Capsule: BioHack

Status: Complete, most challenges met.

Put this on your (nonexistent) box: Play Biochemistry 101!

Most intriguing idea: Modeling a puzzle game after natural regulatory systems.

Best design decision: Keeping things simple in these complex systems.

Worst design decision: The visually confusing quantitative and rainbow modes.


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Dynamics conservation in the Ras superfamily

The proposition that general fold architecture is preserved within a family of evolutionarily-related proteins is not controversial. The amino acid sequence of a protein determines its structure, and countless studies have substantiated the idea that proteins with similar sequences will adopt similar folded conformations. Because structure and dynamics are intrinsically linked, one could reasonably assume that many features of a protein's dynamics get conserved along with the fold. A growing number of experiments show that this is indeed the case, including a recent paper in Structure (1).

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Even more lab courtesy haiku

Alert your labmates
if your prep will require all
the lab's baffled flasks.

Refill or reorder
reagents before you empty
the goddamn bottle.

Touching toxins, gloves
go on. Touching telephones,
take those nasty things off.


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A single residue dictates a fold

Anfinsen's dogma — that the amino acid sequence of a protein uniquely determines its structure — naturally leads one to the idea that identity between amino acid sequences means identity between structures. This has proven to be a successful paradigm: sequence similarity reliably predicts structural and functional similarity. Evidence accruing in recent years, however, suggests that for small proteins, at least, this assumption may not be entirely safe. Adding to this view, in an article in PNAS this week (it's open access, so open it up), a research team led by Philip Bryan reports that they are able to generate significantly different folds with divergent functions from sequences that differ by a single amino acid.

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Alternate structures and catalysis in cyclophilin

Of all the sources of structural variability in proteins, the hardest to pin down is side-chain conformational heterogeneity. Side chains aren't always easy to model into their primary conformation in the first place — you need excellent crystal diffraction or NMR data to do it. Even if you pulled that off, it's not always clear how (or if) side-chain fluctuations relate to a protein's activity. If we carefully examine our data for the faintest signals, however, we can sometimes find evidence of secondary conformations that play an important role in function. In an article in this week's Nature, James Fraser, myself, and others show that in the case of the proline isomerase cyclophilin A (CypA), alternative conformations of side chains play a key role in catalysis.

Previous experiments on CypA had established that the backbone amide groups of many residues were sensitive to a conformational fluctuation on the millisecond timescale. Under conditions where this enzyme is saturated with a peptide substrate, the fluctuation rate for some of these residues is very similar to the catalytic rate, suggesting that the dynamics and catalysis are linked in some way (2). Later experiments also showed that this fluctuation was an intrinsic property of the enzyme, continuing even in the absence of substrate (3). What we didn't know, however, was how the dynamics of cyclophilin were related to catalysis. We couldn't know, because we had no idea what the motion we were detecting was.

In the case of enzymes like adenylate kinase, there is a dramatic rearrangement of structural elements, and the population of conformations corresponding to the "end points" of that motion can be significantly enriched by altering the amount of substrate present in solution. In the case of CypA, neither of these things seems to be true. Supplementary Fig. 1a (freely accessible from the article page) neatly encapsulates the problem. For this figure, 48 structures of CypA, some with ligand and some without, were aligned, and the variation between them was determined. While there is some variability in the chain conformation, it is primarily limited to a group of residues known to undergo fluctuations that are not related with catalysis (blue chain). The residues involved in the catalysis-related dynamics don't seem to have much variability, even across this fairly large group. So we can't trap the unknown, minor state of CypA by adding substrate, and there's no evidence of an alternate state that explains the NMR data.

Knowing this, we suspected that some kind of side-chain motion accounted for the observed dynamics, probably involving an aromatic group of some kind. Our efforts to gather evidence for this, however, ran into some typical NMR problems — resonance overlap and poor sensitivity exacerbated by chemical exchange. Fortunately, the crystallographers came to our rescue, in the form of Tom Alber and his super-talented grad student Jaime Fraser. Jaime had determined a crystal structure of CypA at cryogenic temperature and analyzed the data using their algorithm RINGER, which examines electron density below the threshold typically considered "noise" in order to identify possible alternative rotameric states of side chains. He found evidence of multiple conformations for a few residues, but nothing that would explain the NMR results. Jaime had the bright idea to redo the experiment at room temperature, which Tom was convinced would result in nothing more than a radiation-damaged crystal and bad diffraction data.

