Microbes and Climate Change

Since the very first little blobs of entropy-defying life first appeared around four billion years ago, micro-organisms have played a major role in shaping the temperature of the planet by adjusting the balance of gases in the air. It could even be argued that global warming was one of the first effects of life, when the first methanogens (methane producing bacteria) started pumping greenhouse gasses into the new atmosphere. The evolution of photosynthesis lead to the great oxidation event, and over time the balance of gasses in the atmosphere stabilised into its current composition: lots of nitrogen (controlled by nitrogen fixing bacteria), medium amounts of oxygen (controlled by photosynthesis) and much smaller amounts of carbon dioxide (also controlled by photosynthesis, of both plants and bacteria).

Until humans, the general gaseous air composition was controlled almost exclusively by bacteria, with plants (mostly algae) having a lesser effect on carbon and oxygen levels. Animals didn't really get much of a look in until humans started releasing all the locked up carbon in fossil fuels.

Bacteria that are currently contributing to global warming are the methanogens, most notably those in the gut of ruminant mammals (i.e cows, sheep and other edible things). Cows and sheep can't break down cellulose in the plant material that they eat, so they have bacteria that do it for them. Unfortunately this process releases huge amounts of methane, and methane is around 20 more planet-warming than carbon dioxide.

When I went to Copenhagen last year (I didn't go for the conference, in fact I didn't realise it was on until I started wondering why it was so hard to find a hostel room!) someone handed me a leaflet saying that climate change could be prevented if everyone in the world became a vegetarian. It was an ... interesting point of view, but you could see where the idea came from. Cows are little methane factories.

Just in case anyone forgot what a cow was.

However bacteria are also heavily involved in keeping climate change under control with photosynthesis, which uses up carbon and releases oxygen into the environment. Despite being very leafy and green, forests (even rainforests) tend not to be huge carbon sinks, they take up carbon during the day certainly, but at night they respire and use most of it up again, and anything they've stored tends to be released once they die and decompose. Marine cyanobacteria, however, take in carbon like its going out of fashion, and when they die they sink down to the bottom of the ocean and lock it all away in calcified rocks. One of the most prolific carbon-eating bacteria is Prochlorococcus. Around 100 million Prochlorococcus can be found in every litre of seawater and, along with fellow bacteria Synechococcus it removes about 10 billion tons of carbon from the air every year.

In terms of helping to moderate climate change, there are plenty of ideas floating around as too how bacteria could be useful, but one of the more helpful ones is trying to make a bacterial-based carbon neutral biofuel. The idea is that if you find bacteria that take up as much carbon for their growth as they release while being used as fuel they are technically 'carbon-neutral'. You can grow pretty much anything in bacteria, up to and including oils that can drive cars, it's just currently not very efficient.

Whether or not anything can be done to stop climate change (or, more importantly, whether or not people can agree to do anything) may be an unresolved issue, but its becoming clear that the issue of how the worlds climates are changing is a subject for microbiologists and plants-scientists as much as for meterologists. Whatever happens to the climate in the future, bacteria will still have a large part to play.

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Exams and course-work are all over, so from now on I am hoping to keep this blog purely for the prokaryotes:

Craig Venter's Synthetic Genome

I'm taking a miniscule break away from revision to quickly write my thoughts about the news thatt Craig Venter has finally made a 'synthetic cell' or, as Psi Wavefunction more correctly pointed out, a synthetic genome inside a normal cell. It's quite a landmark for synthetic biology; not only has an entire genome been constructed from scratch, but it's also able to replicate and make new bacteria with the same genome.

What the researchers did was to synthesise an entire genome, that is all the DNA present in the bacterial species Mycoplasma mycoides (1.08 Mbp - mega-base-pair for anyone interested), by making lots of 6 kpb (kilo-base-pair) pieces and splicing them together in yeast. They then had to carefully get the completed genome out of the yeast, and put it into an empty (i.e containing no other DNA) M. mycoides cell. The resulting bacterial cell contained only synthetically made DNA, and was capable of surviving and replicating quite happily.

