The molecular architecture of Lactobacillus S-layer: Assembly and attachment to teichoic acids.

S-layers are crystalline arrays found on bacterial and archaeal cells. Lactobacillus is a diverse family of bacteria known especially for potential gut health benefits. This study focuses on the S-layer proteins from Lactobacillus acidophilus and Lactobacillus amylovorus common in the mammalian gut. Atomic resolution structures of Lactobacillus S-layer proteins SlpA and SlpX exhibit domain swapping, and the obtained assembly model of the main S-layer protein SlpA aligns well with prior electron microscopy and mutagenesis data. The S-layer's pore size suggests a protective role, with charged areas aiding adhesion. A highly similar domain organization and interaction network are observed across the Lactobacillus genus. Interaction studies revealed conserved binding areas specific for attachment to teichoic acids. The structure of the SlpA S-layer and the suggested incorporation of SlpX as well as its interaction with teichoic acids lay the foundation for deciphering its role in immune responses and for developing effective treatments for a variety of infectious and bacteria-mediated inflammation processes, opening opportunities for targeted engineering of the S-layer or lactobacilli bacteria in general.

Improved AlphaFold modeling with implicit experimental information.

Machine-learning prediction algorithms such as AlphaFold and RoseTTAFold can create remarkably accurate protein models, but these models usually have some regions that are predicted with low confidence or poor accuracy. We hypothesized that by implicitly including new experimental information such as a density map, a greater portion of a model could be predicted accurately, and that this might synergistically improve parts of the model that were not fully addressed by either machine learning or experiment alone. An iterative procedure was developed in which AlphaFold models are automatically rebuilt on the basis of experimental density maps and the rebuilt models are used as templates in new AlphaFold predictions. We show that including experimental information improves prediction beyond the improvement obtained with simple rebuilding guided by the experimental data. This procedure for AlphaFold modeling with density has been incorporated into an automated procedure for interpretation of crystallographic and electron cryo-microscopy maps.

Assessing the utility of CASP14 models for molecular replacement.

The assessment of CASP models for utility in molecular replacement is a measure of their use in a valuable real-world application. In CASP7, the metric for molecular replacement assessment involved full likelihood-based molecular replacement searches; however, this restricted the assessable targets to crystal structures with only one copy of the target in the asymmetric unit, and to those where the search found the correct pose. In CASP10, full molecular replacement searches were replaced by likelihood-based rigid-body refinement of models superimposed on the target using the LGA algorithm, with the metric being the refined log-likelihood-gain (LLG) score. This enabled multi-copy targets and very poor models to be evaluated, but a significant further issue remained: the requirement of diffraction data for assessment. We introduce here the relative-expected-LLG (reLLG), which is independent of diffraction data. This reLLG is also independent of any crystal form, and can be calculated regardless of the source of the target, be it X-ray, NMR or cryo-EM. We calibrate the reLLG against the LLG for targets in CASP14, showing that it is a robust measure of both model and group ranking. Like the LLG, the reLLG shows that accurate coordinate error estimates add substantial value to predicted models. We find that refinement by CASP groups can often convert an inadequate initial model into a successful MR search model. Consistent with findings from others, we show that the AlphaFold2 models are sufficiently good, and reliably so, to surpass other current model generation strategies for attempting molecular replacement phasing.

Metastatic TNBC is closely associated with a fused mitochondrial morphology and a glycolytic and lipogenic metabolism.