What actually happened was that when Jaime examined the electron density from that experiment he could identify a group of side chains that had more than one conformation in the crystal, which you can see in Fig. 1. These residues included serine 99, methionine 61, and the catalytic arginine 55. Right in the middle of this group was phenylalanine 113, a residue with an aromatic side chain capable of causing changes in chemical shift at relatively long range. For context, the image to the left shows a structure of cyclophilin (PDB code: 1RMH) in complex with the model substrate we used in our own experiments (succinyl-Ala-Ala-Pro-Phe-p-nitroaniline), with the side chains of S99, F113, M61, and R55 in red. As you can see, F113 and M61 form part of the floor of the binding pocket, with S99 rather remote.

So here we have an alternative structure of CypA, hidden below the threshold typically considered when determining a crystal structure. It was certainly plausible that fluctuations in this ensemble of side chains could give rise to the NMR observations, but plausibility isn't proof. One way to address this would be to try and force CypA to adopt the less-populated conformation. If you look at Fig. 1d you can see that the two conformations of S99 lie at the standard rotameric positions, and that the less-populated rotamer of S99 would run into the more-populated rotamer of F113. So, if you replaced one of the side-chain hydrogens of S99 with a methyl group (i.e. mutated the serine to threonine), that might push the other residues of this group into their minor conformational state. So, that's what we did.

To the right you can see an overlay of structures for wild-type (WT) CypA (red) and S99T (green), aligned using structural elements on the opposite side of the protein from the active site. As you can see, the backbone traces match very closely, except for the helix and loop on the right. These elements are involved in crystal contacts in the S99T structure, but not the WT; a lower-resolution structure of S99T shows no differences here. Another key difference between these structures, of course, is the position of the side chains (thick neon); as shown here (and more clearly in Fig. 2c) they seem to have adopted the minor conformation from the WT structures. Although this mutation inspires widespread chemical shift changes (Fig. 3a) consistent with the hypothesis that this concerted side-chain rotation gives rise to the NMR observations, the structures seem very similar. Yet, S99T CypA differs from WT in two important ways.

The first difference is that the conformational fluctuations are dramatically slower, but only for residues that showed catalysis-related dynamics in WT (Fig 3d). In fact, this rate is now so slow that due to a quirk of NMR we can only determine the slowest rate of the process. At 10 °C, this fluctuation in S99T is about 60 times slower than the slowest process in WT.

The second key difference between the mutant and the WT is that catalysis is dramatically slowed. Because CypA does not consume its substrate (it acts on both cis- and trans- proline bonds) its activity can be assayed by NMR, as you can see in Fig. 4. As with any enzymatic assay, the net activity is proportional to the amount of enzyme added, so just glancing at these spectra (and knowing the enzyme concentration) you can estimate that S99T has at least 40-fold lower activity than WT enzyme. If you actually perform the fits, it turns out that the reaction velocity for S99T is about 240 times lower than that for normal CypA, but this includes a contribution due to the fact that S99T does not bind its substrate as tightly either. If you correct for this, it turns out that S99T has about 70-fold less activity than the normal enzyme. Not only is this similar to the change in dynamics, it's also quite comparable to another mutation, R55K, that removes a group that performs some of the chemistry.

These results indicate that a conformational change in a group of side chains including F113 is primarily responsible for the chemical exchange behavior observed in WT. The S99T mutation stabilizing the minor conformation dramatically and similarly reduces both the conformational fluctuation rate and the catalytic rate. This suggests that dynamics and catalysis are linked not by happenstance but by some direct relationship. Unfortunately, these experiments do not provide any direct insight into the mechanism by which dynamics contribute to catalysis. They do establish, however, that in CypA coherent fluctuations of side chains, barely detectable in protein crystals, nonetheless make a critical contribution to function.

