science literacy – bioliteracy

Misinformation in and about science.

originally published as https://facultyopinions.com/article/739916951 – July 2021

There have been many calls for improved “scientific literacy”. Scientific literacy has been defined in a number of, often ambiguous, ways (see National Academies of Sciences and Medicine, 2016 {1}). According to Krajcik & Sutherland (2010) {2} it is “the understanding of science content and scientific practices and the ability to use that knowledge”, which implies “the ability to critique the quality of evidence or validity of conclusions about science in various media, including newspapers, magazines, television, and the Internet”. But what types of critiques are we talking about, and how often is this ability to critique, and the scientific knowledge it rests on, explicitly emphasized in the courses non-science (or science) students take? As an example, highlighted by Sabine Hossenfelder (2020) {3}, are students introduced to the higher order reasoning and understanding of the scientific enterprise needed to dismiss a belief in a flat (or a ~6000 year old) Earth?

While the sources of scientific illiteracy are often ascribed to social media, religious beliefs, or economically or politically motivated distortions, West and Bergstrom point out how scientists and the scientific establishment (public relations departments and the occasional science writer) also play a role. They identify the problems arising from the fact that the scientific enterprise (and the people who work within it) act within “an attention economy” and “compete for eyeballs just as journalists do.” The authors provide a review of all of the factors that contribute to misinformation within the scientific literature and its media ramifications, including the contribution of “predatory publishers” and call for “better ways of detecting untrustworthy publishers.” At the same time, there are ingrained features of the scientific enterprise that serve to distort the relevance of published studies, these include not explicitly identifying the organism in which the studies are carried out, and so obscuring the possibility that they might not be relevant to humans (see Kolata, 2013 {4}). There are also systemic biases within the research community. Consider the observation, characterized by Pandey et al. (2014) {5} that studies of “important” genes, expressed in the nervous system, are skewed: the “top 5% of genes absorb 70% of the relevant literature” while “approximately 20% of genes have essentially no neuroscience literature”. What appears to be the “major distinguishing characteristic between these sets of genes is date of discovery, early discovery being associated with greater research momentum—a genomic bandwagon effect”, a version of the “Matthew effect” described by Merton (1968) {6}. In the context of the scientific community, various forms of visibility (including pedigree and publicity) are in play in funding decisions and career advancement. Not pointed out explicitly by West and Bergstrom is the impact of disciplinary experts who pontificate outside of their areas of expertise and speculate beyond what can be observed or rejected experimentally, including speculations on the existence of non-observable multiverses, the ubiquity of consciousness (Tononi & Koch, 2015 {7}), and the rejection of experimental tests as a necessary criterion of scientific speculation (see Loeb, 2018 {8}) spring to mind.

Many educational institutions demand that non-science students take introductory courses in one or more sciences in the name of cultivating “scientific literacy”. This is a policy that seems to me to be tragically misguided, and perhaps based more on institutional economics than student learning outcomes. Instead, a course on “how science works and how it can be distorted” would be more likely to move students close to the ability to “critique the quality of evidence or validity of conclusions about science”. Such a course could well be based on an extended consideration of the West and Bergstrom article, together with their recently published trade book “Calling bullshit: the art of skepticism in a data-driven world” (Bergstrom and West, 2021 {9}), which outlines many of the ways that information can be distorted. Courses that take this approach to developing a skeptical (and realistic) approach to understanding how the sciences work are mentioned, although what measures of learning outcomes have been used to assess their efficacy are not described.

