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Biology subjects

Dalchau, N.

Publications and source records attributed to Dalchau, N..

8 recordsLinked to original sources

Decentralizing cell-free RNA sensing with the use of low-cost cell extracts

Cell-free gene expression systems have emerged as a promising platform for field-deployed biosensing and diagnostics. When combined with programmable toehold switch-based RNA sensors, these systems can be used to detect arbitrary RNAs and freeze-dried for room temperature transport to the point-of-need. These sensors, however, have been implemented using reconstituted PURE cell-free protein expression systems that are difficult to source in the Global South due to their high commercial cost and cold-chain shipping requirements. Here, we describe the implementation of RNA toehold switch-based sensors using E. coli cell lysate-based cell-free protein expression systems, which can be produced locally and reduce the cost of sensors by two orders of magnitude. We then demonstrate that these in-house cell lysates provide sensor performance comparable to commercial PURE cell-free systems. We further optimize use of these lysates with a CRISPRi strategy to enhance the stability of linear DNAs, enabling the direct use of PCR products for fast screening of new designs. As a proof-of-concept, we develop novel toehold sensors for the plant pathogen Potato Virus Y (PVY), which dramatically reduces the yield of this important staple crop. The local implementation of low-cost cell-free toehold sensors could enable biosensing capacity at the regional level and lead to more decentralized models for global surveillance of infectious disease.

bioengineering↗

Intein-assisted bisection mapping systematically splits proteins for Boolean logic and inducibility engineering

Split inteins are powerful tools for seamless ligation of synthetic split proteins. Yet, their use remains limited because the already intricate split site identification problem is often complicated by the requirement of extein junction sequences. To address this, we augmented a mini-Mu transposon-based screening approach and devised the intein-assisted bisection mapping (IBM) method. IBM robustly revealed clusters of split sites on five proteins, converting them into AND or NAND logic gates. We further showed that the use of inteins expands functional sequence space for splitting a protein. We also demonstrated the utility of our approach over rational inference of split sites from secondary structure alignment of homologous proteins. Furthermore, the intein inserted at an identified site could be engineered by the transposon again to become partially chemically inducible, and to some extent enabled post-translational tuning on host protein function. Our work offers a generalizable and systematic route towards creating split protein-intein fusions and conditional inteins for protein activity control.

synthetic biology↗

Scalable dynamic characterization of synthetic gene circuits

The dynamic behavior of synthetic gene circuits plays a key role in ensuring their correct function. Although there has been substantial work on modeling dynamic behavior after circuit construction, the forward engineering of dynamic behavior remains a major challenge. Previous engineering methods have focused on quantifying average behaviors of circuits over an extended time window, however this provides a static characterization of behavior that is a poor predictor of dynamics. Here we present a method for characterizing the dynamic behavior of synthetic gene circuits, using parameter inference of dynamical system models applied to time-series measurements of cell cultures growing in microtiter plates. We demonstrate that the behaviors of simple devices can be characterized dynamically and used to predict the behaviors of more complex circuits. Specifically, we compose 23 biological parts into 9 devices and use them to design 9 synthetic gene circuits in E. coli that provide core functionality for engineering cell behavior at the population level, including relays, receivers and a degrader. We embody our method in a software package and corresponding programming language. Our method supports the notion of an inference graph for iterative inference of models as new circuits are constructed, without the need to infer all models from scratch, and lays the foundation for characterizing large libraries of synthetic gene circuits in a scalable manner.

synthetic biology↗

Distributed DNA-based Communication in Populations of Synthetic Protocells

Developing distributed communication platforms based on orthogonal molecular communication channels is a crucial step towards engineering artificial multicellular systems. Here, we present a general and scalable platform entitled Biomolecular Implementation of Protocellular Communication (BIO-PC) to engineer distributed multichannel molecular communication between populations of non-lipid semipermeable microcapsules. Our method leverages the modularity and scalability of enzyme-free DNA strand-displacement circuits to develop protocellular consortia that can sense, process and respond to DNA-based messages. We engineer a rich variety of biochemical communication devices capable of cascaded amplification, bidirectional communication and distributed computational operations. Encapsulating DNA strand-displacement circuits further allows their use in concentrated serum where non-compartmentalized DNA circuits cannot operate. BIO-PC enables reliable execution of distributed DNA-based molecular programs in biologically relevant environments and opens new directions in DNA computing and minimal cell technology.

