Measuring cation dependent DNA polymerase fidelity landscapes by deep sequencing

Long-duration environmental biosensing by recording analyte detection in DNA using recombinase memory

Microbial biosensors that convert environmental information into real-time visual outputs are limited in their sensing abilities in complex environments, such as soil and wastewater, due to optical inaccessibility. Biosensors that could record transient exposure to analytes within a large time window for later retrieval represent a promising approach to solve the accessibility problem. Here, we test the performance of recombinase-memory biosensors that sense a sugar (arabinose) and a microbial communication molecule (3-oxo-C12-L-homoserine lactone) over 8 days (~70 generations) following analyte exposure. These biosensors sense the analyte and trigger the expression of a recombinase enzyme which flips a segment of DNA, creating a genetic memory, and initiates fluorescent protein expression. The initial designs failed over time due to unintended DNA flipping in the absence of the analyte and loss of the flipped state after exposure to the analyte. Biosensor performance was improved by decreasing recombinase expression, removing the fluorescent protein output, and using quantitative PCR to read out stored information. Application of memory biosensors in wastewater isolates achieved memory of analyte exposure in an uncharacterized Pseudomonas isolate. By returning these engineered isolates to their native environments, recombinase-memory systems are expected to enable longer duration and in situ investigation of microbial signaling, cross-feeding, community shifts, and gene transfer beyond the reach of traditional environmental biosensors.IMPORTANCEMicrobes mediate ecological processes over timescales that can far exceed the half-lives of transient metabolites and signals that drive their collective behaviors. We investigated strategies for engineering microbes to stably record their transient exposure to a chemical over many generations through DNA rearrangements. We identify genetic architectures that improve memory biosensor performance and characterize these in wastewater isolates. Memory biosensors are expected to be useful for monitoring cell-cell signals in biofilms, detecting transient exposure to chemical pollutants, and observing microbial cross-feeding through short-lived metabolites within cryptic methane, nitrogen, and sulfur cycling processes. They will also enable in situ studies of microbial responses to ephemeral environmental changes, or other ecological processes that are currently challenging to monitor non-destructively using real-time biosensors and analytical instruments.

Engineering Ca2+-Dependent DNA Polymerase Activity

Advancements in synthetic biology have provided new opportunities in biosensing, with applications ranging from genetic programming to diagnostics. Next generation biosensors aim to expand the number of accessible environments for measurements, increase the number of measurable phenomena, and improve the quality of the measurement. To this end, an emerging area in the field has been the integration of DNA as an information storage medium within biosensor outputs, leveraging nucleic acids to record the biosensor state over time. However, slow signal transduction steps, due to the time scales of transcription and translation, bottleneck many sensing-DNA recording approaches. DNA polymerases (DNAPs) have been proposed as a solution to the signal transduction problem by operating as both the sensor and responder, but there is presently a lack of DNAPs with functional sensitivity to many desirable target ligands. Here, we engineer components of the Pol δ replicative polymerase complex of Saccharomyces cerevisiae to sense and respond to Ca2+, a metal cofactor relevant to numerous biological phenomena. Through domain insertion and binding site grafting to Pol δ subunits, we demonstrate functional allosteric sensitivity to Ca2+. Together, this work provides an important foundation for future efforts in the development of DNAP-based biosensors.

Time-tagged ticker tapes for intracellular recordings

Recording transcriptional histories of a cell would enable deeper understanding of cellular developmental trajectories and responses to external perturbations. Here we describe an engineered protein fiber that incorporates diverse fluorescent marks during its growth to store a ticker tape-like history. An embedded HaloTag reporter incorporates user-supplied dyes, leading to colored stripes that map the growth of each individual fiber to wall clock time. A co-expressed eGFP tag driven by a promoter of interest records a history of transcriptional activation. High-resolution multi-spectral imaging on fixed samples reads the cellular histories, and interpolation of eGFP marks relative to HaloTag timestamps provides accurate absolute timing. We demonstrate recordings of doxycycline-induced transcription in HEK cells and cFos promoter activation in cultured neurons, with a single-cell absolute accuracy of 30-40 minutes over a 12-hour recording. The protein-based ticker tape design we present here could be generalized to achieve massively parallel single-cell recordings of diverse physiological modalities.

A time-resolved, multi-symbol molecular recorder via sequential genome editing

DNA is naturally well suited to serve as a digital medium for in vivo molecular recording. However, contemporary DNA-based memory devices are constrained in terms of the number of distinct 'symbols' that can be concurrently recorded and/or by a failure to capture the order in which events occur1. Here we describe DNA Typewriter, a general system for in vivo molecular recording that overcomes these and other limitations. For DNA Typewriter, the blank recording medium ('DNA Tape') consists of a tandem array of partial CRISPR-Cas9 target sites, with all but the first site truncated at their 5' ends and therefore inactive. Short insertional edits serve as symbols that record the identity of the prime editing guide RNA2 mediating the edit while also shifting the position of the 'type guide' by one unit along the DNA Tape, that is, sequential genome editing. In this proof of concept of DNA Typewriter, we demonstrate recording and decoding of thousands of symbols, complex event histories and short text messages; evaluate the performance of dozens of orthogonal tapes; and construct 'long tape' potentially capable of recording as many as 20 serial events. Finally, we leverage DNA Typewriter in conjunction with single-cell RNA-seq to reconstruct a monophyletic lineage of 3,257 cells and find that the Poisson-like accumulation of sequential edits to multicopy DNA tape can be maintained across at least 20 generations and 25 days of in vitro clonal expansion.

