4,479 research outputs found

    uMELT: prediction of high-resolution melting curves and dynamic melting profiles of PCR products in a rich web application

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    ManuscriptuMeltSM is a flexible web-based tool for predicting DNA melting curves and denaturation profiles of PCR products. The user defines an amplicon sequence and chooses a set of thermodynamic and experimental parameters that include nearest-neighbor stacking energies, loop entropy effects, cation (monovalent and Mg++) concentrations and a temperature range. Using an accelerated partition function algorithm along with chosen parameter values, uMelt interactively calculates and visualizes the mean helicity and the dissociation probability at each sequence position at temperatures within the temperature range. Predicted curves display the mean helicity as a function of temperature or as derivative plots. Predicted profiles display stability as a function of sequence position either as 50% helicity temperatures or as the helicity probability at specific temperatures. The loss of helicity associated with increasing temperature may be viewed dynamically to visualize domain formation within the molecule. Results from fluorescent high-resolution melting experiments match the number of predicted melting domains and their relative temperatures. However, the absolute melting temperatures vary with the selected thermodynamic parameters and current libraries do not account for the rapid melting rates and helix stabilizing dyes used in fluorescent melting experiments. uMelt provides a convenient platform for simulation and design of high-resolution melting assays

    uAnalyze: web-based high-resolution DNA melting analysis with comparison to thermodynamic predictions

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    pre-printAbstract-uAnalyzeSM is a web-based tool for analyzing high-resolution melting data of PCR products. PCR product sequence is input by the user and recursive nearest neighbor thermodynamic calculations used to predict a melting curve similar to uMELT (http://www.dna.utah.edu/umelt/umelt.html). Unprocessed melting data are input directly from LightScanner-96, LS32, or HR-1 data files or via a generic format for other instruments. A fluorescence discriminator identifies low intensity samples to prevent analysis of data that cannot be adequately normalized. Temperature regions that define fluorescence background are initialized by prediction and optionally adjusted by the user. Background is removed either as an exponential or by linear baseline extrapolation. The precision or, "curve spread," of experimental melting curves is quantified as the average of the maximum helicity difference of all curve pairs. Melting curve accuracy is quantified as the area or "2D offset" between the average experimental and predicted melting curves. Optional temperature overlay (temperature shifting) is provided to focus on curve shape. Using 14 amplicons of CYBB, the mean þ= standard deviation of the difference between experimental and predicted fluorescence at 50 percent helicity was 0:04 þ = 0:48C. uAnalyze requires Flash, is not browser specific and can be accessed at http://www.dna.utah.edu/uv/uanalyze.html

    The effect of target secondary structure on microarray data quality

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    DNA? microarrays? have? become? an? invaluable? high? throughput? biotechnology? method,? which? allows? a? parallel? investigation? of? thousands? of? cellular? events? in? a? single?experiment.?The?principle?behind?the?technology?is?very?simple:?fluorescently? labeled? single? stranded? target? molecules? bind? to? their? specific? probes? deposited? on? the? microarray? surface.? However,? the? microarray? data? rarely? represent? a? yes? or? no? answer? to? a? biological? community,? but? rather? provide? a? direction? for? further? investigation.? There? is? a? complicated? quantitative? relationship? between? a? detected? spot? signal? and? the? amount? of? target? present? in? the? unknown? mixture.? We? hypothesize? that? physical? characteristics? of? probe? and? target? molecules? complicate? the?binding?reaction?between?target?and?probe.?To?test?this?hypothesis,?we?designed? a? controlled? microarray? experiment? in? which? the? amount? and? stability? of? the? secondary? structure? present? in? the? probe-binding? regions? of? target? as? biophysical? properties? of? nucleic? acids? varies? in? a? known? way.? ? Based? on? computational? simulations? of? hybridization,? we? hypothesize? that? secondary? structure? formation? in? the? target? can? result? in? considerable? interference? with? the? process? of? probe-target? binding.? ? This? interference? will? have? the? effect? of? lowering? the? spot? signal? intensity.?? We? simulated? hybridization? between? probe? and? target? and? analyzed? the? simulation? data? to? predict? how? much? the? microarray? signal? is? affected? by? folding? of? the? target? molecule,? for? the? purpose? of? developing? a? new? generation? of? microarray? design? and? analysis?software.

