1. BHARATHIAR UNIVERSITY
MICROBIAL GENETICS AND R-DNA TECHNOLOGY
TOPIC :
● SYNTHETIC BIOLOGY
● ARTIFICIAL INTELLIGENCE
● QUANTUM COMPUTING
PRESENTED BY :
SUMESH. M
21MBTB24
1st. M.Sc., Microbiology

2. CONTENTS
➢ SYNTHETIC BIOLOGY
➢ ARTIFICIAL INTELLIGENCE
➢ QUANTUM COMPUTING
➢ SUMMARY AND CONCLUSIONS
➢ REFERENCES

3. SYNTHETIC BIOLOGY

4. INTRODUCTION
● Synthetic biology (SynBio) is a multidisciplinary area of research that seeks to create new
biological parts, devices, and systems, or to redesign systems that are already found in nature.
● It is a branch of science that encompasses a broad range of methodologies from various
disciplines, such as biotechnology, genetic engineering, molecular biology, molecular
engineering, systems biology, membrane science, biophysics, chemical and biological
engineering, electrical and computer engineering, control engineering and evolutionary biology.
Due to more powerful genetic engineering capabilities and decreased DNA synthesis and
sequencing costs, the field of synthetic biology is rapidly growing.
● Many scientists suspect that synthetic biology will not only reveal new knowledge about the
machinery of life but also bring about new biotechnological applications. Two major applications
that are being pursued are biofuels, & pharmaceuticals.

5. SYNTHETIC BIOLOGY
● Synthetic Biology is also known as Synbio, Synthetic Genomics, Constructive Biology or
Systems Biology) - design and construction of new biological parts, devices and systems that do
not exist in the natural world and also the redesign of existing biological systems to perform
specific tasks. Advances in Nano scale technologies - manipulation of matter at the level of atoms
and molecules - are contributing to advances in synthetic biology.
● The title 'synthetic biology' appeared in the literature in 1980, when it was used by Barbara
Hobom to describe bacteria that had been genetically engineered using recombinant DNA
technology. These bacteria are living systems (therefore biological) that have been altered by
human intervention (that is, synthetically). In this respect, synthetic biology was largely
synonymous with bioengineering

6. There are many definitions for synthetic biology. Like,
➢ It is an emerging field of biology that aims at designing and building novel biological
systems.
or
➢ The final goal is to be able to design biological systems in the same way engineers design
electronic or mechanical systems. Etc.
or
➢ An emerging field of research that aims to combine the knowledge and methods of biology,
engineering and related disciplines in the design of chemically synthesized DNA to create
organisms with novel or enhanced characteristics and traits

7. Subfields of contemporary Synthetic Biology
There are 5 main subfields of contemporary synthetic biology
➢ DNA Synthesis
➢ DNA based bio-circuits
➢ Minimal genome
➢ Protocells
➢ Chemical SB/Xenobiology
Components of Synthetic Biology .
➢ Genetic Manipulation
➢ Genetic selection carried out for millennia (domestication of animals)
➢ Mendelian selection 'rationalized' process.
➢ Recombinant DNA Technology

8. APPLICATIONS
ENVIRONMENTALAPPLICATIONS
➢ Synthetic biology has a broad range of applications including the production of photographic
bacteria.
➢ They can also be used to detect toxic chemicals such as arsenic.
MEDICALAPPLICATIONS
➢ One of the avenues of synthetic biology is that has wide application is the development of
alternative production routes for useful compounds, and one of the most discussed of these is
the construction of a artificial metabolic pathway in E.coli and Yeast to produce a precursor
(artemisinin) for a antimalarial drug.

9. ➢ It can be used for development of other therapeutically useful products for cancer and HIV
treatment.
➢ It helps for the development of synthetic vaccines for some viral diseases such as SARS
(Severe Acute Respiratory Syndrome) and Hepatitis C
INDUSTRIALAPPLICATIONS
➢ Synthetic biology is widely used for the production of Biofuels from genetically engineered
microorganisms.

