Harnessing synthetic biology for the production of high-value chemicals
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00:00
Synthetic oilCombine harvesterPuff pastryGrowth mediumMan pageMagmaAlpha particleArginineDrop (liquid)BohriumBleomycinGramicidinKanamycinPenicillinGriseofulvinGentamicinErythromycinVancomycinChromosomeNitrosamineTau proteinHydroxybuttersäure <gamma->Nitrogen fixationGenomeGene clusterOrphan DrugGenePatentPeptide synthesisBogGlutenBiodieselProteinGoldCycloalkaneFoodBreed standardVanillinNew Millennium ProgramEmerinSodium hydrideModul <Membranverfahren>EnzymeMagnetometerRapidMetallclusterMashingProtein domainEnolEthylene-vinyl acetateCigarHost (biology)Gene expressionRegulatorgenReaktionsgleichungNeprilysinMixtureHomocysteineCalciumTransformation <Genetik>Setzen <Verfahrenstechnik>SynthaseElfJohann Sebastian BachMedroxyprogesteroneHybridisierung <Chemie>PlasmidSauerrahmProlineMonoamine oxidaseSubstrat <Chemie>OrganelleHerzog August LibraryPolycyclische AromatenGlutaminstoffwechselThreonineDominican RepublicInclusion (mineral)Sample (material)Maskierung <Chemie>Glutathione S-transferaseChemistryRNAIsomerHigh-performance liquid chromatographySimulationBis (band)CaramelBiosensorTiermodellFoodMetabolic pathwayMeatActinOrganische ChemieMetabolomGrowth mediumRing strainHydroxybuttersäure <gamma->PH indicatorWursthülleBiomolecular structureCell (biology)Gene clusterColourantGemstoneMetallclusterSetzen <Verfahrenstechnik>PlasticOrphan DrugAssetAntibacterialSynthetic oilHost (biology)Peptide synthesisFunctional groupGeneNobeliumChemical compoundArtemisininSpeciesEnzymeChemistryChemical plantRapidVerwitterungFlux (metallurgy)GenomeTranscription (genetics)GoldZunderbeständigkeitVanillinTuberculosisGramicidinBeta sheetInhibitorWalkingPrecursor (chemistry)Baker's yeastSecondary metaboliteElectronic cigaretteChemical structureBiosynthesisMixtureNaturstoffAcidBiscuitGene clusterModul <Membranverfahren>Sea levelMixing (process engineering)Omega-6-FettsäurenIce creamRibosomeSteinkohlenteerMetabolismMass spectrometryResistenzWine tasting descriptorsDeathSoilAmino acidCell growthSignal peptideBreed standardAllosteric regulationGlutaminsynthetaseGene expressionPeptideGenregulationSystemic therapyFeinchemikalieSystems biologyMoleculeToxicityActive siteCombine harvesterOpen reading frameAbbruchreaktionStockfishIce frontScreening (medicine)Binding energyErdrutschSimulationEmission spectrumLipogeneseActivity (UML)Shear strengthAction potentialMetaboliteAroma compoundGrapefruitBiochemistryProcess (computing)CarbonLimoneneTranslation <Genetik>Asymmetric inductionHydrophobic effectScaffold <Biologie>MyosinStructural steelController (control theory)ProteinProtein domainCarbon (fiber)Pharmaceutical drugRiver sourceGlucoseChain (unit)BiofuelLigninPosttranslational modificationRecreational drug useTriterpeneKohlenhydratchemieAgeingPaste (rheology)Ash (analytical chemistry)ButcherAntibodies (film)EukaryoteGesundheitsstörungDeterrence (legal)LactoneLactameCancerGelatinFruchtsaftAdenomatous polyposis coliFiningsDNS-SyntheseAmoxicillinIce shelfCheminformaticsDNA replicationEnzyme inhibitorStarvation responseBeverage canLibrary (computing)Sample (material)HerzfrequenzvariabilitätAusgangsgesteinTransdermales therapeutisches SystemBioassayStop codonPlasmidDifferential calculusFaserplatteMachinabilityPeriodateSynthetic biologyFoodChemistCarbonate platformChemistVSEPR theoryAzo couplingStereoselectivityGlucocorticosteroideTranskriptomAntibiotic resistancePathogenicityPharmaceutical industryBody weightReaction mechanismHomologisierungMeprobamateOrigin of replicationPhenyl groupGlycinePenicillinVancomycinElectronegativityErythromycinAcylEthyleneAmineAgarCyclische VerbindungenSweetnessThermoformingChromosomeActivation energySemisynthesisSaccharomyces cerevisiaeBiocatalysisRepeated sequence (DNA)ElectronMedical historyFluorinePainComputer animation
Transcript: English(auto-generated)
00:17
Thank you very much. Thank you. First, I'd like to thank the organizers for giving me a chance to invite me to this nice
00:25
Conference and also giving me a chance to talk about some of the work that we're doing in the group So, let's see if this works. Yes. Okay. So all of you know that there's a really big problem with antimicrobial resistance There's lots of hospital infection 3 million patients in a year about 50,000 deaths
00:43
25% of those are colonized in hospitals. Subsequent infection and resistance is rising. So here this blue line is MRSA. You can see it started lots of increase Even enterococci which have resistant to vancomycin Which is the so-called antibiotic last resort has emerged and is on the rise
01:06
And you can see the proportion of MRSA in some of the countries within Europe that are quite high But this problem is not just for Europe, but it is absolutely worldwide So let's think of antibiotics
01:21
