Archive for the ‘Biology’ Category

Bacteria Living on Antibiotics

Sunday, April 13th, 2008

I like dabbling in bio, so I keep abreast of recent developments by reading Nature and Science. One article in particular caught my eye the other day–George Church’s “Bacteria Subsisting on Antibiotics” in Science (April 4, 2008, Vol 320, p. 100).

The common wisdom is that “superbugs” — antibiotic resistant bacteria — are being bread inside humans who don’t finish their full course of antibiotics. The theory is that when you don’t finish your full course of antibiotics, you only weaken them, killing off the ones most susceptible to antibiotics: the remaining few were the ones most resistant to antibiotics. If these remaining bacteria cause you to relapse, the new infection will have a greater resistance to antibiotics. Repeat this process a few times, and you are the culture dish for evolving antibiotic resistant bacteria. Clearly, the solution to this problem is to just make sure we all take our antibiotics to the end of its course. Or is it?

The interesting part about Church’s report is that the bacteria commonly found all around us in the soil has a high chance of being resistant to every known antibiotic; and not only do they resist them, they can use these antibiotics as a food source! They are “ultimate superbugs”. The obvious question is, why haven’t these just taken over and killed every human? [Note: the rest is all my speculation, and not part of Church's report...] The answer probably lies along several reasons. Typically, soil-based bacteria doesn’t grow well in human hosts; however, it was noted in the article that several strains of resistant bacteria are close relatives to human pathogens. So maybe that’s not the reason. My thought is that antibiotic resistance requires the bacteria to spend extra energy and resources, so when left in a nutrient-rich environment — like the mucous lining of your sinus — they are out-reproduced by the more nimble, but less robust human pathogens. Since bacterial reproduction happens on an exponential curve, even tiny extra metabolic costs add up to a huge disadvantage in the end. Anyone who has financed a mortgage is aware of how a change of a few fractions of a percentage compound interest per year can add up to a lot over many years!

So, I guess that’s good — the superbugs aren’t winning yet. However, the remaining threat is that bacteria are very promiscuous. They will acquire or exchange DNA under a large number of conditions, including changes in heat, pH, and electric current, as well as viral vectors. My thought is that human pathogens could “acquire” genomes from their resistant soil-based kin when they mix together, and that the slow-growing but long-lived soil based bacteria are acting like a genome archive where useful but expensive bacterial genes are stored. The problem with this theory, of course, is that when the human pathogen acquires the resistance genes, they reproduce slower than those that don’t, so they eventually go extinct, probably before they can infect a human host.

But there’s one other factor that’s missing. A lot of antibiotics used on humans and animals are excreted through urine, feces, and sweat. These antibiotics are concentrated in sewage and released into the environment — into the soil. The presence of these antibiotics, even in small quantities, combined with the genetic archive stored in soil bacteria, could be enough to bias natural selection to favor the bacteria that have acquired the antibiotic resistance genes, thus providing a natural environmental reservoir for the breeding and storage of superbugs.

Think about it: the mere prescription of an antibiotic may ultimately lead to environmental bacteria acquiring a resistance to them, and no amount of care or attention on the part of you and me in finishing our antibiotic courses can prevent this.

That being said, it’s all just speculation on the part of someone who’s really an electronics hacker and not a biologist, so I wouldn’t go sounding any alarms. But it is interesting to think about the role of environmental DNA and the evolution of species; it may be one of those rule-changing disruptive concepts. I’ve been reading about how sea water contains lots of DNA that codes for all kinds of interesting genes, and how our DNA contains lots of “junk” DNA introduced by viruses, etc. Maybe there is more to evolution and genetics than just simple random mutation and how genes are selected from a pool defined by only those found in the parents. With the incorporation of environmental DNA, totally random, unexpected whole genes can be introduced by the environmental library, absent of any parent. Furthermore, genes that fall out of favor (become “extinct”) due to external changes can be archived in this environmental library and brought back into service at a later time, so evolution, at least for simple organisms like bacteria, might not be a simple linear progression.

Also, in the same issue of Science, there is a snazzy article titled “Single-Molecule DNA Sequencing of a Viral Genome”. Really, really clever stuff going on in there that probably has application beyond just DNA sequencing; if you have an interest in nanotechnology or single-molecule data storage/manipulation/retrieval it’s worth the read.

FOO Camp 07 and RNA Folding

Monday, July 2nd, 2007

I was at FOO camp last weekend and it was a blast. As usual, Tim brought together quite an interesting crowd of people. It was a pleasant surprise to see old friends from MIT, some whom I hadn’t seen in years. To date, four FOO alumni worked on the same robotics team (ORCA) building autonomous submarines at MIT back when we were all students there, and at least three students/ra’s of my MIT graduate advisor, Tom Knight, have also attended FOO. Of course, I got to meet some interesting new people, including a group of folks who have expertise and great interest in manufacturing in China (we had a little round table discussion about doing business in China and China’s economic role in the world). I also gave a little presentation about how chumbys are made in China, something which I will blog about in the next couple of days through a set of posts forthcoming (I have a lot of material to go through so it’s taking me a while to organize them and write them).

