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Monday 30 July 2012

Scientists Create First Computerized Model Of Organism’s Entire Lifecycle



For the first time, researchers at Stanford University in California have used computer software to simulate the entire lifecycle of an organism — all 525 genes of the bacterium Mycoplasma genitalium.
The breakthrough, which is described in a paper published in the journal Cell on July 20, could lead to enormous advances in the fields of genetics, personalized medicine, pharmaceuticals and biology in general, allowing scientists to perform experiments that wouldn’t be possible on actual living organisms. Researchers used 128 computers to model an organism that is actually a sexually transmitted parasite.
“I’m a big believer in ‘model-driven discovery’ which simply means that if you have a model of a biological process, you will make discoveries more quickly and efficiently than you would without a model,” said Markus Covert, an assistant professor of bioengineering at Stanford, who led the study, in an email to TPM.
Specifically, Covert explained Stanford’s software simulation of the Mycoplasma genitalium lifecycle is distinct from previous efforts to model organisms using computers because of the vast volume of the data it encompasses — literally every single molecular process that takes place in the single-celled bacterium’s life.
Covert’s team has already begun experimenting with removing certain genes to see what happens in the simulation.
“Each simulation is one cell, one life cycle,” Covert said. “We’ve now run thousands of these, both for the normally growing cell as well as all of the single-gene knockout strains.”
The simulation takes about nine to 10 hours in order for one cell to divide, again emulating its real counterpart, as The New York Times reported about the study. The simulation stops when the organism “dies.”
“‘Death’ of the simulation is defined as an inability to divide, degradation of key components, etc,” Covert explained.
The Standford simulation of the parasite has already led to one important discovery: The finding that the longer it takes for a single cell to begin replicating its DNA in preparation for division, the shorter time it will actually take to replicate, which balances out to the same average time across all cells modeled.
Among the many new advances that the computer simulation could lead to is the possibility “for the wholesale creation of new microorganisms,” according to a Stanford news release on the work.
Still, it was a long road to get from the initial idea to simulate the bacterium’s life cycle on a computer to actually doing it, as covert explained.
“I first thought about getting involved in whole-cell modeling about thirteen years ago, when I read a quote by a scientist in the paper who said (paraphrasing) that the ultimate challenge in biology would be to create a computer model of a cell, because it would imply a fundamental understanding of how cells work,” Covert wrote. “I basically became obsessed with that quote, and still think about it every day!”
It took nearly four years to actually write the software to perform the simulation itself, and the use of over 900 prior scientific papers on Mycoplasma genitalium and other bacterium to create the perfect algorithm to simulate the organism. The research was funded in part by the National Institutes of Health.

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Saturday 28 July 2012

DST JUNIOR RESEARCH FELLOW Vacancy in SCTIMST, Thiruvananthapuram


Qualification & Experience: 1st Class M Sc in Biochemistry and NET. Six months
                                               research   experience is desirable.

Monthly emoluments : ` 12,000/- + 20 % HRA (Consolidated) for 1st and 2nd year and ` 14,000/-
                                     +  20 % HR (Consolidated) during 3rd year.

Maximum age as on 31-7-2012 : 35 years.

No. of vacancies : One

Duration : Three years or till Completion of project, whichever is earlier.

Date & Time of interview : 01-8-2012 at 10:30 AM

Time of reporting : 09:00 AM

Mode of selection : Walk-in-interview

Venue : Biomedical Technology Wing, Satelmond Palace,
              Poojapura, Thiruvananthapuram – 695 012
               (Phone No: 2340801)

for more information visit:  http://www.sctimst.ac.in/Recruitment/resources/RESEARCH%20ASSOCIATE%20%20-%20%28TEMP%29.pdf
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Friday 27 July 2012

Research Assistant & Project Assistant Jobs in IIT Kharagpur, Kharagpur


Project Title INNOVATIVE USE OF UNDULATING DROUGHT PRONE FRAGILE LATERITIC WASTELANDS IN THE REMOTE TRIBAL BELT RECOURSE TO LARGER SCALE PRODUCTION OF A KHARIF MINOR OIL SEED CROP LIKE NIGER (GIUZOTIA ABYSSINICA L.F (CASS) ( IUU )
Reference Number IIT/SRIC/R/IUU/2012/140 DATED 19th March, 2012
Temporary Position(s) Walk-in-interview on 6/8/2012 at 4-00 PM in Rural Dev. Centre for the post of a) Research Assistant and b) Project Assistant
Number of vacancies a) 1
b) 1
Consolidated Compensation a) Rs. 10,000/- to Rs. 12,500/- per month (depending upon qualification & experience)
b) Rs. 8,000/- per month
Coordinator / PI Dr. S. C. Mahapatra, , Rural Development Centre
Qualifications & Experience a) Master in Agricultural Science, Biotechnology, Economics, Social Science, Anthropology; with a valid GATE / NET score; Ability to work in rural areas and making communication with rural people.
b) 1st Class Master Degree in Economics, Agricultural Science, Biotechnology with a good communication skill and working with rural people.
Relevant Experience Candidate should send prior intimation with their CV to the email ID scmaha@hijli.iitkgp.ernet.in by 5.8.2012 with a subject heading “Walk in interview for RA/PA ” 
Last Date 06 Aug 2012
Application Fee Rs. 50 (not for female candidates) /-
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Saturday 21 July 2012

