Is it time to hit the reset button re:origin of life science?

Origin-of-Life Research: Start Over

Evolution News & Views 

Hardly a month goes by without a celebration in the news that the "building blocks of life" have been found somewhere in space, or that chemical reactions "show how life emerged" on the primitive earth. Recently, the University of Bern triumphantly announced that "Rosetta's comet contains ingredients for life." All that was detected was glycine (the simplest and the only achiral amino acid) and the element phosphorus (which is tantamount to calling any other element, like hydrogen or oxygen, an "ingredient for life"). New Scientist chimed in: "Building blocks of life spotted around comet for the first time." Meanwhile, PhysOrg suggested there might be life on the asteroid Ceres. Why? Because water ice probably exists under the surface.

The mainstream media typically report such findings uncritically. It's refreshing, then, to see a chemist and a space scientist take a hard look at the failings in origin-of-life research. In America's leading journal, Science, they ignore the hype about water and simple chemicals implying life. They "get real" about the limits of chemistry. And they seriously look for radically different ways to approach the problem -- some of which will be of interest to design theorists.

One of the authors is Leroy Cronin, a chemist at the University of Glasgow (where, incidentally, Darwin critic William Thomson -- Lord Kelvin -- had his long and distinguished career). The other is Sara Imari Walker from Arizona State where space science is big and aggressive atheist cosmologist Lawrence Krauss is a campus celebrity; she's also a member of the Blue Marble Space Institute for Science here in Seattle.

They have no patience with the usual celebratory fluff. They want a revolution:

How can matter transition from the nonliving to the living state? The answer is essential for understanding the origin of life on Earth and for identifying promising targets in the search for life on other planets. Most studies have focused on the likely chemistry of RNA, protein, lipid, or metabolic "worlds" and autocatalytic sets, including attempts to make life in the lab. Butthese efforts may be too narrowly focused on the biochemistry of life as we know it today. A radical rethink is necessary, one that explores not just plausible chemical scenarios but also new physical processes and driving forces. Such investigations could lead to a physical understanding not only of the origin of life but also of life itself, as well as to new tools for designing artificial biology. [Emphasis added]

In one fell swoop, Cronin and Walker have cast doubt on essentially the whole history of origin-of-life research. Whether from Oparin, Miller, Orgel, Benner, Hud, Russell, Cairns-Smith, Wachtershauser, Shapiro, or maybe even "warm little pond" Darwin himself -- it's all inadequate and probably misguided. Otherwise, why would a "radical rethink" be necessary?

Here's what most of the previous work has been "narrowly focused" on: chemical reactions. From Stanley Miller's 1953 lightning flask to the present, almost all the work has assumed that if you can get some molecules that life uses, you're making progress to understanding life's emergence. One can speculate about a "scenario" where these chemicals would fit into a grand story of life's emergence.

Such thinking is flawed for a number of reasons, some of which we can glean from the paper and summarize here:

• Dilution and entropy: "Left unattended, sophisticated chemistry becomes more dilute and disordered."
• Oversimplification: "A quick route to complexity and enrichment that could lead to the development of evolvable units seems to be required to avoid this serious issue."
• Ends without means: "Yet, most research efforts have focused on detailing precise chemical mechanisms for producing high yields of individual bio-inspired products, without addressing the processes necessary to form increasingly complex molecules and networks."
• Improbability: "The molecular constituents of simple networks are more likely to arise by chance than the highly evolved molecules of extant life."
• Begging the question: "how did evolution begin if the complex machinery for evolution was not in place?"

Indeed, their last paragraph shows they are ready to sweep the field clean and start over:

Progress will be made by challenging all historical prerequisites assumed to be important in the origin of life.We should aim to develop measurable and collaborative routes to explore the physics and chemistry of life's origins and the living state. Not only is a comprehensive understanding of what it means for a physical system to be alive required but also a new multidisciplinary, multinational project to generate new life in the lab or in silico, to search for life on Earth that uses an alternative chemistry to that found in biology, and to explore the potential for life on other worlds. For this to be possible, researchers must challenge the current models and historical approach and be willing to work together across disciplinary boundaries to see if a process-based model can be used to understand and control the transition from inorganic matter to biology.

