Design and characterization of a nanopore-coupled polymerase for single-molecule DNA sequencing by synthesis on an electrode array.

Scalable, high-throughput DNA sequencing is a prerequisite for precision medicine and biomedical research. Recently, we presented a nanopore-based sequencing-by-synthesis (Nanopore-SBS) approach, which used a set of nucleotides with polymer tags that allow discrimination of the nucleotides in a biological nanopore. Here, we designed and covalently coupled a DNA polymerase to an α-hemolysin (αHL) heptamer using the SpyCatcher/SpyTag conjugation approach. These porin-polymerase conjugates were inserted into lipid bilayers on a complementary metal oxide semiconductor (CMOS)-based electrode array for high-throughput electrical recording of DNA synthesis. The designed nanopore construct successfully detected the capture of tagged nucleotides complementary to a DNA base on a provided template. We measured over 200 tagged-nucleotide signals for each of the four bases and developed a classification method to uniquely distinguish them from each other and background signals. The probability of falsely identifying a background event as a true capture event was less than 1.2%. In the presence of all four tagged nucleotides, we observed sequential additions in real time during polymerase-catalyzed DNA synthesis. Single-polymerase coupling to a nanopore, in combination with the Nanopore-SBS approach, can provide the foundation for a low-cost, single-molecule, electronic DNA-sequencing platform.

Real-time single-molecule electronic DNA sequencing by synthesis using polymer-tagged nucleotides on a nanopore array.

DNA sequencing by synthesis (SBS) offers a robust platform to decipher nucleic acid sequences. Recently, we reported a single-molecule nanopore-based SBS strategy that accurately distinguishes four bases by electronically detecting and differentiating four different polymer tags attached to the 5'-phosphate of the nucleotides during their incorporation into a growing DNA strand catalyzed by DNA polymerase. Further developing this approach, we report here the use of nucleotides tagged at the terminal phosphate with oligonucleotide-based polymers to perform nanopore SBS on an α-hemolysin nanopore array platform. We designed and synthesized several polymer-tagged nucleotides using tags that produce different electrical current blockade levels and verified they are active substrates for DNA polymerase. A highly processive DNA polymerase was conjugated to the nanopore, and the conjugates were complexed with primer/template DNA and inserted into lipid bilayers over individually addressable electrodes of the nanopore chip. When an incoming complementary-tagged nucleotide forms a tight ternary complex with the primer/template and polymerase, the tag enters the pore, and the current blockade level is measured. The levels displayed by the four nucleotides tagged with four different polymers captured in the nanopore in such ternary complexes were clearly distinguishable and sequence-specific, enabling continuous sequence determination during the polymerase reaction. Thus, real-time single-molecule electronic DNA sequencing data with single-base resolution were obtained. The use of these polymer-tagged nucleotides, combined with polymerase tethering to nanopores and multiplexed nanopore sensors, should lead to new high-throughput sequencing methods.

Physical principles for scalable neural recording.

Simultaneously measuring the activities of all neurons in a mammalian brain at millisecond resolution is a challenge beyond the limits of existing techniques in neuroscience. Entirely new approaches may be required, motivating an analysis of the fundamental physical constraints on the problem. We outline the physical principles governing brain activity mapping using optical, electrical, magnetic resonance, and molecular modalities of neural recording. Focusing on the mouse brain, we analyze the scalability of each method, concentrating on the limitations imposed by spatiotemporal resolution, energy dissipation, and volume displacement. Based on this analysis, all existing approaches require orders of magnitude improvement in key parameters. Electrical recording is limited by the low multiplexing capacity of electrodes and their lack of intrinsic spatial resolution, optical methods are constrained by the scattering of visible light in brain tissue, magnetic resonance is hindered by the diffusion and relaxation timescales of water protons, and the implementation of molecular recording is complicated by the stochastic kinetics of enzymes. Understanding the physical limits of brain activity mapping may provide insight into opportunities for novel solutions. For example, unconventional methods for delivering electrodes may enable unprecedented numbers of recording sites, embedded optical devices could allow optical detectors to be placed within a few scattering lengths of the measured neurons, and new classes of molecularly engineered sensors might obviate cumbersome hardware architectures. We also study the physics of powering and communicating with microscale devices embedded in brain tissue and find that, while radio-frequency electromagnetic data transmission suffers from a severe power-bandwidth tradeoff, communication via infrared light or ultrasound may allow high data rates due to the possibility of spatial multiplexing. The use of embedded local recording and wireless data transmission would only be viable, however, given major improvements to the power efficiency of microelectronic devices.