literature cited

Science literacy: concepts, contexts, and consequencesCommittee on Science Literacy and Public Perception of Science, Board on Science Education, Division of Behavioral and Social Sciences and Education, National Academies of Sciences, Engineering, and Medicine.2016 10 14; PMID: 27854404
Supporting students in developing literacy in science. Krajcik JS, Sutherland LM.Science. 2010 Apr 23; 328(5977):456-459PMID: 20413490
Flat Earth “Science”: Wrong, but not Stupid. Hossenfelder S. BackRe(Action) blog, 2020, Aug 22 (accessed Jul 29, 2021)
Mice fall short as test subjects for humans’ deadly ills. Kolata G. New York Times, 2013, Feb 11 (accessed Jul 29, 2021)
Functionally enigmatic genes: a case study of the brain ignorome. Pandey AK, Lu L, Wang X, Homayouni R, Williams RW.PLoS ONE. 2014; 9(2):e88889PMID: 24523945
The Matthew Effect in Science: The reward and communication systems of science are considered.Merton RK.Science. 1968 Jan 5; 159:56-63 PMID: 17737466
Consciousness: here, there and everywhere? Tononi G, Koch C.Philos Trans R Soc Lond B Biol Sci. 2015 May 19; 370(1668)PMID: 25823865
Theoretical Physics Is Pointless without Experimental Tests. Loeb A. Scientific American blog, 2018, Aug 10 [ Blog piece] (accessed Jul 29, 2021)
Calling bullshit: the art of skepticism in a data-driven world.Bergstrom CT, West JD. Random House Trade Paperbacks, 2021ISBN: ‎ 978-0141987057

Visualizing and teaching evolution through synteny

Embracing the rationalist and empirically-based perspective of science is not easy. Modern science generates disconcerting ideas that can be difficult to accept and often upsetting to philosophical or religious views of what gives meaning to existence [link]. In the context of biological evolutionary mechanisms, the fact that variation is generated by random (stochastic) events, unpredictable at the level of the individual or within small populations, led to the rejection of Darwinian principles by many working scientists around the turn of the 20th century (see Bowler’s The Eclipse of Darwinism + link). Educational research studies, such as our own “Understanding randomness and its impact on student learning“, reinforce the fact that ideas involving stochastic processes relevant to evolutionary, as well as cellular and molecular, biology, are inherently difficult for people to accept (see also: Why being human makes evolution hard to understand). Yet there is no escape from the science-based conclusion that stochastic events provide the raw material upon which evolutionary mechanisms act, as well as playing a key role in a wide range of molecular and cellular level processes, including the origin of various diseases, particularly cancer [Cancer is partly caused by bad luck](1).

All of which leaves the critical question, at least for educators, of how to best teach students about evolutionary mechanisms and outcomes. The problem becomes all the more urgent given the anti-science posturing of politicians and public “intellectuals”, on both the right and the left, together with various overt and covert attacks on the integrity of science education, such as a new Florida law that lets “anyone in Florida challenge what’s taught in schools”.

Just to be clear, we are not looking for students to simply “believe” in the role of evolutionary processes in generating the diversity of life on Earth, but rather that they develop an understanding of how such processes work and how they make a wide range of observations scientifically intelligible. Of course the end result, unless you are prepared to abandon science altogether, is that you will find yourself forced to seriously consider the implications of inescapable scientific conclusions, no matter how weird and disconcerting they may be.

There are a number of educational strategies, in part depending upon one’s disciplinary perspective, on how to approach teaching evolutionary processes. Here I consider one, based on my background in cell and molecular biology. Genomicus is a web tool that “enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversely across different species, and chronologically along evolutionary time.” It is one of a number of web-based resources that make it possible to use the avalanche of DNA (gene and genomic) sequence data being generated by the scientific community. For example, the ExAC/Gnomad Browser enables one to examine genetic variation in over 60,000 unrelated people. Such tools supplement and extend the range of tools accessible through the U.S. National Library of Medicine / NIH / National Center for Biotechnology Information (NCBI) web portal (PubMed).

In the biofundamentals / coreBio course (with an evolving text available here), we originally used the observation that members of our subfamily of primates, the Haplorhini or dry nose primates, are, unlike most mammals, dependent on the presence of vitamin C (ascorbic acid) in their diet. Without vitamin C we develop scurvy, a potentially lethal condition. While there may be positive reasons for vitamin C dependence, in biofundamentals we present this observation in the context of small population size and a forgiving environment. A plausible scenario is that the ancestral Haplorhini population the lost the L-gulonolactone oxidase (GULO) gene (see OMIM) necessary for vitamin C synthesis. The remains of the GULO gene found in humans and other Haplorhini genomes is mutated and non-functional, resulting in our requirement for dietary vitamin C.

How, you might ask, can we be so sure? Because we can transfer a functional mouse GULO gene into human cells; the result is that vitamin C dependent human cells become vitamin C independent (see: Functional rescue of vitamin C synthesis deficiency in human cells). This is yet another experimental result, similar to the ability of bacteria to accurately decode a human insulin gene), that supports the explanatory power of an evolutionary perspective (2).

