Biology is a Burrito: A text- and visual-based journey through a living cell
burrito.bioTwo books that I highly recommend to give you a visual and numbers view of the cell:
“The Machinery of Life” by David Goodsell is full of illustrations like the ones show in the article and really gave me a sense of what k might imagine when reading about the cell.
“Cell Biology by the Numbers” by Ron Milo and Rob Philips is full of order of magnitude calculations of about the processes of the cell. How fast are they, over what distance, how much, etc.
Just discovered that you can download high quality scans of Davis Goodsells's art here: https://pdb101.rcsb.org/sci-art/goodsell-gallery
> order of magnitude calculations of about the processes of the cell
There's a searchable database of bionumbers[1], and a draft version of "by the Numbers" officially online[2].
[1] https://bionumbers.hms.harvard.edu/search.aspx [2] https://www.dropbox.com/s/gvpleqtcv8scro4/cellBiologyByTheNu...
> For many years, I had an intense aversion to mathematics. Biology was my refuge because it was simple: Read the textbook, memorize the facts, and ace the exam. (The only reason I majored in biochemistry as a college student was because it didn't have a multivariable calculus requirement.)
Every part of this passage is a shockingly accurate description of myself. I felt that I was bad at math and did a biochem degree because it meant I could skip Cal III. Now, I'm a computational biologist and I've mostly made up with math.
If you liked David Goodsell’s illustration you can find more of his work at https://ccsb.scripps.edu/goodsell/. I’m a huge fan.
What a beautiful depiction. Reminds me of high fidelity 3D animation videos I used to watch about DNA replication, cell signalling etc.
One of the most fascinating parts to me was DNA transcription. The engineering is quite precise.
Found the video I was referring to: https://www.youtube.com/watch?v=7Hk9jct2ozY
Looks fascinating. Related: The Machinery of Life https://link.springer.com/book/10.1007/978-0-387-84925-6 (actually it is the book of the person who drew the first illustration in the article but I could not see any mention of the book).
Wow, aptly named "The Machinery of Life".
A cautionary note: the jiggle can be misleading, making one think motion is fully represented. These are traditional 3D animations, with their profoundly misleading handling of motion, just with a "jiggle filter" added.
For illustration, consider the classic animation of a walking kinesin towing a vesicle. One could jiggle-ify it. But that won't convey that during every step, the vesicle has done a "balloon in a hurricane" exploration of every possible position it can reach while remaining tethered. Won't clarify that the very very misleading "I'm just a peaceful barge" vibe is entirely animation fantasy. Secondary content could have been added to defuse this negative educational impact, but the choice was made to optimize for, and I'm quoting, "pretty".
Jiggle-ification takes perhaps the biggest educational downside of these animations, and makes it even more misleading.
Ugh, makes my skin crawl, it's so chaotic! And delicate-looking!
I feel that, too. And the speeds those move at! There's a spot in the video where it refers to "real-time" replication of DNA, but that has got to be more like "sped up until smooth". Miles of DNA aren't getting reproduced in a few minutes at that speed.
One thing that these animations always remind me of is that speeds at that level are tied to size. We're use to a world where birds and cars are faster than pollen and insects (mostly), but the fidgety twerking of all those big proteins is due to collisions with higher-velocity, invisibly small molecules like water (Brownian motion). When was the last time a pollen grain made you flinch? Everything is kinetic/EM energy exchange; everything is in the gray area between Newtonian and quantum physics. (Shout out to Einstein, but also Boltzmann through Dirac.)
> Miles of DNA aren't getting reproduced in a few minutes at that speed.
I didn't get the "miles of DNA" reference. A single strand of DNA is approx 3 meter in length when uncoiled. Now I'm thinking how many strands may be replicated at a time.
That is confusing, I thought it was monads who are Burrito. So is Biology made of monad ?
Lets hear it for Van der Waals forces! Go team!
The painting is wonderful. Yes, it's a snapshot in time of a dynamic state. All paintings are!
Life is amazing. Can anyone recommend good modern starting points to someone who would want to learn more about how living beings work (from bottom up)? It has been a while since I actively delved into Biology (my school days).
The research into the origen of life looks at bottom up fundamentals (how they work) of all cells since the solar system was formed. You could start with the slides in this lecture and read the underlying papers and all the references in all those papers. You probably can find these references also in all the books he wrote. https://www.youtube.com/watch?v=vBiIDwBOqQA
Maybe an educational text for the laymen has summarised this recently but I'm not aware of one. Most Biology from your school days have been rewritten.
I will have to re-read Molecular Biology of the Cell, 7th Edition, 2022. I read the 3th edition and it has changed dramatically since.
You can download it on Anna's Archive or order it at the usual suspects https://www.amazon.com/s?k=Molecular+Biology+of+the+Cell%2C+...
Get any modern undergraduate Intro Biology textbook like Campbell. These are fantastic books: beautifully illustrated and clearly written, and way better than popular science books at the mall bookstore.
