Testing Biological Systems Biological debugging using metabolomics

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Do curso por University of Manchester

Industrial Biotechnology

240 classificações

University of Manchester

Industrial Biotechnology

240 classificações

Fossil fuels have been the primary energy source for society since the Industrial Revolution. They provide the raw material for the manufacture of many everyday products that we take for granted, including pharmaceuticals, food and drink, materials, plastics and personal care. As the 21st century progresses we need solutions for the manufacture of chemicals that are smarter, more predictable and more sustainable. Industrial biotechnology is changing how we manufacture chemicals and materials, as well as providing us with a source of renewable energy. It is at the core of sustainable manufacturing processes and an attractive alternative to traditional manufacturing technologies to commercially advance and transform priority industrial sectors yielding more and more viable solutions for our environment in the form of new chemicals, new materials and bioenergy. This course will cover the key enabling technologies that underpin biotechnology research including enzyme discovery and engineering, systems and synthetic biology and biochemical and process engineering. Much of this material will be delivered through lectures to ensure that you have a solid foundation in these key areas. We will also consider the wider issues involved in sustainable manufacturing including responsible research innovation and bioethics. In the second part of the course we will look at how these technologies translate into real world applications which benefit society and impact our everyday lives. This will include input from our industry stakeholders and collaborators working in the pharmaceutical, chemicals and biofuels industries. By the end of this course you will be able to: 1. Understand enzymatic function and catalysis. 2. Explain the technologies and methodologies underpinning systems and synthetic biology. 3. Explain the diversity of synthetic biology application and discuss the different ethical and regulatory/governance challenges involved in this research. 4. Understand the principles and role of bioprocessing and biochemical engineering in industrial biotechnology. 5. Have an informed discussion of the key enabling technologies underpinning research in industrial biotechnology 6. Give examples of industrial biotechnology products and processes and their application in healthcare, agriculture, fine chemicals, energy and the environment.

Na lição

Methods in Systems and Synthetic Biology

Recent advances in our ability to read and write genome sequences on a large scale have led to an ambitious vision for a new generation of biotechnology, often referred to as Synthetic Biology. Synthetic Biology aims at turning biology into an engineering discipline, in which organism engineers use computational tools to design biological systems with novel valuable functionalities, which are then built using advanced high-throughput genetic engineering, and tested by rapid screening technologies that collect diagnostic molecular profiles to drive improved designs in an iterative design-build-test cycle. This module will introduce the engineering concepts that inform Synthetic Biology and the cutting-edge technologies that underlie our dramatically increasing ability to construct living systems with custom-made functionalities. All stages of the design-build-test cycle for novel biosystems will be discussed, with a special focus on their integration in a unified bioengineering platform. Examples will focus on the application of Synthetic Biology as an enabling technology for the bioindustry, especially for the improved microbial production of high-value chemicals and drugs. A section on responsible research and innovation will explore the transformative potential of this innovative technology within a broader socio-economic context, creating awareness of the ethical and political implications of research in this field.

Introduction to Synthetic Biology: Visions for Biotechnology 2.06:27

Designing biological systems: Computational modelling and systems biology9:10

Building biological systems I: Genome synthesis and genome editing9:25

Controlling and engineering pathways in Synthetic Biology9:00

Testing Biological Systems Biological debugging using metabolomics8:12

Deploying biological systems: Perspectives on Responsible Research & Innovation and bioethics I5:24

Conclusions and Outlook Systems and Synthetic Biology6:40

Conheça os instrutores

Prof. Nicholas Turner
Deputy Director
Manchester Institute of Biotechnology
Prof. Nigel Scrutton
Director
Manchester Institute of Biotechnology

Hi, my name is Dr Nick Rattray and I'm the Experimental Officer in

the SYNBIOCHEM Centre of the Manchester Institute of Biotechnology.

Within my role, I use mass spectrometry as a tool to try and

investigate problems that might occur within synthetic biology.

It's the aim of this talk to try and show how targeted and

untargeted metabolomes eted can be used within synthetic biology.

This talk will be focused on the targeted and untargeted section

within the design, build and test framework of synthetic biology.

Industrial biotechnology is an umbrella term in

which many areas of bioscience operate.

These include synthetic biology, directed evolution metaboomics and chemometrics,

synthetic chemistry, microbiology, and protein engineering.

The goal of industrial biotechnology is to use cells such as micro-organisms, or

part of cells like enzymes, to make industrially useful products in

areas such as chemicals, food and feed, detergents, textiles and biofuels.

Due to advances in computer-based analyses of enzymes and pathways, we

now have tools that can be used to predict and design active sites within enzymes and

place these pathways in chains that can, by using in silico models,

be used to design new routes to the synthesis of valuable chemicals.

We also have ways in which these pathways can be built into DNA and RNA of said

micro-organism scaffolds that can be used to express the desired target compound.

