iGEM 2021 — Team IISER-Tirupati_India

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# Team:IISER-Tirupati India/Notebook

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  + [EDUCATION](https://2021.igem.org/Team%3AIISER-Tirupati_India/Education)
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  + [INCLUSIVITY](https://2021.igem.org/Team%3AIISER-Tirupati_India/Inclusivity)
  + [SUSTAINABLE DEVELOPMENT](https://2021.igem.org/Team%3AIISER-Tirupati_India/Sustainable)
* TEAM
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  + [COLLABORATIONS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Collaborations)
  + [PARTNERSHIP](https://2021.igem.org/Team%3AIISER-Tirupati_India/Partnership)
* [AWARDS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Awards)

### INDEX

* ##### [Wetlab Calender](#1)
* ##### [Protocols](#2)

## Wetlab Calender

## January

**Week 1** (1 Jan 2021 -3 Jan 2021) :

A literature review of the female reproductive tract, found that hZP2 protein mutation in females result in infertility, literature review of the microbiome of the reproductive tract

**Week 2** (4 Jan, 2021 -10 Jan 2021):

A literature review of the targets of the ovum, ruled out producing non-specific enzymes from the bacteria because of the potential harm

**Week 3** (11 Jan 2021 - 17 Jan 2021) :

Learning about iGEM parts, kits and registry to get an idea of availablity of resources.

Categorized the species of bacteria in both fallopian tubes, found ovastacin protein (ASTL gene).

**Week 4** (18 Jan 2021 - 24 Jan 2021) :

Studied more on *Lactobacillus*, met with experts in our institute to discuss the idea, looked into lex A system for progesterone sensing, completely ruled out production of NAG enzyme by bacteria

**Week 5 (**24 Jan 2021 - 31 Jan 2021) :

A literature review about the immune system of the reproductive system, started review on a kill switch for reversibility.

## February

**Week 1** (1 Feb 2021 - 7 Feb 2021 )**:**

Found more about iGEM competition deliverables and had a meeting with our PIs. Literature review on Zona hardening

**Week 2** ( 8 Feb 2021 - 14 Feb 2021)**:**

 A literature review on the hZP2 cleavage model by ovastacin and learnt more about the structure of ovastacin

**Week 3** (15 Feb 2021 - 21 Feb 2021)**:**

Searched for a commensal for implementation of our idea and an appropriate model organism to use as chassis by looking into secretion systems, looked into progesterone sensing by the SRTF1 .

**Week 4** (22 Feb 2021 - 28 Feb 2021)**:**

Finalised model organism as em>Bacillus subtilis for proof of concept and *Lactobacillus acidophilus* as the commensal of reproductive tract to modify, finalized SRTF1 for progesterone inducible system

## March

**Week 1** (1 March 2021 -7 March 2021)**:**

Looked at the HGT aspects of the genetically modified bacteria through literature review and found out more about the safety aspects.

**Week 2** (7 March 2021 - 14 March 2021)**:**

Finalized the different modules of our project, started in-silico work for proof of concept. Looked at different competition deliverables from the wet lab point of view and planned how to achieve them.

**Week 3** (15 March 2021 - 21 March 2021) **:**

Looked into more toxin-antitoxin systems for the kill switch in bacteria, started designing preliminary experiments for the proof of concept

**Week 4** (22 March 2021 - 31 March 2021) **:**

Met Prof Satish K Gupta for getting feedback on our idea, agreement to procure clones of Human ZP2 in *E.coli* *DH5α* from his lab at NII, Delhi. Continued work on the toxin-antitoxin system and started looking for more models for the hormonal sensing system

## April

**Week 1** (1 April 2021- 3 April 2021) **:**

Procured clones of hZP2 from Prof Satish K Gupta and shipped them to our lab at IISER Tirupati. Continued the work on designing experiments for the proof of concept of our project.

**Week 2** (4 April 2021 - 10 April 2021)**:**

Decided to work with yeast as a substitute organism too and started designing experiments for yeast species. Started looking at resources to procure strains of *Bacillus subtilis.*

**Week 3** (11 April 2021 -17 April 2021)**:**

Meeting with experts working on yeast systems from our institute, started looking for protocols for different experiments, realized the limitations of progesterone inducible systems, and started looking for alternative hormone sensing models in prokaryotes.

**Week 4** (18 April 2021 - 30 April 2021) **:**

Realized the sensitivity issue of the estrogen sensing system in prokaryotes

## May

**Week 1** (1 May 2021 - 8 May 2021) **:**

Worked on finding alternatives for the progesterone inducible system, literature review on kill switches resumed and protocol review process started

**Week 2** (9 May 2021 - 15 May 2021)**:**

End Semester exams

**Week 3** (16 May 2021- 22 May 2021) **:**

Started looking into growth kinetics for reducing ovastacin production time, Heterologous gene expression in *Bacillus subtilis*. Ruled out the pH, temperature based kill switches and started to look into light inducible Dnase toxins for kill switch and biosafety. And found yqcG and bovine Dnase 1.

**Week 4** (23 May 2021- 31 May 2021) :

Yeast experimental workflow finalized and started to list out the experiment requirements. Started looking into the ytvA system for biosafety and Decided which promoters to take for experiments, looked for finalized parts in the iGEM parts registry.

## June

**Week 1** ( 1 June 2021 - 5 June 2021) **:**

Started making the *Bacillus subtilis* workflow, finalized the experiments, Calculated d-score for terminator efficiency, and selected terminator for making improvement to part.

**Week 2** ( 6 June 2021 - 12 June 2021) **:**

Worked on Genetic circuits for all the experiments, finalized the protocols for genome integration in *Bacillus subtilis*.

**Week 3** (13 June 2021 - 19 June 2021) **:**

Started looking for protocols of protein purification in the yeast and *Bacillus subtilis* and discussed them with various experts from our institute. Found out the reagents required for carrying out the experiments.

**Week 4** (20 June 2021 - 30 June 2021):

Met with Dr Sabari Sankar Thirupathy from IISER Thiruvananthapuram to discuss *Bacillus subtilis* experiments and had an agreement with him to ship the clones to our laboratory at IISER Tirupati. Did an in-depth analysis of transformation and protein purification protocols for *Bacillus subtilis* and looked for reagents for the same.

## July

**Week 1** (1 July 2021 - 10 July 2021) :

Discussions on experiments and protocols continued and sent a list of required reagents and consumables to our laboratory and placed initial orders for reagents and consumables.

**Week 2** (11 July 2021 - 17 July 2021) :

Talked with PhD students and seniors on performing the experiments upon return to campus, ordered gene fragments from IDT for *Bacillus subtilis*, and ordered yeast gene fragments from Twist Bioscience

**Week 3** (18 July 2021 - 24 July 2021) :

Returned to IISER Tirupati campus and Quarantined for a week. Compiled final protocols for the experiments and placed more orders of consumables for experiments.

**Week 4** (25 July - 31 July 2021) :

We received our iGEM distribution kit and NEB molecular biology kits. We presented the wet lab plan to our guide PhDs and Professors. Had our lab safety training to start the experiments. Prepared experimental things to start our initial experimental journey.

## August

**Week 1** (1 Aug 2021 - 7 Aug 2021):

Started our experiments by culturing the *E. coli* containing the plasmid pDR111 and pDR110 and purified them. Thereafter we did restriction digestion of purified plasmids with BamHI-hf and EcoRI-hf. Performed a growth curve of *E Coli DH5α* and *Bacillus subtilis 168* in LB media and performed *Saccharomyces cerevisiae* strain S288C in YPD media.

**Week 2** (8 Aug 2021 - 14 Aug 2021) :

Received orders from Himedia. Did Miniprep for the plasmid pDR111 stock preparation. Prepared the stock solutions for the competency of *E Coli DH5α* and made *E Coli DH5α* cells competent followed by storing them at -80⁰C. Performed gram staining to check the bacterial contamination on the plates. Had a demo session for Agarose Gel preparation with our seniors.

**Week 3** (15 Aug 2021 - 21 Aug 2021) :

Transformed the *E Coli DH5α* cells with pDR111 to check the quality of the prepared competent cells. Received IDT primers and stock solutions were prepared for SDS PAGE. Worked on making the lab setting more inclusive through LabEyes. Performed Restriction digestion on the plasmid pDR111 with BamHI- hf, and EcoRI- hf.

**Week 4** (22 Aug 2021 - 31 Aug 2021) :

Performed sequential digestion with EcoRI and BamHI and performed gel extraction with the digested vector. Received Twist order for the yeast DNA fragments. Streaked the *E. Coli DH5α* with hZP2 clones and expressed the hZP2 protein by IPTG induction. Stored the extracted protein in -20⁰C. Received the pRS424, pRS426, pRS425 yeast shuttle vector plasmids from Dr Vijayalakshmi Subramanian lab.

## September

**Week 1** ( 1 Sept 2021 - 11 Sept 2021):

Did protein purification and ran SDS PAGE multiple times for standardization of ZP2 clones with different IPTG concentrations (0.5mM and 1mM). Started working on oligonucleotides received from TWIST ( for golden gate of ZP2- Ovastacin cassette) and did not get satisfactory results. Performed miniprep with the pRS426 plasmid (for *S Cerevisiae* vector)and pRSETb plasmid (for ZP2 in *E. Coli* ). Purified the pRS426 plasmid and transformed the *E Coli*  DH5α with pRSETb and got positive results. Prepared stock solutions for *Bacillus subtilis* transformation and competency.

**Week 2** (12 Sept 2021 - 18 Sept 2021) :

Transformed the *Bacillus subtilis* and observed the growth of cells on plates within 9hrs. Prepared competent cells of *E. Coli* BL21 strain and transformed them with pRSETb for ZP2 expression. Golden gate trials for ZP2- Ovastacin cassette was unsuccessful. Ran SDS for purified hZP2.

**Week 3** (19 Sept 2021 - 25 Sept 2021) :

Did IMAC(Ni-NTA) for hZP2 protein purification and Western Blot. Started golden gate trials with spacer cassette for terminator check and SRTF1- P22 combined cassette. Did transformation of the ligated product of ZP2- Ovastacin cassette with pRS426 plasmid in NEB 10β cells and got positive results.

**Week 4** (26 Sept 2021 - 30 Sept 2021) :

Mid sem exams

## October

**Week 1** (1 Oct 2021 - 9 Oct 2021)**:**

Performed golden gate with spacer cassette for terminator check. Mini-prep for the pDR111 and pRS426 plasmids. Did restriction digestion of these plasmids and dephosphorylated them to make them compatible vectors. Did colony PCR with the vector with spacer cassette for terminator check and results were inconsistent. Results with gradient PCR for spacer cassette for terminator check were also not satisfactory.

**Week 2 (**10 Oct 2021 - 16 Oct 2021) **:**

Standardization of PCR with different primers and at different temperatures. Performed golden gate assembly with all the remaining cassettes that we have designed. i.e. ovastacin cassette, BBa\_B0010 terminator cassette , BBa\_K3889070 terminator cassette, SRTF1- P22 combined cassette. Performed transformation with all the cassettes to the NEB 10β cells and still results were not good. Decided to go with colony PCR, did patching, and performed colony PCR to find out the desired transformant by performing gel electrophoresis. Got the positive result for the BBa\_B0010 terminator cassette and did a mini-prep with that to transform it into *Bacillus subtilis* for further experimentation.

