Detailed simulation of complete minimal cellular life

https://www.cell.com/cell/fulltext/S0092-8674(21)01488-4?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0092867421014884%3Fshowall%3Dtrue

by akimball • 4 years ago

155 31 4 years ago

cell.com

aluminum96• 4 years ago

It's wonderful that the entire paper is available freely from the journal. Most journals these days are pay-for-access (and none of the payment makes it to the authors).

ramraj072• 4 years ago

Could be wrong but it’s possible the authors had to pay tens of thousands to make it free.

anon946• 4 years ago

Looks like about $10K.

https://www.cell.com/open-access

brnaftr361• 4 years ago

NVIDIA published a headline on their site. I could imagine them bankrolling the open publication. Good PR, good science it's a win-win and a trivial expense.

https://blogs.nvidia.com/blog/2022/01/20/living-cell-simulat...

Animats2• 4 years ago

The code is on Github:

https://github.com/Luthey-Schulten-Lab/Minimal_Cell

https://github.com/Luthey-Schulten-Lab/Lattice_Microbes

This is an impressive result. They've found a nice level at which to simulate. Down at the atom level would take too long. They got this to work at the chemical reaction in 3D space level, low enough that the model maps directly to the biochemistry.

They don't seem to say how many GPUs they used, but the article seems to indicate small numbers, not entire data centers. Current speed is about 1/30 of real time for one minimal cell, which is pretty good.

_Nat_4• 4 years ago

Looks like they used up to 1 GPU per simulation:

The GPUs used for spatial simulations included NVIDIA Titan V and NVIDIA Tesla Volta V100 GPUs, which took 10 h and 8 h to simulate 20 min of cell time, respectively.

So apparently they tried 3 different GPU configurations:

1. A single Nvidia Titan V, for a non-mixed model, which took 10-hours to simulate 20-minutes.

2. A single Nvidia Tesla Volta V100, for a non-mixed model, which took 8-hours to simulate 20-minutes.

3. No GPU's, for a well-mixed model.

Regarding mixing: A well-mixed model is one where all chemicals are assumed to have spatially-equal concentrations throughout a phase. By contrast, a non-mixed ("spatially resolved", in the paper) model models chemicals as having concentrations that can vary from location to location, making them more realistic but also far more expensive.

For anyone surprised that they only needed up to 1 GPU per simulation: their models appeared to be largely based in rate-kinetics; it's not like they were simulating atoms or really even molecules, but rather more like they were simulating concentrations of molecules.

To note it, they probably couldn't get a linear-speedup by using more GPU's. The thing's that they needed the GPU's to solve interactions over a space; if they had multiple GPU's, then they'd have needed to actively connect them on each iteration, slowing down the simulations. For a small number of GPU's (like maybe 2 to 4), they might try for a near-linear speedup if they fudge the boundaries a bit (allowing computational-artifacts at the edges between them).

brap• 4 years ago

On what level was this simulated? Atomic?

tantalor• 4 years ago

No, several levels higher than that

netizen-936824• 4 years ago

How do you define one level?

akimball• 4 years ago

It is what I would call the biochemical level, not the quantum chemical level. It is sufficiently detailed that the functions of genes can be observed and analyzed.

pfdietz2• 4 years ago

This thing still has billions of atoms in it, so that's not even close to possible.

It's also telling how far this is from something that could plausibly originate from a pre-biotic soup. There's enormous complexity here. Origin of life is very far from a solved problem.

codedokode• 4 years ago

Why is it impossible?

I tried to calculate how many molecules of water can fit into a sphere with radius of 500nm and I got 17 billions. Doesn't look like a big number for modern hardware.

And if modeling billions of atoms is impossible, cannot we model separate reactions? Put several virtual proteins and RNAs near each other and see how they interact?

philipswood• 4 years ago

From the paper:

“ Because of the large variation in timescales and concentrations, developing a whole-cell model that treats metabolism, genetic information processes, and growth can, at the moment, only be achieved by hybrid stochastic and deterministic simulations. Kinetics of the essential metabolic network (Breuer et al., 2019) are handled deterministically via ordinary differential equations (ODEs), and the kinetics of the genetic information processes are handled with stochastic simulations.”

