Relevant bibliographies by topics / Structural Bioinformatic

Academic literature on the topic 'Structural Bioinformatic'

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Published: 9 March 2023

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Journal articles on the topic "Structural Bioinformatic"

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Zok, Tomasz. "BioCommons: a robust java library for RNA structural bioinformatics." Bioinformatics 37, no. 17 (February 3, 2021): 2766–67. http://dx.doi.org/10.1093/bioinformatics/btab069.

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Abstract Motivation Biomolecular structures come in multiple representations and diverse data formats. Their incompatibility with the requirements of data analysis programs significantly hinders the analytics and the creation of new structure-oriented bioinformatic tools. Therefore, the need for robust libraries of data processing functions is still growing. Results BioCommons is an open-source, Java library for structural bioinformatics. It contains many functions working with the 2D and 3D structures of biomolecules, with a particular emphasis on RNA. Availability and implementation The library is available in Maven Central Repository and its source code is hosted on GitHub: https://github.com/tzok/BioCommons Supplementary information Supplementary data are available at Bioinformatics online.
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Breiteneder, Heimo, and Clare Mills. "Structural bioinformatic approaches to understand cross-reactivity." Molecular Nutrition & Food Research 50, no. 7 (July 2006): 628–32. http://dx.doi.org/10.1002/mnfr.200500274.

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Stan, George, D. Thirumalai, George H. Lorimer, and Bernard R. Brooks. "Annealing function of GroEL: structural and bioinformatic analysis." Biophysical Chemistry 100, no. 1-3 (December 2002): 453–67. http://dx.doi.org/10.1016/s0301-4622(02)00298-3.

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Burnim, Audrey, Matthew Spence, Darren Xu, Colin Jackson, and Nozomi Ando. "Structural and bioinformatic analysis of an ancient enzyme family." Acta Crystallographica Section A Foundations and Advances 78, a1 (July 29, 2022): a26. http://dx.doi.org/10.1107/s2053273322099739.

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Grahame, Douglas S. A., John H. Dupuis, Brian C. Bryksa, Takuji Tanaka, and Rickey Y. Yada. "Comparative bioinformatic and structural analyses of pepsin and renin." Enzyme and Microbial Technology 141 (November 2020): 109632. http://dx.doi.org/10.1016/j.enzmictec.2020.109632.

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Shi, Li-ying, Mei Li, Xiao-mian Li, Li-jun Yuan, and Qing Wang. "Bioinformatic analysis of structural proteins of paramyxovirus Tianjin strain." Virologica Sinica 23, no. 4 (August 2008): 279–86. http://dx.doi.org/10.1007/s12250-008-2947-6.

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Kantardjieff, Katherine, and Bernhard Rupp. "Structural Bioinformatic Approaches to the Discovery of New Antimycobacterial Drugs." Current Pharmaceutical Design 10, no. 26 (October 1, 2004): 3195–211. http://dx.doi.org/10.2174/1381612043383205.

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Alsop, E., M. Silver, and D. R. Livesay. "Optimized electrostatic surfaces parallel increased thermostability: a structural bioinformatic analysis." Protein Engineering Design and Selection 16, no. 12 (December 1, 2003): 871–74. http://dx.doi.org/10.1093/protein/gzg131.

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Allen, C. Leigh, and Andrew M. Gulick. "Structural and bioinformatic characterization of anAcinetobacter baumanniitype II carrier protein." Acta Crystallographica Section D Biological Crystallography 70, no. 6 (May 30, 2014): 1718–25. http://dx.doi.org/10.1107/s1399004714008311.

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Microorganisms produce a variety of natural productsviasecondary metabolic biosynthetic pathways. Two of these types of synthetic systems, the nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs), use large modular enzymes containing multiple catalytic domains in a single protein. These multidomain enzymes use an integrated carrier protein domain to transport the growing, covalently bound natural product to the neighboring catalytic domains for each step in the synthesis. Interestingly, some PKS and NRPS clusters contain free-standing domains that interact intermolecularly with other proteins. Being expressed outside the architecture of a multi-domain protein, these so-called type II proteins present challenges to understand the precise role they play. Additional structures of individual and multi-domain components of the NRPS enzymes will therefore provide a better understanding of the features that govern the domain interactions in these interesting enzyme systems. The high-resolution crystal structure of a free-standing carrier protein fromAcinetobacter baumanniithat belongs to a larger NRPS-containing operon, encoded by the ABBFA_003406–ABBFA_003399 genes ofA. baumanniistrain AB307-0294, that has been implicated inA. baumanniimotility, quorum sensing and biofilm formation, is presented here. Comparison with the closest structural homologs of other carrier proteins identifies the requirements for a conserved glycine residue and additional important sequence and structural requirements within the regions that interact with partner proteins.
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Bae, E., R. M. Bannen, and G. N. Phillips. "Bioinformatic method for protein thermal stabilization by structural entropy optimization." Proceedings of the National Academy of Sciences 105, no. 28 (July 8, 2008): 9594–97. http://dx.doi.org/10.1073/pnas.0800938105.

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Dissertations / Theses on the topic "Structural Bioinformatic"

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Roberts, Rick Lee. "Structural and bioinformatic analysis of ethylmalonyl-CoA decarboxylase." Thesis, State University of New York at Buffalo, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1600817.

