Multiplex, Quantitative, High-Resolution Imaging of Protein:Protein Complexes via Hybridization Chain Reaction

Signal amplification based on the mechanism of hybridization chain reaction (HCR) facilitates spatial exploration of gene regulatory networks by enabling multiplex, quantitative, high-resolution imaging of RNA and protein targets. Here, we extend these capabilities to the imaging of protein:protein complexes, using proximity-dependent cooperative probes to conditionally generate a single amplified signal if and only if two target proteins are colocalized within the sample. HCR probes and amplifiers combine to provide automatic background suppression throughout the protocol, ensuring that even if reagents bind nonspecifically in the sample, they will not generate amplified background. We demonstrate protein:protein imaging with a high signal-to-background ratio in human cells, mouse proT cells, and highly autofluorescent formalin-fixed paraffin-embedded (FFPE) human breast tissue sections. Further, we demonstrate multiplex imaging of three different protein:protein complexes simultaneously and validate that HCR enables accurate and precise relative quantitation of protein:protein complexes with subcellular resolution in an anatomical context. Moreover, we establish a unified framework for simultaneous multiplex, quantitative, high-resolution imaging of RNA, protein, and protein:protein targets, with one-step, isothermal, enzyme-free HCR signal amplification performed for all target classes simultaneously.

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets owing to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples, including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of ten RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of the ten channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets due to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of 10 RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of 10 channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

SUMMARY

Spectral imaging with signal amplification based on the mechanism of hybridization chain reaction enables robust 10-plex, quantitative, high-resolution imaging of RNA and protein targets in whole-mount vertebrate embryos and brain sections.

Hybridization Chain Reaction Lateral Flow Assays for Amplified Instrument-Free At-Home SARS-CoV-2 Testing

The lateral flow assay format enables rapid, instrument-free, at-home testing for SARS-CoV-2. Due to the absence of signal amplification, this simplicity comes at a cost in sensitivity. Here, we enhance sensitivity by developing an amplified lateral flow assay that incorporates isothermal, enzyme-free signal amplification based on the mechanism of hybridization chain reaction (HCR). The simplicity of the user experience is maintained using a disposable 3-channel lateral flow device to automatically deliver reagents to the test region in three successive stages without user interaction. To perform a test, the user loads the sample, closes the device, and reads the result by eye after 60 min. Detecting gamma-irradiated SARS-CoV-2 virions in a mixture of saliva and extraction buffer, the current amplified HCR lateral flow assay achieves a limit of detection of 200 copies/μL using available antibodies to target the SARS-CoV-2 nucleocapsid protein. By comparison, five commercial unamplified lateral flow assays that use proprietary antibodies exhibit limits of detection of 500 copies/μL, 1000 copies/μL, 2000 copies/μL, 2000 copies/μL, and 20,000 copies/μL. By swapping out antibody probes to target different pathogens, amplified HCR lateral flow assays offer a platform for simple, rapid, and sensitive at-home testing for infectious diseases. As an alternative to viral protein detection, we further introduce an HCR lateral flow assay for viral RNA detection.

Looking on the horizon; potential and unique approaches to developing radiation countermeasures for deep space travel

Future lunar missions and beyond will require new and innovative approaches to radiation countermeasures. The Translational Research Institute for Space Health (TRISH) is focused on identifying and supporting unique approaches to reduce risks to human health and performance on future missions beyond low Earth orbit. This paper will describe three funded and complementary avenues for reducing the risk to humans from radiation exposure experienced in deep space. The first focus is on identifying new therapeutic targets to reduce the damaging effects of radiation by focusing on high throughput genetic screens in accessible, sometimes called lower, organism models. The second focus is to design innovative approaches for countermeasure development with special attention to nucleotide-based methodologies that may constitute a more agile way to design therapeutics. The final focus is to develop new and innovative ways to test radiation countermeasures in a human model system. While animal studies continue to be beneficial in the study of space radiation, they can have imperfect translation to humans. The use of three-dimensional (3D) complex in vitro models is a promising approach to aid the development of new countermeasures and personalized assessments of radiation risks. These three distinct and unique approaches complement traditional space radiation efforts and should provide future space explorers with more options to safeguard their short and long-term health.

Hybridization chain reaction enables a unified approach to multiplexed, quantitative, high-resolution immunohistochemistry and in situ hybridization

RNA in situ hybridization based on the mechanism of the hybridization chain reaction (HCR) enables multiplexed, quantitative, high-resolution RNA imaging in highly autofluorescent samples, including whole-mount vertebrate embryos, thick brain slices and formalin-fixed paraffin-embedded tissue sections. Here, we extend the benefits of one-step, multiplexed, quantitative, isothermal, enzyme-free HCR signal amplification to immunohistochemistry, enabling accurate and precise protein relative quantitation with subcellular resolution in an anatomical context. Moreover, we provide a unified framework for simultaneous quantitative protein and RNA imaging with one-step HCR signal amplification performed for all target proteins and RNAs simultaneously.

