Team:HUBU-WUHAN/Design

PROJECT DESIGN

PROJECT DESIGN

Background:

Online shopping is becoming the major shopping method nowadays in China, like Amazon, Alibaba. Due to the fast growth of online retailing business in China, more than 165 billion express packages were delivered in one day. However，the recycling of these cartons is still a big problem. Last year, the iGEM team from Hubei University had accomplished the pathway from waste cartons to biofuels. Cartons were firstly smashed and treated with 3% sulfuric acid for 1.5 hours, and then hydrolyzed by liquid enzymes into fermentable glucose, which were lastly utilized by recombinant Zymomonas mobilis for isobutanol production. As the results shown, there are still some problems. The production by recombinant strains with the isobutanol module Peno-kdcA was only 147 mg/L. Moreover, exogenous cellulolytic enzymes were needed for enzymatic hydrolysis.

Apart from this, our human practices found that the plastic packages are widely used in our daily life and their delivery are also a critical source of pollution. Since traditional plastic bags will not be degraded for centuries, it will pollute soil, water and other environment. We read the literature and found bioplastic (Poly-β-hydroxybutyrate, PHB) has been successfully produced in Z. mobilis, so we intend to choose it as our bioproduct.

Which chassis to choose and why?

Z. mobilis is selected as the chassis strain because it is good for biofuel production and easy for molecular modification. Its advantages are as follows:

Figure 1. Advantages of Zymomonas mobilis

What is the solution?

Figure 2. Overview of project.

The step is converting waste cartons to fermentable glucose. To reduce the extra-enzyme addition, a new metabolic pathway is introduced into Z. mobilis to produce three types of cellulases, the

CBH (exoglucanase)

,

EG (endoglucanase)

and

BGL (beta glucanase)

. The plan is cellulases expression in Z. mobilis lead to the

Consolidated Bioprocessing

strains construction that can utilize cellulose directly without extra-enzyme addition.

Figure 3. Waste cartons to fermentable glucose by acid and enzyme treatments.

Figure 4. Design of cellulases plasmids construction.

The renewable bioproducts what wanted are biofuels and bioplastics. Z. mobilis mainly metabolizes glucose by Entner-Doudoroff pathway to produce ethanol. Last year team HUBU-Wuhan had accomplished the pathway from waste cartons to fermentable glucose, and had engineered the valine biosynthetic pathway to make Z .mobilis produce the isobutanol. We want to improve it by connecting these two.

In another part, three genes,

phbA

,

phbB

, and

phbC

from Ralstonia eutropha are introduced into Z .mobilis to modify its metabolic pathways. Expression of these genes lead to acetyl-coA flows into PHB synthesis. In this metabolic diagram, the whole pathway is shown.

Figure 5. Heterogenous PHB biosynthesis pathway.

Figure 6. Design of PHB plasmids construction.

In order to make these genes present and express more stably, the PHB-related genes into the ZM4 genome using

CRISPR-cas

technology.

Figure 7. CRISPR-cas technology

In our project, there are several genes need to be introduced into the plasmid. All genes are preceded by strong promoters, like Pgap of Z. mobilis, it would generate a high RNAP flux and may interfere with the next transcription unit. The un-regulated expression of downstream genes may be toxic to cells. And in the future, we will integrate these biological parts into the genome, this will increase genomic transcriptional events. In addition, the encounters between RNAP and DNAP may result in clashes during replication, which will increase genomic instability and can cause double-stranded breaks. So a model is built to predict the strength of terminators.

Figure 8. Unexpected events during the transcription process.

We build a workflow to predict the strength of terminator sequences. A sequence was input, and the structure was predicted using software with and the structural features identified by the Python scrips we coded. The feature found by the Python script can be used to calculate the free energy, which is then used as inputs of the prediction model. Finally, we can get a predicted terminator strength to choose a stronger terminator and use flow cytometry to verify the real strength of terminators.

Figure 9. Work flow form terminator sequence to real strength.