Synthetic Biology: Engineering Open-Source Software with DNA
blog.drchrono.com
blog.drchrono.com
http://partsregistry.org/Catalog
The biological world is very different from the world of man-made devices and you cannot expect to easily engineer, and even more so, to "program" things using DNA the way you build something from NAND gates or computer instructions - in engineering we strive very hard to make parts independent and abstract away low-level details, in biology everything is interacting all the time (even physically the molecules clash hundreds of times per second) and every low-level physical/chemical effect might be used to serve some purpose. Evolutionary "design" does not have any limits to the intellectual complexity of its results like our limited human intelligence forces us to have in our "purposeful" design process.
Even predicting the outcome of a single gene being expressed is very complicated, protein folding is now a separate field putting our knowledge of physics, chemistry, biology and computer science to a test, and what to say about predicting the interactions of those proteins inside the human body. I wish people would take a good university-level biology 101 course before making nonsensical simplifications and spreading those as "science news".
By the way, I do not doubt this is an interesting initiative and that some useful things will come out of it, I just strongly oppose the notion that we can all now "play with nature’s design".
Working in basic science is perhaps not as glamorous as working as an entrepreneur, a programmer, or whatever else. But over the course of a lifetime, the work is infinitely more satisfying.
On the other hand, know that the field is incredibly political and that the old joke about the average IQ of both physics and biology going up when Delbruck switched from the former to the latter is true.
I wonder if I can somehow find a way to pivot into bio without going through a university. Would love to somehow get there through industry, perhaps through some of the genome sequencing outfits which have some crossover with the semiconductor industry.
Hadn't heard the Delbruck joke but hah good to hear, if I understand you correctly, that in a sense it'd be easier to swim in bio if I was sinking in physics.
Computation chemistry has been going on for decades. Attempts at modeling how molecules behave is still quite primitive. We're talking about modelling the behavior of a object that is comprised of a few dozen atoms. That's it, pretty simple right? We'll the models aren't that good at predicting molecular behavior.
Let's move up a step now. Computation chemistry is used heavily by the drug industry. Get an x-ray structure of a protein (maybe a few hundred to a few thousand atoms) and see if it binds to a drug. Wow, now it's getting complicated. How successful is it? Not very. I can remember a computational chemist saying "oh hey, the model say if you replace X with Y, you'll increase binding by 10x". So we try and guess what? The binding was worse.
Now we move up to a biological system. Now we have hundreds (if not thousands) of proteins floating in a matrix of water and ions. We have a DNA strands of millions of base pairs, of which maybe 10% we actually know what they do. We also have small signalling molecules that do something we understand, but probably also do 10 other things we have no idea about.
It is very impressive how far biological "design" (genomics) has come so far, but right now the tools are incredibly blunt and the analysis is incredibly crude. I have no doubt our understanding will improve immensely over the coming decades, but I would guess we understand less than 1% of what's going on inside of complex living organisms.
What we have very little handle on is gene regulation. All those "non-coding" genes that scientists used to think were junk? They are actually used to control gene transcription.
Controlling this is infinitely easier in a simple organism like a hookworm, but the complexities of in human borders on obscene.
This probably depends a lot on the context you would like to use those things in, but in general there are lots of warnings about potential unexpected interactions in descriptions of some of the parts and the practical projects seem to have lots of safety precautions too.
It is possible to write threaded software in a way that everything interacts with everything and it is almost impossible to make out how anything works. That's why we don't. The halting problem never stopped us from writing software.
The most complicated piece of multithreaded software yet devised by humans does not compare in complexity to the transcription, translation, and interaction events occurring in a typical human cell. The "DNA as software" metaphor is just that, a metaphor - it is an exceedingly poor model. Cellular systems are so quantitatively enormous and convoluted (yet not chaotic!) that we have to compare them to the most complicated designs our species has recently engineered just to begin to get our heads around the problem.
I haven't kept up with the state of the art in the past two years, but I remember an experiment running a ~10k node cluster for several weeks being able to successfully simulate only the cytoplasm of a cell - and 1/1000th of its overall volume at that. And the proteins were all modeled as spheres. I'm sure the art has advanced, but that is orders of magnitude away.
The tiny, tiny amount of bioinformatics knowledge I have makes me think the probability of your prediction is ~ 0.00000000000001%. For non-trivial values of "useful". :)
Can you tell me what experience or knowledge lead you to make that prediction?
Biological systems are highly coupled but also very "fault" tolerant if manipulated at the right pivot points. That's why you can move a fly leg from the torso to the head by just manipulating a few transcription factors.
Platforms like ClothoCAD are great places for those interested in open-source software and syn-bio applications.
Synthetic biology requires an understanding of chemistry, molecular biology, and genetic structure.
Apps and programming/automation have everything to do with the future of the field, its not just test tubes.
The biologist I've worked with tend to be a resourceful bunch, capable of solving difficult problems with simple tools.
EDIT: Granted, there is a growing need for data-scientist who can help sort through mountains of data for relevant information. But I don't think there is much need for pre-built software solutions. Each lab faces unique problems, and their software development needs, if any, are unique.
If anything, I would suspect that the E. Chromi would be at an evolutionary disadvantage in the gut. This is because the E. Chromi would be expending effort trying to color code poo, while their neighboring bacteria would just be focused on digesting and reproduction. Based on the principles of evolution, I would expect the E. Chromi bacteria to disappear entirely from the gut with a few thousand generations of bacteria.
Poking around, I couldn't find the strain they used. They might have engineered a gut isolate. They might not. Doesn't appear to say anywhere.
also gave a talk at Google "solve for <X>": http://www.youtube.com/watch?v=F8qcDQaY8Mw and at Leo Laporte Twit.tv: http://www.youtube.com/watch?v=BLhU1RGTHN4
Is it for someone who wants to take a gene from one organism, move it to another and then order that organism? Is it for people wanting to manually tweak genes to improve efficiency, slightly change function? What kinds of manual tweaks? Is it for someone who wants to understand how an organism works?
When /I/ look at it, I think it could benefit from being more abstract, but I am not your target audience, so take this with a grain of salt. I don't think looking at individual base pairs is useful. Amino acids might be, but are still too emphasized in the interface. The most abstract view, showing genes in order is not abstract enough. I want to see genes grouped by function (e.g. reproductory system, energy production, acidity regulation etc). For each gene I want to see:
a) High level description of function (already there, but in a single line text field. Give more screen estate).
b) What activates the gene? i) Directly (e.g high concentration of Na+) ii) Indirectly (e.g. genes a, b, c) iii) Very Indirectly (environmental stress)
c) As exact specification as possible of what happens when it is activated: i) What does it activate in turn? ii) What does it catalyze?
Biochemistry has no relation to computation.
Neuroscience has no relation to computation.
Anatomy has no relation to computation.
Ecology has no relation to computation.
Someone using an computational image in any of these fields is trying to impart a sense of familiarity for his audience. If you actually want to learn any of these fields, you need to build your thought processes from scratch. No part of you works like a computer.