In an environment in which vitamin C is plentiful in a population’s diet, the mutational loss of the GULO gene would be benign, that is, not strongly selected against. In a small population, the stochastic effects of genetic drift can lead to the loss of genetic variants that are not strongly selected for. More to the point, once a gene’s function has been lost due to mutation, it is unlikely, although not impossible, that a subsequent mutation will lead to the repair of the gene. Why? Because there are many more ways to break a molecular machine, such as the GULO enzyme, but only a few ways to repair it. As the ancestor of the Haplorhini diverged from the ancestor of the vitamin C independent Strepsirrhini (wet-nose) group of primates, an event estimated to have occurred around 65 million years ago, its ancestors had to deal with their dietary dependence on vitamin C either by remaining within their original (vitamin C-rich) environment or by adjusting their diet to include an adequate source of vitamin C.

At this point we can start to use Genomicus to examine the results of evolutionary processes (see a YouTube video on using Genomicus)(3). In Genomicus a gene is indicated by a pointed box ; for simplicity all genes are drawn as if they are the same size (they are not); different genes get different colors and the direction of the box indicates the direction of RNA synthesis, the first stage of gene expression. Each horizontal line in the diagram below represents a segment of a chromosome from a particular species, while the blue lines to the left represent phylogenic (evolutionary) relationships. If we search for the GULO gene in the mouse, we find it and we discover that its orthologs (closely related genes) are found in a wide range of eukaryotes, that is, organisms whose cells have a nucleus (humans are eukaryotes).

We find a version of the GULO gene in single-celled eukaryotes, such as baker’s yeast, that appear to have diverged from other eukaryotes about ~1.500,000,000 years ago (1500 million years ago, abbreviated Mya). Among the mammalian genomes sequenced to date, the genes surrounding the GULO gene are (largely) the same, a situation known as synteny (mammals are estimated to have shared a common ancestor about 184 Mya). Since genes can move around in a genome without necessarily disrupting their normal function(s), a topic for another day, synteny between distinct organisms is assumed to reflect the organization of genes in their common ancestor. The synteny around the GULO gene, and the presence of a GULO gene in yeast and other distantly related organisms, suggests that the ability to synthesize vitamin C is a trait conserved from the earliest eukaryotic ancestors.
Now a careful examination of this map (↑) reveals the absence of humans (Homo sapiens) and other Haplorhini primates – Whoa!!! what gives? The explanation is, it turns out, rather simple. Because of mutation, presumably in their common ancestor, there is no functional GULO gene in Haplorhini primates. But the Haplorhini are related to the rest of the mammals, aren’t they? We can test this assumption (and circumvent the absence of a functional GULO gene) by exploiting synteny – we search for other genes present in the syntenic region (↓). What do we find? We find that this region, with the exception of GULO, is present and conserved in the Haplorhini: the syntenic region around the GULO gene lies on human chromosome 8 (highlighted by the red box); the black box indicates the GULO region in the mouse. Similar syntenic regions are found in the homologous (evolutionarily-related) chromosomes of other Haplorhini primates.

The end result of our Genomicus exercise is a set of molecular level observations, unknown to those who built the original anatomy-based classification scheme, that support the evolutionary relationship between the Haplorhini and more broadly among mammals. Based on these observations, we can make a number of unambiguous and readily testable predictions. A newly discovered Haplorhini primate would be predicted to share a similar syntenic region and to be missing a functional GULO gene, whereas a newly discovered Strepsirrhini primate (or any mammal that does not require dietary ascorbic acid) should have a functional GULO gene within this syntenic region. Similarly, we can explain the genomic similarities between those primates closely related to humans, such as the gorilla, gibbon, orangutan, and chimpanzee, as well as to make testable predictions about the genomic organization of extinct relatives, such as Neanderthals and Denisovians, using DNA recovered from fossils [link].

It remains to be seen how best to use these tools in a classroom context and whether having students use such tools influences their working understanding, and more generally, their acceptance of evolutionary mechanisms. That said, this is an approach that enables students to explore real data and to develop plausible and predictive explanations for a range of genomic discoveries, likely to be relevant both to understanding how humans came to be, and in answering pragmatic questions about the roles of specific mutations and allelic variations in behavior, anatomy, and disease susceptibility.

