Investigating routes for in vitro and in vivo data storage

PhD thesisComputing Science, Synthetic Biology and Nanotechnology are converging. Synthetic Biology and Nanotechnology compose the “hardware” platform, whilst Computing Science formulates the logic, data storage and processing pipelines in order to create complex yet controlled behaviour at the nanoscale. Although much work has been done on information processing at the nanoscale via in vivo constructs, e.g. logic gates in various organisms, relatively little has been done on implementing data structure, a fundamental building block for computation. This dissertation proposes and investigates methods to implement data structures by employing biological molecules via both a Synthetic Biology and a Nanotechnological approach. A data structure implemented at the nanoscale could help to substantially increase the complexity of behaviours that could be programmed and embedded in living cells or at the interface between living cells and other nano-substrates, with potential applications in intelligent drug factories and delivery nanosystems, biosensors, and environmental cleaning bionanotechnologies. This work explores the possibility of implementing via DNA constructs, both in vitro and in vivo, "list-like" data structure that can potentially hold an unlimited number of items. This has not been achieved before. Thus, the text describes designs and test prototypes. Firstly, this thesis focuses on an in vitro approach. This is achieved through a DNA-based machinery implementing a signal recorder based on DNA strand displacement reactions. Such DNA architecture can in principle implement a stack machine, capable of storing data providing a dynamic temporary memory capable of pushing and popping data-items encoded in DNA nanostructures (called DNA "bricks”). The "list-like" data is thus represented by a growing (or shrinking) chain of DNA bricks. iv Secondly, I introduce a potential design and initial experiments for an in vivo approach presenting, a synthetic genetic circuit designed to record and accumulate extracellular signals digitally within a "tape" DNA molecule inside a living cell. The core is based on the engineering of the self-splicing group II retrotransposon Ll.LtrB of Lactococcus lactis. Together, these two in vitro and in vivo routes expand our knowledge in the context of molecular memory devices and the biological operations we can compute

Structural and functional characterisation of human RNA helicase DHX8 provides insights into the mechanism of RNA-stimulated ADP release.

DHX8 is a crucial DEAH-box RNA helicase involved in splicing and required for the release of mature mRNA from the spliceosome. Here, we report the biochemical characterisation of full-length human DHX8 and the catalytically active helicase core DHX8Δ547, alongside crystal structures of DHX8Δ547 bound to ADP and a structure of DHX8Δ547 bound to poly(A)6 single-strand RNA. Our results reveal that DHX8 has an in vitro binding preference for adenine-rich RNA and that RNA binding triggers the release of ADP through significant conformational flexibility in the conserved DEAH-, P-loop and hook-turn motifs. We demonstrate the importance of R620 and both the hook-turn and hook-loop regions for DHX8 helicase activity and propose that the hook-turn acts as a gatekeeper to regulate the directional movement of the 3' end of RNA through the RNA-binding channel. This study provides an in-depth understanding of the activity of DHX8 and contributes insights into the RNA-unwinding mechanisms of the DEAH-box helicase family

