Remembering the 27th, 28th & 1st

When I was a junior in high school, on a day much like today, I wanted to stay home and watch TV a bit, so I was hoping the wintry weather would generate a snow day. I didn't often wish for this, as my childhood love of snow had subsided substantially (though I would sometimes ski through my yard), but on this day I wanted to be home. Winter and the superintendent, however, did not cooperate and we had only a delayed opening, and hooky was out of the question in my family so off I went.

And so I was sitting in Mr. Schmidt's chemistry class that morning. He was a nice man, but that class did very little to prepare me for a life on the periphery of chemistry, except that he did an excellent job of outlining the early 20th century revolution in chemistry & physics. I do not remember what he was talking about that morning when Mrs. Kurtz, the Biology II teacher, came in and commented on a news event. We all nodded, given we expected the news -- but then she restated herself as we had not heard her, and Mr. Schmidt got out the TV in his closet and I found myself watching TV that morning -- exactly what I had hoped to watch on a snow day but also nothing I had ever imagined or could have remotely hoped to watch. For that restatement was: "No, the space shuttle blew up!".

When my boy was three we were going one weekend to take him to the Boston Children's Museum, a wonderful place for a child of that age to explore and run around and have fun. As a bonus, we would ride the subway there and oh how he loves to ride trains. It was again a winter day and I drove the usual route to Boston & there is a spot on I-93 where you come out of the relatively untouched beauty of the Middlesex Fells and the skyline of Boston suddenly appears. It was in that spot that I heard the report on radio whose meaning became instantly clear, and I semi-silently cried "No!" -- an extended loss of radio contact with a space shuttle could not ever end happily.

We are in the midst of that grim week of anniversaries for NASA; yesterday marked the 42nd anniversary of Apollo 1, today the 23rd anniversary of the loss of Challenger and Sunday is 6th anniversary of the loss of Columbia. Only one of those events has any obvious connection to this time of year.

For as long as I can remember the space program has had an outsized influence on my imagination. My career path did not take me in a good direction to go to space, but I still think about it almost daily. In some ways these three disasters are completely removed from what I do, but in other ways they are not. I do subscribe to Edward Tufte's argument that poor data visualization helped enable the Challenger disaster, and while my plots do not carry such weighty implications I still must be ready in case they ever do. All three of these were hardware failures, and I do software, but software failures have caused unmanned probes to be lost and manned missions to go awry.

But of all else, it is important to remember those who pushed the limits and did not return. We must remember who they were and why they died, as they died doing important things and they died because humans make mistakes. Grissom, White & Chaffee were doomed by a design from which escape was impossible and fire likely. Smith, Scobee, McNair, Onizuka, McAuliffe, Jarvis & Resnik died when a machine was run far outside its normal operating regime. Brown, Husband, Clark, Chawla, Anderson, McCool and Ramon died from a design which was not well matched to the materials used to construct it.

We recently learned some more details of the Columbia accident: how the astronauts never realized the disaster approaching them, but how pilot McCool worked calmly to deal with systematic failure just before it killed him. I wish I could have such coolness under stress.

Next, exploding DNA packs at the banks

I use gmail for my personal mail & actually tend to enjoy the sidebar ads. Yes, most are silly or uninteresting, but once in a while there are some odd or amusing ones. There are also some patterns -- email from my one brother often brings up inane creationist sites (which I click through to -- I figure I'd rather Google have their money than them), as we are often talking about chimps -- and that is clearly one of their buzzwords.

So here's a use for DNA that would have never occurred to me: tagging burglars with it. Or more importantly, threatening to tag them with it. All sorts of claims are made that the appearance of surveillance is nearly as useful as actual surveillance for deterring property crime, so I guess this is in that bucket.

Multiple SelectaDNA Spray heads can be fitted at the entry points of premises and on activation emit a burst of SelectaDNA solution onto the offenders. The solution contains a UV tracer and a unique DNA code, linking them irrefutably to the crime scene. The DNA Spray can be armed by a panic button and/or linked to an existing intruder alarm system. As the DNA fear-factor amongst criminals is high, it is likely that sprayed intruders will flee the crime scene before stealing any goods.

Will it work? Will some enterprising criminal start marketing DNase spray? When will it show up on CSI?

Are the old lessons being forgotten?

Okay, first I feel like I have to have a bit of preamble. This, and another post I'm doing the homework on, are pretty critical. Downright negative. I'm not turning into a curmudgeon or planning to turn this space into a rant-a-thon. It's just that both are topics I think are important & have pushed the right buttons.

Also, this isn't meant to be high-and-mighty-and-spotless-expert calling calumny on the great unwashed masses. If I look down at my metaphorical foot I find many tightly spaced patterns of scars, sometimes nearly concentric. We all make mistakes, and often we repeat those of the past. We think we've covered bases that have always been covered or deceive ourselves that safety mechanisms which were needed in the past are no longer necessary.

A bit ago at work I was doing some exploring of a standard a backbone and became curious just how taxonomically widespread pieces of the backbone might be found naturally. So naturally, I pumped the sequence into the NCBI BLASTN server & pointed it at the RefSeq genomes. As expected, a bunch of bacterial plasmids popped up. What was unsettling, though, was a bunch of provisional genomic RefSeqs for eukaryotic chromosomes. Indeed, one project had apparently deposited every chromosome with a pUC-type vector sequence at one end. YIKES!

The other day I got curious again & tried searching the non-redundant DNA and protein databases but with the species filter set to eukaryote. Again, a bunch of hits -- and the shocking part was many were very recently deposited sequences -- even human ones. In some cases, the entire deposited sequence was vector-derived (e.g. the non-human "putative reverse transcriptases" ABK60177.1, CAD59768.1, CAD59767.1 & CAL37000.1).

For example, AK302803.1 is a 1352 nucleotide sequence deposited in 2008; from 888 on is clearly vector -- and the coding region is annotated as 1 to 1275! CAH85743 is a "Plasmodium" protein which is entirely vector derived; again deposited in 2008. PIR (is anybody still curating this?) has a number of vector-derived proteins (e.g. the 231 amino acid "NZ-3 antigen" JC7702; S.pombe beta-lactamase (!) T51301); I was surprised to even find a SwissProt entry that looks like it has pUC-derived sequence

>sp|Q63661.2|MUC4_RAT  RecName: Full=Mucin-4; Short=MUC-4; AltName: Full=Pancreatic 
adenocarcinoma mucin; AltName: Full=Testis mucin; AltName: Full=Ascites 
sialoglycoprotein; Short=ASGP; AltName: Full=Sialomucin 
complex; AltName: Full=Pre-sialomucin complex; Short=pSMC; 
Contains: RecName: Full=Mucin-4 alpha chain; AltName: 
Full=Ascites sialoglycoprotein 1; Short=ASGP-1; Contains: RecName: 
Full=Mucin-4 beta chain; AltName: Full=Ascites sialoglycoprotein 
2; Short=ASGP-2; Flags: Precursor
Length=2344

