Welcome to our Human Practices page! Here you will find an overview of our work as well as the details.

Brainstorm

An aging population, predominantly caused by low birth rate, has been harrassing China and other countries worldwide.As an effort to encounter the adversity of reproduction, the SDGs declared to ensure universal access to sexual and reproductive healthcare services by 2030. Therfore, considering the significance and urgency of dealing with human reproductive health issues, we determined to dive into this field and find a way to mitigate present shortages. Through literature research, we found that the quality of male reproductive cells is a major factor concerning fertility. However, not only is sperm quality test underdeveloped, but also it lacks wide public attention. Consequently, many remain untested, which piles on the woes of infertility.Lack of research on sperm quality test in iGEM and even in the field of synthetic biology has prompted us to use synthetic biology to propose a novel solution. We finally narrowed our research direction down to the detection of semen vitality, in the hope that it will contribute to tackle with the imperative human reproductive health issues.

Split up the tasks

In communication with professors in related fields and with researchers from the National Sperm Bank, we learned that current hospital examinations on sperm concentration, motility, and other indicators are still inconvenient and strenuous, which became the objects we want to optimise. Furthermore, we have divided the project into different parts and optimised them separately to achieve an overall perfection.

Adapt to what we learned

As all the team members are undergraduates, we encountered many problems in the practical implementation of the wet and dry experiments. Through initial communication with Peixuan Zheng, we settled on the two-component system to detect the input signals. Through communication with Fang Ba, we were able to use serine integrase to implement logic gating more smoothly. Through communication with Prof. Jinming Lin and seniors such as and Zheni Zeng, we were also able to gradually develop the dry experiment.

Go out of the lab

The goal of our project is to make a chip-based product that users can use at home. In order to get to the heart of the user's needs and found out their willingness to use it, we launched an online questionnaire focusing on the requirements and concern of the public. Their attitudes toward sperm quality test made us more determined to create an expedient testing method and to further consummate our project.

Interview with Lan Xie:

Who are we interviewing?

Lan Xie
Associate Professor, School of Medicine, Tsinghua University

Background

In this high-pressure society, males are suffering from the degeneration of sperm quality. Generally, males can go to the hospital and detect the quality of their sperm. However, a sense of embarrassment and more often nonsense of this problem hinder their travel to the hospital. Moreover, sperm quality can be examined mainly through hospital appointments which are time-consuming and inconvenient. Therefore, our team has proposed a novel diagnostic method to test sperm quality for household use, using microarray chips and bacteria.

Why was this person contacted?

We contacted Ms. Xie when we were still brainstorming about what to focus our project on, and studying the problem of sperm quality test.

What we have learned?

Ms Xie helped us understand how sperm quality test is carried out in hospitals and sorted out the sperm test indicators. She pointed out that biomarker testing is not a mainstream tool nowadays because a single biomarker cannot indicate the fertility of sperm, but a combination of molecular indicators is a good idea. In addition, she opened up the idea of applying the system in other ways.

What question did it raise?

The remaining question was how to choose the biomarkers and how to construct the hardware.

What improvements we have made?

We further contacted Yikun Gu for more details on the current status of sperm quality test and spaces for improvement

Interview with Yiqun Gu:

Who are we interviewing?

Yiqun Gu
National Institute of Health Sciences, Male Clinical Research Unit

Background

Male infertility is a rising problem and the etiology at the molecular level is unclear. There are some report indicate that the glycoproteins on the surface involved in the acrosome reaction can characterize sperm fertility to some extent. However, at present, when hospitals perform sperm quality tests, they basically do not test the biomarkers.

Why was this person contacted?

We contacted Mr. Gu when we were seeking appropriate biomarkers as target proteins. We would also like to get some new ideas from the interview with Mr. Gu.

What we have learned?

Mr. Gu gave us a detailed overview of the current state of sperm testing in hospitals and talked about more questions that could be addressed. He pointed out the problem of false positives that can now occur with SP10 test strips and made suggestions for the design of our hardware. Most importantly, he gave us more examples of biomarkers to choose from, which helped us to improve our project.

What question did it raise?

How can our product made to be multiplex, high sensitivity, high specificity, low price, and less time consuming. Storage conditions also needed to be considered.

What improvements we have made?

We finally identified SP10 with EGFR as the target protein. And we have further considered convenience in our hardware design and kept costs as low as possible. See https://2022.igem.wiki/tsinghua/hardware.

