Low-Noise Solid-State Nanopore Enhancing Direct Label-Free Analysis for Small Dimensional Assemblies Induced by Specific Molecular Binding.

Solid-state nanopores show special potential as a new single-molecular characterization for nucleic acid assemblies and molecular machines. However, direct recognition of small dimensional species is still quite difficult due the lower resolution compared with biological pores. We recently reported a very efficient noise-reduction and resolution-enhancement mechanism via introducing high-dielectric additives (e.g., formamide) into conical glass nanopore (CGN) test buffer. Based on this advance, here, for the first time, we apply a bare CGN to directly recognize small dimensional assemblies induced by small molecules. Cocaine and its split aptamer (Capt assembly) are chosen as the model set. By introducing 20% formamide into CGN test buffer, high cocaine-specific distinguishing of the 113 nt Capt assembly has been realized without any covalent label or additional signaling strategies. The signal-to-background discrimination is much enhanced compared with control characterizations such as gel electrophoresis and fluorescence resonance energy transfer (FRET). As a further innovation, we verify that low-noise CGN can also enhance the resolution of small conformational/size changes happening on the side chain of large dimensional substrates. Long duplex concatamers generated from the hybridization chain reaction (HCR) are selected as the model substrates. In the presence of cocaine, low-noise CGN has sensitively captured the current changes when the 26 nt aptamer segment is assembled on the side chain of HCR duplexes. This paper proves that the introduction of the low-noise mechanism has significantly improved the resolution of the solid-state nanopore at smaller and finer scales and thus may direct extensive and deeper research in the field of CGN-based analysis at both single-molecular and statistical levels, such as molecular recognition, assembly characterization, structure identification, information storage, and target index.

Single-Molecule Translocation Conformational Sensing of Multiarm DNA Concatemers Using Glass Capillary Nanopore.

Glass capillary-based nanopore is exploited for single-molecule conformational sensing of multiarm DNA concatemers during translocation. Both translocation frequency and orientation preference were found related with the number of arms of the DNA concatemers.

ConcatSeq: A method for increasing throughput of single molecule sequencing by concatenating short DNA fragments.

Single molecule sequencing (SMS) platforms enable base sequences to be read directly from individual strands of DNA in real-time. Though capable of long read lengths, SMS platforms currently suffer from low throughput compared to competing short-read sequencing technologies. Here, we present a novel strategy for sequencing library preparation, dubbed ConcatSeq, which increases the throughput of SMS platforms by generating long concatenated templates from pools of short DNA molecules. We demonstrate adaptation of this technique to two target enrichment workflows, commonly used for oncology applications, and feasibility using PacBio single molecule real-time (SMRT) technology. Our approach is capable of increasing the sequencing throughput of the PacBio RSII platform by more than five-fold, while maintaining the ability to correctly call allele frequencies of known single nucleotide variants. ConcatSeq provides a versatile new sample preparation tool for long-read sequencing technologies.

Relationships of plant pathogenic enterobacteria based on partial atpD, carA, and recA as individual and concatenated nucleotide and peptide sequences.

Relationships of the genera in the Enterobacteriaceae containing plant pathogenic species: Brenneria, Dickeya, Enterobacter, Erwinia, Pantoea, Pectobacterium, and Samsonia, were investigated by comparison of their nucleotide and peptide sequences of atpD, carA, recA, and the concatenated sequences. Erwinia spp. and Pantoea spp., with Pectobacterium cypripedii, formed a group distinct from other pathogenic taxa. Pectobacterium, Brenneria, Dickeya, and Samsonia formed a contiguous clade. Samsonia was usually concurrent with Pectobacterium. Most Brenneria were also close to Pectobacterium, suggesting that these three taxa might be better represented as a single genus. Brenneria quercina was not closely associated with other members of this genus and may represent a separate genus. The sequences representing Dickeya were distinct, further supporting the generic status of the taxon. Plant pathogenic Enterobacter spp. display such sequence variability that few definite conclusions as to their specific placement could be made. These data highlight the difficulty of drawing reliable and robust taxonomic conclusions based on comparative analysis of sequence data without some independent criterion to calibrate a scale for diversity.

SCaFoS: a tool for selection, concatenation and fusion of sequences for phylogenomics.

BACKGROUND: Phylogenetic analyses based on datasets rich in both genes and species (phylogenomics) are becoming a standard approach to resolve evolutionary questions. However, several difficulties are associated with the assembly of large datasets, such as multiple copies of a gene per species (paralogous or xenologous genes), lack of some genes for a given species, or partial sequences. The use of undetected paralogous or xenologous genes in phylogenetic inference can lead to inaccurate results, and the use of partial sequences to a lack of resolution. A tool that selects sequences, species, and genes, while dealing with these issues, is needed in a phylogenomics context. RESULTS: Here, we present SCaFoS, a tool that quickly assembles phylogenomic datasets containing maximal phylogenetic information while adjusting the amount of missing data in the selection of species, sequences and genes. Starting from individual sequence alignments, and using monophyletic groups defined by the user, SCaFoS creates chimeras with partial sequences, or selects, among multiple sequences, the orthologous and/or slowest evolving sequences. Once sequences representing each predefined monophyletic group have been selected, SCaFos retains genes according to the user's allowed level of missing data and generates files for super-matrix and super-tree analyses in several formats compatible with standard phylogenetic inference software. Because no clear-cut criteria exist for the sequence selection, a semi-automatic mode is available to accommodate user's expertise. CONCLUSION: SCaFos is able to deal with datasets of hundreds of species and genes, both at the amino acid or nucleotide level. It has a graphical interface and can be integrated in an automatic workflow. Moreover, SCaFoS is the first tool that integrates user's knowledge to select orthologous sequences, creates chimerical sequences to reduce missing data and selects genes according to their level of missing data. Finally, applying SCaFoS to different datasets, we show that the judicious selection of genes, species and sequences reduces tree reconstruction artefacts, especially if the dataset includes fast evolving species.

Phylogenetic signal and functional categories in Proteobacteria genomes.

BACKGROUND: A comprehensive evolutionary analysis of bacterial genomes implies to identify the hallmark of vertical and non-vertical signals and to discriminate them from the presence of mere phylogenetic noise. In this report we have addressed the impact of factors like the universal distribution of the genes, their essentiality or their functional role in the cell on the inference of vertical signal through phylogenomic methods. RESULTS: We have established that supermatrices derived from data sets composed mainly by genes suspected to be essential for bacterial cellular life perform better on the recovery of vertical signal than those composed by widely distributed genes. In addition, we show that the "Transcription" category of genes seems to harbor a better vertical signal than other functional categories. Moreover, the "Poorly characterized" category performs better than other categories related with metabolism or cellular processes. CONCLUSION: From these results we conclude that different data sets allow addressing different questions in phylogenomic analyses. The vertical signal seems to be more present in essential genes although these also include a significant degree of incongruence. From a functional perspective, as expected, informational genes perform better than operational ones but we have also shown the surprising behavior of poorly annotated genes, which points to their importance in the genome evolution of bacteria.