Independent Subdomains Research Articles

Probing RNA structural landscapes across Candida yeast genomes.

Understanding the intricate roles of RNA molecules in virulence and host-pathogen interactions can provide valuable insights into combatting infections and improving human health. Although much progress has been achieved in understanding transcriptional regulation during host-pathogen interactions in diverse species, more is needed to know about the structure of pathogen RNAs. This is particularly true for fungal pathogens, including pathogenic yeasts of the Candida genus, which are the leading cause of hospital-acquired fungal infections. Our work addresses the gap between RNA structure and their biology by employing genome-wide structure probing to comprehensively explore the structural landscape of mRNAs and long non-coding RNAs (lncRNAs) in the four major Candida pathogens. Specifically focusing on mRNA, we observe a robust correlation between sequence conservation and structural characteristics in orthologous transcripts, significantly when sequence identity exceeds 50%, highlighting structural feature conservation among closely related species. We investigate the impact of single nucleotide polymorphisms (SNPs) on mRNA secondary structure. SNPs within 5' untranslated regions (UTRs) tend to occur in less structured positions, suggesting structural constraints influencing transcript regulation. Furthermore, we compare the structural properties of coding regions and UTRs, noting that coding regions are generally more structured than UTRs, consistent with similar trends in other species. Additionally, we provide the first experimental characterization of lncRNA structures in Candida species. Most lncRNAs form independent subdomains, similar to human lncRNAs. Notably, we identify hairpin-like structures in lncRNAs, a feature known to be functionally significant. Comparing hairpin prevalence between lncRNAs and protein-coding genes, we find enrichment in lncRNAs across Candida species, humans, and Arabidopsis thaliana, suggesting a conserved role for these structures. In summary, our study offers valuable insights into the interplay between RNA sequence, structure, and function in Candida pathogens, with implications for gene expression regulation and potential therapeutic strategies against Candida infections.

Analyzing electromagnetic scattering from complex multi-layer patch objects using a multi-trace domain decomposition method

The local-coupling multi-trace and domain decomposition method originally developed to analyze electromagnetic scattering from closed composite objects is extended to solve the scattering from complex multilayer patch objects. Different from the traditional global radiation coupling surface integral equation domain decomposition method and contact-region modeling method (CRM), the local-coupling property yields many excellent properties, highly sparse matrix, better computational performance, etc. In this novel proposed method, the multilayer patch objects are decomposed into many independent sub-domains, and each sub-domain is assumed as a homogeneous dielectric subdomain to formulate the electric-field integral equation (EFIE) and the magnetic-field integral equation (MFIE) for dielectrics as the governing equations. The corresponding boundary condition of the perfect electric conducting (PEC) surface sheet is then achieved by adopting Robin transmission conditions (RTCs) to PEC surfaces, termed PEC-RTCs. The final resulting equation yield a better performance than the traditional method. Numerical examples validate the advantages of the proposed method.

Leveraging mesh modularization to lower the computational cost of localized updates to regional 2D hydrodynamic model outputs

Hydrodynamic model outputs are used in urban flood risk modelling, flood alert systems, and Monte Carlo hazard assessment. This study tackles an under-explored challenge wherein regular updates to the spatial characteristics of the watershed – due to factors such as changing land use – alter the watershed’s response to rainfall forcing, thus rendering existing model outputs obsolete. Because state-of-the-art hydrodynamic models are computationally expensive, frequently re-running simulations can be costly. Modularization addresses this problem by requiring re-computation only for a limited domain affected by the land use changes. This article introduces a novel approach by modularizing the 2D domain into independent sub-domains before (‘discrete’) and after (‘abstract’) the numerical computations. Using the Hydrologic Engineering Center River Analysis System (HEC-RAS) 2D model of a large urban watershed in Houston as an illustrative and generalizable testbed, we show that both the discrete and abstract modularization closely approximates the results from re-running the entire model. The computational cost of modularization scales linearly with model size for memory requirements as storing the solution on the interior boundaries (discrete) or throughout the domain (abstract) are necessary. This trade-off of memory for computation may facilitate advances in surrogate modelling or Monte Carlo flood risk assessment.