Having dismissed the obsession with "plausible chemical scenarios," what do Cronin and Walker advise for their radical rethink? What should origin-of-life research focus on instead? Here it is -- (drumroll) -- information. We'll understand life, they say, when we look at how information flows in networks.

What happens to our traditional perspectives if we do not restrict attention to the chemical substratesof known life? The development ofnetworks over time may be more important than the specific chemical nature of their molecular components....

A concept of information relevant to biological organization may be essential to identifying these networked processes. Adami and LaBar have described life at a basic level as "information that copies itself". Given that life not only copies information but also uses information to construct itself, we might instead describe the start of life as "simple machines that can construct slightly more complicated machines." Focusing on information in this way moves the narrative even further from a chemistry-specific mode than focusing on networks a lone butterfly may perhaps provide our best shot at uncovering universal laws of life that work not just for biological systems with known chemistry but also for putative artificial and alien life. For example, Walker et al. have recently shown that information-theoretic measures distinguish biological networks from random ones, even in cases where the biological networks share important network properties (such as topological features) with random networks. Life requires chemistry, but the properties of the living state emerge from the dynamical properties of that chemistry, including the temporal and spatial organization of molecular networks and their information management.

Well, Chris Adami of Avida fame has tossed out one point of agreement on which to advance the discussion: information must be central to discussions of life. But doesn't information presuppose sentient agents, or systems designed by sentient agents? Otherwise, how do they recognize and respond to information? How can they perform "information management"? A falling rock that triggers an avalanche can hardly be thought of as managing information in a network. In our uniform experience, machines and networks that share information have been intelligently designed (read Dembski's bookBeing as Communion for a detailed exposition of the concept of information).

So close, yet so far away. Cronin and Walker immediately return to a chemistry focus of their own, trying to compare the emergence of life to a "phase transition," using one of the origin-of-life field's favorite magic words, emergence, a dozen times.

One appreciates their call to scientific rigor: "speculation should be restricted to the development of experimentally testable hypotheses that address key questions and provide a focus for progress." And one appreciates their insertion of the design-rich terms machinery, information, and networks in the discussion. Unfortunately, their own "radical rethink" relies on the same materialistic assumptions that have stifled and baffled researchers since Darwin.

More just so stories to explain away human exceptionalism.

From The Economist story:Of bairns and brains
Babies are born helpless, which might explain why humans are so clever

HUMAN intelligence is a biological mystery. Evolution is usually a stingy process, giving animals just what they need to thrive in their niche and no more. But humans stand out. Not only are they much cleverer than their closest living relatives, the chimpanzees, they are also much cleverer than seems strictly necessary. The ability to do geometry, or to prove Pythagoras’s theorem, has turned out to be rather handy over the past few thousand years. But it is hard to imagine that a brain capable of such feats was required to survive on the prehistoric plains of east Africa, especially given the steep price at which it was bought. Humans’ outsized, power-hungry brains suck up around a quarter of their body’s oxygen supplies.

Sexy brains

There are many theories to explain this mystery. Perhaps intelligence is a result of sexual selection. Like a peacock’s tail, in other words, it is an ornament that, by virtue of being expensive to own, proves its bearers’ fitness. It was simply humanity’s good fortune that those big sexy brains turned out to be useful for lots of other things, from thinking up agriculture to building internal-combustion engines. Another idea is that human cleverness arose out of the mental demands of living in groups whose members are sometimes allies and sometimes rivals.

Now, though, researchers from Rochester University, in New York, have come up with another idea. In Proceedings of the National Academies of Science, Steven Piantadosi and Celeste Kidd suggest that humans may have become so clever thanks to another evolutionarily odd characteristic: namely that their babies are so helpless.

