Induced-fit tightens pleuromutilins binding to ribosomes and remote interactions enable their selectivity
Abstract not provided
Davidovich, Chen↗
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Skip residues modulate the structural properties of the myosin rod and guide thick filament assembly
The rod of sarcomeric myosins directs thick filament assembly and is characterized by the insertion of four skip residues that introduce discontinuities in the coiled-coil heptad repeats. We report in this paper that the regions surrounding the first three skip residues share high structural similarity despite their low sequence homology. Near each of these skip residues, the coiled-coil transitions to a nonclose-packed structure inducing local relaxation of the superhelical pitch. Moreover, molecular dynamics suggest that these distorted regions can assume different conformationally stable states. In contrast, the last skip residue region constitutes a true molecular hinge, providing C-terminal rod flexibility. Assembly of myosin with mutated skip residues in cardiomyocytes shows that the functional importance of each skip residue is associated with rod position and reveals the unique role of the molecular hinge in promoting myosin antiparallel packing. By defining the biophysical properties of the rod, the structures and molecular dynamic calculations presented here provide insight into thick filament formation, and highlight the structural differences occurring between the coiled-coils of myosin and the stereotypical tropomyosin. Finally, in addition to extending our knowledge into the conformational and biological properties of coiled-coil discontinuities, the molecular characterization of the four myosin skip residues also provides a guide to modeling the effects of rod mutations causing cardiac and skeletal myopathies.
59 BASIC BIOLOGICAL SCIENCES↗
Avilamycin and evernimicin induce structural changes in rProteins uL16 and CTC that enhance the inhibition of A-site tRNA binding
Two structurally unique ribosomal antibiotics belonging to the orthosomycin family, avilamycin and evernimicin, possess activity against Enterococci, Staphylococci, and Streptococci, and other Gram-positive bacteria. Here, we describe the high-resolution crystal structures of the eubacterial large ribosomal subunit in complex with them. Their extended binding sites span the A-tRNA entrance corridor, thus inhibiting protein biosynthesis by blocking the binding site of the A-tRNA elbow, a mechanism not shared with other known antibiotics. Along with using the ribosomal components that bind and discriminate the A-tRNA—namely, ribosomal RNA (rRNA) helices H89, H91, and ribosomal proteins (rProtein) uL16—these structures revealed novel interactions with domain 2 of the CTC protein, a feature typical to various Gram-positive bacteria. Furthermore, analysis of these structures explained how single nucleotide mutations and methylations in helices H89 and H91 confer resistance to orthosomycins and revealed the sequence variations in 23S rRNA nucleotides alongside the difference in the lengths of the eukaryotic and prokaryotic α1 helix of protein uL16 that play a key role in the selectivity of those drugs. Here, the accurate interpretation of the crystal structures that could be performed beyond that recently reported in cryo-EM models provide structural insights that may be useful for the design of novel pathogen-specific antibiotics, and for improving the potency of orthosomycins. Because both drugs are extensively metabolized in vivo, their environmental toxicity is very low, thus placing them at the frontline of drugs with reduced ecological hazards.