These systems are then tested for the production of the target compounds and

associated metabolite data can be used to help deeper pathways and

inform in the designing of more efficient iterations of the pathway.

All living organisms stored genetic information within their DNA - it's

a genome.

This DNA in codes for associates RNA the transcriptome that in turn supplies

information on the order and connectivity of amino acids within proteins.

Sometimes these proteins are enzymatic in nature and

thus can catalyze small molecule reactions.

The design and build sections of the synthetic biology pathway focus

on modulating and expressing genetic material

that directly influence downstream metabolite production.

The test platform is mainly focused on analyzing these downstream chemicals and

in a targeted and untargeted fashion.

Both types of data can be used as input back into the design build and

test iteration.

Metabolomics can be described as, the unique study of the unique chemical

fingerprints that specific cellular processes leave behind and

within a synBio free market involves extracting chemicals from microbial

samples are targeting specific products or looking in an untargeted way.

The whole chemical makeup of the system.

This is easier said than done but

there are several types of tool that a researcher can use to help get answers.

Spectroscopy based analysis is the study of physical systems by the electromagnetic

radiation in which they interact, or that that they produce.

Techniques such as FTIR, Fourier Transform Infrared Flurescence.

Ultraviolet or Raman spectroscopy fall into this bracket and have

the advantage of being very quick, cheap generally non-destructive to your sample,

and generate relatively simple data that can be easily manipulated.

NMR, or Nuclear Magnetic Resonance, is also spectroscopic in nature and

can be used to identify the chemical structure and

bond connectivity of individual compounds.

It's a very powerful technique but it's not as sensitive as others,

is expensive and can be technically demanding.

Spectometric based analysis is the measurement of electromagnetic radiation

as a means of obtaining information about physical systems on the components.

Within SynBio Mass Spectrometry Analysis is one of the most popular of this

spectrometric techniques and has the potential to identify and

quantify allows proportion of the chemical species contained within the sample.

Degeneration of the rich multidimensional data is a double-edged sword.

As subsequent data processing and

statistical analysis is a very time-consuming process

Targeted analysis involves only focusing on individual or a small group of chemical

species that are known to be present in a desired pathway that the experiments

are hypothesis-driven, we know what we are looking at.

Depending on the chemical makeup of each target,

specific extraction protocols have to be used and these are usually based upon

the solubility of said chemicals on specific solvents.

The analysis via Mass spectrometry is generally a lot quicker than a targeted

analysis, this is because chromatography techniques can be tailored to be compound

specific and short in time, the subsequent data generated is relatively uncomplicated

due to the experiment of focus on only a small number or individual metabolites.

A high throughput target strategy can be applied to many different aspects

of the SynBio Workflow.

But one of the main uses is in the screening of mutant libraries.

The design and build platforms can generate very high numbers of a bacteria mutants,

each with the potential to be a high producer of a target compound.

These samples are grown in a small-scale environment such as 96-well plates.

Targeted must be so much you can identify the top candidates of production and

this data can be used inform the design architects

on the amount produce of candidates for the next round of intuitive development.

Once the top producing mutants have been identified,

target mass spectrometer can be used in many tracking aspects of the scale up into

bioreactors such as identifying any chemical imbalances within cool factors or

by the build-up of toxic intermediates that might be hindering growth.

Untargeted analysis involves trying to capture data on as many chemical

species as possible within a biological sample.

This is a form of chemical phenotyping with the aim of overlaying this data

onto known species-specific biochemical networks.

By doing this,

it is possible to detect where metabolite bottlenecks are appearing,

whilst at the same time also identifying if any deficiencies are present.

As any untargeted experiment is designed for

maximum chemical coverage, extraction procedures tend to be locked in, that is,

one specific method is used over many experiments.

This form of analysis produces data that is highly complex and

often requires mathematical and statistical models.

The Achilles Heel of the untargeted strategy upon comparison to target methods

is the time taken for analysis.

It tends to be a lot longer as chromatographic methods

have to be longer in order to accommodate the hundreds to thousands

of chemicals that need to be resolved.

But once applied this technique can be exceedingly powerful in the areas

of identifying and debugging bottlenecks and

also supplying population data into metabolic models.

One other area that the untargeted approach is also successful

is in the detection of unknown metabolites.

Within synthetic biology, the generation of chemical diversity, and

synthesis of new, never seen before chemical species are very desirable goals.

By looking at the global chemical constituents of biological system

holds the potential to uncover

broader diversity alongside identifying a new chemical species.

Looking into the future, the number of samples generated in screening

bacterial mutant libraries is huge.

This requires faster pipelines that can deal with larger datasets

to help with debugging and quantification.

Several areas are constantly being looked at for improvement to help with this end.

These include improvement within Analytical Methods,

the automation of MS data processing along with the interpretation of this data,

hypothesis generation and the fusing of datasets within other 'omics data.

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