Here’s his latest.
Also remember, Aron Ra, DPR Jones, Lone Frank, and I will be on the Magic Sandwich Show tomorrow at 8pm GMT, live from Dublin. Tune in!
Pharyngula
Evolution, development, and random biological ejaculations from a godless liberal
Here’s his latest.
Also remember, Aron Ra, DPR Jones, Lone Frank, and I will be on the Magic Sandwich Show tomorrow at 8pm GMT, live from Dublin. Tune in!
Science magazine has published the formal criticisms of the claim to have found extremophiles that substituted arsenic for phosphorus in their chemistry. It’s a thorough drubbing, and the most disappointing part is that Wolfe-Simon’s rebuttal simply insists that they were right, and doesn’t even acknowledge that many valid criticisms of the study were made. That’s not how you do it. Instead, she should answer the complaints by saying that they will do the experiments in a way that specifically addresses the perceived shortcomings of the study; she and her lab have their credibility invested in this research now, and the answer to the barrage is not to batten down the hatches and do nothing, but to do more experiments to show that the critics are wrong.
Nature also has a discussion of the issues, and this article bothered me in other ways. It rationalizes not doing anything to replicate or refute the work.
However, most labs are too busy with their own work to spend time replicating work that they feel is fundamentally flawed, and it’s not likely to be published in high-impact journals. So principal investigators are reluctant to spend their resources, and their students’ time, replicating the work.
“If you extended the results to show there is no detectable arsenic, where could you publish that?” said Simon Silver of the University of Illinois at Chicago, who critiqued the work in FEMS Microbiology Letters in January and on 24 May at the annual meeting of the American Society for Microbiology in New Orleans. “How could the young person who was asked to do that work ever get a job?” Silver said.
It’s true that this ought to be a relatively low priority for labs that are busy with good research, but it’s depressing to see that 1) whether something is publishable in high impact journals is such an important criterion for what we do, 2) skeptical science that replicates and refutes is considered a waste of effort, and 3) students are discouraged from carrying out such work, because there is some strange bias that will hurt their chances of employment.
I’m not disagreeing with those arguments, but I’m suggesting that they are symptoms of something rotten in the world of science. Testing claims ought to be what we do. If the journals are going to fill up with positive claims thanks to the file-drawer effect, and if nobody ever wants to evaluate those claims, and if negative results are unpublishable, the literature is going to decline in utility for lack of rigor and evaluation.
Of course, there is one group that has real incentive to get in there and get their hands dirty refining the results: the Wolfe-Simon lab. But her response implies she’s not going to make the effort (although I hope she really is doing something). And this attitude above suggests that, while the positive claim received a lot of media hoopla, any discovery of alternative explanations is going to get ignored. Methinks I see a ratchet at work.
I also notice that Rosie Redfield, brilliant genius that she is, has a relatively simple test of the claims. It’s not my field and I’m not equipped to do any of it, but I don’t see why anyone would find it a waste of effort to assign that project to a first-year grad student, as an exercise in techniques and skill, and as a way to get a quick (I know, low impact!) publication.
And I’m still bewildered that the scientific community would consider tests of a hypothesis a poor investment of its resources. This isn’t like creationism; Wolfe-Simon has a very specific claim that can be evaluated with standard laboratory techniques.
That study claiming that black women are “objectively” unattractive seems to be finally getting its author, Satoshi Kanazawa, in big trouble. That would be entirely wrong if it were based on disliking his conclusions, but if it were based on a demonstration of Kanazawa’s incompetence, then it would be earned. And that seems to be what is happening. Interestingly, many really good criticisms of Kanazawa are coming from Psychology Today’s blogs.
Daniel Hawes critiques his use of factor analysis and the problem of factor indeterminacy. This is a discussion of the failures of Kanazawa’s methodology, but also points out that he’s been peddling pseudoscience week after week.
An anticipated critique to what I’m saying here is that people will argue that I’m uncomfortable with his argument because it is politically incorrect. My above explanation has no reference to political correctness. The source of my frustration with Kanazawa’s writing is his pseudoscience. Given Kanazawa’s history of unabashedly blogging about research that he very well knows to be faulty at best and outright wrong at worst, my criteria for pseudoscience I discussed above are met. Yet, there is a natural reason that I (and others) have decided to respond to Kanazawa most recent article, and not as extensively to previous ones, that clearly follow the same disturbing pattern. Every other week there is a ridiculous Fundamentalist post claiming to explain “Why Night Owls are more intelligent”, or asking “Are all Women essentially Prostitutes?”, or posing the conjecture that “If Obama is Christian, Michael Jackson is White.” It seems hardly worth the effort to each time try to debunk the absurdity underlying these sensationalist arguments. However, when this unreasonable behavior spills into discussions of socially contentious issues such as race, I believe that pseudoscience left uncommented is dangerous. In particular it can quickly provide a basis for “scientific racism”, and so I believe that it is dutiful behavior for scientists and writers – especially when sharing the same media platform – to take a stance when these kind of discussions surface.
Scott Barry Kaufman and Jelte Wicherts have done something even more interesting: they downloaded the Add Health dataset that Kanazawa used and analyzed it independently. This is very revealing.
Kanazawa mentions several times that his data on attractiveness are scored “objectively”. The ratings of attractiveness made by the interviewers show extremely large differences in terms of how attractive they found the interviewee. For instance the ratings collected from Waves 1 and 2 are correlated at only r = .300 (a correlation ranges from -1.0 to +1.00), suggesting that a meager 9% of the differences in second wave ratings of the same individual can be predicted on the basis of ratings made a year before. The ratings taken at Waves 3 and 4 correlated between raters even lower, at only .136– even though the interviewees had reached adulthood by then and so are not expected to change in physical development as strongly as the teenagers. Although these ratings were not taken at the same time, if ratings of attractiveness have less than 2% common variance, one is hard pressed to side with Kanazawa’s assertion that attractiveness can be rated objectively.