DNA Strand-Displacement Temporal Logic Circuits

Molecular circuits capable of processing temporal information are essential for complex decision making in response to both the presence and history of a molecular environment. A particular type of temporal information that has been recognized to be important is the relative timing of signals. Here we demonstrate the strategy of temporal memory combined with logic computation in DNA strand-displacement circuits capable of making decisions based on specific combinations of inputs as well as their relative timing. The circuit encodes the timing information on inputs in a set of memory strands, which allows for the construction of logic gates that act on current and historical signals. We show that mismatches can be employed to reduce the complexity of circuit design and that shortening specific toeholds can be useful for improving the robustness of circuit behavior. We also show that a detailed model can provide critical insights for guiding certain aspects of experimental investigations that an abstract model cannot. We envision that the design principles explored in this study can be generalized to more complex temporal logic circuits and incorporated into other types of circuit architectures, including DNA-based neural networks, enabling the implementation of timing-dependent learning rules and opening up new opportunities for embedding intelligent behaviors into artificial molecular machines.

Recording Temporal Signals with Minutes Resolution Using Enzymatic DNA Synthesis

Employing DNA as a high-density data storage medium has paved the way for next-generation digital storage and biosensing technologies. However, the multipart architecture of current DNA-based recording techniques renders them inherently slow and incapable of recording fluctuating signals with subhour frequencies. To address this limitation, we developed a simplified system employing a single enzyme, terminal deoxynucleotidyl transferase (TdT), to transduce environmental signals into DNA. TdT adds nucleotides to the 3'-ends of single-stranded DNA (ssDNA) in a template-independent manner, selecting bases according to inherent preferences and environmental conditions. By characterizing TdT nucleotide selectivity under different conditions, we show that TdT can encode various physiologically relevant signals such as Co2+, Ca2+, and Zn2+ concentrations and temperature changes in vitro. Further, by considering the average rate of nucleotide incorporation, we show that the resulting ssDNA functions as a molecular ticker tape. With this method we accurately encode a temporal record of fluctuations in Co2+ concentration to within 1 min over a 60 min period. Finally, we engineer TdT to allosterically turn off in the presence of a physiologically relevant concentration of calcium. We use this engineered TdT in concert with a reference TdT to develop a two-polymerase system capable of recording a single-step change in the Ca2+ signal to within 1 min over a 60 min period. This work expands the repertoire of DNA-based recording techniques by developing a novel DNA synthesis-based system that can record temporal environmental signals into DNA with a resolution of minutes.

Lineage tracing and analog recording in mammalian cells by single-site DNA writing

Studying cellular and developmental processes in complex multicellular organisms can require the non-destructive observation of thousands to billions of cells deep within an animal. DNA recorders address the staggering difficulty of this task by converting transient cellular experiences into mutations at defined genomic sites that can be sequenced later in high throughput. However, existing recorders act primarily by erasing DNA. This is problematic because, in the limit of progressive erasure, no record remains. We present a DNA recorder called CHYRON (Cell History Recording by Ordered Insertion) that acts primarily by writing new DNA through the repeated insertion of random nucleotides at a single locus in temporal order. To achieve in vivo DNA writing, CHYRON combines Cas9, a homing guide RNA and the template-independent DNA polymerase terminal deoxynucleotidyl transferase. We successfully applied CHYRON as an evolving lineage tracer and as a recorder of user-selected cellular stimuli.

RNA timestamps identify the age of single molecules in RNA sequencing

Current approaches to single-cell RNA sequencing (RNA-seq) provide only limited information about the dynamics of gene expression. Here we present RNA timestamps, a method for inferring the age of individual RNAs in RNA-seq data by exploiting RNA editing. To introduce timestamps, we tag RNA with a reporter motif consisting of multiple MS2 binding sites that recruit the adenosine deaminase ADAR2 fused to an MS2 capsid protein. ADAR2 binding to tagged RNA causes A-to-I edits to accumulate over time, allowing the age of the RNA to be inferred with hour-scale accuracy. By combining observations of multiple timestamped RNAs driven by the same promoter, we can determine when the promoter was active. We demonstrate that the system can infer the presence and timing of multiple past transcriptional events. Finally, we apply the method to cluster single cells according to the timing of past transcriptional activity. RNA timestamps will allow the incorporation of temporal information into RNA-seq workflows.