So who makes them? Well, they're actinomycetes. More than 80% of all commercial antibiotics are produced by actinomycetes Actinomycetes are ground dwelling ground positive soil bacteria. You can see a scanning EM picture here This is the soil and you can see spores coming out of the soil
01:42
If you take a grow in the lab a colony of streptomyces or actinomycetes You see some colonies like this growing on an agar plate on the top You see these blobs and these blobs are antibiotics being secreted from the cells Here if you cut the colony in half here and look at it from the side
02:02
So here's the agar and you can see inside a pigmented Antibiotic red pigmented antibiotic being produced and in this case it's being retained in the cell Here are some structures of antibiotics or natural products. You see penicillin to Vancomycin, we just talked about vancomycin just now, daptomycin
02:22
This is the last really approved drug And in fact, I think a lot of people you know already that this year's Nobel Prize for medicine has gone to three people two of them Campbell and Omura were involved in Identifying and developing evermectin so this is drug has an anti parasitic activity and used all over the world and the last person here too was
02:47
awarded because she Re-found artemisinin so she was going through old literature and in the Chinese literature. She found that people used Sweet wormwood a plant to cure against malaria and then so she started extracting
03:06
Artemisinin we'll come back to this story in a minute Okay, so the point is that these natural products they're very diverse in structure Some can be simple and some can be very very complex Now the first antibiotic to be discovered was penicillin in around 1940s
03:25
So called the miracle drug in those days and in the 1960s We had a really lots of antibiotics found novel antibiotics This was the so-called Golden Age of antibiotics, but then after that we've had a steady decline But on the other hand resistance has increased
03:43
So why do we have this decrease of antibiotic discovery? Well, some people say that the pharmaceutical companies are no longer interested in natural products development Why well, it doesn't make a lot of money. So if you want to get any drugs onto the market It costs a lot of money
04:00
Antibiotics usually you take it for two weeks and you're cured You don't have to take it anymore If you're suffering from cancer or from heart disease or diabetes, of course You have to take it for much longer time So you can see what's why the pharmaceutical companies don't really want to work on antibiotics anymore
04:20
Some other people say that okay people don't work on these natural products because actually there's nothing to be found out there We know that's not the case because we've genome sequence and actinomyces, it's called streptomyces clavuligerus This is in fact a commercial producer. It produces something called beta lactamase inhibitor
04:40
So if you take any beta lactams or amoxicillin or whatever There will be these beta lactamase inhibitors in there as well So when we sequence this the first thing we found shockingly enough was that we found 50 in total 50 potential secondary metabolite gene clusters Now clavuligerus is known to produce about five. We know the structures chemical structures of them
05:04
Some we don't know but we know that they make around five or six So the rest the 45 44 of these gene clusters are either asleep Not being transcribed or translated or they're producing in such small quantities that we just cannot identify them
05:21
And in fact It's not atypical for clavuligerus because we've done a global microbial genome analysis And we find there's a lot of secondary metabolite gene clusters out there So if you look at this green part here the tall the bar if it's as tall then you see that There's lots of pathways in these organisms
05:42
So this is actinobacteria here and you can see that there's lots of secondary metabolite gene clusters But in fact in all of the other microbes, yes indeed. In fact, they do have secondary metabolite gene clusters Now if you look at the blobs these blobs show you how novel these structures can be and in fact the actinomyces
06:04
Actinobacterias, of course, they have lots of secondary metabolites, but you can see that the blobs aren't as big It means that they're very similar in class. In fact, these other microbes might have much more Diverse chemical structures Okay, so we have done a proof of principle trying to awaken some of these clusters
06:23
So this is an orphan gene cluster found in a streptomyces species called streptomyces coelicolor This gene cluster was identified right before the genome was sequenced in fact, we found a few enzymes but in the end because of the genome sequence we could identify the cluster and
06:40
