Posted on 12/16/2018 11:40:52 AM PST by ETL
As a principal investigator in the NASA Ames Exobiology Branch, Andrew Pohorille is searching for the origin of life on Earth, yet you won't find him out in the field collecting samples or in a laboratory conducting experiments in test tubes. Instead, Pohorille studies the fundamental processes of life facing a computer.
Pohorille's work is at the vanguard of a sea-change in how science can tackle the complex question of where life came from, how its biochemistry operates and what life elsewhere might be like. Rather than relying on the hit-and-miss of laboratory experiments, Pohorille believes that theoretical work is just as important, if not more so, in understanding how life could have emerged from non-life.
"The role of theory is twofold," he says. "It provides explanations and generalizations of what is observed in experiments, but it also has some predictive power."
Pohorille's theoretical work resides within a field known as computational biology; Pohorille himself is director of the Center for Computational Astrobiology and Fundamental Biology at NASA's Ames Research Center in Mountain View, California, and a Principal Investigator with the Exobiology & Evolutionary Biology Program. Computational biology involves designing and writing algorithms within mathematical models that seek to explain life's complex biochemical processes. This is in comparison to 'artificial life,' which creates virtual life-forms that reside in the computer and which can mimic life's processes. However, the approach of computational biology hasn't been an instant hit with all biochemists and evolutionary biologists.
"It's still contentious, partly because there is a group of people who do believe that [searching for] the origins of life is a strictly experimental issue that can only be solved in the lab," says Pohorille. "I respectfully disagree with those who think that way."
This is a view shared by Eric Smith, a researcher in complex non-equilibrium systems at the Earth-Life Science Institute (ELSI) which is attached to the Tokyo Institute of Technology in Japan. Smith highlights how, in recent years, the fields of computational biology and chemistry have matured to the point that researchers used to working in the laboratory can no longer ignore it. "I think we're on the threshold of where it's going to start becoming a serious tool, but it's important to remember that it's only one tool of many."
An example of the usefulness of computational biology can be seen in Smith's work delving into the origins of carbon-fixing, which describes how organisms convert inorganic carbon into the organic compounds vital to life. Smith and his colleague Rogier Braakman of the Chisholm Lab at the Massachusetts Institute of Technology combined a computational approach to phylogenetics (which is the study of the evolutionary relationships between organisms) with metabolic flux balance analysis (which allows metabolisms to be recreated in mathematical simulations on the computer) to disentangle the six different ways in which life is known to fix carbon, in the process figuring out which of the sextet evolved first. Consequently, Smith and Braakman were able to show how this form of carbon-fixing, which was one of life's original metabolic processes, was able to arise from simple geochemistry. As such, it mirrors the overall quest for the origin of life in terms of how biological processes developed from geochemistry.
Although some of these research questions are attainable using computer modeling, we are still lacking an understanding of many of the basic rules governing biochemistry as well as early life's genetics. Some researchers have speculated about an 'RNA world' wherein the self-replicating RNA molecule not only played the role that DNA, which is fashioned from RNA, does today, but that it also arose pre-biotically and was a cornerstone in the origin of life. However, many scientists, including Pohorille and Smith, disagree, claiming that RNA is too big and unwieldy a molecule to have played a role in life's probably simpler origins. Instead, they suspect that there was some other chemistry at work in the origins of self-reproducing life, although what this chemistry could have been remains a subject of vigorous discussion.
Given this uncertainty, Pohorille favors forming generalizations about the biological processes at work in the origin and earliest evolution of life, rather than looking for specific outcomes. Using computational theory, he advocates focusing on the underlying principles of biological processes that are rooted in the laws of physics and chemistry. "What is needed are some general rules that guide us in building scenarios," he says. "Just having individual experiments that say something is possible – because that's as much as we can get from the experiment – is not enough."
Artificial life
One of the biggest questions about the origin of life and its subsequent evolution is how random molecules managed to organize themselves into complex living organisms. What prompted them to form complex molecular chains that became the basis of life, and what are the underlying principles that govern which molecules became the important cogs in the system? With so many permutations of how molecules can combine, on the face it would seem extremely unlikely that nature would just stumble onto the right combination of molecules to form self-replicating life.