Enzymatic Synthesis of Designer DNA Using Cyclic Reversible Termination and a Universal Template

Phosphoramidite chemistry remains the industry standard for DNA synthesis despite significant limitations on the length and yield of the oligonucleotide, time restrictions, and hazardous waste production. Herein, we demonstrate the synthesis of single-stranded oligos on a solid surface by DNA polymerases and reverse transcriptases. We report the extension of surface-bound oligonucleotides enabled by transient hybridization of as few as two bases to a neighboring strand. When multiple hybridization structures are possible, each templating a different base, a DNA polymerase or reverse transcriptase can extend the oligonucleotide with any of the complementary bases. Therefore, the sequence of the newly synthesized fragment can be controlled by adding only the desired base as a substrate to the reaction solution. We used this enzymatic approach to synthesize a 20 base oligonucleotide by incorporating reversible terminator dNTPs through a two-step cyclic reversible termination process with a corrected stepwise efficiency over 98%. In our approach, a nascent DNA strand that serves as both primer and template is extended through polymerase-controlled sequential addition of 3'-reversibly blocked nucleotides followed by subsequent cleavage of the 3'-capping group. This process enables oligonucleotide synthesis in an environment not permitted by traditional phosphoramidite methods, eliminates the need for hazardous chemicals, has the potential to provide faster and higher yield results, and synthesizes DNA on a solid support with a free 3' end.

Nano-scale transistors for interfacing with brain: design criteria, progress and prospect

According to the World Health Organization, one quarter of the world's population suffers from various neurological disorders ranging from depression to Alzheimer's disease. Thus, understanding the operation mechanism of the brain enables us to help those who are suffering from these diseases. In addition, recent clinical medicine employs electronic brain implants, despite the fact of being invasive, to treat disorders ranging from severe coronary conditions to traumatic injuries. As a result, the deaf could hear, the blind could see, and the paralyzed could control robotic arms and legs. Due to the requirement of high data management capability with a power consumption as low as possible, designing nanoscale transistors as essential I/O electronics is a complex task. Herein, we review the essential design criteria for such nanoscale transistors, progress and prospect for implantable brain-machine-interface electronics. This article also discusses their technological challenges for practical implementation.

High-resolution mapping of DNA polymerase fidelity using nucleotide imbalances and next-generation sequencing

DNA polymerase fidelity is affected by both intrinsic properties and environmental conditions. Current strategies for measuring DNA polymerase error rate in vitro are constrained by low error subtype sensitivity, poor scalability, and lack of flexibility in types of sequence contexts that can be tested. We have developed the Magnification via Nucleotide Imbalance Fidelity (MagNIFi) assay, a scalable next-generation sequencing assay that uses a biased deoxynucleotide pool to quantitatively shift error rates into a range where errors are frequent and hence measurement is robust, while still allowing for accurate mapping to error rates under typical conditions. This assay is compatible with a wide range of fidelity-modulating conditions, and enables high-throughput analysis of sequence context effects on base substitution and single nucleotide deletion fidelity using a built-in template library. We validate this assay by comparing to previously established fidelity metrics, and use it to investigate neighboring sequence-mediated effects on fidelity for several DNA polymerases. Through these demonstrations, we establish the MagNIFi assay for robust, high-throughput analysis of DNA polymerase fidelity.

Technobiology's Enabler: The Magnetoelectric Nanoparticle

To enable patient- and disease-specific diagnostic and treatment at the intracellular level in real time, it is imperative to engineer a perfect way to locally stimulate selected individual neurons, navigate and dispense a cargo of biomolecules into damaged cells or image sites with relatively high efficacy and with adequate spatial and temporal resolutions. Significant progress has been made using biotechnology; especially with the development of bioinformatics, there are endless molecular databases to identify biomolecules to target almost any disease-specific biomarker. Conversely, the technobiology approach that exploits advanced engineering to control underlying molecular mechanisms to recover biosystem's energy states at the molecular level as well as at the level of the entire network of cells (i.e., the internet of the human body) is still in its early research stage. The recently developed magnetoelectric nanoparticles (MENPs) provide a tool to enable the unique capabilities of technobiology. Using exemplary studies that could potentially lead to future pinpoint treatment and prevention of cancer, neurodegenerative diseases, and HIV, this article discusses how MENPs could become a vital enabling tool of technobiology.

Impact of Privacy Issues on Successful Implementation of Personalized Medicare System

Personalized medicare systems is an emerging field of research, which bears the potential to significantly reduce healthcare expenditures and treatment errors and thereby to revolutionize the entire treatment procedure. In this novel approach, genomic variation in different individuals is duly taken into consideration. However, there exist several serious issues (e.g. privacy concerns) that provide hindrance to large-scale adoption of this medicare system. The main objective of this study has been to identify the privacy issues and to evaluate their impact on successful implementation of this novel medical treatment. The methodology used is empirical and is based on a survey-based post facto procedure. The data collected from the survey are analyzed by using the method of structural modelling analysis. This is an original study in the realm of healthcare management, which reveals that the technology related factors and privacy concerns have considerable impact on the successful implementation of personalized medicare system on a large scale. But the privacy concerns have no significant moderating effect on the impact of technology related factors, so far, the success of implementation of personalized medicine is concerned.

