Mutations of penicillin acylase residue B71 extend substrate specificity by decreasing steric constraints for substrate binding

Two mutant forms of penicillin acylase from Escherichia coli strains, selected using directed evolution for the ability to use glutaryl-L-leucine for growth [Forney, Wong and Ferber (1989) Appl. Environ. Microbiol. 55, 2550-2555], are changed within one codon, replacing the B-chain residue Phe(B71) with either Cys or Leu. Increases of up to a factor of ten in k(cat)/K-m values for substrates possessing a phenylacetyl leaving group are consistent with a decrease in K-s. Values of k(cat/)K(m) for glutaryl-L-leucine are increased at least 100-fold. A decrease in k(cat)/K-m for the CySB71 mutant with increased pH is consistent with binding of the uncharged glutaryl group. The mutant proteins are more resistant to urea denaturation monitored by protein fluorescence, to inactivation in the presence of substrate either in the presence of urea or at high pH, and to heat inactivation. The crystal structure of the Leu(B71) mutant protein, solved to 2 X resolution, shows a flip of the side chain of Phe(B256) into the periphery of the catalytic centre, associated with loss of the pi-stacking interactions between Phe(B256) and Phe(B71). Molecular modelling demonstrates that glutaryl-L-leucine may bind with the uncharged glutaryl group in the S-1 subsite of either the wild-type or the Leu(B71) mutant but with greater potential freedom of rotation of the substrate leucine moiety in the complex with the mutant protein. This implies a smaller decrease in the conformational entropy of the substrate on binding to the mutant proteins and consequently greater catalytic activity

Optimal and Efficient Decoding of Concatenated Quantum Block Codes

We consider the problem of optimally decoding a quantum error correction code -- that is to find the optimal recovery procedure given the outcomes of partial "check" measurements on the system. In general, this problem is NP-hard. However, we demonstrate that for concatenated block codes, the optimal decoding can be efficiently computed using a message passing algorithm. We compare the performance of the message passing algorithm to that of the widespread blockwise hard decoding technique. Our Monte Carlo results using the 5 qubit and Steane's code on a depolarizing channel demonstrate significant advantages of the message passing algorithms in two respects. 1) Optimal decoding increases by as much as 94% the error threshold below which the error correction procedure can be used to reliably send information over a noisy channel. 2) For noise levels below these thresholds, the probability of error after optimal decoding is suppressed at a significantly higher rate, leading to a substantial reduction of the error correction overhead.Comment: Published versio

Processing and Transmission of Information

Contains research objectives and reports on three research projects.National Science Foundation (Grant GP-2495)National Institutes of Health (Grant MH-04737-04)National Aeronautics and Space Administration (Grant NsG-334)National Aeronautics and Space Administration (Grant NsG-496

On optimal extended row distance profile

In this paper, we investigate extended row distances of Unit Memory (UM) convolutional codes. In particular, we derive upper and lower bounds for these distances and moreover present a concrete construction of a UM convolutional code that almost achieves the derived upper bounds. The generator matrix of these codes is built by means of a particular class of matrices, called superregular matrices. We actually conjecture that the construction presented is optimal with respect to the extended row distances as it achieves the maximum extended row distances possible. This in particular implies that the upper bound derived is not completely tight. The results presented in this paper further develop the line of research devoted to the distance properties of convolutional codes which has been mainly focused on the notions of free distance and column distance. Some open problems are left for further research

Common structure in the heterogeneity of plant-matter decay

Carbon removed from the atmosphere by photosynthesis is released back by respiration. Although some organic carbon is degraded quickly, older carbon persists; consequently carbon stocks are much larger than predicted by initial decomposition rates. This disparity can be traced to a wide range of first-order decay-rate constants, but the rate distributions and the mechanisms that determine them are unknown. Here, we pose and solve an inverse problem to find the rate distributions corresponding to the decomposition of plant matter throughout North America. We find that rate distributions are lognormal, with a mean and variance that depend on climatic conditions and substrate. Changes in temperature and precipitation scale all rates similarly, whereas the initial substrate composition sets the time scale of faster rates. These findings probably result from the interplay of stochastic processes and biochemical kinetics, suggesting that the intrinsic variability of decomposers, substrate and environment results in a predictable distribution of rates. Within this framework, turnover times increase exponentially with the kinetic heterogeneity of rates, thereby providing a theoretical expression for the persistence of recalcitrant organic carbon in the natural environment

Dentine Oxygn Isotopes (δ18O) as a Proxy for Odontocete Distributions and Movements.

