Field of Science

What I learned at the NIH workshop

This morning's NIH workshop was very useful - I learned quite a bit, and it sure got me ready to start preparing for applying next fall. My plan is to redo the DNA uptake proposal I submitted to CIHR two years ago, and send versions of it to both CIHR and NIH. A new post-doc arrives in a couple of weeks to begin working on aspects of DNA uptake. I'll be just about done teaching by then (classes over), so he, I and the present post-doc (about to be Research Associate) will spend much of the summer getting the preliminary results these proposals need.

What I learned this morning: (I'm collating my scattered notes here so I won't forget them)

Sign up for the weekly NIH Announcements emails. Most of the contents are of no interest to me, but I'm a fast reader so I should be skimming them anyway.

Find a Program Officer and talk to him/her repeatedly about the science. NIH is full of very helpful people, who measure their success by whether or not your grant gets funded! (Not like CIHR.) So the first step in grant preparation is finding the program officer whose interests best match yours. I have the url for a listing of these people (no, it's just the list of Institutes; I guess I should start by calling NIAID - they handle infectious diseases). Anyway, I'll do this on Wednesday. I can also ask US colleagues who their program officer is. And when I go to US meetings I should look for the NIH people and talk to them about my plans. I'm going to the big microbiology meeting in May -- NIH should have a substantial presence there -- and to two meetings on evolution (evolution of sex and molecular evolution) in June (NIH people might be there too).

Use the cover letter to direct your proposal to the right people and places: Name the names of the NIH people who are on your side.

Relationships matter as much as good science. Again, this is all about getting to know a program officer.

Brag! This is hard for Canadians, but being modest is a big msitake here.

NIH is flush right now. Obama has given them $10 billion that must be spent by Sept 2010 (on top of their annual budget of about $30 billion). Most of this can't go outside the country, but some can, as subcontracts and foreign components of domestic grants. And it will take the pressure off of the main grant stream, so hopefully getting funded will be easier for at least the next several years.

Focus on the 'R01' grants: Don't bother applying for the little 'R03" grants ($50k/year for only two years). But it might be worth applying for an 'R21' grant ($275K over two years) - you don't need as much preliminary data as you do for the regular 5-year R01 grants because they're intended to let you generate the preliminary data.

Money is always tight, so having US collaborators is a bonus. I wouldn't be a co-investigator or sub-contractor on someone else's grant (this is our own work), but I should be able to line up a couple of solid American collaborators, or at least have letters of support from Americans who will provide help and advice if needed. But the need for this varies with the NIH program, so I need to talk to 'my program officer'.

Spell out up front why this foreign grant deserves funding. There are three criteria. 1. opportunities not available in the US. In my case, it's that nobody in the US wants to do this, and only I have the combination of evolutionary and molecular expertise to see why it's so important and to carry it through. (Of course this argument will depend on how much evolution is in the grant.) 2. Augmentation of existing US resources. Can I claim this? 3. Potential for improving the health of US taxpayers (it's their money). I can argue that understanding why and how bacteria take up DNA will give is therapeutic targets.

Commit at least 15% of your 'effort' to this project. 20% is probably better. But be prepared to back this claim up with evidence - don't claim to be putting 50% of your effort into each of several projects.

The Budget section of NIH proposals is complex: I was looking forward to the new 'modular' budgeting, where you just need to say how many $25K modules you want per year (up to $250K/year), but this doesn't apply to foreign grants.

Ask for some salary. Canadian faculty have 12-month salaries and we're not allowed to ask for any salary support from the Canadian agencies. But salary support is a standard item on NIH grants so we're not seen as very serious if we don't ask for any. The legalities of doing this are a bit uncertain - I asked my Department Head whether the money is allowed to travel from the UBC Finance account into my bank account; he's going to ask the Dean. Someone said we are allowed to get the equivalent of two months' salary - I don't know if this only applies to consulting fees and running a company on the side, or also to salary from outside grants and contracts.

Some 'indirect costs' can become direct on foreign grants. Foreign grants get only 8% as indirect costs to the institution, and these are intended to defray only the costs of administering the grant, not to cover the indirect costs of doing the research. So some expenses that in the US would be considered indirect costs to be provided by the institution (e.g. phone, office supplies, secretarial support) on foreign grants can be included in direct costs.

