Phylogeny, function, and evolution of the cupins, a structurally conserved, functionally diverse superfamily of proteins

The cupin superfamily is a group of functionally diverse proteins that are found in all three kingdoms of life, Archaea, Eubacteria, and Eukaryota. These proteins have a characteristic signature domain comprising two histidine- containing motifs separated by an intermotif region of variable length. This domain consists of six beta strands within a conserved beta barrel structure. Most cupins, such as microbial phosphomannose isomerases (PMIs), AraC- type transcriptional regulators, and cereal oxalate oxidases (OXOs), contain only a single domain, whereas others, such as seed storage proteins and oxalate decarboxylases (OXDCs), are bi-cupins with two pairs of motifs. Although some cupins have known functions and have been characterized at the biochemical level, the majority are known only from gene cloning or sequencing projects. In this study, phylogenetic analyses were conducted on the conserved domain to investigate the evolution and structure/function relationships of cupins, with an emphasis on single- domain plant germin-like proteins (GLPs). An unrooted phylogeny of cupins from a wide spectrum of evolutionary lineages identified three main clusters, microbial PMIs, OXDCs, and plant GLPs. The sister group to the plant GLPs in the global analysis was then used to root a phylogeny of all available plant GLPs. The resulting phylogeny contained three main clades, classifying the GLPs into distinct subfamilies. It is suggested that these subfamilies correlate with functional categories, one of which contains the bifunctional barley germin that has both OXO and superoxide dismutase (SOD) activity. It is proposed that GLPs function primarily as SODs, enzymes that protect plants from the effects of oxidative stress. Closer inspection of the DNA sequence encoding the intermotif region in plant GLPs showed global conservation of thymine in the second codon position, a character associated with hydrophobic residues. Since many of these proteins are multimeric and enzymatically inactive in their monomeric state, this conservation of hydrophobicity is thought to be associated with the need to maintain the various monomer- monomer interactions. The type of structure-based predictive analysis presented in this paper is an important approach for understanding gene function and evolution in an era when genomes from a wide range of organisms are being sequenced at a rapid rate.

EfeO-cupredoxins: major new members of the cupredoxin superfamily with roles in bacterial iron transport

The EfeUOB system of Escherichia coli is a tripartite, low pH, ferrous iron transporter. It resembles the high-affinity iron transporter (Ftr1p-Fet3p) of yeast in that EfeU is homologous to Ftr1p, an integral-membrane iron-permease. However, EfeUOB lacks an equivalent of the Fet3p component—the multicopper oxidase with three cupredoxin-like domains. EfeO and EfeB are periplasmic but their precise roles are unclear. EfeO consists primarily of a C-terminal peptidase-M75 domain with a conserved ‘HxxE’ motif potentially involved in metal binding. The smaller N-terminal domain (EfeO-N) is predicted to be cupredoxin (Cup) like, suggesting a previously unrecognised similarity between EfeO and Fet3p. Our structural modelling of the E. coli EfeO Cup domain identifies two potential metal-binding sites. Site I is predicted to bind Cu2+ using three conserved residues (C41 and 103, and E66) and M101. Of these, only one (C103) is conserved in classical cupredoxins where it also acts as a Cu ligand. Site II most probably binds Fe3+ and consists of four well conserved surface Glu residues. Phylogenetic analysis indicates that the EfeO-Cup domains form a novel Cup family, designated the ‘EfeO-Cup’ family. Structural modelling of two other representative EfeO-Cup domains indicates that different subfamilies employ distinct ligand sets at their proposed metal-binding sites. The ~100 efeO homologues in the bacterial sequence databases are all associated with various iron-transport related genes indicating a common role for EfeO-Cup proteins in iron transport, supporting a new copper-iron connection in biology.

Leafy, terminal flower1 and agamous are functionally conserved but do not regulate terminal flowering and floral determinacy in Impatiens balsamina

In Impatiens balsamina a lack of commitment of the meristem during floral development leads to the continuous requirement for a leaf-derived floral signal. In the absence of this signal the meristem reverts to leaf production. Current models for Arabidopsis state that LEAFY (LFY) is central to the integration of floral signals and regulates flowering partly via interactions with TERMINAL FLOWER1 (TFL1) and AGAMOUS (AG). Here we describe Impatiens homologues of LFY, TFL1 and AG (IbLFY, IbTFL1 and IbAG) that are highly conserved at a sequence level and demonstrate homologous functions when expressed ectopically in transgenic Arabidopsis. We relate the expression patterns of IbTFL1 and IbAG to the control of terminal flowering and floral determinacy in Impatiens. IbTFL1 is involved in controlling the phase of the axillary meristems and is expressed in axillary shoots and axillary meristems which produce inflorescences, but not in axillary flowers. It is not involved in maintaining the terminal meristem in either an inflorescence or indeterminate state. Terminal flowering in Impatiens appears therefore to be controlled by a pathway that uses a different integration system than that regulating the development of axillary flowers and branches. The pattern of ovule production in Impatiens requires the meristem to be maintained after the production of carpels. Consistent with this morphological feature IbAG appears to specify stamen and carpel identity, but is not sufficient to specify meristem determinacy in Impatiens.

