Team:ShanghaiTech China/Implementation


Proposed Implementation

Proposed Implementation



CESAR aims at fighting against antibiotic resistance and pursues a healthier world.


By making more convenient, sensitive and cheaper on-site detection possible, CESAR-II tries to simplify and shorten current clinical antibiotic resistance genes (ARGs) detection procedure as well as to eliminate the medical disparity (such as limiting detection ability of ARGs) caused by imbalanced economic development. And by making direct antibiotic detection possible, CESAR-I visualizes the antibiotic existence and thus helps the surveillance of antibiotics abuse. Together with CESAR-I and CESAR-II, we believe CESAR can be a powerful solution to antibiotic resistance at both ends: cause and consequences.


End Users

During our whole project, we are constantly asking ourselves questions about interested party of our project, in order to focus on users' needs and to improve CESAR continuely. More specifically, by analyzing people or organization that can be affected by, or perceive itself to be affected by CESAR, it is suggested that quality surveillance staff, clinical laboratories, farmers and people who are in need of POCT (point-of-care testing) are among the most important end users.


For quality surveillance such as Food and Drug management, officers may need a portable equipment like CESAR-I to detect antibiotics in the process of food production. Antibiotics found in river sediment, farmed soil, and other sources are polluting the environment and contributing to the rising rates of antibiotic resistance. Thus, government utilities responsible for environmental monitoring such as CNEMC (China National Environmental Monitoring Centre) are regarded as potential end users.


According to our field research in joggery, it is discovered that farmers are in need of antibiotic detection as well to ensure that they met the requirements that no overuse of antibiotics is added into the fodder. Hence, CESAR-I serves as an option for quality check in farms.


As mentioned in integrated human practices, not all hospitals, especially not all clinics in China possess necessary equipments including mass spectrometer and RT-PCR instrument to examine specific ARG types in samples. Taking China as an example, considering the fact that medical resources are distributed unevenly between developed and undeveloped regions, it is difficult in rural area to implement professional equipments, making current ARG detection procedure in clinical laboratories inaccessible. CESAR-II could be a good choice for the supplement of medical security system in these regions. Therefore, clinics are regarded as end users of CESAR-II as well.


What's more, iGEMers of Shanghaitech_China foresee that with the development of healthcare and ongoing aging of population in China, POCT will be a blue ocean in the near future, which is an important application scenario for CESAR. Imagine this, families request POCT service and the community health care facilities deliver on-site portable detection devices like CESAR-II. Within hours, fluorescence signals are gathered to tell patients the existence of antibiotics resistance in samples. Meanwhile, the data could be uploaded to the cloud, helping doctors to diagnose the disease even without contacts with the patient. Not only community health care centers, centers for disease control or physical examination centers may also take advantages of CESAR system. Based on these predictions, it is concluded that the end users of CESAR-II also include individuals in the community, from the young to the old.


Pipeline for CESAR

a. Determine detection target: ARGs (to b), antibiotics (to c), proteins*



b1. Obtain sample solution. Place the plastic sheets with Cas12a-reporting rings on the lid, power on the electromagnet, and Remove the plastic protective film.

b2. Add samples to CESAR-II combined tubes and wait 20 minutes for RPA amplification of samples.


b3. The electromagnet will automatically power off to release Cas12a-reporting rings to the solution to start cleavage.

b4. Get fluorescence results.



c1. Obtain sample solution. Place the plastic sheets with rings on the lid, power on the electromagnet, and Remove the plastic protective film.

c2. Add samples to CESAR-I combined tubes and wait 20 minutes for aptamer sandwich binding with antibiotics and releasing activator DNAs.


c3. The electromagnet will automatically power off to release Cas12a-reporting rings to the solution to start cleavage.

c4. Get fluorescence results.


*Note: aptamer based proteins detection of CESAR resembles CESAR-I but is not validated through experiments yet.