Compared with other animals, says Dr Kidd, some of whose young can stand up and move around within minutes of being born, human infants take a year to learn even to walk, and need constant supervision for many years afterwards. That helplessness is thought to be one consequence of intelligence—or, at least, of brain size. In order to keep their heads small enough to make live birth possible, human children must be born at an earlier stage of development than other animals. But Dr Piantadosi and Dr Kidd, both of whom study child development, wondered if it might be a cause as well as a consequence of intelligence as well.

Their idea is that helpless babies require intelligent parents to look after them. But to get big-brained parents you must start with big-headed—and therefore helpless—babies. The result is a feedback loop, in which the pressure for clever parents requires ever-more incompetent infants, requiring ever-brighter parents to ensure they survive childhood.

It is an elegant idea. The self-reinforcing nature of the process would explain why intelligence is so strikingly overdeveloped in humans compared even with chimpanzees. It also offers an answer to another evolutionary puzzle, namely why high intelligence developed first in primates, a newish branch of the mammals, a group that is itself relatively young. Animals that lay eggs rather than experiencing pregnancy do not face the trade-off between head size at birth and infant competence that drives the entire process.

To test their theory, Dr Piantadosi and Dr Kidd turned first to a computer model of evolution. This confirmed that the idea worked, at least in principle. They then went looking for evidence to support the theory in the real world. To do that they gathered data from 23 different species of primate, from chimps and gorillas to the Madagascan mouse lemur, a diminutive primate less than 30cm long.

The scientists compared the age at which an animal weaned its young (a convenient proxy for how competent those young were) with their scores on a standardised test of primate intelligence. Sure enough, they found a strong correlation: across all the animals tested, weaning age predicted about 78% of the eventual score in intelligence. That correlation held even after controlling for a slew of other factors, including the average body weight of babies compared with adults or brain size as a percentage of total body mass.

The researchers point to other snippets of data that seem to support their conclusions: a study of Serbian women published in 2008, for instance, found that babies born to mothers with higher IQs had a better chance of surviving than those born to low-IQ women, which bolsters the idea that looking after human babies is indeed cognitively taxing. But although their theory is intriguing, Dr Piantadosi and Dr Kidd admit that none of this adds up to definitive proof.

That, unfortunately, can be the fate of many who study human evolution. Any such feedback loop would be a slow process (at least as reckoned by the humans themselves), most of which would have taken place in the distant past. There are gaps in the theory, too. Even if such a process could drastically boost intelligence, something would need to get it going in the first place. It may be that some other factor—perhaps sexual selection, or the demands of a complex environment, or some mixture of the two—was required to jump-start the process. Dr Piantadosi and Dr Kidd’s idea seems a plausible addition to the list of explanations. But unless human intelligence turns out to be up to the task of building a time machine, it is unlikely that anyone will ever know for sure. 

Re:Darwinism How many trials,How many errors.

What is the maximum number of trials evolution could have performed?
 Kirk Durston

There are countless people who use the following rationale to justify why there was no need for an intelligent creator behind life – evolution has had a near-infinite number of trials in which to create the full diversity of life, including its molecular machines, molecular computers, and digitally encoded genomes. Here, we will take an opportunity to examine these points more closely.

In other scientific disciplines, the first step one must take before figuring out a solution, is to establish the boundary conditions within which a problem must be solved. Since we should require the same standard of scientific rigour from evolutionary biology, let us calculate an extreme upper limit for the total number of evolutionary trials one could expect over the history of life.

An estimate for the total number of bacteria on earth is 3.17 x 10^30.(1,2) In comparison, all other life occurs in relatively insignificant numbers, too many orders of magnitude smaller to matter. Nonetheless, to be generous, let us add .03 x 10^30 other life forms in order to get 3.2 x 10^30 life forms on the planet (starting from the moment the earth cooled enough to permit this).

The larger the genome, the more opportunities there are for mutations to occur. Let us assume a generous average genome size of 100,000 possible protein coding genes. When I say ‘possible’, I include ‘junk’ DNA as fertile ground for new genes.

Since a mutation can change the sequence of a gene, is it possible for evolution to try different gene sequences in sequence space in order to ‘discover’ a novel, functional protein family?