The “waves” refer to the fact that the data is grouped by age into several categories, and he makes another interesting observation: if you look at only the adult wave, which is the only appropriate one if you want to talk about differences in sexual attractiveness, there are no differences by race.
Focusing just on Wave 4, it is obvious that among the women in the sample, there is no difference between the ethnicities in terms of ratings of physical attractiveness. Differences in the distributions for females when tested with a regular (and slightly liberal) test of independence is non-significant and hence can be attributed to chance (Pearson’s Chi-Square=15.6, DF=12, p =.210).
Now there’s the kind of statistical rigor I’ve come to expect and respect from my psychology colleagues.
So many people have sent me this sensationalistic article, “Scientists cure cancer, but no one takes notice“, that I guess I have to respond. I sure wish it were true, but you should be able to tell from how poorly it is written and the ridiculous inaccuracies (mitochondria are cells that fight cancers?) that you should be suspicious. The radical, exaggerated claims make the truth of the story highly unlikely.
Researchers at the University of Alberta, in Edmonton, Canada have cured cancer last week, yet there is a little ripple in the news or in TV. It is a simple technique using very basic drug. The method employs dichloroacetate, which is currently used to treat metabolic disorders. So, there is no concern of side effects or about their long term effects.
The simple summary is this: that claim is a lie. There have been no clinical trials of dichloroacetate (DCA) in cancer patients, so there is no basis for claiming they have a cure; some, but not all, cancers might respond in promising ways to the drug, while others are likely to be resistant (cancer is not one disease!); and there are potential neurotoxic side effects, especially when used in conjunction with other chemotherapies.
So we have one popular account that is badly written and makes exaggerated claims. There is also a university press release, the source for the sloppy popular account, that doesn’t contain the egregious stupidities but does tend to inflate basic research studies into an unwarranted clinical significance. And then, of course, there are the actual peer reviewed papers that describe the research and rationale, and also the reservations, on DCA. It’s like a game of telephone: you can actually trace the account from the sober science paper to the enthusiastic press release to the web account with its extravagant claims of a simple, cheap cure for cancer, and see how the story is gradually corrupted. It would be funny if the final result wasn’t going to dupe a lot of desperate people.
But there is a germ of truth to the story, in that DCA does have potential. Here’s how it works.
There are two major pathways that we use to extract energy from sugar. One is glycolysis, which extracts two ATP molecules from each molecule of sugar, and doesn’t require oxygen. Then there is glucose oxidation, which as you might guess from the name, does require oxygen, but which takes the byproducts of glycolysis and burns them completely to produce 36 ATP. So there’s the tradeoff: if your cells are oxygen-starved, or hypoxic, they can still get energy from sugar, but it’s relatively inefficient, but if they do have access to oxygen, they can extract much more. This is why you breathe, and why your heart beats, and why you have an elaborate circulatory system to deliver oxygenated blood to your tissues: without oxygen, you suffer a catastrophic hit to the efficiency of energy production.
Another feature of these two energy-producing pathways is that they are in different cellular compartments. Glycolysis takes place in the cytoplasm, while glucose oxidation occurs in the mitochondria. There is a gate-keeping enzyme, pyruvate dehydrogenase kinase (PDK), that regulates the flow of pyruvate, a product of the glycolysis pathway, into the mitochondria for oxidation. If PDK is active, it suppresses the transport of pyruvate into the mitochondria, and the cell is forced to rely on glycolysis, even if oxygen is available. If PDK is inactivated, pyruvate is shuttled into the mitochondria, even if oxygen is low.
This is where DCA comes in. DCA inhibits PDK, forcing cells to use the more efficient form of energy production. That sounds like a strange way to make a cancer cell uncomfortable, but the other factor here is that mitochondria are primary regulators of apoptosis, or cell suicide. They are loaded with sensors and enzymes that react to abnormalities in the cell (like being cancerous!) by activating a self-destruct mechanism. Shut down the mitochondra, you shut down the self-destruct mechanism that polices the cell. So the idea is a little indirect: by goosing the mitochondria, we also wake up the safety switch that, if all goes well, will cause the cell to spontaneously kill itself.
There are good reasons to think this might work. Many cancer cells arise in hypoxic environments; a poorly vascularized tumor, for instance, is going to be oxygen starved in the absence of blood flow, and the inhibition of mitochondria may be a factor in their survival. There is a well-known phenomenon called the Warburg effect, in which cancer cells will rely on glycolysis even when oxygen is available, suggesting that they have suppressed their mitochondria.
DCA also seems like a relatively safe drug. It’s been used for a long time in patients with metabolic disorders, or with metabolic side effects from other problems.
A large number of children and adults have been exposed to DCA over the past 40 years, including healthy volunteers and subjects with diverse disease states. Since its first description in 1969, DCA has been studied to alleviate the symptoms or the haemodynamic consequences of the lactic acidosis complicating severe malaria, sepsis, congestive heart failure, burns, cirrhosis, liver transplantation and congenital mitochondrial diseases. Single-arm and randomised trials of DCA used doses ranging from 12.5 to 100 mg kg-1 day-1 orally or intravenously). Although DCA was universally effective in lowering lactate levels, it did not alter the course of the primary disease (for example sepsis).
This is encouraging. It means there is a body of work already published on the effects of DCA, which should simplify the process of moving it into clinical trials. The authors, however, very clearly indicate that it won’t be a magic bullet affecting all cancers, but that some are likely candidates.