Ask for more money than you need: My previous NIH grant was awarded the full amount I had asked for, but now across-the-board cuts of 10% or even 20% are common. So budget in some extra. So I guess I should ask for 20% of my salary?

Don't be overambitious: Don't propose to accomplish an unreasonable amount of science. The reviewers won't think you're exceptional, just naive.

Plan for the long term: When planning your proposal, think beyond the 5-year term. What will you want to do next? How will what you are proposing now affect that? What are your long-term goals and how does each project take you closer?

Be very careful not to write anything that might turn a reviewer against you. Don't be disparaging or smart-assed. Check the membership of the study sections your proposal is likely to be sent to, and be sure to cite all their relevant work.

The font matters? One speaker recommended using Ariel 11 font. I'll have to email him to ask why.

Don't leave town right after your proposal is submitted: The NIH system scans each proposal for technical errors (wrong kinds of information in wrong boxes), and gives you only two days after submission to fix these.

It's fine to apply to both NIH and CIHR for the same project. If both succeed, NIH is happy for the aims to be readjusted and the project split up into two parts, one funded by each agency.

Starting in 2010, a rejected proposal will only be allowed one resubmission. NIH is trying to clear out the deadwood of the grants that just won't die.

Once the project is funded, the budget allocation is flexible. I used to think that NIH budgets were quite rigid, but if I later decide that I need to spend the money on something other than what was originally budgeted I can do so. If I'm changing key personnel (not just a tech or student) or if it would change the 'scope of the work' I need to get NIH approval, but that's usually just an email. However there's no allowance for currency fluctuations.


I'm spending the morning at a workshop on getting NIH grants, sponsored by some consortium of UBC research administrators.  It should be time well spent, as I plan on submitting a proposal next fall to get money for ambitious work on DNA uptake.   

Then maybe a bit of the afternoon can be spent working with the post-doc to finish up the E. coli-Sxy manuscript, so it can be sent (hopefully for the last time) to our former-post-doc co-author in Ireland.

Then a day of thesis defense (someone else's student) and an always-enjoyable meeting evaluating proposals for interdisciplinary workshops.

Then maybe, just maybe, I'll have time to take a long-overdue look at our computer simulation manuscript.

Minor manuscript submitted!

Our London colleagues agreed with our improvements and arguments, and suggested ways to improve the cover letter.  So now we'll see if the editor also buys our arguments.

Too bad I'm just one of the middle authors.  I feel like I've done a lot of work on it, both actual experiments (the time course I did in December) but the senior author is, rightly, the London investigator whose grant supported most of the experiments, and the first author is, rightly, the person in his lab who did those experiments.  My post-doc is sharing official-first-author credit with that person, largely I think because she's taken the initiative of putting the paper together and doing most of the writing.

Minor manuscript progress (major progress on a minor manuscript)

A minor manuscript we've been working on (the one I did the time course for last December) was recently provisionally accepted by an appropriately minor journal, but one of the reviewers wanted us to do some major additional experiments. However neither we nor our coauthors in London are keen to invest any more work on its topic (why some strains of Actinobacillus pleuropneumoniae are competent and others aren't).

None of the unanswered questions can be answered by simple experiments, and if we were to follow this trail we would want to work in Haemophilus influenzae, the species our research focuses on. In particular, the two analyses recommended by the reviewer would both be a waste of time. One, knocking out the sxy gene in a strain that transforms very poorly, wouldn't tell us anything about why the strain doesn't transform better. Neither would the other, sequencing all the competence genes in a strain that transforms well and comparing them to the already-sequenced genes of this strain, because we have no functional framework for interpreting any differences we might find (i.e. we don't know anything about how the encoded proteins do their jobs).

So the post-doc and I spent much of yesterday rewriting the manuscript to address the reviewers' concerns and misunderstandings, and composing a tactful cover letter to the Editor explaining why we aren't going to do the experiments. The paper is much better now - while rewriting we realized that we had been underplaying an important implication of one of the experiments - the demonstration that the A. pleuropneumoniae sxy gene works perfectly in H. influenzae. These genes are quite divergent (only 24% amino acid identity) and because the two species are in the two different Pasteurellaceae subclades, this result lets us conclude that Sxy functions identically in all of the Pasteurellaceae.