High-Performance Allosteric Conditional Guide RNAs for Mammalian Cell-Selective Regulation of CRISPR/Cas

The activity of a conditional guide RNA (cgRNA) is dependent on the presence or absence of an RNA trigger, enabling cell-selective regulation of CRISPR/Cas function. cgRNAs are programmable at two levels, with the target-binding sequence controlling the target of Cas activity (edit, silence, or induce a gene of choice) and the trigger-binding sequence controlling the scope of Cas activity (subset of cells expressing the trigger RNA). Allosteric cgRNA mechanisms enable independent design of the target and trigger sequences, providing the flexibility to select the regulatory target and scope independently. Building on prior advances in dynamic RNA nanotechnology that demonstrated the cgRNA concept, here we set the goal of engineering high-performance allosteric cgRNA mechanisms for the mammalian setting, pursuing both ON → OFF logic (conditional inactivation by an RNA trigger) and OFF → ON logic (conditional activation by an RNA trigger). For each mechanism, libraries of orthogonal cgRNA/trigger pairs were designed using NUPACK. In HEK 293T cells expressing cgRNAs, triggers, and inducing dCas9: (1) a library of four ON → OFF "terminator switch" cgRNAs exhibit a median fold-change of ≈50×, a median fractional dynamic range of ≈20%, and a median crosstalk modulus of ≈9%; (2) a library of three OFF → ON "split-terminator switch" cgRNAs exhibit a median fold-change of ≈150×, a median fractional dynamic range of ≈50%, and a median crosstalk modulus of ≈4%. Further, we demonstrate that xrRNA elements that protect viral RNAs from degradation by exoribonucleases can dramatically enhance the performance of RNA synthetic biology. The high-performance allosteric cgRNAs demonstrated here for ON → OFF and OFF → ON logic in mammalian cells provide a foundation for pursuing applications of programmable cell-selective regulation.

A Unified Dynamic Programming Framework for the Analysis of Interacting Nucleic Acid Strands: Enhanced Models, Scalability, and Speed

Dynamic programming algorithms within the NUPACK software suite enable analysis of nucleic acid sequences over complex and test tube ensembles containing arbitrary numbers of interacting strand species, serving the needs of researchers in molecular programming, nucleic acid nanotechnology, synthetic biology, and across the life sciences. Here, to enhance the underlying physical model, ensure scalability for large calculations, and achieve dramatic speedups when calculating diverse physical quantities over complex and test tube ensembles, we introduce a unified dynamic programming framework that combines three ingredients: (1) recursions that specify the dependencies between subproblems and incorporate the details of the structural ensemble and the free energy model, (2) evaluation algebras that define the mathematical form of each subproblem, (3) operation orders that specify the computational trajectory through the dependency graph of subproblems. The physical model is enhanced using new recursions that operate over the complex ensemble including coaxial and dangle stacking subensembles. The recursions are coded generically and then compiled with a quantity-specific evaluation algebra and operation order to generate an executable for each physical quantity: partition function, equilibrium base-pairing probabilities, MFE energy and proxy structure, suboptimal proxy structures, and Boltzmann sampled structures. For large complexes (e.g., 30 000 nt), scalability is achieved for partition function calculations using an overflow-safe evaluation algebra, and for equilibrium base-pairing probabilities using a backtrack-free operation order. A new blockwise operation order that treats subcomplex blocks for the complex species in a test tube ensemble enables dramatic speedups (e.g., 20-120× ) using vectorization and caching. With these performance enhancements, equilibrium analysis of substantial test tube ensembles can be performed in ≤ 1 min on a single computational core (e.g., partition function and equilibrium concentration for all complex species of up to six strands formed from two strand species of 300 nt each, or for all complex species of up to two strands formed from 80 strand species of 100 nt each). A new sampling algorithm simultaneously samples multiple structures from the complex ensemble to yield speedups of an order of magnitude or more as the number of structures increases above ≈10³. These advances are available within the NUPACK 4.0 code base (www.nupack.org) which can be flexibly scripted using the all-new NUPACK Python module.

Multiplexed Quantitative In Situ Hybridization with Subcellular or Single-Molecule Resolution Within Whole-Mount Vertebrate Embryos: qHCR and dHCR Imaging (v3.0)

In situ hybridization based on the mechanism of hybridization chain reaction (HCR) enables multiplexed quantitative mRNA imaging in the anatomical context of whole-mount vertebrate embryos. Third-generation in situ HCR (v3.0) provides automatic background suppression throughout the protocol, dramatically enhancing performance and ease of use. In situ HCR v3.0 supports two quantitative imaging modes: (1) qHCR imaging for analog mRNA relative quantitation with subcellular resolution in an anatomical context and (2) dHCR imaging for digital mRNA absolute quantitation with single-molecule resolution in an anatomical context. Here, we provide protocols for qHCR and dHCR imaging in whole-mount zebrafish, chicken, and mouse embryos.

