Aggregative & clonal metazoans: a biofundamentalist perspective

21st Century DEVO-2  In the first post in this series [link], I introduced the observation that single celled organisms can change their behaviors, often in response to social signals.  They can respond to changing environments and can differentiate from one cellular state to the another. Differentiation involves changes in which sets of genes are expressed, which polypeptides and proteins are made [previous post], where the proteins end up within the cell, and which behaviors are displayed by the organism. Differentiation enables individuals to adapt to hostile conditions and to exploit various opportunities. 

The ability of individuals to cooperate with one another, through processes such as quorum sensing, enables them to tune their responses so that they are appropriate and useful. Social interactions also makes it possible for them to produce behaviors that would be difficult or impossible for isolated individuals.  Once individual organisms learn, evolutionarily, how to cooperate, new opportunities and challenges (cheaters) emerge. There are strategies that can enable an organism to adapt to a wider range of environments, or to become highly specialized to a specific environment,  through the production of increasingly complex behaviors.  As described previously, many of these cooperative strategies can be adopted by single celled organisms, but others require a level of multicellularity.  Multicellularity can be transient – a pragmatic response to specific conditions, or it can be (if we ignore the short time that gametes exist as single cells) permanent, allowing the organism to develop the range of specialized cells types needed to build large, macroscopic organisms with complex and coordinated behaviors. In appears that various forms of multicellularity have arisen independently in a range of lineages (Bonner, 1998; Knoll, 2011). We can divide multicellularity into two distinct types, aggregative and clonal – which we will discuss in turn (1).  Aggregative (transient) multicellularity:  Once organisms had developed quorum sensing, they can monitor the density of related organisms in their environment and turn or (or off) specific genes (or sets of genes, necessary to produce a specific behavior.  While there are many variants, one model for such  a behavior is  a genetic toggle switch, in which a particular gene (or genes) can be switched on or off in response to environmental signals acting as allosteric regulators of transcription factor proteins (see Gardner et al., 2000).  Here is an example of an activity (↓) that we will consider in class to assess our understanding of the molecular processes involved.

One outcome of such a signaling system is to provoke the directional migration of amoeba and their aggregation to form the transient multicellular “slug”.  Such behaviors has been observed  in a range of normally unicellular organisms (see Hillmann et al., 2018)(↓). The classic example is  the cellular slime mold Dictyostelium discoideum (Loomis, 2014).  Under normal conditions, these

unicellular amoeboid eukaryotes migrate, eating bacteria and such. In this state, the range of an individual’s movement is restricted to short distances.  However when conditions turn hostile, specifically a lack of necessary nitrogen compounds, there is a compelling reason to abandon one environment and migrate to another, more distant that a single-celled organism could reach. This is a behavior that depends upon the presence of a sufficient density (cells/unit volume) of cells that enables them to: 1) recognize one another’s presence (through quorum sensing), 2) find each other through directed (chemotactic) migration, and 3) form a multicellular slug that can go on to differentiate. Upon differentiation about 20% of the cells differentiate (and die), forming a stalk that lifts the other ~80% of the cells into the air.  These non-stalk cells (the survivors) differentiate into spore (resistant to drying out) cells that are released into the air where they can be carried to new locations, establishing new populations.  

The process of cellular differentiation in D. discoideum has been worked out in molecular detail and involves two distinct signaling systems: the secreted pre-starvation factor (PSF) protein and cyclic AMP (cAMP).  PSF is a quorum signaling protein that also serves to activate the cell aggregation and differentiation program (FIG. ↓)

If bacteria, that is food, are present, the activity of PSF is inhibited and  cells remain in their single cell state. The key regulator of downstream aggregation and differentiation is the cAMP-dependent protein kinase PKA.  In the unicellular state, PKA activity is inhibited by PufA.  As PSF increases, while food levels decrease, YakA activity increases, inactivating PufA, leading to increased PKA activity.  Active PKA induces the synthesis of two downstream proteins, adenylate cyclase (ACA) and the cAMP receptor (CAR1). ACA catalyzes cAMP synthesis, much of which is secreted from the cell as a signaling molecule. The membrane-bound CAR1 protein acts as a receptor for autocrine (on the cAMP secreting cell) and paracrine (on neighboring cells) signaling.  The binding of cAMP to CAR1 leads to further activation of PKA, increasing cAMP synthesis and secretion – a positive feed-back loop. As cAMP levels increase, downstream genes are activated (and inhibited) leading cells to migrate toward one another, their adhesion to form a slug.  Once the slug forms and migrates to an appropriate site, the process of differentiation (and death) leading to stalk and spore formation begins. The fates of the aggregated cells is determined stochastically, but social cheaters can arise. Mutations can lead to individuals that avoid becoming stalk cells.  In the long run, if all individuals were to become cheaters, it would be impossible to form a stalk, so the purpose of social cooperation would be impossible to achieve.  In the face of environmental variation, populations invaded by cheaters are more likely to become extinct.  For our purposes the various defenses against cheaters are best left to other courses (see here if interested Strassmann et al., 2000).  

Clonal (permanent) multicellularity:  The type of multicellularity that most developmental biology courses focus on is what is termed clonal multicellularity – the organism is a clone of an original cell, the zygote, a diploid cell produced by the fusion of sperm and egg, haploid cells formed through the process of meiosis (2).  It is during meiosis that most basic genetic processes occur, that is the recombination between maternal and paternal chromosomes leading to the shuffling of alleles along a chromosome, and the independent segregation of chromosomes to form haploid gametes, gametes that are genetically distinct from those present in either parent. Once the zygote forms, subsequent cell divisions involve mitosis, with only a subset of differentiated cells, the cells of the germ line, capable of entering meiosis.  

Non-germ line, that is somatic cells, grow and divide. They interact with one another directly and through various signaling processes to produce cells with distinct patterns of gene expression, and so differentiated behaviors.  A key difference from a unicellular organism, is that the cells will (largely) stay attached to one another, or to extracellular matrix materials secreted by themselves and their neighbors.  The result is ensembles of cells displaying different specializations and behaviors.  As such cellular colonies get larger, they face a number of physical constraints – for example, cells are open non-equilibrium systems, to maintain themselves and to grow and reproduce, they need to import matter and energy from the external world. Cells also produce a range of, often toxic, waste products that need to be removed.  As the cluster of zygote-derived cells grows larger, and includes more and more cells, some cells will become internal and so cut off from necessary resources. While diffusive processes are often adequate when a cell is bathed in an aqueous solution, they are inadequate for a cell in the interior of a large cell aggregate (3).  The limits of diffusive processes necessitate other strategies for resource delivery and waste removal; this includes the formation of tubular vascular systems (such as capillaries, arteries, veins) and contractile systems (hearts and such) to pump fluids through these vessels, as well as cells specialized to process and transport a range of nutrients (such as blood cells).  As organisms get larger, their movements require contractile machines (muscle, cartilage, tendons, bones, etc) driving tails, fins, legs, wings, etc. The coordination of such motile systems involves neurons, ganglia, and brains. There is also a need to establish barriers between the insides of an organism and the outside world (skin, pulmonary, and gastrointestinal linings) and the need to protect the interior environment from invading pathogens (the immune system).  The process of developing these various systems depends upon controlling patterns of cell growth, division, and specialization (consider the formation of an arm), as well as the controlled elimination of cells (apoptosis), important in morphogenesis (forming fingers from paddle-shaped appendages), the maturation of the immune system (eliminating cells that react against self), and the wiring up, and adaptation of the nervous system. Such changes are analogous to those involved in aggregative multicellularity.      

Origins of multicellularity:  While aggregative multicellularity involves an extension of quorum sensing and social cooperation between genetically distinct, but related individuals, we can wonder whether similar drivers are responsible for clonal multicellularity.  There are a number of imaginable adaptive (evolutionary) drivers but two spring to mind: a way to avoid predators by getting bigger than the predators and as a way to produce varied structures needed to exploit various ecological niches and life styles. An example of the first type of driver of multicellularity is offered by the studies of Boraas et al  (1998). They cultured the unicellular green alga Chlorella vulgaris, together with a unicellular predator, the phagotrophic flagellated protist Ochromonas vallescia. After less than 100 generations (cell divisions), they observed the appearance of multicellular, and presumable inedible (or at least less easily edible), forms. Once selected, this trait appears to be stable, such that “colonies retained the eight-celled form indefinitely in continuous culture”.  To my knowledge, the genetic basis for this multicellularity remains to be determined.  

Cell Differentiation:  One feature of simple colonial organisms is that when dissociated into individual cells, each cell is capable of regenerating a new organism. The presence of multiple (closely related) cells in a single colony opens up the possibility of social interactions; this is distinct from the case in aggregative multicellularity, where social cooperation came first. Social cooperation within a clonal metazoan means that most cells “give up” their ability to reproduce a new organism (a process involving meiosis). Such irreversible social interactions mark the transition from a colonial organism to a true multicellular organism. As social integration increases, cells can differentiate so as to perform increasingly specialized functions, functions incompatible with cell division. Think for a moment about a human neuron or skeletal muscle cell – in both cases, cell division is no longer possible (apparently). Nevertheless, the normal functioning of such cells enhances the reproductive success of the organism as a whole – a classic example of inclusive fitness (remember heterocysts?)  Modern techniques of single cell sequencing and data analysis have now been employed to map this process of cellular differentiation in increasingly great detail, observations that will inform our later discussions (see Briggs et al., 2018 and future posts). In contrast, the unregulated growth of a cancer cell is an example of an asocial behavior, an asocial behavior that is ultimately futile, except in those rare cases (four known at this point) in which a cancer cell can move from one organism to another (Ujvari et al., 2016).  

Unicellular affordances for multicellularity:  When considering the design of a developmental biology course, we are faced with the diversity of living organisms – the basic observation that Darwin, Wallace, their progenitors and disciplinary descendants set out to solve. After all there are many millions of different types of organisms; among the multicellular eukaryotes, there are six major group : the ascomycetes and basidiomycetes fungi, the florideophyte red algae, laminarialean brown algae, embryophytic land plants and animals

(Knoll, 2011 ↑).  Our focus will be on animals. “All members of Animalia are multicellular, and all are heterotrophs (i.e., they rely directly or indirectly on other organisms for their nourishment). Most ingest food and digest it in an internal cavity.” [Mayer link].  From a macroscopic perspective, most animals have (or had at one time during their development) an anterior to posterior, that is head to tail, axis. Those that can crawl, swim, walk, or fly typically have a dorsal-ventral or back to belly axis, and some have a left-right axis as well.  

But to be clear, a discussion of the various types of animals is well beyond the scope of any introductory course in developmental biology, in part because there are 35 (assuming no more are discovered) different “types” (phyla) of animals – nicely illustrated at this website [BBC: 35 types of animals, most of whom are really weird)].  So again, our primary focus will be on one group, the vertebrates – humans are members of this group.  We will also consider experimental insights derived from studies of various “model” systems, including organisms from another metazoan group, the  ecdysozoa (organisms that shed their outer layer as they grow bigger), a group that includes fruit flies and nematode worms. 

My goal will be to ignore most of the specialized terminology found in the scholarly literature, which can rapidly turn a biology course into a vocabulary lesson and that add little to understanding of basic processes relevant to a general understanding of developmental processes (and relevant to human biology, medicine, and biotechnology). This approach is made possible by the discovery that the basic processes associated with animal (and metazoan) development are conserved. In this light, no observation has been more impactful than the discovery that the nature and organization of the genes involved in specifying the head to tail axes of the fruit fly and vertebrates (such as the mouse and human) is extremely similar in terms of genomic organization and function (Lappin et al., 2006 ↓), an observation that we will return to repeatedly.  Such molecular similarities extend to cell-cell and cell-matrix adhesion systems, systems that release and respond to various signaling molecules, controlling cell behavior and gene expression, and reflects the evolutionary conservation and the common ancestry of all animals (Brunet and King, 2017; Knoll, 2011). 

What can we know about the common ancestor of the animals?  Early on in the history of comparative cellular anatomy, the striking structural similarities between  the feeding system of choanoflagellate protozoans, a motile (microtubule-based) flagellum a surrounded by a “collar”of microfilament-based microvilli) and a structurally similar organelle in a range of multicellular organisms led to the suggestion that choanoflagellates and animals shared a common ancestor.  The advent of genomic sequencing and analysis has only strengthened this hypothesis, namely that choanoflagellates and animals form a unified evolutionary clade, the ‘Choanozoa’  (see tree↑ above)(Brunet and King, 2017).  Moreover, “many genes required for animal multicellularity (e.g., tyrosine kinases, cadherins, integrins, and extracellular matrix domains) evolved before animal origins”.  The implications is that the Choanozoan ancestor was predisposed to exploit some of the early opportunities offered by clonal multicellularity. These pre-existing affordances, together with newly arising genes and proteins (Long et al., 2013) were exploited in multiple lineages in the generation of multicellular organisms (see Knoll, 2011).