 GENE ID: 303887 Muc4 | mucin 4, cell surface associated [Rattus norvegicus]
(Over 10 PubMed links)

 Score = 46.6 bits (109),  Expect = 0.006
 Identities = 22/35 (62%), Positives = 25/35 (71%), Gaps = 3/35 (8%)
 Frame = -3

pUC19  1427  CCLQTKKPPLPAVVCLPDQELPTLFPKVTGFSRAQ  1323
             CCLQTKKPPLPAVVCLPD   P+  P +   S+ Q
Sbjct  1051  CCLQTKKPPLPAVVCLPD---PSSVPSLMHSSKPQ  1082

Even the RefSeq mRNA section has some very provisional mammalian predicted cDNAs (from chimp) which appear to be polylinker-type sequences from vector (selected restriction sites are marked)

                             =XbaI=      =PstI=
                       =BamHI      =SalI=      =PaeI
pUC19           415  GGGGATCCTCTAGAGTCGACCTGCAGGCATG  444
XM_001160101.1  56   GGGGATCCTCTAGAGTCGACCTGCAGGCAT  85
XM_001146903.1  439    GGATCCTCTAGAGTCGACCTGCAGGCATG  467
XM_001141474.1  1503  GGGATCCTCTAGAGTCGACCTGCAGGCA  1530
XM_001141395.1   922  GGGATCCTCTAGAGTCGACCTGCAGGCA  949

Contamination of various sorts has plagued genome projects from the get-go. Perhaps the most notorious was a large deposition of human ESTs which were donated to the public with great fanfare (as a counterpoint to private EST efforts), only to be found later to be rich in yeast sequences. The solution is to run filters -- search everything you do against vectors, E.coli and other common contaminants. In addition, especially in this day-and-age, if your "human" mRNA sequence doesn't match the genome, you've got some 'splaining to do.

What's the harm? Well, when it comes to databases I don't like mess. You always need to check your data, but it's always a nuisance when you actually have to clean it a bunch. Miss something, and some experiment is dirty or worse ruined. Plus, and this is a bit of the theme to my proto-post, some folks haven't yet figured this out & the results are truly ugly. Even worse, these are the obvious problems since bacterial vectors in a eukaryotic sequence truly stick out. Now I'm wondering about all the pUC-like sequences I found in bacterial sources -- can I trust them either?

So, let's all make a it's-still-a-pretty-new-year resolution to recheck our sequencing pipelines. Deliberately throw pUC19 and the E.coli genome through it & see what comes out.

Earning the right ot put "DNA" in your address

GenomeWeb had an item about real estate developers putting "DNA" in their property names; I had spotted the DNA Lofts in Dorchester but hadn't gotten around to blogging about them (annoying to be scooped, but that's procrastination for you).

However, as far as I can tell the DNA Lofts are just a catchy name, with no actual tie-in. It would be a convenient Red Line ride from the nearby Savin Hill station to the biotech areas of Cambridge. Which is tres disappointing. Surely they could do better by picking something off this list to truly earn a DNA tie-in:

1. Rehabbing space relevant to the history of biotech ("These walls are still contaminated with phage from seminal experiments...")


2. Subtle decorative motifs, such as floors tiled with the genetic code table


3. Major architectural elements. Double-helical staircases are an obvious one, but how about pyrimidine & purine-shaped windows?


4. Under-the counter thermocyclers in the kitchens (and -80 compartments in the freezers), washing machines built by Sorvall, etc.


5. Themed common areas: The Topoisomerase Lounge (where you can unwind). The Proteasome recycling center.

Of course, the best of all -- but quite ambitious -- would be to use a synthetic biology approach to construct the building!

Forgetting Occam's Razor

As I've confessed before, one of my recreational vices is the TV show House. It's entertaining enough & Hugh Laurie is really good in the title role and it just relaxes me a bit. I always thought it was harmless, but now I'm wondering.

There is a saying in medicine which has become quite well known thanks to medical shows: If you hear hoof beats, think horses not zebras. In other words, consider the most common cause for a symptom before marching off to explore some rare disease which could cause it. The thing about House is that it doesn't just feature zebras, but giant carnivorous purple-and-orange Martian zebras. Plots either revolve around very unusual diseases or more commonly not so unusual diseases with totally bizarre presentation.

Some nasty GI bug, or perhaps a gang of them, latched onto me last week and while I was much better this week I couldn't quite seem to kick it. So I was off to my internist yesterday in hopes of getting an antibiotic scrip. TNG was along for the ride, also in the process of shaking off a bug. He at least brought some reading material (the apropos, in a macabre fashion, The Hostile Hospital), but I had not. So I was scanning through the waiting room magazines & lo and behold: a copy of New England Journal of Medicine (and recent too!).

I don't regularly read NEJM for the simple reason that most of the articles aren't really in my field: they rarely publish molecular medicine studies, though when they do show up they tend to be huge splashes. So I started skimming the ToC for something interesting & spotted an intriguing headline.

Hypogonadism Due to Pituicytoma in an Identical Twin

But as I read the short article I became increasingly puzzled as I read it repeatedly: how exactly was the Pituicytoma in one twin causing the hypogonadism in the other twin?

Then it hit me: only a House fan would have parsed that title that way. There was nothing that bizarre going on. One twin: healthy. The other twin: not-healthy. Duh!

Where did those gene count estimates come from anyway?

When mentally reviewing what I wrote yesterday about the great human genome gold rush, I realized I hadn't really touched on one of the most curious bits of that. Indeed, it was GenomeWeb's Daily Scan headline on an entry summarizing mine & Derek Lowe's pieces that reminded me of it: All those varying estimates for human gene count.

When the human genome was only partially sequenced, one of my colleagues at Millennium tried to dig through the literature and figure out the best estimate for the number of human genes. Many textbooks & reviews seem to put the number in the 50,000-75,000 range -- my 2nd edition of Alberts et al, Molecular Biology of the Cell from junior year states

no mammal (or any other organism) is likely to be constructed from more than perhaps 60,000 essential proteins (ignoring for the moment the important consequences of alterative RNA splicing) Thus, from a genetic point of view, humans are unlikely to be more than about 10 times more complex than the fruit fly Drosophila, which is estimate to have about 5000 essential genes.

. The argument laid out in this textbook is one based on population genetics & mutation rates, and is basically an upper bound given observed DNA mutation rates and the size of the genome.

The other pre-sequencing methodology that was often cited was DNA reassociation kinetics, an experimental approach which can estimate the fraction of DNA in a genome which is unique and what fraction is repeated. If we assume that genes are only in the unique regions, then knowing the size of the genome and the unique fraction could estimate the amount of space left over for genes.