Multiplexed Quantitative In Situ Hybridization for Mammalian or Bacterial Cells in Suspension: qHCR Flow Cytometry (v3.0)

In situ hybridization based on the mechanism of hybridization chain reaction (HCR) enables high-throughput expression profiling of mammalian or bacterial cells via flow cytometry. Third-generation in situ HCR (v3.0) provides automatic background suppression throughout the protocol, dramatically enhancing performance and ease of use. In situ HCR v3.0 supports analog mRNA relative quantitation via qHCR flow cytometry. Here, we provide protocols for multiplexed qHCR flow cytometry for mammalian or bacterial cells in suspension.

Multiplexed Quantitative In Situ Hybridization for Mammalian Cells on a Slide: qHCR and dHCR Imaging (v3.0)

In situ hybridization based on the mechanism of hybridization chain reaction (HCR) enables multiplexed quantitative mRNA imaging in diverse sample types. Third-generation in situ HCR (v3.0) provides automatic background suppression throughout the protocol, dramatically enhancing performance and ease of use. In situ HCR v3.0 supports two quantitative imaging modes: (1) qHCR imaging for analog mRNA relative quantitation with subcellular resolution and (2) dHCR imaging for digital mRNA absolute quantitation with single-molecule resolution. Here, we provide protocols for qHCR and dHCR imaging in mammalian cells on a slide.

Conditional Guide RNAs: Programmable Conditional Regulation of CRISPR/Cas Function in Bacterial and Mammalian Cells via Dynamic RNA Nanotechnology

A guide RNA (gRNA) directs the function of a CRISPR protein effector to a target gene of choice, providing a versatile programmable platform for engineering diverse modes of synthetic regulation (edit, silence, induce, bind). However, the fact that gRNAs are constitutively active places limitations on the ability to confine gRNA activity to a desired location and time. To achieve programmable control over the scope of gRNA activity, here we apply principles from dynamic RNA nanotechnology to engineer conditional guide RNAs (cgRNAs) whose activity is dependent on the presence or absence of an RNA trigger. These cgRNAs are programmable at two levels, with the trigger-binding sequence controlling the scope of the effector activity and the target-binding sequence determining the subject of the effector activity. We demonstrate molecular mechanisms for both constitutively active cgRNAs that are conditionally inactivated by an RNA trigger (ON → OFF logic) and constitutively inactive cgRNAs that are conditionally activated by an RNA trigger (OFF → ON logic). For each mechanism, automated sequence design is performed using the reaction pathway designer within NUPACK to design an orthogonal library of three cgRNAs that respond to different RNA triggers. In E. coli expressing cgRNAs, triggers, and silencing dCas9 as the protein effector, we observe a median conditional response of ≈4-fold for an ON → OFF "terminator switch" mechanism, ≈15-fold for an ON → OFF "splinted switch" mechanism, and ≈3-fold for an OFF → ON "toehold switch" mechanism; the median crosstalk within each cgRNA/trigger library is <2%, ≈2%, and ≈20% for the three mechanisms. To test the portability of cgRNA mechanisms prototyped in bacteria to mammalian cells, as well as to test generalizability to different effector functions, we implemented the terminator switch in HEK 293T cells expressing inducing dCas9 as the protein effector, observing a median ON → OFF conditional response of ≈4-fold with median crosstalk of ≈30% for three orthogonal cgRNA/trigger pairs. By providing programmable control over both the scope and target of protein effector function, cgRNA regulators offer a promising platform for synthetic biology.

Signal Transduction in Human Cell Lysate via Dynamic RNA Nanotechnology

Dynamic RNA nanotechnology with small conditional RNAs (scRNAs) offers a promising conceptual approach to introducing synthetic regulatory links into endogenous biological circuits. Here, we use human cell lysate containing functional Dicer and RNases as a testbed for engineering scRNAs for conditional RNA interference (RNAi). scRNAs perform signal transduction via conditional shape change: detection of a subsequence of mRNA input X triggers formation of a Dicer substrate that is processed to yield small interfering RNA (siRNA) output anti-Y targeting independent mRNA Y for destruction. Automated sequence design is performed using the reaction pathway designer within NUPACK to encode this conditional hybridization cascade into the scRNA sequence subject to the sequence constraints imposed by X and Y. Because it is difficult for secondary structure models to predict which subsequences of mRNA input X will be accessible for detection, here we develop the RNAhyb method to experimentally determine accessible windows within the mRNA that are provided to the designer as sequence constraints. We demonstrate the programmability of scRNA regulators by engineering scRNAs for transducing in both directions between two full-length mRNAs X and Y, corresponding to either the forward molecular logic “if X then not Y” (X  Y) or the reverse molecular logic “if Y then not X” (Y  X). In human cell lysate, we observe a strong OFF/ON conditional response with low crosstalk, corresponding to a ≈20-fold increase in production of the siRNA output in response to the cognate versus noncognate full-length mRNA input. 2′OMe-RNA chemical modifications protect signal transduction reactants and intermediates against RNase degradation while enabling Dicer processing of signal transduction products. Because diverse biological pathways interact with RNA, scRNAs that transduce between detection of endogenous RNA inputs and production of biologically active RNA outputs hold great promise as a synthetic regulatory paradigm.