10. ARTIFICIAL INTELLIGENCE

11. INTRODUCTION
● Artificial Intelligence - It is the science and engineering of making intelligent machines,
especially intelligent computer programs. It is related to the similar task of using computers
to understand human intelligence, but AI does not have to confine itself to methods that are
biologically observable.
● Artificial Life is a Field of study and an associated art form which examines systems related
to life, its processes, and its evolution through simulations using computer models, robotics,
and biochemistry. Soft (software) Hard (hardware) Wet (biochemistry).

12. ARTIFICIAL INTELLIGENCE
● Artificial intelligence is at the forefront of modern technology and has begun to parallel in
the world of biotechnology. Machine learning has also been the heart of many tech startups
which is driven by increasing availability and cheaper data paired with more efficient
computers. Throughout the years, Al and ML have started to find their way into the realm of
biotechnology due to the growth of biotechnology data.
● Artificially intelligent machines can perform tasks far better and in a very fast manner than
humans. It has a large number of applications in the field of genetics and biology
● Lab assistants are known for carrying out tedious tasks ranging from gene editing or data
analysis. Many of these tasks are now being passed over to the responsibility of Al.

13. ● The power of artificial intelligence now allows stronger experiments and data to be collected
in any area of science. This advancement and collaboration between biotechnology and
artificial intelligence can increase the time of getting better results back.

14. APPLICATIONS
AI has two main applications in genetics: identification of harmful genes and treatment of
disease.
IDENTIFICATION
● For human beings, it is an extremely tedious and time-consuming process to analyze the vast
amount of data that is present in a single person’s DNA. This analysis can be made much
more efficient and accurate by utilizing machines for their core purpose- to make tiresome
tasks less challenging.
● By using machine learning algorithms to compare the different gene expression levels in
malignant and normal tissue samples of a patient diagnosed with cancer, predictions can be
made about which genes have been mutated in that patient’s DNA.

15. ● Various imaging techniques are used to detect the mutations and diseases in different organisms
like magnetic resonance imaging, fluorescent imaging, and thermography
Magnetic resonance imaging
● Also called as NMR, meaning nuclear magnetic resonance scanner, it is mostly known as
magnetic resonance imaging device, and is usually identified for its powerful magnets. These
magnets are good as they efficiently polarize and further excites the focused proton singly
included in water molecules present in the tissue, helping in a detectable signal spatially encoded
giving various images of the body.
Fluorescence imaging
● Fluorescence imaging is used to detect tumors, and cancer. Fluorescence techniques are also used
in a variety of genetic techniques like PCR, Blotting techniques, DNA sequencing, medical
imaging and surgery.

16. Thermography
● One of the most common applications of it is breast imaging. Usually one of the three
approaches are being used commonly, the tele-thermography, the dynamic
angio-thermography and the contact thermography type. The imaging thermographic digital
methods involve the advantage of the principle derived from metabolic activity. Also
vascular circulation within the area surrounding a developing breast cancer is studied to
detect the higher value.

17. TREATMENT
● Diagnosis
● Treatment protocol development
● Drug development
● Personalized medicine
● Patient monitoring and caring

18. QUANTUM COMPUTING

19. INTRODUCTION
● Quantum computing is a promising field that emerged out of a combination of quantum
physics and computer science. With ever expanding data across different areas, the
conventional computer will run out of its capacity to handle such big data. Further,
extracting the meaningful from big complex data still, accompany challenges with it.
Quantum computing's main goal is to provide such algorithms which are robust and faster in
solving problems as compared to classical computers.

20. QUANTUM COMPUTING
● Quantum computing is an interdisciplinary research area that utilizes the principles of
quantum mechanics.
● David Deutsch is known as the father of quantum computing.
● Quantum computers possess unique abilities such as entanglement, superposition that enable
to surpass some of the limitations of today’s classical computer. For instance, their ability to
perform extremely faster computations by reducing the number of calculations needed to
complete a task. Further, it can help in solving problems that are currently unsolvable in
varied disciplines such as bioinformatics, artificial intelligence, drug discovery, personalized
medicine, biological system, and many others

22. QUANTUM COMPUTERS AND ITS BASIC FEATURES
Well-known high technology using companies like IBM, Microsoft, Google is investing in
research and development towards quantum computing. Recently, IBM Q System OneTM has
been developed by IBM which is the first commercial Quantum computer. Following are some of
the basic features possessed by quantum computing that make it lucrative :
➢ Qubits
● In contrast to bit can have only one possible electronic state out of two (|0⟩ and |1⟩ ) at a time
in classical computing’s, quantum computing leverages the advantage of subatomic particles
where each state is represented by ‘quantum bit’ or ‘qubit’ that can attain 1,0 or any values in
between them at a time. Such a system is called as “complex two-state system” where a state
space has infinitely many possible states.