While CESAR has the privilege of fast, portable and cheap detection, the risks of using CESAR system instead of current detection methods may be the following. Fisrt of all, there are reports regarding off-target effects of Cas12a system, causing false positive results. Regulators may be reluctant to use CESAR if the false positive rates are too high compared with current methods such as qPCR. Second, CESAR-I may be not as sensitive to minute quantities antibiotics in the sample as current detection method such as HPLC-MS, causing false negatives results. Thirdly, for biosafety reasons, inappropriate disposal of crRNA that contains ARG fragments in CESAR may cause leakage and transmission of ARGs.


On one hand, several quality objectives are made based on quality policies to ensure the implementation of CESAR is well-controlled. One of the most important quality policies of our CESAR system is that it should provide cheap, fast and reliable detection for every user. To achieve this, possible quality objectives could be made. For example, the average costs of the whole ARG detection process per capita should be reduced up to 30% of the current detection method; the average time consumption of CESAR detection should be within 4 hours; the average false positive rate of CESAR detection should be less than 0.1%. Though our CESAR demo is not yet released for open-beta test, it should be pointed out when CESAR is implemented in the real world, explicit and definite quality objectives should be documented and checked occasionally, not only in sake of providing traceable records of product design, but also prompts integrity and continual improvement of CESAR system.


On the other hand, we emphasize on the concept of quality by design. In other words, we try to reduce risks mentioned above in our design.


Tackling risks: Examples of crRNA design of CESAR-II for clinical examinations

Taking the risk of off-target effects in clinical examinations as an example, we want to show how we reduce the off-taget effects by design.


Through field research we found that currently the antibiotic resistance test in clinical lab usually takes days. The main reason for the time consumption is strain identification through selective culture. However, in clinical practice, doctors care more about whether the patient shows antibiotic resistance to help them decide prescription rather than the antibiotic resistance is caused by which bacteria. Therefore, CESAR-II focuses on examining the antibiotic resistance and, as mentioned previously, has the potential to shorten the time duration from days to hours.


We investigate in depth about off-target effects of Cas12a, which is mainly due to the incomplete base-pairing of crRNA and targets. By careful screening of target DNA fragments to make sure that they are unique, we believe that off-target effects could be minimized to greatest extents. The targets Cas12a binds to are like fingerprints (no one has the same fingerprint than others). The more unique a target is, the less likely off-target occurs.


In light of this, several candidates occur on the wait list. 16s rRNA, Pol I, RuBisCo and RNR (ribonucleotide reductase) gene are among the most expressed genes in bacteria. 16s rRNA not only exists in genomes of all bacteria, but also contains specific regions (V1~V9) interspaced by invariant regions that can tell different species apart. The specific regions are often regarded as phylogenetic markers. These properties make 16s rRNA appropriate for bacterial taxonomy.


From bacterial occurrence statistics in samples given by EzBioCloud and clinical experiences told by doctors, we design crRNA for 7 bacteria that are carefully selected out of database due to common appearance in clinical labs to demonstrate feasibility and general applicability of CESAR II.


By MSA (Multiple Sequence Alignment) tool Clustal, we calculated out the invariant and variant regions of these 7 bacteria. Next, we want to select an appropriate 23bp-length sequence out of variant regions for crRNA design.


BIn regarding the choice of variant regions, it is reported that V3 to V6 sequencing often carries out sufficient information to classify species; V6 was the most accurate at differentiating species between all CDC-watched pathogens tested.


Considering the specificity of the sequences using blastn, we can verify whether the sequence is unique genome wide. It is V1 chosen out of which the template is come from. More specifically the sequences below:



The transcription template is given by table above, and the corresponding crRNA is given by table below:



By checking the uniqueness of target DNA, it is believed that off-target effect is less likely to occur.

To sum, we propose the principle of QBD (Quality by Design) and a series of quality objectives to ensure integrated and continual improvement of our CESAR system throughout implementation. We consider patients and health care givers, antibiotics surveillance and farmers as some of the most typical and important end users of CESAR-I and CESAR-II.Our design is focused on their needs.