Microbial ß-Galactosidases of industrial importance: Computational studies on the effects of point mutations on the lactose hydrolysis reaction.

Hydrolysis efficiency of ß-galactosidases is affected due to a strong inhibition by galactose, hampering the complete lactose hydrolysis. One alternative to reduce this inhibition is to perform mutations in the enzyme's active site. The aim of this study was to evaluate the effect of point mutations on the active site of different microbial ß-galactosidases, using computational techniques. The enzymes of Aspergillus niger (AnßGal), Aspergillus oryzae (AoßGal), Bacillus circulans (BcßGal), Bifidobacterium bifidum (BbßGal), and Kluyveromyces lactis (KlßGal) were used. The mutations were carried out in all residues that were up to 4.5 Å from the galactose/lactose molecules and binding energy was computed. The mutants Tyr96Ala (AnßGal), Asn140Ala and Asn199Ala (AoßGal), Arg111Ala and Glu355Ala (BcßGal), Arg122Ala and Phe358Ala (BbßGal), Tyr523Ala, Phe620Ala, and Trp582Ala (KlßGal) had the best results, with higher effect on galactose binding energy and lower effect on lactose affinity. To maximize enzyme reactions by reducing galactose affinity, double mutations were proposed for BcßGal, BbßGal, and KlßGal. The double mutations in BcßGal and BbßGal caused the highest reduction in galactose affinity, while no satisfactory results were observed to KlßGal. Using computational tools, mutants that reduced galactose affinity without significantly affecting lactose binding were proposed. The mutations proposed can be used to reduce the negative feedback process, improving the catalytic characteristics of ß-galactosidases and rendering them promising for industrial applications.

Rapid mechanochemical encapsulation of biocatalysts into robust metal-organic frameworks.

Metal-organic frameworks (MOFs) have recently garnered consideration as an attractive solid substrate because the highly tunable MOF framework can not only serve as an inert host but also enhance the selectivity, stability, and/or activity of the enzymes. Herein, we demonstrate the advantages of using a mechanochemical strategy to encapsulate enzymes into robust MOFs. A range of enzymes, namely ß-glucosidase, invertase, ß-galactosidase, and catalase, are encapsulated in ZIF-8, UiO-66-NH2, or Zn-MOF-74 via a ball milling process. The solid-state mechanochemical strategy is rapid and minimizes the use of organic solvents and strong acids during synthesis, allowing the encapsulation of enzymes into three prototypical robust MOFs while maintaining enzymatic biological activity. The activity of encapsulated enzyme is demonstrated and shows increased resistance to proteases, even under acidic conditions. This work represents a step toward the creation of a suite of biomolecule-in-MOF composites for application in a variety of industrial processes.

A Super-Clustering Approach for Fully Automated Single Particle Picking in Cryo-EM.

Structure determination of proteins and macromolecular complexes by single-particle cryo-electron microscopy (cryo-EM) is poised to revolutionize structural biology. An early challenging step in the cryo-EM pipeline is the detection and selection of particles from two-dimensional micrographs (particle picking). Most existing particle-picking methods require human intervention to deal with complex (irregular) particle shapes and extremely low signal-to-noise ratio (SNR) in cryo-EM images. Here, we design a fully automated super-clustering approach for single particle picking (SuperCryoEMPicker) in cryo-EM micrographs, which focuses on identifying, detecting, and picking particles of the complex and irregular shapes in micrographs with extremely low signal-to-noise ratio (SNR). Our method first applies advanced image processing procedures to improve the quality of the cryo-EM images. The binary mask image-highlighting protein particles are then generated from each individual cryo-EM image using the super-clustering (SP) method, which improves upon base clustering methods (i.e., k-means, fuzzy c-means (FCM), and intensity-based cluster (IBC) algorithm) via a super-pixel algorithm. SuperCryoEMPicker is tested and evaluated on micrographs of ß-galactosidase and 80S ribosomes, which are examples of cryo-EM data exhibiting complex and irregular particle shapes. The results show that the super-particle clustering method provides a more robust detection of particles than the base clustering methods, such as k-means, FCM, and IBC. SuperCryoEMPicker automatically and effectively identifies very complex particles from cryo-EM images of extremely low SNR. As a fully automated particle detection method, it has the potential to relieve researchers from laborious, manual particle-labeling work and therefore is a useful tool for cryo-EM protein structure determination.

