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The life cycle of HIV in 3D [video] (scientificamerican.com)
306 points by duncanmeech on May 3, 2018 | hide | past | favorite | 70 comments



As a technologist, I have mixed feelings when I see the fascinating details of life. On one hand, mastering this molecular machine would give us literally God-like powers: we could fabricate, grow or heal anything. We could solve all current problems, we could terraform planets using a few milligrams of DNA and literally redefine what it means to be human.

On the other, I see the human body as a completely unsecured cybernetic system, that can be so easily tricked to pick up any random bit of programming and insert it into it's own code. There is no forethought or design, no rational defense, just good enough systems that have evolved randomly against non-rational adversaries that happened to emerge out of the protein soup surrounding us.

The troubling fact is that mastering the wondrous biomolecular machine necessarily comes with the power to kill every human on the planet. Truly God-like powers.


> power to kill every human on the planet. Truly God-like powers.

You can't really design a perfect virus that will wipe out the human race, because anything you do to affect its properties will also affect its ability to spread. I'd be way more concerned about the destructive power of nuclear weapons, still numerous enough to destroy a very large part of humanity and our vital infrastructures.


Are you sure you aren't still thinking in the conventional, evolutionary paradigm?

A highly engineered bioweapon could circumvent such problems by separating the infection phase (which could be completely silent and airborne) from the eradication phase. The payload could be triggered deliberately at a later date when a certain secret artificial protein is released in the environment - and then produced in industrial quantities by infected hosts. Or maybe airdropped over areas that should be cleansed.

And that's just scratching the surface of what's conceptually possible. It could trigger specific ethnic characteristics or individuals, it could set up exotic cyber-hybrids like public key decryption in DNA for commands from its command and control. It could create side channels among infected hosts, for example by triggering minute anatomical modifications in the inner ear and the vocal centers, making them able to send and receive ultra- or infrasounds controlled by the mallware.

As a more subtle cyberattack, an infected individual could grow a whole parasitic subsystem that extracts select visual and auditory data and stores them in DNA memory for later broadcast.


Wow these are novel concepts, do you read a lot of sci fi? How did you come up with these interesting scenarios?


I'm not really inspired by scifi - but I'm sure some authors have had similar and probably much wilder ideas.

Been thinking for years about the human body as a cybernetic attack surface with no engineered cyberdefense. Most people seem not able to make that mental leap; no, the human body can't behave like a vulnerable Windows 95 machine giving kernel privileges to any ActiveX control it can download, because reasons.

But once you see the biological world like a hacker and DNA like a programming medium, as opposed to a representation of what evolution produced, an endless array of nefarious possibilities become obvious. The rational power of our minds far exceeds what evolution could ever concoct - or defend against.


To be fair, that argument depends on the properties of evolved pathogens. A designed pathogen, in the context of the GP post, would not necessarily be bound by that dilemma.


What would prevent the development of something like HIV that’s able to spread through the air like the flu?


slower replication speed, more difficulty infecting the host, requirement of much greater volume of replication to accomplish the same rate of infection.

think of it this way: every cool feature you add to a living thing has an overhead.

you want your little bacteria to have antibiotic resistance? fine.

but it'll need that much more energy to grow relative to the bacteria which don't have the added burden.

this means that unless there's the selective pressure of antibiotics in the environment, your little antibiotic resistant microbe won't stand a chance -- it's a fraction less efficient under normal conditions, so it's effectively out-competed when in the wild.

as far as massive adaptations like airborne spreading, that's not something that can just mutate overnight. HIV is fragile, so you'd need to engineer an entirely new viral envelope, or, more likely, an entirely new carrier particle that the virus can reconstruct on its own without impacting its infectivity. viruses like the flu have these adaptations by default. but once again, if you decide to turn the flu into HIV, it's going to be at a disadvantage in the wild.

not to say that it is impossible to make virions which are able to out-compete their wild-type cousins when infecting hosts in the real world. far from it. it's just not as easy to make it work as a quick look might find.