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Many enzymes of the major metabolic pathways are categorized into superfamilies which share common folds. Current models postulate these superfamilies are the result of gene duplications coupled with mutations that result in the acquisition of new functions. Some of these new functions are considered advantageous and selected for, while others may simply be tolerated. The latter can result in metabolites being produced at low rates that are of no known use by the cell, and can become toxic when accumulated. Concurrent with the evolution of this tolerable or potentially detrimental metabolism, organisms are selected to evolve a means of correcting or “proofreading” these non-canonical metabolites to counterbalance their detrimental effects. Metabolite proofreading is a process of intermediary metabolism analogous to DNA proof reading that acts on these abnormal metabolites to prevent their accumulation and toxic effects.

Here we structurally characterize ethylmalonyl-CoA decarboxylase (EMCD), a member of the family of enoyl-CoA hydratases within the crotonase superfamily of proteins, which is coded by the ECHDC1 (enoyl-CoA hydratase domain containing 1) gene. EMCD has been shown to have a metabolic proofreading property, acting on the metabolic byproduct ethylmalonyl-CoA to prevent its accumulation which could result in oxidative damage. We use the complimentary methods of in situ crystallography, small angle X-ray scattering, and single crystal X-ray crystallography to structurally characterize EMCD, followed by homology analysis in order to propose a mechanism of action. This represents the first structure of a crotonase superfamily member thought to function as a metabolite proof reading enzyme.

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Stahl, Morgan A. "The Perilipin Family of Proteins: Structural and Bioinformatic Analysis." Otterbein University Honors Theses / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=otbnhonors1620460421392971.

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Chiara, M. "BIOINFORMATIC TOOLS FOR NEXT GENERATION GENOMICS." Doctoral thesis, Università degli Studi di Milano, 2012. http://hdl.handle.net/2434/173424.

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New sequencing strategies have redefined the concept of “high-throughput sequencing” and many companies, researchers, and recent reviews use the term “Next-Generation Sequencing” (NGS) instead of high-throughput sequencing. These advances have introduced a new era in genomics and bioinformatics⁠⁠. During my years as PhD student I have developed various software, algorithms and procedures for the analysis of Nest Generation sequencing data required for distinct biological research projects and collaborations in which our research group was involved. The tools and algorithms are thus presented in their appropriate biological contexts. Initially I dedicated myself to the development of scripts and pipelines which were used to assemble and annotate the mitochondrial genome of the model plant Vitis vinifera. The sequence was subsequently used as a reference to study the RNA editing of mitochondrial transcripts, using data produced by the Illumina and SOLiD platforms. I subsequently developed a new approach and a new software package for the detection of of relatively small indels between a donor and a reference genome, using NGS paired-end (PE) data and machine learning algorithms. I was able to show that, suitable Paired End data, contrary to previous assertions, can be used to detect, with high confidence, very small indels in low complexity genomic contexts. Finally I participated in a project aimed at the reconstruction of the genomic sequences of 2 distinct strains of the biotechnologically relevant fungus Fusarium. In this context I performed the sequence assembly to obtain the initial contigs and devised and implemented a new scaffolding algorithm which has proved to be particularly efficient.
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Gendoo, Deena. "Bioinformatic sequence and structural analysis for Amyloidogenicity in Prions and other proteins." Thesis, McGill University, 2012. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=110518.

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Detection of amyloidogenic peptides or domains in proteins is of paramount importance towards understanding their role in amyloidosis in conformational diseases. This thesis explores different methods towards detection and prediction of amyloidogenic peptides using a variety of bioinformatic analytical methods. Bioinformatic analysis of secondary structural changes is employed to determine whether classes of structurally ambivalent peptides, mainly discordant and chameleon sequences, are efficient predictors of amyloidogenic segments. This analysis elucidates statistical relationships between discordance, chameleonism, and amyloidogenicity across a database of protein domains (SCOP), a subset of amyloid-forming proteins, and the prion family. The presented results stress upon the limitations of these peptides as predictors of amyloidogenicity, and raise issues on the predictive power that can be reaped from secondary structure prediction methods. In another bioinformatic approach, detection of conformationally variable segments in tertiary structures of PrP globular domains has been performed using Principal Component Analysis. This technique succeeded in identifying five conformationally variable domains within PrP, and ranking these subdomains by their ability to differentiate PrPs based on non-local structural response to pathogenic mutation and prion disease susceptibility. The presented results are corroborated by previous observations from experimental methods and molecular dynamic simulations, suggesting that this approach serves as a fast and reliable method for detection of potential amyloidogenic segments in amyloid-forming proteins. Finally, a structural, functional, and evolutionary bioinformatic analysis is conducted to assess the prevalence of the first experimentally verified amyloid fibril fold in nature, and whether this fold can serve as a prototype for other amyloid-forming proteins. The results indicate a limited scope of this fold in amyloid-forming proteins and across the protein universe, and have implications on future identification of amyloid-forming proteins that share this fold. Collectively, the presented thesis compares these different methods and discusses their efficacy in detection of amyloidogenic segments.
La détection de peptides ou de domaines amyloïdogéniques dans les protéines est d'une importance primordiale dans la compréhension de leur rôle dans l'amylose dans les maladies conformationnelles. Cette thèse explore différentes méthodes en vue de la détection et la prédiction des peptides amyloïdogéniques utilisant une variété de méthodes d'analyse bio-informatique. L'analyse bio-informatique des changements structurels secondaires est employé afin de déterminer si les classes des peptides structurellement ambivalentes, principalement des séquences discordantes et caméléons, sont des prédicteurs efficaces de segments amyloïdogéniques. Cette analyse élucide des relations statistiques entre la discordance, la chameleonism et l'amyloïdogénicité à travers une base de données de domaines protéiques (SCOP), un sous-ensemble de protéines formées d'amyloïdes, et de la famille prion. Les résultats présentés soulignent les limites de ces peptides en tant que prédicteurs d'amyloïdogénicité, et soulèvent des questions sur le pouvoir prédictif qui peut être récolté de méthodes de prédiction de structure secondaire. Dans une autre approche bio-informatique, la détection de segments de conformation variables dans les structures tertiaires de domaines globulaires PrP a été effectuée utilisant « Principal Component Analysis ». Cette technique a réussi à identifier cinq domaines de conformation variables au sein de la protéine PrP, et à classer ces sous-domaines par leur capacité à différencier les PrP fondés sur des réponses structurelles non-locales à la mutation pathogène et la susceptibilité aux maladies prion. Les résultats présentés sont corroborés par des observations antérieures à partir de méthodes expérimentales et de simulations de dynamique moléculaire, ce qui suggère que cette approche sert comme une méthode rapide et fiable pour la détection de segments amyloïdogéniques potentiels dans les protéines formées d'amyloïdes. Finalement, une analyse structurelle, fonctionnelle et évolutive bio-informatique est menée afin d'évaluer la prévalence du premier pli de fibrille amyloïde dans la nature vérifié expérimentalement, et si ce pli peut servir de prototype pour d'autres protéines formées d'amyloïdes. Les résultats indiquent une portée limitée de ce pli dans les protéines formées d'amyloïdes et à travers l'univers des protéines, et ont des répercussions sur l'identification future de protéines formées d'amyloïdes qui partagent ce pli. Collectivement, la thèse présentée compare ces différentes méthodes et discute leur efficacité dans la détection de segments amyloïdogéniques.
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MOZZICAFREDDO, MATTEO. "Structural bioinformatic analyses of (macro)molecular interactions of biomedical relevance: an experimental validation." Doctoral thesis, Università degli Studi di Camerino, 2014. http://hdl.handle.net/11581/401775.