Mitochondria modify their function and morphology to satisfy the bioenergetic demand of the cells. Cancer cells take advantage of these features to sustain their metabolic, proliferative, metastatic, and survival necessities. Understanding the morphological changes to mitochondria in the different grades of triple-negative breast cancer (TNBC) could help to design new treatments. Consequently, this research explored mitochondrial morphology and the gene expression of some proteins related to mitochondrial dynamics, as well as proteins associated with oxidative and non-oxidative metabolism in metastatic and non-metastatic TNBC. We found that mitochondrial morphology and metabolism are different in metastatic and non-metastatic TNBC. In metastatic TNBC, there is overexpression of genes related to mitochondrial dynamics, fatty-acid metabolism, and glycolysis. These features are accompanied by a fused mitochondrial morphology. By comparison, in non-metastatic TNBC, there is a stress-associated mitochondrial morphology with hyperfragmented mitochondria, accompanied by the upregulated expression of genes associated with the biogenesis of mitochondria; both of which are characteristics related to the higher production of reactive oxygen species observed in this cell line. These differences between metastatic and non-metastatic TNBC should provide a better understanding of metastasis and contribute to the development of improved specific and personalized therapies for TNBC.

Exolytic and endolytic turnover of peptidoglycan by lytic transglycosylase Slt of Pseudomonas aeruginosa.

ß-Lactam antibiotics inhibit cell-wall transpeptidases, preventing the peptidoglycan, the major constituent of the bacterial cell wall, from cross-linking. This causes accumulation of long non-cross-linked strands of peptidoglycan, which leads to bacterial death. Pseudomonas aeruginosa, a nefarious bacterial pathogen, attempts to repair this aberrantly formed peptidoglycan by the function of the lytic transglycosylase Slt. We document in this report that Slt turns over the peptidoglycan by both exolytic and endolytic reactions, which cause glycosidic bond scission from a terminus or in the middle of the peptidoglycan, respectively. These reactions were characterized with complex synthetic peptidoglycan fragments that ranged in size from tetrasaccharides to octasaccharides. The X-ray structure of the wild-type apo Slt revealed it to be a doughnut-shaped protein. In a series of six additional X-ray crystal structures, we provide insights with authentic substrates into how Slt is enabled for catalysis for both the endolytic and exolytic reactions. The substrate for the exolytic reaction binds Slt in a canonical arrangement and reveals how both the glycan chain and the peptide stems are recognized by the Slt. We document that the apo enzyme does not have a fully formed active site for the endolytic reaction. However, binding of the peptidoglycan at the existing subsites within the catalytic domain causes a conformational change in the protein that assembles the surface for binding of a more expansive peptidoglycan between the catalytic domain and an adjacent domain. The complexes of Slt with synthetic peptidoglycan substrates provide an unprecedented snapshot of the endolytic reaction.

Ega3 from the fungal pathogen Aspergillus fumigatus is an endo-α-1,4-galactosaminidase that disrupts microbial biofilms.

Aspergillus fumigatus is an opportunistic fungal pathogen that causes both chronic and acute invasive infections. Galactosaminogalactan (GAG) is an integral component of the A. fumigatus biofilm matrix and a key virulence factor. GAG is a heterogeneous linear α-1,4-linked exopolysaccharide of galactose and GalNAc that is partially deacetylated after secretion. A cluster of five co-expressed genes has been linked to GAG biosynthesis and modification. One gene in this cluster, ega3, is annotated as encoding a putative α-1,4-galactosaminidase belonging to glycoside hydrolase family 114 (GH114). Herein, we show that recombinant Ega3 is an active glycoside hydrolase that disrupts GAG-dependent A. fumigatus and Pel polysaccharide-dependent Pseudomonas aeruginosa biofilms at nanomolar concentrations. Using MS and functional assays, we demonstrate that Ega3 is an endo-acting α-1,4-galactosaminidase whose activity depends on the conserved acidic residues, Asp-189 and Glu-247. X-ray crystallographic structural analysis of the apo Ega3 and an Ega3-galactosamine complex, at 1.76 and 2.09 Å resolutions, revealed a modified (ß/α)8-fold with a deep electronegative cleft, which upon ligand binding is capped to form a tunnel. Our structural analysis coupled with in silico docking studies also uncovered the molecular determinants for galactosamine specificity and substrate binding at the -2 to +1 binding subsites. The findings in this study increase the structural and mechanistic understanding of the GH114 family, which has >600 members encoded by plant and opportunistic human pathogens, as well as in industrially used bacteria and fungi.

