution possible with results from the nematode Caenorhabditis elegans and the ciliated protozoon Paramecium bursaria containing many endosymbiotic algae. These results demonstrate the versatility and potential wide-ranging utility of cvEM for 3D ultrastructural imaging of whole multicellular and unicellular organisms.

Preparing electron-transparent cryo-lamellae is inherently a serial and low-throughput process. Once the lamellae are milled, these thin structures endure both mechanical and thermal stress, and as a result many valuable lamellae crack or even disintegrate entirely. This loss is often regarded as a "lamella tax", i.e. an unavoidable cost of working with such fragile specimens. In this work, we introduce two modifications to the standard lamella-preparation workflow aimed at improving lamella mechanical resistance to crack formation and external stress. The first modification involves milling arrays of perforations directly within the lamella body. These perforations are designed to function as crack-arrest holes, intercepting cracks as they appear and preventing, or at least delaying their further propagation. By slowing crack growth, these features increase the likelihood that the lamella remains intact long enough to complete cryo-TEM imaging. The second modification replaces the conventional rigid attachment of the lamella to the surrounding cellular bulk material with a softer suspension using ring-shaped springs formed by ion beam milling. Mounting the lamella on smooth annular springs provides mechanical compliance both across and along the lamella axis, as well as at intermediate angles and in the out-of-plane direction. This flexibility allows the lamella to accommodate larger stresses and deformations without reaching its mechanical failure threshold. We fabricated a series of test lamellae incorporating different crack-arrest hole geometries, as well as lamellae suspended on soft annular springs. We performed high-resolution cryo-TEM imaging to characterise the perforations themselves and characterised the captured crack geometry within the lamellae at the highest level of detail achieved to date. TEM imaging shows crack interception and guided, non-catastrophic failure paths, while simulations confirm lowered stress in suspended lamellae.

AO_SCPLOWBSTRACTC_SCPLOWThe Martini coarse-grained force field is widely used for biomolecular simulations by a large and rapidly expanding community worldwide. Over time, the development of Martini parameters, tools, and documentation has become increasingly dispersed across numerous research groups, leading to fragmentation and making it challenging for users and developers to keep track of the latest models, software, and best practices. Consequently, the development of Martini as a genuinely community-driven process has grown into a bottleneck. In response, the Martini Force Field Initiative (MFFI) has been established as an open-science effort to coordinate and support the collaborative development of all Martini resources. Here, we introduce the MFFI web portal, a platform designed around five core pillars: (i) avoiding reliance on a single group or local server; (ii) minimizing long-term maintenance overhead; (iii) reducing technical barriers for contributions; (iv) providing a unified home for parameters, tools, tutorials, example workflows, and research outputs; and (v) enabling timely dissemination of updates to the community. To achieve this, we use Quarto to generate a static website authored in Markdown, lowering the technical barrier to making contributions, and serverless architectures on Amazon Web Services for scalable, event-triggered backend operations. The source code is hosted in a public GitHub repository under an MIT license, with automated deployment via GitHub Actions and a contribution model based on pull requests for quality control. This design creates a sustainable, low-maintenance, and collaborative infrastructure that consolidates Martini resources and supports transparency. More broadly, our design exemplifies a transferable pattern for building open, community-oriented platforms for molecular modeling and computational science.

Microtubules are cytoskeletal filaments typically characterized by a discontinuous helical lattice of /{beta}-tubulin heterodimers. Microtubules can also adopt variable lattice architectures both in vitro and in cellular contexts. Pseudo-helical averaging processing strategies have been developed to generate cryo-EM reconstructions of microtubules with and without decorating protein-binding partners, but these pipelines can be difficult to implement for the average user, especially for undecorated filaments. Here, we describe MiCSPARC, a cryo-EM processing pipeline developed around CryoSPARC (Punjani et al., 2017), which leverages automated particle picking and fast 3D refinement times in CryoSPARC to determine structures of both decorated and undecorated microtubules. We generated reconstructions of undecorated GDP microtubules, as well as kinesin-1 motor domain-decorated GMPCPP filaments at resolutions of up to 2.8 [A], demonstrating the robustness of the pipeline. Based on its convenient implementation and ability to routinely generate high-resolution, seam-corrected microtubule reconstructions, MiCSPARC should provide a valuable tool for understanding microtubule dynamics, microtubule-associated proteins, and microtubule-targeting agents.

Filament-forming proteins such as TasA (Bacillus subtilis) and camelysins CalY1, CalY2 (Bacillus cereus) pose a particular challenge for structural analysis due to their strong tendency to self-association and their polydispersity, which severely limits their ability to crystallize or to be a target for NMR-spectroscopy. To address this, it is necessary to modify the amino acid sequence to prevent filamentation. Engineering a series of N- and C-terminal truncated variants by removing flexible parts is often key to success. N-terminal extensions are also a powerful tool for obtaining crystals of fiber-forming proteins.

