iGEM 2020 — Team NCTU_Formosa

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# Team:NCTU Formosa/Notebook

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Description
Design
Hardware
Contribution
Engineering
Implementation
Sustainable
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Experiment Results
Proof of Concept

Parts

Model

Human Practices
Science Communication

Team Introduction
Attributions
Collaborations
Partnership

Lab Note
Protocols

Medal Criteria

Top

![](https://static.igem.org/mediawiki/2020/1/15/T--NCTU_Formosa--lab.jpg)

[Jul](#mJul)

[Aug](#mAug)

[Sep](#mSep)

[Oct](#mOct)

| SUN | MON | TUE | WED | THU | FRI | SAT |
| --- | --- | --- | --- | --- | --- | --- |
|  |  |  | [1](#July1) | [2](#July2) | [3](#July3) | [4](#July4) |
| [5](#July5) | [6](#July6) | [7](#July7) | [8](#July8) | [9](#July9) | [10](#July10) | [11](#July11) |
| [12](#July12) | [13](#July13) | [14](#July14) | [15](#July15) | [16](#July16) | [17](#July17) | [18](#July18) |
| [19](#July19) | [20](#July20) | [21](#July21) | [22](#July22) | [23](#July23) | [24](#July24) | [25](#July25) |
| [26](#July26) | [27](#July27) | [28](#July28) | [29](#July29) | [30](#July30) | [31](#July31) |

| SUN | MON | TUE | WED | THU | FRI | SAT |
| --- | --- | --- | --- | --- | --- | --- |
|  |  |  |  |  |  | [1](#August1) |
| [2](#August2) | [3](#August3) | [4](#August4) | [5](#August5) | [6](#August6) | [7](#August7) | [8](#August8) |
| [9](#August9) | [10](#August10) | [11](#August11) | [12](#August12) | [13](#August13) | [14](#August14) | [15](#August15) |
| [16](#August16) | [17](#August17) | [18](#August18) | [19](#August19) | [20](#August20) | [21](#August21) | [22](#August22) |
| [23](#August23) | [24](#August24) | [25](#August25) | [26](#August26) | [27](#August27) | [28](#August28) | [29](#August29) |
| [30](#August30) | [31](#August31) |

| SUN | MON | TUE | WED | THU | FRI | SAT |
| --- | --- | --- | --- | --- | --- | --- |
|  |  | [1](#September1) | [2](#September2) | [3](#September3) | [4](#September4) | [5](#September5) |
| [6](#September6) | [7](#September7) | [8](#September8) | [9](#September9) | [10](#September10) | [11](#September11) | [12](#September12) |
| [13](#September13) | [14](#September14) | [15](#September15) | [16](#September16) | [17](#September17) | [18](#September18) | [19](#September19) |
| [20](#September20) | [21](#September21) | [22](#September22) | [23](#September23) | [24](#September24) | [25](#September25) | [26](#September26) |
| [27](#September27) | [28](#September28) | [29](#September29) | [30](#September30) |

| SUN | MON | TUE | WED | THU | FRI | SAT |
| --- | --- | --- | --- | --- | --- | --- |
|  |  |  |  | [1](#October1) | [2](#October2) | [3](#October3) |
| [4](#October4) | [5](#October5) | [6](#October6) | [7](#October7) | [8](#October8) | [9](#October9) | [10](#October10) |
| [11](#October11) | [12](#October12) | [13](#October13) | [14](#October14) | [15](#October15) | [16](#October16) | 17 |
| 18 | 19 | 20 | 21 | 22 | 23 | 24 |
| 25 | 26 | 27 | 28 | 29 | 30 | 31 |

## July 1

---

None

## July 2

---

None

## July 3

---

None

## July 4

---

None

## July 5

---

None

## July 6

---

None

## July 7

---

None

## July 8

---

None

## July 9

---

None

## July 10

---

None

## July 11

---

None

## July 12

---

None

## July 13

---

Digestion

* Sample:pET32a, pUC57a GR(har)

Gel extraction

* Sample:pET32a

Ligation

* Sample:
  + GR(har)+pET32a

Transformation

* Sample:
  + plasmid with GR(har) into DH5α

## July 14

---

Colony PCR & gel electrophoresis

* Sample: GR(har) transformation product

## July 15

---

Culturing

## July 16

---

Dilute IDT solutions

* Sample:
  + GR(har)

## July 17

---

None

## July 18

---

None

## July 19

---

Colony PCR & gel electrophoresis

* Sample:Lemo21, pET32a

Pfu PCR & gel electrophoresis

* Sample: GR(har)