What my colleague was unable to find, strangely, was any paper which actually declared a gene count as an original result. As far as he could tell, the human genome estimate had popped into being like a quantum particle in a vacuum, and then was repeated. I think it would be a great challenge for someone (or a whole class!) at a university with a good (and still accessible!) collection of the older journals to try to find that first paper, if it does exist.

Now the whole reason for this is that it was useful to have a ballpark figure. For example, if we thought we could find 20K human genes and somebody had a database of 200K human genes, then maybe we were missing out on 75% of the valuable genes -- and should consider buying into a database. Or, if we thought we could find them on our own, it made a difference what we might try to negotiate. If we thought 1% of the genes would fall into classical drug target categories, a 4X difference in gene count could really alter how we would structure deals.

MLNM wasn't a great trafficker in human gene numbers, but many other companies were -- and generally seemed to one-up each other. If Incyte claimed their data showed 150K genes, then HGS might claim 175K and Hyseq 200K (I don't remember precisely who claimed which, though these three were big traffickers in numbers).

So my colleague tried a new approach, which I think was to say: we have a few percent of the human genome sequences (albeit mostly around genes of interest and not randomly sampled). How many genes have been found? And what would that extrapolate out to for the whole genome.

His conclusion was so shocking I admit I refused to believe it at first, and never quite bought into it. I think it was about 25-30K. How could the textbooks be off by 2X-3X? I could believe the other genomics companies might be optimistic in interpreting their data, but could they really be deluding themselves that much??

But, the logic was hard to assault. In order for his estimate to be low by a lot, you would have to posit that the genomic regions sequenced to date were unusually gene poor -- and that the rest of the genome was packed.

Lo and behold, when the genome came in his estimate was shown to be prescient. The textbook numbers were based on very crude techniques, and couldn't really be traced down to an original source to verify the methods or check the various inputs. But, what about all those other companies?

I've never heard any of the high estimaters explain themselves, other than the brief bit of "yeah, the genome's out but y'all missed a lot of stuff" which followed the genome announcements. I have some general guesses, however, based on what I saw in our own work. In general, though, it gets down to all the ways you can be fooled looking solely (or primarily) at EST data.

First, there is the contamination/mistracking problem: some of the DNA in your database isn't what it is supposed to be. The easiest is contamination: some bits of environmental stuff get into your sequencing libraries. The simplest is E.coli and early on there was a scandalous amount of yeast in some public EST libraries, but all sorts of other stuff will show up. One public library had traces of Lactobacillus in it -- which I joked was due to the technician eating yogurt with one hand while preparing the library with the other. I saw at least once a library contaminated with tobacco sequences. Now, many of these were probably mistracking of samples at a facility which processed many different sorts of DNA -- indeed, there was a strong correlation between the type of junk found in an EST library and which facility had made it -- and the junk usually corresponded to another project.

But even stranger laboratory-generated wierdness could result. We had one case at MLNM where nearly every gene in a whole library seemed to be fused to a particular human gene. The most likely explanation we came up with is that the common gene had been sequenced, as a short PCR product, and somehow samples had been mixed or contamination left behind in a well. The strong signal from the PCR product swamped out the EST traces -- until the end of the PCR product was reached & the other signal could now be seen.

Still other wierd artifacts were certainly created during the building of the library -- genomic contamination, ligation of bits of DNA to create chimaeras, etc.

Deeper still, bits of the genome sometimes get transcribed or the transcripts spliced in odd ways. We would find ESTs or EST read pairs (one read from each end of the molecule) which would suggest some strange transcript -- but never be able to detect the transcript by RT-PCR. Now, that doesn't prove it never exists, but it does leave open the possibility that the EST was a one-time wonder.

All of these are rare events, but look through enough data and you will see them. So, my best guess for those overestimates was that everything in these companies database's was fed into a clustering algorithm & every unique cluster was called a gene. Given the perceived value of claiming a bigger database, none of them pushed on their Informatics groups to get error bounds or provide a conservative estimate.

Of course, once the genome showed up the evidence was there to rule out a lot of stuff. Even when the genome was quite unfinished, one of my pet projects was to try to clean the junk out of our database. So, once we started trying to align all our human ESTs (which included public ESTs and Incyte's database) to the genome I started asking: what is the remaining stuff. Some could never be figured out, but more than a little mapped to some other genome -- mouse, rat, fly, worm, E.coli, etc. Some stuff mapped to the human genome -- but onto two different chromosomes or too far apart to make sense. Yes, there could be some interesting stuff there (indeed, someone else did realize this was a way to find interesting stuff), but for our immediate needs we just wanted to toss.

If anyone from one of the other genomics companies would like to dispute what I've written here, I invite them to do so -- I think it is a fascinating part of history which should be captured before it is all forgotten.

Ah, them gold rush days!

Derek Lowe had a nice piece yesterday looking back on the genomics bubble. I might quibble with his benchmarking of the end of the insanity -- the stock market bubble would not peak until just before the 2000 elections, but it's a fine piece & pretty accurate.

I should know -- I was there. I was more than just there, I was a significant part of it. No, I didn't think it up & I won't try to exaggerate my importance, but for what is perhaps the poster child of genomics excess (and if not that, certainly in the Pantheon of genomanic deities).

When I got to Millennium they were still largely focused on the positional cloning of disease genes. But, they had started throwing sequencing capacity at ESTs, small bits of genetic message which serve as toeholds to larger ones. The catch was that the sequencing analysis software had been designed for positional cloning work & not ESTs, and it's a very different ballgame. When sequencing genomic DNA seeing anything which looked like a gene was interesting. But when sequencing stuff that is almost nothing but genes, the challenge was to sort the wheat from the chaff. Lots of scientists spent mind-numbing hours scanning BLAST reports for things of interest, and often found things. But this is a lousy technique -- not only might eyes glaze over (or neurons croak) from monotony, but a really interesting match might not be obvious -- what if the top hit was "Uncharacterized protein X" but the 3rd match down was "TotalPharmaceuticalGold"? Or worse, that BLAST couldn't even find a useable match? Plus, was that a match or an identity -- did you find something new or just rediscover a lousy fragment of the old? More mind numbing staring.

Enter a cocky recent Ph.D. After building up some expertise and some more refined tools (which in their embryonic form nailed me the one gene patent of mine perhaps worth something), I had built a system which churned through all the ESTs and crudely organized them by what made things interesting (and tried to ignore all the boring stuff). Ion channels -- look on this web page. GPCRs -- that's over here. Possible secreted proteins, look at this analysis. Furthermore, it also attempted to amalgamate all the different ESTs into a view which was higher quality, longer and more compact -- and tell you which things were already described as proteins and which might be novel. Plus, more sensitive algorithms than BLAST were used to pull things into families.

Now in all honesty, it wasn't nearly perfect. Some of the mind-numbing review had shifted to me -- the early versions in particular had every homology approved (and named!) by me. The semi-automatically generated names were ugly. Various EST artifacts could join webs of unrelated genes into a horrible tangle. But, now there could be reviews of consolidated, pre-analyzed data (though also in fairness nobody ever totally trusted it, so the manual sequence-by-sequence reviews often continued).