High-throughput screening and optimization of high-value protein formulations requires intensified measurements to extract a wide range of properties using a small number of measurement techniques, small sample volumes, and short measurement times. We demonstrate how differential dynamic microscopy (DDM) can fill this need by measuring a broad range of key biophysical properties relevant to protein formulations from a single workflow on microliter-scale samples using label-free video optical microscopy. We show that the use of phase contrast imaging dramatically enhances measurement resolution for protein solutions at dilute and semidilute concentrations, enabling measurement of colloidal properties such as protein-protein interactions, protein size, aggregation, and solution viscosity from a single set of measurements. DDM measurements on a representative human immunoglobulin (IgG) system yield estimates for the hydrodynamic radius (Rh), second osmotic virial coefficient (B2), and hydrodynamic interaction (kd) that are consistent with independently measured values, validating the ability of DDM to extract these parameters from a single set of measurements. Observed trends in B2 with pH and ionic strength are consistent with the antibodys charge and screened electrostatics, demonstrating the ability of DDM to provide insight on protein-protein interactions. To show the utility of DDM as a "multitool" for quantifying multiple formulation properties from a single measurement, we use the results to test a predictive colloidal model for the solution viscosity, which is in fair agreement with measurements obtained using DDM-based microrheology. Combined with low sample requirements and short measurement times, DDM thus offers a high-throughput and efficient route to accelerate protein biophysics and formulation development. SIGNIFICANCE STATEMENTThe formulation of stable, high-concentration antibodies and other protein solutions requires extensive biophysical measurements that are often material- and time-intensive. We demonstrate that differential dynamic microscopy (DDM) provides a powerful alternative by providing rapid access to a broad range of industrially relevant colloidal properties from a single measurement on microliter-scale samples using conventional video optical microscopy. This capability makes DDM an attractive, low-resource approach for routine biomolecular formulation screening and optimization.

Efficient protein synthesis in eukaryotic cells typically requires a 5' cap structure on messenger RNAs (mRNAs). However, under stress conditions or in viral infection, translation can also occur independently of the cap via internal ribosomal entry sites (IRES). IRES elements are therefore key regulators of protein expression in both viral and cellular contexts. Here we describe a cell-free protocol to quantitatively assess IRES-mediated translation using wheat germ extract (WGE) and a firefly luciferase (FLuc) reporter. The protocol includes template preparation, RNA synthesis and luminescence measurement following in vitro translation in WGE. This method enables rapid and robust comparison of IRES activity under controlled conditions and can additionally be applied to evaluate mRNA modifications designed to enhance translation efficiency. Key featuresO_LIStringent in vitro workflow from DNA template preparation through RNA synthesis and protein synthesis to reporter readout, including quality controls. C_LIO_LIEvaluation of IRES-driven translation suitable for testing combinations of IRES and CDS. C_LIO_LItranslation analysis without radioactive labeling. C_LI Graphical overview O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/716985v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@417649org.highwire.dtl.DTLVardef@1bcd186org.highwire.dtl.DTLVardef@15fecb3org.highwire.dtl.DTLVardef@acdf8d_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical AbstractPipeline for the production and evaluation of IRES-firefly luciferase constructs using wheat germ extract. (1-4) Preparation: IRES-firefly luciferase constructs are amplified in E. coli and isolated from bacterial cells. Plasmids are linearized to prepare for in vitro transcription. (5-6) Transcript synthesis and verification: In vitro transcription is followed by electrophoretic validation to confirm integrity and correct molecular weight. (7-8) Translation and detection: Translation is executed in wheat germ extract and quantified by measuring reporter activity in a luminometer.

The rational design of biomolecule immobilization strategies requires molecular-level understanding of how surface properties, tethering geometry, and structural dynamics jointly influence stability and function. Recently, coarse-grained molecular dynamics simulations based on the Martini force field have emerged as an efficient framework for studying enzyme-surface interactions. However, the reproducible construction of immobilized systems with controlled orientations remains technically challenging, usually involving multiple computational tools. Here we present MartiniSurf, an open-source command-line framework for the preparation of protein and DNA systems immobilized on solid supports within the Martini paradigm. MartiniSurf integrates automated structure retrieval and cleaning, coarse graining via tools from the Martini force field software ecosystem, customizable surface generation, and biomolecule orientation based on user-defined anchoring residues, producing complete GROMACS-ready simulation systems. The framework supports both implicit restraint-based anchoring and explicit linker-mediated immobilization, including surfaces functionalized with user-defined ligands or linker-like moieties, enabling representation of mono- and multivalent attachment geometries at different modeling resolutions. Structure-based G[o]Martini potentials can be incorporated for proteins, while DNA systems are modeled using Martini 2. Optional substrate insertion, pre-coarse-grained complex handling, and automated solvation and ionization further extend system flexibility. By integrating these components into a unified workflow, MartiniSurf enables systematic and high-throughput in silico exploration of surface-tethered biomolecules and provides a robust computational platform for rational immobilization studies. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=146 SRC="FIGDIR/small/714767v1_ufig1.gif" ALT="Figure 1"> View larger version (45K): org.highwire.dtl.DTLVardef@bc1ac4org.highwire.dtl.DTLVardef@1813b43org.highwire.dtl.DTLVardef@159b19borg.highwire.dtl.DTLVardef@19b60d6_HPS_FORMAT_FIGEXP M_FIG C_FIG