Visualizing Profilin

Profilin as a part of the musculo-skeletal system that motors our cells around. But how can we tell?

Our cells have structural elements called the cytoskeleton. The term is a misnomer, since the cytoskeleton comprises the muscles of the cell as well as its rigid supports. There are three types of rigid element- actin filaments, intermediate filaments, and microtubules. Intermediate filaments are the stable, relatively inert part of the equation, making up structures like keratins that shape our skin, hair, and nails. Actin and microtubules, however are highly dynamic and contribute to amoeboid motion, developmental cell motions, neural extensions, and all kinds of other shape changes cells perform. Microtubules are bigger and stiffer, (25 nm diameter, hundreds of times stiffer than actin filaments), and participate in big, discrete processes like separating the chromosomes at division, and forming the core of cilia that wave from the outside of the cell. 

Actin (6 nm diameter) is more pervasive all over the cell, and is what provides the main motive force of ameboid motions and cell shape change. Indeed, our muscles are mostly composed of great quantities of actin along with interdigitated filaments of its corresponding motor protein (myosin) in orderly, almost crystalline, arrays. Both myosin and actin create motion in two ways- by their own polymerization / depolymerization, and also by way of motors that can move along their lengths.

Images of cells showing fluorescence labeling of skeletal components. Microtubules are shown in green, and DNA in blue. Panel C shows a neuronal growth cone with actin labeled in red. Note how microtubules and actin cooperate, with actin in the lead, pushing out the cell edges by force of its own polymerization. Panel A shows resting cells, with the microtubule organizing center in red. E shows a yeast cell with microtubules spanning its length. G shows a dividing cell at M phase, where microtubules organize the separation of chromosomes, after the microtubule organizing center has itself first divided into two.

A recent paper discussed new tools in the quest to visualize profilin, one of the many accessory proteins involved in managing the cytoskeleton. The most basic role of profilin is to bind to monomers of actin helping them recharge (that is, exchange their ADP for a new ATP). There is a lot of profilin in the cell, and it mostly sits around complexed with actin, preventing it from spontaneously polymerizing. But then if a signal comes in, profilin has binding sites for formin proteins, which tend to be the main instigators of cell shape change and actin polymerization, and can orchestrate the handoff of actin from profilin to growing actin filaments.

The overall actin cycle. Actin monomers are constantly coming on and off of filaments. ATP-charged actin is held in reserve in complex with profilin (dark shapes). Then formins or other accessory proteins can encourage addition to a filament, at one end, called the barbed end. While in filaments, actin gradually hydrolyzes its ATP, forming ADP. Actin with ADP is prone to dissociation, which may be encouraged or discouraged by various other accessory proteins. The resulting actin monomers are then re-bound by profilin and the cycle begins again.

But how can we see all this? Making proteins fluorescent has been now for decades the amazingly effective way to vizualize them. And one can do that either live, or dead. For the latter, the cell is chemically embalmed and permeabilized, then treated with antibodies that bind to the protein(s) of interest. Then a second set of antibodies are applied that bind to the first set, and are labeled with some fluorescent tag, and voila- images of where your protein of interest is, or was. But much more compelling is to see all this in living, working, and moving cells. To do that, the protein of interest is mutated to add an intrinsically fluorescent tag, such as green fluorescent protein. But profilin is so small, and so packed with critical binding sites, that there is little room for a fluorescent tag protein that is, in fact, almost twice as large as profilin itself. 

What to do? These researchers attached a little tail to one end of the protein, off which they then added their tag, in this case a protein called mApple, chosen for its nice red fluorescence spectrum that doesn't interfere with the other greens and blues typically used in these experiments. The paper is mostly then a laborious verification that this new form of profilin fully functions in cells as the wild type does, engages in all the same interactions, (as far as known), and thus consitutes a wonderful new tool for the field.

An atomic structure of profilin bound to actin. Profilin is a very small protein with many important interactions. That makes altering it very tricky. How to create a fluorescent form, or squeeze in some other tag? Profilin binds to actin, to microtubules, to formins and other proteins with PLP (poly-proline) domains, and to phosphoinositide 4,5-bisphosphate (PIP2), which is not even shown here.

It turns out that profilin binds to microtubules as well as to actin. And so do formins. As shown above in the image of a neural growth cone, though the composition of actin and microtubules and their size and other characteristics are very different, they cooperate extensively, thus must have mechanisms of crosstalk. Not much is known, unfortunately, about how this works- while a good bit is known individually how each of the actin and microtubule systems work, how they work together is poorly understood. But one thing these researchers show is that profilin, along with its abundance all over the cell, is also concentrated at the microtubule organizing center. Indeed, some mutations that cause the disease ALS occur right in these regions of profilin that bind microtubules. So something important is going on, and hopefully this new tool will speed work towards greater understanding of how the cytoskeletons operate.

Profilin imaged in a live cell, with other tagged molecules. At left, profilin occurs all over the cell in its role as actin buffer and storage partner. But note a couple of dots on each side. Next is shown the same cell labeled on alpha tubulin, the major component of microtubules. Next is show DNA, which is condensed, as this cell is undergoing division. Last is shown the merged images, with DNA in blue, tubulin in green, and profilin in red/orange. The dots turn out to be the microtubule organizing centers that run the spindle which is orchestrating chromosome segregation.

• Keep 'em high.. a way to smooth gas price volatility, and fight climate change.
• And we need a carbon tax for comprehensive decarbonization.
• Liberals tied in knots by homelessness.
• All public school systems are at risk.
• Someone has been watching a little too much Grit TV.
• Cry me a river- about a shortage of post-docs.

Evolution Under (Even in) Our Noses

The Covid pandemic is a classic and blazingly fast demonstration of evolution.

Evolution has been "controversial" in some precincts. While tradition told the fable of genesis, evolution told a very different story of slow yet endless change and adaptation- a mechanistic story of how humans ultimately arose. The stark contrast between these stories, touching both on the family tree we are heir to, and also on the overall point and motivation behind the process, caused a lot of cognitive dissonance, and is a template of how a fact can be drawn into the left/right, blue/red, traditional/progressive cultural vortex.

This all came to a head a couple of decades ago, when in the process of strategic retreat, anti-evolution forces latched onto some rather potent formulations, like "just a theory", and "intelligent design". These were given a lot of think tank support and right wing money, as ways to keep doubt alive in a field that scientifically had been settled and endlessly ramified for decades. To scientists, it was the height of absurdity, but necessitated wading into the cultural sphere in various ways that didn't always connect effectively with their intended audience. But eventually, the tide turned, courts recognized that religion was behind it all, and kept it out of schools. Evolution has more or less successfully receded from hot-button status.

