VTechWorks Repository :: Browsing by Author "Tyler, Brett M."

Browsing by Author "Tyler, Brett M."

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The Algebra of Systems Biology
Veliz-Cuba, Alan A. (Virginia Tech, 2010-07-05)
In order to understand biochemical networks we need to know not only how their parts work but also how they interact with each other. The goal of systems biology is to look at biological systems as a whole to understand how interactions of the parts can give rise to complex dynamics. In order to do this efficiently, new techniques have to be developed. This work shows how tools from mathematics are suitable to study problems in systems biology such as modeling, dynamics prediction, reverse engineering and many others. The advantage of using mathematical tools is that there is a large number of theory, algorithms and software available. This work focuses on how algebra can contribute to answer questions arising from systems biology.
Algebraic theory for discrete models in systems biology
Hinkelmann, Franziska (Virginia Tech, 2011-08-01)
This dissertation develops algebraic theory for discrete models in systems biology. Many discrete model types can be translated into the framework of polynomial dynamical systems (PDS), that is, time- and state-discrete dynamical systems over a finite field where the transition function for each variable is given as a polynomial. This allows for using a range of theoretical and computational tools from computer algebra, which results in a powerful computational engine for model construction, parameter estimation, and analysis methods. Formal definitions and theorems for PDS and the concept of PDS as models of biological systems are introduced in section 1.3. Constructing a model for given time-course data is a challenging problem. Several methods for reverse-engineering, the process of inferring a model solely based on experimental data, are described briefly in section 1.3. If the underlying dependencies of the model components are known in addition to experimental data, inferring a "good" model amounts to parameter estimation. Chapter 2 describes a parameter estimation algorithm that infers a special class of polynomials, so called nested canalyzing functions. Models consisting of nested canalyzing functions have been shown to exhibit desirable biological properties, namely robustness and stability. The algorithm is based on the parametrization of nested canalyzing functions. To demonstrate the feasibility of the method, it is applied to the cell-cycle network of budding yeast. Several discrete model types, such as Boolean networks, logical models, and bounded Petri nets, can be translated into the framework of PDS. Section 3 describes how to translate agent-based models into polynomial dynamical systems. Chapter 4, 5, and 6 are concerned with analysis of complex models. Section 4 proposes a new method to identify steady states and limit cycles. The method relies on the fact that attractors correspond to the solutions of a system of polynomials over a finite field, a long-studied problem in algebraic geometry which can be efficiently solved by computing Gröbner bases. Section 5 introduces a bit-wise implementation of a Gröbner basis algorithm for Boolean polynomials. This implementation has been incorporated into the core engine of Macaulay 2. Chapter 6 discusses bistability for Boolean models formulated as polynomial dynamical systems.
Ancestral Genome Reconstruction in Bacteria
Yang, Kuan (Virginia Tech, 2012-06-06)
The rapid accumulation of numerous sequenced genomes has provided a golden opportunity for ancestral state reconstruction studies, especially in the whole genome reconstruction area. However, most ancestral genome reconstruction methods developed so far only focus on gene or replicon sequences instead of whole genomes. They rely largely on either detailed modeling of evolutionary events or edit distance computation, both of which can be computationally prohibitive for large data sets. Hence, most of these methods can only be applied to a small number of features and species. In this dissertation, we describe the design, implementation, and evaluation of an ancestral genome reconstruction system (REGEN) for bacteria. It is the first bacterial genome reconstruction tool that focuses on ancestral state reconstruction at the genome scale instead of the gene scale. It not only reconstructs ancestral gene content and contiguous gene runs using either a maximum parsimony or a maximum likelihood criterion but also replicon structures of each ancestor. Based on the reconstructed genomes, it can infer all major events at both the gene scale, such as insertion, deletion, and translocation, and the replicon scale, such as replicon gain, loss, and merge. REGEN finishes by producing a visual representation of the entire evolutionary history of all genomes in the study. With a model-free reconstruction method at its core, the computational requirement for ancestral genome reconstruction is reduced sufficiently for the tool to be applied to large data sets with dozens of genomes and thousands of features. To achieve as accurate a reconstruction as possible, we also develop a homologous gene family prediction tool for preprocessing. Furthermore, we build our in-house Prokaryote Genome Evolution simulator (PEGsim) for evaluation purposes. The homologous gene family prediction refinement module can refine homologous gene family predictions generated by third party de novo prediction programs by combining phylogeny and local gene synteny. We show that such refinement can be accomplished for up to 80% of homologous gene family predictions with ambiguity (mixed families). The genome evolution simulator, PEGsim, is the first random events based high level bacteria genome evolution simulator with models for all common evolutionary events at the gene, replicon, and genome scales. The concepts of conserved gene runs and horizontal gene transfer (HGT) are also built in. We show the validation of PEGsim itself and the evaluation of the last reconstruction component with simulated data produced by it. REGEN, REconstruction of GENomes, is an ancestral genome reconstruction tool based on the concept of neighboring gene pairs (NGPs). Although it does not cover the reconstruction of actual nucleotide sequences, it is capable of reconstructing gene content, contiguous genes runs, and replicon structure of each ancestor using either a maximum parsimony or a maximum likelihood criterion. Based on the reconstructed genomes, it can infer all major events at both the gene scale, such as insertion, deletion, and translocation, and the replicon scale, such as replicon gain, loss, and merge. REGEN finishes by producing a visual representation of the entire evolutionary history of all genomes in the study.