**Week 3** (17 Oct 2021 - 23 Oct 2021) **:**

BBa\_B0010 terminator cassette with pDR111 plasmid transformed into *Bacillus subtilis* and performed the fluorescence microscopy to check fluorescence (sfGFP and mCherry expression) in bacterial cells. Patched the colonies for spacer cassette for terminator check, BBa\_K3889070 terminator cassette, and SRTF1- P22 combined cassette and performed colony PCR and got the positive clones for all cassettes. Inoculated the colonies with clones and performed miniprep and restriction digestion with BsaI-HFv2 for the vector linearization. Transformed the *Bacillus subtilis* with these different cassettes. We performed the platereader assay with spacer cassette for terminator check and different concentrations of progesterone to check SRTF1- P22 combined cassette.

## Protocols

## INITIAL SETUP AND GROWTH

1. ##### Growth Curve

   1. ###### *Bacillus subtilis* 168

      Click here on button to download the PDF file.

      Download
   2. ###### *E. coli DH5α* strain

      Click here on button to download the PDF file.

      Download
   3. ###### Yeast (*Saccharomyces Cerevisiae* strain S288C)

      Click here on button to download the PDF file.

      Download
2. ##### Culture preparation (Streaking, Spreading, Inoculation, Antibotic stock solution preparation)

   Click here on button to download the PDF file.

   Download
3. ##### Revival from glycerol stock and Preparation of glycerol stock

   Click here on button to download the PDF file.

   Download

## CLONING

1. ##### Oligonucleotides Resuspension

   Click here on button to download the PDF file.

   Download
2. ##### Plasmid purification (Miniprep)

   Click here on button to download the PDF file.

   Download
3. ##### Nanodrop

   Click here on button to download the PDF file.

   Download
4. ##### Agarose gel electrophoresis

   Click here on button to download the PDF file.

   Download
5. ##### Agarose Gel Extraction

   Click here on button to download the PDF file.

   Download
6. ##### Restriction digestion

   Click here on button to download the PDF file.

   Download
7. ##### PCR amplification

   Click here on button to download the PDF file.

   Download
8. ##### PCR cleanup

   Click here on button to download the PDF file.

   Download
9. ##### Golden Gate assembly

   Click here on button to download the PDF file.

   Download
10. ##### SpeedVac

    Click here on button to download the PDF file.

    Download
11. ##### Ligation

    Click here on button to download the PDF file.

    Download
12. ##### Patching and Colony PCR

    Click here on button to download the PDF file.

    Download
13. ##### Replica plating and Starch test

    Click here on button to download the PDF file.

    Download
14. ##### Competency and Transformation

    1. ###### *E. coli*

       Click here on button to download the PDF file.

       Download
    2. ###### *Bacillus subtilis* 168

       Click here on button to download the PDF file.

       Download
    3. ###### *Saccharomyces Cerevisiae strain S288C*

       Click here on button to download the PDF file.

       Download

## PROTEIN PURIFICATION AND ANALYSIS

1. ##### Protein induction

   Click here on button to download the PDF file.

   Download
2. ##### Ni-NTA protein purification

   Click here on button to download the PDF file.

   Download
3. ##### Cell Lysis (with sonication)

   * ###### *E. coli* BL21 strain

     Click here on button to download the PDF file.

     Download
4. ##### SDS-PAGE

   Click here on button to download the PDF file.

   Download
5. ##### Western blotting

   * ###### *E. coli* BL21 strain - ZP2 analysis

     Click here on button to download the PDF file.

     Download

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###### PROJECT

[DESCRIPTION](https://2021.igem.org/Team%3AIISER-Tirupati_India/Description)
[BLUEPRINT](https://2021.igem.org/Team%3AIISER-Tirupati_India/Blueprint)
[ENGINEERING](https://2021.igem.org/Team%3AIISER-Tirupati_India/Engineering)
[BACKGROUND](https://2021.igem.org/Team%3AIISER-Tirupati_India/Background)
[IMPLEMENTATION](https://2021.igem.org/Team%3AIISER-Tirupati_India/Implementation)
[CONTRIBUTION](https://2021.igem.org/Team%3AIISER-Tirupati_India/Contribution)

###### WETLAB

[PROOF OF CONCEPT](https://2021.igem.org/Team%3AIISER-Tirupati_India/Proof_Of_Concept)
[DESIGN](https://2021.igem.org/Team%3AIISER-Tirupati_India/Design)
[PARTS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Parts)
[RESULTS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Results)
[SAFETY](https://2021.igem.org/Team%3AIISER-Tirupati_India/Safety)
[LAB NOTEBOOK](https://2021.igem.org/Team%3AIISER-Tirupati_India/Notebook)
[EXCELLENCE](https://2021.igem.org/Team%3AIISER-Tirupati_India/Excellence)

###### HUMAN PRACTICES

[HUMAN PRACTICES](https://2021.igem.org/Team%3AIISER-Tirupati_India/Human_Practices)
[EDUCATION](https://2021.igem.org/Team%3AIISER-Tirupati_India/Education)
[COMMUNICATION](https://2021.igem.org/Team%3AIISER-Tirupati_India/Communication)
[INCLUSIVITY](https://2021.igem.org/Team%3AIISER-Tirupati_India/Inclusivity)
[SUSTAINABLE DEVELOPMENT](https://2021.igem.org/Team%3AIISER-Tirupati_India/Sustainable)

###### TEAM

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[ATTRIBUTIONS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Attributions)
[COLLABORATIONS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Collaborations)
[PARTNERSHIP](https://2021.igem.org/Team%3AIISER-Tirupati_India/Partnership)

###### DRYLAB

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[WEBSITE](https://2021.igem.org/Team%3AIISER-Tirupati_India/Website)

##### Side Effects of Current Methods of Contraceptives.

* Cancers: Studies link a high risk of breast and cervical cancer for women taking oral contraceptive pills, while there is reduction in risks of endometrial, ovarian, and colorectal cancers.
* Ovarian cysts: About 1 out of 10 women will get these fluid-filled sacs in their ovaries in the first year after they get an IUD. Cysts usually go away on their own within three months.
* Cardiovascular diseases: A rise of 20-30% in arterial plaque was found in two big arteries for each decade of using birth control pills. For women who take a traditional combination pill with a low dose of estrogen, the risk of heart attack increases by 80% for them.
* Depression: Use of hormonal contraception, especially among adolescents, was associated with subsequent use of antidepressants and the first diagnosis of depression, suggesting depression as a potential adverse effect of hormonal contraceptive use.
* Migraines and headaches: In women who are not taking hormonal contraception, estrogen withdrawal during the late luteal phase is a well-recognized trigger of headaches and menstrual migraines

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# Team:IISER-Tirupati India/Engineering

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  + [BACKGROUND](https://2021.igem.org/Team%3AIISER-Tirupati_India/Background)
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* WETLAB
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  + [DESIGN](https://2021.igem.org/Team%3AIISER-Tirupati_India/Design)
  + [PARTS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Parts)
  + [RESULTS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Results)
  + [SAFETY](https://2021.igem.org/Team%3AIISER-Tirupati_India/Safety)
  + [LAB NOTEBOOK](https://2021.igem.org/Team%3AIISER-Tirupati_India/Notebook)
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* DRYLAB
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  + [WEBSITE](https://2021.igem.org/Team%3AIISER-Tirupati_India/Website)
* HUMAN PRACTICES
  + [HUMAN PRACTICES](https://2021.igem.org/Team%3AIISER-Tirupati_India/Human_Practices)
  + [EDUCATION](https://2021.igem.org/Team%3AIISER-Tirupati_India/Education)
  + [COMMUNICATION](https://2021.igem.org/Team%3AIISER-Tirupati_India/Communication)
  + [INCLUSIVITY](https://2021.igem.org/Team%3AIISER-Tirupati_India/Inclusivity)
  + [SUSTAINABLE DEVELOPMENT](https://2021.igem.org/Team%3AIISER-Tirupati_India/Sustainable)
* TEAM
  + [MEMBERS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Team)
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  + [COLLABORATIONS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Collaborations)
  + [PARTNERSHIP](https://2021.igem.org/Team%3AIISER-Tirupati_India/Partnership)
* [AWARDS](https://2021.igem.org/Team%3AIISER-Tirupati_India/Awards)

### INDEX

* [Introduction](#1)
* [Module-1](#2)
* [Module-2](#3)
* [Module-3A](#4)
* [Module-3B](#4A)
* [References](#5)

## Introduction

The engineering cycle is a learning process with properly defined steps to develop a **suitable method for improving the biological system**. The process starts with identifying the problem one is dealing with and the questions that need to be addressed to solve the problem. Next, it is necessary to perform background research on the topic and to come up with a draft **design** suitable to solve the problem. This design is then **constructed** and **tested** using various methods depending on the problem and the results are interpreted. After analysing the results, if the solution doesn't seem to be satisfactory then **redesigning** is done based on the shortcomings in the previous solution and the next solution is tested again. This process continues until one finds a solution that best fits the problem.

![Engineering cycle](https://static.igem.org/mediawiki/2021/f/f7/T--IISER-Tirupati_India--engcyc.png)

All modules of our project went through iterations. This page tries to explain these iterations in the most convenient way.

* Starting with the delivery system, the first idea was to modify an Intrauterine Device (IUD) and deliver the Genetically Modified Organisms (GMO) through the ostia. Its calculations were done, but many drawbacks came up for which an alternative solution of **hysteroscopic delivery method** was chosen.
* Post-delivery, the bacteria colonizes the region that we studied through a growth model.
* After reaching the stationary phase, the bacteria should produce ovastacin during the right period of time i.e. during ovulation and the fertile window, and **genetic circuit needs to be designed** for the same.
* Similarly, for **reversal of contraception and biosafety**, the kill switches had to be designed and improved upon.

## Module 1. Delivery System

### Summary

In our idea, the GMO needs to be introduced into the fallopian tube up to the ampulla which is the desired location. The simplest way that one could think of introducing the GMO is to inject a GMO containing solution directly into the fallopian tube. Nevertheless, this gives rise to some problems and drawbacks. The next method utilizes a long, thin catheter that can reach up to the ampulla and comes with a camera, this was a simplified description of a hysteroscope that helped us overcome those obstacles.

![The dimensions of the fallopian tube showing intramural ,isthmus and ampulla](https://static.igem.org/mediawiki/2021/3/38/T--IISER-Tirupati_India--oviduct.svg)

Fig 1.1 The dimensions of the fallopian tube based on [35].

An ovum takes about 4-5 days to travel from the ovary to the uterus [1]. During the course of its journey, it spends about 3 days in the ampulla and gets degraded if it is not fertilized by the sperm. In order to prevent fertilization of ovum by the sperm we need to ensure that the **ovum gets hardened even before a single sperm can reach it and penetrate it’s membranes**. Thus we want to get as close to the ovum as possible.
Ampulla would thus be the intended location to introduce the GMO because the ovum would more or less be stationary. The commensal of oviduct **Lactobacillus acidophilus** is genetically modified to produce a protease called **ovastacin** that hardens the ovum to prevent sperm penetration. The aim of our first module is the idea of delivery of our GMO into the fallopian tube at the appropriate location.

