Density modification of DNAPL using self-demulsifying colloidal biliquid aphron: Kinetics, mechanisms and influencing factors.

Density-modification remediation of dense nonaqueous phase liquid (DNAPL) using colloidal biliquid aphron (CBLA) is an efficient means of enhancing flushing and avoiding the risk of downward migration of DNAPL. However, the use of demulsifier is currently necessary for CBLA to achieve density modification. This leads to issues such as low modification efficiency and the risk of secondary contamination. In this work, we developed a self-demulsifying CBLA (PO-CBLA-S) for density-modification remediation of DNAPL, eliminating the need for external demulsifiers. The self-demulsification process exhibited pseudo-secondary reaction kinetics, achieving densities below 1 g/cm3 for various DNAPLs. Groundwater chemistry parameters (pH, anions, cations, temperature, and humic acid (HA) content) were investigated for their impact on perchloroethylene (PCE) density modification. Cations were found to enhance PO-CBLA-S density modification more than anions. Both strong acidic and alkaline environments promote the density regulation of PCE by PO-CBLA-S, and temperature positively correlates with the efficiency of density modification. High concentrations of HA also have a favorable facilitating effect on the density modification. The mechanisms of self-demulsifying density modification were clarified at the microscale. Surfactant entanglement caused by internal surfactant-solvent interaction decreased the stability of PO-CBLA-S, leading to self-demulsification. This study addresses density modification challenges and provides a theoretical foundation for its groundwater remediation applications.

Deep-learning map segmentation for protein X-ray crystallographic structure determination.

When solving a structure of a protein from single-wavelength anomalous diffraction X-ray data, the initial phases obtained by phasing from an anomalously scattering substructure usually need to be improved by an iterated electron-density modification. In this manuscript, the use of convolutional neural networks (CNNs) for segmentation of the initial experimental phasing electron-density maps is proposed. The results reported demonstrate that a CNN with U-net architecture, trained on several thousands of electron-density maps generated mainly using X-ray data from the Protein Data Bank in a supervised learning, can improve current density-modification methods.

Machine learning approaches to cryoEM density modification differentially affect biomacromolecule and ligand density quality.

The application of machine learning to cryogenic electron microscopy (cryoEM) data analysis has added a valuable set of tools to the cryoEM data processing pipeline. As these tools become more accessible and widely available, the implications of their use should be assessed. We noticed that machine learning map modification tools can have differential effects on cryoEM densities. In this perspective, we evaluate these effects to show that machine learning tools generally improve densities for biomacromolecules while generating unpredictable results for ligands. This unpredictable behavior manifests both in quantitative metrics of map quality and in qualitative investigations of modified maps. The results presented here highlight the power and potential of machine learning tools in cryoEM, while also illustrating some of the risks of their unexamined use.

Modes and model building in SHELXE.

Density modification is a standard step to provide a route for routine structure solution by any experimental phasing method, with single-wavelength or multi-wavelength anomalous diffraction being the most popular methods, as well as to extend fragments or incomplete models into a full solution. The effect of density modification on the starting maps from either source is illustrated in the case of SHELXE. The different modes in which the program can run are reviewed; these include less well known uses such as reading external phase values and weights or phase distributions encoded in Hendrickson-Lattman coefficients. Typically in SHELXE, initial phases are calculated from experimental data, from a partial model or map, or from a combination of both sources. The initial phase set is improved and extended by density modification and, if the resolution of the data and the type of structure permits, polyalanine tracing. As a feature to systematically eliminate model bias from phases derived from predicted models, the trace can be set to exclude the area occupied by the starting model. The trace now includes an extension into the gamma position or hydrophobic and aromatic side chains if a sequence is provided, which is performed in every tracing cycle. Once a correlation coefficient of over 30% between the structure factors calculated from such a trace and the native data indicates that the structure has been solved, the sequence is docked in all model-building cycles and side chains are fitted if the map supports it. The extensions to the tracing algorithm brought in to provide a complete model are discussed. The improvement in phasing performance is assessed using a set of tests.

Facing the phase problem.