Automatic Reconstruction of the Building Blocks of Molecular Interaction Networks
Rivera, Corban G. (Virginia Tech, 2008-08-11)
High-throughput whole-genome biological assays are highly intricate and difficult to interpret. The molecular interaction networks generated from evaluation of those experiments suggest that cellular functions are carried out by modules of interacting molecules. Reverse-engineering the modular structure of cellular interaction networks has the promise of significantly easing their analysis. We hypothesize that: • cellular wiring diagrams can be decomposed into overlapping modules, where each module is a set of coherently-interacting molecules and • a cell responds to a stress or a stimulus by appropriately modulating the activities of a subset of these modules. Motivated by these hypotheses, we develop models and algorithms that can reverse-engineer molecular modules from large-scale functional genomic data. We address two major problems: 1. Given a wiring diagram and genome-wide gene expression data measured after the application of a stress or in a disease state, compute the active network of molecular interactions perturbed by the stress or the disease. 2. Given the active networks for multiple stresses, stimuli, or diseases, compute a set of network legos, which are molecular modules with the property that each active network can be expressed as an appropriate combination of a subset of modules. To address the first problem, we propose an approach that computes the most-perturbed subgraph of a curated pathway of molecular interactions in a disease state. Our method is based on a novel score for pathway perturbation that incorporates both differential gene expression and the interaction structure of the pathway. We apply our method to a compendium of cancer types. We show that the significance of the most perturbed sub-pathway is frequently larger than that of the entire pathway. We identify an association that suggests that IL-2 infusion may have a similar therapeutic effect in bladder cancer as it does in melanoma. We propose two models to address the second problem. First, we formulate a Boolean model for constructing network legos from a set of active networks. We reduce the problem of computing network legos to that of constructing closed biclusters in a binary matrix. Applying this method to a compendium of 13 stresses on human cells, we automatically detect that about four to six hours after treatment with chemicals cause endoplasmic reticulum stress, fibroblasts shut down the cell cycle far more aggressively than fibroblasts or HeLa cells do in response to other treatments. Our second model represents each active network as an additive combination of network legos. We formulate the problem as one of computing network legos that can be used to recover active networks in an optimal manner. We use existing methods for non-negative matrix approximation to solve this problem. We apply our method to a human cancer dataset including 190 samples from 18 cancers. We identify a network lego that associates integrins and matrix metalloproteinases in ovarian adenoma and other cancers and a network lego including the retinoblastoma pathway associated with multiple leukemias.
A Biclustering Approach to Combinatorial Transcription Control
Srinivasan, Venkataraghavan (Virginia Tech, 2005-07-06)
Combinatorial control of transcription is a well established phenomenon in the cell. Multiple transcription factors often bind to the same transcriptional control region of a gene and interact with each other to control the expression of the gene. It is thus necessary to consider the joint conservation of sequence pairs in order to identify combinations of binding sites to which the transcription factors bind. Conventional motif finding algorithms fail to address this issue. We propose a novel biclustering algorithm based on random sampling to identify candidate binding site combinations. We establish bounds on the various parameters to the algorithm and study the conditions under which the algorithm is guaranteed to identify candidate binding sites. We analyzed a yeast cell cycle gene expression data set using our algorithm and recovered certain novel combinations of binding sites, besides those already reported in the literature.