In fact, we didn't know that there was a secondary metabolite gene cluster apart from the ones we knew on here And so what we did was to delete this repressor and by doing so the mutant started producing this yellow color The parent usually use produces blue color and now it's producing this yellow color And in fact, we could also show that this gene cluster was responsible for a compound that has antimicrobial
07:06
Antimicrobial activity. So this is showing a bioassay that we typically do for looking at antimicrobial activity So you put a lawn of bacillus. This is a ground positive and then if you see a halo like this It means that this streptomyces here. This is a patch of streptomyces is producing a compound that's killing off bacillus
07:26
in fact The yellow compound the structure has been elucidated by Greg jealous's group and you can see that it is absolutely a novel structure So you can imagine going back to this figure, you know If we could awaken all of these potential secondary metabolite gene clusters
07:44
We're surely to have novel activity and surely find novel diverse chemical structures but if to do this, how am I gonna how are we going to do this if I have to delete one gene or Activate a promoter or take all these heterologous pathways into a different host. It just really doesn't work
08:04
It really never works. And of course, it's time-consuming. So we want something that's more systematic Something we can do high throughput and we can design and of course, we want to use synthetic biology So there was a lot of definition about definitions on synthetic biology for the past few days
08:22
My definition for synthetic biology is that it's going to be the next industrial revolution it's going to be the biotech 2.0 and Basically, it's to engineer new life forms with unrestrained versatility Which means that your imagination is the limit for using synthetic biology
08:41
Some of the examples I want to also show you because this I think gives you a flavor of synthetic biology You'll be hearing from Jeff later on tomorrow about synthetic genomes. And of course, you know the story about Craig Venter Institute using them like making the genome from mycoplasma so you can actually synthesize chromosomes
09:03
but one of the favorite projects that I like to Give as an example is those from the iGEMM competition So for those of you who don't know what iGEMM is, iGEMM stands for international genetically engineered machine competition So this happens every year. It's done by undergraduate students
09:22
There's more than 300 teams, international teams coming together to compete around October time so the undergraduate students work over the summer period to produce our microbes, usually microbes, sometimes eukaryotes, using standard parts So here's a little bit of an example. For example
09:43
Heidelberg at one year produced an E.coli that could recycle gold from electronic waste Groningen University, they made a bacillus subtilis, which is a biosensor for rotten food So, you know, we do have sell-by dates on the foods we buy but that doesn't really correspond to the real use-by date
10:08
You don't know if it's okay or gone off And of course we waste so much food now What they wanted to do was to really have some indicator biosensor where you can actually really know whether this food is edible or not, and they took meat as a example
10:22
So they engineered the bacillus It turns blue or purple if the meat has gone off and they actually made a prototype So they had spores of bacillus surrounded by media in two little plastic kind of chassets And if you wanted to activate it you kind of squish it so that the media touches the bacillus
10:41
And then you put it on your meat and if you put it on rotten meat it absolutely went purple So this is some of the ideas that they have So I think these iGEM projects give you a really good idea of what one can do with synthetic biology Another example of course all of you know who are synthetic biologists is about this artemisinin
11:01
So this is work from Jay Keasling's group and I just spoke a little bit about before because this is the Nobel Prize, not Jay but the lady who found artemisinin got the Nobel Prize So artemisinin is made from sweet wormwood and what Jay wanted to do was to produce it in Saccharomyces cerevisiae Why? Because for plants the production rate is not always consistent
11:24
If the weather's good you get lots of plants If the weather's bad you don't get much plants Okay and also it's time consuming to get You need lots of plants to be able to get lots of compound So he decided to take some enzymes using enzymes from yeast itself
11:40
but also some from plants and to make a precursor of artemisinin which is called artemisinic acid and then using semi-synthesis to get the end product So this has already been on the market It's actually free since I think two years ago now So it has been distributed to people who have malaria
12:02