Basically to understand what happened next, some ~600 million years ago or so, we will approach the various processes involved in the shaping of animal development.  Because all types of developmental processes, including the unicellular to colonial transition, involve changes in gene expression, we will begin with the factors involved in the regulation of gene expression.  


Footnotes:
1). Please excuse the inclusive plural, but it seems appropriate in the context of what I hope will be a highly interactive course.
2). I will explicitly ignore variants as (largely) distractions, better suited for more highly specialized courses.
3). We will return to this problem when (late in the course, I think) we will discuss the properties of induced pluripotent stem cell (iPSC) derived organoids.

Literature cited:
Bonner, J. T. (1998). The origins of multicellularity. Integrative Biology: Issues, News, and Reviews: Published in Association with The Society for Integrative and Comparative Biology 1, 27-36.

Boraas, M. E., Seale, D. B. and Boxhorn, J. E. (1998). Phagotrophy by a flagellate selects for colonial prey: a possible origin of multicellularity. Evolutionary Ecology 12, 153-164.

Briggs, J. A., Weinreb, C., Wagner, D. E., Megason, S., Peshkin, L., Kirschner, M. W. and Klein, A. M. (2018). The dynamics of gene expression in vertebrate embryogenesis at single-cell resolution. Science 360, eaar5780.

Brunet, T. and King, N. (2017). The origin of animal multicellularity and cell differentiation. Developmental cell 43, 124-140.

Gardner, T. S., Cantor, C. R. and Collins, J. J. (2000). Construction of a genetic toggle switch in Escherichia coli. Nature 403, 339-342.

Hillmann, F., Forbes, G., Novohradská, S., Ferling, I., Riege, K., Groth, M., Westermann, M., Marz, M., Spaller, T. and Winckler, T. (2018). Multiple roots of fruiting body formation in Amoebozoa. Genome biology and evolution 10, 591-606.

Knoll, A. H. (2011). The multiple origins of complex multicellularity. Annual Review of Earth and Planetary Sciences 39, 217-239.

Lappin, T. R., Grier, D. G., Thompson, A. and Halliday, H. L. (2006). HOX genes: seductive science, mysterious mechanisms. The Ulster medical journal 75, 23.

Long, M., VanKuren, N. W., Chen, S. and Vibranovski, M. D. (2013). New gene evolution: little did we know. Annual review of genetics 47, 307-333.

Loomis, W. F. (2014). Cell signaling during development of Dictyostelium. Developmental biology 391, 1-16.

Strassmann, J. E., Zhu, Y. and Queller, D. C. (2000). Altruism and social cheating in the social amoeba Dictyostelium discoideum. Nature 408, 965-967.

Ujvari, B., Gatenby, R. A. and Thomas, F. (2016). Transmissible cancers, are they more common than thought? Evolutionary applications 9, 633-634.

On teaching developmental biology in the 21st century: a biofundamentalist perspective

On teaching developmental biology and trying to decide where to start: differentiation

Having considered the content of courses in chemistry [1] and  biology [2, 3], and preparing to teach developmental biology for the first time, I find myself reflecting on how such courses might be better organized.  In my department, developmental biology (DEVO) has returned after a hiatus as the final capstone course in our required course sequence, and so offers an opportunity within which to examine what students have mastered as they head into their more specialized (personal) educational choices.  Rather than describe the design of the course that I will be teaching, since at this point I am not completely sure what will emerge, what I intend to do (in a series of posts) is to describe, topic by topic, the progression of key concepts, the observations upon which they are based, and the logic behind their inclusion.

Modern developmental biology emerged during the mid-1800s from comparative embryology [4] and was shaped by the new cell theory (the continuity of life and the fact that all organisms are composed of cells and their products) and the ability of cells to differentiate, that is, to adopt different structures and behaviors [5].  Evolutionary theory was also key.  The role of genetic variation based on mutations and selection, in the generation of divergent species from common ancestors, explained why a single, inter-connected Linnaean (hierarchical) classification system (the phylogenic tree of life →) of organisms was possible and suggested that developmental mechanisms were related to similar processes found in their various ancestors. 

So then, what exactly are the primary concepts behind developmental biology and how do they emerge from evolutionary, cell, and molecular biology?  The concept of “development” applies to any process characterized by directional changes over time.  The simplest such process would involve the progress from the end of one cell division event to the beginning of the next; cell division events provide a convenient benchmark.  In asexual species, the process is clonal, a single parent gives rise to a genetically identical (except for the occurrence of new mutations) offspring. Often there is little distinction between parent and offspring.  In sexual species, a dramatic and unambiguous benchmark involves the generation of a new and genetically distinct organism.  This “birth” event is marked by the fusion of two gametes (fertilization) to form a new diploid organism.  Typically gametes are produced by a complex cellular differentiation process (gametogenesis), ending with meiosis and the formation of haploid cells.  In multicellular organisms, it is often the case that a specific lineage of cells (which reproduce asexually), known as the germ line, produce the gametes.  The rest of the organism, the cells that do not produce gametes, is known as the soma, composed of somatic cells.   Cellular continuity remains, however, since gametes are living (albeit haploid) cells.  

It is common for the gametes that fuse to be of two different types, termed oocyte and sperm.  The larger, and generally immotile gamete type is called an oocyte and an individual that produces oocytes is termed female. The smaller, and generally motile gamete type is called a sperm; individuals that produces sperm are termed male. Where a single organism can produce both oocytes and sperm, either at the same time or sequentially, they are referred to as hermaphrodites (named after Greek Gods, the male Hermes and the female Aphrodite). Oocytes and sperm are specialized cells; their formation involves the differential expression of genes and the specific molecular mechanisms that generate the features characteristic of the two cell types.  The fusion of gametes, fertilization,  leads to a zygote, a diploid cell that (usually) develops into a new, sexually mature organism.    

An important feature of the process of fertilization is that it requires a level of social interaction, the two fusing cells (gametes) must recognize and fuse with one another.  The organisms that produce these gametes must cooperate; they need to produce gametes at the appropriate time and deliver them in such a way that they can find and recognize each other and avoid “inappropriate” interactions”.  The specificity of such interactions underlie the reproductive isolation that distinguishes one species from another.  The development of reproductive isolation emerges as an ancestral population of organisms diverges to form one or more new species.  As we will see, social interactions, and subsequent evolutionary effects, are common in the biological world.  

The cellular and molecular aspects of development involve the processes by which cells grow, replicate their genetic material (DNA replication), divide to form distinct parent-offspring or similar sibling cells, and may alter their morphology (shape), internal organization, motility, and other behaviors, such as the synthesis and secretion of various molecules, and how these cells respond to molecules released by other cells.  Developmental processes involve the expression and the control of all of these processes.

Essentially all changes in cellular behavior are associated with changes in the activities of biological molecules and the expression of genes, initiated in response to various external signaling events – fertilization itself is such a signal.  These signals set off a cascade of regulatory interactions, often leading to multiple “cell types”, specialized for specific functions (such as muscle contraction, neural and/or hormonal signaling, nutrient transport, processing, and synthesis,  etc.).  For specific parts of the organism, external or internal signals can result in a short term “adaptive” response (such as sweating or panting in response to increased internal body temperature), after which the system returns to its original state, or in the case of developing systems, to new states, characterized by stable changes in gene expression, cellular morphology, and behavior.    

Development in bacteria (and other unicellular organisms):  In most unicellular organisms, the cell division process is reasonably uneventful, the cells produced are similar to the original cell – but not always.  A well studied example is the bacterium Caulobacter crescentus (and related species) [link][link].  In cases such as this, the process of growth  leads to phenotypically different daughters.  While it makes no sense to talk about a beginning (given the continuity of life after the appearance of the last universal common ancestor or LUCA), we can start with a “swarmer” cell, characterized by the presence of a motile flagellum (a molecular machine driven by coupled chemical reactions – see past blogpost] that drives motility [figure modified from 6 ]. 

A swarmer will eventually settle down, loose the flagellum, and replace it with a specialized structure (a holdfast) designed to anchor the cell to a solid substrate.  As the organism grows, the holdfast develops a stalk that lifts the cell away from the substrate.  As growth continues, the end of the cell opposite the holdfast begins to differentiate (becomes different) from the holdfast end of the cell – it begins the process leading to the assembly of a new flagellar apparatus.  When reproduction (cell growth, DNA replication, and cell division) occurs, a swarmer cell is released and can swim away and colonize another area, or settle nearby.  The holdfast-anchored cell continues to grow, producing new swarmers.  This process is based on the inherent asymmetry of the system – the holdfast end of the cell is molecularly distinct from the flagellar end [see 7].

The process of swarmer cell formation in Caulobacter is an example of what we will term deterministic phenotypic switching.  Cells can also exploit molecular level noise (stochastic processes) that influence gene expression to generate phenotypic heterogeneity, different behaviors expressed by genetically identical cells within the same environment [see 8, 9].  Molecular noise arises from the random nature of molecular movements and the rather small (compared to macroscopic systems) numbers of most molecules within a cell.  Most cells contain one or two copies of any particular gene, and a similarly small number of molecular sequences involved in their regulation [10].  Which molecules are bound to which regulatory sequence, and for how long, is governed by inter-molecular surface interactions and thermally driven collisions, and is inherently noisy.  There are strategies that can suppress but not eliminate such noise [see 11].  As dramatically illustrated by Elowitz  and colleagues [8](), molecular level noise can produce cells with different phenotypes.  Similar processes are active in eukaryotes (including humans), and can lead to the expression of one of the two copies of a gene (mono-allelic expression) present in a diploid organism.  This can lead to effects such as haploinsufficiency and selective (evolutionary) lineage effects if the two alleles are not identical [12, 13]. Such phenotypic heterogeneity among what are often genetically identical cells is a topic that is rarely discussed (as far as I can discern) in introductory cell, molecular, or developmental biology courses [past blogpost].

The ability to switch phenotypes can be a valuable trait if an organism’s environment is subject to significant changes.  As an example, when the environment gets hostile, some bacterial cells transition from a rapidly dividing to a slow or non-dividing state.  Such “spores” can differentiate so as to render them highly resistant to dehydration and other stresses.  If changes in environment are very rapid, a population can protect itself by continually having some cells (stochastically) differentiating into spores, while others continue to divide rapidly. Only a few individuals (spores) need to survive a catastrophic environmental change to quickly re-establish the population.

Dying for others – social interactions between “unicellular” organisms:  Many students might not predict that one bacterial cell would “sacrifice” itself for the well being of others, but in fact there are a number of examples of this type of self-sacrificing behavior, known as programmed cell death, which is often a stochastic process.  An interesting example is provided by cellular specialization for photosynthesis or nitrogen fixation in cyanobacteria [see 9].  These two functions require mutually exclusive cellular environments to occur, in particular the molecular oxygen (O2) released by photosynthesis inhibits the process of nitrogen fixation.  Nevertheless, both are required for optimal growth.  The solution?  some cells differentiate into what are known as heterocysts, cells committed to nitrogen fixation ( a heterocyst in Anabaena spiroides, adapted from link), while most ”vegetative” cells continue with photosynthesis.  Heterocysts cannot divide, and eventually die – they sacrifice themselves for the benefit of their neighbors, the vegetative cells, cells that can reproduce.

The process by which the death of an individual can contribute resources that can be used to insure or enhance the survival and reproduction of surrounding individuals is an inherently social process, and is subject of social evolutionary mechanisms [14, 15][past blogpost].  Social behaviors can be selected for because the organism’s neighbors, the beneficiaries of their self-sacrifice are likely to be closely (clonally) related to themselves.  One result of the social behavior is, at the population level, an increase in one aspect of evolutionary fitness,  termed “inclusive fitness.”  

Such social behaviors can enable a subset of the population to survive various forms of environmental stress (see spore formation above).  An obvious environmental stress involves the impact of viral infection.  Recall that viruses are completely dependent upon the metabolic machinery of the infected cell to replicate. While there are a number of viral strategies, a common one is bacterial lysis – the virus replicates explosively, kills the infected cells, leading to the release of virus into the environment to infect others.  But, what if the infected cell kills itself BEFORE the virus replicates – the dying (self-sacrificing, altruistic) cell “kills” the virus (although viruses are not really alive) and stops the spread of the infection.  Typically such genetically programmed cell death responses are based on a simple two-part system, involving a long lived toxin and a short-lived anti-toxin.  When the cell is stressed, for example early during viral infection, the level of the anti-toxin can fall, leading to the activation of  the toxin. 