Interview with Peixuan Zheng:

Who are we interviewing?

Peixuan Zheng
The leader of NEU_CHINA iGEM2020

Background & Why this person was interviewed

When we chose sperm quality test to set up our project and began to design the pathway, we considered the possibility of detecting proteins on the surface of the sperm. During our research over winter break, we learned about the NEU2020 team's adaptation of the Pmr two-component system and thought it would be an ideal means for us to accomplish the detection of a certain protein that lacks a natural sensor. In order to obtain the plasmids used by NEU2020 and to get more professional guidance, we contacted Peixuan Zheng through his NEU2020 supervisor and NEU2022 students respectively. In addition, Mr. Zheng has extensive experience in designing two-component systems as part of his final year undergraduate project.

What we have learned?

Mr. Zheng sent us the plasmids used in their 2020 project (many thanks!). We have since modified the plasmid and obtained better results. We also received guidance from Mr. Zheng on the details of the experiment.

Further Contacts

Since then, we have built up an ongoing relationship with Mr. Zheng. He also sits in on our group meetings online sometimes. We finally invited him to sign up as an advisor for our team. We also had communication with NEU-CHINA team with their project and kept on futher contact.

Interview with Fang Ba:

Who are we interviewing?

Fang Ba
PhD Student, ShanghaiTech University A member of ShanghaitechChina iGEM2016

Background

When constructing a two-component downstream logic system, we were inspired by the article published by Jian Li's team in 2022 (doi: 10.1093/nar/gkac124) and decided to use tryptophan integrase as the main control element for logic gating.

Why was this person contacted?

Initially, we used a tryptophan integrase synthesized by the company, however, it was less efficient. In order to improve the efficiency of the tryptophan integrase, we contacted Professor. Jian Li to obtain the plasmid expressing the tryptophan integrase and its target of action mentioned in the article. Through Professor. Li, we contacted the first author, Mr. Fang Ba. He was kind enough to send us the plasmid and gave us advice on the design and details of our experiments.

What we have learned?

Mr. Fang Ba sent us three plasmids expressing tryptophan integrase and one plasmid expressing the target of tryptophan integrase action that he used in his article. We have since modified this and obtained better results; we also received guidance from him on project design and experimental details:
1. We were reminded that the Pmr and Nisin two-component system might be leaking. We were advised to verify the degree of leakage of the two-component system and if the leakage was severe, it would be better not to use a "0 to 1" logical gating like tryptophan integrase, but to adjust the strength of the element to affect the expression of the downstream reporter gene.
2. For adjusting the strength of the components, Mr. Fang Ba provided us with an idea of amplifier based on T3 Sigma and T7 RNA polymerase.
3. In order to solve the leakage of the two-component system, Mr. Fang Ba provided us with three ideas: (1) change the way to detect the expression intensity of the reporter gene: from detecting the expression intensity of the reporter gene at a specific time, change to plotting the curve of the expression intensity of the reporter gene from after the addition of the inducer and compare it with the group without the addition of the inducer. If there is a significant difference between the two curves, the two-component work can be tentatively considered. (2) Add a segment of protein degradation tag to the C-terminal of the reporter gene to reduce the leaked expression of the background. (3) Adjustment of component strength, such as promoter, RBS strength and plasmid copy number, etc.
4. For the selection of reporter genes, we initially considered using colour proteins as the detection of fluorescent proteins requires specialist equipment. In response, Mr. Fang Ba reminded us that colour proteins need to accumulate to a certain amount to be visible, and that the actual amount of expression may not always meet that requirement. He suggested that we could use fluorescent proteins for specific data analysis to verify the feasibility of the project. In addition, Mr. Fang Ba also provided us with ideas on using lacZ.
5. We carefully read the literature recommended by Mr. Fang Ba (doi:10.1038/s41587-021-00950-3) and were inspired to design the part of the project on toehold switch.

Further Contacts

We have established ongoing contact with him and have sought their advice from time to time on the details of the experiment.

Interview with Jinming Lin:

Who are we interviewing?

Jinming Lin
Professor and Doctoral Supervisor, Department of Chemistry, Tsinghua University

Background

We planned to design a hardware which is simple to use and has the potential to be multi-functional for sperm quality tests in both domestic and medical scenarios. It was suggested that microfluidic chips are a new type of integrated assay device with the advantages of miniaturisation and low sample requirements, which fits the needs of sperm quality tests.