The marvel of X-ray crystallography is the beauty and precision of the atomic structures deduced from diffraction patterns. Since these patterns record only amplitudes, phases for the diffracted waves must also be evaluated for systematic structure determination. Thus, we have the phase problem as a central complication, both intellectually for the field and practically so for many analyses. Here, I discuss how we - myself, my laboratory and the diffraction community - have faced the phase problem, considering the evolution of methods for phase evaluation as structural biology developed to the present day. During the explosive growth of macromolecular crystallography, practice in diffraction analysis evolved from a universal reliance on isomorphous replacement to the eventual domination of anomalous diffraction for de novo structure determination. As the Protein Data Bank (PDB) grew and familial relationships among proteins became clear, molecular replacement overtook all other phasing methods; however, experimental phasing remained essential for molecules without obvious precedents, with multi- and single-wavelength anomalous diffraction (MAD and SAD) predominating. While the mathematics-based direct methods had proved to be inadequate for typical macromolecules, they returned to crack substantial selenium substructures in SAD analyses of selenomethionyl proteins. Native SAD, exploiting the intrinsic S and P atoms of biomolecules, has become routine. Selenomethionyl SAD and MAD were the mainstays of structural genomics efforts to populate the PDB with novel proteins. A recent dividend has been paid in the success of PDB-trained artificial intelligence approaches for protein structure prediction. Currently, molecular replacement with AlphaFold models often obviates the need for experimental phase evaluation. For multiple reasons, we are now unfazed by the phase problem. Cryo-EM analysis is an attractive alternative to crystallography for many applications faced by today's structural biologists. It simply finesses the phase problem; however, the principles and procedures of diffraction analysis remain pertinent and are adopted in single-particle cryo-EM studies of biomolecules.

Extending the novel |ρ|-based phasing algorithm to the solution of anomalous scattering substructures from SAD data of protein crystals.

Owing to the importance of the single-wavelength anomalous diffraction (SAD) technique, the recently developed |ρ|-based phasing algorithm (SM,|ρ|) incorporating the inner-pixel preservation (ipp) procedure [Rius & Torrelles (2021). Acta Cryst A77, 339-347] has been adapted to the determination of anomalous scattering substructures and its applicability tested on a series of 12 representative experimental data sets, mostly retrieved from the Protein Data Bank. To give an idea of the suitability of the data sets, the main indicators measuring their quality are also given. The dominant anomalous scatterers are either SeMet or S atoms, or metals/clusters incorporated by soaking. The resulting SAD-adapted algorithm solves the substructures of the test protein crystals quite efficiently.

Density-modification displacement using colloidal biliquid aphron for entrapped DNAPL contaminated aquifer remediation.

Colloidal biliquid aphron (CBLA) is a strong density modifier for dense nonaqueous phase liquids (DNAPLs). However, the underlying mechanisms responsible for density modification and displacement is not yet clear. Here, a series of batch column and sandbox experiments were conducted to achieve substantial removal and irreversible density reduction of tetrachloroethylene (PCE). The mass of PCE retained in the column and sandbox was less than 1% under suitable injection conditions, and the density of PCE in the effluent was less than that of water (fluctuated in the range of 0.74-0.96 g/cm3). The displacement process was controlled by the high viscosity ratio of CBLA to PCE (52.3). The emulsified and dissolved phase of PCE formed after reaction with CBLA, and the light nonaqueous phase liquid (LNAPL) phase formed after injecting demulsifier solution. The phase analysis played a significant role in monitoring the changes in concentration and density of PCE. The density-modification displacement technique using CBLA reduced the mass of residual PCE by a factor of 165 compared to surfactant flushing, and there was no risk of downward migration of PCE. This study contributes to a better remediation of entrapped DNAPL in contaminated aquifer.

Density-regulated remediation of dense non-aqueous phase liquids using colloidal biliquid aphrons (CBLA): Force model of transport and distribution.

Using colloidal biliquid aphrons (CBLAs) for density control has been proved to a promising technology in dense non-aqueous phase liquids (DNAPLs) contaminated aquifer remediation. However, the transport and distribution of CBLAs in aquifer is an urgent issue for actual application in groundwater. Especially considering the fact that CBLAs have a lower density than water. In this work, the role of buoyancy force on CBLA transport in water-saturated sandbox was investigated, and the force model of CBLA in pore space was developed. Furthermore, the density regulation of trichloroethylene (TCE) in sandbox was studied using CBLA. We found that buoyancy plays a significant role compared with other interaction forces in the transport of CBLA, and the sine of the rising angle of CBLA has a significant correlation with the force on CBLA. CBLA at 5 times the volume of TCE displaced the TCE at the bottom of the tank by upward mobility and the maximum concentration dramatically decreased to 31.23 mg/L. These results can be used for predicting the transport of CBLA (as well as other remediation reagents that are less dense than water) in aquifer and are beneficial to the subsequent remediation application of CBLA in actual contaminated sites.