59 BASIC BIOLOGICAL SCIENCES↗
Emergence of granular-sized magnetic bubbles through the solar atmosphere. I. Spectropolarimetric observations and simulations
We study a granular-sized magnetic flux emergence event that occurred in NOAA 11024 in 2009 July. The observations were made with the CRISP spectropolarimeter at the Swedish 1 m Solar Telescope achieving a spatial resolution of 0.''14. Simultaneous full Stokes observations of the two photospheric Fe I lines at 630.2 nm and the chromospheric Ca II 854.2 nm line allow us to describe in detail the emergence process across the solar atmosphere. We report here on three-dimensional (3D) semi-spherical bubble events, where instead of simple magnetic footpoints, we observe complex semi-circular feet straddling a few granules. Several phenomena occur simultaneously, namely, abnormal granulation, separation of opposite-polarity legs, and brightenings at chromospheric heights. However, the most characteristic signature in these events is the observation of a dark bubble in filtergrams taken in the wings of the Ca II 854.2 nm line. There is a clear coincidence between the emergence of horizontal magnetic field patches and the formation of the dark bubble. We can infer how the bubble rises through the solar atmosphere as we see it progressing from the wings to the core of Ca II 854.2 nm. In the photosphere, the magnetic bubble shows mean upward Doppler velocities of 2 km s{sup –1} and expands at a horizontal speed of 4 km s{sup –1}. In about 3.5 minutes it travels some 1100 km to reach the mid chromosphere, implying an average ascent speed of 5.2 km s{sup –1}. The maximum separation attained by the magnetic legs is 6.''6. From an inversion of the observed Stokes spectra with the SIR code, we find maximum photospheric field strengths of 480 G and inclinations of nearly 90° in the magnetic bubble interior, along with temperature deficits of up to 250 K at log τ = –2 and above. To aid the interpretation of the observations, we carry out 3D numerical simulations of the evolution of a horizontal, untwisted magnetic flux sheet injected in the convection zone, using the Bifrost code. The computational domain spans from the upper convection zone to the lower corona. In the modeled chromosphere, the rising flux sheet produces a large, cool, magnetized bubble. We compare this bubble with the observed ones and find excellent agreement, including similar field strengths and velocity signals in the photosphere and chromosphere, temperature deficits, ascent speeds, expansion velocities, and lifetimes.
79 ASTRONOMY AND ASTROPHYSICS↗
EMERGENCE OF GRANULAR-SIZED MAGNETIC BUBBLES THROUGH THE SOLAR ATMOSPHERE. II. NON-LTE CHROMOSPHERIC DIAGNOSTICS AND INVERSIONS
Magnetic flux emergence into the outer layers of the Sun is a fundamental mechanism for releasing energy into the chromosphere and the corona. In this paper, we study the emergence of granular-sized flux concentrations and the structuring of the corresponding physical parameters and atmospheric diagnostics in the upper photosphere and in the chromosphere. We make use of a realistic 3D MHD simulation of the outer layers of the Sun to study the formation of the Ca ii 8542 line. We also derive semi-empirical 3D models from non-LTE inversions of our observations. These models contain information on the line-of-sight stratifications of temperature, velocity, and the magnetic field. Our analysis explains the peculiar Ca ii 8542 Å profiles observed in the flux emerging region. Additionally, we derive detailed temperature and velocity maps describing the ascent of a magnetic bubble from the photosphere to the chromosphere. The inversions suggest that, in active regions, granular-sized bubbles emerge up to the lower chromosphere where the existing large-scale field hinders their ascent. We report hints of heating when the field reaches the chromosphere.
79 ASTRONOMY AND ASTROPHYSICS↗
OpenMDlr: parallel, open-source tools for general protein structure modeling and refinement from pairwise distances
Easy-to-use, open-source, general-purpose programs for modeling a protein structure from inter-atomic distances are needed for modeling from experimental data and refinement of predicted protein structures. OpenMDlr is an open-source Python package for modeling protein structures from pairwise distances between any atoms, and optionally, dihedral angles. Finally, we provide a user-friendly input format for harnessing modern biomolecular force fields in an easy-to-install package that can efficiently make use of multiple compute cores.
59 BASIC BIOLOGICAL SCIENCES↗
Predicted structural proteome of Sphagnum divinum and proteome-scale annotation
Sphagnum-dominated peatlands store a substantial amount of terrestrial carbon. The genus is undersampled and under-studied. No experimental crystal structure from any Sphagnum species exists in the Protein Data Bank and fewer than 200 Sphagnum-related genes have structural models available in the AlphaFold Protein Structure Database. Tools and resources are needed to help bridge these gaps, and to enable the analysis of other structural proteomes now made possible by accurate structure prediction. We present the predicted structural proteome (25,134 primary transcripts) of Sphagnum divinum computed using AlphaFold, structural alignment results of all high-confidence models against an annotated nonredundant crystallographic database of over 90,000 structures, a structure-based classification of putative Enzyme Commission (EC) numbers across this proteome, and the computational method to perform this proteome-scale structure-based annotation.