Dichloroacetate could be tested in a variety of cancer types. The realisation that (i) a diverse group of signalling pathways and oncogenes result in resistance to apoptosis and a glycolytic phenotype, (ii) the majority of carcinomas have hyperpolarised/ remodeled mitochondria, and (iii) most solid tumours have increased glucose uptake on PET imaging, suggest that DCA might be effective in a large number of diverse tumours. However, direct preclinical evidence of anticancer effects of DCA has been published only with non-small cell lung cancer, glioblastoma and breast, endometrial and prostate cancer. In addition, the lack of mitochondrial hyperpolarisation in certain types of cancer, including oat cell lung cancer, lymphomas, neuroblastomas and sarcomas, suggest that DCA might not be effective in such cases. Cancers with limited or no meaningful therapeutic options like recurrent glioblastoma or advanced lung cancer should be on top of the list of cancers to be studied.
Notice that the only work done so far is preclinical: that means it has been tested in mouse models, tissue culture, but hasn’t really been tried in cancer patients yet. The authors come right out and say that, express some possible reservations about its effectiveness, and suggest what needs to be done next.
No patient with cancer has received DCA within a clinical trial. It is unknown whether previously studied dose ranges will achieve cytotoxic intra-tumoral concentrations of DCA. In addition, the overall nutritional and metabolic profile of patients with advanced cancer differs from those in the published DCA studies. Furthermore, pre-exposure to neurotoxic chemotherapy may predispose to DCA neurotoxicity. Carefully performed phase I dose escalation and phase II trials with serial tissue biopsies are required to define the maximally tolerated, and biologically active dose. Clinical trials with DCA will need to carefully monitor neurotoxicity and establish clear dose-reduction strategies to manage toxicities. Furthermore, the pharmacokinetics in the cancer population will need to be defined.
Do not rush out and buy DCA and gurgle it down as a cancer preventative. We don’t know that it works — the safe concentrations for you may not be sufficient to kill any cancer cells, and the concentrations needed to kill cancer cells may be so high that it will do horrible, unpredicted, and dangerous things to you (some work with patients with congenital mitochondrial disorders also revealed some degree of peripheral neuropathy, for instance). This is why we have clinical trials: to work out safe and effective doses, look for dangerous interactions with other drugs — and if you have cancer, you’re already on a complicated cocktail of drugs — and detect unexpected side effects.
We should be urging further investigation of this promising drug with the beginning of clinical trials, but it’s far too early to be babbling about “cancer cures”. There have been lots of drugs that look great in the lab and have excellent rationales for why they should work, but the reality of cancer is that it is complicated and diverse and there are many more pitfalls between a drug that poisons cancer cells in a petri dish and a drug that actually works well in the more complex environment of a human being.
One other factor that inflames the conspiracy nuts over this drug is that DCA is simple, dirt-cheap, and completely unpatentable — there is no economic incentive for a pharmaceutical company to invest a gigantic bucket of money in clinical trials, because there is no hope for a return on the investment.
This is why an independent academic community with research funded for knowledge rather than profit is so important, and really emphasizes why we cannot afford to privatize all biomedical research. The authors propose a plan for progressing without the involvement of the pharmaceutical industry.
Funding for such trials would be a challenge for the academic community as DCA is a generic drug and early industry support might be limited. Fundraising from philanthropies might be possible to support early phase I – II or small phase III trials. However, if these trials suggest a favourable efficacy and toxicity, the public will be further motivated to directly fund these efforts and national cancer organisations like the NCI, might be inspired to directly contribute to the design and structure of larger trials. It is important to note that even if DCA does not prove to be the ‘dawn of a new era’, initiation and completion of clinical trials with a generic compound will be a task of tremendous symbolic and practical significance. At this point the ‘dogma’ that trials of systemic anticancer therapy cannot happen without industry support, suppresses the potential of many promising drugs that might not be financially attractive for pharmaceutical manufacturers. In that sense, the clinical evaluation of DCA, in addition to its scientific rationale, will be by itself another paradigm shift.
I can’t blame the industry for not following up on this: a clinical trial costs millions of dollars, and even if DCA pans out, there is no profit at all to be gained from it. For this research, we have to turn to public support (they have an interest in better cancer treatments!) and to scientists and doctors themselves, who of course have a great personal interest in seeing their patients get better.
Michelakis ED, Webster L, Mackey JR (2008) Dichloroacetate (DCA) as a potential metabolic-targeting therapy for cancer. Br J Cancer 99(7):989-94.
Since I previously expressed my disappointment in the “squid in space” experiment that will be going up on the space shuttle, I’ve received a rebuttal from the lead investigator of the project. Fair’s fair; here it is.
Dear Dr. Myers,
I am the lead investigator on the Squid in Space project and an Assistant Professor at the University of Florida. I have read your description of the project in your blog and I feel that it is incomplete and missing the major point of the experiment. As you can imagine one doesn’t like to have their work labeled as “Bad Science” so I wanted to take this opportunity to write to you to elaborate on the press release that I assume inspired you to write the blog.
First, as you correctly pointed out in the blog that the squid are a models for how bacteria interact with animal tissues. For over 20 years this symbiosis has provided important clues as to how bacteria “talk” and communicate with host animals cells.
Vibrio fischeri induces several developmental events in the juvenile squid including a modification of the host immune system, and induction of an apoptotic cell death event. Similar events also happen in humans in response to both mutualistic bacteria, so by understanding how these mechanisms work in a simple squid/vibrio association we can make inferences to the human body. So that is why we chose the squid as a model system for the space experiment.
Second, we know that in microgravity conditions an astronaut’s immune systems appear to be dysregulated. However, in the few studies that involved human astronauts the results have been variable. So again the squid model allows us to be a bit more invasive than we could with human studies.
Also some bacteria become more virulent in space. The work of Cheryl Nickerson from Tulane has shown several microbes including Salmonella become far more virulent after exposure to microgravity conditions. However nothing is know about how commensal/mutualistic bacteria respond to microgravity conditions at the cellular level. So this experiment allows us to see the impact the microgravity treated V. fischeri has on the immune response and development juvenile squid (no embryos are going into space that was an error by the student reporter who wrote the release; we are sending hatched juvenile animals).