Other types of social behavior and community coordination (quorum effects):  Some types of behaviors only make sense when the density of organisms rises above a certain critical level.  For example,  it would make no sense for an Anabaena cell  to differentiate into a heterocyst (see above) if there are no vegetative cells nearby.  Similarly, there are processes in which a behavior of a single bacterial cell, such as the synthesis and secretion of a specific enzyme, a specific import or export machine,  or the construction of a complex, such as a DNA uptake machine, makes no sense in isolation – the secreted molecule will just diffuse away, and so be ineffective, the molecule to be imported (e.g. lactose) or exported (an antibiotic) may not be present, or there may be no free DNA to import.  However, as the concentration (organisms per volume) of bacteria increases, these behaviors can begin to make biological sense – there is DNA to eat or incorporate and the concentration of secreted enzyme can be high enough to degrade the target molecules (so they are inactivated or can be imported as food).   

So how does a bacterium determine whether it has neighbors or whether it wants to join a community of similar organisms?  After all, it does not have eyes to see. The process used is known as quorum sensing.  Each individual synthesizes and secretes a signaling molecule and a receptor protein whose activity is regulated by the binding of the signaling molecule.  Species specificity in signaling molecules and receptors insures that organisms of the same kind are talking to one another and not to other, distinct types of organisms that may be in the environment.   At low signaling molecule concentrations, such as those produced by a single bacterium in isolation, the receptor is not activated and the cell’s behavior remains unchanged.  However, as the concentration of bacteria increases, the concentration of the signal increases, leading to receptor activation.  Activation of the receptor can have a number of effects, including increased synthesis of the signal and other changes, such as movement in response to signals through regulation of flagellar and other motility systems, such a system can lead to the directed migration (aggregation) of cells [see 16].   

In addition to driving the synthesis of a common good (such as a useful extracellular molecule), social interactions can control processes such as  programmed cell death.  When the concentration of related neighbors is high, the programmed death of an individual can be beneficial, it can  lead to release of nutrients (common goods, including DNA molecules) that can be used by neighbors (relatives)[17, 18] – an increase in the probability of cell death in response to a quorum can increased in a way that increases inclusive fitness.  On the other hand,  if there are few related individuals in the neighborhood, programmed cell death “wastes” these resources, and so is likely to be suppressed (you might be able to generate a plausible mechanism that could control the probability of programmed cell death).     

As we mentioned previously with respect to spore formation, the generation of a certain percentage of “persisters” – individuals that withdraw from active growth and cell division, can enable a population to survive stressful situations, such as the presence of an antibiotic.  On the other hand, generating too many persisters may place the population at a reproductive disadvantage.  Once the antibiotic is gone, the persisters can return into active division. The ability of bacteria to generate persisters is a serious problem in treating people with infections, particularly those who stop taking their antibiotics too early [19].  

Of course, as in any social system, the presumption of cooperation (expending energy to synthesize the signal, sacrificing oneself for others) can open the system to cheaters [blogpost].  All such “altruistic” behaviors are vulnerable to cheaters.*  For example, a cheater that avoids programmed cell death (for example due to an inactivating mutation that effects the toxin molecule involved) will come to take over the population.  The downside, for the population, is that if cheaters take over,  the population is less likely to survive the environmental events that the social behavior was evolve to address.  In response to the realities of cheating, social organisms adopt various social-validation and policing systems [see 20 as an example]; we see this pattern of social cooperation, cheating, and social defense mechanism throughout the biological world. 

Follow-on posts:

footnotes:

* Such as people who fail to pay their taxes or disclose their tax returns.

literature cited: 

1. Cooper, M.M. and M.W. Klymkowsky, Chemistry, life, the universe, and everything: a new approach to general chemistry, and a model for curriculum reform. J. Chem. Educ. 2013. 90: 1116-1122 & Cooper, M. M., R. Stowe, O. Crandell and M. W. Klymkowsky. Organic Chemistry, Life, the Universe and Everything (OCLUE): A Transformed Organic Chemistry Curriculum. J. Chem. Educ. 2019. 96: 1858-1872.

2. Klymkowsky, M.W., Teaching without a textbook: strategies to focus learning on fundamental concepts and scientific process. CBE Life Sci Educ, 2007. 6: 190-3.

3. Klymkowsky, M.W., J.D. Rentsch, E. Begovic, and M.M. Cooper, The design and transformation of Biofundamentals: a non-survey introductory evolutionary and molecular biology course. LSE Cell Biol Edu, 2016. pii: ar70.

4. Arthur, W., The emerging conceptual framework of evolutionary developmental biology. Nature, 2002. 415:  757.

5. Wilson, E.B., The cell in development and heredity. 1940.

6. Jacobs‐Wagner, C., Regulatory proteins with a sense of direction: cell cycle signalling network in Caulobacter. Molecular microbiology, 2004. 51:7-13.

7. Hughes, V., C. Jiang, and Y. Brun, Caulobacter crescentus. Current biology: CB, 2012. 22:R507.

8. Elowitz, M.B., A.J. Levine, E.D. Siggia, and P.S. Swain, Stochastic gene expression in a single cell. Science, 2002. 297:1183-6.

9. Balázsi, G., A. van Oudenaarden, and J.J. Collins, Cellular decision making and biological noise: from microbes to mammals. Cell, 2011. 144: 910-925.

10. Fedoroff, N. and W. Fontana, Small numbers of big molecules. Science, 2002. 297:1129-1131.

11. Lestas, I., G. Vinnicombe, and J. Paulsson, Fundamental limits on the suppression of molecular fluctuations. Nature, 2010. 467:174-178.

12. Zakharova, I.S., A.I. Shevchenko, and S.M. Zakian, Monoallelic gene expression in mammals. Chromosoma, 2009. 118:279-290.

13. Deng, Q., D. Ramsköld, B. Reinius, and R. Sandberg, Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science, 2014. 343: 193-196.

14. West, S.A., A.S. Griffin, A. Gardner, and S.P. Diggle, Social evolution theory for microorganisms. Nature reviews microbiology, 2006. 4:597.

15. Bourke, A.F.G., Principles of Social Evolution. Oxford series in ecology and evolution. 2011, Oxford: Oxford University Press.

16. Park, S., P.M. Wolanin, E.A. Yuzbashyan, P. Silberzan, J.B. Stock, and R.H. Austin, Motion to form a quorum. Science, 2003. 301:188-188.

17. West, S.A., S.P. Diggle, A. Buckling, A. Gardner, and A.S. Griffin, The social lives of microbes. Annual Review of Ecology, Evolution, and Systematics, 2007: 53-77.

18. Durand, P.M. and G. Ramsey, The Nature of Programmed Cell Death. Biological Theory, 2018:  1-12.

19. Fisher, R.A., B. Gollan, and S. Helaine, Persistent bacterial infections and persister cells. Nature Reviews Microbiology, 2017. 15:453.

20. Queller, D.C., E. Ponte, S. Bozzaro, and J.E. Strassmann, Single-gene greenbeard effects in the social amoeba Dictyostelium discoideum. Science, 2003. 299: 105-106.

On teaching genetics, social evolution and understanding the origins of racism

Links between genetics and race crop up periodically in the popular press (link; link), but the real, substantive question, and the topic of a number of recent essays (see Saletan. 2018a. Stop Talking About Race and IQ) is whether the idea of “race” as commonly understood, and used by governments to categorize people (link), makes scientific sense.  More to the point, do biology educators have an unmet responsibility to modify and extend their materials and pedagogical approaches to address the non-scientific, often racist, implications of racial characterizations.  Such questions are complicated by a social geneticssecond factor, independent of whether the term race has any useful scientific purpose, namely to help students understand the biological (evolutionary) origins of racism itself, together with the stressors that lead to its periodic re-emergence as a socio-political factor. In times of social stress, reactions to strangers (others) identified by variations in skin color or overt religious or cultural signs (dress), can provoke hostility against those perceived to be members of a different social group.  As far as I can tell, few in the biology education community, which includes those involved in generating textbooks, organizing courses and curricula, or the design, delivery, and funding of various public science programs, including PBS’s NOVA, the science education efforts of HHMI and other private foundations, and programs such as Science Friday on public radio, directly address the roots of racism, roots associated with biological processes such as the origins and maintenance of multicellularity and other forms of social organization among organisms, involved in coordinating their activities and establishing defenses against social cheaters and processes such as cancer, in an organismic context (1).  These established defense mechanisms can, if not recognized and understood, morph into reflexive and unjustified intolerance, hostility toward, and persecution of various “distinguishable others.”  I will consider both questions, albeit briefly, here. 


Two factors have influenced my thinking about these questions.  The first involves the design of the biofundamentals text/course and its extension to include topics in genetics (2).  This involved thinking about what is commonly taught in genetics, what is critical for students to know going forward (and by implication what is not), and where materials on genetic processes best fit into a molecular biology curriculum (3).  While engaged in such navel gazing there came an email from Malcolm Campbell describing student responses to the introduction of a chapter section on race and racism in his textbook Integrating Concepts in Biology.  The various ideas of race, the origins of racism, and the periodic appearance of anti-immigrant, anti-religious and racist groups raise important questions – how best to clarify what is an undeniable observation, that different, isolated, sub-populations of a species can be distinguished from one another (see quote from Ernst Mayr’s 1994 “Typological versus Population thinking” ), from the deeper biological reality, that at the level of the individual these differences are meaningless. In what I think is an interesting way, the idea that people can be meaningfully categorized as different types of various platonic ideals (for example, as members of one race or the other) based on anatomical / linguistic differences between once distinct sub-populations of humans is similar to the dichotomy between common wisdom (e.g. that has influenced people’s working understanding of the motion of objects) and the counter-intuitive nature of empirically established scientific ideas (e.g. Newton’s laws and the implications of Einstein’s theory of general relativity).  What appears on the surface to be true but in fact is not.  In this specific case, there is a pressure toward what Mayr terms “typological” thinking, in which we class people into idealized (platonic) types or races ().   

As pointed out most dramatically, and repeatedly, by Mayr (1985; 1994; 2000), and supported by the underlying commonality of molecular biological mechanisms and the continuity of life, stretching back to the last universal common ancestor, there are only individuals who are members of various populations that have experienced various degrees of separation from one another.  In many cases, these populations have diverged and, through geographic, behavioral, and structure adaptations driven by natural, social, and sexual selection together with the effects of various events, some non-adaptive, such as bottlenecks, founder effects, and genetic drift, may eventually become reproductively isolated from one another, forming new species.  An understanding of evolutionary principles and molecular mechanisms transforms biology from a study of non-existent types to a study of populations with their origins in common, sharing a single root – the last universal common ancestor (LUCA).   Over the last ~200,000 years the movement of humans first within Africa and then across the planet  has been impressive ().  These movements have been accompanied by the fragmentation of human populations. Campbell and Tishkoff (2008) identified 13 distinct ancestral African populations while Busby et al (2016) recognized 48 sub-saharan population groups.  The fragmentation of the human population is being reversed (or rather rendered increasingly less informative) by the effects of migration and extensive intermingling ().   

    Ideas, such as race (and in a sense species), try to make sense of the diversity of the many different types of organisms we observe. They are based on a form of essentialist or typological thinking – thinking that different species and populations are completely different “kinds” of objects, rather than individuals in a population connected historically to all other living things. Race is a more pernicious version of this illusion, a pseudo-scientific, political and ideological idea that postulates that humans come  in distinct, non-overlapping types (quote  again, from Mayr).  Such a weird idea underlies various illogical and often contradictory legal “rules” by which a person’s “race” is determined.  

Given the reality of the individual and the unreality of race, racial profiling (see Satel,
2002) can lead to serious medical mistakes, as made clear in the essays by Acquaviva & Mintz (2010) “Are We Teaching Racial Profiling?”,  Yudell et al  (2016) “Taking Race out of Human Genetics”, and Donovan (2014) “The impact of the hidden curriculum”. 

The idea of race as a type fails to recognize the dynamics of the genome over time.  If possible (sadly not) a comparative analysis of the genome of a “living fossil”, such as modern day coelacanths and their ancestors (living more than 80 million years ago) would likely reveal dramatic changes in genomic DNA sequence.  In this light the fact that between 100 to 200 new mutations are introduced into the human genome per generation (see Dolgin 2009 Human mutation rate revealed) seems like a useful number to be widely appreciated by students, not to mention the general public. Similarly, the genomic/genetic differences between humans, our primate relatives, and other mammals and the mechanisms behind them (Levchenko et al., 2017)(blog link) would seem worth considering and explicitly incorporating into curricula on genetics and human evolution.  

