Team:TU Dresden/Motivation

Beaming BioBricks from Space...

Project Motivation

 

Motivation

Lower the cost • save privacy • expand accessibility

From antibiotics resistances via genetic diseases to verifying genotypes of recombinant bacteria or knock-out strains. Every day in thousand situations everywhere in the world, there are hours of work and hundreds of dollars spent to determine the presence or absence of a specific DNA sequence.

Which methods are used hereby? Classically DNA extraction (~1h), followed by a PCR (~1-1.5h) and gel electrophoresis (~40-50 min). These methods do not only take a long time but also require advanced technology which is only available in laboratories. Furthermore these technologies were discovered in the 1950s to 1980s. [1,2] In the fast advancing field of molecular biology, it is just about time to come up with newer and faster methods! This will not only save a lot of time for researchers and health workers around the globe but most importantly will make genetic testing for the first time available and affordable for everyone who might be in need of it. Genetic testing nowadays costs up to 500 dollars for a single run and the wait for results ranges from weeks up to months. [3] Also, tests for monogenic diseases are urgently needed as this quote from the World Health Organisation (WHO) highlights :

“Monogenic diseases are responsible for a heavy loss of life. The global prevalence of all single gene diseases at birth is approximately 10/1000. In Canada, it has been estimated that taken together, monogenic diseases may account for upto 40% of the work of hospital based paediatric practice (Scriver, 1995).” WHO. [4]

With the remarkable advancements in genomic research in recent years, genomic testing is highly frequently applied in health and research. But a DNA sample can never be completely anonymous, since the DNA sequence of each person is unique. This introduces a new aspect to patients privacy and the increases the risk of misuse of genetic information.

“Genetic tests give an assessment of an individual's inherent risk for disease and disability. This predictive power makes genetic testing particularly liable for misuse.” WHO. [5]

This is not only an issue in the public and health sector but also in research. [4] Indeed, a study published in 2013 demonstrated that it is possible to re-identify research participants using genomic data. [6] Direct-to-costumer companies that offer genetic testing have been found to store costumers samples and sequencing data, use them for unspecified research and even shared data with third parties. Moreover, the companies did not provide sufficient or clear information to consumers about this. [7]

This is an inherent danger to modern society for which we see an urgent need in solving, because nothing is more private than the information that created yourself and is defining so many aspect of your body and mind.

We believe our improved method shall be easy to use so anybody could do it and that it should not require advanced technology so it can be used at home or in the field or in a country where the advanced technology of modern laboratories is not available. This will not only bridge the gap between scientists and the general public but also enable everyone to get to know their own genetic information without having to share it with any organization or institution.

References

[1] https://en.wikipedia.org/wiki/History_of_electrophoresis, accessed 06/10/2019

[2] https://en.wikipedia.org/wiki/Polymerase_chain_reaction, accessed 06/10/2019

[3] http://clinchem.aaccjnls.org/content/45/6/915

[3] https://www.who.int/genomics/public/geneticdiseases/en/index2.html

[4] https://www.genome.gov/about-genomics/policy-issues/Privacy

[5] https://www.who.int/genomics/elsi/gentesting/en/

[6] Melissa Gymrek, Amy L. McGuire, David Golan, Eran Halperin, Yaniv Erlich, Identifying Personal Genomes by Surname Inference, Science 18 Jan 2013

[7] Emilia Niemiec, Heidi Carmen Howard,Ethical issues in consumer genome sequencing: Use of consumers' samples and data, Appl Transl Genom. 2016 Mar; 8: 23–30