Some footnotes (figures reinserted 2 November 2020, with minor edits)

(1) Interested in a magnetic bumper image? visit: http://www.cafepress.com/bioliteracy

(2) An insight completely missing (unpredicted and unexplained) by any creationist / intelligent design approach to biology.

(3) Note, I have no connection that I know of with the Genomicus team, but I thank Tyler Square (now at UC Berkeley) for bringing it to my attention.

The pernicious effects of disrespecting the constraints of science

By Mike Klymkowsky

Recent political events and the proliferation of “fake news” and the apparent futility of fact checking in the public domain have led me to obsess about the role played by the public presentation of science. “Truth” can often trump reality, or perhaps better put, passionately held beliefs can overwhelm a circumspect worldview based on a critical and dispassionate analysis of empirically established facts and theories. Those driven by various apocalyptic visions of the world, whether religious or political, can easily overlook or trivialize evidence that contradicts their assumptions and conclusions. While historically there have been periods during which non-empirical presumptions are called into question, more often than not such periods have been short-lived. Some may claim that the search for absolute truth, truths significant enough to sacrifice the lives of others for, is restricted to the religious, they are sadly mistaken – political, often explicitly anti-religious movements are also susceptible, often with horrific consequences, think Nazism and communist-inspired apocalyptic purges. The history of eugenics and forced sterilization based on flawed genetic and ideological premises have similar roots.

Given the seductive nature of belief-based “Truth”, many turned to science as a bulwark against wishful and arational thinking. The evolving social and empirical (data-based) nature of the scientific enterprise, beginning with guesses as to how the world (or rather some small part of the world) works, then following the guess’s logical implications together with the process of testing those implications through experiment or observation, leading to the revision (or abandonment) of the original guess, moving it toward hypothesis and then, as it becomes more explanatory and accurately predictive, and as those predictions are confirmed, into a theory. So science is a dance between speculation and observation. In contrast to a free form dance, the dance of science is controlled by a number of rigid, and oppressive to some, constraints [see Feynman & Rothman 2020. How does Science Really work].

Perhaps surprisingly, this scientific enterprise has converged onto a small set of over-arching theories and universal laws that appear to explain much of what is observable, these include the theory of general relativity, quantum and atomic theory, the laws of thermodynamics, and the theory of evolution. With the noticeable exception of relativity and quantum mechanics, these conceptual frameworks appear to be compatible with one another. As an example, organisms, and behaviors such as consciousness, obey and are constrained by, well established and (apparently) universal physical and chemical rules.

A central constraint on scientific thinking is that what cannot in theory be known is not a suitable topic for scientific discussion. This leaves outside of the scope of science a number of interesting topics, ranging from what came before the “Big Bang” to the exact steps in the origin of life. In the latter case, the apparently inescapable conclusion that all terrestrial organisms share a complex “Last Universal Common Ancestor” (LUCA) makes theoretically unconfirmable speculations about pre-LUCA living systems outside of science. While we can generate evidence that the various building blocks of life can be produced abiogenically (a process begun with Wohler’s synthesis of urea) we can only speculate as to the systems that preceded LUCA.

Various pressures have led many who claim to speak scientifically (or to speak for science) to ignore the rules of the scientific enterprise – they often act as if their are no constraints, no boundaries to scientific speculation. Consider the implications of establishing “astrobiology” programs based on speculation (rather than observations) presented with various levels of certainty as to the ubiquity of life outside of Earth [the speculations of Francis Crick and Leslie Orgel on “directed panspermia”: and the psuedoscientific Drake equation come to mind, see Michael Crichton’s famous essay on Aliens and global warming]. Yet such public science pronouncements appear to ignore (or dismiss) the fact that we know, and can study, only one type of life (at the moment), the descendants of LUCA. They appear untroubled when breaking the rules and abandoning the discipline that has made science a powerful, but strictly constrained human activity.