Above is a scanning electron microscope picture of the dividing cells

Probably the first thing to notice about this is despite it being pretty damn impressive, it's not exactly the creation of new life. It fact, I'm not sure I'd say it's even the creation of life, just the creation of a working genome. And despite what Richard Dawkins might think you need a lot more than just a working genome to be defined as life, especially life as complicated as a bacteria. What's been achieved here is sort of the bacterial-genome equivalent of in vitro fertilisation; the DNA has been synthetically made, but it's been put into a working bacteria, containing all the proteins, lipids and other molecules that are essential for life.

I'm certainly not putting this down, it's an amazing piece of work which makes my excitement over getting a 6kb gene synthesised over the summer seem very childish. But heralding it (or indeed condemning it) as 'Scientists create life' is a little over the top. DNA is, if anything, one of the easiest things to make in the cell, given it consists of different rearrangements of four base-pairs, all in a long string. Small bits of DNA have been synthesised for a while, but as yet, no one really has much of a clue how to synthesise bacterial cell membranes, let alone how to get them to synthesise and replicate themselves.

This is the genome that Venter built. The text in the middle shows the process in full. The little letters around the edge (BssH II etc) show sites for restriction enzymes which are used to cut the genome into little pieces for analysis.

One of the questions that always comes up whenever synthetic biology is mentioned is "how safe is it?" after all, this is a man-made genome going into a bacterial cell. Surely you could make another, more dangerous genome, and put that inside a bacteria and then use it to cause destruction, or a B-movie sci-fi plot? I suppose the risk is always there but in all reality, there are much better, cheaper and faster ways to ensure destruction happens. It took Venter's team six years to get this whole thing completed and working and while it's true that the process is only going to get faster I don't see it getting any quicker than rummaging around under the sink and coming up with enough ingredients to explode. Last summer it took around one and a half months to get my 6kb gene sequenced, and two months of work completely failing to make two very small mutations in another 2kb gene. There are people who fiddle around in their garages doing synthetic gene cloning, but there appears to be a pretty non-existent overlap with terrorist activity.

So this is a big step for genomes, but a tiny step towards a fully synthetic cell. Getting the full genome was a matter of time, patience, a large supply of base-pairs, plenty of money, and doing something clever with the base-pair methylation. Trying to make a synthetic membrane requires understanding how the things work first. Every new organism starts its life in a little cocoon of useful proteins, internal-membrane structures and little filaments which help to organise DNA expression even as the DNA controls their production and regulation. Putting new DNA into this pre-existing system is something that organisms do every time they replicate. Making the whole system from scratch is something that's never actually been done before, given that each generation has at best just tweaked the design a little from whatever the original cellular background was - probably just a quick scattering of proteins surrounded by a couple of glycolipid layers. Over the billions of years it's had to evolve, this has created a mysterious and highly complex system which would be incredibly difficult for a research to attempt to replicate.

I bet Venter's labs are trying though. They had pretty-much succeeding at creating synthetic ribosomes last time I looked.

Gibson DG, Glass JI, Lartigue C, Noskov VN, Chuang RY, Algire MA, Benders GA, Montague MG, Ma L, Moodie MM, Merryman C, Vashee S, Krishnakumar R, Assad-Garcia N, Andrews-Pfannkoch C, Denisova EA, Young L, Qi ZQ, Segall-Shapiro TH, Calvey CH, Parmar PP, Hutchison CA 3rd, Smith HO, & Venter JC (2010). Creation of a Bacterial Cell Controlled by a Chemically Synthesized Genome. Science (New York, N.Y.) PMID: 20488990

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Exam Term

Aka ... will you look at that, it's another hiatus!

Exams are coming up in less than three weeks now (scary thought ...) and as these are my finals I really do have to try and make a good go of them. So there will be a spooky silence on the twitter and blogging front, although I may occasionally jump into the Other Blog for some literature-related stress relief.

After exams though I will be completely free and still very much into science. I have a summer project all lined up, so expect more bacteria-related posts to return in full flood once I get these pesky tests out the way.

