Nanofluidic devices for the separation of biomolecules.

Over the last 30-years, microchip electrophoresis and its applications have expanded due to the benefits it offers. Nanochip electrophoresis, on the other hand, is viewed as an evolving area of electrophoresis because it offers some unique advantages not associated with microchip electrophoresis. These advantages arise from unique phenomena that occur in the nanometer domain not readily apparent in the microscale domain due to scale-dependent effects. Scale-dependent effects associated with nanochip electrophoresis includes high surface area-to-volume ratio, electrical double layer overlap generating parabolic flow even for electrokinetic pumping, concentration polarization, transverse electromigration, surface charge dominating flow, and surface roughness. Nanochip electrophoresis devices consist of channels with dimensions ranging from 1 to 1000 nm including classical (1-100 nm) and extended (100 nm - 1000 nm) nanoscale devices. In this review, we highlight scale-dependent phenomena associated with nanochip electrophoresis and the utilization of those phenomena to provide unique biomolecular separations that are not possible with microchip electrophoresis. We will also review the range of materials used for nanoscale separations and the implication of material choice for the top-down fabrication and operation of these devices. We will also provide application examples of nanochip electrophoresis for biomolecule separations with an emphasis on nano-electrophoresis (nEP) and nano-electrochromatography (nEC).

The complete genome sequence of Ethanoligenens harbinense reveals the metabolic pathway of acetate-ethanol fermentation: A novel understanding of the principles of anaerobic biotechnology.

Ethanol-type fermentation is one of three main fermentation types in the acidogenesis of anaerobic treatment systems. Non-spore-forming Ethanoligenens is as a typical genus capable of ethanol-type fermentation in mixed culture (i.e. acetate-ethanol fermentation). This genus can produce ethanol, acetate, CO2, and H2 using carbohydrates, and has application potential in anaerobic bioprocesses. Here, the complete genome sequences and methylome of Ethanoligenens harbinense strains with different autoaggregative and coaggregative abilities were obtained using the PacBio single-molecule real-time sequencing platform. The genome size of E. harbinense strains was about 2.97-3.10 Mb with 55.5% G+C content. 3020-3153 genes were annotated, most of which were methylated at specific sites or motifs. The methylation types included 6mA, 4mC, and unknown types. Comparative genomic analysis demonstrated low levels of genetic similarity between E. harbinense and other well-known hydrogen-producing bacteria (i.e., Clostridium and Thermoanaerobacter) in phylogenesis. Hydrogen production of E. harbinense was catalyzed by genes that encode [FeFe]­hydrogenases and that were synthesized by three maturases of [FeFe]-H2ase. The metabolic mechanism of H2-ethanol co-production fermentation, catalyzed by pyruvate ferredoxin oxidoreductase was proposed. This study provides genetic and evolutionary information of a model genus for the further investigation of the metabolic pathway and regulatory network of ethanol-type fermentation and anaerobic bioprocesses for waste or wastewater treatment.

Benchmark Evaluation of True Single Molecular Sequencing to Determine Cystic Fibrosis Airway Microbiome Diversity.

Cystic fibrosis (CF) is an autosomal recessive disease associated with recurrent lung infections that can lead to morbidity and mortality. The impact of antibiotics for treatment of acute pulmonary exacerbations on the CF airway microbiome remains unclear with prior studies giving conflicting results and being limited by their use of 16S ribosomal RNA sequencing. Our primary objective was to validate the use of true single molecular sequencing (tSMS) and PathoScope in the analysis of the CF airway microbiome. Three control samples were created with differing amounts of Burkholderia cepacia, Pseudomonas aeruginosa, and Prevotella melaninogenica, three common bacteria found in cystic fibrosis lungs. Paired sputa were also obtained from three study participants with CF before and >6 days after initiation of antibiotics. Antibiotic resistant B. cepacia and P. aeruginosa were identified in concurrently obtained respiratory cultures. Direct sequencing was performed using tSMS, and filtered reads were aligned to reference genomes from NCBI using PathoScope and Kraken and unique clade-specific marker genes using MetaPhlAn. A total of 180-518 K of 6-12 million filtered reads were aligned for each sample. Detection of known pathogens in control samples was most successful using PathoScope. In the CF sputa, alpha diversity measures varied based on the alignment method used, but similar trends were found between pre- and post-antibiotic samples. PathoScope outperformed Kraken and MetaPhlAn in our validation study of artificial bacterial community controls and also has advantages over Kraken and MetaPhlAn of being able to determine bacterial strains and the presence of fungal organisms. PathoScope can be confidently used when evaluating metagenomic data to determine CF airway microbiome diversity.

Quantum Point Contact Single-Nucleotide Conductance for DNA and RNA Sequence Identification.

Several nanoscale electronic methods have been proposed for high-throughput single-molecule nucleic acid sequence identification. While many studies display a large ensemble of measurements as "electronic fingerprints" with some promise for distinguishing the DNA and RNA nucleobases (adenine, guanine, cytosine, thymine, and uracil), important metrics such as accuracy and confidence of base calling fall well below the current genomic methods. Issues such as unreliable metal-molecule junction formation, variation of nucleotide conformations, insufficient differences between the molecular orbitals responsible for single-nucleotide conduction, and lack of rigorous base calling algorithms lead to overlapping nanoelectronic measurements and poor nucleotide discrimination, especially at low coverage on single molecules. Here, we demonstrate a technique for reproducible conductance measurements on conformation-constrained single nucleotides and an advanced algorithmic approach for distinguishing the nucleobases. Our quantum point contact single-nucleotide conductance sequencing (QPICS) method uses combed and electrostatically bound single DNA and RNA nucleotides on a self-assembled monolayer of cysteamine molecules. We demonstrate that by varying the applied bias and pH conditions, molecular conductance can be switched ON and OFF, leading to reversible nucleotide perturbation for electronic recognition (NPER). We utilize NPER as a method to achieve >99.7% accuracy for DNA and RNA base calling at low molecular coverage (∼12×) using unbiased single measurements on DNA/RNA nucleotides, which represents a significant advance compared to existing sequencing methods. These results demonstrate the potential for utilizing simple surface modifications and existing biochemical moieties in individual nucleobases for a reliable, direct, single-molecule, nanoelectronic DNA and RNA nucleotide identification method for sequencing.