What would be the overhead for just something "simple" though? Like making HIV airborne? (Or rather what the lay person perceives as a small change)

It seems like there are plenty of diseases out there where a (apparently) "small" modification could have a dramatic effect on how it spreads. And I'll admit my naivety to the subject and do not know if such small changes are actually small, or the related overhead associated with them.


to answer your question, the overhead is very small for a small change. you can add a bit of noncoding DNA to a virus' genome without ruining its ability to compete in the wild. but the survival margins are very thin. on a population scale, natural selection is very harsh. anything that is superfluous given the environment is an inefficiency which eventually results in extinction. of course, between organisms this isn't that frightening because there are different niches, so sometimes a large change can be more viable than a small change even if it's a lot more expensive, provided that the large change lets the organism live in a new niche.

making HIV airborne isn't a simple change, however. it's more like a massive change of niche. it's a change in the transmission modality of the virus -- for comparison, consider the scale of the changes you'd need to make to turn a car into a plane. or maybe a car into a boat.

it's doable, artificially. but the result won't be as good at being a car, plane, or boat as something which was purpose-built for that application and didn't have to carry the features of something intended for a different purpose.

many of the "small" changes that make a disease spread more easily are actually mutations which don't change the ability of the disease to weather external conditions, but rather change the ability of the disease to survive first contact with the host's immune system.

the flu is a great example here. we need a new flu vaccine every year because the flu mutates constantly and drastically. the flu never becomes capable of surviving outside a host for longer than before, though. it just becomes more effective at evading the immune systems of most hosts.


What about starting with the flu and giving it an HIV-like ability to wreck your immune system? Is the “attack” part too intertwined with everything else to be able to do that sort of mix-and-match operation?


the flu gaining deadlier characteristics via engineering is more realistic. unfortunately, i believe that is well within the scope of our present capability. the exact magnitude of how dangerous such engineering could make a virus based on the flu is unclear to me, but i'd estimate somewhere between "globally apocalyptic" and "continentally destabilizing".

the mixing and matching of attack characteristics is probably possible under certain circumstances, but i don't know of any specific instances where it has been done. theoretically, it's easy to swap A for B, but making such changes nearly always has unintended downstream problems.

in the lab we used to do all sorts of mixing and matching, but for defensive characteristics (mostly to see if certain isomorphs were more vulnerable than others).

long story short, generating virus and isolating it is a real PITA for a slew of reasons. experimental cycles might be as long as a week for each trial of "mixing and matching".


How comforting! Thanks for all the info.


> You can't really design a perfect virus

Just design several good-enough viruses.


Interestingly the Gene Regulatory Network (GRN) - the interaction of genes and proteins that control the prosess inside the cell is computationally very similar to recurrent neural network. Gene expression levels is controlled by proteins that are produced by active genes. https://en.wikipedia.org/wiki/Gene_regulatory_network

Harnessing this mechanism directly for neural computation would be grand project.


I think it's a bit of a stretch to say GRN is "computationally similar" to neural networks. That seems to be a shoehorn of the most popular technology of one field into another field.

Just because the GRN contains feedback loops with multiple influences doesn't mean it's suited to NN computation. The GRN is orders of magnitude more complex than computational NNs and it is orders of magnitude slower than signal transduction of axons.

I agree it will be awesome to be able to harness molecular machinery to "do stuff" for us. The "nanotechnology" in our bodies is way beyond any current manufactured nanotechnology.

We currently have only crude control of the cellular functionality -- think point a wind up toy in the direction we want or modify it by taping a flashlight to the top. We are pretty far from being able to use the manufacturing equipment to make cars instead of windup toys. (Not to mention the manufacturer is already making rockets)


> That seems to be a shoehorn of the most popular technology of one field into another field.

Recurrent neural network is used to model gene regulatory network. It's not a shoehorn.