Let us assume there is a fast mutation rate of 10^-3 mutations per possible gene per replication. Given 10^5 possible genes per organism, each lineage should be able to ‘try out’ 100 new possible gene sequences per generation. To make our evolutionary search more efficient, we will also assume that no sequence was ever tried twice over the entire history of life.

Finally, let us use a fast replication rate (for nature) of once every 30 minutes over a 4 billion year period, for a total of 7 x 10^13 generations. These very generous parameters allow us to calculate an upper limit for the total number of evolutionary trials over four billion years.

Total number of possible genes sampled per single lineage over 4 billion years = 7 x 10^15

Extreme upper limit for the total number of possible gene families sampled for all of life over 4 billion years = 2.2 x 10^45 trials.

I have been extremely generous – by two orders of magnitude in comparison to a peer reviewed estimate for ‘an extreme upper limit’ of 4 x 10^43 trials (3). Since Dryden estimates 10^43 as his ‘extreme upper limit’, and it is peer reviewed, we will use his estimate instead of mine.

Stable, functional 3D protein structures are determined by physics, not biology, therefore, we can regard each protein family as a target in sequence space that evolution must find. With 10^43 trials, one would think there would be no problem. Unfortunately, there are virtually no sequences that will produce stable, functional 3D structures. For example, RS7 is a universal protein required for all life forms, yet only 1 in 10^100 sequences will produce a functional RS7 protein domain.

Obviously, in order for evolution to find any RS7 sequences, 10^43 trials is woefully inadequate – by 57 orders of magnitude. As I have shown elsewhere, RS7 requires 332 bits to encode, well within the range of what an intelligent mind can produce. Therefore, what options should we examine?

1) novel protein family sequences were discovered through random genetic drift.

2) novel protein families were discovered via an evolutionary search guided by natural selection.

3) novel protein family sequences were encoded by an intelligent mind.

As I have already established, 3) can be scientifically tested and verified, so it definitely serves as a viable explanation. We shall look at 1) and 2) more carefully in future posts.

References:

K. Lougheed, ‘There are fewer microbes out there than you think’, Nature, (2012).
J. Kallmeyer et al., ‘Global distribution of microbial abundance and biomass in subseafloor sediment’, Proc. Natl. Acad. Sci. USA., (2012) 109 No. 40.

D.T.F. Dryden et al., ‘How much of protein sequence space has been explored by life on Earth?’, Journal of the Royal Society Interface, (2008) 5, 953-956.

Darwinism against the house.

Probability Mistakes Darwinists Make

Kirk Durston 

 Several years ago I delivered a lecture at the University of Maine, showing how advances in science increasingly point to an intelligent mind behind biological life. During the question period a professor in the audience conceded that the probability of evolution "discovering" an average globular protein is vanishingly small. Nonetheless, he insisted we are surrounded by endless examples of highly improbable events. For example, the exact combination of names and birthdates of the hundred or so people in the audience was also amazingly improbable. In the ensuing conversation, it became obvious that there was something about probabilities that he had not considered.