Common and contrasting themes in host cell-targeted effectors from bacterial, fungal, oomycete and nematode plant symbionts described using the Gene Ontology
Torto-Alalibo, Trudy; Collmer, Candace W.; Lindeberg, Magdalen; Bird, David; Collmer, Alan; Tyler, Brett M. (2009-02-19)
A wide diversity of plant-associated symbionts, including microbes, produce proteins that can enter host cells, or are injected into host cells in order to modify the physiology of the host to promote colonization. These molecules, termed effectors, commonly target the host defense signaling pathways in order to suppress the defense response. Others target the gene expression machinery or trigger specific modifications to host morphology or physiology that promote the nutrition and proliferation of the symbiont. When recognized by the host's surveillance machinery, which includes cognate resistance (R) gene products, defense responses are engaged to restrict pathogen proliferation. Effectors from diverse symbionts may be delivered into plant cells via varied mechanisms, including whole organism cellular entry (viruses, some bacteria and fungi), type III and IV secretion (in bacteria), physical injection (nematodes and insects) and protein translocation signal sequences (oomycetes and fungi). This mini-review will summarize both similarities and differences in effectors and effector delivery systems found in diverse plant-associated symbionts as well as how these are described with Plant-Associated Microbe Gene Ontology (PAMGO) terms.
Common themes in nutrient acquisition by plant symbiotic microbes, described by the Gene Ontology
Chibucos, Marcus C.; Tyler, Brett M. (2009-02-19)
A critical function for symbionts is the acquisition of nutrients from their host. Relationships between hosts and symbionts range from biotrophic mutualism to necrotrophic parasitism, with a corresponding range of structures to facilitate nutrient flow between host and symbiont. Here, we review common themes among the nutrient acquisition strategies of a range of plant symbiotic microorganisms, including mutualistic symbionts, biotrophic pathogens that feed from living tissue, necrotrophic pathogens that kill host tissue, and hemibiotrophic pathogens that switch from biotrophy to necrotrophy. We show how Gene Ontology (GO) terms developed by the Plant-Associated Microbe Gene Ontology (PAMGO) Consortium can be used for describing commonalities in nutrient acquisition among diverse plant symbionts. Where appropriate, parallels found among animal symbionts are also highlighted.
Comparative and Functional Genomic Studies of Histophilus somni (Haemophilus somnus)
Siddaramappa, Shivakumara Swamy (Virginia Tech, 2007-04-09)
Histophilus somni is a commensal of the mucosal surfaces of respiratory and reproductive tracts of cattle and sheep. However, as an opportunistic pathogen, H. somni can cause diseases such as pneumonia, myocarditis, abortion, arthritis, and meningo-encephalitis. Previously, several virulence factors/mechanisms had been identified in H. somni of which the phase-variable lipooligosaccharide, induction of host cell apoptosis, intraphagocytic survival, and immunoglobulin Fc binding proteins were well characterized. To further understand the biological properties of H. somni, the genomes of pneumonia strain 2336 and preputial strain 129Pt have been sequenced. Using the genome sequence data and comparative analyses with other members of the Pasteurellaceae, putative genes that encode proteases, restriction-modification enzymes, hemagglutinins, glycosyltransferases, kinases, helicases, and adhesins have been identified in H. somni. Most of the H. somni strain-specific genes were found to be associated with prophage-like sequences, plasmids, and/or transposons. Therefore, it is likely that these mobile genetic elements played a significant role in creating genomic diversity and phenotypic variability among strains of H. somni. Functional characterization of H. somni luxS in the genomic context revealed that the gene encodes S-ribosylhomocysteinase that can complement biosynthesis of AI-2 quorum sensing signal molecules in Escherichia coli DH5alpha. It was also found that several pathogenic isolates of H. somni form a prominent biofilm and that luxS as well as phosphorylcholine expression can influence biofilm formation by H. somni. In conclusion, comparative analyses of the genomes and functional characterization of putative genes have shed new light on the versatility and evolution of H. somni.