See for example:

[1]: Reconstruction of Gene Regulatory Networks from Gene Expression Data Using Decoupled Recurrent Neural Network Model https://link.springer.com/chapter/10.1007/978-4-431-54394-7_...

[2]: Gene regulatory networks inference with recurrent neural network models https://ieeexplore.ieee.org/document/1555844/

[3]: Recurrent Neural Network Based Modeling of Gene Regulatory Network Using Bat Algorithm https://arxiv.org/pdf/1509.03221.pdf

> The GRN is orders of magnitude more complex than computational NNs and it is orders of magnitude slower than signal transduction of axons.

It's possible that we can reduce relevant complexity to the RNN subset that it useful. Feedback loop speeds are slower but they can be below second.

In many search and optimization problems the ability to run say 100 trillion large stochastic RNN's in parallel in a 100 liter tank could be huge. Especially if all you need is glucose and few cheap nutrients to power it.


The articles you cite start with experimental data about Gene regulatory networks (eg from dna microarray) and then use rnn to characterize or produce the networks known or elucidated experimentally.

None of the sources claim functional equivalence of the GRN by the RNN or vice versa.

From a "big O" computational complexity perspective the gap between what you are describing and the actual case is the gap between P and NP. Just because we can confirm the results of a GRN with an RNN doesn't mean we can produce those results.

Yes, biological computing could harness very powerful parallelism. We are nowhere close to harnessing that power. (See toy manufacturing analogy)


I think articles like Ken Shirriff's "Cells are very fast and crowded places"[1] are good companions for visualizations like this. It helps to keep in mind that the things moving around in cells are flying around at break-neck speeds if you scale them up linearly.

1 - http://www.righto.com/2011/07/cells-are-very-fast-and-crowde...


Where "flying around" means "constantly bumping into everything else". This means small stuff doesn't just fly around the cell, it has to diffuse through it. A nice side effect is that eventually, everything gets into contact with everything else. That, as I understand, is how small molecules get to their right place.

Also, this means that it's too tight for large stuff to move around at all. Hence the specialized machinery within the cell that transports large molecules.

Source for both: I'm 1/3d of th way through The Machinery of Life[0]. Incidentally, I learned about this book from HN. It's absolutely amazing. The biggest selling point are the drawings - David S. Goodsell created a lot of illustrations (like these[1]) that give you a good perspective on how stuff is packed within cells.

EDIT: that blog post you linked covers the diffusion aspect well, I second the recommendation to read it.

--

[0] - https://www.goodreads.com/book/show/6601267-the-machinery-of...

[1] - http://mgl.scripps.edu/people/goodsell/illustration/public


Yeah, thinking about incidental chemistry occurring due to many collisions at or near the speed of sound while packed into a fluid solution or compressed gas, definitely puts things in perspective, in terms of how specifically matched and optimized everything needs to be, in order to be fortuitous as an otherwise unplanned event.

It's like stumbling into elevator after elevator, while running the hundred yard dash at top speed, everywhere you go, only to encounter the perfect dance partner to fall in love with at first sight.


This is a really great share! Truly mindblowing.


Absolutely insane how this is actual reality. That millions of people have died from such a small object that seems to have more creativity and complexity than I’ve ever seen.


You might enjoy: Influenza A (H1N1) – How many bits does it take to kill a human? https://www.bunniestudios.com/blog/?p=353


Also, video: https://www.youtube.com/watch?v=NPr-i-IbA7s

This one is about Influenza: https://www.youtube.com/watch?v=7Omi0IPkNpY (not H1N1, but quality is better)

I learned a lot today (At least that's what I felt) LOL


Thanks for sharing. That’s terrifying. I feel like this should be read by more people.


My favourite cell documentary is this. Has more information about the various transport mechanisms in the cell itself. Simply awesome - have watched several times to understand better. See https://www.youtube.com/watch?v=FzcTgrxMzZk


The amazing part for me was that virus "code" automatically finds the unrelated host "code" in what is effectively an equivalent of space travel inside a host body, does copy and paste to insert itself somewhere in host code and everything just works! I can't think of any of our computing models that is capable of doing this and so robust at errors.