And if anyone is in Cambridgeshire, and owns a lab, and is happy to pay a Lab Rat to work in it from October, please do get in touch. :)

Student Symposiums

I'm currently in the middle of a two day symposium for the students. We all make a presentation of our work, and then show it to fellow students and any staff that happen to be floating around. I know this has been done before, but it honestly feels like speaking (and listening!) in code, especially having talked to all my friends before hand and heard the true stories behind the neat little slides. So here's the student version of what you say in a presentation (on the left) vs. what you actually mean (on the right):

In vivo	It works, but I don’t know why
In vitro	It works if I fiddle the salt concentration
In silico	The computer says it works!
It is known that	I’m sure I read a paper on this
It is thought that	My supervisor thinks that
It is generally thought that	The PostDoc agrees with the supervisor
It is believed that	I think that
Unpublished work by Dr. X shows that	My supervisors friends think that
Results were not conclusive…	It didn’t work
… despite multiple repetitions…	Didn’t work the second time either
…including work done by Dr. Y…	Still didn’t work when my supervisor did it
…and collaboration with Dr. X…	Or my supervisors friends
…and attempts at methods suggested by the literature…	IT IS SERIOUSLY NOT MY FAULT THAT THIS DIDN’T WORK
The results show	My correlations are good
The results indicate	My correlations are present
The results suggest	My correlations only work if you ignore the error bars
The results seem to suggest	I have no correlations
The results, although inconclusive, may be helpful…	I have no results

Modelling Virotherapy for Cancer

Most cancer-related research, particularly medical cancer-related research tends for rather obvious reasons to involve animal research, and while I'm more than willing to agree that it's a necessary sacrifice it does always make me feel a bit squeamish on a personal level. Which was why the first thing that struck me when a certain jazz-playing poetry-writing philosopher-doctor sent this paper my way was that it was involved in developing a mathematical model for treatments. Not to replace animal testing, obviously, but to cut the tests down to those that were more likely to work, reducing the need for animal use.

The paper is exploring glioma virotherapy, which uses synthetic viral capsules to target cancer cells and kill them, while not harming the surrounding normal cells. These viruses are known as ontolytic viruses and while they may originate from harmful strains they've had almost all of their own DNA knocked out, turning them into little balls of protein designed to target cancer cells only. This approach has several problems associated with it, but one of the main ones is that the human body generally doesn't like having virus's inside it. Any injected cancer-targeting virus capsids are in danger or being effectively destroyed by the bodies immune system.

One solution to this is to use immunosuppressants, which naturally comes with problems of its own, including the question of dosage. How much immunosuppressant do you give the patient, depending on the corresponding number of viruses used, and the size of the cancer. In order to explore this without having to kill huge numbers of rats, Friedman and colleagues developed a model to explore the effects of differing virus and immunosuppressant concentrations.

First, they needed to specify the parameters they were using:

Number of tumour cells infected with virus = y

Number of tumour cells uninfected = x

Necrotic (dying) cells = n

Immune cells (destroying the viruses) = z

Free virus particles = v

Then some rates to take into account:

Proliferation of non-infected cells = λ

Infection rate of tumour cells = B

Diffusion coefficient of virus particles = D

Adding this all together with some mathematical magic (and a function to include immunosuppressant levels) leads to what is to me a totally incomprehensible series of mathematical squiggles (anyone whose desperate to read them can find them in the appendix of the reference paper below). But somewhere along the line the magic works, as seen when they compare it to experimental data:

The table above (from the reference) isn't remarkably clear, suffice to say that the blue bars are the actual experiment results (carried out in rats) while the red bars are the results of the model simulation. Graph A shows infected tumour cells (after 6 and 72 hours), graph B shows immune cells (after 6 hours 72 hours and just before the rat dies) while graph C shows the immune cells after addition of the immunosuppressant (after 6 hours, 72 hours, and just before the rat dies). The x-axis shows the percentage of cells.

Having got a model that shows a reasonable degree of accuracy, the experimenters can then play around with the parameters without any more rats having too be involved. For example they can explore the effects of adding more viruses. More viruses in the system increase the immune cell response, even in suppressed patients (although obviously the response is lessened). However as the numbers of viruses decrease, the immune cells start to leave the area, allowing any viruses that have survived to quickly recover the population and the immune cells rush back in again. This leads to a feedback loop which, with my knowledge of the effects of the immune system, can't be all that good for the patient.

The results below from the model show the effect of adding varying amounts of virus on the number of infected tumour cells.