Exploiting tertiary structure through local folds for crystallographic phasing.

We describe an algorithm for phasing protein crystal X-ray diffraction data that identifies, retrieves, refines and exploits general tertiary structural information from small fragments available in the Protein Data Bank. The algorithm successfully phased, through unspecific molecular replacement combined with density modification, all-helical, mixed alpha-beta, and all-beta protein structures. The method is available as a software implementation: Borges.

ARCIMBOLDO_LITE: single-workstation implementation and use.

ARCIMBOLDO solves the phase problem at resolutions of around 2 Šor better through massive combination of small fragments and density modification. For complex structures, this imposes a need for a powerful grid where calculations can be distributed, but for structures with up to 200 amino acids in the asymmetric unit a single workstation may suffice. The use and performance of the single-workstation implementation, ARCIMBOLDO_LITE, on a pool of test structures with 40-120 amino acids and resolutions between 0.54 and 2.2 Šis described. Inbuilt polyalanine helices and iron cofactors are used as search fragments. ARCIMBOLDO_BORGES can also run on a single workstation to solve structures in this test set using precomputed libraries of local folds. The results of this study have been incorporated into an automated, resolution- and hardware-dependent parameterization. ARCIMBOLDO has been thoroughly rewritten and three binaries are now available: ARCIMBOLDO_LITE, ARCIMBOLDO_SHREDDER and ARCIMBOLDO_BORGES. The programs and libraries can be downloaded from http://chango.ibmb.csic.es/ARCIMBOLDO_LITE.

Combining phase information in reciprocal space for molecular replacement with partial models.

ARCIMBOLDO allows ab initio phasing of macromolecular structures below atomic resolution by exploiting the location of small model fragments combined with density modification in a multisolution frame. The model fragments can be either secondary-structure elements predicted from the sequence or tertiary-structure fragments. The latter can be derived from libraries of typical local folds or from related structures, such as a low-homology model that is unsuccessful in molecular replacement. In all ARCIMBOLDO applications, fragments are searched for sequentially. Correct partial solutions obtained after each fragment-search stage but lacking the necessary phasing power can, if combined, succeed. Here, an analysis is presented of the clustering of partial solutions in reciprocal space and of its application to a set of different cases. In practice, the task of combining model fragments from an ARCIMBOLDO run requires their referral to a common origin and is complicated by the presence of correct and incorrect solutions as well as by their not being independent. The F-weighted mean phase difference has been used as a figure of merit. Clustering perfect, non-overlapping fragments dismembered from test structures in polar and nonpolar space groups shows that density modification before determining the relative origin shift enhances its discrimination. In the case of nonpolar space groups, clustering of ARCIMBOLDO solutions from secondary-structure models is feasible. The use of partially overlapping search fragments provides a more favourable circumstance and was assessed on a test case. Applying the devised strategy, a previously unknown structure was solved from clustered correct partial solutions.

Biological screening of select Puerto Rican plants for cytotoxic and antitumor activities.

OBJECTIVE: The objective of this study was to evaluate the cytotoxic and anticancer activities of extracts from 7-species of endemic and native plants from Puerto Rico. METHODS: The plant species selected for this study were Canella winterana, Croton discolor, Goetzea elegans, Guaiacum officinale, Pimenta racemosa, Simarouba tulae, and Thouinia striata. The dried plant material was extracted with a 1:1 mixture of CH2CI2-MeOH. The resulting crude extract was suspended in water and extracted with solvents of different polarities. The extracts were evaluated for their cytotoxic effects against Artemia salina and 3 breast cancer cell lines. RESULTS: About 50% of the extracts evaluated against Artemia salina exhibited LC50 values of less than or equal to 200 µg/mL. The strongest activity was detected in the chloroform and ethyl acetate extracts of Guaiacum officinale, with lethality values below 10 µg/mL. The extracts were further evaluated for their bioactivity as possible inhibitors of several breast cancer cell lines, with the extracts from Simarouba tulae and Croton discolor showing the highest percentages of growth inhibition. The dose- effect data analysis for the crude extracts of the different plants also confirms the high cytotoxicities of Guaiacum officinale, Simarouba tulae, and Croton discolor. CONCLUSION: Based on our results, we concluded that the Simarouba, Croton, and Guaiacum plant extracts show cytotoxic and anticancer activities that merit closer investigation in order to identify the chemical compounds responsible for these bioactivities.