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Structural bioinformatics, like many other subdisciplines within bioinformatics, is characterized by the establishment of general purpose methods for manipulating information about biological macromolecules, and the application of these methods to solving problems in biology and creating new knowledge. Among its capabilities, structural bioinformatics can analyse the feasible (macro)molecular interactions and assists, or sometimes anticipates, the experimental approaches in biological research, even starting from a prediction analysis of the three-dimensional structures of the partners. This thesis reports on the in silico and in vitro characterization of a selection on physiologically relevant processes involving binding between proteins and endogenous and exogenous ligands, with results confirming the well-founded capability of the bioinformatic methods to clarify these issues. The general approach consisted in: (i) the in silico derivation of the predictive structural and equilibrium parameters for the ligand-receptor complexes starting from either deposited crystallographic (where available) or homology modeled structures; (ii) the experimental validation of the computational data according to both "in solution" and "on surface" in vitro studies; (iii) the final evaluation of the effects of the interactions on cell based models. Specifically, during the PhD period my interest was mainly focused on the characterization of the molecular basis of the systemic sclerosis (SSc), a rare human auto-immune disease, with particular emphasis on the interaction between platelet-derived growth factor receptor and a selection of human autoantibodies expressed in SSc patients (the revised version of this manuscript is currently under evaluation in Nature Communications). This project was paralleled by several other studies, among which the modulation by natural polyphenols of two human enzymes, HMG-CoA reductase and plasmin, involved in cholesterol biosynthetic pathway and in cellular adhesion and mobility, respectively. The results of these studies were published in impacted scientific journals.
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Martínez, Fundichely Alexander 1978. "Bioinformatic characterization and analysis of polymorphic inversions in the human genome." Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/384837.

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Within the great interest in the characterization of genomic structural variants (SVs) in the human genome, inversions present unique challenges and have been little studied. This thesis has developed "GRIAL", a new algorithm focused specifically in detect and map accurately inversions from paired-end mapping (PEM) data, which is the most widely used method to detect SVs. GRIAL is based on geometrical rules to cluster, merge and refine both breakpoints of putative inversions. That way, we have been able to predict hundreds of inversions in the human genome. In addition, thanks to the different GRIAL quality scores, we have been able to identify spurious PEM-patterns and their causes, and discard a big fraction of the predicted inversions as false positives. Furthermore, we have created â ˘ AIJInvFESTâ˘A˙I, the first database of human polymorphic inversions, which represents the most reliable catalogue of inversions and integrates all the associated information from multiple sources. Currently, InvFEST combines information from 30 different studies and contains 1092 candidate inversions, which are categorized based on internal scores and manual curation. Finally, the analysis of all the data generated has provided information on the genomic patterns of inversions, contributing decisively to the understanding of the map of human polymorphic inversions.
Dentro del estudio de las variantes estructurales en el genoma humano, las inversiones han sido las menos han consolidado sus resultados y constituye uno de los principales retos en la actualidad. Esta tesis aborda el tema a través de la implementación de "GRIAL" un nuevo algoritmo específicamente diseñado para la detección más precisa posible de las inversiones usando el mapeo de secuencias apareadas (del inglés PEM) que es el método más utilizado para estudiar la variación estructural. GRIAL se basa en reglas geométricas para agrupar los patrones de PEM que señalan un posible punto de rotura (del inglés breakpoint) de inversión, además une cada breakpoint correspondientes a inversiones independientes y refina lo más exacto posible su localización. Su uso nos permitió predecir cientos de inversiones. Un gran aporte de nuestro método es la creación de índices (del inglés score) de fiabilidad para las predicciones mediante los cuales identificamos patrones de inversión incorrectos y sus causas. Esto nos permitió filtrar nuestro resultado eliminando un gran número de predicciones posiblemente falsas. Además se creó "InvFEST", la primera base de datos especialmente dedicada a inversiones polimórficas en el genoma humano la cual representa el catálogo más fiable de inversiones, integrando además a cada inversión conocida la información asociada disponible. Actualmente InvFEST contiene (y mantiene la clasificación según el nivel de certeza) un catálogo de 1092 inversiones clasificadas, a partir de datos de 30 estudios diferentes. Finalmente el análisis de toda la información generada nos permitió describir algunos patrones de las inversiones polimórficas en el genoma humano contribuyendo de este modo a la comprensión de esta variante estructural y el estado de su información en los estudios del genoma humano.
Inversió genòmica
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Moss, Tiffanie. "CHARACTERIZATION OF STRUCTURAL VARIANTS AND ASSOCIATED MICRORNAS IN FLAX FIBER AND LINSEED GENOTYPES BY BIOINFORMATIC ANALYSIS AND HIGH-THROUGHPUT SEQUENCING." Case Western Reserve University School of Graduate Studies / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=case1333648149.