Mechanisms of irreversible density modification using colloidal biliquid aphron for dense nonaqueous phase liquids in contaminated aquifer remediation.

The use of colloidal biliquid aphron (CBLA) as density modifier to reduce the density of dense nonaqueous phase liquids (DNAPLs) irreversibly is an efficient strategy to control the migration of DNAPLs in contaminated aquifers. However, the process and mechanism of the density regulation using CBLA is still not clear and there is still a big gap in the application of CBLA in actual contaminated sites. In this study, we carried out density modification of 5 DNAPLs (nitrobenzene (NB), dichloromethane (DCM), trichloroethylene (TCE), carbon tetrachloride (CTC), perchloroethylene (PCE)) using CBLA and studied the effect of co-existing ions by 3D response surface method. We found that DNAPLs changed to light nonaqueous phase liquids (LNAPLs) and float up after interaction with light organic liquid from CBLA. The density modification process is limited by the demulsificaiton of CBLA and the density of DNAPL itself. Density regulation of DNAPLs followed pseudo-second-order kinetics. The co-existing ions affected the stability of CBLA and the demulsification ability of the demulsifier. Aquifer materials and low temperature did not influence the density control effect of CBLA. This research advances the practical application of density control of DNAPLs using CBLA, and makes important contributions for subsequent combined remediation approach.

Using a partial atomic model from medium-resolution cryo-EM to solve a large crystal structure.

Medium-resolution cryo-electron microscopy maps, in particular when they include a significant number of α-helices, may allow the building of partial models that are useful for molecular-replacement searches in large crystallographic structures when the structures of homologs are not available and experimental phasing has failed. Here, as an example, the solution of the structure of a bacteriophage portal using a partial 30% model built into a 7.8 Šresolution cryo-EM map is shown. Inspection of the self-rotation function allowed the correct oligomerization state to be determined, and density-modification procedures using rotation matrices and a mask based on the cryo-EM structure were critical for solving the structure. A workflow is described that may be applicable to similar cases and this strategy is compared with direct use of the cryo-EM map for molecular replacement.

Density modification of cryo-EM maps.

Density modification uses expectations about features of a map such as a flat solvent and expected distributions of density in the region of the macromolecule to improve individual Fourier terms representing the map. This process transfers information from one part of a map to another and can improve the accuracy of a map. Here, the assumptions behind density modification for maps from electron cryomicroscopy are examined and a procedure is presented that allows the incorporation of model-based information. Density modification works best in cases where unfiltered, unmasked maps with clear boundaries between the macromolecule and solvent are visible, and where there is substantial noise in the map, both in the region of the macromolecule and the solvent. It also is most effective if the characteristics of the map are relatively constant within regions of the macromolecule and the solvent. Model-based information can be used to improve density modification, but model bias can in principle occur. Here, model bias is reduced by using ensemble models that allow an estimation of model uncertainty. A test of model bias is presented that suggests that even if the expected density in a region of a map is specified incorrectly by using an incorrect model, the incorrect expectations do not strongly affect the final map.

The role of surfactants in colloidal biliquid aphrons and their transport in saturated porous medium.