Revisiting Hybridization Kinetics with Improved Elementary Step Simulation

Nucleic acid strands, which react by forming and breaking Watson-Crick base pairs, can be designed to form complex nanoscale structures or devices. Controlling such systems requires accurate predictions of the reaction rate and of the folding pathways of interacting strands. Simulators such as Multistrand model these kinetic properties using continuous-time Markov chains (CTMCs), whose states and transitions correspond to secondary structures and elementary base pair changes, respectively. The transient dynamics of a CTMC are determined by a kinetic model, which assigns transition rates to pairs of states, and the rate of a reaction can be estimated using the mean first passage time (MFPT) of its CTMC. However, use of Multistrand is limited by its slow runtime, particularly on rare events, and the quality of its rate predictions is compromised by a poorly-calibrated and simplistic kinetic model. The former limitation can be addressed by constructing truncated CTMCs, which only include a small subset of states and transitions, selected either manually or through simulation. As a first step to address the latter limitation, Bayesian posterior inference in an Arrhenius-type kinetic model was performed in earlier work, using a small experimental dataset of DNA reaction rates and a fixed set of manually truncated CTMCs, which we refer to as Assumed Pathway (AP) state spaces. In this work we extend this approach, by introducing a new prior model that is directly motivated by the physical meaning of the parameters and that is compatible with experimental measurements of elementary rates, and by using a larger dataset of 1105 reactions as well as larger truncated state spaces obtained from the recently introduced stochastic Pathway Elaboration (PE) method. We assess the quality of the resulting posterior distribution over kinetic parameters, as well as the quality of the posterior reaction rates predicted using AP and PE state spaces. Finally, we use the newly parameterised PE state spaces and Multistrand simulations to investigate the strong variation of helix hybridization reaction rates in a dataset of Hata et al. While we find strong evidence for the nucleation-zippering model of hybridization, in the classical sense that the rate-limiting phase is composed of elementary steps reaching a small "nucleus" of critical stability, the strongly sequence-dependent structure of the trajectory ensemble up to nucleation appears to be much richer than assumed in the model by Hata et al. In particular, rather than being dominated by the collision probability of nucleation sites, the trajectory segment between first binding and nucleation tends to visit numerous secondary structures involving misnucleation and hairpins, and has a sizeable effect on the probability of overcoming the nucleation barrier

A last-in first-out stack data structure implemented in DNA

DNA-based memory systems are being reported with increasing frequency. However, dynamic DNA data structures able to store and recall information in an ordered way, and able to be interfaced with external nucleic acid computing circuits, have so far received little attention. Here we present an in vitro implementation of a stack data structure using DNA polymers. The stack is able to record combinations of two different DNA signals, release the signals into solution in reverse order, and then re-record. We explore the accuracy limits of the stack data structure through a stochastic rule-based model of the underlying polymerisation chemistry. We derive how the performance of the stack increases with the efficiency of washing steps between successive reaction stages, and report how stack performance depends on the history of stack operations under inefficient washing. Finally, we discuss refinements to improve molecular synchronisation and future open problems in implementing an autonomous chemical data structure

Computation and programmability at the nano-bio interface

PhD ThesisThe manipulation of physical reality on the molecular level and construction of devices operating on the nanoscale has been the focal point of nanotechnology. In particular, nanotechnology based on DNA and RNA has a potential to nd applications in the eld of Synthetic Biology thanks to the inherent compatibility of nucleic acids with biological systems. Sca olded DNA origami, proposed by P. Rothemund, is one of the leading and most successful methods in which nanostructures are realised through rational programming of short 'staple' oligomers which fold a long single-stranded DNA called the 'sca old' strand into a variety of desired shapes. DNA origami already has many applications; including intelligent drug delivery, miniaturisation of logic circuits and computation in vivo. However, one of the factors that are limiting the complexity, applicability and scalability of this approach is the source of the sca old which commonly originates from viruses or phages. Furthermore, developing a robust and orthogonal interface between DNA nanotechnology and biological parts remains a signi cant challenge. The rst part of this thesis tackles these issues by challenging the fundamental as- sumption in the eld, namely that a viral sequence is to be used as the DNA origami sca old. A method is introduced for de novo generation of long synthetic sequences based on De Bruijn sequence, which has been previously proposed in combinatorics. The thesis presents a collection of algorithms which allow the construction of custom- made sequences that are uniquely addressable and biologically orthogonal (i.e. they do not code for any known biological function). Synthetic sca olds generated by these algorithms are computationally analysed and compared with their natural counter- parts with respect to: repetition in sequence, secondary structure and thermodynamic addressability. This also aids the design of wet lab experiments pursuing justi cation and veri cation of this novel approach by empirical evidence. The second part of this thesis discusses the possibility of applying evolutionary op- timisation to synthetic DNA sequences under constraints dictated by the biological interface. A multi-strand system is introduced based on an alternative approach to DNA self-assembly, which relies on strand-displacement cascades, for molecular data storage. The thesis demonstrates how a genetic algorithm can be used to generate viable solutions to this sequence optimisation problem which favours the target self- assembly con guration. Additionally, the kinetics of strand-displacement reactions are analysed with existing coarse-grained DNA models (oxDNA). This thesis is motivated by the application of scienti c computing to problems which lie on the boundary of Computer Science and the elds of DNA Nanotechnology, DNA Computing and Synthetic Biology, and thus I endeavour to the best of my ability to establish this work within the context of these disciplines