Third-generation in situ hybridization chain reaction: multiplexed, quantitative, sensitive, versatile, robust

In situ hybridization based on the mechanism of the hybridization chain reaction (HCR) has addressed multi-decade challenges that impeded imaging of mRNA expression in diverse organisms, offering a unique combination of multiplexing, quantitation, sensitivity, resolution and versatility. Here, with third-generation in situ HCR, we augment these capabilities using probes and amplifiers that combine to provide automatic background suppression throughout the protocol, ensuring that reagents will not generate amplified background even if they bind non-specifically within the sample. Automatic background suppression dramatically enhances performance and robustness, combining the benefits of a higher signal-to-background ratio with the convenience of using unoptimized probe sets for new targets and organisms. In situ HCR v3.0 enables three multiplexed quantitative analysis modes: (1) qHCR imaging - analog mRNA relative quantitation with subcellular resolution in the anatomical context of whole-mount vertebrate embryos; (2) qHCR flow cytometry - analog mRNA relative quantitation for high-throughput expression profiling of mammalian and bacterial cells; and (3) dHCR imaging - digital mRNA absolute quantitation via single-molecule imaging in thick autofluorescent samples.

Multidimensional quantitative analysis of mRNA expression within intact vertebrate embryos

For decades, in situ hybridization methods have been essential tools for studies of vertebrate development and disease, as they enable qualitative analyses of mRNA expression in an anatomical context. Quantitative mRNA analyses typically sacrifice the anatomy, relying on embryo microdissection, dissociation, cell sorting and/or homogenization. Here, we eliminate the trade-off between quantitation and anatomical context, using quantitative in situ hybridization chain reaction (qHCR) to perform accurate and precise relative quantitation of mRNA expression with subcellular resolution within whole-mount vertebrate embryos. Gene expression can be queried in two directions: read-out from anatomical space to expression space reveals co-expression relationships in selected regions of the specimen; conversely, read-in from multidimensional expression space to anatomical space reveals those anatomical locations in which selected gene co-expression relationships occur. As we demonstrate by examining gene circuits underlying somitogenesis, quantitative read-out and read-in analyses provide the strengths of flow cytometry expression analyses, but by preserving subcellular anatomical context, they enable bi-directional queries that open a new era for in situ hybridization.

Mapping a multiplexed zoo of mRNA expression

In situ hybridization methods are used across the biological sciences to map mRNA expression within intact specimens. Multiplexed experiments, in which multiple target mRNAs are mapped in a single sample, are essential for studying regulatory interactions, but remain cumbersome in most model organisms. Programmable in situ amplifiers based on the mechanism of hybridization chain reaction (HCR) overcome this longstanding challenge by operating independently within a sample, enabling multiplexed experiments to be performed with an experimental timeline independent of the number of target mRNAs. To assist biologists working across a broad spectrum of organisms, we demonstrate multiplexed in situ HCR in diverse imaging settings: bacteria, whole-mount nematode larvae, whole-mount fruit fly embryos, whole-mount sea urchin embryos, whole-mount zebrafish larvae, whole-mount chicken embryos, whole-mount mouse embryos and formalin-fixed paraffin-embedded human tissue sections. In addition to straightforward multiplexing, in situ HCR enables deep sample penetration, high contrast and subcellular resolution, providing an incisive tool for the study of interlaced and overlapping expression patterns, with implications for research communities across the biological sciences.

Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing

Accurate and robust detection of mRNA molecules in thick tissue samples can reveal gene expression patterns in single cells within their native environment. Preserving spatial relationships while accessing the transcriptome of selected cells is a crucial feature for advancing many biological areas – from developmental biology to neuroscience. However, because of the high autofluorescence background of many tissue samples, it is difficult to detect single-molecule fluorescence in situ hybridization (smFISH) signals robustly in opaque thick samples. Here, we draw on principles from the emerging discipline of dynamic nucleic acid nanotechnology to develop a robust method for multi-color, multi-RNA imaging in deep tissues using single-molecule hybridization chain reaction (smHCR). Using this approach, single transcripts can be imaged using epifluorescence, confocal or selective plane illumination microscopy (SPIM) depending on the imaging depth required. We show that smHCR has high sensitivity in detecting mRNAs in cell culture and whole-mount zebrafish embryos, and that combined with SPIM and PACT (passive CLARITY technique) tissue hydrogel embedding and clearing, smHCR can detect single mRNAs deep within thick (0.5 mm) brain slices. By simultaneously achieving ∼20-fold signal amplification and diffraction-limited spatial resolution, smHCR offers a robust and versatile approach for detecting single mRNAs in situ, including in thick tissues where high background undermines the performance of unamplified smFISH.