**Aim:** To find the most feasible delivery mode

### Iteration 1:

#### 1.1 Design:

The fallopian tube can be approximated to be a cylindrical tube of diameter 7.5 mm. The fluid containing our bacteria must be of significant density difference from the oviductal fluid (1260 kg/m3) [36].

![Low fluid density injected in a confined channel containing relatively denser fluid.](https://static.igem.org/mediawiki/2021/c/c6/T--IISER-Tirupati_India--visconf.svg)

Fig 1.2 Low fluid density injected in a confined channel containing relatively denser fluid. Source: [2]

The fluid is then injected from the ostia or into the uterus at a volumetric flow rate of Q.

* $q\rightarrow$ Volumetric flow rate
* $g \rightarrow$ Acceleration due to gravity (g=9.8 m s-1)
* $h\_0 \rightarrow$ Diameter of cylindrical tube *(h0 = 7.5 mm)*
* $\mu\_1 \rightarrow$ Dynamic Viscosity of injected fluid (Water = 6.913 × 10− 4 Pa $\cdot$ s)
* $\mu\_2 \rightarrow$ Dynamic viscosity of oviductal fluid (*Oviductal Fluid = 0.799 Pa $\cdot$ s)*
* $\rho\_1 \rightarrow$ Density of injected fluid *(Water= 1 g cm 3)*
* $\rho\_2 \rightarrow$ Density of oviductal fluid *(Oviductal fluid 1.26 g cm 3)*
* $u\_2 \rightarrow$ Velocity of denser fluid [37] (Vfluid= 0.07 s− 1 [38])

#### 1.2 Build:

Refering to [2]. The injection of fluid is done either with the help of a modified IUD or a catheter. An IUD was known to reach or get closer to both the ends of the ostia, and it was considered that bacterial fluid could then be delivered to both the fallopian tubes at once. The concern was to check how long the bacteria would take to reach the desired site i.e. ampulla and also ensure **minimum invasion**.

#### 1.3 Test:

Defining,

\begin{equation}\tag{1.1.1}
x\_c=\frac{\Delta \rho g h\_0^4}{\mu\_1 q}
\end{equation}
\begin{equation}\tag{1.1.2}
t\_c=\frac{\Delta \rho g h\_0^5}{\mu\_1 q^2}
\end{equation}
\begin{equation}\tag{1.1.3}
H=\frac{h\_1}{h\_0}
\end{equation}
\begin{equation}\tag{1.1.4}
X=\frac{x}{x\_c}
\end{equation}
\begin{equation}\tag{1.1.5}
T=\frac{t}{t\_c}
\end{equation}
\begin{equation}\tag{1.1.6}
X\_f=\frac{x\_f}{x\_c}
\end{equation}
\begin{equation}\tag{1.1.7}
\lambda=\frac{\mu\_1}{\mu\_2}
\end{equation}
\begin{equation}\tag{1.1.8}
\Delta \rho=\rho\_2-\rho\_1
\end{equation}

calculating,

* $\lambda=$ 1.156 × 10 3 Pa $\cdot$ s
* $\Delta \rho=$ 0.26 g cm 3)
* $x\_c=\frac{1.1674\times10^{-6}}{q}$ m
* $t\_c=\frac{8.7555\times10^{-10}}{q^2}$ s

**Early Time** (T << 1)

In the early time period, i.e., T << 1, the horizontal length of the current x << xc, or equivalently, X << 1.

So, the advective term is negligible compared with the diffusive term. In addition, in the early time period, both H <<1 and |($\lambda$ −1)H| << 1 hold such that the current is effectively unconfined. Then, the advection-diffusion equation is reduced to a nonlinear diffusion equation, which describes the spreading of a viscous gravity current on an impermeable horizontal substrate,

\begin{equation}\tag{1.1.9}
H(X,T) \approx 1.6679 \left(1-\frac{X}{0.8 T^{\frac{4}{5}}}\right)^{\frac{1}{3}}T^{\frac{1}{5}}
\end{equation}

Setting H=0, we get

\begin{equation}\tag{1.1.10}
X(T) \approx 0.8 T^{\frac{4}{5}}
\end{equation}

**Late Time**

At longer times, the convective term can no longer be neglected. In the late time period, by neglecting the diffusive term, the full governing equation is approximated by the nonlinear hyperbolic equation. Under the series expansion

\begin{equation}\tag{1.1.11}
\lim\limits\_{H \rightarrow 1^-}\frac{dF}{dH}=\frac{X}{T}=\frac{6}{\lambda}(1-H)+\frac{6(5\lambda-6)}{\lambda^2}(1-H)^2+O((1-H)^3)
\end{equation}

Knowing that $\lambda$ is a large number we choose only the first term.

\begin{equation}\tag{1.1.12}
H \approx 1-\frac{\lambda}{6}\frac{X}{T} \;,\; H \rightarrow 1^{-}
\end{equation}

Setting H=0, we get

\begin{equation}\tag{1.1.13}
X\_f=\frac{6}{\lambda}T
\end{equation}

For higher order terms

\begin{equation}\tag{1.1.14}
\frac{d^2 H(\xi)}{d\xi^2}=10\left(\frac{dH(\xi)}{d\xi}\right)^2
\end{equation}

where,

\begin{equation}\tag{1.1.15}
\xi=\frac{X}{T}
\end{equation}

The plot for the injected fluid length *vs.* time for different time regions is given below.

![Graphical representation of liquid front distance with respect to time.](https://static.igem.org/mediawiki/2021/5/5c/T--IISER-Tirupati_India--Grf.jpg)

Fig 1.3 Liquid front distance with respect to time.

From the above equations, using q=20 mL s− 1 we get

By early time, it can take anywhere from 1.259 or 1.804 seconds for the injected fluid to reach the ampulla.

By the later time, it can take anywhere from 216.711 to 288.948 seconds for the injected fluid to reach the ampulla.

Since, xf < x c we take the early time approximation

#### 1.4 Learn:

As suggested by **Gynecologist Dr Prameela Menon and Prof Debjani Paul** during our iHP meetings, modifying an existing device like an IUD can get complicated and if there exists a method for a similar goal it would be easier to work with. Also, more the modifications in a device, more would be the rise in price of the process and hence not suitable for mass consumption. Another disadvantage of using a modified IUD was that depending on different sizes of the uterus, the ends of the device may or may not reach the fallopian tube entrances on both sides, and the vagina can also get colonised by the GMO.

Other disadvantages:

* The fluid contains the GMO which is in contact with all of the oviduct contaminating the undesirable regions
* The cross-section is too small that surface tension comes into play which isn’t taken into account
* More GMO are needed to account for undesirable colonisation in other regions

A catheter can do fluid injection into the uterine cavity or it can go up to the ostia or even into the fallopian tube itself. The cost goes up as the injection site is closer to the destination (ampulla) but it **minimizes unwanted colonization in other regions**.

### Iteration 2:

#### 2.1 Design:

In this iteration we wanted to explore a design using a catheter with an idea of its prevailing use in the delivery of gametes or zygote during in-vitro fertilization treatments. We wanted to check if we could build upon the idea to **improve this method of delivery** for our purposes. The catheter goes inside the oviduct up to the ampulla. Due to peristalsis and other involuntary actions, the procedure is done under the guidance of a medical practitioner and it involves the application of anaesthesia.

#### 2.2 Build:

After some literature mining during the design phase, we found that the procedure best suited for our purpose is **hysteroscopy under ultrasound sonography (USG) guidance**. We built upon this to find out its working technique. It consists of a catheter of various possible gauges with a camera attached to it for observing the uterine cavity and the ostia of the fallopian tube. Hence we solve the issue of delivering our GMO into different sizes of uteruses using the same device.

After multiple conversations with IVF specialist **Dr Sidra Khot and cardiologist Dr Akbar UL Haque**, we came to a conclusion that to test the working of hysteroscopy, gynecologists, IVF specialists, and other professionals in related fields are familiar and trained with equipment might conduct clinical trials of the whole process which could only be done as a part of the future aspect after developing our GMO. The modification that we would require for our purpose would be that the injected bacteria is light sensitive, hence **light should be used only for guidance, and then the bacteria should be injected under no light**.

#### 2.3 Test

The fallopian tube is a system with multiple species: the number of each individual species and the total number of species will oscillate about a certain equilibrium position.

![Graph showing average population with respect to time y-axis shows bacterial count and x-axis shows time.](https://static.igem.org/mediawiki/2021/d/d8/T--IISER-Tirupati_India--GC_eq.jpg)

Fig 1.4 The average population with respect to time doesn't change even with a small perturbation for long time scales

First, the final population required is figured out using the diffusion and production models of ovastacin. Then using the following assumptions, a system with multiple species is constructed and inoculum calculated.

 Assuming

1. This system is at a stable equilibrium meaning any perturbation of the system will bring it back to the equilibrium. The equilibrium being the carrying capacity.
2. The GMO does not have a survival advantage or disadvantage against normal Lactobacillus.
3. The inner walls of the fallopian tube are smooth.

* $M \rightarrow$ Carrying capacity of the system for all the commensals.
* $N\_0 \rightarrow$ Initial amount of Normal **Lactobacillus acidophilus**
* $N\_f \rightarrow$ Final amount of **Lactobacillus acidophilus**
* $I \rightarrow$ Inoculated/introduced amount of GMO
* $a \rightarrow$ Final amount of GMO which was calculated in Diffusion section in [Model Page](https://2021.igem.org/Team%3AIISER-Tirupati_India/Model#4)

The derivation is based on the steady state achieved by the population after a long time. Since the oviduct is highly competitive we assume that the average proportion of each species is constant. So the ratios are given below as

\begin{equation}\tag{1.2.1}\chi\_1=\frac{N\_0}{M}=\frac{N\_f+a}{M}\end{equation}
\begin{equation}\tag{1.2.2}\chi\_2=\frac{I}{N\_0}=\frac{a}{N\_f}\end{equation}

Assuming the survival factors of GMO and Lactobacillus are the same we continue by cancelling ‘M’ on both sides and substituting for ‘Nf’, Isolating ‘I’ we get,

\begin{equation}\tag{1.2.3}I=\frac{aN\_0}{N\_0-a}\end{equation}

By, [33] the microbe count is 10 8  CFU/mL of oviductal fluid.

In, [34] 1-5% is *Lactobacillus acidophilus*. which gives us 10 6 to 5 × 10 6 CFU/mL

Treating the ampulla as a truncated cone of radii 10 mm and 5 mm of length 5 cm to 8 cm [35]. The volume of the ampulla region of the oviduct is 9.16 to 14.66 mL which means there’s a minimum of 0.92 × 10 7 to 7.3 × 10 7 CFU of  **Lactobacillus acidophilus** in the ampulla.

This gives us ‘I’ to be 6835 to 6830 CFU.

Let the radius of the droplet (rdrop) be 0.75 cm. Hence volume of the droplet is 1.76 mL.

Now calculating

\begin{equation}\tag{1.2.4}\mathrm{The \;number\; of \;transfers\; required\; for\; the\; whole\; ampulla\;}=\frac{L}{2r\_{drop}}\end{equation}

where, L is the length of the ampulla (5 to 8 cm).

The number of such transfers is hence, 6 or 4.

\begin{equation}\tag{1.2.5} \mathrm{The\; concentration\; thus\; prepared\;} = \left(\frac{I}{\mathrm{Number\; of\; transfer\;\; \times\;\; Volume \;of\; droplet}}\right)\end{equation} 644.165 to 966.955 CFU/mL.