## July 20

---

Culturing

## July 21

---

Digestion

* Sample:pET32a, GR(har)

Gel extraction

* Sample:pET32a

Ligation

* Sample:
  + GR(har)+pET32a

Transformation

* Sample:
  + plasmid with GR(har) into DH5α

## July 22

---

Pfu PCR & gel electrophoresis

* Sample: GR(har)

Digestion

* Sample: GR(har)

## July 23

---

Ligation

* Sample:
  + GR(har)+pET32a

Transformation

* Sample:
  + plasmid with GR(har) into DH5α

## July 24

---

Culturing

## July 25

---

None

## July 26

---

Transformation

* Sample:
  + plasmid pET32a into DH5α

## July 27

---

Culturing

## July 28

---

Digestion

* Sample:pET32a

Ligation

* Sample:
  + GR(har)+pET32a

## July 29

---

Transformation

* Sample:
  + plasmid with GR(har) into DH5α

## July 30

---

Culturing

Digestion

* Sample:pET32a

Ligation

* Sample:
  + GR(har)+pET32a

Transformation

* Sample:
  + plasmid with GR(har) into DH5α

PCR & gel electrophoresis

* Sample:pET32a, GR(har)

## July 31

---

None

## August 1

---

None

## August 2

---

Digestion

* Sample:pET32a, GR(har)

## August 3

---

Digestion

* Sample:pET32a, GR(har)

Gel extraction

* Sample:pET32a

Ligation

* Sample:
  + GR(har)+pET32a

Transformation

* Sample:
  + plasmid with GR(har) into DH5α

## August 4

---

None

## August 5

---

Culturing

## August 6

---

None

## August 7

---

None

## August 8

---

None

## August 9

---

None

## August 10

---

None

## August 11

---

Transformation

* Sample:
  + plasmid pET32a into Lemo21

## August 12

---

Culturing

## August 13

---

None

## August 14

---

None

## August 15

---

Funtional test

* Sample:
  + GR(har) in LB culture

## August 16

---

None

## August 17

---

Taiwan conference

## August 18

---

Taiwan conference

Culturing

## August 19

---

None

## August 20

---

Funtional test

* Sample:
  + GR(har) in LB culture

## August 21

---

None

## August 22

---

None

## August 23

---

None

## August 24

---

Culturing

Transformation

* Sample:
  + plasmid with BBa\_K274200 into Lemo21

## August 25

---

Culturing

Transformation

* Sample:
  + plasmid pSB1A3 into Lemo21

Funtional test

* Sample:
  + GR(har) in LB culture

## August 26

---

Culturing

M9 minimal medium preparation

## August 27

---

Cell disruption

* Sample:
  + plasmid pSB1A3 in Lemo21
  + plasmid pSB1A2 with BBa\_K274200 in Lemo21

## August 28

---

Funtional test

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium + Hydrogen peroxide
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium + pSB1A3 Lysate
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium + pSB1A2 BBa\_K274200 Lysate

## August 29

---

None

## August 30

---

None

## August 31

---

None

## September 1

---

Functional test

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium + solvent(5% DMSO+PBS)
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium + pSB1A3 Lysate
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium + pSB1A2 BBa\_K274200 Lysate
  + plasmid pET32a with GR(har) in Lemo21 in LB broth + solvent(5% DMSO+PBS)
  + plasmid pET32a with GR(har) in Lemo21 in LB broth + pSB1A3 Lysate
  + plasmid pET32a with GR(har) in Lemo21 in LB broth + pSB1A2 BBa\_K274200 Lysate
  + plasmid pET32a in Lemo21 in LB broth + solvent(5% DMSO+PBS)
  + plasmid pET32a in Lemo21 in LB broth + pSB1A3 Lysate
  + plasmid pET32a in Lemo21 in LB broth + pSB1A2 BBa\_K274200 Lysate
  + plasmid pET32a in Lemo21 in LB broth
  + plasmid pET32a in Lemo21 in M9 minimal medium
  + plasmid pET32a with GR(har) in Lemo21 in LB broth
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium

## September 2

---

None

## September 3

---

None

## September 4

---

None

## September 5

---

None

## September 6

---

None

## September 7

---

Functional test

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium with yeast extraction+ pSB1A2 BBa\_K274200 Lysate
  + plasmid pET32a in Lemo21 in M9 minimal medium with yeast extraction + pSB1A2 BBa\_K274200 Lysate
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium+ pSB1A2 BBa\_K274200 Lysate
  + plasmid pET32a in Lemo21 in M9 minimal medium + pSB1A2 BBa\_K274200 Lysate