While race may be meaningless, racism is not.  How to understand racism?  Is it some kind of political artifact, or does it arise from biological factors.  Here, I believe, we find a important omission in many biology courses, textbooks, and curricula – namely an introduction and meaningful discussion of social evolutionary mechanisms. Many is the molecular/cell biology curriculum that completely ignores such evolutionary processes. Yet, the organisms that are the primary focus of biological research (and who pay for such research, e.g. humans) are social organisms at two levels.  In multicellular organisms somatic cells, which specialize to form muscular, neural, circulatory and immune systems, bone and connective tissues, sacrifice their own inter-generational reproductive future to assist their germ line (sperm and/or eggs) relatives, the cells that give rise to the next generation of organisms, a form of inclusive fitness (Dugatkin, 2007).  Moreover, humans are social organisms, often sacrificing themselves, sharing their resources, and showing kindness to other members of their group. This social cooperation is threatened by cheaters of various types (POST LINK).  Unless these social cheaters are suppressed, by a range of mechanisms, and through processes of kin/group selection, multicellular organisms die and socially dysfunctional social populations are likely to die out.  Without the willingness to cooperate, and when necessary, self-sacrifice, social organization is impossible – no bee hives, no civilizations.  Imagine a human population composed solely of people who behave in a completely selfish manner, not honoring their promises or social obligations.  

A key to social interactions involves recognizing those who are, and who are not part of your social group.  A range of traits can serve as markers for social inclusion.  A plausible hypothesis is that the explicit importance of group membership and defined social interactions becomes more critical when a society, or a part of society, is under stress.  Within the context of social stratification, those in the less privileged groups may feel that the social contract has been broken or made a mockery of.  The feeling (apparent reality) that members of “elite” or excessively privileged sub-groups are not willing to make sacrifices for others serves as evidence that social bonds are being broken (4). Times of economic and social disruption (migrations and conquests) can lead to increased explicit recognition of both group and non-group identification.  The idea that outsiders (non-group members) threaten the group can feed racism, a justification for why non-group members should be treated differently from group members.  From this position it is a small (conceptual) jump to the conclusion that non-group members are somehow less worthy, less smart, less trustworthy, less human – different in type from members of the group – many of these same points are made in an op-ed piece by Judis. 2018. What the Left Misses About Nationalism.

That economic or climatic stresses can foster the growth of racist ideas is no new idea; consider the unequal effects of various disruptions likely to be associated with the spread of automation (quote from George Will ) and the impact of climate change on migrations of groups within and between countries (see Saletan 2018b: Why Immigration Opponents Should Worry About Climate Change) are likely to spur various forms of social unrest, whether revolution or racism, or both – responses that could be difficult to avoid or control.   

So back to the question of biology education – in this context understanding the ingrained responses of social creatures associated with social cohesion and integrity need to be explicitly presented. Similarly, variants of such mechanisms occur within multicellular organisms and how they work is critical to understanding how diseases such as cancer, one of the clearest forms of a cheater phenotype, are suppressed.  Social evolutionary mechanisms provide the basis for understanding a range of phenomena, and the ingrained effects of social selection may be seen as one of the roots of racism, or at the very least a contributing factor worth acknowledging explicitly.  

Thanks to Melanie Cooper and Paul Strode for comments. Minor edits 4 May 2019.

Footnotes:

  1. It is an interesting possibility whether the 1%, or rather the super 0.1% represent their own unique form of social parasite, leading periodically to various revolutions – although sadly, new social parasites appear to re-emerge quite quickly.
  2. A part of the CoreBIO-biofundamentals project 
  3. At this point it is worth noting that biofundamentals itself includes sections on social evolution, kin/group and sexual selection (see Klymkowsky et al., 2016; LibreText link). 
  4. One might be forgiven for thinking that rich and privileged folk who escape paying what is seen as their fair share of taxes, might be cast as social cheaters (parasites) who, rather than encouraging racism might lead to revolutionary thoughts and actions. 

Literature cited: 

Acquaviva & Mintz. (2010). Perspective: Are we teaching racial profiling? The dangers of subjective determinations of race and ethnicity in case presentations. Academic Medicine 85, 702-705.

Busby et  al. (2016). Admixture into and within sub-Saharan Africa. Elife 5, e15266.

Campbell & Tishkoff. (2008). African genetic diversity: implications for human demographic history, modern human origins, and complex disease mapping. Annu. Rev. Genomics Hum. Genet. 9, 403-433.

Donovan, B.M. (2014). Playing with fire? The impact of the hidden curriculum in school genetics on essentialist conceptions of race. Journal of Research in Science Teaching 51: 462-496.

Dugatkin, L. A. (2007). Inclusive fitness theory from Darwin to Hamilton. Genetics 176, 1375-1380.

Klymkowsky et al., (2016). The design and transformation of Biofundamentals: a non-survey introductory evolutionary and molecular biology course..” LSE Cell Biol Edu pii: ar70.

Levchenko et al., (2017). Human accelerated regions and other human-specific sequence variations in the context of evolution and their relevance for brain development. Genome biology and evolution 10, 166-188.

Mayr, E. (1985). The Growth of Biological Thought: Diversity, Evolution, and Inheritance. Cambridge, MA: Belknap Press of Harvard University Press.

Mayr, E. (1994). Typological versus population thinking. Conceptual issues in evolutionary biology, 157-160.

—- (2000). Darwin’s influence on modern thought. Scientific American 283, 78-83.

Satel, S. (2002). I am a racially profiling doctor. New York Times 5, 56-58.

Yudell et al., (2016). Taking race out of human genetics. Science 351, 564-565.

When is a gene product a protein when is it a polypeptide?

On the left is a negatively-stained electron micrograph of a membrane vesicle isolated from the electric ray Torpedo california, with a muscle-type nicotinic single acetylcholine receptor (AcChR) pointed out . To the right the structure of the AcChR determined to NN resolution using cryoelectron microscopy by Rahman, Teng, Worrell, Noviello, Lee, Karlin, Stowell & Hibbs (2020). “Structure of the native muscle-type nicotinic receptor and inhibition by snake venom toxins.”

As a new assistant professor (1), I was called upon to teach my department’s “Cell Biology” course. I found, and still find, the prospect challenging in part because I am not exactly sure which aspects of cell biology are important for students to know, both in the context of the major, as well as their lives and subsequent careers.  While it seems possible (at least to me) to lay out a coherent conceptual foundation for biology as a whole [see 1], cell biology can often appear to students as an un-unified hodge-podge of terms and disconnected cellular systems, topics too often experienced as a vocabulary lesson, rather than as a compelling narrative. As such, I am afraid that the typical cell biology course often re-enforces an all too common view of biology as a discipline, a view, while wrong in most possible ways, was summarized by the 19th/early 20th century physicist Ernest Rutherford as “All science is either physics or stamp collecting.”  A key motivator for the biofundamentals project [2] has been to explore how to best dispel this prejudice, and how to more effectively present to students a coherent narrative and the key foundational observations and ideas by which to scientifically consider living systems, by any measure the most complex systems in the Universe, systems shaped, but not determined by, physical chemical properties and constraints, together with the historical vagaries of evolutionary processes on an ever-changing Earth. 

Two types of information:  There is an underlying dichotomy within biological systems: there is the hereditary information encoded in the sequence of nucleotides along double-stranded DNA molecules (genes and chromosomes).  There is also the information inherent in the living system.  The information in DNA is meaningful only in the context of the living cell, a reaction system that has been running without interruption since the origin of life.  While these two systems are inextricably interconnected, there is a basic difference between them. Cellular systems are fragile, once dead there is no coming back.  In contrast the information in DNA can survive death – it can move from cell to cell in the process of horizontal gene transfer.  The Venter group has replaced the DNA of bacterial cells with synthetic genomes in an effort to define the minimal number of genes needed to support life, at least in a laboratory setting [see 3, 4].  In eukaryotes, cloning is carried out by replacing a cell’s DNA, with that of another cell (reference).  

Conflating protein synthesis and folding with assembly and function: Much of the information stored in a cell’s DNA is used to encode the sequence of various amino acid polymers (polypeptides).  While over-simplified [see 5], students are generally presented with the view that each gene encodes a particular protein through DNA-directed RNA synthesis (transcription) and RNA-directed polypeptide synthesis (translation).  As the newly synthesized polypeptide emerges from the ribosomal tunnel, it begins to fold, and is released into the cytoplasm or inserted into or through a cellular membrane, where it often interacts with one or more other polypeptides to form a protein  [see 6].  The assembled protein is either functional or becomes functional after association with various non-polypeptide co-factors or post-translational modifications.  It is the functional aspect of proteins that is critical, but too often their assembly dynamics are overlooked in the presentation of gene expression/protein synthesis, which is really a combination of distinct processes. 

Students are generally introduced to protein synthesis through the terms primary, secondary, tertiary, and quaternary structure, an approach that can be confusing since many (most) polypeptides are not proteins and many proteins are parts of complex molecular machines [here is the original biofundamentals web page on proteins + a short video][see Teaching without a Textbook]. Consider the nuclear pore complex, a molecular machine that mediates the movement of molecules into and out of the nucleus.  A nuclear pore is “composed of ∼500, mainly evolutionarily conserved, individual protein molecules that are collectively known as nucleoporins (Nups)” [7]. But what is the function of a particular NUP, particularly if it does not exist in significant numbers outside of a nuclear pore?  Is a nuclear pore one protein?  In contrast, the membrane bound, mitochondrial ATP synthase found in aerobic bacteria and eukaryotic mitochondria, is described as composed “of two functional domains, F1 and Fo. F1 comprises 5 different subunits (three α, three β, and one γ, δ and ε)” while “Fo contains subunits c, a, b, d, F6, OSCP and the accessory subunits e, f, g and A6L” [8].  Are these proteins or subunits? is the ATP synthase a protein or a protein complex?  

Such confusions arise, at least in part, from the primary-quaternary view of protein structure, since the same terms are applied, generally without clarifying distinction, to both polypeptides and proteins. These terms emerged historically. The purification of a protein was based on its activity, which can only be measured for an intact protein. The primary structure of  a polypeptide was based on the recognition that DNA-encoded amino acid polymers are unbranched, with a defined sequence of amino acid residues (see Sanger. The chemistry of insulin).  The idea of a polypeptide’s secondary structure was based on the “important constraint that all six atoms of the amide (or peptide) group, which joins each amino acid residue to the next in the protein chain, lie in a single plane” [9], which led Pauling, Corey and Branson [10] to recognized the α-helix and β-sheet, as common structural motifs.  When a protein is composed of a single polypeptide, the final folding pattern of the polypeptide, is referred to as its tertiary structure and is apparent in the first protein structure solved, that of myoglobin (↓), by Max Perutz and John Kendell. 

Myoglobin’s role in O2 transport depends upon a non-polypeptide (prosthetic) heme group. So far so good, a gene encodes a polypeptide and as it folds a polypeptide becomes a protein – nice and simple (2).  Complications arise from the observations that 1) many proteins are composed of multiple polypeptides, encoded for by one or more genes, and 2) some polypeptides are a part of different proteins.  Hemoglobin, the second protein whose structure was

determined, illustrates the point (←).  Hemoglobin is composed of four polypeptides encoded by distinct genes encoding α- and β-globin polypeptides.  These polypeptides are related in structure, function, and evolutionary origins to myoglobin, as well  as the cytoglobin and neuroglobin proteins (↓).  In

humans, there are a number of distinct α-like globin and β-like globin genes that are expressed in different hematopoetic tissues during development, so functional hemoglobin proteins can have a number of distinct (albeit similar) subunit compositions and distinct properties, such as their affinities for O2 [see 11].  

But the situation often gets more complicated.  Consider centrin-2, a eukaryotic Ca2+ binding polypeptide that plays roles in organizing microtubules, building cilia, DNA repair, and gene expression [see 12 and references therein].  So, is the centrin-2 polypeptide just a polypeptide, a protein, or a part of a number of other proteins?  As another example, consider the basic-helix-loop-helix family of transcription factors; these transcription factor proteins are typically homo- or hetero-dimeric; are these polypeptides proteins in their own right?  The activity of these transcription factors is regulated in part by which binding partners they contain. bHLH polypeptides also interact with the Id polypeptide (or is it a protein); Id lacks a DNA binding domain so when it forms a dimer with a bHLH polypeptide it inhibits DNA binding (↓).  So is a single bHLH polypeptide a protein or is the protein necessarily a dimer?  More to the point, does the current primary→quaternary view of protein structure help or hinder student understanding of the realities of biological systems?  A potentially interesting bio-education research question.

A recommendation or two:  While under no illusion that the complexities of polypeptide synthesis and protein assembly can be easily resolved – it is surely possible to present them in a more coherent, consistent, and accessible manner.  Here are a few suggestions that might provoke discussion.  Let us first recognize that, for those genes that encode polypeptides: i) they encode polypeptides rather than functional proteins (a reality confused by the term “quaternary structure”).  We might well distinguish a polypeptide from a protein based on the concentration of free monomeric polypeptide (gene product) within the cell.  Then we need to convey the reality to students that the assembly of a protein is no simple process, particularly within the crowded cytoplasm [13], a misconception supported by the simple secondary-tertiary structure perspective. While some proteins assemble on their own, many (most?) cannot.