At Michigan State University, Chris Adami thinks he has the answer. A professor of microbiology and molecular genetics, Adami takes computational biology to the next level by using the artificial life software called Avida, which runs self-replicating programs that mimic biology and evolution. Through Avida, which he co-developed in 1993 with his Michigan State colleague Charles Ofria and UC Davis' Titus Brown, Adami is able to test his controversial but potentially revolutionary idea that life can be defined as 'information that self-replicates' and that the selection of useful molecular systems for life is governed by the laws of probability.
Avida operates by creating a virtual world in which programs compete for CPU time and memory access, just like organisms competing for resources in the real world. These virtual lifeforms can self-replicate, but crucially they have copy error programmed into them so that, just like in real life, mutations can be carried over to daughter programs to simulate evolution by natural selection. Because they are self-replicating, mutating computer programs could potentially be very dangerous were they to escape Avida and infect the Internet. As a safety precaution, the virtual world is run on a simulated computer inside a real computer so that the programs appear on the outside merely as data.
Where does the first replicator come from? In Avida the first replicator is purposefully written, but in real life the first biological replicator had to emerge spontaneously from nature, and this is where selectivity comes in. "It turns out that replicators, whether in nature or within Avida, are rare," says Adami, "and the odds are that a random program – or assembly of molecules – will not replicate."
The programs are written in a computer language that contains 26 instructions, analogous to individual monomers in chemistry, labelled as the letters of the alphabet from a to z. Adami uses this system to draw an analogy to the written word. Imagine a bag filled with equal numbers of all the letters of the alphabet. A random drawing of the letters into sequences of varying lengths, called 'linear heteropolymers,' creates strings of instructions into which information is encoded. If these polymers were meant to be 'words,' they would mostly be gibberish, containing a jumble of 'q's and 'z's and other letters without connoting meaning. Similarly, the molecules that were available on early Earth had many different ways to bind together to produce a variety of chemical reactions; the chance of nature generating the right molecular structure to enable self-replication is slim.
The Biased Typewriter
Adami points out though that language is loaded to favor certain letters that crop up more often than others. Seldom are 'q's or 'z's used, but 't's and 'e's and 'a's are common letters in words. Adami suggests that the selection problem can be better understood as the 'biased typewriter' model, in which some molecules and chemical reactions are more likely to occur than others. If the letters in the bag were scrabble tiles, with more of the common letters and fewer of the rarely used letters, then even pulling them out at random would lead to some real words being produced, just by chance.
With his student Thomas LaBar, Adami tested the principle of the biased typewriter in Avida, loading the instructions with those monomers that are useful for self-replication. In a billion random programs made from chains of 'letters' that Avida subsequently produced, Adami found that 27 of them could self-replicate. He used those 27 to create a probability distribution and then kept running the program, finding that the number of self-replicators kept increasing dramatically.
"In other words, what this tells you is that if you have a process that generates these monomers at the right frequency, then you're going to be able to find the self-replicators much faster," says Adami.
Just 27 initial self-replicators out of a billion linear heteropolymers doesn't sound like very much, but early Earth was a big place full of opportunity, with all kinds of different environments in which nature could experiment by combining monomers to form useful polymers for life. However, although Adami's theoretical estimates have been born out experimentally by Avida, replicating the process to test the RNA World theory is a different proposition because the amount of information contained within RNA is too great even for the computer to handle. Nevertheless, Adami sees his 'biased typewriter' model as one of the general rules to which Pohorille was referring.
Eric Smith agrees with Adami that the basic idea behind the biased typewriter is on point.
"By biasing the building block inventory, you can drastically change the likelihood of one assembly versus another and we see it in all sorts of places in biology," he says.
When it comes to the importance of information and the relevance of artificial life, Smith has his doubts. "One shouldn't look for a big answer from any one piece of work," he says. Instead, he says, the origin of life isn't just one problem that requires an overarching solution, but an enormous sequence of problems, including the origin of all the metabolic processes as well as self-replication that must each be solved and no one model or computer program can provide the answer. Yet it was once thought that artificial life might have been able to do just that.