One of the many rearguard arguments of anti-evolutionists was that sure, there is short-term evolution, like that of microbes or viruses, but that doesn't imply that larger organisms are they way they are due to evolution and selection. That would be simply beyond the bounds of plausibility, so we should search for explanations elsewhere. At this point they were a little gun-shy and didn't go so far in public as to say that elsewhere might be in book like the Bible. This line of argument was a little ironic, since Darwin himself hardly knew about microbes, let alone viruses, when he wrote his book. The evidence that he adduced (in some profusion) described the easily visible signs of geology, of animals and plants around the world, (including familar domestic animals), which all led to the subtle, yet vast, implications he drew about evolution by selection. 

So it has been notable that the vistas of biology that opened up since that time, in microbiology, paleontology, genetics, molecular biology, et al., have all been guided by these original insights and have in turn supported them without fail. No fossils are found out of order in the strata, no genes or organisms parachute in without antecedents, and no chicken happens without an egg. Evolution makes sense of all of biology, including our current pandemic.

But you wouldn't know it from the news coverage. New variants arise into the headlines, and we are told to "brace" for the next surge, or the next season. Well, what has happened is that the SARS-COV2 virus has adapted to us, as we have to it, and we are getting along pretty well at this point. Our adaptation to it began as a social (or antisocial!) response that was very effective in frustrating transmission. But of late, it has been more a matter of training our immune systems, which have an internal selective principle. Between rampant infections and the amazing vaccines, we have put up significant protective barriers to severe illness, though not, notably, to transmission.

But what about the virus? It has adapted in the most classic of ways, by experiencing a wide variety of mutations that address its own problems of survival. It is important to remember that this virus originated in some other species (like a bat) and was not very well adapted to humans. Bats apparently have countless viruses of this kind that don't do them much harm. Similarly, HIV originated in chimpanzee viruses that didn't do them much harm either. Viruses are not inherently interested in killing us. No, they survive and transmit best if they keep us walking around, happily breathing on other people, with maybe an occasional sneeze. The ultimate goal of every virus is to stay under the radar, not causing its host to either isolate or die. (I can note parenthetically that viruses that do not hew to this paradigm, like smallpox, are typically less able to mutate, thus less adaptable, or have some other rationale for transmission than upper respiratory spread.)

And that is clearly what has happened with SARS-COV2. Local case rates in my area are quite high, and wastewater surveilance indicates even higher prevalence. Isolation and mask mandates are history. Yet hospitalizations remain very low, with no one in the ICU right now. Something wonderful has happened. Part of it is our very high local vaccination rate, (96% of the population), but another part is that the virus has become less virulent as it has adapted to our physiology, immune systems, media environment and social practices, on its way to becoming endemic, and increasingly innocuous. All this in a couple of years of world-wide spread, after billions of infections and transmissions.

The succession (i.e. evolution) of variants detected in my county. 

The trend of local wastewater virus detection, which currently shows quite high levels, despite mild health outcomes.

So what has the virus been doing? While it has many genes and interactions with our physiology, the major focus has been on the spike protein, which is most prominent on the viral surface, is the first protein to dock to specific human proteins (the ACE2 cell surface receptor), and is the target of all the mRNA and other specific subunit vaccines. (As distinct from the killed virus vaccines that are made from whole viruses.) It is the target of 40% of the antibodies we naturally make against the whole virus, if we are infected. It is also, not surprisingly, the most heavily mutated portion of the virus, over the last couple of years of evolution. One paper counts 45 mutations in the spike protein that have risen to the level of "variants of concern" at WHO. 

"We found that most of the SARS-COV-2 genes are undergoing negative purifying selection, while the spike protein gene (S-gene) is undergoing rapid positive selection."

Structure of the spike protein, in its normal virus surface conformation, (B, C), and in its post-triggering extended conformation that reaches down into the target cell's membrane, and later pulls the two together. Top (in B, C) is where it binds to the ACE2 target on respiratory cells, and bottom is its anchor in the viral membrane coat (D shows it upside-down). At top (A) is the overall domain structure of the protein, in its linear form as synthesized, especially the RBD (receptor binding domain) and the two protease cleavage sites that prepare it for eventual triggering.

The spike protein is a machine, not just a blob. As shown in this video, it starts as a pyramidal blob flexibly tethered to the viral surface. Binding the ACE2 proteins in our respiratory tracts triggers a dramatic re-organization whereby this blob turns into a thin rope, which drops into the target cell. Meanwhile, the portion stuck to the virus unfolds as well and turns into threads that wind back around the newly formed rope, thereby pulling the virus and the target cell membrane together and ultimately fusing them. This is, mechanistically, how the virus gets inside our cells.

The triggering of the spike protein is a sensitive and adjustable process. In related viruses, the triggering is more difficult, and waits till the virus is engulfed in a vesicle that taken into the cell, and acidified in the normal process of lysosomal destruction / ingestion of outside materials. The acidification triggers these viral spike proteins to fire and release the virus into the cell. Triggering also requires cleavage of the spike protein with proteases that cut it at two locations. Other related viruses sometime wait for a target host protease to do the honors, but SARS-COV2 spike protein apparently is mostly cleaved during production by its originating host. This raises the stakes, since it can then more readily trigger, by accident, or once it finds proper ACE2 receptors on a target host. One theme of recent SARS-COV2 evolution is that triggering has become slightly easier, allowing the virus to infect higher up in the respiratory system. The original strains set up infections deep in the lung, but recent variants infect higher up, which lessens the systemic risks of infection to the host, promotes transmissibility, and speeds the infection and transmission process. 

The mutations G339D, N440K, L452R, S477N, T478K, and E484K in the spike region that binds to ACE2 (RBD, or receptor binding domain) promotes this interaction, raising transmissibility. (The nomenclature is that the number gives the position of the amino acid in the linear protein sequence, and the letters give the original version of the amino acid in one letter code (start) and in the mutated version (end)). Overall, mutations of the spike protein have increased the net charge on the spike protein significantly in the positive direction, which encourages binding to the negatively charged ACE2 protein. D614G is not in this region, but is nearby and seems to have similar effects, stabilizing the protein. The P681 mutation in one of the cleaved regions promotes proteolysis by the enzyme furin, thus making the virus more trigger-able. 

What are some other constraints on the spike protein? It needs to evade our vaccines and natural immunity, but has seemingly adapted to a here-and-gone infection style, though with periodic re-infection, like other colds. So any change is good for the purpose of camouflage, as long as its essential functions remain intact. The N-terminal, or front, domain of the spike protein, which is not involved directly in ACE2 binding, has experienced a series of mutations of this kind. An additional function it seems to have is to mimic a receptor for the cytokine interleukin 8, which attracts neutrophils and encourages activation of macrophages. Such mimicry may reduce this immune reaction, locally. 

In comparison to all these transmissibility-enhancing mutations, it is not clear yet where the mutations that decrease virulence are located. It is likely that they are more widely distributed, not in the gene encoding the spike protein. SARS-COV2 has a remarkable number of genes with various interactions with our immune systems, so the scope for tuning is prodigious. If all this can be accomplished in a couple of years, image what a million, or a billion, years can do for other organisms that, while they have slower reproduction cycles and more complicated networks of internal and external relations, still obey that great directive to adapt to their circumstances.

