Team:Edinburgh/Description


Team Edinburgh Finding NEMO

overview

The overall project goal is to design a cell-free and transcription only biosensing platform. The development of a transcription only platform would overcome many of the limitations of cell-based, and even cell-free translational biosensors. Firstly, ribosomal translation is known to be the major rate-limiting factor in protein (readable output) production. Transcription only systems are able to subvert this limitation and therefore are able to provide much shorter response times. Additionally, the use of a transcription only system would provide much the same benefits of a conventional cell-free system in regards to safety. The fact that no live cells are required for operation complies with regulations concerning the use of live genetically modified organisms in field-applications. Moreover, transcription only systems further minimise risk by eliminating any potential risk for toxic protein production. A benefit unique to a transcription only system is its simplicity. Requiring little more than oligonucleotides and polymerase for base function, such a system raises little to no concern in regard to possible toxic substrates or products. Furthermore, the simplicity of the system grants it much improved accessibility. Constructing the base function demands no more than what is commercially and cheaply available to all – synthetic oligonucleotides and T7RNAP.


To achieve a transcription only system we take example from the literature [1][2] in using novel fluorescent aptamers, as opposed to conventional GFP, for readable output. We researched, designed, experimented and optimised the transcription conditions to achieve a reliable fluorescence response. While the development of a transcription only platform is the foundation of our framework, we additionally invested a large amount of effort into expanding the capabilities of our proposed system. The framework below illustrates the breadth of capacities that we have researched and explored to achieve this wider capability. Our system not only explores the integration of three separate sensing mechanisms (transcription factors, riboswitches and direct oligonucleotide sensing) but additionally incorporates an inherent logic processing and signal amplification capacity.


Cell-based vs Cell-free


Cell-free technology is a relatively recent advance which provides great potential for synthetic biology. Most cell-free systems are lysate-based, meaning they are produced by mixing original cell extracts with additional components and buffers. The simplicity of these systems, as well as their ease of manipulation pairs well with the Design - Build - Test ethos, and has been applied to many areas of synthetic biology - particularly in the field of biosensors. Traditional cell-based biosensors typically perform vey well, offering multiple benefits when contrasted to traditional instrument based analytical chemistry such as high performance liquid chromatography (HPLC) and gas-chromatography (GC) - biosensors are generally less costly, faster, easier to operate and capable of real time identification [3]. However, cell based biosensors suffer from numerous inherent performance limitations: variability due to growth-related responsivity, issues with membrane permeability, susceptibility to toxicity, use of live GMO's, difficulty of manipulation and laborious cloning and transformation procedures.In this case, the use of cell-free technology conveniently eliminates most of the major drawbacks of cell based biosensors, making it an ideal format. A cell free solution contains no live cells, therefore no risk of releasing live GMO's, no obstructive membrane barriers, and vastly reduced susceptibility to toxicity. These solutions also require no laborious cloning and transformation procedures and in the complete solution final component concentrations can be easily and accurately calibrated.



Cell based Biosensors
  • Requires laborious cloning and transformation
  • GMO hosts pose potential risk to the environment
  • Variability due to growth-dependance
  • Susceptible to toxicity
  • Cell wall/membrane permeability limits response time
  • Difficult to calibrate component concentrations

Cell-free Biosensors
  • Genes can be cloned separately, or simple linear DNA and PCR products can be used
  • No requirement for live GMO's, so no risk to the environment
  • No growth-dependant variability
  • Resistant to toxicity
  • No permeability restrictions
  • Component concentrations can be calibrated on-demand



Fluorescent aptamers


Fluorescent aptamers are short RNA sequences – typically in the range of 30-100 nt - which form complexes with otherwise weak fluorophores in solution and amplify fluorescence several thousandfolds. It is through the use of these fluorescent aptamers, as an alternative to conventionally used GFP, that the system is able to operate through transcription only. Their application as signal output in transcription only systems has been investigated and they are able to generate potent fluorescent signals in similar transcription only systems. Furthermore, by avoiding ribosomal translation and subsequent protein folding, fluorescent RNA’s benefit from significantly reduced readout times (5 min). Finally, the availability of multiple aptamers producing visibly different colours presents a further opportunity for output multiplexing – as well as more complex functionalities such as FRET and quenching



Transcription factors

Integration of transcription factors (TF) is relatively simple, requiring only that transcripts downstream of the responsive promoter are designed to produce a fluorescent aptamer output directly, or so that their resulting 3’ ends act as primer to the bubble construct for downstream processing. Work has been done in cataloguing a large range of previously characterised responsive transcription factors for biosensing. Further investigation has also been conducted in broadening detection limits (through various genome/chemical based TF searching methods and transcription factor engineering) as well as system optimisations.





Riboswitches

Integration of riboswitches becomes more difficult as the majority are translational as opposed to transcriptional regulators. Thus, a major degree of the work done in this area has been centred around isolating the small number of cases where ribozymes act on transcription. The principles of action in these transcriptional riboswitches are being investigated to determine whether it may be possible (along with novel developments in ribozyme computational design) to design and integrate more transcriptional riboswitches into the proposed system.



Synthetic transcription bubble

The synthetic transcription bubble was devised by adapting previous work from the 1980s on T7 RNAP in-vitro transcription, with a more contemporary understanding of T7 RNAP structure and function relationships. It’s role, to provide the backbone for our integrated amplification and rudimentary logic processing system. The synthetic transcription bubble is formed simply by two partially complemented DNA strands – having a mismatch bubble placed between two flanking complementarity regions both upstream and downstream. Studies have shown that the binding of a short RNA primer to this mismatch region is sufficient to elicit complete and processive transcription of downstream elements – as the disposition of nucleotides mimics that found in a T7 RNAP elongation complex. Such a construct would allow any short RNA to act as a transducer for desired output production – as opposed to indiscriminate promoter-mediated initiation. This model provided a great opportunity, as the flexibility of downstream transcription allowed for a large amount of freedom in dictating output in a transcription-only system. Furthermore, T7 RNAP is an ideal candidate for such applications. First and foremost, T7 RNAP operates a very high rate and efficiency of transcription (in contrast to E.coli RNAP)[18]. This fulfills the “fast response” design ideal as prior described. Secondly, T7 RNAP is known to have a very high degree of specificity to the T7 RNAP promoter [17] (besides the exceptional circumstance described herein) – therefore the chance for aberrant transcription is minimized. This specificity will conveniently ensure the fidelity of any sensing mechanism. The third, T7 RNAP requires no co-factors for efficient and processive transcription [16], therefore adding no superfluous complexity to what is intended to be a minimal system. Finally, T7 RNAP is a small and simple polymerase and is available cheaply commercially – therefore facilitating accessibility to constructing such a system.