Summary: Single-molecule hybridization chain reaction, combined with tissue clearing, allows the near-quantitative and spatially localized detection of mRNAs in thick tissue samples.

Multiplexed miRNA northern blots via hybridization chain reaction

Northern blots enable detection of a target RNA of interest in a biological sample using standard benchtop equipment. miRNAs are the most challenging targets as they must be detected with a single short nucleic acid probe. With existing approaches, it is cumbersome to perform multiplexed blots in which several RNAs are detected simultaneously, impeding the study of interacting regulatory elements. Here, we address this shortcoming by demonstrating multiplexed northern blotting based on the mechanism of hybridization chain reaction (HCR). With this approach, nucleic acid probes complementary to RNA targets trigger chain reactions in which fluorophore-labeled DNA hairpins self-assemble into tethered fluorescent amplification polymers. The programmability of HCR allows multiple amplifiers to operate simultaneously and independently within a blot, enabling straightforward multiplexing. We demonstrate simultaneous detection of three endogenous miRNAs in total RNA extracted from 293T and HeLa cells. For a given target, HCR signal scales linearly with target abundance, enabling relative and absolute quantitation. Using non-radioactive HCR, sensitive and selective miRNA detection is achieved using 2'OMe-RNA probes. The HCR northern blot protocol takes ∼1.5 days independent of the number of target RNAs.

Sequence Design for a Test Tube of Interacting Nucleic Acid Strands

We describe an algorithm for designing the equilibrium base-pairing properties of a test tube of interacting nucleic acid strands. A target test tube is specified as a set of desired "on-target" complexes, each with a target secondary structure and target concentration, and a set of undesired "off-target" complexes, each with vanishing target concentration. Sequence design is performed by optimizing the test tube ensemble defect, corresponding to the concentration of incorrectly paired nucleotides at equilibrium evaluated over the ensemble of the test tube. To reduce the computational cost of accepting or rejecting mutations to a random initial sequence, the structural ensemble of each on-target complex is hierarchically decomposed into a tree of conditional subensembles, yielding a forest of decomposition trees. Candidate sequences are evaluated efficiently at the leaf level of the decomposition forest by estimating the test tube ensemble defect from conditional physical properties calculated over the leaf subensembles. As optimized subsequences are merged toward the root level of the forest, any emergent defects are eliminated via ensemble redecomposition and sequence reoptimization. After successfully merging subsequences to the root level, the exact test tube ensemble defect is calculated for the first time, explicitly checking for the effect of the previously neglected off-target complexes. Any off-target complexes that form at appreciable concentration are hierarchically decomposed, added to the decomposition forest, and actively destabilized during subsequent forest reoptimization. For target test tubes representative of design challenges in the molecular programming and synthetic biology communities, our test tube design algorithm typically succeeds in achieving a normalized test tube ensemble defect ≤1% at a design cost within an order of magnitude of the cost of test tube analysis.

Combinatorial analysis of mRNA expression patterns in mouse embryos using hybridization chain reaction

Multiplexed fluorescent hybridization chain reaction (HCR) and advanced imaging techniques can be used to evaluate combinatorial gene expression patterns in whole mouse embryos with unprecedented spatial resolution. Using HCR, DNA probes complementary to mRNA targets trigger chain reactions in which metastable fluorophore-labeled DNA HCR hairpins self-assemble into tethered fluorescent amplification polymers. Each target mRNA is detected by a probe set containing one or more DNA probes, with each probe carrying two HCR initiators. For multiplexed experiments, probe sets for different target mRNAs carry orthogonal initiators that trigger orthogonal DNA HCR amplification cascades labeled by spectrally distinct fluorophores. As a result, in situ amplification is performed for all targets simultaneously, and the duration of the experiment is independent of the number of target mRNAs. We have used multiplexed fluorescent in situ HCR and advanced imaging technologies to address questions of cell heterogeneity and tissue complexity in craniofacial patterning and anterior neural development. In the sample protocol presented here, we detect three different mRNA targets: Tg(egfp), encoding the enhanced green fluorescent protein (GFP) transgene (typically used as a control); Twist1, encoding a transcription factor involved in cell lineage determination and differentiation; and Pax2, encoding a transcription factor expressed in the mid-hindbrain region of the mouse embryo.