• Late link, on receptor binding vs immune evasion tradeoffs.
• Yes, chimpanzees can talk.
• The rich are getting serious about destroying democracy.
• Forced arbitration is, generally, unconscionable and should be illegal.
• We could get by with fewer nuclear weapons.
• Originalism would never allow automatic or semiautomatic weapons.

Tangling With the Network

Molecular biology needs better modeling.

Molecular biologists think in cartoons. It takes a great deal of work to establish the simplest points, like that two identifiable proteins interact with each other, or that one phosphorylates the other, which has some sort of activating effect. So biologists have been satsified to achieve such critical identifications, and move on to other parts of the network. With 20,000 genes in humans, expressed in hundreds of cell types, regulated states and disease settings, work at this level has plenty of scope to fill years of research.

But the last few decades have brought larger scale experimentation, such as chips that can determine the levels of all proteins or mRNAs in a tissue, or the sequences of all the mRNAs expressed in a cell. And more importantly, the recognition has grown that any scientific field that claims to understand its topic needs to be able to model it, in comprehensive detail. We are not at that point in molecular biology, at all. Our experiments, even those done at large scale and with the latest technology, are in essence qualitative, not quantitative. They are also crudely interventionistic, maybe knocking out a gene entirely to see what happens in response. For a system as densely networked as the eukaryotic cell, it will take a lot more to understand and model it.

One might imagine that this is a highly detailed model of cellular responses to outside stimuli. But it is not. Some of the connections are much less important than others. Some may take hours to have the indicated effect, while others happen within seconds or less. Some labels hide vast sub-systems with their own dynamics. Important items may still be missing, or assumed into the background. Some connections may be contingent on (or even reversed by) other conditions that are not shown. This kind of cartoon is merely a suggestive gloss and far from a usable computational (or true) model of how a biological regulatory system works.

The field of biological modeling has grown communities interested in detailed modeling of metabolic networks, up to whole cells. But these remain niche activities, mostly because of a lack of data. Experiments remain steadfastly qualitative, given the difficulty of performing them at all, and the vagaries of the subjects being interrogated. So we end up with cartoons, which lack not only quantitative detail on the relative levels of each molecule, but also critical dynamics of how each relationship develops in time, whether in a time scale of seconds or milliseconds, as might be possible for phosphorylation cascades (which enable our vision, for example), or a time scale of minutes, hours, or days- the scale of changes in gene expression and longer-term developmental changes in cell fate.

These time and abundance variables are naturally critical to developing dynamic and accurate models of cellular activities. But how to get them? One approach is to work with simple systems- perhaps a bacterial cell rather than a human cell, or a stripped down minimal bacterial cell rather than the E. coli standard, or a modular metabolic sub-network. Many groups have labored for years to nail down all the parameters of such systems, work which remains only partially successful at the organismal scale.

Another approach is to assume that co-expressed genes are yoked together in expression modules, or regulated by the same upstream circuitry. This is one of the earliest forms of analysis for large scale experiments, but it ignores all the complexity of the network being observed, indeed hardly counts as modeling at all. All the activated genes are lumped together into one side, and all the down-regulated genes on the other side, perhaps filtered by biggest effect. The resulting collections are clustered by some annotation of those gene's functions, thereby helping the user infer what general cell function was being regulated in her experiment / perturbation. This could be regarded perhaps as the first step on a long road from correlation analysis of gene activities to a true modeling analysis that operates with awareness of how individual genes and their products interact throughout a network.

Another approach is to resort to a lot of fudge factors, while attempting to make a detailed model of the cell /components. Assume a stable network, and fill in all the values that could get you there, given the initial cartoon version of molecule interactions. Simple models thus become heuristic tools to hunt for missing factors that affect the system, which are then progressively filled in, hopefully by doing new experiments. Such factors could be new components, or could be unsuspected dynamics or unknown parameters of those already known. This is, incidentally, of intense interest to drug makers, whose drugs are intended to tweek just the right part of the system in order to send it to a new state- say, from cancerous back to normal, well-behaved quiescence.

A recent paper offered a version of this approach, modular response analysis (MRA). The authors use perturbation data from other labs, such as the inhibition of 1000 different genes in separately assayed cells, combined with a tentative model of the components of the network, and then deploy mathematical techniques to infer / model the dynamics of how that cellular system works in the normal case. What is observed in either case- the perturbed version, or the wild-type version- is typically a system (cell) at steady state, especially if the perturbation is something like knocking out a gene or stably expressing an inhibitor of its mRNA message. Thus, figuring out the (hidden) dynamic in between- how one stable state gets to another one after a discrete change in one or more components- is the object of this quest. Molecular biologists and geneticists have been doing this kind of thing off-the-cuff forever (with mutations, for instance, or drugs). But now we have technologies (like siRNA silencing) to do this at large scale, altering many components at will and reading off the results.

This paper extends one of the relevant mathematical methods (modular response analysis, MRA) to this large scale, and finds that, with a bit of extra data and some simplifications, it is competitive with other methods (mutual information) in creating dynamic models of cellular activities, at the scale of a thousand components, which is apparently unprecedented. At the heart of MRA are, as its name implies, modules, which break down the problem into manageable portions and allow variable amounts of detail / resolution. For their interaction model, they use a database of protein interactions, which is a reasonably comprehensive, though simplistic, place to start.

What they find is that they can assemble an effective system that handles both real and simulated data, creating quantitative networks from their inputs of gene expression changes upon inhibition of large numbers of individual components, plus a basic database of protein relationships. And they can do so at reasonable scale, though that is dependent on the ability to modularize the interaction network, which is dangerous, as it may ignore important interactions. As a state of the art molecular biology inference system, it is hardly at the point of whole cell modeling, but is definitely a few steps ahead of the cartoons we typically work with.

The authors offer this as one result of their labors. Grey nodes are proteins, colored lines (edges) are activating or inhibiting interactions. Compared to the drawing above, it is decidedly more quantitative, with strengths of interactions shown. But timing remains a mystery, as do many other details, such as the mechanisms of the interactions

• Fiscal contraction + interest rate increase + trade deficit = recession.
• The lies come back to roost.
• Status of carbon removal.
• A few notes on stuttering.
• A pious person, on shades of abortion.
• Discussion on the rise of China.

DNA Mambo in the Nucleus

Some organizational principles for nuclear DNA to organize genes for local regulation.

There has been a long and productive line of research on the mechanisms of transcription from DNA to RNA- the process that reads the genome and translates its code into a running stream of instructions going out to the cell through development and all through life. This search has generally gone from the core of the process outwards to its regulatory apparatus. The opening of DNA by simple RNA polymerases was one of the first topics of study, followed by how the polymerase is positioned at the start site by "promoter" DNA sequences, with ever more ornate and distant surrounding machinery coming under scrutiny over time, as researchers climbed the evolutionary trajectory of life, from viruses and bacteria to mammals. 