## September 8

---

None

## September 9

---

Functional test

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

## September 10

---

None

## September 11

---

None

## September 12

---

Functional test

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

Glucose measurement

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

## September 13

---

None

## September 14

---

None

## September 15

---

None

## September 16

---

Glucose measurement

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

## September 17

---

Glucose measurement (with IPTG　induction)

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

## September 18

---

None

## September 19

---

None

## September 20

---

None

## September 21

---

None

## September 22

---

None

## September 23

---

None

## September 24

---

None

## September 25

---

None

## September 26

---

None

## September 27

---

Glucose measurement (with IPTG　induction)

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

Functional test (with IPTG　induction)

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

Proton pump measurement (with IPTG　induction)

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

## September 28

---

Functional test (with IPTG　induction and NaN3)

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

## September 29

---

None

## September 30

---

None

## October 1

---

None

## October 2

---

None

## October 3

---

None

## October 4

---

None

## October 5

---

None

## October 6

---

None

## October 7

---

None

## October 8

---

None

## October 9

---

None

## October 10

---

None

## October 11

---

Functional test (with IPTG　induction and NaN3)

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

RFP expression in GR expression system (with IPTG　induction and NaN3)

* Sample:
  + plasmid psB1K3 with GR(har) in Lemo21 in LB broth
  + plasmid psB1K3 in Lemo21 in LB broth

## October 12

---

None

## October 13

---

None

## October 14

---

None

## October 15

---

Funtional test-Growth measurement

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

## October 16

---

Funtional test-Growth measurement

* Sample:
  + plasmid pET32a with GR(har) in Lemo21 in M9 minimal medium
  + plasmid pET32a in Lemo21 in M9 minimal medium

## October 17

---

None

## October 18

---

None

## October 19

---

None

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Copyright©2020 NCTU\_Formosa. All rights reserved
National Chiao Tung University

NCTU EF454
No.1001, University Road,
Hsinchu 300, Taiwan

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# Team:NCTU Formosa/Engineering

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Description
Design
Hardware
Contribution
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Experiment Results
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Collaborations
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Lab Note
Protocols

Medal Criteria

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![](https://static.igem.org/mediawiki/2020/8/83/T--NCTU_Formosa--eng.jpg)

* [Research](#Research)
* [Image](#Imagine)
* [Design](#Design)
* [Build](#Build)
* [Test](#Test)
* [Learn](#Learn)
* [Improve](#Improve)

Research

From the research, we know *Gloeobacter* rhodopsin produces proton motive force using light illumination and it would synthesize ATP by ATP synthase.[1] Besides, we also find data show that the growth rate of *E. coli* with proton pumping rhodopsin would increase.[2] Simply speaking, the E. Hybrid might grow faster than wild type *E. coli*.

Image

Short cell cycle and high growth rate are essential for bacteria that are modified for bioengineering usages. For the Wet Lab part, we expected that *E. coli* with our new part, *Gloeobacter* rhodopsin could grow faster with the
additional ATP produced by the light-driven proton pump. And for the Dry Lab part, we assumed that the higher growth rate and the shorter cell cycle of *E. coli* with GR could be precisely determined, analyzed and predicted
by several parameters and functions. Therefore, we kicked off conducting experiments and modelling.

Design

For the Wet Lab, in addition to building a new part for additional ATP production, we designed our experiments by dividing them into two parts: protein expression and functional test. We tried to find the best culture environment for
GR with the simulation of our Dry Lab. And for the Dry Lab, by deriving differential equations based on our assumptions and substituting parameters from published review articles, we could simulate the growth conditions and estimate differences that are possibly produced from the different engineered bacteria and various cultural environments. In this step, we transformed the biological characteristics into mathematical parameters. If the experimental data
meets the predicted results, we could tell how fast the E. Hybrid grows by introducing the parameters in our culture condition to our model.

Build

We built a new part, *Gloeobacter* rhodopsin which is optimized by harmonization and utilized in our experiments.

![](https://static.igem.org/mediawiki/2020/a/ac/T--NCTU_Formosa--exp-result1.png)

Figure1: Colony PCR result
 of Harmonized GR after cloning into *E. coli*

And we simulate that the result would be like the figure shows below. However, we found out that the glucose uptake rate is still under assumption. Therefore, we set the wild type *E. coli* as control and compare the E. Hybrid to
different glucose uptake rates.

![](https://static.igem.org/mediawiki/2020/c/c8/T--NCTU_Formosa--model-data1.png)

Figure 2: The figure shows the growth curve simulation of wild type *E. coli* and E. Hybrid for 8 hours.