1) Fraser, J.S., Clarkson, M.W., Degnan, S.C., Erion, R., Kern, D., & Alber, T. (2009). Hidden alternative structures of proline isomerase essential for catalysis Nature, 462 (7273), 669-673 DOI: 10.1038/nature08615

2) Eisenmesser, E.Z., Bosco, D.A., Akke, M., & Kern, D. (2002). Enzyme Dynamics During Catalysis Science, 295 (5559), 1520-1523 DOI: 10.1126/science.1066176

3) Eisenmesser, E., Millet, O., Labeikovsky, W., Korzhnev, D., Wolf-Watz, M., Bosco, D., Skalicky, J., Kay, L., & Kern, D. (2005). Intrinsic dynamics of an enzyme underlies catalysis Nature, 438 (7064), 117-121 DOI: 10.1038/nature04105

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Don't look for "the" structure

It surprises me how often I hear students, postdocs, and even professors talk about determining the structure of a protein. A singular structure has the advantage of being relatively easy to interpret, but the cost of this is often the loss of functional data. It's easy to understand how this terminology emerges from the discipline of crystallography, which after all only works when the protein molecules adopt only a small number of conformations. Yet even when it comes to NMR, a technique that should be very sensitive to the fact of structural multiplicity, the language of researchers and the structural tools available to them are too often oriented towards the idea of a singular structure. But any representation of a protein as a single conformation is a simplification — every protein exists in multiple structural states.

Trivially, we are aware that a given polypeptide chain can adopt a number of different conformations — the "folded state" of any given polypeptide chain covers only a tiny sliver of the possible conformational space. A protein that is "unfolded" occupies not a single, well-defined state but a vast multiplicity of states, and this kind of statement is not controversial because we tend to imagine unfoldedness as a messy chaotic jumble of conformations. The reality is less cut-and-dried: although unfolded proteins may have no regular structure, many still have a propensity to form particular secondary structures or interactions. The reality of denatured proteins is that they have a complex and varied energy landscape, not an array of possible structures that all have roughly equivalent energy. The flipside of the popular view is that the a protein's native state draws down to a sharp energy well, and this conception is also misguided.

The most dramatic counterexamples to the idea of a neat, punctate energy well come from proteins that adopt several different folds in the native state. One relevant case is lymphotactin, which freely interconverts between an α/β monomer and an all-β dimer under physiological conditions. Lymphotactin may be unusual, but the principal message from that study is one that ought be paid attention to in others, particularly when the protein in question has functional conformational diversity. Consider α-synuclein, a protein implicated in Parkinson's disease. In the presence of some detergent micelles this protein is known to take on an α-helical hairpin structure, with two helices laying down on the charged surface of the lipid headgroup. In solution, however, it seems to take on a number of different forms, and may interact with true lipid bilayers in a completely different way than it interacts with micelles. For proteins that interconvert between several different physiologically-relevant folds, one is never pursuing the structure, but rather a structure.

Of course, we don't expect most proteins or domains to regularly adopt alternate overall folds. However, reorientations of domains or monomers is a relatively common behavior, and one that poses a sticky challenge for structural biologists because incidental properties of a particular arrangement may bias our experiments towards observing it. A minor member of the ensemble, if it has favorable packing geometry, may exclusively populate a crystal. Similarly, NMR experiments to determine domain arrangement via residual dipolar couplings must always be undertaken with an eye to ensuring that interactions with the aligning media do not bias the results. No single structure of adenylate kinase can instruct us about its catalytic cycle, and structures of the unbound state do not capture the reality that the protein continues to open and close in the absence of ligand. Single structures do not capture motions of domains or monomers relative to each other and that often means an incomplete understanding of function.

Domain motions are also an overly dramatic example, because simpler rearrangements of the backbone take place in many proteins, even when regular secondary structures are evident. Fluctuations of the main chain play a functional role in several proteins — as, for instance, in the flaps of the HIV protease. Additionally, rearrangements of the backbone have a significant role in signaling, as in NtrC, which I'll talk about more in two weeks. Proteins where the main chain rearranges in response to ligand binding or post-translational modification generally cannot be described by a single structure.