Single-particle reconstruction statistics: a diagnostic tool in solving biomolecular structures by cryo-EM.

In single-particle analysis (SPA), the aim is to obtain a 3D reconstruction of a biological molecule from 2D electron micrographs to the highest level of detail or resolution as possible. Current practice is to collect large volumes of data, hoping to reach high-resolution maps through sheer numbers. However, adding more particles from a specific data set eventually leads to diminishing improvements in resolution. Understanding what these resolution limits are and how to deal with them are important in optimization and automation of SPA. This study revisits the theory of 3D reconstruction and demonstrates how the associated statistics can provide a diagnostic tool to improve SPA. Small numbers of images already give sufficient information on micrograph quality and the amount of data required to reach high resolution. Such feedback allows the microscopist to improve sample-preparation and imaging parameters before committing to extensive data collection. Once a larger data set is available, a B factor can be determined describing the suppression of the signal owing to one or more causes, such as specimen movement, radiation damage, alignment inaccuracy and structural variation. Insight into the causes of signal suppression can then guide the user to consider appropriate actions to obtain better reconstructions.

A particle-filter framework for robust cryo-EM 3D reconstruction.

Single-particle electron cryomicroscopy (cryo-EM) involves estimating a set of parameters for each particle image and reconstructing a 3D density map; robust algorithms with accurate parameter estimation are essential for high resolution and automation. We introduce a particle-filter algorithm for cryo-EM, which provides high-dimensional parameter estimation through a posterior probability density function (PDF) of the parameters given in the model and the experimental image. The framework uses a set of random support points to represent such a PDF and assigns weighting coefficients not only among the parameters of each particle but also among different particles. We implemented the algorithm in a new program named THUNDER, which features self-adaptive parameter adjustment, tolerance to bad particles, and per-particle defocus refinement. We tested the algorithm by using cryo-EM datasets for the cyclic-nucleotide-gated (CNG) channel, the proteasome, ß-galactosidase, and an influenza hemagglutinin (HA) trimer, and observed substantial improvement in resolution.

APPLE picker: Automatic particle picking, a low-effort cryo-EM framework.

Particle picking is a crucial first step in the computational pipeline of single-particle cryo-electron microscopy (cryo-EM). Selecting particles from the micrographs is difficult especially for small particles with low contrast. As high-resolution reconstruction typically requires hundreds of thousands of particles, manually picking that many particles is often too time-consuming. While template-based particle picking is currently a popular approach, it may suffer from introducing manual bias into the selection process. In addition, this approach is still somewhat time-consuming. This paper presents the APPLE (Automatic Particle Picking with Low user Effort) picker, a simple and novel approach for fast, accurate, and template-free particle picking. This approach is evaluated on publicly available datasets containing micrographs of ß-galactosidase, T20S proteasome, 70S ribosome and keyhole limpet hemocyanin projections.

cryoem-cloud-tools: A software platform to deploy and manage cryo-EM jobs in the cloud.

Access to streamlined computational resources remains a significant bottleneck for new users of cryo-electron microscopy (cryo-EM). To address this, we have developed tools that will submit cryo-EM analysis routines and atomic model building jobs directly to Amazon Web Services (AWS) from a local computer or laptop. These new software tools ("cryoem-cloud-tools") have incorporated optimal data movement, security, and cost-saving strategies, giving novice users access to complex cryo-EM data processing pipelines. Integrating these tools into the RELION processing pipeline and graphical user interface we determined a 2.2 Šstructure of ß-galactosidase in ∼55 h on AWS. We implemented a similar strategy to submit Rosetta atomic model building and refinement to AWS. These software tools dramatically reduce the barrier for entry of new users to cloud computing for cryo-EM and are freely available at cryoem-tools.cloud.

On the interpretation of electron microscopic maps of biological macromolecules.

The images of flash-frozen biological macromolecules produced by cryo-electron microscopy (EM) can be used to generate accurate, three-dimensional, electric potential maps for these molecules that resemble X-ray-derived electron density maps. However, unlike electron density maps, electric potential maps can include negative features that might for example represent the negatively charged, backbone phosphate groups of nucleic acids or protein carboxylate side chains, which can complicate their interpretation. This study examines the images of groups that include charged atoms that appear in recently-published, high-resolution EM potential maps of the ribosome and ß-galactosidase. Comparisons of simulated maps of these same groups with their experimental counterparts highlight the impact that charge has on the appearance of electric potential maps.