DNA-based memory devices for recording cellular events

Measuring biological data across time and space is critical for understanding complex biological processes and for various biosurveillance applications. However, such data are often inaccessible or difficult to directly obtain. Less invasive, more robust and higher-throughput biological recording tools are needed to profile cells and their environments. DNA-based cellular recording is an emerging and powerful framework for tracking intracellular and extracellular biological events over time across living cells and populations. Here, we review and assess DNA recorders that utilize CRISPR nucleases, integrases and base-editing strategies, as well as recombinase and polymerase-based methods. Quantitative characterization, modelling and evaluation of these DNA-recording modalities can guide their design and implementation for specific application areas.

Mapping the Brain's electric fields with Magnetoelectric nanoparticles

Background

Neurodegenerative diseases are devastating diagnoses. Examining local electric fields in response to neural activity in real time could shed light on understanding the origins of these diseases. To date, there has not been found a way to directly map these fields without interfering with the electric circuitry of the brain. This theoretical study is focused on a nanotechnology concept to overcome the challenge of brain electric field mapping in real time. The paper shows that coupling the magnetoelectric effect of multiferroic nanoparticles, known as magnetoelectric nanoparticles (MENs), with the ultra-fast and high-sensitivity imaging capability of the recently emerged magnetic particle imaging (MPI) can enable wirelessly conducted electric-field mapping with specifications to meet the requirements for monitoring neural activity in real time.

Methods

The MPI signal is numerically simulated on a realistic human brain template obtained from BrainWeb, while brain segmentation was performed with BrainSuite software. The finite element mesh is generated with Computer Geometry Algorithm Library. The effect of MENs is modeled through local point magnetization changes according to the magnetoelectric effect.

Results

It is shown that, unlike traditional magnetic nanoparticles, MENs, when coupled with MPI, provide information containing electric field's spatial and temporal patterns due to local neural activity with signal sensitivities adequate for detection of minute changes at the sub-cellular level corresponding to early stage disease processes.

Conclusions

Like no other nanoparticles known to date, MENs coupled with MPI can be used for mapping electric field activity of the brain at the sub-neuronal level in real time. The potential applications span from prevention and treatment of neurodegenerative diseases to paving the way to fundamental understanding and reverse engineering the brain.

Interfacing Neural Network Components and Nucleic Acids

Translating neural activity into nucleic acid modifications in a controlled manner harbors unique advantages for basic neurobiology and bioengineering. It would allow for a new generation of biological computers that store output in ultra-compact and long-lived DNA and enable the investigation of animal nervous systems at unprecedented scales. Furthermore, by exploiting the ability of DNA to precisely influence neuronal activity and structure, it could be possible to more effectively create cellular therapy approaches for psychiatric diseases that are currently difficult to treat.

Increased Processivity, Misincorporation, and Nucleotide Incorporation Efficiency in Sulfolobus solfataricus Dpo4 Thumb Domain Mutants

The present study aimed to increase the processivity of Sulfolobus solfataricus DNA polymerase Dpo4. Protein engineering and bioinformatics were used to compile a library of potential Dpo4 mutation sites. Ten potential mutants were identified and constructed. A primer extension assay was used to evaluate the processivity of Dpo4 mutants. Thumb (A181D) and finger (E63K) domain mutants showed a processivity of 20 and 19 nucleotides (nt), respectively. A little finger domain mutant (I248Y) exhibited a processivity of 17 nt, only 1 nt more than wild-type Dpo4. Furthermore, the A181D mutant showed lower fidelity and higher nucleotide incorporation efficiency (4.74 × 10^-4 s^-1 μM^-1) than E63K and I248Y mutants. When tasked with bypassing damage, the A181D mutant exhibited a 3.81-fold and 2.62-fold higher catalytic efficiency (k_cat/K_m ) at incorporating dCTP and dATP, respectively, than wild-type Dpo4. It also showed a 55% and 91.5% higher catalytic efficiency when moving beyond the damaged 8-oxoG:C and 8-oxoG:A base pairs, respectively, compared to wild-type Dpo4. Protein engineering and bioinformatics methods can effectively increase the processivity and translesion synthesis ability of Dpo4.IMPORTANCE DNA polymerases with poor fidelity can be exploited to store data and record changes in response to the intracellular environment. Sulfolobus solfataricus Dpo4 is such an enzyme, although its use is hindered by its low processivity. In this work, we used a bioinformatics and protein engineering approach to generate Dpo4 mutants with improved processivity. We identified the Dpo4 thumb domain as the most relevant in controlling processivity.