But how this process fits into the larger structure of the nucleus, and how it is globally organized eukaryotes has long been an intriguing question, and tools are finally available to bring this level of organization into focus. For example, genes are known to be activated by direct contact with "enhancer" elements located thousands, even many tens of thousands, of basepairs away on the DNA- so why can't those enhancers activate other genes elsewhere in the nucleus, rather than the genes they are nearest to on the one-dimensional DNA? The nucleus is a small place with a lot of DNA. Roughly 1/100 of its physical space is taken up by DNA, and it is highly likely that such enhancers could be closer in 3-D space to other genes than the ones they are supposed to regulate, if everything were arranged randomly. Similarly, how do such enhancer elements find their proper targets, amid the welter of other DNA and proteins? A hundred thousand base pairs is long enough to traverse the entire nucleus.

So there has to be some organization, and new techniques have come along to illuminate it. These are crosslinking methods where the cells are treated with a chemical to crosslink / freeze a fraction of protein and DNA interactions in place, then enzymes are introduced to chop everything up, to various degrees of completeness. What is left are little clumps of DNA and protein that hopefully include distant cross-links, between enhancers and promoters, between key organizational sites and the genes they interact with, etc. Then comes the sequencing magic. These clumped stray DNAs are diluted and ligated together (only to local ends), amplified and sequenced, generating a slew of DNA sequences. Those hybrid sequences can be interpreted, (given the known sequence of the reference genome), to say whether some genomic location X got tangled up with some other location Y, reflecting their 3-D interaction in the cell when it was originally treated.

A recent paper pushed this method forward a bit, with finer-grained enzymatic digestion and deeper sequencing, to come up with the most detailed look ever at a drosophila genome, and at some particular genes that have long held interest as key regulators of development. This refined detail, plus some experiments mutating some of the key DNA sites involved, allowed them to come up with a new class of organizing elements and a theory of how the nuclear tangle works.

Long range contacts in the Antennapedia locus of flies. Micro-C refers to the crosslinking and sequencing method that maps long-range DNA contacts mediated by proteins. Pyramids in the top diagram map binary location-to-location contacts. Local contacts generally predominate over distant ones, but a few distant connections are visible, such as between the ends of the ftz gene. TAD stands for topologically associating domain, mapping out the connections seen above between pink sites. This line also lists the genes residing in each zone (Deformed, micro RNA 10, Sex combs reduced, fushi terazu, and Antennapedia promoters P1 and P2). The contacts track shows where the authors map specific sites where organizing factors (including Trl (trithorax-like) and CP190 (centrosomal protein of 190 kDa)) bind. The overall idea is that there are two kinds of contacts, boundaries and tethers. Boundaries insulate one region from the next, preventing regulatory spill-over to the wrong gene. Tethers serve as pro-regulatory staging points, helping enhancers contact their proper promoter targets, even though the tether complex does not itself promote RNA transcription.

Insulator elements have been recognized for some time. These are locations that seem to block regulatory interactions across them, thus defining, between two such sites, a topologically associated domain, (TAD). How they work is not entirely clear, but they may stitch themselves to the nuclear membrane. They are thought to interact with a DNA pump called cohesin to extrude a loop of DNA between two insulator sites, thereby keeping that DNA clear of other interactions, at least temporarily, and locally clumped. The authors claim to find a new element called a distal tethering element (DTE), which works like an enhancer in promoting interaction between distant activating regulatory sites and genes, but doesn't actually activate. They just structure the region so that when a signal comes, the gene is ready to be activated efficiently. 

One theory of how insulator elements work. The insulator sites "CTCF motif" are marked on the DNA with dark blue arrow heads. They control the boundaries of action by the protein complex cohesin, which forms dimeric doughnuts around DNA and can pump DNA. Cohesins are central to the mechanisms of meiosis and mitosis. The net effect is to produce a segregated region of DNA as portrayed at the bottom, which should have a much higher rate of local interactions (as seen in the Micro-C method) than distant interactions.

At the largest scale, these authors claim that there are, in the whole fly genome and at this particular (early) point in development, 2034 insulator locations (TADs) and 620 tethering elements (TEs or DTEs). They show that DTEs in the locus they study closely play an active role in turning the nearby genes on at early times in development, and in directing activation from enhancers near the DTE, rather than ones farther away. What binds to the DTEs? So-called "pioneer" regulatory factors(such as Zelda) that have the power to make way through nucleosomes and other chromatin proteins to bind their target DNA. The authors say that these tether sites, once set up, are then stable on a permanent basis, through all developmental stages, even though the genes they assist may only be active transiently. 

The "poised" nature of some genes had been observed long ago, so it is not entirely surprising to see this mechanism get fleshed out a little, as a structural connection that is made between genes and their regulatory sites in advance of the actual activator proteins arriving at the associated enhancers and turning them on.

 

Final model: the normal case around the Antennapedia locus is shown at top, with insulator sites shown in pink, and tethering sites shown in teal. If one of the tethering elements is removed (middle), then the enhancer EE has less effect on the gene Scr, whose expression is reduced. If an insulator is removed (bottom), the re-organized domain allows the ftz gene's regulators, including the enhancer AE1, to affect Scr expression, altering its timing and location of expression.

• Don't hold your breath for capitalism to address climate change.
• How the Russian skating machine works.
• Russia, solved.
• Solar tax for all! Or at least a separation of grid costs and electricity generation costs.

Desperately Seeking Calcium

How cells regulate internal calcium levels.

Now that we are getting a crash course in molecular biology and evolution courtesy of the pandemic, many will be familiar with the intricate and dynamic activities of some proteins. The SARS spike protein doesn't just dock at a particular receptor on our pulmonary epithelial surfaces, but goes through a gymnastic routine to facilitate membrane fusion as well. Many other proteins have dynamic behaviors as well- something that was not fully appreciated back when structural biology was in its infancy and knowing anything about the structure of a protein or DNA or RNA required it to be locked into crystaline form for X-ray diffraction studies.

Another example came up recently, involving calcium regulation within cells. Calcium is a hugely important ion and regulator, central to core signaling cascades in all eukaryotic cells- to neuronal function, and to muscle activation, among many other roles. Our blood levels of calcium are tightly regulated, (to within a 20% range), mostly by way of an axis of parathyroid hormone between the parathyroid gland and the kidney, with additional effects from factors such as vitamin D, calcitonin, and estrogen. So our cells can rely on having a constant level of calcium on the outside. How do they maintain their levels internally?