Exquisite sequence selectivity with small conditional RNAs

Dynamic RNA nanotechnology based on programmable hybridization cascades with small conditional RNAs (scRNAs) offers a promising conceptual framework for engineering programmable conditional regulation in vivo. While single-base substitution (SBS) somatic mutations and single-nucleotide polymorphisms (SNPs) are important markers and drivers of disease, it is unclear whether synthetic RNA signal transducers are sufficiently programmable to accept a cognate RNA input while rejecting single-nucleotide sequence variants. Here, we explore the limits of scRNA programmability, demonstrating isothermal, enzyme-free genotyping of RNA SBS cancer markers and SNPs using scRNAs that execute a conditional hybridization cascade in the presence of a cognate RNA target. Kinetic discrimination can be engineered on a time scale of choice from minutes to days. To discriminate even the most challenging single-nucleotide sequence variants, including those that lead to nearly isoenergetic RNA wobble pairs, competitive inhibition with an unstructured scavenger strand or with other scRNAs provides a simple and effective principle for achieving exquisite sequence selectivity.

Next-generation in situ hybridization chain reaction: higher gain, lower cost, greater durability

Hybridization chain reaction (HCR) provides multiplexed, isothermal, enzyme-free, molecular signal amplification in diverse settings. Within intact vertebrate embryos, where signal-to-background is at a premium, HCR in situ amplification enables simultaneous mapping of multiple target mRNAs, addressing a longstanding challenge in the biological sciences. With this approach, RNA probes complementary to mRNA targets trigger chain reactions in which metastable fluorophore-labeled RNA hairpins self-assemble into tethered fluorescent amplification polymers. The properties of HCR lead to straightforward multiplexing, deep sample penetration, high signal-to-background, and sharp subcellular signal localization within fixed whole-mount zebrafish embryos, a standard model system for the study of vertebrate development. However, RNA reagents are expensive and vulnerable to enzymatic degradation. Moreover, the stringent hybridization conditions used to destabilize nonspecific hairpin binding also reduce the energetic driving force for HCR polymerization, creating a trade-off between minimization of background and maximization of signal. Here, we eliminate this trade-off by demonstrating that low background levels can be achieved using permissive in situ amplification conditions (0% formamide, room temperature) and engineer next-generation DNA HCR amplifiers that maximize the free energy benefit per polymerization step while preserving the kinetic trapping property that underlies conditional polymerization, dramatically increasing signal gain, reducing reagent cost, and improving reagent durability.

Developmental self-assembly of a DNA tetrahedron

Kinetically controlled isothermal growth is fundamental to biological development, yet it remains challenging to rationally design molecular systems that self-assemble isothermally into complex geometries via prescribed assembly and disassembly pathways. By exploiting the programmable chemistry of base pairing, sophisticated spatial and temporal control have been demonstrated in DNA self-assembly, but largely as separate pursuits. By integrating temporal with spatial control, here we demonstrate the "developmental" self-assembly of a DNA tetrahedron, where a prescriptive molecular program orchestrates the kinetic pathways by which DNA molecules isothermally self-assemble into a well-defined three-dimensional wireframe geometry. In this reaction, nine DNA reactants initially coexist metastably, but upon catalysis by a DNA initiator molecule, navigate 24 individually characterizable intermediate states via prescribed assembly pathways, organized both in series and in parallel, to arrive at the tetrahedral final product. In contrast to previous work on dynamic DNA nanotechnology, this developmental program coordinates growth of ringed substructures into a three-dimensional wireframe superstructure, taking a step toward the goal of kinetically controlled isothermal growth of complex three-dimensional geometries.

Conditional Dicer substrate formation via shape and sequence transduction with small conditional RNAs

RNA interference (RNAi) mediated by small interfering RNAs (siRNAs) enables knockdown of a gene of choice, executing the logical operation: silence gene Y. The fact that the siRNA is constitutively active is a significant limitation, making it difficult to confine knockdown to a specific locus and time. To achieve spatiotemporal control over silencing, we seek to engineer small conditional RNAs (scRNAs) that mediate 'conditional RNAi' corresponding to the logical operation: if gene X is transcribed, silence independent gene Y. By appropriately selecting gene X, knockdown of gene Y could then be restricted in a tissue- and time-specific manner. To implement the logic of conditional RNAi, our approach is to engineer scRNAs that, upon binding to mRNA 'detection target' X, perform shape and sequence transduction to form a Dicer substrate targeting independent mRNA 'silencing target' Y, with subsequent Dicer processing yielding an siRNA targeting mRNA Y for destruction. Toward this end, here we design and experimentally validate diverse scRNA mechanisms for conditional Dicer substrate formation. Test tube studies demonstrate strong OFF/ON conditional response, with at least an order of magnitude increase in Dicer substrate production in the presence of the cognate mRNA detection target. By appropriately dimensioning and/or chemically modifying the scRNAs, only the product of signal transduction, and not the reactants or intermediates, is efficiently processed by Dicer, yielding siRNAs. These mechanism studies explore diverse design principles for engineering scRNA signal transduction cascades including reactant stability vs metastability, catalytic vs noncatalytic transduction, pre- vs post-transcriptional transduction, reactant and product molecularity, and modes of molecular self-assembly and disassembly.

