Artificial Beginnings: Understanding the Origin of Life by Recreating It

The Origin of Life on Earth was certainly, in retrospect, and from the human vantage point, the most fateful event in the history of the Universe. On a young, tepid Earth chemistry sprung into biology and set course on a four billion year journey that would eventually lead to us. However, all traces of the first, primitive organisms have vanished. They were outcompeted and devoured by their evolutionary descendents, leaving nothing to form fossils. Though we will never be able to set eyes on the first Earthlings, the first pioneers, we can understand what they must have been like through more subtle, indirect approaches. Comparative biochemistry across the whole of life takes us back quite a ways, though not to the first cells. The most recent common ancestor shared by all living organisms—bacteria, plants, animals, fungi, archaea, and unicellular eukaryotes like amoebae—was born long after the first cell ceased to exist. The only way we can truly understand what life must have been like in its earliest days is to create it ourselves.

Californian biotech firm Life Technologies is the first team to register for the $10 million (£6.4m) Archon Genomics X Prize, which will be a race to sequence the genomes of 100 centenarians.

The prize was first announced in 2006, and is a joint effort between the X Prize Foundation and geneticist J Craig Venter. It’s supposed to stimulate the development of less expensive sequencing technologies, and establish a clinical standard for DNA research.

Interested parties have until May 2013 to register. Late that year, in September, each team will have 30 days to sequence the genomes of 100 people, at a cost of $1,000 (£643) or less.

The DNA has been donated by 100 100 year old people from all over the world, to make the competition “scientifically valuable and more meaningful to the general public”. That way, the prize can double up as medical research into the science of healthy aging and longevity.

Life Technologies’ secret weapon is the Ion Proton Sequencer, which it describes as a “semiconductor device that enables chemical signals to be directly translated into digital information for the first time” — a bit like the CMOS imager in an iPhone, which turns photons into electrons.

"It would have cost $100 million and taken 33 years to meet this challenge when the competition was announced in 2006," said Jonathan Rothberg, CEO and founder of Life Technology’s Ion Torrent brand. "The Ion Proton sequencer is designed to sequence a human genome for $1,000 in just a few hours."

Source: Wired

Stanford researchers produce first complete computer model of an organism

A mammoth effort has produced a complete computational model of the bacterium Mycoplasma genitalium, opening the door for biological computer-aided design.

In a breakthrough effort for computational biology, the world’s first complete computer model of an organism has been completed, Stanford researchers reported last week in the journal Cell.

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.

Scientists have developed a statistical method using evolutionary information to significantly enhance the likelihood of identifying disease-associated alleles in the genome that show better consistency across populations.

The group’s research appeared in the advanced online issue of the journal Molecular Biology and Evolution. The new method is now available to use via the web, so that researchers worldwide can apply it as an aid to discovering disease-associated mutations that are more consistently reproducible and therefore useable as diagnostic markers. Kumar refers to this new approach, combining standard comparative genomic studies with phylogenetic data as phylomedicine, a rapidly developing field that promises to streamline genomic information and improve its diagnostic power.

Read more: Evolutionary information improves discovery of mutations associated with diseases