RNA Polymerase Tags To Monitor Multidimensional Protein-Protein Interactions Reveal Pharmacological Engagement of Bcl-2 Proteins

We report the development of a new technology for monitoring multidimensional protein-protein interactions (PPIs) inside live mammalian cells using split RNA polymerase (RNAP) tags. In this new system, a protein-of-interest is tagged with an N-terminal split RNAP (RNAPN), and multiple potential binding partners are each fused to orthogonal C-terminal RNAPs (RNAPC). Assembly of RNAPN with each RNAPC is highly dependent on interactions between the tagged proteins. Each PPI-mediated RNAPN-RNAPC assembly transcribes from a separate promoter on a supplied DNA substrate, thereby generating a unique RNA output signal for each PPI. We develop and validate this new approach in the context of the Bcl-2 family of proteins. These key regulators of apoptosis are important cancer mediators, but are challenging to therapeutically target due to imperfect selectivity that leads to either off-target toxicity or tumor resistance. We demonstrate binary (1 × 1) and ternary (1 × 2) Bcl-2 PPI analyses by imaging fluorescent protein translation from mRNA outputs. Next, we perform a 1 × 4 PPI network analysis by direct measurement of four unique RNA signals via RT-qPCR. Finally, we use these new tools to monitor pharmacological engagement of Bcl-2 protein inhibitors, and uncover inhibitor-dependent competitive PPIs. The split RNAP tags improve upon other protein fragment complementation (PFC) approaches by offering both multidimensionality and sensitive detection using nucleic acid amplification and analysis techniques. Furthermore, this technology opens new opportunities for synthetic biology applications due to the versatility of RNA outputs for cellular engineering applications.

DNA binding strength increases the processivity and activity of a Y-Family DNA polymerase

DNA polymerase (pol) processivity, i.e., the bases a polymerase extends before falling off the DNA, and activity are important for copying difficult DNA sequences, including simple repeats. Y-family pols would be appealing for copying difficult DNA and incorporating non-natural dNTPs, due to their low fidelity and loose active site, but are limited by poor processivity and activity. In this study, the binding between Dbh and DNA was investigated to better understand how to rationally design enhanced processivity in a Y-family pol. Guided by structural simulation, a fused pol Sdbh with non-specific dsDNA binding protein Sso7d in the N-terminus was designed. This modification increased in vitro processivity 4-fold as compared to the wild-type Dbh. Additionally, bioinformatics was used to identify amino acid mutations that would increase stabilization of Dbh bound to DNA. The variant SdbhM76I further improved the processivity of Dbh by 10 fold. The variant SdbhKSKIP241–245RVRKS showed higher activity than Dbh on the incorporation of dCTP (correct) and dATP (incorrect) opposite the G (normal) or 8-oxoG(damaged) template base. These results demonstrate the capability to rationally design increases in pol processivity and catalytic efficiency through computational DNA binding predictions and the addition of non-specific DNA binding domains.

Nucleotide-time alignment for molecular recorders

Using a DNA polymerase to record intracellular calcium levels has been proposed as a novel neural recording technique, promising massive-scale, single-cell resolution monitoring of large portions of the brain. This technique relies on local storage of neural activity in strands of DNA, followed by offline analysis of that DNA. In simple implementations of this scheme, the time when each nucleotide was written cannot be determined directly by post-hoc DNA sequencing; the timing data must be estimated instead. Here, we use a Dynamic Time Warping-based algorithm to perform this estimation, exploiting correlations between neural activity and observed experimental variables to translate DNA-based signals to an estimate of neural activity over time. This algorithm improves the parallelizability of traditional Dynamic Time Warping, allowing several-fold increases in computation speed. The algorithm also provides a solution to several critical problems with the molecular recording paradigm: determining recording start times and coping with DNA polymerase pausing. The algorithm can generally locate DNA-based records to within <10% of a recording window, allowing for the estimation of unobserved incorporation times and latent neural tunings. We apply our technique to an in silico motor control neuroscience experiment, using the algorithm to estimate both timings of DNA-based data and the directional tuning of motor cortical cells during a center-out reaching task. We also use this algorithm to explore the impact of polymerase characteristics on system performance, determining the precision of a molecular recorder as a function of its kinetic and error-generating properties. We find useful ranges of properties for DNA polymerase-based recorders, providing guidance for future protein engineering attempts. This work demonstrates a useful general extension to dynamic alignment algorithms, as well as direct applications of that extension toward the development of molecular recorders, providing a necessary stepping stone for future biological work.

Rolling Circle Mutagenesis of GST-mCherry to Understand Mutation, Gene Expression, and Regulation

Undergraduates are often familiar with textbook examples of human mutations that affect coding regions and the subsequent disorders, but they may struggle with understanding the implications of mutations in the regulatory regions of genes. We have designed a laboratory sequence that will allow students to explore the effect random mutagenesis can have on protein function, expression, and ultimately phenotype. Students design and perform a safe and time-efficient random mutagenesis experiment using error-prone rolling circular amplification of a plasmid expressing the inducible fusion protein glutathione S-transferase (GST)-mCherry. Mutagenized and wild-type control plasmid DNA, respectively, are then purified and transformed into bacteria to assess phenotypic changes. While bacteria transformed with the wild type control should be pink, some bacterial colonies transformed with mutagenized plasmids will exhibit a different color. Students attempt to identify their mutations by isolating plasmid from these mutant colonies, sequencing, and comparing their mutant sequence to the wild-type sequence. Additionally, students evaluate the potential effects of mutations on protein production by inducing GST-mCherry expression in cultures, generating cell lysates, and analyzing them using SDS-PAGE. Students who have a phenotypic difference but do not obtain a coding region mutation will be able to think critically about plasmid structure and regulation outside of the gene sequence. Students who do not obtain bacterial transformants have the chance to contemplate how mutation of antibiotic resistance genes or replication origins may have contributed to their results. Overall, this series of laboratories exposes students to basic genetic techniques and helps them conceptualize mutation beyond coding regions.