The growth rate of E. Hybrid is from 1.225 to 0.918 (1/hour) when the glucose uptake rate is assumed from 1.2 to 0.9 (mmol/gram dry weight/hour). The mitosis cycle (cell cycle) is 33.95 and 45.30 (min).

Test

By inputting the data, we got the parameters of E. Hybrid and wild type *E. coli*.

![](https://static.igem.org/mediawiki/2020/b/b6/T--NCTU_Formosa--model-data2.png)

Figure 3: The experimental data for fitting and model training for wild type E. *coli* and E.Hybrid for 11 hours.

After calculating growth rate from the data, we know the growth rate of E. Hybrid and wild type *E. coli* are 0.44 and 0.36 (1/hour) respectively. The ratio of growth rate is about 1.22 and increases about 22.2%. The mitosis cycle
(cell cycle) is 94.52 and 115.52 (min) Clearly, the E. Hybrid growth faster than *E. coli*. If you want to know more details, please click “Model”.

![](https://static.igem.org/mediawiki/2020/a/a0/T--NCTU_Formosa--modelun2.png)

Figure 4:The prediction result of Lemo21 pET32a and Lemo21 pET32a (GR harmonized) for 14 hours.

![](https://static.igem.org/mediawiki/2020/a/af/T--NCTU_Formosa--modelpg1.png)

Table1:The table is the error rate of growth curve prediction under 22mM Glucose.

The E. Hybrid not only grows fast but the growth curve of it also declines fast from the simulation results.

Learn

We can find that the predicted growth curve of E. Hybrid declines after 11 hours. However, the detection of O.D.600 would include the dead cell. Therefore, the experiment couldn’t precisely describe the growth curve of *E. coli* when
the *E. coli* start to decline owing to the glucose. This is a benefit of our model-it can describe the decline. For the validation results, we predict the glucose consumption and use experimental data to validate. At last, we assumed
that if we test the glucose concentration and find the glucose uptake rate of E. Hybrid, we can conduct reasonable and precise predictions which results in our improvement part in our engineering progress.

We find E. Hybrid not only grows fast but the growth curve of it also declines fast from the simulation results. And we speculated that it results from different glucose uptake rates to achieve rapid growth. Then, we discovered that
glucose was used up earlier, and the cell population of E. Hybrid declined. At last, we assumed that if we test the glucose concentration and find the glucose uptake rate of E. Hybrid, we can conduct reasonable and precise predictions
which results in our improvement part in our engineering progress.

Improve

We measured the glucose concentration of wild type and E. Hybrid during our functional test and found out that E. Hybrid accelerates glucose consumption.

![](https://static.igem.org/mediawiki/2020/4/4b/T--NCTU_Formosa--model-dataglu.png)

Figure 5: The prediction of extracellular glucose concentration and validation with experimental data for Lemo21 pET32a and Lemo21 pET32a (GR harmonized). The R-square is 0.9174 and 0.9671 for E. Hybrid and wild type *E. coli*.

The glucose uptake rate is 11.718 and 9.667 (mM/OD600/hour) for E. Hybrid and wild type *E. coli*. By Calculating, we can get the Energy Efficiency (Y) is 0.0382 and 0.039, respectively. Last, we take the glucose uptake rate from
experimental data into the prediction’s parameter to improve the prediction.

We have attained our goals, constructing an *E. coli* which could grow faster for bioengineering uses and a system that can determine, analyze and predict the growth of *E. coli* have been successfully achieved. We are able to determine
and analyze the growth of E. Hybrid, and it also grows much faster as our expectations, both of the engineering successes pave promising avenues for uses in the real world.

Reference

1. Lee, K. A., et al. (2011). "ATP regeneration system using *E. coli* ATP synthase and *Gloeobacter* rhodopsin and its stability." 11(5): 4261-4264.
2. Claassens, N. J., et al. (2013). "Potential of proton-pumping rhodopsins: engineering photosystems into microorganisms." 31(11): 633-642.

