Wetlab
To enable batch-screening, we need a convenient reporter system with a signal identifiable with the human eye. To this end, we construct a standard green fluorescent protein (GFP) promoter-reporter system, as shown below, using Golden Gate Assembly.
It is to the consensus that the -35 and -10 boxes, the binding sites of the sigma70 factor during transcription, play a major role determining the strength of the respective promoter. Previous iGEM researchers employed saturation mutagenesis on the two regions and generated the J23119 family promoters. Among these promoters with different strengths, they concluded that J23119 from the family was the strongest [1]. Building upon this discovery, we leave the -35 and –10 consensus sequences identical to J23119 and utilize saturation mutagenesis via Golden Gate Assembly to generate randomized sequences on the sequential context surrounding the sigma factor recognition site, as shown below. This new construct is named pP6, with its design allowing us to explore strong constitutive promoters with a larger diversity in their gene sequence. Meanwhile, our hope was that altering sequential context would yield constitutive promoters even stronger than J23119.
The N-repeat randomized sequence is incorporated into the targeted site by polymerase chain reaction (PCR) with primers ordered from IDT (their oligonucleotide synthesis instrument interprets ‘N’ as an equal mixture of all four bases). We thus get a library of promoters with dramatically varying strengths for characterization.
Upon transformation and plating, we proceed with the brightest colonies, like the ones highlighted below, to isolate plasmid DNA and submit for sequencing.
For successful constructs proven by sequencing, we retransform and measure GFP signal, excited using 483 nm, at 525 nm wavelength with Tecan reader for later significance tests.
[1] http://parts.igem.org/Part:BBa_J23119
Computational Biology
In the CheRMiT notebook, students were guided through the initial setup of the cheminformatics segment of our project, which focuses on verifying if a found set of reactants and products from a sentence is actually capable of having a reaction occur between them based on cheminformatics software. Students were walked through a new cheminformatics library, RDKit, to pivot away from old Java-based libraries that the team no longer wished to use. They were then instructed to program their own reaction validator, which could apply a reaction operator (an abstract chemical operator that can take in a chemical and apply the modifications to the reactant that represent the reaction taking place, and output the modified chemicals, or the product of the reaction).
Upon outlining their code and programming an initial approach, they could then test their implementation by passing a candidate set of reactant-product pairs, as well as a canonical list of reaction operators; students were able to test their implementations and refine these implementations to improve recall, while also identifying concerns with missed reactions or the limitations of the chemical processing functionality that would be useful to address in downstream, mature software development for the project. This holistic validation and varied student approaches invited a wealth of analyses that ended up accelerating the development of the cheminformatics validation software for the project this semester, to the point where a more advanced infrastructure has been rewritten, fleshed out, and is now in the process of getting thoroughly benchmarked based on inputs from language model outputs.