Even if the backbone is rigid, every protein will have flexibility in the side chains of its amino acids. One of course expects to see this kind of behavior in side chains on the surface of a protein, where it is usually dismissed as irrelevant. However, we also know that side chains can rotate and move in the core of a protein, and that on some protein surfaces they can undergo coherent rearrangements. I'll talk a bit more about the functional relevance of side-chain motions next Thursday. For now, suffice to say that side chain rotations cannot be so easily ignored and sometimes have functional effects. Structural studies that do not capture these rotations may be missing something important.

My point here is not that single structures are stupid or useless. A structure can be very informative about about a protein's function, and often has great power to explain the effects of mutations and ligands. However, we should not mislead ourselves into thinking that any single structure will have all the answers, or indeed any of them. Every protein is a constantly interconverting ensemble of structures, and there are many layers of structural diversity within that ensemble, reaching from whole fold rearrangements to "mere" side-chain adjustments. Determining the structure of a protein is not a coherent goal for a research program. The successful structural biology study will characterize the conformation and energy of key, functionally-relevant members of the protein's structural ensemble and identify the pathways between them.

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Let's explore the spectral density!

The model-free formalism of Lipari and Szabo is a way to convert experimental NMR data into a limited number of generalized parameters describing the internal dynamics of a protein. However, the relaxation rates that are typically measured by NMR — the R₁, the R₂, and the steady-state nuclear Overhauser effect (nOe) — do not themselves appear in the model-free formulas. Instead we see a term, J(ω), and this constitutes the interface between the data and the model. This term refers to the spectral density, which is a measure of the power available to relax spins at a given angular frequency. The relaxation rates measured by NMR spectroscopists interrogate this density at known frequencies, which means that we can use those rates to assess general information about the shape of the spectral density function and thus constrain the model-free parameters.

In biomolecular NMR, these rates are most frequently measured on the nitrogen of a backbone amide group, in which case they fundamentally depend on the spectral density at three frequencies: 0, the Larmor frequency of nitrogen (ω_N), and the larmor frequency of the proton (ω_H). The precise relationships are as follows:

R₁ = D [3J(ω_N) + 6J(ω_N+ω_H) + J(ω_N-ω_H)] + C [3J(ω_N)]
R₂ = D/2 [4J(0) + 3J(ω_N) + 6J(ω_H)+ 6J(ω_N+ω_H) + J(ω_N-ω_H)] + C/6[J(0) + 3J(ω_N)]
steady-state nOe = 1 + R_NOE γ_H / R₁ γ_N
R_NOE = D [6J(ω_N+ω_H) - J(ω_N-ω_H)]
D = μ₀²ℏ²γ_N²γ_H²/64π²r_NH⁶
C = Δσ²ω_N²/3

where γ_H and γ_N are the gyromagnetic ratios of these nuclei, ℏ is the reduced Planck constant, and μ₀ is the magnetic constant (or vacuum permeability, if you prefer), and Δσ is the chemical shift anisotropy of the ¹⁵N nucleus (typically -160 - -170ppm).

I'm not going to cover precisely why they have these relationships today; instead I want to focus on how these relationships connect certain dynamic behaviors to particular observations about relaxation rates. The key to this is to think about how the spectral density looks. At right I have a simplified spectral density calculated for a rigid protein of reasonable NMR size (I only show the positive side of the function, the negative is a mirror image). While the particular shape of the spectral density function will depend strongly on the internal dynamics and overall size, certain general features will be the same for most proteins. It should be immediately evident, for instance, that J(0) >> J(ω_N) >> J(ω_H) (shown on the figure for a 500 MHz magnet). This implies that each relaxation rate reports on just one spot in the spectral density. R₂ should be proportional to J(0), R₁ to J(ω_N), and R_NOE to J(ω_H), keeping in mind that ω_H >> ω_N.

The shape of this curve derives in a fairly obvious way from the Lorentzian used to calculate it, in this case the Lipari-Szabo formalism, which if you'll recall is:


Where τ_m is the time it takes the protein to tumble through one radian in solution, S² is the order parameter for the bond in question, and τ_e is the correlation time of internal motions. The Lipari-Szabo model is not the only model of the spectral density, but most of the alternatives just add more Lorentzians or scaling factors. These models differ in the fine structure of the spectral density, but the overall shape (and the features I'm about to describe) is generally not affected.