59 BASIC BIOLOGICAL SCIENCES↗
Walking the interactome for candidate prioritization in exome sequencing studies of Mendelian diseases
Here, whole-exome sequencing (WES) has opened up previously unheard of possibilities for identifying novel disease genes in Mendelian disorders, only about half of which have been elucidated to date. However, interpretation of WES data remains challenging. As a result, we analyze protein–protein association (PPA) networks to identify candidate genes in the vicinity of genes previously implicated in a disease. The analysis, using a random-walk with restart (RWR) method, is adapted to the setting of WES by developing a composite variant-gene relevance score based on the rarity, location and predicted pathogenicity of variants and the RWR evaluation of genes harboring the variants. Benchmarking using known disease variants from 88 disease-gene families reveals that the correct gene is ranked among the top 10 candidates in ≥50% of cases, a figure which we confirmed using a prospective study of disease genes identified in 2012 and PPA data produced before that date. In conclusion, we implement our method in a freely available Web server, ExomeWalker, that displays a ranked list of candidates together with information on PPAs, frequency and predicted pathogenicity of the variants to allow quick and effective searches for candidates that are likely to reward closer investigation.
60 APPLIED LIFE SCIENCES↗
The Unified Phenotype Ontology : a framework for cross-species integrative phenomics
Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses. A major impediment in phenomics is the wide range of distinct and disconnected approaches to recording the observable characteristics of an organism. Phenotype data are collected and curated using free text, single terms or combinations of terms, using multiple vocabularies, terminologies, or ontologies. Integrating these heterogeneous and often siloed data enables the application of biological knowledge both within and across species. Existing integration efforts are typically limited to mappings between pairs of terminologies; a generic knowledge representation that captures the full range of cross-species phenomics data is much needed. We have developed the Unified Phenotype Ontology (uPheno) framework, a community effort to provide an integration layer over domain-specific phenotype ontologies, as a single, unified, logical representation. uPheno comprises (1) a system for consistent computational definition of phenotype terms using ontology design patterns, maintained as a community library; (2) a hierarchical vocabulary of species-neutral phenotype terms under which their species-specific counterparts are grouped; and (3) mapping tables between species-specific ontologies. This harmonized representation supports use cases such as cross-species integration of genotype-phenotype associations from different organisms and cross-species informed variant prioritization.
59 BASIC BIOLOGICAL SCIENCES↗
Mondo: integrating disease terminology across communities
Precision medicine aims to enhance diagnosis, treatment, and prognosis by integrating multimodal data at the point of care. However, challenges arise due to the vast number of diseases, differing methods of classification, and conflicting terminological coding systems and practices used to represent molecular definitions of disease. This lack of interoperability artificially constrains the potential for diagnosis, clinical decision support, care outcome analysis, as well as data linkage across research domains to support the development or repurposing of therapeutics. There is a clear and pressing need for a unified system for managing disease entities—including identifiers, synonyms, and definitions. To address these issues, we created the Mondo disease ontology—a community-driven, open-source, unified disease classification system that harmonizes diverse terminologies into a consistent, computable framework. Mondo integrates key medical and biomedical terminologies, including Online Mendelian Inheritance in Man (OMIM), Orphanet, Medical Subject Headings (MeSH), National Cancer Institute Thesaurus (NCIt), and more, to provide a comprehensive and accurate representation of disease concepts with fully provenanced and attributed links back to the sources. Mondo can be used as the handle for curation of gene–disease associations utilized in diagnostic applications, research applications such as computational phenotyping, and in clinical coding systems in clinical decision support by pointing the clinician to the numerous knowledge resources linked to the Mondo identifier. Mondo's community-centric approach, stewarded by the Monarch Initiative's expertise in ontologies, ensures that the ontology remains adaptable to the evolving needs of biomedical research and clinical communities, as well as the knowledge providers.