Another example I want to bring up is vanillin So everyone knows about vanilla Vanilla is a mixture of tastes and the main component is called vanillin and here's the structure So the real natural extract only takes one percent of the market It's very very expensive
12:22
So all of the ice creams and biscuits and whatever you eat that has vanilla flavor is produced from lignin or coal tar Okay so a company called Evolva said okay why can't we make vanillin in yeast That's exactly what they did and they have now produced vanillin in yeast
12:42
and I think last year they already started selling it They're aiming for 75 percent of the market So that would be great if they can get that far Now at this point I wanted to bring this up because I know that Paul talked a little bit about it but I think it's something as a synthetic biologist
13:00
I don't know if it's to do with mathematics You get to this problem as well The problem about public perception We had a lot of problems when the genetic modified plants came out We don't really want to do this again but you can quickly see that how the NGOs
13:21
This is in Friends of the Earth I think Pick up all these kind of new developments It's something we have to be aware of We should be able to talk with the people, engage with the NGOs and try to say look you know we're not really doing something bad We're not trying to harm the environment In fact it's the other way around
13:41
because instead of chemically synthesizing vanillin we're trying to make it from microbes which is going to be much better for the environment and not going to be toxic to the environment as well So I think this is something that we really should keep in mind about engaging the public So the two examples artemisinin and vanillin It's great that they did this
14:02
We can make these compounds now using microbes in large scale as well But one thing that my group wants to do is to take this even one step further We want to produce compounds that nature has not seen before by using synthetic biology and this is in terms of antibiotics
14:21
And how would we do this? Of course we would use the design, build, test and learn cycle concept And this concept will be in different levels So for example we were talking about parts So parts is enzymes, promoters, ribosome bind sites, terminators
14:43
Any of these components we would design first using in silico analysis We can predict them, we can do simulations And only those that we think is going to be the best enzyme the best activity we go off and build them And once you build it of course you need to test it to see if it actually works
15:03
And this of course if it works, if it doesn't work we'll feed back into the design again And then on the devices level one can model the pathways We can design the pathways, the biosynthesis pathways How do we want it? What kind of ribosomal binding sites do we want? How strong do we want it?
15:21
Again we can simulate it And then only use the ones that we think are going to be the best build it physically And then once you build it of course you need to go off and analyse it And in this case we can do an untargeted metabolomic analysis which means that we look at the metabolite that the cell is producing as a whole And of course from this we can go back into the design
15:43
and rebuild it so that we get the best pathway On the systems level this is the cell level We can again design and model genomes And then to take those predictions actually build those chassis
16:01
deleting enzyme pathways, making more of them, so on and so forth And then again testing them And in this case we want to scale it up into bioprocessing And in fact natural products is wonderful to use synthetic biology because it's naturally modular We talked about modules, modularity before in these talks
16:24
But in fact antibiotics is naturally modular And how is it? Well I'll show you an example here of erythromycin biosynthesis The core gene, the core structure This is the core structure of erythromycin requires three huge open reading frames
16:40
There could be about 100 kB large Within these open reading frames you have modules Within the modules you have domains And these domains are these blobs And in fact the domains have the catalytic activity And what happens is it's very similar to a fatty acid biosynthesis It takes a C3 unit, loads it onto here
17:01
So you have this structure here The next module loads another C3 and does a bit of enzyme activity Does this and then another and another So you elongate this fatty acid chain And at the end an enzyme tells you to cleave it off Cyclize it and then it has some sugar modifications And you get your erythromycin
17:21
And you can see from here that there's modularity here And on this level as well And because it's modular now we can kind of cut and paste And mix things up and start thinking How can we change the actual end compound? So exactly how do we want to do this? How do we want to use synthetic biology for antibiotic production?