Predictors of standardized in-service examination performance and residency outcomes in a graduate periodontics program.

PURPOSE/OBJECTIVES: The objectives of this study were to assess the influence of learner- and education-related factors on standardized in-service examination performance and determine whether in-service examination scores predict residency outcomes. METHODS: American Academy of Periodontology (AAP) In-service Examination (AIE) scores from 10 periodontics residency classes at a single center were recorded and compared against a panel of learner- and education-related variables using multiple linear regression models. Defined residency outcome measures were analyzed against AIE scores using binomial logistic regression. RESULTS: No evaluated learner- or education-related variable was a statistically significant predictor of AIE score in this study sample. Likewise, AIE score was not a statistically significant predictor of any assessed residency outcome. CONCLUSIONS: The AAP has performed a tremendous service to periodontics residents and programs by marshaling the leadership and expertise necessary to offer a professionally constructed assessment instrument. However, in the current study, no relationship could be identified between AIE score and any outcome, including first-attempt board certification. The AAP In-service Committee appears well situated to provide additional leadership focusing on exam implementation, which may enhance AIE value in competency decision making.

Likelihood-based signal and noise analysis for docking of models into cryo-EM maps.

Fast, reliable docking of models into cryo-EM maps requires understanding of the errors in the maps and the models. Likelihood-based approaches to errors have proven to be powerful and adaptable in experimental structural biology, finding applications in both crystallography and cryo-EM. Indeed, previous crystallographic work on the errors in structural models is directly applicable to likelihood targets in cryo-EM. Likelihood targets in Fourier space are derived here to characterize, based on the comparison of half-maps, the direction- and resolution-dependent variation in the strength of both signal and noise in the data. Because the signal depends on local features, the signal and noise are analysed in local regions of the cryo-EM reconstruction. The likelihood analysis extends to prediction of the signal that will be achieved in any docking calculation for a model of specified quality and completeness. A related calculation generalizes a previous measure of the information gained by making the cryo-EM reconstruction.

Likelihood-based docking of models into cryo-EM maps.

Optimized docking of models into cryo-EM maps requires exploiting an understanding of the signal expected in the data to minimize the calculation time while maintaining sufficient signal. The likelihood-based rotation function used in crystallography can be employed to establish plausible orientations in a docking search. A phased likelihood translation function yields scores for the placement and rigid-body refinement of oriented models. Optimized strategies for choices of the resolution of data from the cryo-EM maps to use in the calculations and the size of search volumes are based on expected log-likelihood-gain scores computed in advance of the search calculation. Tests demonstrate that the new procedure is fast, robust and effective at placing models into even challenging cryo-EM maps.

Fragment-Based Ab Initio Phasing of Peptidic Nanocrystals by MicroED.

Electron diffraction (MicroED/3DED) can render the three-dimensional atomic structures of molecules from previously unamenable samples. The approach has been particularly transformative for peptidic structures, where MicroED has revealed novel structures of naturally occurring peptides, synthetic protein fragments, and peptide-based natural products. Despite its transformative potential, MicroED is beholden to the crystallographic phase problem, which challenges its de novo determination of structures. ARCIMBOLDO, an automated, fragment-based approach to structure determination, eliminates the need for atomic resolution, instead enforcing stereochemical constraints through libraries of small model fragments, and discerning congruent motifs in solution space to ensure validation. This approach expands the reach of MicroED to presently inaccessible peptide structures including fragments of human amyloids, and yeast and mammalian prions. For electron diffraction, fragment-based phasing portends a more general phasing solution with limited model bias for a wider set of chemical structures.

