This year, in order to realize the basic idea of LAMPS, the ShanghaiTech-China team closely combined molecular modeling and neural network system to optimize the design of proteins. At the same time, the effectiveness of the entire set of protein engineering was verified through experiments.

At the same time, we successfully proved through experiments the great role of the LuxFG sequence in the Lux luciferase luminescence system, and designed it into our genetic circuit for future team use and reference.

For the cyanobacteria chassis, we developed new and simpler recombination schemes and recombination sites.

At the same time, the rhythmic promoter PkaiBC, which utilizes the internal rhythm of cyanobacteria, was constructed into the gene circuit and verified by modeling.

Finally, we designed a more complete detection system that can be extended to all microbial fermentation applications.

To make the bacterial LuxCDABE fluorescence system brighter and more useful for practical applications, we utilized biofluorescence resonance energy transfer (BRET) to increase its brightness and alter its color. ^[1] We created a new fusion fluorescent protein called LuxB:cp157Venus by attaching the yellow fluorescent protein cp157Venus to the C-terminal of LuxB using a linker (Glu-Leu). Since the emission spectrum of the LuxA-LuxB complex overlaps with that of the excitation spectrum of cp157Venus to a certain extent, when the two are close enough to each other (≤10 nm), the LuxA-LuxB complex in the excited state is able to undergo dipole-dipole resonance with cp157Venus, transferring its own energy to the latter in a non-radiative manner, causing the latter to emit light with different frequencies and amplitudes. Since the efficiency of BRET is related to the sixth power of the distance between the two only when the distance between the fluorescence donor and the fluorescence acceptor is appropriate, it is able to change the wavelength of the light while significantly increasing the brightness. We constructed two plasmids, pET-28a_lacO-LuxA-LuxB, and pET-28a_lacO-LuxA-LuxB:cp157Venus, and transfected them into BL21(DE3) strain after plasmid amplification by DH5`\alpha` strain, cultured at 37℃ and induced expression at 24℃. E. coli transfected with pET-28a_lacO-LuxA-LuxB successfully luminesced, but E. coli with the fusion protein LuxB:cp157Venus did not luminesce due to mutations in the target gene.

Since expressing LuxB:cp157Vunes is just to verify the BRET principle, and our ultimate goal is to find brighter fluorescent proteins after passing BRET, we first skipped this step and turned to directly find or create brighter fluorescent proteins after BRET. We first queried and screened the FPbase database for the two brightest proteins with fluorescence data and excitation light between 490-520 nm and named them A1, A2. For the proteins with only amino acid sequences but no fluorescence data, we first trained the Long Short-Term Memory (LSTM) system with the existing proteins with complete information, constructed the mapping from amino acid sequences to fluorescence data, and then applied the system to predict the fluorescence intensity of the proteins with only amino acid sequences, and screened out the brightest two named B1, B2 from them.

Computer model employed molecular dynamics simulations with Python and GROMACS to model and analyze the luminescence efficiency within experimental BRET systems. System preparation, molecular structure acquisition, and GROMACS formatting were followed by simulation setup, energy minimization, and equilibration. Subsequent production runs captured BRET system dynamics, while Python scripts processed trajectory data for key parameters, enabling the calculation of BRET efficiency. These simulations provided insights into donor-acceptor interactions, distances, and orientations, shedding light on the dynamic nature of BRET under various conditions. This integrated approach enhances our understanding of molecular interactions in biological systems and holds promise for diverse research applications.

To conduct molecular dynamics simulations, we need the corresponding pdb format file for each sequence under investigation. Therefore, we use AlphaFold 2 for protein structure prediction.

Here are the structures of four sequences that are tested in the lab.

In addition, the laboratory's verification of the A and B series sequences has obtained positive results. The new fluorescent protein sequence can indeed change the spectrum and enhance visual luminescence.

The spectrum of LuxCDABEGF fused with A1

The spectrum of LuxCDABEGF fused with A2

The spectrum of LuxCDABEGF fused with B1

The spectrum of LuxCDABEGF fused with B2

We are encouraged by the success of our experiments in generating recommendation sequences.We used the Generative Adversarial Network to generate the amino acid sequences of the candidate fluorescent proteins, and then used the LSTM system to filter the generated sequences, and finally obtained the two brightest fluorescent proteins and named them as C1 and C2. Since the effectiveness of the LSTM system has been proved in the previous experiments, the fluorescent proteins of C1 and C2 have been created with a certain degree of credibility.In related molecular modeling, C series sequences still perform well.

We hope that the LAMPS system will be brighter, so we carried out a basic metabolic upgrade design and verified that the LuxFG sequence can indeed effectively increase the luminous intensity, which can be used as a basic enhancement part for future use of LuxCDABE.

To enhance energy reserves and increase the carbon flux in cyanobacteria for the expression of luciferase genes, we have employed the Hfq companion protein and siRNA to silence the expression of the glgc gene, which encodes D-glucose-6-phosphate translocase. This blocks the conversion of glucose-6-phosphate into ADP-glucose, preventing further synthesis into glycogen, thereby reducing glycogen content and increasing sucrose production.

We want to let LAMPS play a similar function as a "biological clock", using the internal molecular oscillation signals of cyanobacteria to control LAMPS cells to store photosynthetic energy during the day and release oxidative energy at night. Therefore, we synthesized and constructed a sequence with a rhythmic promoter and recombined it into the PCC7942 chassis, and modeled and verified its signal. From this, we have given a set of time signal output circuits that can run in the algae carbon-negative chassis. Through future applications and expression intensity adjustments, this system is expected to output all desirable periodic signals for use by future iGEMers.

constructed plasmid pUC57_NS3-2-PKaiBC-sfGFP-lacI-KanR-NS3-1.

Basic logic of LAMPS rhythm control system

ODE-based modeling results

We predict that one of the main applications of LAMPS in the future will be in urban landscaping. Sustainability and economy are advantages that must be maintained. However, in view of the instability of organisms themselves, we need a device that can detect the steady state and fermentation effect of the system on the one hand. This equipment needs to be easy to use by ordinary gardeners with no experience in biological experiments, but at the same time it should not be too expensive. Therefore, we use spectral sensors and PCBs to perform timely detection through hardware design.

This equipment will also be useful in future fermentation production and other applications. The stability and effect of biological systems can be understood more quickly and conveniently in non-standard fermentation equipment.

In interviews with investors, experts and professors, we realized that the safety of fermentation in environments outside the laboratory is very important. We also designed the suicide switch for the cyanobacteria chassis. Based on the difference in chemical composition between the culture medium and the external environment, leakage can be easily prevented. This also provides security for future teams to fully unleash their creativity.