“Don’t believe anything you read in textbooks.”
“Chickens come and go, but chemistry kits are forever.”
–Mark Davis, Keynote speaker at the Autumn Immunology Conference, Chicago, 11-21-08
(Trust me, context wouldn’t help much.)
Here’s another extraordinary movie, taken from:
A. A. Cohen, N. Geva-Zatorsky, E. Eden, M. Frenkel-Morgenstern, I. Issaeva, A. Sigal, R. Milo, C. Cohen-Saidon, Y. Liron, Z. Kam, L. Cohen, T. Danon, N. Perzov, U. Alon (2008). Dynamic Proteomics of Individual Cancer Cells in Response to a Drug Science DOI: 10.1126/science.1160165
This shows cancer cells responding to a drug used in chemotherapy (camptothecin). The drug kills many, though not all, of the cells; the paper is aimed at finding correlates between various cellular proteins, and the cells’ ability to survive. But the move here can be interpreted more simply. We see the cancer cells, untreated for 24 hours, rapidly dividing and squirming around. (There are lots of clear examples of cells dividing; for example, a little bit toward 7:00 from center, at 5 hours; and just below center, at 19 hours.). At 24 hours, the drug is added; within another 12 hours, the cells slow down, and around 48 hours we see them starting to die (dead and dying cells are helpfully boxed).
In other news, I’ll be at the Autumn Immunology Conference in Chicago this weekend. Should be good.
A couple of years ago I published a paper characterizing a mutant cell line. 1 I had been working, on and off, on the cells for around ten years, and they were already present in the lab when I joined it. To write the paper I needed to know the details of their generation. I clambered the ladder to the box marked “1992 LAB BOOKS”, pulled out Ethan’s notes for the year, flipped through them for a few minutes, and copied down the procedure — concentration of EMS, duration of treatment, and so on.
Since 1992 I’ve used electronic data stored on 5¼-inch floppies, 3½-inch floppies (single and double-sided), Bernoulli drives, zip drives, Jazz drives, CDs, DVDs, and USB flash sticks; as well as on computer hard drives from at least four different OSes, and in God knows how many formats.
The data on at least five of those media are now almost entirely inaccessible to me (if we were desperate, I’m fairly sure we could retrieve them, but it would be a huge chore). Probably more than half of the different formats are almost unreadable today.
Meanwhile, the data in those old-fashioned paper notebook are just as usable today as they were in 1992; and they will be equally usable in another sixteen years.
I’m seeing a lot of discussion online about electronic lab notebooks, but this is an aspect that I don’t think has been emphasized nearly enough. I know when you plan an experiment, you expect to publish it (in Nature) next week; but that’s not what always happens, is it. And even if you do publish in a timely manner, who know what’s going to happen in fifteen years? (I just thawed out some cells, frozen by a colleague in 1985, to analyze their antigen presentation pathways; something he had no interest in at the time. He still has his lab notebooks describing his characterization, though, including stuff he didn’t publish at the time.)
|A crude searchable experiments interface|
How many of the protocols out there today are going to be functional in 15 years? How many web sites from 1992 are still readable today? (Since HTML wasn’t specified until 1993, the answer is “Not many”.) History suggests that those electronic notebooks of today will be the impenetrable floppy disks of tomorrow. 2
Electronic notebooks do have one gigantic advantage over paper: Search. I do use electronic notebooks of one kind or another, and the main reason is so I can search for the half-remembered experiment that used brefeldin A, and find out what concentration. For years I’ve just used a cobbled-together thing I wrote myself, a HTML interface to an SQLite database linked with a Python cgi script (e.g. the screenshot to the right; click for a larger version). It works nicely for searching, but it’s not as future-proof as I’d like (it depends on Python, which is being updated to a partially incompatible version soon; SQLite, which is likely to be stable for a few years, but I’m not counting on fifteen; and html, which is evolving as well.) As well, it’s a little irritating to not have real data in there; so in the past year or so I’ve started using a wiki to keep lab notes in as well.
I’ve actually made multiple false starts at the wiki/notebook thing, and there’s no guarantee that this latest version will stick, but it’s looking more promising than previous runs. I’m using DokuWiki, which uses flat text (marked up) files for each page. I trust txt to be readable in 10 or 15 years, so even if (when) the rest of the interface is incompatible there should be usable information there. It’s also easy to back up, and the wiki in general seems friskier and more responsive than some of the other wikis I’ve looked at. I’m reasonably sure this will work.