As 90% of the cells in our bodies are bacterial, we wanted to assess whether microgravity influences the “healthy” bacteria in anyway. Are developmental time lines disrupted? Does the V. fischeri initiation the changes in the host immune system and normal development (e.g. cell death events)? Basically do “good” bacteria go “bad”? These could be important questions to address for long-duration space flight and reduce the potential risk that astronauts may have to face.
We are also learning more about the natural symbiosis by experimenting with these animals under natural and simulated microgravity. By removing gravity as a constant we are able to determine to see if gravity might be obscuring aspects of the association. For example we are learning that some signals that activate the immune system (e.g. the trafficking of macrophages) are actually uncoupled in microgravity telling us that the signals may not function as we previously thought. More work on what the second signal could be is underway using simulated microgravity.
I hope this explains in a bit more detail why we are looking at these animals and flying the “Squid in Space” experiment. I know the press release did not fully explain the rationale behind the student run experiments.
If you have any additional questions or concerns regarding the science and objectives I would be happy to provide more detail.
Sincerely,
Jamie S. Foster
I’m a major fan of kidneys — they’re fascinating organs for discussion of both development and evolution. Today I lectured about them in my human physiology course, but I could only briefly touch on their development, and instead had to talk on and on about countercurrent multipliers and juxtamedulary nephrons and transport membranes and all that functional physiology stuff. So I thought I’d get the evo-devo out of my system with a few words about them here.
Our kidneys go through an elaborate series of three major developmental stages — we essentially build three pairs of kidneys as embryos, and jettison two pairs as we go along. It actually looks like something out of Haeckel’s recapitulation theory, as we progressively assemble and then discard ‘primitive’ kidneys.
The first stage is the formation of the pronephric kidney. In the embryo, the circulatory system forms glomeruli, or tangled capillary beds, adjacent to the membrane that surrounds the body cavity, or coelom. Filtered plasma oozes into the coelom, and the pronephric kidney has ciliated openings into the coelom called nephrostomes, and the fluid is drawn into the tubules, where membrane pumps recover nutrients and salts and return them to the circulatory system. Whatever is left behind — wastes and water — trickles into the pronephric duct, which terminates in the cloaca.
It’s a simple, low pressure system that is adequate for collecting waste products from the early embryo. It relies on an existing cavity for collecting filtered fluids, and you can tell that it doesn’t use a high-pressure filtration scheme since it can get by with simple ciliary beating to cause fluid flow. It’s a primitive system that is retained for functional reasons: metabolizing embryonic cells are producing chemical waste products, and some kind of waste disposal system is essential for even this early stage.
The second stage is the mesonephric kidney. New tubules bud off the pronephric duct, but unlike the pronephric tubules, these are directly invested with capillary glomeruli and form spherical filtrate collectors called Bowman’s capsules. This is the big functional difference from the pronephros: filtered fluids are no longer collected indirectly from the coelom, but straight from the circulatory system. Some of the mesonephric tubules may retain a connection with the coelom, but this is no longer the sole way to collect filtrate.
The pronephros degenerates completely as the mesonephros takes over its job. As it withers away, the mesonephric tubules continue to use the pronephric duct, which gets renamed: it’s now called either the mesonephric duct, or if you prefer the old school names, the Wolffian duct. Even the mesonephros is doomed, though; it’s an intermediate stage that can cope with the light loads of waste produced by the embryo at this point, but an even more elaborate, more efficient kidney, the metanephros, is also beginning to grow, and it’s going to make the mesonephros superfluous.
<
The metanephric kidney, the third and final stage of development (the metanephric kidney is the familiar adult kidney we all possess), buds from the mesonephric duct and forms a unique structure with familiar elements. The new kidney makes branching ducts from a central collecting point, like a spray of flowers; these new ducts look just like mesonephric tubules, with a Bowman’s capsule on the outer, or cortical side of the kidney, and loops descending down into the medulla to generate a concentration gradient of salts used in generating hyperosmotic urine (which is what I talked about in class today, and won’t say anything further here). The subunits are similar to the mesonephric tubules, just arrayed in a different and specific organization for even more effective mechanisms for maintaining salt balance.
This metanephric stage is also complicated by the co-development of the reproductive system. The gonads are differentiating and forming alongside the degenerating mesonephric kidney. In addition, another duct, the Müllerian duct forms in parallel to the Wolffian duct, so now, briefly, we have two pairs of kidneys and two pairs of longitudinal ducts. This is going to be followed by consolidation and change, though, and it’s going to be a sex dependent pattern.
In females, the Wolffian duct is mostly going to degenerate and be lost, along with the mesonephros. The Müllerian duct is going to develop into the fallopian tubes, uterus, cervix, and upper vagina. The only part of the mesonephric duct retained will be the branch connecting the metanephros to the cloaca.
In males, the M&uum;llerian duct degenerates. Yes, it seems incredibly wasteful and pointless: we guys built this parallel duct as embryos, and then promptly threw it away, unused. Instead, the Wolffian/mesonephric duct is retained and becomes the ductus deferens, that useful tube for transporting sperm from the testis to the penis.
I think you can see what’s cool about the kidneys — they follow a sequential pattern of development that also happens to reflect the evolutionary history of kidneys. You might be tempted to speculate that it follows a Haeckelian model, where development necessarily follows an evolutionary trajectory because change can only come by addition of new features, but don’t be fooled. There are a couple of reasons why this peculiar pattern of retaining ancient kidney types is maintained.