The first few Units cover all the basics: chemistry of life and energy, molecular biology, cell biology, and genetics. From there you can branch out into anything.
> Get any modern undergraduate Intro Biology textbook [...] These are fantastic books
Curious how perspectives vary. I would have said there's basically nothing available, textbooks being horribly wretched.
I don't know of anything which takes a "bottom up", rough quantitative, engineering first-principles intro to cell bio, let alone to biology. No whys and hows of building close to thermal noise energy levels. No focus on pervasive multi-scale cross-cutting strategies for localization and compartmentalization. No energy budgets, not feel for reasonable numbers, no... sigh. When you see a nifty foundational insight mentioned in passing in a research talk, it's a really good bet it won't be in textbooks any year soon. One of the causal threads leading up to TFA, the Harvard bionumbers database, was born out of someone's 'it's absurdly hard to find numbers'.
Chatting with a cell bio tome publisher years ago, about what absurdly implausible resources would be needed to do something transformatively better, the snark for "but it has 100 authors!" was "nifty - and how many for the second page?". Maybe now with AI we can start nibbling away at this faster.
> engineering first-principles intro to cell bio
Very true, these books are qualitative. There's a bit of basic math around delta-G for reactions and Chi-sq tests for genetic associations, but the conventional undergraduate introductory biology course is 99% descriptive.
There are reasonable arguments for taking that approach. These courses are foundations for subsequent study, with the intended outcome that students have a broad but shallow understanding of core basic ideas. Lots of biology makes intuitive, mechanistic, and visual sense, much like introductory computer science and introductory chemistry.
Obviously applied math plays a key role in biology but it tends to address specific needs like protein structure prediction, dynamic modeling of transcription/translation and metabolism, inferring phylogeny, high-throughput 'omics analysis, network simulation of epidemic outbreaks, and so on. These are great to study, but without the broader context the understanding would be relatively fragmented, lacking the big picture.
Rereading OP's question:
> good modern starting points to someone who would want to learn more about how living beings work (from bottom up)?
I interpret that as wanting a general understanding, starting with chemistry and working upwards towards evolution and populations. That's all in the standard two-semester introductory course, hence my book recommendation.
If that's wrong and OP wants a math-centric approach, here are a few gems:
Physical Biology of the Cell, Phillips, et. al
An Introduction to Systems Biology, Alon
Evolutionary Dynamics, Nowack
First, thank you for the comment. It prompted fruitful reflection. I note LLMs as nifty for this.
For me, success means "robust structural intuition". Perhaps frame it as understanding that's robust to adversarial noise? To fuzzing testing? If you fuzz content, changing numbers, inserting negations and lies, how extreme before there's a "wait, that doesn't make sense"?
Merely quantitative isn't sufficient. An Ideal Gas Law chapter problem, with numbers for solid Argon - mindless plug-and-chug - is not this success. But a sense of reasonable values, yes. Contrast the first-tier med student, asked for red blood cell size, who failing to recall it as a factoid, is quantitatively lost, retreating to "really really small".
Similarly, "descriptive" can be deep structure and constraints of a domain, focused on building structural intuition, or at least trying for it, or an embrace of "stamp collecting" focused on regurgitation.
I nod to "foundations for subsequent study, with the intended outcome that students have a broad but shallow understanding of core basic ideas. Lots of biology makes intuitive, mechanistic, and visual sense, much like [...] introductory chemistry. [...] without the broader context the understanding would be relatively fragmented, lacking the big picture." But then contrast it with content presenting a not-broad and quite-shallow take, that pervasively fails to engage with the domain's core structure. And then, even on its own shallow terms, still fails outcome-wise: First-tier institution students, coming to intro genetics from intro bio, lacking even a firm grasp of central dogma? Stoichiometry students not even thinking of atoms as real physical objects? So I see "wonderful books" and think "wat?!? - how about profoundly and pervasively dysfunctionally unhelpful books?".
Perhaps at root, there might be different visions of what a "big picture map" best looks like??? Maybe picture a human surface map, vs a USGS topography and geology one. Do details clarify by exposing patterns, or obscure as clutter? Does underlying structure? Do year-to-year research insights provide opportunity and motivation for frequent rewrites, or is there relative stability and slow evolution? Are labels and vocabulary treated as foundational, or as relatively unimportant? If you haven't seen part of the map, how important is being able to sketch it in plausibly? If fragmented into puzzle pieces, how important is being able to fit them together? How important is seeing why things are the way they are?
Maybe the contrast between a slim tourist guidebook, versus walking in conversation with someone who deeply understands the history and society and structure of a city? Both are accessible experiences. Conversation that's numerate will be richer than non. But while the guidebook can provide a bit of orientation, it's not even trying to leave you insightful and deeply clued in.
Thanks again. I'd not thought of the fuzzing analogy before.
