The sequence comparison index: A novel method for comparing proteins and proteomes

Historically morphological features were used as the primary means to classify organisms. However, the age of molecular genetics has allowed us to approach this field from the perspective of the organism's genetic code. Early work used highly conserved sequences, such as ribosomal RNA. The increasing number of complete genomes in the public data repositories provides the opportunity to look not only at a single gene, but at organisms' entire parts list. ^ Here the Sequence Comparison Index (SCI) and the Organism Comparison Index (OCI), algorithms and methods to compare proteins and proteomes, are presented. The complete proteomes of 104 sequenced organisms were compared. Over 280 million full Smith-Waterman alignments were performed on sequence pairs which had a reasonable expectation of being related. From these alignments a whole proteome phylogenetic tree was constructed. This method was also used to compare the small subunit (SSU) rRNA from each organism and a tree constructed from these results. The SSU rRNA tree by the SCI/OCI method looks very much like accepted SSU rRNA trees from sources such as the Ribosomal Database Project, thus validating the method. The SCI/OCI proteome tree showed a number of small but significant differences when compared to the SSU rRNA tree and proteome trees constructed by other methods. Horizontal gene transfer does not appear to affect the SCI/OCI trees until the transferred genes make up a large portion of the proteome. ^ As part of this work, the Database of Related Local Alignments (DaRLA) was created and contains over 81 million rows of sequence alignment information. DaRLA, while primarily used to build the whole proteome trees, can also be applied shared gene content analysis, gene order analysis, and creating individual protein trees. ^ Finally, the standard BLAST method for analyzing shared gene content was compared to the SCI method using 4 spirochetes. The SCI system performed flawlessly, finding all proteins from one organism against itself and finding all the ribosomal proteins between organisms. The BLAST system missed some proteins from its respective organism and failed to detect small ribosomal proteins between organisms. ^

Learning Models of Gene Expression from Synthetic DNA Sequences

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

EVOLUTIONARY BIOLOGY IN BIODIVERSITY SCIENCE, CONSERVATION, AND POLICY: A CALL TO ACTION

Evolutionary biologists have long endeavored to document how many species exist on Earth, to understand the processes by which biodiversity waxes and wanes, to document and interpret spatial patterns of biodiversity, and to infer evolutionary relationships. Despite the great potential of this knowledge to improve biodiversity science, conservation, and policy, evolutionary biologists have generally devoted limited attention to these broader implications. Likewise, many workers in biodiversity science have underappreciated the fundamental relevance of evolutionary biology. The aim of this article is to summarize and illustrate some ways in which evolutionary biology is directly relevant We do so in the context of four broad areas: (1) discovering and documenting biodiversity, (2) understanding the causes of diversification, (3) evaluating evolutionary responses to human disturbances, and (4) implications for ecological communities, ecosystems, and humans We also introduce bioGENESIS, a new project within DIVERSITAS launched to explore the potential practical contributions of evolutionary biology In addition to fostering the integration of evolutionary thinking into biodiversity science, bioGENESIS provides practical recommendations to policy makers for incorporating evolutionary perspectives into biodiversity agendas and conservation. We solicit your involvement in developing innovative ways of using evolutionary biology to better comprehend and stem the loss of biodiversity.

The impact of a Classroom Performance System on learning gains in a biology course for science majors

This study was conducted to determine if the use of the technology known as Classroom Performance System (CPS), specifically referred to as "Clickers", improves the learning gains of students enrolled in a biology course for science majors. CPS is one of a group of developing technologies adapted for providing feedback in the classroom using a learner-centered approach. It supports and facilitates discussion among students and between them and teachers, and provides for participation by passive students. Advocates, influenced by constructivist theories, claim increased academic achievement. In science teaching, the results have been mixed, but there is some evidence of improvements in conceptual understanding. The study employed a pretest-posttest, non-equivalent groups experimental design. The sample consisted of 226 participants in six sections of a college biology course at a large community college in South Florida with two instructors trained in the use of clickers. Each instructor randomly selected their sections into CPS (treatment) and non-CPS (control) groups. All participants filled out a survey that included demographic data at the beginning of the semester. The treatment group used clicker questions throughout, with discussions as necessary, whereas the control groups answered the same questions as quizzes, similarly engaging in discussion where necessary. The learning gains were assessed on a pre/post-test basis. The average learning gains, defined as the actual gain divided by the possible gain, were slightly better in the treatment group than in the control group, but the difference was statistically non-significant. An Analysis of Covariance (ANCOVA) statistic with pretest scores as the covariate was conducted to test for significant differences between the treatment and control groups on the posttest. A second ANCOVA was used to determine the significance of differences between the treatment and control groups on the posttest scores, after controlling for sex, GPA, academic status, experience with clickers, and instructional style. The results indicated a small increase in learning gains but these were not statistically significant. The data did not support an increase in learning based on the use of the CPS technology. This study adds to the body of research that questions whether CPS technology merits classroom adaptation.