One is existence of developmental linkages: disrupting any of these earlier kidneys leads to serious developmental anomalies in subsequent kidneys. Each kidney is built on the foundations of the previous one; mutations that would excise that old less efficient, less sophisticated form would also prevent the normal development of the metanephros. Even if they were totally non-functional, we would still need the patterning aspect of the primitive kidneys to be present.
The other reason is functional. The metanephric kidney is complex and intricate, and takes more time to develop — but cellular metabolism isn’t going to just stop everywhere else in the embryo and wait for the kidneys to be put in place. It’s like the situation when construction workers are building a house, and they still occasionally need to empty their bladders, even if the elaborate bathroom faced with Grecian marble and equipped with the latest German plumbing fixtures isn’t done yet … so a porta-potty is wheeled onto the site.
And that’s what I like about kidneys: all the funky relics of the construction process are still there, hanging out and seeming to contribute to an excessively complex tangle of complicated relationships.
Kalthoff K (2001) Analysis of biological development. McGraw-Hill, NY.
I’ve been giving talks at scientific meetings on educational outreach — I’ve been telling the attendees that they ought to start blogs or in other ways make more of an effort to educate the public. I mentioned one successful result the other day, but we need more.
I give multiple reasons for scientists to do this. One is just general goodness: we need to educate a scientifically illiterate public. Of course, like all altruism, this isn’t really recommended out of simple kindness, but because the public ultimately holds the pursestrings, and science needs their understanding and support. Another reason, though, is personal. Scientific results get mangled in press releases and news accounts, so having the ability to directly correct misconceptions about your work ought to be powerfully attractive. Even worse, though, I tell them that creationists are actively distorting their work. This goes beyond simple ignorance and incomprehension into the malign world of actively lying about the science, and it happens more often than most people realize.
I have another painful example of deviousness of creationists. There’s a paper I’ve been meaning to write up for a little while, a Nature paper by David and Alm that reveals an ancient period of rapid gene expansion in the Archaean, approximately 3 billion years ago. Last night I thought I’d just take a quick look to see if anybody had already written it up, so I googled “Archaean genetic expansion,” and there it was: a couple of references to the paper itself, a news summary, one nice science summary, and…two creationist distortions of the paper, right there on the first page of google results. I told you! This happens all the time: if there’s a paper in one of the big journals that discusses more evidence for evolution, there is a creationist hack somewhere who’ll quickly write it up and lie about it. It’s a heck of a lot easier to summarize a paper if you don’t understand it, you see, so they’ve got an edge on us.
One of the creationist summaries is by an intelligent design creationist. He looks at the paper and claims it supports this silly idea called front-loading: the Designer seeded the Earth with creatures that carried a teleological evolutionary program, loading them up with genes at the beginning that would only find utility later. The unsurprising fact that many gene families are of ancient origin seems to him to confirm his weird idea of a designed source, when of course it does nothing of the kind, and fits quite well in an evolutionary history with no supernatural interventions at all.
The other creationist summary is from an old earth biblical creationist who tries to claim that “explosive increase in biochemical capabilities happened in anticipation of changes that were to take place in the environment”, a conclusion completely unsupportable from the paper, and also tries to telescope a long series of changes documented in the data into a single ancient event so that they can claim that the rate of innovation was so rapid that it contradicts the “evolutionary paradigm”.
So lets take a look at the actual paper. Does it defy evolutionary theory in any way? Does it actually make predictions that fit creationist models? The answer to both is a loud “NO”: it is a paper using methods of genomic analysis that produce evolutionary histories, it describes long periods of gradual modification of genomes, and it correlates genomic innovations with changes in the ancient environment. It is freakin’ bizarre that anyone can look at this work and think it supports creationism, but there you are, standard operating procedure in the fantasy world of the creationist mind.
Here’s the abstract, so you can get an idea of the conclusions the authors draw from the work.
The natural history of Precambrian life is still unknown because of the rarity of microbial fossils and biomarkers. However, the composition of modern-day genomes may bear imprints of ancient biogeochemical events. Here we use an explicit model of macro- evolution including gene birth, transfer, duplication and loss events to map the evolutionary history of 3,983 gene families across the three domains of life onto a geological timeline. Surprisingly, we find that a brief period of genetic innovation during the Archaean eon, which coincides with a rapid diversification of bacterial lineages, gave rise to 27% of major modern gene families. A functional analysis of genes born during this Archaean expan- sion reveals that they are likely to be involved in electron-transport and respiratory pathways. Genes arising after this expansion show increasing use of molecular oxygen (P=3.4 x 10-8) and redox- sensitive transition metals and compounds, which is consistent with an increasingly oxygenating biosphere.
This work is an analysis of the distribution of gene families in modern species. Gene families, if you’re unfamiliar with the term, are collections of genes that have similar sequences and usually similar functions that clearly arose by gene duplications. A classic example of a gene family are the globin genes, an array of very similar genes that produce proteins that are all involved in the transport of oxygen; they vary by, for instance, their affinity for oxygen, so there is a fetal hemoglobin which binds oxygen more avidly than adult hemoglobin, necessary so the fetus can extract oxygen from the mother’s circulatory system.
So, in this paper, David and Alm are just looking at genes that have multiple members that arose by gene duplication and divergence. They explicitly state that they excluded singleton genes, things called ORFans, which are unique genes within a lineage. That does mean that their results underestimate the production of novel genes in history, but it’s a small loss and one the authors are aware of.
If we were looking for evidence for evolution, we might as well stop here. The existence of gene families, for cryin’ out loud, is evidence for evolution. This paper is far beyond arguing about the truth of evolution — that’s taken for granted as the simple life’s breath of biology — but instead asks a more specific question: when did all of these genes arise? And they have a general method for estimating that.
Here’s how it works. If, for example, we have a gene family that is only found in animals, but not in fungi or plants or protists or bacteria, we can estimate the date of its appearance to a time shortly after the divergence of the animal clade from all those groups. If a gene family is found in plants and fungi and animals, but not in bacteria, we know it arose farther back in the past than the animal-only gene families, but not so far back as a time significantly predating the evolution of multicellularity.