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RIZZA, FABIO. "Structural modelling of biological macromolecules: the cases of neurofibromin, bifurcating Electron Transferring Flavoprotein and Amyloid-β (1-16) peptide." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2021. http://hdl.handle.net/10281/310480.

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In questa tesi sono stati affrontati tre progetti indipendenti, accomunati dall’uso della modellistica molecolare e in particolare della dinamica molecolare. Nel primo progetto è stato studiato il dominio Sec14-PH della neurofibromina (NF1). I domini sec14 sono stati scoperti in numerose proteine dai procarioti all’uomo come scambiatori di lipidi tra membrane, per mezzo di una tasca la cui apertura è legata al movimento di una specifica alpha-elica (elica lid). La struttura cristallina del dominio Sec14 di NF1 (sia del wild type sia di mutanti associati all’insorgenza della patologia neurofibromatosi) ha rivelato la sua particolarità di essere strutturalmente accoppiato ad un dominio PH che interagisce fortemente con l’elica lid tramite un suo loop (detto lid-lock loop). Su questa base è stato formulato un meccanismo di apertura della tasca del Sec14 che coinvolgerebbe un movimento concertato del lid-lock loop, ma questo movimento non è mai stato osservato o dimostrato. Guidati da dati sperimentali sulla denaturazione termica del Sec14-PH di NF1, sia del wild type sia di alcuni mutanti, diverse simulazioni ad alta temperatura sono state effettuare per comparare la dinamica del dominio wild type con un mutante patologico associato all’insorgenza della patologia neurofibromatosi. Con le nostre simulazioni è stato possibile proporre un meccanismo di funzionamento dell’apertura dell’elica lid e fornire delle basi strutturali e dinamiche dell’insorgenza della patologia nel caso del mutante specifico studiato. Nel secondo progetto è stato affrontato lo studio di una proteina chiamata EtfAB che catalizza un processo recentemente scoperto noto come biforcazione elettronica basata sulle flavine. Questo meccanismo è sfruttato solo da alcuni microrganismi anerobici come terza via di accoppiamento energetico e finora si conoscono quattro famiglie di proteine, evolutivamente non correlate, in grado di catalizzarlo. Una di queste è EtfAB, della quale non è chiaro come possa avvenire il trasferimento elettronico tra le due molecole di FAD ad essa legate. Infatti, la distanza tra questi due FAD osservata nella struttura cristalline di EtfAB è di 18 Å, mentre si ritiene più plausibile che i trasferimenti elettronici in biologia non avvengano a distanze maggiori di 14 Å. Per questo è stato suggerito un possibile meccanismo che potrebbe avvicinare le due molecole di FAD. Usando la dinamica molecolare è stato possibile testare, e smentire, il meccanismo proposto. Inoltre, con il Density Functional Theory (DFT), è stato possibile fornire un’interpretazione ad alcuni dati spettroscopici riguardo il possibile trasferimento elettronico tra le due molecole di FAD. Nel terzo progetto, ho collaborato con il Prof. Luca Bertini ad un progetto sulla produzione e propagazione di alcune specie reattive dell’ossigeno (ROS) nel contesto del peptide amiloide beta coinvolto nella patogenesi dell’Alzheimer. Nell’ambito dell’ipotesi amiloide sull’insorgenza della patologia di Alzheimer, un ruolo importante è stato attribuito ai danni causati dai ROS, prodotti da un complesso metallico all’interno del peptide amiloide stesso, in particolare dal radicale ossidrilico (OH.-). Tuttavia, i dettagli su come questi radicali propaghino e reagiscano non sono ancora stati chiariti. Mentre i calcoli DFT del Prof. Bertini affrontavano le capacità ossidative del radicale ossidrilico e i possibili prodotti di reazione nel contesto del peptide amiloide beta, con i miei calcoli di dinamica molecolari è stata fornita una panoramica su quali possibili bersagli del radicale ossidrilico, coordinato allo ione Cu del complesso, possano effettivamente reagire entrando in contatto con il radicale ossidrilico a causa dei moti dinamici del peptide.
In this thesis, three independent projects were addressed, sharing the computational approach based on molecular modeling and in particular molecular dynamics. In the first project, the Sec14-PH domain of neurofibromin (NF1) was investigated. The Sec14 domains have been identified in many different proteins, from prokaryotes to humans, serving as exchangers of lipid molecules between membranes, by means of a pocket whose opening is allowed by the motion of a specific alpha-helix (called lid helix). The crystal structure of the NF1-Sec14 domain (of both the wild type and some mutants associated with the onset of neurofibromatosis pathology) has revealed its peculiarity of being structurally coupled to a PH domain that strongly interacts with the lid helix through a long loop (called lid-lock loop). On this basis, a mechanism for the opening of the Sec14 lipid pocket was formulated which would involve a concerted movement of the lid-lock loop, but this movement has actually never been shown. Guided by available experimental data on the thermal denaturation of Sec14-PH domain of NF1, both on the wild type and some neurofibromin-related mutants, several simulations at high temperature were carried out to compare the dynamics of the wild type domain with a pathological mutant associated with the onset of neurofibromatosis. Our simulations lead us to suggest an opening mechanism for the lid helix and provide a hypothesis for the structural and dynamic basis of the onset of the disease in the case of the specific mutant. The second project addressed the study of a protein called EtfAB which catalyzes a recently discovered process known as Flavin-Based Electron Bifurcation (FBEB). This mechanism is only exploited by some anaerobic microorganisms as a third way of energy coupling. So far, four unrelated protein families are known that are able to catalyze FBEB. Among these, EtfAB, catalyzes the electron transfer between the two FAD molecules bound to it. Surprisingly, the distance between these two FADs, as observed in the crystal structure of EtfAB, is 18 Å, whereas biological electron transfer is considered more likely to occur at a maximal distance of 14 Å. To explain this, a possible mechanism has been suggested that could bring the two FAD molecules closer together. Using molecular dynamics, it was possible to test, and discard, the proposed mechanism. Furthermore, with the Density Functional Theory (DFT), it was possible to provide an interpretation to some spectroscopic data regarding the possible electron transfer between the two FAD molecules. In the third project, I collaborated with Prof. Luca Bertini on a project on the production and propagation of some reactive oxygen species (ROS) in the context of the amyloid-beta peptide involved in the pathogenesis of Alzheimer's. In the amyloid hypothesis on the onset of Alzheimer's disease, an important role has been attributed to the damage caused by ROS, produced by a metal ion coordinated to the amyloid peptide itself, in particular by the hydroxyl radical (OH.-). However, the details of how these radicals propagate and react have not yet been clarified. While Prof. Bertini's DFT calculations addressed the oxidative capacities of the hydroxyl radical and the possible reaction products in the context of the amyloid-beta peptide, my molecular dynamics simulations provided an overview on which possible targets of the hydroxyl radical, coordinated to the ion Cu of the complex, could actually react with the hydroxyl radical due to the dynamic motions of the peptide.
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LAURENZI, TOMMASO. "STUDY ON THE HDL::LCAT INTERACTION AND INSIGHTS INTO LCAT PHARMACOLOGICAL MODULATION." Doctoral thesis, Università degli Studi di Milano, 2021. http://hdl.handle.net/2434/835127.