17:42
First of all we go to all the genomes It doesn't have to be microbial It can be from eukaryotes, anywhere As long as we can find the genomes We want to identify these secondary metabolite gene clusters We also want to identify enzymes that have special activity We want to change the enzyme activity
18:00
We want to change the substrate specificities And then we want to bring all these enzymes together With a promoter, ribosome binding sites, terminators Perhaps even regulatory circuits But at this point what's biggest difference from Something like a biosynthesis that's been done before Is to actually rewrite the DNA
18:22
So if up to now we've been reading the DNA Using DNA sequencing Now we want to rewrite it using genome synthesis Once you rewrite your complete DNA clusters You want to put this into a screening host Screen for the product that you'd like to identify
18:42
And once you've identified that compound We want to put this into a production host Because the production host is completely different screening host Because its primary metabolism will be geared The flux will be changed as well So that we can have large scale production of the compound of your choice
19:01
So when we think about synthetic pathways What do we exactly need? We need libraries of enzyme parts Because without the enzymes you really can't make a pathway You need promoter libraries, different strength Different regulatory promoters, ribosome binding sites And then you stick this together
19:21
But how are you going to make these libraries? Am I going to do it by hand? Of course not So what we've done is to design, develop some software To identify secondary metabolite gene clusters This is called anti-smash And we're on the third version already What this software does is you can put the whole genome sequence Or any gene clusters
19:41
And it will identify like here the gene by synthesis gene clusters In this case this was a genome sequence that was put into the software It identified 25 by synthesis gene clusters And then it shows you the open reading frames that you can find And even the domains as well
20:01
And it even predicts the core structure of this by synthesis gene cluster So this is a web-based software Here's the website If you'd like to use it please do We're always welcome for feedback, to hear feedback And if you have some sequences that you don't want to put on the website You can download the software locally to your desktop and use it yourself
20:26
Another software we've designed is called multi-gene blast It's very similar to anti-smash But the thing is it's not limited to antibiotic by synthesis clusters There are a lot of other gene clusters out there For example membrane-associated, differentiation, developmental gene clusters
20:45
So this is looking using If you want to look for any genes that are clustered and are conserved You can use this software to find it So using these two softwares What we've done together with the natural products community
21:00
Is to make a genome annotation standard It's an annotation standard So we can in fact even use it as a database So we've asked all the natural products community About all these different antibiotic by synthesis cluster Classes of antibiotics All these kind of different questions And we've asked them to put them onto our database
21:23
And here what's the good thing about it is If you find a new by synthesis cluster and it's similar to something You can go into MIBig and actually identify the publications that's been there What kind of experiments that's been done Who's been doing it And all these kind of information
21:43
Anyone working on natural products If you'd like to join us please do We're very happy to have you on board Okay, so another software we've designed or developed is on the devices level That means we're going to the pathway level So this is using mass spec data
22:03
That you get for peptide natural products And linking them with a genome sequence So we can actually identify which is the biosynthetic pathway And predicting that biosynthetic pathway We've also done some systems level design
22:21
And this is using metabolite modelling So there was lots of things about modelling Perhaps I can show you how modelling actually connects with design And the testing of experiments So in this case what we've done is a constraint-based model Of all these different actin mycetes strains
22:42
And the question that we wanted to ask was Which chassis, which strain is going to make a lot of my antibiotic And so here down here you see different classes of natural products antibiotics And the lighter the colour the better the host can produce it Okay, so here is streptomyces here
23:03
So streptomyces are the ones that produce a lot of these natural products And in fact if you look across Okay, so for some classes it's a very good host birth But for others not very good Now if you go down a little bit further down here You can see that this is a very good host for a lot of different compounds
23:20
And in fact these are mycobacterium species Not the pathogenic ones but the natural wild type strains So of course this is only in silico analysis We need to go back into the lab and test this whether this is true And that's exactly what we're doing now Okay, another design software modelling that we've done
23:42
Computational analysis we've done is on regulatory networks So we have some small molecules that we think are regulatory compounds For antibiotic production And in fact we've been able to show that it's a bi-stable switch For antibiotic production And we've also used the constraint-based metallolite modelling
24:03
To try and understand flux So what we did this was use Streptomyces clavuligeris The genome sequence that I talked to you about before We had transcriptome data for the wild type And the high producer of beta-lactamase inhibitor So we put these two transcriptomes data together with the metabolite modelling
24:24
And asked which pathways do we need for the high producer Or we don't need for the high producer And in fact all the green pathways, the metabolite pathways Are those that are redundant in a high producer Which means that we can minimize the metabolite pathway
24:41
Redirects the flux and at the same time minimize the genome as well Okay, now that we've designed our part We've got software that we can use to make our enzymes and pathways We have to think okay how are we going to build them The first question I had was can we actually make enzyme libraries
25:01
And can I swap enzymes around And to understand this we used the biosynthesis cluster That produces the calcium dependent antibiotic This is a non-ribosomal peptide antibiotic You can see all the amino acids are linked together And it uses one amino acid called L-hydrophenoglycine