The cyclical pattern can be clearly seen, especially for the larger numbers of viruses (the blue, red and green lines represent increasing numbers of virus's injected into the system - as the colours are rather faint the blue line is the mostly straight one, the red line is the bumpy one and the green 'line' is a series of peaks). The model was also used to explore different concentrations of immunosuppressant and different dosage schedules (one a week, twice a week etc.) for treatment.

There are limitations to the model, it only considers injections into the centre of spherical tumours, for example, and does nothing to model any potential problems caused by metastasis (bits of the tumour breaking off and moving away). However is does provide the framework of a system to explore different options for bench experimentation, to ensure that any work that is done on animals will be the useful and relevant for the development of this system into a working treatment for human cancers.

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Friedman, A. (2006). Glioma Virotherapy: Effects of Innate Immune Suppression and Increased Viral Replication Capacity Cancer Research, 66 (4), 2314-2319 DOI: 10.1158/0008-5472.CAN-05-2661

Iron and Stress

Iron is a metal that is essential for all living things as it is heavily involved in cell redox reactions and the electron transport chain (a major part of aerobic respiration). However it is strongly reactive with oxygen - outside of living organisms this leads to rust, inside it can lead to the production of dangerous reactive oxygen species - and therefore needs to be controlled and contained within the cell. In order to provide this control, all living organisms (apart from yeast, weirdly enough) use a protein called ferritin. Multiple subunits of ferritin proteins (usually 24, although occasionally only 12) form an outer shell, with a central cavity that can contain around 2000-400 individual ferric ions (iron ions) keeping them safely out of harms way.

Diagram shows the shell created by ferritin (iron, or ferrous, ions help inside). Image from wikimedia commons.

In plants, the ferritin proteins are found in non-chlorophyll containing plastids, and occasionally in mitochondria (although no one is quite sure why). Many plants contain a number of different genes coding for ferritin proteins which, due to a high similarity in sequence identity and functional redundancy (i.e. most of them do similar things) makes individual ferritins difficult to study. The small weed Arabidopsis thaliana is a good model organism in this case as it contains only four ferritins, imaginatively names AtFer1-4.

These four ferritins are expressed differently at different stages of the cell lifecycle, and in responses to different materials. The diagram below shows which genes are upregulated in response to the oxidative compound H2O2, free iron (Fe) and the plant hormone abscisic acid (ABA):

Upstream of the AtFer1 gene is a 15 base pair sequence named IDRS (iron-dependent regulatory sequence) which is used to repress the gene under iron deficient conditions. This is thought to be upregulated by a phosphatase (which would remove phosphate from a DNA binding protein bound to the IDRS) which in turn is upregulated by the plant hormone NO (nitric oxide). The kinetics of AtFer3 are very similar to AtFer1 and it is therefore thought to be regulated by a similar system. AtFer2 may be activated in a different manner, and it shows very different kinetics to the other three genes. It does contain an IDRS sequence upstream of the gene, but it is not certain whether this is functional.

Despite containing a large source of iron, ferritins are likely to function more to prevent the damage caused by reactive oxygen species (caused by reactions of free iron) rather than as an iron store. Mutant plants containing no ferritin do not have an immediately obvious phenotype (outward appearance) although if extra iron is added they have to produce a large number of energetically wasteful detoxifying enzymes, in order to combat the dangers of oxidative stress. Ferritins therefore seem to have evolved not as an iron storage system, but as a buffering mechanism, to allow increases in iron within a plant to have a beneficial, rather than damaging, effect.

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Briat JF, Ravet K, Arnaud N, Duc C, Boucherez J, Touraine B, Cellier F, & Gaymard F (2010). New insights into ferritin synthesis and function highlight a link between iron homeostasis and oxidative stress in plants. Annals of botany, 105 (5), 811-22 PMID: 19482877

The Predictive Power of Evolution

This post is not a breakdown of a paper, but purely an opinion piece based on my own views. I'd love to hear any different opinions people have, feel free to leave them in the comments box.

Definitions of scientific theory can vary slightly (usually depending on the theory the person currently making the definition has in mind) but they tend to boil down to a few basic elements. Explaining observational data, creating a model, falsifiability and predictive power are some of the most usual phrases used. The idea of the predictive power of a theory is an important one, both because it's a good way to make a distinction between a theory and an observation and because it imparts some kind of real-world use to the science.