One FOO attendee who I was most fortunate to stumble upon was Christine Smolke. She gave a fascinating talk about the capabilities of RNA that really opened my mind. As many may be aware, the “central dogma” of biology is being rewritten, and RNA is starting to take a more active role in everything from heredity of genetic traits to catalysis of reactions. Recent findings have caused some hypotheses to be revisited, such as the “RNA world” hypothesis, which indicate that life may actually have started through self-replicating strands of RNA, instead of DNA.

The most interesting connection I made listening to her talk was with my experience looking at the protein folding problem. In a nutshell, protein folding is one of the “grand challenges” of computer science today, and the basic mission is to predict the 3-D structure of a protein given its amino acid sequence–in my opinion, one important part of the “uber-tool” for nanotechnology engineers that would create a catalyst for an arbitrary substrate (another application for protein folding is also to elucidate the structure of proteins that cannot be crystallized and are thus unsuitable for X-ray diffraction analysis).

Protein folding is hard. I mean, really hard. It’s one of the few computational problems that truly scare me. There are whole supercomputer projects devoted to the subject, from DE Shaw’s ambitious project to IBM’s Blue Gene series of machines, to Stanford’s Folding at Home distributed computing project. My facts are a couple years out of date but iirc, a typical goal for such a big project would be to fold one “small-ish” protein of about 50 to 100 amino acids in about a month–a reaction that happens in a cell on a timescale on the order of milliseconds. And, the problem doesn’t scale particularly well. The reasons why protein folding is hard are numerous, and most of them have to do with the enormous dynamic range of timescales required for the simulation, the very sensitive interactions that the numerous hydrophilic and hydrophobic amino acids have with the surrounding water, and the sheer number of particles involved. The simplifying assumptions made in even the most sophisticated simulations today are crude compared to the actual conditions in the cell. The way a protein folds depends upon the rate of sequence output, the temperature, pH conditions, presence of helper molecules, coordinating ions, and even post-folding sequence modifications–all things that challenge current computational models.

To illustrate the point, even the iconic double-helix of DNA is a direct result of its interaction with its surroundings. The double helix arises from the fact that the base pairs are “greasy” (hydrophobic) and they repel water, so they stick together…thus, a structure that might otherwise look like a straight ladder collapses in on itself to minimize the distance between the rungs, squeezing out the water, and in the process twisting the backbone into a double helix; the process also requires coordinating ions from the water to neutralize the concentration of charges brought on by the collapse into the double-helix. Before I learned about this I just took the twisting of DNA for granted…shows how little I know about the real mechanics of biochemistry, but boy, is it fascinating.

Christine’s talk on RNA got me thinking…RNA is nice, as it can function single-stranded, and is very pliable. It only has four base pairs, instead of the twenty basic amino acids found in proteins. The secondary structure of an RNA molecule is also predictable. And, RNA can be active on a variety of substrates. Granted, RNA may not be as effective, efficient, or as versatile as the more complex protein counterparts, but I can’t help but wonder if maybe a good baby-step would be to first try to solve the RNA folding problem. It’s only a hunch right now but it feels like RNA might be an easier beast to tame than proteins. And as a molecular tinkerer, I’d rather have a tool that creates less than optimal results but is available sooner, can iterate faster, and is more affordable, instead of a tool that gives ultimate results but also comes at enormous cost and effort. There are a lot of simple molecular problems that need solutions today, and perhaps from these learnings we can eventually develop smarter tools for the more complex problems.

Ah, if only I had the time and the money…too many interesting things to do! I wonder if I had become a professor instead of a professional, if I would have had the priviledge to investigate such interesting diversions, or if I would simply be consumed by the tenure clock…

DNA Hacks — More Bits per Basepair

Thursday, December 14th, 2006

Eric Kool (what a name, I wonder if he has a brother named Joe) at Stanford University has created a clever hack on DNA where instead of storing the customary two bits per base pair, it can store three bits. Here, he inserts a benzene ring into the chemical structure of the nucleic acids and creates an “expanded” base pair set, thus increasing the set of base pairs from C,G,T, and A to include xC,xG,xT, and xA. So now, instead of being able to store just A-T/G-C pairs, a piece of DNA can now store xA-T, A-xT, xG-C, and G-xC combinations (x-x combinations and non x-x combinations are disallowed due to spacing design rules imposed by the rigidity of the deoxyribose backbone). It’s like StrataFlash for your cell nucleus. Of course, there are no polymerases in the cell that can handle replicating these, and there are no metabolic pathways to synthesize these nucleotides, but Rome wasn’t built in a day either.