Of course, if you have a mountain of loot you probably want to protect it. Enter the lawyers. Millennium had always filed on their discoveries; now they had lots of discoveries to protect. But protect from what? Well, the paranoia was a loss of "Freedom to Operate", usually known as FTO. Nobody knew what would stand up as a patent -- but there were instructive examples from the early biotech era of business plans sunk by a loss of FTO -- and expensive lawsuits that clearly marked that loss. So the patenting engine took off -- an expensive insurance policy against an unpredictable future.

Of course, what the lawyers wanted for the filing was as much info as possible -- and the automated analyses provided lots for them. But, they had been designed to be viewed in a web browser individually, not printed out en masse. Worse yet, by this time Informatics & Legal were in separate buildings -- one of my least pleasant Millennium memories was trying to script the printing a raft of analyses on a printer located in the other building. Plus, if there were inventions then somebody had to have invented them -- such as the person who wrote the code to find them & then reviewed the initial output. And so, I started having dates with the paralegals, an hour of hand-cramping signing of document after document. At one point, there were somewhere between 120-140 patent applications where I was sole or co-inventor.

This was the late 90's and the hype was getting thick -- we were guilty but so were others. Millennium wasn't a big pusher of high gene counts -- at least in the terms of the day (but that's another whole story), but certainly we started selling all those genes we had & the ones we extrapolated were still out there. A key part of the business model was to sell the genes many times -- if we could sell the same gene to Lilly for cardiovascular & Roche for metabolic and AstraZeneca for inflammation, all the better. Not that anything underhanded went on; we'd present the case to each company & most of the deals had exclusivity only within a therapeutic area.

How much did we believe our own Kool Aid? It varied. There was one day where I got in a blue mood because I convinced myself that once MLNM found all the genes we'd put ourselves out of work! But that was an extreme ( and what I hope is the height of my own personal stupidity); most of the time we thought we might be right or we might be overestimating a bunch -- but that our partners were intelligent adults who could make the same calculations. Never did I see an attitude that we were fleecing the suckers.

In particular, I remember one of my colleagues making a comment when the Bayer deal was about to be signed. A premise of that deal is that Millennium would identify proteins which could be easily screened, associate them by multiple means with a plausible role in disease, configure an HTS assay for them -- and then Bayer would quickly get hits from their libraries. Those hits in turn would be used to finish determining whether the protein of interest really played a role in disease. MLNM's (over)confidence in genomics matched by Bayer's (over)confidence in chemistry. My colleague said it was one thing to think up such an idea -- and another to 'go over the cliff' -- and he was nervously surprised that someone else was joining us. He was one of the most sober minded fellows around & wasn't making allusions to
Bayer being foolhardy -- just that we were both taking the leap together. Alas, I didn't think to laugh & reply "The fall will kill you".

The genomics rush, alas, did not end with a huge rush of new drug candidates. We thought we'd get a huge leap in biology -- and we did, but not as big as we thought. Traditional drug development & biology had cleaned out the easy stuff; there weren't tons of hidden gems. The chemical biology concept pretty much disappeared from the Bayer collaboration -- turned out it was long-and-painful to configure all those assays (though we did get them done).

BUT, I will admit to being only a partially reformed genomics fan. We got oversold, and it hurt. Much effort was wasted, and just think of the savings if the patent office had declared that you had to have actual causal function to patent a gene! But, much of what we proposed doing still is worth doing -- or has been done. In some sense the genomics companies were just too early for their own good (though the late entrants such as DeCode haven't fared much better). There are no genomics companies -- yet genomics is everywhere. Basic biology fueled by the genome or the technologies pushed by genomics permeate the drug industry (based on the 2 large pharmas I interviewed at in the year MLNM laid me off & what I can read; constructive dissent on this point is welcomed). Probably no novel small molecule drug development history will be directly pinned back to a 1990's genomics effort -- but also virtually no drugs going forward will have their development unaffected by the knowledge of the genome. Everything is tangled up & confused & merged.

The genomics gold rush was insane & wasteful -- but they were fun times!

Watson's solo discovery of DNA

Well, my memory must be truly failing. No offense to Honest Jim, but I always thought he had a partner in finding the structure of DNA. And didn't some third guy share in the Nobel also? Plus, isn't there some experimentalist that people grouse should have gotten some credit?

But, I stand corrected:

In the last 50 years since Watson first discovered the structure of DNA, many advances have been made to enable researchers to study and dissect this macromolecule.

Now, some might warn that the Internet doesn't always have reliable information, but this is from a .edu site (and not some student's personal page either), so it must be right, right?

A few questions for Governor Palin

It's hard to believe that it's been a full month since the historic election. Well, depends on how you count a month, but today is the first Tuesday after the first Monday in December.

I was more of a political junkie in my youth, but I haven't sworn off the habit. Only in the last few days was I attempting to handicap the electoral college. TNG was a huge Obama fan, asking every adult in sight whether they would be voting for him. On the flip side, the other ticket had Miss Amanda quite charged up -- the idea of a Canino-American being one heartbeat from the presidency was too much to resist (though she has declared she will nip any groomer who attempts to apply lipstick to her!). Her disappointment that night was quickly salved by Obama's first major policy declaration in his celebratory speech. Alas, her closest kin have not been mentioned as in the running for the White House staff position.

Speaking of Governor Palin, it seems she will not be fading from the limelight. No, indeed it looks like her personal Iditarod will be going for the nomination in 2012. Alaska's chief executive made a number of comments during the campaign which induced consternation in the scientific community. Granted, the fruit fly remark was specifically about research on a totally different bug than Drosophila in a completely agriculturally-targeted setting, but it didn't endear her to the fans of Morgan & Bridges. Given she has four years to prepare, it wouldn't hurt to start now. And, in the spirit of reuse, should she not run it would seem the majority of these queries would apply to the majority of other Republicans who went for the high office this year.

1) You have publically taken stands that some views held by a minority (or less) of the scientific community should be accepted and used as the basis for policy decisions (e.g. the existance and/or cause of global warming trends) and/or taught in public schools as viable alternatives to the majority view (e.g. creationism). How do you choose which 'maverick' scientific theories have merit and which do not?

2) Which of the following maverick theories, relevant to major issues in this country today, should be taught in public schools or used to guide policy:

2.1) Healthcare (research priorities, Medicare/Medicaid reimbursement policy)

2.1.1) Childhood vaccines cause autism

2.1.2) AIDS can be treated more effectively with vitamin combinations than antiretrovirals

2.1.3) AIDS is caused by lifestyle factors and not the virus HIV

2.1.4) High cholesterol levels do not cause heart disease; cholesterol lowering using drugs risks cancer & depression

2.2) Physical sciences

2.2.1) Petroleum is not a limited supply of fossil remains of ancient lifeforms but rather is constantly created by processes deep in the earth (clearly an area where Ms. Palin has declared as in her sphere of expertise)

2.2.2) Manned space travel through the van Allen belts is guaranteed to be lethal; funding an attempt to land on the moon should be cancelled.