Direct Electron Detectors.

Direct electron detectors have played a key role in the recent increase in the power of single-particle electron cryomicroscopy (cryoEM). In this chapter, we summarize the background to these recent developments, give a practical guide to their optimal use, and discuss future directions.

Processing of Structurally Heterogeneous Cryo-EM Data in RELION.

This chapter describes algorithmic advances in the RELION software, and how these are used in high-resolution cryo-electron microscopy (cryo-EM) structure determination. Since the presence of projections of different three-dimensional structures in the dataset probably represents the biggest challenge in cryo-EM data processing, special emphasis is placed on how to deal with structurally heterogeneous datasets. As such, this chapter aims to be of practical help to those who wish to use RELION in their cryo-EM structure determination efforts.

Testing the Validity of Single-Particle Maps at Low and High Resolution.

Single-particle electron cryomicroscopy may be used to determine the structure of biological assemblies by aligning and averaging low-contrast projection images recorded in the electron microscope. Recent progress in both experimental and computational methods has led to higher resolution three-dimensional maps, including for more challenging low molecular weight proteins, and this has highlighted the problems of model bias and over-fitting during iterative refinement that can potentially lead to incorrect map features at low or high resolution. This chapter discusses the principles and practice of specific validation tests that demonstrate the consistency of a 3D map with projection images. In addition, the chapter describes tests that detect over-fitting during refinement and lead to more robust assessment of both global and local map resolution. Application of several of these tests together demonstrates the reliability of single-particle maps that underpins their correct biological interpretation.

Tools for Model Building and Optimization into Near-Atomic Resolution Electron Cryo-Microscopy Density Maps.

Electron cryo-microscopy (cryoEM) has advanced dramatically to become a viable tool for high-resolution structural biology research. The ultimate outcome of a cryoEM study is an atomic model of a macromolecule or its complex with interacting partners. This chapter describes a variety of algorithms and software to build a de novo model based on the cryoEM 3D density map, to optimize the model with the best stereochemistry restraints and finally to validate the model with proper protocols. The full process of atomic structure determination from a cryoEM map is described. The tools outlined in this chapter should prove extremely valuable in revealing atomic interactions guided by cryoEM data.

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps.

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of ß-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.

Semi-automated selection of cryo-EM particles in RELION-1.3.

The selection of particles suitable for high-resolution cryo-EM structure determination from noisy micrographs may represent a tedious and time-consuming step. Here, a semi-automated particle selection procedure is presented that has been implemented within the open-source software RELION. At the heart of the procedure lies a fully CTF-corrected template-based picking algorithm, which is supplemented by a fast sorting algorithm and reference-free 2D class averaging to remove false positives. With only limited user-interaction, the proposed procedure yields results that are comparable to manual particle selection. Together with an improved graphical user interface, these developments further contribute to turning RELION from a stand-alone refinement program into a convenient image processing pipeline for the entire single-particle approach.

Cryo-EM enters a new era.

Advances in detector hardware and image-processing software have led to a revolution in the use of electron cryo-microscopy to determine complex molecular structures at high resolution.

Beam-induced motion correction for sub-megadalton cryo-EM particles.

In electron cryo-microscopy (cryo-EM), the electron beam that is used for imaging also causes the sample to move. This motion blurs the images and limits the resolution attainable by single-particle analysis. In a previous Research article (Bai et al., 2013) we showed that correcting for this motion by processing movies from fast direct-electron detectors allowed structure determination to near-atomic resolution from 35,000 ribosome particles. In this Research advance article, we show that an improved movie processing algorithm is applicable to a much wider range of specimens. The new algorithm estimates straight movement tracks by considering multiple particles that are close to each other in the field of view, and models the fall-off of high-resolution information content by radiation damage in a dose-dependent manner. Application of the new algorithm to four data sets illustrates its potential for significantly improving cryo-EM structures, even for particles that are smaller than 200 kDa.

Structure of ß-galactosidase at 3.2-Å resolution obtained by cryo-electron microscopy.