The effects of temperature and light integral on early vegetative growth and chlorophyll fluorescence of four contrasting genotypes of cacao (Theobroma cacao)

The effect of temperature on early vegetative growth, leaf chlorophyll fluorescence and chlorophyll content was examined on four genotypes of cacao (Amelonado, AMAZ 15–15, SCA 6 and SPEC 54/1). A controlled environment glasshouse was used to simulate the temperature conditions of three cacao-growing regions (Bahia, Brazil; Tafo, Ghana and Lower Perak, Malaysia) over the course of a year. Base temperatures calculated from increments in main stem growth varied from 18.6°C for AMAZ 15/15 to 20.8°C for SPEC 54/1. Temporal variation in Fv/Fm observed for two of the clones (SCA 6 and SPEC 54/1) in two of the compartments were correlated with temperature differences over time. Significant differences were also recorded between genotypes in leaf chlorophyll content. It was shown that variation over time in leaf chlorophyll content could be quantified accurately as a function of temperature and light integral. The results imply that genetic variability exists in cacao in response to temperature stress.

A conserved basic loop in hepatitis C virus p7 protein is required for amantadine-sensitive ion channel activity in mammalian cells but is dispensable for localization to mitochondria

We previously identified the function of the hepatitis C virus (HCV) p7 protein as an ion channel in artificial lipid bilayers and demonstrated that this in vitro activity is inhibited by amantadine. Here we show that the ion channel activity of HCV p7 expressed in mammalian cells can substitute for that of influenza virus M2 in a cell-based assay. This was also the case for the p7 from the related virus, bovine viral diarrhoea virus (BVDV). Moreover, amantadine was shown to abrogate HCV p7 function in this assay at a concentration that specifically inhibits M2. Mutation of a conserved basic loop located between the two predicted trans-membrane alpha helices rendered HCV p7 non-functional as an ion channel. The intracellular localization of p7 was unaffected by this mutation and was found to overlap significantly with membranes associated with mitochondria. Demonstration of p7 ion channel activity in cellular membranes and its inhibition by amantadine affirm the protein as a target for future anti-viral chemotherapy.

Complexity of Monte Carlo algorithms for a class of integral equations

In this work we study the computational complexity of a class of grid Monte Carlo algorithms for integral equations. The idea of the algorithms consists in an approximation of the integral equation by a system of algebraic equations. Then the Markov chain iterative Monte Carlo is used to solve the system. The assumption here is that the corresponding Neumann series for the iterative matrix does not necessarily converge or converges slowly. We use a special technique to accelerate the convergence. An estimate of the computational complexity of Monte Carlo algorithm using the considered approach is obtained. The estimate of the complexity is compared with the corresponding quantity for the complexity of the grid-free Monte Carlo algorithm. The conditions under which the class of grid Monte Carlo algorithms is more efficient are given.

Design of a minimum variance multiple input-multiple output neuro self-tuning proportional-integral-derivative controller for non-linear dynamic systems

In this study a minimum variance neuro self-tuning proportional-integral-derivative (PID) controller is designed for complex multiple input-multiple output (MIMO) dynamic systems. An approximation model is constructed, which consists of two functional blocks. The first block uses a linear submodel to approximate dominant system dynamics around a selected number of operating points. The second block is used as an error agent, implemented by a neural network, to accommodate the inaccuracy possibly introduced by the linear submodel approximation, various complexities/uncertainties, and complicated coupling effects frequently exhibited in non-linear MIMO dynamic systems. With the proposed model structure, controller design of an MIMO plant with n inputs and n outputs could be, for example, decomposed into n independent single input-single output (SISO) subsystem designs. The effectiveness of the controller design procedure is initially verified through simulations of industrial examples.

Condition number estimates for combined potential integral operators in acoustics and their boundary element discretisation

We consider the classical coupled, combined-field integral equation formulations for time-harmonic acoustic scattering by a sound soft bounded obstacle. In recent work, we have proved lower and upper bounds on the $L^2$ condition numbers for these formulations, and also on the norms of the classical acoustic single- and double-layer potential operators. These bounds to some extent make explicit the dependence of condition numbers on the wave number $k$, the geometry of the scatterer, and the coupling parameter. For example, with the usual choice of coupling parameter they show that, while the condition number grows like $k^{1/3}$ as $k\to\infty$, when the scatterer is a circle or sphere, it can grow as fast as $k^{7/5}$ for a class of `trapping' obstacles. In this paper we prove further bounds, sharpening and extending our previous results. In particular we show that there exist trapping obstacles for which the condition numbers grow as fast as $\exp(\gamma k)$, for some $\gamma>0$, as $k\to\infty$ through some sequence. This result depends on exponential localisation bounds on Laplace eigenfunctions in an ellipse that we prove in the appendix. We also clarify the correct choice of coupling parameter in 2D for low $k$. In the second part of the paper we focus on the boundary element discretisation of these operators. We discuss the extent to which the bounds on the continuous operators are also satisfied by their discrete counterparts and, via numerical experiments, we provide supporting evidence for some of the theoretical results, both quantitative and asymptotic, indicating further which of the upper and lower bounds may be sharper.