Fine Structure of Viral dsDNA Encapsidation

In vivo configurations of dsDNA of bacteriophage viruses in a capsid are known to form hexagonal chromonic liquid crystal phases. This article studies the liquid crystal ordering of viral dsDNA in an icosahedral capsid, combining the chromonic model with that of liquid crystals with variable degree of orientation. The scalar order parameter of the latter allows us to distinguish regions of the capsid with well-ordered DNA from the disordered central core. We employ a state-of-the-art numerical algorithm based on the finite element method to find equilibrium states of the encapsidated DNA and calculate the corresponding pressure. With a data-oriented parameter selection strategy, the method yields phase spaces of the pressure and the radius of the disordered core, in terms of relevant dimensionless parameters, rendering the proposed algorithm into a preliminary bacteriophage designing tool. The presence of the order parameter also has the unique role of allowing for non-smooth capsid domains as well as accounting for knot locations of the DNA

Unravelling the chromosome:An optical tweezers approach to study the structure of human mitotic chromosomes

The genome of the human body is subdivided into 46 chromosomes, the smallest of which contains a total DNA length of 16 mm. During cell division, the chromosome adopts a compacted X-shaped structure with a length of only a few micrometers. As such, the DNA gets compacted around four orders of magnitude in length. How this extremely robust structure is achieved has been a topic of debate for a few decades. Several proteins have been shown to have key functions in the formation and maintenance of this structure (see Chapter 1). However, due to the relatively small and dense structure of the chromosome and the limited control over the conditions that experimentalists have when dealing with living cells, it is very challenging to study the chromosomal architecture. Therefore, we set out to develop a novel methodology with the aim to study the complex structure of mitotic chromosomes in an environment where we have full control over experimental conditions. To this end, we decided to use the technique of optical tweezers, where highly focused laser beams can be used to grab micron-sized objects and apply forces to them. In our lab, this technique is frequently employed to study DNA molecules, by tethering them in between two micron-sized spheres that can be trapped with the optical tweezers. In this thesis a method is presented that allows for the optical manipulation of mitotic chromosomes. We have developed human cell lines that incorporated a specific linker (biotin) at the end of the chromosome arms (telomeres). After isolating the chromosomes from mitotic cells, we could attach the telomeres via strong biotin-streptavidin interactions to our streptavidin-coated microspheres. This enabled us to perform experiments where we probed the mechanical response of the chromosome to applied extensions. From these experiments, we learned that the chromosome is relatively soft for small extensions, but shows a dramatic increase in the force at higher extensions. The observed behavior is not consistent with any classical model that describes polymer (network) mechanics. Therefore, we proposed a new model to describe the chromosome's mechanical behavior. This model describes the chromosome as consisting of many elements or modes that successively stiffen. Moreover, we were able to investigate the role of a specific protein, TopoisomeraseIIα (TOP2A), in the chromosome structure. We found that upon depletion of TOP2A the chromosome shows a softer stiffening behavior. Interestingly, when we perturbed the structure of the chromosome by swelling it with high salt concentrations and then let it come back to its original shape, the control chromosomes did not show significant changes in their stiffness, but the TOP2A degraded chromosomes did. This indicated that TOP2A plays a structural role in chromosome architecture. Together, these results highlighted the capability of our novel method to determine mechanical properties of chromosomes under highly controlled conditions