Similarly, we can also look at gene losses. If a gene family or member of a gene family is present in the bacteria, and also found in animals, we can assume it is ancient in origin and common; but if that same family is missing in plants, we can detect a gene loss. Also, if the size of the gene family changes in different lineages, we can estimate rates of gene loss and gene duplication events.
I’ve given greatly simplified examples, but really, this is a non-trivial exercise, requiring comparisons of large quantities of data and also analysis from the perspective of the topologies of trees derived from that data. The end result is that each gene family can be assigned an estimated date of origin, and that further, we can estimate how rapidly new genes were evolving over time, and put it into a rather spectacular graph.
Look first at just the red areas. That’s a measure of the rate of novel gene formation, and it shows a distinct peak early in the history of life, around 3 billion years ago. 27% of our genes are very, very old, arising in this first early flowering. Similarly, there’s a slightly later peak of gene loss, the orange area. This represents a period of early exploration and experimentation, when the first crude versions of the genes we use now were formed, tested, discarded if inefficient, and honed if advantageous.
But then the generation of completely novel genes drops off to a low to nonexistent rate (but remember, this is an underestimate because ORFans aren’t counted). If you draw any conclusions from the graph, it’s that life on earth was essentially done generating new genes about one billion years ago…but we know that all the multicellular diversity visible to our eyes arose after that period. What gives?
That’s what the blue and green areas tell us. We live in a world now rich in genetic diversity, most of it in the bacterial genomes, and our morphological diversity isn’t a product so much of creating completely new genes, but of taking existing, well-tested and functional genes and duplicating them (blue) or shuffling them around to new lineages via horizontal gene transfer (green). This makes evolutionary sense. What will produce a quicker response to changing conditions, taking an existing circuit module off the shelf and repurposing it, or shaping a whole new module from scratch through random change and selection?
This diagram gives no comfort to creationists. Look at the scale; each of the squares in the chart represents a half billion years of time. The period of rapid bacterial cladogenesis that produced the early spike is between 3.3 and 2.9 billion years ago — this isn’t some brief, abrupt creation event, but a period of genetic tinkering sprawling over a period of time nearly equal to the entirety of the vertebrate fossil record of which we are so proud. And it’s ongoing! The big red spike only shows the initial period of recruitment of certain genetic sequences to fill specific biochemical roles — everything that follows testifies to 3 billion years of refinement and variation.
The paper takes another step. Which genes are most ancient, which are most recent? Can we correlate the appearance of genetic functions to known changes in the ancient environment?
the metabolites specific to the Archaean Expansion (positive bars in Fig. 2 inset) include most of the compounds annotated as redox/e– transfer (blue bars), with Fe-S-binding, Fe-binding and O
2-binding gene families showing the most significant enrichment (false discovery rate<5%, Fisher’s exact test). Gene families that use ubiquinone and FAD (key metabolites in respiration pathways) are also enriched, albeit at slightly lower significance levels (false discovery rate<10%). The ubiquitous NADH and NADPH are a notable exception to this trend and seem to have had a function early in life history. By contrast, enzymes linked to nucleotides (green bars) showed strong enrichment in genes of more ancient origin than the expansion. The observed bias in metabolite use suggests that the Archaean Expansion was associated with an expansion in microbial respiratory and electron transport capabilities.
So there is a coherent pattern: genes involved in DNA/RNA are even older than the spike (vestiges of the RNA world, perhaps?), and most of the genes associated with the Archaean expansion are associated with cellular metabolism, that core of essential functions all extant living creatures share.
Were we done then, as the creationists would like to imply? No. The next major event in the planet’s history is called the Great Oxygenation Event, in which the fluorishing bacterial populations gradually changed the atmosphere, excreting more and more of that toxic gas, oxygen.
What happened next was a shift in the kinds of novel genes that appeared: these newer genes were involved in oxygen metabolism and taking advantage of the changing chemical constituents of the ocean.
Our metabolic analysis supports an increasingly oxygenated biosphere after the Archaean Expansion, because the fraction of proteins using oxygen gradually increased from the expansion to the present day. Further indirect evidence of increasing oxygen levels comes from compounds whose availability is sensitive to global redox potential. We observe significant increases over time in the use of the transition metals copper and molybdenum, which is in agreement with geochemical models of these metals’ solubility in increasingly oxidizing oceans and with molybdenum enrichments from black shales suggesting that molybdenum began accumulating in the oceans only after the Archaean eon16. Our prediction of a significant increase in nickel utilization accords with geochemical models that predict a tenfold increase in the concentration of dissolved nickel between the Proterozoic eon and the present day but conflicts with a recent analysis of banded iron formations that inferred monotonically decreasing maximum concentrations of dissolved nickel from the Archaean onwards. The abundance of enzymes using oxidized forms of nitrogen (N2O and NO3) also grows significantly over time, with one-third of nitrate-binding gene families appearing at the beginning of the expansion and three-quarters of nitrous-oxide-binding gene families appearing by the end of the expansion. The timing of these gene-family births provides phylogenomic evidence for an aerobic nitrogen cycle by the Late Archaean.
So I don’t get it. I don’t see how anyone can look at that diagram, with its record of truly ancient genomic changes and its evidence of the steady acquisition of new abilities correlated with changes in the environment of the planet, and declare that it supports a creation event or front-loading of biological potential in ancestral populations. That makes no sense. This is work that shouts “evolution” at every instant, yet some people want to pretend it’s an endorsement of theological hocus-pocus? Madness.