It only takes a few minutes of searching YouTube to confirm that numerous Darwinists commit the same mistake. In one example, a fellow randomly fills in a grid of 10 columns and 10 rows with 100 symbols. Then, he states that the probability of getting that exact combination is 1 chance in 10^157 -- yet he just accomplished this astonishing feat. In another clip, a man shuffles a deck of cards, spreads them out on a table, then repeats this two more times. He states that the probability of getting that exact triple combination of cards is roughly 1 chance in 10^204 -- yet he just did it. Both scenarios are supposed to prove there is nothing special about the probability of evolution "discovering" the sequence for a novel protein family with stable, 3D structures. Ironically, these examples demonstrate a profound ignorance of the problem.
In clearing up misconceptions that Darwinists promote, the first step is to clarify what scientists speak of when they discuss the infinitesimal probability of evolution "discovering" a sequence for a novel protein. That probability is found embedded within an equation published by Hazen et al.¹:
I(Ex) = -log2 [M(Ex)/N]where
I(Ex) = the information required to code for a functional sequence within protein family, andM(Ex) = the total number of sequences that are functional, andN = the total number of possible sequences, functional and non-functional.Hazen's equation has two unknowns for protein families: I(Ex) and M(Ex). However, I have published a method² to solve for a minimum value of I(Ex) using actual data from the Protein Family database (Pfam)³, and have made this software publicly available. We can then solve for M(Ex).
Now, back to the question of what type of probability scientists are interested in. The answer is M(Ex)/N. This ratio gives us the probability of finding a functional sequence from a pool of N possibilities in a single trial. To clarify, we are not interested in the probability of getting a specific sequence; any functional sequence will do just fine. Armed with this information, let us see what M(Ex)/N is for the Darwinist/YouTube examples given above.
In the first video, the total number of possibilities is N = 10^157, but what is M(Ex)? In this case, any sequence of symbols would have served as an example. Therefore, M(Ex) = N. The probability M(Ex)/N of obtaining a sequence that serves the purpose is therefore 1. Using Hazen's equation, the functional information required to randomly place the 100 symbols in the grid is 0 bits.
In the second example, the narrator shuffles 52 cards three successive times, then claims the total number of possibilities is N = 10^204. The real question is, What is M(Ex)? How many other sequences of shuffled cards would have served this function? Not surprisingly, any sequence would have sufficed -- again, M(Ex) = N. The probability M(Ex)/N of obtaining three series of card sequences that serves this purpose is exactly 1.
For my lecture at the University of Maine, any combination of people would have been fine so, again, M(Ex) = N and M(Ex)/N = 1.
Now let us do the same thing for a protein, using data from the Pfam database.
I downloaded 16,267 sequences from Pfam for the AA permease protein family. After stripping out the duplicates, 11,056 unique sequences for AA Permease remained. After running the resulting multiple sequence alignment through the software I mentioned earlier, the results showed that a minimum of 466 bits of functional information are required to code for AA permease. Using Hazen's equation to solve for M(Ex), we find that M(Ex)/N < 10^-140 where N = 20^433. The extreme upper limit for the total number of functional sequences for AA permease is M(Ex) = 10^97 functional sequences. The actual value for M(Ex) is certain to be numerous orders of magnitude smaller, due to site interdependencies as explained in my paper².
So what do we see? In a single trial, the probability of obtaining a functional sequence by randomly sequencing codons is pretty much 0. Conversely, the probability of evolution producing a non-functional protein is very close to 1. Therefore, we can predict that evolution will readily produce de novo genes that fail to give functional, stable 3D structures. Clearly, the Darwinists on YouTube ignore this problem in protein science. If you estimate the extreme upper limit for the total number of mutation events in the entire history of life, using 10^30 life forms, a fast mutation rate, large genome size, and fast replication rate, it is less than 10^43 . Not surprisingly, this is pathetically underpowered for locating proteins where only 1 in 10^140 sequences is functional. However, it gets far worse, for evolution must "find" thousands of them.
Nonetheless, scientific literature reveals an unshakable belief that evolution can do the wildest, most improbable things tens of thousands of times over. Consequently, I believe Darwinism has become a religion, specifically a modern form of pantheism, where nature performs thousands of miracles -- none of which can be reproduced in a lab. On the other hand, if we apply a scientific method to detect intelligent design discussed here, we see that 433 bits of information is a strong marker of an intelligent origin. This test for intelligent design reveals the most rational position to take is that the genomes of life contain digital information from an intelligent source.
In a future post, I plan to examine the Darwinists' assumption that if the sequence is assembled step by step, it is much more probable.
References:
(1) Hazen et al., "Functional information and the emergence of biocomplexity," PNAS, 2007 May 15: 104:. suppl 1.
(2) Durston et al., "Measuring the functional sequence complexity of proteins," Theor Biol Med Model, 2007 Dec. 6;4:47.
(3) The Pfam protein families database: towards a more sustainable future: R.D. Finn, P. Coggill, R.Y. Eberhardt, S.R. Eddy, J. Mistry, A.L. Mitchell, S.C. Potter, M. Punta, M. Qureshi, A. Sangrador-Vegas, G.A. Salazar, J. Tate, A. BatemanNucleic Acids Research (2016) Database Issue 44:D279-D285.