As an example, consider the protein tubulin (↑). As noted by Nithianantham et al [14], “ Five conserved tubulin cofactors/chaperones and the Arl2 GTPase regulate α- and β-tubulin assembly into heterodimers” and the “tubulin cofactors TBCD, TBCE, and Arl2, which together assemble a GTP-hydrolyzing tubulin chaperone critical for the biogenesis, maintenance, and degradation of soluble αβ-tubulin.”  Without these various chaperones the tubulin protein cannot be formed.  Here the distinction between protein and multiprotein complex is clear, since tubulin protein exists in readily detectable levels within the cell, in contrast to the α- and β-tubulin polypeptides, which are found complexed to the TBCB and TBCA chaperone polypeptides. Of course the balance between tubulin and tubulin polymers (microtubules) is itself regulated by a number of factors. 

 The situation is even more complex when we come to the ribosome and other structures, such as the nuclear pore.  Woolford [15] estimates that “more than 350 protein and RNA molecules participate in yeast ribosome assembly, and many more in metazoa”; in addition to four ribsomal RNAs and ~80 polypeptides (often referred to as ribosomal proteins) that are synthesized in the cytoplasm and transported into the nucleus in association with various transport factors, these “assembly factors, including diverse RNA-binding proteins, endo- and exonucleases, RNA helicases, GTPases and ATPases. These assembly factors promote pre-rRNA folding and processing, remodeling of protein–protein and RNA–protein networks, nuclear export and quality control” [16].  While I suspect that some structural components of the ribosome and the nuclear pore may have functions as monomeric polypeptides, and so could be considered as proteins, at this point it is best (most accurate) to assume that they are polypeptides, components of proteins and larger, molecular machines (past post). 

We can, of course, continue to consider the roles of common folding motifs,  arising from the chemistry of the peptide bond and the environment within and around the assembling protein, in the context of protein structure [17, 18], The knottier problem is how to help students recognize how functional entities, proteins and molecular machines, together with the coupled reaction systems that drive them and the molecular interactions that regulate them, function. How mutations, alleleic variations, and various environmentally induced perturbations influence the behaviors of cells and organisms, and how they generate normal and pathogenic phenotypes. Such a view emphasizes the dynamics of the living state, and the complex flow of information out of DNA into networks of molecular machines and reaction systems. 


Acknowledgements
: Thanks to Michael Stowell for feedback and suggestions and Jon Van Blerkom for encouragement.  All remaining errors are mine. Post updated to include imagines in the right places (and to include the cryoEM structure of the AcChR + minor edits – 16 December 2020.

Footnotes:

  1. Recently emerged from the labs of Martin Raff and Lee Rubin – Martin is one of the founding authors of the transformative “molecular biology of the cell” textbook. 
  2. Or rather quite over-simplistic, as it ignore complexities arising from differential splicing, alternative promoters, and genes encoding non-polypeptide encoding RNAs. 

Literature cited (please excuse excessive self-citation – trying to avoid self-plagarism)

1. Klymkowsky, M.W., Thinking about the conceptual foundations of the biological sciences. CBE Life Science Education, 2010. 9: p. 405-7.

2. Klymkowsky, M.W., J.D. Rentsch, E. Begovic, and M.M. Cooper, The design and transformation of Biofundamentals: a non-survey introductory evolutionary and molecular biology course. LSE Cell Biol Edu, in press., 2016. pii: ar70.

3. Gibson, D.G., J.I. Glass, C. Lartigue, V.N. Noskov, R.-Y. Chuang, M.A. Algire, G.A. Benders, M.G. Montague, L. Ma, and M.M. Moodie, Creation of a bacterial cell controlled by a chemically synthesized genome. science, 2010. 329(5987): p. 52-56.

4. Hutchison, C.A., R.-Y. Chuang, V.N. Noskov, N. Assad-Garcia, T.J. Deerinck, M.H. Ellisman, J. Gill, K. Kannan, B.J. Karas, and L. Ma, Design and synthesis of a minimal bacterial genome. Science, 2016. 351(6280): p. aad6253.

5. Samandi, S., A.V. Roy, V. Delcourt, J.-F. Lucier, J. Gagnon, M.C. Beaudoin, B. Vanderperre, M.-A. Breton, J. Motard, and J.-F. Jacques, Deep transcriptome annotation enables the discovery and functional characterization of cryptic small proteins. Elife, 2017. 6.

6. Hartl, F.U., A. Bracher, and M. Hayer-Hartl, Molecular chaperones in protein folding and proteostasis. Nature, 2011. 475(7356): p. 324.

7. Kabachinski, G. and T.U. Schwartz, The nuclear pore complex–structure and function at a glance. J Cell Sci, 2015. 128(3): p. 423-429.

8. Jonckheere, A.I., J.A. Smeitink, and R.J. Rodenburg, Mitochondrial ATP synthase: architecture, function and pathology. Journal of inherited metabolic disease, 2012. 35(2): p. 211-225.

9. Eisenberg, D., The discovery of the α-helix and β-sheet, the principal structural features of proteins. Proceedings of the National Academy of Sciences, 2003. 100(20): p. 11207-11210.

10. Pauling, L., R.B. Corey, and H.R. Branson, The structure of proteins: two hydrogen-bonded helical configurations of the polypeptide chain. Proceedings of the National Academy of Sciences, 1951. 37(4): p. 205-211.

11. Hardison, R.C., Evolution of hemoglobin and its genes. Cold Spring Harbor perspectives in medicine, 2012. 2(12): p. a011627.

12. Shi, J., Y. Zhou, T. Vonderfecht, M. Winey, and M.W. Klymkowsky, Centrin-2 (Cetn2) mediated regulation of FGF/FGFR gene expression in Xenopus. Scientific Reports, 2015. 5:10283.

13. Luby-Phelps, K., The physical chemistry of cytoplasm and its influence on cell function: an update. Molecular biology of the cell, 2013. 24(17): p. 2593-2596.

14. Nithianantham, S., S. Le, E. Seto, W. Jia, J. Leary, K.D. Corbett, J.K. Moore, and J. Al-Bassam, Tubulin cofactors and Arl2 are cage-like chaperones that regulate the soluble αβ-tubulin pool for microtubule dynamics. Elife, 2015. 4.

15. Woolford, J., Assembly of ribosomes in eukaryotes. RNA, 2015. 21(4): p. 766-768.

16. Peña, C., E. Hurt, and V.G. Panse, Eukaryotic ribosome assembly, transport and quality control. Nature Structural and Molecular Biology, 2017. 24(9): p. 689.

17. Dobson, C.M., Protein folding and misfolding. Nature, 2003. 426(6968): p. 884.

18. Schaeffer, R.D. and V. Daggett, Protein folds and protein folding. Protein Engineering, Design & Selection, 2010. 24(1-2): p. 11-19.

Molecular machines and the place of physics in the biology curriculum

The other day, through no fault of my own, I found myself looking at the courses required by our molecular biology undergraduate degree program. I discovered a requirement for a 5 credit hour physics course, and a recommendation that this course be taken in the students’ senior year – a point in their studies when most have already completed their required biology courses.  Befuddlement struck me, what was the point of requiring an introductory physics course in the context of a molecular biology major?  Was this an example of time-travel (via wormholes or some other esoteric imagining) in which a physics course in the future impacts a students’ understanding of molecular biology in the past?  I was also struck by the possibility that requiring such a course in the students’ senior year would measurably impact their time to degree. 

In a search for clarity and possible enlightenment, I reflected back on my own experiences in an undergraduate biophysics degree program – as a practicing cell and molecular  biologist, I was somewhat confused. I could not put my finger on the purpose of our physics requirement, except perhaps the admirable goal of supporting physics graduate students. But then, after feverish reflections on the responsibilities of faculty in the design of the courses and curricula they prescribe for their students and the more general concepts of instructional (best) practice and malpractice, my mind calmed, perhaps because I was distracted by an article on Oxford Nanopore’s MinION (↓), a “portable real-time device for DNA and RNA sequencing”,a device that plugs into the USB port on one’s laptop!

Distracted from the potentially quixotic problem of how to achieve effective educational reform at the undergraduate level, I found myself driven on by an insatiable curiosity (or a deep-seated insecurity) to insure that I actually understood how this latest generation of DNA sequencers worked. This led me to a paper by Meni Wanunu (2012. Nanopores: A journey towards DNA sequencing)[1].  On reading the paper, I found myself returning to my original belief, yes, understanding physics is critical to developing a molecular-level understanding of how biological systems work, BUT it was just not the physics normally inflicted upon (required of) students [2]. Certainly this was no new idea.  Bruce Alberts had written on this topic a number of times, most dramatically in his 1989 paper “The cell as a collection of molecular machines” [3].  Rather sadly, and not withstanding much handwringing about the importance of expanding student interest in, and understanding of, STEM disciplines, not much of substance in this area has occurred. While (some minority of) physics courses may have adopted active engagement pedagogies (in the meaning of Hake [4]) most insist on teaching macroscopic physics, rather than to focus on, or even to consider, the molecular level physics relevant to biological systems, explicitly the physics of protein machines in a cellular (biological) context. Why sadly, because conventional, that is non-biologically relevant introductory physics and chemistry courses, all to often serve the role of a hazing ritual, driving many students out of biology-based careers [5], in part I suspect, because they often seem irrelevant to students’ interests in the workings of biological systems. (footnote 1)  

Nanopore’s sequencer and Wanunu’s article (footnote 2) got me thinking again about biological machines, of which there are a great number, ranging from pumps, propellers, and oars to  various types of transporters, molecular truckers that move chromosomes, membrane vesicles, and parts of cells with respect to one another, to DNA detanglers, protein unfolders, and molecular recyclers (↓). 

Nanopore’s sequencer works based on the fact that as a single strand of DNA (or RNA) moves through a narrow pore, the different bases (A,C,T,G) occlude the pore to different extents, allowing different numbers of ions, different amounts of current, to pass through the pore. These current differences can be detected, and allows for a nucleotide sequence to be “read” as the nucleic acid strand moves through the pore. Understanding the process involves understanding how molecules move, that is the physics of molecular collisions and energy transfer, how proteins and membranes allow and restrict ion movement, and the impact of chemical gradients and electrical fields across a membrane on molecular movements  – all physical concepts of widespread significance in biological systems (here is an example of where a better understanding of physics could be useful to biologists).  Such ideas can be extended to the more general questions of how molecules move within the cell, and the effects of molecular size and inter-molecular interactions within a concentrated solution of proteins, protein polymers, lipid membranes, and nucleic acids, such as described in Oliverira et al., (2016 Increased cytoplasmic viscosity hampers aggregate polar segregation in Escherichia coli)[6].  At the molecular level, the processes, while biased by electric fields (potentials) and concentration gradients, are stochastic (noisy). Understanding of stochastic processes is difficult for students [7], but critical to developing an appreciation of how such processes can lead to phenotypic  differences between cells with the same genotypes (previous post) and how such noisy processes are managed by the cell and within a multicellular organism.   

As path leads on to path, I found myself considering the (←) spear-chucking protein machine present in the pathogenic bacteria Vibrio cholerae; this molecular machine is used to inject toxins into neighbors that the bacterium happens to bump into (see Joshi et al., 2017. Rules of Engagement: The Type VI Secretion System in Vibrio cholerae)[8].  The system is complex and acts much like a spring-loaded and rather “inhumane” mouse trap.  This is one of a number of bacterial  type VI systems, and “has structural and functional homology to the T4 bacteriophage tail spike and tube” – the molecular machine that injects bacterial cells with the virus’s genetic material, its DNA.

Building the bacterium’s spear-based injection system is control by a social (quorum sensing) system, a way that unicellular organisms can monitor whether they are alone or living in an environment crowded with other organisms. During the process of assembly, potential energy, derived from various chemically coupled, thermodynamically favorable reactions, is stored in both type VI “spears” and the contractile (nucleic acid injecting) tails of the bacterial viruses (phage). Understanding the energetics of this process, exactly how coupling thermodynamically favorable chemical reactions, such as ATP hydrolysis, or physico-chemical reactions, such as the diffusion of ions down an electrochemical gradient, can be used to set these “mouse traps”, and where the energy goes when the traps are sprung is central to students’ understanding of these and a wide range of other molecular machines. 

Energy stored in such molecular machines during their assembly can be used to move the cell. As an example, another bacterial system generates contractile (type IV pili) filaments; the contraction of such a filament can allow “the bacterium to move 10,000 times its own body weight, which results in rapid movement” (see Berry & Belicic 2015. Exceptionally widespread nanomachines composed of type IV pilins: the prokaryotic Swiss Army knives)[9].  The contraction of such a filament has been found to be used to import DNA into the cell, an early step in the process of  horizontal gene transfer.  In other situations (other molecular machines) such protein filaments access thermodynamically favorable processes to rotate, acting like a propeller, driving cellular movement. 

During my biased random walk through the literature, I came across another, but molecularly distinct, machine used to import DNA into Vibrio (see Matthey & Blokesch 2016. The DNA-Uptake Process of Naturally Competent Vibrio cholerae)[10].