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Lecithin:cholesterol-acyl-transferase (LCAT) plays a major role in cholesterol metabolism as it is the only extracellular enzyme able to esterify cholesterol. LCAT activity is required for lipoprotein remodeling and, most specifically, for the growth and maturation of HDLs. In fact, genetic alterations affecting LCAT functionality may cause a severe reduction in plasma levels of HDL-cholesterol with important clinical consequences, for which, at present, no optimal treatment is available. Within this project, we ultimately aim at establishing landmarks for future structure-based drug-discovery of novel small-molecule activators able to rescue the defective enzyme in LCAT deficiency patients. To this end, we thoroughly studied the LCAT::HDL recognition and activation mechanism and investigated some aspects of LCAT pharmacological modulation. Although several hypotheses were formulated, the exact molecular recognition mechanism between LCAT and HDLs is still unknown. We employed a combination of structural bioinformatics procedures to deepen the insights into the HDL-LCAT interplay that promotes LCAT activation and cholesterol esterification. We have generated a data-driven model of reconstituted HDL (rHDL) and studied the dynamics of an assembled rHDL::LCAT supramolecular complex, pinpointing the conformational changes originating from the interaction between LCAT and apolipoprotein A-I (apoA-I) that are necessary for LCAT activation. Specifically, we propose a mechanism in which the anchoring of LCAT lid to apoA-I helices allows the formation of a hydrophobic hood that expands LCAT active site and shields it from the solvent, allowing the enzyme to process large hydrophobic substrates. Through the atomistic knowledge gained from our modeling work, we then studied the mechanism-of-action of some members of two known classes of small-molecule LCAT modulators and their interaction with a subset of LCAT mutants, rationalizing the bases for the future design of novel activators characterized by higher efficacy.
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Liu, Xiao. "Comprehensive bioinformatic analysis of kinesin classification and prediction of structural changes from a closed to an open conformation of the motor domain." Diss., lmu, 2009. http://nbn-resolving.de/urn:nbn:de:bvb:19-108430.

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Books on the topic "Structural Bioinformatic"

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Gáspári, Zoltán, ed. Structural Bioinformatics. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0270-6.

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Bourne, Philip E., and Helge Weissig, eds. Structural Bioinformatics. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2003. http://dx.doi.org/10.1002/0471721204.

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Structural bioinformatics. 2nd ed. Hoboken, N.J: Wiley-Blackwell, 2009.

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Wei, Dongqing, Qin Xu, Tangzhen Zhao, and Hao Dai, eds. Advance in Structural Bioinformatics. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9245-5.

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Hamelryck, Thomas, Kanti Mardia, and Jesper Ferkinghoff-Borg, eds. Bayesian Methods in Structural Bioinformatics. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27225-7.

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Frishman, Dmitrij. Structural Bioinformatics of Membrane Proteins. Vienna: Springer Vienna, 2010. http://dx.doi.org/10.1007/978-3-7091-0045-5.