Copy Number Variation and Transcriptional Polymorphisms of Phytophthora sojae RXLR Effector Genes Avr1a and Avr3a
Qutob, Dinah; Tedman-Jones, Jennifer; Dong, Suomeng; Kuflu, Kuflom; Pham, Hai; Wang, Yuanchao; Dou, Daolong; Kale, Shiv D.; Arredondo, Felipe D.; Tyler, Brett M.; Gijzen, Mark (Public Library of Science, 2009-04-03)
The importance of segmental duplications and copy number variants as a source of genetic and phenotypic variation is gaining greater appreciation, in a variety of organisms. Now, we have identified the Phytophthora sojae avirulence genes Avr1a and Avr3a and demonstrate how each of these Avr genes display copy number variation in different strains of P. sojae. The Avr1a locus is a tandem array of four near-identical copies of a 5.2 kb DNA segment. Two copies encoding Avr1a are deleted in some P. sojae strains, causing changes in virulence. In other P. sojae strains, differences in transcription of Avr1a result in gain of virulence. For Avr3a, there are four copies or one copy of this gene, depending on the P. sojae strain. In P. sojae strains with multiple copies of Avr3a, this gene occurs within a 10.8 kb segmental duplication that includes four other genes. Transcriptional differences of the Avr3a gene among P. sojae strains cause changes in virulence. To determine the extent of duplication within the superfamily of secreted proteins that includes Avr1a and Avr3a, predicted RXLR effector enes from the P. sojae and the P. ramorum genomes were compared by counting trace file matches from whole genome shotgun sequences. The results indicate that multiple, near-identical copies of RXLR effector genes are prevalent in oomycete genomes. We propose that multiple copies of particular RXLR effectors may contribute to pathogen fitness. However, recognition of these effectors by plant immune systems results in selection for pathogen strains with deleted or transcriptionally silenced gene copies.
Data integration and visualization for systems biology data
Cheng, Hui (Virginia Tech, 2010-10-27)
Systems biology aims to understand cellular behavior in terms of the spatiotemporal interactions among cellular components, such as genes, proteins and metabolites. Comprehensive visualization tools for exploring multivariate data are needed to gain insight into the physiological processes reflected in these molecular profiles. Data fusion methods are required to integratively study high-throughput transcriptomics, metabolomics and proteomics data combined before systems biology can live up to its potential. In this work I explored mathematical and statistical methods and visualization tools to resolve the prominent issues in the nature of systems biology data fusion and to gain insight into these comprehensive data. In order to choose and apply multivariate methods, it is important to know the distribution of the experimental data. Chi square Q-Q plot and violin plot were applied to all M. truncatula data and V. vinifera data, and found most distributions are right-skewed (Chapter 2). The biplot display provides an effective tool for reducing the dimensionality of the systems biological data and displaying the molecules and time points jointly on the same plot. Biplot of M. truncatula data revealed the overall system behavior, including unidentified compounds of interest and the dynamics of the highly responsive molecules (Chapter 3). The phase spectrum computed from the Fast Fourier transform of the time course data has been found to play more important roles than amplitude in the signal reconstruction. Phase spectrum analyses on in silico data created with two artificial biochemical networks, the Claytor model and the AB2 model proved that phase spectrum is indeed an effective tool in system biological data fusion despite the data heterogeneity (Chapter 4). The difference between data integration and data fusion are further discussed. Biplot analysis of scaled data were applied to integrate transcriptome, metabolome and proteome data from the V. vinifera project. Phase spectrum combined with k-means clustering was used in integrative analyses of transcriptome and metabolome of the M. truncatula yeast elicitation data and of transcriptome, metabolome and proteome of V. vinifera salinity stress data. The phase spectrum analysis was compared with the biplot display as effective tools in data fusion (Chapter 5). The results suggest that phase spectrum may perform better than the biplot. This work was funded by the National Science Foundation Plant Genome Program, grant DBI-0109732, and by the Virginia Bioinformatics Institute.