We report the solution structure of Escherichia coli ß-galactosidase (∼465 kDa), solved at ∼3.2-Å resolution by using single-particle cryo-electron microscopy (cryo-EM). Densities for most side chains, including those of residues in the active site, and a catalytic Mg(2+) ion can be discerned in the map obtained by cryo-EM. The atomic model derived from our cryo-EM analysis closely matches the 1.7-Å crystal structure with a global rmsd of ∼0.66 Å. There are significant local differences throughout the protein, with clear evidence for conformational changes resulting from contact zones in the crystal lattice. Inspection of the map reveals that although densities for residues with positively charged and neutral side chains are well resolved, systematically weaker densities are observed for residues with negatively charged side chains. We show that the weaker densities for negatively charged residues arise from their greater sensitivity to radiation damage from electron irradiation as determined by comparison of density maps obtained by using electron doses ranging from 10 to 30 e(-)/Å(2). In summary, we establish that it is feasible to use cryo-EM to determine near-atomic resolution structures of protein complexes (<500 kDa) with low symmetry, and that the residue-specific radiation damage that occurs with increasing electron dose can be monitored by using dose fractionation tools available with direct electron detector technology.

Tilt-pair analysis of images from a range of different specimens in single-particle electron cryomicroscopy.

The comparison of a pair of electron microscope images recorded at different specimen tilt angles provides a powerful approach for evaluating the quality of images, image-processing procedures, or three-dimensional structures. Here, we analyze tilt-pair images recorded from a range of specimens with different symmetries and molecular masses and show how the analysis can produce valuable information not easily obtained otherwise. We show that the accuracy of orientation determination of individual single particles depends on molecular mass, as expected theoretically since the information in each particle image increases with molecular mass. The angular uncertainty is less than 1° for particles of high molecular mass (~50 MDa), several degrees for particles in the range 1-5 MDa, and tens of degrees for particles below 1 MDa. Orientational uncertainty may be the major contributor to the effective temperature factor (B-factor) describing contrast loss and therefore the maximum resolution of a structure determination. We also made two unexpected observations. Single particles that are known to be flexible showed a wider spread in orientation accuracy, and the orientations of the largest particles examined changed by several degrees during typical low-dose exposures. Smaller particles presumably also reorient during the exposure; hence, specimen movement is a second major factor that limits resolution. Tilt pairs thus enable assessment of orientation accuracy, map quality, specimen motion, and conformational heterogeneity. A convincing tilt-pair parameter plot, where 60% of the particles show a single cluster around the expected tilt axis and tilt angle, provides confidence in a structure determined using electron cryomicroscopy.

Temperature alternation by an on-chip microheater to reveal enzymatic activity of beta-galactosidase at high temperatures.

A method to measure enzymatic activity at high temperatures by rapid temperature alternation of a microreactor with a microheater is proposed. On-chip microreactor and microheater were integrated on a glass plate by MEMS technology; this microheater can control the temperature of the microreactor with a response speed of 34.2 and 31.5 K/s for temperature rise and fall, respectively, with an accuracy of 3 degrees C. The enzyme, beta-galactosidase, was revealed to survive short exposure (4-s pulses) to temperatures above that which would "normally" denature them. Its activity at 60 degrees C was revealed to be approximately 4 times greater than that at room temperature. This method not only gives new kinetic information in biochemistry but also enables application in highly sensitive biosensors.

Improved preservation of X-gal reaction product for electron microscopy using hydroxypropyl methacrylate.

In lineage tracing analysis, the beta-galactosidase (beta-gal) gene is a commonly used as a reporter gene because it is relatively stable and highly sensitive in histochemical detection using 5-bromo-4-chloro-3-indolyl-beta-d-galactoside (X-gal). Clear determination of the types and characteristics of labeled cells requires transmission electron microscopic (TEM) examination of their morphology. X-gal staining, which involves the precipitate formed by the reaction between beta-gal and X-gal, is usually recognized as a light blue or green reaction product on light microscopic (LM) examination. However, the standard protocol for TEM preparation weakens the intensity of or results in the loss of X-gal reaction product at the step of substitution of ethanol with Epon using propylene oxide. To solve this problem, we show that hydroxypropyl methacrylate achieves good preservation of X-gal reaction products. The protocol presented here appears to be useful for lineage determination by TEM of all types of X-gal-stained tissues.