Right to die v. Patient's rights

NY High Court Rejects Assisted Suicide Right
Wesley J. Smith

There is no constitutional right to assisted suicide, so the courts keep ruling. In Washington v. Glucksberg (1997), the Supreme Court of the United States rejected an attempt to impose an assisted suicide Roe v. Wade.

State supreme courts have rejected state constitutional claims in Florida, New Mexico, and elsewhere.

In fact no high court in the U.S. has ever ruled that there is a constitutional right to assisted suicide (including in Montana, which issued a muddled ruling that assisted suicide did not violate public policy).

Now,  New York can be added to the growing list.

First, a little background: The zealots at Compassion and Choices — formerly the more honestly named Hemlock Society — want the courts to pretend that when a doctor prescribes a lethal overdose for use in self-killing, it isn’t really suicide. This blatant word-engineering attempt is rejected outright by the court.  From the Myers v. Schneiderman:

Suicide has long been understood as “the act or an instance of taking one’s own life voluntarily and intentionally.”…Black’s Law Dictionary defines “suicide” as “[t]he act of taking one’s own life,” and “assisted suicide” as “[t]he intentional act of providing a person with the medical means or the medical knowledge to commit suicide” (10th ed 2014). Aid-in-dying falls squarely within the ordinary meaning of the statutory prohibition on assisting a suicide.

Duh.

The court proceeds to reject the constitutional claim to assisted suicide by a terminally ill person on several grounds. Here’s one that bears noting: Refusing medical treatment when death is the likely outcome is not synonymous with a “right to die.”

Contrary to plaintiffs’ claim, we have never defined one’s right to choose among medical treatments, or to refuse life-saving medical treatments, to include any broader “right to die” or still broader right to obtain assistance from another to end one’s life…

We have consistently adopted the well-established distinction between refusing life-sustaining treatment and assisted suicide. The right to refuse medical intervention is at least partially rooted in notions of bodily integrity, as the right to refuse treatment is a consequence of a person’s right to resist unwanted bodily invasions.

Yup.

The court also notes that there is a rational basis for the state’s law against assisted suicide:

As to the right asserted here, the State pursues a legitimate purpose in guarding against the risks of mistake and abuse. The State may rationally seek to prevent the distribution of prescriptions for lethal dosages of drugs that could, upon fulfillment, be deliberately or accidentally misused.

This is very good. The last thing this country needs are courts imposing extra-democratically a radical social revolution against venerable values and mores, particularly in the face of hundreds of legalization rejections by voters and legislatures throughout the United States over the last twenty years.

One more point: When a social movement feels the need to hide its actual agenda beneath a veneer of gooey euphemisms (“aid-in-dying,” “death with dignity,” etc.) there is something very subversive about the agenda.

The ostrich v. Darwin.

Ostrich Kneecaps — Another Enduring Mystery for Darwinism
Cornelius Hunter  

Why do ostriches have four, rather than two, kneecaps? new study has found several possible biomechanical advantages. Perhaps they allow the ostrich to straighten its leg more quickly, helping the animal to run quickly. Perhaps the lower kneecap protects the joined tendons crossing the front of the knee.

One reason that does not help to explain the ostriches four kneecaps is evolution. That is because this unique design is not predicted, and makes no sense, on the theory.

As  one article admits: “Bizarrely, many of the ostrich’s closest relatives don’t have kneecaps at all.” Similarities across the species were a strong argument for evolution, but in fact biology is full of unique designs, particular to one or a few species.

Such one-off, “lineage specific” designs are “bizarre” for evolutionists. So while there are design reasons for the ostriches four kneecaps, on the ordinary view of the evolution of each being, we can only say that so it is.