It should be clear from examining this (and given that τ_m >> τ_e) that the point where ωτ_m = 1 divides the spectral density into two regions. Where ωτ_m <= 1, the first term dominates, and the spectral density is determined by S² and τ_m. Where ωτ_m >> 1, the second term dominates and the spectral density is essentially dependent on (1-S²) and τ_e. This being the case, you would expect highly flexible moieties (low S²) to have inefficient R₂ and R₁ relaxation and highly efficient NOE relaxation, and this we generally find to be the case.

Similarly, you would predict that increasing τ_m would cause R₂ to increase. The graph at right simulates relaxation rates for a typical, rigid backbone amide nitrogen (at 500 MHz) as the τ_m increases (note log scale on x). As you can see, the R₂ (red) does in fact get continuously higher as τ_m is increased; this is one of the reasons NMR spectroscopy of very large molecules is so difficult. Also note that R₁ (blue) goes through a maximum and then declines. This is because as τ_m increases, the point where ωτ_m = 1 shifts to lower and lower frequency. When |ω_N| > 1/τ_m, the spectral density at ω_N starts to fall off, reducing R₁. This might sound advantageous, but in fact it is another reason that spectroscopy on large molecules is difficult — their inefficient R₁ relaxation means that additional time must be scheduled after each transient to create a sufficiently sensitive steady state. Because even a simple spectrum can have 2048 transients, adding just a few fractions of a second per transient can rapidly amount to a significant increase in experiment time.

It's obvious that it would be questionable to map the spectral density based on just three relaxation rates, if for no other reason than that we have four unknowns and three pieces of data. This is typically addressed in three ways, which are often used in combination. The first is to reduce the spectral density, by making some general assumptions about the nature of the spectral density around ω_H and collapsing the J(ω_N +/- ω_H) terms into 0.87*J(ω_H). Another approach is to increase the number of relaxation rates measured, by incorporating R_1zz or other measurements, but many of these rates incorporate additional factors (such as ρ_HH) that must also be fit, so that their ability to reduce the dimensionality of the problem is sometimes limited.

The third approach is to take data at several fields. The Larmor frequencies ω_H and ω_N depend on the strength of the magnetic field in the spectrometer, while J(0) is obviously field-independent. As a result, each additional field of data taken improves the ratio between data and unknowns. This improvement is valuable even when the relaxation is being fit to a simplified representation such as the model-free formalism, and therefore dynamics experiments should always include measurements at more than one field if at all possible. Moreover, the field-dependence of relaxation rates can be very informative, in general terms, about the dynamics of the system.

In the simplified view it might seem that R₂ should be essentially independent of field strength, but observations show this not to be the case. R₂ increases at high fields primarily because of the chemical shift anisotropy contribution, which has a square field dependence and therefore increases with field to a greater degree than ω_N declines. As a result, R₂ has a sort of chevron appearance as you vary the field, with differences in dynamics primarily affecting the magnitude rather than the shape. This means that for R₂ the field-dependence is not particularly informative about the dynamics. However, if a residue has anomalous R₂ field-dependence with respect to the rest of the protein, this can be an indicator of a chemical exchange process on the μs - ms timescale.

Because relaxation due to chemical shift anisotropy makes a lesser contribution to R₁ (and depends entirely on J(ω_N) for this rate) the behavior of R₁ with respect to field is generally much simpler — for proteins, the R₁ almost always decreases as field increases. The degree to which this occurs, however, can be quite different depending on the dynamics behavior that is going on. The reason for that can be seen in the sample spectral densities to the left, calculated for a typical backbone amide (blue) and a flexible one (red). As you can see, the more flexible residue has a lower J(0) and a smaller slope between the flat portions of the spectral density than the rigid one. This means that the R₁ will be lower at high field and higher at low field, decreasing the field-dependence of the residue's relaxation. The exact magnetic field where this crossover occurs depends on the correlation times of the internal motion and global tumbling.