In remediation of dense non-aqueous phase liquids (DNAPLs), colloidal biliquid aphrons (CBLAs) could be added to produce a lower density nonaqueous phase which mitigate downward migration of DNAPL to non-polluted aquifers. There is still a big gap in the application of CBLAs in the remediation of actual polluted sites, especially the absence of relevant studies on its transport behavior in the sites, and its structural model has not been fully verified. These two factors could affect the effectiveness of CBLAs in the underground environment and its effect on density control. In this study, we prepared CBLAs with different surfactants and verified the structural model of CBLA based on their particle size distributions and demulsification performance. We studied the effects of particle concentrations, injection velocities, and porous media size on the migration of CBLA using the breakthrough curves and distribution profiles along the column. Experimental results indicated that surface elasticity of CBLAs was inversely proportional to the concentration of the anionic surfactant sodium dodecyl sulphate (SDS), which led to easier demulsification of CBLA with the increase in SDS concentration. This observation was in agreement with the verified structural model of the CBLA which constitute both internal nonionic and external anionic surfactants. Furthermore, CBLA deposition is mainly caused by interception and is not suitable for application in fine media. Low concentration of CBLA and high injection flow rate help CBLA to form a remediation area with a certain radius. This study solved the problem of DNAPLs in contaminated groundwater from the perspective of density regulation, and made contributions towards the development of combined remediation approaches using CBLAs.

Fragon: rapid high-resolution structure determination from ideal protein fragments.

Correctly positioning ideal protein fragments by molecular replacement presents an attractive method for obtaining preliminary phases when no template structure for molecular replacement is available. This has been exploited in several existing pipelines. This paper presents a new pipeline, named Fragon, in which fragments (ideal α-helices or ß-strands) are placed using Phaser and the phases calculated from these coordinates are then improved by the density-modification methods provided by ACORN. The reliable scoring algorithm provided by ACORN identifies success. In these cases, the resulting phases are usually of sufficient quality to enable automated model building of the entire structure. Fragon was evaluated against two test sets comprising mixed α/ß folds and all-ß folds at resolutions between 1.0 and 1.7 Å. Success rates of 61% for the mixed α/ß test set and 30% for the all-ß test set were achieved. In almost 70% of successful runs, fragment placement and density modification took less than 30 min on relatively modest four-core desktop computers. In all successful runs the best set of phases enabled automated model building with ARP/wARP to complete the structure.

An introduction to experimental phasing of macromolecules illustrated by SHELX; new autotracing features.

For the purpose of this article, experimental phasing is understood to mean the determination of macromolecular structures by exploiting small intensity differences of Friedel opposites and possibly of reflections measured at different wavelengths or for heavy-atom derivatives, without the use of specific structural models. The SHELX programs provide a robust and efficient route for routine structure solution by the SAD, MAD and related methods, but involve a number of simplifying assumptions that may limit their applicability in borderline cases. The substructure atoms (i.e. those with significant anomalous scattering) are first located by direct methods, and the experimental data are then used to estimate phase shifts that are added to the substructure phases to obtain starting phases for the native reflections. These are then improved by density modification and, if the resolution of the data and the type of structure permit, polyalanine tracing. A number of extensions to the tracing algorithm are discussed; these are designed to improve its performance at low resolution. Given native data to 2.5 Šresolution or better, a correlation coefficient greater than 25% between the structure factors calculated from such a trace and the native data is usually a good indication that the structure has been solved.

Building the atomic model of a boreal lake virus of unknown fold in a 3.9 Šcryo-EM map.

We report here the protocol adopted to build the atomic model of the newly discovered virus FLiP (Flavobacterium infecting, lipid-containing phage) into 3.9 Šcryo-electron microscopy (cryo-EM) maps. In particular, this report discusses the combination of density modification procedures, automatic model building and bioinformatics tools applied to guide the tracing of the major capsid protein (MCP) of this virus. The protocol outlined here may serve as a reference for future structural determination by cryo-EM of viruses lacking detectable structural homologues.

Experimental Phasing: Substructure Solution and Density Modification as Implemented in SHELX.

This chapter describes experimental phasing methods as implemented in SHELX. After introducing fundamental concepts underlying all experimental phasing approaches, the methods used by SHELXC/D/E are described in greater detail, such as dual-space direct methods, Patterson seeding and density modification with the sphere of influence algorithm. Intensity differences from data for experimental phasing can also be used for the generation and usage of difference maps with ANODE for validation and phasing purposes. A short section describes how molecular replacement can be combined with experimental phasing methods. The second half covers practical challenges, such as prerequisites for successful experimental phasing, evaluation of potential solutions, and what to do if substructure search or density modification fails. It is also shown how auto-tracing in SHELXE can improve automation and how it ties in with automatic model building after phasing.

The Quick and the Dead: A Guide to Fast Phasing of Small Ribozyme and Riboswitch Crystal Structures.