2.2.3) Einstein's Theory of Relativity is clearly wrong, as the concept of time dilation is so opposed to normal experience as to be laughable.



3) Should the U.S. government ever fund research outside its borders? Under what conditions should such operations be funded, if ever?


4) To what degree should non-expert politicians alter the research funding priorities set by experts in the field?

5) What, if any, useful science has come from studying fruit flies? Should the U.S. fund any further research? What other organisms do you also feel are not worth researching?


This is just a draft; readers are invited to submit further questions via the comments

Cilantronomics

We had dinner last night in one of favorite local eateries, a wonderful little Mexican place in a neighboring town. When I sat down, my eye was drawn immediately to my sort of dish -- one with a rich sauce combining the tang of tomatillos with the zing of cilantro. I picked well.

I really do love cilantro. Despite an extensive garden growing up, it was only in my adult life that I encountered this herb. I've been making up ever since. It works well in so many situations, not only in Mexican but also a lot of Asian cooking. The excellent Tibetan buffet in Central Square uses it extensively, particularly in a salad that works equally well before the meal as after, with the bite of cilantro contrasting with sweet cherry tomatoes and mango chunks. I even have a pot of it on my desk, which I share with my neighboring cilantrophiles.

However, not everyone loves cilantro. And it isn't just some folks might not like that little edge -- no, for some it tastes awful. Rather than some herbal bite, they taste soap. Or weirder. What other herb has its own http://www.ihatecilantro.com/?

Is it genetic? Alas, there has been a dearth of research on cilantro tasting -- indeed, it doesn't seem to rate an OMIM entry. There is a compound called PTC which is known to untastable by some, including this correspondent, and is genetically linked (my father can taste it; haven't surveyed the rest of the clan). With the help of some research by one of my office neighbors (and fellow cilantro fan), I did learn that 23andMe includes cilantro taste in their questionnaire. It isn't clear whether the other public and private genome projects are tracking this key phenotype.

Okay, I jest a bit. But while the ability to taste cilantro, or PTC, or the host of other innocuous traits which are staples of grade school genetics labs (e.g. widow's peak, hitchhiker's thumb, attached earlobes, etc) aren't exactly critical to understand, they will be interesting to understand. Widow's peak doesn't change someone's life, but to understand it is to understand a bit more about how patterns are laid out. The sciences of smell and taste have advanced tremendously over my lifetime; a whole new taste was found! Identification of smell receptors (recognized by a Nobel) and taste receptors have given great insights -- but we still understand very little.

Are there practical applications for smell & taste research? Of course. But to me the most interesting part is to figure out how it works. PTC doesn't seem so complicated, as the test paper doesn't have any flavor other than paper. But cilantro seems like a much more complicated, and interesting, question. Why does it taste bad rather than just not taste?

Is there an underlying soapiness which I just don't taste? In this case, tasters have a receptor for the magic compound (which is what?) and non-tasters simply lack it. Or does a different receptor bind the compound in tasters, in which case they have a gain-of-function mutation? Or, perhaps they have a partial loss of function -- there are a number of known compounds with concentration-dependent odor, probably due to differential binding to different receptors. In other words, at low concentrations these compounds bind to high-affinity receptors (yielding one perception) and at high concentrations some additional one Or, perhaps a partial gain of function in the non-tasters -- the same model could apply.

No, I wouldn't recommend basing an R01 application on the science of cilantro taste. Nor is it likely to tease a few million from some VCs as the core of a business plan. Cilantro haters will probably never have the option of genetic therapy to alter their perception. But it is still an interesting scientific question, and I look forward to personal genomics shedding some light on it.

The Blue Bus Grows Up

A striking characteristic of the Cambridge biotech scene is how it is concentrated in an urban setting. While there are a lot of biotechs elsewhere in Massachusetts, the Hub's hub is clearly a 2+ mile long zone. One challenge this offers is getting to work via Boston's transportation system.

Boston doesn't have an awful transportation network, but it isn't golden either. The transit system is decent, but the routes still largely follow a radial design, with routes that have changed little in the last half century (I kid not; I've seen a map that old & it takes a careful eye to find the differences). An extensive network of commuter rail feeds the downtown, but is split between two termini separated by a mile. The highway network has a number of gaping gaps, due to a mass cancellation of uncompleted highways in the early 1970's. However, this wasn't necessarily bad for biotech; I've spent half my career in offices that would literally be in the middle of the road should those highways have been built (for example, this very different vision for 640 Memorial Drive than a genomics-based pharmaceutical company).

The commuter rail option presents a particular challenge. One station, South Station, is connected to the Red Line subway which has two stops (Kendall & Central) proximal to many biotechs. The other station, North Station, has terrible connections to Cambridge, other than the perhaps future expansion of the zone into the Cambridge-Charlestown-Somerville interzone. But, if you live north of town it's either deal with getting from North Station to Cambridge or brave I-93. So, by multiple subway connections or a tortuous pedestrian path through Mass General's campus to the Red Line, a not tiny cohort of biotechies has made their commute this way.

Then about five years ago a new option appeared. Little blue buses promising a single seat ride from North Station to Cambridge, with a twisting route designed to be near nearly every major employer in the zone. Called EZRide, for $1 anyone can ride, but better yet the larger employers offer ride-all-year stickers.

The service was a bit slow starting up & went through a few hiccups, but over time it has been impressive. If memory serves, the initial frequency was every 30 minutes; this has been steadily dropped so that now a bus shows up every 8 minutes during commute time. However, demand has grown even faster; during core commuting times the bus is at its legal limit, with only ~30 seats and less than a dozen legal standees.

But a couple of weeks ago the announcement came out: a new vendor would be running full size buses on the route. And last week they showed up. On the one hand, there are more seats -- but not as many as one might think due to the layout. On another, more legal standees and less of the EZRide shuffle -- having to exit the bus at the early stops to let people off, as if you were standing you were a cork in aisle of the old buses. The longer buses don't handle the tight turns as well but do away with the most unpleasant aspect of the old buses: their short wheelbase combined with Cambridge's potholes yielded an amusement-park quality bumpy ride (particularly unpleasant if you made the mistake of leaning against the wheelchair lift).

EZRide isn't run by the transit system, but rather by a quasi-public entity called CRTMA which is charged with improving transit into Cambridge. The director, Jim Gascoigne, is energetic and personable and often on the scene, particularly when weather or accidents snarl require emergency re-routing.