Why was this person contacted?

We learned that Prof. Jinming Lin from Tsinghua University is dedicated to the research of microfluidics-based rapid microbial assays, including the development of instruments and kits related to the assay technology. In order to obtain more professional guidance on microfluidics, we contacted Prof. Jinming Lin via email. Professor Lin has a long history of teaching courses related to microfluidics and has extensive experience in guiding undergraduate students in their research.

What we have learned?

Prof. Jinming Lin provided us with guidance on the direction of microfluidics development and recommended relevant literature to us based on our ideas. We also received guidance from PhD students in Prof. Jinming Lin's lab on the experimental details.
1. Design
In the course of our online contact with Prof. Jinming Lin, we proposed that we "would like to establish a stable concentration gradient in a microfluidic chip", whereby Prof. Lin recommended to us literature on the use of microfluidics to form concentration gradients of chemical substances, which gave us great inspiration for our hardware design.
2. Techniques
Prof. Jinming Lin recommended an experienced PhD student in his lab to guide us in building microfluidic chips, which enabled us to quickly learn the experimental skills required to build the hardware.
3. Building the platform
Prof. Jinming Lin provided us with a platform in their lab to build microfluidic chips, enabling us to build the hardware on campus.

Further Contacts

We have established an ongoing relationship with Prof. Jinming Lin, and our subsequent hardware build will rely on the microfluidic chip building platform in his lab. Click for more details about the hardware.

Interview with Zheni Zeng:

Who are we interviewing?

Zheni Zeng
A PhD student in the Natural Language Processing and Social Humanities Computing Laboratory (THUNLP) at Tsinghua University

Background

What we want to do is essentially a regression problem, and one of the datasets found now (about 10,000 data) is the promoter sequences of prokaryotes and the expression levels of their corresponding genes. Since prokaryotes do not have many regulatory elements like eukaryotic enhancers, we indirectly consider the expression level of their corresponding genes as the strength of the promoter. We hope to be able to predict the corresponding intensity given the promoter sequence by using some deep learning models.
After literature research, a paper published in Nucleic Acids Research obtained a Pearson correlation of about 0.25 on this dataset using a CNN model, which is not very high, but even with this correlation, they filtered out some promoters that would have a high predictive strength and verified them experimentally, with a validity of almost 50%. We have then tried this on this dataset using the LSTM model, and the correlation is around 0.23 after a simple tuning of the reference.

Why was this person contacted?

What we wonder is whether it is possible to use Transformer model for this problem? And is it better to build some Transformer-based model to try it out ourselves if we want to, or is it better to use DNABert model as the base?

What we have learned?

1. The LSTM model is about the same order of magnitude as the CNN model, and the previous experimental results have roughly verified this, so it would be a good choice to try the Transformer model to increase the order of magnitude of the model.
2. If the sequence length is less than 512, it is definitely feasible to use Transformer. And according to the results of the studies in the field of NLP, there is a high probability that such an approach will lead to an improvement in results.
3. DNABert is a pre-trained large model based on Transformer. So if the framework of Transformer is built up, then it should actually be better to go on to use DNABert in combination with it, or vice versa.

What improvements we have made?

We determined to neural network with model structure free from loops and towards models based on Attemtion mechanisms. Click for more details about the software.

Interview with Yangtianze Tao:

Who are we interviewing?

Yangtianze Tao
A PhD student in Department of Mathematical Sciences, Tsinghua University

Background

What we want to do is a regression problem essentially. One of the datasets found now (about 10,000 data) is the promoter sequences of prokaryotes and the expression levels of their corresponding genes. Since prokaryotes do not have many regulatory elements like eukaryotic enhancers, we consider the expression level of their corresponding genes as the strength of the promoter. We hope to be able to predict the corresponding strengths given the promoter sequences by certain deep learning models.

Why was this person contacted?

After literature research, there is a paper published in Nucleic Acids Research on this dataset using CNN model and got a Pearson correlation of about 0.25, which is not very high, but even with this correlation, they filtered some promoters that would have high predictive strength and performed experimental validation, and the validity reached almost 50%. Then we have tried it on this dataset using the LSTM model, and the correlation is about 0.23 after a simple tuning of the reference. After that we improved our model by adapting it to our biological problem based on Transformer_Encoder and the correlation reached about 0.28. However, the problem we are facing now is that the model often over-fits, which can cause a large degradation in the performance of our model. So we need to we solve this problem and improve the performance of the model.