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Frishman, Dmitrij. Structural bioinformatics of membrane proteins. Wien: Springer, 2010.

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Bayesian methods in structural bioinformatics. Heidelberg: Springer, 2012.

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Shanker, Asheesh, ed. Bioinformatics: Sequences, Structures, Phylogeny. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1562-6.

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Haspel, Nurit, Filip Jagodzinski, and Kevin Molloy, eds. Algorithms and Methods in Structural Bioinformatics. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-05914-8.

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Book chapters on the topic "Structural Bioinformatic"

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McCaffrey, Peter. "Bioinformatic Techniques for Vaccine Development: Epitope Prediction and Structural Vaccinology." In Vaccine Design, 413–23. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1892-9_21.

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Cai, Fei, Cheryl A. Kerfeld, and Gustaf Sandh. "Bioinformatic Identification and Structural Characterization of a New Carboxysome Shell Protein." In Functional Genomics and Evolution of Photosynthetic Systems, 345–56. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1533-2_14.

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Huntley, James J. A., Soheila J. Maleki, Michael D. Gonzales, and William D. Beavis. "Bioinformatic Tools, Resources, and Strategies for Comparative Structural Studies of Food Allergens." In ACS Symposium Series, 322–56. Washington, DC: American Chemical Society, 2008. http://dx.doi.org/10.1021/bk-2008-1001.ch020.

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Altman, Russ B., and Jonathan M. Dugan. "Defining Bioinformatics and Structural Bioinformatics." In Structural Bioinformatics, 1–14. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471721204.ch1.

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Linge, Jens P., and Michael Nilges. "Structural Bioinformatics and NMR Structure Determination." In Practical Bioinformatics, 123–37. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-74268-5_6.

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Patel, Bhumi, Vijai Singh, and Dhaval Patel. "Structural Bioinformatics." In Essentials of Bioinformatics, Volume I, 169–99. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-02634-9_9.

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Tiwary, Basant K. "Structural Bioinformatics." In Bioinformatics and Computational Biology, 65–86. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4241-8_5.

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Berman, Helen M., John D. Westbrook, Zukang Feng, Lisa Iype, Bohdan Schneider, and Christine Zardecki. "The Nucleic Acid Database." In Structural Bioinformatics, 199–216. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471721204.ch10.

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Weissig, Helge, and Philip E. Bourne. "Other Structure-Based Databases." In Structural Bioinformatics, 217–36. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471721204.ch11.

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Reddy, Boojala V. B., and Philip E. Bourne. "Protein Structure Evolution and the Scop Database." In Structural Bioinformatics, 237–48. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471721204.ch12.

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Conference papers on the topic "Structural Bioinformatic"

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Gerasimova, E. O., A. V. Tretyakova, and P. A. Krylov. "Bioinformatic analysis of structural and functional properties of proteins of the surface zone and surfactant-associated proteins." In Mathematical Biology and Bioinformatics. Pushchino: IMPB RAS - Branch of KIAM RAS, 2022. http://dx.doi.org/10.17537/icmbb22.21.

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Odenkirk, Melanie, David Reif, and Erin Baker. "An online structural-based connectivity and omic phenotype evaluations (SCOPE) cheminformatics toolbox for lipidomic data visualization." In 2022 AOCS Annual Meeting & Expo. American Oil Chemists' Society (AOCS), 2022. http://dx.doi.org/10.21748/nleu8917.

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Lipidomic analyses using mass spectrometry have traditionally been complicated by an abundance of isomeric species. The recent emergence of experimental platforms allowing for isomer separation has significantly benefitted lipidomic studies by allowing further speciation and the acquisition of species-specific information. Data interpretation for this detailed information, however, still faces challenges as existing lipid pathways are often defined such that single nodes represent entire lipid classes and not individual species (e.g., pathways may indicate that phosphatidylcholines as a class are increasing). Therefore, most bioinformatic tools cannot assess comprehensively annotated lipid studies. To overcome this limitation, we developed a structural-based connectivity and omic phenotypic evaluation (SCOPE) cheminformatic data analysis toolbox to relate individual lipid species with their associated biological significance and clinical data. The caveat of this work thus far has however been its accessibility to users with limited coding experience. Thus, we have now developed an online graphical user interface (GUI) program removing all previous coding requirements called SCOPE Online. SCOPE Online offers lipidomic researchers the capability to explore trends of lipid perturbations through two steps. Initially, head group and fatty acyl composition are used to relate lipids by shared structural moieties through hierarchical clustering and parsing of groups. Once relationships between lipid structures have been established, summary statistics of fold change, p-value and other metrics can then be overlaid to probe biological trends. To facilitate user annotation, a series of customizable features including color gradient, line thickness, and figure annotations are also possible within the SCOPE Online platform. Altogether, our SCOPE Online cheminformatics toolbox allows for the visualization of structural and phenotypic effects on the biology of individual species that has been made more accessible by the development of a GUI platform for lipidomic data visualization. Example data and SCOPE Online utilities will be showcased in this presentation.
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Birriel, Pamela C., Caitlyn W. Barrett, Tanja M. Davidsen, Martin L. Ferguson, Patee Gesuwan, Nicholas B. Griner, Jaime M. Guidry Auvil, et al. "Abstract 399: NCI Office of Cancer Genomics: Supporting structural and functional genomics and development of bioinformatic approaches to advance precision oncology." In Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.am2018-399.

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An, Lingling. "Session details: Structural bioinformatics." In BCB '21: 12th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3478668.