One of the criticisms of the Theory of Evolution is that at first glance it appears not to contain any appreciative predictive power. You can trace the evolutionary lineage of a horse, or a whale (or a staphylococcus bacteria if you are so inclined) but you can't make any predictions about what they're going to turn into next. What strange creatures will be walking the earth in five thousand years time is occasionally brought up on random TV shows but there's hardly a way to test the accuracy, and it's not exactly science.

However this criticism seems to be conflating 'prediction' with 'predicting the future'. Very few scientific theories can predict the future. Mendelian theory can predict the likelihood of future outcomes, and I'm lead to believe that Newtonian physics can predict planet orbitals to a certain extent (provided you nudge mercury sideways occasionally) but generally the predictive power of a theory can be used to provide explanations for observations without needing to try and head into the future at all.

To use an example from my current revision: chloroplast gene movement. Chloroplasts are little organelles in plants that carry out photosynthesis and contain the green-coloured pigment that makes plants look mostly green. They are thought to have arisen (and there is by now lots of substantive evidence for this) when a free-living cell engulfed a little photosynthesising bacteria (image below taken from George Washington University page explaining eukaryote evolution):

As the little photosynthesising bacteria contained its own DNA the new chloroplast containing cell now has two genomes, the one in the nucleus and the one in the newly-made chloroplast (ignoring mitochondria for the minute to make things simpler). However when you look at modern plants and compare the chloroplast genome to any bacteria genome you can see that the chloroplast genome is massively reduced. Most of the genes have been lost. Further research will identify several of these chloroplast genes inside the nucleus. The genes have migrated out of the chloroplast, and into the nucleus, where they are being expressed by the nucleus.

There's plenty of reasons why the genes would want to be in the nucleus. It provides centralised control, it keeps the DNA safe from all the reactive oxygen species in the chloroplast, and it means that the chloroplast genes can experience sexual selection. However not all of the genes have left. Some have remained inside the chloroplast, and the question is, why? If the nucleus is such a good place to be, why do some genes get left behind?

In answering this (in fact in answering many question here, including why the genes left as well as why some remain) the theory of evolution can be used to provide a predictive framework in which to suggest an answer. These predictions can then be tested with the data to see which ones fit. In the case of why genes remain in the chloroplast, for example, our theory tells us that if there is a reason (they might just have remained through chance if it was one event that transferred the genes, or they might still be moving) it will be to give the cell an evolutionary advantage. These are genes, and there is a lot of selective pressure on what happens to genes, especially in bacteria, which have a limited supply. The genes that stay behind must provide a selective advantage, there must be a reason why these genes help the chloroplast, and the cell to survive, better than they would if the genes moved to the nucleus.

Once in the nucleus, the genes are used to make the corresponding protein, and this protein is then transported back into the chloroplast. In view of this, one of the first suggestions made was that the genes left behind coded for big bulky proteins that were hard to transport through the chloroplast membrane. Chloroplasts that lost these genes would loose valuable proteins, leaving them at a disadvantage. It's a nice prediction, but unfortunately it got shot down after a close examination of the genes that had actually moved revealed that some of them did code for quite big bulky proteins. And artificially moving some of the bigger and bulkier protein-coding genes into the nucleus showed they could get back into the chloroplasts quite happily, although not quite as efficiently.

Another prediction made (which is looking far more likely) is that the genes left behind very specifically control the redox potential (the balance of positive and negative ions) inside the chloroplast. Due to the photosynthesis the chloroplast is carrying out, the redox potential can change quite dramatically (and regularly) and it needs to be sorted out quickly if it does, as it has the potential to cause a lot of problems within the chloroplast. Having the genes that need to respond to redox change in the nucleus means that a) it takes a lot longer for the signal to get to the nucleus and get the proteins made and b) once the proteins are made they will be sent to all the chloroplasts, despite the face that different chloroplasts will be in different redox states. So far the evidence supports this prediction.