> For me, success means "robust structural intuition". Perhaps frame it as understanding that's robust to adversarial noise? To fuzzing testing?
There was a flurry of papers in the early 2000s that aimed to generalize biological robustness, borrowing from ideas and math from engineering. You might find these interesting:
https://www-users.york.ac.uk/~lsdc1/SysBiol/kitano.robustnes...
https://link.springer.com/article/10.1038/msb4100179
https://www.cs.unibo.it/~babaoglu/courses/cas02-03/papers/Ro...
> An Ideal Gas Law chapter problem, with numbers for solid Argon -
Ha!
> First-tier institution students, coming to intro genetics from intro bio, lacking even a firm grasp of central dogma?
Yeah, unfortunately this is a real problem: Foundational biology courses (intro, genetics, cell bio) overwhelm students with a firehose of facts that must be learned or you flunk out. Later, in upper-level undergrad and grad school, those facts start connecting, and biology becomes lots more interesting and actually easier to study.
> Are labels and vocabulary treated as foundational, or as relatively unimportant?
Vocabulary is a big deal in biology. Many terms carry associated meaning, for example polymerase chain reaction helps describe the mechanism, and TAQ polymerase reminds you that heat is important. Bone morphogenic protein says a lot.
That said, plenty of biology terms are pretty useless. Ribosome doesn't provide much intuition other than RNA is involved, and Golgi apparatus is even worse. Many gene names are arbitrary, reflecting a lack of knowledge at the time of discovery. Some are just dorky like sonic hedgehog.
Good undergrad biology books have big, carefully written glossaries in the back, these are absolutely invaluable.
> How important is seeing why things are the way they are?
It's important to internalize: 1) Biology is just physics and chemistry. 2) Millions of years of evolution and randomness produced all these arbitrary biological systems with their endless complexity. That's why living organisms are nothing like rational engineered systems, despite all the shared physics.
> If you haven't seen part of the map, how important is being able to sketch it in plausibly? If fragmented into puzzle pieces, how important is being able to fit them together?
For me, studying any big subject with lots of details, context really helps. It's easy for me to get lost in the details and lose motivation unless the ideas plug into some bigger picture. That's true even if I only want tourist-level knowledge.
I'm currently reading (and enjoying) "How Life Works: A User's Guide to the New Biology" by Philip Ball. It proceeds from the bottom up: the first half is all about cells and smaller structures. Pretty readable but doesn't gloss over complexity.
I can recommend "The song of the cell" as a starting point. If you prefer textbooks, maybe "Life: The Science of Biology". I have a translated non-english copy and besides some math issues it's a nice overview, but I'm not a biologist.
I second "The Song of the Cell" as a good read, as a layman I can't judge the factuality of it but as a reader it was a very enjoyable journey.
> It's a wonder that cells get anything done at all.
> The first time I did these calculations, I felt an intense appreciation for biology. And now, I want everyone else to feel the same. We ought to teach students of biology to think as mathematicians: to carefully quantify biology, to think in absolute units, and to develop a feeling for the organism.
It was interesting to read this article, but I think I would’ve understood a lot more if this entire piece had been (or were) an animated video that described it. Text and a few animations don’t do enough justice for the passion, knowledge and detail that’s in this article, IMO.
Lets hear it for Van der Waals forces! Go team!
> A typical E. coli cell, after all, measures about one micrometer across.
Bit nitpicky here but ... he wrote a typical E. coli cell.
Naturally bacteria have different size ranges, depending on many factors - nutrients, temperature, genome and so forth; e. g. look at how huge Thiomargarita namibiensis is.
But the 1 µm as average here given for E. coli, is not correct:
https://bionumbers.hms.harvard.edu/bionumber.aspx?id=117344&...
Length 1.78±0.54 μm
So while +/- at the lower end may be 1.24 µm, the max range here would be 2.42 µm, which is what I had more in mind (e. g. roughly about 2µm). I don't have all of the data to be able to say which is the exact value, but I think the website at bionumbers.hms.harvard.ed is more realistic, so I would say that E. coli's best average is more at 2µm than 1µm.
Perhaps an order of magnitude approximation, in true physics tradition :P
A micrograph.[1] Usual EM prep caveats: surface appearance is all artifact, ~10% shrinkage.
[1] https://commons.wikimedia.org/wiki/File:E._coli_Bacteria_(73...
.jpg){kind=link}
> converting about 40 bases of DNA into its corresponding RNA each second. If an RNA polymerase were scaled up to the size of a human, it would move twice as fast as Usain Bolt's
Hold up, My own inexpert "numerical intuition" is having problems here.
If polymerase converts 40 bases/sec, and travels ~20m /sec, how on earth is one base pair 2 meters long?
I assume what the author means is that the average conversion work done by each protein is 40 base pairs per second, however it spends most the time "seeking" rather than "converting"?
Logically that the burrito metaphor can explain monads, implies that the burrito metaphor can explain biology.
biology is a monad?