Viruses' Copying Mechanism Demystified, Opening the Door to New Vaccine Strategies

Certain kinds of viruses such as those that cause the common cold, SARS, hepatitis, and encephalitis, copy themselves using a unique mechanism, according to a team of Penn State scientists that includes David Boehr, an assistant professor of chemistry and a co-leader of the research team. The discovery sheds light on a previously identified, but never-before-understood region of an enzyme associated with the process of replicating genetic material. The research is an important step toward the improvement of existing vaccines, as well as toward the design of vaccines against viruses that have eluded vaccination strategies in the past.

The research will be published in the print issue of the journal Structure on Sept. 5.
All organisms use enzymes called polymerases to "read" and copy their genetic material. While the genetic material of viruses that cause diseases such as SARS, influenza, and polio is composed of single-stranded RNA, the genetic material of many other viruses, such as those that cause herpes and conjunctivitis, is composed of double-stranded DNA. Regardless of whether the genetic material is DNA or RNA, viruses hijack a host cell's machinery, forcing it to replicate the virus's own genetic material and, ultimately, to make copies of the virus that will spread to and infect other cells.
The polymerases of many organisms, including DNA viruses, are known to have a "cupped right hand" structure -- a configuration of atoms that can be described as resembling a palm, fingers and thumb.
"We've known for some time that, in organisms that use DNA as their genetic material, within the 'palm' of the hand is specific helical structure where much of the enzyme action takes place. This 'fidelity' helix is where nucleotides -- molecules that join to form RNA and DNA -- are recognized and copied," Boehr said. "However, the polymerases of RNA viruses do not have this helix structure. Instead, the 'cupped hand' holds a different structure -- a loop known as motif D. Until now, the function of motif D was a mystery."
To unravel the mystery of motif D's function, Boehr and his colleagues studied a strain of the poliovirus -- an RNA virus that is similar to many other RNA viruses that affect humans. Using a technique called nuclear magnetic resonance spectroscopy, a process that probes the physical and chemical properties of atoms to determine the structure of organic compounds, they found that motif D is the functional equivalent of the helix structure found in the polymerases of other viruses. "Previously, it was assumed that motif D had no function at all or that it provided some sort of scaffolding to support the cupped palm structure," Boehr said. "But we have found that it is responsible for identifying nucleotides and making sure that a new strand of RNA is replicated faithfully, with as few mistakes as possible."
Boehr explained that what he and his team discovered about motif D's function in the polio strain is applicable to many other RNA viruses such as the common cold. In addition, motif D may function similarly in retroviruses -- viruses such as HIV that are replicated using an enzyme called reverse transcriptase to produce DNA from RNA genomes. "Additional studies will be necessary to confirm that motif D's role is of equal importance in retroviruses," Boehr said.
Boehr and his collaborators hope that motif D might provide a new direction for vaccine research. "Now that motif D has been identified as part of the mechanism by which genetic material is replicated accurately, it might be possible to use that information to create safer and more-efficient vaccines," Boehr said.
He explained that a vaccine, which is a weakened or harmless version of a virus, works by giving the vaccinated person's immune system a "picture" of the enemy. Once the immune system knows what the virus looks like, it can recognize and defend against the pathogen when it comes into contact with the wild, harmful version.
But one concern of this strategy is the possibility that a weakened, vaccine version of a virus might evolve once it has been introduced into a population, eventually reverting back to a wild type and becoming harmful again.
"Ideally, every copy a vaccine virus makes of itself inside human cells will be the original, lab-created, harmless version," Boehr said. "So by fine-tuning motif D; that is, by making this fidelity mechanism even more faithful, it might be possible to reduce the chances that the vaccine version of the virus will mutate and evolve on its own."
Boehr added that the research also might provide a new strategy to design vaccines for some of the RNA viruses for which vaccines have not yet been developed.
In addition to Boehr, other scientists who contributed to the research include Xiaorong Yang, David Lum, and Jesse L. Welch from Penn State's Department of Chemistry; and Eric D. Smidansky, Kenneth R. Maksimchuk, Jamie J. Arnold, and Craig E. Cameron from Penn State's Department of Biochemistry and Molecular Biology.
The research is supported, in part, by the National Institutes of Health.