25:23
And in fact because it's not being produced by the organism It needs the three biosynthesis enzymes embedded into the biosynthesis cluster To produce this compound So we took a look at this enzyme here And asked the question can we swap it around Can we, is there orthologs, is there homologs
25:42
In fact there are homologs and orthologs unrelated from actinomyces To test whether these enzymes can actually replace the original enzyme We deleted the enzyme original hdmo from the producer strain And then complemented these six genes or enzymes
26:02
And you can see over here in this panel We tested to see if they have bioactivity Again this is a lona bacillus And the halo means that it's killing the bacillus So yes it has antimicrobial activity It's producing something But to make absolutely sure that it's a calcium dependent antibiotic We did a LCMS and showed that it was indeed the compound that we're after
26:23
So this tells me and gives me a good idea Yes we can do this Now it's really we can make library of enzymes to make antibiotics The next thing to think about If I have the enzyme parts Now I want to put them together Okay So what's the order that I should put them together
26:42
Remember we're completely rewriting this We're coming up from scratch So we decided to use a test case for these six enzymes Which produces this compound here This is the natural orientation of the genes and the promoters That's found in streptomyces But if you think about it
27:00
Because you're going to rewrite it It doesn't have to be like this It can be like this with each promoter in front of each enzyme It can be coupled with only three It can be in all sorts directions So if you start thinking about this You have thousands of combinations that one has to test To see whether which pathway
27:22
Which orientation Which combination is going to be the best That's a lot of work I didn't want my PhD student to spend all his time making lots of these constructs So what we did was to go back to nature Nature's been using evolution to get the best out of producing compounds
27:41
So can we learn something from nature So these are five different biosynthesis clusters Which make a very similar compound to this What we found out was there was two enzymes here Two genes that are always always next to each other And in fact these are two proteins that have protein-protein interaction
28:03
And you can't split them And so now we can use this rule to start off with And say okay these two enzymes always have to be together And then carry on and start making manipulations And doing this we can try and we're learning What is the best way of constructing a pathway
28:21
What's the best promoter strengths What are the rules that we need to follow to actually design these pathways We're also doing this refactoring Building pathways using another compound which is monoterpenes So as you saw from the previous slides Antibiotics are a very complex structure
28:41
So we wanted to use something that's a little bit more simple For that we decided to use something called monoterpenes So monoterpenes in this case this is limonene Sorry it's covered up a bit now So monoterpenes are used for flavor and fragrances Like mint flavors, lots of the smells Lemon smells, grapefruit
29:01
All of these are very close to monoterpenes So what we've done now is to And monoterpenes by the way is made from plants not from microbes So what we had to do is to get enzymes from the plants And also using some from microbes as well to produce this limonene So all these enzymes here What Adrian's done is to put these pathways together
29:23
And of course we had the challenge just like Jay did How do we put them together What's the best way of putting them together What's the promoter, how about the promoter strengths Does it have to be always very strong Or does it not have to be strong So Adrian made two different constructs like this And decided and started testing them
29:40
Of course we tested for translation Here as well And tested for different strengths of promoters And then also induction levels Because these promoters can be induced by different compounds He looked at induction levels And to cut the long story short What we find is strong is not always good
30:00
It looks as though the promoters that are a bit weaker Is much better than having very very strong promoters In fact this is still on a plasmid And this is an E. coli by the way And the plasmid is quite a high copy number plasmid What we're doing now is actually putting this onto the genome To make it much more stable
30:20
And also it seems that it works much better this way Okay so we've written the genes We've made the pathways And is that all it is for synthetic biology In fact it isn't There's other things we can do Other things we can engineer Some of the things we can do in terms of spatial control We can make synthetic proteins scaffold
30:41
Or compartments Making compartments We had a speaker in the first day talking about compartments We can also make microglucone sorts So if we want to use synthetic biology for industrial biotech Really make it cheap We have to have it cheap The end product has to come down in price And the process has to come down in price
31:01
A lot of the things that people are thinking about now Is not using glucose as carbon source Rather lignin or other waste products And for that we can use some microbes Which are very good in degrading these things Converting into glucose And giving it to somebody else who can do For example biofuel production So these are the ideas for microbial consortia
31:23
So one of the things that we're doing in my group Is making compartments And you've heard already nicely about the compartments I don't have to iterize now But just the idea that if we want to express a pathway It's much more nicer to have it in a compartment Because the intermediates don't get degraded
31:41
If you have toxicity you can overcome that So what we're using is a bacterial micro compartment BMC from Ute So what this compartment does naturally Is to degrade ethylene amine
32:01
But what we want to do is get rid of this pathway here And just make this core empty shell And we can do this by expressing these five enzymes And into this empty shell What we want to do is to express monoterpenes Now monoterpenes are volatile compounds
32:21
And this is all work done in E. coli And if you try to express lots or produce lots of monoterpenes E. coli just dies It just cannot cope anymore So the idea is to put this biosynthesis cluster Into the BMC shell Encapsulate it so the E. coli is not so toxic And it can grow much better So Ash has already made these constructs
32:41
