![]() ![]() Initially, all possible probes for the user-selected probe length are sorted according to a target “ss-count fraction” ( Fig. Out of the total number predicted (comprising the MFE and suboptimal structures) in which the corresponding nucleotide is This file lists, for each nucleotide in the target RNA, the number of structures PinMol uses as input the “ss-count” file generated by mfold upon folding the RNA target sequence of interest. mfold and RNAstructure predict MFE and suboptimal RNA secondary structures, while the RNAfold generates an MFE secondary structure ( Zuker 2003 Reuter and Mathews 2010 Lorenz et al. mfold, RNAstructure, and the Vienna RNAfold package use similar algorithms, and although they use different sets of RNA thermodynamic parameters ( mfold: 1999 Turner set RNAstructure: 2004 Turner set Vienna RNAfold: choice of 1999 or subset of 2004 Turner set, 2007 Andronescu set) that result in slightly different predictions, their accuracy Parameters, yields a minimum free energy (MFE) structure and a user-selected number of suboptimal (SO) structures ( Zuker 2003). mfold, a software commonly used to predict the secondary structure of nucleic acids using experimentally derived thermodynamic Structure prediction of a limited region within that target ( Lu and Mathews 2008a). When using results fromįree energy minimization algorithms, it is recommended to consider the global structure of a target RNA rather than a local Probe is directly correlated to the accuracy of the predicted secondary structure of the target RNA. Which is generated using either phylogenetic analysis or free energy minimization algorithms. To assess target-site accessibility, it is common to evaluate the predicted secondary structure of the RNA target of interest, Here, we describe a new open-source Python-basedĪpplication that allows fast and easy prediction of molecular beacons tailored for live cell imaging. Need to be optimized to ensure specific and efficient detection of the target RNA. Another reason for the limited in vivo use of molecular beacons is the challenge to design them, as several properties 2011), and more recently, gold nanoparticles were shown to efficiently deliver molecular beacons into live breast cancer cellsįor multiplex detection of mRNAs ( Jackson et al. Others have described the use of toxin-based membrane permeabilization and microporation for efficient cytoplasmic delivery In fruit fly egg chambers via microinjection, to study transport and localization of endogenous maternal mRNAs ( Bratu et al. We have successfully introduced nuclease-resistant molecular beacons One reason is the difficulty in findingĪn efficient delivery method for the chosen live specimen. However, not many groups have reported in vivo mRNA imaging using molecular beacons. One major advantage of using this technology is that molecular beacons allow direct visualization of endogenous mRNAs. Increase in the fluorescence signal ( Fig. In the presence of target, the hybridization of the probe region with the target is energetically moreįavorable than preserving the duplex in the stem, which leads to the separation of the fluorophore/quencher pair and a significant Sequence complementary to the mRNA target (18–26 nucleotides ), and to the double-stranded region (five G/C-rich base In this study, we use the terms “probe” and “stem” to refer to the loop or single-stranded region of the hairpin with a Molecular beacons are oligonucleotides labeled with a fluorophore at the 5′ end and a quencher at the 3′ end that are designed We use the molecular beacon technology for live cell imaging of mRNA transport and localization in the fruit fly egg chamber Previous Section Next Section INTRODUCTIONĬurrently, there are a few methods that are used to image RNA in live tissues and cells, and each has its advantages and disadvantages Here, we show that osk1236 outperformed osk2216 in live cell imaging experiments. We previously demonstrated osk2216 to be efficient in detecting oskar mRNA in in vivo experiments. To demonstrate its applicability, we synthesized an oskar mRNA-specific molecular beacon (osk1236), which is selected by PinMol to target a more accessible region than a manually designed oskar-specific molecular beacon (osk2216). PinMol takes into account the accessibility of the targeted regions, as well as the inter- and intramolecular interactions of each Of the target RNA, predicted via energy minimization approaches. Here, we report a Python program ( PinMol) that designs molecular beacons best suited for live cell imaging by using structural information from secondary structures They are used for the visualization of endogenous mRNAs in live cells. Which fluoresce only when bound to their target RNA. Molecular beacons are nucleic acid oligomers labeled with a fluorophore and a quencher that fold in a hairpin-shaped structure, ![]()
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