"People on both sides—artificial life and origins of life—don't really pursue that much anymore," he says. "There's not much cross-talk between the two."
Andrew Pohorille is also skeptical about Adami's approach, as well as the usefulness of artificial life to origin of life research, suggesting that without some high-level mathematical concept that explains why there is only one set of rules that governs the origin of life and life's processes, whether real or virtual, then the rules of virtual worlds like Avida will not necessarily translate into the real world.
"There may be many rules that lead to these kinds of processes," says Pohorille. "The question is whether any of these rules have anything to do with the rules that operated at the origins of life."
Adami acknowledges that the rules in Avida won't be the same as the geochemical and biochemical rules that operate in real life, but he argues that regardless of the chemistry, the principles of information theory remain.
"It's of course true that we will not find how life evolved on Earth by looking inside a computer," he admits, "But we can test general principles and, once we know these principles, we can go ahead and test those in biochemical systems."
Computational Astrobiology
In the laboratory researchers work with terrestrial life and observe its processes, but on alien worlds life could be very different, operating under different rules that are impossible to test with Earthly life in an experiment. Computational biology and artificial life, however, offer the unique abilities to explore life abstractly by investigating different processes that could exist on other planets with different environments and geochemistry. Could computational biology help astrobiologists describe alien life before we even find it?
NASA scientists certainly think that's feasible, having recently invited Chris Adami to a workshop to discuss biomarkers, where he presented his idea of how to look for life through information and its replication, rather than RNA and proteins. Adami describes this research effort in terms of patterns that are unnatural or in disequilibrium, looking for letters and finding 'e' more common than 'h', as in the Avidian life example. In order to do this the local geochemistry needs to be known fairly well, which is something far beyond out current abilities of exoplanet studies.
Closer to home our knowledge of geochemistry is a little better, or at least can be improved in the near future. Take Europa, for instance. "We're thinking about what evidence for life we should search for there," says Pohorille. The idea is to computationally explore the range of molecules other than proteins or nucleic acids that could perform the same functions as they do on Earth, and figure out what their biosignatures would be on Europa. On a cautionary note, it might be tempting to describe something too extreme using these alternative concepts for life. "It's kind of a dilemma," says Pohorille. "What is enough and what is too much?"
Something might look like life in Avida, but there's a danger of falling into the trap of looking for a pattern that resembles life, but isn't, like confusing the motions of a slinky toy with those of a snake. It's this concern that virtual life in the computer, such as Avidian life, may only be masquerading as representing life that causes so many researchers to be suspicious of its results. "In principle artificial life could help provide alternatives to Earth life, but you've got to figure out what your computer model is an abstraction of, and that's the hard part," says Smith.
Nevertheless, the scientific community as a whole is slowly coming around to the notion that computational biology and chemistry, as well as possibly artificial life, could be vital in progressing the field further. Smith, for example, wonders whether our understanding of the chemistry of complex systems needs to take on a cyborg-like quality by integrating a lot more closely with computational research.
Meanwhile, the field needs a new generation of scientists trained in the use and application of computers for theoretical work, something that is forthcoming now that the computational tools are available and scientists are figuring out new and innovative ways to use them.
"When I started doing these computational simulations, almost nobody could see how it could possibly be related to anything remotely interesting to the origins of life community," admits Pohorille, saying he was tolerated by his peers because he was just "one odd guy." Today, however, he says that younger researchers are realizing that theory and experiments have to go hand-in-hand.
If the field of computational biology is truly going to grow, the funding has to also. Currently, NASA is the only agency in the United States funding origin of life research, with some private money coming from the likes of the Simons Foundation and the Templeton Foundation. "Tell me of a university that is looking for theorists specializing in the origin of life," asks Pohorille rhetorically. "I haven't heard of one." Internationally, ELSI in Japan is one of the few institutions hoping to get closer to the origin of life through computational efforts.