Putting AlphaFold models to work with phenix.process_predicted_model and ISOLDE.

AlphaFold has recently become an important tool in providing models for experimental structure determination by X-ray crystallography and cryo-EM. Large parts of the predicted models typically approach the accuracy of experimentally determined structures, although there are frequently local errors and errors in the relative orientations of domains. Importantly, residues in the model of a protein predicted by AlphaFold are tagged with a predicted local distance difference test score, informing users about which regions of the structure are predicted with less confidence. AlphaFold also produces a predicted aligned error matrix indicating its confidence in the relative positions of each pair of residues in the predicted model. The phenix.process_predicted_model tool downweights or removes low-confidence residues and can break a model into confidently predicted domains in preparation for molecular replacement or cryo-EM docking. These confidence metrics are further used in ISOLDE to weight torsion and atom-atom distance restraints, allowing the complete AlphaFold model to be interactively rearranged to match the docked fragments and reducing the need for the rebuilding of connecting regions.

Structure of the class XI myosin globular tail reveals evolutionary hallmarks for cargo recognition in plants.

The plant-specific class XI myosins (MyoXIs) play key roles at the molecular, cellular and tissue levels, engaging diverse adaptor proteins to transport cargoes along actin filaments. To recognize their cargoes, MyoXIs have a C-terminal globular tail domain (GTD) that is evolutionarily related to those of class V myosins (MyoVs) from animals and fungi. Despite recent advances in understanding the functional roles played by MyoXI in plants, the structure of its GTD, and therefore the molecular determinants for cargo selectivity and recognition, remain elusive. In this study, the first crystal structure of a MyoXI GTD, that of MyoXI-K from Arabidopsis thaliana, was elucidated at 2.35 Šresolution using a low-identity and fragment-based phasing approach in ARCIMBOLDO_SHREDDER. The results reveal that both the composition and the length of the α5-α6 loop are distinctive features of MyoXI-K, providing evidence for a structural stabilizing role for this loop, which is otherwise carried out by a molecular zipper in MyoV GTDs. The crystal structure also shows that most of the characterized cargo-binding sites in MyoVs are not conserved in plant MyoXIs, pointing to plant-specific cargo-recognition mechanisms. Notably, the main elements involved in the self-regulation mechanism of MyoVs are conserved in plant MyoXIs, indicating this to be an ancient ancestral trait.

Accurate prediction of protein structures and interactions using a three-track neural network.

DeepMind presented notably accurate predictions at the recent 14th Critical Assessment of Structure Prediction (CASP14) conference. We explored network architectures that incorporate related ideas and obtained the best performance with a three-track network in which information at the one-dimensional (1D) sequence level, the 2D distance map level, and the 3D coordinate level is successively transformed and integrated. The three-track network produces structure predictions with accuracies approaching those of DeepMind in CASP14, enables the rapid solution of challenging x-ray crystallography and cryo-electron microscopy structure modeling problems, and provides insights into the functions of proteins of currently unknown structure. The network also enables rapid generation of accurate protein-protein complex models from sequence information alone, short-circuiting traditional approaches that require modeling of individual subunits followed by docking. We make the method available to the scientific community to speed biological research.

ALIXE: a phase-combination tool for fragment-based molecular replacement.