Whether life is unique to Earth or not requires future explorations and discoveries that may (or given the technological hurdles involved, may not) occur. Similarly postulating theoretically unobservable alternative universes or the presence of some form of consciousness in inanimate objects [an unscientific speculation illustrated here] crosses a dividing line between belief for belief’s sake, and the scientific – it distorts and obscures the rules of the game, the rules that make the game worth playing [again, the Crichton article cited above makes this point]. A recent rather dramatic proposal from some in the physical-philosophical complex has been the claim that the rules of prediction and empirical confirmation (or rejection) are no longer valid – that we can abandon requiring scientific ideas to make observable predictions [see Ellis & Silk]. It is as if objective reality is no longer the benchmark against which scientific claims are made; that perhaps mathematical elegance (see Sabine Hossenfelder’s Losts in Math) or spiritual comfort are more important – and well they might be (more important) but they are outside of the limited domain of science. At the 2015 “Why Trust a Theory” meeting, the physicist Carlo Rovelli concluded “by pointing out that claiming that a theory is valid even though no experiment has confirmed it destroys the confidence that society has in science, and it also misleads young scientists into embracing sterile research programs.” [quote from Massimo’s Pigliucci’s Footnotes to Plato blog].

While the examples above are relatively egregious, it is worth noting that various pressures for glory, fame, and funding can to impact science more frequently – leading to claims that are less obviously non-scientific, but that bend (and often break) the scientific charter. Take, for example, claims about animal models of human diseases. Often the expediencies associated with research make the use of such animal models necessary and productive, but they remain a scientific compromise. While mice, rats, chimpanzees, and humans are related evolutionarily, they also carry distinct traits associated with each lineage’s evolutionary history, and the associated adaptive and non-adaptive processes and events associated with that history. A story from a few years back illustrates how the differences between the immune systems of mice and humans help explain why the search, in mice, for drugs to treat sepsis in humans was so relatively unsuccessful [Mice Fall Short as Test Subjects for Some of Humans’ Deadly Ills]. A similar type of situation occurs when studies in the mouse fail to explicitly acknowledge how genetic background influences experimental phenotypes [Effect of the genetic background on the phenotype of mouse mutations], as well as how details of experimental scenarios influence human relevance [Can Animal Models of Disease Reliably Inform Human Studies?].

Speculations that go beyond science (while hiding under the aegis of science – see any of a number of articles on quantum consciousness) – may seem just plain silly, but by abandoning the rules of science they erode the status of the scientific process. How, exactly, would one distinguish a conscious from an unconscious electron?

In science (again as pointed out by Crichton) we do not agree through consensus but through data and respect for critical analyzed empirical observations. The laws of thermodynamics, general relativity, the standard model of particle physics, and evolution theory are conceptual frameworks that we are forced (if we are scientifically honest) to accept. Moreover the implications of these scientific frameworks can be annoying to some; there is no possibility of a “zero waste” process that involves physical objects, no free lunch (perpetual motion machine), no efficient, intelligently-designed evolutionary process (just blind variation and differential reproduction), and no zipping around the galaxy. The apparent limitation of motion to the speed of light means that a “Star Wars” universe is impossible – happily, I would argue, given the number of genocidal events that appear to be associated with that fictional vision – just too many storm troopers for my taste.

Whether our models for the behavior of Earth’s climate or the human brain can be completely accurate (deterministic), given the roles of chaotic and stochastic events in these systems, remains to be demonstrated; until they are, there is plenty of room for conflicting interpretations and prescriptions. That atmospheric levels of greenhouse gases are increasing due to human activities is unarguable, what it implies for future climate is less clear, and what to do about it (a social, political, and economic discussion informed but not determined by scientific observations) is another.

As we discuss science, we must teach (and continually remind ourselves, even if we are working scientific practitioners) about the limits of the scientific enterprise. As science educators, one of our goals needs to be to help students develop an appreciation of the importance of an honest and critical attitude to observations and conclusions, a recognition of the limits of scientific pronouncements. We need to explicitly identify, acknowledge, and respect the constraints under which effective science works and be honest in labeling when we have left scientific statements, lest we begin to walk down the path of little lies that morph into larger ones. In contrast to politicians and other forms of religious and secular mystics, we should know better than to be seduced into abandoning scientific discipline, and all that that entails.

Minor update + figures reintroduced 20 October 2020

M.W. Klymkowsky web site: http://klymkowskylab.colorado.edu