To prevent possible blockage saline solution can be used although it was assured to us by the IVF specialist that it’s not likely to happen

If it’s a 0.1 mL droplet ($r\_{drop}=0.288 cm $) then 9 to 14 transfers would be required and 4882.14 to 7588.89 CFU/mL solution would be prepared.

#### 2.4 Learn:

The hysteroscopy procedure inserts the catheter. Since the ostia of the fallopian tube is a dynamical structure, it’s under USG guidance.

![Schematics of the hysteroscopy](https://static.igem.org/mediawiki/2021/1/1b/T--IISER-Tirupati_India--oildrop.svg)

Fig 1.5 Schematics of the hysteroscopy procedure. Refer to the Model page for more explanation.

A solution of GMO is prepared either in **saline (for biosafety) or an oil sono-opaque transfer**, which can help locate the injected fluid’s presence. 2.9 mm is the hysteroscope diameter, and injectable volume will be 2-3ml, using air as the pushing entity. Based on current assumptions, **$\approx$ 103 CFU/mL** inoculum concentration of bacterial fluid is needed using air is used to push out the 1.76 mL of a droplet containing the bacteria under USG guidance multiple times (usually 4 to 6 times) as much as it’s desired.

Now that the delivery of GMO has a clear picture, we move on to focus on the design of the GMO i.e contraception. The modified bacteria must be able to **express ovastacin at the right time**, and there shouldn’t be excess production of the protease. The next iteration discusses how the genetic circuits were modified in order to attain a fairly accurate expression pattern.

## Module 2. Genetic Circuits (Producing ovastacin)

##### **Aim**: To modulate the ovastacin production to avoid fertilization

### Iteration 1:

#### 1.1 Design:

With an aim to design a contraceptive for uterus owners which would be **non-hormonal, long-term, reversible and with minimal side-effects, we chose to target the ovum**. During the hunt for an ovum specific target molecule, it was found that fertilization couldn’t take place in the case of women with mutations in ZP proteins [4]. Hence targeting the zona pellucida could help in preventing fertilisation. Enzymes like trypsin and chymotrypsin can degrade the zona pellucida but they are not specific to zona pellucida protein which might lead to off-target protein or cellular degradation. It was then found that zona pellucida specific proteases are present in the acrosomes of sperms namely, hyaluronidase and acrosin. However, they act on a small area of the ovum which is specifically directed by sperms and the constitutive production and release of these eukaryotic proteases into the fallopian tube environment by bacteria could be a problem.
Another way to prevent fertilisation was to start the cortical reaction and render the ovum hardened to prevent sperm entry. This could be possible with the help of a protease, ovastacin which acts on the Zona Pellucida 2 glycoprotein component of ZP and cleaves it in order to inhibit sperm binding. Having a specific function known only to cleave ZP2 made this an ideal candidate to be used as the contraceptive molecule to prevent fertilisation [6].

Constitutively producing ovastacin can have effects on the body as well as on the metabolism of the bacteria. Hence it would be necessary to regulate the production of ovastacin. In the fallopian tube environment, various ions and metabolites keep changing, but this change in concentration would not be sufficient for any system to properly regulate ovastacin. [7]. Hormones provide an advantage as inducers since they are more linked with the menstrual cycle and are responsible for these changes in the concentration of ions and metabolites. Hormones like luteinizing hormones (LH), follicular stimulating hormone (FSH), progesterone, and estrogen [8] are in sync with the menstruation cycle. Among these hormones, LH and FSH are secreted by the anterior pituitary and, with the help of blood circulation, reach the ovaries, which is their main target organ [9]. Since they have no significant role in the fallopian tube, they are not present in abundance to act as inducers for ovastacin regulation. Now using estrogen or progesterone, the ovastacin could be regulated with the help of some specific hormone sensing systems.

#### 1.2 Build:

As per the planning in design, progesterone and estrogen sensing systems in bacteria were looked into. One of them was the mifepristone (progesterone antagonist) inducible system composed of the DNA-binding domain of lexA gene from *E. coli*, progesterone receptor from *Homo sapiens*, and transcriptional activation domain from the *Homo sapiens* RELA gene [10]. It was later confirmed from literature studies that this system was still not suitable for regulating ovastacin as it can act on mifepristone and not progesterone. Hence more systems were looked into and an **allosteric transcription factor namely SRTF1** which represses gene expression in absence of progesterone seemed suitable [11,13]. With simple control on ovastacin production with the help of SRTF1, a system was prepared such that it starts producing ovastacin when progesterone concentration rises in the fallopian tube and ovulation has occurred simultaneously. Since there is no control on ovastacin production during the follicular phase due to the absence of progesterone a repressor known as P22 C2 repressor [14] was simultaneously produced with ovastacin in order to inhibit ovastacin and itself for a short period of time acting as a negative feedback loop.

[

](https://static.igem.org/mediawiki/2021/0/03/T--IISER-Tirupati_India--Engsucc.mov)

Working of the genetic circuit for ovastacin production and hormone sensing

Before testing the system we got some feedback from experts, **Dr Satish Gupta** notified that the progesterone onset post ovulation is minimal and advised to check if the sensitivity of SRTF1 is enough to induce ovastacin production.

Consequently, we tried to find out the sensitivity of SRTF1 towards progesterone concentration and guessed that there could be a delay in the induction of ovastacin production.

**Dr Prameela Menon** also brought up the concern addressing the progesterone-induced ovastacin production, as the fertilisation window of the ovum is short. Even if the progesterone sensing molecule is sensitive to a low concentration of progesterone, under any circumstances, if there’s a late expression of the hormone, it may lead to the fertilisation of the ovum.

#### 1.3 Test:

To be able to answer these questions we tested the system with the help of mathematical modelling.

The ODEs of this progesterone inducible system were built and the expression of ovastacin was checked. Following are the equations describing the above genetic circuit.

**Progesterone production:**

\begin{equation}\tag{2.1}\frac{\mathrm{[P\_{r}]}}{dt}=p(t)-k\_{dpr}[P\_r]-\frac{[S][{P\_r}]}{K\_D’}\end{equation}

**SRTF production:**

\begin{equation}\tag{2.2}\frac{\mathrm{d}[S]}{\mathrm{d} t} = k\_p - k\_d [S] - \frac{[S][P\_r]}{K\_D’}\end{equation}

**Ovastacin production:**

\begin{equation}\tag{2.3}\frac{\mathrm{d} [O]}{\mathrm{d} t} = k\_{p}'\frac{K\_D^2}{K\_D^2 + [S]^2} \frac{K\_{D}^{2'}}{K\_{D}^{2'}+[P\_{22}]}- k\_{d}' [O]\end{equation}

**P22 production:**

\begin{equation}\tag{2.3}\frac{\mathrm{d} [P\_{22}]}{\mathrm{d} t} = k\_{p}''\frac{K\_D^2}{K\_D^2 + [S]^2} \frac{K\_{D}^{2'}}{K\_{D}^{2'}+[P\_{22}]}- k\_{d}'' [P\_{22}]\end{equation}

Solving these equations using MATLAB ODE solver, the following graph was obtained.

![Graph showing ovastacin production over a month, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/c/c6/T--IISER-Tirupati_India--projind.png)

Fig 2.1. Ovastacin Production Over a Month

###### MATLAB File

[Download](https://static.igem.org/mediawiki/2021/1/15/T--IISER-Tirupati_India--projinducible.zip)

The graph obtained showed increased production of ovastacin after ovulation and almost after the fertile window of the cycle. This tells us that the progesterone surge is delayed for this model, hence an alternative had to be figured out.

After getting suitable results, we built a P43+ovastacin cassette with which we wanted to produce ovastacin to get our recombinant protein for further assays to check the functionality of the protein via our experiments . We carried out the cloning procedure using Golden Gate assembly and transformed our plasmid in *E coli* NEB10𝛃. Then we performed a colony PCR with the transformants, however we couldn’t get suitable transformants as we suspected there might be experimental errors during cloning or transformation. We are troubleshooting this experiment further.

#### 1.4 Learn:

Protease production is required at least for a week's interval taking into account three days pre and post-ovulation which is usually considered as the fertile window. Progesterone levels rise after ovulation, hence ovastacin production takes longer than the assumption taken while designing. This is why the above system needed to be modified such that ZP2 can be hardened in time [15].

### Iteration 2:

#### 2.1 Design:

From what we learned it was clear that progesterone induction would not be able to regulate ovastacin properly. Hence another inducible system based on estrogen might work but still, estrogen surge comes twice which would lead to a tightly regulated inducible system. If no suitable system is found, alternatively, the effect of progesterone could be changed to repressible in order to regulate ovastacin.

#### 2.2 Build:

Estrogen biosensors had been worked upon in the past by Team: Carnegie\_Mellon in iGEM 2015 [12]. It was designed using the fusion of T7 polymerase and estrogen receptor such that T7 polymerase undergoes conformational changes and gets activated inducing gene expression in presence of estrogen. But their results showed that even though the biosensor increases production of the downstream gene in presence of estrogen, there was leaky expression of the gene even in absence of estrogen. This meant that ovastacin production would just get upregulated with an increase in estrogen level, which would not act as a perfect regulatory system in our design.

Unable to find a well-characterized and sensitive estrogen biosensor that could regulate ovastacin production, the circuit was modified with the help of a P22 repressor to make it an inhibitory circuit as shown below:

[

](https://static.igem.org/mediawiki/2021/2/2f/T--IISER-Tirupati_India--Ovastacin_Progesterone.mov)

Working of the genetic circuit for ovastacin production and hormone sensing.

Now, this system can regulate ovastacin to be present during the fertile period since ovastacin is now negatively regulated by progesterone due to indirect interference.

#### 2.3 Test:

The main focus was to get enough expression of ovastacin before ovulation so that it can harden the zona pellucida. This newly constructed genetic circuit was studied, and equations of production were written. While doing so, an inhibitor of ovastacin known as fetuin B was also considered. Fetuin B is known to act as an antagonist inhibitor of ovastacin in order to prevent pre-fertilization hardening of the ovum due to leakage of ovastacin from the cortical granules [16]. On considering these factors and progesterone variation the following graph was obtained.

![Graphical representation of first cycle after GMO delivery. Graph showing ovastacin production over a month, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/6/61/T--IISER-Tirupati_India--Module2graph2.png)

Fig 2.2. Ovastacin production over a period of (first) month after GMO delivery.

![Graph showing ovastacin production after the first month, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/8/89/T--IISER-Tirupati_India--Module2graph3.png)

Fig 2.3. Ovastacin production over a period of any month after the first menstrual cycle.

Apart from the above model, we built the **SRTF1+mCherry and P22 repressor+Azurite** cassettes with which we wanted to check the progesterone repressible system in our experiments. SRTF1 is expressed under a constitutive promoter SP126. Therefore, relatively higher red fluorescence will be detected in the plate reader as there could be a leaky expression of the Azurite blue fluorescence protein. While in the presence of progesterone, SRTF1 binds with progesterone. Due to which the binding of SRTF1 to the operator region of the P22 repressor cassette is hindered. This hindrance increases the expression of the P22 repressor protein. Therefore, in the presence of progesterone, two different fluorescence will be observed. In the plate reader, the red fluorescence of mCherry and the blue fluorescence of Azurite will be detected in the absence of progesterone. We used the Golden Gate assembly to prepare our clones and transformed *E coli* NEB10𝛃. We then conducted colony PCR of the transformants to get our desired colony. **We could confirm the results of this using fluorescence microscopy and plate reader at various concentrations of progesterone**. To know more [See Results](https://2021.igem.org/Team%3AIISER-Tirupati_India/Results#5)

#### 2.4 Learn:

Looking at the above graph, we can observe how fetuin B levels don't affect the ovastacin concentration and ovastacin production can be seen from day 11 to day 17 of the cycle. The only minor concern is to avoid the production of ovastacin during the first 10 days of the cycle.