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National Chiao Tung University

NCTU EF454
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# Team:NCTU Formosa/Experiments

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Team Introduction
Attributions
Collaborations
Partnership

Lab Note
Protocols

Medal Criteria

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![](https://static.igem.org/mediawiki/2020/f/f8/T--NCTU_Formosa--proto.jpg)

Glucose Measurement

×

General
protocols

×

Functional
 Test

×

Transmembrane
 Protein Expression protocol

×

M9 minimal medium preparation

×

Bacteria Killing Test Protocol

×

Beta-Carotene Extraction

×

Turbidity
 Test

×

Photocurrent
 Measurement

×

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Copyright©2020 NCTU\_Formosa. All rights reserved
National Chiao Tung University

NCTU EF454
No.1001, University Road,
Hsinchu 300, Taiwan

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# Team:NCTU Formosa/Results

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Description
Design
Hardware
Contribution
Engineering
Implementation
Sustainable
Safety

Experiment Results
Proof of Concept

Parts

Model

Human Practices
Science Communication

Team Introduction
Attributions
Collaborations
Partnership

Lab Note
Protocols

Medal Criteria

Top

![](https://static.igem.org/mediawiki/2020/9/93/T--NCTU_Formosa--exp.jpg)

* [Overview](#overview)
* [Gene Construct & Protein Expression](#Gene)
* [GR Functional Tests](#function)
* [Protein Expression Enhancement](#enhance)

Overview

To incorporate light driven proton pump into *E. coli*, we first built up the
gene construct and expressed the transmembrane protein and observed its influence exerted on
*E.
coli* to evaluate its function and finally its ability to enhance target protein
expression
[1] (Graph 1).

![](https://static.igem.org/mediawiki/2020/d/d5/T--NCTU_Formosa--resultoverview.png)

Graph 1: Experiment workflow

Gene Construct & Protein Expression

Overall, we constructed three gene types in *E. coli*, Lemo21(DE3) in the
experiment(Graph 2). We did colony PCR and digest to check their genotype respectively.

![](https://static.igem.org/mediawiki/2020/0/04/T--NCTU_Formosa--exp-resultgr.png)

![](https://static.igem.org/mediawiki/2020/d/d2/T--NCTU_Formosa--exp-resultbeta.png)

![](https://static.igem.org/mediawiki/2020/3/3b/T--NCTU_Formosa--exp-resultmrfp.png)

Graph 2: Light driven proton pump expressing *E. coli* (left). Chromophore producing
 *E. coli* (middle). Target protein expressing *E. coli* (right).

Harmonized GR Expression

(A) Harmonized GR in pET32a Cloning PCR & Digest

We conducted colony PCR to verify that harmonized GR-GFP was correctly cloned
into the *E. coli* Lemo21 (DE3).

![](https://static.igem.org/mediawiki/2020/0/04/T--NCTU_Formosa--exp-resultgr.png)

![](https://static.igem.org/mediawiki/2020/a/ac/T--NCTU_Formosa--exp-result1.png)

Figure 1: Colony PCR result of harmonized GR-GFP after cloning
 into *E. coli*
Lemo21(DE3). (2680 b.p.)

(B) Harmonized GR Expression Tests

Expression of harmonized GR-GFP in pET32a with various L-Rhamnose concentrations

The proper folding of transmembrane light-induced proton pump(GR) can be visualized
by GFP. (More information see [Design](https://2020.igem.org/Team%3ANCTU_Formosa/Design)) It is generally
acknowledged that transmembrane
proteins are difficult targets for expression, so we chose *E. coli*, Lemo-21, which
features tunable T7 promoter expression system for the expression of GR[2]. We found
out that GFP expressed best without L-Rhamnose
inhibition (Fig. 2a, 2b). Accordingly, *Gloeobacter* rhodopsin can be easily expressed with
proper folding after sequence harmonization, which is good news for GR expression.

![](https://static.igem.org/mediawiki/2020/b/b0/T--NCTU_Formosa--expresult2.jpg)

Figure 2(a): GR-GFP expression with various L-Rhamnose concentrations

![](https://static.igem.org/mediawiki/2020/0/0e/T--NCTU_Formosa--expresult3.jpg)

Figure 2(b): The best expression occurred without addition of L-Rhamnose.

BBa\_K274200 Cloning & Expression

(A) CrtEBIY in psB1K3 Cloning PCR

We conducted colony PCR and digest to verify that BBa\_K274200 was correctly
cloned into *E. coli* Lemo21 (DE3).

![](https://static.igem.org/mediawiki/2020/d/d2/T--NCTU_Formosa--exp-resultbeta.png)

![](https://static.igem.org/mediawiki/2020/3/33/T--NCTU_Formosa--exp-result5.png)

Figure 3: Confirmation of BBa\_K274200 by digest(4555 b.p./ 2079 b.p.)

![](https://static.igem.org/mediawiki/2020/e/ea/T--NCTU_Formosa--exp-result4.png)

Figure 4: Colony PCR of BBa\_K274200(CrtEBIY), *E. coli* Lemo21(5078 b.p.)

