Team:Hong Kong HKU/wetlabreview



Past iGEM teams

Team Microbial Consortium Regulation Project Methods
2012 Buenos_Aires Tunable Synthetic Ecology Metabolic Intermediate
2013 Braunschweig Engineering a Synthetic Microbial Consortium QS system Antibiotic (Kill)
2014 Edinburg RewirED: Introducing a new intercellular signalling mechanism based on metabolic pathways - Metabolic Wiring Metabolic Intermediate
2015 MIT Microbial Consortia Engineering for Consolidated Bioprocessing QS system Toxin (Kill)
2016 Imperial_College Ecolibrium: developing a framework for engineering co-cultures. QS system
Growth Retardation (Slow)
2018 Waterloo E. co-light : Dynamic Optogenetic Control of Co-cultures Optogenetic
Growth Retardation (Slow)
2018 Duesseldorf Towards an Engineered Co-culture Toolbox QS system (Kill)
Metabolic Intermediate (sub-project)
2019 SDU_Chiina Optogenetic control of microbial consortium Optogenetic
Quorum Sensing (QS) system
Toxin (Kill)

Team Inversion Related Project Methods
Missouri Western State University 2006 Solving the Pancake Problem with an E. coli Computer Hin Recombinase
Davidson Missouri W 2007 Solving the Hamiltonian Path Problem in vivo Hin Recombinase
2020 HKU Beyond Unicellular: Recombinase circuits to develop monoculture phenotypic heterogeneity with precise ratiometric control Lambda Red
Recombinase Circuits (Switch)
crRNA array with CMR or Cas13

What if… we could achieve population control without any intercellular communication.

Natural diversity, recombinase systems

Recombinases are enzymes that facilitate mobile DNA recombination events. Which means it allows DNA to be excised, interchanged, inverted with specific recognition sites.

In general, recombinases could be separated into tyrosine and serine recombinases.
They are used in nature to generate population diversity. Like the use of Hin gene for flagella on/off random expression in Salmonella for virulence, immune escape[1].
In nature, there are two ways to generate diversity[2], one is based on sensing and induction. Another way is to use random expressions like Hin mediated circuits in Salmonella.

On the left, we could see one mode of induced diversity, which for example is the mediation and expression of flagella expression under stress. Which mediates locomotion and hence escape to better environment. The unfit was screened out but the whole population prevails.
On the right, which is also the idea of our project design, is the allocation of work throughout the population. The differentiated bacteria may have lower growth rate when performing tasks like forming biofilms, but the other would proliferate and sustain the population. In our project, we allocate tasks randomly, also taking considerations in the growth rate and metabolic burden, in order to allow the proper ratio control of the sub-populations.

Detrimental problem of cre-loxP systems

Brainbow system

Brainbow[3] highlighs the use of cre-loxP to generate phenotypic heterogeneity in neuron cells. However, the difference is the cre-loxP system in this case is used for a non-dividing cell which is the neuron cells. And a random shuffling could only occur once due to the use of deletion based circuits. Brainbow2.0 utilizes inversion only circuits.
In natural science research, cre-loxP is mostly used in generating conditional knock-out mouse models. Like generating transgenic mice with organ specific knock-out, or temporal knockout of essential gene using inducers like tamoxifen or tetracycline. However, most cre-loxP system is used for deletions like the FLEX switches. And these expression are mostly in a very short time-frame with high level of cre expression. Cre-lox is also well known for its off-target effects.

Why do we still choose it

There is not much research in Cre for long term usage. Which is due to its fast loss of function due to genomic targeting. However, with a publication by Dr. Eroshenko[4], who created a mutant cre enzyme that can catalyse inversion in long time frame in vivo, which he also mentioned that the cre mutant could be used in inversion only synthetic biology circuits. That’s why we hope to give it a shot.
Despite early experimental results were not promising, we still hope to adjust different parameters and find out the optimal expression level (in correlation to the lox copy number in cell) for our purpose. However, as a backup plan, we also designed gene circuits with the invertase Hin, with E.coli codon optimized versions. With other Serine recombinases also available from our purchase with human (similar with yeast) and e. coli codon optimized, we can try to develop toolkits for our own purposes.

