Carbohydrates are one of the four main building blocks of life, and are categorized as monosaccharides (sugars), oligosaccharides and polysaccharides. Each sugar can exist in two alternative anomers (in which a hydroxy group at C-1 takes different orientations) and each pair of sugars can form different epimers (isomers around the stereocentres connecting the sugars). This leads to a vast combinatorial complexity, intractable to mass spectrometry and requiring large amounts of sample for NMR characterization. Combining measurements of collision cross section with mass spectrometry (IM–MS) helps, but many isomers are still difficult to separate. Here, we show that recognition tunnelling (RT) can classify many anomers and epimers via the current fluctuations they produce when captured in a tunnel junction functionalized with recognition molecules. Most importantly, RT is a nanoscale technique utilizing sub-picomole quantities of analyte. If integrated into a nanopore, RT would provide a unique approach to sequencing linear polysaccharides.

A reader molecule, which recognizes all the naturally occurring nucleobases in an electron tunnel junction, is required for sequencing DNA by a recognition tunneling (RT) technique, referred to as a universal reader. In the present study, we have designed a series of heterocyclic carboxamides based on hydrogen bonding and a large-sized pyrene ring based on a π-π stacking interaction as universal reader candidates. Each of these compounds was synthesized to bear a thiolated linker for attachment to metal electrodes and examined for their interactions with naturally occurring DNA nucleosides and nucleotides by H NMR, ESI-MS, computational calculations, and surface plasmon resonance. RT measurements were carried out in a scanning tunnel microscope. All of these molecules generated electrical signals with DNA nucleotides in tunneling junctions under physiological conditions (phosphate buffered aqueous solution, pH 7.4). Using a support vector machine as a tool for data analysis, we found that these candidates distinguished among naturally occurring DNA nucleotides with the accuracy of pyrene (by π-π stacking interactions)> azole carboxamides (by hydrogen-bonding interactions). In addition, the pyrene reader operated efficiently in a larger tunnel junction. However, the azole carboxamide could read abasic (AP) monophosphate, a product from spontaneous base hydrolysis or an intermediate of base excision repair. Thus, we envision that sequencing DNA using both π-π stacking and hydrogen-bonding-based universal readers in parallel should generate more comprehensive genome sequences than sequencing based on either reader molecule alone.

In the present study, we demonstrate a tunneling nanogap technique to identify individual RNA nucleotides, which can be used as a mechanism to read the nucleobases for direct sequencing of RNA in a solid-state nanopore. The tunneling nanogap is composed of two electrodes separated by a distance of <3 nm and functionalized with a recognition molecule. When a chemical entity is captured in the gap, it generates electron tunneling currents, a process we call recognition tunneling (RT). Using RT nanogaps created in a scanning tunneling microscope (STM), we acquired the electron tunneling signals for the canonical and two modified RNA nucleotides. To call the individual RNA nucleotides from the RT data, we adopted a machine learning algorithm, support vector machine (SVM), for the data analysis. Through the SVM, we were able to identify the individual RNA nucleotides and distinguish them from their DNA counterparts with reasonably high accuracy. Since each RNA nucleoside contains a hydroxyl group at the 2'-position of its sugar ring in an RNA strand, it allows for the formation of a tunneling junction at a larger nanogap compared to the DNA nucleoside in a DNA strand, which lacks the 2' hydroxyl group. It also proves advantageous for the manufacture of RT devices. This study is a proof-of-principle demonstration for the development of an RT nanopore device for directly sequencing single RNA molecules, including those bearing modifications.

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While cancer is mostly viewed as a genetic disease and characterized by genetic markers and expression of mutant proteins, there is considerable evidence that there is more to cancer than somatic mutations. For example, the first signature looked for by a pathologist is a grossly aberrant cell nucleus. Chromatin compaction and structure play a major role in the overall nuclear structure. We compared chromatin compaction, structure and gene expression for two esophageal cell lines, EPC2 (non-cancerous) and CP-D (cancerous) by using a combination of salt fractionation, DNA quantification by spectroscopy, atomic force microscopy, and sequencing.Salt fractionation is believed to be an efficient method for quantitative extraction of intact chromatin fragments from cell nuclei. We found that this method is not quantitative unless the supernatant fraction is included. For EPC2 and CP-D cells, about half of the genomic content is solved in the supernatant fraction. Further, we found significant differences for DNA amounts, and chromatin morphology for the cancerous and non-cancerous cell lines, as well as variations in the nucleosome partitioning. We anticipate that our results will help to get insights into the mechanisms of cell phenotype changes from normal to cancerous.