CAS9 transcriptional activators for target specificity screening and paired nickases for cooperative genome engineering.

Prokaryotic type II CRISPR-Cas systems can be adapted to enable targeted genome modifications across a range of eukaryotes. Here we engineer this system to enable RNA-guided genome regulation in human cells by tethering transcriptional activation domains either directly to a nuclease-null Cas9 protein or to an aptamer-modified single guide RNA (sgRNA). Using this functionality we developed a transcriptional activation-based assay to determine the landscape of off-target binding of sgRNA:Cas9 complexes and compared it with the off-target activity of transcription activator-like (TALs) effectors. Our results reveal that specificity profiles are sgRNA dependent, and that sgRNA:Cas9 complexes and 18-mer TAL effectors can potentially tolerate 1-3 and 1-2 target mismatches, respectively. By engineering a requirement for cooperativity through offset nicking for genome editing or through multiple synergistic sgRNAs for robust transcriptional activation, we suggest methods to mitigate off-target phenomena. Our results expand the versatility of the sgRNA:Cas9 tool and highlight the critical need to engineer improved specificity.

A comparison of successful and failed protein interface designs highlights the challenges of designing buried hydrogen bonds.

The accurate design of new protein-protein interactions is a longstanding goal of computational protein design. However, most computationally designed interfaces fail to form experimentally. This investigation compares five previously described successful de novo interface designs with 158 failures. Both sets of proteins were designed with the molecular modeling program Rosetta. Designs were considered a success if a high-resolution crystal structure of the complex closely matched the design model and the equilibrium dissociation constant for binding was less than 10 µM. The successes and failures represent a wide variety of interface types and design goals including heterodimers, homodimers, peptide-protein interactions, one-sided designs (i.e., where only one of the proteins was mutated) and two-sided designs. The most striking feature of the successful designs is that they have fewer polar atoms at their interfaces than many of the failed designs. Designs that attempted to create extensive sets of interface-spanning hydrogen bonds resulted in no detectable binding. In contrast, polar atoms make up more than 40% of the interface area of many natural dimers, and native interfaces often contain extensive hydrogen bonding networks. These results suggest that Rosetta may not be accurately balancing hydrogen bonding and electrostatic energies against desolvation penalties and that design processes may not include sufficient sampling to identify side chains in preordered conformations that can fully satisfy the hydrogen bonding potential of the interface.

Computational design of a symmetric homodimer using ß-strand assembly.

Computational design of novel protein-protein interfaces is a test of our understanding of protein interactions and has the potential to allow modification of cellular physiology. Methods for designing high-affinity interactions that adopt a predetermined binding mode have proved elusive, suggesting the need for new strategies that simplify the design process. A solvent-exposed backbone on a ß-strand is thought of as "sticky" and ß-strand pairing stabilizes many naturally occurring protein complexes. Here, we computationally redesign a monomeric protein to form a symmetric homodimer by pairing exposed ß-strands to form an intermolecular ß-sheet. A crystal structure of the designed complex closely matches the computational model (rmsd = 1.0 Å). This work demonstrates that ß-strand pairing can be used to computationally design new interactions with high accuracy.

A generic program for multistate protein design.

Some protein design tasks cannot be modeled by the traditional single state design strategy of finding a sequence that is optimal for a single fixed backbone. Such cases require multistate design, where a single sequence is threaded onto multiple backbones (states) and evaluated for its strengths and weaknesses on each backbone. For example, to design a protein that can switch between two specific conformations, it is necessary to to find a sequence that is compatible with both backbone conformations. We present in this paper a generic implementation of multistate design that is suited for a wide range of protein design tasks and demonstrate in silico its capabilities at two design tasks: one of redesigning an obligate homodimer into an obligate heterodimer such that the new monomers would not homodimerize, and one of redesigning a promiscuous interface to bind to only a single partner and to no longer bind the rest of its partners. Both tasks contained negative design in that multistate design was asked to find sequences that would produce high energies for several of the states being modeled. Success at negative design was assessed by computationally redocking the undesired protein-pair interactions; we found that multistate design's accuracy improved as the diversity of conformations for the undesired protein-pair interactions increased. The paper concludes with a discussion of the pitfalls of negative design, which has proven considerably more challenging than positive design.