We've now sent the revisions off to our London coauthors (without the point-by-point response to the reviews, which we need to compose today). They've been a bit more cautions than us on this manuscript, arguing even before we submitted it that more experiments probably should have been done, even though they don't have the resources to do them. Hopefully our arguments will convince them that we should just send the revised manuscript back to the Editor and hope for the best. Our cover letter to the Editor does say that, if he still thinks it necessary, we will make and test the sxy knockout, but by 'we' we mean them.

ANOVA success

I found our lab stats package (Graphpad Prism), and read bits of its very detailed and user-friendly help files. Then I pasted in my data and did some two-way ANOVAs. Then I read the help files some more and decided I should have done 1-way ANOVAs with 'repeated measures'. (That tells the software to consider all the values in the same row as belonging together.)

I first analyzed each group of tripeptides separately (the blue ones as one dataset, then the pink, then the yellow). The blue set had significant differences between the columns in the ANOVA (p=0.01). It also had significant differences between the bright-blue column and all other columns by Tukey's multiple comparison test. I used this rather then the Bonferroni test but I'm not sure which would have been more appropriate - I think this is less sensitive than the experiment deserves, because I had specific comparisons in mind from the start. The pink set had not-quite significant differences (p=0.058) in the ANOVA, and not-significant differences between any pairs of columns in the Tukey's test. The yellow data had very significant differences between the columns in the ANOVA (p<0.0001), and significant differences between the bright-yellow column and all other columns by the Tukey's test.

I then rearranged the data, putting the bright-colour data all in the same column (the 'cognate-proteome' column), and the pale-colour data in the other columns. This let me analyze all three colours together. The ANOVA found very significant differences between the columns (p<0.0001) and the Tukey's test found significant differences between the cognate-proteome column and all the other columns.

The control comparisons ( using reversed tripeptides) were never significant.

So now I can add a sentence to the manuscript, reporting that the effects shown in Figure 1 are statistically significant.

I should have paid more attention in stats class

One of the reviewers of the manuscript I'm revising for Genome Biology and Evolution asked if we could do some statistical analysis of the data we present in a graph. On the left I've put the graphs and the data . The lower graph panel and lower block of data are the controls; we can ignore them for now. I think we can also safely ignore what the data represent.

I'll describe the significance questions with respect to the top-panel graph (A):

We want to know the following:
In the left group (4 blocks of four bars, labels SAV, TAL, KEG, PHF/L), are the four blue bars significantly higher than the red, yellow and green bars beside them?
In the middle group (4 blocks of 4 bars, labels QAV, TAC, TSG, PLV), are the four red bars significantly higher than the blue, yellow and green bars beside them?
In the right group,(5 blocks of 4 bars, labels PSE, SDG, FRR, QTA, RLN/K), are the five yellow bars significantly higher than the blue, red and green bars beside them?

The actual numbers are in the upper part of the table, in the correspondingly coloured cells, and below I'll restate the above questions in terms of these numbers.

In the top four rows of the table (blue), are the numbers in the bright-blue cells significantly higher than the numbers in the light-blue cells in the same rows?
In the next four rows of the table (pink), are the numbers in the bright-pink cells significantly higher than the numbers in the light-pink cells in the same rows?
In the next four rows of the table (yellow), are the numbers in the bright-yellow cells significantly higher than the numbers in the light-yellow cells in the same rows?

I suspect this is an ANOVA (analysis of variance) type of problem. But I'm pretty sure it would require more complicated analysis than the simple ANOVA described the new statistics textbook my author-colleague kindly gave me (probably to get me off his back with dumb statistics questions). Hmmm, maybe it would be possible to do a separate ANOVA on each group -- i.e. one for the blue data, one for the red data, and one for the yellow data.


My basic version of EXCEL doesn't have the statistics add-in needed for ANOVAs, and I can't even remember the name of the statistics/graphing package the lab owns (it's not installed on my computer). But I found an on-line applet to do two-way ANOVAs here ( I need two-way because I have two variables, the rows and the columns). So I pasted the data from the blue cells into the applet, with the following results.

"Conclusion on Treatments Effects: Very strong evidence against the null hypothesis." The null hypothesis is that all treatments (columns) gave the same results, so there are very significant differences between the data in the different columns (p=0.00058).

