Robert M. Dirks

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.

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(N5) 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.

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’1, 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.

Thermodynamic Analysis of Interacting Nucleic Acid Strands

Motivated by the analysis of natural and engineered DNA and RNA systems, we present the first algorithm for calculating the partition function of an unpseudoknotted complex of multiple interacting nucleic acid strands. This dynamic program is based on a rigorous extension of secondary structure models to the multistranded case, addressing representation and distinguishability issues that do not arise for single-stranded structures. We then derive the form of the partition function for a fixed volume containing a dilute solution of nucleic acid complexes. This expression can be evaluated explicitly for small numbers of strands, allowing the calculation of the equilibrium population distribution for each species of complex. Alternatively, for large systems (e.g., a test tube), we show that the unique complex concentrations corresponding to thermodynamic equilibrium can be obtained by solving a convex programming problem. Partition function and concentration information can then be used to calculate equilibrium base-pairing observables. The underlying physics and mathematical formulation of these problems lead to an interesting blend of approaches, including ideas from graph theory, group theory, dynamic programming, combinatorics, convex optimization, and Lagrange duality.

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.

Selective cell death mediated by small conditional RNAs

Cancer cells are characterized by genetic mutations that deregulate cell proliferation and suppress cell death. To arrest the uncontrolled replication of malignant cells, conventional chemotherapies systemically disrupt cell division, causing diverse and often severe side effects as a result of collateral damage to normal cells. Seeking to address this shortcoming, we pursue therapeutic regulation that is conditional, activating selectively in cancer cells. This functionality is achieved using small conditional RNAs that interact and change conformation to mechanically transduce between detection of a cancer mutation and activation of a therapeutic pathway. Here, we describe small conditional RNAs that undergo hybridization chain reactions (HCR) to induce cell death via an innate immune response if and only if a cognate mRNA cancer marker is detected within a cell. The sequences of the small conditional RNAs can be designed to accept different mRNA markers as inputs to HCR transduction, providing a programmable framework for selective killing of diverse cancer cells. In cultured human cancer cells (glioblastoma, prostate carcinoma, Ewing’s sarcoma), HCR transduction mediates cell death with striking efficacy and selectivity, yielding a 20- to 100-fold reduction in population for cells containing a cognate marker, and no measurable reduction otherwise. Our results indicate that programmable mechanical transduction with small conditional RNAs represents a fundamental principle for exploring therapeutic conditional regulation in living cells.