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Gene regulation in prokaryotes often depends on RNA elements such as riboswitches or RNA thermometers located in the 5′ untranslated region of mRNA. Rearrangements of the RNA structure in response, e.g., to the binding of small molecules or ions control translational initiation or premature termination of transcription and thus mRNA expression. Such structural responses are amenable to computational modelling, making it possible to rationally design synthetic riboswitches for a given aptamer. Starting from an artificial aptamer, we construct the first synthetic transcriptional riboswitches that respond to the antibiotic neomycin. We show that the switching behaviour in vivo critically depends not only on the sequence of the riboswitch itself, but also on its sequence context. We therefore developed in silico methods to predict the impact of the context, making it possible to adapt the design and to rescue non-functional riboswitches. We furthermore analyse the influence of 5′ hairpins with varying stability on neomycin riboswitch activity. Our data highlight the limitations of a simple plug-and-play approach in the design of complex genetic circuits and demonstrate that detailed computational models significantly simplify, improve, and automate the design of transcriptional circuits. Our design software is available under a free licence on GitHub (https://github.com/xileF1337/riboswitch_design). [ABSTRACT FROM AUTHOR]

Atomic force microscopy (AFM) is employed to explain the mechanism of the scission of single-walled carbon nanotubes, which is often shown to be induced due to cavitation. The sonication time is shown to exhibit a power law relationship with the maximum tube length distribution.

Individualized single-walled carbon nanotubes (SWNTs) are studied using Resonance Raman spectroscopy/microscopy. It is shown that the high-power, short time sonication used to generate individualized SWNT suspensions does not induce defects in great quantities.

Spontaneous electron loss from Ni(Pc (SO3) sub 4) (super 4-) and Cu(Pc(SO3) sub 4 (super 4-) studied in a UHV Penning trap at ambient temperature is described. The electron detachment energy should be lower for the C (sub 2v) isomer than for the other isomers.

Methylation of cytosine 32 in the anticodon loop of tRNAs to 3-methylcytosine (m 3 C) is crucial for cellular translation fidelity. Misregulation of the RNA methyltransferases setting this modification can cause aggressive cancers and metabolic disturbances. Here, we report the cryo-electron microscopy structure of the human m 3 C tRNA methyltransferase METTL6 in complex with seryl-tRNA synthetase (SerRS) and their common substrate tRNA Ser . Through the complex structure, we identify the tRNA-binding domain of METTL6. We show that SerRS acts as the tRNA Ser substrate selection factor for METTL6. We demonstrate that SerRS augments the methylation activity of METTL6 and that direct contacts between METTL6 and SerRS are necessary for efficient tRNA Ser methylation. Finally, on the basis of the structure of METTL6 in complex with SerRS and tRNA Ser , we postulate a universal tRNA-binding mode for m 3 C RNA methyltransferases, including METTL2 and METTL8, suggesting that these mammalian paralogs use similar ways to engage their respective tRNA substrates and cofactors., (© 2024. The Author(s).)

We have studied intersubband decay of E22 excitons in semiconducting carbon nanotubes experimentally and theoretically. Photoluminescence excitation line widths of semiconducting nanotubes with chiral indicess (n,m) can be mapped onto a connectivity grid with curves of constant (n - m) and (2n + m). Moreover, the global behavior of E22 line widths is best characterized by a strong increase with energy irrespective of their (n-m)mod(3) = +/-1 family affiliation. Solution of the Bethe-Salpeter equations shows that the E22 line widths are dominated by phonon assisted coupling to higher momentum states of the E11 and E12 exciton bands. The calculations also suggest that the branching ratio for decay into exciton bands vs free carrier bands, respectively is about 10:1.