"Conclusion on Blocks Effects: Moderate evidence against the null hypothesis." The null hypothesis is that all blocks (rows) gave the same results, so there are moderately significant differences between the data in the different rows (p=0.011).

This is definitely the kind of information I want, so I guess I should find the lab's statistical/graphing package and find someone to show me how to use it to do ANOVAs properly.

But this analysis doesn't let me see whether it's only the bright-blue column that's significantly different from the others. I guess I could repeat the analysis, leaving out the bright-blue data, and see if the others are not significantly different, but I'm sure there's a better way to do this. After I play around with our statistical/graphing package for a bit, I might be knowledgeable enough to go ask my colleague for help without embarrassing myself too badly.
The uptake-sequence manuscript we submitted to the new journal Genome Biology and Evolution has been provisionally accepted. One of the reviewers said the following, and I'm wondering if there might be an easy way to do this suggested analysis:
...despite claiming that one of their main goals was to determine whether uptake sequences had an effect on protein and organismal fitness, the authors did not look if these sites are under purifying/diversifying selection. It would be greatly relevant for their question of interest, which is currently only supported by indirect evidence.
The reviewer is absolutely right. We didn't think of doing this analysis, but we should have (though of it, not necessarily done it).

I don't think our dataset is appropriate for anything more sophisticated than simply calculating dN/dS ratios, and I'm not at all sure it's even suitable for that. I had to start by pulling out my complimentary copy of Freeman and Herron's undergraduate textbook Evolutionary Analysis, which explains how dN/dS ratios and McDonald Kreitman tests are used to examine DNA sequences for evidence of purifying or diversifying selection on the amino acids they encode. For a pair of aligned DNA sequences, dN/dS is the ratio of the number of differences that change the encoded amino acid to the number of differences that don't change the encoded amino acid. There are lots of programs and web sites that will do this analysis, given pairs of aligned seuqences in the appropriate format.

I think that my bioinformatician coauthor has DNA sequences of hundreds of H. influenzae and N. meningitidis genes, each aligned with each of three 'standard' homologs from genomes that don't have uptake sequences. These alignments have been sorted into classes, based on how many uptake sequences the H. influenzae or N. meningitidis gene has (0, 1, 2, 3, >3). I think the appropriate analysis would be to score the dN and dS ratio for each alignment, calculate the mean score of the three standard alignments of each H. influenzae or N. meningitidis gene, and then calculate the grand mean score for all the genes in each class.

This analysis isn't hard to describe, but it might be harder for my coauthor to automate, depending on the details of how the alignments are fomatted and what the dN/dS programs will accept. I'm going to email my former post-doc who has a lot of sophisticated knowledge about these methods, asking for her advice.

Should Darwin be an 'ism'?

On Tuesday evening I'm leading a Cafe Scientifique discussion on the topic Should Darwin be an 'ism'? I chose this topic as something that a broad range of people would be interested in and have ideas about, but I need to do some reading and thinking first.  Luckily the discussions take place in a local pub (The Railway Club, 579 Dunsmuir, 7:30pm, in case you're interested), and the atmosphere is very informal.
What will I read?  Carl Safina had a very relevant article in the New York Times last month (Darwinism must die so that evolution may live, Feb. 9), which I need to read carefully.  When it came out I didn't take the time to read it properly because I expected to agree with everything it said.  But I also need to read a bit more history of the use of the term Darwinism, maybe in Ernst Mayr's The Growth of Biological Thought
What do I think?  Maybe biologists started referring to evolutionary theory as Darwinism as a way to give credit to a truly exemplary scientist.  But now the creationists are turning this against us, claiming that we 'worship Darwin like a god', and that any evidence that Darwin made any error is evidence that evolutionary theory is wrong.  Using the term Darwinism also lets people put evolutionary biology in with a pile of what are now largely discredited ideologies and belief systems (Marxism, Raelism, Freudian psychology, etc.).
Unfortunately the cat is out of the bag.  Getting evolutionary biologists to forego using Darwinism will be easy, but re-educating the general public will be much harder.  The real problem is still that the creationists are much better publicists than we are, and they are determined to keep the public believing that evolutionary biology is synonymous with Darwinism.

