In my various readings and travelings through the complex and confusing world that is science, I have a tendency to pick up 'pet theories'. Theories that I think are so wonderful and fantastic and explanatory, and that make a lot of things that I'm doing make sense. I've never made any up myself (technically they are 'pet hypothesis' actually thinking about it) but I do steal other peoples.
My latest little pet comes from a series of papers written by Julian Davis; which look at the effects of low antibiotic concentrations on bacteria. Because antibiotics do exist in the wild, just in far lower quantities than are used in hospitals. The big question for a while has been what do they do in the wild. The common idea was that they were used for defense purposes, but they're usually released at quite low concentrations, only a few of them actually lead to death, and even then under very specific conditions.
[as an aside, Alexander Flemming (of penicillin fame) was very lucky to get the visual effect that he did. If the room had been slightly colder, or warmer, it wouldn't have worked. Naturally produced antibiotics at naturally produced concentrations are pretty rubbish when it comes to killing things]
So Davis's idea, which is an AMAZING idea, is that the antibiotics are used as signalling molecules. They are quite small molecules, which can diffuse relatively easily into the bacteria, and once inside they can effect which proteins the bacteria express. Take a look at the picture to the right (taken from this paper):
The little disks contain antibiotics, at low concentrations (known as sub-inhibitory concentrations because they don't inhibit growth). The colourful image on the right shows different levels of reporter protein. The antibiotics are effecting the level of protein expressed. If they can do it for a reporter protein, they can do it for other proteins in the cell. Antibiotic signalling could be a way for bacteria to find out and communicate information about their immediate environment, both within and between species.
Which is why the last week, back when I was still doing my project, my supervisor pulled our crazy-result plates out of the incubator, shook her head turned to me and said "Look. They are talking to each other!"
This is all epigenetics by the way, rather than genetics. The antibiotics are effecting which proteins the gene expresses, and at what levels, rather than changing the genome of the bacteria.The bacteria I've been working on, for example, have about 20 'silent genes' which don't get expressed in lab conditions, maybe antibiotic signalling would turn some of them on?
It's a lovely idea, and it fits in so well with the results I've been getting. I will reverentially place it with the Histone Code Hypothesis and the Aquatic Ape Hypothesis, in the place in my head reserved for pet theories.
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in The Biology Files
How bacteria make antibiotics
There are many different types of antibiotics bacteria can make, but my lab project (now finished, alas) was concentrating mostly on a type called polyketides. These are not just antibiotics, some polyketides can also be antifungals and anticancer agents too, so it's not surprising that quite a lot of work has been done characterising their formation.
Here is the molecular structure of erythromycin. Like many polyketides it is circular, which at first appears to be a bit of a headache to synthesise. The way it's put together, though, is actually very clever. The backbone of the circular section is made up first, using a system of modular enzymes that pass the growing chain along like a conveyor belt, adding new residues at each stage. Then the straight chain is curled up into a ring, and finally the two side residues (the ones on the bottom right of the chemical structure, that look a bit like squashed rectangles with dents in them) are stuck on.
So here is the picture that has appeared on every slide show in every lab meeting we've had this term, showing the formation of the straight-chain backbone before it gets curved into a circle:
Ignoring the little letters (which are just names of enzymes) it really does look a lot like a conveyor belt. At each stage the chain is lengthened, before finally being taken off and twisted around onto itself (to form a circular molecule called DEB). The modular nature of this system is fascinating to work with, but a real problem to sequence. DNA sequencing techniques work mainly by chopping the genome up, sequencing the bits, then trying to stick them back together and modular repeats tend to confuse them.
The last stage, going from DEB to erythromycin, is just a matter of decoration. Although the squashed-rectangle additions (glycosylases, added by glycosylation I believe) look complex, they are quite common molecules that get added onto things in the cell. Glycosylase residues and glycosylation enzymes are very common.
And that's how bacteria make polyketides :)
Here is the molecular structure of erythromycin. Like many polyketides it is circular, which at first appears to be a bit of a headache to synthesise. The way it's put together, though, is actually very clever. The backbone of the circular section is made up first, using a system of modular enzymes that pass the growing chain along like a conveyor belt, adding new residues at each stage. Then the straight chain is curled up into a ring, and finally the two side residues (the ones on the bottom right of the chemical structure, that look a bit like squashed rectangles with dents in them) are stuck on.