### Iteration 3:

#### 3.1 Design:

Now to overcome the production of ovastacin before the fertile period the system should either be more tightly regulated by progesterone or regulated by both estrogen and progesterone.

#### 3.2 Build:

Inteins are protein elements that get removed from the protein after translation by itself and ligate the remaining protein (protein splicing). Our further literature hunting made us realise that an estrogen-sensitive intein could be used to regulate ovastacin in absence of progesterone. While building upon this idea, we found a study which showed that, if a chimeric estrogen-sensitive intein was designed with N and C-terminal of *lacZ* was fused with N and C-terminal of this intein, this would lead to formation of an inactive 𝛃-galactosidase. This inactive form of the protien can get activated by protien splicing in presence of 𝛃 estradiol [17].

Using this intein and replacing *lacZ* with ASTL gene (codes for ovastacin) would mean that ovastacin would be produced in an inactive form and it could only become active when estrogen levels increase in the system as shown below:

[

](https://static.igem.org/mediawiki/2021/2/21/T--IISER-Tirupati_India--intein.mov)

Working of Intein protein circuit.

This can provide the advantage of producing active ovastacin only in the fertile period. Now that a regulated production of ovastacin has been designed, the reversal of contraception is addressed in the next iteration.

## Module 3A. Kill Switch for Reversibility

**Aim:** To reverse the contraceptive

### Iteration 1:

#### 1.1 Design:

Inducer:

To reverse the effects of contraception, one way could be to remove the source of contraception that could be achieved by **inducing apoptosis**. Hence a kill switch based on inducer with the following properties was needed:

* Not present in the fallopian tube in order to avoid accidental death of the genetically modified commensal
* **Non-toxic** to the user
* Have a well-characterized system for the given inducer
* Should be removed from the fallopian tube in order to avoid any change in the system due to the inducer

Monosaccharides like xylose are not known to be present in the fallopian tube. They can be consumed by bacteria preventing them from remaining in the environment and do not pose any harm to the user. The presence of operons working on various monosaccharides provides the necessary elements required for an inducible system to perform the required function.

*Toxin:*

Now in order to kill the bacteria, an efficient toxin needs to be induced by the inducer. Most toxins either lyse the cells which can lead to horizontal gene transfer due to the release of DNA in the environment or just inhibit major cellular function inducing stasis. Hence, a better method for killing the genetically modified bacteria is required to prevent horizontal gene transfer.

*Need for anti-toxin:*

Most inducible systems are leaky which can lead to the accidental death of the GMOs. This also burdens the system with natural selection that can lead to the presence of some genetically modified bacteria with non-functional toxins. Hence regulating the leakiness stabilizes the system for long-term usage.

#### 1.2 Build:

*Inducer:*

pxylA, a xylose inducible promoter induces the production of toxin.

*Toxin:*

There are a variety of toxin-antitoxin systems present in *Bacillus subtilis* [1].

Toxins from Type 1 toxin-antitoxin system:

* txpA/RatA
* bsrG/SR4
* bsrE/SR5
* yonT-yoyJ/SR6
* bsrH/as-bsrH

All these toxins contain transmembrane domains and are able to bind to the membrane and cause cell lysis [18].

Toxins from Type 2 toxin-antitoxin system:

* SpoIISA (YkaC)/SpoIISB or SpoIISC
* NdoA (YdcE, MazF)/NdoAI (YdcD, MazE)
* YqcG/YqcF
* YokI/YokJ
* YobL/YobK
* YxiD/YxxD
* YeeF/YezG

Initially, ydcE was chosen as the toxin which is an endonuclease that cleaves UACAU-rich genes’ mRNA leading to inhibition of cell growth [19,20,21] due to a decrease in some specific proteins due to their mRNA destruction.

Among other options, bsrE and bsrG both lyse cells but are also dependent on various factors that affect their proteins and mRNA.

One of the other toxins **yqcG** which is an **endonuclease that cleaves DNA** [18] was chosen as the most suitable option available. This is because it leads to fragmentation of DNA into smaller fragments which results in apoptosis. It also potentially prevents transfer of DNA to other bacteria and reduces the chances of horizontal gene transfer [22,23].

Combining all these factors the following genetic circuit was build:

[

](https://static.igem.org/mediawiki/2021/e/e1/T--IISER-Tirupati_India--Xylose.mov)

Working of Xylose inducible kill switch.

[

](https://static.igem.org/mediawiki/2021/0/0a/T--IISER-Tirupati_India--dnadegxylose.mov)

DNA degradation due to Xylose uptake

#### 1.3 Test:

To check that the efficiency of our genetic circuit design, the variables and parameters were identified. Starting from xylose, its diffusion inside the bacterial cells is taken into account using Michaelis-Menten equation. Using this time-dependent equation based on total xylose concentration, the equations for XylR, toxin and antitoxin are obtained. The constants in the equations include promoter based transcription rate of the gene cassettes. The strengths of all three cassettes were varied and the protein production graphs were obtained.

Using initial assumptions for promoter strengths, the following graph was obtained.

**Test 1**

A. Before xylose induction, there would be continuous XylR and antitoxin production. Whereas toxin production should be minimal, and any leakage would be taken care by the antitoxin.

![Graph showing scenario of before Xylose induction, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/8/81/T--IISER-Tirupati_India--ecks1.png)

Fig 3.1 Before xylose induction.

B. Post xylose induction, the XylR and antitoxin concentrations should drop while the toxin concentration should increase.

![Graph showing scenario of post xylose induction, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/3/3a/T--IISER-Tirupati_India--ecks2.png)

Fig 3.2 Post xylose induction.

###### MATLAB File

[Download](https://static.igem.org/mediawiki/2021/8/81/T--IISER-Tirupati_India--killswitch_ec.zip)

The above graph shows that the production rates of all the genes inside the cell is too high compared to the rate of xylose uptake by the bacterial cell. **Hence the production rates were reduced and since the toxin levels must rise higher than antitoxin for the kill switch to be effective, the relative strengths were varied to obtain the expected graph nature.**

**Test 2**

A. In absence of xylose, as the graph shows, xylR is taking longer to rise and prevent toxin production.

This is why toxin levels rose more than antitoxin in the first few hours, increasing the risk of bacterial death without induction. To overcome this problem it was decided that xylR can be expressed before toxin-antitoxin genes.

![Graph showing XylR expression before toxin - antitoxin expression, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/b/bb/T--IISER-Tirupati_India--xylr.svg)

Fig 3.3 XylR expression before toxin-antitoxin expression.

B. In absence of xylose and XylR continuously produced before the toxin-antitoxin system is introduced. The toxin levels are maintained below anti-toxin concentrations.

![Graph showing toxin - antitoxin expression before xylose induction, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/d/d5/T--IISER-Tirupati_India--Module3_graph_1.png)

Fig 3.4 Toxin-Antitoxin expression before xylose induction.

C. After xylose induction, toxin levels rise and antitoxin levels reduce. According to the assumption that when the toxin is greater than antitoxin levels and after 5 hours of continuous production bacterial lysis shall take place.

![Graph showing toxin-antitoxin system after xylose induction, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/7/76/T--IISER-Tirupati_India--Module3_graph_2.png)

Fig 3.5 Toxin-antitoxin system after xylose induction.

###### MATLAB File

[Download](https://static.igem.org/mediawiki/2021/7/7a/T--IISER-Tirupati_India--killswitch.zip)

#### 1.4 Learn:

The above graphs closely resemble the way kill switches should work, but it is safer to have toxin levels at zero before xylose induction. This could be achieved by increasing the **rate of xylose uptake** by bacterial cells. Hence, if found to or adapted to faster uptake of xylose then the kill switch shall be more accurate at its work.

Also, **Dr Brenda Wilson** explained that a toxic shock from the endotoxins is possible. The alternatives to the kill switch she suggested were using antibiotics and replication inhibitors called Psoralen. Hence, this could be a viable option for future aspects of this project.

## Module 3B. Kill Switch for Biosafety

Aim: To avoid biocontamination by the GMO

### Iteration 1:

#### 1.1 Design:

To kill bacteria as it comes in contact with the environment, **natural conditions need to trigger apoptosis**. For this, the candidates were auxotrophs, temperature, pH, and light.

Auxotrophs pose a stability threat to the population of genetically modified bacteria and there is no guarantee that there would be no horizontal gene transfer between them. The temperature being a good option wasn’t the same at all times and at all places so depending on the temperature wasn’t good either. Now pH changes from acidic (approximately 4.4) in the lower reproductive tract and towards the alkaline side (approx. 7.9) in the upper reproductive tract [24] this could have worked but our transportation of bacteria was also through the vagina. Moreover, the pH of sewage is also alkaline (7.82) [25] meaning if they get flush out there are still low chances that acidic pH alone could work as a kill switch inducer. Now our last candidate light showed a universal effect as light is present even when the sun goes down thanks to advancements in technology. Since not all spectrums of light can penetrate our body hence it will not be able to induce death accidentally (keeping in mind choosing the right spectrum). Hence a light-activated system or inactivation system could work to regulate apoptosis.

From the previous module, it was learned that a toxin-antitoxin system or equivalent is required in order to maintain the kill switches/toxins. So a similar system needs to be built for biocontamination as well.

#### 1.2 Build:

Among various light-inducible systems ranging from repressors, activators to receptors [26], a **blue light receptor** present in *Bacillus subtilis* known as YtvA seemed perfect for the job. YtvA gets activated by the blue light of the visible spectrum and upregulates SigB which is responsible for regulating the activity of promoters that are dependent on sigB, a transcription factor. (see figure). After looking into ytvA more, a previous team (iGEM08\_Imperial\_College) had also used ytvA with the promoter of gsiB[26,27]. For this, we had **Bovine pancreatic DNase 1** which was also used by iGEM20\_IISER-Tirupati\_India with greater efficiency even at lower concentrations. Now we needed to check the levels of Bovine pancreatic DNase 1 which could be achieved by fusing it with a protein degradation tag of mf-Lon. This protease can degrade a protein if it has a specific tag attached to it letting us control the levels of our Bovine pancreatic DNase 1 [28].

[

](https://static.igem.org/mediawiki/2021/0/0d/T--IISER-Tirupati_India--Lightinducible.mov)

Working of light-inducible kill switch.

![Cascade reaction initiated by active YtvA](https://static.igem.org/mediawiki/2021/e/e2/T--IISER-Tirupati_India--activation.png)

Fig 4.0 Cascade reaction initiated by active YtvA

[

](https://static.igem.org/mediawiki/2021/0/02/T--IISER-Tirupati_India--dnadeglight.mov)

DNA degradation due to light

#### 1.3 Test:

Using the selected components YtvA, SigB, bp DNase, and mf-Lon a genetic circuit was constructed for the kill switch. For testing, this system can be divided into three parts:

1. YtvA activation
2. YtvA to SigB activation- SigB to toxin production and cell death.

When illuminated by light, YtvA undergoes a cycle consisting of three states namely dark state, excited state, and light-induced signaling state. (figure)

The **light-induced signaling state** is known to act on the stressosome complex leading to a cascade of reactions for SigB activation.