This molecular machine enables the bacterium to import DNA from the environment, released, perhaps, from a neighbor killed by its spear.  In this system (←), the double stranded DNA molecule is first transported through the bacterium’s outer membrane; the DNA’s two strands are then separated, and one strand passes through a channel protein through the inner (plasma) membrane, and into the cytoplasm, where it can interact with the bacterium’s  genomic DNA.

The value of introducing students to the idea of molecular machines is that it helps to demystify how biological systems work, how such machines carry out specific functions, whether moving the cell or recognizing and repairing damaged DNA.  If physics matters in biological curriculum, it matters for this reason – it establishes a core premise of biology, namely that organisms are not driven by “vital” forces, but by prosaic physiochemical ones.  At the same time, the molecular mechanisms behind evolution, such as mutation, gene duplication,  and genomic reorganization provide the means by which new structures emerge from pre-existing ones, yet many is the molecular biology degree program that does not include an introduction to evolutionary mechanisms in its required course sequence – imagine that, requiring physics but not evolution? (see [11]).

One final point regarding requiring students to take a biologically relevant physics course early in their degree program is that it can be used to reinforce what I think is a critical and often misunderstood point. While biological systems rely on molecular machines, we (and by we I mean all organisms) are NOT machines, no matter what physicists might postulate -see We Are All Machines That Think.  We are something different and distinct. Our behaviors and our feelings, whether ultimately understandable or not, emerge from the interaction of genetically encoded, stochastically driven non-equilibrium systems, modified through evolutionary, environmental, social, and a range of unpredictable events occurring in an uninterrupted, and basically undirected fashion for ~3.5 billion years.  While we are constrained, we are more, in some weird and probably ultimately incomprehensible way.

Footnotes:

[1]  A discussion with Melanie Cooper on what chemistry is relevant to a life science major was a critical driver in our collaboration to develop the chemistry, life, the universe, and everything (CLUE) chemistry curriculum.  

[2]  Together with my own efforts in designing the biofundamentals introductory biology curriculum. 

literature cited

1. Wanunu, M., Nanopores: A journey towards DNA sequencing. Physics of life reviews, 2012. 9(2): p. 125-158.

2. Klymkowsky, M.W. Physics for (molecular) biology students. 2014  [cited 2014; Available from: http://www.aps.org/units/fed/newsletters/fall2014/molecular.cfm.

3. Alberts, B., The cell as a collection of protein machines: preparing the next generation of molecular biologists. Cell, 1998. 92(3): p. 291-294.

4. Hake, R.R., Interactive-engagement versus traditional methods: a six-thousand-student survey of mechanics test data for introductory physics courses. Am. J. Physics, 1998. 66: p. 64-74.

5. Mervis, J., Weed-out courses hamper diversity. Science, 2011. 334(6061): p. 1333-1333.

6. Oliveira, S., R. Neeli‐Venkata, N.S. Goncalves, J.A. Santinha, L. Martins, H. Tran, J. Mäkelä, A. Gupta, M. Barandas, and A. Häkkinen, Increased cytoplasm viscosity hampers aggregate polar segregation in Escherichia coli. Molecular microbiology, 2016. 99(4): p. 686-699.

7. Garvin-Doxas, K. and M.W. Klymkowsky, Understanding Randomness and its impact on Student Learning: Lessons from the Biology Concept Inventory (BCI). Life Science Education, 2008. 7: p. 227-233.

8. Joshi, A., B. Kostiuk, A. Rogers, J. Teschler, S. Pukatzki, and F.H. Yildiz, Rules of engagement: the type VI secretion system in Vibrio cholerae. Trends in microbiology, 2017. 25(4): p. 267-279.

9. Berry, J.-L. and V. Pelicic, Exceptionally widespread nanomachines composed of type IV pilins: the prokaryotic Swiss Army knives. FEMS microbiology reviews, 2014. 39(1): p. 134-154.

10. Matthey, N. and M. Blokesch, The DNA-uptake process of naturally competent Vibrio cholerae. Trends in microbiology, 2016. 24(2): p. 98-110.

11. Pallen, M.J. and N.J. Matzke, From The Origin of Species to the origin of bacterial flagella. Nat Rev Microbiol, 2006. 4(10): p. 784-90.

Is a little science a dangerous thing?

Is the popularization of science encouraging a growing disrespect for scientific expertise? 
Do we need to reform science education so that students are better able to detect scientific BS? 

It is common wisdom that popularizing science by exposing the public to scientific ideas is an unalloyed good,  bringing benefits to both those exposed and to society at large. Many such efforts are engaging and entertaining, often taking the form of compelling images with quick cuts between excited sound bites from a range of “experts.” A number of science-centered programs, such PBS’s NOVA series, are particularly adept and/or addicted to this style. Such presentations introduce viewers to natural wonders, and often provide scientific-sounding, albeit often superficial and incomplete, explanations – they appeal to the gee-whiz and inspirational, with “mind-blowing” descriptions of how old, large, and weird the natural world appears to be. But there are darker sides to such efforts. Here I focus on one, the idea that a rigorous, realistic understanding of the scientific enterprise and its conclusions, is easy to achieve, a presumption that leads to unrealistic science education standards, and the inability to judge when scientific pronouncements are distorted or unsupported, as well as anti-scientific personal and public policy positions.That accurate thinking about scientific topics is easy to achieve is an unspoken assumption that informs much of our educational, entertainment, and scientific research system. This idea is captured in the recent NYT best seller “Astrophysics for people in a hurry” – an oxymoronic presumption. Is it possible for people “in a hurry” to seriously consider the observations and logic behind the conclusions of modern astrophysics? Can they understand the strengths and weaknesses of those conclusions? Is a superficial familiarity with the words used the same as understanding their meaning and possible significance? Is acceptance understanding?  Does such a cavalier attitude to science encourage unrealistic conclusions about how science works and what is known with certainty versus what remains speculation?  Are the conclusions of modern science actually easy to grasp?
The idea that introducing children to science will lead to an accurate grasp the underlying concepts involved, their appropriate application, and their limitations is not well supported [1]; often students leave formal education with a fragile and inaccurate understanding – a lesson made explicit in Matt Schneps and Phil Sadler’s Private Universe videos. The feeling that one understands a topic, that science is in some sense easy, undermines respect for those who actually do understand a topic, a situation discussed in detail in Tom Nichols “The Death of Expertise.” Under-estimating how hard it can be to accurately understand a scientific topic can lead to unrealistic science standards in schools, and often the trivialization of science education into recognizing words rather than understanding the concepts they are meant to convey.

The fact is, scientific thinking about most topics is difficult to achieve and maintain – that is what editors, reviewers, and other scientists, who attempt to test and extend the observations of others, are for – together they keep science real and honest. Until an observation has been repeated or confirmed by others, it can best be regarded as an interesting possibility, rather than a scientifically established fact.  Moreover, until a plausible mechanism explaining the observation has been established, it remains a serious possibility that the entire phenomena will vanish, more or less quietly (think cold fusion). The disappearing physiological effects of “power posing” comes to mind. Nevertheless the incentives to support even disproven results can be formidable, particularly when there is money to be made and egos on the line.

While power-posing might be helpful to some, even though physiologically useless, there are more dangerous pseudo-scientific scams out there. The gullible may buy into “raw water” (see: Raw water: promises health, delivers diarrhea) but the persistent, and in some groups growing, anti-vaccination movement continues to cause real damage to children (see Thousands of cheerleaders exposed to mumps).  One can ask oneself, why haven’t professional science groups, such as the American Association for the Advancement of Science (AAAS), not called for a boycott of NETFLIX, given that NETFLIX continues to distribute the anti-scientific, anti-vaccination program VAXXED [2]?  And how do Oprah Winfrey and Donald Trump  [link: Oprah Spreads Pseudoscience and Trump and the anti-vaccine movement] avoid universal ridicule for giving credence to ignorant non-sense, and for disparaging the hard fought expertise of the biomedical community?  A failure to accept well established expertise goes along way to understanding the situation. Instead of an appreciation for what we do and do not know about the causes of autism (see: Genetics and Autism Risk & Autism and infection), there are desperate parents who turn to a range of “therapies” promoted by anti-experts. The tragic case of parents trying to cure autism by forcing children to drink bleach (see link) illustrates the seriousness of the situation.

So why do a large percentage of the public ignore the conclusions of disciplinary experts?  I would argue that an important driver is the way that science is taught and popularized [3]. Beyond the obvious fact that a range of politicians and capitalists (in both the West and the East) actively distain expertise that does not support their ideological or pecuniary positions [4], I would claim that the way we teach science, often focussing on facts rather than processes, largely ignoring the historical progression by which knowledge is established, and the various forms of critical analyses to which scientific conclusions are subjected to, combines with the way science is popularized, erodes respect for disciplinary expertise. Often our education systems fail to convey how difficult it is to attain real disciplinary expertise, in particular the ability to clearly articulate where ideas and conclusions come from and what they do and do not imply. Such expertise is more than a degree, it is a record of rigorous and productive study and useful contributions, and a critical and objective state of mind. Science standards are often heavy on facts, and weak on critical analyses of those ideas and observations that are relevant to a particular process. As Carl Sagan might say, we have failed to train students on how to critically evaluate claims, how to detect baloney (or BS in less polite terms)[5].

In the area of popularizing scientific ideas, we have allowed hype and over-simplification to capture the flag. To quote from a article by David Berlinski [link: Godzooks], we are continuously bombarded with a range of pronouncements about new scientific observations or conclusions and there is often a “willingness to believe what some scientists say without wondering whether what they say is true”, or even what it actually means.  No longer is the in-depth, and often difficult and tentative explanation conveyed, rather the focus is on the flashy conclusion (independent of its plausibility). Self proclaimed experts pontificate on topics that are often well beyond their areas of training and demonstrated proficiency – many is the physicist who speaks not only about the completely speculative multiverse, but on free will and ethical beliefs. Complex and often irreconcilable conflicts between organisms, such as those between mother and fetus (see: War in the womb), male and female (in sexually dimorphic species), and individual liberties and social order, are ignored instead of explicitly recognized, and their origins understood. At the same time, there are real pressures acting on scientific researchers (and the institutions they work for) and the purveyors of news to exaggerate the significance and broader implications of their “stories” so as to acquire grants, academic and personal prestige, and clicks.  Such distortions serve to erode respect for scientific expertise (and objectivity).

So where are the scientific referees, the individuals that are tasked to enforce the rules of the game; to call a player out of bounds when they leave the playing field (their area of expertise) or to call a foul when rules are broken or bent, such as the fabrication, misreporting, suppression, or over-interpretation of data, as in the case of the anti-vaccinator Wakefield. Who is responsible for maintaining the integrity of the game?  Pointing out the fact that many alternative medicine advocates are talking meaningless blather (see: On skepticism & pseudo-profundity)? Where are the referees who can show these charlatans the “red card” and eject them from the game?

Clearly there are no such referees. Instead it is necessary to train as large a percentage of the population as possible to be their own science referees – that is, to understand how science works, and to identify baloney when it is slung at them. When a science popularizer, whether for well meaning or self-serving reasons, steps beyond their expertise, we need to call them out of
bounds!  And when scientists run up against the constraints of the scientific process, as appears to occur periodically with theoretical physicists, and the occasional neuroscientist (see: Feuding physicists and The Soul of Science) we need to recognize the foul committed.  If our educational system could help develop in students a better understanding of the rules of the scientific game, and why these rules are essential to scientific progress, perhaps we can help re-establish both an appreciation of rigorous scientific expertise, as well as a respect for what is that scientists struggle to do.



Footnotes and references:

  1. And is it clearly understood that they have nothing to say as to what is right or wrong.
  2.  Similarly, many PBS stations broadcast pseudoscientific infomercials: for example see Shame on PBS, Brain Scam, and the Deepak Chopra’s anti-scientific Brain, Mind, Body, Connection, currently playing on my local PBS station. Holocaust deniers and slavery apologists are confronted much more aggressively.
  3.  As an example, the idea that new neurons are “born” in the adult hippocampus, up to now established orthodoxy, has recently been called into question: see Study Finds No Neurogenesis in Adult Humans’ Hippocampi
  4.  Here is a particular disturbing example: By rewriting history, Hindu nationalists lay claim to India
  5. Pennycook, G., J. A. Cheyne, N. Barr, D. J. Koehler and J. A. Fugelsang (2015). “On the reception and detection of pseudo-profound bullshit.” Judgment and Decision Making 10(6): 549.