    Oligonukleotiidide hübridisatsioonimudeli rakendamine PCR-i ja mikrokiipide optimeerimiseks

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    Väitekirja elektrooniline versioon ei sisalda publikatsioone.Nukleiinhapped on orgaaniliste makromolekulide hulgas unikaalsed tänu oma võimele kodeerida, dekodeerida ja kanda üle digitaalset informatsiooni. See omadus on aluseks nende kasutamisele arenevates tehnoloogiavaldkondades, alates kliinilisest diagnostikast kuni nanotehnoloogia ja informatsiooni talletamiseni. On aga oluline mõista, et digitaalse informatsiooni töötlemise ja säilitamise aluseks nukleiinhapetes on nende keemilised omadused. Tähtsaim nendest on hübridiseerumine - nukleiinhapete võime moodustada spontaanselt kaheahelaline heeliks kahe komplementaarse või osaliselt komplementaarse üheahelalise molekuli liitumisel. Nukleiinhapete hübridisatsiooni termodünaamika arvestamine võimaldab selle protsessi käitumist suure täpsusega modelleerida ja täiustada paljusid biotehnoloogilisi protsesse. Käesolevas väitekirjas on hübridisatsioonimudelit kasutatud multipleks-PCR-i ja detektsiooni mikrokiipide optimeerimiseks. Me töötasime välja ökonoomse algoritmi jaotamaks PCR praimeripaarid multipleksigruppidesse vastavalt nende omavahelisele sobivusele. Algoritm on realiseeritud nii iseseisva programmi kui veebirakendusena. Me uurisime multipleks PCR ebaõnnestumise põhjuseid ja näitasime, et suur arv mittespetsiifilisi seondumiskohti lähte DNA-l vähendab praimerite töötamise edukust. Need praimeripaarid, millel oli liiga suur arv mittespetsiifilisi seondumisi mitte ainult ei töötanud ise halvasti, vaid vähendasid ka teiste nendega koos amplifiseeritud praimeripaaride õnnestumise tõenäosust. Me töötasime välja arvutiprogrammi genereerimaks täieliku nimekirja kõigist võimalikest bakteriaalse tmRNA hübridiseerimisproovidest mis eristaksid omavahel kahte gruppi organisme. Proovide valideerimise käigus me näitasime, et valides hübridisatsioonienergia läviväärtuse suurema kui 4 kcl/mol on võimalik täielikult vältida valepositiivseid signaale. Me uurisime võimalust suurendada bakteriaalse RNA hübridiseerumiskiirust lisades lühikesi spetsiifilisi oligonukleotiide, mis hübridiseerudes lähtemolekulile ei lase selle sekundaarstruktuuril moodustuda. Seda meetodit kasutades tõusis hübridiseerumiskiirus temperatuuril 37C neli korda.Nucleic acids are unique among all organic macromolecules by the ability to encode, decode and transmit digital information. This property is used in emergent technologies as diverse as medical diagnosis, nanoscale engineering and information storage. Still it is important to understand that the basis of this digital information processing are the chemical properties of nucleic acids, the most important being the spontaneous formation of double-stranded helix between complementary or semi-complementary single-stranded molecules, called hybridization. Taking into account the thermodynamic properties of nucleic acid hybridization allows researchers to model the process with great accuracy and thus improve many associated technologies. In current thesis the hybridization model is used to optimize multiplex PCR and microarray hybridization. We developed an efficient algorithm to distribute PCR primer pairs into multiplex groups based on their compatibility with each other. The algorithm is also implemented as both standalone and web-based computer program. We analyzed the probable causes of failure of multiplex PCR and demonstrated that the large number of nonspecific hybridization sites in template DNA is detrimental to PCR quality. Primer pairs with too many nonspecific hybridization sites not only worked poorly but caused the failure of other primer pairs as well. We developed a computer program to generate exhaustive list of all possible hybridization probes for the detection of bacterial tmRNA, capable of distinguishing between two groups of source RNA. The probes were evaluated on microarray and shown that by keeping the hybridization energy cutoff between target and non-target groups over 4 kcal/mol all false-positive signals were eliminated. We analyzed the possibility of increasing the hybridization speed of bacterial tmRNA on low temperatures by applying short specific oligonucleotides that selectively hybridize with template molecules and break their secondary structure. Using this method the hybridization speed was increased fourfold at 37C

    Programing strand displacement reaction pathways using small molecular DNA binders

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    DNA has been used in nature as carriers of heredity information for billions of years. The last four decades have witnessed the success of DNA nanotechnology, an interdisciplinary research area in which DNA is used as a synthetic engineering tool rather than a carrier of genetic information. The growth of DNA nanotechnology crosses the boundaries between physics, chemistry, biology and computer science and enables DNA to function as an electronic component, substrate, drug delivery vector and data storage unit. The hybridization of DNA strictly follows the by Watson-Crick rule; thus, DNA base pairs are the most reliable and predictable building block in the true nanometer range. New methods and designs for controlling DNA hybridization have always provided the most essential momentum for the development of DNA nanotechnology. When small molecules bind to the double helical structure of DNA, either through intercalation or minor groove binding, the stability and functionality of DNA may be significantly altered, which is a fundamental basis for many therapeutic and sensing applications. Herein, we reveal, for the first time, that small molecular DNA binders may also be used to program the reaction pathways of toehold-mediated DNA strand displacement, an elementary building block in DNA nanotechnology