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Mettu, Ramgopal. "Session details: Structural bioinformatics." In BCB '22: 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3552474.

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Giorgetti, Alejandro. "Structural bioinformatics: advances and applications." In FROM PHYSICS TO BIOLOGY: The Interface between Experiment and Computation - BIFI 2006 II International Congress. AIP, 2006. http://dx.doi.org/10.1063/1.2345623.

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Rokde, Chandrayani N., and Manali Kshirsagar. "Bioinformatics: Protein structure prediction." In 2013 Fourth International Conference on Computing, Communications and Networking Technologies (ICCCNT). IEEE, 2013. http://dx.doi.org/10.1109/icccnt.2013.6726753.

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Haspel, Nurit, Amarda Shehu, and Kevin Molloy. "The 2017 Computational Structural Bioinformatics Workshop." In BCB '17: 8th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3107411.3108166.

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Kazmerchuk, A. D., E. V. Snytkov, and B. A. Tonkonogov. "SOFTWARE SYSTEM PROJECT FOR PROTEINS’ INTERACTION ANALYSIS UNDER CONDITIONS OF WEAK STRUCTURAL SIMILARITY." In SAKHAROV READINGS 2022: ENVIRONMENTAL PROBLEMS OF THE XXI CENTURY. International Sakharov Environmental Institute of Belarusian State University, 2022. http://dx.doi.org/10.46646/sakh-2022-2-419-422.

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Practical purpose, functioning algorithm, architecture, technologies and means of implementation, functionality and testing of software system project for proteins’ interaction analysis under conditions of weak structural similarity, based on bioinformatics technologies, implementing computational methods and mathematical models at various computational levels and allowing making research decisions in various fields of biology and medicine are considered.
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Yu-Feng Huang, Chia-Jui Yang, Yi-Wei Yang, Chun-Chin Huang, and Chien-Kang Huang. "Protein supporting structure discovery by rigid structure identification via one-dimensional structural signature." In 2008 IEEE International Conference on Bioinformatics and Biomedcine Workshops. IEEE, 2008. http://dx.doi.org/10.1109/bibmw.2008.4686203.

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Reports on the topic "Structural Bioinformatic"

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Brueggemeier, Robert W. Drug Discovery and Structural Bioinformatics in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, December 1999. http://dx.doi.org/10.21236/ada384146.

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Wallace, Susan S. DOE EPSCoR Initiative in Structural and computational Biology/Bioinformatics. Office of Scientific and Technical Information (OSTI), February 2008. http://dx.doi.org/10.2172/924036.

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Minz, Dror, Stefan J. Green, Noa Sela, Yitzhak Hadar, Janet Jansson, and Steven Lindow. Soil and rhizosphere microbiome response to treated waste water irrigation. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598153.bard.