The gyromagnetic ratios of the hydrogen and nitrogen nuclei have opposite signs, so the heteronuclear NOE measured for these nuclei should be less than one. How much less depends on the relative ratio between J(ω_H) and J(ω_N). For flexible residues, the spectral density at large ω will be high (and that at lower ω will be low), this ratio will be large, and a low value will be measured in the hetNOE experiment. R_NOE typically has a steep field-dependence for flexible residues, and because this rate dominates the ratio, one tends to see greater field-dependence of the hetNOE for flexible residues. However, the situation for the hetNOE is more complex than for the other two rates because the spectral density around ω_H defines the relaxation. As a result, the internal correlation time (particularly if it's on the order of 100 ps - 1 ns) starts to dictate the shape of the spectral density, and hence the magnetic field-dependence of relaxation. For certain τ_e, the hetNOE will have no apparent field dependence, whether the residue is flexible or not.

Actually parameterizing the dynamics of a given group requires numerical fitting of the relaxation data, but for many questions a qualitative estimate will suffice. In these cases just examining the field-dependence of one or two relaxation rates (especially R₁ or NOE) can provide valuable insight into the heterogeneous dynamics of a given protein. In the next post I'll describe an example of a case in which this turns out to be true.

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More lab courtesy haiku

It's time once again to remind your labmates how to behave, seventeen syllables at a time.

Dust and detritus of past ages brushed away — leave balances clean!

Microbe-encrusted, reeking of death: your uncleaned centrifuge bottles.

If it cannot touch your skin, it must not touch my keyboard. Remove gloves!

Banshee scream boiling precious samples — don't mess with the sonicator!

Chemicals, hazards, trailing you in the hallways... Lab coats stay in labs.

Although you're wearing headphones, we can all still hear you singing along.

Unlabeled buffers may sometimes be used to make your morning coffee.

Washing glassware may not be your job, but please rinse that salty crust off!

The bear seeks a lost cub — I find my pipetman on your filthy bench.

Vapor will corrode them — store pipetmen upright, with tips ejected.

It takes five minutes to make destain — replenish the carboy when low.

Hiding that ruined column will not magically make it fix itself.

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[Insert poop joke here]

It's rare for me to be reading just one book at a time. Usually I bounce back and forth between at least two—one that I read at my desk or on the couch, and one that I read in my "inner sanctum". It's an unusual book that has me so interested that I'm willing to go searching for it every time I want something to read (or need to use the can). Yet for the time it took to read it, Carl Zimmer's Microcosm: E. Coli and the New Science of Life was essentially glued to my hand. Perhaps it would have been more appropriate, given the subject matter, to only read it on the throne, but it was just too good to be read in mere 15-minute snippets.

First isolated from baby diapers by a German physician in the 19th century, Escherichia coli (and its Mr. Hyde, Shigella) is most famous today for making people sick. Inside our bodies E. coli is a pioneer—one of the first species of bacterium to set up shop inside us, though hardly the last, and in normal circumstances it can provide a protective effect. At the heart of this seeming contradiction is the fact that E. coli has enormous diversity. Much of the fun in reading Microcosm lies in coming to understand how that could be so, given that this lowly microbe mostly reproduces by binary fission.

As a structural biologist, I frequently use liters of E. coli—primarily a strain called BL21(DE3). One thing Zimmer notes is that E. coli is absolutely essential to modern molecular bioscience. Its ability to produce the DNA and proteins we need for research makes this lowly bacterium one of our greatest investigative tools. Biomolecular NMR as we know it owes as much or more to the humble microbe (and its willingness to grow thickly in nutrient-poor media) as it does to men like Wüthrich and Bax.

Those who, like myself, primarily know E. coli as a tool for bioscience will recognize several names along this little tour, and learn a great deal about how it came to be such a powerful resource for us. Many will be surprised to learn how controversial some activities we take for granted (transfection of exogenous genetic material into bacteria, for example) were 20-30 years ago. Readers who have very little biology background need not fret, of course. Carl Zimmer is an excellent writer who introduces all the material carefully. Only some very basic knowledge about DNA, proteins, and bacteria is necessary. Zimmer will carry you the rest of the way, from bacteriophages and flagella all the way to synthetic biology, GM crops, and gene circuits.

Whether you work with E. coli every day or just cringe when you hear those words on the evening news, Microcosm will be an engaging, rewarding, and informative read.

While you wait for a chance to go to the bookstore (or for delivery, if like me you use Amazon all the time) check out Carl Zimmer's blog, The Loom, at ScienceBlogs.