Multi-domain physics-informed neural networks for solving transient heat conduction problems in multilayer materials

In this paper, we aim to numerically resolve linear and nonlinear transient heat conduction problems in multilayer composite materials using a deep learning method called multi-domain physics-informed neural networks (MDPINNs). For this purpose, the multilayer media are first divided into independent sub-domains based on domain decomposition technique. The single-layer deep neural networks are first established, and each sub-domain has its corresponding sub-network. Then, each two sub-networks are connected by continuity conditions on the interface to form a MDPINNs’ framework that can directly solve the transient heat conduction problem in multilayer media. The temperature distribution in the computational domain can be obtained by training the MDPINNs, including the temperature values on the interface. A series of numerical experiments are carried out to verify that the proposed framework can achieve satisfactory accuracy, including in micrometer or even nanometer structures. Compared with conventional methods, the MDPINNs have the advantage of directly solving both linear and nonlinear heat conduction problems in multilayer materials in a unified and concise form.

The transmembrane domains mediate oligomerization of the human ZIP4 transporter in vivo

The human (h) ZIP4 is a plasma membrane transporter that functions to increase cytosolic zinc levels. hZIP4 encodes eight transmembrane domains and a large extracellular domain (ECD). This ECD is cleaved from the holo-transporter when cells are zinc-deficient. At the same time, mutations in the ECD can result in the zinc-deficiency disease Acrodermatitis enteropathica. Previously, it was shown that hZIP4’s ECD is comprised of two structurally independent subdomains where contacts between the ECD monomeric units are centered at the PAL motif. These results lead to the hypothesis that ZIP4-ECD is essential to the dimerization of the holo-transporter. To test this hypothesis, we used Fluorescence Correlation Spectroscopy (FCS) to quantify the oligomeric state of full-length hZIP4 and hZIP4 lacking the ECD domain, each tagged with eGFP. Inspection of our experimental results demonstrate that both the full-length and truncated hZIP4 is a dimer when expressed in HEK293 cells. Parallel functional experiments demonstrate that the Km and Vmax for truncated and full-length hZIP4/eGFP are similar. Determining that truncated hZIP4/eGFP forms a dimer is a crucial step for understanding the function of the hZIP4-ECD, which provides more insight into how the diseases related to hZIP4 protein.

Deep learning to decompose macromolecules into independent Markovian domains

The increasing interest in modeling the dynamics of ever larger proteins has revealed a fundamental problem with models that describe the molecular system as being in a global configuration state. This notion limits our ability to gather sufficient statistics of state probabilities or state-to-state transitions because for large molecular systems the number of metastable states grows exponentially with size. In this manuscript, we approach this challenge by introducing a method that combines our recent progress on independent Markov decomposition (IMD) with VAMPnets, a deep learning approach to Markov modeling. We establish a training objective that quantifies how well a given decomposition of the molecular system into independent subdomains with Markovian dynamics approximates the overall dynamics. By constructing an end-to-end learning framework, the decomposition into such subdomains and their individual Markov state models are simultaneously learned, providing a data-efficient and easily interpretable summary of the complex system dynamics. While learning the dynamical coupling between Markovian subdomains is still an open issue, the present results are a significant step towards learning Ising models of large molecular complexes from simulation data.

High-efficient decoupling method for coupling systems with multiple subdomains and time steps

This paper proposes a high-efficient decoupling method with energy conservation property to solve a coupling system with multiple subdomains and time steps using arbitrary Newmark schemes. Moreover, new General-α integration schemes with desirable algorithmic damping and accuracy are investigated and incorporated in the proposed method to filter spurious high-frequency vibration contents and retain the second-order accuracy. The proposed method can decompose the coupling system into several independent subdomains with different time steps, and different integration schemes can be employed to solve various subdomains independently. Accuracy and stability for each decoupling subdomain are ensured and adjusted using its integration parameters. The complicated and time-consuming border program is not used in the calculation process, and all subdomain vibrations are not split into link vibrations and free vibrations, therefore, computational efficiency is improved significantly compared with existing coupling methods. To conveniently derive the decoupling method, the coupling dynamic system with two subdomains and different time steps is established using the Newmark compact form firstly. Subsequently, a decoupling strategy is formulated to decompose and solve the coupling system, and its stability is proved by using the pseudo-energy method and classic mechanical energy method. Accordingly, New General-α schemes are investigated and incorporated in the proposed method to obtain desirable algorithmic damping and accuracy. Three illustrative examples are employed to demonstrate the accuracy, efficiency, energy property, and adaptability for multi-subdomains (≥3) of the proposed method.