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Research objectives : Identify genetic potential and community structure of soil and rhizosphere microbial community structure as affected by treated wastewater (TWW) irrigation. This objective was achieved through the examination soil and rhizosphere microbial communities of plants irrigated with fresh water (FW) and TWW. Genomic DNA extracted from soil and rhizosphere samples (Minz laboratory) was processed for DNA-based shotgun metagenome sequencing (Green laboratory). High-throughput bioinformatics was performed to compare both taxonomic and functional gene (and pathway) differences between sample types (treatment and location). Identify metabolic pathways induced or repressed by TWW irrigation. To accomplish this objective, shotgun metatranscriptome (RNA-based) sequencing was performed. Expressed genes and pathways were compared to identify significantly differentially expressed features between rhizosphere communities of plants irrigated with FW and TWW. Identify microbial gene functions and pathways affected by TWW irrigation*. To accomplish this objective, we will perform a metaproteome comparison between rhizosphere communities of plants irrigated with FW and TWW and selected soil microbial activities. Integration and evaluation of microbial community function in relation to its structure and genetic potential, and to infer the in situ physiology and function of microbial communities in soil and rhizospere under FW and TWW irrigation regimes. This objective is ongoing due to the need for extensive bioinformatics analysis. As a result of the capabilities of the new PI, we have also been characterizing the transcriptome of the plant roots as affected by the TWW irrigation and comparing the function of the plants to that of the microbiome. *This original objective was not achieved in the course of this study due to technical issues, especially the need to replace the American PIs during the project. However, the fact we were able to analyze more than one plant system as a result of the abilities of the new American PI strengthened the power of the conclusions derived from studies for the 1ˢᵗ and 2ⁿᵈ objectives. Background: As the world population grows, more urban waste is discharged to the environment, and fresh water sources are being polluted. Developing and industrial countries are increasing the use of wastewater and treated wastewater (TWW) for agriculture practice, thus turning the waste product into a valuable resource. Wastewater supplies a year- round reliable source of nutrient-rich water. Despite continuing enhancements in TWW quality, TWW irrigation can still result in unexplained and undesirable effects on crops. In part, these undesirable effects may be attributed to, among other factors, to the effects of TWW on the plant microbiome. Previous studies, including our own, have presented the TWW effect on soil microbial activity and community composition. To the best of our knowledge, however, no comprehensive study yet has been conducted on the microbial population associated BARD Report - Project 4662 Page 2 of 16 BARD Report - Project 4662 Page 3 of 16 with plant roots irrigated with TWW – a critical information gap. In this work, we characterize the effect of TWW irrigation on root-associated microbial community structure and function by using the most innovative tools available in analyzing bacterial community- a combination of microbial marker gene amplicon sequencing, microbial shotunmetagenomics (DNA-based total community and gene content characterization), microbial metatranscriptomics (RNA-based total community and gene content characterization), and plant host transcriptome response. At the core of this research, a mesocosm experiment was conducted to study and characterize the effect of TWW irrigation on tomato and lettuce plants. A focus of this study was on the plant roots, their associated microbial communities, and on the functional activities of plant root-associated microbial communities. We have found that TWW irrigation changes both the soil and root microbial community composition, and that the shift in the plant root microbiome associated with different irrigation was as significant as the changes caused by the plant host or soil type. The change in microbial community structure was accompanied by changes in the microbial community-wide functional potential (i.e., gene content of the entire microbial community, as determined through shotgun metagenome sequencing). The relative abundance of many genes was significantly different in TWW irrigated root microbiome relative to FW-irrigated root microbial communities. For example, the relative abundance of genes encoding for transporters increased in TWW-irrigated roots increased relative to FW-irrigated roots. Similarly, the relative abundance of genes linked to potassium efflux, respiratory systems and nitrogen metabolism were elevated in TWW irrigated roots when compared to FW-irrigated roots. The increased relative abundance of denitrifying genes in TWW systems relative FW systems, suggests that TWW-irrigated roots are more anaerobic compare to FW irrigated root. These gene functional data are consistent with geochemical measurements made from these systems. Specifically, the TWW irrigated soils had higher pH, total organic compound (TOC), sodium, potassium and electric conductivity values in comparison to FW soils. Thus, the root microbiome genetic functional potential can be correlated with pH, TOC and EC values and these factors must take part in the shaping the root microbiome. The expressed functions, as found by the metatranscriptome analysis, revealed many genes that increase in TWW-irrigated plant root microbial population relative to those in the FW-irrigated plants. The most substantial (and significant) were sodium-proton antiporters and Na(+)-translocatingNADH-quinoneoxidoreductase (NQR). The latter protein uses the cell respiratory machinery to harness redox force and convert the energy for efflux of sodium. As the roots and their microbiomes are exposed to the same environmental conditions, it was previously hypothesized that understanding the soil and rhizospheremicrobiome response will shed light on natural processes in these niches. This study demonstrate how newly available tools can better define complex processes and their downstream consequences, such as irrigation with water from different qualities, and to identify primary cues sensed by the plant host irrigated with TWW. From an agricultural perspective, many common practices are complicated processes with many ‘moving parts’, and are hard to characterize and predict. Multiple edaphic and microbial factors are involved, and these can react to many environmental cues. These complex systems are in turn affected by plant growth and exudation, and associated features such as irrigation, fertilization and use of pesticides. However, the combination of shotgun metagenomics, microbial shotgun metatranscriptomics, plant transcriptomics, and physical measurement of soil characteristics provides a mechanism for integrating data from highly complex agricultural systems to eventually provide for plant physiological response prediction and monitoring. BARD Report
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Shpigel, Nahum Y., Ynte Schukken, and Ilan Rosenshine. Identification of genes involved in virulence of Escherichia coli mastitis by signature tagged mutagenesis. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7699853.bard.

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Mastitis, an inflammatory response of the mammary tissue to invading pathogenic bacteria, is the largest health problem in the dairy industry and is responsible for multibillion dollar economic losses. E. coli are a leading cause of acute mastitis in dairy animals worldwide and certainly in Israel and North America. The species E. coli comprises a highly heterogeneous group of pathogens, some of which are commensal residents of the gut, infecting the mammary gland after contamination of the teat skin from the environment. As compared to other gut microflora, mammary pathogenic E. coli (MPEC) may have undergone evolutionary adaptations that improve their fitness for colonization of the unique and varied environmental niches found within the mammary gland. These niches include competing microbes already present or accompanying the new colonizer, soluble and cellular antimicrobials in milk, and the innate immune response elicited by mammary cells and recruited immune cells. However, to date, no specific virulence factors have been identified in E. coli isolates associated with mastitis. The original overall research objective of this application was to develop a genome-wide, transposon-tagged mutant collection of MPEC strain P4 and to use this technology to identify E. coli genes that are specifically involved in mammary virulence and pathogenicity. In the course of the project we decided to take an alternative genome-wide approach and to use whole genomes bioinformatics analysis. Using genome sequencing and analysis of six MPEC strains, our studies have shown that type VI secretion system (T6SS) gene clusters were present in all these strains. Furthermore, using unbiased screening of MPEC strains for reduced colonization, fitness and virulence in the murine mastitis model, we have identified in MPEC P4-NR a new pathogenicity island (PAI-1) encoding the core components of T6SS and its hallmark effectors Hcp, VgrG and Rhs. Next, we have shown that specific deletions of T6SS genes reduced colonization, fitness and virulence in lactating mouse mammary glands. Our long-term goal is to understand the molecular mechanisms of host-pathogen interactions in the mammary gland and to relate these mechanisms to disease processes and pathogenesis. We have been able to achieve our research objectives to identify E. coli genes that are specifically involved in mammary virulence and pathogenicity. The project elucidated a new basic concept in host pathogen interaction of MPEC, which for the best of our knowledge was never described or investigated before. This research will help us to shed new light on principles behind the infection strategy of MPEC. The new targets now enable prevalence and epidemiology studies of T6SS in field strains of MPEC which might unveil new geographic, management and ecological risk factors. These will contribute to development of new approaches to treat and prevent mastitis by MPEC and perhaps other mammary pathogens. The use of antibiotics in farm animals and specifically to treat mastitis is gradually precluded and thus new treatment and prevention strategies are needed. Effective mastitis vaccines are currently not available, structural components and effectors of T6SS might be new targets for the development of novel vaccines and therapeutics.
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