Ribozymes and riboswitches are examples of non-protein-coding (nc)RNA molecules that achieve biological activity by adopting complex three-dimensional folds. Visualization of such molecules at near-atomic resolution can enhance our understanding of how chemical groups are organized spatially, thereby providing novel insight into function. This approach has its challenges, which mainly entail sample crystallization followed by the application of empirical, structure-determination methods that often include experimental "phasing" of X-ray diffraction data. A paucity of high-quality crystals or a low symmetry space group are factors that demand rapid assessment of phasing potential during an ongoing experiment in order to assure a successful outcome. Here we describe the process of evaluating the anomalous signal-to-noise as a prelude to single wavelength or multiwavelength anomalous diffraction (SAD or MAD) phasing. Test cases include an autolytic 62-mer RNA enzyme known as the hairpin ribozyme, and a 33-mer riboswitch that binds the modified guanine metabolite preQ1. The crystals were derivatized with iridium (III) hexammine and osmium (III) pentaammine triflate, respectively. Each data set was then subjected to the XPREP and SHELX programs to assess the anomalous signal-to-noise and to locate the heavy-atom substructure. Subsequent noise filtering was conducted in SHELXE or RESOLVE. The methods described are applicable to the rapid phasing of RNA X-ray diffraction data, and contrast the efficacy of in-house X-rays with those attainable from synchrotron-radiation sources in terms of the potential to plan for and execute an experimental structure determination.

Atomic resolution experimental phase information reveals extensive disorder and bound 2-methyl-2,4-pentanediol in Ca(2+)-calmodulin.

Calmodulin (CaM) is the primary calcium signaling protein in eukaryotes and has been extensively studied using various biophysical techniques. Prior crystal structures have noted the presence of ambiguous electron density in both hydrophobic binding pockets of Ca(2+)-CaM, but no assignment of these features has been made. In addition, Ca(2+)-CaM samples many conformational substates in the crystal and accurately modeling the full range of this functionally important disorder is challenging. In order to characterize these features in a minimally biased manner, a 1.0 Å resolution single-wavelength anomalous diffraction data set was measured for selenomethionine-substituted Ca(2+)-CaM. Density-modified electron-density maps enabled the accurate assignment of Ca(2+)-CaM main-chain and side-chain disorder. These experimental maps also substantiate complex disorder models that were automatically built using low-contour features of model-phased electron density. Furthermore, experimental electron-density maps reveal that 2-methyl-2,4-pentanediol (MPD) is present in the C-terminal domain, mediates a lattice contact between N-terminal domains and may occupy the N-terminal binding pocket. The majority of the crystal structures of target-free Ca(2+)-CaM have been derived from crystals grown using MPD as a precipitant, and thus MPD is likely to be bound in functionally critical regions of Ca(2+)-CaM in most of these structures. The adventitious binding of MPD helps to explain differences between the Ca(2+)-CaM crystal and solution structures and is likely to favor more open conformations of the EF-hands in the crystal.

Iterative projection algorithms in protein crystallography. II. Application.

Iterative projection algorithms (IPAs) are a promising tool for protein crystallographic phase determination. Although related to traditional density-modification algorithms, IPAs have better convergence properties, and, as a result, can effectively overcome the phase problem given modest levels of structural redundancy. This is illustrated by applying IPAs to determine the electron densities of two protein crystals with fourfold non-crystallographic symmetry, starting with only the experimental diffraction amplitudes, a low-resolution molecular envelope and the position of the non-crystallographic axes. The algorithm returns electron densities that are sufficiently accurate for model building, allowing automated recovery of the known structures. This study indicates that IPAs should find routine application in protein crystallography, being capable of reconstructing electron densities starting with very little initial phase information.

FEM: feature-enhanced map.

A method is presented that modifies a 2mFobs - DFmodel σA-weighted map such that the resulting map can strengthen a weak signal, if present, and can reduce model bias and noise. The method consists of first randomizing the starting map and filling in missing reflections using multiple methods. This is followed by restricting the map to regions with convincing density and the application of sharpening. The final map is then created by combining a series of histogram-equalized intermediate maps. In the test cases shown, the maps produced in this way are found to have increased interpretability and decreased model bias compared with the starting 2mFobs - DFmodel σA-weighted map.