One way is to have a large store socked away, as we have in bones for the body generally. Within cells, the endoplasmic reticulum (ER) turns out to have far higher concentrations of calcium than the rest of the cytosol, up to 10,000 fold. In muscle cells, the ER gets a special name- as the sarcoplasmic reticulum. Many calcium regulatory events rely on calcium being released briefly from the ER, having some effect, and then gradually getting pumped back in. But what if the ER is short of calcium? That would be a crisis!  

It turns out that we have a sensor system for that, llinking an ER protein called STIM1, which senses levels of Ca++ in the ER with a plasma membrane channel called ORAI1, which can open to let in Ca++ from the outside. A recent paper, (review), in combination with much other past work, demonstrates how STIM1 works. The two proteins turn out to interact directly, thanks to the fact that the ER, which is a huge organelle that extends all over the cell, always has some spots that interact with the plasma membrane, called membrane contact sites. These are strucured by other proteins, so there is a set distance between the two membranes, which must never fuse together. This means that while STEM1 can get very close to ORAI1 in the plasma membrane, there will still be a gap between them. How to bridge it?

Overall model for how STIM1 works. The luminal side sticks into the ER and binds calcium (red dots). If levels are low, the protein dimerizes at the transmembrane and internal domains, causing extensive refolding of the external domains residing in the cytosol. This causes them to straighten out and span the space of the contact structure between the ER and the plasma membrane, where it activates the ORAI1 calcium channel protein by direct contact.

The STIM1 protein turns out to provide the bridge, in the form of a transformer-style mechanism that shifts it from a compact blob on the ER when calcium levels are high, to an extended rod that pokes into ORAI1, activating it, when calcium levels are low. Since it is the ER-internal level of calcium that needs to be sensed, it is the ER-internal (or luminal) portion of the STIM1 that does this sensing. It has about five calcium binding sites that, if filled, prevent its dimerization, but which if empty, promote it. Internal dimerization induces a dramatic refolding of the cytoplasmic portion of STIM1 into the active, extended rod. 

These authors were faced with a situation where the full STIM1 protein was apparently impossible to crystalize, so no full structure was available. Worse, some of the prior structural studies of fragments of STIM1 conflicted with each other. So they turned to very clever method to probe structural dimensions point by point, called fluorescence (or Förster) resonance energy transfer, (FRET). If by mutation or chemical modification one installs fluorescent molecules on a protein of interest, indeed installs two different ones, one of whose absorbtion spectrum overlaps with the emission spectrum of the other, one can measure quantitatively the distance between them.

How the FRET fluorescence method works. Different fluorophores are placed on the protein of interest, here the EFSAM luminal domain of STIM1. The absorption spectrum of one (acceptor) overlaps the emission spectrum of the other fluorophore (donor). In the first graph, the green graph shows that when the two are combined on the same molecule, emission from the acceptor goes up dramatically, due to its proximity-dependent absorbance of emissions from the donor fluorophore. The second graph shows how this protein responds to calcium, by increasing interaction (absorbance-emission intensity at 620 nm, reflecting the physical distance between the fluorescence probes) as Ca++ concentration goes down.

 

By placing fluorescence probe pairs all over the external regions of STIM1, these authors were able to definitively refute one of the prior structural models, and then outline the probable sequence of events by which STIM1 opens up into its active form. The image above ably summarizes their model, by which the ORAI1-interacting domain (CC2/CC3) is stored upside-down and inside out in the inactive conformation. It is quite a proposal, all carried out by domains which are alpha helixes hinged at strategic locations and obviously highly sensitive to slight changes in the structure, induced by the dimerization outlined above, in low calcium conditions.

Finally, they investigated a mutation which in humans causes Stormorken syndrome, a wide-ranging set of deficiencies including bleeding, dyslexia, muscle weakness, and hypocalcemia. In molecular terms it is a "gain of function" mutation. It weakens the interactions that keep STIM1 closed during high calcium conditions, so promotes its stimulation of ORAI1 and excess uptake by cells all over the body. The mutation changes argenine at position 304 in STIM1 to tryptophan, which has much different characteristics. It is genetically dominant, meaning that a single allele, combined with a wild-type allele on the other chromosome, gives the syndrome. Thus it is a powerful mutation, tweeking the sensitivity of this system just enough to screw up a lot of physiology. Deletions of this gene are not lethal, however, in part because there is also a STIM2 gene that encodes a similar function.

Analysis of the effect of the Stormorken mutation (R304W) on the physical proximities and overall shape of the STIM1 protein. The FRET graphs track different probe pairs that were placed all over the cytosolic (folding) portion of STIM1. In these graphs, degree of FRET relative frequency shift/communication is on the X axis, while photon counts are on the Y axis. They show noticeable shifts in distances, reflected in the structural model. The mutation significantly loosens up the high-calcium folded state, inducing more Ca++  influx when it is not needed.

So, we are just full of little machines, developed and refined over the billions of years in the ongoing race to live a little better, keep things humming, and to defend ourselves against all the other machines, such as parasitic viruses.

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The RNAs Shall Protect Us

The humble skin mole has at least one oncogenic mutation. But it is not cancer- why not?

We know that mutations cause cancer. But we also know that it takes multiple mutations, not just one, in virtually all cases. This is one reason why age is such a strong risk factor, providing the time to accumulate multiple "hits". One place where this is particularly apparent is the skin. Most people have moles (nevi) and other imperfections, which are no cause for alarm. We are also on the lookout for the unusual signs and forms that indicate melanoma- which truly is a cause for alarm. Moles typically have one of the key oncogenic mutations for melanoma, however: BRAF V600E (which means the 600th amino acid in its protein chain has been changed from valine to glutamic acid). So what is behind the difference? What systems do cells and organs have to keep this train on the tracks, despite a wheel or two coming off?

A recent paper (review) explored this issue, and tells a complicated technical and scientific story. But the bottom line is that certain miRNAs- a novel form a gene regulator discovered just in the last couple of decades- form a firewall against further proliferation. The BRAF mutation is an activating change, which disrupts the normal "off" state of this protein kinase. BRAF is a protein kinase that attaches phosphate groups to serines and threonines on other proteins. And some those other proteins are specifically other (MAP) protein kinases that form cascades promoting cell proliferation and differentiation. In the case of melanocytes in the skin, the BRAF mutation promotes just that: proliferation, mole formation, and, in some cases, progression to full blown melanoma. 

What is a skin mole? Well, it clearly is composed of lots of cells, so whatever is arresting the mutant BRAF-activated proliferation is taking its sweet time. Proliferation goes for a while, but then stops for an unknown reason. It had been thought in the field (and by these researchers as well) that mole cells had gone into senescence- an irreversible division arrest that is frequently activated in cancer cells and is similar to age-dependent cell cycle arrest. But they show now that senescence is not the explanation. If the BRAF mutation state is reversed, the cells resume dividing. And they also have other hallmarks of a different form of (G2/M) cell division arrest. So something more dynamic is going on.