Fragment-based molecular replacement exploits the use of very accurate yet incomplete search models. In the case of the ARCIMBOLDO programs, consistent phase sets produced from the placement and refinement of fragments with Phaser can be combined in order to increase their signal before proceeding to the step of density modification and autotracing with SHELXE. The program ALIXE compares multiple phase sets, evaluating mean phase differences to determine their common origin, and subsequently produces sets of combined phases that group consistent solutions. In this work, its use on different scenarios of very partial molecular-replacement solutions and its performance after the development of a much-optimized set of algorithms are described. The program is available both standalone and integrated within the ARCIMBOLDO programs. ALIXE has been analysed to identify its rate-limiting steps while exploring the best parameterization to improve its performance and make this software efficient enough to work on modest hardware. The algorithm has been parallelized and redesigned to meet the typical landscape of solutions. Analysis of pairwise correlation between the phase sets has also been explored to test whether this would provide additional insight. ALIXE can be used to exhaustively analyse all partial solutions produced or to complement those already selected for expansion, and also to reduce the number of redundant solutions, which is particularly relevant to the case of coiled coils, or to combine partial solutions from different programs. In each case parallelization and optimization to provide speedup makes its use amenable to typical hardware found in crystallography. ARCIMBOLDO_BORGES and ARCIMBOLDO_SHREDDER now call on ALIXE by default.

ALEPH: a network-oriented approach for the generation of fragment-based libraries and for structure interpretation.

The analysis of large structural databases reveals general features and relationships among proteins, providing useful insight. A different approach is required to characterize ubiquitous secondary-structure elements, where flexibility is essential in order to capture small local differences. The ALEPH software is optimized for the analysis and the extraction of small protein folds by relying on their geometry rather than on their sequence. The annotation of the structural variability of a given fold provides valuable information for fragment-based molecular-replacement methods, in which testing alternative model hypotheses can succeed in solving difficult structures when no homology models are available or are successful. ARCIMBOLDO_BORGES combines the use of composite secondary-structure elements as a search model with density modification and tracing to reveal the rest of the structure when both steps are successful. This phasing method relies on general fold libraries describing variations around a given pattern of ß-sheets and helices extracted using ALEPH. The program introduces characteristic vectors defined from the main-chain atoms as a way to describe the geometrical properties of the structure. ALEPH encodes structural properties in a graph network, the exploration of which allows secondary-structure annotation, decomposition of a structure into small compact folds, generation of libraries of models representing a variation of a given fold and finally superposition of these folds onto a target structure. These functions are available through a graphical interface designed to interactively show the results of structure manipulation, annotation, fold decomposition, clustering and library generation. ALEPH can produce pictures of the graphs, structures and folds for publication purposes.

Fragment-based determination of a proteinase K structure from MicroED data using ARCIMBOLDO_SHREDDER.

Structure determination of novel biological macromolecules by X-ray crystallography can be facilitated by the use of small structural fragments, some of only a few residues in length, as effective search models for molecular replacement to overcome the phase problem. Independence from the need for a complete pre-existing model with sequence similarity to the crystallized molecule is the primary appeal of ARCIMBOLDO, a suite of programs which employs this ab initio algorithm for phase determination. Here, the use of ARCIMBOLDO is investigated to overcome the phase problem with the electron cryomicroscopy (cryoEM) method known as microcrystal electron diffraction (MicroED). The results support the use of the ARCIMBOLDO_SHREDDER pipeline to provide phasing solutions for a structure of proteinase K from 1.6 Šresolution data using model fragments derived from the structures of proteins sharing a sequence identity of as low as 20%. ARCIMBOLDO_SHREDDER identified the most accurate polyalanine fragments from a set of distantly related sequence homologues. Alternatively, such templates were extracted in spherical volumes and given internal degrees of freedom to refine towards the target structure. Both modes relied on the rotation function in Phaser to identify or refine fragment models and its translation function to place them. Model completion from the placed fragments proceeded through phase combination of partial solutions and/or density modification and main-chain autotracing using SHELXE. The combined set of fragments was sufficient to arrive at a solution that resembled that determined by conventional molecular replacement using the known target structure as a search model. This approach obviates the need for a single, complete and highly accurate search model when phasing MicroED data, and permits the evaluation of large fragment libraries for this purpose.