In some ways the EZRide highlights issues in Boston. The T does an okay job, but it apparently never occurred to them in several decades that a market existed for a route from North Station to Cambridge. I've also seen the truly surreal quality of Boston from the blue bus: due to some construction, one Boston police officer directed the bus to stop in a new location, where the driver was promptly berated & ticketed by a second Boston officer. This is the town where the mayor had major apoplexy when a nearby airport added Boston to their name; transportation issues are about turf battles as much as moving people around. The planners also have a fondness for expensive megaprojects (the current shopping list can be found here). Several of these would have important benefits for the biotech zone -- for example, the proposed Urban Ring would run right through it & connect the zone to the Longwood Medical Area.

However, perhaps what is more realistic are more EZRide-like services, perhaps connecting to the south (Brookline, Brighton/Allston) that have surprisingly poor connections, or to the large transit hubs to the north (Wellington, Anderson). A direct connection to Charlestown wouldn't be a bad concept either.

In the meantime, I'll keep riding EZRide. And anxiously awaiting my train line(s) getting the free WiFi service a few lucky commuters have gotten to pilot. One more good reason to stay off the road and out of my car!

Panda genome arrives

China announced over the weekend the completion of the giant panda genome.

For the benefit of presidential candidates who can't conceive of the value of scientific research on bears I'll suggest a few questions worth exploring in the panda genome (beyond the obvious direction of weapons development)

First, the panda genome is one more mammalian genome to add to the zoo. For comparative purposes you can never have too many. Since other carnivore genomes are done (first & foremost the dog, but cat as well), this is an important step towards understanding genome evolution within this important group. It is the first bear genome, but with the price of sequencing falling it is likely that the other bears will not be in the extremely distant future (with the possible exception of Ursa theodoris).

Second, completion of a genome gives a rich resource of potential genetic variants. In the case of an endangered wildlife species such as panda, these will be useful for developing denser genetic maps which can be used to better understand the wild population structure and the gene flow within that structure. Again, if you are running for president please read this carefully: this has nothing to do with paternity suits. If you want to manage wildlife intelligently and make intelligent decisions about the state of a species, you want to know this information.

Third, pandas have many quirks. That bambooitarian diet for starters. Since they once were carnivores, it is likely that their digestive systems haven't fully adapted to the bamboo lifestyle. Comparisons with other carnivores and with herbivores may reveal digestive tract genes at various steps in the route from meat-eater to plant-eater.

Fourth, as the press release points out, there are many questions critical to preserving the species which (with a lot of luck) the genome sequence may give clues to. First among these: why is panda fertility so low? U.S. zoos have been doing amazingly well in this century, but that's only 4 breeding pairs. The Chinese zoos have many more pandas & many more babies, but it's going to take a lot more to save the species.

Great Galloping Gerbils!

An item on CNN mentioned that satellite technology will be employed to monitor the endangered California Kangaroo Rat. This reminded me of a Nature paper this summer I meant to mention, because the image blew me away (plus it's the first time I've seen Google Earth used as a source for a scientific paper!).

The paper is about models of disease spread (these gerbils are reservoirs for plague), but the thing which jumped out was the Google Earth image; the two images above are from around the same region of Kazakhstan. The gerbils clear vegetation from around their burrows, and these burrows are in huge complexes. The more zoomed in image above is several kilometers wide and yet is packed with gerbil burrows. If you have Google Earth and look around 44.766991 76.449699 you can zoom way out and still see the gerbil complexes. I saw some huge prairie dog towns out west when I was a boy, but nothing on this scale!

How many animals leave traces which can be seen from 30+Km up (the image quality is uneven for this region of the world in Google Earth -- clearly shots are merged from different seasons and resolutions, but 30Km is a conservative estimate)? Human activity obviously. When I think of animal-built structures I generally jump to beaver dams or termite mounds, but they aren't nearly this extensive.

The Joys of DIY Dynamic Programming

For nearly the first decade of my bioinformatics career I carried around a dirty little secret -- well, at least at times I felt it was one. I had coded many things, I could explain many algorithms, but I had never coded a dynamic programming alignment algorithm -- the core to so much I did. I had slightly hacked one version (just to have it do an all-all comparison of a database, doing each possible pairing only once). Finally, for a bunch of reasons, I sat down and did it -- my very own Smith-Waterman implementation.

I'm reminded of this because a couple of weeks ago I rolled back my sleeves and knocked one out again. Now, just the fact I did this reveals a bit about me. I did find at least two freely available C# implementations on-line (e.g. the C# version of JAlign) and there is a plethora of C implementations. There is also Ewan Birney's magnificent Dynamite, pretty much the catch-all for the field (Dynamite is a programming kit for doing this; in effect a programming language for dynamic programming). But, partly as a point of pride & partly because I saw I'd need to hack the one C# copy I looked at in detail, I did it. I even wrote a schmancy version -- a simple cDNA to genomic sequence aligner with two classes of gaps (one being an intron, with a really trivial model of a splice junction -- I think it used dinucleotides) All coded in Perl -- no speed demon, but it solved the problem where we needed it.

Now, it took me a good few hours to do it -- better than the few days of the first time, but not instant. I can claim that this time I didn't fall back on any study aids, such as the many online descriptions or Eddy & Durbin's & co. very well written book.

The implementation says a lot about me too. I thought of many ways to code it and finally settled on one. For example, there is the question of how to represent the alignment matrix; I used a two-dimensional array scheme (actually implemented using dictionaries -- a holdover from my Perl-centric days) but I could have also made it a graph of nodes. There is also the actual thrashing through the matrix -- the algorithm is inherently recursive, but following familial idiosyncracies I wrote the code to use loops -- well, actually I completely waffled and implemented so it can use recursion, but actually loops through! The applications I'm considering are going to be short alignments, so I didn't worry about memory efficiency (who wants to be that will bite me back!) nor did I fixate on speed (care to double the bet?) -- indeed, I wrote it to allow all sorts of baroque variations, such as different penalties for opening gaps in the two different sequences & for basic profile-to-sequence alignments. Plus it is either Smith-Waterman (local) or Needleman-Wunsch-Sellers (global), with a simple toggle.

So now the pitch: If you are a bioinformatics programmer & you haven't written one, I urge you to do it. It's great practice & nothing illustrates an algorithm like trying to implement it. If you don't consider yourself a programmer, guess what? It's perhaps not the obviously easy first start, but just thinking about it will stretch your mind. Plus, you get a free bioinformatics Rorschach test from your implementation choices!

One last thought: who can think up (and execute) the most comically baroque -- but functional -- implementation of S-W/NWS? Has it already been done in PostScript? How about in a relational database (I've written some pretty baroque SQL this year, but I doubt I could tackle this)? S-W as an Excel spreadsheet? Coded with glider guns? A full description for a true Turing machine? Of course, the grand prize winner would clearly either be to build a DNA computer to compute an alignment -- but perhaps that could even be topped by implementing the algorithm with living cells as the alignment cells!