Selective nucleic acid capture with shielded covalent probes

Nucleic acid probes are used for diverse applications in vitro, in situ, and in vivo. In any setting, their power is limited by imperfect selectivity (binding of undesired targets) and incomplete affinity (binding is reversible, and not all desired targets bound). These difficulties are fundamental, stemming from reliance on base pairing to provide both selectivity and affinity. Shielded covalent (SC) probes eliminate the longstanding trade-off between selectivity and durable target capture, achieving selectivity via programmable base pairing and molecular conformation change, and durable target capture via activatable covalent cross-linking. In pure and mixed samples, SC probes covalently capture complementary DNA or RNA oligo targets and reject two-nucleotide mismatched targets with near-quantitative yields at room temperature, achieving discrimination ratios of 2-3 orders of magnitude. Semiquantitative studies with full-length mRNA targets demonstrate selective covalent capture comparable to that for RNA oligo targets. Single-nucleotide DNA or RNA mismatches, including nearly isoenergetic RNA wobble pairs, can be efficiently rejected with discrimination ratios of 1-2 orders of magnitude. Covalent capture yields appear consistent with the thermodynamics of probe/target hybridization, facilitating rational probe design. If desired, cross-links can be reversed to release the target after capture. In contrast to existing probe chemistries, SC probes achieve the high sequence selectivity of a structured probe, yet durably retain their targets even under denaturing conditions. This previously incompatible combination of properties suggests diverse applications based on selective and stable binding of nucleic acid targets under conditions where base-pairing is disrupted (e.g., by stringent washes in vitro or in situ, or by enzymes in vivo).

NUPACK: Analysis and design of nucleic acid systems

The Nucleic Acid Package (NUPACK) is a growing software suite for the analysis and design of nucleic acid systems. The NUPACK web server (http://www.nupack.org) currently enables:

ANALYSIS

thermodynamic analysis of dilute solutions of interacting nucleic acid strands.

DESIGN

sequence design for complexes of nucleic acid strands intended to adopt a target secondary structure at equilibrium.Utilities: evaluation, display, and annotation of equilibrium properties of a complex of nucleic acid strands. NUPACK algorithms are formulated in terms of nucleic acid secondary structure. In most cases, pseudoknots are excluded from the structural ensemble.

Nucleic acid sequence design via efficient ensemble defect optimization

We describe an algorithm for designing the sequence of one or more interacting nucleic acid strands intended to adopt a target secondary structure at equilibrium. Sequence design is formulated as an optimization problem with the goal of reducing the ensemble defect below a user-specified stop condition. For a candidate sequence and a given target secondary structure, the ensemble defect is the average number of incorrectly paired nucleotides at equilibrium evaluated over the ensemble of unpseudoknotted secondary structures. To reduce the computational cost of accepting or rejecting mutations to a random initial sequence, candidate mutations are evaluated on the leaf nodes of a tree-decomposition of the target structure. During leaf optimization, defect-weighted mutation sampling is used to select each candidate mutation position with probability proportional to its contribution to the ensemble defect of the leaf. As subsequences are merged moving up the tree, emergent structural defects resulting from crosstalk between sibling sequences are eliminated via reoptimization within the defective subtree starting from new random subsequences. Using a Θ(N(3) ) dynamic program to evaluate the ensemble defect of a target structure with N nucleotides, this hierarchical approach implies an asymptotic optimality bound on design time: for sufficiently large N, the cost of sequence design is bounded below by 4/3 the cost of a single evaluation of the ensemble defect for the full sequence. Hence, the design algorithm has time complexity Ω(N(3) ). For target structures containing N ∈{100,200,400,800,1600,3200} nucleotides and duplex stems ranging from 1 to 30 base pairs, RNA sequence designs at 37°C typically succeed in satisfying a stop condition with ensemble defect less than N/100. Empirically, the sequence design algorithm exhibits asymptotic optimality and the exponent in the time complexity bound is sharp.

An autonomous polymerization motor powered by DNA hybridization

We present a synthetic molecular motor capable of autonomous nanoscale transport in solution. Inspired by bacterial pathogens such as Rickettsia rickettsii, which locomote by inducing the polymerization of the protein actin at their surfaces to form 'comet tails', the motor operates by polymerizing a double-helical DNA tail2. DNA strands are propelled processively at the living end of the growing polymers, demonstrating autonomous locomotion powered by the free energy of DNA hybridization.

Topological constraints in nucleic acid hybridization kinetics

A theoretical examination of kinetic mechanisms for forming knots and links in nucleic acid structures suggests that molecules involving base pairs between loops are likely to become topologically trapped in persistent frustrated states through the mechanism of ‘helix-driven wrapping’. Augmentation of the state space to include both secondary structure and topology in describing the free energy landscape illustrates the potential for topological effects to influence the kinetics and function of nucleic acid strands. An experimental study of metastable complementary ‘kissing hairpins’ demonstrates that the topological constraint of zero linking number between the loops effectively prevents conversion to the minimum free energy helical state. Introduction of short catalyst strands that break the topological constraint causes rapid conversion to full duplex.

