Molecular phylogenetic analysis of evolutionary trends in stonefly wing structure and locomotor behavior

Insects in the order Plecoptera (stoneflies) use a form of two-dimensional aerodynamic locomotion called surface skimming to move across water surfaces. Because their weight is supported by water, skimmers can achieve effective aerodynamic locomotion even with small wings and weak flight muscles. These mechanical features stimulated the hypothesis that surface skimming may have been an intermediate stage in the evolution of insect flight, which has perhaps been retained in certain modern stoneflies. Here we present a phylogeny of Plecoptera based on nucleotide sequence data from the small subunit rRNA (18S) gene. By mapping locomotor behavior and wing structural data onto the phylogeny, we distinguish between the competing hypotheses that skimming is a retained ancestral trait or, alternatively, a relatively recent loss of flight. Our results show that basal stoneflies are surface skimmers, and that various forms of surface skimming are distributed widely across the plecopteran phylogeny. Stonefly wings show evolutionary trends in the number of cross veins and the thickness of the cuticle of the longitudinal veins that are consistent with elaboration and diversification of flight-related traits. These data support the hypothesis that the first stoneflies were surface skimmers, and that wing structures important for aerial flight have become elaborated and more diverse during the radiation of modern stoneflies.

A fully automatic evolutionary classification of protein folds: Dali Domain Dictionary version 3

The Dali Domain Dictionary (http://www.ebi.ac.uk/dali/domain) is a numerical taxonomy of all known structures in the Protein Data Bank (PDB). The taxonomy is derived fully automatically from measurements of structural, functional and sequence similarities. Here, we report the extension of the classification to match the traditional four hierarchical levels corresponding to: (i) supersecondary structural motifs (attractors in fold space), (ii) the topology of globular domains (fold types), (iii) remote homologues (functional families) and (iv) homologues with sequence identity above 25% (sequence families). The computational definitions of attractors and functional families are new. In September 2000, the Dali classification contained 10 531 PDB entries comprising 17 101 chains, which were partitioned into five attractor regions, 1375 fold types, 2582 functional families and 3724 domain sequence families. Sequence families were further associated with 99 582 unique homologous sequences in the HSSP database, which increases the number of effectively known structures several-fold. The resulting database contains the description of protein domain architecture, the definition of structural neighbours around each known structure, the definition of structurally conserved cores and a comprehensive library of explicit multiple alignments of distantly related protein families.

Photoactive yellow protein: A structural prototype for the three-dimensional fold of the PAS domain superfamily

PAS domains are found in diverse proteins throughout all three kingdoms of life, where they apparently function in sensing and signal transduction. Although a wealth of useful sequence and functional information has become recently available, these data have not been integrated into a three-dimensional (3D) framework. The very early evolutionary development and diverse functions of PAS domains have made sequence analysis and modeling of this protein superfamily challenging. Limited sequence similarities between the ∼50-residue PAS repeats and one region of the bacterial blue-light photosensor photoactive yellow protein (PYP), for which ground-state and light-activated crystallographic structures have been determined to high resolution, originally were identified in sequence searches using consensus sequence probes from PAS-containing proteins. Here, we found that by changing a few residues particular to PYP function, the modified PYP sequence probe also could select PAS protein sequences. By mapping a typical ∼150-residue PAS domain sequence onto the entire crystallographic structure of PYP, we show that the PAS sequence similarities and differences are consistent with a shared 3D fold (the PAS/PYP module) with obvious potential for a ligand-binding cavity. Thus, PYP appears to prototypically exhibit all the major structural and functional features characteristic of the PAS domain superfamily: the shared PAS/PYP modular domain fold of ∼125–150 residues, a sensor function often linked to ligand or cofactor (chromophore) binding, and signal transduction capability governed by heterodimeric assembly (to the downstream partner of PYP). This 3D PAS/PYP module provides a structural model to guide experimental testing of hypotheses regarding ligand-binding, dimerization, and signal transduction.

Evolutionary reconstruction of a hairpin deleted from the genome of an RNA virus.

The intercistronic region between the maturation and coat-protein genes of RNA phage MS2 contains important regulatory and structural information. The sequence participates in two adjacent stem-loop structures, one of which, the coat-initiator hairpin, controls coat-gene translation and is thus under strong selection pressure. We have removed 19 out of the 23 nucleotides constituting the intercistronic region, thereby destroying the capacity of the phage to build the two hairpins. The deletion lowered coat-protein yield more than 1000-fold, and the titer of the infectious clone carrying the deletion dropped 10 orders of magnitude as compared with the wild type. Two types of revertants were recovered. One had, in two steps, recruited 18 new nucleotides that served to rebuild the two hairpins and the lost Shine-Dalgarno sequence. The other type had deleted an additional six nucleotides, which allowed the reconstruction of the Shine-Dalgarno sequence and the initiator hairpin, albeit by sacrificing the remnants of the other stem-loop. The results visualize the immense genetic repertoire created by, what appears as, random RNA recombination. It would seem that in this genetic ensemble every possible new RNA combination is represented.