Authentication of Sub-NUMA Clustering effect on Intel Skylake for Memory Latency and Bandwidth

The search efficiency of in-memory databases depends significantly on how quickly DRAM data can be obtained. With an increasing multiple core on processors, it is more difficult to satisfy the requirement that all attached DRAM on a processor is equally accessible to any core. Intel has therefore implemented a Sub-NUMA Clustering (SNC) mode on Skylake, which subdivides cores and memories into various sub for enhanced core-to-memory access within each processor sub-domain. Similar modes are given by other models. When an in-memory database shares data between staff on cores in separate sub-domains, the use of SNC creates problems in how to manage database workloads among domains. In this research, we verify the effect of SNC specifically on Intel Skylake on memory latency and bandwidth. We conclude that two similarly broad analytical workloads are focused on different and fully independent sub-domains just up to 3 percent will improve query throughput and be totally isolated from each other. Often, as memory bandwidth is split into sub-domains rather than aggregated across the entire processor, bandwidth-sensitive analytical workloads significantly reduce application performance if data is not split equally among sub-domains.

The dynamics of free and phosphopeptide-bound Grb2-SH2 reveals two dynamically independent subdomains and an encounter complex with fuzzy interactions

The growth factor receptor-bound protein 2 (Grb2) is a key factor in the regulation of cell survival, proliferation, differentiation, and metabolism. In its structure, the central Src homology 2 (SH2) domain is flanked by two Src homology 3 (SH3). SH2 is the most important domain in the recognition of phosphotyrosines. Here, we present the first dynamical characterization of Grb2-SH2 domain in the free state and in the presence of phosphopeptide EpYINSQV at multiple timescales, which revealed valuable information to the understanding of phophotyrosine sensing mechanism. Grb2-SH2 presented two dynamically independent subdomains, subdomain I involved in pY recognition and subdomain II is the pY + 2 specificity pocket. Under semi-saturated concentrations of pY-pep we observed fuzzy interactions, which led to chemical exchange observed by NMR. This information was used to describe the encounter complex. The association with pY-pep is dynamic, involving fuzzy interactions and multiple conformations of pY-pep with negative and hydrophobic residues, creating an electrostatic-potential that drives the binding of pY-pep. The recognition face is wider than the binding site, with many residues beyond the central SH2 binding site participating in the association complex, which contribute to explain previously reported capability of Grb2 to recognize remote pY.

Solving electromagnetic scattering from complex composite objects with domain decomposition method based on hybrid surface integral equations

A new domain decomposition method (DDM) is proposed to solve the electromagnetic scattering from microstrip antennas and arrays conformally mounted on a perfect electrically conducting (PEC) platform. Based on the local geometrical structures and material properties, the complex composite structures is first decomposed into independent sub-domains, following the philosophy of divide and conquer. The combined field integral equation (CFIE), the electric field integral equation (EFIE), and the Poggio–Miller–Chang–Harrington–Wu–Tsai (PMCHWT) formulation are then combined seamlessly in the framework of DDM. These equations are applied for different sub-domains: CFIE is used for the platform (closed PEC) sub-domains and EFIE–PMCHWT is employed for the microstrip (composite structure with dielectric substrate and open PEC sheet) sub-domains. To ensure the continuities of fields, the transmission conditions (TCs) are applied on the touching-faces. Compared with the traditional method, the newly developed DDM not only releases the burden of geometry preparation, but also results in a better conditioned matrix.

NMR solution structure of the RED subdomain of the Sleeping Beauty transposase.

DNA transposons can be employed for stable gene transfer in vertebrates. The Sleeping Beauty (SB) DNA transposon has been recently adapted for human application and is being evaluated in clinical trials, however its molecular mechanism is not clear. SB transposition is catalyzed by the transposase enzyme, which is a multi-domain protein containing the catalytic and the DNA-binding domains. The DNA-binding domain of the SB transposase contains two structurally independent subdomains, PAI and RED. Recently, the structures of the catalytic domain and the PAI subdomain have been determined, however no structural information on the RED subdomain and its interactions with DNA has been available. Here, we used NMR spectroscopy to determine the solution structure of the RED subdomain and characterize its interactions with the transposon DNA.

Reconstruction of independent sub-domains for a class of Hamilton–Jacobi equations and application to parallel computing

A previous knowledge of the domains of dependence of a Hamilton–Jacobi equation can be useful in its study and approximation. Information of this nature is, in general, difficult to obtain directly from the data of the problem. In this paper we formally introduce the concept of an independent sub-domain , discuss its main properties and provide a constructive implicit representation formula. Through these results, we propose an algorithm for the approximation of these sets that is shown to be relevant in the numerical resolution, via parallel computing.

Structural insights of ZIP4 extracellular domain critical for optimal zinc transport.