Lisp


Wait, it is really interesting may HIV can solve N=NP problem


I know it's just my own biased anthropomorphizing but the virus almost looks sinister and intentional in its actions.


Agreed. These Harryhausen-like creatures are every bit as menacing as the Kraken. I naively failed to realize the deadly complexity (genius) of the HIV virus. Well done piece.


The music really helps with that. The video gave me a spooky feeling.


Ha, I didn't even watch it with sound. Will have to do that when I get home.


I would love to know how this animation was made. Is there any sort of simulation happening?


It's two separate things, both mentioned in your question: simulation then animation. Both steps are computationally expensive enough that they can't be done in one run.

For simulation, typically a molecular dynamics code is used along with features specific to biological analysis (since MD by itself is a physics simulator). NAMD is one of the well-known MD tools used for bio work. Depending on the complexity and features/accuracy sought, a whole host of other tools might be involved. The timeframe of simulation is of the order of weeks to months given massive computational power (e.g., a large allocation on one of the national supercomputing grids).

Once tons of simulation data is generated (as the output of simulation), then 3D visualization tools can be used. NAMD has a sister vis tool called VMD. Blender is another option. Incidentally, Janet Iwasa (the narrator and researcher behind this work) is a visualization expert, so it's likely she only worked on the second step (animation) by using existing simulation data, or collaborating with a simulation group. (Again the computation required for rendering is very high, on the order of days to weeks using a large allocation on a supercomputer).


Drew Berry creates similar animations and refers to them (in this talk) as "accurate representations", but doesn't go into much detail. Interesting history in the beginning as well. https://www.youtube.com/watch?v=WFCvkkDSfIU


Yes, that was my first thought as well. I'm curious what parts are accurate and what parts are simplifications for ease of visualization and comprehension. Colors are clearly not representative. What about movements? Relative speed of movements? Shapes? Density? If we could see these processes in some magical microscope would this look close to what is happening or not?


Makes one really wonder just what, exactly, is out there mindlessly gobbling and reproducing itself in an endless quest to just keep going. Puts human life in perspective too. We're all just mindless gobblers when zoomed out enough.


Hard to believe that no one has programmed this. Evolution is insane.


If you look at a "program" in a more abstract way and recognize that evolution is declarative it's a bit easier to reconcile.


Seems that you are not a programmer. Even with Intelligence people can write code (much much simpler and buggy) how can chaos build such a complex thing? Can you answer what was first? information (RNA/DNA) or the first cell?


What makes you think I'm not a programmer? I was marveling at how evolution can lead so something so systematic.

> Can you answer what was first? information (RNA/DNA) or the first cell?

No I can't. What are you getting at?


Question. How is that even knowing the lifecycle of HIV at this level of detail, there is not a cure for it?



>in the U.S. HIV kills 10,000 people per year

I remember an early passage from Buckminster Fuller's Grunch of Giants where he tells the reader to visualize fully packed stadium and explains that's what 10,000 people looks like.


I'm not sure 10,000 packs a stadium in the US. Maybe the bleachers of a high school football stadium.


Ha, my thoughts were similar to yours but in the opposite direction: With such complicated machinery being involved in every part of micro biology, how can humans ever hope to cure anything? Everything down there is so complex, fast and intricate and we're stuck up here able to interact with it only in the most brute force and imprecise ways.


I think the general strategy to fight HIV is to try to disrupt one or two key events of the process. https://en.wikipedia.org/wiki/Management_of_HIV/AIDS


Yeah, that's what I would imagine, it is a chain of events so you could disrupt the process breaking one step, which one? I can't tell. But I know for sure that we are smarter than those micro organisms trying to do their thing :)


One major issue is the fact that reverse transcriptase, which copies the HIV genome inside the cell, is sloppy and makes lots of mistakes. As a consequence, every viral particle produced is a little different. A drug that targets any given HIV protein to disrupt it, will work on most particles, but there’s always some that carry mutations that allow them to escape. The solution is to treat with multiple orthogonal drugs.