Spatial variation in marine oxygen isotope ratios ( δ18O) resulting from differential evaporation rates and precipitation inputs is potentially useful for characterizing marine mammal distributions and tracking movements across δ18O gradients. Dentine hydroxyapatite contains carbonate and phosphate that precipitate in oxygen isotopic equilibrium with body water, which in odontocetes closely tracks the isotopic composition of ambient water. To test whether dentine oxygen isotope composition reliably records that of ambient water and can therefore serve as a proxy for odontocete distribution and movement patterns, we measured δ18O values of dentine structural carbonate (δ18OSC) and phosphate (δ18OP) of seven odontocete species (n = 55 individuals) from regional marine water bodies spanning a surface water δ18O range of several per mil. Mean dentine δ18OSC (range +21.2 to +25.5‰ VSMOW) and δ18OP (+16.7 to +20.3‰) values were strongly correlated with marine surface water δ18O values, with lower dentine δ18OSC and δ18OP values in high-latitude regions (Arctic and Eastern North Pacific) and higher values in the Gulf of California, Gulf of Mexico, and Mediterranean Sea. Correlations between dentine δ18OSC and δ18OP values with marine surface water δ18O values indicate that sequential δ18O measurements along dentine, which grows incrementally and archives intra- and interannual isotopic composition over the lifetime of the animal, would be useful for characterizing residency within and movements among water bodies with strong δ18O gradients, particularly between polar and lower latitudes, or between oceans and marginal basins

Complexity of Discrete Energy Minimization Problems

Discrete energy minimization is widely-used in computer vision and machine learning for problems such as MAP inference in graphical models. The problem, in general, is notoriously intractable, and finding the global optimal solution is known to be NP-hard. However, is it possible to approximate this problem with a reasonable ratio bound on the solution quality in polynomial time? We show in this paper that the answer is no. Specifically, we show that general energy minimization, even in the 2-label pairwise case, and planar energy minimization with three or more labels are exp-APX-complete. This finding rules out the existence of any approximation algorithm with a sub-exponential approximation ratio in the input size for these two problems, including constant factor approximations. Moreover, we collect and review the computational complexity of several subclass problems and arrange them on a complexity scale consisting of three major complexity classes -- PO, APX, and exp-APX, corresponding to problems that are solvable, approximable, and inapproximable in polynomial time. Problems in the first two complexity classes can serve as alternative tractable formulations to the inapproximable ones. This paper can help vision researchers to select an appropriate model for an application or guide them in designing new algorithms.Comment: ECCV'16 accepte

The impact of predation by marine mammals on Patagonian toothfish longline fisheries

Predatory interaction of marine mammals with longline fisheries is observed globally, leading to partial or complete loss of the catch and in some parts of the world to considerable financial loss. Depredation can also create additional unrecorded fishing mortality of a stock and has the potential to introduce bias to stock assessments. Here we aim to characterise depredation in the Patagonian toothfish (Dissostichus eleginoides) fishery around South Georgia focusing on the spatio-temporal component of these interactions. Antarctic fur seals (Arctocephalus gazella), sperm whales (Physeter macrocephalus), and orcas (Orcinus orca) frequently feed on fish hooked on longlines around South Georgia. A third of longlines encounter sperm whales, but loss of catch due to sperm whales is insignificant when compared to that due to orcas, which interact with only 5% of longlines but can take more than half of the catch in some cases. Orca depredation around South Georgia is spatially limited and focused in areas of putative migration routes, and the impact is compounded as a result of the fishery also concentrating in those areas at those times. Understanding the seasonal behaviour of orcas and the spatial and temporal distribution of “depredation hot spots” can reduce marine mammal interactions, will improve assessment and management of the stock and contribute to increased operational efficiency of the fishery. Such information is valuable in the effort to resolve the human-mammal conflict for resources

Probing the role of proton cross-shell excitations in Ni 70 using nucleon knockout reactions

The neutron-rich Ni isotopes have attracted attention in recent years because of the occurrence of shape or configuration coexistence. We report on the difference in population of excited final states in Ni70 following γ-ray tagged one-proton, one-neutron, and two-proton knockout from Cu71, Ni71, and Zn72 rare-isotope beams, respectively. Using variations observed in the relative transition intensities, signaling the changed population of specific final states in the different reactions, the role of neutron and proton configurations in excited states of Ni70 is probed schematically, with the goal of identifying those that carry, as leading configuration, proton excitations across the Z=28 shell closure. Such states are suggested in the literature to form a collective structure associated with prolate deformation. Adding to the body of knowledge for Ni70, 29 new transitions are reported, of which 15 are placed in its level scheme

Composition codes

In this paper we introduce a special class of 2D convolutional codes, called composition codes, which admit encoders G(d1,d2) that can be decomposed as the product of two 1D encoders, i.e., G(d1,d2)=G2(d2)G1(d1). Taking into account this decomposition, we obtain syndrome formers of the code directly from G1(d1) andG2(d2), in case G1(d1) andG2(d2) are right prime. Moreover we consider 2D state-space realizations by means of a separable Roesser model of the encoders and syndrome formers of a composition code and we investigate the minimality of such realizations. In particular, we obtain minimal realizations for composition codes which admit an encoder G(d1,d2)=G2(d2)G1(d1) withG2(d2) a systematic 1D encoder. Finally, we investigate the minimality of 2D separable Roesser state-space realizations for syndrome formers of these codes.publishe