Dissection of Regulatory Networks Mediating Resistance and Susceptibility of Arabidopsis thaliana to the Downy Mildew Pathogen Hyaloperonospora parasitica
Hoff, Troy Colston (Virginia Tech, 2008-12-19)
Plants and pathogenic microorganisms are in constant conflict with each other. Understanding the molecular networks that trigger resistance, along with the molecular networks that pathogens might co-opt to infect susceptible plants, is important for developing the integrated, holistic perspective that is necessary for innovative development of engineered resistance to current and emerging pathogens. The first objective of the dissertation was to increase the understanding of mechanisms by which plants recognize pathogen attack and mount an appropriate defense response. These experiments focused on resistance triggered by the Arabidopsis thaliana R gene, RPP7, which encodes a coiled-coil nucleotide binding-leucine-rich repeat (CC-NB-LRR) protein that activates race-specific resistance to the downy mildew pathogen, Hyaloperonospora parasitica (Hpa). Previously-published genetic epistasis tests have established that RPP7 activates defense responses through a signaling mechanism that does not require accumulation of salicylic acid (SA), or components of the ethylene and jasmonate response pathways. Furthermore, RPP7 is not strongly compromised by mutations in genes associated with defense signal transduction (PAD4, NDR1, NPR1, RAR1). Double mutant combinations of these signal transduction components were analyzed to detect additive or functionally-redundant contributions to RPP7-dependent resistance. Most of the double mutants support an enhanced level of asexual sporulation compared to the single mutant parental lines. Time-course experiments with histochemical stains revealed that these double mutants delay, but do not suppress, the oxidative burst and the hypersensitive response. These results suggest that RPP7 activates multiple signaling pathways, each of which makes incremental contributions to the timing of defense activation. The second objective of the dissertation was to investigate the role that auxin plays in enabling virulent H. parasitica to colonize Arabidopsis. Transcript profiling revealed induction of auxin-associated genes in response to infection of Arabidopsis thaliana by virulent strains of the oÃ¶mycete pathogen, H. parasitica. Experiments with the DR5
Distinctive Expansion of Potential Virulence Genes in the Genome of the Oomycete Fish Pathogen Saprolegnia parasitica
Jiang, Rays H. Y.; de Bruijn, Irene; Haas, Brian J.; Belmonte, Rodrigo; Loebach, Lars; Christie, James; van den Ackerveken, Guido; Bottin, Arnaud; Bulone, Vincent; Diaz-Moreno, Sara M.; Dumas, Bernard; Fan, Lin; Gaulin, Elodie; Govers, Francine; Grenville-Briggs, Laura J.; Horner, Neil R.; Levin, Joshua Z.; Mammella, Marco; Meijer, Harold J. G.; Morris, Paul; Nusbaum, Chad; Oome, Stan; Phillips, Andrew J.; van Rooyen, David; Rzeszutek, Elzbieta; Saraiva, Marcia; Secombes, Chris J.; Seidl, Michael F.; Snel, Berend; Stassen, Joost H. M.; Sykes, Sean; Tripathy, Sucheta; van den Berg, Herbert; Vega-Arreguin, Julio C.; Wawra, Stephan; Young, Sarah K.; Zeng, Qiandong; Dieguez-Uribeondo, Javier; Russ, Carsten; Tyler, Brett M.; van West, Pieter (PLoS, 2013-06)
Oomycetes in the class Saprolegniomycetidae of the Eukaryotic kingdom Stramenopila have evolved as severe pathogens of amphibians, crustaceans, fish and insects, resulting in major losses in aquaculture and damage to aquatic ecosystems. We have sequenced the 63 Mb genome of the fresh water fish pathogen, Saprolegnia parasitica. Approximately 1/3 of the assembled genome exhibits loss of heterozygosity, indicating an efficient mechanism for revealing new variation. Comparison of S. parasitica with plant pathogenic oomycetes suggests that during evolution the host cellular environment has driven distinct patterns of gene expansion and loss in the genomes of plant and animal pathogens. S. parasitica possesses one of the largest repertoires of proteases (270) among eukaryotes that are deployed in waves at different points during infection as determined from RNA-Seq data. In contrast, despite being capable of living saprotrophically, parasitism has led to loss of inorganic nitrogen and sulfur assimilation pathways, strikingly similar to losses in obligate plant pathogenic oomycetes and fungi. The large gene families that are hallmarks of plant pathogenic oomycetes such as Phytophthora appear to be lacking in S. parasitica, including those encoding RXLR effectors, Crinkler's, and Necrosis Inducing-Like Proteins (NLP). S. parasitica also has a very large kinome of 543 kinases, 10% of which is induced upon infection. Moreover, S. parasitica encodes several genes typical of animals or animal-pathogens and lacking from other oomycetes, including disintegrins and galactose-binding lectins, whose expression and evolutionary origins implicate horizontal gene transfer in the evolution of animal pathogenesis in S. parasitica.
