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0 pointstimr10y ago0 comments

No offense, but nothing you've described is what I'd characterize as "difficult". I looked at your benchling link, and it's stuff that most labs give to undergrad work-study kids to get their feet wet with labs. Mostly it's about having access to the right equipment. Ligation reactions are trivial if -- as you've noted -- you use a (relatively expensive) kit. It's just a matter of time and labor costs, and with these new tools, you can trade some money for time/labor. That much is true, but it's never really been the limiting factor in biology. It's the constant on the algorithmic complexity of research.

When the parent says that "even the simplest wet-lab reactions take very exacting conditions to work", they're not really talking about transforming cells with plasmids and autoclaving plates. The conditions are exacting, but the equipment to provide those conditions is not exotic.

The hard, expensive part of biology is the part where someone spends weeks/months/years using those tools to make a new construct that should work, but then doesn't work, because unknown. Then you spend months trying to figure out what factor you're not accounting for, then you give up and start over from a new angle. Then you repeat for 5-7 years, and someone gives you a doctorate.

Saying that biology mostly works is like saying that self-driving cars are easy because we can reliably attach computers to the steering wheel and the gas pedal. It's the parts we don't know about that cost the money.

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dnautics10y ago· 2 in thread

Perhaps I should qualify what I mean by difficult: growing something with a doubling time of 6 hours is fundamentally more difficult than, say e. coli (40 minutes) because you have to worry about things like sterility, because other things can outgrow you. This is one of the primary concerns in a garage environment.

I mean, I'm not a complete idiot here. I do have a PhD in biophysics/chemistry/biology and four years of postdoc experience. I've designed expression constructs nearly from whole cloth; I've done spectroscopy on metastable peptides; I've produced, characterized and sent for testing a mutasynthesis product; I've improved an enzyme four-fold. Of course all of those things were done in 'real labs', but the last two were done under budgetary pressure where there was a strong emphasis on getting things done cheaply (UMD is not very well-funded, J. Craig Venter Institute was making a painful transition from hard money to soft money). A lot of those lessons I learned under budgetary pressure translate to doing things in the garage, except, more extreme.

I think the primary obstacle to people doing garage biology is not that the biology is hard, but that there are generally two classes of operators, those who have little biology experience, and those who have worked under coddled environments. The real trick is to find things that are maybe a little hard, but not insurmountably so, but with one or two difficult pain points. And which are also interesting. The first class of operator is not generally capable of identifying those qualities, the second class of operator is out of the habit of identifying those qualities.

Biology really does mostly work, you're just looking at a biased system where people are just throwing money at problems and also looking for reasons to justify continuing to throw money at them (so they have to do hard things). That also creates silly folkways like the 'biology is hard' trope which makes the operators miss obvious things because it's just easier to say 'biology is hard' than to think about the problem and figure out how to solve it cheaply and effectively.

timrOP10y ago

I think that "biology is hard" isn't a trope, because I don't believe in the existence of readily commercializable biotech projects that would exist but for the existence of the kind of stuff that the OP is talking about here. We don't have a lack of biotech startups because robots are too expensive (they are not) or because people can't get access to lab equipment (they can), but because the problems that are potentially commercial are many hard problems away from commercial success.

In case you're wondering, my definition of "hard" is the CS definition: there are "trivial" problems ("send this structured text over a network connection"), there are "straightforward" problems ("scale this website to X requests per second with a median latency of Y"), there are the "hard" problems ("translate english text to another language"), and there are the problems we suspect are intractable ("solve the halting problem"). Pretty much all of the wealth generation in software over the last 30 years has come from the "trivial" and "straightforward" problem sectors. Even Google, when you back out a bit, was the result of the careful solution of straightforward problems. It's not like they "solved" information retrieval or machine translation -- they just took existing research, and scaled it.

In contrast to CS, biology is loaded with stuff that shows potential, but that we just don't understand very well. The money isn't in making bacteria glow, it's in making bacteria glow in a way that provides a reliable biosensor, or making those bacteria produce things that are safe to put inside people. The limiting step here isn't access to robots -- it's our horrible understanding of the underlying biological systems. There's very little (if any) biotech stuff out there that is a "straightforward" problem away from commercial success.

dnautics10y ago

Yeah, I totally disagree. There is a lot of biology that are in the 'trivial' and 'straightforward' problem sectors. (btw, the halting problem is provably intractable, not suspected intractable) A large reason why these have not been commercialized is because of the strong IP culture that permeates biology, and the chilling effect that has had. It's so much so that, for example, Hastings has an "IP garage" where you get a freedom to operate analysis on your biotech idea. This also creates a bias towards intractable problems. The more difficult your problem is, the less likely it is to have been patented, so there is an incentive to work on those problems.

And, while the design cycle for biology is longer than CS, it's not that bad, especially now. Given that I have decades of computer programming and wet biology in my background, I guess you can 'trust' that I'm not one of these guys that thinks progamming a cell is as easy as programming a computer. But I do also frequently lament that the approach to biology is often the 'script kiddie' approach.

Among academics and in industry, I OFTEN see that the operator's understanding lacks depth (not the field). We were having a problem with DNA shearing once, and I asked all of my coworkers if they could explain to me the chemical mechanism of DNA shearing and not a single person could even postulate a testable experiment that could have a positive effect on both what we were trying to do and our global understanding.

In another case, I asked around if anyone knew the mechanism of electroporative transformation into E. coli. Looking it up (the answer had been known for about two decades) resulted in a small change in our transformation procedure (at no extra cost!) and a reproducible 20x improvement in the transformation efficiency of 500+kbp DNA.

Yeah, maybe "we just don't understand it well", but it's often because the scientists don't understand it well, not the corpus of humanity as a whole. Now: I'm not saying we have a comprehensive understanding of biology, I'm saying it what we the culture have is enough that simple, useful, garage operations are really in striking range.

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