So here is the picture that has appeared on every slide show in every lab meeting we've had this term, showing the formation of the straight-chain backbone before it gets curved into a circle:
Ignoring the little letters (which are just names of enzymes) it really does look a lot like a conveyor belt. At each stage the chain is lengthened, before finally being taken off and twisted around onto itself (to form a circular molecule called DEB). The modular nature of this system is fascinating to work with, but a real problem to sequence. DNA sequencing techniques work mainly by chopping the genome up, sequencing the bits, then trying to stick them back together and modular repeats tend to confuse them.
The last stage, going from DEB to erythromycin, is just a matter of decoration. Although the squashed-rectangle additions (glycosylases, added by glycosylation I believe) look complex, they are quite common molecules that get added onto things in the cell. Glycosylase residues and glycosylation enzymes are very common.
And that's how bacteria make polyketides :)
Scanner Woes
How many times have I heard it on deviantart.com? The continual cry of "Oh noes! The scanner ate my picture!" And now I'm making the same complaints about mine.
Actually, my plate pictures haven't been too bad. Although a couple of them are somewhat ... darker and fuzzier than they could be. As there are no labels for anyone to pinch my results with, I think I am justified on posting a few on here:
That one's alright. A bit dark though. At least the contrast can be seen. In case anyone was wondering, what you are seeing is bacteria streaked across the plate and left to grow (marked by the black line across the plate) and the another bacteria grown on top of it, which has subsequently been killed.
But as this may turn into a paper (oh please! *crosses fingers and hopes*) I can't be any more specific.
This one (on the right) hasn't really come out at all. meh. There's not much I can do except tell people what they should be seeing and hope it all works out alright. So what you should be seeing is a patch of dead overlay (the light bit) that follows the line of the mould (crosshatched black pen), but is not actually present under most of the mould.
I have a dissertation to write up based on these! *panic*
On the plus side, my scanner seems to have also created some results of its own. Take a look at this bioassay:
See the white lines around the circles on the first two rows? They were not at all obvious in the photo. Although when I squint at the photo now I can kind of see them.
Yes, that is my handwriting at the bottom of the photo. Which was taken by yours truly in the (very old) lightbox, narrowly avoiding getting an accidental blast of UV light as well (UV light is used to take pictures of gels, and nobody bothers to switch the switch back to 'white light' when they've finished; noticed just in time)
I am very proud of all my results :) Which has probably confirmed for a Certain Special Someone that they are indeed going out with a very nerdy little thing.
=D
Actually, my plate pictures haven't been too bad. Although a couple of them are somewhat ... darker and fuzzier than they could be. As there are no labels for anyone to pinch my results with, I think I am justified on posting a few on here:
That one's alright. A bit dark though. At least the contrast can be seen. In case anyone was wondering, what you are seeing is bacteria streaked across the plate and left to grow (marked by the black line across the plate) and the another bacteria grown on top of it, which has subsequently been killed.
But as this may turn into a paper (oh please! *crosses fingers and hopes*) I can't be any more specific.
This one (on the right) hasn't really come out at all. meh. There's not much I can do except tell people what they should be seeing and hope it all works out alright. So what you should be seeing is a patch of dead overlay (the light bit) that follows the line of the mould (crosshatched black pen), but is not actually present under most of the mould.
I have a dissertation to write up based on these! *panic*
On the plus side, my scanner seems to have also created some results of its own. Take a look at this bioassay:
See the white lines around the circles on the first two rows? They were not at all obvious in the photo. Although when I squint at the photo now I can kind of see them.
Yes, that is my handwriting at the bottom of the photo. Which was taken by yours truly in the (very old) lightbox, narrowly avoiding getting an accidental blast of UV light as well (UV light is used to take pictures of gels, and nobody bothers to switch the switch back to 'white light' when they've finished; noticed just in time)
I am very proud of all my results :) Which has probably confirmed for a Certain Special Someone that they are indeed going out with a very nerdy little thing.
=D
Yes but what does it do...
I am currently trying to get myself to finished writing an essay (rather terrifyingly my first essay of term) on the different approaches to gene annotation in vertebrates. As I've just woken up (afternoon naps seem like such a good idea until you wake up with a mouth that feels like a hamster died in it) I thought I'd give a quick summary of gene annotation methods:
Gene annotation is the 'interesting' bit of genomics. Quite a lot of gene sequencing work has been done, some of it (especially the human bits) very highly publicised. And while genome sequencing is probably useful (more on that maybe in a more ethically-inclined post) on it's own it's not terribly exciting. You're left with a big database full of mindless streams of nucleotides and one bit embarrassing question:
What does it all do?