Open access at the American Society for Microbiology annual general meeting

In May I'll be part of a panel discussion on open-access publishing, at the big General Meeting of the American Society for Microbiology.  The other participants are 'professional experts': Jon Eisen, Academic Editor in Chief, PLoS; Sam Kaplan, Chair of the ASM Publications Board (ASM publishes about a dozen journals and many books); and Joe Deken of the California Institute for Telecommunications and Information Technology.  I guess what I'll bring to the table is the perspective of the ordinary scientist trying to do what's right.


In addition to How to Write a Lot, I've been re-reading a little book on writing by Joseph Williams, Style, the Basics of Clarity and Grace.  This wonderful book is mainly about how to write sentences that are easy to read and understand, something all scientists strive for but few of us achieve.

One reason scientific sentences are often hard to follow is called 'nominalization'.  That's when an action is described by a noun rather than a verb.  For example, instead of writing 'the cell divided' we might write 'cell division occurred'.  I'm building my ability to avoid this by going through the manuscript I'm revising, rewriting sentences that suffer excessively from nominalization.  I don't have to search for these sentences, almost every sentence has one or more nominalized actions in it.

Here's an all-too-typical example:  "In E. coli, the dramatic reduction in growth and eventual cell death caused by sxy overexpression made it impossible to test whether sxy induction produces the typical ‘natural competence’ phenotype of high-efficiency transformation with linear chromosomal DNA."  It's a perfectly OK sentence, no grammar or syntax errors, but it's still a bit of an effort to read.  Can I improve it by replacing some of the nominalizations (reduction, overexpression, induction, transformation) with verbs?  

Yes I can.  "We could not test whether inducing sxy causes E. coli cells to become naturally competent and efficiently transform with chromosomal DNA, because when cells overexpress sxy their growth rate slows and they eventually die."

Small steps

Prompted by the How to Write a Lot book, I'm trying to spend half an hour on a scholarly-writing task before I get up, each morning that I don't have to be somewhere early (i.e. not at the gym by 8:00am).  As a result of this, I've nearly finished the first draft of my short essay for the ASM evolution book.  Only about 3 paragraphs still to go, and I know what they're going to say!

Yesterday I started reading the revised manuscript about Sxy in E. coli.  It still needs a fair bit of rewriting work, but maybe the post-doc and I will have enough time for sitting-down-together-and-revising that we can still get it out by the end of the week.

Manuscript work

The end of term is approaching so I can see the light at the end of the teaching tunnel (mixed metaphor?).  Here's a list of the manuscript-related tasks on my plate:

Informal chapter for the feitschrift for John Roth:  The first draft is in the hands of the editors, who I hope will soon give me feedback on how to improve it.  The post-doc and undergrad also have it - I haven't had any feedback from them either.

Short essay for the ASM popular science book on Darwin and microbial evolution:  I'm working on this.  I need 2000 words and have about 1500.  It's turning into a nice discussion of how we can study natural selection in bacteria.  I should soon have a list of all the other authors and their topics, which will help me integrate mine.  I just reread the email invitation, and now realize that I'm supposed to include personal stuff about me as a scientist - maybe I will, maybe it won't fit.

Manuscript about regulation by E. coli Sxy:  This was gently rejected by J. Bacteriology (with the possibility of resubmission).  The post-doc first-author has now rewritten it for resubmission, with input from the former post-doc other-author, and she's now passed it on to me.  If it's OK we'll submit it this week. 

Manuscript on co-evolution of uptake sequences and proteomes:  This has been provisionally accepted by Genome Biology and Evolution.  I asked the bioinformatician coauthor for feedback -she sent me a short email with some questions I haven't responded to.  So the first step is to respond to her questions (well, after I re-read the reviewers' comments).  I'm hoping we won't need to do any substantial new work.

Manuscript on student writing and learning:  This has been languishing since my teaching-fellow post-docs left town.  It's nearly finished so I should get it done.

Manuscript on the perl model of uptake sequence evolution:  As I recall, this needs a bit more computer-simulation work and quite a bit more writing.  The post-doc senior author has moved to Toronto, but we should still be able to get this done.

Manuscript on the phylogeny of H. influenzae strains and competence:  This is the work of this same post-doc.  The manuscript was provisionally accepted, but with requests for substantial additional work.  Based on her past performance I'm confident that she will get this done, but I should touch bases with her about it.