Humanized mice & porcinized people

mouse and pig

Updates:  12 January 2022

7 December 2020: US FDA declares genetically modified pork ‘safe to eat

A practical benefit, from a scientific and medical perspective, of the evolutionary unity of life (link) are the molecular and cellular similarities between different types of organisms. Even though humans and bacteria diverged more than 2 billion years ago (give or take), the molecular level conservation of key systems makes it possible for human insulin to be synthesized in and secreted by bacteria and pig-derived heart valves to be used to replace defective human heart valves (see link). Similarly, while mice, pigs, and people are clearly different from one another in important ways they have, essentially, all of the same body parts. Such underlying similarities raise interesting experimental and therapeutic possibilities.

A (now) classic way to study the phenotypic effects of human-specific versions of genes is to introduce these changes into a model organism, such as a mouse (for a review of human brain-specific human genes – see link).  A example of such a study involves the gene that encodes the protein foxp2, a protein involved in the regulation of gene expression (a transcription factor). The human foxp2  protein differs from the foxp2 protein in other primates at two positions; foxP2 evolution these two amio acid changes alter the activity of the human protein, that is the ensemble of genes that it regulates. That foxp2 has an important role in humans was revealed through studies of individuals in a family that displayed a severe language disorder linked to a mutation that disrupts the function of the foxp2 protein. Individuals carrying this mutant  foxp2 allele display speech apraxia, a “severe impairment in the selection and sequencing of fine oral and facial movements, the ability to break up words into their constituent phonemes, and the production and comprehension of word inflections and syntax” (cited in Bae et al, 2015).  Male mice that carry this foxp2 mutation display changes in the “song” that they sing to female mice (1), while mice carrying a humanized form of foxp2 display changes in “dopamine levels, dendrite morphology, gene expression and synaptic plasticity” in a subset of CNS neurons (2).  While there are many differences between mice and humans, such studies suggest that changes in foxp2 played a role in human evolution, and human speech in particular.

Another way to study the role of human genes using mouse as a model system is to generate what are known as chimeras, named after the creature in Greek mythology composed of parts of multiple organisms.  A couple of years ago, Goldman and colleagues (3) reported that human glial progenitor cells could, when introduced into immune-compromised mice (to circumvent tissue rejection), displaced the mouse’s own glia, replacing them with human glia cells.iPSC transplant Glial cells are the major non-neuronal component of the central nervous system. Once thought of as passive “support” cells, it is now clear that the two major types of glia, known as astrocytes and oligodendrocytes, play a number of important roles in neural functioning [back track post].  In their early studies, they found that the neurological defects associated with the shaker mutation, a mutation that disrupts the normal behavior of oligodendrocytes, could be rescued by the implantation of normal human glial progenitor cells (hGPCs)(4).  Such studies confirmed what was already known, that the shaker mutation disrupts the normal function of myelin, the insulating structure around axons that dramatically speeds the rate at which neuronal signals (action potentials) move down the axons and activate the links between neurons (synapses). In the central nervous system, myelin is produced by oligodendrocytes as they ensheath neuronal axons.  Human oligodendrocytes derived from hGPCs displaced the mouse’s mutation carrying oligodendrocytes and rescued the shaker mouse’s mutation-associated neurological defect.

golgi staining- diagramSubsequently, Goldman and associates used a variant of this approach to introduce hGPCs (derived from human embryonic stem cells) carrying either a normal or mutant version of the  Huntingtin protein, a protein associated with the severe neural disease Huntington’s chorea (OMIM: 143100)(5).  Their studies strongly support a model that locates defects associated with human Huntington’s disease to defects in glia.  This same research group has generated hGPCs from patient-derived, induced pluripotent stem cells (patient-derived HiPSCs). In this case, the patients had been diagnosed with childhood-onset schizophrenia (SCZ) [link](6).  Skin biopsies were taken from both normal and children diagnosed with SCZ; fibroblasts were isolated, and reprogrammed to form human iPSCs. These iPSCs were treated so that they formed hGPCs that were then injected into mice to generate chimeric (human glial/mouse neuronal) animals. The authors reported systematic differences in the effects of control and SCZ-derived hGPCs; “SCZ glial mice showed reduced prepulse inhibition and abnormal behavior, including excessive anxiety, antisocial traits, and disturbed sleep”, a result that suggests that defects in glial behavior underlie some aspects of the human SCZ phenotype.

The use of human glia chimeric mice provides a powerful research tool for examining the molecular and cellular bases for a subset of human neurological disorders.  Does it raise a question of making mice more human?  Not for me, but perhaps I do not appreciate the more subtle philosophical and ethical issues involved. The mice are still clearly mice, most of their nervous systems are composed of mouse cells, and the overall morphology, size, composition, and organization of their central nervous systems are mouse-derived and mouse-like. The situation becomes rather more complex and potentially therapeutically useful when one talks about generating different types of chimeric animals or of using newly developed genetic engineering tools (the CRISPR CAS9 system found in prokaryotes), that greatly simplify and improve the specificity of the targeted manipulation of specific genes (link).  In these studies the animal of choice is not mice, but pigs – which because of their larger size produce organs for transplantion that are similar in size to the organs of people (see link).  While similar in size, there are two issues that complicate pig to human organ transplantation: first there is the human immune system mediated rejection of foreign  tissue and second there is the possibility that transplantation of porcine organs will lead to the infection of the human recipient with porcine retroviruses.

The issue of rejection (pig into human), always a serious problem, is further exacerbated by the presence in pigs of a gene encoding the enzyme α-1,3 galactosyl transferase (GGTA1). GGTA1 catalyzes the addition of the gal-epitope to a number of cell surface proteins. The gal-epitope is “expressed on the tissues of all mammals except humans and subhuman primates, which have antibodies against the epitope” (7). The result is that pig organs provoke an extremely strong immune (rejection) response in humans.  The obvious technical fix to this (and related problems) is to remove the gal-epitope from pig cells by deleting the GGTA1 enzyme (see 8). It is worth noting that “organs from genetically engineered animals have enjoyed markedly improved survivals in non-human primates” (see Sachs & Gall, 2009).

pig to humanThe second obstacle to pig → human transplantation is the presence of retroviruses within the pig genome.  All vertebrate genomes, including those of humans, contain many inserted retroviruses; almost 50% of the human genome is retrovirus-derived sequence (an example of unintelligent design if ever there was one). Most of these endogenous retroviruses are “under control” and are normally benign (see 9). The concern, however, is that the retroviruses present in pig cells could be activated when introduced into humans. To remove (or minimize) this possibility, Niu et al set out to use the CRISPR CAS9 system to delete these porcine endogenous retroviral sequences (PERVs) from the pig genome; they appear to have succeeded, generating a number of genetically modified pigs without PERVs (see 10).  The hope is that organs generated from PERV-minus pigs from which antigen-generating genes, such as α-1,3 galactosyl transferase, have also been removed or inactivated together with more sophisticated inhibitors of tissue rejection, will lead to an essentially unlimited supply of pig organs that can be used for heart and other organ transplantation (see 11), and so alleviate the delays in transplantation, and so avoid deaths in sick people and the often brutal and criminal harvesting of organs carried out in some countries.

The final strategy being explored is to use genetically modified hosts and patient derived iPSCs  to generate fully patient compatible human organs. To date, pilot studies have been carried out, apparently successfully, using rat embryos with mouse stem cells (see 12 and 13), with much more preliminary studies using pig embryos and human iPSCs (see 14).  The approach involves what is known as chimeric  embryos.  In this case, host animals are genetically modified so that they cannot generate the organ of choice. Typically this is done by mutating a key gene that encodes a transcription factor directly involved in formation of the organ; embryos missing pancreas, kidney, heart, human pig embryo chimeraor eyes can be generated.  In an embryo that cannot make these organs, which can be a lethal defect, the introduction of stem cells from an animal that can form these organs can lead to the formation of an organ composed primarily of cells derived from the transplanted (human) cells.

At this point the strategy appears to work reasonably well for mouse-rat chimeras, which are much more closely related, evolutionarily, than are humans and pigs. Early studies on pig-human chimeras appear to be dramatically less efficient. At this point, Jun Wu has been reported as saying of human-pig chimeras that “we estimate [each had] about one in 100,000 human cells” (see 15), with the rest being pig cells.  The bottom line appears to be that there are many technical hurdles to over-come before this method of developing patient-compatible human organs becomes feasible.  Closer to reality are PERV-free/gal-antigen free pig-derived, human compatible organs. The reception of such life-saving organs by the general public, not to mention religious and philosophical groups that reject the consumption of animals in general, or pigs in particular, remains to be seen.

figures reinserted & minor edits 23 October 2020 – new link 17 December 2020.
references cited

  1. A Foxp2 Mutation Implicated in Human Speech Deficits Alters Sequencing of Ultrasonic Vocalizations in Adult Male Mice.
  2. A Humanized Version of Foxp2 Affects Cortico-Basal Ganglia Circuits in Mice
  3. Modeling cognition and disease using human glial chimeric mice.
  4. Human iPSC-derived oligodendrocyte progenitor cells can myelinate and rescue a mouse model of congenital hypomyelination.
  5. Human glia can both induce and rescue aspects of disease phenotype in Huntington disease
  6. Human iPSC Glial Mouse Chimeras Reveal Glial Contributions to Schizophrenia.
  7.  The potential advantages of transplanting organs from pig to man: A transplant Surgeon’s view
  8. see Sachs and Gall. 2009. Genetic manipulation in pigs. and Fisher et al., 2016. Efficient production of multi-modified pigs for xenotransplantation by ‘combineering’, gene stacking and gene editing
  9. Hurst & Magiokins. 2017. Epigenetic Control of Human Endogenous Retrovirus Expression: Focus on Regulation of Long-Terminal Repeats (LTRs)
  10. Nui et al., 2017. Inactivation of porcine endogenous retrovirus in pigs using CRISPR-Cas9
  11. Zhang  2017. Genetically Engineering Pigs to Grow Organs for People
  12. Kobayashi et al., 2010. Generation of rat pancreas in mouse by interspecific blastocyst injection of pluripotent stem cells.
  13. Kobayashi et al., 2015. Targeted organ generation using Mixl1-inducible mouse pluripotent stem cells in blastocyst complementation.
  14. Wu et al., 2017. Interspecies Chimerism with Mammalian Pluripotent Stem Cells
  15. Human-Pig Hybrid Created in the Lab—Here Are the Facts

Reverse Dunning-Kruger effects and science education

The Dunning-Kruger (DK) effect is the well-established phenomenon that people tend to over estimate their understanding of a particular topic or their skill at a particular task, often to a dramatic degree [link][link]. We see examples of the DK effect throughout society; the current administration (unfortunately) and the nutritional supplements / homeopathy section of Whole Foods spring to mind as examples. But there is a less well-recognized “reverse DK” effect, namely the tendency of instructors, and a range of other public communicators, to over-estimate what the people they are talking to are prepared to understand, appreciate, and accurately apply. The efforts of science communicators and instructors can be entertaining but the failure to recognize and address the reverse DK effect results in ineffective educational efforts. These efforts can themselves help generate the illusion of understanding in students and the broader public (discussed here). While a confused understanding of the intricacies of cosmology or particle physics can be relatively harmless in their social and personal implications, similar misunderstandings become personally and publicly significant when topics such as vaccination, alternative medical treatments, and climate change are in play.

There are two synergistic aspects to the reverse DK effect that directly impact science instruction: the need to understand what one’s audience does not understand together with the need to clearly articulate the conceptual underpinnings needed to understand the subject to be taught. This is in part because modern science has, at its core, become increasingly counter-intuitive over the last approximately 100 years or so, a situation that can cause serious confusions that educators must address directly and explicitly. The first reverse DK effect involves the extent to which the instructor (and by implication the course and textbook designer) has an accurate appreciation of what students think or think they know, what ideas they have previously been exposed to, and what they actually understand about the implications of those ideas.  Are they prepared to learn a subject or does the instructor first have to acknowledge and address conceptual confusions and build or rebuild base concepts?  While the best way to discover what students think is arguably a Socratic discussion, this only rarely occurs for a range of practical reasons. In its place, a number of concept inventory-type testing instruments have been generated to reveal whether various pre-identified common confusions exist in students’ thinking. Knowing the results of such assessments BEFORE instruction can help customize how the instructor structures the learning environment and content to be presented and whether the instructor gives students the space to work with these ideas to develop a more accurate and nuanced understanding of a topic.  Of course, this implies that instructors have the flexibility to adjust the pace and focus of their classroom activities. Do they take the time needed to address student issues or do they feel pressured to plow through the prescribed course content, come hell, high water, or cascading student befuddlement.