Evolution of a split RNA polymerase as a versatile biosensor platform

Biosensors that transduce target chemical and biochemical inputs into genetic outputs are essential for bioengineering and synthetic biology. Current biosensor design strategies are often limited by a low signal-to-noise ratio, the extensive optimization required for each new input, and poor performance in mammalian cells. Here we report the development of a proximity-dependent split RNA polymerase (RNAP) as a general platform for biosensor engineering. After discovering that interactions between fused proteins modulate the assembly of a split T7 RNAP, we optimized the split RNAP components for protein-protein interaction detection by phage-assisted continuous evolution (PACE). We then applied the resulting activity-responsive RNAP (AR) system to create biosensors that can be activated by light and small molecules, demonstrating the 'plug-and-play' nature of the platform. Finally, we validated that ARs can interrogate multidimensional protein-protein interactions and trigger RNA nanostructure production, protein synthesis, and gene knockdown in mammalian systems, illustrating the versatility of ARs in synthetic biology applications.

Extracting structural and functional features of widely distributed biological circuits with single cell resolution via tissue clearing and delivery vectors

The scientific community has learned a great deal from imaging small and naturally transparent organisms such as nematodes and zebrafish. The consequences of genetic mutations on their organ development and survival can be visualized easily and with high-throughput at the organism-wide scale. In contrast, three-dimensional information is less accessible in mammalian subjects because the heterogeneity of light-scattering tissue elements renders their organs opaque. Likewise, genetically labeling desired circuits across mammalian bodies is prohibitively slow and costly via the transgenic route. Emerging breakthroughs in viral vector engineering, genome editing tools, and tissue clearing can render larger opaque organisms genetically tractable and transparent for whole-organ cell phenotyping, tract tracing and imaging at depth.

Mapping DNA polymerase errors by single-molecule sequencing

Genomic integrity is compromised by DNA polymerase replication errors, which occur in a sequence-dependent manner across the genome. Accurate and complete quantification of a DNA polymerase's error spectrum is challenging because errors are rare and difficult to detect. We report a high-throughput sequencing assay to map in vitro DNA replication errors at the single-molecule level. Unlike previous methods, our assay is able to rapidly detect a large number of polymerase errors at base resolution over any template substrate without quantification bias. To overcome the high error rate of high-throughput sequencing, our assay uses a barcoding strategy in which each replication product is tagged with a unique nucleotide sequence before amplification. This allows multiple sequencing reads of the same product to be compared so that sequencing errors can be found and removed. We demonstrate the ability of our assay to characterize the average error rate, error hotspots and lesion bypass fidelity of several DNA polymerases.

Puzzle Imaging: Using Large-Scale Dimensionality Reduction Algorithms for Localization

Current high-resolution imaging techniques require an intact sample that preserves spatial relationships. We here present a novel approach, "puzzle imaging," that allows imaging a spatially scrambled sample. This technique takes many spatially disordered samples, and then pieces them back together using local properties embedded within the sample. We show that puzzle imaging can efficiently produce high-resolution images using dimensionality reduction algorithms. We demonstrate the theoretical capabilities of puzzle imaging in three biological scenarios, showing that (1) relatively precise 3-dimensional brain imaging is possible; (2) the physical structure of a neural network can often be recovered based only on the neural connectivity matrix; and (3) a chemical map could be reproduced using bacteria with chemosensitive DNA and conjugative transfer. The ability to reconstruct scrambled images promises to enable imaging based on DNA sequencing of homogenized tissue samples.

Critical Challenges for Adopting Personalized Medicine System in Healthcare Management

Personalized Medicine is an emerging approach in today's healthcare management. It bears a very strong potential to consolidate modern e-health systems fundamentally. Scientists have already discovered some of the personalized drugs that can shift the whole medicare process into a new dimension. However, bringing the change in healthcare management is an easy task. There are several critical challenges in the implementation of Personalized Medicine systems. This paper aims at identifying some of these critical challenges through a survey with medical doctors and patients. Challenges involved in implementing Personalized Medicine are listed. A questionnaire was distributed amongst a set of medical doctors, medical researchers, practitioners in pharmaceutical industries, regulatory board members, and a larger section of patients. The response data collected thereby were analysed statistically by using t-test. Summary of the descriptive statistical results of the responses received from medical doctors and patients are presented in tabular form. Based upon the statistical analysis, an attempt has been made in the paper to make a ranking of the challenges. A comparison of the perspectives of the doctors and patients has been made by using bar diagrams. The observations have been discussed in detail and some specific conclusions have been made. To the best of the author's knowledge and belief, this is the first academic paper in which an attempt has been made to suggest the crucial challenges for the implementation of Personalized Medicine. The study shows that both the medical doctors and patients perceive that genomic analysis of all the individuals is the most critical challenge.