biomedical informatics↗
Stellar wind impact on early atmospheres around unmagnetized Earth-like planets
ABSTRACT Stellar rotation at early ages plays a crucial role in the survival of primordial atmospheres around Earth-mass exoplanets. Earth-like planets orbiting fast-rotating stars may undergo complete photoevaporation within the first few hundred Myr driven by the enhanced stellar XUV [X-rays and extreme ultraviolet (EUV)] radiation, while planets orbiting slow-rotating stars are expected to experience difficulty in losing their primordial envelopes. Besides the action of stellar radiation, stellar winds induce additional erosion on these primordial atmospheres, altering their morphology, extent, and causing supplementary atmospheric losses. In this paper, we study the impact of activity-dependent stellar winds on primordial atmospheres to evaluate the extent to which the action of these winds can be significant in the whole planetary evolution at early evolutionary stages. We performed 3D magnetohydrodynamical (MHD) simulations of the interaction of photoevaporating atmospheres around unmagnetized Earth-mass planets in the time span between 50 and 500 Myr, analysing the joint evolution of stellar winds and atmospheres for both fast- and slow-rotating stars. Our results reveal substantial changes in the evolution of primordial atmospheres when influenced by fast-rotating stars, with a significant reduction in extent at early ages. In contrast, atmospheres embedded in the stellar winds from slow-rotating stars remain largely unaltered. The interaction of the magnetized stellar winds with the ionized upper atmospheres of these planets allows us to evaluate the formation and evolution of different MHD structures, such as double bow shocks and induced magnetospheres. This work will shed light on the first evolutionary stages of Earth-like exoplanets, which are of crucial relevance in terms of planet habitability.
Astronomy & Astrophysics↗
The Human Phenotype Ontology in 2024: phenotypes around the world
The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.
59 BASIC BIOLOGICAL SCIENCES↗
The Human Phenotype Ontology in 2017
Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human PhenotypeOntology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.
59 BASIC BIOLOGICAL SCIENCES↗
The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species
In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.
59 BASIC BIOLOGICAL SCIENCES↗
The western redcedar genome reveals low genetic diversity in a self-compatible conifer
We assembled the 9.8-Gbp genome of western redcedar (WRC; Thuja plicata), an ecologically and economically important conifer species of the Cupressaceae. The genome assembly, derived from a uniquely inbred tree produced through five generations of self-fertilization (selfing), was determined to be 86% complete by BUSCO analysis, one of the most complete genome assemblies for a conifer. Population genomic analysis revealed WRC to be one of the most genetically depauperate wild plant species, with an effective population size of approximately 300 and no significant genetic differentiation across its geographic range. Nucleotide diversity, π, is low for a continuous tree species, with many loci showing zero diversity, and the ratio of π at zero- to fourfold degenerate sites is relatively high (approximately 0.33), suggestive of weak purifying selection. Using an array of genetic lines derived from up to five generations of selfing, we explored the relationship between genetic diversity and mating system. Although overall heterozygosity was found to decline faster than expected during selfing, heterozygosity persisted at many loci, and nearly 100 loci were found to deviate from expectations of genetic drift, suggestive of associative overdominance. Nonreference alleles at such loci often harbor deleterious mutations and are rare in natural populations, implying that balanced polymorphisms are maintained by linkage to dominant beneficial alleles. This may account for how WRC remains responsive to natural and artificial selection, despite low genetic diversity.