The ZIP zinc transporter family is responsible for zinc uptake from the extracellular milieu or intracellular vesicles. The LIV-1 subfamily, containing nine out of the 14 human ZIP proteins, is featured with a large extracellular domain (ECD). The critical role of the ECD is manifested by disease-causing mutations on ZIP4, a representative LIV-1 protein. Here we report the first crystal structure of a mammalian ZIP4-ECD, which reveals two structurally independent subdomains and an unprecedented dimer centred at the signature PAL motif. Structure-guided mutagenesis, cell-based zinc uptake assays and mapping of the disease-causing mutations indicate that the two subdomains play pivotal but distinct roles and that the bridging region connecting them is particularly important for ZIP4 function. These findings lead to working hypotheses on how ZIP4-ECD exerts critical functions in zinc transport. The conserved dimeric architecture in ZIP4-ECD is also demonstrated to be a common structural feature among the LIV-1 proteins.

Structural Studies of The N‐terminal Domain of Plasmodium Falciparum Copper P‐ATPase (PfCuP‐ATPase)

Plasmodium falciparum is one of the four parasites that cause malaria in humans. Resistance of malarial parasites to some of existing drugs calls for a need to develop new therapeutic agents. Integral membrane proteins which are metal transporters are potential targets for drug development. PfCuP-ATPase, a copper-transporting ATPase in Plasmodium parasites, is a potential target for new antimalarials. PfCuP-ATPase has one copper binding motif in the N-terminal region. The C-terminal portion of the protein has ten predicted trans-membrane helices and multiple inserts of unknown function. The structural organization of PfCuP-ATPase has not been elucidated. Our objective is to understand the structure and function of the N-terminal region. We have applied protein modeling tools to predict structured sub-domains in the N-terminal domain of PfCuP-ATPase (Fig. 1 &2). Circular Dichroism and Nuclear Magnetic Resonance spectroscopy methods were used to study the biophysical properties of the predicted domains (Fig. 3). Our preliminary results indicate that the N-terminal domain structured regions may have multiple ferredoxin folds. We have been able to determine that there exists three independent subdomains in the N-terminal portion of PfCuP-ATPase.

Overlapping for preconditioners based on incomplete factorizations and nested arrow form

In this paper, we discuss the usage of overlapping techniques for improving the convergence of preconditioners based on incomplete factorizations. To enable parallelism, these preconditioners are usually applied after the input matrix is permuted into a nested arrow form using k-way nested dissection. This graph partitioning technique uses k-way partitionning by vertex separator to recursively partition the graph of the input matrix into k subgraphs using a subset of its vertices called a separator. The overlapping technique is then based on algebraically extending the associated subdomains of these subgraphs and their corresponding separators obtained from k-way nested dissection by their direct neighbours. A similar approach is known to accelerate the convergence of domain decomposition methods, where the input matrix is partitioned into a number of independent subdomains using k-way vertex partitioning of a graph by edge separators, a different graph decomposition technique. We discuss the effect of the overlapping technique on the convergence of two classes of preconditioners, on the basis of nested factorization and block incomplete LDU factorization.

High-resolution structure of the Tiam1 PHn-CC-Ex domain.

The T-lymphoma and metastasis gene 1 (TIAM1) encodes a guanine nucleotide-exchange factor protein (Tiam1) that is specific for the Rho-family GTPase Rac1 and is important for cell polarity, migration and adhesion. Tiam1 is a large multi-domain protein that contains several protein-protein binding domains that are important for regulating cellular function. The PHn-CC-Ex domain is critical for plasma-membrane association and interactions with protein-scaffold proteins (e.g. Par3b, spinophilin, IRSp53 and JIP2) that direct Tiam1-Rac1 signaling specificity. It was determined that the coiled-coil domain of Par3b binds the PHn-CC-Ex domain with a dissociation constant of ≈ 30 µM. Moreover, the structures of two variants of the Tiam1 PHn-CC-Ex domain were solved at resolutions of 1.98 and 2.15 Å, respectively. The structures indicate that the PHn, CC and Ex regions form independent subdomains that together provide an integrated platform for binding partner proteins. Small-angle X-ray scattering (SAXS) data indicate that the Tiam1 PHn-CC-Ex domain is monomeric in solution and that the solution and crystal structures are very similar. Together, these data provide the foundation necessary to elucidate the structural mechanism of the PHn-CC-Ex/scaffold interactions that are critical for Tiam1-Rac1 signaling specificity.