They do a few technical tours de force of modern DNA sequencing and large-scale molecular biology to find what unusual genes are being expressed in these cells, and find two:  MIR211-5p and MIR328-3p. These are miRNAs, which are short RNA pieces that repress the expression of other genes. We have thousands of them, and each can repress hundreds of other genes, forming a somewhat crazy interdigitated regulatory network. They evolved from an immune function of repressing the expression of viruses and other foreign DNA, but have been repurposed to have broad regulatory effects, often in development and disease.

In BRAF-activated skin mole cells, these miRNAs have one effective target, which is AURKB (Aurora B kinase), another protein kinase that is needed for cell division. No AURKB, no cell division. Indeed, skin mole cells have a high rate of cells stuck in the last phase of cell division, with 4 genome equivalents. They found that AURKB has low expression in skin mole cells, but high expression, as expected, in melanoma cells, while the miRNAs had the reverse pattern. And tellingly, artificial inhibition of these miRNAs released mole cells from their proliferation arrest and allowed the BRAF mutation to have its way with them.

Model of this paper's findings about melanocytes. Starting with stem-like melanocytes, mutated BRAF can cause oncogenenic or pre-oncogenic proliferation. Separately, TPA, or some local tissue factor like TPA, can encourage stem melanocytes to grow and differentiate properly into mature melanocytes. But those same activators (TPA and its natural analog) increase miRNA expression of particularly MIR211-5p, which (by inhibiting AURKB) arrests growth as part of the differentiation program, and also shuts down proliferation caused by mutated BRAF, (at late mitosis / G2 arrest), at least most of the time.

But there was still a problem- what activates the miRNA gene expression in the natural setting? It isn't the mutated BRAF protein, since it routinely drives cells through several replication cycles to form moles, and didn't have any regulatory effect on the miRNAs. The researchers focused on the kinds of local secreted hormones, like endothelin, that might locally inhibit overgrowth of cells, and logically lead to a mole-like pattern. What they hit on was TPA, an artificial analog of diacylglycerol, which is an activator of yet another protein kinase, PKC. TPA is paradoxically a tumor promoter, and is routinely used in cell culture systems to goose the proliferation of melanocytes. But for the mutated BRAF- driven cells from moles, TPA arrests their growth, and it does so because PKC activates the expression of MIR211-5p. They showed that taking TPA out of their cell culture mixes dramatically restarted the growth of mole-derived and other BRAF mutation-driven cells. So this closes the circle in some degree, explaining how it is that skin moles form as sort of arrested mini-cancers.

Unfortunately, TPA is not a natural chemical, and diacylglycerol is not hormone, though many hormones, such as thyroid hormone and oxytocin, do affect PKC activity. So the natural PKC and miRNA activator, and inhibitor of excess proliferation in these BRAF mutation-driven melanocytes remains unknown. I am sure that this research group will be hunting diligently for it, since it is an extremely interesting issue not just in oncology, but in skin and tissue development generally.

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• Electrification.
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Supergroups in Search of Their Roots

The early stages of eukaryotic evolution are proving hard to reconstruct.

There is normal evolution, and then there are great evolutionary transitions. Not to say that the latter don't obey the principles of normal evolution, but they go by so fast, and render so many transitional forms obsolete along the way, that there is little record left of what happened. Among those great transitions are the origin of life itself, the origin of humans, and the origin of eukaryotes. We are slowly piecing together human evolution, from the exceedingly rare fossils of intermediate forms and branch off-shoots. But looking at the current world, we are the lone hominin, having displaced or killed off all competitors and predecessors to stand alone atop the lineage of primates, and over the biosphere generally. Human evolution didn't violate any natural laws, but it seems to have operated under uniquely directional selection, especially for intelligence and social sophistication, which led to a sort of arms race of rapid evolution that laid the groundwork for an exponential rate in the invention of technologies and collective social forms over the last million years.

Similarly, it is clear that however the origin of life started out, it was a very humble affair, with each innovation quickly displacing its progenitors, just as the early cell phones came out in quick succession, until a technological plateau was reached from which further development was / is less obvious. While the origin and success of eukaryotes did not erase the prokaryotic kingdoms from which they sprang, it does seem to have erased the early stages of its own development, to the point that those stages are very hard to reconstruct, especially given the revolutionary and multifarious nature of their innovations.

Eukaryotes differ from prokaryotes in possessing: nuclei and a nuclear membrane with specialized pores; mitochondria descended from a separate bacterial ancestor (and photosynthetic plastids descended from yet other bacterial ancestors in some cases); sex and meiosis; greater size by several orders of magnitude; phagocytosis by amoeboid cells; internal membrane organelles like golgi, peroxisomes, lysosomes, endocytic and exocytic vesicles; cyclins that run the cell cycle; microtubules that participate in the cell cycle, cytoskeleton, and cilia; cilia, as distinct from flagella; an active actin-based cytoskeleton, with novel motor proteins; a greatly elaborated transcriptional apparatus with modular enhancers and novel classes of transcription regulators; histones; mRNA splicing and introns; nucleolus and small nucleolar RNAs; telomeres on linear chromosomes; a significant increment in the size of both ribosomal subunits. Indeed, the closer one looks at the molecular landscape, the more differences accumulate. This was quite simply a quantum leap in cellular organization, which happened sometime between 1.8 and 3 billion years ago. Indeed, eukaryotes are not just the McMansions of the microbial world, but the Downton Abbeys- with dutiful servants and complex and luxurious internal economies that prokaryotic cells couldn't conceive of.

Major lineages of eukaryotes are traced back to their origins in a molecular-based phylogeny. Animals (and fungi!) are in the Opisthokonta, plants in the Chloroplastida. So many groups connect right to the "root" of this tree that there is little way to figure out which came first. Also, the dashed lines indicate uncertainty about those orderings/rootings as well, which leaves a great deal of early eukaryotic evolution obscure. Some abbreviations / links are- CRuMs: collodictyonids (syn. diphylleids) + rigifilida + mantamonas; excavates, hemimastigophora, haptista, TSAR:  telonemids, stramenopiles, alveolates, and rhizaria.

A recent paper recounts the current phylogenetic state of affairs, and a variety of other papers over the last decade delve into the many questions surrounding eukaryotic origins. While molecular phylogenies have improved tremendously with the advent of faster, whole-genome sequencing and the continued collection of obscure single-celled eukaryotes, (aka protists), the latest phylogeny, as shown above, remains inconclusive. The deepest root is both uncertain with regard to its bacterial progenitor, and to which current eukaryotes bear the closest relation. There are occasional fossil kelps, algae, and other biochemical traces back to 2.0 to 2.7 billion years, (though some do not put the origin earlier than 1.8 billion years) but these have not been able to shed any light on the order of events either.

