How plants recognize pathogens and defend themselves

Plants have an innate immunity system to defend themselves against pathogens. With the primary immune system, plants recognize microbe-associated molecular patterns (MAMPs) of potential pathogens through pattern recognition receptors (PRRs) that mediate a basal defense response. Plant pathogens suppress this basal defense response by means of effectors that enable them to cause disease. With the secondary immune system, plants have gained the ability to recognize effector-induced perturbations of host targets through resistance proteins (RPs) that mediate a strong local defense response that stops pathogen growth. Both primary and secondary immune responses in plants depend on germ line-encoded PRRs and RPs. During induction of local immune responses, systemic immune responses also become activated, which predispose plants to become more resistant to subsequent pathogen attacks. This review gives an update on recent findings that have enhanced our understanding of plant innate immunity and the arms race between plants and their pathogens. Received 24 June 2007; received after revision 18 July 2007; accepted 15 August 2007     

Exploitation of structural and regulatory diversity in glutamate racemases

Glutamate racemase is an enzyme essential to the bacterial cell wall biosynthesis pathway, and has therefore been considered as a target for antibacterial drug discovery. We characterized the glutamate racemases of several pathogenic bacteria using structural and biochemical approaches. Here we describe three distinct mechanisms of regulation for the family of glutamate racemases: allosteric activation by metabolic precursors, kinetic regulation through substrate inhibition, and D-glutamate recycling using a d-amino acid transaminase. In a search for selective inhibitors, we identified a series of uncompetitive inhibitors specifically targeting Helicobacter pylori glutamate racemase that bind to a cryptic allosteric site, and used these inhibitors to probe the mechanistic and dynamic features of the enzyme. These structural, kinetic and mutational studies provide insight into the physiological regulation of these essential enzymes and provide a basis for designing narrow-spectrum antimicrobial agents.     

Demonstration of controlled-NOT quantum gates on a pair of superconducting quantum bits

Quantum computation requires quantum logic gates that use the interaction within pairs of quantum bits (qubits) to perform conditional operations. Superconducting qubits may offer an attractive route towards scalable quantum computing. In previous experiments on coupled superconducting qubits, conditional gate behaviour and entanglement were demonstrated. Here we demonstrate selective execution of the complete set of four different controlled-NOT (CNOT) quantum logic gates, by applying microwave pulses of appropriate frequency to a single pair of coupled flux qubits. All two-qubit computational basis states and their superpositions are used as input, while two independent single-shot SQUID detectors measure the output state, including qubit-qubit correlations. We determined the gate's truth table by directly measuring the state transfer amplitudes and by acquiring the relevant quantum phase shift using a Ramsey-like interference experiment. The four conditional gates result from the symmetry of the qubits in the pair: either qubit can assume the role of control or target, and the gate action can be conditioned on either the 0-state or the 1-state. These gates are now sufficiently characterized to be used in quantum algorithms, and together form an efficient set of versatile building blocks.     

Classification and Categorical Inputs with Treed Gaussian Process Models

Recognizing the successes of treed Gaussian process (TGP) models as an interpretable and thrifty model for nonparametric regression, we seek to extend the model to classification. Both treed models and Gaussian processes (GPs) have, separately, enjoyed great success in application to classification problems. An example of the former is Bayesian CART. In the latter, real-valued GP output may be utilized for classification via latent variables, which provide classification rules by means of a softmax function. We formulate a Bayesian model averaging scheme to combine these two models and describe a Monte Carlo method for sampling from the full posterior distribution with joint proposals for the tree topology and the GP parameters corresponding to latent variables at the leaves. We concentrate on efficient sampling of the latent variables, which is important to obtain good mixing in the expanded parameter space. The tree structure is particularly helpful for this task and also for developing an efficient scheme for handling categorical predictors, which commonly arise in classification problems. Our proposed classification TGP (CTGP) methodology is illustrated on a collection of synthetic and real data sets. We assess performance relative to existing methods and thereby show how CTGP is highly flexible, offers tractable inference, produces rules that are easy to interpret, and performs well out of sample.     

Evidence for a spin-aligned neutron-proton paired phase from the level structure of (92)Pd

Shell structure and magic numbers in atomic nuclei were generally explained by pioneering work that introduced a strong spin-orbit interaction to the nuclear shell model potential. However, knowledge of nuclear forces and the mechanisms governing the structure of nuclei, in particular far from stability, is still incomplete. In nuclei with equal neutron and proton numbers (N = Z), enhanced correlations arise between neutrons and protons (two distinct types of fermions) that occupy orbitals with the same quantum numbers. Such correlations have been predicted to favour an unusual type of nuclear superfluidity, termed isoscalar neutron-proton pairing, in addition to normal isovector pairing. Despite many experimental efforts, these predictions have not been confirmed. Here we report the experimental observation of excited states in the N = Z = 46 nucleus (92)Pd. Gamma rays emitted following the (58)Ni((36)Ar,2n)(92)Pd fusion-evaporation reaction were identified using a combination of state-of-the-art high-resolution γ-ray, charged-particle and neutron detector systems. Our results reveal evidence for a spin-aligned, isoscalar neutron-proton coupling scheme, different from the previous prediction. We suggest that this coupling scheme replaces normal superfluidity (characterized by seniority coupling) in the ground and low-lying excited states of the heaviest N = Z nuclei. Such strong, isoscalar neutron-proton correlations would have a considerable impact on the nuclear level structure and possibly influence the dynamics of rapid proton capture in stellar nucleosynthesis.