Essential and non‐essential interactions in interactome networks: the Escherichia coli division proteins FtsQ–FtsN interaction

The Escherichia coli division protein FtsQ, which plays a central role in the septosome assembly, interacts with several protein partners of the division machinery. Its interaction with FtsB and FtsL allows the formation of the trimeric complex connecting the early cytoplasmic cell division proteins with the late, essentially periplasmic, ones. Little is known about the interactions that FtsQ contracts with other divisome components, besides the fact that all are localized in its periplasmic domain. In this domain, two independent subdomains, both involved in FtsQ, FtsI and FtsN interactions, were also identified. The study of FtsQ interaction-defective mutants constituted a basis to investigate the biological significance of its interactions. However, in the case of interactions where two independent sites are involved, mutation(s) in one domain can be suppressed by the presence of the still-functional second interaction region. To ascertain the biological role of these interactions, it is therefore necessary to select double mutants, where both sites are impaired. This paper describes the behaviour of FtsQ double mutants that have lost the ability to interact with FtsN, which is the last component in the hierarchy of divisome assembly, and is necessary to guarantee its stability and function.

Towards an integrative approach to understanding quality of life in schizophrenia: the role of neurocognition, social cognition, and psychopathology

The term “schizophrenia” refers to a debilitating group of disorders that usually results in a severely impaired quality of life (QoL). Symptomatology appears to have a substantial role in determining QoL, although the relationship between QoL and specific psychotic symptoms is still unclear and has demonstrated mixed results. Due to the intrinsic importance of social functioning in QoL, and the mediating effect of social cognition on social functioning, the aim of this study was to try to investigate QoL in schizophrenia, not only in terms of symptomatology, but also in consideration of potential neurocognitive and social cognitive contributing factors. MethodsTwenty-eight clinically stable patients with schizophrenia performed a broad range of neurocognitive and social cognitive assessments, and also participated in a semi-structured interview of QoL, assessing four partially independent subdomains of QoL. A stepwise regression model was used to determine the best predictors of QoL, and additionally a mediator analysis was performed to test for the mediating power of social cognition on QoL. ResultsNegative symptoms, intelligence, executive functioning and social cognition all had some power in predicting QoL in schizophrenia. Though most interestingly, mental state reasoning was specifically found to be most strongly related with the Intrapsychic Foundation subdomain of QoL, whereas neurocognition and symptom severity were associated with other subdomains of QoL. ConclusionsThe association between mental state reasoning and the more “internal” aspects of QoL in schizophrenia may reflect a specific role for social cognition in introspective and subjective judgments of one's own QoL, whereas neurocognition and negative symptomatology may be more predictive of the external or extrinsic aspects of QoL. In conclusion, social cognitive skills appear to play a crucial role in the experience of one's own subjective well-being, which could help to explain previous inconsistencies in the literature investigating QoL in schizophrenia.

Parallel solution of an electrostatic field problem — case study

The paper presents a parallel approach for the efficient solution of a simple 1D Laplace-Poisson equation problem by parallel finite element method. This problem is a case study. The non-overlapping domain decomposition method has been used to cut the problem into sub-regions or also called sub-domains, and it reduces the large mass matrix into smaller parts. The independent subdomains, and the assembling of these equation systems can be handled by the independent processors of a supercomputer, i.e. in a parallel way. The results of parallel finite element method have been compared to the results of serial finite element method as well as the analytical results.

Sense of agency and mentalizing: Dissociation of subdomains of social cognition in patients with schizophrenia

The sense of agency, i.e., the sense that “I am the one who is causing an action”, and mentalizing, the ability to understand the mental states of other individuals, are key domains of social cognition. It has been hypothesized that an intact sense of agency is an important precondition for higher-level mentalizing abilities. A substantial body of evidence shows that both processes rely on similar brain areas and are severely impaired in schizophrenia, suggesting a close link between agency and mentalizing. Yet this relationship has not been explicitly tested. We investigated 40 individuals with schizophrenia and 40 healthy controls on an agency and mentalizing task. On the agency task, participants carried out simple mouse movements and judged the partially manipulated visual feedback as either self- or other-generated. On the mentalizing task, participants inferred mental states from pictures that depicted others' eyes (“Reading the mind in the eyes test”). Neuropsychological, psychopathological and social functioning levels were also evaluated. Both sense of agency and mentalizing were impaired in schizophrenia patients compared to healthy controls. However, testing for a relationship revealed no significant correlations between the two processes, either in the schizophrenia or the control group. The present findings demonstrate a dissociation of agency and mentalizing deficits in schizophrenia, suggesting that the multifaceted construct of social cognition consists of independent subdomains in healthy and psychiatrically ill individuals.