Results

Attempt to build the split RNAP

We initially chose a blue-light-controlled sensor as candidate. The sensor, opto T7 RNA polymerase is a pair of fusion proteins which initiates transcription of P_T7 by dimerize when exposed to light 450 nm. nMag is fused with the CT (carbon terminal)^[1] of T7RNAP and pMag is fused with NT (nitrogen terminal). Due to the toxicity of the part, the expression of both the two fusion proteins are induced by L-arabinose^[2]. And we set a concentration gradient to explore the optimized condition.

1. Characterization of sensor opto T7 RNAP

We inserted the sfGFP after the P_T7 to characterize the behavior of the blue light sensor. The experimental result shows no significant induction compared with the dark control.

2.Validation at protein level

To verify the expression of the sensors, whose MWs are 53.9kD and 78.5kD respectively. We tested the sample containing sensor induced by 0, 0.1%, 0.2%, 0.5% arabinose and empty vector. The SDS-PAGE result shows no significant existence of the sensors.

Characterization of CcaS/CcaR system

The CcaS protein acts as a light sensing part in CcaS/CcaR two-component system (TCS). CcaS consists of an N-terminal transmembrane helix; a GAF domain, which serves as the sensor domain; a linker region (L1); two PAS domains; a second linker region (L2); and a C-terminal histidine kinase (HK) domain. We were inspired by Professor Koji’s work^[3] to remove the L1 linker region and the two PAS domains, then fuse the GAF and HK domains with a truncated linker region.

Our advanced system was characterized over wild type in M9 medium with glycerol but without yeast extract. The fluorescence intensity was acquired 9 hours after inoculated into 24-well plate with Abs600 about 0.1. Our culture was exposed to different light to characterize different transcription level. The basic OD and fluorescence were wiped off. (n=3)

The dynamic ranges of green over red light of different system are: 2.8(wild type), 2.7(#3), 4.9(#10). The #4 has the reverse function and the dynamic range is about 1.5.

The construction of the metabolic flux regulation platform.

We selected type I-E CRISPRi system as the cut-over dynamically switching the metabolic flux. Type I-E CRISPRi system can inhibit the aimed gene’s transcription through expressing crRNA combining endogenous Cas protein.

1. Characterization of type-I-E CRISPRi system

To remove the DNA degradation function and maintain the DNA binding function of the modified type I-E CRISPR system, a special E.coli TOP10 with Cas3 protein knocked out and promoter of Cascade substituted by promoter J23119 was constructed and named EE-E15. To verify the system in EE-E15, the GFP gene was chosen as a reporter to test the function of crRNA targeting different sites of GFP[4]. The results showed that there were wide rages of repression among different sites and the spacer posited on the promotor region presented high repression level (82%).

TCA cycle is one of the most significant metabolic pathways for energy supplement. The cycle starts with the process that citrate synthase catalyzes acetyl-coA and oxaloacetate to form citric, which is the rate-limiting step in the TCA cycle and irreversible, thus the regulation of expression of gltA which codes the citrate synthase may have great effect in central metabolism, and through model we also found that control of gltA can regulate the metabolic flux. We got the target site of gltA gene from previous work and then we constructed a plasmid containing crRNA targeting gltA to inhibit expression. With 0.2% L-arabinose induction, the samples showed an obvious repression on growth compared with the ones without L-arabinose (Figure 8.). furthermore, we investigated the regulatory effects of targeting gltA at different stages of growth by adding L-arabinose at 0h, 2.5h, 5h, 7.5h and 9h. As shown in the figure, there presented an obvious difference between different induced time, in which the strains added L-arabinose at the beginning had the strongest repression in growth while with the delay of the induction time, the effect of inhibiting growth was gradually weakened. It indicated that this system can inhibit TCA cycle through inducing crRNA targeting gltA at different time, thus it proved that our idea that dynamically regulating metabolic flux was feasible to some extent.

2. light-induced type I-E CRISPRi system

Further, we utilized CcaS/CcaR sensor with type I-E CRISPRi system to induction of crRNA targeting the site of gltA through switching light. To optimize this system, we chose different culture medium verifying the function of light-induced crRNA.

In the figures we can find that cell cultured with glycerol growth had a higher level of repression compared with glucose. It indicates that crRNA targeting gltA to inhibit TCA cycle from the first step showed a better effect when nutrition was not directly utilized. In addition, it illustrates that condition made sense for the function of our system. Meanwhile the phenomenon was analyzed through flux balance analysis (FBA) mathematical model. With the data we found there was a threshold when inhibiting gltA, exceeding which appears an obvious transform in metabolic flux. We analyzed that glycerol as carbon source can reduce this threshold showing great repression which was in accordance with the growth results described above. Then we chose M9 medium with 1% glycerol as the condition for the characterization of crRNA targeting gltA.

To optimize the expression of crRNAs in EE-E15, then we constructed a medium-copy plasmid (pSR43.6) and high-copy plasmid (phz) to express crRNA targeting endogenous gltA. The two strains showed significant variance in growth in figure 4, suggesting crRNA on high-copy plasmid showed stronger repression than on medium-copy one. We supposed that the inhibition function was related to the quantity of crRNA and light-sensing promotor PcpG2-172 works well in high-copy number, leading to this result. It indicated that copy-number for light-induced crRNA had a great impact on this photoactivated regulation system.