Can that be all?  

progress (?) on the ligase puzzle

The NHEJ expert said that he thought the periplasmic assignment of the H. influenzae ATP DNA ligase must be an error.  I was discussion the ligases with a colleague who works on Campylobacter (which also has one of these ligases) and she suggested I try running the sequences through the program PSORT-b, which is particularly good with bacterial proteins.  

PSRT-b could not assign a high-probability location to most of the ligases I tried, suggesting that the HMM method used by TIGR's database may be overconfident.  I was also surprised to find that its BLAST search pulled up some NAD-dependent ligases as matches to the ATP-dependent ligase sequences I tried.  I had been thinking that the two families had very dissimilar sequences, but maybe I'm wrong in that. 

The possibility that these ATP-dependent ligases act in the cytoplasm is interesting, as the competence-induction of the H. influenzae one may mean that it contributes to the postulated replication-arrest problem rather than to DNA uptake.

That periplasmic ligase

Yesterday I talked to Tom Silhavy about the periplasmic ATP-dependent DNA ligase that's co-induced with H. influenzae DNA-uptake genes (see old blog post here). He hadn't heard of this and was adamant that there is no ATP in the periplasm. So I did some more poking around.

I found papers about bacterial ATP-dependent ligases that function in 'non-homologous end joining' (NHEJ) reactions - these serve as last-resort repair mechanisms for double-strand DNA breaks that can't find a homologous template to use for repair. I emailed the author of a review, asking if the H. influenzae ligase belonged in this category. (He turned out to also be the person who had done the biochemical characterization of the H. influenzae ligase!)

He said that H. influenzae doesn't have the other NHEJ genes Ku and LigD, so it probably can't do NHEJ. I suspect the H. influenzae protein is in a different category of ligase, because a BLAST search with the H. influenzae ligase doesn't find known NHEJ ligases.

He also asked why I think it's targeted to the periplasm. At first I thought he meant, what do I think is the reason it's target to the periplasm, so I explained that I don't know. But then I realized he might be asking what is the reason I think it's targeted to the periplasm. I couldn't remember so I looked at it and its homologs using TIGR's HMM (hidden Markov model) location analysis function - this says that the H. influenzae protein and the four homologs I checked (Neisseria, Campylobacter, Shewanella and Thiomicrosomethingorother) all have a high probability of being periplasmic, with a single strong transmembrane domain close to the N-terminus. Tim VanWagoner, who also worked on the H. influenzae gene, also wrote that its Vibrio homolog is predicted to be periplasmic. Tom Silhavy had wondered if the apparent signal sequence might be an annotation error (wrong start site?), but this is very unlikely to be the case for all the homologs, so the odds are very high that these really are periplasmic.

I mentioned to Tom my idea that the ligase might be exported to the periplasm with an ATP already bound (the purified protein has its ATP covalently bound, ready for action). He said that, if that were the case, the protein would have to be exported by the Tat (twin argine translocation)system, because that's the only export system that can handle folded proteins. Luckily there's now a TatFind server, so I pasted in the various protein sequences, all of which had no recognizable TAT site in their first 35 aas.

How peculiar... We must be overlooking something important...

outer membrane issues

Later this morning I'll be meeting with Tom Silhavy, who's visiting to give the Microbiology seminar today.  He's an expert on outer membrane biogenesis, so what might I ask him about?

In the context of the development of competence, there's the timing issue.  How long should it take H. influenzae to assemble its DNA-uptake machinery once the genes have been turned on? We traditionally allow 100 minutes from transfer to starvation medium.  The microarray analysis showed that under these conditions gene expression is higher at 30 minutes than at 10 minutes.  Addition of cAMP to non-starved cells induced competence with a peak at 45 minutes.  How much of this time is needed for assembling DNA uptake complexes in the membranes?  What other factors might contribute to a lag?  Should E. coli be faster?

Another issue Tom's interested in is energy sources for periplasmic and outer membrane processes.  He might have some insight into the periplasmic ATP-dependent ligase that's co-induced with H. influenzae competence genes.  Where might it get its energy and what might it be contributing to uptake.

He might also have ideas about the "getting stiff DNA across the outer membrane without a free end" problem.  How flexible is the outer membrane to being pushed around?  And what about the cell wall - is it an obstacle we should worry about?

Should Darwin be an 'ism'?