But I’m still backing up to a paper lab notebook, because I know that works.
“The issue of data integrity should not be left to chance and probability. This is scholarly publishing, not blackjack.”
–M. Rossner (2008). A false sense of security. The Journal of Cell Biology, 183 (4), 573-574 DOI: 10.1083/jcb.200810172
|“Death and the Doctor”
Published by William Humphrey, 1777
Last April I commented on a series of experiments that used intravital microscopy to visualize cytotoxic T lymphocytes (CTL) attacking a tumor. 1 Immensely cool though the movie is, I noted that I was surprised by their estimate of the rate of cell killing:
Another surprising finding — which is so different from previous work in different systems that I’m hesitant to believe it — is the timing of cell killing. Previous studies (such as the von Andrian paper2 that produced this video) have suggested that CTL kill their targets in something under an hour; maybe 30 minutes or even less. Here. Bousso’s group find that the tumor cells take something like 6 hours to be killed. That’s such a large difference — and has such important implications for effectiveness of CTL killing — that, as I say, I’d like to see it confirmed before I take it to the bank.3
A new paper4 has run another estimate of the time it takes for a CTL to kill its target, and like most of the previous work, they conclude that it takes about a half-hour, give or take, to kill a target. They do come up with a fairly wide range of killing times, that depend on the target and the timing of the immune response — at the peak of the immune response when there are many cells the targets are killed faster (between 2 and 14 minutes), while at later stages, when there aren’t so many CTL, targets have half-lives of 48 min and 2.8 hr.
|CTL killing a target cell
(From a video by von Andrian)
This is not quite looking at the same thing as the video showed, though. In this paper, they were looking at the bulk effects, and that’s what almost all the previous studies have also looked at. The video was looking at a one-on-one interaction. What if targets are killed faster when several CTL gang up on them? Here, having different numbers of CTL caused the half-life of the targets to increase between about 10 and 20-fold. But this is probably simply because, with fewer CTL present, it took longer for them to find the target: Once a CTL found the target, the rate of killing was if anything faster than effectors at killing (“we find that LCMV-specific memory CD8 T cells kill more target cells per day than effectors”). 5
This is actually a disagreement with a previous paper 6 that also looked at killing rates, and offered evidence that different types of CTL can have different killing rates:
We reanalyse data previously used to estimate killing rates of CTL specific for two epitopes of lymphocytic choriomeningitis virus (LCMV) in mice and show that, contrary to previous estimates the “killing rate” of effector CTL is approximately twice that of memory CTL. 6
However, whichever of those studies is correct , both suggest that different types of CTL can have different killing efficiencies. This goes back to a point I’ve made several times, as have others (see e.g. Michael Palm’s TAG post here and references therein, including the comments by me and by Otto Yang) — CTL aren’t a uniform batch, and different kinds of CTL may have different types as well as rates of activities.
Returning to the intravital microscopy killing rate of 6 hours:7 I wonder if that reflects the nature of the CTL there, perhaps influenced by the tumor environment. Tumors are notoriously resistant to killing (probably because those tumors that are not resistant to killing were, um, killed, before they ever become clinically detectable) and it seems quite likely that an immunosuppressive tumor environment may change CTL types, or activities. I wonder if that would offer some way of intervention. Speeding up the rate of CTL killing from 6 hours to 30 minutes seems like it would be a huge influence of clearance of tumors. On the other hand, of course, it may be that the targets themselves are much more resistant to killing (again because tumor cells have been through selection to be resistant to the immune system) and cranking up CTL won’t make much difference.