Scientists, you need to be aware of this. The David and Alm paper is an unambiguously evolutionary paper, using genomic data to describe evolutionary events via evolutionary mechanisms, and the creationists still appropriate and abuse it. If you publish anything about evolution, be sure to google your paper periodically — you may find that you’ve been unwittingly roped into endorsing creationism.
David LA, Alm EJ (2011) Rapid evolutionary innovation during an Archaean genetic expansion. Nature 469(7328):93-6.
I read this story with mounting disbelief. Every paragraph had me increasingly aghast. It’s another case of physicists explaining biology badly.
It started dubiously enough. Paul Davies, cosmologist and generally clever fellow, was recruited to help cure cancer, despite, by his own admission, having “no prior knowledge of cancer”.
Two years ago, in a spectacularly enlightened move, the US National Cancer Institute (NCI) decided to enlist the help of physical scientists. The idea was to bring fresh insights from disciplines like physics to help tackle cancer in radical new ways.
Uh, OK…I can agree that fresh insights can sometimes stimulate novel approaches. Cancer is an extraordinarily complex process, but maybe, just maybe, the scientists studying it are so deep in the details that they’re missing some obvious alternative avenue that would be productive to study. I can think of examples; for instance, Judah Folkman’s realization that inhibiting angiogenesis, the process by which cancers recruit a blood supply from healthy tissue, would be a clever way to attack cancers beyond just bashing the cancer cells themselves. But then, Folkman wasn’t ignorant of cancer…he came up with that strategy from a deep understanding of how cancers work.
So I’m doubtful, but prepared to read something that might be new and interesting…and then I read Davies’ suggestion. Gah.
A century ago the German biologist Ernst Haekel pointed out that the stages of embryo development recapitulate the evolutionary history of the animal. Human embryos, for instance, develop, then lose, gills, webbed feet and rudimentary tails, reflecting their ancient aquatic life styles. The genes responsible for these features normally get silenced at a later stage of development, but sometimes the genetic control system malfunctions and babies get born with tails and other ancestral traits. Such anomalous features are called atavisms.
Charles Lineweaver of the Australian National University is, like me, a cosmologist and astrobiologist with a fascination for how cancer fits into the story of life on Earth. Together we developed the theory that cancer tumours are a type of atavism that appears in the adult form when something disrupts the silencing of ancestral genes. The reason that cancer deploys so many formidable survival traits in succession, is, we think, because the ancient genetic toolkit active in the earliest stages of embryogenesis gets switched back on, re-activating the Proterozoic developmental plan for building cell colonies. If you travelled in a time machine back one billion years, you would see many clumps of cells resembling modern cancer tumours.
The implications of our theory, if correct, are profound. Rather than cancers being rogue cells degenerating randomly into genetic chaos, they are better regarded as organised footsoldiers marching to the beat of an ancient drum, recapitulating a billion-year-old lifestyle. As cancer progresses in the body, so more and more of the ancestral core within the genetic toolkit is activated, replaying evolution’s story in reverse sequence. And each step confers a more malignant trait, making the oncologist’s job harder.
I’m almost speechless. I’m almost embarrassed enough for Davies that I don’t want to point out the profound stupidities in that whole line of argument. But then, there’s this vicious little part of my brain that perks up and wants to leap and rend and gnaw and shred. Maybe it’s an atavism.
Please, someone inform Davies that Haeckel was wrong. Recapitulation theory doesn’t work and embryos do not go through the evolutionary stages of their ancestors. We do not develop and then lose gills: we develop generalized branchial structures that subsequently differentiate and specialize. In fish, some of those arches differentiate into gills, but those same arches in us develop into the thyroid gland and miscellaneous cartilagenous and bony structures of the throat and ears.
It’s better to regard embryos as following von Baerian developmental trajectories, proceeding from an initially generalized state to a more refined and specialized state over time. Limbs don’t reflect our ancient aquatic ancestry in utero, instead, limbs develop as initially blobby protrusions and digits develop by later sculpting of the tissue.
Sure, there is an ancestral core of genes and processes deep in metazoan development. But Davies seems to think they’re lurking, silenced, waiting to be switched on and turn the cell into a prehistoric monster. This is not correct. Those ancient genes are active, operating in common developmental processes all over the place. You want to see Proterozoic cell colonies? Look in the bone marrow, at the hematopoietic pathways that produce masses of blood cells. The genes he’s talking about are those involved in mitosis and cell adhesion. They aren’t dinosaurs of the genome that get resurrected by genetic accidents. but the engines of cell proliferation that lose the governors that regulate their controlled expression, and go into runaway mode in cancers.
But even if their model were correct (which is such a silly way to start a paragraph; it’s like announcing, “If the Flintstones were an accurate portrayal of stone age life…”), it doesn’t help. We don’t have tools to manipulate atavisms. We don’t see any genetic circuits that can be called atavistic. The Flintstones might have made record players out of rocks, but that doesn’t imply that the music recording industry can get valuable insights from the show.
Oh, well, I shouldn’t be so negative. I’m alienating possible sources of work here. I understand the physicists have encountered some peculiar results lately. Have they considered bringing in a biologist consultant with no prior knowledge of particle physics? I have some interesting ideas that might explain their anomalies, based on my casual understanding of phlogiston theory and ætheric humours.
In my talk at the Society for Developmental Biology, I encouraged more scientists to take advantage of the internet to share science with the public. Someone fell for it! Saori Haigo has started a blog, and she even explains why.
I’ve started this blog because I believe I have a social responsibility as a professional scientist to communicate science openly to the people. I will blog about what I think are important topics in the biological and biomedical sciences and explore the value, current issues, and realistic expectations of what we gain from doing research on that topic. In addition, I’ll explore how science is done, share with you why I think the research I’m working on is of interest and worth funding by taxpayers, give you a taste of what my daily activities entail, and share the latest cutting edge research published in science journals. All in layman’s terms, so you can follow too.
