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Abstract Human mitochondrial tRNAs (mt-tRNAs), critical for mitochondrial biogenesis, are frequently associated with pathogenic mutations. These mt-tRNAs have unusual sequence motifs and require post-transcriptional modifications to stabilize their fragile structures. However, whether a modification that stabilizes a wild-type (WT) mt-tRNA would also stabilize its pathogenic variants is unknown. Here we show that the N 1-methylation of guanosine at position 9 (m1G9) of mt-Leu(UAA), while stabilizing the WT tRNA, has a destabilizing effect on variants associated with MELAS (mitochondrial myopathy, encephalopathy, lactic acidosis, and stroke-like episodes). This differential effect is further demonstrated, as removal of the m1G9 methylation, while damaging to the WT tRNA, is beneficial to the major pathogenic variant, improving the structure and activity of the variant. These results have therapeutic implications, suggesting that the N 1-methylation of mt-tRNAs at position 9 is a determinant of pathogenicity and that controlling the methylation level is an important modulator of mt-tRNA-associated diseases.

Abstract Chemical modifications to mRNA respond dynamically to environmental cues and are important modulators of gene expression. Nanopore direct RNA sequencing has been applied for assessing the presence of pseudouridine (ψ) modifications through basecalling errors and signal analysis. These approaches strongly depend on the sequence context around the modification, and the occupancies derived from these measurements are not quantitative. In this work, we combine direct RNA sequencing of synthetic RNAs bearing site-specific modifications and supervised machine learning models (ModQuant) to achieve near-analytical, site-specific ψ quantification. Our models demonstrate that the ionic current signal features important for accurate ψ classification are sequence dependent and encompass information extending beyond n + 2 and n − 2 nucleotides from the ψ site. This is contradictory to current models, which assume that accurate ψ classification can be achieved with signal information confined to the 5-nucleotide k-mer window (n + 2 and n − 2 nucleotides from the ψ site). We applied our models to quantitatively profile ψ occupancy in five mRNA sites in datasets from seven human cell lines, demonstrating conserved and variable sites. Our study motivates a wider pipeline that uses ground-truth RNA control sets with site-specific modifications for quantitative profiling of RNA modifications. The ModQuant pipeline and guide are freely available at https://github.com/wanunulab/ModQuant .

Pseudouridine (psi) is an RNA modification that can affect its physiology, including increased half-life. Here the authors identify sites of psi modification in the human transcriptome using direct RNA sequencing and provide a “ground truth” list of psi sites, sites of high psi occupancy, and transcripts that may be modified at multiple sites.

Molybdenum disulfide membranes are attractive for filtration of nanoscale species but should be optimized for application. Here, the authors report composite membranes with tunable surface charge, pore size and interlayer spacing, achieving efficient filtration of small-molecule dyes and osmosis.

Solid state nanopores are robust but the sizing can be variable, whereas protein nanopores are precisely sized but lack robustness. Here the authors cork a solid state nanopore with the DNA-translocating portal protein from the virus G20c to obtain a lipid-free hybrid nanopore that can sense various biopolymers.

Abstract We study the driven translocation of a semi-flexible polymer through a nanopore by means of a modified version of the iso-flux tension propagation theory, and extensive molecular dynamics (MD) simulations. We show that in contrast to fully flexible chains, for semi-flexible polymers with a finite persistence length $${\tilde{{\boldsymbol{\ell }}}}_{{\boldsymbol{p}}}$$ ℓ ˜ p the trans side friction must be explicitly taken into account to properly describe the translocation process. In addition, the scaling of the end-to-end distance R N as a function of the chain length N must be known. To this end, we first derive a semi-analytic scaling form for R N, which reproduces the limits of a rod, an ideal chain, and an excluded volume chain in the appropriate limits. We then quantitatively characterize the nature of the trans side friction based on MD simulations. Augmented with these two factors, the theory shows that there are three main regimes for the scaling of the average translocation time τ ∝ N α . In the rod $${\boldsymbol{N}}{\boldsymbol{/}}{\tilde{{\boldsymbol{\ell }}}}_{{\boldsymbol{p}}}{\boldsymbol{\ll }}1$$ N / ℓ ˜ p ≪ 1 , Gaussian $${\boldsymbol{N}}{\boldsymbol{/}}{\tilde{{\boldsymbol{\ell }}}}_{{\boldsymbol{p}}}\sim {\bf{1}}{{\bf{0}}}^{{\bf{2}}}$$ N / ℓ ˜ p ∼ 1 0 2 and excluded volume chain $${\boldsymbol{N}}{\boldsymbol{/}}{\tilde{{\boldsymbol{\kappa }}}}_{{\boldsymbol{p}}}$$ N / κ ˜ p ≫ 10 6 limits, α = 2, 3/2 and 1 + ν, respectively, where ν is the Flory exponent. Our results are in good agreement with available simulations and experimental data.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.