Evolutionary changes in the expression pattern of a developmentally essential gene in three Drosophila species.

The hypothesis that morphological evolution may largely result from changes in gene regulation rather than gene structure has been difficult to test. Morphological differences among insects are often apparent in the cuticle structures produced. The dopa decarboxylase (Ddc) and alpha-methyldopa hypersensitive (amd) genes arose from an ancient gene duplication. In Drosophila, they have evolved nonoverlapping functions, including the production of distinct types of cuticle, and for Ddc, the production of the neurotransmitters, dopamine and serotonin. The amd gene is particularly active in the production of specialized flexible cuticles in the developing embryo. We have compared the pattern of amd expression in three Drosophila species. Several regions of expression conserved in all three species but, surprisingly, a unique domain of expression is found in Drosophila simulans that does occur in the closely related (2-5 million years) Drosophila melanogaster or in the more remote (40-50 million years) Drosophila virilis. The "sudden" appearance of a completely new and robust domain of expression provides a glimpse of evolutionary variation resulting from changes in regulation of structural gene expression.

Chaperonin-facilitated protein folding: optimization of rate and yield by an iterative annealing mechanism.

We develop a heuristic model for chaperonin-facilitated protein folding, the iterative annealing mechanism, based on theoretical descriptions of "rugged" conformational free energy landscapes for protein folding, and on experimental evidence that (i) folding proceeds by a nucleation mechanism whereby correct and incorrect nucleation lead to fast and slow folding kinetics, respectively, and (ii) chaperonins optimize the rate and yield of protein folding by an active ATP-dependent process. The chaperonins GroEL and GroES catalyze the folding of ribulose bisphosphate carboxylase at a rate proportional to the GroEL concentration. Kinetically trapped folding-incompetent conformers of ribulose bisphosphate carboxylase are converted to the native state in a reaction involving multiple rounds of quantized ATP hydrolysis by GroEL. We propose that chaperonins optimize protein folding by an iterative annealing mechanism; they repeatedly bind kinetically trapped conformers, randomly disrupt their structure, and release them in less folded states, allowing substrate proteins multiple opportunities to find pathways leading to the most thermodynamically stable state. By this mechanism, chaperonins greatly expand the range of environmental conditions in which folding to the native state is possible. We suggest that the development of this device for optimizing protein folding was an early and significant evolutionary event.

Real time optimization in chemical process: evaluation of strategies, improvements and industrial application.

The increasing economic competition drives the industry to implement tools that improve their processes efficiencies. The process automation is one of these tools, and the Real Time Optimization (RTO) is an automation methodology that considers economic aspects to update the process control in accordance with market prices and disturbances. Basically, RTO uses a steady-state phenomenological model to predict the process behavior, and then, optimizes an economic objective function subject to this model. Although largely implemented in industry, there is not a general agreement about the benefits of implementing RTO due to some limitations discussed in the present work: structural plant/model mismatch, identifiability issues and low frequency of set points update. Some alternative RTO approaches have been proposed in literature to handle the problem of structural plant/model mismatch. However, there is not a sensible comparison evaluating the scope and limitations of these RTO approaches under different aspects. For this reason, the classical two-step method is compared to more recently derivative-based methods (Modifier Adaptation, Integrated System Optimization and Parameter estimation, and Sufficient Conditions of Feasibility and Optimality) using a Monte Carlo methodology. The results of this comparison show that the classical RTO method is consistent, providing a model flexible enough to represent the process topology, a parameter estimation method appropriate to handle measurement noise characteristics and a method to improve the sample information quality. At each iteration, the RTO methodology updates some key parameter of the model, where it is possible to observe identifiability issues caused by lack of measurements and measurement noise, resulting in bad prediction ability. Therefore, four different parameter estimation approaches (Rotational Discrimination, Automatic Selection and Parameter estimation, Reparametrization via Differential Geometry and classical nonlinear Least Square) are evaluated with respect to their prediction accuracy, robustness and speed. The results show that the Rotational Discrimination method is the most suitable to be implemented in a RTO framework, since it requires less a priori information, it is simple to be implemented and avoid the overfitting caused by the Least Square method. The third RTO drawback discussed in the present thesis is the low frequency of set points update, this problem increases the period in which the process operates at suboptimum conditions. An alternative to handle this problem is proposed in this thesis, by integrating the classic RTO and Self-Optimizing control (SOC) using a new Model Predictive Control strategy. The new approach demonstrates that it is possible to reduce the problem of low frequency of set points updates, improving the economic performance. Finally, the practical aspects of the RTO implementation are carried out in an industrial case study, a Vapor Recompression Distillation (VRD) process located in Paulínea refinery from Petrobras. The conclusions of this study suggest that the model parameters are successfully estimated by the Rotational Discrimination method; the RTO is able to improve the process profit in about 3%, equivalent to 2 million dollars per year; and the integration of SOC and RTO may be an interesting control alternative for the VRD process.