However,a second major issue is what’s mentioned in the movie, that the viral genome integrates into the host genome and can lie dormant for years. So even if you kill off every single viral particle, years later new particles can be produced from the dormant genome.

A third major issue is that HIV specifically infects T cells, which are the very immune cells that are supposed to combat infection. This weakens the natural defenses, and also makes it difficult to create a successful vaccine.


I would think that once you kill all infected T-cells, yo got rid of all infection?


I doubt a body can completely rid itself of HIV but once you get rid of all infected T-cells you've Acquired Immune Deficiency Syndrome.


One of the problems is that HIV stitches it's DNA into the cells DNA. The result is a latent infection reservoir that can last decades.


the crazy thing is that's not even the main part of the "viral reservoir."

even when medicated -- for decades -- viral particles hang out safely in the body, often in the lymph nodes. as soon as the medication stops, they bounce back.


When I see the animations I can't stop thinking about a Turing machine. How it works in a similar fashion, copying symbols to keep track of the program while generating the result in the process.

It will be nice to know if you can build a Turing complete machine using DNA and the cellular mechanisms. https://www.quora.com/Is-DNA-a-Turing-machine


Here's the video on vimeo https://vimeo.com/260291607


Related to this type of animation, there is a great book called "The Machinery of Life" that talks abut molecular level biology with amazing illustrations. https://www.amazon.com/Machinery-Life-David-S-Goodsell/dp/03...


A better animation is the winner of the AutoPACK challenge few years back: https://vimeo.com/62635232

Those guys did an awesome job because: a) use of brownian motion b) sick af music.


That's a poor visual of Brownian motion. Things don't giggle they randomly fly around at ~250 miles an hour.

It's still a great video just IMO misleading in its own way.


Mindblowing. To think that chance+time produced something like that is staggering.


Chance+time also created a network of trillions of similar things that are now comprehending this sentence right now. It's absurd.


+reproduction +selection


I haven't yet seen a good explanation as to why this focus on randomness is so prevalent, but chance really is almost irrelevant when it comes to evolution.

The main mechanisms of reproduction and selection that you point out have almost no randomness at a population level.

Selection of individuals has some randomness associated with it, as death can come unexpectedly to anyone, but at population levels it is the genes that make it more likely for an individual to survive/pass on their genes that are the ones that get passed on. It's possible that an entire population gets wiped out, or a particular gene gets wiped out due to chance, but as long as the population is reproducing then on average the genes that are passed on are the ones that help the population survive.

Similarly reproduction isn't random at population levels either. Sexually reproducing populations mix their surviving genes evenly within geographical locations over evolutionary timescales (such as trees), or selectively if individuals choose their mates (like humans!). Neither of those things are random. Mutations that happen during reproduction are somewhat random but, as for asexual populations, the amount of mutation at the population level is not random. It's reasonable to expect the reproductive mechanisms to be selected for in such a way to maintain coding errors and the like (at an appropriate level) so that mutations continue to develop and strengthen the gene pool.

While there are lots of single events where randomness and chance come into play, as soon as you have a collection of things that reproduce those things must either get better at reproducing or cease to exist. Chance has nothing to do with it.


ENTROPY BABY.


Living in 2018 is quite a privilege. Most microbiologists who spent their lives trying to puzzle this out won't get to sit back and watch the answer.


This is why I'll never go on tinder or screw around, frightened about getting stds. My friends act like STDs are no big deal and joke around about the times they've contracted chlamydia and gonorrhea etc like it's a cost of doing business (getting laid).

I'll stick to long term relationship.


Amazing! So there is self-replicating, self-modifying code (HIV quickly mutates to avoid detection) code, that sometimes jumps into middle of an instruction (GAG proteins being cut into the enveloping proteins).


Wow that gives me shivers, creepy.


That looks scary. VERY scary!




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