Wednesday, November 21, 2012

http://biotechview.blogspot.in/2012/11/first-ever-computer-model-of-living.htmlIn what can only be described as a milestone in biological and genetic engineering, scientists at Stanford University
have, for the first time ever, simulated a complete bacterium. With the
organism completely in virtual form, the scientists can perform any
kind of modification on its genome and observe extremely quickly what
kind of changes would occur in the organism. This means that in the
future, current lab research that takes extremely long to perform or is
hazardous in nature (dealing with lethal strains of viruses for
instance), could be moved almost exclusively to a computer.The researchers chose a pathogen called Mycoplasma genitaliumas
their target for modeling, out of practical reasons. For one, the
bacterium is implicated in a number of urethral and vaginal infections,
like its name might imply as well, however this is of little importance.
The bacterium distinguishes itself by having the smallest genome of any
free-living organism, with just 525 genes. In comparison, the ever
popular lab pathogen, E. coli has 4288 genes.Don’t be fooled, however. Even though this bacterium has the smallest
amount of genetic data that we know of, it still required a tremendous
amount of research work from behalf of the team. For one, data from more
than 900 scientific papers and 1,900 experiments concerning the
pathogen’s behavior, genetics, molecular interactions and so on, were
incorporated in the software simulation. Then, the 525 genes were
described by 28 algorithms, each governing the behaviour of a software
module modelling a different biological process.

“These modules then communicated with each other after every time step, making for a unified whole that closely matched M. genitalium‘s real-world behaviour,” claims the Stanford team in a statement.

Thus, even for an organism of its size, it takes that much
information to account for every interaction it will undergo in its
lifespan. The simulation work was made using a 128-node computing
cluster, and, even so, a single cell division takes about 10 hours to
simulate, and generates half a gigabyte of data. By adding more
computing power, the computing process can be shortened, however its
pretty clear that for more complex organisms, much more resources might
be required.

“You don’t really understand how something works until
you can reproduce it yourself,” says graduate student and team member
Jayodita Sanghvi.

Emulating for the first time a living organisms is fantastic by
itself, and is sure to set the ground for the development of Bio-CAD
(computer-aided-design). CAD is primarily used in engineering, be
it aeronautic, civil, mechanical, electrical and so on, and along the
years has become indispensable, not only in the design process, but more
importantly in the innovation process. For instance, by replacing the
insulating material for a boiler in CAD, the software will imediately
tell the engineer how this will affect its performance, all without
having to actually build and test it. Similarly, scientists hope to
achieve a similar amount of control from bio-CAD as well. The problem is
that biological organisms need to be fully described into the software
for bio-CAD to become lucrative and accurate.

“If you use a model to guide your experiments, you’re
going to discover things faster. We’ve shown that time and time again,”
said team leader and Stanford professor Markus Covert.

We’d love to see this research expanded forward, which most likely
will happen, but we’re still a long way from modeling a human – about
20,000 genes short.The findings were presented in the journal Cell.

In
a move that promises to bring the advantages of computer aided design
(CAD) to genetic engineers, the first computer model of a complete
bacterium has been produced in the US. It means researchers will soon be
able to modify models of an organism's genome on a computer screen - or
create artificial lifeforms - without the risks of undertaking wet
biology in secure biosafety labs.The pathogen is called Mycoplasma genitalium,
a bacterium implicated in a number of urethral and vaginal infections.
The bug was ripe for modelling say researchers at Stanford University in
California, because it has the smallest genome of any free-living
organism, with just 525 genes. By contrast, the popular lab pathogen E. coli has 4288 genes.The modelling was undertaken by bioengineer Markus Covert and colleagues.
To get the raw data for their model, they undertook an exhaustive
literature review - spanning 900 research papers - to allow them to
program into their model some 1900 experimentally observed behaviours
and molecular interactions that M. genitalium can take part in during its life cycle.
In software terms, they found the behaviours of the 525 genes could
be described by 28 algorithms, each governing the behaviour of a
software module modelling a different biological process. "These modules
then communicated with each other after every time step, making for a
unified whole that closely matched M. genitalium's real-world
behaviour," claims the Stanford team in a statement. Their research appears in the journal Cell (doi: 10.1016/j.cell.2012.05.044).Such
models will ultimately give biologists the freedom to undertake "what
if" scenarios common in regular engineering - changing parameters in a
genome design, say, like a civil engineer adjusts the width of a bridge
deck on a computer to see what happens. As well as being experimentally
useful, allowing artificial organisms and synthetic lifeforms
to be created virtually (harming no-one), they could also boost
biosafety by preventing accidental creations of lethal pathogens. In
2001, for instance, researchers in Australia accidentally created a lethal strain of mousepox.In a commentary article in Cell,
systems biologists Peter Freddolino and Saeed Tavazoie of Columbia
University say they hope the work will soon be extended to more commonly
used lab bugs like E. coli - but also warn that the technique's
accuracy has yet to be demonstrated. It is unclear, they say, "how well
overall behaviors will be predicted from a collection of separately
obtained parameters" gleaned from hundreds of research papers.But
the US National Institutes of Health, which funded the modelling work,
is excited. It believes the model a major step towards finding "new
approaches for the diagnosis and treatment of disease", says James
Anderson, an NIH program director.