After the verification of the culture condition, we investigated the dynamic regulation effects of targeting gltA with light-controlled system through switching red light to green light at 2h, 5h and 9h. As shown in figure 5, all strains induced at different time grow better compared with illuminating at 0h. Bacteria growth was inhibited the most when being induced at 5h, showing an obvious palliation after sensing green light. The strains induced at the early-log phase (2h) grew slower than the control (upon red illumination), whereas it continuously grew and maintained a relatively high K value. It was supposed that cells growing at a moderate speed at early consumed less nutrition, thus drove the biomass constantly increase and had a higher level of K value. In accordance with the hypothesis, we concluded the negative control without crRNA targeting gltA which presented a lowest level of K value consumed too much nutrition so that it can’t satisfy the need of cell in late period of growth. In addition, inducing crRNA expression at 9h through green light, we found there were little growth variance between the strains green light induced at 9h and the control illuminated at red light continuously. It was supposed that at the stationary phase there was nearly no effect for inhibiting TCA cycle to repress the cell’s growth, which might due to its metabolic flow. The difference between the regulation effect of different induction time isn’t obvious through light switching compared with L-arabinose (figure 8.), might due to light sensor CcaS/CcaR system which only have 4.8-fold difference between red/green light induction.

We reconstructed EE-E15 driving its metabolic flux regulation at different time through switching red light to the green one. Then we made polyhydroxybutyrate(PHB) as an example to demonstrate our dynamically regulating metabolic flux platform.

PHB fermentation

PHB synthesis with CcaS/CcaR system

Firstly, in order to verify that phbCAB cluster could be expressed induced by CcaS/CcaR system and synthesize Polyhydroxybutyrate (PHB) successfully, phbCAB cluster (without its original constitutive promoter) was cloned right behind the light sensing promoter, PcpcG2-172 (Figure 12).

TAlso strain “PHB induced Red/Green” was illuminated with red light and green light respectively throughout the PHB fermentation while light illuminating “PHB induced 5h” was switched from red light to green light at 5h (exponential phase) so that we can tell whether turning on PHB synthesis pathway at different periods could affect PHB content within the cells and cell growth, as well.

Though green light is turned on at different fermentation periods, there is no distinguishable growing difference between "phb con + crRNA 0h/5h and 13.5h". And furthermore, a striking decrease on OD can be found among strains "phb con + crRNA" compared to negative control (“phb con”) (Figure 2.a). So it is considered that the expression of crRNA, even at a low leakage expressing level, has a significant detrimental impact on cell growth. However, cell growth is inhibited on almost the same level, in spite of high or low transcription level as no significant difference can be told among “phb con 0h/5h/13.5h/Red”. On the other hand, there is no distinguishable distinction of PHB content between "phb con + crRNA 0h/5h/13.5h" and "phb con", while "phb con + crRNA Red" produce only half as much PHB as the others (Figure 2.b). Hence, it seems that crRNA transcribed by CcaS/CcaA system under green light, cannot improve PHB content as we expected. And besides, surprisingly, the leaky expression of crRNA under red light decreases the PHB content inside the cells (Figure 2.b). This is probably because the impact of crRNA varies from different expression level. Combining the cell growth as well as the PHB production result discussed above, we can see clearly, "phb con" in fact produce more PHB than others (Figure 2.c).

Despite of the experiment above, we conducted another experiment meanwhile. In order to demonstrate our growth-production switching system, here, both phaCAD cluster and crRNA is expressed under CcaS/CcaA system (Figure 3.a, b). However, the plasmid engaged here has a slight difference from the one used in the former experiment---crRNA is expressed on a low-copy-number plasmid. This is because we were running out of and thus didn’t construct the high-copy-number plasmid. And what's worse, the data of "phb induced + crRNA 13.5h" and "phb induced 13.5h" was lost by mistakes.

Opposite to the first experiment, here we found out that the expression of crRNA actually contributes to the high cell density in "phb induced + crRNA 0h/5h" groups for the duration of PHB fermentation (Figure 4.a). This surprising result was completely to the opposite to our expectation, as crRNA was supposed to inhibit TCA pathway and thus, have a dramatically detrimental effect on cell growth. But to some extent, it was consistent to the part of the results of our former experiments. For the duration of crRNA characterization and PHB fermentation seed culturing, we did witness the tendency that in spite of being depressed by crRNA, E. coli will would grow slowly after entering the platform period and probably will grow better than the control in the long run (data not shown). With respect to PHB content, no significant difference could be told between "phb induced + crRNA 0h/5h" and "phb induced 0h/5h" (Figure 4.b), consistent to the first experiment. In addition, "phb induced + crRNA Red" containsed as much PHB content as "phb induced Red" (Figure 4.b). Thus, it appeared that crRNA expressed on low-copy-number plasmid had no impact on PHB production.

According to the PHB fermentation data, the effect of crRNA on both cell growth and PHB production is very complicated. From these two experiments, it appears that the specific impact of crRNA on cell growth has something to do with the expression level, generally, significant decrease in OD can only be seen in those groups expressing crRNA on a high-copy-number plasmid while an increase in OD is witnessed in those groups expressing crRNA on a high-copy-number plasmid. In addition, though the expression of crRNA on low or high-copy-number plasmid does not improve PHB production, the leaky expression of crRNA on high-copy-number plasmid somehow can be detrimental to PHB biosynthesis. So our growth-production switching system failed in the example of PHB fermentation as crRNA has a complicated impact on cell growth and cannot improve PHB content as we expected.

In the following days, we intend to use HPLC for analyzing the metabolic flux inside the cells, to clarify the impact of crRNA on metabolic flux. In addition, we may attempt to highly express crRNA, for the reason that based on the prediction made by modelling, PHB synthesis will be improved dramatically when gltA is inhibited by about 80 %. Under this condition, our growth-production switching system probably work very well. Also, since several catalytic steps are involved in order to transform acetyl-CoA into PHB, the metabolic flux may be complicated and thus reduce the effect of crRNA on metabolic flux redirection. Hence, we might also try some other easier examples. Like some biosynthesized material with less synthesis steps and simple metabolic flux to demonstrate the possibility of our system.