Without the theory of evolution behind this, there's almost no reason to look for a reason. Why the genes moved, and why some stayed behind can be answered by 'they just did'. The framework of an answer that requires an increase in the 'fitness' of the resulting organism helps to give suggestions, and predictions, that can be looked into with further study and gives a focus for directed research.

Extended Hiatus

I had hoped that my little holiday-hiatus wouldn't last much longer than two weeks. However due to a certain volcano going off, I am now stranded in the land of Dial-Up Internet and not quite sure when I'll be getting back. The time I do spend on the internet is spent contacting my partner, trying to download papers and trying desperately to get in touch with my supervisor who has an electronic copy of my (as yet unchecked) dissertation I would really like her to take a look at.

I have a horrible feeling she's stuck in an airport in Canada...

So while the forces of plate-techtonics conspire against my Finals I don't have all that much time for blogging. I'll return as soon as I can, with lots of science stuff (most of it about plants probably, as I'll still be revising) but until the ash clears there won't be anything.

It's really irritating, as I want to get into proper paper-trail revision, which I can't do without an internet source. And the deadline for my dissertation is the Wednesday after next, so I really need to be back by then.

Also I have a library book with me that just went overdue...

(On an unrelated note something happened on the 11th - my page views took a spike. Thank you to whoever-it-was that caused that! Much appreciated, expecially as I'm not able to write much at the moment).

How The Animal Lost Its Sensor

Two-Component Systems are one of the major sensory systems used by bacteria to detect and respond to changes in both their outside environment, and their internal state. I cover them in more detail here, but just in summary they consist of two proteins,a sensor and a responder. The sensor senses the change, and activates the responder, which binds to the bacterial DNA and leads the production of a protein that will enact a suitable response.

Although Two-Component Systems (TCS) are found in all three superkingdoms of life (Archaea, Bacteria and Eukaryotes) they are suspiciously absent from the animal kingdom. Plants have them, as do fungi and several protazoa, but they just aren't present in animals. For this reason they've been looked into as potential antibiotic targets as knocking out the Two-Component Systems of most bacteria is fatal.

Why don't animals use TCSs? To answer this you have to start looking at the evolution of the system itself, because despite being nominally present in eukaryotes such as plants and fungi, TCSs are used very differently in bacteria and archaea. Bacteria use TCSs for sensing a wide variety of signals; stress, metabolism, nutrient regulation, chemotaxis, pathogen-host interactions etc. in eukaryotes on the other hand, they are used sparingly, for ethylene responses and photosensitivity in plants and osmoregulation in fungi and slime moulds.

Bacteria (especially soil bacteria which have a lot of environment to sense) can contain up to 50 TCSs although many internal parasite bacteria (with a lot less to sense) contain far less. The maximum for Archaea is around 20 TCSs. Eukaryote number drop right down, with only one in the yeast Saccharomyces cerevisiae (one sensor kinase and three response regulators). None have yet been found in any animal genomes, or in the few partial protist genomes sequences (although I doubt if anyone's had a complete scan through the protist genomes for them).

Comparing the TCSs of Bacteria, Archaea and Eukaryotes leads to the interesting conclusion that the bacterial and eukaryotic systems are far more closely related than the archaeal, and in fact are thought to be monophyletic (all evolved from a single common ancestor). In contrast, the archaeal TCSs appear to be polyphyletic and some archaea lack TCSs entirely. It's therefore thought that TCSs originated in bacteria and spread by horizontal gene transfer to both archaea and eukaryotes (until the eukaryotes developed a nuclear membrane). In eukaryotes very little further diversification took place, whereas the bacterial TCSs diversified widely, and occasionally passed new systems back to the archaea. I've tried to show this in the diagram below:

Diagram made by Lab Rat. Red arrows show the movement (straight arrows) and duplication (curved arrows) of TCS genes. No horizontal gene transfer can take place in eukaryotes after the nuclear membrane (well....it *can* do but very, very rare) although gene duplication may still have occurred.

The eukaryotic kingdom appears not to have contained very many of these TCS genes to start with, and the animal kingdom may just have lost the very few it possessed. This makes sense from the point of view of cellular control because while TCSs are very useful in the small genomed and non-nuclear membrane containing bacteria, it's less clear how useful they are in eukaryotes as a whole. Introducing a membrane around the nucleus makes it harder for proteins to get in and bind to the DNA, and introducing systems of membranes inside a far bigger cell makes it harder for a simple two-component system to sense what's going on. Added to which, cells inside a multicellular organism don't really need to sense what's going on, they get told what's going on by the surrounding cells and circulating hormones.