One more Olympic thought

One other item that was in the mental draft of yesterday's Olympic pondering, but was inadvertantly dropped. Another possible genetically-driven edge in athletic performance would not be directly on performance but on the reaction to performance. Prime athletes might have different pain or endorphin responses, less post-exercise inflammation, different injury responses. Some of these might be specific to specific events or types of sports -- joint pounding running or gymnastics puts very different stresses on the body than something like swimming or speedskating.

An Olympic Pondering Decathlon

Okay, my biannual stint of Olympic watching is about to conclude. A bunch of speculations suggested by this year's stretch, starting with the utterly unscientific and ending with more genomic oriented queries.

1) Having now watched two Olympics using a Digital Video Recorder, it's completely clear that having a few fast forward speeds is no way to navigate multi-hour recordings to find what you want. Surely there are better UIs for this! The thumbwheel on an iPod is one obvious choice, but there must be other ways.

2) The Summer games are blessed with multiple events which touch on multiple disciplines: the decathlon, heptathlon, modern pentathlon & triathlon. Why isn't there a true multi-discipline Winter sport? Biathlon is a glorious combination of two diametrically opposed skills -- racing and precision shooting -- and there is also the Nordic combined, but neither of these sample a wide range. How about this for a Winter hexathlon:
A) 500m long-track speedskating
B) 2500m long-track speedskating
C) Downhill skiing
D) Slalom
E) 10Km X-C skiing
F) ski jump (small hill)

3) I once contemplated attending a HUPO meeting in Beijing; atop an interesting program there was a post-conference trip option to tour the country. There were two issues: I'd have to foot my own travel expenses & I'd be in serious hot water at home for visiting the Wolong panda center solo. But, now I'd definitely go -- particularly if they replaced a typical dry scientific kickoff with another Zhang Yimou spectacular, I wouldn't hesitate!

4) As a kid I did occasionally have Olympic daydreams. I'm a bit over the hill now, but between athletes older than I such as Dara Torres and hearing that some countries will field just about anyone, perhaps I gave up too soon. If I could pick anything, it would be long track speedskating, the most graceful speed sport bar none. But, more realistically perhaps I could go for the 1500 meter freestyle swimming -- I'd estimate my time is off by only a factor of 3 -- perhaps with some regular training I can get that down to 2!

5) Of course, even with some extensive training I'd look pretty odd on the blocks -- I'm 5'8" and from what I can tell in the TV coverage, it's a rare swimmer who isn't a few inches over 6'. Clearly there are advantages to height in a large number of sports -- but I'm also clearly too tall for a shot at women's gymnastics (atop the other obvious issue). It would be interesting to see which sports have the highest and lowest dispersion in athlete height -- and what those patterns look like. What sport should I have chosen based only on my height?

6) During the Olympics, the world's tallest living woman died, after a life with many health difficulties. Clearly, there are limits to the advantages to height. What sport has the tallest athletes?

7) What more subtle anatomic characteristics might lead to athletic advantage? Differences in muscle fiber composition are an oft-cited one. A TV profile of superswimmer Michael Phelps claimed he is 'double jointed'. But what else. For example, are there subtle differences in some individual's lungs which lead to more efficient air exchange? Smoother surfaces on bone joints?

8) Diving lower, are there biochemical differences? Again, could there be differences in oxygen transfer or usage? Differences in energy metabolism?

9) If we did genome screens of the athletes, what SNPs would we find over-represented? How many of those would be 'obvious' and how many would lead to new genes which influence performance? Already there is at least one company offering genome scans to predict what sport you should stuff (er, steer) your kid into.

10) The sad story of Flo Hyman illustrates another aspect of selection for unusual body types: she died of a aortic dissection due to Marfan's syndrome, which probably also led to her tall, thin stature which was an advantage on the volleyball court. What other genetic variants have a dicey risk/reward trade-off in the athletic arena? And how many of these are a serious medical issue for regular folks?

Any leads on when pandas join the genome club?

Tonight's bedtime conversation veered all over the map (par for the course), but at one point touched on the announced Chinese effort to sequence the genome of the giant panda. Of course, a key concern was that this did not involve any pain or injury to the beloved bicolors, so the concept of buccal swabbing was introduced.

This project was announced last spring. I thought it was planned to be released during the Beijing Olympics, but that is apparently an invention of my imagination.

So, anyone out there in the know care to hint or leak? When will the first ursid genome arrive? And who was the lucky bear?

Larry Ellison, please join the 21st century!

I've sniped at Microsoft at least once, so in the interest of balance I'll take a crack at the other software giant I rely on but also frequently complain about: Oracle.

Oracle is truly amazing. Now, I don't have much experience with other relational database systems, so this isn't comparative. But relational databases are amazing. I give it a query of what I want and if I cross all my t's and dot all my i's, then huge databases are searched rapidly (often a matter of seconds).

My first complaint is with inconsistency in syntax. Oracle has several flavors of text types depending on how big you might let your text get. I mostly query databases, not create them, and so I generally want to treat them all the same. Now there might be some good reason I need to use a different function to get the substring from each type, but I really don't want that hassle. But if I'm stuck with it, why couldn't you keep the argument orders the same? Standard substring, like every substring method I've ever met, has the order: string, start, length. But for the really big text columns ("CLOB"s), it's string, length, start. WHY???

But worse, is when I'm having trouble dotting those i's and crossing the t's, Oracle really doesn't give much help. The error messages are somewhere out of the 60's.

For example, one handy feature of Perl (and other environments) is some attempt to identify common pitfalls and give hints about them in the error messages. A common mistake for me is to include an extra , in my query

select x,y,z,
from mytable

In this example, of course, it's small -- but many of my queries are 30-40 lines long. Surely it could detect that the unrecognized field name is a reserved word and therefore hint that I've included an extra comma.

Another example. For one query I have I've been parsing out a numeric string and then trying to convert it to a number. Alas, somehow my parse is failing and I'm getting some unconvertable strings back. Oracle gives me an error that it can't convert something to a number -- but keeps that something a secret from me!

I could go on-and-on. Line numbers for the error are frequently non-helpful, the error messages don't give the context of the offending bit, etc, etc.

The one thing I haven't tried is to edit my queries in Visual Studio, which has an SQL mode. I really should try that -- not that VS's error messages are always golden, but it is good about highlighting the likely neighborhood of mistakes in a way SQL Developer (the Oracle interface I use) just doesn't even attempt

Ah well, I'll live. Larry probably has bigger fish to fry. Personally, though, if it was my software I'd be cringing.

Farewell to some bits of olde Cambridge

We sent off one of our departing colleagues in style yesterday, taking him to the finest cuisine in Cambridge: the MIT Food Trucks. These institutions are various privately run trucks serving hot foods, from around the world, to long lines of students. While private, the trucks are sanctioned: not only do they have specially reserved parking spots but they also are listed in the MIT Food Service website.