Gene annotation attempts to answer that; trying to work out which proteins each gene codes for, essentially what the end function of the genome is, what each piece of DNA is used for. There are two main methods: just using DNA, and using data from protein/cDNA sources. Both of these methods can be either comparative or non-comparative:
1) Just using DNA: Non-Comparative
This relies on getting a program such as GENSCAN to, quite literally, scan along the DNA looking for the beginning and end of genes based on sequence patterns it had been told to recognise. Not so good for function, but useful enough for finding the damn genes in the first place. Also relatively cheap and you can go run it overnight.
2)Just using DNA: Comparative
Like it says, this compares your DNA with other previously annotated pieces of DNA to see if there are any very similar bits it can ascribe function to. It's a good starting point, especially now the pool of annotated genomes is increasing, but it's really bad at finding gene start point, especially when there are 'introns', or bits of DNA that are not actually turned into protein. Which is around 95% of the human genome incidentally. (an e.g of this, if anyones interested, is TWINSCAN)
3) cDNA/Protein data: Non-comparitive
cDNA, just to clarify, is DNA that has been reverse transcribed from RNA templates; i.e itt's all the DNA that will get turned into protein, and without any of the introns. A good way to use this is to make cDNA 'libraries' i.e all the cDNA within the cell stored on plasmids, choose one at random, see what it makes and, at the same time, find where it is in the genome. Simple and useful.
4) cDNA/Protein data: Comparative
This compares your genome with bits of cDNA from other genomes, where the cDNA has known function. Protein comparison is even more useful as seeing what protein your protein most resembles provides structural information, as well as functional and allows you to build up homologous families of proteins with similar function (if you have enough genomes). Also if you have enough protein data you can say you're doing 'proteomics' and the more 'omics' words in your project, the more funding you're likely to get :)
By the way, all of these comparative methods are based on homologous evolutionary relationships between the genomes, so anyone who says that scientists never use evolution is WRONG. (and probably pissing off the evodevo people as well)
As always, any questions are welcomed, leave them in the comments and I'll get back to you.
Gene annotation is the 'interesting' bit of genomics. Quite a lot of gene sequencing work has been done, some of it (especially the human bits) very highly publicised. And while genome sequencing is probably useful (more on that maybe in a more ethically-inclined post) on it's own it's not terribly exciting. You're left with a big database full of mindless streams of nucleotides and one bit embarrassing question:
What does it all do?
Gene annotation attempts to answer that; trying to work out which proteins each gene codes for, essentially what the end function of the genome is, what each piece of DNA is used for. There are two main methods: just using DNA, and using data from protein/cDNA sources. Both of these methods can be either comparative or non-comparative:
1) Just using DNA: Non-Comparative
This relies on getting a program such as GENSCAN to, quite literally, scan along the DNA looking for the beginning and end of genes based on sequence patterns it had been told to recognise. Not so good for function, but useful enough for finding the damn genes in the first place. Also relatively cheap and you can go run it overnight.
2)Just using DNA: Comparative
Like it says, this compares your DNA with other previously annotated pieces of DNA to see if there are any very similar bits it can ascribe function to. It's a good starting point, especially now the pool of annotated genomes is increasing, but it's really bad at finding gene start point, especially when there are 'introns', or bits of DNA that are not actually turned into protein. Which is around 95% of the human genome incidentally. (an e.g of this, if anyones interested, is TWINSCAN)
3) cDNA/Protein data: Non-comparitive
cDNA, just to clarify, is DNA that has been reverse transcribed from RNA templates; i.e itt's all the DNA that will get turned into protein, and without any of the introns. A good way to use this is to make cDNA 'libraries' i.e all the cDNA within the cell stored on plasmids, choose one at random, see what it makes and, at the same time, find where it is in the genome. Simple and useful.
4) cDNA/Protein data: Comparative
This compares your genome with bits of cDNA from other genomes, where the cDNA has known function. Protein comparison is even more useful as seeing what protein your protein most resembles provides structural information, as well as functional and allows you to build up homologous families of proteins with similar function (if you have enough genomes). Also if you have enough protein data you can say you're doing 'proteomics' and the more 'omics' words in your project, the more funding you're likely to get :)
By the way, all of these comparative methods are based on homologous evolutionary relationships between the genomes, so anyone who says that scientists never use evolution is WRONG. (and probably pissing off the evodevo people as well)
As always, any questions are welcomed, leave them in the comments and I'll get back to you.
Disclaimer: This post was written while half asleep. Any spelling/grammer mistakes are therefore completely the fault of the writers Brain On Sleep.
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