Solid-state nanopore electrical signatures can be convoluted and are thus challenging to interpret. In order to better understand the origin of these conductance changes, we investigate the translocation of DNA through small, thin pores over a range of voltage. We observe multiple, discrete populations of conductance blockades that vary with applied voltage. To describe our observations, we develop a simple model that is applicable to solid-state nanopores generally. These results represent an important step toward understanding the dynamics of the electrokinetic translocation process.

Based on theoretical evidence, it has been proposed that HIV-1 may encode several selenoprotein modules, one of which (overlapping the env gp41-coding region) has highly significant sequence similarity to the mammalian selenoprotein glutathione peroxidase (GPx; EC 1.11.1.9). The similarity score of the putative HIV-1 viral GPx homolog relative to an aligned set of known GPx is 6.3 SD higher than expected for random sequences of similar composition. Based on that alignment, a molecular model of the HIV-1 GPx was constructed by homology modeling from the bovine GPx crystal structure. Despite extensive truncation relative to the cellular GPx gene, the structural core and the geometry of the catalytic triad of selenocysteine, glutamine, and tryptophan are well conserved in the viral GPx. All of the insertions and deletions predicted by the alignment proved to be structurally feasible. The model is energetically favorable, with a computed molecular mechanics strain energy close to that of the bovine GPx structure, when normalized on a per-residue basis. However, considering the remote homology, this model is intended only to provide a working hypothesis allowing for a similar active site and structural core. To validate the theoretical predictions, we cloned the hypothetical HIV-1 gene and found it to encode functional GPx activity when expressed as a selenoprotein in mammalian cells. In transfected canine kidney cells, the increase in GPx activity ranged from 21% to 43% relative to controls (average 30%, n ‫؍‬ 9, P < 0.0001), whereas, in transfected MCF7 cells, which have low endogenous GPx activity, a near 100% increase was observed (average 99%, n ‫؍‬ 3, P < 0.05).A s various genome projects have continued to expand the number of entries in nucleic acid sequence databases, there has been an increasing demand for computational biology and computational chemistry methods capable of solving several fundamental problems (1). The latter include the prediction of (i) the existence, location and architecture of genes, (ii) the functions of the encoded proteins, and, ultimately, (iii) the structures of the encoded proteins. Advances in comparative sequence analysis, including methods for the identification of remote homologs (1, 2), coupled with advances in protein structure prediction and molecular mechanics (3-5), have now brought all of these objectives within reach, at least when there is some degree of homology between a novel gene and known examples in databases. The ability to identify remote homologs and predict their protein structures is still a major challenge for computational chemists and biologists.The need for such advanced computational methods should not be underestimated, because their use can lead to the identification of genes whose existence or function is not obvious and which can be missed even after extensive analysis by conventional methods.

We demonstrate a solid-state nanopore assay for the unambiguous discrimination and quantification of modified DNA. Individual streptavidin proteins are employed as high-affinity tags for DNA containing a single biotin moiety. We establish that the rate of translocation events corresponds directly to relative concentration of protein-DNA complexes and use the selectivity of our approach to quantify modified oligonucleotides from among a background of unmodified DNA in solution.

The detection and quantification of short nucleic acid sequences has many potential applications in studying biological processes, monitoring disease initiation and progression, and evaluating environmental systems, but is challenging by nature. We present here an assay based on the solid-state nanopore platform for the identification of specific sequences in solution. We demonstrate that hybridization of a target nucleic acid with a synthetic probe molecule enables discrimination between duplex and single-stranded molecules with high efficacy. Our approach requires limited preparation of samples and yields an unambiguous translocation event rate enhancement that can be used to determine the presence and abundance of a single sequence within a background of non-target oligonucleotides.

Higher selenium status has been shown to improve the clinical outcome of infections caused by a range of evolutionally diverse viruses, including SARS-CoV-2. However, the impact of SARS-CoV-2 on host-cell selenoproteins remains elusive. The present study investigated the influence of SARS-CoV-2 on expression of selenoprotein mRNAs in Vero cells. SARS-CoV-2 triggered an inflammatory response as evidenced by increased IL-6 expression. Of the 25 selenoproteins, SARS-CoV-2 significantly suppressed mRNA expression of ferroptosis-associated GPX4, DNA synthesis-related TXNRD3 and endoplasmic reticulum-resident SELENOF, SELENOK, SELENOM and SELENOS. Computational analysis has predicted an antisense interaction between SARS-CoV-2 and TXNRD3 mRNA, which is translated with high efficiency in the lung. Here, we confirmed the predicted SARS-CoV-2/ TXNRD3 antisense interaction in vitro using DNA oligonucleotides, providing a plausible mechanism for the observed mRNA knockdown. Inhibition of TXNRD decreases DNA synthesis which is thereby likely to increase the ribonucleotide pool for RNA synthesis and, accordingly, RNA virus production. The present findings provide evidence for a direct inhibitory effect of SARS-CoV-2 replication on the expression of a specific set of selenoprotein mRNAs, which merits further investigation in the light of established evidence for correlations between dietary selenium status and the outcome of SARS-CoV-2 infection.