This reminds me of a description of how different levels of realism were chosen and combined to simulate a whole person in a Greg Egan science fiction book (Permutation City - I think). IIRC there is a scene where a character spends some time in the shower knowing that the partial differential equations for simulation of the water will be driving up the costs of running the simulation.

Edit: added the bit about Greg Egan.

dekhn3• 4 years ago

Alastair Reynolds books also have several levels of simulation: https://revelationspace.fandom.com/wiki/Alpha-level_simulati... https://revelationspace.fandom.com/wiki/Beta-level_simulatio... https://revelationspace.fandom.com/wiki/Gamma-level_simulati...

_Nat_4• 4 years ago

It's a phase-level simulation.

Like, in highschool/undergraduate Chemistry classes, students sometimes calculate chemical-concentrations for [equilibrium reactions](https://en.wikipedia.org/wiki/Determination_of_equilibrium_c... ). This paper's basically at the same level.

Unlike highschool modeling, though, this paper:

1. Uses dynamic models, where things evolve over time (rather than everything being at-equilibrium).

2. Involves a large number of interacting systems (rather than just one system by itself).

3. Involves a lot more species, reactions, and complexity than one'd generally see in a classroom.

4. Involves spatially-variable concentrations, where chemicals have different concentrations at different points in space, rather than being the same throughout (well-mixed). (Actually, they did this both ways: they did the simpler well-mixed model without needing a GPU at all, then they used a GPU in their non-mixed models.)

Each one of those generalizations can make the problem, say, an order-of-magnitude more complex, if not more. Combined, they create a much larger model.

However, it's still largely based around that phase-level scale that students might be familiar with.

soheil• 4 years ago

Simulation seems like a step that requires knowing the initial state of a system. I wish there were more efforts focused on finding ways to scan the constituents of a cell all the way close to the atomic level. As far as I know the closest thing we have are Atomic Force Microscope and Scanning Electron Microscopy both several-decade-old technologies. They're also pretty invasive and require access to the surface area of the object to be scanned.

Knowing the position and charge density of atoms in a cell is required to simulate it.

ChuckMcM• 4 years ago

Nice! This looks like really important work. As we get closer to being able to completely simulate more complex cells, it becomes possible to do the sorts of analysis that leads to not only understanding the cell, but how to tune cells to do exactly what we need them to do. I wish I had a broader bio background while reading the paper!

wdwvt1• 4 years ago

This seems like a really interesting work in terms of synthesizing and systematizing the known reactions/fluxes in a minimal cell. However, the paper seems to be like many other modeling studies in the field of microbiology - there are either no, or very few testable predictions made. It's hard to think of the model of metabolism this paper presents as valid without at least some idea of it's predictive accuracy. The concordance with previously published results does not seem like very strong evidence.

hwers• 4 years ago

Can't wait until we get fast enough computers to simulate this interactively. Biology education would be so much more accessible for everyone.

periheli0n• 4 years ago

Computers being fast enough to do this in biology education is quite along way out. They probably used a farm of Nvidia racks for several months to obtain the simulation.

Personally I doubt that an atom-scale simulation of a cell is very useful for education. Rather, I’d approach it in a hierarchical fashion, where progressive coarser scales are used to model progressively larger systems.

This way one learns not only about a cell, but also about principles of modeling, and that each model comes with assumptions, simplifications, and errors.

Choosing the right scale of modeling for the problem is crucial. In this case they have chosen a very fine scale to model a rather large system. But what’s the scientific insight gained?

dataangel• 4 years ago

a farm of Nvidia racks for several months

Ok so what my phone GPU will do in a day less than ten years from now.

Detailed simulation of complete minimal cellular life

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