However, first we had to find them. Their previous locale is now a major hole in the ground, to be filled in with the new Koch Cancer Institute (or some such name). With the MIT web site's help, we were able to find the new location.

During the year I (and others) have discovered two other institutions which were not so lucky.

It was a bit of a shock one day to discover the Quantum Books location cleared out, though not much after recollection. Quantum was a bookstore specializing in technical books -- particularly computing books. It was a handy place to browse such books before investing; I've spent far too much on books that looked good but were awful. The not so much shock was on thinking about it: not only was Quantum getting hammered by the usual Amazon internet tide, but they were in a perfectly awful location. While there might be a lot of commuter traffic, otherwise they were in a nearly retail-free zone that is one of the many crimes against urban design inflicted on Kendall Square in the 60's/70's. They tried to have a children's section and other experiments, but it was hard to see much hope of success. Quantum isn't kaput, but has gone to a nearly totally Internet model, but unless their fans are super-loyal, it's hard to see that lasting long.

Cambridge was once a center of conventional industry. For example, a huge fraction (I forget the amount; it's on a plaque in the park on Sidney Street) of the undersea telegraph cable used in WW2 was created in Cambridge. But fewer and fewer remain. Even in my short tenure at least 2 candy factories have closed, leaving only one left (tootsie rolls!). A prominent paint company moved out a few years ago. Sometimes it's hard to tell what's still active & what is only an empty shell. But not in this case.

There will be no more "goo goo g'joob" in Cambridge; Siegal egg company has not only cleared out but been cleared out -- the building is gone. A distributor of eggs, they were across the street from one MLNM building and adjacent to Alkermes. Indeed, it was that proximity to MLNM that forced me to notice them: their egg trucks would sometimes block Albany Street while backing into the loading dock, trapping the MLNM shuttle van (always with me late for a meeting!). I think the demolition was part of the adjacent MIT dorm construction, but perhaps a new biotech building will go in. By chance, the Google street view catches the building being prepared for demolition.

Will some future writer remark wistfully on the disappearance of biotech buildings from Cambridge? It's difficult to imagine -- but who a century ago could have imagined Cambridge getting out of the business of supplying everyday things.

Paring pair frequencies pares virus aggressiveness

Okay, a bit late with this as it came out in Science about a month ago, but it's a cool paper & illustrates a number of issues I've dealt with at my current shop.. Also, in the small world department one of the co-author's was my eldest brother's roommate at one point.

The genetic code uses 64 codons to code for 21 different symbols -- 20 amino acids plus stop. Early on this was recognized as implying that either (a) some codons are simply not used or (b) many symbols have multiple, synonymous codons, which turns out to be the case (except in a few species, such as Micrococcus luteus, which have lost the ability to translate certain codons).

Early on in the sequencing era (certainly before I jumped in) it was noted that not all synonymous codons are used equally. These patterns, or codon bias, were specific to specific taxa. The codon usage of Escherichia is different from that of Streptomyces. Furthermore, it was noted that there is a signal in pairs of successive codons; that is that the frequency of a given codon pair is often not simply the product of the two codon's individual frequencies. This was (and is) one of the key signals which gene finding programs use to hunt for coding regions in novel DNA sequences.

Codon bias can be mild or it can be severe. Earlier this year I found myself staring at a starkly simple codon usage pattern: C or G in the 3rd position. In many cases the C+G codons for an amino acid had >95% of the usage. For both building & sequencing genes this has a nasty side-effect: the genes are very GC rich, which is not good (higher melting temp, all sorts of secondary structure options, etc).

Another key discovery is that codon usage often correlates with protein abundance; the most abundant proteins show the greatest hewing to the species-specific codon bias pattern. It further turned out that highly used codons tend to be most abundant in the cell, suggesting that frequent codons optimize expression. Furthermore, it could be shown that in many cases rare codons could interfere with translation. Hence, if you take a gene from organism X and try to express it in E.coli, it would frequently translate poorly unless you recoded the rare codons out of it. Alternatively, expressing additional copies of the tRNAs matching rare codons could also boost expression.

Now, in the highly competitive world of gene synthesis this was (and is) viewed as a selling point: building a gene is better than copying it as it can be optimized for expression. Various algorithms for optimization exist. For example, one company optimizes for dicodons. Many favor the most common codons and use the remainder only to avoid undesired sequences. Locally we use codons with a probability proportional to their usage (after zeroing out the 'rare' codons). Which algorithm is best? Of course, I'm not impartial, but the real truth is there isn't any systematic comparison out there, nor is there likely to be one given the difficulty of doing the experiment well and the lack of excitement in the subject.

Besides the rarity of codons affecting translation levels, how else might synonymous codons not be synonymous? The most obvious is that synonymous codons may sometimes have other signals layered on them -- that 'free' nucleotide may be fixed for some other reason. A more striking example, oft postulated but difficult to prove, is that rare codons (especially clusters of them) may be important for slowing the ribosome down and giving the protein a chance to fold. In one striking example, changing a synonymous codon can change the substrate specificity of a protein.

What came out in Science is using codon rewriting, enabled by synthetic biology, on a grand scale. Live virus vaccines are just that: live, but attenuated, versions of the real thing. They have a number of advantages (such as being able to jump from one vaccinated person to an unvaccinated one), but the catch is that attenuation is due to a small number of mutations. Should these mutations revert, pathogenicity is restored. So, if there was a way to make a large number of mutations of small effect in a virus, then the probability of reversion would be low but the sum of all those small changes would be attenuation of the virus. And that's what the Science authors have done.

Taking poliovirus they have recoded the protein coding regions to emphasize rare (in human) codon pairs (PV-Min). They did this while preserving certain other known key features, such as secondary structures and overall folding energy. A second mutant was made that emphasized very common codon pairs (PV-Max). In both cases, more than 500 synonymous mutations were made relative to wild polio. Two further viruses were built by subcloning pieces of the synthetic viruses into a wildtype background.

Did this really do anything? Well, their PV-Max had similar in vitro characteristics to wild virus, whereas PV-Min was quite docile, failing to make plaques or kill cells. Indeed, it couldn't be cultured in cells.

The part-Min part wt chimaeras also showed severe defects and some also couldn't be propagated as viruses. However, one containing two segments of engineered low-frequency codon pairs, called PV-MinXY, could but was greatly attenuated. While its ability to make virions was slightly attenuated (perhaps one tenth the number), more strikingly about 100X the number of virions was required for a successful infection. Repeated passaging of PV-MinXY and another chimaera failed to alter the infectivity of the viruses; the attenuation stability through a plethora of small mutations strategy appears to work.

When my company was trying to sell customers on the value of codon optimization, one frustration for me as a scientist was the paucity of really good studies showing how big an effect it could have. Most studies in the field are poorly done with too few controls and only a protein or two. Clearly there is a signal, but it was always hard to really say "yes, it can have huge effects". Clearly in this study of codon optimization writ large, codon choice has enormous effects.