(B) β-carotene Extraction in acetone

The chromophore we used in GR-GFP was β-carotene, the precursor of all-trans
retinal, which could be produced by the iGEM biobrick BBa\_K274200. Due to its difficulty in
producing all-trans retinal in *E. coli*, we tried β-carotene
as an alternative chromophore. We thus produced β-carotene by ourselves and extracted it for
extracellular addition in the subsequent functional test experiment.

We extracted β-carotene from CrtEBIY expressing *E. coli* and measured the
spectrum to confirm if β-carotene be successfully produced.

β-carotene extraction after consulting Professor Kao

After consulting Professor Kao in NCTU DBT to troubleshoot our β-carotene extraction
method (More information is in [Human Practices](https://2020.igem.org/Team%3ANCTU_Formosa/Human_Practices)), we have
confirmed that β-carotene
is successfully produced (Fig. 5) in *E. coli* with the new protocol (More information is
in
[Protocol](https://2020.igem.org/Team%3ANCTU_Formosa/Experiments)).

TAS\_Taipei validation of β-carotene extraction in acetone

We collaborated with TAS\_Taipei for validation of β-carotene extraction. (More
information is in [Collaborations](https://2020.igem.org/Team%3ANCTU_Formosa/Collaborations)) They
followed the protocol (More informations
is in [Protocol](https://2020.igem.org/Team%3ANCTU_Formosa/Experiments)) we
constructed, and successfully repeated the experiment (Fig. 6).

![](https://static.igem.org/mediawiki/2020/0/07/T--NCTU_Formosa--expresult6.jpg)

Figure 5: β-carotene Extraction Absorption Spectrum

![](https://static.igem.org/mediawiki/2020/c/c4/T--NCTU_Formosa--colltas.jpg)

Figure 6: TAS\_Taipei Validation(green line): β-carotene extraction absorption spectrum

GR Functional Tests

After the expression of GR in *E. coli*, we tested the light-induced proton
pump by measuring photocurrent and evaluated the influence on bacterial growth.

Proton Pumping Activity Measurement

With an aim to directly observe the proton pumping activity of GR-GFP in living
cells, we consulted senior iGEMer, Lung-Chieh Chen, and instructor, prof. Wen-Liang, Chen. The
lab offered its special techniques originally used as an
electrochemical biosensor for detecting various biomolecules, which features its ability to
accurately measure the amount by the detecting the resistance or electric current[3].
We thus designed an experiment based on
this platform by directly depositing a droplet of living GR-expressing *E. coli* on the
electrode of the detection chip. The droplet served as an bridge between the two electrodes. By
detecting the difference of current produced
during the experiment, we hypothesized that a difference of current induced by illumination,
which could be viewed as photocurrent produced by the proton pump.

We measured the proton pumping amount of *Gloeobacter* rhodopsin by directly
detecting the electric current under intervals of light and dark conditions.(The arrangement of
the experiment see Fig. 7, and the measuring detail see
[Protocol](https://2020.igem.org/Team%3ANCTU_Formosa/Experiments)) *Gloeobacter*
rhodopsin expressing *E. coli* showed a significant increase in photocurrent under light
excitation (Fig. 8), compared with the
vector control, thus proving its proton pumping activity.

![](https://static.igem.org/mediawiki/2020/a/ab/T--NCTU_Formosa--resultchip.jpg)

Figure 7: Photocurrent Measurement Device

![](https://static.igem.org/mediawiki/2020/0/05/T--NCTU_Formosa--photocurrent.jpg)

Figure 8: Photocurrent Measurement of GR-expressing *E. coli*

The proton pumping efficiency was determined by the increase in photocurrent at the
duration of illumination. We considered the first illumination to be the genuine representation
of reflecting the proton pumping activity of GR, so
we took the first duration (420 sec to 540 sec, Fig. 9) and analyzed it through proton pumping
simulation, and the proton pumping of GR was 0.16 (extracellular, ΔH+ × 10
-7/min OD), whereas the value of GR’s proton pumping rate by Pil Kim et al was
0.38[5].

>
![](https://static.igem.org/mediawiki/2020/c/c4/T--NCTU_Formosa--model-datapp.png)

Figure 9: Validation of Proton Pumping Activity in GR-expressing *E. coli*

Phototrophic Effect-Growth Measurement

The effect of additional ATP increase should affect the behavior of proton pumping
expressing *E. coli*, either in causing growth perturbation[4] or phototrophic
growth
[5]. We observed the growth of GR-GFP expressing *E. coli* with β-carotene as
chromophore and further evaluated its potential role in chemiosmotic effect. We used modified M9
minimum medium to evaluate the phototrophic
growth.