In a few weeks I'm leading a Cafe Scientifique discussion on the topic "Should Darwin be an 'ism'?" I promised to provide a short abstract, so here goes:

Darwin's place in modern biology is unusually personal. When The Origin of Species was first published, biologists readily accepted the publicly controversial idea that all modern life evolved from simpler organisms. But they were dubious of natural selection's role in adaptation, and 'Darwinism' competed with 'Lamarckism' and then ''Mendelism' until the genetic basis of inheritance became clear in the 1930s. Since then many biologists have invoked Darwin whenever they spoke of natural selection, perhaps to make up for our original skepticism. But creationists are now turning this against us, claiming that evolution is nothing but Darwin-worship. Is it time to push Darwin into the closet?

ECOR strains

Yesterday I was filling in the form to apply for a permit to import pathogenic bacteria, so we could get the 'ECOR' set of E. coli strains. This is a set of 72 different E. coli strains from many different human and animal sources, chosen by Howard Ochman and Bob Selander to represent the diversity of this species.

Since Ochman and Selander's original analysis (1984) they've been examined for many different genotypes and phenotypes. The group that maintains the strains has a long list of papers describing work on them, but it only goes to 2001. So just now I did a Google Scholar search for 'ECOR collection' and one of the top hits was a paper by a UBC colleague, Julian Davies, describing these strains' repertoire of antibiotic resistance genes carried on integrons.

So I just emailed Julian. If he already has these strains, we won't have to bother importing them!

Experiments with stalled replication forks?

We think (I think) bacteria turn on their 'competence' genes because they are running out of deoxynucleotides for DNA synthesis. Part of this adaptive response is taking up DNA (an excellent dietary source of deoxynucleotides) and part of it is other changes that help cells cope with problems that arise when DNA replication is interrupted.

If I'm right, then cells with their competence genes already on might be better able to survive interruption of DNA replication. How can we test this? Are there antibiotics that block DNA replication, that can be used to create a transient block and then washed out? What about temperature-sensitive (ts) mutations in DNA replication genes? This might best be done in E. coli, not H. influenzae, because ts mutations don't work well in the latter ( it's intrinsically sensitive to minor shifts in temperature). E. coli also has a fine collection of already characterized ts mutations, and we now are able to artificially induce its CRP-S (competence) regulon by putting E. coli sxy on an inducible plasmid.

Manuscript progress

I've known for several weeks that one of the manuscripts we submitted before Christmas has been accepted, and this morning I got a 'provisional acceptance' email about another.  This latter manuscript is the one about the impact of uptake sequences on the evolution of bacterial proteomes.  The work was started more than 10 years ago, so it will be great to get this finally off my plate.

The reviewers were generally positive but they did suggest quite a few new analyses.  I'll have to consult with my bioinformatics co-author to decide which of these we might reasonably undertake.  There'll be some rewriting too of course - parts that seemed very clear to me were not so clear to the reviewers.

p.s.  Thanks to commenter (commentor?) Phagenista (great name) for the information about where to get the ECOR collection.  I've emailed them to ask about shipping to Canada - I think our strain import permit may still be valid.

DH5alpha is mutant in recA

The post-doc sent me a list she's compiled of the experiments we're planning and the genotypes of the E. coli strains we'll use.  So far I've just glanced at them, but I noticed that one of the strains used for recombination is recA.  This means that the protein responsible for almost all homologous recombination is missing, so recombination shouldn't happen!  We'll have to get this sorted out asap.

A new leaf?

I've been reading a little book called "How to write a lot" and I'm now abashed at how little I've been writing in this blog.  Nothing since December!  (Actually I have been writing in it lately, just not taking the final step of posting, because I find the blog format helps me to work on a book chapter that needs a conversational writing style.)  I'm going to get back to posting something every day, no matter how minor it has to be.

Yesterday the post-doc (I'm temporarily down to one, but a new one arrives next month!) presented some exciting data (I won't describe it until it's a bit more solid) that can be expanded by work with some old E. coli strains.  So I promised to draw up a detailed outline, spelling out the strains and their genotypes and how we'd use them.  

And we need to order the 'ECOR' collection of E. coli strains, and maybe some other strains that were recommended by a commenter on this blog a couple of years ago.  The ECOR collection is a set of a couple of dozen strains from very diverse human and animal sources - I don't yet know who we'd get them from.