Okay, okay, so this wasn’t a name that ware–it’s coming soon, I promise, and it’s a pretty interesting one too, I think–but when I read the article in Nature, I thought it was just too cool not to write a short post about it. The thought that something as evolved and taken for granted as DNA can be improved upon is pretty exciting; there’s apparently a lot more to explore out there! Presumably, there is some marked downside to xDNA, otherwise, evolution would have picked up on it…perhaps the metabolic overhead of creating and maintaining all of these extra base pairs wasn’t worth the overhead of getting better coding efficiency. Small viruses could probably benefit from more coding density, but there’s that nasty interoperability problem of xDNA with regular DNA. Then again, evolution tends towards local minima, and perhaps xDNA is in fact superior but chance never lined up to put all the right factors together in a single cell to create a sustainable xDNA line. I wonder if there is some alien lifeform out there (or perhaps a yet undiscovered species on this good planet) that uses the xDNA coding scheme.

Here’s the image from the Nature article, which gives you a better idea of how this stuff works:

Epigenomics

Saturday, May 13th, 2006

So I’ve been admonished in the past for posting ponderings and opinions on my blog–I guess the problem is that my comments are not a-priori peer-reviewed, and it seems a lot like I’m just pontificating to an audience on my personal peeves. I think, however, writing to the blog helps me organize my internal thoughts, and I enjoy the a-postiori commentary to my post, which can be more embarrassing and candid than any private peer-review. Well, either way, if you don’t like reading about my opinions or don’t want to be influenced by them, skip this post and the one after it.

I was reading Nature again (a lot of my pondering posts seem to start there!) and being a hacker as well as an armchair quarterback in molecular biology and genomics, I’m gently amused by the surprise that the genetics community is registering about the results from the Human Genome project. Simply put, there was a prevailing notion that once we had the entire genetic sequence written out, we would crack the code on all sorts of diseases and be able to trace out the function of a cell–and perhaps the human body–from the ground truth of the genetic code.

However, for the past year I have read numerous articles that contain a phrase similar to this: researchers were surprised to find that having the source code told them nothing about how the network was configured. Or better yet, having the source code wasn’t useful because the code is self-modifying. Simply put, the Human Genome project is like having the source code to your OS, but humans are complex networks of cellular machines; many diseases and problems arise from a failure of the network or a failure of the configuration of the OS, which is not apparent from the source code alone.

I guess, to some extent, it’s not surprising that biologists are peeling the onion instead of cutting through it. I remember back in college, I took a couple of molecular biology courses. It was interesting to see the approach of the typical pre-med/biology student toward biology: lots of rote memorization, with no attention at all to system design. It’s like trying to study computer architecture by memorizing the configuration of all the transistors in a standard cell library, without understanding why you’d use one element over another.

My personal experience is that there is a significant amount of architecture in biology. When people found out I had none of the organic chemistry or genetics prerequisites for the molecular biology class, they looked at me like I was crazy. However, I survived the class with relatively little studying, the difference being that I looked at molecular biology from a system standpoint. I tried to look for high-level patterns, and totally skipped the memorizing the basic patterns–because for the tests, we were allowed to bring in an 8.5×11 sheet with notes. I wrote the basic organic chemistry operations on there, as well as the basic formulae and chemical reaction sequences I would need, so I didn’t have to memorize them. The class also focused a lot of its attention on the design of an experiment–how do you analyze a complex system and determine its features given a set of limited techniques? I remember we had a number of difficult questions about using radioactive carbon labeling to try and determine the metabolic path of a molecule. The techniques you use to design these experiments are very similar to those you use when reverse engineering a hardware system.

Epigenomics is a field that I think is very interesting and exciting, and is closing in on the idea of a “biological architect”. Epigenomics is the study of the tertiary and quaternary genetic code, to borrow terms from protein folding (okay, for you real biologists out there, I am really pushing it). It turns out that DNA is indeed self-modifying and carries information beyond the genetic code. For example, your DNA adds methyl (CH3) groups to its backbone, which modifies the rate of protein expression from that segment of DNA. Also, DNA has a very complex 3-D structure. Those Hollywood views we have of DNA being this beautiful, perfect double-helix are eminently misleading. DNA is twisted upon itself, tied in knots, and bound up by histones (protein complexes that act like DNA katamari). Given that chemical machinery is essentially a mechanical computer, the 3-D morphology of a molecule is as much part of the programming as is its composition. So Epigenomics in my view should be the study of all the factors that aren’t coded in the genome–sort of like a study of all the different configurations of an OS and how it affects the race conditions, callbacks and stability of an OS. Stepping beyond that, we have the network context and ultimately the user behavior. A human cell is many orders of magnitude more complex than the internet, and a single cell is a far cry from a human being. We are a long way off from understanding the human genome and what it really means in the context of the human network, which means there will be a lot of interesting and exciting work for years to come.

And so I ponder on this beautiful, mellow Saturday afternoon in San Diego as I procrastinate on my long list of things to do…