A complementary aspect of the reverse DK effect, well-illustrated in the “why magnets attract” interview with the physicist Richard Feynman, is that the instructor, course designer, or textbook author(s) needs to have a deep and accurate appreciation of the underlying core knowledge necessary to understand the topic they are teaching. Such a robust conceptual understanding makes it possible to convey the complexities involved in a particular process and explicitly values appreciating a topic rather than memorizing it.  It focuses on the general, rather than the idiosyncratic. A classic example from many an introductory biology course is the difference between expecting students to remember the steps in glycolysis or the Krebs cycle reaction system, as opposed to the general principles that underlie the non-equilibrium reaction networks involved in all biological functions, a reaction network based on coupled chemical reactions and governed by the behaviors of thermodynamically favorable and unfavorable reactions. Without a explicit discussion of these topics, all too often students are required to memorize names without understanding the underlying rationale driving the processes involved; that is, why the system behaves as it does.  Instructors also give false “rubber band” analogies or heuristics to explain complex phenomena (see Feynman video 6:18 minutes in). A similar situation occurs when considering how molecules come to associate and dissociate from one another, for example in the process of regulating gene expression or repairing mutations in DNA. Most textbooks simply do not discuss the physiochemical processes involved in binding specificity, association, and dissociation rates, such as the energy changes associated with molecular interactions and thermal collisions (don’t believe me? look for yourself!). But these factors are essential for a student to understand the dynamics of gene expression [link], as well as the specificity of modern methods involved in genetic engineering, such as restriction enzymes, polymerase chain reaction, and CRISPR CAS9-mediated mutagenesis. By focusing on the underlying processes involved we can avoid their trivialization and enable students to apply basic principles to a broad range of situations. We can understand exactly why CRISPR CAS9-directed mutagenesis can be targeted to a single site within a multibillion-base pair genome.

Of course, as in the case of recognizing and responding to student misunderstandings and knowledge gaps, a thoughtful consideration of underlying processes takes course time, time that trades the development of a working understanding of core processes and principles for broader “coverage” of frequently disconnected facts, the memorization and regurgitation of which has been privileged over understanding why those facts are worth knowing. If our goal is for students to emerge from a course with an accurate understanding of the basic processes involved rather than a superficial familiarity with a plethora of unrelated facts, however, a Socratic interaction with the topic is essential. What assumptions are being made, where do they come from, how do they constrain the system, and what are their implications?  Do we understand why the system behaves the way it does? In this light, it is a serious educational mystery that many molecular biology / biochemistry curricula fail to introduce students to the range of selective and non-selective evolutionary mechanisms (including social and sexual selection – see link), that is, the processes that have shaped modern organisms.

Both aspects of the reverse DK effect impact educational outcomes. Overcoming the reverse DK effect depends on educational institutions committing to effective and engaging course design, measured in terms of retention, time to degree, and a robust inquiry into actual student learning. Such an institutional dedication to effective course design and delivery is necessary to empower instructors and course designers. These individuals bring a deep understanding of the topics taught and their conceptual foundations and historic development to their students AND must have the flexibility and authority to alter the pace (and design) of a course or a curriculum when they discover that their students lack the pre-existing expertise necessary for learning or that the course materials (textbooks) do not present or emphasize necessary ideas. Radiation-kills-in-BoulderUnfortunately, all too often instructors, particularly in introductory level college science courses, are not the masters of their ships; that is, they are not rewarded for generating more effective course materials. An emphasis on course “coverage” over learning, whether through peer-pressure, institutional apathy, or both, generates unnecessary obstacles to both student engagement and content mastery.  To reverse the effects of the reverse DK effect, we need to encourage instructors, course designers, and departments to see the presentation of core disciplinary observations and concepts as the intellectually challenging and valuable endeavor that it is. In its absence, there are serious (and growing) pressures to trivialize or obscure the educational experience – leading to the socially- and personally-damaging growth of fake knowledge.

empty images holders removed, new image added – 17 December 2020

Is it time to start worrying about conscious human “mini-brains”?

A human iPSC cerebral organoid in which pigmented retinal epithelial cells can be seen (from the work of McClure-Begley et al.).   Also see “Can lab-grown brains become conscious?” by Sara Readon Nature 2020.

The fact that experiments on people are severely constrained is a major obstacle in understanding human development and disease.  Some of these constraints are moral and ethical and clearly appropriate and necessary given the depressing history of medical atrocities.  Others are technical, associated with the slow pace of human development. The combination of moral and technical factors has driven experimental biologists to explore the behavior of a wide range of “model systems” from bacteria, yeasts, fruit flies, and worms to fish, frogs, birds, rodents, and primates.  Justified by the deep evolutionary continuity between these organisms (after all, all organisms appear to be descended from a single common ancestor and share many molecular features), experimental evolution-based studies of model systems have led to many therapeutically valuable insights in humans – something that I suspect a devotee of intelligent design creationism would be hard pressed to predict or explain (post link).

While humans are closely related to other mammals, it is immediately obvious that there are important differences – after all people are instantly recognizable from members of other closely related species and certainly look and behave differently from mice. For example, the surface layer of our brains is extensively folded (they are known as gyrencephalic) while the brain of a mouse is smooth as a baby’s bottom (and referred to as lissencephalic). In humans, the failure of the brain cortex to fold is known as lissencephaly, a disorder associated with severe neurological defects. With the advent of more and more genomic sequence data, we can identify human specific molecular (genomic) differences. Many of these sequence differences occur in regions of our DNA that regulate when and where specific genes are expressed.  Sholtis & Noonan (1) provide an example: the HACNS1 locus is a 81 basepair region that is highly conserved in various vertebrates from birds to chimpanzees; there are 13 human specific changes in this sequence that appear to alter its activity, leading to human-specific changes in the expression of nearby genes (↓). At this point ~1000 genetic elements that are different in humans compared to other vertebrates have been identified and more are likely to emerge (2).  Such human-specific changes can make modeling human-specific behaviors, at the cellular, tissue, organ, and organism level, in non-human model systems difficult and problematic (3, 4).   It is for this reason that scientists have attempted to generate better human specific systems.

human sequence divergence

One particularly promising approach is based on what are known as embryonic stem cells (ESCs) or pluripotent stem cells (PSCs). Human embryonic stem cells are generated from the inner cell mass of a human embryo and so involve the destruction of that embryo – which raises a number of ethical and religious concerns as to when “life begins” (5).  Human pluripotent stem cells are isolated from adult tissues but in most cases require invasive harvesting methods that limit their usefulness.  Both ESCs and PSCs can be grown in the laboratory and can be induced to differentiate into what are known as gastruloids.  Such gastruloids can develop anterior-posterior (head-tail), dorsal-ventral (back-belly), and left-right axes analogous to those found in embryos (6) and adults (top panel ↓). In the case of PSCs, the gastruloid (bottom panel ↓) is essentially a twin of the organism from which the PSCs were derived, a situation that raises difficult questions: is it a distinct individual, is it the property of the donor or the creation of a technician.  The situation will be further complicated if (or rather, when) it becomes possible to generate viable embryos from such gastruloids.

Axes

gastruloid-embryo-comparisonThe Nobel prize winning work of Kazutoshi Takahashi and Shinya Yamanaka (7), who devised methods to take differentiated (somatic) human cells and reprogram them into ESC/PSC-like cells, cells known as induced pluripotent stem cells (iPSCs)(8), represented a technical breakthrough that jump-started this field. While the original methods derived sample cells from tissue biopsies, it is possible to reprogram kidney epithelial cells recovered from urine, a non-invasive approach (910).  Subsequently, Madeline Lancaster, Jurgen Knōblich, and colleagues devised an approach by which such cells could be induced to form what they termed “cerebral organoids” (although Yoshiki Sasai and colleagues were the first to generate neuronal organoids); they used this method to examine the developmental defects associated with microencephaly (11).  The value of the approach was rapidly recognized and a number of studies on human conditions, including  lissencephaly (12), Zika-virus infection-induced microencephaly (13), and Down’s syndrome (14);  investigators have begun to exploit these methods to study a range of human diseases – and rapid technological progress is being made.

The production of cerebral organoids from reprogrammed human somatic cells has also attracted the attention of the media (15).  While “mini-brain” is certainly a catchier name, it is a less accurate description of a cerebral organoid, itself possibly a bit of an overstatement, since it is not clear exactly how “cerebral” such organoids are. For example, the developing brain is patterned by embryonic signals that establish its asymmetries; it forms at the anterior end of the neural tube (the nascent central nervous system and spinal cord) and with distinctive anterior-posterior, dorsal-ventral, and left-right asymmetries, something that simple cerebral organoids do not display.  Moreover, current methods for generating cerebral organoids involve primarily what are known as neuroectodermal cells – our nervous system (and that of other vertebrates) is a specialized form of the embryo’s surface layer that gets internalized during development. In the embryo, the developing neuroectoderm interacts with cells of the circulatory system (capillaries, veins, and arteries), formed by endothelial cells and what are known as pericytes that surround them. These cells, together with interactions with glial cells (astrocytes, a non-neuronal cell type) combine to form the blood brain barrier.  Other glial cells (oligodendrocytes) are also present; in contrast, both types of glia (astrocytes and oligodendrocytes) are rare in the current generation of cerebral organoids. Finally, there are microglial cells,  immune system cells that originate from outside the neuroectoderm; they invade and interact with neurons and glia as part of the brain’s dynamic neural capillary and neuronssystem. The left panel of the figure shows, in highly schematic form how these cells interact (16). The right panel is a drawing of neural tissue stained by the Golgi method (17), which reveals ~3-5% of the neurons present. There are at least as many glial cells present, as well as microglia, none of which are visible in the image. At this point, cerebral organoids typically contain few astrocytes and oligodendrocytes, no vasculature, and no microglia. Moreover, they grow to be about 1 to 3 mm in diameter over the course of 6 to 9 months; that is significantly smaller in volume than a fetal or newborn’s brain. While cerebral organoids can generate structures characteristic of retinal pigment epithelia (top figure) and photo-responsive neurons (18), such as those associated with the retina, an extension of the brain, it is not at all clear that there is any significant sensory input into the neuronal networks that are formed within a cerebral organoid, or any significant outputs, at least compared to the role that the human brain plays in controlling bodily and mental functions.

The reasonable question, then, must be whether a  cerebral organoid, which is a relatively simple system of cells (although itself complex), is conscious. It becomes more reasonable as increasingly complex systems are developed, and such work is proceeding apace. Already researchers are manipulating the developing organoid’s environment to facilitate axis formation, and one can anticipate the introduction of vasculature. Indeed, the generation of microglia-like cells from iPSCs has been reported; such cells can be incorporated into cerebral organoids where they appear to respond to neuronal damage in much the same way as microglia behave in intact neural tissue (19).

We can ask ourselves, what would convince us that a cerebral organoid, living within a laboratory incubator, was conscious? How would such consciousness manifest itself? Through some specific pattern of neural activity, perhaps?  As a biologist, albeit one primarily interested in molecular and cellular systems, I discount the idea, proposed by some physicists and philosophers as well as the more mystical, that consciousness is a universal property of matter (20,21).  I take consciousness to be an emergent property of complex neural systems, generated by evolutionary mechanisms, built during embryonic and subsequent development, and influenced by social interactions (BLOG LINK) using information encoded within the human genome (something similar to this: A New Theory Explains How Consciousness Evolved). While a future concern, in a world full of more immediate and pressing issues, it will be interesting to listen to the academic, social, and political debate on what to do with mini-brains as they grow in complexity and perhaps inevitably, towards consciousness.

Footnotes and references

Thanks to Rebecca Klymkowsky, Esq. and Joshua Sanes, Ph.D. for editing and disciplinary support. Minor updates and the reintroduction of figures 22 Oct. 2020.

  1. Gene regulation and the origins of human biological uniqueness
  2.  See also Human-specific loss of regulatory DNA and the evolution of human-specific traits
  3. The mouse trap
  4. Mice Fall Short as Test Subjects for Some of Humans’ Deadly Ill
  5. The status of the human embryo in various religions
  6. Interactions between Nodal and Wnt signalling Drive Robust Symmetry Breaking and Axial Organisation in Gastruloids (Embryonic Organoids)
  7.  Induction of pluripotent stem cells from mouse embryonic and adult fibroblast cultures by defined factors
  8.  How iPS cells changed the world
  9.  Generation of Induced Pluripotent Stem Cells from Urine
  10. Urine-derived induced pluripotent stem cells as a modeling tool to study rare human diseases
  11. Cerebral organoids model human brain development and microcephaly.
  12. Human iPSC-Derived Cerebral Organoids Model Cellular Features of Lissencephaly and Reveal Prolonged Mitosis of Outer Radial Glia
  13. Using brain organoids to understand Zika virus-induced microcephaly
  14. Probing Down Syndrome with Mini Brains
  15. As an example, see The Beauty of “Mini Brains”
  16. Derived from Central nervous system pericytes in health and disease
  17. Golgi’s method .
  18. Cell diversity and network dynamics in photosensitive human brain organoids
  19. Efficient derivation of microglia-like cells from human pluripotent stem cells
  20. The strange link between the human mind and quantum physics – BBC:
  21. Can Quantum Physics Explain Consciousness?

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).

Teach Evolution

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.

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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.GULO phylogeny mouse
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.synteny-GULO region

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.spacer bar

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.