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A Chilling Dilemma

Back when I was at Chapel Hill, a fellow student asked my help in figuring out a strange phenomenon he observed with one of his proteins. It seemed that the protein was perfectly soluble at room temperature, but precipitated when it was cooled. Because proteins typically denature at higher, rather than lower, temperatures, he was mystified. Mostly out of luck, the first question I asked him proved to be the right one: "What buffer are you using?" As it happened, he was using Tris buffer, a very common buffer in the biosciences, but also one that changes pH significantly upon cooling. It was not temperature that was denaturing his protein, but rather a change in the alkalinity of the solution it was dissolved in. The change of buffer pH with temperature is one of the most subtle and least-discussed issues in biochemistry, but as in my friend's case, can often produce confusing effects that significantly complicate research. An article by scientists from the University of Illinois online now at Chemical Communications (click link for open access), however, aims to resolve this problem by producing a temperature-independent pH (TIP) buffer for biological applications.

The approach they employed was actually very simple: rather than search the ends of the earth for a buffering agent that would maintain its pH across a huge temperature spread, they just found two that had opposite reactions to chilling and mixed them together. The buffer system they ended up with contained 60% HEPES and 40% potassium phosphate and experienced a pH change of less than 0.07 ± 0.1 over a temperature range from 25 °C to -180 °C. Readers who have encountered this subject before will recognize that HEPES and K₂HPO₄ are already fairly pH-stable over most of the laboratory temperature range, but as the paper's first figure shows, the TIP maintains these benefits down to very low temperature. A colorimetric assay was used to track the pH to very low temperatures.

So, problem solved, right? Well, not exactly. This finding is very nice as far as it goes, and has some promise for labs that do a lot of work that involves freezing proteins—structural biology labs come to mind. But while it would be nice to be able to select buffers on the basis of pH characteristics alone, that's rarely feasible. Not all buffers work with all proteins. In some cases, this can be rationalized: proteins that bind ATP or nucleic acids often bind or interact with phosphate buffers, resulting in poor solubility or aberrant structural dynamics. In other cases the observations are harder to understand—it seems that some proteins just "don't like" some buffers. So long as you're dealing with very dilute proteins, this is not usually an issue, though the biochemistry is sometimes deranged as a result. However, when high protein concentrations are employed—again, this is characteristic of structural biology—incompatible buffer-protein combinations tend to result in crashed protein.

The good news is that, with the exception of proteins that normally interact with phosphate moieties, both of these buffers are fairly well tolerated by a wide spectrum of systems. So long as a nearly-neutral pH is desired, this buffer combination should be useful. Researchers wishing to safely put pH-sensitive small molecules into long-term cold storage are also likely to find this buffer a boon. Moreover, because the buffer components are common and inexpensive almost any lab will be able to use this approach.

Sieracki, N. A., Hwang, H-J., Lee, M.K., Garner, D.K. and Lu, Y. "A temperature independent pH (TIP) buffer for biomedical biophysical applications at low temperatures." Chem. Commun. 2008 DOI 10.1039/b714446f

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America and the Meiji Restoration

While I was home, incidentally reading an enormous book on the history of Japan, Dad asked me why I was so interested in Japan and Japanese history. Despite the typical interest in understanding the samurai ethos, however, my interest is not in Japanese history generally, except in terms of contextualizing the Meiji era of its history. Japan transformed from a medieval, decentralized, semi-feudal congeries of partially autonomous states into a highly centralized modern empire ranking among the most important world powers with amazing speed. America had its part in this: Perry's gunboat diplomacy played a significant role not only in demonstrating the powerlessness of the Shogunate but also in convincing the elites that they must adopt Western technology. It is an interesting case of a social and technological transformation of a whole society. This of course begs the question: why am I interested in that?

