Wednesday 19 October 2022

Novel techniques in synthetic biology: ultrasound, CRISPR and more

 Ultrasensitive ultrasound imaging of gene expression with signal unmixing

Acoustic reporter genes (ARGs) that encode air-filled gas vesicles enable ultrasound-based imaging of gene expression in genetically modified bacteria and mammalian cells, facilitating the study of cellular function in deep tissues. Despite the promise of this technology for biological research and potential clinical applications, the sensitivity with which ARG-expressing cells can be visualized is currently limited. They present BURST, a method that improves the cellular detection limit by more than 1,000-fold compared to conventional methods. BURST takes advantage of the unique temporal signal pattern produced by gas vesicles as they collapse under acoustic pressure above a threshold defined by the ARG. BURST can detect ultrasound signals from individual bacteria and mammalian cells, enabling quantitative single-cell imaging.

https://www.nature.com/articles/s41592-021-01229-w

Dynamic modulation of enzyme activity by synthetic CRISPR-Cas6 endonucleases

RNA-scaffolds can increase flux through a given metabolic pathway by keeping the pathway’s enzymes in close proximity to increase the local concentration of pathway intermediates. Here, RNA scaffolds are built using the crRNA-Cas6 system: enzymes of interest are fused to Cas6, which in turn binds a specific loop of RNA. By engineering complementarity into the RNA sequence upstream of the Cas6-bound loop, the RNA scaffold assembles by RNA:RNA hybridisation. The authors can then use other input RNA strands to trigger the assembly and disassembly of the scaffold through TSMD reactions. With this method, the authors demonstrate controllable scaffold assembly, break-down and cycles of assembly/disassembly in vivo.

Dynamic modulation of enzyme activity by synthetic CRISPR–Cas6 endonucleases | Nature Chemical Biology

A domain-level DNA strand displacement reaction enumerator allowing arbitrary non-pseudoknotted secondary structures

Domain-level DNA strand displacement crn simulators. I've read up on visualDSD and peppercorn enumerator. The aim of these computational models is to 1) enumerate WC bonded domain level complexes which could from when designing DNA strand displacement circuits, 2) to use approximate the kinetics of the systems and 3) simulate them so that mechanisms can be inspected and designs can be updated to yield desired results, perhaps by inspection or by algorithmic approaches. Classic visual DSD (https://ph1ll1ps.github.io/visualdsd/index.html) could describe only a very limited set of toehold mediated strand displacement and other binding mechanisms. More recently visualDSD has been converted to use "logic dsd" semantics (https://pubs.acs.org/doi/pdf/10.1021/acssynbio.8b00229) which can describe a very wide range of customizable reactions, including DNA strand displacements and enzymatic reactions such as ligation and cleaving. It is unclear where to find and how to use the logicDSD version, as the link provided in the paper no longer works. Classic visualDSD is incapable of simulating the remote toehold used in handhold mediated strand displacement.

Peppercorn enumeration does biomolecular binding interactions and a multitude of intramolecular reactions for non pseudoknotted secondary structured DNA complexes (where kinetics and thermodynamics are well characterised).

Approximate rates for each type of reaction based upon domain lengths can be generated within the software. Once the complexes have been enumerated and the rates of each reaction have been estimated, a CRN can be constructed. The combinatorics of enumerating all possible domain-level complexes can be challenging as the number of complexes may explode with increasing number of domains. Therefore the software has built-in coarse-graining methods based upon timescale separation. Simulation can be separated into fast and slow reactions. Unimolecular reactions may be fast, slow or negligible and bimolecular reactions are slow (which is valid for low concentrations < 10nM, uni-rates go as conc^1 and bi-rates go as conc^2). A "condensed" CRN which features fewer species can be constructed on the basis of timescale separation that has the same slow dynamics as the original CRN but can be simulated more easily. Care must be taken in cases in which sequential bimolecular reactions are required, as if all unimolecular reactions are assumed to be fast compared to biomolecular reactions, the subsequent bimolecular reaction may never occur in the condensed CRN. No net production or degradation reactions allowed in peppercorn, and therefore all strands are conserved. Toeholds less than 7 nt by default are reversible. Branch migrations are irreversible. Zero-toehold branch migrations aren't included. peppercorn would be capable of simulating hmsd, but this would require the implementation of custom reactions and custom rates.

https://doi.org/10.1098/RSIF.2019.0866

Molecular filters for noise reduction

In classical signal processing a filter takes an input signal and produces an output signal with reduced noise. This paper investigates three classes of bimolecular chemical reaction networks (CRNs) that act as filters by producing a new output chemical that tracks the input chemical but with reduced noise. One critical difference between classical filters and CRN filters is that CRNs have intrinsic noise associated with the stochastic firing of reactions as well as noise in the input signal, where as classical filters only have noise in the input signal.

The first class of CRNs that are analysed are the linear filters, the paper shows through classical frequency domain analysis that linear filters have the same transfer function as the low-pass filter. Low-pass filters attenuate high-frequency oscillations while preserving the low-frequency ones. They show that the output signal of linear filters are limited by the Poisson’s level, a lower bound on the variance of your output signal that is at minimum the mean of the output signal.

They then go onto to investigate the annihilation module which includes complex formation reactions. They show that this can reduce the noise of the output to below the Poisson’s level. They then introduce the annihilation filter which is similar to the annihilation module except that the mean of the output signal is proportional to the mean of the input signal.

Finally they suggest that the translation and transcription of mRNA to produce proteins can be seen as two cascading linear filters and that certain microRNA pathways might be annihilation filters.

Molecular filters for noise reduction

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