First, we wrote the equations for YtvA activation and tried to get its graphs after light illumination.

##### A. YtvA System

1. YtvA production in absence of light i.e. when the GMO is inside the body there would be continuous production of YtvA with little to no toxin production.
![Graph showing Ytva production over a span of 10 days, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/a/a2/T--IISER-Tirupati_India--ytva_dark_state.png)

Fig 4.1 YtvA production.

###### MATLAB File

[Download](https://static.igem.org/mediawiki/2021/5/5f/T--IISER-Tirupati_India--ytva_darkstate.zip)

2. YtvA activation, in presence of light YtvA enters the cycle of three states as shown in the graph below.
![Graph showing Ytva activation over a span of 6 seconds, the y-axis shows the concentration of different proteins in nm and x axis shows time in seconds.](https://static.igem.org/mediawiki/2021/b/b0/T--IISER-Tirupati_India--ytva_light_induced.png)

Fig 4.2 YtvA activation.

###### MATLAB File

[Download](https://static.igem.org/mediawiki/2021/7/77/T--IISER-Tirupati_India--ytva1.zip)

The enlarged version of the above graph (Fig4.2) shows that the light-induced signaling state does not go to zero. Hence it then moves on to the second part of the model that is SigB activation.

First, the stoichiometric relations of all the reactions were determined. Using these and the **Michaelis–Menten kinetics**, an equation for SigB production was written. This equation along with the toxin-antitoxin system was then used to get the following graphs.

##### B. Toxin-antitoxin system

1. In absence of light, there would be no SigB production and the system would look like the following graph.

![Graph showing toxin-antitoxin system in absence of light over a span of 10 days, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/7/7a/T--IISER-Tirupati_India--bs2.png)

Fig 4.3 Toxin-antitoxin system in absence of light.

2. In the presence of light, SigB production takes place inducing toxin production.

![Graph showing toxin-antitoxin system in presence of light over a span of 2 days, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/e/e7/T--IISER-Tirupati_India--bs3.png)

Fig 4.3 Toxin-antitoxin system in presence of light.

###### MATLAB File

[Download](https://static.igem.org/mediawiki/2021/e/e6/T--IISER-Tirupati_India--Biosafety1.zip)

#### 1.4 Learn:

YtvA production, its activation, sigB production and the toxin-antitoxin production are all linked. Hence the relation between one, YtvA system and two, toxin antitoxin system graphs from above had to be deduced in order to get a combined graph.

### Iteration 2:

#### 2.1 Design:

The general stress response that leads to SigB activation involves a reaction cascade triggered by the signaling state of YtvA.

The reaction cascade was studied in detail to find the interactions of all the molecules involved in SigB activation [29-32]

Substrate or the stressosome was taken as [RsbR40RsbS20RsbT20] = [C]

Here, this complex is formed with RsbR: the stressosome sensor protein, RsbS: the scaffold protein and RsbT: the protein kinase. The protein kinase phosphorylates the other two proteins and dissociates from the complex. RsbT binds to RsbV a phosphatase to stimulate its activity towards RsbV, an anti-sigma antagonist. RsbV binds to the regulatory protein RsbW to free the SigB that it’s bound to otherwise.

All these molecules are written as,

Table 1: Proteins involved in SigB activation.

| **Protein Molecules** | **Representation** |
| --- | --- |
| Phosphorylated RsbR and RsbS | [P] |
| [RsbT] | [T] |
| Dimer of RsbU | [U2] |
| Phosphorylated RsbV | [V'] |
| RsbV | [V] |
| RsbW | [W] |
| SigB | [B] |
| YtvA in light-induced signaling state | [S2] |

Reactions:

[C]+**[S2]** $\longrightarrow$ [P]+**[S2]**+20[T]

20[T]+20[U2] $\longrightarrow$ 20[U2T]

20[U\_2]+20[V’] $\longrightarrow$ 20[U\_2T]+20[V]

5[W4B2]2+40[V] $\longrightarrow$ 20[B]+5[W4V2]2

#### 2.2 Build:

We used the above set of reactions along with the Michaelis-Menten equation to connect all the three parts to obtain the ODEs as shown in [mathematical modelling](https://2021.igem.org/Team%3AIISER-Tirupati_India/Model#8).

Since the design of the system does not change, only the turnover number (Vmax = ktn x [S]) of YtvA comes into the picture, it helps combine both the systems of equations. The Sig B production would now depend on the concentration of light-induced signaling YtvA.

#### 2.3 Test:

Solving all the equations together, the following graphs are obtained

A] In absence of Light, no Sigma B production.

![Graph showing biosafety system before light illumination over a span of 20 days, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/c/c4/T--IISER-Tirupati_India--biosafety3.png)

Fig 5.1 Biosafety: System before light illumination.

B] In the presence of light, sigma B production takes place inducing toxin production.

![Graph showing biosafety system after light illumination over a span of 4.5 days, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/4/4c/T--IISER-Tirupati_India--biosafety5.png)

Fig 5.2 Biosafety: System after light illumination.

Bovine pancreatic DNase takes over the mf-Lon concentration within 10 seconds after light induction.

###### MATLAB File

[Download](https://static.igem.org/mediawiki/2021/6/68/T--IISER-Tirupati_India--Biosafety2.zip)

#### 2.4 Learn:

This bp DNase degrades the DNA by digesting its phosphodiester bonds, so the concentration of DNA shall reduce eventually. To check the effect of Bovine DNase on the DNA concentration, their graph was obtained and is shown below[33].

![Graph showing biosafety action of DNase on DNA concentration over span of two days, the y-axis shows the concentration of different proteins in nm and x axis shows time in days.](https://static.igem.org/mediawiki/2021/3/30/T--IISER-Tirupati_India--Last_graph.png)

Fig 5.4 Biosafety: Action of DNase on DNA concentration.

###### MATLAB File

[Download](https://static.igem.org/mediawiki/2021/0/04/T--IISER-Tirupati_India--dnabovine.zip)

This shows the effect of Bovine DNase on the DNA concentration inside the cell, as the concentration reduces as the cell starts dying. The DNA concentration does not go negative, the minimum it can go is up to 0. We conclude this cycle, with the help of all the above graphs that show how this system could work i.e. as blue light falls on the bacteria, bp DNase levels grow as a result of which DNA concentration reduces.

![Diagrammatic representation of Yeast genetic circuit](https://static.igem.org/mediawiki/2021/e/ed/T--IISER-Tirupati_India--Legends.jpeg)

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33. Damage to oviduct organ cultures by Gardnerella vaginalis,Species specificity of attachment and damage to oviduct mucosa by Neisseria gonorrhoeae
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##### Side Effects of Current Methods of Contraceptives.

* Cancers: Studies link a high risk of breast and cervical cancer for women taking oral contraceptive pills, while there is reduction in risks of endometrial, ovarian, and colorectal cancers.
* Ovarian cysts: About 1 out of 10 women will get these fluid-filled sacs in their ovaries in the first year after they get an IUD. Cysts usually go away on their own within three months.
* Cardiovascular diseases: A rise of 20-30% in arterial plaque was found in two big arteries for each decade of using birth control pills. For women who take a traditional combination pill with a low dose of estrogen, the risk of heart attack increases by 80% for them.
* Depression: Use of hormonal contraception, especially among adolescents, was associated with subsequent use of antidepressants and the first diagnosis of depression, suggesting depression as a potential adverse effect of hormonal contraceptive use.
* Migraines and headaches: In women who are not taking hormonal contraception, estrogen withdrawal during the late luteal phase is a well-recognized trigger of headaches and menstrual migraines

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# Team:IISER-Tirupati India/Experiments

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## Introduction

Natural systems are highly complex to understand as well as to experiment with. To make predictions of the outcomes,
we use the available information and the knowledge of physics, mathematics, chemistry, and computer science to build a theoretical model. This page deals with the models built on the different aspects of our project namely :

1. GMO delivery
2. GMO growth and colonisation
3. Protease production
4. Diffusion and ovum Hardening
5. Kill switch for reversibility
6. Kill switch for Biosafety

## Delivery & Colonisation

### INTRODUCTION: THE JOURNEY OF GMO BEGINS

#### PART A: Delivery

##### OVERVIEW

Delivery is an essential part of our project as it determines the audience we reach. We tried to develop multiple
ways to deliver GMO in a user-friendly way with minimum invasion. Minimum invasion means it should not colonize
the whole reproductive tract or reach the ovaries. The device should ensure bacterial colonization in the ampulla
of the fallopian tube.
One of the constraints that we faced is the high viscosity of the oviductal fluid.

After calculating the time taken for delivery in each method, talking to a couple of IVF experts, and getting their
inputs into it,we thought hysteroscopic techniques would be the best for our purpose. This method gives us an advantage
by delivering the bacteria directly into the ampulla region.

##### DEVICE DESIGNING (How to deliver?)

GMO will be delivered directly to the ampulla by a process called Hysteroscopy. It’s done with medical assistance and requires
constant X-Ray monitoring to ensure the catheter is inserted without any issues. The reason is that the Ostia and the Fallopian
tube are dynamic structures and that there is no chemical or significant physical difference between the ampulla and the other
components of the Fallopian tube.

A solution of GMO of a specific concentration is prepared. Then the catheter is inserted under medical guidance up to the ampulla.
Then an injector is projected with narrow long incisions on both sides of it, which ensures that the GMO forms a ring along the
circumference of the tube. Ovum is now
360° surrounded by the GMO.

The GMO Lactobacillus Acidophilus has pili which expectantly forms hydrogen bonds at the tube circumference with mucin found in mucus.
The GMO is now adhered to the walls and multiplies once it adjusts to the introduced environment (lag phase)

##### FUTURE ASPECTS:

Since we aim to reach a larger population, the hysteroscopic technique, we believe, is too expensive.
We also considered using hydrogels for the delivery of bacteria at a pH-specific region.

Why is this system compatible with the delivery of bacteria in the ampulla of the Fallopian tube region?

We found out that the pH in the oviductal Ampulla region is close to 8.0.
That’s why we considered using hydrogels for bacterial delivery, which swells up at a pH range of 7.8 to 8.0.

Amongst the stimuli-responsive hydrogels, pH-sensitive hydrogels are the most studied hydrogels. The rate at
which hydrogels respond depends upon their size, shape, cross-linking density, number of ionic groups, and composition,
which can be tailored by varying these factors. The response rate increases with increasing pore size and number of ionic
groups and decreasing their size and cross-linking density.

For a delivery in a basic medium, we planned to use anionic hydrogels, such as carboxymethyl chitosan, which swell at higher
pH (basic medium) due to ionization of the acidic groups. As a result, the ionized negatively charged pendant groups on the
polymer chains cause repulsion leading to swelling. This property of hydrogels can be exploited for GMO delivery at pH 7.4
in the ampulla of the fallopian tube.

##### CELL ENCAPSULATION (What to deliver?)

Our goal is to design a live-bacteria entrapment system. More than just encapsulating bacteria, we want to entirely prevent
their escape from the bead body into the surroundings.