Recombinases to be used in our project

Recombinases Type Property Cassette Organism
Cre (Mutants) Tyrosine Recombinases Symmetric. Random flipping if no extra regulatory module. Prokaryotes, Eukaryotes
Bxb1 excisionase Serine Recombinases Asymmetric, directional flipping. Requires Bxb1 Integrase for reversal of flipping events. Prokaryotes, Eukaryotes
(with nuclear import signal)
phiC31 Serine Recombinases Integration of attB-attP pair to genome landing spots. Prokaryotes, Eukaryotes
(with nuclear import signal)
Hin, Fin, Gin Serine Invertase Symmetric, Random flipping. Requires bacteria cofactors. Bacteria.

Why not use quorum sensing module? As illustrated from an review article [5], there has been a lot of development with quorum sensing modules. However, these circuits may or may not apply to most of the gene circuits and have need to optimize. In industrial settings, these things are often not necessary and deemed too troublesome, which most industrial application in the synbio era is still using mono-cultures with single strain of cells. We will come into play with offering the ease of maintaining a mono-culture, but generating functionality of a mixed culture.

Recombinase Researches and Memory gene circuits

There has been recombinase researches using various serine and tyrosine recombinases for various purposes. Mostly are for genetic memory [6-9], some for genetic state machine[10] and logic gates[11]. Most of these recent researches were big publications on Nature, which indicates the rise and innovation for recombinase gene circuits. Most of these papers utilizes serine recombinase systems (phiC31, Bxb1), and only some utilizes tyrosine recombinases like Cre-lox, Flp-frt. Tyrosine systems like Cre-lox does not offer as much control as much as other serine recombinase. However, since our project looks towards introducing randomness into a gene system, we build and test these devices with symmetric rotations and without much regulations. Another system to look at is the Hin recombinase, which is a natural invertase. However, with Hin recombinase needing bacterial cofactors for its action, it is not applicable or does not have tools which allows the eukaryotic usage.
Beside logic synthesis and genetic memory, we believe recombinase is also a method to introduce desynchronization and phenotypic variation in a bacterial system. Therefore, we are striving to use an old method, to tackle a new problem.


1. Bonifield HR, Hughes KT. Flagellar phase variation in Salmonella enterica is mediated by a posttranscriptional control mechanism. Journal of bacteriology. 2003 Jun 15;185(12):3567-74. .
2. Ackermann M. A functional perspective on phenotypic heterogeneity in microorganisms. Nature Reviews Microbiology. 2015 Aug;13(8):497-508.
3. Livet, J., et al., Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature, 2007. 450(7166): p. 56-62.
4. Eroshenko, N. and G.M. Church, Mutants of Cre recombinase with improved accuracy. Nat Commun, 2013. 4: p. 2509.
5. Stephens K, Bentley WE. Synthetic Biology for Manipulating Quorum Sensing in Microbial Consortia. Trends in Microbiology. 2020 Apr 24.
6. Farzadfard, F. and T.K. Lu, Genomically encoded analog memory with precise in vivo DNA writing in living cell populations. Science, 2014. 346(6211).
7. Friedland, A.E., et al., Synthetic Gene Networks That Count. Science, 2009. 324(5931): p. 1199-1202.
8. Sheth, R.U. and H.H. Wang, DNA-based memory devices for recording cellular events. Nature Reviews Genetics, 2018. 19(11): p. 718-732.
9. Yang, L., et al., Permanent genetic memory with> 1-byte capacity. Nature methods, 2014. 11(12): p. 1261-1266.
10. Roquet, N., et al., Synthetic recombinase-based state machines in living cells. Science, 2016. 353(6297).
11. Chiu, T.-Y. and J.-H.R. Jiang, Logic synthesis of recombinase-based genetic circuits. Scientific reports, 2017. 7(1): p. 1-13.