Part of my interest arises from the fact that this transformation was actually a subversion of the intentions of many of its supporters. As the name implies, the Meiji Restoration was intended by many to be a return to an older version of Japan. The intention was to promote loyalty to the Emperor and expulsion of the foreigners. Since neither of these goals was truly compatible with the aims and abilities of the Shogunate, it was a powerful rallying cry against it. At the same time, the latter aim was totally unrealistic even for a reconstituted imperium. Thus the message changed to one of Imperial loyalty combined with national strength, to be achieved by adopting the technologies and institutions of Western powers. Some Meiji-era heroes reconciled themselves to this shift in emphasis, while others did not, or were not pleased with the way in which modernization was achieved. Samurai insurrections, recently romanticized in The Last Samurai, were one of the results. I find it interesting that this Restoration, with its roots in primitivism and xenophobia, actually resulted in modernization and international engagement.

More than that, however, I feel that we are in a similar time of transition and challenge. Scientific illiteracy and disrespect for science, especially in regard of religious meddling, seems to be rising. American industry, once a wellspring of innovation, is now tentative and fearful — the failures of the automobile giants are just one example of how conservative thinking is working against us. The budget for basic sciences has again suffered at the hands of an incompetent Congress. The rest of the world will soon embark on a significant transformation. By the end of the century petroleum will be dead, perhaps replaced by biodiesel, but it is also quite likely that hydrocarbon fuel itself will be a thing of the past. This single change alone will require enormous adjustments in infrastructure and the development of new technologies. The challenges of feeding the world's population and dealing with antibiotic- and drug- resistant infectious agents will also require scientific advances. The retirement of the baby boomers will place an enormous strain on our benefits system, reminiscent of the unsustainable samurai retainers which had to be done away with to revitalize Meiji Japan.

In short, the world is changing and we are not doing anything to keep up with it. The Japanese of the 1860s had Perry's black ships to tell them that they were too far behind the world order and had to catch up, but I doubt any such thing will happen to us. American corporations, bloated and clumsy, will not be able to catch up to the new world that is developing; American science, hamstrung by politicization, poor planning, and antiquated methods of delivering funding and education, to say nothing of the ongoing assaults of Christians, will also lag. We will simply wake up one day and realize that the rest of the world has undergone a green revolution and left us behind technologically and economically.

In order to avoid this fate I feel we must have our own restoration. And unlike the Meiji Restoration, I don't feel that we must start with fundamentalism and work our way around to progress. We have the advantage that a dedication to reason is part of our national heritage. Despite the distortions and outright lies of fundamentalists, we were founded as a secular nation by Enlightenment Deists who believed in the power of reason to resolve the problems of mankind. They were not superstitious men who believed that the answers to their problems lay within religious doctrine or the rulers those doctrines had imbued with absolute authority. The finest expression of this is in the First Amendment, which firmly places religion in a subordinate position. In the nation they devised, man would rule religion; religion would not rule man. That is our past, and I believe that principle can be used to build our future.

It's not a simple analogy — the differences between modern America and Meiji Japan are enormous. The transformation I am suggesting, being primarily cultural and economic, is also quite dissimilar to that undergone by Japan. Yet I feel it is equally necessary, especially in light of the rising tide of conservatism and superstition that seems poised to stifle innovation and scientific advancement at just the moment — with practically all of our industries foundering — that we need it most. Inventiveness, independence, rationality... these qualities are our heritage from our Founding Fathers. They are the true American values, and we ought to restore them to their rightful place at the center of our national identity.

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Lab courtesy haiku

In the bastardized American format...

Agar will gel up,
vile gray sink-lake develops.
Next time, use trashcan.

Technically, they're not
my Pipetmen either — that
does not make them yours.

Reducing agents,
like open sewers in lab —
put the cap back on.

Autoclaves melt agar;
now your waste is everywhere.
Remember, use trays!

It's called a Bunsen
burner for a reason — don't
leave unattended.

Foetid, abhorrent,
vile... your unbleached media,
or eldritch horror?

Seriously, man,
clean centrifuge after use;
it smells like a morgue.

Needles go in "Sharps
container", not underneath
the paper towels.

Floor grabs onto shoes;
try cleaning up spills as soon
as they happen, please.

Crystals belong in
screening trays, not pumps — wash with
water every time.

No, seriously,
I meant that about needles:
dispose properly.

Beware: grad students
will eat anything left out
in your lab's breakroom.

Water bottles and
computers — two great things that
ought not be combined.

This ain't no disco,
You ain't no DJ. This ain't
no foolin' around.

So I was a little bored today.
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