Distinctive Nuclear Localization Signals in the Oomycete Phytophthora sojae
Fang, Yufeng; Jang, Hyo Sang; Watson, Gregory W.; Wellappili, Dulani P.; Tyler, Brett M. (Frontiers, 2017-02-02)
To date, nuclear localization signals (NLSs) that target proteins to nuclei in oomycetes have not been defined, but have been assumed to be the same as in higher eukaryotes. Here, we use the soybean pathogen Phytophthora sojae as a model to investigate these sequences in oomycetes. By establishing a reliable in vivo NLS assay based on confocal microscopy, we found that many canonical monopartite and bipartite classical NLSs (cNLSs) mediated nuclear import poorly in P. sojae. We found that efficient localization of P. sojae nuclear proteins by cNLSs requires additional basic amino acids at distal sites or collaboration with other NLSs. We found that several representatives of another well-characterized NLS, proline-tyrosine NLS (PY-NLS) also functioned poorly in P. sojae. To characterize PY-NLSs in P. sojae, we experimentally defined the residues required by functional PY-NLSs in three P. sojae nuclear-localized proteins. These results showed that functional P. sojae PY-NLSs include an additional cluster of basic residues for efficient nuclear import. Finally, analysis of several highly conserved P. sojae nuclear proteins including ribosomal proteins and core histones revealed that these proteins exhibit a similar but stronger set of sequence requirements for nuclear targeting compared with their orthologs in mammals or yeast.
Diverse Evolutionary Trajectories for Small RNA Biogenesis Genes in the Oomycete Genus Phytophthora
Bollmann, Stephanie R.; Fang, Yufeng; Press, Caroline M.; Tyler, Brett M.; Gruenwald, Niklaus J. (Frontiers, 2016-03-15)
Gene regulation by small RNA pathways is ubiquitous among eukaryotes, but little is known about small RNA pathways in the Stramenopile kingdom. Phytophthora a genus of filamentous oomycetes, contains many devastating plant pathogens, causing multibillion-dollar damage to crops, ornamental plants, and natural environments. The genomes of several oomycetes including Phytophthora species such as the soybean pathogen P. sojae, have been sequenced, allowing evolutionary analysis of small RNA-processing enzymes. This study examined the evolutionary origins of the oomycete small RNA-related genes Dicer-like (DCL), and RNA-dependent RNA polymerase (RDR) through broad phylogenetic analyses of the key domains. Two Dicer gene homologs, DCL1 and DCL2, and one RDR homolog were cloned and analyzed from P sojae. Gene expression analysis revealed only minor changes in transcript levels among different life stages. Oomycete DCL1 homologs clustered with animal and plant Dicer homologs in evolutionary trees, whereas oomycete DCL2 homologs clustered basally to the tree along with Drosha homologs. Phylogenetic analysis of the RDR homologs confirmed a previous study that suggested the last common eukaryote ancestor possessed three RDR homologs, which were selectively retained or lost in later lineages. Our analysis clarifies the position of some Unikont and Chromalveolate RDR lineages within the tree, including oomycete homologs. Finally, we analyzed alterations in the domain structure of oomycete Dicer and RDR homologs, specifically focusing on the proposed domain transfer of the DEAD-box helicase domain from Dicer to RDR. Implications of the oomycete domain structure are discussed, and possible roles of the two oomycete Dicer homologs are proposed.