I hope through my posts you will come to appreciate the value of academic science and learn about a world which may seem ‘foreign’ to you. And also to learn something neat along the way. Enjoy!
So go browse already. It’s a brand new blog, but she’s already got some interesting stuff, including spinning eggs.
I am a gorgeous hunk of virile manhood. How do I know? I looked at my fingers.
Research has shown that men whose ring finger on their right hand is longer than their index finger are regarded as better looking by women, possibly because their faces are more symmetrical.
There is no link, however, between this finger length and how alluring women find a man’s voice or his body odour, the study found.
Guys, you may be looking at my picture on the sidebar and thinking there must be something wrong here…but no, I assure you, my right ring finger is distinctly longer than my right index finger, and I will waggle that in your face and tell you to ignore the schlubby, hairy, homely middle-aged guy attached to that hand — the fingers don’t lie.
Right now I know a lot of you fellows are staring at your hand, and some of you are noticing that you have a long index finger, a sure sign that you are a hideous beast, unlike me. And others have nice long ring fingers, and you get to join me in my club of attractive manly men, no matter what the rest of your body looks like. We’ll get together and make the ladies swoon.
Except, well…I’ve been looking at some of the data, and I’m distinctly unimpressed.
It’s not the idea that digit ratios vary, though: that looks to be well established, with observations first made in the 19th century that men have relatively longer ring fingers, while women have relatively longer index fingers. There does seem to be an entirely plausible (but small) side-effect of testosterone/estrogen on digit development. There is even some rather noisy looking data that suggests that we can use digit length ratios as a proxy for embryonic testosterone/estrogen exposure.
The problem, unfortunately, is that there seems to be a little industry of scientific palmists who are busily cross-correlating these digit ratios with just about anything, and I think they are drifting off into measuring random noise. It’s amazing what can get published in respectable journals, and subsequently get loads of attention from the press. Look at the methods for this study of attractiveness, for instance.
The team studied 49 Caucasian men aged between 18 and 33 years of age. They measured their finger ratio, got them to recite into a voice recorder, took a photograph of them with a neutral expression and got the non-smokers to wear cotton pads under their armpits for a day. The men were then evaluated for attractiveness, facial symmetry and masculinity by 84 women, and the results are published in the Proceedings of the Royal Society B.
Wow. Tiny little sample size, probably drawn from the usual limited population of college students, one straightforward objective measure (the digit ratio), and a subjective evaluation…and from this the authors try to infer a general rule. And sometimes they get a positive correlation with one thing, and no correlations with other things.
This is not only rather uninteresting, it’s also not very reliable. But it’s easy to do!
But wait, you might say, statistics is a powerful tool, and maybe those correlations are awesomely solid. This could be, so I went looking for papers that showed some of the data, so I could get a feel for how robust these effects were. Here, for example is a chart comparing number of the number of children to the ratio of index finger length to ring finger length (2D:4D ratio) for English men, where we’d expect low ratios to be a consequence of higher testosterone and therefore more virility, and for English women, where we’d expect a reversal, because fertile womanly women would of course have more estrogen. And it works!
Look at the slopes of those lines, and they actually fit the prediction. But then…look at the actual data points, and I think you can see that knowing the length of the fingers of any individual tells you absolutely nothing about how many children they have. You can guess why: it’s because there are a great many factors that influence how fecund you are, and small variations in hormones are only going to be a tiny component of such decisions.
You may also notice the outliers. Look at that man with most womanly hands of the entire group, having a 2D:4D ratio of 1.1 — he also has the second largest brood of the whole sample, with 5 kids. And the woman with man-hands with ratio somewhere around 0.87? Four kids.
It’s also a good thing that these data are collected in two separate graphs, because if you put the men and the women on the same chart, they’d overlap so much that you wouldn’t be able to tell them apart. While the sex difference may have been documented since the 19th century, it’s clearly not a big and obvious difference, and the overlap between the sexes is huge.
Or how about these data?
That’s the splat you get when you compare 2D:4D ratio in women against another classic magic number associated with attractiveness, the waist-hip ratio. A correlation emerges out of that mess, too, and it turns out that more estrogen exposure (as indirectly measured by looking at digit lengths) is correlated with relatively thicker waists. Sort of. I guess. Yeah, it’s statistics all right.
How these sorts of data are interpreted is to see them as suggesting the presence of sexually anatagonistic genes, that is, genes that respond to high testosterone with expression patterns that are beneficial to males, and genes that respond to high estrogen with expression that favorably biases morphology towards typically female variants. I can believe that such phenomena exist, and that doesn’t bother me in the slightest; what does, though, is this I’ve-got-a-hammer-so-everything-looks-like-a-nail approach, using an easily measured metric that is indirect and variable, and the neglect of the particular for the useless general. This is clearly a situation where testosterone/estrogen levels are only one relatively minor variable, and the more interesting factors would be allelic variations, genetic background, and social/cultural effects. But hey, we can measure fingers with calipers, easy, and then we can through questionnaires or easy, fast, noninvasive tests at a handy population, and look! Numbers! Must be science, then.
Except that we don’t really learn very much from it, other than that I’m really beautiful, despite what I actually look like.
Ferdenzi C,
Lemaître J-F,
Leongómez JD,
Craig Roberts SC (2011)
Digit ratio (2D:4D) predicts facial, but not voice or body odour, attractiveness in men.
Published online before print April 20, 2011, doi: 10.1098/rspb.2011.0544 Proc. R. Soc. B
Manning JT, Barley L, Walton J, Lewis-Jones DI, Trivers RL, Singh D, Thornhill R, Rohde P, Bereczkei T, Henzi P, Soler M, Szwed A. (2000) The 2nd:4th digit ratio, sexual dimorphism, population differences, and reproductive success. evidence for sexually antagonistic genes? Evol Hum Behav. 21(3):163-183.