23. ➢ Superposition
● In quantum computing, pure qubit (|Ψ⟩ ) can attain any superposition or linear combination
of two basic states represented by Dirac notation |0⟩ and |1⟩ , a|0⟩ + b|1⟩ ), where a and b
denote complex numbers given |a| 2 + |b| 2 = 1. Further, two bits in classical computing can
be indicated as 00, 01, 10 and 11. In contrast, a qubit can be represented by any of those
numbers at the same time. As a result, greater number of qubits will lead to an exponential
increase in the number of superpositions that facilitates faster calculations involving very
complicated numbers.
➢ Quantum parallelism
● The superposition feature imparts an ability to run a computation on possible classical states
at a time that provides enormous computational power to quantum computing, and the
process is referred to as quantum parallelism.

24. Consequently, parallelism in quantum computing can perform some tasks shown to have
advantages over classical computing. Some of these advantages include factorization of large
numbers and searching large databases.
➢ Entanglement
● Quantum entanglement refers to a process where a change in the state of one qubit is
inseparable from the change in the state of others regardless of their spatial separation.
● Entanglement enables quantum computing to solve problems quickly to get to the right
answer and fosters role in a variety of applications including teleportation, quantum
cryptography, and others.

25. APPLICATIONS
● Solving biological problems
● Drug designing
● Drug development
● Storing Genomic data and genetic informations
● Cancer disease detection

26. SUMMARY AND CONCLUSIONS
According to Synthetic biology, It is a multidisciplinary area of research that seeks to create new
biological parts, devices, and systems, or to redesign systems that are already found in nature. Synthetic
Biology is used to design and construct new biological parts, devices and systems that do not exist in
the natural world and also the redesign of existing biological systems to perform specific tasks.
Advances in Nano scale technologies - manipulation of matter at the level of atoms and molecules - are
contributing to advances in synthetic biology.
According to Artificial Intelligence, It is the science and engineering of making intelligent
machines, especially intelligent computer programs. It is related to the similar task of using computers
to understand human intelligence, but AI does not have to confine itself to methods that are biologically
observable.

27. According to Quantum Computing, Quantum computing is an interdisciplinary research area
that utilizes the principles of quantum mechanics. Quantum computers possess unique abilities
such as entanglement, superposition that enable to surpass some of the limitations of today’s
classical computer. For instance, their ability to perform extremely faster computations by
reducing the number of calculations needed to complete a task. Further, it can help in solving
problems that are currently unsolvable in varied disciplines such as bioinformatics, artificial
intelligence, drug discovery, personalized medicine, biological systems, and many others
Synthetic biology, Artificial intelligence and Quantum computing, These three have their
own importance and applications in the field of life sciences.

28. REFERENCES
Bennett, H. C. 1995. Quantum information and computation. Physics Today. 24-30
Britannica.com/syntheticbiology
Bueso, F. Y.; Tangney, M. (2017). "Synthetic Biology in the Driving Seat of the Bioeconomy".
Trends in Biotechnology. 35(5): 373–378.
Garfinkel et al. 2007
John McCarthy, 2007
Levskaya, A.; et al. (2005). ""Synthetic biology " engineering Escherichia coli to see light".
Nature. 438 (7067): 441–442.

29. Martin, V. J., Pitera, D. J., Withers, S. T., Newman, J. D. & Keasling, J. D. Engineering a
mevalonate pathway in Escherichia coli for production of terpenoids. Nature Biotech. 21,
796–802 (2003)
Olmschenk, S. et al. 2009. Quantum teleportation between distant matter qubits. Science,
323(5913), 486–489
Synthetic Biology/wikipedia
Sutor, B. 2018. Scientists Prove a Quantum Computing Advantage over Classical. IBM Research
Blog.
Yeager, Ashley. “Could AI Make Gene Editing More Accurate?” Thescientist.com.

30. THANK YOU