The Oviductal Fluid is slightly alkaline (ph 7.4 to 7.7), so we need our encapsulating membrane to dissolve away at this pH.
Potential candidates for hydrogel materials include chitosan, guar gum, and xanthan. Chitosan forms Hydrogen bonds with the
mucin protein in the mucus allowing for the anchoring at the walls and preventing the hydrogels from getting washed away.

#### PART B: Colonization

##### OVERVIEW (why is it necessary to study growth and colonization)

In biosynthesis, growth kinetics is a crucial study to be conducted. The growth of a cell comprises both the size and the number.
These growths are affected by external factors such as temperature, the chemical composition of the growth nutrient, etc., and by
different physiological factors such as growth factor proteins[1][2]. The cells in a particular environment extract the nutrients
from the growth media and produce biomolecules, which humans utilize for different purposes. This phenomenon has applications, from
producing delicious Italian wine to getting antibiotics which saves millions of lives every year. We will be using this simple
formula to reach the goals of our project. To have a qualitative understanding of the protein production by the Genetically Modified
anism(GMO), we need to have a theoretical approach. We need to understand how we can calculate the growth of GMOs [3]. This, in turn,
will help us figure out protein production. This detailed study of growth kinetics will help us calculate the initial inoculation
required for the production of a protein that we need.

For a better understanding, we will be considering two cases. The first comprises the study of the growth of Bacillus Subtilis in
normal petri dish conditions. This is the known environment and we can have this condition easily in computer simulation and/or lab
and reconfirm our model. The second case of study is the continuous culture model where we study the growth of Lactobacillus
Acidophilus in the fallopian tube, which is our target region.

###### GROWTH MODELS

PETRI DISH MODEL (Bacillus Subtilis, curve fitting)

CONTINUOUS CULTURE MODEL (lactobacillus acidophilus + fallopian tube environment)

##### INOCULUM CALCULATIONS (connection with 2nd module)

## Protease production

### OVERVIEW ( overall picture)

Well known for extracellular protease production[1], Bacillus subtilis is our model organism for the proof of concept experiments. Moreover,
it is a gram-positive bacteria which even if not too close but is closer than e coli (gram-negative) to our proposed bacteria lactobacillus
Acidophilus. This module deals with the whole mechanism of action ideally the GMO must follow for contraception to be attained. To know how
this module developed to what it is, please refer to the engineering success (hyperlink).

Let's create the flow, you must know by now that we plan to produce the protease known as ovastacin,
an indigenous protease[2] to the human ovum. It is known to cause Zona pellucida hardening naturally
used by the ovum to prevent polyspermy[3]. To see the mechanism of zona pellucida hardening click here
(goes to project overview where it is explained).

##### 1] Total amount of ovastacin required:

[We assume one active ovastacin cleaves one ZP2 glycoprotein present in the Zona pellucida matrix. To get the number of molecules of ovastacin needed, we calculated the number of ZP2 glycoproteins present on the surface of the ovum. For this, we reached out to studies that looked at the thickness of the ovum with and without the zona pellucida layer to find its overall thickness and the radius of the ovum[4].

###### Constants and calculations:

| Parameter (need alternative) | Value | References |
| --- | --- | --- |
| Zona pellucida thickness | 18.9 μm | Does zona pellucida thickness influence the fertilization rate? E. Bertrand1 , M.Van Den Bergh and Y.Englert |
| Oocyte diameter | 123.5 μm | Does zona pellucida thickness influence the fertilization rate? E. Bertrand1 , M.Van Den Bergh and Y.Englert |
| Size of ZP2 | 90–110 kDa | Characterization of human zona pellucida glycoproteins A R Bauskin 1, D R Franken, U Eberspaecher, P Donner DOI: 10.1093/molehr/5.6.534 |
| Diameter of ZP2r | 0.0092 μm | Zetasizer Nano Sensitivity Calculator (Classic) |

Assuming cuboid with all spheres of size same as ZP2 to
get volume of one unit = 3.1 e-6 μm3

Volume occupied by whole ZP matrix = 12.4 e5 μm3

Calculated the number of ZP2 glycoproteins present in the ZP matrix = 3.92 x 1011 molecules

Assuming 1 ovastacin cleaves 1 ZP2

No. of ovastacin = No. of ZP2 = 12.4 e5 / 3.1 e-6 = 3.92 x 1011 molecules ]

In order to cause complete hardening \_\_ number of molecules are required to reach the ovum. The next question that arises is how much is produced and how much of produced ovastacin will reach the ovum. So we have two major things left to look at:

##### 2] Production and transport of ovastacin by GMO

The production of ovastacin is required for three days pre and post ovulation, please go to “Genetic Circuits” to learn details regarding the genetic circuit.

#### GENETIC CIRCUIT

Progesterone repressible system

#### JOURNEY OF OVASTACIN

From the papers, we know that the ovum is propelled by the ciliary motion away from the uterus and that means the ovum is in contact with the wall. Thesize ampulla region of the Fallopian tube (2.5 mm ≤ radius ≤ 5 mm ) is much larger than the radius of the ovum (61.7μm) A molecule under the influence of Brownian motion move according to the equation

* < r 2 >= 4Dt (for 2-D)
* < r 2 >= 6Dt (for 3-D)

Where,

* < r 2 > → mean squared (radial) distance travelled by the molecule

using,

1. kB = 1.38064852 ×1023 m2 kg-2 s-1 K [Boltzmann constant]
2. η = 0.799 Pa·s [Viscosity of Oviductal Fluid]
3. T = 35.5 + 273.15 = 308.65 K [Temperature of Oviduct]
4. r = 22kDa = 2.43 nm [Radius of ovastacin molecule]
5. a = 61.7 μm [Radius of the ovum]
6. s = 5 mm [Radius of the ampulla region of the oviduct]
7. N0 = 3.92 ×1011 molecules = 0.000650946529392 nanomoles [Number of ovastacin to react with all ZP2]

For, Ovastacin D=1.1644194699 ×10-13 m2 s-1

* t → Time elapsed

##### INDEX

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* [waste 2](#waste2)
* [waste 3](#waste3)
* [waste 4](#waste4)
* [waste 1](#waste1)
* [waste 2](#waste2)
* [waste 3](#waste3)
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##### Side Effects of Current Methods of Contraceptives.

* Cancers: Studies link a high risk of breast and cervical cancer for women taking oral contraceptive pills, while there is reduction in risks of endometrial, ovarian, and colorectal cancers.
* Ovarian cysts: About 1 out of 10 women will get these fluid-filled sacs in their ovaries in the first year after they get an IUD. Cysts usually go away on their own within three months.
* Cardiovascular diseases: A rise of 20-30% in arterial plaque was found in two big arteries for each decade of using birth control pills. For women who take a traditional combination pill with a low dose of estrogen, the risk of heart attack increases by 80% for them.
* Depression: Use of hormonal contraception, especially among adolescents, was associated with subsequent use of antidepressants and the first diagnosis of depression, suggesting depression as a potential adverse effect of hormonal contraceptive use.
* Migraines and headaches: In women who are not taking hormonal contraception, estrogen withdrawal during the late luteal phase is a well-recognized trigger of headaches and menstrual migraines

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# Team:IISER-Tirupati India/Results

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### INDEX

* [Results of Basic Experiments](#index2)
* [Preparation of competent cells and transformation](#2)
* [Protein Purification](#3)
* [Cloning](#4)
* [Fluorescence assay](#5)

India was gripped by the novel coronavirus in the deadly second wave of the pandemic, earlier this year. This devastating period of the ongoing pandemic delayed our plans and the wetlab team could arrive on campus and get access to the lab only in the last week of July after more than six months of planning the project.

Though we had hardly two months in our hands to achieve our experimental goals, we were determined and hopeful to try and obtain results for our **Proof of Concept**. With ample preparation of protocols, ordering all consumables, discussions with seniors, and advice from our PIs, we thought we were set for all kinds of experiments.

The safety guidelines issued during **the COVID-19 pandemic** also limited our hours of access to the lab. We began with laboratory **safety training** conducted by our technical assistants. The pandemic also significantly delayed the process of acquiring resources including reagents and DNA from our kind sponsors IDT and Twist Bioscience which was a major roadblock for us. We **received our DNA in mid-September** and picked up the pace, only to realise that 2 months of lab access might not be enough to conduct all our experiments.

We had a bunch of successful experiments, but a pile of failed ones as well (that’s how science works, isn’t it?). This page talks about our journey of those **two months in the laboratory** and the amount of background work put together by the entire team to try and actualise OviCloak.

## Results of Basic Experiments

**Our team performed some preliminary experiments in the first few weeks.**

### Growth curves

![Comparison of E.coli DH5-α and B.subtilis 168 curves](https://static.igem.org/mediawiki/2021/d/d2/T--IISER-Tirupati_India--EcoliandBsub.png)

Fig 1. Growth curve of *Bacillus subtilis* 168 (in blue) and E. coli DH5-α (in red)

#### *Escherichia coli* DH5-α

We could observe a trend in the curve and we could use this as a reference for our future experiments. However, the growth curves had unusual data points for the OD at 600 nm when observed at different time points.

We realise that this is not the ideal or the best representation of a growth curve.

#### *Bacillus subtilis* 168

Upon performing a growth curve experiment using *Bacillus subtilis* 168 in LB, we observed an expected sigmoidal pattern of growth. From the graph, we could infer that the bacteria enters the stationary phase after 6 hours from inoculation. Using this value for the stationary phase as a reference, we further performed transformation experiments of *B. subtilis* 168 with our plasmid of interest.

#### *Saccharomyces cerevisiae* S288C

![Comparison of Saccharomyces cerevisiae S288C curves](https://static.igem.org/mediawiki/2021/1/1b/T--IISER-Tirupati_India--Yeast_growth_curve_comparison.png)

Fig 2. Comparison of *Saccharomyces cerevisiae* S288C curves

These 24-hours growth curves of *Saccharomyces cerevisiae* S288C in YPD, show a similar trend of a sigmoidal growth (with a few outliers).

**Important pointers:**

1. **Growth curves need to be standardized by all labs**, even if 2 labs share the same strain of the organism
2. Growth curves are an **easy and effective** way to study the nature and behaviour of an organism in a particular given environment.
3. All the above growth curves were **observed in nutrient-rich media** (LB for bacterial strains and YPD for *S. cerevisiae*)

### Plasmid Isolation

After receiving the *E. coli* clones for ZP2 in pRSET-B vector (generously provided by Dr SK Gupta from NII, India), pDR111 and pDR110 vectors (generously provided by Dr Sabari from IISER Thiruvananthapuram) and the plasmids for pRS426 (generously shared by Dr Vijayalakshmi Subramanian, from IISER Tirupati) our team set forth to isolate these plasmids for our future cloning experiments.

## Preparation of competent cells and transformation

### *Escherichia coli* DH5-α and *Escherichia coli* BL21

We used the chemical competency method to obtain competent *E. coli* DH5α and *E. coli* BL21 cells. We verified the competency of DH5α cells, by transforming empty backbone pDR111 isolated earlier. Likewise to check the competency of BL21 cells, we transformed pRSETB containing ZP2 protein.