An evolutionary approach to the delineation of functional areas based on travel-to-work flows

This paper presents a new approach to the delineation of local labor markets based on evolutionary computation. The aim of the exercise is the division of a given territory into functional regions based on travel-to-work flows. Such regions are defined so that a high degree of inter-regional separation and of intra-regional integration in both cases in terms of commuting flows is guaranteed. Additional requirements include the absence of overlap between delineated regions and the exhaustive coverage of the whole territory. The procedure is based on the maximization of a fitness function that measures aggregate intra-region interaction under constraints of inter-region separation and minimum size. In the experimentation stage, two variations of the fitness function are used, and the process is also applied as a final stage for the optimization of the results from one of the most successful existing methods, which are used by the British authorities for the delineation of travel-to-work areas (TTWAs). The empirical exercise is conducted using real data for a sufficiently large territory that is considered to be representative given the density and variety of travel-to-work patterns that it embraces. The paper includes the quantitative comparison with alternative traditional methods, the assessment of the performance of the set of operators which has been specifically designed to handle the regionalization problem and the evaluation of the convergence process. The robustness of the solutions, something crucial in a research and policy-making context, is also discussed in the paper.

Multi-objective adaptive evolutionary strategy for tuning compilations

Tuning compilations is the process of adjusting the values of a compiler options to improve some features of the final application. In this paper, a strategy based on the use of a genetic algorithm and a multi-objective scheme is proposed to deal with this task. Unlike previous works, we try to take advantage of the knowledge of this domain to provide a problem-specific genetic operation that improves both the speed of convergence and the quality of the results. The evaluation of the strategy is carried out by means of a case of study aimed to improve the performance of the well-known web server Apache. Experimental results show that a 7.5% of overall improvement can be achieved. Furthermore, the adaptive approach has shown an ability to markedly speed-up the convergence of the original strategy.

Tuning compilations by multi-objective optimization: Application to Apache web server

Modern compilers present a great and ever increasing number of options which can modify the features and behavior of a compiled program. Many of these options are often wasted due to the required comprehensive knowledge about both the underlying architecture and the internal processes of the compiler. In this context, it is usual, not having a single design goal but a more complex set of objectives. In addition, the dependencies between different goals are difficult to be a priori inferred. This paper proposes a strategy for tuning the compilation of any given application. This is accomplished by using an automatic variation of the compilation options by means of multi-objective optimization and evolutionary computation commanded by the NSGA-II algorithm. This allows finding compilation options that simultaneously optimize different objectives. The advantages of our proposal are illustrated by means of a case study based on the well-known Apache web server. Our strategy has demonstrated an ability to find improvements up to 7.5% and up to 27% in context switches and L2 cache misses, respectively, and also discovers the most important bottlenecks involved in the application performance.

Parametric Optimization of Inductively Driven Liner Compression Driver System

Thesis (Master's)--University of Washington, 2016-06

Optimization and Machine Learning Frameworks for Complex Network Analysis

Thesis (Ph.D.)--University of Washington, 2016-06

Wurst: a protein threading server with a structural scoring function, sequence profiles and optimized substitution matrices

Wurst is a protein threading program with an emphasis on high quality sequence to structure alignments (http://www.zbh.uni-hamburg.de/wurst). Submitted sequences are aligned to each of about 3000 templates with a conventional dynamic programming algorithm, but using a score function with sophisticated structure and sequence terms. The structure terms are a log-odds probability of sequence to structure fragment compatibility, obtained from a Bayesian classification procedure. A simplex optimization was used to optimize the sequence-based terms for the goal of alignment and model quality and to balance the sequence and structural contributions against each other. Both sequence and structural terms operate with sequence profiles.

Discovery, structural determination, and putative processing of the precursor protein that produces the cyclic trypsin inhibitor sunflower trypsin inhibitor 1

Backbone-cyclized proteins are becoming increasingly well known, although the mechanism by which they are processed from linear precursors is poorly understood. In this report the sequence and structure of the linear precursor of a cyclic trypsin inhibitor, sunflower trypsin inhibitor 1 (SFTI-1) from sunflower seeds, is described. The structure indicates that the major elements of the reactive site loop of SFTI-1 are present before processing. This may have importance for a protease-mediated cyclizing reaction as the rigidity of SFTI-1 may drive the equilibrium of the reaction catalyzed by proteolytic enzymes toward the formation of a peptide bond rather than the normal cleavage reaction. The occurrence of residues in the SFTI-1 precursor susceptible to cleavage by asparaginyl proteases strengthens theories that involve this enzyme in the processing of SFTI-1 and further implicates it in the processing of another family of plant cyclic proteins, the cyclotides. The precursor reported here also indicates that despite strong active site sequence homology, SFTI-1 has no other similarities with the Bowman-Birk trypsin inhibitors, presenting interesting evolutionary questions.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.