Effector diversification within compartments of the Leptosphaeria maculans genome affected by Repeat-Induced Point mutations
Rouxel, Thierry; Grandaubert, Jonathan; Hane, James K.; Hoede, Claire; van de Wouw, Angela P.; Couloux, Arnaud; Dominguez, Victoria; Anthouard, Veronique; Bally, Pascal; Bourras, Salim; Cozijnsen, Anton J.; Ciuffetti, Lynda M.; Degrave, Alexandre; Dilmaghani, Azita; Duret, Laurent; Fudal, Isabelle; Goodwin, Stephen B.; Gout, Lilian; Glaser, Nicolas; Linglin, Juliette; Kema, Gert H. J.; Lapalu, Nicolas; Lawrence, Christopher B.; May, Kim; Meyer, Michel; Ollivier, Benedicte; Poulain, Julie; Schoch, Conrad L.; Simon, Adeline; Spatafora, Joseph W.; Stachowiak, Anna; Turgeon, B. Gillian; Tyler, Brett M.; Vincent, Delphine; Weissenbach, Jean; Amselem, Joelle; Quesneville, Hadi; Oliver, Richard P.; Wincker, Patrick; Balesdent, Marie-Helene; Howlett, Barbara J. (Springer Nature, 2011-02)
Fungi are of primary ecological, biotechnological and economic importance. Many fundamental biological processes that are shared by animals and fungi are studied in fungi due to their experimental tractability. Many fungi are pathogens or mutualists and are model systems to analyse effector genes and their mechanisms of diversification. In this study, we report the genome sequence of the phytopathogenic ascomycete Leptosphaeria maculans and characterize its repertoire of protein effectors. The L. maculans genome has an unusual bipartite structure with alternating distinct guanine and cytosine-equilibrated and adenine and thymine (AT)-rich blocks of homogenous nucleotide composition. The AT-rich blocks comprise one-third of the genome and contain effector genes and families of transposable elements, both of which are affected by repeat-induced point mutation, a fungal-specific genome defence mechanism. This genomic environment for effectors promotes rapid sequence diversification and underpins the evolutionary potential of the fungus to adapt rapidly to novel host-derived constraints.
Enhanced resistance in Theobroma cacao against oomycete and fungal pathogens by secretion of phosphatidylinositol-3-phosphate-binding proteins
Helliwell, Emily E.; Vega-Arreguin, Julio; Shi, Zi; Bailey, Bryan; Xiao, Shunyuan; Maximova, Siela N.; Tyler, Brett M.; Guiltinan, Mark J. (2016-03)
The internalization of some oomycete and fungal pathogen effectors into host plant cells has been reported to be blocked by proteins that bind to the effectors' cell entry receptor, phosphatidylinositol-3-phosphate (PI3P). This finding suggested a novel strategy for disease control by engineering plants to secrete PI3P-binding proteins. In this study, we tested this strategy using the chocolate tree Theobroma cacao. Transient expression and secretion of four different PI3P-binding proteins in detached leaves of T.cacao greatly reduced infection by two oomycete pathogens, Phytophthora tropicalis and Phytophthora palmivora, which cause black pod disease. Lesion size and pathogen growth were reduced by up to 85%. Resistance was not conferred by proteins lacking a secretory leader, by proteins with mutations in their PI3P-binding site, or by a secreted PI4P-binding protein. Stably transformed, transgenic T.cacao plants expressing two different PI3P-binding proteins showed substantially enhanced resistance to both P.tropicalis and P.palmivora, as well as to the fungal pathogen Colletotrichum theobromicola. These results demonstrate that secretion of PI3P-binding proteins is an effective way to increase disease resistance in T.cacao, and potentially in other plants, against a broad spectrum of pathogens.
Estimation of gene network parameters from imaging cytometry data
Lux, Matthew W. (Virginia Tech, 2013-05-23)
Synthetic biology endeavors to forward engineer genetic circuits with novel function. A major inspiration for the field has been the enormous success in the engineering of digital electronic circuits over the past half century. This dissertation approaches synthetic biology from the perspective of the engineering design cycle, a concept ubiquitous across many engineering disciplines. First, an analysis of the state of the engineering design cycle in synthetic biology is presented, pointing out the most limiting challenges currently facing the field. Second, a principle commonly used in electronics to weigh the tradeoffs between hardware and software implementations of a function, called co-design, is applied to synthetic biology. Designs to implement a specific logical function in three distinct domains are proposed and their pros and cons weighed. Third, automatic transitioning between an abstract design, its physical implementation, and accurate models of the corresponding system are critical for success in synthetic biology. We present a framework for accomplishing this task and demonstrate how it can be used to explore a design space. A major limitation of the aforementioned approach is that adequate parameter values for the performance of genetic components do not yet exist. Thus far, it has not been possible to uniquely attribute the function of a device to the function of the individual components in a way that enables accurate prediction of the function of new devices assembled from the same components. This lack presents a major challenge to rapid progression through the design cycle. We address this challenge by first collecting high time-resolution fluorescence trajectories of individual cells expressing a fluorescent protein, as well as snapshots of the number of corresponding mRNA molecules per cell. We then leverage the information embedded in the cell-cell variability of the population to extract parameter values for a stochastic model of gene expression more complex than typically used. Such analysis opens the door for models of genetic components that can more reliably predict the function of new combinations of these basic components.
