How NOT To Think About Cells

A few years ago Veritasium posted a video portraying 'molecular machines'. But is that really the right way to think about the inner workings of our cells? Are we all just running on molecular clockwork?

SOURCES + FURTHER READING:

CORRECTIONS:

5:09 - This is not actually a map of metabolic reactions in the cell, but rather a map of various signalling pathways.
6:11 - I should have said “parts of the ribosome” (certain ribosomal proteins) moonlight in the nucleus not the whole ribosome itself.

#veritasium #cell

[SubAnima]

Responses to some of the common critiques I've gotten:

*1. I disagree with your definition of a "machine."*

I was deliberately vague on how to define what a machine is. I plucked out two key features (has static + specific parts) purely because this is how the metaphor is being used to do work in biology today. These are both wrong and are actively misleading people, as I explained in the video.


All in all, the point of the video was to help us conceptualise the cell more accurately, not get into the metaphysical weeds about what a machine is.


*2. Drew Berry's animations are commonly considered to be very accurate, why did you call them misleading?*


Nonetheless, I still call Drew's animations misleading. Not because they're inaccurate but because of how they influence us to think about the cell. We see proteins moving like clockwork and then begin to think that the whole cell behaves that way. Everything must be running on clockwork, with static, specific gear-like pieces. Case in point, the Veritasium comments I put on screen.

This is wrong, and should not be the mindset we aim towards. Hence, the animations are misleading.

*3. What's your solution then?*

No theory will continue to produce knowledge forever. There comes a time when the gold begins to run out. Some may disagree with me on this stating that we seem to be in a 'golden age' of data for biology. I would counter that and say that we still have no idea how to put the data together. And we are no closer to answering the tagline of this channel: what is life?



"The cell is not a machine, but something altogether different—something more interesting yet also more unruly. It is a bounded, self-maintaining, steady-state organization of interconnected and interdependent processes; an integrated, dynamically stable, multi-scale system of conjugated fluxes collectively displaced from thermodynamic equilibrium."

There are also many alternate metaphors we could employ e.g. a stream, a vortex, a fire. None of these are perfect either, but they capture the processual nature of organisms that much better.

*4. You've completely ignored how successful the machine metaphor has been!*

Yes I have, because you can get that from pretty much any other YouTube biology channel, paper or high-school textbook. Machine talk in biology is everywhere, it needs no introduction. If you’d like to make your own video talking up how good the machine metaphor has been, be my guest.

All I am saying is that the “cell=machine” seam is running out of gold. If we acknowledge that reality and begin to look elsewhere, we might just find a whole lot more gold.

[thomasmurphy]

Speaking as a budding biochemist, I agree with 90% of this video with the big exception that the pathway maps were made to “make us feel more optimistic about what we can understand.” At least for real scientists, no not at all. We use these maps to chart out what we know to be a subset of known protein interactions, from a much larger set of known and unknown interactions, in order to help designing experiments about particular interactions.

[marceloorlando]

As a PhD student in biophysics I constantly use these analogies betweens biological processes and engineering systems, never have I claimed that the cells behaves exactly according to those models, but such analogies are incredibly usefull and allow us to apply shitloads of methods and protocols used for decades in systems engineering to better understand the complexity of living things

[trimarcopolo]

From a molecular point of view those types of animations are extremely valuable. In the field, we are all aware that brownian motion and microscopic reversibility are always present. Depicting the overal trend, however, allows us to better understand the process. Of course, they dont depict the full picture, but in most cases this is not needed.
Anyway we could say that molecules are so small we cannot directly observe them, therefore, any visual represenration of them is wrong. But we need some level of abstraction to understand and communicate things, don't we?
Now about the definition of molecular machines, this term is widely used in academia (it was even awarded a nobel prize in chemistry in 2016). The fact that they are not static doesn't mean that we cannot regard them as machines, but rather a new type of them operating under a different set of rules due to their size. And I think that there is the beuty of these things, we don't limit them to the macroscopic description of machines, but we rather expanded the concept of machines to the molecular level.

[MJS-lkej]

the one critique I have is when you said "proteins aren't really solids but more jiggly liquids" this is a misnomer. phases of matter are an emergent macroscopic phenomenon, it emerges from layers of specific structures of molecules. calling proteins, which are singular molecules (admittedly a drastic simplification) a specific state of matter is akin to calling a chemical reaction a specific state of matter, you can't because they are both sub-macroscopic, they come together to form the macroscopic.

[CrazyLinguiniLegs]

My proteins don’t jiggle, jiggle; they _fold_

[PearlyBarley]

Nice! The metaphor is exactly backwards: living systems aren't complicated machines. Machines are extremely simple mechanical systems. Simple mechanical systems are qualitatively different from complex living systems. Very few people getting engineering degrees are being taught systems theory, so they approach the horse from behind and wonder why it doesn't seem to have any interest in hay.