As computing power increases, scientists using it will increasingly be able to solve problems about life's processes. Perhaps computational biology will be just one tool among many available to researchers, but its presence will not only help scientists to think of new ways to explore the origins of life, but also to come up with new ways to think about it too. The mystery of life's origins could one day be solved thanks to that modern antithesis of life – the computer.
Explore further: Quantum artificial life created on the cloud
Source:: Astrobiology Magazine 
“The picture is a reminder of the “primordial soup,””
Yes, everyone knows that and now you’ve said what everyone knows twice.
Exactly.
I have a feeling it looked as much like that as the “primordial soup” looked like the top picture.
They’re both religious iconography art.
Oh, sorry.
I thought this post was by ETL.
ETL was not restating what he’d said, you are.
That convinces me! Case closed!
JF's scenario for the DNA->AI phenotypic revolution, as he sees it, takes place over the next few thousand years; but the technology to begin the process exists now.
The new phenotype does not cause the old phenotype to vanish. Rather, it uses the old phenotype as a tool and the old phenotype continues to do things it does well; while the new phenotype calls the shots on matters of replication and organization. When AI becomes the 4th Revolutionary Phenotype, it does not need to perform the massive tasks (you speak of) performed by earlier phenotypes. They still do their jobs, but under a new boss.
As these phenotypic revolutions occur, life becomes composed of layers, where each layer performs certain kinds of work—organized by the next layer up. Each phenotypic revolution is a revolution in organizational power. Protein is a tool used by RNA; RNA is a tool used by DNA; DNA will be a tool used by AI.
It is a forge for making virtually everything we can touch, and so much more.
How will your assessment of possible AI complexity look in 75 years?
I thought the Internet came from 10000 Al Gores in a room with typewriters.
The simplest known living organism is Mycoplasma hominis H39. It contains about 600 different kinds of proteins, each having an average length of 400 amino acids.
Some years ago, NASA contracted a Yale professor (who had since moved to George Mason) named Dr. Harold J Morowitz to try and derive the theoretical limit of the simplest living thing. The result of that study required 239 of 124 different kinds of proteins, each with an average length of 445 amino acids.
There are 20 different types of amino acids in living organisms (all with so-called left handed symmetry.) Chemically produced amino acids would feature the same number of left and right handed amino acids, so there would be 40 types of naturally produced amino acids.
To arrange these 40 types of amino acids into just one specific protein of 445 amino acids in the proper order has a probability of 40^445 = 8x10^712 against. To randomly produce 239 necessary proteins, each with an average length of 445 has a probability of about 10^(170,000) against.
Pretty big odds. But the universe is big, you say? Well, let’s see... We estimate there to be about 10^80 atoms in the universe. If every atom in the universe was an amino acid instead of an atom, and if this universe of amino acids could combine random chains, 445 amino acids in length, a thousand times per second and it has been trying these combinations since the beginning of time (13.7 billion years ago) it could have tried about 10^98 combinations, so far.
The universe is about 10^600 times too small to have produced even one of the necessary proteins. More than 10^(100,000) against to produce the whole set.
This simply cannot happen by random processes. One can argue that the impossible can happen once. That would be just one protein. But to have over 200 distinctly different but specified impossibilities occur all at the time and same place. No way.
Life, once you’ve got it, you can’t get rid of it. But the initial origin or life from inert matter? That requires something beyond our present understanding of the laws of physics.
No primordial soup for you!
You’ll have to ask the designer.
Well done. New respect for math majors!
Emprizice this “science”...grab a can of chicken noodle soup....sterilize it....without destroying most of the life associated molecules..sit in warm bath bathed in sterile environment. ...sunlight...cosmic rays and like natural phenomena...sample every 5 years for simple life forms...if no positive results for 25 years...consider that abiogenesis should never be assumed to be true....no matter what computer say...i.e..if all the raw materials preformed cant organize into living creatures...the theory would have a HUGE argument against it. I think these theorists know the odds...but dont want to accept the philosophical consequences of the obvious. Please note...raw chemicals ARE assembled into living organisms trillions of times a day by gestating organism instructions in reproductive structures.