59 BASIC BIOLOGICAL SCIENCES↗
Nanolitre-scale crystallization using acoustic liquid-transfer technology
Acoustic droplet ejection achieves precise, tipless, non-invasive transfer of diverse aqueous solutions, enabling nanolitre-scale crystallization trials. The rapid and scalable technique demonstrated successful crystal growth with diverse targets in drop volumes as small as 20 nl. Focused acoustic energy allows accurate and precise liquid transfer on scales from picolitre to microlitre volumes. This technology was applied in protein crystallization, successfully transferring a diverse set of proteins as well as hundreds of precipitant solutions from custom and commercial crystallization screens and achieving crystallization in drop volumes as small as 20 nl. Only higher concentrations (>50%) of 2-methyl-2, 4-pentanediol (MPD) appeared to be systematically problematic in delivery. The acoustic technology was implemented in a workflow, successfully reproducing active crystallization systems and leading to the discovery of crystallization conditions for previously uncharacterized proteins. The technology offers compelling advantages in low-nanolitre crystallization trials by providing significant reagent savings and presenting seamless scalability for those crystals that require larger volume optimization experiments using the same vapor-diffusion format.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Addressing Load Imbalance in Bioinformatics and Biomedical Applications: Efficient Scheduling across Multiple GPUs
Computational bioinformatics and biomedical applications frequently contain heterogeneously sized units of work or tasks, for instance due to variability in the sizes of biological sequences and molecules. Variable-sized workloads lead to load imbalances in parallel implementations which detract from efficiency and performance. Many modern computing resources now have multiple graphics processing units(GPUs) per computer for acceleration. These multiple GPU resources need to be used efficiently through balancing of workloads across the GPUs. OpenMP is a portable directive-based parallel programming API used ubiquitously in bioscience applications to program CPUs; recently, the use of OpenMP directives for GPU acceleration has become possible. Here, motivated by experiences with imbalanced loads in GPU-accelerated bioinformatics applications, we address the load balancing problem using OpenMP task-to-GPU scheduling combined with OpenMP GPU offloading for multiply heterogeneous workloads – loads with both variable input sizes, and simultaneously, variable convergence rates for algorithms with a stochastic component – scheduled across multiple GPUs. We aim to develop strategies which are both easy to use and have lower overheads, and may be incorporated incrementally in existing programs which already make use of OpenMP for CPU-based threading in order to make use of multi-GPU computers. We test different combinations of input size variability and convergence rate variability, and characterize the effects of these different scenarios on the performance of scheduling strategies across multiple GPUs with OpenMP. We present several dynamic scheduling solutions for different parallel patterns, explore optimizations, and provide publicly available example computational kernels to make these strategies easy to use in programs. This work will enable application developers to efficiently and easily use multiple GPUs for imbalanced workloads found in bioinformatics and biomedical applications.
Thavappiragasam, Mathialakan↗
Portability for GPU-accelerated molecular docking applications for cloud and HPC: can portable compiler directives provide performance across all platforms?
High-throughput structure-based screening of drug-like molecules has become a common tool in biomedical research. Recently, acceleration with graphics processing units (GPUs) has provided a large performance boost for molecular docking programs. Both cloud and high-performance computing (HPC) resources have been used for large screens with molecular docking programs; while NVIDIA GPUs have dominated cloud and HPC resources, new vendors such as AMD and Intel are now entering the field, creating the problem of software portability across different GPUs. Ideally, software productivity could be maximized with portable programming models that are able to maintain high performance across architectures. While in many cases compiler directives have been used as an easy way to offload parallel regions of a CPU-based program to a GPU accelerator, they may also be an attractive programming model for providing portability across different GPU vendors, in which case the porting process may proceed in the reverse direction: from low-level, architecture-specific code to higher-level directive-based abstractions. MiniMDock is a new mini-application (miniapp) designed to capture the essential computational kernels found in molecular docking calculations, such as are used in phar-maceutical drug discovery efforts, in order to test different solutions for porting across GPU architectures. Here we extend MiniMDock to GPU offloading with OpenMP directives, and compare to performance of kernels using CUDA and HIP on NVIDIA and AMD GPUs, respectively, as well as across different compilers, exploring performance bottlenecks. We document this reverse-porting process, from highly optimized device code to a higher-level version using directives, compare code structure, and describe barriers that were overcome in this effort.
Thavappiragasam, Mathialakan↗