Nevertheless, the field can agree on a few ideas. One is that the assimilation of mitochondria (whether willing or unwilling) is perhaps the dominant event in the sequence. That doesn't mean it was necessarily the first event, but means that it created a variety of conditions that led to a cascade of other consequences and features. The energy mitochondria provided enabled large cell sizes and the accumulation of a whole new household full of junk, like lipids in several new membrane compartments. The genome that they contributed brought in thousands of new genes, including introns. 

Secondly, the loss of cell walls and the adoption of amoeboid carnivory is likely one of the first events in the evolutionary sequence. Shedding the obligatory cell wall that all bacteria have necessitates a cytoskeleton of some kind, and it is also conducive to the engulfment of the proto-mitochondrion. For while complicated co-symbiotic metabolic arguments have been devised to explain why these two cells may have engaged in a long-term mutual relationship long before their ultimate consumation, the most convenient hypothesis for assimilation remains the simplest- that one engulfed the other, in a meal that lasted well over a billion years.

Thirdly, the question of what the progenitor cell was has been refined somewhat. One of the most intriguing findings of the last half-century of biology was the discovery of archaebacteria (also called archaea)- a whole new kingdom of bacteria characterized by their tendency to occupy extreme habitats, their clear separation from bacteria by chemical and genetic criteria, and also their close relationship to eukaryotes, especially what is presumed to be the original host genome. Many proposals have been made, (including that archaea are the original cell, preceding other bacteria), but the best one currently is that archaea split from the rest of bacteria rather late, after which eukaryotes split off from archaea, thus making the latter two sister groups. This explains the many common traits they share, while allowing significant divergence, plus the incorporation of many bacterial features into eukaryotes, either through the original lineage, or by later transfer from the proto-mitochondrion. So here at last is one lineage that survived out of the gradual development of eukaryotes- the archaea, though one wouldn't guess it from looking at them. It took analysis at the molecular level to even know that archaea existed, let alone that they are the last extant eukaryotic sister group.

A comically overstuffed figure from an argument for the late development of archaebacteria out of pre-existing bacteria (prokaryotes), with subsequent split and diversification of eukaryotes out of a proto-archaeal lineage. Many key molecular and physiological characters are mentioned.

Lastly, surveying the various outlying protist lineages for clues about which might hearken back to primitive eukaryotic forms, one research group suggests that the collodictyonids might fit the bill. Being an ancient lineage means that it is lonesome, without a large family of evolutionary development to show diversification and change. It also means that in molecular terms, it is highly distinct, branching deeply from all other groups. Whether that all means that it resembles an ancient / early form of the eukaryotic cell, or went its own way on a unique evolutionary trajectory, is difficult to say. For each trait, (including sequence traits), a phylogenetic analysis is done to figure out whether it is differential- shared with some other lineages but not all- whether those without the trait lost it at some later point, or whether it was gained by a sub-group. After analyzing enough such traits, one can make a statement about the overall picture, and thus the "ancient-ness", of an organism.

Is anything special about collodictyon? Not really. It is predatory, and has four flagella and a feeding groove, which functions as a sort of mouth. It can make pseudopods, has normal microtubule organizing centers for its flagella, and generally all the accoutrements of a eukaryotic cell. It lacks nothing, and thus may be an early branching eukaryote, but is not in any way a transitional form.

An unassuming protist (collodictyon) as possible representative of early eukaryotes. Its cilia are numbered.

At this point, we are left still peering darkly into the past, though obscure living protists and their molecular fossils, trying to figure out what happened when they split from the bacteria and archaea. A tremendous amount happened, but little record survives of the path along the way. That tends to be characteristic of the most momentous evolutionary events, which cause internal and external cataclysms, (including the opening of whole new lifestyles to exploit), that necessitate a rapid dynamic of further adaptation before their descendents achieve a stable and successful state sufficient to ride out the ensuing billion or more years ... before we come on the scene with the ability and interest to contemplate what went before.

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Alzheimer's: Wnt or Lose

A molecular exploration of the causes of Alzheimer's disease.

What causes Alzheimer's disease remains a bit of a mystery, as there is no simple and single molecular explanation, as there is with, say, Huntington's disease, which is caused by a single gene defect. There is one leading candidate, however, which is the amyloid protein, one of the accumulated molecular signatures of the disease in post-mortem brains. Some genetic forms of Alzheimer's start with defects in the gene that encodes this protein, APP (amyloid precursor protein). And a protease processing system that cleaves out the toxic amyloid beta protein from the much larger original APP protein is also closely involved with Alzheimer risk. So while there are many other genetic risk factors and possible causes relating to the APP and other systems, this seems to be the dominant causal element in Alzheimer's disease.

The naming of this protein is rather backwards, focusing on the pathological roles of defective forms, rather than on what the normal protein does. But we don't really know what that normal function is yet, so have had little choice. A recent paper described one new function for the normal APP protein, which is as a receptor for a family of proteins called WNT (for wingless integration site, an obscure derivation combining findings from fly and mouse genetics). APP had long been known to interact with WNT functions, and a reduction of WNT signaling is one of the pathologic (and possibly pathogenic) hallmarks of Alzheimer's, but this seems to be the first time it has been tabbed as a direct receptor for WNT.

What is WNT? These proteins track back to the dawn of multicelled animals, where they first appear in order to orchestrate the migration and communication of cells of the blastopore. This is the invagination that performs the transition (gastrulation) from an egg-derived ball of cells to the sheets of what will become the endoderm and mesoderm on the inside, and the ectoderm on the outside. The endoderm becomes the gut and respiratory organs, the mesoderm becomes the skeleton, muscles, blood, heart, and connective tissue, and the ectoderm becomes the skin and nervous system. WNT proteins are the ligands expressed in one set of cells, and their receptors (Frizzled and a few other proteins) are expressed on other cells which are nearby and need to relate for some developmental / migration / identification, or other purpose. One other family, the NOTCH proteins and their respective cell surface receptors, have a similar evolutionary history and likewise function as core developmental cell-cell signaling and identification systems. 

Rough structure of the APP protein. The membrane  spanning portion is in teal at the bottom, showing also some key secretase protease cleavage sites, which liberate alpha and beta portions of the protein. The internal segment is at bottom, and functions, when cleaved from the rest of the protein, as a nuclear transcription activator. Above are various extracellular domains, including one for "ligand binding", which is thought by at least one research group to bind WNT. The dimerization domain can bind other APP proteins on other cells, and heparin, another binding partner is a common component of the extracellular environment.