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Researchers Produce First Complete Computer Model of an Organism

A team led by Markus Covert, assistant professor of bioengineering, used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium, the world's smallest free-living bacterium.
By encompassing the entirety of an organism in silico, the paper fulfills a longstanding goal for the field. Not only does the model allow researchers to address questions that aren't practical to examine otherwise, it represents a stepping-stone toward the use of computer-aided design in bioengineering and medicine.
"This achievement demonstrates a transforming approach to answering questions about fundamental biological processes," said James M. Anderson, director of the National Institutes of Health Division of Program Coordination, Planning and Strategic Initiatives. "Comprehensive computer models of entire cells have the potential to advance our understanding of cellular function and, ultimately, to inform new approaches for the diagnosis and treatment of disease."
The research was partially funded by an NIH Director's Pioneer Award from the National Institutes of Health Common Fund.
From information to understanding
Biology over the past two decades has been marked by the rise of high-throughput studies producing enormous troves of cellular information. A lack of experimental data is no longer the primary limiting factor for researchers. Instead, it's how to make sense of what they already know.
Most biological experiments, however, still take a reductionist approach to this vast array of data: knocking out a single gene and seeing what happens.
"Many of the issues we're interested in aren't single-gene problems," said Covert. "They're the complex result of hundreds or thousands of genes interacting."
This situation has resulted in a yawning gap between information and understanding that can only be addressed by "bringing all of that data into one place and seeing how it fits together," according to Stanford bioengineering graduate student and co-first author Jayodita Sanghvi.
Integrative computational models clarify data sets whose sheer size would otherwise place them outside human ken.
"You don't really understand how something works until you can reproduce it yourself," Sanghvi said.
Small is beautiful
Mycoplasma genitalium is a humble parasitic bacterium known mainly for showing up uninvited in human urogenital and respiratory tracts. But the pathogen also has the distinction of containing the smallest genome of any free-living organism -- only 525 genes, as opposed to the 4,288 of E. coli, a more traditional laboratory bacterium.
Despite the difficulty of working with this sexually transmitted parasite, the minimalism of its genome has made it the focus of several recent bioengineering efforts. Notably, these include the J. Craig Venter Institute's 2008 synthesis of the first artificial chromosome.
"The goal hasn't only been to understand M. genitalium better," said co-first author and Stanford biophysics graduate student Jonathan Karr. "It's to understand biology generally."
Even at this small scale, the quantity of data that the Stanford researchers incorporated into the virtual cell's code was enormous. The final model made use of more than 1,900 experimentally determined parameters.
To integrate these disparate data points into a unified machine, the researchers modeled individual biological processes as 28 separate "modules," each governed by its own algorithm. These modules then communicated to each other after every time step, making for a unified whole that closely matched M. genitalium's real-world behavior.
Probing the silicon cell
The purely computational cell opens up procedures that would be difficult to perform in an actual organism, as well as opportunities to reexamine experimental data.
In the paper, the model is used to demonstrate a number of these approaches, including detailed investigations of DNA-binding protein dynamics and the identification of new gene functions.
The program also allowed the researchers to address aspects of cell behavior that emerge from vast numbers of interacting factors.
The researchers had noticed, for instance, that the length of individual stages in the cell cycle varied from cell to cell, while the length of the overall cycle was much more consistent. Consulting the model, the researchers hypothesized that the overall cell cycle's lack of variation was the result of a built-in negative feedback mechanism.
Cells that took longer to begin DNA replication had time to amass a large pool of free nucleotides. The actual replication step, which uses these nucleotides to form new DNA strands, then passed relatively quickly. Cells that went through the initial step quicker, on the other hand, had no nucleotide surplus. Replication ended up slowing to the rate of nucleotide production.
These kinds of findings remain hypotheses until they're confirmed by real-world experiments, but they promise to accelerate the process of scientific inquiry.
"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 Covert.
Bio-CAD
Much of the model's future promise lies in more applied fields.
CAD -- computer-aided design -- has revolutionized fields from aeronautics to civil engineering by drastically reducing the trial-and-error involved in design. But our incomplete understanding of even the simplest biological systems has meant that CAD hasn't yet found a place in bioengineering.
Computational models like that of M. genitalium could bring rational design to biology -- allowing not only for computer-guided experimental regimes, but also for the wholesale creation of new microorganisms.
Once similar models have been devised for more experimentally tractable organisms, Karr envisions bacteria or yeast specifically designed to mass-produce pharmaceuticals.
Bio-CAD could also lead to enticing medical advances -- especially in the field of personalized medicine. But these applications are a long way off, the researchers said.
"This is potentially the new Human Genome Project," Karr said. "It's going to take a really large community effort to get close to a human model."
Stanford's Department of Bioengineering is jointly operated by the School of Engineering and the School of Medicine.
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