The whole incubation process was illuminated by white light LED strip and the
O.D.600 was documented every 20 minutes in either transparent or dark 96-well plates by LogPhase
600 for 22 hours. Fig.10 showed that GR-expressing *E. coli* showed better growth rate than
vector control once. The maximum cell growth of GR-expressing *E. coli* is
0.071(O.D.600/h), whereas its pET32a control is 0.054 (O.D.600/h).

![](https://static.igem.org/mediawiki/2020/a/a2/T--NCTU_Formosa--expresult9.jpg)

Figure 10: Phototrophic growth measurement of GR-expressing *E. coli*

(A)Sodium Azide

![](https://static.igem.org/mediawiki/2020/2/2e/T--NCTU_Formosa--designelectron.jpg)

Graph 3: Hypothetical mechanism of the role of light induced proton pump(GR) in *E.
coli*

To further investigate the role of GR-GFP expressed in *E. coli*, we added
sodium azide to inhibit the respiratory electron transport chain to assess the function of
GR-GFP. We hypothesized that GR-GFP’s proton pumping activity
could compensate for the loss of function of respiratory electron transport chain due to sodium
azide as graph 3 shows[6].

![](https://static.igem.org/mediawiki/2020/1/1a/T--NCTU_Formosa--expresult10.jpg)

Figure 11: Phototrophic growth measurement of GR-expressing
*E. coli* under
sodium azide(0.001%)

![](https://static.igem.org/mediawiki/2020/9/90/T--NCTU_Formosa--expresult11.jpg)

Figure 12: Phototrophic growth measurement of GR-expressing *E. coli*
with/without sodium azide addition

![](https://static.igem.org/mediawiki/2020/d/d1/T--NCTU_Formosa--expresult12.jpg)

Figure 13: Phototrophic growth measurement of GR-expressing *E. coli*
with/without sodium azide addition at 20th hour
(\*\*:p value<0.01/
\*\*\*\*:p
value<0.0001)

With the addition of sodium azide, it strongly inhibited the growth of *E.
coli*; moreover, we found that GR-expressing *E. coli* survived in 0.01% sodium
azide growing environment (Fig. 11), which proved the hypothesis we proposed. This experiment of
growth measurement was performed simultaneously
with growing conditions without sodium azide (Fig.10). Altogether, we found that the proton pump
we expressed in *E. coli* serves as an alternative for respiratory electron transport
chain, thus proving its function of creating
proton gradient in *E. coli*. The experiment was done with 3 technical replicates and the
growing pattern shows significant difference among GR-expressing
*E. coli* and vector control (Fig. 13).

(B)Glucose Consumption

With respect to the phototrophic growth pattern observed, faster growth of
GR-expressing
*E. coli* not only relies on the proton gradient, additional ATP it produces, but also on
its carbon sources, mass increase, for growth. We were next interested in finding the
consumption rate of glucose in GR-expressing
*E. coli*. Basically, we expected the higher consumption rate of glucose with additional
ATP produced by GR. We used M9 medium with glucose (0.4%, 22.2mM), and used DNS reagent to
determine the glucose concentration.

Glucose Measurement Standard Curve

Before we measured the glucose concentration in our M9 minimal culture, we should
set up a standard for it. The R square of our standard curve is 1, so we ensured that the
glucose concentrations were precisely measured.

![](https://static.igem.org/mediawiki/2020/0/05/T--NCTU_Formosa--expresult13.jpg)

Figure 14: Glucose Measurement Standard Curve

Glucose Consumption of *E. coli* -WT & GR-expressing *E. coli*

We found that GR-expressing *E. coli* consumed GR faster, as it exhausted
glucose in 12 hours, while the vector control one (pET32a, Lemo21) took 14 hours for glucose
depletion(Fig.15). The maximum glucose uptake rate(QMax)
of GR-expressing  *E. coli* Lemo21 is 11.28(Mm/O.D.600·h) whereas that of vector control
one is 9.47(Mm/O.D.600·h). Also, we successfully built a system for the prediction for the
growth curve with glucose concentration, we
have integrated it into our culture condition optimization model. (More information is in [ENGINEERING](https://2020.igem.org/Team%3ANCTU_Formosa/Engineering))

![](https://static.igem.org/mediawiki/2020/4/4b/T--NCTU_Formosa--model-dataglu.png)

Figure 15: Glucose Consumption of GR-expressing *E. coli*

Summary

In the functional test of GR-GFP, we provided evidence for proving its pumping
activity and its participating role in  *E. coli’s* chemiosmotic proton gradient with the
sodium azide test. The proton pumping activity was first
measured by the chip in photocurrent difference with illumination, and its phototrophic growing
effect was revealed by growth measurement with our proton pump with faster glucose consumption,
which was in line with our expectation
that GR-GFP offers an additional facilitating source of energy. In that GR-GFP gene can be
easily expressed and visualized in  *E. coli*, it may be also expressed in other strain of
*E. coli* and modified through extensive gene engineering techniques.