Flash memory: photochemical imprinting of neuronal action potentials onto a microbial rhodopsin

We developed a technique, "flash memory", to record a photochemical imprint of the activity state--firing or not firing--of a neuron at a user-selected moment in time. The key element is an engineered microbial rhodopsin protein with three states. Two nonfluorescent states, D1 and D2, exist in a voltage-dependent equilibrium. A stable fluorescent state, F, is reached by a photochemical conversion from D2. When exposed to light of a wavelength λ(write), population transfers from D2 to F, at a rate determined by the D1 ⇌ D2 equilibrium. The population of F maintains a record of membrane voltage which persists in the dark. Illumination at a later time at a wavelength λ(read) excites fluorescence of F, probing this record. An optional third flash at a wavelength λ(reset) converts F back to D2, for a subsequent write-read cycle. The flash memory method offers the promise to decouple the recording of neural activity from its readout. In principle, the technique may enable one to generate snapshots of neural activity in a large volume of neural tissue, e.g., a complete mouse brain, by circumventing the challenge of imaging a large volume with simultaneous high spatial and high temporal resolution. The proof-of-principle flash memory sensors presented here will need improvements in sensitivity, speed, brightness, and membrane trafficking before this goal can be realized.

The role of replicates for error mitigation in next-generation sequencing

Advances in next-generation sequencing (NGS) technologies have rapidly improved sequencing fidelity and substantially decreased sequencing error rates. However, given that there are billions of nucleotides in a human genome, even low experimental error rates yield many errors in variant calls. Erroneous variants can mimic true somatic and rare variants, thus requiring costly confirmatory experiments to minimize the number of false positives. Here, we discuss sources of experimental errors in NGS and how replicates can be used to abate such errors.

Introduction to focus issue: rhythms and dynamic transitions in neurological disease: modeling, computation, and experiment

Rhythmic neuronal oscillations across a broad range of frequencies, as well as spatiotemporal phenomena, such as waves and bumps, have been observed in various areas of the brain and proposed as critical to brain function. While there is a long and distinguished history of studying rhythms in nerve cells and neuronal networks in healthy organisms, the association and analysis of rhythms to diseases are more recent developments. Indeed, it is now thought that certain aspects of diseases of the nervous system, such as epilepsy, schizophrenia, Parkinson's, and sleep disorders, are associated with transitions or disruptions of neurological rhythms. This focus issue brings together articles presenting modeling, computational, analytical, and experimental perspectives about rhythms and dynamic transitions between them that are associated to various diseases.

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.

Incorporation of nucleoside probes opposite O⁶-methylguanine by Sulfolobus solfataricus DNA polymerase Dpo4: importance of hydrogen bonding

O⁶-Methylguanine (O⁶-MeG) is a mutagenic DNA lesion, arising from the action of methylating agents on guanine (G) in DNA. Dpo4, an archaeal low-fidelity Y-family DNA polymerase involved in translesion DNA synthesis (TLS), is a model for studying how human Y-family polymerases bypass DNA adducts. Previous work showed that Dpo4-mediated dTTP incorporation is favored opposite O⁶-MeG rather than opposite G. However, factors influencing the preference of Dpo4 to incorporate dTTP opposite O⁶-MeG are not fully defined. In this study, we investigated the influence of structural features of incoming dNTPs on their enzymatic incorporation opposite O⁶-MeG in a DNA template. To this end, we utilized a new fluorescence-based primer extension assay to evaluate the incorporation efficiency of a panel of synthetic dNTPs opposite G or O⁶-MeG by Dpo4. In single-dNTP primer extension studies, the synthetic dNTPs were preferentially incorporated opposite G, relative to O⁶-MeG. Moreover, pyrimidine-based dNTPs were generally better incorporated than purine-based syn-conformation dNTPs. The results suggest that hydrophobicity of the incoming dNTP appears to have little influence on the process of nucleotide selection by Dpo4, with hydrogen bonding capacity being a major influence. Additionally, modifications at the C2-position of dCTP increase the selectivity for incorporation opposite O⁶-MeG without a significant loss of efficiency.