In fact we have some preliminary evidence to see That we can see these BMCs being made in E. coli Another thing we're trying to do is What you need is a tag to encapsulate these enzymes Into the empty shell And we've been able to synthesize some of these target
33:02
Sequences And Ash is also testing these as well Okay another level of things that we can do in synthetic biology Is to control its expression So it can be a very fast control Like an allosteric control Or just in time so you only have the genes expressed
33:22
When you want them Or you can have signaling molecules Which can synchronize the cell growth So in our group we're working on small molecules Called gamma-butyl lactones And these are found in actinomyces Or stratumyces in fact And if you look at the structure you can see
33:40
That it's very similar to acyl homosurine lactones So AHLs have been used as regulatory circuits Very well in E. coli And what we'd like to do is to use this As an alternative to AHL Or complementary to AHL regulatory circuits So Mark is starting to use this circuit into E. coli
34:00
And see how far we can produce a nice regulatory circuit to be used Okay so now we've designed everything We've built our pathways We've built our chassis So now we're going to produce everything fine In huge amounts But normally it doesn't work like that
34:21
And if you're engineering a chair or a shelf It's the same Even with computers or cars Sometimes you need to tweak it And so our favorite way of tweaking is metabolomics And we're using the untargeted metabolite analysis Using the high precision LC-MS
34:41
And to show that metabolomics really actually does work We've done a proof of concept experiment And this is actually inducing antisense glutamine synthetase So what it does is when you induce it It stops growth So you make a synthetic switch And this is the wild type This is the switch
35:00
And at all these time points We actually got all the metabolites And looked to see how the metabolite profiles change I think you were saying that you can only do seven experiments Well we did lots So you can see here we did five Six biological replicates That's the growth curves
35:21
Within the six biological replicates We had five time points each And then we had two LCs Two different LCs And we had the positive and negative mode as well And we did three technical replicates So that's quite a lot of samples that we tested But by doing this
35:40
We could actually see a trend Though it gives you variability in lots of From each of these samples You see variability But if you do lots enough of them You can in fact see a trend And you can see some of the compounds Like this one here Is immediately reacting to the induction So is this one While other compounds
36:02
I'm going to ask this here Are only changing when there is a stop in growth So these are all the metabolites that we saw That changed by perturbing this This is the antisense gluteus synthetase So we don't really understand why this happens
36:21
But one thing we can say is that Metabolomics is a great debugging tool Because it shows us the cell What's happening in the cell as a whole Okay so What do we need for synthetic biology antibiotics production? We need parts by synthesis
36:41
Genes from different sources We need to engineer the chassis Circuits Control of gene expression Not just on transcription but translational levels We need lots of computational software and modeling and analysis That feeds back into the building And we need to have these analytical routes
37:02
And of course this shows you the design and build test concept We really need to do this over and over again And in fact This is not just for antibiotics It can be used for any high value chemicals or functional metabolites And at this point this was my group
37:20
My intention of doing it as a group So there's one PhD student or postdoc work on different things But to get it to the next level We need to do this high throughput in a much larger scale And to do this we're doing this in our synthetic biology research center So we've been awarded from the BBSRC and EPSRC The research center which we call SYMBiocam
37:43
Which is on fine and speciality chemicals And of course we're taking the design build test cycle concept And it's housed in this building here called MIB in Manchester So what do we want to do? We want to access wide range of chemical diversity
38:02
Rapid delivery And of course we want it to be predictable And we're using this design build test cycle and platforms In fact we can do this in Manchester because we have a lot of expertise So we have lots of these All these are PIs, professors who are involved in our center
38:22
There are people like Doug Kell, John Loob and Peter Mendes Who are systems biology experts We have Nigel and Nick Turner who's our biocatalysis experts We have also Jason who's an expert in antibiotic production
38:41
Let's see, we also have Roy and Perdita who's absolutely experts in mass spec and GCs So because we have all these expertise in house This is the reason why we can actually get this center up and running And so what we've done with the center is to get the money that we received
39:03
We've made a platform All the money has gone for equipment These are all the new equipment, analysis equipment that we have Also getting lots of robotics and design softwares And of course to run all these softwares we need people And here we have now 12 SEOs appointed
39:24
Neil is upstairs as well He's got a poster on a little bit more about the design of this What we're doing in the design platform Please have a look at the poster It's on the... over here So we have also people in place And so now our ambition now is to take this into really a higher level
39:45
Making it into a production level So that we can even have real collaboration with industry And to have a product in the end from synthetic biology And last but not least I'd like to acknowledge all the people involved People in the group Symbiocam team as well
40:01
Nigel's group All these people here are informaticians I have a very good collaboration with the informaticians And I have a project with companies as well Looking for novel antibiotics And here also on the monoterpene project And I'd also like to thank all the funding bodies And thank you for listening Thank you very much
40:26
I think there's time for two technical questions So is there gold in your teeth? The microbes from biology you still have your gold in your teeth
40:40
Sorry, gold in my teeth Because you said the microbes taking out the gold from the... Ah, right, right, right ...they come to your teeth Ah, yes May I ask one question just to find here what you get Can you couple it with selection mechanism for bacteria?