Another thing worth noting: There are high-tech bio-engineering companies that produce synthesized nucleotides. However, all of their nucleotides are derived from biologically produced nucleotides. This is because no one has been able to synthesize a nucleotide molecule from its basic chemical components.
So something that still cannot be done in even the highest technology labs is expected to just fall together by random process.
One of the biggest questions about the origin of life and its subsequent evolution is how random molecules managed to organize themselves into complex living organisms.
Nothing random about it, but if that's the premise, no one ever need worry about discovering the right answer.
It's all kind of funny about these self-replication studies with letters, though, because "In the beginning..."
...בראשית ברא
In the beginning created God the heavens and the earth.
"In the beginning, [the letters] bet resh alef..." repeat themselves.
The sum of bet, resh, and alef is 203, the 7th Bell number. Bell numbers are all about partitions, groupings, and organization, and are named after Eric Temple Bell, whose last name is spelled bet lamed, which are the first and last letters of the Torah (and also the whole Tanakh). Therefore everything in the Hebrew Bible is contained within these two letters that spell Bell, or lev, heart.
The Amalekite system of probabilities and randomness fails spectacularly because nothing is random. 1 and 2, well known from the Purim commentaries...
502:
1. "Cursed be Haman" (ארור המן)
2. "Blessed be Mordecai". (ברוך מרדכי)
3. "Eric Temple Bell" (אריק טמפל בל)
The Great Pyramid is missing its capstone. That's not random, because it's absurd to conclude that those with the skill and knowledge to build it with such fine precision in the first place would mess up on the last block. So there it stands, with its 203 courses of masonry.
Back to basics. Case in point:
Eze 37
16. And you, son of man, take one stick [etz], and write upon it, For Judah, and for the people of Israel his companions; then take another stick [etz], and write upon it, For Joseph, the stick [etz] of Ephraim, and for all the house of Israel his companions:
17. And join them one to the other into one stick [l'etz echad, 203]; and they shall become one in your hand:
etz: tree, wood, stick
The two Hebrew letters that are shaped like sticks (i.e. tree branches) are the ayin and tzaddi sofit. Put them together and they spell the word etz, tree. Nothing weird or mystical magicky there. Two sticks, one tree:
עץ
Child's play, but people overthink this stuff. ;)
The random letter researcher is named Chris Adami. What's in a name (names)? He really should look those up.
Everything is ordered:
In number theory and enumerative combinatorics, the ordered Bell numbers or Fubini numbers count the number of weak orderings on a set of n elements (orderings of the elements into a sequence allowing ties, such as might arise as the outcome of a horse race).[1] Starting from n = 0, these numbers are 1, 1, 3, 13, 75, 541...
All Israel in the beginning...
An ordered tree (or plane tree) is a rooted tree in which an ordering is specified for the children of each vertex.[16] This is called a "plane tree" because an ordering of the children is equivalent to an embedding of the tree in the plane, with the root at the top and the children of each vertex lower than that vertex. Given an embedding of a rooted tree in the plane, if one fixes a direction of children, say left to right, then an embedding gives an ordering of the children. Conversely, given an ordered tree, and conventionally drawing the root at the top, then the child vertices in an ordered tree can be drawn left-to-right, yielding an essentially unique planar embedding.
https://en.wikipedia.org/wiki/Tree_(graph_theory)#Ordered_tree
Who can keep track?! God's a funny guy..
In 7 decades... yeah, we will probably have quantum computers that will be able to replicate the complexity of protein folding in real time (not quite as fast as the actual chemical reactions. The current quantum computers can barely even completely model a hydrogen atom. Couple that with advanced techniques in AI (current techniques are NOT intelligent, they're just a bunch of statistics - and yes that includes neural networks) and there might be something navigating around like C3PO or R2D2.
Life was spoken into existence.
Given the state of the world, I certainly hope so!
DEC's president couldn't foresee anyone ever wanting a home computer in 1977...
The speaker wasn't alive?
Did you just say God is dead?
Disclaimer: Opinions posted on Free Republic are those of the individual posters and do not necessarily represent the opinion of Free Republic or its management. All materials posted herein are protected by copyright law and the exemption for fair use of copyrighted works.