Whatever the reason though (and any other ideas would be welcomed, the above paragraph is mostly speculation) it is clear that despite this system being vital for bacteria it isn't used widely, or most likely at all, in animals. Research into this would be particularly useful against opportunistic pathogens which tend to have a large selection of two-component systems to allow them to adapt to different lifestyles depending on the conditions of their immediate environment.

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Kristin K. Koretke , Andrei N. Lupas , Patrick V. Warren , Martin Rosenberg , and James R. Brown (2000). Evolution of Two-Component Signal Transduction Mol Biol Evol, 17, 1956-1970

Wolanin PM, Thomason PA, & Stock JB (2002). Histidine protein kinases: key signal transducers outside the animal kingdom. Genome biology, 3 (10) PMID: 12372152

The Impact of Impact!

I went down to London for the weekend to see an exhibition by the Royal College of Art entitled "Impact!" which was a colaboration between designers and research teams to explore the potential impacts and implications of future scientific research. I always like watching when the worlds of art and science collide, and it was a good excuse to get away from my dissertation for a while.

I've done some work with designers before (during my last summer project, I wrote about it here) and I loved it. Designers bring new ways of looking at a project; they have the ability to take science out of the lab and into the real world, while still addressing social and ethical concerns. What I saw at Impact! was the ultimate in science communication and to be honest I think it showed the reasons most people get into science in the first place. It was fun, slightly geeky (five dimensional cameras!) colourful, thought-provoking and all with a wonderful overtone of sci-fi.

The project I enjoyed most (probably because I've met the designer, and saw little sneak-peaks of of it being constructed) was "Cellularity" by James King. This explored the potential of using cell-like structures to deliver pharmaceutical products into a patient, structures that over time, and years of research became so cell-like that they begin to blur the devide between life and non-life, bringing up fundamental questions abut what life even is.

Cellularity from James King on Vimeo.

Start by considering an empty cell filled with drugs and swallowed, like a tablet. Inside the body the membrane dissolves and and drug is released, similar to chemical pills. Clearly the 'cell' (if it can even be called that) is dead. Move on, design a cell which can both produce the drug itself (from a small DNA coil inside it) and replicate itself. Is that alive - or is it merely a biological drug-dispenser?

Next stage...suggested for patients who respond to no current therapy, allow the little drug-making cells to breed within the pateint, replicating in a semi-asexual manner, so that each offspring is producing a different drug. While James indroduces 'death' as a later stage in the line denoting life from non-life I think that for pure health and safety reasons it should probably slot in here. Cells that produce drugs that could potentially harm the patient must be able to die, either by self-destruction or (as James suggests) signalling to the bodys immune system to come and take them away.

If you start giving these cells the power to sense their surroundings as well (maybe to predict the best drug to produce) you get very close to something that can be called life. It's artificial life, life designed exclusively to serve the humans that use it, but life non-the-less. At this stage, it becomes almost meaningless to talk about 'life' and 'non-life' as separate boxes, and instead they become a gradiant, a sliding scale between the living and the dead. This is something that is starting to be appreciated even now when considering things like virus's, or prions. A prion is an infectious protein element, with no DNA or cell wall yet it is capible of replicating and evolving (and consequently sticking two fingers up to Dawkins a bit). If a small piece of twisted protein has a passing claim to 'life' the definition of what life actually is starts to become somewhat hazy. And scientists have made virus's in the lab, creating what could potentially be classified as living organisms from 'dead' pieces of DNA and protein.

One thing that worries me though, how many scientists went to Impact!? I'm sure plenty of designers did, and I'm sure they got a lot out of it, I certainly did. But this is really something I think more scientists should get engaged with. Designers are fun to work with, and they're good at communication especially to a general audience. They make colourful posters, and five-dimentional photography machines, and wierd spiky machines that hang from the ceiling. They bring the excitment back into biology, they remind you why you went there in the first place.

Also I really, really want a five-dimensional camera...

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