Protein Expression Enhancement

Now that we had proved the gene to be functional and beneficial to *E. coli*,
we finally came to the final proof of concept in the experiment. The concept of E. hybrid can be
exemplified with a simple target protein, red fluorescence
protein, RFP. We assessed the ability of engineered GR-GFP expressing *E. coli*, Lemo21 by
expressing RFP. We expected the fluorescence intensity to be stronger than vector control ones,
if so proving its ability to achieve
the goal of protein expression enhancement and its protein function.

RFP Expression in GR-expressing Lemo21

We expressed RFP in the GR-expressing system to know how it helps the protein
expression.

(A) RFP(BBa\_J04450) in psB1K3 Cloning PCR

We conducted colony PCR to verify that BBa\_J04450 and harmonized GR-GFP were
both correctly cloned into the *E. coli* Lemo21 (DE3).

![](https://static.igem.org/mediawiki/2020/3/3b/T--NCTU_Formosa--exp-resultmrfp.png)

![](https://static.igem.org/mediawiki/2020/3/36/T--NCTU_Formosa--exp-result17.png)

Figure 16: Colony PCR result of BBa\_J04450(1382 b.p.)

![](https://static.igem.org/mediawiki/2020/d/df/T--NCTU_Formosa--exp-result16.png)

![](https://static.igem.org/mediawiki/2020/e/e3/T--NCTU_Formosa--exp-result20.png)

Figure 17: Colony PCR of co-transform of BBa\_J04450(1382 b.p.) &
harmonized
GR(2680 b.p.) into *E. coli* Lemo21

![](https://static.igem.org/mediawiki/2020/6/66/T--NCTU_Formosa--exp-result18.png)

![](https://static.igem.org/mediawiki/2020/d/d8/T--NCTU_Formosa--exp-result15.png)

Figure 18: Colony PCR of co-transform of BBa\_J04450(1382 b.p.) &
pET32a(754 b.p.)
into *E. coli* Lemo21

(B) RFP Expression in GR-expressing *E. coli* Lemo21

We cultivated both the GR-expressing *E. coli* and vector control ones in LB
with IPTG induction in LB broth for incubation. We measured the end point of the final samples
and compared their RFP fluorescent intensity.

![](https://static.igem.org/mediawiki/2020/a/a1/T--NCTU_Formosa--expresult21.jpg)

Figure 19(a): RFP expression in GR-expressing *E. coli* The test was done
with triplicate(\*:p value<0.05)

![](https://static.igem.org/mediawiki/2020/c/c6/T--NCTU_Formosa--redddddddd.png)

Figure 19(b): Visualization of RFP Expression

GR-expressing *E. coli* shows stronger fluorescence intensity than the vector
control ones (Fig. 19a, 19b), as can be visualized under blue light illuminator (BLooK,
GeneDireX).

Reference

1. Kim, H.-J., et al. (2012). "An engineered Escherichia coli having a high intracellular level
   of ATP and enhanced recombinant protein production." Applied microbiology and biotechnology
   94(4): 1079-1086
2. Schlegel, S., et al. (2012). "Optimizing membrane protein overexpression in the Escherichia
   coli strain Lemo21 (DE3)." Journal of molecular biology 423(4): 648-659.
3. Chen, L.-C., et al. (2020). "Improving the reproducibility, accuracy, and stability of an
   electrochemical biosensor platform for point-of-care use." Biosensors and Bioelectronics
   155: 112111.
4. Na, Y.-A., et al. (2015). "Growth retardation of Escherichia coli by artificial increase of
   intracellular ATP." Journal of industrial microbiology & biotechnology 42(6): 915-924.
5. Kim, H. A., et al. (2017). "An evolutionary optimization of a rhodopsin-based phototrophic
   metabolism in Escherichia coli." Microbial cell factories 16(1): 111
6. Walter, J. M., et al. (2007). "Light-powering Escherichia coli with proteorhodopsin."
   Proceedings of the National Academy of Sciences 104(7): 2408-2412.

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