- Breart, B., Lemaître, F., Celli, S., Bousso, P. (2008). Two-photon imaging of intratumoral CD8+ T cell cytotoxic activity during adoptive T cell therapy in mice. Journal of Clinical Investigation, 118(4), 1390-1397. DOI: 10.1172/JCI34388 [↩]
- Mempel, T. R., Pittet, M. J., Khazaie, K., Weninger, W., Weissleder, R., von Boehmer, H., and von Andrian, U. H. (2006). Regulatory T cells reversibly suppress cytotoxic T cell function independent of effector differentiation. Immunity 25, 129-141.[↩]
- From this post[↩]
- V. V. Ganusov, R. J. De Boer (2008). Estimating In Vivo Death Rates of Targets due to CD8 T-Cell-Mediated Killing Journal of Virology, 82 (23), 11749-11757 DOI: 10.1128/JVI.01128-08[↩]
- There are also other videos of one-to-one killing, at least in vitro, that are more consistent with the 30-minute ballpark; see the image to the right for one example.[↩]
- Yates A, Graw F, Barber DL, Ahmed R, Regoes RR, et al. (2007) Revisiting Estimates of CTL Killing Rates In Vivo. PLoS ONE 2(12): e1301. doi:10.1371/journal.pone.0001301[↩][↩]
- Which I have become more relaxed about since my earlier skeptical comment[↩]
I got a letter from the government
The other day
I opened and read it
It said I was a sucker
They didn’t want me for their R01 or whatever
Picture me giving a damn – I said never
Here is a land that never gave a damn
About a geek like me and myself
|HIV budding from a macrophage|
The STEP anti-HIV vaccine trial received a lot of press coverage last year, when the vaccine was pulled for fear that it actually worsened HIV disease. A number of mechanisms were proposed for the exacerbation. One of those has now received some support.1
The STEP study used adenovirus vectors, expressing HIV proteins, to induce immunity to HIV. Adenoviruses are ubiquitous viruses in most human populations, usually causing fairly mild upper respiratory tract infections (i.e. cold-like symptoms), and most people have been repeatedly exposed to adenoviruses. As part of the adenovirus/HIV vaccine, people developed immunity to the HIV proteins, and also increased their immunity to the adenovirus component. Unfortunately, the preliminary analysis suggested that those vaccinees with high anti-adenovirus immune responses, were actually more susceptible to HIV, not more resistant. Obviously, that was a bad thing.
One suggestion at the time was that having immunity against adenoviruses might lead to increased activation of the immune system. There was already evidence at the time that activated T cells are more susceptible to HIV infection in several ways, and that evidence has been boosted by several studies since. For example, just the other day there was a paper showing that
… circulating microbial products can increase viral replication by inducing immune activation and increasing the number of viral target cells, thus demonstrating that immune activation and T cell proliferation are key factors in AIDS pathogenesis.2
In fact, in monkey species (e.g. sooty mangabeys) that don’t develop disease after SIV infection, you don’t see a lot of immune activation; whereas those species that do develop disease, show significant immune activation:
SIV-infected SMs3 do not manifest the chronic generalized immune activation that characterizes pathogenic SIV and HIV infections, a process that is thought to play a central role in driving CD4+ T cell depletion through bystander activation and loss of uninfected T cells. 4
|HIV infecting a macrophage5|
So there was theoretical support for the concept that immunity to adenoviruses could lead to immune activation, which in turn could lead to increased HIV replication, causing increased susceptibility to HIV. The paper I mentioned that provides more direct support 1 also spells out a mechanism in a little more detail, looking at antibodies against adenovirus and their effect on activation; as well as noting that at least one other potential problem might be that the anti-adenovirus response could indirectly cause a reduced anti-HIV response (by killing dendritic cells).
This study (and others) actually point to a couple of useful directions. For one thing, although in this case it seems that immune activation was bad, in most cases it’s just the opposite.6 The anti-HIV vaccine is actually a very special case where we might not want an activated immune response, and even there it’s not strictly activation we want to avoid, just off-target activation. (A strong, activated immune response against HIV is probably a good thing,4 because it can shut down the virus.) This adenovirus trick may be a fairly straightforward way of getting immune activation, if it can be harnessed.
Another point is that in this special case, where immune activation may be harmful, maybe blocking activation would be beneficial. It’s a little counterintuitive to try to suppress the immune response when you’re infected with a virus, but it’s probably worth looking at:
These data suggest that therapeutic strategies to reduce immune activation should be explored, in addition to the classic antiretroviral therapies, in preventing progression to AIDS in chronically HIV-infected individuals.2
Added note: The Michael Palm Treatment Action Group blog has commentary on the STEP vaccine trial conclusions published in The Lancet, as well as a previous series of commentaries on the vaccine trial. Highly recommended.