The Impact of a Classroom Performance System on Learning Gains in a Biology Course for Science Majors

This study was conducted to determine if the use of the technology known as Classroom Performance System (CPS), specifically referred to as “Clickers”, improves the learning gains of students enrolled in a biology course for science majors. CPS is one of a group of developing technologies adapted for providing feedback in the classroom using a learner-centered approach. It supports and facilitates discussion among students and between them and teachers, and provides for participation by passive students. Advocates, influenced by constructivist theories, claim increased academic achievement. In science teaching, the results have been mixed, but there is some evidence of improvements in conceptual understanding. The study employed a pretest-posttest, non-equivalent groups experimental design. The sample consisted of 226 participants in six sections of a college biology course at a large community college in South Florida with two instructors trained in the use of clickers. Each instructor randomly selected their sections into CPS (treatment) and non-CPS (control) groups. All participants filled out a survey that included demographic data at the beginning of the semester. The treatment group used clicker questions throughout, with discussions as necessary, whereas the control groups answered the same questions as quizzes, similarly engaging in discussion where necessary. The learning gains were assessed on a pre/post-test basis. The average learning gains, defined as the actual gain divided by the possible gain, were slightly better in the treatment group than in the control group, but the difference was statistically non-significant. An Analysis of Covariance (ANCOVA) statistic with pretest scores as the covariate was conducted to test for significant differences between the treatment and control groups on the posttest. A second ANCOVA was used to determine the significance of differences between the treatment and control groups on the posttest scores, after controlling for sex, GPA, academic status, experience with clickers, and instructional style. The results indicated a small increase in learning gains but these were not statistically significant. The data did not support an increase in learning based on the use of the CPS technology. This study adds to the body of research that questions whether CPS technology merits classroom adaptation.

Fragment-guided approach to incorporating structural information into a CoMFA study: BACE-1 as an example

Alzheimer`s disease is an ultimately fatal neurodegenerative disease, and BACE-1 has become an attractive validated target for its therapy, with more than a hundred crystal structures deposited in the PDB. In the present study, we present a new methodology that integrates ligand-based methods with structural information derived from the receptor. 128 BACE-1 inhibitors recently disclosed by GlaxoSmithKline R&D were selected specifically because the crystal structures of 9 of these compounds complexed to BACE-1, as well as five closely related analogs, have been made available. A new fragment-guided approach was designed to incorporate this wealth of structural information into a CoMFA study, and the methodology was systematically compared to other popular approaches, such as docking, for generating a molecular alignment. The influence of the partial charges calculation method was also analyzed. Several consistent and predictive models are reported, including one with r (2) = 0.88, q (2) = 0.69 and r (pred) (2) = 0.72. The models obtained with the new methodology performed consistently better than those obtained by other methodologies, particularly in terms of external predictive power. The visual analyses of the contour maps in the context of the enzyme drew attention to a number of possible opportunities for the development of analogs with improved potency. These results suggest that 3D-QSAR studies may benefit from the additional structural information added by the presented methodology.

Extensive structural change of the envelope protein of dengue virus induced by a tuned ionic strength: conformational and energetic analyses

The Dengue has become a global public health threat, with over 100 million infections annually; to date there is no specific vaccine or any antiviral drug. The structures of the envelope (E) proteins of the four known serotype of the dengue virus (DENV) are already known, but there are insufficient molecular details of their structural behavior in solution in the distinct environmental conditions in which the DENVs are submitted, from the digestive tract of the mosquito up to its replication inside the host cell. Such detailed knowledge becomes important because of the multifunctional character of the E protein: it mediates the early events in cell entry, via receptor endocytosis and, as a class II protein, participates determinately in the process of membrane fusion. The proposed infection mechanism asserts that once in the endosome, at low pH, the E homodimers dissociate and insert into the endosomal lipid membrane, after an extensive conformational change, mainly on the relative arrangement of its three domains. In this work we employ all-atom explicit solvent Molecular Dynamics simulations to specify the thermodynamic conditions in that the E proteins are induced to experience extensive structural changes, such as during the process of reducing pH. We study the structural behavior of the E protein monomer at acid pH solution of distinct ionic strength. Extensive simulations are carried out with all the histidine residues in its full protonated form at four distinct ionic strengths. The results are analyzed in detail from structural and energetic perspectives, and the virtual protein movements are described by means of the principal component analyses. As the main result, we found that at acid pH and physiological ionic strength, the E protein suffers a major structural change; for lower or higher ionic strengths, the crystal structure is essentially maintained along of all extensive simulations. On the other hand, at basic pH, when all histidine residues are in the unprotonated form, the protein structure is very stable for ionic strengths ranging from 0 to 225 mM. Therefore, our findings support the hypothesis that the histidines constitute the hot points that induce configurational changes of E protein in acid pH, and give extra motivation to the development of new ideas for antivirus compound design.