synthetic biology↗

A theory for how the antigen presentation profile influences the timing of T-cell detection

T-cells are activated when their receptor molecules recognize complexes of MHC proteins bound to peptides on the surface of neighbouring cells. Each T-cell expresses one variant of many possible receptor molecules, which are generated through a partially random process that culminates in approximately 107 possible T-cell receptors. As the peptide sequence bound to an MHC molecule is also highly variable, the optimal strategy of an antigen-presenting cell for displaying peptide-MHC complexes is not obvious. A natural compromise arises between aggressive peptide filtering, displaying a few peptides with high stability MHC binding in high abundance and regularity, and promiscuous peptide binding, which can result in more diverse peptides being presented, but in lower abundance. To study this compromise, we have combined a model of MHC class I peptide filtering with a simple probabilistic description of the interactions between antigen presenting cells (APCs) and cytotoxic Tcells (CTLs). By asking how long it takes, on average, for an APC to encounter a circulating CTL that recognises one of the peptides being presented by its MHC molecules, we found that there often exists an optimal degree of peptide filtering, which minimises this expected time until first encounter. The optimal degree of filtering is often in the range of values that the chaperone molecule tapasin confers on peptide selection, but varies between MHC class I molecules that have different peptide binding properties. Our model-based analysis therefore helps to understand how variations in the antigen presentation profile might be exploited for vaccine design or immunotherapies.

immunology↗

Model reduction permits Turing instability analysis of arbitrary reaction-diffusion models

Synthesising a genetic network which generates stable Turing patterns is one of the great challenges of synthetic biology, but a significant obstacle is the disconnect between the mathematical theory and the biological reality. Current mathematical understanding of patterning is typically restricted to systems of 2 or 3 chemical species, for which equations are tractable, but plausible genetic networks typically consist of dozens of interacting species. In this article, we suggest a method for reducing large biochemical systems to systems with 2 or 3 species which can then be studied analytically. We provide conditions to guarantee that the full system forms patterns if the reduced system does, and vice-versa. We confirm our technique with 3 examples: the Brusselator, an example proposed by Turing, and a biochemically plausible patterning system consisting of 17 species. These examples show that our method significantly simplifies the study of pattern formation in large systems.

synthetic biology↗

Predicting DNA Hybridization Kinetics from Sequence

Hybridization is a key molecular process in biology and biotechnology, but to date there is no predictive model for accurately determining hybridization rate constants based on sequence information. To approach this problem systematically, we first performed 210 fluorescence kinetics experiments to observe the hybridization kinetics of 100 different DNA target and probe pairs (subsequences of the CYCS and VEGF genes) at temperatures ranging from 28 {degrees}C to 55 {degrees}C. Next, we rationally designed 38 features computable based on sequence, each feature individually correlated with hybridization kinetics. These features are used in our implementation of a weighted neighbor voting (WNV) algorithm, in which the hybridization rate constant of an unknown sequence is predicted based on similarity reactions with known rate constants (a.k.a. labeled instances). Automated feature selection and weighting optimization resulted in a final 6-feature WNV model, which can predict hybridization rate constants of new sequences to within a factor of 2 with {approx}74% accuracy and within a factor of 3 with {approx}92% accuracy, based on leave-one-out cross-validation. Predictive understanding of hybridization kinetics allows more efficient design of nucleic acid probes, for example in allowing sparse hybrid-capture panels to more quickly and economically enrich desired regions from genomic DNA.

biophysics↗

A Spatially Localized Architecture for Fast and Modular Computation at the Molecular Scale

Cells use spatial constraints to control and accelerate the flow of information in enzyme cascades and signaling networks. Here we show that spatial organization can be a similarly powerful design principle for overcoming limitations of speed and modularity in engineered molecular circuits. We create logic gates and signal transmission lines by spatially arranging reactive DNA hairpins on a DNA origami. Signal propagation is demonstrated across transmission lines of different lengths and orientations, and logic gates are modularly combined into circuits that establish the universality of our approach. Because reactions preferentially occur between neighbors, identical DNA hairpins can be reused across circuits. Colocalization of circuit elements decreases computation time from hours to minutes compared to circuits with diffusible components. Detailed computational models enable predictive circuit design. We anticipate that our approach will motivate the use of spatial constraints in molecular engineering more broadly, bringing embedded molecular control circuits closer to applications.

synthetic biology↗