How to use an Oxford Nanopore MinION to extract DNA from river water and determine which bacteria live in it Sample collection by 
Ciro Santilli 40 Updated 2025-07-16
Ciro Santilli 40 Updated 2025-07-16As you would expect, not much secret here, we just dumped a 1 liter glass bottle with a rope attached around the neck in a few different locations of the river, and pulled it out with the rope.
How to use an Oxford Nanopore MinION to extract DNA from river water and determine which bacteria live in it Pre-sequencing preparation by Ciro Santilli 40 Updated 2025-07-16
Ciro Santilli 40 Updated 2025-07-16One cool thing we did in this procedure was to use magnetic separation with magnetic beads to further concentrate the DNA: Figure 1. "GE MagRack 6 pipetting.".
The beads are coated to stick to the DNA, which allows us to easily extract the DNA from the rest of the solution. This is cool, but bio people are borderline obsessed by those beads! Go figure!
Then we prepared the DNA for sequencing with the Oxford Nanopore specific part: Oxford Nanopore SQK-LSK109 Ligation Sequencing Kit.
Rational representation can refer to different concepts depending on the context, but it is most commonly associated with mathematics, particularly in number theory and algebra. 1. **In the context of numbers**: A rational representation usually refers to the expression of a number as a ratio of two integers.
In this section we will use the file nodejs/bench_mem.js, tests are run on Node.js v16.14.2 from NVM, Ubuntu 21.10, on Lenovo ThinkPad P51 (2017) which has 32 GB RAM.
Related answer: stackoverflow.com/questions/12023359/what-do-the-return-values-of-node-js-process-memoryusage-stand-for/72043884#72043884
First using
topp from stackoverflow.com/questions/1221555/retrieve-cpu-usage-and-memory-usage-of-a-single-process-on-linux/40576129#40576129 let's observe the memory usage of some baseline cases.For a Node.js infinite loop nodejs/infinite_loop.jsThis gives approximately:
topp infinite_loop.js- RSS: 20 MB
- VSZ: 230 MB
Adding a single hello world to it as in nodejs/infinite_hello.js and running:leads to:We understand that Node.js preallocates VSZ wildly. No big deal, but it does mean that VSZ is a useless measure for Node.js.
topp infinite_hello.js- RSS: 26 MB
- VSZ: 580 MB
Forcing garbage collection as in nodejs/infinite_hello.js brings it down to 20 MB however:
topp node --expose-gc infinite_hello_gc.jsFinally let's see a baseline for which gives initially:but after a few seconds randomly jumps to:so we understand that
process.memoryUsage nodejs/infinite_memoryusage.js:node --expose-gc infinite_memoryusage.js{
rss: 23851008,
heapTotal: 6987776,
heapUsed: 3674696,
external: 285296,
arrayBuffers: 10422
}{
rss: 26005504,
heapTotal: 9084928,
heapUsed: 3761240,
external: 285296,
arrayBuffers: 10422
}First a baseline case with an array of length 1:This gives the same results as with:
node --expose-gc bench_mem.js n 1node --expose-gc infinite_memoryusage.js. The same result is obtained by doing:a = undefinednode --expose-gc bench_mem.js deallocIf we use we see that the memory is now, unsurprisingly, accounted for under Results for different N:We see therefore that typed arrays are much closer to what they advertise (4 bytes per element), even for smaller element counts, as expected.
Int32Array typed array buffers instead of a simple Array:node --expose-gc bench_mem.js array-buffer n NarrayBuffers, e.g. for N 1 million:{
rss: 31776768,
heapTotal: 6463488,
heapUsed: 3674520,
external: 4285296,
arrayBuffers: 4010422
}|| N
|| `arrayBuffers`
|| `rss`
|| `rss` per elem
| 1 M
| 4 MB
| 31 MB
| 5
| 10 M
| 40 MB
| 67 MB
| 4.6
| 100 M
| 40 MB
| 427 MB
| 4Now let's try one million objects of type gives:Disaster! Memory usage is up to 70 MB! Why?? We were expecting only about 24, 4 baseline + 2 * 10 for each million int?!
{ a: 1, b: -1 }:node --expose-gc bench_mem.js obj{
rss: 138969088,
heapTotal: 105246720,
heapUsed: 70103896,
external: 285296,
arrayBuffers: 10422
}And now an equivalent version using gives the same result.
class:node --expose-gc bench_mem.js classLet's try Array:is even worse at 78 MB!! OMG why.
node --expose-gc bench_mem.js arr{
rss: 164597760,
heapTotal: 129363968,
heapUsed: 78117008,
external: 285296,
arrayBuffers: 10422
}TODO why is it so hard to find anything non perturbative :-(
- www.youtube.com/channel/UCPHFUHiwbpMqC8ONxEICCiQ NanoNebula using raw Perl PDFL en.wikipedia.org/wiki/Perl_Data_Language (the Perl NumPy)
- www.youtube.com/watch?v=9TJe1Pr5c9Q "Interplay of Quantum Electrodynamics and Quantum Chromodynamics in the Nontrivial Vacuum" by CSSM Visualisation (2019)
On a quantum computer...:
- www.cornell.edu/video/john-preskill-simulating-quantum-field-theory-with-quantum-computer Simulating Quantum Field Theory with a Quantum Computer by John Preskill (2019)
- www.youtube.com/watch?v=Lln-C21u0U8 Quantum Simulation from Quantum Chemistry to Quantum Field Theory by Peter Love (2019)
Are we living in the matrix? by David Tong (2020)
Source. Talks about how the Nielsen-Ninomiya theorem means it is impossible to simulate QFT on a computer in the case of a lattice gauge theory. Pinned article: Introduction to the OurBigBook Project
Welcome to the OurBigBook Project! Our goal is to create the perfect publishing platform for STEM subjects, and get university-level students to write the best free STEM tutorials ever.
Everyone is welcome to create an account and play with the site: ourbigbook.com/go/register. We belive that students themselves can write amazing tutorials, but teachers are welcome too. You can write about anything you want, it doesn't have to be STEM or even educational. Silly test content is very welcome and you won't be penalized in any way. Just keep it legal!
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Figure 3. Visual Studio Code extension installation.
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