- M. Perreau, G. Pantaleo, E. J. Kremer (2008). Activation of a dendritic cell-T cell axis by Ad5 immune complexes creates an improved environment for replication of HIV in T cells Journal of Experimental Medicine DOI: 10.1084/jem.20081786[↩][↩]
- The Journal of Immunology, 2008, 181: 6687-6691.[↩][↩]
- SMs: Sooty Mangabeys[↩]
- J Immunol. 2008 May 15;180(10):6798-807[↩][↩]
- Gross, L., 2006. Reconfirming the Traditional Model of HIV Particle Assembly. PLoS Biology, 4(12), p.e445 EP [↩]
Ever wondered what it looks like in your finger, say, when you get a splinter and your immune system leaps into action? Of course you have.
This amazing movie (double-click to play, I think) shows neutrophils (in green) responding to the presence of either a parasite (Leishmania major; in red) or to simple artificial beads (in blue), injected into the ear of a mouse. Neutrophils react to both foreign materials by galloping to the site and swarming the target. Neutrophils are a part of the rapid-response innate immune system, and this movie shows the first five hours of the response.
|4-dimensional image series from the ear pinna of a LYS-eGFP mouse in which blue fluorescent beads and L. major had been deposited adjacent to one another in the skin of the same ear. eGFP-expressing cells are shown in green, L. major-RFP is shown in red, and beads are shown in blue. Playback speed is 1200x. Scale bar, 200?m|
N. C. Peters, J. G. Egen, N. Secundino, A. Debrabant, N. Kimblin, S. Kamhawi, P. Lawyer, M. P. Fay, R. N. Germain, D. Sacks (2008). In Vivo Imaging Reveals an Essential Role for Neutrophils in Leishmaniasis Transmitted by Sand Flies Science, 321 (5891), 970-974 DOI: 10.1126/science.1159194
|Dicing with Death
By Abraham a Sancta Clara and Christoph Weigel, 1764
Why aren’t our bodies choked with T cells?
Whenever we’re infected with a microbe (which is often, even if we aren’t aware of it) our immune system reacts. As part of the reaction, T cells become activated, and as part of the activation, the T cells replicate, at an incredible rate. We may start off with a few hundred T cells that react with any particular microbe, but within a week each of those will expand between a thousand and a hundred thousand fold, so for each microbe that is carried in on a splinter, or that we breath in, we will develop millions of T cells. After ten or twenty years of this, we should be nothing but a gigantic, rolling ball of T cells.
We’re not a ball of T cells because the T cells die off. After a week, or thereabouts, most of those millions of T cells die: About 95% of them. The remaining 5% or so stick around, as memory cells, but almost all of them are cleared away to make room for the next immune response.
How does that die-off work? How do cells decide if they’re going to die, or survive and become a memory cell? How do they know that the response has been going on long enough? Bits and pieces are already known. For example, there are spontaneously-mutant mice (“lpr” and “gld” mice) that don’t look after the die-off properly (because one of the pathways that’s involved in delivering a “death” signal to the T cells is defective in these mice; they lack Fas and FasL, respectively). The figure on the right is what happens to them. The right-most panel shows a spleen and some lymph nodes from a normal mouse; the left panel shows the same, from an lpr mouse. 1 The grotesquely oversized lymph nodes are crammed with T cells: Normal T cells, in that they’re not cancerous, but there are far too many of them, and these mice die young.
But in spite of these little snippets of information, “The contraction phase that connects the initial expansion phase with the memory phase has been a black box from which surviving effectors emerge as bona fide long-lived memory cells”.2
Michael Bevan has just published some more data on the T cell contraction phase (at least for one T cell subset, the CD8 T cells).2 He manages to rule out a couple of the major hypotheses as to how contraction works, and his conclusion is that the contraction is part of the overall response program — it’s all predetermined during the brief period, at the beginning of the immune response, where the T cells are activated and set forth onto their journey. They become activated, expand, control infection, and then contract, all based on a hardwired program that kicked on days earlier.
That doesn’t explain, though, why some cells don’t die off and end up becoming memory cells. Bevan basically shrugs; there doesn’t seem to be anything different about the survivors, and he suggests that it’s just chance; that cell division isn’t completely symmetrical, and that some cells end up more equal than others:
Cell death could be the default pathway during contraction and a combination of epigenetic modifications and transcriptional changes could allow a subset of cells to survive and progress to the memory stage.
That’s a little unsatisfying, though “unsatisfying” doesn’t mean “wrong” by any means. It would be a little easier to understand if there were some special signals or some special predetermination that established the proper numbers for memory, and so on, but maybe assymetric division is all there is.