41:01
I couple the selection We can couple it with selection for bacteria to fine-tune what you get Because you get it roughly and then you want to fine-tune For example, against a given pathogen you want to make antibiotics And to make a circuit with a selection Is it possible to make it? To make a circuit Circuit, yeah, of course you have electronics analysis
41:21
And then there is a selection for bacteria and then they go together Yes, why not Is it possible to make a coupling of those, right? Yes, I think so Circuit, as in circuit in the microbe, right? That's where you're thinking You know, I say okay, you still have your software, you prepare this And you make selection and then see what happens Make analysis and repeat this cycle Yeah, so the idea is really designing something, building it
41:42
And then testing and then coming back and doing it So we had some discussions in the previous section But you need to distribute the selection Yes, you need to have a good selection You need to know what you want If you don't know that, then you can't do this No, but you don't know exactly the shape of a chemical But you know what pathogen you want to make Exactly, exactly, that's right Then it's easy to organize selection schemes That's right, that's right, that's right
42:08
About the biocompartment or the mini compartment strategy So you want to produce a toxic end product And this is supposed to accumulate in those compartments Because in a way it's just postponing the death
42:21
Yes, but then even postponing it, you get more cell mass And then you can produce more Are there compartments that you could actually kick out of the cell? Not these BMCs Then another way you can kind of purify them a bit easier as well too You can try and extract them But the most important thing is actually just
42:41
Even this delaying helps with the cell mass It's just getting much more biomass Because if you don't have biomass, you don't get production So that's the idea The first antibiotic, it was not penicillin, it was Gram-C-D It was used by Dubor a couple of years before fluorine She made penicillin
43:01
Gram-C-D Yes It was before penicillin Yeah So can we make it? No, it was made before penicillin The first was not penicillin Okay, okay, that's what you mean Okay, okay, okay Okay Yeah, well identified, let's say identified Not produced, but identified No, identified, it was identified long time ago Before, you know, in the 19th century
43:21
It was a name Flaming gave the name to penicillin Right But terpefic use came in 1939 by Gram-C-D And first he was born from penicillin Penicillin was only given a name It was known there for ages Uh-huh, okay, yes, thank you It's tricky, history Yeah, okay
43:41
But for terpefic use, it was first Gram-C-D was a couple of years before penicillin Okay In 1939, I guess Right, okay, thank you I have actually a question, a brief question And if you want to produce antibiotics or look for new antibiotics Usually you find a lot of them Which inhibit the growth of other organisms, prokaryotes
44:01
But most of them cannot be used because they have negative side effects on humans Is there something in your procedure which tries to take this into account That you do not develop hundreds of potential candidates with no chance? It's all to do with the screening method Of course you can put in lots of different screening methods
44:21
I just put antimicrobial because it's the easiest But of course you can put in toxicity screening and all this in there as well too So the nice thing about this is it's flexible Whatever you want to do, you can plug into it But there is no universal way to fight toxicity It's not to be experimental Being toxic, there is no chemical way to say whether it's toxic or not
44:41
No, of course not That's why you need to do screening like using mammalian cells or whatever, yeah And then they are quite very different for different organs Pain cell is toxic, for example Yes, that's right So some industries want broad spectrum, some want very narrow spectrum So it depends on what you use as a screening