[Saleca]

Just because its jiggly, multitasking and shapeshifting doesn't mean it isn't machine like. Ironically Veritassium also made a video on soft machines.. and after all its not man made machine, is just machine like metaphorically.

[TheEpicRandomGuy]

While I do appreciate a critical view of science communication, this video seems to avoid engaging with the reason why models like this exist in the first place. They simply give us the best chance of making useful conclusions. If there is a superior model for something scientists will generally trend towards using it. By stating only “here is where all of the scientific models have failed.” This video seems to beg the question: “Maybe we should stop trying to understand things?” Kind of a suspiciously vague take imo. That being said, I do want to thank you for putting together a video about your thoughts, as it was well polished and brought up some interesting ideas.

[nathanthp]

I see Veritasium as a channel that promotes curiosity in STEM, providing dissectible information about subjects that give viewers a solid foundation to begin building their own research on. I don't expect him to go into the fine details about how each individual protein behaves because, the way I see it, it is now my job to find that information. He sparked my curiosity, I set out to learn more, I watched your video. You provided great information to expand on the points made in the Veritasium video, but to say this is "NOT" how to think about cells is a pretentious statement considering most people only know "mitochondria = powerhouse of the cell."

[oswaldcobblebot]

Well, your arguments make the machine analogy even more fantastic. It's stil a "machine", but even 100 times more complex than shown in these animations.

[BarryKort]

Werner Heisenberg was the first to point out that there is always some amount of unavoidable blurriness in taking a picture. Most of the time, this is of no consequence. But if you are trying to take a picture of something very very tiny, then it does matter. You can still tell that something very very tiny is dancing, and you can even reckon how much energy is wrapped up in the dance routine, but you can't extract the fine details of the choreography.

[jonathanpicket]

These animations are very cool! I agree. And, it's good to be a bit critical as, yes, they don't show everything and couldn't possibly do so... nor are they meant to. They are learning/teaching tools. As such, being overly critical of them rings a bit hollow. There are a few issues with your critics:

Proteins, when interacting with binding partners, absolutely can become rigid and tightly bound. This isn't misleading. Most proteins have some intrinsically disorders regions. This doesn't mean that the functional or protein interacting domains don't have specific roles and confirmations, though.. even in highly disordered proteins. But yes, alpha fold and AI, in general, will never be able to predict a structure for IDPs or disordered regions, as those generally do not have structure, independent of their binding partners.

X-ray crystallography doesn't just give us the structure of a protein in one confirmation. It gives us many confirmations so that we can see most of the states the protein is capable of assuming. Most papers that discuss crystallography results will include discussions on the distribution of confirmations in order to make sense of the proteins' potential function(s).

Most proteins are not moving about randomly throughout the cell. Most proteins are highly localized to where they perform their primary function (with the caveat that they first need to be assembled and delivered to that location). For many proteins, this means that they are localized in the cytosol, which, granted, is a huge portion of the cell and proteins that are cytosol-localized move around a lot.

Aside from these errors and being a bit too critical (IMO) of some cool animations, this was an informative and well-made video. Thank you for working to push science communication forward, truly! ❤😀

[japhethkallombo]

I'm glad I have met another YouTuber who thinks like a biochemist. The cell is complex and proteins switch function based on so many things. The rigidity of proteins varies thats why we might never know all the functions of one particular protein. In addition some functions show up only in rare environmental conditions. Proteins also show quantum effects on the molecular scale like the generation of excitons by pigment protein complexes.

[SteveEwe]

There's nothing wrong with saying that living organisms are LIKE machines. Metaphors are not meant to describe exactly. That's why they are metaphors. They are used to describe something similar (not exactly the same), to convey some aspect(s) in an imperfect manner. Veritasium need only make a small disclaimer something to the effect of "this is a model of a functioning molecule", and it's fine.

Oversimplified, perhaps, but that is usually the case when trying to explain complex topics to a lay audience. And all of this is for a lay audience.

We still use Bohr's model eventhough we know electrons don't orbit the nucleus that way.

This metaphor doesn't give us a false sense of confidence in how much we know, it dispels a false sense of ignorance in how much we don't know. A lay audience would not have know otherwise, and presumed the scientific community didn't either, unless you happen to be a conspiracist who things they know it all and just aren't telling you.

"These animations would be an incredibly useful learning resource for students learning these processes for the first time."

Precisely.