An expanded phylogeny for the genus Phytophthora.
Yang, Xiao; Tyler, Brett M.; Hong, Chuanxue (2017-11-21)
A comprehensive phylogeny representing 142 described and 43 provisionally named Phytophthora species is reported here for this rapidly expanding genus. This phylogeny features signature sequences of 114 ex-types and numerous authentic isolates that were designated as representative isolates by the originators of the respective species. Multiple new subclades were assigned in clades 2, 6, 7, and 9. A single species P. lilii was placed basal to clades 1 to 5, and 7. Phytophthora stricta was placed basal to other clade 8 species, P. asparagi to clade 6 and P. intercalaris to clade 10. On the basis of this phylogeny and ancestral state reconstructions, new hypotheses were proposed for the evolutionary history of sporangial papillation of Phytophthora species. Non-papillate ancestral Phytophthora species were inferred to evolve through separate evolutionary paths to either papillate or semi-papillate species.
Fine Mapping and Candidate Gene Discovery at the Rsv3 Locus
Bowman, Brian Carter (Virginia Tech, 2011-04-28)
Soybean mosaic virus (SMV) is the most common member of the viral genus Potyvirus to infect soybeans (Glycine max [L.] Merr.) worldwide. SMV has been traditionally controlled by the deployment of single dominant, strain specific resistance genes, referred to as Rsv genes. Rsv1 is the most widely used form of SMV resistance with nine different alleles conferring resistance only to the lower numbered less virulent strains, G1 to G3. Rsv3 gives resistance to higher numbered more virulent strains G5 to G7. Soybean lines containing Rsv4, are resistant to all seven currently recognized North American SMV strains. In this study, the recently released soybean whole genome sequence was used to design molecular markers for fine mapping Rsv3 to a ~150 kb genomic region containing four coiled-coil nucleotide-binding leucine-rich repeat proteins. In a related study a large population segregating at the Rsv3 locus was screened for resistance to facilitate future characterization of this region. The markers identified in this study will allow for more accurate marker-assisted selection of Rsv3.
Genetic resources for advanced biofuel production described with the Gene Ontology
Torto-Alalibo, Trudy; Purwantini, Endang; Lomax, Jane; Setubal, João C.; Mukhopadhyay, Biswarup; Tyler, Brett M. (Frontiers, 2014-10-10)
Dramatic increases in research in the area of microbial biofuel production coupled with high-throughput data generation on bioenergy-related microbes has led to a deluge of information in the scientific literature and in databases. Consolidating this information and making it easily accessible requires a unified vocabulary. The Gene Ontology (GO) fulfills that requirement, as it is a well-developed structured vocabulary that describes the activities and locations of gene products in a consistent manner across all kingdoms of life. The Microbial ENergy processes Gene Ontology (http://www.mengo.biochem.vt.edu) project is extending the GO to include new terms to describe microbial processes of interest to bioenergy production. Our effort has added over 600 bioenergy related terms to the Gene Ontology. These terms will aid in the comprehensive annotation of gene products from diverse energy-related microbial genomes. An area of microbial energy research that has received a lot of attention is microbial production of advanced biofuels. These include alcohols such as butanol, isopropanol, isobutanol, and fuels derived from fatty acids, isoprenoids, and polyhydroxyalkanoates. These fuels are superior to first generation biofuels (ethanol and biodiesel esterified from vegetable oil or animal fat), can be generated from non-food feedstock sources, can be used as supplements or substitutes for gasoline, diesel and jet fuels, and can be stored and distributed using existing infrastructure. Here we review the roles of genes associated with synthesis of advanced biofuels, and at the same time introduce the use of the GO to describe the functions of these genes in a standardized way.

Browsing by Author "Tyler, Brett M."

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