What we have learned?

1. The problem of overfitting can be solved by stopping early and adding Dropout layer, which can make the model avoid learning too many non-common features.
2. After that, Dr. Tao suggested some reference codes which might be beneficial to our performance improvement.
https://github.com/lucidrains/tab-transformer-pytorch/blob/main/tab_transformer_pytorch/tab_transformer_pytorch.py https://github.com/codertimo/BERT-pytorch/blob/master/bert_pytorch/model/embedding/bert.py
3. In addition, we also had a discussion about the process of code implementation and he helped us to check some details of the code implementation.

What improvements we have made?

After the discussion, we decided to add Dropout mechanism to avoid the overfitting problem of the model.

Interview with Guoqiang Chen:

Who are we interviewing?

Guoqiang Chen
Professor and Doctor of Philosophy, School of Life Sciences, Tsinghua University

Background

We started with the overall design of the sperm test chip, but as the members were relatively new to hardware design and actual construction, we consulted Professor Chen, who has been an iGEM instructor for many years, for advice.

What we have learned?

During our consultation with Professor Guoqiang Chen, he mentioned that the cost of microfluidic chips might be an issue, and this is what we were reminded of during the hardware exchange with the BIT team: we should try to control the cost when designing microfluidic systems. In this regard, we approached Taiyan Zhou, who has extensive experience in microfluidic chip design, to ask him how to minimise costs.

What question did it raise?

How we can minimise the cost of making microfluidic chips. So we further contact Taiyan Zhou, the leader of hardware group of BIT iGEM 2021, for advise.

Interview with Taiyan Zhou:

Who are we interviewing?

Taiyan Zhou
Leader of Team BIT, and the leader of hardware group of BIT iGEM 2021

What we have learned?

1. Mr. Zhou asked if the system we were designing has a complex power drive system. He mentioned that this would be an important factor in determining the cost of a microfluidic chip. As we want to be able to establish a concentration gradient of small molecules within our chip, this requires the design of a source and sink to be maintained. We will try to keep costs as low as possible in this regard.
2. Secondly, Mr. Zhou also mentioned that the material chosen for the microfluidic chip may also affect the cost. Our current design is using PDMS as the substrate. And he suggested that we reduce the hardware cost step by step through iterative approach.

What question did it raise?

We need to consider the power drive system of the chip, as well as the choice of chemotactic substances. Our inprovement can be seen via this link: https://2022.igem.wiki/tsinghua/hardware.

Users' needs: Questionnaire

In the week following its release, our questionnaire was viewed 1407 times, with a final valid return of 435. In the valid questionnaires, 56.3% of the sample were male and 42.8% were female. Several age groups were covered, with a predominance of 18-30 years old, which corresponds to the main group of childbirth. Also, the majority of them were undergraduates. The basic information of the sample showed that the questionnaire returned is statistically significant.

We asked the completers to rate (out of 5) their usual concern for reproductive health, as well as their concern for male infertility issues. The majority of people scored 3 or 4 on reproductive health issues, showing a general attitude of concern. For male infertility, scores of 1 to 3 were predominant, indicating that this problem is generally neglected. We also asked them for their views on the current situation of male sperm quality in general, and most of them felt that the current male sperm quality was not promising.

In terms of the current social situation, the respondents rated the "shame of men going to the men's hospital for reproductive health check-ups" with a majority of 4, showing that the shame is generally considered high. We also asked them about their knowledge of the sperm test strips currently available on the market for home use and most were completely unaware.

Depending on the gender, men were asked to rate their willingness to perform sperm quality self-tests using devices such as home test strips. Women were also asked about their willingness to have their partner perform the self-test if they had a male partner. For the other genders, they were asked about their willingness to self-test their sperm quality if they had a male reproductive organ.

After a brief introduction to our project, we asked them for their views and suggestions on home sperm quality test chips. Accuracy and price costs have received the most attention, and many others have also focused on the need to advertise accordingly and to be user-friendly. Biosecurity was also a concern.

We thank all the people who have helped us to make our project better. This is the harmony of iGEM community, and we will take this passion to help more iGEMers！