A neural network enhanced generalized minimum variance self-tuning proportional, integral and derivative control algorithm for complex dynamic systems

A neural network enhanced proportional, integral and derivative (PID) controller is presented that combines the attributes of neural network learning with a generalized minimum-variance self-tuning control (STC) strategy. The neuro PID controller is structured with plant model identification and PID parameter tuning. The plants to be controlled are approximated by an equivalent model composed of a simple linear submodel to approximate plant dynamics around operating points, plus an error agent to accommodate the errors induced by linear submodel inaccuracy due to non-linearities and other complexities. A generalized recursive least-squares algorithm is used to identify the linear submodel, and a layered neural network is used to detect the error agent in which the weights are updated on the basis of the error between the plant output and the output from the linear submodel. The procedure for controller design is based on the equivalent model, and therefore the error agent is naturally functioned within the control law. In this way the controller can deal not only with a wide range of linear dynamic plants but also with those complex plants characterized by severe non-linearity, uncertainties and non-minimum phase behaviours. Two simulation studies are provided to demonstrate the effectiveness of the controller design procedure.

Self-tuning proportional, integral and derivative controller based on genetic algorithm least squares

A self-tuning proportional, integral and derivative control scheme based on genetic algorithms (GAs) is proposed and applied to the control of a real industrial plant. This paper explores the improvement in the parameter estimator, which is an essential part of an adaptive controller, through the hybridization of recursive least-squares algorithms by making use of GAs and the possibility of the application of GAs to the control of industrial processes. Both the simulation results and the experiments on a real plant show that the proposed scheme can be applied effectively.

Conserved hydrophobic clusters on the surface of the Caf1A usher C-terminal domain are important for F1 antigen assembly

The outer membrane usher protein Caf1A of the plague pathogen Yersinia pestis is responsible for the assembly of a major surface antigen, the F1 capsule. The F1 capsule is mainly formed by thin linear polymers of Caf1 (capsular antigen fraction 1) protein subunits. The Caf1A usher promotes polymerization of subunits and secretion of growing polymers to the cell surface. The usher monomer (811 aa, 90.5 kDa) consists of a large transmembrane β-barrel that forms a secretion channel and three soluble domains. The periplasmic N-terminal domain binds chaperone-subunit complexes supplying new subunits for the growing fiber. The middle domain, which is structurally similar to Caf1 and other fimbrial subunits, serves as a plug that regulates the permeability of the usher. Here we describe the identification, characterization, and crystal structure of the Caf1A usher C-terminal domain (Caf1A(C)). Caf1A(C) is shown to be a periplasmic domain with a seven-stranded β-barrel fold. Analysis of C-terminal truncation mutants of Caf1A demonstrated that the presence of Caf1A(C) is crucial for the function of the usher in vivo, but that it is not required for the initial binding of chaperone-subunit complexes to the usher. Two clusters of conserved hydrophobic residues on the surface of Caf1A(C) were found to be essential for the efficient assembly of surface polymers. These clusters are conserved between the FGL family and the FGS family of chaperone-usher systems.

A new frequency-uniform coercive boundary integral equation for acoustic scattering

A new boundary integral operator is introduced for the solution of the soundsoft acoustic scattering problem, i.e., for the exterior problem for the Helmholtz equation with Dirichlet boundary conditions. We prove that this integral operator is coercive in L2(Γ) (where Γ is the surface of the scatterer) for all Lipschitz star-shaped domains. Moreover, the coercivity is uniform in the wavenumber k = ω/c, where ω is the frequency and c is the speed of sound. The new boundary integral operator, which we call the “star-combined” potential operator, is a slight modification of the standard combined potential operator, and is shown to be as easy to implement as the standard one. Additionally, to the authors' knowledge, it is the only second-kind integral operator for which convergence of the Galerkin method in L2(Γ) is proved without smoothness assumptions on Γ except that it is Lipschitz. The coercivity of the star-combined operator implies frequency-explicit error bounds for the Galerkin method for any approximation space. In particular, these error estimates apply to several hybrid asymptoticnumerical methods developed recently that provide robust approximations in the high-frequency case. The proof of coercivity of the star-combined operator critically relies on an identity first introduced by Morawetz and Ludwig in 1968, supplemented further by more recent harmonic analysis techniques for Lipschitz domains.

Boundary integral methods for singularly perturbed boundary value problems

In this paper we consider boundary integral methods applied to boundary value problems for the positive definite Helmholtz-type problem -DeltaU + alpha U-2 = 0 in a bounded or unbounded domain, with the parameter alpha real and possibly large. Applications arise in the implementation of space-time boundary integral methods for the heat equation, where alpha is proportional to 1/root deltat, and deltat is the time step. The corresponding layer potentials arising from this problem depend nonlinearly on the parameter alpha and have kernels which become highly peaked as alpha --> infinity, causing standard discretization schemes to fail. We propose a new collocation method with a robust convergence rate as alpha --> infinity. Numerical experiments on a model problem verify the theoretical results.