Fast forward a billion years, and WNT family members are deeply involved in many decisions during animal development and afterwards, particularly in the brain, controlling nerve cell branching and synapse formation in adults. WNT, NOTCH, and APP are each ligand+receptor systems, where a ligand from one cell or in soluble form binds to a receptor on the surface of another cell, which "receives" the signal and can do a multitude of things in response. The usual receptors for WNT are a family of Frizzled proteins plus a bunch of other helper proteins, the receptors for NOTCH are Jagged proteins, and the APP protein is itself a receptor whose ligand has till now been unclear, though it can homodimerize, detecting APP on other cells. APP is a large protein, and one of its responses to signals is to be cleaved in several ways. Its short cell-interior tail can be cleaved, (by gamma secretase), upon which that piece travels to the nucleus and with other proteins acts as a transciption regulator, activating, among other genes, its own gene, APP. Another possible cleavage is done by alpha secretase, causing the release of soluble APP alpha (sAPPα), which has pro-survival activities for neurons and protects them against excessive activity (excito-toxicity). Lastly, beta-secretase can cleaves APP into the toxic beta (Aβ), which in tiny amounts is also neuro-protective, but in larger amounts is highly toxic to neurons, starting the spiral of death which characterizes the hollowing out of the brain in Alzheimer's disease.

The cleavages by alpha secretase and beta secretase are mutually exclusive- the cleavage sites and products overlap, so cleavage by one prevents cleavage by the other, or destroys its product. And WNT signaling plays an important role in which route is chosen. WNT signals by two methods, called canonical or non-canonical, depending on which receptor and which ligand meet. Canonical signaling is neuro-protective, opposed to Alzheimer development, and leads to alpha secretase cleavage. Non-canonical signaling tends to the opposite, leading to internalization of APP from the surface, and beta secretase cleavage which needs acidic conditions that are found in the internal endsomes where APP ends up. So the balance of WNT "tone" is critical, and is part of the miscellaneous other risk factors that make up the background for Alzheimer's disease. Additionally, cleavage by gamma secretase is needed following cleavage by beta secretase in order to make the final forms of APP beta. The gene for gamma secretase is PSEN1 (presenilin-1), mutations in which are the leading genetic cause of Alzheimer's disease. Yet these mutations have no clear relation with the activity of the resulting gamma secretase or the accumulation of particular APP cleaved forms, so this area of causality research remains open and active.

But getting back the WNT story, if APP is itself a WNT receptor, then that reinforces the centrality of WNT signaling in this syndrome. Indeed, attempts to treat Alzheimer's by reducing the toxic amyloid (APP beta) build up in various ways have not been successful, so researchers have been looking for causal factors antecedent to that stage. One clue is that a key WNT inhibitor, DKK (for dick-kopf, derived from fly genetics, which have had some prominent German practitioners), has been experimentally an effective therapy for mice with a model form of Alzheimers. DKK is an inhibitor of the canonical WNT pathway, (via the LRP6 co-receptor of Frizzled), shunting it towards more non-canonical signaling. This balance, or "tone" of WNT signaling seems to have broad effects in promoting neurite outgrowth and synapse formation, or the reverse. Once this balance is lost, APP beta induces the production of more DKK, which starts a non-virtuous feedback cycle that may form the core of Alzheimer's pathology. This cycle could be started by numerous genetic defects and influenced by other environmental risk factors, leading to the confusing nature of the syndrome (no pun intended!). And of course the cycle starts long before symptoms are apparent and even longer before autopsy can verify what happened, so getting to the bottom of this story has been hugely frustrating.

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The Hunt for Enemy RNA

How our cells tell foreign RNA from friendly RNA, in a truly baroque process.

RNA is hot these days. It is the active ingredient of the leading and innovative coronavirus vaccines, it appears to be the primordial molecule at the origin of life, and it keeps cropping up in new permutations in molecular biology, with every year bringing new acronyms for novel roles it plays in our cells. Half of viruses use RNA for their genomes, making it an important target of the immune system as well. We have several mechanisms that sense viral RNAs, and likewise several mechanisms to differentiate self-RNA from foreign RNA. It is evident that an arms race of military intelligence has been taking place over the evolutionary eons. 

Among the common ways we have to tell friendly RNA from foe are special "caps" chemically attached to the front end of message RNAs, further methylation modifications of the front end of RNAs, and the existence of double-stranded RNA, which is generally rare in our cells. Most RNA viruses have single-standed genomes, but they usually have a double-stranded RNA intermediate in their replication process. Eukaryotic cells focus intently on recognizing that double-stranded RNA, doing so with proteins named RIG1 and MDA5. RIG1 is an RNA helicase that binds and recognizes double-stranded RNA, and then triggers the production of interferons, the primary signaling molecules telling cells that there is a viral infection, and which induce production of a wide range of other antiviral proteins.

But with our own RNA all over the place, it naturally happens that some double-stranded RNA forms accidentally, from our own sequences. What to do about that? One mechanism is RNA editing, where selected "A" residues are chemically switched to "I" or inosine, which base pairs differently from A, and destabilizes double-stranded RNA. This editing is performed by an enzyme called ADAR1. For coding mRNAs, these edits can alter their meaning, so it is also called RNA recoding, and  routinely affects the sequences of several important proteins. 

ADAR gene products and isoforms (left) all perform RNA editing of A (adenine) to I (inosine) in double-standed RNA regions of self-RNAs, (right), to prevent them from causing false alarms of our internal antiviral surveillance systems.

Another mechanism to protect friendly RNA is the attachment of methyl groups to A residues, (m6A), which also shields them directly from RIG1 surveillance. The m6A modifications are applied by enzymes METTL3 and METTL14, and are detected by YTHDF1, which binds them and can increase their expression by speeding up translation, or destabilize them, or have other effects on their expression. The logic of the various proteins that recognize m6A modifications is diverse and remains rather unclear, actually, though the general trend is one of increasing expression of recognized messages. 

One has to suppose that these editing and modification systems are relatively slow, so that incoming viral RNAs can be recognized before they themselves are modified and turned into invisible infiltrators. So there must be some very careful tuning involved, and great incentives for viruses to encode such modification systems for themselves. For example, coronaviruses encode in their tiny genomes several proteins that put "friendly" chemical caps on the front ends of their own RNAs.

Getting back to the editing and m6A systems, genetic mutations generating defective ADAR1 cause severe auto-immune disorders, where the anti-viral interferon system is over-activated. What recent researchers found curious, however, was that defects in YTHDF1 cause similar effects, over-activating antiviral immune systems, even though YTHDF1 is not inherently part of the core systems of protecting self-RNA from recognition by all these antiviral detectors. It turns out that YTHDF1's effect is mediated by just one of its gene targets- ADAR1. Translation of the ADAR1 mRNA is enhanced by YTHDF1 after it binds to m6A modifications on that mRNA. This in turn promotes the ADAR1- catalyzed edits of other cellular RNAs, especially double-stranded ones, preventing them from getting caught up in the RIG1-activated red alert system of interferons and viral response.

In this way, one system of self-identification and protection is tied into another system, for reasons that are truly hard to fathom, and are only a tiny part of a far more elaborate system. I think it is an example of evolution run amok, developing one bureaucracy on top of other ones, on top of yet other ones, in a gerry-rigged system that has had billions of years to accumulate. Yes, it is all very finely tuned, thanks to the necessities of natural selection and the struggle against predation by invaders. But it is the farthest thing from being designed.

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