![Escherichia coli DH5α Transformants - pRSETB with ZP2 gene](https://static.igem.org/mediawiki/2021/8/8f/T--IISER-Tirupati_India--Transformation_Results.png)

Fig 3. *Escherichia coli* DH5α Transformants - pRSETB with ZP2 gene
Image 1 and 2: Transformants on LB agar plate with Ampicillin
Image 3: a. Top left corner: Control (without DNA) on LB agar plate with Ampicillin ; b. Other 3 plates: Transformants on LB agar plate with Ampicillin

### *Bacillus subtilis* 168

With the *B.subtilis* strain and protocols provided by Dr Sabari, we were able to **successfully transform pDR111 empty backbone** and pDR111 containing genes of interest and **verified genome integration of the antibiotic-resistant gene**.

This protocol for *B. subtilis* exploits the 10xMC media and the natural competency of *B.subtilis* to transform the plasmid of interest.

Here, the plasmid has to be linearised before transformation, because pDR111 is compatible for genome integration.

![Bacillus subtiils 168 Transformants - BBa_B0010 terminator check cassette- Improvement](https://static.igem.org/mediawiki/2021/3/39/T--IISER-Tirupati_India--Transformation_Results2.png)

Fig 4. *Bacillus subtilis* 168 Transformants - BBa\_B0010 terminator check cassette- Improvement
Image 1: Control (Without DNA) on LB agar plate with Spectinomycin
Image 2-6: Transformants on LB agar plate with Spectinomycin

### *Saccharomyces cerevisiae* S288C

We couldn’t perform this experiment due to a delay in the delivery of certain important growth media requirements for culturing this strain.

## Protein Purification

### The mysterious tale of ZP2

Our goal was to **purify ZP2 and ovastacin** during the course of our experiments. Since we had a clone provided by Dr Gupta, we began with our **pilot experiment of IMAC protein purification of His-tagged ZP2** after transforming pRSETB into *E. coli* BL21.

Since the ZP2 protein was cloned downstream to a T7 promoter which is an IPTG inducible promoter, we began by standardizing the amount of IPTG required for induction of the promoter and purification of ZP2.

![IPTG Induction for ZP2 Production](https://static.igem.org/mediawiki/2021/4/41/T--IISER-Tirupati_India--sdspageinduction.png)

Fig 5. SDS-PAGE Gel Image for IPTG Induction
In this gel image wells 1, 2 and 3 have supernatant of 0.5 mM IPTG induced culture, well 4 has supernatant of uninduced cell, well 5 has 10-250 kDa ladder and well 6,7,8 have supernatant of 1 mM IPTG induced cell culture and well 9 has supernatant of uninduced cell

After standardization of induction, we found that the amount of IPTG required was 1 nM for 2.5 hours. This was in accordance with literature that we got from Dr Satish Gupta’s work with the same clones.

We further moved to **purify ZP2 using IMAC for His-tagged ZP2 protein**. The protocol was standardized here as well for binding, washing and elution of the protein.

![ZP2 purified by NiNTA](https://static.igem.org/mediawiki/2021/9/9b/T--IISER-Tirupati_India--SDS_PAGE-NiNTA_purified_ZP2.png)

Fig 6. In this gel, well 1 has a 10-250kDa ladder. While well 2 and well 3 have Elution fraction 1 (with imidazole concentration of 50 mM) and Elution fraction 2 (with imidazole concentration of 150 mM) respectively. In these we can see the bands for our purified eluted protein with His-tag upon IPTG induction.

We went ahead with Immunoblot analysis to verify the presence of His-tagged protein using antibodies.

We found that the **purified protein is more than the expected molecular weight** and tried to troubleshoot our experiments.

![Immunoblot-ZP2](https://static.igem.org/mediawiki/2021/e/ec/T--IISER-Tirupati_India--Immunoblot-ZP2.png)

Fig 7. Immunoblot-ZP2
After performing immunoblotting, well 1 consists of a 10-250 kDa protein ladder. While in well 2 and 3 have Elution fraction 1 and Elution fraction 2. In this blot we can see a band in well 3 at >120 kDa position, which is suspected to be our desired protein ZP2.

To rule out any chances of mutations in the plasmid, we **contacted Dr Gahlay from GNDU, India** who was also using the same ZP2 clones. We obtained another set of the purified plasmid from her and carried out further experiments

We used this plasmid to transform *E.coli* DH5-α to amplify the plasmid and compared it with our previously extracted pRSETB. We further transformed *E.coli* BL21 cells to purify ZP2 protein.

Using the same protocol for induction, we could **observe induction of the promoter** and **expression of the protein**.

![IPTG-Induction-ZP2](https://static.igem.org/mediawiki/2021/8/81/T--IISER-Tirupati_India--IPTG_Induction-_ZP2_clones-Dr_Gahlay.png)

Fig 8. In this gel image, well 1 has uninduced resuspended cell pellet, well 2 has 10-250 kDa ladder, well 3 has IPTG induced cell supernatant, well 4 has uninduced cell supernatant

We went ahead with Ni-NTA IMAC purification of the His-tagged ZP2 and optimization of the protocol is still under progress.

## Cloning *E. coli* and *B. subtilis* (Restriction digestion, Ligation and Gel Extraction)

Once we **received our parts from IDT and Twist in the month of September**, we began to assemble the DNA parts.

Initially we didn't obtain bands of desired sizes on the gel when we began our cloning process with **Golden Gate assembly** and hence we went through several cycles of troubleshooting.

We also discussed the protocol with one of our partners, Team Groningen as they were using the same assembly standards.

After integrating the suggested modifications to our protocol for Golden Gate assembly, **we were able to assemble our desired constructs**.

We made 8 constructs to perform our further assays and transformed these constructs into *E. coli* NEB10-beta competent cells as they’re known to have higher transformation efficiency.

We obtained plates with good number of colonies after incubation following transformation.

For standardization of primers to be used for amplification of genes of interest, we performed gradient PCR. We observed intense bands at temperature **65.6 °C and 68.6 °C**, hence we went ahead with a temperature of **66 °C** for further PCR.

To further confirm the presence of our genes of interest in our obtained colonies, we patched the colonies of these transformants to a fresh plate and performed colony PCR reactions on randomly selected clones.

![Colony PCR standardization with Q5 polymerase](https://static.igem.org/mediawiki/2021/7/72/T--IISER-Tirupati_India--6_q5_standardisation_%2820.10.21%29.png)

Fig 9. Gradient PCR for Q5 polymerase for pDR111 plasmid
with Forward Primer: AAAGGTCATTGTTGACGCGG and Reverse Primer: AAGCCAGGCTGATTCTGACC

Lane 1: 61.1 °C
Lane 2: 61.7 °C
Lane 3: 63.2 °C

Lane 4: 65.6 °C
Lane 5: 68.6 °C
Lane 6: NEB Quick-Load Purple 1kb Plus Ladder

Lane 7: 70.9 °C
Lane 8: 72. 4 °C
Lane 9: 73.1 °C

Upon running the products of PCR reactions on the gel we observed 2 positive clones for one of our constructs.

![Positive clone for Spacer Cassette for Terminator Check](https://static.igem.org/mediawiki/2021/4/4e/T--IISER-Tirupati_India--2_I1_%2Bve.png)

Fig 10. Positive clone for Spacer Cassette for Terminator Check
Lane 1: NEB Quick-Load Purple 1kb Plus Ladder
Lane 3: Positive clone for Spacer Cassette for Terminator Check
Lane 2,4,5,6,7: Negative clones for Spacer Cassette for Terminator Check

![Positive clone for B0010 Terminator Check Cassette](https://static.igem.org/mediawiki/2021/6/60/T--IISER-Tirupati_India--3_improvement_gel-2_14.10.2021.png)

Fig 11. Positive clone for B0010 Terminator Check Cassette
Lane 1: NEB Quick-Load Purple 1kb Plus Ladder
Lane 2,8 : Positive Clones for BBa\_B0010 terminator check cassette
Lane 3-7, 9-11: Negative Clones for BBa\_B0010 terminator check cassette

![Positive clone for SRTF1-P22 combined Cassette](https://static.igem.org/mediawiki/2021/0/0d/T--IISER-Tirupati_India--4_p22srtf_20_to_38_20.10.21.png)

Fig 12. Positive clone for SRTF1-P22 combined Cassette
Lane 1: Positive clone for SRTF-P22 combined cassette
Lane 6: NEB Quick-Load Purple 1kb Plus Ladder
Lane 2-5: Negative clone for SRTF-P22 combined cassette

## Fluorescence assay

### Attempt to Improvement of a part

We purified the plasmid from these colonies and transformed them into *B. subtilis* for fluorescence assay.

![Fluoresence under confocal microscope of B.subtilis 168 with B0010 Terminator Check Cassette](https://static.igem.org/mediawiki/2021/8/89/T--IISER-Tirupati_India--Bsfield1.png)

Fig 13. Field 1:
a. B.subtilis 168 with B0010 Terminator Check Cassette-green fluorescence at wavelength 498 nm (under magnification 100X)
b. B.subtilis 168 with B0010 Terminator Check Cassette in bright field (under magnification 100X)
c. B.subtilis 168 with B0010 Terminator Check Cassette-red fluoresence at wavelength 587 nm (under magnification 100X)

![Fluoresence under confocal microscope of B.subtilis 168 with B0010 Terminator Check Cassette](https://static.igem.org/mediawiki/2021/3/3f/T--IISER-Tirupati_India--Bsfield2.png)

Fig 14. Field 2:
a. B.subtilis 168 with B0010 Terminator Check Cassette-green fluorescence at wavelength 498 nm (under magnification 100X)
b. B.subtilis 168 with B0010 Terminator Check Cassette in bright field(under magnification 100X)
c. B.subtilis 168 with B0010 Terminator Check Cassette-red fluorescence at wavelength 587 nm (under magnification 100X)
d. B.subtilis 168 with B0010 Terminator Check Cassette at wavelength 383 nm (under magnification 100X)

**Under a confocal microscope, we could observe the expression of sfGFP and mCherry and observe their differences in fluorescence intensities signifying that BBa\_B0010 works in *Bacillus subtilis***.

### Progesterone sensing

![Graph of Progesterone sensing in SRTF1-P22 Combined Cassette](https://static.igem.org/mediawiki/2021/b/b8/T--IISER-Tirupati_India--Progesterone_sensing_in_SRTF1-P22_Combined_Cassette.png)

Fig 15. Progesterone sensing in SRTF1-P22 Combined Cassette ( BBa\_K3889100 +BBa\_K388910)

In this graph, SRTF1 cassette (BBa\_K3889100) and P22 Cassette (BBa\_K3889101) were co-expressed in *Bacillus subtilis* 168 consisting of SRTF1 with mCherry reporter and P22 Cassette with Azurite reporter under various concentrations of progesterone.

Unexpectedly, the mCherry expression decreased at higher concentrations of progesterone. Further experimental evidence is needed to determine the cause. Additionally, the Azurite expression increased with progesterone levels signifying that p22 protein production increased. **Hence, this evidence suggests that SRTF1 and SRTF1 DNA binding sites were interacting as expected, and progesterone sensing is taking place in *Bacillus subtilis* 168**.

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##### Side Effects of Current Methods of Contraceptives.

* Cancers: Studies link a high risk of breast and cervical cancer for women taking oral contraceptive pills, while there is reduction in risks of endometrial, ovarian, and colorectal cancers.
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