Structure-activity relationships for a new family of sulfonylurea herbicides

Acetohydroxyacid synthase (AHAS; EC 2.2.1.6) catalyzes the first common step in branched-chain amino acid biosynthesis. The enzyme is inhibited by several chemical classes of compounds and this inhibition is the basis of action of the sulfonylurea and imidazolinone herbicides. The commercial sulfonylureas contain a pyrimidine or a triazine ring that is substituted at both meta positions, thus obeying the initial rules proposed by Levitt. Here we assess the activity of 69 monosubstituted sulfonylurea analogs and related compounds as inhibitors of pure recombinant Arabidopsis thaliana AHAS and show that disubstitution is not absolutely essential as exemplified by our novel herbicide, monosulfuron (2-nitro-N-(4'-methyl-pyrimidin-2'-yl) phenyl-sulfonylurea), which has a pyrimidine ring with a single meta substituent. A subset of these compounds was tested for herbicidal activity and it was shown that their effect in vivo correlates well with their potency in vitro as AHAS inhibitors. Three-dimensional quantitative structure-activity relationships were developed using comparative molecular field analysis and comparative molecular similarity indices analysis. For the latter, the best result was obtained when steric, electrostatic, hydrophobic and H-bond acceptor factors were taken into consideration. The resulting fields were mapped on to the published crystal structure of the yeast enzyme and it was shown that the steric and hydrophobic fields are in good agreement with sulfonylurea-AHAS interaction geometry.

Topological side-chain classification of beta-turns: Ideal motifs for peptidomimetic development

beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi 2, psi 2, phi 3 and psi 3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C-alpha-C-beta vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C-alpha-C-beta vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Application of computer-aided tomography techniques to visualize kelp holdfast structure reveals the importance of habitat complexity for supporting marine biodiversity

Ecosystem engineers that increase habitat complexity are keystone species in marine systems, increasing shelter and niche availability, and therefore biodiversity. For example, kelp holdfasts form intricate structures and host the largest number of organisms in kelp ecosystems. However, methods that quantify 3D habitat complexity have only seldom been used in marine habitats, and never in kelp holdfast communities. This study investigated the role of kelp holdfasts (Laminaria hyperborea) in supporting benthic faunal biodiversity. Computer-aided tomography (CT-) scanning was used to quantify the three-dimensional geometrical complexity of holdfasts, including volume, surface area and surface fractal dimension (FD). Additionally, the number of haptera, number of haptera per unit of volume, and age of kelps were estimated. These measurements were compared to faunal biodiversity and community structure, using partial least-squares regression and multivariate ordination. Holdfast volume explained most of the variance observed in biodiversity indices, however all other complexity measures also strongly contributed to the variance observed. Multivariate ordinations further revealed that surface area and haptera per unit of volume accounted for the patterns observed in faunal community structure. Using 3D image analysis, this study makes a strong contribution to elucidate quantitative mechanisms underlying the observed relationship between biodiversity and habitat complexity. Furthermore, the potential of CT-scanning as an ecological tool is demonstrated, and a methodology for its use in future similar studies is established. Such spatially resolved imager analysis could help identify structurally complex areas as biodiversity hotspots, and may support the prioritization of areas for conservation.

Validity of the computer science and applications (CSA) activity monitor in children

Purpose The purpose of this study was to evaluate the validity of the CSA activity monitor as a measure of children's physical activity using energy expenditure (EE) as a criterion measure. Methods Thirty subjects aged 10 to 14 performed three 5-min treadmill bouts at 3, 4, and 6 mph, respectively. While on the treadmill, subjects wore CSA (WAM 7164) activity monitors on the right and left hips. (V) over dot O-2 was monitored continuously by an automated system. EE was determined by multiplying the average (V) over dot O-2 by the caloric equivalent of the mean respiratory exchange ratio. Results Repeated measures ANOVA indicated that both CSA monitors were sensitive to changes in treadmill speed. Mean activity counts from each CSA unit were not significantly different and the intraclass reliability coefficient for the two CSA units across all speeds was 0.87. Activity counts from both CSA units were strongly correlated with EE (r = 0.86 and 0.87, P < 0.001). An EE prediction equation was developed from 20 randomly selected subjects and cross-validated on the remaining 10. The equation predicted mean EE within 0.01 kcal.min(-1). The correlation between actual and predicted values was 0.93 (P < 0.01) and the SEE was 0.93 kcal.min(-1). Conclusion These data indicate that the CSA monitor is a valid and reliable tool for quantifying treadmill walking and running in children.