    Synthesis, Binding and Antiviral Properties of Potent Core-Extended Naphthalene Diimides Targeting the HIV-1 Long Terminal Repeat Promoter G-Quadruplexes

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    We have previously reported that stabilization of the G-quadruplex structures in the HIV-1 long terminal repeat (LTR) promoter suppresses viral transcription. Here we sought to develop new G-quadruplex ligands to be exploited as antiviral compounds by enhancing binding toward the viral G-quadruplex structures. We synthesized naphthalene diimide derivatives with a lateral expansion of the aromatic core. The new compounds were able to bind/stabilize the G-quadruplex to a high extent, and some of them displayed clear-cut selectivity toward the viral G-quadruplexes with respect to the human telomeric G-quadruplexes. This feature translated into low nanomolar anti-HIV-1 activity toward two viral strains and encouraging selectivity indexes. The selectivity depended on specific recognition of LTR loop residues; the mechanism of action was ascribed to inhibition of LTR promoter activity in cells. This is the first example of G-quadruplex ligands that show increased selectivity toward the viral G-quadruplexes and display remarkable antiviral activity

    Unraveling the structural complexity in a single-stranded RNA tail: implications for efficient ligand binding in the prequeuosine riboswitch

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    Single-stranded RNAs (ssRNAs) are ubiquitous RNA elements that serve diverse functional roles. Much of our understanding of ssRNA conformational behavior is limited to structures in which ssRNA directly engages in tertiary interactions or is recognized by proteins. Little is known about the structural and dynamic behavior of free ssRNAs at atomic resolution. Here, we report the collaborative application of nuclear magnetic resonance (NMR) and replica exchange molecular dynamics (REMD) simulations to characterize the 12 nt ssRNA tail derived from the prequeuosine riboswitch. NMR carbon spin relaxation data and residual dipolar coupling measurements reveal a flexible yet stacked core adopting an A-form-like conformation, with the level of order decreasing toward the terminal ends. An A-to-C mutation within the polyadenine tract alters the observed dynamics consistent with the introduction of a dynamic kink. Pre-ordering of the tail may increase the efficacy of ligand binding above that achieved by a random-coil ssRNA. The REMD simulations recapitulate important trends in the NMR data, but suggest more internal motions than inferred from the NMR analysis. Our study unmasks a previously unappreciated level of complexity in ssRNA, which we believe will also serve as an excellent model system for testing and developing computational force fields

    Experimental and computational exploration of enzyme sequence space

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    Millions of enzymes with desirable features or new exciting activities can be found in organisms occupying diverse niches all around the earth. However, enzyme studies tend to be biased towards characterisation of representatives from eukaryotes, model organisms, or disease-causing bacteria. As such, a large number of enzymes still remains underexplored. The so-called sequence space of proteins - all possible protein sequences - is even greater when we include not only natural sequences, but also the ones designed by human or artificial intelligence. This thesis explores various reasons, approaches, and outcomes of investigation of large enzymatic sequence spaces.\ua0In the first part of my work, I focused on investigation of a natural sequence space of oxidases using a high-throughput activity profiling platform. A functional screen of an industrially important class of enzymes, S-2-hydroxyacid oxidases (EC 1.1.3.15), revealed that nearly 80% of the class is misannotated. Further exploration of annotations to public databases indicated that similar errors of annotations can be found in other enzyme classes. A broader activity profiling of 1.1.3.x oxidases resulted in the discovery of two novel microbial enzymes: N-acetyl-hexosamine oxidase, and a novel type of long-chain alcohol oxidase.\ua0Natural enzymes often need to be improved in order to be industrially applied, for example to become more stable, or accept non-natural substrates. A novel, and constantly developing, approach for enzyme design involves the use of machine learning (ML) tools. Second part of my work focused on screening an enzyme sequence space designed by generative adversarial networks. Our work proved that ML methods can generate fully functional enzymes that mimic sequences present in nature.Enzyme assays are necessary to get a full understanding of how enzymes work. Traditional kinetic assays are time- and reagent-consuming and as a result a limited number of variants and conditions are being tested for each target. In my final work I described a novel approach for enzyme kinetic studies, by adaptation of a microfluidic qPCR device
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