A synthetic DNA walker for molecular transport

Inspired by kinesin movement along a microtubule, we demonstrate a processive bipedal DNA walker. Powered by externally controlled DNA fuel strands, the walker locomotes with a 5 nm stride by advancing the trailing foot to the lead at each step. Real-time monitoring of specific bidirectional walker movement is achieved via multiplexed fluorescence quenching.

Triggered amplification by hybridization chain reaction

We introduce the concept of hybridization chain reaction (HCR), in which stable DNA monomers assemble only upon exposure to a target DNA fragment. In the simplest version of this process, two stable species of DNA hairpins coexist in solution until the introduction of initiator strands triggers a cascade of hybridization events that yields nicked double helices analogous to alternating copolymers. The average molecular weight of the HCR products varies inversely with initiator concentration. Amplification of more diverse recognition events can be achieved by coupling HCR to aptamer triggers. This functionality allows DNA to act as an amplifying transducer for biosensing applications.

An algorithm for computing nucleic acid base-pairing probabilities including pseudoknots

Given a nucleic acid sequence, a recent algorithm allows the calculation of the partition function over secondary structure space including a class of physically relevant pseudoknots. Here, we present a method for computing base-pairing probabilities starting from the output of this partition function algorithm. The approach relies on the calculation of recursion probabilities that are computed by backtracking through the partition function algorithm, applying a particular transformation at each step. This transformation is applicable to any partition function algorithm that follows the same basic dynamic programming paradigm. Base-pairing probabilities are useful for analyzing the equilibrium ensemble properties of natural and engineered nucleic acids, as demonstrated for a human telomerase RNA and a synthetic DNA nanostructure.

Paradigms for computational nucleic acid design

The design of DNA and RNA sequences is critical for many endeavors, from DNA nanotechnology, to PCR-based applications, to DNA hybridization arrays. Results in the literature rely on a wide variety of design criteria adapted to the particular requirements of each application. Using an extensively studied thermodynamic model, we perform a detailed study of several criteria for designing sequences intended to adopt a target secondary structure. We conclude that superior design methods should explicitly implement both a positive design paradigm (optimize affinity for the target structure) and a negative design paradigm (optimize specificity for the target structure). The commonly used approaches of sequence symmetry minimization and minimum free-energy satisfaction primarily implement negative design and can be strengthened by introducing a positive design component. Surprisingly, our findings hold for a wide range of secondary structures and are robust to modest perturbation of the thermodynamic parameters used for evaluating sequence quality, suggesting the feasibility and ongoing utility of a unified approach to nucleic acid design as parameter sets are refined further. Finally, we observe that designing for thermodynamic stability does not determine folding kinetics, emphasizing the opportunity for extending design criteria to target kinetic features of the energy landscape.

A partition function algorithm for nucleic acid secondary structure including pseudoknots

Nucleic acid secondary structure models usually exclude pseudoknots due to the difficulty of treating these nonnested structures efficiently in structure prediction and partition function algorithms. Here, the standard secondary structure energy model is extended to include the most physically relevant pseudoknots. We describe an O(N(5)) dynamic programming algorithm, where N is the length of the strand, for computing the partition function and minimum energy structure over this class of secondary structures. Hence, it is possible to determine the probability of sampling the lowest energy structure, or any other structure of particular interest. This capability motivates the use of the partition function for the design of DNA or RNA molecules for bioengineering applications.

Exact rotamer optimization for protein design

Computational methods play a central role in the rational design of novel proteins. The present work describes a new hybrid exact rotamer optimization (HERO) method that builds on previous dead-end elimination algorithms to yield dramatic performance enhancements. Measured on experimentally validated physical models, these improvements make it possible to perform previously intractable designs of entire protein core, surface, or boundary regions. Computational demonstrations include a full core design of the variable domains of the light and heavy chains of catalytic antibody 48G7 FAB with 74 residues and 10(128) conformations, a full core/boundary design of the beta1 domain of protein G with 25 residues and 10(53) conformations, and a full surface design of the beta1 domain of protein G with 27 residues and 10(60) conformations. In addition, a full sequence design of the beta1 domain of protein G is used to demonstrate the strong dependence of algorithm performance on the exact form of the potential function and the fidelity of the rotamer library. These results emphasize that search algorithm performance for protein design can only be meaningfully evaluated on physical models that have been subjected to experimental scrutiny. The new algorithm greatly facilitates ongoing efforts to engineer increasingly complex protein features.

Protein design is NP-hard

Biologists working in the area of computational protein design have never doubted the seriousness of the algorithmic challenges that face them in attempting in silico sequence selection. It turns out that in the language of the computer science community, this discrete optimization problem is NP-hard. The purpose of this paper is to explain the context of this observation, to provide a simple illustrative proof and to discuss the implications for future progress on algorithms for computational protein design.