Statistical analysis of molecular signal recording

A molecular device that records time-varying signals would enable new approaches in neuroscience. We have recently proposed such a device, termed a “molecular ticker tape”, in which an engineered DNA polymerase (DNAP) writes time-varying signals into DNA in the form of nucleotide misincorporation patterns. Here, we define a theoretical framework quantifying the expected capabilities of molecular ticker tapes as a function of experimental parameters. We present a decoding algorithm for estimating time-dependent input signals, and DNAP kinetic parameters, directly from misincorporation rates as determined by sequencing. We explore the requirements for accurate signal decoding, particularly the constraints on (1) the polymerase biochemical parameters, and (2) the amplitude, temporal resolution, and duration of the time-varying input signals. Our results suggest that molecular recording devices with kinetic properties similar to natural polymerases could be used to perform experiments in which neural activity is compared across several experimental conditions, and that devices engineered by combining favorable biochemical properties from multiple known polymerases could potentially measure faster phenomena such as slow synchronization of neuronal oscillations. Sophisticated engineering of DNAPs is likely required to achieve molecular recording of neuronal activity with single-spike temporal resolution over experimentally relevant timescales.

Recording of physiological signals from inaccessible microenvironments is often hampered by the macroscopic sizes of current recording devices. A signal-recording device constructed on a molecular scale could advance biology by enabling the simultaneous recording from millions or billions of cells. We recently proposed a molecular device for recording time-varying ion concentration signals: DNA polymerases (DNAPs) copy known template DNA strands with an error rate dependent on the local ion concentration. The resulting DNA polymers could then be sequenced, and with the help of statistical techniques, used to estimate the time-varying ion concentration signal experienced by the polymerase. We develop a statistical framework to treat this inverse problem and describe a technique to decode the ion concentration signals from DNA sequencing data. We also provide a novel method for estimating properties of DNAP dynamics, such as polymerization rate and pause frequency, directly from sequencing data. We use this framework to explore potential application scenarios for molecular recording devices, achievable via molecular engineering within the biochemical parameter ranges of known polymerases. We find that accurate recording of neural firing rate responses across several experimental conditions would likely be feasible using molecular recording devices with kinetic properties similar to those of known polymerases.

Nanotools for neuroscience and brain activity mapping

Neuroscience is at a crossroads. Great effort is being invested into deciphering specific neural interactions and circuits. At the same time, there exist few general theories or principles that explain brain function. We attribute this disparity, in part, to limitations in current methodologies. Traditional neurophysiological approaches record the activities of one neuron or a few neurons at a time. Neurochemical approaches focus on single neurotransmitters. Yet, there is an increasing realization that neural circuits operate at emergent levels, where the interactions between hundreds or thousands of neurons, utilizing multiple chemical transmitters, generate functional states. Brains function at the nanoscale, so tools to study brains must ultimately operate at this scale, as well. Nanoscience and nanotechnology are poised to provide a rich toolkit of novel methods to explore brain function by enabling simultaneous measurement and manipulation of activity of thousands or even millions of neurons. We and others refer to this goal as the Brain Activity Mapping Project. In this Nano Focus, we discuss how recent developments in nanoscale analysis tools and in the design and synthesis of nanomaterials have generated optical, electrical, and chemical methods that can readily be adapted for use in neuroscience. These approaches represent exciting areas of technical development and research. Moreover, unique opportunities exist for nanoscientists, nanotechnologists, and other physical scientists and engineers to contribute to tackling the challenging problems involved in understanding the fundamentals of brain function.

Polymerization of non-complementary RNA: systematic symmetric nucleotide exchanges mainly involving uracil produce mitochondrial RNA transcripts coding for cryptic overlapping genes

Usual DNA→RNA transcription exchanges T→U. Assuming different systematic symmetric nucleotide exchanges during translation, some GenBank RNAs match exactly human mitochondrial sequences (exchange rules listed in decreasing transcript frequencies): C↔U, A↔U, A↔U+C↔G (two nucleotide pairs exchanged), G↔U, A↔G, C↔G, none for A↔C, A↔G+C↔U, and A↔C+G↔U. Most unusual transcripts involve exchanging uracil. Independent measures of rates of rare replicational enzymatic DNA nucleotide misinsertions predict frequencies of RNA transcripts systematically exchanging the corresponding misinserted nucleotides. Exchange transcripts self-hybridize less than other gene regions, self-hybridization increases with length, suggesting endoribonuclease-limited elongation. Blast detects stop codon depleted putative protein coding overlapping genes within exchange-transcribed mitochondrial genes. These align with existing GenBank proteins (mainly metazoan origins, prokaryotic and viral origins underrepresented). These GenBank proteins frequently interact with RNA/DNA, are membrane transporters, or are typical of mitochondrial metabolism. Nucleotide exchange transcript frequencies increase with overlapping gene densities and stop densities, indicating finely tuned counterbalancing regulation of expression of systematic symmetric nucleotide exchange-encrypted proteins. Such expression necessitates combined activities of suppressor tRNAs matching stops, and nucleotide exchange transcription. Two independent properties confirm predicted exchanged overlap coding genes: discrepancy of third codon nucleotide contents from replicational deamination gradients, and codon usage according to circular code predictions. Predictions from both properties converge, especially for frequent nucleotide exchange types. Nucleotide exchanging transcription apparently increases coding densities of protein coding genes without lengthening genomes, revealing unsuspected functional DNA coding potential.