As for all the comments, this is the same kind of cringe comments you get from creationists. "You think you're nothing more than atoms" or "just a bunch of chemicals". No. We are atoms and chemicals, but more. Not "just", not "nothing more". There is indeed much more. The error is in thinking a narrow explanation from one domain explains the totality. Only the incurious think this way.

If researchers in the field are overusing the metaphor inferring more than is valid to use, then thats an issue among researchers using the metaphor.

Correct me if I'm wrong but I don't thing any of those researchers are listing a Veratasium video as reference source for their papers.

Also, definitions for what constitute a "machine" are our definitions. Like any word, it is subject to change, just as our world does. What happens when we invent "machines" that are not solid, or if we find ways to build them from generic parts. Will you deny "machines" built from lego or erector sets?

[Dave-iddk]

@SubAnima This is an interesting video that contains some useful points, but also suffers from a reliance on narrow definitions. First the good points:
1) The warnings against overconfidence are certainly warranted. As exciting as the recent decades have been for microbiology, there remain massive gaps in our knowledge, including "unknown unknowns."
2) It's important to understand the boundaries between metaphor and identity. As a STEM professional, it's obvious to me that descriptions of "circuitry" in a cellular context are only metaphorical, especially as it pertains to enzymatic pathways. But that usage could create misconceptions.
3) The video highlights the stochastic nature of the cellular environment.
4) Dan Nicholson's paper is an interesting and thoughtful read, and I think the video represents it fairly.
So now the issues with the video:
1) As several other comments have highlighted, the main point of this video is that cells & their constituents are not machines. But this assertion is critically dependent on an understanding of "machine" that adds extra constraints. Most common definitions of the word (i.e., the way most people understand the term) emphasize two principal aspects--the assemblage of parts and resultant functionality. So when distinct parts come together to form a functional whole (or system), that is a "machine" as generally understood. You have added in private qualifications to disqualify proteins from being identified as machines. That individual proteins can shift between conformations ("wiggle") and large protein complexes often contain modular parts in no way violates the standard definition of machine. Actually, flexible and even fluid components are essential to many machines that we build and use everyday (e.g., transmission fluid, fuel, coolant, motor oil, refrigerant, battery electrolytes, hydraulic fluid). Though you seemed to dismiss definitional criticisms in your pinned comment, you should do better, especially if you are primarily in addressing biology from a philosophical standpoint.
2) The analogy to your bike wiggling seems particularly poorly thought out. The structure and function of machines is inextricably bound up with their environmental context. At the scale in which proteins exist, Brownian motion is the norm; it would be weird if they didn't wiggle in that environment! If your bike could be measured in Angstroms, it would wiggle too. Disqualifying proteins as machines because they differ from macro machines is just as wrongheaded as an F-1 driver saying that street legal tires aren't "really" tires because they don't work in the context of an F-1 race. The forces at work in the cellular environment mean that a functional system will have different constraints to satisfy as compared to bikes, cars, etc.
3) Your characterization of Drew Barry's work as misleading seems to ignore the fact that he has given lectures addressing some of the criticisms in your video. He talks about the challenges inherent in creating videos based on the literature that accurately portray the stochastic aspects of cellular processes while still being visually intelligible. I believe he has commented below. There are always tradeoffs/simplifications to be made in addressing a complex subject. If everything moved at speed, it would be unwatchable.
4) Both your video and Nicholson's paper seem to ignore perhaps the most compelling reason for machine language in biology: it is extremely successful at the macro level. Hearts are not "like" pumps, they ARE pumps; eyes are not "like" cameras, they ARE cameras; etc. The machine view of organisms at the level of gross anatomy is the bedrock of modern medicine and surgery. It's why we can replace heart valves and bad hips, perform laser eye surgery, and develop pharmaceuticals to solve specific malfunctions.
Perhaps more could be said, but if I were to suggest a way forward, it would be this: instead of rejecting machine language in a cellular context, augment such descriptions by emphasizing the dynamism of the cellular environment, compare and contrast molecular machines to macro machines, and where metaphors are being used, make it clear that they are metaphors. Just my two cents😏

[rubenhillier]

The definition of machine according to the dictionary:
"A machine is a physical system using power to apply forces and control movement to perform an action"
so proteins may be super complex and unpredictable in all actions they can perform, but they still fall under a machine.
These diagrams of metabolic pathways are good for teaching as it would be too much to explain it in a fluidly, dynamically changing system to new students.

[WerexZenok]

Just because a machine is more complex than you initially thought, it doesn't mean it's not a machine.
But I appreciate the point you are trying to make.

[eileen]

This pretty much just proves that the cellular process is just a far more complex machine, one that we don’t fully understand; A machine doesn’t need to be simple or complex it just is a process fulfilling a purpose right?

[shaunmcinnis]

Hard to say it's unpredictable when the end result is a function.